Fragility Analysis of Rectangular and Circular Reinforced Concrete Columns under Bidirectional Multiple Excitations

The aim of this study is to investigate the dynamic performance of rectangular and circular reinforced concrete (RC) columns considering biaxial multiple excitations. For this purpose, an advanced nonlinear finite element model which can simulate various features of cyclic degradation in material and structural components is used. The implemented nonlinear fiber beam-column model accounts for inelastic buckling and low-cycle fatigue degradation of longitudinal reinforcement and can simulate multiple failure modes of RC columns under dynamic loading. Hypothetical rectangular and circular columns are used to investigate the failure modes of RC columns. A detailed ground motion selection is implemented to generate real mainshock and aftershocks. It was found that multiple excitations due to aftershock has the potential of increasing the damage of the RC columns and longitudinal reinforcements are significantly affected low-cycle fatigue. Also, it was found that rectangular column is more sensitive to accumulative damage due to cyclic fatigue. This study increases the accuracy of structural analysis of RC columns and consequently improves understanding the failure modes of RC columns with different cross-sectional shapes.

The Behavior of Rectangular and Circular Reinforced Concrete Columns under Biaxial Multiple Excitation

Surrogate-assisted finite element model updating for detecting scour depths in a continuous bridge

Accurately identifying the axle loads of the moving train on the railway bridge can provide reliable information for assessing the safety of the train–bridge system. Bridge weigh-in-motion, namely, BWIM, is an effective approach for identifying the positions and weights of the train axles based on the monitored bridge responses. Existing BWIM methods generally focus on identifying the probable value of the axle weights instead of quantifying the identification uncertainty. To address this issue, a novel two-stage train load identification framework for the medium-small railway bridge is developed by combining the virtual axle theory and Bayesian inference. In the first stage, the axle configuration including the axle number, axle spacing and axle weight of the moving train, are estimated according to the modified virtual axle theory in which a clustering algorithm is embedded to automatically determine the axle number. In the second stage, the most probable value (MPV) and the uncertainty of the train axle weight are accurately identified using the Bayesian inference method which takes five types of error patterns into consideration. Finally, the proposed framework is verified using the data from numerical simulations and an in-situ railway bridge. Results show that the proposed framework can improve the accuracy of train load identification after quantifying the uncertainty of estimated axle weights and can confirm the confidence interval of the individual axle weight and gross train weight. 

Train load identification of the medium-small railway bridge using virtual axle theory and Bayesian inference

Foundation scour poses a serious threat to bridge safety in the whole life cycle and leads to many bridge failure incidents. Recently, as an important subfield of bridge structural health monitoring, vibration-based scour diagnosis methods have garnered widespread attention, particularly due to their rapid and low-cost features, which overcomes the difficulties of complex equipment installation associated with the traditional approaches. Recent advances of this method within the last decade are reviewed in this paper. Firstly, the principle of scour diagnosis and vibration excitation methods are introduced. Then, existing qualitative and quantitative studies on scour diagnosis are reviewed, respectively. The former refers to identifying the scour location based on the bridge dynamic characteristics or dynamic response changes, and the latter refers to identifying scour depth based on model updating or machine learning methods. Based on the above review, some important but neglected issues are summarized and discussed in depth, and some challenges and future trends are proposed, including innovative excitation methods, mitigation of environmental conditions interference, soil–structure interaction prediction and application of machine learning techniques.

/pdf/a-review-of-vibration-based-scour-diagnosis-methods-for-2sqislbg.pdf

A Review of Vibration-Based Scour Diagnosis Methods for Bridge Foundation

Several innovative scour diagnostic indexes are proposed based on the cross-correlation analysis for bridge dynamic response excited by vehicle braking. Firstly, a vehicle-bridge coupled vibration model considering vehicle braking is established and its accuracy is verified by a field loading test. Secondly, the fixed shape characteristic of cross-correlation function amplitude vector of the braking-induced dynamic response is theoretically deduced and verified numerically with a continuous girder bridge example considering various test parameters, which is the basic for scour diagnosis. Further, two scour diagnostic indexes are proposed, one is the cross-correlation function amplitude change rate vector, which is used to identify the scour location with a threshold of 2%, and the other is the transversal cross-correlation function amplitude change rate vector, which is used to identify the scour uniformity. The good applicability and accuracy of proposed indexes for different scour states is verified by numerical simulation for above bridge example. The proposed diagnostic indexes are very sensitive to foundation scour and have strong error tolerance for test parameters. The dynamic response required for scour diagnosis can be obtained with regular bridge loading test.

Scour diagnosis index based on cross-correlation analysis of bridge dynamic response under vehicle braking

To investigate the seismic behavior of RC columns under bidirectional lateral loading, numerical analysis for tests of RC columns under biaxial loading were performed using fiber model. The simulation results agreed well with test results. The effect of axial compression ratio on the seismic behavior of RC columns under biaxial lateral load was analyzed. The analytical results showed that biaxial lateral loading had little effect on critical axial compression ratio, and the value of critical axial compression ratio was between 0.4~0.5. Bevel carrying capacity under bidirectional lateral loading was a little greater than that under principal axial loading when axial compression ratio was less than 0.1. There had been about 10 percent decrease in bevel carrying capacity at critical axial compression ratio but principal axial bearing capacity declined about 35 percent. Moreover, ultimate displacement angle and accumulative hysteretic dissipation energy decreased observably with increase of axial compression ratio. The adverse influence of special effect on principal axis should be considered in the actual design.

Simulation of Seismic Behavior for RC Columns under Bidirectional Compression-Bending

A highly efficient and accurate mapping relationship model of subgrade disease and track geometry is significant for determining criterion of subgrade deformation and evaluating operation safety of High-speed Railway. In this paper, an innovative spatial mapping relationship model (SMRM) is proposed for describing track spatial geometry under subgrade disease of differential settlement and frost heave. Starting from analysing the theoretical interaction mechanism between subgrade and ballastless track, and presenting the flowchart of SMRM and its implementation process are described in detail. The good accuracy and applicability of SMRM method is verified based on the finite element model (FEM) and scale model experiment. The results indicate that it can better simulate the spatial characteristic of above mapping relationship than traditional theoretical model and avoid complicated and time-consuming FEM analysis process. It has high accuracy and reliability for the most application scenarios. The proposed method also can analyse the influences of others’ diseases on track geometry as long as the disease description function is available.

Spatial mapping relationship model of subgrade disease and track geometry for high-Speed railway

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Yan Jun Li

Author Tools

Chat about Author

Papers

Scour diagnosis index based on cross-correlation analysis of bridge dynamic response under vehicle braking

Simulation of Seismic Behavior for RC Columns under Bidirectional Compression-Bending

A Review of Vibration-Based Scour Diagnosis Methods for Bridge Foundation

Spatial mapping relationship model of subgrade disease and track geometry for high-Speed railway