Engineering Commons^™

A Decision Support Model For Building Material And Component Reuse In The Context Of Circular Buildings, Havva Aksel

Journal of Sustainable Construction Materials and Technologies

Construction activities cause significant environmental impacts such as waste generation, pollution, resource consumption, and land use, which are expected to increase with global construction demands. To mitigate these environmental problems, the circular building occurs as an emerging concept depending on in the circular economy, which aims to minimize waste and redefine the “end-of-life” concept by reducing, reusing, recycling, and recovering materials. The reuse of building materials and components (BMCs) from existing structures represents a crucial strategy for achieving circularity in the built environment. Within this framework, design plays a key role. However, designing with reclaimed BMCs remains complex due to …

Cache-Conscious Sparse Matrix Dense Matrix Multiplication On Gpus, Haoqiang Guo

LSU Doctoral Dissertations

Over the past decade, high-performance deep learning has evolved into a critical research domain, driven by the demand for efficient models and high inference throughput. Deep learning architectures have shifted from stacked convolutional layers to transformer-based models, while pruning techniques and graph-structured data have established sparse matrix–dense matrix multiplication (SpMM) as a fundamental kernel—particularly in graph neural networks (GNNs). Modern GPUs, with their massive parallelism and high-bandwidth memory, offer immense potential for accelerating these workloads. While SpMM implementations using the compressed sparse row (CSR) format remain common to avoid conversion overhead, preprocessing-based methods have recently demonstrated superior potential. In GNN …

Advancements In Perfect Matchings Within Neutrosophic Fuzzy Graphs: Theory And Applications, Muhammad Saeed, Fatima Razaq

Neutrosophic Systems with Applications

Graph theory has been widely used in exemplifying relational structure, and a greater generalization to fuzzy and neutrosophic space enables the exemplification of uncertainty, indeterminacy, and inconsistency in complex systems. Some of these extensions include the neutrosophic fuzzy graphs that provide a more detailed description of the loose relations between the vertices and the edges. However, unlike in classical graph theory, where the concepts of matching and perfect matching are well developed, very little has been studied on how the two concepts can be extended to neutrosophic fuzzy graphs. To seal this gap, the current paper develops and defines the …

Integrating Mcdm Techniques For Optimized Task Offloading In Multi-Uav- Enaled Mobile Edge Computing System, Amira Salam

Neutrosophic Systems with Applications

Carefully choosing a task offloading strategy is crucial for optimizing task scheduling and offloading strategies in a multi-UAV system. Regarding cost, responsiveness, scalability, and data security, each strategy has pros and cons. As a result, selecting the best offloading technique is essential to multi-UAV mobile edge computing task scheduling optimization. A methodical and well-informed decision-making process accomplishes this.

The current study introduces a new hybrid methodology for the multi-criteria decision-making (MCDM) model, known as IVNs-DEMATEL-ANP-VIKOR. The purpose of this model is to find and choose an efficient task offloading strategy. With this method, we use IVNs-DEMATEL to show how different …

Mixed Linear Equation–Inequality Systems Over The Pura Vida Neutrosophic Algebra, Muhammad Rayyanu Abdullahi, Abdulhadi Aminu

Neutrosophic Systems with Applications

This paper proposes a neutrosophic extension of max-plus algebra for solving mixed systems of linear equations and inequalities.Classical max-plus algebra is a powerful tool for modeling synchronization in discrete-event systems LastNatpreClose LastNatClose, but it assumes fully deterministic data.To incorporate uncertainty and indeterminacy, we reformulate the framework so that coefficients and variables are expressed as neutrosophic numbers

γ+λI,γ,λ∈ℝ,I∈[0,1],

where I quantifies the degree of indeterminacy.

