The influence of different nanoparticle sizes on the elastic modulus and the fatigue properties of epoxy/SiO_(2) nanocomposite is studied in this ***,the cross-linked epoxy resins formed by the combination of DGEBA an...
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The influence of different nanoparticle sizes on the elastic modulus and the fatigue properties of epoxy/SiO_(2) nanocomposite is studied in this ***,the cross-linked epoxy resins formed by the combination of DGEBA and 1,3-phenylenediamine are used as the matrix phase,and spherical SiO_(2) particles are used as the reinforcement *** order to simulate the elastic modulus and long-term performance of the composite material at room temperature,the simulated temperature is set to 298 K and the mass fraction of SiO_(2) particles is set to 28.9%.The applied strain rate is 109/s during the simulation of the elastic *** results show that the elastic modulus of the material increases with the increase in particle ***,fatigue simulation under strain control is performed on the model with SiO_(2) nanoparticle radius of 12˚*** results indicate that the influence trend of variable frequencies on the fatigue mechanical response is similar,and the mean stress decreases with the increase in number of *** addition,the smaller the loading period and the more the number of cycles,the greater the mean stress ***,the change in energy and free volume fraction are evaluated under fatigue loading condition.
Shock responses of Mg-Al-Zn alloy are investigated by the molecular dynamics(MD)*** wave propagation,plastic deformation behavior and failure mechanism along the[0001]and[1010]orientations are *** both orientations,si...
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Shock responses of Mg-Al-Zn alloy are investigated by the molecular dynamics(MD)*** wave propagation,plastic deformation behavior and failure mechanism along the[0001]and[1010]orientations are *** both orientations,simulation results show that the shock wave has an obvious double-wave structure(plastic-elastic)under a piston velocity of 1200 m/s.A higher Hugoniot elastic limit(HEL)is observed for[0001]-oriented *** the shock pressure is along the[1010]direction,the distance between plastic and elastic waves is closer,and higher dislocation density and more twins are ***,the spall strength for[1010]-oriented shock is predicted to be *** addition,the wave interactions,HEL and spall strength predicted for Mg-Al-Zn alloy are compared with the experimental results and MD simulation results of Mg single crystal in the *** is concluded that the shock performance of Mg-Al-Zn is better than that of Mg single crystal.
Most inorganic thermoelectric semiconductors are intrinsically brittle,restricting the application of ther-moelectric ***,developing ductile thermoelectric materials is crucial to thermoelectric technology *** this wo...
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Most inorganic thermoelectric semiconductors are intrinsically brittle,restricting the application of ther-moelectric ***,developing ductile thermoelectric materials is crucial to thermoelectric technology *** this work,single-phase SnTe bulks with dense dislocations were prepared by melting quenching combined with spark plasma *** resulting SnTe thermoelectric materials exhibited a large compressive strain of∼7.5%at room temperature,originating from high-density pre-existing mobile *** initiation of localized slip bands and preferred slip system were also identified by first-principles *** microstructural characterizations reveal that the thermal activated dislocation emission and migration lead to higher compressive strains at intermediate *** 673 K,the deformation mechanism changed from dislocation mediated to grain boundary mediated plasticity,resulting in an ultra-high compressive strain of∼42%.In sum,new insights into the mechanical behavior of SnTe thermoelectric material over a wide range of temperatures were *** work offers the dislocation engineering strategy to design ductile thermoelectric materials for flexi-ble electronics and energy systems.
High-dimensional data streams are ubiquitous in modern manufacturing, due to their ability to provide valuable information about the industrial system’s performance on a real-time basis. If a shift occurs in a produc...
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High-dimensional data streams are ubiquitous in modern manufacturing, due to their ability to provide valuable information about the industrial system’s performance on a real-time basis. If a shift occurs in a production process, fault diagnosis based on the data streams is of critical importance for identifying the root cause. Existing methods have largely focused on controlling the total missed discovery rate without distinguishing missed signals for positive versus negative components of the shift vector. In practice, however, losses incurred from the two directional shifts can differ substantially, so it is desirable to constrain the proportions of missed signals for positive and negative components at two distinctive levels. In this article, we propose a fault classification procedure that controls the two proportions separately. By formulating the problem as Lagrangian multiplier optimization, we show that the proposed procedure is optimal in the sense that it minimizes the expected number of false discoveries. We also suggest an iterative adjustment algorithm that converges to the optimal Lagrangian parameters. The asymptotic optimality for the data-driven version of our procedure is also established. Theoretical justification and numerical comparison with state-of-the-art methods show that the proposed procedure works well in applications.
