Academic literature on the topic 'Sparse VAR Modelling'
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Journal articles on the topic "Sparse VAR Modelling"
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Barcia García, Camilo, and Alfredo M. Maximiano Castillejo. "Interpretar la oscuridad: cuevas, arte rupestre y análisis de luz simulada mediante escenas virtuales." Virtual Archaeology Review 6, no. 12 (October 16, 2015): 5. http://dx.doi.org/10.4995/var.2015.4146.
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Advances in digital technology have raised the capacity of capturing, processing and analyzing spatial data, bringing realistic and accurate reproductions of the elements in archaeological spaces. Current hardware and software have great potential in modelling phenomena and simulating their parameters, leading effective resources to these archaeological issues that have been hard to tackle until recent dates (intrusive techniques, heritage risk, hidden places, unavoidable impediments…). Thus, to approach contextual implications, we propose lighting simulation in aphotic sites as a procedure to study spatial relations between social agents and elements. In this paper we relate the necessary light intensity, its spatial distribution, and any derived implications for activity performing, especially in rock art production and visualization.
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Barreau, Jean-Baptiste, Elen Esnault, Jérôme Foucher, Manon Six, and Cécile Le Faou. "3D modelling of a 15th century city gate of Rennes: Portes Mordelaises." Virtual Archaeology Review 11, no. 22 (January 28, 2020): 41. http://dx.doi.org/10.4995/var.2020.12653.
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The Portes Mordelaises, remnants of the medieval city walls of Rennes, France, has been the subject of several archaeological excavations until 2017. From these excavations, we created a three-dimensional (3D) model of the site reconstructed as it would have appeared during the 15th century, including the surrounding plus the interiors of its famed towers. Once our efforts and results were officially recognised as being of national interest by the French Ministry of Culture and Communication, Department of Heritage and the National Museum Service of France, we presented our virtual model reconstruction in an exhibition curated by the Museum of Bretagne, entitled "Rennes, les vies d'une ville" (Rennes, the Lives of a City). This approach to 3D reconstruction of the site served to further study Rennes’ origins, its construction, organisation, as well as its historic relationship to surrounding territories. The main objective of this work was to investigate, using of a significant and complex archaeological site as proof of concept, how the digitalisation of an existing structure, the modelling of its hypothetical structures, and the interactions with its virtual spaces enabled the general public to provide critical feedback, and enhance archaeological knowledge and evaluation of such sites. This reconstruction was carried out under a West Digital Conservatory of Archaeological Heritage project, whose mission is to support and advise archaeologists in the production and exploration of 3D archaeological datasets using the latest digitisation, modelling, and virtual reality (VR) techniques. Through a complex but repeatable process, using the valuable data provided by various excavations, in addition to new information provided by the 3D digitalisation itself, we produced a 3D model, fully satisfactory to rigorous scientific standards, which was then incorporated into a VR space ready for diffusion to the general public. Furthermore, the fact that 45850 visitors were welcome to experience our 3D model at an exhibition in a city the size of Rennes proved to be a significant success.
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Redweik, Paula, Susana Reis, and Maria Cristina Duarte. "A digital botanical garden: using interactive 3D models for visitor experience enhancement and collection management." Virtual Archaeology Review 14, no. 28 (September 8, 2022): 65–80. http://dx.doi.org/10.4995/var.2023.17629.
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Highlights: A virtual 3D model of a botanical garden was built based on a GIS with plants botanical information and buildings, statues and other assets historical information. The height and crown diameter of individual trees were determined from watershed operations on aerial LiDAR data. Statues were modelled photogrammetrically. Buildings were modelled procedurally using CGA rules. Users found realism and information access to be the most positive points. The way of data organisation and the elaborated modelling rules make the product easily extendable for new data and objects. Abstract: Botanical gardens are important spots in urban spaces, both for researchers and for many different kinds of public. Conveying scientific information by means of an attractive digital product, on a pre- or post-visit experience, is a way of captivating the public, especially the younger generation, to the relevance of those gardens as repositories of knowledge and for conservation of plant species diversity. This approach also facilitates communication with the general public and access to historical data. On the other hand, bringing the garden to the desktop of researchers and managers can be an advantage, not only for an overview of the status quo but also in spatial planning matters. This paper describes the production of a 3D dynamic model of the Tropical Botanical Garden in Lisbon on top of a Geographic Information System (GIS). Its development included creating a spatial database to organise data originating from a variety of sources, the three-dimensional (3D) modelling of plants, buildings and statues, the creation of web pages with historic and contextual information, as well as the publication of a number of interactive 3D scenes. Several software packages were used, and the final outputs were published in ArcGIS Online to be explored by the public and researchers (link provided at the end of the text). The data are organised in a database, and most 3D modelling tasks are procedural through Computer Generated Architecture (CGA) rules. Thus, updating information or 3D models can be done without having to repeat all steps, an important feature for a dynamic botanical garden. Challenges and solutions are also addressed, providing a constructive contribution to the further implementation of similar experiences in other botanical gardens. According to a user survey carried out, the realism of the representation and the possibility of easily retrieving information from the objects are the most positive aspects of the project.
