Engineering Commons^™

Hybrid Jaya-Transformer-Based Task Scheduling Algorithm For Super-Agile Satellites, Haoyu Zhao, Guanghui Zhang, Lanting Hao, Meijia Guo

Journal of System Simulation

Abstract: Super-agile satellite task scheduling is characterized by complex constraints and tight coupling among task transitions. To address the relatively long online solution times of traditional heuristic algorithms, this paper establishes a super-agile satellite task scheduling model that aims to maximize the task profit ratio while considering constraints on visible time windows, attitude transition time, energy, and storage capacity. A Transformer is used to learn task requirements, visible time windows, and global correlations among tasks, and a dynamic mask and a task scheduler are incorporated to generate feasible task sequences. To enhance the model's ability to learn complex task correlations …

Aerial Refueling Scheduling Plan Generation Method For Multi-Position Task Management *, Jiachen Hu, Huanyu Li

Journal of System Simulation

Abstract: An aerial refueling scheduling plan generation method based on hierarchical hybrid strategy is proposed to address the high complexity of aerial refueling scheduling for multi-position tasks and the difficulty for traditional manual operations or single-position-oriented solutions to manage tasks effectively. A multi-level strategic framework based on fixed-rule heuristics, rolling horizon optimization, and steady-state cyclic scheduling is developed and integrated into a hierarchical hybrid strategy to balance scheduling efficiency, optimization capability, and emergency response capability. Simulation results demonstrate that the proposed method effectively generates feasible refueling scheduling plans, producing viable plans under both undisturbed rotational operations and disturbed dynamic support …

Flight Test Mission Planning Method Based On Adaptive Large Neighborhood Search, Luofu Wu, Xinyang Wu, Lunhao Ju, Guopeng Song, Rui Wang, Jiang Jiang

Journal of System Simulation

Abstract: Flight test mission planning is critical to aircraft performance evaluation, but traditional manual methods often struggle with extensive solution spaces and complex constraints. This paper constructs an overall flight test mission planning model and introduces a flight test planning algorithm (FTPA) based on adaptive large neighborhood search. FTPA utilizes Kahn topological sorting to generate an initial test-item priority sequence, which is then decoded into an initial solution, and jointly schedules flight test items and test aircraft within the adaptive large neighborhood search framework. A comparison with the CPLEX solver shows that the FTPA algorithm yields solutions with a gap …

Large Language Model-Assisted Control Framework For Mixed Remote Sensing Satellite Constellations, Guohua Wu, Ziyan You, Lei Li, Yi Gu, Shuanglin Li

Journal of System Simulation

Abstract: A LLM-assisted control framework for mixed remote sensing satellite constellations is proposed to address the problem that the control and scheduling of mixed remote sensing satellite constellations cannot process users' raw natural language observation requirements and realize full-process automation from requirement input to scheduling schemes. LLMs are utilized to enhance the construction of domain knowledge graphs, requirement understanding and task characterization, and realize intelligent generation of scheduling schemes and optimal solution of scheduling models. A scheduling scheme generation method based on the "planning and execution" dual-Agent architecture is designed. Combined with the constellation scheduling toolset, the capability boundary of …

On-Orbit Refueling Mission Planning Of Satellites Based On Improved Nsga-Ii, Guozheng Li, Rui Wang, Yi Lu

Journal of System Simulation

Abstract: An improved NSGA-II solution framework based on multi-tree encoding is proposed to address the problems of high modeling complexity under large-scale scenarios and the tendency of traditional algorithms to fall into local optima. Based on multi-tree modeling, the complex mixed-integer programming problem is transformed into a multi-tree configuration optimization problem, thus reducing the constraint handling difficulty and improving the search efficiency of the solution space. Multi-tree crossover and mutation operators as well as the calculation method for objective functions are designed. A large neighborhood search (LNS) strategy is introduced, and the global exploration and local exploitation capabilities of the …

High-Fidelity Dynamic Digital Twin Modeling Method For Permanent Magnet Synchronous Motor, He Lai, Jinquan Yang, Cong Peng, Bei Li

