Numerical and analytic routes from microscales to macroscales in theories of deformation and fracture
Abstract Numerical simulation has reached a point where it is on a par with laboratory experiment and mathematical theory as a tool for materials research. For example, molecular dynamics computations now can predict the motions of tens of millions of molecules in a solid that is undergoing deformat...
Ausführliche Beschreibung
Autor*in: |
Langer, J.S. [verfasserIn] |
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Format: |
Artikel |
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Sprache: |
Englisch |
Erschienen: |
1999 |
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Schlagwörter: |
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Anmerkung: |
© Kluwer Academic Publishers 1999 |
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Übergeordnetes Werk: |
Enthalten in: Journal of computer-aided materials design - Kluwer Academic Publishers, 1993, 6(1999), 2-3 vom: Mai, Seite 89-94 |
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Übergeordnetes Werk: |
volume:6 ; year:1999 ; number:2-3 ; month:05 ; pages:89-94 |
Links: |
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DOI / URN: |
10.1023/A:1008740120212 |
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OLC2034719808 |
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10.1023/A:1008740120212 doi (DE-627)OLC2034719808 (DE-He213)A:1008740120212-p DE-627 ger DE-627 rakwb eng 004 VZ Langer, J.S. verfasserin aut Numerical and analytic routes from microscales to macroscales in theories of deformation and fracture 1999 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Kluwer Academic Publishers 1999 Abstract Numerical simulation has reached a point where it is on a par with laboratory experiment and mathematical theory as a tool for materials research. For example, molecular dynamics computations now can predict the motions of tens of millions of molecules in a solid that is undergoing deformation or fracture. The question is how to use such huge amounts of information to gain deeper understanding of the properties of real materials. I believe that it is an inefficient use of computational facilities to try to go directly from atomistic simulations to specific macroscopic phenomena. A better strategy is to use the simulations to identify dynamic variables that characterize the internal states of materials, and to use the equations of motion for these variables along with equations for stress and strain to predict macroscopic behavior. I shall illustrate this strategy by describing recent work by M. Falk and myself on plasticity in amorphous solids. Plastic Zone Memory Effect Plasticity Theory Molecular Dynamic Computation Plastic Strain Rate Enthalten in Journal of computer-aided materials design Kluwer Academic Publishers, 1993 6(1999), 2-3 vom: Mai, Seite 89-94 (DE-627)192061305 (DE-600)1306273-6 (DE-576)078706963 0928-1045 nnns volume:6 year:1999 number:2-3 month:05 pages:89-94 https://doi.org/10.1023/A:1008740120212 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-CHE SSG-OLC-MAT SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_70 AR 6 1999 2-3 05 89-94 |
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10.1023/A:1008740120212 doi (DE-627)OLC2034719808 (DE-He213)A:1008740120212-p DE-627 ger DE-627 rakwb eng 004 VZ Langer, J.S. verfasserin aut Numerical and analytic routes from microscales to macroscales in theories of deformation and fracture 1999 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Kluwer Academic Publishers 1999 Abstract Numerical simulation has reached a point where it is on a par with laboratory experiment and mathematical theory as a tool for materials research. For example, molecular dynamics computations now can predict the motions of tens of millions of molecules in a solid that is undergoing deformation or fracture. The question is how to use such huge amounts of information to gain deeper understanding of the properties of real materials. I believe that it is an inefficient use of computational facilities to try to go directly from atomistic simulations to specific macroscopic phenomena. A better strategy is to use the simulations to identify dynamic variables that characterize the internal states of materials, and to use the equations of motion for these variables along with equations for stress and strain to predict macroscopic behavior. I shall illustrate this strategy by describing recent work by M. Falk and myself on plasticity in amorphous solids. Plastic Zone Memory Effect Plasticity Theory Molecular Dynamic Computation Plastic Strain Rate Enthalten in Journal of computer-aided materials design Kluwer Academic Publishers, 1993 6(1999), 2-3 vom: Mai, Seite 89-94 (DE-627)192061305 (DE-600)1306273-6 (DE-576)078706963 0928-1045 nnns volume:6 year:1999 number:2-3 month:05 pages:89-94 https://doi.org/10.1023/A:1008740120212 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-CHE SSG-OLC-MAT SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_70 AR 6 1999 2-3 05 89-94 |
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10.1023/A:1008740120212 doi (DE-627)OLC2034719808 (DE-He213)A:1008740120212-p DE-627 ger DE-627 rakwb eng 004 VZ Langer, J.S. verfasserin aut Numerical and analytic routes from microscales to macroscales in theories of deformation and fracture 1999 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Kluwer Academic Publishers 1999 Abstract Numerical simulation has reached a point where it is on a par with laboratory experiment and mathematical theory as a tool for materials research. For example, molecular dynamics computations now can predict the motions of tens of millions of molecules in a solid that is undergoing deformation or fracture. The question is how to use such huge amounts of information to gain deeper understanding of the properties of real materials. I believe that it is an inefficient use of computational facilities to try to go directly from atomistic simulations to specific macroscopic phenomena. A better strategy is to use the simulations to identify dynamic variables that characterize the internal states of materials, and to use the equations of motion for these variables along with equations for stress and strain to predict macroscopic behavior. I shall illustrate this strategy by describing recent work by M. Falk and myself on plasticity in amorphous solids. Plastic Zone Memory Effect Plasticity Theory Molecular Dynamic Computation Plastic Strain Rate Enthalten in Journal of computer-aided materials design Kluwer Academic Publishers, 1993 6(1999), 2-3 vom: Mai, Seite 89-94 (DE-627)192061305 (DE-600)1306273-6 (DE-576)078706963 0928-1045 nnns volume:6 year:1999 number:2-3 month:05 pages:89-94 https://doi.org/10.1023/A:1008740120212 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-CHE SSG-OLC-MAT SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_70 AR 6 1999 2-3 05 89-94 |
