Mechanical Engineering Commons^™

Spatiotemporal Deep Learning To Forecast Storm Surge Water Levels And Storm Trajectory: Case Study Hurricane Harvey, Junqin Hou, Muhammad K. Akbar, Manar D. Samad, Lizhi Ouyang

Mechanical and Manufacturing Engineering Faculty Research

No abstract provided.

Effect Of A Small Control Rod On The Aerodynamic Forces And Wake Structure Of Side-By-Side Cylinders At Moderate Reynolds Number, M. M. Mosallem

Journal of Engineering Research

The unsteady wake interaction between two side-by-side circular cylinders often leads to significant vortex shedding and fluctuating aerodynamic forces. This numerical study investigates the effect of a small passive control rod with a rod-to-cylinder diameter ratio d/D = 0.07 on the wake dynamics and aerodynamic forces of two side-by-side circular cylinders. Two configurations are explored: one where the control rod is placed directly behind the cylinders (x/D = 0), and another where it is located downstream (x/D = 0.5). The two cylinders are arranged with a center-to-center spacing ratio T/D = 1.25. The simulations were …

Employing Machine Learning Regression Models For Performance Prediction Of A Two-Stage Solar Dryer, Hany El-Ghaish, Ahmed Aman, Mohamed Abdelgaied

Journal of Engineering Research

The present manuscript aims to examine the application of artificial intelligence techniques to predict the performance of a two-stage solar dryer system equipped with preheating via two solar air collectors. Three machine learning algorithms, namely Linear Regression, k-Nearest Neighbors, and Multilayer Perceptron, were developed, trained, and evaluated on experimental data to identify the most accurate model for predicting the system's performance throughout the year. The dataset undergoes a preprocessing step including temporal linear augmentation, z-score normalization, and second-degree polynomial feature expansion. The evaluation process utilized several performance indices, including mean square error, mean absolute error, mean absolute percentage error, and …

Design And Implementation Of A Smart Solar Tracking System Using Hydraulic Actuation, Bassem Nashaat Zakher, Mahmoud M. Ramzi, Kirolos A. Amin

Journal of Engineering Research

This research presents the design and implementation of a smart single-axis solar tracking system that introduces a novel integration of hydraulic actuation with minimalistic sensor control. Unlike traditional trackers that rely on multiple light sensors and complex mechanical setups, the proposed system uses a simplified control mechanism driven by a single-point light detection strategy to maintain panel alignment with the sun. The core innovation lies in replacing motor-driven tracking mechanisms with a hydraulic actuator, offering smoother, more durable movement with reduced maintenance. Additionally, the system integrates smart monitoring via Arduino, enabling real-time data processing and decision-making without relying on costly …

Optimization Of Surface Integrity And Fatigue Life In Hard Turning Of K110 Tool Steel, Y. A. Mashal, Mohamed G. Yousef, M. H. El-Axir

Journal of Engineering Research

The influence of various machining process parameters on surface integrity elements (e.g. surface roughness and surface residual stress) and fatigue life of hard metals is an important area of engineering. This study investigates the effect of various turning parameters on the surface integrity and fatigue life of K110 hard tool steel. The determination of residual stress was performed by a non-destructive testing technique using X-ray diffraction analysis (XRD). The experimental work extended to perform fatigue experiments using rotary bending machine which was designed and manufactured to assess the fatigue behavior under rotating bending stresses. In this investigation, single optimization of …

Enhancement Of Spin Transport Properties In Angled-Channel Graphene Spin Valves Via Hybrid Spin Drift-Diffusion, Samuel Olson, Kaleb Hood, Otto Zietz, Jun Jiao

Mechanical and Materials Engineering Faculty Publications and Presentations

Graphene has promise as a channel connecting separate units of large-scale spintronic circuits owing to its outstanding theoretical spin transport properties. However, spin transport properties of experimental devices consistently fall short of theoretical estimates due to impacts from the substrate, electrodes, or defects in the graphene itself. In this study, we fabricate both traditional non-local spin valves (NLSVs) and novel hybrid drift-diffusion spin valves (HDDSVs) to explore the impact of charge current and AC spin injection efficiency on spin transport. HDDSVs feature channel branches that allow investigation of charge-based spin drift enhancement compared to diffusion-only configurations. We investigate the modulation …

Transparent Eeg Analysis: Leveraging Autoencoders, Bi-Lstms, And Shap For Improved Neurodegenerative Diseases Detection, Badr Mouazen, Ahmed Bendaouia, Omaima Bellakhdar, Khaoula Laghdaf, Aya Ennair, El Hassan Abdelwahed, Giovanni De Marco

Manufacturing & Industrial Engineering Faculty Publications

Highlights

• Novel hybrid architecture: Combined autoencoders with bidirectional LSTM networks for enhanced EEG signal classification, achieving 98% accuracy in distinguishing AD, FTD, and healthy controls.

