Engineering Commons^™

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, …

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 …

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 …

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 …

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 …

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 …

Joining Wood Plastic Composites Using A New Self-Reacting Friction Stir Toolset – A Comparative Study, Mohamed Moustafa Elmeligy Mr, Ahmed Elkassas, Ammar H. Elsheikh

Journal of Engineering Research

Wood-plastic composite (WPC) is an environmentally friendly material that promotes the recycling of wood and plastic waste. However, there is a notable lack of research on methods for joining these materials. This study introduces an innovative approach using a uniquely designed self-reacting friction stir toolset specifically for WPC joining. The performance of this new toolset is evaluated against prior research that employed a hot-shoe friction stir welding toolset on a WPC with a different composition. The study focuses on key parameters such as revolutions per welding line (RPWL), rotational speed, and welding speed, emphasizing their critical impact on the quality …

Gaze Tracking Embedded Collaborative Robots For Automated Metrology And Reverse Engineering, Sachithra H. Karunathilake, Md Shahriar Forhad, Zhaohui Geng

Manufacturing & Industrial Engineering Faculty Publications

Conventional geometric metrology, or three-dimensional (3D) scanning, and reverse engineering heavily rely on the experience of the operators. With an increasing need for automation, robot arms have been adopted for this task. However, due to the large variety of parts and designs, automated path planning could provide a scanning solution that may overlook the critical area, which could potentially deteriorate the scan results. This article explores the integration of collaborative robotics (cobots) with eye-tracking technology to improve the autonomous 3D scanning process. The primary objective of this study is to enhance the accuracy and efficiency of cobots in 3D scanning, …

Data-Driven Roughness Estimation Of Additively Manufactured Samples Using Build Angles, Jose Galarza, Jose Barron Jr., Farid Ahmed, Jianzhi Li

Manufacturing & Industrial Engineering Faculty Publications

Achieving control of Laser Powder Bed Fusion (L-PBF) over the quality of the print is the main motivation for finding an optimum set of parameters in the process. Surface roughness is one of the characteristics of the print that impacts the performance of the desired functionality. This research focus is to relate the build angle with the surface roughness on the L-PBF printed specimens and utilize machine learning methods for roughness estimation of geometric features with varying build angles. The EOS M290 L-PBF printer was used to print Inconel-718 coupons using standard process parameters while varying build angles from 20 …

Enhancing Resilience In Complex Energy Systems Through Real-Time Anomaly Detection: A Systematic Literature Review, Ali Aghazadeh Ardebili, Oussama Hasidi, Ahmed Bendaouia, Adem Khalil, Sabri Khalil, Dalila Luceri, El Hassan Abdelwahed, Sara Qassimi, Antonio Ficarella

Manufacturing & Industrial Engineering Faculty Publications

As real-time data sources expand, the need for detecting anomalies in streaming data becomes increasingly critical for cutting edge data-driven applications. Real-time anomaly detection faces various challenges, requiring automated systems that adapt continuously to evolving data patterns due to the impracticality of human intervention. This study focuses on energy systems (ES), critical infrastructures vulnerable to disruptions from natural disasters, cyber attacks, equipment failures, or human errors, leading to power outages, financial losses, and risks to other sectors. Early anomaly detection ensures energy supply continuity, minimizing disruption impacts, an enhancing system resilience against cyber threats. A systematic literature review (SLR) is …

An Agent-Based Approach For Designing A Sustainable Supplier Selection In Stochastic Environment: A Simulation Study, Sheida Etemadidavan

Engineering Management & Systems Engineering Theses & Dissertations

In the 21st century, businesses are constantly striving for competitive advancement and increasing their economic performance in the rapidly changing market. Collaboration with other businesses and partnerships with them are becoming more common. As such, businesses are starting to invest in finding the right partners to stay competitive in an ever-changing business landscape. Suppliers play a crucial role in businesses' decision-making as they provide the materials, goods, and services necessary for a company to operate and succeed. Therefore, their selection, management, and relationship must be carefully considered to ensure optimal performance and profitability. A sustainable framework in a business's relationship …

An Integrated Theoretical Socio-Technical Framework For Implementing Service Robots’ Integration In Healthcare, Sujatha Alla

