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All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Reusing Data and Metadata to Create New Metadata Through Machine-Learning & Other Programmatic Methods

Recent improvements in natural language processing (NLP) enable metadata to be created programmatically from reused original metadata or even the dataset itself. Transfer-learning applied to NLP has greatly improved performance and reduced training data requirements. In this talk, we’ll compare machine-generated metadata to human-generated metadata and discuss characteristics of metadata and data archives that affect suitability for machine-learning reuse of metadata. Where as human-generated metadata is often populated once, populated from the perspective of data supplier, populated by many individuals with different words for the same thing, and limited in length, machine-generated metadata can be updated any number of times, generated from the perspective of any user, constrained to a standardized set of terms that can be evolved over time, and be any length required. Machine-learning generated metadata offers benefits but also additional needs in terms of version control, process transparency, human-computer interaction, and IT requirements. As a successful example, we’ll discuss how a dataset of abstracts and associated human-tagged keywords from a standardized list of several thousand keywords were used to create a machine-learning model that predicted keyword metadata for open-source code projects on code.nasa.gov. We’ll also discuss a less successful example from data.nasa.gov to show how data archive architecture and characteristics of initial metadata can be strong controls on how easy it is to leverage programmatic methods to reuse metadata to create additional metadata.

Gosses, Justin↗
NASA NTRS2019

Dynamic Modeling of Gaseous Multicomponent Trace Contaminant Adsorption

Activated carbon is a porous material in the Trace Contaminant Control (TCC) system that physically adsorbs volatile organic compounds (VOCs) generated within spacecraft and spacesuit environments. Several isotherm models exist to predict adsorption equilibria for processes involving multicomponent systems. This paper investigates the use of Ideal Adsorbed Solution Theory (IAST) for predicting multicomponent trace contaminant adsorption behavior using single-component isotherms based on potential theory. Developing simulations for experimental breakthrough curves will gauge the validity on the sizing and design of TCC architecture. Model results on predicting bed performance and roll-up effects are compared with available multicomponent test data.

Ideal Adsorbed Solution Theory (IAST)↗
NASA NTRS2022

Limitations in Representation of Physical Processes Prevents Successful Simulation of PM2.5 During KORUS-AQ

High levels of fine particulate matter (PM2.5) pollution in East Asia often exceed local air quality standards. Observations from the Korea United States-Air Quality (KORUS-AQ) field campaign in May and June 2016 showed that development of extreme pollution (haze) occurred through a combination of long-range transport and favorable meteorological conditions that enhanced local production of PM2.5. Atmospheric models often have difficulty simulating PM2.5 chemical composition during haze, which is of concern for the development of successful control measures. We use observations from KORUS-AQ to examine the ability of the GEOS-Chem chemical transport model to simulate PM2.5 composition throughout the campaign and identify the mechanisms driving the pollution event. At the surface, the model underestimates sulfate by -64% but overestimates nitrate by +36%. The largest underestimate in sulfate occurs during the pollution event, where models typically struggle to generate elevated sulfate concentrations due to missing heterogeneous chemistry in aerosol liquid water in the polluted boundary layer. Hourly surface observations show that the model nitrate bias is driven by an overestimation of the nighttime peak. In the model, nitrate formation is limited by the supply of nitric acid, which is biased by +100% against aircraft observations. We hypothesize that this is due to a large missing sink, which we implement here as a factor of five increase in dry deposition. We show that the resulting increased deposition velocity is consistent with observations of total nitrate as a function of photochemical age. The model does not account for factors such as the urban heat island effect or the heterogeneity of the built-up urban landscape resulting in insufficient model turbulence and surface area over the study area that likely results in insufficient dry deposition. Other species such as NH3 could be similarly affected but were not measured during the campaign. Nighttime production of nitrate is driven by NO2 hydrolysis in the model, while observations show that unexpectedly elevated nighttime ozone (not present in the model) should result in N2O5 hydrolysis as the primary pathway. The model is unable to represent nighttime ozone due to an overly rapid collapse of the afternoon mixed layer and excessive titration by NO. We attribute this to missing nighttime heating driving deeper nocturnal mixing that would be expected to occur in a city like Seoul. This urban heating is not considered in air quality models run at large enough scales to treat both local chemistry and long-range transport. Key model failures in simulating nitrate, mainly overestimated daytime nitric acid, incorrect representation of nighttime chemistry, and an overly shallow and insufficiently turbulent nighttime mixed layer, exacerbate the model’s inability to simulate the buildup of PM2.5 during haze pollution. To address the underestimate in sulfate most evident during the haze event, heterogeneous aerosol uptake of SO2 is added to the model which previously only considered aqueous production of sulfate from SO2 in cloud water. Implementing a simple parameterization of this chemistry improves the model abundance of sulfate but degrades the SO2 simulation implying that emissions are underestimated. We find that improving model simulations of sulfate has direct relevance to determining local vs. transboundary contributions to PM2.5. During the haze pollution event, the inclusion of heterogeneous aerosol uptake of SO2 decreases the fraction of PM2.5 attributable to long-range transport from 66% to 54%. Locally-produced sulfate increased from 1% to 25% of locally-produced PM2.5, implying that local emissions controls would have a larger effect than previously thought. However, this additional uptake of SO2 is coupled to the model nitrate prediction which affects the aerosol liquid water abundance and chemistry driving sulfate-nitrate-ammonium partitioning. An additional simulation of the haze pollution with heterogeneous uptake of SO2 to aerosol and simple improvements to the model nitrate simulation results in 30% less sulfate due to 40% less nitrate and aerosol water, and results in an underestimate of sulfate during the haze event. Future studies need to better consider the impact of model physical processes such as dry deposition and nighttime boundary layer mixing on the simulation of nitrate and the effect of improved nitrate simulations on the overall simulation of secondary inorganic aerosol (sulfate+nitrate+ammonium) in East Asia. Foreign emissions are rapidly changing, increasing the need to understand the impact of local emissions on PM2.5 in South Korea to ensure continued air quality improvements.

