Physical Sciences and Mathematics Commons^™

High-Dimensional Multi-Objective Optimization Algorithm Based On Large Language Model Assistance, Yichao Ma, Jingxuan Wei

Journal of System Simulation

Abstract: The increase in the dimension of objective functions in optimization problems makes it challenging to balance convergence and diversity in population-based algorithms, which is a key factor leading to performance degradation of multi-objective evolutionary algorithms. To address this issue, a dynamic switching mechanism assisted by a large language model is proposed. By continuously evaluating the changes in hypervolume and convergence metrics of the solution set, the search process is adaptively divided into three phases: convergence-oriented, diversity-oriented, and large language model-suggested phases, achieving precise allocation of computational resources. Furthermore, to mitigate the high computational cost of large language models in …

Modeling, Dynamical Analysis, And Lmplementation Of Switched Memristive Neural Networks, Zhuang Qu, Shaohua Zhang, Cong Wang, Hongli Zhang, Xinkai Li, Ping Ma

Journal of System Simulation

Abstract: To simulate the dynamic functional switching of brain networks, a time-switched memristive Hopfield neural network (TSM-HNN) model is proposed. The model utilizes external time-sequential signals to control memristive synapses, allowing it to dynamically generate multi-scroll chaotic attractors of varying numbers and morphologies without altering the system's structure. This overcomes the limitation of traditional chaotic systems, which can typically only produce a single type of attractor. The model exhibits complex chaotic behavior, high sensitivity to initial conditions, and coexisting attractors. Its physical feasibility has been verified through PSPice circuit simulations. This enhanced complexity and randomness give the model significant potential …

Design And Research Of A Microfocus X-Ray Tube, Haodong Zhao, Shizong Wei, Daolong Yu, Zhixia Liu, Yuezhong Chen, Ji Xu

Journal of System Simulation

Abstract: With the rapid advancement of high-resolution imaging and Micro-nano detection technology, microfocus X-ray sources show great potential for applications in industrial non-destructive testing, biomedical imaging, and material microstructure analysis. Achieving a focal spot size below 10 μm is essential for enhancing spatial resolution. However, traditional X-ray tubes are constrained by heat source dimensions, electron beam divergence, and limited focusing capabilities, which makes it challenging to simultaneously achieve focal spot miniaturization and adequate radiation intensity. In this study, a hot cathode electron gun is modeled using CST particle studio. Simulations are conducted to analyze the influence of the first anode …

Research On Characteristics Of Inclined Jet Flow For Aircraft De-Icing Based On Multiphysics Coupling, Zhiwei Xing, Hongbin Zhang, Ke Sun, Wenliang Miao

Journal of System Simulation

Abstract: To address the complex multiphysics coupling and lack of theoretical guidance for spray parameters in aircraft ground de-icing, a simulation model based on the Phase-Field method and Realizable k-ε turbulence model is proposed to investigate inclined jet flow over airfoil surfaces. The model enables the numerical reconstruction of jet impingement, liquid film flow, and unsteady heat transfer processes, providing a framework to elucidate the regulatory mechanisms of jet angles on momentum distribution and thermal characteristics. The simulation results reveal distinct variations in the flow and heat-transfer characteristics at different jet inclination angles. At a jet angle of 15°, the …

Physics-Driven Efficient Simulation Platform For Warhead-Target Engagement And Damage Assessment, Yidan Cui, Jingyao Ke, Yufeng Zheng, Kun Xue

Journal of System Simulation

Abstract: To address the limitations of incomplete physical modeling, low computational efficiency, fragmented simulation workflows, and insufficient visual immersion in existing damage simulations of fragment warheads, this paper proposes and develops a physics-driven, high-efficiency visualization platform for warhead-target engagement and damage assessment. The platform implements a full-chain, closed-loop simulation framework covering scenario configuration, force-field computation, fragment dispersion, warhead-target intersection, and damage evaluation. A finite element-discrete element (JK2024-06) coupled dynamics framework is established, integrating a detonation model, shell expansion correction, and fragment velocity inheritance to accurately reproduce the complete dynamic process from detonation to dispersion. A three-level acceleration algorithm based on …

