Computational Engineering Commons^™

Rejection Of Fe (Iron) And Kmno4 (Organic Substance) Parameters In Peat Water Using Organic Membranes, Muhamad Rafli Sakti Mulia Gonera, Siti Umi Kalsum, Sarah Fiebrina Heraningsih

Journal of Materials Exploration and Findings

Peat water is a surface water source widely used by people in swampy and lowland areas, but it has poor quality characteristics such as high organic matter content, low pH, and dissolved metal levels such as iron that exceed the threshold. These conditions can cause health problems and reduce the quality of clean water so that effective treatment technology is needed. This study aims to analyze the effectiveness of ultrafiltration membranes made from chitosan from shrimp shell waste in rejecting iron (Fe) and organic substances in peat water, and to determine the effect of pressure on separation performance. This study …

Ensemble Learning Framework For Predicting Close Proximity Tire–Pavement Noise On Expressways, Woo Young Cho, Jin Hwan Kim, Guk Gon Song, Kyungnam Kim, Youngguk Seo

Faculty Articles

Traffic noise is a critical public health concern affecting millions of highway users and adjacent residents worldwide. In response, many transportation agencies have adopted functional surface materials to reduce noise at the source on pavement, but assessing their effectiveness remains expensive and logistically challenging. Close Proximity (CPX) testing quantifies tire-pavement noise but requires specialized equipment costing $50,000-$126,000 and is limited to existing pavement, preventing proactive noise assessment during pavement design. This study develops machine learning models to predict CPX noise levels from readily available pavement characteristics, eliminating the need for costly tests during design and planning phases. To train and …

Assessing Passenger Electric Vehicle Growth Strategies And Their Impacts On Electricity Demand Load And Co2 Emissions In Aceh Province To Achieve Net Zero Emission Target By 2060, Taufik Hidayat, Widodo Wahyu Purwanto

Journal of Materials Exploration and Findings

The electrification of the transport sector is a crucial pathway for achieving Indonesia’s Net Zero Emissions (NZE) target by 2060. This study assesses the potential impact of passenger electric vehicle (EV) penetration on electricity demand and CO2 emissions in Aceh Province through a scenario-based modelling approach. Two policy-aligned scenarios are assessed: a low-penetration (LP) scenario and a high-penetration (HP) scenario. Using the Gompertz model and the ASIF framework, total CO2 emissions were projected from 2020 to 2060. Results show that although higher EV penetration reduces direct emissions from internal combustion engine (ICE) vehicles, total CO2 emissions increase more significantly under …

A Novel Federated Llm Framework For Distributed Traffic Modelling In Intelligent Transportation Systems, Seerat Kaur

Theses and Dissertations (Comprehensive)

Intelligent transportation systems (ITS) depend on accurate traffic prediction to support congestion management, infrastructure planning, and real-time operational decisions. Despite substantial progress in data-driven forecasting, several challenges continue to limit practical deployment: traffic data is distributed across independent regional authorities, making centralized aggregation infeasible, standard federated aggregation strategies ignore traffic-specific characteristics that meaningfully affect model quality, and existing models produce only numerical outputs without interpretable reasoning that urban planners can act upon. This thesis addresses these challenges through four contributions that collectively advance privacy-preserving, explainable, and scalable traffic forecasting.

The first contribution provides a systematic review of 129 peer-reviewed publications, …

Morphological Test Of Areca Nut Fiber Ceramic Membrane Using Scanning Electron Microscopy Energy Dispersive X-Ray Mapping Spectroscopy, Amelia Marzain, Siti Umi Kalsum, Marhadi Marhadi, Ahmad Nabil Shahab

Journal of Materials Exploration and Findings

This study investigates the potential of ceramic membranes derived from areca nut fiber as a cost-effective and environmentally sustainable material for the removal of iron (Fe) and manganese (Mn) from groundwater. Two types of membranes were fabricated: one without activation and one chemically activated using 10% sodium hydroxide (NaOH). The morphological and elemental characteristics of both membranes were analyzed using Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray (EDX) mapping. The concentrations of Fe and Mn before and after treatment were measured using Atomic Absorption Spectroscopy (AAS). The NaOH-activated membrane exhibited a more porous surface structure and higher oxygen content, …

Modeling Disaster Resilience Through A Human-Centered Lens: Exposure, Vulnerability And Adaptation, Tong Liu

All Dissertations

The core of reframing and operationalizing disaster resilience with a human-centered lens is to incorporate concepts from socio-ecological resilience into engineering resilience to better understand the humans’ capability for disaster adaptation. Existing studies have drawn practical implications by identifying actionable thresholds for infrastructure systems under disasters, which can be easily applied by policymakers, emergency managers and municipal agencies. However, how individuals interact with, respond to, or adapt under these infrastructure thresholds remain understudied. This hinders the operationalization of disaster resilience at the human scale.

