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At least 199 records · Page 11

Rotation Rate of Saturn's Magnetosphere using CAPS Plasma Measurements

We present the present status of an investigation of the rotation rate of Saturn's magnetosphere using a 3D velocity moment technique being developed at Goddard which is similar to the 2D version used by Sittler et al. for SOI and similar to that used by Thomsen et al.. This technique allows one to nearly cover the full energy range of the Cassini Plasma Spectrometer (CAPS) IMS from 1 V . E/Q < 50 kV. Since our technique maps the observations into a local inertial frame, it does work during roll maneuvers. We make comparisons with the bi-Maxwellian fitting technique developed by Wilson et al. and the similar velocity moment technique by Thomsen et al. . We concentrate our analysis when ion composition data is available, which is used to weight the non-compositional data, referred to as singles data, to separate H+, H2+ and water group ions (W+) from each other. The chosen periods have high enough telemetry rates (4 kbps or higher) so that coincidence ion data, similar to that used by Sittler et al. for SOI is available. The ion data set is especially valuable for measuring flow velocities for protons, which are more difficult to derive using singles data within the inner magnetosphere, where the signal is dominated by heavy ions (i.e., proton peak merges with W+ peak as low energy shoulder). Our technique uses a flux function, which is zero in the proper plasma flow frame, to estimate fluid parameter uncertainties. The comparisons investigate the experimental errors and potential for systematic errors in the analyses, including ours. The rolls provide the best data set when it comes to getting 4PI coverage of the plasma but are more susceptible to time aliasing effects. In the future we will then make comparisons with magnetic field observations, Saturn ionosphere conductivities as presently known and the field aligned currents necessary for the planet to enforce corotation of the rotating plasma.

Sittler, E.↗

Reliability of COPVs Accounting for Margin of Safety on Design Burst

In this paper, the stress rupture reliability of Carbon/Epoxy Composite Overwrapped Pressure Vessels (COPVs) is examined utilizing the classic Phoenix model and accounting for the differences between the design and the actual burst pressure, and the liner contribution effects. Stress rupture life primarily depends upon the fiber stress ratio which is defined as the ratio of stress in fibers at the maximum expected operating pressure to actual delivered fiber strength. The actual delivered fiber strength is calculated using the actual burst pressures of vessels established through burst tests. However, during the design phase the actual burst pressure is generally not known and to estimate the reliability of the vessels calculations are usually performed based upon the design burst pressure only. Since the design burst is lower than the actual burst, this process yields a much higher value for the stress ratio and consequently a conservative estimate for the reliability. Other complications arise due to the fact that the actual burst pressure and the liner contributions have inherent variability and therefore must be treated as random variables in order to compute the stress rupture reliability. Furthermore, the model parameters, which have to be established based on stress rupture tests of subscale vessels or coupons, have significant variability as well due to limited available data and hence must be properly accounted for. In this work an assessment of reliability of COPVs including both parameter uncertainties and physical variability inherent in liner and overwrap material behavior is made and estimates are provided in terms of degree of uncertainty in the actual burst pressure and the liner load sharing.

