Multilevel Monte Carlo applied to chemical engineering systems subject to uncertainty
The aim of this study is to evaluate the performance of Multilevel Monte Carlo (MLMC) sampling technique for uncertainty quantification in chemical engineering systems. Three systems (a mixing tank, a wastewater treatment plant, and a ternary distillation column, all subject to uncertainty) were con...
Uložené v:
| Vydané v: | AIChE journal Ročník 64; číslo 5; s. 1651 - 1661 |
|---|---|
| Hlavní autori: | , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
New York
American Institute of Chemical Engineers
01.05.2018
|
| Predmet: | |
| ISSN: | 0001-1541, 1547-5905 |
| On-line prístup: | Získať plný text |
| Tagy: |
Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
|
| Abstract | The aim of this study is to evaluate the performance of Multilevel Monte Carlo (MLMC) sampling technique for uncertainty quantification in chemical engineering systems. Three systems (a mixing tank, a wastewater treatment plant, and a ternary distillation column, all subject to uncertainty) were considered. The expected values of the systems' observables were estimated using MLMC, Power Series and Polynomial Chaos expansions, and standard Monte Carlo (MC) sampling. The MLMC technique achieved results of significantly greater accuracy than other methods at a lower computational cost than standard MC. This study highlights the nuances of adapting the MLMC technique to chemical engineering systems and the advantages of using MLMC for uncertainty quantification. © 2017 American Institute of Chemical Engineers AIChE J, 64: 1651–1661, 2018 |
|---|---|
| AbstractList | The aim of this study is to evaluate the performance of Multilevel Monte Carlo (MLMC) sampling technique for uncertainty quantification in chemical engineering systems. Three systems (a mixing tank, a wastewater treatment plant, and a ternary distillation column, all subject to uncertainty) were considered. The expected values of the systems' observables were estimated using MLMC, Power Series and Polynomial Chaos expansions, and standard Monte Carlo (MC) sampling. The MLMC technique achieved results of significantly greater accuracy than other methods at a lower computational cost than standard MC. This study highlights the nuances of adapting the MLMC technique to chemical engineering systems and the advantages of using MLMC for uncertainty quantification. © 2017 American Institute of Chemical Engineers AIChE J, 64: 1651–1661, 2018 |
| Author | Kimaev, Grigoriy Ricardez‐Sandoval, Luis A. |
| Author_xml | – sequence: 1 givenname: Grigoriy surname: Kimaev fullname: Kimaev, Grigoriy organization: University of Waterloo – sequence: 2 givenname: Luis A. orcidid: 0000-0001-9867-6778 surname: Ricardez‐Sandoval fullname: Ricardez‐Sandoval, Luis A. email: laricard@uwaterloo.ca organization: University of Waterloo |
| BookMark | eNp1kD1PwzAQhi1UJNrCwD-IxMSQ1o5jJxmriI9KrVjobDmOXVy5TrAdUP49LmVCMJ3u9Lx3umcGJrazEoBbBBcIwmzJtVggCnNyAaaI5EVKKkgmYAohRGkcoCsw8_4Qu6wosynYbQcTtJEf0iTbzgaZ1NyZLuF9b7Rsk9Al4k0eteAmkXavrZRO233iRx_k0Sd-aA5ShBM3WCFd4NqG8RpcKm68vPmpc7B7fHitn9PNy9O6Xm1SgXFO0pZULaUYN5USlSKEVwVtSKkqWBBa5kLQVrUtVaghBWmqkpIWCUUUblVGEWrwHNyd9_auex-kD-zQDc7GkyyDGUYYY4gjtTxTwnXeO6mY0IEHHd91XBuGIDu5Y9Ed-3YXE_e_Er3TR-7GP9mf7Z9R4_g_yFbr-pz4AgLagIU |
