The use of wood poses a significant threat to human safety and property preservation in the event of a fire. In this study, the fire risk of wood was evaluated using Chung's equation-IV and Chung's equation-XII. The test subjects were selected as building materials such as larch, Russian ash, cherry, and camphor and performed using the cone calorimeter according to ISO 5660-1.The test subjects were selected as building materials such as larch, Russian ash, cherry, and camphor and the experiment was conducted using a cone calorimeter according to ISO 5660-1. The evaluation results by fire risk index-IV (FRI-IV) and fire risk index-XII (FRI-XII) were compared. According to the FRI-IV, the larch (0.01) was described as the wood with the lowest fire risk, and polymethylmethacrylate (PMMA) (1.00) was evaluated as the wood with the highest fire risk. However, according to the fire risk index-XII, the fire risk was evaluated as the lowest for larch (0.07) as grade A and the highest for Russian ash (4.10) as grade F. Therefore, the fire risk evaluation by Chung's equation-XII is explained as a useful method to comprehensively evaluate the prediction of the fire risk of combustion targets.

Natural materials, including wood, are becoming increasingly important for fire safety along with eco-friendly living. The fire risks of combustible materials were comprehensively reviewed using Chung's equation-XII and the newly proposed Chung's equation-XV. As a case study, the fire characteristics of five wood specimens were evaluated using a cone calorimeter according to the ISO 5660-1 standard. The external heat flux was set to 50 kW/m(2). The relative rankings based on the fire risk index-XII (FRI-XII) were as follows: zelkova (0): ranking 6 < oak (0.02): ranking 5 < pine rigida (0.09): ranking 4 < chestnut (0.19): ranking 3 < polymethylmethacrylate (PMMA) (1): ranking 2 < lauan (4.69): ranking 1. The relative rankings based on the fire risk index-XV (FRI-XV) were as follows: zelkova (0.00): ranking 3 approximate to oak (0.00): ranking 3 approximate to pine rigida (0.00): ranking 3 approximate to chestnut (0.00): ranking 3 < lauan (0.03): ranking 2 < PMMA (1): ranking 1. However, the results based on the fire risk index-XV (FRI-XV) did not provide discrimination between test specimens. Therefore, it was found that there is a need to comprehensively evaluate the fire risk, including the ratio of mean carbon monoxide production rate (COPmean, g/s) to mean carbon dioxide production rate (CO2Pmean, g/s), as in the evaluation of FRI-XII.

The thermal decomposition process of combustible materials is known to be a complex combination of thermal, chemical, and mechanical reactions. In this study, the fire risk of combustible materials was evaluated using both the fire risk index-XII (A) and the newly proposed fire risk index-XII (B) based on Chung's equation-XII. As a case study, the combustion characteristics of five wood species were tested using a cone calorimeter according to ISO 5660-1. The experiment was conducted at an external heat flux of 50 kW/m2. As a result of the examination, according to (A), the fire risk ranking was lowest for zelkova (0.00) and highest for lauan (4.69). Also, according to (B), the ranking was lowest for zelkova (0.00) and highest for lauan (5.142). In other words, it appears that the first maximum heat release rate and first maximum smoke generation rate based on the instantaneous maximum values had a significant influence on (A), and the time-averaged and mass-based maximum average rate of heat emission and smoke extinction area had a significant influence on (B), respectively. In conclusion, the fire risk index-XII (A) and the newly proposed fire risk index-XII (B) can be applied as a useful method for comprehensively predicting and evaluating the fire safety of combustible materials.

