Read Nanoelectronic Coupled Problems Solutions (Mathematics in Industry Book 29)

Nanoelectronic Coupled Problems Solutions (Mathematics in Industry Book 29)

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Description:Designs in nanoelectronics often lead to large-size simulation problems and include strong feedback couplings. Industry demands the provisions of variability 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 scientific challenges are: (1) to create efficient and robust simulation techniques for strongly coupled systems, that exploit the different dynamics of sub-systems within multiphysics problems and that allow designers to predict reliability and ageing; (2) 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) 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 models that are efficient to simulate. The methods developed for this advance a methodology for circuit-and-system-level modelling and simulation based on best practice rules to deal with coupled electromagnetic field-circuit-heat problems as well as coupled electro-thermal-stress problems that emerge in nanoelectronic designs. The new methods are robust and allow for strong feedback coupling when integrating systems to increase the performance of both existing devices and when integrating systems to produce new devices. With the new techniques it is possible to efficiently analyze the effects due to variability. Our methods are designed to solve reliability questions resulting from manufacturability. They facilitate robust design as well as enable worst case analysis. They can also be used to study effects due to ageing. Ageing causes variations in parameters over a long-term period, which cannot be predicted exactly and thus are typically uncertain. Novel Model Order Reduction techniques, developed here for the fast repeated simulation of the coupled problems under consideration, are applicable to both coupled systems and parameterized sub-systems. As such they are an essential ingredient for the Uncertainty Quantification. In summary, our solutions are:- advanced co-simulation/multirate/monolithic techniques, combined with envelope/wavelet approaches;- new generalized techniques in Uncertainty Quantification (UQ) for coupled problems, tuned to the statistical demands from manufacturability;- enhanced parametric Model Order Reduction techniques for coupled problems and for UQ.All the new algorithms produced were implemented, transferred and tested by the EDA-vendor MAGWEL. Validation was conducted on industrial designs provided by partners from semiconductor industry. These industrial end-users gave feedback during the project life-time, contributed to measurements and supplied material data as well as process data. A thorough comparison to measurements on real devices was being made to demonstrate the industrial applicability.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Nanoelectronic Coupled Problems Solutions (Mathematics in Industry Book 29). To get started finding Nanoelectronic Coupled Problems Solutions (Mathematics in Industry Book 29), you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

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ISBN: 3030307263

Description: Designs in nanoelectronics often lead to large-size simulation problems and include strong feedback couplings. Industry demands the provisions of variability 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 scientific challenges are: (1) to create efficient and robust simulation techniques for strongly coupled systems, that exploit the different dynamics of sub-systems within multiphysics problems and that allow designers to predict reliability and ageing; (2) 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) 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 models that are efficient to simulate. The methods developed for this advance a methodology for circuit-and-system-level modelling and simulation based on best practice rules to deal with coupled electromagnetic field-circuit-heat problems as well as coupled electro-thermal-stress problems that emerge in nanoelectronic designs. The new methods are robust and allow for strong feedback coupling when integrating systems to increase the performance of both existing devices and when integrating systems to produce new devices. With the new techniques it is possible to efficiently analyze the effects due to variability. Our methods are designed to solve reliability questions resulting from manufacturability. They facilitate robust design as well as enable worst case analysis. They can also be used to study effects due to ageing. Ageing causes variations in parameters over a long-term period, which cannot be predicted exactly and thus are typically uncertain. Novel Model Order Reduction techniques, developed here for the fast repeated simulation of the coupled problems under consideration, are applicable to both coupled systems and parameterized sub-systems. As such they are an essential ingredient for the Uncertainty Quantification. In summary, our solutions are:- advanced co-simulation/multirate/monolithic techniques, combined with envelope/wavelet approaches;- new generalized techniques in Uncertainty Quantification (UQ) for coupled problems, tuned to the statistical demands from manufacturability;- enhanced parametric Model Order Reduction techniques for coupled problems and for UQ.All the new algorithms produced were implemented, transferred and tested by the EDA-vendor MAGWEL. Validation was conducted on industrial designs provided by partners from semiconductor industry. These industrial end-users gave feedback during the project life-time, contributed to measurements and supplied material data as well as process data. A thorough comparison to measurements on real devices was being made to demonstrate the industrial applicability.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Nanoelectronic Coupled Problems Solutions (Mathematics in Industry Book 29). To get started finding Nanoelectronic Coupled Problems Solutions (Mathematics in Industry Book 29), you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

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Nanoelectronic Coupled Problems Solutions (Mathematics in Industry Book 29)

Nanoelectronic Coupled Problems Solutions (Mathematics in Industry Book 29)

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