Mechanical Engineering Commons^™

Refinement Of Wind Speed Estimation At Turbine Hub Height Using Satellite Data And Regression Analysis Under Complex Terrain Conditions, Isroil Abriyevich Yuldoshev, Tulqin Rustamovich Jamolov, Sa'dullo Sayfiddin Ugli Fazliddinov, Jumanazar Farhodjon OʻGʻL Abdurashidov

Technical science and innovation

Reliable assessment of wind energy potential in regions characterized by complex terrain is often constrained by the limited availability of ground-based meteorological measurements. This study proposes an improved regression-based approach for refining wind speed estimates at the wind turbine hub height of 65 m using satellite-derived data from the NASA POWER database combined with a logarithmic vertical wind profile. The proposed methodology is validated using real operational data from a 750 kW wind power plant located in the mountainous Bostanlyk district of Uzbekistan for the period 2018–2021. The regression analysis demonstrates a strong linear relationship between the extrapolated wind speed …

Adaptive Multi-Stage Fuzzy Logic Approach With Dynamic Weight Adjustment For Robust Power Transformer Diagnostics, Dilafruz Rustamovna Abdullabekova, Odiljon Muhammadjonovich Kutbidinov

Technical science and innovation

An adaptive multi-level fuzzy logic framework with dynamic weight adjustment for power transformer fault diagnosis and health index assessment was proposed in this study. A comprehensive analysis of existing transformer diagnostic approaches was performed, and their limitations related to static weighting schemes and uncertainty handling were identified. A hierarchical fuzzy inference structure was introduced, integrating multi-source diagnostic data, including dissolved gas analysis, transformer oil quality indicators, thermal parameters, and electrical measurements. At the first level, individual fuzzy subsystems were developed to evaluate partial condition indices associated with insulation degradation, oil aging, and thermal–electrical stress. At the second level, a global …

Theoretical And Practical Foundations Of Healthcare System Digitalization, Sanjarbek Bekturdiev Sharifboyevich Phd, Muxlisa G‘Ulom Qizi G‘Ofurova

Technical science and innovation

The digital transformation of healthcare represents a key direction in improving the accessibility, quality, and efficiency of medical services. This study examines the main components of eHealth, including telemedicine, electronic health records, cloud technologies, and mobile applications, as well as the role of international organizations in promoting national digital health strategies. Particular attention is given to the current state of digital healthcare in the Republic of Uzbekistan, where significant progress has been made in developing infrastructure and implementing information systems, although challenges related to integration, standardization, and regulatory support remain. The work identifies the main trends in the development of …

Manufacturing Of Functional Surface Coatings In The Automotive Industry, Gulirano Saidakhmedova

Technical science and innovation

The development of environmentally sustainable technologies for material processing represents one of the most pressing scientific and technical challenges in modern industrial production. This issue is particularly relevant to the automotive industry, where growing demands for energy efficiency, durability, and environmental safety necessitate the adoption of advanced manufacturing methods. Special attention is given to developing vacuum-based, import-substituting equipment and technologies for producing functional coatings from composite materials with predefined physical, mechanical, and optical properties, including reflective and protective characteristics. Current requirements for mechanical engineering products and production technologies drive the need for innovative approaches to material processing and specialized technical …

Development Of A Novel Cfd Approach For Predicting Multiphase Flow Enhanced By Machine Learning, Abdulrahman Elazazi Mohamed

Thesis/ Dissertation Defenses

Accurate estimation of interface orientation is crucial for ensuring both the accuracy and robustness of Volume of Fluid (VOF) schemes in multiphase flow simulations, especially when using non-uniform Cartesian meshes. Conventional gradient reconstruction approaches, such as least-squares (LSQ) methods, often suffer from significant errors and strong oscillations on highly stretched grids. This thesis proposes a grid-transferable, learning-based methodology that predicts interface unit normal vectors directly from the local volume-fraction field on non-uniform structured Cartesian grids by means of a compact feedforward neural network.

