Engineering Commons^™

Identifying Hidden Factors Influencing Soil Olsen-P In An Alkaline Calcareous Soil Using Machine Learning And Geostatistical Techniques, Moussa Bouray, Mohammed Bayad, Adnane Beniaich, Ahmed G. El-Naggar, Rebecca Muenich, Kahlil El Mejahed, Abdallah Oukarroum, Mohamed El Gharous

Biological and Agricultural Engineering Faculty Publications and Presentations

Phosphorus (P) deficiency is one of the major constraints for sustainable crop production in calcareous soils. This study aimed to elucidate the key soil characteristics modulating the variability of soil Olsen P in these typical soils. A comprehensive soil sampling initiative (1.5 samples per hectare) was conducted on a 100-ha farm, considering 31 attributes that included soil physical and chemical properties, and geographic attributes. Three machine learning algorithms—partial least squares regression (PLSR), random forest (RF), and cubist regression (CR)—were employed to understand key variables controlling soil Olsen P. Furthermore, the same data set was used to spatially map the …

Surely You Can’T Be Serious: A Student’S Guide For Flight School Closure, Aidan Mcglasson, Sarah Nilsson

Publications

Flying aircraft, whether at a general aviation, commercial, or military level, is deeply engrained in American culture. Opinion polls place being a professional pilot as one of the most respected, and prestigious jobs in the country (Mushtaque, 2023). As evidenced by the popularity of movies such as Airplane!, Top Gun, or Sully, flying is something that fascinates many people. Perhaps contributing to its mystique is the difficulty and expense in obtaining the necessary training and certifications to be a pilot. Some people undergo flight training with the goal of flying commercially, as an airline or corporate pilot, while others do …

Formation Mechanism And Strengthening Method Of Geometric-Mechanical Structure Of Plugging Zone In Deep Naturally Fractured Reservoir, Chengyuan Xu, Honglin Zhang, Jianhong Fu, Yili Kang, Zhenjiang You

Research outputs 2022 to 2026

Efficient fracture plugging plays a critical role during drilling and completion of deep naturally fractured reservoirs, minimizing fluid loss, and ensuring reservoir protection. This study investigates the formation process of the geometric-mechanical structure of fracture plugging zones through a series of experiments including microscopic visualization, photoelastic and fracture plugging experiments. By examining these experiments, we reveal the relationship between lost circulation materials (LCMs) at the micro-scale, force chain network structures at the meso-scale, and the pressure stability of plugging zones at the macro-scale. Based on the analytic hierarchy process (AHP), we introduce an evaluation index for assessing the stability of …

Characterization Of Non-Gaussianity In The Snow Distributions Of Various Landscapes, Noriaki Ohara, Andrew D. Parsekian, Benjamin M. Jones, Rodrigo C. Rangel, Kenneth M Hinkel, Rui A.P. Perdigão

Michigan Tech Publications

Seasonal snowpack is an important predictor of the water resources available in the following spring and early-summer melt season. Total basin snow water equivalent (SWE) estimation usually requires a form of statistical analysis that is implicitly built upon the Gaussian framework. However, it is important to characterize the non-Gaussian properties of snow distribution for accurate large-scale SWE estimation based on remotely sensed or sparse ground-based observations. This study quantified non-Gaussianity using sample negentropy; the Kullback-Leibler divergence from the Gaussian distribution for field-observed snow depth data from the North Slope, Alaska; and three representative SWE distributions in the western USA from …

The Future Of Flying: An Exploration Of New Aircraft Design And Energy Required To Support Advanced Air Mobility – Part 1, Sarah Nilsson

Publications

Lecture exploring new aircraft design and energy required to support advanced air mobility.

