Structural and mechanical effects of interstitial sinks
Structural changes in niobium base alloys induced by exposure to titanium interstitial sink at elevated temperature
TITANIUM↗
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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.
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The Effect of Nonuniform Temperature Distributions on the Stresses and Distortions of Stiffened-Shell Structures
The structural effects of nonuniform temperature distributions, such as those produced by aerodynamic heating or thermal ice-prevention systems, are discussed and found to be of two types: The introduction of thermal stresses and distortions as a result of restrained thermal expansion and a change in the stresses and distortions produced by the applied loads as a result of the variation of elastic properties of materials with temperature. These effects are illustrated by sample analyses of the stress and distortion distributions of simple box beams and by calculation of the stresses on a typical wing section.
ALUMINUM ALLOYS - ALCOA 75ST6 - ELASTICITY↗
Kuramoto synchronization of quantum tunneling polarons for describing the dynamic structure in cuprate superconductors
A major open topic in cuprates is the interplay between the lattice and electronic dynamics and the importance of their coupling to the mechanism of high-temperature superconductivity (HTSC). As evidenced by extended x-ray absorption fine structure (EXAFS) experiments, anharmonic structural effects are correlated with the charge dynamics and the transition to a superconducting phase in different HTSC compounds. Here, in this paper, we describe how structural anharmonic effects can be coupled to electronic and lattice dynamics in cuprate systems by performing the exact diagonalization of a prototype anharmonic many-body Hamiltonian on a relevant 6-atom cluster and show that the EXAFS results can be understood as a Kuramoto synchronization transition between coupled internal quantum tunneling of polarons associated with the two-site distribution of the copper–apical oxygen (Cu-O ap ) pair in the dynamic structure. The transition is driven by the anharmonicity of the lattice vibrations and promotes the pumping of charge, initially stored at the apical oxygen reservoirs, into the copper-oxide plane. Simultaneously, a finite projection of the internal quantum tunneling polaron extends to the copper–planar oxygen (Cu-O pl ) pair. All these findings allow an interpretation based on an effective quantum-mechanical triple-well potential associated with the oxygen sites of the 6-atom cluster, which accurately represents the phase synchronization of apical oxygens and lattice-assisted charge transfer to the CuO 2 plane.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Equivariant Graph Attention Network - 3D Conformers & Feature Fusion
EGAN-3F (Equivariant Graph Attention Network - 3D Conformers & Feature Fusion) presents an innovative approach for predicting binding affinity between small molecules and protein targets, a fundamental task in drug discovery. Traditional structure-based methods often depend on protein-ligand complex structures obtained from crystallography or molecular docking. In contrast, ligand-only machine learning models using 1D or 2D representations such as SMILES have been developed to predict binding affinity without structural information about the target; however, their accuracy is often limited due to the lack of 3D ligand information. EGAN-3F addresses this limitation by integrating spatially aware graph learning with traditional descriptor-based features. We systematically investigate how combining 2D and 3D molecular representations enhances binding affinity prediction from SMILES strings. This approach underscores the importance of modeling conformational diversity and incorporating chemically meaningful descriptors to improve predictive accuracy. The key innovation of EGAN-3F lies in its ability to achieve robust ligand-based binding affinity predictions without requiring protein-ligand complex structures, effectively bridging the gap between purely structural and ligand-only modeling paradigms.
Shim, Heesung [Lawrence Livermore National Laborat↗
Gravity and suspension effects on the dynamics of controlled structures
The effects of gravity on the actuators, sensors and structural plant of a controlled flexible structure are investigated. These influences include gravity stiffening, gravity induced deformations, gravity influence on inertial sensors and actuators, and the interaction with the suspension system. For each of the four influences, a simplified model is derived, from which the appropriate non-dimensional parameter can be identified, and the magnitude of the influence estimated. The construction of a detailed numerical model, which includes the four gravity influences, is outlined. This modeling procedure is then applied to a simplified model of the Middeck Active Control Eperiment (MACE). The influence on the poles and input-output transfer function is examined for several variations in the plant. The modeling procedure is also applied to the MACE experimental hardware. Experimental and model-based transfer functions are compared to demonstrate the significant improvement by incorporating gravity effects.
