This study discusses the potential areas for productivity improvement in roofing construction. In order to achieve the project objectives, a survey was designed and sent to roofing companies in the Midwestern United States. Of the 78 questionnaires sent, 20 were returned. On-site interviews were also arranged to visit the roofing job sites for additional information. The study results indicated that the productivity in roofing construction has been estimated by taking the number of hours worked per day or week and dividing that value into the square footage of work completed. Another finding was that better planning, scheduling, and communication were claiming to have the highest potential for increasing productivity in the roofing industry. The roofing contractors have utilized good employer/employee relationships. Camaraderie among crew members within their firms to maintain a high level of productivity. The managers stated that weather and poor communication were the main reasons for lost productivity, whereas field workers pointed out that the roof pitch, height, and age of the roof along with weather were the major causes for the lack of productivity in their job-sites. Roofing contractors generally incorporate safety to achieve higher productivity, but they may not consider safety as a high priority in their business. The results of other findings are also discussed in detail.

The aim of this multidisciplinary work is to assess the potentiality of remote sensing multispectral infrared, visible imaging spectrometer (MIVIS) data classified for mapping asbestos-cement roofing. In order to validate the methodology, measurement were carried out on the ground in order to later verify the results between the processed data and reality. All roofs classified as asbestos-cement were then sampled. Analysed by phase contrast optical microscopy and/or scanning electron microscopy. The average classification accuracy obtained corresponds to 89.1%, and the classification accuracy of the test pixels of asbestos-cement is equal to 94.3%. Only 5.7% of pixels were misclassified. Information about the presence of asbestos-cement in the studied area has been also collected. The asbestos-cement surfaces of buildings vary from 100 to 5,000 m2, totalling to 30,800 m2, which is approximately 400,400 kg of asbestos surfaces in an area of 5.2 km2. The integration of these techniques, resulting from both MIVIS data classification and the results provided by laboratory analyses of the roofs samples, in particular from those not detected by processing MIVIS data, allowed the validation and improvement of this method, and the possibility to develop researches specifically aimed at highlighting the state of alteration of asbestos-cement surfaces. Regardless of these encouraging results, further testing in different areas is still needed in order to improve the methodology developed.

Mahendran, Mahen (1990) Fatigue behaviour of corrugated roofing under cyclic wind loading. Technical Report / Cyclone Testing Station. James Cook University, Townsville, QLD. Citation counts are sourced monthly from Scopus. Web of Science® citation databases. These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database. No count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards. Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search. Full-text downloads displays the total number of times this work's files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

Impervious surface discrimination and mapping are important in urban and environmental studies. Confusion in discriminating urban materials using multispectral systems has led to the use of hyperspectral remote sensing data as an effective way to improve urban analysis. However, the high dimensionality of these data needs to be reduced to extract significant wavelengths useful in roof discrimination. Therefore, this research used feature selection algorithms of the support vector machine (SVM), genetic algorithm (GA), and random forest (RF) to select the most significant wavelengths, and the separability between classes was assessed using the SVM classification. Accordingly, the visible, shortwave infrared-1, and shortwave infrared-2 regions were most important in distinguishing different roofing materials and conditions. A comparative analysis of the feature selection models showed that the highest accuracy of 97.53% was obtained using significant wavelengths produced by RF. Accuracy of spectra without feature selection was also investigated, and the result was lower compared with classification using significant wavelengths, except for the accuracy of roof type classification, which produced an accuracy similar to SVM and GA (96.30%). This study offers new insight into within-class urban spectral classification, and the results may be used as the basis for the development of urban material indices in the future.

By applying finite element modeling the table size effect was investigated. Rain Gutters San Pedro were benchmarked with experimental data. The validated model was further used to identify the required table width. It was found that an increase in the table width beyond the required table width did not significantly change the system response. The required table width depends mainly on two system parameters, namely, fastener row spacing and fastener spacing. Based on the parametric investigation generalized correction factor curves were developed such that the roofing designer can apply these factors irrespective of the investigated table width. In MAS, the fluttering or "billowing" action of the membrane draws air into the system, thereby affecting the system's wind uplift performance. There is no standard specification or test method available to quantify the air leakage rate. By designing an experimental setup, systems with and without barriers were investigated. Data clearly indicate that systems without barrier had a high rate of air leakage, compared to systems with barrier. With the quantification of air leakage, its impact on the wind uplift resistance was also evaluated under a dynamic wind environment. Improvement in wind uplift resistance was evident for systems with barriers.