Validation of a Smoke Detection Performance Prediction Methodology. Volume 4. Evaluation of FDS Smoke Detection Prediction Methodology

Transcription

1 Validation of a Smoke Detection Performance Prediction Methodology Volume 4. Evaluation of FDS Smoke Detection Prediction Methodology Prepared by: Frederick W. Mowrer and James A. Milke University of Maryland Pravinray Gandhi Underwriters Laboratories Inc. October 2008 Fire Protection Research Foundation

2 FOREWORD This report presents the results of a Foundation project whose goal was to develop a validated engineering methodology to calculate and accurately predict the response time of spot-type and aspirated smoke detection systems exposed to incipient fires and growing fires. The report, divided into four volumes, describes the test methods, test results, computer simulations and analyses used for this project, which addresses the validation of a smoke detection performance prediction methodology. The four volumes of this report include: Volume 1, which addresses the characterization of the heat and smoke release rates of eight incipient fire sources selected for this project; Volume 2, which addresses the large-scale room fire tests conducted as part of this project; Volume 3, which addresses evaluation of smoke detector performance in the large-scale room fire tests conducted as part of this project; Volume 4, which addresses comparisons of current FDS smoke detection prediction methodologies with actual smoke detector performance in the largescale room fire tests. The Research Foundation expresses gratitude to the project sponsors and technical panelists listed on the following page. The content, opinions and conclusions contained in this report are solely those of the authors.

3 Validation of a Smoke Detection Performance Prediction Methodology Research Project Technical Panel Shane Clary, Bay Alarm Company Kenneth Dungan, PLC Foundation Jay Ierardi, R.W. Sullivan Engineering Kevin McGrattan, National Institute of Standards and Technology Dan Nichols, NYS Code Enforcement and Administration Ali Rangwala, Worcester Polytechnic Institute Joseph Su, National Research Council of Canada Principal Sponsors Honeywell Life Safety National Electrical Manufacturers Association Siemens Building Technologies, Inc. SimplexGrinnell Contributing Sponsors Automatic Fire Alarm Association Bosch Security Systems Xtralis, Inc.

4 Validation of a Smoke Detection Performance Prediction Methodology Volume 4. Evaluation of FDS smoke detection prediction methodology Prepared for: Kathleen Almand Fire Protection Research Foundation 1 Batterymarch Park Quincy, MA Prepared by: Frederick W. Mowrer and James A. Milke University of Maryland Pravinray Gandhi Underwriters Laboratories, Inc. October 10, 2008

5 October 10, 2008 p. ii Executive Summary This report, divided into four volumes, describes the test methods, test results, computer simulations and analyses used for this project, which addresses the validation of a smoke detection performance prediction methodology. This project was conducted jointly by the University of Maryland (UM) and Underwriters Laboratories, Inc., (UL) under the auspices of the Fire Protection Research Foundation (FPRF). The financial and technical support of the FPRF, the project sponsors and the project technical panel are gratefully acknowledged. The four volumes of this report include: Volume 1, which addresses the characterization of the heat and smoke release rates of eight incipient fire sources selected for this project; Volume 2, which addresses the large-scale room fire tests conducted as part of this project; Volume 3, which addresses evaluation of smoke detector performance in the large-scale room fire tests conducted as part of this project; Volume 4, which addresses comparisons of current FDS smoke detection prediction methodologies with actual smoke detector performance in the large-scale room fire tests. The overall objective of this project has been to evaluate the capabilities of the current release version (5.1.0) of the Fire Dynamics Simulator (FDS) to predict smoke detector activation in response to relatively low energy incipient fire sources. The project was subdivided into four tasks, consistent with the four volumes included in this report. The first task was to characterize the heat and smoke release rates of eight incipient fire sources selected for this project. The incipient fire sources are described in Table E1; the fire sources include four flaming fire sources and four smoldering/pyrolyzing fire sources. The heat and smoke release rates of these incipient fire sources were measured in the same IMO intermediate scale calorimeter that UL used previously as part of its FPRF-sponsored smoke characterization project [Fabian, et al., 2007]. Three replicate tests were conducted for each of the eight incipient fire sources to provide a measure of the repeatability of these tests. Volume 1 of this report provides descriptions of the incipient fire source fuels and ignition sources, the fire test apparatus and instrumentation used for this task, and the results of these tests. Volume 1 also addresses FDS simulations of these tests conducted in the IMO calorimeter as a means to evaluate the predictive capabilities of the FDS model on a preliminary basis. These FDS simulations were not originally planned, but have proven valuable in troubleshooting issues related to the simulation of fires involving these incipient sources. They provide an indication of the uncertainty in simulating the fire source terms in FDS. The second task was to perform large-scale room fire tests using the eight incipient fire sources characterized in Task 1. The large-scale room fire tests were conducted in two rooms at the UL facility in Northbrook, IL. The first set of large-scale tests was conducted under unventilated conditions in the standard room used to test smoke detectors for the UL 217/268 standards; this room measures 10.8 m (36 ft.) long by 6.6 m (22 ft.) wide by 3.0 m (10 ft.) tall. Three replicate tests were conducted with each of the eight incipient fire sources, for a total of 24 unventilated

6 October 10, 2008 p. iii room fire tests. The second set of large-scale tests was conducted in a 7.2 m (24 ft) long by 7.2 m (24 ft) wide by 3.0 m (10 ft) high room constructed specifically for this project to represent a mechanically ventilated commercial space. This room was provided with mechanical injection ventilation and a ceiling return air plenum to represent a typical commercial type of installation. Three replicate tests were conducted with each of the eight incipient fire sources at nominal mechanical ventilation rates of 6 and 12 air changes per hour; two replicate tests were conducted with each of the incipient fire sources under unventilated conditions in this room. Thus, 64 fire tests were conducted in the ventilated room, for a total of 88 large-scale fire tests in the two rooms. A matrix showing the designations of the 88 large-scale tests is provided in Table E2. Table E1. Incipient fire sources Fuel source Ignition source Fire type Shredded office paper Small flame (50 W) Flaming Flexible PU foam / Small flame (50 W) Flaming microfiber fabric Flexible PU foam / Hotplate Smoldering/pyrolysis microfiber fabric Ponderosa pine Hotplate Smoldering/pyrolysis Cotton linen fabric Hotplate Smoldering/pyrolysis PVC wire Electric overcurrent Smoldering/pyrolysis Computer case Small flame (UL 94) Flaming Printed circuit board Small flame (ATIS T1.319) Flaming Table E2. Matrix of large-scale room fire test designations Incipient fire source Unventilated Ventilated room room 6 ach 12 ach 0 ach Shredded office paper 1, 2, 3 25, 26, 27 49, 50, 51 73, 74 Flaming PU foam / 4, 5, 6 28, 29, 30 52, 53, 54 75, 76 microfiber fabric Smoldering PU foam / 7, 8, 9 31, 32, 33 55, 56, 57 77, 78 microfiber fabric Ponderosa pine 10, 11, 12 34, 35, 36 58, 59, 60 79, 80 Cotton linen fabric 13, 14, 15 37, 38, 39 61, 62, 63 81, 82 PVC wire 16, 17, 18 40, 41, 42 64, 65, 66 83, 84 Computer case 19, 20, 21 43, 44, 45 67, 68, 69 85, 86 Printed circuit board 22, 23, 24 46, 47, 48 70, 71, 72 87, 88 ach = nominal mechanical injection ventilation rate in air changes per hour The large-scale rooms were instrumented with a number of thermocouples, velocity probes and light obscuration measurement devices to provide a basis for evaluating the current capability of FDS to predict fire-induced conditions throughout a room in response to incipient fire sources. The rooms were both equipped with a number of spot-type commercial smoke detectors from two manufacturers. The ventilated test room was also equipped with three aspirated smoke

