Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Daniele Bigoni"'
Publikováno v:
European Social Work Research. 1:118-139
Digital features like virtual reality have hardly been used in the framework of data collection in qualitative social work research. Virtual reality holds specific promise because it allows the immersion of participants in a situation and has the pot
Publikováno v:
Mechanics. 25:455-462
This paper aims to investigate uncertainties in railway vehicle suspension components and the implement of uncertainty quantification methods in railway vehicle dynamics. The sampling-based method represented by Latin Hypercube Sampling (LHS) and gen
Publikováno v:
arXiv
This paper suggests a framework for the learning of discretizations of expensive forward models in Bayesian inverse problems. The main idea is to incorporate the parameters governing the discretization as part of the unknown to be estimated within th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a02a92b4f76f7ad495b01e26ea1782c0
https://hdl.handle.net/1721.1/134038
https://hdl.handle.net/1721.1/134038
Publikováno v:
Journal of Computational Physics. 318:1-21
We present an arbitrary-order spectral element method for general-purpose simulation of non-overturning water waves, described by fully nonlinear potential theory. The method can be viewed as a high-order extension of the classical finite element met
Publikováno v:
Mathematics and Computers in Simulation. 95:78-97
The paper contains a report of the experiences with numerical analyses of railway vehicle dynamical systems, which all are nonlinear, non-smooth and stiff high-dimensional systems. Some results are shown, but the emphasis is on the numerical methods
Publikováno v:
Multiscale Modeling & Simulation. 10:936-953
Analysis of propagation of a fault driven by a steadily moving shearing force through a structural interface reveals a channeling effect for the energy release. This effect implies that a steady-state solution for propagation exists, but, differently
Publikováno v:
Bigoni, D, Engsig-Karup, A P & Marzouk, Y M 2015, ' Adaptive spectral tensor-strain decomposition for the construction of surrogate models ' SIAM Conference on Computational Science and Engineering (SIAM CSE 2015), Salt Lake City, Utah, United States, 04/03/2015-18/03/2015, .
Technical University of Denmark Orbit
Technical University of Denmark Orbit
The construction of surrogate models is important as a mean of acceleration in computational methods for uncertainty quantification (UQ). When the forward model is particularly expensive, surrogate models can be used for the forward propagation of un
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::1d80c459f83c1883ab16de0db8f9cc4d
http://orbit.dtu.dk/en/publications/adaptive-spectral-tensorstrain-decomposition-for-the-construction-of-surrogate-models(453bf212-4da1-41e9-afd7-894df2e3bf31).html
http://orbit.dtu.dk/en/publications/adaptive-spectral-tensorstrain-decomposition-for-the-construction-of-surrogate-models(453bf212-4da1-41e9-afd7-894df2e3bf31).html
Publikováno v:
Bigoni, D, Engsig-Karup, A P & Eskilsson, C 2016, ' Efficient uncertainty quantification of a fully nonlinear and dispersive water wave model with random inputs ', Journal of Engineering Mathematics, vol. 101, no. 1, pp. 87-113 . https://doi.org/10.1007/s10665-016-9848-8
A major challenge in next-generation industrial applications is to improve numerical analysis by quantifying uncertainties in predictions. In this work we present a formulation of a fully nonlinear and dispersive potential flow water wave model with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::24bab3a707bd4152236fbd7ef94c0b0f
http://arxiv.org/abs/1410.6338
http://arxiv.org/abs/1410.6338
Publikováno v:
Volume 2: Dynamics, Vibration and Control; Energy; Fluids Engineering; Micro and Nano Manufacturing.
This work addresses the problem of the reliability of simulations for realistic nonlinear systems, by using efficient techniques for the analysis of the propagation of the uncertainties of the model parameters through the dynamics of the system. We p