Engineering Commons^™

Automation Of Post Fermentation Must Removal, Grace Hurley, Jakob Spink, Ariel Metscher

Industrial and Manufacturing Engineering

The Harvest Haulers project addresses a critical operational inefficiency at Saucelito Canyon Winery, where post-fermentation must removal from wine barrels was labor-intensive and potentially hazardous. This project aimed to develop a custom forklift attachment that could securely handle Bordeaux and Burgundy barrels, streamline the dumping process, and improve worker safety.

The resulting solution is a forklift-compatible fixture designed to lift, secure, and tilt barrels using a robust combination of a modified aluminum pallet, padded hoop, ratchet straps, and a custom hinge mechanism. The design meets all engineering requirements, including a 600 lb. load capacity, 135° tilt, and a single-operator setup …

Supporting Academic Parents: The Effects Of Dependent Care Policies On Research Productivity Trends, Drake Van Egdom, Matthew M. Piszczek, Christiane Spitzmueller, Peggy Lindner, Aaron Clauset

Engineering Management and Systems Engineering Faculty Research & Creative Works

On average, women faculty take on more childcare responsibilities, posing barriers to career success. Work-family policies represent one solution for advancing gender equity in academia as they support parents after childbirth with benefits for children, employees, and organizations. We contribute to understanding how the availability and use of dependent care policies (paid parental leave and childcare benefits) relate to long-term research productivity trends. Based on the work-home resources model, we theorize that policy availability provides contextual resources and policy use provides personal resources, leading to improvements in an individual's research productivity after they have a child. We also examine potential …

From Tarmac To Timetable: A Data-Driven Study Of Airline Delay Performance In Nigeria, Kelechi V. Iwuagwu

Dissertations, Theses, and Capstone Projects

This capstone project investigates the patterns, causes, and impacts of flight delays in the Nigerian aviation sector from January 2024 to January 2025. Utilizing a dataset containing flight details—including scheduled and actual departure/arrival times, routes, and airline information—the study employs advanced data analytics and visualization techniques to uncover critical insights. The research highlights discrepancies between scheduled and actual flight performance, identifies delay patterns across airlines and timeframes, and explores the ripple effects of delays on subsequent flights.

Furthermore, Nigerian passengers frequently express frustrations over flight delays, cancellations, and poor communication from airlines, yet no publicly available data systematically documents these …

On-Demand Heterogeneous Drone Delivery Problem, Xupeng Wen, Zhiguang Cao, Shu Xu, Dapeng Ren, Guohua Wu, Yaoxin Wu

Research Collection School Of Computing and Information Systems

In the on-demand problem domain, actual demand frequently deviates from the expected demand. This paper intricately delves into the exploration of on-demand heterogeneous multi-drone routing problem (ODHDRP), in which a transport drone carries multiple terminal drones to subregions in the first echelon, and the terminal drones deliver parcels during a flight trip to customers with demands in subregions to maintain economies of scale in the second echelon. We formulate the customer demands using a normal distribution, and exploit a reliability model of customer demands with chance constraints. To solve the ODHDRP efficiently, we propose a hybrid iterative optimisation heuristic (HIOH) …

Data-Driven Product Recommendations: A Decision Support Framework Utilizing Customer Reviews, Tyler A. Lopez

Master's Theses

With the considerable presence of e-commerce in society, vast number of purchasable goods, and increasing brand variety, consumers are faced with the challenge of buying products that they perceive to be of greatest value to them. To assist consumers with making better informed decisions, e-commerce websites allow individuals to post their own experiences and score the products that they purchase. Despite this information, the variety of experiences and feedback that consumers share do not always lead to clarity on whether a product is best suited for the purchaser. To help guide customers through a simplified purchasing process from the perspective …

Rotating Scatter Mask System Optimization Study For Determining Optimal Image Recreation, Seth L. Grover

Theses and Dissertations

The Rotating Scatter Mask (RSM) system is a radiation imaging technology currently limited by the mask design and governing identification algorithm parameters. To optimize the RSM design, Dakota—an optimization software—was integrated with a ray tracing code that simulates particle interactions with the RSM detector, and with the Locally Competitive Algorithm (LCA), which reconstructs the source image based on the ray tracing code’s Detector Response Matrix (DRM). Since the original ray tracing code was developed in MATLAB, it was translated into Python to improve compatibility with both Dakota and LCA. The Python version of the ray tracing code was then integrated …

