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At least 883 records · Page 49

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Ultrasonic Elastography for Nondestructive Evaluation of Dissimilar Material Joints

Dissimilar material joints or multilayered metals have become inevitable in the manufacturing industry due to the increasing demand for multifunctional materials with variable mechanical, thermal, or electrical characteristics in a single assembly. Lattice mismatch of materials at the interface of dissimilar materials leads to inferior mechanical characteristics. In particular, the mismatch in elastic properties indicated by a large initial elastic deformation is critical to determine the extent of variation in stress. However, nanoindentation, the most common and accepted technique to measure elastic modulus, is destructive, time-consuming, and can only examine mechanical properties within a limited area. A non-invasive elastographic mapping technique evaluates the mechanical properties using ultrasonic elastography to study incompressibility. The dissimilar joint between steel and copper was obtained via friction stir welding. The variation of the stress developed at the welded joint of the two different metals was evaluated from the dynamic bulk modulus map. A tensile test of the involved workpiece confirmed a good agreement with our analysis based on the dynamic bulk modulus elastographic mapping results. This study provides a rapid and non-invasive technique for the bulk metallurgic elastic modulus inspection to overcome the limitations of conventional methods.

Jin, Yuqi↗

NASA NTRS1993

Investigation of Mars Rotational Dynamics Using Earth-based Radio Tracking of Mars Landers

The development of space geodetic techniques over the past two decades has made it possible to measure the rotational dynamics of the Earth at the milliarcsecond level, improving our geophysical models of the Earth 's interior and the interactions between the solid Earth and its atmosphere. We have found that the rotational dynamics of Mars can be determined to nearly the same level of accuracy by acquiring Earth-based two-way radio tracking observations of three or more landers globally distributed on the surface of Mars. Our results indicate that the precession and long-term obliquity changes of the Mars pole direction can be determined to an angular accuracy corresponding to about 15 cm/yr at the planet's surface. In addition, periodic nutations of the pole and seasonal variations in the spin rate of the planet can be determined to 10 cm or less. Measuring the rotation of Mars at this accuracy would greatly improve the determination of the planet' s moment of inertia and would resolve the size of a planetary fluid core, providing a valuable constraint on Mars interior models. Detecting seasonal variations in the spin rate of Mars would provide global constraints on atmospheric angular momentum changes due to sublimation of the Mars CO2 polar ice caps. Finally, observation of quasisecular changes in Mars obliquity would have significant implications for understanding long-term climatic change. The key to achieving these accuracies is a globally distributed network of Mars landers with stable, phase-coherent radio transponders. By simultaneously acquiring coherent two-way carrier phase observations between a single Earth tracking station and multiple Mars landers, Earth media errors are essentially eliminated, providing an extremely sensitive measure of changes in the differential path lengths between the Earth tracking station and the Mars landers due to Mars rotation. Time variability of the instrumental phase delay through the radio transponder may represent the limiting error source for this technique. Calibration of the transponder stability to about 0.1 ns or less, over a single tracking arc of up to 12 hr, is sufficient to provide the decimeter-level determination of Mars orientation parameters quoted above. We will provide a detailed description of the multilander tracking technique and the requirements it imposes on both the lander radio system and the Earth-based ground-tracking system. This concept is currently part of the strawman science plan for the Mars Environmental Survey (MESUR) mission and complements many of the other MESUR science goals.

Edwards, C. D., Jr.↗

NASA NTRS2003

High Pressure X-Ray Diffraction Studies on Nanocrystalline Materials

Application of in situ high pressure powder diffraction technique for examination of specific structural properties of nanocrystals based on the experimental data of SiC nanocrystalline powders of 2 to 30 nrn diameter in diameter is presented. Limitations and capabilities of the experimental techniques themselves and methods of diffraction data elaboration applied to nanocrystals with very small dimensions (< 30 nm) are discussed. It is shown that due to the complex structure, constituting a two-phase, core/surface shell system, no unique lattice parameter value and, consequently, no unique compressibility coefficient can satisfactorily describe the behavior of nanocrystalline powders under pressure. We offer a tentative interpretation of the distribution of macro- and micro-strains in nanoparticles of different grain size.

