reliability of a system is the probability that it will function as intended for the required period of time. the opposite of reliability is failure probability per unit time or over time, such as a life cycle. following a review of existing reliability codes and approaches, comprehensive approaches to assess the reliability of offshore structures are described, including probabilistic analysis...

Due to the probabilistic nature and uncertainties of structural parameters, reliability-based optimization will enable engineers to account for the safety of the structures and allow for its decision making applicability. Thus, reliability-based design will substitute deterministic rules of codes of practice. Space structures are of those types that have an exceedingly high range of applicabili...

This paper reports a neural network-based methodology for failure probability prediction and quality enhancement of microengine MEMS using attribute data derived from actual measurements on microengines. A backpropagation neural network was employed for failure probability prediction. Microengine attributes constituted the inputs while time-tofailure statistics (mean, median and shape parameter...

Moderate Density Parity Check (MDPC) codes are defined here as codes which have a parity-check matrix whose row weight is O( √ n) where n is the length n of the code. They can be decoded like LDPC codes but they decode much less errors than LDPC codes: the number of errors they can decode in this case is of order Ω( √ n). Despite this fact they have been proved very useful in cryptography for d...

This paper presents basic decision theory rationale for selecting a particular failure probability value from its uncertainty distribution to compare to a defined acceptability criterion. Since the success probability, or reliability, is one minus the failure probability, the rationale also applies to selecting a particular reliability value to compare to a reliability criterion. The uncertaint...

Evaluation of failure probability of a given system requires sampling of the system response and can be computationally expensive. Therefore it is desirable to construct an accurate surrogate model for the system response and subsequently to sample the surrogate model. In this paper we discuss the properties of this approach. We demonstrate that the straightforward sampling of a surrogate model...