Results for “Dynamic State Estimation” — Page 14

NASA NTRS1977

Time delay occultation data of the Helios spacecrafts and preliminary analysis for probing the solar corona

S-band time delay measurements were collected from the spacecrafts Helios A and B during three solar occultations in 1975/76 within heliocentric distances of about 3 and 215 solar radii in terms of range, Doppler frequency shift, and electron content. A description is given concerning some characteristic features of the methods of measurement and data processing. Typical data sets are discussed to probe the electron density distribution near the sun (west and east limb as well) including the outer and extended corona. Steady-state and dynamical aspects of the solar corona are presented and compared with earth-bound K-coronagraph measurements. Using a weighted least squares estimation 3 parameters of an average coronal electron density profile are derived in a preliminary analysis to yield electron densities of about 130 billion; 100 million; 7 million/cu m at r?3; 65; 215 solar radii. Transient phenomena are discussed and a velocity of propagation v approximately 900 km/s for plasma ejecta from a solar flare is determined from an extraordinary set of Helios B electron content measurements on April 30/May 1, 1976.

Edenhofer, P.↗

NASA NTRS1985

Self-Tuning Adaptive-Controller Using Online Frequency Identification

A real time adaptive controller was designed and tested successfully on a fourth order laboratory dynamic system which features very low structural damping and a noncolocated actuator sensor pair. The controller, implemented in a digital minicomputer, consists of a state estimator, a set of state feedback gains, and a frequency locked loop (FLL) for real time parameter identification. The FLL can detect the closed loop natural frequency of the system being controlled, calculate the mismatch between a plant parameter and its counterpart in the state estimator, and correct the estimator parameter in real time. The adaptation algorithm can correct the controller error and stabilize the system for more than 50% variation in the plant natural frequency, compared with a 10% stability margin in frequency variation for a fixed gain controller having the same performance at the nominal plant condition. After it has locked to the correct plant frequency, the adaptive controller works as well as the fixed gain controller does when there is no parameter mismatch. The very rapid convergence of this adaptive system is demonstrated experimentally, and can also be proven with simple root locus methods.

Chiang, W. W.↗

NASA NTRS1990

Compensating for pneumatic distortion in pressure sensing devices

A technique of compensating for pneumatic distortion in pressure sensing devices was developed and verified. This compensation allows conventional pressure sensing technology to obtain improved unsteady pressure measurements. Pressure distortion caused by frictional attenuation and pneumatic resonance within the sensing system makes obtaining unsteady pressure measurements by conventional sensors difficult. Most distortion occurs within the pneumatic tubing which transmits pressure impulses from the aircraft's surface to the measurement transducer. To avoid pneumatic distortion, experiment designers mount the pressure sensor at the surface of the aircraft, (called in-situ mounting). In-situ transducers cannot always fit in the available space and sometimes pneumatic tubing must be run from the aircraft's surface to the pressure transducer. A technique to measure unsteady pressure data using conventional pressure sensing technology was developed. A pneumatic distortion model is reduced to a low-order, state-variable model retaining most of the dynamic characteristics of the full model. The reduced-order model is coupled with results from minimum variance estimation theory to develop an algorithm to compensate for the effects of pneumatic distortion. Both postflight and real-time algorithms are developed and evaluated using simulated and flight data.

Whitmore, Stephen A.↗

NASA NTRS1990

Compensating for pneumatic distortion in pressure sensing devices

A general numerical technique for obtaining unsteady pressure measurements using conventional pressure sensing technology has been developed. A pneumatic distortion model, based on the Navier-Stokes equations of momentum and continuity, was reduced to a low-order, state-variable model retaining most of the dynamic characteristics of the full model. The reduced-order model is coupled with results from minimum variance estimation theory to develop an algorithm to compensate the effects of pneumatic distortion. Both postflight and real-time algorithms were developed and evaluated using simulated and flight data.

