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- CCFSS Proceedings of International Specialty Conference on Cold-Formed Steel Structures (1971 - 2018) (1036)
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Articles 1 - 30 of 1914
Full-Text Articles in Engineering
Enhancing Frp-Concrete Interface Bearing Capacity Prediction With Explainable Machine Learning: A Feature Engineering Approach And Shap Analysis, Yanping Zhu, Woubishet Zewdu Taffese, Genda Chen
Enhancing Frp-Concrete Interface Bearing Capacity Prediction With Explainable Machine Learning: A Feature Engineering Approach And Shap Analysis, Yanping Zhu, Woubishet Zewdu Taffese, Genda Chen
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
This study introduces a novel approach to predict the shear bearing capacity of FRP-concrete interfaces using explainable machine learning. Eight algorithms are employed: three standalone models (Artificial Neural Network, Support Vector Regression, and Decision Tree) and five ensemble learning models (Bagging, Random Forest, Adaptive Boosting, Gradient Boosting, and Extreme Gradient Boosting). Four scenarios with varying input features, including engineered features inspired by mechanics-based bearing capacity equations, are examined. Notably, the inclusion of engineered features such as the stiffness of the FRP strip (Kf) significantly enhanced prediction accuracy and efficiency, although the width correction coefficient (bf/bc) did not yield significant benefits, …
The Effectiveness Of Waste Tire Pyrolysis Oils (Wtpos) As Rejuvenating Agents For Asphalt Materials, Ahmed S. El-Ashwah, Magdy Abdelrahman
The Effectiveness Of Waste Tire Pyrolysis Oils (Wtpos) As Rejuvenating Agents For Asphalt Materials, Ahmed S. El-Ashwah, Magdy Abdelrahman
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
The continuous increase in solid waste materials, such as waste tires, underscores the critical importance of recycling them to mitigate environmental impact and promote sustainable resource management. This research study evaluated the effectiveness of utilizing waste tire pyrolysis oils (WTPOs) as recycling agents for asphalt materials. The chemical composition and thermal behavior of WTPO were analyzed using Fourier transform infrared (FT-IR) spectroscopy and thermogravimetric analysis (TGA). Mechanically, the prepared WTPO binders were assessed by measuring dynamic viscosity and changes in high- and intermediate-temperature performance grades. Additionally, the cracking susceptibility of the binders was evaluated using the Glover-Rowe (G-R) parameter. The …
Influence Of Aggregate Properties On Skid Resistance Of Pavement Surface Treatments, Alireza Roshan, Magdy Abdelrahman
Influence Of Aggregate Properties On Skid Resistance Of Pavement Surface Treatments, Alireza Roshan, Magdy Abdelrahman
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Skid resistance is a critical aspect for traffic safety since it significantly influences vehicle control and minimizes the distance required for emergency braking. The surface characteristics of pavements play a pivotal role in determining skid resistance. To achieve the optimal skid resistance performance, the pavement must sustain a specific level of friction. Thus, it is advantageous to apply surface treatments in areas that require enhanced friction. This study investigates the impact of factors such as the aggregate source, size, morphological properties, and abrasion levels on the skid resistance and frictional characteristics of a high-friction surface treatment (HFST). A complete investigation …
Early Detection Of Pipeline Natural Gas Leakage From Hyperspectral Imaging By Vegetation Indicators And Deep Neural Networks, Pengfei Ma, Tarutal Ghosh Mondal, Zhenhua Shi, Mohammad Hossein Afsharmovahed, Kevin Romans, Liujun Li, Ying Zhuo, Genda Chen
Early Detection Of Pipeline Natural Gas Leakage From Hyperspectral Imaging By Vegetation Indicators And Deep Neural Networks, Pengfei Ma, Tarutal Ghosh Mondal, Zhenhua Shi, Mohammad Hossein Afsharmovahed, Kevin Romans, Liujun Li, Ying Zhuo, Genda Chen
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
