Computer Engineering Commons^™

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, …

Context Matters: Evaluating Llm-Generated Knowledge Graph Schemas, Ritvik Garimella, Riju Marwah, Atishay Jain, Khusham Bansal, Amit Sheth

Publications

Knowledge graph (KG) schema engineering is labor-intensive and resists automation at scale. We investigate whether LLMs can generate domain-specific KG schemas of sufficient quality for downstream symbolic reasoning. We propose a tiered contextual framework that varies domain context richness across four levels: zero context, domain scope, task requirements, and data distribution. Generated schemas are evaluated intrinsically on BioRED (600 PubMed abstracts, multi-type entities and relations), where automated tiered schemas match an established KG construction baseline at 79.9% EC, with edge conformance rising from 47.5% at L1 to a stable 78–80% from L2 onward. Extrinsic evaluation on a 50-record MedHop controlled …

Cognitive Resilience At The Edge: Hyperdimensional Computing Versus Deep Learning For Hardware-Degraded Rf Classification, Adrian B. Cisneros, Jeong Yang

Military Cyber Affairs

Autonomous Collaborative Combat Aircraft (CCA) operating in contested electromagnetic environments must classify Radio Frequency (RF) signals on edge silicon that degrades over the mission lifetime due to thermal stress, radiation, and manufacturing variation. Deep neural networks dominate RF classification on pristine hardware, but their weights are precise and interdependent, causing catastrophic accuracy collapse as the underlying chip ages. We investigate whether Hyperdimensional Computing (HDC), a brain-inspired paradigm that distributes information across thousands of dimensions, can provide a reliability floor where Deep Learning fails. Using the RadioML 2016.10A dataset filtered to five digital modulations relevant to drone command-and-control links, we trained …

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.

Breaking The Build: Detecting Software Supply Chain Vulnerabilities In Ci/Cd Pipelines, Mercedes R. Wahl, Dr. Benjamin Yankson

Military Cyber Affairs

This study examines whether integrating structured DevSec- Ops security controls into CI/CD pipelines can reduce software supply chain risk by preventing vulnerable components from progressing through the software development lifecycle. Software supply chain attacks frequently originate from weaknesses or compromises within dependencies, build environments, and trusted development stages, making early detection essential. A controlled sandbox experiment compared two pipeline configurations: a baseline CI/CD pipeline with no automated security enforcement and a secure DevSecOps pipeline integrating automated vulnerability scanning, SBOM generation, and artifact integrity verification. A known vulnerable dependency, the Python requests package (version 2.19.0) associated with CVE-2018-18074, was intentionally introduced …

Mitigating Common Vulnerabilities And Exposures In Cobol-Based Critical Systems Using The Strangler-Fig Pattern, Lauren E. Caruso, Vincent J. Compeau, Assefaw H. Gebremedhin

Military Cyber Affairs

COBOL-based legacy systems continue to underpin critical infrastructure in banking and government sectors despite their age and associated cybersecurity risks. Originally developed through a Department of Defense–sponsored initiative to standardize business computing, COBOL remains widely used in mission-critical environments. However, these systems face increasing vulnerabilities due to outdated security architectures, workforce shortages, and rising maintenance costs. This paper examines cybersecurity and operational challenges associated with COBOL systems and evaluates the Strangler Fig pattern as a modernization strategy that enables incremental replacement while maintaining continuity. The findings highlight implications for financial institutions and public-sector organizations dependent on legacy infrastructure.

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 …