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Effects caused on Leaky integrate and fire model

Effects caused on Leaky integrate and fire model

Membrane potential characterises the neuron state in integrate and fire neuron model. Excitatory or inhibitory contributions by synaptic inputs are received by membrane potential that arrive from other neurons by their relative synapses. Spatial structure of the neuron associated with dendrites is neglected in single compartment integrate and fire model. The entire range of computational functions cannot be accounted for spiking neurons by the simplified mathematical models of biological neurons as in [Renaud Jolivetz et al.]. The temporal summation function is the main parameter of integrate and fire model of the neuron. To understand the behaviour of large recurrent networks of spiking neurons is the major challenge in computational neuroscience.

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Assessing the sprinkler activation predictive capability of the BRANZFIRE fire model

Assessing the sprinkler activation predictive capability of the BRANZFIRE fire model

A set of base case values were chosen and input files constructed for the simulations. The experiments were then simulated by the fire model using both the NIST/JET ceiling jet and Alpert’s ceiling jet options (which are the two ceiling jet correlations available in the BRANZFIRE zone model). The fire model included a heat transfer calculation for the temperature of the heat sensitive sprinkler element. Different sprinkler operational parameters such as the conduction factor, response time index (RTI) and the sprinkler depth below ceiling were also varied to assess the sensitivity of their effect on the activation time.

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Comparing modelled fire dynamics with charcoal records for the Holocene

Comparing modelled fire dynamics with charcoal records for the Holocene

Z-score transformed data do not provide information about quantitative changes in burned area, because the trans- formation is rank conserving but not linear. So, a given dif- ference in Z-score values [ ] does not imply an increase or decrease by the same magnitude in burned area [Mha] among different Z-scores. This suggests regional averages of trans- formed and untransformed data may not necessarily result in the same trends. Thus, with respect to the research ques- tion “What is the best way to compare fire model output with charcoal records?”, we conclude that it is more meaningful to convert the time series of modelled burned area or carbon emissions to Z-score for comparing modelled and observed palaeofire variability. While we do see some general agree- ment between model results and reconstructions, it is still un- clear whether the absolute values of simulated burned area are capturing the right magnitude for past fire activity. While high fluctuations could suggest huge changes (e.g. Fig. 4e), the absolute change is rather small (2 Mha, ca. 7 %). Future studies should consider methods of transforming model out- put variables and palaeo-proxy data consistently to increase the comparability of simulated and observed data. In this study the Z-score transformation helps to validate modelled natural fire occurrence and compare it to reconstructed val- ues of charcoal influxes reported as Z-scores.

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Analysis fire patterns and drivers with a global SEVER-FIRE v1.0 model incorporated into dynamic global vegetation model and satellite and on-ground observations

Analysis fire patterns and drivers with a global SEVER-FIRE v1.0 model incorporated into dynamic global vegetation model and satellite and on-ground observations

Advantages of including the relationship between land use and timing of pyrogenic activities in SEVER would possi- bly also extend to a better representation of fire seasonality. In sub-Saharan Africa for example, Fig. 11 reveals that the fire season (October–February, Fig. 10) is shifted towards early months of the dry season, which mainly results from the use of fires for agricultural and land management prac- tices (Clerici et al., 2004). For the whole Southern Hemi- sphere, however, human pyrogenic activity in SEVER is set to reach a maximum from March to May and September to November, which is not realistic in the case of sub-Saharan Africa, a major fire region. Timing of pyrogenic activities in sub-Saharan Africa may be rather challenging as even im- plementation of land use in a global fire model (Le Page et al., 2015) still brings a 1- to 3-month delay in fire peak. Fur- thermore, it was demonstrated that religious affiliation mod- ulates agricultural burning activities in the area (Pereira et al., 2015), which was not taken into account by global fire mod- elers at the time. It is seen that a set of regional case studies with an active use of available historical data is necessary to implement more realistic features of human pyrogenic ac- tivities in global fire models. Study and parameterization of

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Predicting Post-Fire Tree Mortality for 12 Western US Conifers Using the First Order Fire Effects Model (FOFEM)

Predicting Post-Fire Tree Mortality for 12 Western US Conifers Using the First Order Fire Effects Model (FOFEM)

