Introduction Database features Automation of input file preparation Available experiments Database availability & future plans Database of publicly available VVER PIE data sek HAVL ˚ Frantiˇ UJ Nuclear Research Institute at Rez, plc. Czech Republic WPNCS / EG ADSNF meeting Issy-les-Moulineaux, September 22 – 24, 2008 sek HAVL ˚ Frantiˇ UJ VVER PIE Database
Introduction Database features Automation of input file preparation Available experiments Database availability & future plans Contents Introduction 1 Database features 2 Automation of input file preparation 3 Available experiments 4 Database availability & future plans 5 sek HAVL ˚ Frantiˇ UJ VVER PIE Database
Introduction Database features Automation of input file preparation Available experiments Database availability & future plans VVER PIEs few experiments are publicly available only ISTC #2670 VVER-440 PIE and ORNL VVER-1000 benchmark are well-documented and complete the data are scattered among various benchmark specifications or journal articles up to now, the available data are not part of the SFCOMPO database sek HAVL ˚ Frantiˇ UJ VVER PIE Database
Introduction Database features Automation of input file preparation Available experiments Database availability & future plans Goals of this project gather all publicly available VVER PIE data fill in all missing information, prepare the documentation in a consistent way, ready for simulation present them all in one place add all source descriptions to make QA effortless is not intended to be ’concurrent’ to SFCOMPO in any way; if it will be possible / reasonable, all the experiments can be readily put into SFCOMPO sek HAVL ˚ Frantiˇ UJ VVER PIE Database
Introduction Database features Automation of input file preparation Available experiments Database availability & future plans Consistent format all the data are presented in as uniform way as possible conversions are made to the usual units e.g. depletion history is always presented in terms of burn time, power and down time (originally, different specifications give per-cycle burnups, powers per assembly etc.) no more conversions have to be made sek HAVL ˚ Frantiˇ UJ VVER PIE Database
Introduction Database features Automation of input file preparation Available experiments Database availability & future plans Traceability of all data in many descriptions/specifications the exact sources of the data is often unclear and so are all transformations, auxiliary calculations etc. this database describes from what source were all the data exactly taken in case of any transformations or calculations these are precisely documented all numbers can be either traced to their primary sources or their calculation can be reproduced no more time has to be spent verifying the data reliability sek HAVL ˚ Frantiˇ UJ VVER PIE Database
Introduction Database features Automation of input file preparation Available experiments Database availability & future plans Data completeness usually, more or less data are missing in the PIE descriptions (and, unfortunately, sometimes also in benchmark specifications) all indispensable data are contained in the database – they are based on reasonable assumptions, on other similar PIEs, on calculations again, such completions/assumptions are well documented and are performed as consistently as possible sek HAVL ˚ Frantiˇ UJ VVER PIE Database
Introduction Database features Automation of input file preparation Available experiments Database availability & future plans Automation readiness especially for PIE simulation it is not convenient to prepare the input files manually only a few parameters differ among the particular samples for this task a tool was developed, which can be used with any computer code/method sek HAVL ˚ Frantiˇ UJ VVER PIE Database
Introduction Database features Automation of input file preparation Available experiments Database availability & future plans PREDATOR tool: basic principle parameters template sample data describes general construction data - sample burnup dimensions, geometry etc. sample position differs for each materials sample/position case-inspecific computer code dependent depletion depletion history history data parameters sek HAVL ˚ Frantiˇ UJ VVER PIE Database
