ENDF:Multiple emission:
12.3. Bringing Nuclear Physics back into Reactor Engineering
As was pointed out in Section 9., an alternative approach to the data evaluation method would be one nuclear model supercode that produces better results than all data files com- bined for all energies and isotopes, and is so fast that it can be hardwired directly in a transport code. With such an approach, a direct link between reactor properties and the underlying nuclear physics would be established.
Recently, a first step in this direction has been taken [99]. In TALYS, a limited number of free parameters are determined by fits to the global database. In such fits, a best-fit
value is obtained, but also an uncertainty. A recent development is to issue a second step: massive computation. Literally 5000 calculations of the properties of a nuclear reactor are performed. In each calculation, TALYS is used to obtain a nuclear data library, which in turn is used as input in a reactor physics code. The input parameters to TALYS are randomised by the probability functions obtained in the preceding global fit. Thus, 5000 slightly different nuclear data libraries are used as input, leading to 5000 slightly different results on the reactor performance.
With this approach, the 5000 outputs can be analysed statistically. The reactor codes do not only provide a single value as before, but the uncertainties in key parameters can be obtained from the distribution of results on the same key parameters in the massive computation approach.
Already in the pioneering publication in which the methodology was applied in MCNP simulations of some Gen-IV and ADS cases, the method has revealed some very fundamen- tal findings. The most important is that it has proven one basic assumption in all modelling today to be fundamentally wrong. It has been a common prejudgment in reactor physics that uncertainties follow Gaussian distributions, but in fast reactors, the results on critical- ity are far from a Gaussian distribution. This means that with conventional methodology, the results have over-estimated safety margins because tails in the probability distribution have been neglected, and in cases where calculations have indicated the reactor design to be stable, it could in reality be prompt critical.
That the values on keff deviate from Gaussian distributions in fast reactor systems but not in thermal makes sense from very fundamental considerations. In the fast energy range, some dominating cross sections are strongly correlated, and therefore the central limit the- orem does not apply. Hence, Gaussian distributions cannot be a priori presumed.
We are convinced that this methodology has important use in also present nuclear power technology. Although the methodology can be used to improve safety of nuclear power plants, the main use is in cost-cutting. Present nuclear power plants are so safe that the nuclear information is not the dominating uncertainty in safety assessment. The method therefore has its cutting edge in economizing the operation. With improved handling of uncertainties in, e.g., core planning, less conservatism would be required, leading to, e.g., more efficient use of the fuel.
In the design of future reactors, the method has revolutionary implications. In such development and design, the massive computation approach can save enormous costs and efforts. By establishing direct links between fundamental physics and practical engineering, research can be guided far more efficiently than today. Basic physics can be used more, and trial-and-error less in the development process.
Acknowledgements
Part of this work was supported by the HINDAS project of the 5th Euratom Framework Programme, contract no. FIKW-CT-2000-0031, and the EUROTRANS project of the 6th Euratom Framework Programme, contract no. FI6W-CT-2004-516520. This work was sup- ported by the Swedish Natural Science Research Council, Vattenfall AB, Swedish Nuclear Fuel and Waste Management Company, Swedish Nuclear Power Inspectorate, Barseb¨ack Power AB, Forsmark Power AB, Ringhals AB, the Swedish Nuclear Technology Centre
and the Swedish Defence Research Agency.
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Chapter 2
AN OVERVIEW ABOUT MODELING APPROACHES
FOR TURBULENT MIXING AND VOID DRIFT
IN SUB-CHANNEL ANALYSIS
Markus Glück
∗AREVA, AREVA NP GmbH, an AREVA and Siemens Company, Department FDWT-G (Core thermal hydraulics),
Erlangen, Germany
Abstract
If the boiling flow through fuel assemblies in a reactor core is to be predicted numerically by means of a sub-channel code, two important lateral exchange processes between neighboring sub-channels have to be taken into account: turbulent mixing and void drift. Whereas mixing is a kind of turbulent gradient diffusion occurring in both single-phase and two-phase flow, void drift is a two-phase phenomenon which is physically not yet well understood. However, there are a lot of phenomenological attempts to model this superimposed effect, which can act in the same direction as turbulent mixing, but also contrarily depending on sub-channel geometries and flow conditions.
The present paper will classify the physical background of both phenomena including a detailed overview about the flow conditions which have to be existent in order to cause the one or other phenomenon. Furthermore, it will provide a well-structured thread through the whole calculation methodology. Thereby, each single phenomenon will be discussed in detail (physically and mathematically) and an overview about both the particular state-of-the-art models and new approaches in open literature will be given.
∗ E-mail address: [email protected]. Correspondence to: AREVA NP GmbH, Department FDWT-G (Core thermal hydraulics), Paul-Gossen-Straße 100, D-91052 Erlangen, Germany.