Abhash Nigam

TL;DR: In this article, a stochastic method was devised to transform efficient sets of analytical characterizations into molecular representations of complex petroleum feedstocks, and the atomic detail of a large ensemble of representative molecular structures from which both molecular and global product properties were deduced.

TL;DR: In this article, the problem of asphaltene precipitation during their thermolysis in a hypothetical inert oil motivated the development of a stochastic model of the structure, reactions, and product identification.

Abstract: A thermochemical kinetics-based lumping strategy for modeling the pyrolysis of individual components of heavy hydrocarbon mixtures is suggested. Pyrolysis of a given feedstock is viewed from two perspectives. First, molecules are organized into compound classes, e.g., paraffins, alkylnaphthenes, and alkylaromatics. Second, the elementary steps of pyrolysis of each member of a compound class are constrained by a quantitative structure-reactivity relationship (QSRR). This two-dimensional, mechanism-oriented lumping approach provides significant reduction in the number of parameters required to model pyrolysis

TL;DR: In this article, asphaltenes were pyrolyzed at 400, 425, and 450°C (752, 797, 842°F) for batch holding limes ranging from 20 to 180 minutes.

TL;DR: The model of uniform nonlinear kinetics recently developed for the continuous description of a multicomponent mixture reacting in a batch or plug flow reactor is applied and it is shown that most of the equations can be solved in general, independently of the specific kinetic mechanism.