Engineering Commons^™

Workforce Forecasting For State Transportation Agencies: A Machine Learning Approach, Adedolapo Ogungbire, Suman Mitra

Civil Engineering Faculty Publications and Presentations

A decline in the number of construction engineers and inspectors at state transportation agencies (STAs) to manage the ever-increasing lane miles has emphasized the importance of workforce planning in these agencies. Forecasting workforce requirements is crucial for effective planning in any industry or agency. This study developed machine learning (ML) models to estimate the person-hour requirements of STAs at the project level. The Arkansas Department of Transportation (ARDOT) was used as a case study, using its employee and project details data between 2012 and 2021. ML regression models ranging from linear, tree ensembles, kernel-based, and neural network-based models were …

Sdl Optomechanical Engineering Discussion, Tyrel Rupp

Space Dynamics Laboratory Publications

• About SDL
• SDL Manufacturing Capabilities
• Optomechanical Example-AWE
• Optomechanical Example – AWE Telescope Design
• Optomechanical Example – AWE Telescope Fabrication
• Optomechanical Example – AWE Optomechanical Assembly
• AWE Infrared Radiance of OH Layer Above Hurricane Helene
• Current Challenges in Optomechanics for SDL
• Precision Manufacturing IR&D (ongoing)
• Low CTE Moldable Composite IR&D: Athermal Design Background
• Low CTE Moldable Composite IR&D: Overview
• Low CTE Moldable Composite IR&D: Lens Tube Fabrication
• Low CTE Moldable Composite IR&D: Lens Tube Fabrication

Reconstruction From Variable Aperture Measurements Using Band-Limited Inversion Algorithms, Harrison C. Garrett

Theses and Dissertations

The signal reconstruction process from discrete samples is inherently band-limited due to the limited amount of spectral content in the discrete set of measurements. In the case of 1D sampling using ideal measurements, the maximum bandwidth of regular and irregular sampling is well known using Nyquist and Gröchenig sampling theorems and lemmas, respectively. However, determining the appropriate reconstruction bandwidth becomes difficult when considering 2D sampling geometries, samples with variable apertures, or signal to noise ratio limitations. Instead of determining the maximum bandwidth a priori, this thesis introduces the use of a bandlimited inverse to simultaneously reconstruct a signal and determine …

2024, A Landmark Year For Climate Change And Global Carbon Capture, Utilization, And Storage: Annual Progress Review, Shangli Shi, Yun Hang Hu

Michigan Tech Publications

This annual review outlines the progress of carbon capture, utilization, and storage (CCUS) technologies in 2024. As human-induced CO2 emissions continued to rise, the year presented critical challenges. Notably, 2024 was the hottest year on record and the first in which global temperatures exceeded preindustrial levels by more than 1.5°C, driving intensified efforts to advance CCUS. Scientific interest in CCUS grew significantly, with the annual number of related publications increasing by 11.4% compared to 2023, reaching 53,970. The total number of operational commercial CCUS facilities also expanded, rising by 16.3% to a total of 50. In the political area, governments …

Wind-Resilient Solar: Harnessing Cfd For Enhanced Load Estimation, Aly Mousaad Aly

Faculty Publications

Solar panels are a cornerstone of renewable energy infrastructure, playing a pivotal role in global sustainability efforts. To ensure their resilience and long-term viability, accurate wind load estimations are essential for designing supporting structures, which account for nearly 50% of their total cost. However, traditional building codes lack comprehensive guidance for solar panels, resulting in inconsistent estimations due to discrepancies in scaled wall-bounded wind tunnel testing methodologies. These inaccuracies pose safety risks, increase costs, and hinder adoption. Emerging technologies like computational fluid dynamics (CFD) simulations offer a promising alternative by enabling full-scale analysis under realistic conditions of complete turbulence. This …

Advancing Solar Farm Resilience: Cfd-Driven Wind Load Optimization, Aly Mousaad Aly

