Статті в журналах: "Computationat modelling"

1

Kourou, K., and DI Fotiadis. "Computational Modelling in Cancer: Methods and Applications." Biomedical Data Journal 01, no. 1 (January 2015): 15–25. http://dx.doi.org/10.11610/bmdj.01103.

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Lloyd, Austin, Helen Moylan, and Joseph McDouall. "Modelling the Effect of Zero-Field Splitting on the 1H, 13C and 29Si Chemical Shifts of Lanthanide and Actinide Compounds." Magnetochemistry 5, no. 1 (January 11, 2019): 3. http://dx.doi.org/10.3390/magnetochemistry5010003.

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The prediction of paramagnetic NMR (pNMR) chemical shifts in molecules containing heavy atoms presents a significant challenge to computational quantum chemistry. The importance of meeting this challenge lies in the central role that NMR plays in the structural characterisation of chemical systems. Hence there is a need for reliable assignment and prediction of chemical shifts. In a previous study [Trends in Physical Chemistry, 17, 25–57, (2017)] we looked at the computation of pNMR chemical shifts in lanthanide and actinide complexes using a spin Hamiltonian approach. In that study we were principally concerned with molecules with S = 1/2 ground states. In the present work we extend that study by looking at the effect of zero field splitting (ZFS) for six complexes with S = 3/2 ground states. It is shown that the inclusion of ZFS can produce substantial shifts in the predicted chemical shifts. The computations presented are typically sufficient to enable assignment of experimental spectra. However for one case, in which the peaks are closely clustered, the inclusion of ZFS re-orders the chemical shifts making assignment quite difficult. We also observe, and echo, the previously reported importance of including the paramagnetic spin-orbit hyperfine interaction for 13 C and 29 Si atoms, when these are directly bound to a heavy element and thus subject to heavy-atom-light-atom effects. The necessary computations are very demanding, and more work is needed to find theoretical and computational approaches that simplify the evaluation of this term. We discuss the computation of each term required in the spin Hamiltonian. The systems we study in this work are restricted to a single heavy atom ion (one Nd(III) and five U(III) complexes), but typify some of the computational complexity encountered in lanthanide and actinide containing molecules.

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Čiegis, R., A. Dement'ev, and G. Šilko. "PARALLEL NUMERICAL MODELLING OF SHORT LASER PULSE COMPRESSION." Mathematical Modelling and Analysis 9, no. 2 (June 30, 2005): 115–26. http://dx.doi.org/10.3846/13926292.2004.9637246.

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In this paper we investigate parallel numerical algorithms for solution of the transient stimulated scattering processes. A new symmetrical splitting scheme is proposed and a parallel version is given. The efficiency of the parallel algorithm is investigated for two cases. The first one describes a case when the computation region is constant during the whole time of computations. The second one describes the initial phase of the process, when the computational region increases linearly in time. In order to distribute more evenly jobs between processors a dynamical the grid redistribution algorithm is is used. We also give a proof of one result about optimal static grid distribution in the case of linearly increased problem complexity. The results of computations are presented. They were obtained on different parallel computers and clusters of workstations. Nagrinejamas priverstines Brijueno sklaidos fokusuotuose pluoštuose uždavinio lygiagretusis skaitinis sprendimo algoritmas. Sukonstruota simetrinio skaidymo baigtiniu skirtumu schema, kurios tikslumas yra antrosios eiles. Lygiagretusis algoritmas gautas naudojant duomenu lygiagretumo paradigma. Detaliai nagrinejamas dinamiškai didejančio sudetingumo uždavinys, modeliuojantis Brijueno sklaidos procesa, kai neužduodama kraštine salyga Stokso bangai. Irodyta hipoteze apie vieno stacionaraus blokinio duomenu paskirstymo algoritmo op‐timaluma. Eksperimentiškai ištirtas dinaminis duomenu perskirstymo algoritmas, patvirtintas jo efektyvumas net ir fiksuoto dydžio uždaviniams. Darbe pateikti skaitinio eksperimento, atlikto naudojant VGTU 20 procesoriu klasteri, rezultatai. Jie patvirtino gautuosius teorinius rezultatus, išsam us fizikiniai rezultatai bus išspausdinti kituose darbuose.

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Dayan, P. "Computational modelling." Current Opinion in Neurobiology 4, no. 2 (1994): 212–17. http://dx.doi.org/10.1016/0959-4388(94)90075-2.

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Nivelkar, Mukta, and S. G. Bhirud. "Modeling of Supervised Machine Learning using Mechanism of Quantum Computing." Journal of Physics: Conference Series 2161, no. 1 (January 1, 2022): 012023. http://dx.doi.org/10.1088/1742-6596/2161/1/012023.

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Abstract Mechanism of quantum computing helps to propose several task of machine learning in quantum technology. Quantum computing is enriched with quantum mechanics such as superposition and entanglement for making new standard of computation which will be far different than classical computer. Qubit is sole of quantum technology and help to use quantum mechanism for several tasks. Tasks which are non-computable by classical machine can be solved by quantum technology and these tasks are classically hard to compute and categorised as complex computations. Machine learning on classical models is very well set but it has more computational requirements based on complex and high-volume data processing. Supervised machine learning modelling using quantum computing deals with feature selection, parameter encoding and parameterized circuit formation. This paper highlights on integration of quantum computation and machine learning which will make sense on quantum machine learning modeling. Modelling of quantum parameterized circuit, Quantum feature set design and implementation for sample data is discussed. Supervised machine learning using quantum mechanism such as superposition and entanglement are articulated. Quantum machine learning helps to enhance the various classical machine learning methods for better analysis and prediction using complex measurement.

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Jain, Rishabh. "Review on Computational Bioinformatics and Molecular Modelling: Novel Tool for Drug Discovery." International Journal of Trend in Scientific Research and Development Volume-3, Issue-1 (December 31, 2018): 51–56. http://dx.doi.org/10.31142/ijtsrd18914.

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Okeke, Saviour I., Noel M. Harrison, and Mingming Tong. "Computational modelling of dynamic recrystallisation of Ni-based superalloy during linear friction welding." International Journal of Advanced Manufacturing Technology 119, no. 7-8 (January 12, 2022): 4461–84. http://dx.doi.org/10.1007/s00170-021-08559-1.

