Engineering Commons^™

Effects Of Ball Milling Duration And Sintering Temperature On Mechanical Alloying Fe3si, Varistha Chobpattana, Chakansin Phoomkong, Peerawat Nutnual, Kritsada Thaengthong, Wanchai Pijitrojana

Journal of Metals, Materials and Minerals

Fe3Si is under interest as a ferromagnetic electrode of magnetic tunneling junctions (MTJs). Its crystalline structure is important for achieving high device efficiency. This work focuses on mechanical alloying of 3:1 ratio of 99% pure Fe and Si powder mixtures by ball milling and sintering. The mixtures were ball-milled for various durations up to 20 h. Then, they were sintered from 400°C  to 800°C for 4 h in Ar.  SEM images and particle size analysis show significant reduction in average particle size of the mixtures after ball milling for 20 h. The longer duration of ball milling process promotes powder …

Enhancing Shipboard Safety Management Under The Ism Code: An Innovative Risk Assessment Framework With A Stern Tube Case Study, Pi-Yen Lin

Journal of Marine Science and Technology–Taiwan

The shipboard safety management system (SMS) is designed to enhance safe operations, risk management, and emergency response to improve overall ship safety and efficiency. This paper demonstrates the use of an engine room simulator (ERS) for collecting failure modes and applies it to a comprehensive failure analysis of the stern tube lubricating oil system. A new risk closeness coefficient method was developed, integrating expert background knowledge and weighted risk assessments. The analysis, based on multiple expert evaluations, covered five subsystems, eight main components, 23 failure modes, and 112 failure causes. This study presents 26 recommendations for maritime practitioners and onboard …

Port And Vessel Communication Traffic Intrusion Detection: A Variational Autoencoder‑Enhanced Multilayer Perceptron Approach, Chien-Lin Chiang, Hsien-Cheng Chou, Ming-Yuan Peng, Yi-Yuan Chiang, Yu-Shun Liu

Journal of Marine Science and Technology–Taiwan

Port and vessel networks increasingly operate on IP/Ethernet backbones with high‑noise, high‑dimensional traffic. We present a lightweight hybrid intrusion‑detection model that couples a variational autoencoder (VAE) with a multilayer perceptron (MLP) and augments training with a boundary‑oriented latent‑space mixup strategy. The VAE models the distribution of normal traffic and identifies anomalies through reconstruction errors. Subsequently, it generates robust latent vectors, enabling the MLP to perform highly accurate supervised classification. On the UNSW‑NB15 dataset, the proposed pipeline attains ≥97% accuracy and an outstanding recall of 99.56% in binary intrusion detection, and visualization of the latent space (PCA) together with reconstruction‑error analyses …

Sar Ship Detection Based On Shallow Feature Guidance, Chenxu Xia, Peng Chen, Ya Zhang, Ying Li

Journal of Marine Science and Technology–Taiwan

Maritime ship detection is of great significance for both military security and civilian applications. Synthetic Aperture Radar (SAR), with its all-weather and all-day imaging capability, plays a vital role in maritime surveillance. Nevertheless, SAR ship targets typically appear small in scale, embedded in complex backgrounds, blurred at boundaries, and easily confused with near-shore features, which pose substantial challenges for accurate detection. To address these issues, we propose a SAR ship detection network that integrates dual enhancements of small-object representation and edge information. The network introduces two key components: the Small Target Refine Pyramid (STRP) to strengthen shallow feature representation for …

Structural And Electrochemical Characterization Of Na2co3/ Γ- Al2o3 Electrodes For Supercapacitor, Wiwin Dwiana, Jeniva Dinta Nanda Fahreza, Anissa Chairani Alfin Nadhira, Fatimatuz Zahra, Erma Surya Yuliana, Muhammad Safwan Abd Aziz, Nandang Mufti

Journal of Mechanical Engineering Science and Technology (JMEST)

The development of electrode materials with suitable structural and surface properties is crucial for improving electrochemical energy storage systems. Gamma alumina (𝛾-Al₂O₃) has attracted considerable interest in electrochemical research due to its unique structural and surface properties. However, its charge-storage capacity is still limited, highlighting the need for structural and compositional modifications to improve its electrochemical performance. In this study, Na₂CO₃ was introduced into 𝛾-Al₂O₃ as a sodium precursor to induce phase modification and enhance the electrochemical activity. The systematic incorporation of Na₂CO₃ also provides an opportunity …

