A STUDY ON ESTIMATION METHODS OF LIFE SPAN OF BUILDINGS : The case of the "K" city public buildings

Choi, Junyoung; Okada, Kunihide; Kashihara, Shiro; Yoshimura, Hidetoshi; Yokota, Takashi

doi:10.3130/aijax.402.0_87

Cited by 3 publications

(1 citation statement)

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“…This methodology was employed by Kato and Komatsu (1986), Choi and colleagues (1989), Yashiro and colleagues (1990), Hagishima and colleagues (2002), Oikawa and Urabe (2002), and Fujikawa and colleagues (2006) for estimating the lifespan distribution of buildings. This methodology was also employed for capital stock accounts (e.g., Erumban 2008).…”

Section: A Review Of Methodologies For Estimating Lifespan Distributionmentioning

confidence: 99%

Lifespan of Commodities, Part II

Oguchi

Murakami

Tasaki

et al. 2010

J of Industrial Ecology

113

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Summary Lifespan of commodities is essential information for material flow analysis and material stock accounting. Lifespan data is available in the literature; however, it varies in definition and in methodology employed. This article reviews and categorizes different types of lifespan distribution and distribution estimation methodologies, and investigates the relationship and differences between lifespan definitions and estimation methodologies. Lifespan distribution of commodities can be classified into five types from two perspectives: base year for which the distribution is drawn, and vertical axis of the distribution. The methodologies for estimating lifespan distribution were classified into four types and the details of each methodology and the relationship to the definition of lifespan were also clarified. This article also examines differences in actual lifespan data—between the types of distribution, the definitions, and the employed methodologies—by comparing reported data in literature. Any of the four methodologies are theoretically applicable and provide the same value of a lifespan; however unless accurate data such as census statistics are available, lifespan data can vary, and therefore we must be very cautious about the representativeness of sample data.

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Section: A Review Of Methodologies For Estimating Lifespan Distributionmentioning

confidence: 99%

Lifespan of Commodities, Part II

Oguchi

Murakami

Tasaki

et al. 2010

J of Industrial Ecology

113

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Estimation of Exterior Wall Refurbishment Cycle of Detached Houses Using Propotional Hazard Model

Saito¹,

Fukao²,

Kadowaki³

2008

Transactions of AIJ

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The purpose of this research is to clarify the specifi cation and evaluation of a factor which affects presumption of an exterior wall refurbishment cycle by using a proportional hazard model. Covariates affecting exterior wall refurbishment were "Lath-mortar" and an "Area". A Congested area of wooden built-up area has a long refurbishment cycle, and lath-mortar tends to shorten a refurbishment cycle. Moreover, an exterior wall refurbishment cycle will tend to become short if the number of times of repair increases, and it became clear that there is no difference of the refurbishment cycle by a construction age.

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Factors of Closing of Public Cultural Hall

Katsumata

2022

AIJ J. Technol. Des.

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A STUDY ON ESTIMATION METHODS OF LIFE SPAN OF BUILDINGS : The case of the "K" city public buildings

Cited by 3 publications

References 0 publications

Lifespan of Commodities, Part II

Lifespan of Commodities, Part II

Estimation of Exterior Wall Refurbishment Cycle of Detached Houses Using Propotional Hazard Model

Factors of Closing of Public Cultural Hall

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