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2024

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Articles 61 - 90 of 363

Full-Text Articles in Numerical Analysis and Scientific Computing

Research On Application Of Intelligent Indication Signs In Improving Efficiency Of Crowd Evacuation, Heng Niu, Yanbin Han, Liang Li, Weilin Chen, Sijie Niu, Qingtao Hou Oct 2024

Research On Application Of Intelligent Indication Signs In Improving Efficiency Of Crowd Evacuation, Heng Niu, Yanbin Han, Liang Li, Weilin Chen, Sijie Niu, Qingtao Hou

Journal of System Simulation

Abstract: Aiming at the low emergency evacuation efficiency of dense crowds in confined spaces, a crowd evacuation guidance model based on intelligent signs is constructed in this paper. A balanced congestion strategy to optimize the signs layout and a social network search-based sign guidance weights optimization method are proposed to improve evacuation efficiency. Simulation experiments show that the optimized intelligent sign layout can effectively alleviate the local congestion during evacuation and reduce the time consumption of pedestrians caused by congestion. The optimized intelligent sign guidance weights can further balance the utilization rate of exits, which is conducive to making full …

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Garage Agv Path Planning And Simulation Based On Improved Dwa, Zongfang Ma, Linxuan Zhang, Lin Song, Jia Wang Oct 2024

Garage Agv Path Planning And Simulation Based On Improved Dwa, Zongfang Ma, Linxuan Zhang, Lin Song, Jia Wang

Journal of System Simulation

Abstract: Aiming at the path planning and real-time obstacle avoidance of AGV in complex path environment of intelligent garage, an improved hybrid algorithm combining ant colony algorithm and dynamic window method is proposed. In the global planning, the adaptive adjustment of pheromone volatilization coefficient and the fusion of angle parameters are introduced to establish the garage direction pheromone matrix to increase the guidance ability of target points, expand the direction selectivity of ants. In the local planning, the improved DWA of the obstacle distance evaluation subfunction based on elliptic equation is designed. By extracting the global path node of the …

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Adaptive Tracking Control For Omnidirectional Vehicle Based On Characteristic Modeling, Lei Cheng, Haoyou Wang, Xinjie Chen Oct 2024

Adaptive Tracking Control For Omnidirectional Vehicle Based On Characteristic Modeling, Lei Cheng, Haoyou Wang, Xinjie Chen

Journal of System Simulation

Abstract: Aiming at the stable and high-precision tracking control of omnidirectional mobile vehicles affected by their own characteristics and external disturbances, an adaptive tracking control approach for omnidirectional vehicles based on characteristic modeling is designed. The characteristic model is established by integrating the model properties into the characteristic parameters, and the characteristic parameters are estimated online by using the projected gradient method. A full coefficient adaptive control law based on the characteristic model is designed, and the stability of the proposed control method is analyzed by using Lyapunov theory. The effectiveness and rationality of the proposed adaptive control scheme are …

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Modeling Method Of Blue Army Warship Formation Air Defense Command And Control For System-Of-Systems Simulation, Shikang Chen, Zhimin Wang, Biao Liang, Kunren Gu, Keman Song, Yuan Gao Oct 2024

Modeling Method Of Blue Army Warship Formation Air Defense Command And Control For System-Of-Systems Simulation, Shikang Chen, Zhimin Wang, Biao Liang, Kunren Gu, Keman Song, Yuan Gao

Journal of System Simulation

Abstract: The command and control of warship formation air defense is a key link for the blue army's sea to air combat tasks and the modeling of air defense for warship formation is an important component of simulation modeling of blue army's maritime combat system. Based on the background of system-of-systems simulation, the air defense command and control modeling for blue army is designed. Through a modular modeling method, functional module including asset management and plan, unified situation generation, command decision are designed. According to blue army's command and control logic, these modules are integrated and the air defense command …

