Engineering Commons^™

Automatic Multi-Objective Optimization Based On Dynamic Storage Location Allocation Strategy, Juan Chen, Wang Zheng, Qianqian Liu, Bin Lu

Journal of System Simulation

Abstract: Based on the dynamic storage allocation strategy, the two-stage optimization model is constructed with the whole warehouse as the main optimization body, in order to meet the safety and rationality of the storage allocation goals, and to meet the dispatching goals of the shortest operation time and the lowest energy consumption of each stacke. The upper and lower levels of the model are typical multi-objective optimization problems, and the ideal solution of the upper level model will be the initial condition of the lower level model. The multi-objective genetic algorithm is used to solve the ideal solution of the …

Soft Sensor Modeling Based On Adaptive Sparse Broad Learning System⋅, Kangping Du, Lin Sui, Weili Xiong

Journal of System Simulation

Abstract: To address the challenges posed by nonlinearity and the coupling of multiple features in complex industrial processes, resulting in increased model complexity and decreased performance, a soft sensor modeling method based on adaptive sparse broad learning system is proposed. Building upon the lateral enhancement transmission of features, the trace least absolute shrinkage and selection operator (LASSO) is further used to optimize the feature weights of the network, adaptively adjusting the penalty intensity based on the correlation between different variables to enhance the feature extraction capabilities of the model. The Dropout mechanism is introduced in the enhanced part, and the …

Enhanced Artificial Gorilla Algorithm For Mobile Robot Path Planning, Chen Ye, Peng Shao, Shaoping Zhang, Wenting Li, Tengming Zhou

Journal of System Simulation

Abstract: To address the issues of susceptibility to local optima and slow convergence in mobile robot path planning within complex terrain scenarios, an enhanced artificial gorilla troops optimizer with integration of quadratic interpolation and elite individual genetic strategies (QGGTO) is proposed. The algorithm integrates quadratic interpolation and elite individual genetic strategies to promote information exchange among candidate solutions, thereby accelerating convergence, while maintaining population diversity to avoid local optima. For complex terrains containing both regular and irregular obstacles, a cost function that comprehensively considers walking distance, safety, and turning angles is constructed to uniformly evaluate the path planning performance of …

Multi-Model Based Iterative Method For System-Of-Systems Architecture Design, Xuemeng Zhao, Tianzhu Ren, Zhemei Fang

Journal of System Simulation

Abstract: In order to solve the problems of difficulties in expressing dynamic characteristics and lack of decision analysis support in developing models of the department of defense architecture framework (DoDAF), an integrated iterative method for combat SoS architecture design is proposed. The DoDAF architecture model integrates and expresses combat-related information from multiple perspectives; the ExtendSim executable model simulates the emergence behavior and dynamic characteristics of combat SoS architecture in multiple scenarios; and the decision model quantitatively analyzes and selects architecture schemes by multi-objective decision rules. Ultimately, a SoS architecture integrated iterative design method of "view-simulate-decide-iterate" is formed. The design process …

A Drl⁃Based Approach For Distributed Equipment Nodes Selection, Ziyi Wang, Kai Zhang, Dianwei Qian, Yuzhen Liu

Journal of System Simulation

Abstract: Aiming at the problem of insufficient solution speed and poor generalization of traditional algorithms in large-scale scenarios, this paper intelligently solves the large-scale distributed equipment system preference problem based on deep reinforcement learning. According to the characteristics of distributed equipment system combat, using the complex network to its graph form modeling, and based on the attention mechanism to the equipment between the connecting edge relationship for the characterization, in order to build a distributed equipment system digital simulation environment. Simulation results show that compared with the genetic evolutionary algorithm, the obtained model has obvious advantages in terms of solution …

Life Cycle Costs Of The Little Cottonwood Canyon Transportation Scenarios Under Varied Economic Conditions And Analysis Periods, Emma Reeves, Dane Richards, Darrell Sonntag

Faculty Publications

Abstract— This study revisits the life cycle cost analysis (LCCA) of the Utah Department of Transportation’s (UDOT) proposed gondola project, using recommended best practices for selecting the discount rate, life cycle periods, and conducting a sensitivity analysis on cost projections. We reanalyze the life cycle costs of the five alternatives in the Environmental Impact Statement (EIS) (Scenario 1) across different economic scenarios, and subsequently, we reanalyze the life cycle costs of the Scaled Enhanced Bus (Scenario 2) and Enhanced Bus to Gondola (Scenario 3) from UDOT’s Revised LCCA, using construction dates in the record of decision (ROD) and considering various …

