table of contentsIvana Turekova, Zuzana Turnova, Jozef Harangozo: Autonomous Alert and Warning Systems ... Ing . Michal Cehlár, PhD . – Technical university, Košice, Slovakia Assoc

table of contentsMiloš Birtus, Erika Spuchľáková: Infrastructure of the Venture Capital . . . . . . . . . . . . . . . . . . . . . . . . 3Štefan Cisko, Milan Vašanič: Development of Derivatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10Juraj Cúg, Pavol Kubala: The Application of Neural Networks in Corporate Governance . . . . . . . . . 17Veronika Frnková: Criteria for Selection of Methods for Evaluationof Effectiveness

of Investment Projects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21Ladislav Halada, Jan Glasa, Lukas Valasek, Peter Weisenpacher: The Use of Fire Dynamics

Simulator for Modelling Firesin Human Structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27Jana Jurková: Marketing and Consumer’s Behaviour in Context of University Education . . . . . . . . 36Rastislav Kazanský: The Security Policy - Cooperation of Actors . . . . . . . . . . . . . . . . . . . . . . . . . . . 40Tomáš Klieštik, Petra Solárová: Companies Multicriterial Benchmark on the Basis

of the Indicatorsof the Financial Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46Tomáš Klieštik, Daniel Žilovec: Corporate Metrics and Risk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51Marcela Korenková: Approaches of Managers to the Solving the Conflicts at the Place of Work . . . . 56Andrea Majlingová, Zuzana Verbovská, Mikuláš Monoši: Analysis of Presov Town Related to the

Potential Hazard and its Impact . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61Štefan Markulik, Marek Šolc, Lukáš Kamenický: Business Continuity Planning in Crisis Situations . . 68Mikuláš Monoši, Jozef Svetlík: Fires of Personal Cars in Underground Car Parks

and Precautions for Loss Elimination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72Vladimír Mózer, Anton Osvald: Recommended Features of Documentation

for Fire-Engineered Design Submissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76Jaroslav Oberuč, Gabriela Sláviková: Human Resources Management is the Key

for the Achievement of the Basic Conditions for the Successful Organization Operation . . . . . . 79Lukáš Pavelek: Networking in the Health Center of Trnava . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82Jana Pešoutová: Selected Aspects of International Legal Assistance . . . . . . . . . . . . . . . . . . . . . . . . . . 84Karel Schelle, Ilona Schelleová: Czech Insolvency Law after Updating . . . . . . . . . . . . . . . . . . . . . . . . . 87Erika Spuchľáková, Miloš Birtus: Fuzzy Logic Control in Finance . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90Katarina Štrbac, Milovan Subotić, Branislav Milosavljević: Extremist Trends in the Western

Balkans and the Republic of Serbia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94Juraj Tomlain: Factors Related to Marketing Strategies of Enterprises in the Czech Republic . . . . 101Ivana Turekova, Zuzana Turnova, Jozef Harangozo: Autonomous Alert and Warning Systems

of Population . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104Ivan Uher, Milena Pullmannová Švedová: Listening and Perception of Others . . . . . . . . . . . . . . . . . . 109Katarína Valášková: Basic Concept of Fuzzy Logic and Fuzzy Sets and Their Practical Application . . 112Milan Vašanič, Štefan Cisko: Prediction of a the Tisk of the Businesses Using Logistic Regression . 117Milan Vošta, Josef Abrhám: Clusters as Instruments of Regional Competitiveness in the Czech Republic . 123

LE&M

Journal on Law, Economy and Management© 2012 STS Science Centre Ltd .

All rights reserved . Neither this publication nor any part of it may be reproduced, stored in a retreival system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without the prior permission of STS Science Centre Ltd . Issued twice a year . Printed in the EU .

ISSN 2048-4186

Board in Chief Assoc . prof . Casimir Dadak – Hollins University

Virginia, USA

Scientific Board Prof . h .c . dr Ing . Thomas Bock – University Tokio,

TU Muenchen, GermanyProf. dr hab. Inź. Stanisław Borkowski – University

of Technology, Częstochowa, PolandProf . Dr . Yuriy L . Boshytsky – rector of Kyiv University of Law of National Academy of Sciences, UkraineProf . Ing . Michal Cehlár, PhD . – Technical university,

Košice, SlovakiaAssoc . prof . dr Ceslovas Christauskas – Kaunas

University of Technology, LithuaniaProf . Ing . Ignacio Escuder-Bueno – Universidad

Politécnica de Valencia, SpainProf . Adam Gwiazda, PhD . – Casimir the Great

University in Bydgoszcz and Higher School of Law and Diplomacy, Gdynia, Poland

Ass . Prof . Shaohua Jiang, Ph .D . – Dalian University of Technology, Dalian, P .R .China

Prof . col . Klára Siponé Kecskeméthy, PhD . – Zrínyi Miklós National Defence University, Budapest, Hungary

Doc . Ing . Miroslav Kelemen, PhD . – University of Security Management in Košice, Slovakia

Prof . JUDr . Mojmír Mamojka, CSc . – Faculty of Law Jesenského Janka, Sládkovičovo, Slovakia