Katherine R. Travis↗
NASA NTRSDate not supplied

Supervisory On-line Optimal Control of an Electric Power Microgrid Design for Lunar Habitation

The following article describes an optimal control algorithm for the operation and study of an electric microgrid designed to power a lunar habitat. A photovoltaic (PV) generator powers the habitat and the presence of predictable lunar eclipses necessitates a system to prioritize and control loads within the microgrid. The algorithm consists of a reduced order model (ROM) that describes the microgrid, a discretization of the equations that result from the ROM, and an optimization formulation that controls the microgrid’s behavior. In order to validate this approach, the paper presents results from simulation based on lunar eclipse information and a schedule of intended loads.

Joseph Young↗
NASA NTRS2024

A Summary of the 2023 Joint High-Speed Boundary Layer Transition Workshop

A joint workshop between the Air Force Office of Scientific Research, the Office of Naval Research, and the NASA Hypersonic Technology Project was held in June 2023 on the topic of high-speed boundary-layer transition. The purpose of this workshop was to gather subject matter experts in the areas of supersonic and hypersonic boundary-layer transition in the areas of geometries of interest, computational methods, facilities and diagnostics, flight experiments, flow control, and new approaches and to discuss the current state of the art in the field. As gaps and accomplishments were identified, roadmaps were also created to guide future investments in these areas. The top recommendations are (1) to define relevant common geometries of interest that can be worked by multiple research groups; (2) improve modeling of high-enthalpy flows involving chemistry and ablation, studies of receptivity of freestream disturbances and atmospheric particulates into the boundary layer, surface feature characterization and modeling of changes to geometry; (3) design and determine viable flow control methods; and (4) move towards incorporating boundary layer transition prediction into a standard practice for design of high-speed vehicles. To execute this last recommendation successfully, investments beyond fundamental (basic and early applied) research are needed.

boundary layer transition↗
NASA NTRS2022

Hybrid data-driven and model-informed online tool wear detection in milling machines

Precision machining tool wear is responsible for low product throughput and quality. Monitoring the tool wear online is vital to prevent degradation in machining quality. However, direct real-time tool wear measurement is not practical. This paper presents residual-based anomaly detection models, combining a hybrid model comprised of a physics-based model and a data-driven model (a decision tree or a neural network) to predict signals of interest (e.g., power or forces) under nominal conditions, followed by Page’s cumulative sum test for detecting tool wear on-line using the computer numerical control machine measurements. The most informative features are ranked using dynamic programming and its approximation variants from real-time measurements and machine settings, such as the width of cut, depth of cut, feed rate and spindle speed, that serve as inputs to the predictive models. The baseline nominal model is incrementally updated with experimental data via a gradient boosted adaptation model to generate the residuals that account for discrepancies between the actual machine data under normal conditions and the baseline nominal model predictions. The hybrid model is validated against 20 Mazak milling machine experimental tests and one Haas run-to-failure experiment. The proposed anomaly detector is applied to synthetic data from simulations of the physics-based model at different operating conditions, measurement noise levels, and tool wear levels, and the methods were able to achieve an overall 92% accuracy in data with 1% noise. The anomaly detection methods based on hybrid model reduced the false alarms of either the data-driven or physical-based models alone, and are found to be capable of good online detection of tool wear.

