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At least 217 records · Page 12

Advancing Additive Manufacturing Through Artificial Intelligence–Powered, High-Throughput, Nondestructive Characterization and Process Optimization

This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and ZEISS Industrial Metrology has demonstrated the transformative potential of artificial intelligence (AI)-enabled x-ray computed tomography (XCT) to accelerate the qualification and certification of additively manufactured (AM) parts. At the core of this effort is Simurgh, an AI-powered XCT reconstruction framework jointly advanced by ORNL and ZEISS that integrates computer-aided design (CAD) models, physics-based simulations, and deep learning to overcome the long-standing challenges of metal artifact correction, long scan durations, and limited flaw detectability in dense and geometrically complex components. Simurgh enables high-throughput, high-quality 3D reconstruction from sparse and fast scans, which reduces XCT acquisition times by more than an order of magnitude and simultaneously improves defect detection limits by up to fourfold compared with industry-standard approaches. This capability reduces scan costs by more than 50%, lowers labor overhead, and makes XCT characterization economically viable for routine industrial use. By enabling reliable flaw detection in minutes rather than hours, Simurgh facilitates real-time feedback loops for process parameter optimization, which was highlighted in a recent npj Computational Materials (a Nature journal) issue. In the published study, more than 100 alloy coupons were characterized within a single day. This work represents a tenfold acceleration in the development of novel AM alloys and processes compared with conventional workflows. The ZEISS collaboration has also demonstrated the scalability of Simurgh to diverse application domains, including aerospace, nuclear, automotive, and biomedical components; in these applications, ensuring structural integrity is paramount. By drastically reducing barriers to XCT adoption, this partnership has laid the foundation for digital twins and data-driven certification pipelines and directly addressed bottlenecks in qualifying new materials and designs. Together, ORNL and ZEISS have shown that Simurgh advances the state of the art in nondestructive evaluation and aligns with the broader mission of enabling Industry 4.0 manufacturing ecosystems, in which intelligent, cost-effective, rapid quality assurance is integral to accelerating innovation and ensuring safety in critical applications.

36 MATERIALS SCIENCE↗

Advancing Additive Manufacturing Through Artificial Intelligence–Powered, High-Throughput, Nondestructive Characterization and Process Optimization

This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and ZEISS Industrial Metrology has demonstrated the transformative potential of artificial intelligence (AI)-enabled x-ray computed tomography (XCT) to accelerate the qualification and certification of additively manufactured (AM) parts. At the core of this effort is Simurgh, an AI-powered XCT reconstruction framework jointly advanced by ORNL and ZEISS that integrates computer-aided design (CAD) models, physics-based simulations, and deep learning to overcome the long-standing challenges of metal artifact correction, long scan durations, and limited flaw detectability in dense and geometrically complex components. Simurgh enables high-throughput, high-quality 3D reconstruction from sparse and fast scans, which reduces XCT acquisition times by more than an order of magnitude and simultaneously improves defect detection limits by up to fourfold compared with industry-standard approaches. This capability reduces scan costs by more than 50%, lowers labor overhead, and makes XCT characterization economically viable for routine industrial use. By enabling reliable flaw detection in minutes rather than hours, Simurgh facilitates real-time feedback loops for process parameter optimization, which was highlighted in a recent npj Computational Materials (a Nature journal) issue. In the published study, more than 100 alloy coupons were characterized within a single day. This work represents a tenfold acceleration in the development of novel AM alloys and processes compared with conventional workflows. The ZEISS collaboration has also demonstrated the scalability of Simurgh to diverse application domains, including aerospace, nuclear, automotive, and biomedical components; in these applications, ensuring structural integrity is paramount. By drastically reducing barriers to XCT adoption, this partnership has laid the foundation for digital twins and data-driven certification pipelines and directly addressed bottlenecks in qualifying new materials and designs. Together, ORNL and ZEISS have shown that Simurgh advances the state of the art in nondestructive evaluation and aligns with the broader mission of enabling Industry 4.0 manufacturing ecosystems, in which intelligent, cost-effective, rapid quality assurance is integral to accelerating innovation and ensuring safety in critical applications.

