• Asian-Australasian Journal of Animal Sciences
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• v.19 no.10
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• pp.1379-1383
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• 2006

A total of 6,804 records for Duroc breed were collected from three farms registered at the Korean Animal Improvement Association (KAIA) from 1998 to 2004 of which both records from two ultrasound modes (A and B) were analyzed to estimate the variance components of carcass traits. Three carcass traits backfat thickness (bf), loin eye muscle area (lma) and lean meat percentage (lmp) were measured. These traits were analyzed separately as bf1, lma1 and lmp1 for ultrasound mode A and bf2, lma2 and lmp2 for ultrasound mode B with multiple trait animal model by using MTDFREML (Boldman et al., 1993). All the traits revealed medium heritability values. Estimated heritabilities for bf1, bf2, lma1, lma2, lmp1 and lmp2 were 0.45, 0.39, 0.32, 0.25, 0.28 and 0.39, respectively. Estimated genetic correlations for traits bf1 and bf2, lma1 and lma2, lmp1 and lmp2 were positive but low. Specifically, genetic correlations between bf1 and bf2 was 0.30 while the estimates for lean traits between lma1 and lma2 and between lmp1 and lmp2 were 0.15 and 0.18, respectively. Conversely, high negative genetic correlations existed between bf1 and the lean traits lma2, lmp2. Likewise, the estimated genetic correlations between lma1 and lma2 and lmp1 and lmp2 were low.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.637-648
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• 2007

This paper presents a sensor fusion method based on indirect Kalman filter(IKF) for error compensation of low-cost inertial sensors and its application to the determination of attitude and position of small flying robots. First, the analysis of the measurement error characteristics to zero input is performed, focusing on the bias due to the temperature variation, to derive a simple nonlinear bias model of low-cost inertial sensors. Moreover, from the experimental results that the coefficients of this bias model possess non-deterministic (stochastic) uncertainties, the bias of low-cost inertial sensors is characterized as consisting of both deterministic and stochastic bias terms. Then, IKF is derived to improve long term stability dominated by the stochastic bias error, fusing low-cost inertial sensor measurements compensated by the deterministic bias model with non-inertial sensor measurement. In addition, in case of using intermittent non-inertial sensor measurements due to the unreliable data link, the upper and lower bounds of the state estimation error covariance matrix of discrete-time IKF are analyzed by solving stochastic algebraic Riccati equation and it is shown that they are dependant on the throughput of the data link and sampling period. To evaluate the performance of proposed method, experimental results of IKF for the attitude determination of a small flying robot are presented in comparison with that of extended Kaman filter which compensates only deterministic bias error model.

• Nuclear Engineering and Technology
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• v.47 no.2
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• pp.204-211
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• 2015

Probabilistic safety assessment (PSA) has had a significant role in quantitative decision-making by finding design and operational vulnerabilities and evaluating cost-benefit in improving such weak points. In particular, it has been widely used as the core methodology for risk-informed applications (RIAs). Even though the nature of PSA seeks realistic results, there are still "conservative" aspects. One of the sources for the conservatism is the assumptions of safety analysis and the estimation of failure frequency. Surveillance, diagnosis, and prognosis (SDP), utilizing massive databases and information technology, is worth highlighting in terms of its capability for alleviating the conservatism in conventional PSA. This article provides enabling techniques to solidify a method to provide time- and condition-dependent risks by integrating a conventional PSA model with condition monitoring and prognostics techniques. We will discuss how to integrate the results with frequency of initiating events (IEs) and probability of basic events (BEs). Two illustrative examples will be introduced: (1) how the failure probability of a passive system can be evaluated under different plant conditions and (2) how the IE frequency for a steam generator tube rupture (SGTR) can be updated in terms of operating time. We expect that the proposed model can take a role of annunciator to show the variation of core damage frequency (CDF) depending on operational conditions.

