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Many retrofit projects are being carried out in existing buildings to reduce energy consumption. However, the energy consumptions before and after retrofit need to be known in order to evaluate such retrofit projects. Even though the energy consumption after retrofit can be determined through measurement, the energy consumption before retrofit cannot be known. This study is to more easily estimate energy usage prior to the retrofit. Generally, dynamic simulation or regression model should be used to estimate the energy consumption of buildings before retrofit. However, existing regression models have no way to calibrate the model if it is inaccurate. In this paper, we use a clustering technique to improve the accuracy of the regression model. The estimation of energy consumption before retrofit is referred to as “baseline model” and the inverse model is used to create this baseline model. The inverse model is created through monthly data, daily data, and other similar data. In this study, the inverse model was created through daily data and the baseline model was derived from it. The conventional change-point Model and the cluster inverse model presented in this paper were compared and evaluated with the criteria presented through M&V (Measurement and Verification). The results suggest that the cluster inverse model which reflects the characteristics of data is more appropriate when the baseline model is derived from daily data. [ABSTRACT FROM AUTHOR]

Harvesting daylight for improving building energy performance has become an important issue in recent years. Most energy simulation tools use a Daylight Factor (DF) based algorithm to capture the complexity of daylight behaviors. However, DF has a limitation for fully accounting realistic daylight conditions, and several modifications or integrations with other supporting tools were developed to compensate for this limitation. This paper uses the Kriging method to predict daylight conditions for a whole year, and couples this method with energy simulation tools. Kriging is a group of geo-statistical techniques used to interpolate the value of a random field at an unobserved location from discrete observed values at nearby locations. In previous research, the Kriging method showed promising outcomes; that result was significantly better than current daylight modeling in energy simulation tool, and very close to the results from advanced physics-based daylight simulation tool. However, Kriging also comes with certain limitations that require further investigation. One major hurdle was Kriging’s long computational time compared to current daylight models in energy simulation tools. For this reason, this paper aims to find possibilities to reduce computational time to realistic levels that can be applicable in practice. Furthermore, it proposes a method to integrate Kriging-based daylight model with an energy simulation tool that can plot hourly indoor light distribution. This proposal obtains more realistic results than current energy simulation daylight models, while reducing computational expense. [ABSTRACT FROM AUTHOR]

Abstract Sensitivity analysis (SA) can be applied to building energy models (BEM) to identify which input parameters that drive the majority of the model output variation. The screening-based Morris method is often applied for this purpose; however, consideration regarding the effect of the user-defined number of levels (p) and trajectories (r) on the obtained results are rare. This paper investigates how the choice of p and r affects the outcome of a SA using the Morris method on a high fidelity BEM. The results indicates that the Morris method was not able to replicate the ranking from the variance-based Sobol' method no matter the choice of r and p. It was, however, able to identify groups of input parameters (parameter clusters) most sensitive to the model output variability, but it required significantly more r than usually applied in studies featuring the Morris method. The reason is that marginal differences in absolute values of elementary effects (the sensitivity indices of the Morris method) for some input parameters may lead to a change in ranking position several times as the number of r increases. Users of the Morris method must therefore not be predetermined on the size of the parameter cluster; instead, they must make a visual assessment of the convergence of the parameter ranking to qualitatively determine the appropriate size of parameter cluster. The final recommendation for future studies deploying the Morris method for SA applied to a high fidelity BEM is to choose p ≥ 4 as it seems to lead the analysis towards a more truthful ranking, and then run simulations in steps of r = 100 when making the visual assessment to determine convergence and the size of parameter cluster. The identified need for more r questions the general notion that the Morris method is a computationally efficient screening method in terms of absolute time use. However, the Morris method is still much more computational efficient than a Sobol'-based analysis if the purpose of the SA is to identify a cluster of input parameters most sensitive to the model output variability. [ABSTRACT FROM AUTHOR]

