Systems Science Commons^™

Robust Emergency Dispatch Method Considering Dynamic Frequency Security And N-K Contingency, Tao Huang, Zhi Zhang, Yujie Ding, Yanbo Chen, Jing Wang, Wenqian Zhang

Journal of System Simulation

Abstract: To address the risk of system inertia loss and frequency instability caused by grid integration of high-proportioned new energy and unit failures, an N-k robust emergency dispatch method considering dynamic frequency security constraints was proposed. With the consideration of the frequency response characteristics of variable-speed pumped storage, a dynamic frequency response model incorporating variable-speed pumped storage was constructed, and the nadir frequency constraint was established through second-order cone transformation. Information entropy theory was employed to quantify the uncertainty of unit failures, and an uncertainty set considering N-k unit failures was developed. A twostage robust emergency dispatch model considering N-k …

Vibration Control Of Offshore Wind Turbine Towers Based On Eddy Current Nonlinear Energy Sink, Xiangxing Yu, Yandong Zhao, Baolin Zhang

Journal of System Simulation

Abstract: To address the issue of tower vibrations induced by wind loads, which can damage the structure of wind turbines, a vibration control method for monopile offshore wind turbine towers based on an eddy current-nonlinear energy sink (EC-NES) was proposed. The dynamic model of monopile offshore wind turbines based on EC-NES was constructed according to the Euler-Lagrange equation, and based on the output response of FAST software, the unknown parameters of the model and the wind loads were identified in terms of parameters. The optimal parameters of EC-NES stiffness and damping were obtained using PSO. The eddy current damper …

Fault Diagnosis Method For Photovoltaic Systems Based On Multi-Strategy Fusion, Bin Li, Yuchuo Wang

Journal of System Simulation

Abstract: To address the problem of frequent PV system faults, a multimodal fusion fault diagnosis model based on the optimization of the improved lemming algorithm was proposed. The one-dimensional time series signals of PV currents and voltages were converted into two-dimensional images by Markov transformation field, and the spatial features of the original waveforms were mined by using multiscale CNN (MCCNN); BiGRU was used to extract the temporal dynamic features of the original waveforms, and complementary enhancement of the temporal and spatial features was realized by the feature fusion layer. The improved lemming algorithm was innovatively introduced to adaptively optimize …

Numerical Simulations Of Ship Liquid Tank Sloshing Based On Graph Neural Networks, Wenkang Zhang, Xiaofeng Sun, Yiping Zhong, Yong Yin

Journal of System Simulation

Abstract: To address the high consumption of computational resources in simulating ship liquid tank sloshing using computational fluid dynamics simulation methods, a data-driven numerical simulation model was proposed based on graph neural networks. An encoder-processor-decoder framework was employed in the proposed model. The encoder extracted features of fluid particles from the first five time steps. The processor learnt latent motion patterns of fluid and updated features, and the decoder predicted features of particles at subsequent time steps. The processor incorporated a self-attention mechanism to enable dynamic adjacency weight allocation and emphasize the influence of irregular tank wall regions. Training …

Lightweight Assembly Workpiece Detection Algorithm Based On Improved Yolov8, Shuheng Wu, Yongkui Liu, Lin Zhang, Yingying Xiao, Lihui Wang

Journal of System Simulation

Abstract: To address the issues of low recognition accuracy and slow detection speed with existing deep learning-based object detection algorithms for robotic automatic assembly tasks, a lightweight assembly workpiece object detection algorithm based on YOLOv8 was proposed. The PConv was introduced to improve the C2f module, and a new Faster_C2f module was designed to enhance the detection speed of the model. The SIoU loss function was employed to optimize the location prediction accuracy of the CIoU loss function and improve the localization accuracy of small targets. The high-level screening-feature fusion pyramid networks (HS-FPN) structure was used to improve the Neck …

Probing The Mechanisms Of Reinforcement Learning: Reinforcement Learning, Ventral Striatal Astrocytes, And The Dynamic Coordination Of Information Seeking With Learning, Fatih Sogukpinar

McKelvey School of Engineering Graduate Student Theses & Dissertations

While reinforcement learning has been a vital component in artificial intelligence and machine learning, there exist many open questions about its implementations and how to improve them, in both minds and machines. Among these are i) the contribution of non-neuronal cell types to reinforcement learning, and ii) information-seeking behavior during reinforcement learning. In this thesis, we studied these main topics pertaining to reinforcement learning. In the first chapter, we examined the role of astrocytes in reinforcement learning, and in the second, we investigated human information seeking during reinforcement learning. Neurons in the human and animal brain have been known to …