Prof . dr A . Zoran Ristić – University from Novi Sad, Serbia

Doc . JUDr . Karel Schelle, CSc . – Faculty of Law, Masaryk University, Brno, Czech Republic

Prof . Alfredo Serpell, CE, MSc, PhD . – Pontificia Universidad Catolica de Chile, Santiago, Chile

Miroslaw J . Skibniewski, Ph .D ., A .J . Clark Chair Professor of Project Management University of Maryland, USA

Prof . Dr . Ljubomir Stajič - Faculty of Law, University of Novi Sad, Serbia

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JUDr. Jozef Zaťko – Eastern european developement agency n .o ., Podhájska, Slovakia

Editor in ChiefJUDr. Jozef Zaťko – Eastern european developement

agency n .o ., Podhájska, Slovakia

Editor & CorectorIng . Jana Jurková, PhD . – Presov University in Presov .

Editorial staff

The turn of the centuries, even millennia, a time of un-precedented globalization of today‘s world, military-strategic, economic, political, and cultural information . Current theories of law, economics and management are required to respond to a wide-ranging challenges of globalization . The answers to the challenges of civilization are sought in close cooperation, because today, as never before, law issues, management and economics are closely intertwined with issues of morality and justice, freedom and responsibility of man, the third company millennium . Today‘s situation is unique in that there is an accu-mulation of many changes and critical phenomena in all three areas, and nobody knows to predict their cumulative impact . Although the main issue of these days is financial system cri-sis, this will certainly impact other sectors of the economy, law and consequently the management . That is why the magazine monitors historical as well as current events in law, economics and management in form of expertise together with practical examples . The journal thus provides a comprehensive method-ology that can be applied both in simple as well as in most complex cases which experts from scientific research and educa-tional institutions, as well as managers, economists and lawyers in their daily practice can meet .

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272/2012

The Use of Fire Dynamics Simulator for Modelling Fires in Human Structures

Ladislav Halada, Jan Glasa, Lukas Valasek, Peter Weisenpacher

Abstract

Preparedness of security system workers for performing practical tasks of defence and safety against hazardous phenomena threatening people lives, their health, property and environment comprises also the preparation of alternative procedures to face emergency events. Such procedures are a necessary condition to mitigate destructive consequences of such events. In this article, we point out for a great potential of using computer simula-tion of fires. Analysis of the course of anticipated, or potential fires in endangered environments or structures is one of the chances of preparation for fire fighting. In some cases, it can also serve for analysis of the cause, or source of fire. In this paper, basic principles of the model for simulation of fires in human structures and wildland-urban interface implemented in the FDS and WFDS simulation systems, as well as some demonstrations of their use in various environments are briefly described.

Key words: fire dynamics simulator, fire, automobile

IntroductionNumber of large catastrophic events which cause enormous

damage of property and environment, people lives losses and possible area danger for people health are a warning message for Europe . Their occurrence and extensiveness cannot gener-ally be predicted in advance but their effects and consequences can be mitigated in the case when society is prepared to face them . This is the reason why EU requirements and initiatives of particular states focus in the development of specialized emer-gency modules which would be technically and tactically pre-pared for execution of emergency works and activities related to such events suppression . Computer simulation of possible types of threats and their development in anticipated environments is the next significant alternative . One of such alternatives is a computer simulation of fires . Advances in computers and the rapid increase of their computational power as well as obtained knowledge in the field of modelling physical and chemical processes during fire have led to the situation in which teams (often international) of specialists are able mathematically for-mulate these models and then to create advanced codes which enable to evaluate the fire processes and present them continu-ally in 3D space . Advances in this field achieved during the last two decades were so intensive that, at present, several program systems have been developed by such teams . Such systems are capable to be used, and have already been verified and certified by relevant institutions for practical use . Verification and vali-dation of these programs continually continue, and correcting and computational changes are made in order to improve the systems and their application use .

The main aim of this contribution is to briefly present results of two such systems, FDS and WFDS, which are intended for

obtaining the course of fires in wild-land urban interface (WUI) and in its close vicinity . Authors have a dozen-year experience with their use in various environments .

1. Computer simulation in WUI and its close vicinityAt present, several program systems are available for com-

puter simulation of fire in closed and semi-closed structures . PHOENICS, SMARTFIRE, SOFIE, FLUENT and FDS belong to the most known such systems . In our research, we decided to use the FDS (Fire Dynamics Simulator) system [15, 16] . Its first version was released for public use by NIST (National In-stitute of Standards and Technology, USA) in 2000 . Nowadays, already its fifth version is available . For its simulation results are continually compared with real experiments, its new versions are significantly better and thus also more reliable . Recently, this system was verified and tested by U .S . Nuclear Regulatory Commission (NRC) and recommended for simulation of po-tential consequences of fires in nuclear power plants (NUREG-1824) [14] . At present, the FDS version capable to realize the calculation on multi-core computer systems is also available . The aim of this paper is to point out for potential of the use of FDS for relatively complicated structures and document the ability of the program to simulate also more detailed processes of fire and their intensity, record measured quantities and visua-lise them . In the sequel, we characterize fundamental principles on which the system is based [13, 15] .