7 October 10, 2008 p. iv detection systems from one manufacturer. The response of these different smoke detection devices during these tests provides a basis for evaluating the current capability of FDS to predict smoke detector activation in response to incipient fire sources. Volume 2 of this report describes the details of the large-scale room fire tests and provides the instrumentation and detection data from these 88 fire tests. More than 1,200 graphs have been developed to illustrate the results of these 88 tests; these graphs are too voluminous to print, so they are provided on electronic media in Excel files associated with each test. This large-scale room fire test data set should prove useful for future smoke transport and smoke detection validation exercises as well as for this one. The third task was to evaluate smoke detector performance during the large-scale fire tests. For this task, the response of the spot-type and aspirated smoke detectors during the fire tests was evaluated and characterized. These results were then compared with methodologies available in the fire safety literature for predicting the activation of smoke detectors. Volume 3 of this report describes the details of these comparisons. One objective of this project has been to develop the means, based on experimental data, to estimate the response of smoke detectors using the simulated results of the smoke conditions computed by FDS. Smoke conditions estimated by FDS throughout the domain include temperature, velocity and mass fraction of smoke (which can be related to light obscuration or visibility). One of the relatively unique aspects of this study is an examination of the role of ventilation conditions in identifying surrogate measures to predict smoke detector response. Within the last 10 years, there have been five significant studies examining the response of smoke detectors. These studies, examined as part of this project, include: Kemano by the National Research Council of Canada Naval Research Laboratory and Hughes Associates tests for shipboard applications Home Smoke Alarm Project by NIST Smoke Characterization Project by Underwriters Laboratories for the Fire Protection Research Foundation Experiments program in this project. These experimental programs include a sufficiently wide variety of spaces, fuels and ventilation conditions to form a substantial basis for the development of robust, simple guidelines for estimating smoke detector response. Unfortunately, the smoke detector responses appear to be strongly dependent on the specific characteristics of the smoke and in some cases on the detector technology. Consequently, proposing a single set of guidelines for obscuration, temperature rise and velocity which can apply to a wide range of applications is difficult, other than suggesting guidelines which would be very conservative in some applications. For flaming fires, the obscuration level in tests without forced ventilation ranged from 1.4 to 10.7 %/ft for ionization detectors and from 2.7 to 12.9 %/ft for photoelectric detectors. Given the noted range in the 80 th percentile values of obscuration at the time of response, a guideline which reasonably captures much of the data for smoke detectors of either type of technology is 8 %/ft.

8 October 10, 2008 p. v In the case of flaming fires in ventilated rooms, the 80 th percentile values of the obscuration levels differ appreciably for the two detection technologies. For flaming fires with ventilation, the 80 th percentile values of the obscuration level for photoelectric smoke detectors were 4.3 to 4.9 %/ft. In contrast, the 80 th percentile values of the obscuration level for ionization smoke detectors were 8.0 to 10.3 %/ft, although it is noted that the 10.3% is based on only two tests conducted at a forced ventilation rate of 12 ACH. As such, a possible guideline of obscuration levels for photoelectric detectors could be 5 %/ft for ventilation rates ranging from 6 to 12 ACH. For ionization detectors, the 8 %/ft value appears to be an appropriate guideline considering only the results from the tests with 6 ACH. With the limited number of tests conducted at 12 ACH where ionization detectors responded, a guideline to estimate their response cannot be suggested. For non-flaming fires without ventilation, the 80 th percentile values of the obscuration levels ranged from 4.4 to 18.5 %/ft for ionization smoke detectors and 1.6 to 12.1 %/ft for photoelectric smoke detectors. The 80 th percentile values of the obscuration levels for non-flaming fires with ventilation were all less than 1 %/ft in this study and approximately 5 %/ft for ionization detectors in the NRL study. Given the limited data in this area, a recommendation for establishing a guideline of only 1 %/ft is questionable, especially in light of the difference in results obtained from experiments conducted as part of this study and the NRL study. Until further data is obtained, a value in excess of 1 %/ft is recommended and should perhaps be as large as 2.5 %/ft. The temperature rise at the time of detection response for flaming fires with no forced ventilation is highly dependent on the detection technology. A temperature rise of approximately 5 K can be suggested as a reasonable conservative guideline for ionization detectors, though should be greater than 5 K, e.g. 15 K given the measurements obtained in the NRL and NIST tests. For non-flaming fires and all fires with forced ventilation a temperature rise of approximately 3 K appears to be a reasonable guideline to estimate smoke detector response of either technology. Because the velocities associated with the forced ventilation provided in the test room were appreciably greater than the ceiling jet velocity, a guideline based on velocity cannot be recommended for such cases. An appreciable variation of smoke conditions was noted at the time of response of smoke detectors in all of the experimental programs reviewed. While guidelines of obscuration level or temperature rise can be suggested, these are very approximate in nature and may involve appreciable errors. One reason for this error is the fact that light obscuration and temperature are not related to the operating mechanisms of current smoke detector technologies, i.e. light scattering and ionization. Volume 3 presents an outline of additional research which could be used to better correlate light obscuration with light scattering measurements. The fourth task of this project was to evaluate the capabilities of the current release version (5.1.0) of the Fire Dynamics Simulator (FDS) to predict smoke detector activation in the two rooms described in Task 2 in response to the relatively low energy incipient fire sources characterized in Task 1. As part of this task, FDS simulations were performed of the 32 different room fire scenarios conducted as part of this project. The FDS simulated results were then

