Information technology is being used to provide interactive access to data collected from the electro-metallurgical treatment of spent fuel. The data are results from many hundreds of experiments performed to better characterize the processes by which uranium is separated from the waste products. Web-based display and relational database query capabilities facilitate the identification of trends in the data and the relating of these trends to the underlying electrochemistry. The objectives are to ensure that the process behavior is well understood, to make readily accessible the necessary data for development and validation of models, and to identify unexpected trends in the data as indications of phenomena not yet represented in the models

Vilim, R. B.

UNT Digital Library

.,AW-,,RI$W- )04Y53Paper to be submitted to: International Topical Meeting on Nuclear Plant Instrumentation,Controls, and Human-Machine Interface Technologies (NPIC&HMIT 2000), Washington, DC,November 13-17,2000.INFORMATION TECHNOLOGY AND DATA MININGFOR SPENT FUEL TREATMENT*byR. B. VilimReactor Analysis DivisionArgonne National Laboratory9700 South Cass AvenueArgonne, IL 60439 USAThe submitted manuscript has been created by theUniversity of Chicago as GperatOr of ArgonueNational Laboratory (“Argonne”) under ContractNo. W-31-109-ENG-38with the U.S. DepartmentofEnergy. The U.S. Government retains for itself, sndothers acting on its&half, a paid-op, non-exclusive,irrevocable worldwide license in said ardcIe toreproduce, prepare derivative works, disoibutecopies to the public, and perform publicly anddisplay publicly, by or on behalf of the Government.*Work supported by the U.S. Department of Energy, Nuclear Energy Programs under ContractW-3 1-109-ENG-38.DISCLAIMERThis repofi was.prepared as an account of work sponsoredby an agency of the United States Government. Neitherthe United States Government nor any agency thereof, norany of their employees, make any warranty, express orimplied, or assumes any legal liability or responsibility forthe accuracy, completeness, or usefulness of anyinformation, apparatus, product, or process disclosed, orrepresents that its use would not infringe privately ownedrights. Reference herein to any specific commercialproduct, process, or service by trade name, trademark,manufacturer, or otherwise does not necessarily constituteor imply its endorsement, recommendation, or favoring bythe United States Government or any agency thereof. Theviews and opinions of authors expressed herein do notnecessarily state or reflect those of the United StatesGovernment or any agency thereof.DISCLAIMERPortions of this document may be illegiblein electronic image products. Images areproduced from the best available originaldocument.International Topical Meeting on Nuclear Plant Instrumentation, Controls, and Human-Machine Interface Technologies(NPIC&HMIT 2b), Washingt&r, DC, November, 2000.INFORMATION TECHNOLOGY AND DATATREATMENTRichard B. VilimMINING FOR SPENT FUELArgonne National Laboratory9700 S. Cass AvenueArgonne IL 60439vilim@ ra.anl.govKeywords: Information technology, data mining, spent fuelABSTRACTInformation technology is being used to provide interactive access to data collectedfrom the electro-metallurgical treatment of spent fuel. The data are results from manyhundreds of experiments performed to better characterize the processes by which uraniumis separated from the waste products. Web-based display and relational database querycapabilities facilitate the identification of trends in the data and the relating of these trendsto the underlying electrochemistry. The objectives are to ensure that the process behavioris well understood, to make readily accessible the necessary data for development andvalidation of models, and to identify unexpected trends in the data as indications ofphenomena not yet represented in the models.1. INTRODUCTIONElectro-metallurgical methods for processing spent nuclear fuel have been underdevelopment at Argonne National Laboratory since the mid- 1980s. Many hundreds ofexperiments have been performed to develop and better characterize the processes bywhich uranium is separated from the waste products in spent nuclear fuel. The basicprocess involves the electrochemical dissolution of the uranium in the fiel and itssubsequent collection on a cathode with minimal carry-over of impurities .