Probabilistic structural analysis of aerospace components using NESSUS

Sensitivity of the shape of a turbine blade shapes on its performance is more compared to the compressor blade shape. Thus, a lot of research is concentrated on design of turbine blades and wide range of methods were suggested for the same. A blade with acceptable performance should have minimum of first order continuity along the blade curve. Discontinuity on the blade geometry leads to higher pressure gradient and affects the performance drastically. Hence, in this paper a turbine blade is generated, by using Bezier control points, to obtain a smooth blade curve. The blade is divided into leading section, main section and trailing section. The middle section of the blade is formed by cubic Bezier splines ensuring the first and second order continuity on the blade geometry. New blade geometries are formed by shifting the positions of the Bezier control points. The blade geometry formed from this newly shifted Bezier control points is subjected to the same boundary conditions as the baseline profile and the pressure distribution is analysed.The different blades generated are analysed in ANSYS FLUENT 17.2. The computational domain is a two dimensional turbine cascade, consisting of a turbine blade enclosed by periodic boundaries to mimic realistic conditions. A second order upwind strategy is used for inviscid flow analysis.

Influence of micro-scale uncertainties on the reliability of fibre-matrix composites

Uncertainties in material properties, geometry, manufacturing processes, and operational environments are clearly critical at all scales (nano-, micro-, meso-, and macro-scale). The incorporation of reliability analysis is critical in designing material structures when material properties are uncertain. The concept of mesostructured or cellular materials is motivated by the desire to put material only where it is needed for a specific application. Typically, the cellular materials have superior structural compliant performance per weight than parts with bulk material or foams. This research develops a reliability-based synthesis method to design cellular material structures under random fields. The efficiency of the proposed framework is achieved with the combination of topology optimisation and stochastic local regression by utilising polynomial chaos expansion and Karhunen–Loeve transform. The effectiveness of the proposed framework is demonstrated with two examples including a ground truss structure and an automotive component which is composed of cellular material.

Reliability analysis of homogeneous and bimaterial cracked structures by the scaled boundary finite element method and a hybrid random-interval model

Miter gate is a type of navigation lock gate which is used to allow the passage of inland navigation across different levels in a river system. Aging miter gates have come down with structural degradation due to fatigue and corrosion bringing about a deterioration of structural resistance, influencing the integrity and life cycle costs. Therefore, it is essential to re-assess our belief in the structural safety and perform maintenance accordingly to optimize the operation and maintenance costs. This study demonstrates an approach to update the reliability of aging miter gates under the effect of fatigue and corrosion. The failure probability calculated in this study is founded on a probabilistic crack propagation analysis which considers the uncertainty in material properties, weld geometry, and fatigue loading. The time-dependent capacity of a miter gate is assessed including the influence of corrosion fatigue and corrosion growth rate. The procedure is then used for an example where the probability of failure of a miter gate welded joint is updated based on inspection outcomes. The reliability updating approach presented here can be used for risk-based maintenance optimization of lock gates.

The effect of interference of corrosion pits on the failure probability of a reinforced concrete beam

Effect of Pit Distance on Failure Probability of a Corroded RC Beam

The probabilistic distribution of crack lengths at a critical location is a key input for risk assessment of structural failure of airframes due to fracture. This distribution depends on the initial surface condition of the structural component, the crack growth behaviour of the material, and the applied load history. MIL-STD-1530C suggests the use of a single master crack growth curve to derive the subsequent crack length distributions from the initial crack length distribution, without taking into consideration the well-recognized scatter in crack growth rates due to uncertainties in material properties. In this paper, we report the results of a study that aims to quantify the scatter in crack growth rates of 7075-T7351 aluminium alloy subjected to spectrum loading, and to assess its effect on risk assessment. About 80 middle-tension specimens were planned to be tested under nominally identical conditions, with the crack lengths recorded using crack cameras and direct current differential potential method. Based on the test data and the analyses, crack length distributions are developed for different times. These are then compared to the distributions derived from the master curve approach. This investigation attempts to quantitatively demonstrate the reasonableness, or otherwise, of using a single crack growth curve to derive the distributions of crack lengths for risk analyses, and the conditions under which the observations apply. The results reported here and those from other researchers show that this scatter in crack growth rates cause by variation in material properties cannot be appropriately addressed by the master crack growth curve approach for the purpose of risk analysis.

