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At least 163 records · Page 9

Advanced Techniques for Assessment of Postural and Locomotor Ataxia, Spatial Orientation, and Gaze Stability

In addition to adapting to microgravity, major neurovestibular problems of space flight include postflight difficulties with standing, walking, turning corners, and other activities that require stable upright posture and gaze stability. These difficulties inhibit astronauts' ability to stand or escape from their vehicle during emergencies. The long-ter7n goal of the NSBRI is the development of countermeasures to ameliorate the effects of long duration space flight. These countermeasures must be tested with valid and reliable tools. This project aims to develop quantitative, parametric approaches for assessing gaze stability and spatial orientation during normal gait and when gait is perturbed. Two of this year's most important findings concern head fixation distance and ideal trajectory analysis. During a normal cycle of walking the head moves up and down linearly. A simultaneous angular pitching motion of the head keeps it aligned toward an imaginary point in space at a distance of about one meter in front of a subject and along the line of march. This distance is called the head fixation distance. Head fixation distance provides the fundamental framework necessary for understanding the functional significance of the vestibular reflexes that couple head motion to eye motion. This framework facilitates the intelligent design of counter-measures for the effects of exposure to microgravity upon the vestibular ocular reflexes. Ideal trajectory analysis is a simple candidate countermeasure based upon quantifying body sway during repeated up and down stair stepping. It provides one number that estimates the body sway deviation from an ideal sinusoidal body sway trajectory normalized on the subject's height. This concept has been developed with NSBRI funding in less than one year. These findings are explained in more detail below. Compared to assessments of the vestibuo-ocular reflex, analysis of vestibular effects on locomotor function is relatively less well developed and quantified. We are improving this situation by applying methodologies such as nonlinear orbital stability to quantify responses and by using multivariate statistical approaches to link together the responses across separate tests. In this way we can exploit the information available and increase the ability to discriminate between normal and pathological responses. Measures of stability and orientation are compared to measures such as dynamic visual acuity and with balance function tests. The responses of normal human subjects and of patients having well documented pathophysiologies are being characterized. When these studies are completed, we should have a clearer idea about normal and abnormal patterns of eye, head, and body movements during locomotion and their stability in a wide range of environments. We plan eventually to use this information to validate the efficacy of candidate neurovestibular and neuromuscular rehabilitative techniques. Some representative studies made during this year are summarized.

Wall, Conrad., III↗

Calibration of a Spacecraft Gyro Quadruplet

This work presents a new approach to gyro calibration where, in addition to being used for computing attitude that is needed in the calibration process, the gyro outputs are also used as measurements in a Kalman filter. Gyro calibration as well as calibration of other instruments occurs in two steps. In the first step, the instrument error parameters are estimated. During the second stage, those errors are continuously removed from the gyro readings. In the classical approach to gyro calibration, the gyro outputs are used to maintain or compute body orientation rather than being used as measurements in the context of filtering. In inertial navigation, for example, gyro errors cause erroneous computation of velocity and position, and then when the latter are compared to measured velocity and position, a great portion of the computed velocity and position errors can be determined. The latter errors are then fed into a Kalman filter (KF) that uses the INS error model to infer on the gyro errors. Similarly, when applying the classical approach to spacecraft (SC) altitude determination, the gyro outputs are used to compute the attitude and then attitude measurements are used to determine the attitude errors, which again using a KF, indicates what the gyro errors are. In the approach adopted in this work the gyro outputs are used as angular rate measurements and are compared to estimated angular rate measurements. However, this approach requires the knowledge of the angular rate. In the past, the estimated angular rate was computed in a rather simplistic way assuming that the rate was constant. In the present work, the estimated angular rate is derived using a KF whose input can be any kind of attitude measurement, therefore the angular rate experienced by the SC can be continuously changing, and yet a good estimate of the rate, necessary for calibration, can be obtained.

