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Articles 811 - 840 of 11942
Full-Text Articles in Entire DC Network
The Economics Of Privacy And Utility: Investment Strategies, Chandra Sharma, George Amariucai, Shuangqing Wei
The Economics Of Privacy And Utility: Investment Strategies, Chandra Sharma, George Amariucai, Shuangqing Wei
Faculty Publications
The inevitable leakage of privacy as a result of unrestrained disclosure of personal information has motivated extensive research on robust privacy-preserving mechanisms. However, existing research is mostly limited to solving the problem in a static setting with disregard for the privacy leakage over time. Unfortunately, this treatment of privacy is insufficient in practical settings where users continuously disclose their personal information over time resulting in an accumulated leakage of the users' sensitive information. In this paper, we consider privacy leakage over a finite time horizon and investigate optimal strategies to maximize the utility of the disclosed data while limiting the …
Performance Optimization Of Software-Defined Industrial Internet-Of-Things (Sd-Iiot), Jehad Ali, Celestine Iwendi, Gaoyang Shan, Hsiao Chun Wu, Mohammed J.F. Alenazi, Zaid Bin Faheem, Cresantus N. Biamba
Performance Optimization Of Software-Defined Industrial Internet-Of-Things (Sd-Iiot), Jehad Ali, Celestine Iwendi, Gaoyang Shan, Hsiao Chun Wu, Mohammed J.F. Alenazi, Zaid Bin Faheem, Cresantus N. Biamba
Faculty Publications
Software-Defined Networking (SDN) offers a centralized network management approach that can effectively address the complex and varied traffic demands characteristic of Industrial Internet of Things (IIoT) environments by decoupling the control plane from the data plane. The centralized control architecture of SDN necessitates the performance optimization of controllers to manage diverse traffic efficiently within IIoT applications. This paper explores the criteria for selecting controllers in SDN-enabled IIoT (SD-IIoT) environments, utilizing the Less Complex Analytic Network Process (LC-ANP) to establish their prioritization. A ranking system for SD-IIoT controllers is formulated using LC-ANP, and experimental validation of this method underscores its effectiveness …
Tensor Z -Transform, Shih Yu Chang, Hsiao Chun Wu
Tensor Z -Transform, Shih Yu Chang, Hsiao Chun Wu
Faculty Publications
The multi-input multioutput (MIMO) systems involving multirelational signals generated from distributed sources have been emerging as the most generalized model in practice. The existing work for characterizing such a MIMO system is to build a corresponding transform tensor, each of whose entries turns out to be the individual z-transform of a discrete-time impulse response sequence. However, when a MIMO system has a global feedback mechanism, which also involves multirelational signals, the aforementioned individual z-transforms of the overall transfer tensor are quite difficult to formulate. Therefore, a new mathematical framework to govern both feedforward and feedback MIMO systems is in crucial …
Fractal Surface Recovery And Self-Healing Contributed To Sustainable Superhydrophobicity: A Review, Yunfei Peng, Zhihang Ma, Xiao Wang, Junru Li, Xinlin Li, Chuanwei Zhang, Tian He, Guoqiang Li, Pengfei Zhang
Fractal Surface Recovery And Self-Healing Contributed To Sustainable Superhydrophobicity: A Review, Yunfei Peng, Zhihang Ma, Xiao Wang, Junru Li, Xinlin Li, Chuanwei Zhang, Tian He, Guoqiang Li, Pengfei Zhang
Faculty Publications
The concept of superhydrophobicity has been widely used after years of theoretical and experimental exploration. Researchers have obtained materials with excellent surface superhydrophobicity for numerous areas (e.g. textiles, paints, and coatings industries), through different design and synthesis methods using low surface energy components (LSECs) and micro/nanohierarchy composite structures. However, the durability of superhydrophobic material surfaces has gradually become a prominent obstacle to restricting applications. In this paper, advances in improving the durability of superhydrophobic surfaces in the past decade are reviewed, covering different schemes for recovering fractal surfaces based on the LSECs and micro/nanocomposite structures. It also presents a balanced …
Electrical Energy Harvesting By Connected Form Stable Phase Change Material Composites, Chengbin Yu, Guoqiang Li