| CitedBy_id | crossref_primary_10_1016_j_fuel_2023_127393 crossref_primary_10_1016_j_apenergy_2020_114533 crossref_primary_10_1016_j_cherd_2018_10_006 crossref_primary_10_1002_aic_16262 crossref_primary_10_1016_j_cherd_2018_08_006 crossref_primary_10_1029_2022WR032599 crossref_primary_10_1016_j_ces_2021_117224 crossref_primary_10_1016_j_compchemeng_2020_106918 crossref_primary_10_1016_j_compchemeng_2019_106663 crossref_primary_10_1016_j_ijggc_2020_103113 |
| Cites_doi | 10.1007/s40072-015-0063-9 10.1115/1.1767847 10.1016/j.advwatres.2005.11.013 10.2118/181764-PA 10.1016/j.ress.2017.03.003 10.1002/2016WR019475 10.1111/j.2517-6161.1951.tb00067.x 10.1016/j.jcp.2013.05.039 10.1115/1.2888303 10.1016/j.cam.2016.10.008 10.1016/j.advwatres.2016.01.004 10.1016/j.ress.2004.09.006 10.1002/aic.690420814 10.1016/j.jcp.2013.03.023 10.1016/j.jprocont.2017.07.002 10.1016/j.jprocont.2006.10.008 10.1016/j.jcp.2016.03.027 10.1007/s10596-013-9358-y 10.1017/S096249291500001X 10.1016/j.compchemeng.2016.12.015 10.1002/aic.690450710 10.2307/j.ctv7h0skv 10.1137/120883803 10.1137/110840546 10.1016/j.compchemeng.2014.09.019 10.2307/1268522 10.1080/01621459.2017.1295863 10.1080/00224065.1999.11979891 10.1109/TCST.2003.816419 10.1016/j.jprocont.2003.07.004 10.1002/cjce.22912 10.1002/aic.15702 10.1002/aic.15215 10.1137/S1064827501387826 10.2118/172635-PA 10.1007/978-3-319-33507-0_8 10.2514/6.2009-2274 10.1063/1.4960118 10.1137/140960086 10.1016/j.ces.2014.05.027 10.1002/aic.14040 10.1287/opre.1070.0496 10.1016/j.compchemeng.2014.01.002 10.1016/j.advwatres.2016.06.007 10.1016/S0951-8320(03)00058-9 10.1016/j.jcp.2014.02.047 |
| ContentType | Journal Article |
| Copyright | 2017 American Institute of Chemical Engineers 2018 American Institute of Chemical Engineers |
| Copyright_xml | – notice: 2017 American Institute of Chemical Engineers – notice: 2018 American Institute of Chemical Engineers |
| DBID | AAYXX CITATION 7ST 7U5 8FD C1K L7M SOI |
| DOI | 10.1002/aic.16045 |
| DatabaseName | CrossRef Environment Abstracts Solid State and Superconductivity Abstracts Technology Research Database Environmental Sciences and Pollution Management Advanced Technologies Database with Aerospace Environment Abstracts |
| DatabaseTitle | CrossRef Solid State and Superconductivity Abstracts Technology Research Database Environment Abstracts Advanced Technologies Database with Aerospace Environmental Sciences and Pollution Management |
| DatabaseTitleList | Solid State and Superconductivity Abstracts CrossRef |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering |
| EISSN | 1547-5905 |
| EndPage | 1661 |
| ExternalDocumentID | 10_1002_aic_16045 AIC16045 |
| Genre | article |
| GrantInformation_xml | – fundername: Natural Sciences and Engineering Research Council of Canada |