Pre-fire and post-fire models were devel- oped for each species, with two exceptions. Lodgepole pine and whitebark pine were grouped because of the small sample size of whitebark pine (n = 147) and because there were no statistical differences between DBH, crown volume scorched, and CKR between the two species. Because the ponderosa pines and Jeffrey pines from fires in California were grouped into one yellow pine category during data collection, they were modeled together. The pre-fire model is designed for planning prescribed burns and uses a limited set of vari- ables to predict tree mortality. Candidate vari- ables for the pre-fire mortality model included DBH and crown scorch. The post-fire model is the most accurate model for predicting tree mortality and is likely the most useful in post- fire planning, such as creating individual tree marking guidelines. Candidate variables for the post-fire model included DBH, crown scorch, CKR, and beetle attack. Due to differ- ences in data collection methods among the datasets available for analysis, we developed separate crown volume scorched and crown volume killed models for ponderosa pine and Jeffrey pine and used crown length scorched for white fir, red fir, incense cedar, and sugar pine models, while all other species models used crown volume scorched. Based on plots of the logits, CKR was included as a continu- ous rather than class variable (Hosmer and Le- meshow 2000).

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Controls on fire activity over the Holocene

Controls on fire activity over the Holocene

The default JSBACH model was extended with a process- based fire model (Arora and Boer, 2005; Kloster et al., 2010; Krause et al., 2014) with updates according to Li et al. (2012). The fire model calculates the total fire occurrence probability as the product of three probability functions rep- resenting the availability of biomass, fuel moisture and igni- tion potential. The fire then spreads as a function of wind speed and soil moisture. Fuel availability is simulated as a function of aboveground biomass. Soil moisture is used as a surrogate for fuel moisture. Lightning ignitions are pre- scribed from a satellite-based climatology (Cecil et al., 2012) extended by a latitudinal dependency of the cloud-to-ground vs. intra-cloud lightning fraction (Price and Rind, 1994). Hu- man ignitions are not accounted for. With poorly constrained data on human fire interaction over the Holocene, we do not see any means to include those in the present study. However, fire models that do not explicitly account for human ignition can still reproduce the main features of the fire regime even in areas in which many fires are set by humans as has been shown by Prentice et al. (2011). Humans often set fire in re- gions that are fire-prone; as such, human ignitions tend to preempt, rather than augment, the natural fire regime (Pren- tice et al., 2011).

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Climate Change Impact on Future Wildfire Danger and Activity in Southern Europe: A Review

Climate Change Impact on Future Wildfire Danger and Activity in Southern Europe: A Review

Finally, some studies (5,6,7,8) have projected burnt areas with DGVM-fire models, namely the CARAIB (5) and CLM-AB DGVM (6,8) coupled with a fire model inspired in the CETEM model (Arora and Boer 2005), and the LPJ-GUESS-SIMFIRE and LPJmL-SPITFIRE DGVM-fire models both used in the same study (7). Importantly, the physiological processes at play are represented in the DGVMs, which enables the capture of climate and CO2 effects on primary production and gives a basis for the estimation of fuel load dynamics. Except for LPJ-GUESS-SIMFIRE, fuel loads are computed from the carbon pools accounting for the above-ground biomass. In SIMFIRE, the annual maximum FAPAR (fraction of vegetation-absorbed photosynthetically active radiation) represents vegetation fractional cover and is used as a proxy for fuel load/continuity. In CARAIB and CLM models, soil moisture dynamics as driven by climate/weather variations are predicted from the coupling of plant and soil hydrological processes, and soil moisture is used to represent fuel moisture, which in turn conditions fire spread in the fire module. Both LPJ-GUESS and LPJmL DGVM use the Nesterov drought index to represent the effect of fuel moisture on fire. It is calculated using daily temperature, dew point (~relative humidity), and number of days since last significant precipitation event. This index is used to compute fuel moisture and a fire danger index that influences both the probability of ignition success and fire spread in SPITFIRE, while the maximum daily Nesterov index is used to calibrate the annual burnt area model in SIMFIRE. An important difference between LPJ-GUESS and LPJmL is that the former represents vegetation based on explicit-individuals, whereas the later uses average individuals. It must also be noticed that SPITFIRE is a detailed process-based fire model and includes fire effects (Thonicke et al. 2010), whereas SIMFIRE predicts fractional burnt area from a simple function of land cover type, mean monthly FAPAR, annual maximum of the Nesterov index and population density, which has to be parameterized from observed burnt areas (Knorr et al. 2013).

