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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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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

How Frequent Will the Rarest Daily Rainfall Records of Hurricane Ida’s Remnants Be in the Future?

Abstract Gaining continued insights into the impact of global warming on the occurrence of hurricane-associated intense record downpours is essential for building climate resilient communities. This study investigates projected future changes in extreme rainfall over the Northeast United States, as represented by extreme daily amounts during Hurricane Ida in 2021. We used historical control simulations of Weather Research and Forecasting (WRF) Model generated from 40 years of weather events (1980–2014, 12 km) forced by the fifth generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis. These simulations are thermodynamically modified (2060–2100) via an imposed warming for the high-emission scenario of shared socioeconomic pathway (SSP585) from a range of general circulation models. Ground observations from the Global Historical Climatology Network (1950–2014) and WRF simulations (historical, 1980–2014, and future, 2060–2100) are integrated into a nonstationary generalized extreme value (GEV) framework to assess the frequency of Ida’s heaviest daily rain rates under the SSP585 scenario. Results show that Ida’s daily maximum rainfall recorded at different observation locations was higher than the single highest September daily maximum observed (1950–2014) for 5 out of 17 stations (∼30% of the stations). Ida-like extreme daily rain rates are projected to be, on average, more than 2 times more likely to occur at the end of the century in the simulations (with some regions as high as 5 times). This work demonstrates that integrating a high-resolution atmospheric model’s present-day and thermodynamically modified future simulations along with ground observations, within a nonstationary statistical framework, is crucial for understanding changing characteristics of extreme weather events. Significance Statement Daily scale extreme precipitation is expected to become more frequent and severe, as evidenced by observations and model simulations. While it is important to investigate how these intensifying heavy rainfall events affect current engineering standards, fewer studies have contextualized how warming impacts the most extreme rainfall from a single storm event relative to historical heavy downpours. In this study, we focused on the daily extreme rainfall associated with the extratropical transition of Hurricane Ida (2021), particularly over the northeastern United States—some of which exceeded the commonly used hydrologic design criteria for a 100-yr storm. Using a high-resolution atmospheric model simulation, we investigated how continued warming may influence the frequency of such daily rain rates. Under a high-emission scenario, these events are projected to become up to 5 times more likely at the end of the twenty-first century.

Dollan, Ishrat J↗
NASA NTRS2017

Hemispherical Optical Dome for Underwater Communication

For many years, acoustic systems have been used as the primary method for underwater communication; however, the data transfer rate of such systems is low because sound propagates slowly through the water. A higher throughput can be achieved using visible light to transmit data underwater. The first issue with using this approach is that there is generally a large loss of the light signal due to scattering and absorption in water even though there is an optimal wavelength for transmission in the blue or green wavelengths of the visible spectrum. The second issue is that a simple system consisting only of a highly directional source transmitter and small optical detector receiver has a very narrow field of view. The goal of this project is to improve an optical, underwater communication system by increasing the effective field of view of the receiving optics. To this end, we make two changes to the simple system: (1) An optical dome was added near the receiver. An array of lenses is placed radially on the surface of the dome, reminiscent of the compound eye of an insect. The lenses make the source and detector planes conjugate, and each lens adds a new region of the source plane to the instrument's total field of view. (2) The receiver was expanded to include multiple photodiodes. With these two changes, the receiver has much more tolerance to misalignments (in position and angle) of the transmitter.Two versions of the optical dome (with 6 and 8 diameters) were designed using the CREO CAD software and modeled using the CODE V optical design software. A series of these transparent hemispherical domes, with both design diameters, were manufactured using a 5-axis mill. The prototype was then retrofitted with lenses and compared with the computer-generated model to demonstrate the effectiveness of this solution. This work shows the dome design improves the optical field of view of the underwater communication system considerably. Furthermore, with the experimental test results, a geometric optimization model was derived providing insights to the design performance limits.