9 October 10, 2008 p. vi compared with the experimental results. Volume 4 of this report describes the details of these simulations and comparisons. The baseline FDS simulations of the room tests were performed with a uniform grid size of 10 cm (4 in.). This resulted in a total number of 233,280 computational cells in both the unventilated enclosure domain, which had dimensions of 10.8 m (108 cells) by 7.2 m (72 cells) by 3.0 m (30 cells) high, as well as in the ventilated enclosure domain, which had dimensions of 7.2 m (72 cells) by 7.2 m (cells) by 4.5 m (45 cells) high. On a single-processor PC, it took a few hours to run the 5 to 10 minute simulations of the flaming fire sources to a few days to run the 80 to 90 minute simulations of the smoldering fire sources at this resolution. Doubling the grid resolution from 10 cm (4 in.) to 5 cm (2 in.) changes these run times from a few days to a number of weeks and consequently would be unreasonable for most applications. It is difficult to generalize about the comparisons of the FDS simulations of detector activation in the room tests with the actual room test detection data because of the wide range of results. In some cases, the simulated and actual smoke conditions at the detection stations were relatively close to one another and within the experimental scatter, while in other cases, the simulated smoke concentrations exceeded the measured smoke concentrations by relatively large margins. There are at least three potentially significant sources of uncertainty associated with FDS simulation of smoke detector performance in room fire scenarios: Uncertainties in the initial and boundary conditions specified for a scenario, including uncertainties in specification of the fire heat and smoke release rate histories and in specification of the mechanical ventilation; Uncertainties in the calculations performed by FDS to simulate heat and smoke transport; Uncertainties in the empirical models FDS currently uses to calculate smoke detector response and to predict smoke detector activation. Quantitative uncertainty analysis has not been performed as part of this project, but qualitatively it appears that the greatest uncertainties are associated with the first and third sources of uncertainty identified here. The eight incipient fire sources used for this project each exhibited a range of fire growth, heat release and smoke release rates that limited the reproducibility of the bench-scale and large-scale fire tests. It is unreasonable to expect the simulation of these fire scenarios to be any better than the scatter in the experiments being simulated. It is suspected that the treatment of mechanical ventilation represents another source of considerable uncertainty in the FDS simulations performed as part of this project. Real ventilation grilles and resulting airflows are more complicated than the simulated grilles and airflows in the ventilated enclosure. More work is needed to more fully explore this issue. Before this project was undertaken, the prediction of smoke production in FDS was based only on a user-specified constant soot yield tied to the heat release rate of a fire. During this project, at least three limitations with this approach to predicting smoke production were recognized:

10 October 10, 2008 p. vii Only a single fire source could be specified, which did not allow separate specification of an ignition source and other fuels subsequently ignited; The smoke release rate could not vary independently of the heat release rate, so products with variable smoke yields could not be modeled properly; Smoldering and pyrolyzing smoke sources that produce substantial quantities of smoke but little heat could not be modeled properly. As a result of these limitations, the developers of the FDS model incorporated a new algorithm that permits the user to specify smoke release independently of heat release. This new feature was used to specify smoke release rates for this project. The primary findings of this project can be summarized as follows: The smoke release rates of eight different incipient fire sources, including four flaming sources, three smoldering sources and one overheated electrical wire, have been measured under well-characterized conditions in replicate bench-scale tests conducted in the IMO intermediate scale calorimeter at Underwriters Laboratories in Northbrook, IL. The primary smoke signature of interest in this project was the obscuration of visible light. Additional data was gathered during the bench-scale tests, including particle count density, mean particle diameter, carbon monoxide production and carbon dioxide production. This additional data may be of use in future investigations, but has not been analyzed for this project. Smoke obscuration was measured in the exhaust duct of the IMO intermediate scale calorimeter by projecting a white light beam across the diameter of the exhaust duct onto a photocell and measuring the change in voltage at the photocell caused by smoke particles in the light beam. Smoke release rates are characterized in units of m 2 /s, where the smoke release rate is calculated as the product of the smoke extinction coefficient, k (m -1 ), by the volumetric flow rate in the exhaust duct, V (m 3 /s): I I S kv ln( o / ) V L The total smoke release (TSR) is characterized in units of m 2 and is calculated as the integral of the smoke release rate over the period of a test, i.e., the area under the smoke release rate curve: TSR t 0 Sdt The mass of smoke released during a test is characterized in units of g s and is calculated as the quotient of the total smoke release to the specific extinction coefficient, k m, which was assumed to have a constant value of 8.7 m 2 /g s :

11 October 10, 2008 p. viii m s TSR k m The average smoke yield during a test is calculated as the quotient of the mass of smoke released to the fuel mass loss during a test: y s ms m f When calculated in this way, the average smoke yields obtained for the eight incipient sources in the IMO apparatus are shown in Table E3 along with other data from the IMO tests. These data provide an indication of the variability in the replicate tests. When this project started, smoke production was calculated in FDS only in terms of constant smoke yield factors tied to the specified heat release rate through the mixture fraction model used by FDS. During this project, it became apparent that smoke yields for the eight incipient sources are not constant and that characterizing smoke production in terms of a constant smoke yield factor would not produce accurate smoke production or transport results in FDS for these incipient fire sources. During this project, the developers of FDS implemented a new method to specify smoke production independently of heat release. Called the species ID method, this method was used throughout this project to specify smoke production in FDS for both the IMO test simulations and the room fire simulations. The bench-scale tests conducted in the IMO apparatus were simulated in FDS as one means to validate the capabilities of FDS to model smoke production and transport. For these FDS simulations, a uniform grid size of 2.5 cm was used. These simulations of the IMO tests showed that the calculated smoke quantity transported past the smoke eye in the exhaust duct was similar to the quantity of smoke released from the fuel package, as shown in Table E4. The largest variation between output and input was 5.4%. Differences in the peak obscuration values and the times to reach these peaks between the IMO physical tests and FDS simulations are shown in Table E5. The simulated peak smoke release rate was within 17.3% of the specified peak smoke release rate for all fuels except the PVC insulated wire. The FDS simulated time to peak obscuration lagged the specified peak time by 4 to 33 seconds, with two exceptions. This lag time is most likely related to the transport lag between smoke release at the fuel source and measurement at the smoke eye in the exhaust duct. The IMO apparatus smoke test data was not corrected for transport lag; this suggests that the actual smoke release in the IMO tests occurred earlier than represented in the smoke release rate curves for these tests. For the FDS simulations of the IMO tests, one replicate test for each fire source was selected for simulation and comparison with the measured data from that test. For the FDS simulations of the room fire tests, the IMO test data was typically averaged for each fire source and this average data was used as input to the FDS simulations. The expected uncertainty in the FDS input data based on this approach has not yet been characterized.

12 October 10, 2008 p. ix Table E3. Summary of data obtained from tests conducted in IMO apparatus Sample Description Mode Peak HRR Peak SRR Smoke Yield Total SR Total HR (kw) (m 2 /s) (g/g) (m²) (MJ) Shredded Paper-1 Flaming Shredded Paper-2 Flaming Shredded Paper-3 Flaming Shredded Paper Average PU Foam/Microfiber-1 Flaming PU Foam/Microfiber-2 Flaming PU Foam/Microfiber-3 Flaming PU Foam/Microfiber Average Circuit Board-1 Flaming Circuit Board-2 Flaming Circuit Board-3 Flaming Circuit Board Average Computer Case-1 Flaming Computer Case-2 Flaming Computer Case-3 Flaming Computer Case Average PU Foam/Microfiber-1 Smoldering N/A N/A PU Foam/Microfiber-2 Smoldering N/A N/A PU Foam/Microfiber-3 Smoldering N/A N/A PU Foam/Microfiber Average Ponderosa Pine-1 Smoldering N/A N/A Ponderosa Pine-2 Smoldering N/A N/A Ponderosa Pine-3 Smoldering N/A N/A Ponderosa Pine Average Cotton Linen Fabric-1 Smoldering N/A N/A Cotton Linen Fabric-2 Smoldering N/A N/A Cotton Linen Fabric-3 Smoldering N/A N/A Cotton Linen Fabric Average PVC Insulated Wire-1 Smoldering N/A N/A PVC Insulated Wire-2 Smoldering N/A N/A PVC Insulated Wire-3 Smoldering N/A N/A PVC Insulated Wire Average