Electrical Energy Harvesting By Connected Form Stable Phase Change Material Composites, Chengbin Yu, Guoqiang Li
Faculty Publications
Over the years, thermoelectric energy harvesting has been becoming a topic of intensive research and thermoelectric power generator has been utilized in various energy harvesting applications. However, a thermoelectric device is required to harvest energy, which has relatively low efficiency and high cost. To overcome such a common problem, the objective of this study is to generate electrical energy without using thermoelectric devices. To this end, an advanced energy harvester composed of two different phase change material composites was explored. It was hypothesized that based on the well-known Seebeck effect, stable electrical energy output would be feasible without a thermoelectric …
Fracture Conductivity Management To Improve Heat Extraction In Enhanced Geothermal Systems, Qitao Zhang, Arash Dahi Taleghani, Guoqiang Li
Fracture Conductivity Management To Improve Heat Extraction In Enhanced Geothermal Systems, Qitao Zhang, Arash Dahi Taleghani, Guoqiang Li
Faculty Publications
The efficiency of an enhanced geothermal reservoir (EGS) depends on the effective circulation of the working fluid through the geothermal formation. To remove the thermal shortcut that leads to thermal short-circuiting in the EGS, we present a method of fracture hydraulic conductivity management and present some practical ways to implement it in the field. The core idea is to correlate the flow resistance in different flow channels with temperature, in order to make uniform heat extraction through each flow path. The presented technique is an adaptive and reversible system and is trying to engineer the fracture system for effective delay …
Subcooled Pool Boiling On Hierarchical Micro- And Nanostructure-Modified Copper Surfaces In Hfe-7100 Dielectric Liquid, Shayan Davani, Bin Zhang, Brendon Doran, Luke Hansen, Mohammad Khan, Mahdi Roodbari, Wen Jin Meng, Arden L. Moore
Subcooled Pool Boiling On Hierarchical Micro- And Nanostructure-Modified Copper Surfaces In Hfe-7100 Dielectric Liquid, Shayan Davani, Bin Zhang, Brendon Doran, Luke Hansen, Mohammad Khan, Mahdi Roodbari, Wen Jin Meng, Arden L. Moore
Faculty Publications
Hierarchical surfaces comprised both microscale and nanoscale structures have been previously studied as a means of targeting multiple length scales to achieve superior pool boiling performance. However, preceding studies have focused almost exclusively on high surface tension working fluids, while technologically important low surface tension fluids have remained largely unexplored. Due to their significantly lower surface tension these liquids tend to push out the air trapped in surface cavities of the heating surface, resulting in fewer nucleation sites compared to the same surface in water at low to moderate superheats. Thus, developing effective surface modification techniques for pool boiling in …
Biomarkers In Cancer Detection, Diagnosis, And Prognosis, Sreyashi Das, Mohan Kumar Dey, Ram Devireddy, Manas Ranjan Gartia
Biomarkers In Cancer Detection, Diagnosis, And Prognosis, Sreyashi Das, Mohan Kumar Dey, Ram Devireddy, Manas Ranjan Gartia
Faculty Publications
Biomarkers are vital in healthcare as they provide valuable insights into disease diagnosis, prognosis, treatment response, and personalized medicine. They serve as objective indicators, enabling early detection and intervention, leading to improved patient outcomes and reduced costs. Biomarkers also guide treatment decisions by predicting disease outcomes and facilitating individualized treatment plans. They play a role in monitoring disease progression, adjusting treatments, and detecting early signs of recurrence. Furthermore, biomarkers enhance drug development and clinical trials by identifying suitable patients and accelerating the approval process. In this review paper, we described a variety of biomarkers applicable for cancer detection and diagnosis, …
The Effects Of Layer Thickness On The Mechanical Properties Of Additive Friction Stir Deposition-Fabricated Aluminum Alloy 6061 Parts, Hamed Ghadimi, Mojtaba Talachian, Huan Ding, Selami Emanet, Shengmin Guo
The Effects Of Layer Thickness On The Mechanical Properties Of Additive Friction Stir Deposition-Fabricated Aluminum Alloy 6061 Parts, Hamed Ghadimi, Mojtaba Talachian, Huan Ding, Selami Emanet, Shengmin Guo
Faculty Publications
