Open Access. Powered by Scholars. Published by Universities.®

Operations Research, Systems Engineering and Industrial Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

Discipline
Institution
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 2101 - 2130 of 13783

Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

Naphtha Characterization (Piona, Density, Distillation Curve And Sulfur Content): An Origin Comparison, Aline Pioli Silva, Juliana Otavia Bahú, Renato Soccol Jr., Leonardo Rodriguez-Urrego, William Stive Fajardo-Moreno, Hiram Moya, Jeffrey Leon-Pulido, Víktor Oswaldo Cárdenas Concha Apr 2023

Naphtha Characterization (Piona, Density, Distillation Curve And Sulfur Content): An Origin Comparison, Aline Pioli Silva, Juliana Otavia Bahú, Renato Soccol Jr., Leonardo Rodriguez-Urrego, William Stive Fajardo-Moreno, Hiram Moya, Jeffrey Leon-Pulido, Víktor Oswaldo Cárdenas Concha

Manufacturing & Industrial Engineering Faculty Publications

Naphtha is an important distillation product of crude oil, and is used as a raw material for first-generation products such as ethylene, propylene, gasoline, xylene (BTX), and others. However, due to the different sources of crude oil, differences in naphtha composition impact the quality of conversion processes. Parameters such as pressure, charge flow, and temperature need to be adjusted for conversion efficiency. This work aims to compare naphtha samples from different origins, through the analysis of distillation curve (ASTM D86), density (ASTM D4052), total sulfur (ASTM D4294), and n-paraffins, iso-paraffins, olefins, naphthene, and aromatics (PIONA, ASTM D5134). Among these parameters …


Development Of A Smart Waste Management System For City Application, Lawrence D. Fraction Apr 2023

Development Of A Smart Waste Management System For City Application, Lawrence D. Fraction

Morehead State Theses and Dissertations

A thesis presented to the faculty of the Elmer R. Smith College of Business and Technology Morehead State University in partial fulfillment of the requirements for the Degree Master of Science by Lawrence D. Fraction on April 14, 2023.


Effective Use Methods For Continuous Sensor Data Streams In Manufacturing Quality Control, William Hitchcock Apr 2023

Effective Use Methods For Continuous Sensor Data Streams In Manufacturing Quality Control, William Hitchcock

Senior Honors Theses

This work outlines an approach for managing sensor data streams of continuous numerical data in product manufacturing settings, emphasizing statistical process control, low computational and memory overhead, and saving information necessary to reduce the impact of nonconformance to quality specifications. While there is extensive literature, knowledge, and documentation about standard data sources and databases, the high volume and velocity of sensor data streams often makes traditional analysis unfeasible. To that end, an overview of data stream fundamentals is essential. An analysis of commonly used stream preprocessing and load shedding methods follows, succeeded by a discussion of aggregation procedures. Stream storage …


Dynamic Target Assignment Of Multiple Unmanned Aerial Vehicles Based On Clustering Of Network Nodes, Tuo Zhao, Hanqiang Deng, Jialong Gao, Jian Huang Apr 2023

Dynamic Target Assignment Of Multiple Unmanned Aerial Vehicles Based On Clustering Of Network Nodes, Tuo Zhao, Hanqiang Deng, Jialong Gao, Jian Huang

Journal of System Simulation

Abstract: In order to solve the problem that the distributed multi-UAV target assignment algorithm is prone to communication redundancy, which leads to the large communication scale of formation, a multi-UAV dynamic target assignment algorithm (CU-CBBA) based on node clustering in communication network is proposed.The algorithm introduces the communication network node grouping clustering strategy. According to the node's degree centrality, feature vector centrality, intermediate centrality and other attributes, the network node importance ranking model is established. A group of key nodes in the network topology structure are selected and the network topology node clustering is completed according to the shortest …


Trajectory Control Of Crawler Robot Based On Lstm And Smc, Dongyang Liu, Wenwen Zha, Liang Tao, Cheng Zhu, Lichuan Gu, Jun Jiao Apr 2023

