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THE NSMMS & CRASTE JOINT SYMPOSIA
June 26 @ 8:00 am - June 29 @ 5:00 pm PDT
NSMMS and CRASTE, two space focused conferences, will co-locate events for the 11th year. These co-located Symposia continue their outstanding legacy in bringing together technologists, users, and decision makers from across the nation. Discussions involves key technology issues related to space, missile, hypersonic systems, and a variety of ground-breaking commercial space topics necessary for our Country’s defense and research and development pursuits. What this means for you – you can attend two events with one registration fee, experience an expanded exhibit show and poster session, have more people to network and exchange ideas with, and have even more technical talks to participate in.
The 2023 forum will have a joint senior level Plenary Session, a variety of technical sessions covering ground-breaking research and technology, an exhibit show, a student grant program which promotes college-level participation in science and technology, and a work-share and job board program to promote workforce development.
Abstract:
Constructing a well-characterized aero-database is essential for understanding the flight characteristics of a vehicle. High-fidelity CFD simulations can be time-consuming to generate. Generating samples in an efficient manner can greatly reduce the total simulation time. In practice, standard approaches often consider the whole space to be equally important, but there are many situations where this assumption does not hold. For example, the surrogate model is often queried non-uniformly and this information can be utilized to better refine the database. We develop an efficient approach to weighted active-learning for Gaussian process and multi-fidelity cokriging models. We apply this approach to multiple examples to demonstrate potential use cases and show its effectiveness in practice.
This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.