Digital Commons Network^™

Data-Driven Shear Capacity Prediction Of Studs Embedded In Uhpc For Steel-Uhpc Composite Structures, Yanping Zhu, Woubishet Zewdu Taffese, Genda Chen

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This study employs ensemble learning algorithms to accurately predict the shear capacity of studs embedded in ultrahigh performance concrete (UHPC), a critical aspect of structural engineering. Using a comprehensive data set featuring six UHPC slab features, seven stud features, and one shear pocket feature, 35 ensemble models are developed across five cases and seven algorithms (bagging, random forest, AdaBoost, gradient boosting, XGBoost, CatBoost, and LightGBM). The Shapley additive explanations (SHAP) analysis is conducted on the top-performing models to gain insights into their decision-making mechanisms. Results indicate that transforming UHPC slab geometry parameters into a volume, alongside different diameter ratios, proves …

Amorphous Sio2-Stabilized High-Valent Iron-Oxo Complexes Derived From Fe- And Si-Rich Solid Wastes For Efficient Tetracycline Hydrochloride Degradation, Cuirong Yan, Hongyan Ma, Xiunan Cai, Zhongqiu Luo, Jinyu Shi, Wenhao Li, Xintao Zhou

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

High-valent iron-oxo complexes show promise as green oxidants for water remediation but suffer from critical limitations in stability and pH adaptability. Herein, we report a facile method to synthesize amorphous SiO₂-stabilized high-valent iron-oxo complexes via Na⁺ diffusion activation of iron/silicon-rich copper smelting slag. In the complex, the synergistic coexistence of two distinct silica‑oxygen tetrahedral configurations-basic Na₂SiO₃ and acidic SiO2 oxides establishes a self-regulating pH buffering system that stabilizes solution neutrality. This unique structural design ensures sustained oxidative activity of the complex, representing a significant advancement over conventional silica-supported catalysts due to its intrinsic acid-base …

Guiding State-Specific Studies On Highway Disasters: Examining Differences In Postdisaster Funding, Mariam Elazhary, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The highway sector is frequently and severely impacted by natural disasters. To mitigate these effects and reduce the need for large relief budgets or emergency funds, it is crucial to study the resilience of the transportation network. As such, defining resilience in absolute terms is not enough; instead, it is equally important to analyze specific case studies and build a lessons-learned rapport. This is critical because it helps identify unique vulnerabilities and strengths that might be overlooked in broader analyses. However, current research on highway resilience often lacks empirical evidence to support the selection of these unique and significant case …

Temporal Evolution Of Workforce Fatality-Linked Factors In The Transportation Construction Sector, Mariam Elazhary, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Despite advancements in safety measures, fatalities in the transportation sector remain disproportionately higher than in other industries. Transportation sector fatalities arise from a combination of demographic, environmental, and occupational factors that amplify the overall risk. While strides have been made in understanding the factors contributing to fatalities, there remains a critical gap in research focused on their temporal evolution. The goal of this study is to investigate the temporal evolution of fatality-linked association factors in the transportation construction sector. The methodology encompassed three stages. Stage 1 was preprocessing the data: the US Census of Fatal Occupational Injuries, covering 3,792 fatality …

Price Adjustment Clauses: Enhanced Price Volatility Forecasting For Construction Materials, Ahmed Shiha, Mariam Elazhary, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Price adjustment clauses (PACs) are used by state departments of transportation (DOTs) to share the risk of material price fluctuations. Existing models that depict the price fluctuations of materials forecast a mean within a horizon while relying on the assumption of a constant volatility throughout that horizon. However, none of them examine whether the prices of construction material exhibit similar volatility following a sudden price surge or a price drop. The prospect of PACs and their associated trigger values is hindered in the absence of empirical assessments of their capacity to capture the volatilities in material prices. This paper fills …

Labor Productivity Losses Across Construction Trades: A Machine Learning Approach, Tamima Elbashbishy, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Labor productivity is a major concern in the construction industry. Existing research on construction labor productivity (CLP) within specific trades has produced inconsistent findings due to differences in the factors analyzed. This lack of consistency makes it difficult to identify the most critical drivers of productivity losses across trades. To address this gap, this study adopts a cross-trade analytical approach to systematically identify and evaluate the inefficiencies impacting labor productivity in multiple construction trades. Specifically, the study (1) identified common organizational and project-level inefficiencies that influence labor performance; (2) conducted an expert-based survey to measure the frequency and perceived impact …