Harman, Richard R.↗

Software Reduces Radio-Interference Effects in Radar Data

A computer program suppresses the effects of narrow-band radio-frequency interference (RFI) on the data collected by a wide-band radar system. The need for this program arises because some advanced wide-band synthetic-aperture radar systems utilize frequency bands that include frequencies used by other radio services. In this program, the RFI environment is represented by an auto-regressive process, the frequency band of which is narrow relative to that of the radar. Most of the RFI signals, both narrow- and wide-band, are estimated in one pass of a least-mean-square (LMS) adaptive filter. The program implements three popular LMS algorithms: the time-domain LMS, the frequency-domain LMS, and the filter-bank LMS adaptive-filter algorithms. The program can be run in a manual or automatic mode. In the manual mode, the user selects the filter parameters prior to execution. In the automatic mode, the program utilizes median-filter and spectral-estimation techniques plus the variable-step-size LMS algorithm for automatic determination of filter parameters, and the parameters are adaptively changed as functions of the inputs, resulting in better overall performance.

Le, Charles T-C↗

Insights into Long-Term Global Precipitation from IMERG and GPCP

Multiple satellite-based datasets provide estimates of the long-term record of global precipitation. Each necessarily includes both the real atmospheric behavior and a collection of artifacts driven by the input data sources and design choices in the retrievals and dataset construction. For this presentation, the Integrated Multi-satellitE Retrievals for GPM (IMERG) products from the Global Precipitation Measurement (GPM) mission’s U.S. Science Team are designed as a modern High-Resolution Precipitation Product (HRPP), while the Global Precipitation Climatology Project’s (GPCP) products are designed as a modern Climate Data Record (CDR). Although they share some common input data sources, the computational process for each is rather different. Comparing the precipitation estimates from each algorithm gives us insights into likely artifacts and the natural variations that are common to both. The goal of an HRPP is to give the best estimate of precipitation at each time step in the dataset, generally meaning that “all possible available” data are used. In contrast, the CDR is intended to provide a precipitation record that has relatively homogeneous statistics, necessary for climate analysis. Each analysis strives for both goals, of course, but this means that the HRPP uses the disparate collection of satellites whose statistics don’t quite match the ideal record, while the CDR is computed from fewer satellites that provide a relatively homogeneous set of precipitation statistics. This presentation employs the current versions of the IMERG and GPCP products, V07B and V3.2, respectively. A variety of analyses have demonstrated that IMERG has more artifacts, as expected, which tend to result from changes in the source of intercalibration for the various input satellites, namely the Combined Radar-Radiometer Algorithm using TMI and PR during the TRMM era and using GMI and DPR-Ku during the GPM era. As well, a shift occurs when the altitudes of the TRMM and GPM satellites change as a result of orbit boosts. For the most part the mean precipitation shows good continuity across these boundaries, but there are noticeable changes in the respective histograms. The latter has taken on more importance in recent years due to increased scrutiny on extremes which implicitly focus on the upper end of the precipitation histograms. The GPCP product is more homogeneous, with only one major change in calibrator, transitioning from the SSMI series of satellites to the SSMIS series of satellites in 2009. The GPCP analysis does a good job of minimizing artifacts in the means at this boundary, while the histograms show a smaller, but still noticeable shift in the histograms, a result that is similar to data boundaries in IMERG. The GPCP Daily, which is a month-by-month rescaling of the daily accumulated IMERG Final product, shows more consistency than the equivalent daily IMERG, but inherits the histogram shifts from IMERG. Given this overlay of artifacts, there is enough consistency between the products to illustrate some important long-term variations, including interannual variations, not all of which are easily attributable to ENSO events, and trends that are large regionally, but comparatively small when averaged across the globe.

precipitation↗

Weight Assessment for Fuselage Shielding on Aircraft With Open-Rotor Engines and Composite Blade Loss