[McPheeters,1997]The ensemble of experiments performed to date represent a rich body of data forthe electrometallurgical process. The greatest information is extracted from theseexperiments when they are regarded as a related set tied together by the underlyingelectrochemistry and conservation laws, rather than a set of experiments independent ofeach other. To help with extracting this cross-experiment information the experiment datahave been placed in a database that can be accessed through the World Wide Web byauthorized personnel. This paper describes mining the database and some findings thathave led to improved understanding of the electrorefining process.Data mining involves the use of software tools to facilitate the identification oftrends and patterns in data sets too iarge to be captured through traditional paper boundmethods. In the case of the Spent Fuel Treatment project the number of experiments isvery large, the experiments are spread out over many years, there are severalexperimenters involved, and the experiment data was spread across several geographicallyseparate facilities. A method was needed to make all the data accessible to those in theproject.This paper describes how information technology has been used to makeelectrorefiner data accessible for analyses. Examples are given of how the database hassupported: (1) development and validation of models; (2) data inspection to ensure thatprocess behavior is well understood; and, (3) identification of unexpected trends thatindicate phenomena not yet represented in the models.2. DESCRIPTION OF THE ELECTROREFINERThe electrorefiner consists of a 36 in. cylindrical vessel containing a pool ofmolten cadmium of uniform depth in the range of 7 to 15 cm. deep at the bottom of thevessel. A salt pool of LiC1-KCl electrolyte approximately 37 cm. deep floats on thecadmium pool. The tank cover has four ports, one for a salt pool mixer, another for acadmium pool mixer, an anodic dissolution port for dissolving material, and a cathodeport for growing deposits. In the port used to grow deposits there are ceramic scrapersdesigned to shape the deposit into a right circular cylinder as it grows. The electrorefinersalt pool is normally maintained at 500° C. A schematic of the electrorefiner is shownin Fig. 1.r-vi+I&:-------- ------ .------------ +-------------------------- j ------------CaAminmpc.li~Fig. 1 Electric Circuit Equivalent ofElectrorefiner(2)3. INFORMATION TECHNOLOGYThe use of information technology made it possible to provide electronic desk topaccess to experiment records formerly distributed across several locations and in severaldifferent media. The data included experiment log books in hardcopy form, monthlyreports of post-experiment results in word processor format, images of equipment andprocess product as photograph negatives, chemical analysis of samples in hardcopy form,and computer files of digital acquisition system data recorded during each experiment.The data, however, is now stored in database tables and can be viewed as Web pages.Access is limited by 1P address to ANL personnel working on the project.3.1 Relational Database ModelThe experiment data and records described above are stored using the OracleRelational Database Model (RDBM). The RDBM provides tables for housing the data,permits definition of logical relationships among tables, and supports the retrieval ofinformation by data association. A Master table associates a unique key with eachexperiment. The key is used to identify the row in each of five lower level tables thatcontain information on the experiment. These tables are Run Description, InitialConditions, Time Dependent Process Variables, Deposition Results, and AnalyticChemistries.3.2 Web InterfaceThe capability for interactive access to the data by modelers, analysts, andexperimenters is provided by an Internet interface to the database. The Common GatewayInterface (CGI) approach of linking database tables was adopted. In this approach theWorld Wide Web serves as an efficient medium for retrieving information from thedatabase.3.3 Query ModesThe contents of a single run can be browsed, the runs that satisfy user specifiedconditions can be searched for, and the values of parameters across a subset of runsmeeting user conditions can be trended using scatter plots or a cluster analysis. All thiscan be done interactively over the World Wide Web from the user’s browser.4. DATA MININGThree cases are described where the understanding of electrorefining on anengineering scale has been improved through use of the database.4.1 Search on Conditions: Experiment SelectionAn application involved identifying experiments suitable for use in estimating avalue for the exchange current density for uranium. This parameter represents afundamental limit on the