research

Optimizing deployment dynamics of composite tape-spring hinges

Submitted by Jinxiong Zhou on Fri, 03/29/2024 - 04:34

The composite tape-spring hinge (CTSH) is a lightweight structural connector widely employed in space structures, including spacecraft and satellites, due to its high specific strength and stiffness. Introducing cutouts enables CTSH to possess folding and deployment capability, while optimizing the cutouts finely to optimize the performance of CTSH. However, the interaction between cutout size and the dynamic deployment of CTSH is a novel topic.

A mesoscale computational approach to predict ABD matrix of thin woven composites

Submitted by Jinxiong Zhou on Fri, 03/29/2024 - 04:27

Finite Element Method

The ABD matrix is a fundamental method to characterize the overall stiffness behavior of laminated composite structures. Although classical laminate theory has been widely used, it has limitations in predicting the ABD matrix for woven composites. To address this issue, this paper presents a mesoscale homogenization approach aimed at computing the ABD matrix for thin woven composites accurately. The mesoscale representative volume element (RVE) of the woven composite is generated using TexGen and imposed with periodic boundary conditions to enforce the Kirchhoff thin plate assumption.

A hybrid proper orthogonal decomposition and next generation reservoir computing approach for high-dimensional chaotic prediction: Application to flow-induced vibration of tube bundles

Submitted by Jinxiong Zhou on Fri, 03/29/2024 - 04:00

research

Flow-induced vibration (FIV)

Neural networks (NNs)

Chaotic systems

Next generation reservoir computing (NGRC)

Time series prediction

To address the significant challenges in predicting high-dimensional chaotic systems, this paper introduces a novel hybrid strategy that combines proper orthogonal decomposition (POD), which serves as reduced order modeling (ROM), with next generation reservoir computing (NGRC), a data-driven prediction model. The POD-NGRC strategy harnesses the strengths of POD in extracting principal evolutionary features and reducing system complexity, along with the high accuracy, ease of design, enhanced robustness, and high computational efficiency offered by NGRC.

Best Paper Award for Young Investigators - Int. J. Solids & Structures

Submitted by Rui Huang on Thu, 03/28/2024 - 20:32

Young Investigator Award

The International Journal of Solids and Structures is pleased to institute an annual Best Paper Award for Young Investigators. The award will be given annually to a paper published in the previous year whose principal or corresponding author is under the age of 38 or within 10 years of the completion of their PhD.

Common Misconceptions on Rules of Mixtures

Submitted by Wenbin Yu on Thu, 03/28/2024 - 18:56

research

Please pardon me if I am preaching to the choir here. Rules of mixtures (ROM) are very simple mechanics models. Everybody on this site has a very good understanding of it. However, confusion and mistakes on ROM constantly appear in textbooks, journal articles, online learning materials, etc. See attached two wiki articles. The major confusing point is that vf*Ef+vm*Em is derived from the isostrain assumption and the upper bound. Both statements are incorrect. There might be two main reasons contributed to this mistake/confusion.

Issues with normal and cohesive surface contact definition for model with Johnson-Cook material model in Abaqus

Submitted by Monica Dhinde on Thu, 03/21/2024 - 16:18

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I am modelling a 3D solid model of simply supported sandwich plate with foam core, the core is modelled as Johnson-Cook material model with damage definitions, so the element deletion can be acheived. I tried using tie constraints between the core and face sheets, but due to the deletion of elements in the core at the interface, the face sheet is penetrating into the core beyond the supports. I tried using nodal surfaces and surface interactions, which avoids this issue but after defining the cohesive propeties for the interaction, the analysis is shutting abruply.

A solid-shell model of hard-magnetic soft materials

Submitted by Fan Xu on Mon, 03/18/2024 - 01:27

research

Morphing Structures

large deformation

Hard-magnetic soft materials (HMSMs) consisting of an elastomer matrix filled with high remnant magnetic particles can exhibit flexible programmability and rapid shape changing under non-contact activation, showing promising potential applications in soft robotics, biomedical devices and flexible electronics. Precise predictions of large deformations of hard-magnetic soft materials would be a key for relevant applications.

Deep-learning model using a small dataset

Submitted by Mirkhalaf on Fri, 03/15/2024 - 09:37

research

One the main challenges of developing data-driven models is the data-hungry nature of Artificial Neural Networks (ANNs). In our recent paper, we introduced a data augmentation approach to expand a small original dataset without conducting extra expensive high-fidelity simulations. We then used the original and augmented datasets for developing ANN models for non-linear path dependent composites. The obtained results showed the great impact of the data augmentation approach on the accuracy of the data-driven models.