Sustainable Mobility: Machine Learning-Driven Deployment Of Ev Charging Points In Dublin, Ruairí De Fréin, Alexander Mutiso Mutua Mr

Articles

Electric vehicle (EV) drivers in urban areas face range anxiety due to the fear of running out of charge without timely access to charging points (CPs). The lack of sufficient numbers of CPs has hindered EV adoption and negatively impacted the progress of sustainable mobility. We propose a CP distribution algorithm that is machine learning-based and leverages population density, points of interest (POIs), and the most used roads as input parameters to determine the best locations for deploying CPs. The objects of the following research are as follows: (1) to allocate weights to the three parameters in a $6$ km …

Collapse Of Pre-Covid-19 Differences In Performance In Online Vs. In-Person College Science Classes, And Continued Decline In Student Learning, Gregg R. Davidson, Hong Xiao, Kristin Davidson

Faculty and Student Publications

Abstract: Studies comparing student outcomes for online vs. in-person classes have reported mixed results, though with a majority finding that lower-performing students, on average, fare worse in online classes, attributed to the lack of built-in structure provided by in-person instruction. The online/in-person outcome disparity was normative for non-major geology classes at the University of Mississippi prior to COVID-19, but the difference disappeared in the years after 2020. Previously distinct trendlines of GPA-based predictions of earned-grade for online and in-person classes merged. Of particular concern, outcomes for in-person classes declined to match pre-COVID-19 online expectations, with lower-GPA students disproportionally impacted. Objective …

Fringe-Field Actuation Of Mems Cantilever Resonators: Capacitance Model For Frequency-Amplitude Response Of Parametric Resonance, Miguel A. Martinez, Dumitru I. Carantu

Mechanical Engineering Faculty Publications

The paper investigates the frequency-amplitude response of micro-electromechanical system (MEMS) cantilever beams, which are actuated by the fringe field at parametric resonance. In this design, a micro cantilever beam (flexible electrode) and a ground plate (fixed electrode) are placed in parallel and connected through an AC voltage. The electrostatic force is due to electric field lines within the volume directly between the cantilever and the ground plate. The parallel-plate capacitance is directly related to the overlapping area of the two electrodes. However, to accurately compute the capacitance of the two electrodes, the effects due to the fringing field must be …

Electrostatically Actuated Bio-Mems Circular Membrane Resonator Sensors: Voltage Response Of Primary Resonance, Dumitru I. Caruntu, Marcos Alipi

Mechanical Engineering Faculty Publications

This paper deals with the voltage-amplitude relationship during the primary resonance of electrostatically actuated circular membrane resonator sensors within the context of BIO-MEMS. The motion of these membranes is governed by a partial differential equation, which is nondimensionalized for analysis. This equation incorporates both damping effects and soft electrostatic actuation. The actuation AC frequency is set close to half of the membrane’s first natural frequency, leading to primary resonance. To investigate membrane’s voltage response, two principal methods were employed: the method of multiple scales (MMS) and a reduced order model (ROM) that incorporates two modes of vibration. This research provides …

Sediment Transport On Rippled Beds, Octavio Guevara, L. Guan, J. S. Salinas, ‪Nadim Zgheib, S. Balachandar

Mechanical Engineering Faculty Publications

We conduct an Euler-Lagrange, direct numerical simulation of a turbulent channel flow at a shear Reynolds number of Reτ=180 over an erodible particle bed. The particle bed consists of approximately 1.3 × 10⁶ monodisperse particles, resulting in a bed thickness of around 12–13 particles. The particle density and size are chosen to achieve a ratio of 4 for the Shields stress to the critical Shields stress necessary for incipient motion such that particle transport occurs primarily as bedload. The simulation is run long enough for ripples to form. We track the temporal evolution of the particle flux and excess …

Importance Of Soft Skills Comparative Study With Cybersecurity Professionals In The Manufacturing And Finance Critical Sectors, Stanley Mierzwa, Mary Lind

Center for Cybersecurity

Cybersecurity professionals require and will benefit from having strong and competent technical and soft skills, knowledge, and abilities. Cyber-attacks continue to plague our organizations and businesses, and finding the individuals with the skills needed for industry teams to contend with these broad and varying types of breaches is essential. This research article will outline the results of a comparative quantitative study that compares the importance of soft skills or nontechnical competencies by information security and cybersecurity professionals in the finance and manufacturing critical infrastructure sectors. This research study used a validated survey instrument from a previous seminal study to capture …