Modeling The Mojave: A Multiphase, Mixed Methods Phenomenological Investigation Of Novice Understanding Of A Complex Ecological System, Nicole Juliana Thomas

UNLV Theses, Dissertations, Professional Papers, and Capstones

This research explores early college science majors’ conceptions of the Mojave Desert ecosystem as a complex system. A multi-level, explanatory sequential mixed methods design was employed to study college science majors’ understanding of the Mojave Desert ecosystem to better inform science pedagogy. The first level, the quantitative phase of the study, consisted of developing a mathematical representation of twelve ecosystem variables present within the Mojave Desert. The second level, the qualitative phase of the study, consisted of phenomenological semi-structured interviews with 23 early college science majors. The findings of this research suggest that the Mojave Desert operates as a complex, …

An Innovative Hdm Model For Assessing Renewable Heat Energy Resources In Utility Energy Systems, Mark Alan Ryan

Dissertations and Theses

Renewable Heat Energy projects exhibit numerous unique, complex, and often conflicting characteristics, including varying project sizes, diverse energy resources, stakeholder demands, and significant challenges in energy conversion applications. Traditionally, cash flow analysis and return on investment are the most widely recognized metrics for evaluating remote energy projects. However, numerous quantitative and qualitative factors influence the overall performance and success of Renewable Heat Energy System (RHES) projects. A comprehensive approach using advanced tools is essential for assessing the factors and criteria that significantly impact these projects.

This research investigates the key quantitative and qualitative factors that contribute to the successful implementation …

A Transition Framework For Hybrid Tls In Enterprise-Level Systems, William Hadd

Cybersecurity Undergraduate Research Showcase

Enterprises face an immediate need to protect long-lived data against harvest-now, decrypt-later threats while maintaining interoperability across layered systems. With NIST’s first post-quantum standards finalized (ML-KEM, ML-DSA, SLH-DSA) and TLS hybridization drafts defining concrete ECDHE + ML-KEM groups, adoption can begin at the TLS termination layer even before full ecosystem support for post-quantum signatures arrives (NIST, 2024; IETF, 2025). In this paper, we propose an enterprise-oriented transition framework and maturity model for hybrid TLS across email, internal API gateways, and object storage. We specify where to enforce, which hybrid groups to select, and how to prevent silent downgrade with policy …

Mbse For Process Analytical Technology- Bwon Analysis Case Study, Arnaldo Garcia Cervantes

Open Access Theses & Dissertations

Volatile Organic Compound (VOC) emissions from industrial sources, particularly Benzene, present significant environmental and public health challenges. Regulatory frameworks, such as the U.S. Environmental Protection Agency’s Benzene Waste Operations NESHAP (BWON), mandate strict monitoring of control devices, specifically carbon adsorption canisters, to prevent emission breakthrough. However, current industry practices rely heavily on manual Method 21 testing, a labor-intensive process that creates lagging indicators and increases the risk of non-compliance events. This thesis proposes the design and development of an on-line, automated fugitive emissions monitoring system tailored for carbon canisters using Model-Based Systems Engineering (MBSE). Utilizing the Object-Oriented System Engineering Method …

Comparative Analysis Of Emergent Behaviors Of Three Drone Swarm System Models For Targeting Using Agent-Based Modeling And Simulation, Arsenio T. Gumahad Ii

Engineering Management & Systems Engineering Theses & Dissertations

This dissertation introduces a novel computational simulation framework for evaluating the emergent behaviors of three swarm drone models using Agent-Based Modeling and Simulation (ABMS). The three swarm models are a Leader-Follower swarm model based on Bruckstein's antline theory, a Flocking model based on a simplified Reynolds 'Boids’ model, and a Stigmergic model with pheromone-based coordination. The primary objective of the simulation is to evaluate the performance of these models in delivering a user-defined number of drones of each type to a target area of interest in four separate scenarios, resulting in 50,000 separate simulation trials. Each scenario was structured to …

Component Model Development Of Heat Exchangers, Expanders, And Control Valves For Autonomous Cryogenics Plant Cool-Down, William Harris Buhrig Iv

Mechanical & Aerospace Engineering Theses & Dissertations

The traditional method of cryogenic plant cool-down involves having continuous on-call staff to head into the office at any time to modify the existing multi-layered PID control systems if the on-call staff member detects a significant deviation from the cool-down plan. This thesis aims to outline an effective method for modeling the structure of systems with performance characteristics that deviate from design requirements and from ideal inlet-outlet correspondence, enabling the adjustment and modification of existing control structures across all Thomas Jefferson National Accelerator Facility (JLab) cryogenic refrigeration plants. Analytical Modeling and Gaussian Process Regression (GPR) are applied to model the …

