Dissertations / Theses: 'Network thermodynamics'

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Squadrani, Lorenzo. "Deep neural networks and thermodynamics." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020.

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Deep learning is the most effective and used approach to artificial intelligence, and yet it is far from being properly understood. The understanding of it is the way to go to further improve its effectiveness and in the best case to gain some understanding of the "natural" intelligence. We attempt a step in this direction with the aim of physics. We describe a convolutional neural network for image classification (trained on CIFAR-10) within the descriptive framework of Thermodynamics. In particular we define and study the temperature of each component of the network. Our results provides a new point of view on deep learning models, which may be a starting point towards a better understanding of artificial intelligence.

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Pierantozzi, Mariano. "Mathematical modeling for Thermodynamics: Thermophysical Properties and Equation of State." Doctoral thesis, Università Politecnica delle Marche, 2015. http://hdl.handle.net/11566/242931.

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Nelle moderne società multiculturali e multidisciplinari, sempre di più si devono adottare delle prospettive più ampie possibili. In questa tesi, si è tentato di adottare un metodo multidisciplinare che coinvolgesse non solo la matematica e la fisica, ma anche la chimica, la statistica, e più in generale l’ingegneria. Gli aspetti toccati sono quelli delle proprietà termofisiche della materia e delle equazioni di stato dei gas (EOS). Le proprietà termofisiche analizzate sono: tensione superficiale, conduttività termica, viscosità, dei liquidi e dei gas ed il secondo coefficiente del viriale. Dopo la raccolta dei dati sperimentali, essi sono stati analizzati con varie tecniche statistiche che trasformassero i dati grezzi in dati più attendibili. Dopo lo studio delle equazioni della letteratura si è proceduto con uno studio di sensibilità dei dati per vedere quali proprietà fisiche avessero maggiore impatto sulle proprietà studiate. Infine si è cercata un’equazione che potesse rappresentare nel migliore modo possibile i dati sperimentali. Si sono sempre preferite equazioni scalate ad equazioni puramente empiriche, in modo da avere non solo l’aderenza ai dati sperimentali, ma anche il rispetto dell’aspetto chimico-fisico. Dall’analisi dei residui, confrontandoci con le migliori equazioni in letteratura, i nostri risultati sono sempre stati migliori, tanto che hanno avuto dignità di pubblicazione nelle maggiori riviste del settore. Discorso a parte per le EOS. Analizzando la letteratura, ciò che subito è saltato all’occhio è che cercare la migliore equazione possibile è impossibile! Oppure come dice Martin parafrasando una frase della favola Biancaneve: “Specchio specchio delle mie brame, qual è la più bella del reame?” Abbiamo scelto la modifica dell’equazione Carnahan-Starling-De Santis. Tramite tecniche di minimizzazione multi obiettivo si sono migliorate le performance di tal equazione proprio intorno al punto critico. Questi sono gli aspetti principali toccati in questo lavoro di tesi, che di là dai risultati, pur buoni ottenuti, mi ha aperto il mondo della ricerca.
Abstract In the modern multicultural and multidisciplinary society, always adopting more and more wider prospective than before. In this thesis, we try to adopt a multidisciplinary method, which involves Mathematics, Physics, but also Chemistry, Statistics, and in general the scientific engineering. The aspects explained are thermo physical properties, and Equations of State (EOS) of gases. Regarding thermo physical properties have been analysed Surface Tension, Thermal Conductivity, Viscosity, and the second virial coefficient. On this arguments, the work had been subdivided between the gathering of experimental data, the analysing of data with statistical techniques transforming them to more reliable data than row. The second step was to collect the equations of literature. Then we went ahead studying the sensibility of data to find out which physical properties could have bigger impact to property examined. At the end, we looked for an equation that could represent experimental data in a better way. We always preferred the scaled equations that respect chemical and physical aspects, to the empirical ones. Comparing our results with better equations in literature, our results are always better, in fact all of the have been published in the best international journals on this subject. A separate discussion is that of EOS. Analyzing the previous literature, the first thing that came to our minds was that to find the best possible equation is impossible. Or as Martin wrote copying words of the famous fables Snow White: “Mirror mirror on the wall, who is the fairest of them all?”. We choose to modify The Carnahan-Starling-De Santis (CSD) equation of state, a parametrich equation with good results in the calculation of Vapor Liquid Equilibrium. Due to multi objective minimization techniques the performance of CSD has been improved. These are the principals aspect brought to light in this research, which apart from the results, with good results has opened to me the world of research.

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Ozaki, Hiroto. "Study of Network Structures and Rheological Properties of Physical Gels." Kyoto University, 2017. http://hdl.handle.net/2433/227633.

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Loutchko, Dimitri. "A Theoretical Study of the Tryptophan Synthase Enzyme Reaction Network." Doctoral thesis, Humboldt-Universität zu Berlin, 2018. http://dx.doi.org/10.18452/19384.

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Das Enzym Tryptophan Synthase ist ein ausgezeichnetes Beispiel einer molekularen Fabrik auf der Nanoskala mit zwei katalytischen Zentren. Der katalytische Zyklus des Moleküls beruht zudem auf zahlreichen allosterischen Wechselwirkungen sowie der Übertragung des Intermediats Indol durch einen intramolekularen Tunnel. In dieser Arbeit wird das erste kinetische Modell eines einzelnen Tryptophan Synthase Moleküls konstruiert und analysiert. Simulationen zeigen starke Korrelationen zwischen den Zuständen der Katalysezentren sowie die Ausbildung von Synchronisation. Mit stochastischer Thermodynamik wird die experimentell unzugängliche Reaktionskonstante für die Rückübertragung des Indols aus Messdaten rekonstuiert. Methoden, die den Informationsaustausch in bipartiten Markovnetzwerken charakterisieren, werden auf beliebige Markovnetzwerke verallgemeinert und auf das Modell angewendet. Der abschließende Teil befasst sich mit chemischen Reaktionsnetzwerken von Metaboliten und Enzymen. Es werden algebraische Modelle (Halbgruppen) konstruiert, welche aufeinanderfolgende und simultane katalytische Funktionen von Enzymen und von Unternetzwerken erfassen. Diese Funktionen werden genutzt, um eine natürliche Dynamikum sowie hinreichende und notwendige Bedingungen für seine Selbsterhaltung zu formulieren. Anschließend werden die algebraischen Modelle dazu genutzt, um eine Korrespondenz zwischen Halbgruppenkongruenzen und Skalenübergängen auf den Reaktionsnetzwerken herzustellen. Insbesondere wird eine Art von Kongruenzen erörtert, welche dem Ausspuren der globalen Struktur des Netzwerkes unter vollständiger Beibehaltung seiner lokalen Komponenten entspicht. Während klassische Techniken eine bestimmte lokale Komponente fixieren und sämtliche Informationen über ihre Umgebung ausspuren, sind bei dem algebraischen Verfahren alle lokalen Komponenten zugleich sichtbar und eine Verknüpfung von Funktionen aus verschiedenen Komponenten ist problemlos möglich.
The channeling enzyme tryptophan synthase provides a paradigmatic example of a chemical nanomachine with two distinct catalytic subunits. It catalyzes the biosynthesis of tryptophan, whereby the catalytic activity in a subunit is enhanced or inhibited depending on the state of the other subunit, gates control the accessibility of the reactive sites and the intermediate product indole is directly channeled within the protein. The first single-molecule kinetic model of the enzyme is constructed. Simulations reveal strong correlations in the states of the active centers and the emergent synchronization. Thermodynamic data is used to calculate the rate constant for the reverse indole channeling. Using the fully reversible single-molecule model, the stochastic thermodynamics of the enzyme is closely examined. The current methods describing information exchange in bipartite systems are extended to arbitrary Markov networks and applied to the kinetic model. They allow the characterization of the information exchange between the subunits resulting from allosteric cross-regulations and channeling. The final part of this work is focused on chemical reaction networks of metabolites and enzymes. Algebraic semigroup models are constructed based on a formalism that emphasizes the catalytic function of reactants within the network. A correspondence between coarse-graining procedures and semigroup congruences respecting the functional structure is established. A family of congruences that leads to a rather unusual coarse-graining is analyzed: The network is covered with local patches in a way that the local information on the network is fully retained, but the environment of each patch is not resolved. Whereas classical coarse-graining procedures would fix a particular patch and delete information about the environment, the algebraic approach keeps the structure of all local patches and allows the interaction of functions within distinct patches.

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Hui, Qing. "Nonlinear dynamical systems and control for large-scale, hybrid, and network systems." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/24635.

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Thesis (Ph.D.)--Aerospace Engineering, Georgia Institute of Technology, 2009.
Committee Chair: Haddad, Wassim; Committee Member: Feron, Eric; Committee Member: JVR, Prasad; Committee Member: Taylor, David; Committee Member: Tsiotras, Panagiotis

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Grondin, Yohann. "Biological networks : a thermodynamical approach." Thesis, University of Leicester, 2006. http://hdl.handle.net/2381/30584.

