Engineering Commons^™

Comparative Catalytic Pyrolysis Of Wheat Straw For Enhanced Bio-Oil Production, Nourhan H. Khashaba, Noura F. Abdelsalam, Hany A. Elazab, Mamdouh A. Gadalla, Thokozani Majozi, Fatma H. Ashour

Chemical and Biochemical Engineering Faculty Research & Creative Works

Catalytic fast pyrolysis of lignocellulosic biomass is a promising thermochemical route for producing renewable biofuels and value-added chemicals. Many African countries have abundant underutilized agricultural residues whose reuse can improve waste management while reducing reliance on fossil fuels. This study used wheat straw as a representative residue to examine how two catalysts—zinc oxide (ZnO) and cement kiln dust (CKD)—affect bio-oil yield and quality. Bench-scale experiments were performed in a fixed-bed reactor under an inert nitrogen atmosphere at 500–600 °C. Each catalyst was tested separately at loadings from 0 to 7 g per 500 g of biomass to evaluate impacts on …

Veribrief: A Multi-Agent Retrieval-Augmented Generation System For Policy Decision Support, Imane Bahji

Electrical and Computer Engineering ETDs

VeriBrief is a multi-agent retrieval-augmented generation (RAG) system for evidence-grounded economic policy analysis. The system orchestrates a five-stage LangGraph pipeline, retrieval, research, analysis, synthesis, and critique, to produce cited, structured responses while detecting out-of-scope queries. An empirical evaluation on eight questions drawn from official U.S. macroeconomic releases compared VeriBrief against a single-pass RAG baseline. The multi-agent system achieved 100% refusal precision on unanswerable analytical queries versus 0% for the baseline. Unsupported claims fell substantially on answerable factual questions. A context-propagation defect discovered during evaluation was diagnosed and corrected. Limitations include failure of the evidence gate on policy-counterfactual queries and a …

Neural Network Technologies In The Automatical Control Systems Of Absorption Process For Pureficating Natural Gas, Abdishukurov Maqsudovich Shavkat Mr, Xuecheng Li Li Xuecheng Mr

Technical science and innovation

Analysis of methods and algorithms for synthesizing adaptive control systems for technological processes based on the neural network approach is carried out in this search. The stages of mathematical modeling of complex technological processes using neural network technology were considered. Additionally, an algorithm for solving the interpolation and extrapolation problem that arises in the training process a neural network to control system was proposed. At the final stage of this article, algorithms based on neural network technology are synthesized for the control system for the parameters of the technological process of natural gas purification by absorption

Analysis Of Inhibitor Supply Control Systems To Prevent Hydrate Formation In A Low-Temperature Gas Separation Unit And A Method For Solving The Problem, Shakhzod Nurmuhammadovich Amirov Mr, Erkin Xxx Uljayev

Technical science and innovation

The article examines and analyzs patents, published scientific works, and currently used scientific and practical methods and devices for regulating the parameters of the low-temperature separation process in production. However, the conducted analysis showed that one of the main causes of hydrate formation in the device is the lack of continuous comprehensive control over parameters such as the pressure of the inhibitors supplied to the injectors at each stage and the moisture content of the total gas, i.e., the moisture content of the total gas at the system inlet, the gas temperature at the device outlet, and the pressure and …

Multi-Parametric Nonlinear Programming For Lossy Lmp Sensitivity Analysis Using Outer Progressive Cuts, Yuhan Huang, Tao Ding, Chenggang Mu, Rui Bo, Pengwei Du

Electrical and Computer Engineering Faculty Research & Creative Works

Accurate sensitivity analysis of locational marginal price (LMP) is crucial for risk hedging and market management. This paper proposes multiparametric nonlinear programming for sensitivity analysis of LMP with nonlinear network loss, also known as lossy LMP. Global analytical solutions for lossy LMP and the corresponding critical regions are derived. An outer progressive cut algorithm is developed to constrain the network loss error within a specific range for the whole parametric domain. Case studies show the improved accuracy over methods with lossless or fixed loss factors, and a two-order-of-magnitude online speedup over Monte Carlo methods while maintaining lower total computational time.

