Extension of the universal erosive burning law to partly symmetric propellant grain geometries

This paper aims at extending the universal erosive burning law developed by two of the present authors from axi-symmetric internally burning grains to partly symmetric burning grains. This extension revolves around three dimensional flow calculations inside highly loaded grain geometry and benefiting from an observation that the flow gradients normal to the surface in such geometries have a smooth behavior along the perimeter of the grain. These are used to help identify the diameter that gives the same perimeter the characteristic dimension rather than a mean hydraulic diameter chosen earlier. The predictions of highly loaded grains from the newly chosen dimension in the erosive burning law show better comparison with measured pressure-time curves while those with mean hydraulic diameter definitely over-predict the pressures. (c) 2013 IAA. Published by Elsevier Ltd. All rights reserved.

Generalized distributive law for ML decoding of STBCs: further results

The problem of designing good Space-Time Block Codes (STBCs) with low maximum-likelihood (ML) decoding complexity has gathered much attention in the literature. All the known low ML decoding complexity techniques utilize the same approach of exploiting either the multigroup decodable or the fast-decodable (conditionally multigroup decodable) structure of a code. We refer to this well known technique of decoding STBCs as Conditional ML (CML) decoding. In [1], we introduced a framework to construct ML decoders for STBCs based on the Generalized Distributive Law (GDL) and the Factor-graph based Sum-Product Algorithm, and showed that for two specific families of STBCs, the Toepltiz codes and the Overlapped Alamouti Codes (OACs), the GDL based ML decoders have strictly less complexity than the CML decoders. In this paper, we introduce a `traceback' step to the GDL decoding algorithm of STBCs, which enables roughly 4 times reduction in the complexity of the GDL decoders proposed in [1]. Utilizing this complexity reduction from `traceback', we then show that for any STBC (not just the Toeplitz and Overlapped Alamouti Codes), the GDL decoding complexity is strictly less than the CML decoding complexity. For instance, for any STBC obtained from Cyclic Division Algebras that is not multigroup or conditionally multigroup decodable, the GDL decoder provides approximately 12 times reduction in complexity compared to the CML decoder. Similarly, for the Golden code, which is conditionally multigroup decodable, the GDL decoder is only about half as complex as the CML decoder.