| GroupedDBID | -~X .3N .4S .DC .GA .Y3 05W 0R~ 10A 1L6 1OB 1OC 1ZS 23M 31~ 33P 3EH 3SF 3V. 3WU 4.4 4ZD 50Y 50Z 51W 51X 52M 52N 52O 52P 52S 52T 52U 52W 52X 53G 5GY 5VS 66C 6J9 6P2 6TJ 702 7PT 7XC 8-0 8-1 8-3 8-4 8-5 88I 8FE 8FG 8FH 8G5 8R4 8R5 8UM 8WZ 930 9M8 A03 A6W AAESR AAEVG AAHHS AAHQN AAIHA AAIKC AAMNL AAMNW AANHP AANLZ AAONW AASGY AAXRX AAYCA AAZKR ABCQN ABCUV ABDEX ABDPE ABEML ABIJN ABJCF ABJNI ABPVW ABUWG ACAHQ ACBEA ACBWZ ACCFJ ACCZN ACGFO ACGFS ACGOD ACIWK ACNCT ACPOU ACRPL ACSCC ACXBN ACXQS ACYXJ ADBBV ADEOM ADIZJ ADKYN ADMGS ADNMO ADOZA ADXAS ADZMN ADZOD AEEZP AEGXH AEIGN AEIMD AENEX AEQDE AEUQT AEUYN AEUYR AFBPY AFFPM AFGKR AFKRA AFPWT AFRAH AFWVQ AFZJQ AHBTC AIAGR AITYG AIURR AIWBW AJBDE AJXKR ALAGY ALMA_UNASSIGNED_HOLDINGS ALUQN ALVPJ AMBMR AMYDB ARCSS ASPBG ATCPS ATUGU AUFTA AVWKF AZBYB AZFZN AZQEC AZVAB BAFTC BDRZF BENPR BFHJK BGLVJ BHBCM BHPHI BLYAC BMNLL BMXJE BNHUX BPHCQ BROTX BRXPI BY8 CCPQU CS3 CZ9 D-E D-F D1I DCZOG DPXWK DR1 DR2 DRFUL DRSTM DWQXO EBS EJD F00 F01 F04 FEDTE G-S G.N GNP GNUQQ GODZA GUQSH H.T H.X HBH HCIFZ HF~ HGLYW HHY HHZ HVGLF HZ~ IX1 J0M JPC KB. KC. KQQ L6V LATKE LAW LC2 LC3 LEEKS LH4 LH6 LITHE LOXES LP6 LP7 LUTES LW6 LYRES M2O M2P M7S MEWTI MK4 MRFUL MRSTM MSFUL MSSTM MXFUL MXSTM N04 N05 N9A NDZJH NF~ NNB O66 O9- OIG P2P P2W P2X P4D PALCI PATMY PDBOC PQQKQ PRG PROAC PTHSS PYCSY Q.N Q11 Q2X QB0 QRW R.K RBB RIWAO RJQFR RNS ROL RWI RX1 S0X SAMSI SUPJJ TAE TN5 TUS UAO UB1 UHS V2E V8K W8V W99 WBFHL WBKPD WH7 WIB WIH WIK WJL WOHZO WQJ WRC WSB WXSBR WYISQ XG1 XPP XSW XV2 Y6R ZE2 ZZTAW ~02 ~IA ~KM ~WT AAMMB AAYXX ABJIA ADMLS AEFGJ AEYWJ AFFHD AGHNM AGQPQ AGXDD AGYGG AIDQK AIDYY CITATION O8X PHGZM PHGZT PQGLB 7ST 7U5 8FD C1K L7M SOI |
| ID | FETCH-LOGICAL-c3345-d59d6633b9fc9f55a976b58f9075684cc6dfdd6f1b575b9865d1cf5f3df2611b3 |
| IEDL.DBID | DRFUL |
| ISICitedReferencesCount | 13 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000429536200013&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0001-1541 |
| IngestDate | Mon Nov 10 03:04:59 EST 2025 Sat Nov 29 07:21:17 EST 2025 Tue Nov 18 21:07:14 EST 2025 Wed Jan 22 16:58:08 EST 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 5 |
| Language | English |
| License | http://onlinelibrary.wiley.com/termsAndConditions#vor |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c3345-d59d6633b9fc9f55a976b58f9075684cc6dfdd6f1b575b9865d1cf5f3df2611b3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ORCID | 0000-0001-9867-6778 |
| PQID | 2023133303 |
| PQPubID | 7879 |
| PageCount | 11 |
| ParticipantIDs | proquest_journals_2023133303 crossref_citationtrail_10_1002_aic_16045 crossref_primary_10_1002_aic_16045 wiley_primary_10_1002_aic_16045_AIC16045 |
| PublicationCentury | 2000 |
| PublicationDate | May 2018 |
| PublicationDateYYYYMMDD | 2018-05-01 |
| PublicationDate_xml | – month: 05 year: 2018 text: May 2018 |
| PublicationDecade | 2010 |
| PublicationPlace | New York |
| PublicationPlace_xml | – name: New York |
| PublicationTitle | AIChE journal |
| PublicationYear | 2018 |
| Publisher | American Institute of Chemical Engineers |
| Publisher_xml | – name: American Institute of Chemical Engineers |
