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Simulation investigation on the smoke spread process in the large-space building with various height
Case Studies in Thermal Engineering 18 (2020) 100594
Contents lists available at ScienceDirect
Case Studies in Thermal Engineering journal homepage: http://www.elsevier.com/locate/csite
Simulation investigation on the smoke spread process in the large-space building with various height Yufeng Huang *, Ershen Wang , Yuxia Bie College of Electronic and Information Engineering, Shenyang Aerospace University, Shenyang, Liaoning, 110136, PR China
A R T I C L E I N F O
A B S T R A C T
Keywords: Large-space buildings FDS Smoke spread process LSD ASD
In this paper, the fire growth and smoke spread process in Large-space building have been investigated through the Fire Dynamics Simulator (FDS). What’s more, the alarm process of the Line-type Infra-red Beam Smoke Fire Detector (LSD) and the Aspirating Smoke Detection System (ASD) have discussed, some valuable results have been obtained. The results indicated that the raise of the difference between the two height, and the smoke spread process is becoming slower at the constant heat release rate. The set of fire alarm system in large-space should be consider the “height advantage”, as the higher set of the smoke decent responding earlier than the lower ones. What’s more, referring to the ASD system the aspirator samplers close to the building’s edge should be affected by the edge. For the LSD system should determine the parameter of install by the numerical or experimental test to optimizing the performance of the LSD, which has been proposed in the paper. In summary, the research investigates the basic fire alarm process for the LSD and the ASD System in the large-space buildings, and these are valuable for the selecting and setting of fire alarm system in the large-space buildings.
1. Introduction Along the process of urbanization in China, more and more large-space buildings have been emerged. The large-space building meeting the expectation of the space utilization ratio, open views and so on, however the large-space building also accelerate the smoke spread speed due to the open-type space convection of air, which should be enhance the fire risk of the large-space building. Thus, the early detection of the fire should be necessary, which meet many difficulties in the large-space building due to the open-type space convection of air and thermal barrier effect because of the space height. The normal fire detection systems used in the large-space building are the Line-type Infra-red Beam Smoke Detector (LSD) and the Aspirating Smoke Detection System (ASD). The detection principle of LSD is according to the obscuration value caused by the smoke particles yield of the fire in the buildings, and ASD is according to the collected smoke particles quantity of the fire in the buildings. So that the fire growth rate and smoke spread process is the key factor in the open-area fire detection process. In order to investigate the fire growth rate and smoke spread process in largespace buildings, many researches have been done lots of work, which is a research hot-point along with the urbanization in China. For the traditional point-type smoke detector, many standards and rules have been proposed by reference groups. For example, ISO 7240-15 [1] specifies requirements, test methods, and performance criteria for point-type fire detectors using smoke and heat sensors, Underwriters Laboratories Inc (UL) raise the requirements for smoke detectors and its accessories of electrically operated single and
* Corresponding author. E-mail address: [email protected] (Y. Huang). https://doi.org/10.1016/j.csite.2020.100594 Received 14 January 2020; Received in revised form 21 January 2020; Accepted 21 January 2020 Available online 23 January 2020 2214-157X/© 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Case Studies in Thermal Engineering 18 (2020) 100594
Y. Huang et al.
multiple station by UL standards [2,3]. What’s more, mounts of standards is enacted, such as British Standards Institution (BSI) [4,5], National Fire Protection Association (NFPA) [6,7] and so on. How to manage the fire alarm system in large-space building? Many researchers [8–14] have been seeking for other method. Till [8] discussed the selection of the fire alarm system, and proposed two basic requirements for the detection system. Wang et al. [9]. have proposed A Sauter mean diameter sensor for fire smoke detection. Zhang et al. [10]. has carried experimental Study on the Characteristics of Fire Smoke Movement in Ultra-Thin and Tall Atriums by Hot Smoke Test. Lan et al. [11].have proposed designation performance assessment of fire alarm system based on principal components analysis. Wang et al. [12].have discussed two kinds of circular fire source arrangement localization methods on the basis of the dynamic optimization technology. Huang et al. [13]. have investigated the smoke spread process and proposed the soot yield rate by experimental and numerical studies. Shaltout et al. [14]. have represents a comprehensive account of the computational fluid dynamics model used for the simulation of the fire dynamics in full scale rolling stock vehicle. In order to research the fire alarm process of LSD and ASD, lots of numerical simulation research have been carried in this paper. The aim of the study is to provide the basic data and simulation methods for the engineering application of ASD and LSD in large-space buildings, which is important in the fire safety of the public buildings. 2. Experiment 2.1. Fire Dynamics Simulator software The FDS software [15,16], which is authoritative in the fire safety engineering field, is used to predict the flow state and the obscuration of the smoke. FDS analyzes the process of smoke and heat transfer during combustion by using numerical methods to solve the turbulence equation. FDS includes combustion models, thermal radiation models, pyrolysis models and so on [17]. 2.2. Simulation models As shown in Fig. 1, the combustion chamber has a flat roof, the room’s height is 12.0 m, the width is 40.0 m and the length is 50.0 m with a fire source in the center. The fire alarm system is ASD and LSD, which is marked in Fig. 1.