• Explainable AI integration: Implemented SHAP (SHapley Additive exPlanations) framework to enhance model transparency and identify entropy as the most influential feature for neurodegenerative disease detection.

• Optimal temporal segmentation: Demonstrated that 5-s EEG windows with 50% overlap provide the best balance between classification accuracy and computational efficiency.

• Comprehensive feature extraction: Utilized Power Spectral Density (PSD) analysis across standard frequency bands (Delta, Theta, Alpha, Beta, Gamma) following autoencoder-based dimensionality reduction.

• Superior performance validation: Outperformed traditional machine learning …

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Self-Organization In Metal Plasticity: An Ilg Update †, Avraam Konstantinidis, Konstantinos Spiliotis, Amit Chattopadhyay, Elais C. Aifantis

Michigan Tech Publications

In a 1987 article of the last author dedicated to the memory of a pioneer of classical plasticity Aris Philips of Yale, the last author outlined three examples of self-organization during plastic deformation in metals: persistent slip bands (PSBs), shear bands (SBs) and Portevin Le Chatelier (PLC) bands. All three have been observed and analyzed experimentally for a long time, but there was no theory to capture their spatial characteristics and evolution in the process of deformation. By introducing the Laplacian of dislocation density and strain in the standard constitutive equations used for these phenomena, corresponding mathematical models and nonlinear …

Energy-Aware Optimal Reconfiguration Of A Heterogeneous Connected And Automated Vehicle Cohort On A Limited-Access Highway, Pruthwiraj Santhosh, Darrell Robinette, Daniel Knopp, Jeffrey Naber, Jungyun Bae

Michigan Tech Publications

This paper presents an optimized vehicular reordering methodology designed to minimize energy consumption within heterogeneous cohorts operating at constant velocity on limited-access highways. The approach addresses the challenge of optimizing vehicle sequencing by considering both aerodynamic drag reduction benefits and the energy costs of reconfiguring a cohort from a stochastic initial state. This study provides empirical validation through on-road vehicle tests, demonstrating significant energy savings, achieving up to 10% reduction in axle energy for optimally configured cohorts compared to independent operation. A System of Systems (SoS) simulation environment, integrating micro-traffic, validated powertrain, and aerodynamic drag reduction models, was developed to …

Ferric Metal-Organic Frameworks (Mofs)-Based Electrospinning Fibers For Supercapacitors, Samar A. Salim, Hani Nasser Abdelhamid

Nanotechnology Research Centre

Ferric-based metal-organic frameworks (Fe-MOFs) were synthesized and incorporated into poly(methyl methacrylate) (PMMA) using electrospinning to produce PMMA_Fe-MOF nanofibers. The materials were analyzed using X-ray diffraction (XRD), attenuated total reflectance Fourier-transform infrared spectroscopy (ATR-FTIR), and scanning electron microscopy (SEM). The electrospun materials were directly integrated into nickel foam (NF) electrodes for energy storage applications, e.g., supercapacitors. The electrochemical performance was assessed using cyclic voltammetry (CV), galvanostatic charge-discharge curves (GCDC), linear sweep voltammetry (LSV), and electrochemical potentiokinetic reactivation (EPR). The PMMA_Fe-MOF electrodes exhibited outstanding capacitive performance, achieving specific capacitances of up to 1017.5 F/g at 1 A/g for the 2.5 % Fe-MOF …

Underwater Acoustic Integrated Sensing And Communication: A Spatio-Temporal Freshness For Intelligent Resource Prioritization, Ananya Hazarika, Mehdi Rahmati

Electrical and Computer Engineering Faculty Publications

Underwater acoustic communication faces significant challenges including limited bandwidth, high propagation delays, severe multipath fading, and stringent energy constraints. While integrated sensing and communication (ISAC) has shown promise in radio frequency systems, its adaptation to underwater environments remains challenging due to the unique acoustic channel characteristics and the inadequacy of traditional delay-based performance metrics that fail to capture the spatio-temporal value of information in dynamic underwater scenarios. This paper presents a comprehensive underwater ISAC framework centered on a novel Spatio-Temporal Information-Theoretic Freshness metric that fundamentally transforms resource allocation from delay minimization to value maximization. Unlike conventional approaches that treat all …

A Polar Turbulence Invariant Map With Applicability To Realisable Machine Learning Turbulence Models, James G. Wnek, Christopher Schrock, Eric M. Wolf, Mitch Wolff