Faculty Publications

This study investigates wind load design methods for ground-mounted solar panels and arrays by comparing Computational Fluid Dynamics (CFD) simulations with design standards. A case study of a solar farm impacted by Hurricane Maria examines the effects of elevation height, tilt angle, and variations in the American Society of Civil Engineers (ASCE) standards on wind loads and structural failure. Turbulence models, including Reynolds Stress Model, k–ε Model, and Large Eddy Simulation (LES), are used to analyze wind pressures, lift, drag, and peak pressures. Results show Phase 1 experienced higher wind loads than Phase 2 due to design differences. A cost-benefit …

Improved Estimator For Population Mean Utilizing Known Medians Of Two Auxiliary Variables Under Neutrosophic Framework, Rajesh Singh, Shobh Nath Tiwari

Neutrosophic Systems with Applications

In the context of classical statistics, the estimation of the population mean is done with determinate, precise, and crisp data when auxiliary information is available. However, there are instances where dealing with uncertain, indeterminate, and imprecise data in interval form is required. To overcome this issue, Florentin Smarandache introduced neutrosophic statistics as a novel approach. This paper introduces a neutrosophic modified ratio-cum-product log-type estimator for the estimation of the population mean using known medians of two auxiliary variables in the neutrosophic context. The bias and mean squared error (MSE) for the proposed estimators are computed to the first-order approximation. The …

Some Graph Parameters For Superhypertree-Width And Neutrosophictree-Width, Takaaki Fujita, Florentin Smarandache

Neutrosophic Systems with Applications

Graph characteristics are often studied through various parameters, with ongoing research dedicated to exploring these aspects. Among these, graph width parameters—such as treewidth—are particularly important due to their practical applications in algorithms and real-world problems. A hypergraph generalizes traditional graph theory by abstracting and extending its concepts [77]. More recently, the concept of a SuperHyperGraph has been introduced as a further generalization of the hypergraph. Neutrosophic logic [133], a mathematical framework, extends classical and fuzzy logic by allowing the simultaneous consideration of truth, indeterminacy, and falsity within an interval. In this paper, we explore Superhypertree-width, Neutrosophic treewidth, and t-Neutrosophic tree-width.

Enhancing Smart City Management With Ai: Analyzing Key Criteria And Their Interrelationships Using Dematel Under Neutrosophic Numbers And Mabac For Optimal Development, Asmaa Elsayed, Mai Mohamed

Neutrosophic Systems with Applications

Purpose: This paper explores the transformative role of AI across various domains of smart cities, including urban mobility, energy management, public safety, healthcare, environmental monitoring, economic development, and data management. It aims to develop a novel decision-making framework that integrates AI technologies with a hybrid approach to analyze the interrelationships among smart city components.

Methodology: This paper employs a hybrid decision-making framework that combines the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method with single-valued trapezoidal neutrosophic numbers (STrNN). This approach is used to analyze the complex relationships among criteria and sub-criteria in smart city contexts, addressing uncertainty and incomplete information …

The Impact Of Visual Stimuli And The Properties Of Green Walls On Human Well-Being In Built And Immersive Virtual Environments, Alireza Sedghikhanshir

LSU Doctoral Dissertations

The built environment significantly influences human well-being, particularly in the context of stress recovery and cognitive restoration. This dissertation investigates the impact of visual stimuli, particularly green walls, on human responses related to stress, restoration, and thermal comfort. The research is guided by three primary objectives: (1) examining the role of visual stimuli and their properties in promoting stress recovery and restoration, (2) evaluating the potential of Immersive Virtual Environments (IVEs) as tools for delivering and studying restorative environments, and (3) investigating the influence of green walls on indoor environmental conditions.