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Banfi, Fabrizio, Raffaella Brumana, Angelo Giuseppe Landi, Mattia Previtali, Fabio Roncoroni, and Chiara Stanga. "Building archaeology informative modelling turned into 3D volume stratigraphy and extended reality time-lapse communication." Virtual Archaeology Review 13, no. 26 (January 21, 2022): 1–21. http://dx.doi.org/10.4995/var.2022.15313.
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This paper describes the case study of the damaged church of St. Francesco in the hamlet of Arquata del Tronto (Italy) that was struck by the earthquake in 2016. The municipality commissioned the research to support the preliminary design of the preservation plan. The first digitisation level has been started from the richness of surveying data acquired from static and dynamic terrestrial laser scanning (TLS), and photogrammetry, overcoming challenging constraints due to the scaffolding covering the surfaces. The geometric survey allowed authors to acquire massively geometric and material information supporting the three-dimensional (3D) volume stratigraphic and the creation of the Heritage Building Information Modelling (HBIM). The paper proposes a shift from the Geographic Information System (GIS)-based analysis of the materials toward spatial HBIM management. Building Archaeology is turned into HBIM 3D volume stratigraphy, overcoming the bidimensional (2D) surface mapping, in favour of a 3D understanding of direct and indirect sources. Material mapping is added to HBIM 3D volume stratigraphy, and each stratigraphic unit (SU) has its proprieties. The 3D volume stratigraphic database has been designed to collect the data on the unit detection at three levels (direct sources data collection, indirect data documentation, the relation among the BIM object elements). A common data environment (CDE) has been set up to share the 3D volume informative models that can be accessed, and all the information gathered. The knowledge transfer using the eXtended reality (XR) has been devoted to the citizen and tourist fruition, enhancing the comprehension of difficult concepts like the SUs to support a better critical 3D reconstruction. It includes the phases of construction across time-lapse documentation that validates related information within the building archaeology informative models leaving spaces to the uncertainty and documenting the relationship established so far thanks to the direct and indirect sources. The result obtained is a live digital twin that can be continuously updated, which justifies the costs and time demanding of HBIM despite 2D drawings.Highlights: • 3D survey and scan-to-HBIM process for the creation of a digital twin were oriented to the preliminary design of the preservation plan of the church of St. Francesco in Arquata del Tronto (Italy). • Stratigraphy is investigated and oriented towards a digitisation process to share different levels of knowledge through new forms of digital-sharing such as Common Data Environment (CDE) and cloud-based BIM platform. • eXtended reality (XR) is the final tool to reach new levels of communication and a wider audience characterised by experts in the construction sector and virtual and non-expert tourists.
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Yoshii, Kentaro, Manabu Igarashi, Osamu Ichii, Kana Yokozawa, Kimihito Ito, Hiroaki Kariwa, and Ikuo Takashima. "A conserved region in the prM protein is a critical determinant in the assembly of flavivirus particles." Journal of General Virology 93, no. 1 (January 1, 2012): 27–38. http://dx.doi.org/10.1099/vir.0.035964-0.
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Flaviviruses are assembled to bud into the lumen of the endoplasmic reticulum (ER) and are secreted through the vesicle transport pathway, but the details of the molecular mechanism of virion assembly remain largely unknown. In this study, a highly conserved region in the prM protein was identified among flaviviruses. In the subviral particle (SP) system of tick-borne encephalitis virus (TBEV) and Japanese encephalitis virus, secretion of SPs was impaired by a mutation in the conserved region in the prM protein. Viral proteins were sparse in the Golgi complex and accumulated in the ER. Ultrastructural analysis revealed that long filamentous structures, rather than spherical SPs, were observed in the lumen of the ER as a result of the mutation. The production of infectious virions derived from infectious cDNA of TBEV was also reduced by mutations in the conserved region. Molecular modelling analysis suggested that the conserved region is important for the association of prM–envelope protein heterodimers in the formation of a spike of immature virion. These results are the first demonstration that the conserved region in the prM protein is a molecular determinant for the flavivirus assembly process.
