Reliability Modeling And Improvement Of Critical Infrastructures: Theory, Simulation, And Computational Methods,
2023
University of Arkansas, Fayetteville
Reliability Modeling And Improvement Of Critical Infrastructures: Theory, Simulation, And Computational Methods, José Carlos Hernández Azucena
Graduate Theses and Dissertations
This dissertation presents a framework for developing data-driven tools to model and improve the performance of Interconnected Critical Infrastructures (ICIs) in multiple contexts. The importance of ICIs for daily human activities and the large volumes of data in continuous generation in modern industries grant relevance to research efforts in this direction. Chapter 2 focuses on the impact of disruptions in Multimodal Transportation Networks, which I explored from an application perspective. The outlined research directions propose exploring the combination of simulation for decision-making with data-driven optimization paradigms to create tools that may provide stakeholders with optimal policies for a wide array …
Optimal Route Planning Using Computer Simulation In The Context Of Distributor-To-Consumer Supply Network,
2023
University of Texas at El Paso
Optimal Route Planning Using Computer Simulation In The Context Of Distributor-To-Consumer Supply Network, Miriam Aguilera Nava
Open Access Theses & Dissertations
Effective route planning for distribution centers is a multifaceted challenge crucial tobusiness success, as it directly impacts time and cost savings while enhancing overall delivery efficiency. Oversight of proper planning can lead to problems and inefficiencies in the distribution process. Hence, this work undertakes a comparative experiment of two delivery strategies in a distributor-to-consumer supply network. While the first strategy investigates the delivery process by zip area, the second strategy considers the clustering of the areas for more streamlined delivery fulfillment. The effectiveness of the delivery process is gauged based on a set of metrics, including total distance traveled, average …
Finite Element Modeling And Analysis Of Perforated Steel Members Under Blast Loading,
2023
East Texas A&M University
Finite Element Modeling And Analysis Of Perforated Steel Members Under Blast Loading, Mahmoud T. Nawar, Ayman El-Zohairy, Ibrahim T. Arafa
Faculty Publications
Perforated steel members (PSMs) are now frequently used in building construction due to their beneficial features, including their proven blast-resistance abilities. To safeguard against structural failures from explosions and terrorist threats, perforated steel beams (PSBs) and perforated steel columns (PSCs) offer a viable alternative to traditional steel members. This is attributed to their impressive energy absorption potential, a result of their combined high strength and ductile behavior. In this study, numerical examinations of damage assessment under the combined effects of gravity and blast loads are carried out to mimic real-world scenarios of external explosions close to steel structures. The damage …
Gaze Tracking Embedded Collaborative Robots For Automated Metrology And Reverse Engineering,
2023
The University of Texas Rio Grande Valley
Gaze Tracking Embedded Collaborative Robots For Automated Metrology And Reverse Engineering, Sachithra H. Karunathilake
Theses and Dissertations
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 study 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 …
Barriers To Integrating Magnetic Resonance Imaging Systems In Emergency Medical Service Ambulances For Stroke Care,
2023
Clemson University
Barriers To Integrating Magnetic Resonance Imaging Systems In Emergency Medical Service Ambulances For Stroke Care, Arvind Kolangarakath
All Theses
Stroke is a life-threatening condition that can cause permanent damage by stopping blood flow in the brain. Quick and precise intervention is imperative, as every second lost increases tissue deterioration and impacts patient outcomes. Several technological advancements such as Magnetic Resonance Imaging (MRI), have revolutionized stroke care by enabling more accurate and quicker diagnoses in hospitals. Portable head MRI scanners with lower magnetic fields are a recent innovation capable of providing neuroimaging at the point of care within hospital settings. Integrating such a device into ambulances could potentially enhance stroke care during transit, facilitating prompt diagnosis and prognosis. However, few …
Neural Airport Ground Handling,
2023
Eindhoven University of Technology
Neural Airport Ground Handling, Yaoxin Wu, Jianan Zhou, Yunwen Xia, Xianli Zhang, Zhiguang Cao, Jie Zhang
Research Collection School Of Computing and Information Systems
