Howard Hung

National Institute of Standards and Technology

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James S. Sims

National Institute of Standards and Technology

William L. George

National Institute of Standards and Technology

J E. Devaney

National Institute of Standards and Technology

John G. Hagedorn

Information Technology Laboratory

Steven G. Satterfield

University of West Florida

C. E. Bouldin

National Institute of Standards and Technology

Adele P. Peskin

National Institute of Standards and Technology

Garnett W. Bryant

National Institute of Standards and Technology

Terence J. Griffin

National Institute of Standards and Technology

James A. Warren

National Institute of Standards and Technology

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National Institute of Standards and Technology

United States Department of Commerce

National Institute of Standards

Information Technology Laboratory

University of Maryland, College Park

University of Washington

Material Measurement Laboratory

University of Illinois Urbana-Champaign

Physical Measurement Laboratory

Institute For Defense Analyses

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Accelerating scientific discovery through computation and visualization II

James S. Sims William L. George Steve G Satterfield Howard Hung John G. Hagedorn

This is the second in a series of articles describing a wide variety of projects at NIST that synergistically combine physical science and information science.It describes, through examples, how the Scientific Applications and Visualization Group (SAVG) at NIST has utilized high performance parallel computing, visualization, and machine learning to accelerate research.The examples include scientific collaborations in the following areas: (1) High Precision Energies for few electron atomic systems, (2) Flows of suspensions, (3) X-ray absoiption.(4) Molecular dynamics of fluids, (5) Nanostructures, (6) Dendritic growth in alloys, (7) Screen saver science, (8) genetic programming.

Scientific discovery

10.6028/nist.ir.6877

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Citations (2)

Accelerating scientific discovery through computation and visualization

Journal of Research of the National Institute of Standards and Technology (2000)

James S. Sims John G. Hagedorn Peter M Ketcham Steven G. Satterfield Timothy J. Griffin

The rate of scientific discovery can be accelerated through computation and visualization. This acceleration results from the synergy of expertise, computing tools, and hardware for enabling high-performance computation, information science, and visualization that is provided by a team of computation and visualization scientists collaborating in a peer-to-peer effort with the research scientists. In the context of this discussion, high performance refers to capabilities beyond the current state of the art in desktop computing. To be effective in this arena, a team comprising a critical mass of talent, parallel computing techniques, visualization algorithms, advanced visualization hardware, and a recurring investment is required to stay beyond the desktop capabilities. This article describes, through examples, how the Scientific Applications and Visualization Group (SAVG) at NIST has utilized high performance parallel computing and visualization to accelerate condensate modeling, (2) fluid flow in porous materials and in other complex geometries, (3) flows in suspensions, (4) x-ray absorption, (5) dielectric breakdown modeling, and (6) dendritic growth in alloys.

Scientific visualization

NIST

10.6028/jres.105.068

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Citations (6)

Life Cycle costing :

S Wayne Stiefel S Justin Kim Howard Hung

This report assesses the practicability for applying the life cycle costing (LCC) approach to consumer products.The report provides a basis for understanding: the potential for application, benefits and effects of LCC; the basic concept of LCC; its interaction with performance, and the state-of-the- art of "life" testing as it relates to developing extended performance test methods for consumer products.The report reviews information now obtainable and barriers to labeling consumer products with LCC information.An observation is made that application of LCC to consumer products is not iumediately practicable.The basic areas requiring further investigation are identified, long term research goals are suggested and activities deserving immediate attention are described.1 .

Life Cycle Costing

10.6028/nbs.ir.77-1212

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Strength of Solvent-Exposed Salt-Bridges

The Journal of Physical Chemistry B (1999)

Ray Luo Laurent David Howard Hung J E. Devaney Michael K. Gilson

This paper uses a recently developed computer model to study the energetics of solvent-exposed salt-bridges. The model uses the "mining minima" method to compute conformational free energies with the CHARMm empirical force and the generalized Born solvation model. Satisfactory agreement is obtained in comparison with the measured binding affinities of ion pairs in solution and with the salt-bridge energetics deduced from studies of salt-bridges in helical peptides. The calculations suggest that stabilizing charge−charge interactions in helical peptides do not require well-defined salt-bridge conformations. This is in agreement with crystallographic studies of charge pairs added to T4 lysozyme by site-directed mutagenesis. The computer model is also used to make a testable prediction that arginine and phosphotyrosine residues in an (i, i + 4) relationship will form a particularly strong salt-bridge in helical peptides. The biological implications of these results are discussed.

