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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Integration of renewable energy generation and storage systems for emissions reduction in an islanded campus microgrid

Microgrid connected building communities are projected to play an integral part in the clean energy transition. These types of systems, when integrated with distributed energy resources (DERs) such as combined heat and power (CHP), district heating and cooling, renewable generation, and energy storage, can provide clean, reliable power to critical facilities and vulnerable communities. The intermittent nature of renewable generation is a challenge when integrating renewables into any grid system, but particularly in islanded microgrids. The University of Texas at Austin (UT) operates an islanded microgrid powered by a CHP plant, while also utilizing district heating and cooling systems and thermal energy storage (TES). High fidelity operating data was used to develop a validated reduced order model of UT’s integrated campus energy systems to serve as a testbed for use in a case study. Hypothetical renewable energy installations on land owned by UT in west Texas were modeled and integrated into the validated campus models along with battery energy storage (BES). Simulations showed that a combination of renewable energy from wind, and optimally controlled 24-hour thermal and battery storage systems could reduce carbon dioxide emissions on campus by 45.4%. The additional retrofit of burner systems to utilize hydrogen natural gas blends resulted in an overall annual emissions reduction of 54.7%. Carbon capture and storage eliminated the majority of the remaining emissions with increased plant energy expenditure. The presented simulations display the practical limitations of a CHP system complemented by renewable generation and short-term storage in eliminating emissions. Furthermore, results highlight the need for further research and development in long duration storage technologies and hydrogen fueled turbines to increase penetration of renewable energy and reduce emissions.

CHP↗
NASA NTRS2010

Data-Flow Based Model Analysis

The concept of (meta) modeling combines an intuitive way of formalizing the structure of an application domain with a high expressiveness that makes it suitable for a wide variety of use cases and has therefore become an integral part of many areas in computer science. While the definition of modeling languages through the use of meta models, e.g. in Unified Modeling Language (UML), is a well-understood process, their validation and the extraction of behavioral information is still a challenge. In this paper we present a novel approach for dynamic model analysis along with several fields of application. Examining the propagation of information along the edges and nodes of the model graph allows to extend and simplify the definition of semantic constraints in comparison to the capabilities offered by e.g. the Object Constraint Language. Performing a flow-based analysis also enables the simulation of dynamic behavior, thus providing an "abstract interpretation"-like analysis method for the modeling domain.

Saad, Christian↗
DOE OSTI2025

Toward a Generalizable Prediction Model of Molten Salt Mixture Density with Chemistry‐Informed Transfer Learning

Optimally designing applications of molten salts requires knowledge of their thermophysical properties over a wide range of temperatures and compositions. There exist significant gaps in existing databases and this data can be challenging to experimentally measure due to high temperatures, salt corrosivity, and salt hygroscopicity. Existing databases have been used to create Redlich–Kister (RK) models for mixture density showing improved accuracy with respect to ideal mixing assumptions, but these models require subcomponent data measurements for each new system, therefore lacking generality. In order to address generalizability and data sparsity, a transfer learning procedure is proposed to train deep neural networks (DNNs) using a combination of semi‐empirical relationships (RK), data from the thermophysical arm of the molten salt thermal properties database and universal ab initio properties of component mixtures taken from the joint automated repository for various integrated simulations (JARVIS) classical force‐field inspired descriptors database to predict density in molten salts. Herein, it is shown that DNNs predict molten salt density with an r 2 over 0.99 and a mean absolute percentage error under 1%, outperforming alternative methods.

inorganic materials↗
DOE OSTI2021

Integrating renewable energy into mining operations: Opportunities, challenges, and enabling approaches

Mining is one of the most energy-intensive industries worldwide. It also provides a critical source of raw materials for the manufacturing, transportation, construction, and energy sectors. Demand for raw materials is projected to increase as the world population grows and many low-income economies become middle-income countries. This growth in mineral demand, coupled with falling mineral ore grade, will likely increase the mining industry’s energy demand, used for activities across exploration, extraction, beneficiation and processing, and refining. At the time of this writing, mine operations are – due to their remoteness – dependent on fossil fuels such as diesel, heavy oils, and coal. In principle, mining could use energy recovery, renewable energy, and carbon capture to supplement, replace, or mitigate the impacts of fossil fuel use. However, a combination of renewable-energy technologies would be required. We explore challenges, opportunities, and enabling approaches to integrate renewable energy technologies into mining operations by examining the literature, including academic work, technical reports, and data produced by international agencies. Here, we find that despite numerous opportunities, technical issues still need to be considered, but solutions can tailor renewables to the mining industry. Further research should focus on identifying specific opportunities, technologies, and implementation strategies across the value chain of a variety of minerals with similar operational procedures.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Validation of two-layer model for underexpanded hydrogen jets