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Resolving vorticity-driven lateral fire spread using the WRF-Fire coupled atmosphere–fire numerical model

Resolving vorticity-driven lateral fire spread using the WRF-Fire coupled atmosphere–fire numerical model

Abstract. Vorticity-driven lateral fire spread (VLS) is a form of dynamic fire behaviour, during which a wildland fire spreads rapidly across a steep leeward slope in a direction approximately transverse to the background winds. VLS is often accompanied by a downwind extension of the active flaming region and intense pyro-convection. In this study, the WRF-Fire (WRF stands for Weather Research and Forecast- ing) coupled atmosphere–fire model is used to examine the sensitivity of resolving VLS to both the horizontal and ver- tical grid spacing, and the fire-to-atmosphere coupling from within the model framework. The atmospheric horizontal and vertical grid spacing are varied between 25 and 90 m, and the fire-to-atmosphere coupling is either enabled or disabled. At high spatial resolutions, the inclusion of fire-to-atmosphere coupling increases the upslope and lateral rate of spread by factors of up to 2.7 and 9.5, respectively. This increase in the upslope and lateral rate of spread diminishes at coarser spatial resolutions, and VLS is not modelled for a horizontal and vertical grid spacing of 90 m. The lateral fire spread is driven by fire whirls formed due to an interaction between the background winds and the vertical circulation generated at the flank of the fire front as part of the pyro-convective updraft. The laterally advancing fire fronts become the domi- nant contributors to the extreme pyro-convection. The results presented in this study demonstrate that both high spatial res- olution and two-way atmosphere–fire coupling are required to model VLS with WRF-Fire.

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Modelling the role of fires in the terrestrial carbon balance by incorporating SPITFIRE into the global vegetation model ORCHIDEE – Part 1: simulating historical global burned area and fire regimes

Modelling the role of fires in the terrestrial carbon balance by incorporating SPITFIRE into the global vegetation model ORCHIDEE – Part 1: simulating historical global burned area and fire regimes

In this study, we have incorporated the SPITFIRE fire model (Thonicke et al., 2010) into the global land surface model ORCHIDEE (Krinner et al., 2005). This allowed us to simulate global fire activity during the 20th century, and to perform an in-depth model evaluation. In present study, we focus on evaluating the ORCHIDEE-SPITFIRE model per- formance in simulating fire behaviours and regimes, includ- ing ignitions, fire spread rate, fire patch length, fire size distri- bution, fire season and burned area. Quantification of fire car- bon emission as a component of the terrestrial carbon balance will be presented in a companion paper (Part 2). Specifically, the objectives of the present study are: (1) to evaluate simu- lated burned area using multiple data sets including that from satellite observation, government fire agency, and historical reconstruction over the 20th century (Sects. 3.1, 3.2, 3.3, 3.4. 3.5); (2) to compare simulated fire size distribution with ob- servations, in order to investigate especially the model’s abil- ity to simulate large fire occurrence (Sect. 3.6); and (3) to examine potential sources of model error in order to iden- tify future research need and potential model improvements (Sect. 4.2).

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Fire suppression using water mists – a numerical model

Fire suppression using water mists – a numerical model

This paper examines the numerical modeling of fine watersprays or mists for fire suppression, where the term “fine” refers to sprays or mists with diameters ranging from 20 to 120 pm (Jones and Nolan, 1995). It should be mentioned that the technology has gained considerable maturity over the past decade, and commercial applications - such as the BP twin fluid nozzle, and the Marioff Highfog system (Jones and Nolan, 1995), have been in place for some time. Early attempts to characterize the mists within the context of fire protection are reported in (Mawhinney, 1993), however, by no means, it can be implied that the technology is well-known, and its applications are “routine”. In fact, a considerable R & D effort is still going on, and the literature, although not yet extensive, is growing at high pace, particularly in the experimental area (Ndubizu et al., 1998; Yao et al., 1999). Also, the recent regulation by the International Maritime Organization (IMO), which requires the replacement in commercial ships o f the current sprinkler system with low impact systems, such as water mists, gave renewed impetus upon the already existing R & D. In what concerns modelling, progress has kept a slower pace. It

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Observed versus predicted fire behavior in an Alaskan black spruce forest ecosystem: an experimental fire case study