Distinct Regulatory Dna Methylation Signatures Across Multiple Sclerosis, Neuromyelitis Optica, And Neurological Post-Acute Sequelae Of Covid-19, Syed Ilyas Munzir, Daniel B. Hier, Michael D. Carrithers

Electrical and Computer Engineering Faculty Research & Creative Works

Background/Objectives: Our prior epigenome-wide association study (EWAS) on multiple sclerosis (MS) identified myeloid-associated methylation signatures and an association with enhancer regions. Here we compared differential DNA methylation across three central nervous system inflammatory disorders: MS, neuromyelitis optica (NMO), and neurologic post-acute sequelae of COVID-19 (neuro-PASC). Methods: Whole-blood DNA was profiled on Infinium MethylationEPIC arrays. Analyses included EWAS at the CpG level, differentially methylation region (DMR) analysis, and gene regulatory-element enrichment using Locus Overlap Analysis (LOLA). Limma linear models were adjusted for race, EPIC array version, age, sex, disease-modifying treatment class, and blood cell composition. Results: All three diseases were associated …

Study Of Onshore And Offshore Upwind And Downwind Wind Turbine Configurations: Performance Differences And Aerodynamic Characteristics, Ahmed Ismail

Mechanical Engineering Theses

The aerodynamic performance and loading behavior of large- scale wind turbines depend heavily on atmospheric inflow conditions and rotor orientation. While upwind turbines remain the most common design in the industry, recent progress in materials, aeroelastic modeling, and control systems has sparked renewed interest in downwind configurations. This study aims to assess how ABL characteristics and rotor orientation affect the aerodynamic performance of a utility- scale wind turbine. A CFD framework was built in ANSYS Fluent to model the NREL 5 MW Reference Wind Turbine. Transient simulations employed the SST k–ε turbulence model under various inflow conditions: uniform, onshore, and …

Numerical Investigation Of Shock-Induced Deformation Of Bubble-Laden Droplets, Juan Roldan

Doctoral Dissertations and Master's Theses

Rain impact can be a source of surface erosion on hypersonic vehicles, and the severity of each impact depends on droplet velocity, mass, and final shape, all of which are set by how the droplet breaks up under shock loading. Real droplets are expected to carry entrained non-condensable gas (NCG) nuclei from their formation. This dissertation investigates whether the purely mechanical, pressure-driven response of these nuclei, independent of vaporization, is large enough to measurably alter the internal pressure field and early deformation of a shock-loaded droplet.

The droplet and surrounding gas are modeled with a compressible, diffuse-interface, axisymmetric Eulerian framework …

Leader Election System For An Unmanned Ground Vehicle Swarm, Milan Chhetri, Brendan Beas, Paul Levin

Electrical Engineering

This senior project presents the design and implementation of a leader-election system for a leader-follower unmanned ground vehicle (UGV) swarm using embedded control and wireless communication. The objective of the project is to improve the robustness and mission longevity of a multi-agent robotic system by allowing the swarm to dynamically select the most suitable leader during operation. Each UGV is equipped with an ESP32 microcontroller, DWM1000 Ultra-Wideband (UWB) ranging modules, an MPU-6050 inertial measurement unit (IMU), motor drivers, and supporting power electronics to enable communication, sensing, and autonomous control. A battery monitoring subsystem was developed using the ESP32's built-in Analog-to-Digital …

Archimedean Spiral Antenna Array With Klopfenstein And Exponential Tapered Balun Feeds, Leo Joseph Alvelais Iv, Paul Obrecht, Naguib Abdulla, Preston Mavady, Collin Fan

Electrical Engineering

This project presents the design, fabrication, and experimental evaluation of a broadband 3x3 Archimedean spiral antenna array tile for 2.8-3.8 GHz. Each element combines a two-arm spiral on Rogers RO4350B, a printed 50 to 150 Ω tapered balun, and a conductive backplane. Klopfenstein and Exponential feed implementations were modeled in Ansys HFSS, generated and tuned with automated scripting, fabricated, and evaluated with calibrated network and anechoic-chamber measurements. The Klopfenstein-fed hardware met the -10 dB input-reflection criterion across the project band. The exponential array provided a broad matched response but reached approximately -8 dB near 2.95 GHz. Measured center-element patterns retained …

Vision-Based Autonomous Tracking Rover, Alejandro Ahumada, Erick Ayala, Jonathan Chavez

