摘要 :
An efficient approximate RBDO method under both aleatory and epistemic uncertainty is presented. As stated by the Unified Uncertainty Analysis based on the First Order Reliability Method (FORM-UUA), it is possible to merge the pro...
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An efficient approximate RBDO method under both aleatory and epistemic uncertainty is presented. As stated by the Unified Uncertainty Analysis based on the First Order Reliability Method (FORM-UUA), it is possible to merge the probability and evidence theory to quantify the belief and plausibility of a specific performance function under mixed uncertainty. When the number of evidence variables and the number of intervals increases, the frame of discernment and consequently the number of focal elements grows dramatically. As a result, if the hybrid reliability analysis is included in an optimization problem, it becomes unmanageable due to its high computational cost. The strategy proposed allows to avoid the computation of the sub-plausibilities for each focal element as required in the FORM-UUA. The HRBDO problem is decoupled into an iterative process with a deterministic optimization and a reliability analysis phase consisting of two separated but connected reliability analyses that handle separately the random and evidence variables. Then, the optimum design obtained is checked and adjusted through the FORM-UUA method. Two analytical examples and one numerical problem are presented to validate the proposed method.
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摘要 :
An efficient approximate RBDO method under both aleatory and epistemic uncertainty is presented. As stated by the Unified Uncertainty Analysis based on the First Order Reliability Method (FORM-UUA), it is possible to merge the pro...
展开
An efficient approximate RBDO method under both aleatory and epistemic uncertainty is presented. As stated by the Unified Uncertainty Analysis based on the First Order Reliability Method (FORM-UUA), it is possible to merge the probability and evidence theory to quantify the belief and plausibility of a specific performance function under mixed uncertainty. When the number of evidence variables and the number of intervals increases, the frame of discernment and consequently the number of focal elements grows dramatically. As a result, if the hybrid reliability analysis is included in an optimization problem, it becomes unmanageable due to its high computational cost. The strategy proposed allows to avoid the computation of the sub-plausibilities for each focal element as required in the FORM-UUA. The HRBDO problem is decoupled into an iterative process with a deterministic optimization and a reliability analysis phase consisting of two separated but connected reliability analyses that handle separately the random and evidence variables. Then, the optimum design obtained is checked and adjusted through the FORM-UUA method. Two analytical examples and one numerical problem are presented to validate the proposed method.
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摘要 :
The fail-safe design philosophy aims to achieve safe designs under the different accidental scenarios that structures might undergo throughout their lifespan. The Probability-Damage approach for Fail-Safe Optimization (PDFSO) led ...
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The fail-safe design philosophy aims to achieve safe designs under the different accidental scenarios that structures might undergo throughout their lifespan. The Probability-Damage approach for Fail-Safe Optimization (PDFSO) led to an improvement over the traditional multi-model optimization strategy, since it takes into account the available data on the probability of occurrence of each partial collapse and allows the designer to assume certain risk over the damaged configurations less likely to occur. However, that methodology can be improved considering the inherent uncertainty in some random parameters such as loads or material properties. The objective of this research is to formulate a PDFSO approach including this randomness and therefore, obtain more reliable designs. Two application examples were considered: a 2D truss structure with stress constraints as well as the tail section of an aircraft fuselage with stress and buckling constraints.
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摘要 :
The fail-safe design philosophy aims to achieve safe designs under the different accidental scenarios that structures might undergo throughout their lifespan. The Probability-Damage approach for Fail-Safe Optimization (PDFSO) led ...
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The fail-safe design philosophy aims to achieve safe designs under the different accidental scenarios that structures might undergo throughout their lifespan. The Probability-Damage approach for Fail-Safe Optimization (PDFSO) led to an improvement over the traditional multi-model optimization strategy, since it takes into account the available data on the probability of occurrence of each partial collapse and allows the designer to assume certain risk over the damaged configurations less likely to occur. However, that methodology can be improved considering the inherent uncertainty in some random parameters such as loads or material properties. The objective of this research is to formulate a PDFSO approach including this randomness and therefore, obtain more reliable designs. Two application examples were considered: a 2D truss structure with stress constraints as well as the tail section of an aircraft fuselage with stress and buckling constraints.
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摘要 :
The fail-safe design philosophy aims to achieve safe designs under the different accidental scenarios that structures might undergo throughout their lifespan. The Probability-Damage approach for Fail-Safe Optimization (PDFSO) led ...
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The fail-safe design philosophy aims to achieve safe designs under the different accidental scenarios that structures might undergo throughout their lifespan. The Probability-Damage approach for Fail-Safe Optimization (PDFSO) led to an improvement over the traditional multi-model optimization strategy, since it takes into account the available data on the probability of occurrence of each partial collapse and allows the designer to assume certain risk over the damaged configurations less likely to occur. However, that methodology can be improved considering the inherent uncertainty in some random parameters such as loads or material properties. The objective of this research is to formulate a PDFSO approach including this randomness and therefore, obtain more reliable designs. Two application examples were considered: a 2D truss structure with stress constraints as well as the tail section of an aircraft fuselage with stress and buckling constraints.