Design↗
NASA NTRS2017

Hemispherical Optical Dome for Underwater Communication

For many years, acoustic systems have been used as the primary method for underwater communication; however, the data transfer rate of such systems is low because sound propagates slowly through the water. A higher throughput can be achieved using visible light to transmit data underwater. The first issue with using this approach is that there is generally a large loss of the light signal due to scattering and absorption in water even though there is an optimal wavelength for transmission in the blue or green wavelengths of the visible spectrum. The second issue is that a simple system consisting only of a highly directional source/transmitter and small optical detector/receiver has a very narrow field of view. The goal of this project is to improve an optical, underwater communication system by increasing the effective field of view of the receiving optics. To this end, we make two changes to the simple system: (1) An optical dome was added near the receiver. An array of lenses is placed radially on the surface of the dome, reminiscent of the compound eye of an insect. The lenses make the source and detector planes conjugate, and each lens adds a new region of the source plane to the instrument's total field of view. (2) The receiver was expanded to include multiple photodiodes. With these two changes, the receiver has much more tolerance to misalignments (in position and angle) of the transmitter.Two versions of the optical dome (with 6 and 8 diameters) were designed using the CREO CAD software and modeled using the CODE V optical design software. A series of these transparent hemispherical domes, with both design diameters, were manufactured using a 5-axis mill. The prototype was then retrofitted with lenses and compared with the computer-generated model to demonstrate the effectiveness of this solution. This work shows the dome design improves the optical field of view of the underwater communication system considerably. Furthermore, with the experimental test results, a geometric optimization model was derived providing insights to the design performance limits.

Underwater↗
DOE OSTI2026

Generative Electrolyte Solvent and Formulation Discovery

Molecular mixtures and/or formulations are of great importance in fields ranging from materials science to pharmaceuticals to chemistry. In batteries, electrolytes are complex molecular mixtures consisting of multiple salts and solvents and additives at different concentrations that dictate battery capacity, safety, and cycle life, among others. Unfortunately, due to the complex composition and infinite design space as well as the conflicting property requirements, electrolyte design is the rate-determining step in the design of next generation battery chemistries. In this work, we develop a transformer-based generative AI model − ElectrolyteGPT − capable of generating solvents and electrolyte formulations to satisfy a wide range of desired property requirements. First, we curate an electrolyte-relevant database and develop a new line notation for formulations. Then, we show that ElectrolyteGPT can generate solvents and formulations conditioned on a wide range of important electrolyte properties such as ionic conductivity, oxidative stability, Coulombic efficiency, viscosity, and more. Finally, we experimentally synthesize the generated solvents and fabricate the electrolyte formulations and show that they can meet the desired property requirements and enable longterm cycling in energy-dense anode-free lithium metal batteries. Our work showcases the ability of generative models to address challenges in molecular mixture design for next generation batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Muon-Neutrino Charged-Current Cross Sections from MicroBooNE: First Simultaneous Measurements of Final States with and without Protons for Muon-Neutrino Scattering on Argon

A detailed understanding of muon neutrino charged-current interactions on argon is crucial to the study of neutrino oscillations in current and future experiments using liquid argon time projection chambers. To help fill this need, MicroBooNE has produced a comprehensive set of cross section measurements which simultaneously probe the leptonic and hadronic systems by dividing the inclusive channel into final states with and without protons. Data-driven model validation utilizing the conditional constraint formalism is employed to detect mismodeling that may bias the nominal flux averaged cross section results, which are extracted with the Wiener-SVD unfolding method. The results are compared to widely used event generator predictions revealing significant mismodeling of final states without protons, possibly due to insufficient treatment of final state interactions. These are first differential muon neutrino-argon cross section measurements made simultaneously for final states with and without protons and provide novel information that will help stimulate the improvement of event generator modeling.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2021

Limits on Runoff Episode Duration for Early Mars: Integrating Lake Hydrology and Climate Models