The methodology extends earlier work originally developed for uniform grids, which is first reproduced to assess how …

Quantitative Phase-Field Modeling Of Nonequilibrium Microstructural Evolution In Rapid Solidification For Additive Manufacturing, Leiji Li, Fei Xiao, Ying Zhou, Xiaorong Cai, Chongfeng Zhang, Jinzhong Gao, Xiaopeng Shen, Tianchi Zhu, Sihan Wang, Yijia Gu, Xuejun Jin

Materials Science and Engineering Faculty Research & Creative Works

Fusion-based metal additive manufacturing (AM) relies on layer-by-layer deposition and rapid solidification, where the material transitions swiftly from liquid to solid. A key phenomenon during this process is solute trapping, a nonequilibrium effect governed by a velocity-dependent partition coefficient, which critically influences microstructure kinetics, morphology, and phase formation. In this study, we employ a recently proposed quantitative phase field (PF) model to systematically explore solute trapping, solute drag, and their impacts on pattern formation during rapid solidification at AM-relevant velocities, in both one and two dimensions. Our simulations reveal a growth mode transition from planar to cellular to dendritic, and …

Tunable Shock And Vibration Damping In Metal Laser Powder Bed Fusion Components Via Controlled Post-Print Compaction Of Particle Damper Cavities, Joud N. Stame, Yanzhou Fu, Samuel Roberts, Austin Downey, Tianyu Zhang, Lang Yuan, Daniel Kiracofe

Faculty Publications

Components manufactured by Laser Powder Bed Fusion (LPBF) can incorporate particle dampers (PDS) by retaining unfused powder within internal pockets, providing inherent vibration suppression without added mass or separate damping components. This study investigates the damping performance of such LPBF-integrated PDs through two complementary approaches: (1) quantifying the effect of post-printing volume compression on energy absorption by mechanically indenting the damper pocket, and (2) evaluating how variations in particle packing density influence the dynamic response under both sinusoidal and transient impulse excitation. Experimental results from shaker and shock testing demonstrate that increased packing density, whether by compression or tighter confinement, …

Sustainable Materials And Energy Management In Interfacial Solar Evaporation Systems, Maryam Nooman Almallahi

Thesis/ Dissertation Defenses

Water scarcity is an escalating global challenge, particularly in arid regions, necessitating sustainable, decentralized technologies for freshwater production. Traditionally used desalination technologies include membrane and thermal distillation; neither approach has achieved the desired high level of environmental friendliness because both consume substantial electricity generated by fossil fuels. Therefore, new desalination technologies powered by sustainable energy and eco-friendly materials are in high demand. Solar-driven interfacial solar evaporation (SDIE) is a promising alternative for environmentally friendly, sustainable freshwater production, which involves efficient solar-to-heat conversion and heat localization at the evaporator surface. An evaporator usually consists of three main components—photothermal absorber, thermal insulation, …

Biomass Demineralization: A Critical Need For Future Biorefineries, Leoncio Santiago-Martínez, Styliani Avraamidou, Alejandro Ayala-Cortés, Ruth Azike, Santanu Bakshi, Chumki Banik, Ezra Bar Ziv, Fei Long, Rebecca Ong, Et Al.

Michigan Tech Publications

Biomass contains up to 14 essential elements that serve as nutrients for plant growth and development, including photosynthesis and enzyme functionalities. These elements in different chemical forms (e.g., minerals) constitute the inorganic fraction of biomass and can cause operational issues in thermal and biochemical biomass conversion technologies. In biomass gasification and pyrolysis processes, for instance, inorganics can cause fouling, tar formation, and corrosion. In catalytic and biochemical processes, inorganics can poison catalysts, alter biochemical pathways, and modify product yields and selectivity. This review provides an overview of the inorganic content in biomass feedstocks, the critical role inorganics play in plant …

Preliminary Study Of Circular Lithium-Ion Battery Thermal Management System With Intermittent Cooling, Muhammad Luthfi, Leo Van Gunawan, Yudhy Kurniawan, Sabda Ikhwal Rahmatullah, Alfarikh Muhammad Daen

Journal of Mechanical Engineering Science and Technology (JMEST)

