Designing a Model for Controlling Fire and Smoke - Report Example

Fire Engineering Student’s Name College Instructor’s Name 2012 Outline I Introduction II Basic building information III Fire scenarios modeled IV The CFAST/FDS modeling performed and the results obtained V Program and comparison between the programs VI Critical analysis and discussion of the results V Conclusions References Introduction Smoke control in warehouse is very important in ensuring that in case of fire it is controlled. Therefore air flow into and out of plays an important role in managing fire in a warehouse. This means ventilation should be designed to allow smoke escape from the building. If proper ventilation is not provided property may be lost due to collapse as result of pressure from smoke and heat from fire. Smoke is said be stratified and needs to be cooled down by fresh air and release of heat. Smoke is known to move upward therefore the height of the building is very important. The height will enable evacuators push smoke from the fire in order to be in a position to safe life and property. Smoke control ventilation for warehouse should be designed based on type of inventory stored. Flammable materials stored in warehouse will require large ventilation for evacuation and release of smoke. This means ventilation will depend in pressure that is likely to calculate during the fire period. However there is difference between the wall and ceiling ventilations when it comes to smoke control and burning rate (Bishop and Drysdale, 1995). Two vent wall case and single wall vent can also be related. In the case of a uniform temperature compartment where there is a steady flow with air flowing through the lower vent; it is possible to show by hydrostatics and Bernoulli flow that it is possible to compute the mass flow. Usually the pressure is determined by temperature flow of air and other atmospheric conditions. In design a model for controlling fire and smoke, heat release rate and the ventilation size plays an important. The model usually relies on the physical and chemical relationship where fail us scenarios are determined. In a warehouse a two zone model is designed that is one zone which will control volume near the ceiling and another near the ground with cooled air. In designing this model temperature, pressure, density and air flow are taken into consideration. Basic building information The building is warehouse which stores goods on transit and the warehouse is near the port. The warehouse should have exterior staircase, should have also interior fans, lighting lights should be on ceiling as well as on the walls. There should be a walkway which will be used with employees. The fire proposed in modeling is assumed have capacity of heat of 6000kw inside the warehouse. All conditions within the warehouse at the time it is carrying goods have been taken into consideration. The height of the walls of the building have been assumed to be 25feet in which 15 is assumed to be the smoke zone. The rate at which air is entering to the building is assumed to be 300feet per minute. Fire scenarios modeled In designing the fire model 6 ventilations were considered along the top of the walls of the building. The ventilations are meant to release hot air and smoke during the fire. The ventilations are supplied fresh air by 3 openings at the south, north and west lower part of the walls. The openings are estimated of about 200 feet square. The fire that is included in the calculation is assumed to be 20 feet in diameter and smoke production is up to 200,000 cfm with a supply of fresh air of 190,000 cfm. The following formula will determine the smoke layer interface: Tn = Cn(Tmax – Tb) + Tb Be used, where Tn = interface height temperature Tmax = maximum temperature (at the ceiling) Tb = temperature near bottom of warehouse Cn = interpolation constant. The exhaust vent will help reduce smoke and increase efficiency in removing smoke that is hot. The following is heat release rate formula from the warehouse; Heat release rate = or The HRR is then calculated using the following equation: Where: = heat release rate (kW) = burning or mass loss rate (kg/sec) = effective heat of combustion (kJ/kg) D= the diameter of the fire. T= temperature The following was the formula that was used to measure the floor of smoke through ventilation. V leak = AL Where v leak is the volume flow of smoke through the ventilation AL is the ventilation area ∆p is the change of pressure and p∞ is the density. With the availability of an inaccurate prediction of an incomplete burning levels thud impacts the calculations derived from radioactive heat transfer and burning rates which are estimated by human tenability’s. High quality which comes in with quantified uncertainty and relatively low temperatures provides measurements of fires gas species from the interior of the under ventilated compartment fires that are needed for guiding the development and also for validation of improved fire fields models. The CFAST/FDS modeling performed and the results obtained The fire dynamic simulator designed was meant