Engineering Commons^™

Material Costs, Karima Weinman

Masters Theses

This thesis investigates how migration fatality and disappearance data can be reinterpreted through material craft to create a more reflective encounter with information. Working with the Missing Migrants Project's dataset, this project asks how design can communicate dimensions of human loss that conventional data visualization cannot reach.

The work situates contemporary border violence within a longer colonial history, arguing that the logics of surveillance and quantification that structured European imperial expansion persist in the databases that govern mobility in the Mediterranean today.

Terrazzo is a 15th-century Venetian flooring technique built from discarded fragments bound together into a unified surface. This …

Power Consumption Prediction And Energy Forecasting Using Machine Learning Models, Sheik Mohideen Shah S Mr

Theses and Dissertations

Power consumption trends are essential to be identified in the energy grid areas to analyze the utilization, deficiency, and the measures to be taken for an effective and comfortable usage of energy. There are two scenarios in which the power consumption can be analyzed, namely identification and prediction. Identification deals with the post-utilization analysis of energy trends, whereas prediction deals with prior analysis of various factors of energy utilization, including the cost, supply details, shortages, and the need for new energy resources. In the existing models, the power consumption-related data are collected through smart meters, and the energy forecasting methods …

Les Grands Chantiers De La Transition Énergétique Au Maroc: Le Cas De Dakhla-Oued Eddahab Entre Réalisations, Facteurs De Réussite Et Perspectives, Limam Boussif, Jalila Ait Soudane

Journal of Maya Heritage

Résumé: Cet article examine la dynamique de la transition énergétique au Maroc à travers une analyse descriptive et analytique du cas de Dakhla-Oued Eddahab. Dans un contexte marqué par l’accélération des politiques de décarbonation à l’échelle mondiale, le Maroc s’impose comme un acteur stratégique en matière de développement des énergies renouvelables et de l’hydrogène vert. L’étude met en lumière les principaux chantiers structurants engagés dans la région de Dakhla, notamment le développement des énergies éolienne et solaire, les projets de production d’hydrogène vert, le dessalement de l’eau de mer, ainsi que la réalisation du port Dakhla Atlantique. L’analyse montre que …

Characterizing Stiffness Dynamics Of Normal And Malignant Breast Spheroids Using Brillouin Microscopy, Razanne Rafat Zaghloul, Karlin Hilai, Chenjun Shi, Jitao Zhang

Medical Student Research Symposium

Background: Breast cancer progression and metastasis are closely linked to alterations in the mechanical properties of tumor cells and their microenvironment. Softer, more deformable cells are often associated with higher metastatic potential. While atomic force microscopy (AFM) is the current gold standard for mechanical characterization, it is limited to surface measurements and can damage 3D cultures. It remains unclear how the mechanical properties evolve over time in normal versus malignant spheroids. This study utilizes Brillouin light-scattering microscopy, a non-contact and label-free optical technique, to assess stiffness changes in normal and malignant breast epithelial spheroids over time. Understanding these mechanical signatures …

The Analytic Hierarchy Process As A Tool For Architectural Quality Assessment: A Case Study On Municipal Facades, Gül Şebnem Tutal, Fatma Demet Aykal

HBRC Journal

This study evaluates the façade quality of three municipal buildings using the Analytic Hierarchy Process (AHP) to identify strengths, weaknesses, and improvement priorities in public architecture. Although façade design has been widely studied, quantitative and integrated assessment frameworks for municipal building façades remain limited. To address this gap, the study integrates the Design Quality Indicator (DQI) with AHP within a Multi-Criteria Decision Making (MCDM) framework, proposing a systematic and replicable evaluation model. The research assesses three main DQI criteria-functionality, building quality, and impact-subdivided into twelve sub-criteria and analyzed through pairwise comparison matrices. Data were collected through structured expert interviews with …

Towards The Integration Of Living Plants In Urban Design For Desert Regions \Fontsize1213\Selectfont\Textcolorblack(A Dynamic Shading Unit Inspired By Plant Movements), Amira Medhat Ibrahim Gouda

