Distributed consensus and fault tolerance mechanisms in blockchain form a core research area that underpins the reliability, security, and scalability of decentralized systems. Research papers in this domain explore how consensus protocols enable blockchain networks to agree on a single version of the ledger, even in the presence of failures, adversaries, or malicious nodes. Studies compare classical mechanisms such as Proof of Work (PoW), Proof of Stake (PoS), and Practical Byzantine Fault Tolerance (PBFT) with advanced models like Delegated Proof of Stake (DPoS), Raft, HotStuff, and hybrid protocols that balance performance, decentralization, and energy efficiency. Recent works emphasize fault tolerance strategies to mitigate issues like double-spending, Sybil attacks, and network partitioning while maintaining liveness and safety guarantees. Multi-objective optimization approaches are being developed to trade off throughput, latency, and energy use in large-scale blockchain networks. Emerging research also integrates machine learning for adaptive consensus tuning and investigates cross-chain consensus for interoperability between heterogeneous blockchains. Applications range from financial services and supply chains to IoT and smart grids, where reliable distributed consensus and robust fault tolerance are critical. Overall, this research provides the foundation for building scalable, secure, and resilient blockchain ecosystems suitable for mission-critical and large-scale decentralized applications.