Observed versus predicted fire behavior in an Alaskan black spruce forest ecosystem: an experimental fire case study

observations to compare with model predictions. Com- paring model predictions with observed fire behavior characteristics allows end users to select a modeling sys- tem based on the model’s ability to produce predictions that most closely represent reality. For example, a spe- cific modeling system 1 might be chosen over modeling system 2 because the modeled rate of spread from sys- tem 1 was consistently closest to a documented set of rate-of-spread observations. To effectively evaluate fire behavior fuel modeling systems currently in operation, or to evaluate new fire behavior modeling systems when they are released, more fire behavior case studies for which direct observations of fire behavior are coupled with onsite sampled weather data and field-sampled tree demographic data are needed. Hand in hand with model development comes evaluation (Alexander and Cruz 2006), which should be an ongoing activity (Cruz et al. 2018). Future data sets that look to couple fire behavior observations with field observations should collect at- mosphere, landscape, and vegetation data that serve as input to fire behavior modeling systems. The current study could provide a template for how fire managers could collect and assemble fire behavior observations needed to choose the most appropriate fire behavior modeling system for their use.

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An Expected Value Comparative Analysis Study on First Responder and Fire Protection Policies, Services, and Products in the United States

An Expected Value Comparative Analysis Study on First Responder and Fire Protection Policies, Services, and Products in the United States

Fire insurance does not provide economic value once the cost of the policy and the net savings from fire damage as well as the probability of a fire are taken into consideration. The National Fire Protection Agency (2017) reported that United States fire departments responded to 358,500 home structure fires that caused $6.7 billion in fire damage. According to Statist a (2018), there were 127.59 million households in the United States making the probability that one’s home will catch on fire during any given year 1 in 2,800 (358,000 home fires/127,590,000 households = 0.0028). The average annual cost per household for fire damage is $52.51 ($6.7 billion/ 127.59 million). According to Value Penguin (2019), the average annual cost of a homeowner’s fire insurance policy was $1,083 nationwide. Therefore, the average expected value of fire insurance policy would be 0.0484 ($52.51/ $1,083) so those who purchased a fire insurance policy receive on average a return of less than five cents (0.0484) for every dollar invested. Home Fire Sprinklers

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Fire Fighting Robot Controlled Using Android Application

Fire Fighting Robot Controlled Using Android Application

ABSTRACT: Detection of fire at an early stage can avoid loss. Normally fire causes huge damage because of absence of human beings to detect fire. If fire is detected and extinguished at an early stage, one can avoid loss of life and property. Robotics has gained popularity due to the advancement of many technologies. Properly equipped Robot will detect fire. Once fire is detected equipped robot can be instructed to extinguish fire. The robot is mounted with sensors and fire extinguisher. The light and smoke sensor will detect fire and extinguisher will extinguish fire. In this paper we will discuss the development of android application that will control the robot. In this way we develop full fledge robot to perform fire fighting.

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Fire at high latitudes: Data-model comparisons and their consequences

Fire at high latitudes: Data-model comparisons and their consequences

ing the interannual variability of burned area to be consistent with data increases the interannual variability of NBP, but cli- mate variability remains the main factor determining its mag- nitude; and (iii) overall biomass values alter only slightly, but the spatial distribution of biomass exhibits changes. It must be stressed that these conclusions are derived using model es- timates of fi re emissions, which this study has demonstrated to be problematic; thus, they should not be considered robust un- til veri fi ed by measurements or by models with considerably improved representation of boreal fi re processes. We also demonstrate that it is crucial to alter the current representations of fi re occurrence and severity in land surface models if the links between permafrost and fi re are to be captured, in partic- ular, the dynamics of permafrost properties, such as active layer depth. This is especially important if models are to be used to predict the effects of a changing climate, because of the consequences of permafrost changes for greenhouse gas emissions, hydrology, and land cover.

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Sensitivity Analysis of a Fire Spread Model in a Chaparral Landscape

Sensitivity Analysis of a Fire Spread Model in a Chaparral Landscape

This study was also a conceptual validation of HFire, a spatially explicit model developed for predicting fire spread in chaparral fuels. The objective was to use SA techniques to quantitatively establish the way in which the output of HFire is dependent on the inputs of fuel and weather conditions. This analysis was framed in terms of predicting the size of fires during potential Santa Ana events, and the research hypothesis being tested was that wind speed accounts for more variability in simulated fire size than fuel-related variables such as fine dead fuel moisture and fuel model. The modeling framework introduced in this study could be extended by repeating the analysis under a wider range of conditions representative of the climatology of southern California, which would allow for a more complete characterization of the role that weather and fuels play in terms of the modern chaparral fire regime.

