This Grant is a continuation of N000141410521.Stochastic inversion framework for monitoring evolving surface ship mass properties during arctic

Abstract

1.Study Arctic operational conditions and climatological data to gain sufficient physical insight to be able to eff ectively model salient meteorologicalconditions aff ecting ice accretion2. Study existing approaches to modeling ice accretion on surface combatanttopside structures in order that improvements in predictive mechanismsmight be uncovered3. Develop of computational infrastructure to predict accretion, furnish stochas-tic inversions of mass properties (as well as the modeling parameters de-scribing accretion severity), and quantify uncertainty within all of themodeling parameters4. Close the loop with respect to the infl uence of ice accretion on alteredmass properties, and their subsequent eff ects on seakeeping and stabilityof surface combatants, in order that operational envelopes may be adjusted

Document Details

Document Type
DoD Grant Award
Publication Date
Aug 12, 2016
Source ID
N000141612369

Entities

People

  • Christopher Earls

Organizations

  • Cornell University
  • Office of Naval Research
  • United States Navy

Tags

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Distributed Systems and Data Platform Development
  • Polar and Arctic Studies