FDS is able to solve such processes as low speed, thermally driven flow of combustion products, thermal radiation, pyroly-sis, combustion of pyrolysis products, flame and smoke spread, sprinklers activation and fire suppression . The physical model used in FDS is based on the conservation laws of mass, species,

28 Journal on Law, Economy and Management

momentum and energy . The equations describing these process-es are as follows [16]:

where is the gas density; is the produc-tion rate of species by evaporating droplets or particles; u = (u, v, w) is the velocity vector; Yα, Dα, and are the mass fraction, the diffusion coefficient, and the mass production rate of α-th species per unit volume, respectively; is the pressure; g is the acceleration of gravity; fb is the external force vector; τij is the viscous stress tensor; hs is the sensible enthalpy; is the heat release rate per unit volume from a chemical reaction is the energy transferred to the evaporating droplets; rep-resents the conductive and radiative heat fluxes; is the dis-sipation rate; and D( )/Dt = = ∂ ( )/∂t + u .grad ( ) is the material derivative . For solving these equations, the so-called low Mach number approximation is used which assumes that the pressure changes caused by fire are negligible in comparison with the ambient pressure . Such approximation significantly reduces mathematical complexity of the problem . Other two equations, the pressure equation and the equation of state,

are added to the previous equations . The pressure equation is obtained applying the divergence on the momentum equation . In this equation, the value H represents the total pressure di-vided by the density; R is the universal gas constant; T is the temperature; and W is the molecular weight of the gas mixture . These six equations allows us to compute six unknowns from the combustion process such as the density ρ, three components of u = (u, v, w), the temperature T, and the pressure p . All un-knowns are functions of space coordinates and time, x, y, z, and t .

The equations must be simplified in order to filter out sound waves, which are much faster than the flow speed typical for fire . The final numerical scheme is an explicit predictor-corrector finite dif-ference scheme, which is second order accurate in space and time . The flow variables are updated in time using an explicit second-order Runge-Kutta scheme . The computational domain in which fire is simulated must be approximated by rectilinear meshes . This fact slightly complicates modelling the space and objects placed in it especially in the case when they are not rectangular . Initial and boundary conditions in the beginning of fire and objects, obstruc-tions, vents, walls, material properties values, and other param-eters necessary for the simulation are included into the simula-tion input . Simulation outputs include quantities for gas phase (temperature, velocity, species concentration, visibility, pressure, heat release rate per unit volume, etc .), for solid surfaces (tem-perature, heat flux, burning rate, etc .), as well as global quantities (total heat release rate, mass and energy fluxes through openings, etc .) . These outputs are recorded during simulation in the desired format and can be visualized by the Smokeview program . As it is mentioned in [16], the overall computation can either be treated as Direct Numerical Simulation (DNS), in which the dissipative terms are computed directly, or as Large Eddy Simulation (LES), in which large-scale eddies are computed directly and subgrid-scale dissipative processes are modelled . The numerical algorithm is de-signed so that LES becomes DNS as grid is refined . The numeri-cal schemes used for the solution of all equations are completely described in [16] . Since all FDS calculations must be performed within a domain consisting of rectilinear meshes divided into rect-angular cells, the cells must fulfill the requirements of finite dif-ference numerical scheme used in FDS . Their number depends on the desired resolution of fire scenario . As the FDS numerical scheme uses Fast Fourier Transforms (FFTs) in the y and z direc-tions, the second and third mesh dimensions should each be the product of the numbers 2, 3 and 5 .

2. Simulation of automobile fire and fire spread onto neighbouring vehicle

In 2009, several full-scale automobile fire experiments were conducted in open air in the testing facilities of Fire Protection College of the Ministry of Interior of the Slovak Republic in Pov-azsky Chlmec to verify the simulation system FDS . The first expe-riment investigated a fire in automobile engine compartment of an older Audi 80 model . The used vehicle was placed on concrete ground and temperature values inside, on and above the engine compartment were measured by thermocouples . The course of fire was recorded by infrared camera (see Fig . 1) .

At present, several program systems are available for computer simulation of fire in closed and semi-closed structures. PHOENICS, SMARTFIRE, SOFIE, FLUENT and FDS belong to the most known such systems. In our research, we decided to use the FDS (Fire Dynamics Simulator) system [15, 16]. Its first version was released for public use by NIST (National Institute of Standards and Technology, USA) in 2000. Nowadays, already its fifth version is available. For its simulation results are continually compared with real experiments, its new versions are significantly better and thus also more reliable. Recently, this system was verified and tested by U.S. Nuclear Regulatory Commission (NRC) and recommended for simulation of potential consequences of fires in nuclear power plants (NUREG-1824) [14]. At present, the FDS version capable to realize the calculation on multi-core computer systems is also available. The aim of this paper is to point out for potential of the use of FDS for relatively complicated structures and document the ability of the program to simulate also more detailed processes of fire and their intensity, record measured quantities and visualise them. In the sequel, we characterize fundamental principles on which the system is based [13, 15]. FDS is able to solve such processes as low speed, thermally driven flow of combustion products, thermal radiation, pyrolysis, combustion of pyrolysis products, flame and smoke spread, sprinklers activation and fire suppression. The physical model used in FDS is based on the conservation laws of mass, species, momentum and energy. The equations describing these processes are as follows [16]:

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volume from a chemical reaction bq is the energy transferred to the evaporating droplets; q represents the conductive and radiative heat fluxes; is the dissipation rate; and D( )/Dt = = ( )/ t + u.grad ( ) is the material derivative. For solving these equations, the so-called low Mach number approximation is used which assumes that the pressure changes caused by fire are negligible in comparison with the ambient pressure. Such approximation significantly reduces mathematical complexity of the problem. Other two equations, the pressure equation and the equation of state,

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Fig. 1.: Tested vehicle before (left) and after (right) the experiment

292/2012

Fire was initiated by a small burning cloth placed on the engine block under the rubber tube of air filter . At first, smoke went through interstices at the front and back sides of the engine compartment and on the lid edges . At the 8th minute, varnish on the lid surface was ignited on the place

above the air filter . The temperature inside the engine com-partment reached the maximal value about 900°C at the 7th minute of fire and then decreased slightly . At the 12th min-ute, the fire was suppressed . The fire and its consequences are shown in Fig . 2 .

The whole computational domain in the simulation was rep-resented by one computational mesh of 1 cm resolution with 503712 cells which was assigned to one CPU core . Most of the dynamic processes of burning occurred in the left part of the mesh . The simulation of 720 s of fire required 207 hours of CPU time at Intel Q9550, 2 .83 GHz CPU . The simulation reliably

Fig. 2.: Tested vehicle at the 8th minute of fire (left) and after the fire suppression (right)

Fig. 3.: Simulation of fire in engine compartment at the 7th minute of fire

modelled the main aspects of the fire (see Fig . 3) . Particularly, the fire dynamics inside the engine compartment, time (and val-ue) of reaching the maximal value of the temperature inside the engine compartment, distribution of surface temperature on the engine lid, and time of the surface varnish ignition were reliably modelled by FDS (see Fig . 4 and 5) [11, 12, 13, 21, 24] .

Fig. 4.: Lid surface temperature distribution at the 9th minute of fire


Fig. 5.: Maximal temperature curve on the engine compartment lid

The next experiment (the third in the order) which was modelled using the FDS system was a fire in the interior of new model of Kia Cee‘d automobile (see Fig . 6) . The tested vehicle has two broken windows . The initial fire source was places on the back seat . After 150 s, flashover appeared . The neighbouring vehicle, an older model of BMW, was ignited roughly after the 7th minute . After 12 min, the fire was sup-pressed .

The simulation performed realistically and with sufficient accuracy reproduced the course of fire . Particularly the tem-perature distribution inside the passenger compartment, time of flashover and time of the neighbouring vehicle ignition were simulated reliably . Some important moments of the fire devel-opment are shown in Fig . 7 . The computational complexity of the simulation required the use of parallel calculation using 8, 16 and 48 processors (for more details see [24]) .Fig. 6.: Automobile interior fire and spread of fire onto neighbouring vehicle

3. Simulation of a short road tunnel fireAlthough automobile fires in tunnels are relatively rare,

their impact on people lives and health, tunnel equipment and property could be extraordinary devastating . Therefore, pre-paredness on such events is necessary . As the main threat of such a fire is smoke inside the tunnel, the simulation focused

engine compartment, time (and value) of reaching the maximal value of the temperature inside the engine compartment, distribution of surface temperature on the engine lid, and time of the surface varnish ignition were reliably modelled by FDS (see Fig. 4 and 5) [11, 12, 13, 21, 24].

Fig. 4. Lid surface temperature distribution at the 9th minute of fire

Fig. 5. Maximal temperature curve on the engine compartment lid The next experiment (the third in the order) which was modelled using the FDS system was a fire in the interior of new model of Kia Cee‘d automobile (see Fig. 6). The tested vehicle has two broken windows. The initial fire source was places on the back seat. After 150 s, flashover appeared. The neighbouring vehicle, an older model of BMW, was ignited roughly after the 7th minute. After 12 min, the fire was suppressed. The simulation performed realistically and with sufficient accuracy reproduced the course of fire. Particularly the temperature distribution inside the passenger compartment, time of flashover and time of the neighbouring vehicle ignition were simulated reliably. Some important moments of the fire development are shown in Fig. 7. The computational complexity of the simulation required the use of parallel calculation using 8, 16 and 48 processors (for more details see [24]).

Lid Temperatures

0

50

100

150

200

250

300

350

400

450

500

0 100 200 300 400 500t/s

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Fig. 7.: Fire in luggage compartment at the 124th, 165th and 545th second of fire

Fig. 8.: Tested tunnel scheme

on the smoke spread during fire and ability of the tunnel venti-lation system to clean the air at the upwind side of the tunnel (see Fig . 8) . The tunnel under consideration is 180 m long and the ventilation system is represented by two fans .

The simulation covered 150 s of fire .