The timely detection of underground natural gas (NG) leaks in pipeline transmission systems presents a promising opportunity for reducing the potential greenhouse gas (GHG) emission. However, existing techniques face notable limitations for prompt detection. This study explores the utility of Vegetation Indicators (VIs) to reflect vegetation health deterioration, thereby representing leak-induced stress. Despite the acknowledged potential of VIs, their sensitivity and separability remain understudied. In this study, we employed ground vegetation as biosensors for detecting methane emissions from underground pipelines. Hyperspectral imaging from vegetation was collected weekly at both plant and leaf scales over two months to facilitate stress detection …
Experimental Study On The Detection Of The Existence And Location Of Mimicked And Unexpected Interface Debonding Defects In An Existing Rectangular Cfst Column With Pzt Materials, Qian Liu, Bin Xu, Genda Chen, Weilong Ni, Zhixun Liu, Chun Lin, Zhiyou Zhuang
Experimental Study On The Detection Of The Existence And Location Of Mimicked And Unexpected Interface Debonding Defects In An Existing Rectangular Cfst Column With Pzt Materials, Qian Liu, Bin Xu, Genda Chen, Weilong Ni, Zhixun Liu, Chun Lin, Zhiyou Zhuang
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Interface bonding conditions between concrete and steel materials play key roles in ensuring the composite effect and load-carrying capacity of concrete–steel composite structures such as concrete-filled steel tube (CFST) members in practice. A method using both surface wave and electromechanical impedance (EMI) measurement for detecting the existence and the location of inaccessible interface debonding defects between the concrete core and steel tube in CFST members using piezoelectric lead zirconate titanate (PZT) patches as actuators and sensors is proposed. A rectangular CFST specimen with two artificially mimicked interface debonding defects was experimentally verified using PZT patches as the actuator and sensor. …
Ensemble-Learning Model Based Ultimate Moment Prediction Of Reinforced Concrete Members Strengthened By Uhpc, Woubishet Zewdu Taffese, Yanping Zhu, Genda Chen
Ensemble-Learning Model Based Ultimate Moment Prediction Of Reinforced Concrete Members Strengthened By Uhpc, Woubishet Zewdu Taffese, Yanping Zhu, Genda Chen
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Data-driven model development brings new approaches to solve conventional civil engineering problems, which are usually considered and answered by experimental, analytical, and numerical methods. This study aims to develop an ensemble learning model (i.e., XGBoost: eXtreme Gradient Boosting) to predict ultimate moment of reinforced concrete (RC) members strengthened by a newly developed concrete technology – ultrahigh performance concrete (UHPC). The study considered two scenarios, incorporating eighteen and seventeen features, with one feature modification involving the transformation of width and height to the cross-sectional area of RC members. Incorporating three substrate damage levels, two substrate surface treatments preceding UHPC strengthening, and …
Multifunctional Models In Digital And Physical Twinning Of The Built Environment—A University Campus Case Study, Genda Chen, Ibrahim Alomari, Woubishet Zewdu Taffese, Zhenhua Shi, Mohammad Hossein Afsharmovahed, Tarutal Ghosh Mondal, Son Nguyen
Multifunctional Models In Digital And Physical Twinning Of The Built Environment—A University Campus Case Study, Genda Chen, Ibrahim Alomari, Woubishet Zewdu Taffese, Zhenhua Shi, Mohammad Hossein Afsharmovahed, Tarutal Ghosh Mondal, Son Nguyen
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
The Digital Twin (DT) Concept Has Been Developed for a Single Function in Previous Studies. This Study Aims to Empower DTs with a Layered Integration of Multifunctional Models in the Built Environment. It Develops a Framework of DT Modules in Three Hierarchical Tiers: Region, Asset, and System; Defines a New Concept of the Degree of Digital Twinning (DODT) to the Real World by the Number of Models Enabled by a Common DT Platform; and Enables Spatiotemporal Analysis in Multiple Scales to Couple Nonstructural with Structural Building Components and Connect the Built Environment to Planning Constructions. While the Asset and System …
Natural Gas Induced Vegetation Stress Identification And Discrimination From Hyperspectral Imaging For Pipeline Leakage Detection, Pengfei Ma, Ying Zhuo, Genda Chen, Joel G. Burken
Natural Gas Induced Vegetation Stress Identification And Discrimination From Hyperspectral Imaging For Pipeline Leakage Detection, Pengfei Ma, Ying Zhuo, Genda Chen, Joel G. Burken
