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DTSTART;TZID=America/Los_Angeles:20190208T111000
DTEND;TZID=America/Los_Angeles:20190208T120000
DTSTAMP:20260611T175909
CREATED:20190208T171147Z
LAST-MODIFIED:20190208T171147Z
UID:63927-1549624200-1549627200@tricities.wsu.edu
SUMMARY:CE Seminar Series - Uncertainty quantification and reduction with conditional Gaussian process models in high dimensional stochastic systems
DESCRIPTION:Ramakrishna Tipireddy\, Ph.D.\nResearch Scientist in the Physical and Computational Sciences Directorate \nPacific Northwest National Laboratory (PNNL) \n  \nAbstract\nThis talk will present a brief introduction to uncertainty quantification (UQ) quantification methods for\nhigh dimensional stochastic PDEs and introduce conditional Gaussian process (GP) models for uncertainty\nreduction. The PDE coefficient is represented as a log-normal random field\, with the corresponding\nGaussian part modeled as a zero-mean Gaussian process (GP) with appropriate covariance function. The\nreduction in uncertainty is achieved by conditioning the GP model on observations of the coefficient at a\nfew spatial locations. The resulting conditional GP model is then discretized using truncated Karhunen-\nLo`eve (KL) expansion and the stochastic solution of the PDE is computed using Monte Carlo and sparsegrid\ncollocation methods. Finally\, uncertainty in the system is further reduced by adaptively selecting\nadditional observation locations using two active learning criteria. The first criteria minimizes the\nvariance of the PDE coefficient\, while the second criteria employs approximately minimizes the variance\nof the solution of the PDE.\nBio\nThis talk will present a brief introduction to uncertainty quantification (UQ) quantification methods for\nhigh dimensional stochastic PDEs and introduce conditional Gaussian process (GP) models for uncertainty\nreduction. The PDE coefficient is represented as a log-normal random field\, with the corresponding\nGaussian part modeled as a zero-mean Gaussian process (GP) with appropriate covariance function. The\nreduction in uncertainty is achieved by conditioning the GP model on observations of the coefficient at a\nfew spatial locations. The resulting conditional GP model is then discretized using truncated Karhunen-\nLo`eve (KL) expansion and the stochastic solution of the PDE is computed using Monte Carlo and sparsegrid\ncollocation methods. Finally\, uncertainty in the system is further reduced by adaptively selecting\nadditional observation locations using two active learning criteria. The first criteria minimizes the\nvariance of the PDE coefficient\, while the second criteria employs approximately minimizes the variance\nof the solution of the PDE.\nCivil
URL:/event/ce-seminar-series-uncertainty-quantification-and-reduction-with-conditional-gaussian-process-models-in-high-dimensional-stochastic-systems/
LOCATION:BSEL 103
CATEGORIES:academic,Calendar,Event,Professional Development
ORGANIZER;CN="Srinivas Allena":MAILTO:srinivas.allena@wsu.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20190218T090000
DTEND;TZID=America/Los_Angeles:20190218T160000
DTSTAMP:20260611T175909
CREATED:20190123T160551Z
LAST-MODIFIED:20190123T160551Z
UID:63382-1550480400-1550505600@tricities.wsu.edu
SUMMARY:Professional Learning Opportunity - Culturally Relevant Teaching
DESCRIPTION:Participants in this session will engage in critical conversations involving gender\, class ethnicity\, and sexual orientation\, and will experience the positive and negative effects that teacher expectations\, privilege\, and stereotyping can have on student achievement. Participants will be encouraged to reflect on their own classroom management and teaching style and will apply their knowledge by creating culturally relevant classrooms and infusing lesson plans with culturally relevant teaching strategies.
URL:/event/professional-learning-opportunity-culturally-relevant-teaching/
LOCATION:CIC 120\, 2710 University Dr\, Richland\, 99354\, United States
CATEGORIES:academic,Calendar,Faculty Development
ORGANIZER;CN="Sara Petersen":MAILTO:sarapetersen@wsu.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20190222T121000
DTEND;TZID=America/Los_Angeles:20190222T130000
DTSTAMP:20260611T175909
CREATED:20190221T011101Z
LAST-MODIFIED:20190221T011101Z
UID:64248-1550837400-1550840400@tricities.wsu.edu
SUMMARY:MME Seminar Series - Vortex-Breakdown and Wall-Separation States in Swirling Flows in Finite-Length Pipes
DESCRIPTION:Abstract\nThe dynamics of inviscid-limit\, incompressible and axisymmetric swirling flows in finite-length\, long circular pipes\nwith varying geometries is studied through global analysis techniques and numerical simulations. The inlet flow is\ndescribed by fixed-in-time profiles of the circumferential and axial velocity together with a fixed azimuthal vorticity\,\nwhile the outlet flow is characterized by a state with zero radial velocity. A numerical algorithm based on the upwind\nfinite-difference method for the evolution of the circulation and azimuthal vorticity together with a Poisson solver for\nthe solution of the stream function in terms of the azimuthal vorticity is developed. The convergence of computed\nresults with mesh refinement is demonstrated. Moreover\, a mathematical analysis that is based on the Squire-Long\nequation (SLE) is formulated to identify steady-state solutions of the problem with special conditions to describe\nstates with separation zones. These solutions include the base columnar flow state\, a decelerated flow along the\ncenterline\, an accelerated flow along the centerline\, a vortex-breakdown state and a wall-separation state. The\nproblem is then reduced to the columnar (axially independent) SLE\, with centerline and wall conditions for the\nsolution of the outlet flow stream function. The numerical simulations realize the various flow states and show\ncorrelation between time-asymptotic states and steady states predicted according to the SLE and the columnar\nSLE problems. The simulations also shed light on the stability of the various steady states. Results show that pipe\ndivergence promotes the appearance of breakdown states at lower inlet swirl levels while pipe contraction delays\nthe appearance of vortex breakdown to higher swirl levels and promotes formation of wall-separation states. The\ninfluence of various inlet swirling flow profiles on the manifold of steady states in a straight\, finite-length pipe and\non flow dynamics is also investigated. Depending on the inlet profiles\, flows may first exhibit vortex breakdown while\nothers wall-separation states. \nMME Seminar_Flyer_Zhang_02.22.2019
URL:/event/mme-seminar-series-vortex-breakdown-and-wall-separation-states-in-swirling-flows-in-finite-length-pipes/
LOCATION:BSEL 102
CATEGORIES:academic,Calendar,Event,student,university
ORGANIZER;CN="Changki Mo":MAILTO:changki.mo@wsu.edu
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