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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Large-Scale Circulation and Climate Variability

The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.

Perlwitz, J.↗
NASA NTRS1993

Observational aspects of the low-frequency intraseasonal variability of the atmosphere in middle latitudes

An integrated description of the planetary-scale structures that emerge as organized entities on intraseasonal temporal scales in the middle latitudes is developed. Spatial scales of atmospheric motions involved in the generation of variability in the LF range are specified. An overview of the 3D structure of the seasonally averaged eddies in which the intraseasonal fluctuations are superposed is presented. The generation and maintenance mechanisms possibly responsible for the existence of the seasonal, quasi-stationary disturbances are discussed. It is shown that in the LF, low-zonal wavenumber part of the spectrum, the power displayed by standing variance exceeds that of propagating variance and vice versa for HFs and wavenumbers.

Pandolfo, Lionel↗
NASA NTRS2008

Rolls-Royce Low Noise Highly Variable Cycle Nozzle for Next Generation Supersonic Aircraft

An overview of the work performed by Rolls-Royce under contract NNL08AA29C is presented. The work includes computational fluid dynamic (CFD) analysis for, and design of, a highly variable cycle exhaust model for the Supersonic project (NRA NN06ZEA001N). The CFD analysis shows that the latest design improvements to the clam shell doors have increased flow through the ejector over that achieved with previous designs.

Sokhey, Jack S.↗
NASA NTRS1991

Dynamic compensatory pattern matching in a fuzzy rule-based control system

A dynamic compensatory matching procedure is suggested as a method to generate an aggregated measure for evaluating the appropriateness of rules for control systems. It is a dynamic weighted matching technique which takes into account incomplete information under real-time requirements. The initial weights of importance of variables are generated with a generalized neural network architecture and a gradient descent algorithm. An intuitive compensatory scheme based on correlations among input variables of training data is adopted so that the system is coherent to a noisy environment.

Sun, Chuen-Tsai↗
NASA NTRSDate not supplied

Using A Guided Interview to Create an Individual Exposure Profile for The Lifetime Surveillance of Astronaut Health (LSAH)

BACKGROUND To support NASA’s Lifetime Surveillance of Astronaut Health (LSAH) project, Individual Exposure Profiles (IEPs) were developed to record an astronaut’s pre-, in-, and post-NASA exposures. NASA astronauts were invited to participate in a one-time guided interview to review known hazard exposures and medical history documented in NASA records and to add new information not otherwise reported. The purpose of the IEP project was to determine if any significant information was gained from these interviews and identify potential trends in long-term health. METHODOLOGY The pre-filled exposure profile data was extracted from several sources including medical records, biographies, and LSAH records. The information that was pre-filled before the interview included occupational exposures prior to selection to the Astronaut Corps, during active astronaut career (e.g., EVA and ground-based training, on-orbit exposures), and after active career. The IEPs also contained relevant medical history (e.g., audiometry, illnesses, injuries) and significant non-occupational exposures. 189 interviews were conducted from 2012-2014. A Microsoft Access database was created to store the information collected in the IEPs before and after the interviews. The database houses the information from the IEPs to track the updates made to the original data. By analyzing which astronauts supplied additional information and which kinds of data were consistently added, potential gaps and trends in missing data may be identified. In designing the database, an efficient structure was implemented for ease of inputting data and to create variables that would generate quantifiable data. Creating standardized variables within the structure helped ease the process of inputting, organizing data, and analyzing data. Additional updates/data were denoted and were categorized by type of update. The categories identified were “Confirmed”, “Confirmed & Supplemented”, “Supplemented”, “Denied”, “Denied & Supplemented”, and “Other”. STATISTICAL ANALYSIS AND RESULTS To assess frequency of exposure updates, descriptive statistics will be generated and stratified by relevant factors such as astronaut selection decade, age at selection, and program/era. Hypothesis testing will be performed to understand the associations between updates to exposure information and population characteristics.