312/2012

Because of relatively large dimensions of the tunnel (10 m x 180 m x 7 m) and selected 10 cm resolution of cube compu-tational meshes, the parallel realization of the simulation was required . At 40th second of simulation, the fire was ignited . After the fire reached the HRR value of 10 MW, it remained constant . In reaction to the fire, the jet fans increased their per-formance and the air velocity in the tunnel achieved the value of 20 m .s-1 and the smoke was pushed out of the tunnel . In Fig . 9, the simulation of smoke spread in this scenario is illustrated . The relation between the simulation duration and number of used processors was investigated [23, 25] . The simulation was

Fig. 9.: Fire and smoke spread in the tunel

Fig. 10.: Family house fire simulation: at the 7th minute (left) and after one hour (right) of fire; front wall of the house is made transparent

carried out in parallel on the HP Blade Cluster at our Institute consisting of 16 computational nodes, each comprising of two quadcore Intel Xeon X5570 CPU, 2 .93GHz with 8MB cache . Each node contains 48 GB of RAM . Nodes are connected by the infiniband interconnection network with the bandwidth of 40 Gbit/s per link and direction . It was found that for this scenario the use of 24 cores brought more than 10-times improvement of computational performance compared to the use of a single core . Total computational time was 377 and 32 hours for 1 and 24 cores, respectively . However, parallel calculation is more de-manding for competent preparation of calculation processes .

4. Simulation of a family house fireThe aim of the FDS simulation of a family house fire [11]

was to determine when appeared the crucial moments of the fire development leading to its destruction . The family house used in the simulation have concrete walls, wooden joists, wooden ceiling of the first floor, and roof (see Fig . 10) . The house fur-nishing was wooden (staircase, cupboards), or it consists of

illustrated. The relation between the simulation duration and number of used processors was investigated [23, 25]. The simulation was carried out in parallel on the HP Blade Cluster at our Institute consisting of 16 computational nodes, each comprising of two quadcore Intel Xeon X5570 CPU, 2.93GHz with 8MB cache. Each node contains 48 GB of RAM. Nodes are connected by the infiniband interconnection network with the bandwidth of 40 Gbit/s per link and direction. It was found that for this scenario the use of 24 cores brought more than 10-times improvement of computational performance compared to the use of a single core. Total computational time was 377 and 32 hours for 1 and 24 cores, respectively. However, parallel calculation is more demanding for competent preparation of calculation processes.

Fig. 9. Fire and smoke spread in the tunel 4. Simulation of a family house fire The aim of the FDS simulation of a family house fire [11] was to determine when appeared the crucial moments of the fire development leading to its destruction. The family house used in the simulation have concrete walls, wooden joists, wooden ceiling of the first floor, and roof (see Fig. 10). The house furnishing was wooden (staircase, cupboards), or it consists of wood, plastic materials and upholstery (sofa, chairs, beds and TV). In simulated fire scenario, the fire was ignited in front of the door. After the door burned away, the fire penetrated into the house interior. The goal of the simulation was to determine the time at which the fire penetrated through the door into the room and to estimate the time of the house joist destruction.

Fig. 10. Family house fire simulation: at the 7th minute (left) and after one hour (right) of fire; front wall of the house is made transparent

wood, plastic materials and upholstery (sofa, chairs, beds and TV) . In simulated fire scenario, the fire was ignited in front of the door . After the door burned away, the fire penetrated into the house interior . The goal of the simulation was to determine the time at which the fire penetrated through the door into the room and to estimate the time of the house joist destruction .

In the simulation, table values of material properties were used for plastic materials and upholstery . However, param-eters for the materials crucial for the fire behaviour were determined during forensic investigation of a similar house fire (parameters for concrete and wood) . The size of compu-tational domain was 1080 cm x 1080 cm x 600 cm and the computational mesh resolution was 10 cm . The simulations were carried out in parallel on the HP Blade Cluster at our

Institute . One node with 8 CPU cores was used for the simu-lation . The simulation of 420 s fire required about 106 hours of wall clock time .

The simulation indicated that the fire penetrated into the house interior approximately 30 min after the fire ignition and critical weakening of wooden joists occurred between the 60th and 75th minute of fire . At that time, a significant por-tion of the joists material was evaporated .


5. Simulation of a cinema fire

In this part, the use of FDS for simulation of the fire and

toxic smoke spread in a typical small cinema is illustrated [7, 8] . The cinema consists of three rooms, the entrance hall, cinema hall and projection room (see Fig . 12) .

Fig. 12.: Cinema model and its ground plan

Fig. 13.: Input FDS geometry of the cinema and its visualization in PyroSim

Fig. 14.: Smoke spread at the 10th s of fire

In the simulation, table values of material properties were used for plastic materials and upholstery. However, parameters for the materials crucial for the fire behaviour were determined during forensic investigation of a similar house fire (parameters for concrete and wood). The size of computational domain was 1080 cm x 1080 cm x 600 cm and the computational mesh resolution was 10 cm. The simulations were carried out in parallel on the HP Blade Cluster at our Institute. One node with 8 CPU cores was used for the simulation. The simulation of 420 s fire required about 106 hours of wall clock time. The simulation indicated that the fire penetrated into the house interior approximately 30 min after the fire ignition and critical weakening of wooden joists occurred between the 60th and 75th minute of fire. At that time, a significant portion of the joists material was evaporated. 5. Simulation of a cinema fire In this part, the use of FDS for simulation of the fire and toxic smoke spread in a typical small cinema is illustrated [7, 8]. The cinema consists of three rooms, the entrance hall, cinema hall and projection room (see Fig. 12).

