Search NASA⌕ Search

SEARCH · Search NASA

Results for “Ultrasound materials processing”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

78 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

New developments in structure-property and amorphous materials research at the upgraded 16-BM-B Paris-Edinburgh press station at HPCAT

Beamline 16-BM-B of the High-Pressure Collaborative Access Team (HPCAT) at the Advanced Photon Source (APS) provides a Paris-Edinburgh press program to probe the structure and properties of crystalline and amorphous materials up to 12 GPa at room temperature or 7 GPa at 2000°C. During the recent APS upgrade, 16-BM-B undertook major improvements to its instrumentation and measurement techniques. The upgrade includes the addition of a 1.2 m horizontal “condenser” mirror and a new variable-sized collimation system, the combination of which decreases the acquisition time for energy dispersive X-ray diffraction measurements by a factor of 10 when compared to pre-upgrade measurements. The addition of a new Ge energy-sensitive detector and DANTE (XGLab) digital pulse processor allows for processing the increased diffraction counts with minimal deadtime. In addition to upgraded beamline components, new techniques are being developed for eventual release to the user community, including electrical resistivity and tomography measurements.

APS upgrade↗
DOE OSTI2021

Evaluation of thermal processing and properties of 422 martensitic stainless steel for replacement of 4140 steel in diesel engine pistons

The thermal and mechanical properties of martensitic stainless steel 422 were evaluated for suitability as a drop-in replacement for 4140 steel in next generation heavy-duty diesel engine (HDDE) pistons. The time and temperature of the austenitization and tempering steps were studied to achieve optimum materials performance in piston applications, including the balance of thermal and mechanical properties and resistance to long-term thermal aging. Reducing the tempering temperature from 700 to 600 °C caused a substantial increase in elevated temperature strength from 25 to 600 °C, but had no significant influence on thermal conductivity, suggesting that thermal conductivity in 422 is dominated largely by composition and distribution of alloying elements and mostly independent of the sub-grain structure size and precipitate size. Compared to the current HDDE piston alloy 4140, 422 exhibits substantially higher elevated temperature strength and lower thermal conductivity, the latter which will cause 422 to operate at higher temperatures in pistons, possibly requiring a piston redesign to take advantage of the improved high temperature strength of 422. Piston material selection and alloy design strategies with potential to mitigate some of the shortcomings of martensitic stainless steels, such as 422, as drop-in replacements are discussed.

36 MATERIALS SCIENCE↗
NASA NTRS2000

Hardware Development Process for Human Research Facility Applications

The simple goal of the Human Research Facility (HRF) is to conduct human research experiments on the International Space Station (ISS) astronauts during long-duration missions. This is accomplished by providing integration and operation of the necessary hardware and software capabilities. A typical hardware development flow consists of five stages: functional inputs and requirements definition, market research, design life cycle through hardware delivery, crew training, and mission support. The purpose of this presentation is to guide the audience through the early hardware development process: requirement definition through selecting a development path. Specific HRF equipment is used to illustrate the hardware development paths. The source of hardware requirements is the science community and HRF program. The HRF Science Working Group, consisting of SCientists from various medical disciplines, defined a basic set of equipment with functional requirements. This established the performance requirements of the hardware. HRF program requirements focus on making the hardware safe and operational in a space environment. This includes structural, thermal, human factors, and material requirements. Science and HRF program requirements are defined in a hardware requirements document which includes verification methods. Once the hardware is fabricated, requirements are verified by inspection, test, analysis, or demonstration. All data is compiled and reviewed to certify the hardware for flight. Obviously, the basis for all hardware development activities is requirement definition. Full and complete requirement definition is ideal prior to initiating the hardware development. However, this is generally not the case, but the hardware team typically has functional inputs as a guide. The first step is for engineers to conduct market research based on the functional inputs provided by scientists. CommerCially available products are evaluated against the science requirements as well as modifications needed to meet program requirements. Options are consolidated and the hardware development team reaches a hardware development decision point. Within budget and schedule constraints, the team must decide whether or not to complete the hardware as an in-house, subcontract with vendor, or commercial-off-the-shelf (COTS) development. An in-house development indicates NASA personnel or a contractor builds the hardware at a NASA site. A subcontract development is completed off-site by a commercial company. A COTS item is a vendor product available by ordering a specific part number. The team evaluates the pros and cons of each development path. For example, in-bouse developments utilize existing corporate knowledge regarding bow to build equipment for use in space. However, technical expertise would be required to fully understand the medical equipment capabilities, such as for an ultrasound system. It may require additional time and funding to gain the expertise that commercially exists. The major benefit of subcontracting a hardware development is the product is delivered as an end-item and commercial expertise is utilized. On the other hand, NASA has limited control over schedule delays. The final option of COTS or modified COTS equipment is a compromise between in-house and subcontracts. A vendor product may exist that meets all functional requirements but req uires in-house modifications for successful operation in a space environment. The HRF utilizes equipment developed using all of the paths described: inhouse, subcontract, and modified COTS.