Fig. 1. The location of the fire alarm detectors in the fire scenarios. (A) the top view of the fire scenarios with LSD and ASD system; (B) the front view of the fire scenarios. 2
Case Studies in Thermal Engineering 18 (2020) 100594
Y. Huang et al.
As shown in Fig. 1A, the LSD system is adopted three groups in the length direction, which are marking as Rank1 to Rank3 with 14 m distance between each other. Similar to the length LSD, there are four groups in the width direction, marking as Row1 to Row4 with a 12 m gap distance. What’s more, the LSD system have been set two layers with a height of 10 m and 5 m as shown in Fig. 1B. As shown in Fig. 1A, the ASD system is adopt twelve Aspirator samplers, which are marked as Point and divided to three groups. The group1 contains Piont11 to Piont14, the group2 contains Piont21 to Piont24 and the group3 contains Piont31 to Piont34. And similar to LSD, the ASD system have been set two layers with a height of 10 m and 5 m as shown in Fig. 1B. 2.3. Simulation parameters As shown in Fig. 2, the 3D model of LSD and ASD system have set in the FDS. The parameters of LSD and ASD system have list as follow. The enable setpoint of LSD is set as 30%/m, which is default value in the FDS model. The flow rate of the Aspirator samplers is 0.3 kg/s, and the transfer delay of Piont11 to Point 14 are 6s, 19s, 32s and 45s respectively. The enable setpoint of ASD is 50.0%, which is general value in the fire alarm test. The power of fire source is set as 80 kW, the soot yield rate of wood is set as 0.15 g/g [13]. For simulations involving buoyant plumes, a measure of how well the flow field is resolved is given by the non-dimensional expression D* =δx , where D* is a characteristic fire diameter and δx is the nominal size of a mesh cell. � D* ¼
Q pffiffi ρ∞ cp T∞ g
�25
(1)
The simulation grid used in this calculation is 0.1 m � 0.1 m � 0.1 m, the power of fire source is 80 kW, then the mesh is satisfied independence request with the FDS Validation Guide [18]. 2.4. Simulation environment These FDS models are simulated on the DELL computing server R930, which is equipped with two Intel Xeon E7-4809 v3 of 8-core CPU, 64GB memory of 1333 Mhz and 10 TB disk with RAID (Redundant Array of Inexpensive Disks). The simulation time of the model is 1800 s, the environment temperature is 25 � C. 3. Results and discussion 3.1. The visibility chart As shown in Fig. 3, the simulation result at height of 10.0 m and 5.0 m is indicated by the visibility cloud chart. At the height of 5.0 m, the growth of visibility chart is later than that of height ¼ 10.0 m, which is conform to the general process of smoke spread. The distance between the two-difference height is becoming bigger alone the fire growth. At the time ¼ 30s, height ¼ 10.0 m, the similar chart at height ¼ 5.0 m is appearing at the time ¼ 120s, which is 90s later. While the time ¼ 480s, the visibility chart of height ¼ 5.0 m is analogous to the visibility chart of height ¼ 5.0 m at the time ¼ 60s, the difference is about 420s, which is much bigger than the distance at the previous ones. The raise of the difference between the two height is indicate that the smoke spread process is becoming slower at the constant heat release rate. What’s more, the result of the visibility chart is also indicated the smoke entrainment and descend progress. As the influence of the building’s edge, once the smoke arrived the edge, the smoke is becoming slow and descend. As shown in Fig. 3, the visibility charts are becoming from the edge to the center, which have proved the affection of the edge. 3.2. The detector in FDS 3.2.1. The simulation mechanism of LSD LSD is a kind of fire detector used pairs beam detectors, which can be defined by specifying the endpoints, (x1, y1, z1) and (x2, y2,
Fig. 2. The 3D model in the FDS with the location of the ASD and LSD. 3
Case Studies in Thermal Engineering 18 (2020) 100594
Y. Huang et al.
Fig. 3. The visibility cloud chart acorss the fire source plane.