Fluvio-lacustrine features on the martian surface attest to a climate that was radically different in the past. Since climate models have difficulty sustaining a liquid hydrosphere at the surface, multiple cycles of runoff episodes may have characterized the ancient Mars climate. A fundamental question thus remains: what was the duration of these runoff-producing episodes? Here we use morphometric measurements from newly identified coupled lake systems, containing both an open- and a closed-basin lake (n=7). We combined hydrological balances with precipitation outputs from climate models, and found that breaching runoff episodes likely lasted 102−105yr; other episodes may have been shorter but could not be longer. Runoff episode durations are model-dependent and spatiallyvariable, and no27climate model scenario can satisfy a unique duration for all coupled systems. In the near future, these quantitative constraints on early Mars lake persistence may be tested through in situ observations from Perseverance rover. Plain Language Summary Ancient river and lake beds on the martian surface point to a climate that was radically different in the past, unlike the dry, cold desert that Mars is today. It experienced significant liquid water flowing across the surface (i.e., ‘runoff’) and hosted long-lived bodies of water (lakes and seas). However, scientists that generate models to simulate the ancient Mars climate have difficulty sustaining this proposed liquid water cycle at the surface. One possible hypothesis is that multiple cycles of individual liquid water episodes may have characterized the ancient martian climate (i.e. runoff episodes). A fundamental question thus remains: what was the duration of these individual runoff-producing episodes? Here we use an approach that takes advantage of unique martian lake system, ‘coupled’ lake systems, and their shapes. We combined these measurements with precipitation results from previous climate models, and found that runoff episodes likely lasted 100-10,000 years, requiring a global climate mechanism that generated repeated cycles of this duration. Ultimately, our results can be tested through observations made by NASA’s Perseverance rover, shedding light on the uninterrupted duration of surface water on Mars and its potential to host life in the past.

Gaia Stucky de Quay↗
DOE OSTI2024

Stochastic Modeling Workflow to Generate Representative Geologic Variability in Training Dataset for SMART Initiative

The poster discusses the modeling workflow to generate ensemble of geologic realizations of the Illinois Basin Decatur Project (IBDP) site, based on available site characterization data and inherent uncertainty of those data, for use by project collaborators in DOE SMART Initiative (Phase 2) to build their forward modeling, history matching, and optimization workflows. This poster is summarized from the technical report for the SMART project submitted to U.S. DOE earlier this year.

Ganesh, Priya Ravi↗
NASA NTRS1997

Steady-State Cycle Deck Launcher Developed for Numerical Propulsion System Simulation

One of the objectives of NASA's High Performance Computing and Communications Program's (HPCCP) Numerical Propulsion System Simulation (NPSS) is to reduce the time and cost of generating aerothermal numerical representations of engines, called customer decks. These customer decks, which are delivered to airframe companies by various U.S. engine companies, numerically characterize an engine's performance as defined by the particular U.S. airframe manufacturer. Until recently, all numerical models were provided with a Fortran-compatible interface in compliance with the Society of Automotive Engineers (SAE) document AS681F, and data communication was performed via a standard, labeled common structure in compliance with AS681F. Recently, the SAE committee began to develop a new standard: AS681G. AS681G addresses multiple language requirements for customer decks along with alternative data communication techniques. Along with the SAE committee, the NPSS Steady-State Cycle Deck project team developed a standard Application Program Interface (API) supported by a graphical user interface. This work will result in Aerospace Recommended Practice 4868 (ARP4868). The Steady-State Cycle Deck work was validated against the Energy Efficient Engine customer deck, which is publicly available. The Energy Efficient Engine wrapper was used not only to validate ARP4868 but also to demonstrate how to wrap an existing customer deck. The graphical user interface for the Steady-State Cycle Deck facilitates the use of the new standard and makes it easier to design and analyze a customer deck. This software was developed following I. Jacobson's Object-Oriented Design methodology and is implemented in C++. The AS681G standard will establish a common generic interface for U.S. engine companies and airframe manufacturers. This will lead to more accurate cycle models, quicker model generation, and faster validation leading to specifications. The standard will facilitate cooperative work between industry and NASA. The NPSS Steady-State Cycle Deck team released a batch version of the Steady-State Cycle Deck in March 1996. Version 1.1 was released in June 1996. During fiscal 1997, NPSS accepted enhancements and modifications to the Steady-State Cycle Deck launcher. Consistent with NPSS' commercialization plan, these modifications will be done by a third party that can provide long-term software support.