36 MATERIALS SCIENCE↗

Gas-Phase Composition as a Predictive Metric for Calendar Life Behavior of Next-Generation Silicon Anodes

The expansion of renewable technologies and electrification of the transportation sector is driving increased demand for next-generation battery materials that provide higher power and energy density with superior cycling and calendar life stability. Silicon (Si) has a theoretical capacity nearly 10x that of graphite, and is therefore a promising anode material candidate to meet these rigorous performance demands. While leading Si anode battery demonstrations are approaching target metrics for cycle life, a series of complex and interrelated modes of reactivity lead to reduced calendar life and therefore challenge practical adoption of these materials. Deconvoluting the degradation processes that impact Si calendar life is critical to informing the rational and accelerated design of improved Si materials. In the present work, we employ novel sampling techniques and GC-MS-FID characterization to measure gas-phase composition during initial Si cycling, which we tie to selective mechanisms of Si passivation. We utilize a tiered analysis approach to identify and quantify the gas-phase reaction products associated with three advanced Si material candidates under practical operating conditions. Ex situ analysis of Si powders (pure chemical reactivity) is coupled with nondestructive in situ sampling of Si electrodes in a practical pouch-cell format (coupled chemical and electrochemical reactivity). We link the observed gas-phase species evolution to electrochemical behavior and measured calendar life of the three Si materials. Further, we evaluate the voltage-resolved evolution of gas-phase species for one such Si nanomaterial, where nonmonotonic gas generation implies competition between passivating reaction pathways. The measured gas-phase compositional data serves as a critical input for our advanced electrochemical SEI models to identify favorable vs unfavorable reaction pathways to stabilize Si. In addition to bolstering a fundamental understanding of Si reactivity, the present approach informs specific and quantifiable gas-phase metrics tied to calendar life improvements in Si, which can streamline and accelerate the process of next-generation material development.

DIRECT ENERGY CONVERSION,ENERGY STORAGE↗

Noninvasive acoustic time-of-flight measurements in heated, hermetically-sealed high explosives using a convolutional neural network

In this work, we present a data-driven technique for measuring the time-of-flight through material sealed within a container. Time-of-flight measurement provides a noninvasive means of quantifying the sound speed profile within a material by transmitting an acoustic burst and then measuring the time required for the burst to arrive at an opposing receiver. In a hermetically-sealed cylindrical container, a portion of the acoustic energy propagates through the material as a bulk wave, while the remainder of the acoustic energy propagates around the container walls as guided waves. As a result, interference from the guided waves obscures the bulk arrival, inhibiting measurement of the sound speed. The technique uses a Convolutional Neural Network (CNN) to identify critical features in the measured waveforms and identify bulk wave arrivals. We demonstrate this time-of-flight measurement technique on high explosive-filled containers as they are heated from room temperature to detonation. This is a particularly challenging application for acoustic time-of-flight measurements as the high explosives have significant sound speed gradients as they undergo heating, and they lead to significant attenuation of the bulk wave, as opposed to the guided waves, which do not suffer significant attenuation. We characterize the performance of the CNN as a function of the high explosive temperature and as a function of the CNN hyperparameters. We then provide physical insight into the error trends.

47 OTHER INSTRUMENTATION↗

Nondestructive Characterization of Adhesive Bonds from Guided Wave Data

The critical role played by adhesive bonds in the fracture and failure of composites and other bonded materials is well known. A good knowledge of the mechanical properties of these adhesion joints is a prerequisite to reliable design and reliable prediction of the performance of these bonded structures.

moduli↗

Investigating Premature Ignition of Thruster Pressure Cartridges by Vibration-Induced Electrostatic Discharge