Salt bridge

Energetics

Implicit solvation

Affinities

Maxima and minima

10.1021/jp982715i

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Citations (66)

Dependence of electron density on Fermi energy in N-type gallium antimonide

Journal of Research of the National Institute of Standards and Technology (2003)

Herbert S. Bennett Howard Hung

The majority electron density as a function of the Fermi energy is calculated in zinc blende, n-type GaSb for donor densities between 10(16) cm(-3) and 10(19) cm(-3). These calculations solve the charge neutrality equation self-consistently for a four-band model (three conduction sub-bands at Γ, L, and X and one equivalent valence band at Γ) of GaSb. Our calculations assume parabolic densities of states and thus do not treat the density-of-states modifications due to high concentrations of dopants, many body effects, and non-parabolicity of the bands. Even with these assumptions, the results are important for interpreting optical measurements such as Raman measurements that are proposed as a nondestructive method for wafer acceptance tests.

Density of states

Gallium antimonide

10.6028/jres.108.019

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Citations (19)

Probabilities of vertical overlap :

Howard Hung Judith F Gilsinn Karla Hoffman

Because of the potential increase in traffic at FL 290 and above, both current and alternative vertical separation standards are being reviewed. A plan to collect data on the vertical navigational performance of aircraft is also contemplated. This report documents a sensitivity analysis carried out to assess how different assumptions about the probability distribution of 'total vertical error' affect the probability of vertical overlap. The four factors affecting the probability of vertical overlap which are examined in this study are: the functional form of the vertical-error distribution function; the standard deviation of this probability distribution; the vertical dimensions of the aircraft; and the vertical separation standard. Probabilities of vertical overlap were computed over a range of possibilities for each of these four factors in order to discern the effect of each factor. A final section discusses the findings of this study and draws some conclusions.

10.6028/nbs.ir.80-1990

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Accelerating scientific discovery through computation and visualization

James S. Sims John G. Hagedorn Peter M Ketcham Steven G. Satterfield Terence J Grifin

The rate of scientific discovery can be accelerated through computation and visualization.This acceleration results from the synergy of expertise, computing tools, and hardware for enabling high-performance computation, information science, and visualization that is pro- vided by a team of computation and visualization scientists collaborating in a peer-to-peer effort with the re- search scientists.In the context of this discussion, high performance refers to capabilities beyond the current state of the art in desktop computing.To be effective in this arena, a team comprising a critical mass of talent, parallel computing techniques, visualization algorithms, advanced visualization hardware, and a recurring investment is required to stay beyond the desktop capabilities.This article describes, through examples, how the Scientific Applications and Visualization Group (SAVG) at NIST has utilized high performance parallel computing and visualization to accelerate scientific discovery.The examples include scientific collaborations that have ad- vanced research in the following areas: ( 1 ) Bose-Einstein condensate modeling, (2) fluid flow in porous materi- als and in other complex geometries, (3) flows in sus- pensions, (4) X-ray absorption, (5) dielectric breakdown modeling, and (6) dendritic growth in alloys.

Scientific discovery

10.6028/nist.ir.6709

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Citations (3)

Accelerating scientific discovery through computation and visualization II

Journal of Research of the National Institute of Standards and Technology (2002)

James S. Sims William L. George Steven G. Satterfield Howard Hung John G. Hagedorn

This is the second in a series of articles describing a wide variety of projects at NIST that synergistically combine physical science and information science. It describes, through examples, how the Scientific Applications and Visualization Group (SAVG) at NIST has utilized high performance parallel computing, visualization, and machine learning to accelerate research. The examples include scientific collaborations in the following areas: (1) High Precision Energies for few electron atomic systems, (2) Flows of suspensions, (3) X-ray absorption, (4) Molecular dynamics of fluids, (5) Nanostructures, (6) Dendritic growth in alloys, (7) Screen saver science, (8) genetic programming.

NIST

Scientific visualization

10.6028/jres.107.019

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Citations (28)

Accelerating scientific discovery through computation and visualization - III. Tight-binding wave functions for quantum dots

Journal of Research of the National Institute of Standards and Technology (2008)

James S. Sims William L. George Terence J. Griffin John C. Hagedorn Howard Hung

This is the third in a series of articles that describe, through examples, how the Scientific Applications and Visualization Group (SAVG) at NIST has utilized high performance parallel computing, visualization, and machine learning to accelerate scientific discovery. In this article we focus on the use of high performance computing and visualization for simulations of nanotechnology.

NIST

Scientific visualization

Scientific discovery

10.6028/jres.113.010

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Citations (2)

Alignment of fiducial marks in a tomographic tilt series with an unknown rotation axis

Computer Physics Communications (2007)

Zachary H. Levine Alex Volkovitsky Howard Hung

Fiducial marker

Test fixture

10.1016/j.cpc.2007.01.008

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Citations (4)