Mathematical Problems in Engineering

Statistical and Probabilistic Approach in Monitoring-based Structure Rating and Risk Assessment


Publishing date
16 May 2014
Status
Published
Submission deadline
27 Dec 2013

Lead Editor

1School of Civil Engineering, Dalian University of Technology, Dalian 116023, China

2School of Architecture and Civil Engineering, Xiamen University, Xiamen 361005, China

3Medway School of Engineering, The University of Greenwich Central Avenue, Chatham Maritime, Kent ME4 4TB, UK

4School of Civil Engineering, Purdue University, West Lafayette, IN 47907, USA


Statistical and Probabilistic Approach in Monitoring-based Structure Rating and Risk Assessment

Description

Aging civil infrastructural facilities like long-span bridges, super-tall buildings, and large-scale space structures that form the life of a country's economy are facing a severe crisis in some countries. Long service lives, inadequate designs, and increasing extreme loads are responsible for the current state of affairs. Thus, knowledge about the in-service condition of the structures is one of the most essential parts required for the engineering community. This opens a wide field for structural health monitoring (SHM) systems which are set up to assure the safe operation of structures requiring linking sensors with computational tools able to interpret sensor data in terms of structural performance. Although intensive development continues on innovative sensor systems, there is still considerable uncertainty in deciding structural behavior since there are many factors in abundant measured data from the SHM system that may influence the health assessment of a structure. The most appropriate and efficient way to alleviate this multiple input problem is by the statistical and probabilistic approach including data normalization, feature extraction, statistical modeling, risk management, and so forth.

Therefore, in the light of the these considerations, we invite investigators to contribute original research papers as well as review papers for this special issue that aim at becoming an international forum for researchers and practitioners to summarize the most recent advances, progress, and ideas in the field of the statistical and probabilistic approach and its application in structure rating and risk assessment; more specifically, the focus will be on parametric tests, correlation analysis, regression analysis, cluster analysis, principal component analysis, factor analysis, correlation analysis, decision tree analysis, and Bayesian, rough set, and support vector machines, and so forth. Potential topics include, but are not limited to:

  • Data compression and cleaning
  • Data mining and fusing technology
  • Pattern recognition and feature extraction
  • Damage detection and condition assessment
  • Performance prediction and risk management
  • Other related issues

Before submission authors should carefully read over the journal’s Author Guidelines, which are located at http://www.hindawi.com/journals/mpe/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/submit/journals/mpe/spa/ according to the following timetable:


Articles

  • Special Issue
  • - Volume 2014
  • - Article ID 761341
  • - Editorial

Statistical and Probabilistic Approach in Monitoring-Based Structure Rating and Risk Assessment

Ting-Hua Yi | Ying Lei | ... | Fei Kang
  • Special Issue
  • - Volume 2014
  • - Article ID 479197
  • - Research Article

Solving Parameter Identification of Nonlinear Problems by Artificial Bee Colony Algorithm

S. Talatahari | H. Mohaggeg | ... | A. Manafzadeh
  • Special Issue
  • - Volume 2014
  • - Article ID 986050
  • - Research Article

Damage Detection Based on Cross-Term Extraction from Bilinear Time-Frequency Distributions

Ma Yuchao | Yan Weiming | ... | Wang Kai
  • Special Issue
  • - Volume 2014
  • - Article ID 317954
  • - Review Article

Application of Hilbert-Huang Transform in Structural Health Monitoring: A State-of-the-Art Review

Bo Chen | Sheng-lin Zhao | Peng-yun Li
  • Special Issue
  • - Volume 2014
  • - Article ID 837963
  • - Research Article

Damage Localization of Cable-Supported Bridges Using Modal Frequency Data and Probabilistic Neural Network

X. T. Zhou | Y. Q. Ni | F. L. Zhang
  • Special Issue
  • - Volume 2014
  • - Article ID 340896
  • - Research Article

Measurement-Based Vehicle Load Model for Urban Expressway Bridges

Bin Chen | Zheng Zhong | ... | Pengzhen Lu
  • Special Issue
  • - Volume 2014
  • - Article ID 734016
  • - Research Article

Simplified Reliability Estimation for Optimum Strengthening Ratio of 30-Year-Old Double T-Beam Railway Bridge by NSM Techniques

Minkwan Ju | Hongseob Oh | Jong-Wan Sun
  • Special Issue
  • - Volume 2014
  • - Article ID 985659
  • - Research Article

Data Mining of the Thermal Performance of Cool-Pipes in Massive Concrete via In Situ Monitoring

Zheng Zuo | Yu Hu | ... | Liyuan Zhang
  • Special Issue
  • - Volume 2014
  • - Article ID 621314
  • - Research Article

A Robust Probability Classifier Based on the Modified -Distance

Yongzhi Wang | Yuli Zhang | ... | Jinli Miu
  • Special Issue
  • - Volume 2014
  • - Article ID 707969
  • - Research Article

Damage Detection for Continuous Bridge Based on Static-Dynamic Condensation and Extended Kalman Filtering

Haoxiang He | Yongwei Lv | Enzhen Han
Mathematical Problems in Engineering
 Journal metrics
Acceptance rate27%
Submission to final decision64 days
Acceptance to publication34 days
CiteScore1.800
Impact Factor1.009
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