Astronaut health↗
DOE OSTI2024

Generative deep-learning reveals collective variables of Fermionic systems

Complex processes of fermionic systems ranging from protein folding to nuclear fission often follow a low-dimensional reaction path parametrized in terms of a few collective variables. In nuclear theory, variables related to the shape of the nuclear density in a mean-field picture are key to describing the large amplitude collective motion of the neutrons and protons. Exploring the adiabatic energy landscape spanned by these degrees of freedom reveals the possible reaction channels while simulating the dynamics in this reduced space yields their respective probabilities. Unfortunately, this theoretical framework breaks down whenever the systems encounters a quantum phase transition with respect to the collective variables. Here, in this study, we introduce a novel generative deep-learning algorithm designed to build reaction paths that ensure that the many-fermion wave function stays differentiable with respect to the collective variables. This approach is applicable to any fermionic system described by a coherent state. We use the case of potential energy curves in the 16 O nucleus within the Hartree-Fock theory to illustrate its main features.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2019

Constraint-Based Off-Nominal Behavior Modeling for Europa Clipper

The risk analysis for the Europa Clipper mission evaluates the probability of mission failure based on the failure rates of individual components and dependencies among them. The probabilities are calculated by integrating over the intervals of time within which a fault occurs, accounting for an infinite number of cases. The response of the spacecraft to different faults can result in different schedules of activities, changing the intervals of integration. Europa currently uses models of spacecraft systems and components to simulate individual flight scenarios. The goal is to develop a framework for integrating, automating, and improving this modeling process. We describe an approach to generating the schedules for the different fault cases and determining the intervals for faults. It is not enough to just simulate individual cases because we are working with continuous variables that generate an infinite number of possible futures. Instead, we determine time windows within which certain faults can occur and use these time windows as bounds for integration. We found that determining these time windows is a constraint optimization problem. In order to represent these problems, we employ a language based on ontologies of behavior and scenarios. The language enables us to specify constraints in a simple, declarative syntax. A constraint-based analysis engine uses the declarative specification to identify bounds on system parameters and fill in details of behavior. For example, we created a detailed model of power generation, power use, and the corresponding effects on the battery in order to determine when an undervoltage fault can occur. An undervoltage during a trajectory correction maneuver requires that thrusting be interrupted for just enough time to recharge the battery such that the maneuver can be completed within battery limits. This behavior is generated based on the model to minimize the interruption time. For certain scenarios the constraint optimization problems were simple enough to be solved by hand, but the framework made the process substantially faster. It also produced solutions to other problems that we could not solve by hand or with existing tools and allowed us to generate and run many scenarios at once. The scenario language and engine greatly simplified the process of identifying time bounds and separating cases.

Everline, Chester J.↗
DOE OSTI2026

Digital Twin User Guide for Chelan County Public Utility District

This user manual offers a comprehensive guide for developing a Digital twin (DT) of a Kaplan turbine at Chelan County Public Utility District (Chelan PUD) using neural networks. As variable renewable generation expands, hydropower units must operate with optimal efficiency and stability. For Kaplan machines, this flexibility is achieved through coordinated control of guide vane (wicket gates) opening and runner blade pitch, which amplifies the plant’s inherent nonlinear behavior and challenges traditional physics-only modeling. The efficiency of the Kaplan turbine varies with different combinations of the guide vans (wicket gate) opening and the blade angle. Each guide van opening and blade angle has a corresponding highest efficiency point, forming a cam relationship that represents the optimal combination.The discharge of a hydraulic turbine is controlled by the opening angle of the guide vans. Therefore, for each value of head, there is a certain guide van opening and blade angle that corresponds to the highest efficiency. For a given head, different combinations of the guide van opening and blade angle have different efficiencies. Therefore, coordinate cam curves are used to describe the relationship between the wicket gate opening and blade angle with different water head. To address these challenges, the manual details a data-driven modeling and learning workflow centered on structured neural networks. The approach is designed to forecast critical operational variables—discharge flow, net head, penstock (or scroll-case) pressure, and generator electrical outputs—by leveraging real-time inputs such as the generator power control setpoint, exciter field current and field voltage, together with hydromechanical commands (e.g., gate position and, when available, runner blade-pitch angle). The neural models are trained and validated on operational data from a Kaplan unit operated by Chelan PUD, demonstrating that the structured NN architecture can learn the coupled gate–blade–electrical dynamics. The result is a robust DT that improves situational awareness and supports data-informed decision-making for Chelan PUD’s Kaplan turbine operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Development of Energy Storage: Cost models