Evaluating Large Language Models For Requirements Engineering And Verification: A Comparative Analysis Of Gpt-5 And Gemini 3 Pro, Guadalupe Nevarez

Open Access Theses & Dissertations

Large Language Models (LLMs) are increasingly viewed as viable tools for Systems Engineering, yet empirical data regarding their effectiveness in generating engineering-quality requirements remains limited. This thesis compares the performance of GPT-5 and Gemini 3 Pro in generating system functional requirements for the Miner Guardian Drone, a prototype UAV designed for minefield remediation. Both models were provided with identical prompts and tasked with producing 15 functional requirements. Two independent raters evaluated the outputs using a nine-dimensional quality rubric aligned with IEEE 29148 and INCOSE guidelines to ensure rigorous assessment. The difference between the models was analyzed using descriptive statistics and …

A Usv Path Planning Algorithm Under Special Environment Based On Td3-Rrt, Jitong Chen, Jiajia Zhou, Di Wu, Hailong Jiang

Journal of System Simulation

Abstract: In view of USV path planning in special environments such as multiple obstacles, large-size obstacles, and narrow passages, the rapidly-exploring random tree (RRT) algorithm suffers from drawbacks such as a large sampling base, low success rate, and zigzagging planned path. To address these problems, a global path planning algorithm (TD3-RRT) was proposed based on the twin delayed deep deterministic policy gradient (TD3). The USV path search model was established by combining the RRT algorithm with deep reinforcement learning. Forward looking detection was used to sense the environment to adaptively adjust the step size. The path search direction was exported …

Path Planning For Mobile Robots Based On Improved Artificial Potential Field Algorithm, Chi Zhang, Wei Wei

Journal of System Simulation

Abstract: In view of the problems of unreachable target areas and easy local minima in traditional artificial potential field methods, an improved artificial potential field method was proposed. The improved algorithm optimized the repulsive field function by introducing obstacle angle factors and distance factors to control the repulsive force magnitude. At the same time, an additional repulsive force towards the target point was added to solve the problem of unreachable target areas in traditional algorithms. When the robot fell into a local minimum, by introducing turning towards obstacles and turning factors to accurately apply escape forces to the robot, the …

Improvement Of Slam Localization Accuracy In Ar By Enhancing Yolov8, Jia Liu, Zengwei Zhang, Dapeng Chen, Nanxuan Huang, Bin Wang, Hong Song

Journal of System Simulation

Abstract: In the presence of dynamic interference in the environment, traditional simultaneous localization and mapping (SLAM) methods often experience reduced precision and stability in the registration of virtual objects during three-dimensional registration in augmented reality (AR). To address these issues, an improved method for dynamic scenes based on semantic segmentation and optical flow tracking was proposed. The convolutional block attention module (CBAM) attention mechanism was incorporated into YOLOv8 to enhance its focus on dynamic objects in the environment, thereby improving detection performance and accuracy. The semantic segmentation functionality of the improved YOLOv8 was integrated into the front-end of ORB-SLAM3 to …

Parking Space Reasoning Model For Complex Scenarios, Congling Zhou, Chunpeng Wang, Qiwei Xie, Yongqiang Wang, Lijun Shen

Journal of System Simulation

Abstract: In the industrialization process of the combined driving assistance system, complex parking environments bring many challenges, such as occlusion of parking spaces, uneven lighting, and missed and false detections. To address these issues, a parking space reasoning model named PIPS-Net was proposed through PINet optimization. In terms of network architecture design, the model deeply integrated the stacked hourglass network with the recurrent feature-shift aggregator (RESA) to construct a context feature extraction architecture, which enhanced the feature reasoning ability in complex scenarios. Meanwhile, it reconstructed the output to meet the requirements of parking space detection tasks, thereby jointly improving the …

Research On Vehicle Path Optimization Algorithms For Urban Logistics And Distribution, Zhenpeng Ma, Hanyang Jiao, Zhe Zhang, Cheng Liu, Bo Jiang, Lin Wang

Journal of System Simulation

Abstract: Existing optimization algorithms for solving the vehicle routing problem with time windows (VRPTW) are prone to fall into local optimal solutions and have slow convergence speed. To address this issue, a K-means clustering algorithm and improved large neighborhood search algorithm (K-means-ILNSA) was proposed. A strategy of clustering before optimization was adopted, and the K-means algorithm was adopted to group the customers to be delivered, so as to improve the optimization efficiency. The genetic algorithm was adopted to optimize each group of customers generated by clustering separately to initially plan the distribution routes. The large neighborhood search (LNS) algorithm was …

