A study on buoyancy-driven flows: Using particle image velocimetry for validating the Fire Dynamics Simulator

The aim of this thesis is to design and carry out bench-scale laboratory experiments specifically designed for the validation of fire models, and to use the experimental data for a validation study of the Fire Dynamics Simulator (FDS). The focus of the experiments is on one of the key components of fire models, the modeling of buoyancy-driven flows. The experimental setup is simplified by neglecting pyrolysis and combustion and its objective is to achieve high precision and reproducibility. Therefore, an electrically heated block of copper is used as a heat source and particle image velocimetry (PIV) is applied for measuring the flow velocities. Two different setups are investigated: an undisturbed open buoyant plume above the heat source, and a buoyant spill plume emerging from a compartment opening. Depending on the setup, different characteristic values of the flow are evaluated. For the undisturbed buoyant plume setup, maximum velocities in the plume, plume widths and flow integrals are determined. Furthermore, a centerline analysis is carried out in order to localize the transition from laminar to turbulent flow as a function of the Grashof number. The obtained values lie in the range 4 X 10$^{8}$ < Gr < 2 X 10$^{9}$ and therefore agree well with previous studies. For the buoyant spill plume compartment setup, position and maximum velocity of the out flow as well as volume flows in front of the opening are compared. The heat flows out of the opening cannot be measured directly and are therefore estimated based on the available data. The validation study with FDS leads to mixed results. For the open plume setup, generally a good agreement is achieved. Provided that a sufficiently fine resolution is used, the important flow characteristics are reproduced in the simulations. With the spill plume setup, significant differences between experiments and simulations are observed. In order to analyze them in detail, modifcations of the experiments are required. Therefore, in conclusion of the study, areas of potential improvements for future experiments and the suitability of PIV for this kind of experiment are discussed

Brandversuch und FDS-Simulation im Vergleich

Der Beitrag basiert auf einem Brandversuch im Realmaßstab, der anhand von Temperaturmessungen im Versuchsobjekt zur Validierung von FDS genutzt wurde. Des Weiteren wurden im Nachgang des Versuchs Simulationsrechnungen von mehreren Ingenieurbüros durchgeführt um den Einfluss verschiedener Materialkennwerte auf die Simulationsergebnisse darzustellen. Hierbei ging es speziell um die Erwärmung und den Wärmedurchgang durch vier Materialien: Gipskarton, Holz, Stahl und Glas. Die Ergebnisse lassen sich wie folgt zusammenfassen. Die Simulationen der verschiedenen Büros weichen nur wenig voneinander ab, die Temperatur der einzelnen Probekörper variiert jedoch signifikant. Das unterschiedliche Erwärmungsverhalten in Simulation und Experiment ist auf die unterschiedliche Wärmeausbreitung im Objekt sowie das unterschiedliche Schichtungsverhalten der Rauchgase zurückzuführen. Anhand weitergehender Berechnungen mit FDS konnte gezeigt werden, dass sich diese Abweichungen zumindest teilweise durch die verwendete Gitterauflösung sowie die besondere Art der Öffnung zwischen den Räumen erklären lassen. Ergänzend zu den Vergleichsrechnungen mit FDS wurde ein einfaches eigenes Modell entwickelt, das speziell auf das vorliegende Szenario – Erwärmung eines Körpers durch eine heiße Rauchschicht – zugeschnitten ist. Basierend auf den experimentell bestimmten Rauchschichttemperaturen wird die Wärmeübertragung ermittelt und die Erwärmung der Materialien bestimmt. Die Ergebnisse stimmen sehr gut mit den gemessenen Werten überein

Automated Generation and Evaluation of FDS Simulations for Optimizing Parameters with Dakota

