Engineering Commons^™

Enhancing Thermal Energy Storage Efficiency Using Optimized Concrete Materials: A Review, Ahmed Mohamed Abbass, Ahmed M. El-Khayatt, Khaled A. Eltawil

Mansoura Engineering Journal

The increasing global energy demand and the environmental impact of fossil fuels necessitate the development of sustainable energy solutions. Solar energy is a promising alternative, but its intermittency and inefficiency limit its widespread adoption. This study explores the role of advanced concrete-based thermal energy storage systems in addressing these challenges. Key aspects examined include packing density optimization, high-temperature performance, and hydrothermal durability of concrete. The research highlights the importance of granulometric optimization, binder selection, and hydration mechanisms in enhancing concrete properties. Additionally, the effects of heat exposure on concrete durability, permeability, and mechanical strength are analyzed, with a focus on …

Optimized Thermal Management Of Cylindrical Lithium-Ion Batteries Using Circular Fins And Forced Air-Cooling, Mohamed M. Donia, Ahmed A. Hegazi, Mohamed A. Aziz, Osama Abdelrehim

Mansoura Engineering Journal

The Battery Thermal Management System (BTMS) is vital for maintaining the optimal performance, safety, and longevity of electric vehicle batteries by keeping their temperature within a desired range. This study proposes an optimized cooling solution for BTMS based on both experimental and numerical investigations. Experimental tests were performed on a single battery cell under discharging rates of 1C, 2C, 3C, and 4C using an electronic load, with thermal performance evaluated under natural convection. Numerical models simulating both forced and natural convection were developed using ANSYS 19.3, and a combined Computational Fluid Dynamics (CFD) and Response Surface Methodology (RSM) approach was …

Verification Of Offline Signature Based On A Hybrid Dense-Attention-Residual-Cnn Structure Optimized By Grey Wolf Algorithm, Zeyad T. Salim, Mahmoud M. Saafan, Eman M. El-Gendy

Mansoura Engineering Journal

Signature verification is a necessary vision task with prevalent use in securing realworld applications. Offline signature is a popular type that needs to efficacious approach to be checked due to the depending on the paper time and the written tool. The progress in intelligent algorithms participates in supporting simple way authentication-based signatures. In this research work, an offline signature verification (OSV) based on an optimized and costumed convolutional neural network(CNN) infrastructure is suggested. The CNN is costumed by integrating residual, dense, and attention mechanisms, then optimized by applying a grey wolf optimization(GWO) algorithm. The system is trained and tested with …

Assessing The Geomechanical Modelling Of Underground Reservoir For Co₂ Storage Trapping Mechanisms, Bonavian Hasiholan, Mohammed Ali Farea, Elhassan Mostafa Abdallah, Sami Abdelrahman M. Yagoub, Yasir Mukhtar

Mathematical Modelling and Numerical Simulation with Applications

Effective carbon dioxide (CO₂) storage is essential for mitigating climate change amid increasing global greenhouse gas emissions. This study investigates the influence of geomechanics on CO₂ storage performance within carbon capture and storage (CCS), focusing on structural, residual, and solubility trapping mechanisms using a fully coupled modeling framework. Two numerical models, with and without geomechanical effects, are developed to evaluate impacts on reservoir behavior, CO₂ migration, and trapping efficiency. Each mechanism is analyzed separately and within an integrated framework to assess their combined contributions. Results indicate that geomechanical coupling increases reservoir pressure, reduces CO₂ flow velocity, enhances migration control, and …

Volcanic Plume Height During The 2021 Tajogaite Eruption (La Palma) From Two Complementary Monitoring Methods-Implications For Satellite-Based Products, África Barreto, Francisco Quirós, Omaira E. García, Jorge Pereda-De-Pablo, Daniel González-Fernández, Andrés Bedoya-Velásquez, Simon Carn, Et. Al.

