An optimal control problem governed by a class of multisolution semilinear elliptic equations is studied in this paper. It is pointed out that the control domain and cost functional are nonconvex. By analyzing the max...
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An optimal control problem governed by a class of multisolution semilinear elliptic equations is studied in this paper. It is pointed out that the control domain and cost functional are nonconvex. By analyzing the maximum condition for an optimal relaxed control, one nonexistence and some existence results of an optimal pair are obtained. The idea of using relaxed controls is mainly derived from the paper (Lou, 2007) by Lou where a linear and well-posed controlled system was considered. The present paper is mainly devoted to discussing the case not contained in Lou (2007). (c) 2015 Elsevier Ltd. All rights reserved.
Designing micro-electro-mechanical system (MEMS) sensors to meet specific performance requirements is essential. Traditional approaches, which rely heavily on expert knowledge and extensive finite-element simulations,...
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Designing micro-electro-mechanical system (MEMS) sensors to meet specific performance requirements is essential. Traditional approaches, which rely heavily on expert knowledge and extensive finite-element simulations, are often time-consuming. Current deep learning (DL) methods in MEMS design typically focus on finding a single feasible solution, neglecting the need to generate multiple solutions simultaneously, which is critical in practical design scenarios. This article presents a methodology to address these limitations, introducing a hybrid network called the conditional variational autoencoder (VAE) and generative adversarial network (CVAE-GAN), along with a multisolution generator (G-MS). The CVAE-GAN enables high-accuracy Picturesistive acceleromete 4450 Desired Multi-solution Hosctural para 772 performance generator (G-MS) Multiple candidate solutions and high-efficiency inverse design, while the G-MS, with its tailored noise updating strategy, generates multiple distinct feasible solutions for given performance criteria. This methodology has been experimentally validated on a piezoresistive MEMS accelerometer, finding the second solution in 3.60 +/- 2.46 s, with a normalized distance of 0.75 +/- 0.19, improving the existing method as much as 3.63x and 7.19x, respectively. While traditional methods struggle to find more than two solutions, our G-MS can continuously output solutions according to the specified number, with the time taken to find each solution remaining nearly constant. This approach demonstrates the capability to quickly generate multiple accurate structural parameters based on desired performance, showcasing significant potential and providing valuable insights for MEMS sensor design.
Supercritical fluids (SCFs) become more and more important in various engineering applications. In nuclear power systems, SCFs are considered as coolant of the reactor core such as the supercritical water-cooled react...
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Supercritical fluids (SCFs) become more and more important in various engineering applications. In nuclear power systems, SCFs are considered as coolant of the reactor core such as the supercritical water-cooled reactor (SCWR), superconducting magnets and blankets in the fusion reactors, or as fluid in the energy conversion systems of the next generation nuclear reactors. Accurate determination of heat transfer and the temperature of the structural material (e.g., fuel rod cladding) is of crucial importance for the system design. Thus, extensive studies on heat transfer to SCFs have been carried out in the past five decades and are still ongoing worldwide. However, no breakthrough is recognized or expected in the near future. In this paper, the status, main challenges, and future R&D needs are briefly reviewed. Three aspects are taken into consideration, i.e., experimental studies, numerical analysis, and model development for the prediction of heat transfer coefficient (HTC). Several key challenges and also the important subjects of the future R&D needs are identified. They are (a) data base for turbulence quantities, (b) multisolution of wall temperature, (c) extensive Reynolds-averaged Navier-Stokes (ERANS) method, and (d) new prediction method for HTC.
In this paper,the authors study an optimal control problem governed by a class of multistateordinary differential equations in the absence of *** overcome the difficulty that thecorresponding approximate optimal contr...
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In this paper,the authors study an optimal control problem governed by a class of multistateordinary differential equations in the absence of *** overcome the difficulty that thecorresponding approximate optimal control problem may have no solution,relaxed controls are *** the help of relaxation theory,Pontryagin's maximum principle for the optimal pairs ofthe original control problem is *** the end of this paper,the authors discuss the applicationof the maximum principle by an example.
Multiple solutions exist in many experimental situations where several interfering amplitudes are summed to fit experimentally measured distributions, such as cross sections, mass spectra, and/or angular distributions...
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Multiple solutions exist in many experimental situations where several interfering amplitudes are summed to fit experimentally measured distributions, such as cross sections, mass spectra, and/or angular distributions. We show a few examples where multiple solutions are found, but only one solution is reported in publications. Since there is no standard rule for choosing one among the solutions as the physics one, we propose a simple rule that agrees with what has been adopted in previous literature: the solution corresponding to the minimal magnitudes of the amplitudes must be the physical solution. We suggest testing this rule in future analyses.
The use of multi-formalism techniques is very appealing in modeling complex systems since they allow for building of complex models by integrating or composing sub-models specified by different formalisms. Hence, the ...
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ISBN:
(纸本)9789639799004
The use of multi-formalism techniques is very appealing in modeling complex systems since they allow for building of complex models by integrating or composing sub-models specified by different formalisms. Hence, the most suitable formalism may be used according to the evaluation goals, the level of abstraction of the sub-models and the nature of the sub-systems. Each formalism is usually coupled with efficient solution methods, thus multi-solution approaches are needed to solve multi-formalism models whose analysis involves different techniques and tools. In this paper the software architecture of the OsMoSys Multi-solution Framework (OMF) is presented. OMF was born to provide the support needed to allow for loosely coupled cooperation among heterogeneous analysis techniques and tools, and automates the tasks that must be performed to solve complex multiformalism models. OMF does not require that heterogeneous models are translated into a common formalism in order to be solved, nor that the available tools are modified to be integrated in the framework, but it achieves multisolution by orchestration.
This paper give a method to compress image data on the basis of wavelet analyze. The resolution coefficient has been well *** method take the respective characteristic of three high-frequency part into ***,it overcome...
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ISBN:
(纸本)7505338900
This paper give a method to compress image data on the basis of wavelet analyze. The resolution coefficient has been well *** method take the respective characteristic of three high-frequency part into ***,it overcomes some shortcomings of international standard still image compression method(JPEG protocol).
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