Search NASA⌕ Search

SEARCH · Search NASA

Results for “multimode”

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.

At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Auna: A Geospatial System for Assessing Equity in Multimodal Mobility

Traditionally, new modes of transportation in the United States have benefited upper social classes at the expense of underrepresented and lower socioeconomic classes. Several recent studies in transportation have explored this disparity, and research has highlighted factors that contribute to transportation equity. In this effort, we will examine this previous work as it applies to the broader, current transportation system. Based on findings, we propose Auna, a tool to better visualize spatial data, including social injustice, ground and air mobility data.

GIS↗
NASA NTRS2026

Proactive Wildfire Management: A Remote Sensing and Multimodal CNN-MLP Architecture for Ignition Risk Forecasting

As the frequency and intensity of wildfires increase, with fire seasons now starting earlier and ending later than they have over the past decades, current monitoring systems, such as lookout towers and satellites, are hindered by cloud cover, low-resolution imagery, and static data gaps that fail to track vegetation moisture levels fast enough to catch rapid pre-ignition changes. This report proposes a Machine Learning-enabled Wildfire Ignition Prediction framework that combines satellite monitoring with dynamic and high-resolution remote sensing from Unmanned Aerial Vehicle (UAV) swarms. The method would use multispectral and thermal data from the Landsat program to create a baseline for vegetation health, calculating a two-band Enhanced Vegetation Index (EVI2) and the moisture content of the vegetation. These inputs will later be fused with microscale UAV weather data, including thermal hotspots found through thick canopies, hyperspectral chemical signatures of pre-visual combustion, and local weather streams. The multispectral satellite, multispectral Light Detection and Ranging (LiDAR), and thermal data would then be processed through a Convolutional Neural Network (CNN), alongside a Multilayer Perceptron (MLP) for the micro-weather telemetry. The outputs of these networks would be fused into a single feature representation and passed through a final prediction network to generate real-time ignition risk scores and hotspot alerts. Model performance would be assessed using standard classification metrics, including a Receiver Operating Characteristic - Area Under the Curve (ROC AUC) and F1 score. This system would allow first responders to identify high-risk zones and intervene before ignition occurs, improving emergency response time compared to current approaches.

machine learning↗
DOE OSTI2024

Evaluating the Use of Foundational Chemical Language Models in Multimodal Graph Fusion

Rapid and accurate prediction of the physicochemical properties of molecules given their structures remains a key challenge in cheminformatics. Machine learning approaches offer high-throughput options, but the optimality of inductive biases and data representations are up for debate. For example, BERT-based masked language models (MLMs) can be trained in a self-supervised way on hundreds of millions to billions of readily available SMILES strings. Another option is graph neural networks (GNNs), which can operate directly on molecular structures. Yet, generating accurate molecular geometry is computationally expensive, leading to a relative scarcity in data compared to SMILES strings. It is attractive to combine these two paradigms by pre-training an LM on a large corpus of SMILES strings and embedding these representation into a geometric graph neural network. Despite the promise of such an approach, and contrary to previous studies, we find mixed results with the combination of the LMs and GNNs on several molecule datasets. In particular, we found evidence for improvement on the FreeSolv and QM7 benchmarks, but degraded performance on the ESOL, LIPO and QM9 datasets compared to a GNN baseline.

Francel, Collin [University of Alabama]↗
DOE OSTI2024

Correlative multimodal chemical imaging via machine learning

Machine learning approach can combine mass spectral imaging (MSI) techniques, one with low spatial resolution but intact molecular spectra and the other with nanometer spatial resolution but fragmented molecular signatures, to predict molecular MSI spectra with submicron spatial resolution. The machine learning approach can perform transformations on the spectral image data of the two MSI techniques to reduce dimensionality, and using a correlation technique, find relationships between the transformed spectral image data. The determined relationships can be used to generate MSI spectra of desired resolution.