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Remote Sensing Detection of Natural Gas Leaks Remains Challenging When using Ground Vegetation Stress to Detect Underground Pipeline Leaks. Other Natural Stressors May Co-Present and Complicate Gas Leak Detection. This Study Explores the Feasibility of Identifying and Distinguishing Gas-Induced Stress from Other Natural Stresses by Analyzing the Hyperspectral Reflectance of Vegetation. the Effectiveness of This Discrimination is Assessed Across Three Distinct Spectral Ranges (VNIR, SWIR, and Full Spectra). Greenhouse Experiments Subjected Three Plant Species to Controlled Environmental Stressors, Including Gas Leakage, Salinity Impact, Heavy-Metal Contamination, and Drought Exposure. Spectral Curves Obtained from the Experiments Underwent Preprocessing Techniques Such as Standard …
Characterization Of Alkali-Silica Reaction (Asr) Products And C-S-H Using Swir Spectroscopy For Nondestructive Detection Of Asr, Pengfei Ma, Wenyu Liao, Ying Zhuo, Hongyan Ma, Yanping Zhu, Genda Chen
Characterization Of Alkali-Silica Reaction (Asr) Products And C-S-H Using Swir Spectroscopy For Nondestructive Detection Of Asr, Pengfei Ma, Wenyu Liao, Ying Zhuo, Hongyan Ma, Yanping Zhu, Genda Chen
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
This study explores the feasibility of characterizing alkali-silica reaction (ASR) products and calcium silicate hydrates (C-S-H) from short-wave infrared (SWIR) spectroscopy. ASR products and C-S-H samples with different Ca/Si ratios were synthesized and analyzed through XRD, 29Si nuclei magnetic resonance (NMR) and SWIR spectroscopy. Fourier-transform infrared spectroscopy (FTIR) was collected to help interpret the results from the SWIR spectroscopy. The obtained spectroscopic features were applied to quantify the ASR product abundance denoted by the length expansion of mortar bars after an accelerated ASR test. The results show that the SWIR spectra of the synthetic ASR gels are similar regardless of …
Evaluating Friction Characteristics Of High Friction Surface Treatment Application Under Varied Polishing And Slippery Conditions, Alireza Roshan, Magdy Abdelrahman
Evaluating Friction Characteristics Of High Friction Surface Treatment Application Under Varied Polishing And Slippery Conditions, Alireza Roshan, Magdy Abdelrahman
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
The frictional attributes of high friction surface treatment (HFST) play a crucial role in ensuring optimal traffic safety, particularly in wet weather conditions. Friction consists of two important components: adhesion and hysteresis. This research focuses on evaluating these essential factors in HFST using two different aggregates and two distinct sizes by considering various abrasion and polishing methods. To isolate these components for assessment, testing was carried out under various slippery conditions, including dry, wet with water, and wet with water + soap. The inclusion of liquid hand soap in the test procedure effectively minimized or even eliminated the adhesion component's …
A Vehicle-Bridge Interaction Model Considering Contact Patch Size And Vehicle Self-Generated Excitation – A Theoretical Study, Zhenhua Shi, Yahya M. Mohammed, Nasim Uddin, Genda Chen
A Vehicle-Bridge Interaction Model Considering Contact Patch Size And Vehicle Self-Generated Excitation – A Theoretical Study, Zhenhua Shi, Yahya M. Mohammed, Nasim Uddin, Genda Chen
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
This paper presents an improved theoretical damped single-axle vehicle-bridge dynamic interaction model to consider the effect of the contact patch size and motor-induced vehicle excitation. The contact patch issue is critical as it determines the minimum time step for simulation and maximum identifiable frequency, while the inclusion of the motor-induced vehicle excitation benefits the design of autonomous self-driven rather than towed vehicles. Estimations of the contact patch size for both the pneumatic tire and solid wheel scenarios are discussed. The contact patch responses, which degenerate into contact point responses when the contact patch size is assumed to be infinitely small, …
Performance Of Smart Shear Keys In Concrete Bridges Under Tsunami Loading: An Experimental Study, Haibin Zhang, Xinzhe Yuan, Genda Chen, Pedro Lomonaco
Performance Of Smart Shear Keys In Concrete Bridges Under Tsunami Loading: An Experimental Study, Haibin Zhang, Xinzhe Yuan, Genda Chen, Pedro Lomonaco