First, I examined exposure by analyzing how configuration and distribution of urban infrastructure systems, such as …

Multi-Parameter Optimization Of Brine Desalination Using Machine Learning, Elaf Mman Seif

Theses and Dissertations

Air Gap Membrane Distillation (AGMD) is a promising desalination technology with significant potential for addressing global water scarcity. However, the interplay of operational parameters significantly impacts its performance, making optimization a challenging task. This research focuses on brine desalination as a means to mitigate the negative environmental impacts of brine disposal which will eventually help in provide a sustainable solution for handling brine while producing freshwater. The study seeks to develop a predictive model and optimize the AGMD process for efficient brine desalination. To achieve this, Response Surface Methodology (RSM) and Artificial Neural Networks (ANNs) were utilized to develop predictive …

False Information Attack Detection In A Connected Vehicle Environment With Quantum Inspired Long Short-Term Memory, Jean Michel M. Tine

All Theses

Wireless communication Systems enabling Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) data exchange, supported by technologies such as Cellular-V2X (C-V2X), has introduced significant cybersecurity challenges, particularly the threat of false information attacks that can compromise traffic safety and efficiency. In this thesis, the author focuses on identifying false information cyber-attack on V2I, in which vehicles are sending Basic Safety Messages (BSMs) to a Roadside Unit (RSU) and RSUs are collecting, processing and communicating data back to Connected Vehicles (CVs) to support different CV applications. Despite advances in anomaly detection using Long Short-Term Memory (LSTM) networks, these models often struggle with computational efficiency …

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 …

Investigating The Discrepancies Between Acoustic And Radar Measurements Of Water Level Using Data Analysis And Computational Modeling, Ohiedul Haque Mohammad Asad

Civil & Environmental Engineering Theses & Dissertations

Observations indicate that there is a discrepancy between water level measurements from NOAA’s acoustic gauges and radar gauges. NOAA’s acoustic gauges use a downward-looking acoustic sensor that measures the instantaneous distance from the sensor to the water level. To create a calm water surface for measurements, the sensor is placed in a PVC tube that penetrates the water surface to a certain depth. This tube is called the stilling well. In this thesis, discrepancies in water level measurements from acoustic and radar sensors were explored through data analysis and computational modeling. Specifically, the correlations between the error, which is defined …

Modelled Flooding Impacts On Lower Fish River Watershed, Sebastian Loschner

Shelby Hall Graduate Research Forum Posters

This study investigates the impacts of compound flooding in the Lower Fish River watershed, Baldwin County, Alabama, with a focus on the potential effects of sea level rise due to climate change. Coastal flooding, particularly in smaller watersheds, is a growing concern as it results from the interaction of multiple factors, including rainfall, tidal changes, and extreme weather events. Compound flooding, which involves multiple flood drivers, is expected to worsen with climate change, as increased precipitation and rising sea levels create heightened flood risks. However, existing research on compound flooding predominantly focuses on large-scale watersheds, leaving a knowledge gap in …

Assessing Water Quantity And Quality In The Mississippi River Valley Alluvial Aquifer And Coastal Louisiana Through Integrated Airborne Electromagnetic And Borehole Data, Michael George Henin Attia Khalil

LSU Doctoral Dissertations

Numerical modeling has contributed significantly to the understanding of groundwater systems. Many challenges are associated with constructing groundwater models which include an accurate understanding of the geology and aquifer parameters estimation. Traditionally boreholes are a successful way to capture geological features, however, boreholes often have sparse data. Airborne electromagnetic (AEM) data allows for efficient and cost-effective surveying of large areas, providing valuable information about the subsurface electrical resistivity. By bridging the gap between boreholes, AEM data offers a broader view of the aquifer system's structure and heterogeneity. However, interpreting geophysical AEM data has uncertainties. Developing a framework to apply the …

