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33rd CIRP Design Conference

作者： Zhou, Shiyang Meierhofer, Alexander Kugu, Ozan Xia, Yuxi Grafinger, Manfred TU Wien Institute of Engineering Design and Product Development Lehargasse 6/307 Vienna1060 Austria Virtual Vehicle Research GmbH Co-Simulation and Software Group Inffeldgasse 21a Graz8010 Austria University of Vienna Faculty of Computer Science Kolingasse 14-16 Vienna1090 Austria

A holistic railway infrastructure digital twin (DT) platform is sophisticated and consists of a series of submodels (e.g., turnouts, tracks, vehicles, etc.) that are built through various methodologies and software. However, integrating these submodels into the DT platform is tremendously challenging due to considerable computational complexity, software and interface restrictions. To this end, we designed a machine learning (ML) based surrogate modeling methodology for the submodel integration in the holistic railway infrastructure DT platform and illustrated the methodology through a case study. In this case study, an ML-based surrogate model for multibody simulation of railway vehicle-track dynamics is created, which can replace the railway vehicle-track simulation executed with the Multibody Dynamics (MBD) simulation commercial software SimPACK. The well-built ML model can accurately and quickly predict the vehicle-track system's dynamic responses to different track irregularities. Besides, the integration process of the ML-based surrogate model into the DT platform through a standardized open-source Functional Mock-up Interface (FMI) is also proposed. The developed surrogate modeling methodology shows great promise owing to its high fidelity, which is verified by the measurement data collected from the Austrian national railway track system. The main contribution of our work lies in the well-built ML-based surrogate modeling methodology for reducing the computation complexity and time of different submodels, which facilitates the unification and integration of different submodels. Furthermore, this approach can also be applied to other submodels and help to build the holistic railway DT platform collaboratively. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： Machine learning

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Thermal simulation of microwave kiln based on multiphysics

Thermal simulation of microwave kiln based on multiphysics

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International Technical Conference o Circuits/Systems, computers and Communications (ITC-CSCC)

作者： Thodsaphon Jansaengsuk Sorathon Pattanapichai Piyawong Poopanya Nonthawat Phimphakan Jatuporn Thongsri Computer Simulation in Engineering Research Group College of Advanced Manufacturing Innovation King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Program of Physics Faculty of Science Ubon Ratchathani Rajabhat University Ubonratchatani Thailand

A microwave kiln, made of silicon carbide and ceramic fiber, commonly employs in a household glassware production process. In this process, when the kiln was in a microwave oven, a microwave transmitted to the kiln generating a high temperature to fuse the glass inside. This article presents a thermal simulation to investigate the temperature inside the kiln based on multiphysics consisting of a high-frequency structure simulator (HFSS) and computational fluid dynamics (CFD). The multiphysics results revealed the temperature inside the kiln in a transient state, consistent with the experimental results. As expected, the temperature increased with the increasing time of the process. Significantly, the silicon carbide had higher temperatures than the ceramic fiber; therefore, silicon carbide is a crucial material for generating heat inside the kiln. In addition, the temperature-increasing rate (TIR) inside the kiln depended on the kiln's thickness (Th). As a result, the thinner Th provided better TIR. The research findings can be applied to develop a high-efficacy household glassware production process.

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Chances and Challenges of ChatGPT and Similar Models for Education in M&S

Chances and Challenges of ChatGPT and Similar Models for Edu...

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2023 Winter simulation Conference, WSC 2023

作者： Tolk, Andreas Barry, Philip Loper, Margaret L. Rabadi, Ghaith Scherer, William T. Yilmaz, Levent The Mitre Corporation Modeling and Analysis Innovation Center 1001 Research Park Blvd #200 CharlottesvilleVA22911 United States L3Harris Corporation Mission Analysis Group 2235 Monroe Street HerndonVA20171 United States Georgia Tech Research Institute Georgia Institute of Technology AtlantaGA30308 United States University of Central Florida School of Modeling Simulation and Training 3100 Technology Pkwy OrlandoFL32826 United States University of Virgina Department of Systems and Information Engineering CharlottesvilleVA22904 United States Auburn University Samuel Ginn College of Engineering Computer Science and Software Engineering AuburnAL36849 United States