Palosz, B.↗

DOE OSTI2024

A Third Harmonic Voltage Injection Technique to Improve The Power Transmission Capacity

To facilitate the growing deployment of renewable energy sources and increasing load demand, it is imperative to increase the power transmission capacity of the existing transmission corridors. The available power uprating techniques are either costly, or require significant alteration to the existing system. Moreover, most of these techniques are suitable for long transmission lines. In light of these limitations, a third harmonic voltage injection based power uprating technique is proposed in this article. The proposed technique is economic, immune to line impedance unbalance, and is applicable for any length of transmission line. Most importantly, the technique needs very minimal modification in the existing system at the substation level. The efficacy of the proposed technique is validated through simulation and experiments.

Das, Anubrata↗

NASA NTRS1990

Functional requirements for an intelligent RPC

An intelligent remote power controller (RPC) based on microcomputer technology can implement advanced functions for the accurate and secure detection of all types of faults on a spaceborne electrical distribution system. The intelligent RPC will implement conventional protection functions such as overcurrent, under-voltage, and ground fault protection. Advanced functions for the detection of soft faults, which cannot presently be detected, can also be implemented. Adaptive overcurrent protection changes overcurrent settings based on connected load. Incipient and high-impedance fault detection provides early detection of arcing conditions to prevent fires, and to clear and reconfigure circuits before soft faults progress to a hard-fault condition. Power electronics techniques can be used to implement fault current limiting to prevent voltage dips during hard faults. It is concluded that these techniques will enhance the overall safety and reliability of the distribution system.

Aucoin, B. M.↗

NASA NTRS1980

Surface temperatures and glassy state investigations in tribology, part 3

Research related to the development of the limiting shear stress rheological model is reported. Techniques were developed for subjecting lubricants to isothermal compression in order to obtain relevant determinations of the limiting shear stress and elastic shear modulus. The isothermal compression limiting shear stress was found to predict very well the maximum traction for a given lubricant. Small amounts of side slip and twist incorporated in the model were shown to have great influence on the rising portion of the traction curve at low slide-roll ratio. The shear rheological model was also applied to a Grubin-like elastohydrodynamic inlet analysis for predicting film thicknesses when employing the limiting shear stress model material behavior.

Bair, S.↗

NASA NTRS2016

Synthetic Astrobiology

Synthetic biology - the design and construction of new biological parts and systems and the redesign of existing ones for useful purposes - has the potential to transform fields from pharmaceuticals to fuels. Our lab has focused on the potential of synthetic biology to revolutionize all three major parts of astrobiology: Where do we come from? Where are we going? and Are we alone? For the first and third, synthetic biology is allowing us to answer whether the evolutionary narrative that has played out on planet earth is likely to have been unique or universal. For example, in our lab we are re-evolving the biosynthetic pathways of amino acids in order to understand potential capabilities of an early organism with a limited repertoire of amino acids and developing techniques for the recovery of metals from spent electronics on other planetary bodies. And what about the limits for life? Can we create organisms that expand the envelope for life? In the future synthetic biology will play an increasing role in human activities both on earth, in fields as diverse as human health and the industrial production of novel bio-composites. Beyond earth, we will rely increasingly on biologically-provided life support, as we have throughout our evolutionary history. In order to do this, the field will build on two of the great contributions of astrobiology: studies of the origin of life and life in extreme environments.

synthetic biology↗

NASA NTRS2016

Where Synthetic Biology Meets ET

life in extreme environments↗

DOE OSTI2024

Toward Ultra‐High‐Quality‐Factor Wireless Masing Magnetic Resonance Sensing

It has recently been shown that a bolus of hyperpolarized nuclear spins can yield stimulated emission signals similar in nature to maser signals, potentially enabling new ways of sensing hyperpolarized contrast media, including most notably [1- 13 C]pyruvate that is under evaluation in over 50 clinical trials for metabolic imaging of cancer. The stimulated NMR signal emissions lasting for minutes do not require radio-frequency excitation, offering unprecedented advantages compared to conventional MR sensing. However, creating nuclear spin maser emission is challenging in practice due to stringent fundamental requirements, making practical in vivo applications hardly possible using conventional passive MR detectors. Here, in this study, we demonstrate the utility of a wireless NMR maser detector, the quality factor of which was enhanced 22-fold (to 1,670) via parametric pumping. This active-feedback technique breaks the intrinsic fundamental limit of NMR detector circuit quality factor. We show the use of parametric pumping to reduce the threshold requirement for inducing nuclear spin masing at 300 MHz resonance frequency in a preclinical MRI scanner. Indeed, stimulated emission from hyperpolarized protons was obtained under highly unfavorable conditions of low magnetic field homogeneity (T 2 * of 3 ms). Greater gains of the quality factor of the MR detector (up to 1 million) were also demonstrated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Applicability of 1D site response analysis to shallow sedimentary basins: A critical evaluation through physics-based 3D ground motion simulations