Journal of System Simulation

Abstract: Conventional mechanism models often suffer from model mismatch due to the absence of nonlinear mechanical damping representation and the dynamic drift of electromagnetic parameters. To address this issue, a high-fidelity dynamic digital twin modeling method for permanent magnet synchronous motors is proposed. In the static mechanism modeling dimension, a friction energy decoupling strategy is proposed, which fundamentally overcomes the inherent conflict between steady-state accuracy and transient response from a physical logic perspective. For dynamic model updating, a distributed cascaded sensing architecture based on the multi-innovation recursive least squares and extended Kalman filter (MIRLS-MIEKF) algorithms is proposed. This architecture enables …

Scheduling Optimization For Cascaded Hybrid Flow Shop Integrating Llm And Rl, Fuqing Zhao, Bin Wu, Tianpeng Xu, Ningning Zhu, Houbin Song, Yukai Yao

Journal of System Simulation

Abstract: For the cascaded hybrid flow shop scheduling problem with AGV transportation, a multiobjective optimization model is built to minimize the makespan and total energy consumption. A hybrid algorithm framework integrating the LLM, covariance matrix adaptation evolution strategy, and RL strategy selection mechanism is proposed. LLMs are employed to generate heuristic priority rules and construct high-quality initial solutions. Covariance matrix adaption evolution strategy is adopted to optimize the search in continuous priority space, and an enhanced scalar fitness function integrating hypervolume gain and solution diversity is introduced. An RL strategy selection module based on the upper level information boundary is …

Q-Learning Enhanced Memetic Algorithm For Robust Scheduling Of Space Launch Missions, Rui Lin, Xiaolu Liu, Yonghao Du, Mingyang Geng, Zhenshun Shi

Journal of System Simulation

Abstract: A robust optimization mathematical model and an enhanced memetic algorithm (MA) for space launch mission scheduling are proposed to address the practical challenges in space launch mission scheduling under the influence of multiple uncertainties such as equipment failure, process rework due to quality issues, and technological changes. A robust optimization scheduling model for space launch missions is built by integrating the makespan under the worst-case scenario, the average maximum makespan, and the average deviation of process start times. A Q-learning enhanced memetic algorithm (QMA) is proposed, which can dynamically select parent solutions based on the population state. Simulation experiments …

A Philosophical Introduction To Elements And Relations: Aspects Of A Scientific Metaphysics, Martin Zwick

Complex Systems Faculty Publications and Presentations

My book, Elements and Relations*, amplifies Bunge’s characterization of the systems project as the construction an “exact and scientific metaphysics” (ESM) different from and broader than the reductionist and physicalist ontology of conventional science. This paper discusses the scientific theories constituting this project and the central notion of “system” as a structure-function dyad, where “structure” is the system’s internal order and “function” is its participation in the external order of its environment. The paper also discusses the book’s proposal of ontology and ethics as a structure-function dyad for the systems field, an ontology of problems that exemplifies the ESM idea.

The Pure Water Project, Colton Casey, Anna Engelman, Abby Strobel

Sustainability Conference

After earthquakes devastated Haiti in 2010, a team of Embry-Riddle students and faculty built and installed a solar-powered water purifier to improve both the environmental and human health concerns created by the lack of infrastructure, clean water, and sanitation. Since then, the group Pure Water Project has installed 12 water purifiers in orphanages, clinics, schools, and community centers in Haiti and the Dominican Republic. The group relies on its partner selection criteria and local contacts to determine the installation site for the purifier. The fall and spring semester leading up to the installation trip in May are spent designing, building, …

A Macroergonomic Analysis Of Autonomous Robotic Construction For Affordable Housing, Ricardo Leon Jimenez

Sustainability Conference

As communities seek to increase housing supply, the construction sector continues to grapple with rising costs, skilled labor shortages, and growing pressure to improve environmental sustainability. Meeting these demands will require new approaches that increase productivity while lowering environmental impact throughout the building lifecycle. Recent advances in autonomous systems developed for space exploration offer alternative ways to design, assemble, and maintain residential buildings. This study examines the potential application of NASA's Automated Reconfigurable Mission Adaptive Digital Assembly Systems (ARMADAS) technology from space construction to terrestrial affordable housing construction.

