A Comprehensive Validation of Two Airflow Models — COMIS and CONTAM

Abstract Several airflow and contaminant dispersion models have been developed to study air distribution in buildings. This paper reports the results of a comprehensive validation of two models: COMIS and CONTAM. The validation process was carried out at three different levels; inter-program comparison; validation with experimental data which was collected in a controlled environment; and finally, validation with field measurement data. At the inter-program level, the airflow rates and pressure values predicted by COMIS and CONTAM for a four-zone paper building were compared with the airflow rates and pressures predicted by CBSAIR, AIRNET and BUS. The results show good agreement between these software programs. The second level of validation compares the models’ predictions with measured data collected in a controlled environment. Fan pressurisation, smoke and tracer gas tests were conducted to estimate the permeability of building envelope components, to locate cracks, and to determine the interzonal airflow rates between rooms. The results confirm that there is good agreement between predictions made by COMIS and CONTAM; there are, however, some differences between these models’ predictions and the measured data. The predictions made by these models were also compared with the results of a tracer gas measurement carried out in a residential building. The predicted and measured values were in good agreement.     

Analytical and inter-program validation of a building thermal model

Results from the analytical and inter-program validation of a building thermal model (CBS-MASS) are presented. Within the analytical validation, the analytical solutions of the steady-state and the transient heat transfer through the exterior walls of an intermediate floor room are compared with the predictions of the computer program. The analysis of the transient process concerns the response of the room air temperature and the inside surface temperature of walls subjected to step-function change of outdoor conditions. Good agreement between the analytical solutions and the simulation results indicates that the basic heat transfer processes are well simulated by the computer program. The inter-program validation deals with the comparison between the estimations of the space thermal loads in one office space provided by the CBS-MASS program against the predictions of two well-known programs used in the thermal analysis of buildings: BLAST and TARP. The results show good agreement between the predictions of these programs. Hence, the analytical and inter-program validation indicates that the CBS-MASS program provides good estimation of the thermal behavior of buildings.     

Application of computational fluid dynamics in building performance simulation for the outdoor environment: an overview

This article provides an overview of the application of computational fluid dynamics (CFD) in building performance simulation for the outdoor environment, focused on four topics: (1) pedestrian wind environment around buildings, (2) wind-driven rain on building facades, (3) convective heat transfer coefficients at exterior building surfaces and (4) air pollutant dispersion around buildings. For each topic, its background, the need for CFD, an overview of some past CFD studies, a discussion about accuracy and some perspectives for practical application are provided. This article indicates that for all four topics, CFD offers considerable advantages compared with wind tunnel modelling or (semi-)empirical formulae because it can provide detailed whole-flow field data under fully controlled conditions and without similarity constraints. The main limitations are the deficiencies of steady Reynolds-averaged Navier–Stokes modelling, the increased complexity and computational expense of large eddy simulation and the requirement of systematic and time-consuming CFD solution verification and validation studies.     

Overheating in English dwellings: comparing modelled and monitored large-scale datasets

ABSTRACT

Monitoring and modelling studies of the indoor environment indicate that there are often discrepancies between simulation results and measurements. The availability of large monitoring datasets of domestic buildings allows for more rigorous validation of the performance of building simulation models derived from limited building information, backed by statistical significance tests and goodness-of-fit metrics. These datasets also offer the opportunity to test modelling assumptions. This paper investigates the performance of domestic housing models using EnergyPlus software to predict maximum daily indoor temperatures over the summer of 2011. Monitored maximum daily indoor temperatures from the English Housing Survey’s (EHS) Energy Follow-Up Survey (EFUS) for 823 nationally representative dwellings are compared against predictions made by EnergyPlus simulations. Due to lack of information on the characteristics of individual dwellings, the models struggle to predict maximum temperatures in individual dwellings and performance was worse on days when the outdoor maximum temperatures were high. This research indicates that unknown factors such as building characteristics, occupant behaviour and local environment makes the validation of models for individual dwellings a challenging task. The models did, however, provide an improved estimate of temperature exposure when aggregated over dwellings within a particular region.     

A case study of validation of an energy analysis program: MICRO-DOE2.1E

A case study is presented of a multiple-step validation undertaken to test the MICRO-DOE2.1E program, which includes the following: (i) response of the model to a given perturbation in the outdoor environment, (ii) comparison with another modelling tool, (iii) sensitivity analysis, and (iv) empirical validation using information from a large existing office building.     

