A systemic approach to moisture problems in buildings for mould safety modelling

Pietrzyk, Krystyna

doi:10.1016/j.buildenv.2014.12.013

Cited by 45 publications

(24 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Besides, instead of determining the best model for a particular problem, the main purpose of this study is to demonstrate the effect of the hybrid method we propose on the predictive performance. Therefore, this study implemented several classifiers using common classification algorithms including decision tree (DT) [30,31], support vector machine (SVM) [32][33][34], and k-nearest neighbor (k-NN) [28,35], as well as three classifiers applying ensemble learning strategies [28], and then conducted the training process using these classifiers upon two training datasets, one with the feedback from rule-based reasoning and the other without it, and compared both predictive performances. The decision tree is chosen because it works well with both numerical and categorical features and provides interpretability for decision-making [29], while SVM can generate robust results for complex classification problems [15].…”

Section: Classification Algorithms and Parametersmentioning

confidence: 99%

Filtering of Irrelevant Clashes Detected by BIM Software Using a Hybrid Method of Rule-Based Reasoning and Supervised Machine Learning

Lin

Huang

2019

Applied Sciences

View full text Add to dashboard Cite

Construction projects are usually designed by different professional teams, where design clashes may inevitably occur. With the clash detection tools provided by Building Information Modeling (BIM) software, these clashes can be discovered at an early stage. However, the number of clashes detected by BIM software is often huge. The literature states that the majority of those clashes are found to be irrelevant, i.e., harmless to the building and its construction. How to filter out these irrelevant clashes from the detection report is one of the issues to be resolved urgently in the construction industry. This study develops a method that automatically screens for irrelevant clashes by combining the two techniques of rule-based reasoning and supervised machine learning. First, we acquire experts’ knowledge through interviews to compile rules for the preliminary classification of clash types. Subsequently, the results of the initial classification inferred by the rules are added into the training dataset to improve the predictive performance of the classifiers implemented by supervised machine learning. The average predictive performance obtained by using the hybrid method is up to 0.96, which has been improved from the traditional machine learning process only using individual or ensemble learning classifiers by 6%–17%.

show abstract

Section: Classification Algorithms and Parametersmentioning

confidence: 99%

Filtering of Irrelevant Clashes Detected by BIM Software Using a Hybrid Method of Rule-Based Reasoning and Supervised Machine Learning

Lin

Huang

2019

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…This systemic approach provides a proper theoretical tool for the analysis of the interrelations between the structure, its environment and its performance. An example of systemic model of a building, applicable in building physics studies, is shown in Figure 2 [19].…”

Section: Form Versus Monte Carlo Simulationmentioning

confidence: 99%

“…The building site in the district of Gothenburg has been considered and can be described as a semi-urban area with the surface roughness equal Figure 2. Building/Environment system applied in a traditional building physics analysis [19]. The house was constructed in 1979 with the intention of using it for experimental studies in building physics with focus on ventilation and energy saving.…”

Section: Description Of the Test Housementioning

confidence: 99%

On Risk and Reliability Studies of Climate-Related Building Performance

Pietrzyk¹,

Czmoch²

2018

Risk Assessment

Self Cite

View full text Add to dashboard Cite

A design strategy based on integration of the building form and structure with its external environment in order to take advantage of natural forces (wind and buoyancy effects) has been evaluated in terms of risk and reliability measures. Tools for the probabilistic analysis (First-Order Reliability Method (FORM), Monte Carlo) have been presented and applied in the probabilistic modelling and sensitivity analysis of the response function of the studied building physics problem. Sensitivity analysis of the influence of basic random variables on the probability distribution of a response function is straightforward in FORM methodology. The case-based studies of probabilistic modelling of uncertainties coupled to wind speed and temperature difference through the specified building/environment system have been presented (i.e., the distribution models of the air change rate ACH and the dynamic U value characterising thermal performance of dynamic insulation). Sensitivities of the probability model of ACH to the parameters of wind speed and temperature distributions have been estimated for the consecutive values of the air change rate using FORM methodology. Reliability of ACH turned out to be most sensitive to the shape parameter of the wind speed distribution (in two-parameter Weibull model). The probabilistic risk analysis along with the effective tools for sensitivity analysis can be used to support design decisions and also to develop better models for evaluation of building performance.

show abstract

“…A passive control creates an extra climate-comfort loop (see Figure 1). Figure 1 Bioclimatic thinking at the early stage of the design process -systemic approach; modified from (Pietrzyk 2015).…”

Section: Communication Of Building Climatology Principles To Support mentioning

confidence: 99%

“…The way of presenting performance criterion depends on the investigated problem and availability of data. Stochastic threshold criterion is built up because of the uncertainties regarding the climatic conditions or humans response (Pietrzyk 2008, Pietrzyk 2015. Generally, variability in time, space, and among individuals can be included in the performance criterion R (see Figure 3).…”

Section: Boundaries Of a Comfort Zone -A Probabilistic Approachmentioning

confidence: 99%

Bioclimatic tools for sustainable design – uncertainty perspective

Pietrzyk¹

2018

Healthy, Intelligent and Resilient Buildings and Urban Environments

Self Cite

View full text Add to dashboard Cite

Overall, holistic approach in which the building is integrated into its environment with respect to building physics principles allows for discussion of a variety of passive strategies regarding the building placement (local climatic conditions, microclimate etc.), building types, building materials and technical systems. Bioclimatic design is referred to as a proper approach to highlight the connection of a building with the natural environment, which can be treated as the prerequisite for energy efficient design.The research results within the reliability studies of building performance become an inspiration for architects and engineers to further discuss tools supporting decisions at the early stage of design process from the reliability perspective. The bioclimatic tools allowing for interpretation of the sense of comfort as a variable dependent on the variability of climatic conditions, and human factors are suggested for the analysis at the early stage of building design. A framework for the probabilistic analysis of comfort performance to be included in bioclimatic design tools is proposed.The uncertainty of the variables and unknown parameters are critically (qualitatively) examined. Further research is needed to quantify the uncertainty of the boundaries of the comfort caused by the variability of climatic conditions and the uncertainty of human perception of comfort.

show abstract

A systemic approach to moisture problems in buildings for mould safety modelling

Cited by 45 publications

References 12 publications

Filtering of Irrelevant Clashes Detected by BIM Software Using a Hybrid Method of Rule-Based Reasoning and Supervised Machine Learning

Filtering of Irrelevant Clashes Detected by BIM Software Using a Hybrid Method of Rule-Based Reasoning and Supervised Machine Learning

On Risk and Reliability Studies of Climate-Related Building Performance

Bioclimatic tools for sustainable design – uncertainty perspective

Contact Info

Product

Resources

About