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Building performance simulations (BPS) are used to test different designs and systems with the intention of reducing building costs and energy demand while ensuring a comfortable indoor climate. Unfortunately, software for BPS is computationally intensive. This makes it impractical to run thousands of simulations for sensitivity analysis and optimization. Worse yet, millions of simulations may be necessary for a thorough exploration of the high-dimensional design space formed by the many design parameters. This computational issue may be overcome by the creation of fast metamodels. In this paper, we aim to find suitable metamodeling techniques for diverse outputs from BPS. We consider five indicators of building performance and eight test problems for the comparison six popular metamodeling techniques – linear regression with ordinary least squares (OLS), random forest (RF), support vector regression (SVR), multivariate adaptive regression splines, Gaussian process regression (GPR), and neural network (NN). The methods are compared with respect to accuracy, efficiency, ease-of-use, robustness, and interpretability. To conduct a fair and in-depth comparison, a methodological approach is pursued using exhaustive grid searches for model selection assisted by sensitivity analysis. The comparison shows that GPR produces the most accurate metamodels, followed by NN and MARS. GPR is robust and easy to implement but becomes inefficient for large training sets compared to NN and MARS. A coefficient of determination, R 2 , larger than 0.9 have been obtained for the BPS outputs using between 128 and 1024 training points. In contrast, accurate metamodels with R 2 values larger than 0.99 can be achieved for all eight test problems using only 32–256 training points. [ABSTRACT FROM AUTHOR]

Thermal radiation within buildings is a significant component of thermal comfort. Typically the methods applied for calculating view factors between a person and its building surfaces requires great computational time. This research developed a view factor calculation method suitable for building energy simulations. The method calculates view factors by numerical integration of projected area factor. Over time the projected area factor of a person has been simplified by geometrical shapes. These shapes were compared with more complex equations on precision and calculation time. The same was done for the resulting view factors, where the results were compared with view factors found by ray tracing. While geometrical simplifications of the human body gave the fastest calculations, the complex equations gave the most accurate results. Non-rectangular surfaces and obstacles were treated by comparing intersection points with the edges of the surface, making the method applicable to rooms with complex geometry. The method for calculating view factors is robust and applicable to building energy simulation tools. Calculation time can be long depending on the complexity of geometry, grid-size and the choice of method for the projected area factor, but view factor calculations are done only once for a whole year simulation. [ABSTRACT FROM AUTHOR]

There is very little knowledge on the occupant actual hot water comfort (temperature and flow), usage practice, and routines (temporal and spatial distribution of hot water usage in a household). This paper describes the results from the total and hot water measurements in two Danish detached houses. The results show that, at the draw-off points, the temperature of 55 °C is never asked by the occupants, not even in the kitchen sink. The domestic water temperature differentiates depending on the function of the draw-off point, with the shower and kitchen taps being most energy- and water-intense. They constitute around 90% of the hot water use in the house. Shower units on average demand for highest temperature (i.e., 35.5 °C to 40.4 °C). Hand washing operates, on average, at temperature between 20.5 °C to 26.5 °C. Average water temperature at the taps located in utility room varies between 23 °C to 26 °C. These in-depth insight in the total and hot water use in two new-built low energy houses, can a) help building professionals designing more efficient hot water installations; b) enhance the research work on energy flexibility buildings by providing knowledge on most energy-intensive draw-off points; and c) facilitate district heating professionals in improving the network performance. [ABSTRACT FROM AUTHOR]

• Two systematic and one heuristic OAT approaches compared to Monte Carlo simulations. • 93.750 whole-year simulations of office room constitute the design space. • Bootstrapping used to consider numerous baselines, fixing orders and sample sizes. • Monte Carlo outperforms systematic OAT with a mere 32 random simulations. • Systematic OAT optimization finds local optima close to baseline – far from optimum. What is the best approach to perform building simulations as means to support decision-making and optimize building performance? Traditionally, the search for a compliant design is carried out in a manual one-at-a-time (OAT) approach where one design parameter is optimized before attention is shifted to the next one. In contrast, the Monte Carlo method makes it possible to combine many design parameters simultaneously and consider numerous input combinations. This paper presents a comparison of design approaches and their ability to optimize the performance of an office room with respect to energy demand and indoor climate. The test case is an office space with eight discretized inputs resulting in 93,750 possible designs. Bootstrapping is used to vary the baseline and fixing order for two systematic OAT approaches and to assess an increasing number of Monte Carlo samples. Summarily, OAT optimization depends heavily on the baseline and reveals only few, local optima close to this baseline, which are potentially far from the best solutions. On average, sampling 32 random simulations unveils better solutions and is less likely to suggest poor solutions. An increased sample of 1024 simulations reveals diverse solutions and favourable input ranges, while enabling sensitivity analysis, metamodeling, and flexible constraints. [ABSTRACT FROM AUTHOR]

