1. Introduction Adiabatic pumping, a transport phenomenon induced by quasi-static periodic parameter driving, has attracted significant interest since it was first proposed by Thouless. 1) In the field of mesoscopic physics, electron turnstile and pumping were studied both theoretically and experimentally by a number of researchers. 2 – 6) For electronic transport via non-interacting quantum Parameter optimization was conducted using a generalized least square method for the entire growth cycles for all PPDs and years. Data from in situ plant digitization were used to establish geometrical symbol files for organs that were then applied to translate model output directly into 3-D representation for each time step of the model execution.

2020/2/3After the multiple-parameter optimization, the cell voltage could be improved by 0.1 V with respect to that in the case of the conventional electrode architecture. In summary, the simultaneous optimization of the electrode and channel parameters is essential for designing the optimal fibrous electrode and flow field and hence realizing further improvements in the performance of RFBs.

The focus of this paper is to locating the precise position of strain gauge on the sensor's substrate using geometrical parameters of the substrate. We used the program Autodesk Simulation Multiphysics 2012 student edition for modeling and finite

2019/11/13Geometrical and material parameter variations used to obtain these new solutions may also be constrained by technological limitations. In a classical process, the design would be realized by experts using tools and methodologies that have been developed over the years.

parameter values will be optimized and where as in tolerance design, tolerances will be determined and analyzed for optimal values set by parameter design [22-24]. The method of optimization cycles allows expanding the number of optimized

Energies 2020, 13, 5164 3 of 18 geometrical parameters, the trained neuron network then served as the direct solution provider and outputs numerical information of the indicated power output and the thermal efficiency of the engine. On the other hand, an objective

2015/6/7Introduction Geometric programming was introduced in 1967 by Duffin, Peterson and Zener. It is very useful in the applications of a variety of optimization problems, and falls under the general class of signomial problems[1]. It can be used to solve large scale

2020/10/23The optimal geometrical parameter scheme of magnetic drive coupling was obtained, and the magnetic performance of the optimal geometrical parameter model was studied experimentally. The geometrical parameters of the optimal scheme of magnetic drive coupling are internal radius of magnet r = 80 mm, thickness of permanent magnet tm = 8 mm, axial length Lb = 144 mm, and thickness of

Optimization techniques are regularly used in geophysical parameter estimation problems. Given a set of geophysical measurements, e.g. seismic recordings, it is common to solve for the physical properties and geometrical shapes of the underlying rocks and fluids.

Geometrical Optimization of Pumping Power under Adiabatic Parameter Driving Hasegawa, Masahiro; Kato, Takeo Abstract Adiabatic pumping is a fundamental concept in the time-dependent transport of To maximize pumping performance, i.e., the amount of

2020/10/1A prediction model of the crusher performances is established, then, multi-objective optimization of the crusher performance is performed, and the optimized values of the MSA, CA, EA, and MSS are 13, 14, 0.29, and 129.63 rpm, respectively.

Optimization techniques are regularly used in geophysical parameter estimation problems. Given a set of geophysical measurements, e.g. seismic recordings, it is common to solve for the physical properties and geometrical shapes of the underlying rocks and fluids.

Convex Optimization — Boyd Vandenberghe 4. Convex optimization problems • optimization problem in standard form • convex optimization problems Optimization problem in standard form minimize f 0(x) subject to fi(x) ≤ 0, i = 1,,m hi(x) = 0, i = 1,,p • x ∈ Rn is the optimization variable

2015/6/7Geometric programming was introduced in 1967 by Duffin, Peterson and Zener. It is very useful in the applications of a variety of optimization problems, and falls under the general class of signomial problems[1]. It can be used to solve large scale, practical

The scaledown of magnetic tunnel junctions (MTJ) and related nanoscale spintronics devices poses unique challenges for energy optimization of their performance. We demonstrate the dependence of the switching current on the scaledown variable, while considering the influence of geometric parameters of MTJ, such as the free layer thickness, tSUBfree/SUB, lateral size of the MTJ, w, and the

2015/12/24In this blog post, we will introduce the concept of shape optimization for adjusting part dimensions by using analytic sensitivity methods. If you have a single objective function that you want to improve, a set of geometric parameters that you want to change, as well

This paper presents a new edge blunting method of the three screw pump rotor with an elliptic arc and equations of the rotor profile after edge blunting. Through comparisons of different geometrical parameters of the pump, i.e., flow area, contact line length per lobe

Moreover, each parameter combination requires a separate setting of the overall system and the control strategy which makes it even more difficult to achieve an optimal solution. Therefore IAV developed very detailed geometrical and physical based simulation models for different types of refrigerant compressors, heat exchangers and expansion valves.

276 IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, VOL. 52, NO. 1, JANUARY 2004 Fast Parameter Optimization of Large-Scale Electromagnetic Objects Using DIRECT with Kriging Metamodeling Eng Swee Siah, Student Member, IEEE, Micheal Sasena, John L. Volakis, Fellow, IEEE, Panos Y. Papalambros,

The scaledown of magnetic tunnel junctions (MTJ) and related nanoscale spintronics devices poses unique challenges for energy optimization of their performance. We demonstrate the dependence of the switching current on the scaledown variable, while considering the influence of geometric parameters of MTJ, such as the free layer thickness, tSUBfree/SUB, lateral size of the MTJ, w, and the

Topology Optimization of Distributed Parameter Systems Peter W. Christensen, Anders Klarbring Pages 179-201 Back Matter concrete geometrical optimization shape optimization sizing optimization structural optimizastion structure topology optimization

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