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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13

Estimation of Modal Parameters Using a Wavelet-Based Approach

Modal stability parameters are extracted directly from aeroservoelastic flight test data by decomposition of accelerometer response signals into time-frequency atoms. Logarithmic sweeps and sinusoidal pulses are used to generate DAST closed loop excitation data. Novel wavelets constructed to extract modal damping and frequency explicitly from the data are introduced. The so-called Haley and Laplace wavelets are used to track time-varying modal damping and frequency in a matching pursuit algorithm. Estimation of the trend to aeroservoelastic instability is demonstrated successfully from analysis of the DAST data.

Lind, Rick↗

On the robustness of a Bayes estimate

This paper examines the robustness of a Bayes estimator with respect to the assigned prior distribution. A Bayesian analysis for a stochastic scale parameter of a Weibull failure model is summarized in which the natural conjugate is assigned as the prior distribution of the random parameter. The sensitivity analysis is carried out by the Monte Carlo method in which, although an inverted gamma is the assigned prior, realizations are generated using distribution functions of varying shape. For several distributional forms and even for some fixed values of the parameter, simulated mean squared errors of Bayes and minimum variance unbiased estimators are determined and compared. Results indicate that the Bayes estimator remains squared-error superior and appears to be largely robust to the form of the assigned prior distribution.

Canavos, G. C.↗

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↗

Real-Time Sea State Estimation for Wave Energy Converter Control via Machine Learning

Wave energy converters (WECs) harness the untapped power of ocean waves to generate renewable energy, offering a promising solution to sustainable energy. An optimal WEC control strategy is essential to maximize power capture that dynamically adjusts system parameters in response to rapidly changing sea states. This study presents a novel control approach that leverages neural networks to estimate sea states from onboard WEC measurements such as position, velocity, and force. Using a point absorber WEC device as a test platform, our proposed approach estimates sea states in real-time and subsequently adjusts PID controller gains to maximize energy extraction. Simulation results across diverse sea conditions demonstrate that our strategy eliminates the need for external wave monitoring equipment while maintaining power capture efficiency. The results show that our neural network-based control technique can improve power capture by 25.6% while significantly reducing system complexity. This approach offers a practical alternative for WEC deployments where direct wave measurements are either infeasible or cost prohibitive.

PIDcontrol↗

Voxel carving–based 3D reconstruction of sorghum identifies genetic determinants of light interception efficiency

Changes in canopy architecture traits have been shown to contribute to yield increases. Optimizing both light interception and light interception efficiency of agricultural crop canopies will be essential to meeting the growing food needs. Canopy architecture is inherently three-dimensional (3D), but many approaches to measuring canopy architecture component traits treat the canopy as a two-dimensional (2D) structure to make large scale measurement, selective breeding, and gene identification logistically feasible. We develop a high throughput voxel carving strategy to reconstruct 3D representations of sorghum from a small number of RGB photos. Our approach builds on the voxel carving algorithm to allow for fully automatic reconstruction of hundreds of plants. It was employed to generate 3D reconstructions of individual plants within a sorghum association population at the late vegetative stage of development. Light interception parameters estimated from these reconstructions enabled the identification of known and previously unreported loci controlling light interception efficiency in sorghum. The approach is generalizable and scalable, and it enables 3D reconstructions from existing plant high throughput phenotyping datasets. We also propose a set of best practices to increase 3D reconstructions’ accuracy.

3D plant reconstruction↗

Electric vehicle batteries alone could satisfy short-term grid storage demand by as early as 2030

The energy transition will require a rapid deployment of renewable energy (RE) and electric vehicles (EVs) where other transit modes are unavailable. EV batteries could complement RE generation by providing short-term grid services. However, estimating the market opportunity requires an understanding of many socio-technical parameters and constraints. We quantify the global EV battery capacity available for grid storage using an integrated model incorporating future EV battery deployment, battery degradation, and market participation. We include both in-use and end-of-vehicle-life use phases and find a technical capacity of 32–62 terawatt-hours by 2050. Low participation rates of 12%–43% are needed to provide short-term grid storage demand globally. Participation rates fall below 10% if half of EV batteries at end-of-vehicle-life are used as stationary storage. Short-term grid storage demand could be met as early as 2030 across most regions. Our estimates are generally conservative and offer a lower bound of future opportunities.

