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Full-Text Articles in Engineering

Lifting-Line Predictions For The Ideal Twist Effectiveness Of Spanwise Continuous And Discrete Control Surfaces, Zachary S. Montgomery, Douglas F. Hunsaker, James J. Joo Mar 2025

Lifting-Line Predictions For The Ideal Twist Effectiveness Of Spanwise Continuous And Discrete Control Surfaces, Zachary S. Montgomery, Douglas F. Hunsaker, James J. Joo

Mechanical and Aerospace Engineering Faculty Publications

Modern materials and manufacturing technologies have allowed the construction of morphing wings that are able to continuously vary certain airfoil parameters such as twist, camber, or control surface deflection as a function of span. This work presents a twist effectiveness parameter as a means of comparing the ideal aerodynamic efficiency of spanwise continuous control surfaces (morphing wings) and spanwise discrete control surfaces (standard wings). A numerical algorithm is used to compute the twist effectiveness of both continuous and discrete control-surface designs over a wide range of planform shapes with evenly spaced actuation for inviscid, incompressible flow. Results included here show …

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Modeling And Analysis Of Wind Turbine Wake Vortex Evolution Due To Time-Constant Spatial Variations In Atmospheric Flow, Alayna Farrell, Fernando Ponta, North Yates Mar 2025

Modeling And Analysis Of Wind Turbine Wake Vortex Evolution Due To Time-Constant Spatial Variations In Atmospheric Flow, Alayna Farrell, Fernando Ponta, North Yates

Michigan Tech Publications

Modern utility-scale wind turbines are evolving toward larger, lighter, and more flexible designs to meet the growing demand for renewable energy while minimizing logistical costs. However, these advancements in lightweight design result in heightened aeroelastic sensitivity, leading to complex interactions which affect the rotor’s capacity to withstand aerodynamic loading and the cascading effects that manifest in the wake’s vortex-structure evolution under variable atmospheric conditions. In this paper, we analyze the influence of stream-wise fluctuating atmospheric flow conditions on wind turbines with large, flexible rotors through simulations of the National Rotor Testbed (NRT) turbine, located at Sandia National Labs’ Scaled Wind …

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Denitrification Processes, Inhibitors, And Their Implications In Ground Improvement, Yasaman Abdolvand, Mohammadhossein Sadeghiamirshahidi, Ishi Keenum Mar 2025

Denitrification Processes, Inhibitors, And Their Implications In Ground Improvement, Yasaman Abdolvand, Mohammadhossein Sadeghiamirshahidi, Ishi Keenum

Michigan Tech Publications

Ureolysis and denitrification are the two major microbial metabolic pathways commonly used in Microbially induced calcite precipitation (MICP) for geoengineering applications. Although ureolysis is generally the more efficient pathway, the denitrification pathway has gained more attention recently because a diverse group of bacteria can precipitate calcite via denitrification, and no harmful byproduct is generated provided that the reduction of nitrate to nitrogen gas is complete. There are, however, many environmental factors that could inhibit or reduce the efficiency of the denitrification process in soil. Some examples of these factors include salinity, pH, temperature, biodiversity (abundance and species of denitrifiers and …

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Denitrification Processes, Inhibitors, And Their Implications In Ground Improvement, Yasaman Abdolvand, Mohammadhossein Sadeghiamirshahidi, Ishi Keenum Mar 2025

Denitrification Processes, Inhibitors, And Their Implications In Ground Improvement, Yasaman Abdolvand, Mohammadhossein Sadeghiamirshahidi, Ishi Keenum

Michigan Tech Publications

Ureolysis and denitrification are the two major microbial metabolic pathways commonly used in Microbially induced calcite precipitation (MICP) for geoengineering applications. Although ureolysis is generally the more efficient pathway, the denitrification pathway has gained more attention recently because a diverse group of bacteria can precipitate calcite via denitrification, and no harmful byproduct is generated provided that the reduction of nitrate to nitrogen gas is complete. There are, however, many environmental factors that could inhibit or reduce the efficiency of the denitrification process in soil. Some examples of these factors include salinity, pH, temperature, biodiversity (abundance and species of denitrifiers and …