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Sbrogiò, Luca. "Parametric approach to the reconstruction of timber structures in Campanian Roman houses." Virtual Archaeology Review 13, no. 26 (January 21, 2022): 45–61. http://dx.doi.org/10.4995/var.2022.15319.
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The virtual reconstruction of ancient architecture aims at describing the ‘original’ elevation and volume of a disappeared building. The feeble archaeological traces, often limited to their foundations, left by houses impair the reinstating of their image, in contrast to that which is made possible by the massive structures of public buildings. A twofold problem arises when dealing with timber structures during a reconstruction procedure: at the local scale of the individual beam (e.g. joists or rafters), one must define a beam’s cross-section given its span; at the overall scale, the shape of a building results from that which its structures allowed it to have been. Therefore, this work proposes a procedure to deal with the ‘local’ problem, i.e. the definition of a beam’s cross-section from its span. To that end, a simplified, parametric structural model is required. The available bits of information are organized into inputs, parameters and outputs of the analytical problem by matching each information with a structural quantity (load, cross-section, spacing, etc.). Two mathematical relationships among them are proposed, which express two equally possible dimensioning criteria, based either on joists’ strength or deformability. It seems that the joist’s strength was the option for lightly loaded joists, as in roofs or tightly spaced floor frames; conversely, heavily loaded joists conformed to the deformability criterion. Both dimensioning procedures are translated into a visual algorithm in Grasshopper, a plugin for Rhinoceros modelling software, which enables the parametric definition of objects. Finally, the proposed procedure is tentatively applied to automatically reconstruct the floor and roof frames that belonged to the domus on top of the Sarno Baths in Pompeii. The algorithm automatically picked the dimensioning criterion in relation to each frame’s span and hypothesized loads and determined joists’ orientation and minimum cross-sections. The obtained floor frames, whose structural conditions are considered as sensible, will be adopted in the overall virtual reconstruction proposal of the ruins, also based on the analytical evaluation of masonry structures.Highlights:- Proposal of a structural model for the dimensioning of timber floor beams in domestic spaces based on archaeological and literature information.- Parametrical interpretation of the model in Grasshopper for Rhinoceros software and optimization analysis of the structural parameters involved.- Application of the model to the reconstruction of floor frames in a house in the Sarno Baths complex, Pompeii.
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HASPOT, BORIS. "CAUCHY PROBLEM FOR VISCOUS SHALLOW WATER EQUATIONS WITH A TERM OF CAPILLARITY." Mathematical Models and Methods in Applied Sciences 20, no. 07 (July 2010): 1049–87. http://dx.doi.org/10.1142/s0218202510004532.
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In this paper, we consider the compressible Navier–Stokes equation with density-dependent viscosity coefficients and a term of capillarity introduced formally by van der Waals in Ref. 51. This model includes at the same time the barotropic Navier–Stokes equations with variable viscosity coefficients, shallow-water system and the model introduced by Rohde in Ref. 46. We first study the well-posedness of the model in critical regularity spaces with respect to the scaling of the associated equations. In a functional setting as close as possible to the physical energy spaces, we prove global existence of solutions close to a stable equilibrium, and local in time existence of solutions with general initial data. Uniqueness is also obtained.
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Juglea, S., Y. Kerr, A. Mialon, E. Lopez-Baeza, D. Braithwaite, and K. Hsu. "Evaluation of PERSIANN database in the framework of SMOS Calibration/Validation activities over Valencia Anchor Station." Hydrology and Earth System Sciences Discussions 7, no. 1 (February 11, 2010): 1143–66. http://dx.doi.org/10.5194/hessd-7-1143-2010.