Research On Simulation Technology Of Sea Yawing Test For Amphibious Vehicles, Yue Zhong, Wenlong Ji, Shiqi Feng, Feng Xu, Shuangping Ye

Journal of System Simulation

Abstract: Addressing the challenges of achieving extreme operating conditions and understanding the boundary conditions of yaw performance in offshore yaw tests for amphibious vehicles, a heading-flow direction angle mapping analysis method based on computational fluid dynamics (CFD) simulation and a three-dimensional hydrodynamic stratified model is proposed. Under environmental conditions of second-level (wave height of 0.5 m, wind speed of 3.3 m/s) and third-level (wave height of 1.0 m, wind speed of 5.1 m/s) sea states, a hundred-meter yaw test is simulated to reveal the nonlinear evolution law of yaw displacement and heading-flow direction angle. The research indicates that the extreme …

Vibration Characteristics Of Compact Hydraulic System Pipelines Based On Two-Way Fluid- Structure Interaction, Lichen Shi, Xujia Feng, Weitao Dou, Yanyan Li

Journal of System Simulation

Abstract: Amid growing demands for green manufacturing, equipment miniaturization, and high efficiency, compact hydraulic systems are critical in disassembly, assembly, and transport operations due to their high power density and flexibility. However, severe vibration in the pipeline systems significantly compromises equipment reliability. This study investigates the dynamic response mechanism of a compact on-board hydraulic pipeline system, using a specific piece of disassembly and assembly equipment with spatially constrained clamp placement as a case study, through a two-way fluid-structure interaction method, and optimizes the clamp layout. The results show that resonance occurs when the excitation frequency of the hydraulic oil pressure …

Research On Automated Generation Method Of Data-Based Architectural View Products, Kui Wang, Tianrong Gao, Cheng Chen, Mengyin Cui, Ping Wang, Xiaoping Wang, Huaijin Ge

Journal of System Simulation

Abstract: To address the issue of insufficient consistency among view products in the architectural design process, this paper proposes an automatic view product generation method based on the architecture metamodel. To enhance the consistency of view products, the method abandons the traditional post-design verification approach. Instead, it uses the information flow/data flow defined in the metamodel as the benchmark, and through explicit associations among architectural data as well as mapping relationships between view products and data, automatically derives and generates behavioral view products from structural and classificational view products. A prototype tool developed based on this method has been validated …

Research Of Data-Model Integrated Digital Twin-Based Health Intelligent Monitoring For Multi-Stage Centrifugal Compressors, Xiaomo Jiang, Jigang Meng, Huaiyu Hui, Wenqing Meng, Haibin Yang, Huize Chen

Journal of System Simulation

Abstract: To address the challenges of insufficient real-time monitoring capability and weak coupling between physical entities and virtual models in the long-term safe and reliable operation of multi-stage centrifugal compressors under complex operating conditions, this paper proposes a digital twin construction method based on data-model fusion for intelligent health monitoring. A unit-system-component hierarchical virtual twin model is established to achieve the coordinated mapping of geometric structure, operational behavior, and monitoring data of the compressor. By integrating a terminal-edge-cloud collaborative architecture, data-driven models are dynamically coupled with the virtual twin to construct a digital twin-based health monitoring platform, enabling operating state …

Design Of A Simulation Dataset For Fine-Grained Detection Of Space Target Sequence Images, Shiyan Wang, Danpu Zhao, Haikun Hong

Journal of System Simulation

Abstract:

With the increasing number of space objects such as satellites, there is a growing need for fine-grained detection and recognition of distant space targets. However, obtaining real observational data remains difficult due to high costs and insufficient annotation detail. To overcome these limitations, asynthetic dataset generation system based on multi-module collaboration is developed. Using joint simulation with STK and Blender, the proposed system simulates optical imaging conditions of space targets and automatically produces sequential images along with corresponding fine-grained labels. A large-scale simulation dataset is constructed for fine-grained detection in space target image sequences. It contains …

Robotic Digital Twin Modeling Method Integrating Mbse And Modelica, Zaiwu Mei, Jiangman Zhou, Cong Zhang, Yiping Gao, Zerun Zhu