Rey, Daniel A.↗
The effects of the space environment on damping materials and damping designs on flexible structures
The effects of space environments on damping materials and damping designs on flexible structures were investigated. The following items were examined: damping of flexible spacecraft appendages; composite loss factor (n sub s) vs. time in high vacuum for damped test beams and damping of flexible structures. The STEP experiments show inherent damping of flexible structures in space effective possible damping design configurations for space structures, effects of passively damped components on the system loss factor of flexible structures and the effect of space environment on properties of damping materials.
Kluesener, M. F.↗
A parametric study of planform and aeroelastic effects on aerodynamic center, alpha- and q- stability derivatives. Appendix A: A computer program for calculating alpha- and q- stability derivatives and induced drag for thin elastic aeroplanes at subsonic and supersonic speeds
The computer program used to determine the rigid and elastic stability derivatives presented in the summary report is listed in this appendix along with instructions for its use, sample input data and answers. This program represents the airplane at subsonic and supersonic speeds as (a) thin surface(s) (without dihedral) composed of discrete panels of constant pressure according to the method of Woodward for the aerodynamic effects and slender beam(s) for the structural effects. Given a set of input data, the computer program calculates an aerodynamic influence coefficient matrix and a structural influence coefficient matrix.
Roskam, J.↗
Effect of substrate structure on deposition of evaporated carbon
Effect of substrate structure on deposition of evaporated carbon
Fischbach, D. B.↗
Radiation effects on composite structures Final report
Radiation and temperature effects on composite structures in Pegasus satellite
Source record↗
A Mono-cuboctahedral Series of Gold Nanoclusters: Photoluminescence Origin, Large Enhancement, Wide Tunability, and Structure–Property Correlation
The origin of the near-infrared photoluminescence (PL) from thiolate-protected gold nanoclusters (Au NCs, <2 nm) has long been controversial, and the exact mechanism for the enhancement of quantum yield (QY) in many works remains elusive. Meanwhile, based upon the sole steady-state PL analysis, it is still a major challenge for researchers to map out a definitive relationship between the atomic structure and the PL property and understand how the Au(0) kernel and Au(I)–S surface contribute to the PL of Au NCs. Herein, we provide a paradigm study to address the above critical issues. By using a correlated series of “mono-cuboctahedral kernel” Au NCs and combined analyses of steady-state, temperature-dependence, femtosecond transient absorption, and Stark spectroscopy measurements, we have explicitly mapped out a kernel-origin mechanism and clearly elucidate the surface–structure effect, which establishes a definitive atomic-level structure–emission relationship. A ~100-fold enhancement of QY is realized via suppression of two effects: (i) the ultrafast kernel relaxation and (ii) the surface vibrations. Furthermore the new insights into the PL origin, QY enhancement, wavelength tunability, and structure–property relationship constitute a major step toward the fundamental understanding and structural-tailoring-based modulation and enhancement of PL from Au NCs.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
Effects of ball milling on the structure of cotton cellulose
Cellulose is typically characterized as a mixture of crystalline and amorphous material. A large part of the general understanding of the chemical, biochemical and physical properties of cellulosic materials is thought to depend on the consequences of the ratio of these components. For example, amorphous materials are said to be more reactive and have less tensile strength but comprehensive understanding and definitive analysis remain elusive. Ball milling has been used for decades to increase the ratio of amorphous material. The present work used 13 techniques to follow the changes in cotton fibers (nearly pure cellulose) after ball milling for 15, 45 and 120 min. X-ray diffraction results were analyzed with the Rietveld method; DNP (dynamic nuclear polarization) natural abundance 2D NMR studies in the next paper in this issue assisted with the interpretation of the 1D analyses in the present work. A conventional NMR model’s paracrystalline and inaccessible crystallite surfaces were not needed in the model used for the DNP studies. Sum frequency generation (SFG) spectroscopy also showed profound changes as the cellulose was decrystallized. Optical microscopy and field emission-scanning electron microscopy results showed the changes in particle size; molecular weight and carbonyl group analyses by gel permeation chromatography confirmed chemical changes. Specific surface areas and pore sizes increased. Fourier transform infrared (FTIR) and Raman spectroscopy also indicated progressive changes; some proposed indicators of crystallinity for FTIR were not in good agreement with our results. Thermogravimetric analysis results indicated progressive increase in initial moisture content and some loss in stability. Although understanding of structural changes as cellulose is amorphized by ball milling is increased by this work, continued effort is needed to improve agreement between the synchrotron and laboratory X-ray methods used herein and to provide physical interpretation of the SFG results.