Whitmore, Stephen A.↗

NASA NTRS2016

Modeling ARRM Xenon Tank Pressurization Using 1D Thermodynamic and Heat Transfer Equations

As a first step in understanding what ground support equipment (GSE) is required to provide external cooling during the loading of 5,000 kg of xenon into 4 aluminum lined composite overwrapped pressure vessels (COPVs), a modeling analysis was performed using Microsoft Excel. The goals of the analysis were to predict xenon temperature and pressure throughout loading at the launch facility, estimate the time required to load one tank, and to get an early estimate of what provisions for cooling xenon might be needed while the tanks are being filled. The model uses the governing thermodynamic and heat transfer equations to achieve these goals. Results indicate that a single tank can be loaded in about 15 hours with reasonable external coolant requirements. The model developed in this study was successfully validated against flight and test data. The first data set is from the Dawn mission which also utilizes solar electric propulsion with xenon propellant, and the second is test data from the rapid loading of a hydrogen cylindrical COPV. The main benefit of this type of model is that the governing physical equations using bulk fluid solid temperatures can provide a quick and accurate estimate of the state of the propellant throughout loading which is much cheaper in terms of computational time and licensing costs than a Computation Fluid Dynamics (CFD) analysis while capturing the majority of the thermodynamics and heat transfer.

Xenon storage↗

NASA NTRS2017

Modeling Xenon Tank Pressurization using One-Dimensional Thermodynamic and Heat Transfer Equations

As a first step in understanding what ground support equipment (GSE) is required to provide external cooling during the loading of 5,000 kg of xenon into 4 aluminum lined composite overwrapped pressure vessels (COPVs), a modeling analysis was performed using Microsoft Excel. The goals of the analysis were to predict xenon temperature and pressure throughout loading at the launch facility, estimate the time required to load one tank, and to get an early estimate of what provisions for cooling xenon might be needed while the tanks are being filled. The model uses the governing thermodynamic and heat transfer equations to achieve these goals. Results indicate that a single tank can be loaded in about 15 hours with reasonable external coolant requirements. The model developed in this study was successfully validated against flight and test data. The first data set is from the Dawn mission which also utilizes solar electric propulsion with xenon propellant, and the second is test data from the rapid loading of a hydrogen cylindrical COPV. The main benefit of this type of model is that the governing physical equations using bulk fluid solid temperatures can provide a quick and accurate estimate of the state of the propellant throughout loading which is much cheaper in terms of computational time and licensing costs than a Computation Fluid Dynamics (CFD) analysis while capturing the majority of the thermodynamics and heat transfer.

Thermodynamic tank modeling↗

NASA NTRS2019

Efficient method for approximating nonlinear dynamics: applications to uncertainty propagation and estimation

High-order Taylor series expansions can be used to model nonlinear dynamics at the cost of integrating a large set of variational equations to obtain high-order state-transition tensors (STTs). This paper presents an innovative technique for approximating the high-order STTs that reduces significantly the computational cost by retaining only the dominant secular terms. We propagate the low-order partial derivatives of Kepler’s equation, which only requires the integration of six additional equations to extend an n-th order approximation to order (n + 1). The approximation stems from the Lindstedt-Poincare procedure and exploits the stability properties of orbital motion. Since the method makes no dynamical assumptions, it can accommodate any source of orbital perturbations. We show how the approximation of the second-order STT significantly increases the accuracy of the linear method for uncertainty propagation with only a small computational overhead. Finally, we derive a high-order approximate extended Kalman filter that implements the proposed approximation of the STT and improves the performance of linear filters. Examples of application with different perturbation sources include the heliocentric orbit of an asteroid, an orbiter around Europa, and an Earth-orbiting satellite.