Michigan Tech Publications

Volcanic emissions from the Tajogaite volcano, located on the Cumbre Vieja edifice on the island of La Palma (Canary Islands, Spain), caused significant public health and aviation disruptions throughout the eruption (19 September–13 December 2021, officially declared over on 25 December). Nonetheless, it is considered the most significant volcanic event in Europe over the past 75 years due to the substantial amount of SO2 released into the atmosphere. The Instituto Geográfico Nacional (IGN), the authority responsible for volcano surveillance in Spain, implemented extensive operational monitoring to track volcanic activity and to provide a robust estimation of the volcanic plume height …

Digital Twin Enabled Robot Collision Detection Using Time Series Forecasting, Fadi El Kalach, Mojaba A. Farahani, Philip Samaha, Thorsten Wuest, Ramy Harik

Faculty Publications

The advent of Industry 4.0 has reshaped modern manufacturing, driven by breakthroughs in cutting-edge technologies. A key example is the widespread deployment of sensors, which capture and transmit large volumes of operational data. This data surge has fueled the development of advanced Artificial Intelligence (AI) applications, enhancing manufacturing intelligence and efficiency. A key enabler of such intelligence is Time-Series Forecasting (TSF), which leverages historical data to predict future trends and events, thereby providing actionable insights for proactive decision-making. In parallel, Digital Twin (DT) technology has gained significant prominence due to its capacity for bidirectional communication with physical manufacturing systems, enabling …

Approaching Lower Bound Of Lattice Thermal Conductivity By Simultaneously Suppressing Diagonal And Off-Diagonal Phonon Contributions, Alejandro David Rodriguez, Riccardo Rurali, Changpeng Lin, Joshua Ojih, Mohammed Al-Fahdi, G. Jeffrey Snyder, Ming Hu

Faculty Publications

Pushing the intrinsic lattice thermal conductivity (LTC) in crystalline materials to lower bounds is crucial for fundamental materials research towards emerging technologies including thermoelectric energy conversion and thermal management in both hypersonic aircraft and next-generation turbine systems. However, in the ultralow LTC regime ( <  1 Wm-1K-1), the competition between propagative (particle-like) and coherent phonons—arising from off-diagonal components—poses a significant challenge in further reducing LTC. We perform quantitative analysis of 4700 materials using density functional theory (DFT), spanning all crystallographic groups, to elucidate the interplay between diagonal and off-diagonal phonon contributions. We identify a critical balance between these transport mechanisms, where intermediate phonon lifetimes ( ~ 1 ps) and slow group velocities ( ~ 1 km/s) collectively suppress both contributions, enabling ultralow LTC. Results from a large dataset of 31,058 structures by machine learning models strongly resemble the DFT trends of two-channel phonon transport. Leveraging these models, we screen 25,882 additional materials and confirm their properties with DFT, identifying 12 candidates with ultralow room-temperature LTC—including a record-low value of 0.132 Wm-1K-1. Our large-scale analysis reveals fundamental insights into dual-channel phonon transport, enabling rational design of ultralow LTC materials and accelerating the discovery of advanced phononic crystals with tailored thermal transport properties.

Strategic Research On Rebco High-Temperature Superconducting Tapes, Tianping Ying, Dongliang Wang, Pengtao Yang, Lin Zhao, Zhongtang Xu, Ziyi Liu, Chao Yao, Yanwei Ma, Xingjiang Zhou, Jinguang Cheng, Zhong Fang

Bulletin of Chinese Academy of Sciences (Chinese Version)

High-temperature superconducting materials, represented by REBCO (REBa2Cu3O7-δ, where RE denotes rare-earth elements), are of significant strategic importance in fields such as energy, healthcare, and large-scale scientific facilities due to their excellent performance in the liquid nitrogen temperature range. However, they still face severe challenges in long-tape uniformity, production cost, and engineering reliability. Future development must shift toward a “material-processing-application” collaborative innovation model, aiming at enhancing flux pinning, optimizing the interfaces and mechanical properties of the multilayer structure, and integrating scalable and intelligent fabrication technologies to promote the low-cost and stable production of high-performance tapes. This study analyzes the core application …

A Holistic Modelling Framework For Functionally Safe Software Architectures In Embedded Control Systems, Thomas Barth

Doctoral

Embedded control systems are integral to most modern electrified products and an essential backbone of ongoing digitalisation [1]. In this context, these systems increasingly perform safety-critical functions where failures can lead to severe personal injury, environmental damage, or significant economic loss [2]. Consequently, they fall more often within the scope of regulation such as IEC 61508 and its derivatives [3]. At the same time, driven by hardware evolution and market demands, embedded control systems continue to grow in both integration density and functional complexity [4]. These demands necessitate structured development methods that balance compliance with cost-efficiency and development agility. A …