rate that uranium can be electrotransported out of the cadmium(3)pool. The parameter appears in electrochemical models and influences the proportioningof the applied voltage across the various loss terms (surface overpotential, concentrationoverpotential, and ohmic) and hence plays a key role in the carry over of impurities tothe cathode product. The absence of a published value led us to estimate a value.The search capability was used to identify experiments in the database satisfyingcertain conditions. These conditions ensure that the data reflect processes consistent withthe models to which data was fit. The conditions are: 1) uranium is electrotransportedexclusively from the cadmium pool and there is no contribution from the vessel wall; 2)the anode surface is flat with no scraped dendrites heaping up above it under the deposit;and, 3) there is no shorting, that is, dendrites are not bridging spaces that are normallyopen. The runs are not, however, Iabelled explicitly in the database as to whether eachcondition is met. Instead inspection of the transport mode, applied voltage, and uraniumcontent in the cadmium pool data by the analyst was needed to make that determination.The list of candidate runs was reduced to about ten runs from an initial number of about200 after the database was used in this inspection.A value for the exchange current density was obtained by fitting the model to datafrom the experiments. The most reliable value is obtained for an electrorefiner statewhere the controlling rate process is the surface overpotential at the salt-cadmiuminterface. In this regime the current is very sensitive to the value of the exchange currentdensity parameter. The associated electrorefiner state exists for certain values of the ratioof uranium to zirconium concentration in the cadmium pool and relative current fractions.The database was used to further classify with respect to these measures among thoseruns already meeting the three conditions above. The runs and the class they belong toare given in Table 1. These runs were used to estimate the uranium and zirconiumexchange current densities.The values obtained provide a measure of the role of surface overpotential inelectrorefiner performance. As the original source of uranium is depleted an increase inimpurity transport and reduction in current will occur due to surface overpotentialincrease. The depletion level at which this occurs depends on the value of the exchangecurrent density. The nominal value obtained for exchange current density at 500° C is22 milliamps/cm2 for uranium dissolved in cadmium to saturation and is 2200rnilliarnps/cm2 for solid uranium. The experimental uncertainty in these values is 50percent. There is a further uncertainty associated with the lumped parameter approachfor representing the cadmium pool. A CFD calculation in the future will eliminate thissource of uncertainty. These values indicate that impurity transport and reduced currentdue to increasing surface overpotential should not be an issue until the uranium in pinsegments is depleted down to a few percent and until uranium in the cadmium pool isdepleted down to a few percent of the value at saturation.(4)Table 1 Classification of Deposition Runsclass Criteria ‘f ~ 1, ~a < ~a_wiAuf ~ 1, ma < ~a- , [a]a = [zr]a_aiB “Expected Runs [uldeJ UJIC,4 [ZdcdTrendsurface 64 0.22 0 1overpotentialm1 Ia fi = current fraction, [U]c~ = cad pool U concentration, [Zr]c~ = cad pool Zr concentration, sat= saturation4.2 Timeline Analysis: Long Term Behavior of ZirconiumEven though electrorefining of spent fuel proceeds on a batch basis, the chemicalstate of the electrorefiner evolves on a continuous basis. The content of the electrorefinerchanges as material is added at the start of a run, is removed at the end of the run, andas the constituents react over time. Tracking the contents through time through a massbalance and comparing this to expected behavior is useful for discovering unexpectedtrends. The process of doing so revealed zirconium was behaving in the electrorefinerdifferently than expected.The behavior was initially hinted at by the difficulty found in recovery operationswhen growing zirconium cathodes. The time history of the zirconium content of theelectrorefiner shown in Fig. 1 and the dissolution rate of zirconium solids in theelectrorefiner shown in Fig. 2 were prepared from the database. The data indicate thatfor zirconium in excess of what the cadmium pool could dissolve, the rate at which thiszirconium later dissolves back into an unsaturated cadmium pool correlates more stronglywith when zirconium metal was last introduced rather than the means used to bring it outof solid form. One possibility is that zirconium combines over time with other materialsin the electrorefiner to form a substance from which the zirconium is not nearly as readilydissolved either passively or electrochemically as the pure metal. Samples taken fromthe electrorefiner showed the presence of a solid substance composed of zirconium,uranium, and cadmium. These findings pointed to the need for a better understanding ofthe long term behavior of zirconium if the zirconium inventory is to be managed.