ISBN: (纸本)9798350369663

This position paper summarizes the inputs of a group of experts from academia and industry presenting their view on chances and challenges of using ChatGPT within Modeling and simulation education. The experts also address the need to evaluate continuous education as well as education of faculty members to address scholastic challenges and opportunities while meeting the expectation of industry. Generally, the use of ChatGPT is encouraged, but it needs to be embedded into an updated curriculum with more emphasis on validity constraints, systems thinking, and ethics. © 2023 IEEE.

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Self-Attention Based Vision Processing for Prosthetic Vision

Self-Attention Based Vision Processing for Prosthetic Vision

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Jack White Jaime Ruiz-Serra Stephen Petrie Tatiana Kameneva Chris McCarthy School of Science Computing and Engineering Technologies Swinburne University of Technology Melbourne VIC Australia Modelling and Simulation Research Group School of Computer Science The University of Sydney Sydney NSW Australia Centre for Transformative Innovation Swinburne University of Technology Melbourne VIC Australia Department of Biomedical Engineering University of Melbourne Melbourne VIC Australia

We investigate Self-Attention (SA) networks for directly learning visual representations for prosthetic vision. Specifically, we explore how the SA mechanism can be leveraged to produce task-specific scene representations for prosthetic vision, overcoming the need for explicit hand-selection of learnt features and post-processing. Further, we demonstrate how the mapping of importance to image regions can serve as an explainability tool to analyse the learnt vision processing behaviour, providing enhanced validation and interpretation capability than current learning-based methods for prosthetic vision. We investigate our approach in the context of an orientation and mobility (OM) task, and demonstrate its feasibility for learning vision processing pipelines for prosthetic vision.

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Spectroscopic Study, Hirshfeld Surface, DFT, In-Silico Molecular Docking and ADMET Studies of 2,6-Bis(4-Chlorophenyl)-3,3-Dimethylpiperidin-4-One (BCDP): a Potent Antiviral Agent

SSRN

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SSRN 2023年

作者： Ramalingam, Arulraj Sambandam, Sivakumar Louis, Hitler Imojara, Anna Mathias, Gideon E. Department of Electrical and Computer Engineering National University of Singapore 117 583 Singapore Research and Development Centre Bharathiar University Tamil Nadu Coimbatore641 046 India BPJ College of Arts and Science Kozhai Srimushnam Tamil Nadu Cuddalore608703 India Computational and Bio-Simulation Research Group University of Calabar Calabar Nigeria

In this present study, the possibility of using 2,6-bis(4-chlorophenyl)-3,3-dimethylpiperidin-4-one (BCDP) as an antiviral agent against HIV was carefully evaluated. In order to achieve this, the compound BCDP was synthesized and characterized employing various spectroscopic methods including FT-IR, 13C-NMR and 1H- NMR. The theoretical calculations for the compound were carried out using the DFT using 6-311++(2d,2p) basic set and ωBD7XD functional. Both structural and electronic properties of the compound have also been studied. The frontier molecular orbital and the global reactivity descriptors were determined and the energy gap E obtained is 8.220 eV. The chemical hardness value for the BCDP obtained is 4.110 eV. In order to provide essential details concerning the non-covalent interaction of the molecules, the Hirshfeld analysis alongside finger plot has been carried out in this study. Furthermore, the NBO has been employed to provide more elucidation on charge transfer due to the inter and intramolecular interaction. Also, the antiviral potential of the BCDP compound against HIV was observed from the molecular docking studies. The docking result suggest that the drug has a good biological activity with values of -7.11, -5.9 and -7.8 kcal/mol for three different protein 5V4Y, 6IOC and 6OGP respectively. Furthermore, the SwissADME online tool was utilized to explore the pharmacokinetic and physicochemical features of the BCDP molecule. © 2023, The Authors. All rights reserved.