| References | 2007; 17 2017; 317 2014; 116 1990; 57 2013; 1 2003; 81 2015; 3 2010 2009 1999; 45 2008; 56 2016; 52 2016; 95 2016; 94 2014; 63 2012; 10 2005; 89 2003; 11 2015; 24 2016; 4 2016; 6 2013; 59 2013; 17 2004; 14 2017; 99 2002; 24 2004; 57 1951; 13 2016; 21 2006; 29 2017 2016; 62 1999; 31 2013; 251 2016 2016; 314 2013; 250 2009; 5 2017; 165 1979; 21 2014; 71 2014; 268 1996; 42 e_1_2_9_30_1 e_1_2_9_31_1 Box GEP (e_1_2_9_9_1) 1951; 13 e_1_2_9_11_1 e_1_2_9_34_1 e_1_2_9_10_1 e_1_2_9_35_1 e_1_2_9_13_1 e_1_2_9_32_1 e_1_2_9_12_1 e_1_2_9_33_1 e_1_2_9_15_1 e_1_2_9_38_1 e_1_2_9_14_1 e_1_2_9_39_1 e_1_2_9_36_1 e_1_2_9_16_1 e_1_2_9_37_1 e_1_2_9_19_1 e_1_2_9_18_1 e_1_2_9_41_1 e_1_2_9_42_1 e_1_2_9_20_1 e_1_2_9_40_1 e_1_2_9_22_1 e_1_2_9_45_1 e_1_2_9_21_1 e_1_2_9_46_1 e_1_2_9_24_1 e_1_2_9_43_1 e_1_2_9_23_1 e_1_2_9_44_1 e_1_2_9_8_1 e_1_2_9_7_1 e_1_2_9_6_1 e_1_2_9_5_1 e_1_2_9_4_1 e_1_2_9_3_1 e_1_2_9_2_1 Xiu D. (e_1_2_9_17_1) 2009; 5 e_1_2_9_26_1 e_1_2_9_25_1 e_1_2_9_28_1 e_1_2_9_47_1 e_1_2_9_27_1 e_1_2_9_48_1 e_1_2_9_29_1 |
| References_xml | – volume: 57 start-page: 345 issue: 5 year: 2004 end-page: 384 article-title: Verification, validation, and predictive capability in computational engineering and physics publication-title: Appl Mech Rev. – volume: 59 start-page: 2497 issue: 7 year: 2013 end-page: 2514 article-title: Simultaneous process synthesis and control design under uncertainty: a worst‐case performance approach publication-title: AIChE J. – volume: 314 start-page: 661 year: 2016 end-page: 681 article-title: Approximation of probability density functions by the Multilevel Monte Carlo Maximum Entropy method publication-title: J Comput Phys. – volume: 116 start-page: 590 year: 2014 end-page: 600 article-title: Uncertainty analysis and robust optimization of multiscale process systems with application to epitaxial thin film growth publication-title: Chem Eng Sci. – volume: 42 start-page: 2251 issue: 8 year: 1996 end-page: 2272 article-title: Optimal design of dynamic systems under uncertainty publication-title: AIChE J. – volume: 56 start-page: 607 issue: 3 year: 2008 end-page: 617 article-title: Multi‐level Monte Carlo path simulation publication-title: Oper Res. – volume: 251 start-page: 445 year: 2013 end-page: 460 article-title: Stabilized multilevel Monte Carlo method for stiff stochastic differential equations publication-title: J Comput Phys. – volume: 10 start-page: 146 issue: 1 year: 2012 end-page: 179 article-title: Multilevel Monte Carlo for continuous time Markov Chains, with applications in biochemical kinetics publication-title: Multiscale Model Simul. – volume: 1 start-page: 2 issue: 1 year: 2013 end-page: 18 article-title: Mean exit times and the multilevel Monte Carlo method publication-title: SIAM/ASA J Uncertain Quantif. – volume: 14 start-page: 411 issue: 4 year: 2004 end-page: 422 article-title: Open‐loop and closed‐loop robust optimal control of batch processes using distributional and worst‐case analysis publication-title: J Process Control. – volume: 21 start-page: 1192 issue: 4 year: 2016 end-page: 1203 article-title: Applying the Multilevel Monte Carlo method for heterogeneity‐induced uncertainty quantification of surfactant/polymer flooding publication-title: SPE J. – volume: 17 start-page: 229 issue: 3 year: 2007 end-page: 240 article-title: Distributional uncertainty analysis using power series and polynomial chaos expansions publication-title: J Process Control. – article-title: A comparison of efficient uncertainty quantification techniques for stochastic