One-dimensional site response analysis (1D SRA) remains the standard practice in considering the effect of local soil deposits and predicting site-specific ground motions, although its range of applicability to realistic seismic wavefields is still in question. In this 1D approach, horizontal and vertical ground shaking are assumed to be induced by vertically propagating shear and compressional waves, respectively. A recent study based on analytical two-dimensional (2D) plane waves and simple point source earthquake simulations has shown two mechanistic limitations in this 1D modelling technique for general inclined seismic waves, that is, systematic over-prediction of the vertical motion and wave trapping in the 1D soil column. In this article, we evaluate in detail the applicability of this 1D modelling approach to realistic three-dimensional (3D) simulated seismic wavefields in shallow sedimentary basins. Linear-viscoelastic 1D SRA predictions using two types of input motions that are commonly used in practice—rock outcrop and in-column motions, are compared with the reference true site response results from 3D earthquake simulations in terms of various measures in the frequency and time domain. It is shown that the horizontal motion in the 3D seismic wavefield exhibits dominant shear wave propagation phenomenon, while the vertical motion is a combined effect of compressional and shear waves and can be over-predicted by the 1D approach when the incident seismic waves are inclined. Direct evidence of the wave refraction process that leads to the vertical motion over-prediction is provided. 1D SRA with in-column inputs can yield motions that have significantly longer duration compared to the true 3D site response solution due to trapped waves, casting in doubt the frequent need for increased soil damping in existing site studies to compensate for wave attenuation due to scattering alone. Sensitivity investigation on the increase of soil profile damping by a multiplier D mul shows D mul values compatible with those found in the literature for both horizontal and vertical motions. It is shown that the level of D mul optimized for a best match of the spectral acceleration is dependent on the characteristic of the input motion and a larger D mul is typically required for the vertical component. In contrast, 1D SRA with outcrop motions predicts motions with shorter significant duration due to its inability to capture the basin-edge generated surface waves. A suite of ground motion simulations was performed to assess the sensitivity of the observations to the basin geologic structure including the velocity gradient, rock-basin impedance contrast and basin depth. The analysis results show that the accuracy of the simplified 1D procedure is dependent on the wavefield composition of both the input motions and the true 3D site response solution. While the horizontal motions in shallow sedimentary basins can, to the first order, be reasonably captured by the simplified 1D approach, 1D SRA for the vertical component is in general not reliable and contributions from inclined shear waves should be accounted for in site-specific evaluation of the vertical design ground motion.

1D assumption↗

DOE OSTI2023

Depth profiling and standardization from the back side of a sample for accurate analyses: Emphasis on quantifying low‐fluence, shallow implants in diamond‐like carbon

Rationale Back‐side thinning of wafers is used to eliminate issues with transient sputtering when analyzing near‐surface element distributions. Precise and accurate calibrated implants are created by including a standard reference material during the implantation. Combining these methods allows accurate analysis of low‐fluence, shallow features even if matrix effects are a concern. Methods Implanted Na (<2.0 × 10 11 ions/cm 2 , peaking <50 nm) in diamond‐like carbon (DLC) film on silicon (solar wind returned by NASA's Genesis mission) was prepared for measurement as follows. Implanted surfaces of samples were epoxied to wafers and back‐side‐thinned using physical or chemical methods. Thinned samples were then implanted with reference ions for accurate quantification of the solar wind implant. Analyses used a CAMECA IMS 7f‐GEO SIMS in depth‐profiling mode. Results Back‐side‐implanted reference ions reduced the need to change sample mounts or stage position and could be spatially separated from the solar wind implant even when measuring monoisotopic ions. Matrix effects in DLC were mitigated and the need to find an identical piece of DLC for a reference implant was eliminated. Accuracy was only limited by the back‐side technique itself. Conclusions Combining back‐side depth profiling with back‐side‐implanted internal standards aides quantification of shallow mono‐ and polyisotopic implants. This technique helps mitigate matrix effects and keeps measurement conditions consistent. Depth profile acquisition times are longer, but if sample matrices are homogeneous, procedural changes can decrease measurement times.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Going off topics to demix quark and gluon jets in α S extractions