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Bridges have recently been exposed to an increasing number of natural hazards such as earthquakes and tsunamis. These extreme events have resulted in transverse offsets, overturning moments, and even dropping-off of superstructures due to their weak connection to substructures. These outcomes are potentially prevented or mitigated by developing and deploying sliding, modular, adaptive, replaceable, and two-dimensional (SMART) shear keys as fuse elements between superstructures and substructures. The novelty of SMART shear keys is to enable an adaptive control of both the force and displacement of bridges under different types of loads. In this study, the performance of SMART shear keys …
Defects Detection Of Concrete Bridge Decks Using Uav-Based Infrared Thermography, H. B. Zhang, Z. Zhou, G. Chen
Defects Detection Of Concrete Bridge Decks Using Uav-Based Infrared Thermography, H. B. Zhang, Z. Zhou, G. Chen
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Concrete bridges are vulnerable to both natural and man-made disasters, as well as aging and deterioration processes throughout their lifespan. Timely detection of defects in concrete structures is crucial for repair and decision-making purposes. However, traditional methods like visual inspection are time-consuming and expensive. Unmanned aerial vehicles (UAVs) equipped with infrared thermography (IRT) offer an efficient and cost-effective solution for detecting defects in concrete structures. This study presents passive and active IRT techniques for detecting common concrete defects, such as delamination and cracks. Principle and methods for quantifying these defects and evaluating the extent of damage are introduced. Experiments are …
Inspire Newsletter Spring 2024, Missouri University Of Science And Technology Inspire - University Transportation Center
Inspire Newsletter Spring 2024, Missouri University Of Science And Technology Inspire - University Transportation Center
INSPIRE Newsletters
No abstract provided.
Improving Aggregate Abrasion Resistance Prediction Via Micro-Deval Test Using Ensemble Machine Learning Techniques, Alireza Roshan, Magdy Abdelrahman
Improving Aggregate Abrasion Resistance Prediction Via Micro-Deval Test Using Ensemble Machine Learning Techniques, Alireza Roshan, Magdy Abdelrahman
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Aggregate is the most extracted material from the world's mines and widely used in civil and construction projects. The Micro-Deval abrasion test (MD) is one of the most important tests that provides characteristics of crushed aggregates that show their resistance against mechanical abrasive factors such as repeated impact loading. The impact of various factors on abrasive resistance properties of aggregates has led researchers to seek correlations, often focusing on limited data samples, leading to reduced accuracy. This study employs machine learning (ML) methods to predict MD abrasion values, considering diverse aggregate properties. Various ensemble ML methods were applied, revealing the …
Effect Of Type And Quantity Of Inherent Alkali Cations On Alkali-Silica Reaction, Pengfei Ma, Jiaoli Li, Jincheng Bai, Ying Zhuo, Lingyu Chi, Yanping Zhu, Zhenhua Shi, Hongyan Ma, Genda Chen
Effect Of Type And Quantity Of Inherent Alkali Cations On Alkali-Silica Reaction, Pengfei Ma, Jiaoli Li, Jincheng Bai, Ying Zhuo, Lingyu Chi, Yanping Zhu, Zhenhua Shi, Hongyan Ma, Genda Chen
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
In this study, the macroscopical expansion induced by alkali-silica reaction (ASR) and its corresponding ASR products are investigated using ordinary Portland cement (OPC) mortar specimens with a gradient of boosted alkalis. Experimental results show that the expansion increases with the concentration of inherent alkalis. Sodium-boosted samples expand approximately three times as much as potassium-boosted samples. ASR gels that are present in aggregate veins are calcium-free and amorphous; the atomic ratios of ASR gels are nearly independent of the type and quantity of alkali cations. Aggregate ASR gel exudation occurs in high (≥2.5 %) sodium cases and produces potential Na-shlykovite. Crystalline …
Semi-Annual Progress Report #12, Missouri University Of Science And Technology. Inspire - University Transportation Center
Semi-Annual Progress Report #12, Missouri University Of Science And Technology. Inspire - University Transportation Center
Semi-Annual Progress Reports
No abstract provided.