59 BASIC BIOLOGICAL SCIENCES↗
The middeck active control experiment: Gravity and suspension effects
Viewgraphs on the Middeck Active Control Experiment (MACE): Gravity and Suspension Effects are presented. Topics covered include: gravity and suspension influences; gravity and suspension effects on structure; gravity effects on sensors and actuators; modeling of gravity and suspension effects on structure; geometric stiffness theory and initial static deformation calculation; modeling gravity's effect on accelerometers and PMA's; application to MACE; MACE EM configuration study; and MACE DM configuration study.
Crawley, Edward F.↗
Technology integration box beam failure study
Composite structures have the potential to be cost effective, structurally efficient primary aircraft structures. As part of the Advanced Composite Technology (ACT) program to exploit this potential for heavily loaded aircraft structures, the design and fabrication of the technology integration box beam (TIBB) was completed. The TIBB is an advanced composite prototype structure for the center wing section of the Lockheed C-130 aircraft. The TIBB was tested for downbending, upbending, torsion, and combined upbending and torsion load conditions to verify the design. The TIBB failed at 83 percent of design ultimate load for the combined upbending and torsion load condition. Current analytical and experimental results are described for a study of the mechanisms that led to the failure of the TIBB. Experimental results include load, strain, and deflection data. An analytical study was conducted of the TIBB structural response. Analytical results include strain and deflection results from a global analysis of the TIBB.
Shuart, Mark J.↗
A Cloud Hydrology and Albedo Synthesis Mission (CHASM)
This slide presentation reviews the Cloud Hydrology and Albedo Synthesis Mission (CHASM). The interaction of clouds with radiation and the hydrological cycle represents a huge uncertainty in our understanding of climate science and the modeling of climate system feedbacks. Despite the recognized need for a unified treatment of cloud processes, the present global average values of remotely sensed cloud liquid water and theoretically accepted values used for cloud physics and precipitation modeling differ by an order of magnitude. This is due in part to sampling and saturation effects, as well as to threedimensional cloud structure effects. In recent work with the Multiangle Imaging SpectroRadiometer (MISR) on Terra, we have gained new insights as to how the remote sensing approach could be significantly improved using a new instrument that combines passive optical (visible and near infrared) and microwave measurements, both as pushbroom scanners with multiple viewing angles, to the degree that measurements of liquid water path over deep convective clouds over land also become possible. This instrument would also have the ability of measuring height-resolved cloud-tracked winds using a hyper stereo retrieval technique. Deployment into a precessing low earth orbit would be optimal for measuring diurnal cloud activity. We have explored an instrument design concept for this that looks promising if we can establish partnerships that provide launch and bus capabilities.