Solid-state additive friction stir deposition (AFSD) is a thermomechanical-based additive manufacturing technique. For this study, AFSD was utilized to produce aluminum alloy 6061 (AA6061) blocks with varying layer thicknesses (1 mm, 2 mm, and 3 mm). The mechanical properties were assessed through uniaxial tensile tests and Vickers microhardness measurement, and statistical analysis was employed to investigate differences among data groups. The results revealed that the deposition layer thickness influences tensile properties in the building (Z) direction, while the properties in the X and Y directions showed minor differences across the three AFSD blocks. Furthermore, variations in tensile properties were observed …
Review Of Artificial Neural Networks For Wind Turbine Fatigue Prediction, Alshannaq, Aly Mousaad Aly
Review Of Artificial Neural Networks For Wind Turbine Fatigue Prediction, Alshannaq, Aly Mousaad Aly
Faculty Publications
Wind turbines have emerged as a prominent renewable energy source globally. Efficient monitoring and detection methods are crucial to enhance their operational effectiveness, particularly in identifying fatigue-related issues. This review focuses on leveraging artificial neural networks (ANNs) for wind turbine monitoring and fatigue detection, aiming to provide a valuable reference for researchers in this domain and related areas. Employing various ANN techniques, including General Regression Neural Network (GRNN), Support Vector Machine (SVM), Cuckoo Search Neural Network (CSNN), Backpropagation Neural Network (BPNN), Particle Swarm Optimization Artificial Neural Network (PSO-ANN), Convolutional Neural Network (CNN), and nonlinear autoregressive networks with exogenous inputs (NARX), …
Reliability Analysis Of End Cracking In Continuous Prestressed Concrete Girders, A. M. Okeil, S. Ghimire
Reliability Analysis Of End Cracking In Continuous Prestressed Concrete Girders, A. M. Okeil, S. Ghimire
Faculty Publications
Constructing bridges using precast prestressed concrete girders is extremely popular because of their durability and ease of construction. Establishing continuity between precast girders has its advantages and has been employed in many projects. It causes the development of positive restraint moments at intermediate supports as a result of long-term effects such as creep, shrinkage and thermal gradients. Prestressed concrete girder end cracking occurs if the positive restraint moments exceed the girder’s cracking moment. In this study, the probability of girder end cracking in continuous prestressed concrete bridges is assessed using structural reliability concepts. This study focuses on two bridge configurations …
Field Monitoring Of Bridge Link Slab Performance Under Long-Term And Live Load Effects, A. M. Okeil, M. Canales
Field Monitoring Of Bridge Link Slab Performance Under Long-Term And Live Load Effects, A. M. Okeil, M. Canales
Faculty Publications
Several details to eliminate bridge expansion joints have been proposed, and employed, in bridge construction. Expansion joints are known to require regular maintenance and are the cause of a host of problems including damage to girder ends and substructure components in the vicinity of the joints. The link slab detail is one of these alternatives that eliminates bridge expansion joints without introducing full bridge girder continuity. It has been gaining wide acceptance in North America and is becoming a standard construction detail. A bridge over the Ouachita River in Louisiana, US, employed the link slab detail to connect prestressed concrete …
Instrumentation And Strain Monitoring Of Bfrp Bars In Pedestrian Bridge Deck Link Slab, A. Elsafty, A. Okeil, J. Fletcher, T. Fowler, D. Jones, S. Nolan
Instrumentation And Strain Monitoring Of Bfrp Bars In Pedestrian Bridge Deck Link Slab, A. Elsafty, A. Okeil, J. Fletcher, T. Fowler, D. Jones, S. Nolan
Faculty Publications
Eliminating bridge deck expansion joints is considered a feasible alternative for addressing problems associated with deck joints, which results in reduced maintenance and improved bridge-deck design life. Link slabs introduce partially continuity for bridge girders and improve the seismic performance, wind and storm wave loads resistance. It also leads to lower cost, improved riding quality, and improved structural integrity, and may lead to longer spans. The goal of this study is to monitor the performance of a link slab employed in a pedestrian bridge where Basalt Fiber Reinforced Polymer (BFRP) bars were used for its reinforcement. The pedestrian bridge was …