Introduction Database features Automation of input file preparation Available experiments Database availability & future plans PREDATOR tool: a simple example (1) parameters template uptime 500 ’ sample %smpid% downtime 60 ... begin depletion sample data burn=%uptime% power=&%burnup%/%uptime%& smpid burnup down=%downtime% 1 15000 end depletion 2 20000 ... 3 25000 sek HAVL ˚ Frantiˇ UJ VVER PIE Database
Introduction Database features Automation of input file preparation Available experiments Database availability & future plans PREDATOR tool: a simple example (2) case 1 case 2 case 3 sample 1 sample 2 sample 3 ... ... ... begin depletion begin depletion begin depletion burn=500 burn=500 burn=500 power=30 power=40 power=50 down=60 down=60 down=60 end depletion end depletion end depletion ... ... ... sek HAVL ˚ Frantiˇ UJ VVER PIE Database
Introduction Database features Automation of input file preparation Available experiments Database availability & future plans PREDATOR tool: other features including files (for larger sample-dependent parts, like assembly maps) evaluating expressions (e.g. for inline unit conversions) automatic radius/diameter conversions grouping samples (e.g. by assembly) and assigning parameter values to the groups short-hand specification of some code-specific blocks (currently history description in SCALE) available on ScaleTools website ( http://scaletools.lecerisier.net ) sek HAVL ˚ Frantiˇ UJ VVER PIE Database
Introduction Database features Automation of input file preparation Available experiments Database availability & future plans Available PIEs – overview N B [MWd/tU] VVER-440 VVER-440, 3.6% 11 20 ÷ 37 actinides benchmark (8 th AER) ISTC #2670 VVER-440, 3.6% 8 22 ÷ 47 actinides+FP project Khlopin VVER-440, 3.3% 7 8 ÷ 17 actinides institute VVER-440, 3.6% 10 37 ÷ 44 experiments VVER-1000, 4.4% 10 21 ÷ 52 ORNL VVER-1000, 3.6% 2 14 ÷ 16 actinides benchmark VVER-1000, 4.4% 4 42 ÷ 47 sek HAVL ˚ Frantiˇ UJ VVER PIE Database
Introduction Database features Automation of input file preparation Available experiments Database availability & future plans Available PIEs – enrichment/burnup Available samples 5 ISTC 2670 4.8 VVER-440 benchmark Khlopin (440) 4.6 Khlopin (1000) 4.4 enrichment [%] ORNL 4.2 4 3.8 3.6 3.4 3.2 3 2.8 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 55000 burnup [MWd/tUi] sek HAVL ˚ Frantiˇ UJ VVER PIE Database
Introduction Database features Automation of input file preparation Available experiments Database availability & future plans Data quality ISTC #2670 PIE and VVER-1000 ORNL benchmark provide all data needed for simulation VVER-440 (8th AER symposium) benchmark also gives most of the needed data Khlopin Institute measurements supply no depletion history data, only the measurements are given sek HAVL ˚ Frantiˇ UJ VVER PIE Database
Introduction Database features Automation of input file preparation Available experiments Database availability & future plans Preliminary results simulation was performed for all the experiments, up to now the experiments only using TRITON (SCALE5.1) sample-averaged C/E results are presented here error bars show standard deviation among the samples sek HAVL ˚ Frantiˇ UJ VVER PIE Database
Introduction Database features Automation of input file preparation Available experiments Database availability & future plans TRITON results (1/4) Sample-averaged results 2.2 2 1.8 1.6 1.4 C/E 1.2 1 0.8 0.6 0.4 ag109 am241 am242m am243 ce140 ce142 cm242 cm244 cm245 cm246 cs133 cs134 cs135 cs137 nuclide sek HAVL ˚ Frantiˇ UJ VVER PIE Database
Introduction Database features Automation of input file preparation Available experiments Database availability & future plans TRITON results (2/4) Sample-averaged results 10 9 8 7 6 C/E 5 4 3 2 1 eu151 eu153 eu154 eu155 gd155 nuclide sek HAVL ˚ Frantiˇ UJ VVER PIE Database
Introduction Database features Automation of input file preparation Available experiments Database availability & future plans TRITON results (3/4) Sample-averaged results 1.8 1.6 1.4 1.2 C/E 1 0.8 0.6 0.4 0.2 mo95 nd142 nd143 nd144 nd145 nd146 nd148 nd150 np237 pd105 pd108 pu238 pu239 pu240 pu241 pu242 nuclide sek HAVL ˚ Frantiˇ UJ VVER PIE Database
Introduction Database features Automation of input file preparation Available experiments Database availability & future plans TRITON results (4/4) Sample-averaged results 1.7 1.6 1.5 1.4 1.3 C/E 1.2 1.1 1 0.9 0.8 0.7 ru101 sm147 sm148 sm149 sm150 sm151 sm152 sm154 tc99 u234 u235 u236 u238 nuclide sek HAVL ˚ Frantiˇ UJ VVER PIE Database
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