Particle damping, an effective passive vibration control technology, is developing dramatically at the present stage, especially in the aerospace and machinery fields. The aim of this paper is to provide an overview of particle damping technology, beginning with its basic concept, developmental history, and research status all over the world. Furthermore, various interpretations of the underlying damping mechanism are introduced and discussed in detail. The theoretical analysis and numerical simulation, together with their pros and cons are systematically expounded, in which a discrete element method of simulating a multi-degree-of-freedom structure with a particle damper system is illustrated. Moreover, on the basis of previous studies, a simplified method to analyze the complicated nonlinear particle damping is proposed, in which all particles are modeled as a single mass, thereby simplifying its use by practicing engineers. In order to broaden the applicability of particle dampers, it is necessary to implement the coupled algorithm of finite element method and discrete element method. In addition, the characteristics of experimental studies on particle damping are also summarized. Finally, the application of particle damping technology in the aerospace field, machinery field, lifeline engineering, and civil engineering is reviewed at length. As a new trend in structural vibration control, the application of particle damping in civil engineering is just at the beginning. The advantages and potential applications are demonstrated, whereas the difficulties and deficiencies in the present studies are also discussed. The paper concludes by suggesting future developments involving semi-active approaches that can enhance the effectiveness of particle dampers when used in conjunction with structures subjected to nonstationary excitation, such as earthquakes and similar nonstationary random excitations.

Particle impact dampers: Past, present, and future

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A comprehensive review on mechanical, electromagnetic radiation shielding, and thermal conductivity of fibers/inorganic fillers reinforced hybrid polymer composites

A review of multifunctional structure technology for aerospace applications

The ability to 3D print lithium ion batteries (LIBs) in an arbitrary geometry would not only allow the battery form factor to be customized to fit a given product design but also facilitate the use of the battery as a structural component A major hurdle to achieving this goal is the low ionic conductivity of the polymers used for 3D printing This article reports the development of anode, cathode, and separator materials that enable 3D printing of complete lithium ion batteries with low cost and widely available fused filament fabrication (FFF) 3D printers Poly(lactic acid) (PLA) was infused with a mixture of ethyl methyl carbonate, propylene carbonate, and LiClO4 to obtain an ionic conductivity of 0085 mS cm–1, a value comparable to that of polymer and hybrid electrolytes Different electrically conductive (Super P, graphene, multiwall carbon nanotubes) and active (lithium titanate, lithium manganese oxide) materials were blended into PLA to determine the relationships among filler loading, conductivi

Three-Dimensional Printing of a Complete Lithium Ion Battery with Fused Filament Fabrication

A review of recent research on multifunctional composite materials and structures with their applications

Vibration suppression of printed circuit boards using an external particle damper

Test-analysis models are used in the validation of the nite element models of spacecraft structures. Here, a probabilistic approach is used to assess the robustness of a system equivalent reduction expansion process based testanalysis model when experimental and analytical modes contain different levels of inaccuracy. The approach is applied to three spacecraft models, and Monte Carlo simulations were used to determine the sensitivity of the normalized cross-orthogonality check to the system equivalent reduction expansion process reduced matrix. The effect of parameters used in this reduction and the amount of inaccuracies that can be tolerated in the modes before failing the normalized cross-orthogonality check were also determined. The results show that the probability to pass the normalized cross-orthogonality check is highly determined by the number of modes used in the reduction. The relation between capability of the nite element models to predict the frequency-response function and the quality of the model validation determined using normalized cross-orthogonality check is also investigated, and it is observed that the quantities are not always correlated. This study also shows that the sensor locations can be optimally chosen using the system equivalent reduction expansion process reduced mass matrix, and this can increase the probability to pass the normalized cross-orthogonality check.

Robustness of System Equivalent Reduction Expansion Process on Spacecraft Structure Model Validation

Reduction of spacecraft structure mass is an important design goal as it helps to increase the payload fraction, improve agility and also reduce launch cost. The spacecraft is subjected to mechanical loads during launch and thermal loads during on orbit operations. A typical spacecraft contains a main load bearing base structure, which supports all primary payloads and connects the satellite with the launch vehicle. The dimensional stability and tolerance requirements of the payload interfaces are very stringent and there is a need to improve these under the specified thermal environment. This paper explains a novel design consisting of a bonded assembly of metal and laminated composites to achieve a dimensionally stable, low mass base structure without altering the interfaces and overall dynamic behavior of the spacecraft. The design was checked for its performance under all critical loading conditions and was found to meet all requirements including stiffness and stability. Thermal distortion analysis showed that radial distortion is an order of magnitude lower than that of the existing design. The structure was fabricated and it showed compliance to dimensional accuracy requirements. The new base structure weighed 7.54 kg achieving a mass saving of 35% on the existing structure.

Design of low mass dimensionally stable composite base structure for a spacecraft

Particle damping is one of the recent passive damping methods and its relevance in space structural applications is increasing. This paper presents the novel application of a radial basis function (RBF) neural network to accurately predict the modal damping ratio of a particle damping system using system input parameters such as particle size, particle density, packing ratio, and their effect at different modes of vibration. The prediction of particle damping using the RBF neural network is studied in comparison with the back propagation neural (BPN) network on an aluminum alloy beam structure with extensive experimental tests. The prediction accuracy of the RBF neural network is significant with 9.83% error compared to 12.22% obtained by the BPN network for a best case. Limited experiments were also carried out on a mild steel beam to study and compare the trends predicted in earlier studies. The relationships obtained by the proposed method readily provide useful guidelines in the design of particle dam...

K.K. Sairajan

Papers

A review of multifunctional structure technology for aerospace applications

Vibration suppression of printed circuit boards using an external particle damper

Robustness of System Equivalent Reduction Expansion Process on Spacecraft Structure Model Validation

Design of low mass dimensionally stable composite base structure for a spacecraft

Application of RBF neural network in prediction of particle damping parameters from experimental data