z2), of the beam and the total percent obscuration at which the detector activates. FDS determines which mesh cells lie along the linear path defined by the two endpoints. The beam detector response is evaluated as follow [15]: !! N X � 100% (2) obscuration ¼ 1 exp Km ρs;i Δxi i¼1
where i is a mesh cell along the path of the beam, ρs;i is the soot density of the mesh cell, Δxi is the distance within the mesh cell that is traversed by the beam, and Km is the mass extinction coefficient. Since a single linear path cannot span more than one mesh, having a beam detector that crosses multiple meshes will require post processing. Break the beam detector path into multiple DEVC lines, one for each mesh that the beam crosses. The total obscuration is given by Ref. [19]: " # N Y O¼ 1 ð1 Oi = 100Þ � 100% (3) i¼1
where Oi is the FDS output for the beam detector of the ith path (note that the bracketed term contains a product rather than a sum). 3.2.2. The simulation mechanism of ASD [19] An aspiration detection system groups together a series of smoke measurement devices. An aspiration system consists of a sampling pipe network that draws air from a series of locations to a central point where an obscuration measurement is made. To define such a system in FDS, you must provide the sampling locations, sampling flow rates, the transport time from each sampling location, and if an alarm output is desired, the overall obscuration “setpoint.” [15].
Fig. 4. Obscuration rate curves with in different groups of ASD in large-space buildings. 4
Case Studies in Thermal Engineering 18 (2020) 100594
Y. Huang et al.
PN obscuration ¼ 1
exp
Km
N td;i Þm_ i X i¼1 s;i ðt PN _i i¼1 i¼1 m
ρ
!!
ρs;i Δxi
� 100% = m
(4)
where m_ i is the mass FLOWRATE at sampling location i, ρs;i ðt td;i Þ is the soot density at sampling location i, td;i s prior (DELAY) to the current time t, and Km is the MASS_EXTINCTION_COEFFICIENT associated with visible light. 3.3. Fire alarm process of ASD With the fire growth and smoke spread process, the ASD system is alarming along with the Obscuration rate raise. For the obscuration rate curve of group 1 contains four Aspirator samplers from Point 11 to Point 14, so that the alarm process curve of group1 is marked with Rank1, and Rank2 for group2, Rank3 for group3, respectively. As shown in Fig. 4, as the threshold of 50% the Rank2 is alarming for fire later than Rank1 and Rank3, which is difference with the general view. For the large-space buildings is so tall that the smoke layer is descend in the edge of the building, which is same as the result of the visibility chart in Fig. 3. However, the alarm process is not as slow as the smoke spread shown in Fig. 3, the gap value between different groups of ASD is small. The maximum value the difference is 15s between Rank1 and Rank3, which is much smaller, comparing with the smoke space process. Further, in order to investigate the fire alarm process of ASD at different height, more study works have been carried. As shown in Fig. 5, the fire alarm process of ASD at different height (H ¼ 10.0 m, H ¼ 5.0 m) have investigated and compared. The obstruction rate curve of the group1 (from point11 to point14), the obstruction rate curve of height ¼ 5.0 m colored as rad is sometime later than the obstruction rate curve of height ¼ 10.0 m colored as black, as shown in Fig. 5A. For the smoke entrainment and descendant at the edge of the building, the obstruction rate curves have been across and overlap between the value at difference height. As shown in Fig. 5A and Fig. 5C, the overlap of the curve is obvious. As shown in Fig. 5B, the result of the obstruction rate curve is difference with the others, because of the curve is not affected by the edge of the building, and the fire source is below the ASD of group2. 3.4. Fire alarm process of LSD In this paper, two kinds method of the LSD set have been investigated, which are both conformed to the technical code for fire safety. The first one is set along the length direction marked with Rank1 to Rank3, which is an economical choice for this building as show in Fig. 1A. However, the length direction set should be saving a pair of LSD equipment than width direction set marked with Row1 to Row4, the performance of LSD equipment should be better for the length direction set. In the paper, an assumption has been proposed as follow, the two kinds method of the LSD set is same as each other. As shown in Fig. 6A, the obscuration rate curve of Row4 and Row1 have been indicated a sharp jump at the time about 150s, which is obviously different from Row2 and Row3. As the Row4 and Row1 is near the edge of the building, which is influence by the entertainment and descend affection of the smoke. So that the LSD system is response at the time about 150s with the width direction set. As shown in Fig. 6B, the obscuration rate curve of Rank2 have been indicated a sharp jump at the time about 100s and same for the curve at difference height. The obscuration rate curve of Rank1 and Rank3, which is influence by the entertainment and descend affection of the smoke, is responded about 150s. As shown in Fig. 6, except for Rank2, the obscuration rate curve of others has been indicated that the higher detector is responding earlier than the lower ones, while is similar to the ASD system. 4. Conclusions The FDS code is used to simulate the smoke filling process in a large-space building with the length, width and height equal to 50 m, 40 m and 12 m respectively. This paper mainly studies the alarm process of LSD and ASD system under the influence of the height and the building’s edge. The obscuration rate has been investigated, and some valuable result have been gained as follow:
Fig. 5. The obstruction rate curve of the ASD with different height. (A) the curve of group1 contains the Aspirator samplers from point11 to point14; (B) the curve of group2 contains the Aspirator samplers from point21 to point24; (C) the curve of group3 contains the Aspirator samplers from point31 to point34. 5
Case Studies in Thermal Engineering 18 (2020) 100594
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Fig. 6. Obscuration rate curves of LSD with different way for decorating the detector. (A) the detector is set along the width direction, marked as Row1 to Row4; (B) the detector is set along the length direction, marked as Rank1 to Rank3.
