BuildOpt—a new building energy simulation program that is built on smooth models

Building energy simulation programs compute numerical approximations to physical phenomena that can be modeled by a system of differential algebraic equations (DAE). For a large class of building energy analysis problems, one can prove that the DAE system has unique solution that is once continuously differentiable in the building design parameters. Consequently, if building simulation programs are built on models that satisfy the smoothness assumptions required to prove existence of a unique smooth solution, and if their numerical solvers allow controlling the approximation error, one can use such programs with generalized pattern search optimization algorithms that adaptively control the precision of the solutions of the DAE system. Those optimization algorithms construct sequences of iterates with stationary accumulation points and have been shown to yield a significant reduction in computation time compared to algorithms that use fixed precision cost function evaluations.In this paper, we state the required smoothness assumptions and present the theorems that state existence of a unique smooth solution of the DAE system. We present BuildOpt, a detailed thermal and daylighting building energy simulation program. We discuss examples that explain the smoothing techniques used in BuildOpt. We present numerical experiments that compare the computation time for an annual simulation with the smoothing techniques applied to different parts of the models. The experiments show that high precision approximate solutions can only be computed if smooth models are used. This is significant because today's building simulation programs do not use such smoothing techniques and their solvers frequently fail to obtain a numerical solution if the solver tolerances are tight. We also present how BuildOpt's approximate solutions converge to a smooth function as the precision parameter of the numerical solver is tightened.     

Stochastic analysis of building thermal processes

A methodology is presented for investigating the uncertainty properties of the building thermal processes caused by the random behaviour of the meteorological processes and the casual gains. A detailed building thermal model is used with a stochastic weather model and a random casual gain model. The probability distribution of the zone temperature of the building is calculated directly from these models. The overheating risk has been analysed as an example. The probability distribution of the periods when the zone temperature is higher than the demand temperature is calculated. The result shows all the possible situations rather than only a sample as would be obtained by running a normal simulation using given weather data. The influence of different building components on the overheating risk has been studied. The result shows that the most likely component for overheating risk in a residential building in Beijing is the window size. The thermal mass of the internal walls and the placing of windows have little effect on overheating risk.     

Measurement of diffusion coefficients of VOCs for building materials: review and development of a calculation procedure

The measurement and prediction of building material emission rates have been the subject of intensive research over the past decade, resulting in the development of advanced sensory and chemical analysis measurement techniques as well as the development of analytical and numerical models. One of the important input parameters for these models is the diffusion coefficient. Several experimental techniques have been applied to estimate the diffusion coefficient. An extensive literature review of the techniques used to measure this coefficient was carried out, for building materials exposed to volatile organic compounds (VOC). This paper reviews these techniques; it also analyses the results and discusses the possible causes of difference in the reported data. It was noted that the discrepancy between the different results was mainly because of the assumptions made in and the techniques used to analyze the data. For a given technique, the results show that there can be a difference of up to 700% in the reported data. Moreover, the paper proposes what is referred to as the mass exchanger method, to calculate diffusion coefficients considering both diffusion and convection. The results obtained by this mass exchanger method were compared with those obtained by the existing method considering only diffusion. It was demonstrated that, for porous materials, the convection resistance could not be ignored when compared with the diffusion resistance.     

Feasibility of utilizing numerical viscosity from coarse grid CFD for fast turbulence modeling of indoor environments

Computational fluid dynamics (CFD) is a useful tool in building indoor environment study. However, the notorious computational effort of CFD is a significant drawback that restricts its applications in many areas and stages. Factors such as grid resolution and turbulence modeling are the main reasons that lead to large computing cost of this method. This study investigates the feasibility of utilizing inherent numerical viscosity induced by coarse CFD grid, coupled with simplest turbulence model, to greatly reduce the computational cost while maintaining reasonable modeling accuracy of CFD. Numerical viscosity introduced from space discretization in a carefully specified coarse grid resolution may have similar magnitude as turbulence viscosity for typical indoor airflows. This presents potentials of substituting sophisticated turbulence models with inherent numerical viscosity models from coarse grid CFD that are often used in fast CFD analysis. Case studies were conducted to validate the analytical findings, by comparing the coarse grid CFD predictions with the grid-independent CFD solutions as well as experimental data obtained from literature. The study shows that a uniform coarse grid can be applied, along with a constant turbulence viscosity model, to reasonably predict general airflow patterns in typical indoor environments. Although such predictions may not be as precise as fine-grid CFDs with well validated complex turbulence models, the accuracy is acceptable for indoor environment study, especially at an early stage of a project. The computing speed is about 100 times faster than a fine-grid CFD, which makes it possible to simulate a complicated 3-dimensional building in real-time (or near real-time) with personal computer.     