Cellular Automaton Simulation Of Grain And Sub-Grain Evolution With Eutectic Growth In Laser Scanned And Rescanned Al–10si, With Experimental Validation, Kai Kang, Lang Yuan, Can Sun, Javier Miranda, André B. Phillion

Faculty Publications

This study presents a three-dimensional Cellular Automaton (3D CA) model incorporating eutectic growth mechanisms to simulate grain and sub-grain structure evolution in an additive manufacturing (AM) scenario, with surface laser rescanning of Al–10Si alloy as a case study. Unlike conventional CA models in AM, this work introduces a eutectic solidification framework within the CA approach, allowing dynamical transitions between dendritic and eutectic growth modes based on local thermal and solute conditions. The CA model integrates finite element analysis (FEA)-derived thermal data, solute redistribution tracking, nucleation behaviors, and growth kinetics under rapid solidification conditions in laser scanning and rescanning. The simulation …

Integrated Decision Support System For Optimizing Time And Cost Tradeoffs In Linear Repetitive Construction Projects, Ahmed Gouda Mohamed, Ali Hassan Ali, Ahmed Adel Abdelhady

Civil Engineering

No abstract provided.

Simulation Study On Adaptive Signal Control Of Deformed Intersection Based On Lstm-Gnn, Kun Chen, Liang Chen, Jiming Xie, Fengbo Liu, Taixiong Chen, Lukuan Wei

Journal of System Simulation

Abstract: Aiming at the traffic congestion at deformed intersections, an improved adaptive traffic signal control scheme based on deep learning is designed, the scheme integrates the adaptive signal control of LSTM and GNN at deformed intersections. LSTM is used to capture the dependence between time series traffic data, while GNN is used to construct a spatial interaction model between lanes. By integrating the information of time and space dimensions, the model can dynamically adjust the phase duration of signal lights according to real-time traffic conditions. The results indicate that the LSTM-GNN adaptive control scheme improves overall traffic throughput efficiency by …

Modeling And Simulation Of Dual-Podded-Propulsion Ship Motions, Bing Han, Yunhe Lin, Yuhang Chen, Zhouhua Peng

Journal of System Simulation

Abstract: Aiming at the autonomous navigation control requirements of the Dalian Maritime University's dual-purpose intelligent research and training ship "Xin Hong Zhuan," the design of the motion model for this dual-podded-propulsion ship is carried out. Utilizing an MMG model structure, it calculates the hull's hydrodynamic viscous forces, single/dual-propeller thrust, and hydrodynamic forces acting on the podded propulsion units. Based on data from sea trials and open-water propeller tests, straight-navigation resistance is derived via data fitting, while a method using simulated turning circle tests and PSO algorithms is proposed to determine some hydrodynamic coefficients, refining existing empirical formulas. The model's maneuvering …

Simulation Study On Optimizing Microgrid Scheduling With Electric Vehicle Participation Under V2g Mode, Zhongan Yu, Hongliang Xiao, Qiangwei Xia, Jiawei Liu

Journal of System Simulation

Abstract: To address the negative impact of source-load uncertainty on the stable operation of the grid, a two-stage optimization scheduling strategy for the microgrid participation of electric vehicles based on the vehicle-to-grid (V2G) mode is proposed. In the first stage, the charging and discharging costs of electric vehicles as well as the load fluctuation target are determined taking into account the battery losses. Through a zero-sum game, we objectively weigh the interests of both vehicle owners and the microgrid, utilizing the mobile energy storage characteristics of electric vehicles to optimize the load curve and integrate renewable energy; in the second …

Construction Method Of Digital Twin System For High-Low Temperature Test Chamber, Qinghua Chen, Zuoyou Liang, Weijuan Guan, Jiadong Ji, Ping Liu

Journal of System Simulation

Abstract: In view of the construction requirements of the digital twin system of the high-low temperature test chamber, the EMQX server with MQTT as the communication protocol is used for data transmission. Driven by real-time data, real-time dynamic interactive mapping between the physical entity and the virtual model is realized. The neural network model and genetic algorithm are used to evaluate and predict the running state of the equipment and provide the system adjustment strategy, so as to realize the whole climate, life and working condition of the staff to understand the running state of the equipment, and effectively ensure …