HBRC Journal

With the rapid urban expansion of new cities in hot desert climates, the challenge of designing open urban spaces and public squares becomes evident, particularly in providing thermal comfort. These spaces are exposed to intense sunlight and temperatures exceeding 40°C for extended periods, limiting their usability and increasing reliance on traditional, non sustainable shading methods. Addressing this issue, the research explores the potential of bio-dynamic shading units that utilize plants with self-moving responses such as nyctinastic and heliotropic movements as sustainable alternatives that adapt automatically to climatic changes without mechanical systems or energy consumption. The study assumes that integrating plants …

Characterization And Potential Suitability Of Some Egyptian Clays For Ceramic Building Applications, Marwa Askar, Medhat Sobhy El-Mahllawy, Mohamed Hamed Abdel-Aal, Ali Mohamed Ali Abd-Allah, Safia Gaber Al Menoufy

HBRC Journal

This study investigates the suitability of five Egyptian clay deposits—Wadi El-Natrun, Qasr El-Sagha, Kafr Homied, Fayed, and Suez Road—for ceramic building applications. Representative samples were characterized chemically and mineralogically, with grain size distribution and Atterberg limits determined to assess their industrial potential. Mineralogical analysis identified montmorillonite, illite, and kaolinite as the dominant clay minerals. Grain size and plasticity data, plotted on industrial diagrams, revealed that all samples are highly plastic clays with elevated clay fractions and minimal sand content. Such properties, while beneficial for molding, require modification to reduce excessive plasticity. The addition of non-plastic materials is recommended to enhance …

Detection Method For Laboratory Ppe Compliance Wearing Based On Human Key Points, Lijun Peng, Tingqi Su, Peijin Liu, Lin He, Xiewu Zhou, Minxin Zhang

Journal of System Simulation

To address the problems of high missed detection rate and inaccurate judgment of wearing compliance when multi-scale and multi-category targets of laboratory personnel's safety protective equipment are detected in a complex laboratory environment, this paper proposes a laboratory personnel's standard personal protective equipment (PPE) wearing detection method (multi-scale multi- target joint key point detection method, MSMT-JKDM) that integrates multi-scale features and human keypoints. The multi-scale adaptive down sampling (MSA-Down) module and the cascaded group attention transformer (CGA Former) are introduced to enhance the feature representation ability of PPE (especially small targets such as goggles and gloves) in laboratory detection scenarios, …

Automatic Speed Guidance Method And Simulation Evaluation For Trams At Intersections, Jing Teng, Wencong Tong, Zhongjie Zhang, Xing Yao, Junxian Li

Journal of System Simulation

To address the lack of speed regulation mechanism and the high dispersion of operational time in the current manual driving mode, this paper proposes an automatic speed guidance method for trams at intersections. Considering the speed disturbances caused by potential traffic conflicts at intersections, an initial decision point for safe passage speed at an intersection is established, dividing the operational curve into deterministic segments and disturbance-response segments.To verify the effectiveness of the method, a case study of Songjiang Tram Line 1 is conducted.Driving simulation experiments are performed to obtain manual driving trajectories, and a dynamic trajectory simulation model …

Robot Trajectory Planning And Adjustment Method For Abnormal Pose Of Actuator, Lang Qin, Jiacheng Xie, Xiaojun Qiao, Xuewen Wang, Zhijie Xiao

Journal of System Simulation

To address the influence of the abnormal pose of the robot actuator on the robot trajectory, an adaptive planning and adjustment method of trajectory based on virtual-real fusion was proposed. AR technology was introduced to couple with the robot kinematics model, and the hardware dependence on multiple sensors was replaced by synchronous comparison of three-dimensional virtual and real poses; AR gestures and voice interaction were combined to simplify the operation process; based on the actual pose of the actuator, the trajectory of the robot terminal axis was dynamically adjusted. The experimental results show that this method breaks through the technical …