Development and validation of regression models to predict monthly heating demand for residential buildings

The present research work concerns development of regression models to predict the monthly heating demand for single-family residential sector in temperate climates, with the aim to be used by architects or design engineers as support tools in the very first stage of their projects in finding efficiently energetic solutions. Another interest to use such simplified models is to make it possible a very quick parametric study in order to optimize the building structure versus environmental or economic criteria. All the energy prediction models were based on an extended database obtained by dynamic simulations for 16 major cities of France. The inputs for the regression models are the building shape factor, the building envelope U-value, the window to floor area ratio, the building time constant and the climate which is defined as function of the sol-air temperature and heating set-point. If the neural network (NN) methods could give precise representations in predicting energy use, with the advantage that they are capable of adjusting themselves to unexpected pattern changes in the incoming data, the multiple regression analysis was also found to be an efficient method, nevertheless with the requirement that an extended database should be used for the regression. The validation is probably the most important level when trying to find prediction models, so 270 different scenarios are analysed in this research work for different inputs of the models. It has been established that the energy equations obtained can do predictions quite well, a maximum deviation between the predicted and the simulated is noticed to be 5.1% for Nice climate, with an average error of 2%. In this paper, we also show that is possible to predict the building heating demand even for more complex scenarios, when the construction is adjacent to non-heated spaces, basements or roof attics.     

Analytical investigation of elastic period of infilled RC MRF buildings

Fundamental period of vibration, dependent on mass and stiffness structure characteristics, is a key parameter in assessing seismic demand. The period can be evaluated both by means of empirical formulas and modal analysis carried out on a structure numerical model. The presence of external or internal infill elements, usually considered as “non-structural” elements, is generally not taken into account in structural modelling, although these elements can significantly increase the lateral stiffness of a Reinforced Concrete (RC) Moment Resisting Frame (MRF) building leading to a modification in dynamic properties.In this study, results of modal analyses carried out on 3D numerical RC MRF building models are presented, varying structure morphology (height, surface area, ratio between plan dimensions) and infill characteristics. Simplified formulas based on regression analysis of obtained numerical data are presented and discussed. These relationships are also compared with similar literature numerical expressions and empirical data from experimental measurements on existing buildings.     

Detail design,building and commissioning of tall building structural models for experimental shaking table tests

In the areas of seismic engineering, shaking table tests are powerful methods for assessing the seismic capacity of buildings. Since the size and capacity of existing shaking tables are limited, using scale structural models seems to be necessary. In recent years, many experimental studies have been performed using shaking table tests to determine seismic response of structural models subjected to various earthquake records. However, none of the past research works discussed practical procedure for creating the physical model. Therefore, in this study, a comprehensive procedure for design, building and commissioning of scale tall building structural models has been developed and presented for practical applications in shaking table test programmes. To validate the structural model, shaking table tests and numerical time history dynamic analyses were performed under the influence of different scaled earthquake acceleration records. Comparing the numerical predictions and experimental values of maximum lateral displacements, it became apparent that the numerical predictions and laboratory measurements are in a good agreement. As a result, the scale structural model can replicate the behaviour of real tall buildings with acceptable accuracy. It is concluded that the physical model is a valid and qualified model that can be employed for experimental shaking table tests. Copyright © 2015 John Wiley & Sons, Ltd.     

裂隙网络模型在地下水数值模拟中的应用研究进展

地下水在裂隙介质中的渗流和运移过程与在多孔介质中的过程存在机理上的差别,这与裂隙系统的尺度效应和非均质性有关,这也给数值模拟带来困难。采用裂隙网络模型可以对发生在不同尺度上的渗流和运移过程进行模拟,从而有效地解决以上存在的问题。构建裂隙网络模型的方法主要有体视学方法和随机模拟方法。按照假设条件和概念框架的不同,裂隙网络模型主要可分为连续体模型、离散裂隙模型和混合模型,在应用过程中可根据研究区的实际情况选择合适的模型。本文在对已有成果进行综合论述的基础上,指出其中存在的不足和需要改进之处,从而为以后的进一步研究指明方向。     

Numerical modelling of the structural fire behaviour of composite buildings

This paper describes numerical models constructed to simulate the response of composite steel/concrete building floors under fire conditions. In particular, this study deals with two of the fire tests recently undertaken on a full-scale multi-storey building at Cardington, UK. The analysis is carried out using a structural analysis program which accounts for both geometric and material nonlinearities, and which includes temperature-dependent constitutive models for steel and concrete materials. The approaches used to represent the various structural details are discussed, and the procedure employed for incorporating the experimentally measured temperature profiles and histories is outlined. For the two tests considered in this investigation, the numerical results are in general agreement with the experimental data, particularly in terms of the magnitude of vertical deformations induced in the floors at elevated temperatures. Close examination of the numerical and experimental findings provides an insight into the complex interactions that occur in the structure at elevated temperatures. Most significantly, the influence of the restraint to thermal expansion of the heated floor area, which is provided by the surrounding parts of the structure, is shown to be of paramount importance. The increasing confidence that can be placed in numerical models as well as the improved understanding of the structural fire response may be used in developing more realistic and cost-effective design methods which are based on the actual structural response rather than that of isolated members.     