This paper is devoted to study the proportional reinsurance/new business and investment problem under the mean-variance criterion in a continuous-time *** strategies are constrained in the non-negative cone and all co...
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This paper is devoted to study the proportional reinsurance/new business and investment problem under the mean-variance criterion in a continuous-time *** strategies are constrained in the non-negative cone and all coefficients in the model except the interest rate are stochastic processes adapted the filtration generated by a Markov *** the help of a backward stochastic differential equation driven by the Markov chain,we obtain the optimal strategy and optimal cost explicitly under this non-Markovian regime-switching *** cases with one risky asset and Markov regime-switching model are considered as special cases.
The wetting behavior of molten Cu on the B_(4)C-xTiB_(2)ceramic composites was investigated in this *** results show that the contact angle of molten Cu alloy on B_(4)C-TiB_(2)ceramic composites is linear with the com...
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The wetting behavior of molten Cu on the B_(4)C-xTiB_(2)ceramic composites was investigated in this *** results show that the contact angle of molten Cu alloy on B_(4)C-TiB_(2)ceramic composites is linear with the composition rate of TiB_(2)or B_(4)C while the temperature is in the range of 1300 to 1350℃,consistent with the expectation of the commonly used theoretical ***,a nonlinear relationship between the contact angle and the composition rate unexpectedly occurred at temperatures ranging from 1400 to 1500℃.The big difference of the contact angles between the molten metal and the components in the composites was found to be the key *** result identifies that the commonly used theoretical method only works at a limited difference of the contact angle of the liquid on the different phases in the composites,and fails at a big difference.
Half Heusler materials exhibit excellent thermoelectric and mechanical properties,rendering them potential candidates for advanced thermoelectric ***,the developments on interrelated devices are impeded by their inher...
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Half Heusler materials exhibit excellent thermoelectric and mechanical properties,rendering them potential candidates for advanced thermoelectric ***,the developments on interrelated devices are impeded by their inherent brittleness and limited ***,it exists the potential ductility on half Heusler materials with face-centered cubic sub-lattices through the expectation of the occurrence of shear-induced‘catching bonds’which can result in excellent ductility on other face-centered cubic materials.
This paper develops a new deep learning algorithm to solve a class of finite-horizon mean-field games. The proposed hybrid algorithm uses Markov chain approximation method combined with a stochastic approximation-base...
This paper develops a new deep learning algorithm to solve a class of finite-horizon mean-field games. The proposed hybrid algorithm uses Markov chain approximation method combined with a stochastic approximation-based iterative deep learning algorithm. Under the framework of finite-horizon mean-field games, the induced measure and Monte-Carlo algorithm are adopted to establish the iterative mean-field interaction in Markov chain approximation method and deep learning, respectively. The Markov chain approximation method plays a key role in constructing the iterative algorithm and estimating an initial value of a neural network, whereas stochastic approximation is used to find accurate parameters in a bounded region. The convergence of the hybrid algorithm is proved; two numerical examples are provided to illustrate the results.
We study a multiple-urn version of the Ehrenfest *** this setting,we denote the n urns by Urn l to Urn n,where n≥***,M balls are randomly placed in the n *** each subsequent step,a ball is selected and put into the o...
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We study a multiple-urn version of the Ehrenfest *** this setting,we denote the n urns by Urn l to Urn n,where n≥***,M balls are randomly placed in the n *** each subsequent step,a ball is selected and put into the other n-1 urns with equal *** expected hitting time leading to a change of the M balls'status is computed using the method of stopping *** a corollary,we obtain the expected hitting time of moving all the M balls from Urn 1 to Urn 2.
The paper first analyzes price change due to stock splits in Chinese stock markets,which shows stock prices typically go up for stock *** theoretical analyses based on risk theory are presented to explain the reason,w...
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The paper first analyzes price change due to stock splits in Chinese stock markets,which shows stock prices typically go up for stock *** theoretical analyses based on risk theory are presented to explain the reason,where the method comes from a new perspective and obtained theoretical conclusions show that stock splits typically make stock price go up if risk-compensation function is convex,and go down if risk-compensation function is *** prices typically go up for stock splits because risk-compensation functions are mainly *** obtained conclusions are consistent with the known results in the last three decades.
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