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All sources NASA NTRS DOE OSTI

DOE OSTI2021

A temperature profile diagnostic for radiation waves on OMEGA-60

Predicting and matching radiation wave propagation with computational models has proven difficult. Information provided by experiments studying radiation flow has been limited when only radiation breakout is measured. We have developed the COAX (co-axial) diagnostic platform to provide spatial temperature profiles of a radiation wave through low density foams as a more detailed constraint for simulations. COAX uses a standard, laser-driven OMEGA-60 halfraum to drive radiation down a titanium-laden silicon oxide foam. Point-projection X-ray absorption spectroscopy perpendicular to the radiation flow measures the spatial profile of titanium ionization. The spectroscopic measurement utilizes a broadband capsule backlighter. Imaging and streak spectroscopy are used to characterize the size and spectrum of this source. Radiography provides an additional constraint by capturing the developing shock as the radiation flow becomes subsonic. The DANTE diagnostic is used to measure the halfraum temperature. Here, we provide a spectroscopic analysis of COAX data to determine temperature, and we describe experimental sources of uncertainty. The temperature is obtained by comparison to multi-temperature synthetic spectra post-processed from radiation-hydrodynamics simulations. Quantitative comparison between data and synthetic spectra generated from temperature profiles at relevant simulation times enable determination of a peak temperature of 114 ± 8 eV at 265 ± 22.4 μm from the halfraum. This represents an improvement over the temperature uncertainties of previous radiation flow experiments. Further refinements to the spectroscopic analysis could achieve ±4 eV. The combination between space-resolved spectroscopy and radiography enables us to determine the distance from the halfraum of both the radiation front and the shock front at the time of measurement. For the example shown in this paper the radiation front position is 600–630 μm at 3.43 ± 0.16 ns and the shock front position is 633 μm at 3.3 ± 0.24 ns.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Seal Strength Calculations for Low Mass DDT Vessel

Lawrence Livermore National Laboratory (LLNL) is collaborating with Colorado School of Mines (Mines), to field the first dynamic experiments on the 3-ring flash radiography system (3-ring). One set of experiments for 3-ring concerns the deflagration to detonation transition (DDT), within a sealed column of high-explosives. The high-explosive material is ignited at one end with a BK-80, an igniter made from Boron Potassium-Nitrate (BKNO 3 ). The initial deflagration reaction will increase the pressure in the sealed vessel, resulting in the formation of a dense "plug" of material ahead of the deflagration front. The transition to detonation is thought to be related to the plug formation. Previous experiments have been able to resolve the plug geometry, but only in a two dimensional radio-graph. 3-ring offers a novel diagnostic tool which could provide three dimensional density fields via few-view reconstruction algorithms and computed tomography.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS2000

Enhanced Imaging of Corrosion in Aircraft Structures with Reverse Geometry X-ray(registered tm)

The application of Reverse Geometry X-ray to the detection and characterization of corrosion in aircraft structures is presented. Reverse Geometry X-ray is a unique system that utilizes an electronically scanned x-ray source and a discrete detector for real time radiographic imaging of a structure. The scanned source system has several advantages when compared to conventional radiography. First, the discrete x-ray detector can be miniaturized and easily positioned inside a complex structure (such as an aircraft wing) enabling images of each surface of the structure to be obtained separately. Second, using a measurement configuration with multiple detectors enables the simultaneous acquisition of data from several different perspectives without moving the structure or the measurement system. This provides a means for locating the position of flaws and enhances separation of features at the surface from features inside the structure. Data is presented on aircraft specimens with corrosion in the lap joint. Advanced laminographic imaging techniques utilizing data from multiple detectors are demonstrated to be capable of separating surface features from corrosion in the lap joint and locating the corrosion in multilayer structures. Results of this technique are compared to computed tomography cross sections obtained from a microfocus x-ray tomography system. A method is presented for calibration of the detectors of the Reverse Geometry X-ray system to enable quantification of the corrosion to within 2%.