Airport ground handling (AGH) offers necessary operations to flights during their turnarounds and is of great importance to the efficiency of airport management and the economics of aviation. Such a problem involves the interplay among the operations that leads to NP-hard problems with complex constraints. Hence, existing methods for AGH are usually designed with massive domain knowledge but still fail to yield high-quality solutions efficiently. In this paper, we aim to enhance the solution quality and computation efficiency for solving AGH. Particularly, we first model AGH as a multiple-fleet vehicle routing problem (VRP) with miscellaneous constraints including precedence, time windows, …
A System Theoretic Process Analysis Framework And Model Based Approach For Resilient Space Architecture Design,
2023
Air Force Institute of Technology
A System Theoretic Process Analysis Framework And Model Based Approach For Resilient Space Architecture Design, Eric T. Sommer
Theses and Dissertations
As the capabilities provided by space-based systems offer significant contributions toward defense applications, potential adversaries stand to gain significant value in disrupting them. Therefore, the United States must pursue the development and operation of resilient space architectures, capable of delivering capabilities in the face of disruptions. To support this development, systems engineering methods require innovation to effectively ensure design of complex space architectures to meet their objectives. This thesis recommends and demonstrates a System-Theoretic Process Analysis (STPA) framework to qualitatively analyze space architectures. The analysis outputs identify design considerations, requirements, and constraints required for resilience. To enable a model-based systems …
Automated Usability Evaluation Utilizing Log Files And Data Mining Techniques.,
2023
University of Louisville
Automated Usability Evaluation Utilizing Log Files And Data Mining Techniques., Sima Shafaei
Electronic Theses and Dissertations
Usability evaluation is one of the essential aspects of software production. This evaluation should be done during the entire life cycle of a software application, from pre-production to production and post-production. However, the collection and evaluation of usability data can be a very challenging, time-consuming, and expensive task to be conducted manually, particularly for certain types of products and working conditions. These challenges may include the need to recruit participants fully engage and motivate them during evaluation, and factor in environmental conditions. Other challenges may include collecting data in real-world environments, especially when the users are geographically dispersed, minimizing evaluator …
Task Optimization Utilizing Digital Transformation Concepts - Automation Project Execution Via Agile Methodology,
2023
Florida Institute of Technology
Task Optimization Utilizing Digital Transformation Concepts - Automation Project Execution Via Agile Methodology, Anthony Steven Maiello
Theses and Dissertations
Task Optimization via the use of automated process improvements is becoming more widespread as more industries lean into the concepts surrounding digital transformation. This shift also necessitates a complementary adaptation in project management methodologies to support the rapid and ever-changing environment, requirements, and innovations. This thesis examines the effectiveness of Agile methodology in managing digital automation projects, with a specific focus placed on process improvements with systems engineering. It accomplished this by contrasting the original model, designed and derived utilizing traditional project management techniques, with the proposed model which is a direct result of the application of Agile project practices. …
Design Space Visualization And Exploration For Many Goal Problems Under Uncertainity,
2023
Florida Institute of Technology
Design Space Visualization And Exploration For Many Goal Problems Under Uncertainity, Niharika Balaji
Theses and Dissertations
ABSTRACT
Designing a complex engineered system is challenging due to many conflicting goals, uncertainties, and multiple interactions. Traditional optimization approaches often yield single-point solutions, which may not be suitable for early design stages due to their susceptibility to changes in conditions and uncertainties. To address this challenge, a satisficing approach is employed. This approach enables designers to effectively navigate the design space and identify satisficing solutions that balance conflicting goals in the face of uncertainties and changes in conditions. From a systems design perspective, we view design as an iterative process that involves making informed decisions based on available information …
A Poisson-Based Distribution Learning Framework For Short-Term Prediction Of Food Delivery Demand Ranges,
2023
Singapore Management University
A Poisson-Based Distribution Learning Framework For Short-Term Prediction Of Food Delivery Demand Ranges, Jian Liang, Jintao Ke, Hai Wang, Hongbo Ye, Jinjun Tang
Research Collection School Of Computing and Information Systems
