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B. T. Kornblum

dblp:32/273 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1990
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
High-performance computing · 50% Performance modeling and evaluation · 50%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational science and engineering · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational science and engineering
computational physics
0.011990
MONT3E: a Monte Carlo electron heat transfer code · SC 1990
Performance modeling and evaluation › simulation
monte carlo simulation
0.011990
MONT3E: a Monte Carlo electron heat transfer code · SC 1990
High-performance computing
scientific computing systems
0.011990
MONT3E: a Monte Carlo electron heat transfer code · SC 1990

Methods — techniques the papers use, named apart from their topics

monte carlo method · 0.0
YearPublicationVenuePosition
1990 MONT3E: a Monte Carlo electron heat transfer code
abstract
A Monte Carlo code, MONT3E, was written to analyze heat transfer due to electron backscattering. The availability of supercomputers has made large-scale applications of this analysis technique possible. The physical theory of electron trajectories is described and related to implementation of an electron tracing algorithm. The analysis requires three types of information: a geometric description of the enclosed volume under analysis, a magnetic field definition, and a model of electron-surface interaction. The implementation of these three components in MONT3E is presented. An electron backscatter experiment was modeled using the code. The MONT3E predictions compared favorably to the experimental data, lending confidence to code predictions.>
J. D. Maltby, B. T. Kornblum
SC2