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AbstractLinear friction welding (LFW) is an advanced joining technology used for manufacturing and repairing complex assemblies like blade integrated disks (blisks) of aeroengines. This paper presents an integrated multiphysics computational modelling for predicting the thermomechanical-microstructural processes of IN718 alloy (at the component-scale) during LFW. Johnson–Mehl–Avrami-Kolmogorov (JMAK) model was implemented for predicting the dynamic recrystallisation of γ grain, which was coupled with thermomechanical modelling of the LFW process. The computational modelling results of this paper agree well with experimental results from the literature in terms of γ grain size and weld temperature. Twenty different LFW process parameter configurations were systematically analysed in the computations by using the integrated model. It was found that friction pressure was the most influential process parameter, which significantly affected the dynamic recrystallisation of γ grains and weld temperature during LFW. The integrated multiphysics computational modelling was employed to find the appropriate process window of IN718 LFW.

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Rautenbach, Christo, Julia C. Mullarney, and Karin R. Bryan. "Parallel computing efficiency of SWAN 40.91." Geoscientific Model Development 14, no. 7 (July 6, 2021): 4241–47. http://dx.doi.org/10.5194/gmd-14-4241-2021.

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Abstract. Effective and accurate ocean and coastal wave predictions are necessary for engineering, safety and recreational purposes. Refining predictive capabilities is increasingly critical to reduce the uncertainties faced with a changing global wave climatology. Simulating WAves in the Nearshore (SWAN) is a widely used spectral wave modelling tool employed by coastal engineers and scientists, including for operational wave forecasting purposes. Fore- and hindcasts can span hours to decades, and a detailed understanding of the computational efficiencies is required to design optimized operational protocols and hindcast scenarios. To date, there exists limited knowledge on the relationship between the size of a SWAN computational domain and the optimal amount of parallel computational threads/cores required to execute a simulation effectively. To test the scalability, a hindcast cluster of 28 computational threads/cores (1 node) was used to determine the computation efficiencies of a SWAN model configuration for southern Africa. The model extent and resolution emulate the current operational wave forecasting configuration developed by the South African Weather Service (SAWS). We implemented and compared both OpenMP and the Message Passing Interface (MPI) distributing memory architectures. Three sequential simulations (corresponding to typical grid cell numbers) were compared to various permutations of parallel computations using the speed-up ratio, time-saving ratio and efficiency tests. Generally, a computational node configuration of six threads/cores produced the most effective computational set-up based on wave hindcasts of 1-week duration. The use of more than 20 threads/cores resulted in a decrease in speed-up ratio for the smallest computation domain, owing to the increased sub-domain communication times for limited domain sizes.

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MUSKULUS, MICHAEL, and ROBERT BRIJDER. "COMPLEXITY OF BIO-COMPUTATION: SYMBOLIC DYNAMICS IN MEMBRANE SYSTEMS." International Journal of Foundations of Computer Science 17, no. 01 (February 2006): 147–65. http://dx.doi.org/10.1142/s0129054106003747.

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We discuss aspects of biological relevance to the modelling of bio-computation in a multiset rewriting system context: turnover, robustness against perturbations, and the dataflow programming paradigm. The systems under consideration are maximally parallel and asynchronous parallel membrane systems, the latter corresponding to computation in which the notion of time is operationally meaningless. A natural geometrical setting which seems promising for the study of computational processes in general multiset rewriting systems is presented. Configuration space corresponds to a subset of the lattice [Formula: see text], d ∈ N, and state transitions correspond to vector addition. The similarities and differences with Vector Addition Systems and Petri nets are discussed. Symbolic dynamics are introduced on special partitions of configuration space and we indicate different notions of complexity for membrane systems based on this and related concepts such as graph complexity and minimal automata. Some examples of synchronized, pipelined dataflow computations are given and decompositions into functional subunits are briefly commented on.

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Düben, Peter D., Jaume Joven, Avinash Lingamneni, Hugh McNamara, Giovanni De Micheli, Krishna V. Palem, and T. N. Palmer. "On the use of inexact, pruned hardware in atmospheric modelling." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 372, no. 2018 (June 28, 2014): 20130276. http://dx.doi.org/10.1098/rsta.2013.0276.

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Inexact hardware design, which advocates trading the accuracy of computations in exchange for significant savings in area, power and/or performance of computing hardware, has received increasing prominence in several error-tolerant application domains, particularly those involving perceptual or statistical end-users. In this paper, we evaluate inexact hardware for its applicability in weather and climate modelling. We expand previous studies on inexact techniques, in particular probabilistic pruning , to floating point arithmetic units and derive several simulated set-ups of pruned hardware with reasonable levels of error for applications in atmospheric modelling. The set-up is tested on the Lorenz ‘96 model, a toy model for atmospheric dynamics, using software emulation for the proposed hardware. The results show that large parts of the computation tolerate the use of pruned hardware blocks without major changes in the quality of short- and long-time diagnostics, such as forecast errors and probability density functions. This could open the door to significant savings in computational cost and to higher resolution simulations with weather and climate models.

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Mohammed, Abdul-Wahid, Yang Xu, Ming Liu, and Haixiao Hu. "Semantical Markov Logic Network for Distributed Reasoning in Cyber-Physical Systems." Journal of Sensors 2017 (2017): 1–15. http://dx.doi.org/10.1155/2017/4259652.

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The challenges associated with developing accurate models for cyber-physical systems are attributable to the intrinsic concurrent and heterogeneous computations of these systems. Even though reasoning based on interconnected domain specific ontologies shows promise in enhancing modularity and joint functionality modelling, it has become necessary to build interoperable cyber-physical systems due to the growing pervasiveness of these systems. In this paper, we propose a semantically oriented distributed reasoning architecture for cyber-physical systems. This model accomplishes reasoning through a combination of heterogeneous models of computation. Using the flexibility of semantic agents as a formal representation for heterogeneous computational platforms, we define autonomous and intelligent agent-based reasoning procedure for distributed cyber-physical systems. Sensor networks underpin the semantic capabilities of this architecture, and semantic reasoning based on Markov logic networks is adopted to address uncertainty in modelling. To illustrate feasibility of this approach, we present a Markov logic based semantic event model for cyber-physical systems and discuss a case study of event handling and processing in a smart home.

