PSI - Issue 57

Andrew Halfpenny et al. / Procedia Structural Integrity 57 (2024) 718–730 Andrew Halfpenny / Structural Integrity Procedia 00 (2023) 000–000

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Fig. 1. Modelling variability and uncertainty

linearization. Linearization errors can therefore be modelled as a source of uncertainty whose influence is usually less than that of material variability. Fig. 1 illustrates the probability of damage at the end of the target reliability period. The variability and uncertainty in customer loading is expressed as a probability curve titled ‘Stress’. Similarly, the distribution of variability and uncertainty in fatigue strength is expressed as a probability curve title ‘Strength’. The area under the intersection of the curves represents the probability of failure. For example, in the automotive industry, this could represent the likelihood of the most aggressive users being in possession of the statistically worst-performing product. The general approach to design qualification in the automotive industry is illustrated in Fig. 2. A similar approach is taken in the aerospace industry where the ‘proving ground’ is e ff ectively replaced with a ‘flight profile’, (which is also known as a ‘duty schedule’, or ‘mission profile’). The four stages of design qualification are discussed below. 1.2.1. Statistical target customer analysis This involves a measurement campaign to characterise the variability of usage throughout the customer base. Historically this was based on measurements taken several decades ago; however, these have become engrained in national, international, and company qualification test standards such as, MIL-STD-810G (2008), RTCA / DO-160G (2010), and Def Stan 00-35 (2021). Recently, standards have evolved to represent new technological advances such as EV battery systems, for example, SAE J2380 (2013), ISO (2020), and IEC (2018). OEMs (Original Equipment Manufacturers) have also become interested in re-characterising their own product usage. This drive is prompted in the automotive industry by economic requirements to develop a ‘world car’ that is suitable for all markets, and accounts for evolving performance and driving characteristics. A similar phenomenon occurs in the aerospace industry, where many aircraft are expected to survive long service periods under evolving operational profiles. The intention is to transform a representative customer vehicle into an unbiased transducer for measuring usage severity. A range of instrumentation is available in both aerospace and automotive applications. These instruments are often suboptimal for design purposes because they are compromised by the requirements of real-world customers. This means they cannot adequately measure the individual component loads required for design purposes, but are suitable for characterising usage. (Component loads are better measured using proving ground (or flight test) data where more appropriate instrumentation options are available.) A detailed study of target customer analysis in the automotive industry is given by Halfpenny and Pompetzki (2011). 1.2. Simulation, Verification and Validation (SV & V)