Building energy models (BEMs) are typically used for design and code compliance for new buildings and in the renovation of existing buildings to predict energy use. The increasing adoption of BEM as standard practice in the building industry presents an opportunity to extend the use of BEMs into construction, commissioning and operation. In 2009, the authors developed a real-time simulation framework to execute an EnergyPlus model in real time to improve building operation. This paper reports an enhancement of that real-time energy simulation framework. The previous version only works with software tools that implement the custom co-simulation interface of the Building Controls Virtual Test Bed (BCVTB), such as EnergyPlus, Dymola and TRNSYS. The new version uses an open standard interface, the Functional Mockup Interface (FMI), to provide a generic interface to any application that supports the FMI protocol. In addition, the new version utilizes the Simple Measurement and Actuation Profile (sMAP) tool as the data acquisition system to acquire, store and present data. This paper introduces the updated architecture of the real-time simulation framework using FMI and presents proof-of-concept demonstration results which validate the new framework. [ABSTRACT FROM AUTHOR]

Occupants account for a significant impact on building performance through their interactions with zone level building components. Empirically-derived occupant models, despite their potential to represent occupants’ impact in building performance simulation (BPS), have minimal penetration in design and code compliance processes. Instead, occupants are represented with static schedules or simple deterministic triggers. The objective of this paper is to better understand the influence of assumptions made in representing occupant interactions with building components over a BPS model's energy use and comfort predictions, as well as their ability to promote better design decisions. To this end, the energy and daylight performance of a generic perimeter office space in Ottawa, Canada were evaluated using a set of comprehensive performance metrics. Results indicate that representing dynamic occupant–building interactions lead to different energy predictions from the static schedules. The maximum difference in the total electricity use was for window-to-wall area ratios (WWR) of 20%, which was about 30% higher with the stochastic cases than the blind-open static cases. WWR 60% and 40% generally yielded the lowest lighting electricity use with the static and stochastic cases, respectively. This paper emphasizes the importance of incorporating empirically-derived dynamic occupant models for simulation-aided design and code compliance. [ABSTRACT FROM AUTHOR]

Energy consumption models play an integral part in energy management and conservation, as it pertains to buildings. It can assist in evaluating building energy efficiency, in carrying out building commissioning, and in identifying and diagnosing building system faults. This review takes an in-depth look at energy-demand prediction models for buildings in that it delves into recent developments in building energy approaches used to predict energy usage. By enlisting current approaches to the modelling of buildings, methods for building energy simulations can be categorized into four level classes as follows: (i) data-driven approaches; (ii) physics-based approaches; (iii) large scale building energy forecasting approaches; and (iv) hybrid approaches. The focus of this review is to target the data-driven approach and large-scale building energy predicting-based approaches. Here the data driven approaches can be categorized by (1) artificial neural network based approaches; (2) clustering based approaches; (3) statistical and machine learning-based approaches; and (4) support vector machine based approaches. From there, the type of data-driven based approach is further grouped by (a) benchmarking models; (b) energy-mapping models; (c) energy forecasting models; and (d) energy profiling models. Large-scale building-energy prediction techniques is then categorized as follows: (1) white-box based approaches; (2) black-box based approaches, and (3) grey-box based approaches. The current study explores first-rate data-driven based approaches about building energy analysis for industrial, commercial, domestic, etc., within a rural and urban setting. This review paper is based on the necessity of identifying points of departure and research opportunities for urban and rural-level analyses of building level energy performance. A variety of issues are explored which include: energy performance metrics; end-use of different building types; multiple levels of granularity; and urban and rural scales. Each technique encompasses a variety of input information as well as varying calculations or simulation models along with furnishing contrasting outcomes that suggest a variety of usages. A thorough review of each technique is presented in this study. This review highlights strengths, shortcomings, and purpose of the methods of numerous data-mining based approaches. A comprehensive review of energy forecasting models that are specified in the literature part is also provided. [ABSTRACT FROM AUTHOR]

