04092nam a22005415i 4500 978-3-031-47036-3 DE-He213 20251030110824.0 cr nn 008mamaa 231021s2024 sz | s |||| 0|eng d 9783031470363 978-3-031-47036-3 10.1007/978-3-031-47036-3 doi TJ1-1570 TGB bicssc TEC009070 bisacsh TGB thema Proceedings of the 6th International Symposium on Uncertainty Quantification and Stochastic Modelling [electronic resource] : Uncertainties 2023 / edited by José Eduardo Souza De Cursi. 1st ed. 2024. Cham : Springer International Publishing : Imprint: Springer, 2024. XI, 272 p. 139 illus., 116 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda ABCM Series on Mechanical Sciences and Engineering, 2662-303X Uncertainties 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. This 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. Mechanical engineering. 58323 Stochastic models. 66661 Financial risk management. 59046 Mechanical Engineering. 58323 Stochastic Modelling. 66662 Risk Management. 59047 De Cursi, José Eduardo Souza. editor. edt http://id.loc.gov/vocabulary/relators/edt 66663 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031470356 Printed edition: 9783031470370 Printed edition: 9783031470387 ABCM Series on Mechanical Sciences and Engineering, 2662-303X 66247 https://doi.org/10.1007/978-3-031-47036-3 ZDB-2-ENG ZDB-2-SXE 56430 56430