Thapar University

About: Thapar University is a education organization based out in Patiāla, Punjab, India. It is known for research contribution in the topics: Cloud computing & Fuzzy logic. The organization has 2944 authors who have published 8558 publications receiving 130392 citations.

Biodiesel production from waste cooking oil using heterogeneous catalysts and its operational characteristics on variable compression ratio CI engine

Abstract: In the present work, the optimum biodiesel conversion from waste cooking oil to biodiesel through transesterification method was investigated. The base catalyzed transesterification under different reactant proportions such as the molar ratio of alcohol to oil and mass ratio of catalyst to oil was studied for optimum production of biodiesel. The optimum condition for base catalyzed transesterification of waste cooking oil was determined to be 12:1 and 5 wt% of zinc doped calcium oxide. The fuel properties of the produced biodiesel such as the calorific value, flash point and density were examined and compared to conventional diesel. The properties of produced biodiesel and their blend for different ratios (B20, B40, B60, B80 and B100) were comparable with properties of diesel oil and ASTM biodiesel standards. Tests have been conducted on CI engine which runs at a constant speed of 1500 rpm, injection pressure of 200 bar, compression ratio 15:1 and 17.5, and varying engine load. The performance parameters include brake thermal efficiency, brake specific energy consumption and emissions parameters such as Carbon monoxide (CO), Hydrocarbon (HC), Oxides of Nitrogen (NOx) and smoke opacity varying with engine load (BP). Diesel engine's thermal performance and emission parameters such as CO, HC, and NOx on different biodiesel blends demonstrate that biodiesel produced from waste cooking oil using heterogeneous catalyst was suitable to be used as diesel oil blends and had lesser emissions as compared to conventional diesel.

Generalized Cubic Intuitionistic Fuzzy Aggregation Operators Using t-Norm Operations and Their Applications to Group Decision-Making Process

Abstract: Cubic intuitionistic fuzzy (CIF) set (CIFS) is one of the newly developed extension of the intuitionistic fuzzy set (IFS) in which data are represented in terms of their interval numbers membership and non-membership degrees and further the degree of agreeness, as well as disagreeness corresponding to these intervals, are given in the form of an IFS Its fundamental characteristic lies in the fact that it is a combined version of both interval-valued IFS and IFS rather than being confined to any single fuzzy environment Under this environment, the present work focused on exploring the structural characteristics of the CIFS by defining operational laws between them Further, based on these operational laws, we propose some new generalized CIF averaging aggregation operators and group decision-making methods Finally, an illustrative example is provided to discuss the reliability of the proposed operators