multiscale systems publication-title: AIChE J. – volume: 6 start-page: 75020 issue: 7 year: 2016 article-title: Multi‐level methods and approximating distribution functions publication-title: AIP Adv. – volume: 5 start-page: 242 issue: 2–4 year: 2009 end-page: 272 article-title: Fast numerical methods for stochastic computations: a review publication-title: Commun Comput Phys. – volume: 268 start-page: 39 year: 2014 end-page: 50 article-title: Solver‐based vs. grid‐based multilevel Monte Carlo for two phase flow and transport in random heterogeneous porous media publication-title: J Comput Phys. – volume: 89 start-page: 305 issue: 3 year: 2005 end-page: 330 article-title: A comparison of uncertainty and sensitivity analysis results obtained with random and Latin hypercube sampling publication-title: Reliab Eng Syst Saf. – volume: 24 start-page: 619 issue: 2 year: 2002 end-page: 644 article-title: The Wiener‐Askey polynomial chaos for stochastic differential equations publication-title: SIAM J Sci Comput. – volume: 24 start-page: 259 year: 2015 end-page: 328 article-title: Multilevel Monte Carlo methods publication-title: Acta Numer. – article-title: Robust dynamic optimization in heterogeneous multiscale catalytic flow reactors using polynomial chaos expansion publication-title: J Process Control. – volume: 94 start-page: 498 year: 2016 end-page: 509 article-title: Multilevel Monte Carlo methods for computing failure probability of porous media flow systems publication-title: Adv Water Resour. – article-title: Robust optimization of a multiscale heterogeneous catalytic reactor system with spatially‐varying uncertainty descriptions using polynomial chaos expansions publication-title: Can J Chem Eng. – start-page: 209 year: 2016 end-page: 227 – volume: 45 start-page: 1469 issue: 7 year: 1999 end-page: 1476 article-title: Worst‐case performance analysis of optimal batch control trajectories publication-title: AIChE J. – year: 2010 – volume: 95 start-page: 46 year: 2016 end-page: 60 article-title: On the predictivity of pore‐scale simulations: estimating uncertainties with multilevel Monte Carlo publication-title: Adv Water Resour. – volume: 250 start-page: 685 year: 2013 end-page: 702 article-title: Multilevel Monte Carlo for two phase flow and Buckley‐Leverett transport in random heterogeneous porous media publication-title: J Comput Phys. – volume: 21 start-page: 2027 issue: 6 year: 2016 end-page: 2037 article-title: Parallel Multilevel Monte Carlo for two‐phase flow and transport in random heterogeneous porous media with sampling error and discretization error balancing publication-title: SPE J. – start-page: 1 year: 2009 end-page: 37 – volume: 31 start-page: 30 issue: 1 year: 1999 end-page: 44 article-title: Response surface methodology–current status and future directions publication-title: J Qual Technol. – volume: 13 start-page: 1 issue: 1 year: 1951 end-page: 45 article-title: On the Experimental Attainment of Optimum Conditions publication-title: J R Stat Soc Ser B. – volume: 71 start-page: 618 year: 2014 end-page: 635 article-title: Integrated design and control of chemical processes—part II: an illustrative example publication-title: Comput Chem Eng. – volume: 165 start-page: 188 year: 2017 end-page: 196 article-title: Multilevel Monte Carlo for reliability theory. publication-title: Eng Syst Saf. – volume: 63 start-page: 66 year: 2014 end-page: 81 article-title: Simultaneous design and MPC‐based control for dynamic systems under uncertainty: a stochastic approach publication-title: Comput Chem Eng. – volume: 17 start-page: 833 issue: 5 year: 2013 end-page: 850 article-title: Multilevel Monte Carlo methods using ensemble level mixed MsFEM for two‐phase flow and transport simulations publication-title: Comput Geosci. – volume: 3 start-page: 267 issue: 1 year: 2015 end-page: 295 article-title: Multilevel Monte Carlo approximation of distribution functions and densities publication-title: SIAM/ASA J Uncertain Quantif. – volume: 99 start-page: 66 year: 2017 end-page: 81 article-title: Simultaneous design and control under uncertainty: a back‐off approach using power series expansions publication-title: Comput Chem Eng. – volume: 4 start-page: 3 issue: 1 year: 2016 end-page: 40 article-title: Estimation of arbitrary order central statistical moments by the Multilevel Monte Carlo method publication-title: Stoch Partial Differ Equations Anal Comput. – volume: 317 start-page: 700 year: 2017 end-page: 717 article-title: Multilevel approximate Bayesian approaches for flows in highly heterogeneous porous media and their applications publication-title: J Comput Appl Math. – volume: 11 start-page: 694 issue: 5 year: 2003 end-page: 704 article-title: Worst‐case and distributional robustness analysis of finite‐time control trajectories for nonlinear distributed parameter systems publication-title: IEEE Trans Control Syst Technol. – volume: 57 start-page: 197 issue: 1 year: 1990 end-page: 202 article-title: Polynomial chaos in stochastic finite elements publication-title: J Appl Mech. – year: 2017 article-title: Upscaling uncertainty with dynamic discrepancy for a multi‐scale carbon capture system publication-title: J Am Stat Assoc. – volume: 81 start-page: 23 issue: 1 year: 2003 end-page: 69 article-title: Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems publication-title: Reliab Eng Syst Saf. – volume: 29 start-page: 1586 issue: 11 year: 2006 end-page: 1597 article-title: A framework for dealing with uncertainty due to model structure error publication-title: Adv Water Resour. – volume: 21 start-page: 239 issue: 2 year: 1979 end-page: 245 article-title: A comparison of three methods for selecting values of input variables in the analysis of output from a computer code publication-title: Technometrics. – volume: 62 start-page: 1 issue: 7 year: 2016 end-page: 17 article-title: Distributional uncertainty analysis and robust optimization in spatially heterogeneous multiscale process systems publication-title: AIChE J. – volume: 52 start-page: 9642 issue: 12 year: 2016 end-page: 9660 article-title: An improved multilevel Monte Carlo method for estimating probability distribution functions in stochastic oil reservoir simulations publication-title: Water Resour Res. – ident: e_1_2_9_28_1 doi: 10.1007/s40072-015-0063-9 – ident: e_1_2_9_2_1 doi: 10.1115/1.1767847 – ident: e_1_2_9_5_1 doi: 10.1016/j.advwatres.2005.11.013 – ident: e_1_2_9_35_1 doi: 10.2118/181764-PA – ident: e_1_2_9_41_1 doi: 10.1016/j.ress.2017.03.003 – ident: e_1_2_9_32_1 doi: 10.1002/2016WR019475 – volume: 13 start-page: 1 issue: 1 year: 1951 ident: e_1_2_9_9_1 article-title: On the Experimental Attainment of Optimum Conditions publication-title: J R Stat Soc Ser B. doi: 10.1111/j.2517-6161.1951.tb00067.x – ident: e_1_2_9_25_1 doi: 10.1016/j.jcp.2013.05.039 – ident: e_1_2_9_16_1 doi: 10.1115/1.2888303 – ident: e_1_2_9_36_1 doi: 10.1016/j.cam.2016.10.008 – ident: e_1_2_9_38_1 doi: 10.1016/j.advwatres.2016.01.004 – ident: e_1_2_9_7_1 doi: 10.1016/j.ress.2004.09.006 – ident: e_1_2_9_47_1 doi: 10.1002/aic.690420814 – ident: e_1_2_9_33_1 doi: 10.1016/j.jcp.2013.03.023 – ident: e_1_2_9_22_1 doi: 10.1016/j.jprocont.2017.07.002 – ident: e_1_2_9_20_1 doi: 10.1016/j.jprocont.2006.10.008 – ident: e_1_2_9_30_1 doi: 10.1016/j.jcp.2016.03.027 – ident: e_1_2_9_39_1 doi: 10.1007/s10596-013-9358-y – ident: e_1_2_9_24_1 doi: 10.1017/S096249291500001X – ident: e_1_2_9_43_1 doi: 10.1016/j.compchemeng.2016.12.015 – ident: e_1_2_9_11_1 doi: 10.1002/aic.690450710 – ident: e_1_2_9_18_1 doi: 10.2307/j.ctv7h0skv – ident: e_1_2_9_27_1 doi: 10.1137/120883803 – ident: e_1_2_9_26_1 doi: 10.1137/110840546 – ident: e_1_2_9_44_1 doi: 10.1016/j.compchemeng.2014.09.019 – ident: e_1_2_9_6_1 doi: 10.2307/1268522 – ident: e_1_2_9_4_1 doi: 10.1080/01621459.2017.1295863 – ident: e_1_2_9_10_1 doi: 10.1080/00224065.1999.11979891 – ident: e_1_2_9_12_1 doi: 10.1109/TCST.2003.816419 – ident: e_1_2_9_13_1 doi: 10.1016/j.jprocont.2003.07.004 – ident: e_1_2_9_21_1 doi: 10.1002/cjce.22912 – ident: e_1_2_9_46_1 doi: 10.1002/aic.15702 – ident: e_1_2_9_15_1 doi: 10.1002/aic.15215 – ident: e_1_2_9_19_1 doi: 10.1137/S1064827501387826 – ident: e_1_2_9_42_1 doi: 10.2118/172635-PA – ident: e_1_2_9_40_1 doi: 10.1007/978-3-319-33507-0_8 – ident: e_1_2_9_3_1 doi: 10.2514/6.2009-2274 – volume: 5 start-page: 242 issue: 2 year: 2009 ident: e_1_2_9_17_1 article-title: Fast numerical methods for stochastic computations: a review publication-title: Commun Comput Phys. – ident: e_1_2_9_31_1 doi: 10.1063/1.4960118 – ident: e_1_2_9_29_1 doi: 10.1137/140960086 – ident: e_1_2_9_14_1 doi: 10.1016/j.ces.2014.05.027 – ident: e_1_2_9_48_1 doi: 10.1002/aic.14040 – ident: e_1_2_9_23_1 doi: 10.1287/opre.1070.0496 – ident: e_1_2_9_45_1 doi: 10.1016/j.compchemeng.2014.01.002 – ident: e_1_2_9_37_1 doi: 10.1016/j.advwatres.2016.06.007 – ident: e_1_2_9_8_1 doi: 10.1016/S0951-8320(03)00058-9 – ident: e_1_2_9_34_1 doi: 10.1016/j.jcp.2014.02.047 |
| SSID | ssj0012782 |
| Score | 2.3144028 |
| Snippet | The aim of this study is to evaluate the performance of Multilevel Monte Carlo (MLMC) sampling technique for uncertainty quantification in chemical engineering... |
| SourceID | proquest crossref wiley |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 1651 |
| SubjectTerms | Chemical engineering Computer applications Distillation Monte Carlo simulation multilevel Monte Carlo Polynomial Chaos Power Series Sampling Studies Uncertainty uncertainty quantification Wastewater treatment Wastewater treatment plants |