Online anomaly detection↗
NASA NTRS1988

An integrated and modular digital modeling approach for the space station electrical power system development

An electrical power system for the Space Station was designed, developed and built. This system provides for electrical power generation, conditioning, storage, and distribution. The initial configuration uses photovoltaic power generation. The power system control is based on a hierarchical architecture to support the requirements of automation. In the preliminary design and technology development phase of the program, various modeling techniques and software tools were evaluated for the purpose of meeting the Space Station power system modeling requirements. Rocketdyne and LeRC jointly selected the EASY5 simulation software, developed by Boeing Computer Services, as a system level modeling tool. The application of the selected analytical modeling approach to represent the entire power system is described. Typical results of model predictions are also summarized. The equipment modeled includes solar arrays, dc to ac converters, resonant inverters, battery storage system, alternator, transmission line, switch gear, and system level microprocessor controls. During the advanced development phase of this program, several models were developed using this approach.

Gombos, Frank J.↗
NASA NTRS1988

An integrated and modular digital modeling approach for the Space Station electrical power system development

An electrical power system for the Space Station was designed, developed and built. This system provides for electrical power generation, conditioning, storage, and distribution. The initial configuration uses photovoltaic power generation. The power system control is based on a hierarchical architecture to support the requirements of automation. In the preliminary design and technology development phase of the program, various modeling techniques and software tools were evaluated for the purpose of meeting the Space Station power system modeling requirements. Rocketdyne and LeRC jointly selected the EASY5 simulation software, developed by Boeing Computer Services, as a system level modeling tool. The application of the selected analytical modeling approach to represent the entire power system is described. Typical results of model predictions are also summarized. The equipment modeled includes solar arrays, dc to ac converters, resonant inverters, battery storage system, alternator, transmission line, switch gear, and system level microprocessor controls. During the advanced development phase of this program, several models were developed using this approach.

Gombos, Frank J.↗
NASA NTRS2000

Exploratory Studies in Generalized Predictive Control for Active Aeroelastic Control of Tiltrotor Aircraft

The Aeroelasticity Branch at NASA Langley Research Center has a long and substantive history of tiltrotor aeroelastic research. That research has included a broad range of experimental investigations in the Langley Transonic Dynamics Tunnel (TDT) using a variety of scale models and the development of essential analyses. Since 1994, the tiltrotor research program has been using a 1/5-scale, semispan aeroelastic model of the V-22 designed and built by Bell Helicopter Textron Inc. (BHTI) in 1981. That model has been refurbished to form a tiltrotor research testbed called the Wing and Rotor Aeroelastic Test System (WRATS) for use in the TDT. In collaboration with BHTI, studies under the current tiltrotor research program are focused on aeroelastic technology areas having the potential for enhancing the commercial and military viability of tiltrotor aircraft. Among the areas being addressed, considerable emphasis is being directed to the evaluation of modern adaptive multi-input multi- output (MIMO) control techniques for active stability augmentation and vibration control of tiltrotor aircraft. As part of this investigation, a predictive control technique known as Generalized Predictive Control (GPC) is being studied to assess its potential for actively controlling the swashplate of tiltrotor aircraft to enhance aeroelastic stability in both helicopter and airplane modes of flight. This paper summarizes the exploratory numerical and experimental studies that were conducted as part of that investigation.

