Simulation Tools for the Building and its System

Simulation involves the creation of numerical models of a building and is thereby a process of simplifying the complex physical reality to a computable set of equations [27,28]. In other words, the purpose of modelling is to create a mathematical model from a physical system [29]. In the past few decades, the development and professional use of simulation tools has been strongly evolved. To predict the unsteady indoor conditions in a building, many simulation tools are available. Underwood and Yik categorized these tools into three groups [30]. A fourth group was added in this dissertation to incorporate the software focussing on modelling of the building envelope. The four groups are:

 Group 1: Building energy and environment. Part of this group of simulation tools are building energy simulation (BES) software. They are widely used for the evaluation or comparison of different heating systems to meet sizing and energy operating cost

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requirements [31]. In the work of Harish and Kumar [32] a review can be read of all noteworthy modelling methodologies which have been developed and adopted to model the energy systems of buildings.

 Group 2: Plant and control: This group consists of models which focusses on the modelling of systems, plants and control. Some programs belonging to the first group also provide a full treatment of the plants and controls [30].

 Group 3: Zonal ventilation modelling and computational fluid dynamics: This group consists of models which focus on the airflow in a space.

 Group 4: Building envelope: In this group detailed transient tools have been developed (e.g. in the context of IEA Annex 24 [33]) for combined heat, air and moisture transfer (HAM) within individual building components [34].

In the scope of this work, following criteria were considered in selecting the simulation tool:

- The model of the building contains the room or whole building and its systems (not modelling microclimate).

- The modelling tool has to estimate long-term fluctuations, as well as short-term fluctuations. In other words, a non-steady calculation of the building and its system for at least a year.

- The simulation tool has to be fast so the calculation of one retrofitting option for a case study will be performed in maximum one hour.

- The calculations can be performed by a ‘standard’ laptop (8GB RAM –CPU 2 cores- 2.67 GHz).

Based on these criteria, the preferred tool to estimate the indoor climate in a historic building is the tool which is also used for the modelling of building energy use (group 1). These tools are most suitable because they calculate the desired parameters over the course of a full year relatively fast, which is needed to be able to evaluate the indoor climate for the long term seasonal changes [35–37]. Thereby, a fast calculation allows to simulate, analyse and compare multiple retrofitting strategies and define the ‘optimal’ solution. Concerning historical buildings, where an insufficient climate could cause the loss of irreplaceable valuable works of art, this makes those simulation tools indispensable [22]. Damage to works of art can also be studied with computational fluid dynamics (CFD – group 3) [38–40]. For example, in a previous project (FWO G.0420.05) a coupled 3D-HAM-CFD-model² has been developed which predicts the local temperature and relative humidity variations of the indoor air together with the hygrothermal interaction with hygroscopic materials like sculpture, panel paintings, books,… [41,42]. However, CFD is not in the scope of this work since this tool is too computationally demanding and too time-consuming.

Simulation Tools for the Building (group 1)

According to ASHRAE handbook [43], modelling of building energy use can be classified into two different approaches: forward and inverse approach.

2 link between Building envelope and CFD

The forward modelling approach, also called the law-driven approach, is the classical approach.

The objective of this approach is to predict the output (e.g. the temperature course) based on input of the physical system (e.g. weather, occupancy, ...). This approach includes Building Energy Simulation (BES) models where TRNSYS, ESP-r, BLAST, DOE-2, and Energy Plus are the most widespread simulation codes [37]. In the forward approach, the goal is to build a model of the building and its boundary conditions as detailed as necessary. To do so, information is needed about the building geometry, material properties, user behaviour, internal gains, … For old historic buildings, however, this information is often lacking. Furthermore, destructive methods to obtain building material properties are often not allowed because the building is protected [44].

Therefore, some researchers prefer the second approach, the inverse or data-driven approach.

Inverse approach refers to modelling methods which determine model parameters by matching the output of the model as close as possible to measurement data [44,45]. The data-driven approach has a higher accuracy than the forward modelling approach, but suffers from generalization beyond the existing situation and is therefore more useful for the evaluation of as-built system performance [37,46] [47]. In other words, the forward modelling approach is satisfactory and allows more accurate prediction of future system performance under specific, real boundary conditions..

Figure 1.3: Law-driven (forward) models vs. data-driven (inverse) models

In this dissertation, it is preferred to work with the forward modelling approach. Although more assumptions are necessary, the classical approach is more appropriate to design a new system or to improve the existing system. To deal with the lack of some detailed information, on required input parameters, in this work the BES models were calibrated using measured data, which is called grey box modelling approach [47–49].

Other tools necessary?

To assess the preservation conditions properly, it is important to take typical conditions in monumental historical buildings into account in the simulation study which are calculated by

Detailed Physical Model of

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tools from another group. For example; the presence of moisture in heavy building walls (group 4: HAM) and the occurrence of hygrothermal gradients in the often very large interior volumes (group 3: zonal airflow model).

Though fully integrated programs encompassing all groups are possible, as shown in Figure 1.4, the current state-of-the-art remains somewhat fragmented and a single program code that treats all areas in an integrated manner is still under development [30].

Figure 1.4: Relationships between available program codes. Based on Underwood and Yik [30].

This PhD-dissertation aims at developing a simulation strategy to assess the damage risk for works of art, taking into account the presence of moisture in heavy building walls and the occurrence of hygrothermal gradients (stratification) in the often very large interior volumes due to the limited control by (older) climate installation system. The emphasis lies on developing a fast calculating modelling approach intended for practical use which predicts if the preservation measures lead to the desired improvement concerning preservation conditions. This holds that there was started from a ‘classical’ BES tool and it has been studied which adjustments to the tool are required to contain the mentioned boundary conditions. This means that the necessary adjustments are integrated in the BES-tool and not linked to another software tool. Because the results of the simulation study are used to assess and to compare the outcome on the indoor climate of different retro-fitting measures, there is also looked which assessment tool is suitable.