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Abstract. Soil moisture is a key parameter for land surface water resource and climate change monitoring. ESA's Soil Moisture and Ocean Salinity (SMOS) mission will deliver, as one of its main goals, global fields of surface soil moisture with an accuracy better than 0.04 m3 m−3. SMOS relies on an L-band (1.4 GHz) interferometric radiometer. Within the context of the preparation for this mission over land, the Valencia Anchor Station (VAS) experimental site, in Spain, was selected to be one of the main test sites in Europe for the SMOS Calibration/Validation (Cal/Val) activities. This study presents preliminary analysis of PERSIANN in the framework of SMOS Cal/Val activities at the Valencia Anchor Station. The PERSIANN database is an automated system for Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks. The real interest of using the PERSIANN database into the hydrologic applications is mainly with the goal of having access to the spatial and temporal distribution of precipitation over a significant area (typically here an area equivalent to a SMOS pixel). The goal of this study is to quantify the gain of using PERSIANN instead of distributing sparse rain gauge measurements. The interest of using satellite rainfall estimates as well as the influence that the precipitation events can induce on the modelling of the water content in the soil was depicted by a comparison between different soil moisture products. Having an accurate estimation of the amount and temporal/spatial distribution of precipitation is a critical issue so as to have a faithful representation of the soil moisture distribution.
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Lau, Jun Yan, and James Binney. "Modes of a stellar system I: Ergodic systems." Monthly Notices of the Royal Astronomical Society 507, no. 2 (August 2, 2021): 2241–52. http://dx.doi.org/10.1093/mnras/stab2227.
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ABSTRACT The excursions of star clusters and galaxies around statistical equilibria are studied. For a stable ergodic model Antonov’s Hermitian operator on six-dimensional phase space has the normal modes as its eigenfunctions. The excitation energy of the system is just the sum of the (positive) energies associated with each normal mode. Formulae are given for the DFs of modes, which are of the type first described by van Kampen rather than Landau, and Landau ‘modes’ can be expressed as sums of van Kampen modes. Each van Kampen mode comprises the response of non-resonant stars to driving by the gravitational field of stars on a group of resonant tori, so its structure is sensitive to the degree of self gravity. The emergence of global distortions in N-body models when particles are started from an analytical equilibrium is explained in terms of the interplay of normal modes. The positivity of modal energies opens the way to modelling the thermal properties of clusters in close analogy with those of crystals.
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Wei, Xuebin, and Xiaobai Yao. "3D Model Construction in an Urban Environment from Sparse LiDAR Points and Aerial Photos—a Statistical Approach." GEOMATICA 69, no. 3 (September 2015): 271–84. http://dx.doi.org/10.5623/cig2015-302.
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Light Detection and Ranging (LiDAR) has become an important data source in urban modelling. Traditional methods of LiDAR data processing for building detection require high spatial resolution data and sophisticated algorithms. The aerial photos, on the other hand, provide continuous spectral information on buildings. However, the accuracy of classified building boundaries from aerial photos is constrained when building roofs and their surroundings share analogous spectral characteristics. This paper develops a statistical approach that can integrate characteristic variables derived from sparse LiDAR points and air photos to detect buildings by estimating object heights and identifying clusters of similar heights. Within this study, the approach chooses a local regression method, namely geographically-weighted regression (GWR), to account for local variations of building surface height. In the GWR model, LiDAR data provide the height information of spatial objects, which is the dependent variable, while the brightness values from visible bands of the aerial photo serve as the independent variables. The established GWR model estimates the height at each pixel based on height values of its surrounding pixels with consideration of the distances between the pixels as well as similarities between their brightness values in visible bands. Clusters of contiguous pixels with higher estimated height val ues distinguish themselves from surrounding roads or other surfaces. A case study is conducted to evaluate the performance of the proposed method. It is found that the accuracy of the proposed statistical method is better than those by image classification of aerial photos alone or by building extraction of LiDAR data alone. The results demonstrate that this simple and effective method can be very useful for automatic detection of buildings in urban areas. The approach can be most helpful for studies of urban areas where more suitable but expensive high resolution data are not available.
Dissertations / Theses on the topic "Sparse VAR Modelling"
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Mody, Sandeep K. "Computation of Sparse Representations of High Dimensional Time Series Data and Experimental Applications." Thesis, 2017. http://etd.iisc.ac.in/handle/2005/4295.
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Obtaining a sparse representation of high dimensional data is often the first step
towards its further analysis. Conventional Vector Autoregressive (VAR) modelling
methods applied to such data results in noisy, non-sparse solutions with a too many
spurious Coefficients. Computing auxiliary quantities such as the Power Spectrum,
Coherence and Granger causality (GC) from such non-sparse models is slow and
gives wrong results. Thresholding the distorted values of these quantities as per
some criterion, statistical or otherwise, does not alleviate the problem.