Quantum chromodynamics is the theory of the strong interaction between quarks and gluons; the coupling strength of the interaction, α S , is the least precisely-known of all interactions in nature. An extraction of the strong coupling from the radiation pattern within jets would provide a complementary approach to conventional extractions from jet production rates and hadronic event shapes, and would be a key achievement of jet substructure at the Large Hadron Collider (LHC). Presently, the relative fraction of quark and gluon jets in a sample is the limiting factor in such extractions, as this fraction is degenerate with the value of αS for the most well-understood observables. To overcome this limitation, we apply recently proposed techniques to statistically demix multiple mixtures of jets and obtain purified quark and gluon distributions based on an operational definiton. We illustrate that studying quark and gluon jet substructure separately can significantly improve the sensitivity of such extractions of the strong coupling. We also discuss how using machine learning techniques or infrared- and collinear-unsafe information can improve the demixing performance without the loss of theoretical control. While theoretical research is required to connect the extract topics with the quark and gluon objects in cross section calculations, our study illustrates the potential of demixing to reduce the dominant uncertainty for the α S extraction from jet substructure at the LHC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

Deep learning for time series forecasting: a survey of recent advances

Time series forecasting plays a critical role in numerous real-world applications, such as finance, healthcare, transportation, and scientific computing. In recent years, deep learning has become a powerful tool for modeling complex temporal patterns and improving forecasting accuracy. This survey provides an overview of recent deep learning approaches for time series forecasting, involving various architectures including RNNs, CNNs, GNNs, transformers, large language models, MLP-based models, and diffusion models. We first identify key challenges in the field, such as temporal dependency, efficiency, and cross-variable dependency, which drive the development of forecasting techniques. Then, the general advantages and limitations of each architecture are discussed to contextualize their adaptation in time series forecasting. Furthermore, we highlight promising design trends like multi-scale modeling, decomposition, and frequency-domain techniques, which are shaping the future of the field. This paper serves as a compact reference for researchers and practitioners seeking to understand the current landscape and future trajectory of deep learning in time series forecasting.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Audacity of huge: overcoming challenges of data scarcity and data quality for machine learning in computational materials discovery

Machine learning (ML)-accelerated discovery requires large amounts of high-fidelity data to reveal predictive structure–property relationships. For many properties of interest in materials discovery, the challenging nature and high cost of data generation has resulted in a data landscape that is both scarcely populated and of dubious quality. Data-driven techniques starting to overcome these limitations include the use of consensus across functionals in density functional theory, the development of new functionals or accelerated electronic structure theories, and the detection of where computationally demanding methods are most necessary. When properties cannot be reliably simulated, large experimental data sets can be used to train ML models. In the absence of manual curation, increasingly sophisticated natural language processing and automated image analysis are making it possible to learn structure–property relationships from the literature. Finally, models trained on these data sets will improve as they incorporate community feedback.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Temporally continuous thermofluidic–thermomechanical modeling framework for metal additive manufacturing

Additive manufacturing (AM) is known to generate large magnitudes of residual stresses (RS) within builds due to steep and localized thermal gradients. In the current state of commercial AM technology, manufacturers generally perform heat treatments in effort to reduce the generated RS and its detrimental effects on part distortion and in-service failure. Computational models that effectively simulate the deposition process can provide valuable insights to improve RS distributions. Accordingly, it is common to employ Computational fluid dynamics (CFD) models or finite element (FE) models. While CFD can predict geometric and thermal-fluid behavior, it cannot predict the structural response (e.g., stress–strain) behavior. On the other hand, an FE model can predict mechanical behavior, but it lacks the ability to predict geometric and fluid behavior. Thus, an effectively integrated thermofluidic–thermomechanical modeling framework that exploits the benefits of both techniques while avoiding their respective limitations can offer valuable predictive capability for AM processes. In contrast to previously published efforts, the work herein describes a one-way coupled CFD-FEA framework that abandons major simplifying assumptions, such as geometric steady-state conditions, the absence of material plasticity, and the lack of detailed RS evolution/accumulation during deposition, as well as insufficient validation of results. Here, the presented framework is demonstrated for a directed energy deposition (DED) process, and experiments are performed to validate the predicted geometry and RS profile. Both single- and double-layer stainless steel 316L builds are considered. Geometric data is acquired via 3D optical surface scans and X-ray micro-computed tomography, and residual stress is measured using neutron diffraction (ND). Comparisons between the simulations and measurements reveal that the described CFD-FEA framework is effective in capturing the coupled thermomechanical and thermofluidic behaviors of the DED process. The methodology presented is extensible to other metal AM processes, including power bed fusion and wire-feed-based AM.

