• Journal of the Korean Data and Information Science Society
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• v.10 no.2
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• pp.329-340
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• 1999

We consider a Bayesian forcasting method for the analysis of repeated surveys. It is assumed that the parameters of the superpopulation model at each time follow a stochastic model. We propose Bayesian prediction procedures for the finite population total under multiprocess dynamic generalized linear models. The multiprocess dynamic model offers a powerful framework for the modelling and analysis of time series which are subject to a abrupt changes in pattern. Some numerical studies are provided to illustrate the behavior of the proposed predictors.

• Nuclear Engineering and Technology
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• v.29 no.1
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• pp.1-6
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• 1997

This paper presents a new dynamic approach for assessing feasibility associated with the implementation of accident management strategies by the operators. This approach includes the combined use of both the concept of reliability physics and a dynamic event tree generation scheme. The reliability physics is based on the concept of a comparison between two competing variables, i.e., the requirement and the achievement parameter, while the dynamic event tree generation scheme on the continuous generation of the possible event sequences at every branch point up to the desired solution. This approach is applied to a cavity flooding strategy in a reference plant, which is to supply water into the reactor cavity using emergency fire systems in the station blackout sequence. The MAAP code and Latin Hypercube sampling technique are used to determine the uncertainty of the requirement parameter. It has been demonstrated that this combined methodology may contribute to assessing the success likelihood of the operator actions required during accidents and therefore to developing the accident management procedures.

• Journal of Welding and Joining
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• v.18 no.2
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• pp.239-239
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• 2000

Automobile manufacturers have employed resistance spot welding(RSW) to join steel sheets for structural rigidity o automobile body. Driven by the need to reduce weight and fuel consumption, car companies have been evaluating aluminum intensive vehicles(AIVs) as a way to reduce vehicle weight without downsizing. During the transition from all steel-construction vehicle body to aluminum intensive body, joining aluminum to steel sheets emerges as a serious contender in automobile body. This paper deals with application of transition material to RSW aluminum to steel. Placing transition material insert between the aluminum/steel interface was found very effective to overcome incompatibility between aluminum and steel. Use of transition insert allows for two separate weld muggets to be formed in their respective aluminum/ aluminum and steel/ steel interfaces. This RSW process was monitored with the aid of dynamic resistance sampling. Typical patterns in sampled dynamic resistance curves indicated formation of sound nugget. (Received February 28, 2000)

• Journal of Welding and Joining
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• v.18 no.2
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• pp.112-118
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• 2000

Automobile manufacturers have employed resistance spot welding(RSW) to join steel sheets for structural rigidity of automobile body. Driven by the need to reduce weight and fuel consumption, car companies have been evaluating aluminum intensive vehicles(AIVs) as a way to reduce vehicle weight without downsizing. During the transition from all steel-construction vehicle body to aluminum intensive body, joining aluminum to steel sheets emerges as a serious contender in automobile body. This paper deals with application of transition material to RSW aluminum to steel. Placing transition material insert between the aluminum/steel interface was found very effective to overcome incompatibility between aluminum and steel. Use of transition insert allows for two separate weld nuggets to be formal in their respective aluminum/aluminum and steel/steel interfaces. This RSW process was monitored with the aid of dynamic resistance sampling. Typical patterns in sampled dynamic resistance curves indicated formation of sound nugget.

• Investigative Magnetic Resonance Imaging
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• v.23 no.1
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• pp.1-16
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• 2019

Dynamic contrast enhanced (DCE) magnetic resonance (MR) imaging plays an important role in non-invasive detection and characterization of primary and metastatic lesions in the liver. Recently, efforts have been made to improve spatial and temporal resolution of DCE liver MRI for arterial phase imaging. Review of recent publications related to arterial phase imaging of the liver indicates that there exist primarily two approaches: breath-hold and free-breathing. For breath-hold imaging, acquiring multiple arterial phase images in a breath-hold is the preferred approach over conventional single-phase imaging. For free-breathing imaging, a combination of three-dimensional (3D) stack-of-stars golden-angle sampling and compressed sensing parallel imaging reconstruction is one of emerging techniques. Self-gating can be used to decrease respiratory motion artifact. This article introduces recent MRI technologies relevant to hepatic arterial phase imaging, including differential subsampling with Cartesian ordering (DISCO), golden-angle radial sparse parallel (GRASP), and X-D GRASP. This article also describes techniques related to dynamic 3D image reconstruction of the liver from golden-angle stack-of-stars data.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.3
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• pp.189-193
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• 2015

