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Bounded model checking (BMC) based on Boolean satisfiability (SAT) methods has recently gained popularity as a viable alternative to BDD-based techniques for verifying large designs. This work proposes a number of conceptually simple, but extremely effective, optimizations for enhancing the performance of SAT-based BMC flows. The key ideas include: (1) a novel idea to combine SAT-based inductive reasoning and BMC; (2) clever orchestration of variable ordering and learned information in an incremental framework for BMC; and (3) BMC-specific ordering strategies for the SAT solver. Our experiments, conducted on a wide range of industrial designs, show that the proposed optimizations consistently provide between 1-2 orders of magnitude speedup and can be extremely useful in enhancing the efficacy of typical SAT-BMC tools.