Energy storage technologies offer a promising solution to electric grid stability issues associated with the integration of variable renewable generators. The capability to match the electrical power output to instantaneous fluctuations in grid demand is crucial to ensure continuity of service. Including energy storage capability in an integrated energy system (IES) can provide the flexibility needed to meet variable electric demand and reduce the load following demands place on the reactor. In this report, economic data collected for energy storage (ES) technologies are described to support the objective of assessing the profitability of ES integration within the IES framework. In particular, there is a growing interest in thermal energy storage (TES) given its unique capability for long-duration storage for improving electricity reliability at a low levelized cost. It is common practice to evaluate the total lifetime cost and profitability before commercializing new technologies. In this report we identify and examine the models needed to better understand the economics of thermal energy storage. We extend the TES cost model in RAVEN in the context of a balance of plant (BOP) that incorporates thermal storage. To focus the discussion, following a general overview of the most promising TES technologies, we consider a use case that involves a sensible heat, two-tank, molten-salt system. Structural and operational details are reported to identify the source of construction capital expenditure and operation and maintenance cost. A detailed description of the different cost items is provided as well as the cost scaling with different storage capacity and power ratings for capacity optimization purpose. In addition, the capital expenditure and the recurring cost of representative two-tank, molten salt coupled with concentrated solar plants are provided for readers’ reference. The ES use case is noteworthy as it is in the pilot stage of commercialization. We identify those areas that would benefit from an increased economic focus to obtain a more complete compilation of cost data. We also describe the thermal coupling issues that arise from integration of the two-tank molten salt thermal energy storage system with a BOP, which is the subject of our current research. Some components of costs will need to be evaluated through dedicated technoeconomic analysis in future modeling activities using modeling procedures proposed in this report. With the data presented and the procedures described in this report, sufficiently accurate models can be implemented for the solution of both the power dispatch and the capacity expansion problems within the RAVEN-based HYBRID framework.

25 ENERGY STORAGE↗
DOE OSTI2020

Comparing Generator Predictions of Single Transverse Variables in Neutrino-Argon Scattering [Poster]

Precise modeling of neutrino-argon scattering is a crucial requirement for the DUNE and SBN neutrino oscillation programs. Single transverse variables provide a powerful handle on theoretically-challenging nuclear effects in neutrino-carbon scattering, but they remain unmeasured for argon. The MicroBooNE experiment has the opportunity to achieve the first measurement of STVs in a LArTPC. The first detailed study of generator predictions for STVs in vμ-Ar scattering, reported in this poster, reveals substantial opportunities for model discrimination: Relative contributions of CCQE vs. 2p-2h interactions; and,Treatment of nucleon pair initial state. We encourage MicroBooNE to pursue a measurement of this kind. Many more generator comparisons from our study are available.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Evolving Metrics for Resource Adequacy Assessment

Resource adequacy analysis quantifies the likelihood of capacity shortfall on a power system in a probabilistic manner. Using a combination of statistical techniques and power system fundamentals, the analysis typically evaluates hundreds or thousands of stochastic random samples (replications) of varying load, generator outages, variable renewable energy availability, and other aspects of power system uncertainty. In this range of uncertainty, there are - at times - periods where the power system's available resources are insufficient to meet system demand, referred to as a shortfall event. Today's power systems' rapidly evolving generation mix is changing the types of data needed by system planners and regulators, which can often render traditional resource adequacy metrics insufficient for ensuring resource adequacy for tomorrow's grid. In this paper we provide a critical assessment of traditional measures of shortfall risk in power systems, discussing their shortcomings and how they compare to metrics used in other domains. From this analysis we propose four steps forward for improving power system resource adequacy risk metrics in the future.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗
DOE OSTI2023

Beyond Expected Values Evolving Metrics for Resource Adequacy Assessment

Resource adequacy analysis quantifies the likelihood of capacity shortfall on a power system in a probabilistic manner. Using a combination of statistical techniques and power system fundamentals, the analysis typically evaluates hundreds or thousands of stochastic random samples (replications) of varying load, generator outages, variable renewable energy availability, and other aspects of power system uncertainty. In this range of uncertainty, there are - at times - periods where the power system's available resources are insufficient to meet system demand, referred to as a shortfall event. Today's power systems' rapidly evolving generation mix is changing the types of data needed by system planners and regulators, which can often render traditional resource adequacy metrics insufficient for ensuring resource adequacy for tomorrow's grid. In this paper we provide a critical assessment of traditional measures of shortfall risk in power systems, discussing their shortcomings and how they compare to metrics used in other domains. From this analysis we propose four steps forward for improving power system resource adequacy risk metrics in the future.

ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1977

Two-body coordinate system generation using body-fitted coordinate system and complex variable transformation

Attempts are made to generate acceptable coordinate systems for two-body configurations. The first method to be tried was to use the body-fitted coordinate system technique to obtain the best system. This technique alone did not produce very good results, so another approach was investigated. This new approach involved using a combination of the body fitted coordinate system procedure and a complex variable transformation method that was used successfully in conformal mapping.