Auv Path Planning Based On Behavior Cloning And Improved Dqn In Partially Unknown Environments, Lijing Xing, Min Li, Xiangguang Zeng, Ping Zhang, Bei Peng

Journal of System Simulation

Abstract: To address the problems of large randomness and slow convergence of the DQN dynamic path planning algorithm for a single autonomous underwater vehicle (AUV) in a partially unknown environment, a path planning method combining behavior cloning with A* algorithm and DQN (BA_DQN) was proposed. Based on the known environmental information, an improved A* algorithm incorporating ocean current resistance was proposed to guide DQN, thereby reducing the randomness of the DQN algorithm. By considering the complexity of the marine environment, the sampling probability was improved again after expanding the positive experience pool to enhance the training success rate. To address …

Bayesian Network Parameter Learning Based On Ahp-Dst Fusion Of Expert Prior Knowledge, Haiyang Chen, Hongkai Lin, Zhifang Ren, Jing Liu, Jing Zhang

Journal of System Simulation

Abstract: Aiming at the problem of low accuracy of BN parameter learning due to the uncertainty of a single expert prior knowledge under the condition of small sample data set, a BN parameter learning method based on AHP-DST fusion expert prior knowledge was designed. The synthetic prior knowledge of experts was calculated by using the thought of analytic hierarchy process combined with the rules of evidence theory synthesis. The expert comprehensive prior knowledge was added to the normal distribution and combined with the monotonicity constraint to obtain the virtual sample information. The virtual sample information was added to the Bayesian …

Attitude Control Of Quadrotor Uav Based On Disturbance Observer And Command Filtering, Boning Li, Ming Chen, Shuchang Qi, Haoran Meng, Lei Wang

Journal of System Simulation

Abstract: A finite-time fault-tolerant control scheme based on backstepping was proposed for the attitude tracking control problem of quadrotor UAVs. A finite-time neural network disturbance observer was designed, which could quickly compensate for the impacts of actuator failures and external disturbances, thereby enhancing the system's robustness. A first-order command filter and a compensation mechanism were introduced, which could avoid the computational complexity caused by differentiating the virtual control law and eliminate the influence of filtering errors. The hyperbolic tangent function was selected as the constraint function for the input torque, which restricted the input signal to prevent excessive magnitude …

Research On Path Smoothing Processing Of Mobile Robot Based On Improved A* Algorithm, Mengyuan Chen, Guifang Qiao, Xu Zou, Jiayu Cao, Lei Tian

Journal of System Simulation

Abstract: Traditional bidirectional A* algorithm has many path inflection points, undergoes smoothness, and faces diagonal obstacles in path traversing. Therefore, an improved bidirectional A* algorithm was proposed. Local path constraint search was added to the forward search and backward search, respectively to solve the problem of planning paths traversing diagonal obstacles, and the effectiveness of the improved bidirectional A* algorithm to avoid traversing diagonal obstacles was verified through simulations. The path inflection points were optimized by introducing the cubic B-spline curve, and the paths before and after smoothing were tracked and controlled, respectively by using the differential-driven mobile robot. The …

Boolean Network Model Optimization Based On Neural Network And Genetic Programming, Jinlin Tang, Yan Wang, Xiang Liu, Tuanjie Wang, Zhicheng Ji

Journal of System Simulation

Abstract: To address the issues of complex node relationships and low accuracy in large-scale Boolean network inference, a new optimization algorithm integrated with long short-term memory (LSTM) networks and genetic programming was proposed. An enhanced LSTM network combined with a self-attention mechanism was designed to extract potential regulatory nodes from time-series data. These nodes were utilized as terminals of the syntax tree for the design of the genetic programming algorithm, and new operators were introduced to optimize Boolean function search. Experimental results have demonstrated that the proposed method significantly outperforms the most advanced existing algorithms in inference accuracy. The Boolean …

Twin Modeling Of Gearbox Fault Early Warning System Based On Spatio-Temporal Characteristics, Yuanxing Tian, Zeyin Han, Ning Wang, Baoding Su, Weilin Xiang

Journal of System Simulation

Abstract: The wind turbine gearbox cannot effectively collect vibration signals under complex faults, which leads to the decline of fault early warning accuracy of wind turbine gearbox. To address this issue, this study investigated the twin modeling of gearbox fault early warning system based on spatio-temporal characteristics. Through the information acquisition subsystem and optical fiber sensing technology, the time sequence and spatial position data of the wind turbine gearbox during operation were collected in real time to obtain spatio-temporal characteristic data. By using the twin space, the collected spatiotemporal characteristic data of the gearbox were transmitted to the virtual space. …

