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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
DOE OSTI2021

Climate Drives Modeled Forest Carbon Cycling Resistance and Resilience in the Upper Great Lakes Region, USA

Forests dominate the global terrestrial carbon budget, but their ability to continue doing so in the face of a changing climate is uncertain. A key uncertainty is how forests will respond (resistance) and recover from (resilience) to rising levels of disturbance of varying intensities. This knowledge gap can optimally be addressed by integrating manipulative field experiments with ecophysiological modeling. We used the ED-2.2 model to project carbon fluxes for a northern temperate deciduous forest subjected to a real-world disturbance severity manipulation experiment. ED-2.2 was run for 150 years, starting from near bare ground in 1900, and subjected to three disturbance treatments under an ensemble of climate conditions. Both disturbance severity and climate strongly affected carbon fluxes, and interacted with one another. We then calculated metrics of functional ecosystem stability. Modeled gross primary production exhibited a mean resistance of -0.13, -0.23, and -0.42 (unitless) in response to increasing disturbance severity of 45%, 65%, and 85% mortality, respectively; and resilience of 0.002, 0.004, 0.008 (yr-1) respectively. This pattern held true for other carbon fluxes, meaning that in general simulated GPP declined more initially but recovered more quickly from higher mortality. Notably, however, heterotrophic respiration responded more slowly to disturbance, and its highly variable response was affected by different drivers. This work provides insight into how future conditions might affect the functional stability of mature forests in this region under ongoing climate change and changing disturbance regimes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1973

Numerical calculation of the three dimensional transonic flow over a yawed wing.

Results are presented of calculations of the three dimensional steady transonic flow over a finite yawed wing. The full potential flow equation is solved in a transformed coordinate system which permits the boundary conditions to be satisfied exactly. The correct differential properties are enforced by rotating the difference scheme to conform with the flow direction, and fast convergence is assured by simulating a time dependent equation designed to settle quickly to a steady state. Computed lift drag ratios are consistent with the results of wind tunnel tests of a yawed wing conducted by R. T. Jones (1972).-

Jameson, A.↗
NASA NTRS2005

Using In-Situ Deposition of Metallic Thin Films on Mars to Monitor Atmospheric H20

We describe the use of a novel sensor, designed to characterize the reactive nature of the Martian atmosphere, to also characterize the instantaneous abundance of atmospheric H,O. The sensor deposits, in situ, a thin silver film onto a sapphire substrate and monitors oxidation by measuring resistance of the Ag film during both deposition and subsequent oxidation [1,2]. . The evaporation source is placed in the center of a hollow, open-ended tube. On flash heating the source, evaporated metallic silver rapidly reacts with oxidizing gases in the tube, depositing on the tube walls as a resisitive Ag oxide film. Unoxidized silver deposits over the Ag oxides, once the oxidizing gases in the vicinity of the source have been consumed. Since the ends of the tube are open, atmospheric gases in the tube cause a time delay as the evaporated silver initially reacts with the available O2, and H2O; once oxidizing gases in the tube are significantly depleted, a silver film closes the chemiresistor circuit. In principle this operation mode provides a repeatable measure of the variable H2O abundance, since O2, levels are constant in the atmosphere. To explore the utility of the instrument as an H2O sensor, predict its behavior, and identify possible failure modes, we developed a numerical model of the instrument, and exercised it for Mars conditions. The model predicts the behavior of the electrical circuit, the temperature dependence of resistivity for each component, and the resultant Joule heating. The model balances Joule heating against radiation, sensible heat loss to ambient CO2, and, latent heat loss from sublimating Ag. The flux of Ag atoms from the source is tracked continuously. In the gas phase, the number density of Ag, O2, and H2O is calculated, along with their reaction rates on collision. The model suggests that Ag substantially depletes H2O only near the center of the tube. The model supports the hypothesis that the onset of high conductivity between the A u electrodes is a function of the H2O abundance in the ambient gas, but only to a limit; when H2O abundances are buffered at or above 240K (an H2O abundance that would not have occurred on Mars), metallic Ag never deposits in excess of Ago, and the circuit does not close. A significant difference in the Mars simulation is that the Ag source sublimates more quickly, primarily because of differences in sensible heat fluxes from the source. This allows subsequent heating of the W filament used to support the Ag source. Had the originally-designed experimental sequence been carried out on Mars, the filament might have melted, making subsequent investigations impossible.