Solving Short-Term Relocalization Problems In Monocular Keyframe Visual Slam Using Spatial And Semantic Data, Azmyin Md Kamal, Nenyi Kweku Nkensen Dadson, Donovan Gegg, Corina Barbalata
Solving Short-Term Relocalization Problems In Monocular Keyframe Visual Slam Using Spatial And Semantic Data, Azmyin Md Kamal, Nenyi Kweku Nkensen Dadson, Donovan Gegg, Corina Barbalata
Faculty Publications
In Monocular Keyframe Visual Simultaneous Localization and Mapping (MKVSLAM) frameworks, when incremental position tracking fails, global pose has to be recovered in a short-time window, also known as short-term relocalization. This capability is crucial for mobile robots to have reliable navigation, build accurate maps, and have precise behaviors around human collaborators. This paper focuses on the development of robust short-term relocalization capabilities for mobile robots using a monocular camera system. A novel multimodal keyframe descriptor is introduced, that contains semantic information of objects detected in the environment and the spatial information of the camera. Using this descriptor, a new Keyframe-based …
Water Wave Optimization Algorithm-Based Dynamic Optimal Dispatch Considering A Day-Ahead Load Forecasting In A Microgrid, Duy C. Huynh, Loc D. Ho, Hieu M. Pham, Matthew W. Dunnigan, Corina Barbalata
Water Wave Optimization Algorithm-Based Dynamic Optimal Dispatch Considering A Day-Ahead Load Forecasting In A Microgrid, Duy C. Huynh, Loc D. Ho, Hieu M. Pham, Matthew W. Dunnigan, Corina Barbalata
Faculty Publications
A novel strategy is proposed to tackle an optimal dispatch of a microgrid in response to dynamic conditions, utilizing a water wave optimization (WWO) algorithm and considering a day-ahead load forecasting. Amongst meta-heuristic algorithms, the WWO algorithm stands out in terms of population size, parameter tuning, exploitation and exploration, convergence speed, as well as optimization mechanism. It leverages its ability to efficiently explore solution spaces and adapt to changing conditions. It is applied to the dynamic optimal dispatch of a microgrid with the uncertainty of load power considered and solved by day-ahead load forecasting. It dynamically adjusts the microgrid operation …
Single-Component Hydrophilic Terpolymer Thin Film Systems For Imparting Surface Chemical Versatility On Various Substrates, Yun Hee Ko, Hai Ha Tran Nguyen, Christopher R. Branstetter, Soeun Park, Jin Kyun Lee, Jaesung Yang, Jangwook P. Jung, Myungwoong Kim
Single-Component Hydrophilic Terpolymer Thin Film Systems For Imparting Surface Chemical Versatility On Various Substrates, Yun Hee Ko, Hai Ha Tran Nguyen, Christopher R. Branstetter, Soeun Park, Jin Kyun Lee, Jaesung Yang, Jangwook P. Jung, Myungwoong Kim
Faculty Publications
We demonstrate a single-component hydrophilic photocrosslinkable copolymer system that incorporates all critical functionalities into one chain. This design allows for the creation of uniform functional organic coatings on a variety of substrates. The copolymers were composed of a poly(ethylene oxide)-containing monomer, a monomer that can release a primary amine upon UV light, and a monomer with reactive epoxide or cyclic dithiocarbonate with a primary amine. These copolymers are easily incorporated into the solution-casting process using polar solvents. Furthermore, the resulting coating can be readily stabilized through UV light-induced crosslinking, providing an advantage for controlling the surface properties of various substrates. …
Method For Assessing Coating Uniformity Of Angioplasty Balloons Coated With Poly(Lactic-Co-Glycolic Acid) Nanoparticles Loaded With Quercetin, Allison D. Zieschang, Kevin F. Hoffseth, Tammy R. Dugas, Carlos E. Astete, Dorin Boldor
Method For Assessing Coating Uniformity Of Angioplasty Balloons Coated With Poly(Lactic-Co-Glycolic Acid) Nanoparticles Loaded With Quercetin, Allison D. Zieschang, Kevin F. Hoffseth, Tammy R. Dugas, Carlos E. Astete, Dorin Boldor
Faculty Publications