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Search Technology For Aircraft Debris Integrating Data Augmentation And Deep Learning Algorithm, Zhe Yang, Yinghan Cui, Lingxi Guo, Jiaxin Li, Xusheng Wu Oct 2024

Search Technology For Aircraft Debris Integrating Data Augmentation And Deep Learning Algorithm, Zhe Yang, Yinghan Cui, Lingxi Guo, Jiaxin Li, Xusheng Wu

Journal of System Simulation

Abstract: The reliable recovery of aircraft debris is of great significance for the complete acquisition of flight test data and the subsequent research and development of models. To ensure the safety of flight tests,the landing area of aircraft experiments is generally an unmanned area,and the actual landing point of the aircraft often deviates from the theoretical landing point. The characteristics of the debris target are complex and the dispersion area is large, making it difficult to search for aircraft debris solely by manpower. Aiming at the difficult problem of aircraft debris recovery in the landing area, through on UAV platforms …

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Two-Level Optimal Dispatch Of Power System Based On Load-Storage Carbon Flow Model, Yang Yu, Yuxing Xia, Wentao Lu, Mai Liu, Shixu Gao, Dongyang Chen Oct 2024

Two-Level Optimal Dispatch Of Power System Based On Load-Storage Carbon Flow Model, Yang Yu, Yuxing Xia, Wentao Lu, Mai Liu, Shixu Gao, Dongyang Chen

Journal of System Simulation

Abstract: In order to reduce the output of high energy consuming units on the power generation side, increase the absorption capacity of wind power, and consider the flexible resource allocation such as load and energy storage, a two-level economic low-carbon optimal scheduling method for power systems based on a carbon storage and discharge model is proposed. Based on the carbon emission flow theory of power system, a model for load and energy storage equipment is established; A demand response model based on the electricity carbon coupling price is established on the load side, and in view of the limitation on …

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Research On Flexible Operational Optimization Of Cchp System Based On Intelligent Fusion Algorithm, Zhe Bao, Xiaofang Zhang, Wei Li, Ye Xu, Xu Wang Oct 2024

Research On Flexible Operational Optimization Of Cchp System Based On Intelligent Fusion Algorithm, Zhe Bao, Xiaofang Zhang, Wei Li, Ye Xu, Xu Wang

Journal of System Simulation

Abstract: To further improve the accuracy of gas turbine simulation models, based on the construction of a gas turbine mechanism simulation model and BP simulation model, through model substitution technology and BP neural network algorithm three intelligent fusion simulation models for gas turbines, and two intelligent fusion simulation models for parallel gas turbines are constructed respectively as well as the combination of, by comparing the simulated results of the above models with the actual operating data, the simulation model with the best performance was selected. Using the intelligent fusion simulation model of the gas turbine as the output constraint, a …

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Chaotic-Encode Quantum Pso Algorithm For Flexible Job-Shop Scheduling Problem, Yuanxing Xu, Mengjian Zhang, Deguang Wang Oct 2024

Chaotic-Encode Quantum Pso Algorithm For Flexible Job-Shop Scheduling Problem, Yuanxing Xu, Mengjian Zhang, Deguang Wang

Journal of System Simulation

Abstract: To solve the flexible job-shop scheduling problem (FJSP), a chaotic-encode quantum PSO (CQPSO) algorithm is proposed. Aiming at the premature convergence of particles to local optimum in standard QPSO, the methods for computing the adaptive contraction-expansion coefficient and mean best position using fitness values of associated particles are proposed to improve the global search ability of QPSO. Through chaotic boundary variation strategy, the probability of a large number of particles gathering at the boundary is reduced and the population diversity is increased to enhance the ability of searching the optimal solution. According to the iterative property of QPSO, a …

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Multi-Strategy Partheno-Genetic Algorithm Based On Dynamic Reduction Mechanism For Solving Cvrp Problem, Jiajun Chen, Dailun Tan Oct 2024

Multi-Strategy Partheno-Genetic Algorithm Based On Dynamic Reduction Mechanism For Solving Cvrp Problem, Jiajun Chen, Dailun Tan