Journal of System Simulation

Abstract: To address the issues of disconnection between system architecture design and dynamic simulation, as well as the limited reusability and scalability of models in robotic digital twin modeling, a modular modeling approach integrating MBSE (model-based systems engineering) and Modelica is proposed. The method employs MBSE for system architecture design and requirement traceability, and combines Modelica for multi-domain dynamic simulation, forming a full-chain digital twin model from system design to physical behavior simulation. Standardized interfaces and a generic component model library are developed to decouple and integrate mechanical, electrical, and control subsystems, enabling rapid model assembly and functional expansion. A …

Modeling And Simulation Of Multi-Hop Routing In 3d Tunnel Wireless Sensor Networks, Fang Cao, Jiguang Yang, Jiuyuan Huo

Journal of System Simulation

Abstract: To address the unbalanced energy consumption and short network lifetime caused by the complex topology and strong energy coupling of three-dimensional tunnel wireless sensor networks, this study constructs a system-level operating model integrating spatial topology, energy evolution, and routing decision-making, and proposes an energy management for balanced and efficient routing (EMBER) algorithm based on the competition of tribes and cooperation of members (CTCM) algorithm. The optimal number of cluster heads is derived through tunnel spatial modeling. Clustering is performed using a Gaussian mixture model optimized by CTCM, and efficient cluster-head selection is achieved by combining data envelopment analysis. An …

Rrt*-Based Robotic Manipulator Path Planning With Artificial Potential Field Guidance And Accumulator-Based Adaptive Adjustment, Fangzheng Gao, Xu Guo, Quan Sun, Jiacai Huang, Zhongcai Zhang

Journal of System Simulation

Abstract: To address the problems of blind sampling, slow convergence, and path redundancy in robotic manipulator path planning in cluttered and unstructured three-dimensional environments, An RRT* algorithm integrating artificial potential field guidance and accumulator-based adaptive adjustment, namely APGA-RRT* (artificial potential field guidance and accumulator adaptive adjustment-RRT*). The proposed algorithm improves the overall planning performance from three aspects: sampling, expansion, and path optimization. In the sampling stage, a potential-field-guided sampling strategy based on target-distance weighting and virtual-target switching is constructed, obstacle suppression and safe-distance gating mechanisms are incorporated to dynamically adjust the guidance intensity, thereby enhancing target directivity and local escape …

Online Fine-Tuning Of Binocular Camera Extrinsic Parameters Based On Position-Iteration Dual Perception, Qian Long, Tuerhong Dilixiati, Qi Zheng, Lijun Shen

Journal of System Simulation

Abstract: In long-term operation of binocular systems, small drifts in extrinsic parameters may occur due to temperature changes, vibration, and mechanical shocks. As these drifts accumulate, the ranging error increases with distance and seriously degrades long-range measurement performance. Because online compensation is difficult, such small drifts are often neglected. To address this problem, an online fine-tuning method based on position-iteration dual perception is proposed. A multiplicative coupling weighting model is established by integrating spatial reliability with an iteration-stage modulation function. A three-stage progressive optimization algorithm is designed to balance convergence speed and robustness. A simulation framework for offline calibration and …

Review Of Evaluation Metrics For The Credibility Of Autonomous Driving Test Scenarios, Jiwei Li, Runmin Wang, Yu Zhu, Jingjun Cheng, Xiangmo Zhao

Journal of System Simulation

Abstract: Currently, scenario-based simulation testing has become a core technical approach for verifying autonomous driving system functionality. However, due to the absence of unified evaluation standards for simulation scenarios, significant differences exist among the metrics constructed and adopted by different studies, each with its own limitations. This hinders mutual recognition of research outcomes and prevents scientific measurement of scenario quality. This study systematically reviews relevant research from the past five years, categorizing autonomous driving test scenarios into four types: parameter-descriptive, trajectory-driven, environment-simulation, and perception-data-driven. It clarifies the core characteristics, application objectives, and generation mechanisms of each scenario type. Subsequently, focusing …

Hybrid Attention For Low-Overlap Point Cloud Registration, Huaijun Wang, Zonghua Yu, Chenxin Xu, Junhuai Li, Chenzhi Li, Junjie Yin

