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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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An extensive investigation was conducted to provide realistic error models for Global Positioning System (GPS) related numerical simulation. This study considers most of the important error sources for measurement and dynamic models which are currently being used for GPS geodetic applications. These error models were evaluated by comparing with real GPS data.
Models are an important tool to predict Earth system dynamics. An accurate prediction of future states of ecosystems depends on not only model structures but also parameterizations. Model parameters can be constrained by data assimilation. However, applications of data assimilation to ecology are restricted by highly technical requirements such as model-dependent coding. To alleviate this technical burden, we developed a model-independent data assimilation (MIDA) module. MIDA works in three steps including data preparation, execution of data assimilation, and visualization. The first step prepares prior ranges of parameter values, a defined number of iterations, and directory paths to access files of observations and models. The execution step calibrates parameter values to best fit the observations and estimates the parameter posterior distributions. The final step automatically visualizes the calibration performance and posterior distributions. MIDA is model independent, and modelers can use MIDA for an accurate and efficient data assimilation in a simple and interactive way without modification of their original models. We applied MIDA to four types of ecological models: the data assimilation linked ecosystem carbon (DALEC) model, a surrogate-based energy exascale earth system model: the land component (ELM), nine phenological models and a stand-alone biome ecological strategy simulator (BiomeE). The applications indicate that MIDA can effectively solve data assimilation problems for different ecological models. Additionally, the easy implementation and model-independent feature of MIDA breaks the technical barrier of applications of data–model fusion in ecology. MIDA facilitates the assimilation of various observations into models for uncertainty reduction in ecological modeling and forecasting.
Provide a graphical user interface based simulator for desktop training, operations and procedure development and system reference. This simulator allows for engineers to train and further understand the dynamics of their system from their local desktops. It allows the users to train and evaluate their system at a pace and skill level based on the user's competency and from a perspective based on the user's need. The simulator will not require any special resources to execute and should generally be available for use. The interface is based on a concept of presenting the model of the system in ways that best suits the user's application or training needs. The three levels of views are Component View, the System View (overall system), and the Console View (monitor). These views are portals into a single model, so changing the model from one view or from a model manager Graphical User Interface will be reflected on all other views.
The use of Tri‐gas in rocket propulsion systems is somewhat of a new technology. This paper defines Tri‐gas as a mixture of gases composed largely of helium with a small percentage of a stoichiometric mixture of hydrogen and oxygen. When exposed to a catalyst the hydrogen and oxygen in the mixture combusts, significantly raising the temperature of the mixture. The increase in enthalpy resulting from the combustion process significantly decreases the required quantity of gas needed to pressurize the ullage of the vehicle propellant tanks. The objective of this effort was to better understand the operating characteristics of Tri‐gas in a pressurization system with low temperature applications. In conjunction with ongoing programs at NASA Marshall Space Flight Center, an effort has been undertaken to evaluate the operating characteristics of Tri‐gas through modeling and bench testing. Through improved understanding of the operating characteristics, the risk of using this new technology in a launch vehicle propulsion system was reduced. Bench testing of Tri‐gas was a multistep process that targeted gas characteristics and performance aspects that pose a risk to application in a pressurization system. Pressurization systems are vital to propulsion system performance. Keeping a target ullage pressure in propulsions tanks is necessary to supply propellant at the conditions and flow rates required to maintain desired engine functionality. The first component of testing consisted of sampling Tri‐gas sources that had been stagnant for various lengths of time in order to determine the rate at which stratification takes place. Second, a bench test was set up in which Tri‐gas was sent through a catalyst bed. This test was designed to evaluate the performance characteristics of Tri‐gas, under low temperature inlet temperatures, in a flight‐like catalyst bed reactor. The third, most complex, test examined the performance characteristics of Tri‐gas at low temperature temperatures in a test configuration built to more closely resemble a vehicle pressurization system. The results of these bench tests address various risks that all relate to underperformance of Tri‐gas pressurization systems.