War, Wounds, And Strategy: Patient Movement Lessons From The World Wars For Great Power Competition, Phillip R. Jenkins

Faculty Publications

This thesis examines the evolution of the U.S. military's patient movement system during World War I and World War II to evaluate how well it may perform under the conditions of future large-scale combat operations. It asks whether the United States can move, treat, and sustain wounded personnel at the scale and pace required to preserve combat power in a prolonged, high-intensity conflict. Using detailed case studies of the Meuse-Argonne Offensive and the Battle of the Bulge, the analysis focuses on how transportation platforms, organizational structure, and standard operating procedures (SOPs) shaped patient movement under conditions of attrition, disruption, and …

Machine Learning And Optimization For Intelligent Decision-Making, Elson Cibaku

Dissertations

This dissertation presents a series of innovative machine learning and optimization model designs that address complex operational challenges across logistics and power systems. By integrating advanced neural architectures with robust optimization techniques, the work delivers scalable solutions designed to improve efficiency, reliability, and decision-making in dynamic and real-world environments. The first study introduces a two-stage approach to effective vaccine distribution. This framework tackles the capacitated vehicle routing problem by combining adaptive clustering techniques with reinforcement learning and a simulated annealing pickup policy. Through extensive computational experiments, the approach demonstrates substantial improvements in routing efficiency, reducing both computational time and logistical …

A System Of Systems (Sos) Meta-Architecture Approach To Design Digital Platform-Based Domestic Worker Distribution System, Prithbey Raj Dey, Cihan H. Dagli, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

In this research, a System of Systems (SoS) meta-architecture is conceptualized to design a digital platform-based system framework for the distribution of domestic workers to boost the crowd-sourced economy. While an Object Process Methodology (OPM) is used to articulate the relationships between the objects and functions, a Design Structure Matrix (DSM) has been applied to address the interactions between individual components to categorize them into subsystems to create the SoS architecture. This SoS architecture incorporates several Key Performance Attributes (KPAs) and Key Performance Parameters (KPPs) to systematically evaluate the meta-architectures. The Analytical Hierarchical Process (AHP), Pugh’s Evaluation Matrix, and Technique …

The Prospect Of Geospatial Analysis In The Prediction Of Surface Quality In Machining, Prithbey Raj Dey, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

This research underscores the prospect of geospatial analysis in machining operations to enhance precise prediction and robustness, offering a comprehensive framework of spatial modeling for advanced manufacturing processes. Geospatial analysis not only provides accurate predictions but also estimates the uncertainty associated with these predictions, offering valuable insights for process optimization. The surface quality in the machining processes is expressed by the estimation of the average surface roughness. While machining parameters are extensively analyzed for their influence on surface quality, the roughness profile parameters are inadequately explored. This work integrates these underexplored parameters into geospatial predictive models and evaluates their impact …

Blockchain-Based Ai-Assisted Cyber-Physical Systems For Robust And Reliable Machining Processes, Prithbey Raj Dey, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

This study demonstrates the prospects of Blockchain-based Cyber-Physical Systems (CPS) to establish a scalable framework for designing a secured, automated, and traceable modeling in machining processes. Machining operations like turning, being inherently complex, rely on different types of explanatory parameters such as feed rate, depth of cut, cutting speed, tools, and environmental factors. All of these variables significantly influence key response variables like surface quality, tool wear, cutting forces, and energy consumption. The proposed Blockchain-based framework, designed using the Object-Process Methodology (OPM) systems modeling language, enables the reliable exchange of comparative data streams within a unified data analytics platform. By …

Linear Mixed Model For The Surface Roughness Prediction In Hard Turning Operation, Prithbey Raj Dey, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

Surface machining using hard turning is an intricate operation due to the influence of multiple machining parameters, their non-linear interactions, and the inherent variability introduced by different experimental trials. This study proposes a Linear Mixed Model (LMM) for predicting surface roughness, effectively addressing the challenges in traditional linear models, posed by the influencing factors, non-linearity, and interactions. The LMM incorporates variability from both fixed effects, such as cutting parameters (feed rate, depth of cut, and cutting speed), and random effects arising from tool wear across experimental runs. As a result, it provides a more comprehensive understanding of how these factors …

Research On Grey-Box Modeling Method Of Digital Twins For Cantilever Structure, Wenjia Zhang, Heming Zhang

