Engineering Commons^™

Fuel Adulteration Detection Using Open-Ended Coaxial Line And Circular Waveguide Techniques, Abdulrahman Alofi, Ahmed Shamseldin, Sharif Iqbal M. Sheikh, Hussein Attia

Faculty Publications

Fuel adulteration, the practice of blending lower-quality substances like kerosene with gasoline, poses significant challenges for ensuring fuel quality and safety. This study investigates two electromagnetic-based methods for detecting such adulteration: the open-ended coaxial line method and the circular waveguide method. The results reveal that the open-ended coaxial line technique is particularly effective in detecting kerosene contamination, identifying levels as low as 10% by measuring changes in the dielectric constant of the gasoline-kerosene mixture. Operating in the frequency range of 0.25–1.25 GHz, this method captures subtle changes in permittivity. In contrast, the circular waveguide method evaluates contamination by monitoring shifts …

Graphene Screen-Printed Electrode For Wound-Related Biosensing, Chanyapat Sriviroch

USF Tampa Graduate Theses and Dissertations

Monitoring wound healing is critical for improving patient outcomes, especially for chronic wounds, which often have complications like delayed healing and infections. Current methods for monitoring wound healing are invasive and costly. Also, these methods have a limited ability to provide real-time, continuous data. This study seeks to explore a graphene screen-printed electrode (SPE) electrochemical biosensor that is non-invasive and efficient to constantly monitor wound healing in real time. This research study focuses specifically on the electrochemical detection of the Human Neutrophil Elastase (HNE) and Secretory Leukocyte Protease Inhibitor (SLPI), which is one of the most abundant neutral proteinases in …

Al-Driven Interfacial Gap Prediction In Overlapped Al/Cu Laser Weld Joint For Battery Applications, Hyeonhee Kim, Sanghoon Kang, Cheolhee Kim, Yong Hoon Jang, Minjung Kang

Mechanical and Materials Engineering Faculty Publications and Presentations

The battery tab-to-busbar welding process forms the primary electrical path in battery packs and is directly linked to both performance and safety. Variations in jig alignment, material tolerance, and forming quality can cause small interfacial gaps that lead to weak welds. An artificial intelligence (AI)-driven method was proposed in this study for predicting interfacial gaps in aluminum-copper overlap joints by integrating deep learning with multi-sensor data. A charge-coupled device (CCD) camera, spectrometer, and optical coherence tomography (OCT) sensors were employed to develop and validate deep learning models under varying gap conditions. The results revealed that the variation in melt-pool dimensions, …

Utilizing Ensemble Learning Techniques To Enhance Corn Price Prediction: A Case Study On South Dakota, Youssef Harrath, Jihene Kaabi, Ethan Price

Research & Publications

Predicting crop prices is a complex challenge that farmers must navigate each year, but machine learning algorithms can provide valuable insights to support more informed decision making. In recent years, agricultural price prediction models have made significant advances, with architectures achieving varying degrees of success. However, ensuring the accuracy and reliability of these models remains an ongoing challenge. This research explores the use of stacking, an ensemble learning technique, to enhance the performance of base models in predicting corn prices in many regions of the state of South Dakota in the USA. We propose a hybrid architecture that combines Long …

Characterizing Surface Waviness Of Aluminum Alloy: An Approach To Minimize Post-Processing In Wire Arc Additive Manufacturing (Waam) Production, Shammas Mahmood Shafi, Anis Fatima, Nicholas V. Hendrickson

Michigan Tech Publications

Wire Arc Additive Manufacturing (WAAM) offers high deposition rates and cost-effective production of large metal components but suffers from poor surface quality, particularly surface waviness, which increases post-processing requirements and limits industrial adoption. Since waviness directly impacts structural integrity, resource efficiency, and industrial applicability, understanding how process parameters govern this feature is critical for reducing post-processing requirement. This study systematically investigated the influence of voltage, travel speed, and wire feed speed on surface waviness in aluminum alloy walls fabricated by WAAM. A two-level factorial design with 16 experiments was conducted, and surface waviness was quantified using height gauge measurements relative …

Characterization Of Sediment Loads And Size Distribution In Nebraska Roadway Runoff, Pavel Shrestha

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

The Nebraska Department of Transportation (NDOT) must manage sediment and pollutant loads from roadway runoff to meet stormwater regulations for discharges into impaired waters. The SAFL Baffle, a hydrodynamic separator used by NDOT, depends on accurate estimates of total suspended solids (TSS) and particle size distribution (PSD). However, existing studies show large variability in these characteristics, limiting their relevance to Nebraska roadways.