13 October 10, 2008 p. x Table E4. Variation in FDS modeling results of smoke measurement in IMO apparatus Fuel Source Model Output to Input Model Output to Test Flaming Shredded Office Paper -0.8% 4.8% PU Foam with Microfiber Fabric -5.4% -4.7% Printed Circuit Board 0.1% -1.6% Computer Case ABS Plastic 4.3% 4.7% Smoldering PU Foam with Microfiber Fabric -3.1% -1.5% Ponderosa Pine -1.6% 1.9% Cotton Linen Fabric -0.9% 1.3% PVC Insulated Wire -1.6% -5.2% Table E5. Peak obscuration values and times in the IMO physical tests and FDS simulations. The 88 room fire tests conducted as part of this project provide a wealth of data on the conditions resulting from the eight incipient fire sources and the response of spot, beam and aspirated detection systems to these conditions in both unventilated and mechanically ventilated enclosures. Only a fraction of this data has been analyzed in detail as part of this project, but all the data acquired during this project has been summarized in tabular and chart form in Excel spreadsheet files and will be made available for future analysis. More than 1,200 data charts have been generated to illustrate the data from these tests.

14 October 10, 2008 p. xi The responses of the two brands of photoelectric detectors used in this project were generally consistent with each other, but the levels of smoke obscuration reported by these detectors was not always consistent with the smoke obscuration levels measured at the adjacent detection stations. This may be due to the different methods used to measure smoke obscuration by the detectors, which use light reflection, and by the adjacent photocell assemblies, which use light obscuration. The levels of smoke obscuration reported by the spot detectors are based on correlations developed from testing in the UL smoke box using only a single smoke source, a smoldering cotton wick. This correlation has not been demonstrated for the smoke sources used in this project; this may account for at least some of the differences between the smoke obscuration levels reported by the spot detectors and those measured by the adjacent photocell assemblies. Based on analysis of the smoke detector data from the room fire tests in this project, the smoke obscuration at detection, represented in %/ft and based on the 80 th percentile values, are shown in Table E6 for the different ventilation conditions, fire conditions and detector types. Table E6. Smoke obscuration at detection in room tests based on 80 th percentile values. Unventilated 6 ACH Ventilated 12 ACH Flaming Ionization 8 8 Insuff. Data Photoelectric Nonflaming Ionization 12 1? Insuff. Data Photoelectric 10 1? 1? Based on analysis of the smoke detector data from the room fire tests in this project, the temperature rise at detection, represented in K and based on the 80 th percentile values, are shown in Table E7 for the different ventilation conditions, fire conditions and detector types. Table E7. Temperature rise at detection in room tests based on 80 th percentile values. Unventilated 6 ACH Ventilated 12 ACH Flaming Ionization 5 3 Insuff. Data Photoelectric Nonflaming Ionization 3 3 Insuff. Data Photoelectric 3 3 3

15 October 10, 2008 p. xii Based on analysis of the smoke detector data from the room fire tests in this project, substantial errors are indicated in using simplistic guidelines of obscuration and temperature rise based on 80th percentile values. The values reported in the previous tables both overestimate and underestimate response times in specific tests. These errors may be reduced through use of a dual parameter approach, e.g. obscuration and velocity in unventilated rooms: o Flaming fires, photoelectric detectors: %/ft and m/s o Non-flaming fires, photoelectric detectors: %/ft and m/s The near-ceiling velocity of ventilation in the ventilated room tests with 6 and 12 ACH exceeds the velocity of the ceiling jet from the incipient fires in these tests. The near-ceiling velocity field caused by the mechanical injection of air at 6 and 12 ACH has not been experimentally characterized. The responses of the aspirated systems in the 64 tests in the ventilated room have been summarized in Excel spreadsheets, but have not yet been analyzed. The data from the aspirated systems has not yet been synchronized with the other experimental data due to technical difficulties with the synchronization process. Baseline FDS simulations have been conducted for 32 different room fire scenarios involving the 8 incipient fire sources under 4 different conditions, including unventilated tests conducted in the UL 217/268 standard smoke room, unventilated tests conducted in the ventilated room constructed for this project, and ventilated tests conducted at 6 and 12 air changes per hour in this ventilated room. For the baseline FDS simulations, a 10 cm uniform grid was used, resulting in a total of 233,280 computational cells for both the unventilated and ventilated enclosures. For the baseline FDS simulations, the specified smoke release rate was based on measurements of smoke release rate in the IMO benchscale tests and was not corrected for transport lag. Additional FDS simulations have been conducted for a few scenarios using the multimesh feature of FDS to provide a higher level of resolution of 5 cm in the fire plume and ceiling jet regions of the two enclosures, but these simulations have not yet been compared with the experimental data or the baseline FDS simulations. These results and comparisons will be reported separately. Additional FDS simulations have also been conducted for the 16 mechanically ventilated scenarios using a different description for the ceiling vents than in the baseline calculations. These simulations use a uniform cell size of 10 cm, but they have not yet been compared with the experimental data or the baseline FDS simulations. These results and comparisons will be reported separately. The 32 FDS baseline simulations demonstrate a wide range of results in comparison with the related room fire tests so it is difficult to generalize about the current capability of FDS to predict smoke detector activation over the range of fuels and ventilation conditions evaluated in this project. In many of the 32 baseline FDS simulations, the predicted maximum level of smoke obscuration is higher than the measured level of smoke obscuration in the related room fire tests. This may be due to the relatively coarse resolution of 10 cm used for the baseline FDS simulations. In these simulations, it appears that the dynamics of plume entrainment is not fully captured, which would lead to higher concentrations of smoke in the FDS simulations. Another factor that may contribute to the higher predicted smoke

16 October 10, 2008 p. xiii obscuration levels is smoke deposition to room surfaces, which is not currently addressed in FDS. The levels of smoke obscuration measured by the photocell assemblies at the detection stations during the mechanically ventilated tests were low in comparison with the levels of smoke obscuration reported by the adjacent smoke detectors and in comparison with the levels of smoke obscuration predicted by the associated FDS simulations. The reason for this has not yet been determined. The mechanically ventilated tests conducted at 6 and 12 ACH demonstrated conditions different from those observed in the unventilated tests. In particular, smoke did not readily transport past the plane defined by the line between the two injection louvers at the center of the room. Instead, the smoke tended to stack up on the fire side of this plane, suggesting that the mechanical injection of air was acting as an air curtain. Qualitatively, this was observed in both the room fire tests as well as in the baseline FDS simulations. This also had the effect of delaying smoke detector response on the downstream side of the injection louvers. The impact of mechanical ventilation on smoke detector response warrants further investigation. Recommendations for further study include: Develop the relationship between light scattering and light obscuration for fuels of primary interest (UL 217 fuels, PU foam, etc.) as a means to resolve the differences in smoke obscuration levels reported by the smoke detectors and those measured by the adjacent photocell assemblies. Perform additional FDS simulations at higher resolutions to evaluate the effects on predicted smoke obscuration levels. Perform additional mechanically ventilated room tests to characterize the velocity field caused by the injection of air through representative air louvers. Establish methods to more accurately simulate the injection of air through representative air louvers in FDS. Further investigate the impact of mechanical ventilation on smoke detector response. In summary, this project has generated a wealth of new data on the fire-induced conditions in the room of origin resulting from a range of different incipient fire sources under both unventilated and mechanically ventilated conditions. It has also generated a wealth of data on the response of both spot-type and aspirated smoke detection systems to these conditions. Thirty-two different room fire scenarios were conducted in replicate in 88 large-scale tests and each scenario was simulated using the current release version (5.1.0) of the Fire Dynamics Simulator to evaluate the current capabilities of FDS to predict smoke detector response and activation. In light of the large number of room fire tests conducted and FDS simulations performed, it has not been possible to perform a comprehensive analysis of the results. The data from these tests and FDS simulations demonstrate a range of results that warrants further analysis.

