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020 _a9783031470363
_9978-3-031-47036-3
024 7 _a10.1007/978-3-031-47036-3
_2doi
050 4 _aTJ1-1570
072 7 _aTGB
_2bicssc
072 7 _aTEC009070
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072 7 _aTGB
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245 1 0 _aProceedings of the 6th International Symposium on Uncertainty Quantification and Stochastic Modelling
_h[electronic resource] :
_bUncertainties 2023 /
_cedited by José Eduardo Souza De Cursi.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2024.
300 _aXI, 272 p. 139 illus., 116 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aABCM Series on Mechanical Sciences and Engineering,
_x2662-303X
505 0 _aUncertainties of numerical simulation for static liquefaction potential of saturated soils -- Uncertainties about the Toughness Property of raw earth construction materials -- Uncertainties of Experimental Tests on Cyclic Liquefaction Potential of Unsaturated Soils -- Analysis of the Impact of Uncertainties on the Estimation of Geotechnical Engineering Properties of Soil from SPT on the Design of Aerogenerators Foundation -- Uncertainties on the unconfined compressive strength of raw and textured concrete -- Bio-inspired shape optimization for structural robust design using isogeometric analysis.
520 _aThis proceedings book covers a wide range of topics related to uncertainty analysis and its application in various fields of engineering and science. It explores uncertainties in numerical simulations for soil liquefaction potential, the toughness properties of construction materials, experimental tests on cyclic liquefaction potential, and the estimation of geotechnical engineering properties for aerogenerator foundation design. Additionally, the book delves into uncertainties in concrete compressive strength, bio-inspired shape optimization using isogeometric analysis, stochastic damping in rotordynamics, and the hygro-thermal properties of raw earth building materials. It also addresses dynamic analysis with uncertainties in structural parameters, reliability-based design optimization of steel frames, and calibration methods for models with dependent parameters. The book further explores mechanical property characterization in 3D printing, stochastic analysis in computational simulations, probability distribution in branching processes, data assimilation in ocean circulation modeling, uncertainty quantification in climate prediction, and applications of uncertainty quantification in decision problems and disaster management. This comprehensive collection provides insights into the challenges and solutions related to uncertainty in various scientific and engineering contexts.
650 0 _aMechanical engineering.
_958323
650 0 _aStochastic models.
_966661
650 0 _aFinancial risk management.
_959046
650 1 4 _aMechanical Engineering.
_958323
650 2 4 _aStochastic Modelling.
_966662
650 2 4 _aRisk Management.
_959047
700 1 _aDe Cursi, José Eduardo Souza.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_966663
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031470356
776 0 8 _iPrinted edition:
_z9783031470370
776 0 8 _iPrinted edition:
_z9783031470387
830 0 _aABCM Series on Mechanical Sciences and Engineering,
_x2662-303X
_966247
856 4 0 _uhttps://doi.org/10.1007/978-3-031-47036-3
912 _aZDB-2-ENG
912 _aZDB-2-SXE
999 _c56430
_d56430