42 ENGINEERING↗

DOE OSTI2022

INTERFACES. A Program for Determining the 3D Structures of Surfaces Sites Using NMR Data

Dynamic nuclear polarization surface enhanced NMR spectroscopy has enabled the determination of high-resolution structures from surface-supported molecules, including singlesite heterogeneous catalysts. Structure determinations have largely mimicked the approaches used in biomolecular NMR spectroscopy, namely, using distance measurements to constrain a conformational search. These early demonstrations made use of purpose-built software, which has limited the adoption of the technique. Herein, we describe the open-source program INTERFACES (Interpret NMR to Elucidate or Reconstruct the Full Atomistic Configurations of External Surfaces) which automates the analysis of RE(SP)DOR data as well as the structure determination for surface sites. Distances, angles, dihedral angles, complex orientation, and distance from the support can all be sampled to find all structures that agree with the experimental data. A χ 2 metric is used to define the error ranges of the REDOR fits and produce structures with an arbitrary level of confidence. Structural solutions are then provided as both overlays and ORTEP-like probability ellipsoids.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

The carbon challenge: Design, synthesis, and chemisorption behavior of solid sorbents in direct air capture of carbon dioxide

Direct air capture (DAC) of CO 2 is a promising solution for reducing the carbon footprint through "negative emission" technology. However, the low CO 2 concentration (~400 ppm) and the dynamic nature of DAC processes present challenges in designing effective sorbent systems. Recent advancements in material design and structural engineering have led to the development of high-performance solid sorbents, offering a more stable, safe, and energy-efficient alternative to traditional liquid CO 2 capture methods. This review highlights progress in solid sorbent-based DAC, focusing on amine-modified materials, hydrogen-bonded frameworks, and ionic liquid-engineered scaffolds. The discussion covers design principles, synthesis methodologies, and their impact on CO 2 chemisorption, comparing the advantages and limitations of each approach. Characterization techniques, especially operando methods and computational tools, are reviewed to understand sorbent behavior during CO 2 integration and release. The reaction pathways and interaction mechanisms of these sorbents with CO 2 are analyzed to guide future design. Additionally, the CO 2 chemisorption behaviors, including capacity, sorption kinetics, recyclability, and durability in the presence of gaseous impurities and under humid conditions will be evaluated and compared. Further, the review offers unique insights into the physical properties, chemical structures, and surface engineering effects of these sorbents, based on comprehensive characterization and evaluation techniques.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Quantification of manganese for ChemCam Mars and laboratory spectra using a multivariate model

In this work, we report a new calibration model for manganese using the laser-induced breakdown spectroscopy instrument that is part of the ChemCam instrument suite onboard the NASA Curiosity rover. The model has been trained using an expanded set of 523 manganese-bearing rock, mineral, metal ore, and synthetic standards. The optimal calibration model uses the Partial Least Squares (PLS) and Least Absolute Shrinkage and Selection Operator (LASSO) multivariate techniques, with a novel “double blending” technique. We determined the detection limit for manganese is 82 ppm using a method blank procedure and is possibly as low as 27 ppm based on visual inspection of the spectra. Based on a representative test set consisting of measurements on 93 standards, the double blended multivariate model shows a Root Mean Squared Error of Prediction (RMSEP) accuracy of 1.39 wt% MnO for the full blended model. Employing a local RMSEP estimate where the model performance is evaluated based on nearby test samples, the accuracy is 0.03 wt% at the quantification limit (0.05 wt% MnO), 0.4 wt% accuracy at 1.0 wt% MnO, and 4.4 wt% accuracy at 100 wt% MnO. Precision is estimated using the standard deviation of the test set measurements, and is ±0.01 wt% MnO at the quantification limit, ±0.09 wt% MnO at 1.0 wt% MnO, and ± 2.1 wt% MnO at 100 wt% MnO (all 1 standard deviation). This new calibration is important for understanding the variation of manganese in the bedrock with the Curiosity rover on Mars, which provides insight into past redox conditions on Mars.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