van Awm Jos Schijndel

Modeling and solving building physics problems with FemLab

The commercially available software package FemLab is evaluated as solver for building physics problems based on partial differential equations (PDEs). The software is designed to simulate systems of coupled PDEs which may be 1D, 2D or 3D, non-linear and time dependent. An important feature of FemLab is that the user can focus on the model (PDE coefficients on the domain and boundary) and does not have to spend much time on solving and visualization. In this paper, 4 cases are considered. First, in order to illustrate how FemLab works, an example including the complete code for solving as well as the results are given for a simple 2D steady-state heat transfer problem. In the next 2 cases, the reliability is tested for two very different building physics problems: A 2D dynamic airflow problem, modeled using Navier–Stokes and buoyancy equations, and a 1D dynamic non-linear moisture transport in a porous material. These simulation results are validated and show a good agreement with measurements. In the last case, FemLabs capability of simulating 3D problems is shown by a dynamic combined heat and moisture transport problem. This example is a 3D extension of a given 2D problem from IEA Annex 24 (Final Report—Task 1). For all models the crucial part of the codes (geometry, PDEs and boundary specifications) are given. The FemLab software is written in the MatLab environment (The Mathworks, Inc. MatLab manual, Version 5.3, 1998) and therefore it is possible to use the visualization tools, toolboxes and all other programs written in MatLab. The evaluation illustrates the powerful and flexible nature of FemLab for solving scientific and engineering building physics problems.

Optimal operation of a hospital power plant

In this paper the operation of an Academic Hospital installation is evaluated by simulation and optimization on a yearly base. A mathematical model has been developed, which is based on energy balances of the installed components. Manufacturer specifications of the components are used for calculating the parameters. The model is formulated using vector equations. Advantages of this type of model formulations are presented. The tools used for optimization are custom developed back-tracking methods for calculating a good starting point and a SQP optimization tool for finding the optimum. Detailed control strategies are calculated for three types of optimization strategies simulated. The simulation results show the impact of the choice of a control strategy on the optimized operation. The results are also applicable for on-line setpoint optimization.

A review of the application of SimuLink S-functions to multi domain modeling and building simulation

Multi domain modelling provides great opportunities for possible synergy between the building simulation domain and other scientific and technological domains. Although domains may have quite different models, they often use common mathematical representations, based on differential algebraic equations (DAEs) and/or ordinary differential equations (ODEs). This paper reviews the use of S-Functions in SimuLink for DAEs and ODEs modelling regarding building simulation and its potential for multi domain applications. It is concluded that ODEs are directly implementable using S-Functions in SimuLink. DAEs are indirectly implementable by a manual process of integrating Dymola/Modelica models. Examples from the literature confirm the great opportunities for the combined building thermal, geothermal, electrical and grid performance simulation.Multi domain modelling provides great opportunities for possible synergy between the building simulation domain and other scientific and technological domains. Although domains may have quite different models, they often use common mathematical representations, based on differential algebraic equations (DAEs) and/or ordinary differential equations (ODEs). This paper reviews the use of S-Functions in SimuLink for DAEs and ODEs modelling regarding building simulation and its potential for multi domain applications. It is concluded that ODEs are directly implementable using S-Functions in SimuLink. DAEs are indirectly implementable by a manual process of integrating Dymola/Modelica models. Examples from the literature confirm the great opportunities for the combined building thermal, geothermal, electrical and grid performance simulation.

Evaluation of the Climate Control Performance and Reliability of Active Display Cases

The study concerns the reliability of active display cases to be used at the Dutch Maritime Museum located in Amsterdam. The paper presents heat, air and moisture (HAM) models of display cases and the indoor climate of the zone surrounding them. Furthermore, data from measurements are provided for validation purposes. It is concluded that in case of failure of the climate system, responsible for the indoor climate surrounding the active display case, the climate inside the active display case will stay within the required limits for more than five hours during the winter and for more than half an hour during the summer. However, some undetected failure scenarios could be responsible for exceeding the required limits of the indoor climate inside the display case within five minutes. The latter shows the importance of the presence of reliable failure detection and handling system.

The effect of micro air movement on the heat and moisture characteristics of building constructions

The present study aims at the reliability analysis of steel towers against the limit state of deflection. For this purpose tip deflection of the tower has been obtained after carrying out the dynamic analysis of the tower using modal method. This tip deflection is employed for subsequent reliability analysis. A limit state function based on serviceability criterion of deflection is derived in terms of random variables. A complete procedure of reliability computation is then presented. To study the influence of various random variables on tower reliability, sensitivity analysis has been carried out. Design points, important for probabilistic design of towers, are also located on the failure surface. Some parametric studies have also been included to obtain the results of academic and field interest.