Murthy, Pappu L.N.↗

Rotation Rate of Saturn's Magnetosphere using CAPS Plasma Measurements

We present the present status of an investigation of the rotation rate of Saturn 's magnetosphere using a 3D velocity moment technique being developed at Goddard which is similar to the 2D version used by Sittler et al. (2005) [1] for SOI and similar to that used by Thomsen et al. (2010). This technique allows one to nearly cover the full energy range of the CAPS IMS from 1 V less than or equal to E/Q less than 50 kV. Since our technique maps the observations into a local inertial frame, it does work during roll manoeuvres. We have made comparisons with Wilson et al. (2008) [2] (2005-358 and 2005-284) who performs a bi-Maxwellian fit to the ion singles data and our results are nearly identical. We will also make comparisons with results by Thomsen et al. (2010) [3]. Our analysis uses ion composition data to weight the non-compositional data, referred to as singles data, to separate H+, H2+ and water group ions (W+) from each other. The ion data set is especially valuable for measuring flow velocities for protons, which are more difficult to derive using singles data within the inner magnetosphere, where the signal is dominated by heavy ions (i.e., proton peak merges with W+ peak as low energy shoulder). Our technique uses a flux function, which is zero in the proper plasma flow frame, to estimate fluid parameter uncertainties. The comparisons investigate the experimental errors and potential for systematic errors in the analyses, including ours. The rolls provide the best data set when it comes to getting 4PI coverage of the plasma but are more susceptible to time aliasing effects. Since our analysis is a velocity moments technique it will work within the inner magnetosphere where pickup ions are important and velocity distributions are non-Maxwellian. So, we will present results inside Enceladus' L shell and determine if mass loading is important. In the future we plan to make comparisons with magnetic field observations, use Saturn ionosphere conductivities as presently known and the field aligned currents necessary for the planet to enforce corotation of the rotating plasma.

Sittler, E.↗

Spacecraft Thermal and Optical Modeling Impacts on Estimation of the GRAIL Lunar Gravity Field

We summarize work performed involving thermo-optical modeling of the two Gravity Recovery And Interior Laboratory (GRAIL) spacecraft. We derived several reconciled spacecraft thermo-optical models having varying detail. We used the simplest in calculating SRP acceleration, and used the most detailed to calculate acceleration due to thermal re-radiation. For the latter, we used both the output of pre-launch finite-element-based thermal simulations and downlinked temperature sensor telemetry. The estimation process to recover the lunar gravity field utilizes both a nominal thermal re-radiation accleration history and an apriori error model derived from that plus an off-nominal history, which bounds parameter uncertainties as informed by sensitivity studies.

thermal modeling↗

Follow on Researches for X-56A Aircraft at NASA Dryden Flight Research Center (Progress Report)

A lot of composite materials are used for the modern aircraft to reduce its weight. Aircraft aeroservoelastic models are typically characterized by significant levels of model parameter uncertainty due to composite manufacturing process. Small modeling errors in the finite element model will eventually induce errors in the structural flexibility and mass, thus propagating into unpredictable errors in the unsteady aerodynamics and the control law design. One of the primary objectives of X-56A aircraft is the flight demonstration of active flutter suppression, and therefore in this study, the identification of the primary and secondary modes is based on the flutter analysis of X-56A aircraft. It should be noted that for all three Mach number cases rigid body modes and mode numbers seven and nine are participated 89.1 92.4 % of the first flutter mode. Modal participation of the rigid body mode and mode numbers seven and nine for the second flutter mode are 94.6 96.4%. Rigid body mode and the first two anti-symmetric modes, eighth and tenth modes, are participated 93.2 94.6% of the third flutter mode. Therefore, rigid body modes and the first four flexible modes of X-56A aircraft are the primary modes during the model tuning procedure. The ground vibration test-validated structural dynamic finite element model of the X-56A aircraft is to obtain in this study. The structural dynamics finite element model of X-56A aircraft is improved using the parallelized big-bang big-crunch algorithm together with a hybrid optimization technique.

Structural Dynamic Model Tuning↗

Follow on Research for Multi-Utility Technology Test Bed Aircraft at NASA Dryden Flight Research Center (FY13 Progress Report)

Modern aircraft employ a significant fraction of their weight in composite materials to reduce weight and improve performance. Aircraft aeroservoelastic models are typically characterized by significant levels of model parameter uncertainty due to the composite manufacturing process. Small modeling errors in the finite element model will eventually induce errors in the structural flexibility and mass, thus propagating into unpredictable errors in the unsteady aerodynamics and the control law design. One of the primary objectives of Multi Utility Technology Test-bed (MUTT) aircraft is the flight demonstration of active flutter suppression, and therefore in this study, the identification of the primary and secondary modes for the structural model tuning based on the flutter analysis of MUTT aircraft. The ground vibration test-validated structural dynamic finite element model of the MUTT aircraft is created in this study. The structural dynamic finite element model of MUTT aircraft is improved using the in-house Multi-disciplinary Design, Analysis, and Optimization tool. In this study, two different weight configurations of MUTT aircraft have been improved simultaneously in a single model tuning procedure.