A series of experimental studies were carried out to …

A Neutrosophic Micro Vague Correlation Measure: Application To Multi-Criteria Decision Making Problems, Vargees Vahini T, Trinita Pricilla M

Neutrosophic Systems with Applications

Statistical methods called correlation measures are employed to express the degree of association or relationship between two variables. The correlation coefficient which may be computed in a variety of ways is the most often used kind of correlation measure in many disciplines including biology, psychology, economics, and finance. Knowing the correlations between variables is essential for analysis and decision-making. This paper aims to commence a novel type of correlation measure called Neutrosophic Micro vague Correlation Measure and Neutrosophic Micro Vague Weighted Correlation Measure. Further demonstrates the implementation of the Neutrosophic Micro Vague correlation measure in the MCDM Problem. By adopting …

An Approach For Hybridizing N-Subalgebra With Quantified Neutrosophic Set Using G-Algebra, Neha Andaleeb Khalid, Muhammad Saeed

Neutrosophic Systems with Applications

Neutrosophic sets are a generalized form of fuzzy sets as well as intuitionistic fuzzy sets, as they address the uncertainty factor as an independent component along with truthfulness and falsity. However, traditional neutrosophic approaches often struggle with effectively managing and quantifying indeterminate elements in complex algebraic structures. To address this limitation, this paper employs an expanded version of the neutrosophic set, incorporating a subalgebra. The proposed research is multifaceted: firstly, the new concept of N-Subalgebra (NSU) is proposed. This is the modified setting in the family of subalgebras whose proposed name is the representation of the author's initial name. Secondly, …

Neutrosophic Automata And Its Algebraic Properties, Anil Kr. Ram, Anupam K. Singh

Neutrosophic Systems with Applications

This research endeavors to elucidate the interrelationships among various classes of operators, including neutrosophic successor/neutrosophic source/neutrosophic core operators of neutrosophic automata based on neutrosophic resituated lattices. Furthermore, it delves into the characterization of algebraic properties such as neutrosophic subsystem, neutrosophic connectivity, and neutrosophic separability of a neutrosophic automaton using these operators. Finally, we study the concepts of neutrosophic primaries of the given neutrosophic automata using neutrosophic core operators.

A Reconsideration Of Advanced Concepts In Neutrosophic Graphs: Smart, Zero Divisor, Layered, Weak, Semi, And Chemical Graphs, Takaaki Fujita, Florentin Smarandache

Neutrosophic Systems with Applications

One of the most powerful tools in graph theory is the classification of graphs into distinct classes based on shared properties or structural features. Over time, many graph classes have been introduced, each aimed at capturing specific behaviors or characteristics of a graph. Neutrosophic Set Theory, a method for handling uncertainty, extends fuzzy logic by incorporating degrees of truth, indeterminacy, and falsity. Building on this framework, Neutrosophic Graphs [9, 84, 135] have emerged as significant generalizations of fuzzy graphs. In this paper, we extend several classes of fuzzy graphs to Neutrosophic graphs and analyze their properties.

Mbj-Neutrosophic Structure Applied To Bp-Algebras: Bp-Subalgebras And Α-Ideals, Bavanari Satyanarayana, Shake Baji, Anjaneyulu Naik K.

Neutrosophic Systems with Applications

In this article, we introduce the concepts of MBJ-neutrosophic BP-subalgebras and MBJ-neutrosophic α-ideals in BP-algebra by applying MBJ-neutrosophic logic to algebraic structure BP-algebra. We prove that the intersection of two MBJ-neutrosophic α-ideals and the inverse image of an MBJ-neutrosophic α-ideal are also MBJ-neutrosophic α-ideals. Furthermore, we prove an MBJ-neutrosophic set is an MBJ-neutrosophic BP-subalgebra if and only if its level sets are BP-subalgebras.