A Systematic Review Of Alkali-Treated Polylactic Acid Biocomposites Relevant To Pineapple Leaf And Water Hyacinth Hybrid Design, Muhammad Rizky Adrianto Subandi, Tri Hartutuk Ningsih, Hanna Zakiyya

Journal of Mechanical Engineering Science and Technology (JMEST)

The increasing demand for sustainable materials has accelerated the development of biodegradable polymer composites. Polylactic acid (PLA)-based natural fiber composites have attracted significant attention due to their renewable characteristics; however, their performance remains limited by weak fiber–matrix compatibility, moisture sensitivity, and inconsistent interfacial behavior. Alkali treatment has been widely applied to modify lignocellulosic fibers by removing non-cellulosic components and improving surface characteristics, although its effectiveness remains dependent on treatment conditions and fiber properties. This systematic review evaluates the influence of alkali treatment on PLA-based natural fiber composites and assesses the available evidence supporting future pineapple leaf fiber (PALF) and water …

Effect Of Preheating Palm Oil Biodiesel Fuel On The Performance And Emissions Of Diesel Engine Common Rail Direct Injection, Nanang Romandoni, Achmad Aminudin, Hari Setiapraja, Bima Randi Wardiasaputra, Kelvin Dwi Wardana, Ahmad Yusril Aminullah, Deni Nur Fauzi, Kholis Nur Faizin, Nur Ihda Farikhatin Nisa

Journal of Mechanical Engineering Science and Technology (JMEST)

Fossil fuel consumption continues to increase while its reserves continue to decrease and produce high emissions that trigger global warming. Therefore, more environmentally friendly alternative energy is needed. Biodiesel is a sustainable choice because it is biodegradable, low in sulphur, and can replace fossil fuels. This study investigates the influence of biodiesel fuel preheating temperature on engine performance, fuel consumption, and emissions in a Common Rail Direct Injection (CRDI) diesel engine. The experimental method was carried out by heating B40 and B50 fuels at temperatures of 40°C to 60°C at intervals of 10 °C. Engine performance was evaluated using a …

Simulating Diesel And Battery-Electric Haulage In Underground Mines: Productivity, Heat Load, And Energy Usage, Aaron Swift, Jason M. Porter, Alexandra M. Newman

Journal of Sustainable Mining

Battery-electric vehicles can improve ambient conditions in underground mines by reducing the amount of heat and diesel exhaust produced during the execution of mining activities (e.g., hauling fragmented rock). Literature comparing diesel- and battery-powered vehicles considers differences in cost, productivity, and heat load between individual vehicles or one type of vehicle (e.g., only trucks or only loaders); this paper determines the effect of electrifying an entire haulage fleet on the productivity, heat load, energy usage, and emissions of an underground mine using discrete-event simulation. Battery-electric loaders and haul trucks reduce heat load by 76 to 82%, CO₂ emissions by …

Evaluating The Effectiveness Of Building Information Modeling (7d Bim) In Enhancing Facility Management And Maintenance Of Heritage Buildings, Hasnaa M. Taye, Yasmine S. Hegazy, Mohamed A .Abu Ashour, Hesham Hendawy

Mansoura Engineering Journal

Heritage buildings continue to face persistent challenges in documentation, fragmented data management, and limited integration of digital technologies in post-restoration facility management. Building Information Modelling (BIM), particularly 7D BIM, provides a framework for managing heritage assets throughout their operational lifecycle. Yet, despite increasing interest in BIM for construction and conservation, empirical evidence on its contribution to facility management efficiency in heritage settings, especially in Arabic-speaking contexts, remains limited. This study investigates the extent to which BIM adoption enhances facility management performance, with attention to operational efficiency, risk reduction, maintenance quality, and decision support. A mixed-methods explanatory sequential design was employed. …

A Built Environment Framework For Sustainable Urban Transport In Developing Countries: Lessons From Copenhagen, Nassamat Mahdy Mohamed, Mohamed Anwer Zayed, Ingy Mohamed El Barmelgy

