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Erik L Frankforter

Publications and source records attributed to Erik L Frankforter.

4 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Flash Thermal Diffusivity Measurements and Inspection of Additively Manufactured Ti-6Al-4V Specimens with Varying Process Parameters

Flash thermal diffusivity measurements were obtained on additively manufactured Ti-6Al-4V disk shaped specimens with various process parameters. For additively manufactured metal parts, processing parameters such as laser power and scanning speed are critical to ensure the desired microstructure. For this study, the laser powder bed fusion process parameters were changed at various angular sections on a 21 mm diameter and 3.0 mm thick disk. The measurement of thermal diffusivity was performed by fitting a 1-dimensional thermal model to the data pixel by pixel to produce an inspection image. The image revealed the detection of defects such as lack of fusion porosity and areas of aggregated porosity. The thermal diffusivity imagery was compared to immersion scan ultrasonic and X-ray computed tomography (CT) measurements for validation. Based on these results, additional samples were investigated using a single side thermal inspection technique to detect lack of fusion porosity and near surface voids.

thermal nondestructive evaluation↗
NASA NTRSDate not supplied

Automated Registration of Multi-Mode Nondestructive Evaluation Data

Registration techniques play a central role in applications of image processing to computer vision, medical imaging, and automatic target tracking. Feature-based techniques such as scale-invariant feature transform (SIFT) and speeded up robust features (SURF) are commonly used to register images derived from a single modality. However, SIFT and SURF struggle to register images from different modalities because the features tend to manifest rather differently and at sometimes very different length-scales. The most successful methods that have been developed to register multi-modal data use information-theoretic approaches. These methods play a key part in nondestructive evaluation scenarios where data that is collected by sensors of different modalities must be registered to be fused. In this paper, automated registration based on normalized mutual information is applied to align data derived from ultrasonic and radiographic inspections of (i) additively manufactured titanium alloy test coupons, and (ii) thin, lithium metal pouch-cell batteries. The quality of the registration is quantified in terms of computational resources and spatial accuracy. In the first case the X-ray computed tomography (XCT) data is captured on a region corresponding to a small subset of the ultrasonic data, while in the case of the lithium batteries the digital radiography (DR) captures a larger region of interest than the ultrasonic data. In both cases the radiographic data resolution is much higher than for ultrasound, but interestingly, in both cases the accuracy of the registration is approximately equal to two-to-three-pixel lengths in the ultrasonic images.

Nondestructive Evaluation↗