VanDrei, Donald E.↗
NASA NTRS1999

Neural-Net Processing of Characteristic Patterns From Electronic Holograms of Vibrating Blades

Finite-element-model-trained artificial neural networks can be used to process efficiently the characteristic patterns or mode shapes from electronic holograms of vibrating blades. The models used for routine design may not yet be sufficiently accurate for this application. This document discusses the creation of characteristic patterns; compares model generated and experimental characteristic patterns; and discusses the neural networks that transform the characteristic patterns into strain or damage information. The current potential to adapt electronic holography to spin rigs, wind tunnels and engines provides an incentive to have accurate finite element models lor training neural networks.

Decker, Arthur J.↗
NASA NTRS1995

Diabatic forcing and intialization with assimilation of cloud water and rainwater in a forecast model

In this study, diabatic forcing, and liquid water assimilation techniques are tested in a semi-implicit hydrostatic regional forecast model containing explicit representations of grid-scale cloud water and rainwater. Diabatic forcing, in conjunction with diabatic contributions in the initialization, is found to help the forecast retain the diabatic signal found in the liquid water or heating rate data, consequently reducing the spinup time associated with grid-scale precipitation processes. Both observational Special Sensor Microwave/Imager (SSM/I) and model-generated data are used. A physical retrieval method incorporating SSM/I radiance data is utilized to estimate the 3D distribution of precipitating storms. In the retrieval method the relationship between precipitation distributions and upwelling microwave radiances is parameterized, based upon cloud ensemble-radiative model simulations. Regression formulae relating vertically integrated liquid and ice-phase precipitation amounts to latent heating rates are also derived from the cloud ensemble simulations. Thus, retrieved SSM/I precipitation structures can be used in conjunction with the regression-formulas to infer the 3D distribution of latent heating rates. These heating rates are used directly in the forecast model to help initiate Tropical Storm Emily (21 September 1987). The 14-h forecast of Emily's development yields atmospheric precipitation water contents that compare favorably with coincident SSM/I estimates.

Raymond, William H.↗
NASA NTRS1991

Infiltration/cure modeling of resin transfer molded composite materials using advanced fiber architectures

A model was developed which can be used to simulate infiltration and cure of textile composites by resin transfer molding. Fabric preforms were resin infiltrated and cured using model generated optimized one-step infiltration/cure protocols. Frequency dependent electromagnetic sensing (FDEMS) was used to monitor in situ resin infiltration and cure during processing. FDEMS measurements of infiltration time, resin viscosity, and resin degree of cure agreed well with values predicted by the simulation model. Textile composites fabricated using a one-step infiltration/cure procedure were uniformly resin impregnated and void free. Fiber volume fraction measurements by the resin digestion method compared well with values predicted using the model.

Loos, Alfred C.↗
NASA NTRS2013

Strengthening of Ocean Heat Uptake Efficiency Associated with the Recent Climate Hiatus

The rate of increase of global-mean surface air temperature (SAT(sub g)) has apparently slowed during the last decade. We investigated the extent to which state-of-the-art general circulation models (GCMs) can capture this hiatus period by using multimodel ensembles of historical climate simulations. While the SAT(sub g) linear trend for the last decade is not captured by their ensemble means regardless of differences in model generation and external forcing, it is barely represented by an 11-member ensemble of a GCM, suggesting an internal origin of the hiatus associated with active heat uptake by the oceans. Besides, we found opposite changes in ocean heat uptake efficiency (k), weakening in models and strengthening in nature, which explain why the models tend to overestimate the SAT(sub g) trend. The weakening of k commonly found in GCMs seems to be an inevitable response of the climate system to global warming, suggesting the recovery from hiatus in coming decades.

