258 research outputs found

    Comparison of Transport Properties Models for Flowfield Simulations of Ablative Heat Shields

    Full text link
    Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140699/1/1.t4233.pd

    Application of a Modular Particle-Continuum Method to Hypersonic Propulsive Deceleration

    Full text link
    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90682/1/AIAA-2011-3137-898.pd

    Evaluation of Computational Modeling of Electron Transpiration Cooling at High Enthalpies

    Full text link
    Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143076/1/1.T4932.pd

    Interactions of Single-Nozzle Supersonic Propulsive Deceleration Jets on Mars Entry Aeroshells

    Full text link
    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90635/1/AIAA-2011-138-807.pd

    Investigations of Peripheral 4-Jet Sonic and Supersonic Propulsive Deceleration Jets on a Mars Science Laboratory Aeroshell

    Full text link
    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90686/1/AIAA-2011-1036-531.pd

    Investigation of the Interactions of Reaction Control Systems with Mars Science Laboratory Aeroshell

    Full text link
    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/83545/1/AIAA-2010-1558-704.pd

    Planar Laser-Induced Fluorescence Velocity Measurements of Retropropulsion Jets in a Mach 12 Freestream

    Full text link
    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106464/1/AIAA2013-2810.pd

    Revisiting the Random Subset Sum Problem

    Get PDF
    International audienceThe average properties of the well-known Subset Sum Problem can be studied by the means of its randomised version, where we are given a target value zz, random variables X1,
,XnX_1, \ldots, X_n, and an error parameter Δ>0\varepsilon > 0, and we seek a subset of the XiX_i's whose sum approximates zz up to error Δ\varepsilon.In this setup, it has been shown that, under mild assumptions on the distribution of the random variables, a sample of size O(log⁥(1/Δ))\mathcal{O}\left(\log (1/\varepsilon)\right) suffices to obtain, with high probability, approximations for all values in [−1/2,1/2][-1/2, 1/2]. Recently, this result has been rediscovered outside the algorithms community, enabling meaningful progress in other fields. In this work we present an alternative proof for this theorem, with a more direct approach and resourcing to more elementary tools, in the hope of disseminating it even further

    Investigations of Peripheral Propulsive Deceleration Jets on a Mars Science Laboratory Aeroshell

    Full text link
    Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140658/1/1.a32456.pd
    • 

    corecore