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12

Kanai, Taro, Kenji Takizawa, Tayfun E. Tezduyar, Kenji Komiya, Masayuki Kaneko, Kyohei Hirota, Motohiko Nohmi, Tomoki Tsuneda, Masahito Kawai, and Miho Isono. "Methods for computation of flow-driven string dynamics in a pump and residence time." Mathematical Models and Methods in Applied Sciences 29, no. 05 (May 2019): 839–70. http://dx.doi.org/10.1142/s021820251941001x.

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We present methods for computation of flow-driven string dynamics in a pump and related residence time. The string dynamics computations help us understand how the strings carried by a fluid interact with the pump surfaces, including the blades, and get stuck on or around those surfaces. The residence time computations help us to have a simplified but quick understanding of the string behavior. The core computational method is the Space–Time Variational Multiscale (ST-VMS) method, and the other key methods are the ST Isogeometric Analysis (ST-IGA), ST Slip Interface (ST-SI) method, ST/NURBS Mesh Update Method (STNMUM), a general-purpose NURBS mesh generation method for complex geometries, and a one-way-dependence model for the string dynamics. The ST-IGA with NURBS basis functions in space is used in both fluid mechanics and string structural dynamics. The ST framework provides higher-order accuracy. The VMS feature of the ST-VMS addresses the computational challenges associated with the turbulent nature of the unsteady flow, and the moving-mesh feature of the ST framework enables high-resolution computation near the rotor surface. The ST-SI enables moving-mesh computation of the spinning rotor. The mesh covering the rotor spins with it, and the SI between the spinning mesh and the rest of the mesh accurately connects the two sides of the solution. The ST-IGA enables more accurate representation of the pump geometry and increased accuracy in the flow solution. The IGA discretization also enables increased accuracy in the structural dynamics solution, as well as smoothness in the string shape and fluid dynamics forces computed on the string. The STNMUM enables exact representation of the mesh rotation. The general-purpose NURBS mesh generation method makes it easier to deal with the complex geometry we have here. With the one-way-dependence model, we compute the influence of the flow on the string dynamics, while avoiding the formidable task of computing the influence of the string on the flow, which we expect to be small.

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Bragard, Jean R., Oscar Camara, Blas Echebarria, Luca Gerardo Giorda, Esther Pueyo, Javier Saiz, Rafael Sebastián, Eduardo Soudah, and Mariano Vázquez. "Cardiac computational modelling." Revista Española de Cardiología (English Edition) 74, no. 1 (January 2021): 65–71. http://dx.doi.org/10.1016/j.rec.2020.05.024.

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Nien, Chia-Hsing, and Frederick J. Wicklin. "An Algorithm for the Computation of Preimages in Noninvertible Mappings." International Journal of Bifurcation and Chaos 08, no. 02 (February 1998): 415–22. http://dx.doi.org/10.1142/s0218127498000279.

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For discrete dynamical systems generated by iterating a diffeomorphism, every point in the phase space has a unique preimage and it is straightforward to compute geometric structures such as inverse orbits and one-dimensional stable manifolds of periodic points. For noninvertible mappings, however, some points have multiple preimages; others may have no preimages. This makes the computation of inverse orbits difficult, because accurate computations require global knowledge about the way the mapping folds and pleats phase space. In this article we use ideas from singularity theory to examine the geometry of noninvertible mappings. We use the geometry to derive a computational algorithm for efficiently computing preimages in noninvertible mappings.

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Gujer, W. "Activated sludge modelling: past, present and future." Water Science and Technology 53, no. 3 (February 1, 2006): 111–19. http://dx.doi.org/10.2166/wst.2006.082.

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Model complexity in activated sludge modelling has increased over 30 years in parallel with the computational power of computers. Today, the complexity of biokinetics has reached a practical limit. Future advances may be in the direction of enhanced spacial resolution (CFD, single organisms) respectively, in repetitive computations (MC simulation, parameter identification). Further model development may be in niches such as population dynamics, micropollutants, etc.

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GAO, ZHENXIAO, TIANYUAN XIAO, and WENHUI FAN. "COLLABORATIVE OPTIMIZATION WITH DIMENSION REDUCTION." International Journal of Modeling, Simulation, and Scientific Computing 01, no. 02 (June 2010): 179–98. http://dx.doi.org/10.1142/s1793962310000134.

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Collaborative optimization (CO) method is widely used in solving multidisciplinary design optimization (MDO) problems, yet its computation requirement has been an obstacle to the applications, leading to doubts about CO's convergence property. The feasible domain of CO problem is first examined and it is proven that feasible domain remains the same during the CO formulation. So is the same with extreme points. Then based on contemporary research conclusion that the system-level optimization problem suffers from inherent computational difficulties, it is further pointed out that the employment of meta-heuristic optimization methods in CO could eliminate these difficulties. To make CO more computational feasible, a new method collaborative optimization with dimension reduction (CODR) is proposed. It focused on optimization dimension reduction and lets local copy of common shared design variables equal system shared design variables directly. Thus, the number of dimensions that CODR could reduce equal the number of common shared design variables. Numerical experiment suggests that CODR reduces computations greatly without losing of optimization accuracy.

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Abdulle, A., and Y. Bai. "Reduced-order modelling numerical homogenization." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 372, no. 2021 (August 6, 2014): 20130388. http://dx.doi.org/10.1098/rsta.2013.0388.

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A general framework to combine numerical homogenization and reduced-order modelling techniques for partial differential equations (PDEs) with multiple scales is described. Numerical homogenization methods are usually efficient to approximate the effective solution of PDEs with multiple scales. However, classical numerical homogenization techniques require the numerical solution of a large number of so-called microproblems to approximate the effective data at selected grid points of the computational domain. Such computations become particularly expensive for high-dimensional, time-dependent or nonlinear problems. In this paper, we explain how numerical homogenization method can benefit from reduced-order modelling techniques that allow one to identify offline and online computational procedures. The effective data are only computed accurately at a carefully selected number of grid points (offline stage) appropriately ‘interpolated’ in the online stage resulting in an online cost comparable to that of a single-scale solver. The methodology is presented for a class of PDEs with multiple scales, including elliptic, parabolic, wave and nonlinear problems. Numerical examples, including wave propagation in inhomogeneous media and solute transport in unsaturated porous media, illustrate the proposed method.