Park, Ryan S↗

NASA NTRS2024

High Spectral Resolution Lidar – Generation 2 (HSRL-2) Retrievals of Ocean Surface Wind Speed: Methodology and Evaluation

Ocean surface wind speed (i.e., wind speed 10 m above sea level) is a critical parameter used by atmospheric models to estimate the state of the marine atmospheric boundary layer (MABL). Accurate surface wind speed measurements in diverse locations are required to improve characterization of MABL dynamics and assess how models simulate large-scale phenomena related to climate change and global weather patterns. To provide these measurements, this study introduces and evaluates a new surface wind speed data product from the NASA Langley Research Center nadir-viewing High Spectral Resolution Lidar – generation 2 (HSRL-2) using data collected as part of the NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) mission. The HSRL-2 can directly measure vertically resolved aerosol backscatter and extinction profiles without additional constraints or assumptions, enabling the instrument to accurately derive atmospheric attenuation and directly determine surface reflectance (i.e., surface backscatter). Also, the high horizontal spatial resolution of the HSRL-2 retrievals (0.5 s or ∼ 75 m along track) allows the instrument to probe the fine-scale spatial variability in surface wind speeds over time along the flight track and over breaks in broken cloud fields. A rigorous evaluation of these retrievals is performed by comparing coincident HSRL-2 and National Center for Atmospheric Research (NCAR) Airborne Vertical Atmosphere Profiling System (AVAPS) dropsonde data, owing to the joint deployment of these two instruments on the ACTIVATE King Air aircraft. These comparisons show correlations of 0.89, slopes of 1.04 and 1.17, and y intercepts of −0.13 and −1.05 m s−1 for linear and bisector regressions, respectively, and the overall accuracy is calculated to be 0.15 ± 1.80 m s−1. It is also shown that the dropsonde surface wind speed data most closely follow the HSRL-2 distribution of wave slope variance using the distribution proposed by Hu et al. (2008) rather than the ones proposed by Cox and Munk (1954) and Wu (1990) for surface wind speeds below 7 m s−1, with this category comprising most of the ACTIVATE data set. The retrievals are then evaluated separately for surface wind speeds below 7 m s−1 and between 7 and 13.3 m s−1 and show that the HSRL-2 retrieves surface wind speeds with a bias of ∼ 0.5 m s−1 and an error of ∼ 1.5 m s−1, a finding not apparent in the cumulative comparisons. Also, it is shown that the HSRL-2 retrievals are more accurate in the summer (−0.18 ± 1.52 m s−1) than in the winter (0.63 ± 2.07 m s−1), but the HSRL-2 is still able to make numerous (N=236) accurate retrievals in the winter. Overall, this study highlights the abilities and assesses the performance of the HSRL-2 surface wind speed retrievals, and it is hoped that further evaluation of these retrievals will be performed using other airborne and satellite data sets.

Sanja Dmitrovic↗

NASA NTRS2015

Improved Rainfall Estimates and Predictions for 21st Century Drought Early Warning

As temperatures increase, the onset and severity of droughts is likely to become more intense. Improved tools for understanding, monitoring and predicting droughts will be a key component of 21st century climate adaption. The best drought monitoring systems will bring together accurate precipitation estimates with skillful climate and weather forecasts. Such systems combine the predictive power inherent in the current land surface state with the predictive power inherent in low frequency ocean-atmosphere dynamics. To this end, researchers at the Climate Hazards Group (CHG), in collaboration with partners at the USGS and NASA, have developed i) a long (1981-present) quasi-global (50degS-50degN, 180degW-180degE) high resolution (0.05deg) homogenous precipitation data set designed specifically for drought monitoring, ii) tools for understanding and predicting East African boreal spring droughts, and iii) an integrated land surface modeling (LSM) system that combines rainfall observations and predictions to provide effective drought early warning. This talk briefly describes these three components. Component 1: CHIRPS The Climate Hazards group InfraRed Precipitation with Stations (CHIRPS), blends station data with geostationary satellite observations to provide global near real time daily, pentadal and monthly precipitation estimates. We describe the CHIRPS algorithm and compare CHIRPS and other estimates to validation data. The CHIRPS is shown to have high correlation, low systematic errors (bias) and low mean absolute errors. Component 2: Hybrid statistical-dynamic forecast strategies East African droughts have increased in frequency, but become more predictable as Indo- Pacific SST gradients and Walker circulation disruptions intensify. We describe hybrid statistical-dynamic forecast strategies that are far superior to the raw output of coupled forecast models. These forecasts can be translated into probabilities that can be used to generate bootstrapped ensembles describing future climate conditions. Component 3: Assimilation using LSMs CHIRPS rainfall observations (component 1) and bootstrapped forecast ensembles (component 2) can be combined using LSMs to predict soil moisture deficits. We evaluate the skill such a system in East Africa, and demonstrate results for 2013.