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Many real systems can be represented by networks, that is a set of nodes connected to each other. The study of these systems as such has proven extremely useful as it gives access to a series of parameters that characterise their non-trivial architecture. This architecture is the product of many factors from the evolutionary mechanisms that shape the system during its growth to the functional dynamics on a shorter time scale. Gaining knowledge on the architecture is then of importance but faces many challenges in particular in the study of biological networks. The first challenge is in terms of the method used to generate networks as we need to adopt an approach that, we expect, would allow us to understand those constraints and forces that shape the network. The second challenge is that of understanding the relationship between the architecture of the system and its dynamics and functionality. The third challenge is to get access using suitable techniques to the network architecture from expression data, such as mRNA abundances, for example. We first show in this thesis that it is possible to generate networks from a thermodynamical viewpoint. This approach allows us to relate the architecture of network to some constraints. Furthermore, we show that some information on the structure resides in the non-randomness of the links between nodes. If we were to draw an analogy with traditional thermodynamics, networks could be modelled in a first approximation as perfect gases. On a dynamical network of our design, we show a dependence of the architecture on the distribution of the level of expression of the nodes. Surprisingly, the distribution of the periods of those networks is a power-law and independent of the underlying architecture of the system. By comparing the data obtained from our model to experimental mRNA data we found a correlation between the degree of connectivity of genes and their level of abundance. Finally, we show how we can apply a method used traditionally in image reconstruction to inference of networks.

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Kotjabasakis, E. "Design of flexible heat exchanger networks." Thesis, University of Manchester, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.235140.

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Design for process flexibility is an industrially important topic so it is not surprising that it is attracting much research work. Given the size of the problem it is also not surprising that workers have concentrated on heat exchanger networks, which can be considered to be a self-contained sub-problem. Unfortunately, recent research has suffered from a number of major drawbacks. Problem formulation has often been unrealistic. Proposed procedures tend to be 'clinical' rather than practical. Academic research has often been conducted without proper consideration of the industrial environment. Very few research results have been tested on full scale industrial problems. In this thesis a new problem formulation and new solution techniques are presented. They have been designed to fulfil the needs of industry. In problem formulation it is recognised that the specification of flexibility is primarily an economic problem. The amount of flexibility industry will demand is a function of how much it costs. The methodology developed here allows both, the flexibility cost and the existing trade-off between flexibility needs, capital costs and energy costs to be fully evaluated. Flexibility problem formulation is mainly based on Multiple Base Cases. Different plant operating scenarios are set and a design found that is able to satisfy each case. This is a formulation that has found a wide acceptance in industry. To be industrially practical, process design techniques must be intelligible to the non-specialist. The techniques developed here are simple and straightforward and give insight. Two new design techniques have been developed. The first of these is 'Downstream Paths'. These are used to identify and evolve the network structures that permit cost effective flexibility. The second technique is 'Sensitivity Tables'. These can be used to analyse the performance of a given structure. In addition they determine the cost effective modification to elements of the structure which provide the specified flexibility needs. The technique is rapid, simple to apply and easy to repeat. Consequently, many scenarios can be screened without much effort and a cost profile developed in order to evaluate the cost trade-off described above. The approach proposed in this thesis, involving the new problem formulation and solution techniques, has been applied to a number of case studies of industrial scale. These case studies have covered problems as diverse as catalyst deactivation, fouling, and plant debottlenecking. One major spin-off from the work is a new approach to the design of heat exchanger networks subjected to fouling. Large potential savings have been identified.

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Garcia, Cantu Ros Anselmo. "Thermodynamic and kinetic aspects of interaction networks." Doctoral thesis, Universite Libre de Bruxelles, 2007. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210420.

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In view of the fact that a same complex phenomenon can be approached by different conceptual frameworks, it is natural to inquire on the possibility to find connections between different types of quantities, such as topological, dynamical, statistical or thermodynamical, characterizing the same system. The present work is built on the idea that this line of approach can provide interesting insights on possible universal principles governing complex phenomena. In Chapter I we introduce concepts and tools of dynamical systems and thermodynamics as applied in macroscopic scale description as well as, for a later use, a number of selected representative models. In Chapter II we briefly present the elements of the theory of Markov processes describing a large class of stochastic process and also introduce some important concepts on the probabilistic description of deterministic systems. This chapter ends with a thermodynamic formulation accounting for the evolution of the entropy under the effect of stochastic fluctuations. In Chapter III, after introducing the main concepts and recent advances in network theory, we provide a connection between dynamical systems and network theory, which shows how universal structural properties of evolving networks can arise from deterministic dynamics. More specifically, we show explicitly the relation between the connectivity patterns of these networks and the indicators of the underlying dynamics, such as the local Lyapunov exponents. Our analysis is applied to representative models of chaotic maps, chaotic flows and is finally extended to stochastic processes. In Chapter IV we address the inverse problem, namely, processes whose dynamics is determined, in part, by the structure of the network in which they are embedded. In particular, we focus on systems of particles diffusing on a lattice and reacting instantaneously upon encountering each other. We study the role of the topology, the degree of synchronicity of motion and the reaction mechanism on the efficiency of the process. This lead us to identify a common generic mechanism responsible for the behavior of the efficiency, as a function of the control parameters. Finally, in Chapter V we study the connection between the topology and the thermodynamic properties of reaction networks, with focus on the entropy production and the system’s efficiency at nonequilibrium steady states. We also explore the connection between dynamic and thermodynamic properties of nonlinear feedbacks, as well as the response properties of reaction networks against both deterministic and stochastic external perturbations. We address networks of varying topologies, from regular lattices to complex structures./Le présent travail s’inscrit dans le domaine de recherche sur les systèmes complexes. Différentes approches, basées des systèmes dynamiques, de la thermodynamique des systèmes hors d’équilibre, de la physique statistique et, plus récemment, de la théorie des réseaux, sont combinés afin d’explorer des liens entre différentes types de grandeurs qui caractérisent certaines classes de comportements complexes. Dans le Chapitre I nous introduisons les principaux concepts et outils de systèmes dynamiques et de thermodynamique. Dans le Chapitre II nous présentons premièrement des éléments de la théorie de processus de Markov, ainsi que les concepts à la base de la description probabiliste des systèmes déterministes. Nous finissons le chapitre en proposant une formulation thermodynamique qui décrit l’évolution de l’entropie hors d’équilibre, soumis à l’influence de fluctuations stochastiques. Dans le Chapitre III nous introduisons les concepts de base en théorie des réseaux, ainsi qu’un résumé générale des progrès récents dans le domaine. Nous établissons ensuite une connexion entre la théorie des systèmes dynamiques et la théorie de réseaux. Celle-ci permet d’approfondir la compréhension des mécanismes responsables de l’émergence des propriétés structurelles dans des réseaux crées par des lois dynamiques déterministes. En particulier, nous mettons en évidence la relation entre des motifs de connectivité de ce type de réseaux et des indicateurs de la dynamique sous-jacente, tel que des exposant de Lyapounov locaux. Notre analyse est illustrée par des applications et des flots chaotiques et étendue à des processus stochastiques. Dans le Chapitre IV nous étudions le problème complémentaire, à savoir, celui de processus dont la dynamique est déterminée, en partie, par la structure du réseau dans lequel elle se déroule. Plus précisément, nous nous concentrons sur le cas de systèmes de particules réactives, diffusent au travers d’un réseau et réagissant instantanément lorsqu’un rencontre se produit entre elles. Nous étudions le rôle de la topologie, du degré de synchronicité des mouvements et aussi celui du mécanisme de réaction sur l’efficacité du processus. Dans les différents modèles étudiés, nous identifions un mécanisme générique commun, responsable du comportement de l’efficacité comme fonction des paramètres de contrôle. Enfin, dans le Chapitre V nous abordons la connexion entre la topologie et les propriétés thermodynamiques des réseaux de réactions, en analysant le comportement local et global de la production d’entropie et l’efficacité du système dans des état stationnaires de non-équilibre. Nous explorons aussi la connexion entre la dynamique et les propriétés de boucles de rétroaction non linéaires, ainsi que les propriétés de réponse des réseaux de réaction à des perturbations stochastiques et déterministes externes. Nous considérons le cas de réseaux à caractère régulier aussi bien que celui de réseaux complexes.

Doctorat en Sciences
info:eu-repo/semantics/nonPublished

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Honorato-Zimmer, Ricardo. "On a thermodynamic approach to biomolecular interaction networks." Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/28904.

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We explore the direct and inverse problem of thermodynamics in the context of rule-based modelling. The direct problem can be concisely stated as obtaining a set of rewriting rules and their rates from the description of the energy landscape such that their asymptotic behaviour when t → ∞ coincide. To tackle this problem, we describe an energy function as a finite set of connected patterns P and an energy cost function e which associates real values to each of these energy patterns. We use a finite set of reversible graph rewriting rules G to define the qualitative dynamics by showing which transformations are possible. Given G and P, we construct a finite set of rules Gp which i) has the same qualitative transition system as G and ii) when equipped with rates according to e, defines a continuous-time Markov chain that has detailed balance with respect to the invariant probability distribution determined by the energy function. The construction relies on a technique for rule refinement described in earlier work and allows us to represent thermodynamically consistent models of biochemical interaction networks in a concise manner. The inverse problem, on the other hand, is to i) check whether a rule-based model has an energy function that describes its asymptotic behaviour and if so ii) obtain the energy function from the graph rewriting rules and their rates. Although this problem is known to be undecidable in the general case, we find two suitable subsets of Kappa, our rule-based modelling framework of choice, were this question can be answer positively and the form of their energy functions described analytically.