This study monitored stormwater runoff for 1.5 years at four NDOT-maintained sites—two in Lincoln and two in Beatrice—that received runoff from areas outside the roadway right-of-way. The SAFL Baffle was evaluated using the SHSAM (Sizing Hydrodynamic Separators and …

Coupling The Parflow Integrated Hydrology Model Within The Nasa Land Information System: A Case Study Over The Upper Colorado River Basin, P.Eyman Abbaszadeh, Fadji Zaouna Maina, Chen Yang, Dan Rosen, Sujay Kumar, Matthew Rodell, Reed Maxwell

Civil and Environmental Engineering Faculty Publications and Presentations

Understanding, observing, and simulating Earth's water cycle is imperative for effective water resource management in the face of a changing climate. While NASA's Land Information System (LIS)/Noah-MP is widely used for land surface modeling, its ability to represent groundwater processes is limited. In contrast, the ParFlow hydrologic model explicitly simulates subsurface water movement. This study explores the effectiveness and usefulness of the newly coupled modeling framework, ParFlow-LIS/Noah-MP (PF-LIS/Noah-MP) over the Upper Colorado River Basin (UCRB). The framework integrates the strengths of both models to provide a physically based representation of surface and subsurface processes and their interactions. Unlike standalone LIS/Noah-MP, …

Formulation And Characterization Of Albumin Nanoparticles For Nsclc Photochemotherapy, Faisal Mohammad Shamim Khan

USF Tampa Graduate Theses and Dissertations

Non-small Cell Lung Cancer (NSCLC) is the most common type of lung cancer and is a leading cause of worldwide cancer-related death, which is a strong motivation to develop more efficacious approaches to its treatment. This thesis outlines the construction of folate-targeted bovine serum albumin (FA-BSA) nanoparticles co-loading Chlorin e6 (Ce6), a photodynamic therapy photosensitizer, and Evofosfamide (EVO), a hypoxia-activated prodrug, to enable synergistic photochemotherapy. The 1-Ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDC) is a water-soluble carbodiimide coupling reagent and used for amide bonds between carboxylic acid and amines. FA-BSA nanoparticles were prepared through a desolvation approach and stabilized through crosslinking by the carbodiimide reagent …

Systems Intelligence Manager: Warfighter Dominance 2025 Technical Review Key Program, Daniel Hornberger

Space Dynamics Laboratory Publications

Objective & Background

• Objective
• Provide a governing network framework that reduces network congestion and improves connectivity, stability, and resilience
• Provide a single point for systems to connect to on varied networks, which also federates data to required entities
• Manage complex military CONOPs, controlling one or many heterogeneous unmanned platforms while coordinating collection efforts of varying sensor suites on each platform

Atomistic Insights Into Dual Mechanisms For Nacl-Driven Dissolution And Polymerization Of Tricalcium Silicate, Wei Zhang, Jia Sun, Juntao Dang, Bo Tao Huang, Biqin Dong, Hongyan Ma, Dongshuai Hou

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

In this study, experimental characterization and reactive molecular dynamics simulations were integrated to reveal the effects of NaCl on the early hydration of tricalcium silicate (C3S). The results demonstrate that NaCl significantly accelerates the early hydration of C3S by promoting Ca dissolution and silicate tetrahedra polymerization. Specifically, Cl^–ions coordinate with surface Ca, weakening the Ca–O bonds in C3S and reducing the energy barrier for Ca dissolution. Meanwhile, Na⁺ions compete with Ca²⁺for the O atoms, creating localized charge imbalance and attracting protons, which destabilize Si–O bonds and facilitate the polymerization of silicate tetrahedra. These effects …

Shifted Frequency Analysis Hybrid Simulation Algorithm Based On Multi-Rate Asynchronous Coordination, Yankan Song, Libin Wen, Ying Chen, Jinji Xi, Haoyuan Zhang, Li Xiong

Journal of System Simulation

Abstract: Large-scale AC/DC power systems exhibit complex dynamics across multiple time scales, and existing hybrid simulations suffer from interface delays and frequency losses during multi-rate coordination, compromising accuracy. To address this issue, a multi-rate asynchronous coordination method was proposed to construct hybrid simulations using shifted frequency analysis (SFA). Within the multi-area Thevenin equivalence (MATE) framework, the algorithm introduced an interpolation-based asynchronous coordination mechanism, effectively eliminating interface delays; by extending SFA theory and designing a universal interface model, it achieved lossless data exchange between partitions with different rates and model types. Case studies on an AC/DC test system demonstrate that …

Soft Sensor Modeling Based On Improved Transformer In Dual-Stream Framework, Hao Gu, Jiayu Wang, Weili Xiong