hydrology↗
Wildfire Segmentation From Remotely Sensed Data Using Quantum-Compatible Conditional Vector Quantized-Variational Autoencoders
Wildfires represent a critical environmental hazard with multifaceted implications for ecosystems, communities, and public health [1]. The escalating frequency and intensity of wildfires globally have intensified the urgency for robust segmentation methodologies to facilitate effective mitigation, response, and recovery strategies [2]. Accurate wildfire segmentation is pivotal for delineating fire boundaries, assessing progression patterns, and prioritizing resource allocation during emergency scenarios. Furthermore, precise segmentation enables stakeholders, including policymakers, environmental scientists, and emergency responders, to formulate evidence-based strategies, thereby minimizing socio-economic disruptions and ecological degradation. Consequently, advancing wildfire segmentation techniques through innovative technological interventions remains a paramount research imperative. Although foundational in wildfire segmentation, traditional deterministic models exhibit inherent limitations that compromise their efficacy in dynamic and uncertain environments. These models often operate on rigid algorithms prioritizing deterministic classifications, thereby overlooking the inherent complexities and uncertainties associated with wildfire behavior and satellite data variability. Such deterministic frameworks tend to produce oversimplified representations that fail to capture the intricate nuances of evolving fire dynamics, spatial heterogeneity, and environmental interactions [1]. Consequently, the deterministic approach’s propensity for uncertainty collapsing [1, 3] hampers the accuracy, reliability, and applicability of segmentation outcomes in real-world scenarios. Contrastingly, stochastic models offer a more nuanced and adaptable framework for wildfire segmentation. By integrating probabilistic elements into the modeling paradigm, stochastic approaches, particularly probabilistic approaches such as variational auto encoders (VAEs) [4], facilitate comprehensive uncertainty assessment, enabling researchers to quantify and incorporate uncertainties into segmentation outcomes effectively. This probabilistic nature empowers stochastic models to encapsulate variability, account for data inconsistencies, and adapt to evolving environmental conditions, enhancing segmentation accuracy, reliability, and robustness. Embracing stochastic methodologies thus catalyzes advancements in wildfire science by fostering a more holistic, adaptive, and resilient segmentation framework. Despite VAEs demonstrating significant promise in various applications, they come with inherent limitations that have garnered attention within the machine learning community. One of the primary drawbacks lies in their reliance on static priors, which essentially assume a fixed distribution for latent variables, thereby limiting the model’s flexibility to capture complex data structures effectively [5]. This static nature leads to suboptimal representations, especially when dealing with complex and high-dimensional data. Additionally, VAEs often struggle with generating sharp and realistic samples, a phenomenon commonly referred to as mode collapse [5, 7, 6]. Furthermore, the optimization process in VAEs, which involves balancing the reconstruction loss and the regularization term, can sometimes be challenging to fine-tune [7]. In recent efforts to address these shortcomings, alternative approaches like Vector Quantized Variational Auto encoders(VQ-VAEs) [7], address the challenges by incorporating discrete latent variables and leveraging techniques that enhance the quality and diversity of generated samples while maintaining efficient training dynamics. VQ-VAEs propose a dynamic prior distribution generation mechanism that diverges from the static priors commonly associated with traditional VAEs. This dynamic approach allows for more adaptive and context-aware latent variable representations, thereby potentially capturing complex data structures more effectively. Unlike autoregressive prior models such as PixelCNN, which, despite their ability to model dependencies across data dimensions, suffer from significant computational inefficiencies and lack flexibility in handling diverse datasets. In our work, we propose to use a generative quantum-compatible approach to help alleviate the shortcomings of autoregressive prior model in VQ-VAEs. Restricted Boltzmann Machines (RBMs) are a viable alternative prior model that can learn prior distributions in a faster and more flexible manner. In this research endeavor, we meticulously curate a state-of-the-art dataset leveraging satellite MODIS data in conjunction with VIIRS fire masks, derived from Fire Radiative Power (FRP), thereby encapsulating diverse wildfire scenarios and environmental contexts. We developed a conditional VQ-VAE architecture with the RBM prior model that is trained in a supervised manner for segmenting wildfire masks. This innovative approach synergistically harnesses deep learning capabilities, enabling the generation of segmentation maps characterized by heightened precision, granularity, and contextual relevance. Furthermore, replacing the autoregressive prior learning method proposed by the original VQ-VAE with a prior density approximation via quantum-compatible RBM facilitates expedited inference processes, augments flexibility in prior sampling, optimizes computational efficiency and establishes a groundbreaking benchmark in wildfire segmentation methodologies.