Developing BEPS models which predict energy usage to a high degree of accuracy can be extremely time consuming. As a result, assumptions are often made regarding the input data required. Making these assumptions without introducing a significant amount of uncertainty to the model can be difficult, and requires experience. Even so, rules of thumb from one geographic region are not automatically transferrable to other regions. This paper develops a methodology which can be used to determine useful guidelines for defining the most influential input data for an accurate BEPS model. Differential sensitivity analysis is carried out on parametric data gathered from five archetype dwelling models. The sensitivity analysis results are used in order to form a guideline minimum set of accurately defined input data. Although the guidelines formed apply specifically to Irish residential dwellings, the methodology and processes used in defining the guidelines is highly repeatable. The guideline minimum data set was applied to practical examples in order to be validated. Existing buildings were modelled, and only the parameters within the minimum data set are accurately defined. All building models predict annual energy usage to within 10% of actual measured data, with seasonal energy profiles well-matching. [ABSTRACT FROM AUTHOR]

In this paper the authors present an algorithm that abstracts an arbitrarily shaped set of building volumes into a group of simplified ‘shoebox’ building energy models. It is shown that for generic perimeter and core floorplans the algorithm provides a faster but comparably accurate simulation results of annual load profiles vis-à-vis multi-zone thermal models generated according to ASHRAE90.1 Appendix G guidelines. Envisioned applications range from rapid thermal model generation for urban building energy modelling to schematic architectural design. Following a description of the algorithm, its ability to produce load profiles for a mixed-use neighborhood of 121 fully conditioned buildings for a variety of climates is demonstrated. The comparison yields relative mean square errors in simulated annual building energy use intensity of five to 10 percent compared to ASHRAE 90.1 compliant building energy models while reducing simulation times by a factor of 296. [ABSTRACT FROM AUTHOR]

The paper shows the results of measurements of carbon dioxide concentrations conducted in the school buildings located in two different climates: Białystok (Poland) and Belmez/Córdoba (Spain). CO 2 concentration in first 45 min met requirements of regulations, but with medium occupation of places in classrooms, then the recommended values were excided. We developed a model for CO 2 level estimation. This model allowed us to simulated the CO 2 concentration for full occupation of classrooms in both countries. In these cases CO 2 concentration would exceed maximum value (1000 ppm) during the first hour. Furthermore required air change rates were calculated: for actual occupation they should be in a range 2.5–5 h −1 to maintain IDA2 and carbon dioxide concentration below 1000 ppm, while in case of full occupation even 6–9 h −1 . Finally, surveys of student satisfaction were performed in situ during the measurements of CO 2 level to obtain the dependence of student comfort perception on this concentration. [ABSTRACT FROM AUTHOR]

Evaluation methods can be used to determine what constitutes good energy performance in a building. With an increasing focus on energy use of buildings worldwide, this evaluation assumes a fundamental importance. This paper provides a comprehensive review of the available methods for analysing, classifying, benchmarking, rating and evaluating energy performance in non-domestic buildings. Methodologies are grouped in five categories: engineering calculations, simulation, statistical methods, machine learning and other methods. Techniques for evaluating buildings are described, their principal applications are shown and limitations are identified. The use of performance evaluation in energy efficiency programmes and standards is mapped. There is a need to further develop interactions between the main modelling techniques to produce simple, robust and validated models. Also, evaluation techniques must be developed to consider comfort or service provision in the buildings as a factor in energy performance. [ABSTRACT FROM AUTHOR]

Several new technologies can be today implemented in buildings in order to achieve the NZEB goal. In this paper a novel computer model for predicting the energy demand of buildings integrating phase change materials, photovoltaic-thermal collectors, adjacent sunspaces and innovative daylighting control is presented. Through this tool, DETECt 2.2, written in MatLab and conceived for research purposes, the overall energy and economic performance of multi-zone NZEBs can be assessed. Both the active and passive effects on the energy demands of all the above mentioned technologies, even if simultaneously utilized, are taken into account by means of an integrated building modelling approach. In addition, parametric and sensitivity analyses, with a single simulation run, can be carried out for design purposes. A novel relevant case study referred to the energy design of a non-residential NZEB for Mediterranean climates is developed. For this building a suitable energy optimization analysis was also carried out. For each use of the indoor space, the optimal value of the pivotal design and operating parameters is calculated. Details about the optimal position of building PCMs and thermal insulation layers, also coupled to BIPV and/or BIPV/T systems, are provided. For the obtained best configuration very low heating and cooling demands are achieved (0.9 and 1.5 kWh/m 3 y, respectively). Results about a simplified economic analysis carried out on the investigated energy saving technologies are also reported. At last, new NZEB definition details and criteria are provided for non-residential buildings located in the southern European zones (Mediterranean climates). [ABSTRACT FROM AUTHOR]

