Reliability Based Design Optimization of Concrete Mix Proportions Using Generalized Ridge Regression Model

This paper presents Reliability Based Design Optimization (RBDO) model to deal with uncertainties involved in concrete mix design process. The optimization problem is formulated in such a way that probabilistic concrete mix input parameters showing random characteristics are determined by minimizing the cost of concrete subjected to concrete compressive strength constraint for a given target reliability. Linear and quadratic models based on Ordinary Least Square Regression (OLSR), Traditional Ridge Regression (TRR) and Generalized Ridge Regression (GRR) techniques have been explored to select the best model to explicitly represent compressive strength of concrete. The RBDO model is solved by Sequential Optimization and Reliability Assessment (SORA) method using fully quadratic GRR model. Optimization results for a wide range of target compressive strength and reliability levels of 0.90, 0.95 and 0.99 have been reported. Also, safety factor based Deterministic Design Optimization (DDO) designs for each case are obtained. It has been observed that deterministic optimal designs are cost effective but proposed RBDO model gives improved design performance

Reliability improvement of electronic circuits based on physical failure mechanisms in components

Traditionally the position of reliability analysis in the design and production process of electronic circuits is a position of reliability verification. A completed design is checked on reliability aspects and either rejected or accepted for production. This paper describes a method to model physical failure mechanisms within components in such a way that they can be used for reliability optimization, not after, but during the early phase of the design process. Furthermore a prototype of a CAD software tool is described, which can highlight components likely to fail and automatically adjust circuit parameters to improve product reliability

Optimization of structures on the basis of fracture mechanics and reliability criteria

Systematic summary of factors which are involved in optimization of given structural configuration is part of report resulting from study of analysis of objective function. Predicted reliability of performance of finished structure is sharply dependent upon results of coupon tests. Optimization analysis developed by study also involves expected cost of proof testing

Composite laminate tailoring with probabilistic constraints and loads

A reliability-based structural synthesis procedure was developed to tailor laminates to meet reliability-based (ply) strength requirements and achieve desirable laminate responses. The main thrust is to demonstrate how to integrate the optimization technique in the composite laminate tailoring process to meet reliability design requirements. The question of reliability arises in fiber composite analysis and design because of the inherent scatter that is observed in the constituent (fiber and matrix) material properties during experimentation. Symmetric and asymmetric composite laminates subject to mechanical loadings are considered as application examples. These application examples illustrate the effectiveness and ease with which reliability considerations can be integrated in the design optimization model for composite laminate tailoring

Robust Dynamic Selection of Tested Modules in Software Testing for Maximizing Delivered Reliability

Software testing is aimed to improve the delivered reliability of the users. Delivered reliability is the reliability of using the software after it is delivered to the users. Usually the software consists of many modules. Thus, the delivered reliability is dependent on the operational profile which specifies how the users will use these modules as well as the defect number remaining in each module. Therefore, a good testing policy should take the operational profile into account and dynamically select tested modules according to the current state of the software during the testing process. This paper discusses how to dynamically select tested modules in order to maximize delivered reliability by formulating the selection problem as a dynamic programming problem. As the testing process is performed only once, risk must be considered during the testing process, which is described by the tester's utility function in this paper. Besides, since usually the tester has no accurate estimate of the operational profile, by employing robust optimization technique, we analysis the selection problem in the worst case, given the uncertainty set of operational profile. By numerical examples, we show the necessity of maximizing delivered reliability directly and using robust optimization technique when the tester has no clear idea of the operational profile. Moreover, it is shown that the risk averse behavior of the tester has a major influence on the delivered reliability.Comment: 19 pages, 4 figure

A Derivative-Free Trust-Region Algorithm for Reliability-Based Optimization

In this note, we present a derivative-free trust-region (TR) algorithm for reliability based optimization (RBO) problems. The proposed algorithm consists of solving a set of subproblems, in which simple surrogate models of the reliability constraints are constructed and used in solving the subproblems. Taking advantage of the special structure of the RBO problems, we employ a sample reweighting method to evaluate the failure probabilities, which constructs the surrogate for the reliability constraints by performing only a single full reliability evaluation in each iteration. With numerical experiments, we illustrate that the proposed algorithm is competitive against existing methods

Frameless ALOHA with Reliability-Latency Guarantees

One of the novelties brought by 5G is that wireless system design has increasingly turned its focus on guaranteeing reliability and latency. This shifts the design objective of random access protocols from throughput optimization towards constraints based on reliability and latency. For this purpose, we use frameless ALOHA, which relies on successive interference cancellation (SIC), and derive its exact finite-length analysis of the statistics of the unresolved users (reliability) as a function of the contention period length (latency). The presented analysis can be used to derive the reliability-latency guarantees. We also optimize the scheme parameters in order to maximize the reliability within a given latency. Our approach represents an important step towards the general area of design and analysis of access protocols with reliability-latency guarantees.Comment: Accepted for presentation at IEEE Globecom 201

Reliability based robust design optimization based on sensitivity and elasticity factors analysis

In this paper, a Reliability Based Robust Design Optimization (RBRDO) based on sensitivity and elasticity factors analysis is presented. In the first step, a reliability assessment is performed using the First-and Second Order Reliability Method (FORM)/ (SORM), and Monte Carlo Simulation. Furthermore, FORM method is used for reliability elasticity factors assessment, which can be carried out to determine the most influential parameters, these factors can be help to reduce the size of design variables vector in RBRDO process. The main objective of the RBRDO is to improve both reliability and design of a cylindrical gear pair under uncertainties. This approach is achieved by integration of two objectives which minimize the variance and mean values of performance function. To solve this problem a decoupled approach of Sequential Optimization and Reliability Assessment (SORA) method is implemented. The results obtained shown that a desired reliability with a robust design is progressively achieved

Reliability-based design optimization using kriging surrogates and subset simulation

The aim of the present paper is to develop a strategy for solving reliability-based design optimization (RBDO) problems that remains applicable when the performance models are expensive to evaluate. Starting with the premise that simulation-based approaches are not affordable for such problems, and that the most-probable-failure-point-based approaches do not permit to quantify the error on the estimation of the failure probability, an approach based on both metamodels and advanced simulation techniques is explored. The kriging metamodeling technique is chosen in order to surrogate the performance functions because it allows one to genuinely quantify the surrogate error. The surrogate error onto the limit-state surfaces is propagated to the failure probabilities estimates in order to provide an empirical error measure. This error is then sequentially reduced by means of a population-based adaptive refinement technique until the kriging surrogates are accurate enough for reliability analysis. This original refinement strategy makes it possible to add several observations in the design of experiments at the same time. Reliability and reliability sensitivity analyses are performed by means of the subset simulation technique for the sake of numerical efficiency. The adaptive surrogate-based strategy for reliability estimation is finally involved into a classical gradient-based optimization algorithm in order to solve the RBDO problem. The kriging surrogates are built in a so-called augmented reliability space thus making them reusable from one nested RBDO iteration to the other. The strategy is compared to other approaches available in the literature on three academic examples in the field of structural mechanics.Comment: 20 pages, 6 figures, 5 tables. Preprint submitted to Springer-Verla