Image Feature Point Matching Algorithm Based On Attention And Hierarchical Features, Na Chen, Jiajia Bai, Qiyin Zhou, Jialin Li

Journal of System Simulation

Abstract: Feature point detection and matching is one of the core technologies in the field of intelligent driving. Aiming at the lack of consistency and continuity of feature points extracted by the existing algorithms, as well as the problem of easily ignoring the contextual semantic information when matching, this paper proposes an image feature point matching algorithm based on attention and hierarchical features (AHMF). In the feature point detection stage, differential interaction attention module (DIAM) is proposed to enhance the model's attention to the salient regions so as to improve the robustness of the feature points; further introduction of hierarchical …

Evolutionary Reinforcement Learning Based On Elite Instruction And Random Search, Jian Di, Xue Wan, Limei Jiang

Journal of System Simulation

Abstract: Evolutionary reinforcement learning currently suffers from low sample efficiency, a single coupling method, and poor convergence, which can affect its performance and scaling. To address this issue, an improved algorithm based on elite gradient instruction and double random search was proposed. The direction of the reinforcement strategy gradient update was corrected by introducing elite strategy gradient guidance carrying evolutionary information during reinforcement strategy training. Double stochastic search was used to replace the original evolutionary component, reducing the complexity of the algorithm while making the policy search meaningful and controllable in the parameter space. The introduction of complete replacement information …

Research On Temperature Compensation Technology Of Fiber Optic Gyroscope Based On Iscso-Bp Neural Network Model, Zhili Zhang, Jin Liu, Zhaofa Zhou, Zhe Liang, Yunhao Zhang

Journal of System Simulation

Abstract: To address the issue that changes in ambient temperature significantly affect the output accuracy of the fiber optic gyro (FOG), which causes zero bias drift, increases measurement errors, and limits their application accuracy in complex environments, a temperature compensation model based on BP neural networks was proposed. To improve the performance of neural networks, the sand cat swarm optimization (SCSO) was improved, and the improved SCSO (ISCSO) was used to optimize the weights and thresholds of BP neural networks. Experimental results show that using the ISCSO-BPNN temperature compensation model to compensate for the gyro's temperature errors significantly improves the …

Dynamic Supernetwork Modeling Of Command Information System Based On Task Timing, Xuehuan Qiu, Zhiming Dong, Liang Li, Zhuoli Liu

Journal of System Simulation

Abstract: Due to the difficulty in reflecting the various information activities and interactions within the command information system using general modeling methods for complex system structure, the advantages of supernetwork in characterizing node heterogeneity and link multiplicity of the system were utilized. Based on the research on the mapping mechanism of the command information system across three domains, the dynamic and multifunctional properties of the functional network structure were analyzed. A dynamic supernetwork model based on task timing was constructed considering task requirements, providing model support for further research on complex interaction relationships in the command information system. The dynamic …

Research On Time Sequence Design Method Of Dynamic Simulation Scene For Starlight Navigation, Xiaoting Su, Xiaowei Zhang, Yi Tian, Qi Li, Shuaihao Wang

Journal of System Simulation

Abstract: To solve the problem of misidentification of star maps due to time sequence mismatch in the hardware-in-the-loop simulation system of star navigation, where star trackers with different shutter types (global shutter and rolling shutter) and star simulators with varying refresh display methods (whole frame refresh and line sweep refresh) operated without synchronization, a time sequence design method of the dynamic simulation scene for starlight navigation without the need of external synchronization signals was proposed. The method could design the refresh frequency and duty cycle of the corresponding star simulators according to the detector integration time of the tested star …

Robot Path Planning Optimization Based On Fusion Of Improved Ant Colony Algorithm And A* Algorithm, Lanying Yang, Chao Li, Haifeng Zou, Jiangtao Wan, Renqiang Zhang, Hui Liu, Hong Lu

Journal of System Simulation

Abstract: To improve slow search efficiency and achieve real-time obstacle avoidance in traditional ant colony algorithms, an adaptive ant colony algorithm was proposed. A guidance direction mechanism was introduced to shorten the time of node selection. The A* algorithm's path-finding mechanism was introduced into the heuristic function to reduce the length and number of circles of the optimal path solution. The route planned by the traditional A* algorithm was used as the initial iteration data of the ant colony algorithm in global path planning, so as to solve the problem of slow initial convergence of the ant colony algorithm. The …