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10.1023/A:1008740120212 doi (DE-627)OLC2034719808 (DE-He213)A:1008740120212-p DE-627 ger DE-627 rakwb eng 004 VZ Langer, J.S. verfasserin aut Numerical and analytic routes from microscales to macroscales in theories of deformation and fracture 1999 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Kluwer Academic Publishers 1999 Abstract Numerical simulation has reached a point where it is on a par with laboratory experiment and mathematical theory as a tool for materials research. For example, molecular dynamics computations now can predict the motions of tens of millions of molecules in a solid that is undergoing deformation or fracture. The question is how to use such huge amounts of information to gain deeper understanding of the properties of real materials. I believe that it is an inefficient use of computational facilities to try to go directly from atomistic simulations to specific macroscopic phenomena. A better strategy is to use the simulations to identify dynamic variables that characterize the internal states of materials, and to use the equations of motion for these variables along with equations for stress and strain to predict macroscopic behavior. I shall illustrate this strategy by describing recent work by M. Falk and myself on plasticity in amorphous solids. Plastic Zone Memory Effect Plasticity Theory Molecular Dynamic Computation Plastic Strain Rate Enthalten in Journal of computer-aided materials design Kluwer Academic Publishers, 1993 6(1999), 2-3 vom: Mai, Seite 89-94 (DE-627)192061305 (DE-600)1306273-6 (DE-576)078706963 0928-1045 nnns volume:6 year:1999 number:2-3 month:05 pages:89-94 https://doi.org/10.1023/A:1008740120212 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-CHE SSG-OLC-MAT SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_70 AR 6 1999 2-3 05 89-94 |
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Abstract Numerical simulation has reached a point where it is on a par with laboratory experiment and mathematical theory as a tool for materials research. For example, molecular dynamics computations now can predict the motions of tens of millions of molecules in a solid that is undergoing deformation or fracture. The question is how to use such huge amounts of information to gain deeper understanding of the properties of real materials. I believe that it is an inefficient use of computational facilities to try to go directly from atomistic simulations to specific macroscopic phenomena. A better strategy is to use the simulations to identify dynamic variables that characterize the internal states of materials, and to use the equations of motion for these variables along with equations for stress and strain to predict macroscopic behavior. I shall illustrate this strategy by describing recent work by M. Falk and myself on plasticity in amorphous solids. © Kluwer Academic Publishers 1999 |
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Abstract Numerical simulation has reached a point where it is on a par with laboratory experiment and mathematical theory as a tool for materials research. For example, molecular dynamics computations now can predict the motions of tens of millions of molecules in a solid that is undergoing deformation or fracture. The question is how to use such huge amounts of information to gain deeper understanding of the properties of real materials. I believe that it is an inefficient use of computational facilities to try to go directly from atomistic simulations to specific macroscopic phenomena. A better strategy is to use the simulations to identify dynamic variables that characterize the internal states of materials, and to use the equations of motion for these variables along with equations for stress and strain to predict macroscopic behavior. I shall illustrate this strategy by describing recent work by M. Falk and myself on plasticity in amorphous solids. © Kluwer Academic Publishers 1999 |
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Abstract Numerical simulation has reached a point where it is on a par with laboratory experiment and mathematical theory as a tool for materials research. For example, molecular dynamics computations now can predict the motions of tens of millions of molecules in a solid that is undergoing deformation or fracture. The question is how to use such huge amounts of information to gain deeper understanding of the properties of real materials. I believe that it is an inefficient use of computational facilities to try to go directly from atomistic simulations to specific macroscopic phenomena. A better strategy is to use the simulations to identify dynamic variables that characterize the internal states of materials, and to use the equations of motion for these variables along with equations for stress and strain to predict macroscopic behavior. I shall illustrate this strategy by describing recent work by M. Falk and myself on plasticity in amorphous solids. © Kluwer Academic Publishers 1999 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC2034719808</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230509113612.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200819s1999 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1023/A:1008740120212</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2034719808</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)A:1008740120212-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Langer, J.S.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Numerical and analytic routes from microscales to macroscales in theories of deformation and fracture</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">1999</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Kluwer Academic Publishers 1999</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Numerical simulation has reached a point where it is on a par with laboratory experiment and mathematical theory as a tool for materials research. For example, molecular dynamics computations now can predict the motions of tens of millions of molecules in a solid that is undergoing deformation or fracture. The question is how to use such huge amounts of information to gain deeper understanding of the properties of real materials. I believe that it is an inefficient use of computational facilities to try to go directly from atomistic simulations to specific macroscopic phenomena. A better strategy is to use the simulations to identify dynamic variables that characterize the internal states of materials, and to use the equations of motion for these variables along with equations for stress and strain to predict macroscopic behavior. I shall illustrate this strategy by describing recent work by M. 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