Mechanical and Materials Engineering Faculty Publications

Invariant maps are a useful tool for turbulence modelling, and the rapid growth of machine learning-based turbulence modelling research has led to renewed interest in them. They allow different turbulent states to be visualised in an interpretable manner and provide a mathematical framework to analyse or enforce realisability. Current invariant maps, however, are limited in machine learning models by the need for costly coordinate transformations and eigendecomposition at each point in the flow field. This paper introduces a new polar invariant map based on an angle that parametrises the relationship of the principal anisotropic stresses, and a scalar that describes …

Impact Of Composite Materials Research On Underrepresented Communities, Neil Mahesh Bedagkar, Ramanan Sritharan, Wyatt Barnes

Mechanical Engineering

This research assesses how advancements in composites material research affect communities from lower socioeconomic backgrounds, using a dual track strategy to quantitatively and qualitatively examine their impact. A keyword-based classification algorithm was applied to a sample of research papers from ScienceDirect spanning the last 24 years to quantify which engineering industries benefit most from this research. The findings indicate that the construction industry benefits the most, followed by the automotive, defense, renewable energy, and biomedical sectors. A broader qualitative analysis of the social implications of these industries was also conducted to provide context. Each sector were found to have either …

Effect Of Graphene Nanoplatelets Fraction On The Microstructure And Mechanical Properties Of Inconel 718 Composites Prepared By Spark Plasma Sintering, Sanoj Karki, Manoj Mugale, Satyavan Digole, Amit Choudhari, Mayank Garg, Caleb Schenck, Fu-Yun Tsai, Bharat Gwalani, Tushar Borkar

Mechanical Engineering Faculty Publications

Nickel-based superalloy, particularly Inconel 718, is a promising candidate in advanced structural and high-temperature applications, including turbine blades, combustors, and turbochargers. However, high-efficiency energy systems such as jet engines and land-based gas turbines demand increasingly high strength for advanced structural applications. Therefore, significant efforts are underway to enhance the strength of these materials. Reinforcement of graphene nanoplatelet (GNP), owing to its exceptional mechanical strength, lightweight, high aspect ratio, and high level of coherency with metal matrix, has been proposed as an effective way of incorporating high strength into the existing Inconel 718. In addition, the spark plasma-assisted heating process is …

Physics-Based Machine Learning Framework For Predicting Structure-Property Relationships In Ded-Fabricated Low-Alloy Steels †, Atiqur Rahman, Md Hazrat Ali, Asad Waqar Malik, Muhammad Arif Mahmood, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The Directed Energy Deposition (DED) process has demonstrated high efficiency in manufacturing steel parts with complex geometries and superior capabilities. Understanding the complex interplays of alloy compositions, cooling rates, grain sizes, thermal histories, and mechanical properties remains a significant challenge during DED processing. Interpretable and data-driven modeling has proven effective in tackling this challenge, as machine learning (ML) algorithms continue to advance in capturing complex property structural relationships. However, accurately predicting the prime mechanical properties, including ultimate tensile strength (UTS), yield strength (YS), and hardness value (HV), remains a challenging task due to the complex and non-linear relationships among process …

Experimental Study Of Gas-Dynamic Heating In Hartmann-Sprenger Tubes For Rocket Engine Ignition, Jacob T. Huff

Master's Theses

Ignition systems for chemical rocket engines typically rely on hypergolic propellants or auxiliary electrical hardware to supply the energy required to initiate combustion. The resonance igniter is a simple and robust alternative to these conventional methods, capable of inducing autoignition of non-hypergolic propellants without an external ignition source. At the core of this concept is the Hartmann-Sprenger Tube (HST), a device in which a high-velocity jet of gas impinges on a resonance cavity. This interaction establishes self-sustaining gas oscillations within the cavity that heat the propellants to their autoignition temperature. To facilitate the development of a functional resonance igniter at …

A Biocompatible Nitinol Based Triboelectric Stent Sensor For Prospective Cardiovascular Health Monitoring, Ulises Vidaurri Romero, Sk Shamim Hasan Abir, Najlah Karam, Mariana Torres, Shahria Ahmed, Md. Wasikur Rahman, Bahareh Azimi, Serena Danti, Jianzhi Li, M. Jasim Uddin

