Development of a prediction model for the proportion of buildings exposed to construction noise in excess of the construction noise regulation at urban construction sites

2021 ◽  
Vol 125 ◽  
pp. 103656
Author(s):  
Juwon Hong ◽  
Hyuna Kang ◽  
Taehoon Hong ◽  
Hyo Seon Park ◽  
Dong-Eun Lee
Keyword(s):  
Prediction Model ◽  
Construction Sites ◽  
Urban Construction

Prediction Model for Cementing Efficiency of Fly Ash Concrete by Statistical Analyses

2011 ◽  
Vol 250-253 ◽  
pp. 1293-1296 ◽  
Author(s):  
Hong Bum Cho ◽  
Nam Yong Jee
Keyword(s):  
Fly Ash ◽  
Prediction Model ◽  
Statistical Analyses ◽  
Test Results ◽  
Construction Sites ◽  
K Value ◽  
Fly Ash Concrete ◽  
Mix Proportion ◽  
Wide Range ◽  
Binder Ratio

This paper offers the model that can estimate the cementing efficiency of fly ash (k value) based on a mix proportion of concrete containing fly ash (FA). The prediction model was derived using various statistical analyses, based on a wide range of mix proportions and a number of strength test results of ready mixed concretes used in eight construction sites. The k value increases with increasing water-binder ratio. As the FA replacement ratios increase, the k value increases at FA replacement ratios of less than 15%, but decreases at ratios of 15% or more. The k values obtained from the cementing efficiency estimate model range from 0.1 to 2.1.

scholarly journals Challenges of UK/Irish contractors regarding material management and logistics in confined site construction

2011 ◽  
Vol 1 (1) ◽  
pp. 25-42 ◽  
Author(s):  
John Spillane ◽  
◽  
Lukumon Oyedele ◽  
Jason von Meding ◽  
Ashwini Konanahalli ◽  
...  
Keyword(s):  
Cognitive Mapping ◽  
Extensive Literature ◽  
Construction Site ◽  
Materials Management ◽  
Construction Sites ◽  
Material Management ◽  
Project Completion ◽  
Urban Construction ◽  
Cost Of Materials ◽  
Monetary Savings

The aim of this paper is to identify the various managerial issues encountered by UK/Irish contractors in the management of materials in confined urban construction sites. Through extensive literature review, detailed interviews, case studies, cognitive mapping, causal loop diagrams, questionnaire survey and documenting severity indices, a comprehensive insight into the materials management concerns within a confined construction site environment is envisaged and portrayed. The leading issues highlighted are: that contractors’ material spatial requirements exceed available space, it is difficult to coordinate the storage of materials in line with the programme, location of the site entrance makes delivery of materials particularly difficult, it is difficult to store materials on-site due to the lack of space, and difficult to coordinate the storage requirements of the various sub-contractors. With the continued development of confined urban centres and the increasing high cost of materials, any marginal savings made on-site would translate into significant monetary savings at project completion. Such savings would give developers a distinct competitive advantage in this challenging economic climate.As on-site management professionals successfully identify, acknowledge and counteract the numerous issues illustrated, the successful management of materials on a confined urban construction site becomes attainable.

scholarly journals Mosquito Adaptation to the Extreme Habitats of Urban Construction Sites

2019 ◽  
Vol 35 (8) ◽  
pp. 607-614 ◽  
Author(s):  
André B.B. Wilke ◽  
Alberto J. Caban-Martinez ◽  
Marco Ajelli ◽  
Chalmers Vasquez ◽  
William Petrie ◽  
...  
Keyword(s):  
Construction Sites ◽  
Urban Construction ◽  
Extreme Habitats

Strength Prediction of Fly Ash Concrete Using Cementing Efficiency by Statistical Analysis

2011 ◽  
Vol 374-377 ◽  
pp. 1774-1777
Author(s):  
Hong Bum Cho ◽  
Nam Yong Jee ◽  
Jun Ho Shin
Keyword(s):  
Compressive Strength ◽  
Fly Ash ◽  
Prediction Model ◽  
Mean Squared Error ◽  
Strength Prediction ◽  
Test Results ◽  
Construction Sites ◽  
Fly Ash Concrete ◽  
Squared Error ◽  
Wide Range

This paper offers a model that can estimate the 28-day compressive strength of concrete containing fly ash (FA) using the concept of cementing efficiency. Using various statistical analyses, the prediction model was derived from a wide range of mix proportions and a number of strength test results of concretes used in eight construction sites. A strength prediction model was proposed in terms of a function of the modified cement-water ratio reflecting the equations for cementing efficiency. This prediction model that has R2 of 0.88 and root mean squared error (RMSE) of 1.6MPa is capable of properly predicting the 28-day compressive strength within strength variation of FA concrete.

scholarly journals Use of electric resistivity tomography (ERT) for detecting underground voids on highly anthropized urban construction sites

2017 ◽  
Vol 209 ◽  
pp. 202-209 ◽  
Author(s):  
Constantin Ungureanu ◽  
Adrian Priceputu ◽  
Adrian Liviu Bugea ◽  
Anton Chirică
Keyword(s):  
Electric Resistivity ◽  
Construction Sites ◽  
Resistivity Tomography ◽  
Urban Construction

scholarly journals Predicting the Safety Climate in Construction Sites of Saudi Arabia: A Bootstrapped Multiple Ordinal Logistic Regression Modeling Approach

2021 ◽  
Vol 11 (4) ◽  
pp. 1474
Author(s):  
Anas A. Makki ◽  
Ibrahim Mosly
Keyword(s):  
Logistic Regression ◽  
Saudi Arabia ◽  
Prediction Model ◽  
Safety Climate ◽  
Prediction Models ◽  
Ordinal Logistic Regression ◽  
Decision Makers ◽  
Construction Site ◽  
Construction Sites ◽  
Ordinal Logistic Regression Model

Construction site accidents can be reduced through proactive steps using prediction models developed based on factors that influence the safety climate. In this study, a prediction model of the safety climate observed by construction site personnel in Saudi Arabia was developed, identifying a set of significant safety climate predictors. The model was built with data collected from 401 active construction site personnel using a bootstrapped multiple ordinal logistic regression model. The model revealed five significant predictors: supervision, guidance, and inspection; social security and health insurance; management’s commitment to safety; management’s safety justice; and coworker influence. The model can correctly predict 67% of the safety evaluations. The identified predictors present proof of the importance of safety support, commitment, and interaction in construction sites and their influence on the perceived evaluations of the safety climate by personnel. Moreover, the prediction model can help construction industry decision makers, safety policy designers, government agencies, and stakeholders to estimate the safety climate and assess the current situation. Furthermore, the model can help form a better understanding and determine areas of improvement, which can translate into higher safety performance levels.

1575: External Validation of Outcome Prediction Model for Ureteral/Renal Calculi

2005 ◽  
Vol 173 (4S) ◽  
pp. 427-427
Author(s):  
Sijo J. Parekattil ◽  
Udaya Kumar ◽  
Nicholas J. Hegarty ◽  
Clay Williams ◽  
Tara Allen ◽  
...  
Keyword(s):  
Prediction Model ◽  
Outcome Prediction ◽  
External Validation ◽  
Renal Calculi
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