Funk, Chris↗

NASA NTRS2015

Improved Rainfall Estimates and Predictions for 21st Century Drought Early Warning

As temperatures increase, the onset and severity of droughts is likely to become more intense. Improved tools for understanding, monitoring and predicting droughts will be a key component of 21st century climate adaption. The best drought monitoring systems will bring together accurate precipitation estimates with skillful climate and weather forecasts. Such systems combine the predictive power inherent in the current land surface state with the predictive power inherent in low frequency ocean-atmosphere dynamics. To this end, researchers at the Climate Hazards Group (CHG), in collaboration with partners at the USGS and NASA, have developed i) a long (1981-present) quasi-global (50degS-50degN, 180degW-180degE) high resolution (0.05deg) homogenous precipitation data set designed specifically for drought monitoring, ii) tools for understanding and predicting East African boreal spring droughts, and iii) an integrated land surface modeling (LSM) system that combines rainfall observations and predictions to provide effective drought early warning. This talk briefly describes these three components. Component 1: CHIRPS The Climate Hazards group InfraRed Precipitation with Stations (CHIRPS), blends station data with geostationary satellite observations to provide global near real time daily, pentadal and monthly precipitation estimates. We describe the CHIRPS algorithm and compare CHIRPS and other estimates to validation data. The CHIRPS is shown to have high correlation, low systematic errors (bias) and low mean absolute errors. Component 2: Hybrid statistical-dynamic forecast strategies East African droughts have increased in frequency, but become more predictable as Indo- Pacific SST gradients and Walker circulation disruptions intensify. We describe hybrid statistical-dynamic forecast strategies that are far superior to the raw output of coupled forecast models. These forecasts can be translated into probabilities that can be used to generate bootstrapped ensembles describing future climate conditions. Component 3: Assimilation using LSMs CHIRPS rainfall observations (component 1) and bootstrapped forecast ensembles (component 2) can be combined using LSMs to predict soil moisture deficits. We evaluate the skill such a system in East Africa, and demonstrate results for 2013.

Funk, Chris↗

NASA NTRS1997

An Estimation of the Climatic Effects of Stratospheric Ozone Losses during the 1980s

In order to study the potential climatic effects of the ozone hole more directly and to assess the validity of previous lower resolution model results, the latest high spatial resolution version of the Atmospheric and Environmental Research, Inc., seasonal radiative dynamical climate model is used to simulate the climatic effects of ozone changes relative to the other greenhouse gases. The steady-state climatic effect of a sustained decrease in lower stratospheric ozone, similar in magnitude to the observed 1979-90 decrease, is estimated by comparing three steady-state climate simulations: 1) 1979 greenhouse gas concentrations and 1979 ozone, II) 1990 greenhouse gas concentrations with 1979 ozone, and III) 1990 greenhouse gas concentrations with 1990 ozone. The simulated increase in surface air temperature resulting from nonozone greenhouse gases is 0.272 K. When changes in lower stratospheric ozone are included, the greenhouse warming is 0.165 K, which is approximately 39% lower than when ozone is fixed at the 1979 concentrations. Ozone perturbations at high latitudes result in a cooling of the surface-troposphere system that is greater (by a factor of 2.8) than that estimated from the change in radiative forcing resulting from ozone depiction and the model's 2 x CO, climate sensitivity. The results suggest that changes in meridional heat transport from low to high latitudes combined with the decrease in the infrared opacity of the lower stratosphere are very important in determining the steady-state response to high latitude ozone losses. The 39% compensation in greenhouse warming resulting from lower stratospheric ozone losses is also larger than the 28% compensation simulated previously by the lower resolution model. The higher resolution model is able to resolve the high latitude features of the assumed ozone perturbation, which are important in determining the overall climate sensitivity to these perturbations.