关键词： Molecules

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Weighting construction by bag-of-words with similarity-learning and supervised training for classification models in court text documents[Formula presented]

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Applied Soft Computing 2022年 124卷

作者： Castro, Antonio P. Wainer, Gabriel A. Calixto, Wesley P. Electrical Mechanical & Computer Engineering School Federal University of Goias Goias Goiania Brazil Experimental & Technological Research and Study Group Federal Institute of Goias GoianiaGoias Brazil Visualization Simulation and Modeling Carleton University Ottawa Canada Court of Justice Goias Brazil

Traditional models of bag-of-words for text classification are unable to identify weights for the co-occurrence of terms, and, mainly, for this reason, they are being replaced by models of word embedding. This article proposes a method to enhance traditional bag-of-words models in two aspects: (a) build features on the co-occurrence of terms and (b) smooth the non-linearity or make the terms linear for different corpus categories. The datasets used are characterized by the non-linearity of the terms, having four different categories of documents. Two computational representations of the datasets are generated: binary and frequency, being used for supervised training of nine classification technologies: random forest, multilayer perceptron neural networks, adaptive boosting, gradient boosting, Gaussian process, support vector machine, Naive Bayes, k-nn and decision trees, its results are compared with nine other algorithms used in other research work. The combinations of each obtained result are compared and assessed using the accuracy, f-measure, precision, and recall metrics. The research and studies generated resulted in the construction of an API that will integrate the Department of Justice software that controls the judicial proceedings. The results of the evaluation metrics and the comparisons with other studies demonstrate that the proposed methodology is feasible to be applied in meeting the needs of the court, allowing to speed up the judgment of lawsuits. © 2022 Elsevier B.V.

关键词： Knowledge management

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Two-Dimensional Thin Layer Convective Flow and Heat Transfer of a Dusty Fluid on a Nonlinear Stretching Sheet

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Multiscale Science and engineering 2022年第3期4卷 111-118页

作者： Islam, Md. Robiul Ferdows, M. Misra, J. C. Murtaza, M. G. Research Group of Fluid Flow Modeling and Simulation Department of Applied Mathematics University of Dhaka Dhaka Bangladesh Department of Computer Science and Engineering Green University of Bangladesh Dhaka Bangladesh Centre for Healthcare Science and Technology Indian Institute of Engineering Science and Technology Howrah India Department of Mathematics Comilla University Cumilla Bangladesh

In this study, steady two-dimensional boundary layer flow and heat transfer of a dusty fluid over a nonlinearly stretching sheet with variable thickness, $${u}_{w} (x)={U}_{0}{(x+b)}^{m}$$ has been considered. A variable magnetic field is applied transversely to the direction of the flow. The general problem has been reduced to a system of coupled non-linear ordinary differential equations of two-dimensional boundary layer. By means of similarity transformation, the basic governing equations are transformed into a set of nonlinear ordinary differential equation and then are solved numerically by dsolve routine in MAPLE. Results of the present study have been duly validated by adopting an appropriate procedure. The influence of various parameters such as velocity power index, wall thickness parameter, magnetic parameter fluid-particle interaction parameter for velocity, fluid-particle interaction parameter for temperature, mass concentration of dust particle, Prandtl number, Eckert number has been investigated. The effects are then presented graphically both for dust phase and fluid phase. It is clear that flow field and other quantities of physical interest are significantly influenced by these parameters. Also the effects of the parameters on the skin-friction coefficients and rate of heat transfer in terms of the Nusselt number, which are of physical interest, are shown graphically/in tabular form. The study reveals that the impact of the parameters for the dusty fluid on Nusselt number is considerably higher than that for a clean fluid.