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Jones, Paul Simon. "Targeting and design for heat exchanger networks under multiple base case operation." Thesis, University of Manchester, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.292518.

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Alanis, Francisco J. "Thermodynamic optimisation of industrial cogeneration systems and conventional power plant." Thesis, University of Manchester, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.292578.

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Reimers, Arne Cornelis [Verfasser]. "Metabolic Networks, Thermodynamic Constraints, and Matroid Theory / Arne C. Reimers." Berlin : Freie Universität Berlin, 2014. http://d-nb.info/1058587331/34.

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Morri, Francesco. "A thermodynamic approach to deep learning." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020.

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Neural Networks are an incredibly powerful tool used to solve complex problems. The actual functioning of this tool and its behaviour when applied to different kind of problems is not completely explain though. In this work we study the behaviour of a neural network, used to classify images, through a physical model, based on statistical thermodynamics. We found interesting results regarding the temperature of the different components of the network, that may be exploited in a more efficient training algorithm.

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Latino, Diogo Alexandre Rosa Serra. "Automatic learning for the classification of chemical reactions and in statistical thermodynamics." Doctoral thesis, FCT - UNL, 2008. http://hdl.handle.net/10362/1752.

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This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

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Mamouni, Mahdi-Amine. "Thermodynamique des réseaux et application à la thermoélectricité." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPAST131.

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La thermodynamique des processus hors équilibre est reconnue de longue date comme un lieu de prédilection de la modélisation des conversions de l’énergie. Initialement développée par Sadi Carnot pour optimiser l’utilisation des machines à vapeur durant l’essor de l’ère industrielle, la modélisation de la conversion thermodynamique a connu de nombreux développements, dont en particulier ceux de Lars Onsager puis Herbert Callen, et enfin Prigogine. Au cœur de ces développements se trouve la question de la puissance extractible, question qui ne peut être abordée par la thermostatique mais par la thermodynamique à temps fini. Cette dernière, formulée depuis le milieu du siècle dernier par Novikov et Chambadal, a été remise en lumière par Curzon et Ahlborn dans les années 1970 sous la forme des machines endoréversibles. Dans ce cadre où l’évolution d’un système est gouvernée par les gradients des grandeurs intensives, il devient possible de modéliser complètement le comportement des machines, les puissances produites et les entropies créées, dépassant ainsi le simple cadre endoréversible. Dans le cas de systèmes décrits par une seule grandeur intensive, le comportement retrouvé est celui des lois empiriques simples telles que les lois d’Ohm, de Fourier ou de Darcy. Lorsque plusieurs grandeurs intensives couplées sont en jeu, le comportement devient complexe à modéliser, surtout si le système présente des inhomogénéités des propriétés physiques du fluide de travail thermodynamique. Le travail mené au cours de cette thèse traite de ces questions. Il est basé sur la conception d’un simulateur de réseaux thermodynamiques, appliqués spécifiquement à la thermoélectricité, qui est un système modèle particulièrement fructueux. Le système est décrit par les relations force-flux et une approche en volume fini, ce qui permet de reconstruire un réseau thermodynamique fidèle au système étudié. Cette approche prend rigoureusement en compte l’hypothèse de continuité des grandeurs intensives entre chaque élément de volume, dont sa validité est tout d’abord démontrée en considérant la fluctuation de la production d’entropie et son caractère résiduel en situation stationnaire. Ce résultat est discuté dans le cadre du débat sur les questions de principe de minimisation de production d’entropie. Cette approche a été validée par plusieurs simulations de réseaux thermoélectriques dans différents régimes, qu’ils soient stationnaires, transitoires et harmoniques. La réponse obtenue contient les termes électriques et thermiques à la fois linéaires et non linéaires, ces derniers résultant des couplages énergie-matière. Ce simulateur a permis d’intégrer des matériaux dont la conductivité thermique peut être modulé tel que dans des matériaux férroélectriques. Les simulations transitoires incluant des matériaux à conductivité thermique modulable permettent ainsi de déterminer le temps de redistribution de la chaleur dans le réseau à la suite de cette modulation. Ces travaux ouvrent la voie à des simulations thermoélectriques complexes et peu accessibles par d’autres voies, telle que l’étude et le dimensionnement de modules thermoélectriques hétérogènes. L’intégration de la description locale sur le volume permet de faire émerger un comportement global issu de la prise en compte d’effets d’inclusions sur le couplage, suggérant de nouvelles perspectives de développement, tel que dans le cadre d’effets thermomagnétiques issus d’inhomogénéités
In this context, where the evolution of a system is governed by the gradients of intensive quantities, it becomes possible to completely model the behavior of machines, the produced power, and the created entropy, thus surpassing the simple endoreversible framework. In the case of systems described by a single intensive quantity, the behavior found is that of simple empirical laws such as Ohm’s law, Fourier’s law, or Darcy’s law. When several coupled intensive quantities are involved, the behavior becomes complex to model, especially if the system exhibits inhomogeneities in the physical properties of the working fluid. The work carried out in this thesis addresses these issues. It is based on the design of a thermodynamic network simulator, specifically applied to thermoelectricity, which is a particularly fruitful model system. The system is described by force-flux relations and a finite volume approach, which allows for the reconstruction of a thermodynamic network faithful to the studied system. This approach rigorously takes into account the hypothesis of continuity of intensive quantities between each volume element, whose validity is first demonstrated by considering the fluctuation of entropy production and its residual character in a stationary situation. This result also helped clarify the debate on the principles of entropy production minimization, a debate that still stirs part of the scientific community. This approach was validated by several simulations of thermoelectric networks in various regimes, stationary, transient, and harmonic. The obtained response includes both linear and nonlinear electrical and thermal terms, the latter resulting from energy-matter couplings. Beyond thermoelectricity, this simulator made it possible to integrate ferroelectric and antiferroelectric materials, whose thermal conductivity varies according to polarization. Transient simulations including materials with modifiable thermal conductivity thus allow determining the heat redistribution time in the network following this modulation. This work paves the way for complex thermoelectric simulations that are not accessible by other means, such as the study and design of heterogeneous thermoelectric modules. The integration of local description over volume allows for the emergence of global behavior resulting from the consideration of exotic inclusion effects on coupling, suggesting new development perspectives, notably in the context of thermomagnetic effects arising from local current loops

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Pracný, Vladislav. "Neural network based shock absorber model with a thermodynamical coupling : experiment, modeling and vehicle simulation /." Aachen : Shaker, 2009. http://d-nb.info/994209967/04.

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Fischer, Jakob [Verfasser], Peter [Gutachter] Dittrich, and Daniel [Gutachter] Merkle. "Thermodynamic patterns of life : emergent phenomena in reaction networks / Jakob Fischer ; Gutachter: Peter Dittrich, Daniel Merkle." Jena : Friedrich-Schiller-Universität Jena, 2018. http://d-nb.info/1170689094/34.

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Gros, Alice. "Modélisation de la cristallisation sous tension du caoutchouc naturel." Thesis, Ecole centrale de Nantes, 2016. http://www.theses.fr/2016ECDN0018.

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Bien que la cristallisation sous tension du caoutchouc naturel ait fait l'objet de nombreuses investigations expérimentales au cours du dernier siècle, et notamment dans les quinze dernières années, les résultats obtenus ne permettent toujours pas d'aboutir à une compréhension fine des mécanismes physiques en jeu, limitant la modélisation à des approches phénoménologiques. La présente thèse vise à élaborer un modèle rendant qualitativement compte des phénomènes observés lors d'un essai de traction uniaxiale du caoutchouc naturel. Dans un premier temps, une chaîne représentative modélise le réseau amorphe dont l'inhomogénéité est exprimée au travers de la distribution des longueurs des chaînes polymères qu'on suppose déformées à force égale. Les conditions de cristallisation et de fusion sont ensuite définies par la thermodynamique de changement de phase classique à laquelle est ajouté le caractère enchevêtré du réseau ; les conditions obtenues éclaircissent notamment la relation entre la déformation et la température lors de la fusion des cristallites. Finalement, un modèle de chaîne semicristallisée associant l'inhomogénéité des chaînes amorphes et l'hétérogénéité due à la présence de la phase cristalline est proposé, puis inclus dans une loi de comportement de type full-network dont les équations sont adaptées en conséquence. Ce travail aboutit à un modèle thermo-mécanique complet permettant de décrire qualitativement la réponse du caoutchouc naturel, ainsi qu'à une description interprétative originale de la cristallisation sous tension
Despite the numerous experimental inverstigations performed over the past century and more intensively in the last fifteen years, strain-induced crystallization taking place in natural rubber still remains hardly understood in its precise mechanisms, leading models to remain phenomenological ones. The present study aims to develop a physicallymotivated model which qualitatively reproduces physical phenomena observed during an uniaxial tensile test. Firstly, the amorphous network is assumed to deform in an equal-force manner, resulting in a representative chain encompassing the inhomogeneity of matter through the chain-length distribution. Secondly, based on classical thermodynamics and on the entangled nature of the polymer network, both crystallization and fusion conditions are established. Moreover the derivation of the equilibrium point of a finite crystallite in a deformed network clarifies the tight relation between deformation and temperature during fusion. Finally, a semi-crystallized chain is defined, accounting for both the inhomogeneity of the amorphous phase and the heterogeneity due to the presence of a crystalline phase. This chain is included in a modified full-network model, initially dedicated to amorphous networks. This work leads to a complete thermo-mechanical constitutive equation which qualitatively reproduces the response of natural rubber in tension, but also to an original interpretative description of strain-induced crystallization

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Pracný, Vladislav [Verfasser]. "Neural network-based shock absorber model with a thermodynamical coupling : Experiment, modeling and vehicle simulation / Vladislav Pracny." Aachen : Shaker, 2009. http://d-nb.info/1161302549/34.