Estimating Values for the Moisture Source Load and Buffering Capacities from Indoor Climate Measurements

The objective of this study is to investigate the potential for estimating values for the total size of human induced moisture source load and the total buffering (moisture storage) capacity of the interior objects with the use of relatively simple measurements and the use of heat, air, and moisture (HAM) models. The study presents the related modeling approaches, the implementation in the MatLab/ SimuLink environment, and a verification study of the models using indoor climate measurements of a Dutch museum. It is concluded that the modeling approach may be useful for estimating the magnitude of the human induced heat and moisture source loads. The case study is not usable for estimating the buffering capacity of the interior objects due to the weak dependency on the quantity of moisture storage material (there is almost no hygroscopic material present). However, the present approach has the side effect that it may be usable to indicate the effect of wet clothing. This study shows that the moisture source load of wet clothing per person can be of the same order as the moisture produced per person. Further research is needed if one wants to quantify the effect of wet clothing on the moisture load more accurately. More case studies are required to evaluate the approach for the determination of such moisture capacities.The objective of this study is to investigate the potential for estimating values for the total size of human induced moisture source load and the total buffering (moisture storage) capacity of the interior objects with the use of relatively simple measurements and the use of heat, air, and moisture (HAM) models. The study presents the related modeling approaches, the implementation in the MatLab/ SimuLink environment, and a verification study of the models using indoor climate measurements of a Dutch museum. It is concluded that the modeling approach may be useful for estimating the magnitude of the human induced heat and moisture source loads. The case study is not usable for estimating the buffering capacity of the interior objects due to the weak dependency on the quantity of moisture storage material (there is almost no hygroscopic material present). However, the present approach has the side effect that it may be usable to indicate the effect of wet clothing. This study shows that the moisture source load of wet clothing per person can be of the same order as the moisture produced per person. Further research is needed if one wants to quantify the effect of wet clothing on the moisture load more accurately. More case studies are required to evaluate the approach for the determination of such moisture capacities.

Indoor climate design for a monumental building with periodic high indoor moisture loads

The paper presents a case study on the performance based design for the indoor climate of a monumental building with periodic high indoor moisture loads. Several scenarios of the past performance and new control classes are simulated and evaluated. The results include the influence of hygric inertia on the indoor climate and (de)humidification quantities of the Heating, Venting & Air Conditioning (HVAC) system. It is concluded that: (1) The past indoor climate can be classified as ASHRAE control C with expected significant occurrences of dry (Relative Humidity (RH ) below 25 %) and humid (RH above 80 %) conditions; (2) ASHRAE control C is not suitable for the new hall. The climate control classification for the new hall ranges from B to A.; (3) The demands on the HVAC system to facilitate pop concerts in the new hall are 40 kW heating power, between 100 and 200 kW cooling power, between 40 and 80 kW humidification power and 125 kW dehumidification power; (4) In case of control class A, placing additional hygroscopic material has no significant effect. In case of control class B, the placing of additional moisture buffering material (5 air-volume-equivalents) does not decrease the (de)humidification power but decreases the (de)humidification energy by 5 %.

Dynamic Programming for Integrated Emission Management in Diesel Engines

Integrated Emission Management (IEM) is a supervisory control strategy that aims at minimizing the operational costs of diesel engines with an aftertreatment system, while satisfying emission constraints imposed by legislation. In previous work on IEM, a suboptimal real-time implementable solution was proposed, which was based on Pontryagins Minimum Principle (PMP). In this paper, we compute the optimal solution using Dynamic Programming (DP). As the emission legislation imposes a terminal state constraint, standard DP algorithms are sensitive to numerical errors that appear close to the boundary of the backward reachable sets. To avoid these numerical errors, we propose Boundary Surface Dynamic Programming (BSDP), which is an extension to Boundary Line Dynamic Programming and uses an approximation of the backward reachable sets. We also make an approximation of the forward reachable sets to reduce the grid size over time. Using a simulation study of a cold-start World Harmonized Transient Cycle for a Euro VI engine, we show that BSDP results in the best approximation of the optimal cost, when compared to existing DP methods, and that the real-time implementable solution only deviates 0.16 [%] from the optimal cost obtained using BSDP. cop. IFAC.