Journal of System Simulation

Abstract: Aiming at the problems of premature, slow convergence and low accuracy of traditional genetic algorithm in solving capacitated vehicle routing problem,a multi-strategy partheno-genetic algorithm based on dynamic reduction mechanism is proposed. The algorithm divides the optimization space based on similar individuals, and uses simulated annealing criterion to eliminate or update the lowest category subspace, which constitutes the reduction and movement mechanism of the optimization space. Based on parthenogenetic algorithm,a variety of genetic evolution strategies including intra-group, inter-group, global search, disturbance and jump strategy are designed Based on the three penalty factors of individual development, population evolution and overall convergence, …

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Unmanned Vehicle Path Planning And Tracking Control Based On Improved Artificial Potential Field Method, Minghao Guo, Peng Ji, Haiwei Huang Oct 2024

Unmanned Vehicle Path Planning And Tracking Control Based On Improved Artificial Potential Field Method, Minghao Guo, Peng Ji, Haiwei Huang

Journal of System Simulation

Abstract: A path planning algorithm based on improved artificial potential field method and a tracking control strategy based on model predictive controller are proposed for the unmanned vehicle avoiding dynamic obstacles in the complex scene of lane changing and overtaking. The theory of safety ellipse and the concept of prediction distance are introduced to adjust the influence region of potential field. By adding velocity potential field to change potential field function, the problem of vehicle avoiding dynamic obstacles is solved. Based on the linear three-degree-of-freedom vehicle dynamics model, a model prediction controller including potential field environment is established. The effectiveness …

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Path Following Control And Simulation Analysis Of Multi-Articulated Vehicles, Yu Zhao, Caijin Yang, Tanming Wang, Jing Xu, Shuai Zhou Oct 2024

Path Following Control And Simulation Analysis Of Multi-Articulated Vehicles, Yu Zhao, Caijin Yang, Tanming Wang, Jing Xu, Shuai Zhou

Journal of System Simulation

Abstract: The structure of multi-articulated vehicle body limits the flexibility of the vehicle and causes the deviation of the rear vehicle. Taking the ideal articulation angle as the control target, a feedforward plus feedback path following control method is proposed, which realizes the precise path following of rear vehicle bodies by minimizing the deviation between the ideal articulation angle and the actual articulation angle. According to the geometric position relationship between the vehicle and the desired path, the traditional calculation method of the ideal articulation angle is improved from two perspectives of application range and error accumulation. Based on the …

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Improved Foggy Pedestrian And Vehicle Detection Algorithm Based On Yolov5, Tong Su, Ying Wang, Qiyang Deng, Zhaobin Li Oct 2024

Improved Foggy Pedestrian And Vehicle Detection Algorithm Based On Yolov5, Tong Su, Ying Wang, Qiyang Deng, Zhaobin Li

Journal of System Simulation

Abstract: Due to the poor environment perception of car in bad weather, the detection ability on dynamic targets is significantly reduced, and thus the problems such as low accuracy and poor robustness of the deep learning-based target detection network will occur when detecting pedestrians and vehicles in foggy days. A YOLOv5-SGE foggy detection network is proposed on the basis of the combination of image dehazing DehazeNet and the improved YOLOv5. The adaptive calculation of anchor frame is realized by canceling the initial anchor frame of YOLOv5, and the anchor frame suitable for the current dataset is generated. A three-dimensional weighted …

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A Method For Battlefield Situation Information Ontology Construction Based On Top-Down And Bottom-Up Integration, Cong Zhou, Sihang Zhou, Jian Huang, Dong Wang Oct 2024

A Method For Battlefield Situation Information Ontology Construction Based On Top-Down And Bottom-Up Integration, Cong Zhou, Sihang Zhou, Jian Huang, Dong Wang

