Modeling of Hypervelocity Impact of Sandwiched Open Cell Aluminum Foam

Zhang, Xiaotian; Ruiqing, Wang; Li, Q.M.

doi:10.1016/j.proeng.2017.09.734

Cited by 4 publications

(3 citation statements)

References 13 publications

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“…In the field of destruction, aluminum alloys are often used as equivalent materials for complex equipment structures and are widely used in practical equipment. Therefore, in this study, we chose aluminum alloys as the correction object and summarized the values of the relevant parameters of the aluminum alloy by reviewing several pieces of literature [29][30][31][32][33][34]. A total of 12 parameters (E, v, A, B, N, C, M, T m , D 1 , D 2 , D 3 , and D 4 ) with a range of more than 10% change in value were initially selected as correction variables, and their values are listed in table 7.…”

Section: Basic Information About the Experimentsmentioning

confidence: 99%

Finite element model correction method based on surrogate model with multiple working conditions and multiple measurement points

Song,

Shi,

You

et al. 2023

Meas. Sci. Technol.

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The finite element model inversion method has been widely used in recent years for iterative adjustment of finite element model parameters. However, the models constructed in the existing literature are weak and time consuming to adapt to the environment, which makes it difficult to adapt to the current needs of numerical simulations. To address the problem of large uncertainty in the material parameters of real objects and the difficulty of constructing finite element simulation models, a surrogate-based model correction method was proposed for multi-condition and multi-measurement point finite element models. The innovative use of the working condition parameter as one of the training parameters of the surrogate model to construct the optimal mathematical model for parameter correction of the finite element model to variable working conditions. To reduce the number of finite element model calls and speed up the convergence process, an MP-CV-Voronoi parallel infill sampling method for the surrogate model was proposed to overcome the problems of easily falling into local optima and slow convergence when solving after constructing the surrogate model. The proposed parallel infill sampling method was tested using the test functions. The finite element model correction method with multiple working conditions and multiple measurement points was applied for material parameter correction and identification of aluminum alloys. The superiority of the proposed parallel point addition method in terms of the solution accuracy and speed was demonstrated. The results show that the multi-measurement points have a significant effect on improving the model correction effect, and the constructed multi-condition surrogate model can make fast predictions for arbitrary conditions and has strong environmental adaptability. The finite element model correction method proposed in this paper, with strong environmental adaptability, high accuracy and fast iteration, has been tested to be very effective.

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Section: Basic Information About the Experimentsmentioning

confidence: 99%

Finite element model correction method based on surrogate model with multiple working conditions and multiple measurement points

Song,

Shi,

You

et al. 2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…Micrometeoroids and orbital debris (MMOD) poses a significant danger to both robotic and crewed spacecraft operating beyond Earth's atmosphere [1,2,3,4,5,6]. Despite sizes under 2 mm, even miniscule particles can have tremendous impact velocities (10-12 km/s or Mach ∼35, equivalently) that result in catastrophic damage [1].…”

Section: Introductionmentioning

confidence: 99%

“…Open cell metallic foam sandwich panel structures have proven effective at mitigating damage from MMOD strikes [3,4,5]. Commercially available metallic foams sandwiched between solid metallic facesheets are widely used for MMOD shielding on a range of spacecraft.…”

Section: Introductionmentioning

confidence: 99%

Stochastic mechanical modeling of metallic foams to determine onset of mesoscale behavior

Seif¹,

Puppo²,

Zlatinov³

et al. 2023

Preprint

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Metallic foams are crucial to many emerging applications, among them shielding against hypervelocity impacts caused by micrometeoroids and orbital debris. The variability of properties at feature-scale and mesoscale lengths originating from the foam's inherently random microstructure makes predictive models of their properties challenging. It also hinders the optimization of components fabricated with such foams, an especially serious problem for spacecraft design where the balance between cost and mass must also be balanced against the catastrophic results of component failure. To address this problem, we compute the critical transition length between the feature-scale, where mechanical properties are determined by individual features, and the mesoscale, where behavior is determined by ensembles of features. At the mesoscale, distributions of properties-with respect to both expectation value and standard variability-are consistent and predictable. The Kentucky Random Structure Toolkit (KRaSTk) is applied to determine the transition from feature-scale to mesoscale for computational volumes representing metallic foams at a range of reduced densities. The transition is found to occur when the side length of a cubic sample volume is ∼10× greater than the characteristic length. Comparing KRaSTk-computed converged stiffness distributions with experimental measurements of a commercial metallic foam found excellent agreement for both expectation value and standard variability at all reduced densities. Lastly, we observe that the diameter of a representative MMOD strike is ∼30× shorter than the feature-scale to mesoscale transition for the foam at any reduced density. Therefore, features will determine response to hypervelocity impacts, rather than bulk (or even mesoscale) structure.

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Stochastic mechanical modeling of Duocel foam from micro- to macro- length scales

Seif

Puppo²,

Zlatinov³

et al. 2022

AIAA SCITECH 2022 Forum

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Modeling of Hypervelocity Impact of Sandwiched Open Cell Aluminum Foam

Cited by 4 publications

References 13 publications

Finite element model correction method based on surrogate model with multiple working conditions and multiple measurement points

Finite element model correction method based on surrogate model with multiple working conditions and multiple measurement points

Stochastic mechanical modeling of metallic foams to determine onset of mesoscale behavior

Stochastic mechanical modeling of Duocel foam from micro- to macro- length scales

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