1. the raise of the difference between the two height is indicate that the smoke spread process is becoming slower at the constant heat release rate. 2. the higher set of the smoke decent is responding earlier than the lower ones in the large-space open environment, which should be named as “height advantage”. 3. for the ASD system, the height advantage will be reduced along with the descend of smoke at the building’s edge. 4. the optimizing set of LSD could be calculated by the numerical simulation, as the result indicate an interest phenomenon in the investigation. CRediT authorship contribution statement Yufeng Huang: Conceptualization, Methodology, Software, Writing - original draft, Writing - review & editing, Visualization, Supervision, Project administration, Funding acquisition. Ershen Wang: Investigation, Formal analysis, Writing - original draft. Yuxia Bie: Investigation, Formal analysis, Writing - original draft. Acknowledgement This work was supported by the National undergraduate innovation and entrepreneurship training program (201910143417) and Doctoral Initiation Fund of Shenyang Aerospace University (18YB02). The authors appreciate the supports deeply. References [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11]
ISO7240-15, Fire Detection and Alarm Systems -Part 15:Point-type Fire Detectors Using Smokeand Heat Sensors, International Standard, 2014. UL217, Smoke Alarms. 2015, Inc, U.L. UL268, Smoke Detectors for Fire Alarm Systems, Inc, U.L, 2016. EN54-22, Fire Detection and Fire Alarm Systems Part 22-line Type Heat Detectors, BSI Standards Publication, 2007. BS 5839-1, Fire Detection and Fire Alarm Systems for Buildings –Part 1: Code of Parctice for Design, Istallation, Commissioning and Maintenance of Systems in Non-domesic Premises, 2013. NFPA, Standard for Automotive Fire Apparatus, 2009. NFPA, National Fire Alarm and Signaling Code, 2013. R.C. Till, J.W. Coon, Other detection and alarm devices, in: Fire Protection, Springer, 2019, pp. 27–38. S. Wang, et al., A Sauter mean diameter sensor for fire smoke detection, Sensor. Actuator. B Chem. 281 (2019) 920–932. H. Zhang, et al., Experimental study on the characteristics of fire smoke movement in Ultra thin and tall Atriums by hot smoke test, in: E3S Web of Conferences, EDP Sciences, 2019. Z. Lan, N. Qu, M. Zhu, Design performance assessment of fire alarm system based on principal components analysis, in: 5th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering (ICMMCCE 2017). 2017, Atlantis Press, 2017.
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[12] G. Wang, X. Feng, Z. Zhang, Fire source range localization based on the dynamic optimization method for large-space buildings, Sensors 18 (6) (2018) 1954. [13] Y. Huang, X. Chen, C. Zhang, Numerical simulation of the variation of obscuration ratio at the fire early phase with various soot yield rate, Case Stud. Therm. Eng. 18 (2020) 100572. [14] R.E. Shaltout, M.A. Ismail, Simulation of fire dynamics and firefighting system for a full-scale passenger rolling stock, in: Sustainable Rail Transport, Springer, 2020, pp. 209–228. [15] K.B. McGrattan, G.P. Forney, Fire Dynamics Simulator User’s Guide, 2004. [16] McGrattan, K.B. and G.P. Forney, Fire Dynamics Simulator Technical Reference Guide Volume vol. 2: Verification. [17] McGrattan, K.B. and G.P. Forney, Fire Dynamics Simulator Technical Reference Guide Volume vol. 1: Mathematical Model. [18] McGrattan, K.B. and G.P. Forney, FDS_Validation_Guide. [19] McGrattan, K.B. and G.P. Forney, FDS_Technical_Reference_Guide.