17 October 10, 2008 p. xiv Acknowledgements The authors would like to acknowledge the financial and technical support provided by the Fire Protection Research Foundation, the project sponsors and the members of the project technical panel. The authors would also like to acknowledge the assistance provided by Alyson Blair, Allison Carey and Andrew Laird, who were undergraduate students in the Department of Fire Protection Engineering at the University of Maryland when this project was conducted as well as the assistance and technical support of Tom Fabian, Tom Lackhouse and Dan Steppan of UL. Special thanks to Scott Lang of System Sensor for his technical support throughout this project.

18 October 10, 2008 p. xv Validation of a Smoke Detection Performance Prediction Methodology Volume 4. Evaluation of FDS smoke detection prediction methodology Prepared for: Kathleen Almand Fire Protection Research Foundation 1 Batterymarch Park Quincy, MA Prepared by: Frederick W. Mowrer and James A. Milke University of Maryland Pravinray Gandhi Underwriters Laboratories, Inc. October 10, 2008

19 October 10, 2008 p. xvi TABLE OF CONTENTS Page Executive Summary Acknowledgements 1.0 Introduction Overview of the FDS smoke detection prediction methodology Description of unventilated test enclosure in FDS Description of the ventilated test enclosure in FDS Characterization of incipient fire sources for FDS Shredded office paper Flaming polyurethane foam with microfiber fabric Smoldering polyurethane foam with microfiber fabric Ponderosa pine sticks Cotton linen fabric PVC insulated wire Computer case Printed circuit board Comparisons of FDS simulations with large-scale room fire experiments (Note this section available on CD) 7.0 Summary and Conclusions References 28 Appendix A. Channel designations and measurement locations Appendix B. Measured and simulated temperature data at detection stations (Note Appendices available on CD) ii xiv

20 October 10, 2008 p. xvii List of Figures Page Figure 1. Approximate instrumentation locations in unventilated test room 7 Figure 2. Perspective view of unventilated test enclosure as represented in FDS. 8 Figure 3. Approximate instrumentation locations in ventilated test room. 11 Figure 4. Perspective view of ventilated test enclosure as represented in FDS. 12 Figure 5a. Measured and average heat release rates for shredded office paper. 13 Figure 5b. Measured heat release rate and FDS representation for shredded office paper test Figure 5c. Measured and average smoke release rates for shredded office paper. 14 Figure 5d. Measured smoke release rate and FDS representation for shredded office paper test Figure 6a. Measured and average heat release rates for flaming polyurethane foam with microfiber fabric. 16 Figure 6b. Average heat release rate and FDS representation for flaming polyurethane foam with microfiber fabric. 16 Figure 6c. Measured and average smoke release rates for flaming polyurethane foam with microfiber fabric. 17 Figure 6d. Average smoke release rate and FDS representation for flaming polyurethane foam with microfiber fabric. 17 Figure 7a. Measured and average smoke release rates for smoldering polyurethane foam with microfiber fabric. 18 Figure 7b. Average smoke release rate and FDS representation for smoldering polyurethane foam with microfiber fabric. 19 Figure 8a. Measured and average smoke release rates for Ponderosa pine sticks. 20 Figure 8b. Average smoke release rate and FDS representation for Ponderosa pine sticks. 20 Figure 9a. Measured and average smoke release rates for cotton linen fabric. 21 Figure 9b. Average smoke release rate and FDS representation for cotton linen fabric. 22 Figure 10a. Measured and average smoke release rates for overheated PVC wire. 23 Figure 10b. Average smoke release rate and FDS representation for overheated PVC wire. 23 Figure 11a. Measured and average smoke release rates for computer case. 24 Figure 11b. Average smoke release rate and FDS representation for computer case. 25 Figure 12a. Measured and average heat release rates for flaming printed circuit board. 26 Figure 12b. Average heat release rate and FDS representation for printed circuit board. 26 Figure 12c. Measured and average smoke release rates for printed circuit board. 27 Figure 12d. Average smoke release rate and FDS representation for printed circuit board. 27 (Figures 13a through B32c available on CD)

21 October 10, 2008 p. xviii List of Tables Page E1. Incipient fire sources iii E2. Matrix of large-scale room fire test designations iii E3. Summary of data obtained from tests conducted in IMO apparatus ix E4. Variation in FDS modeling results of smoke measurement in IMO apparatus x E5. Peak obscuration values and times in the IMO physical tests and FDS simulations. x E6. Smoke obscuration at detection in room tests based on 80th percentile values. xi E7. Temperature rise at detection in room tests based on 80th percentile values. xi 1. Designations used for the FDS simulations of the large-scale room experiments. 1

22 October 10, 2008 p Introduction This volume of this 4-volume report describes the fire modeling simulations that were conducted as part of this project to evaluate the current capabilities of the Fire Dynamics Simulator (FDS) to predict smoke detector activation in response to relatively low energy incipient fire sources. Version of the FDS model was used to perform these simulations and comparisons. This volume of the report also addresses comparisons of these FDS simulations with the large-scale room fire tests described in Volume 2 of this report. A series of eighty-eight large-scale room fire tests were conducted to develop data for use in this validation exercise. Twenty-four tests were conducted under unventilated conditions in the standard room used to test smoke detectors for the UL 217/268 standards; this room measures 10.8 m (36 ft.) long by 6.6 m (22 ft.) wide by 3.0 m (10 ft.) tall. Three replicate tests were conducted with each of the eight incipient fire sources identified in Table 1. The second set of large-scale tests were conducted in a 7.2 m (24 ft) long by 7.2 m (24 ft) wide by 3.0 m (10 ft) high room constructed specifically for this project to represent a mechanically ventilated space in a commercial facility. This room was provided with mechanically injected ventilation and a ceiling return air plenum to represent a typical commercial type of installation. Three replicate tests were conducted with each of the eight incipient fire sources at nominal mechanical ventilation rates of 6 and 12 air changes per hour; two replicate tests were also conducted with each of the eight incipient fire sources under unventilated conditions in this room. Thus, 32 different large-scale fire scenarios were conducted in replicate as part of this project; these 32 different fire scenarios have been simulated using the current release (5.1.0) of the FDS model. Table 1 summarizes the designations used for these 32 FDS simulations. Table 1. Designations used for the FDS simulations of the large-scale room experiments. Incipient fire source Unventilated Ventilated room room 6 ach 12 ach 0 ach Shredded office paper FPRF1 FPRF25 FPRF49 FPRF73 Flaming PU foam / FPRF4 FPRF28 FPRF52 FPRF75 microfiber fabric Smoldering PU foam / FPRF7 FPRF31 FPRF55 FPRF77 microfiber fabric Ponderosa pine FPRF10 FPRF34 FPRF58 FPRF79 Cotton linen fabric FPRF13 FPRF37 FPRF61 FPRF81 PVC wire FPRF16 FPRF40 FPRF64 FPRF83 Computer case FPRF19 FPRF43 FPRF67 FPRF85 Printed circuit board FPRF22 FPRF46 FPRF70 FPRF87 2. Overview of the FDS smoke detection prediction methodology The current release of FDS (5.1.0) includes three different methods for predicting the response and activation of spot, beam and aspirated smoke detectors, respectively, to fire-induced