multi-utility technology test bed aircraft↗

Spacecraft Stabilization and Control for Capture of Non-Cooperative Space Objects

This paper addresses stabilization and control issues in autonomous capture and manipulation of non-cooperative space objects such as asteroids, space debris, and orbital spacecraft in need of servicing. Such objects are characterized by unknown mass-inertia properties, unknown rotational motion, and irregular shapes, which makes it a challenging control problem. The problem is further compounded by the presence of inherent nonlinearities, signi cant elastic modes with low damping, and parameter uncertainties in the spacecraft. Robust dissipativity-based control laws are presented and are shown to provide global asymptotic stability in spite of model uncertainties and nonlinearities. It is shown that robust stabilization can be accomplished via model-independent dissipativity-based controllers using thrusters alone, while stabilization with attitude and position control can be accomplished using thrusters and torque actuators.

Joshi, Suresh↗

Desensitized Optimal Filtering and Sensor Fusion Toolkit

Analytical Mechanics Associates, Inc., has developed a software toolkit that filters and processes navigational data from multiple sensor sources. A key component of the toolkit is a trajectory optimization technique that reduces the sensitivity of Kalman filters with respect to model parameter uncertainties. The sensor fusion toolkit also integrates recent advances in adaptive Kalman and sigma-point filters for non-Gaussian problems with error statistics. This Phase II effort provides new filtering and sensor fusion techniques in a convenient package that can be used as a stand-alone application for ground support and/or onboard use. Its modular architecture enables ready integration with existing tools. A suite of sensor models and noise distribution as well as Monte Carlo analysis capability are included to enable statistical performance evaluations.

Karlgaard, Christopher D.↗

Optimal Design of Calibration Signals in Space Borne Gravitational Wave Detectors

Future space borne gravitational wave detectors will require a precise definition of calibration signals to ensure the achievement of their design sensitivity. The careful design of the test signals plays a key role in the correct understanding and characterization of these instruments. In that sense, methods achieving optimal experiment designs must be considered as complementary to the parameter estimation methods being used to determine the parameters describing the system. The relevance of experiment design is particularly significant for the LISA Pathfinder mission, which will spend most of its operation time performing experiments to characterize key technologies for future space borne gravitational wave observatories. Here we propose a framework to derive the optimal signals in terms of minimum parameter uncertainty to be injected to these instruments during its calibration phase. We compare our results with an alternative numerical algorithm which achieves an optimal input signal by iteratively improving an initial guess. We show agreement of both approaches when applied to the LISA Pathfinder case.

LISA Path_nder mission↗

Developing Atmospheric Retrieval Methods for Direct Imaging Spectroscopy of Gas Giants in Reflected Light I: Methane Abundances and Basic Cloud Properties

Reflected light spectroscopy and photometry of cool, directly imaged extrasolar giant planets are expected to be performed in the next decade by space-based telescopes equipped with optical wavelength coronagraphs and integral field spectrographs, such as the Wide-Field Infrared Survey Telescope (WFIRST). We are developing a new atmospheric retrieval methodology to help assess the science return and inform the instrument design for such future missions, and ultimately interpret the resulting observations. Our retrieval technique employs an albedo model coupled with both a Markov chain Monte Carlo Ensemble Sampler (emcee) and a multimodal nested sampling algorithm (MultiNest) to map the posterior distribution. This combination makes the global evidence calculation more robust for any given model, and highlights possible discrepancies in the likelihood maps. Here we apply this methodology to simulated spectra of cool giant planets. As a proof-of-concept, our current atmospheric model contains 1 or 2 cloud layers, methane as a major absorber, and a H2-He background gas. This 6-to-9 parameter model is appropriate for Jupiter-like planets and can be easily expanded in the future. In addition to deriving the marginal likelihood distribution and confidence intervals for the model parameters, we perform model selection to determine the significance of methane and cloud detection as a function of expected signal-to-noise, in the presence of spectral noise correlations. After internal validation, the method is applied to realistic reflected-light spectra of Jupiter, Saturn, and HD 99492 c, a likely observing target. We find that the presence or absence of clouds and methane can be determined with high accuracy, while parameters uncertainties are model-dependent.