We propose two sparse Vector Autoregressive (VAR) modelling methods that work
well for high dimensional time series data, even when the number of time points
is relatively low, by incorporating only statistically significant Coefficients. In numerical
experiments using simulated data, our methods show consistently higher
accuracy compared to other contemporary methods in recovering the true sparse
model. The relative absence of spurious Coefficients in our models permits more
accurate, stable and efficient evaluation of auxiliary quantities. Our VAR modelling
methods are capable of computing Conditional Granger causality (CGC) in
datasets consisting of tens of thousands of variables with a speed and accuracy that
far exceeds the capabilities of existing methods.
Using the Conditional Granger causality computed from our models as a proxy for
the weight of the edges in a network, we use community detection algorithms to
simultaneously obtain both local and global functional connectivity patterns and
community structures in large networks.
We also use our VAR modelling methods to predict time delays in many-variable
systems. Using simulated data from non-linear delay differential equations, we compare
our methods with commonly used delay prediction techniques and show that
our methods yield more accurate results.
We apply the above methods to the following real experimental data:
1. Analysis of data from the Human Connectome Project (HCP): fMRI data from
the HCP database is used to compute sparse brain functional connectivity networks.
The network and community structures obtained are consistent over independent
recording sessions and show good spatial correspondence with known
functional and anatomical regions of the brain.
2. Analysis of ADHD-200 data: fMRI data from children with ADHD (Attention
Deficit Hyperactive Disorder) is used to compute sparse brain functional connectivity
networks. Analysis of the network measures obtained provide new ways of differentiating between ADHD and typically developing children using global and node-level network measures. They also enable refinement of
published results relating to the rFIC-ACC interaction in fMRI resting state
data.
3. Time-delay prediction from LFP recordings: When applied to Local Field Potential
(LFP) recordings from the rat and monkey, our methods predict consistent
delays across a range of sampling frequencies.
4. Application to the Hela gene interaction dataset: The network obtained by applying
our methods to this dataset yields results that are at least as good as
those from a specialized method for analyzing gene interaction. This demonstrates
that our methods can be applied to any time series data for which VAR
modelling is valid.
In addition to the above methods, we apply non-parametric Granger causality analysis
(originally developed by A. Nedungadi, G. Rangarajan et al) to mixed point process
and local field potential data. Extending the computations to Conditional
GC and by increasing the efficiency of the original algorithm, we can compute the
Conditional GC spectrum in systems consisting of hundreds of variables in a relatively
short period. Further, combining this with VAR modelling provides an alternate
faster route to compute the significance level of each element of the GC and
CGC matrices. We use these techniques to analyze mixed spike train and LFP data
from monkey electrocorticography (ECoG) recordings during a behavioral task. A
preliminary interpretation of the results of the analysis is provided.
Book chapters on the topic "Sparse VAR Modelling"
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Verma, Gyanendra K. "Multimodal Fusion Framework and Multiresolution Analysis." In Multimodal Affective Computing: Affective Information Representation, Modelling, and Analysis, 59–74. BENTHAM SCIENCE PUBLISHERS, 2023. http://dx.doi.org/10.2174/9789815124453123010009.
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This chapter presents a multi-modal fusion framework for emotion recognition using multiresolution analysis. The proposed framework consists of three significant steps: (1) feature extraction and selection, (2) feature level fusion, and (3) mapping of emotions in three-dimensional VAD space. The proposed framework considers subject-independent features that can incorporate many more emotions. It is possible to handle many channel features, especially synchronous EEG channels and feature-level fusion works. This framework of representing emotions in 3D space can be extended for mapping emotion in three-dimensional spaces with three specific coordinates for a particular emotion. In addition to the fusion framework, we have explained multiresolution approaches, such as wavelet and curvelet transform, to classify and predict emotions.
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Cocco, Simona, Rémi Monasson, and Francesco Zamponi. "Unsupervised learning: from representations to generative models." In From Statistical Physics to Data-Driven Modelling, 107–36. Oxford University PressOxford, 2022. http://dx.doi.org/10.1093/oso/9780198864745.003.0006.
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Abstract Unsupervised learning is the task of inferring the statistical structure common to a set of data. Unveiling this structure may be helpful for multiple purposes, such as interpreting the defining characteristics of the data, allowing for further processing, or even generating new data items. We have already encountered methods for unsupervised learning in the previous chapters. An example is that of Boltzmann machine learning of a probability distribution, which can then be sampled to produce new data. If the learning is good, the generated data should be statistically indistinguishable from the training data. The principal component analysis (PCA) method discussed in chapter 3 is another example, in which one learns some features of the data (the directions in the data space along which data vary the most) that can be used to represent them. The field of unsupervised learning is particularly vast. In this chapter we will only discuss a few examples, in particular autoencoders, restricted Boltzmann machines, and a revisited version of PCA. The emphasis will be put on two major goals of unsupervised learning, that is, the production of adequate representations of the data, and the generative character of the models. Applications to the design of new proteins from sequence-based models will be presented.