Opportunities And Challenges In Synthetic Biology For Manufacture Of Bulk Chemicals, Xiaolin Shen, Qipeng Yuan

Bulletin of Chinese Academy of Sciences (Chinese Version)

Traditional chemical manufacturing, reliant on fossil resources, meets material demands but faces challenges such as resource depletion, environmental pollution, and carbon emissions. This underscores the urgent need for a shift towards green and sustainable production methods. Biomanufacturing, which uses renewable resources to produce chemicals, offers a promising pathway for the chemical industry’s green transition. In recent years, biomanufacturing has emerged as a key area of global attention. Through synthetic biology, bulk chemicals like 1,3-propanediol have been successfully produced. Nevertheless, biomanufacturing of bulk chemicals still faces significant challenges, including high costs, low efficiency, and limited scalability. This is particularly true for …

Tribological Properties Of Aisi 420 Esr Stainless Steel Modified By Sequential Boriding And Nitriding, Melvyn Alvarez Vera, Rafael Carrera Espinoza, Valeria López López, Marc Wettlaufer, Stefan Barth, Juan Carlos Díaz Guillén, Héctor Manuel Hernández García, Rita Muñoz Arroyo, Javier A. Ortega, Marco A. Cruz-Gómez

Mechanical Engineering Faculty Publications

This study investigates the effects of surface thermochemical treatments using boriding, nitriding, and boronitriding on the microstructure and mechanical properties of martensitic stainless steel AISI 420 ESR. Powder-pack boriding, gas nitriding, and sequential boronitriding processes were applied to enhance surface hardness, wear resistance, and adhesion. The microstructural and mechanical properties of the surface samples were analyzed using scanning electron microscopy, energy-dispersive spectroscopy, X-ray diffraction, microhardness, and nanoindentation testing. Tribological behavior was analyzed using a pin-on-disk tribometer under dry-sliding wear conditions, with applied normal loads of 5 N and 10 N and a sliding distance of 1000 m. The results showed …

Trusted Forms—The Case Of Barack Obama’S Birth Certificate, Karl-Heinrich Schmidt, Frederik Schlupkothen

Proceedings from the Document Academy

Documents can be understood as containers for information that enable remote communication between people across space and time. They are therefore fundamentally subject to issues of trust. The theoretical treatment of documents as a means of remote communication has a long history and has arrived in the age of electronic document exchange, as shown by the work of R. T. Pédauque, which is taken as a starting point here.

To take theory further, form-based documents are discussed here as an example. Form-based documents control the information provided by fillers by specifying form fields. The core of this paper is to …

Toward Transparent Bureaucracy: Nlp-Based Document Classification And Power Dynamics In The Srikandi System, Zulfatun Sofiyani, Suprayitno Suprayitno, Faisal Fahmi, Mega Putri Mahadewi

Proceedings from the Document Academy

As the Indonesian government advances digital document management through the SRIKANDI system, challenges persist regarding fragmented and subjective classification practices. This study proposes the integration of Natural Language Processing (NLP)-based classification within SRIKANDI to enhance consistency, transparency, and accountability in document management. Framed by an interdisciplinary theoretical foundation, the study synthesizes Michael Buckland’s document theory, viewing documents as dynamic social evidence, with Michel Foucault’s theory of power, highlighting classification as an exercise of institutional authority, and NLP methodologies that enable automated, content-driven categorization. The study positions documents as both technological artifacts and political constructs, whose classification practices simultaneously structure meaning …

Exploring Noise Induced Extreme Events In Neuronal Oscillators Networks And Machine Learning Forecasts, Hariharan S Mr

Theses and Dissertations

This doctoral dissertation comprehensively investigates the underexplored phenomenon of noise-induced extreme events (EE). The word “extreme” is accompanied by an occurring “event” when the deviation is extreme or higher than that of regular occurrences. These extreme occurrences are rare, abrupt, sudden, and irregular, often causing a profound impact on the system and its surroundings. Tsunami, earthquakes, solar flares, and tornadoes are such events that do not occur often but still significantly cause damage to mankind. This thesis particularly focuses on EE in neuronal systems where sudden synchronization can trigger seizures, tremors, and strokes which serve as classic examples of such …