Variable refrigerant flow (VRF) systems vary the refrigerant flow to meet the dynamic zone thermal loads, leading to more efficient operations than other system types. This paper introduces a new model that simulates the energy performance of VRF systems in the heat pump (HP) operation mode. Compared with the current VRF-HP models implemented in EnergyPlus, the new VRF system model has more component models based on physics and thus has significant innovations in: (1) enabling advanced controls, including variable evaporating and condensing temperatures in the indoor and outdoor units, and variable fan speeds based on the temperature and zone load in the indoor units, (2) adding a detailed refrigerant pipe heat loss calculation using refrigerant flow rate, operational conditions, pipe length, and pipe insulation materials, (3) improving accuracy of simulation especially in partial load conditions, and (4) improving the usability of the model by significantly reducing the number of user input performance curves. The VRF-HP model is implemented in EnergyPlus and validated with measured data from field tests. Results show that the new VRF-HP model provides more accurate estimate of the VRF-HP system performance, which is key to determining code compliance credits as well as utilities incentive for VRF technologies. [ABSTRACT FROM AUTHOR]

Occupant behavior is a major contributing factor to building energy consumption. Large discrepancies might occur when occupants with diverse types in terms of behavior patterns reside in an identical building. Moreover, it is vital to derive several kinds of typical occupant behavior that represent the assemblage of occupants in a simplified way as the reference for building designers and energy policy makers. This paper presents a preliminary research on occupant behavior categorization through the building energy simulation, where some typical occupant air-conditioning behavior patterns use in Chengdu, China have been derived from a large-scale questionnaire survey based on the energy consumption levels. These typical occupant behavior patterns could be used as the context for an overview of building energy in a community, as well as the evaluation of building energy-saving technology where occupants are involved. Further efforts are required in the algorithm of dividing occupant behavior into typical patterns, the validation of the classification results, and the analysis of other behaviors. [ABSTRACT FROM AUTHOR]

Traditionally, in building energy modeling (BEM) programs, occupant behavior (OB) inputs are deterministic and less indicative of real world scenarios, contributing to discrepancies between simulated and actual energy use in buildings. This paper presents a new OB modeling tool, with an occupant behavior functional mock-up unit (obFMU) that enables co-simulation with BEM programs implementing functional mock-up interface (FMI). The components detailed in the development of the obFMU include an overview of the DNAS (drivers-needs-actions-systems) ontology and the occupant behavior eXtensible Markup Language (obXML) schema, in addition to details on the creation of the obFMU that contains the co-simulation interface, the data model and solvers. To demonstrate functionality of the tool, three examples of occupant behaviors were simulated, including: (1) turning on and off lights, (2) opening and closing windows, and (3) turning on and off the air conditioners. The obFMU can be used via co-simulation with all building simulation programs that implement the FMI, thus users are not limited to a particular tool. Another advantage is the use of obXML schema to represent occupant behavior, standardize the description of occupant behavior enabling information exchange. [ABSTRACT FROM AUTHOR]

The paper introduces an approach to replicate building stock energy data using energy survey data. For demonstration of the approach, the research uses energy consumption data for office buildings in Chicago from Commercial Building Energy Consumption Survey (CBECS) 2003. The replication starts from derivation of the energy use distribution for a building stock in a specific location from the survey data. Then probabilistic methods are used to map building stock model space to real-world data space reflecting a weather adjustment of the energy survey data. The approach leverages a linear surrogate model of the physics-based reduced order normative energy model. The normative building energy model can rapidly estimate the building energy performance with respect to its design and operational characteristics. The research investigates a statistical procedure to inversely estimate building parameters using regression and Bayesian inference model based on the Markov Chain Monte Carlo (MCMC) sampling techniques. The research serves a new paradigm of the building stock aggregation that can lead to an efficient energy model, which contributes the body of knowledge of energy modeling beyond the single building scale. [ABSTRACT FROM AUTHOR]