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摘要 :
The fail-safe design philosophy aims to achieve safe designs under the different accidental scenarios that structures might undergo throughout their lifespan. The Probability-Damage approach for Fail-Safe Optimization (PDFSO) led ...
展开
The fail-safe design philosophy aims to achieve safe designs under the different accidental scenarios that structures might undergo throughout their lifespan. The Probability-Damage approach for Fail-Safe Optimization (PDFSO) led to an improvement over the traditional multi-model optimization strategy, since it takes into account the available data on the probability of occurrence of each partial collapse and allows the designer to assume certain risk over the damaged configurations less likely to occur. However, that methodology can be improved considering the inherent uncertainty in some random parameters such as loads or material properties. The objective of this research is to formulate a PDFSO approach including this randomness and therefore, obtain more reliable designs. Two application examples were considered: a 2D truss structure with stress constraints as well as the tail section of an aircraft fuselage with stress and buckling constraints.
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The emerging need in the aerospace engineering field to design more environmentally-friendly and safer aircraft is leading to the development of novel engine concepts. These new-generation aircraft engines, which include big open ...
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The emerging need in the aerospace engineering field to design more environmentally-friendly and safer aircraft is leading to the development of novel engine concepts. These new-generation aircraft engines, which include big open rotors or ultra-high-bypass models, would pose a potential risk due to an engine failure, where some structural components would be released hitting the fuselage. Unfortunately, the existing optimization methodologies do not contemplate this fact when performing the design process of these structures. Therefore, the fuselage would not be able to resist the debris impact, resulting in the loss of structural integrity of the aircraft. The purpose of this paper is to define how to apply the multi-model optimization concept into existing methodologies for optimization under uncertainty, providing several options to the designer depending on the order of merit to be considered: if it is preferable to guarantee a specific safety level with respect to the structural constraints at the expense of having a heavier design, or conversely, obtaining a design that does not guarantee the desired safety level but which is not stochastically dominated by another design. A set-up problem of a 3 bar structure and a realistic example of an aircraft-tail fuselage are used to test the capabilities of the different methodologies.
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摘要 :
The emerging need in the aerospace engineering field to design more environmentally-friendly and safer aircraft is leading to the development of novel engine concepts. These new-generation aircraft engines, which include big open ...
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The emerging need in the aerospace engineering field to design more environmentally-friendly and safer aircraft is leading to the development of novel engine concepts. These new-generation aircraft engines, which include big open rotors or ultra-high-bypass models, would pose a potential risk due to an engine failure, where some structural components would be released hitting the fuselage. Unfortunately, the existing optimization methodologies do not contemplate this fact when performing the design process of these structures. Therefore, the fuselage would not be able to resist the debris impact, resulting in the loss of structural integrity of the aircraft. The purpose of this paper is to define how to apply the multi-model optimization concept into existing methodologies for optimization under uncertainty, providing several options to the designer depending on the order of merit to be considered: if it is preferable to guarantee a specific safety level with respect to the structural constraints at the expense of having a heavier design, or conversely, obtaining a design that does not guarantee the desired safety level but which is not stochastically dominated by another design. A set-up problem of a 3 bar structure and a realistic example of an aircraft-tail fuselage are used to test the capabilities of the different methodologies.
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摘要 :
Fail-safe design methodology is a crucial design requirement for aviation safety and airworthiness, as it allows designs to be safe from structural component failures. A well-know example to apply this methodology is the accidenta...
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Fail-safe design methodology is a crucial design requirement for aviation safety and airworthiness, as it allows designs to be safe from structural component failures. A well-know example to apply this methodology is the accidental situation of an uncontained engine rotor failure or a propeller blade failure, where debris violently strike the fuselage. This research presents a tool that allows the automatic generation of randomly damaged FE models based on information from real accident databases involving failure of engine components, from impact tests of engine fragments or from expertise in the field. The tool greatly facilitates and enhances the analysis and design of fail-safe structures, since it can generate a wide set of damaged configurations representing real accidents. Thus, we can avoid current fail-safe techniques based on damage envelopes that lead to oversized designs. To do so, the input parameters taken into account are the location of the debris origin, impact orientation, number of impacts, debris size, debris velocity, spread angles and ballistic penetration equations.
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Fail-safe design in aerospace is often addressed by the use of envelopes of possible damaged configurations when there is uncertainty about the size or location of the damage. This strategy leads to oversized designs, since realis...
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Fail-safe design in aerospace is often addressed by the use of envelopes of possible damaged configurations when there is uncertainty about the size or location of the damage. This strategy leads to oversized designs, since realistic damage scenarios are not considered. In a previous research, we developed the DamageCreator software to automatically generate a large set of damaged FE meshes representing real accidental situations, coming from uncontained engine failures or propeller blade failures. This paper aims to perform a fail-safe optimization of a industry-like aerospace structure using realistic damaged scenarios automatically generated by the DamageCreator tool. A real historical accident database will be taken as input to generate the set of damaged configurations.
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