Reliability optimization design for composite laminated plate considering multiple types of uncertain parameters

Peng, Xiang; Guo, Yuliang; Qiu, Chao; Wu, Huaping; Li, Jiquan; Chen, Guohai; Jiang, Shaofei; Liu, Zhenyu

doi:10.1080/0305215x.2019.1705289

Cited by 25 publications

(6 citation statements)

References 51 publications

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“…After determining the 1~4 order moments of the triangular fuzzy variable using Equation ( 13), the four statistical moments M 1 ∼ M 4 for triangular fuzzy variable are calculated using Equations ( 8)- (11). Then, the lower and upper bounds of M 1 ∼ M 4 for a triangular fuzzy variable are determined using Equation (12).…”

Section: Moments Calculation For Triangular Fuzzy Variablementioning

confidence: 99%

“…To address the problems of incomplete information or insufficient data for uncertain variables, the use of epistemic uncertainty is proposed. This has been widely applied to the uncertainty analysis and reliability design of engineering products [9][10][11]. Some non-probabilistic uncertainty analysis methods have been proposed to address epistemic uncertainties, and summarized by Beer [12], which includes the interval analysis approach [13,14], the convex model [15,16], the fuzzy set [17,18], and the evidence theory [19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

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Probabilistic Representation Approach for Multiple Types of Epistemic Uncertainties Based on Cubic Normal Transformation

Peng

Gao

et al. 2020

Applied Sciences

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Many non-probabilistic approaches have been widely regarded as mathematical tools for the representation of epistemic uncertainties. However, their heavy computational burden and low computational efficiency hinder their applications in practical engineering problems. In this article, a unified probabilistic representation approach for multiple types of epistemic uncertainties is proposed based on the cubic normal transformation method. The epistemic uncertainties can be represented using an interval approach, triangular fuzzy approach, or evidence theory. The uncertain intervals of four statistical moments, which contain mean, variance, skewness, and kurtosis, are calculated using the sampling analysis method. Subsequently, the probabilistic cubic normal distribution functions are conducted for sampling points of four statistical moments of epistemic uncertainties. Finally, a calculation procedure for the construction of probabilistic representation functions is proposed, and these epistemic uncertainties are represented with belief and plausibility continuous probabilistic measure functions. Two numerical examples and one engineering example demonstrate that the proposed approach can act as an accurate probabilistic representation function with high computational efficiency.

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Section: Moments Calculation For Triangular Fuzzy Variablementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Probabilistic Representation Approach for Multiple Types of Epistemic Uncertainties Based on Cubic Normal Transformation

Peng

Gao

et al. 2020

Applied Sciences

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“…Carbon fiber-reinforced composites (CFRP) have been widely used in the aerospace industry due to their high specific strength and stiffness, performance design, corrosion resistance, and overall shape [1][2][3][4][5][6]. The stiffened composite structure can reduce the weight of structure due to its own material and structural characteristics, which has a great impact on the weight reduction of modern aircraft.…”

Section: Introductionmentioning

confidence: 99%

Study on Low-Velocity Impact Damage and Residual Strength of Reinforced Composite Skin Structure

Zhang

Jia

et al. 2020

Materials

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In order to better understand the damage tolerance of reinforced composite plates, the impact damage of the reinforced composite plates was investigated under low-velocity impact test. The experimental results show that the impact of different positions and energies causes different degrees of damage to the specimens, including but not limited to ply fracture, internal delamination of the skin, and debonding of the stiffeners and skin. After impacting, the specimens were tested in an axial compression. The results show that the ultimate bearing capacity of the specimen is also affected by different forms of impact. The impact point has the greatest influence on the specimen while it locates at the intersection of longitudinal and transverse bars. Compared with the intact specimen, the ultimate load carrying capacity was reduced by 16.83% and 44.02%, while the specimen impacted by 15 J and 30 J, respectively. The compression failure mode of the damaged specimen is mainly the breakage of the stiffeners and the delamination of the skin.

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“…RBDO problems for composite materials can be solved using a double-loop approach, where the reliability analysis is performed as an inner-loop each time the design variables are updated to assess the reliability constraints (Thompson et al , 2006). However, this can result in a large number of function evaluations, leading to high computational cost (Díaz et al , 2016; Peng et al , 2020; Li et al , 2019). Thus, the double loop approach is usually only computationally feasible when solving the problem using a gradient-based optimisation method, with analytical models (or small numerical models) and an approximate analytical reliability method (e.g.…”

Section: Introductionmentioning

confidence: 99%

Multi-scale reliability-based design optimisation framework for fibre-reinforced composite laminates

Omairey

Dunning

Sriramula

2020

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Purpose The purpose of this study is to enable performing reliability-based design optimisation (RBDO) for a composite component while accounting for several multi-scale uncertainties using a large representative volume element (LRVE). This is achieved using an efficient finite element analysis (FEA)-based multi-scale reliability framework and sequential optimisation strategy. Design/methodology/approach An efficient FEA-based multi-scale reliability framework used in this study is extended and combined with a proposed sequential optimisation strategy to produce an efficient, flexible and accurate RBDO framework for fibre-reinforced composite laminate components. The proposed RBDO strategy is demonstrated by finding the optimum design solution for a composite component under the effect of multi-scale uncertainties while meeting a specific stiffness reliability requirement. Performing this using the double-loop approach is computationally expensive because of the number of uncertainties and function evaluations required to assess the reliability. Thus, a sequential optimisation concept is proposed, which starts by finding a deterministic optimum solution, then assesses the reliability and shifts the constraint limit to a safer region. This is repeated until the desired level of reliability is reached. This is followed by a final probabilistic optimisation to reduce the mass further and meet the desired level of stiffness reliability. In addition, the proposed framework uses several surrogate models to replace expensive FE function evaluations during optimisation and reliability analysis. The numerical example is also used to investigate the effect of using different sizes of LRVEs, compared with a single RVE. In future work, other problem-dependent surrogates such as Kriging will be used to allow predicting lower probability of failures with high accuracy. Findings The integration of the developed multi-scale reliability framework with the sequential RBDO optimisation strategy is proven computationally feasible, and it is shown that the use of LRVEs leads to less conservative designs compared with the use of single RVE, i.e. up to 3.5% weight reduction in the case of the 1 × 1 RVE optimised component. This is because the LRVE provides a representation of the spatial variability of uncertainties in a composite material while capturing a wider range of uncertainties at each iteration. Originality/value Fibre-reinforced composite laminate components designed using reliability and optimisation have been investigated before. Still, they have not previously been combined in a comprehensive multi-scale RBDO. Therefore, this study combines the probabilistic framework with an optimisation strategy to perform multi-scale RBDO and demonstrates its feasibility and efficiency for an fibre reinforced polymer component design.

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Reliability optimization design for composite laminated plate considering multiple types of uncertain parameters

Cited by 25 publications

References 51 publications

Probabilistic Representation Approach for Multiple Types of Epistemic Uncertainties Based on Cubic Normal Transformation

Probabilistic Representation Approach for Multiple Types of Epistemic Uncertainties Based on Cubic Normal Transformation

Study on Low-Velocity Impact Damage and Residual Strength of Reinforced Composite Skin Structure

Multi-scale reliability-based design optimisation framework for fibre-reinforced composite laminates

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