Trajectory Control Of Crawler Robot Based On Lstm And Smc, Dongyang Liu, Wenwen Zha, Liang Tao, Cheng Zhu, Lichuan Gu, Jun Jiao

Journal of System Simulation

Abstract: Trajectory tracking is an important part of mobile robot control technology and possesses prospect. Highly nonlinear dynamic characteristics are the main obstacles of controller design. A SMC method based on LSTM and quasi-sliding mode is proposed. The kinematics model and dynamics model of the tracked vehicle are given, and the sliding mode control system is established based on the dynamics model. LSTM network based on deep learning method is designed to control and compensate the unknown interference items, reduce the influence of external interference, and reduce the tremor phenomenon by combining the advantages of LSTM network and quasi-sliding …


Research On Modeling And Scheduling Of Virtual Power Plant With Dual Demand Response, Qiang Chen, Yi Wang, Kangshun Li Apr 2023

Research On Modeling And Scheduling Of Virtual Power Plant With Dual Demand Response, Qiang Chen, Yi Wang, Kangshun Li

Journal of System Simulation

Abstract: Virtual power plant technology provides an effective means to aggregate distributed power and user side resources to participate in power scheduling. Most of the existing research focus on the scheduling optimization of distributed energy instead of the demand response of user side. The user side resources are divided into contracted reliable response load and non-contracted random response load, and the load response is regulated through price adjustment mechanism to adapt to the change of distributed. A virtual power plant optimal scheduling model with dual demands response is constructed, in which the maximizing overall profit of the power grid is …


Voltage And Reactive Power Combinational Evaluation Of Regional Power Grid Based On Ewm-Ahp-Bp Neural Network, Yuqi Ji, Huan Xie, Shaoyu Shi, Ping He, Nan Jin, Huili Wang Apr 2023

Voltage And Reactive Power Combinational Evaluation Of Regional Power Grid Based On Ewm-Ahp-Bp Neural Network, Yuqi Ji, Huan Xie, Shaoyu Shi, Ping He, Nan Jin, Huili Wang

Journal of System Simulation

Abstract: In order to quantitatively evaluate the influence of renewable energy access on voltage and reactive power operation, a combinational evaluation method of voltage and reactive power based on EWM-AHP-BP neural network is proposed to carry out the multi-objective evaluation weight calculation. Considering voltage qualified rate, voltage fluctuation, power factor qualified rate and reactive power reserve, the comprehensive evaluation model is established. The operation data of renewable energy and power load are clustered to divide the typical scenarios and the evaluation model under multiple scenarios is scored by the combination method of entropy weight method and analytic hierarchy process. The …


Research On Modeling And Solution Method Of Operational Tasks Assignment, Yue Ma, Lin Wu, Shengming Guo Apr 2023

Research On Modeling And Solution Method Of Operational Tasks Assignment, Yue Ma, Lin Wu, Shengming Guo

Journal of System Simulation

Abstract: Aiming at the prewar operational tasks assignment in operation task planning, a multi constraint model of operational tasks assignment is constructed to describe the dynamic mapping relationship between operational tasks and operational units. The solution strategy of decision space pruning and constraint condition judgment is proposed, and the methods of decision variable coding, assignment scheme decoding and phased fitness calculation are described. Differential evolution algorithm is used to work out the solution. The experimental results show that the multi constraint assignment model and solution algorithm can effectively reduce the scale of decision space, and can improve the rationality …


Knowledge Graph-Based Process Knowledge Reasoning Method For Intelligent Production System, Weikai Yang, Yan Wang, Zhicheng Ji Apr 2023

Knowledge Graph-Based Process Knowledge Reasoning Method For Intelligent Production System, Weikai Yang, Yan Wang, Zhicheng Ji

