Tel: +1(757) 864-8048; Fax: +1 (757) 864-8290
Email: plassman@nianet.org
Research Interests
- Engineering:
- Acoustic Simulation and Imaging
- Structural Design
- Numerical Methods:
- Optimization
- Linear Systems
- Statistical Analysis
- Signal Processing
- High Performance Computing:
- Parallel Processing
- Scalable Algorithms
- Data Visualization
Current Research
The current research objective is the development, evaluation, and selection of measured noise deconvolution methods appropriate for the 2012 NASA Langley Hybrid Wing Body Acoustic Test. Supporting goals include the development and application of deconvolution methods for quantifying and characterizing varied and partially shielded noise sources in an environment with flow. This includes propagating non-coherent and coherent noise sources in both subsonic and supersonic jet exhaust plumes based on acoustic signal acquisition with two-dimensional microphone array in varied flow-external position and orientation relative to the noise source. Recent focal points include: signal path modeling in a partially shielded environment, the investigation of source scanning grid extent and resolution requirements, array response blending techniques for optimizing the extraction of shock cell characteristics in supersonic flows, the characterization of flow shear layer correction method effectiveness, calibration noise source based techniques for its improvement by the conditioning of array response derived test noise source cross spectral representation, and selective application of an effective coherent noise deconvolution algorithm variant.
Publications
- Brooks, T. F.; Humpherys, W. M. Jr.; and Plassman, G. E.: “DAMAS Processing for a Phased Array Study in the NASA Langley Jet Noise Laboratory”, AIAA Paper 2010-3780, June 2010.
- Plassman, G. E.; Mall, G. H.; and Quagliano’ J. R.: “Linear Multivariable Regression Models for Prediction of Eddy Dissipation Rate from Available Meteorological Data”, NASA CR-2005-213504, July 2005.
- Plassman, G. E.; “A Survey of Singular Value Decomposition Methods and Performance Comparison of Some Available Serial Codes”, NASA CR-2005-213500, July 2005.
- Plassman, G. E. and Sobieszczanski-Sobieski, J.: “Experience with a genetic algorithm implemented on a multi-processor computer”, Structural and Multidisciplinary Optimization, Vol. 22, No. 2, Sept. 2001.
- Plassman, G. E. and Sobieszczanski-Sobieski, J.: “Experience with a genetic algorithm implemented on a multi-processor computer”, AIAA Paper 2000-4844, Sept. 2000.