A Predictor-Corrector Algorithm for Fast Polynomial Chaos-Based Uncertainty Quantification of Multi-Walled Carbon Nanotube Interconnects
In this article, a predictor-corrector algorithm for the fast polynomial chaos (PC)-based uncertainty quantification (UQ) of multi-walled carbon nanotube (MWCNT) interconnect networks is presented. The proposed algorithm intelligently combines the numerical efficiency of the approximate equivalent s...
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| Veröffentlicht in: | IEEE transactions on components, packaging, and manufacturing technology (2011) packaging, and manufacturing technology (2011), 2019-10, Vol.9 (10), p.1963-1975 |
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| container_issue | 10 |
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| container_title | IEEE transactions on components, packaging, and manufacturing technology (2011) |
| container_volume | 9 |
| creator | Li, Yingheng Bhatnagar, Sakshi Merkely, Amanda Weber, David Charles Roy, Sourajeet |
| description | In this article, a predictor-corrector algorithm for the fast polynomial chaos (PC)-based uncertainty quantification (UQ) of multi-walled carbon nanotube (MWCNT) interconnect networks is presented. The proposed algorithm intelligently combines the numerical efficiency of the approximate equivalent single conductor (ESC) model of the MWCNT interconnect network with the rigor and accuracy of a multi-conductor circuit (MCC) model. Consequently, this algorithm significantly accelerates the generation of the PC surrogate models (or metamodels) of the network responses for minimal loss in accuracy. These metamodels can be probed efficiently and repeatedly to quantify the impact of manufacturing and fabrication process uncertainty on the MWCNT network responses. |
| doi_str_mv | 10.1109/TCPMT.2019.2936262 |
| format | Article |
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(IEEE) 2019</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c295t-5729552b4292be16ff93ec49df8980923d1dffe1e6770c835441fe751ecfdeb93</citedby><cites>FETCH-LOGICAL-c295t-5729552b4292be16ff93ec49df8980923d1dffe1e6770c835441fe751ecfdeb93</cites><orcidid>0000-0002-9860-3242 ; 0000-0002-5454-9897</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8805342$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/8805342$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Li, Yingheng</creatorcontrib><creatorcontrib>Bhatnagar, Sakshi</creatorcontrib><creatorcontrib>Merkely, Amanda</creatorcontrib><creatorcontrib>Weber, David Charles</creatorcontrib><creatorcontrib>Roy, Sourajeet</creatorcontrib><title>A Predictor-Corrector Algorithm for Fast Polynomial Chaos-Based Uncertainty Quantification of Multi-Walled Carbon Nanotube Interconnects</title><title>IEEE transactions on components, packaging, and manufacturing technology (2011)</title><addtitle>TCPMT</addtitle><description>In this article, a predictor-corrector algorithm for the fast polynomial chaos (PC)-based uncertainty quantification (UQ) of multi-walled carbon nanotube (MWCNT) interconnect networks is presented. 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The proposed algorithm intelligently combines the numerical efficiency of the approximate equivalent single conductor (ESC) model of the MWCNT interconnect network with the rigor and accuracy of a multi-conductor circuit (MCC) model. Consequently, this algorithm significantly accelerates the generation of the PC surrogate models (or metamodels) of the network responses for minimal loss in accuracy. These metamodels can be probed efficiently and repeatedly to quantify the impact of manufacturing and fabrication process uncertainty on the MWCNT network responses.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/TCPMT.2019.2936262</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0002-9860-3242</orcidid><orcidid>https://orcid.org/0000-0002-5454-9897</orcidid></addata></record> |
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| subjects | Algorithms Carbon nanotubes Circuits Conductors equivalent single conductor (ESC) model Integrated circuit interconnections Integrated circuit modeling Metamodels Model accuracy Multi wall carbon nanotubes multi-conductor circuit (MCC) model Numerical models polynomial chaos (PC) Polynomials Prediction algorithms Predictor-corrector methods SPICE transient response Uncertainty uncertainty quantification (UQ) |
| title | A Predictor-Corrector Algorithm for Fast Polynomial Chaos-Based Uncertainty Quantification of Multi-Walled Carbon Nanotube Interconnects |
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