Winfree, William P.↗

NASA NTRS2017

Fully Coupled Aero-Thermochemical-Elastic Simulations of an Eroding Graphite Nozzle

A multiphysics simulation capability has been developed that incorporates mutual interactions between aerodynamics, structural response from aero/thermal loading, ablation/pyrolysis, heating, and surface-to-surface radiation to perform high-fidelity, fully coupled aerothermoelastic ablation simulations, which to date had been unattainable. The multiphysics framework couples CHAR (a 3-D implicit charring ablator solver), Loci/CHEM (a computational fluid dynamics solver for high-speed chemically reacting flows), and Abaqus (a nonlinear structural dynamics solver) to create a fully coupled aerothermoelastic charring ablative solver. The solvers are tightly coupled in a fully integrated fashion to resolve the effects of the ablation pyrolysis and charring process and chemistry products upon the flow field, the changes in surface geometry due to recession upon the flow field, and thermal-structural analysis of the body from the induced aerodynamic heating from the flow field. The multiphysics framework was successfully demonstrated on a solid rocket motor graphite nozzle erosion application. Comparisons were made with available experimental data that measured the throat erosion during the motor firing. The erosion data is well characterized, as the test rig was equipped with a windowed nozzle section for real-time X-ray radiography diagnostics of the instantaneous throat variations for deducing the instantaneous erosion rates. The nozzle initially undergoes a nozzle contraction due to thermal expansion before ablation effects are able to widen the throat. A series of parameters studies were conducted using the coupled simulation capability to determine the sensitivity of the nozzle erosion to different parameters. The parameter studies included the shape of the nozzle throat (flat versus rounded), the material properties, the effect of the choice of turbulence model, and the inclusion or exclusion of the mechanical thermal expansion. Overall, the predicted results match the experiment very well, and the predictions were able to bound the data within acceptable limits.

Blades, E. L.↗

DOE OSTI2020

Extended-magnetohydrodynamics in under-dense plasmas

Extended-magnetohydrodynamics (MHD) transports magnetic flux and electron energy in high-energy-density experiments, but individual transport effects remain unobserved experimentally. Two factors are responsible in defining the transport: electron temperature and electron current. Here, each electron energy transport term has a direct analog in magnetic flux transport. To measure the thermally driven transport of magnetic flux and electron energy, a simple experimental configuration is explored computationally using a laser-heated pre-magnetized under-dense plasma. Changes to the laser heating profile precipitate clear diagnostic signatures from the Nernst, cross-gradient-Nernst, anisotropic conduction, and Righi-Leduc heat-flow. With a wide operating parameter range, this configuration can be used in both small and large scale facilities to benchmark MHD and kinetic transport in collisional/semi-collisional, local/non-local, and magnetized/unmagnetized regimes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1999

Synergistic Effects of Physical Aging and Damage on Long-Term Behavior of Polymer Matrix Composites

The research consisted of two major parts, first modeling and simulation of the combined effects of aging and damage on polymer composites and secondly an experimental phase examining composite response at elevated temperatures, again activating both aging and damage. For the simulation, a damage model for polymeric composite laminates operating at elevated temperatures was developed. Viscoelastic behavior of the material is accounted for via the correspondence principle and a variational approach is adopted to compute the temporal stresses within the laminate. Also, the effect of physical aging on ply level stress and on overall laminate behavior is included. An important feature of the model is that damage evolution predictions for viscoelastic laminates can be made. This allows us to track the mechanical response of the laminate up to large load levels though within the confines of linear viscoelastic constitutive behavior. An experimental investigation of microcracking and physical aging effects in polymer matrix composites was also pursued. The goal of the study was to assess the impact of aging on damage accumulation, in ten-ns of microcracking, and the impact of damage on aging and viscoelastic behavior. The testing was performed both at room and elevated temperatures on [+/- 45/903](sub s) and [02/903](sub s) laminates, both containing a set of 90 deg plies centrally located to facilitate investigation of microcracking. Edge replication and X-ray-radiography were utilized to quantify damage. Sequenced creep tests were performed to characterize viscoelastic and aging parameters. Results indicate that while the aging times studied have limited ]Influence on damage evolution, elevated temperature and viscoelastic effects have a profound effect on the damage mode seen. Some results are counterintuitive, including the lower strain to failure for elevated temperature tests and the catastrophic failure mode observed for the [+/- 45/9O3](sub s), specimens. The fracture toughness for transverse cracks increases with increasing temperature for both systems: transverse cracking was completely absent prior to failure in [+/- 45/903](sub s), and was suppressed for [02/903](sub s). No significant effect of damage on aging or viscoelastic parameters was observed.