Sos Effectiveness Evaluation Method Based On Fuzzy Functional Dependency Network Analysis, Hongjia Su, Cheng Zhang, Fei Liu

Journal of System Simulation

Functional dependency network analysis (FDNA) enables modeling functional dependencies among equipment in a system of systems (SoS) and then computing the whole SoS effectiveness based on the effectiveness of each equipment, thus overcoming the deficiency of traditional SoS effectiveness evaluation based on tree-like index systems. However, critical parameters such as strength/criticality of dependency in this methodology currently rely on subjective empirical assignments, where the deviations resulting from subjectivity may compromise the accuracy of effectiveness evaluation. To address this limitation, this paper proposes a fuzzy FDNA (FFDNA)-based SoS effectiveness evaluation method. This method constructs a functional dependency network (FDN) model …

Research On Completion Method For Trajectory Based On Image Representation And Collaborative Feature Perception, Ye Tao, Jinhui Tang, Chen Zhou, Chong Wang

Journal of System Simulation

To address the constraints imposed by missing trajectory data in surveillance systems on the efficacy of civil aviation safety monitoring, as well as the limitations on the development and application of advanced technologies within trajectory-based operational frameworks, a completion method for trajectory based on image representation and collaborative feature perception was proposed. A conversion strategy for trajectory image representation was designed to reformulate the trajectory completion task as a deterministic image completion problem, effectively circumventing the cumulative error problem of traditional time-series data caused by the limitation of recurrent neural network inference mechanisms.A regression model fusing a multi-kernel hybrid …

Capacity Market Trading Strategies Of Generators Based On Per-Maddpg Algorithm, Yanbin Li, Zhaolun Pan, Xinyue Ma, Minghao Song, Yujie Hu, Xiaoda Xue

Journal of System Simulation

Considering the issue of how power generators trade off their quantity and price bidding strategies to maximize profits in different capacity market environments, a capacity market bidding equilibrium model is constructed. Recognizing the limitations of traditional solution methods, which rely on the assumption of complete information and have low utilization of historical trading strategy information, a capacity market trading simulation method based on prioritized experience replay multi- agent deep deterministic policy gradient (PER-MADDPG) is proposed. The action space is constructed using quantity bidding strategy and price bidding strategy, and the state space is constructed using historical transaction strategies and winning …

Multi-Agent Cbs Path Planning Algorithm Based On Minimum Planning Margin First, Longxiao Liang, Jianlin Mao, Niya Wang, Chengyuan Fang, Wenna Zhou

Journal of System Simulation

To address the problems of chain effect and insufficient solving efficiency in the conflict tree (CT) expansion of the traditional conflict-based search (CBS) framework, a minimum-margin-first CBS algorithm based on planning margin was proposed. The calculation of planning margin was introduced into the underlying A* search, and the robots with the minimum margin were prioritized in the high-level conflict resolution, to suppress the chain expansion of the CT while ensuring path optimality.Simulation experiments show that the proposed algorithm significantly reduces the amount of CT node expansion and the number of root node conflicts and effectively improves the solving efficiency, …

An Automated Generation Method For Combat Simulation Scenarios Based On Large Language Models, Zhiming Dong, Zhongqi Hu, Haoran Dai, Jiancheng Gao

Journal of System Simulation

To address the issue of low efficiency in generating traditional army tactical combat simulation scenarios, an automated generation method based on large language models is proposed. The large language model invokes a semantic segmentation algorithm to parse and restructure the combat scenario, forming semantic modules. Utilizing a multi-agent collaborative framework based on the model contextual protocol, the large language model drives each agent to extract simulation elements from the corresponding semantic modules, constructing a knowledge graph of scenario elements. Using this knowledge graph as a retrieval medium, the method employs a dense retrieval algorithm to achieve precise matching between simulation …

The Structural Limitations Of Mining Output Growth In Nevada, Mckinley Brown, Emma Kitchen

Undergraduate Economics Working Paper Series

This study compares short and long trends in Nevada to the production output within the mining industry. Nevada produces around 70% of the United States gold and about 15% of the world's critical minerals. From its position as one of the most resource rich mining regions globally to its emergence as a growing economic hub, mining played a central role in Nevada's economy. However, despite the industry’s importance, Nevada still faces inefficiencies in production output due to insufficient attention to key inputs such as labor, infrastructure, technology, and energy resources.