Electrical Engineering

AAC Vision designed and constructed a vision-based autonomous tracking rover capable of exploring an indoor environment, avoiding obstacles, generating a two-dimensional LiDAR map, detecting a standard orange basketball, and approaching the target without manual steering. The rover uses a Raspberry Pi 4, an Intel RealSense D435 RGB-D camera, an RPLIDAR C1, four JGB37-520 Hall-encoder motors, dual H-bridge motor drivers, a 12 V battery, and a custom aluminum chassis measuring approximately 8 in by 12 in and weighing 6.7 lb. The final mission emphasized reliable target discovery rather than travel between predetermined points. The software integrates Python, OpenCV, Ultralytics YOLO, RealSense …

Chi Meta-Project Ecosystem Overview - Spring 2026, David B. Smith

Publications and Research

This paper offers a high-level account of the Center for Holistic Integration’s (CHI) meta-project ecosystem as visualized in the included system map. CHI provides an organizational structure framed around persistent meta-projects that support and extend individual initiatives across curriculum, scholarly and applied research, infrastructure, artistic production, AI development, cultural inquiry, and external partnerships. Rather than presenting the map as a static inventory of projects, the paper examines how its core domains function as living systems through which knowledge, tools, documentation, participants, and collaborations can accumulate over time. It also considers how CHI-mediated connectivity, institutional integration, and external funding allow the …

Multidisciplinary Inverse Robust Co-Design Of Materials, Products, And Manufacturing Processes, H M Dilshad Alam Digonta

Theses and Dissertations

Realizing the design for Integrated Computational Materials Engineering (ICME) requires the materials, product, and manufacturing-process disciplines to be designed together. Because these disciplines interact and influence one another's decisions, coordination is needed among their distributed decision-makers. Their interactions are captured through the processing-structure-property-performance (PSPP) linkages, which must be established from limited, costly data. Moreover, each discipline introduces its own sources of uncertainty, and these propagate through the process chain to influence final product performance. The effective realization of the product-material-manufacturing system, therefore, calls for a co-design approach that enables the concurrent coordination of the interacting disciplines while quantifying and managing …

Life Cycle Of Lithium-Ion Battery Recycling Systems Enable Carbon Capture, Utilization, And Storage: A Review, Nabeel Al-Qirim, Mohammad Kamrul Hasan, Hussam Al Hamadi, Akm Ahasan Habib, Shayla Islam

All Works

The lithium-ion battery (LIB) is the primary component of electric vehicles (EVs), and its environmental consequences are significant for the eventual widespread adoption of EVs. Recycling used LIBs protects the environment and allows for the reuse of valuable materials. To achieve the goal of a circular economy, LIB recycling processes that conserve environmentally friendly resources and maintain sustainability need to be developed. The critical technology for achieving global climate goals is carbon capture, utilization, and storage (CCUS), which makes it possible to significantly lower carbon dioxide (CO2) emissions across power and industrial systems. The LIB recycling and CCUS are becoming …

The Privacy Trap: Keeping Sensitive Data Safe In The Ai Era, Xiaohui Liang

Paul English Applied Artificial Intelligence (AI) Institute Publications

This presentation examines privacy and data security risks associated with the growing use of artificial intelligence, with particular attention to the sensitive information users may disclose when interacting with AI systems. It explores how voice, text, images, and prompts can expose personally identifiable and privacy-sensitive information and introduces privacy threats associated with large language models and other AI systems. The presentation discusses approaches for identifying and protecting sensitive information, including named entity recognition, prompt modification, masking, replacement, and other privacy-preserving techniques. It also examines the trade-off between protecting privacy and maintaining the usefulness of AI-generated responses. Drawing on research in …

Confidenceai: A Wearable And Predictive Ai Ecosystem, Denzil Paul, Xuejun Kong, Raymond Wang, Flora Fleith Lopes, Zhengjia Yang, Brain Chu, Weijian Wang, Leo Chen

Paul English Applied Artificial Intelligence (AI) Institute Publications

This group project presents ConfidenceAI, a conceptual wearable and predictive artificial intelligence ecosystem designed to help teenagers build confidence and manage stress in high-pressure situations such as classroom participation and public speaking. The system combines wrist-based biosensing with a personalized machine-learning model that uses physiological signals, including heart rate and heart rate variability, electrodermal activity, skin temperature, and movement, to learn an individual's baseline patterns and anticipate heightened stress responses. Rather than relying on universal thresholds, ConfidenceAI is designed to personalize the timing, method, and delivery of interventions based on each user's physiological patterns and prior responses. The proposed ecosystem …

Actioncaptions: Making Movies, Shows, And Daily Life Accessible For All, Haruna Hosokawa, Rhianon Gutierrez, Matt Davis, Justin Wang, Eric Gu, Arthur Miao, Andrew Duan, Perry Yu, Ziqi Yan, Susie Yan

