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A Digital Twin Framework for Bridges

A Digital Twin Framework for Bridges

引用

ASCE international conference on Computing in Civil Engineering (I3CE)

作者： Najafi, Amirali Amir, Zaid Salman, Baris Sanaei, Parisa Lojano-Quispe, Erick Maher, Ali Schaefer, Richard Rutgers State Univ Ctr Adv Infrastruct & Transportat Piscataway NJ 08854 USA Rutgers State Univ Dept Civil & Environm Engn Piscataway NJ USA Syracuse Univ Dept Civil & Environm Engn Syracuse NY 13244 USA New Jersey Transit Newark NJ USA

ISBN: (数字)9780784485231

ISBN: (纸本)9780784485231

Current inspection and maintenance practices for bridges involve periodic manual visual surveys which are time consuming and cumbersome due to number of bridges in need of assessment. Unprecedented capabilities have become possible in recent years thanks to strides made in sensing technologies, computer vision, and machine learning. These technologies can be integrated into a digital twin framework for better insight into a bridge's structural integrity, maintenance needs, and potential risks. A digital twin framework involves creating a virtual model that mimics the behavior and performance of a physical bridge. Data collection about a bridge's physical condition is the first step in developing a framework. Physics simulation and graphical environment are next needed to host relevant models of the bridge. An illustrative example involving these steps and digital twin use for scenario simulation for different mechanisms is provided. The example focuses on modeling of a railway bridge in Lyndhurst, New Jersey.

关键词： digital twin geometry extraction bridges health monitoring scenario simulation

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Inverse Problem Antidote (IPA): modeling of Systems Biology Model with Invertible Neural Networks

Inverse Problem Antidote (IPA): Modeling of Systems Biology ...

引用

2024 IEEE international conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Li, Linlin Lu, Shenyu Umulis, David M. Wang, Xiaoqian Purdue University Weldon School of Biomedical Engineering West LafayetteIN United States Purdue University Elmore Family School of Electrical and Computer Engineering West LafayetteIN United States

ISBN: (纸本)9798350386226

In computational biology, accurately modeling biological systems is essential for understanding the underlying mechanisms of biological processes. One of the primary challenges in modeling lies in the inability to measure certain biological parameters directly. The task of identifying the parameters is known as the inverse problem and it entails estimating these unobservable parameters from available data. Existing modeling methods primarily focus on single-direction prediction. These methods include traditional Partial Differential Equation (PDE) modeling and machine learning approaches where given parameters are provided to predict the output and further compare the output with experimental evidence. However, these unidirectional methods struggle to effectively apply the experimental evidence directly to address the inverse problem. We contend that a single biological process should be modeled bidirectionally to simultaneously address the inverse problem. To this end, we propose leveraging the capabilities of the invertible neural network (INN) to establish a connection between the input parameter space and the model output space. We meticulously designed a bidirectional training technique that effectively applies real-world experimental data in guiding the INN in modeling the biological process. We tested our approach on a PDE-based Bone Morphogenic Protein (BMP) signaling network system in the zebrafish embryo and found the bidirectional modeling approach significantly enhances the alignment between simulation and experimental data. This method achieves a 94.65% reduction in Root Mean Square Error (RMSE) compared to the single-direction model when reconstructing experimental data using simulation with INN-identified parameters. Moreover, our method is rapid to implement, facilitating the precise identification of parameter ranges from experimental data. It makes parameter optimization feasible and provides a guideline for determining simulation parameter ranges,

关键词： Inverse problems

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computer Aided Design of Microwave Circuits Based on BP Neural Networks 5

Computer Aided Design of Microwave Circuits Based on BP Neur...

引用

5th international conference on Communications, Information System and computer Engineering, CISCE 2023

作者： Liu, Junze Yu, Miao Changchun University of Science and Technology Changchun China

ISBN: (纸本)9798350326796

In addition to meeting basic electrical characteristics, the design of a microwave circuit must also consider the ease and accuracy of the circuit model, the time required for circuit design, the availability of tolerance analysis, and the ability to optimize output. Artificial Neural Network (ANN) technology has recently been introduced into microwave circuit CAD and optimization due to its nonlinear mapping function and high real-time computing capability. This technology has been shown to significantly improve the accuracy of modeling and compensate for errors in traditional microwave circuit design methods. In this study, we propose a BP neural network-based modeling method for microwave integrated circuits. This model can be used for computer-aided integrated microsystem simulation and analysis. The fitting error(RMSE) between the original simulation data and the test data is reduced from 0.868 to 0.274 before and after compensation, demonstrating the effectiveness of the proposed method. Experimental results show that the accuracy of the circuit model is improved after the optimization of the BP neural network. © 2023 IEEE.