Experimental modelling of buoyancy-driven flows in buildings using a fine-bubble technique

A new technique has been developed for demonstration and experimental modelling of buoyancy-driven ventilation airflows in buildings by using electrolytically generated fine hydrogen bubbles. Experiments for displacement natural ventilation in a single-zone building induced by two types of buoyancy sources, i.e. a point source and a line source, showed that the ventilation and stratification phenomena are successfully modelled by the fine-bubble technique. The experimental results for stratification interfacial positions are in good agreement with both the experimental data and theoretical predictions available in the literature. An analysis has also been carried out on similarities between the natural ventilation flows due to temperature difference and that due to concentration difference.     

Toolbox for development and validation of grey-box building models for forecasting and control

As automatic sensing and information and communication technology get cheaper, building monitoring data becomes easier to obtain. The availability of data leads to new opportunities in the context of energy efficiency in buildings. This paper describes the development and validation of a data-driven grey-box modelling toolbox for buildings. The Python toolbox is based on a Modelica library with thermal building and Heating, Ventilation and Air-Conditioning models and the optimization framework in JModelica.org. The toolchain facilitates and automates the different steps in the system identification procedure, like data handling, model selection, parameter estimation and validation. To validate the methodology, different grey-box models are identified for a single-family dwelling with detailed monitoring data from two experiments. Validated models for forecasting and control can be identified. However, in one experiment the model performance is reduced, likely due to a poor information content in the identification data set.     

Assessment of the Use of Fire Dynamics Simulator in Performance-Based Design

This paper discusses a procedure for the use of fire modelling in the performance-based design environment to quantify design fires for commercial buildings. This procedure includes building surveys, medium-and full-scale experiments and computer modelling. In this study, a survey of commercial premises was conducted to determine fire loads and types of combustibles present in these buildings. Statistical data from the literature were analysed to determine the frequency of fires, ignition sources, and locations relevant to these premises. Based on the results of the survey and the statistical analyses a number of fuel packages were designed that represent fire loads and combustible materials in commercial buildings. The fuel packages were used to perform medium- and full-scale, post-flashover fire tests to collect data on heat release rates, compartment temperatures and production and concentration of toxic gases. Based on the experimental results, input data files for the computational model, Fire Dynamics Simulator (FDS), were developed to simulate the burning characteristics of the fuel packages observed in the experiments. Comparative analysis between FDS model predictions and experimental data of HRR, carbon monoxide (CO), and carbon dioxide (CO₂), indicated that FDS model was able to predict the HRR, temperature profile in the burn room, and the total production of CO and CO₂ for medium- and large-scale experiments as well as real size stores.     

Cross-correlations between weather variables in Australia

The information on climate variations is essential for the research of many subjects, such as the performance of buildings and agricultural production. However, recorded meteorological data are often incomplete. There may be a limited number of locations recorded, while the number of recorded climatic variables and the time intervals can also be inadequate. Therefore, the hourly data of key weather parameters as required by many building simulation programmes are typically not readily available. To overcome this gap in measured information, several empirical methods and weather data generators have been developed. They generally employ statistical analysis techniques to model the variations of individual climatic variables, while the possible interactions between different weather parameters are largely ignored.     

Development of a control algorithm to optimize airflow rates through variable size windows

The present paper aims in investigating, in a systematic way, using both experimental and theoretical tools, the potential of natural ventilation control techniques when applied to full scale buildings. Experiments have been carried out in outdoor test cell and different configurations have been tested for two window types (bottom hung and sliding) under various meteorological conditions. Based on the experimental results, specific modeling activities have been undertaken and theoretical methods for calculating airflow rates through the above-mentioned windows have been developed. The theoretical predictions are compared with the corresponding experimental data and a very satisfactory agreement has been observed. Following the data analysis an algorithm was developed for the control of the natural ventilation.     

The gap between predicted and measured energy performance of buildings: A framework for investigation

There often is a significant difference between predicted (computed) energy performance of buildings and actual measured energy use once buildings are operational. This article reviews literature on this ‘performance gap’. It discerns three main types of gap: (1) between first-principle predictions and measurements, (2) between machine learning and measurements, and (3) between predictions and display certificates in legislation. It presents a pilot study that attempts an initial probabilistic probe into the performance gap. Findings from this pilot study are used to identify a number of key issues that need to be addressed within future investigations of the performance gap in general, especially the fact that the performance gap is a function of time and external conditions. The paper concludes that the performance gap can only be bridged by a broad, coordinated approach that combines model validation and verification, improved data collection for predictions, better forecasting, and change of industry practice.     