We redefine the max-plus semiring in this neutrosophic setting, extend solvability and uniqueness results, and adapt the ONEMLP-EI algorithm LastNatpreClose LastNatClose to handle neutrosophic …

Mapping Sustainability To Cybernetic-Generative Artificial Intelligence-Based Education: An Innovative Neutrosophic Orbifold-Lattice Methodology, Mona Mohamed, Ahmed A. Metwaly

Neutrosophic Systems with Applications

The lightning-fast development of artificial intelligence (AI), notably generative artificial intelligence (Gen AI) technologies, has intrigued multiple disciplines, particularly education. In this context, Large Language Models (LLMs) serve as beneficial cognitive resources that address knowledge deficits and provide tailored educational support for learners and staff. For learners, LLMs are regarded as knowledgeable educators who offer prompt, focused responses and rationales to tricky queries. Whereby LLMs for staff, Strength enhancer, automating tedious tasks, and creating intelligent resources.Gen AI’s rapid growth offers enormous obstacles for educational systems, compelling them to discover solutions for these obstacles.

Conceptually, cybernetics is leveraged for bridging the …

Neutrosophic Σ - Baire Spaces, R. Vijayalakshmi, F. Josephine Daisy, M. Simaringa

Neutrosophic Systems with Applications

A Neutrosophic Baire Space extends the concept of Baire Space from classical topology to the realm of neutrosophic topology which deals with sets and spaces where truth, falsehood and indeterminancy are explicitly considered. In this paper the concept of neutrosophic σ - baire spaces are introduced in Neutrosophic topological spaces. Also Neutrosophic σ - dense, Neutrosophic σ - nowhere dense, Neutrosophic σ -first category and Neutrosophic σ - second category sets are defined. Several characterizations of neutrosophic σ - baire spaces are investigated and explained using examples and the conditions under which a neutrosophic topological space becomes a neutrosophic σ …

Vibrissae-Inspired Vision-Based Magnetic-Actuated Whisker, Zhixian Hu, Yi Cheng, Juan P. Wachs, Yu She

School of Industrial Engineering Faculty Publications

Tactile perception is significant for robotic operation in unstructured environments. Whisker-based sensors offer lightweight bio-inspired solutions, yet most rely on single-whisker sensing and are limited by passive interaction and constrained functionality. Here we present a circular array of eight independently actuated whiskers, each driven by a pulse-switchable permanent magnet and tracked by a camera. This design enables simultaneous multi-point sensing and coordinated actuation, supporting diverse functions. Quantitative analyses demonstrate accurate pixel-to-physical mapping, consistent pixel-to-force characterization, and long-term repeatability. In this work, we show that an vibrissae-inspired vision-based magnetic-actuated whisker array integrating distributed perception with active interaction achieves reliable physical mapping, …

Characterization And Control Of Rod-Like Soft Robots, Tianrui Li

Mechanical Engineering Research Theses and Dissertations

Micro-scale robotic systems have garnered significant interest for applications in micromanufacturing and biosensing, yet quantitative design rules linking geometry, stiffness distribution, and magnetic actuation to locomotion performance at low Reynolds number remain limited. This thesis investigates magnetically actuated rod-like soft robots composed of hydrogel filaments with embedded micro-magnets and tunable hard:soft length ratios. Four- and eight-magnet swimmers with hard:soft ratios ranging from 1:1 to 2.5:1 and 4:3:1 are fabricated using a simple molding-and-insertion process and tested in water and silicone oil. A triaxial Helmholtz coil system generates rotating magnetic fields from 1 to 10 Hz, and a custom image-processing pipeline …

Accurate Prediction Of Geometrical Parameters Of An Ultra-Broadband Metamaterial Absorber Using Machine Learning, Md. Rezwan Ahmed, Oishi Jyoti, Pritu Parna Sarkar, Mohammod Abdul Motin, Md. Selim Habib, Md. Samiul Habib