The fire risk prediction and fire risk rating of wood were comprehensively evaluated using Chung's Equation-XII. The Japanese cedar, spruce, lauan, and red pine were selected as the test specimens. The combustion test on the specimen was performed using a cone calorimeter according to the ISO 5660-1 standard. After combustion, the fire performance index-XI (FPI-XI) by Chung's equations-XI ranged from 0.34 to 1.26, and the fire growth index-XI (FGI-XI) ranged from 0.78 to 2.78. The newly proposed fire risk rankings (FRR) for the calculated Fire Risk Index-XII (FRI-XII) by Chung's equation-XII increased in the following order: spruce (0.60): grade A approximate to polymethylmethacrylate (PMMA) (1): grade A < red pine (1.10): grade B < Japanese cedar (4.17): grade G approximate to laun (8.18): grade G. In conclusion, the materials with low moisture content and high COPmean/CO2Pmean have lower fire performance index-XI, and the materials with long accumulated smoke generation time (ASGT) and low COPmean/CO2Pmean have lower fire growth index-XI. In other words, as the fire performance index-XI increases and the fire growth index-XI decreases, the fire risk index-XII decreases.

In this study, the fire risk assessment method for wood specimens is demonstrated using Chung's equations-VII, Chung's equations-VIII, and Chung's equation-IX. As an example, the fire properties were tested using a cone calorimeter according to the ISO 5660-1 standard by selecting wood specimens coated with flame retardants. The external heat flux was 50 kW/m(2). The fire performance index-VII (FPI-VII) is defined as the ignition time (TTI, s) divided by the product of the peak smoke release rate (SPRpeak, m(2)/s), the peak heat release rate (PHRR, kW/m(2)), and the CO/CO2 mean rate ratio (COPmean (g/s) / CO2Pmean (g/s)). Considering the importance of the early stage of fire, the first peak smoke release rate and the first peak heat release rate were applied. The Fire Growth Index-VII (FGI-VII) is defined as the product of the maximum smoke release rate (m(2)/s), the maximum heat release rate (kW/m(2)), and the CO/CO2 mean production ratio (COPmean (g/s) /CO2Pmean (g/s)) divided by the time to reach the maximum smoke production rate. The first maximum values of SPR and PHRR were chosen to assess the risk in the early stage of fire. The comprehensive fire risk assessment was conducted using the fire risk index-IX (FRI-IX), which is obtained by dividing the fire growth index-VIII (FGI-VIII) by the fire performance index-VIII (FPI-VIII).

The fire risk and fire safety of four types of wood were comprehensively evaluated according to Chung's equation-XII. White ash, willow, fraxinus mandshurica, and sagent cherry trees were selected as test specimens. A cone calorimetery (ISO 5660-1) was used to examine the combustion characteristics of the test piece, and finally, the fire risk rating (FRR) was predicted using the fire risk index-XII (FRI-XII). The predicted fire performance index-X (FPI-X) and fire growth index-X (FGI-X) ranged from 469.03 to 1109.73 s(2)/kW and 0.0009 to 0.0280 kW/s(2), respectively. Additionally, the fire performance index-XI (FPI-XI) and fire growth index-XI (FGI-XI) ranged from 0.41 to 0.97 and 1.11 to 3.11, respectively. The fire risk index-XII (FRI-XII), representing a fire risk rating, showed that the fire risk of frasxinus mandsurica tree (FM) was very high at 7.60 (fire risk rating: D). And it was compared with Chung's equation-IX, fire risk index-IX (FRI-IX). The fire risk ratings according to FRI-IX and FRI-XII were generally high for willow and frasxinus mandsurica trees. Additionally, the results of FRI-XII and FRI-IX had a similar relationship, and the size of each fire safety rating closely matched each other.

Thermochromic and hydrochromic (H) materials were selected to develop a self-sensitive mixture that visually illustrates black ice formation. A 200 mu m thick film was prepared to evaluate the thermochromic performance. The freezing visualization materials showed a rapid discoloration response time of 10 s. R0H, a 0 degrees C sensitive material combined with a weight ratio of red color and hydrochromic material (1:8), showed an excellent rating response of 19 seconds. As exposure to moisture increased, the color recovery rate was a maximum of 4.8 times slower than under dry freezing conditions. The color difference performance of the freezing visualization material was up to 31.18 with R0H (1:8) when dry freezing conditions were changed to moisture freezing conditions. When combined with moisture, and the moisture-freezing conditions were formed, the color of the frozen area was darker than the surrounding color and had high visibility. The samples had excellent temperature sensing performance and showed clear color conversion in response to moisture.