While most construction automation research focuses on technical performance, this study considers …

A Performance-Based Indicator Framework For Assessing Innovative Materials In Modular Emergency Shelters, Riham Nady Faragallah, M. S. Refaey, Naglaa M. Yussuf, Riham S. Hassan

HBRC Journal

In recent years, the increasing intensity of disasters, conflicts and mass displacement has amplified the need for emergency shelters that are rapidly deployable, structurally safe, and thermally comfortable, particularly when delivered through prefabricated modular systems. The recent development of innovative materials—including smart, recycled, bio-based, and 3D-printed composites—has demonstrated considerable potential for improving emergency shelter performance. However, existing studies primarily evaluate these materials individually, with limited efforts to integrate them into a comprehensive performance-based decision framework for modular emergency shelters. This research aims to develop a performance-based indicator framework for evaluating and selecting innovative materials to enhance the safety, comfort, durability, …

Two-Stage Stochastic Programming For Resource Allocation In Mobile Underwater Acoustic Networks, Sadaf Vahabli, Iftekhar Ahmad, Quoc Viet Phung, Daryoush Habibi

Research outputs 2022 to 2026

Underwater Acoustic Networks (UANs) enable long-range communication for a range of applications. However, UANs are severely limited by scarce acoustic spectrum, which is shared with marine animals and can lead to disruptive interference, contributing to anthropogenic ocean noise. In addition, the underwater environment is highly dynamic, where: marine-animal presence is uncertain, channel conditions fluctuate, and Doppler effects degrade communication reliability. Prior UAN studies have addressed these challenges separately, despite their combined effect on resource allocation. Accordingly, this paper proposes a two-stage Scenario-based Stochastic Programming (SSP) framework with a hybrid risk approach that jointly treats these challenges within a single resource …

Adaptive Improved Particle Swarm Optimization-Based Maximum Power Point Tracking And Energy Smoothing For Photovoltaic Hybrid Battery–Supercapacitor Storage Systems, Mohammad Aminul Islam, Guo Shaokai, Jakaria Mahdi Imam, Mohammad Khairul Basher, Nowshad Amin, Tarek Abedin, Mohammad Nur-E-Alam

Research outputs 2022 to 2026

The rapid development of photovoltaic (PV) systems has made them an important component of the global clean energy strategy. However, the intermittency and non-linear characteristics of photovoltaic (PV) output remain major challenges for stable renewable energy utilization. This study proposes an adaptive improved particle swarm optimization (IPSO)-based maximum power point tracking (MPPT) strategy integrated with hybrid energy storage coordination for photovoltaic systems. The IPSO introduces adaptive inertia adjustment, velocity clamping, and stagnation reinitialization, which improve the convergence robustness under dynamic irradiance and temperature conditions. The algorithm was benchmarked against Perturb & Observe (P&O), Incremental Conductance (INC), and standard PSO using …

Several Complex Variables, Pseudoconvexity, And Plurisubharmonic Defining Functions, Luka Mernik

Math Department Colloquium Series

This talk introduces some basic concepts in several complex variables and explains the role of pseudo convexity through two fundamental topics: Hartog’s' extension phenomenon and the Levi problem. A stronger property than pseudo convexity is the existence of a plurisubharmonic defining function. Such defining functions play an important role in the study of analytic objects associated with a domain, including the regularity of the d-bar Neumann operator and the Bergman projection. The main question of this talk is whether a pseudo convex domain admits a plurisubharmonic defining function. We approach this question in two steps. First, we establish a necessary …

Education Before Electricity: Ai-Facilitated Capability Formation As A Pre-Condition For Productive Energy Use In Off-Grid Communities, Kevin Hallinan, Lu Hao, Bennywhite Davidson, Divinegift Morris, Confidence Onuahu, Silas Clergy

Mechanical and Aerospace Engineering Working Papers

Solar microgrids in sub-Saharan Africa routinely fail to generate the productive demand needed to service their investment, because the capability to convert electricity into economic activity does not exist at electrification. We report a 15-month deployment in Oloibiri, Nigeria, a community whose productive base was displaced by oil extraction, testing whether AI-facilitated learning can build that capability at a cost compatible with microgrid investment.