Pyrotechnic thruster pressure cartridges (TPCs) are used for aeroshell separation on a new NASA crew launch vehicle. Nondestructive evaluation (NDE) during TPC acceptance testing indicated that internal assemblies moved during shock and vibration testing due to an internal bond anomaly. This caused concerns that the launch environment might produce the same movement and release propellant grains that might be prematurely ignited through impact or through electrostatic discharge (ESD) as grains vibrated against internal surfaces. Since a new lot could not be fabricated in time, a determination had to be made as to whether the lot was acceptable to fly. This paper discusses the ESD evaluation and a separate paper addresses the impact problem. A challenge to straight forward assessment existed due to the unavailability of triboelectric data characterizing the static charging characteristics of the propellants within the TPC. The approach examined the physical limitations for charge buildup within the TPC system geometry and evaluated it for discharge under simulated vibrations used to qualify components for launch. A facsimile TPC was fabricated using SS 301 for the case and surrogate worst case materials for the propellants based on triboelectric data. System discharge behavior was evaluated by applying high voltage to the point of discharge in air and by placing worst case charge accumulations within the facsimile TPC and forcing discharge. The facsimile TPC contained simulated propellant grains and lycopodium, a well characterized indicator for static discharge in dust explosions, and was subjected to accelerations equivalent to the maximum accelerations possible during launch. The magnitude of charge generated within the facsimile TPC system was demonstrated to lie in a range of 100 to 10,000 times smaller than the spark energies measured to ignite propellant grains in industry standard discharge tests. The test apparatus, methodology, and results are described in this paper.

Woods, Stephen S.↗

Ultrasonic nondestructive evaluation of additively manufactured wear coatings

Here, this work pertains to the nondestructive evaluation of additively deposited coatings using ultrasound measurements. The specific objective was to evaluate using ultrasound surface wave measurements the quality of Stellite 21 coatings deposited on Inconel 718 substrates by the directed energy deposition (DED) additive manufacturing (AM) process. The surface wave speed and diffuse backscatter amplitude of the ultrasound waves were correlated with both cracking and warpage of the coating. This research is important, because, the integrity of DED-processed coatings currently requires a combination of destructive metallographic studies and X-ray computed tomography analysis, which are both expensive and time consuming. Instead of using a normal incidence configuration for the ultrasound measurements, the surface-wave approach allows the inspection of the near surface coating integrity. Three different frequencies were used to excite surface waves because each frequency has a different penetration depth. The signals obtained were used to quantify and compare the surface wave speed and surface wave-diffuse ultrasonic backscatter amplitude from five different DED-processed Stellite coated samples. Considering destructive metallurgical characterization as a reference, surface wave measurements were found to be effective for examining coating integrity. Further, the backscatter amplitude of the surface waves was correlated with the crack density and warpage. These flaws also change the stress state of the Stellite coating and consequently the surface wave propagation speed and its scattering behavior.

36 MATERIALS SCIENCE↗

Surface Characterization and Contamination

Nondestructive characterization of surface contamination can play an extremely important role in improving quality in manufacturing processes. This area of interest led to the formation of a Surface Contamination Analysis Team (SCAT) at Marshall Space Flight Center, which is primarily concerned with critical bondlines and has provided the major focus for activities under this grant. In addition, determining minute levels of contamination on emerging aerospace systems fabricated from composites has also been an area of interest for which the methods being presented here can be used. Important considerations for the inspection methodologies are good sensitivity, large area coverage, robustness, portability and ease of use for normal production personnel. In parallel with the evaluation of detection methods, considerable effort has been made to developing good, uniform contamination films to use as calibration standards. This activity within itself has presented unique challenges. The development of NIR methods for detecting and identifying contaminants has been in progress for several years. Cooperative efforts between the University, NASA, and Thiokol Corporation has shown some useful results for implementation in both laboratory and on-line procedures.

Workman, Gary L.↗

Robotic Assisted Non-Destructive Testing (NDT)

