Abstracts – Browse Results
Click on the titles below to expand the information about each abstract.
Viewing 10 results ...
Al Haj, R A and El-Sayegh, S M (2015) Time–Cost Optimization Model Considering Float-Consumption Impact. Journal of Construction Engineering and Management, 141(05).
Bijleveld, F R, Miller, S R and Dorée, A G (2015) Making Operational Strategies of Asphalt Teams Explicit to Reduce Process Variability. Journal of Construction Engineering and Management, 141(05).
Che Ibrahim, C K I, Costello, S B and Wilkinson, S (2015) A Fuzzy Approach to Developing Scales for Performance Levels of Alliance Team Integration Assessment. Journal of Construction Engineering and Management, 141(05).
Fitch, G J, Odeh, I and William Ibbs, C (2015) Economic Sustainability of DBO Water Based on Wastewater Projects in the U.S.: Three Case Studies. Journal of Construction Engineering and Management, 141(05).
Jablonowski, C J (2015) Quantitative Method to Model the Underreporting of Safety Incidents. Journal of Construction Engineering and Management, 141(05).
Jafarzadeh, R, Ingham, J M, Walsh, K Q, Hassani, N and Ghodrati Amiri, G R (2015) Using Statistical Regression Analysis to Establish Construction Cost Models for Seismic Retrofit of Confined Masonry Buildings. Journal of Construction Engineering and Management, 141(05).
- Type: Journal Article
- Keywords: Confined masonry buildings; Unreinforced masonry walls; Seismic retrofit; Construction cost; Prediction; Regression analysis; Cost and schedule;
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000968
- Abstract:
The presented research deals with the development of statistical models for predicting seismic retrofit net construction cost (RNCC) of confined masonry (CM) buildings. Real data from 183 CM school buildings in Iran were collected to establish the RNCC and its determinant variables, among which two were unprecedented in the literature: (1) mortar quality, and (2) the concrete quality of confinement elements. Parametric models were developed using the stepwise regression technique, and the leave-one-out cross-validation technique was utilized to examine the predictive performance of these models. Four variables were selected that collectively best predicted the RNCC variation: (1) total floor area, (2) seismic weight indicator, (3) floor and roof diaphragm type, and (4) mortar quality. On the basis of this selection, similarities and discrepancies between the RNCC prediction of framed and CM structures were described, with dissimilarities being postulated to arise from different seismic evaluation and strengthening approaches practiced for these structures. Finally, the importance of the total floor area for the RNCC prediction of CM buildings was highlighted, with the double-log cost-area model being recommended for making this prediction at an early design stage of seismic retrofitting.
Lin, S (2015) An Analysis for Construction Engineering Networks. Journal of Construction Engineering and Management, 141(05).
Rodríguez-Garzón, I, Lucas-Ruiz, V, Martínez-Fiestas, M and Delgado-Padial, A (2015) Association between Perceived Risk and Training in the Construction Industry. Journal of Construction Engineering and Management, 141(05).
Shahtaheri, M, Nasir, H and Haas, C T (2015) Setting Baseline Rates for On-Site Work Categories in the Construction Industry. Journal of Construction Engineering and Management, 141(05).
Zhang, P, Lingard, H, Blismas, N, Wakefield, R and Kleiner, B (2015) Work-Health and Safety-Risk Perceptions of Construction-Industry Stakeholders Using Photograph-Based Q Methodology. Journal of Construction Engineering and Management, 141(05).