HBRC Journal

Developing countries are suffering from several urban transport challenges. In addition, global strategies of sustainable urban transport (SUT) lack integration with the seven dimensions of the built environment (7Ds). Therefore, there is a gap between the global strategies and their practical application, especially in the developing countries. To address this gap, this study aims to propose built environment framework for SUT in developing countries. This is addressed by analyzing a selection of global urban transport strategies and extracting consolidated applicable principles, then analyzing Copenhagen as a leading case study in SUT. Based on the research foundation and literature review, the …

Experimental And Cfd Analysis Of Heat Generation During Fly Ash Carbonation From Fbc Boiler, Tomasz Janoszek

Journal of Sustainable Mining

The transition toward a closed-loop economy and improved energy efficiency in the industrial sector has highlighted the importance of waste heat recovery and carbon dioxide (CO₂) sequestration. This study investigates the carbonation of fly ash derived from fluidized bed boilers as a method for stabilizing reactive calcium oxide (CaO) while recovering the exothermic heat released during the process. Fly ash carbonation involves reactions between free CaO, CO₂, and water, forming stable calcium carbonate (CaCO₃) and generating significant thermal energy. Laboratory experiments were conducted in an adiabatic rotary reactor equipped with seven thermocouples to monitor the temperature profile of the carbonating …

Forecast Of Mining Fatalities Using Machine Learning Algorithms, Enoch Nii-Okai

Journal of Sustainable Mining

The mining industry plays a crucial role in economic development, but is often accompanied by notable occupational hazards, including fatalities. This research investigates the application of machine learning techniques to predict mining fatalities in the United States using historical data from 1983 to 2023, sourced from the National Institute for Occupational Safety and Health (NIOSH) and FRED Economic Data. Predictive models, including random forest (RF), gradient boosting (GB), decision tree (DT), multiple linear regression (MLR), and linear regression (LR), were employed to assess relationships between operational parameters and annual fatality counts. The dataset was thoroughly preprocessed, addressing missing values and …

Effect Of Cryogenic Soaking Duration On The Crystallographic Structure And Corrosion Resistance Of Astm A36 Steel, Sukri Mubarok, Andoko Andoko, Retno Wulandari

Journal of Mechanical Engineering Science and Technology (JMEST)

This study investigates the influence of cryogenic soaking duration on the crystallographic characteristics and corrosion resistance of ASTM A36 structural steel. Specimens were immersed in liquid nitrogen at −196°C for 0, 12, 36, and 60 hours. Crystallographic analysis was conducted using X-ray diffraction (XRD), while electrochemical corrosion behavior was assessed through Tafel polarization in 3.5% NaCl solution using an Autolab PGstat. Key parameters evaluated included crystallite size, microstrain, dislocation density, corrosion rate, and material degradation. The results showed that soaking up to 36 hours significantly refined the microstructure, as indicated by reduced crystallite size and increased dislocation density and microstrain. …

Thermal Performance Analysis And Heat Transfer Characteristics Of A Solar Powered Paddy Dryer Using A Flat Plate Solar Collector, Peter Sahupala, Daniel Parenden

Journal of Mechanical Engineering Science and Technology (JMEST)

Freshly harvested paddy holds much water (23.00% wet basis in this study) and spoils quickly without prompt drying. Open sun drying depends on the weather and heats the grain unevenly. This study tested an indirect solar paddy dryer with a 0.60 m² flat plate collector, a 10 kg capacity, and natural convection airflow in Merauke, South Papua. Six thermocouples (collector, drying chamber, and chimney), a pyranometer, and a moisture meter recorded data every 15 minutes at drying temperatures of 40°C, 50°C, and 60°C. The data gave useful heat energy, collector thermal efficiency, and drying rate. Useful heat energy ranged from …

The Effects Of Transportation Distribution On Dry Ice Insulated Containers' Thermal Performance, Edmund Tang

Journal of Applied Packaging Research

This study builds upon methodologies established in a 2024 investigation of the combined effects of physical distribution stresses and thermal environments on cold chain packaging performance. Prior results showed that moisture-resistant gel packs generally maintained a vaccine storage range of +2°C to +8°C. However, when exposed to extreme combined stresses, thermal performance degradation of up to 13.5% was observed. The present work applies a similar experimental framework to transportation systems that rely on dry ice as the primary cooling medium, addressing the distinct challenges associated with ultra-cold distribution.

