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RISS 인기검색어
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- 저자 : Mayuram, M.M. (검색결과 2 건)
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Coupled temperature-displacement modeling to study the thermo-elastic instability in disc brakes
Ramkumar, E.,Mayuram, M.M. Techno-Press 2012 Coupled systems mechanics Vol.1 No.2
Macroscopic hot spots formed due to the large thermal gradients at the surface of the disc brake rotor, make the rotor to fail or wear out early. Thermo-elastic deformation results in contact concentration, leading to the non uniform distribution of temperature making the disc susceptible to hot spot formation. The formation of one hot spot event will predispose the system to future hot spotting at the same location. This leads to the complete thermo-elastic instability in the disc brakes; multitude parameters are responsible for the thermo elastic instability. The predominant factor is the sliding velocity and above a certain sliding velocity the instability of the brake system occurs and hot spots is formed in the surface of the disc brake. Commercial finite element package ABAQUS(R) is used to find the temperature distribution and the result is validated using Rowson's analytical model. A coupled analysis methodology is evolved for the automotive disc brake from the transient thermo-elastic contact analysis. Temperature variation is studied under different sliding speeds within the operation range.
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ForestDB: A Fast Key-Value Storage System for Variable-Length String Keys
Jung-Sang Ahn,Chiyoung Seo,Mayuram, Ravi,Yaseen, Rahim,Jin-Soo Kim,Seungryoul Maeng IEEE 2016 IEEE Transactions on Computers Vol.65 No.3
<P>Indexing key-value data on persistent storage is an important factor for NoSQL databases. Most key-value storage engines use tree-like structures for data indexing, but their performance and space overhead rapidly get worse as the key length becomes longer. This also affects the merge or compaction cost which is critical to the overall throughput. In this paper, we present ForestDB, a key-value storage engine for a single node of large-scale NoSQL databases. ForestDB uses a new hybrid indexing scheme called HB+-trie, which is a disk-based trie-like structure combined with B+-trees. It allows for efficient indexing and retrieval of arbitrary length string keys with relatively low disk accesses over tree-like structures, even though the keys are very long and randomly distributed in the key space. Our evaluation results show that ForestDB significantly outperforms the current key-value storage engine of Couchbase Server [1], LevelDB [2], and RocksDB [3], in terms of both the number of operations per second and the amount of disk writes per update operation.</P>
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