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Novel Method For Pure Polymer Vagus Nerve Stimulators, James Dodge Iii Mar 2025

Novel Method For Pure Polymer Vagus Nerve Stimulators, James Dodge Iii

ENGS 88 Honors Thesis (AB Students)

Vagus nerve stimulation (VNS) has become a promising treatment for epilepsy, depression, obesity, and more. However, the state-of-the-art nerve cuffs use metal conductors, limiting the implanted VNS devices’ biocompatibility, electronic properties, and ultimately the device lifetime. Because the benefits of VNS treatment increase over time, and metal limits the lifetime of devices, a transition to non-metallic conductors with a better match to tissue material properties and safer electronic properties promises to increase the lifetime of VNS devices. To demonstrate the replacement of metal with a conductor with properties closer to that of body tissue, a novel fabrication scheme was designed …

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Raising Awareness About Hydrographic Careers Through Sea-Going Opportunities, Juliet Kinney, Rochelle Wigley, Sara Cardigos, Fahima Bellabad, Larissa Marques Freguette Mar 2025

Raising Awareness About Hydrographic Careers Through Sea-Going Opportunities, Juliet Kinney, Rochelle Wigley, Sara Cardigos, Fahima Bellabad, Larissa Marques Freguette

Center for Coastal and Ocean Mapping

There is a worldwide shortage of hydrographic personnel (van Wegen, 2021, Hydro International 2008).  Calls for action to address this issue include the IHO’s Hydrography at Sea opportunities, while intiatiative such as Seabed 2030 are bringing broader attention to the field and helping to catalyze new discussions and partnerships in hydrography (IHO, 2024).  The global sea floor mapping community needs to develop a broader workforce pipeline.  We would like to highlight the importance of providing time at sea and leadership opportunities in developing a robust workforce.  We start with an overview of a selection of current exchange and training programs …

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Using Thermal Camera Drones In Beef Cattle Roundup, Justin Wyatt Clawson, Eric Galloway, Shalyn Drake, Shawn Barstow, Ross Israelsen, Michael Pate Mar 2025

Using Thermal Camera Drones In Beef Cattle Roundup, Justin Wyatt Clawson, Eric Galloway, Shalyn Drake, Shawn Barstow, Ross Israelsen, Michael Pate

All Current Publications

Using drones with thermal sensors can be an effective tool in finding and collecting livestock from summer mountain ranges in the West. Drones can complete searches in much less time than required on horseback in demonstrated areas. Using drones reduces the workload of the rider and horse, saving time and energy and reducing the risk of injury. With proper training and certification, livestock producers can use drones to locate cattle and perform many other cost-cutting operations.

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Spatio-Temporal Graph Neural Networks For Streamflow Prediction In The Upper Colorado Basin, Akhila Akkala, Soukaina Filali Boubrahimi, Shah Muhammad Hamdi, Pouya Hosseinzadeh, Ayman Nassar Mar 2025

Spatio-Temporal Graph Neural Networks For Streamflow Prediction In The Upper Colorado Basin, Akhila Akkala, Soukaina Filali Boubrahimi, Shah Muhammad Hamdi, Pouya Hosseinzadeh, Ayman Nassar

Computer Science Student Research

Streamflow prediction is vital for effective water resource management, enabling a better understanding of hydrological variability and its response to environmental factors. This study presents a spatio-temporal graph neural network (STGNN) model for streamflow prediction in the Upper Colorado River Basin (UCRB), integrating graph convolutional networks (GCNs) to model spatial connectivity and long short-term memory (LSTM) networks to capture temporal dynamics. Using 30 years of monthly streamflow data from 20 monitoring stations, the STGNN predicted streamflow over a 36-month horizon and was evaluated against traditional models, including random forest regression (RFR), LSTM, gated recurrent units (GRU), and seasonal auto-regressive integrated …