Bauer, Liz↗
DOE OSTI2021

Automating Bayesian inference and design to quantify acoustic particle levitation

Self-propulsion of micro- and nanoparticles powered by ultrasound provides an attractive strategy for the remote manipulation of colloidal matter using biocompatible energy inputs. Quantitative understanding of particle motion and its dependence on size, shape, and composition requires accurate characterization of the acoustic field, which depends sensitively on the experimental setup. Here, we show how automated experiments based on Bayesian inference and design can accurately and efficiently characterize the acoustic field within resonant chambers used to propel acoustic nanomotors. Repeated cycles of observation, inference, and design (OID) are guided by a physical model that describes the rate at which levitating particles approach the nodal plane. Using video microscopy, we observe the relaxation of tracer particles to this plane following the application of the acoustic field. We use sequential Monte Carlo methods to infer model parameters such as the amplitude and frequency of the resonant chamber while accounting for particle-level measurement noise and population-level heterogeneity in the field. Guided by simulated outcomes, we select the optimal design for the next experiment as to maximize the information gain in the relevant parameters. We show how this iterative process serves to discriminate between competing hypotheses and efficiently converges to accurate parameter estimates using only few automated experiments. We discuss the need for model criticism to ensure the validity of the guiding model throughout automated cycles of observation, inference, and design. Furthermore, this work demonstrates how Bayesian methods can learn the parameters of nonlinear, hierarchical models used to describe video microscopy data of active colloids.

42 ENGINEERING↗
NASA NTRS2025

Improving Adhesive Bondline Time of Flight Predictions During Autoclave Cure Utilizing Machine Learning

Composite materials are increasingly being used in aerospace applications due to their superior strength-to-weight ratio compared to commonly used metals. A current limitation to widespread adoption is the certification of adhesively bonded joints. One approach to improving adhesive bonding in composites is accurately measuring the thickness of adhesive bondlines in composite laminates. Precise bondline thickness control is essential for aerospace applications where adhesive layer thickness directly affects joint fracture properties and structural performance. This study focused on implementing machine learning techniques to determine the ultrasonic time of flight (directly correlated to thickness) in adhesive bondlines throughout autoclave cure cycles. A high-temperature (use up to 180°C) ultrasonic scanning system was deployed in an autoclave to provide time of flight data through composite panels. Three experiments were conducted on the curing of 305 mm × 305 mm unidirectional composite panels. In the first experiment, a piecewise function was fit for the temperature correction factor to account for changing autoclave temperatures. Due to deficiencies in the first calibration experiment, a second experiment was run, and the results were used to train a machine learning model. The revised experiment, in combination with the machine learning model, significantly increased the accuracy of the bondline time of flight predictions (~14% error reduced to <1%). Data was processed using the Regression Learner Application in MATLAB®, with a Support Vector Machine selected for the model. The result was a machine learning algorithm capable of reliably quantifying ultrasonic time of flight through adhesive bondlines. The third experiment provided independent test data for the machine learning model, demonstrating that the model produces accurate predictions from data beyond its training set.

Machine Learning↗
DOE OSTI2021

In situ monitoring of microstructure evolution during thermal processing of uranium-zirconium alloys using laser-generated ultrasound

In this study, laser-generated ultrasound was used to monitor microstructure evolution during thermal processing of as-cast, polycrystalline binary uranium-zirconium metallic fuel alloys with compositions of U-20wt.%Zr (U-20Zr), U-50wt.%Zr (U-50Zr) and U-80wt.%Zr (U-80Zr). Ultrasonic waveforms were recorded during heating and cooling the samples from room temperature to >973 K and back. A phase transition temperature for all three compositions was estimated from the temperature at which an abrupt and rapid reduction in ultrasonic velocities was observed. Microstructural features on the length scale of tens of micrometers were inferred from the observation of scattering of ultrasonic waves by elastic heterogeneities above ~823 K in U-20Zr, while a hysteresis in the ultrasonic velocities of U-80Zr upon cooling was attributed to a partial retention of the high temperature phase following thermal annealing. The U-50Zr alloy exhibited a reversible viscoelastic response above 933 K, as evidenced by the observation of high frequency attenuation of the shear component of the waveforms at high temperature. Ultrasonic measurements were supplemented by in situ transmission electron microscopy (TEM). The TEM images revealed that the δ-U-Zr matrix in the three compositions underwent a spinodal decomposition above ~823 K into nanoscale regions. The ultrasonic measurements revealed larger, micron-scale structure evolution in the U-20Zr alloy at the same temperature. This large-scale structure is associated with heterogeneous regions having different Zr content. Our findings show the potential heating rate dependence of microstructural evolution in U-Zr alloys and highlight differences in the thermomechanical response and associated length scales during thermal annealing between single- and dual-phase compositions. These results demonstrate the utility of laser ultrasonics to rapidly and efficiently scan phase boundaries and monitor micrometer-scale structure evolution in metallic fuel alloys.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