Impact Of Coverage And Guest Residue On Polyproline Ii Helix Peptide Antifouling, Rebecca S. Ahn, Henry T. Grome, Sogol Asaei, Geeta Verma, Christina S. Dang, Harihara Baskaran, Julie N. Renner

Faculty Scholarship

Polyproline II (PPII) peptide sequences are recognized as promising biomaterials because of their attractive antifouling properties. However, the mechanisms behind their antifouling behavior have not been fully characterized. In this work we show that PPII peptide coverage, controlled by adsorption time, significantly reduces the fouling of bovine serum albumin (BSA, a model foulant). In addition, guest residues introduced into the PPII sequence are shown to significantly impact BSA adsorption as well as human mesenchymal stem cell (hMSC) spreading. This research will help guide future PPII peptide designs for incorporation into novel biomaterials.

A Benchmark Knowledge Graph Of Driving Scenes For Knowledge Completion Tasks, Ruwan Wickramarachchi, Cory Henson, Amit Sheth

Publications

Knowledge graph completion (KGC) is a problem of significant importance due to the inherent incompleteness in knowledge graphs (KGs). The current approaches for KGC using link prediction (LP) mostly rely on a common set of benchmark datasets that are quite different from real-world industrial KGs. Therefore, the adaptability of current LP methods for real-world KGs and domain-specific ap- plications is questionable. To support the evaluation of current and future LP and KGC methods for industrial KGs, we introduce DSceneKG, a suite of real-world driving scene knowledge graphs that are currently being used across various industrial applications. The DSceneKG is publicly …

Three-Dimensional Technique For Accurate Pavement Macrotexture Measurement Using Surface Volume Parameters, Alireza Pourhassan, Ahmed A. Gheni, Mohamed A. Elgawady

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This study introduces a novel three-dimensional (3D) pavement macrotexture measurement technique using ISO 25178 Surface Volume Parameters (SVP). The method calculates pavement material volume and texture height using cutoff thresholds based on the cumulative probability density function of measured heights. The research aims to optimize these cutoff thresholds for accurate 3D analysis of pavement macrotexture. The study evaluates the performance of various 3D and 2D parameters—assessing their repeatability, reliability, and accuracy—across thirty pavement samples with diverse macrotexture conditions. Findings show that the 3D SVP method, with optimized cutoff thresholds, strongly correlates with sand patch mean texture depth (MTD) and exhibits …

Partnering With Communities To Understand Social Determinants Of Health (Sdoh) Impacts On Access To Shared Micromobility, Elizabeth K. Mcclain, Kaitlynn Walker, Ganesh Kumar, Ashley Bright, Clare Aziz, Ann W. Banchoff, Zacharia N. Doueiri, Abby C. King, Suman Mitra

Civil Engineering Faculty Publications and Presentations

This study explored the facilitators and barriers of community bike share use in a mid-sized city with high incidence of poverty and racial diversity using a community-based participatory action research (CBPAR) photovoice framework with the Stanford Our Voice (OV) Discovery Tool digital application. Community members participated in one of three community citizen science walks with follow up focus groups facilitated by osteopathic medical student researcher to address “What makes it easy or hard to ride a bike using the bike share?” Twenty-seven diverse community members partnered with four osteopathic medical students exploring vulnerable individuals’ lived experiences, beliefs/understanding of the Social …

Internet Of Things-Based Automated Solutions Utilizing Machine Learning For Smart And Real-Time Irrigation Management: A Review, Bryan Nsoh, Abia Katimbo, Hongzhi Guo, Derek M. Heeren, Hope Njuki Nakabuye, Xin Qiao, Yufeng Ge, Daran R. Rudnick, Joshua Wanyama, Erion Bwambale, Shafik Kiraga

Department of Agricultural and Biological Systems Engineering: Faculty Publications

