A hybrid mechanistic machine learning approach to model industrial network dynamics for sustainable design of emerging carbon capture and utilization technologies
Source abstract
Abstract
Industrial networks consist of multiple industrial nodes interacting with each other through material exchanges that support the overall production goal of the network.
Only a short abstract or summary was supplied by the source.
Source: crossref · Quality: short
Research context
OpenAlex topics: Process Optimization and Integration · Gene Regulatory Network Analysis · Microbial Metabolic Engineering and Bioproduction
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Agricultural & Biological Engineering, Purdue University, West Lafayette, USA
Microsoft Research, Hyderabad, India
Environmental & Ecological Engineering, Purdue University, West Lafayette, USA
Davidson School of Chemical Engineering (By Courtesy), Purdue University, West Lafayette, USA
Funding
Division of Chemical, Bioengineering, Environmental, and Transport Systems · National Science Foundation
References (55)
Show source-provided references
1. I. P. on Climate Change, The evidence is clear: the time for action is now. We can halve emissions by 2030 , 2022 , https://www.ipcc.ch/2022/04/04/ipcc-ar6-wgiii-pressrelease/
2. U. S. E. P. Agency , Greenhouse Gas Inventory Data Explorer , 2022 , https://cfpub.epa.gov/ghgdata/inventoryexplorer/#industry/entiresector/allgas/category/all
3. A. J. L.Angela and C.Jones , Carbon Capture and Sequestration (CCS) in the United States (R44902) , 2022
4. Laufenberg · Bioresour. Technol. · 2003 · 87 · 16710.1016/S0960-8524(02)00167-0 ↗
5. Panda · Renewable Sustainable Energy Rev. · 2010 · 14 · 23310.1016/j.rser.2009.07.005 ↗
6. Muhlack · Waste Manage. · 2018 · 72 · 9910.1016/j.wasman.2017.11.011 ↗
7. Shekhar · J. Power Sources · 2022 · 523 · 23101510.1016/j.jpowsour.2022.231015 ↗
8. J. B.Guinee , R.Heijungs , G.Huppes , A.Zamagni , P.Masoni , R.Buonamici , T.Ekvall and T.Rydberg , Life Cycle Assessment: Past, Present, and Future , 2011
9. Fischer-Kowalski · J. Ind. Ecol. · 2011 · 15 · 85510.1111/j.1530-9290.2011.00366.x ↗
10. Bankes · Proc. Natl. Acad. Sci. U. S. A. · 2002 · 99 · 719910.1073/pnas.072081299 ↗
11. Bebbington · Ecol. Econ. · 2007 · 61 · 22410.1016/j.ecolecon.2006.10.021 ↗
12. Shamsuzzaman · Applied Energy · 2021 · 300 · 11735210.1016/j.apenergy.2021.117352 ↗
13. Corbett · Eur. J. Oper. Res. · 2002 · 139 · 6810.1016/S0377-2217(01)00155-2 ↗
14. Coyle · J. Oper. Res. Soc. · 1997 · 48 · 54410.1057/palgrave.jors.2600682 ↗
15. G.Radons and R.Neugebauer , Nonlinear Dynamics of Production Systems , Wiley Online Library , 200410.1002/3527602585 ↗
16. Leonov · IFAC Proceedings Volumes · 2013 · 46 · 3310.3182/20130619-3-RU-3018.00638 ↗
17. Shi · J. Phys.: Conf. Ser. · 2021 · 012037
18. B. J.Angerhofer and M. C.Angelides , 2000 Winter Simulation Conference Proceedings (Cat. No. 00CH37165) , 2000 , pp. 342–35110.1109/WSC.2000.899737 ↗
19. Bichraoui · Procedia Environ. Sci. · 2013 · 17 · 19510.1016/j.proenv.2013.02.029 ↗
20. K. J.Keesman and K. J.Keesman , System Identification: an Introduction , Springer , 2011 , vol. 210.1007/978-0-85729-522-4 ↗
21. Ljung · Annu. Rev. Control · 2010 · 34 · 110.1016/j.arcontrol.2009.12.001 ↗
22. Brunton · Annu. Rev. Fluid. Mech. · 2020 · 52 · 47710.1146/annurev-fluid-010719-060214 ↗
23. Y. J.Cho , N.Ramakrishnan and Y.Cao , Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining , 2008 , pp. 142–15010.1145/1401890.1401912 ↗
