Diverse science and engineering problems are governed by delay differential equations (DDE). Seeking periodic solutions of DDEs is crucial for many nonlinear dynamic systems. The incremental harmonic balance (IHB) method is an efficient semi-analytical ap- proach for periodic solutions of DDE.
The thermal-hydraulics as well as flow-induced vibration of wire-wrapped rod bundles calls for accurate and efficient liquid metal flow simulation and prediction, yet it remains a challenge due to the complex geometries and high Reynolds number flow in wire-wrapped rod channel. Previous efforts towards this goal exclusively adopts full-order modeling (FOM), which is prohibitively computation-intensive.
Design of mechanical metamaterials is typically realized by repeating microstructured building blocks or unit cells. Microstructures of these unit cells can be identical, whereas individual design of each cell and various combinations of unit cells definitely offer more freedoms and possibilities for combinatorial design of metamaterials. Unfortunately, this combinatorial design problem is prohibitively challenging, if not impossible, due mainly to its huge number of combinatorial cases.
Selective electron beam melting (SEBM) is one of the popular powder-bed additive manufacturing (AM) technologies, of which there have been extensive studies employing numerical simulations to investigate the thermo-physical phenomena. A procedure for deducing thermo-physical properties of powders from bulk properties of tantalum is presented.
Composite tape-spring hinge (CTSH) is a simple yet elegant mechanical component for various deployable space structures. This paper formulates and addresses cut-out shape optimization of a CTSH, which is seldom touched upon in literature. Both the maximum strain energy stored during the folding process as well as the maximum bending moment during deployment were maximized in a concurrent way, and the multi-objective optimization problem was realized by merging data-driven surrogate modeling and shape optimization.
Due to the inherent viscoelasticity of constituent matrix and the possibility of long-term storage, space deployable structures made of composites are likely to exhibit relaxation in the stored strain energy, which may degrade their deployment performance. This paper presents a bottom-up finite element based multiscale computational strategy that bridges the experimentally measurable properties of constituent fibers and matrix to numerical predictions of viscoelastic behavior of composite laminates and general shell structures.
This paper describes a numerical scheme that implements reduced order modeling of transient heat transfer problems by enhancing a standard fifinite element code, ABAQUS, and integrating it with proper orthogonal decomposition (POD). The capability of output and manipulation of matrices, the user subroutine for moving heat source and easy enforcement of boundary conditions, and the powerfulness of pre- and post-processing in the commercial software package are leveraged, resulting in a standard and accessible tool for POD analysis.
Electron beam melting (EBM) is a metal powder bed fusion additive manufacturing (AM) technology that is widely used for making three-dimensional (3D) objects by adding materials layer by layer. EBM is a very complex thermal process which involves several physical phenomena such as moving heat source, material state change, and material deposition. Conventionally, these phenomena are implemented using in-house codes or embedding some user subroutines in commonly used commercial software packages, like Abaqus, which generally requires considerable expertise.
When a soft mechanical metamaterial, consisting of a regular array of representative volume elements (RVE), is stressed up to a large strain, the delicately tailored behavior of the RVE does not prevail in the metamaterial due to boundary effect and manufacturing imperfections. A metamaterial sheet comprising RVEs designed for snapping-back behavior exhibits random snapping-through instability when uniaxially stretched. We conceptualize that loss of representativeness of RVE can be avoided by introducing fibre reinforcement to regulate boundary conditions.
This paper describes a data-driven approach to predict mechanical properties of auxetic kirigami metamaterials with randomly oriented cuts. The finite element method (FEM)was used to generate datasets, the convolutional neural network (CNN) was introduced to train these data, and an implicit mapping between the input orientations of cuts and the output Young’s modulus and Poisson’s ratio of the kirigami sheets was established. With this input–output relationship in hand, a quick estimation of auxetic behavior of kirigami metamaterials is straightforward.