The active battery thermal management system is important to maintain the lithium-ion battery temperature within the optimum and safe range. However, current research has not considered the potential for excessive energy consumption due to the continuous operation of a fluid flow source, such as a fan. This research aims to investigate the effect of a novel approach called intermittent cooling on the cooling efficacy and energy consumption of the circular-configuration BTMS. Both transient computational fluid dynamic simulation and experiment were conducted in this work with 30 pieces of 18650 Lithium-Ion batteries positioned in a staggered circular configuration. From the result, …

Gas Lift Valve Operation Under Elevated Pressure And Temperature Conditions, Pedro O. De Melo Flores

LSU Master's Theses

Gas lift valves are critical components in artificial lift systems, and their performance directly influences well unloading efficiency and long-term production. Current industry models used to correct valve opening and closing pressure for temperature rely on assumptions that have not been extensively validated against experimental data. This study experimentally investigates the opening and closing behavior of injection pressure-operated (IPO) gas lift valves under controlled elevated-temperature conditions. A load rate test bench was modified to include a heating system capable of maintaining valve temperatures up to 220°F. Five gas lift valve designs from multiple manufacturers were tested over a range of …

Evolution Of Polypyrrole Electrode During Electropolymerization And Its Effect On Energy Storage Performance, Duy Pham, Ryan Tcheutchoua Gouafong, Jake Irvin, Ben Mckinney, Jacob Dileonardi, Mason Cox, Ashish Aphale

Faculty Articles

This study investigates the influence of electropolymerization time on the evolution of morphology and the electrochemical performance of polypyrrole (PPy) electrodes. The PPy films were synthesized by varying the deposition time from 300 seconds to 1800 seconds, corresponding to 5 to 50 cycles. The electrodes were characterized by Raman spectroscopy, XPS, and SEM, and electrochemical analyses were conducted using cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and galvanostatic charge-discharge (GCD). Experimental results showed that increasing deposition time yields large cauliflower-like structures, thereby enhancing capacitance. The 50 cycle electrode exhibited the highest specific capacitance of 412 F/g in a three-electrode configuration …

Comparative Evaluation Of Segmentation-Based And Pose-Assisted Head Temperature Estimation From Uas Thermal Imagery Under Controlled Conditions, Owais Ahmed, Justin A. Guye, Muhammad Hassan Tanveer, Adeel Khalid

Faculty Articles

This paper presents a vision-based framework for detecting humans and estimating head surface temperature from aerial thermal imagery acquired by Unmanned Aerial Systems (UAS). A comparative evaluation of recent object detection architectures was conducted to identify the most stable and reliable model for thermal human detection under varying flight altitudes. The selected framework integrates two head localization strategies, namely, segmentation-based mask slicing and pose-assisted keypoint localization, to extract head regions and compute per-pixel temperature values from radiometric metadata. The results show that cross-domain inference using pre-trained YOLOv11 models achieves reliable human detection across controlled outdoor environments. Between the two pipelines, …

Performance Analysis Of A Converted Electric Underbone Motorcycle: A Combined Dynamometer And Road Test Approach, Dhimas Oki Permata Aji, Sigit Suwarto, Yunus Ari Rokhim

Journal of Mechanical Engineering Science and Technology (JMEST)

In developing countries, converting traditional underbone motorcycles to electric vehicles transforms sustainable transportation from a theoretical concept to a practical implementation. This paper describes the design and operational performance evaluation of an electric underbone motorcycle conversion system that integrates a 2.0 kW, 72 V BLDC motor and a 72 V, 20 Ah lithium-ion battery pack. Compared to previous studies, this paper combines, for the first time, both dynamometer and road tests as the basis for a comprehensive performance assessment of low-cost motorcycle conversion. The dynamometer test was conducted under laboratory conditions to evaluate the test system for torque, power output, …

A Platform For Acquiring And Classifying Low-Noise Electrocardiogram Signals For Applications In Cardiovascular Monitoring, Begmamat Berdimurodovich Dushanov, Narzullo Mamatov Dr.

