CONSOLIDATED RESULTS OF THE BENCHMARK ANALYSIS

The following sections highlight the most relevant issues related to the benchmark specifications, code applicability, modelling considerations and major results, including user effects, for eight benchmark specifications. Further details are available in the corresponding Annexes.

3.3.1. ETRR-2

Five sets of results were provided for the ETRR-2 benchmark specifications using the RELAP5 and MERSAT codes.

The ETRR-2 experiment data is generally well-documented. For the scope of this CRP, only the thermal-hydraulic data has been analysed.

The model estimations for the temperature and the transient behaviour throughout the transient course showed that the 1-D codes used can provide satisfactory predictions in cases when forced flow prevails. During natural circulation conditions, the 1-D codes give results that tend to deviate significantly from the experimental values. It may be inferred that in regions where significant 3-D effects exist, the 1-D models are of limited applicability and accuracy. However, in this case the calculated parameters were always conservative, i.e., on the ‘safe side’, as far as safety analysis is concerned.

This benchmark had noticeable user effects. Differences were noted in the flapper valve treatment, nodalization schemes used, fuel and cladding thermal properties and pump coast-down flow characteristics. Substantial user effects were also noted in the assessment of the natural convection regime for the same experimental data.

3.3.2. IEA-R1

The benchmark specifications are of a good quality, but a number of reasons exist that some of the input parameters lack of precise definition such as the thermocouple mounting technique or placement and response time to changes in the clad temperature. Specifically, the mounting of the thermocouples to the cladding provided data that was not representative of the clad temperature; they were not welded to the clad, and therefore most probably gave a temperature somewhere between the coolant and clad temperatures.

For the temperature range in the benchmark data, the codes give satisfactory results. The predicted evolution of coolant and cladding temperatures follow in general the overall trend of the measurements. However, the predicted clad temperature peaks are higher than measured, which may be a result of the issue regarding mounting of the thermocouples to the cladding, described above. Also, the time occurrences of the peak temperatures are generally earlier than the experimental results, but this could again be due to the mounting of the thermocouples.

Temperature predictions (coolant and cladding) have much faster gradients than the measurement during a Loss of Flow Accident (LOFA). It is clear that there is room for improvement in all the models used in the benchmark. At the same time, in order to validate any such changes, the uncertainties in the experimental data mentioned above need to be carefully considered and re-examined.

It was found that it is possible to evaluate the user effect on this benchmark due to overlapping code usage. There was a clear user effect found in the case of RELAP usage as several models predicted significantly different times for flow reversal and peak transient temperature. The

23 differences in the model output can be attributed to several sources, including different input data, modelling assumptions and user choices about how to use the code (e.g., forcing operations within the code instead of allowing the code to operate without interruption).

From this exercise, it was concluded that benchmarking studies need to use standardized/unique initial conditions and assumptions in order to eliminate discrepancies in various models of the same benchmark data other than those caused by differences in the models themselves. Limited efforts were made to standardize the input parameters in this benchmark, the result of which is visible in the spread of the results obtained.

3.3.3. MNR

The experiments that comprise the MNR benchmark specification are based on standard operational measurements for an open-pool MTR-type research reactor and represent typical or routine neutronic simulation problems.

It is noteworthy that significant amount of interpretation is needed in the processing of some of the provided experimental data. Corresponding comparisons presented in this report are of qualitative value and may not be appropriate for code validation. For example, the calculated initial core number densities were supplied by the data provider as this is a benchmark on a burned core, so the experimental data for the control rod worth experiments had to be processed to some extent before being used for benchmarking. The data for the control rod worth experiment remains suitable for individual benchmark analysis.

The results showed that nodal diffusion theory, finite-difference diffusion theory, and explicit-geometry continuous-energy Monte Carlo models can all be used to accurately model such irradiation experiments.

The quality and extent of the experimental data and the limited participation in this benchmark analysis are not sufficient to evaluate the different modelling approaches apart from having identified a user effect due to modelling details of structural and reflector zones, and in the geometrical details of experimental equipment.

3.3.4. OPAL

The benchmark data describes a commissioning core with relatively low uncertainties in material distribution. The reactor was commissioned in 2006 and hence advanced methods were used to collect the experimental data. Furthermore, the described facility represents a multipurpose research reactor design with challenging modelling issues such as burnable absorbers, heavy water reflector and numerous ex-core facilities (e.g., cold neutron source, beam tubes and irradiation channels).

Research reactors with similar design are already planned. The OPAL benchmark specifications provide a relevant benchmark for designing the facility and to support its commissioning. In this context, the OPAL team was encouraged to collect and disseminate additional data in the future.