Paul English Applied Artificial Intelligence (AI) Institute Publications

This group project presents ACTIONCAPTIONS, a proposed downloadable application or web application designed to improve access to audio content through customizable captioning. The project addresses limitations associated with existing captioning options in settings such as movie theaters, including limited device availability, cumbersome equipment, lack of portability, and the absence of live captioning capabilities. ACTIONCAPTIONS proposes a free and accessible platform that provides both live transcription and captioning for uploaded files. The application incorporates customizable settings for user preferences, including caption size, color, contrast, and language, and is designed around principles of accessibility and universal design. The project demonstrates how speech …

Thermal Transport Tuning Via Nanoscale Hierarchical Frameworks For Fe2val Thermoelectric Materials, Apoorva Pradip Joshi

Dartmouth College Master’s Theses

Waste heat represents a vast, untapped energy resource. Thermoelectric materials offer a promising route to harvest this energy by directly converting thermal gradients into electricity. The Heusler alloy Fe2VAl is a prime candidate for such applications because it is non-toxic and cost-effective. However, its intrinsically-high thermal conductivity severely limits performance. A detailed understanding of thermal transport mechanisms is therefore essential for improving its thermoelectric efficiency. This work examines the effect of atomic disorder on the thermal transport behaviour of Fe2VAl. We use germanium doping to introduce atomic-scale disorder and demonstrate a substantial reduction in thermal conductivity, from 28 W/m-K in …

Production Of Seismic-Resistant Steel From Scrap With Up To 0.6% Copper, Iman El-Mahallawi, Ahmed Ramadan Seada Dr.

Mechanical Engineering

Earthquake-resistant steel grades of characteristic value defined by the ratio (UTS/YS) greater than 1.25 are verified through controlling the proportion of alloying elements in steel. This work illustrates a novel idea to produce earthquake-resistant steel grade utilizing steel scrap. Different heats were produced containing varying levels of copper, manganese, and silicon, along with deep desulfurization. The heats were hot rolled to diameters of 10, and 16 mm, followed by Tempcore process. JMatPro software was used to predict the formed phases. The chemical composition was determined by optical emission spectrometry. The tensile properties were determined by tensile testing, and bend testing …

Harnessing Tio2-Based Nanofilaments: A Pathway To Enhanced Optoelectronic Performance In Dye-Sensitized And Perovskite Light Harvesters, Zahraa Ismail, Tarek A. Elmelegy, Hassan Nageh, Sameh Abdellatif

Mechanical Engineering

This study explores the integration of TiO2-based nanofilaments into dye-sensitized solar cells (DSSCs) and perovskite solar cells (PSCs) to enhance their optoelectronic performance. Despite the advancements in one-dimensional lepidocrocite TiO2 nanofilaments, there remains a significant gap in understanding their optical scattering mechanisms and dual applicability in both types of solar cells. We synthesized TiO2 nanofilaments and compared their performance to conventional P25 TiO2 in terms of morphology, electrical, and optical properties. The results indicate that the DSSC utilizing nanofilaments achieved a short-circuit current density of 8.2 mA/cm² and a power conversion efficiency (PCE) of 6.9%, compared to 7.1 mA/cm² and …

Developing Solvent-Based Recycling Methods At Ambient Conditions To Regenerate Bisphenol A Diglycidyl Ether And Recover Metal Oxides From Epoxy Nanocomposites, Heaven Smith

Rose-Hulman Undergraduate Research Publications

No abstract provided.

How Do Different Food Influents Affect Biogas Production, Process And Operational Stability, And System Performance In The Armfield W8, A Bench-Scale Anaerobic Digester, Jarko Rumbaoa, Anahita Adhikari

Rose-Hulman Undergraduate Research Publications

No abstract provided.

Center Of Mass (Com) Shift In Electric Vertical Takeoff And Landing (Evtol) Aircraft, Irene Lema Madueno

Rose-Hulman Undergraduate Research Publications

No abstract provided.

Sustainable Extraction Of A New Diketopiperazine, Anthony Chapman

Rose-Hulman Undergraduate Research Publications

No abstract provided.

Native Plants For Green Roofs In Indiana, Alasdair Curts

Rose-Hulman Undergraduate Research Publications

No abstract provided.