23 October 10, 2008 p. 2 conditions within an enclosure. These methods are described in detail in the FDS Technical Reference Guide [McGrattan, et al., 2008] and in the FDS User s Guide [McGrattan, el al., 2008a]; they are summarized here. In general, FDS predicts the mass fraction of smoke throughout the computational domain based on user-specified heat and smoke release rates along with user-specified initial and boundary conditions. FDS then uses the predicted smoke mass fraction at the position of each specified smoke detection device to predict the level of smoke obscuration at the detector as well as the response and activation of the detection device. FDS uses a number of different sub-grid empirical models to calculate the response and activation of the different detection devices, as described below. For spot detectors, FDS uses a relatively simple model proposed by Heskestad [1975] to characterize the entry lag associated with smoke entering the detection chamber from the surrounding environment: dy ( t) c dt Y ( t) e Y ( t) c L / u( t) (1) Y c (t) is the smoke mass fraction inside the detection chamber at time t, Y e (t) is the smoke mass fraction in the environment outside the detector at time t, L is a characteristic length for the detection device and u(t) is the local free stream velocity of smoke outside the detection device at time t. FDS also includes a two-chamber variant of the entry lag model developed by Cleary, et al. [2000]. In this model, smoke first enters an antechamber before entering the detection chamber, with characteristic filling times associated with each process: t e e eu ; t c c u c The ' s and ' s in these relationships are empirical constants related to a specific detector geometry, while u is the local free stream velocity, as in the simpler one-chamber model. For the two-chamber model, the mass fraction of smoke within the detection chamber is calculated as: dy ( t) Y ( t t ) Y ( t) c dt e e t c c (2) Note that Equation 2 reduces to Equation 1 when e 0, c L and c 1. As noted in the FDS Technical Reference Guide, proponents of this model claim that the two filling times are needed to better capture the behavior of detectors in scenarios with relatively slow free-stream velocities(u < 0.5 m/s). In light of the increased complexity of the two-chamber model and the lack of suitable values for the four empirical constants needed for this model for the spot detectors used in this project, the simpler one-chamber entry lag model was used to model spot detector response for this project.

24 October 10, 2008 p. 3 The smoke obscuration at any position as well as within a detection chamber is related to the local smoke mass fraction as: OBS(% / m) 100 (1 exp( Km Ys (1m ))) (3) K m is the specific extinction coefficient of the smoke (m 2 /kg s ), is the local gas density (kg/m 3 ) and Y s is the smoke mass fraction (kg s /kg), either in the environment (Y e ) or in a detection chamber (Y c ). As noted in the FDS Technical Reference Guide, for most flaming fuels a suggested value for K m is 8700 m 2 /kg s ± 1100 m 2 /kg s at a wavelength of 633 nm. A value of 8700 m 2 /kg s was used for the specific extinction coefficient for this project. As noted in the FDS Technical Reference Guide, to model beam detectors in FDS, the user specifies the emitter and receiver positions and the total obscuration at which the beam detector will alarm. FDS then integrates the obscuration over the specified path length using the predicted smoke concentration in each grid cell along the path. As noted in the FDS User s Guide, a beam detector is defined by specifying the endpoints (x1,y1,z1) and (x2,y2,z2) of the beam, and the total % obscuration at which the beam detector activates. The beam detector response is evaluated as N OBS(%) exp K Y x (4) m i 1 i s, i i For an aspirated detection system, the user specifies the sampling port locations, the flow rate at each location, the transport time from each sampling port to the central detection unit, the flow rate of any bypass flow, and the total obscuration at which the detector will alarm. FDS then computes the smoke concentration at the central detection unit by weighting the predicted soot concentrations at the sampling locations with their flow rates after applying the appropriate time delay for each sampling port. The output of each aspiration system is computed as: OBS(%/ m) exp K m N i 1 s, i ( t td ), i N i 1 m i m i (5) where m is the mass flow rate of the i th sampling location and t t ) is the smoke density i s, i ( d, i at the i th sampling location t d,i s prior to the current time t. The lag time, t d,i, for each sampling port accounts for the time delay associated with transporting smoke from each sampling port back to the central detection unit. Before this project was undertaken, the prediction of smoke production in FDS was based only on a user-specified constant soot yield tied to the heat release rate of a fire. During this project, at least three limitations with this approach to predicting smoke production were recognized:

25 October 10, 2008 p. 4 Only a single fire source could be specified, which did not allow separate specification of an ignition source and other fuels subsequently ignited; The smoke release rate could not vary independently of the heat release rate, so products with variable smoke yields could not be modeled properly; Smoldering and pyrolyzing smoke sources that produce substantial quantities of smoke but little heat could not be modeled properly. As a result of these limitations, the developers of the FDS model incorporated a new algorithm that permits the user to specify smoke release independently of heat release. This new feature was used to specify smoke release rates for this project. 3.0 Description of unventilated test enclosure in FDS The unventilated test enclosure used for 24 of the large-scale room fire tests is illustrated in plan view in Figure 1. A perspective view of the unventilated test enclosure is shown in Figure 2; this view is a rendering of the enclosure as it was represented in FDS for this project. This enclosure, which is normally used as part of the UL 217/268 standards for listing smoke detectors, measures 10.8 m (36 ft.) long by 6.6 m (22 ft.) wide by 3.0 m (10 ft.) tall. The enclosure is equipped with a number of air supply and exhaust vents in the walls and ceiling for purging smoke from the room between tests, but these vents were not in operation during the unventilated fire tests; one open vent was included in the FDS simulations of this enclosure to provide a pathway for leakage flow between the enclosure and the external environment. A uniform 10 cm (4 in.) grid was used for the baseline FDS simulations of the unventilated enclosure. Because FDS uses a Poisson solver based on Fast Fourier Transforms in the y and z directions, the FDS User s Guide indicates that the second and third dimensions of the computational mesh should be of the form 2 l 3 m 5 n, where l, m and n are integers. For this reason, the computational domain was specified as 108 x 72 x 30 cells in the x, y and z directions, respectively, for a total of 233,280 computational cells. Since this resulted in a room that was 7.2 m (24 ft) wide instead of 6.6 m (22 ft), a solid wall was specified to fill the extra 0.6 m (2 ft) of width. The fire source is situated on a stand located 2.1 m (7 ft.) from the south wall along the longitudinal centerline of the room, as illustrated in Figure 1. The top of the stand is approximately 0.8 m (2 ft 8 in) above floor level. In the coordinate system adopted for this project, with the southeast corner of the room serving as the origin, the coordinates of the fire source base would be x = 2.1 m (7 ft), y = 3.3 m (11 ft) and z = 0.8 m (32 in), as illustrated in Figures 1 and 2. This fire source location was used for all tests conducted in the unventilated room test series. For standard test purposes, the unventilated test enclosure is equipped with three photocell/lamp assemblies as illustrated in Figure 1. The three photocell/lamp assemblies are located along the west wall, along the longitudinal centerline and along the east wall of the room, respectively, with the center of each assembly located approximately 5.3 m (17.7 ft) from the fire source in plan view. The photocell and lamp units of each assembly are spaced 1.5 m (5 ft) from each

