TGA/DSC study to characterise and classify coal seams conforming to susceptibility towards spontaneous combustion

Thermogravimetric analysis/differential scanning calorimeter (TGA/DSC) technique along with basic coal characteristics study is carried out for eighty coal samples of Indian coalfields, to determine spontaneous combustion propensity behaviour of coal. TGA study of coal samples indicates that there is an increase in the mass of coal samples in the temperature range 150–350 ℃, which may be due to oxygen adsorption and absorption. The correlation and principal component analysis states that the component of proximate analysis (Mad, VMd, FR, and VR) have an acceptable correlation with the TGA experiments results i.e., Tgsh and Tgign. Multiple fixed nonlinear regression analysis shows that thermogravimetry (TG) experiment results Tgign may be the best index to categorise/classify the coal as per their susceptibility towards spontaneous combustion. The authors proposed four groups of classification as per their propensity towards spontaneous combustion depending upon the moisture (Mad), volatile matter (VMd), and TG ignition temperature from differential thermogravimetric (DTG) curve (Tgign) using hierarchal clustering analysis. The coal samples of different seams from Indian coalfield may be classified into four different clusters, viz. very highly/extremely susceptible (Tgign 320 ℃). The field observations and TGA/DSC experiment results with the following statistical analysis substantiate a similar assessment

Comparison of Single-Session Dose Response Effects of Whole Body Vibration on Spasticity and Walking Speed in Persons with Spinal Cord Injury

Spasticity affects approximately 65% of persons with spinal cord injury (SCI) and negatively impacts function and quality of life. Whole body vibration (WBV) appears to reduce spasticity and improve walking function; however, the optimal dose (frequency/duration) is not known. We compared single-session effects of four different WBV frequency/duration dose conditions on spasticity and walking speed, in preparation for a planned multi-session study. Thirty-five participants with motor-incomplete SCI received four different doses of WBV: high frequency (50 Hz)/short duration (180 s), high frequency/long duration (360 s), low frequency (30 Hz)/short duration, and low frequency/long duration, plus a control intervention consisting of sham electrical stimulation. In all conditions, participants stood on the WBV platform for 45-s bouts with 1 min rest between bouts until the requisite duration was achieved. The frequency/duration dose order was randomized across participants; sessions were separated by at least 1 week. Quadriceps spasticity was measured using the pendulum test at four time points during each session: before, immediately after, 15 min after, and 45 min after WBV. Walking speed was quantified using the 10-m walk test at three time points during each session: baseline, immediately after, and 45 min after WBV. In the full group analysis, no frequency/duration combination was significantly different from the sham-control condition. In participants with more severe spasticity, a greater reduction in stretch reflex excitability was associated with the high frequency/long duration WBV condition. The sham-control condition was associated with effects, indicating that the activity of repeated sitting and standing may have a beneficial influence on spasticity. NCT02340910 (assigned 01/19/2015)

A comparative kinetic study between TGA & DSC techniques using model-free and model-based analyses to assess spontaneous combustion propensity of Indian coals

Kinetic study of coal was carried out using simultaneous thermal analysis (STA) technique to assess the spontaneous combustion propensity of coal samples collected from various Indian coalfields having both fiery and non-fiery seams. The kinetic parameters were estimated by using both model-free and model-based analysis for both TGA & DSC data. The model-based method comprises four different consecutive reaction steps, viz. A→B→C→D→E for the spontaneous combustion process and the second reaction step (B→C) were used for this investigation. Chemometric analysis was applied to know the relation between the proximate analysis and activation energy of the samples using model-free and model-based techniques. The activation energy for the second reaction step of the model-based method for both TGA and DSC data showed a good relationship with the standard methods i.e., crossing point temperature (XPT) and Tgign of the samples. It indicates that the activation energy values at the oxidation stage (2nd stage) play a significant role in the spontaneous combustion propensity of coal. The study also reveals that the model-based analysis provided better results in comparison to model-free analysis to assess the spontaneous combustion propensity of coal