Journal of System Simulation

Abstract: Industrial process information is highly nonlinear and dynamic, with long-term dependencies between data, making it difficult to adequately extract time-series features. To address this issue, an improved Transformer-based soft sensor model in a dual-stream framework was proposed. The data were segmented and expanded. The features were extracted in parallel using a dual-stream structure combining a convolutional neural network with a self-attention mechanism and the improved Transformer model. The dual-stream features were fused for soft sensor regression. Residual connections were further introduced to accelerate the convergence speed of the model, and an orthogonal random features-based improved multi-head attention mechanism was …

Path Planning Of Improved Rrt Algorithm Based On Deep Reinforcement Learning, Xiuman Liang, Ziliang Liu, Zhendong Liu

Journal of System Simulation

Abstract: To address the low planning efficiency, poor safety, and limited practicability of the RRT algorithm in global path planning within complex three-dimensional environments, which fail to meet the requirements of planning the safe flight path of UAVs, an improved SAC-RRT algorithm was proposed, which fused SAC deep reinforcement learning algorithm and RRT algorithm. A target point bias strategy and a dynamic step size based on the SAC decision-making network were designed to reduce the blindness of RRT. A random point correction process was designed to optimize the position of random points based on actions from the decision network and …

Low-Energy Multi-Robot Path Planning Algorithm Under Hca* Framework, Ning Wang, Jianlin Mao, Dayan Li, Chengyuan Fang, Chengze Qian

Journal of System Simulation

Abstract: To address the energy optimization problem in multi-robot path planning, this paper proposed a multi-robot path planning algorithm based on the energy-guided hierarchical cooperative A* (E-HCA*) algorithm. To address the issue of robot oscillations caused by mutual avoidance at bottlenecks and narrow passages in multi-robot systems, a node expansion method with path length as a secondary feature was introduced, and a greedy suppression strategy under the cooperative A* framework was proposed. A differential-drive robot energy consumption model was established, and an energy-guided heuristic function was constructed by integrating energy metrics into the underlying A* algorithm to guide low-energy path …

Multi-Objective Optimization Of Signal Timing At Intersections Considering Tailpipe Emissions, Xinhuan Ding, Huaqing Wang, Xu Dang

Journal of System Simulation

Abstract: In order to alleviate urban road congestion and improve the traffic and environmental benefits at intersections, a multi-objective timing optimization model with total delay time, total number of stops, capacity, and total tailpipe emission at intersections as optimization objectives was developed. The model incorporated tailpipe emissions into a mathematical optimization model and quantified the mathematical relationship between traffic efficiency indicators and tailpipe emissions by constructing a specific power-based algorithm for measuring total tailpipe emissions. According to the intersection delay time and the number of stops, the total tailpipe emissions could be estimated. Both the NDX crossover operator and the …

Multisource Information Fusion Method For Human Gait Perception, Guiliang Chen, Guowei Liu, Yongchao Li, Chao Cai, Zihao Li, Dong Yang

Journal of System Simulation

Abstract: In response to the insufficient gait perception capability during lower limb exoskeleton assistance, a human lower limb gait phase optimization classification model was proposed. A wireless transmission gait information collection system was designed for collecting the required gait phase feature information. Human joint angles were accurately calculated by fusing acceleration and angular velocity information using extended Kalman filtering. Additionally, kernel principal component analysis was applied to reduce dimensionality in conjunction with plantar pressure data. The LSSVM algorithm was employed to classify gait data, and the PSO algorithm was utilized to find the optimal classification parameters. Experimental results demonstrate that …

10.20.2025 Ored Connect, Liz Williamson

ORED Newsletter

• OTC Director Candidate Forum
• ORED Small Grants Program RFP

Optimal Scheduling Of Integrated Energy Systems Considering Source-Load Uncertainty And Linear Carbon Trading, Huaping Zhong, Yubo Fan, Jijun Shui, Danhao Wang, Daogang Peng

Journal of System Simulation

Abstract: In order to overcome the impact of source-load uncertainty on the scheduling of integrated energy systems (IES) and reflect the flexibility of the carbon trading price with the change in trading volume, an optimal scheduling method for integrated energy systems considering source-load uncertainty and linear carbon trading was proposed. The equipment within the IES was modeled, and nonparametric kernel density estimation was used to obtain the probability density function for each time period, generating the set of scenes through Monte Carlo simulation and calculating the probability of each scene. For the time shift of wind and solar output peaks …

