• Progress in Superconductivity and Cryogenics
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• v.21 no.1
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• pp.25-30
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• 2019

This paper presents a conceptual design approach of air-cored synchronous machine with high temperature superconductor (HTS) field winding. With a given configuration of a target machine, boundary conditions are set in the cylindrical coordinate system and analytic field calculation is performed by solving a governing equation. To set proper boundary conditions, current distributions of the field winding and the armature winding are expressed by the Fourier expansion. Based on analytic magnetic field calculation results, key machine parameters are calculated: 1) inductance, 2) critical current of field winding, 3) weight, 4) HTS conductor consumption, and 5) efficiency. To investigate all potential design options, 6 sweeping parameters are determined to characterize the geometry of the machine and the parameter calculation process is performed for each design options. Among design options satisfying constraints including >80 % critical current margin and >95 % efficiency, in this paper, a first-cut design was selected in terms of overall machine weight and HTS conductor consumption to obtain a lightweight and economical design. The goal is to design a 5-MW machine by referring to the same capacity machine that was previously constructed by another group. Our design output is compared with finite element method (FEM) simulation to validate our design approach.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.131-135
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• 2021

Numbers of studies related to optimization of design of organic light emitting diodes(OLED) through machine learning are increasing. We propose the generative method of the image to assess the performance of the device combining with machine learning technique. Principle parameter regarding dark spot growth mechanism of the OLED can be the key factor to determine the long-time performance. Captured images from actual device and randomly generated images at specific time and initial pinhole state are fed into the deep neural network system. The simulation reinforced by the machine learning technique can predict the device parameters accurately and faster. Similarly, the inverse design using multiple layer perceptron(MLP) system can infer the initial degradation factors at manufacturing with given device parameter to feedback the design of manufacturing process.

• Geomechanics and Engineering
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• v.21 no.4
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• pp.349-356
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• 2020

Rock brittleness, which is closely related to the failure modes, plays a significant role in the design and construction of many rock engineering applications. However, the brittle-ductile failure transition is mostly ignored by the current statistical damage constitutive model, which may misestimate the failure strength and failure behaviours of intact rock. In this study, a new statistical damage model considering rock brittleness is proposed for brittle to ductile behaviour of rocks using brittleness index (BI). Firstly, the statistical constitutive damage model is reviewed and a new statistical damage model considering failure mode transition is developed by introducing rock brittleness parameter-BI. Then the corresponding damage distribution parameters, shape parameter m and scale parameter F₀, are expressed in terms of BI. The shape parameter m has a positive relationship with BI while the scale parameter F₀ depends on both BI and ε_e. Finally, the robustness and correctness of the proposed damage model is validated using a set of experimental data with various confining pressure.

• Journal of Power Electronics
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• v.17 no.5
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• pp.1298-1307
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• 2017

The constant on-time current-mode controlled (COT-CMC) switching dc-dc converter is stable, with no subharmonic oscillation in its current loop when a voltage ripple in its outer voltage loop is ignored. However, when its output capacitance is small or its feedback gain is high, subharmonic oscillation may occur in a COT-CMC buck converter with a proportional-integral (PI) compensator. To investigate the subharmonic instability of COT-CMC buck converters with a PI compensator, an accurate reduced-order asynchronous-switching map model of a COT-CMC buck converter with a PI compensator is established. Based on this, the instability behaviors caused by output capacitance and feedback gain are investigated. Furthermore, an approximate instability condition is obtained and design-oriented stability boundaries in different circuit parameter spaces are yielded. The analysis results show that the instability of COT-CMC buck converters with a PI compensator is mainly affected by the output capacitance, output capacitor equivalent series resistance (ESR), feedback gain, current-sensing gain and constant on-time. The study results of this paper are helpful for the circuit parameter design of COT-CMC switching dc-dc converters. Experimental results are provided to verify the analysis results.

• Interaction and multiscale mechanics
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• v.5 no.3
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• pp.211-228
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• 2012

This paper reports the development of a generalized inverse analysis formulation for the parameter estimation of four-parameter Burger model. The analysis is carried out by formulating the problem as a mathematical programming formulation in terms of identification of the design vector, the objective function and the design constraints. Thereafter, the formulated constrained nonlinear multivariable problem is solved with the aid of fmincon: an in-built constrained optimization solver module available in MatLab. In order to gain experience, a synthetic case-study is considered wherein key issues such as the determination and setting up of variable bounds, global optimality of the solution and minimum number of data-points required for prediction of parameters is addressed. The results reveal that the developed technique is quite efficient in predicting the model parameters. The best result is obtained when the design variables are subjected to a lower bound without any upper bound. Global optimality of the solution is achieved using the developed technique. A minimum of 4-5 randomly selected data-points are required to achieve the optimal solution. The above technique has also been adopted for real-time settlement of four oil refineries with encouraging results.