Energetische Sanierung von Schulgebäuden in den neuen Bundesländern – Sanierungsprojekt Förderschule Rathenow

Energy efficiency improvements for school buildings in Germany's new federal states; Rathenow special school refurbishment project. Current energy saving measures for existing buildings focus on refurbishment of schools and other educational buildings. The building described in this article represents the standard type of a large‐panel construction series in the new federal states. Due to the large number of buildings (540) constructed in this way the project can act as a model for similar projects. Initial studies indicated that structural refurbishment measures for these buildings are required as a matter or urgency. The energy performance calculations for the building showed good agreement between the calculated demand values and actual heating energy consumption values and can serve as basis for predictions of energy savings through various refurbishment measures. The new DIN 18599 calculation standard enables significantly more differentiated consideration of boundary conditions such as occupied periods, occupancy levels, internal heat sources, and the effect of night setback. Based on comparative calculations, different refurbishment concepts can be developed and assessed.     

History and development of validation with the ESP-r simulation program

It is well recognised that validation of dynamic building simulation programs is a long-term complex task. There have been many large national and international efforts that have led to a well-established validation methodology comprising analytical, inter-program comparison and empirical validation elements, and a significant number of tests have been developed. As simulation usage increases, driven by such initiatives as the European Energy Performance of Buildings Directive, such tests are starting to be incorporated into national and international standards. Although many program developers have run many of the developed tests, there does not appear to have been a systematic attempt to incorporate such tests into routine operation of the simulation programs. This paper reports work undertaken to address this deficiency. The paper summarizes the tests that have been applied to the simulation program ESP-r. These tests have been developed within International Energy Agency Annexes, within CEN standards, within various large-scale national projects, and by the UK's Chartered Institution of Building Services Engineers. The structure used to encapsulate the tests allows developers to ensure that recent code modifications have not resulted in unforeseen impacts on program predictions, and allows users to check for themselves against benchmarks.     

Occupants' operation of lighting and shading systems in office buildings

In most buildings, people operate control devices such as windows, shades, luminaires, radiators and fans to bring about desirable indoor environmental conditions. These control actions have a significant impact on buildings' performance and sustainability (energy use, indoor climate). A better understanding of the logic and patterns of such control-oriented user behaviour can not only facilitate better predictions of buildings' performance, but also support the effective operation of buildings' service systems. This paper describes an extensive empirical study of control-oriented user behaviour (as related to systems for lighting and shading) in a number of office buildings in Austria. The results specifically shed light on the relationships between control actions and environmental conditions inside and outside buildings.     

Predicting pile dynamic capacity via application of an evolutionary algorithm

This study presents the development of a new model obtained from the correlation of dynamic input and SPT data with pile capacity. An evolutionary algorithm, gene expression programming (GEP), was used for modelling the correlation. The data used for model development comprised 24 cases obtained from existing literature. The modelling was carried out by dividing the data into two sets: a training set for model calibration and a validation set for verifying the generalization capability of the model. The performance of the model was evaluated by comparing its predictions of pile capacity with experimental data and with predictions of pile capacity by two commonly used traditional methods and the artificial neural networks (ANNs) model. It was found that the model performs well with a coefficient of determination, mean, standard deviation and probability density at 50% equivalent to 0.94, 1.08, 0.14, and 1.05, respectively, for the training set, and 0.96, 0.95, 0.13, and 0.93, respectively, for the validation set. The low values of the calculated mean squared error and mean absolute error indicated that the model is accurate in predicting pile capacity. The results of comparison also showed that the model predicted pile capacity more accurately than traditional methods including the ANNs model.     