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Юрий Николаевич, Згода,, and Семенов, Алексей Александрович. "High performance computation of thin shell constructions with the use of parallel computations and GPUs." Вычислительные технологии, no. 6 (December 23, 2022): 45–57. http://dx.doi.org/10.25743/ict.2022.27.6.005.

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Предложен ряд высокопроизводительных алгоритмов компьютерного моделирования оболочечных конструкций (или оболочек) с использованием метода Ритца. Эти алгоритмы могут быть применены как при реализации метода Ритца в общем случае, так и при расчете напряженно-деформированного состояния (НДС) оболочечных конструкций. Описывается применение графических ускорителей в задаче расчета НДС. Предложенные алгоритмы включены в ранее разработанное авторами программное обеспечение моделирования НДС-оболочек. Для их апробации проведен вычислительный эксперимент. Исследование алгоритмов показало, что они позволяют повысить производительность расчета на несколько порядков в сравнении с неоптимизированной версией программного обеспечения. Purpose. The Ritz method often used for calculation of thin-shell structures allows performing a transition from a variational problem to the problem of multidimensional function minimization. The main disadvantage of this method is the nonlinear increase of computational complexity with the increase of terms amount in approximation functions. This fact makes it difficult or impossible to obtain results in cases where high solution accuracy is required or when a shell structure with complex geometry is investigated. At the same time, studies aimed at improving computing performance of the Ritz method, especially in problems of shell computer modelling, are rare. The purpose of this work is to develop algorithms for high-performance calculation of the stress-strain state (SSS) of thin-walled shell structures using the Ritz method. Methodology. Analysis of the current state in the field of computer modelling for shell structures was performed. Shell SSS calculation schemes are studied. Algorithms are proposed to improve computer modelling performance by using different mathematical model properties, multi-core CPUs and graphics accelerators. Findings. Described algorithms were implemented in shell SSS modelling software previously developed by the authors. Tests of the performance have shown that they improve the calculation time by several orders compared with the non-optimized version of the software. Originality/Value. New effective algorithms have been developed for modelling the SSS of thin- walled shell structures using the Ritz method. These algorithms can be applied not only to the calculation of shells, but to any other application of Ritz method to the problem of functional minimization.

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Petrovskii, Sergei, and Natalia Petrovskaya. "Computational ecology as an emerging science." Interface Focus 2, no. 2 (January 5, 2012): 241–54. http://dx.doi.org/10.1098/rsfs.2011.0083.

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It has long been recognized that numerical modelling and computer simulations can be used as a powerful research tool to understand, and sometimes to predict, the tendencies and peculiarities in the dynamics of populations and ecosystems. It has been, however, much less appreciated that the context of modelling and simulations in ecology is essentially different from those that normally exist in other natural sciences. In our paper, we review the computational challenges arising in modern ecology in the spirit of computational mathematics, i.e. with our main focus on the choice and use of adequate numerical methods. Somewhat paradoxically, the complexity of ecological problems does not always require the use of complex computational methods. This paradox, however, can be easily resolved if we recall that application of sophisticated computational methods usually requires clear and unambiguous mathematical problem statement as well as clearly defined benchmark information for model validation. At the same time, many ecological problems still do not have mathematically accurate and unambiguous description, and available field data are often very noisy, and hence it can be hard to understand how the results of computations should be interpreted from the ecological viewpoint. In this scientific context, computational ecology has to deal with a new paradigm: conventional issues of numerical modelling such as convergence and stability become less important than the qualitative analysis that can be provided with the help of computational techniques. We discuss this paradigm by considering computational challenges arising in several specific ecological applications.

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Hajder, Piotr, and Łukasz Rauch. "Moving Multiscale Modelling to the Edge: Benchmarking and Load Optimization for Cellular Automata on Low Power Microcomputers." Processes 9, no. 12 (December 9, 2021): 2225. http://dx.doi.org/10.3390/pr9122225.

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Numerical computations are usually associated with the High Performance Computing. Nevertheless, both industry and science tend to involve devices with lower power in computations. This is especially true when the data collecting devices are able to partially process them at place, thus increasing the system reliability. This paradigm is known as Edge Computing. In this paper, we propose the use of devices at the edge, with lower computing power, for multi-scale modelling calculations. A system was created, consisting of a high-power device—a two-processor workstation, 8 RaspberryPi 4B microcomputers and 8 NVidia Jetson Nano units, equipped with GPU processor. As a part of this research, benchmarking was performed, on the basis of which the computational capabilities of the devices were classified. Two parameters were considered: the number and performance of computing units (CPUs and GPUs) and the energy consumption of the loaded machines. Then, using the calculated weak scalability and energy consumption, a min–max-based load optimization algorithm was proposed. The system was tested in laboratory conditions, giving similar computation time with same power consumption for 24 physical workstation cores vs. 8x RaspberryPi 4B and 8x Jetson Nano. The work ends with a proposal to use this solution in industrial processes on example of hot rolling of flat products.

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Fontanarosa, Donato, Giacomo Cinieri, Maria Grazia De Giorgi, and Antonio Ficarella. "Effects of plasma kinetic modeling on performance characterization of plasma actuators for active flow control." E3S Web of Conferences 197 (2020): 10004. http://dx.doi.org/10.1051/e3sconf/202019710004.

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This work focuses on the development of a multiscale computational fluid dynamics (CFD) simulation framework for the investigation of the effects of plasma kinetics on the performance of a microscale dielectric barrier discharge plasma actuator (DBD-PA). To this purpose, DBD-PA multi-scale dual-step modelling approach has been implemented, by considering plasma chemistry and flow dynamic. At first, a microscopic plasma model based on the air plasma kinetics has been defined and plasma reactions have been simulated in zero-dimensional computations in order to evaluate the charge density. At this aim computations have been performed using the toolbox ZDPlasKin, which solves plasma reactions by means of Bolsig+ solver. An alternate current (AC) electrical feeding has been assumed: in particular, the sinusoidal voltage amplitude and the frequency have been fixed at 5 kV and 1 kHz at atmospheric pressure and 300 K temperature in quiescent environment. The predictal charge density has been in a macroscopic plasma-fluid model based on Suzen Dual Potential Model (DPM), which has implemented in the computation fluid dynamic CFD code OpenFoam. Hence, as second step, 2D-CFD simulations of the electro-hydrodynamic body forces induced by the microscale DBDPA have been performed, based on the previously predicted charge densities at the operating conditions. Quiescent flow over a dielectric barrier discharge actuator has been simulated using the plasma-fluid model. The novel modelling framework has been validated with experimental data.

