• Structural Engineering and Mechanics
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• v.86 no.3
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• pp.291-309
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• 2023

This paper addresses the finite element modeling of functionally graded porous (FGP) beams for free vibration and buckling behaviour cases. The formulated finite element is based on simple and efficient higher order shear deformation theory. The key feature of this formulation is that it deals with Euler-Bernoulli beam theory with only three unknowns without requiring any shear correction factor. In fact, the presented two-noded beam element has three degrees of freedom per node, and the discrete model guarantees the interelement continuity by using both C⁰ and C¹ continuities for the displacement field and its first derivative shape functions, respectively. The weak form of the governing equations is obtained from the Hamilton principle of FGP beams to generate the elementary stiffness, geometric, and mass matrices. By deploying the isoparametric coordinate system, the derived elementary matrices are computed using the Gauss quadrature rule. To overcome the shear-locking phenomenon, the reduced integration technique is used for the shear strain energy. Furthermore, the effect of porosity distribution patterns on the free vibration and buckling behaviours of porous functionally graded beams in various parameters is investigated. The obtained results extend and improve those predicted previously by alternative existing theories, in which significant parameters such as material distribution, geometrical configuration, boundary conditions, and porosity distributions are considered and discussed in detailed numerical comparisons. Determining the impacts of these parameters on natural frequencies and critical buckling loads play an essential role in the manufacturing process of such materials and their related mechanical modeling in aerospace, nuclear, civil, and other structures.

• Structural Engineering and Mechanics
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• v.86 no.1
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• pp.119-137
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• 2023

The purpose of this research is to assess the performance of CBN and ceramic tools during the dry turning of gray cast iron EN GJL-350. During the turning operation, the variable machining parameters are cutting speed, feed rate, depth of cut and type of the cutting material. This contribution consists of two sections, the first one deals with the performance evaluation of four materials in terms of evolution of flank wear, surface roughness (2D and 3D) and cutting forces. The focus of the second section is on statistical analysis, followed by modeling and optimization. The experiments are conducted according to the Taguchi design L₃₂ and based on ANOVA approach to quantify the impact of input factors on the output parameters, namely, the surface roughness (Ra), the cutting force (Fz), the cutting power (Pc), specific cutting energy (Ecs). The RSM method was used to create prediction models of several technical factors (Ra, Fz, Pc, Ecs and MRR). Subsequently, the desirability function approach was used to achieve a multi-objective optimization that encompasses the output parameters simultaneously. The aim is to obtain optimal cutting regimes, following several cases of optimization often encountered in industry. The results found show that the CBN tool is the most efficient cutting material compared to the three ceramics. The optimal combination for the first case where the importance is the same for the different outputs is Vc=660 m/min, f=0.116 mm/rev, ap=0.232 mm and the material CBN. The optimization results have been verified by carrying out confirmation tests.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1422-1431
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• 2015

The reliability of power system components can be affected by a numbers of factors such as the health level of components, external environment and operation environment of power systems. These factors also affect the electrical parameters of power system components for example the thermal capacity of a transmission element. The relationship of component reliability and power system is, therefore, a complex nonlinear function related to the above-mentioned factors. Traditional approaches for reliability assessment of power systems do not take the influence of these factors into account. The assessment results could not, therefore, reflect the short-term trend of the system reliability performance considering the influence of the key factors and provide the system dispatchers with enough information to make decent operational decisions. This paper discusses some of these important operational issues from the perspective of power system reliability. The discussions include operational reliability of power systems, reliability influence models for main performance parameters of components, time-varying reliability models of components, and a reliability assessment algorithm for power system operations considering the time-varying characteristic of various parameters. The significance of these discussions and applications of the proposed techniques are illustrated by case study results using the IEEE-RTS.

• International Journal of Industrial Entomology and Biomaterials
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• v.14 no.1
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• pp.45-50
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• 2007

Ethanol extract of 20 botanicals in 3 concentrations i.e., 2.5%, 5% and 10% were evaluated for their efficacy to improve reproductive performance of mulberry silkworm (Bombyx mod L.) through feeding botanical enriched mulberry leaves during $2^{nd}$ day of $4^{th}$ age as well as $1^{st}$ and $3^{rd}$ day of $5^{th}$ age larvae. The preliminary screening was done by ranking the botanicals based on influence in most important reproductive contributing parameters such as single cocoon weight, effective rate of rearing, pupation rate, fecundity and recovery of eggs/kg cocoon. Five botanicals viz., Asparagus recemosus, Achyranthes aspera, Tribulus terrestris, Withania somnifera, Parthenium histerophorus ranked first were further evaluated at 8% 5% and 3% concentrations to confirm their effectiveness and standardize effective concentration. Among the rearing parameters, mature larval weight, shell ratio and number of cocoons/kg were not significantly influenced by the treatments. However, reproductive parameters such as effective rate of rearing (wt), pupation rate (%), fecundity (No.) and egg recovery (g)/kg cocoon were significantly (P<0.05) influenced by the botanicals. Higher fecundity and egg recovery were obtained on treatment with Withania somnifera irrespective of concentrations. However at 5% concentration, pupation rate, fecundity as well as egg recovery were found significantly higher than that of other concentrations, confirming its effectiveness for improving reproductive efficiency.