The generation of frequency-domain macromodels for passive interconnects such as power delivery networks can be computationally expensive. In this work, macromodels are constructed through the Latency Insertion Method in the time-domain before conversion to the frequency domain via the Fast Fourier transform. Results show an improvement in the simulation time as well as good accuracy over the frequency range of interest. The method is used to characterize a power delivery plane with uncertainties in geometry and material properties.

Two Euler analysis techniques, finite difference and finite volume, are employed to predict the blade surface pressure distributions of a large scale advanced propeller. The predicted pressure distributions are compared with wind tunnel data. Both techniques produced blade pressure distributions which are in fairly good agreement with the data over the range of test Mach numbers of 0.2 to 0.78. However, the numerical simulations fail to predict correctly the measured pressure distributions for the low Mach number, high power case which seem to have a leading edge vortex. A discussion of the compressibility effects is also presented.

The water retention of coating color on base paper is one of the most important properties that affects the sheet properties of coated paper. We have JIS regulations to measure water absorbency of paper and paper board. However, we do not have any regulation to evaluate water retention of coating color. Some methods to evaluate water retention of coating color were suggested. However, any definition of the word “Water Retention” was not given.In this study, we divided “Water Retention” into static water retention and dynamic water retention. We also suggest a new concept “Blade Response”, which is calculated from coating weight and blade pressure. Static and dynamic water retention, and coating viscosity are the most important properties of “Blade Response”. Hi-share viscometer, Brookfield viscometer, Capillary viscometer, and Water retention meter were used to evaluate properties of coating color. “Blade Response” was used as an index to evaluate the runnability of coating color.The runnability was successfully assumed from static water retention, hi-share viscosity and capillary viscosity of coating colors.

Uncertain material properties on wave dispersion behaviors of smart magneto-electro-elastic nanobeams

Design rules for modern cable suspension bridges are developed using reliability theories inside a general risk management based framework. In this context, optimal structural design must be considered under the presence of uncertainties in loading, geometry and material properties, whereas the deterministic approaches of optimization neglect the effects of uncertainties associated with design variables. This paper is based on the theory of finite element reliability analysis of geometrically nonlinear elastic structures. It provides computer implementation considerations and developments. For the assessment of overall reliability of suspension bridges, in this paper only static load effects are examined. The sensitivity of the reliability judgments with respect to different loading combinations is also studied.

Higher accuracy in estimation of stress distribution, especially in the critical locations with stress variation, is important for a more reliable prediction of possible damage or prognosis of the structure. A structure can have several such locations and it is not economically feasible to monitor all of them with traditional sensing methods. Moreover, these methods often provide response measurements at a few localized points and demand deployment in large numbers to get a distributed response. Hybrid submodeling is a data-driven physics-based submodeling method to achieve a refined estimate of distributed structural response in and around the critical locations or other locations of interest. This method uses measured response on the pre-meditated boundaries around the location of interest to drive the corresponding submodel of the structural component or connection to achieve a more spatially refined response. The method accumulates and propagates uncertainty in different stages of response estimation such as uncertainty in sensor location, measurement noise, uncertainty in submodel geometry, material properties, and boundary condition uncertainty at submodel boundaries. This article demonstrates uncertainty propagation in the hybrid-submodeling method, considering uncertainty in the submodel boundary conditions as the only source of uncertainty. This is demonstrated by using DIC digital image correlation (DIC) to measurements to drive the submodel region around a critical location on a structural component. Monte-Carlo simulation (MCS) is used to study the uncertainty propagated to the response in the hybrid-submodeling method. The study observed lower variability in the distribution of response in each location obtained through hybrid submodeling compared to its corresponding distribution from DIC measurements on the plate under the same loading conditions.KeywordsUncertainty propagationHybrid-submodelingResponse estimationDigital image correlationMonte-Carlo simulation

Reliability analysis of smart laminated composite plates under static loads using artificial neural networks