• Journal of Magnetics
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• v.20 no.2
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• pp.161-165
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• 2015

The Permanent Magnet Brushless DC (PMBLDC) motors have been used in modern industrial factories, hazardous chemical process, modern medical devices, and especially in advanced military devices such as army drones. By considering their sensitive role in the industrial and military applications, their optimal design has a real concern. This paper proposes a method for optimal eco-design of a PMBLDC motor using improved tabu search optimization. The objective function is based on losses, volume and cost. Electrical and mechanical requirements and other limitations are combined into constraints of problem. Also, finite element analysis has been used for verifications in magnetic mode.

• Structural Engineering and Mechanics
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• v.50 no.3
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• pp.323-347
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• 2014

This paper proposes a Particle Swarm Optimization (PSO) algorithm, which is improved by making use of the Harmony Search (HS) approach and called HS-PSO algorithm. A computer code is developed for optimal sizing design of non-linear steel frames with various semi-rigid and rigid beam-to-column connections based on the HS-PSO algorithm. The developed code selects suitable sections for beams and columns, from a standard set of steel sections such as American Institute of Steel Construction (AISC) wide-flange W-shapes, such that the minimum total cost, which comprises total member plus connection costs, is obtained. Stress and displacement constraints of AISC-LRFD code together with the size constraints are imposed on the frame in the optimal design procedure. The nonlinear moment-rotation behavior of connections is modeled using the Frye-Morris polynomial model. Moreover, the P-${\Delta}$ effects of beam-column members are taken into account in the non-linear structural analysis. Three benchmark design examples with several types of connections are presented and the results are compared with those of standard PSO and of other researches as well. The comparison shows that the proposed HS-PSO algorithm performs better both than the PSO and the Big Bang-Big Crunch (BB-BC) methods.

• Nuclear Engineering and Technology
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• v.49 no.6
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• pp.1358-1367
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• 2017

The data integration with modeled predictions (DIMP) model is a promising inverse radiation transport method for solving the special nuclear material (SNM) holdup problem. Unlike previous methods, DIMP is a completely passive nondestructive assay technique that requires no initial assumptions regarding the source distribution or active measurement time. DIMP predicts the most probable source location and distribution through Bayesian inference and quasi-Newtonian optimization of predicted detector responses (using the adjoint transport solution) with measured responses. DIMP performs well with forward hemispherical collimation and unshielded measurements, but several considerations are required when using narrow-view collimated detectors. DIMP converged well to the correct source distribution as the number of synthetic responses increased. DIMP also performed well for the first experimental validation exercise after applying a collimation factor, and sufficiently reducing the source search volume's extent to prevent the optimizer from getting stuck in local minima. DIMP's simple point detector response function (DRF) is being improved to address coplanar false positive/negative responses, and an angular DRF is being considered for integration with the next version of DIMP to account for highly collimated responses. Overall, DIMP shows promise for solving the SNM holdup inverse problem, especially once an improved optimization algorithm is implemented.

• Smart Structures and Systems
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• v.11 no.3
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• pp.241-259
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• 2013

This paper presents the optimum load-speed diagram evaluation for a linear micromotor, including multitude cantilever piezoelectric bimorphs, briefly. Each microbeam in the mechanism can be actuated in both axial and flexural modes simultaneously. For this design, we consider quasi-static and linear conditions, and a relatively new numerical method called the smoothed finite element method (S-FEM) is introduced here. For this purpose, after finding an optimum volume fraction for piezoelectric layers through a standard numerical method such as quadratic finite element method, the relevant load-speed curves of the optimized micromotor are examined and compared by deterministic topology optimization (DTO) design. In this regard, to avoid the overly stiff behavior in FEM modeling, a numerical method known as the cell-based smoothed finite element method (CS-FEM, as a branch of S-FEM) is applied for our DTO problem. The topology optimization procedure to find the optimal design is implemented using a solid isotropic material with a penalization (SIMP) approximation and a method of moving asymptotes (MMA) optimizer. Because of the higher efficiency and accuracy of S-FEMs with respect to standard FEMs, the main micromotor characteristics of our final DTO design using a softer CS-FEM are substantially improved.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.4
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• pp.120-127
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• 2009

Spindle units of machine tool are very important part in the manufacturing area. Recently high speed machining has become the main issue of metal cutting. To develop high speed machine tools, a lot of studies have been carried out for high speed spindle. Due to increase of the rotational speed of the spindle, there has been renewal of interest in vibration of spindle. This paper concerns the improvement of spindle design using design of experiments. To improve the design of critical speed and weight of spindle, the experiments using central composite method have been carried out. The targets are critical speed and weight of spindle. For optimization of critical speed and weight and optimization of only critical speed by operation of all area search through response optimizer, the result of analysis has improved design of each factor. Finite element analyses are performed by using the commercial codes ARMD, CATIA V5 and ANSYS workbench. From the results, it has been shown that the proposed method is effective for modification of spindle design to improve critical speed and weight.