Optimization Of The Cross-Section Of Generic Flexible Bridges, Manal Kamal Zaki, Mina M. Helmy, Mark M. Tawadros

Journal of Engineering Research

This paper investigates the behavior of flexible bridges prone to aerodynamic instabilities due to wind. Optimal cross-sections that reduce aerodynamic forces are recommended. This is achieved by studying a variety of bridge sections with different widths of upper and lower sloping edges in addition to studying the upper and lower cramps of the deck. The wind velocities are also parameterized. Computations are developed based on the powerful computational fluid dynamics (CFD) method known as FLUENT and embedded in ANSYS software. For parametric study, a design of experiments (DOE) is performed based on the response surface methodology (RSM) combined with the …

Cognitive Map Generation For Vision And Language Navigation, Alexander Sandoval Mesa

Dissertations and Theses

Visual-Language Navigation (VLN) presents significant challenges for autonomous agents, such as robots and virtual assistants, particularly in complex, dynamic environments where the seamless integration of visual perception and natural language understanding is critical. Traditional VLN systems often struggle with effectively aligning language instructions and visual scene understanding, limiting their adaptability and navigation efficiency.

This thesis proposes a novel Cognitive Map-based framework that addresses these challenges by transforming natural language navigation instructions into structured graph representations. The Cognitive Map consists of nodes representing waypoints, landmarks, decision points, and edges encoding spatial relationships and navigational actions. These maps are generated using Large …

The Impact Of Skew On The Flexural Behavior Of Press-Brake-Formed Tub Girders, Matthew Allan Weatherholt

Graduate Theses, Dissertations, and Problem Reports (ETD)

The Short Span Steel Bridge Alliance (SSSBA) is a group of bridge and buried soil steel structure industry leaders who have joined together to provide educational information on the design and construction of short span steel bridges in installations up to 140 feet in length. Press-brake-formed-tub-girders (PBFTGs) were developed by a technical working group within the SSSBA in response to a rising demand for rapid infrastructure replacements for short span bridge applications. PBFTGs are produced from structural steel plate and can be finished as weathering steel or galvanized. After being cold bent to the appropriate shape, shear studs are welded …

Collision Hazard Prevention And Notification For Construction Worker Safety Using Audio Surveillance, Kehinde Elelu

All Dissertations

The construction industry faces significant safety challenges, with collision hazards ranking as the second highest cause of annual fatalities and injuries in the United States, as reported by the Occupational Safety and Health Administration (OSHA). Current collision detection methods predominantly rely on proximity technologies, which necessitate costly and complex installations on each construction equipment piece. Furthermore, auditory situational awareness declines among workers due to hearing loss and intricate construction noises, which further heightens collision risks. This research introduces an innovative, low-cost, audio-based collision prevention technology aimed at enhancing auditory situational awareness for construction workers exposed to high noise levels. The …

Sustainable And User-Driven Scope Development Framework For Engineering Design Services Of Transportation Infrastructure Projects, Ahmad Zaki Ghafari

All Dissertations

Rapid economic growth has led to a significant increase in transportation demands, exerting unprecedented pressure on infrastructure systems in the United States. State transportation agencies play a vital role in maintaining and developing transportation infrastructure networks within their regions. State transportation agencies face immense pressure from federal and state governments, elected officials, and the public to deliver projects efficiently and within budget. State transportation agencies rely on professional consultants for engineering design services. Engineering design services for transportation infrastructure projects are delayed due to incomplete inaccurate scope. For state Department of Transportation (DOTs), a streamlined scope development process is essential …

Development Of Machine Learning-Based Tool For Prediction Of Long-Term Field Performance Of Asphalt Concrete Overlays In A Hot And Humid Climate, Elise Mansour

LSU Doctoral Dissertations

The performance of pavement plays a critical role in Maintenance, Rehabilitation and Reconstruction (MR&R) for highway agencies. Reliable and accurate estimation of pavement performance can be instrumental in prioritization of the limited resources and funding for highway agencies. The latter requires robust prediction models that can handle large-scale, real-world data and can forecast pavement performance in the long run. Unfortunately, the traditional performance prediction models have raised concerns regarding their efficiency and accuracy. It is because these models were based on a limited number of explanatory variables, were not up-to-date and were designed for forecasting short-term (up to five years) …