This paper provides the design techniques of a successive approximation register (SAR) type 12b analog-to-digital converter (ADC) for distributed maximum power point tracking (DMPPT) control in a photovoltaic system. Both a top-plate sampling technique and a $V_{CM}$-based switching technique are applied to the 12b capacitor digital-to-analog converter (CDAC). With these techniques, we can implement a 12b SAR ADC with a 10b capacitor array digital-to-analog converter (DAC). To enhance the accuracy of the ADC, a single-to-differential converted DAC is exploited with the dual sampling technique during top-plate sampling. Simulation results show that the proposed ADC can achieve a signal-to-noise plus distortion ratio (SNDR) of 70.8dB, a spurious free dynamic range (SFDR) of 83.3dB and an effective number of bits (ENOB) of 11.5b with bipolar CMOS LDMOD (BCDMOS) $0.35{\mu}m$ technology. Total power consumption is 115uW under a supply voltage of 3.3V at a sampling frequency of 1.25MHz. And the figure of merit (FoM) is 32.68fJ/conversion-step.

• Structural Engineering and Mechanics
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• v.84 no.3
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• pp.323-335
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• 2022

The main idea of the framework is to seamlessly combine a reasonably accurate and fast surrogate model with the importance sampling strategy. Developing a surrogate model for predicting structures' dynamic responses is challenging because it involves high-dimensional inputs and outputs. For this purpose, a novel surrogate model based on cutting-edge deep learning architectures specialized for capturing temporal relationships within time-series data, namely Long-Short term memory layer and Transformer layer, is designed. After being properly trained, the surrogate model could be utilized in place of the finite element method to evaluate structures' responses without requiring any specialized software. On the other hand, the importance sampling is adopted to reduce the number of calculations required when computing the failure probability by drawing more relevant samples near critical areas. Thanks to the portability of the trained surrogate model, one can integrate the latter with the Importance sampling in a straightforward fashion, forming an efficient framework called TTIS, which represents double advantages: less number of calculations is needed, and the computational time of each calculation is significantly reduced. The proposed approach's applicability and efficiency are demonstrated through three examples with increasing complexity, involving a 1D beam, a 2D frame, and a 3D building structure. The results show that compared to the conventional Monte Carlo simulation, the proposed method can provide highly similar reliability results with a reduction of up to four orders of magnitudes in time complexity.

• Proceedings of the Korean Reliability Society Conference
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• 2000.04a
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• pp.239-246
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• 2000

This paper presents a new dynamic approach for assessing feasibility associated with the implementation of accident management strategies by the operators. This approach includes the combined use of both the concept of reliability physics and a dynamic event tree generation scheme. The reliability physics is based on the concept of a comparison between two competing variables, i.e., the requirement and the achievement parameter, while the dynamic event tree generation scheme on the continuous generation of the possible event sequences at every branch point up to the desired solution. This approach is applied to a cavity flooding strategy in a reference plant, which is to supply water into the reactor cavity using emergency fire systems in the station blackout sequence. The MAAP code and Latin Hypercube sampling technique are used to determine the uncertainty of the requirement parameter. It has been demonstrated that this combined methodology may contribute to assessing the success likelihood of the operator actions required during accidents and therefore to developing the accident management procedures.

• Coupled systems mechanics
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• v.4 no.4
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• pp.279-295
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• 2015

The article presents a theoretical-experimental approach developed for modeling the coefficient of sliding friction in the dynamic system tool-workpiece in slide diamond burnishing of low-alloy unhardened steels. The experimental setup, implemented on conventional lathe, includes a specially designed device, with a straight cantilever beam as body. The beam is simultaneously loaded by bending (from transverse slide friction force) and compression (from longitudinal burnishing force), which is a reason for geometrical nonlinearity. A method, based on the idea of separation of the variables (time and metric) before establishing the differential equation of motion, has been applied for dynamic modeling of the beam elastic curve. Between the longitudinal (burnishing force) and transverse (slide friction force) forces exists a correlation defined by Coulomb's law of sliding friction. On this basis, an analytical relationship between the beam deflection and the sought friction coefficient has been obtained. In order to measure the deflection of the beam, strain gauges connected in a "full bridge" type of circuit are used. A flexible adhesive is selected, which provides an opportunity for dynamic measurements through the constructed measuring system. The signal is proportional to the beam deflection and is fed to the analog input of USB DAQ board, from where the signal enters in a purposely created virtual instrument which is developed by means of Labview. The basic characteristic of the virtual instrument is the ability to record and visualize in a real time the measured deflection. The signal sampling frequency is chosen in accordance with Nyquist-Shannon sampling theorem. In order to obtain a regression model of the friction coefficient with the participation of the diamond burnishing process parameters, an experimental design with 55 experimental points is synthesized. A regression analysis and analysis of variance have been carried out. The influence of the factors on the friction coefficient is established using sections of the hyper-surface of the friction coefficient model with the hyper-planes.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06a
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• pp.181-182
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• 2010