Engineering Commons^™

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 …

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

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 …

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 …

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, …

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 Reports

No abstract provided.

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

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

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

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

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 …

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 …

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 …

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 Newsletters

No abstract provided.

Inspire Newsletter Fall 2023, Missouri University Of Science And Technology. Inspire - University Transportation Center

INSPIRE Newsletters

No abstract provided.

Deep Reinforcement Learning For Approximate Policy Iteration: Convergence Analysis And A Post-Earthquake Disaster Response Case Study, Abhijit Gosavi, L. (Lesley) H. Sneed, L. A. Spearing

Engineering Management and Systems Engineering Faculty Research & Creative Works

Approximate Policy Iteration (API) is a Class of Reinforcement Learning (RL) Algorithms that Seek to Solve the Long-Run Discounted Reward Markov Decision Process (MDP), Via the Policy Iteration Paradigm, Without Learning the Transition Model in the Underlying Bellman Equation. Unfortunately, These Algorithms Suffer from a Defect Known as Chattering in Which the Solution (Policy) Delivered in Each Iteration of the Algorithm Oscillates between Improved and Worsened Policies, Leading to Sub-Optimal Behavior. Two Causes for This that Have Been Traced to the Crucial Policy Improvement Step Are: (I) the Inaccuracies in the Policy Improvement Function and (Ii) the Exploration/exploitation Tradeoff Integral …

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

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

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 …

Semi-Annual Progress Report #11, Missouri University Of Science And Technology. Inspire - University Transportation Center

Semi-Annual Progress Reports

No abstract provided.

Reliability Of Bridge Inspection Technologies, Glenn A. Washer

INSPIRE Archived Webinars

This presentation will discuss the reliability of inspection technologies used for the condition assessment of highway bridges. Data from condition assessments are critical to asset management and decision-making. The methodologies used to assess condition are usually subjective methods, such as visual inspections, that can vary as a result of human factors and differences in training and interpretation of inspection procedures. Nondestructive evaluation technologies (NDE) are implemented on a more limited basis and rely on indirect measurements to infer the presence of damage, and these assessments are affected by environmental factors, materials variability, and limitations in the interpretation of the resulting …

2022 Technical Program, Inspire - University Transportation Center

INSPIRE-UTC Annual Meetings

INSPIRE University Transportation Center 2022 Annual Meeting
August 1-2, 2022

Structural Design For Fire Conditions Of A Prototype Metal Building Using The New Proposed Appendix To Aisi S100, Xia Yan, Thomas Gernay

American Iron and Steel Institute (AISI) Specifications, Standards, Manuals and Research Reports (1946 - present)

Performance-based design for fire conditions has been increasingly adopted for different structural systems over the last decade. The objective of this project is to exemplify through a case study how the newly proposed Appendix 4 to AISI S100 [1] on ‘Structural Design for Fire Conditions’ could be used by the metal building industry. The scope of work on the project includes the following:

(1) Identification of a prototype metal building to serve as an exemplar case study for the structural fire design procedure.

(2) Definition of the performance objectives and design requirements for the building in the fire situation. This …

Semi-Annual Progress Report #10, Missouri University Of Science And Technology. Inspire - University Transportation Center

Semi-Annual Progress Reports

No abstract provided.

Structural Health Monitoring: From Virtual Shakers To Machine Learning, Ahsan Kareem

Abbett Distinguished Seminar Series

Structural health monitoring (SHM) is a critical means of assessing the performance of aging civil infrastructure. Earlier studies used heavy dynamic shakers to assess the dynamics of structures, which are unwieldy and reliance has been shifted to ambient vibration of structures to extract dynamic features. This study introduces a “virtual shaker” concept that effectively replaces the physical shaker and provides all the desired features for SHM. Examples are provided along with an App that facilitates the use of this concept to identify dynamic features. A traditional structural health monitoring (SHM) operation requires a wired system, which is often termed “hub …

Fast Forest Fire Smoke Detection Using Mvmnet, Yaowen Hu, Jialei Zhan, Guoxiong Zhou, Aibin Chen, Weiwei Cai, Kun Guo, Yahui Hu, Liujun Li

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Forest fires are a huge ecological hazard, and smoke is an early characteristic of forest fires. Smoke is present only in a tiny region in images that are captured in the early stages of smoke occurrence or when the smoke is far from the camera. Furthermore, smoke dispersal is uneven, and the background environment is complicated and changing, thereby leading to inconspicuous pixel-based features that complicate smoke detection. In this paper, we propose a detection method called multioriented detection based on a value conversion-attention mechanism module and Mixed-NMS (MVMNet). First, a multioriented detection method is proposed. In contrast to traditional …

Toward Dexterous Aerial Manipulation Using Embodied Human-Intelligence For Bridge Inspection And Maintenance, Dongbin Kim

INSPIRE Archived Webinars

Current drones perform a wide variety of tasks in surveillance, photography, agriculture, package delivery, etc. However, these tasks are performed passively without the use of human interaction. Aerial manipulation shifts this paradigm and implements drones with robotic arms that allow interaction with the environment rather than simply sensing it. Many research groups have demonstrated aerial manipulation for various applications for over a decade. For example, in construction, aerial manipulation in conjunction with human interaction could allow operators to perform several tasks, such as hosing decks, drill into surfaces, and sealing cracks via a drone. This integration with drones will henceforth …

Bc-Dunet-Based Segmentation Of Fine Cracks In Bridges Under A Complex Background, Tao Liu, Liangji Zhang, Guoxiong Zhou, Weiwei Cai, Chuang Cai, Liujun Li

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Crack is the external expression form of potential safety risks in bridge construction. Currently, automatic detection and segmentation of bridge cracks remains the top priority of civil engineers. With the development of image segmentation techniques based on convolutional neural networks, new opportunities emerge in bridge crack detection. Traditional bridge crack detection methods are vulnerable to complex background and small cracks, which is difficult to achieve effective segmentation. This study presents a bridge crack segmentation method based on a densely connected U-Net network (BC-DUnet) with a background elimination module and cross-attention mechanism. First, a dense connected feature extraction model (DCFEM) integrating …