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Raux, Paul. "Circuit theory for thermodynamic engines in stationary nonequilibrium." Electronic Thesis or Diss., Université Paris Cité, 2024. http://www.theses.fr/2024UNIP7061.

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À l'instar de l'étude des circuits électroniques, l'étude des systèmes complexes est souvent facilitée par leur décomposition en sous-systèmes plus simples. Deux sous-problèmes apparaissent alors : 1) l'étude de chaque sous-système séparément ; 2) l'émergence de nouveaux comportements lors de leur réassemblage. La théorie des circuits hors équilibre est la mieux comprise pour un unique couple de courant (électrique) et de force thermodynamique conjuguée (tension), comme c'est le cas en électronique. Chaque sous-système est alors décrit par une caractéristique courant-tension, résumée dans le concept d'impédance scalaire. La caractéristique courant-tension de l'ensemble du système est alors obtenue en utilisant les lois de conservation au sein et à l'interface de chaque sous-système (par exemple, les lois de Kirchoff). Le but de cette thèse est d'étendre les résultats de l'électronique stationnaire aux machines thermodynamiques stationnaires hors équilibre présentant un nombre arbitraire de courants et de forces conjuguées soumis à différents couplages (par exemple, thermoélectriques). Pour ce faire, nous devons identifier des outils permettant le traitement des lois de conservation à l'intérieur d'un réseau complexe. La notion d'impédance scalaire doit aussi être remplacée par un objet matriciel, la matrice de conductance hors équilibre, pour prendre en compte le couplage entre les différents types de courants traversant le système. Ce manuscrit est divisé en trois parties. Dans la première partie, nous faisons un état de l'art du traitement algébrique des convertisseurs thermodynamiques. Dans la deuxième, nous démontrons le calcul de la matrice de conductance hors équilibre pour des réseaux de réactions chimiques ainsi que pour des convertisseurs thermoélectriques. Enfin, dans la dernière partie, nous démontrons les lois d'addition des résistances/conductance pour des associations série/parallèle
As with the study of electronic circuits, the study of complex systems is often facilitated by breaking them down into simpler subsystems. Two sub-problems then arise: 1) the study of each sub-system separately; 2) the emergence of new behaviours when they are reassembled. The theory of non-equilibrium circuits is best understood for a single pair of current (electric) and conjugate thermodynamic force (voltage), as is the case in electronics. Each subsystem is then described by a current-voltage characteristic, summarised in the concept of scalar impedance. The current-voltage characteristic of the whole system is then obtained using the conservation laws within and at the interface of each subsystem (e.g. Kirchoff's laws). The aim of this thesis is to extend the results from steady state electronics to non-equilibrium steady state thermodynamic machines with an arbitrary number of conjugate currents and forces subject to different couplings (e.g. thermoelectric). To do this, we need to find tools for treating conservation laws within a complex network. The notion of scalar impedance must also be replaced by a matrix object, the non-equilibrium conductance matrix, to account for the coupling between the different types of currents flowing through the system. This manuscript is in three parts. In the first part, we review the state of the art in the algebraic treatment of thermodynamic converters. In the second part, we demonstrate the calculation of the non-equilibrium conductance matrix for chemical reaction networks and thermoelectric converters. Finally, in the last section, we demonstrate the resistance/conductance summation laws for series/parallel combinations

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Mancini, Francesca. "Information theory in biochemical regulatory networks: a theoretical study." Doctoral thesis, SISSA, 2015. http://hdl.handle.net/20.500.11767/3906.

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In this Thesis we consider the optimization of information transmission as a viable design principle for biochemical networks. We apply this principle to a simple model regulatory circuit, given by an input and a delayed output that switch randomly between two states in continuous time. First we maximize the transmitted information in the network at a given output delay, when the system has no external constraints and it is in steady state or can optimize its initial condition. We find that optimal network topologies correspond to common biological circuits linked to stress response and that circuits functioning out of steady state may exploit absorbing states to be more informative than in steady state. We then take into account that biological regulatory networks need to dissipate energy in order to transmit biochemical signals and that such signaling often happens in challenging environmental conditions. Hence we explore the system's trade-offs between information transmission and energetic efficiency. At fixed delay and dissipated energy, we determine the most informative networks both in the absence and in the presence of feedback. We find that negative feedback loops are optimal at high dissipation, whereas positive feedback loops become more informative close to equilibrium conditions. Moreover, feedback allows the system to transmit almost the maximum available information at a given delay, even in the absence of dissipation. Finally, within a game-theoretic maximin approach, we ask how a biochemical network should be constructed to be most informative in the worst possible initial condition set by the environment. We find that, in the limit of large energy dissipation, the system tunes the ratio of the input and output timescales so that the environmental disturbance is marginalized as much as possible.

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Strang, Alexander. "Applications of the Helmholtz-Hodge Decomposition to Networks and Random Processes." Case Western Reserve University School of Graduate Studies / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=case1595596768356487.

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Chassé, Walter [Verfasser], Kay [Akademischer Betreuer] Saalwächter, Wolfgang [Akademischer Betreuer] Paul, and Matthias [Akademischer Betreuer] Ballauff. "Structure, formation and thermodynamic properties of polymer networks as studied by NMR : [kumulative Dissertation] / Walter Chassé. Betreuer: Kay Saalwächter ; Wolfgang Paul ; Matthias Ballauff." Halle, Saale : Universitäts- und Landesbibliothek Sachsen-Anhalt, 2013. http://d-nb.info/1036129802/34.

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Dal'Boit, Silvia. "Predição do equilibrio liquido-vapor atraves de redes neurais artificiais." [s.n.], 2008. http://repositorio.unicamp.br/jspui/handle/REPOSIP/266193.

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Orientador: Roger Josef Zem
Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Quimica
Made available in DSpace on 2018-08-11T09:38:40Z (GMT). No. of bitstreams: 1 Dal'Boit_Silvia_M.pdf: 447965 bytes, checksum: c94324c82fb6fa904907ff7875b11ae1 (MD5) Previous issue date: 2008
Resumo : Esse trabalho tem como objetivo o estudo da viabilidade de se utilizar se redes neurais artificiais (RNAs) para a predição de equilíbrio líquido-vapor (EL V), utilizando a abordagem do método de contribuição de grupos, método UNIF AC. Foram feitas duas propostas de trabalho, uma substituindo o método UNIF AC para o cálculo do coeficiente de atividade (?) pelas RNAs e outra calculando diretamente a composição da fase vapor (y) através das RNAs. A principal vantagem da utilização de uma rede neural reside na sua capacidade de modelar o sistema em equilíbrio sem a necessidade da definição prévia de um modelo de equilíbrio específico, como ocorre, por exemplo, no método UNIF AC. Foram estudados dois sistemas, um sistema constituído de misturas binárias álcoois água com cinco grupos funcionais UNIF AC e outro com misturas binárias de: álcoois, água, aldeídos e cetonas, com oito grupos funcionais UNIF AC. Foram usadas redes neurais do tipo feedforward com uma camada escondida. Utilizou-se o software Matlab 7.0 como ferramenta para esse trabalho. Nesse trabalho o número de neurônios na camada escondida foi estimado por três métodos diferentes. No entanto, os melhores resultados não foram obtidos por nenhum .destes e sim por redes com números de neurônios bem menores. Esse resultado demonstrou a independência de teorias e postulados na área de redes neurais artificiais, já que não existe como prever o seu desempenho e nem como escolher através de uma forma ótima e única os seus algoritmos e funções. Os resultados obtidos mostraram uma. boa capacidade de predição da rede, com desvios na mesma ordem de grandeza que os métodos baseados no uso de um modelo específico para a descrição do comportamento de equilíbrio líquido-vapor, mas sem a necessidade de se definir um modelo ou de seretp calculados parâmetros de interação ou constantes ajustáveis. Esse resultado é relevànte, uma vez que os sistemas estudados apresentam não idealidades acentuadas
Abstract : In this work the suitability of artificial neural networks (ANN) for the prediction of vapour-liquid equilibrium (VLE) is analyzed, using molecular groups that describe the components as input. Two different approaches were studied. In the first proposal the ANN is used to predict activity coefficients, in a similar way as done by the UNIF AC method. In the second proposal, vapour composition and equilibrium temperature are computed by the neural network without intermediate activity coefficient calculation. The main gain of the neural network is it capability to model the VLE without a previous definition of a specific equilibrium mo dei, like the UNIF AC mode!, for instance. Two different systems were studied, one of these is consisting of only binary mixtures for alcohols-water components with five UNIF AC functional groups. The other one is composed of binary mixtures of alcohols, water, aldehydes and ketones components with eight UNIF AC functional groups. The ANN used in this work is a feedforward network with one hidden layer, the networks was implemented in Matlab 7.0 software. In this work the numbers of hidden layers was estimating by three different methods. However the best results weren't found by none of these methods, but by a . smaller number of neurons than the indicated methods. These results show the independency of theories and postulates in the ANN area. There isn't a simple way to preview the network performance nor hüw to chose the optimum and unique form its algorithms and functions. The results showed that the proposed networks are capable of predicting VLE within a reasonable error margin, comparable to methods using specific thermodynamic models, without the necessity to define a mo dei, to calculate interaction parameters or adjustables constants. This result is relevant, respecting the systems presented here have a highly non-ideal behaviour
Mestrado
Sistemas de Processos Quimicos e Informatica
Mestre em Engenharia Química

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Perabathini, Bhanukiran. "Limites fondamentales de l'efficacité énergétique dans les réseaux sans fil." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLC011/document.

