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VERSION:2.0
PRODID:icalendar-ruby
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BEGIN:VEVENT
DTSTAMP:20260705T072209Z
UID:cc46b374-eb0f-4897-be3b-b2ef2361d049
DTSTART:20210510T073000Z
DTEND:20210512T150000Z
DESCRIPTION:Uncertainty in computer simulations\, deterministic and probabi
 listic methods for quantifying uncertainty\, OpenTurns software\, Uranie s
 oftware\n\nContent\nUncertainty quantification takes into account the fact
  that most inputs to a simulation code are only known imperfectly. It seek
 s to translate this uncertainty of the data to improve the results of the 
 simulation. This training will introduce the main methods and techniques b
 y which this uncertainty propagation can be handled without resorting to a
 n exhaustive exploration of the data space. HPC plays an important role in
  the subject\, as it provides the computing power made necessary by the la
 rge number of simulations needed.\nThe course will present the most import
 ant theoretical tools for probability and statistical analysis\, and will 
 illustrate the concepts using the OpenTurns software.\n\nCourse Outline\n\
 nDay 1 : Methodology of Uncertainty Treatment – Basics of Probability an
 d Statistics\n•    General Uncertainty Methodology (30’) : A. Dutfo
 y\n•    Probability and Statistics: Basics (45’) : G. Blondet\n•
     General introduction to Open TURNS and Uranie (2 * 30’) : G. Blon
 det\, J.B. Blanchard\n•    Introduction to Python and Jupyter (45’)
 : practical work on distributions manipulations\nLunch\n•    Uncertai
 nty Quantification (45’) : J.B. Blanchard\n•    OpenTURNS – Urani
 e practical works: sections 1\, 2 (1h): G. Blondet\,  J.B. Blanchard\,  
 A. Dutfoy\n•    Central tendency and Sensitivity analysis (1h): A. Du
 tfoy\n\nDay 2 : Quantification\, Propagation and Ranking of Uncertainties\
 n•    Application to OpenTURNS and Uranie (1h): section 3 M. Baudin\,
  G. Blondet\, F. Gaudier\, J.B. Blanchard\n•    Estimation of probabi
 lity of rare events (1h): G. Blondet\n•    Application to OpenTURNS a
 nd Uranie (1h): M. Baudin\, G. Blondet\, F. Gaudier\, J.B. Blanchard\nLunc
 h\n•    Distributed computing (1h) : Uranie (15’\, F. Gaudier\, J.B
 . Blanchard)\, OpenTURNS (15’\, G. Blondet)\, Salome et OpenTURNS (30’
 \, O. Mircescu)\n•    Optimisation and Calibration (1h) : J.B. Blanch
 ard\, M. Baudin\n•    Application to OpenTURNS and Uranie (1h): J.B. 
 Blanchard\, M. Baudin\n\nDay 3 : HPC aspects – Meta model\n•    HPC
  aspects specific to the Uncertainty treatment (1h) : K. Delamotte\n• 
    Introduction to Meta models (validation\, over-fitting) – Polynomia
 l chaos expansion (1h) : JB Blanchard\, C. Mai\,\n•    Kriging meta m
 odel (1h): C. Mai\nLunch\n•    Application to OpenTURNS and Uranie (2
 h) : C. Mai\, G. Blondet\, J.B. Blanchard\n•    Discussion /  Partic
 ipants projects\n\nLearning outcomes\nLearn to recognize when uncertainty 
 quantification can bring new insight to simulations.\nKnow the main tools 
 and techniques to investigate uncertainty propagation.\nGain familiarity w
 ith modern tools for actually carrying out the computations in a HPC conte
 xt.\n\nPrerequisites\nBasic knowledge of probability will be useful\, as w
 ill a basic familiarity with Linux.\nhttps://events.prace-ri.eu/event/1081
 /
SUMMARY:[ONLINE] Uncertainty quantification @ MdlS
URL;VALUE=URI:https://events.prace-ri.eu/event/1081/
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