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Computational Approaches of Modelling Human Papillomavirus Transmission and Prevention Strategies: A Systematic Review

arXiv

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arXiv 2024年

作者： Wang, Weiyi Sawleshwarkar, Shailendra Piraveenan, Mahendra Modelling and Simulation Research Group School of Computer Science Faculty of Engineering The University of Sydney SydneyNSW2006 Australia Sydney Medical School Faculty of Medicine The University of Sydney SydneyNSW2006 Australia Sydney Infectious Diseases Institute The University of Sydney Australia Charles Perkins Centre The University of Sydney John Hopkins Drive SydneyNSW2006 Australia

Human papillomavirus (HPV) infection is the most common sexually transmitted infection in the world. Persistent oncogenic Human papillomavirus infection has been a leading threat to global health and can lead to serious complications such as cervical cancer. Prevention interventions including vaccination and screening have been proved effective in reducing the risk of HPV-related diseases. In recent decades, computational epidemiology has been serving as a very useful tool to study HPV transmission dynamics and evaluation of prevention strategies. In this paper, we conduct a comprehensive literature review on state-of-the-art computational epidemic models for HPV disease dynamics, transmission dynamics, as well as prevention efforts. Selecting 45 most-relevant papers from an initial pool of 10,497 papers identified through keyword search, we classify them based on models used and prevention strategies employed, summarise current research trends, identify gaps in the present literature, and identify future research directions. In particular, we describe current consensus regarding optimal prevention strategies which favour prioritising teenage girls for vaccination. We also note that optimal prevention strategies depend on the resources available in each country, with hybrid vaccination and screening being the most fruitful for developed countries, and screening-only approaches being most cost effective for low and middle income countries. We also highlight that in future, the use of computational and operations research tools such as game theory and linear programming, coupled with the large scale use of census and geographic information systems data, will greatly aid in the modelling, analysis and prevention of HPV. © 2024, CC BY-NC-ND.

关键词： Health risks

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Chances and Challenges of Chatgpt and Similar Models for Education in M&S 23

Chances and Challenges of Chatgpt and Similar Models for Edu...

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Proceedings of the Winter simulation Conference

作者： Andreas Tolk Philip Barry Margaret L. Loper Ghaith Rabadi William T. Scherer Levent Yilmaz The MITRE Corporation Modeling and Analysis Innovation Center Charlottesville USA L3Harris Corporation Mission Analysis Group Herndon USA Georgia Tech Research Institute Georgia Institute of Technology Atlanta USA University of Central Florida School of Modeling Simulation and Training Orlando USA University of Virgina Department of Systems and Information Engineering Charlottesville USA Auburn University Samuel Ginn College of Engineering Computer Science and Software Engineering Auburn USA

ISBN: (纸本)9798350369663

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Enhancing Digital Twins with Advances in simulation and Artificial Intelligence: Opportunities and Challenges 23

Enhancing Digital Twins with Advances in Simulation and Arti...

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Proceedings of the Winter simulation Conference

作者： Simon J. E. Taylor Charles M. Macal Andrea Matta Markus Rabe Susan M. Sanchez Guodong Shao Modelling & Simulation Group Department of Computer Science Brunel University London Uxbridge UK Decision & Infrastructure Sciences Division Argonne National Laboratory Lemont USA Department of Mechanical Engineering Politecnico di Milano Milano Italy Department IT in Production and Logistics TU Dortmund University Dortmund Germany Operations Research Department Naval Postgraduate School Monterey USA Engineering Laboratory National Institute of Standards and Technology Gaithersburg USA

ISBN: (纸本)9798350369663

simulations are used to investigate physical systems. A digital twin goes beyond this by connecting a simulation with the physical system with the purpose of analyzing and controlling that system in real-time. In the past 5 years there has been a substantial increase in research into simulation and Artificial Intelligence (AI). The combination of simulation with AI presents many possible innovations. Similarly, combining AI with simulation presents further possibilities including approaches to developing trustworthy and explainable AI methods, solutions to problems arising from sparce or no data and better methods for time series analysis. Given the progress that has been made in Digital Twins and simulation and AI, what opportunities are there from combining these two exciting research areas? What challenges need to be overcome to achieve these? This article discusses these from the perspectives of six leading members of the Modeling & simulation community.

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