Ovchinnikova, Olga S.↗
DOE OSTI2026

CRCNS21 Computational Models of Multisensory Integration by Upper Limb in Humanoids and Amputees

This international collaborative research project between Johns Hopkins University (JHU) and the Technical University of Munich (TUM) investigated how the human brain processes and integrates multiple types of sensory information, such as touch and force, with the goal of improving prosthetic limbs for amputees and advancing sensory capabilities in humanoid robots. The research advanced our understanding of how the brain responds to sensory feedback in upper-limb amputees. Through experiments in which amputees received electrical stimulation while performing phantom hand movements, we demonstrated that sensory feedback activates the cortical sensorimotor and multisensory regions, and that these regions communicate dynamically during stimulation. Experiments with intact-limb participants explored the integration of visual, haptic, and force feedback, as well as in virtual reality motor training, further showing how the brain processes multimodal sensory information. In addition, this research inspired work on examining the reliability of where amputees perceive sensations over time, which contributed to a successful doctoral fellowship for continued investigation. Our collaborators at TUM improved multimodal sensor technology combining tactile and thermal feedback for humanoid robots, demonstrating the feasibility of integrating multiple sensor types into a unified system for detecting and responding to environmental stimuli. The experimental methods and analysis techniques developed across both teams, including functional network analysis and multimodal sensor integration, provide a foundation for future research in prosthetics and robotics. This research benefits the public by generating knowledge about how amputees process restored sensory information. Advances in humanoid sensing contribute to safer human-robot interaction. The project also fostered international collaboration and cross-disciplinary training: one TUM doctoral student spent a summer at JHU working on multimodal sensor integration, while two JHU students traveled to TUM to host workshops on neuromorphic sensory encoding and sensory integration.

42 ENGINEERING↗
NASA NTRS1980

Multi-mode horn antenna simulation

Radiation patterns were computed for a circular multimode horn antenna using waveguide electric field radiation expressions. The circular multimode horn was considered as a possible reflector feed antenna for the Large Antenna Multifrequency Microwave Radiometer (LAMMR). This horn antenna uses a summation of the TE sub 11 deg and TM sub 11 deg modes to generate far field primary radiation patterns with equal E and H plane beamwidths and low sidelobes. A computer program for the radiation field expressions using the summation of waveguide radiation modes is described. The sensitivity of the multimode horn antenna radiation patterns to phase variations between the two modes is given. Sample radiation pattern calculations for a reflector feed horn for LAMMR are shown. The multimode horn antenna provides a low noise feed suitable for radiometric applications.

Dod, L. R.↗
DOE OSTI2026

Thermal Stability and Ion Irradiation Response of Refined Grained V – 4Cr – 4Ti

Since the 1960’s, there has been interest in V-4Cr-4Ti and similar alloys as candidates for low activation structural materials for advanced nuclear reactors. V-4Cr-4Ti was produced using arc melting and subsequently subjected to large strain extrusion machining to produce a multimodal microstructure largely composed of nanocrystalline and ultrafine grain sizes. In-situ thermal stability of the multimodal V-4Cr-4Ti to 800 °C shows the formation of vanadium carbides with negligible grain growth. In-situ dual-beam 16 KeV He+ and 1 MeV Kr2+ ion irradiation performed at 700 °C to a final dose of ~5 displacements per atom show the formation of small He cavities well distributed throughout the system, with preferential clustering at grain boundaries. This work provides insight into how the increased fraction of grain boundaries affect the simultaneous dual beam ion irradiation response of multimodal V – 4 wt.% Cr – 4 wt.% Ti at elevated temperatures. Analysis of the cavities reveal an areal density of 0.024±0.007 cavities/nm2 and swelling of 0.236% after the dual-beam ion irradiation. Nanoindentation shows a ~50% increase in hardening after the ion irradiation at 700 °C.