Electrical and Computer Engineering Faculty Publications

In this paper, we systematically demonstrate the design and analysis of a new type of ultra-broadband tunable metamaterial perfect absorber (MPA) comprising a top vanadium dioxide (VO2) based patterned resonating patch, a continuous metallic film at the bottom, and an intermediate dielectric substrate having a thickness of only 0.18 at the center working frequency. The simulation results reveal that the absorber achieves a bandwidth of 7.26 THz, ranging from 5.40 THz to 12.66 THz, with more than 90% absorptance and an average absorption of 98.21% under normal incidence of the incoming THz wave. Furthermore, absorptance exceeding 99% is achieved between …

Thermoeconomic Optimization Of Climate-Adaptive Solar And Wind Multi-Generation Systems Using Artificial Intelligence And Thermal Energy Recovery, Ehsanolah Assareh, Nima Izadyar, Emad Tandis, Mehdi Khiadani, Amir Shahavand, Neha Agarwal, Arian Gerami, Ahmed Rezk, Minkyu Kim, Reza Kord, Tahereh Pirhoushyaran, Mehdi Hosseinzadeh, Saleh Mobayen

Research outputs 2022 to 2026

This study presents a hybrid multi-generation energy system designed to overcome solar intermittency while meeting the global demand for integrated delivery of electricity, water, cooling, and sustainable fuels in the transition to decarbonization. The engineering application integrates solar thermal and wind energy with a modified Brayton cycle, a Steam Rankine Cycle (SRC), and a Thermoelectric Generator (TEG) to simultaneously produce electricity, fresh water via Reverse Osmosis (RO), hydrogen and oxygen via Proton Exchange Membrane Electrolyzer (PEME), and cooling (via absorption chiller) within a unified optimization framework. The system was modeled using Engineering Equation Solver (EES) and optimized via Response Surface …

Integrated Chitosan-Based Coagulation And Microbubble Pre-Treatment For Improved Microplastic Fibre Removal From Water, Nimesha Thathsarani, Mohadeseh Najafi, Mehdi Khiadani, Muhammad Rizwan Azhar, Masoumeh Zargar

Research outputs 2022 to 2026

Microplastic fibres (MPFs) dominate treatment plant influents but are difficult to remove due to their morphology, composition and low density, limiting the effectiveness of coagulation flocculation pre-treatment. Integrating coagulation-flocculation with microbubble introduction offers a sustainable route to improve MPF removal, yet conventional inorganic coagulants often require high dosages, show strong pH dependence, and pose environmental risks. Chitosan is a biodegradable and non-toxic green alternative, but its application is limited due to its low solubility and pH sensitivity. In this study, two amphoteric derivatives of Chitosan have been successfully developed: CMC-CTA, produced by modifying carboxymethyl Chitosan (CMC) with 3-chloro-2-hydroxypropyl trimethyl ammonium …

A Modular Design And Construction Framework For Enhancing The Sustainability Of National Housing Projects In Egypt, Ayman Ahmed Ezzat, Farah Ibrahim El Sahzly

Mansoura Engineering Journal

Egypt’s national housing sector faces mounting sustainability challenges due to outdated design and construction practices that cause material waste, high costs, and inefficient resource use. This study develops a framework for integrating modular design and construction principles into Egypt’s National Housing Projects (NHPs) to strengthen their social, economic, and environmental sustainability. A mixed-method approach combined a literature review, case studies, and a survey of Egyptian Architectural Design Firms (ADFs). The literature review revealed a global consensus on the benefits of modular design and construction, such as improved efficiency, reduced waste, and faster project delivery, yet found limited adoption in Egypt …

Financial Risk Trends During Covid-19: A Comparative Analysis Of Three Major U.S. Airlines (2020-2022), Kamanda Mosongo

The Journal of Purdue Undergraduate Research

No abstract provided.

Analyzing Ethics Education Strategies In Biomedical Engineering Programs, Sanjana Prashanth

The Journal of Purdue Undergraduate Research

No abstract provided.

