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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

The design of a model-following control system for helicopters

The design of an explicit model-following control system is described and the results of a ground-based simulation experiment investigating the performance and limitations of this control system for a hingeless-rotor and a teetering-rotor helicopter are reported. The explicit model was a linear, decoupled model such that the pilot commanded pitch attitude with the longitudinal cyclic, roll attitude with the lateral cyclic, yaw rate with the pedals, and earth-fixed vertical velocity with the collective. A new model-following performance criterion was developed to optimize the control-law design and to evaluate the model-following performance. The results of the simulation indicate that the performance of the model-following control system is dependent on the dynamics of the explicit model and on the limitations of the actuating system. Increases in the bandwidth of the explicit model placed higher demands on the control system and resulted in degraded model-following performance. Significant improvements in model-following performance were achieved when a control-law switching feature, which was designed to account for position- or rate-limited actuators, was included in the control system. The excellent overall model-following performance obtained for these two radically different helicopters indicates the flexibility and versatility of this control technique.

Hilbert, K. B.↗
NASA NTRS1985

Understanding the Radiant Scattering Behavior of Vegetated Scenes

Knowledge of the physics of the scattering behavior of vegetation will ultimately serve the remote sensing and earth science community in many ways. For example, it will provide: (1) insight and guidance in developing new extraction techniques of canopy characteristics, (2) a basis for better interpretation of off-nadir satellite and aircraft data, (3) a basis for defining specifications of future earth observing sensor systems, and (4) a basis for defining important aspects of physical and biological processes of the plant system. The overall objective of the three-year study is to improve our fundamental understanding of the dynamics of directional scattering properties of vegetation canopies through analysis of field data and model simulation data. The specific objectives are to: (1) collect directional reflectance data covering the entire exitance hemisphere for several common vegetation canopies with various geometric structure (both homogeneous and row crop structures), (2) develop a scene radiation model with a general mathematical framework which will treat 3-D variability in heterogeneous scenes and account for 3-D radiant interactions within the scene, (3) conduct validations of the model on collected data sets, and (4) test and expand proposed physical scattering mechanisms involved in reflectance distribution dynamics by analyzing both field and modeling data.

Kimes, D. S.↗
DOE OSTI2023

3P Program: Phenotyping X Prediction = Productivity (Final Scientific/Technical Report)

The goal of the 3P Program was to establish integrated, real-time phenotyping and to analyze above- and below-ground plant architecture and total carbon partitioning and allocation to predict heterosis and develop superior crop hybrids by fully leveraging the Sorghum gene pool. There were two overarching themes: 1) the development of a new crop improvement approach utilizing advances in high-throughput phenotyping (HTP), computing, and genomics for public dissemination and 2) leveraging this platform for sorghum crop improvement and commercialization. The Clemson team worked on creating genomic resources and using both statistical learning and high-throughput phenotyping in genomics-assisted breeding. Research was broadly interested in the genetics of carbon partitioning, with the aim of improving crop performance and achieving sustainability. The technology and resources created can be readily found in the public domain and serve to advance scientific understanding of crop genomics and breeding. Genomic prediction was able to identify top crosses to be made, and a hybrid prediction pipeline is in place to drive year-over-year genetic gain. Roots have long been ignored by plant breeders and agronomists, not because they are unimportant but because they are hard to measure. This is an untapped white space of potential insight and innovation. To address this, Hi Fidelity Genetics developed the RootTracker to measure roots in the field on a continuous basis. A database system called RootTracker Tracker was developed to handle data coming from the RootTrackers. In using this device, valuable data was observed for plant breeding, hydrochemical development, and other agricultural biology applications. Carnegie Mellon’s goal was developing new techniques to generate high-resolution 3D models of plants from data collected in the field. The idea was that more useful and more informative phenotypes could be extracted by resolving small features, such as seeds and flowers, and that by modeling in 3D, the spatial structure of plants could be examined. To achieve this, multiple images collected by a new small format structured light stereo imager were fused together. A sorghum panicle modeling pipeline was developed to allow the collection and processing of data. Carolina Seed Systems is an agricultural technology company focused on decarbonizing the agricultural system. Their technology pipeline serves to drive fundamental progress towards creation and distribution of carbon negative crops. The genomic and the engineering technology developed through the 3P Program was leveraged to deliver both value and sustainability from the grower to the consumer. Promising sorghum hybrids were scaled up and commercialized. The overall goal of our research was to integrate, create, and deploy genetic and engineering concepts and technologies to enhance crop productivity in a sustainable fashion. The combination of public and private partners allowed the basic research and hypothesis testing to be quickly accelerated for commercial application by the companies yet maintained that the core framework and academic insights remain in the public domain for continued market disruption, competition, and innovation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

