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SUMMARY:LRS² - Daniel J. Siefman\, Criticality Validation with Bayesian A
 nalysis
DTSTART:20180530T110000
DTEND:20180530T120000
DTSTAMP:20260510T062831Z
UID:89a70515969a4ceb817048902369f64df062dc2202ca91a9ca47a5c4
CATEGORIES:Conferences - Seminars
DESCRIPTION:Daniel J. Siefman\nLRS Lab Research Seminar\nSeason 2\n\nDanie
 l J. Siefman\, Criticality Validation with Bayesian Analysis\n\nA central 
 question in modeling physical systems is “how reliable are our calculati
 ons?” If we say a reactor is safe based on a simulation\, we better be c
 onfident about it. The easiest way to check\, or validate\, a simulation i
 s to compare a calculated value and an experimental value. In reactor phys
 ics\, for example\, we simulate a reactor and calculate keff and then we c
 ompare the calculated value to the actual keff value of the system. But wh
 at do when we do not have any experimental values? If we are designing a f
 ast molten salt reactor with a thorium fuel cycle\, we do not have any exp
 erimental reactors to validate our simulations. Furthermore\, to build a r
 esearch reactor to test our simulations would require millions of dollars 
 in investment. We would want to be confident that the reactor is a good id
 ea before investing in the research reactor\, right?\nWhen we do have expe
 rimental values to validate a simulation\, we see that there is a bias bet
 ween our calculation and the experiment. The bias can come from a number o
 f sources:\n\n	Modeling approximations: How well do we know the fuel compo
 sition\, the geometry of the core?\n	Methodology: How are we approximating
  a solution to the neutron transport equation? Diffusion theory? The Monte
  Carlo method? Approximations cause a bias.\n	Nuclear data: The cross sect
 ions input into our neutron transport code have inherent uncertainties tha
 t cause a bias and uncertainty in the calculation.\n\n\nWhen designing a n
 ew reactor\, we have to quantify the uncertainty coming from modeling\, me
 thodology\, and nuclear data and see how they affect economic and safety a
 nalyses. We can then improve our predictions by performing a Bayesian upda
 te with experiments that are similar to our new reactor. With the updated 
 calculated values\, we can then update our safety and economic analyses an
 d then be that much more confident in our approach.\n 
LOCATION:PH L1 503 - Salle Aquarium https://plan.epfl.ch/?room=PHL1503
STATUS:CONFIRMED
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