Humans are potentially exposed to microplastics through food, drink, and air. The first two pathways have received quite some scientific attention, while little is known about the latter. We address the exposure of humans to indoor airborne microplastics using a Breathing Thermal Manikin. Three apartments were investigated, and samples analysed through FPA-µFTIR-Imaging spectroscopy followed by automatic analyses down to 11 µm particle size. All samples were contaminated with microplastics, with concentrations between 1.7 and 16.2 particles m−3. Synthetic fragments and fibres accounted, on average, for 4% of the total identified particles, while nonsynthetic particles of protein and cellulose constituted 91% and 4%, respectively. Polyester was the predominant synthetic polymer in all samples (81%), followed by polyethylene (5%), and nylon (3%). Microplastics were typically of smaller size than nonsynthetic particles. As the identified microplastics can be inhaled, these results highlight the potential direct human exposure to microplastic contamination via indoor air. [ABSTRACT FROM AUTHOR]

This paper applies previously validated multiple pile g-functions, for estimating operational average fluid temperatures in an actual energy pile foundation in Rosborg, Denmark. We find that the multiple pile g-functions yield fluid temperatures similar to what is observed, at minimal computational cost. The temperature model is then utilised in an optimisation algorithm that yields the minimum number of energy piles required by simultaneously maximising the pile spacing and taking into consideration the thermal load of the building. The optimisation shows that the thermal needs of the building can be fully supplied by 148 rearranged energy piles, instead of the current 219. The optimisation tool is also applied to a full-factorial design sweep which shows a large sensitivity of the number of energy piles on the thermal conductivity of the ground. [ABSTRACT FROM AUTHOR]

Highlights • 3D numerical analyses are used to derive the semi-empirical pile g-functions. • Fluid temperatures obtained in multiple pile patterns are analysed. • Semi-empirical g-functions give fluid temperatures close to the 3D modelled. • Semi-empirical g-functions are faster and allow easier analysis. Abstract This paper investigates the applicability of numerical and semi-empirical heat flow models for calculating average fluid temperatures in groups of quadratic, precast pile heat exchangers. A 3D finite element model (FEM), verified with experimental data, is extended to account for multiple pile heat exchangers. Semi-empirical dimensionless temperature g-functions for multiple piles are developed by utilising single pile 3D FEM heat transport simulations with temporal and spatial superposition techniques to account for the thermal interaction between piles. The multiple pile g-functions, yet less accurate for short times, yield fluid temperatures similar to those obtained with full 3D modelling (with 7% of largest deviation), at minimal computational cost. [ABSTRACT FROM AUTHOR]

Abstract: The study presented in this paper focuses on an experimental investigation of the specific heat capacity as a function of the temperature Cp (T) of concrete mixed with various amounts of phase change material (PCM). The tested specimens are prepared by directly mixing concrete and microencapsulated PCM. This paper describes the development of the new material and the experimental set-up to determine the specific heat capacity of the PCM concrete material. Moreover, various methods are proposed and compared to calculate the specific heat capacity of the PCM concrete. Finally, it is hoped that this work can be used as an inspiration and guidance to perform measurements on the various composite materials containing PCM. [Copyright &y& Elsevier]

Abstract: The paper presents the full-scale experimental investigation of the dynamic heat storage potential of the prefabricated hollow core deck elements with and without phase change material (PCM) and with and without increased bottom surface area of the decks. In the presented investigation five types of hollow core decks with different surfaces on the bottom are investigated: reference deck made of standard concrete and flat surface, deck with special mortar grooved tiles, deck with flat mortar tiles, deck with grooved mortar and phase change material tiles, deck with flat mortar and phase change material tiles. The experimental investigation presented in the paper is performed in the specially designed modified hot box apparatus that allows maintaining periodic steady-state tests with the full-scale concrete deck elements. The presented research investigates if the extended surface area and PCM can result in the increased heat amount that can be transferred and stored in the heavy construction element during the diurnal indoor temperature fluctuations. [Copyright &y& Elsevier]