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Ilic, Milica, Milan Petrovic, and Vladimir Stevanovic. "Boiling heat transfer modelling: A review and future prospectus." Thermal Science 23, no. 1 (2019): 87–107. http://dx.doi.org/10.2298/tsci180725249i.

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This paper reviews the current status of boiling heat transfer modelling, discusses the need for its improvement due to unresolved intriguing experimental findings and emergence of novel technical applications and outlines the directions for an advanced modelling approach. The state-of-the-art of computational boiling heat transfer studies is given for: macro-scale boiling models applied in two-fluid liquid-vapour interpenetrating media approach, micro-, meso-scale boiling computations by interface capturing methods, and nano-scale boiling simulations by molecular dynamics tools. Advantages, limitations and shortcomings of each approach, which originate from its grounding formulations, are discussed and illustrated on results obtained by the boiling model developed in our research group. Based on these issues, we stress the importance of adaptation of a multi-scale approach for development of an advanced boiling predictive methodology. A general road-map is outlined for achieving this challenging goal, which should include: improvement of existing methods for computation of boiling on different scales and development of conceptually new algorithms for linking of individual scale methods. As dramatically different time steps of integration for different boiling scales hinder the application of full multi-scale methodology on boiling problems of practical significance, we emphasise the importance of development of another algorithm for the determination of sub-domains within a macro-scale boiling region, which are relevant for conductance of small-scale simulations.

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Kuraishi, Takashi, Kenji Takizawa, and Tayfun E. Tezduyar. "Space–time Isogeometric flow analysis with built-in Reynolds-equation limit." Mathematical Models and Methods in Applied Sciences 29, no. 05 (May 2019): 871–904. http://dx.doi.org/10.1142/s0218202519410021.

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We present a space–time (ST) computational flow analysis method with built-in Reynolds-equation limit. The method enables solution of lubrication fluid dynamics problems with a computational cost comparable to that of the Reynolds-equation model for the comparable solution quality, but with the computational flexibility to go beyond the limitations of the Reynolds-equation model. The key components of the method are the ST Variational Multiscale (ST-VMS) method, ST Isogeometric Analysis (ST-IGA), and the ST Slip Interface (ST-SI) method. The VMS feature of the ST-VMS serves as a numerical stabilization method with a good track record, the moving-mesh feature of the ST framework enables high-resolution flow computation near the moving fluid–solid interfaces, and the higher-order accuracy of the ST framework strengthens both features. The ST-IGA enables more accurate representation of the solid-surface geometries and increased accuracy in the flow solution in general. With the ST-IGA, even with just one quadratic NURBS element across the gap of the lubrication fluid dynamics problem, we reach a solution quality comparable to that of the Reynolds-equation model. The ST-SI enables moving-mesh computation when the spinning solid surface is noncircular. The mesh covering the solid surface spins with it, retaining the high-resolution representation of the flow near the surface, and the SI between the spinning mesh and the rest of the mesh accurately connects the two sides of the solution. We present detailed 2D test computations to show how the method performs compared to the Reynolds-equation model, compared to finite element discretization, at different circumferential and normal mesh refinement levels, when there is an SI in the mesh, and when the no-slip boundary conditions are weakly-enforced.

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24

A Nasar, Zuhair. "Information Processing and Assessment for Improved Computational Energy Modelling." Wasit Journal of Engineering Sciences 9, no. 1 (September 22, 2021): 37–49. http://dx.doi.org/10.31185/ejuow.vol9.iss1.226.

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This study explores how designer interacts with the computational model. This research intends to demystify how “design knowledge” is obtained, used and processed in the age of computation. The paper shows how the computational modelling tools associated with performance-based parametric design help support design decisions during the initial design phases. Building Energy Performance (BEP) is chosen as the main context to develop a set of criteria for the iterative development, testing, evaluation, and validation of a prototype model. Therefore, as a practical work, the research explores a series of new energy simulation modelling techniques based on parametric design and multi optimization-based design. Specifically, it aims to explore, develop, and test new approaches in parametric modelling that can support energy simulation, using multi optimization, where designers can easily state the design parameters and use them in energy-performance-based design. The exploratory research approach is the main theme of this research. However, during the development of the research it was found that there is a need to blend this research design with the descriptive research approach. One of the key contributions of this study will be the development of a more direct link and useful methods for the translation of information into data inputs to support computational thinking and modelling processes.

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25

Martina Perez, Simon, Heba Sailem, and Ruth E. Baker. "Efficient Bayesian inference for mechanistic modelling with high-throughput data." PLOS Computational Biology 18, no. 6 (June 21, 2022): e1010191. http://dx.doi.org/10.1371/journal.pcbi.1010191.

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Bayesian methods are routinely used to combine experimental data with detailed mathematical models to obtain insights into physical phenomena. However, the computational cost of Bayesian computation with detailed models has been a notorious problem. Moreover, while high-throughput data presents opportunities to calibrate sophisticated models, comparing large amounts of data with model simulations quickly becomes computationally prohibitive. Inspired by the method of Stochastic Gradient Descent, we propose a minibatch approach to approximate Bayesian computation. Through a case study of a high-throughput imaging scratch assay experiment, we show that reliable inference can be performed at a fraction of the computational cost of a traditional Bayesian inference scheme. By applying a detailed mathematical model of single cell motility, proliferation and death to a data set of 118 gene knockdowns, we characterise functional subgroups of gene knockdowns, each displaying its own typical combination of local cell density-dependent and -independent motility and proliferation patterns. By comparing these patterns to experimental measurements of cell counts and wound closure, we find that density-dependent interactions play a crucial role in the process of wound healing.

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26

Guinot, Vincent. "Linear advection modelling: the issue of divergent flows." Journal of Hydroinformatics 2, no. 2 (March 1, 2000): 113–21. http://dx.doi.org/10.2166/hydro.2000.0009.