TEM↗
DOE OSTI2025

Diverse Manifestations of Electron-Phonon Coupling in a Kagome Superconductor

Recent angle-resolved photoemission spectroscopy (ARPES) experiments on the kagome metal CsV_{3}Sb_{5} revealed distinct multimodal dispersion kinks and nodeless superconducting gaps across multiple electron bands. The prominent photoemission kinks suggest a definitive coupling between electrons and certain collective modes, yet the precise nature of this interaction and its connection to superconductivity remain to be established. Here, employing the state-of-the-art ab initio many-body perturbation theory computation, we present direct evidence that electron-phonon (e-ph) coupling induces the multimodal photoemission kinks in CsV_{3}Sb_{5}, and profoundly, drives the nodeless s-wave superconductivity, showcasing the diverse manifestations of the e-ph coupling. Our calculations well capture the experimentally measured kinks and their fine structures, and reveal that vibrations from different atomic species dictate the multimodal behavior. Results from anisotropic GW-Eliashberg equations predict a phonon-mediated superconductivity with nodeless s-wave gaps, in excellent agreement with various ARPES and scanning tunneling spectroscopy measurements. Despite the universal origin of the e-ph coupling, the contributions of several characteristic phonon vibrations vary in different phenomena, highlighting a versatile role of e-ph coupling in shaping the low-energy excitations of kagome metals.

Electron-phonon coupling↗
NASA NTRS1986

Optical fiber characteristics and standards; Proceedings of the Meeting, Cannes, France, November 25-27, 1985

Papers are presented on outside vapor deposition, the plasma activated CVD process for large scale production of telecommunication fibers, axial lateral plasma deposition technology from plastic clad silica, coatings for optical fibers, primary coating characterization, and radiation-induced time dependent attenuation in a fiber. Topics discussed include fibers with high tensile strength, the characteristics and specifications of airborne fiber optic components, the baseband frequency response of multimode fibers, and fibers for local and broadband networks. Consideration is given to industrial measurements for single mode and multimode fibers, the characterization of source power distribution in a multimode fiber by a splice offset technique, the measurement of chromatic dispersion in a single mode optical, and the effect of temperature on the refracted near-field optical fiber profiling technique.

Bouillie, Remy↗
NASA NTRS1991

Multiple-mode reconfigurable electro-optic switching network for optical fiber sensor array

This paper reports the first switching network compatible with multimode fibers. A one-to-many cascaded reconfigurable interconnection was built. A thin glass substrate was used as the guiding medium which provides not only higher coupling efficiency from multimode fiber to waveguide but also better tolerance of phase-matching conditions. Involvement of a total-internal-reflection hologram and multimode waveguide eliminates interface problems between fibers and waveguides. The DCG polymer graft has proven to be reliable from -180 C to +200 C. Survivability of such an electrooptic system in harsh environments is further ensured. LiNbO3 was chosen as the E-O material because of its stability at high temperatures (phase-transition temperature of more than 1000 C) and maturity of E-O device technology. Further theoretical calculation was conducted to provide the optimal interaction length and device capacitance.

Chen, Ray T.↗
NASA NTRS1996

Numerical Analysis of the Sea State Bias for Satellite Altimetry

Theoretical understanding of the dependence of sea state bias (SSB) on wind wave conditions has been achieved only for the case of a unidirectional wind-driven sea. Recent analysis of Geosat and TOPEX altimeter data showed that additional factors, such as swell, ocean currents, and complex directional properties of realistic wave fields, may influence SSB behavior. Here we investigate effects of two-dimensional multimodal wave spectra using a numerical model of radar reflection from a random, non-Gaussian surface. A recently proposed ocean wave spectrum is employed to describe sea surface statistics. The following findings appear to be of particular interest: (1) Sea swell has an appreciable effect in reducing the SSB coefficient compared with the pure wind sea case but has less effect on the actual SSB owing to the corresponding increase in significant wave height. (2) Hidden multimodal structure (the two-dimensional wavenumber spectrum contains separate peaks, for swell and wind seas, while the frequency spectrum looks unimodal) results in an appreciable change of SSB. (3) For unimodal, purely wind-driven seas, the influence of the angular spectral width is relatively unimportant; that is, a unidirectional sea provides a good qualitative model for SSB if the swell is absent. (4) The pseudo wave age is generally much better fo parametrization the SSB coefficient than the actual wave age (which is ill-defined for a multimodal sea) or wind speed. (5) SSB can be as high as 5% of the significant wave height, which is significantly greater than predicted by present empirical model functions tuned on global data sets. (6) Parameterization of SSB in terms of wind speed is likely to lead to errors due to the dependence on the (in practice, unknown) fetch.

