ICALEPCS2013 - List of Authors (Conder, A.D.)

Paper

Title

Page

Rapid Software Prototyping into Large Scale Controls Systems

166

B.T. Fishler, M.W. Bowers, G.K. Brunton, S. Cohen, A.D. Conder, J.-M.G. Di Nicola, J. Heebner, J.T. Matone, M. Paul, M. A. Rever, M.J. Shaw, E.M. Tse
LLNL, Livermore, California, USA

Funding: This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. #LLNL-ABS-632892
The programmable spatial shaper (PSS) within the National Ignition Facility (NIF) reduces energy on isolated optic flaws in order to lower the optics maintenance costs. This will be accomplished by using a closed-loop system for determining the optimal liquid-crystal-based spatial light pattern for beamshaping and placement of variable transmission blockers. A stand-alone prototype was developed and successfully run in a lab environment as well as on a single quad of NIF lasers following a temporary hardware reconfiguration required to support the test. Several challenges exist in directly integrating the C-based PSS engine written by an independent team into the Integrated Computer Control System (ICCS) for proof on concept on all 48 NIF laser quads. ICCS is a large-scale data-driven distributed control system written primarily in Java using CORBA to interact with +60K control points. The project plan and software design needed to specifically address the engine interface specification, configuration management, reversion plan for the existing 0% transmission blocker capability, and a multi-phase integration and demonstration schedule.

Poster MOPPC038 [2.410 MB]

THMIB04

Optimizing Blocker Usage on NIF Using Image Analysis and Machine Learning

1079

L.M. Kegelmeyer, A.D. Conder, L.A. Lane, M.C. Nostrand, J.G. Senecal, P.K. Whitman
LLNL, Livermore, California, USA

Funding: This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. #LLNL-ABS-633358
To optimize laser performance and minimize operating costs for high energy laser shots it is necessary to locally shadow, or block, flaws from laser light exposure in the beamline optics. Blockers are important for temporarily shadowing a flaw on an optic until the optic can be removed and repaired. To meet this need, a combination of image analysis and machine learning techniques have been developed to accurately define the list of locations where blockers should be applied. The image analysis methods extract and measure evidence of flaw candidates and their correlated downstream hot spots and this information is passed to machine learning algorithms which rank the probability that candidates are flaws that require blocking. Preliminary results indicate this method will increase the percentage of true positives from less than 20% to about 90%, while significantly reducing recall – the total number of candidates brought forward for review.

Slides THMIB04 [0.243 MB]

Poster THMIB04 [2.532 MB]

Paper	Title	Page
MOPPC038	Rapid Software Prototyping into Large Scale Controls Systems	166
	B.T. Fishler, M.W. Bowers, G.K. Brunton, S. Cohen, A.D. Conder, J.-M.G. Di Nicola, J. Heebner, J.T. Matone, M. Paul, M. A. Rever, M.J. Shaw, E.M. Tse LLNL, Livermore, California, USA
	Funding: This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. #LLNL-ABS-632892 The programmable spatial shaper (PSS) within the National Ignition Facility (NIF) reduces energy on isolated optic flaws in order to lower the optics maintenance costs. This will be accomplished by using a closed-loop system for determining the optimal liquid-crystal-based spatial light pattern for beamshaping and placement of variable transmission blockers. A stand-alone prototype was developed and successfully run in a lab environment as well as on a single quad of NIF lasers following a temporary hardware reconfiguration required to support the test. Several challenges exist in directly integrating the C-based PSS engine written by an independent team into the Integrated Computer Control System (ICCS) for proof on concept on all 48 NIF laser quads. ICCS is a large-scale data-driven distributed control system written primarily in Java using CORBA to interact with +60K control points. The project plan and software design needed to specifically address the engine interface specification, configuration management, reversion plan for the existing 0% transmission blocker capability, and a multi-phase integration and demonstration schedule.
	Poster MOPPC038 [2.410 MB]

THMIB04	Optimizing Blocker Usage on NIF Using Image Analysis and Machine Learning	1079
	L.M. Kegelmeyer, A.D. Conder, L.A. Lane, M.C. Nostrand, J.G. Senecal, P.K. Whitman LLNL, Livermore, California, USA
	Funding: This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. #LLNL-ABS-633358 To optimize laser performance and minimize operating costs for high energy laser shots it is necessary to locally shadow, or block, flaws from laser light exposure in the beamline optics. Blockers are important for temporarily shadowing a flaw on an optic until the optic can be removed and repaired. To meet this need, a combination of image analysis and machine learning techniques have been developed to accurately define the list of locations where blockers should be applied. The image analysis methods extract and measure evidence of flaw candidates and their correlated downstream hot spots and this information is passed to machine learning algorithms which rank the probability that candidates are flaws that require blocking. Preliminary results indicate this method will increase the percentage of true positives from less than 20% to about 90%, while significantly reducing recall – the total number of candidates brought forward for review.
	Slides THMIB04 [0.243 MB]
	Poster THMIB04 [2.532 MB]