• Journal of Hydrogen and New Energy
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• v.35 no.1
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• pp.75-82
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• 2024

In this study, design parameter exploration based on finite element analysis was performed to find the optimal shape of bellows, the key component of compressor-embedded refueling tank for a newly developed hydrogen refueling station capable of high-pressure charging above 900 bar. In the design parametric study, the design variables took into account the bellows shapes such as contour radius and span spacing, and the response factors were set to the maximum stress and the gap in the contact direction. In the shape design of the compressor bellows for hydrogen refueling station considered in this study, it was found that adjusting the contour span is an appropriate design method to improve the compression performance and structural safety. From the selection of optimal design, the maximum stress was reduced to 49% compared to the initial design without exceeding the material yield stress.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.413-435
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• 2018

Although the accuracy of handwritten character recognition based on deep networks has been shown to be superior to that of the traditional method, the use of an overly deep network significantly increases time consumption during parameter training. For this reason, this paper took the training time and recognition accuracy into consideration and proposed a novel handwritten character recognition algorithm with newly designed network structure, which is based on an extended nonlinear kernel residual network. This network is a non-extremely deep network, and its main design is as follows:(1) Design of an unsupervised apriori algorithm for intra-class clustering, making the subsequent network training more pertinent; (2) presentation of an intermediate convolution model with a pre-processed width level of 2;(3) presentation of a composite residual structure that designs a multi-level quick link; and (4) addition of a Dropout layer after the parameter optimization. The algorithm shows superior results on MNIST and SVHN dataset, which are two character benchmark recognition datasets, and achieves better recognition accuracy and higher recognition efficiency than other deep structures with the same number of layers.

• Structural Engineering and Mechanics
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• v.71 no.1
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• pp.45-56
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• 2019

A modified mechanical model of pre-pressed spring self-centering energy dissipation (PS-SCED) brace is proposed, and the hysteresis band is distinguished by the indication of relevant state variables. The MDOF frame system equipped with the braces is formulated in an incremental form of linear acceleration method. A multi-objective genetic algorithm (GA) based brace parameter optimization method is developed to obtain an optimal solution from the primary design scheme. Parameter sensitivities derived by the direct differentiation method are used to modify the change rate of parameters in the GA operator. A case study is conducted on a steel braced frame to illustrate the effect of brace parameters on node displacements, and validate the feasibility of the modified mechanical model. The optimization results and computational process information are compared among three cases of different strategies of parameter change as well. The accuracy is also verified by the calculation results of finite element model. This work can help the applications of PS-SCED brace optimization related to parameter sensitivity, and fulfill the systematic design procedure of PS-SCED brace-structure system with completed and prospective consequences.

• Journal of Power Electronics
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• v.15 no.6
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• pp.1446-1455
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• 2015

This paper illustrates resonant tank design considerations and the implementation of a LLC resonant converter with a wide battery voltage range based on the fundamental harmonic approximation (FHA) analysis. Unlike the conventional design at zero load, the parameter K (the ratio of the transformer magnetizing inductor L_m to the resonant inductor L_r) of the LLC converter in this paper is designed with two charging points, (V_{o_min}, I_{o_max1}) and (V_{o_max}, I_{o_max2}), according to the battery charging strategy. A 2.9kW prototype with an output voltage range of 36V to 72V dc is built to verify the design. It achieves a peak efficiency of 96%.

• Nuclear Engineering and Technology
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• v.53 no.9
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• pp.2960-2967
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• 2021

In this work, a new hardening model is proposed for the depth-dependent hardness of ion-irradiated polycrystals with obvious grain size effect. Dominant hardening mechanisms are addressed in the model, including the contribution of dislocations, irradiation-induced defects and grain boundaries. Two versions of the hardening model are compared, including the linear and square superposition models. A succinct parameter calibration method is modified to parametrize the models based on experimentally obtained hardness vs. indentation depth curves. It is noticed that both models can well characterize the experimental data of unirradiated polycrystals; whereas, the square superposition model performs better for ion-irradiated materials, therefore, the square superposition model is recommended. In addition, the new model separates the grain size effect from the dislocation hardening contribution, which makes the physical meaning of fitted parameters more rational when compared with existing hardness analysis models.