Simulation Of Three-Degree-Of-Freedom Internal Mode Sliding Mode Control For Non-Ideal Single-Inductor Dual-Output Boost Converter, Bingli Liu, Jiarong Wu, Lin Yang, Dinglin Yan

Journal of System Simulation

Abstract: To reduce the cross-interference in the single-inductor dual-output (SIDO) Boost converter and to enhance the output accuracy and stability of the system, the parasitic resistances of the circuit components were considered, and a three-degree-of-freedom internal model sliding mode control strategy was proposed for the non-ideal SIDO Boost converter. An affine nonlinear mathematical model of the non-ideal SIDO Boost converter was established, and the nonlinear system was linearized and decoupled into two linear subsystems based on the differential geometry theory. The linear subsystem was designed as a three-degree-of-freedom internal model controller and a sliding mode controller, respectively. The robustness …

A Novel Joint Training Simulation Evaluation Framework And Its Key Techniques, Rusheng Ju, Dongdong Chen, Yunxiu Zeng, Jiyuan Liu, Sihang Qiu, Peng Zhou

Journal of System Simulation

Abstract: To address the challenges of traditional evaluation systems, such as internal module coupling, lack of reusability, and poor adaptability to multi-domain evaluation needs, a three-tier decoupled technical evaluation framework of "data + service + application" was designed. A strategy was proposed for extracting high-value information from massive audio and video data based on key events, resolving the problem of unstructured evaluation data processing. A design method combining general and dedicated evaluation model templates was proposed, improving the general applicability of the evaluation model. An expert knowledge-driven comprehensive integrated discussion and evaluation environment was constructed using qualitative and …

An Improved Virtual Terrain Generation Method Based On Simplex Noise, Bo Shen, Jianqin Zhang, Shuaibao Ma, Zheng Wen

Journal of System Simulation

Abstract: To address the issues of high computational complexity, slow generation speed, and insufficient realism present in traditional virtual terrain generation methods, this study proposed an improved virtual terrain generation method based on Simplex noise. This method leveraged the advantages of Simplex noise, such as high computational efficiency, low hardware overhead, and more natural randomness, to construct a basic terrain template. A fractal algorithm was introduced to enhance the level of terrain details through the superposition of noises with multiple frequencies and amplitudes. With the integration of a turbulence algorithm, random perturbations and complexity were added to further improve the …

Research On Constrained Programming Of Manipulator Using Rrt* Algorithm And Ellipse Prior, Zhen Yang, Li Su, Zhiyu Cheng

Journal of System Simulation

Abstract: There are problems in the traditional RRT* algorithm using a uniform sampling strategy applied in constrained programming problems, such as inaccurate turning guidance of sampling points and unnecessary node cost comparisons, which lead to an increase in additional time costs. To address these issues, an improved RRT* algorithm was proposed. This algorithm leveraged a heuristic function cost of the projected sampling points to make an ellipse prior judgment on the sampling points. Based on the ellipse prior, the sampling points were judged to determine whether they could optimize the path and shorten the programming time. The geodesics were used …

Robust Identification Of Dual-Rate Sampled Nonlinear Systems Based On Salr Network, Wenbin Jiang, Yuqing Cao, Li Xie, Huizhong Yang

Journal of System Simulation

Abstract: A robust identification algorithm based on the self-join adjacent-feedback loop reservoir (SALR) network was proposed for dual-rate sampled nonlinear systems with complex nonlinear characteristics and measurement outputs containing outliers. The SALR network was applied to describe the nonlinear characteristics of the target system, and wavelet neurons were injected into the reservoir to enhance its memory and nonlinear description capabilities. The identification problem of the nonlinear system was transformed into the identification problem of the network's output weight matrix. The Huber loss function was used to construct the criterion function, and an error threshold was introduced to improve the robustness …

Distributed Dispatch Method For Distribution Network And Microgrid Considering Diverse Regulating Resources, Yanbo Chen, Jiahao Yin, Tuben Qiang, Haoxin Tian, Yuxin Liang, Zhi Zhang

Journal of System Simulation

Abstract: Traditional centralized optimization-based dispatch methods for distribution networks struggle to balance the interests of multiple stakeholders while ensuring economic efficiency and operational reliability of the system. To address this issue, a distributed dispatch method for distribution network and microgrid considering diverse regulating resources was proposed. The operational models of the distribution network and microgrid were established by comprehensively incorporating active management elements and demand response mechanisms. A fuzzy chance-constrained method was employed to model the uncertainty in renewable energy output, thereby constructing a coordinated optimization dispatch model for distribution network and microgrid under renewable generation uncertainty. An improved goal …