檐口形状对低矮房屋屋面风压分布的影响

基于计算流体动力学（CFD）和剪切应力输运（SST）k-ω湍流模型,对带不同尺寸檐口低矮房屋的屋盖风压进行了数值模拟计算.首先,对TTU建筑模型屋盖体型系数进行数值计算,并与其他文献的结果进行对比吻合较好,验证了本文计算方法和湍流模型参数选取的合理性.然后,基于此方法研究不同尺寸檐口对低矮房屋屋面体型系数分布情况,总结出檐口尺寸对屋盖体型系数变化的规律,优化其抗风性能,研究结果可为该类建筑的工程抗风设计提供参考.     

Computational fluid dynamics and artificial neural network-based analysis and forecasting of wind effects on obliquely parallel multiple building models using categorical variable encoding

This research investigates the influence of wind on four closely spaced parallel building models using computational fluid dynamics (CFD). The buildings are positioned either perpendicular to the wind direction or at various oblique angles. The aerodynamic results obtained for these buildings in an interfering condition are compared to those of an isolated tall building using the interference and obliquity effect (IOE) factor. Graphical comparisons are made among the different models and faces, considering various obliquity angles (OAs). The inner building models exhibit higher pressure and force coefficients at higher OAs. The variation of pressure coefficients along the horizontal peripheral direction is also analyzed, and the trade-offs of higher and lower OAs are discussed for the different building models. Furthermore, an artificial neural network (ANN) is trained using surface pressure coefficients from approximately 6000 data points distributed over different facets of building models. Categorical encoding is employed using one-hot encoding-based dummy variables for different building models, while numerical variables such as OA and X, Y, and Z coordinates are included as input for the ANN. The ANN is trained using a total of 238,340 data points (considering different building models and different OA scenarios), and its parameters are monitored during training to minimize errors and achieve high predictability. Finally, a representative case is used to plot the pressure contour obtained from the trained ANN, which is shown to be highly comparable to the CFD-based contour.     

Bestimmung des thermischen und hygrischen Zustands der Raumluft bei freier Konvektion

Determination of the thermal and hygric room air parameters considering buoyancy and free convection. The knowledge of the room air parameters concerning temperature and moisture already in the planning phase of a building is significant in various ways. Especially in high rooms a vertical gradient of temperature and moisture may occur. The influence of buoyancy and free convection should not be neglected in a calculation. Therefore suitable mathematical models are needed. A field model and a multi‐zone model were developed and the results were being compared with the measured data. The use of the field model leads to detailed information about the room air parameters at any position in the room; the numerical effort indeed is very high. By use of the multi‐zone model it is possible to calculate the room air parameters at some spaces in the room taking principle buoyancy effects into account; the numerical effort is low. The two models supplement each other and give the chance to adapt the numerical effort to the problem.     

Performance of wall-stud cold-formed shear panels under monotonic and cyclic loading: Part II: Numerical modelling and performance analysis

The main components to provide earthquake performance of a light-gauge steel house are the shear walls. Understanding shear wall behaviour and finding suitable hysteretic models is important in order to be able to build realistic finite element models and assess structural performance in case of earthquake. As for any building structure expected to exceed its elastic behaviour-range in case of earthquake, the interaction of design capacity, load bearing capacity and structural ductility will influence the performance.In this paper alternative design methods and hysteretic modeling techniques are presented. Based on tests described in Part I, a numerical equivalent model for hysteretic behavior of wall panels working in shear was built and used in 3D dynamic nonlinear analysis of cold-formed steel framed buildings. Preliminary conclusions refer to the effect of over-strength and ductility upon possible earthquake load reduction in case of light-gauge shear wall structures.     

Experimental and numerical investigation of brace configuration effects on steel structures

The study is concerned with the experimental and numerical investigations of brace configurations on steel buildings in terms of dynamic characteristics. A three-storey steel building model with 1/2 scale of a real building, which was constructed at the laboratory of Civil Engineering Department of Karadeniz Technical University, was selected for investigations. A series of ambient vibration tests were conducted on the building model for bare frame and braced cases. Four different brace types were applied to the model: cross type, Λ type, V type and K type. The natural frequencies and their associated mode shapes and modal damping ratios were identified for each different case in the frequency domain by the Frequency Domain Decomposition method. Also, finite element models for these cases were developed to simulate dynamic behavior. The effect of brace configurations was evaluated by comparing the braced dynamic characteristics with those of the bare case. Also, the experimental and numerical dynamic characteristics were compared with each other, the differences between results were revealed by considering experimental results as exact. The study showed that the stiffness of steel buildings can be increased by applying brace elements considerably and the effects of braces vary depending on brace configuration. The cross type bracing produced the highest stiffness both experimentally and numerically. From the finite element analysis, it was observed that the numerical results were bigger than the experimental results in all cases; therefore the initial finite element models need to be updated.     