Engineering Management & Systems Engineering Theses & Dissertations

Healthcare workers, either clinical or non-clinical, are obligated to serve patients. However, lack of a sufficient number of professionals leads to burnout, severe stress, and, consequently, decreased quality of services. In this context, very few countries have been successful in employing service robots to perform dull, dirty, and/or dangerous tasks related to patient wellbeing/healthcare, while most countries are still skeptical about it. As robotics advances, there is an opportunity for healthcare to take advantage of this technology to reduce personnel workload and to reduce the possibility of exposure to contagious pathogens. However, healthcare is a vulnerable environment and requires critical …

Prediction Of Tool Wear And Surface Finish Using Anfis Modelling During Turning Of Carbon Fiber Reinforced Plastic (Cfrp) Composites, Anil K. Srivastava, Md. Mofakkirul Islam

Manufacturing & Industrial Engineering Faculty Publications

Carbon fiber-reinforced plastics (CFRP) are widely used in various industries due to their high strength to weight ratio, corrosion resistance, durability, and excellent thermo-mechanical properties. The machining of CFRP composites has always been a challenge for the manufacturers. In this study, CNC turning operation with coated carbide tool is used to machine a specific CFRP and the relationship between the cutting parameters (Speed, Feed, Depth of Cut) and response parameters (Vibration, Surface Finish, Cutting Force and Tool Wear) are investigated. An adaptive-network-based fuzzy inference system (ANFIS) model with two multi-input–single-output (MISO) system has been developed to predict the tool wear …

Exploring Human Responses In Conversations With Ai Entities, Phillip Semenov, Miguel Coronado

College of Engineering Summer Undergraduate Research Program

This study argues that while AI systems have become increasingly advanced, they still evoke distinct emotional responses compared to human interactions, potentially limiting their effectiveness in emotionally-driven environments. We used the Emotiv Insight brain-computer interface to monitor participants' emotional responses during controlled interactions with both AI systems and other humans. Key emotional metrics, such as arousal, focus, and stress, were recorded in real time, providing a detailed picture of the emotional dynamics at play in each type of interaction. Participants exhibited higher levels of excitement, stress, and focus during interactions with humans compared to AI systems, while other emotions like …

Inexact Methods For Large-Scale Stochastic Programming, Niloofar Fadavi

Operations Research and Engineering Management Theses and Dissertations

This dissertation addresses the development of inexact methods for solving large-scale stochastic programming problems, with a focus on two-stage and multistage settings. Stochastic programming is a robust approach for managing uncertainty in decision-making, with applications across various domains like supply chain management, power systems, and logistics. However, solving large-scale stochastic programming problems, especially those with a nonlinear structure, is computationally challenging due to the high-dimensional nature of uncertainties and the need for efficient optimization techniques.

This work introduces novel inexact proximal bundle algorithms designed to solve two-stage stochastic quadratic programming problems. The proposed methods utilize dual-based and partition-based approaches to …

A Systems Theory-Based Framework For Uncertainty In Complex System Governance, Teresa Anne Crater

Engineering Management & Systems Engineering Theses & Dissertations

Complex systems are all around. A complex system is a system whose collective behavior is more than the behavior exhibited by the individual parts. Such a system is characterized by an exponential increase in information, complexity, ambiguity, emergence, and high levels of uncertainty (Jaradat, 2015). Uncertainty is intrinsic to complex systems. Uncertainty refers to epistemic situations involving imperfect or unknown information. Uncertainty can refer to the chance of certain anticipated outcomes occurring, or it can refer to the unknown events that are not foreseeable as to when or if one might occur. It applies to predictions of future events, to …

An Interaction Between Mental Integration And Levels Of Automation: An Analytic Approach Applying Systems Factorial Technology, Shelby Kate Scarbrough Long

Psychology Theses & Dissertations

Automation has become nearly ubiquitous in modern society, supporting human performance in personal and professional tasks. Recent works have begun to focus on human-automation performance in speeded perceptual-cognitive tasks using workload capacity analysis, a novel mathematical analysis to measure efficiency of a human-automation team. The present dissertation examined how level of automation and demand for mental integration of information influence human-automation efficiency. Participants performed a multi-element probabilistic decision task with or without the assistance of an automated aid where level of automation and task demand were manipulated. Experiment 1 employed a mixed design with Automation (present vs. absent) and Task …

