Results for “feature importance analysis” — Page 6

NASA NTRS2019

Annual and Semiannual Oscillations of Thermospheric Composition in TIMED/GUVI Limb Measurements

The Global UltraViolet Imager (GUVI) onboard the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite provides a data set of vertical thermospheric composition (O, N2, and O2 densities) and temperature profiles from 2002–2007. Even though GUVI sampling is limited by orbital constraint, we demonstrated that the GUVI data set can be used to derive the altitude profiles of the amplitudes and phases of annual oscillation (AO) and semiannual oscillation (SAO), thereby providing important constraints on models seeking to explain these features. We performed a seasonal and interannual analysis of GUVI limb O, O2, and N2 densities and volume number density ratio O/N2 at constant pressure levels. These daytime observations of O and O/N2 in the lower thermosphere show a strong AO at midlatitudes and a clear SAO at lower latitudes. The global mean GUVI O/N2 number density ratio shows the AO, with slightly larger values in January than in July and a SAO with O/N2 greater during equinoxes than at the solstices. O and N2 densities on fixed pressure levels in the upper thermosphere are anticorrelated with solar extreme ultraviolet flux. On the other hand, O/N2 is smaller during solar minimum and larger during solar maximum. The thermospheric AO and SAO in composition have a constant phase with altitude throughout the thermosphere.

thermosphere composition↗

NASA NTRS1978

NASTRAN analysis of a wheel-rail loading on its foundation

One type of azimuth bearing for a large ground antenna (100 m) will consist of steel wheels, mounted at four corners of the alidade, rolling on a circular flat rail which provides the vertical restraints; a radial constraining bearing at the center of the alidade provides the horizontal restraints. One important design feature is the compressive stresses in the grout or concrete foundation under the wheel-rail load. A finite element analysis check was made of a particular design that consists of a steel rail resting on a concrete foundation. Symmetry was assumed as much as possible in order to minimize the models, but meaningful element sizes were used. Recently developed isoparametric hexahedron elements available in the NASTRAN computing program, which minimizes the number of elements required while maintaining the accuracy of the computed stresses, were used with two versions of NASTRAN. Test cases to check with the analytical solutions were made. A side loading was also applied to calculate the increase in the concrete stresses.

Katow, M. S.↗

NASA NTRS1992

Optimizing tuning masses for helicopter rotor blade vibration reduction including computed airloads and comparison with test data

The development and validation of an optimization procedure to systematically place tuning masses along a rotor blade span to minimize vibratory loads are described. The masses and their corresponding locations are the design variables that are manipulated to reduce the harmonics of hub shear for a four-bladed rotor system without adding a large mass penalty. The procedure incorporates a comprehensive helicopter analysis to calculate the airloads. Predicting changes in airloads due to changes in design variables is an important feature of this research. The procedure was applied to a one-sixth, Mach-scaled rotor blade model to place three masses and then again to place six masses. In both cases the added mass was able to achieve significant reductions in the hub shear. In addition, the procedure was applied to place a single mass of fixed value on a blade model to reduce the hub shear for three flight conditions. The analytical results were compared to experimental data from a wind tunnel test performed in the Langley Transonic Dynamics Tunnel. The correlation of the mass location was good and the trend of the mass location with respect to flight speed was predicted fairly well. However, it was noted that the analysis was not entirely successful at predicting the absolute magnitudes of the fixed system loads.

Pritchard, Jocelyn I.↗

DOE OSTI2025

Design of diverse, functional mitochondrial targeting sequences across eukaryotic organisms using variational autoencoder