In Silico Molecular Docking Study Of Antidiabetic Bioactive Compounds From Brotowali (Tinospora Cordifolia) Targeting Glut4 In Type Ii Diabetes Mellitus, Gita Euaggelion Tarigan, Surya Dwira

Indonesian Journal of Medical Chemistry and Bioinformatics

Type 2 diabetes mellitus (T2DM) is a global metabolic disorder characterized by insulin resistance and impaired glucose uptake. Despite the availability of pharmacological therapies, limitations such as adverse effects and high costs highlight the need for alternative therapeutic candidates. Tinospora cordifolia has been widely reported to contain bioactive compounds with antidiabetic potential; however, comparative evaluation of their interaction with glucose transporter type 4 (GLUT4) remains limited.

This study aimed to identify the most promising bioactive compounds from Tinospora cordifolia targeting GLUT4 using an in silico molecular docking approach, followed by pharmacokinetic and toxicity (ADMET) prediction. Molecular docking was performed using …

Data Driven Estimation Of Pore Size Using 1d Light Emissions For Laser Powder Bed Fusion Additive Manufacturing, Jose Galarza, Jorge Barron, Luis Jimenez, Tamer Oraby, Jianzhi Li, Farid Ahmed

Manufacturing & Industrial Engineering Faculty Publications

The quality assurance of the Laser Powder Bed Fusion Process (LPBF) has been extensively investigated over the last decade for in-situ monitoring of metal additive manufacturing. The process inherently generates voids within the bulk of the part, which can detrimentally affect the quality of the printed part. The characterization of these voids by estimating their size and identifying their geometrical features remains a challenge. This study introduces a Machine Learning (ML) based framework for estimating void sizes of varying geometries using layer-wise one-dimensional (1D) average light intensity signal obtained from the optical tomography system during the 3D printing of metallic …

Robust Identification Of Black-Box Nonlinear Ssm Using Expectation-Maximization, Xiaonan Li, Tao Chao, Ping Ma, Ming Yang, Yuxuan Wang

Journal of System Simulation

To address the robust identification problem of nonlinear state space models (SSM) with outliers, missing observations, and unknown state equations, this paper proposes a modeling method based on eigenfunction expansion, Gaussian-process state-space models (GP-SSM), and Student-t distribution. The proposed approach consists of: modeling the state transition function using eigenfunctions and pre-encoding the priors of basis function coefficients via GP-SSM to enhance flexibility; modeling observations as a Student-t distribution with unknown parameters to enhance robustness against outliers; proposing the enhanced particle Gibbs with ancestor sampling (EPGAS) algorithm to adapt to state estimation in scenarios with missing observations; and deriving unknown model …

Topology Identification Of Complex Dynamical Networks Under Dynamical Saturation Inputs, Haoyu Wang, Yayong Wu, Guoping Jiang, Ying Zheng, Xuanxin Zhou

Journal of System Simulation

In view of the problem that the controller inputs in actual engineering systems are vulnerable to the constraints of dynamical saturation and delayed dynamical saturation, which makes it difficult for the topology identification of complex dynamical networks to adapt to real physical scenarios, a topology identification method based on the drive-response mechanism was proposed. A response network with the same dynamical characteristics and node scale as the original network was constructed, and the dynamical equation of synchronization error between the drive-response networks was established. A controller with dynamical saturation and delayed dynamical saturation and a topology identifier were designed, and …

Robust Two-Stage Mimo-Ofdm Channel Estimation Method Against Sensing Errors, Yi Peng, Jun Wang, Qingqing Yang, Jianming Wang, Hui Li