• Nuclear Engineering and Technology
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• v.48 no.3
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• pp.765-772
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• 2016

In analyzing residual radiation, researchers generally use a two-step Monte Carlo (MC) simulation. The first step (MC1) simulates neutron transport, and the second step (MC2) transports the decay photons emitted from the activated materials. In this process, the stochastic uncertainty estimated by the MC2 appears only as a final result, but it is underestimated because the stochastic error generated in MC1 cannot be directly included in MC2. Hence, estimating the true stochastic uncertainty requires quantifying the propagation degree of the stochastic error in MC1. The brute force technique is a straightforward method to estimate the true uncertainty. However, it is a costly method to obtain reliable results. Another method, called the adjoint-based method, can reduce the computational time needed to evaluate the true uncertainty; however, there are limitations. To address those limitations, we propose a new strategy to estimate uncertainty propagation without any additional calculations in two-step MC simulations. To verify the proposed method, we applied it to activation benchmark problems and compared the results with those of previous methods. The results show that the proposed method increases the applicability and user-friendliness preserving accuracy in quantifying uncertainty propagation. We expect that the proposed strategy will contribute to efficient and accurate two-step MC calculations.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.411-425
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• 2017

Using a probabilistic safety assessment, a risk evaluation framework for an aircraft crash into an interim spent fuel storage facility is presented. Damage evaluation of a detailed generic cask model in a simplified building structure under an aircraft impact is discussed through a numerical structural analysis and an analytical fragility assessment. Sequences of the impact scenario are shown in a developed event tree, with uncertainties considered in the impact analysis and failure probabilities calculated. To evaluate the influence of parameters relevant to design safety, risks are estimated for three specification levels of cask and storage facility structures. The proposed assessment procedure includes the determination of the loading parameters, reference impact scenario, structural response analyses of facility walls, cask containment, and fuel assemblies, and a radiological consequence analysis with dose-risk estimation. The risk results for the proposed scenario in this study are expected to be small relative to those of design basis accidents for best-estimated conservative values. The importance of this framework is seen in its flexibility to evaluate the capability of the facility to withstand an aircraft impact and in its ability to anticipate potential realistic risks; the framework also provides insight into epistemic uncertainty in the available data and into the sensitivity of the design parameters for future research.

• Nuclear Engineering and Technology
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• v.50 no.4
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• pp.589-598
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• 2018

To maintain safety and reliability of reactors, redundant sensors are usually used to measure critical variables and estimate their averaged time-dependency. Nonhealthy sensors can badly influence the estimation result of the process variable. Since online condition monitoring was introduced, the online cross-calibration method has been widely used to detect any anomaly of sensor readings among the redundant group. The cross-calibration method has four main averaging techniques: simple averaging, band averaging, weighted averaging, and parity space averaging (PSA). PSA is used to weigh redundant signals based on their error bounds and their band consistency. Using the consistency weighting factor (C), PSA assigns more weight to consistent signals that have shared bands, based on how many bands they share, and gives inconsistent signals of very low weight. In this article, three approaches are introduced for improving the PSA technique: the first is to add another consistency factor, so called trend consistency (TC), to include a consideration of the preserving of any characteristic edge that reflects the behavior of equipment/component measured by the process parameter; the second approach proposes replacing the error bound/accuracy based weighting factor ($W^a$) with a weighting factor based on the Euclidean distance ($W^d$), and the third approach proposes applying $W^d$, TC, and C, all together. Cold neutron source data sets of four redundant hydrogen pressure transmitters from a research reactor were used to perform the validation and verification. Results showed that the second and third modified approaches lead to reasonable improvement of the PSA technique. All approaches implemented in this study were similar in that they have the capability to (1) identify and isolate a drifted sensor that should undergo calibration, (2) identify a faulty sensor/s due to long and continuous missing data range, and (3) identify a healthy sensor.

• Nuclear Engineering and Technology
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• v.52 no.2
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• pp.296-307
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• 2020

Permanent magnet sodium flowmeter (PMSF) have been used to measure the sodium flow in fast breeder reactors. Due to the effects of irradiation, thermal cycling, time lapse, etc., the magnetic flux density of the PMSF will decrease after being used in the reactor for a period of time. Therefore, it must be calibrated regularly. But some flowmeters that immersed in sodium cannot be removed for an off-line calibration, so the on-line calibration is required. However, the best online calibration accuracy of PMSF using cross-correlation analysis method was 2.0-level without considering the repeatability. In order to further improve this work, the operational principle of the transducer in PMSF is analyzed and the design principle of the transducer is proposed. The transducers were tested on the sodium flow loop to collect the experimental data. The signal characteristics are analyzed from the time and frequency domains, respectively. The cross-correlation analysis method based on biased estimation is adopted to obtain the flow rate. The verification experimental results showed that the measurement accuracy is 1.0-level when the flow velocity is above 0.5 m/s, and the measurement accuracy is 3.0-level when the flow velocity is in the range of 0.2 m/s to 0.5 m/s.