Fig. 12. Cinema model and its ground plan The cinema hall has a stage with two small stairways in the front part of the hall; seating space with sloping floor ordered into a stairway consisting of 9 stairs with 108 upholstered chairs; two doors, the entrance door and emergency exit; and curved ceiling. The cinema ground plan with dimensions is shown in Fig. 12. We created the input FDS representation of the cinema using the ground plan by the graphical user interface, PyroSim (see Fig. 13).

Fig. 13. Input FDS geometry of the cinema and its visualization in PyroSim

In the simulation, table values of material properties were used for plastic materials and upholstery. However, parameters for the materials crucial for the fire behaviour were determined during forensic investigation of a similar house fire (parameters for concrete and wood). The size of computational domain was 1080 cm x 1080 cm x 600 cm and the computational mesh resolution was 10 cm. The simulations were carried out in parallel on the HP Blade Cluster at our Institute. One node with 8 CPU cores was used for the simulation. The simulation of 420 s fire required about 106 hours of wall clock time. The simulation indicated that the fire penetrated into the house interior approximately 30 min after the fire ignition and critical weakening of wooden joists occurred between the 60th and 75th minute of fire. At that time, a significant portion of the joists material was evaporated. 5. Simulation of a cinema fire In this part, the use of FDS for simulation of the fire and toxic smoke spread in a typical small cinema is illustrated [7, 8]. The cinema consists of three rooms, the entrance hall, cinema hall and projection room (see Fig. 12).

Fig. 12. Cinema model and its ground plan The cinema hall has a stage with two small stairways in the front part of the hall; seating space with sloping floor ordered into a stairway consisting of 9 stairs with 108 upholstered chairs; two doors, the entrance door and emergency exit; and curved ceiling. The cinema ground plan with dimensions is shown in Fig. 12. We created the input FDS representation of the cinema using the ground plan by the graphical user interface, PyroSim (see Fig. 13).

Fig. 13. Input FDS geometry of the cinema and its visualization in PyroSim

In the sequel, we illustrate the potential of FDS to catch reliably the main aspects of fire behaviour in the selected cinema. We considered a fire ignited in the 5th row under the 7th chair and assumed all doors closed during the first minute of fire. The fire source was represented by 20 x 20 cm surface with 800 kW/m2 HRRPUA during the first 3 s of fire. Fire of the dominantly flammable material, upholstery, causes extremely dangerous toxic smoke which threatens spectators in the cinema. Parameters for upholstery have been determined by laboratory measurements and validated by fire experiments and FDS simulations (for more details see [8]). The whole computational domain in the simulation was represented by one computational mesh of 10 cm resolution with 967680 cells which was assigned to one CPU core. Total computational time for 60 s fire simulation realised on Intel Core i7 990-X, 3.46 GHz, 24 GB RAM was 3,04 hours. In Figs. 14-15, some interesting moments of the smoke formation are illustrated.

Fig. 14. Smoke spread at the 10th s of fire

Fig. 15. Temperature slices in the 12th and 40th s of fire It can be seen in Figs. 14 and 15 that toxic clouds of turbulent mixing gases origin after the hit of smoke spread under the ceiling on the vertical wall at the back part of the hall and on the curved parts of the ceiling at the side parts of the hall. The simulation results confirmed that spectators would be endangered by smoke already during the first minute of fire. Simulation indicated that the highest chair rows in the back part and side parts of the cinema hall under the curved parts of the ceiling are critical for safe spectators evacuation [7, 8]. However, for simulation of fires in bigger structures (bigger cinemas, or multiplexes consisting of several multi-purpose halls), parallel realization on multi-core computers or computer clusters will be required. 6. Simulation of a fire in WUI using WFDS

Several advanced, so-called semi-empirical fire models are available for forest fire simulation, such as for instance the FARSITE system, which has been successfully adapted for forests in Slovakia and used for a past fire reconstruction [2, 3, 4, 5, 6, 9, 10, 19]. However, such models have some fundamental limitations such as the assumption of continuous medium

The cinema hall has a stage with two small stairways in the front part of the hall; seating space with sloping floor ordered into a stairway consisting of 9 stairs with 108 upholstered chairs; two doors, the entrance door and emergency exit; and

curved ceiling . The cinema ground plan with dimensions is shown in Fig . 12 . We created the input FDS representation of the cinema using the ground plan by the graphical user interface, PyroSim (see Fig . 13) .

In the sequel, we illustrate the potential of FDS to catch reliably the main aspects of fire behaviour in the selected cinema . We considered a fire ignited in the 5th row under the 7th chair and assumed all doors closed during the first minute of fire . The fire source was represented by 20 x 20 cm surface with 800 kW/m2 HRRPUA during the first 3 s of fire . Fire of the dominantly flammable material, upholstery, causes extremely dangerous toxic smoke which threatens spectators in the cinema . Parameters for upholstery have

been determined by laboratory measurements and validated by fire experiments and FDS simulations (for more details see [8]) . The whole computational domain in the simulation was represented by one computational mesh of 10 cm resolu-tion with 967680 cells which was assigned to one CPU core . Total computational time for 60 s fire simulation realised on Intel Core i7 990-X, 3 .46 GHz, 24 GB RAM was 3,04 hours . In Figs . 14-15, some interesting moments of the smoke for-mation are illustrated .