• Mass Spectrometry Letters
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• v.1 no.1
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• pp.21-24
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• 2010

The development of clinical biomarkers involves discovery, verification, and validation. Recently, multiple reaction monitoring (MRM) coupled with stable isotope dilution mass spectrometry (IDMS) has shown considerable promise for the direct quantification of proteins in clinical samples. In particular, multiple biomarkers have been tracked in a single experiment using MRM-based MS approaches combined with liquid chromatography. We report here a highly reproducible, quantitative, and dynamic MRM system for validating multi-biomarker proteins using Nanoflow HPLC-Microfluidics Chip/Triple-Quadrupole MS. In this system, transitions were acquired only during the retention window of each eluting peptide. Transitions with the highest MRM-MS intensities for the five target peptides from colon cancer biomarker candidates were automatically selected using Optimizer software. Relative to the corresponding non-dynamic system, the dynamic MRM provided significantly improved coefficients of variation in experiments with large numbers of transitions. Linear responses were obtained with concentrations ranging from fmol to pmol for five target peptides.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.4
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• pp.436-442
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• 2016

An electroencephalogram (EEG)-connectome processor to monitor and diagnose mental health is proposed. From 19-channel EEG signals, the proposed processor determines whether the mental state is healthy or unhealthy by extracting significant features from EEG signals and classifying them. Connectome approach is adopted for the best diagnosis accuracy, and synchronization likelihood (SL) is chosen as the connectome feature. Before computing SL, reconstruction optimizer (ReOpt) block compensates some parameters, resulting in improved accuracy. During SL calculation, a sparse matrix inscription (SMI) scheme is proposed to reduce the memory size to 1/24. From the calculated SL information, a small world feature extractor (SWFE) reduces the memory size to 1/29. Finally, using SLs or small word features, radial basis function (RBF) kernel-based support vector machine (SVM) diagnoses user's mental health condition. For RBF kernels, look-up-tables (LUTs) are used to replace the floating-point operations, decreasing the required operation by 54%. Consequently, The EEG-connectome processor improves the diagnosis accuracy from 89% to 95% in Alzheimer's disease case. The proposed processor occupies $3.8mm^2$ and consumes 1.71 mW with $0.18{\mu}m$ CMOS technology.

• Journal of the Korean Society of Propulsion Engineers
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• v.6 no.2
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• pp.65-74
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• 2002

Optimal supersonic diffuser shape of integrated rocket ramjet engine was derived which maximizes the total pressure recovery. Mass flux is considered as a design constraint and the second oblique shock angle of the external ramp, the cowl-lip angle and the throat area are selected as design variables. Refined response surface method through design space transformation technique was developed and employed, and high confidence level of the regression model could be obtained. Genetic algorithm was implemented for both system optimizer and subspace regression model optimization. Virtual nozzle was located at the end of throat to adjust the back pressure. With only 20 aerodynamic analyses, optimal supersonic diffuser shape which has 14% improved total pressure recovery characteristics was successfully designed.

• Steel and Composite Structures
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• v.43 no.5
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• pp.625-637
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• 2022

Axial compression capacity (P_u) is a significant yet complex parameter of concrete-filled steel tube (CFST) columns. This study offers a novel ensemble tool, adaptive neuro-fuzzy inference system (ANFIS) supervised by equilibrium optimization (EO), for accurately predicting this parameter. Moreover, grey wolf optimization (GWO) and Harris hawk optimizer (HHO) are considered as comparative supervisors. The used data is taken from earlier literature provided by finite element analysis. ANFIS is trained by several population sizes of the EO, GWO, and HHO to detect the best configurations. At a glance, the results showed the competency of such ensembles for learning and reproducing the P_u behavior. In details, respective mean absolute errors along with correlation values of 4.1809% and 0.99564, 10.5947% and 0.98006, and 4.8947% and 0.99462 obtained for the EO-ANFIS, GWO-ANFIS, and HHO-ANFIS, respectively, indicated that the proposed EO-ANFIS can analyze and predict the behavior of CFST columns with the highest accuracy. Considering both time and accuracy, the EO provides the most efficient optimization of ANFIS and can be a nice substitute for experimental approaches.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.10
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• pp.8-16
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• 1999

This paper presents a new simulation-based analog cell synthesis approach with improved simulation efficiency For the hierarchical synthesis of analog cells we developed the sub-circuit optimizers such as current mirror and differential input stage. Each sub-circuit optimizer can be used for synthesis of analog cells such as OTA(operational transconductance amplifier), 2-stage OP-AMP and comparator. To reduce the time spending of the simulation-based synthesis we propose 2-stage searching scheme and simulation data reusing scheme. With those schemes the synthesis time spending of OTA was reduced from 301.05sec to 56.52sec by 81.12%. Since our synthesis system doesn't need other additional physical parameters except SPICE parameters, and is independent of the process and its model level, the time spending to port to other process is minimized. We synthesized OTA and 2-stage OP-AMP respectively with our approach to show its usefulness.