Development Of A Rule-Based Monitoring System For Autonomous Heavy Equipment Safety, Amirpooya Shirazi

Department of Construction Engineering and Management: Dissertations, Theses, and Student Research

Roadway construction work zones are constantly exposed to interactions among construction equipment, workers, and vehicles. Furthermore, ensuring safety in these areas is considered a challenging task due to the complexity of the environment. As shown in the rising trend of fatal accidents in roadway work zones, current OSHA regulations in construction safety are insufficient in effectively detecting unsafe situations and mitigating the risks. Furthermore, best practices, such as internal traffic control planning (ITCP), exhibit critical limitations requiring continuous monitoring of active work zones as well as adjustments to the site coordination plans due to the dynamic nature of work zone …

Examining The Impact Of Customer Rfp Characteristics On Award Compliance, Laasya Ravipati

Data Science Undergraduate Honors Theses

In the context of intermodal transportation, understanding the dynamics of award compliance holds significant importance for operational efficiency and strategic decision-making. Award compliance refers to the percentage of awarded freight volume that is realized, indicating the extent to which contractual agreements are fulfilled. This analysis delves into the intricate relationship between customer characteristics and award compliance, aiming to provide valuable insights into the variability and predictability of compliance rates. By analyzing Request for Pricing (RFP) data and primary awarded freight volumes, the study seeks to address the need for more accurate volume estimations, crucial for sales planning, revenue projections, and …

Quantifying Hurricane Effects On Housing: Evaluating Damage, Loss, And Shelter Demands Using Historical And Simulated Storm Tracks, Adish Deep Shakya

All Theses

This research introduces an advanced framework which employs parametric wind field models for peak wind speeds, and building fragility curves, loss functions, and demographic data to estimate for estimating housing damage and loss. The uninhabitable units immediate displaced households, short-term and long-term shelter need households are determined. with a particular focus on those eligible for FEMA assistance. The framework's validity is reinforced by a high correlation in the analysis of recent hurricane events between estimated numbers of displaced households and actual FEMA aid recipients, where FEMA aids about 20-60% of the predicted long-term displaced households. A novel application of the …

A 4-Node Shell Finite Element Based On Assumed Bending And Membrane Strains For Static Analysis Of Plates And Shells, Sifeddine Abderrahmani

Emirates Journal for Engineering Research

In this paper the development of a new rectangular flat shell element is proposed. This element is called SBRPK-SBRIE. This element is used in the numerical analysis of thin structures based on the strain approach with linear elastic behavior. Combining bending and membrane elements yields the proposed element.The strain-based rectangular finite element for the thin plate bending element denoted SBRPK, and the strain-based membrane element denoted SBRIE. Several numerical examples have been conducted to assess the accuracy and reliability of the developed element compared with the theoretical results and other finite elements. Obtained results show its good performance compared to …

Streamlining Public Engagement In Transportation Projects Using Text Analytics, Alireza Shamshiri

Civil Engineering Dissertations - Archive

Infrastructure projects impact a broad range of stakeholders, particularly local communities, whose engagement is critical for successful outcomes. Despite the importance of public engagement in these projects, traditional methods of capturing and analyzing public opinion often fail to fully represent the diverse, genuine perspectives involved. This has led to conflicts between community members and project sponsors. On the other hand, despite advancements in text analytics, including natural language processing (NLP) and its subfields such as topic modeling, sentiment analysis, and neural networks, their functionalities and effectiveness in analyzing public opinion in the domain of infrastructure projects have not been fully …

Analysis Of Earthquake Resistant Structures Using Matlab, Rhett Hamilton Brodie

Williams Honors College, Honors Research Projects

This paper is a report for the development of MATLAB software to aid in the organization, analysis, and interpretation of results from the research and design of earthquake resistant structures.