The Davidson AI Innovation Center enrolled 104 learners (136 accounts) with zero prior computer access. They recorded 4,134 learning sessions, and 25 individuals earned 90 certifications on unscaffolded work, for just over $20,000 in cumulative investment, …

Metal Oxide Semiconductor Gas Sensors For Exhaled Breath Cancer Biomarker Detection, Guang-Lan Chen, Hui-Hui Luo, Wen-Wen Peng, Shi-Yu Xu, Yu-Ting Li, Hui-Jie Ke, Si-Hui Zhong, Jia-Ao Wei, Tong Chen, Xiao-Kun Li, You-Lin Zhang, Wei Chen

Journal of Electrochemistry

Early cancer screening can significantly improve therapeutic outcomes, volatile organic compounds (VOCs) and other related gases in exhaled breath, as cancer-specific biomarkers, offer a novel approach for non-invasive diagnosis. Metal oxide semiconductor (MOS)-based gas sensors are pivotal for exhaled breath VOCs detection, featuring compact size, cost-effectiveness, and rapid response. This review summarizes the most recent five-year research advances in cancer biomarker detection, and clarifies the core mechanisms of electrical property changes from sensing material-VOCs interactions and key performance metrics including sensitivity, selectivity, humidity tolerance, response/recovery time, stability, and operating temperature. This review also highlights the optimization strategies of sensing materials …

Influence Of Particle Properties And Grain Size On Aggregation In Dry Particle-Laden Volcanic Jets, Md Miraz Hossain, Stephen A. Solovitz, Josef Dufek, Joshua S. Mendez Harper, Alexa R. Van Eaton, Mary C. Benage, Larry G. Mastin, Benjamin J. Andrews

Electrical and Computer Engineering Faculty Publications and Presentations

Explosive volcanic eruptions can inject large amounts of ash into the atmosphere. These suspended particles pose hazards to aircraft, so a better understanding of the ash residence time and transport distance is needed. Fine particles combine to form larger aggregates, altering their settling behavior. Ash aggregation is influenced by liquid bonding, electrostatic forces, and preferential concentration driven by turbulence. We examine particle aggregation through controlled, low-humidity experiments at similar particle-fluid scaling to conditions near a volcanic vent. Particle-laden jets used compressed air containing three types of particles at controlled mass loadings: hollow glass spheres (∼10 μm diameter), solid nickel spheres …

Integrated Automation Framework For Generation Retirement Studies In Transmission Planning, Mohammed Sleiman, Tianwei Xia, Zhangxin Zhou, Nathaniel Rice

Electrical and Computer Engineering Faculty Research & Creative Works

Generation retirement studies are a critical part of long-term transmission planning, as power systems transition toward higher penetration of renewable energy and the retirement of conventional generation. However, existing study workflows are often fragmented across multiple tools and platforms such as PSS/E, TARA, Python, and Excel resulting in time-intensive processes, limited scalability, and reduced reproducibility. This paper showcases an integrated automation tool developed for generation retirement studies that is designed to streamline and unify the end-to-end analytical workflow.

The proposed framework consolidates key study components, including generator retirement modeling, power flow redispatch, contingency analysis (N-1 and N-1-1), and mitigation cost …

Beyond Probability: An Analytical Exploration Of Fuzzy And Neutrosophic Paradigms In Binomial Acceptance Sampling, Uma G, Vela Muruga Anurahini P

Neutrosophic Systems with Applications

Acceptance sampling plans are widely used in Statistical Quality Control to determine the acceptance or rejection of production lots based on sample inspection. Classical sampling plans under the binomial distribution assume precise parameter values, which may not adequately represent uncertainty, vagueness, and indeterminacy encountered in practical inspection environments. This review summarizes acceptance probability formulations for single and double sampling plans developed using fuzzy and neutrosophic logic under the binomial distribution. The focus is on studies that model the fraction defective and related parameters as fuzzy or neutrosophic numbers, allowing imprecise and indeterminate quality information to be incorporated into sampling decisions. …

Reliability-Calibrated Q-Rung Orthopair Neutrosophic Soft Ranking Under Partial Observability: An Auditable Industrial-Process Benchmark, Nagham Ahmed Abdelmegeed, Zeshan Aslam Khan