Journal of System Simulation

Abstract: Aiming at the disadvantages of high redundancy and weakness between knowledge and data in intelligent production system, and the difficulty to perform knowledge reasoning, a process knowledge reasoning method for knowledge maps is proposed. The input information is semantically labeled and classified, the characteristics of the information match are extracted, the extracted local feature and global feature are associated through graph convolution method, and the feature of the difference value information is integrated and mapped with the constructed knowledge graph. Different reasoning rules are used according to different reasoning types, and the association and topology information between instances are …


Adaptive Correction Tracking Algorithm Based On Detector And Locator Fusion, Yecai Guo, Cheng Liu Apr 2023

Adaptive Correction Tracking Algorithm Based On Detector And Locator Fusion, Yecai Guo, Cheng Liu

Journal of System Simulation

Abstract: In order to avoid tracking failure caused by occlusion, rotation and other factors in complex dynamic scenes, an adaptive correction tracking algorithm based on detector and locator fusion is proposed. The locator trains a convolutional neural network (CNN) filter for location estimation by extracting the deep features of target. The CNN filter adds two layers of shallow features to the three layers of the convolution features of original CF2 algorithm, which enhances the extraction of target texture information. The detector calculates the confidence score by extracting histogram of oriented gradient(HOG) feature of target and combining the context information. …


Cross-Domain Text Sentiment Classification Based On Auxiliary Classification Networks, Na Ma, Tingxin Wen, Xu Jia, Xiaohui Li Apr 2023

Cross-Domain Text Sentiment Classification Based On Auxiliary Classification Networks, Na Ma, Tingxin Wen, Xu Jia, Xiaohui Li

Journal of System Simulation

Abstract: To align exactly the texts with same sentiment polarities of source and target domains, and to enlarge the feature difference of different sentiment texts as much as possible, a domain adaptation model with weighted adversarial networks is proposed. A new structured classification network consisting of a main classification network and an auxiliary classification network is proposed, in which the main classification network is used to perform supervised learning on the labeled texts of the source domain, and the auxiliary classification network is used to improve the distinguishability of the text features. A calculation method of multiple adversarial network weights …


Dual Resource Constrained Flexible Job Shop Energy-Saving Scheduling Considering Delivery Time, Hongliang Zhang, Jingru Xu, Bo Tan, Gongjie Xu Apr 2023

Dual Resource Constrained Flexible Job Shop Energy-Saving Scheduling Considering Delivery Time, Hongliang Zhang, Jingru Xu, Bo Tan, Gongjie Xu

Journal of System Simulation

Abstract: To handle the flexible job shop energy-saving scheduling with machines and workers constraints, on the considering of delivery time, the optimization model of dual resource constrained flexible job shop energy-saving scheduling is established with the goal of minimizing the total earliness and tardiness penalties, and total energy consumption. An improved non-dominated sorting genetic algorithm II(INSGA-II) is proposed. Aiming at the optimized objectives, a three-stage decoding method is designed to gain more feasible solutions. The dynamic adaptive crossover and mutation operators are applied to get more excellent individuals. The crowding distance is improved to obtain a population with better …


Shared Subnet Synthesis And Application Of Object-Oriented Pres Net, Chuanliang Xia, Maibo Guo, Zhuangzhuang Wang, Yan Sun Apr 2023

Shared Subnet Synthesis And Application Of Object-Oriented Pres Net, Chuanliang Xia, Maibo Guo, Zhuangzhuang Wang, Yan Sun

Journal of System Simulation

Abstract: Focus on embedded system modeling, a solution to obtain a synthesized net via the shared subnet of an extended Petri net is proposed. Object-oriented technology and Petri net-based representation for embedded system (PRES net) are merged to obtain an object-oriented PRES net (OOPRES net). A method of synthesized operation of the shared subnet of OOPRES net is proposed, and the preservation of the liveness and boundedness of synthesized net system is studied. Taking the modeling analysis of intelligent transportation system as an example, the effectiveness of the synthesized method is verified. The method can provide an effective way for …


Research On Improvement Of Social Force Model Based On Non-Motor Vehicle Active Overtaking Behavior, Minghui Yang, Rui Zhang, Qiaobing Yan, Jiahe Wang Apr 2023