Mission Statement: Concrete wall characterization for structural integrity evaluation of H-Canyon exhaust tunnel using a remote controlled robotic arm with a NDT Concrete Instrument. Challenges: Rough and Curved Surfaces, Remote location. The UR5 is a collaborative robotic arm capable of: Payload: 11 lbs (5 kg), Reach: 33.5 in (850 mm), Footprint: 5.87 in (149 mm) diameter, Weight: 45.4 Ibs (20.6 kg). The force torque sensor reacts to a set value inputted by the user that can be utilized for sensitive products. This allows the UR5 to react to surfaces using the built-in function to search for a wall and orient itself normal to that plane. The Proceq Pundit 250 array is a nondestructive device that the user applies against a concrete wall and scans using ultrasonic transducers. The back wall and other defects can be show through the touchscreen. A fixture to hold the Proceq Pundit 250 array onto the UR5 robotic arm was designed and 3D printed. It includes openings for easy access to the buttons from the Pundit array as well as a reinforced structural design. The scan from the Pundit array can show the back-wall, rebars, and other defects to assist in determining the structural integrity. In order to scan, a program was made to search for the wall first. 1. The UR5 robotic arm will go to the desired location away from the wall. 2. It will then search for the wall by moving towards it slowly. 3. After contact, the force applied will slowly but steadily increase to a preset value inputted by the user. 4. The force torque sensor will use those values and communicate with the UR5 by adjusting the arm to become normal to the wall. 5. The arm will then apply force to push back the transducers on the Pundit array to avoid gaps. 6. It will then prompt the user to collect data and wait until finished. The UR5 teach pendant allows the user to program the robot to perform automated and repeatable tasks. It includes a free drive mode which allows the user to move the arm to a desired position by hand. The user can also apply restricted planes which include either stopped or slower motion to ensure safety. The concrete sample being tested includes rebars and different grades of surface roughness to understand the readings from the Proceq Pundit 250 array. Desired concrete samples are currently being fabricated that will simulate the terrain being tested.

3D PRINTING↗

NDE of advanced ceramics

Radiographic, ultrasonic, and scanning laser acoustic microscopy (SLAM) techniques were used to characterize silicon nitride and silicon carbide modulus-of-rupture test specimens in various stages of fabrication. Conventional and microfocus X-ray techniques were found capable of detecting minute high-density inclusions in as-received powders, green compacts, and fully densified specimens. Significant density gradients in sintered bars were observed by radiography, ultrasonic velocity, and SLAM. Ultrasonic attenuation was found sensitive to microstructural variations due to grain and void morphology and distribution. SLAM was capable also of detecting voids, inclusions, and cracks in finished test bars. Consideration is given to the potential for applying thermoacoustic microscopy techniques to green and densified ceramics. Some limitations and the detection probability statistics of the aforementioned nondestructive evaluation (NDE) processes are also discussed.

Klima, S. J.↗

Advanced quantitative magnetic nondestructive evaluation methods - Theory and experiment

The paper reviews the scale of fatigue crack phenomena in relation to the size detection capabilities of nondestructive evaluation methods. An assessment of several features of fatigue in relation to the inspection of ball and roller bearings suggested the use of magnetic methods; magnetic domain phenomena including the interaction of domains and inclusions, and the influence of stress and magnetic field on domains are discussed. Experimental results indicate that simplified calculations can be used to predict many features of these results; the data predicted by analytic models which use finite element computer analysis predictions do not agree with respect to certain features. Experimental analyses obtained on rod-type fatigue specimens which show experimental magnetic measurements in relation to the crack opening displacement and volume and crack depth should provide methods for improved crack characterization in relation to fracture mechanics and life prediction.

Barton, J. R.↗

Characterization of Ceramic Matrix Composite Combustor Components: Pre and Post Exposure

The pursuit of lower emissions and higher performance from gas turbine engines requires the development of innovative concepts and the use of advanced materials for key engine components. One key engine component is the combustor, where innovative design and material improvements have the potential to lower emissions. Efforts to develop a High Speed Civil Transport with low emissions were focused on the evaluation of combustor concepts with liners fabricated from a ceramic matrix composite of silicon carbide fibers in a silicon carbide matrix (SiC/SiC). The evaluation of SiC/SiC composites progressed from simple coupons (to establish a first-order database and identify operant failure mechanisms and damage accumulation processes), to feature-based subelements (to assess fabricability and in situ material response), to actual components (to assess structural integrity, dimensional, and compositional fidelity) tested under simulated engine conditions. As in the case of all evolutionary material and process work, a key element to resolving fabrication issues is the evaluation of witness areas taken from fabricated components before testing the actual component. The witness material from these components allowed microstructural and mechanical testing to be performed and compared to the ideal, flat panel, conditions and data that are typical of basic characterization. This also allowed samples of similar design to be taken from components after 115 hours of combustion exposure. Testing consisted of tensile, double notch shear, ring burst, and thermal conductivity that sampled various regions of the components. The evaluation of the witness material allowed an understanding of the fabrication process, highlighting critical issues, in an early phase of the learning curve development of these configuration and material unique parts. Residual property testing, after exposure, showed if degradation of the material under actual service conditions was occurring. This paper will present the results of this critical testing. Evaluations that consider the degree of complexity of the fabricated part were established to relate in situ performance to that of flat panel based coupons. Nondestructive evaluation was used throughout the evaluation process. These results will also be discussed as an aid in understanding the test results.