Pharmaceutical products requiring dry ice are highly temperature-sensitive and vulnerable to performance …

Quantifying Attacker Payoff In Harvest Now, Decrypt Later Attacks: A Persistence-Based Framework For Trade Secret Risk, Arjun Kumar, Gene Yang, Turiya Misra, Francis Kagai

Journal of Cybersecurity Education, Research and Practice

Harvest-now, decrypt-later (HNDL) assumes that encrypted secrets stolen today will remain worth decrypting when quantum computers eventually make that possible. But what if they do not? This paper models HNDL from the attacker’s perspective by asking a different question: how much will a stolen secret still be worth when it can finally be decrypted? We develop a conditional retained-value framework combining probabilistic Q-day timing, information depreciation, and adversary-access delay. The results reveal a sharp divide. Rapidly depreciating secrets can lose much of their strategic value before quantum decryption becomes useful, while persistent secrets can retain substantial attacker payoff even under …

Llm-Driven Simulation Method For Mobilization Decision-Making In Weapons And Equipment Supply Chain, Qichang Guo, Jihai Zhang, Zichu Qin

Journal of System Simulation

Abstract: A LLM-driven multi-agent simulation model for production mobilization in the weapons and equipment supply chain is developed to address the practical challenge of transitioning the supply chain from peacetime to wartime production in response to surging wartime demand. The model consists of a military demand layer, a supply chain execution layer, and a mobilization decision-making layer. An LLM is incorporated as a mobilization decision generation module to represent the dynamic regulation of production conversion and expansion under war-readiness budget and production safety constraints. The simulation results show that compared with the no-mobilization and rule-based mobilization strategies, the LLM-based strategy …

Chemical Plant Control Based On Dynamic Simulation And Reinforcement Learning, Yuxin Li, Haijie Li, Shangbo Han, Kai Gao, Qingyuan Zhang, Yanwen Xiao, Zhengcai Liu

Journal of System Simulation

Abstract: An intelligent control strategy framework combining offline training and on-site deployment for regenerative thermal oxidizer (RTO) operation control based on RL is proposed to solve the problem that fluctuations in exhaust gas concentration and flow, as well as changes in working conditions, make it difficult for RTO to maintain the system operating parameters within the economically optimal range in practical applications. In the offline phase, RL is employed to enable autonomous policy learning and global optimization. In the online phase, an adaptive policy correction mechanism based on real-time data is introduced. RL control strategy is integrated with the operation …

Five-Dimensional Digital Twin System For Closed-Loop Gasoline Blending Optimization, Yaning Fang, Renchu He

Journal of System Simulation

Abstract: An adaptive blending optimization system based on five-dimensional digital twin theory is designed and developed to address the challenges of strict nonlinear constraints and frequent raw material fluctuations. A five-dimensional model architecture is constructed to achieve virtual-real mapping and synergy throughout the blending process. A closed-loop control strategy of "online model correction and dynamic recipe optimization" is proposed. The constrained recursive least squares (RLS) algorithm is adopted to update the octane blending effect model parameters, resolving the model mismatch caused by raw material fluctuations. The linear decreasing weight particle swarm optimization algorithm (LDW-PSO) is combined to determine the optimal …

Research On Digital Shipyard Design-Procurement Coupling Based On Multi-Agent Systems, Kaitai Peng, Dingyi Feng, Wenbo Zhao, Feier Chen

Journal of System Simulation

Abstract: To address the issues of low supply chain collaboration efficiency and inadequate dynamic scheduling capability caused by the disconnection between design and procurement in digital shipbuilding, a method integrating multi-agent simulation with the Q-learning reinforcement learning algorithm is proposed, and a four-tier dynamic supply chain model coupling design and procurement is developed, covering mines, steel mills, shipyards, and shipowners. Based on the depth of collaboration, steel mills are classified into three levels, including full collaboration, partial collaboration, and noncollaboration, with differentiated state spaces and reward functions designed to simulate intelligent pricing and game behaviors under information asymmetry. Simulation results …