In complex physical process characterization, such as the measurement of the regression rate for solid hybrid rocket fuels, where both the observation data and the model used have uncertainties originating from multiple sources, combining these in a systematic way for quantities of interest (QoI) remains a challenge. In this paper, we present a forward propagation uncertainty quantification (UQ) process to produce a probabilistic distribution for the observed regression rate r. We characterized two input data uncertainty sources from the experiment (the distortion from the camera U c and the non-zero-angle fuel placement U Y ), the prediction and model form uncertainty from the deep neural network (U m ), as well as the variability from the manually segmented images used for training it (U s ). Here, we conducted seven case studies on combinations of these uncertainty sources with the model form uncertainty. The main contribution of this paper is the investigation and inclusion of the experimental image data uncertainties involved, and how to include them in a workflow when the QoI is the result of multiple sequential processes.
An overview is given of the flight planning activities to date in the current National Aero-Space Plane (NASP) program. The government flight-envelope expansion concept and other design flight operational assessments are discussed. The NASA Dryden NASP real-time simulator configuration is examined and hypersonic flight planning simulation propulsion modeling requirements are described. The major propulsion modeling techniques developed by the Edwards flight test team are outlined, and the application value of techniques for developmental hypersonic vehicles are discussed.
The rapid development of energy storage technologies is motivating researchers to understand the possible value of energy storage. This paper evaluates the multiservice dispatch of distribution-sited energy storage systems with realistic degradation models by integrating a multiservice optimization model with a distribution system simulator. This work attempts to define the theoretical value energy storage can bring when multiple value streams are considered in the modeling environment. Use cases presented in this paper deliver multiple services to both distribution and transmission stakeholders that can provide positive net value to the electricity system under prevailing energy storage cost structures. Furthermore, this work was performed in collaboration with a distribution utility to help utility personnel understand the value distributed energy storage can provide by examining different utility use cases without considering implementation costs.
Consistent modeling assumptions across any large project are crucial to minimize errors between different approaches. Use of consistent material and fluid properties across a large project supports consistent interpretation and application within modeling and simulation results as well as their relevancy to operational systems. NASA’s Space Nuclear Propulsion program dedicates extensive resources towards establishing consistent and, to the extent possible, accurate property databases for its internal staff and all external partners. This work highlights the extensive research performed to modernize the fluid property database of hydrogen which is the leading propellant option for in-space nuclear propelled spacecraft. Specifically, the parahydrogen spin state is of interest since the propellant is stored in a near normal boiling point liquid state which results in it consisting almost entirely of the parahydrogen spin isomer. This database tool has taken recent NASA work and modernized it into a python-based package for easy usage across all modeling entities. The package allows users to provide temperature and pressure pairs along with their desired output properties to yield results accounting for both real-gas and equilibrium dissociation effects while also sharing the default thermodynamic reference state provided by the National Institute of Standards and Technology (NIST) Standard Database 23. The suite also includes advanced capabilities to increase usability, such as on-the-fly interpolation and multidimensional plotting.
Consistent modeling assumptions across any large project are crucial to minimize errors between different approaches. Use of consistent material and fluid properties across a large project supports consistent interpretation and application within modeling and simulation results as well as their relevancy to operational systems. NASA’s Space Nuclear Propulsion program dedicates extensive resources towards establishing consistent and, to the extent possible, accurate property databases for its internal staff and all external partners. This work highlights the extensive research performed to modernize the fluid property database of hydrogen which is the leading propellant option for in-space nuclear propelled spacecraft. Specifically, the parahydrogen spin state is of interest since the propellant is stored in a near normal boiling point liquid state which results in it consisting almost entirely of the parahydrogen spin isomer. This database tool has taken recent NASA work and modernized it into a python-based package for easy usage across all modeling entities. The package allows users to provide temperature and pressure pairs along with their desired output properties to yield results accounting for both real-gas and equilibrium dissociation effects while also sharing the default thermodynamic reference state provided by the National Institute of Standards and Technology (NIST) Standard Database 23. The suite also includes advanced capabilities to increase usability, such as on-the-fly interpolation and multidimensional plotting.
A comprehensive study of braze alloy selection process and strength characterization with application to wind tunnel models is presented. The applications for this study include the installation of stainless steel pressure tubing in model airfoil sections make of 18 Ni 200 grade maraging steel and the joining of wing structural components by brazing. Acceptable braze alloys for these applications are identified along with process, thermal braze cycle data, and thermal management procedures. Shear specimens are used to evaluate comparative shear strength properties for the various alloys at both room and cryogenic (-300 F) temperatures and include the effects of electroless nickel plating. Nickel plating was found to significantly enhance both the wetability and strength properties for the various braze alloys studied. The data are provided for use in selecting braze alloys for use with 18 Ni grade 200 steel in the design of wind tunnel models to be tested in an ambient or cryogenic environment.