System Reliability Analysis Capability and Surrogate Model Application in RAVEN

This report collect the effort performed to improve the reliability analysis capabilities of the RAVEN code and explore new opportunity in the usage of surrogate model by extending the current RAVEN capabilities to multi physics surrogate models and construction of surrogate models for high dimensionality fields.

31274↗
DOE OSTI2024

Experimental validation of a Kalman observer using linearized OpenFAST and a fully instrumented 1:70 model

Abstract To enable real‐time monitoring and control strategies for floating offshore wind turbines, accurate information about the state of the system is needed. This paper details the application of a Kalman filter to the UMaine VolturnUS‐S floating wind platform to provide accurate state estimates in real time using minimal system measurements. The midfidelity nonlinear simulation tool OpenFAST was used to generate the underlying linear state‐space model for the Kalman filter. This linear model and its limitations are demonstrated through comparison with experimental data collected on a 1:70 froude‐scaled model of the floating platform and tower. Using a selection of five measurements from the real system, a Kalman filter was developed to provide estimates for the remaining system states and measurements. These estimates were then validated against the experimental values collected from testing of the scale model. Validation of the Kalman filter produced accurate estimates of surge, heave, and tower base bending moment, measurements of which were not available to the Kalman filter. Performance of the Kalman filter was tested and validated over a range of sea conditions from rated wind speed to storm events and demonstrated robustness in the Kalman filter to maintain accuracy across all operating conditions despite significant error in the underlying linear model for extreme conditions.

17 WIND ENERGY↗
DOE OSTI2019

Mechanical-force-induced non-local collective ferroelastic switching in epitaxial lead-titanate thin films

Ferroelastic switching in ferroelectric/multiferroic oxides plays a crucial role in determining their dielectric, piezoelectric, and magnetoelectric properties. In thin films of these materials, however, substrate clamping is generally thought to limit the electric-field- or mechanical-force-driven responses to the local scale. Here, we report mechanical-force-induced large-area, non-local, collective ferroelastic domain switching in PbTiO 3 epitaxial thin films by tuning the misfit-strain to be near a phase boundary wherein c/a and a 1 / a 2 nanodomains coexist. Phenomenological models suggest that the collective, c-a-c-a ferroelastic switching arises from the small potential barrier between the degenerate domain structures, and the large anisotropy of a and c domains, which collectively generates much larger response and large-area domain propagation. Large-area, non-local response under small stimuli, unlike traditional local response to external field, provides an opportunity of unique response to local stimuli, which has potential for use in high-sensitivity pressure sensors and switches.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Breaking of axial symmetry in excited heavy nuclei as identified in giant dipole resonance data

Here, a recent theoretical prediction of a breaking of axial symmetry in quasi all heavy nuclei is confronted to a new critical analysis of photon strength functions of nuclei in the valley of stability. For the photon strength in the isovector giant dipole resonance (IVGDR) regime a parameterization of GDR shapes by the sum of three Lorentzians (TLO) is extrapolated to energies below and above the IVGDR. The impact of non-GDR modes adding to the low energy slope of photon strength is discussed including recent data on photon scattering and other radiative processes. These are shown to be concentrated in energy regions where various model calculations predict intermediate collective strength; thus they are obviously separate from the IVGDR tail. The triple Lorentzian (TLO) ansatz for giant dipole resonances is normalized in accordance to the dipole sum rule. The nuclear droplet model with surface dissipation accounts well for positions and widths without local, nuclide specific, parameters. Very few and only global parameters are needed when a breaking of axial symmetry already in the valley of stability is admitted and hence a reliable prediction for electric dipole strength functions also outside of it is expected.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2000