关键词： Neural networks

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Automatic spray shop monitoring system based on digital twin 4

Automatic spray shop monitoring system based on digital twin

引用

4th international conference on Internet of Things and Smart City, IoTSC 2024

作者： Ma, Hangxing Xu, Jiangmin School of Mechanical Engineering Jiangsu University of Science and Technology Zhenjiang212000 China Marine Equipment and Technology Institute Jiangsu University of Science and Technology Zhenjiang212000 China

ISBN: (纸本)9781510681767

A digital-based method was proposed to address challenges in large-scale segmented hull automated spraying workshops, such as the production of toxic gases and solid particles during operations, hindering real-time monitoring of spraying activities. The method focuses on the mismatch between site data and process system performance, leading to poor film quality. The intelligent monitoring method of twin technology establishes a system architecture for a digital twin five-dimensional model, exploring twin model establishment and data-driven technology. Specifically, a new digital twin modeling method for spray film thickness was studied and validated through experiment-simulation comparisons, showing high accuracy in restoring film thickness and uniformity. The system leverages the iterative nature of the spraying process to accumulate and process on-site data, allowing for iterative optimization of spraying process parameters to enhance efficiency and quality. © 2024 SPIE.

关键词： Film thickness Data modeling Mathematical modeling Associative arrays Coating 3D modeling computer simulations Mathematical optimization modeling Virtual reality

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Construction of Intelligent Financial Decision Support System Based on computer

Construction of Intelligent Financial Decision Support Syste...

引用

2023 international conference on computer simulation and modeling, Information Security, CSMIS 2023

作者： Han, Bing School of Accounting Zhanjiang University of Science and Technology Zhanjiang524094 China West Guangdong Digital Intelligent Accounting Development Research Center Zhanjiang524094 China

ISBN: (纸本)9798350343724

In the Big Data Age, the company's financial management is confronted with a bigger challenge. In the face of the growing quantity of data, financial managers have difficulty providing the related information quickly and accurately. Therefore, it is very important to construct an intelligent financial decision-making system for enterprise finance management. computer intelligence financial decision support system (IFDSS) is used to solve financial decision problems in enterprises, to provide analysis, prediction and decision-making, and to extract and analyze financial information. The IFDSS can help the enterprises to make more efficient strategic decision-making, make more scientific and rational development target, and prevent risk better. This paper conducts in-depth research on the construction of intelligent financial decision support system, and puts forward some suggestions for the development of IFDSS. Experimental results indicate that the maximum working efficiency of this system is up to 92.9%. © 2023 IEEE.

关键词： Intelligent systems

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Use-Case- Dependent modeling Approach for computer simulation of Hybrid AC-DC Grids 5

Use-Case- Dependent Modeling Approach for Computer Simulatio...

引用

5th IEEE international conference on DC Microgrids, ICDCM 2023

作者： Lavery, Melanie Schwanninger, Raffael Marz, Martin Institute for Power Electronics Friedrich-Alexander-University Erlangen Germany

ISBN: (纸本)9798350321272

An analysis-use-case dependent modeling approach for the computer simulation of hybrid AC-DC grids employing component models with varying degrees of complexity is presented. Three different component model complexity levels for three different component functionality groups and three different use cases are defined. The component modeling is based on analytical averaged descriptions of the converter behavior and introduces a standardized model interface. The proposed merits of this approach are faster simulation times and easier result evaluation making this approach suitable for automated grid simulation and assisted layout evaluation. This makes a technical and economical design evaluation of AC- DC grids much more feasible. Furthermore, manufacturers of grid components could use this design approach to develop models with unified interface ports to be used in DC grid model component libraries. The optimization of computing time for different simulation run times is tested and presented using a simulation tool developed using this approach. © 2023 IEEE.

关键词： Rectifying circuits

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FLARES: A Framework for Large-scale Agent-based Rapid Epidemic simulation 22

FLARES: A Framework for Large-scale Agent-based Rapid Epidem...

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22nd IEEE international conference on Industrial Informatics, INDIN 2024

作者： Peng, Ruoling Liu, Kang Yang, Po Department of Computer Science University of Sheffield Sheffield United Kingdom

ISBN: (纸本)9798331527471

Agent-based modeling (ABM) is a powerful simulation methodology employed to analyze complex systems by representing individual entities, known as agents, which interact autonomously within a defined set of rules. This approach is particularly effective for epidemic simulation, where capturing the nuanced interactions and behaviors of individuals is crucial for understanding disease dynamics and spread. However ABM often come with complected and slow implementation. To address the performance issue, in this paper, we introduce a Framework for Large-scale Agent-based Rapid Epidemic simulation (FLARES), a novel GPU-accelerated framework designed to enhance the performance of agent-based infectious disease transmission model. FLARES provides robust support for parallel execution, significantly reducing the overall time consumption for high computational cost tasks, enables researchers to conduct detailed and accurate epidemic analysis of disease spread. © 2024 IEEE.

关键词： Digital elevation model

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Promoting Safety, Security, Awareness and Productivity in Port Plants 5

Promoting Safety, Security, Awareness and Productivity in Po...