Journal of System Simulation

Abstract: To address the significant registration errors caused by large initial pose deviations in low overlap ratio point cloud, this paper presents a two-stage optimization method that integrates selfattention and cross-attention mechanisms. Orientation feature representation is enhanced using equivariant self-attention, semantic alignment is achieved through invariant cross-attention, and rotational equivariance is modeled with an octahedral group for coarse registration. Various attention variants are employed to aggregate features along the anchor dimension, and a local-to-global module is utilized for fine registration. On the 3DLoMatch dataset, the proposed method achieves a registration recall of 77.0% and an inlier ratio of 44.3%. Even …

Numerical Simulation Study On Flow-Induced Vibration Energy Harvesting Characteristics Of Piezoelectric Energy Harvester With Elliptical Cylinder Bluff-Body, Jiechao Lei, Long Li, Ji Yao

Journal of System Simulation

Abstract: To improve the self-powering efficiency of miniature internet of things devices, this paper establishes a fluid-structure-electric multi-field coupled computational fluid dynamics (CFD) model based on the ANSYS Fluent platform. It conducts a numerical simulation study on the flow-induced vibration energy harvesting characteristics of a piezoelectric cantilever beam energy harvester with an elliptical cylinder bluff-body. A systematic analysis is performed on the influence mechanism of flow velocity within the range of 0.1~0.5 m/s on the output power. The results indicate that the output power of the harvester exhibits phased growth with increasing flow velocity. In the range below 0.15 m/s, …

Hands-On Ransomware: An Experiential Wannacry Case Study For Undergraduate Cybersecurity Education, Eli Creek Richmond, Thomas R. Devine

Military Cyber Affairs

Ransomware represents one of the most disruptive threats in the cyber landscape, yet hands-on malware analysis remains rare in undergraduate cybersecurity curricula. This paper presents the design, implementation, and evaluation of an experiential learning module centered on the WannaCry ransomware case study, deployed in a senior-level course at West Virginia University. Students performed static and dynamic analysis using industry-standard tools. Pre- and post-module assessments demonstrated measurable gains in self-reported competency across seven technical dimensions. The module's competencies align directly with DoD Cyber Workforce Framework Work Role 212, Cyber Defense Forensics Analyst, supporting education-to-workforce pipeline development.

From Framework To Toolchain: Implementing Zero Trust Architecture In Cloud-Native Environments For Dow Compliance, Shelby C. Snyder

Military Cyber Affairs

Federal agencies face a fiscal year 2027 target for enterprise-wide Zero Trust deployment, but NIST SP 800-207A defines logical components without identifying the Kubernetes technologies that implement them. This paper proposes a three-tier mapping of the Policy Engine, Policy Administrator, and Policy Enforcement Point to service mesh, microsegmentation, and perimeter tooling, stating the criteria by which each component is classified. It then applies a defined rubric to six Zero Trust vendors across component alignment, Kubernetes capability, federal authorization posture, and evidence quality, finding that no single vendor covers all three tiers. The mapping is a testable architectural proposition; a Stage …

Semantic Shields: Automating Critical Infrastructure Defense Via Nlp-Driven Ransomware Profiling, Henry Trowbridge, Ian Zalcberg, Ryan Schley, Carter Yagemann, Natasha Phan, Srikar Maduposu, Vimal Buck

Military Cyber Affairs

Ransomware poses a growing threat to critical infrastructure, where successful attacks can disrupt operational technology (OT) and industrial control systems (ICS) with significant public safety consequences. However, attributing ransomware incidents to specific threat actors remains challenging due to ransomware-as-a-service ecosystems, actor rebranding, and the obfuscation of traditional indicators of compromise. This paper presents Semantic Shields, an NLP-driven attribution framework that leverages BERT-generated semantic embeddings and DBSCAN clustering to profile ransomware actors through the linguistic characteristics of ransom notes. Using a dataset of 295 ransom notes from 189 distinct threat groups, the framework achieved an 87.2% true positive clustering rate and …

Challenges, Trends, And The Role Of Lstm In Ai-Based Predictive Maintenance Of Electrolyzers For Solar Hydrogen Systems: A Review, Yani Koerniawan Kuatno, Muhamad Zahim Sujod

