Probabilistic design approach reliability analysis

The conceptual system selected in step 3 is designed. Reliability and maintainability of this design are assessed. Various methodologies, such as design review, failure mode and effect analysis, fault tree analysis, and probabilistic design approach, can be applied at this step. Reliability is a design parameter and must be incorporated in the system at the design step. 

A separated reliability analysis of structural and technical systems into dynamic by Eq. (12) and static by Eq. (14) or (15) parts helps designers to simplify probabilistic calculations. The presented unsophisticated probability-based approaches, design models and calculation equations may be convenient for many practitioners and can stimulate designers to use the full probabilistic methods in their practice more actively and effectively. 

Probabilistic structural reliability analysis is performed to ensure that a structure is able to withstand the required design loads. A realistic description of the environmental loads and structural response is a crucial prerequisite for structural reliability analysis of structures exposed to environmental forces. The concept of environmental contours is an efficient method of estimating extreme conditions as basis for design. See (Winterstein et d., 1993) and (Haver Winterstein 2009). It is widely used in marine structural design. See e.g., (Baarholm et al., 2010), (Fontaine et al., 2013), (Jonathan et al., 2011), (Moan 2009) and (Ditlevsen 2002). The traditional approach is to use the well-known Rosenblatt transformation introduced in (Rosenblatt 1952) to transform the environmental variables into independent standard normal variables and identify a sphere with desired radius in the transformed space. Environmental contours are then found by re-transforming the sphere back to the original space. This approach is closely related to the FORM-approximation (First Order Reliability Method), where the failure boundary in the transformed space is approximated by a hyperplane at the design point. 

The press had been designed with a capacity to deliver 280 kN press force and to work at a production rate of 40 lids per minute. Calculations to determine the distribution of forming loads required indicated that the press capacity was adequate to form the family of steel lids to be produced on the machine. One of the major areas of interest in the design was the con-rod and pin (see Figure 4.66). The first option considered was based on a previous design where the con-rod was manufactured from cast iron with phosphor bronze bearings at the big and small ends. However, weaknesses in this approach necessitated the consideration of other options. The case study presents the analysis of the pin and con-rod using simple probabilistic techniques in an attempt to provide in-service reliable press operation. The way a weak link was introduced to ensure ease of maintenance and repair in the event... 

In the last twenty years, various non-deterministic methods have been developed to deal with optimum design under environmental uncertainties. These methods can be classified into two main branches, namely reliability-based methods and robust-based methods. The reliability methods, based on the known probabiUty distribution of the random parameters, estimate the probability distribution of the system s response, and are predominantly used for risk analysis by computing the probability of system failure. However, variation is not minimized in reliability approaches (Siddall, 1984) because they concentrate on rare events at the tail of the probability distribution (Doltsinis and Kang, 2004). The robust design methods are commonly based on multiobjective minimization problems. The are commonly indicated as Multiple Objective Robust Optimization (MORO) and find a set of optimal solutions that optimise a performance index in terms of mean value and, at the same time, minimize its resulting dispersion due to input parameters uncertainty. The final solution is less sensitive to the parameters variation but eventually maintains feasibility with regards probabilistic constraints. This is achieved by the optimization of the design vector in order to make the performance minimally sensitive to the various causes of variation. 

Any autosystem is a highly correlated series system of particular elements and their durabihty parameters are related to reliability indices. However, the values of safety and durability indices may be objectively defined only by fully probability-based concepts and models because probabilistic approaches allow us explicitly predict uncertainties of analysis parameters and design models. 

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