Research On Improvement Of Social Force Model Based On Non-Motor Vehicle Active Overtaking Behavior, Minghui Yang, Rui Zhang, Qiaobing Yan, Jiahe Wang

Journal of System Simulation

Abstract: Aiming at the social force model not to illustrate the active overtaking behavior of the rear non-motor vehicle to the front vehicle, an improved social force model is proposed. The traffic behavior characteristics of non-motorized vehicles mixed flow during the active overtaking is analyzed. Considering the compressible characteristics of non-motorized vehicle distancing in different density environments, the model is improved by presenting the concept of dynamic perception space and introducing the overtaking force into the social force model. The model is verified by analyzing the active overtaking behavior, active overtaking distance and speed-density basic graphs. The results indicate that …


Multi-Agent Cooperative Combat Simulation In Naval Battlefield With Reinforcement Learning, Ding Shi, Xuefeng Yan, Lina Gong, Jingxuan Zhang, Donghai Guan, Mingqiang Wei Apr 2023

Multi-Agent Cooperative Combat Simulation In Naval Battlefield With Reinforcement Learning, Ding Shi, Xuefeng Yan, Lina Gong, Jingxuan Zhang, Donghai Guan, Mingqiang Wei

Journal of System Simulation

Abstract: Due to the rapidly-changed situations of future naval battlefields, it is urgent to realize the high-quality combat simulation in naval battlefields based on artificial intelligence to comprehensively optimize and improve the combat effectiveness of our army and defeat the enemy. The collaboration of combat units is the key point and how to realize the balanced decision-making among multiple agents is the first task. Based on decoupling priority experience replay mechanism and attention mechanism, a multi-agent reinforcement learning-based cooperative combat simulation (MARL-CCSA) network is proposed. Based on the expert experience, a multi-scale reward function is designed, on which a naval …


Research Progress Of Opponent Modeling Based On Deep Reinforcement Learning, Haotian Xu, Long Qin, Junjie Zeng, Yue Hu, Qi Zhang Apr 2023

Research Progress Of Opponent Modeling Based On Deep Reinforcement Learning, Haotian Xu, Long Qin, Junjie Zeng, Yue Hu, Qi Zhang

Journal of System Simulation

Abstract: Deep reinforcement learning is an agent modeling method with both deep learning feature extraction ability and reinforcement learning sequence decision-making ability, which can make up for the depleted non-stationary adaptation, complex feature selection and insufficient state-space representation ability of traditional opponent modeling. The deep reinforcement learning-based opponent modeling methods are divided into two categories, explicit modeling and implicit modeling, and the corresponding theories, models, algorithms and applicable scenarios are sorted out according to the categories. The applications of deep reinforcement learning-based opponent modeling techniques on different fields are introduced. The key problems and future development are summarized to provide …


Research On Workshop Logic Modeling And Simulation Based On Finite State Machine, Mingyuan Liu, Jiaxiang Xie, Hao Wu, Jianlin Fu, Guofu Ding Apr 2023

Research On Workshop Logic Modeling And Simulation Based On Finite State Machine, Mingyuan Liu, Jiaxiang Xie, Hao Wu, Jianlin Fu, Guofu Ding

Journal of System Simulation

Abstract: Discrete manufacturing is common in aircraft, ships, electronic equipment, automobile and other manufacturing industries. To ensure the correctness and flexibility of the modeling and simulation process of discrete manufacturing workshops, a logical modeling and simulation method for the production process of discrete manufacturing workshop is proposed. Based on the theory of discrete event dynamic systems and finite-state machines, the attributes and behaviors of the key elements of the discrete manufacturing workshop are abstracted into a unified logic model, and the function of various elements are realized through inheritance. A production process simulation algorithm is designed for the unified model …


Research On Unmanned Swarm Combat System Adaptive Evolution Model Simulation, Zhiqiang Li, Yuanlong Li, Laixiang Yin, Xiangping Ma Apr 2023

Research On Unmanned Swarm Combat System Adaptive Evolution Model Simulation, Zhiqiang Li, Yuanlong Li, Laixiang Yin, Xiangping Ma