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Schemes for linear advection modelling in multiple dimensions on structured grids use either time-splitting or an unsplit approach for flux computation. In the case of strongly divergent flows, time-splitting introduces anisotropy in the solution whereas, with the unsplit approach, more mass than actually available may be abstracted from the computational cells, leading for instance to oscillations and sometimes instability. A simple correction for the flux, taking into account the divergence of the flow, is proposed to eliminate the problem for the unsplit approach. This correction introduces a limitation on the computational time step. An experiment carried out using a market-available software package shows that the problem above is of practical interest, and that verification procedures of modelling software should take into account simulations under non-uniform flows.

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27

Latifah, Arnida Lailatul, and Adi Nurhadiyatna. "Parallel Algorithms for Spatial Rainfall Distribution." Jurnal INKOM 8, no. 1 (December 8, 2014): 29. http://dx.doi.org/10.14203/j.inkom.383.

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This paper proposes parallel algorithms for precipitation of flood modelling, especially applied in spatial rainfall distribution. As an important input in flood modelling, spatial distribution of rainfall is always needed as a pre-conditioned model. In this paper two interpolation methods, Inverse distance weighting (IDW) and Ordinary kriging (OK) are discussed. Both are developed in parallel algorithms in order to reduce the computational time. To measure the computation efficiency, the performance of the parallel algorithms are compared to the serial algorithms for both methods. Findings indicate that: (1) the computation time of OK algorithm is up to 23% longer than IDW; (2) the computation time of OK and IDW algorithms is linearly increasing with the number of cells/ points; (3) the computation time of the parallel algorithms for both methods is exponentially decaying with the number of processors. The parallel algorithm of IDW gives a decay factor of 0.52, while OK gives 0.53; (4) The parallel algorithms perform near ideal speed-up.

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28

Redfern, Simon A. T. "Advances in computer modelling of mineral properties." Mineralogical Magazine 59, no. 397 (December 1995): 585–87. http://dx.doi.org/10.1180/minmag.1995.059.397.01.

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The following six papers were presented at a meeting, held in September 1994, which reviewed some of the recent advances in the application of computational methods to mineralogy. Talks covered the developing and challenging field of ab initio quantum mechanical computations as well as new applications and insights afforded by the use and refinement of the more established methods of empirical simulation and modelling. The former attempt to solve Schrdinger's equation for the material in question, and in doing so determine the energy surface and electronic structure. The latter use parameterized interatomic potentials to describe the energy of interaction between pairs or groups of atoms, the parameters typically derived either by fitting to the results of quantum mechanical calculations of small clusters, or empirically determined from fitting to the known physical properties of crystals (e.g. to the elastic constants, structural parameters or dielectric constants). A certain rivalry and antipathy occasionally surfaces between computational theorists from either camp.

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29

Moore, Jennifer A., David A. Steinman, and C. Ross Ethier. "Computational blood flow modelling." Journal of Biomechanics 31, no. 2 (May 1997): 179–84. http://dx.doi.org/10.1016/s0021-9290(97)00125-5.

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30

Parton, Andrew, Victoria McGilligan, Maurice O’Kane, Francina R. Baldrick, and Steven Watterson. "Computational modelling of atherosclerosis." Briefings in Bioinformatics 17, no. 4 (September 22, 2015): 562–75. http://dx.doi.org/10.1093/bib/bbv081.

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31

Brito-Parada, Pablo. "Foreword to Computational Modelling." Minerals Engineering 90 (May 2016): 1. http://dx.doi.org/10.1016/j.mineng.2016.03.024.

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32

Miller, Karol, Stuart Bunt, and Adam Wittek. "Computational modelling of hydrocephalus." Journal of Biomechanics 46, no. 14 (September 2013): 2558–59. http://dx.doi.org/10.1016/j.jbiomech.2013.07.040.

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33

de Borst, René, and Joris J. C. Remmers. "Computational modelling of delamination." Composites Science and Technology 66, no. 6 (May 2006): 713–22. http://dx.doi.org/10.1016/j.compscitech.2004.12.025.

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34

Papanastasiou, Panos. "Hydraulic fracturing: Computational modelling." Revue européenne de génie civil 10, no. 6-7 (September 28, 2006): 829–48. http://dx.doi.org/10.3166/regc.10.829-848.

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35

Li, Xiumin, Qing Chen, and Fangzheng Xue. "Biological modelling of a computational spiking neural network with neuronal avalanches." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 375, no. 2096 (May 15, 2017): 20160286. http://dx.doi.org/10.1098/rsta.2016.0286.

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In recent years, an increasing number of studies have demonstrated that networks in the brain can self-organize into a critical state where dynamics exhibit a mixture of ordered and disordered patterns. This critical branching phenomenon is termed neuronal avalanches. It has been hypothesized that the homeostatic level balanced between stability and plasticity of this critical state may be the optimal state for performing diverse neural computational tasks. However, the critical region for high performance is narrow and sensitive for spiking neural networks (SNNs). In this paper, we investigated the role of the critical state in neural computations based on liquid-state machines, a biologically plausible computational neural network model for real-time computing. The computational performance of an SNN when operating at the critical state and, in particular, with spike-timing-dependent plasticity for updating synaptic weights is investigated. The network is found to show the best computational performance when it is subjected to critical dynamic states. Moreover, the active-neuron-dominant structure refined from synaptic learning can remarkably enhance the robustness of the critical state and further improve computational accuracy. These results may have important implications in the modelling of spiking neural networks with optimal computational performance. This article is part of the themed issue ‘Mathematical methods in medicine: neuroscience, cardiology and pathology’.

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36

Stajuda, Mateusz, Damian Obidowski, Maciej Karczewski, and Krzysztof Jóźwik. "Modified Virtual Blade Method for Propeller Modelling." Mechanics and Mechanical Engineering 22, no. 2 (August 24, 2020): 603–18. http://dx.doi.org/10.2478/mme-2018-0048.

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AbstractThe emergence of large, propeller-based aircraft has revived interest in propeller design and optimization with the use of numerical methods. The flow complexity and computational time necessary to solve complicated flow patterns trailing behind rotating blades, created a need for faster than fully resolved 3D CFD, yet comparably accurate methods for validating multiple design points in shorter time. Improved Virtual Blade Method (VBM) for 2-bladed propeller, including method implementation, analysis and validation against 3D numerical and experimental data is presented. The study introduces adjustments to the original method, accounting for differences between VBM and fully resolved numerical models. These modifications prove to increase the model accuracy for the propeller under consideration and could potentially be applied for different blade configurations as well. The modified Virtual Blade Method allows one to compute the propeller performance with comparable accuracy to 3D CFD computation using only 10% of time needed for one computational point.

