Non-Destructive Testing Using Millimeter-Wave Radar Imaging

Cynthia Gonzales | 23-FS-005

Project Overview

Identified as one of five Director's initiatives in Lawrence Livermore National Laboratory's 2022 Investment Strategy, Accelerated Materials and Manufacturing (AM), is essential to the creation of innovative materials with utilization across a broad range of mission applications. The initiative's success is dependent on the development of novel methods for quality assurance (QA) and techniques which provide guidance throughout the production process. Non-destructive testing (NDT) methods are crucial to identifying defects present in AM parts. Digital radiography and computed tomography are currently the most reliable methods aside from standard electro-optical (EO) techniques, but these methods have limitations in the size of the device, the achieved resolution, diversity of applications, and in initial and operational expense. Motivated by its successful application to vision-sensing problems in the automotive industry and its relatively low cost, we proposed millimeter-wave radar imaging (mm-Wave) as an alternative. We attempted to form reconstructed digital models of various objects by performing a series of transmit and receive collections using the mm-Wave array. Through our efforts, it was determined that an off-the-shelf mm-wave Frequency Modulated Continuous Wave (FMCW) radar sensor could not be used to achieve the necessary ~1mm^3 - 5mm^3 resolution to perform NDT of larger (~1cm^3 - 10cm^3) polymeric AM parts. However, additional research suggests that an off-the shelf mm-Wave pulse radar sensor could potentially achieve the desired resolution needed for this application.

Mission Impact

By developing non-destructive capabilities for evaluating the integrity of AM materials we are promoting a responsive approach for material development as well as a metric for meeting NNSA needs. Specifically, this capability is directly in line with the Director's Initiative on Accelerated Materials and Manufacturing in the areas of optimal design and advanced in-situ characterizations. Successfully implementing this capability would develop science and technology tools and capabilities to meet future national security challenges.