MacKay, Robert M.↗

NASA NTRS2020

Critical land change information enhances the understanding of carbon balance in the United States

Large‐scale terrestrial carbon (C) estimating studies using methods such as atmospheric inversion, biogeochemical modeling, and field inventories have produced different results. The goal of this study was to integrate fine‐scale processes including land use and land cover change into a large‐scale ecosystem framework. We analyzed the terrestrial C budget of the conterminous United States from 1971 to 2015 at 1‐km resolution using an enhanced dynamic global vegetation model and comprehensive land cover change data. Effects of atmospheric CO2 fertilization, nitrogen deposition, climate, wildland fire, harvest, and land use/land cover change (LUCC) were considered. We estimate annual C losses from cropland harvest, forest clearcut and thinning, fire, and LUCC were 436.8, 117.9, 10.5, and 10.4 TgC/year, respectively. C stored in ecosystems increased from 119,494 to 127,157 TgC between 1971 and 2015, indicating a mean annual net C sink of 170.3 TgC/year. Although ecosystem net primary production increased by approximately 12.3 TgC/year, most of it was offset by increased C loss from harvest and natural disturbance and increased ecosystem respiration related to forest aging. As a result, the strength of the overall ecosystem C sink did not increase over time. Our modeled results indicate the conterminous US C sink was about 30% smaller than previous modeling studies, but converged more closely with inventory data.

carbon sequestration↗

NASA NTRSDate not supplied

Gust Load Alleviation Control and Gust Estimation for a High Aspect Ratio Wing Wind Tunnel Model

This paper presents the gust load alleviation (GLA) study of the aspect ratio 13.5 Common Research Model (CRM) wind-tunnel model. This study details the design of the GLA controller in preparation for wind-tunnel testing in the Transonic Dynamics Tunnel at NASA Langley Research Center. An aeroservolastic (ASE) model was first reduced using a model reduction method that takes advantage of the sinusoidal steady-state response. Then, the reduced model was used to design an extended-state Kalman filter which estimates the states and the sinusoidal gust input. The GLA control was then derived using the optimal control solution to a multi-objective cost function. The results of the GLA controller indicate a 75.6% reduction in wing-root strain while maintaining robust stability margins. The final paper will include performance under sub-optimal conditions, e.g., sensor noise, uncertainty in gust frequency, etc..

Christopher Forte↗

NASA NTRSDate not supplied

Gust Load Alleviation Control and Gust Estimation for a High Aspect Ratio Wing Wind Tunnel Model

This paper presents the gust load alleviation (GLA) study of the aspect ratio 13.5 Common Research Model (CRM) wind-tunnel model. This study details the design of the GLA controller in preparation for wind-tunnel testing in the Transonic Dynamics Tunnel at NASA Langley Research Center. An aeroservolastic (ASE) model is first reduced using a model reduction method that takes advantage of the sinusoidal steady-state response. Then, the reduced model is used to design an extended-state Kalman filter which estimates the states and the sinusoidal gust input. The GLA control is then derived using the optimal control solution to a multi-objective cost function. The results of the GLA controller indicate a 69.07% reduction in wing-root strain without sensor noise and 68.45% reduction with sensor noise, while maintaining robust stability margins. An adaptive GLA controller is developed for uncertain gust frequency and shows a 71.03% reduction in wing root strain compared to the non-adaptive control reduction of just 39.19%.