Microwave Driven Actuators Power Allocation and Distribution

Design, fabrication and test of a power allocation and distribution (PAD) network for microwave driven actuators is presented in this paper. Development of a circuit that would collect power from a rectenna array amplify and distribute the power to actuators was designed and fabricated for space application in an actuator array driven by a microwave. A P-SPICE model was constructed initially for data reduction purposes, and was followed by a working real-world model. A voltage up - converter (VUC) is used to amplify the voltage from the individual rectenna. The testing yielded a 26:1 voltage amplification ratio with input voltage at 9 volts and a measured output voltage 230VDC. Future work includes the miniaturization of the circuitry, the use of microwave remote control, and voltage amplification technology for each voltage source. The objective of this work is to develop a model system that will collect DC voltage from an array of rectenna and propagate the voltage to an array of actuators.

Forbes, Timothy↗
DOE OSTI2010

Growth model of binary alloy nanopowders for thermal plasma synthesis

A new model is developed for numerical analysis of the entire growth process of binary alloy nanopowders in thermal plasma synthesis. The model can express any nanopowder profile in the particle size-composition distribution (PSCD). Moreover, its numerical solution algorithm is arithmetic and straightforward so that the model is easy to use. By virtue of these features, the model effectively simulates the collective and simultaneous combined process of binary homogeneous nucleation, binary heterogeneous cocondensation, and coagulation among nanoparticles. The effect of the freezing point depression due to nanoscale particle diameters is also considered in the model. In this study, the metal-silicon systems are particularly chosen as representative binary systems involving cocondensation processes. In consequence, the numerical calculation with the present model reveals the growth mechanisms of the Mo-Si and Ti-Si nanopowders by exhibiting their PSCD evolutions. The difference of the materials' saturation pressures strongly affects the growth behaviors and mature states of the binary alloy nanopowder.

36 MATERIALS SCIENCE↗
DOE OSTI2010

A survey of techniques to estimate the uncertainty in material parameters.

When estimating parameters for a material model from experimental data collected during a separate effects physics experiment, the quality of fit is only a part of the required data. Also necessary is the uncertainty in the estimated parameters so that uncertainty quantification and model validatino can be performed at the full system level. The uncertainty and quality of fit of the data are many times not available and should be considered when fitting the data to a specified model. There are many techniques available to fit data to a material model and a few of them are presented in this work using a simple acoustical emission dataset. The estimated parameters and the affiliated uncertainty will be estimated using a variety of techniques and compared.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Derivation of physical and optical properties of mid-latitude cirrus ice crystals for a size-resolved cloud microphysics model

Abstract. Single-crystal images collected in mid-latitude cirrus are analyzed to provide internally consistent ice physical and optical properties for a size-resolved cloud microphysics model, including single-particle mass, projected area, fall speed, capacitance, single-scattering albedo, and asymmetry parameter. Using measurements gathered during two flights through a widespread synoptic cirrus shield, bullet rosettes are found to be the dominant identifiable habit among ice crystals with maximum dimension (Dmax) greater than 100 µm. Properties are therefore first derived for bullet rosettes based on measurements of arm lengths and widths, then for aggregates of bullet rosettes and for unclassified (irregular) crystals. Derived bullet rosette masses are substantially greater than reported in existing literature, whereas measured projected areas are similar or lesser, resulting in factors of 1.5–2 greater fall speeds, and, in the limit of large Dmax, near-infrared single-scattering albedo and asymmetry parameter (g) greater by -0.2 and 0.05, respectively. A model that includes commonly imaged side plane growth on bullet rosettes exhibits relatively little difference in microphysical and optical properties aside from -0.05 increase in mid-visible g primarily attributable to plate aspect ratio. In parcel simulations, ice size distribution, and g are sensitive to assumed ice properties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Using an external surrogate for predictor model training in real-time motion management of lung tumors