Journal of System Simulation

Abstract: The construction of accurate and highly real-time digital twin models in complex industrial setting presents several challenges. Traditional model construction approaches based only on mechanism or data show certain limitations. Therefore, this study is based on the idea of grey-box modeling, taking the cantilever structure within a boom-type roadheader as the object, and proposes a novel modeling approach that combines the characteristics of the mechanism model and introduces a self-attention mechanism. This method performs grayscale transformation on the original input and splices it with physical features to achieve organic fusion of mechanism information, which not only enhances the expressiveness …

An Extended Image Features Based Uncalibrated Visual Servoing Method, Shuzhen Zhang, Yukun Cheng, Yangbo Liu, Fusheng Zha

Journal of System Simulation

Abstract: Aiming at the traditional uncalibrated visual servo relying on the estimation of image Jacobi matrix and the coupling of the motion of each degree of freedom of the camera, on the basis of imagebased uncalibrated visual servo, an extended image features based uncalibrated visual servo method is proposed. By analyzing the relationship between image features and camera frames change in the visual servoing process, the visual servoing process in the image space is decomposed into four basic processes: translation, stretching, rotation and scaling; by analyzing the changing of image features in the visual servoing process, extended image features are …

A Modeling And Simulation Method For Firepower Intelligent Decision-Making Of Directed Energy System Basedon Joint Dqn, Changhong Qu, Junjie Wang, Kun Wang, Qingyong Cui, Jiangyang Chen, Xinpeng Wang

Journal of System Simulation

Abstract: In order to solve the problem of dynamically addressing firepower intelligent decision-making in anti-UAV cluster combat using a directed energy system, a deep reinforcement learning model is established. Based on the high multi-agent state and action space dimensions of this model, a modeling and simulation method of firepower intelligent decision-making of directed energy system based on joint deep Q network (DQN) is proposed. The state space is constructed from the state of directed energy system, UAV cluster and the directed energy system deployment area. The joint mechanism is used to share the state information of each equipment and the …

Research On Modeling, Optimization And Application Of Aeroengine Oil System, Shijie Huang, Zhensheng Zhang, Jing Cai, Rui Zhang

Journal of System Simulation

Abstract: In response to the high cost and long cycle of using experimental methods for monitoring, diagnosing, and predicting lubricating oil system, a simulation model for oil system is constructed and optimized, and the application of the model in health management of oil system is proposed. Based on the physical characteristics of the components in the oil system, subsystem models for ventilation, oil supply, thermodynamics, and oil return are constructed using a certain engine oil system as an example, and the whole oil system model is constructed and solved iteratively. The model is optimized by combining particle swarm optimization and …

Adaptive Multi-Scale Feature Pyramid Network For Occlusion Pedestrian Detection, Huaping Zhou, Tao Wu, Kelei Sun

Journal of System Simulation

Abstract: To address the issue of current pedestrian detectors, which struggle to extract complete features in occlusion-heavy environments and consequently have low detection accuracy. A novel adaptive multiscale feature pyramid network is proposed. A multi-scale feature enhancement module (MFEM) is developed. It captures the visible area of pedestrians at different scales through a multi-branch network with different receptive fields. An AFM (adaptive fusion module) is proposed. It calculates the importance of different pixels by optimizing the mean variance at the spatial and feature levels. It enhances the texture and semantic features of pedestrians and fuses the features of different scales …

Design And Realization Of Integrated Energy System Dynamic Stability Simulation And Steady-State Simulation System, Guixiong He, Xiaoqiang Jia, Shufeng Dong, Yonglu Han, Yonghua Chen, Yiming Zheng

Journal of System Simulation

Abstract: Aiming for“carbon peak”and“carbon neutrality”, the energy sector is undergoing significant reform. To address energy flow and planning optimization in integrated energy systems, a comprehensive simulation platform is developed. This platform combines physical and digital simulations with real-world validation and is modular in design, It includes an integrated energy model library, energy flow optimization, modeling management, real-time simulation, and energy monitoring. The platform enhances system safety, stability, and economic efficiency, While also improving planning and energy management. The paper analyzes the platform′s functional and physical architecture, introduces key modules, establishes dynamic and steady-state model libraries, and optimizes energy flow using …

Research On Modeling Methods For Industrial Core Capability Architecture Based On The Dodaf Framework, Xiaoqiang Dou, Yan Liu, Zhilong Zhao, Chao Fu, Fulin Zhang, Shanshan Zou