Long, W. S.↗
DOE OSTI2024

To Derive or Not to Derive: I/O Libraries Take Charge of Derived Quantities Computation

The ever-increasing volume of data produced by HPC simulations necessitates scalable methods for data exploration and knowledge extraction. Scientific data analysis often involves complex queries across distributed datasets, requiring manipulation of multiple primary variables and generating derived data that needs to be handled efficiently, creating challenges for applications that need to parse many large datasets. Relying on individual applications to handle all intermediate data generally leads to redundant computations across studies and unnecessary data transfers. In this paper, we investigate the performance of different approaches where applications define derived variables as quantities of interest (QoIs) and offload the computation and transfer of these QoIs to the I/O library. This significantly reduces redundancy and optimizes data movement across the distributed storage and processing infrastructure by allowing control over when and where derived variables are computed. We present a detailed analysis of the performance-storage trade-offs associated with different solutions and showcase results for our study on two large-scale datasets created from climate and combustion simulations.

Gainaru, Ana↗
DOE OSTI2023

Visualization of the Oscillatory Dynamics of an Island Power System

In this work, we discuss the design of visualizations for understanding the complex oscillatory dynamics of an island power system with renewable generation sources after the loss of a large oil power plant. As more renewable generation sources are added to power systems, the oscillatory dynamics will change, which requires new visualization techniques to determine causes and strategies to avoid unwanted behaviors in the future. Our approach integrates geographic views, time-series plots, and novel oscillatory-trajectory curves, providing unique insights into the interdependent oscillatory behaviors of multiple state variables and generators over time. By enabling multi-node and multivariate comparisons over time, users can qualitatively determine drivers of oscillations and differences in generator dynamics, which is not possible with other commonly used visualization techniques.

inverters↗
DOE OSTI2023

Visualization of the Oscillatory Dynamics of an Island Power System: Preprint

In this work, we discuss the design of visualizations for understanding the complex oscillatory dynamics of an island power system with renewable generation sources after the loss of a large oil power plant. As more renewable generation sources are added to power systems, the oscillatory dynamics will change, which requires new visualization techniques to determine causes and strategies to avoid unwanted behaviors in the future. Our approach integrates geographic views, time-series plots, and novel oscillatory-trajectory curves, providing unique insights into the interdependent oscillatory behaviors of multiple state variables and generators over time. By enabling multi-node and multivariate comparisons over time, users can qualitatively determine drivers of oscillations and differences in generator dynamics, which is not possible with other commonly used visualization techniques.

inverters↗
DOE OSTI2022

Hydrogen Storage for Load-Following and Clean Power: Duct-firing of Hydrogen to Improve the Capacity Factor of NGCC Plants (Final Report, Phase I Conceptual Study)

The 12-month Feasibility study in Phase I study was completed and confirmed the system is feasible and the proposed system is an improvement over alternate low carbon dispatchable power options. Our demonstration will include 54 MWh of hydrogen storage. CO 2 capture inherent to the CHG process can capture 90% of the CO 2 (with upgrades to >98%) in a commercial system (~300 MWth) for sequestration or other uses. The hydrogen will be utilized in a duct burner in a Heat Recovery Steam Generator (HRSG) integrated with the existing Southern Company fossil asset. Here, the firing rate of the duct burner is varied to let the plant respond to fluctuations of electrical load. However, H 2 production is relatively constant by storing H 2 , and revenues are improved by arbitrage between use of low-cost off-peak variable electricity generation or use of stored H 2 under peak demand. The study enabled the fidelity of the concept to be improved and allowed identification of the requirements for the system. Defining the individual system and component requirements was performed via system requirements review with the whole team. These requirements were then incorporated into/iterated with our Heat & Mass Balance models and process flow diagrams were generated to reflect the overall system. This information was then used to complete the TEA and show economic feasibility. Our system generates power at 17.4% lower cost than other low carbon approaches for the H 2 generation, H 2 compression and storage, carbon sequestration, and HRSG added electricity production for a large-scale duct-fired system. Our team recommends completing the Phase II Pre-FEED study for the proposed system as the next step for the project and its tasks will achieve the overall objective and be ready to launch the FEED. The Pre-FEED tasks include updating the requirements, Concept of Operations, plant scope/process description, component modeling, system modeling, performance estimates, emission estimates, block flow diagrams, fluid/process conditions (PFD), utility usage, and facility sizing/definition. The approach will be to complete these updates in a greater level of detail for the selected site. The approach for developing the EIV is to use the updated results, including model outputs, for carbon dioxide and waste streams.

03 NATURAL GAS↗