Purpose: Precise prediction of respiratory motion is a prerequisite for real-time motion compensation techniques such as beam, dynamic couch, or dynamic multileaf collimator tracking. Collection of tumor motion data to train the prediction model is required for most algorithms. To avoid exposure of patients to additional dose from imaging during this procedure, the feasibility of training a linear respiratory motion prediction model with an external surrogate signal is investigated and its performance benchmarked against training the model with tumor positions directly. Methods: The authors implement a lung tumor motion prediction algorithm based on linear ridge regression that is suitable to overcome system latencies up to about 300 ms. Its performance is investigated on a data set of 91 patient breathing trajectories recorded from fiducial marker tracking during radiotherapy delivery to the lung of ten patients. The expected 3D geometric error is quantified as a function of predictor lookahead time, signal sampling frequency and history vector length. Additionally, adaptive model retraining is evaluated, i.e., repeatedly updating the prediction model after initial training. Training length for this is gradually increased with incoming (internal) data availability. To assess practical feasibility model calculation times as well as various minimum data lengths for retraining are evaluated. Relative performance of model training with external surrogate motion data versus tumor motion data is evaluated. However, an internal–external motion correlation model is not utilized, i.e., prediction is solely driven by internal motion in both cases. Results: Similar prediction performance was achieved for training the model with external surrogate data versus internal (tumor motion) data. Adaptive model retraining can substantially boost performance in the case of external surrogate training while it has little impact for training with internal motion data. A minimum adaptive retraining data length of 8 s and history vector length of 3 s achieve maximal performance. Sampling frequency appears to have little impact on performance confirming previously published work. By using the linear predictor, a relative geometric 3D error reduction of about 50% was achieved (using adaptive retraining, a history vector length of 3 s and with results averaged over all investigated lookahead times and signal sampling frequencies). The absolute mean error could be reduced from (2.0 ± 1.6) mm when using no prediction at all to (0.9 ± 0.8) mm and (1.0 ± 0.9) mm when using the predictor trained with internal tumor motion training data and external surrogate motion training data, respectively (for a typical lookahead time of 250 ms and sampling frequency of 15 Hz). Conclusions: A linear prediction model can reduce latency induced tracking errors by an average of about 50% in real-time image guided radiotherapy systems with system latencies of up to 300 ms. Training a linear model for lung tumor motion prediction with an external surrogate signal alone is feasible and results in similar performance as training with (internal) tumor motion. Particularly for scenarios where motion data are extracted from fluoroscopic imaging with ionizing radiation, this may alleviate the need for additional imaging dose during the collection of model training data.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1989

Application of photometric models to asteroids

The way an asteroid or other atmosphereless solar system body varies in brightness in response to changing illumination and viewing geometry depends in a very complicated way on the physical and optical properties of its surface and on its overall shape. This paper summarizes the formulation and application of recent photometric models by Hapke (1981, 1984, 1986) and by Lumme and Bowell (1981). In both models, the brightness of a rough and porous surface is parameterized in terms of the optical properties of individual particles, by shadowing between particles, and by the way in which light is scattered among collections of particles. Both models succeed in their goal of fitting the observed photometric behavior of a wide variety of bodies, but neither has led to a very complete understanding of the properties of asteroid regoliths, primarily because, in most cases, the parameters in the present models cannot be adequately constrained by observations of integral brightness alone over a restricted range of phase angles.

Bowell, Edward↗
NASA NTRS2022

An Advanced Open-Source Platform for Air Quality Analysis, Visualization, and Prediction

Ambient air pollution is the largest environmental health risk factor, leading to several million premature deaths globally per year. The challenge of combating poor air quality is exacerbated by growing urban populations, changing emissions, and a warming climate. While there have been many advances monitoring and modeling of atmospheric composition, reflected in the dramatic increase in archived Earth Observations, there is no single measurement or method that alone can provide an accurate depiction of the entire atmosphere. The rapidly growing collections of observational and modeling data require us to be smarter about what data to include, and how such data is used. In recent years, NASA has invested significantly in advancing the concepts for Analytics Collaborative Framework (ACF) [5] and New Observing Strategies (NOS) [4] to tackle our software infrastructure need for harmonized data management and dynamic acquisition of diverse measurements for on-demand, interactive, multivariate analysis, and access [3]. It is not enough to have a big data, standalone analytics solution; it is critical that we start integrating data from remote sensing, modeling, and in-situ networks in a harmonized manner that enables timely and data-driven decision-making for air quality management. This work presents the design and development of an Air Quality Analytics Collaborative Framework (AQ ACF), as part of NASA’s Advanced Information Systems Technology (AIST) effort, to establish a data, machine-learning, and numerically driven platform for air quality analysis, visualization, and prediction.