Journal of System Simulation

To address the challenges of performance degradation, high pilot overhead, and high computational complexity in traditi onal channel estimation methods for integrated sensing and communication (ISAC) assisted MIMO-OFDM systems when radar sensing information contains errors, this paper proposes a robust two-stage sparse channel estimation framework designed to be tolerant of sensing errors. In the first stage, a residual energy weighted simultaneous orthogonal matching pursuit (REW-SOMP) algorithm is designed. Leveraging locally adaptive dictionary expansion and a residual- weighted path selection mechanism, it accurately captures communication-associated paths even under sensing errors. The second stage introduces an adaptive penalty factor alternating direction method …

Dynamic Task Planning For Wargaming Based On Large Language Models, Yingang Liu, Ming Ma, Ronghua Zhang

Journal of System Simulation

To address the problems of great difficulty in intelligent decision-making and insufficient dynamism in task planning caused by the complex adversarial environment and strong uncertainty in wargaming tasks, this paper proposed a hierarchical Agent collaborative decision-making framework based on large and small model synergy.Through a multi-level structure, the hierarchical decoupling and dynamic coordination of battlefield tasks were achieved. A memory management module was constructed, and a query optimization mechanism driven by large language models was introduced to dynamically perceive the decision-making process and query intent, completing the semantic reconstruction and context completion of raw queries. A time-driven two-stage task …

Ultra-Short-Term Photovoltaic Power Prediction Based On Improved Patchtst Considering Data Drift, Huawei Mei, Penghui Yang, Yang Yu

Journal of System Simulation

Existing PV power prediction methods often suffer from limited accuracy and robustness due to three key shortcomings: relying on single-point mapping that cannot fully extract local temporal patterns; inadequate exploration of the global temporal dependencies in PV output, and failure to account for prevalent data drift phenomena. To overcome these limitations,an improved patch time series transformer (PatchTST) based approach is proposed for ultra-short-term PV power prediction. The methodology applies rough set theory for feature dimensionality reduction, effectively preserving critical decision information by analyzing both feature-label relationships and inter-feature correlations. An enhanced PatchTST model with a modified channel-independent mechanism extracts …

Modeling Of Penicillin Fermentation Process Based On A Multi-Stage Lhs-Eprcc Method, Quan Li, Peng Su, Haiying Wan, Chengxi Zhang, Zhijian He, Yiyang Ni

Journal of System Simulation

This paper focused on the modeling of microbial fermentation processes under varying production environments and proposed a novel approach. Considering that the dynamic characteristics of microorganism s differ across growth stages, we introduced the concept of multi-stage sensitivity analysis, in which each stage was investigated separately. The fuzzy C-means (FCM) algorithm was employed to cluster process data under nominal conditions, thereby dividing the penicillin fermentation process into distinct growth stages. Based on this division, the Latin hypercube sampling with partial rank correlation coefficient (LHS-EPRCC) method was applied to conduct sensitivity analysis for each stage, identifying an importance parameter set (IPS) …

Multi-Agent Reinforcement Learning Method For Wargame Simulation Based On Suboptimal Demonstration Guidance, Zicong Zhou, Junjie Zeng, Yue Hu, Zhengqiu Zhu, Quanjun Yin

Journal of System Simulation

To address issues such as fixed behavior patterns and insufficient adaptability in complex adversarial environments exhibited by traditional wargame agent decision-making models, this paper proposes a multi-agent reinforcement learning method based on suboptimal demonstrations (MARLSD). The proposed method integrates reward relabeling with a self-imitation learning mechanism, effectively improving the training efficiency of multi-agent reinforcement learning algorithms in environments with large state-action spaces and sparse rewards, even when only a small number of suboptimal demonstrations are available, while encouraging agents to explore better strategies. Experimental results show that, compared with baselines such as QMIX and MAGAIL, MARLSD significantly improves performance and …