Technical science and innovation

The early screening and continuous monitoring of cardiovascular diseases need effective acquisition and smart processing of electrocardiogram (ECG) signals. In this article, we introduce a compact platform designed for the acquisition of low-noise ECG signals and classification of the signals using a one-dimensional convolutional neural network (1D-CNN). Our compact platform consists of a low-noise analog front-end (AFE), including an instrumentation amplifier and a chain of analog filters, along with a data acquisition component designed to ensure effective suppression of baseline wander and high frequencies. Our compact platform consumes a low amount of power and can therefore be used for continuous …

Simulating Thermal Diffusion Through Image-Derived Microstructures Of Ceramic Matrix Composites, Matik Heskin

Miners Solving for Tomorrow Research Conference

Thermal energy transport in materials can be effectively modeled using finite element software such as COMSOL. Experimentally measured or NIST–JANAF thermal conductivity data can be used to represent material behavior within these simulations. For heterogeneous or composite materials, effective properties are often approximated using rule-of-mixtures calculations. However, this overlooks the nuanced effects caused by complex microstructural geometry. To address this limitation, imaging and coding tools such as MATLAB can be used to process scanning electron microscopy (SEM) images. By thresholding the images to distinguish constituent materials, a representative mesh can be generated and imported into an FEM program. This approach …

Human Intention Prediction Using Cnn And Lstm Networks In Physical Human–Robot Interactions, Khosro Ghorbani Zadeh

Miners Solving for Tomorrow Research Conference

Advances in robotics and artificial intelligence have increased expectations for interactive robots in eldercare and assistive applications. A key challenge in creating safe and effective systems is accurately recognizing human intent and translating it into meaningful commands for robots to follow. Traditional physics-based models often fail to fully represent human force interactions due to their dynamic nature, while neural networks provide a promising alternative for predicting force-movement intentions. Multi-layer perceptrons (MLPs) show potential, however, they struggle with temporal dependencies and generalization. Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNNs) help address these limitations. This study compares these architectures …

Scale-Dependent Particle Transport Over Urban-Like Roughness In Turbulent Flow, Rae Riddle

Dissertations and Theses

This study employs direct numerical simulation (DNS) to investigate the dispersion of inertial particles in turbulent flow over three-dimensional urban-like roughness at Reτ = 200. Particles with Stokes numbers St = 5, 25, and 100 are tracked over cubic arrays with spanwise spacings Sy from 2h to 32h, where h = δ/8 and δ is the half-channel height, alongside a smooth-wall reference case. The results reveal scale-dependent particle responses characterized by three distinct regimes. First, high-inertia particles (St = 100) align strongly with mean secondary flows, exhibiting organized plumes above roughness elements. Their vertical transport peaks at intermediate spacing …

Ballistic Trajectories From Triangular Libration Points To Moon, Collin Gentry

Miners Solving for Tomorrow Research Conference

As stable points in the Earth-Moon system, the triangular libration points, L4 and L5, have many advantageous properties for space exploration. Ballistic trajectories at varying delta-Vs and impulse angles are computed and propagated from the libration points, and trajectories that arrive at the lunar surface are investigated. Preliminary conclusions are drawn about the accessibility of the lunar surface from the triangular libration points, and the implications for mission design are discussed. These trajectories present an alternative means of accessing the Moon, expanding the viability of the triangular points for missions and offering additional options for the use of cisular space.

Roof Mounted Single-Axis Solar Tracking Platform, German Markaryan, Dean Schultz, Isabella Bravo, Lucas Matter, Quacy Moore, Robert Wang

Mechanical Engineering Senior Theses

The growing need for efficient and reliable renewable energy sources has been increasing in the 21st century. All residential solar panel systems suffer from efficiency losses due to their inability to adjust their angle and a lack of a proper cleaning system. Automated Tracking Light Acquisition System (ATLAS) aims to solve this problem. Fixed solar panels without self cleaning harvest 30% less energy than adjustable counterparts. With an Arduino Nano ESP32 and Raspberry Pi 3B+ controlling ATLAS, it is designed to autonomously log data, have a night mode, have battery safety features and automatically adjust to the trajectory of the …