24. Karnaukhov · Biophys. J. · 2007 · 92 · 345910.1529/biophysj.106.093344 ↗
25. Craciun · J. Math. Chem. · 2008 · 44 · 24410.1007/s10910-007-9307-x ↗
26. Bachnas · J. Process Control · 2014 · 24 · 27210.1016/j.jprocont.2014.01.015 ↗
27. Subramanian · Machine Learning with Applications · 2021 · 3 · 10001410.1016/j.mlwa.2020.100014 ↗
28. Farlessyost · Nonlinear Dyn. · 2022 · 110 · 161310.1007/s11071-022-07695-x ↗
29. Noël · Mech. Syst. Signal. Process. · 2017 · 83 · 210.1016/j.ymssp.2016.07.020 ↗
30. Sirca Jr · Sci. Iran. · 2012 · 19 · 135510.1016/j.scient.2012.09.002 ↗
31. M.Sorokina , S.Sygletos and S.Turitsyn , 2017 19th International Conference on Transparent Optical Networks (ICTON) , 2017 , pp. 1–4
32. Loiseau · Theor. Comput. Fluid Dyn. · 2020 · 34 · 33910.1007/s00162-020-00536-w ↗
33. Hoffmann · J. Chem. Phys. · 2019 · 150 · 02510110.1063/1.5066099 ↗
34. Lai · J. Sound Vib. · 2021 · 508 · 11619610.1016/j.jsv.2021.116196 ↗
35. Y.Sun , L.Zhang and H.Schaeffer , Mathematical and Scientific Machine Learning , 2020 , pp. 352–372
36. Zhang · Multiscale Model. Simul. · 2019 · 17 · 94810.1137/18M1189828 ↗
37. Boninsegna · J. Chem. Phys. · 2018 · 148 · 24172310.1063/1.5018409 ↗
38. Åström · Automatica · 1971 · 7 · 12310.1016/0005-1098(71)90059-8 ↗
39. Bongard · Proc. Natl. Acad. Sci. U. S. A. · 2007 · 104 · 994310.1073/pnas.0609476104 ↗
40. Brunton · Proc. Natl. Acad. Sci. U. S. A. · 2016 · 113 · 393210.1073/pnas.1517384113 ↗
41. Raissi · J. Comput. Phys. · 2017 · 348 · 68310.1016/j.jcp.2017.07.050 ↗
42. Ouyang · Phys. Rev. Mater. · 2018 · 2 · 08380210.1103/PhysRevMaterials.2.083802 ↗
43. R. T.Chen , Y.Rubanova , J.Bettencourt and D. K.Duvenaud , Advances in Neural Information Processing Systems , 2018 , vol. 31
44. Kukreja · IFAC Proceedings Volumes · 2006 · 39 · 81410.3182/20060329-3-AU-2901.00128 ↗
45. Cortiella · Comput. Methods Appl. Mech. Eng. · 2021 · 376 · 11362010.1016/j.cma.2020.113620 ↗
46. Marquardt · Am. Stat. · 1975 · 29 · 310.1080/00031305.1975.10479105 ↗
47. Zheng · IEEE Access · 2018 · 7 · 140410.1109/ACCESS.2018.2886528 ↗
48. Zou · J. R. Stat. Soc. Series B Stat. Methodol. · 2005 · 67 · 30110.1111/j.1467-9868.2005.00503.x ↗
49. B. M.de Silva , K.Champion , M.Quade , J.-C.Loiseau , J. N.Kutz and S. L.Brunton , arXiv, preprint, 2020, arXiv:2004.08424, 10.48550/arXiv.2004.0842410.48550/arXiv.2004.08424 ↗
50. R.Davis , C.Kinchin , J.Markham , E.Tan , L.Laurens , D.Sexton , D.Knorr , P.Schoen and J.Lukas , Process Design and Economics for the Conversion of Algal Biomass to Biofuels: Algal Biomass Fractionation to Lipid-And Carbohydrate-Derived Fuel Products , technical report, National Renewable Energy Lab , Golden, Co, United States , 201410.2172/1271650 ↗
51. J. D.Lambert , et al. , Numerical Methods for Ordinary Differential Systems , Wiley , New York , 1991 , vol. 146
52. U. C. Bureau , Census Bureau Regions and Divisions with State FIPS Codes , 2019 , http://web.archive.org/web/20080207010024/http://www.808multimedia.com/winnt/kernel.htm
53. B. International , U.S. Biodiesel Plants , 2023 , https://biodieselmagazine.com/plants/listplants/USA/
54. Independent Statistics and Analysis, U.S. E. I. A. , U.S. Energy-Related Carbon Dioxide Emissions 2021 , 2022 , https://www.eia.gov/environment/emissions/carbon/pdf/2021_co2analysis.pdf
55. Y.Huang , Toward Dynamic Sustainability Assessment in the Digital Age , 2022