Cooperative Guidance For Multigroup Flight Vehicles Against Multiple Targets With Separated Impact Time, Guofei Li, Shituo Li, Yilun Huangfu, Yueyang Hua, Yunjie Wu, Zongyu Zuo

Journal of System Simulation

Abstract: To cope with cooperative guidance against multiple targets, a distributed cooperative guidance for multigroup flight vehicles to strike multiple targets with separated impact time is proposed. The collaborative variables for multigroup flight vehicles with separated impact time are given, and the guidance law in the line of sight (LOS) is proposed. The guidance laws on the normal and lateral directions of the LOS are proposed to make the LOS deflection angle rate and LOS the inclination angle rate converge rapidly, which ensures that each vehicle is able to strike the target. The finite-time convergence of the proposed guidance laws …

Dynamic Path Planning For Robotic Arms Based On An Improved Ppo Algorithm, Yuhang Wan, Zilu Zhu, Chunfu Zhong, Yongkui Liu, Tingyu Lin, Lin Zhang

Journal of System Simulation

Abstract: Aiming at the increased environmental uncertainties and more difficult modeling for robotic arm path planning in unstructured environments, an approach to dynamic path planning of robotic arms based on an improved PPO algorithm is proposed. In order to solve the problem that the input length of the state space is not fixed due to the change of number of obstacles in dynamic environment, an environmental state input processing method based on the LSTM network is proposed, and the network structure of PPO algorithm is also improved; a reward function is designed based on the artificial potential field method, and …

Aerial Target Detection Algorithm Fused With Multi-Scale Features, Lu Yang, Junying Pei

Journal of System Simulation

Abstract: In order to solve the problem that UAV aerial images have a large number of small target samples but little extractable feature information, which is not conducive to improving the accuracy of aerial target detection, an improved small target detection algorithm for aerial photography based on YOLOv8s is proposed. The algorithm applies deformable convolution to the feature extraction module of the backbone network to adaptively capture the details of the target at different locations and scales. The feature information at different scales of the backbone network is extracted and enhanced by the feature collection module in the multilevel information …

Operation System For Simulation Roadheader Based On Visual Motion Capture, Yongling Li, Lingzhi Liu, Baishun Zhou, Jingfa Lei, Miao Zhang, Ruhai Zhao

Journal of System Simulation

Abstract: To enhance the natural human-machine interaction in simulation roadheader environment, a vision-based simulation roadheader operation system is proposed. The visual motion capture unit is based on the MediaPipe framework, which captures hand gestures through cameras and creates a correspondence between the physical world and virtual space. An improved Kalman filter algorithm is proposed by setting a weighted centroid to address the issue of unreasonable jumps in hand keypoint data during large-scale movements. The operator's gestures are discerned and the corresponding commands are conveyed. The results show that the improved method has significant advantages over the control group in terms …

Research On Behavior Control Techniques For Autonomous Vehicles Based On Parallel Behavior Tree Architecture, Jianchao Yuan, Shuo Yang, Qi Zhang, Ge Li

Journal of System Simulation

Abstract: Aiming at the problem of high collision rate and low efficiency of traditional serial behavior tree in autonomous vehicle control, a solution based on improved parallel behavior tree architecture is discussed to achieve safe behavior control. A safety behavior control strategy under dynamic road conditions is proposed, and behavior models for observation, decision-making, and movement are constructed, as well as their temporal constraint relationships; an improved parallel behavior tree control architecture is proposed, which achieves parallel execution and real-time interaction of behaviors through parallel control nodes, improving the real-time performance of decision control. The results show that compared with …

Research On Improving Design Efficiency Of Coaxial Magnetic Gear Based On Linear Model, Shuguang Zhao, Ce Chen, Xiaochang Xie, Fuping Li, Jin Han

Journal of System Simulation

Abstract: To address the issues of large model computation load and cumbersome magnetization direction setting during the simulation design of coaxial magnetic field modulation type magnetic gears, a simplified design method is proposed, which uses a linear model to replace the original conventional circular ring model. Based on the periodicity of the structure and magnetic field of each part of the magnetic gear, the modeling work is simplified and the computational load of the simulation analysis is reduced. The results show that compared with the circular ring structure, the number of magnetization coordinate system settings for the linear structure is …

Towards Sustainable Manufacturing: A Framework For Resource Conservation And Waste Mitigation, Mahmood Talal Sultan

Thesis/ Dissertation Defenses

The manufacturing industry drives economic expansion, but it also contributes significantly to environmental change and shortages of resources. Therefore, the transformation to sustainable manufacturing has become an urgent need, driven by worldwide efforts to address climate change, minimize waste, and protect valuable assets. This thesis develops a robust framework tailored to the manufacturing sector, focusing on resource conservation and waste reduction. The framework is built on the identification and categorization of Key Performance Indicators (KPIs) and assessment tools, which address five major implementation challenges: complex supply chains, regulatory barriers, economic challenges, technological limitations, and social and cultural challenges.

