Application of TG technique to determine spontaneous heating propensity of coals

© 2020, Akadémiai Kiadó, Budapest, Hungary. The TG method is applied to eleven coal samples of varying rank collected from across the Jharia coalfield, India, to determine spontaneous heating susceptibility. Previous literature does not agree as to the TG experimental parameter that characterizes the spontaneous heating susceptibility of coal. A series of TG experiments were performed on triplicate samples of each coal to determine the susceptibility of coal to spontaneous heating. Each prepared sample had the following properties: mass–10mg, size distribution − 212µm, and was subjected to a sample gas flow rate of 40mLmin−1 and a balance gas flow rate of 60mLmin−1 under the following four different heating rates: 1, 5, 15 and 30°Cmin−1. The study concludes that the heating rate of 5°Cmin−1 should be used to determine the spontaneous heating susceptibility. The experimental data obtained are subjected to chemo-metric tools, i.e. principal component analysis and hierarchical clustering analysis to establish any linkage between the coal characteristics parameters and spontaneous heating susceptibility indices. These analyses reveal that the self-heating (Tsh) and ignition temperature (Tign) determined from the TG experiment results may indicate the susceptibility of coal to spontaneous heating, which is corroborated by well-established standard experiments as well as with field observations

Estimation of greenhouse gas emissions from spontaneous combustion/fire of coal in opencast mines – Indian context

There are a significant number of uncontrolled coal mine fires (primarily due to spontaneous combustion of coal), which are currently burning all over the world. These spontaneous combustion sources emit greenhouse gases (GHGs). A critical review reveals that there are no standard measurement methods to estimate GHG emissions from mine fire/spontaneous combustion areas. The objective of this research paper was to estimate GHGs emissions from spontaneous combustion of coals in the Indian context. A sampling chamber (SC) method was successfully used to assess emissions at two locations of the Enna Opencast Project (OCP), Jharia Coalfield (JCF), for 3 months. The study reveals that measured cumulative average emission rate for CO2 varies from 75.02 to 286.03 gs−1m−1 and CH4 varies from 41.49 to 40.34 gs−1m−1 for low- and medium-temperature zones. The total GHG emissions predicted from this single fire affecting mines of JCF vary from 16.86 to 20.19 Mtyr−

Review of experimental methods to determine spontaneous combustion susceptibility of coal – Indian context

This paper presents a critical review of the different techniques developed to investigate the susceptibility of coal to spontaneous combustion and fire. These methods may be sub-classified into the two following areas: (1) Basic coal characterisation studies (chemical constituents) and their influence on spontaneous combustion susceptibility. (2) Test methods to assess the susceptibility of a coal sample to spontaneous combustion. This is followed by a critical literature review that summarises previous research with special emphasis given to Indian coals

Tracing SPLs precisely and efficiently

International audienceIn a Software Product Line (SPL) comprising specifications (feature sets), implementations (component sets) and traceability between them, the definition of product is quite subtle. Intuitively, a strong relation of implementability should be established between implementations and specifications due to traceability. Various notions of traceability has been proposed in the literature : [13], [17], [8], [9]; but we found in our experience that they do not capture all situations that arise in practice. One example is the case where, an implementation, due to packaging reasons, contains additional components not required for a particular product specification. We have defined a general notion of traceability in order to cover such situations. Moreover, state-of-the-art satisfiability based notions lead to products where the implementability relation does not exist. Therefore, in this paper, we propose a simple, set-theoretic formalism to express the notions of traceability and implementability in a formal manner. The subsequent definition of SPL products is used to introduce a set of analysis problems that are either refinements of known problems, or are completely novel. Last but not the least, we propose encoding the analysis problems as Quantified Boolean Formula (QBF) constraints and use Quantified SAT (QSAT) solvers to solve these problems efficiently. To the best of our knowledge, the QBF encoding is novel; we prove the correctness of our encoding and demonstrate its practical feasibility through our prototype implementation Software Product Line Engine (SPLE)

Knowledge Representation of Cyber-physical Systems for Monitoring Purpose

Automated warehouses, as a form of cyber-physical systems (CPSs), require several components to work collaboratively to address the common business objectives of complex logistics systems. During the collaborative operations, a number of key performance indicators (KPI) can be monitored to understand the proficiency of the warehouse and control the operations and decisions. It is possible to drive and monitor these KPIs by looking at both the state of the warehouse components and the operations carried out by them. Therefore, it is necessary to represent this knowledge in an explicit and formally-specified data model and provide automated methods to derive the KPIs from the representation. In this paper, we implement a minimalistic data model for a subset of warehouse resources using linked data in order to monitor a few KPIs, namely sustainability, safety and performance. The applicability of the approach and the data model is illustrated through a use case. We demonstrate that it is possible to develop minimalistic data models through Open Services for Lifecycle Collaboration (OSLC) resource shapes which enables compatibility with the declarative and procedural knowledge of automated warehouse agents specified in Planning Domain Definition Language (PDDL)