Journal of System Simulation

Abstract: Against the backdrop of the industrial sector actively pursuing digital capability building, this paper describes the necessity and current status of architecture theory methods guiding industrial core capability construction. It proposes the conceptual connotation of industrial core capability architecture and four key modeling elements. Based on DoDAF, it conducts the overall design of industrial core capability architecture. By integrating systems engineering principles, it establishes a five-stage process model for capability-building activities, embedding critical elements such as capability/business/ application/data/technology architecture viewpoint, and explains data model design, and logical compositions of various viewpoints. By selecting a capability building project in a …

Survey On Large Language Agent Technologies For Intelligent Game Theoretic Decision-Making, Xueqiang Gu, Junren Luo, Yanzhong Zhou, Wanpeng Zhang

Journal of System Simulation

Abstract: The development of artificial intelligence technology has greatly promoted the transformation of the solving paradigm of intelligent game decision problems. From optimal solution, equilibrium solution to adaptive variable solution, how to build an intelligent game adaptive decision agent based on generative large model is full of challenges. The force distribution and multi-entity coordination in the game strong confrontation environment are the core issues in the study of troop deployment and operational coordination. Based on the methods of strategy reinforcement learning, strategy game tree search and strategy preference voting based on skill, ranking and preference meta-game model construction, a large …

Modeling And Simulation Of Intelligent Underwater Acoustic Countermeasure Based On The Matrix Game, Huijin Zhao, Yu Chen

Journal of System Simulation

Abstract: Due to the great threat of torpedo against surface warships, an efficient hydroacoustic countermeasure system must output real-time strategies to accommodate varied antagonizing scenarios. Aiming at the decision-making problem in the anti-torpedo hydroacoustic countermeasure cases, an intelligent adversarial strategy is proposed based on the game theory. By discretizing the strategy space of both sides, a matrix game model is established where the payoff is characterised by the capture probability of attacking torpedo. An improved simplex algorithm is then developed to get the mixedstrategy Nash equilibrium of the game model, which can be used to obtain preferred avoidance strategies to …

Optimal Scheduling Of Virtual Power Plant With Coupled Operation Of Ccs-P2g Considering Wind And Photovoltaic Uncertainty, Xurong Jin, Jiang Yin, Guohua Yang, Wei Li, Guobin Wang, Lele Wang, Na Yang, Xuenian Zhou

Journal of System Simulation

Abstract: In order to solve the problem that the uncertainty of wind power and photovoltaic power generation output easily affects the scheduling of virtual power plant, a new optimal scheduling model of virtual power plant is proposed based on information gap decision theory (IGDT) . In order to reduce the carbon emission of the system, carbon capture and storage (CCS) is installed on the combined heat and power units; in order to improve the utilization rate of renewable energy, the power to gas (P2G) device is introduced into the system, and the operation mode of CCS-P2G coupling is proposed; based …

A Quadrotor Trajectory Tracking Control Method Based On Deep Reinforcement Learning, Guohua Wu, Jiaheng Zeng, Dezhi Wang, Long Zheng, Wei Zou

Journal of System Simulation

Abstract: Traditional quadrotor controllers, constrained by fixed model equation structures, encounter challenges in addressing control errors stemming from variations in parameters and environmental disturbances. This paper proposes a deep reinforcement learning solution for the quadrotor trajectory following control problem. We present the PPO-SAG algorithm incorporated into the PPO framework, utilizing adaptive mechanisms and PID expert knowledge to enhance training convergence and stability. Target functions incorporating distance constraint penalties and entropy policies are designed in alignment with the characteristics of the given problem. We also devise innovative disturbance-adaptive structures and trajectory feature selection mechanisms to augment control error information and extract …

Improved Hybrid Optimization Algorithm For Multi-Objective Ipps Problem, Wenbin Gu, Jiexia Qing, Jie Fang, Siqi Liu

Journal of System Simulation

Abstract: For the problem of multi-objective integrated process planning and scheduling (MOIPPS), an improved hybrid optimization algorithm considering global and local optimum is proposed to optimize two objectives about minimum makespan and energy consumption. A multi-objective problem model and solution framework are established by analyzing the difference and connection between process planning and scheduling in integrated system. A hybrid optimization algorithm is proposed for the two-stage integration problem. In the process planning stage, global search algorithm is employed to provide a variety of process schemes for the integrated system and to ensure the global search performance of the integrated algorithm. …

Optimization Of Cargo Location Allocation In Four-Way Shuttle Warehousing System Based On Two-Stage Hybrid Algorithm, Zisong Wu, Daofang Chang, Yuchun Gai