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La tâche de répondre à une demande croissante pour une meilleure qualité de l'expérience utilisateur dans les communications sans fil, est contestée par la quantité d'énergie consommée par les technologies concernées et les méthodes employées. Sans surprise, le problème de la réduction de la consommation d'énergie doit être abordé à diverses couches de l'architecture de réseau et de diverses directions. Cette thèse traite de certains aspects cruciaux de la couche physique de l'architecture de réseau sans fil afin de trouver des solutions efficaces d'énergie. Dans la première partie de cette thèse, nous explorons l'idée de l'efficacité énergétique à un niveau fondamental. A commencer par répondre aux questions telles que: - Qu'est-ce que la forme physique d'information ?, nous construisons un dispositif de communication simple afin d'isoler certaines étapes clés dans le processus physique de la communication et nous dire comment elles affectent l'efficacité énergétique d'une communication système. Dans la deuxième partie, nous utilisons des outils de la géométrie stochastique pour modéliser théoriquement réseaux cellulaires afin d'analyser l'efficacité énergétique du système. L'exploitation de la traçabilité d'une telle modélisation mathématique, nous explorons les conditions dans lesquelles la consommation d'énergie peut être réduite. En outre, dans cette partie, nous introduisons le concept de la mise en cache des données des utilisateurs à la périphérie du réseau (à savoir le final ac BS qui est en contact avec l'utilisateur) et de montrer quantitativement comment la mise en cache peut aider à améliorer l'efficacité énergétique d'un cellulaire réseau. Nous tenons également à ce traitement à un ac Hetnet scénario (à savoir quand il y a plus d'un type de glspl déployé BS) et étudions divers indicateurs de performance clés. Nous explorons également les conditions où l'efficacité énergétique d'un tel système peut être améliorée. Les résultats de thèse fournissent quelques idées clés pour améliorer l'efficacité énergétique dans un réseau cellulaire sans fil contribuant ainsi à l'avancement vers la prochaine génération (5 G) des réseaux cellulaires
The task of meeting an ever growing demand for better quality of user experience in wireless communications, is challenged by the amount of energy consumed by the technologies involved and the methods employed. Not surprisingly, the problem of reducing energy consumption needs to be addressed at various layers of the network architecture and from various directions. This thesis addresses some crucial aspects of the physical layer of wireless network architecture in order to find energy efficient solutions.In the first part of this thesis, we explore the idea of energy efficiency at a fundamental level. Starting with answering questions such as - emph{What is the physical form of `information'?}, we build a simple communication device in order to isolate certain key steps in the physical process of communication and we comment on how these affect the energy efficiency of a communication system.In the second part, we use tools from stochastic geometry to theoretically model cellular networks so as to analyze the energy efficiency of the system. Exploiting the tractability of such a mathematical modeling, we explore the conditions under which the consumption of energy can be reduced. Further in this part, we introduce the concept of caching users' data at the edge of the network (namely the final ac{BS} that is contact with the user) and show quantitatively how caching can help improve the energy efficiency of a cellular network. We also extend this treatment to a ac{HetNet} scenario (namely when there are more than one type of glspl{BS} deployed) and study various key performance metrics. We also explore the conditions where energy efficiency of such a system can be improved.The results in thesis provide some key ideas to improve energy efficiency in a wireless cellular network thereby contributing to the advancement towards the next generation (5G) cellular networks

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Groman, Martin. "Tvorba umělé neuronové sítě pro výpočet termodynamických veličin." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2019. http://www.nusl.cz/ntk/nusl-400473.

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This master thesis is dealing with application of an artificial neural network for calculating specific volume of steam. There is described type and construction of the needed neural network. The main outcome of this work is an executable programme, which calculates specific volume of steam for given pressure and temperature, using neural nets.

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Igarashi, Edson Massakazu de Souza. "Modelagem, consistência e simulação termodinâmica do comportamento de fases líquido-vapor de sistemas binários contendo componentes presentes na produção de biodiesel." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/97/97137/tde-21112017-135312/.

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Considerado a alternativa mais pesquisada para substituir o diesel, o biodiesel, oriundo da transesterificação, é cotado como a mais promissora opção de combustível obtido de fontes renováveis para o lugar dos ameaçados combustíveis de origem fóssil. A reação de transesterificação para produção do biodiesel pode ocorrer de forma catalítica, a mais utilizada atualmente, e não-catalítica, por meio de fluidos supercríticos. A grande diversidade de matérias-primas que pode ser usada na obtenção do biodiesel supercrítico é apenas um dos atrativos para sua produção, porém uma produção em larga escala esbarraria nos altos custos operacionais do processo. Devido ao potencial revelado nos processos supercríticos, o estudo do comportamento de fases dentro de um reator se mostra relevante ao domínio do processo, visto que pesquisas indicam que é possível balancear os custos de uma produção de biodiesel em condições supercríticas com os custos de uma produção de biodiesel com uso de catalisadores. Na termodinâmica, a modelagem é um método prático e rápido de se estimar o comportamento do equilíbrio líquido-vapor (ELV) do sistema e reduzir gastos com excessivos experimentos, através de um modelo termodinâmico apropriado. Para isso, os modelos testados foram obtidos pela equação de estado (EdE) de Peng-Robinson com as regras de misturas de van der Waals com um (vdW1) e dois (vdW2) parâmetros de interação binária em sistemas formados por componentes presentes na produção do biodiesel. Utilizando a abordagem phi-phi e o método de BOLHA P, sistemas binários em condições próximas ao ponto crítico e em condições supercríticas, encontrados na literatura, foram modelados. A modelagem termodinâmica foi realizada após a aplicação de um teste de consistência termodinâmica, uma vez que foram encontradas diferenças nas propriedades críticas de um mesmo composto em diferentes referências. A adequação dos modelos termodinâmicos variou de acordo com as condições do processo, o que fará necessária uma análise específica da situação de acordo com o caso em que estiver sendo empregada. Na simulação termodinâmica, as redes neurais artificiais foram utilizadas para o ajuste computacional dos dados experimentais, produzindo os melhores resultados com a introdução dos descritores moleculares, junto às variáveis independentes do processo (temperatura e composição na fase líquida), na primeira camada de neurônios nas diversas configurações analisadas dentre as arquiteturas utilizadas, demonstrando ser uma ferramenta interessante para o estudo do equilíbrio de fases.
Considered the most researched alternative to replace the diesel fuel, the biodiesel, from transesterification, is rated as the most promising fuel option from renewable sources for the place of threatened fossil fuels. The transesterification reaction for biodiesel production can occur catalytically, commonly used, and non-catalytic, through supercritical fluids. The diversity of raw materials that can be used to obtain supercritical biodiesel is only one of the attractions for its production, but a large-scale production would encounter obstacles in the high operating costs of the process. Due to the potential revealed in the supercritical processes, the study of phase behavior in a reactor is relevant for domaining the process, since researches indicates that it is possible to balance the costs of producing biodiesel in supercritical conditions with the costs of a production of biodiesel using catalysts. In thermodynamics, modeling is a quick and practical method of estimating the vapor-liquid equilibria (VLE) behavior of the system and reducing expenses with excessive experiments, using an appropriated thermodynamic model. For this, the models tested were obtained by the Peng-Robinson equation of state (EoS) with the mixture rules of van der Waals with one (vdW1) and two (vdW2) binary interaction parameters in systems formed by components present in the production of biodiesel. Using the phi-phi approach and the BOL P method, binary systems in conditions near to the critical point and under supercritical conditions, found in the literature, were modeled. The thermodynamic modeling was performed after the application of a thermodynamic consistency test, since differences were found in the critical properties of the same compound in different references. The suitability of the thermodynamic models varied according to the process conditions, which will require a specific analysis of the situation according to the case in which it is being used. In the thermodynamic simulation, the artificial neural networks were used for the computational adjustment of the experimental data, producing the best results when the molecular descriptors were used with the independent variables of the process (temperature and composition of the liquid phase) in the first layer of nodes in the different configurations analyzed among the architectures used, proving to be a tool of interest for the study of phase equilibria.

