Rolf Sandström · Springer series in materials science · 2024
Abstract The extrapolation of creep data to longer times is technically very important. The traditional way of extrapolating creep rupture data is to use time temperaturer parameters (TTPs). In this way data from several test temperatures are combined to a single master curve that can be used to assess rupture strengths at long times. Recently, there is much focus on machine learning techniques (neural networks, NNs). Both types of procedures can generate accurate results, but a detailed analysis is required. A good way to assess the quality of the results is to use the post assessment tests (PATs) developed by ECCC. Without such tests arbitrary results can be obtained. They are important for both TTPs and NNs. It has been shown that by putting requirements on the derivatives of the creep rupture curves, the PATs can more or less automatically be satisfied. In addition, the error in the extrapolated values should be estimated. Using the basic creep models presented in this book, prediction of rupture strength and ductility can be made in a safer way. It is demonstrated for Cu that accurate extrapolation of many order of magnitude in the creep rate can be made, which is never possible with empirical models.
Cited by 0Open access
Richard C. Hertzberg · Encyclopedia of Environmetrics · 2006
Abstract Quantitative extrapolation refers to a process where inferences about data‐poor scenarios are developed from studies of data‐rich scenarios. For dose–response relationships in environmental risk assessment, several different kinds of extrapolation are used in order to accommodate the variety of available information and risk assessment goals. Examples of such extrapolation include estimating human health risk at low doses from rodent toxicology data at high doses, or estimating ecosystem response at a given ambient pollution concentration from laboratory studies of individual animal or plant species at similar concentrations. The examples discussed in this article are for human health risk assessment but most of the principles apply to ecological risk assessment as well. These examples include low‐dose extrapolation of cancer response (extending a fitted function below the range of the data), simple scaling methods (e.g. allometric interspecies extrapolation), biomathematical models (e.g. physiologically‐based pharmacokinetic models), and quantitative formulas for estimating mixture response (e.g. modifying dose addition to account for synergism).
Cited by 0
2005
Cited by 0
Glenn W. Suter · 2023
Cited by 0
Chuanmiao Chen, Hongling Hu, Ziqing Xie et al. · 2010
The multigrid method solves the finite element equations in optimal order, i.e., solving a linear system of O(N) equations in O(N) arithmetic operations. Based on low level solutions, we can use finite element extrapolation to obtain the high-level finite element solution on some coarse-level element boundary, at an higher accuracy O(h 4 i). Thus, we can solve higher level (hj, j < ∼ 2i) finite element problems locally on each such coarse-level element. That is, we can skip the finite element problem on middle levels, hi+1, hi+2,..., hj−1. Roughly speaking, such a jumping multigrid method solves an order O(N) = O(2 2di) linear system of equations by a memory of O ( √ N) = O(2 di), and by a parallel computation of O ( √ N), where d is the space dimension. elliptic equation, finite element, extrapolation, uniform grid, super-Keywords. convergence.
Cited by 0
Willem Otterspeer · 2012
Cited by 0
Robert Hauptman · Lexington Books · 2011
Cited by 0
The SAGE Encyclopedia of Social Science Research Methods · 2004
Cited by 0
Paul S. Levy · Encyclopedia of Biostatistics · 2005
Cited by 0
Encyclopedic Dictionary of Genetics, Genomics and Proteomics · 2004
Cited by 0
Encyclopedia of Statistical Sciences · 2005
Cited by 0
2024
Cited by 0
RWTH Publications (RWTH Aachen)
Cited by 0
Peijuan Zhu, Andrej Skerjanec · AAPS advances in the pharmaceutical sciences series · 2018
Cited by 0
Andrew P. Sage · Elsevier eBooks · 1992
Cited by 0
Amsterdam University Press eBooks · 2010
Cited by 0
Peter Kenny · RePEc: Research Papers in Economics
Abstract Thomas Malthus, an English cleric, economist, and statistician, is known for his theories on population growth. He wrote in 1798 in his Essay on the Principle of Population that, because population increases geometrically (1, 2, 4, 8, …) and food increases arithmetically (1, 2, 3, 4, …), the population would eventually outstrip food supply. He warned of premature death visiting the human race. The onset of disaster would be prevented only by epidemics, pestilence, plague, famine, and preventive measures. His numerous writings on the subject gave rise to the Malthusian doctrine.
Cited by 0
Otto Neurath · 1931
Cited by 0
Josh Moos, Jamie A. Morgan · Edward Elgar Publishing eBooks · 2023
This comprehensive Dictionary brings together an extensive range of definitive terms in ecological economics. Assembling contributions from distinguished scholars, it provides an intellectual map to this evolving subject ranging from the practical to the philosophical.
Cited by 0
Mental D-struction · Bulletin of Miscellaneous Information (Royal Gardens Kew) · 2010
Mental D-struction - Extrapolation² Tracklist : 01. Remember 02. Jeremie 25.30 03. Last Breath (feat. Darkselvedge) 04. Arkan 05. Intrusion 06. Discharge 07. Doomed http://www.myspace.com/mmentaldestruction http://www.mentald-struction.com Material recorded between 2008 and 2010. Free digital version extract from the upcoming 14 songs CD album "Extrapolation Of Human Perspectives", Contagious Programm, CPG 02. All songs written-by Evelyne Manganese Vocals [track 3] By Julien Gomez Artwork By Beatricide, Evelyne Manganese Mastering By Pyrrhon
Cited by 0