The fire risk rating assessment of wood was evaluated using fire performance index-VIII, fire growth index-VIII, and fire risk index-IX from previously described Chung's equations. The burning properties of the materials was measured using a cone calorimeter (ISO 5660-1). SnO, SnO2, FeO and Fe2O3 were used as the metal oxides, and sodium silicate was mixed to increase the flame-retardant effect. The fire performance index-VIII was 15.5-139.3 times higher than the uncoated specimen. The fire growth index-VIII was 12-71 times lower than the uncoated specimen. The fire risk index-IX of the coated specimens was 239-9861 times lower than the uncoated specimens. SnOSS was the lowest risk material according to the fire risk rating FRI-IX. A lower oxidation state was a safer material for an initial fire than a higher oxidation state. All specimens showed an improved fire risk compared to uncoated specimens.

This study evaluated the fire risk of building materials by calculating the fire risk index-IX (FRI-IX) and fire risk rating (FRR) according to Chung's equations-VII, Chung's equations-VIII, and Chung's equation-IX. White ash, hard maple, willow, fraxinus mandschurica, Sargent cherry, and polymethylmethacrylate (PMMA) were selected as specimens. The combustion characteristics of the specimens were tested via cone calorimetry according to ISO 5660-1. After combustion, the fire performance index-VII (FPI-VII) of the specimens, as calculated by Chung's equations, varied between 23.51 and 87.84 s2/kW, and the fire growth index-VII (FGI-VII) varied between 0.0025 and 0.0170 kW/s2. The fire performance index-VIII (FPI-VIII) and fire growth index-VIII (FGI-VIII) based on polymethylmethacrylate (PMMA) varied between 0.44 and 1.66, and between 3.13 and 21.25, respectively. The fire risk index-IX (FRI-IX), which is the fire risk rating, showed that willow had a very high fire risk, with an FRI-IX value of 48.30 (fire risk rating: G). Materials with fast time to ignition (TTI), short time to reach 1st_peak smoke production rate (TSPR1st_peak), and high (CO/CO2) mean production rate ratio (COPmean/CO2Pmean) values owing to low volume density had low FPI-VII and FPI-VIII, and high FGI-VII and FGI-VIII, resulting in high FRI-IX values.

Chung's equations-X, -XII, and -XII were applied to evaluate the fire risk index (FRI) and fire risk rating (FRR) of five wood species. The test specimens used were ginkgo tree, dawn redwood tree, toona tree, lime tree, and walnut tree. A cone calorimeter (ISO 5660-1) was selected and used to test the combustion characteristics of the specimens. The fire performance index-X (FPI-X) and fire growth index-X (FGI-X) calculated using Chung’s equations ranged from 560.59 to 2689.89 s2/kW and from 0.0005 to 0.0016 kW/s2, respectively. Furthermore, the FPI-XI and FGI-XI varied from 0.49 to 2.35 and from 1.67 to 5.33, respectively. FRI-XII, a FRR, showed that the fire risks of dawn redwood tree and ginkgo tree, at 10.88 (FRR: F) and 10.25 (FRR: F), respectively, were very high. In conclusion, a high FRI-XII value indicates that FPI-X and FPI-XI are low whereas FGI-X and FGI-XI are high.

Metal oxides were applied to cypress wood typically used as an interior building material. Combustion characteristics were evaluated focusing on the oxidation state of metal ions and char characteristics of the second stage of combustion. The burning properties of the materials were measured using a cone calorimeter (ISO 5660-1). The external heat flux was fixed at 50 kW/m 2 . FeO, Fe 2 O 3 , SnO and SnO 2 were used as the metal oxides, and sodium silicate was mixed with increasing the flame-retardant effect. SnO 2 SS was 1.05 times lower than the 164.76 kW/m 2 of the uncoated specimen. The other specimens increased 1.03–1.09 times. The peak smoke production rate of the wood specimens coated with flame retardant was 1.2–1.6 times lower than the uncoated specimens. SnO 2 SS had the lowest value and showed a synergetic effect with SS. The CO/CO 2 ratio of the test specimens coated with the silicate compound was 1.6–2.3 times lower than that of the uncoated specimen. In SnO 2 SS, HRR 2nd_peak and SPR 2nd_peak decreased because the generated heat was dispersed by convection because of pores in the char. This formed a relatively hard and heat-stable char structure.