Research On System And Application Framework Of Tactical Wargaming Simulation Driven By Ai4s, Dayong Liu, Qisheng Guo, Zhiming Dong, Xuehuan Qiu, Zhuoli Liu

Journal of System Simulation

Abstract: Tactical wargaming simulation, as a crucial tool for combat analysis, simulation training, and equipment demonstration and test, has become a significant means for generating combat effectiveness. Integrating AI into simulation not only enhances simulation efficiency but also diminishes reliance on humans. To assist professionals engaged in tactical wargaming simulation in mastering AI application methods, fostering a systematic mindset, and understanding evolving trends, this paper provided a concise overview of the principles behind AI for science (AI4S). Subsequently, it conducted an analysis of AI4S's application effectiveness in tactical wargaming simulation, established an AI4S-driven wargaming simulation system, and elucidated its composition, …

Social Cognition Simulation With Large Language Model-Driven Agents, Mingxin Zhang, Jinxuan Wu, Rui Zhu, Yunlong Wang, Wenjuan Meng, Zhe Liu, Xu Li, Xiaolei Chen, Yuxuan Liang, Yi Zheng, Xiangyang Xue

Journal of System Simulation

Abstract: With the continuous evolution of the capabilities of generative LLMs, their application in social cognition simulation is demonstrating paradigm-shifting potential. Traditional social simulation methods predominantly rely on static rules and simplified behavioral models, making it difficult to capture the dynamic evolution and cultural complexity of human social behavior. LLM-driven agents, equipped with contextual understanding and natural language generation capabilities, are emerging as novel tools for modeling social cognitive mechanisms, enabling the simulation of complex sociopsychological processes such as identity construction, value judgment, and intentional reasoning. This paper briefly introduced the technical foundations of LLMs and highlighted their suitability for …

Integrated Development Environment For Digital Test Applications Based On Cloud-Edge-End Architecture, Wenguang Yu, Qun Li, Hongjie Dang, Hao Chen, Ping Yang

Journal of System Simulation

Abstract: Digital test applications need to be constructed using the unified digital test development tool. After analyzing the features of digital test applications such as large-sample autonomous run, high computational efficiency requirement, and diverse task scenarios, this paper proposes the integrated development environment (IDE) for digital test applications based on cloud-edge-end architecture. The layered expandable architecture, the hybrid integration framework of multi-source heterogeneous models, and the cloud-edge-end collaborative deployment architecture are designed for the IDE of digital test applications. The IDE supports the rapid development, integration, and execution of digital test models and enables development of digital test applications on …

Research On Chain-Of-Thought Technology For Situational Awareness Based On Modular Reasoning, Hongyuan Ji, Duzheng Qing

Journal of System Simulation

Abstract: To address issues such as insufficient intelligence of situational understanding in traditional simulation systems, a situational visual question answering dataset was constructed, and a modular reasoning framework was proposed. The SACoT was built, which, under a zero-shot setting, employed expert prompts to guide the model in task decomposition and multimodal information fusion, generating reasoning chains to enhance semantic cognition and interpretability and offering a scalable solution with low computation cost. Experimental results indicate that SACoT improves task allocation, enables models to focus on query-relevant image details, mitigates the fragmentation of chain-of-thought induced by multi-step reasoning, and reduces long-form …

Simulation Of Robotic Arm Ball-Catching Strategy Based On Curriculum Rl Of Transformer, Ziyao Zhang, Yunfeng Ji

Journal of System Simulation

Abstract: Method integrating the PPO algorithm with Transformer network architecture is proposed, and curriculum learning strategy is introduced to solve the difficult training convergence and low efficiency of traditional RL methods in complex and dynamic high-degree-of-freedom tasks such as robotic arm ball catching. The Transformer is employed to effectively capture the complex high-dimensional dependency between the robotic arm's state space, ball trajectory, and environmental physical parameters. Curriculum learning progressively increases catching difficulty by designing training tasks from simple to complex objectives. The experimental results show this method increases the ball-catching success rate by over 60% compared to the traditional …

Research On Uav Target Tracking Algorithm For Simulation Scenarios, Xinyi Li, Zhenfei Wang, Han Wu

