Soft computing in estimating the compressive strength for high-performance concrete via concrete composition appraisal

Date: 10 October, 2020

This study investigates the predictive performance of Concrete Compressive Strength (CCS) for high-performance, based on concrete mixture constituents and proportioning. A new ensemble computational technique – Boosting Smooth Transition regression trees (BooST), is adopted and compared with other contemporary methods for higher predictive accuracy and analyses.

Analysis of Magnetic-Flux Leakage (MFL) Data for Pipeline Corrosion Assessment

Date: 17 March, 2020

For corrosion prediction, this article investigates multiple MFL data matching methods, which align defects from successive in-line inspection (ILI) runs. Subsequently, corrosion growth models, which aim to predict the future corrosion status, are presented. Besides, the reliability analysis of the corroded pipeline is reviewed. The potential of fusing MFL with other non-destructive testing (NDT) techniques are explored as well. At the end of this article, we summarize the existing issues and describe the trends for future research on pipeline corrosion assessment.

Applied computational analyses for concrete compressive strength performance assessment

Date: 09 September, 2019

The first study investigates the possibility to explore concrete mixture design to produce favorable and optimal compressive strength results for situations where some experimental tests may be difficult to run due to challenges in obtaining certain constituents which may be expensive or not readily available. With intentions to reduce the need for preparing a large number of trial mixes to avoid material wastage, a simple statistical approach for concrete mixture design via a response surface method was proposed to overcome this drawback.



In the second study, a series of ensemble meta-algorithms were employed to investigate the performance of concrete compressive strength with considered concrete features.  A section of this study further tests the sensitivity analysis on concrete relative to the complex variables used in evaluating its compressive strength. Sections of these studies employed diverse feature engineering principles that span across linear and quadratic relationships between a series of variables with which the compressive strength of concrete were obtained using their correlation coefficients.

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Parameterizing Magnetic Flux Leakage Data for Pipeline Corrosion Defect Retrieval

Date: 12 June, 2019

 In this study, the concept of MFL data parameterization is proposed first. Parameterization is a contextual defect representation, which considers both corrosion defect and its surroundings to deal with the signal interference. Besides, one two-dimensional Gaussian function is introduced to denote the interference strength, and three parameterization models are then developed to obtain a reliable representation of corrosion defect. In the end, two experiments on corrosion defect retrieval are conducted to evaluate the performance of three parameterization models.

Concrete performance prediction using boosting smooth transition regression trees (BooST)

Date: 01 April, 2019

The compressive strength of concrete structure is always influenced by the composition of varied materials, casting process, and curing period, etc. Among these variables, an optimal mix of different materials will achieve better structural compressive strength. Thus, understanding the non-linearity of concrete and its variables is paramount for improving and predicting the performance of concrete structures. In this study, a predictive analysis was carried out to investigate the performance of concrete compressive strength at 28 days with a new machine learning model called boosting smooth transition regression trees (BooST).

Contributions of the Weakness of Local Aggregates to the Failure of Buildings in Anambra State of Nigeria

Date: 01 December, 2014

There appears to be an increase in the frequency of building collapse in Nigeria,especially in Anambra state where the Governor recently opened what is widely believed to be the first building and construction materials quality control laboratory in Nigeria. This was to ensure that substandard materials are not used in construction.

This research paper investigated the contributions of the weakness of substandard local broken stone aggregates (commonly used in the study area as a substitute for granite chippings) to the incessant collapse of buildings. Part of this study revealed that impurities in the particular local broken stone aggregates accounted for about 16% of the weakness contributing to the concrete used.


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