Bewertung bestehender Natursteinbogenbrücken

Assessment of existing natural stone arch bridges. Arch bridges made of natural stone masonry rank among the oldest structures still in full function within road and railways. With a age from partly far over 100 years these represent historically very valuable built volumes in large number of several thousand buildings at the same time. The oldest existing bridges based on empirical values design, later there were graphic procedures for structural design, one developed approximation formulas on basis of the arch line of thrust for the draft of substantial geometry parameters such as span, type of arch as well as arch thickness at the crown and springing. In the course of the revision of these buildings evaluations regarding load‐carrying capacity and serviceability on the basis are demanded under today valid loads and standards. In this paper apart from a short overview to the existing arch bridges the possibilities of the structural modelling are discussed. An emphasis forms the computation of the masonry load‐carrying capacity, which is described in particular by safety considerations. The procedures referred to the bridge construction are transferable in principle to other structures of building construction.     

Empirical validation of building energy simulation programs

The largest-ever exercise to validate dynamic thermal simulation programs (DSPs) of buildings has recently been completed. It involved 25 program/user combinations from Europe, the USA and Australia, and included both commercial and public domain programs. Predictions were produced for three single-zone test rooms in the UK. These had either a single-glazed or double-glazed south-facing window, or no window at all. In one 10-day period the rooms were intermittently heated and in another 10-day period they were unheated. The predictions of heating energy demands and air temperatures were compared. The observed interprogram variability was highly likely to be due to inherent differences between the DSPs, rather than the way they were used. Predictions of the difference in performance of two rooms were no more consistent than predictions of the absolute performance of a single room. By comparing the predictions with the measurements and taking due account of experimental uncertainty, the DSPs that are likely to contain significant internal errors are distinguished from those which, in these tests, performed much better. The likely sources of internal error are discussed. It is recommended that empirical validation exercises should consist of an initial blind phase in which program users are unaware of the actual measured performance of the building, and then an open phase in which the measurements are made available. The work has produced five empirical validation benchmarks, which have significant practical benefits for program users, vendors and potential purchasers. There is considerable scope for improving the predictive ability of DSPs and so suggestions for further work are made.     

Numerical model and validation experiments of atrium enclosure fire in a new fire test facility

The use of computational fluid dynamics (CFD) as a tool for buildings, warehouses or factories design requirements fulfilling about fire safety is becoming more common and reliable. Performance-based fire safety assurance procedures make use of the CFD fire modelling to anticipate the evolution of fire, but they need always to be validated. This is especially difficult for big structures, with great clear volumes, where effects of natural and forced ventilation can be very scale dependent. A good opportunity to check the prediction capability of CFD codes to establish temperatures and velocities fields is the new full-scale fire test facility of the Technological Metal Centre in Murcia, Spain. It is an aluminium prismatic squared base building of 19.5 m×19.5 m×20 m, with several vents arranged in its walls and four exhaust fans at the roof. Series of experimental tests have been carried out using several heptane normalized pool-fires placed at the centre of the atrium. The data obtained from these experiments have been later used in a validation study of two CFD simulations implemented for temperature wall, ambient temperature prediction and exhaust fan assessment. The results show good agreement between experimental and numerical predictions and allow concluding that for a fire test of 1.6 MW of average heat release power, the exhaust and ventilation system is not enough to extract the hot combustion products. There is an excessive and dangerous accumulation of hot gases at the upper part of the atrium and the exhaust capacity of the roof fans must be increased. The CFD models can give the answer to that question.     

Clustering a building stock towards representative buildings in the context of air-conditioning electricity demand flexibility

Energy modelling for the prediction of energy use in buildings, especially under novel energy management strategies, is of great importance. In buildings there are several flexible electrical loads which can be shifted in time such as thermostatically controllable loads. The main novelty of this paper is to apply an aggregation method to effectively characterize the electrical energy demand of air-conditioning (AC) systems in residential buildings under flexible operation during demand response and demand shaping programs. The method is based on clustering techniques to aggregate a large and diverse building stock of residential buildings to a smaller, representative ensemble of buildings. The methodology is tested against a detailed simulation model of building stocks in Houston, New York and Los Angeles. Results show good agreement between the energy demand predicted by the aggregated model and by the full model during normal operation (normalized mean absolute error, NMAE, below 10%), even with a small number of clusters (sample size of 1%). During flexible operation, the NMAE rises (around 20%) and a higher number of representative buildings become necessary (sample size at least 10%). Multiple cases for the input data series were considered, namely by varying the time resolution of the input data and the type of input data. These characteristics of the input time series data are shown to play a crucial role in the aggregation performance. The aggregated model showed lower NMAE compared to the original model when clustering is based on a hybrid signal resolved at 60-minute time intervals, which is a combination of the electricity demand profile and AC modulation level.