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Because existing buildings occupy most of our built environment, there is an urgent need to upgrade them considering building sustainability criteria. Therefore, many optimization models were proposed to find the optimum upgrading solution that improves the building sustainability while minimizing its costs using traditional sustainability rating tools [e.g., Leadership in Energy and Environmental Design (LEED) (US), Building Research Establishment Environmental Assessment Methodology (BREEAM) (UK), and others]. The variations among these tools hinder their application outside their original countries, calling for global tools. Therefore, this study contributes to the knowledge by developing a novel multiobjective optimization model to solve the life cycle cost (LCC)-sustainability trade-off for building upgrading using a generic sustainability rating tool. This tool includes seven sustainability criteria and 29 subcriteria, resulting in 134 decision variables. The proposed model finds the near-optimum upgrading solutions that minimize their LCC while improving the building sustainability using the multiobjective artificial immune system algorithm. The model was applied to a real case study of a large building in Montreal, Canada. The obtained solutions covered almost all the ratings ranges from pass to outstanding and showed the trade-offs between the building sustainability and LCC. This research is a step toward adopting a global sustainability rating tool to find the optimum building upgrading solutions that can address the regional limitations of the traditional rating tools. [ABSTRACT FROM AUTHOR]

Adoption of a suitable sewer pipeline condition classification protocol is recognized as an indispensable first step in worldwide sewer rehabilitation industry. Various condition classification systems for sewers have been developed in this regard. These systems differ according to local requirements in which no integrated and unified sewer condition assessment protocol is available. Therefore, an urgent need exists to develop standardized sewer condition assessment procedures. The presented research in this paper aims to review the historical development of different sewer condition classification protocols and develop a combined condition index (CCI) for sewers that integrates the combined effect of structural and operational conditions. To achieve these objectives, unsupervised neural network models have been developed. The CCI is divided into five condition categories ranging from 'acceptable' to 'critical.' An unsupervised, self-organizing, neural network approach is also used to develop the CCI. The opinion of municipal practitioners is utilized to verify the CCI and integrated protocol. The developed integrated models and protocols will assist municipal engineers in developing a unified sewer condition assessment system. An unsupervised neural network methodology is adapted for integrating sewer condition assessment protocols and developing the CCI of sewer pipelines. The protocols developed by the Water Research Centre (WRc), United Kingdom, and the Centre for Expertise and Research on Infrastructures in Urban Areas (CERIU), Canada, have been used for the modeling process. [ABSTRACT FROM AUTHOR]

Continuous flight auger (CFA) piles are widely used in the US and the UK as well as in many other countries. This paper focuses on developing simulation models to provide productivity and cost for various pile sizes and depths. Two simulation models were developed. Based on these models, various charts were developed to assess productivity and cost of the CFA process. Results showed that productivity is approximately 14, 24 and 93 piles (holes)/day for 0.36 m diameter piles at 21.34 m, 12.19 m, and 3.05 depths, respectively. In addition, a pile of 0.36 m diameter and 12.19 m depth costs approximately US$790.00; however, it costs approximately US$1200/pile for 21.34 m depth. For the same pile size, the cost per unit volume is approximately US$620.00/m³. The developed tools play an essential role in the CFA decision-making process. The results of simulation models are validated with an average validation factor (VF) of 1.01. This paper provides charts for practitioners' usage to schedule and price CFA pile construction projects. In addition, it provides researchers with a methodology for applying simulation to the CFA pile construction process and its limitations. [ABSTRACT FROM AUTHOR]