quantum machine learning↗
Turbulence effects on flame speed and flame structure
Turbulence effects on methane-air flames stabilized in grid turbulence were investigated through measurements of flame speed and mean and fluctuating flame temperature profiles. Published turbulent flame speed correlations were able to correlate the experimental flame speed data but were contradictory in indicating flame structure and combustion mechanisms. A simple, one-dimensional, wrinkled laminar flame model was used to predict characteristic flame temperature fluctuation levels. Comparison of these predictions with measured temperature fluctuations indicated that the majority of the flames studied were wrinkled laminar flames. However, a wrinkled laminar flame structure was inappropriate for the most intensely turbulent flames examined.
Smith, K. O.↗
Integrated Propulsion/Vehicle System Structurally Optimized
Ongoing research and testing are essential in the development of air-breathing hypersonic propulsion technology, and this year some positive advancement was made at the NASA Glenn Research Center. Recent work performed for GTX, a rocket-based combined-cycle, single-stage-to-orbit concept, included structural assessments of both the engine and flight vehicle. In the development of air-breathing engine technology, it is impractical to design and optimize components apart from the fully integrated system because tradeoffs must be made between performance and structural capability. Efforts were made to control the flight trajectory, for example, to minimize the aerodynamic heating effects. Structural optimization was applied to evaluate concept feasibility and was instrumental in the determination of the gross liftoff weight of the integrated system. Achieving low Earth orbit with even a small payload requires an aggressive approach to weight minimization through the use of lightweight, oxidation-resistant composite materials. Assessing the integrated system involved investigating the flight trajectory to determine where the critical load events occur in flight and then generating the corresponding environment at each of these events. Structural evaluation requires the mapping of the critical flight loads to finite element models, including the combined effects of aerodynamic, inertial, combustion, and other loads. NASA s APAS code was used to generate aerodynamic pressure and temperature profiles at each critical event. The radiation equilibrium surface temperatures from APAS were used to predict temperatures through the thickness. Heat transfer solutions using NASA's MINIVER code and the SINDA code (Cullimore & Ring Technologies, Littleton, CO) were calculated at selective points external to the integrated vehicle system and then extrapolated over the entire exposed surface. FORTRAN codes were written to expedite the finite element mapping of the aerodynamic heating effects for the internal structure.
Hunter, James E.↗
High Electron Mobility SiGe/Si Transistor Structures on Sapphire Substrates
SiGe/Si n-type modulation doped field effect structures and transistors (n-MODFETs) have been fabricated on r-plane sapphire substrates. The structures were deposited using molecular beam epitaxy, and antimony dopants were incorporated via a delta doping process. Secondary ion mass spectroscopy (SIMS) indicates that the peak antimony, concentration was approximately 4 x 10(exp19) per cubic cm. The electron mobility was over 1,200 and 13,000 sq cm/V-sec at room temperature and 0.25 K, respectively. At these two temperatures, the electron carrier densities were 1.6 and 1.33 x 10(exp 12) per sq cm, thus demonstrating that carrier confinement was excellent. Shubnikov-de Haas oscillations were observed at 0.25 K, thus confirming the two-dimensional nature of the carriers. Transistors, with gate lengths varying from 1 micron to 5 microns, were fabricated using these structures and dc characterization was performed at room temperature. The saturated drain current region extended over a wide source-to-drain voltage (V(sub DS)) range, with (V(sub DS)) knee voltages of approximately 0.5 V and increased leakage starting at voltages slightly higher than 4 V.
Alterovitz, Samuel A.↗