Editorial : Cross-industry multi-domain modeling language applications for building simulation

Recent changes in the ever increasing performance requirements for buildings such as the recast 2010/31/EU of the European directive 2002/91/EC on building energy performance and the development of smart grids, require a new approach in designing energy efficient buildings. To support the design and the decision making process, building energy simulation (BES) tools are faced with new challenges as new areas of research will focus on the assessment of taking advantage of energy exchange on district level and the implementation of distributed renewable energy generation, on and on integrating advanced controllers. Typical BEStools modeling the energy required for heating and cooling, however, mainly focus on the individual building level, are not well suited for simulating large scale energy systems or integrating electricity grids and/or lack a straightforward integration of external codes such as advanced controllers algorithms. Therefore, in order to meet and even exceed the new performance requirements standard BES-tools need to be expanded by integrating multiple domains and disciplines. To create such a multi disciplinary modeling environment mainly two options are available. A first approach combines existing software and focuses on exchange of data through export and import interfaces and coupled simulation. An example of this so-called co-simulation approach is the already available Functional Mockup Interface standard supported by more than 30 tools. A second approach is to combine all subproblems into one simulation environment. The advantage of this integrated approach is the ease of use and the shorter calculation time. The main disadvantage is that the existing algorithms have to be integrated in the simulation environment. This special issue provides an upto-date overview of recent developments in multi-domain modeling languages for simulating and control systems in the built environment. As this integrated modeling approach deviates from existing approaches it is indicated with a new term: ‘Cross-industry Multi-domain Modeling Language’ (CMML). CMML represents a modeling language that is applied in several domains of science and technology and is commonly used by a vast number of users and developers across the industry. It provides a large opportunity for possible synergy between the building simulation domain and other scientific and technological domains. For example, two important modeling languages that meet the definition of CMML are MatLab/SimuLink and Modelica. MATLAB/SimuLink users come from various backgrounds of engineering, science, and economics. It is widely used in academic and research institutions as well as industrial enterprises. Modelica is a freely available, object-oriented language for modeling of large, complex, and multi-domain physical systems. It is suited for multi-domain modeling, for example, mechatronic models in robotics, automotive and aerospace applications involving mechanical, electrical, hydraulic and control subsystems, process oriented applications and generation and distribution of electric power. The Modelica Association is a non-profit organization with members from Europe, U.S.A. and Canada. Traditionally Modelica was developed primarily for use in the automotive, aerospace and chemical industry. Today however a lot of effort is done by various research groups to develop libraries to model building energy systems. Recently the new IEA ECBCS Annex 60 started to join these research activities and develop computational tools for building and community energy systems. The special issue includes four papers. The topics of the papers included in the issue are: (1) The description of the Buildings library, a free open-source library that is implemented in Modelica. This library demonstrates the ongoing efforts to model buildings, building services and advanced control systems in an integrated approach. The paper also shows how co-simulation can still be an essential complimentary approach and demonstrates the possibilities of real-time data exchange with building automation systems. (2) An assessment of rule-based demand-sidemanagement techniques to overcome some of the problems that arise from a massive integration of distributed renewable energy sources (i.e. the combination of heat pumps and building integrated photovoltaics). In order to perform this assessment, a district energy simulation environment that is capable of the simultaneous modeling of thermal energy fluxes as well as electricity has been developed in Modelica. (3) A Review of the Application of SimuLink SFunctions to Multi Domain Modeling and Building Simulation. This paper reviews the use of S-Functions in SimuLink for DAEs and ODEs modeling regarding building simulation and its potential for multi domain applications (this article was mistakenly published in the previous issue and can be seen on pages 165-178 of issue 3). (4) A multi-level modeling and evaluation of thermal performance of phase-change materials in

Optimal setpoint operation to reduce peak drying of a church organ

The paper presents the characteristics of the Walloon Church in Delft (Netherlands) and a description of constraints for the indoor climate, giving criteria for the indoor air temperature and relative humidity with the focus on the preservation of the monumental church organ. The set point operation of the Heating Venting and Air Conditioning (HVAC) system is evaluated by simulation. The next main model components are presented and combined in a single integrated model: 1) a whole building response model for simulating the indoor temperature and relative humidity, 2) a Partial Differential Equation (PDE) based model for simulating detailed dynamic moisture transport in the monumental wood (church organ) and 3) a SimuLink controller model. The building model is validated with measurements. The main advantage of the integrated model is that it directly simulates the impact of HVAC control set point strategies on the indoor climate and the church organ. Two types of control strategies are discussed. The first type is a limited indoor air temperature-changing rate. The second type is a limited indoor air relative humidity changing rate. Recommendations from international literature suggest that 1) a changing rate of 2 K/h will preserve the interior of churches and 2) a limited drying rate is important for the conservation of monumental wood. This preliminary study shows that a limitation of indoor air temperature changing rate of 2 K/h can reduce the peak drying rates by a factor 20 and a limitation of the relative humidity changing rate of 2%/h can reduce the peak drying rates by a factor 50. The second strategy has the disadvantage that the heating time is not constant.