• The Korean Journal of Ecology
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• v.24 no.4
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• pp.227-232
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• 2001

The biomass structure for three major components viz., the dominant grass, Chrysopogon zeylanicus Thw., the 'other grasses' and the'remaining species'and dry matter dynamics for total community were studied over a period of one year in an annual fire influenced subtropical humid grassland community in Western Ghats, India. The biomass of aboveground, belowground and litter compartments were high as in other humid grasslands and generally have positive correlation with rainfall, rainy days and relative humidity with the exception of litter parts. The above and belowground net primary productions (4,561 and 722 g/㎡, respectively) were also higher and were comparable with other humid tropical grasslands. The turnover of organic matter was rapid, Of the total input of 14.47 g/㎡ into the system, about 86.3% was allocated to above ground parts and 13.7% to below ground parts. The total disappearance was 2.56 g/㎡ and it was accounted to be 17.68% of the total output. The net surplus of dry matter (82.32%) in the post fire community indicates that the grassland was maintained in a seral stage. Hence it is suggested that prescribed burning may keep this ecosystem in a highly productive and seral stage.

• Journal of Ecology and Environment
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• v.38 no.3
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• pp.281-291
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• 2015

To clarify the effects of forest fire on the carbon budget of a forest ecosystem, this study compared the seasonal variation of soil respiration, net primary production and net ecosystem production (NEP) over the year in unburned and burned Pinus densiflora forest areas. The annual net carbon storage (i.e., NPP) was $5.75t\;C\;ha^{-1}$ in the unburned site and $2.14t\;C\;ha^{-1}$ in the burned site in 2012. The temperature sensitivity of soil respiration (i.e., $Q_{10}$ value) was higher in the unburned site than in the burned site. The annual soil respiration rate was estimated by the exponential regression equation with the soil temperatures continuously measured at the soil depth of 10 cm. The estimated annual soil respiration and heterotrophic respiration (HR) rates were 8.66 and $4.50t\;C\;ha^{-1}yr^{-1}$ in the unburned site and 4.08 and $2.12t\;C\;ha^{-1}yr^{-1}$ in the burned site, respectively. The estimated annual NEP in the unburned and burned forest areas was found to be 1.25 and $0.02t\;C\;ha^{-1}yr^{-1}$, respectively. Our results indicate that the differences of carbon budget and cycling between both study sites are considerably correlated with the losses of living plant biomass, insufficient nutrients and low organic materials in the forest soil due to severe damages caused by the forest fire. The burned Pinus densiflora forest area requires at least 50 years to attain the natural conditions of the forest ecosystem prior to the forest fire.

• Fire Protection Technology
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• s.11
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• pp.23-30
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• 1991

For the prevent of fire accident or explosion disasters from inflammable gas and vapour, flame arresters are used in chemical equipment, oil tank or other similar installation. The flame arresters have been used mainly wire gauze type. Wire gauze type flame arrestes is affected several factors. We have know that the quenching ability has a great of difference the preference in accordance with flame velocity, direction of flame propagation and wire net of mesh and number of qauze and introduce examination result data quoated from the abroad.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2006.06a
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• pp.155-156
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• 2006

Developed and conducted a performance test of the Water mist system that is satisfied with the requirement of a fire test requiring Class 3 Engine Mock-up exceeding net volume $3,000m^3$ as per IMO's MSC/Circ. 668 Appendix B(Test method for fire testing equivalent water-based fire-extinguishing systems for machinery spaces of category A and cargo pump rooms).Even though fuel atomizing was continued for 15 sec. after stopping of the system according to the test method relating to the atomizing fire type, no fire was reignited. This result shows the excellence of the system. There was no damage to the contents of the system after the test.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.979-995
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• 2023

As wildfires are difficult to predict, real-time monitoring is crucial for a timely response. Geostationary satellite images are very useful for active fire detection because they can monitor a vast area with high temporal resolution (e.g., 2 min). Existing satellite-based active fire detection algorithms detect thermal outliers using threshold values based on the statistical analysis of brightness temperature. However, the difficulty in establishing suitable thresholds for such threshold-based methods hinders their ability to detect fires with low intensity and achieve generalized performance. In light of these challenges, machine learning has emerged as a potential-solution. Until now, relatively simple techniques such as random forest, Vanilla convolutional neural network (CNN), and U-net have been applied for active fire detection. Therefore, this study proposed an active fire detection algorithm using state-of-the-art (SOTA) deep learning techniques using data from the Advanced Himawari Imager and evaluated it over East Asia and Australia. The SOTA model was developed by applying EfficientNet and lion optimizer, and the results were compared with the model using the Vanilla CNN structure. EfficientNet outperformed CNN with F1-scores of 0.88 and 0.83 in East Asia and Australia, respectively. The performance was better after using weighted loss, equal sampling, and image augmentation techniques to fix data imbalance issues compared to before the techniques were used, resulting in F1-scores of 0.92 in East Asia and 0.84 in Australia. It is anticipated that timely responses facilitated by the SOTA deep learning-based approach for active fire detection will effectively mitigate the damage caused by wildfires.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.4
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• pp.99-115
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• 2005