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Blokhuis, Alexander. "Aspects physiques des scénarios d'origines de la vie." Thesis, Paris Sciences et Lettres (ComUE), 2019. http://www.theses.fr/2019PSLET043.

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Le domaine des Origines de la vie cherche à expliquer l’abiogenèse : comment la matière abiotique peut se transformer en vivant. Ces dernières décennies ont vu l’élaboration de plusieurs scénarios prébiotiques : hypothèses sur la place, la chimie et les mécanismes physiques de l’abiogenèse. Dans cette thèse, nous introduisons des cadres rigoureux, pour l’étude systématique des aspects physiques de l’abiogenèse. Ces cadres s’appuient sur des avancements en thermodynamique hors d’équilibre, réseaux de réactions chimiques et sélection sur plusieurs niveaux. Ils soulignent la cohérence thermodynamique et la structure fondamentale de la chimie. Ch.1 donne une introduction critique au domaine des origines de la vie, soulignant ce que nous savons, ce que les scénarios supposent et les développements historiques qui ont façonné la pensée actuelle. Ch.2 présente le cadre théorique des réseaux chimiques. Nous élargissons le cadre avec de nouveaux outils et un critère pour une description universelle de la chimie : la non-ambiguïté. Ch.3 décrit des moyens pour rendre les réseaux "ouverts" : chimiostats, CSTR, transfert en série, couplage diffusif aux compartiments. Le concept de chimiostat est étendu au "chimiostat composite", qui fixe une combinaison d’espèces. Nous corrigeons la loi zéro de la thermodynamique, qui, en thermodynamique stochastique, peut être brisée pour les quantités entières conservées. Ch.4 illustre le concept d'information dans les réseaux chimiques à l'aide d'un moteur qui extrait du travail en racémisant des énantiomères purs. On passe ensuite au procédé inverse : la purification des compositions. On présente des réseaux qui améliorent la purification, avec différents compromis. Ch.5 présente la dérivation des critères universels pour la catalyse et l'autoréplication pour les réseaux chimiques non-ambigus. L'échange entre phases et compartiments (diffusion, évaporation, etc.) conduit à l'émergence de nouvelles formes d'autocatalyse à compartiments multiples.Nous passons en revue différents cadres théoriques pour l’évolution chimique en Ch.6. Ces cadres se concentrent sur des chimies et des structures de réseaux spécifiques, et dépendent sensiblement du niveau de description. Ces approches peuvent être réunis et étendues, ils sont compris dans notre cadre général pour l'autocatalyse. On décrit des aspects thermodynamiques et structuraux de l’évolution autocatalytique, qui se produit par des processus de branchement aux taux microscopiques. L'extension à l’autocatalyse à compartiments multiples conduit à des comportements écologiques (syntrophie, parasitisme, coopération). Ch.7 étudie la formation de copolymères longes (par adsorption, recombinaison, ligature chimiquement activé). On trouve les coûts thermodynamiques pour la génération dissipative des séquences aléatoires. Ceci introduit des bornes énergétiques sur les scénarios qui reposent sur l’apparition des structures rares. Ch.8 présente un cadre statistique pour la compartimentation transitoire. Cette forme de sélection multi-niveaux n'a pas de lignées : un compartiment survivant disparaît après sa croissance et sélection. Cela fait que son contenu peut être multiplié par plus qu'un facteur de 2 (expérimentalement : >10^6). Ce mécanisme s'est avéré capable de surmonter les invasions parasitaires, d'induire une coopération et d'abaisser les seuils d'erreur. Le bruit de composition suit de la cinétique de croissance. La polymérisation peut réduire considérablement ce bruit, ce qui peut favoriser sa sélection. À ce niveau de description, les parasites donnent lieu à une nouvelle catastrophe lié à la complexation. Ch.9 présente un nouveau scénario, fondé sur des mécanismes. Le scénario est basé sur la structure de la chimie, l'autocatalyse et sélection à plusieurs niveaux, mais ne spécifie pas de molécules : elles peuvent être introduites a posteriori. Nous fournissons une base sur laquelle des scénarios rigoureux pour l'avenir peuvent être construits
The academic field of Origins of Life seeks to explain abiogenesis: how abiotic matter can be transformed to living systems. Recent decades have seen a substantial development of prebiotic scenarios: hypotheses on the place, chemistry and physical mechanisms of abiogenesis. In this thesis, we introduce rigorous frameworks, for the systematic study of physical aspects of abiogenesis. These frameworks build upon recent insights in nonequilibrium thermodynamics, chemical reaction networks and group selection. They stress thermodynamic consistency and the fundamental structure of chemistry. In Ch.1, a critical introduction to the field of origins of life is given, highlighting what we truly know, what popular scenarios assume and historical developments that have shaped the current thinking. In Ch.2, the theoretical framework of chemical networks is introduced. We extend the framework with new tools and a criterion for a universal description of chemistry: nonambiguity. In Ch.3, we describe ways to make networks ‘open’: chemostats, CSTR, serial transfer, diffusive coupling to compartments. The concept of chemostats is extended to ‘composite chemostats’, which chemostats combinations of species. We correct the zeroth law of thermodynamics, which is shown to be violated for conserved integer quantities in stochastic thermodynamics. In Ch.4, we illustrate the concept of information in chemical networks, using a scalable engine that extracts work from the racemization of enantiomerically pure molecules. We then move to the opposite process: purifying compositions. We illustrate a variety of chemical networks that achieve purification, and we discuss their tradeoffs. In Ch.5, we derive universal criteria for catalysis and self-replication for unambiguous chemical networks. The addition of exchange processes between phases and compartments (diffusion, evaporation, partitioning etc.) leads to emergent new forms of multicompartment autocatalysis. In Ch.6, we review the concept of chemical evolution and some of the frameworks developed for it. These frameworks focus on specific chemistries and network structures, and we show that their interpretation critically hinges on the level of coarse graining. These approaches, often treated as mutually exclusive, are united, extended and encompassed by our general framework for autocatalysis. We study structural and thermodynamic aspects of autocatalytic evolution in a single reactor, which occurs by branching processes built up from microscopic rates. The extension to multicompartment autocatalysis leads to new emergent ecological behavior (syntrophy, parasitism), favoring cooperation and spatial confinement. In Ch.7, we study the thermodynamics of making long polymers in various out-of-equilibrium situations (adsorption, recombination reactions, chemically activated ligation). We derive thermodynamic costs for the dissipative generation of random copolymer sequences. This allows to place energetic bounds on scenarios that rely on the appearance of rare structures. In Ch.8, we set up a statistical framework to study transient compartmentalization. This new form of multilevel selection has no lineages: surviving compartments vanish after growth and selection, which means contents may multiply by more than a factor 2 (experimentally: >10^6). This mechanism is shown capable of overcoming parasite invasions, induce cooperation and lower error thresholds. Compositional noise is derived from growth kinetics. Polymerization can drastically decrease such noise, which can improve selection. On this level of description, a new parasite catastrophe emerges: a complexation catastrophe. In Ch.9, we formulate a mechanism-based scenario. The scenario is based on the structural features of chemistry, multicompartment autocatalysis and multi-level evolution, but does not specify any molecules: they can be introduced a posteriori. We provide a foundation on which rigorous future scenarios can be built

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Schulz, Christoph. "Causation and the objectification of agency." Thesis, University of Hertfordshire, 2015. http://hdl.handle.net/2299/16480.

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This dissertation defends the so-called 'agency-approach' to causation, which attempts to ground the causal relation in the cause's role of being a means to bring about its effect. The defence is confined to a conceptual interpretation of this theory, pertaining to the concept of causation as it appears in a causal judgement. However, causal judgements are not seen as limited to specific domains, and they are not exclusively attributed to human agents alone. As a methodological framework to describe the different perspectives of causal judgments, a method taken from the philosophy of information is made use of - the so-called 'method of abstraction'. According to this method, levels of abstraction are devised for the subjective perspective of the acting agent, for the agent as observer during the observation of other agents' actions, and for the agent that judges efficient causation. As a further piece of propaedeutic work, a class of similar (yet not agency-centred) approaches to causation is considered, and their modelling paradigms - Bayesian networks and interventions objectively construed - will be criticised. The dissertation then proceeds to the defence of the agency-approach, the first part of which is a defence against the objection of conceptual circularity, which holds that agency analyses causation in causal terms. While the circularity-objection is rebutted, I rely at that stage on a set of subjective concepts, i.e. concepts that are eligible to the description of the agent's own experience while performing actions. In order to give a further, positive corroboration of the agency-approach, an investigation into the natural origins and constraints of the concept of agency is made in the central chapter six of the dissertation. The thermodynamic account developed in that part affords a third-person perspective on actions, which has as its core element a cybernetic feedback cycle. At that point, the stage is set to analyse the relation between the first- and the third-person perspectives on actions previously assumed. A dual-aspect interpretation of the cybernetic-thermodynamic picture developed in chapter six will be directly applied to the levels of abstraction proposed earlier. The level of abstraction that underpins judgments of efficient causation, the kind of causation seemingly devoid of agency, will appear as a derived scheme produced by and dependent on the concept of agency. This account of efficient causation, the 'objectification of agency', affords the rebuttal of a second objection against the agency-approach, which claims that the approach is inappropriately anthropomorphic. The dissertation concludes with an account of single-case, or token level, causation, and with an examination of the impact of the causal concept on the validity of causal models.