Solving N-Players Continuous Differential Games Under Neutrosophic Environment, M. G. Brikaa

Neutrosophic Systems with Applications

Uncertainty plays a crucial role in decision-making problems, particularly in game theory. Various forms of uncertainty have been explored in the literature, including fuzzy, soft, rough, and interval-based approaches. Game theory has been extensively studied under these uncertainty models, with researchers addressing vagueness, and imprecision from multiple perspectives. More recently, neutrosophic sets have emerged as an alternative framework for handling uncertainty. Neutrosophic numbers effectively incorporate indeterminacy in decision-making by considering factors such as intuition, assumptions, judgment, behavior, evaluation, and preferences of decision-makers. This paper presents a novel approach to solving a new class of n-player continuous differential games within a …

Einstein Aggregate Operators Under Q-Rung Orthopair Fuzzy Hypersoft Sets With Machine Learning, Muhammad Gulistan, Muhammad Abid

Neutrosophic Systems with Applications

Thailand with its impressive 15.5% global share of renewable energy production, has a small 1% share of bitcoin mining. At the same time, the country is dealing with the severe effects of climate change, which emphasizes the necessity of taking proactive steps to solve environmental issues. This research integrates machine learning techniques and Einstein Aggregate Operators under q-rung orthopair fuzzy hypersoft set (q-ROFHS)-based multi-criteria decision-making technique to present a new method for analyzing CO₂ impacts and mitigation solutions in Thailand. We evaluate the environmental impacts of bitcoin mining and the incorporation of renewable energy sources using an interdisciplinary framework, …

Fabrication Of Ultra High-Temperature Compact Heat Exchanger By Extrusion-Based Ceramic Additive Manufacturing, Abid Hasan Rafi, David W. Lipke, Jeremy Lee Watts, Greg Hilmas, Ming-Chuan Leu

Miners Solving for Tomorrow Research Conference

No abstract provided.

Effects Of The Sintering Process On Additively Manufactured Copper Projectiles, Avery Lyons, William Petzoldt, Phillip R. Mulligan

Miners Solving for Tomorrow Research Conference

No abstract provided.

Cascaded Hydropower Plant Optimization Using A Bi-Level Mixed Integer Model, Ahmad Heidari, Rui Bo

Miners Solving for Tomorrow Research Conference

No abstract provided.

Physical Characterization Of Copper Anode Slimes, Carter Glynn, Michael S. Moats

Miners Solving for Tomorrow Research Conference

No abstract provided.

Multidisciplinary Design Optimization Of A Notional Cubesat Mission, Collin Gentry

Miners Solving for Tomorrow Research Conference

No abstract provided.

Development Of Intelligent Robot Assistance In Mining (Iram), Khosro Ghorbani Zadeh, Yun Seong Song

Miners Solving for Tomorrow Research Conference

No abstract provided.

Extreme Fast Charging Algorithm For Lithium-Ion Batteries With Precision Lithium Plating Regulation For Degradation Reduction, Kiernan O'Boyle, Yaqi Zhu, Jonghyun Park

Miners Solving for Tomorrow Research Conference

No abstract provided.

Sustainable Solutions To Eutrophication: The Role Of Glass Fertilizers, Lucas Greiner, Charmayne Lonergan

Miners Solving for Tomorrow Research Conference

No abstract provided.

Additive Manufacturing Of Thermoplastic Composites, Matik Heskin, K. Chandrashekhara, Richard Billo, Ming-Chuan Leu, Thomas P. Schuman

Miners Solving for Tomorrow Research Conference

No abstract provided.

Image-Based Stage Prediction Of Pressure Injuries Using Deep Learning, Mehedi Tusar, Fateme Fayyazbakhsh, Ming-Chuan Leu

Miners Solving for Tomorrow Research Conference

No abstract provided.

Neural Network-Based Renewal Reward Theory (Rrt) For Optimal Maintenance Scheduling, Samiksha Aryal, Abhijit Gosavi, Susan L. Murray

Miners Solving for Tomorrow Research Conference

No abstract provided.

Electrospun Rgo-Pan Filters For High-Performance Removal Of Respirable Silica And Coal Dust, Mahsa Moradi, Ashish Kakoria, Guang Xu

Miners Solving for Tomorrow Research Conference

No abstract provided.

Sources Of Tensions In Ai Adoption For Organ Procurement Organizations, Amaneh Babaee, Grace Hall, Daniel Burton Shank, Casey I. Canfield

Miners Solving for Tomorrow Research Conference

No abstract provided.