Risk Allocation Model For Price Escalations In Construction Projects: Integrating Bargaining Game Theory And Probabilistic Bayesian Modeling, Yasser Jezzini, Rayan H. Assaad, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Economic market uncertainties, like those witnessed during pandemics and supply chain-related challenges, introduce complexity in ascertaining precise price estimates for construction materials. Despite some studies on risk allocation in construction projects utilizing quantitative and qualitative approaches, these studies fail to explain the underlying process of risk allocation due to a lack of theoretical support, indicating a need for a more structured and theoretically grounded approach to understanding risk allocation, specifically under volatile market conditions. To bridge this knowledge gap, this study proposes a novel game-theoretical model integrating Bayesian statistics and bargaining game theory dynamics, offering a robust framework for optimal …

Failure Analysis Of Prestressed Concrete Girder Bridges Under Over-Height Truck Impacts, Mohamed T. Elshazli, Mohamed Elgawady, Tao Xing, Ahmed Ibrahim

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Accidental collisions between over-height trucks and bridge superstructures are a common threat to existing bridge infrastructure. These incidents often stem from illegal over-height vehicles or truck operators' unawareness of clearance limits, posing serious safety risks and causing substantial structural damage. This study presents a comprehensive numerical investigation of the dynamic response of prestressed concrete girder bridges subjected to over-height truck impacts. Large-scale finite element models were developed in LS-DYNA, with validation conducted against experimental results. The parametric study explored impact speeds ranging from 16 to 113 km/h (10 to 70 mph), impactor masses between 2 and 6 tons, impact locations, …

Epa Region 8 Optimized Ufp-Qapp Review Crosswalk, Environmental Protection Agency, Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

In Situ High-Temperature Raman Spectroscopy For Online Eaf Slag Analysis, Bohong Zhang, Hanok Tekle, Ronald J. O'Malley, Jeffrey D. Smith, Farhan Mumtaz, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Real-time monitoring of slag chemistry is critical for optimizing Electric Arc Furnace (EAF) steelmaking operations, where dynamic variations in slag composition directly influence slag foaming, refractory degradation, and thermal efficiency. Conventional techniques such as X-ray fluorescence (XRF), Fourier-transform infrared (FTIR), and scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM-EDS) are commonly used to analyze slag composition, but their offline nature and equipment constraints limit their applicability for online monitoring in harsh industrial environments. To address this challenge, we present an in situ, high-temperature analytical approach that integrates Raman spectroscopy with a custom-designed fiber-optic probe for real-time slag characterization at …

Rsif Benin Country Report 2025 - English, Regional Scholarship And Innovation Fund (Rsif)

Rsif Country Progress Reports

Benin is among the world’s fastest growing economies. Highly skilled human capital will boost this growth rate and drive implementation of Benin’s National Development Plan. Benin is one of the nine African countries that is contributing to the Regional Scholarship and Innovation Fund (Rsif) of the Partnership for skills in Applied Sciences, Engineering and Technology (PASET) since 2021. Its contribution is USD 2 million to train Beninese PhD students in selected African host universities and collaborating with international partner institutions. Through PASET-Rsif Benin will build strong institutions and future science leaders to drive a science and technology-led growth and development. …

Rsif Mozambique Country Report 2025 - English, Regional Scholarship And Innovation Fund (Rsif)

Rsif Country Progress Reports

With its abundant natural resources, including arable land, water, energy and mineral resources, Mozambique has potential to diversify its economy. It’s strategic location as a logistics corridor in the Southern Africa region is another natural advantage. Mozambique is paying great attention to higher education, science and innovation to increase the proportion of scientifically skilled workforce that is necessary to sustain and increase growth opportunities.

Mozambique is one of the nine African countries that is contributing to the Regional Scholarship and Innovation Fund (Rsif) of the Partnership for skills in Applied Sciences, Engineering and Technology (PASET), since 2021. Its contribution of …

Acoustic Emission Sensing For Assessing Compressive Strain In Impacted Thermoplastic Composites, M. M. Shahzamanian, Li Ai, Sydney Houck, Md Mushfiqur Rahman Fahim, Sourav Banerjee, Paul Ziehl