332/2012

Fig. 15.: Temperature slices in the 12th and 40th s of fire

Fig. 16.: Fire of a coniferous tree canopy

Fig. 17.: Cottage fire and surrounding vegetation fire

In the sequel, we illustrate the potential of FDS to catch reliably the main aspects of fire behaviour in the selected cinema. We considered a fire ignited in the 5th row under the 7th chair and assumed all doors closed during the first minute of fire. The fire source was represented by 20 x 20 cm surface with 800 kW/m2 HRRPUA during the first 3 s of fire. Fire of the dominantly flammable material, upholstery, causes extremely dangerous toxic smoke which threatens spectators in the cinema. Parameters for upholstery have been determined by laboratory measurements and validated by fire experiments and FDS simulations (for more details see [8]). The whole computational domain in the simulation was represented by one computational mesh of 10 cm resolution with 967680 cells which was assigned to one CPU core. Total computational time for 60 s fire simulation realised on Intel Core i7 990-X, 3.46 GHz, 24 GB RAM was 3,04 hours. In Figs. 14-15, some interesting moments of the smoke formation are illustrated.

Fig. 14. Smoke spread at the 10th s of fire

Fig. 15. Temperature slices in the 12th and 40th s of fire It can be seen in Figs. 14 and 15 that toxic clouds of turbulent mixing gases origin after the hit of smoke spread under the ceiling on the vertical wall at the back part of the hall and on the curved parts of the ceiling at the side parts of the hall. The simulation results confirmed that spectators would be endangered by smoke already during the first minute of fire. Simulation indicated that the highest chair rows in the back part and side parts of the cinema hall under the curved parts of the ceiling are critical for safe spectators evacuation [7, 8]. However, for simulation of fires in bigger structures (bigger cinemas, or multiplexes consisting of several multi-purpose halls), parallel realization on multi-core computers or computer clusters will be required. 6. Simulation of a fire in WUI using WFDS

Several advanced, so-called semi-empirical fire models are available for forest fire simulation, such as for instance the FARSITE system, which has been successfully adapted for forests in Slovakia and used for a past fire reconstruction [2, 3, 4, 5, 6, 9, 10, 19]. However, such models have some fundamental limitations such as the assumption of continuous medium

covering large areas. That is why such models are not suitable to capture local events in strongly heterogeneous environment, for example an event on the scale of a particular tree, or a small group of trees. Moreover, the models are linear and do not have any mechanism to involve non-linear processes inherently connected with fire dynamics, such as e. g. non-linear, abrupt fire eruptions, and do not take into account the interaction between fire and atmosphere. In this part, we illustrate the use of the WFDS (Wildland-Urban Interface Fire Dynamics Simulator) system [17, 18], which is an extension of FDS capable to include vegetation into the model and incorporate more of physical mechanism of fire. For instance, WFDS is able to describe fire spread on a flat terrain, for a grass, or a small group of trees or shrubs (for more details about models included in WFDS see e.g. [17, 18, 20, 22]). We demonstrate the WFDS simulation of two typical situations which can occur in WUI. In Fig. 17, ignition of a coniferous tree crown from a grass fire is illustrated. In Fig. 18, some important moments of a cottage fire ignited by a grass fire are shown. [20, 22]

Fig. 16. Fire of a coniferous tree canopy

Fig. 17. Cottage fire and surrounding vegetation fire 7. Conclusion

Computer simulation can be useful for emergency system workers in realization of practical tasks in the fields of defence and safety related to the risk phenomena threatening people lives, their health, property and environment. The use of advanced fire simulation systems can help increase the preparedness of crisis management staff and fire fighting corps for emergency situations in structures afflicted by fires. Fire simulation can be used as a flexible, inexpensive means for the fire safety increase utilizing its ability to model as many fire scenarios in given environment as necessary and change particular parameters of simulated scenario according to the user requirements. The aim of this article was not to describe in details theoretical and methodological fundaments of the used methods and systems, but to point out to the wide spectrum of possible use of FDS and WFDS systems in various environments. Note that abilities of the FDS system for simulation of potential consequences

covering large areas. That is why such models are not suitable to capture local events in strongly heterogeneous environment, for example an event on the scale of a particular tree, or a small group of trees. Moreover, the models are linear and do not have any mechanism to involve non-linear processes inherently connected with fire dynamics, such as e. g. non-linear, abrupt fire eruptions, and do not take into account the interaction between fire and atmosphere. In this part, we illustrate the use of the WFDS (Wildland-Urban Interface Fire Dynamics Simulator) system [17, 18], which is an extension of FDS capable to include vegetation into the model and incorporate more of physical mechanism of fire. For instance, WFDS is able to describe fire spread on a flat terrain, for a grass, or a small group of trees or shrubs (for more details about models included in WFDS see e.g. [17, 18, 20, 22]). We demonstrate the WFDS simulation of two typical situations which can occur in WUI. In Fig. 17, ignition of a coniferous tree crown from a grass fire is illustrated. In Fig. 18, some important moments of a cottage fire ignited by a grass fire are shown. [20, 22]