The Federal Aviation Administration (FAA) has been engaged in discussions with airframe and engine manufacturers concerning regulations that would apply to new technology fuel efficient "openrotor" engines. Existing regulations for the engines and airframe did not envision features of these engines that include eliminating the fan blade containment systems and including two rows of counter-rotating blades. Damage to the airframe from a failed blade could potentially be catastrophic. Therefore the feasibility of using aircraft fuselage shielding was investigated. In order to establish the feasibility of this shielding, a study was conducted to provide an estimate for the fuselage shielding weight required to provide protection from an open-rotor blade loss. This estimate was generated using a two-step procedure. First, a trajectory analysis was performed to determine the blade orientation and velocity at the point of impact with the fuselage. The trajectory analysis also showed that a blade dispersion angle of 3deg bounded the probable dispersion pattern and so was used for the weight estimate. Next, a finite element impact analysis was performed to determine the required shielding thickness to prevent fuselage penetration. The impact analysis was conducted using an FAA-provided composite blade geometry. The fuselage geometry was based on a medium-sized passenger composite airframe. In the analysis, both the blade and fuselage were assumed to be constructed from a T700S/PR520 triaxially-braided composite architecture. Sufficient test data on T700S/PR520 is available to enable reliable analysis, and also demonstrate its good impact resistance properties. This system was also used in modeling the surrogate blade. The estimated additional weight required for fuselage shielding for a wing- mounted counterrotating open-rotor blade is 236 lb per aircraft. This estimate is based on the shielding material serving the dual use of shielding and fuselage structure. If the shielding material is not used for dual purpose, and is only used for shielding, then the additional weight per aircraft is estimated to be 428 lb. This weight estimate is based upon a number of assumptions that would need to be revised when applying this concept to an actual airplane design. For example, the weight savings that will result when there is no fan blade containment system, manufacturing limitations which may increase the weight where variable thicknesses was assumed, engine placement on the wing versus aft fuselage, etc.

aircraft safety↗

An investigation of gap heating due to stepped tiles in zero pressure gradient regions of the Shuttle Orbiter Thermal Protection System

An analytical study is presented which investigates the cause of the excessive heating in the tile-to-tile gaps of the Shuttle Orbiter Thermal Protection System, as evidenced by the visible discoloration and charring of the filler bar and strain isolation pad used in the attachment of tiles to the aluminum substrate. Techniques are developed to estimate the pressure disturbances due to a stepped tile and to calculate the disturbance-induced mass flow rates in the tile-to-tile gaps, filler bar, strain isolation pad, and the tile itself. A thermal analysis in the tile-to-tile gap is then performed in order to determine the temperature response to the hot gas flow. Calculations are performed at locations on the fuselage and the left wing where damaged filler bars were observed on the first flight of the Shuttle. It is concluded that the steps and gaps must be controlled within tight tolerances during tile installation and the tolerances must be maintained in flight. If the tolerances cannot be maintained, tile-to-tile gap filler may be an alternative.

Smith, D. M.↗

The augmented Lagrangian method for parameter estimation in elliptic systems

In this paper a new technique for the estimation of parameters in elliptic partial differential equations is developed. It is a hybrid method combining the output-least-squares and the equation error method. The new method is realized by an augmented Lagrangian formulation, and convergence as well as rate of convergence proofs are provided. Technically the critical step is the verification of a coercivity estimate of an appropriately defined Lagrangian functional. To obtain this coercivity estimate a seminorm regularization technique is used.

Ito, Kazufumi↗

Synergistic Retrievals of Ice in High Clouds From Elastic Backscatter Lidar, Ku-band Radar and Submillimeter Wave Radiometer Observations

In this study, we investigate the synergy of elastic backscatter lidar, Ku-band radar, and sub-millimeter-wave radiometer measurements in the retrieval of ice from satellite observations. The synergy is analyzed through the generation of a large dataset of IceWater Content (IWC) profiles and simulated lidar, radar and radiometer observations. The characteristics of the instruments e.g. frequencies, sensitivities, etc. are set based on the expected characteristics of instruments of the Atmosphere Observing System (AOS) mission. A hold-out validation methodology is used to assess the accuracy of the IWC profiles retrieved from various combinations of observations from the three instruments. Specifically, the IWC and associated observations are randomly divided into two datasets, one for training and the other for evaluation. The training dataset is used to train the retrieval algorithm, while the evaluation dataset is used to assess the retrieval performance. The dataset of IWC profiles is derived from CloudSat reflectivity and CALIOP lidar observations. The retrieval of the ice water content IWC profiles from the computed observations is achieved in two steps. In the first step, a class, out of 18 potential classes characterized by different vertical distribution of IWC, is estimated from the observations. The 18 classes are predetermined based on the k-Means clustering algorithm. In the second step, the IWC profile is estimated using an Ensemble Kalman Smoother (EKS) algorithm that uses the estimated class as a priori information. The results of the study show that the synergy of lidar, radar, and radiometer observations is significant in the retrieval of the IWC profiles. Nevertheless, it should be mentioned that this synergy was found under idealized conditions, and additional work might be required to materialize it in practice. The inclusion of the lidar backscatter observations in the retrieval process has a larger impact on the retrieval performance than the inclusion of the radar observations. As ice clouds have a significant impact on atmospheric radiative processes, this work is relevant to ongoing efforts to reduce uncertainties in climate analyses and projections.

