國立高雄大學圖資館 |

Language: English

Back

Nanoelectronic coupled problems solu...

SpringerLink (Online service)

Nanoelectronic coupled problems solutions

Record Type:	Electronic resources : Monograph/item
Title/Author:	Nanoelectronic coupled problems solutionsedited by E. Jan W. ter Maten ... [et al.].
other author:	ter Maten, E. Jan W.
Published:	Cham :Springer International Publishing :2019.
Description:	xxx, 587 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Coupled problems (Complex systems)
Online resource:	https://doi.org/10.1007/978-3-030-30726-4
ISBN:	9783030307264$q(electronic bk.)

Nanoelectronic coupled problems solutions
Nanoelectronic coupled problems solutions[electronic resource] /edited by E. Jan W. ter Maten ... [et al.]. - Cham :Springer International Publishing :2019. - xxx, 587 p. :ill. (some col.), digital ;24 cm. - The European consortium for mathematics in industry ;29. - European consortium for mathematics in industry ;29..

Equations, discretizations -- Time integration for coupled problems -- Uncertainty quantification -- Model order reduction -- Robustness, reliability, ageing -- Testcases and measurements.

Designs in nanoelectronics often lead to challenging simulation problems and include strong feedback couplings. Industry demands provisions for variability in order to guarantee quality and yield. It also requires the incorporation of higher abstraction levels to allow for system simulation in order to shorten the design cycles, while at the same time preserving accuracy. The methods developed here promote a methodology for circuit-and-system-level modelling and simulation based on best practice rules, which are used to deal with coupled electromagnetic field-circuit-heat problems, as well as coupled electro-thermal-stress problems that emerge in nanoelectronic designs. This book covers: (1) advanced monolithic/multirate/co-simulation techniques, which are combined with envelope/wavelet approaches to create efficient and robust simulation techniques for strongly coupled systems that exploit the different dynamics of sub-systems within multiphysics problems, and which allow designers to predict reliability and ageing; (2) new generalized techniques in Uncertainty Quantification (UQ) for coupled problems to include a variability capability such that robust design and optimization, worst case analysis, and yield estimation with tiny failure probabilities are possible (including large deviations like 6-sigma); (3) enhanced sparse, parametric Model Order Reduction techniques with a posteriori error estimation for coupled problems and for UQ to reduce the complexity of the sub-systems while ensuring that the operational and coupling parameters can still be varied and that the reduced models offer higher abstraction levels that can be efficiently simulated. All the new algorithms produced were implemented, transferred and tested by the EDA vendor MAGWEL. Validation was conducted on industrial designs provided by end-users from the semiconductor industry, who shared their feedback, contributed to the measurements, and supplied both material data and process data. In closing, a thorough comparison to measurements on real devices was made in order to demonstrate the algorithms' industrial applicability.

ISBN: 9783030307264$q(electronic bk.)

Standard No.: 10.1007/978-3-030-30726-4doiSubjects--Topical Terms:

211502
Coupled problems (Complex systems)

LC Class. No.: TA347.C68 / N35 2019

Dewey Class. No.: 621.381

Nanoelectronic coupled problems solutions
LDR:03419nmm a2200349 a 4500 001 569648
003 DE-He213
005 20191106082501.0
006 m d
007 cr nn 008maaau
008 200723s2019 gw s 0 eng d
020 $a 9783030307264$q(electronic bk.)
020 $a 9783030307257$q(paper)
024 7 $a 10.1007/978-3-030-30726-4 $2 doi
035 $a 978-3-030-30726-4
040 $a GP $c GP
041 0 $a eng
050 4 $a TA347.C68 $b N35 2019
072 7 $a PBWH $2 bicssc
072 7 $a MAT003000 $2 bisacsh
072 7 $a PBWH $2 thema
072 7 $a TBJ $2 thema
082 0 4 $a 621.381 $2 23
090 $a TA347.C68 $b N186 2019
245 0 0 $a Nanoelectronic coupled problems solutions $h [electronic resource] / $c edited by E. Jan W. ter Maten ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a xxx, 587 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a The European consortium for mathematics in industry ; $v 29
505 0 $a Equations, discretizations -- Time integration for coupled problems -- Uncertainty quantification -- Model order reduction -- Robustness, reliability, ageing -- Testcases and measurements.
520 $a Designs in nanoelectronics often lead to challenging simulation problems and include strong feedback couplings. Industry demands provisions for variability in order to guarantee quality and yield. It also requires the incorporation of higher abstraction levels to allow for system simulation in order to shorten the design cycles, while at the same time preserving accuracy. The methods developed here promote a methodology for circuit-and-system-level modelling and simulation based on best practice rules, which are used to deal with coupled electromagnetic field-circuit-heat problems, as well as coupled electro-thermal-stress problems that emerge in nanoelectronic designs. This book covers: (1) advanced monolithic/multirate/co-simulation techniques, which are combined with envelope/wavelet approaches to create efficient and robust simulation techniques for strongly coupled systems that exploit the different dynamics of sub-systems within multiphysics problems, and which allow designers to predict reliability and ageing; (2) new generalized techniques in Uncertainty Quantification (UQ) for coupled problems to include a variability capability such that robust design and optimization, worst case analysis, and yield estimation with tiny failure probabilities are possible (including large deviations like 6-sigma); (3) enhanced sparse, parametric Model Order Reduction techniques with a posteriori error estimation for coupled problems and for UQ to reduce the complexity of the sub-systems while ensuring that the operational and coupling parameters can still be varied and that the reduced models offer higher abstraction levels that can be efficiently simulated. All the new algorithms produced were implemented, transferred and tested by the EDA vendor MAGWEL. Validation was conducted on industrial designs provided by end-users from the semiconductor industry, who shared their feedback, contributed to the measurements, and supplied both material data and process data. In closing, a thorough comparison to measurements on real devices was made in order to demonstrate the algorithms' industrial applicability.
650 0 $a Coupled problems (Complex systems) $3 211502
650 0 $a Nanoelectronics $x Mathematics. $3 855742
650 1 4 $a Mathematical Modeling and Industrial Mathematics. $3 274070
650 2 4 $a Continuous Optimization. $3 558846
700 1 $a ter Maten, E. Jan W. $3 792977
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a European consortium for mathematics in industry ; $v 29. $3 855741
856 4 0 $u https://doi.org/10.1007/978-3-030-30726-4
950 $a Mathematics and Statistics (Springer-11649)