26 October 10, 2008 p. 5 other, with the photocell and lamp units located 0.1 m (4 in) below the ceiling; the sidewall units are located m (7 in) from the adjacent walls. The purpose of these assemblies is to measure light obscuration in the vicinity of the west, center and east detector stations, respectively. The photocell used in these assemblies is a Weston Photronic Cell Model 594 unit, while the lamp is a GE model 4515 incandescent 6V/30W sealed beam all glass unit. Spot-type smoke detectors were mounted in the standard locations along the west wall, on the ceiling along the longitudinal centerline and along the east wall of the test room. The standard west wall and east wall detector stations only accommodate one detector each, so one brand of detector (SS) was mounted along the west wall while the other brand (SG) was mounted along the east wall. The standard ceiling detector station can accommodate two detectors, so one of each brand (SS and SG) was mounted at this south center location. A non-standard detector station was also located along the longitudinal centerline of the room at a horizontal distance of 6.3 m (21 ft) from the fire source. This site, designated as north center, could accommodate two detectors, so one of each brand (SS and SG) of spot detector was mounted at this north center location. A thermocouple was located at each of the four detector stations to measure gas temperatures at each station. The unventilated enclosure was equipped with additional instrumentation for this test series, including: A photocell tree with 3 photocell/lamp assemblies and associated thermocouples mounted at three different heights; A thermocouple tree with 8 thermocouples mounted at eight different heights; Three thermocouples located at three elevations within the fire plume and one thermocouple to measure the hotplate temperature during tests using the hotplate; Five thermocouples mounted in the ceiling jet along the longitudinal centerline; Probes to measure velocities in the x- and y-directions at one location in the ceiling jet, along with the gas temperature at this location. The photocell tree was located at coordinates of x = 7.5 m (25 ft) and y = 2.1 m (7 ft) relative to the southeast corner of the room. The elevations of the three photocell assemblies and associated thermocouples was 1.5 m (5 ft), 2.4 m (8 ft) and 2.7 m (9 ft) above the floor, respectively. The photocell used in these assemblies is a Weston Photronic Cell Model BB unit, while the lamp is a GE Edison Spot Halogen 20 #99372 (Q20MR16NSPICG) 12 volt 20 watt unit. The photocell and lamp in each assembly were separated by a horizontal distance of 0.3 m (1 ft). The thermocouple tree was located at coordinates of x = 7.5 m (25 ft) and y = 4.8 m (16 ft) relative to the southeast corner of the room. The eight thermocouples were located at elevations of 2.1 m (7 ft), 2.5 m (8 ft 4 in), 2.7 m (9 ft), 2.85 m (9ft 6 in), 2.9 m (9 ft 8 in), m (9 ft 9 in), 2.95 m (9 ft 10 in) and m (9 ft 11 in) above the floor, respectively. The three thermocouples within the fire plume were centered on the fire source at coordinates of x = 2.1 m (7 ft) and y = 3.3 m (11 ft). The lowest of the three plume thermocouples was located at an elevation of 0.1 m (4 in.) above the surface of the fuel, so the elevation of this

27 October 10, 2008 p. 6 thermocouple depended on the fuel source geometry. The middle of the three plume thermocouples was located at an elevation of 2.1 m (7 ft) above the floor and the upper plume thermocouple was located at an elevation of 2.85 m (9 ft 6 in) above the floor. The five thermocouples mounted in the ceiling jet were all located along the longitudinal centerline of the room (y = 3.3 m (11 ft)) at an elevation of m (9 ft 9 in) above the floor. The x-coordinates for these ceiling jet thermocouples were approximately 0.9 m (3 ft), 3.3 m (11 ft), 4.5 m (15 ft), 5.7 m (19 ft) and 6.9 m (23 ft), respectively. The velocity probe was located at coordinates of x = 7.5 m (25 ft), y = 4.5 m (15 ft) and z = m (9 ft 11 in) relative to the southeast corner of the room. The velocity probe was also equipped with a thermocouple to measure gas temperature at the location of the velocity probe. A complete listing of the instrumentation types, coordinates and data acquisition channel assignments for the unventilated room tests is provided in Table A1 in Appendix A of this volume of this report.

28 October 10, 2008 p. 7 N North center detector station West detector station South center detector station East detector station Fire source x Smoke detector MIC unit Velocity probe Ceiling jet TC Photocell tree y Photocell/lamp assembly TC tree z Figure 1. Approximate instrumentation locations in unventilated test room

29 October 10, 2008 p. 8 Figure 2. Perspective view of unventilated test enclosure as represented in FDS. 4.0 Description of the ventilated test enclosure in FDS The ventilated test enclosure used for 64 of the large-scale room fire tests is illustrated in Figure 3. A perspective view of the ventilated test enclosure is shown in Figure 4; this view is a rendering of the enclosure as it was represented in FDS for this project. This enclosure, which was designed and constructed for this project, measures 7.2 m (24 ft) long by 7.2 m (24 ft) wide by 3.0 m (10 ft.) tall. The enclosure was equipped with a mechanical ventilation system of the injection type, with two ceiling air diffusers provided for air injection and four transfer grilles provided in the ceiling for air exhaust to a 1.5 m (5 ft) deep plenum located above the ventilated test room. The ceiling plenum was vented to the general laboratory space through a large opening in the east wall. The air diffuser and transfer grille locations are shown in Figure 3. A uniform 10 cm grid was used for the baseline FDS simulations of the ventilated enclosure. The computational domain was specified as 72 x 72 x 45 cells in the x, y and z directions, respectively, for a total of 233,280 computational cells. For test purposes, the fire source was located on a stand located 0.6 m (2 ft.) from the north wall along the longitudinal centerline of the room, as illustrated in Figure 2. The top of the stand was located approximately 0.8 m (32 in) above floor level. In the coordinate system adopted for this project, with the northeast corner of the room serving as the origin, the coordinates of the fire source base would be x = 0.6 m (2 ft), y = 3.6 m (12 ft) and z = 0.8 m (32 in), as illustrated in Figures 3 and 4. This fire source location was used for all tests in this series. The ventilated test enclosure was equipped with four detector stations located at ceiling level at the quarter-points of the room, as shown in Figure 3. Each detector station was equipped with two spot-type photoelectric smoke detectors, including one of each brand (SS and SG), a photocell/lamp assembly and a thermocouple. The photocell and lamp units of each assembly were spaced 0.3 m (1 ft) from each other; the purpose of these assemblies was to measure light obscuration in the vicinity of the four detector stations. The photocell used in these assemblies is

