Open AccessBook
Computational Science and Engineering
Gilbert Strang
- 01 Jan 2007
544
TL;DR: Computational Science and Engineering (CSE) is the multi-disciplinary field of computer-based modelling and simulation for studying scientific phenomena and engineering designs.
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Abstract: Computational Science and Engineering (CSE) is the multi-disciplinary field of computer-based modelling and simulation for studying scientific phenomena and engineering designs. Modelling and simulation helps to validate theory, and makes it possible to analyse scenarios that would otherwise be too time-consuming, expensive, or dangerous to study by experiment. Data exploration helps to turn numbers into insight which is especially challenging in times of Big Data.
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Citations
Universal Differential Equations for Scientific Machine Learning
Christopher Rackauckas,Yingbo Ma,Julius Martensen,Collin Warner,Kirill Zubov,Rohit Supekar,Dominic J. Skinner,Ali Ramadhan,Alan Edelman +8 more
TL;DR: The UDE model augments scientific models with machine-learnable structures for scientifically-based learning and shows how UDEs can be utilized to discover previously unknown governing equations, accurately extrapolate beyond the original data, and accelerate model simulation, all in a time and data-efficient manner.
Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems
Laura von Rueden,Sebastian Mayer,Katharina Beckh,Bogdan Georgiev,Sven Giesselbach,Raoul Heese,Birgit Kirsch,Julius Pfrommer,Annika Pick,Rajkumar Ramamurthy,Michal Walczak,Jochen Garcke,Christian Bauckhage,Jannis Schuecker +13 more
TL;DR: A definition and proposed concept for informed machine learning is provided, which illustrates its building blocks and distinguishes it from conventional machine learning, and a taxonomy is introduced that serves as a classification framework forinformed machine learning approaches.
Adjoint shape optimization applied to electromagnetic design.
TL;DR: This work presents an adjoint-based optimization for electromagnetic design that embeds commercial Maxwell solvers within a steepest-descent inverse-design optimization algorithm, and finds that convergence is much faster, within a larger design space.
High-resolution tensor MR elastography for breast tumour detection.
TL;DR: The analysis of the eigenvalues of the elasticity tensor support the hypothesis that breast carcinoma might exhibit an anisotropic elasticity distribution and the surrounding benign tissue appears isotropic.
576
Perfused multiwell plate for 3D liver tissue engineering
TL;DR: A bioreactor is developed that fosters maintenance of 3D tissue cultures under constant perfusion and multiple bioreactors are integrated into an array in a multiwell plate format to capture the complexity of in vivo tissue and organ behaviors.
References
Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems
Laura von Rueden,Sebastian Mayer,Katharina Beckh,Bogdan Georgiev,Sven Giesselbach,Raoul Heese,Birgit Kirsch,Julius Pfrommer,Annika Pick,Rajkumar Ramamurthy,Michal Walczak,Jochen Garcke,Christian Bauckhage,Jannis Schuecker +13 more
TL;DR: A definition and proposed concept for informed machine learning is provided, which illustrates its building blocks and distinguishes it from conventional machine learning, and a taxonomy is introduced that serves as a classification framework forinformed machine learning approaches.
Adjoint shape optimization applied to electromagnetic design.
TL;DR: This work presents an adjoint-based optimization for electromagnetic design that embeds commercial Maxwell solvers within a steepest-descent inverse-design optimization algorithm, and finds that convergence is much faster, within a larger design space.
Perfused multiwell plate for 3D liver tissue engineering
TL;DR: A bioreactor is developed that fosters maintenance of 3D tissue cultures under constant perfusion and multiple bioreactors are integrated into an array in a multiwell plate format to capture the complexity of in vivo tissue and organ behaviors.
Climatological aspects of the optical properties of fine/coarse mode aerosol mixtures
Thomas F. Eck,Thomas F. Eck,Brent N. Holben,Aliaksandyr Sinyuk,Rachel T. Pinker,Philippe Goloub,Hongbin Chen,B. Chatenet,Zhanqing Li,Ramesh P. Singh,Sachchida Nand Tripathi,Jeffrey S. Reid,David M. Giles,Oleg Dubovik,Norman T. O'Neill,Alexander Smirnov,Pucai Wang,Xiangao Xia +17 more
TL;DR: In this paper, the spectral variation of the averaged aerosol absorption optical depth was nearly linear in logarithmic coordinates over the wavelength range of 440-870 nm for both the Kanpur and Ilorin sites.
Network Properties Revealed through Matrix Functions
TL;DR: A general class of measures based on matrix functions is introduced, and it is shown that a particular case involving a matrix resolvent arises naturally from graph-theoretic arguments.
385
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