Climate hiatus↗
NASA NTRS2001

The Evaluation of the Regional Atmospheric Modeling System in the Eastern Range Dispersion Assessment System

The Applied Meteorology Unit (AMU) evaluated the Regional Atmospheric Modeling System (RAMS) contained within the Eastern Range Dispersion Assessment System (ERDAS). ERDAS provides emergency response guidance for Cape Canaveral Air Force Station and Kennedy Space Center operations in the event of an accidental hazardous material release or aborted vehicle launch. The RAMS prognostic data are available to ERDAS for display and are used to initialize the 45th Space Wing/Range Safety dispersion model. Thus, the accuracy of the dispersion predictions is dependent upon the accuracy of RAMS forecasts. The RAMS evaluation consisted of an objective and subjective component for the 1999 and 2000 Florida warm seasons, and the 1999-2000 cool season. In the objective evaluation, the AMU generated model error statistics at surface and upper-level observational sites, compared RAMS errors to a coarser RAMS grid configuration, and benchmarked RAMS against the nationally-used Eta model. In the subjective evaluation, the AMU compared forecast cold fronts, low-level temperature inversions, and precipitation to observations during the 1999-2000 cool season, verified the development of the RAMS forecast east coast sea breeze during both warm seasons, and examined the RAMS daily thunderstorm initiation and precipitation patterns during the 2000 warm season. This report summarizes the objective and subjective verification for all three seasons.

Case, Jonathan↗
NASA NTRS2001

Reusable Solid Rocket Motor Nozzle Joint-4 Thermal Analysis

This study provides for development and test verification of a thermal model used for prediction of joint heating environments, structural temperatures and seal erosions in the Space Shuttle Reusable Solid Rocket Motor (RSRM) Nozzle Joint-4. The heating environments are a result of rapid pressurization of the joint free volume assuming a leak path has occurred in the filler material used for assembly gap close out. Combustion gases flow along the leak path from nozzle environment to joint O-ring gland resulting in local heating to the metal housing and erosion of seal materials. Analysis of this condition was based on usage of the NASA Joint Pressurization Routine (JPR) for environment determination and the Systems Improved Numerical Differencing Analyzer (SINDA) for structural temperature prediction. Model generated temperatures, pressures and seal erosions are compared to hot fire test data for several different leak path situations. Investigated in the hot fire test program were nozzle joint-4 O-ring erosion sensitivities to leak path width in both open and confined joint geometries. Model predictions were in generally good agreement with the test data for the confined leak path cases. Worst case flight predictions are provided using the test-calibrated model. Analysis issues are discussed based on model calibration procedures.

Clayton, J. Louie↗
DOE OSTI2026

Identifying stochastic dynamics via finite expression methods

Modeling stochastic differential equations (SDEs) is crucial for understanding complex dynamical systems in various scientific fields. Recent methods often employ neural network-based models, which typically represent SDEs through a combination of deterministic and stochastic terms. However, these models usually lack interpretability and have difficulty in generalizing beyond their training domain. Here, this paper introduces the Finite Expression Method (FEX), a symbolic learning approach designed to derive interpretable mathematical representations of the deterministic component of SDEs. For the stochastic component, we integrate FEX with advanced generative modeling techniques to provide a comprehensive representation of SDEs. The numerical experiments on linear, nonlinear, and multidimensional SDEs demonstrate that FEX generalizes well beyond the training domain and delivers more accurate long-term predictions compared to neural network-based methods. The symbolic expressions identified by FEX not only improve prediction accuracy but also offer valuable scientific insights into the underlying dynamics of the systems.