For an analysis of the performance of a computer system, the minimum cycle time method has been widely used. The minimum cycle time method is a mathematical technique with which we can find the minimum duration time needed to fire all the transitions at least once and coming back to the Initial marking in a timed net. A timed net is a modified version of a Petri net where a transition is associated with a delay time. In the real world, an event is associated with a probability of occurrence. However, a timed net is not equipped with any facility of specifying probability of event occurrence. Therefore, the minimum cycle time method applied on a timed net can easily overlook probabilities of occurrences of events and yield a wrong result. We are proposing 'Timed Net with Probabilities of Choices' where a transition can be associated with both delay time and a probability of occurrence. We also introduce an algorithm for minimum cycle time analysis on a 'Timed Net with Probabilities of Choices'. As an example of application, we are performing an analysis of the location based service system using 'Timed Net with Probabilities of Choices'.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.2941-2959
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• 2022

The fire brigade non-suppression probability model is a major factor that should be considered in evaluating fire-induced risk through fire probabilistic risk assessment (PRA), and also uncertainty is a critical consideration in support of risk-informed performance-based (RIPB) fire protection decision-making. This study developed an optimal integrated probabilistic fire brigade non-suppression model considering uncertainty of parameters based on the Bayesian Markov Chain Monte Carlo (MCMC) approach on electrical fire which is one of the most risk significant contributors. The result shows that the log-normal probability model with a location parameter (µ) of 2.063 and a scale parameter (σ) of 1.879 is best fitting to the actual fire experience data. It gives optimal model adequacy performance with Bayesian information criterion (BIC) of -1601.766, residual sum of squares (RSS) of 2.51E-04, and mean squared error (MSE) of 2.08E-06. This optimal log-normal model shows the better performance of the model adequacy than the exponential probability model suggested in the current fire PRA methodology, with a decrease of 17.3% in BIC, 85.3% in RSS, and 85.3% in MSE. The outcomes of this study are expected to contribute to the improvement and securement of fire PRA realism in the support of decision-making for RIPB fire protection programs.

• Nuclear Engineering and Technology
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• v.45 no.2
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• pp.223-236
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• 2013

In the present study the behavior of fire and the residual strength of fire-ignited RC slabs are investigated by experimental tests and numerical simulations. The fire tests of RC slabs were carried out in a furnace using the ISO 834 standard fire. The load capacity of the cooled RC slabs that were not loaded during the fire tests was evaluated by additional 3 point bending tests. The influence of the proportion of PP (polypropylene) fibers in the RC slabs on the structural behavior of the RC slabs after the fire loading was investigated. The results of the fire tests showed that the maximum temperature of concrete with PP fiber was lower than that of concrete without PP fiber. As the concrete was heated, the ultimate compressive strength decreased and the ultimate strain increased. The load-deflection relations of RC slabs after fire loading were compared by using existing stress-strain-temperature models. The comparison between the numerical analysis and the experimental tests showed that some numerical analyses were reliable and therefore, can be applied to evaluate the ultimate load of RC slabs after fire loading. The ultimate load capacity after cooling down the RC slabs without PP fiber showed a considerable reduction from that of the RC slabs with PP fiber.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1273-1283
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• 2022

Recently, forest fires have frequently occurred due to climate change, leading to human and property damage every year. The forest fire monitoring technique using remote sensing can obtain quick and large-scale information of fire-damaged areas. In this study, the Gangneung and Donghae forest fires that occurred in March 2022 were analyzed using the spectral band of Sentinel-2, the normalized difference vegetation index (NDVI), and the normalized difference water index (NDWI) to classify the affected areas of forest fires. The U-net based convolutional neural networks (CNNs) model was simulated for the fire-damaged areas. The accuracy of forest fire classification in Donghae and Gangneung classification was high at 97.3% (f₁=0.486, IoU=0.946). The same model used in Donghae and Gangneung was applied to Uljin and Samcheok areas to get rid of the possibility of overfitting often happen in machine learning. As a result, the portion of overlap with the forest fire damage area reported by the National Institute of Forest Science (NIFoS) was 74.4%, confirming a high level of accuracy even considering the uncertainty of the model. This study suggests that it is possible to quantitatively evaluate the classification of forest fire-damaged area using a spectral band and indices similar to that of the Compact Advanced Satellite 500 (CAS500-4) in the Sentinel-2.

• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1571-1584
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• 2023

In this study, a numerical analysis was performed as part of an international joint research project to reproduce a real cable tray fire that occurred in the heater bay area of the turbine building of a nuclear power plant. A sensitivity analysis was performed on various input parameters to derive results consistent with the sprinkler activation time obtained from the fire event analysis. For all sensitive parameters, the normalized sprinkler activation time correlated well with the power function of the normalized sprinkler height. A correlation equation was developed to identify the sprinkler activation time at any location when determining the slope or fire growth rate under the conditions assuming a linear or t-squared heat release rate (HRR) time curve. Various cable fire growth assumptions were used to determine which assumption was better to provide the prediction coincident with the information given from the fire event analysis in terms of the sprinkler activation time and total energy generated from cables damaged by fire. In the comprehensive analysis of all the sensitive parameters, the standard deviation of the input parameters increased as the sprinkler height decreased. Within the range of the sensitivity parameter values given in this study, when considering all sprinkler heights, the standard deviation of the cable model change was the largest and that of the overhang position change was the smallest.