The aim of this study is to develop a BIM-based Whole-life Performance Estimator (BWPE) for appraising the salvage performance of structural components of buildings right from the design stage. A review of the extant literature was carried out to identify factors that influence salvage performance of structural components of buildings during their useful life. Thereafter, a mathematical modelling approach was adopted to develop BWPE using the identified factors and principle/concept of Weibull reliability distribution for manufactured products. The model was implemented in Building Information Modelling (BIM) environment and it was tested using case study design. Accordingly, the whole-life salvage performance profiles of the case study building were generated. The results show that building design with steel structure, demountable connections, and prefabricated assemblies produce recoverable materials that are mostly reusable. The study reveals that BWPE is an objective means for determining how much of recoverable materials from buildings are reusable and recyclable at the end of its useful life. BWPE will therefore provide a decision support mechanism for the architects and designers to analyse the implication of designs decision on the salvage performance of buildings over time. It will also be useful to the demolition engineers and consultants to generate pre-demolition audit when the building gets to end of its life.

/pdf/salvaging-building-materials-in-a-circular-economy-a-bim-24vn987fb9.pdf

Salvaging building materials in a circular economy: A BIM-based whole-life performance estimator

Modifications of the Weibull distribution: A review

/pdf/review-m-r-leadbetter-georg-lindgren-and-holger-rootzen-2flt32nd9c.pdf

Review: M. R. Leadbetter, Georg Lindgren and Holger Rootzen, Extremes and related properties of random sequences and processes

In this paper a comprehensive survey of the different methods of generating discrete probability distributions as analogues of continuous probability distributions is presented along with their applications in construction of new discrete distributions. The methods are classified based on different criterion of discretization.

/pdf/generating-discrete-analogues-of-continuous-probability-3mp3pr9ikt.pdf

Generating discrete analogues of continuous probability distributions-A survey of methods and constructions

Disassembly and deconstruction analytics system (D-DAS) for construction in a circular economy

A new modified Weibull distribution

A three-parameter discrete distribution is introduced based on a recent modification of the continuous Weibull distribution. It is one of only three discrete distributions allowing for bathtub shaped hazard rate functions. We study some of its mathematical properties, discuss estimation by the method of maximum likelihood, and describe applications to four real data sets. The new distribution is shown to outperform at least three other models including those allowing for bathtub shaped hazard rate functions.

A New Discrete Modified Weibull Distribution

The generalized log-logistic distribution is especially useful for modelling survival data with variable hazard rate shapes because it extends the log-logistic distribution by adding an extra parameter to the classical distribution, resulting in greater flexibility in analyzing and modelling various data types. We derive the fundamental mathematical and statistical properties of the proposed distribution in this paper. Many well-known lifetime special submodels are included in the proposed distribution, including the Weibull, log-logistic, exponential, and Burr XII distributions. The maximum likelihood method was used to estimate the unknown parameters of the proposed distribution, and a Monte Carlo simulation study was run to assess the estimators' performance. This distribution is significant because it can model both monotone and nonmonotone hazard rate functions, which are quite common in survival and reliability data analysis. Furthermore, the proposed distribution's flexibility and usefulness are demonstrated in a real-world data set and compared to its submodels, the Weibull, log-logistic, and Burr XII distributions, as well as other three-parameter parametric survival distributions, such as the exponentiated Weibull distribution, the three-parameter log-normal distribution, the three-parameter (or the shifted) log-logistic distribution, the three-parameter gamma distribution, and an exponentiated Weibull distribution. The proposed distribution is plausible, according to the goodness-of-fit, log-likelihood, and information criterion values. Finally, for the data set, Bayesian inference and Gibb's sampling performance are used to compute the approximate Bayes estimates as well as the highest posterior density credible intervals, and the convergence diagnostic techniques based on Markov chain Monte Carlo techniques were used.

/pdf/bayesian-and-classical-inference-for-the-generalized-log-ijgn8ql485.pdf

Bayesian and Classical Inference for the Generalized Log-Logistic Distribution with Applications to Survival Data.

The author proposes a reduced version, with three parameters, of the new modified Weibull (NMW) distribution in order to avoid some estimation problems. The mathematical properties and maximum-likelihood estimation of the reduced version are studied. Four real data sets (complete and censored) are used to compare the flexibility of the reduced version versus the NMW distribution. It is shown that the reduced version has the same desirable properties of the NMW distribution in spite of having two less parameters. The NMW distribution did not provide a significantly better fit than the reduced version.

Saad J. Almalki

Papers

A new modified Weibull distribution

Modifications of the Weibull distribution: A review

A New Discrete Modified Weibull Distribution

Bayesian and Classical Inference for the Generalized Log-Logistic Distribution with Applications to Survival Data.

A reduced new modified Weibull distribution