Civil Engineering Faculty Publications

Composite materials used in aircraft during in-flight service are vulnerable to impacts, which can lead to undetected damage and deterioration. Impact incidents can cause considerable structural harm that might not be immediately apparent, resulting in a decline in the mechanical properties of material and overall performance. There are currently limited advanced models capable of assessing the state of compressive strain (or stress) in a compression after impact (CAI) test based on acoustic emission (AE) data. Developing such a model may enable real-time monitoring and evaluation during in-flight service, providing users with alerts when composite material failure is approaching. This paper …

The Application Of Vetiver Grass In Natural Disaster Mitigation And Environmental Protection In Vietnam: A Bibliometric Analysis And Literature Review, Truc Phan, Tan Nguyen, Thang Pham, Bich T. Luong, Huong Nguyen

Civil Engineering Faculty Publications

Vetiver grass (Vetiveria zizanioides or Chrysopogon zizanioides) is a versatile tropical plant widely recognized for its applications in environmental protection and natural disaster mitigation. In Vietnam, where natural disasters such as floods and landslides are frequent, particularly along highways, Vetiver grass has proven to be an effective bioengineering solution. This paper provides a comprehensive review of the applications and benefits of Vetiver grass in preventing soil erosion and stabilizing slopes along Vietnam’s transportation systems. A bibliometric analysis of 555 Scopus-indexed publications (2000 – 2024) was conducted using VOSviewer software to identify research trends, key themes, and knowledge gaps. The findings …

Static Analysis As A Feedback Loop: Enhancing Llm-Generated Code Beyond Correctness, Scott Blyth, Sherlock Licorish, Christoph Treude, Markus Wagner

Research Collection School Of Computing and Information Systems

Large language models (LLMs) have demonstrated impressive capabilities in code generation, achieving high scores on benchmarks such as HumanEval and MBPP. However, these benchmarks primarily assess functional correctness and neglect broader dimensions of code quality, including security, reliability, readability, and maintainability. In this work, we systematically evaluate the ability of LLMs to generate high-quality code across multiple dimensions using the PythonSecurityEval benchmark. We introduce an iterative static analysis-driven prompting algorithm that leverages Bandit and Pylint to identify and resolve code quality issues. Our experiments with GPT-4o show substantial improvements: security issues reduced from >40% to 13%, readability violations from >80% …

Coupling Category Alignment For Graph Domain Adaptation, Nan Yin, Xiao Teng, Zhiguang Cao, Mengzhu Wang

Research Collection School Of Computing and Information Systems

Graph domain adaptation (GDA), which transfers knowledge from a labeled source domain to an unlabeled target graph domain, attracts considerable attention in numerous fields. However, existing methods commonly employ message-passing neural networks (MPNNs) to learn domain-invariant representations by aligning the entire domain distribution, inadvertently neglecting category-level distribution alignment and potentially causing category confusion. To address the problem, we propose an effective framework named Coupling Category Alignment (CoCA) for GDA, which effectively addresses the category alignment issue with theoretical guarantees. CoCA incorporates a graph convolutional network branch and a graph kernel network branch, which explore graph topology in implicit and explicit …

Identification Of Flow Regime In A Co-Current Upflow Packed Bed Reactor (U-Pbr) Using Gamma-Ray Densitometry (Grd), Youssef Yatimi, Ahmed Alalou, Muthanna H. Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

Owing to their significant impact on the reaction rate, the comprehensive understanding of the hydrodynamics in any novel design of the Upflow Packed Bed Reactor (U-PBR) is essential for the optimization of its throughput. In this regard, the identification of the flow regime is of paramount importance. Therefore, in this work, we use the photon counts time-series data obtained using the non-invasive Gamma-ray densitometry (GRD) to identify, for the first time, the flow regimes and their transition velocities at two axial locations (Z/D=0.8,1.56) and five radial locations (r/R=0,±0.5,±0.9) within the packed catalysts' bed of U-PBR with a novel plenum design …

Full Issue, Volume 20, Issue 3

Journal of Youth Development

No abstract provided.