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37

Needleman, A. "Computational Mechanics." Applied Mechanics Reviews 38, no. 10 (October 1, 1985): 1282–83. http://dx.doi.org/10.1115/1.3143692.

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Computational methods play a key role in solid mechanics, as a way of modelling fundamental aspects of mechanical behavior, as a vehicle for transferring this improved modelling capability into new engineering tools, and as a means of utilizing these tools in engineering practice. Modern computational methods enable realistic models of mechanical systems to be formulated without regard as to whether or not analytical solutions are feasible. Increased computational capability is also an incentive for developing more accurate theories, since it becomes possible to use such theories to solve complex engineering problems.

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38

Kalinowska, M. B., and P. M. Rowiński. "Uncertainty in computations of the spread of warm water in a river – lessons from Environmental Impact Assessment." Hydrology and Earth System Sciences Discussions 9, no. 5 (May 8, 2012): 5871–904. http://dx.doi.org/10.5194/hessd-9-5871-2012.

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Abstract. The present study aims at evaluation of sources of uncertainty in modelling of heat transport in a river caused by the discharge coming from a cooling system of a designed gas-stem power plant. This study was a part of Environmental Impact Assessment and was based on two-dimensional modelling of temperature distribution in an actual river. The problems with proper description of the computational domain, velocity field and hydraulic characteristics were considered in the paper. An in-depth discussion on the methods of evaluation of dispersion coefficients in the model comprising all four components of the dispersion tensor was carried out. Numerical methods and their influence on final results of computations were also discussed. All computations were based upon a real case study performed in Vistula River in Poland.

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39

Dykas, Sławomir, Mirosław Majkut, Krystian Smołka, and Michał Strozik. "Analysis of the steam condensing flow in a linear blade cascade." Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy 232, no. 5 (November 22, 2017): 501–14. http://dx.doi.org/10.1177/0957650917743365.

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This study presents experimental and numerical testing of the steam condensing flow through a linear blade cascade made of blades of a 200 MW steam turbine last stage stator. The tests were carried out on an in-house laboratory stand and using an in-house numerical code modelling the water vapour flow with homo- and heterogeneous condensation. Additionally, this paper presents a comparison of calculations of a flow field modelled by means of a single-fluid model using both an in-house computational fluid dynamics code and the commercial Ansys CFX v16.2 software package. The aim of the research was to identify difficulties involved by comparing the numerical modelling results with the experimental data for a linear blade cascade. The experimental results, which are very well supplemented by those obtained from numerical computations, may be used to validate computational fluid dynamics codes.

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40

Annamalai, Chinnaraji. "Computation and Calculus for Combinatorial Geometric Series and Binomial Identities and Expansions." Journal of Engineering and Exact Sciences 8, no. 7 (September 22, 2022): 14648–01. http://dx.doi.org/10.18540/jcecvl8iss7pp14648-01i.

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Nowadays, the growing complexity of mathematical and computational modelling demands the simplicity of mathematical and computational equations for solving today’s scientific problems and challenges. This paper presents combinatorial geometric series, innovative binomial coefficients, combinatorial equations, binomial expansions, calculus with combinatorial geometric series, and innovative binomial theorems. Combinatorics involves integers, factorials, binomial coefficients, discrete mathematics, and theoretical computer science for finding solutions to the problems in computing and engineering science. The combinatorial geometric series with binomial expansions and its theorems refer to the methodological advances which are useful for researchers who are working in computational science. Computational science is a rapidly growing multi-and inter-disciplinary area where science, engineering, computation, mathematics, and collaboration use advance computing capabilities to understand and solve the most complex real-life problems.

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41

Lim, T. C., S. Ramakrishna, and H. M. Shang. "Deep Drawing of Plain Weft-Knitted Fabric Composites Part 2.: Strain Field Analysis." Advanced Composites Letters 9, no. 1 (January 2000): 096369350000900. http://dx.doi.org/10.1177/096369350000900106.

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Previous modelling techniques in sheet forming of textile composites have focused on computational simulations due to the numerous computations involved. Recently a procedure for stretch forming analysis of plain weft-knitted fabric composites has been developed. The analytical model for the stretch forming process is now being extended for the deep drawing process in this paper. The theoretical strain field gives good approximation to the experimental results.

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42

Pino Romero, Neisser, and Gabriel Wainer. "Modelado e implementación computacional de la propagación de las enfermedades de transmisión sexual por autómatas celulares (Cell-DEVS)." Campus 26, no. 31 (May 31, 2021): 83–98. http://dx.doi.org/10.24265/campus.2021.v26n31.07.

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43

Ahmed Hussein Hafez, Tamer Heshmat Mohamed Aly Kasem, Basman Elhadidi, and Mohamed Madbouly Abdelrahman. "Modelling Three Dimensional Unsteady Turbulent HVAC Induced Flow." Journal of Advanced Research in Fluid Mechanics and Thermal Sciences 87, no. 1 (September 7, 2021): 76–90. http://dx.doi.org/10.37934/arfmts.87.1.7690.

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A three-dimensional numerical model for HVAC induced flow is presented. The nonlinear set of buoyancy driven incompressible flow equations, augmented with those of energy and turbulence model is solved. Various relevant are discussed. These challenges include avoiding expensive commercial packages, modeling complex boundaries, and capturing near wall gradients. Adaptive time stepping is employed to optimize computational effort. Three-dimensional simulation requirements are addressed using parallel computations. Two-dimensional and three-dimensional results are presented to clarify the model significance. Validation is done using full scale measurements. Good agreement with velocity and temperature profiles are illustrated.

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44

Wellman, Michael P., John S. Breese, and Robert P. Goldman. "From knowledge bases to decision models." Knowledge Engineering Review 7, no. 1 (March 1992): 35–53. http://dx.doi.org/10.1017/s0269888900006147.