Abstract: This paper presents a heat storage and cooling concept that utilizes a phase change material (PCM) and a thermally activated building system (TABS) implemented in a hollow core concrete deck. Numerical calculations of the dynamic heat storage capacity of the hollow core concrete deck element with and without microencapsulated PCM are presented. The new concrete deck with microencapsulated PCM is the standard deck on which an additional layer of the PCM concrete was added and, at the same time, the latent heat storage was introduced to the construction. The challenge of numerically simulating the performance of the new deck with PCM concrete is the thermal properties of such a new material, as the PCM concrete is yet to be well defined. The results presented in the paper include models in which the PCM concrete material properties, such as thermal conductivity, and specific heat capacity were first calculated theoretically and subsequently the models were updated with the experimentally determined thermal properties of the PCM concrete. Then, the heat storage of the decks with theoretically and experimentally determined thermal properties were compared with each other. Finally, the results presented in the article highlight the potential of using TABS and PCM in a prefabricated concrete deck element. [Copyright &y& Elsevier]

Sustainable building design requires an interplay between multidisciplinary input and fulfilment of diverse criteria to align into one high-performing whole. BIM has already brought a profound change in that direction, by allowing execution of efficient collaborative workflows. However, design decision-making still relies heavily on rules of thumb and previous experiences, and not on sound evidence. To improve the design process and effectively build towards a sustainable future, we need to rely on the multiplicity of data available from our existing building stock. The objective of this research is, therefore, to transform existing data, discover new knowledge and inform future design decision-making in an evidence-based manner. This article looks specifically into this task by (1) outlining and distinguishing between the diverse building data sources and types, (2) indicating how the data can be analysed, (3) demonstrating how the discovered knowledge can be implemented in a semantic integration layer and (4) how it can be brought back to design professionals through the design aids they use. We, therefore, propose a performance-oriented design decision support system, relying on BIM, data mining and semantic data modelling, thereby allowing customized information retrieval according to a defined goal. [ABSTRACT FROM AUTHOR]

This paper investigates the applicability of currently available analytical, empirical and numerical heat flow models for interpreting thermal response tests (TRT) of quadratic cross section precast pile heat exchangers. A 3D finite element model (FEM) is utilised for interpreting five TRTs by inverse modelling. The calibrated estimates of soil and concrete thermal conductivity are consistent with independent laboratory measurements. Due to the computational cost of inverting the 3D model, simpler models are utilised in additional calibrations. Interpretations based on semi-empirical pile G-functions yield soil thermal conductivity estimates statistically similar to those obtained from the 3D FEM inverse modelling, given minimum testing times of 60 h. Reliable estimates of pile thermal resistance can only be obtained from type curves computed with 3D FEM models. This study highlights the potential of applying TRTs for sizing quadratic, precast pile heat exchanger foundations. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the performance of diffuse ceiling ventilation in a classroom. An experimental study is carried out in a test chamber to examine the impact of diffuse ceiling opening area on the system cooling capacity and thermal comfort. The results indicate that diffuse ceiling ventilation provides a satisfied thermal comfort level in the occupied zone even under a high ventilation rate and a high heat load condition. A design chart method is adopted to compare different diffuse ceiling configurations, and the results indicate that the system with a 18% diffuse ceiling opening area is able to handle the highest heat load without discomfort. On the other hand, a CFD model is built where the diffuse ceiling is simulated with a porous media zone. This model is validated by experimental results and further used to analyze the effect of heat load distribution and room height. The numerical results reveal that even distribution of heat sources gives a lower draught risk environment than centralized distribution. In addition, there is a significant increase on the draught risk with increase of room height. [ABSTRACT FROM AUTHOR]

This paper presents and analyses the performance of an integrated system with diffuse ceiling ventilation and a thermally activated building construction. A full-scale experiment is carried out in a hot box with an office setup. The performance of the integrated system is evaluated under different boundary conditions, considering different weather conditions, internal heat loads, TABS activation modes and with/without diffuse ceiling. The measurement results indicate that the diffuse ceiling plays a beneficial role improving thermal comfort in the occupied zone. However, the diffuse ceiling has the opposite effect on energy performance when TABS is activated in heating or cooling mode. Finally, the air temperature distribution in the plenum and the surface temperature distribution of the diffuse ceiling point out that the air does not perfectly mix in the plenum, the air is not evenly distributed throughout the entire ceiling area and the radiation cooling potential of diffuse ceiling is not sufficient. Thus, a further study should be conducted on optimizing diffuse ceiling and plenum design. [ABSTRACT FROM AUTHOR]