Mission-Oriented Combat Effectiveness Evaluation Model For Intelligent Equipment System-Of-Systems, Long Zhang, Wenbo Huang, Xuanming Feng, Zhen Lei, Ying Wang

Journal of System Simulation

Abstract: A hierarchical evolutionary adaptive learning (HEAL) framework is proposed to address the problems in the operational simulation of intelligent equipment systems under complex adversarial environments, including fragmented hierarchical decision-making, unclear mapping between algorithmic indicators and operational effectiveness, and the lack of adaptive evolution capability of simulation models. A multi-layer learning architecture that integrates robust autonomous decision-making for single units, emergent collaboration of system networks, and game-theoretic evolution of system-of-systems strategies is constructed by following the “micro-meso-macro” system-oriented hierarchical modeling paradigm. A cross-layer closed-loop coupling among learned policies, cooperative structures, and operational effectiveness is achieved by combining bottom-up behavioral abstraction …

Multimodal Perception-Based Trajectory Planning Method For Uavs In Forest Environments, Dequan Li, Jiahao Jiang

Journal of System Simulation

Abstract: To address the requirements for low-latency local planning and safe obstacle avoidance in UAV forest-fire patrol under dense tree-trunk occlusion and locally invalid depth observations, this paper proposes a learning-based local trajectory planning method that fuses depth images, local occupancy distance maps, candidate-level collision-risk assessment, and pre-execution safety reranking. The method uses depth images, local occupancy distance maps, motion states, and target direction as inputs and generates 15 quintic-polynomial candidate trajectories in parallel using 3 × 5 angular motion primitives. During training, candidate safety costs, ranking supervision, and near-collision risk labels are constructed. During inference, online LiDAR point clouds …

Manifold Alignment And Dual Prediction-Based Adaptive Dynamic Multi-Objective Evolutionary Algorithm, Xuezhi Yue, Chao Xiong, Yanshen Jiang, Zhaolu Guo, Hu Peng

Journal of System Simulation

Abstract: To address prediction failure, manifold topology distortion, and insufficient adaptability in environmental response and operator configuration in existing prediction-based algorithms for dynamic multi-objective optimization under complex nonlinear environments and small-sample settings, this paper proposes a manifold alignment and dual prediction-based adaptive dynamic multi-objective evolutionary algorithm, termed MADP-DMOEA. When the environment changes, the algorithm decomposes the decision-variable manifold into center and shape components, effectively aligns manifolds at adjacent time instants via bipartite optimal matching, and identifies environmental change severity using geometric displacement. A dual prediction model is developed, in which a GRNN performs center extrapolation under severe changes, while an …

Cooperative Hunting Method For Multiple Usvs Based On Improved Maddpg, Yonghao Zhang, Changyou Xue, Xueman Fan, Zhuo Cheng

Journal of System Simulation

Abstract: A cooperative hunting method based on improved multi-agent deep deterministic policy gradient (MADDPG) is proposed to address the challenges of non-stationary environments, sparse rewards, and partial observations in the cooperative hunting of targets with unknown motion patterns by multiple unmanned surface vessels (USVs). A Markov game model for hunting is built, and a multidimensional guided reward shaping function incorporating collision avoidance, hunting success, and energy consumption penalties is designed to mitigate the sparse reward problem. ResNet residual networks are introduced to construct the Actor and Critic networks and thus enhance the representation capability of deep networks for complex state-action …

Five-Axis Multi-Station Process Planning Based On Multi-Task Graph Reinforcement Learning, Junjie Liu, Jianlei Xu, Litao Ju, Yanhai Hu, Qinghao Zhang, Qiang Liu

Journal of System Simulation

Abstract: A hierarchical intelligent planning architecture integrating multi-task graph and masked proximal policy optimization (MTG-MPPO) is proposed to address the challenges of factorial expansion of the state space and multi-objective interference in five-axis multi-feature machining. An attributed adjacency graph integrating boundary representation and machining direction vectors is constructed. Probabilistic soft labels are output through a multi-task network to quantify process flexibility and thus achieve prior topological pruning of solution space. An MDP model integrating directed acyclic graph masks and dense reward shaping is built. A Monte Carlo (MC) optimization mechanism based on policy distribution is introduced to coordinate cutting, tool-changing, …