Research On Calculation Model Of Excavation Resistance Under Heterogeneous Soil Conditions, Xin Zhang, Ping Zhang, Chen Zhang, Wei Liu, Boyang Han

Journal of System Simulation

To address the problem of insufficient prediction accuracy of excavation resistance in heterogeneous cohesive soil, a spatial calculation model of excavation resistance at each excavation stage under heterogeneous soil conditions was proposedbased on the cutting wedge model, comprehensively considering multi-dimensional factors such as bucket geometry, side plate effect, lateral force, and inertia. By taking a small crawler hydraulic excavator as the research object, a coupled simulation model of boom multi-body dynamics and soil-rock particle discrete element was established, and the theoretical model was validated through the co-simulation of excavation operations. The simulation results indicate that under the working …

Annotation-Free 6-Dof Grasp Detection Method Integrating Physical And Geometric Priors, Min Shi, Shisheng Guo, Suqin Wang, Zhaoxin Li, Dengming Zhu

Journal of System Simulation

To improve the stability and cross-category generalization capability of grasp pose estimation in complex stacked scenes, an annotation-free 6-DoF grasp detection method integrating physical rules and geometric structure priors was proposed. In the offline stage, a template library of feasible grasp poses was constructed based on multi-physical constraints, without relying on manual grasp annotations. In the network design, the modeling of structural symmetry of objects and spatial overlap relationships was introduced; a geometric guidance mechanism with occlusion perception and exposure modeling capabilities was designed, and robust pose alignment of target objects was achieved by combining keypoint regression. A multi-type stacked …

Detection Method For 3d Lanes Based On Graph Relationship Optimization Integrating Point And Lane Features, Yanji Jiang, Xingyi Xiao, Hao Dong, Miao Yu, Jinshan Huang, Daqian Liu, Bowen Fei

Journal of System Simulation

Under complex road conditions, the thin and elongated structure and small proportion of lanes lead to blurred visual features and insufficient positioning accuracy, which in turn threatens the road safety of autonomous driving. To address these issues, a 3D lane detection method or graph-based point and lane optimization network (GPLNet), based on graph relationship optimization integrating point and lane features, was proposed. Preliminary feature extraction was completed by the backbone network. 3D spatial positional coding with geometric constraints was obtained through a joint query embedding generation module. A graph relationship optimization network was utilized to perform graph relationship calculation and …

Multi-Level Digital Model Of Dynamic Earned Value Management For Complex Engineering Projects And Its Applications, Wei Wang, Dong Liu, Xinhao Cui, Bo Li, Yiyong Xiao, Yi Ren

Journal of System Simulation

The economic management of existing engineering projects is usually based on organizational structure, which presents problems such as complex processes and difficulty in clarifying main responsibilities when applied to complex engineering projects. In response to this limitation, a multi-level digital model of dynamic earned value management is proposed for complex engineering projects, which extends the traditional cost performance indicators to engineering resource utility indicators, thereby decomposing the earned value of costs into segmented earned values of different engineering resources. This enables managers to dynamically supervise projects based on traditional "schedule-cost" performance indicators and carry out more refined cost control …

Hierarchical Motion Planning Of Mobile Robot Based On Dynamic Corridor Inflation And Convex Optimization, Dingkun Zhang, Haizhao Liang

Journal of System Simulation

Motion planning for robots with Ackermann chassis in dynamic complex environments faces nonholonomic constraints and kinematic-dynamic coupling challenges. However, traditional methods suffer from path redundancy, random fluctuations, and local optimality. A hierarchical motion planning method based on dynamic corridor inflation and convex optimization is proposed. Topologically sparse paths are generated by fusing the Ramer-Douglas-Peucker (RDP) path compression operator with the A* algorithm to reduce redundant path points' interference with backend optimization. Dynamic corridor inflation strategies are designed considering Ackermann steering characteristics, and safe corridors satisfying kinematic constraints are constructed via convex decomposition. Corridor constraints are then transformed into linear inequalities …