Neutrosophic Systems with Applications

Multi-criteria decision systems often interpret disagreement among criteria as evidence that some criteria are unreliable. This is problematic when the disagreement reflects a genuine operational trade-off. We develop a reliability-and-admissibility-calibrated q-rung orthopair neutrosophic soft ranking procedure (RAC-qRON) that distinguishes recorded evidence quality from the direction of criterion preferences. An explicitly bounded interval for each alternative–criterion observation is mapped to truth, indeterminacy and falsity memberships, with an admissibility proof for every integer rung q ≥ 1. Criterion weights are adjusted according to recorded information coverage rather than cross-criterion correlation, and a fixed-reference ideal-distance calculation produces an auditable rank. The method is …

Risk Prioritization Of ``Digital Drug'' And Consumer Neurostimulation Modalities: A Reproducible Interval-Valued Fermatean Fuzzy Entropy–Topsis Framework, Rawan Emad El-Saadany, Ahmed Samy, Mohamed M. Abdelhafeez, Mahmoud M. Ismail

Neutrosophic Systems with Applications

Consumer audio and multisensory stimulation technologies are increasingly accessible through streaming platforms, mobile applications, and immersive media. The expression digital drug is sometimes used for binaural-beat content intended to alter subjective states, but the term is a consumer/cultural label and does not imply pharmacological equivalence. Risk prioritization in this area is difficult because evidence is heterogeneous, several relevant criteria are qualitative, and judgments may be imprecise rather than point-valued. This paper develops a transparent interval-valued Fermatean fuzzy (IVFF) group decision framework that combines interval-preserving aggregation, Shannon entropy weighting, and TOPSIS for prioritizing digital drug risk scenarios under uncertainty. The method …

Risk-Based Cybersecurity Threat Prioritization In Digital Twin-Enabled Cyber-Physical Systems, Nada Mohamed, Alshaimaa A. Tantawy, Ahmed M. Abdelmouty

Neutrosophic Systems with Applications

Digital Twin (DT)-enabled cyber-physical systems (CPS) face cybersecurity risks due to their complex connections and high levels of interdependence. Traditional methods, for assessing risk often fail to rank these threats. This is especially true when expert opinions include ambiguity, uncertainty or unclear information. A Type 2 Neutrosophic Entropy– Measurement of Alternatives and Ranking according to COmpromise Solution (Entropy- MARCOS) framework for cybersecurity threat prioritization in DT-enabled CPS is proposed in this paper. The uncertainty and indeterminacy present in expert evaluations are represented by Type 2 Neutrosophic Numbers (T2NNs). While the MARCOS technique is used to assess and rank cybersecurity threats …

Context-Regulated Q-Neutrosophic Soft Model Selection Under Input Perturbation: Evidence From Three Classification Benchmarks, Poom Kumam, Supak Phiangsungnoen

Neutrosophic Systems with Applications

Selecting a classifier using a single average metric can conceal instability across validation splits, poor lower-tail behavior, and sensitivity to input perturbations. This study formulates a context-regulated Q-neutrosophic soft model-selection procedure with two fixed evaluation conditions. For each classifier and performance criterion, mean attainment (truth), across-split dispersion (indeterminacy), and the complement of a lower empirical quantile (falsity) form an auditable three-component descriptor. A bounded lower-context regulator aggregates their penalized utilities; monotonicity and perturbation bounds follow directly from its convex representation. Four fixed classifiers are compared using five benefit-oriented criteria, three repetitions of stratified five-fold cross-validation, and paired test-feature perturbations. Three …

Nitrate Plants Nominees To The Alabama Engineering Hall Of Fame Correspondence From William K. Rey, Oct. 3, 1988, William K. Rey

Correspondence

Correspondence from Chairman William K. Rey to William Lindsey McDonald confirming the nomination of the Nitrate Plants in North Alabama to the Alabama Engineering Hall of Fame.