Journal of System Simulation

Abstract: Aiming at the fact that the intelligent unmanned swarm combat system is mainly composed of large-scale combat individuals with limited behavioral capabilities and has limited ability to adapt to the changes of battlefield environment and combat opponents, a learning evolution method combining genetic algorithm and reinforcement learning is proposed to construct an individual-based unmanned bee colony combat system evolution model. To improve the adaptive evolution efficiency of bee colony combat system, an improved genetic algorithm is proposed to improve the learning and evolution speed of bee colony individuals by using individual-specific mutation optimization strategy. Simulation experiment on …


I-Nicemo Enhanced Algorithm Based On Intersection Angel Geometry, Yifan He, Yulin He, Yongda Cai, Zhexue Huang Apr 2023

I-Nicemo Enhanced Algorithm Based On Intersection Angel Geometry, Yifan He, Yulin He, Yongda Cai, Zhexue Huang

Journal of System Simulation

Abstract: To exactly determine the number of cluster centers and correctly identify the candidate cluster centers, an I-niceMO enhanced(I-niceMOEn) algorithm based on intersection angel geometry is proposed. As many distributions of intersection angles and distances as possible between observation points and data points are utilized to recognize the candidate cluster centers to avoid the neglection of cluster centers. The spectral clustering algorithm is used to automatically merge the candidate cluster centers according to the eigenvalues of Laplacian matrices. The number of final cluster centers is determined by the number of merged candidate cluster centers. The number of clusters can be …


Dynamics Modeling And Online Prediction Of Energy Consumption Of Discrete Manufacturing System, Wei Chen, Yan Wang, Zhicheng Ji Apr 2023

Dynamics Modeling And Online Prediction Of Energy Consumption Of Discrete Manufacturing System, Wei Chen, Yan Wang, Zhicheng Ji

Journal of System Simulation

Abstract: Aiming at the traditional energy consumption modeling methods of discrete manufacturing system being difficult to adapt to the complexity and variability of working conditions, an online dynamic energy consumption modeling method based on real-time data is proposed. The energy consumption affecting factors are determined by analyzing the operation mechanism of the discrete manufacturing system and equipment. An online sequential extreme learning machine algorithm that can dynamically adjust the number of hidden layer nodes is proposed to construct the energy consumption model. The real-time data can update the model quickly. Bernstein's inequality is introduced to improve the model data screening …


Construction Technology Of Hand Posture Dataset Based On Virtual Simulation Method, Jiaxin Chen, Guohui Zhou, Jianbai Yang Apr 2023

Construction Technology Of Hand Posture Dataset Based On Virtual Simulation Method, Jiaxin Chen, Guohui Zhou, Jianbai Yang

Journal of System Simulation

Abstract: Hand posture is an important carrier of human-computer interaction, and the acquisition and recognition of posture information largely depends on the hand posture dataset. Existing datasets can be divided into two categories, real datasets and synthetic datasets. As real data is limited by equipment, environment, and other factors, the classification of hand posture is insufficient and the annotation is mixed with a lot of manual errors. The existing synthetic data can solve the data scale problem of real data, but the synthetic hand posture volume is limited and with some unreasonable kinematic postures of which the data form are …


Bottleneck Drift Fluctuation Analysis Of Discrete Remanufacturing System Under Disturbance, Yongzhang Zhou, Yan Wang, Zhicheng Ji Apr 2023

Bottleneck Drift Fluctuation Analysis Of Discrete Remanufacturing System Under Disturbance, Yongzhang Zhou, Yan Wang, Zhicheng Ji

Journal of System Simulation

Abstract: Considering comprehensively the influence of each production process on the bottleneck degree of discrete remanufacturing system, the interval bottleneck index matrix is established by collecting data repeatedly in the observation stage to obtain the comprehensive bottleneck index of equipment, which is used as the identification basis. Aiming at the volatility of bottleneck drift in the uncertain environment of discrete remanufacturing system, based on the interval bottleneck index matrix and comprehensive bottleneck index, a theoretical method of visual dynamic analysis including system sensitivity coefficient, machine sensitivity coefficient and bottleneck drift judgment model is established. The discrete event simulation case is …