Robotic Inspection Of Infrastructure Using Vision, Gpr, And Impact-Echo Sensors, Jizhong Xiao
Robotic Inspection Of Infrastructure Using Vision, Gpr, And Impact-Echo Sensors, Jizhong Xiao
INSPIRE Archived Webinars
Bridges, dams, highways, and tunnels in the U.S. are reaching their life expectancy, and thus have imperative needs for routine inspection and maintenance to ensure sustainability. It is reported that 42% of over 600,000 highway bridges in the National Bridge Inventory (NBI) have exceeded their design life of 50 years, and 42,951 bridges are rated in poor condition and classified as "structurally deficient". To inspect the structurally integrity of bridges, the inspectors also need to detect subsurface defects (i.e., delamination, voids) using NDE instruments such as GPR and impact-echo (IE) device at difficult to access components (i.e., pier, bottom side …
Machine Learning-Based Seismic Damage Assessment Of Residential Buildings Considering Multiple Earthquake And Structure Uncertainties, Xinzhe Yuan, Liujun Li, Haibin Zhang, Yanping Zhu, Genda Chen, Cihan H. Dagli
Machine Learning-Based Seismic Damage Assessment Of Residential Buildings Considering Multiple Earthquake And Structure Uncertainties, Xinzhe Yuan, Liujun Li, Haibin Zhang, Yanping Zhu, Genda Chen, Cihan H. Dagli
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Wood-frame structures are used in almost 90% of residential buildings in the United States. It is thus imperative to rapidly and accurately assess the damage of wood-frame structures in the wake of an earthquake event. This study aims to develop a machine-learning-based seismic classifier for a portfolio of 6,113 wood-frame structures near the New Madrid Seismic Zone (NMSZ) in which synthesized ground motions are adopted to characterize potential earthquakes. This seismic classifier, based on a multilayer perceptron (MLP), is compared with existing fragility curves developed for the same wood-frame buildings near the NMSZ. This comparative study indicates that the MLP …
Development And Characterization Of Coal-Based Thermoplastic Composite Material For Sustainable Construction, Haibin Zhang, Wenyu Liao, Genda Chen, Hongyan Ma
Development And Characterization Of Coal-Based Thermoplastic Composite Material For Sustainable Construction, Haibin Zhang, Wenyu Liao, Genda Chen, Hongyan Ma
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
The exploitation of coal and the disposal of waste plastic present significant environmental and economic challenges that require sustainable and profitable solutions. In response, we propose a renewable construction composite material of coal-based thermoplastic composite (CTC) that can be made from low-grade coal and plastic waste. We developed and tested the hot-press fabrication method for this CTC, using coal with a maximum particle size of 4.75 mm and recycled high-density polyethylene (HDPE). The effects of the coal fraction (50–80 wt.%) on compressive properties, thermal properties, microstructure, and ecological and economic efficiencies of the CTC were investigated. Test results revealed that …
A Spike-Shaped Anchorage For Steel Reinforced Polymer (Srp)-Strengthened Concrete Structures, Xingxing Zou, Keenan L. Mcburney, Lesley H. Sneed
A Spike-Shaped Anchorage For Steel Reinforced Polymer (Srp)-Strengthened Concrete Structures, Xingxing Zou, Keenan L. Mcburney, Lesley H. Sneed
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Steel reinforced polymer (SRP) composite has recently emerged as an effective and economical solution for strengthening of reinforced concrete (RC) structures. Premature debonding failure of unanchored SRP at low load levels generally governs the performance of RC structures strengthened with externally bonded SRP. Therefore, a novel yet simple spike-shaped anchorage system was proposed in this study to prevent the debonding failure of SRP and to improve the interfacial shear capacity. Experimental investigation through single-lap shear tests of SRP-concrete joints showed that the anchorage system changed the failure mode from composite debonding to fiber rupture. In addition, the anchorage system substantially …