Christopher Forte↗

NASA NTRS1982

The adaptation of a strap down formulation for processing inertial platform data

An estimator propagation formulation which ultilizes dynamic data (attitude and sensed acceleration information) from a gimballed inertial platform has been developed to aid in the Shuttle post-flight trajectory reconstruction process and aerodynamic coefficient determination studies. Unlike the classical inertial algorithms, this formulation yields a six degree-of-freedom fully coupled state and attitude estimate. Furthermore, this inertial version is shown to be independent of initial unknown platform misalignments. Results obtained using actual Inertial Measurement Unit (IMU) data and Aerodynamic Coefficient Identification Package (ACIP) strap down data from Shuttle flights are presented.

Heck, M. L.↗

NASA NTRS1990

Reduced-order filtering for flexible space structures

There is a need for feedback control of the large flexible space structures which are going to be increasingly important in the future of the space program. These structures are very lightly damped, and vibrations may persist for a long time when the system is disturbed unless an active feedback control strategy is used to damp out the vibrations. The system is best described by a partial differential equation description, but the more common approach is to use a large set of second order differential equations, where a large number of modes must be retained if the mathematics is to provide an adequate description of the dynamical process. Sensors, such as accelerometers and rate gyros, may provide data to the feedback controller so that it may respond appropriately to control the system. The data from the sensors is not perfect, but is subject to noise, called measurement noise, and the dynamical process itself is subject to disturbances referred to as process noise. Filtering the sensor signals to remove the measurement noise, and using the resulting state estimates to control the system are investigated.

Sims, Craig S.↗

NASA NTRS1990

Formulation of a minimum variance deconvolution technique for compensation of pneumatic distortion in pressure sensing devices

Increasingly, aircraft system designs require that aerodynamic parameters derived from pneumatic measurements be employed as control-system feedbacks. Such high frequency pressure measurements' accuracy is compromised by pressure distortion due to frictional attenuation and pneumatic resonance within the sensing system. A pneumatic distortion model is here formulated and reduced to a low-order state-variable model which retains most of the full model's dynamic characteristics. This reduced-order model is coupled with standard results from minimum variance estimation theory to develop an algorithm to compensate for pneumatic-distortion effects.

Whitmore, Stephen A.↗

NASA NTRS2023

Finding the magnetopause location using soft X-ray observations and a statistical inverse method

Variability in the location and shape of the dayside magnetopause is attributed to magnetic reconnection, a fundamental process that enables the transfer of mass, energy, and momentum from the solar wind into the magnetosphere. The spatial and temporal properties of the magnetopause, under varying solar and magnetospheric conditions, remain largely unknown because empirical studies using in-situ observations are challenging to interpret. Global wide field-of-view (FOV) imaging is the only means to simultaneously observe the spatial distribution of the plasma properties over the vast dayside magnetospheric region and, subsequently, quantify the energy transport from the interplanetary medium into the terrestrial magnetosphere. Two upcoming missions, ESA/CAS SMILE and NASA’s LEXI will provide wide-field imagery of the dayside magnetosheath in soft X-rays, an emission generated by charge exchange interactions between high charge-state heavy ions of solar wind origin and exospheric neutral atoms. High-cadence two-dimensional observations of the magnetosheath will allow the estimation of dynamic properties of its inner boundary, the magnetopause, and enable studies of its response to changes in the solar wind dynamic pressure and interplanetary magnetic field orientation. This work introduces a statistically-based estimation approach based on inverse theory to estimate the spatial distribution of magnetosheath soft X-ray emissivities and, with this, identify the location of the magnetopause over the Sun−Earth line. To do so, we simulate the magnetosheath structure using the MHD-based OpenGGCM model and generate synthetic soft X-ray images using LEXI’s orbit and attitude information. Our results show that 3-D estimations using the described statistically-based technique are robust against Poisson-distributed shot noise inherent to soft X-ray images. Also, our proposed methodology shows that the accuracy of both three-dimensional (3-D) estimation and the magnetopause standoff distance calculation highly depends on the observational point.

Gonzalo Cucho-Padin↗