Deep Learning Modeling Of Multi-Scale Characteristics Of Large-Scale Wind Turbine Gearbox, Yang Hu, Zihao Li, Deyi Fu, Ziqiu Song, Fang Fang, Jizhen Liu

Journal of System Simulation

Abstract: To address challenges in characterizing high-frequency vibrations of wind turbine gearboxes, the long computation time of rigid-flexible coupled multi-body dynamics models, and the complexity of configuring gearbox models across multiple scenarios, this study proposed a deep learning modeling method for multi-scale operation using full-condition digital testing. The study proposed a cascaded extended simulation scheme based on stream data-driven OpenFAST and Adams and utilized dynamic mode decomposition technology to construct a multi-scale dataset for the flexible multi-body dynamics characteristics of the gearbox under all operating conditions of the wind turbine. Based on this dataset, a digital surrogate model covering multiple …

Optimization Dispatch Method For High-Proportion Renewable Energy Power Systems Based On Sc-Ppo, Zhongkai Xu, Chenyang Chu, Kai Xie, Ruizhuo Zhao, Wenjun Ke

Journal of System Simulation

Abstract: The high proportion of renewable energy integration brings significant challenges of randomness, multi-objective coupling, and security constraints to power systems. Traditional model-driven methods have limitations in modeling accuracy and adaptability. To address these issues, this paper proposed a safety-constrained PPO algorithm (SC-PPO). The method included three improvements. A temporal convolutional network was utilized to construct a dynamic state encoder that integrated historical operation, real-time monitoring, and prediction data to form a causal state representation. A hierarchical reward structure was designed, and an adaptive weighting mechanism based on constraint satisfaction degree was introduced to coordinate multi-objective optimization. Physical constraint projection …

Microsimulation Of Infectious Disease Transmission Considering Virus Release, Transmission, And Action, Zhiming Fang, Shengdong Yuan, Ge Huang, Jingqian Yang, Zhongyi Huang

Journal of System Simulation

Abstract: Existing infection risk assessment methods mostly evaluate infection probability through mathematical models or simulation, but they lack analysis of the relationship between air circulation and individual infection probability. This study proposed a risk prediction model for infectious disease transmission based on indoor air circulation. At the microscopic scale, the space was discretized into grid points. By integrating CFD numerical simulation, the entire process of virus droplet release, transmission, and action was fully simulated. The simulation results show that in an obstacle-free room, the error between the total indoor viral load predicted by the model under windless and low wind …

Path Planning For Mobile Robots Based On Improved Rrt-Connect And Dwa Fusion, Yi Luo, Jia Deng

Journal of System Simulation

Abstract: To improve the efficiency and quality of dynamic path planning for mobile robots in complex environments, this paper proposed a path planning algorithm that combined an improved RRT-connect with the DWA. Two expanding random trees were introduced for alternating expansion, and a dynamically restricted sampling area was set to reduce the randomness of the sampling process while ensuring the probability completeness of the algorithm. A target bias adaptive step size strategy was employed to enhance the target orientation of the random tree expansion process. A greedy strategy was adopted to prune redundant nodes in the path and smooth the …

Modeling And Simulation Of Traffic Signal Control Based On Mlp With Improved Gcn-Td3, Deqi Huang, Yating Tu, Zhenhua Zhang, Xin Guo

Journal of System Simulation

Abstract: To address the issues of uneven traffic flow at urban intersections, limited road capacity, and the poor coordination of existing traffic signal control algorithms, a traffic signal control algorithm based on graph convolutional reinforcement learning was proposed. By utilizing a multilayer perceptron, the dynamic features of vehicles and phase information at the controlled intersection and its neighboring intersections were extracted. A graph convolutional neural network was then employed to aggregate these vehicle dynamic features into potential features representing regional traffic. The control strategy was derived through multiple iterations of an improved twin delayed deep deterministic policy gradient (TD3) algorithm. …

Dynamic Order Scheduling For Pick-And-Pass System Considering Workload Balance And Learning Effects, Weihong Liu, Sixiang Zhao, Dali Zhang, Zhenhui Jiang

Journal of System Simulation

Abstract: In e-commerce logistics, the hybrid pick-and-pass systems offer both complexity and flexibility, enabling adaptation to a wider range of order picking scenarios. Therefore, they have been widely used. However, this also complicates the order scheduling problem, particularly when both workload balance and pickers' learning effects need to be considered. Efficiently scheduling orders to reduce picking time under these conditions poses a significant challenge. This study began by constructing a mathematical model for the static scheduling problem with known orders. Based on this model, a simulation model of hybrid pick-and-pass zones was developed, and a scheduling rule incorporating multiple system …