25 ENERGY STORAGE↗

Satellite rainfall retrieval by logistic regression

The potential use of logistic regression in rainfall estimation from satellite measurements is investigated. Satellite measurements provide covariate information in terms of radiances from different remote sensors.The logistic regression technique can effectively accommodate many covariates and test their significance in the estimation. The outcome from the logistical model is the probability that the rainrate of a satellite pixel is above a certain threshold. By varying the thresholds, a rainrate histogram can be obtained, from which the mean and the variant can be estimated. A logistical model is developed and applied to rainfall data collected during GATE, using as covariates the fractional rain area and a radiance measurement which is deduced from a microwave temperature-rainrate relation. It is demonstrated that the fractional rain area is an important covariate in the model, consistent with the use of the so-called Area Time Integral in estimating total rain volume in other studies. To calibrate the logistical model, simulated rain fields generated by rainfield models with prescribed parameters are needed. A stringent test of the logistical model is its ability to recover the prescribed parameters of simulated rain fields. A rain field simulation model which preserves the fractional rain area and lognormality of rainrates as found in GATE is developed. A stochastic regression model of branching and immigration whose solutions are lognormally distributed in some asymptotic limits has also been developed.

Chiu, Long S.↗

Non-Linear System Identification for Aeroelastic Systems with Application to Experimental Data

Representation and identification of a non-linear aeroelastic pitch-plunge system as a model of the NARMAX class is considered. A non-linear difference equation describing this aircraft model is derived theoretically and shown to be of the NARMAX form. Identification methods for NARMAX models are applied to aeroelastic dynamics and its properties demonstrated via continuous-time simulations of experimental conditions. Simulation results show that (i) the outputs of the NARMAX model match closely those generated using continuous-time methods and (ii) NARMAX identification methods applied to aeroelastic dynamics provide accurate discrete-time parameter estimates. Application of NARMAX identification to experimental pitch-plunge dynamics data gives a high percent fit for cross-validated data.

Kukreja, Sunil L.↗

Nonlinear System Identification for Aeroelastic Systems with Application to Experimental Data

Representation and identification of a nonlinear aeroelastic pitch-plunge system as a model of the Nonlinear AutoRegressive, Moving Average eXogenous (NARMAX) class is considered. A nonlinear difference equation describing this aircraft model is derived theoretically and shown to be of the NARMAX form. Identification methods for NARMAX models are applied to aeroelastic dynamics and its properties demonstrated via continuous-time simulations of experimental conditions. Simulation results show that (1) the outputs of the NARMAX model closely match those generated using continuous-time methods, and (2) NARMAX identification methods applied to aeroelastic dynamics provide accurate discrete-time parameter estimates. Application of NARMAX identification to experimental pitch-plunge dynamics data gives a high percent fit for cross-validated data.

Kukreja, Sunil L.↗

Integration of Uncertain Ramp Area Aircraft Trajectories and Generation of Optimal Taxiway Schedules at Charlotte Douglas (CLT) Airport

The integration of aircraft maneuver characteristics into an optimal taxiway scheduling solution is challenging due to the uncertainties that are intrinsic to ramp area aircraft trajectories. To address the challenge, we build a stochastic model of ramp area aircraft trajectories that is used to generate a probabilistic measure of conflict within the Charlotte Douglas International Airport (CLT) ramp area. Parameters of the conflict distributions are estimated and passed to a Mixed Integer Linear Program that solves for an optimal taxiway schedule constrained to be conflict free in the presence of trajectory uncertainties. Here we extend our previous research by accounting for departing and arriving aircraft whereas our prior formulation only accounted for departing aircraft.

taxiway schedule↗

Measurement of surface microtopography using helicopter-mounted stereo film cameras and two stereo matching techniques