Democratizing Community Discourse Analysis In Computational Social Science, Md Towhidul Absar Chowdhury

Theses

Community resource inequities and undetected infrastructure vulnerabilities cost municipalities billions annually, with disproportionate impacts on marginalized communities. Current computational approaches to community needs assessment suffer from two critical limitations: they rely on aggregate-level analysis that obscures granular community expressions, and they implement sophisticated computational tools that remain inaccessible to stakeholders without technical expertise. This creates what we term the Community-Computational Gap—a persistent divide where domain experts with vital contextual knowledge cannot access the analytical tools they need, while computational experts develop models without sufficient community context. This dissertation addresses these challenges through a novel methodological framework for fine-grained utterance-level classification …

Understanding The Relationship Between Structural Failure And Fatalities In Tornadoes: A Quantitative Investigation Of The 2021 Midwest Tornado Outbreak, Yi Zhao, Ruwen Qin, John W. Van De Lindt, Justin Sharpe, Grace Yan

Engineering Management and Systems Engineering Faculty Research & Creative Works

During 1950-2011, the number of fatalities caused by tornadoes in the U.S. significantly exceeded the fatalities caused by both hurricanes and earthquakes. To reduce tornado induced fatalities, it is essential to understand how structures/building failures correlate with fatalities and who are more vulnerable to tornadoes. Insights from this study are intended to help provide information to decision-makers on where to allocate limited resources for enhancing tornado resilience. By examining both the fatality data and structural damage data in the 2021 Midwest Tornado Outbreak, the objective of this study is to examine the occurrence of fatalities during tornadoes across various types …

Machine Learning-Based Electric Vehicle Charging Demand Forecasting: A Systematized Literature Review, Maher Alaraj, Mohammed Radi, Elaf Alsisi, Munir Majdalawieh, Mohamed Darwish

All Works

The transport sector significantly contributes to global greenhouse gas emissions, making electromobility crucial in the race toward the United Nations Sustainable Development Goals. In recent years, the increasing competition among manufacturers, the development of cheaper batteries, the ongoing policy support, and people’s greater environmental awareness have consistently increased electric vehicles (EVs) adoption. Nevertheless, EVs charging needs—highly influenced by EV drivers’ behavior uncertainty—challenge their integration into the power grid on a massive scale, leading to potential issues, such as overloading and grid instability. Smart charging strategies can mitigate these adverse effects by using information and communication technologies to optimize EV charging …

Diffusion Mri Biomarkers For Predicting Treatment Outcomes In Infantile Epileptic Spasms Syndrome With Non-Lesional Mri, Daniel Ackom, Scott A. Beardsley, Jennifer Meylor, Kayleigh Butler, Ricardo Vega, Andrew J.D. Crow, Hema Patel, Brian D. Schmit, Pradeep Javarayee

Biomedical Engineering Faculty Research and Publications

Background

Infantile epileptic spasms syndrome (IESS) is a devastating developmental epileptic encephalopathy (DEE) and patients exhibit diffuse white matter alterations and structural remodeling. However, the correlation between these structural changes and brain network properties, or their effect on the efficacy of treatment outcomes in MRI non-lesional IESS patients is not clear.

Method

This retrospective study was conducted on IESS patients using fixel-based analysis (FBA) of diffusion MRI and graph theory analysis of structural connectivity, involving 26 non-lesional IESS patients aged 2 to 12 months and 120 age-matched controls. We further examined the differences between antiseizure medication (ASM) responders and non-responders …

Lung Injury Risk Curves From Behind Armor Blunt Trauma Using A Live Swine Model, Narayan Yoganandan, Lewis Somberg, Danielle Wilson, Alok Shah, Jared Michael Koser, Brian D. Stemper, Valeta Carol Chancey, Joseph Mcentire

Biomedical Engineering Faculty Research and Publications

Introduction

From structural, anatomical, and functional perspectives, components of the thoracoabdominal region are heterogeneous and physiologically and functionally different. Although their tolerances to injury are expected to be different, the current Roma Plastilina No. 1 clay penetration criterion for behind armor blunt trauma (BABT) is not specific to the body region. It is important to develop regional injury criteria to ensure its specificity. The objective of the study is to conduct impact tests on the lung region using a live animal model and develop injury risk curves using velocity and deflection metrics via parametric survival analysis.

Materials and Methods

Live …

Experimental Study Of Dehydration Performance Of Re-Crosslinkable Preformed Particle Gel During Extruding Through An Open Fracture, Shu Da Zhao, Baojun Bai, Thomas P. Schuman

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Re-cross linkable preformed particle gel (RPPG) has been considered to be one of the most promising gels for dealing with fracture and void space conduit (VSC) conformance problems. However, the dehydration of RPPG during its propagation in the fracture-type features and its effect on gel properties remains unclear. This paper investigates the dehydration behavior during RPPG propagating in an open fracture using matrix-free fracture model. Then the results were verified using real fractured sandstone core model. Moreover, the gel properties after extruding a fracture were studied in detail including gel dehydration and gel strength. Results reveal that the RPPG properties …