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Gait Characteristics In People With Friedreich Ataxia: Daily Life Versus Clinic Measures, Hannah L. Casey, Vrutangkumar V. Shah, Daniel Muzyka, James Mcnames, Mahmoud El-Gohary, Kristen Sowalsky, Delaram Safarpour, Patricia Carlson-Kuhta, Christian Rummey, Fay B. Horak, Christopher M. Gomez Mar 2025

Gait Characteristics In People With Friedreich Ataxia: Daily Life Versus Clinic Measures, Hannah L. Casey, Vrutangkumar V. Shah, Daniel Muzyka, James Mcnames, Mahmoud El-Gohary, Kristen Sowalsky, Delaram Safarpour, Patricia Carlson-Kuhta, Christian Rummey, Fay B. Horak, Christopher M. Gomez

Electrical and Computer Engineering Faculty Publications and Presentations

Gait assessments in a clinical setting may not accurately reflect mobility in everyday life. To better understand gait during daily life, we compared measures that discriminated Friedreich ataxia (FRDA) from healthy control (HC) subjects in prescribed clinic tests and free, daily-life monitoring.MethodsWe recruited 9 people with FRDA (median age: 20, IQR [12, 48] years). A comparative healthy control (HC) subject cohort of 9 was sampled using propensity matching on age (median age: 18 [13, 22] years). Subjects wore 3 inertial sensors (one each foot and lower back) in the laboratory during a 2-min walk at a natural pace, followed by …

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A Gaze-Driven Manufacturing Assembly Assistant System With Integrated Step Recognition, Repetition Analysis, And Real-Time Feedback, Haodong Chen, Niloofar Zendehdel, Ming C. Leu, Zhaozheng Yin Mar 2025

A Gaze-Driven Manufacturing Assembly Assistant System With Integrated Step Recognition, Repetition Analysis, And Real-Time Feedback, Haodong Chen, Niloofar Zendehdel, Ming C. Leu, Zhaozheng Yin

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Modern manufacturing faces significant challenges, including efficiency bottlenecks and high error rates in manual assembly operations. To address these challenges, we implement artificial intelligence (AI) and propose a gaze-driven assembly assistant system that leverages artificial intelligence for human-centered smart manufacturing. Our system processes video inputs of assembly activities using a Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) network for assembly step recognition, a Transformer network for repetitive action counting, and a gaze tracker for eye gaze estimation. The application of AI integrates the outputs of these tasks to deliver real-time visual assistance through a software interface that displays …

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Neurosymbolic Knowledge-Grounded Planning And Reasoning In Ai Systems, Amit Sheth, Vedant Khandelwal, Kaushik Roy, Vishal Pallagani, Megha Chakraborty Mar 2025

Neurosymbolic Knowledge-Grounded Planning And Reasoning In Ai Systems, Amit Sheth, Vedant Khandelwal, Kaushik Roy, Vishal Pallagani, Megha Chakraborty

Faculty Publications

To build AI systems capable of decision-support assistance, such as AI-assisted healthcare, it is essential to develop user-centric decision-making processes that are robust, interpretable, and capable of effectively processing and acting on natural language interactions. Instruction-based prompting of large language models has demonstrated considerable success in supporting humans with information assistance tasks, including creative writing and content generation. However, recent studies reveal that language models exhibit limitations in performing complex reasoning and planning tasks, such as constructing compositional or hierarchical plans involving multiple reasoning steps. To address these challenges, we propose a neurosymbolic framework that integrates large language models with …

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Multi-Model Integration For Dynamic Forecasting (Midf): A Framework For Wind Speed And Direction Prediction, Molaka Maruthi, Bubryur Kim, Sujeen Song, Jinwoo An, Zengshun Chen Mar 2025

Multi-Model Integration For Dynamic Forecasting (Midf): A Framework For Wind Speed And Direction Prediction, Molaka Maruthi, Bubryur Kim, Sujeen Song, Jinwoo An, Zengshun Chen