This benchmark included a variety of codes and methods spanning deterministic (full core transport and diffusion) and stochastic (Monte Carlo) approaches. Most of the calculated and measured results agreed well with no significant unresolved discrepancies. Those observed are

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probably at the level of code convergence and cross-section library effects and resolution of these would require further sensitivity analyses.

No significant user effects were observed when different CRP participants used the same code.

3.3.5. RSG-GAS

In general, the experimental data is suitable for benchmarking codes for a loss of flow transient with flow reversal. Participants identified a need for clarification of the positions of the thermocouples and all models used a common interpretation of the positions. This interpretation was added to the benchmark specification as an addendum. Other uncertainties in the input parameters (for example, flow scram set point, fuel thermal conductivity and cladding thermal conductivity) had a minimal effect on model benchmarks for this particular transient. Similar uncertainties could be significant for more rapid or severe transients.

In general, the transient model predictions exhibit similar behaviour despite the differences among the codes, choice of input parameters and models. The small discrepancies observed between the model predictions and experimental measurements can be attributed to different interpretations and assumptions made by the modelling groups about issues such as transient sequence and flapper valve opening time, among otheers).

There were small user effects caused by different input parameters and model assumptions. In particular, the effects were magnified in the natural convection regime, where the models used different assumptions for operation of the flapper valve.

3.3.6. SPERT III

The SPERT III experiment data is well-documented and extensive. There is enough design information in text, photographs, and diagrams to enable a reasonably complete reconstruction of this 1965 SPERT III E-Core test series. Details of transient rod and control rod configuration at the junction between absorber and follower are not clear. This uncertainty affects predicted axial power shapes and reactivity.

The benchmark analysis was intended to provide fundamental experimental data to support licensing of PWRs and does not represent typical research reactor configurations. The benchmark analysis describes reactivity transients that range from mild to severe.

The results typically show that the codes and models give conservative predictions of peak power. Trends in peak power, energy release and peak clad temperature vs. reactivity insertion succeed in capturing the physical phenomena.

There are significant uncertainties in measured reactivity insertion that have a very large effect on computed results. It is recommended that future analysts fit reactivity to measured period rather than use quoted inferred reactivity in dollars.

Space-dependent feedback coefficients were not used in this work and could be included in the modelling methods to better predict the peak power measured in the benchmark analysis.

Given that only two CRP participants provided models of the SPERT III experiment, no conclusion was made regarding user effects.

25 3.3.7. SPERT IV Static

The SPERT IV experiment data is well-documented and extensive. Experimental data includes flux measurements, control rod calibrations, feedback coefficients and kinetic parameters.

There is enough design information in the text, photographs, and diagrams to enable a reasonably complete reconstruction of the SPERT IV static tests. Details of control rod junction design and placement of void plates are not well specified.

The comprehensive data covers a variety of core configurations and therefore can be very useful to support the validation of neutronic codes and models.

In general, both stochastic and deterministic codes were well suited to the range of experiments and provided good agreement with the benchmark data. In particular, agreement was observed for core flux distribution with most values within 10%. Relative values and features such as peaks and troughs were generally well predicted. However, prediction of cadmium ratios proves to be a difficult problem.

Some limitations were noted for Monte Carlo simulations of small reactivity changes, such as the temperature coefficient of the system over small temperature ranges, where the statistical uncertainty and convergence of the Monte Carlo calculations requires many histories.

The modelling difference of most relevance to the comparison of the simulation results are the approximations/assumptions adopted by each participating group with respect to the absorber rod tapering.

No systematic user effects were notable among the various Monte Carlo codes utilized.

3.3.8. SPERT IV Transient

The SPERT IV transient experiment data is well-documented and extensive. Experimental data includes power, reactivity and temperature measurements. There is enough design information in the text, photographs, and diagrams to enable a reasonably complete reconstruction of the SPERT IV transient tests. However, the reactivity insertion times were not well specified.

The comprehensive benchmark data covers a variety of reactivity insertions for a range of flow conditions and regimes, and therefore can be very useful to support the validation of thermal hydraulic codes and models.

The codes reasonably predict the behaviour of reactivity transients for all but the most severe events (large reactivity insertion over a short time period), where the predictions vary widely in the peak power and clad temperatures. Extreme temperature predictions result from codes predicting film boiling while the benchmark data does not indicate that this phenomenon occurred in any of the experiments.

User effects are particularly noticeable in this benchmark and are prevalent in the choice of heat transfer correlations used in the models. This can be qualitatively seen in the spread of the results from the models using the same code.

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