Dokument-ID Dokumenttyp Verfasser/Autoren Herausgeber Haupttitel Abstract Auflage Verlagsort Verlag Erscheinungsjahr Seitenzahl Schriftenreihe Titel Schriftenreihe Bandzahl ISBN Quelle der Hochschulschrift Konferenzname Quelle:Titel Quelle:Jahrgang Quelle:Heftnummer Quelle:Erste Seite Quelle:Letzte Seite URN DOI Abteilungen OPUS4-2985 Konferenzveröffentlichung Stoimenova, Eugenia; Lins, Yvonne; Datcheva, Maria; Schanz, Tom Gürlebeck, Klaus; Könke, Carsten INVERSE MODELLING OF SOIL HYDRAULIC CHARACTERISTIC FUNCTIONS In this paper we evaluate 2D models for soil-water characteristic curve (SWCC), that incorporate the hysteretic nature of the relationship between volumetric water content θ and suction ψ. The models are based on nonlinear least squares estimation of the experimental data for sand. To estimate the dependent variable θ the proposed models include two independent variables, suction and sensors reading position (depth d in the column test). The variable d represents not only the position where suction and water content are measured but also the initial suction distribution before each of the hydraulic loading test phases. Due to this the proposed 2D regression models acquire the advantage that they: (a) can be applied for prediction of θ for any position along the column and (b) give the functional form for the scanning curves. 12 urn:nbn:de:gbv:wim2-20170327-29858 10.25643/bauhaus-universitaet.2985 Professur Bodenmechanik OPUS4-2913 Konferenzveröffentlichung Schanz, Tom; Wuttke, Frank; Dineva, Petia Gürlebeck, Klaus; Könke, Carsten HYBRID APPROACH OF WAVE NUMBER INTEGRATION-BOUNDARY INTEGRAL EQUATION METHOD FOR SITE EFFECT ESTIMATION OF A LATERALLY VARYING SEISMIC REGION In this paper we evaluate 2D models for soil-water characteristic curve (SWCC), that incorporate the hysteretic nature of the relationship between volumetric water content Θ and suction Ψ. The models are based on nonlinear least squares estimation of the experimental data for sand. To estimate the dependent variable Θ the proposed models include two independent variables, suction and sensors reading position (depth d in the column test). The variable d represents not only the position where suction and water content are measured but also the initial suction distribution before each of the hydraulic loading test phases. Due to this the proposed 2D regression models acquire the advantage that they: (a) can be applied for prediction of Θ for any position along the column and (b) give the functional form for the scanning curves. 15 urn:nbn:de:gbv:wim2-20170327-29132 10.25643/bauhaus-universitaet.2913 Professur Bodenmechanik