Journal of System Simulation

Abstract: The construction of the unified expression model of battlefield situational information is challenging due to the complexity of data sources and the significant differences in data structures and expression methods. Ontologies, as semantic conceptual models, are often used to describe concepts, relationships, and attributes within knowledge domains. An ontology construction method for the battlefield situational information domain based on a top-down and bottom-top integration is proposed. The top-down method is used to construct the upper ontology, in which a conceptual hierarchy model with a clear top-down structure is designed to establish the hierarchical relationships and semantic associations. A bottom-up …

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Peer-To-Peer Energy-Carbon Management Method Of Multiple Integrated Energy Systems Considering Multi-Agent Interaction Strategy, Yudong Wang, Junjie Hu Oct 2024

Peer-To-Peer Energy-Carbon Management Method Of Multiple Integrated Energy Systems Considering Multi-Agent Interaction Strategy, Yudong Wang, Junjie Hu

Journal of System Simulation

Abstract: To explore a new energy management model of P2P transaction of electricity, heat and carbon among IES with the participation of ESP, a P2P energy-carbon management method of IES considering multi-agent interaction strategy is proposed. A two-layer energy management framework with the multiagent participation of involving ESP and IES is established. A two-layer electricity-heat-carbon energy management model is constructed in which the upper model is constructed based on reinforcement learning framework to optimize the energy management strategy between ESP and IES cooperative alliance and the lower model is based on Nash negotiation game theory to optimize the cooperative operation …

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Solubility Characterization Of Organic Molecules For Aqueous Organic Redox Flow Batteries, Anthony W. Ferrell, Harkeerith K. Vij, Seamus D. Jones Oct 2024

Solubility Characterization Of Organic Molecules For Aqueous Organic Redox Flow Batteries, Anthony W. Ferrell, Harkeerith K. Vij, Seamus D. Jones

College of Engineering Summer Undergraduate Research Program

The major obstacle to renewable energy sources is a lack of long-term energy storage capabilities. Energy produced during the day dissipates, leaving insufficient electricity for at night. The goal of the project is to design an Aqueous Organic Redox Flow Battery (AORFB) to act as long-term energy storage. Work has been done using machine learning to identify suitable compounds for the batteries. In this work there was no indication as to the aqueous solubility of the molecules; this controls the device’s energy storage capabilities. We used a machine learning model to determine the aqueous solubility of slightly more than 3000 …

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Leveraging Tradespace-Exploration For A Senior Project Team Formation Application, Miguel Saenz Oct 2024

Leveraging Tradespace-Exploration For A Senior Project Team Formation Application, Miguel Saenz

College of Engineering Summer Undergraduate Research Program

This project revolves around the development of an app in MATLAB that leverages the VASSAR rule-based system and a genetic algorithm to form groups of teams for the Mechanical Engineering Senior Design project class. We leveraged the iterative design process to eventually attain a functional app with a reasonable runtime that works provided correctly formatted rulesheets describing student project preference and member preference.

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Joint Weakly Supervised Image Emotion Analysis Based On Interclass Discrimination And Intraclass Correlation, Xinyue Zhang, Zhaoxia Wang, Guitao Cao, Seng-Beng Ho Oct 2024

Joint Weakly Supervised Image Emotion Analysis Based On Interclass Discrimination And Intraclass Correlation, Xinyue Zhang, Zhaoxia Wang, Guitao Cao, Seng-Beng Ho

Research Collection School Of Computing and Information Systems

Regional information-based image emotion analysis has recently garnered significant attention. However, existing methods often focus on identifying region proposals through layered steps or merely rely on visual saliency. These approaches may lead to an underestimation of emotional categories and a lack of comprehensive interclass discrimination perception and emotional intraclass contextual mining. To address these limitations, we propose a novel approach named InterIntraIEA, which combines interclass discrimination and intraclass correlation joint learning capabilities for image emotion analysis. The proposed method not only employs category-specific dictionary learning for class adaptation, but also models intraclass contextual relationships and perceives correlations at the channel …