In this study, we aim to quantify coating uniformity and correlate fluorescence intensity to drug loading for drug-coated angioplasty balloons (DCB) coated with 5, 10, 15, or 20 layers of poly(lactic-co-glycolic acid) nanoparticles (NPs) entrapped with quercetin. Uniformity was quantified from histograms and horizontal line profiles of microscopic fluorescent images acquired with sample specific parameters, and cracks in the coating were measured and counted. The fluorescence of images acquired with global parameters was correlated with quercetin loading measured via gravimetric/HPLC analysis. More layers on DCBs may be associated with less uniform coatings, as indicated by differences in histogram standard deviations. …
Machine Learning For Automated Sand Transport Monitoring In A Pipeline Using Distributed Acoustic Sensor Data, Harrison Gietz, Jyotsna Sharma, Mayank Tyagi
Machine Learning For Automated Sand Transport Monitoring In A Pipeline Using Distributed Acoustic Sensor Data, Harrison Gietz, Jyotsna Sharma, Mayank Tyagi
Faculty Publications
Uncontrolled sand production presents a substantial challenge to wellbore and pipeline integrity and efficiency of hydrocarbon production operations, often leading to equipment damage and compromised productivity. Traditional sand detection methods on the surface alert operators to sanding issues, but they are often a lagging indicator of downhole sanding events and do not provide precise identification of the problematic reservoir zones. Addressing this limitation, this study harnesses a combination of efficient signal processing and machine learning (ML) to analyze data from optical-fiber-based distributed acoustic sensors (DASs), thus serving as the first instance (to the authors' knowledge) of an automated and real-time …
Countermeasures To Improve Pedestrian Safety On Arterials, Nicholas Ferenchak
Countermeasures To Improve Pedestrian Safety On Arterials, Nicholas Ferenchak
Publications
This work analyzed the pedestrian safety and overall traffic safety impacts – in terms of both motor vehicle speeds and crash outcomes – of several countermeasures applied to the Central Avenue arterial corridor in Albuquerque, New Mexico. Findings suggest that the infrastructure changes associated with a bus rapid transit (BRT) system improved traffic safety by reducing vehicle 85th percentile speeds by 11.5% and reducing serious and fatal injuries by 60.0%. While pedestrian safety outcomes were more variable, pedestrians generally fared better on BRT segments than on control segments. The mechanism behind these improvements was traffic calming through the BRT’s …
Economic, Environmental, And Social Characteristics Of E-Scooters On Lsu Campus, Mostafa Elseifi, Md Afif Rahman Chowdhury
Economic, Environmental, And Social Characteristics Of E-Scooters On Lsu Campus, Mostafa Elseifi, Md Afif Rahman Chowdhury
Publications
This study provides a comprehensive evaluation of e-scooter technology, with a focus on its environmental, economic, and social impacts, particularly within university settings at the Louisiana State University (LSU) campus. A life-cycle assessment (LCA) was conducted to assess the environmental sustainability of e-scooters, encompassing all stages from raw materials acquisition to end-of-life. The analysis determined that the total CO2 emissions for an e-scooter over a five-year lifespan were approximately 389 kg, with significant reductions possible by improving the lifespan of e-scooters, integrating recycled materials, and utilizing renewable energy sources for charging batteries. The study also compared the environmental and …
Vehicle Classification Technologies For Toll Collection, Samir Ahmed
Vehicle Classification Technologies For Toll Collection, Samir Ahmed
Publications
Toll facilities (roads, bridges, and tunnels) are intended for revenue generation to pay off the long-term debt issued to finance construction, capacity expansion, operations, and maintenance of these facilities. Tolls are one form of a broad concept known as road pricing. In addition to revenue generation, road pricing is used for other reasons including transportation demand management to reduce peak hour travel and the recurring traffic congestion on some corridors. The aim of this study is to provide the tolling industry with detailed analysis of the suitability of various non‐ pavement‐intrusive vehicle classification technologies (imaging using radar, Lidar, thermal profiling, …
Designing And Characterizing New Coating Materials To Increase The Corrosion Resistance Of Steel Reinforcement Embedded In Concrete, Homero Castaneda Lopez
Designing And Characterizing New Coating Materials To Increase The Corrosion Resistance Of Steel Reinforcement Embedded In Concrete, Homero Castaneda Lopez