spectroscopy↗

Sliding Mode Transient Scaling Controller for Gas Turbine Engine Emulation on an Electric Machine

The testing of hybrid-electric aircraft propulsion system components and control strategies has dictated the need for a low-cost gas turbine engine (GTE) emulation testbed. Within that testbed, electric machines (EMs) are used to emulate the dynamics of a GTE. GTE mathematical models are used to provide control torque commands to EMs. Most GTEs operate at much higher power levels than commercially available EMs. Therefore, the transient shaft dynamics of the GTE must be scaled appropriately. The sliding mode controller being presented here aims to deliver a control torque to an electric machine with a fixed inertia that will allow it to mimic the response of a GTE with a different inertia. This solution provides an easily scalable and tunable transient emulation method without having to scale the GTE mathematical model and/or add inertia to the physical EM shaft. This controller has been proven in simulation to produce nearly identical transient rotational speed response to a reference GTE shaft model which has a large difference in rotational inertia compared to the motor. Also, the inherent robustness of the sliding mode control scheme results in negligible changes in performance for large amounts of parameter uncertainty while minimizing high frequency fluctuations in the control signal.

sliding mode↗

Simulation of Hydrogen Flow in a Nuclear-Thermal Propulsion Reactor Subsystem: Conjugate Heat Transfer in Surrogate Fuel Elements and Flow Through the Dome Inlet to the Fuel Elements

NASA is performing research related to a Nuclear-Thermal Propulsion (NTP) engine as a step toward future manned missions to Mars. BWX Technologies (BWXT), in conjunction with NASA, is developing the reactor subsystem for that NTP engine design. As a subset of the reactor subsystem, the fuel elements have continued to evolve in design, as well. A set of experiments within the Nuclear Thermal Reactor Element Environmental Simulator at NASA Marshall has been developed to compliment that design process, including a series of surrogate fuel elements. Before the experiments of each surrogate can be completed, they must be deemed safe using structural analysis, which itself requires thermal and conjugate heat transfer analyses of the articles. Therefore, conjugate heat transfer simulations of the hydrogen flow through the test article fuel element surrogates were developed to provide estimates of heating, as well as to provide assessments of the fluid flow through the elements. The set of simulations involved not only the separate test conditions, but also a sensitivity study to estimate the effect of physical parameter uncertainty on the selected quantities of interest. Additionally, the fluid flow through the fore section inner plenum dome to the entrances of the fuel elements, another section of the reactor subsystem still under active development, was simulated and analyzed. The simulations show the extent of non-uniformity in the mass flow distribution across the dome outlets. Furthermore, additional analyses estimate the effects of required flow blockages on the potential development of flow dynamics. These analyses were used in the design cycle to make improvements to the reactor subsystem design.

Kalen E. Braman↗

Mars Pathfinder Cruise Stage/Entry Vehicle Separation Dynamics

Prior to atmospheric entry, Mars Pathfinder flight system will separate its entry vehicle from its cruise stage, and establish the entry conditions for a passive and unconventional entry, descent, and landing approach. This paper summarizes a separation dynamics analysis conducted to demonstrate that the cruise separation system design is viable and ensure that adequate design margins exist with the effects from parameter uncertainty included.