Brinson, L. Cate↗

DOE OSTI2024

L-PBF High-Throughput Data Pipeline Approach for Multi-modal Integration

Abstract Metal-based additive manufacturing requires active monitoring solutions for assessing part quality. Multiple sensors and data streams, however, generate large heterogeneous data sets that are impractical for manual assessment and characterization. In this work, an automated pipeline is developed that enables feature extraction from high-speed camera video and multi-modal data analysis. The framework removes the need for manual assessment through the utilization of deep learning techniques and training models in a weakly supervised paradigm. We demonstrate this pipeline’s capability over 700,000 high-speed camera frames. The pipeline successfully extracts melt pool and spatter geometries and links them to corresponding pyrometry, radiography, and processparameter information. 715 individual prints are examined to reveal melt pool areas that exceeds 0.07 mm 2 and pyrometry signal over a threshold (375 pyrometry units) were more likely to have defects. These automated processes enable massive throughput of characterization techniques.

36 MATERIALS SCIENCE↗

NASA NTRS2017

Some Observations on Damage Tolerance Analyses in Pressure Vessels

AIAA standards S080 and S081 are applicable for certification of metallic pressure vessels (PV) and composite overwrap pressure vessels (COPV), respectively. These standards require damage tolerance analyses with a minimum reliable detectible flaw/crack and demonstration of safe life four times the service life with these cracks at the worst-case location in the PVs and oriented perpendicular to the maximum principal tensile stress. The standards require consideration of semi-elliptical surface cracks in the range of aspect ratios (crack depth a to half of the surface length c, i.e., (a/c) of 0.2 to 1). NASA-STD-5009 provides the minimum reliably detectible standard crack sizes (90/95 probability of detection (POD) for several non-destructive evaluation (NDE) methods (eddy current (ET), penetrant (PT), radiography (RT) and ultrasonic (UT)) for the two limits of the aspect ratio range required by the AIAA standards. This paper tries to answer the questions: can the safe life analysis consider only the life for the crack sizes at the two required limits, or endpoints, of the (a/c) range for the NDE method used or does the analysis need to consider values within that range? What would be an appropriate method to interpolate 90/95 POD crack sizes at intermediate (a/c) values? Several procedures to develop combinations of a and c within the specified range are explored. A simple linear relationship between a and c is chosen to compare the effects of seven different approaches to determine combinations of aj and cj that are between the (a/c) endpoints. Two of the seven are selected for evaluation: Approach I, the simple linear relationship, and a more conservative option, Approach III. For each of these two Approaches, the lives are computed for initial semi-elliptic crack configurations in a plate subjected to remote tensile fatigue loading with an R-ratio of 0.1, for an assumed material evaluated using NASGRO (registered 4) version 8.1. These calculations demonstrate that for this loading, using Approach I and the initial detectable crack sizes at the (a/c) endpoints in 5009 specified for the ET and UT NDE methods, the smallest life is not at the two required limits of the (a/c) range, but rather is at an intermediate configuration in the range (a/c) of 0.4 to 0.6. Similar analyses using both Approach I and III with the initial detectable crack size at the (a/c) endpoints in 5009 for PT NDE showed the smallest life may be at an (a/c) endpoint or an intermediate (a/c), depending upon which Approach is used. As such, analyses that interrogate only the two (a/c) values of 0.2 and 1 may result in unconservative life predictions. The standard practice may need to be revised based on these results.

Raju, Ivatury S.↗

DOE OSTI2020

MAD using INRAD and Radiography [Slides]

We have previously evaluated Intrinsic Radiation Detection Algorithms from vendors for the Department of Homeland Security. These algorithms have limited spectra capability due to both the relatively low spectral content of the signal due to the use of PVT in the Radiation Portal detectors as well as relatively simple algorithms which are based on energy windowing and other simple algorithms to perform classification of Special Nuclear Material. Current detection algorithms are suceptible to nuissance alarms due to Naturally Occuring Radiation (NORM) and variations in background suppression. In this work, we propose to fuse the intrinsic radiation and radiographic data in conjunction with well-established machine learning algorithms to developed enhanced Threat Object detection capability.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2023

Machine learning for detection of 3D features using sparse x-ray tomographic reconstruction