The evaluation of fire risk for combustible materials was carried out using Chung's equations-X, Chung's equations-XI, and Chung's equation-XII, which were newly established. The fire risk index-XII (FRI-XII) and fire risk rating (FRR) were calculated for specimens including camphor tree, cherry, rubber tree, and elm. The combustion characteristics were determined using a cone calorimeter according to ISO 5660-1. Chung's equations caculated the fire performance index-X (FPI-X) and fire growth index-X (FGI-X) values ranged from 89.34 to 1696.75 s2/kW and from 0.0006 to 0.0107 kW/s2, respectively. In addition, the fire performance index-XI (FPI-XI) and fire growth index-XI (FGI-XI) varied from 0.08 to 1.48 and from 0.67 to 11.89, respectively. The fire risk index-XII (FRI-XII), which is an indicator of fire risk, showed that camphor tree had a value of 148.63 (fire risk rating: G), indicating a very high fire risk. This suggests that combustible materials with a high concentration of volatile organic compounds have lower FPI-X and FPI-XI values, higher FGI-X and FGI-XI values, and consequently higher FRI-XII values, indicating an increased fire risk.

Chung's equations-II, -III, and -IV were applied to evaluate the fire risk and fire risk ratings of flame retardants. As an example, a wood specimen coated with a flame retardant was selected and tested using a cone calorimeter according to the ISO 5660-1 standard. The external heat flux was fixed to 50 kW/m2. Fire performance index-III used three variables to evaluate the initial fire risk: the time to ignition, first peak heat release rate, and first peak smoke release rate. Fire growth index-III was calculated using the first peak heat release rate, peak smoke production rate, and time to reach the first peak smoke production rate. This index is a standardized fire hazard category with poly(methyl methacrylate) as the reference material. The fire risk rating index, fire risk index-IV, is expressed as the value obtained by dividing the fire growth index-III by fire performance index-III. In this study, the methodology for fire risk rating evaluation is discussed.

Titanium dioxide/talc/water glass mixtures were applied to cypress wood typically used as an interior building material. Cypress is in the spotlight for its water repellency, light weight, and phytoncide release to improve health. The fire performance was investigated in terms of fire performance index-III, fire growth index-III, and fire risk index-IV culminating in a fire risk rating assessment using Chung’s equations. The fire performance was measured using a cone calorimeter (ISO 5660-1). The external heat flux was fixed at 50 kW/m2. Titanium dioxide was used as the metal oxide, and mixed with talc to increase the flame retardant effect. Titanium dioxide was differentiated into rutile and anatase because of their different structure. The fire performance index-III measured after combustion was 3.2–12.0 times higher than that of the uncoated specimen. The fire growth index-III was 2.9–36.4 times lower than that of the uncoated specimen and the fire risk index-IV of the coated specimens was 9.5–302.9 times lower than that of the uncoated specimens. Talc/water glass (TSS) and water glass (SS) were the safest materials using the fire risk rating FRI-IV. Rutile TiO2 had a lower fire risk rating than anatase form. The CO concentration of the coated specimens was about 69–120 ppm and it was 1.2–2.1 times lower than the 147 ppm of the uncoated specimens.

In this study, the fire risk index of different wood species used in construction was calculated using Chung's equations-II, Chung's equations-III, and Chung's equation-IV. The test specimens were from larch, Russian ash, sapele, and camphor tree. Their fire characteristics were evaluated using a cone calorimeter according to ISO 5660-1. After combustion, the fire performance index-II (FPI-II) of the specimens, as calculated by Chung's equations, varied between 1.56 and 8.12 s2/kW, and the fire growth index-II (FGI-II) varied between 0.03 and 0.23 kW/s2. The fire performance index-III (FPI-III) based on polymethylmetacrylate varied between 5.27 and 27.36, and the fire growth index-III (FGI-III) varied between 0.20 and 1.58. The fire risk index-IV (FRI-IV), which is the fire risk grade, showed that Russian ash and camphor tree have a high fire risk, with FRI-IV values of 0.27 and 0.30, respectively. Therefore, wood species that contain volatile compounds or have a low bulk density have a high FRI-IV value owing to decreased FPI-II and FPI-III and increased FGI-II and FGI-III.