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Fire Protection for Facilities Engineering, Design, and Construction   MIL HDBK 1008C pdf

Fire Protection for Facilities Engineering, Design, and Construction MIL HDBK 1008C pdf

1.3 Criteria. This handbook implements the National Technology Transfer and Advancement Act, Public Law 104-113, March 7, 1996, Section 12 (d), identifying the necessary consensus technical standards required to implement policy objectives and activities within the area of fire protection engineering for the DOD. Compliance with criteria issued in accordance with this handbook does not constitute an exception under Public Law 104-113, March 7, 1996, Section 12 (d) (3). Fire protection criteria shall conform to the requirements of this handbook, the National Fire Codes, published by the National Fire Protection Association (NFPA), except as modified herein, and portions of the Uniform Building Code (UBC), published by the International Conference of Building Officials, as specifically referenced herein. Additional criteria includes portions of the Loss Prevention Data Sheets, published by Factory Mutual

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Gold deportment and geometallurgical recovery model for the La Colosa porphyry gold deposit, Columbia

Gold deportment and geometallurgical recovery model for the La Colosa porphyry gold deposit, Columbia

Cordillera of Colombia. It is unusual because it is gold rich and has low amounts of copper and trace molybdenum. The deposit consists of multiple intrusions of early, intermineral, and late porphyritic phases of diorites, dacite, and quartz diorites that have intruded into the schist and hornfels basement rock. The dominant alteration assemblage is potassic with weaker amounts of potassic-calcic and sodic calcic alteration. Gold-related veins include quartz- sulfide (A type) and sulfide (S and D type) veins. Geologic aspects of the deposit were used to create a general geologic model for gold mineralisation at La Colosa that was used to help create a recovery model.

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Internet of Things Technology  for Fire Monitoring System

Internet of Things Technology  for Fire Monitoring System

The new modern fire monitoring system is based on wireless sensor network in combination with Internet of Things. Because of modern advanced technology, the system minimize the losses due to fire. Sensors detects the fire condition and transfers the data to the system. Fire brigade and building owners can do the interactions with the system. All the data from the sensor nodes located in the buildings are provided to the users. The historical data reference from building data base server provides final useful response mechanisms. The users can communicate with the system through different ways to monitor and control the environment and get more information about it. The wireless fire fighting or monitoring system consists of the following units as shown in figure 1.

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Assessment and Validation of the Fire Brigade Intervention Model for use within New Zealand and Performance Based Fire Engineering

Assessment and Validation of the Fire Brigade Intervention Model for use within New Zealand and Performance Based Fire Engineering

The times from climbers carrying specific pieces of equipment were isolated from the majority of the climbers wearing only PPE and BA. These times were compared to investigate if the times could be distinguished from those not carrying any additional equipment and thus whether any specific hindrance factor could be established from this data. Nine climbers with and without BA have been specifically investigated, including the times of two climbers who only wore their PPE, did not wear BA or carry any additional equipment. Seven climbers carried either a 45 mm or 70 mm hose in bandolier fashion as shown in Figure 46. Although other equipment was carried by climbers, including an axe and a number of branches, this equipment was noted to be passed between climbers on their ascent, making isolation of specific individuals and the effect of this equipment on their time difficult to establish. This equipment is typical of that required to be carried by fire fighters as part of high-rise fire-fighting operations as shown in Figure 47; note that hoses can be carried either over the shoulder in a bandolier or coiled (Dutch rolled) in a back pack.

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Privatisation of the shipping industry in Vietnam : the benefit, problems and proposals

Privatisation of the shipping industry in Vietnam : the benefit, problems and proposals

The philosophies of ship fire protection have been primarily developed from passenger ship experience (Cowley, 1994). Until November 1952 when SOLAS 48 entered into force, there were no international fire regulations applicable to cargo ships. However, in SOLAS 29 several basic principles of structural fire protection had already been established. It required “fire resisting” bulkheads continuous form side-to-side of the ship spaced not more than 40 m in length. They were to be constructed of metal or other fire resisting material, effective to prevent for one hour. Escapes to the open deck were to be provided from passenger and crew spaces and, within machinery and working spaces, a means of escape independent of watertight doors was required.

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