Journal of System Simulation

Abstract: To address the need for automatic UAV tracking of moving targets in simulated experiments, this paper proposed a long-term automatic tracking method based on an improved channel and spatial reliability-aware tracker (CSRT) algorithm. The target edge features were detected using the Laplacian of guided filter (LOGF) through guided filtering and then fused with the histogram of oriented gradient (HOG) and color names (CN) features to enhance the algorithm's discriminative ability for the target. To evaluate the target state, the paper used average peak correlation energy and perceptual hash Hamming distance. When the target was occluded, the paper employed YOLOv8 …

Distributed Optimization For Integrated Energy Based On Multi-Agent Reinforcement Learning, Caixia Tao, Naikun Chen, Fengyang Gao, Jiangang Zhang

Journal of System Simulation

Abstract: To address the energy management and privacy preservation problems faced by the coordinated optimization of distributed integrated energy systems, a distributed coordinated optimization strategy based on the multi-agent proximal policy optimization algorithm was proposed. An energy management model was established under the MDP framework; the electrical and thermal heterogeneous energy characteristics were considered; a multi-region two-layer interaction mechanism was constructed. Under the framework of centralized training and decentralized execution, homomorphic encryption was utilized to avoid privacy leakage during the coordination process, while accurately quantifying individual contributions to mitigate the problem of variance explosion in multi-agent policy evaluation. In the …

Prediction Of Inflow Wind Field For Large-Scale Wind Turbines Based On Multimodal Hybrid Deep Learning, Jiheng Wang, Yang Hu, Ziqiu Song, Fang Fang, Jizhen Liu

Journal of System Simulation

Abstract: To address the demand for high-precision inflow wind field prediction in large-scale wind turbines, traditional CFD methods suffer from high computational costs and poor real-time applicability. This paper proposed a multimodal hybrid deep learning-based wind field prediction method. The proposed method took turbine operating parameters and far-range wind field images as inputs and generated short-range wind field images as outputs. By employing a U-Net-Transformer-GAN hybrid architecture, the model achieved multi-scale feature extraction, temporal dependency modeling, and highresolution wind field image generation. The vorticity transport equation and Kármán-Howarth turbulence statistics were incorporated as weak constraints to enhance physical consistency, while …

Llm-Driven Multi-Agent Social Network Simulation: Interdisciplinary Integration And Cutting-Edge Development, Jiting Li, Yi Sun, Yirong Wang, Yiqin Lin, Jun Jia, Gangsong Ding

Journal of System Simulation

Abstract: The breakthrough of LLMs has provided powerful tools for social network research, advancing multi-agent social network simulation into a new era. This review systematically examined recent progress in LLM-driven multi-agent social network simulation research through a integrated perspective of multi-disciplines such as artificial intelligence, psychology, communication studies, and sociology. A three-tiered research system, which has gradually formed in this field and encompassed micro-level individual behaviors, meso-level interactive relations, and macro-level system emergence, was summarized. At the micro-level, research focuses on individual human behavior simulation, and numerous studies are dedicated to developing human-like agents with complex cognitive and affective architectures …

An Adaptive Robot Path Planning Based On Improved Rea* Algorithm, Ling Zhu, Jing Li, Zhaohui Zhang

Journal of System Simulation

Abstract: In order to improve the computational efficiency and path smoothness in a robot's global path planning, an adaptive robot path planning strategy based on an improved unilateral rectangle expansion A*(REA*) algorithm was proposed. The robot's operational safety was ensured by setting a buffer around obstacles. A passable interval formed by unilateral rectangle expansion was used as the operation unit, and bidirectional alternating search was combined to enhance the path planning efficiency. Inspired by potential field theory, the evaluation function was optimized by introducing a vector form to achieve fast adaptive obstacle avoidance. A new path planning strategy was proposed …

Evolutionary Game-Based Analysis Of Responses To Hallucinations In Generative Artificial Intelligence, Qiang Yan, Qianyu Zhang, Na Wei