Simulation Of Wave Propagation In Granular Particles Using A Discrete Element Model, Syed Tahmid Hussan

College of Graduate Studies: Theses & Dissertations

The understanding of Bender Element mechanism and utilization of Particle Flow Code (PFC) to simulate the seismic wave behavior is important to test the dynamic behavior of soil particles. Both discrete and finite element methods can be used to simulate wave behavior. However, Discrete Element Method (DEM) is mostly suitable, as the micro scaled soil particle cannot be fully considered as continuous specimen like a piece of rod or aluminum. Recently DEM has been widely used to study mechanical properties of soils at particle level considering the particles as balls. This study represents a comparative analysis of Voigt and Best …

Early-Age Strength And Failure Characteristics Of 3d Printable Polymer Concrete: Numerical Modelling And Experimental Testing, Mohammad Amin Dehghani Najvani

Civil Engineering ETDs

The time-dependent rheological and early-age strength parameters of Polymer concrete (PC) were investigated. PC flow decreased, and the static yield stress and thixotropy increased as the specimen aged, while the dynamic yield stress remained unchanged. The study found that the Herschel-Bulkley model can accurately describe the PC’s rheological behavior over time. The change in cohesion strength and internal friction angle over time was observed using uniaxial unconfined compression and direct shear tests of fresh PC. A time-dependent MohrCoulomb failure criterion was established. Temperature analysis was used to determine the gel time and explain the evolution of the time-dependent early-age strength …

I-Guide Climbers: A Model For Multidisciplinary Academic Labs For Early Career Development, Iman Haqiqi, Wei Hu, Ramya Kumaran, Pin-Ching Li, Nicholas Manning, Alex Michels, Ayman Nassar, Jinwoo Park, Jimeng Shi, Adam Tonks, Zhaonan Wang

I-GUIDE Forum

In this paper, we propose a new form of multidisciplinary academic collaboration that goes beyond the traditional modes of knowledge exchange. We argue that most research collaboration today is based on interactions between closely related disciplines, in which researchers share data, methods, and insights within a common framework or problem. However, such collaboration may not foster the development of the communication and management skills essential to a multi-disciplinary research career. Therefore, we suggest establishing a network of researchers from divergent, yet complementary, disciplines who are interested in improving these skills through regular interactions and feedback. The main goal of this …

Permeability Prediction For Expansive Soil Based On Physical Properties Using Artificial Neural Networks, Ferry Fatnanta, Imam Suprayogi, Nicola Rabb Ranata, Soewignjo Agus Nugroho, Agus Ika Putra

Makara Journal of Technology

Permeability is a soil parameter related to the construction industry to understand the processes of infiltration, runoff, and settlement. The risk of testing errors is inevitable in permeability investigations, especially in expansive soils. Trial and error in permeability testing becomes difficult due to soils with small pore sizes and large shrinkage expansion. Several studies related to soil physical properties that affect permeability have been conducted. However, the correlation results obtained still have poor accuracy. Artificial neural networks (ANN) are machine learning systems that can change their structure to solve problems that are included in the system. The use of ANNs …

Resources Based Planning Framework For Infrastructure Maintenance And Rehabilitation Projects, Heba Gad

Theses and Dissertations

Infrastructure maintenance and rehabilitation projects involve activities scattered over a large geographical area (e.g., scattered road segments maintenance, telecom towers maintenance program, etc.). Planning such projects require a resource-based approach that accounts for the implications of resource mobility between activities’ locations in terms of time & cost. Existing scheduling techniques fall short of addressing the unique challenges of the scattered nature of these projects in combination with organization's limited resources availability. To address this need, this research presents a resources-based planning framework for infrastructure maintenance and rehabilitation scattered projects with the objective of enhancing resources utilization achieving time and cost …

Machine Learning-Based Data And Model Driven Bayesian Uncertanity Quantification Of Inverse Problems For Suspended Non-Structural System, Zhiyuan Qin

All Dissertations

Inverse problems involve extracting the internal structure of a physical system from noisy measurement data. In many fields, the Bayesian inference is used to address the ill-conditioned nature of the inverse problem by incorporating prior information through an initial distribution. In the nonparametric Bayesian framework, surrogate models such as Gaussian Processes or Deep Neural Networks are used as flexible and effective probabilistic modeling tools to overcome the high-dimensional curse and reduce computational costs. In practical systems and computer models, uncertainties can be addressed through parameter calibration, sensitivity analysis, and uncertainty quantification, leading to improved reliability and robustness of decision and …