Liu, Qian↗
DOE OSTI2014

Five-minute oscillation power within magnetic elements in the solar atmosphere

It has long been known that magnetic plage and sunspots are regions in which the power of acoustic waves is reduced within the photospheric layers. Recent observations now suggest that this suppression of power extends into the low chromosphere and is also present in small magnetic elements far from active regions. In this paper we investigate the observed power suppression in plage and magnetic elements, by modeling each as a collection of vertically aligned magnetic fibrils and presuming that the velocity within each fibril is the response to buffeting by incident p modes in the surrounding field-free atmosphere. We restrict our attention to modeling observations made near the solar disk center, where the line-of-sight velocity is nearly vertical and hence, only the longitudinal component of the motion within the fibril contributes. Therefore, we only consider the excitation of axisymmetric sausage waves and ignore kink oscillations as their motions are primarily horizontal. We compare the vertical motion within the fibril with the vertical motion of the incident p mode by constructing the ratio of their powers. In agreement with observational measurements we find that the total power is suppressed within strong magnetic elements for frequencies below the acoustic cut-off frequency. However, further physical effects need to be examined for understanding the observed power ratios for stronger magnetic field strengths and higher frequencies. We also find that the magnitude of the power deficit increases with the height above the photosphere at which the measurement is made. Furthermore, we argue that the area of the solar disk over which the power suppression extends increases as a function of height.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Benefits of Higher-Temperature Operation in Boosted SI Engines Enabled by Advanced Materials

To meet the demand for greater fuel efficiency in passenger vehicles, various strategies are employed to increase the power density of light-duty SI engines, with attendant thermal or system efficiency increases. One approach is to incorporate higher-performance alloys for critical engine components. These alloys can have advantageous thermal or mechanical properties at higher temperatures, allowing for components constructed from these materials to meet more severe pressure and temperature demands, while maintaining durability. Advanced alloys could reduce the need for charge enrichment to protect certain gas-path components at high speed and load conditions, permit more selective cooling to reduce heat-transfer losses, and allow engine downsizing, while maintaining performance, by achieving higher cylinder temperatures and pressures. As a first step in investigating downsizing strategies made possible through high-performance alloys, a GT-Power model of a 4-cylinder 1.6L turbocharged direct-injection SI engine was developed. The model was tuned and validated against experimental dynamometer data collected from a corresponding engine. The model was then used to investigate various operating strategies for increasing power density. Results from these investigations will provide valuable insight into how new materials might be utilized to meet the needs of future light-duty engines and will serve as the basis for a more comprehensive investigation using more-detailed thermo-mechanical modeling.

Mills, Zachary↗
DOE OSTI2010

Unintended consequences of atmospheric injection of sulphate aerosols.

Most climate scientists believe that climate geoengineering is best considered as a potential complement to the mitigation of CO{sub 2} emissions, rather than as an alternative to it. Strong mitigation could achieve the equivalent of up to -4Wm{sup -2} radiative forcing on the century timescale, relative to a worst case scenario for rising CO{sub 2}. However, to tackle the remaining 3Wm{sup -2}, which are likely even in a best case scenario of strongly mitigated CO{sub 2} releases, a number of geoengineering options show promise. Injecting stratospheric aerosols is one of the least expensive and, potentially, most effective approaches and for that reason an examination of the possible unintended consequences of the implementation of atmospheric injections of sulphate aerosols was made. Chief among these are: reductions in rainfall, slowing of atmospheric ozone rebound, and differential changes in weather patterns. At the same time, there will be an increase in plant productivity. Lastly, because atmospheric sulphate injection would not mitigate ocean acidification, another side effect of fossil fuel burning, it would provide only a partial solution. Future research should aim at ameliorating the possible negative unintended consequences of atmospheric injections of sulphate injection. This might include modeling the optimum rate and particle type and size of aerosol injection, as well as the latitudinal, longitudinal and altitude of injection sites, to balance radiative forcing to decrease negative regional impacts. Similarly, future research might include modeling the optimum rate of decrease and location of injection sites to be closed to reduce or slow rapid warming upon aerosol injection cessation. A fruitful area for future research might be system modeling to enhance the possible positive increases in agricultural productivity. All such modeling must be supported by data collection and laboratory and field testing to enable iterative modeling to increase the accuracy and precision of the models, while reducing epistemic uncertainties.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