• Geomechanics and Engineering
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• v.22 no.6
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• pp.489-496
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• 2020

This study proposes a new empirical model to effectively predict the excavation performance of a shield tunnel boring machine (TBM). The TBM performance is affected by the geological and geotechnical characteristics as well as the machine parameters of TBM. Field penetration index (FPI) is correlated with rock mass parameters to analyze the effective geotechnical parameters influencing the TBM performance. The result shows that RMR has a more dominant impact on the TBM performance than UCS and RQD. RMR also shows a significant relationship with the specific energy, which is defined as the energy required for excavating the unit volume of rock. Therefore, the specific energy can be used as an indicator of the mechanical efficiency of TBM. Based on these relationships with RMR, this study suggests an empirical performance prediction model to predict FPI, which can be derived from the correlation between the specific energy and RMR.

• Steel and Composite Structures
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• v.37 no.5
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• pp.517-532
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• 2020

This paper firstly developed a new type of Double Skin Composite (DSC) beams using novel enhanced C-channels (ECs). The shear behaviour of novel ECs was firstly studied through two push-out tests. Eleven full-scale DSC beams with ECs (DSCB-ECs) were tested under four-point loading to study their ultimate strength behaviours, and the studied parameters were thickness of steel faceplate, spacing of ECs, shear span, and strength of concrete core. Test results showed that all the DSCB-ECs failed in flexure-governed mode, which confirmed the effective bonding of ECs. The working mechanisms of DSCB-ECs with different parameters were reported, analysed and discussed. The load-deflection (or strain) behaviour of DSCB-ECs were also detailed reported. The effects of studied parameters on ultimate strength behaviour of DSCB-ECs have been discussed and analysed. Including the experimental studies, this paper also developed theoretical models to predict the initial stiffness, elastic stiffness, cracking, yielding, and ultimate loads of DSCB-ECs. Validations of predictions against 11 test results proved the reasonable estimations of the developed theoretical models on those stiffness and strength indexes. Finally, conclusions were given based on these tests and analysis.

• Smart Structures and Systems
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• v.25 no.6
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• pp.657-668
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• 2020

A novel multistage approach is developed for structural model updating based on sensitivity ranking of the selected updating parameters. Modal energy-based sensitivities are formulated, and maximum-normalized indices are designed for sensitivity ranking. Based on the ranking strategy, a multistage approach is proposed, where these parameters to be corrected with similar sensitivity levels are updated simultaneously at the same stage, and the complete procedure continues sequentially at several stages, from large to small, according to the predefined levels of the updating parameters. At every single stage, a previously developed cross model cross mode (CMCM) method is used for structural model updating. The effectiveness and robustness of the multistage approach are investigated by implementing it on an offshore structure, and the performances are compared with non-multistage approach using numerical and experimental vibration information. These results demonstrate that the multistage approach is more effective for structural model updating of offshore platform structures even with limited information and measured noise. These findings serve as a preliminary strategy for structural model updating of an offshore platform in service.

• ETRI Journal
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• v.46 no.2
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• pp.333-346
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• 2024

Various techniques for noninvasively focus microwave energy on lesions have been proposed for thermotherapy. To focus the microwave energy on the lesion, a focusing parameter, which is referred to as the magnitude and phase of microwaves radiated from an external array antenna, is very important. Although the finite-difference time-domain (FDTD)-based time-reversal (TR) focusing algorithm is widely used, it has a long processing time if the focusing target position changes or if optimization is needed. We propose a technique to obtain multistatic data (MSD) based on Green's function and use it to derive the focusing parameters. Computer simulations were used to evaluate the electric fields inside the object using the FDTD method and Green's function as well as to compare the focusing parameters using FDTD- and MSD-based TR focusing algorithms. Regardless of the use of Green's function, the processing time of MSD-based TR focusing algorithms reduces to approximately 1/2 or 1/590 compared with the FDTD-based algorithm. In addition, we optimize the focusing parameters to eliminate hotspots, which are unnecessary focusing positions, by adding phase-reversed electric fields and confirm hotspot suppression through simulations.

• ETRI Journal
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• v.36 no.5
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• pp.714-720
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• 2014

In this paper, we propose the use of data-driven probabilistic utterance-level decision logic to improve Weighted Finite State Transducer (WFST)-based endpoint detection. In general, endpoint detection is dealt with using two cascaded decision processes. The first process is frame-level speech/non-speech classification based on statistical hypothesis testing, and the second process is a heuristic-knowledge-based utterance-level speech boundary decision. To handle these two processes within a unified framework, we propose a WFST-based approach. However, a WFST-based approach has the same limitations as conventional approaches in that the utterance-level decision is based on heuristic knowledge and the decision parameters are tuned sequentially. Therefore, to obtain decision knowledge from a speech corpus and optimize the parameters at the same time, we propose the use of data-driven probabilistic utterance-level decision logic. The proposed method reduces the average detection failure rate by about 14% for various noisy-speech corpora collected for an endpoint detection evaluation.

• Transactions on Electrical and Electronic Materials
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• v.17 no.6
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• pp.369-374
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• 2016

This paper presents a design procedure of an integrated inductor with a magnetic core for power converters. This procedure considerably reduces design time and effort. The proposed design procedure is verified by the development of an inductor model dedicated to the monolithic integration of DC-DC converters for portable applications. The numerical simulation based on the FEM (finite elements method) shows that 3D modeling of the integrated inductor allows better estimation of the electrical parameters of the desired inductor. The optimization of the electrical parameter values is based on the numerical analysis of the influence of the geometric parameters on the electrical characteristics of the inductor. Using the VHDL-AMS language, implementation of the integrated inductor in a micro Buck converter demonstrate that simulation results present a very promising approach for the monolithic integration of DC-DC converters.