Devidas S. Nimaje

Work place: Department of Mining Engineering, National Institute of Technology, Rourkela, Odisha, India



Research Interests: Data Structures and Algorithms, Data Mining, Autonomic Computing


Devidas S. Nimaje (1974) served as Assistant Professor in Department of Mining Engineering, National Institute of Technology, Rourkela since 1999. He did his B.E. (Mining) from RKNEC Nagpur; M.Tech. (Mining) from IIT, Khragpur, PGDCA from CMC, Hyderabad. His current areas of research are Coal mine fire, Computer application in mining, Mine environment and soft computing. He has more than 12 research articles in reputed National and International Journals and Conferences etc. He has visited Czech Republic under TEQIP program. He is a member of IE (I) and other prestigious professional societies like ISTE.

Author Articles
Development of Regression Models for Assessing Fire Risk of Some Indian Coals

By Devidas S. Nimaje D.P. Tripathy Santosh Kumar Nanda

DOI:, Pub. Date: 8 Jan. 2013

Spontaneous combustion of coals leading to mine fires is a major problem in Indian coal mines that creates serious safety and mining risk. A number of experimental techniques based on petrological, thermal and oxygen avidity studies have been used for assessing the spontaneous heating liability of coals all over the world. Crossing point temperature (CPT) is one of the most common methods in India to assess the fire risk of coal so that appropriate strategies and effective action plans could be made in advance to prevent occurrence and spread of fire and hence minimize coal loss. In this paper, the spontaneous heating risks of some of the Indian coals covering few major coalfields were assessed using CPT apparatus. Statistical analysis was carried out between CPT and the proximate analysis parameters and it was found that the Mixture Surface Regression (MSR) model was more effective and gave very good residual values as compared to the polynomial and simple multiple regression models. The performance of Anderson-Darling testing was done between the prediction results of MSR model and measured value of CPT showed that the residual follows normal distribution hence justifies the suitability of model for the prediction of spontaneous heating liability of coal.

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