Mechanical Engineering Faculty Publications

Triboelectric nanogenerators (TENGs) have been considered as an effective approach for self-powered systems. Currently, coronary heart disease remains the leading cause of death in the United States. This can be easily resolved by balloon angioplasty or a specialized mesh tube called a stent. This study demonstrates a stent sensor made of nitinol, a nickel—titanium alloy used in the medical field for its pseudo-elasticity and strong corrosion resistance, poly(vinylidene fluoride) (PVDF) and polydimethylsiloxane (PDMS), which can measure several physiological parameters while placing it in the arteries. This nitinol health monitor sensor (NHMS) device thus integrates the TENG with a specific medical …

Wind Turbine Rotor Design Using High-Fidelity Aerostructural Optimization, Marco Mangano, Sicheng He, Yingqian Liao, Denis-Gabriel Caprace, Andrew Ning, Joaquim R. R. A. Martins

Faculty Publications

Large wind turbines yield more energy but demand careful aeroelastic blade design. Coupled multiphysics design strategies can reduce wind energy costs exploiting fluid-structure interactions. This work presents the first high-fidelity aerostructural optimization study of a large wind turbine rotor.We use blade-resolved fluid dynamics and structural solvers in a monolithic gradient-based optimization framework to explore steady-state torque and blade mass trade-offs. The coupled-adjoint approach computes gradients efficiently, enabling the optimization of over 100 structural and geometric parameters simultaneously. Our optimization study modifies a DTU 10 MW benchmark with a simplified structure and isotropic material properties. The tightly coupled optimizations increase torque …

Optimizing Hip And Knee Assistance For Walking And Sit-To-Stand Transitions: An Intrinsic Muscle Mechanics Based Predictive Approach, Neethan Ratnakumar

Dissertations

As the global population ages, the demand for wearable assistive technologies continues to rise, driven by their potential to enhance mobility and independence in older adults. Effectively designed controllers for lower-limb exoskeletons to assist sit-to-stand (STS) and walking are crucial for delivering efficient, safe, and comfortable assistance during daily activities. Traditionally, controller optimization involves biomechanical modeling and user-specific customization. Musculoskeletal simulations play a central role in this process by providing insights into human-exoskeleton interaction dynamics, thereby informing and refining control strategies.

This work presents a simulation-driven approach for developing exoskeleton controllers for walking and STS using two distinct methods: optimal …

Pressure And Force Dynamics In Artificial Muscle Actuators: A State-Space And Optimization-Based Approach, Mohammad Elzein

Dissertations and Theses

This two-part investigation explores the dynamic behavior of braided pneumatic actuators (BPAs) under bio-inspired pulse modulation, with the aim of improving their biomimetic force output and control. The first study examines the effect of pulse length and inter-pulse timing on BPA performance, revealing that force output is highly sensitive to the temporal structure of input pulses mirroring biological muscle behavior. Using dual-pulse actuation schemes, the results demonstrate that force responses exceed the additive contributions of individual pulses, with peak amplification occurring consistently at a 27 ms inter-pulse gap. Shorter pulse lengths (10–20 ms) yielded the highest normalized force increases, up …

Computational Fluid Dynamics (Cfd) Modeling For Bio-Inspired Aerodynamic Optimization In Autonomous Drones, Hyginus C.O. Unegbu, Danjuma Saleh Yawas

Makara Journal of Technology

This study explores the aerodynamic benefits of bio-inspired design modifications for autonomous drones using advanced Computational Fluid Dynamics (CFD) simulations. Four bio-inspired configurations—leading-edge serrations, winglets, riblet surfaces, and curved wings—were assessed and compared against a baseline drone model to evaluate their impact on aerodynamic performance. The results indicated that all bio-inspired designs significantly enhanced lift, reduced drag, and improved overall aerodynamic efficiency. The leading-edge serration configuration achieved the highest performance gains, with a 33.6% increase in maximum lift coefficient (CL) and a 29.5% improvement in lift-to-drag ratio (CL/CD), primarily due to delayed flow separation and reduced turbulence. Winglets minimized wingtip …

Hourly Simulated Power Production Data With Snow Loss Model At Existing Utility-Scale Pv Sites (>5 Mw) In The U.S. Eastern Interconnection In 2018, Shelbie Wickett, Ana Dyreson

Simulated Solar Capacity Including Snow Cover in the Eastern U.S.

Project Summary: We ran PySAM power production simulations for utility-scale (>5 MW) PV sites located in the U.S. Eastern Interconnection in the year 2018. Site panel mounts (fixed-tilt or single-axis tracking), capacities, and locations (latitudes and longitudes) were extracted from Lawrence Berkeley National Laboratory's Utility-Scale Solar 2024 Edition dataset. See 2018_PV_existing_site_metadata.csv file for individual site metadata.