Zent, A. P.↗
NASA NTRS2011

Pattern Recognition for a Flight Dynamics Monte Carlo Simulation

The design, analysis, and verification and validation of a spacecraft relies heavily on Monte Carlo simulations. Modern computational techniques are able to generate large amounts of Monte Carlo data but flight dynamics engineers lack the time and resources to analyze it all. The growing amounts of data combined with the diminished available time of engineers motivates the need to automate the analysis process. Pattern recognition algorithms are an innovative way of analyzing flight dynamics data efficiently. They can search large data sets for specific patterns and highlight critical variables so analysts can focus their analysis efforts. This work combines a few tractable pattern recognition algorithms with basic flight dynamics concepts to build a practical analysis tool for Monte Carlo simulations. Current results show that this tool can quickly and automatically identify individual design parameters, and most importantly, specific combinations of parameters that should be avoided in order to prevent specific system failures. The current version uses a kernel density estimation algorithm and a sequential feature selection algorithm combined with a k-nearest neighbor classifier to find and rank important design parameters. This provides an increased level of confidence in the analysis and saves a significant amount of time.

Restrepo, Carolina↗
NASA NTRSDate not supplied

Ballistic Lunar Transfers to Near Rectilinear Halo Orbit: Operational Considerations

This paper presents a study of ballistic lunar transfer (BLT) trajectories from Earth launch to insertion into a near rectilinear halo orbit (NRHO). BLTs have favorable properties for uncrewed launches to orbits in the vicinity of the Moon, such as dramatically reduced spacecraft ΔV requirements. Results are described from a detailed set of related mission design studies: BLTs with and without an outbound lunar flyby, insertion and rendezvous of a single spacecraft with a target in an NRHO, and insertion and rendezvous of multiple spacecraft with a target NRHO in quick succession. Monte Carlo analyses are presented of simulated rendezvous operations with realistic errors. These analyses are presented to inform future missions to NRHOs.

Nathan L Parrish↗
NASA NTRS2019

Measuring the D/H Ratios of Exoplanets and Brown Dwarfs

The relative abundance of deuterium and hydrogen is a potent tracer of planet formation and evolution. Jupiter and Saturn have protosolar atmospheric D/H ratios, a relic of substantial gas accretion from the nebula, while the atmospheres of Neptune and Uranus are enhanced in D by accretion of ices into their envelopes. For terrestrial planets, D/H ratios are used to determine the mechanisms of volatile delivery and subsequent atmosphere loss over the lifetime of the planet. Planets and brown dwarfs more massive than ~13 M(J) quickly fuse their initial D reservoir. Here, we simulate spectra for giant exoplanets and brown dwarfs (2 M(Neptune) to ~10 M(Jupiter)) from T(eff) = 200–1800 K including both CH3D and HDO to determine the observability of these dominant deuterium isotopologues in mid-infrared thermal emission spectra. Colder objects have stronger molecular features in their spectra, due to the temperature dependence of molecular cross sections. CH3D is easier to observe than HDO at all temperatures considered, due to the strength of its absorption bands and locations of features at wavelengths with few other strong absorption features. We predict that for nearby cool brown dwarfs, the CH3D abundance can be measured at high signal to noise with the James Webb Space Telescope (JWST); for objects from 200 to 800 K closer than 10 pc, a protosolar D/H ratio would be readily observable in 2.5 hr. Moderately young Jupiter-mass planets (100–300 Myr) and young Neptunes (10 Myr) may be discovered with JWST and provide the best targets for detecting deuterium on an exoplanet in the coming decade. Future telescope designs should consider the importance of isotopes for understanding the formation and evolution of planetary atmospheres.

Caroline V. Morley↗
NASA NTRSDate not supplied

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben D Phillips↗
NASA NTRSDate not supplied