Green building design is presently among the hottest research topics in the world. Maintaining a comfortable indoor environment with minimum energy consumption is a challenging task that attracts the attention of experts around the world. With the recent advances in building performance simulation tools, it is now possible to predict and assess building performance at the design stage. Simulation-based optimization of building design is a potential application that connects building performance simulation with optimization algorithms. In this paper, numerous studies on the optimization of building envelope design were assembled and reviewed. Popular optimization algorithms were compared and discussed. Targeted objectives were collected and summarized. Based on the statistical results, the limitations in this research area were identified, and some potential breakthroughs were suggested. [ABSTRACT FROM AUTHOR]

Model predictive control (MPC) has been studied in the building science realm for about three decades. However, the following two aspects of the building control have not been studied thoroughly in MPC research. One is the impact of the mixed-mode cooling system on the active heating ventilation and air conditioning (HVAC) energy consumption, and the other is the differences of individual thermal comfort preference and its impact on energy. This paper proposes an occupant-oriented mixed-mode EnergyPlus predictive control system to optimize HVAC energy consumption while meeting the individual thermal comfort preference. A web-based dashboard is implemented in the test-bed building for three months to collect individual thermal comfort preference data. The data analysis results suggest that occupants have various tolerances and preferences about thermal comfort. The simulation results show that, during one week of a typical swing season, the mixed-mode system further reduces the active HVAC energy consumption, and the diversified occupant thermal comfort preference has significant impact on HVAC energy consumption. [ABSTRACT FROM AUTHOR]

This paper quantifies green roofs energy savings which is a challenging topic, namely in Mediterranean climate with distinct heating and cooling seasons. The thermal behavior of a green roof case study in Lisbon, Portugal, was assessed through an experimental campaign during heating and cooling periods of the year of 2013. These experimental results were then used to calibrate a building energy simulation in EnergyPlus. After validation, the numerical model was used to compare the energy performance of intensive, semi-intensive and extensive green roofs. The three green roof types lead to similar heating energy needs but extensive green roof solution shows higher cooling energy needs than semi-intensive and intensive ones, of 2.8 and 5.9 times more, respectively. Furthermore, the performance of each type of green roof and different insulation properties was compared to traditional roof solutions. With no thermal insulation, extensive green roofs require 20% less energy use than black roofs and show a similar annual behavior than white roofs. Semi-intensive and intensive green roofs energy use is 60–70% and 45–60% lower than black and white roofs, respectively. Well insulated roofs do not take full advantage of evapotranspiration cooling effects, which is particularly noticeable when comparing with high reflective white roofs. [ABSTRACT FROM AUTHOR]

Occupant behavior is one of the major factors influencing building energy consumption and contributing to uncertainty in building energy use prediction and simulation. Currently the understanding of occupant behavior is insufficient both in building design, operation and retrofit, leading to incorrect simplifications in modeling and analysis. This paper introduced the most recent advances and current obstacles in modeling occupant behavior and quantifying its impact on building energy use. The major themes include advancements in data collection techniques, analytical and modeling methods, and simulation applications which provide insights into behavior energy savings potential and impact. There has been growing research and applications in this field, but significant challenges and opportunities still lie ahead. [ABSTRACT FROM AUTHOR]

