• Nuclear Engineering and Technology
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• v.41 no.10
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• pp.1293-1306
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• 2009

In this paper, an infinite impulse response locally recurrent neural network (IIR-LRNN) is employed for modelling the dynamics of the Lead Bismuth Eutectic eXperimental Accelerator Driven System (LBE-XADS). The network is trained by recursive back-propagation (RBP) and its ability in estimating transients is tested under various conditions. The results demonstrate the robustness of the locally recurrent scheme in the reconstruction of complex nonlinear dynamic relationships.

• Journal of Power Electronics
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• v.11 no.2
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• pp.156-162
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• 2011

The control loop time delay caused by sampling, the zero-order-holder effect and calculations is inevitable in the digital control of dc-dc switching converters. The time delay will limit the bandwidth of the control loop and therefore degrade the transient performance of digital systems. In this paper, the quantization time delay effects with different time delay values based on a generic second-order system are analyzed. The conclusion that the bandwidth of digital control is reduced by about 20% with a one cycle delay and by 50% with two cycles of delay in comparison with no time delay is obtained. To compensate the time delay and to increase the control loop bandwidth, a duty ratio predictive control scheme based on linear extrapolation is proposed. The compensation effect and a comparison of the load variation transient response characteristics with analogy control, conventional digital control and duty ratio predictive control with different time delay values are performed on a point-of-load Buck converter by simulations and experiments. It is shown that, using the proposed technique, the control loop bandwidth can be increased by 50% for a one cycle delay and 48.2% for two cycles of delay when compared to conventional digital control. Simulations and experimental results prove the validity of the conclusion of the quantization effects of the time delay and the proposed control scheme.

• Biotechnology and Bioprocess Engineering:BBE
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• v.10 no.6
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• pp.571-575
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• 2005

A simple, but effective on-line method for estimating the mycelial cell mass concentration from agitation speed data, a most readily-available process variable, has been developed for DO-stat cultures of Agaricus blazei. The dynamic change of dissolved oxygen concentration (DOC) in the initial transient period and the change in yield were considered in the development of the estimation algorithm or estimator. Parameters in the estimation algorithm were calculated from the agitation speed data at 20% of DOC. The proposed estimator could accurately predict the cell mass concentration regardless of DOC levels in the tested range of $10{\sim}40%$, showing a good extrapolation capability.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.346-351
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• 1998

In design of a digital current controller for a 3-phase (3 ) voltage-source (VS) PWM converter, its conventional model, i.e., stationary or synchronous reference frame model, is used in obtaining its discretized version. It introduces, however, inherent errors since the following practical problems are not taken into consideration: the characteristics of the space vector-based pulse-width modulation (SVPWM) and the time delays in the process of sampling and computation. In this paper, the new hybrid reference frame model of the 3 VS PWM converter is proposed considering these problems. In addition, the direct digital current controller based on this model is designed without any prediction or extrapolation algorithm to compensate the time delay. So the control algorithm is made very simple. It represents no steady-state error in input current control and has the optimized transient responses. The validity of the proposed algorithm is proved by the computer simulation and experimental results.

• Nuclear Engineering and Technology
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• v.42 no.6
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• pp.690-703
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• 2010

Sampling based uncertainty analysis was carried out to quantify uncertainty in predictions of best estimate code RELAP5/MOD3.2 for a thermal hydraulic test (10% hot leg break LOCA) performed in the Large Scale Test Facility (LSTF) as a part of an IAEA coordinated research project. The nodalisation of the test facility was qualified for both steady state and transient level by systematically applying the procedures led by uncertainty methodology based on accuracy extrapolation (UMAE); uncertainty analysis was carried out using the Latin hypercube sampling (LHS) method to evaluate uncertainty for ten input parameters. Sixteen output parameters were selected for uncertainty evaluation and uncertainty band between $5^{th}$ and $95^{th}$ percentile of the output parameters were evaluated. It was observed that the uncertainty band for the primary pressure during two phase blowdown is larger than that of the remaining period. Similarly, a larger uncertainty band is observed relating to accumulator injection flow during reflood phase. Importance analysis was also carried out and standard rank regression coefficients were computed to quantify the effect of each individual input parameter on output parameters. It was observed that the break discharge coefficient is the most important uncertain parameter relating to the prediction of all the primary side parameters and that the steam generator (SG) relief pressure setting is the most important parameter in predicting the SG secondary pressure.