Constrained Assortment Optimization Under The Cross-Nested Logit Model, Cuong Le, Tien Mai

Research Collection School Of Computing and Information Systems

We study the assortment optimization problem under general linear constraints, where the customer choice behavior is captured by the cross-nested logit model. In this problem, there is a set of products organized into multiple subsets (or nests), where each product can belong to more than one nest. The aim is to find an assortment to offer to customers so that the expected revenue is maximized. We show that, under the cross-nested logit model, the unconstrained assortment problem is NP-hard even when there are only two nests, and the problem is generally NP-hard to approximate to any constant factors. To tackle …

A Theoretical Framework For Resilience In Complex System Governance (Csg), Susan A. Caskey

Engineering Management & Systems Engineering Theses & Dissertations

This dissertation addresses a critical gap in resilience research within complex systems by developing a theoretical framework for governance resilience—an underexplored area despite governance's crucial role in maintaining system resilience. Using the Complex System Governance (CSG) framework (Keating, Katina, Chesterman, et al., 2022; Keating & Katina, 2019), resilience is conceptualized as a system's ability to absorb disturbances while sustaining performance and enabling adaptive transformation. This involves three main capabilities: persistence, adaptability, and transformation in response to both internal and external pressures.

Through a constructivist grounded theory approach involving iterative coding, memoing, and theory development, this study inductively constructs a governance …

Final Report - An Interactive System For Training And Assisting Bridge Inspectors In Inspection Video Data Analytics, Genda Chen, Ruwen Qin, Mohammad Hossein Afsharmovahed, Kevin Lai, Ritesh Sharma

Project WD-4

This project aims to develop an interactive, web-based system to assist bridge inspectors in machine learning and video analytics for a rapid condition state assessment of bridge elements in accordance with the 2019 Manual for Bridge Element Inspection. Referred to BridgeNet, the system includes region-based convolutional neural network (RCNN) models for bridge element and defect segmentation and an inspection video analytic tool that is integrated into a unified graphical user interface (GUI). It provides users with an image-based testbed of modulated RCNN models. The BridgeNet has evolved in four phases: (1) backend and frontend framework setups, (2) Mask-RCNN-based bridge segmentation, …

Fatigue-Resistant Mechanoresponsive Color-Changing Hydrogels For Vision-Based Tactile Robots, Jiabin Liu, Wei Li, Yu She, Sean Blanchard, Shaoting Lin

School of Industrial Engineering Faculty Publications

Mechanoresponsive color-changing materials that can reversibly and resiliently change color in response to mechanical deformation are highly desirable for diverse modern technologies in optics, sensors, and robots; however, such materials are rarely achieved. Here, a fatigue-resistant mechanoresponsive color-changing hydrogel (FMCH) is reported that exhibits reversible, resilient, and predictable color changes under mechanical stress. At its undeformed state, the FMCH remains dark under a circular polariscope; upon uniaxial stretching of up to six times its initial length, it gradually shifts its color from black, to gray, yellow, and purple. Unlike traditional mechanoresponsive color-changing materials, FMCH maintains its performance across various strain …

Finite Element Modeling And Analysis Of Rc Shear Walls With Cutting-Out Openings, Islam M. Saad, Mohamed Emara, Ayman El-Zohairy, Sherif El-Beshlawy

Faculty Publications

In recent decades, reinforced concrete (RC) shear walls have been one of the best structural solutions to resist lateral load in high-rise buildings. Shear wall openings are essential for preparations and architectural requirements, which weaken the wall, reducing bearing capacity, energy absorption, and stiffness while also causing stress concentrations. This paper presents a comprehensive finite element (FE) investigation of the behavior and performance of RC shear walls with openings and subjected to lateral loads. The study aims to evaluate the influence of various parameters, such as opening location, size, wall aspect ratio, axial load, and concrete strength, which affect the …

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 …

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 …

Research On Digital Twin System Of Rockshaft Hoist, Baiting Zhao, Jianguo Shi, Xiaofen Jia

