Michael R. Larche
Pacific Northwest National Laboratory
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Featured researches published by Michael R. Larche.
42ND ANNUAL REVIEW OF PROGRESS IN QUANTITATIVE NONDESTRUCTIVE EVALUATION: Incorporating the 6th European-American Workshop on Reliability of NDE | 2016
Gerges Dib; Michael R. Larche; Aaron A. Diaz; Susan L. Crawford; Matthew S. Prowant; Michael T. Anderson
Computer modeling and simulation is becoming an essential tool for transducer design and insight into ultrasonic nondestructive evaluation (UT-NDE). As the popularity of simulation tools for UT-NDE increases, it becomes important to assess their reliability to model acoustic responses from defects in operating components and provide information that is consistent with in-field inspection data. This includes information about the detectability of different defect types for a given UT probe. Recently, a cooperative program between the Electrical Power Research Institute and the U.S. Nuclear Regulatory Commission was established to validate numerical modeling software commonly used for simulating UT-NDE of nuclear power plant components. In the first phase of this cooperative, extensive experimental UT measurements were conducted on machined notches with varying depth, length, and orientation in stainless steel plates. Then, the notches were modeled in CIVA, a semi-analytical NDE simulation platform develope...
Proceedings of SPIE | 2017
Michael R. Larche; Mathew Prowant; Tobias Hagge; Leonard S. Fifield; Michael S. Hughes; Xin Sun
This study compares different approaches for imaging the internal architecture of graphite/epoxy composites using backscattered ultrasound. Two cases are studied. In the first, near-surface defects in a thin graphite/epoxy plates are imaged. The backscattered waveforms were used to produce peak-to-peak, logarithm of signal energy, as well as entropy images of different types. All of the entropy images exhibit better border delineation and defect contrast than either the peak-to-peak or the logarithm of signal energy. The best results are obtained using the joint entropy of the backscattered waveforms with a reference function. Two different references are examined. The first is a reflection of the insonifying pulse from a stainless steel reflector. The second is an approximate optimum obtained from an iterative parametric search. The joint entropy images produced using this reference exhibit three times the contrast obtained in previous studies. These plates were later destructively analyzed to determine size and location of near-surface defects and the results are found to agree with the defect location and shape as indicated by the entropy images. In the second study, images of long carbon fibers (50% by weight) in polypropylene thermoplastic were obtained as a first step toward ultrasonic determination of the distributions of fiber position and orientation.
Archive | 2015
Susan L. Crawford; Michael T. Anderson; Aaron A. Diaz; Michael R. Larche; Matthew S. Prowant; Anthony D. Cinson
Ultrasonic evaluation of materials for material characterization and flaw detection is as simple as manually moving a single-element probe across a specimen and looking at an oscilloscope display in real time or as complex as automatically (under computer control) scanning a phased-array probe across a specimen and collecting encoded data for immediate or off-line data analyses. The reliability of the results in the second technique is greatly increased because of a higher density of measurements per scanned area and measurements that can be more precisely related to the specimen geometry. This chapter will briefly discuss applications of the collection of spatially encoded data and focus primarily on the off-line analyses in the form of data imaging. Pacific Northwest National Laboratory (PNNL) has been involved with assessing and advancing the reliability of inservice inspections of nuclear power plant components for over 35 years. Modern ultrasonic imaging techniques such as the synthetic aperture focusing technique (SAFT ), phased-array (PA) technology, and sound field mapping have undergone considerable improvements to effectively assess and better understand material constraints.
Archive | 2014
Susan L. Crawford; Matthew S. Prowant; Anthony D. Cinson; Michael R. Larche; Aaron A. Diaz; Michael T. Anderson
This study maps the phased array-generated acoustic sound fields through three types of CASS microstructure in four specimens to quantitatively assess the beam formation effectiveness in these materials.
ASME 2014 Pressure Vessels and Piping Conference | 2014
Susan L. Crawford; Matthew S. Prowant; Anthony D. Cinson; Michael R. Larche; Aaron A. Diaz; Michael T. Anderson
The Pacific Northwest National Laboratory (PNNL) has been involved with nondestructive examination (NDE) of coarse-grained cast austenitic stainless steel (CASS) components for over 30 years. More recent work has focused on mapping the ultrasonic sound fields generated by low-frequency phased array probes that are typically used for the evaluation of CASS materials for flaw detection and characterization. The casting process results in the formation of large grained material microstructures that are nonhomogeneous and anisotropic. The propagation of ultrasonic energy for examination of these materials results in scattering, partitioning and redirection of these sound fields. The work reported here provides an assessment of sound field formation in these materials and provides recommendations on ultrasonic inspection parameters for flaw detection in CASS components.
Archive | 2013
Ryan M. Meyer; Anthony M. Jones; Allan F. Pardini; Kayte M. Denslow; Susan L. Crawford; Michael R. Larche
This report documents FY14 efforts for two instrumentation subtasks under storage and transportation. These instrumentation tasks relate to developing effective nondestructive evaluation (NDE) methods and techniques to (1) verify the integrity of metal canisters for the storage of used nuclear fuel (UNF) and to (2) verify the integrity of dry storage cask internals.
Archive | 2013
Ryan M. Meyer; Allan F. Pardini; Judith M. Cuta; Harold E. Adkins; Andrew M. Casella; Hong Qiao; Michael R. Larche; Aaron A. Diaz; Steven R. Doctor
Materials evaluation | 2018
Ryan M. Meyer; Pradeep Ramuhalli; Steven R. Doctor; Susan L. Crawford; Matthew S. Prowant; Michael R. Larche; Aaron A. Diaz; Michael T. Anderson
Archive | 2016
Gerges Dib; Michael R. Larche; Aaron A. Diaz; Susan L. Crawford; Michael T. Anderson
Archive | 2015
Aaron A. Diaz; Clyde E. Chamberlin; Matthew K. Edwards; Tobias Hagge; Michael S. Hughes; Michael R. Larche; Royce Mathews; Kevin J. Neill; Matthew S. Prowant