Previous studies have shown that the two-layer model more accurately predicts hydrogen dispersion than the conventional notional nozzle models without significantly increasing the computational expense. However, the model was only validated for predicting the concentration distribution and has not been adequately validated for predicting the velocity distributions. In the present study, particle imaging velocimetry (PIV) was used to measure the velocity field of an underexpanded hydrogen jet released at 10 bar from a 1.5 mm diameter orifice. The two-layer model was the used to calculate the inlet conditions for a two-dimensional axisymmetric CFD model to simulate the hydrogen jet downstream of the Mach disk. The predicted velocity spreading and centerline decay rates agreed well with the PIV measurements. The predicted concentration distribution was consistent with data from previous planar Rayleigh scattering measurements used to verify the concentration distribution predictions in an earlier study. The jet spreading was also simulated using several widely used notional nozzle models combined with the integral plume model for comparison. These results show that the velocity and concentration distributions are both better predicted by the two-layer model than the notional nozzle models to complement previous studies verifying only the predicted concentration profiles. Thus, this study shows that the two-layer model can accurately predict the jet velocity distributions as well as the concentration distributions as verified earlier. Though more validation studies are needed to improve confidence in the model and increase the range of validity, the present work indicates that the two-layer model is a promising tool for fast, accurate predictions of the flow fields of underexpanded hydrogen jets.

08 HYDROGEN↗
DOE OSTI2023

Deep learning enables nanoscale X-ray 3D imaging with limited data

Deep neural network can greatly improve tomography reconstruction with limited data. A recent effort of combining ptycho-tomography model with the 3D U-net demonstrated a significant reduction in both the number of projections and computation time, and showed its potential for integrated circuit imaging that requires high-resolution and fast measurement speed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Testing biasedness of self-reported microbusiness innovation in the annual business survey

This study tests for potential bias in self-reported innovation due to the inclusion of a research and development (R&D) module that only microbusinesses (less than 10 employees) receive in the Annual Business Survey (ABS). Previous research found that respondents to combined innovation/R&D surveys reported innovation at lower rates than respondents to innovation-only surveys. A regression discontinuity design is used to test whether microbusinesses, which constitute a significant portion of U.S. firms with employees, are less likely to report innovation compared to other small businesses. In the vicinity of the 10-employee threshold, the study does not detect statistically significant biases for new-to-market and new-to-business product innovation. Statistical power analysis confirms the nonexistence of biases with a high power. Comparing the survey design of ABS to earlier combined innovation/R&D surveys provides valuable insights for the proposed integration of multiple Federal surveys into a single enterprise platform survey. The findings also have important implications for the accuracy and reliability of innovation data used as an input to policymaking and business development strategies in the United States.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1974

Charged particles

Calibrations compensating for the effects of charged particles in the ionosphere and in the interplanetary medium were applied to the Doppler tracking data acquired during Mariner 9 missions on a demonstration basis. The combined effects of the space plasma and the ionosphere were measured by a comparison of the range and Doppler observables (Differenced Range Versus Integrated Doppler (DRVID). Independent measurements of the ionospheric effects were obtained from polarimeter devices located at the Goldstone, California, tracking complex.

Madrid, G. A.↗
NASA NTRS1985

Finite-difference computations of rotor loads

The current and future potential of finite difference methods for solving real rotor problems which now rely largely on empiricism are demonstrated. The demonstration consists of a simple means of combining existing finite-difference, integral, and comprehensive loads codes to predict real transonic rotor flows. These computations are performed for hover and high-advanced-ratio flight. Comparisons are made with experimental pressure data.

Caradonna, F. X.↗
NASA NTRS1985

Finite-difference computations of rotor loads

This paper demonstrates the current and future potential of finite-difference methods for solving real rotor problems which now rely largely on empiricism. The demonstration consists of a simple means of combining existing finite-difference, integral, and comprehensive loads codes to predict real transonic rotor flows. These computations are performed for hover and high-advance-ratio flight. Comparisons are made with experimental pressure data.

Caradonna, F. X.↗
NASA NTRS1988

Acquisition Technique For Spread-Spectrum Codes

Ability to lock onto signal increased with minimal equipment. Technique proposed to improve acquisition of spread-spectrum (pseudonoise) coded signal modulated by digital data signal. Divides correlation time into subintervals, integrates over subintervals, passes integrator outputs through square-law detectors, and adds detector outputs over all subintervals to reach decision regarding detection of code. Reduces effect of data-bit transitions at price of non-coherent-combining loss.