In this paper, measures such as planting urban greenery and using high-albedo paint to mitigate the urban heat-island effect, conserve energy, and reduce CO 2 emissions were assessed. As a typical energy-saving method for buildings, reducing the internal heat sources and increasing the insulation are also assessed. We used a coupled urban canopy and building energy model to predict the heat loads of buildings in city districts, the effects of air-conditioning on energy consumption, and air temperature changes. In this model, a vertical one-dimensional local atmospheric model is coupled with an air-conditioning load calculation model for buildings, making it possible to assess the interaction between anthropogenic heat release due to air-conditioning usage and the outside thermal environment. In this study, we selected a target study region in the city of Kawasaki, Japan. When typical city districts were assessed, planting greenery or increasing albedo achieved temperature reductions of 0.6–1.0 °C and 0.1–0.5 °C, respectively, and energy savings of 40–80 and 70–90 kJ/m 2 /day (per unit floor area) on a typical summer day. The results from the large-scale assessment show that urban greening or albedo increases achieved the highest energy savings, of up to 400 t-CO 2 /day, in the entire target study region. [ABSTRACT FROM AUTHOR]

Light pipes transmit daylight into building interiors. Their installation into thermally insulated roofs of low energy buildings can be a problem because of thermal bridges and condensation problems. This article is focused on a CFD simulation thermal analysis that includes four variations of light pipes with a segment of a flat roof. Common light pipes with a hollow light guiding tube were compared to special light pipes containing an additional glass unit located inside the tube. The additional glass units increase thermal resistance and reduce condensation risks of the light guiding systems. The light pipes were compared in two different simulation models run in ANSYS Fluent software and the CalA program. Temperature profiles and air flow patterns of the cross sectional profiles of the light pipes served to determine the total heat transmittance and heat losses of the studied light pipes installed in a segment of a thermally insulated flat roof. The paper compares simplified 2D rotational–symmetrical numerical model based on the thermal diffusion equation with the complex 3D CFD numerical simulation. The results confirm that the simplified 2D numerical model is suitable for the thermal evaluation of the light pipes containing an additional glass unit, too. The additional glass unit with the triple glass improves thermal resistance up to 88% in case of light pipe with diameter 600 mm and reduces optical transmittance to 28%. [ABSTRACT FROM AUTHOR]

The paper presents the results of 1-year measurement of indoor environment parameters (temperature, relative humidity, CO 2 concentration) in exhibition rooms of one Polish museum in various periods of the year, and the results of simulation on thermal model of this building. The influence of a temperature control scheme in museum rooms on heating and cooling demand was analysed. The actual state (poor control of internal temperature) and ideal control of internal temperature were analysed – two cases in the winter and two cases in the summer. Simulations were performed by ESP-r program. The multi-zone model of the building was validated based on measurement data. Measurements and simulations revealed significant variations in the temperature in the rooms of the museum. The analysis showed that the maintaining internal temperature at constant level of 20 °C in winter reduces monthly heat demand in most of the exhibition rooms. Obtained effect is 5–16% depending on the premises. Provision the raise of a temperature by 1 K results in the increase of heat consumption by 6%. Maintenance of a desired internal temperature, which does not exceed 24 °C in the summer, requires the provision of coolness to the museum premises. [ABSTRACT FROM AUTHOR]

Abstract: The building sector is an energy intensive sector, with great potential to reduce energy needs and environmental pollution. Several measures are being taken to increase the energy efficiency and avoid energy consumption in this sector. A recent trend is the nearly zero energy buildings, which was already adopted by some of the latest regulations, such as the 2010 recast of the European Performance of Buildings Directive (EPBD). However, to reach these goals, especially considering the existing building stock, new retrofit solutions are required, which must be well adapted to the specific building stock needs, and ensure that the building retrofit can achieve the nearly zero energy buildings standards. This paper presents a new prefabricated retrofit module solution for the facades of existing buildings, and also the steps taken to optimise its performance, which includes a judicious choice of materials, 3D modelling, cost–benefit analysis, use of different simulation tools for performance optimisation and prototyping. It is also shown the implementation of the retrofit module within an integrated retrofit approach, whose final goal was to obtain a building with the minimum possible energy consumption and greenhouse gas emissions. [Copyright &y& Elsevier]

