Research on air infiltration predictive models for residential building at different pressure

Li, Xiangli; Zhou, Wenqian; Lin, Defu

doi:10.1007/s12273-020-0685-3

Cited by 6 publications

(3 citation statements)

References 11 publications

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“…Chan et al, 2,22 Montoya et al, 21 Pan, 5 Fernàndez-Agüera et al 28 and Bramiana et al 31 presented empirical regression predictive models using several regression analyses on airtightness. In addition, Li et al 40 presented several regression methods including ordinary least squares (OLS), stepwise regression, partial least squares (PLS) and nonlinear fitting with independent variable screening methods to establish an airflow coefficient model. The simulation results show that the improvement with the nonlinear fitting was weaker.…”

Section: Current Research Of Air Leakage Prediction Models and Resear...mentioning

confidence: 99%

Airtightness evaluation of Canadian dwellings and influencing factors based on measured data and predictive models

Ismaiel

Gouda

et al. 2022

Indoor and Built Environment

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The airtightness of buildings has a significant impact on buildings’ energy efficiency, maintenance and occupant comfort. The main goal of this study is to provide an evaluation of the air leakage characteristics of dwellings in different regions in Canada. This study evaluated the key influencing factors on airtightness performance based on a large set of measured data (73,450 dwellings located in Canada with 11 measurement parameters for each). Machine learning models based on multivariate regression (MVR) and Random Forest Ensemble (RFE) were developed to predict the air leakage value. The RFE model, which shows better results than MVR, was used to evaluate the effect of the ageing of buildings. Results showed that the maximum increase in air leakage occurs during the first year after construction – approximately 25%, and then 3.7% in the second year, after which the increase rate becomes insignificant and relatively constant – approximately 0.3% per year. The findings from this study can provide significant information for building designs, building performance simulations and strengthening standards and guidelines policies on indoor environmental quality.

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Section: Current Research Of Air Leakage Prediction Models and Resear...mentioning

confidence: 99%

Airtightness evaluation of Canadian dwellings and influencing factors based on measured data and predictive models

Ismaiel

Gouda

et al. 2022

Indoor and Built Environment

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“…The airtightness value in natural conditions is quite a bit lower than that under a 50 Pa pressure difference between indoors and outdoors. Specifically, the pressure difference between indoors and outdoors under the natural airflow condition is lower than 10 Pa [26]. Generally, the tracer gas method has been used to measure infiltration under natural air flow conditions, and it can provide a more reliable result than that offered by the fan pressurization method [27][28][29].…”

Section: Introduction 1background and Objectivementioning

confidence: 99%

Airtightness Assessment under Several Low-Pressure Differences in Non-Residential Buildings

Shim,

Hong

2023

Energies

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The thermal performance of building envelopes is significantly affected by building insulation and airtightness. However, most studies have focused on improving thermal performance in building envelopes, while few studies on improving airtightness in buildings have been conducted. The present study measured airtightness and infiltration in non-residential buildings using fan pressurization and tracer gas methods. By analyzing the results obtained from both methods, the distribution of the correlation factors was identified, which can be used for the air leakage rates obtained from the blower door test to estimate the infiltration rates under natural airflow conditions. Since it is difficult to get the values of ACH50 through the blower door test in buildings of large volume or where large air leakages occur, the study proposed a method to convert the values of airtightness under several low-pressure differences of 20 Pa, 25 Pa, 30 Pa and 35 Pa into ACH50 using conversion coefficient. By dividing the air leakage rate under 20 Pa pressure difference by the conversion coefficient of 0.60, the values of ACH50 can be estimated. Results converted to ACH50 using conversion coefficient for various pressure differences of 20 Pa, 25 Pa, 30 Pa, and 35 Pa showed an error of 0.1–4.4%, respectively, compared to actual ACH50 measurement results.

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“…In terms of quality, when establishing its management plan, there may be project deliverables and processes, related to sustainability, that need to be checked for quality. For example, in the construction of houses according to the Passivhaus (passive house in translation) standard [86,87], it will be necessary to perform tests to detect air penetration through doors and windows and thus assess the permeability of the building envelope (BlowerDoor Test; [88,89]).…”

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confidence: 99%

New Approach for Managing Sustainability in Projects

et al. 2021

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Despite the work done to date, project sustainability management (PSM) is still at an embryonic stage. The existing literature considers sustainability as a transversal aspect to be incorporated into the traditional management functions (scope, time, cost, quality, etc.). This article proposes sustainability as a key aspect of project management, with three essential components: principles, processes and competences. Regarding principles, the principle of sustainable development should be added to those generally suggested. As for processes, seven are proposed for (1) planning sustainability management; (2) establishing a sustainability breakdown structure; (3) defining the sustainability objective; (4) identifying project alternatives to achieve it; (5) planning and (6) implementing the sustainability strategy; and (7) monitoring and control. The main interrelationships between these processes and those of project initiation, planning, implementation, control, and closure are also analysed. In addition, the competences that the project manager should have in this field are identified, as well as the main criteria to take into account in order to adapt PSM processes to the characteristics of the project and the organisation. Finally, the results of a Delphi analysis carried out to validate these proposals are presented.

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Research on air infiltration predictive models for residential building at different pressure

Cited by 6 publications

References 11 publications

Airtightness evaluation of Canadian dwellings and influencing factors based on measured data and predictive models

Airtightness evaluation of Canadian dwellings and influencing factors based on measured data and predictive models

Airtightness Assessment under Several Low-Pressure Differences in Non-Residential Buildings

New Approach for Managing Sustainability in Projects

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