Influence Of Support Attachment Pattern On The Out-Of-Plane Buckling Capacity Of Steel Deck, Divyansh R. Kapoor, Brian Bogh, Kara D. Peterman
Influence Of Support Attachment Pattern On The Out-Of-Plane Buckling Capacity Of Steel Deck, Divyansh R. Kapoor, Brian Bogh, Kara D. Peterman
American Iron and Steel Institute (AISI) Specifications, Standards, Manuals and Research Reports (1946 - present)
Diaphragms (Figure 1) serve as a critical component of a building's lateral force resisting system (LFRS), transferring lateral loads from the façade of the structure to the designated vertical lateral force resisting system. Design guidance for profiled steel diaphragm panels can be found in AISI S310 - 20 (AISI 2020) and SDI DDM04 (Luttrell 2015) and are controlled by connection limit states or buckling limit states. Deck connectivity with the underlying frame can either be fully attached (For example 36/7), i.e. connected through the bottom of each flute, or partially attached (for example 36/5 or 36/4) where not all the …
Coating Condition Detection And Assessment On The Steel Girder Of A Bridge Through Hyperspectral Imaging, Pengfei Ma, Jiaoli Li, Ying Zhuo, Pu Jiao, Genda Chen
Coating Condition Detection And Assessment On The Steel Girder Of A Bridge Through Hyperspectral Imaging, Pengfei Ma, Jiaoli Li, Ying Zhuo, Pu Jiao, Genda Chen
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
The organic coating of bridge steel girders is subjected to physical scratches, corrosion, and aging in natural weathering. The breakdown of the coating may cause serviceability and safety problems if left unnoticed. Conventional coating inspection is time-consuming and lacks information about the coating's chemical integrity. A hyperspectral imaging method is proposed to detect the condition of steel coatings based on coating-responsive features in reflectance spectra. A field test was conducted on the real-world bridge, which shows obvious signs of degradation. The hyperspectral signature enables an assessment of the coating's health and defect severity. The results indicated that the coating scratch …
Preliminary Bond Capacity Exploration Between Monolayer Graphene And Cementitious Composites, Yanping Zhu, Chuanrui Guo, Genda Chen
Preliminary Bond Capacity Exploration Between Monolayer Graphene And Cementitious Composites, Yanping Zhu, Chuanrui Guo, Genda Chen
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
This Study Aims to Explore Bond Capacity between Monolayer Graphene and Cementitious Composites for the First Time through a Pullout Test. the Low-Pressure Chemical Vapor Deposition Method Was Used to Synthesize Monolayer Graphene on the Copper Substrate to Be Embedded in the Mortar Made by the Briquette Mold. the Bond Capacity between Them Was Higher Than the Tensile Strength of the Copper Sheet with As-Grown Monolayer Graphene on the Surface Since All Specimens Failed in Fracture with Embedment Length of More Than 30 Mm. the Monolayer Graphene Enhanced the Copper Tensile Fracture Stress and Normalized Energy during the Test as …
Probability Of Detection In Structural Health Monitoring, Genda Chen
Probability Of Detection In Structural Health Monitoring, Genda Chen
INSPIRE Archived Webinars
The fundamental concept of the probability of detection in structural health monitoring is introduced. The traditional Probability of Detection (POD) method as described in the Department of Defense Handbook MIL-HDBK-1823A for nondestructive evaluation systems does not take the time dependency of data collection into account. When applied to in-situ sensors for the measurement of flaw sizes, such as fatigue-induced crack length and corrosion-induced mass loss, the validity and reliability of the traditional method is unknown. In this 50-minute lecture, the POD for in-situ sensors and their associated reliability assessment for detectable flaw sizes are evaluated using a Flaw-Size-at-Detection (FSaD) method …
Inspire Newsletter Spring 2023, Missouri University Of Science And Technology. Inspire - University Transportation Center
Inspire Newsletter Spring 2023, Missouri University Of Science And Technology. Inspire - University Transportation Center
INSPIRE Newsletters
No abstract provided.