• Nuclear Engineering and Technology
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• v.52 no.2
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• pp.344-351
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• 2020

AgInCd alloy is widely used as neutron absorber in nuclear reactors. However, the AgInCd control rods may fail during service due to the irradiation swelling. In the present study, a calculational method is proposed to calculate the composition change of the AgInCd absorber. Calculated results show that neutron fluence has significant impact on the chemical compositions. Ag and In contents gradually decrease while Cd and Sn conversely increases from the center to the rim of AgInCd absorber due to the depression of neutron flux. The composition change at the surface is higher almost two times than that at the center. Based on the calculated compositions, six simulated AgInCdSn alloys were prepared and examined. With the increase of Cd and Sn, the simulated AgInCdSn alloys transform from a single fcc phase into the mixed fcc and hcp phases, and finally into the single hcp phase. The atomic volume of the hcp phase is obviously larger than the fcc phase. The fcc-hcp transformation results in considerable volume swelling of the AgInCd absorber. Moreover, the lattice parameters of the fcc and hcp phases gradually increase with Cd and Sn contents, which also can induce small volume swelling.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.5
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• pp.415-419
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• 2008

Detecting and correcting defects on LCD glasses early in the manufacturing process becomes important for panel makers to reduce the manufacturing costs and to improve productivity. Many attempts have been made and were successfully applied to detect and identify simple defects such as scratches, dents, and foreign objects on glasses. However, it is still difficult to robustly detect low-contrast defect region, called Mura or blemish area on glasses. Typically, these defect areas are roughly defined as relatively large, several millimeters of diameter, and relatively dark and/or bright region of low Signal-to-Noise Ratio (SNR) against background of low-frequency signal. The aim of this article is to present a robust algorithm to segment these blemish defects. Early 90's, a highly robust estimator, known as the Model-Fitting (MF) estimator was developed by X. Zhuang et. al. and have been successfully used in many computer vision application. Compared to the conventional Least-Square (LS) estimator the MF estimator can successfully estimate model parameters from a dataset of contaminated Gaussian mixture. Such a noise model is defined as a regular white Gaussian noise model with probability $1-\varepsilon$ plus an outlier process with probability $varepsilon$. In the sense of robust estimation, the blemish defect in images can be considered as being a group of outliers in the process of estimating image background model parameters. The algorithm developed in this paper uses a modified MF estimator to robustly estimate the background model and as a by-product to segment the blemish defects, the outliers.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.8
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• pp.1109-1112
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• 2000

A field experiment was carried out to determine the effects of mechanical and chemical conditioning at mowing on field drying rate and quality of grass hay in 1996. Mower conditioner and/or chemical drying agent $(K_2CO_3)$ were used at different harvest stages (late boot, heading and bloom stages) for hastening hay-making. After field drying, square bales were made by hay baler, and the visual estimation and nutritive value of hay were evaluated after storing two months. In mower conditioning, the duration of field drying was shortened by 0.5 to 1 day compared with drying agent, and by 1 to 2 days compared with control. The drying matter loss of hay was reduced by late harvest and mechanical conditioning. The visual score (leafiness, green color, odor and softness), and acid detergent fiber (ADF), neutral detergent fiber (NDF), in vitro dry matter digestibllity (IVDMD), and relative feed value (RFV) of hay were improved with mechanical conditioning, but chemical alone had little effect on quality. The quality of hay harvested at bloom stage was much lower than that of hay harvested at late boot and heading stage. In conclusion, mower conditioning can enhance the field drying rate of grass hay, however the drying efficiency of chemical drying agent is very low. Also the effects of chemical/mechanical combined conditioning are very similar compared with mechanical conditioning alone. Harvesting at late boot to heading stage is recommended for the production of high quality hay.