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Large discrepancies can occur between building energy performance simulation (BEPS) outputs and reference data. Uncertainty and sensitivity analyses are performed to discover the significant contributions of each input parameter to these discrepancies. Variance-based sensitivity analyses typically require many stochastic simulations, which is computationally demanding (especially in the case of the large number of input parameters involved in the analysis). To overcome these impediments, this study proposes a reliable meta-model-based sensitivity analysis, including validation, Morris' method, multivariate adaptive regression splines (MARS) meta-modeling, and Sobol' method, to identify the most influential input parameters on BEPS prediction (annual energy consumption) at the early building design process. A hypothetical building is used to analyze the proposed methodology. Six statistical metrics are applied to verify and quantify the accuracy of the model. It is concluded that the cooling set-point temperature and g-value of the window are the most influential input parameters for the analyzed case study. [ABSTRACT FROM AUTHOR]

Climate neutrality goals in the building sector require a large-scale estimation of environmental impacts for various stakeholders. Life Cycle Assessment (LCA) is a viable method for this purpose. However, its high granularity, and subsequent data requirements and effort, hinder its propagation, and potential employment of Machine Learning (ML) applications on a larger scale. The presented paper outlines the current state of research and practice on district-scale building LCA in terms of standards, software and certifications, and data availability. For this matter, the authors present the development and application of two district-scale LCA tools, Teco and DisteLCA, to determine the Global Warming Potential (GWP) of three different residential districts. Both tools employ data based on (including, but not limited to) CityGML, TABULA, and ÖKOBAUDAT. The results indicate that DisteLCA's granular approach leads to an overestimation of environmental impacts, which can be derived from the statistical approach to operational energy use and related emissions. While both tools lead to substantial time savings, Teco requires less manual effort. The linkage of the aforementioned data sources has proven laborious and could be alleviated with a common data framework. Furthermore, large-scale data analysis could substantially increase the viability of the presented approach. [ABSTRACT FROM AUTHOR]

Urban Building Energy Modelling (UBEM) requires adequate geometrical information to represent buildings in a 3D digital form. However, open data models usually lack essential information, such as building geometries, due to a lower granularity in available data. For heating demand simulations, this scarcity impacts the energy predictions and, thereby, questioning existing simulation workflows. In this paper, the authors present an open-source CityGML LoD Transformation (CityLDT) tool for upscaling or downscaling geometries of 3D spatial CityGML building models. With the current support of LoD0–2, this paper presents the adapted methodology and developed algorithms for transformations. Using the presented tool, the authors transform open CityGML datasets and conduct heating demand simulations in Modelica to validate the geometric processing of transformed building models. [ABSTRACT FROM AUTHOR]

Virtual simulations and calculations are a key technology for future development methods. A variety of tools and methods for calculating thermal comfort have not gained sufficient acceptance in practice due to their inherent complexity. This article investigates alternative means of determining thermal comfort, namely, the linearization of the equivalent temperature calculation. This enables a wide range of users to evaluate thermal comfort in a fast and easy manner, for example, for energy efficiency simulation. A flow and thermal model were created according to the requirements of DIN EN ISO 14505 to determine heat transfer coefficients under calibration conditions. The model to simulate the equivalent temperature in calibration conditions comprises a geometrically realistic 3D model of a human test person according to the standard. The influence of the turbulence model, as well as the influence of the equivalent temperature on the heat transfer coefficient in calibration conditions, was investigated. It was found that the dependence of the equivalent temperature is mandatory. The dependence between the heat transfer and the equivalent temperature was taken into account with a continuous linearization approach. An equation-based implementation methodology is proposed, enabling a quick implementation of comfort evaluation in future simulation models. Two test cases show the capabilities of the new model and its application in future work. [ABSTRACT FROM AUTHOR]