A common problem in acquiring ground-truth data for use in microwave interaction modeling is the capture of surface roughness data that are both sampled at distances comparable to a fraction of the wavelength and extensive enough to represent the surface statistics in at least one resolution cell of the microwave remote sensor used. A technique has been developed for acquiring the necessary photogrammetric data using twin 70-mm film cameras mounted on a helicopter boom. The apparatus is described, and the accuracy with which ground surface roughness can be characterized using this device is estimated. Both standard and cross-correlation methods were used for data reduction. Stereogrammetry is compared with a completely automated image-matching technique. Dense disparity images were generated from the helicopter stereo pairs. Using interior orientation parameters supplied by the camera manufacturers, and assuming that exterior orientation parameters remain constant between control target and test field photography, an extremely dense DEM (digital elevation model) for a test field has been derived. Results are compared, and accuracy estimates are presented.

Wall, S. D.↗

Self-generated magnetic fields in the hot spot of direct-drive cryogenic implosions at Omega

This work reports that Biermann self-generated magnetic fields of ≈200 MG and Hall parameters of ≈1.5 are produced in the stagnation phase of direct-drive cryogenic implosions at Omega. The magnetic fields produce a drop of 2.4% in fusion yield and 1% in ion temperature. A quantitative estimate of the effect of self-generated magnetic fields on yield and ion temperature is essential, since direct measurements of these fields are not available. Reconstructed simulations of the 50 Gbar implosions, with all the stagnation measurements reproduced simultaneously by a combination of mid- and low-mode asymmetries as degradation mechanisms [Bose et al., Phys. Plasmas 25, 062701 (2018)], are used to obtain the estimates. The magnetic fields cause a decrease in yield due to the Righi–Leduc heat flow, which exceeds any benefits from heat flow suppression due to magnetization. It is important to note that both direct-drive Omega-scale implosions and indirect-drive National Ignition Facility (NIF)-scale implosions [Walsh et al., Phys. Rev. Lett. 118, 155001 (2017)] produce similar estimates for the magnetic field strength, and both show a decrease in fusion yield, with the Righi–Leduc transport as the loss mechanism. However, the yield degradation at Omega is small and lower by ≈5× compared to the indirect-drive ignition-scale NIF estimate.

Physics↗

First generation atmospheric probes (10-BARS) for Uranus and Neptune

The feasibility of atmospheric entry probe missions to Uranus and Neptune is studied, and preliminary estimates of missions parameters are presented. Most of the study results are applicable, with only minor modifications, to Uranus-Neptune entry probes included on any type of outer planet mission. Trajectory dynamics is discussed first because it imposes some important constraints upon the total time available for data transmission, which in turn determines the descent rate. This last quantity provides important information for the design of the scientific payload.

Sullivan, R. J.↗

Reconstruction of the 1st Space Shuttle (STS-1) entry trajectory

A discussion of the generation of the best estimate trajectory (BET) of the first Space Shuttle Orbiter entry flight is presented. The BET defines a time history of the state, attitude, and atmospheric relative parameters throughout the Shuttle entry from an altitude of approximately 183 km to rollout. The inertial parameters were estimated utilizing a weighted least squares batch filter algorithm. Spacecraft angular rate and acceleration data derived from the Inertial Measurement Unit were utilized to predict the state and attitude which was constrained in a weighted least squares process to fit external tracking data consisting of ground based S-band and C-band data. Refined spacecraft altitude and velocity during and post rollout were obtained by processing artificial altimeter and Doppler data. The BET generation process is discussed. Software and data interface discussions are included. The variables and coordinate systems utilized are defined. STS-1 mission peculiar inputs are summarized. A listing of the contents of the actual BET is provided.

Findlay, J. T.↗

Shape optimization under uncertainty for rotor blades of horizontal axis wind turbines

We present a computational framework for the shape optimization of a Horizontal-Axis Wind Turbine (HAWT) rotor blade under uncertainty. Our framework integrates aerodynamic simulations based on the blade element method which utilizes reduced order models of the blade structure and wind load with design sensitivity analysis and nonlinear programming. The wind velocity is modeled as a stochastic process to account for variations in time and space. An additional stochastic process accounts for uncertainties in the structural material properties. The uncertainty propagation is based on a non-intrusive polynomial chaos expansion that allows accurate estimation of stochastic performance metrics such as generated power and structural compliance. Sensitivities of cost and constraint functions with respect to shape parameters namely twist angles are computed with an efficient scheme to enable gradient based optimization. To demonstrate the effect of uncertainty, designs obtained from optimization under uncertainty are compared to those obtained from deterministic optimization.