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Contents lists available at ScienceDirect
Case Studies in Thermal Engineering journal homepage: http://www.elsevier.com/locate/csite
Simulation investigation on the smoke spread process in the large-space building with various height Yufeng Huang *, Ershen Wang , Yuxia Bie College of Electronic and Information Engineering, Shenyang Aerospace University, Shenyang, Liaoning, 110136, PR China
A R T I C L E I N F O
A B S T R A C T
Keywords: Large-space buildings FDS Smoke spread process LSD ASD
In this paper, the fire growth and smoke spread process in Large-space building have been investigated through the Fire Dynamics Simulator (FDS). What’s more, the alarm process of the Line-type Infra-red Beam Smoke Fire Detector (LSD) and the Aspirating Smoke Detection System (ASD) have discussed, some valuable results have been obtained. The results indicated that the raise of the difference between the two height, and the smoke spread process is becoming slower at the constant heat release rate. The set of fire alarm system in large-space should be consider the “height advantage”, as the higher set of the smoke decent responding earlier than the lower ones. What’s more, referring to the ASD system the aspirator samplers close to the building’s edge should be affected by the edge. For the LSD system should determine the parameter of install by the numerical or experimental test to optimizing the performance of the LSD, which has been proposed in the paper. In summary, the research investigates the basic fire alarm process for the LSD and the ASD System in the large-space buildings, and these are valuable for the selecting and setting of fire alarm system in the large-space buildings.
1. Introduction Along the process of urbanization in China, more and more large-space buildings have been emerged. The large-space building meeting the expectation of the space utilization ratio, open views and so on, however the large-space building also accelerate the smoke spread speed due to the open-type space convection of air, which should be enhance the fire risk of the large-space building. Thus, the early detection of the fire should be necessary, which meet many difficulties in the large-space building due to the open-type space convection of air and thermal barrier effect because of the space height. The normal fire detection systems used in the large-space building are the Line-type Infra-red Beam Smoke Detector (LSD) and the Aspirating Smoke Detection System (ASD). The detection principle of LSD is according to the obscuration value caused by the smoke particles yield of the fire in the buildings, and ASD is according to the collected smoke particles quantity of the fire in the buildings. So that the fire growth rate and smoke spread process is the key factor in the open-area fire detection process. In order to investigate the fire growth rate and smoke spread process in largespace buildings, many researches have been done lots of work, which is a research hot-point along with the urbanization in China. For the traditional point-type smoke detector, many standards and rules have been proposed by reference groups. For example, ISO 7240-15 [1] specifies requirements, test methods, and performance criteria for point-type fire detectors using smoke and heat sensors, Underwriters Laboratories Inc (UL) raise the requirements for smoke detectors and its accessories of electrically operated single and
* Corresponding author. E-mail address: [email protected] (Y. Huang). https://doi.org/10.1016/j.csite.2020.100594 Received 14 January 2020; Received in revised form 21 January 2020; Accepted 21 January 2020 Available online 23 January 2020 2214-157X/© 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Case Studies in Thermal Engineering 18 (2020) 100594
Y. Huang et al.
multiple station by UL standards [2,3]. What’s more, mounts of standards is enacted, such as British Standards Institution (BSI) [4,5], National Fire Protection Association (NFPA) [6,7] and so on. How to manage the fire alarm system in large-space building? Many researchers [8–14] have been seeking for other method. Till [8] discussed the selection of the fire alarm system, and proposed two basic requirements for the detection system. Wang et al. [9]. have proposed A Sauter mean diameter sensor for fire smoke detection. Zhang et al. [10]. has carried experimental Study on the Characteristics of Fire Smoke Movement in Ultra-Thin and Tall Atriums by Hot Smoke Test. Lan et al. [11].have proposed designation performance assessment of fire alarm system based on principal components analysis. Wang et al. [12].have discussed two kinds of circular fire source arrangement localization methods on the basis of the dynamic optimization technology. Huang et al. [13]. have investigated the smoke spread process and proposed the soot yield rate by experimental and numerical studies. Shaltout et al. [14]. have represents a comprehensive account of the computational fluid dynamics model used for the simulation of the fire dynamics in full scale rolling stock vehicle. In order to research the fire alarm process of LSD and ASD, lots of numerical simulation research have been carried in this paper. The aim of the study is to provide the basic data and simulation methods for the engineering application of ASD and LSD in large-space buildings, which is important in the fire safety of the public buildings. 2. Experiment 2.1. Fire Dynamics Simulator software The FDS software [15,16], which is authoritative in the fire safety engineering field, is used to predict the flow state and the obscuration of the smoke. FDS analyzes the process of smoke and heat transfer during combustion by using numerical methods to solve the turbulence equation. FDS includes combustion models, thermal radiation models, pyrolysis models and so on [17]. 2.2. Simulation models As shown in Fig. 1, the combustion chamber has a flat roof, the room’s height is 12.0 m, the width is 40.0 m and the length is 50.0 m with a fire source in the center. The fire alarm system is ASD and LSD, which is marked in Fig. 1.