Abstract: To streamline the design of the energy efficient buildings, appropriate tools are needed to assess their energy performance taking into account the microclimatic context. Numerical simulation seems to be the most suitable issue, but none tool is dedicate to the direct evaluation of the microclimate influence on the building energy consumption. A complete solution could be to use both CFD and thermoradiative simulation tools complementary with the coupling technique perspective. This paper presents both a developed CFD–thermoradiative coupled simulation tool and a typical application on an urban fragment. The results lead to two kind of observations: [•] Integration of the thermal model of a building in the microclimatic simulation platform enable a quantitative evaluation of the building energy demand regarding different urban design scenarii (e.g. mineralized vs vegetated). [•] Different physical phenomena do not contribute as much in the energy balance and it is important to compute precisely each one to obtain the small scale microclimatic influence. [Copyright &y& Elsevier]

Abstract: This paper describes the analysis of the hygrothermal behaviours of stabilised rammed earth (SRE) walls used in a building in the UK. The analysis was achieved by computer simulation using WUFI Plus v1.2 whole building hygrothermal analysis software. To validate the model, an unoccupied test room in an unheated SRE building was monitored for 10 months. The hygrothermal properties of the SRE material were measured in the laboratory. It is shown that the SRE walls significantly reduced the amplitude of relative humidity fluctuations in the room air and reduced the frequency of high humidity periods at the wall surface. By adapting the model to represent an occupied and conditioned space, it is demonstrated that SRE walls have the potential to reduce the energy demand for humidification/dehumidification plant. [Copyright &y& Elsevier]

Abstract: Mean wind pressure coefficients (C p) are key input parameters for air infiltration and ventilation studies. However, building energy simulation and stand-alone airflow network programs usually only provide and/or use a limited amount of C p data, which are based on several assumptions. An important assumption consists of using surface-averaged C p values instead of local C p values with a high resolution in space. This paper provides information on the uncertainty in the calculated airflow rate due to the use of surface-averaged C p data. The study is performed using published empirical data on pressure coefficients obtained from extensive wind tunnel experiments. The uncertainty is assessed based on the comparison of the airflow rate (ϕ) calculated using the surface-averaged C p values (ϕ AV) and the airflow rate calculated using local C p values (ϕ LOC). The results indicate that the uncertainty with a confidence interval of 95% is high: 0.23 ϕ AV < ϕ LOC <5.07 ϕ AV. In cases with the largest surface-averaged ΔC p, the underestimation or overestimation is smaller but not negligible: 0.52 ϕ AV < ϕ LOC <1.42 ϕ AV. These results provide boundaries for future improvements in C p data quality, and new developments can be evaluated by comparison with the uncertainty of the current methods. [Copyright &y& Elsevier]

Abstract: Enhancing load calculation tools into building simulation programs requires an in-depth revision and fine tuning of the load calculation assumptions prior to the addition of the HVAC system modelling routines. It is of special interest the analysis of transient heat conduction through multi-layer walls where, in order to improve the coupling between the passive elements of the building and the HVAC systems, an improvement of the time resolution in the calculation becomes critical. Several methods have been historically used, although recently Laplace''s method has been displaced by the State Space method. This paper proposes a new strategy for fine time resolution on the calculation of the response factors through Laplace''s method considering a comparison with the performance of the State Space method when used to calculate conduction transfer functions. Our analysis shows that in order to achieve similar accuracy with both approaches, the State Space method requires significant additional computational time. [Copyright &y& Elsevier]

Abstract: The Kyoto protocol binded the developed countries to reduce the greenhouse gas emissions at least by 5% by 2008–2012 in order to tackle global warming and climate change. Some of the measures of the governments to achieve this goal are to promote new buildings construction and to retrofit existing buildings while satisfying low energy criteria. This means improving energy efficiency of buildings and energy systems, developing sustainable building concepts and promoting renewable energy sources. The design of a low energy building requires parametric studies via simulation tools in order to optimize the design of the building envelope and HVAC systems. These studies are often complex and time consuming due to a large number of parameters to consider. Hence, this paper aims to set up a methodology that simplifies parametrical studies during the design process of a low energy building. The methodology is based on the Design of Experiments (DOE) method which is a statistical method widely used in industry to perform parametric studies that reduces the required number of experiments. [Copyright &y& Elsevier]