In this study, Chung's equations 1, 2, and 3 were extended to standardize smoke safety rating evaluation in case of fire, and Chung's equations-V, smoke performance index-V, and smoke growth index-V were calculated. Five types of wood were selected and their smoke indices were measured using the cone calorimeter method according to ISO 5660-1. The smoke risk was graded by the smoke risk index-VI according to Chung's equation-VI. Smoke risk index-VI increased in the order of PMMA (1) approximate to maple (1.01) < ash (1.57) < needle fir (4.98) < paulownia (46.15) < western red cedar (106.26). It was predicted that maple and ash had the lowest smoke risk, and paulownia and western red cedar had the highest. The five samples' CO mean production rate (COPmean) was 0.0009-0.0024 g/s, indicating that these woods were incompletely burned than the polymethyl methacrylate (PMMA) reference material. Regarding the smoke properties of the chosen woods, the smoke performance index-V (SPI-V) increased as the bulk density increased, and the smoke risk index-VI (SRI-VI) decreased.

This study aims to assess the smoke hazard of wood materials, focusing on smoke performance index (SPI), smoke growth index (SGI), and smoke intensity (SI). The species used are Japanese cedar, spruce, lauan, and red pine. The smoke characteristics were investigated using a cone calorimeter (ISO 5660-1) on the specimen wood. The radiant heat was fixed at an external heat flux of 50 kW/m2. The SPI measured after the combustion reaction of each wood increased by 1.27 to 2.21 times compared with that of Japanese cedar. The fire risk due to the SPI increased in the order of spruce, lauan, red pine, and Japanese cedar. The SGI of each wood increased by 1.19 to 1.78 times compared to that of spruce. The risk of fire caused by the SGI increased in the order of spruce, Japanese cedar, lauan, and red pine. The SI of each wood increased by 1.11 to 1.99 times compared to that of spruce. The COmean production rate ranged from 0.00128 to 0.00310 g/s, and the second peak oxygen depletion concentration was much higher than the level of 15%, which can be fatal to humans and the resulting risk could thus be eliminated.

In this study, fire risk was evaluated using Chung's equations-II, Chung's equations-III, and Chung's equation-IV to predict the fire risk and grade of wood for construction materials. Spruce wood, Rigida pine, Lauan, Chestnut, Oak, and Zelkova wood were used as test pieces. The fire characteristics of the test pieces were investigated using a cone calorimeter (ISO 5660-1) equipment. After combustion of the specimen, FPI-II measured by Chung's equations was 1.36 to 113.49 s2/kW, and FGI-II was 0.01 to 0.29 kW/s2. FPI-III was 4.53~378.30 based on polymethylmethacrylate (PMMA), and FGI-III was 0.07~1.93 based on PMMA. The fire risk index-IV, which is a fire risk rating index, was 0.33 and 0.43 for Spruce and Lauan, respectively, indicating that they are woods with relatively high fire risk.

In this study, smoke performance index-V and smoke growth index-V were calculated to expand Chung's equations 1, 2, and 3 and to standardize smoke hazard rating evaluation in case of fire. For this purpose, six types of wood were selected and measured by the cone calorimeter method according to ISO 5660-1. Also, overall, smoke risk was graded by smoke risk index-VI according to Chung's equation-VI. As a results, smoke hazard index-VI was found in the order of oyster oak (0.03) ≈ chestnut (0.04) ≈ zelkova (0.08) < PMMA (1.00) < pitch pine (3.13) < spruce (10.08) < lauan (11.65). Therefore, it was predicted that oyster oak, chestnut, and zelkova had the lowest smoke risk, and lauan had the highest. However, the average concentration of carbon monoxide in the specimen is 53-142 ppm, which is higher than the OSHA limit (PEL), it is concerned that it will harm health.