Hourly Simulated Power Production Data With No Snow Loss Model At Existing Utility-Scale Pv Sites (>5 Mw) In The U.S. Eastern Interconnection In 2014, Shelbie Wickett, Ana Dyreson

Simulated Solar Capacity Including Snow Cover in the Eastern U.S.

Project Summary: We ran PySAM power production simulations for utility-scale (>5 MW) PV sites located in the U.S. Eastern Interconnection in the year 2014. Site panel mounts (fixed-tilt or single-axis tracking), capacities, and locations (latitudes and longitudes) were extracted from Lawrence Berkeley National Laboratory's Utility-Scale Solar 2024 Edition dataset. See 2014_PV_existing_site_metadata.csv file for individual site metadata.

Hourly Simulated Power Production Data With No Snow Loss Model At Queued Utility-Scale Pv Sites Simulated As Single-Axis Tracking Systems In The U.S. Eastern Interconnection For Weather Year 2014, Shelbie Wickett, Ana Dyreson

Simulated Solar Capacity Including Snow Cover in the Eastern U.S.

Using 2014 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory's Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadata

Hourly Simulated Power Production Data With No Snow Loss Model At Queued Utility-Scale Pv Sites Simulated As Single-Axis Tracking Systems In The U.S. Eastern Interconnection For Weather Year 2021, Shelbie Wickett, Ana Dyreson

Simulated Solar Capacity Including Snow Cover in the Eastern U.S.

Using 2021 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory's Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadata

Hourly Simulated Power Production Data With No Snow Loss Model At Queued Utility-Scale Pv Sites Simulated As Single-Axis Tracking Systems In The U.S. Eastern Interconnection For Weather Year 2022, Shelbie Wickett, Ana Dyreson

Simulated Solar Capacity Including Snow Cover in the Eastern U.S.

Using 2022 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory's Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadata

Hourly Simulated Power Production Data With Snow Loss Model At Existing Utility-Scale Pv Sites (>5 Mw) In The U.S. Eastern Interconnection In 2022, Shelbie Wickett, Ana Dyreson

Simulated Solar Capacity Including Snow Cover in the Eastern U.S.

Project Summary: We ran PySAM power production simulations for utility-scale (>5 MW) PV sites located in the U.S. Eastern Interconnection in the year 2022. Site panel mounts (fixed-tilt or single-axis tracking), capacities, and locations (latitudes and longitudes) were extracted from Lawrence Berkeley National Laboratory's Utility-Scale Solar 2024 Edition dataset. See 2022_PV_existing_site_metadata.csv file for individual site metadata.

Hourly Simulated Power Production Data With No Snow Loss Model At Existing Utility-Scale Pv Sites (>5 Mw) In The U.S. Eastern Interconnection In 2017, Shelbie Wickett, Ana Dyreson

Simulated Solar Capacity Including Snow Cover in the Eastern U.S.

Project Summary: We ran PySAM power production simulations for utility-scale (>5 MW) PV sites located in the U.S. Eastern Interconnection in the year 2017. Site panel mounts (fixed-tilt or single-axis tracking), capacities, and locations (latitudes and longitudes) were extracted from Lawrence Berkeley National Laboratory's Utility-Scale Solar 2024 Edition dataset. See 2017_PV_existing_site_metadata.csv file for individual site metadata.

Hourly Simulated Power Production Data With No Snow Loss Model At Existing Utility-Scale Pv Sites (>5 Mw) In The U.S. Eastern Interconnection In 2018, Shelbie Wickett, Ana Dyreson

Simulated Solar Capacity Including Snow Cover in the Eastern U.S.

Project Summary: We ran PySAM power production simulations for utility-scale (>5 MW) PV sites located in the U.S. Eastern Interconnection in the year 2018. Site panel mounts (fixed-tilt or single-axis tracking), capacities, and locations (latitudes and longitudes) were extracted from Lawrence Berkeley National Laboratory's Utility-Scale Solar 2024 Edition dataset. See 2018_PV_existing_site_metadata.csv file for individual site metadata.

Hourly Simulated Power Production Data With No Snow Loss Model At Existing Utility-Scale Pv Sites (>5 Mw) In The U.S. Eastern Interconnection In 2022, Shelbie Wickett, Ana Dyreson

Simulated Solar Capacity Including Snow Cover in the Eastern U.S.

Project Summary: We ran PySAM power production simulations for utility-scale (>5 MW) PV sites located in the U.S. Eastern Interconnection in the year 2022. Site panel mounts (fixed-tilt or single-axis tracking), capacities, and locations (latitudes and longitudes) were extracted from Lawrence Berkeley National Laboratory's Utility-Scale Solar 2024 Edition dataset. See 2022_PV_existing_site_metadata.csv file for individual site metadata.