Y. Namba’s scientific contributions

The several that many fires occurred simultaneously at the time of the Kobe earthquake in 1995 became urban area fires. Thereupon, we analyzed the fire spread situation of urban area fires of Kobe city in this research. We used the data that was obtained by Fire Department of Kobe city and Tokyo Fire Department. The fire data that we analyzed has over about 10,000 m² of burn-out area. It is as a future research theme about the fire spread condition which fire fighting water is considered. The fire spread model that considered bum-out area, fire front length and also the fire spread speed, were examined in this paper. The several that many fires occurred simultaneously at the time of the Kobe earthquake in 1995 became urban area fires. Thereupon, we analyzed the fire spread situation of urban area fires of Kobe city in this research. We used the data that was obtained by Fire Department of Kobe city and Tokyo Fire Department. The fire data that we analyzed has over about 10,000 m² of burn-out area. It is as a future research theme about the fire spread condition which fire fighting water is considered. The fire spread model that considered bum-out area, fire front length and also the fire spread speed, were examined in this paper.

The quantitative ratio of buliding fire is relatively high in Japan and especially the number of deaths in fire of house shows a increasing tendency lately. On the other hand, there are some studies on the forecast of seismic fire for urban conflagration risk but there are very few cases of the forecast of ordinary fire. And a lot of fire and deaths break out every year. Then it is important to study on forecast of ordinary building fire. This is the basic study for fire fighting planning and we are trying to analyze statistically the better forecast model by using data to be obtained easily. The number of fire is assumed to be a function of one or more independent variables. So the method of this study is first to classify the independent veriables into small group according to urban characteristics by using Factor Analysis, secondly to find the best model by Multi-regression Analysis. Judging of the model adaptation is mainly used AIC, i.e Akaike’s Information Criteria (Akaike, 1977), which is better evaluation method in the recent statistics. Four factors were drawed for urban characteristics data by Factor Analysis. But one of them is not connected with the cause of fire. Then the data were classified into three groups, i.e. commercial district, manufacting one and residential one, according to land use ratio. Population and quantity of consumed water were selected from activity one. By considering these three factors, six models were made and examined. Then it was showed that {model 3 | population, quantity of consumed water} and {model 6 | household, quantity of consumed water} are adapted by Multi-regression Analysis and AIC from six models. Because population and household selected from life gorup and quantity of consumed water selected from activity one are able to obtain easily, it is seemed that these models can be analyzed and used in the other cities and towns. © 1994, The Society of Fiber Science and Technology, Japan. All rights reserved.