Journal of System Simulation

Abstract: In order to solve the problem of low intelligence and digitization of the current mine hoisting system, a method based on DT for digital modeling, 3D visualization, and virtual real interaction of shaft hoisting machines is proposed. Aiming at the rockshaft hoist system, based on the digital twin five dimensional model framework, we analyze the operating mechanism of the equipment, and model the fully physical digital system of the rockshaft hoist. By constructing multidimensional multi-scale models and multidimensional heterogeneous data models, twin digital scenes are constructed, and virtual real mapping technology is combined to achieve dynamic mapping and virtual …

A Multimodal Residual Spatial-Temporal Fusion Model Based On Automatic Sleep Classification, Yecai Guo, Shuang Tong

Journal of System Simulation

Abstract: Highly accurate sleep staging plays a crucial role in correctly assessing sleep conditions. Aiming at the problem that the existing convolutional network cannot obtain the topological characteristics of physiological signals, a sleep staging algorithm based on multi-modal residual spatio-temporal fusion is proposed. Time-frequency images and spatio-temporal images are obtained using short-time Fourier transform and adaptive map convolution, which are converted into high-dimensional feature vectors; lightweight interaction of feature information flow is realized through time-frequency feature and spatiotemporal feature extraction modules; the feature enhancement fusion module fuses feature information to outputs sleep staging results. The results show that the model …

Research On Autonomous Decision-Making In Air-Combat Based On Improved Proximal Policy Optimization, Dianwei Qian, Hongmin Qi, Zhen Liu, Zhiming Zho, Jianqiang Yi

Journal of System Simulation

Abstract: To address the problems of high information redundancy and slow convergence speed of traditional reinforcement learning in air-combat autonomous decision-making applications, a proximal policy optimization air-combat autonomous decision-making method, based on dual observation and composite reward is proposed. A dual observation space, which contains interaction information as the main information and individual feature information as a supplement, was designed to reduce the influence of redundant battlefield information on the training efficiency of the decision model. A composite reward function combining result reward and process reward was designed to improve convergence speed. The generalized advantage estimator was applied in the …

An Intelligent Adversaries Behavior Simulation Technology Based On Improved Behavior Trees, Fang Zhou, Bo Fan, Xiaoyi Liu, Yishan Ding, Ningxin Zhang, Yachao Shao, Xiaoyu Zhai

Journal of System Simulation

Abstract: Intelligent algorithm/intelligent platform/intelligent system intelligence capability testing and evaluation need to solve high-level intelligent opponent simulation problems, an intelligent opponent behavior simulation technology based on improved behavior tree is proposed. Four types of behavior tress nodes are designed, including behavior control, combat tasks, behavior actions, and execution condition node. Five atomic behavior actions and parameters are established, including maneuver, reconnaissance and early warning, command and decision-making, firepower strike, and electronic interference node. Five atomic condition nodes are provided, including target selection, weapon launch, and incoming weapon judgment node. The intelligent adversarial behavior simulation system is designed, including a behavior …

Study On Invulnerability Of Urban Rail Network Considering Sum Of The Neighbors Degree, Shuqing Li, Yixiao Song, Guojian Zhong

Journal of System Simulation

Abstract: In order to solve the problem of network cascade paralysis caused by urban rail station or line failure, considering the influence of the first-order neighborhood of network nodes, the load distribution impedance coefficient is proposed based on the nonlinear capacity load model, and a nonlinear capacity load optimization model considering the sum of the neighbors degree is constructed. By optimizing load structure, the alternative probability of nodes during load redistribution is adjusted to reduce the number of node failures in the cascading process, thereby the rail network invulnerability is improved. Taking Chongqing rail network as an example, the rail …

Multi-Step Information Aided Q-Learning Path Planning Algorithm, Yuelong Wang, Songyan Wang, Tao Chao

Journal of System Simulation

Abstract: To improve the path planning capability of mobile robots in a static environment and solve the problem of slow convergence of the traditional Q-learning algorithm in path planning, this paper proposes a multi-step information-aided Q-learning improvement algorithm. Using the multi-step information of greedy action in ε -greedy strategy and length of the historical optimal path to update the eligibility traces, which makes the effective eligibility traces work continuously in the iteration of the algorithm and solves the loop traps that may fall into with the preserved multi-step information; using the local multiflower pollination algorithm to initialize the Q-value table …