Kvaternik, Raymond G.↗
NASA NTRS2004

Probabilistic Residual Strength Model Developed for Life Prediction of Ceramic Matrix Composites

For the next generation of reusable launch vehicles, NASA is investigating introducing ceramic matrix composites (CMCs) in place of current superalloys for structural propulsion applications (e.g., nozzles, vanes, combustors, and heat exchangers). The higher use temperatures of CMCs will reduce vehicle weight by eliminating and/or reducing cooling system requirements. The increased strength-to-weight ratio of CMCs relative to superalloys further enhances their weight savings potential. However, in order to provide safe designs for components made of these new materials, a comprehensive life prediction methodology for CMC structures needs to be developed. A robust methodology for lifing composite structures has yet to be adopted by the engineering community. Current industry design practice continues to utilize deterministic empirically based models borrowed from metals design for predicting material life capabilities. The deterministic nature of these models inadequately addresses the stochastic character of brittle composites, and their empirical reliance makes predictions beyond the experimental test conditions a risky extrapolation. A team of engineers at the NASA Glenn Research Center has been developing a new life prediction engineering model. The Probabilistic Residual Strength (PRS) model uses the residual strength of the composite as its damage metric. Expected life and material strength are both considered probabilistically to account for the observed stochastic material response. Extensive experimental testing has been carried out on C/SiC (a candidate aerospace CMC material system) in a controlled 1000 ppm O2/argon environment at elevated temperatures of 800 and 1200 C. The test matrix was established to allow observation of the material behavior, characterization of the model, and validation of the model's predictive capabilities. Sample results of the validation study are illustrated in the graphs.

Thomas, David J.↗
NASA NTRS2001

Challenges Facing Design and Analysis Tools

The design and analysis of future aerospace systems will strongly rely on advanced engineering analysis tools used in combination with risk mitigation procedures. The implications of such a trend place increased demands on these tools to assess off-nominal conditions, residual strength, damage propagation, and extreme loading conditions in order to understand and quantify these effects as they affect mission success. Advances in computer hardware such as CPU processing speed, memory, secondary storage, and visualization provide significant resources for the engineer to exploit in engineering design. The challenges facing design and analysis tools fall into three primary areas. The first area involves mechanics needs such as constitutive modeling, contact and penetration simulation, crack growth prediction, damage initiation and progression prediction, transient dynamics and deployment simulations, and solution algorithms. The second area involves computational needs such as fast, robust solvers, adaptivity for model and solution strategies, control processes for concurrent, distributed computing for uncertainty assessments, and immersive technology. Traditional finite element codes still require fast direct solvers which when coupled to current CPU power enables new insight as a result of high-fidelity modeling. The third area involves decision making by the analyst. This area involves the integration and interrogation of vast amounts of information - some global in character while local details are critical and often drive the design. The proposed presentation will describe and illustrate these areas using composite structures, energy-absorbing structures, and inflatable space structures. While certain engineering approximations within the finite element model may be adequate for global response prediction, they generally are inadequate in a design setting or when local response prediction is critical. Pitfalls to be avoided and trends for emerging analysis tools will be described.

Knight, Norman F., Jr.↗
NASA NTRS2010

Soil Moisture Controls on Rainfall and Temperature Variability: A Modeler Searches Through Observational Data

The degree to which atmospheric processes respond to variations in soil moisture - a potentially important but largely untapped element of subseasonal to seasonal prediction - can be determined easily and directly for an atmospheric model but cannot be determined directly for nature through an analysis of observations. In atmospheric models) directions of causality can be artificially manipulated; we can avoid difficulties associated with the fact that atmospheric variations have a much larger impact on land state variations than vice-versa. In nature) on the other hand) the dominant direction of causality (the atmosphere forcing the ground) cannot be artificially "turned off") and the statistics associated with this dominant direction overwhelm those of the feedback signal. Observational data) however) do allow a number of indirect measures of landatmosphere feedback. This seminar reports on a series of joint analyses of observational and model data designed to illuminate the degree of land-atmosphere feedback present in the real world. The indirect measures do in fact suggest that feedback in nature, though small) is significant - enough to warrant the development of realistic land initialization strategies for subseasonal and seasonal forecasts.

Koster, Randal↗
NASA NTRS1990

On the nature of the interaction between structures and actuators in vibration suppression

This lecture presents a summary of work on the analysis of the interaction between a structure, an actuator used to suppress the vibration of the structure, and the control law implemented by the actuator. Two control applications are considered. First, a proof-mass actuator with experimentally verified dynamics, capable of being used in a space structure configuration is examined. This is connected to a cantilevered beam modeled as a single degree of freedom system. Secondly, an electric motor, again with experimentally verified dynamics, is used to slew a beam modeled by a partial differential equation. Both the experimental and numerical configuration predict the presence of potential instabilities in system performance if proper consideration is not given to interactions between the control law, the structure and the actuator. In addition, an understanding of the interaction is shown to greatly effect performance. In particular it is shown that judicious choice of actuator parameters greatly improves closed loop performance.