Pathfinder↗

Nonlinear Unsteady Aerodynamic Modeling Using Empirical Orthogonal Functions

Empirical orthogonal function modeling is explained and applied to identify compact discrete-time nonlinear unsteady aerodynamic models from data generated by an unsteady three-dimensional compressible Navier-Stokes flow solver for an airfoil undergoing various pitching motions. Model structures, model parameter estimates, and model parameter uncertainty estimates for nondimensional lift, drag, and pitching moment coefficient models were determined autonomously and directly from the data. Prediction tests using data that were not used in the modeling process showed that the identified models exhibited excellent prediction capability, which is a strong indicator of an accurate model.

empirical↗

Modelling the Greenland Ice Sheet's Committed Contribution to Sea Level During the 21st Century

Mass loss from the Greenland Ice Sheet can be partitioned between surface mass balance and discharge due to ice dynamics through its marine-terminating outlet glaciers. A perturbation to a glacier terminus (e.g., a calving event) results in both an instantaneous response in velocity and mass loss and a diffusive response due to the evolution of ice thickness over time. This diffusive response means the total impact of a retreat event can take decades to be fully realized. Here we model the committed response of the Greenland Ice Sheet by applying perturbations to the marine-terminating glacier termini that represent recent observed changes, and simulating the response over the 21st century, while holding the climate forcing constant. The sensitivity of the ice sheet response to model parameter uncertainty is explored within an ensemble framework, and Gravity Recovery and Climate Experiment data is used to constrain the results using a Bayesian calibration approach. We find that the Greenland Ice Sheet's committed contribution to 21st century sea level rise is at least 33.5 [17.5 52.4] mm (25th and 75th percentiles in brackets), with at least 6 mm being attributable directly to terminus retreat that occurred between 2007 and 2015. The spread in our projections is driven by uncertainty in the basal friction coefficient. Our results complement the ISMIP6 Greenland projections, which report the ice sheet response to future forcing, excluding the background response. In this way, we can obtain estimates of Greenland's total contribution to sea level rise in 2100.

Isabel J. Nias↗

Using Importance Sampling Monte Carlo to Analyze Aircraft Takeoff and Landing

Aircraft have achieved high levels of reliability, so the probability of undesirable dynamics is very low. The low probability of a bad takeoff or landing challenges nondeterministic methods to quantify the uncertainty of these improbable events. In the present work, a Monte Carlo method is defined to more effectively quantify these unlikely events that is suitable for uncertainty analysis of a mature design with many uncertainty parameters. The proposed Monte Carlo method has been applied to the takeoff and landing of the X-59 Quiet SuperSonic Technology (QueSST). Takeoff and landing simulation profiles were defined using a combination of industry standards and piloted simulation experience. The proposed method is shown to be able to quantify events with significantly fewer samples than would be required with conventional Monte Carlo. These results improve understanding of the sensitivity of the takeoff and landing dynamics to inform further studies and test planning.

Jeffrey Ouellette↗

Using Importance Sampling Monte Carlo to Analyze Aircraft Takeoff and Landing

Aircraft have achieved high levels of reliability, so the probability of undesirable dynamics is very low. The low probability of a bad takeoff or landing challenges nondeterministic methods to quantify the uncertainty of these improbable events. In the present work, a Monte Carlo method is defined to more effectively quantify these unlikely events that is suitable for uncertainty analysis of a mature design with many uncertainty parameters. The proposed Monte Carlo method has been applied to the takeoff and landing of the X-59 Quiet SuperSonic Technology (QueSST). Takeoff and landing simulation profiles were defined using a combination of industry standards and piloted simulation experience. The proposed method is shown to be able to quantify events with significantly fewer samples than would be required with conventional Monte Carlo. These results improve understanding of the sensitivity of the takeoff and landing dynamics to inform further studies and test planning.

Jeffrey Ouellette↗

NASA POWER: Providing Analysis-Ready, Cloud-Optimized Data for AI /ML Training and Applications in Earth Science

As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.

Neha Khadka↗