Developing a Systematic Approach to Evaluate and Predict Building Service Life

Chen, Chien-Jung; Juan, Yi‐Kai; Hsu, Yin-Hao

doi:10.3846/13923730.2017.1341956

Cited by 24 publications

(16 citation statements)

References 34 publications

(32 reference statements)

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“…The most popular hybrid MCDM methods demonstrate the advantages over traditional ones to solve complicated problems which involve stakeholder preferences, interconnected or contradictory criteria, and uncertain environments. Decision-makers could use multi-criteria decision-making methods [46] such as analytic hierarchy process [47], fuzzy analytic hierarchy process [48,49], fuzzy Delphi [50], analytic network process under intuitionistic fuzzy set [51], Additive Ratio Assessment (ARAS) [52], simple additive weighting and game theory [53], discrete two persons' zero-sum matrix game theory [54], Evaluation based on Distance from Average Solution (EDAS), COPRAS, TOPSIS [55], as well as developing original models [56].…”

Section: Multi-criteria Methods and Construction Managementmentioning

confidence: 99%

A Multi-Criteria Decision-Making Model to Choose the Best Option for Sustainable Construction Management

2019

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The article briefly discusses the content and terms of construction project management. It identifies the main problems of construction management and discusses ways to solve those using multi-criteria methods. Well-performed management is one of the critical factors which leads to the success of any significant sustainable project. Construction project management consists of setting goals and defining user requirements, project constraints, and resources needed. This paper aims to create a practically useful model. The paper presents a comprehensive set of criteria, which led to the creation of a decision-making model for construction management, which was applied to a Turkish case study. The Analytic Hierarchy Process (AHP) method and the Expert Choice computer program were used for calculations.

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Section: Multi-criteria Methods and Construction Managementmentioning

confidence: 99%

A Multi-Criteria Decision-Making Model to Choose the Best Option for Sustainable Construction Management

2019

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“…In addition, the accelerated tests are quite expensive. There are also some other approaches to predict SL by considering service life models and obsolescence factors [1,34]. This method can be used for existing buildings or to be built buildings with the same material.…”

Section: Authormentioning

confidence: 99%

Impact of Service Life on the Environmental Performance of Buildings

2019

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The environmental performance assessment of the building and construction sector has been in discussion due to the increasing demand of facilities and its impact on the environment. The life cycle studies carried out over the last decade have mostly used an approximate life span of a building without considering the building component replacement requirements and their service life. This limitation results in unreliable outcomes and a huge volume of materials going to landfill. This study was performed to develop a relationship between the service life of a building and building components, and their impact on environmental performance. Twelve building combinations were modelled by considering two types of roof frames, two types of wall and three types of footings. A reference building of a 50-year service life was used in comparisons. Firstly, the service life of the building and building components and the replacement intervals of building components during active service life were estimated. The environmental life cycle assessment (ELCA) was carried out for all the buildings and results are presented on a yearly basis in order to study the impact of service life. The region-specific impact categories of cumulative energy demand, greenhouse gas emissions, water consumption and land use are used to assess the environmental performance of buildings. The analysis shows that the environmental performance of buildings is affected by the service life of a building and the replacement intervals of building components.

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“…According to the literature (Chen et al, 2017), the reinforcement corrosion is mainly related to the diameter of the steel bar, the thickness of the protective layer, the strength of the concrete, and the width of the rust crack.…”

Section: Neural Network Model For Prediction Of Reinforcement Corrosimentioning

confidence: 99%

Prediction of Concrete Structure Service Life Based on the Principle of Neural Connections in Brain Circuits

Zhou¹,

Gao²,

Fan³

et al. 2018

Neuroquantology

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Concrete is the most widely used structural material in the world; however, its structural safety is affected by concrete carbonization and reinforcement corrosion. According to the principles and characteristics of concrete carbonization and reinforcement corrosion, this paper establishes artificial neural network prediction and evaluation models for the depth of carbonization and the degree of reinforcement corrosion based on the principle of neural connections in brain circuits. The results show that the artificial neural network prediction models are of high accuracy, and that the RBF neural network prediction model is more accurate and requires far less training time than the BP neural network model.

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Developing a Systematic Approach to Evaluate and Predict Building Service Life

Cited by 24 publications

References 34 publications

A Multi-Criteria Decision-Making Model to Choose the Best Option for Sustainable Construction Management

A Multi-Criteria Decision-Making Model to Choose the Best Option for Sustainable Construction Management

Impact of Service Life on the Environmental Performance of Buildings

Prediction of Concrete Structure Service Life Based on the Principle of Neural Connections in Brain Circuits

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