Mitochondria play a key role in energy production and metabolism, making them a promising target for metabolic engineering and disease treatment. However, despite the known influence of passenger proteins on localization efficiency, only a few protein-localization tags have been characterized for mitochondrial targeting. To address this limitation, we leverage a Variational Autoencoder to design novel mitochondrial targeting sequences. In silico analysis reveals that a high fraction of the generated peptides (90.14%) are functional and possess features important for mitochondrial targeting. We characterize artificial peptides in four eukaryotic organisms and, as a proof-of-concept, demonstrate their utility in increasing 3-hydroxypropionic acid titers through pathway compartmentalization and improving 5-aminolevulinate synthase delivery by 1.62-fold and 4.76-fold, respectively. Moreover, we employ latent space interpolation to shed light on the evolutionary origins of dual-targeting sequences. Overall, our work demonstrates the potential of generative artificial intelligence for both fundamental research and practical applications in mitochondrial biology.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Scalable Computation of Topological Abstractions for Scalar Data

Topological data analysis has become an important tool for large scale scalar data analysis and visualization, efficiently extracting the inherent structure and features of interest of the data. However, with growing dataset sizes and complexity, it is increasingly becoming infeasible to compute topological abstractions of interest in serial and on single machines. This paper presents the state of the art in the scalable computation of topological abstractions on scalar data, in shared memory parallel on single machines, and in distributed memory parallel on multiple machines. We highlight results for set‐based, graph‐based and complex‐based abstractions and organize the state of the art based on this taxonomy. The paper identifies parallelization and distribution techniques common in topological algorithms and highlights further areas of interest with underdeveloped efforts.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Unlocking Scholarly Insights: Leveraging Machine Learning Approaches for Citation Analysis and Intent Classification

Publicly funded organizations, notably institutions like the Los Alamos National Laboratory (LANL), are deeply vested in acquiring robust productivity metrics to gauge the entirety of their research output. Motivated by the imperative to enhance institutional productivity assessment, this study investigates the utilization of Large Language Models (LLM) such as BERT-based models, as well as local LLaMa-30b-instruct and Mixtral-8x7b-instruct architectures for classifying type of URL referenced resources in academic papers such as software, dataset, as well as authorship intent. Challenges in discerning resource types from context are highlighted, along with the potential of BERT and LLMs to address these challenges. Through comprehensive analysis, this research unveils a notable surge in documents featuring URL citations, indicative of the escalating importance of digital resources in scholarly publications. Moreover, citations to datasets and software demonstrate consistent growth over time, underscoring their increasing significance. Our findings also reveal that LANL authors contribute substantially to accessible science, comprising about 10% of dataset and software mentions in LANL

Large Language Models, BERT, citation classificati↗

DOE OSTI2024

Data for "Design of Diverse, Functional Mitochondrial Targeting Sequences Across Eukaryotic Organisms Using Variational Autoencoder"

Mitochondria play a key role in energy production and metabolism, making them a promising target for metabolic engineering and disease treatment. However, despite the known influence of passenger proteins on localization efficiency, only a few protein-localization tags have been characterized for mitochondrial targeting. To address this limitation, we leverage a Variational Autoencoder to design novel mitochondrial targeting sequences. In silico analysis reveals that a high fraction of the generated peptides (90.14%) are functional and possess features important for mitochondrial targeting. We characterize artificial peptides in four eukaryotic organisms and, as a proof-of-concept, demonstrate their utility in increasing 3-hydroxypropionic acid titers through pathway compartmentalization and improving 5-aminolevulinate synthase delivery by 1.62-fold and 4.76-fold, respectively. Moreover, we employ latent space interpolation to shed light on the evolutionary origins of dual-targeting sequences. Overall, our work demonstrates the potential of generative artificial intelligence for both fundamental research and practical applications in mitochondrial biology.

AI/ML↗

NASA NTRS1981

A navigation model for the Venusian atmosphere

A static, exponential atmosphere model for Venus has been developed using period change data from the Pioneer Venus spacecraft. The model was derived from approximately 600 passages of the spacecraft through the upper Venusian atmosphere, or almost three full circulations of the planet. The model reflects several important, known atmospheric features (diurnal bulge, layering, etc.) and confirms several observations of a more sophisticated analysis. Several new phenomena were observed and successfully modeled.