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben Phillips↗
DOE OSTI2020

Finite temperature auxiliary field quantum Monte Carlo in the canonical ensemble

Finite temperature auxiliary field-based quantum Monte Carlo methods, including determinant quantum Monte Carlo and Auxiliary Field Quantum Monte Carlo (AFQMC), have historically assumed pivotal roles in the investigation of the finite temperature phase diagrams of a wide variety of multidimensional lattice models and materials. Despite their utility, however, these techniques are typically formulated in the grand canonical ensemble, which makes them difficult to apply to condensates such as superfluids and difficult to benchmark against alternative methods that are formulated in the canonical ensemble. Working in the grand canonical ensemble is furthermore accompanied by the increased overhead associated with having to determine the chemical potentials that produce desired fillings. Given this backdrop, in this work, we present a new recursive approach for performing AFQMC simulations in the canonical ensemble that does not require knowledge of chemical potentials. To derive this approach, we exploit the convenient fact that AFQMC solves the many-body problem by decoupling many-body propagators into integrals over one-body problems to which non-interacting theories can be applied. We benchmark the accuracy of our technique on illustrative Bose and Fermi–Hubbard models and demonstrate that it can converge more quickly to the ground state than grand canonical AFQMC simulations. We believe that our novel use of HS-transformed operators to implement algorithms originally derived for non-interacting systems will motivate the development of a variety of other methods and anticipate that our technique will enable direct performance comparisons against other many-body approaches formulated in the canonical ensemble.

Shen, Tong (ORCID:0000000206292468)↗
NASA NTRS1993

Development and operation of a real-time simulation at the NASA Ames Vertical Motion Simulator

The Vertical Motion Simulator (VMS) facility at the NASA Ames Research Center combines the largest vertical motion capability in the world with a flexible real-time operating system allowing research to be conducted quickly and effectively. Due to the diverse nature of the aircraft simulated and the large number of simulations conducted annually, the challenge for the simulation engineer is to develop an accurate real-time simulation in a timely, efficient manner. The SimLab facility and the software tools necessary for an operating simulation will be discussed. Subsequent sections will describe the development process through operation of the simulation; this includes acceptance of the model, validation, integration and production phases.

Sweeney, Christopher↗
NASA NTRS1997

A Java-Enabled Interactive Graphical Gas Turbine Propulsion System Simulator

This paper describes a gas turbine simulation system which utilizes the newly developed Java language environment software system. The system provides an interactive graphical environment which allows the quick and efficient construction and analysis of arbitrary gas turbine propulsion systems. The simulation system couples a graphical user interface, developed using the Java Abstract Window Toolkit, and a transient, space- averaged, aero-thermodynamic gas turbine analysis method, both entirely coded in the Java language. The combined package provides analytical, graphical and data management tools which allow the user to construct and control engine simulations by manipulating graphical objects on the computer display screen. Distributed simulations, including parallel processing and distributed database access across the Internet and World-Wide Web (WWW), are made possible through services provided by the Java environment.

Reed, John A.↗
DOE OSTI2022

liionpack: A Python package for simulating packs of batteries with PyBaMM

Electrification of transport and other energy intensive activities is of growing importance as it provides an underpinning method to reduce carbon emissions. With an increase in reliance on renewable sources of energy and a reduction in the use of more predictable fossil fuels in both stationary and mobile applications, energy storage will play a pivotal role and batteries are currently the most widely adopted and versatile form. Therefore, understanding how batteries work, how they degrade, and how to optimize and manage their operation at large scales is critical to achieving emission reduction targets. The electric vehicle (EV) industry requires a considerable number of batteries even for a single vehicle, sometimes numbering in the thousands if smaller cells are used, and the dynamics and degradation of these systems, as well as large stationary power systems, is not that well understood. As increases in the efficiency of a single battery become diminishing for standard commercially available chemistries, gains made at the system level become more important and can potentially be realised more quickly compared with developing new chemistries. Mathematical models and simulations provide a way to address these challenging questions and can aid the engineer and designers of batteries and battery management systems to provide longer lasting and more efficient energy storage systems.

25 ENERGY STORAGE↗
DOE OSTI2020

An Enhanced Vertical Ground Heat Exchanger Model for Whole-Building Energy Simulation

This paper presents an enhanced vertical ground heat exchanger (GHE) model for whole-building energy simulation (WBES). WBES programs generally have computational constraints that affect the development and implementation of component simulation sub-models. WBES programs require models that execute quickly and efficiently due to how the programs are utilized by design engineers. WBES programs also require models to be formulated so their performance can be determined from boundary conditions set by upstream components and environmental conditions. The GHE model developed during this work utilizes an existing response factor model and extends its capabilities to accurately and robustly simulate at timesteps that are shorter than the GHE transit time. This was accomplished by developing a simplified dynamic borehole model and then exercising that model to generate exiting fluid temperature response factors. This approach blends numerical and analytical modeling methods. The existing response factor models are then extended to incorporate the exiting fluid temperature response factor to provide a better estimate of the GHE exiting fluid temperature at short simulation timesteps.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1994