The Neuropsychological Analysis Of The Effect Of Shame And Traumatic Memories In Paranoia: A Network Analysis, Anwesha Maitra

Clinical Psychology Dissertations

Paranoia is increasingly recognized as a multidimensional psychological phenomenon influenced by trauma-related distress, shame, maladaptive interpersonal experiences, and emotional functioning. Although these factors have been extensively associated with paranoia, their relationships with neurocognitive functioning, social cognition, and global functioning remain less well understood. The present study examined these relationships using traditional statistical analyses, network analysis, and machine-learning approaches in a non-clinical sample of 42 adults.

Participants completed self-report measures assessing trauma-related distress, childhood interpersonal experiences, shame, paranoia, depressive symptoms, fear of negative evaluation, self-esteem, and hostile attribution bias, in addition to a comprehensive neurocognitive battery, an emotion recognition task, and …

Effect Of Anisotropic Hydraulic Conductivity On Groundwater Seepage Into A Rectangular Tunnel In Submerged Sand, Deki Yangzom Ghaley, Sanjay Kumar Shukla

Research outputs 2022 to 2026

Managing groundwater seepage around tunnels is critical to tunnel design, particularly when the tunnel is constructed below the water table. Accurate seepage flow patterns and water inflow prediction under ordinary and critical conditions are imperative to mitigate potential tunnel construction and service disasters. In the past, an in-depth study on the anisotropic hydraulic conductivity of the soil mass that may affect the seepage condition has not been carried out. In this work, this aspect has been investigated numerically for a rectangular tunnel submerged within a homogeneous sand mass, considering the anisotropic hydraulic conductivity ratio (kz / kx, kz = vertical …

Impact Of Capillary Imbibition On Development Of Unconventional Oilfields: A Five-Year Review, Yihang Xiao, You, Yongming He, Han Xu, Lei Wang, Yujie Yuan

Research outputs 2022 to 2026

The imbibition process, which is characterized by the displacement of non-wetting phase by wetting phase in porous media, plays a crucial role in enhancing oil recovery of unconventional reservoirs. However, due to the complex nature of reservoir characteristics and fluid properties, existing research on this phenomenon presents contradictory conclusions and interpretations. This paper aims to fill this knowledge gap by providing a comprehensive review of the fundamental concepts, primary mechanical factors, and critical influences in oil-water imbibition. Primary mechanisms, including capillary, viscous, gravitational, hydrostatic, inertial, capillary back, dead end, and osmotic forces, are analyzed in terms of their key roles …

Pfas Quantification Using Solid Phase Extraction And Low Field Nuclear Magnetic Resonance (Spe-Nmr), Nicholas N.A. Ling, Ghasemi, Ella Shilliday, Masoumeh Zargar, Einar Fridjonsson, Michael L. Johns

Research outputs 2022 to 2026

Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals that are highly resistant to biodegradation. Due to their bioaccumulation, long-term persistence, and adverse human health effects, they have been classified as organic pollutants. The leaching of PFAS into water sources has resulted in their detection in global drinking water supplies. To mitigate adverse health effects and minimise environmental damage, regulations regarding maximum allowable PFAS concentrations in water have been imposed. Traditional PFAS in water quantification methods, such as liquid chromatography–mass spectrometry (LC–MS), gas chromatography–mass spectrometry (GC–MS), and high-performance liquid chromatography (HPLC), have intrinsic limitations that pose challenges in such PFAS analysis. …

Optimal Co2 Storage Interval In Heterogeneous Tight Formation: Implications For Long-Term Carbon Sequestration, Yujie Yuan, Yuxin Cao, Emad A. Al-Khdheeawi, Maxim Lebedev, Zhenjiang You, Reza Rezaee, Stefan Iglauer, Lai Chang Zhang, Zhuo Feng

Research outputs 2022 to 2026

The efficiency of CO2 geo-sequestration relies heavily on the storage capacity and sealing integrity of the heterogeneous strata. Tight formations offer substantial advantages for long-term CO2 geological storage, however, the stratigraphic variability and lithological heterogeneity introduce substantial uncertainty in real-world engineering applications. Particularly, for tight formations with pronounced heterogeneous lithologies, traditional methods oversimplify their impact on CO2 geo-sequestration. To address this challenge and identify the most effective intervals for CO2 geo-sequestration, we investigated the middle Permian Lucaogou Formation (P2l) in the Jimusar Sag, Junggar Basin, Northwest China, a region known for its strong lithological heterogeneity. By integrating multi-scale analytical techniques, …