Predicting psychrometric conditions in biocontaminant microenvironments with a microclimate heat and moisture transfer model -- description and field comparison

A numerical model is described that is designed to model psychrometric conditions in biocontaminant microenvironments, such as in bedding and the base of carpets for dust-mites, and on the surface of linings for molds. The model is very general and can include room air, other room components, other zones including the outdoors, other rooms and any subfloor space. Mechanical plant can be modeled. Good agreement between modeled and field results are reported for the complex case of an occupied bed and for the microclimate in the base of a carpet, before and after its timber floor above a crawl space was retrofitted with insulation. PRACTICAL IMPLICATIONS: Biocontaminants such as dust-mites and molds can pose serious health problems. Understanding microclimates in biocontaminant microhabitats, when coupled with biologic models, will make it possible to predict how the life cycles of these biocontaminants are affected as these conditions change. In turn, this will suggest which interventions that modify indoor climate and microclimate are likely to control these biocontaminants. Furthermore such interventions might include indoor humidity control, changing building insulation and ventilation levels, covering mattresses, use of electric blankets, use of carpet heating, etc. Such models will provide a fast way for screening for interventions that are likely to be effective in the control of biocontaminants.     

Evaluation of distributed environmental control systems for improving IAQ and reducing energy consumption in office buildings

Conventional heating, ventilation, and air conditioning (HVAC) systems are incapable of providing control over individual environments or adjusting fresh air supply based on the dynamic occupancy of individual rooms in an office building. This paper introduces the concept of distributed environmental control systems (DECS) and shows that improvement in indoor air quality (IAQ) and energy efficiency can be achieved by providing required amounts of fresh air directly to the individual office spaces through distributed demand controlled ventilation (DDCV). In DDCV, fresh air is provided to each micro-environment (room or cubicle) based on input from distributed sensors (CO₂, VOC, occupancy, etc.) or intelligent scheduling techniques to provide acceptable IAQ for each occupant, rather than for groups or populations of occupants. In order to study DECS, a numerical model was developed that incorporates some of the best available models for studying building energy consumption, indoor air flow, contaminant transport and HVAC system performance. The developed model was applied to a DECS in a model office building equipped with a DDCV system. By implementing DECS/DDCV and intelligent scheduling techniques it is possible to achieve an improvement in IAQ along with a reduction in annual energy consumption compared to conventional ventilation systems.     

建筑结构倒塌过程模拟与防倒塌设计

针对结构性能的数值模拟方法进行了综合分析,基于离散单元法提出了结构倒塌分析的理论模型。通过试验研究了混凝土块体间碰撞的力学行为,并结合扩展的数值分析建立了混凝土块体在不同碰撞形式下的计算模型。针对建筑物内的局部爆炸作用,在分析构件反应的基础上采用离散单元法对结构平面及空间倒塌过程进行了数值模拟。建立了适用于任意加载路径的材料弹簧力-位移本构关系,据此分析了地震作用下钢筋混凝土框架结构以及砌体结构空间倒塌过程。采用基于OpenGL的图形建模技术,实现了结构倒塌过程数值模拟结果的三维可视化。模拟结果与振动台模型试验结果及工程实测结果比较表明,所采用的离散单元法适合结构大变形阶段的分析。为提高计算效率和精度,有必要采用多尺度的模拟分析。另外,对不同荷载及作用下建筑结构抗倒塌设计方法进行了总结。并指出结构参数对抗连续倒塌性能的影响、结构倒塌机理、实用的防连续倒塌设计方法以及地震作用下结构防倒塌定量设计方法等方面尚待深入研究,以便建立相应的防倒塌设计规范。图15参21     

Effect of calculation zoning on numerical modelling of ventilation airflows

The paper presents the results of numerical simulation of infiltration and ventilation airflows in three different objects: small single-family building, school building and multifamily building. Each of these buildings was represented by several different numerical models varying in the degree of detail of calculation zoning representation, from the simplest, single-zone models to complicated, multizone ones. The results of simulations provided the data, which enable indication how the detail of zoning of the building affects the results of calculations of ventilation airflows. Simulations were carried out in CONTAM software. The results showed that the detail of zoning causes differences in air infiltration within the range of 7%–40% for particular cases. Several guidelines concerning building numerical models for simulation of ventilation airflows were formulated.