Fig. 16. Fire of a coniferous tree canopy

Fig. 17. Cottage fire and surrounding vegetation fire 7. Conclusion

Computer simulation can be useful for emergency system workers in realization of practical tasks in the fields of defence and safety related to the risk phenomena threatening people lives, their health, property and environment. The use of advanced fire simulation systems can help increase the preparedness of crisis management staff and fire fighting corps for emergency situations in structures afflicted by fires. Fire simulation can be used as a flexible, inexpensive means for the fire safety increase utilizing its ability to model as many fire scenarios in given environment as necessary and change particular parameters of simulated scenario according to the user requirements. The aim of this article was not to describe in details theoretical and methodological fundaments of the used methods and systems, but to point out to the wide spectrum of possible use of FDS and WFDS systems in various environments. Note that abilities of the FDS system for simulation of potential consequences

It can be seen in Figs . 14 and 15 that toxic clouds of turbulent mixing gases origin after the hit of smoke spread under the ceiling on the vertical wall at the back part of the hall and on the curved parts of the ceiling at the side parts of the hall . The simulation results confirmed that spectators would be endangered by smoke already during the first minute of fire . Simulation indicated that the highest chair rows in the back part and side parts of the cin-ema hall under the curved parts of the ceiling are critical for safe spectators evacuation [7, 8] . However, for simulation of fires in bigger structures (bigger cinemas, or multiplexes consisting of several multi-purpose halls), parallel realization on multi-core computers or computer clusters will be required .

6. Simulation of a fire in WUI using WFDS Several advanced, so-called semi-empirical fire models are

available for forest fire simulation, such as for instance the FARSITE system, which has been successfully adapted for for-ests in Slovakia and used for a past fire reconstruction [2, 3, 4, 5, 6, 9, 10, 19] . However, such models have some fundamen-tal limitations such as the assumption of continuous medium

covering large areas . That is why such models are not suitable to capture local events in strongly heterogeneous environment, for example an event on the scale of a particular tree, or a small group of trees . Moreover, the models are linear and do not have any mechanism to involve non-linear processes inherently con-nected with fire dynamics, such as e . g . non-linear, abrupt fire eruptions, and do not take into account the interaction between fire and atmosphere .

In this part, we illustrate the use of the WFDS (Wildland-Urban Interface Fire Dynamics Simulator) system [17, 18], which is an extension of FDS capable to include vegetation into the model and incorporate more of physical mechanism of fire . For instance, WFDS is able to describe fire spread on a flat terrain, for a grass, or a small group of trees or shrubs (for more details about models included in WFDS see e .g . [17, 18, 20, 22]) . We demonstrate the WFDS simulation of two typi-cal situations which can occur in WUI . In Fig . 17, ignition of a coniferous tree crown from a grass fire is illustrated . In Fig . 18, some important moments of a cottage fire ignited by a grass fire are shown . [20, 22]


7. Conclusion

Computer simulation can be useful for emergency system workers in realization of practical tasks in the fields of de-fence and safety related to the risk phenomena threatening people lives, their health, property and environment . The use of advanced fire simulation systems can help increase the pre-paredness of crisis management staff and fire fighting corps for emergency situations in structures afflicted by fires . Fire simulation can be used as a flexible, inexpensive means for the fire safety increase utilizing its ability to model as many fire scenarios in given environment as necessary and change particular parameters of simulated scenario according to the user requirements . The aim of this article was not to de-scribe in details theoretical and methodological fundaments of the used methods and systems, but to point out to the

wide spectrum of possible use of FDS and WFDS systems in various environments . Note that abilities of the FDS system for simulation of potential consequences of fire in nuclear power plants were thoroughly verified and recommended by the U .S . Nuclear Regulatory Commission [14] .

Acknowledgement Authors of this paper are grateful to mjr . Ing . S . Galla,

PhD ., plk . Mgr . P . Komar, Prof . P . Polednak, Ing . Schmidt, as well as to the management of VVUJ, a .s ., Ostrava Rad-vanice for their kind advisement, consultations and techni-cal support for the research . This paper was partially sup-ported by the VEGA Scientific Research Agency (project VEGA 2/0216/10), and the Research and Development Operational Program funded by ERDF (project ITMS 26240220060) .

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18 . MELL, W . E ., JENKINS, M . A ., GOULD, J ., CHENEY, P . A physics-based approach to modelling grassland fires, In Int. J. of Wildland Fire, Vol . 16, Iss . 1, 2007, pp . 1-22 .

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doc. RNDr. Ladislav Halada, PhD.

RNDr. Ján Glasa, CSc.

Ing. Lukáš Valášek

Mgr. Peter Weisenpacher PhD.

Ústav informatiky SAV BratislavaDúbravská cesta 9845 07 BratislavaSlovak Republic

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