Civil Engineering Faculty Publications

Accurate forecasting of wind speed and direction is critical for the efficient integration of wind power into energy systems, ensuring reliable renewable energy production and grid stability. Traditional methods often struggle with capturing nonlinear interdependencies, quantifying uncertainties, and providing reliable long-term predictions, particularly in complex atmospheric conditions. To address these challenges, this study introduces multi-model Integration for dynamic forecasting (MIDF), an ensemble machine learning framework that combines the strengths of DeepAR and temporal fusion transformer (TFT) models through a two-step meta-learning process. MIDF leverages DeepAR’s probabilistic forecasting capabilities and TFT’s attention mechanisms to enhance accuracy, robustness, and interpretability. Using a …

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Exploring The Effect Of The Architecture Morphology On Urban Ventilation At Block Scale Using Cfd-Gis And Random Forest Combined Method, Bin Guo, Miaoyi Chen, Xiaowei Zhu, Zheng Wang, Lu Li, Lin Pei, Hailong Chen, Puhao Chen, Tengyue Guo Mar 2025

Exploring The Effect Of The Architecture Morphology On Urban Ventilation At Block Scale Using Cfd-Gis And Random Forest Combined Method, Bin Guo, Miaoyi Chen, Xiaowei Zhu, Zheng Wang, Lu Li, Lin Pei, Hailong Chen, Puhao Chen, Tengyue Guo

Mechanical and Materials Engineering Faculty Publications and Presentations

Urban ventilation plays a crucial role in dispersing air pollutants and mitigating the urban heat island effect. As a key factor, urban architectural morphology can significantly impact the wind field and ventilation efficiency. This study combines Computational Fluid Dynamics (CFD), Geographic Information System (GIS), and Random Forest (RF) methods to investigate the influence of architectural morphology on urban ventilation at the block scale. First, Remote Sensing (RS) and GIS were used to extract architectural morphology parameters. Second, CFD simulations, guided by in-situ observations, were conducted to model the wind field, with the Standard k-ɛ model validated as the optimal choice. …

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Physical And Biological Effects On Moths’ Navigation Performance, Yiftach Golov, Roi Gurka, Alexander Liberzon, Ally Harari Mar 2025

Physical And Biological Effects On Moths’ Navigation Performance, Yiftach Golov, Roi Gurka, Alexander Liberzon, Ally Harari

Physics and Engineering Science

In a chemosensing system, the local olfactory environment experienced by a foraging organism is defined as an odorscape. Using the nocturnal pink bollworm moth (Pectinophora gossypiella), we tested the combined effect of three biophysical aspects in its immediate odorscape to shed light on the coupling effects of biotic and abiotic factors on navigation performances of a nocturnal forager: i) the quality of the pheromone source, ii) the pheromone availability, and iii) the airflow characteristics. The navigation performance of the males was investigated using a wind tunnel assay equipped with 3D infrared high-speed cameras. The navigation performance of the males was …

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Feature Manifold Transformer For Detection Of Differential Item Functioning: Visual Detection Of Categorical Feature Nonconformity Through Attention-Based Analysis, Derrick A. Cox, Tanvi Banerjee, William L. Romine Mar 2025

Feature Manifold Transformer For Detection Of Differential Item Functioning: Visual Detection Of Categorical Feature Nonconformity Through Attention-Based Analysis, Derrick A. Cox, Tanvi Banerjee, William L. Romine

Computer Science and Engineering Faculty Publications

Methods for interpreting complex feature interactions in educational assessment data remain a critical challenge, with traditional statistical approaches often creating barriers to accessibility and interpretability. We introduce the Feature Manifold Transformer (FMT), a novel machine learning approach that leverages dimensionality reduction, representation learning, and transformer architectures to visualize and interpret feature relationships in categorical data. Using the Concept Inventory of Natural Selection (CINS) and Concept Assessment of Natural Selection (CANS) datasets as testbeds, we demonstrate the FMT’s ability to capture subtle relationships between student demographics and response patterns. Our methodology enables both global and local pattern analysis, providing interpretable visualizations …