Cheng, Unjeng↗
NASA NTRS1991

Addressable-Matrix Integrated-Circuit Test Structure

Method of quality control based on use of row- and column-addressable test structure speeds collection of data on widths of resistor lines and coverage of steps in integrated circuits. By use of straightforward mathematical model, line widths and step coverages deduced from measurements of electrical resistances in each of various combinations of lines, steps, and bridges addressable in test structure. Intended for use in evaluating processes and equipment used in manufacture of application-specific integrated circuits.

Sayah, Hoshyar R.↗
NASA NTRS1994

Environmentally sound manufacturing

The NASA/Thiokol/industry team has developed and started implementation of an environmentally sound manufacturing plan for the continued production of solid rocket motors. They have worked with other industry representatives and the U.S. Environmental Protection Agency to prepare a comprehensive plan to eliminate all ozone depleting chemicals from manufacturing processes and to reduce the use of other hazardous materials used to produce the space shuttle reusable solid rocket motors. The team used a classical approach for problem solving combined with a creative synthesis of new approaches to attack this problem. As our ability to gather data on the state of the Earth's environmental health increases, environmentally sound manufacturing must become an integral part of the business decision making process.

Caddy, Larry A.↗
NASA NTRS2003

Genomic clocks and evolutionary timescales

For decades, molecular clocks have helped to illuminate the evolutionary timescale of life, but now genomic data pose a challenge for time estimation methods. It is unclear how to integrate data from many genes, each potentially evolving under a different model of substitution and at a different rate. Current methods can be grouped by the way the data are handled (genes considered separately or combined into a 'supergene') and the way gene-specific rate models are applied (global versus local clock). There are advantages and disadvantages to each of these approaches, and the optimal method has not yet emerged. Fortunately, time estimates inferred using many genes or proteins have greater precision and appear to be robust to different approaches.

Evolution, Molecular↗
NASA NTRS2010

Sublimator Driven Coldplate Engineering Development Unit Test Results

The Sublimator Driven Coldplate (SDC) is a unique piece of thermal control hardware that has several advantages over a traditional thermal control scheme. The principal advantage is the possible elimination of a pumped fluid loop, potentially increasing reliability and reducing complexity while saving both mass and power. Because the SDC requires a consumable feedwater, it can only be used for short mission durations. Additionally, the SDC is ideal for a vehicle with small transport distances and low heat rejection requirements. An SDC Engineering Development Unit was designed and fabricated. Performance tests were performed in a vacuum chamber to quantify and assess the performance of the SDC. The test data was then used to develop correlated thermal math models. Nonetheless, an Integrated Sublimator Driven Coldplate (ISDC) concept is being developed. The ISDC couples a coolant loop with the previously described SDC hardware. This combination allows the SDC to be used as a traditional coldplate during long mission phases and provides for dissimilar system redundancy

Sheth, Rubik B.↗
NASA NTRSDate not supplied

Post-Flight Reconstruction Approach for Space Launch System Artemis I Mission

Upon completion of the first Space Launch System flight, NASA personnel will begin post-flight analyses. Telemetry from across the vehicle will be combined with external radar tracking and environmental observation data in order to close validation criteria and generate a best estimated trajectory (BET). This paper will describe the approach taken by the SLS team to integrate flight data from multiple flights sources into BET, pre-flight simulation and testing results, primary sources of uncertainty, and path towards processing flight results. This paper also includes a brief description of algorithms and approaches to estimate as-flown vehicle parameters such as booster specific impulse, booster (and core) thrust multipliers and dry mass.

Evan John Anzalone↗
NASA NTRS2003

Advantages of Brahms for Specifying and Implementing a Multiagent Human-Robotic Exploration System

We have developed a model-based, distributed architecture that integrates diverse components in a system designed for lunar and planetary surface operations: an astronaut's space suit, cameras, all-terrain vehicles, robotic assistant, crew in a local habitat, and mission support team. Software processes ('agents') implemented in the Brahms language, run on multiple, mobile platforms. These mobile agents interpret and transform available data to help people and robotic systems coordinate their actions to make operations more safe and efficient. The Brahms-based mobile agent architecture (MAA) uses a novel combination of agent types so the software agents may understand and facilitate communications between people and between system components. A state-of-the-art spoken dialogue interface is integrated with Brahms models, supporting a speech-driven field observation record and rover command system. An important aspect of the methodology involves first simulating the entire system in Brahms, then configuring the agents into a runtime system Thus, Brahms provides a language, engine, and system builder's toolkit for specifying and implementing multiagent systems.

Clancey, William J.↗