Application Of Reinforcement Learning To Precision Aerial Delivery System Control In Adverse Wind Conditions, Radman Zarbock

The Journal of Purdue Undergraduate Research

Precision aerial delivery systems (PADS) are a subset of airdropped parachute-leveraging package delivery systems that use autonomous guidance, navigation, and control (GNC) to reach targets with high degrees of accuracy. This technology emerged in the 1990s, and strides have been made since to improve the reliability of traditional physics-based controllers that guide PADS. However, these algorithms still struggle to deliver acceptable performance results when PADS are subjected to austere operating environments, such as those with unpredictable wind. Building on a foundational study in 2022 that used artificial intelligence (AI) and machine learning to improve PADS GNC performance, this study aims …

Flood Prediction With Sentinel-1 Synthetic Aperture Radar From Hurricane Helene, Jingyu Xiao, Jessica Li

The Journal of Purdue Undergraduate Research

Floods are the most common natural disaster globally, causing thousands of deaths every year. Timely and accurate flood forecasts are crucial for developing early warning systems, evacuation plans, and effective strategies to enhance community resilience. Soil moisture is an important parameter in flood forecasting. Unfortunately, existing soil moisture sensor networks and optical remote sensing–based techniques for soil moisture estimation lack the spatial resolution needed for accurate flood forecasting. This study presents an approach for flood prediction using Sentinel-1 C-band synthetic aperture radar (SAR) data. SAR offers high spatial resolution and operates day and night under all weather conditions, making it …

Impact Of Slot Liner Compression On The Total Thermal Resistance Of The Stator-Winding Assembly In Electric Motors, Lindsay Sutherland

The Journal of Purdue Undergraduate Research

The increasing demand for high-performance electric motors, driven by the rapid adoption of electric vehicles, necessitates effective thermal management techniques that improve their safety, efficiency, and reliability. Heat must be transferred from the current-carrying copper windings to the metallic stator body through an electrically insulating material called the slot liner. However, little research has focused on the interactions between the slot liner and the windings. This study examines the impact of slot liner compression on the thermal resistance across the stator-winding assembly considering two common slot liners: Nomex® 410 and Kapton® MT+. A mock stator-winding assembly was developed by stacking …

Validation Of Innovative Method Of Murine Vertebral Compression Testing, Sarah Staller

The Journal of Purdue Undergraduate Research

Murine vertebral compression testing is a common technique to quantify trabecular bone biomechanics. Having a precise method of vertebral compression is important for aiding researchers in making clinically relevant discoveries in musculoskeletal research. While many methods exist in literature, there has yet to be established a universal protocol for this procedure. Many challenges exist in vertebral compression, such as the irregular shape of the vertebral body (trabecular region of interest), uneven endplate surface morphology, and surrounding cortical processes. Therefore, the aim of this study was to develop a new method of vertebral compression that accounts for these factors and to …

The Automation Of Lamp Biomolecular Assays Using The Eppendorf Epmotion™ 5075 Robotic Pipettor, Shamalaa Sathiasealan

The Journal of Purdue Undergraduate Research

Loop-mediated isothermal amplification (LAMP) is a nucleic acid amplification technique known for its specificity and efficiency in less controlled environments than laboratories. Designing novel LAMP reagents requires strict contamination control, and unlike the more commonly automated polymerase chain reaction, LAMP’s heightened sensitivity poses unique challenges to automation. To address this, we optimized automation procedures for LAMP using a robotic pipettor without altering the core assay itself. This project focuses on minimizing contamination using sealed plates, reducing operator intervention by automating pipetting, and preventing enzyme degradation using cooling plates. Our approach employs pre-slit pierceable seals and cooling blocks to prevent cross-contamination …

Implications Of Noninvasive Blood Pressure Pumps On Mean Arterial Pressure, Sammie Miller