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Msbzip55 Regulates Salinity Tolerance By Modulating Melatonin Biosynthesis In Alfalfa, Tingting Wang, Jiaqi Yang, Jiamin Cao, Qi Zhang, Huayue Liu, Peng Li, Yizhi Huang, Wenwu Qian, Xiaojing Bi, Hui Wang, Yunwei Zhang Mar 2025

Msbzip55 Regulates Salinity Tolerance By Modulating Melatonin Biosynthesis In Alfalfa, Tingting Wang, Jiaqi Yang, Jiamin Cao, Qi Zhang, Huayue Liu, Peng Li, Yizhi Huang, Wenwu Qian, Xiaojing Bi, Hui Wang, Yunwei Zhang

Faculty Publications

No abstract provided.

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Real-Time Defect Detection And Classification In Robotic Assembly Lines: A Machine Learning Framework, Fadi El Kalach, Mojtaba Farahani, Thorsten Wuest, Ramy Harik Mar 2025

Real-Time Defect Detection And Classification In Robotic Assembly Lines: A Machine Learning Framework, Fadi El Kalach, Mojtaba Farahani, Thorsten Wuest, Ramy Harik

Faculty Publications

Manufacturing systems have witnessed a significant transformation with the introduction of Industry 4.0, introducing new capabilities with the emergence of new technologies. One such instance is the proliferation of sensors enabling the generation and acquisition of vast amounts of data, leading to advancements in Artificial Intelligence (AI) for manufacturing. One field profiting from this is that of Time Series Analytics (TSC) which includes forecasting and classification. TSC can be crucial for fault detection and diagnosis in manufacturing systems. However, there are still challenges in utilizing manufacturing datasets to train and deploy classification algorithms for real time classification. As such this …

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Introducing A Novel Figure Of Merit For Evaluating Stability Of Perovskite Solar Cells: Utilizing Long Short-Term Memory Neural Networks, Zahraa Ismail, Ahmed Alali, Mahmoud Ashraf, Ahmad Muhammad, Sameh O. Abdellatif Mar 2025

Introducing A Novel Figure Of Merit For Evaluating Stability Of Perovskite Solar Cells: Utilizing Long Short-Term Memory Neural Networks, Zahraa Ismail, Ahmed Alali, Mahmoud Ashraf, Ahmad Muhammad, Sameh O. Abdellatif

Electrical Engineering

This study introduces a novel figure of merit for evaluating the stability of perovskite solar cells (PSCs) by employing advanced Long Short-Term Memory (LSTM) neural networks to investigate degradation mechanisms. By harnessing the power of artificial intelligence and data analytics, we analyzed extensive datasets encompassing PSC parameters, experimental results, and environmental conditions, revealing critical insights into the degradation patterns affecting cell performance over time. Our findings indicate that the LSTM model effectively captures and predicts the complex relationships between key design parameters—efficiency, fill factor, and open-circuit voltage—and degradation-induced changes in PSCs. Specifically, we identified three degradation coefficients associated with the …

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Behavior Of Buried Sliplined Corrugated Metal Pipes Subjected To Footing Loading, S. Mustapha Rahmaninezhad, Saif Jawad, Jie Han, Mahdi Al-Naddaf, Robert L. Parsons Mar 2025

Behavior Of Buried Sliplined Corrugated Metal Pipes Subjected To Footing Loading, S. Mustapha Rahmaninezhad, Saif Jawad, Jie Han, Mahdi Al-Naddaf, Robert L. Parsons

Civil Engineering Faculty Publications

Buried structures (e.g., culverts and pipes under roadways) installed several decades ago are reaching the end of their service life. Excavation and replacement of these structures will cause disturbances to the transportation network and require significant funding. Trenchless techniques (e.g., sliplining) have been increasingly employed to rehabilitate deteriorated buried structures (e.g., corroded corrugated steel pipes). Sliplining includes inserting a new pipe (liner) into an existing deteriorated pipe and filling the gap between them with grout. The objective of this study was to evaluate the effect of sliplining on the behavior of buried corrugated steel pipes with different degrees of corrosion …