| Title | Multilevel Monte Carlo applied to chemical engineering systems subject to uncertainty |
| URI | https://onlinelibrary.wiley.com/doi/abs/10.1002%2Faic.16045 https://www.proquest.com/docview/2023133303 |
| Volume | 64 |
| WOSCitedRecordID | wos000429536200013&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVWIB databaseName: Wiley Online Library Full Collection 2020 customDbUrl: eissn: 1547-5905 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0012782 issn: 0001-1541 databaseCode: DRFUL dateStart: 19980101 isFulltext: true titleUrlDefault: https://onlinelibrary.wiley.com providerName: Wiley-Blackwell |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LS8NAEB5q60EPvsX6YhEPXkLTJJvs4qlUi4IWEQu9hX1koVBaaVLBf-9sNn0ICoK3HGY3YWY3883s7DcA14ajZWPGPc1D34uYEB7PEt_jlErFE5_7mpXNJpJ-nw2H_KUGt4u7MI4fYplwszuj_F_bDS5k3lqRhoqRsqmRiG5AI8B1S-vQuHvtDZ6WhwhBwhxZOEbMiBTaC2IhP2gtB393RyuMuY5US1fT2_3XR-7BToUwScctiX2oZZMD2F7jHTyEQXntdmzrhcizpaciXTEbT4lwkJQUU6IqIgGSrQYSR_uck3wubfrGyqFbdEUFxecRDHr3b90Hr-qv4KkwjKinKdcIOELJjeKGUoHQRFKG5ktozCKlYm20jk1bIqaTnMVUt5WhJtQG4662DI-hPplOshMgLKJS4KQqCrVtgCWUiQIdYzhGRRQkSRNuFmpOVUU-bntgjFNHmxykqKm01FQTrpai745x4yeh84Wt0mrT5antBI8hNzplfF1pld8nSDuP3fLh9O-iZ7CFcIm5csdzqBezeXYBm-qjGOWzy2r1fQF43twc |
| linkProvider | Wiley-Blackwell |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3dS8MwED_mJqgPfovzM4gPvhS7NmkT8GVMx4bbENnAt5ImDQhjk20K_vdemu5DUBB868MlLblL73eXy-8Aro1AzUZceFqEvke5lJ7IYt8TjKVKxL7wNc-bTcS9Hn95EU8luJvfhXH8EIuEm90Z-f_abnCbkL5dsobKV2VzI5StQYWiGaF9V-6fm4PO4hQhiLljC8eQGaFCbc4s5Ae3i8Hf_dESZK5C1dzXNHf-95W7sF1gTFJ3RrEHpWy0D1srzIMHMMgv3g5txRDpWoIq0pCT4ZhIB0rJbExUQSVAsuVA4oifp2T6ntoEjpVDx-jKCmafhzBoPvQbLa_osOCpMKTM00xohBxhKowShjGJ4CRlHBUYs4hTpSJttI5MLUVUlwoeMV1ThplQG4y8aml4BOXReJQdA-GUpRInVTTUtgWWVIYGOsKAjEkaxHEVbubrnKiCftx2wRgmjjg5SHClknylqnC1EH1znBs_CZ3NlZUU226a2F7wGHSjW8bX5Wr5fYKk3m7kDyd_F72EjVa_20k67d7jKWwieOKu-PEMyrPJe3YO6-pj9jqdXBSm-AWvmeAM |
| linkToPdf | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3dS8MwED_mJqIPfovTqUF88KXYtUmbgC9jszicY4iDvZU0aWAwtrEPwf_epGm3CQqCb324pCWX6_3ucvkdwJ1iWrMBZY5kvutgyrnD0tB1GCGJYKHLXEmzZhNht0sHA9YrwWNxF8byQ6wSbsYysv-1MfB0KtXDmjWUD4XJjWCyBRVsmsiUodJ6i_qd1SmCF1LLFq5DZg0V6gWzkOs9rAZ_90drkLkJVTNfEx387ysPYT_HmKhhN8URlNLxMextMA-eQD-7eDsyFUPo1RBUoSafjSaIW1CKFhMkcioBlK4HIkv8PEfzZWISOEZOO0ZbVrD4PIV-9PTefHbyDguO8H1MHEmY1JDDT5gSTBHCNThJCNUKDElAsRCBVFIGqp5oVJcwGhBZF4ooXyodedUT_wzK48k4PQdEMUm4nlRgX5oWWFwo7MlAB2SEYy8Mq3BfrHMscvpx0wVjFFviZC_WKxVnK1WF25Xo1HJu_CRUK5QV52Y3j00veB10a7esX5ep5fcJ4ka7mT1c_F30BnZ6rSjutLsvl7CrsRO1tY81KC9my_QKtsXHYjifXec78QtpGN-H |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Multilevel+Monte+Carlo+applied+to+chemical+engineering+systems+subject+to+uncertainty&rft.jtitle=AIChE+journal&rft.au=Kimaev%2C+Grigoriy&rft.au=Ricardez%E2%80%90Sandoval%2C+Luis+A.&rft.date=2018-05-01&rft.issn=0001-1541&rft.eissn=1547-5905&rft.volume=64&rft.issue=5&rft.spage=1651&rft.epage=1661&rft_id=info:doi/10.1002%2Faic.16045&rft.externalDBID=10.1002%252Faic.16045&rft.externalDocID=AIC16045 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0001-1541&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0001-1541&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0001-1541&client=summon |