The Journal of Purdue Undergraduate Research

Noninvasive blood pressure pumps are recommended as the primary form of acquiring patient blood pressure to test for blood poisoning. The Philips IntelliVue Patient Monitor MP5, the Philips SureSigns VS4/VS3 Vital Signs Monitor, the Philips EarlyVue VS30 Vital Signs Monitor, the Philips IntelliVue Patent Monitor MP2/X2, the Philips IntelliVue Patent Monitor MMS, and the Philips IntelliVue Patent Monitor MP3/X3 were tested for accuracy. The control condition for hypotension was 95/55 (68) mmHg, normal blood pressure was 120/80 (93) mmHg, and hypertension was 155/85 (108) mmHg. The order of values is arrayed according to diastolic, systolic, and mean arterial pressure. The …

From Test Tracks To Carbon Tracks: Evaluating The Carbon Emissions Of Autonomous Vehicle Development, Sarah Deniz

The Journal of Purdue Undergraduate Research

Autonomous vehicle (AV) development has seen a sharp increase in the past 10 years, and there is a significant energy cost of training AVs to meet safety regulations. The training process includes virtual simulation training as well as physical training on public roads and within private testing facilities. The high energy expenditure associated with AV training has a respective environmental cost that can be quantified as a lifetime “carbon debt” of released carbon emissions. The environmental sustainability of AVs has not been thoroughly studied in currently available literature, and this paper showcases a model that quantifies the total “carbon debt” …

A Parallel Interval Modeling Framework For Nonlinear Systems: Application To A Modified Duffing Oscillator, Roman Voliansky, Nina Volianska

Northeast Journal of Complex Systems (NEJCS)

The paper presents a mathematical framework for converting nonlinear dynamical systems into parallel forms. This framework replaces the exact system motion equations with interval equations, enabling the representation of nonlinear functions over piecewise linear domains. Such representation enables the description of system motions using linear-like differential equations, which can be analyzed and manipulated using well-known control methods. One such method is eigenvalue analysis, a powerful tool in classical control theory since many techniques rely on the system’s characteristic polynomial and its eigenvalues. We apply this method to define interval system eigenvalues and track their variation during system operation. These eigenvalues …

A Proposed Secure Video Using Lightweight Chacha20 Based On Chaotic Map, Hadeel Mohammed Taher, Ali Makki Sagheer

Iraqi Journal for Computer Science and Mathematics

Multimedia content has become a necessary part of our daily lives in many domains, including medical imaging, surveillance, and entertainment. Among all multimedia categories, video is mainly critical because of its high content density and large size. For that, ensuring the security of video has become a necessity for transmission and storage. This paper proposed an enhancement to the Chacha algorithm integration with a hybrid chaotic map for generating keys to secure video. The main motivation for the selection ChaCha algorithm is that it is fast, simple, and appropriate for widespread applications, whereas the motivation for using chaos is to …

Control Techniques And Design Of Load-Side Controls For The Mitigation Of Late-Time High-Altitude Electromagnetic Pulse, Connor A. Lehman, Rush Robinett, Wayne Weaver, David G. Wilson

Michigan Tech Publications

This paper introduces a novel control archetype designed to mitigate high-altitude electromagnetic pulse (HEMP) (Formula presented.) disturbances on the power grid, as well as information on performance and specifications of different control laws for the controller archetype. This method of protection has been overlooked in the literature until now. A controlled voltage supply is placed on the load-side of a transformer, diverting unwanted power from the transformer core to prevent saturation. The controlled voltage source is modeled using four control laws: an integral controller (capacitor), Linear Quadratic Regulator (LQR), an energy storage minimized feedforward control law, and a Hamiltonian feedback …

Amp: Single-Shot Ultra-Wide Fisheye-To-Cubemap Pnp Pose Estimation, Ryan M. Raettig, Richard R. Nyquist, Scott L. Nykl, Clark N. Taylor, Christine M. Schubert Kabban