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Cost-Effective Active Laser Scanning System For Depth-Aware Deep-Learning-Based Instance Segmentation In Poultry Processing, Pouya Sohrabipour, Chaitanya Kumar Reddy Pallerla, Amirreza Davar, Siavash Mahmoudi, Philip Crandall, Wan Shou, Yu She, Dongyi Wang Mar 2025

Cost-Effective Active Laser Scanning System For Depth-Aware Deep-Learning-Based Instance Segmentation In Poultry Processing, Pouya Sohrabipour, Chaitanya Kumar Reddy Pallerla, Amirreza Davar, Siavash Mahmoudi, Philip Crandall, Wan Shou, Yu She, Dongyi Wang

School of Industrial Engineering Faculty Publications

The poultry industry plays a pivotal role in global agriculture, with poultry serving as a major source of protein and contributing significantly to economic growth. However, the sector faces challenges associated with labor-intensive tasks that are repetitive and physically demanding. Automation has emerged as a critical solution to enhance operational efficiency and improve working conditions. Specifically, robotic manipulation and handling of objects is becoming ubiquitous in factories. However, challenges exist to precisely identify and guide a robot to handle a pile of objects with similar textures and colors. This paper focuses on the development of a vision system for a …

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Direct Water Reuse: A Hydraulic Economic Analysis Of Connecting The Wastewater Treatment Effluent To Water Treatment Influent, Brian Barkdoll, Amber G. Strutz Mar 2025

Direct Water Reuse: A Hydraulic Economic Analysis Of Connecting The Wastewater Treatment Effluent To Water Treatment Influent, Brian Barkdoll, Amber G. Strutz

Michigan Tech Publications

Climate change is causing increased flooding and droughts. Droughts can cause drinking water sources to run dry. Therefore, recycling water from the wastewater plant effluent to the water treatment plant influent, also called ‘direct reuse’ is becoming necessary. A connection between a city's wastewater treatment plant (WWTP) effluent and water treatment plant (WTP) influent via pipe was simulated to provide an understanding of the capital costs and feasibility of execution. Hydraulic pipe-flow and pump equations were used to calculate the pipe and pump sizes needed for various flow rate and elevation head values. Various flow rate recycle rates were modeled …

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Flipping Out: Role Of Arginine In Hydrophobic Interactions And Biological Formulation Design, Jonathan W.P. Zajac, Praveen Muralikrishnan, Idris Tohidian, Xianci Zeng, Caryn L. Heldt, Sarah L. Perry, Et. Al. Mar 2025

Flipping Out: Role Of Arginine In Hydrophobic Interactions And Biological Formulation Design, Jonathan W.P. Zajac, Praveen Muralikrishnan, Idris Tohidian, Xianci Zeng, Caryn L. Heldt, Sarah L. Perry, Et. Al.

Michigan Tech Publications

Arginine has been a mainstay in biological formulation development for decades. To date, the way arginine modulates protein stability has been widely studied and debated. Here, we employed a hydrophobic polymer to decouple hydrophobic effects from other interactions relevant to protein folding. While existing hypotheses for the effects of arginine can generally be categorized as either direct or indirect, our results indicate that direct and indirect mechanisms of arginine co-exist and oppose each other. At low concentrations, arginine was observed to stabilize hydrophobic polymer folding via a sidechain-dominated direct mechanism, while at high concentrations, arginine stabilized polymer folding via a …

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Flapping Dynamics And Wing Flexibility Enhance Odor Detection In Blue Bottle Flies, Naeem Haider, Zhipeng Lou, Chengyu Li Mar 2025

Flapping Dynamics And Wing Flexibility Enhance Odor Detection In Blue Bottle Flies, Naeem Haider, Zhipeng Lou, Chengyu Li

