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Hugh A. Bruck

Researcher at University of Maryland, College Park

Publications -  173
Citations -  6666

Hugh A. Bruck is an academic researcher from University of Maryland, College Park. The author has contributed to research in topics: Digital image correlation & Flapping. The author has an hindex of 30, co-authored 170 publications receiving 5876 citations. Previous affiliations of Hugh A. Bruck include Sewanee: The University of the South & University of Maryland, Baltimore County.

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Digital image correlation using Newton-Raphson method of partial differential correction

TL;DR: In this paper, the authors developed and limited experimental verification of a method which can determine displacements and gradients using the Newton-Raphson method of partial corrections, which was shown to be accurate in determining displacement and certain gradients, while using significantly less CPU time than the current coarse-fine search method.
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Processing bulk natural wood into a high-performance structural material

TL;DR: A simple and effective strategy to transform bulk natural wood directly into a high-performance structural material with a more than tenfold increase in strength, toughness and ballistic resistance and with greater dimensional stability is reported.
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Quasi-static constitutive behavior of Zr41.25Ti13.75Ni10Cu12.5Be22.5 bulk amorphous alloys

TL;DR: In this paper, it was shown that amorphous metal alloys obey a Von Mises yield criterion, which has implications in determining the micromechanisms of plastic deformation in these materials.
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The dynamic compressive behavior of beryllium bearing bulk metallic glasses

TL;DR: In this article, the dynamic compressive yield behavior of a beryllium bearing bulk metallic glass was characterized at strain rates of 102 to 104/s by using the split Hopkinson pressure bar.
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Full-field representation of discretely sampled surface deformation for displacement and strain analysis

TL;DR: In this paper, a detailed evaluation of the feasibility of determining displacements and displacement gradients from measured surface displacement fields is presented, and an improved methodology for both the estimation and elimination of noise is proposed.