Program Simulates Spacecraft Communication Scenarios

Dynamic Environment Communications Alalysis Testbed (DECAT) computer program is modular simulation program. Computes effects of motion, antenna radiation patterns, noise, interference, and other phenomena. Flexibility enables users to analyze many communications scenarios quickly and easily, eliminating need for users to create specific computer programs. Users create simulations involving any number of vehicles, receivers, transmitters, and antennas via graphical user interface (GUI). DECAT GUI implemented by use of software tool called "Transportable Applications Environment Plus" (TAE Plus). Written in C language. Graphical user interface requires TAE Plus, Version 5.1 package available from COSMIC (GSC-13463).

Land, Kenneth P.↗
NASA NTRS1986

Simulation of the space station information system in Ada

The Flexible Ada Simulation Tool (FAST) is a discrete event simulation language which is written in Ada. FAST has been used to simulate a number of options for ground data distribution of Space Station payload data. The fact that Ada language is used for implementation has allowed a number of useful interactive features to be built into FAST and has facilitated quick enhancement of its capabilities to support new modeling requirements. General simulation concepts are discussed, and how these concepts are implemented in FAST. The FAST design is discussed, and it is pointed out how the used of the Ada language enabled the development of some significant advantages over classical FORTRAN based simulation languages. The advantages discussed are in the areas of efficiency, ease of debugging, and ease of integrating user code. The specific Ada language features which enable these advances are discussed.

Spiegel, James R.↗
NASA NTRS2006

Control Room Training for the Hyper-X Program Utilizing Aircraft Simulation

The NASA Dryden Flight Research Center flew two Hyper-X Research Vehicles and achieved hypersonic speeds over the Pacific Ocean in March and November 2004. To train the flight and mission control room crew, the NASA Dryden simulation capability was utilized to generate telemetry and radar data, which was used in nominal and emergency mission scenarios. During these control room training sessions, personnel were able to evaluate and refine data displays, flight cards, mission parameter allowable limits, and emergency procedure checklists. Practice in the mission control room ensured that all primary and backup Hyper-X staff were familiar with the nominal mission and knew how to respond to anomalous conditions quickly and successfully. This paper describes the technology in the simulation environment and the mission control center, the need for and benefit of control room training, and the rationale and results of specific scenarios unique to the Hyper-X research missions.

Lux-Baumann, Jessica R.↗
NASA NTRS2006

Control Room Training for the Hyper-X Project Utilizing Aircraft Simulation

The NASA Dryden Flight Research Center flew two Hyper-X research vehicles and achieved hypersonic speeds over the Pacific Ocean in March and November 2004. To train the flight and mission control room crew, the NASA Dryden simulation capability was utilized to generate telemetry and radar data, which was used in nominal and emergency mission scenarios. During these control room training sessions personnel were able to evaluate and refine data displays, flight cards, mission parameter allowable limits, and emergency procedure checklists. Practice in the mission control room ensured that all primary and backup Hyper-X staff were familiar with the nominal mission and knew how to respond to anomalous conditions quickly and successfully. This report describes the technology in the simulation environment and the Mission Control Center, the need for and benefit of control room training, and the rationale and results of specific scenarios unique to the Hyper-X research missions.

Lux-Baumann, Jesica↗
NASA NTRS1991

A two-dimensional numerical investigation of the interaction between sea breezes and deep convection over the Florida peninsula

The Colorado State University Regional Atmospheric Modeling System is used to investigate the interaction between sea breezes and deep convection over the Florida peninsula, and it is shown that this model can simulate the broad features of the three characteristic types of convection systems classified by Blanchard and Lopez (1985). In sensitivity tests performed for a variety of wind and thermodynamic profiles and for different soil-moisture contents, it was found that increases in the low-level temperature and in moisture content speeded up the development of convection. It was found that the dry-soil simulation produced rapidly developing sea breezes that moved inland quickly, while the moist soil case produced a much more slowly developing sea breeze. The total rainfall over the peninsula for the dry-soil case was greater than for the moist soil; it is suggested that the enhanced surface heat fluxes for the dry soil case create stronger low-level convergence over the peninsula (than in the moist-soil case) to force the convection.

Nicholls, Melville E.↗