Faculty Scholarship

One of the most ancient and evolutionarily conserved behaviors in the animal kingdom involves utilizing wind-borne odor plumes to track essential elements such as food, mates, and predators. Insects, particularly flies, demonstrate a remarkable proficiency in this behavior, efficiently processing complex odor information encompassing concentrations, direction, and speed through their olfactory system, thereby facilitating effective odor-guided navigation. Recent years have witnessed substantial research explaining the impact of wing flexibility and kinematics on the aerodynamics and flow field physics governing the flight of insects. However, the relationship between the flow field and olfactory functions remains largely unexplored, presenting an attractive frontier …

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Solid Wastes From Geothermal Energy Production And Implications For Direct Lithium Extraction, William T. Stringfellow, Mary K. Camarillo Mar 2025

Solid Wastes From Geothermal Energy Production And Implications For Direct Lithium Extraction, William T. Stringfellow, Mary K. Camarillo

Pacific Faculty Work

Direct lithium extraction (DLE) of brines after geothermal power production offers opportunities to produce environmentally benign “green” lithium; however, some environmental impact is inevitable. We examined solid waste production at geothermal power plants in southern California that are also locations for planned DLE facilities. Currently, the geothermal plants in this region produce approximately 79,800 metric tons (wet weight) per year of solid waste, which represents about 28 metric tons per GWh of net electricity production or approximately 500 mg solids per kg geothermal brine. Approximately 15% of this waste requires management as hazardous waste. Solids produced during power production represent …

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Time-Series Forecasting In Smart Manufacturing Systems: An Experimental Evaluation Of The State-Of-The-Art Algorithms, Mojaba A. Farahani, Fadi El Kalach, Austin Harper, M.R. Mccormick, Ramy Harik, Thorsten Wuest Mar 2025

Time-Series Forecasting In Smart Manufacturing Systems: An Experimental Evaluation Of The State-Of-The-Art Algorithms, Mojaba A. Farahani, Fadi El Kalach, Austin Harper, M.R. Mccormick, Ramy Harik, Thorsten Wuest

Faculty Publications

Time-Series Forecasting (TSF) is a growing research area across various domains including manufacturing. Manufacturing can benefit from Artificial Intelligence (AI) and Machine Learning (ML) innovations for TSF tasks. Although numerous TSF algorithms have been developed and proposed over the past decades, the critical validation and experimental evaluation of the algorithms hold substantial value for researchers and practitioners and are missing to date. This study aims to fill this research gap by providing a rigorous experimental evaluation of the state-of-the-art TSF algorithms on thirteen manufacturing-related datasets with a focus on their applicability in smart manufacturing environments. Each algorithm was selected based …

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Intelligent Turning Cyber-Physical Systems Modeling Using Sysml, Prithbey Raj Dey, David Lee Enke, Mario F. Buchely Mar 2025

Intelligent Turning Cyber-Physical Systems Modeling Using Sysml, Prithbey Raj Dey, David Lee Enke, Mario F. Buchely

Engineering Management and Systems Engineering Faculty Research & Creative Works

Cyber-Physical Systems (CPS) support industrial automation that incorporates people, hardware, signal, computation, and control using networking to achieve desired results. The complex automated CPS design demands a standard and comprehensive approach to appropriately identify the system requirements, define the architecture, and model the relationships among the software and hardware components. Systems Modeling Language (SysML) provides the capability for a comprehensive modeling to capture the desired design requirements in the systems architecture. SysML enables performance estimation of the model by analyzing constraints while identifying interactions among the components through various behavioral diagrams. In this paper, SysML is applied to the design …

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Martensitic Transformation Induced Strength-Ductility Synergy In Additively Manufactured Maraging 250 Steel By Thermal History Engineering, Shahryar Mooraj, Shuai Feng, Matthew Luebbe, Matthew Register, Jian Liu, Tianyi Li, Baris Yavas, David P. Schmidt, Matthew W. Priddy, Michael B. Nicholas, Victor K. Champagne, Mark Aindow, Haiming Wen, Wen Chen Mar 2025