In many inertial confinement fusion (ICF) experiments, the neutron yield and other parameters cannot be completely accounted for with one and two dimensional models. This discrepancy suggests that there are three dimensional effects that may be significant. Sources of these effects include defects in the shells and defects in shell interfaces, the fill tube of the capsule, and the joint feature in double shell targets. Due to their ability to penetrate materials, x rays are used to capture the internal structure of objects. Methods such as computational tomography use x-ray radiographs from hundreds of projections, in order to reconstruct a three dimensional model of the object. In experimental environments, such as the National Ignition Facility and Omega-60, the availability of these views is scarce, and in many cases only consists of a single line of sight. Mathematical reconstruction of a 3D object from sparse views is an ill-posed inverse problem. These types of problems are typically solved by utilizing prior information. Neural networks have been used for the task of 3D reconstruction as they are capable of encoding and leveraging this prior information. We utilize half a dozen, different convolutional neural networks to produce different 3D representations of ICF implosions from the experimental data. Deep supervision is utilized to train a neural network to produce high-resolution reconstructions. These representations are used to track 3D features of the capsules, such as the ablator, inner shell, and the joint between shell hemispheres. Machine learning, supplemented by different priors, is a promising method for 3D reconstructions in ICF and x-ray radiography, in general.

Wolfe, Bradley T. (ORCID:0000000268301614)↗

NASA NTRS2003

Uses of Computed Tomography for Characterizing Materials Grown Terrestrially and in Microgravity

Tomography (CT) has proved to be of inestimable use in providing a rapid evaluation of a variety of samples from Mechanics of Granular Materials (MGM) to electronic materials (Ge-Si alloys) to space grown materials such as meteorites. The system at Kennedy Space Center (KSC), because of its convenient geographical location, is ideal for examining samples before launch and immediately after returning to Earth. It also has the advantage of the choice of fluxes, and in particular the use of a radioactive cobalt source, which is basically monochromatic. This permits a reasonable measurement of density to be made from which chemical composition can be determined. Due to the current dearth of long duration space grown materials, the CT instrument has been used: (1) to characterize materials in preparation for flight, (2) to determine thermal expansion values, and (3) to examine long duration space grown materials, i.e. meteorites. This work will first describe the establishment of the protocol for obtaining the optimum density readings for any material. Included will be the effects of the hardware or instrumental parameters that can be controlled, and the techniques used to process the CT data. Examples will be given of the compositional variation along a single crystal of Ge-Si alloy. Density variation with temperature has been measured in preparation for future materials science experiments; this involved the fabrication at MSFC and installation of a single zone furnace at KSC incorporating a heat pipe to ensure high temperature uniformity. At the time of writing the thermal expansion of lead (Pb) has been measured from room temperature to 900 C. Three methods are available. Digital radiography enables length changes to be determined. Prior to melting the sample is smaller than the container and the diameter change can be measured. Most critical, however, is the density change in solid, through the melting region, and in the liquid state. These data are needed for engineering purposes to aid in the design of containment cartridges, and for enabling fluid flow calculations. A second sample, with the Pb alloyed with Sb is ready for scanning. This corresponds to the planned composition of Dr. Poirier s flight experiment. Other materials pertinent to NASA programs such as Al-Cu (Trivedi), CdTe (Banish), HgCdTe (Lehoczky) will be examined below and above the melting point. Finally, three-dimensional results will be shown of the structure of a two-phase metallic meteorite of metal and sulfide, in which the Fe-Ni phase has coarsened during slow cooling over hundreds of millions of years.

Source record↗

DOE OSTI2025

Using X-ray radiography to study oxygen flow in a proton exchange membrane electrolyzer operating under balanced pressure conditions

Of the various water electrolyzer technologies, the proton exchange membrane electrolyzer (PEMWE) is one of the best solutions for producing clean hydrogen without releasing CO 2 . In order to allow for widespread use of clean hydrogen, it is necessary to decrease its cost, which is intrinsically related to system operation. Current PEMWE plants operate in differential mode, directly pressurizing hydrogen and benefiting from thermodynamic compression, which increases overall system efficiency. However, high differential pressure above 30 bar can cause membrane stress, resulting in membrane creeping and failure. Pressurizing the water and operating at balanced pressure allows hydrogen to be produced at higher pressures while preserving the integrity of the membrane and porous layers. Nevertheless, the impact of pressurizing water on PEMWE performance must be better understood to maximize performance under balanced pressure conditions. Here, this study examined the impact of water pressure on two-phase flow. A high-pressure electrolyzer setup was developed to perform operando X-ray radiography and examine oxygen transport with high temporal resolution. The imaging segmentation process, developed to capture bubble properties in the channel, was applied to a specific experiment. The results clearly showed that as pressure increased up to 30 bars, the initial bubbly flow transitioned to slug flow, which led to channel saturation with oxygen. This work demonstrates that two-phase flow in an electrolyzer can be studied using X-ray radiography, which has the advantages of fast measurements and the ability to probe dense materials, such as those required for pressurized electrolyzers.

