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Composite Tape-Spring Hinge (CTSH) is one of the basic components of space deployable structures achieving large-scale deployable mechanisms for various space missions. It is crucial to obtain the lamina parameters of the composite at the design stage to ensure that the CTSH possesses the required structural response. This work presents a strategy for extracting lamina parameters from structural response of CTSH based on optimization method. An efficient Artificial Neural Network (ANN)-based surrogate model is integrated into the optimization loop to replace the time-costing finite element simulation and establish the relationship between lamina parameters and bending response of CTSH. The inverse characterization process is achieved by minimizing the objective function defined as the error between the predefined target and output results from ANN model. The efficiency of the proposed strategy was validated by using a predefined bending moment-angle curve of CTSH with known lamina parameters, and an arbitrary bending moment-angle curve was inversely constructed to further demonstrate the capability in inverse design. It is shown that the proposed method can be applied not only to extract lamina parameters from structural response, but also to guide the selection of composite lamina based on the expected structural response of deployable structures. [ABSTRACT FROM AUTHOR]

Fiber-modified asphalt has excellent road performance, but the mechanism of this enhancement still requires deeper understanding. Herein, the interfacial interaction between fibers and asphalt is explored using an adsorption kinetic model with the adsorption of fibers on the four components of asphalt as a criterion. The proposed pseudo-first-order kinetic model and pseudo-second-order kinetic model were developed using aramid fibers (AF) and AF-polydopamine (PDA)-octadecylamine (ODA) (AF-PDA-ODA), which were prepared by grafting ODA onto AF with PDA and nacre fibers and molybdenum disulfide (MoS2). Fourier-transform infrared (FT-IR) spectroscopy analysis confirmed that the modified fibers exhibit physical and chemical cross-linking with the four components of asphalt, which facilitated the uniform distribution of fiber and effectively improved its compatibility with asphalt. This led to the formation of an excellent network structure that consequently boosted the rheological properties of the modified-fiber-incorporated asphalt. [ABSTRACT FROM AUTHOR]

The recently emerged data-driven dynamic mode decomposition (DMD) method was employed to investigate the free surface sloshing dynamics of a partially filled rigid tank excited by horizontal harmonic motions. The volume of fluid algorithm was adopted for liquid–gas free surface tracking, and DMD was utilized for decomposition with physical interpretations of the DMD modes and the eigenvalues. Our results demonstrate that DMD works well for both data reconstruction and future-state prediction in terms of either free surface profiles or the sloshing pressure exerted on the rigid wall. DMD presents an efficient and versatile approach for accelerated reduced-order modeling and future-state forecasting. Our efforts provide the first reference on use of DMD for free surface sloshing problems to the best knowledge of the authors. We publicly share our data and codes for all the implementation. [ABSTRACT FROM AUTHOR]