Publications
To develop a sustainable and durable rebar on different elements of the RC as a corrosion control system in regions where corrosion is the leading risk for the infrastructure system. The outcome of this research leads to a comprehensive report that provides methods, testing results, peer review papers, conference proceedings, and guidance for the utilization of rebar for corrosion control actions in RC, capable of long-term performance in harsh corrosive environments (deicing cycle conditions). Workforce development will also take place through a series of outreach activities targeting the broader audience of corrosion, civil, and materials engineers, and potential industrial partners …
Evaluating The Moisture Susceptibility Of Asphalt Mixes In Oklahoma, Mohamed Elkashef, Samir Ahmed, Sina Mousavi Rad
Evaluating The Moisture Susceptibility Of Asphalt Mixes In Oklahoma, Mohamed Elkashef, Samir Ahmed, Sina Mousavi Rad
Publications
Moisture-induced damage can be detrimental to asphalt pavements. The modified Lottman approach (AASHTO T 283) is used to evaluate the stripping susceptibility of mixtures in Oklahoma. There are concerns about the ability of the AASHTO 283 to predict moisture damage in the field. In this study, the AASHTO T 283, the moisture-induced stress tester (MiST), and the Hamburg wheel tracking (HWT) test are used to evaluate the moisture susceptibility of mixes prepared using different gradations, local aggregate sources, and binders sampled from different refineries in Oklahoma. The mixes were also tested for cracking and rutting using the indirect tensile asphalt …
Monitoring Of Transportation System Assets Using Synthetic Aperture Radar (Sar) Satellite Data, Anand Puppala, Nripojyoti Biswas, Amit Gajurel
Monitoring Of Transportation System Assets Using Synthetic Aperture Radar (Sar) Satellite Data, Anand Puppala, Nripojyoti Biswas, Amit Gajurel
Publications
This research harnessed both high and medium resolution Synthetic Aperture Radar (SAR) data to delve into infrastructure health assessment. High resolution SAR analyses capable of identifying differences between asphalt and concrete pavement surfaces. Particularly, it was found that Normalized Radar Cross Section (NRCS) values can deftly distinguish pavement types and detect surface anomalies such as alligator cracks in asphalt ahead of conventional methods. On the other hand, Time-Series Interferometric Synthetic Aperture Radar (InSAR) insights, extracted from medium resolution SAR, established a direct linkage between environmental factors and ground deformations. Such findings were corroborated by optical images collected during May 2017 …
Stabilization Of Expansive Soil Using Geopolymers From Locally Available Resources, Anand Puppala, Miladin Radovic, Nripojyoti Biswas, Sopharith Chou, Oscar Huang
Stabilization Of Expansive Soil Using Geopolymers From Locally Available Resources, Anand Puppala, Miladin Radovic, Nripojyoti Biswas, Sopharith Chou, Oscar Huang
Publications
Traditional calcium-based stabilizers are generally used to stabilize native expansive soils that are often found throughout Region 6. Due to their high carbon footprint, many studies are being conducted to identify a suitable green alternative for stabilizing expansive soils. Geopolymer (GP) received a lot of attention in the past few decades owing to its similar properties to that of ordinary Portland cement (OPC) yet with a lower carbon footprint. Previous studies have shown that metakaolin-based GP is an effective stabilizer to stabilize expansive soils. This study investigated the feasibility of stabilizing native expansive soils with GP synthesized with locally sourced …
Framework Of Internal Damage Identification In Inhomogeneous Medium Interweaving Wave Scattering Model And Deep Learning, Suyun Ham, Stefan Romanoschi, Yin Chao Wu, Dafnik Saril Kumar David
Framework Of Internal Damage Identification In Inhomogeneous Medium Interweaving Wave Scattering Model And Deep Learning, Suyun Ham, Stefan Romanoschi, Yin Chao Wu, Dafnik Saril Kumar David
Publications