Complex dynamical systems↗
NASA NTRS2005

Predictive Interfaces for Long-Distance Tele-Operations

We address the development of predictive tele-operator interfaces for humanoid robots with respect to two basic challenges. Firstly, we address automating the transition from fully tele-operated systems towards degrees of autonomy. Secondly, we develop compensation for the time-delay that exists when sending telemetry data from a remote operation point to robots located at low earth orbit and beyond. Humanoid robots have a great advantage over other robotic platforms for use in space-based construction and maintenance because they can use the same tools as astronauts do. The major disadvantage is that they are difficult to control due to the large number of degrees of freedom, which makes it difficult to synthesize autonomous behaviors using conventional means. We are working with the NASA Johnson Space Center's Robonaut which is an anthropomorphic robot with fully articulated hands, arms, and neck. We have trained hidden Markov models that make use of the command data, sensory streams, and other relevant data sources to predict a tele-operator's intent. This allows us to achieve subgoal level commanding without the use of predefined command dictionaries, and to create sub-goal autonomy via sequence generation from generative models. Our method works as a means to incrementally transition from manual tele-operation to semi-autonomous, supervised operation. The multi-agent laboratory experiments conducted by Ambrose et. al. have shown that it is feasible to directly tele-operate multiple Robonauts with humans to perform complex tasks such as truss assembly. However, once a time-delay is introduced into the system, the rate of tele\ioperation slows down to mimic a bump and wait type of activity. We would like to maintain the same interface to the operator despite time-delays. To this end, we are developing an interface which will allow for us to predict the intentions of the operator while interacting with a 3D virtual representation of the expected state of the robot. The predictive interface anticipates the intention of the operator, and then uses this prediction to initiate appropriate sub-goal autonomy tasks.

Wheeler, Kevin R.↗
DOE OSTI2026

Generation of random geological models using multi-randomization for machine learning

Generating high-fidelity geological models is essential for advancing machine learning (ML) methods in automated seismic interpretation. For instance, seismic images paired with corresponding fault labels are foundational for ML-based fault detection from seismic migration sections. While several open-access datasets of random geological models exist, open-source tools specifically designed to produce large volumes of such models for ML applications remain scarce. To address this gap, we present RGM (Random Geological Model), an open-source software package for efficiently generating 2D and 3D synthetic geological models tailored for ML workflows. RGM supports the creation of diverse model components, including medium property distributions (P-/S-wave velocities and density), seismic reflectivity images (i.e., synthetic migration sections), relative geological time, and discrete fault attributes such as probability, dip, strike, rake, and displacement. It also accommodates the creation of complex geological features such as salt bodies and unconformities. The model generation algorithm employs a multi-randomization strategy, yielding an effectively infinite-dimensional model space that encompasses a wide range of geological scenarios and associated seismic features. Furthermore, RGM incorporates a method to generate synthetic elastic migration images using analytical elastic reflection coefficients combined with frequency-dependent scaling. This functionality enables the creation of training datasets for ML models that leverage elastic seismic images. RGM is implemented in modern object-oriented Fortran, allowing users to flexibly control statistical parameters governing model variability. We demonstrate the capability, performance, and geological realism of the package through comprehensive 2D and 3D examples.

58 GEOSCIENCES↗
DOE OSTI2026

Fidelity-preserving enhancement of ptychography with foundational text-to-image models

Ptychographic phase retrieval enables high-resolution imaging of complex samples but often suffers from artifacts such as grid pathology and multislice crosstalk, which degrade reconstructed images. We propose a plug-and-play (PnP) framework that integrates physics model-based phase retrieval with text-guided image editing using foundational diffusion models. By employing the alternating direction method of multipliers, our approach ensures consensus between data fidelity and artifact removal subproblems, maintaining physical consistency while enhancing image quality. Artifact removal is achieved using a text-guided diffusion image editing method (LEDITS++) with a pre-trained foundational diffusion model, allowing users to specify artifacts for removal in natural language. Demonstrations on simulated and experimental datasets show significant improvements in artifact suppression and structural fidelity, validated by metrics such as peak signal-to-noise ratio and diffraction pattern consistency. This work highlights the combination of text-guided generative models and model-based phase retrieval algorithms as a transferable and fidelity-preserving method for high-quality diffraction imaging.

image editing↗