Balanced high pressure operation↗

DOE OSTI2023

A physics-driven Σ-Y atomization model for heavy-duty engine simulations

The atomization of a liquid jet is a multi-scale and multi-physics problem of interest for many engineering applications. Particularly, it drives the fuel-oxidizer mixing and dictates the efficiency of combustion engines. High-fidelity multi-phase simulations remain challenging due to the excessive computational cost required to capture all the atomization scales. Thus, atomization models are necessary to represent sub-grid liquid structures. Here, in this work, a modified Σ-Y model in the context of Eulerian-Lagrangian Spray Atomization (ELSA) is used to transport the surface area density of the spray. The model's predictive performance is assessed under various operating conditions relevant to heavy-duty engines using the Engine Combustion Network (ECN) Spray C and Spray D research-grade injectors. The classic droplet collision formulation of the Σ-Y model alone does not replicate the response of the measured spray surface area to changes in injector, ambient pressure, and injection pressure, requiring individual tuning of the model's parameters. Instead, a transition between dense and dilute spray breakup mechanisms is proposed in terms of the average droplet spacing. The collision breakup mechanism represents the dilute spray, whereas the droplet size in the dense spray is driven by a competition between the integral scale of turbulence and the balance between the turbulent kinetic energy and the surface energy of the droplets. Such an approach minimizes the requirements for model tuning. Moreover, the role of the constants of a compressible standard k-ε RANS model is assessed in the injector's internal flow and external spray simulation framework, and an updated set is proposed. The results are validated against x-ray radiography and Ultra-Small Angle X-ray Scattering (USAXS) data and highlight the predictive capabilities of the proposed physics-driven Σ-Y model, which is compatible with engine simulation turnaround times.

42 ENGINEERING↗

NASA NTRS2002

Uses of Computed Tomography in the NASA Materials Science Program

Computed Tomography (CT) has proved to be of inestimable use in providing a rapid evaluation of a variety of samples from Mechanics of Granular Materials (MGM) to electronic materials (Ge-Si alloys) to space grown materials such as meteorites. The system at Kennedy Space Center (KSC), because of its convenient geographical location, is ideal for examining samples immediately after returning to Earth. It also has the advantage of the choice of fluxes, and in particular the use of a radioactive cobalt source, which is basically monochromatic. This permits a reasonable measurement of density to be made from which chemical composition can be determined. Due to the current dearth of long duration space grown materials, the CT instrument has been used to characterize materials in preparation for flight, to determine thermal expansion values, and to examine long duration space grown materials, i.e. meteorites. The work will first describe the establishment of the protocol for obtaining the optimum density readings for any material. This will include both the effects of the hardware or instrumental parameters that can be controlled, and the techniques used to process the CT data. Examples will be given of the compositional variation along single crystals of germanium-silicon alloys. Density variation with temperature has been measured in preparation for future materials science experiments; this involved the fabrication and installation of a single zone furnace incorporating a heat pipe to ensure of high temperature uniformity. At the time of writing the thermal expansion of lead has been measured from room temperature to 900 C. Three methods are available. Digital radiography enable length changes to be determined. Prior to melting the sample is small than the container and the diameter change can be measured. Most critical, however, is the density change in solid, through the melting region, and in the liquid state. These data are needed for engineering purposes to aid in the design of containment cartridges, and for enabling fluid flow calculations. A second sample, with the lead alloyed with antimony is ready for scanning. This corresponds to the planned composition of Dr. Poirier's flight experiment. Finally, three-dimensional results will be shown of the structure of a two-phase metallic meteorite of metal and sulfide, in which the iron-nickel phase has coarsened during slow cooling over hundreds of millions of years.

