Ignition of single coal particle in a hot furnace under normal- and micro-gravity condition

An experimental study on ignition and combustion of single particles was conducted at normal gravity (1-g) and microgravity (l-g) for three high volatile coals with initial diameter of 1.5 and 2.0 mm, respectively. The non-intrusive twin-color pyrometry method was used to retrieve the surface temperature of the coal particle through processing the images taken by a color CCD camera. At the same time, a mathematical model considering thermal conduction inside the coal particle was developed to simulate the ignition process. Both experiments and modeling found that ignition occurred homogeneously at the beginning and then heterogeneously for the testing coal particles burning at l-g. Experimental results confirmed that ignition temperature decreased with increasing volatile content and increasing particle size. However, contradicted to previous studies, this study found that for a given coal with certain particle size, ignition temperature was about 50–80 K lower at l-g than that at 1-g. The model predictions agreed well with the l-g experimental data on ignition temperature. The criterion that the temperature gradient in the space away from the particle surface equaled to zero was validated to determine the commence of homogeneous ignition. Thermal conduction inside the particle could have a noticeable effect for determining the ignition temperature. With the consideration of thermal conduction, the critical size for the phase transient from homogeneous to heterogeneous is about 700 lm at ambient temperature 1500 K and oxygen concentration 0.23. 2009 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

地理信息系统支持下的滑坡灾害空间分析预测-以云南小江流域为例

As a typical geological and environmental hazard, landslide has been causing more and more property and life losses. However, to predict its accurate occurring time is very difficult or even impossible due to landslide's complex nature. It has been realized that it is not a good solution to spend a lot of money to treat with and prevent landslide. The research trend is to study landslide's spatial distribution and predict its potential hazard zone under certain region and certain conditions. GIS(Geographical Information System) is a power tools for data management, spatial analysis based on reasonable spatial models and visualization. It is new and potential study field to do landslide hazard analysis and prediction based on GIS. This paper systematically studies the theory and methods for GIS based landslide hazard analysis. On the basis of project "Mountainous hazard study-landslide and debris flows" supported by Chinese Academy of Sciences and the former study foundation, this paper carries out model research, application, verification and model result analysis. The occurrence of landslide has its triggering factors. Landslide has its special landform and topographical feature which can be identify from field work and remote sensing image (aerial photo). Historical record of landslide is the key to predict the future behaviors of landslide. These are bases for landslide spatial data base construction. Based on the plenty of literatures reviews, the concept framework of model integration and unit combinations is formed. Two types of model, CF multiple regression model and landslide stability and hydrological distribution coupled model are bought forward. CF multiple regression model comes form statistics and possibility theory based on data. Data itself contains the uncertainty and random nature of landslide hazard, so it can be seen as a good method to study and understand landslide's complex feature and mechanics. CF multiple regression model integrates CF (landslide Certainty Factor) and multiple regression prediction model. CF can easily treat with the problems of data quantifying and combination of heteroecious data types. The combination of CF can assist to determine key landslide triggering factors which are then inputted into multiple regression model. CF regression model can provide better prediction results than traditional model. The process of landslide can be described and modeled by suitable physical and mechanical model. Landslide stability and hydrological distribution coupled model is such a physical deterministic model that can be easily used for landslide hazard analysis and prediction. It couples the general limit equilibrium method and hydrological distribution model based on DEM, and can be used as a effective approach to predict the occurrence of landslide under different precipitation conditions as well as landslide mechanics research. It can not only explain pre-existed landslides, but also predict the potential hazard region with environmental conditions changes. Finally, this paper carries out landslide hazard analysis and prediction in Yunnan Xiaojiang watershed, including landslide hazard sensitivity analysis and regression prediction model based on selected key factors, determining the relationship between landslide occurrence possibility and triggering factors. The result of landslide hazard analysis and prediction by coupled model is discussed in details. On the basis of model verification and validation, the modeling results are showing high accuracy and good applying potential in landslide research.