Turkish Journal of Electrical Engineering and Computer Sciences

The transition toward low-carbon energy systems has increased interest in hydrogen as a clean energy carrier, with solar-driven water electrolysis emerging as a promising technology due to its high efficiency and compatibility with renewable energy sources. However, dynamic operating conditions and intermittent renewable input accelerate electrolyzer degradation, reducing reliability and system lifespan. Predictive maintenance (PdM), supported by artificial intelligence (AI), offers a data-driven approach to anticipate failures and improve operational durability. This review systematically investigates AI-based PdM approaches for electrolyzers, with an emphasis on long short-term memory (LSTM) networks and Internet of things (IoT) integration. Following PRISMA 2020 guidelines, 35 …

Dynamic Focal Loss Adjustment For Railway Defect Detection, Mehmet Koç, Ridvan Özdemi̇r, Ömer Gerek

Turkish Journal of Electrical Engineering and Computer Sciences

Railway infrastructure is critical to the safe and efficient operation of transportation systems, and the early detection of defects is essential for preventing catastrophic failures. Automated defect detection methods are therefore crucial for maintaining continuous safety while reducing maintenance costs. Although Focal Loss is widely used in object detection under class-imbalanced conditions, its fixed α parameter may limit its effectiveness in detecting rare defects. In this study, we propose an adaptive α-tuned Focal Loss approach that dynamically adjusts class weights based on average precision (AP) values. By iteratively optimizing α without relying on gradient-based optimization, the proposed method improves the …

Relative Rate Observer-Based Online Tuning Mechanism For Single-Input Interval Type-2 Fuzzy Pid Controllers, Oqba Aldreiei, Cenk Ulu, Mert Can Kurucu, Müjde Güzelkaya

Turkish Journal of Electrical Engineering and Computer Sciences

The characteristics of the footprint of uncertainty (FOU) in interval type-2 membership functions (IT2-MFs) are crucial to the performance and robustness of interval type-2 fuzzy controllers (IT2-FCs). However, existing IT2-FC design approaches mostly use fixed FOU structures. This study proposes an online membership function (MF) adjustment mechanism for a single-input interval type-2 fuzzy PID controller (SIT2-FPID)  that adjusts the FOU of the antecedent MFs and weights of the consequent MFs, respectively, to achieve high performance and robustness. The proposed online adjustment mechanism consists of a relative rate observer (RRO), a two-input rule-base adjustment system, and a first-order smoothing filter. The …

Cuip-X25: A Real-World Network Intrusion Dataset For Next-Generation Ai-Driven Security, Arshad Iqbal, Sohail Asghar

Turkish Journal of Electrical Engineering and Computer Sciences

The efficacy of artificial intelligence (AI) in intrusion detection systems (IDS) is critically dependent on high-fidelity training data. However, as detailed in the manuscript's literature review, existing benchmark datasets are predominantly synthetic, outdated, or imbalanced and fail to capture the complexity of the contemporary threat landscape. To bridge this gap, this study introduces CUIP-X25, a novel real-world cyber-attack dataset captured over a four-month period using a dionaea honeypot deployed on a public network. Unlike synthetic alternatives, this dataset provides an authentic representation of modern adversarial tactics, techniques, and procedures, encompassing 3.16 million real events across ten distinct attack categories, including …

Robust Load Frequency Control For Multiarea Electrical Power Systems Via Analytical Proportional-Integral-Derivative Plus Second Order Derivative Controller Design, Yavuz Güler, Mustafa Nalbantoğlu, Ibrahim Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

This research presents a proportional-integral-derivative plus second order derivative (PIDD2) controller design based on the Direct Synthesis Method (DSM) for load frequency control (LFC) of interconnected power systems. The parameters of the proposed PIDD2 controller are determined using the DSM, which offers an analytical approach for tuning. The design approaches have been developed specifically for single, two, and three-area power systems, encompassing nonreheated and reheated thermal turbines. In the proposed design method, the best values of PIDD2 controller parameters were found by using a multicriteria objective function that includes the integral of absolute error (IAE) and settling time. In response …

Boundary Layer Sliding Mode Control Strategy For Variable-Speed Compressor In Deep Freezers: Experimental Validation Of Energy Efficiency And Freezing Capacity, Sertan Aksoy, Kami̇l Çeti̇n, Sezai̇ Taşkin