This systematic review critically evaluates the current state and future potential of real-time, end-to-end smart, and automated irrigation management systems, focusing on integrating the Internet of Things (IoTs) and machine learning technologies for enhanced agricultural water use efficiency and crop productivity. In this review, the automation of each component is examined in the irrigation management pipeline from data collection to application while analyzing its effectiveness, efficiency, and integration with various precision agriculture technologies. It also investigates the role of the interoperability, standardization, and cybersecurity of IoT-based automated solutions for irrigation applications. Furthermore, in this review, the existing gaps are identified …

Trisc: Low-Cost Design Of Trigonometric Functions With Quasi Stochastic Computing, Mehran Shoushtari Moghadam, M. Hassan Najafi

Faculty Scholarship

Low-cost and hardware-efficient design of trigonometric functions is challenging. Stochastic computing (SC), an emerging computing model processing random bit-streams, offers promising solutions for this problem. The existing implementations, however, often overlook the importance of the data converters necessary to generate the needed bit-streams. While recent advancements in SC bit-stream generators focus on basic arithmetic operations such as multiplication and addition, energy-efficient SC design of non-linear functions demands attention to both the computation circuit and the bit-stream generator. This work introduces TriSC, a novel approach for SC-based design of trigonometric functions enjoying state-of-the-art (SOTA) quasi-random bit-streams. Unlike SOTA SC designs of …

Sensitivity Of Wavelet-Based Optical Flow Velocimetry (Wofv) To Common Experimental Error Sources, Bryan E. Schmidt, Gauresh Raj Jassal

Faculty Scholarship

The influence of several potential error sources and non-ideal experimental effects on the accuracy of a wavelet-based optical flow velocimetry (wOFV) method when applied to tracer particle images is evaluated using data from a series of synthetic flows. Out-of-plane particle displacements, severe image noise, laser sheet thickness reduction, and image intensity non-uniformity are shown to decrease the accuracy of wOFV in a similar manner to correlation-based particle image velocimetry (PIV). For the error sources tested, wOFV displays a similar or slightly increased sensitivity compared to PIV, but the wOFV results are still more accurate than PIV when the magnitude of …

Boosting The Power Performance Of Microbial Fuel Cells By Using Dual Nanomaterial-Modified Carbon Felt Electrodes, Krishna Thapa, Wenyan Liu, Yuwei Zhang, David J. Westenberg, Yishu Zhou, Risheng Wang

Chemistry Faculty Research & Creative Works

Innovative design enhancements to microbial fuel cells (MFCs) are pivotal for improving their viability as renewable energy sources. This study introduces a dual approach to electrode modification, integrating polyaniline (PANI) and gold nanoparticles (AuNPs) on carbon felt (CF) anodes coupled with a unique cathode composed of DNA origami and chitosan. The synergistic effect of PANI and AuNPs significantly increases the hydrophilicity and conductivity of the anode, leading to a considerable surge in power density. Concurrently, the biocompatible DNA origami and chitosan-functionalized cathode facilitates efficient electron transfer without relying on conventional catalysts. Together, these modifications yield a 52.42% increase in the …

Single-Molecule Profiling Of Per- And Polyfluoroalkyl Substances By Cyclodextrin Mediated Host-Guest Interactions Within A Biological Nanopore, Xiaojun Wei, Aditya Choudhary, Leon Y. Wang, Lixing Yang, Mark J. Uline, Mario Tagliazucchi, Qian Wang, Dmitry Bedrov, Chang Liu

Faculty Publications

Biological nanopores are increasingly used in molecular sensing due to their single-molecule sensitivity. The detection of per- and polyfluoroalkyl substances (PFAS) like perfluorooctanoic acid and perfluorooctane sulfonic acid is critical due to their environmental prevalence and toxicity. Here, we investigate selective interactions between PFAS and four cyclodextrin (CD) variants (α-, β-, γ-, and 2-hydroxypropyl-γ-CD) within an α-hemolysin nanopore. We demonstrate that PFAS molecules can be electrochemically sensed by interacting with a γ-CD in a nanopore. Using HP-γ-CDs with increased steric resistance, we can identify homologs of the perfluoroalkyl carboxylic acid and the perfluoroalkyl sulfonic acid families and detect common PFAS …