Conference papers on the topic "Sparse VAR Modelling"
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Fedotov, A. A., and R. V. Baluev. "Search for deviations in exoplanetary infrared profiles, based on the secondary eclipse analysis." In ASTRONOMY AT THE EPOCH OF MULTIMESSENGER STUDIES. Proceedings of the VAK-2021 conference, Aug 23–28, 2021. Crossref, 2022. http://dx.doi.org/10.51194/vak2021.2022.1.1.080.
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Aperture photometry of Spitzer space telescope observations of HD209458 b in the 3.6µm channel was conducted. Tofind deviations in the exoplanetary infrared emission, the modelling of secondary eclipse light curves was carried out. Thenoise from intrapixel sensitivity variations was modelled by Gaussian processes. The obtained value of the eclipse depth is0.094±0.013% of the total flux of the system and is consistent with the results of previous work and the works of otherauthors.
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Martin, Blake, and Armaghan Salehian. "Vibration Modelling of String-Harnessed Beam Structures Using Homogenization Techniques." In ASME 2014 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/imece2014-37039.
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Harnessing structural elements with strings, power cables, and signal cables increases the complexity in modelling the dynamic behaviour of such structures. Developing models capable of accurately predicting the dynamic behaviour of these systems is of great importance for space structures that cannot be tested prior to launch. The focus of this work is obtaining an equivalent continuum model for string-harnessed beam-like structures with periodic wrapping patterns. The tension in the string is assumed to vary as the beam deflects. The displacement field with second-order terms is determined and from which the Green-Lagrange strain tensor is obtained. After finding kinetic and potential energy expressions Hamilton’s principle is used to obtain the partial differential equation and boundary conditions. Numerical results for the shift in the natural frequencies are presented for various string properties to investigate their effects on the structure.
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Antokhina, E., I. Antokhin, G. Lenoir-Craig, N. St-Louis, and A. Moffat. "Light-curve modelling in a Roche plus stellar wind model: the massive binary WR22." In ASTRONOMY AT THE EPOCH OF MULTIMESSENGER STUDIES. Proceedings of the VAK-2021 conference, Aug 23–28, 2021. Crossref, 2022. http://dx.doi.org/10.51194/vak2021.2022.1.1.034.
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A code for the synthesis of light curves of close binaries in the Roche model is proposed which incorporates a stellarwind around one of the stars. The code makes it possible to analyze observations of binary systems containing Wolf-Rayetstars. This paper presents the results of the application of this code to the spectroscopic binary WR22, whose componentsare stars of spectral types WN7h and O9III-V (P = 80.336 d , e ∼ 0.6). The light curves were obtained with one of theBRITE-Constellation space-based telescopes. Two solutions to the problem were found, corresponding to two possibleluminosity classes of the O star, O9III and O9V. For each solution, the orbital inclination, the masses of the components,the temperature of the WR star, the WR mass-loss rate, and other parameters were determined. The resulting stellarparameters favour the solution for the WN7h+O9V model
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Shishaev, Gleb, Vasily Demyanov, Daniel Arnold, and Roman Vygon. "History Matching and Uncertainty Quantification of Reservoir Performance with Generative Deep Learning and Graph Convolutions." In International Petroleum Technology Conference. IPTC, 2022. http://dx.doi.org/10.2523/iptc-22167-ms.
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Abstract Generative deep learning is becoming a widely used approach in geological modelling, especially in problems that involve optimization processes under uncertainty like history matching. The basic idea of reservoir modelling and history matching by generative deep learning is to train some kind of reservoir generator and provide optimization under different constraints. There are different approaches that have been developed to utilize various modifications of Generative Adversarial Networks or Variational Autoencoders to implement reservoir generators, but most of them have "conventional" convolution neural networks, hence all data have to be regular (rectangular) in structure. This should be recognized as a limitation. In this work, we introduce a novel approach of reservoir modelling with Variational Autoencoders based on graph convolutions as opposed to "conventional" convolutions. In our approach reservoir model is considered as a graph, i.e., not a structured data type. Graph convolutions can deal with these data types, and connection with Variational Autoencoders provides us with the capability to generate initially unstructured reservoirs. Variational Autoencoders (VAE) demonstrate the ability to implicitly parameterize geological representations into a latent space of reduced dimensionality and provide ways to uncertainty quantification and production profiling among various geological concepts. In the first part, we introduce the motivation to Graph Variational Autoencoders (GVAE) as opposed to conventional Generative Deep learning models. The rest of the paper is dedicated to experiments on a synthetic dataset with two different geological scenarios. We show that trained GVAE performs the generation of reservoir models with reliable geology. A latent space structure between Encoder and Decoder of GVAE is represented, and interpretation considering geology under investigation is performed. Finally, we show how latent space can help to estimate the uncertainty of production and an optimization workflow under well data constraints.