Birkeland, P. W.↗

NASA NTRS1983

The Influence of Sensor and Flight Parameters on Texture in Radar Images

Texture is known to be important in the analysis of radar images for geologic applications. It was previously shown that texture features derived from the grey-level co-occurrence matrix (GLCM) can be used to separate large scale texture in radar images. The influence of sensor parameters, specifically the spatial and radiometric resolution and flight parameters, i.e., the orientation of the surface structure relative to the sensor, on the ability to classify texture based on the GLCM features is investigated. It was found that changing these sensor and flight parameters greatly affects the usefulness of the GLCM for classifying texture on radar images.

Frost, V. S.↗

NASA NTRS1991

Nighttime reactive nitrogen measurements from stratospheric infrared thermal emission observations

IR thermal emission spectra of the earth's atmosphere in the 700-2000/cm region were obtained with a cryogenically cooled high-resolution interferometer spectrometer on a balloon flight from Palestine, Texas, on September 15-16, 1986. The observations exhibit spectral features of a number of stratospheric constituents, including important species of the reactive nitrogen family. An analysis of the observed data for simultaneously measured vertical distributions of O3, H2O, N2O, NO2, N2O5, HNO3, and ClONO2 is presented. These measurements permit the first direct determination of the nighttime total reactive nitrogen concentrations, and the partitioning of the important elements of the NO(x) family. Comparisons of the total reactive nitrogen budget are made with the measurements by the ATMOS experiment and with the predictions of one-dimensional and two-dimensional photochemical models.

Abbas, Mian M.↗

DOE OSTI2025

Fundamental Insights into Cathode Stability: Linking Compositional Tuning and Local Coordination in Complex Metal Oxides under Aqueous Transformations

Compositional tuning of complex metal oxides in Li-ion battery materials influences their performance as well as their end-of-life behavior, in particular, the tendency to release toxic metal cations in aqueous solution. We modeled ternary variants of a parent LiCoO 2 delafossite structure by varying the metal identity and relative amounts. This yielded ten model formulations of Li(A 4/6 B 1/6 C 1/6 )O 2 , where the material is enriched with the A metal and doped with B and C, with Ni, Mn, Co, Fe, Al, V, and Ti as constituent metals. To assess their stability in aqueous conditions, metal release energetics were calculated using a combination of Density Functional Theory calculations and thermodynamics. Metal release in ternary oxides is dictated by subtle variations in the coordination environment of the leaving group. To identify governing chemical features across diverse compositions with varying local coordination environments, we leverage random forest regression and descriptor importance analysis. A key result is that metal–oxygen orbital hybridization, quantified using a projected density-of-states-derived descriptor, H d/p , provides a physically grounded measure of interaction strength that governs metal release energetics. This refined perspective goes beyond conventional oxidation state considerations and offers more robust insights for materials science. Finally, we model defect surface-bound O 2 dimer formation as a proxy for reactive oxygen species (ROS) generation. The results show that Ni-rich compositions more readily stabilize spin-polarized O 2 dimers, corroborating experimental reports of an increased ROS-driven biological response. In conclusion, our results establish a compositional and electronic basis for metal release and surface oxygen reactivity that form a rationale for complex metal oxide design principles.

36 MATERIALS SCIENCE↗

NASA NTRS1983

The influence of sensor and flight parameters on texture in radar images

Texture is known to be important in the analysis of radar images for geologic applications. It has previously been shown that texture features derived from the grey level co-occurrence matrix (GLCM) can be used to separate large scale texture in radar images. Here the influence of sensor parameters, specifically the spatial and radiometric resolution and flight parameters, i.e., the orientation of the surface structure relative to the sensor, on the ability to classify texture based on the GLCM features is investigated. It was found that changing these sensor and flight parameters greatly affects the usefulness of the GLCM for classifying texture on radar images.

Frost, V. S.↗

NASA NTRS1984

The influence of sensor and flight parameters on texture in radar images

Texture is known to be important in the analysis of radar images for geologic applications. It has previously been shown that texture features derived from the grey level co-occurrence matrix (GLCM) can be used to separate large scale texture in radar images. Here the influence of sensor parameters, specifically the spatial and radiometric resolution and flight parameters, i.e., the orientation of the surface structure relative to the sensor, on the ability to classify texture based on the GLCM features is investigated. It was found that changing these sensor and flight parameters greatly affects the usefulness of the GLCM for classifying texture on radar images.