Ojard, G.↗

Early detection of fatigue damage in composite materials

Early detection of fatigue damage in composite materials by nondestructive inspection (NDI) techniques has been demonstrated for glass/epoxy, graphite/glass/epoxy, and graphite/epoxy composites. Modulus and temperature were monitored and a correlation between them observed. Axial modulus and torsional modulus changes were a function of the laminate orientation. Torsional modulus measurements and coin tap tests were performed at 0, 1 million, 5 million, and 10 million cycles, on axial fatigue specimens. Three distinct regions were noted. In the primary region a small but rapid change in stiffness was noted in the first few thousand cycles. This was followed by a secondary region of little or no stiffness change. The tertiary region was characterized by an increasing rate of stiffness change leading to fracture. NDI procedures including holographic interferometry, ultrasonics, penetrant, and X-ray radiography were evaluated for fatigue damage detection.

Salkind, M. J.↗

Local Guided Wavefield Analysis for Characterization of Delaminations in Composites

Delaminations in composite laminates resulting from impact events may be accompanied by minimal indication of damage at the surface. As such, inspection techniques are required to ensure defects are within allowable limits. Conventional ultrasonic scanning techniques have been shown to effectively characterize the size and depth of delaminations but require physical contact with the structure. Alternatively, a noncontact scanning laser vibrometer may be used to measure guided wave propagation in the laminate structure. A local Fourier domain analysis method is presented for processing guided wavefield data to estimate spatially-dependent wavenumber values, which can be used to determine delamination depth. The technique is applied to simulated wavefields and results are analyzed to determine limitations of the technique with regards to determining defect size and depth. Finally, experimental wavefield data obtained in quasi-isotropic carbon fiber reinforced polymer (CFRP) laminates with impact damage is analyzed and wavenumber is measured to an accuracy of 8.5% in the region of shallow delaminations. Keywords: Ultrasonic wavefield imaging, Windowed Fourier transforms, Guided waves, Structural health monitoring, Nondestructive evaluation

Rogge, Matthew D.↗

Structural analysis of an NDE-inspected carbon-carbon component

In this research, it is demonstrated that the integration of nondestructive evaluation with the finite element method (a quantitative NDE/FEM approach) can be used for analysis and behavior prediction of advanced materials, such as fiber composites, after processing and during in-service testing. First, stress, strain, and energy data were calculated by the finite element method for square plates with a 10 percent difference in the material properties between specified segments, i.e., between the center and the outside section or between two halves of the plate. This demonstrated the efficiency of the method in predicting variations in the structural behavior based on small material property differences. Then, finite element analyses and actual axial compression tests were performed on a Space Shuttle brake stator made from woven carbon-carbon composites. The material properties used in the numerical modeling of the stator were previously characterized at a large number of points on the component by quantitative NDE-procedures, i.e., ultrasonics and radiography. The results from the experimental compressive loading tests were used to verify the NDE/FEM results. Good agreement was found for most parameters.