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ALIX, Guillaume, and Alessio DULBECCO. "On the integration of a K-k turbulence approach to improve CFM1D combustion modelling in modern Spark Ignition engines." In FISITA World Congress 2021. FISITA, 2021. http://dx.doi.org/10.46720/f2021-caf-031.
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Reducing vehicle fuel consumption while respecting pollutants emission standards has been a major concern over the last decades in the automotive industry. Consequently, Spark Ignition (SI) engine air-paths can now incorporate devices such as Exhaust Gas Recirculation (EGR), Variable Valve Timing (VVT) or Actuation (VVA), Variable Geometry Turbocharger (VGT) or even Variable Compression Ratio (VCR). Optimizing the settings for all these devices made engine development more complex and challenging. The development of engine control strategy can be efficiently performed through system simulation with a complete engine simulator, as it allows describing the phenomenological process occurring in the engine while requiring reasonable quantity of measurement data. CPU time is also a constraint, therefore 0-dimensional models are commonly used, particularly to represent in-cylinder combustion process. Still, the combustion model has to account for the influence of air-path settings, as they strongly impact turbulence in chamber and the resulting combustion speed. This paper focuses on the system simulation version of the Coherent Flame Model (CFM1D), more precisely on its development to make it more predictive to different air path settings variations. Based on previous work, the equations of a K-k family turbulence model are introduced to replace the simplified turbulence model, on which CFM1D lies during closed valve operation to determine the increase of the flame front speed compared to laminar case. In the same time, the initialisation of turbulence variable at the intake valve closure (IVC) is modified to better take into account VVT effects. Additionally, an optional equation accounting for the physical description of the laminar to turbulent transition is proposed and discussed, allowing to further simplify the calibration process. The improved model is calibrated to fit measurements on reference engine operating points, and played on different settings including variations on spark advance VVT, VVA, VCR and EGR. The achieved results bring out the advantage of the new approach in terms model sensitivity and robustness, while pointing out further areas of improvement.
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Hawi, Meshack, Mahmoud Ahmed, and Shinichi Ookawara. "Modelling and Simulation of Homogeneous Charge Compression Ignition Engine Fueled by Biodiesel." In ASME 2018 Power Conference collocated with the ASME 2018 12th International Conference on Energy Sustainability and the ASME 2018 Nuclear Forum. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/power2018-7202.
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Homogeneous charge compression ignition (HCCI) is a combustion technology which has received increased attention of researchers in the combustion field for its potential in achieving low oxides of nitrogen (NOx) and soot emission in internal combustion (IC) engines. HCCI engines have advantages of higher thermal efficiency and reduced emissions in comparison to conventional internal combustion engines. In HCCI engines, ignition is controlled by the chemical kinetics, which leads to significant variation in ignition time with changes in the operating conditions. This variation limits the practical range of operation of the engine. Additionally, since HCCI engine operation combines the operating principles of both spark ignition (SI) and compression ignition (CI) engines, HCCI engine parameters such as compression ratio and injection timing may vary significantly depending on operating conditions, including the type of fuel used. As such, considerable research efforts have been focused on establishing optimal conditions for HCCI operation with both conventional and alternative fuels. In this study, numerical simulation is used to investigate the effect of compression ratio on combustion and emission characteristics of an HCCI engine fueled by pure biodiesel. Using a zero-dimensional (0-D) reactor model and a detailed reaction mechanism for biodiesel, the influence of compression ratio on the combustion and emission characteristics are studied in Chemkin-Pro. Simulation results are validated with available experimental data in terms of incylinder pressure and heat release rate to demonstrate the accuracy of the simulation model in predicting the performance of the actual engine. Analysis shows that an increase in compression ratio leads to advanced and higher peak incylinder pressure. The results also reveal that an increase in compression ratio produces advanced ignition and increased heat release rates for biodiesel combustion. Emission of NOx is observed to increase with increase in compression ratio while the effect of compression ratio on emissions of CO, CO2 and unburned hydrocarbon (UHC) is only marginal.