Inspire Newsletter Fall 2023, Missouri University Of Science And Technology. Inspire - University Transportation Center
Inspire Newsletter Fall 2023, Missouri University Of Science And Technology. Inspire - University Transportation Center
INSPIRE Newsletters
No abstract provided.
A Deep Learning-Informed Design Scheme For Shear Friction At Concrete-To-Concrete Interface: Recommendations For Inclusion In Aashto Lrfd Guidelines, Tarutal Ghosh Mondal, Nikkolas Edgmond, Lesley Sneed, Genda Chen
A Deep Learning-Informed Design Scheme For Shear Friction At Concrete-To-Concrete Interface: Recommendations For Inclusion In Aashto Lrfd Guidelines, Tarutal Ghosh Mondal, Nikkolas Edgmond, Lesley Sneed, Genda Chen
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Recent advancements in construction technology have led to high-strength concrete and steel. However, these developments have depreciated the accuracy of the design equations in current provisions, which were based on normal-grade materials. To fill such a research gap, this study presents a novel deep learning-based computation scheme that can replace the current design provisions by virtue of its superior accuracy and reliability. The proposed approach exploits Neural Additive Models (NAMs) in which geometric and material properties associated with a normal weight concrete-to-concrete shear interface are inputted to individual neural network blocks. The outputs of the individual blocks are linearly combined …
Hardware-In-The-Loop And Digital Twin Enabled Autonomous Robotics-Assisted Environment Inspection, Johnny Li, Bo Shang, Iresh Jayawardana, Genda Chen
Hardware-In-The-Loop And Digital Twin Enabled Autonomous Robotics-Assisted Environment Inspection, Johnny Li, Bo Shang, Iresh Jayawardana, Genda Chen
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Empowered by the advanced 3D sensing, computer vision and AI algorithm, autonomous robotics provide an unprecedented possibility for close-up infrastructure environment inspection in an efficient and reliable fashion. Deep neural network (DNN) learning algorithms, pretrained on the large database can empower real-time object detection as well as fully autonomous, safe robotic navigation in unstructured environments while avoiding the potential obstacle. However, the development and deployment of the robots, inspection planning and operation procedures are still tedious and segmented with tremendous manual intervention during environmental inspection and anomaly monitoring. The proposed digital twin approach is able to provide a virtual representation …
Analyzing Ground Motion Records With Cvi Fuzzy Art, Dustin Tanksley, Xinzhe Yuan, Genda Chen, Donald C. Wunsch
Analyzing Ground Motion Records With Cvi Fuzzy Art, Dustin Tanksley, Xinzhe Yuan, Genda Chen, Donald C. Wunsch
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
This paper explores using Cluster Validity Indices Fuzzy Adaptative Resonance Theory (CVI Fuzzy ART) to cluster ground motion records (GMRs). Clustering the features extracted from a supervised network trained for predicting the structure damage results in less overfitting from the trained network. Using Cluster Validity Indices (CVIs) to evaluate the clustering gives feedback to how well the data is being classified, allowing further separation of the data. By using CVI Fuzzy ART in combination with features extracted from a trained Convolutional Neural Network (CNN), we were able to form additional clusters in the data. Within the primary clusters, accuracy was …