Striz, A. G.↗

Vibration-Based Data Used to Detect Cracks in Rotating Disks

Rotor health monitoring and online damage detection are increasingly gaining the interest of aircraft engine manufacturers. This is primarily due to the fact that there is a necessity for improved safety during operation as well as a need for lower maintenance costs. Applied techniques for the damage detection and health monitoring of rotors are essential for engine safety, reliability, and life prediction. Recently, the United States set the ambitious goal of reducing the fatal accident rate for commercial aviation by 80 percent within 10 years. In turn, NASA, in collaboration with the Federal Aviation Administration, other Federal agencies, universities, and the airline and aircraft industries, responded by developing the Aviation Safety Program. This program provides research and technology products needed to help the aerospace industry achieve their aviation safety goal. The Nondestructive Evaluation (NDE) Group of the Optical Instrumentation Technology Branch at the NASA Glenn Research Center is currently developing propulsion-system-specific technologies to detect damage prior to catastrophe under the propulsion health management task. Currently, the NDE group is assessing the feasibility of utilizing real-time vibration data to detect cracks in turbine disks. The data are obtained from radial blade-tip clearance and shaft-clearance measurements made using capacitive or eddy-current probes. The concept is based on the fact that disk cracks distort the strain field within the component. This, in turn, causes a small deformation in the disk's geometry as well as a possible change in the system's center of mass. The geometric change and the center of mass shift can be indirectly characterized by monitoring the amplitude and phase of the first harmonic (i.e., the 1 component) of the vibration data. Spin pit experiments and full-scale engine tests have been conducted while monitoring for crack growth with this detection methodology. Even so, published data are extremely limited, and the basic foundation of the methodology has not been fully studied. The NDE group is working on developing this foundation on the basis of theoretical modeling as well as experimental data by using the newly constructed subscale spin system shown in the preceding photograph. This, in turn, involved designing an optimal sub-scale disk that was meant to represent a full-scale turbine disk; conducting finite element analyses of undamaged and damaged disks to define the disk's deformation and the resulting shift in center of mass; and creating a rotordynamic model of the complete disk and shaft assembly to confirm operation beyond the first critical concerning the subscale experimental setup. The finite element analysis data, defining the center of mass shift due to disk damage, are shown. As an example, the change in the center of mass for a disk spinning at 8000 rpm with a 0.963-in. notch was 1.3 x 10(exp -4) in. The actual vibration response of an undamaged disk as well as the theoretical response of a cracked disk is shown. Experiments with cracked disks are continuing, and new approaches for analyzing the captured vibration data are being developed to better detect damage in a rotor. In addition, the subscale spin system is being used to test the durability and sensitivity of new NDE sensors that focus on detecting localized damage. This is designed to supplement the global response of the crack-detection methodology described here.

Gyekenyesi, Andrew L.↗

Development and Characterization of the Bonding and Integration Technologies Needed for Fabricating Silicon Carbide Based Injector Components

Advanced ceramic bonding and integration technologies play a critical role in the fabrication and application of silicon carbide based components for a number of aerospace and ground based applications. One such application is a lean direct injector for a turbine engine to achieve low NOx emissions. Ceramic to ceramic diffusion bonding and ceramic to metal brazing technologies are being developed for this injector application. For the diffusion bonding technology, titanium interlayers (coatings and foils) were used to aid in the joining of silicon carbide (SiC) substrates. The influence of such variables as surface finish, interlayer thickness, and processing time were investigated. Electron microprobe analysis was used to identify the reaction formed phases. In the diffusion bonds, an intermediate phase, Ti5Si3Cx, formed that is thermally incompatible in its thermal expansion and caused thermal stresses and cracking during the processing cool-down. Thinner interlayers of pure titanium and/or longer processing times resulted in an optimized microstructure. Tensile tests on the joined materials resulted in strengths of 13-28 MPa depending on the SiC substrate material. Nondestructive evaluation using ultrasonic immersion showed well formed bonds. For the joining technology of brazing Kovar fuel tubes to silicon carbide, preliminary development of the joining approach has begun. Various technical issues and requirements for the injector application are addressed.

Halbig,Michael C.↗

NDE of ceramics and ceramic composites

Although nondestructive evaluation (NDE) techniques for ceramics are fairly well developed, they are difficult to apply in many cases for high probability detection of the minute flaws that can cause failure in monolithic ceramics. Conventional NDE techniques are available for monolithic and fiber reinforced ceramic matrix composites, but more exact quantitative techniques needed are still being investigated and developed. Needs range from flaw detection to below 100 micron levels in monolithic ceramics to global imaging of fiber architecture and matrix densification anomalies in ceramic composites. NDE techniques that will ultimately be applicable to production and quality control of ceramic structures are still emerging from the lab. Needs are different depending on the processing stage, fabrication method, and nature of the finished product. NDE techniques are being developed in concert with materials processing research where they can provide feedback information to processing development and quality improvement. NDE techniques also serve as research tools for materials characterization and for understanding failure processes, e.g., during thermomechanical testing.

Vary, Alex↗