The COVID-19 pandemic has caused a dramatic change in the demand composition of restaurants and, at the same time, catalyzed on-demand food delivery (OFD) services—such as DoorDash, Grubhub, and Uber Eats—to a large extent. With massive amounts of data on customers, drivers, and merchants, OFD platforms can achieve higher efficiency with better strategic and operational decisions; these include dynamic pricing, order bundling and dispatching, and driver relocation. Some of these decisions, and especially proactive decisions in real time, rely on accurate and reliable short-term predictions of demand ranges or distributions. In this paper, we develop a Poisson-based distribution prediction (PDP) …
Application Of Virtual-Real Simulation In Military Field,
2023
College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410000, China
Application Of Virtual-Real Simulation In Military Field, Ziquan Mao, Jialong Gao, Jianxing Gong, Quan Liu
Journal of System Simulation
Abstract: The definition and content of the virtual-real simulation are presented. According to different technical ideas, the development status and existing problems of virtual-real simulation are summarized from three aspects of digital twin, live-virtual-constructive (LVC) simulation, and parallel system. The similarities and differences, as well as the advantages and disadvantages of the three methods are analyzed and compared, and their main application fields are discussed. In order to deal with difficulties encountered in military training, operational tests, equipment development, and equipment maintenance, a solution based on virtual-real simulation is proposed by means of theoretical guidance, case comparison, and transfer and …
Research On Multi-Process Product Quality Prediction Based On Improved Bilstm,
2023
School of Mechanical Engineering, Shenyang University, Shenyang 110044, China
Research On Multi-Process Product Quality Prediction Based On Improved Bilstm, Tianrui Zhang, Yuting Liu, Yike Wang
Journal of System Simulation
Abstract: In response to the complex manufacturing process of multi-process products, a multi-process product quality prediction model based on the kernel principal component analysis (KPCA) - and improved sparrow search algorithm (ISSA) optimized bi-directional long short term memory (BiLSTM) was proposed to address the uncertain factors that affect product quality, while improving the capacity for each process and ensuring the stability, in multi-process production. Firstly, KPCA was used for data preprocessing, and a kernel function was established on the basis of principal component analysis together with kernel methods. As redundant features were removed through dimension reduction, an improved Gaussian mutation …
Adaptive Robust Trajectory Tracking Control For Nsv With Multiple Stochastic Disturbances,
2023
Key Laboratory of Applied Mathematics and Artificial Intelligence Mechanism, Hefei University, Hefei 230601, China; Hefei Comprehensive National Science Center, Institute of Artificial Intelligence, Hefei 230088, China
Adaptive Robust Trajectory Tracking Control For Nsv With Multiple Stochastic Disturbances, Xiaohu Yan, Yuwu Yao, Yuhua Wu, Jiangxin Xu
Journal of System Simulation
Abstract: A stochastic control scheme of adaptive robust trajectory tracking is proposed for near space vehicle (NSV) with stochastic noise input disturbances, Poisson random fluctuation disturbances, and control input saturation. The effective tracking of the height and speed reference signals is realized. For the outer loop trajectory control, the robust stochastic controller is designed for the height subsystem and the speed subsystem respectively. Additionally, the required attitude angle reference signals for the inner loop attitude control are obtained by converting the equivalent control input via numerical calculation. For the inner loop attitude control problems, an adaptive robust stochastic control scheme …
Image Semantic Segmentation Algorithm Based On Improved Deeplabv3+,
2023
Liaoning General Aviation Academy, Shenyang Aerospace University, Shenyang 110034, China; College of Electronic Information Engineering, Shenyang Aerospace University, Shenyang 110034, China
Image Semantic Segmentation Algorithm Based On Improved Deeplabv3+, Weiping Zhao, Yu Chen, Song Xiang, Yuanqiang Liu, Chaoyue Wang
Journal of System Simulation
Abstract: Mainstream image semantic segmentation networks currently face problems such as incorrec segmentation, discontinuous segmentation, and high model complexity, which cannot be flexibly and efficiently deployed in practical scenarios. To this end, an image semantic segmentation network that optimizes the DeepLabv3+ model is designed by comprehensively considering the network parameters, prediction time, and accuracy. The lightweight EfficientNetv2 is adopted to extract backbone network features and improve parameter utilization. In the atrous spatial pyramid pooling module, the mixed strip pooling is utilized to replace the global average pooling, and a depthwise separable dilated convolution is introduced to reduce parameters and improve …
Intercell Dynamic Scheduling Method Based On Deep Reinforcement Learning,