42 ENGINEERING↗

Isotherm Modeling and Techno-Economic Analysis of Contactor Technologies for New Tetraamine-Appended MOF for NGCC Applications

Recently, a family of tetraamine-functionalized metal-organic frameworks (MOF) has been reported as promising sorbent materials for capturing CO2 from flue gas conditions relevant to natural gas combined cycle (NGCC) applications. The main advantages of these materials are their two-step cooperative CO2 adsorption, which gives rise to unusual two step-shaped CO2 adsorption profiles and their high thermal stability. This work presents the modelling of the two-transition isotherm of the tetraamine-appended MOF, N,N'-bis(3-aminopropyl)-1,4-diaminobutane (3-4-3)-appended Mg2(dobpdc), and the techno-economic analysis (TEA) of carbon capture processes utilizing this sorbent. Due to the unusual isotherm shapes of the experimental CO2 adsorption data for tetraamine-appended Mg2(dobpdc) and the strong nonlinearity of CO2 loading with respect to temperature and pressure, we tested two different models which use logistic functions for representing the different isotherm behaviors in the different pressure ranges. The first model uses the quadratic isotherm model in the low-pressure region, the Langmuir isotherm model in the middle pressure range, and the dual site Langmuir isotherm model in the high-pressure range. To model the transition between regions we used the arctangent functions independent of temperature and the thermal effect was accounted by using the Clausius-Clapeyron relation]. The second model is an extension of the weighted dual-site Langmuir isotherm model presented by Hughes et al.. In this extended model, the dual-site Langmuir isotherm is employed in the three transition regions, using temperature-dependent logistic functions to activate or deactivate the isotherm model in the low, middle, and high-pressure ranges. Both models fit the experimental data quite well with root mean squared errors (RMSE’s) of 0.41 and 0.17 for model 1 and model 2, respectively. Since model 2 resulted in a lower RMSE, it was leveraged for the development of the gas/solid contactor models used by the TEA. Specifically, two different contactor models, an axial-flow fixed bed and moving bed contactor, were developed as part of this work. These models are dynamic, pressure-driven, and consist of mass, energy, and momentum conservation equations. A kinetic model was also developed by performing parameter estimation using experimental fixed bed breakthrough data. These models are then used to simulate CO2 capture processes from the flue gas generated from a ~600 gross MW NGCC power plant. A cost model was developed which considers the capital cost of the reactors and the significant operating costs such as steam and electricity. Using NETL’s Framework for the Optimization and Quantification of Uncertainty of Uncertainty and Surrogates tool (FOQUS), which has the capability of linking models built using numerous modelling platforms with derivative-free optimization solvers, a techno-economic optimization of the carbon capture processes was performed which minimizes the cost of capture.

Caballero, Daison↗

Fuzzy Modeling and Parallel Distributed Compensation for Aircraft Flight Control from Simulated Flight Data

A method is described that combines fuzzy system identification techniques with Parallel Distributed Compensation (PDC) to develop nonlinear control methods for aircraft using minimal a priori knowledge, as part of NASA’s Learn-to-Fly initiative. A fuzzy model was generated with simulated flight data, and consisted of a weighted average of multiple linear time invariant state-space cells having parameters estimated using the equation-error approach and a least-squares estimator. A compensator was designed for each subsystem using Linear Matrix Inequalities (LMI) to guarantee closed-loop stability and performance requirements. This approach is demonstrated using simulated flight data to automatically develop a fuzzy model and design control laws for a simplified longitudinal approximation of the F-16 nonlinear flight dynamics simulation. Results include a comparison of flight data with the estimated fuzzy models and simulations that illustrate the feasibility and utility of the combined fuzzy modeling and control approach.

Weinstein, Rose↗