Fig. 1. The location of the fire alarm detectors in the fire scenarios. (A) the top view of the fire scenarios with LSD and ASD system; (B) the front view of the fire scenarios. 2
Case Studies in Thermal Engineering 18 (2020) 100594
Y. Huang et al.
As shown in Fig. 1A, the LSD system is adopted three groups in the length direction, which are marking as Rank1 to Rank3 with 14 m distance between each other. Similar to the length LSD, there are four groups in the width direction, marking as Row1 to Row4 with a 12 m gap distance. What’s more, the LSD system have been set two layers with a height of 10 m and 5 m as shown in Fig. 1B. As shown in Fig. 1A, the ASD system is adopt twelve Aspirator samplers, which are marked as Point and divided to three groups. The group1 contains Piont11 to Piont14, the group2 contains Piont21 to Piont24 and the group3 contains Piont31 to Piont34. And similar to LSD, the ASD system have been set two layers with a height of 10 m and 5 m as shown in Fig. 1B. 2.3. Simulation parameters As shown in Fig. 2, the 3D model of LSD and ASD system have set in the FDS. The parameters of LSD and ASD system have list as follow. The enable setpoint of LSD is set as 30%/m, which is default value in the FDS model. The flow rate of the Aspirator samplers is 0.3 kg/s, and the transfer delay of Piont11 to Point 14 are 6s, 19s, 32s and 45s respectively. The enable setpoint of ASD is 50.0%, which is general value in the fire alarm test. The power of fire source is set as 80 kW, the soot yield rate of wood is set as 0.15 g/g [13]. For simulations involving buoyant plumes, a measure of how well the flow field is resolved is given by the non-dimensional expression D* =δx , where D* is a characteristic fire diameter and δx is the nominal size of a mesh cell. � D* ¼
Q pffiffi ρ∞ cp T∞ g
�25
(1)
The simulation grid used in this calculation is 0.1 m � 0.1 m � 0.1 m, the power of fire source is 80 kW, then the mesh is satisfied independence request with the FDS Validation Guide [18]. 2.4. Simulation environment These FDS models are simulated on the DELL computing server R930, which is equipped with two Intel Xeon E7-4809 v3 of 8-core CPU, 64GB memory of 1333 Mhz and 10 TB disk with RAID (Redundant Array of Inexpensive Disks). The simulation time of the model is 1800 s, the environment temperature is 25 � C. 3. Results and discussion 3.1. The visibility chart As shown in Fig. 3, the simulation result at height of 10.0 m and 5.0 m is indicated by the visibility cloud chart. At the height of 5.0 m, the growth of visibility chart is later than that of height ¼ 10.0 m, which is conform to the general process of smoke spread. The distance between the two-difference height is becoming bigger alone the fire growth. At the time ¼ 30s, height ¼ 10.0 m, the similar chart at height ¼ 5.0 m is appearing at the time ¼ 120s, which is 90s later. While the time ¼ 480s, the visibility chart of height ¼ 5.0 m is analogous to the visibility chart of height ¼ 5.0 m at the time ¼ 60s, the difference is about 420s, which is much bigger than the distance at the previous ones. The raise of the difference between the two height is indicate that the smoke spread process is becoming slower at the constant heat release rate. What’s more, the result of the visibility chart is also indicated the smoke entrainment and descend progress. As the influence of the building’s edge, once the smoke arrived the edge, the smoke is becoming slow and descend. As shown in Fig. 3, the visibility charts are becoming from the edge to the center, which have proved the affection of the edge. 3.2. The detector in FDS 3.2.1. The simulation mechanism of LSD LSD is a kind of fire detector used pairs beam detectors, which can be defined by specifying the endpoints, (x1, y1, z1) and (x2, y2,
Fig. 2. The 3D model in the FDS with the location of the ASD and LSD. 3
Case Studies in Thermal Engineering 18 (2020) 100594
Y. Huang et al.
Fig. 3. The visibility cloud chart acorss the fire source plane.