30 October 10, 2008 p. 9 a Weston Photronic Cell Model BB unit, while the lamp is a GE Edison Spot Halogen 20 #99372 (Q20MR16NSPICG) 12 volt 20 watt unit. The ventilated test enclosure was also equipped with three aspiration type (VESDA) smoke detection systems. Each aspirated system had two sampling ports within the test enclosure, as illustrated in Figure 3, as well as one sampling port located outside the test enclosure. The VESDA1 system had sampling ports located near detector stations 1 and 2, with one sampling port located at coordinates x = 1.95 m (6 ft 6 in), y = 1.8 m (6 ft) and z = m (9 ft 11 in), and the other sampling port located at coordinates x = 1.95 m (6 ft 6 in), y = 5.4 m (18 ft) and z = m (9 ft 11 in). The VESDA2 system had sampling ports located near detector stations 3 and 4, with one sampling port located at coordinates x = 5.55 m (18 ft 6 in), y = 1.8 m (6 ft) and z = m (9 ft 11 in), and the other sampling port located at coordinates x = 5.55 m (18 ft 6 in), y = 5.4 m (18 ft) and z = m (9 ft 11 in). The VESDA3 system had sampling ports located near the west wall of the enclosure, with one sampling port located at coordinates x = m (23 ft 3 in), y = 1.8 m (6 ft) and z = m (9 ft 11 in), and the other sampling port located at coordinates x = m (23 ft 3 in), y = 5.4 m (18 ft) and z = m (9 ft 11 in) The ventilated enclosure was equipped with additional instrumentation for this test series, including: A photocell tree with 3 photocell/lamp assemblies and associated thermocouples mounted at three different heights located near the center of the room; A thermocouple tree with 8 thermocouples mounted at eight different heights located at the center of the room; Three thermocouples located at three elevations within the fire plume and one thermocouple to measure the hotplate temperature during tests that used the hotplate; Six thermocouples mounted in the ceiling jet along the longitudinal centerline; Probes to measure velocities in the x- and y-directions at one location in the ceiling jet, along with the gas temperature at this location. The photocell tree was located at coordinates of x = 3.6 m (12 ft) and y = 3.6 m (12 ft) relative to the northeast corner of the room. The elevations of the three photocell assemblies and associated thermocouples was 1.5 m (5 ft), 2.4 m (8 ft) and 2.7 m (9 ft) above the floor, respectively. The photocell used in these assemblies is a Weston Photronic Cell Model BB unit, while the lamp is a GE Edison Spot Halogen 20 #99372 (Q20MR16NSPICG) 12 volt 20 watt unit. A thermocouple was located adjacent to each photocell assembly. The thermocouple tree was located at coordinates of x = 3.6 m (12 ft) and y = 3.6 m (12 ft) relative to the northeast corner of the room. The eight thermocouples were located at elevations of 2.1 m (7 ft), 2.5 m (8 ft 4 in), 2.7 m (9 ft), 2.85 m (9ft 6 in), 2.9 m (9 ft 8 in), m (9 ft 9 in), 2.95 m (9 ft 10 in) and m (9 ft 11 in) above the floor, respectively. The three thermocouples within the fire plume were centered on the fire source at coordinates of x = 0.6 m (2 ft) and y = 3.6 m (12 ft). The lowest of the three plume thermocouples was located at an elevation of 0.1 m (4 in.) above the surface of the fuel, so the elevation of this thermocouple depended on the fuel source geometry. The middle of the three plume

31 October 10, 2008 p. 10 thermocouples was located at an elevation of 2.1 m (7 ft) above the floor and the upper plume thermocouple was located at an elevation of 2.85 m (9 ft 6 in) above the floor. The six thermocouples mounted in the ceiling jet were all located along the longitudinal centerline of the room (y = 3.6 m (12 ft)) at an elevation of m (9 ft 9 in) above the floor. The x-coordinates for these ceiling jet thermocouples were approximately 0.1 m (4 in), 1.8 m (6 ft), 3.0 m (10 ft), 4.2 m (14 ft), 5.4 m (18 ft) and 6.6 m (22 ft), respectively. The velocity probe was located at coordinates of x = 7.5 m (25 ft), y = 4.5 m (15 ft) and z = m (9 ft 11 in) relative to the southeast corner of the room. The velocity probe was also equipped with a thermocouple to measure gas temperature at the location of the velocity probe. A complete listing of the instrumentation types, coordinates and data acquisition channel assignments for the unventilated room tests is provided in Table A2 in Appendix A of this volume of this report. Mechanical ventilation was specified in FDS by injecting air through the two ceiling diffusers shown in Figure 3. For the baseline FDS simulations of the mechanically ventilated scenarios, two vents measuring 0.6 m by 0.6 m (2 ft by 2 ft) were specified in the ceiling, with a solid deflector plate specified 10 cm (4 in.) beneath the vent. For the simulations of the tests conducted at 6 ach, air was injected through these two vents at a velocity of 0.36 m/s; for the tests conducted at 12 ach, the air velocity was doubled to 0.72 m/s. It should be recognized that the air flow through the actual ceiling diffusers is more complicated than represented in the baseline FDS simulations. The real ceiling diffusers are composed of three concentric rings of square diffuser plates of various sizes that divert air at an angle in all four directions in the x- and y-directions. The air is injected through a duct that is much smaller than the nominal 0.6 m by 0.6 m area of the diffuser and consequently at much higher speed than assumed in the baseline case. A few additional FDS simulations have been conducted in an attempt to more accurately simulate the flow from the ceiling diffusers, but these are not discussed in detail in this report.

32 October 10, 2008 p. 11 VESDA 1 VESDA 2 VESDA 3 Detector station 1 Detector station 4 Fire source Detector station 2 Detector station 3 y z x Smoke detector MIC unit Photocell assembly Photocell tree Air transfer grille N Velocity probe Ceiling jet TC TC tree Ceiling diffuser Figure 3. Approximate instrumentation locations in ventilated test room.

33 October 10, 2008 p. 12 Figure 4. Perspective view of ventilated test enclosure as represented in FDS. 5.0 Characterization of incipient fire sources for FDS The smoke release rates of each of the eight incipient fire sources identified in Table 1 were measured in three replicate tests in the IMO bench-scale calorimeter, as described in Volume 1 of this report. Heat release rates were also measured in these tests for the flaming fire sources. These three replicate measurements for each incipient fire source provide an indication of the repeatability of these measurements and the uncertainties associated with characterizing the heat and smoke release rates of these incipient fire sources. For most of the fire sources, the measured heat and smoke release rates were averaged; then these average values were characterized for input into FDS, as described below. For some of the fire sources, notably the shredded office paper, averaging the three measurements did not characterize the heat and smoke release rate histories very well; for these fire sources, heat and smoke release rate histories were characterized from individual tests for input into FDS. 5.1 Shredded office paper Figure 5a shows the heat release rates measured in the IMO calorimeter for the three replicate tests of the shredded office paper along with the average heat release rates for these tests. Note how the individual tests show single peaks in HRR, while the average shows dual peaks due to the differences in the time to reach the peak in the individual tests. Because the average HRR