Inman, Daniel J.↗
NASA NTRSDate not supplied

Modeling and Simulation of Rotary Sloshing in Launch Vehicles

The nonlinear dynamics of propellant sloshing during orbital ascent are usually neglected in the flight control analysis of large boost vehicles under the assumption that the viscous damping of the fluid is sufficient to suppress nonlinear phenomena and confine the fluid to small, planar free surface displacements. In this case, the sloshing dynamics can be modeled using a spring-mass-damper or linearized pendulum mechanical analog. However, large, smooth-wall tanks without significant internal hardware or ring baffles are still susceptible to nonlinear effects. In particular, rotary sloshing can present a risk to flight control as it involves the formation of a stable limit cycle which can lead to undesirable roll coupling. The underlying phenomena of jump resonance does not manifest in linear models, but can be reproduced using a nonlinear spherical pendulum or the Bauer paraboloid model developed during the Apollo/Saturn program. In this paper, a detailed analysis of the rotary sloshing dynamics of these mechanical analogs is presented, and discussed in the context of flight control stability. High-fidelity simulations of a representative boost vehicle are used to verify the semi-analytical predictions of the nonlinear dynamic response.

Modeling↗
NASA NTRS1974

In flight ground control of high drag satellites utilizing on-board accelerometer data and rapid orbit prediction techniques

High drag satellites frequently require precise verification of orbital maneuvers and the accurate prediction of perigee height. An in-flight ground support system designed to monitor and compute orbital state and maneuvers is described. The use of on-board three-axis accelerometer data in a flight support software system to perform on-line maneuver analysis and atmospheric model updating is discussed. In addition, automated analytic techniques to rapidly and accurately predict perigee height following a maneuver are described, as well as semianalytic averaging techniques designed to predict a decaying orbital state for mission control.

Fuchs, A. J.↗
NASA NTRS1993

Laser tracking for vertical control

The Global Laser Tracking Network has provided LAGEOS ranging data of high accuracy since the first MERIT campaign in late 1983 and we can now resolve centimeter-level three dimensional positions of participating observatories at monthly intervals. In this analysis, the station height estimates have been considered separately from the horizontal components, and can be determined by the strongest stations with a formal standard error of 2 mm using eight years of continuous observations. The rate of change in the vertical can be resolved to a few mm/year, which is at the expected level of several geophysical effects. In comparing the behavior of the stations to that predicted by recent models of post-glacial rebound, we find no correlation in this very small effect. Particular attention must be applied to data and survey quality control when measuring the vertical component, and the survey observations are critical components of the geodynamic results. Seasonal patterns are observed in the heights of most stations, and the possibility of secular motion at the level of several millimeters per year cannot be excluded. Any such motion must be considered in the interpretation of horizontal inter-site measurements, and can help to identify mechanisms which can cause variations which occur linearly with time, seasonally, or abruptly.

Dunn, Peter↗
NASA NTRS2001

Dynamic Analysis of a Building Under Rocket Engine Plume Acoustic Load

Studies have been performed to develop finite-element modeling and simulation techniques to predict the dynamic structural response of Building 4010 to the acoustic load from the plume of high-thrust rocket motors. The building is the Test Control Center and general office space for the E-complex at Stennis Space Center. It is a large single span; light-structured building located approximately 1,000 feet from the E-1 test stand. A three-dimensional shell/beam combined model of the building was built using Pro/Engineer platform and imported into Pro/Mechanica for analysis. An Equivalent Shell technique was developed to simplify the highly complex building structure so that the calculation is more efficient and accurate. A deterministic approach was used for the dynamic analysis. A pre-stressed modal analysis was performed to simulate the weight stiffening of the structure, through which about 200 modes ranging from 0 to 35 Hz were identified. In an initial dynamic frequency analysis, the maximum response over the model was found. Then the complete 3-D distributions of the displacement, as well as the stresses, were calculated through a final frequency analysis. The results were compared to a strain gage and accelerometer recordings from rocket engine tests and showed reasonable agreement.

Qian, Z.↗