z2), of the beam and the total percent obscuration at which the detector activates. FDS determines which mesh cells lie along the linear path defined by the two endpoints. The beam detector response is evaluated as follow [15]: !! N X � 100% (2) obscuration ¼ 1 exp Km ρs;i Δxi i¼1
where i is a mesh cell along the path of the beam, ρs;i is the soot density of the mesh cell, Δxi is the distance within the mesh cell that is traversed by the beam, and Km is the mass extinction coefficient. Since a single linear path cannot span more than one mesh, having a beam detector that crosses multiple meshes will require post processing. Break the beam detector path into multiple DEVC lines, one for each mesh that the beam crosses. The total obscuration is given by Ref. [19]: " # N Y O¼ 1 ð1 Oi = 100Þ � 100% (3) i¼1
where Oi is the FDS output for the beam detector of the ith path (note that the bracketed term contains a product rather than a sum). 3.2.2. The simulation mechanism of ASD [19] An aspiration detection system groups together a series of smoke measurement devices. An aspiration system consists of a sampling pipe network that draws air from a series of locations to a central point where an obscuration measurement is made. To define such a system in FDS, you must provide the sampling locations, sampling flow rates, the transport time from each sampling location, and if an alarm output is desired, the overall obscuration “setpoint.” [15].
Fig. 4. Obscuration rate curves with in different groups of ASD in large-space buildings. 4
Case Studies in Thermal Engineering 18 (2020) 100594
Y. Huang et al.
PN obscuration ¼ 1
exp
Km
N td;i Þm_ i X i¼1 s;i ðt PN _i i¼1 i¼1 m
ρ
!!
ρs;i Δxi
� 100% = m
(4)
where m_ i is the mass FLOWRATE at sampling location i, ρs;i ðt td;i Þ is the soot density at sampling location i, td;i s prior (DELAY) to the current time t, and Km is the MASS_EXTINCTION_COEFFICIENT associated with visible light. 3.3. Fire alarm process of ASD With the fire growth and smoke spread process, the ASD system is alarming along with the Obscuration rate raise. For the obscuration rate curve of group 1 contains four Aspirator samplers from Point 11 to Point 14, so that the alarm process curve of group1 is marked with Rank1, and Rank2 for group2, Rank3 for group3, respectively. As shown in Fig. 4, as the threshold of 50% the Rank2 is alarming for fire later than Rank1 and Rank3, which is difference with the general view. For the large-space buildings is so tall that the smoke layer is descend in the edge of the building, which is same as the result of the visibility chart in Fig. 3. However, the alarm process is not as slow as the smoke spread shown in Fig. 3, the gap value between different groups of ASD is small. The maximum value the difference is 15s between Rank1 and Rank3, which is much smaller, comparing with the smoke space process. Further, in order to investigate the fire alarm process of ASD at different height, more study works have been carried. As shown in Fig. 5, the fire alarm process of ASD at different height (H ¼ 10.0 m, H ¼ 5.0 m) have investigated and compared. The obstruction rate curve of the group1 (from point11 to point14), the obstruction rate curve of height ¼ 5.0 m colored as rad is sometime later than the obstruction rate curve of height ¼ 10.0 m colored as black, as shown in Fig. 5A. For the smoke entrainment and descendant at the edge of the building, the obstruction rate curves have been across and overlap between the value at difference height. As shown in Fig. 5A and Fig. 5C, the overlap of the curve is obvious. As shown in Fig. 5B, the result of the obstruction rate curve is difference with the others, because of the curve is not affected by the edge of the building, and the fire source is below the ASD of group2. 3.4. Fire alarm process of LSD In this paper, two kinds method of the LSD set have been investigated, which are both conformed to the technical code for fire safety. The first one is set along the length direction marked with Rank1 to Rank3, which is an economical choice for this building as show in Fig. 1A. However, the length direction set should be saving a pair of LSD equipment than width direction set marked with Row1 to Row4, the performance of LSD equipment should be better for the length direction set. In the paper, an assumption has been proposed as follow, the two kinds method of the LSD set is same as each other. As shown in Fig. 6A, the obscuration rate curve of Row4 and Row1 have been indicated a sharp jump at the time about 150s, which is obviously different from Row2 and Row3. As the Row4 and Row1 is near the edge of the building, which is influence by the entertainment and descend affection of the smoke. So that the LSD system is response at the time about 150s with the width direction set. As shown in Fig. 6B, the obscuration rate curve of Rank2 have been indicated a sharp jump at the time about 100s and same for the curve at difference height. The obscuration rate curve of Rank1 and Rank3, which is influence by the entertainment and descend affection of the smoke, is responded about 150s. As shown in Fig. 6, except for Rank2, the obscuration rate curve of others has been indicated that the higher detector is responding earlier than the lower ones, while is similar to the ASD system. 4. Conclusions The FDS code is used to simulate the smoke filling process in a large-space building with the length, width and height equal to 50 m, 40 m and 12 m respectively. This paper mainly studies the alarm process of LSD and ASD system under the influence of the height and the building’s edge. The obscuration rate has been investigated, and some valuable result have been gained as follow:
Fig. 5. The obstruction rate curve of the ASD with different height. (A) the curve of group1 contains the Aspirator samplers from point11 to point14; (B) the curve of group2 contains the Aspirator samplers from point21 to point24; (C) the curve of group3 contains the Aspirator samplers from point31 to point34. 5
Case Studies in Thermal Engineering 18 (2020) 100594
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Fig. 6. Obscuration rate curves of LSD with different way for decorating the detector. (A) the detector is set along the width direction, marked as Row1 to Row4; (B) the detector is set along the length direction, marked as Rank1 to Rank3.