Atmospheric Corrosion Simulation Of Air Conditioning Heat Exchanger In Service Under Marine Environment, Huang Peng, Jun Wang, Li Qi, Zhidong Wu Apr 2023

Atmospheric Corrosion Simulation Of Air Conditioning Heat Exchanger In Service Under Marine Environment, Huang Peng, Jun Wang, Li Qi, Zhidong Wu

Journal of System Simulation

Abstract: Aiming at the performance degradation of airconditioner heat exchanger caused by serious corrosion under marine environment, an atmospheric corrosion simulation method is studied to analyze and predict the influence on corrosion conditions of marine environment and working condition of air conditioner heat exchanger. From the acquisition of material parameters, the construction the model and the setting of boundary conditions, the atmospheric corrosion simulation process of air conditioner heat exchanger in service under marine environment is systematically introduced, and a method to verify the accuracy of the simulation model by using an artificially accelerated environmental test chamber is provided. From …


A Molecular Dynamics Study Of Atomic Diffusion Effects On Thermomechanical Properties Applying Laser Additive Alloying Process For The Cantor High Entropy Alloy, Mathew Farias, Han Hu, Shanshan Zhang, Jianzhi Li, Ben Xu Apr 2023

A Molecular Dynamics Study Of Atomic Diffusion Effects On Thermomechanical Properties Applying Laser Additive Alloying Process For The Cantor High Entropy Alloy, Mathew Farias, Han Hu, Shanshan Zhang, Jianzhi Li, Ben Xu

Manufacturing & Industrial Engineering Faculty Publications

High entropy alloys (HEAs) can be manufactured in many conventional ways, but it becomes difficult to fabricate heterogeneous materials and structures. The Selective Laser Melting (SLM) method generally melts pure elemental powders or prefabricated alloy powders without an alloying process. In-situ alloying in SLM, which is also called Laser Additive Alloying (LAA), using pure elemental powders becomes a promising method for creating HEA with heterogeneous structures. However, the effect of the diffusion of elements in the molten pool on the formation of HEA remains unclear. In this paper, the well-discussed Cantor HEA was studied in an in-situ alloying situation, where …


Urban Public Transportation Planning With Endogenous Passenger Demand, Yifei Sun Apr 2023

Urban Public Transportation Planning With Endogenous Passenger Demand, Yifei Sun

Dartmouth College Ph.D Dissertations

An effective and efficient public transportation system is crucial to people's mobility, economic production, and social activities. The Operations Research community has been studying transit system optimization for the past decades. With disruptions from the private sector, especially the parking operators, ride-sharing platforms, and micro-mobility services, new challenges and opportunities have emerged. This thesis contributes to investigating the interaction of the public transportation systems with significant private sector players considering endogenous passenger choice. To be more specific, this thesis aims to optimize public transportation systems considering the interaction with parking operators, competition and collaboration from ride-sharing platforms and micro-mobility platforms. …


Nonconvex Optimization For Statistical Learning With Structured Sparsity, Chengyu Ke Apr 2023

Nonconvex Optimization For Statistical Learning With Structured Sparsity, Chengyu Ke

Operations Research and Engineering Management Theses and Dissertations

Sparse learning problems, known as feature selection problems or variable selection problems, are a popular branch in the field of statistical learning. When faced with a dataset with only a few observations but a large number of features, we are interested in extracting the most useful features automatically by solving an optimization problem. In this dissertation, we start by introducing a novel penalty function as well as an iterative reweighted algorithm to solve the group sparsity problem, a special type of feature selection problems. The penalty function, named group LOG, shows a better ability to recover the ground-truth compared to …


Experimental Investigation Of Self-Compacting Concrete With Recycled Concrete Aggregate, Sayed Ahmed, Ayman El-Zohairy, Ahmed S. Eisa, Mohamed Abd El-Aziz Badran Mohamed Mar 2023