This study concerns the rotor dynamic characteristics of fluid-encompassed rotors, with special emphasis on shrouded pump impellers. The core of the study is a versatile and categorically new finite-element-based perturbation model, which is based on a rigorous flow analysis and what we have generically termed the 'virtually' deformable finite-element approach. The model is first applied to the case of a smooth annular seal for verification purposes. The rotor excitation components, in this sample problem, give rise to a purely cylindrical, purely conical, and a simultaneous cylindrical/conical rotor whirl around the housing centerline. In all cases, the computed results are compared to existing experimental and analytical data involving the same seal geometry and operating conditions. Next, two labyrinth-seal configurations, which share the same tooth-to-tooth chamber geometry but differ in the total number of chambers, were investigated. The results, in this case, are compared to experimental measurements for both seal configurations. The focus is finally shifted to the shrouded-impeller problem, where the stability effects of the leakage flow in the shroud-to-housing secondary passage are investigated. To this end, the computational model is applied to a typical shrouded-impeller pump stage, fabricated and rotor dynamically tested by Sulzer Bros., and the results compared to those of a simplified 'bulk-flow' analysis and Sulzer Bros.' test data. In addition to assessing the computed rotor dynamic coefficients, the shrouded-impeller study also covers a controversial topic, namely that of the leakage-passage inlet swirl, which was previously cited as the origin of highly unconventional (resonance-like) trends of the fluid-exerted forces. In order to validate this claim, a 'microscopic' study of the fluid/shroud interaction mechanism is conducted, with the focus being on the structure of the perturbed flow field associated with the impeller whirl. The conclusions of this study were solidified by the outcome of a numerical-certainty exercise, where the grid dependency of the numerical results is objectively examined. The final phase of the shrouded-impeller investigation involves the validation of a built-in assumption, in all other perturbation models, whereby single-harmonic tangential distributions of all the flow thermophysical properties are imposed. The last phase of the investigation course is aimed at verifying the fine details of the perturbed flow field in light of recent set of detailed LDA measurements in a smooth annular seal. Grid dependency of the fluid-induced forces is also investigated, and specific recommendations are made.
Accurate estimates of electron-capture cross sections at energies relevant to energetic neutral atom (ENA) modeling (approx few MeV per nucleon) and for multi-electron ions must rely on first-principles approaches and/or detailed quantum-mechanical simulation of the collision process. Kuang's semi-classical approach offers a middle-ground, elegant and efficient way to arrive at these estimates. We shall present a sample application and current progress in applying and extending Kuang's formalism to ENA modeling.
Accurately modeling real-world systems requires scientific applications at exascale to generate massive amounts of data and manage data storage efficiently. However, parallel input and output (I/O) faces challenges due to new application workflows and the state-of-the-art memory, interconnect, and storage architectures considered in exascale designs. The storage hierarchy has expanded with node-local persistent memory, solid-state storage, and traditional disk and tape-based storage, thus requiring efficiency at each layer and much more efficient data movement among these layers. This paper discusses how the ExaHDF5 project improved the I/O performance and data management for exascale architectures by enhancing HDF5, a widely used parallel I/O library. The team developed an Asynchronous I/O Virtual Object Layer (VOL) connector that allowed overlapping I/O with computation. They also created a Cache VOL to complement asynchronous I/O by incorporating fast storage layers, such as burst buffer and node-local storage, into the parallel I/O workflow through caching and staging data. Additionally, the team enabled data aggregation and I/O at the node level by using a Subfiling Virtual File Driver (VFD). To demonstrate superior I/O performance with HDF5 at exascale, the ExaHDF5 team collaborated with several exascale applications. In this paper, we show I/O performance improvements for three applications: Cabana (a particle-based simulation library), EQSIM (a regional earthquake simulation software), and E3SM (a climate system modeling library).
Discussion of 'model following,' a term used to describe a class of problems characterized by having two dynamic systems, generically known as the 'plant' and the 'model,' it being required to find a controller to attach to the plant so as to make the resultant compensated system behave, in an input/output sense, in the same way as the model. The approach presented to the problem takes a structural point of view. The result is a complex but informative definition which solves the problem as posed. The application of both the algorithm and its basis, equicontrollability, to the decoupling problem is considered.