Frost, V. S.↗

NASA NTRS1988

Modal analysis applied to circular, rectangular, and coaxial waveguides

Recent developments in the analysis of various waveguide components and feedhorns using Modal Analysis (Mode Matching Method) are summarized. A brief description of the theory is presented, and the important features of the method are pointed out. Specific examples in circular, rectangular, and coaxial waveguides are included, with comparisons between the theory and experimental measurements. Extensions to the methods are described.

Hoppe, D. J.↗

NASA NTRS1988

Dynamic structural correlation via nonlinear programming techniques

A solution to the correlation between structural dynamic test results and finite element analyses of the same components is presented in this paper. Basically, the method can be categorized as a Levenberg-Marquardt type Gauss-Newton method which requires only the differences between FE modal analyses and test results and their first derivatives with respect to preassigned design variables. With proper variable normalization and equation scaling, the method has been made numerically better-conditioned and the inclusion of the Levenberg-Marquardt technique overcomes any remaining difficulty encountered in inverting singular or near-singular matrices. An important feature is that each iteration requires only one function evaluation along with the associated design sensitivity analysis and so the procedure is computationally efficient.

Ting, T.↗

NASA NTRS2018

High Efficiency Megawatt Motor Conceptual Design

The High Efficiency Megawatt Motor (HEMM) is being designed to meet the needs of Electrified Aircraft Propulsion (EAP). The key objective of this work is to establish a motor technology which simultaneously attains high specific power (>16kW/kg ratio to electromagnetic weight) and high efficiency (>98%) by judicious application of high temperature superconducting wire and integrated thermal management. Another important feature is to achieve the performance goals with an eye to aircraft integration constraints. An electromagnetic analysis was performed which shows that the proposed HEMM design meets the performance objectives if key current capability and mechanical constraints are achieved. Sensitivity of motor power and performance to those parameters is illustrated. The HEMM technology could be applied to a range of aircraft types that require megawatt level electrical power.

Superconducting↗

NASA NTRS2019

High Efficiency Megawatt Motor Preliminary Design

The High Efficiency Megawatt Motor (HEMM) is being designed to meet the needs of Electrified Aircraft Propulsion (EAP). A preliminary design has been completed and risk reduction activities are being conducted in three key areas: cryogenic cooler design, superconducting rotor coil design and manufacturing, and stator thermal management. The key objective of HEMM is to establish a motor technology which simultaneously attains high specific power (>16kW/kg ratio to electromagnetic weight) and high efficiency (>98%) by judicious application of high temperature superconducting wire and integrated thermal management. Another important feature is to achieve the performance goals with an eye to aircraft integration constraints. An electromagnetic analysis was performed which shows that the proposed HEMM design meets the performance objectives if key current capability and mechanical constraints are achieved. The risk reduction activities are the first assessment of the key design features. The HEMM technology could be applied to a range of aircraft types that require megawatt level electrical power.

Jansen, Ralph H.↗

NASA NTRS2018

High Efficiency Megawatt Motor Conceptual Design

The High Efficiency Megawatt Motor (HEMM) is being designed to meet the needs of Electrified Aircraft Propulsion (EAP). The key objective of this work is to establish a motor technology which simultaneously attains high specific power (>16kW/kg ratio to electromagnetic weight) and high efficiency (>98%) by judicious application of high temperature superconducting wire and integrated thermal management. Another important feature is to achieve the performance goals with an eye to aircraft integration constraints. An electromagnetic analysis was performed which shows that the proposed HEMM design meets the performance objectives if key current capability and mechanical constraints are achieved. Sensitivity of motor power and performance to those parameters is illustrated. The HEMM technology could be applied to a range of aircraft types that require megawatt level electrical power.

Jansen, Ralph H.↗