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AbstractIn recent years there has been a growing interest among AI researchers in probabilistic and decision modelling, spurred by significant advances in representation and computation with network modelling formalisms. In applying these techniques to decision support tasks, fixed network models have proven to be inadequately expressive when a broad range of situations must be handled. Hence many researchers have sought to combine the strengths of flexible knowledge representation languages with the normative status and well-understood computational properties of decision-modelling formalisms and algorithms. One approach is to encode general knowledge in an expressive language, then dynamically construct a decision model for each particular situation or problem instance. We have developed several systems adopting this approach, which illustrate a variety of interesting techniques and design issues.

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45

Gomez, Hector, Miguel Bures, and Adrian Moure. "A review on computational modelling of phase-transition problems." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 377, no. 2143 (March 4, 2019): 20180203. http://dx.doi.org/10.1098/rsta.2018.0203.

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Phase-transition problems are ubiquitous in science and engineering. They have been widely studied via theory, experiments and computations. This paper reviews the main challenges associated with computational modelling of phase-transition problems, addressing both model development and numerical discretization of the resulting equations. We focus on classical phase-transition problems, including liquid–solid, gas–liquid and solid–solid transformations. Our review has a strong emphasis on the treatment of interfacial phenomena and the phase-field method. This article is part of the theme issue ‘Heterogeneous materials: metastable and non-ergodic internal structures’.

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46

Abily, M., C. M. Duluc, J. B. Faes, and P. Gourbesville. "Performance assessment of modelling tools for high resolution runoff simulation over an industrial site." Journal of Hydroinformatics 15, no. 4 (March 20, 2013): 1296–311. http://dx.doi.org/10.2166/hydro.2013.063.

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Intense rainfall can generate storm sewer system failures along with large surface runoff events which represent an issue for industrial sites' security assessment. Numerical modelling tools, including standard bi-dimensional (2D) free surface flow models, are applied in a wide variety of flood risk practical studies straight from the purpose for which they had originally been designed. This study focuses on possibilities, performances and limits of the use of standard modelling tools for high resolution runoff simulations over an industrial site. Two categories of runoff scenarios are tested over this industrial site test case, with three modelling tools relying on different numerical schemes. Simulated water depth evolutions are found to be comparable between modelling tools, nevertheless, the possibilities of these modelling tools' optimal use with a highly refined topographical resolution for runoff scenarios are revealed to be unequal. Used indicators for computation reliability checks do not point out major inconsistencies in calculation under critical models' optimisation. Indeed, emphasis is placed on restrictive aspects to achieve with standard modelling tools a balance between computational stability, swift and precise in high resolution runoff modelling.

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47

Matusevich, Ariel E., and José A. Inaudi. "A Computational Implementation of Modal Analysis of Continuous Dynamic Systems." International Journal of Mechanical Engineering Education 33, no. 3 (July 2005): 215–34. http://dx.doi.org/10.7227/ijmee.33.3.4.

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A computational implementation of modal analysis of continuous systems is presented. Modal analysis of truss, beam and shaft structures is developed in Matlab®. A numerical and an analytical method are developed for the computation of mode shapes, natural frequencies and modal equations of continuous structures using the method of separation of variables. Time domain techniques are programmed in modular functions for structural analysis. The functions constitute a set of tools of the Structural Analysis Toolbox (SAT-Lab), developed recently for teaching modelling, analysis and design of structures and mechanical systems. Application examples of the computational tools are presented.

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48

Sanjaya, Yongky, Doni Priambodo, Prasanti Widyasih Sarli, Herlien Dwiarti Setio та Syariefatunnisa Syariefatunnisa. "Numerical Model of Wind Flow around High-Rise Buildings Using RANS Standard k-ε on OpenFOAM". MEDIA KOMUNIKASI TEKNIK SIPIL 28, № 1 (29 липня 2022): 153–60. http://dx.doi.org/10.14710/mkts.v28i1.37375.

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Amplified wind loads around buildings could induce structural failure, thus making it important to understand the behavior of fluid flow between buildings. In this study, the analysis is performed using RANS, a computational fluid dynamics (CFD) simulation with faster computation time compared to other methods. OpenFOAM, an open-source software, is used to run the simulations. This study used a structured mesh with standard RANS k − ε turbulence model. Four symmetrical buildings with a scale of 1: 420 are used as the model of this study. Numerical modelling of different computational domain size and different degrees of fineness of the meshing is simulated to determine margin of errors. The result indicates that changes in computational domain has a significant effect on CFD analysis in lowering the error value in area with high flow speed ratio (U/U0> 1) to reach the acceptable error limit. Contrastingly, changes in the degree of fineness of the meshing do not give a significant change in error value. A relatively coarse meshing with fast computation time could give a similar result as A fine meshing model with longer computation time.

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49

Baskaran, A., and T. Stathopoulos. "Prediction of wind effects on buildings using computational methods — review of the state of the art." Canadian Journal of Civil Engineering 21, no. 5 (October 1, 1994): 805–22. http://dx.doi.org/10.1139/l94-087.

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Advancements in computer software and hardware technology provide a new direction for analyzing engineering problems. Recently the field of wind engineering has gained significant momentum in the computer modelling process. This paper reviews the state of the art in computational wind engineering, including the finite element method, finite difference method, and control volume technique. A portion of this paper summarizes the research in this area carried out by the authors. Computations have been made for a variety of building configurations, including normal wind flow conditions for a building with different aspect ratios, and modelling wind environmental conditions around groups of buildings. The computer modelling technique may eventually enhance the design of buildings and structures against wind loading and supplement the current design practice of using building codes and standards or performing experiments in wind tunnels. Key words: buildings, computer modelling, pressure, velocity, wind engineering, wind tunnels.

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50

Prinz, Astrid A. "Computational approaches to neuronal network analysis." Philosophical Transactions of the Royal Society B: Biological Sciences 365, no. 1551 (August 12, 2010): 2397–405. http://dx.doi.org/10.1098/rstb.2010.0029.

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Computational modelling is an approach to neuronal network analysis that can complement experimental approaches. Construction of useful neuron and network models is often complicated by a variety of factors and unknowns, most notably the considerable variability of cellular and synaptic properties and electrical activity characteristics found even in relatively ‘simple’ networks of identifiable neurons. This chapter discusses the consequences of biological variability for network modelling and analysis, describes a way to embrace variability through ensemble modelling and summarizes recent findings obtained experimentally and through ensemble modelling.

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