Review of preventive and constructive measures for coal mine explosions: An Indian perspective

Firedamp and coal dust explosion constitute a lion’s share in mine accidents in a global mining scenario. This paper reports a list of mine explosion disasters since last two decades, a critical review of the different prevention and constructive measures, and its recent development to avoid firedamp and coal dust explosion. Preventive legislation in core coal-producing countries, viz. China, USA, Australia, South Africa, and India related to firedamp and coal dust explosion are critically analysed. Accidents occurred due to explosion after Nationalisation of Coal Mines (1973) in India are listed. Prevention and constructive measures adopted in India are critically analysed with respect to the global mining scenario. Measures like methane credit concept, classification of mines/seams with respect to explosion risk zone, deflagration index; installation of automatic fire warning devices, canopy air curtain technology, explosion-prevention measures, such as fire-retardant materials, inhibitors, extinguishing agent, dust suppressor, and active explosion barrier are discussed in detail to avoid explosion and thereby adhering to zero accident policy due to coal mine explosion

Experimental and CFD Simulation Techniques for Coal Dust Explosibility: A Review

Coal is a low-cost and high-calorific-value fuel. The coal mining industry worldwide has been suffering from severe accidents due to coal dust explosion hazards since its inception. Statistically, it was observed that 12,489 fatalities had occurred in 104 reported mining accidents from coal dust explosions during 1900–2020. There are numerous methods for detection, prevention, and control of coal dust explosions in mines. The underground mining environment is unpredictable and has an array of variables. These undulating factors make it difficult to prevent or control the coal dust explosion hazard. However, coal mining is done aggressively throughout the world, especially in developing countries as coal is a major source of thermal energy used in power plants contributing to about 38% (IEA, (2019), World Energy Outlook, IEA, Paris https://www.iea.org/reports/world-energy-outlook-2019.) of world electricity. Worldwide, coal dust explosibility studies are carried out in experimental mines, laboratories, and simulations. The complexity, lack of proper infrastructure, and unavailability of laboratory equipment sometimes make it difficult to study coal dust explosibility. The authors have discussed in detail and proposed that the CFD modelling can be a viable option for studying and evaluating coal dust explosibility

TGA/DSC study to characterise and classify coal seams conforming tosusceptibility towards spontaneous combustion

Thermogravimetric analysis/differential scanning calorimeter (TGA/DSC) technique along with basic coalcharacteristics study is carried out for eighty coal samples of Indian coalfields, to determine spontaneouscombustion propensity behaviour of coal. TGA study of coal samples indicates that there is an increase inthe mass of coal samples in the temperature range 150–350 ℃, which may be due to oxygen adsorptionand absorption. The correlation and principal component analysis states that the component of proxi-mate analysis (Mad,VMd, FR, and VR) have an acceptable correlation with the TGA experiments resultsi.e., Tgshand Tgign. Multiple fixed nonlinear regression analysis shows that thermogravimetry (TG) exper-iment results Tgignmay be the best index to categorise/classify the coal as per their susceptibility towardsspontaneous combustion. The authors proposed four groups of classification as per their propensitytowards spontaneous combustion depending upon the moisture (Mad), volatile matter (VMd), and TG ignition temperature from differential thermogravimetric (DTG) curve (Tgign) using hierarchal clustering analysis. The coal samples of different seams from Indian coalfield may be classified into four different clusters, viz. very highly/extremely susceptible (Tgign 320 ℃). The field observations and TGA/DSC experiment results with the following statistical analysis substantiate a similar assessment

Prevention and control of spontaneous combustion/fire in coal stockpiles of power plants using firefighting chemicals