to help the flow of smoke from the warehouse. The equations used mostly depended on the density rather than pressure. In designing this model a few challenges were experienced which included heat transfer and combustion of gases. During the period of experiment various scenarios were used and they include unventilated conditions, partially ventilated, fully ventilated and only the bottom pane. In the first case all the openings to the warehouse are close making the building unventilated where the second instance three windows were left open making it partially ventilated. The other case was when the pane of a window left open to provide ventilation. After carrying out the experiment the heat release rate was measured and the following graph was determined together with FDS and the experiment. The graph above shows that heat release rate is higher in the experiment than in FDS. The graph below shows the same result but the FDS heat release rate is higher. This is because the ventilation in the first graph brought in air which supported the fire while in the second case there was no enough ventilation something that lead to dying out of fire. With the growth of the fire a layer will form under the ceiling as a result of the smoke and gases that are generated by the fire. The fire at this point may start flowing out of the compartment and with increased growth of the fire where the opening is small to be able to carry out the products generated during combustion at the rate of production there will be an increase in the upper layer making it to descent to the floor. There may be full involvement in the compartment as the fire develops leading to flashover occurrence. Program and comparison between the programs There are two programs that can be used here; FDS simulator and he zone model approach. FDS takes into consideration all factors unlike NIST-FDS program which considers volume of smoke that is being released. It can use many chemical reactions unlike other models. This program solves for chemical reactions, radiation, temperature changes and combustion. It carries out large tabulation of data that carries the bulk of the energy system and require direct resolutions so as to represent a flow process that has the desired accuracy. The modelling involving small scale eddies has in addition the ability to reduce computational demand with the overall speed of simulation process being improved. It does not use averaged parameters and this makes it possible for a transient solution being obtained easily Critical analysis and discussion of the results In the model just like any other standard FDS model there is no account for the deposition of soot. Lack of consideration of the deposition of soot in the FDS model results into an increase the optical density of the smoke layer. Because of high optical densities in the model will result in optimistic detector response times in addition to a conservative tenability analysis. A performance based system whose design has a base in erroneous FDS results may cause the overcompensating for the smoke amount registered in the upper layer. FDS model helps in modelling the spread of smoke in a warehouse thus helping to know the ventilations to be provided for in designing the warehouse. It also helps in modelling where all indicators of fires and smoke are considered which other models do not consider. The model is accurate and considers various fire scenarios. The model considers time as conditions of fire changes. It uses fluid flows techniques that puts emphasis on the flow of gases because they have turbulence. Conclusions A two zone model is found to provide a good smoke control for a warehouse building. Ventilations in the building on upper part of a wall is essential as well the fresh air feed at lower end of the wall. This increases the exhaust out flow of unclean gas from the building. FDS modelling technique gives a temporal resolution that plays a vital in the evaluation of entrainment. It can therefore, be seen that a time averaged technique may have a very serious on the total air that is entrained into fire. The development of basic model for FDS was through a mathematical approach which is common in CDF models where proper emphasis is placed on slowing down the flow of heat transfer that is brought about by fire (Novozhilov, 2001). The simulation has the capability of fully simulating all the fluctuations which are large than the mesh size. When an estimation is being made for smaller eddies there is little uncertainties due to the fact that the eddies are of a uniform character. References Bishop, S & Drysdale, D (1995) Experimental Comparison with a Compartment Fire Model. International Communications in Heat and Mass Transfer. Novozhilov, V (2001) Computational fluid dynamics modeling of compartment fires. Progress in energy and combustion science. 27 () p611-666 Chang, C., Banks, D., & Meroney., R. 2003. Computational Fluid Dynamics Simulation of the Progress of Fire Smoke in Large Space, Building Atria. Tamkang Journal of Science and Engineering, Vol. 6, No. 3, pp. 151-157 (2003) Read More