To build …

Artificial Intelligence In Surveillance And Privacy, Elizabeth D. Brasher

NEXUS: The Liberty Journal of Interdisciplinary Studies

This paper attempts to provide insight into the new and developing world of artificial intelligence and its integration into surveillance technologies. These technologies being implemented by the government, retail companies, healthcare organizations, and more, all raise ethical questions and implications addressed in this article; other topics, such as the integration of Christian ethics and responsibilities, are also explored.

Empowering Tanzanian Education: Personalized And Accessible Test Preparation, Brian Wiebe, Shiv Jhalani

Computer Science and Engineering Senior Theses

Only 20% of students performed well enough on their secondary exams to continue their A-level studies. This challenge exists due to a lack of resources, classroom overcrowding, and absenteeism of the instructors. The project focuses on improving the pass rate for these national exams; we have built an intelligent quiz generating platform that helps Tanzanian students prepare more effectively for exams by meeting user needs including active recall, answer explanations, increasing difficulty, and filtered studying. Students can select the subject, form level, topic, and the difficulty level, and the platform provides different types of questions, including true/false, multiple choice, and …

Bridging Virtual Robots And Physical Tasks Via Augmented Reality, Xiangfei Kong

USF Tampa Graduate Theses and Dissertations

Entry to human-robot interaction research, e.g., conducting empirical experiments, faces a significant economic barrier due to the high cost of physical robots, ranging from thousands to tens of thousands. This cost issue also severely limits the field’s ability to replicate user studies and reproduce the results to verify their reliability, thus offering more confidence to incorporate these findings. Although virtual reality (VR) user studies present a potential solution, it is unclear whether we can confidently transfer the findings to physical robots and physical environments because VR isolates both the physical robot and the physical world where robots operate. To address …

Embedding-Based Deep Learning Frameworks For Multimodal Oncology Data Integration, Aakash Gireesh Tripathi

USF Tampa Graduate Theses and Dissertations

This dissertation presents a cohesive set of novel frameworks developed to address critical challenges in oncology data integration, representation learning, and clinical information extraction. The work encompasses four interconnected projects: MINDS (Multimodal Integration of Oncology Data System), HoneyBee (Harmonized ONcologY Biomedical Embedding Encoder), LLM Extraction (Large Language Model-based Extraction from Pathology Reports), and EAGLE (Embedding Analysis for Generalized Learning in Oncology). Together, these systems enable the unification of diverse cancer data modalities—from genomics and clinical records to histopathology images and radiological scans—creating a robust foundation for advanced machine learning applications in precision oncology. By addressing key barriers in data accessibility, …

Examining Green And Chemical Methods For Zero-Valent Iron Nanoparticle Synthesis In Heavy Metal Adsorption, Juan Ferro-Falla, Lewis Stetson Rowles, Farith Diaz Arriaga, Jaime Plazas-Tuttle

Civil Engineering & Construction: Faculty Publications

The increasing concern over heavy metal contamination in water has necessitated the development of sustainable and efficient treatment methods. This study compares two synthesis approaches for zero-valent iron nanoparticles (nZVI) for cadmium, chromium, and arsenic removal: chemical reduction using sodium borohydride and green synthesis utilizing cocoa husk extracts combined with hydrothermal carbonization (HTC). Chemically synthesized nZVI exhibited high initial removal efficiencies (>98%), though desorption effects occurred over time due to particle aging. In contrast, green-synthesized nZVI, stabilized by a carbon matrix, maintained consistent removal efficiencies above 98% for 120 h under acidic conditions, showcasing superior stability and reactivity. Characterization …

Data-Driven Machine Learning Applications For Predictive Modeling Of Petrochemical And Ecofrendly Systems, Noora Al Mansoori