Predicting Groundwater Withdrawals Using Machine Learning With Limited Metering Data: Assessment Of Training Data Requirements, Dawit Asfaw, Ryan G. Smith, Sayantan Majumdar, Katherine Grote, Bin Fang, B. B. Wilson, V. Lakshmi, J. J. Butler

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

The future of major aquifer systems supporting irrigated agriculture is threatened due to unsustainable groundwater pumping. Metering of pumping is key for implementing robust groundwater management, but metering is limited in most aquifers. Although machine learning methods have been used to estimate pumping over certain regions, these studies have not fully demonstrated the data quantity and input parameter requirements to accurately estimate regional groundwater pumping. This study determined the data quantity required and identified relevant features to develop Random Forests-based annual groundwater pumping estimates (2008–2020) over the Kansas High Plains aquifer. We predicted pumping at two spatial scales, i.e., point …

Rsif Nigeria Country Report 2025, Regional Scholarship And Innovation Fund (Rsif)

Rsif Country Progress Reports

Nigeria is Africa’s biggest economy. Investment in higher education and research can be a catalyst for positive change and innovation. Moreover, Nigeria’s participation in Rsif is advancing a Pan-African approach, internationalization and intra-Africa mobility. Nigeria is one of the nine African countries that is contributing to the Regional Scholarship and Innovation Fund (Rsif) of the Partnership for skills in Applied Sciences, Engineering and Technology (PASET) since 2022. Its contribution of USD 4 million is through the World Bank supported Africa Centres of Excellence for Higher Education for Development Impact (ACE Impact) project, to train Nigerian PhD students in selected African …

Rsif Uganda Country Report 2025, Regional Scholarship And Innovation Fund (Rsif)

Rsif Country Progress Reports

Uganda’s GDP grew by an estimated 6.3% in 2024 driven by strong growth in all sectors, including agriculture and services. Investment in higher education would contribute to more productive employment and uptake of digital and other innovative technologies. Revenue from crude oil could be channeled into green technologies. Uganda’s green metals and iron-ore deposits could be developed using technologies for greening manufacturing and construction to provide the basis for transforming to a green economy. Uganda is one of eleven African countries that are active in the Partnership for skills in Applied Sciences, Engineering and Technology (PASET), and has expressed its …

Rsif Kenya Country Report 2025, Regional Scholarship And Innovation Fund (Rsif)

Rsif Country Progress Reports

Kenya is the leading economy in East Africa. World Bank projects average GDP growth of 4.9% from 2025-27. Kenya pursues its Vision 2030 and a bottom-up economic model, which prioritizes agriculture, healthcare, affordable housing, micro and small enterprises, and the digital and creative economy. Consistent investment in human capital and higher education is paving the way for a skilled labour force that is contributing to sustainable inclusive growth, job creation and socio-economic transformation. Kenya is one of the nine African countries that is contributing to the Regional Scholarship and Innovation Fund (Rsif) of the Partnership for skills in Applied Sciences, …

Rsif Senegal Country Report 2025, Regional Scholarship And Innovation Fund (Rsif)

Rsif Country Progress Reports

Senegal’s economy is expected to be among the fastest growing in the world, with 10.3% real GDP growth expected in 2025 and 7.1% in 2026 according to the African Development Bank. Highly qualified human capital is the driver for implementation of the Senegal 2050 National Transformation Agenda. Senegal is one of the nine African countries that is contributing to the Regional Scholarship and Innovation Fund (Rsif) of the Partnership for skills in Applied Sciences, Engineering and Technology (PASET) since 2020. Its contribution of USD 2 million is financed through the World Bank supported Africa Centres of Excellence for Higher Education …

Rsif Rwanda Country Report 2025, Regional Scholarship And Innovation Fund (Rsif)

Rsif Country Progress Reports

Rwanda is among the world’s fastest growing economies. GDP growth is expected to maintain momentum at more than 8% in 2025–26, thanks to a recovery in global tourism, new construction projects, and manufacturing activities. The need for highly skilled human capital is a driver for Rwanda’s Vision 2050. Investing in higher education, research and innovation will enable Rwanda to close the skills gap and contribute to sustainable economic growth and development. Rwanda is one of the nine African countries that are contributing to the Regional Scholarship and Innovation Fund (Rsif) of the Partnership for skills in Applied Sciences, Engineering and …