The primary objective of this project is to investigate the framework of internal damage identification in inhomogeneous media (IHM) using deep learning techniques and wave scattering. The study focuses on two main steps: 1) analyzing the wave response pattern in homogeneous media (HM) and 2) characterizing the wave response variation (WRV) in IHM with different aggregate sizes and random distributions. The WRV patterns are then classified and used to predict internal damage using a convolutional neural network (CNN). The accuracy of the finite element (FE) model is verified using laboratory tests with artificial internal crack models of varying depths. The …
Identifying Wrong-Way Driving Entry Points On Interstate Highways Using Land-Use Impact Assessment And 911 Calls, Farman Mia, Samer Dessouky
Identifying Wrong-Way Driving Entry Points On Interstate Highways Using Land-Use Impact Assessment And 911 Calls, Farman Mia, Samer Dessouky
Publications
The research aims to provide insight into the initiation event of Wrong-way Driving (WWD) on highways. The intense severity of a WWD accident is encouraging the authorities to install mitigation systems that will ensure safety for motorists on highways. The WWD events are mostly resulting of intoxicated driving, where the unconscious driver takes the wrong way to enter the highway and place other motorists into life-threatening danger. This research attempted to explore from basic knowledge of WWD occurrence to examine the origin and driving philosophy of intoxicated drivers from land-use impact and mathematical modeling point of views. To identify the …
Automated Vehicle Impacts On Underserved Populations, Kate Kyung Hyun, Stephen Mattingly, Katie Kam
Automated Vehicle Impacts On Underserved Populations, Kate Kyung Hyun, Stephen Mattingly, Katie Kam
Publications
This research report describes the scenario framework created to determine the potential role automated vehicles (AVs) have in benefiting and adversely impacting the following underserved populations: people with disabilities and impairments (visually, hearing, physically, intellectually) and with autism spectrum disorder, younger and older populations, immigrants, low income, indigenous, rural, female and LGBTQ+, vulnerable road users (cyclists, pedestrians, low speed riders and drivers), and minority races. After presenting a literature review, three chapters explain the 3 modules of the framework: (1) scenario construction, (2) scenario factors, and (3) GIS methodology for evaluating community level AV impacts. Module 1 describes the use …
Monotonic And Cyclic Behavior Of High Strength Reinforcing Steel (Hsrs) After High Temperature Exposure, Himan Hojat Jalali, Moein Ebrahimi, Khaled Abuhishmeh, Mohammadamin Soltanianfard
Monotonic And Cyclic Behavior Of High Strength Reinforcing Steel (Hsrs) After High Temperature Exposure, Himan Hojat Jalali, Moein Ebrahimi, Khaled Abuhishmeh, Mohammadamin Soltanianfard
Publications
Conventional reinforced concrete transportation structures in North America often use Grade 40 ksi-60 ksi reinforcing steel. The introduction of high strength reinforcing steel (HSRS) with higher yield strength in the reinforced concrete industry has led to many economic and workability advantages such as construction time saving, reduced labor cost and steel consumption which in turn alleviates congestion of reinforcement, savings in transportation and deliveries that finally results in lower carbon emission. Despite these benefits, many states, including those in Region 6, have not widely adopted the use of higher strength reinforcing steels in practice due to lack of knowledge and …
Green Mobility In Texas: Comparative Environmental Impacts And Lifecycle Cost Analysis Of Hybrid, Electric, And Hydrogen Fuel Cell Cars, Raghava R. Kommalapati, Hongbo Du, Md Jobair Bin Alam
Green Mobility In Texas: Comparative Environmental Impacts And Lifecycle Cost Analysis Of Hybrid, Electric, And Hydrogen Fuel Cell Cars, Raghava R. Kommalapati, Hongbo Du, Md Jobair Bin Alam
Publications
Compared to gasoline/diesel cars and battery electric cars (BECs), hydrogen fuel cell cars (HFCCs) are relatively new. Two main advantages of HFCCs over electric vehicles are no special requirements for heavy batteries and long charging time. There is no HFCC in Texas; thus, exploring the use of electricity or hydrogen produced from renewable energies for personal cars and mitigating vehicle emissions is critical for sustaining a long-term decarburization strategy for megacities like Houston and Dallas. This project addressed this critical gap and developed environmental impacts and cost assessments for hybrid gasoline cars, BECs, and HFCCs in Texas under several possible …