Indian Institute of Technology Bombay

About: Indian Institute of Technology Bombay is a education organization based out in Mumbai, India. It is known for research contribution in the topics: Population & Thin film. The organization has 16756 authors who have published 33588 publications receiving 570559 citations.

A Scalable Approximate Model Counter

Abstract: Propositional model counting} (#SAT), i.e., counting the number of satisfying assignments of a propositional formula, is a problem of significant theoretical and practical interest. Due to the inherent complexity of the problem, approximate model counting, which counts the number of satisfying assignments to within given tolerance and confidence level, was proposed as a practical alternative to exact model counting. Yet, approximate model counting has been studied essentially only theoretically. The only reported implementation of approximate model counting, due to Karp and Luby, worked only for DNF formulas. A few existing tools for CNF formulas are bounding model counters; they can handle realistic problem sizes, but fall short of providing counts within given tolerance and confidence, and, thus, are not approximate model counters. We present here a novel algorithm, as well as a reference implementation, that is the first scalable approximate model counter for CNF formulas. The algorithm works by issuing a polynomial number of calls to a SAT solver. Our tool, ApproxMC, scales to formulas with tens of thousands of variables. Careful experimental comparisons show that ApproxMC reports, with high confidence, bounds that are close to the exact count, and also succeeds in reporting bounds with small tolerance and high confidence in cases that are too large for computing exact model counts.

A critical re-evaluation of the usefulness of R-D framework in predicting NBTI stress and recovery

Abstract: Reaction-Diffusion (R-D) framework for interface trap generation along with hole trapping in pre-existing and generated bulk oxide traps are used to model Negative Bias Temperature Instability (NBTI) in differently processed SiON p-MOSFETs. Time, temperature and bias dependent degradation and recovery transients are predicted. Long-time power law exponent of DC degradation and uniquely renormalized duty cycle and frequency dependent AC degradation data from a wide range of sources are shown to have universal features and a broad consensus across industry/academia. These universal features can also be predicted using the classical R-D framework.

Optimal operation of industrial cogeneration for load management

Abstract: This paper presents a generalized formulation to determine the optimal operating strategy of industrial cogeneration schemes. The model includes both electrical and thermal systems. All types of cogeneration equipment viz steam turbines, gas turbines, diesel generators, steam boilers, waste heat recovery boilers, and steam header configuration, with grid connection are separately represented in terms of their characteristics so that the model has the flexibility to be applicable for any industry. The model is multiperiod and nonlinear in nature and utilizes a Newton based algorithm for minimizing the total operating cost. Optimal operating strategies for different equipment combinations for a typical industrial configuration under different electricity tariff rates are determined using the proposed model. The results show that industrial cogeneration has a significant potential in reducing peak coincident demand. The optimal response of cogeneration plant reduces the peak coincident demand by 42.8 MW (71%) under flat tariff and 54 MW (90%) under TOU tariff. The industry gets 16% saving in the total operating cost with the optimal operation of the cogeneration plant. When power export is permitted to grid, it provides the utility a peak saving of 63.7 MW.