Residual-based a posteriori error estimation for stochastic magnetostatic problems
In this paper, we propose an a posteriori error estimator for the numerical approximation of a stochastic magnetostatic problem, whose solution depends on the spatial variable but also on a stochastic one. The spatial discretization is performed with finite elements and the stochastic one with a pol...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Mac, D.H. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2015 |
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| Schlagwörter: |
Residual-based a posteriori error estimate Stochastic spectral finite element method |
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| Umfang: |
17 |
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| Übergeordnetes Werk: |
Enthalten in: Dielectric relaxation and microwave dielectric properties of low temperature sintering LiMnPO4 ceramics - Hu, Xing ELSEVIER, 2015transfer abstract, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:289 ; year:2015 ; day:1 ; month:12 ; pages:51-67 ; extent:17 |
| Links: |
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| DOI / URN: |
10.1016/j.cam.2015.03.027 |
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ELV034590390 |
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| 520 | |a In this paper, we propose an a posteriori error estimator for the numerical approximation of a stochastic magnetostatic problem, whose solution depends on the spatial variable but also on a stochastic one. The spatial discretization is performed with finite elements and the stochastic one with a polynomial chaos expansion. As a consequence, the numerical error results from these two levels of discretization. In this paper, we propose an error estimator that takes into account these two sources of error, and which is evaluated from the residuals. | ||
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10.1016/j.cam.2015.03.027 doi GBVA2015012000018.pica (DE-627)ELV034590390 (ELSEVIER)S0377-0427(15)00180-6 DE-627 ger DE-627 rakwb eng 510 510 DE-600 670 VZ 540 VZ 630 VZ Mac, D.H. verfasserin aut Residual-based a posteriori error estimation for stochastic magnetostatic problems 2015 17 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In this paper, we propose an a posteriori error estimator for the numerical approximation of a stochastic magnetostatic problem, whose solution depends on the spatial variable but also on a stochastic one. The spatial discretization is performed with finite elements and the stochastic one with a polynomial chaos expansion. As a consequence, the numerical error results from these two levels of discretization. In this paper, we propose an error estimator that takes into account these two sources of error, and which is evaluated from the residuals. Finite element method Elsevier Residual-based a posteriori error estimate Elsevier Stochastic spectral finite element method Elsevier Stochastic partial differential equation Elsevier Polynomial chaos expansion Elsevier Tang, Z. oth Clénet, S. oth Creusé, E. oth Enthalten in North-Holland Hu, Xing ELSEVIER Dielectric relaxation and microwave dielectric properties of low temperature sintering LiMnPO4 ceramics 2015transfer abstract Amsterdam [u.a.] (DE-627)ELV013217658 volume:289 year:2015 day:1 month:12 pages:51-67 extent:17 https://doi.org/10.1016/j.cam.2015.03.027 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA AR 289 2015 1 1201 51-67 17 045F 510 |
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10.1016/j.cam.2015.03.027 doi GBVA2015012000018.pica (DE-627)ELV034590390 (ELSEVIER)S0377-0427(15)00180-6 DE-627 ger DE-627 rakwb eng 510 510 DE-600 670 VZ 540 VZ 630 VZ Mac, D.H. verfasserin aut Residual-based a posteriori error estimation for stochastic magnetostatic problems 2015 17 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In this paper, we propose an a posteriori error estimator for the numerical approximation of a stochastic magnetostatic problem, whose solution depends on the spatial variable but also on a stochastic one. The spatial discretization is performed with finite elements and the stochastic one with a polynomial chaos expansion. As a consequence, the numerical error results from these two levels of discretization. In this paper, we propose an error estimator that takes into account these two sources of error, and which is evaluated from the residuals. Finite element method Elsevier Residual-based a posteriori error estimate Elsevier Stochastic spectral finite element method Elsevier Stochastic partial differential equation Elsevier Polynomial chaos expansion Elsevier Tang, Z. oth Clénet, S. oth Creusé, E. oth Enthalten in North-Holland Hu, Xing ELSEVIER Dielectric relaxation and microwave dielectric properties of low temperature sintering LiMnPO4 ceramics 2015transfer abstract Amsterdam [u.a.] (DE-627)ELV013217658 volume:289 year:2015 day:1 month:12 pages:51-67 extent:17 https://doi.org/10.1016/j.cam.2015.03.027 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA AR 289 2015 1 1201 51-67 17 045F 510 |
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In this paper, we propose an a posteriori error estimator for the numerical approximation of a stochastic magnetostatic problem, whose solution depends on the spatial variable but also on a stochastic one. The spatial discretization is performed with finite elements and the stochastic one with a polynomial chaos expansion. As a consequence, the numerical error results from these two levels of discretization. In this paper, we propose an error estimator that takes into account these two sources of error, and which is evaluated from the residuals. |
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In this paper, we propose an a posteriori error estimator for the numerical approximation of a stochastic magnetostatic problem, whose solution depends on the spatial variable but also on a stochastic one. The spatial discretization is performed with finite elements and the stochastic one with a polynomial chaos expansion. As a consequence, the numerical error results from these two levels of discretization. In this paper, we propose an error estimator that takes into account these two sources of error, and which is evaluated from the residuals. |
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In this paper, we propose an a posteriori error estimator for the numerical approximation of a stochastic magnetostatic problem, whose solution depends on the spatial variable but also on a stochastic one. The spatial discretization is performed with finite elements and the stochastic one with a polynomial chaos expansion. As a consequence, the numerical error results from these two levels of discretization. In this paper, we propose an error estimator that takes into account these two sources of error, and which is evaluated from the residuals. |
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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">ELV034590390</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230624014226.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">180603s2015 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.cam.2015.03.027</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBVA2015012000018.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV034590390</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0377-0427(15)00180-6</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=" "><subfield code="a">510</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">510</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">670</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">540</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">630</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Mac, D.H.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Residual-based a posteriori error estimation for stochastic magnetostatic problems</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2015</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">17</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">In this paper, we propose an a posteriori error estimator for the numerical approximation of a stochastic magnetostatic problem, whose solution depends on the spatial variable but also on a stochastic one. The spatial discretization is performed with finite elements and the stochastic one with a polynomial chaos expansion. As a consequence, the numerical error results from these two levels of discretization. In this paper, we propose an error estimator that takes into account these two sources of error, and which is evaluated from the residuals.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Finite element method</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Residual-based a posteriori error estimate</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Stochastic spectral finite element method</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Stochastic partial differential equation</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Polynomial chaos expansion</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Tang, Z.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Clénet, S.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Creusé, E.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">North-Holland</subfield><subfield code="a">Hu, Xing ELSEVIER</subfield><subfield code="t">Dielectric relaxation and microwave dielectric properties of low temperature sintering LiMnPO4 ceramics</subfield><subfield code="d">2015transfer abstract</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV013217658</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:289</subfield><subfield code="g">year:2015</subfield><subfield code="g">day:1</subfield><subfield code="g">month:12</subfield><subfield code="g">pages:51-67</subfield><subfield code="g">extent:17</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.cam.2015.03.027</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">289</subfield><subfield code="j">2015</subfield><subfield code="b">1</subfield><subfield code="c">1201</subfield><subfield code="h">51-67</subfield><subfield code="g">17</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">510</subfield></datafield></record></collection>
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