Ignis: A One-Dimensional Laminar Flame Code, Jansen P. Berryhill, Jacob K. Spinti, David O. Lignell

Faculty Publications

Laminar flame codes have an important role in combustion modeling. They can provide a fundamental understanding of flame dynamics and provide a basis for building subgrid scale models in turbulent flow simulations. This paper presents Ignis, an open-source laminar flame code with the capability to offload submodels, like soot formation and radiation, using external packages and libraries. Ignis is written in C++, is documented with Doxygen, and is available on GitHub. It contains three different flame formulations: diffusion flames, premixed flames, and laminar flamelets solved in the mixture fraction coordinate. An option to facilitate creation of a diffusion flame table …

A Study Of Fit And Friction Force As A Function Of The Printing Process For Fff 3d-Printed Piston–Cylinder Assembly, Philippe A. Passeraub, Quentin Allen, Elizabeth Clark, Michael Miles, Siddartha Berns, Maija Pearson, Sterling Allred, Jonah Brooks, Sylvain Hugon

ScholarsArchive Data

Dataset DOI: https://doi.org/10.26067/hjm6-3d45

The shared data comprises the experimental measurements performed presented in the figures 5, 6, 7, 9, 10, 11, 12, and in the tables for the following article:

Passeraub, P.A.; Allen, Q.; Clark, E.; Miles, M.; Berns, S.; Pearson, M.; Allred, S.; Brooks, J.; Hugon, S. A Study of Fit and Friction Force as a Function of the Printing Process for FFF 3D-Printed Piston–Cylinder Assembly. J. Manuf. Mater. Process. 2024, 8, 249. https://doi.org/10.3390/jmmp8060249

Quantifying Chemomechanical Weakening In Muscovite Mica With A Simple Micromechanical Model, Jordan J. Sickle, William M. Mook, Frank W. Delrio, Anastasia G. Ilgen, Wendelin Wright, Karin A. Dahmen

Faculty Journal Articles

In response to gradual nanoindentation, the surface of muscovite mica deforms by sudden stochastic nanometer-scale displacement bursts. Here, the statistics of these displacement events are interpreted using a statistical model previously used to model earthquakes to understand how chemically reactive environments alter the surface properties of this material. We show that the statistics of nanoindentation displacement bursts in muscovite mica are tuned by chemomechanical weakening in a manner similar to how the statistics of model events are tuned by a mechanical weakening parameter that describes how easily system-spanning cracks can be nucleated. Because the predictions of this model are independent …

A Distributed Secure System For Threads Detection In Crowded Environments Based On Biometric Facial Expression, Nourhan Zayed, Hassan I. Sayed, Ghada F. El-Kabbany

Mechanical Engineering

Ensuring security in crowded areas poses a significant problem due to the dense population and the intricate task of monitoring their behaviors. This research presents a real-time security system that utilizes facial expression analysis to identify potential threats. The technology utilizes sophisticated facial recognition and emotion detection techniques to accurately recognize emotions such as wrath, fear, and anxiety. These feelings can serve as indicators of suspicious activities or potential security risks. The system utilizes a Convolutional Neural Network (CNN) to classify facial expressions and recognize objects. In addition, it integrates an SVM classifier trained on features derived from the combined …

A Comparative Analysis Of Optimizing Classification Techniques On Fruits Images Dataset, Ghada F. Elkabbany, Youssef G. Fouad, Kerollos W. Youssef, Jannah A. Amir, Nourhan Zayed

Mechanical Engineering

Data mining; known as data dredging or data archeology; provides several techniques to extract new and interpretable information from existing datasets. This work presents a comparison of the performance of various classification techniques, specifically Support Vector Machine (SVM), Radial Basis Function (RBF), K-Nearest Neighbors (KNN), and decision trees, using images of fruits. An open-source dataset called fruits360 is used focusing on three specific fruits: pineapple, cocos, and avocado. This selection allows testing the classification techniques in different ways, as pineapples and cocos are similar in color, while cocos and avocados resemble each other in shape due to their oval-like geometry. …