Mircea Grecu↗

Models implemented in the methodological approach to design the initial STEP first wall contour

The official Spherical Tokamak for Energy Production mission aims to demonstrate the ability to generate net electricity from fusion with the STEP Prototype Power plant. One of the key technological and engineering challenges in fusion power plants is managing the loads on the first wall within acceptable limits. Therefore, the conceptual design development of the STEP Prototype Power plant needs to be based on load estimates derived using legitimate plasma physics assumptions through dynamic and flexible tools. The current design foresees the STEP main chamber first wall to withstand steady-state heat loads of up to ~1 MW/m 2 , excluding critical regions expected to receive higher heat loads such as the baffle regions approaching the divertors. These critical areas will require ad hoc assessments and will be designed with the presence of limiters. This article focuses on the models and methodology adopted for designing the 2-D poloidal contour of the STEP first wall, based on the anticipated charged particle and radiation heat loads during normal operation. Firstly, the models adopted for calculating the charged particle and radiation heat loads are introduced. The first model is validated through benchmarking against the particle tracing code SMARDDA, while the second model is verified by comparing it with data from the MAST-U experiment. Secondly, the model used to design the 2-D first wall contour according to the heat loads is explained. We acknowledge that this preliminary design stage assumes certain simplifications, notably an axisymmetric geometry, for computational efficiency and clarity in presentation. It is understood that subsequent design phases will address the complexities of real-world engineering, including non-axisymmetric effects, transient plasma scenarios, and the impact of disruptions on the first wall design. Finally, an automatic procedure based on these models is presented for defining the 2-D poloidal contour of the STEP first wall to minimize heat loads, taking into account the need to radiate most of the alpha-particle and auxiliary heating power. Here, by providing an overview of the models, methodology, and an automatic procedure, this paper contributes to the design process of the STEP first wall, addressing the engineering challenges associated with fusion power plant development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Estimation of Soil Moisture Profile using a Simple Hydrology Model and Passive Microwave Remote Sensing

Soil moisture is an important component of analysis in many Earth science disciplines. Soil moisture information can be obtained either by using microwave remote sensing or by using a hydrologic model. In this study, we combined these two approaches to increase the accuracy of profile soil moisture estimation. A hydrologic model was used to analyze the errors in the estimation of soil moisture using the data collected during Huntsville '96 microwave remote sensing experiment in Huntsville, Alabama. Root mean square errors (RMSE) in soil moisture estimation increase by 22% with increase in the model input interval from 6 hr to 12 hr for the grass-covered plot. RMSEs were reduced for given model time step by 20-50% when model soil moisture estimates were updated using remotely-sensed data. This methodology has a potential to be employed in soil moisture estimation using rainfall data collected by a space-borne sensor, such as the Tropical Rainfall Measuring Mission (TRMM) satellite, if remotely-sensed data are available to update the model estimates.

Soman, Vishwas V.↗

Evaluation of GlassNet for physics-informed machine learning of glass stability and glass-forming ability