Some questions in Fire Safety Engineering require multiple execution and evaluation of firesimulations with changed parameters or a modified setup: A thorough sensitivity study requiresthe execution of one simulation per sample point. For a design of a fire safety system takinginto account n different scenarios, n simulations are needed. And for an automated parameteroptimization, repetitive simulations are necessary to determine the optimal parameter values.However, one of the most popular tools for fire simulation – the Fire Dynamics Simulator –lacks a functionality for automated batch processing of parameter spaces.In this paper, FDSgeogen is presented, a tool that enables the user to automatically generateFDS input files implementing freely selectable variables, e.g. for material properties orgeometrical measures. The automated input file generation is based on a file containing informationabout the simulation setup, which is formatted in Extensible Markup Language (XML),a file containing the parameter sets for the different simulations, usually formatted as commaseparatedvalues (CSV) and a python parser for the generation of the FDS input files on the basisof the XML and CSV files. Since the XML file contains most of the relevant information aboutthe setup of the simulation, the boundary conditions and the output values, it may seem similarto an FDS input file. However, in combination with the parameter file and the python parser itis not only possible to include freely selectable variables but also to make them dependent oneachother. That is why the presented method provides a lot of flexibility and adaptability forthe automatic input file generation for different applications. The authors strongly encourageothers to make use of the presented method and participate in further development of the code.In order to demonstrate the applicability of the proposed method, an automated parameteroptimization for cone calorimeter experiments is presented. Based on measurements of the heatrelease rate (HRR) of polyurethane foam subjected to two different heat fluxes, the materialproperties emissivity, ", thermal conductivity, k, and specific heat, cp, of polyurethane wereoptimized. For the automated parameter optimization Dakota [1] was utilized. It is an opensource software toolkit that amongst other things includes algorithms for design optimization,parameter estimation, and sensitivity analysis. For determining the loss function value theeuclidean relative differences between the HRR in experiment and simulation were calculated

Small scale validation experiments applying particle image velocimetry

Since the early days of fire simulation, experiments for model validation are an integral part of the development process. Oftentimes the used experimental setups are complex and involve numerous physical phenomena. This allows for a model evaluation under realistic conditions, however, it makes it difficult to localise errors and assign deviations to specific submodels.That is why we present two simplified experimental setups, which neglect complex phenomena such as pyrolysis and combustion and focus on buoyancy-driven flows only. For both setups particle image velocimetry is applied for measuring gas velocities. This laser-based method is non-invasive, highly accurate and yields instantaneous velocity vector fields for a whole plane. An electrically heated block of copper with a defined emissivity and a defined heat output is used as heat source. In the first setup the open plume that develops above the heat source is investigated. In the second setup the same heat source is positioned inside a room with a single opening. Here, the focus lies on the spill plume developing in front of the opening.For both setups FDS simulations with different heat outputs are carried out. Crucial output values are velocity profiles, maximum velocities, and volume flows. The simulation results are compared with experimental measurements afterwards

Velocity measurements of a bench scale buoyant plume applying particle image velocimetry

This paper presents the experimental investigation of the buoyant plume above an electrically heated block of copper. The velocity field in a vertical plane along the plume axis is investigated via particle image velocimetry. Experiments with electrical power from 30  W to 96  W are carried out, which lead to heat source temperatures of 149–307  °C. The resulting flow is laminar for the lowest power setting and undergoes a transition to turbulent flow for higher heat inputs. With increasing heat input the point of transition from laminar to turbulent flow occurs at lower heights.Time-averaged velocity fields are presented together with the according measurement uncertainty that results from the evaluation with particle image velocimetry. Based on these velocity fields a number of characteristic values for the plume is derived in different heights, e.g. maximum velocities, plume widths and flow integrals. In order to further evaluate the transition from laminar to turbulent flow the vertical velocity and the standard deviation of the horizontal velocity along the plume axis and as a function of the Grashof number are investigated. The transition occurs at Grashof numbers in the range 4×10^8 < Gr < 2×10^9, which is in accordance with previous findings. In addition to the velocity measurements, the temperature stratification inside the enclosure is measured to quantify the ambient conditions

Automated FDS Input File Generation with fdsgeogen

Ensemble simulations become popular in computational sciences, and also in fire safety engineering, to tackle sensitivities and uncertainties of complex systems. In many cases, the involved parameters have simple and explicit impact, like randomization of initial conditions (placement of agents in pedestrian simulation) or material properties in fire simulation. However, there exist parameters, like geometrical ones, whose changes may implicitly require to adopt other settings. As FDS uses an absolute definition in its input files, we introduce an intermediate file format – including an according parser – to allow for relative definition of parameter values.The presented tool fdsgeogen uses an XML based file format to define a single FDS input file or an ensemble of those. The parser is implemented in Python and therefore platform independent as well as easy to use and to extend. Besides a variable-driven FDS input declaration, it supports a selective import of existing FDS files, loop directives to ease repetitive tasks, as well as simplified and compact declaration of common FDS input structures, like devices or slices.This contribution presents the structure of fdsgeogen and demonstrates its usage. fdsgeogen is freely available via a git repository and any kind of contribution is encouraged