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Efficient Cascaded Multiscale Adaptive Network For Image Restoration, Yichen Zhou, Pan Zhou, Teck Khim Ng Oct 2024

Efficient Cascaded Multiscale Adaptive Network For Image Restoration, Yichen Zhou, Pan Zhou, Teck Khim Ng

Research Collection School Of Computing and Information Systems

Image restoration, encompassing tasks such as deblurring, denoising, and super-resolution, remains a pivotal area in computer vision. However, efficiently addressing the spatially varying artifacts of various low-quality images with local adaptiveness and handling their degradations at different scales poses significant challenges. To efficiently tackle these issues, we propose the novel Efficient Cascaded Multiscale Adaptive (ECMA) Network. ECMA employs Local Adaptive Module, LAM, which dynamically adjusts convolution kernels across local image regions to efficiently handle varying artifacts. Thus, LAM addresses the local adaptiveness challenge more efficiently than costlier mechanisms like self-attention, due to its less computationally intensive convolutions. To construct a …

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Does Ceo Agreeableness Personality Mitigate Real Earnings Management?, Shan Liu, Xingying Wu, Nan Hu Oct 2024

Does Ceo Agreeableness Personality Mitigate Real Earnings Management?, Shan Liu, Xingying Wu, Nan Hu

Research Collection School Of Computing and Information Systems

Despite efforts to mitigate aggressive financial reporting, earnings management remains challenging to parties interested in inhibiting its dysfunctional effects. Using linguistic algorithms to assess CEO agreeableness personality from their unscripted texts in conference calls, we find that it is a determinant that mitigates a firm's real earnings management. Furthermore, such an effect is more pronounced when firms confront intensive market competition and financial distress and have weaker managerial entrenchment or when CEOs face stronger internal governance. Our findings persist even after we utilize several alternative real earnings management metrics and control other confounding personalities in prior earnings management studies. The …

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Motif Graph Neural Network, Xuexin Chen, Ruicui Cai, Yuan Fang, Min Wu, Zijian Li, Zhifeng Hao Oct 2024

Motif Graph Neural Network, Xuexin Chen, Ruicui Cai, Yuan Fang, Min Wu, Zijian Li, Zhifeng Hao

Research Collection School Of Computing and Information Systems

Graphs can model complicated interactions between entities, which naturally emerge in many important applications. These applications can often be cast into standard graph learning tasks, in which a crucial step is to learn low-dimensional graph representations. Graph neural networks (GNNs) are currently the most popular model in graph embedding approaches. However, standard GNNs in the neighborhood aggregation paradigm suffer from limited discriminative power in distinguishing high-order graph structures as opposed to low-order structures. To capture high-order structures, researchers have resorted to motifs and developed motif-based GNNs. However, the existing motif-based GNNs still often suffer from less discriminative power on high-order …

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Large-Scale Graph Label Propagation On Gpus, Chang Ye, Yuchen Li, Bingsheng He, Zhao Li, Jianling Sun Oct 2024

Large-Scale Graph Label Propagation On Gpus, Chang Ye, Yuchen Li, Bingsheng He, Zhao Li, Jianling Sun

Research Collection School Of Computing and Information Systems

Graph label propagation (LP) is a core component in many downstream applications such as fraud detection, recommendation and image segmentation. In this paper, we propose GLP, a GPU-based framework to enable efficient LP processing on large-scale graphs. By investigating the data processing pipeline in a large e-commerce platform, we have identified two key challenges on integrating GPU-accelerated LP processing to the pipeline: (1) programmability for evolving application logics; (2) demand for real-time performance. Motivated by these challenges, we offer a set of expressive APIs that data engineers can customize and deploy efficient LP algorithms on GPUs with ease. To achieve …

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Transformer-Based Joint Learning Approach For Text Normalization In Vietnamese Automatic Speech Recognition Systems, The Viet Bui, Tho Chi Luong, Oanh Thi Tran Oct 2024