Glassy materials form the basis of many modern applications, including nuclear waste immobilization, touch-screen displays, and optical fibers, and also hold great potential for future medical and environmental applications. However, their structural complexity and large composition space make design and optimization challenging for certain applications. Of particular importance for glass processing and design is an estimate of a given composition's glass-forming ability (GFA). However, there remain many open questions regarding the underlying physical mechanisms of glass formation, especially in oxide glasses. It is apparent that a proxy for GFA would be highly useful in glass processing and design, but identifying such a surrogate property has proven itself to be difficult. While glass stability (GS) parameters have historically been used as a GFA surrogate, recent research has demonstrated that most of these parameters are not accurate predictors of the GFA of oxide glasses. Here, in this work, we explore the application of an open-source pre-trained neural network model, GlassNet, that can predict the characteristic temperatures necessary to compute GS with reasonable performance and assess the feasibility of using these physics-informed machine learning (PIML)-predicted GS parameters to estimate GFA. In doing so, we track the uncertainties at each step of the computation—from the original ML prediction errors to the compounding of errors during GS estimation, and finally to the final estimation of GFA. While GlassNet exhibits reasonable accuracy on all individual properties, we observe a large compounding of error in the combination of these individual predictions for the PIML prediction of GS, finding that random forest models offer similar accuracy to GlassNet. We also break down the performance of GlassNet on different glass families and find that the error in GS prediction is correlated with the error in crystallization peak temperature prediction. Lastly, we utilize this finding to assess the relationship between top-performing GS parameters and GFA for two ternary glass systems: sodium borosilicate and sodium iron phosphate glasses. We conclude that to obtain true ML predictive capability of GFA, significantly more data needs to be collected.

36 MATERIALS SCIENCE↗

Parameter Estimation for Compact Binary Coalescence Signals with the First Generation Gravitational-Wave Detector Network

Compact binary systems with neutron stars or black holes are one of the most promising sources for ground-based gravitational-wave detectors. Gravitational radiation encodes rich information about source physics; thus parameter estimation and model selection are crucial analysis steps for any detection candidate events. Detailed models of the anticipated waveforms enable inference on several parameters, such as component masses, spins, sky location and distance, that are essential for new astrophysical studies of these sources. However, accurate measurements of these parameters and discrimination of models describing the underlying physics are complicated by artifacts in the data, uncertainties in the waveform models and in the calibration of the detectors. Here we report such measurements on a selection of simulated signals added either in hardware or software to the data collected by the two LIGO instruments and the Virgo detector during their most recent joint science run, including a blind injection where the signal was not initially revealed to the collaboration. We exemplify the ability to extract information about the source physics on signals that cover the neutron-star and black-hole binary parameter space over the component mass range 1M25M and the full range of spin parameters. The cases reported in this study provide a snapshot of the status of parameter estimation in preparation for the operation of advanced detectors.

Aasi, J.↗

Incorporating Risk

This presentation is about cost risk identification and estimation which is only a part of risk management. The purpose of this step is to identify common software risks, to assess their impact on the cost estimate, and to make revisions to the estimate based on these impacts.

Risk identifcation↗

Machine learning-driven predictive resource management in complex science workflows

Here, the collaborative efforts of large communities in science experiments, often comprising thousands of global members, reflect a monumental commitment to exploration and discovery. Recently, advanced and complex data processing has gained increasing importance in science experiments. Data processing workflows typically consist of multiple intricate steps, and the precise specification of resource requirements is crucial for each step to allocate optimal resources for effective processing. Estimating resource requirements in advance is challenging due to a wide range of analysis scenarios, varying skill levels among community members, and the continuously increasing spectrum of computing options. One practical approach to mitigate these challenges involves initially processing a subset of each step to measure precise resource utilization from actual processing profiles before completing the entire step. While this two-staged approach enables processing on optimal resources for most of the workflow, it has drawbacks such as initial inaccuracies leading to potential failures and suboptimal resource usage, along with overhead from waiting for initial processing completion, which is critical for fast-turnaround analyses. In this context, our study introduces a novel pipeline of machine learning models within a comprehensive workflow management system, the Production and Distributed Analysis (PanDA) system. These models employ advanced machine learning techniques to predict key resource requirements, overcoming challenges posed by limited upfront knowledge of characteristics at each step. Accurate forecasts of resource requirements enable informed and proactive decision-making in workflow management, enhancing the efficiency of handling diverse, complex workflows across heterogeneous resources.