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Musavu-Ndob, Aïchatou. "Mesures, modélisation, prédiction des propriétés physico-chimiques dans les aliments à l'aide d'un modèle thermodynamique : application aux produits carnés et aux produits laitiers." Thesis, Clermont-Ferrand 2, 2016. http://www.theses.fr/2016CLF22682/document.

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Le développement de simulateurs de procédés alimentaires est limité par le manque d’outils permettant de prédire les propriétés physicochimiques (pH, aw, Eh) dans les aliments. Les aliments sont généralement des milieux très complexes contenant un nombre élevé de constituants (eau, solvants organiques, solides dissous, gaz dissous, espèces ioniques, macromolécules), et ces propriétés sont essentielles pour caractériser leur qualité technologique, sanitaire et organoleptique. Cependant, elles évoluent au cours d’un procédé de transformation ou de conservation. La prédiction de ces propriétés physicochimiques passe par la détermination de potentiels chimiques. Une approche de modélisation basée sur la thermodynamique est utilisée pour prédire l’évolution du pH et de l’aw de produits carné et produits laitiers dans certaines conditions rencontrées en industrie alimentaire. En s’appuyant sur le modèle ULPDHS développé par Achard en 1992 pour les milieux liquides, ce travail a nécessité la création de molécules fictives à ayant le même comportement que les aliments modélisés. La cohérence entre les données expérimentales et les données prédites est satisfaisante, le modèle thermodynamique permet de prédire correctement le pH et l’aw des différents milieux étudiés. Cependant l’intégration du modèle thermodynamique dans un simulateur de procédé nécessite la création d’un réseau de neurone mimétique du modèle thermodynamique. En conséquent a été développé un réseau de neurones dont les sorties sont identiques aux sortie du modèle thermodynamique. Ainsi il est possible d’intégrer les résultats du modèles thermodynamique dans un simulateur de procédé sans trop rallonger les temps de simulations. Les résultats obtenus dans ce travail peuvent être une aide importante à la formulation de nouveaux produits. Le modèle étant entièrement prédictif, il est possible de déterminer l’effet d’une modification de composition de l’aliment sur le pH et l’aw
The development of food process simulators is actually limited by absence of tools that can predict de evolution of the physical-chemical properties (pH, aw, Eh) in food. Food are generallymulticomponent medias (including water, organic solvents, dissolved solids, dissolved gases, ionic species, macromolecules), and these properties are essential to characterize technological, sanitary and organoleptic qualities. However, these physical-chemical properties change during transformation or preservation process. The prediction of these properties requires the determination of chemical potentials. Thermodynamic approach is used to predict pH and water activity of meat and dairy products in different condition encountered in the food industry. Based on the model ULPDHS developed by Achard in 1992 for liquid medias, this work required the creation of fictive molecule who have the same behavior as modeled food. Consistency between the experimental data and the predicted data is very satisfactory, the thermodynamic model correctly predict the pH and aw of different products studied. The integration of the thermodynamic model in a process simulator requires the creation of a mimetic neural network. Therefore, was developed a neural network whose outputs are identical to the output of the thermodynamic model. So it is possible to integrate the results of thermodynamic models in a process simulator without too lengthen the time simulations. The results obtained in this work can be an important aid to the formulation of new products. The model is completely predictive and it is possible to determine the effect of a change in the composition of the feed on the pH and aw

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Andersson, Martin. "Phase Phenomena in Polymer Networks : Empirical Studies on the Influence of Hydrophobicity, Charge Density and Crosslinks on Macroion-Induced Phase Transitions in Polyelectrolyte Gels." Doctoral thesis, Uppsala universitet, Institutionen för farmaci, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-145381.

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The thesis concerns polyelectrolyte gels in contact with oppositely charged proteins and surfactant micelles, and includes of four papers (I-IV). In paper I confocal Raman spectroscopy was introduced as a method to trace micelles and investigate the structure of gel-surfactant complexes, in phase separated gel spheres. In paper II, the binding of surfactants to microspheres (~50-100 µm) was investigated by means of a micromanipulator-assisted microscopy method. The two surfactants were found to display qualitative difference respect to degree of swelling, surfactant distribution in the gels, and the difference is discussed in terms of absence/presence of hydrophobic attraction to the polyelectrolyte gel network. Kinetics of volume change in gels were analyzed. Aggregation numbers of micelles in polystyrenesulfonate (PSS) solutions, obtained from fluorescence quenching measurements, are presented. In paper III, phase behaviour, protein assembly and diffusion, was studied in PSS gel microspheres. Interpretation of results was aided by measurements of osmotic swelling of individual gel networks, and by combining the results with studies of protein diffusion in macroscopic (cm-sized) gel spheres. Complexes formed were further analyzed with small angle x-ray spectroscopy. In paper IV phase behaviour of mixed ionic/nonionic surfactant micelles is investigated in cm-sized gel spheres. The coexistence of three phases, the formation of dense shells in the bulk of the gels and other phenomena are described for the first time, and the results are presented along with discussion on the charge-density of spherical micelles and of network induced hysteresis effects in gels. The composition and microstructure of phases are investigated by confocal Raman spectroscopy and small-angle x-ray scattering respectively. The results are interpreted with aid of highly detailed theoretical model calculations.

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Zhu, Xin X. (Xin Xiong). "Strategies for optimization in heat exchanger network design / by (Frank) Xin X. Zhu." 1994. http://hdl.handle.net/2440/21540.

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Bibliography: leaves 273-287.
xviii, 289 leaves : ill. ; 30 cm.
Title page, contents and abstract only. The complete thesis in print form is available from the University Library.
The aim of this thesis is to develop a new method for the conceptual design of heat exchanger networks. The initial designs can be optimized using conventional non-linear optimization techniques in the subset of the problem's initial dimensionality.
Thesis (Ph.D.)--University of Adelaide, Dept. of Chemical Engineering, 1994

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Van, Bussel Frank. "Topological Optimization in Network Dynamical Systems." Thesis, 2010. http://hdl.handle.net/11858/00-1735-0000-0006-B5BF-1.

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CHEN, RUI-TANG, and 陳瑞堂. "Thermodynamic property prediction with the aid of artificial neural network." Thesis, 1992. http://ndltd.ncl.edu.tw/handle/47211590476821040308.

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Chang, Chan-Chi, and 張展綺. "Improving Neural Network Training Program and Programming of Auto-Training Feedforward Neural Network of Thermodynamic Model." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/46q8m4.

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碩士
國立臺北科技大學
化學工程研究所
96
At this study, the crash problem of our laboratory developed program of Quasi-Newton training feedforward neural network was solved. And the normalization of input and output data of neural network model no longer required. In many simulations of chemical engineering process, it is common to calculate the boiling point and the equilibrium composition of gas phase by thermodynamic model.But the calculation direct from thermodynamic model spends much time in iteration.At this work developing a auto-training neural network sub program, which can fit VLE data calculating from thermodynamic model to a neural network model.Then thermodynamic model is replaced by neural network model to reduce computation time in simulation. This program is developed by Visual Basic 2005. Thermodynamic model is NRTL (Non Random Two Liquid) binary model in this program. Program according the parameters to get VLE data, and neural network training fit the data to get neural network model, program determine the numbers of neurons at hidden layer in training procedure automatically. 18 azeotrope and 5 non-azeotrope examples were used to test the applicability of the program. The result shows the program is practicable.

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Schröder, Heiko Christian [Verfasser]. "Thermodynamic functionality of autonomous quantum networks / vorgelegt von Heiko Christian Schröder." 2010. http://d-nb.info/1008368156/34.

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Ren, Yikai. "A recursive design method for heat exchanger networks / by Yikai Ren." Thesis, 2000. http://hdl.handle.net/2440/19833.

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Last leaf includes a list of publications co-authored by the author during the preparation of this thesis.
Includes bibliographical references (leaves 179-187).
xiv, 188 leaves : ill. ; 30 cm.
A novel and reliable method for heat exchanger network synthesis is proposed.The prime objective has been the elimination or reduction of drawbacks inherent in both evolutionary methods and mathematical programming methods while retaining the adevantages of both methods.
Thesis (Ph.D.)--Adelaide University, Dept. of Chemical Engineering, 2001

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Ren, Yikai. "A recursive design method for heat exchanger networks / by Yikai Ren." 2000. http://hdl.handle.net/2440/19833.

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Last leaf includes a list of publications co-authored by the author during the preparation of this thesis.
Includes bibliographical references (leaves 179-187).
xiv, 188 leaves : ill. ; 30 cm.
Title page, contents and abstract only. The complete thesis in print form is available from the University Library.
A novel and reliable method for heat exchanger network synthesis is proposed.The prime objective has been the elimination or reduction of drawbacks inherent in both evolutionary methods and mathematical programming methods while retaining the adevantages of both methods.
Thesis (Ph.D.)--Adelaide University, Dept. of Chemical Engineering, 2001

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Chang, Kai-Yi, and 張凱伊. "A Study on Effect of Network Structure on Mechanical and Thermodynamic Properties in Bis-phenol A Diglycidylmethacrylate." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/aywf48.