1. the raise of the difference between the two height is indicate that the smoke spread process is becoming slower at the constant heat release rate. 2. the higher set of the smoke decent is responding earlier than the lower ones in the large-space open environment, which should be named as “height advantage”. 3. for the ASD system, the height advantage will be reduced along with the descend of smoke at the building’s edge. 4. the optimizing set of LSD could be calculated by the numerical simulation, as the result indicate an interest phenomenon in the investigation. CRediT authorship contribution statement Yufeng Huang: Conceptualization, Methodology, Software, Writing - original draft, Writing - review & editing, Visualization, Supervision, Project administration, Funding acquisition. Ershen Wang: Investigation, Formal analysis, Writing - original draft. Yuxia Bie: Investigation, Formal analysis, Writing - original draft. Acknowledgement This work was supported by the National undergraduate innovation and entrepreneurship training program (201910143417) and Doctoral Initiation Fund of Shenyang Aerospace University (18YB02). The authors appreciate the supports deeply. References [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11]
ISO7240-15, Fire Detection and Alarm Systems -Part 15:Point-type Fire Detectors Using Smokeand Heat Sensors, International Standard, 2014. UL217, Smoke Alarms. 2015, Inc, U.L. UL268, Smoke Detectors for Fire Alarm Systems, Inc, U.L, 2016. EN54-22, Fire Detection and Fire Alarm Systems Part 22-line Type Heat Detectors, BSI Standards Publication, 2007. BS 5839-1, Fire Detection and Fire Alarm Systems for Buildings –Part 1: Code of Parctice for Design, Istallation, Commissioning and Maintenance of Systems in Non-domesic Premises, 2013. NFPA, Standard for Automotive Fire Apparatus, 2009. NFPA, National Fire Alarm and Signaling Code, 2013. R.C. Till, J.W. Coon, Other detection and alarm devices, in: Fire Protection, Springer, 2019, pp. 27–38. S. Wang, et al., A Sauter mean diameter sensor for fire smoke detection, Sensor. Actuator. B Chem. 281 (2019) 920–932. H. Zhang, et al., Experimental study on the characteristics of fire smoke movement in Ultra thin and tall Atriums by hot smoke test, in: E3S Web of Conferences, EDP Sciences, 2019. Z. Lan, N. Qu, M. Zhu, Design performance assessment of fire alarm system based on principal components analysis, in: 5th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering (ICMMCCE 2017). 2017, Atlantis Press, 2017.
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[12] G. Wang, X. Feng, Z. Zhang, Fire source range localization based on the dynamic optimization method for large-space buildings, Sensors 18 (6) (2018) 1954. [13] Y. Huang, X. Chen, C. Zhang, Numerical simulation of the variation of obscuration ratio at the fire early phase with various soot yield rate, Case Stud. Therm. Eng. 18 (2020) 100572. [14] R.E. Shaltout, M.A. Ismail, Simulation of fire dynamics and firefighting system for a full-scale passenger rolling stock, in: Sustainable Rail Transport, Springer, 2020, pp. 209–228. [15] K.B. McGrattan, G.P. Forney, Fire Dynamics Simulator User’s Guide, 2004. [16] McGrattan, K.B. and G.P. Forney, Fire Dynamics Simulator Technical Reference Guide Volume vol. 2: Verification. [17] McGrattan, K.B. and G.P. Forney, Fire Dynamics Simulator Technical Reference Guide Volume vol. 1: Mathematical Model. [18] McGrattan, K.B. and G.P. Forney, FDS_Validation_Guide. [19] McGrattan, K.B. and G.P. Forney, FDS_Technical_Reference_Guide.
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