Plume impingement effects of the service module reaction control system thruster firings were studied to determine if previous flight experience would support the current plume impingement model for the orbiter reaction control system engines. The orbiter reaction control system is used for rotational and translational maneuvers such as those required during rendezvous, braking, docking, and station keeping. Therefore, an understanding of the characteristics and effects of the plume force fields generated by the reaction control system thruster firings were examined to develop the procedures for orbiter/payload proximity operations.
As advanced nuclear technologies continue to develop, the need for the flexible operation and generation of these advanced reactors becomes necessary to maximize economic potential. As large-scale experiments are not always feasible, modeling and simulations of advanced reactors play a crucial role in design optimization and analysis. The SAM (System Analysis Module) code developed at Argonne National Laboratory is a state-of-the-art system-level thermal-hydraulic code aimed at simulating advanced reactor systems. Recent code developments have implemented two-phase flow modeling using the homogeneous equilibrium model, and a new steam generator component has been developed to utilize the two-phase flow implementation. In addition to verification tests, a load-following simulation was performed to model a realistic load-following transient in a proposed integrated system consisting of a conceptual advanced reactor known as the Advanced Burner Test Reactor (ABTR) and thermal energy storage (TES) tanks. The integrated system model uses two large TES tanks designed for sodium and a model helical coil steam generator to simulate the operational load-following transient. The flow rates of the feedwater and secondary loops are regulated to meet a prescribed steam generator load consistent with the electricity demand over a 24-h period. In conclusion, the results found the ABTR system was able to maintain stable reactor conditions and primary- and secondary-side characteristics over the course of the load-following transient.
There have been ongoing efforts in the Aeronautics Systems Analysis Branch at NASA Langley Research Center to develop a suite of integrated physics-based computational utilities suitable for modeling and analyzing extended-duration missions carried out using solar powered aircraft. From these efforts, SolFlyte has emerged as a state-of-the-art vehicle analysis and mission simulation tool capable of modeling both heavier-than-air (HTA) and lighter-than-air (LTA) vehicle concepts. This study compares solar powered airplane and airship station-keeping capability during a variety of high altitude missions, using SolFlyte as the primary analysis component. Three Unmanned Aerial Vehicle (UAV) concepts were designed for this study: an airplane (Operating Empty Weight (OEW) = 3285 kilograms, span = 127 meters, array area = 450 square meters), a small airship (OEW = 3790 kilograms, length = 115 meters, array area = 570 square meters), and a large airship (OEW = 6250 kilograms, length = 135 meters, array area = 1080 square meters). All the vehicles were sized for payload weight and power requirements of 454 kilograms and 5 kilowatts, respectively. Seven mission sites distributed throughout the United States were selected to provide a basis for assessing the vehicle energy budgets and site-persistent operational availability. Seasonal, 30-day duration missions were simulated at each of the sites during March, June, September, and December; one-year duration missions were simulated at three of the sites. Atmospheric conditions during the simulated missions were correlated to National Climatic Data Center (NCDC) historical data measurements at each mission site, at four flight levels. Unique features of the SolFlyte model are described, including methods for calculating recoverable and energy-optimal flight trajectories and the effects of shadows on solar energy collection. Results of this study indicate that: 1) the airplane concept attained longer periods of on-site capability than either airship concept, and 2) the airship concepts can attain higher levels of energy collection and storage than the airplane concept; however, attaining these energy benefits requires adverse design trades of reduced performance (small airship) or excessive solar array area (large airship).
Previously, a predictive model was developed to identify optimal blends of expensive high-quality and cheaper low-quality feedstocks for a given geographical location that can deliver high sugar yields. Here, the optimal process conditions were tested for application at commercially-relevant higher biomass loadings. We observed lower sugar yields but 100% conversion to ethanol from a blend that contained only 20% high-quality feedstock. The impact of applying this predictive model simultaneously with least cost formulation model for a biorefinery location outside of the US Corn Belt in Lee County, Florida was investigated. A blend ratio of 0.30 EC, 0.45 SG, and 0.25 CS in Lee County was necessary to produce sugars at high yields and ethanol at a capacity of 50 MMGY. This work demonstrates utility in applying predictive model and LCF to reduce feedstock costs and supply chain risks while optimizing for product yields.