2023
University of Shanghai for Science and Technology, Shanghai 200093, China
Intercell Dynamic Scheduling Method Based On Deep Reinforcement Learning, Jing Ni, Mengke Ma
Journal of System Simulation
Abstract: In order to solve the intercell scheduling problem of dynamic arrival of machining tasks and realize adaptive scheduling in the complex and changeable environment of the intelligent factory, a scheduling method based on a deep Q network is proposed. A complex network with cells as nodes and workpiece intercell machining path as directed edges is constructed, and the degree value is introduced to define the state space with intercell scheduling characteristics. A compound scheduling rule composed of a workpiece layer, unit layer, and machine layer is designed, and hierarchical optimization makes the scheduling scheme more global. Since double deep …
Analysis Of Autonomous Aerial Refueling Capability Requirements And Key Evaluation
Indicators,
2023
Chinese Flight Test Establishment, Xi'an 710089, China; Key Laboratory of Flight Simulation Aeronautical Technology of AVIC, Xi'an 710089, China
Analysis Of Autonomous Aerial Refueling Capability Requirements And Key Evaluation Indicators, Quan Zou, Yixin Hua, Zhu Shao, Wenbi Zhao
Journal of System Simulation
Abstract: From the perspective of flight tests, how to evaluate the autonomous aerial refueling (AAR) capability and select key indicators for evaluation is a key problem to be solved for AAR trials. The standards requirements of aerial refueling and manned aircraft aerial refueling experience in China and abroad are analyzed. The total capability of AAR is studied, and key evaluation indicators in the AAR whole process including rendezvous, formation, docking, refueling, and disengagement are proposed. The evaluation method is demonstrated in both numerical simulation and hardware-in-loop test environments. Finally, the key indicators affecting the docking success of AAR are analyzed, …
Imitative Generation Of Optimal Guidance Law Based On Reinforcement Learning,
2023
Beijing Simulation Center, Beijing 100854, China
Imitative Generation Of Optimal Guidance Law Based On Reinforcement Learning, Zhengxuan Jia, Tingyu Lin, Yingying Xiao, Guoqiang Shi, Hao Wang, Bi Zeng, Yiming Ou, Pengpeng Zhao
Journal of System Simulation
Abstract: Under the background of high-speed maneuvering target interception, an optimal guidance law generation method for head-on interception independent of target acceleration estimation is proposed based on deep reinforcement learning. In addition, its effectiveness is verified through simulation experiments. As the simulation results suggest, the proposed method successfully achieves head-on interception of high-speed maneuvering targets in 3D space and largely reduces the requirement for target estimation with strong uncertainty, and it is more applicable than the optimal control method.
A Cellular Automata Model For Simulating Ships Passing Through Waterways With Alternating Wide And Narrow Sections,
2023
Transportation Engineering College, Dalian Maritime University, Dalian 116026, China
A Cellular Automata Model For Simulating Ships Passing Through Waterways With Alternating Wide And Narrow Sections, Yulong Sun, Jianfeng Zheng, Jiaxuan Han, Chao Li
Journal of System Simulation
Abstract: For improving the traffic efficiency of wide and narrow alternating waterways, considering Kiel Canal as an example, according to the structural characteristics of Kiel Canal with alternating width and narrow sections, a two-way ship traffic flow cellular automata model is established, and the simulation of ships passing through Kiel Canal is studied. Cellular space is set up according to the actual structure of Kiel Canal, and the evolution rules are set up based on the fixed block theory and moving block theory. In particular, due to the structure of Kiel Canal, large ships cannot pass simultaneously in the narrow …
Rolling Bearing Fault Diagnosis Based On Weighted Domain Adaptive
Convolutional Neural Network,
2023
Engineering Research Center of Internet of Things Technology Appliations Ministry of Education, Jiangnan University, Wuxi 214122, China
Rolling Bearing Fault Diagnosis Based On Weighted Domain Adaptive Convolutional Neural Network, Wenfeng Zhang, Zhichao Zhu, Dinghui Wu
Journal of System Simulation
Abstract: A rolling bearing fault diagnosis method based on a weighted domain adaptive convolutional neural network (WDACNN) is proposed to solve the problem that the data distribution of vibration signals of rolling bearings changes due to workload changes, which leads to poor generalization of fault diagnosis algorithm. In this method, the domain adaptation algorithm is embedded in the convolutional neural network to make the classifier based on the source domain achieve excellent generalization in the target domain, and the weight coefficient is introduced to weight the samples in the source domain to reduce the influence of the class weight deviation. …