Journal of System Simulation

Abstract: To address issues such as the dense distribution of storage locations and the potential congestion of shuttle vehicles in the four-way shuttle dense storage system, a grid-based approach to the storage location distribution is developed. A location allocation model is then constructed with the goals of ensuring shelf stability, improving warehousing efficiency, and balancing equipment utilization. A twostage hybrid algorithm is designed for the model. In the first stage, the local search strategy of nondominant sequencing genetic algorithm(NSGA-II) is enhanced by incorporating the hill climbing algorithm to address a set of Pareto front sets. In the second stage, the …

Robot Path Planning Based On Ant Colony Algorithm With Dual Heuristic Information, Xiaohui Zhou, Yanqiang Li, Yong Wang, Decai Zhao, Xiaoyao Yang

Journal of System Simulation

Abstract: The traditional ant colony algorithm is characterized by a slow convergence speed, numerous turning points, and a tendency to fall into local minima. These characteristics make the algorithm less effective for path planning research in mobile robotics. Therefore, this paper proposes an improved ant colony algorithm and applies it to global path planning for robots. The A* algorithm is used to quickly plan a path and increase the initial pheromone of that path, so that the improved algorithm is guided by the global path during the local search, preventing excessive ants from entering dead ends, and reducing the randomness …

A Simulating Framework Construction Method About New Distributed Confrontation, Zhipeng Liu, Yanyang Gu, Baojie Hu, Fangjun He, Zhipeng Fan

Journal of System Simulation

Abstract: The new distributed confrontation in future emphasizes systematic combat and flexible use of power in the resistance environment. To study and analyze the potential threats of such new forms of distributed confrontation, this paper proposes a system confrontation strategy focused on decisionmaking confrontation from the perspective of network and electromagnetic space. In addition, a highly flexible and saleable behavior model adversarial framework is proposed. By parameterizing the network and electrical countermeasure strategy, an adversarial model based on typical airspace scenarios is designed, and the confrontation effectiveness of traditional multifunctional platforms and distributed units is quantitatively compared and analyzed. The …

Research On A Credibility Information Management Method Of Simulation Modeling, Qiming Gu, Jiazhi Chen, Guoyan Cao, Chenchu Zhou, Dengxiu Yu, Haifeng Hu

Journal of System Simulation

Abstract: A proposed method for managing credibility information in simulation modeling draws insights from the NASA-STD-7009 standard for modeling and simulation. From the perspective of credibility information recording, definition, and assessment, this method aims to address the core issue of whether the credibility requirements are met in simulation modeling research. A simulation system credibility information extraction tool is designed to extract three types of information including modeling credibility information, data credibility information, and development process credibility information, enabling recording, definition, and traceability of credibility information in simulation models. Taking a servo system credibility evaluation as an example, a simulation system …

Hierarchical Optimal Scheduling Of Integrated Energy System With Electric Vehicles Based On Empc, Miaomiao Ma, Zijuan Long, Zhiwei Ren, Yongqiang Cheng

Journal of System Simulation

Abstract: A hierarchical real-time optimization (HRTO) based on economic model predictive control is designed to address the issues of randomness and uncertainty of renewable energy and demand-side in integrated energy systems (IES) with electric vehicles. The optimization problem of the entire system is divided into three sub-problems: day-ahead rolling optimization, real-time rolling optimization, and tracking control. The day-ahead optimization strategy based on economic model predictive control is constructed to ensure that the operational units can meet users' demands. The optimal steady-state operating points of the entire IES are obtained through the real-time optimization layer. The tracking model predictive controller is …

Method For Dynamic Coalition Formation Of Wargame Agent For Force Cooperation, Changhua Yao, Shanning Bi, Rufei Ma, Xiaohan Yu, Jiaqiang Li, Jinli Chen

Journal of System Simulation

Abstract: Regarding the issue of cooperative task alliance formation and adjustment in multi-agent dynamic confrontation scenarios at the tactical level, this method comprehensively considers factors such as target value, task allocation, and operator characteristics, as well as the benefits and costs of executing different types of tasks. we propose a targeted force coordination adjustment for dynamic task alliance formation based on behavioral constraints. The “MiaoSuan-Wise Winning Instant Strategy Human-Computer Confrontation Platform” of Chinese Academy of Sciences (CAS) is used as an experimental platform to conduct confrontation experiments. The experiment demonstrates that the proposed method improves the dynamic coordination ability of …