Dynamic Multi-Objective Optimization Algorithm Based On Residual-Driven Two-Stage Prediction And Its Application, Xin Zhang, Han Wang, Pengjiang Qian, Wei Fang

Journal of System Simulation

Abstract: A dynamic multi-objective optimization algorithm based on residual-driven two-stage prediction (RDTP) is proposed to address the dilemma of prediction strategies in dynamic multi-objective optimization struggling with insufficient samples in the early stage and low accuracy in the later stage. In the initial stage, if an environmental change is detected, grey prediction, which is fast and suitable for small samples, is employed to generate individuals for the new environment. A residual analysis is performed to determine whether to switch to a LSSVM to improve prediction accuracy as more samples become available. The Pareto front is clustered to select detection objects. …

Optimization Of Mobile Power Resource Allocation And Scheduling For Multi-Point Emergency Response, Ding Ma, Tao Zhang, Bo Jiang, Yajie Liu, Shuijia Li

Journal of System Simulation

Abstract: In extreme event scenarios, urban mobile power resources (MPRs) suffer from uneven spatial distribution and capacity mismatch during emergency scheduling. To achieve globally rational allocation and improve resource configuration and power supply guarantee, a two-stage decision-making method for MPR allocation and scheduling is proposed for multi-point emergency power demands. First, the characteristics of MPRs and travel energy consumption are modeled. In the first stage, an allocation model considering demand satisfaction, capacity matching, and dispatch time is established to solve the macro-level matching problem between MPRs and demand points. In the second stage, an interface scheduling model is constructed based …

Coordinated Optimization Of Heterogeneous Fleet Configuration And Multimodal Routing For Industrial Clusters, Renxin Xiao, Yifan Xu, Guisheng Chen, Nan Pan

Journal of System Simulation

Abstract: A two-level optimization model integrating heterogeneous electric vehicle fleet configuration with multimodal path coordination is built to address the challenges in industrial cluster freight transportation involving electric heterogeneous fleet scheduling, such as diverse tasks and stringent constraints on energy consumption and delivery timeliness. Considering the performance coupling characteristics of heterogeneous electric fleets in terms of load-energy consumption-endurance, based on the coordination of multimodal paths and fleet configuration coding, the upper level employs the GWO to optimize task splitting and fleet configuration. The lower level adopts a multi-neighborhood SA algorithm to achieve path coordination scheduling. Simulation results show that the …

Simulation Study On Circular-Track Rgv Scheduling Based On Railway Operating Rules, Hualan Wang, Li Wang, Zhongning Fu

Journal of System Simulation

Abstract: To address the limitations of circular RGV systems under high-density operating conditions, including a simple operational structure and limited parallel operation capability, this study investigates track structures and dispatching mechanisms for complex operational requirements. Based on the agent-based modeling method implemented on the AnyLogic platform, a simulation model of an RGV system with a nested circular track layout was developed, in which an embedded sub-loop equipped with track-switching devices is introduced into the traditional circular track structure. Operating and dispatching rules suitable for the nested circular structure are designed by incorporating the concepts of section operation and overtaking in …

Air Defense Resource Allocation And Reconstruction Method Based On Kggom, Jiaoxiong Chen, Chenglong Zhang, Yuqiang Zhao, Xianglin Li, Qiang Zhao

Journal of System Simulation

Abstract: To address the challenge that traditional solving methods cannot meet real-time requirements in the intelligent allocation and reconstruction of air defense operation resources, this paper focuses on an intelligent solving method for the dynamic allocation and reconstruction of intercept timing sensor-weapon-target. A multi-constraint model is established with damage effectiveness and operation cost as optimization objectives, and a knowledge-guided genetic optimization method (KGGOM) is proposed. Through knowledge-guided population generation and evolution, constraint-aware operators with correction mechanisms, and multi-path search combined with simulated annealing for gene correction, it improves its optimization capability and speed. Historical superior solution retention and dynamic elite …