Spontaneous combustion of coal in stockpiles of power plants has a significant problem worldwide which leads to several health hazards, environmental pollution and coal loss. Spontaneous combustion coal stockpiles depend on both endogenous (coal characteristics) and exogenous parameters (stockpile geometry, wind speed, wind direction, local temperature). This paper describes the laboratory experiments to study the suitability of firefighting chemicals on the spontaneous combustion/fire of coal in stockpiles. Coal samples were collected from four different heaps of coal laid in coal storage yards of Talwandi Sabo Power Limited (TSPL), Punjab. This study comprises laboratory analysis i.e., proximate analysis, ultimate analysis, critical oxidation temperature, differential scanning calorimetry (DSC) analysis, gross calorific value (GCV), particle size analysis, and field studies i.e., thermal monitoring of fire-affected area before and after firefighting chemicals. Experiments on mixtures of coal and firefighting chemical having compositions viz. 1, 2, 3, and 5%, were carried out using DSC study for optimization of inhibitors as well as its efficacy. During the laboratory study the chemical composition of 3% was found to be optimum for field application to extinguish coal stockpile fire

Prior Elicitation and Bayesian Analysis of the Steroids for Corneal Ulcers Trial

PurposeTo elicit expert opinion on the use of adjunctive corticosteroid therapy in bacterial corneal ulcers. To perform a Bayesian analysis of the Steroids for Corneal Ulcers Trial (SCUT), using expert opinion as a prior probability.MethodsThe SCUT was a placebo-controlled trial assessing visual outcomes in patients receiving topical corticosteroids or placebo as adjunctive therapy for bacterial keratitis. Questionnaires were conducted at scientific meetings in India and North America to gauge expert consensus on the perceived benefit of corticosteroids as adjunct treatment. Bayesian analysis, using the questionnaire data as a prior probability and the primary outcome of SCUT as a likelihood, was performed. For comparison, an additional Bayesian analysis was performed using the results of the SCUT pilot study as a prior distribution.ResultsIndian respondents believed there to be a 1.21 Snellen line improvement, and North American respondents believed there to be a 1.24 line improvement with corticosteroid therapy. The SCUT primary outcome found a non-significant 0.09 Snellen line benefit with corticosteroid treatment. The results of the Bayesian analysis estimated a slightly greater benefit than did the SCUT primary analysis (0.19 lines verses 0.09 lines).ConclusionIndian and North American experts had similar expectations on the effectiveness of corticosteroids in bacterial corneal ulcers; that corticosteroids would markedly improve visual outcomes. Bayesian analysis produced results very similar to those produced by the SCUT primary analysis. The similarity in result is likely due to the large sample size of SCUT and helps validate the results of SCUT

Prior Elicitation and Bayesian Analysis of the Steroids for Corneal Ulcers Trial

PURPOSE: To elicit expert opinion on the use of adjunctive corticosteroid therapy in bacterial corneal ulcers. To perform a Bayesian analysis of the Steroids for Corneal Ulcers Trial (SCUT), using expert opinion as a prior probability. METHODS: The SCUT was a placebo-controlled trial assessing visual outcomes in patients receiving topical corticosteroids or placebo as adjunctive therapy for bacterial keratitis. Questionnaires were conducted at scientific meetings in India and North America to gauge expert consensus on the perceived benefit of corticosteroids as adjunct treatment. Bayesian analysis, using the questionnaire data as a prior probability and the primary outcome of SCUT as a likelihood, was performed. For comparison, an additional Bayesian analysis was performed using the results of the SCUT pilot study as a prior distribution. RESULTS: Indian respondents believed there to be a 1.21 Snellen line improvement, and North American respondents believed there to be a 1.24 line improvement with corticosteroid therapy. The SCUT primary outcome found a non-significant 0.09 Snellen line benefit with corticosteroid treatment. The results of the Bayesian analysis estimated a slightly greater benefit than did the SCUT primary analysis (0.19 lines verses 0.09 lines). CONCLUSION: Indian and North American experts had similar expectations on the effectiveness of corticosteroids in bacterial corneal ulcers; that corticosteroids would markedly improve visual outcomes. Bayesian analysis produced results very similar to those produced by the SCUT primary analysis. The similarity in result is likely due to the large sample size of SCUT and helps validate the results of SCUT