Electrocatalytic Oxidation Of Ethylene Glycol To Glycolic Acid: From Mechanism And Catalyst Design To Emerging Neutral Electrolyte Systems, Man Zhang, Xue Li, Xin-Yu Peng, Lin Wang, Wen-Wen Chen, Yao-Yue Yang

Journal of Electrochemistry

Polyethylene terephthalate (PET) waste represents both an environmental burden and a loss of carbon resources. Alkaline depolymerization of PET yields terephthalic acid and ethylene glycol (EG). Electrocatalytic oxidation of EG to glycolic acid (GA), the monomer of biodegradable polyglycolic acid (PGA), offers a sustainable route driven by renewable electricity. However, the ethylene glycol oxidation reaction (EGOR) involves competing pathways toward C2 products (GA and oxalic acid) and C1 products (formic acid and CO₂), making selective GA production a central challenge. This review provides a comprehensive overview of recent progress in selective EG-to-GA electrooxidation from catalyst design, mechanistic understanding, …

Regularization-Based Crystallite Size Distribution Analysis Of Pt/C Catalysts From X-Ray Diffraction, Cheng-Long Ma, Wei-Yu Shi, Zhong-Jun Hou

Journal of Electrochemistry

Accurate determination of the platinum crystallite size distribution in carbon-supported platinum (Pt/C) catalysts is critical for evaluating both the initial performance and long-term durability of proton exchange membrane fuel cells (PEMFCs). Conventional characterization approaches—including transmission electron microscopy (TEM), small-angle X-ray scattering (SAXS), and the Scherrer equation—are limited by restricted statistical sampling, sensitivity to support interference, or the inability to resolve the full breadth of the size distribution. In this work, we present a regularization-based inversion framework that extracts the volume-weighted crystallite size distribution directly from X-ray diffraction (XRD) line profiles, without requiring any a priori assumption regarding the functional form …

Connecting Bim And Gis Through Bsdd: Automating Gis Data Templates And Semantic Mapping - Research Explainer, Hamza Tariq, Ciaran Mcnally

Reports

This research explainer examines how the buildingSMART Data Dictionary (bSDD) can support greater interoperability between Building Information Modelling (BIM) and Geographic Information Systems (GIS).

Drawing on research presented at the 2026 Civil Engineering Research in Ireland conference, it explores practical approaches to automatically generating standardised GIS data templates, mapping existing asset information to common data definitions, and validating information against agreed requirements.

The explainer demonstrates how open standards and structured data can improve information quality, reduce manual processing and support more consistent asset information management throughout the asset lifecycle.

Magnetic Cellulose Nanocrystal Composites Functionalized With Benzalkonium Chloride For Potential Pathogen Control, Kishore Chand, Sydney Herzog, Mohammad Jahid Hasan, Juganta Roy, Moses Ayitey-Adjin Jr., Corbon M. Moss, Sarah Khan, Sara Tester, Monishita Deb, Katherine Schlaak, Sarah Watzman, Yvonne Sun, Esteban Ureña-Benavides, Erick S. Vasquez-Guardado

Chemical and Materials Engineering Faculty Publications

This study presents the design and synthesis of multifunctional magnetic cellulose nanocrystal (CNC) composites engineered for targeted adsorption and broad-spectrum antimicrobial applications. The nanocomposites were fabricated by anchoring mixed-valence Fe₃O₄ magnetic nanoparticles on eco-friendly CNC frameworks, followed by surface functionalization with benzalkonium chloride (BC), a potent quaternary ammonium biocide. Both sulfated (S) and TEMPO-oxidized CNC (T) variants were investigated across Fe₃O₄:CNC mass ratios of 1:2 and 1:4. Comprehensive structural, magnetic, and morphological characterization confirmed successful surface modification, superparamagnetic responsiveness, and uniform component dispersion. Thermogravimetric analysis confirmed precise compositional tailoring, capturing up to 87 …

A Computational Framework For Modeling Fluid And Solid Stressesin Porous Tissues With Application To The Trabeculated Embryonic Heart, Christine Buffinton, James W. Baish

Faculty Journal Articles

This study provides a framework for efficient solutions of computational fluid-solid interaction models of porous tissue, with a focus on blood flow through the developing heart wall in the critical chamber and valve formation stages, when trabeculation fills much of the ventricles. This porous, trabeculated tissue is the site of complex mechanotransduction processes, but accurately estimating solid and fluid stresses within such intricate geometries is difficult. We addressed this with three levels of modeling and verification. Images of E12.5 mouse ventricles were first obtained through confocal microscopy and 3D reconstruction. These guided creation of explicit pore-scale finite element simulations with …