(5)18t~ 16-su7514-0“EJ!~“ -QJP=’Jp=#74 790°64lJ97679e 10 -0~s0~8 -G3~E6 %“6.!680 m61 70E4 - Onto 9300105OCZ. 0 CdrnimPod C.mcattrafMs in W% i2m——— .Izfl. ozz[saq [.31.0,11 [a. 0.M5 fzll.o.lz0 t0 102U?O4OWI 607090931W 110Rm t4.mbrFig. 2 Electrorefiner Zirconium Inventory+P.sswe D!!.al.hon0 0 Electrwhemud Oisal.ticm0++++00+ 00 -+0Peak of dectrwefinw Zr !nvmt.vw%i%$--51991 1991.5 1992 1992.5 1993 1993.5 1Time [year)Fig. 3 Rate of Zirconium Dissolving Out ofSolids4.3 Process Inference: Deposit Morphology FactorsA compelling understanding of how a process behaves emerges when patterns inthe data identified by empirical means prove consistent with fundamental electrochemicalprinciples. In one such instance the conditions giving rise to the plate-like crystallinedeposit morphology were identified through data inspection and first principles analysisafter correlating below average collection efficiencies with plate-like morphology.Collection efficiency is a measure of the amount of electricity needed to produce a givenmass tid should be maintained high to maximize throughput. Because of the low(6).+efficiency associated with this morphology, the electrorefiner should be operated to avoidit.Analysis of data in the database linked plate-like crystalline growth with lowmixing and low current density as seen in Fig. 4 and 5. But this is the result expectedfrom the electrochemical theory for dendrite growth. According to the standard0 Uo,phdqy clump● M@m@y D8ndtic+ Morphc4cgy Flate-LJte Crystalline●✝ ●3,. ●,.●=-2s0t●--3- I-1 -0.9 -0.8 -0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1Cauwde to Am-de voltage. voltsFig. 4 Current Versus Voltage Partitioned byDeposit Morphology -50 -0 --60 -g.~._,@$-15n --w --253 -0 Mwholcqy Chmw● Mmplm!qy Oendrtic+ Mo@wlw Pbte.ltke Crystatirm-303 I-20020406980 103 720 140 160 180 :Salt Mraer qmed, FFig. 5 Current Versus Salt Mixer SpeedPartitioned by Morphologyelectrochemical model a concentration boundary layer surrounds all surfaces of thecathode. ~ockris, 1993] A dendrite is created locally when a solid surface grows furtherout into the concentration boundary layer where the fluid has a higher ion concentration.The rate of growth accelerates and gives rise to a dendrite. There are two dependencies.(7)First, as the thickness of the concentration boundary layer is reduced, the probability thata surface will reach sufficiently concentration rich fluid to accelerate growth so that adendrite will form increases. Second, as the concentration gradient is increased anincreased rate of growth concentrated in fewer dendrites occurs giving rise to a moredendritic deposit. Low mixing favors a thicker concentration boundary layer and lowcurrent density favors a smaller concentration gradient. Thus, these two conditions favorplate-like growth rather than dendritic growth.5. CONCLUSIONSInformation technologies including Web-based display and relational databasecapabilities are being used to provide access to data collected from the electro-metallurgical treatment of spent fuel. The objectives are to make readily accessible thenecessary data for development and validation of models and for analysis to ensure thatthe process behavior is well understood and that unexpected trends in the data whichwould indicate phenomena not yet represented in the models are identified. Examplesof three such applications were described.REFERENCESBockris, J., 1993. Surjace Electrochemistry, Plenum Press.McPheeters, C. C., Gay, E. C., Karen, E. J., and Ackerman, J.P., 1997.Electrometallurgically Treating Metal, Oxide, and Al Alloy Spent Nuclear Fuel Types,”Journal of Minerals, Metals, and Materials,” Journal of Minerals, Metals, and Materials,49, 22.(8)

Information technology and data mining for spent fuel treatment

https://digital.library.unt.edu/ark:/67531/metadc710216/m2/1/high_res_d/759089.pdf

Information technology and data mining for spent fuel treatment

Abstract

Similar works

Full text

Available Versions

UNT Digital Library