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents the design and experimental validation of a nonlinear sliding mode controller developed for a deep freezer equipped with a variable-speed compressor. The proposed control strategy aims to minimize energy consumption while maintaining rapid and stable cooling performance under varying ambient conditions. A detailed thermal model of the deep freezer was established using an equivalent resistance–capacitance network representation, enabling precise analysis of temperature dynamics. The sliding mode-based control algorithm dynamically adjusts the compressor’s operating frequency according to temperature deviation, ambient conditions, and time-dependent factors, providing robust performance without requiring parameter retuning for different models. Beyond theoretical-based analysis, a …

Empowering Edge Intelligence Through Reparameterized Lightweight Transformers And Distributed Inference, Hosein Esmaeili, Mohammad Ali Afshar Kazemi, Reza Radfar, Nazanin Pilevari

Turkish Journal of Electrical Engineering and Computer Sciences

Deploying advanced transformer-based models on resource-constrained edge devices remains a significant challenge due to their high memory footprint and substantial compute requirements. In this paper, we propose a reparameterized transformer framework that integrates High-Rank Factorization (HRF) during training, layer merging at inference, and dynamic, load-balanced distributed inference across multiple devices. To further reduce resource usage, our framework supports mixed-precision quantization down to 4-bit, enabling flexible accuracy–latency–energy trade-offs. Experimental evaluations on the ESC-50 environmental sound dataset demonstrate that our method matches or exceeds the performance of larger baseline models while using 20–30% fewer parameters, achieving up to 48% latency reduction in …

Measurement-Aware Zero-Phase Iterative Learning Control For Robust Regulation Of Nonideal Boost Converters In Electric Vehicle Fast Charging, Aytaç Altan, Mohammed S. Alzaidi, Cağfer Yanarateş

Turkish Journal of Electrical Engineering and Computer Sciences

Integrating battery energy storage with DC-DC boost converters for electric vehicle fast charging exposes the regulator to ageing-induced parameter drift, periodic load pulses, and, critically, the nonidealities in the output-voltage sensing chain. This paper proposes a measurement-aware, zero-phase iterative learning control scheme for robust output-voltage regulation of a nonideal boost converter whose parameters are matched to those of a commercial Texas Instruments TPS6102x battery regulator. The controller combines an inner proportional-integral stabilizing loop with an outer zero-phase learning law that updates a feedforward correction based on the sensor-captured output trajectory; a forward-backward robustness filter suppresses the amplification of measurement noise …

A Binary Multiobjective Hippopotamus Optimization Algorithm For Feature Selection In Phishing Website Detection, Fatima Belmessaoud, Sofiane Maza, Djaafar Zouache

Turkish Journal of Electrical Engineering and Computer Sciences

Phishing website detection remains a major challenge in cybersecurity as attackers continuously develop new techniques to deceive users. Identifying the most informative features from large datasets is essential to improve classification accuracy while reducing computational complexity. Feature selection is therefore widely addressed using metaheuristic optimization techniques due to their flexibility and global search capability. In this study, we propose a Binary Multiobjective Hippopotamus Optimization Algorithm (B-MOHOA) for feature selection in phishing website detection. The proposed method simultaneously optimizes two conflicting objectives: maximizing classification accuracy and minimizing the number of selected features. Unlike many existing studies that mainly focus on transfer …

Range–Angle-Dependent Oam Beamforming With A Concentric Helical Circular Fda, Uğur Yeşi̇lyurt

Turkish Journal of Electrical Engineering and Computer Sciences

Secure and spatially selective wireless transmission requires orbital angular momentum (OAM) beams that are confined to a specific range and angle, rather than propagating indefinitely along the beam axis. In this paper, a concentric helical circular frequency diverse array (CHCFDA) is proposed to generate range–angle-dependent OAM beams without requiring external phase shifters. The helical element positioning inherently provides the necessary interelement phase distribution through physical step height, while logarithmically increasing frequency offsets are applied across concentric rings—and optionally across individual elements—to eliminate range periodicity and achieve a single, well-focused OAM beam exclusively at the target location. Both linear and logarithmic …