Material Design And Performance Study Of HGMs/EP Syntactic Foams

The syntactic foams is a kind of new functional composites, it has been used in quitly widespread, such as insulation material, lightweight high strength sandwich materials, anti-vibration packaging materials, aircraft sound-absorbing materials, the core of compound interlayer board, the raw materials of hull exteriors, amphibious tanks pontoon, underwater device components and floating pieces, etc. For these various application environments and conditions, the syntactic foams must have material performance presents, such as low density, high strength, impact resistance, resistance to crack expansibility, good stability, low water-absorbing, oil and solvent resistance, etc. It was the focus to design and preparation of strong applicability of syntactic foams in this study.Firstly, Uniform Design (UD) method was employed to formulate the configuration scheme of syntactic foams. It was selected through many experiment design methods. The main raw material of syntactic foams, such as hollow glass micro-particulates (HGMs), curing agent, plasticizer and coupling agent, was selected as stay examines factors, and was divided into a number of levels.Then, the syntactic foams and samples was prepared. The UD can complete the realize analysis of multiple factors and more levels in short time.Secondly, the theoretical formula of density was derived of syntactic foams and the computed values were compared with the measureds. The water abosorbtion of syntactic foams was tested according to the related standard, and reference to this test, another scheme of resistant the acid and alkali and seawater corrode was done.Thirdly, scanning electron microscopyusing (SEM) was employed to observe surfaces of the syntactic foams specimens after soaking in long-term various liquid environment. And the morphology of this surface was analysised resistance performance evaluation, The fracture morphology was analysised and the destruction mechanism of syntactic foams was inferenced.Fourthly, the mechanics pereformence of syntactic foams, such as tensile strength, compression strength and elastic modulus and specific strength and modulus, were tested through quasi-static force test. Though the dynamic mechanical testing, it was obtained that the DMA curve, glass transition temperature, energy-storage modulus and the loss factor affecting performance indicators. Then, the properties of various factors was analyzed and appraised, and the micromechanics model of effective modulus was used to forecast the Young's modulus of syntactic foams.Fively, Back Propagation Neutral Network (BP) and Radial Basis Function Neural Network (RBF) back, socalled artificial intelligence method, were applied to forcast the tensile strength, compression strength and elastic modulus of syntactic foams. -index Prediction of them, single, double and both was taken. For The ability of the two kinds of neural network for predictive and generalization ability was compared analysis. This proved that the artificial intelligence method could be applicated to the performance prediction of syntactic foams, feasibly and reliably.Finally, the configuration schemes were optimizated by the UD and the genetic algorithm (GA). The objective function were tensile strength, compression strength and elastic modulus. Stepwise regression analysis method was used in UD. The optimization results of them were compared and analyzed.