Thesis/ Dissertation Defenses

Traditional experimental approaches in industrial processes, such as Fourier Transform Infrared Spectroscopy (FTIR) spectroscopy, thermogravimetric analysis (TGA), and well-drilling operations, are often constrained by time, cost, and operational limitations. This research explores the application of data-driven Machine Learning (ML)-based predictive modeling to improve efficiency and reduce dependency on resource-intensive experimentation. The study develops ML models for three distinct processes: FTIR intensity prediction of bitumen thermal cracking products, thermal degradation of Medium-Density Fibreboard (MDF) using TGA data, and Rate of Penetration (ROP) prediction in petrochemical industry. Six algorithms: Linear Regression (LinReg), Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), Gradient …

Engineering Bio-Based Poly (Ethylene Furanoate) Blends And Nanocomposites, Safa Fadl Eldin Mohamed

Thesis/ Dissertation Defenses

The growing demand for sustainable materials has directed attention toward bio-based polymers such as poly(ethylene furanoate) (PEF), a 100% bio-derived alternative to PET. While PEF offers excellent gas barrier and thermal properties, its limited mechanical strength restricts its use. This study explores polymer blending and nanocomposite strategies to enhance PEF’s mechanical and electrical performance.
Blending PEF with linear low-density polyethylene (PE) using reactive compatibilizers (SEBS-g-MA, PE-g-MA) significantly improved ductility and tensile toughness. Interfacial reactions between PEF and compatibilizers transformed the blend morphology, resulting in improved flexibility suitable for packaging applications.
Electrically conductive composites were developed by localizing graphene nanoplatelets (GNP) …

Knee-Thigh-Hip Impact In Children: Effects Of Age And Impact Velocity, Mohammad Ziad Turki

Thesis/ Dissertation Defenses

Brief introduction: This thesis examined the crash impact injury outcomes of the knee-thigh-hip complex (KTH) in children based on age and impact velocity using computational modelling. Child occupant (3YO, 6YO, 10YO) Total Human Body Model for Safety (THUMS) models developed by Toyota were used to evaluate the effects of age and impact velocity on pediatric KTH crash impact response. Aims: The main objectives of this thesis are to analyze the effect of child age and impact velocity on KTH crash impact response. Methods: The knee impact simulations were performed based on different impact velocities (1.2, 3.5, 7.2, …

An Integrated Geophysical Approach For Estimating The Depth Of Mineral Potential In Some Part Of Basement Complex Terrain Southwestern Nigeria, Hamid Titilope Oladunjoye, Joseph Coker, Niyi-Ola Adebisi, Omolara Abosede Adenuga, Sofiat Adetomilola Adekoya, Aderemi Alabi, Abisola Akinmoladun

Al-Bahir

Effective mineral exploration in a basement complex necessitates precise delineation of overburden thickness and mineral potential within the Basement Complex terrain. This study examined the subsurface geology and assesses the abundance of prospective mineral deposits within the study area The objective of the study was to outline the overburden thickness and infer mineral potential using integrated ground magnetic and electrical resistivity geophysical methods. The electrical resistivity method unraveled the litho-stratigraphic sequence as surmised from geo-electric layers. Consequently, the mineralization of the basement delineated was characterized by the magnetic method. The acquired data were processed using WINRESIST and Oasis Montaj respectively. …

Cross-Cultural Inspiration Coach, Romeo Nickel, Veronica Flores, Rahul Rani, Andrew Yang

Computer Science and Engineering Senior Theses

Personal inspiration and motivation are fundamental drivers of well-being and growth, yet current digital wellness solutions predominantly reflect Western perspectives, failing to address the diverse cultural contexts through which inspiration manifests globally. This thesis presents the development of an Inspirational Coach platform that leverages artificial intelligence to deliver culturally-adaptive personal development content. The system employs a fine-tuned Llama 3.1 8B model using Low-Rank Adaptation (LoRA) techniques to generate personalized motivational content that incorporates users’ cultural backgrounds, personal themes, and individual preferences.

The platform integrates four core features within a comprehensive React-based web application: guided journaling with mood tracking, goal setting …

Teaching Computer Science Through An Educational Game, Aidan Walker, Matthew Leonard, Grant Goldman

Computer Science and Engineering Senior Theses

In our ever-evolving technological landscape, it is becoming more and more important for students of all ages to have at least a basic concept of coding fundamentals. It’s not just the basic knowledge of how to code; knowing important coding concepts is just as important. To help introduce these concepts to young students, we developed an educational game in the Roblox platform aimed at teaching foundational programming concepts—specifically recursion—to young learners through interactive and engaging gameplay. Leveraging Roblox’s accessibility and popularity among younger audiences, the game introduces players to recursive thinking in a visual and intuitive manner. Players control a …