Building Retrofit Measures and Design: A Probabilistic Approach for LCA

Green building design and architecture have become widespread tenets in the development of sustainable buildings. In this context, the use of sustainable materials and the awareness of resource/energy consumption are strategic aspects to consider for the improvement of building performances. This paper presents a new and structured approach to address uncertainty and sensitivity analysis in Life Cycle Assessment (LCA) to support the decision-making process in building renovation. This “probabilistic” approach to LCA allows for the obtaining of results expressed as ranges of environmental impacts and for alternative solutions, offering an idea of the meaning of input parameters’ uncertainties and their influence on the result. The approach includes (i) the assessment of inputs’ uncertainties (represented by Probability Density Functions—PDF); (ii) the data sampling; and (iii) the uncertainty propagation (Monte Carlo method). Variance decomposition techniques have been used to sample inputs’ PDFs and assess their impact on the LCA result distribution (sensitivity analysis). The methodology application is illustrated through a case study where three building retrofit measures were assessed. Results provide an insight about the uncertainties of LCA indicators in terms of climate change and nonrenewable energy. The input parameters related to the use phase are confirmed as the most influential in building LCA.

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Sobol′ Sensitivity Analysis Using a Neural Network Model of a LB-LOCA in the ZION Nuclear Power Plant With CATHARE-2 V2.5 Code

Volume 4: Thermal Hydraulics ◽

10.1115/icone21-15674 ◽

2013 ◽

Author(s):

Fabrice Fouet ◽

Pierre Probst

Keyword(s):

Neural Network ◽

Sensitivity Analysis ◽

Nuclear Power ◽

Uncertainty Propagation ◽

Correlation Coefficients ◽

Computer Code ◽

Numerical Application ◽

Loss Of Coolant Accident ◽

Input Parameters ◽

Artificial Neural Network Ann

In nuclear safety, the Best-Estimate (BE) codes may be used in safety demonstration and licensing, provided that uncertainties are added to the relevant output parameters before comparing them with the acceptance criteria. The uncertainty of output parameters, which comes mainly from the lack of knowledge of the input parameters, is evaluated by estimating the 95% percentile with a high degree of confidence. IRSN, technical support of the French Safety Authority, developed a method of uncertainty propagation. This method has been tested with the BE code used is CATHARE-2 V2.5 in order to evaluate the Peak Cladding Temperature (PCT) of the fuel during a Large Break Loss Of Coolant Accident (LB-LOCA) event, starting from a large number of input parameters. A sensitivity analysis is needed in order to limit the number of input parameters and to quantify the influence of each one on the response variability of the numerical model. Generally, the Global Sensitivity Analysis (GSA) is done with linear correlation coefficients. This paper presents a new approach to perform a more accurate GSA to determine and to classify the main uncertain parameters: the Sobol′ methodology. The GSA requires simulating many sets of parameters to propagate uncertainties correctly, which makes of it a time-consuming approach. Therefore, it is natural to replace the complex computer code by an approximate mathematical model, called response surface or surrogate model. We have tested Artificial Neural Network (ANN) methodology for its construction and the Sobol′ methodology for the GSA. The paper presents a numerical application of the previously described methodology on the ZION reactor, a Westinghouse 4-loop PWR, which has been retained for the BEMUSE international problem [8]. The output is the first maximum PCT of the fuel which depends on 54 input parameters. This application outlined that the methodology could be applied to high-dimensional complex problems.

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Structure Design for Green Building in some Residential Area in Sino-Singapore Tianjin Eco-City

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.71-78.655 ◽

2011 ◽

Vol 71-78 ◽

pp. 655-658

Author(s):

Rong Qin

Keyword(s):

Energy Saving ◽

Indoor Environment ◽

Residential Building ◽

Green Building ◽

Building Design ◽

Residential Area ◽

Structure Design ◽

Green Building Design ◽

Land Saving ◽

Material Saving

There are six basic control items, land saving, energy saving, water saving, material saving, indoor environment and operation, among which, only material saving are related to structure design. We followed the green building design concept and the control items list in those standards during structure design of one of the residential area in Sino-Singapore Tianjin Eco-city, which consist of 15~18-story residential building connected to a large underground garage, as is shown below.

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