Reducing Carbon Footprint In Ai: A Framework For Sustainable Training Of Large Language Models, Sunbal Iftikhar, Steven Davy

Conference papers

In the world of artificial intelligence (AI), large language models (LLMs) are leading the way, transforming how people understand and use language. These models have significantly impacted various domains, from natural language processing (NLP) to content generation, sparking a wave of innovation and exploration. However, this rapid progress brings to light the environmental implications of LLMs, particularly the significant energy consumption and carbon emissions during their training and operational phases. This requires a shift towards more energy-efficient practices in training and deploying LLMs, balancing AI innovation with environmental responsibility. This paper emphasizes the need for improving the energy efficiency of …

A Probabilistic Kp And Hp Driven Auroral Boundary Model Using 28 Years Of Dmsp Data, Riley N. Troyer, Russell Landry, Michael David, Vincent Eccles, Adrian E. Acosta

Space Dynamics Laboratory Publications

This paper uses energy flux data from the DMSP F6 thru F19 satellites to construct a new equatorward auroral boundary model. This method of processing the data allows one to easily extend boundary detections to different instrument generations because it is based on a standard deviation value instead of hard thresholds. Using this method, the paper provides statistics from just under 1 million auroral boundaries between 1986 and 2014. These statistics are based on normal distribution fits for each Kp/Hp and MLT bin, which allows one to specify the boundary for an arbitrary distribution percentile. The paper compares …

Digital Health Intervention For Children With Adhd To Improve Mental Health Intervention, Patient Experiences, And Outcomes: A Study Protocol, Nancy Herrera, Franceli L. Cibrian, Lucas M. Silva, Jesus Armando Beltran, Sabrina E. B. Schuck, Gillian R. Hayes, Kimberley D. Lakes

Engineering Faculty Articles and Research

Background

Attention Deficit Hyperactivity Disorder (ADHD) is the most prevalent childhood psychiatric condition with profound public health, personal, and family consequences. ADHD requires comprehensive treatment; however, lack of communication and integration across multiple points of care is a substantial barrier to progress. Given the chronic and pervasive challenges associated with ADHD, innovative approaches are crucial. We developed the digital health intervention (DHI)—CoolTaCo [Cool Technology Assisting Co-regulation] to address these critical barriers. CoolTaCo uses Patient-Centered Digital Healthcare Technologies (PC-DHT) to promote co-regulation (child/parent), capture patient data, support efficient healthcare delivery, enhance patient engagement, and facilitate shared decision-making, thereby improving access to …

Active Grid Turbulence Anomalies Through The Lens Of Physics Informed Neural Networks, Sofía Angriman, Sarah E. Smith, Patricio Clark Di Leoni, Pablo J. Cobelli, Pablo D. Mininni, Martín Obligado

Mechanical and Materials Engineering Faculty Publications and Presentations

Active grids operated with random protocols are a standard way to generate large Reynolds number turbulence in wind and water tunnels. But anomalies in the decay and third-order scaling of active-grid turbulence have been reported. We combine Laser Doppler Velocimetry and hot-wire anemometry measurements in a wind tunnel, with machine learning techniques and numerical simulations, to gain further understanding on the reasons behind these anomalies. Numerical simulations that incorporate the statistical anomalies observed in the experimental velocity field near the active grid can reproduce the experimental anomalies observed later in the decay. The results indicate that anomalies in experiments near …

Synthetic Network Creation And Visualization, Kaylee Sloat, Jeremy Evert

Student Research

The code in the repository, “synthetic_network_creation_and_visualization” is inspired by the foundational work presented in "NetProbe: A Fast and Scalable System for Fraud Detection in Online Auction Networks" by Shashank Pandit, Duen Horng Chau, Samuel Wang, and Christos Faloutsos.

Link to the original paper:https://kilthub.cmu.edu...