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Zanganeh, Hossein, and Narakorn Srinil. "Coupled Axial/Lateral VIV of Marine Risers in Sheared Currents." In ASME 2015 34th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/omae2015-41606.
Full textAbstract:
Modelling and prediction of vortex-induced vibrations (VIV) of marine risers is a challenging task due to the associated multi degrees of freedom in both cross-flow/in-line directions and the multi-mode fluid-structure interactions. In addition, the axial motion and its geometrically nonlinear coupling with lateral responses can be significant, especially at higher-order modes. Nevertheless, several papers in the literature dealing with VIV predictions have often overlooked such aspects. Therefore, this study aims to investigate and understand the effect of axial or longitudinal motion through a theoretical model and numerical approach in time domain. Attention is paid to VIV of vertical risers subjected to linearly sheared currents. To capture a three-dimensional aspect of the flexible cylinder experiencing VIV, a semi-empirical model is developed consisting of nonlinear equations of cross-flow, in-line and axial structural oscillations which are coupled with the distributed van der Pol-type wake-oscillators modelling the fluctuating fluid lift/drag forces. The mean drag force is also taken into account. These model equations are numerically solved via a space-time finite difference scheme, and the obtained numerical results highlight several aspects of VIV of elastic cylinders along with the axial motion effects. Apart from the validation of the numerical model with published experimental results, this study reveals how the effect of axial motion and its nonlinear coupling with the two lateral cross-flow/in-line motions can be very important. These depend on the flow velocity, the fluid-structure parameters, the single or multi-mode lock-in condition, and the standing-wave or travelling-wave feature. We recommend that the axial response should be accounted for in VIV analysis and prediction model.
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Marshall, Stephen, and Yuerong Zhang. "Towards a ‘fractal’ typomorphology: integrating concepts of type, form and dimension." In 24th ISUF 2017 - City and Territory in the Globalization Age. Valencia: Universitat Politècnica València, 2017. http://dx.doi.org/10.4995/isuf2017.2017.6151.
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While the urban fabric has both three and two dimensional aspects, we rarely if ever experience urban form as a fully three-dimensional object nor as a two-dimensional ground plan. Rather, the urban fabric is experienced more in terms of places with a fractal dimension lying between two and three. Hence we can (re)interpret urban form elements from colonnades to streets as ‘fractal’ types. This in turn suggests the possibility for a ‘fractal’ typo-morphology, addressing elements that occupy a typological space ‘in between’ 3D architectural modelling and 2D urban plan analysis. While Moudon could note that aspects of type were ‘vague and flawed with ambiguity’ (1994), it seems that there is still room for clarity; Dovey’s recent review of type (2016) invites further development and integration of the concept of type what may still be a disparate and ambiguous territory. Meanwhile, fractal approaches to morphology have been traditionally more concerned with larger scale urban patterns (e.g. Frankhauser, 2004) or measurement of architectural elements (e.g. Ostwald et al, 2015) with a fractal dimension less than two. This paper explores the possibilities for establishing a ‘fractal typo-morphology’ that recognises the ‘2.x’ dimensional aspect of the urban fabric and its component types. The paper generates a solution-space of types, illustrated with empirical examples, and organizes these into a typology for onward use, so that ideas of type, form and fractal dimension can contribute more fully as ‘conceptual tools’ both for understanding the urban fabric and for use as building blocks for urban design. References (100 words) Dovey, K. (2016) Urban Design Thinking. London: Bloomsbury Academic. Moudon, A. V. (1994) Getting to know the built landscape: typomorphology, in Franck, K. A and H. Schneekloth (eds) Ordering Space: Types in Architecture and Design. New York: VNR. Frankhauser, P. (2004) Comparing the morphology of urban patterns in Europe – a fractal approach, in Borsdorf, A. and Zembri, P. (eds) European Cities – Insights on outskirts. Brussels: COST. Ostwald, M., Vaughan, J. and Tucker, C. (2015) Characteristic visual complexity: Fractal dimensions in the architecture of Frank Lloyd wright and Le Corbusier, in Williams, K. and Ostwald, M. (eds) Architecture and Mathematics from Antiquity to the Future. Switzerland: Springer.