97 MATHEMATICS AND COMPUTING↗

Coherent reference generator phase stability

Approximate phase stability estimates for the coherent reference generator (CRG) unit in the DSN's Frequency and Timing Subsystem (FTS) are calculated. The method used involves estimating the phase noise introduced by CRG components based upon measurements made in the past on similar components in other parts of the FTS and obtaining the CRG phase noise from the component phase noises. Three estimates of phase stability are calculated: the fractional frequency change for a 5 C step in temperature, the phase noise spectral density, and the Allan standard deviation. It is found from these estimates that the CRG phase stability is better than that of the H-maser physics unit + receiver. Thus, the first step in improving FTS phase stability would be to make improvements in the H-maser physics unit + receiver. These results are corroborated by indirect clock stability estimates calculated from Doppler data.

Korwar, V. N.↗

Estimation With Range Dependent Sensor Model

This paper focuses on the improvement of target tracking accuracy taking into account the sensor’s reading degradation as the relative range increases. The approach is based on the assumption that range measurement error depends on the actual range. Specifically, we model the measurement error as a proportional to the actual range term plus a zero-mean, Gaussian distributed, and uncorrelated process. We present two approaches to tracking a target with constant velocity model. The first approach uses Extended Kalman Filter (EKF) framework to estimate target's states and the unknown proportionality coefficient with linearization on the observation model on the predicted states at each time step. The second one uses a measurement conversion method to estimate the target's scaled by the unknown constant term states, which is shown to be unbiased. This conversion results in linear state and observation models, hence the standard Kalman filter can be applied. The actual target state is computed by application of back scaling with the estimate of unknown scale factor. We evaluate the approaches in desktop simulations.

Target tracking↗

Vision Based Localization in Urban Environments

As part of DARPA's MARS2020 program, the Jet Propulsion Laboratory developed a vision-based system for localization in urban environments that requires neither GPS nor active sensors. System hardware consists of a pair of small FireWire cameras and a standard Pentium-based computer. The inputs to the software system consist of: 1) a crude grid-based map describing the positions of buildings, 2) an initial estimate of robot location and 3) the video streams produced by each camera. At each step during the traverse the system: captures new image data, finds image features hypothesized to lie on the outside of a building, computes the range to those features, determines an estimate of the robot's motion since the previous step and combines that data with the map to update a probabilistic representation of the robot's location. This probabilistic representation allows the system to simultaneously represent multiple possible locations, For our testing, we have derived the a priori map manually using non-orthorectified overhead imagery, although this process could be automated. The software system consists of two primary components. The first is the vision system which uses binocular stereo ranging together with a set of heuristics to identify features likely to be part of building exteriors and to compute an estimate of the robot's motion since the previous step. The resulting visual features and the associated range measurements are software component, a particle-filter based localization system. This system uses the map and the then fed to the second primary most recent results from the vision system to update the estimate of the robot's location. This report summarizes the design of both the hardware and software and will include the results of applying the system to the global localization of a robot over an approximately half-kilometer traverse across JPL'S Pasadena campus.

unmanned-ground vehicles↗

Science challenges and research opportunities for plasma applications in microelectronics

Low-temperature plasmas (LTPs) are essential to manufacturing devices in the semiconductor industry, from creating extreme ultraviolet photons used in the most advanced lithography to thin film etching, deposition, and surface modifications. It is estimated that 40%–45% of all process steps needed to manufacture semiconductor devices use LTPs in one form or another. LTPs have been an enabling technology in the multidecade progression of the shrinking of device dimensions, often referred to as Moore’s law. New challenges in circuit and device design, novel materials, and increasing demands to achieve environmentally benign processing technologies require advances in plasma technology beyond the current state-of-the-art. The Department of Energy Office of Science Fusion Energy Sciences held a workshop titled Plasma Science for Microelectronics Nanofabrication in August 2022 to discuss the plasma science challenges and technical barriers that need to be overcome to continue to develop the innovative plasma technologies required to support and advance the semiconductor industry. One of the key outcomes of the workshop was identifying a set of priority research opportunities (PROs) to focus attention on the most strategic plasma science challenges to address to benefit the semiconductor industry. For each PRO, scientific challenges and recommended strategies to address those challenges were identified. Furthermore, this article summarizes the PROs identified by the workshop participants.

36 MATERIALS SCIENCE↗