Engel, H. Peter↗

DOE OSTI2024

Qualification and Quantification of Porosity at the Top of the Fuel Pins in Metallic Fuels Using Image Processing

Approximately 130,000 metal fuel pins were irradiated in the Experimental Breeder Reactor II (EBR-II) during its 30 years of operation to develop and characterize existing and prospective fuels. For many of the metal fuel irradiation experiments, neutron radiography imaging was performed to characterize fuel behavior, such as fuel axial expansion. While several fuel expansion results obtained from neutron radiography imaging have been published, the analysis of neutron radiography for the purpose of describing statistical properties of porous matter formed on top of the fuel pins, also referred to as fluff in previous publications, is significantly less represented in the literature with just a single paper so far. This study aims to validate and augment results reported in previous publications using automated image processing. The paper describes the statistical properties of the porous matter in terms of nine parameters derived from radiography images and correlates those parameters with such fuel properties as composition, expansion, temperature, and burnup. The reported results are based on 1097 fuel pins of eight different fuel compositions. For three major fuel types, U-10Zr, U-8Pu-10Zr, and U-19Pu-10Zr, a clear negative correlation is found between the Pu content and five parameters describing the amount of porous matter generated. The parameters describing granularity properties, however, showed either negative correlation or nonlinear dependency from fuel composition. The parameters describing the amount showed a positive correlation with fuel axial expansion, while granularity parameters showed a negative correlation with axial expansion. The dependency on cladding temperature was found to be weak. A positive correlation is demonstrated for volume parameters and fuel burnup. In general, reported results confirm and validate findings published in previous studies using a much larger number of pins and automated processing techniques, which easily lend themselves to reproducibility, thus avoiding subjective bias.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Bayesian Spatially Varying Multi-Regularization Image Deblurring

Many scientific experiments such as those found in astronomy, geology, microbiology, and X-ray radiography require the use of high-energy instruments to capture images. Since blur and noise are inevitably present in any imaging system, the images must be \deblurred" to extract the full information content. Mathematically, image deblurring is an ill-posed inverse problem that requires regularization. The regularization, in turn, has a large effect on the deblurred image: different regularization strengths, and types, lead to drastically different reconstructions. Moreover, many images contain a mixture of smooth and sharp features which suggests the use of multi-regularization, i.e., varying the type of regularization (e.g. Tikhonov or total variation) across the image. We address these issues by formulating the image deblurring problem within a hierarchical Bayesian framework in which we spatially adapt the strength of the regularization and also vary the regularization type across the image. In this way, the image itself, along with corresponding regularization strength at each pixel, are described jointly by a posterior distribution which we can sample by Markov chain Monte Carlo (MCMC) methods. We illustrate our techniques on simplified test problems and apply them to high-energy X-ray images taken at the Nevada National Security Site. Numerical tests show that our new method is robustly applicable and increases the quality of the image reconstruction when compared to other (Bayesian) methods.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Deep learning with mixup augmentation for improved pore detection during additive manufacturing

In additive manufacturing (AM), process defects such as keyhole pores are difficult to anticipate, affecting the quality and integrity of the AM-produced materials. Hence, considerable efforts have aimed to predict these process defects by training machine learning (ML) models using passive measurements such as acoustic emissions. This work considered a dataset in which keyhole pores of a laser powder bed fusion (LPBF) experiment were identified using X-ray radiography and then registered both in space and time to acoustic measurements recorded during the LPBF experiment. Due to AM’s intrinsic process controls, where a pore-forming event is relatively rare, the acoustic datasets collected during monitoring include more non-pores than pores. In other words, the dataset for ML model development is imbalanced. Moreover, this imbalanced and sparse data phenomenon remains ubiquitous across many AM monitoring schemes since training data is nontrivial to collect. Hence, we propose a machine learning approach to improve this dataset imbalance and enhance the prediction accuracy of pore-labeled data. Specifically, we investigate how data augmentation helps predict pores and non-pores better. This imbalance is improved using recent advances in data augmentation called Mixup, a weak-supervised learning method. Convolutional neural networks (CNNs) are trained on original and augmented datasets, and an appreciable increase in performance is reported when testing on five different experimental trials. When ML models are trained on original and augmented datasets, they achieve an accuracy of 95% and 99% on test datasets, respectively. We also provide information on how dataset size affects model performance. Lastly, we investigate the optimal Mixup parameters for augmentation in the context of CNN performance.

42 ENGINEERING↗

DOE OSTI2024

Deep learning with mixup augmentation for improved pore detection during additive manufacturing

36 MATERIALS SCIENCE↗