Transformer-Based Joint Learning Approach For Text Normalization In Vietnamese Automatic Speech Recognition Systems, The Viet Bui, Tho Chi Luong, Oanh Thi Tran

Research Collection School Of Computing and Information Systems

In this article, we investigate the task of normalizing transcribed texts in Vietnamese Automatic Speech Recognition (ASR) systems in order to improve user readability and the performance of downstream tasks. This task usually consists of two main sub-tasks: predicting and inserting punctuation (i.e., period, comma); and detecting and standardizing named entities (i.e., numbers, person names) from spoken forms to their appropriate written forms. To achieve these goals, we introduce a complete corpus including of 87,700 sentences and investigate conditional joint learning approaches which globally optimize two sub-tasks simultaneously. The experimental results are quite promising. Overall, the proposed architecture outperformed the …

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Latent Representation Learning For Geospatial Entities, Ween Jiann Lee, Hady Wirawan Lauw Oct 2024

Latent Representation Learning For Geospatial Entities, Ween Jiann Lee, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

Representation learning has been instrumental in the success of machine learning, offering compact and performant data representations for diverse downstream tasks. In the spatial domain, it has been pivotal in extracting latent patterns from various data types, including points, polylines, polygons, and networked structures. However, existing approaches often fall short of explicitly capturing both semantic and spatial information, relying on proxies and synthetic features. This article presents GeoNN, a novel graph neural network-based model designed to learn spatially-aware embeddings for geospatial entities. GeoNN leverages edge features generated from geodesic functions, dynamically selecting relevant features based on relative locations. It introduces …

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Data Provenance Via Differential Auditing, Xin Mu, Ming Pang, Feida Zhu Oct 2024

Data Provenance Via Differential Auditing, Xin Mu, Ming Pang, Feida Zhu

Research Collection School Of Computing and Information Systems

With the rising awareness of data assets, data governance, which is to understand where data comes from, how it is collected, and how it is used, has been assuming evergrowing importance. One critical component of data governance gaining increasing attention is auditing machine learning models to determine if specific data has been used for training. Existing auditing techniques, like shadow auditing methods, have shown feasibility under specific conditions such as having access to label information and knowledge of training protocols. However, these conditions are often not met in most real-world applications. In this paper, we introduce a practical framework for …

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Research On Simulation Resource Management Based On Graph Association Organization, Zewei Liu, Yishan Ding, Tingyu Lin, Mingxing Ke, Liqing Guo, Yingying Xiao, Zhilong Zhao, Yan Li, Xuan Lü Sep 2024

Research On Simulation Resource Management Based On Graph Association Organization, Zewei Liu, Yishan Ding, Tingyu Lin, Mingxing Ke, Liqing Guo, Yingying Xiao, Zhilong Zhao, Yan Li, Xuan Lü

Journal of System Simulation

Abstract: The simulation test and evaluation of intelligent system of systems, systems and single equipment is a complex system engineering, which requires effective management of multi-source, heterogeneous and distributed massive simulation resources scattered in cloud test centers and test sites of various units; and good control of dynamically generated tasks, assumptions, configurations, results, evaluations and other data and files. The traditional way of managing and querying simulation resources by category is inefficient and difficult to meet the requirements of large-scale intelligent simulation test and evaluation activities. An overall framework for simulation resource management based on graph association organization, defines a …

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Simulation Study Of Personnel Evacuation In Fire Scenarios Of Old School Buildings, Qiankun Zhu, Jiwu Li, Yongfeng Du Sep 2024

Simulation Study Of Personnel Evacuation In Fire Scenarios Of Old School Buildings, Qiankun Zhu, Jiwu Li, Yongfeng Du

Journal of System Simulation

Abstract: In order to improve the emergency evacuation capability of an old school building under fire scenarios, a fire evacuation model of an old school building is developed. The PyroSim software is used to build a fire dispersion model to simulate and analyse the changes of smoke visibility, temperature and CO at the safety exit of the fire floor in the school building under the condition of mechanical smoke exhaust, automatic sprinkler and whether the windows of the fire room are open or not. The simulation of the exit status and evacuation of people has been carried out in conjunction …