Martensitic Transformation Induced Strength-Ductility Synergy In Additively Manufactured Maraging 250 Steel By Thermal History Engineering, Shahryar Mooraj, Shuai Feng, Matthew Luebbe, Matthew Register, Jian Liu, Tianyi Li, Baris Yavas, David P. Schmidt, Matthew W. Priddy, Michael B. Nicholas, Victor K. Champagne, Mark Aindow, Haiming Wen, Wen Chen

Materials Science and Engineering Faculty Research & Creative Works

Maraging steels are known for their exceptional strength but suffer from limited work hardening and ductility. Here, we report an intermittent printing strategy to tailor the microstructure and mechanical properties of maraging 250 steel via tuning the thermal history during wire-arc directed energy deposition. By introducing a dwell time between adjacent layers, the maraging 250 steel is cooled below the martensite start temperature, triggering thermally driven martensitic transformation during the printing process. Thermal cycling during subsequent layer deposition results in the formation of reverted austenite which shows a refined microstructure and induces elemental segregation between martensite and reverted austenite. The …

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Emg-Based Intraoperative Neuromonitoring Using Advanced Machine Learning Approaches, Abdalla Nabil Elsharkawy, Nourhan Zayed Mar 2025

Emg-Based Intraoperative Neuromonitoring Using Advanced Machine Learning Approaches, Abdalla Nabil Elsharkawy, Nourhan Zayed

Mechanical Engineering

Intraoperative neuromonitoring (IONM) plays a critical role in minimizing nerve damage during surgeries by providing real-time feedback on neural integrity. This study evaluated models associated with deep learning and machine learning models for electromyography classification of signal during intraoperative neuromonitoring (IONM). The CNNLSTM model achieved the highest accuracy (85.2%), outperforming traditional models like KNN (53%), RF (62%), and CNN (76%). This demonstrates the degree to which the CNN-LSTM model can gain insight into temporal and spatial dependencies throughout the EMG signals, which makes it optimal for real-time classification in IONM applications. This implies that deep learning techniques can improve surgical …

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Neurophisology Biosignals Of Cognitive Training Classification In Virtual Reality Environment Using Deep Learning Model, Nourhan Zayed, Mohamed Reda Mar 2025

Neurophisology Biosignals Of Cognitive Training Classification In Virtual Reality Environment Using Deep Learning Model, Nourhan Zayed, Mohamed Reda

Mechanical Engineering

This research investigates the potential of neurophysiological biosignals fusion, such as electroencephalogram (EEG) and Eye Tracking signals (ET), to classify cognitive states during virtual reality (VR) training, specifically for the rehabilitation of neurodegenerative diseases. By analyzing EEG data collected from participants engaged in VR-based cognitive exercises, we aim to identify patterns associated with different cognitive states and develop a robust classification system. A Convolutional Neural Network (CNN) model was developed to predict task performance utilizing neurophysiological inputs in an immersive world. This system could be used to monitor cognitive function, assess treatment efficacy, and provide real-time feedback to adapt the …

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Combining Passive And Active Ultrasonic Stress Wave Monitoring For The Characterization Of The Early-Age Properties Of A Uhpfrc Beam, Numa Bertola, Thomas Schumacher, Ernst Niederleithinger, Eugen Bruhwiler Mar 2025

Combining Passive And Active Ultrasonic Stress Wave Monitoring For The Characterization Of The Early-Age Properties Of A Uhpfrc Beam, Numa Bertola, Thomas Schumacher, Ernst Niederleithinger, Eugen Bruhwiler

Civil and Environmental Engineering Faculty Publications and Presentations

This article focuses on the characterization of the early-age properties of Ultra-High-Performance Fiber-Reinforced Cementitious Composite (UHPFRC), which is becoming popular for designing lightweight and durable structures. Due to the large proportion of cement in the mix, the hardening of UHPFRC is significantly faster than conventional concrete. Therefore, the development of UHPFRC properties, such as the elastic modulus, is difficult to monitor as it happens while elements are within the formwork. For this reason, the hydration process of UHPFRC elements is not fully understood yet. A combined passive (or acoustic emission) and active ultrasonic stress wave monitoring approach has the potential …

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