TID.
Author | : |
Publisher | : |
Total Pages | : 76 |
Release | : 1961 |
Genre | : Energy development |
ISBN | : |
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Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Void Distribution PDF full book. Access full book title Void Distribution.
Author | : |
Publisher | : |
Total Pages | : 76 |
Release | : 1961 |
Genre | : Energy development |
ISBN | : |
Author | : |
Publisher | : |
Total Pages | : |
Release | : 1963 |
Genre | : |
ISBN | : |
Author | : Gary M. Gladysz |
Publisher | : Newnes |
Total Pages | : 215 |
Release | : 2014-09-09 |
Genre | : Science |
ISBN | : 0444563741 |
Voids in Materials treats voids of different shapes and forms in various materials, and examines their effects on material properties. The book covers the origins of voids in materials, how they are sometimes introduced in the form of hollow spheres, and the resultant properties of materials containing voids. There are many books that focus on foams (which intentionally incorporate voids into materials) and that cover voids incidental to or unwanted in the fabrication of non-porous materials. In fact, all materials have voids. This book starts from the premise that voids are pervasive in all material on some level. It goes beyond foams to provide a comprehensive overview of voids, a central reference for scientists and engineers to use for the effect of voids in materials. Includes 3D renderings of void geometries Explains how and why voids are introduced into materials across the length scales; from nanometer-scale voids up to macro-scale voids Provides a continuous picture of how material properties change as the volume fraction of voids increases, and the implications for product design
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Total Pages | : 542 |
Release | : |
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ISBN | : |
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Publisher | : |
Total Pages | : 1228 |
Release | : 1899 |
Genre | : Law reports, digests, etc |
ISBN | : |
Author | : Marcos Szydlo |
Publisher | : |
Total Pages | : 116 |
Release | : 1983 |
Genre | : |
ISBN | : |
Author | : Pang, Bo |
Publisher | : KIT Scientific Publishing |
Total Pages | : 146 |
Release | : 2014-07-23 |
Genre | : |
ISBN | : 3731502194 |
Author | : PoulV. Lade |
Publisher | : Routledge |
Total Pages | : 385 |
Release | : 2018-04-27 |
Genre | : Technology & Engineering |
ISBN | : 1351424475 |
The workshop aims to provide a fundamental understanding of the liquefaction process, necessary to the enhancement of liquefaction prediction. The contributions are divided into eight sections, which include: factors affecting liquefaction susceptibility and field studies of liquefaction.
Author | : |
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Total Pages | : 364 |
Release | : 1999 |
Genre | : Fluids |
ISBN | : |
Author | : Dan Gabriel Cacuci |
Publisher | : Springer |
Total Pages | : 451 |
Release | : 2018-12-29 |
Genre | : Technology & Engineering |
ISBN | : 366258395X |
This book addresses the experimental calibration of best-estimate numerical simulation models. The results of measurements and computations are never exact. Therefore, knowing only the nominal values of experimentally measured or computed quantities is insufficient for applications, particularly since the respective experimental and computed nominal values seldom coincide. In the author’s view, the objective of predictive modeling is to extract “best estimate” values for model parameters and predicted results, together with “best estimate” uncertainties for these parameters and results. To achieve this goal, predictive modeling combines imprecisely known experimental and computational data, which calls for reasoning on the basis of incomplete, error-rich, and occasionally discrepant information. The customary methods used for data assimilation combine experimental and computational information by minimizing an a priori, user-chosen, “cost functional” (usually a quadratic functional that represents the weighted errors between measured and computed responses). In contrast to these user-influenced methods, the BERRU (Best Estimate Results with Reduced Uncertainties) Predictive Modeling methodology developed by the author relies on the thermodynamics-based maximum entropy principle to eliminate the need for relying on minimizing user-chosen functionals, thus generalizing the “data adjustment” and/or the “4D-VAR” data assimilation procedures used in the geophysical sciences. The BERRU predictive modeling methodology also provides a “model validation metric” which quantifies the consistency (agreement/disagreement) between measurements and computations. This “model validation metric” (or “consistency indicator”) is constructed from parameter covariance matrices, response covariance matrices (measured and computed), and response sensitivities to model parameters. Traditional methods for computing response sensitivities are hampered by the “curse of dimensionality,” which makes them impractical for applications to large-scale systems that involve many imprecisely known parameters. Reducing the computational effort required for precisely calculating the response sensitivities is paramount, and the comprehensive adjoint sensitivity analysis methodology developed by the author shows great promise in this regard, as shown in this book. After discarding inconsistent data (if any) using the consistency indicator, the BERRU predictive modeling methodology provides best-estimate values for predicted parameters and responses along with best-estimate reduced uncertainties (i.e., smaller predicted standard deviations) for the predicted quantities. Applying the BERRU methodology yields optimal, experimentally validated, “best estimate” predictive modeling tools for designing new technologies and facilities, while also improving on existing ones.