Faculty Publications

Estimating the position and orientation of a rigid object from an image is critical for situational awareness in robotics and autonomous systems. This study explores relative pose estimation using an ultra-wide fisheye camera for unmanned aircraft inspection vehicles. Ultra-wide fisheye lenses introduce radial distortion and capture features beyond the rectilinear image plane, rendering rectilinear Perspective-n-Point (PnP) algorithms inadequate. Designing a bespoke ultra-wide fisheye localization algorithm requires consideration of both the feature detection method and the pose estimator itself. This study proposes a novel method that combines (1) a fisheye-to-cubemap reprojection, (2) a You Only Look Once (YOLO) convolutional neural network …

Evaluation And Calibration Of Coupled Low-Cost Particulate Matter Sensors, Tyler Cargill

McKelvey School of Engineering Graduate Student Theses & Dissertations

Low-cost sensors (LCS), if used appropriately, are useful instruments to elucidate human exposure to particles suspended in the air (i.e. particulate matter, PM). Characterizing this exposure is crucial, as exposure to PM2.5 (i.e. particles with aerodynamic diameter ≤ 2.5 μm) negatively affects the respiratory, cardiovascular, and other organ systems and is the leading environmental burden for global mortality. Similarly, exposure to particles with aerodynamic diameters greater than 2.5 μm and less than or equal to 10 μm, here forth termed as PMCoarse, is known to cause health ailments for the upper respiratory system. This dissertation focuses on the MODULAIRTM-PM (MOD-PM), …

Probing The Mechanisms Of Reinforcement Learning: Reinforcement Learning, Ventral Striatal Astrocytes, And The Dynamic Coordination Of Information Seeking With Learning, Fatih Sogukpinar

McKelvey School of Engineering Graduate Student Theses & Dissertations

While reinforcement learning has been a vital component in artificial intelligence and machine learning, there exist many open questions about its implementations and how to improve them, in both minds and machines. Among these are i) the contribution of non-neuronal cell types to reinforcement learning, and ii) information-seeking behavior during reinforcement learning. In this thesis, we studied these main topics pertaining to reinforcement learning. In the first chapter, we examined the role of astrocytes in reinforcement learning, and in the second, we investigated human information seeking during reinforcement learning. Neurons in the human and animal brain have been known to …

Transforming Co2 Into Value-Added Products: Liquefied Petroleum Gas And Solid Carbon Materials, Kaiying Wang

McKelvey School of Engineering Graduate Student Theses & Dissertations

The escalating climate crisis, driven by anthropogenic carbon dioxide (CO2) emissions, necessitates the development of advanced Carbon Capture and Utilization (CCU) technologies. A critical distinction within CCU lies between transient carbon cycling, which converts CO2 into fuels, and permanent sequestration, which transforms it into durable, solid materials. This dissertation addresses fundamental catalytic challenges across both pathways to develop economically viable and technologically sound solutions for CO2 valorization. This work seeks to answer two primary research questions: (1) How can the catalyst temperature mismatch and stability limitations in the tandem conversion of CO2 to Liquefied Petroleum Gas (LPG) be overcome to …

Optimal Sizing Of Battery Energy Storage Systems For Peak Shaving And Demand Response Using A Degradation-Aware Bayesian Optimization-Mixed-Integer Linear Programming Framework, Jiwei Yao, Blake Billings, Tao Gao, John Hedengren, Kody M. Powell

Faculty Publications

The increasing integration of renewable energy and rising electricity demand highlight the importance of battery energy storage systems for peak shaving and demand response. Unlike prior approaches that overlook operational impacts on degradation, this study proposes a Bayesian Optimization–Mixed Integer Linear Programming framework for optimal battery energy storage system sizing. In this framework, Mixed Integer Linear Programming determines short-term scheduling while a calibrated electrochemical model iteratively evaluates degradation. The central hypothesis is that the framework can efficiently identify optimal sizes that yield realistic and economically robust outcomes. The method is tested across three scenarios: peak shaving, peak shaving with energy-reduction …