引用

5th international conference on Industry 4.0 and Smart Manufacturing (ISM)

作者： Bruzzone, Agostino G. Massei, Marina Sinelshichikov, Kirill De Paoli, Alberto Giovannetti, Antonio Longo, Francesco Fancello, Gianfranco Vairo, Tommaso Giliberti, Claudia Mariconte, Raffaele Univ Genoa Via Opera Pia 15 I-16145 Genoa Italy Simulat Team Via Magliotto 2 I-17100 Savona Italy Sim4Future Via Trento 43 I-16145 Genoa Italy Univ Calabria Simulat Team MSC LES Via Pietro Bucci I-87036 Arcavacata Di Rende Italy Univ Cagliari DICAAR Via Marengo 2 I-09121 Cagliari Italy INAIL DIT Piazzale Pastore 6 I-0144 Rome Italy

This paper focuses on the combined use of eXtended Reality and simulation to improve awareness and confidence in Container Terminal Operations by tailoring a simulation Systems. Experimentation is proposed as example of the benefits achievable by training virtually operators in this context. The complexity of Port Operations creates a quite dangerous environment where the highly competitive business sector push to increase speed of operations and flows. In additions Port Terminals involve many actors that have to work and interoperate within a multi domain environment, outdoor all around the clock along the year in an almost all-weather context. Ports are growing getting encapsulated within major city that over time turn to be megacities creating additional challenges especially in terms of Safety and Security that require to operate with high performance in a safe framework. The automation obviously is crucial to further increase operations, therefore up to know the human component is still quite critical for many ancillary activities as well as often on main and secondary ones due to the flexibility and reliability required. This aspect could suggest a big potential for Industry 4.0 and its future evolution in this field as well as a continuous struggling with the very conservative mentality of Shipping and Maritime Operations relying in Systems able to operate in the previous mentioned conditions. Indeed, Training and Education are crucial to face these challenges and make it possible to introduce new technologies, policies and approaches in the very strategic field of Port Activities. The authors propose an experimentation carried out to demonstrate the potential to move training and education on virtual interactive solutions based on MS2G paradigm (modeling, interoperable simulation and Serious Games) by tailoring a simulation System on specific criticalities (c) 2023 The Authors. Published by Elsevier B.V.

关键词： modeling & simulation IoT Serious Games Safety & Security Port operations

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Non Linear Homogenization of Laminate Magnetic Material by Computing Equivalent Magnetic Reluctivity 14

Non Linear Homogenization of Laminate Magnetic Material by C...

引用

19th international conference on Software Technologies, ICSOFT 2024

作者： Yousfi, Ghania Mohellebi, Hassane Electrotechnics Department Faculty of Electrical Engineering and Computer Science Mouloud Mammeri University Tizi-Ouzou Algeria

ISBN: (纸本)9789897587061

In the present study we present a numerical modeling of a laminate magnetic material using an homogenization technique which exploit an inverse problem resolution. The laminate magnetic material is consisting of an alternate of magnetic and insulates layers. The equivalent magnetic reluctivity is computed for the homogenized domain by considering a non linear behavior of the magnetic layers. A finite element method is used to solve the 2D non-linear electromagnetic partial differential equation. An optimization problem is constructed and solved with the association of the 2D finite element resolution and a conjugate bi-gradient algorithm. The computation of the equivalent magnetic reluctivity is then performed for different excitation field value according to B-H curve. The comparison of the obtained B-H curves of the laminate and the homogenized domains to the theoretical B-H curve (experimental data) show a good agreement of laminate results. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Inverse problems

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DeletePop: A DLT Execution Time Predictor Based on Comprehensive modeling 1

引用

23rd international conference on Algorithms and Architectures for Parallel Processing (ICA3PP)

作者： He, Yongzhe Zhou, Yueyuan Shao, En Tan, Guangming Sun, Ninghui Chinese Acad Sci Inst Comp Technol State Key Lab Processors Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Nanjing Inst InforSuperBahn Nanjing 211100 Peoples R China

ISBN: (数字)9789819708628

ISBN: (纸本)9789819708611;9789819708628

The modeling and simulation of Deep Learning Training (DLT) are challenging problems. Due to the intricate parallel patterns, existing modelings and simulations do not consider enough factors that influence the training, which brings inaccuracy for the prediction of DLT time. To address these rising challenges, we propose DeletePop, a Deep Learning Training Execution time Predictor based on comprehensive modeling at the Operator level. It systematically abstracts the process of DLT by dividing it into computation, memory access, and communication three parts. DeletePop could predict the Job Execution Time (JET) according to the operator dataset obtained from the homogeneous network. Finally, we integrate the DeletePop into a Job Scheduling Simulator (JSS) DLTSim to make support more efficient scheduling. Although the implementation of DeletePop is based on the TensorFlow framework, the theoretical model could adapt to any other frameworks that use static graphs. DeletePop achieves up to 90% accuracy for Homogeneous Networks, and we also provide the theoretical manners to add support for Heterogeneous Networks.

关键词： Deep Learning Training Job Execution Time modeling and simulation Job Scheduling Simulator

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