SSD - Renard Seminar
Prof. Dr. Philippe Renard - Stochastic Modeling of Karstic Systems
Centre d'Hydrogéologie et de Géothermie, University of Neuchâtel, Paris
Karstic aquifers are characterized by the presence of rare but highly permeable karstic conduits embedded in a carbonate matrix of lower permeability. This highly heterogeneous structure results from the dissolution of the matrix by acidic water and a self-reinforcing process. Karst aquifers can present very fast flow and contaminant transfer in the conduits. Consequently, these aquifers are often highly vulnerable to groundwater pollution and extremely sensitive to climate fluctuations. In recent years, significant progresses have been made to model karstic reservoirs. In this presentation, we will discuss several of these modeling aspects, including techniques that can be used to simulate the geometry of karstic networks (often only partially known), flow and transport simulation methods, but also the speleogenesis processes.
SSD - Marzouk Seminar
Prof. Youssef Marzouk, Ph.D. - Transport Methods for Sampling: Preconditioning and Low-dimensional Structure
Department of Aeronautics and Astronautics,Massachusetts Institute of Technology, USA
Integration against an intractable probability measure is a fundamental challenge in Bayesian inference and well beyond. A useful approach to this problem seeks a deterministic coupling of the measure of interest with a tractable “reference” measure (e.g., a standard Gaussian). Such couplings are induced by transport maps, and enable direct simulation from the desired measure simply by evaluating the transport map at samples from the reference. In recent years, an enormous variety of representations and constructions for such transport maps have been proposed—ranging from monotone polynomials or invertible neural networks to the flows of ODEs. Approximate transports can also be used to “precondition” and accelerate standard Monte Carlo schemes. Within this framework, one can describe many useful notions of low-dimensional structure: for instance, sparse or decomposable transports underpin modeling and computation with non-Gaussian Markov random fields, and low-rank transports arise frequently in inverse problems.
I will present a broad overview of this framework, describing how to construct suitable classes of transport maps, and then focus on two recent developments: adaptive MCMC schemes that use transport to create more favorable target geometry, and greedy variational methods that build high-dimensional transport maps by composing multiple low-dimensionalmaps or flows.
This is joint work with Daniele Bigoni, Matthew Parno, Alessio Spantini, and Olivier Zahm.
Speaker bio: Youssef Marzouk is an associate professor in the Department of Aeronautics and Astronautics at MIT, and co-director of the MIT Center for Computational Engineering. He is also director of MIT’s Aerospace Computational Design Laboratory and a core member of MIT's Statistics and Data Science Center. His research interests lie at the intersection of physical modeling with statistical inference and computation. In particular, he develops methodologies for uncertainty quantification, inverse problems, large-scale Bayesian computation, and optimal experimental design in complex physical systems. His methodological work is motivated by a wide variety of engineering, environmental, and geophysics applications. He received his SB, SM, and PhD degrees from MIT and spent several years at Sandia National Laboratories before joining the MIT faculty in 2009. He is a recipient of the Hertz Foundation Doctoral Thesis Prize (2004), the Sandia Laboratories Truman Fellowship (2004-2007), the US Department of Energy Early Career Research Award (2010), and the Junior Bose Award for Teaching Excellence from the MIT School of Engineering (2012). He is an Associate Fellow of the AIAA and currently serves on the editorial boards of the SIAM Journal on Scientific Computing, Advances in Computational Mathematics, and the SIAM/ASA Journal on Uncertainty Quantification, among other journals. He is also an avid coffee drinker and occasional classical pianist.
EU Regional School - Kiendl Seminar
Prof. Dr. Josef Kiendl - Structural Analysis of Shells: Geometry, Mechanics, and Computational Methods
, Norwegian University of Science and Technology, Norway
Shell structures are ubiquitous in engineering and nature as they provide a very high ratio of stiffness to weight. Their structural behavior is mainly determined by their shape, and geometry plays a fundamental role in establishing the equations for shell mechanics. In practice, structural analysis is performed mainly through numerical methods like finite element analysis and there have been decades of research for developing efficient and robust shell elements. Isogeometric Analysis, which aims at combining computer-aided geometric design and analysis, has shown to be especially well-suited for shell analysis and has led to a new wave of research on shell element formulations.
In this lecture, we will first discuss the theory of shell structures, starting with an introduction to differential geometry and then deriving the governing equations in strong and weak forms. Based on that, we will discuss their solution with numerical methods and consider different element formulations from FEA and IGA. Finally, some applications from actual research within isogeometric shell analysis will be presented.
SSD - Elber Seminar
Prof.Gershon Elber, Ph.D. - Volumetric Representations: the Geometric Modeling of the Next Generation
The needs of modern (additive) manufacturing (AM) technologies can be satisfied no longer by boundary representations (B-reps), as AM requires the representation and manipulation of interior fields and materials as well. Further, while the need for a tight coupling between design and analysis has been recognized as crucial almost since geometric modeling (GM) has been conceived, contemporary GM systems only offer a loose link between the two, if at all.
For about half a century, (trimmed) Non Uniform Rational B-spline (NURBs) surfaces has been the B-rep of choice for virtually all the GM industry. Fundamentally, B-rep GM has evolved little during this period. In this talk, we seek to examine an extended volumetric representation (V-rep) that successfully confronts the existing and anticipated design, analysis, and manufacturing foreseen challenges. We extend all fundamental B-rep GM operations, such as primitive and
surface constructors and Boolean operations, to trimmed trivariate V-reps. This enables the much needed tight link to (Isogeometric) analysis on one hand and the full support of (heterogeneous and anisotropic) additive manufacturing on the other.
Examples and other applications of V-rep GM, including AM and lattice- and micro-structure synthesis and heterogeneous materials will also be demonstrated.
SSD - Brockmann Seminar
Dr. Matthias Brockmann- Internet of Production – Need for Simulation and Data Science for the Future of Production
Chair of Machine Tools, RWTH Aachen University
The vision of the „Internet of Production“ describes the common research
roadmap of RWTH Aachen University concerning Industrie 4.0 within the
Cluster of Excellence EXC 2023 at RWTH Aachen University.
Due to highly sophisticated, specialized models and data in production,
Digital Twins – in their meaning as full digital representations – are
neither computationally feasible nor purposeful.
The concept of Digital Shadows will provide cross-domain data access in
real time by combining reduced engineering models and production data
This seminar will provide an overview of actual research topics, as well
as needs and requirements for data science and simulation in the context
of the Internet of Production.
Core concepts like the Digital Shadow, a new reference infrastructure and
approaches for a new level of cross-domain collaboration will be
Practical examples for agile manufacturing will be presented by means of
chosen use cases from different fields of production technology.