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A New Model Predictive Current Controller Forac-Dc Matrix Converter In Unbalanced Grids, Wenlang Deng, Minghai Wu, Haipeng Xie, Yingjie Hu Sep 2024

A New Model Predictive Current Controller Forac-Dc Matrix Converter In Unbalanced Grids, Wenlang Deng, Minghai Wu, Haipeng Xie, Yingjie Hu

Journal of System Simulation

Abstract: To reduce the fluctuation of active power on the grid side of AC-DC matrix converters under unbalanced input conditions and to address the issue of variable switching frequency in discrete model predictive control, this paper proposes a novel model predictive control method. This method selects effective vectors based on the phase angle of the grid current, thus avoiding the computational burden of evaluating the value function in traditional model predictive control. Additionally, a second-order extended complex Kalman filter is introduced, which achieves the computation accuracy of the secondorder term of the Taylor series expansion and enables the application of …

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Path Planning Based On Improved A* And Dynamic Window Approach, Peng Ji, Xinyuan Zhang, Shuaixuan Gao, Shuorang Wei Sep 2024

Path Planning Based On Improved A* And Dynamic Window Approach, Peng Ji, Xinyuan Zhang, Shuaixuan Gao, Shuorang Wei

Journal of System Simulation

Abstract: In response to the low efficiency, redundant turning points, and collision issues of the traditional A* algorithm, a smart vehicle path planning algorithm that integrates an improved A* algorithm with a dynamic window approach has been proposed. The algorithm has enhanced the search point selection method, optimized the evaluation function, selected key turning points based on the slope values between turning points, and removed redundant turning points. Between every two optimized key turning points, a dynamic window approach that balances speed and safety is used for local obstacle avoidance. Experiments show that compared to the traditional A* algorithm, this …

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Research On System-Of-Systems Confrontation Simulation Method Based On Operation Loops, Shan Zhong, Yesheng Zhu, Menglu Zhou Sep 2024

Research On System-Of-Systems Confrontation Simulation Method Based On Operation Loops, Shan Zhong, Yesheng Zhu, Menglu Zhou

Journal of System Simulation

Abstract: In the field of modeling and analyzing capabilities for operation system-of-systems (SoS), traditional structured capability assessment models lack the analysis of the interaction between both rivals and armies in different roles. The system model based on operation loop theory can be combined with the relationship between sensor, decision-making, influence, and target nodes for system capability calculation, but the existing model is usually only suitable for static analysis and cannot be used for dynamic simulation of SoS confrontation. In order to solve the problems above, a SoS confrontation simulation method based on operation loops is proposed. It abstracts both rivals’ …

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Carbon Footprint Analysis And Low-Carbon Optimization Method Simulation Study Of Power Transformer Based On Digital Twin Technology, Dongxue Li, Yan Liu, Boyao Shen, Yongteng Jing, Qiang Ma, Ran Liu Sep 2024

Carbon Footprint Analysis And Low-Carbon Optimization Method Simulation Study Of Power Transformer Based On Digital Twin Technology, Dongxue Li, Yan Liu, Boyao Shen, Yongteng Jing, Qiang Ma, Ran Liu

Journal of System Simulation

Abstract: Power transformers are the main energy-consuming equipment for substations. According to the goal of “carbon peak, carbon neutralization” in China, it is of great significance to accurately calculate the carbon footprint of transformers and seek low-carbon optimization methods. A method for constructing a digital twin model of power transformer magnetic characteristics is proposed. Based on the three-dimensional electromagnetic time-harmonic field finite element analysis method, a threedimensional model of SZ11-31.5MVA/66kV power transformer is established. The transformer loss map is obtained under fluctuating load condition, and the transformer digital twin model is constructed. The carbon footprint of the transformer is analyzed, …

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