Journal of System Simulation

Abstract: The accelerated deployment of generative artificial intelligence, particularly large language models, has amplified the social risks of hallucinations, posing systemic threats to the credibility of the information ecosystem, the effectiveness of users’ cognitive decision-making, and the governance security in the public domain. Research primarily focuses on hallucination mitigation mechanisms at the technical level or the design of regulatory frameworks at the policy level, lacking a systematic theoretical analysis of the evolutionary logic of strategic interactions among the “large language models, users, and regulators” under conditions of bounded rationality. By introducing evolutionary game theory into the field of generative artificial …

Intelligent Air Combat Decision-Making Method Based On Bigru And Priority Dynamic Sampling, Zhengkun Ding, Jiaqi Liu, Junzheng Xu, Yuezhu Xu, Xingmei Wang

Journal of System Simulation

Abstract: Current multi-agent reinforcement learning algorithms suffer from low efficiency in utilizing experience data and difficulties in setting appropriate learning rates. To address these issues, this paper proposed a BiGRU multi-agent PPO with priority sampling and dynamic learning rate. The algorithm incorporated a BiGRU network to enhance the policy network's ability to model temporal information. A priority partial sampling mechanism was introduced to improve the utilization efficiency of high-value experience data. Additionally, an improved Adam optimizer with dynamic learning rate adjustment was employed to address the challenge of learning rate configuration. Simulation experiment results demonstrate that the algorithm significantly …

Knowledge-Enhanced Llm-Based Method For Regional Traffic Signal Control, Risheng Xu, Linyao Yang, Yuanqi Qin, Xiao Wang, Changyin Sun

Journal of System Simulation

Abstract: Adaptive traffic signal control (ATSC) is crucial for alleviating regional traffic congestion, yet it faces severe challenges in real-time response to unexpected events and global coordination. The DRL method relies on pure data-driven approaches, suffering from core limitations such as poor generalization, weak interpretability, and a lack of guidance from emergency disposal knowledge, which makes them difficult to meet the demands of complex traffic scenarios. A control system that integrates knowledge-driven and data-optimized approaches was proposed. The GraphRAG was used to construct a dynamic traffic knowledge graph, providing LLMs with real-time updated historical emergency disposal experience and road …

Resource-Efficient Continuous Learning Framework For Edge Real-Time Video Analytics, Shuxia Wu, Junjie Zhang, Delong Chen, Zheyi Chen

Journal of System Simulation

Abstract: By deploying lightweight models at the network edge, edge systems can provide services of real-time video analytics. However, due to the data drift caused by the discrepancy between model training and actual deployment, it is challenging to construct lightweight models that match real-world environments. To address this challenge, a resource-efficient continuous learning framework for edge real-time video analytics (CL4VA) was proposed. A region of interest-granularity predictor for accuracy degradation was introduced to efficiently select key samples from real-time video streams. A two-layer mixed sample pool was constructed to adaptively trigger the model's continuous learning and avoid the issue of …

Reinforcement Learning Based Method For Uav Team Orienteering Optimization Under Multi-Constraint Condition, Can Yang, Kai Chen, Feng Zhu

Journal of System Simulation

Abstract: Traditional optimization methods struggle with efficiency, while reinforcement learning approaches often yield low solution quality and high training costs. In response, this paper proposes an attention mechanism-based reinforcement learning method. A dynamic attention strategy network with multi-information fusion is designed to improve solution quality. A visibility-graph approach is employed to simplify threat zone constraints and speed up convergence, and a decoding sequence reordering mechanism is introduced for further performance optimization of the solution. The simulation results show that the method generates high-quality solutions within milliseconds, achieving total rewards that approach or even surpass those obtained by traditional solvers …

Strike Strategy Planning Method Of Unmanned Ground Vehicles Based On Improved Ppo Algorithm, Bingkun Wang, Yue Wang, Mei Yang, Pengnian Zhang, Bohao Fan, Jie Tang

Journal of System Simulation

Abstract: An improved PPO algorithm based on the hybrid action space and gated recurrent unit (GRU) is proposed to address the limitations of predefined strike rules in maximizing the hitting accuracy of unmanned ground vehicles and the difficult coupling and optimization of continuous motion planning and discrete strike decision-making. The environmental model and target model are built for the process of unmanned ground vehicles' strike missions, coupled with a three-layer model for unmanned ground vehicles that fuses kinematic constraints, situational awareness, and dynamic decision-making. Two distinct policy networks are employed, including the continuous motion planning network for path planning, and …