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碩士
國立臺灣科技大學
材料科學與工程系
100
Adhesives were prepared by using bis-phenol A diglycidylmethacrylate（BisGMA）and 2-hydroxyethyl methacrylate（HEMA）of different weight ratios in feed. Camphoroquinone（CQ）and diphenylphosphine oxide are photoinitiators. We add silica in various contents of feed and cure BisGMA and HEMA with visible light and photoinitiators. We discuss the effects of BisGMA/HEMA weight ratios in feed and contents of silica on conversion of reaction, network structure, thermodynamic and mechanical properties. 　　Results show that quantities of unreacted C=C increase with increasing the contents of BisGMA in polymer by 13C Solid-state NMR. According to FTIR analysis, as the contents of BisGMA increase, the conversions of double bonds decrease. Mass conversion ratios have the same trend as the conversions of double bonds. Compressive modulus, Young’s modulus and crosslinking densities increase with increasing the contents of BisGMA in feed. Both of the density of physical entanglement（Ns）and the density of chemical crosslinking in network（Nc） increase with increasing the contents of BisGMA in feed, showing that adding BisGMA is favorable for physical and chemical crosslinking. When BisGMA/HEMA weight ratio in feed is 60/40, the ultimate strength and ultimate elongation at the maximum. In addition, the interaction parameters of water and polymers in adhesives (χ) were calculated by crosslinking densities and equilibrium water contents. As the χ values increase, the equilibrium water contents decrease. Curing volume shrinkages decrease with increasing the contents of BisGMA in feed because of BisGMA with more unsaturated bonds. We find pyrolysis temperatures increase with increasing the relative contents of HEMA by TGA, because the solubility parameter of HEMA is higher than BisGMA’s. 　　On the other hand, when the polymers are with low contents of silica, the conversions of double bonds increase with increasing the contents of silica. But we observed with SEM the aggregation of the silica particles at the excess of silica contents, and the conversions of double bonds decrease at this juncture. As the contents of silica increase, decreasing equilibrium water contents was found because the silica is hydrophobic. In addition, all of compressive modulus, crosslinking densities, the densities of physical entanglement in network, the densities of chemical crosslinking in network, ultimate strength and ultimate elongation increase with increasing the contents of silica. And Young’s modulus increase in a nonlinear relationship with increasing the contents of silica. The volume shrinkages decrease with increasing the contents of silica. Adding inorganic particles in adhesives can raise pyrolysis temperatures and thermal stability of materials. The char yield increases slightly because the carbonization of the polymer is affected in a minor way by silica and it accumulates at the silica surface. 　　Experimental results show that when we vary BisGMA/HEMA ratios in feed and silica contents, that will influence the network structure of polymer, thereby affecting crosslinking density of adhesives, mechanical properties, equilibrium water contents, interactions between water and polymers, thermal stability and other properties of polymers.

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Tran, Duc T. "Development and Application of a quantitative Mass spectrometry based Platform for Thermodynamic Analysis of Protein interaction Networks." Diss., 2013. http://hdl.handle.net/10161/8187.

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The identification and quantification of protein-protein interactions in large scale is critical to understanding biological processes at a systems level. Current approaches for the analysis of protein -protein interactions are generally not quantitative and largely limited to certain types of interactions such as binary and strong binding interactions. They also have high false-positive and false-negative rates. Described here is the development of and application of mass spectrometry-based proteomics metehods to detect and quantify the strength of protein-protein and protein-ligand interactions in the context of their interaction networks. Characterization of protein-protein and protein-ligand interactions can directly benefit diseased state analyses and drug discovery efforts.

The methodologies and protocols developed and applied in this work are all related to the Stability of Unpurified Proteins from Rates of amide H/D Exchange (SUPREX) and Stability of Protein from Rates of Oxidation (SPROX) techniques, which have been previously established for the thermodynamic analysis of protein folding reactions and protein-ligand binding interactions. The work in this thesis is comprised of four parts. Part I involves the development of a Histidine Slow H/D exchange protocol to facility SURPEX-like measurements on the proteomic scale. The Histidine Slow H/D exchange protocol is developed in the context of selected model protein systems and used to investigate the thermodynamic properties of proteins in a yeast cell lysate.

In Part II an isobaric mass tagging strategy is used in combination with SPROX (i.e., a so-called iTRAQ-SPROX protocol) is used to characterize the altered protein interactions networks associated with lung cancer. This work involved differential thermodynamic analyses on the proteins in two different cell lines, including ADLC-5M2 and ADLC-5M2-C2.

Parts III and IV of this thesis describe the development and application of a SPROX protocol for proteome-wide thermodynamic analyses that involves the use of Stable Isotope Labeling by Amino acid in cell Culture (SILAC) quantitation. A solution-based SILAC-SPROX protocol is described in Part III and a SILAC-SPROX protocol involving the use of cyanogen bromide and a gel-based fractionation step is described in Part IV. The SILAC-SPROX-Cyanogen bromide (SILAC-SPROX-CnBr) protocol is demonstrated to significantly improve the peptide and protein coverage in proteome-wide SPROX experiments. Both the SILAC-SPROX and SILAC-SPROX-CnBr porotocols were used to characterize the ATP binding properties of yeast proteins. Ultimately, the two protocols enabled 526 yeast proteins to be assayed for binding to AMP-PNP, an ATP mimic. A total of 140 proteins, including 37 known ATP-binding proteins, were found to have ATP binding interactions.

Dissertation

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Mondal, Chandana. "Equilibrium and Rheological Properties of Model Network Formers." Thesis, 2019. http://hdl.handle.net/10821/8292.

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This thesis embodies a study of the static and dynamic aspects of network forming liquids in two-dimensions starting from a very simple model of binary mixture of Lennard-Jones type particles to patchy colloids with complex inter-particle interactions. In the rst chapter we provide a general overview of simple and complex colloids which is then followed by a discussion on the various anomalous properties shown by network forming liquids and their computer simulation models focusing mainly on the most common and important network-forming liquid i.e. water. Discussion on the dynamic aspects like di usion, response to external shear and glassy dynamics is then presented in the following section. E ect of con nement on the thermodynamic and dynamic properties of network-formers is discussed in the last section of this chapter.
Research was carried out under the supervision of Prof. Surajit Sengupta of CAM under SPS [School of Physical Sciences]
Research was conducted under IACS fellowship and DST grant

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Ulrich, Stephan. "Aggregation and Gelation in Random Networks." Doctoral thesis, 2010. http://hdl.handle.net/11858/00-1735-0000-0006-B4C7-A.

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Kapustin, Victor. "Povaha podnikání: společnost, jednotlivec a firma." Master's thesis, 2016. http://www.nusl.cz/ntk/nusl-345286.

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Entrepreneurship is often perceived as a crucial component of economic growth and social development. Studies into entrepreneurship inform policy design, thus the diverse understanding of entrepreneurship among scholars can create confusion in policy design. The current state of the field of entrepreneurial research is examined in order to identify the need for a universal definition of entrepreneurship. After a synthesis and analysis of prior research is conducted to identify the various links in perspectives, a new definition and framework is suggested. The resulting framework sees entrepreneurship as an autocatalytic process of creation of meaning and the consequent retention of said meaning in the structure of a new venture. The elements of this framework (autocatalytic process, creation of meaning, and retention in structure) can be assigned varying degrees of importance corresponding to differing perspectives, while simultaneously ensuring the presence of each element. The developed framework can be used to better inform the decisions of scholars and policy makers, due to the uncovering of the complex relationships between society, individuals and firms.

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(8790188), Abhishek Navarkar. "MACHINE LEARNING MODEL FOR ESTIMATION OF SYSTEM PROPERTIES DURING CYCLING OF COAL-FIRED STEAM GENERATOR." Thesis, 2020.

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The intermittent nature of renewable energy, variations in energy demand, and fluctuations in oil and gas prices have all contributed to variable demand for power generation from coal-burning power plants. The varying demand leads to load-follow and on/off operations referred to as cycling. Cycling causes transients of properties such as pressure and temperature within various components of the steam generation system. The transients can cause increased damage because of fatigue and creep-fatigue interactions shortening the life of components. The data-driven model based on artificial neural networks (ANN) is developed for the first time to estimate properties of the steam generator components during cycling operations of a power plant. This approach utilizes data from the Coal Creek Station power plant located in North Dakota, USA collected over 10 years with a 1-hour resolution. Cycling characteristics of the plant are identified using a time-series of gross power. The ANN model estimates the component properties, for a given gross power profile and initial conditions, as they vary during cycling operations. As a representative example, the ANN estimates are presented for the superheater outlet pressure, reheater inlet temperature, and flue gas temperature at the air heater inlet. The changes in these variables as a function of the gross power over the time duration are compared with measurements to assess the predictive capability of the model. Mean square errors of 4.49E-04 for superheater outlet pressure, 1.62E-03 for reheater inlet temperature, and 4.14E-04 for flue gas temperature at the air heater inlet were observed.

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Dissertations / Theses on the topic 'Network thermodynamics'

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