Experimental Investigation Of Self-Compacting Concrete With Recycled Concrete Aggregate, Sayed Ahmed, Ayman El-Zohairy, Ahmed S. Eisa, Mohamed Abd El-Aziz Badran Mohamed

Faculty Publications

Due to the depletion of natural aggregates and raw materials for contemporary construction, the construction and demolition waste existing in old concrete structures is an imperative problem. Cutting down on exploiting natural aggregates and reusing construction and demolition waste in the concrete industry are solutions to this problem. This paper investigated the replacement of natural coarse aggregate (NCA) with recycled concrete aggregates (RCA) with different ratios (0%, 50%, 75%, and 100%) in producing self-compacting concrete (SCC). Different components of supplementary cementitious materials (SCMs), such as nano-silica (NS), fly ash (FA), and metakaolin (MK), as well as PVA fibers, were incorporated …


Obstacle Avoidance And Simulation Of Carrier-Based Aircraft On The Deck Of Aircraft Carrier, Junxiao Xue, Xiangyan Kong, Bowei Dong, Hao Tao, Haiyang Guan, Lei Shi, Mingliang Xu Mar 2023

Obstacle Avoidance And Simulation Of Carrier-Based Aircraft On The Deck Of Aircraft Carrier, Junxiao Xue, Xiangyan Kong, Bowei Dong, Hao Tao, Haiyang Guan, Lei Shi, Mingliang Xu

Journal of System Simulation

Abstract: A predictive depth deterministic policy gradient (PDDPG) algorithm is proposed by combining the least squares method with deep deterministic policy gradient(DDPG) for the problems of strong randomness, poor real-time performance, and slow planning speed by obstacle avoidance on aircraft carrier deck. The short-term trajectory of dynamic obstacles on the deck is predicted by the least square method. DDPG is used to provide agents with the ability to learn and make decisions in continuous space by the short-term trajectory of dynamic obstacles. The reward function is set based on the artificial potential field to improve the convergence speed and accuracy …


Lightweight Webvr Real-Time Simulation Of Large-Scale Fire Scenario In Metro, Yang Li, Huijuan Zhang, Chenchen Ge, Kang Xie, Zhuang Li, Jinyuan Jia Mar 2023

Lightweight Webvr Real-Time Simulation Of Large-Scale Fire Scenario In Metro, Yang Li, Huijuan Zhang, Chenchen Ge, Kang Xie, Zhuang Li, Jinyuan Jia

Journal of System Simulation

Abstract: Large-scale fire simulation requires a huge amount of calculation and excellent rendering capabilities, which poses a challenge to the realization of a real-time online fire simulation system on the Web. A lightweight Web-based real-time simulation technology framework for subway station fire is proposed. Based on the simplification of calculation formulas in the field of fire safety and the analysis of the impact of smoke prevention facilities in subway stations, a two-stage smoke diffusion model based on smoke bay is proposed to achieve the smoke diffusion trend calculation; a Web-side multi-granularity particle emitter framework at the smoke bay level is …


Learning-Based High-Performance Algorithm For Long-Term Motion Prediction Of Fluid Flows, Jingyuan Zhu, Huimin Ma, Jian Yuan Mar 2023

Learning-Based High-Performance Algorithm For Long-Term Motion Prediction Of Fluid Flows, Jingyuan Zhu, Huimin Ma, Jian Yuan

Journal of System Simulation

Abstract: Simulating the dynamics of fluid flows accurately and efficiently remains a challenging task nowadays, and traditional fluid simulation methods consume large computational resources to obtain accurate results. Deep learning methods have developed rapidly, which makes data-based fluid simulation and generation possible. In this paper, a motion prediction algorithm for long-term fluid simulation is proposed, which is based on a density field with a single frame and a previous velocity field of a sequence. The model focuses on matching the velocity and density fields predicted by the neural network with the simulated data based on the Navier-Stokes equation …