Glazman, R. E.↗
NASA NTRS2005

A least-squares parameter estimation algorithm for switched hammerstein systems with applications to the VOR

A "Multimode" or "switched" system is one that switches between various modes of operation. When a switch occurs from one mode to another, a discontinuity may result followed by a smooth evolution under the new regime. Characterizing the switching behavior of these systems is not well understood and, therefore, identification of multimode systems typically requires a preprocessing step to classify the observed data according to a mode of operation. A further consequence of the switched nature of these systems is that data available for parameter estimation of any subsystem may be inadequate. As such, identification and parameter estimation of multimode systems remains an unresolved problem. In this paper, we 1) show that the NARMAX model structure can be used to describe the impulsive-smooth behavior of switched systems, 2) propose a modified extended least squares (MELS) algorithm to estimate the coefficients of such models, and 3) demonstrate its applicability to simulated and real data from the Vestibulo-Ocular Reflex (VOR). The approach will also allow the identification of other nonlinear bio-systems, suspected of containing "hard" nonlinearities.

Evaluation Studies↗
NASA NTRS2008

Optical Measurement of Mass Flow of a Two-Phase Fluid

An optoelectronic system utilizes wavelength-dependent scattering of light for measuring the density and mass flow of a two-phase fluid in a pipe. The apparatus was invented for original use in measuring the mass flow of a two-phase cryogenic fluid (e.g., liquid hydrogen containing bubbles of hydrogen gas), but underlying principles of operation can readily be adapted to non-cryogenic two-phase fluids. The system (see figure) includes a laser module, which contains two or more laser diodes, each operating at a different wavelength. The laser module also contains beam splitters that combine the beams at the various wavelengths so as to produce two output beams, each containing all of the wavelengths. One of the multiwavelength output beams is sent, via a multimode fiberoptic cable, to a transmitting optical coupler. The other multiwavelength output beam is sent, via another multimode fiber-optic cable, to a reference detector module, wherein fiber-optic splitters split the light into several multiwavelength beams, each going to a photodiode having a spectral response that is known and that differs from the spectral responses of the other photodiodes. The outputs of these photodiodes are digitized and fed to a processor, which executes an algorithm that utilizes the known spectral responses to convert the photodiode outputs to obtain reference laser-power levels for the various wavelengths. The transmitting optical coupler is mounted in (and sealed to) a hole in the pipe and is oriented at a slant with respect to the axis of the pipe. The transmitting optical coupler contains a collimating lens and a cylindrical lens that form the light emerging from the end of the fiber-optic cable into a fan-shaped beam in a meridional plane of the pipe. Receiving optical couplers similar to the transmitting optical couplers are mounted in the same meridional plane at various longitudinal positions on the opposite side of the pipe, approximately facing the transmitting optical coupler along the same slant. Light collected by each receiving optical coupler is sent, via a multimode fiber-optic cable, to a detector module similar to the reference detector module. The outputs of the photodiodes in each detector module are digitized and processed, similarly to those of the reference detector module, to obtain indications of the amounts of light of each wavelength scattered to the corresponding receiving position. The value for each wavelength at each position is also normalized to the reference laser-power level for that wavelength. From these normalized values, the density and the mass flow rate of the fluid are estimated.

Wiley, John↗