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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 1,351 records · Page 75

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NASA NTRS1973

A new approach to the design of time-varying control systems with application to the Space Shuttle Boost

A general approach to the analysis and design of closed-loop control for slowly time-varying linear systems is presented. The approach uses the method of generalized multiple scales in which slow and fast dynamics are systematically separated by employing different 'clocks' which measure time at varying rates. The clocks, which are necessarily nonlinear functions of time, are chosen in such a manner that the system dynamics are asymptotically invariant with respect to the new time scale. A transfer function relating the output to the input for general linear slowly time-varying systems is developed and represents the actual system under certain conditions. The clock function is shown to satisfy an algebraic characteristic equation and can be determined in terms of the coefficients. The approach can be viewed as an extension of time-invariant linear feedback control theory.

Ramanth, R. V.↗

NASA NTRS1981

The integrated optic RF spectrum analyzer

The results of measurements made on a fully integrated optic RF spectrum analyzer (IOSA) are reported. The performance of the device acousto-optic bandwidth, single-tone RF resolution, two-tone RF resolution, single-tone dynamic range, two-tone dynamic range, and single-tone RF response are presented. The device parameters that control device performance are analyzed. These results demonstrate the viability of the IOSA for real time spectrum analysis of pulsed and CW RF signals. Improvements of RF bandwidth resolution can be obtained by the use of larger collimated optical beams which requires larger optical lens elements, and hence, larger crystals.

Pedinoff, M. E.↗

NASA NTRS1985

Application of Ritz vectors for dynamic analysis of large structures

The use of an orthogonal set of specially selected Ritz vectors is shown to be very effective in reducing the cost of dynamic analysis by modal superposition. Several mechanical structures are examined, and the Ritz vector approach is compared to the classical eigenvector approach on the basis of cost, accuracy and elapsed analysis (throughput) time. Mathematical proof of the completeness of orthogonal Ritz vectors is provided for the case of a positive definite mass matrix and a symmetric stiffness matrix.

Arnold, R. R.↗

NASA NTRS1987

Mariner Mark II - Spacecraft control for the 1990's and beyond

The Mariner Mark II reconfigurable modular spacecraft concept will incorporate a Spacecraft Attitude and Articulation Control System of novel design. Attention is presently given to key component technologies that will be used for the first time in the Mariner Mark II; these encompass CCD-based, target-referenced extended body tracking, fiber-optic rate sensing, and momentum compensation for dynamic isolation of payloads. An analysis of star and target body-tracking requirements is presented, together with an account of the precision-pointing platform disturbance rejection properties required.

Bell, Charles E.↗

NASA NTRS1990

Integrated Communication and Control Systems. III - Nonidentical sensor and controller sampling

Networking in Integrated Communication and Control Systems (ICCS) introduces randomly varying delays which degrade the system dynamic performance and are a source of potential instability. In Part I of this sequence of papers, a discrete-time, finite-dimensional model of the delayed control system for analysis and design of ICCS was developed where the sensor and controller have identical sampling rates. In Part II, two alternate approaches for ICCS design, namely, identical and nonidentical sampling rates for sensor and controller were proposed. This Part III presents extended modeling of ICCS for nonidentical sensor and controller sampling rates. This model is also suitable for analyzing tracking problems, i.e., control systems with time-dependent reference inputs.

Liou, Luen-Woei↗

NASA NTRS1998

X-33 Telemetry Best Source Selection, Processing, Display, and Simulation Model Comparison

The X-33 program requires the use of multiple telemetry ground stations to cover the launch, ascent, transition, descent, and approach phases for the flights from Edwards AFB to landings at Dugway Proving Grounds, UT and Malmstrom AFB, MT. This paper will discuss the X-33 telemetry requirements and design, including information on fixed and mobile telemetry systems, best source selection, and support for Range Safety Officers. A best source selection system will be utilized to automatically determine the best source based on the frame synchronization status of the incoming telemetry streams. These systems will be used to select the best source at the landing sites and at NASA Dryden Flight Research Center to determine the overall best source between the launch site, intermediate sites, and landing site sources. The best source at the landing sites will be decommutated to display critical flight safety parameters for the Range Safety Officers. The overall best source will be sent to the Lockheed Martin's Operational Control Center at Edwards AFB for performance monitoring by X-33 program personnel and for monitoring of critical flight safety parameters by the primary Range Safety Officer. The real-time telemetry data (received signal strength, etc.) from each of the primary ground stations will also be compared during each nu'ssion with simulation data generated using the Dynamic Ground Station Analysis software program. An overall assessment of the accuracy of the model will occur after each mission. Acknowledgment: The work described in this paper was NASA supported through cooperative agreement NCC8-115 with Lockheed Martin Skunk Works.

Burkes, Darryl A.↗

NASA NTRS2001

On-Line Mu Method for Robust Flutter Prediction in Expanding a Safe Flight Envelope for an Aircraft Model Under Flight Test

A structured singular value (mu) analysis method of computing flutter margins has robust stability of a linear aeroelastic model with uncertainty operators (Delta). Flight data is used to update the uncertainty operators to accurately account for errors in the computed model and the observed range of aircraft dynamics of the aircraft under test caused by time-varying aircraft parameters, nonlinearities, and flight anomalies, such as test nonrepeatability. This mu-based approach computes predict flutter margins that are worst case with respect to the modeling uncertainty for use in determining when the aircraft is approaching a flutter condition and defining an expanded safe flight envelope for the aircraft that is accepted with more confidence than traditional methods that do not update the analysis algorithm with flight data by introducing mu as a flutter margin parameter that presents several advantages over tracking damping trends as a measure of a tendency to instability from available flight data.

Lind, Richard C.↗

NASA NTRS2021

Plumelets: Dynamic Filamentary Structures in Solar Coronal Plumes

Solar coronal plumes long seemed to possess a simple geometry supporting spatially coherent, stable outflow without significant fine structure. Recent high-resolution observations have challenged this picture by revealing numerous transient, small-scale, collimated out-flows (“jetlets”) at the base of plumes. The dynamic filamentary structure of solar plumes above these outflows, and its relationship with the overall plume structure, have remained largely unexplored. We analyzed the statistics of continuously observed fine structure in-side a single representative bright plume within a mid-latitude coronal hole during 2016 July2-3. By applying advanced edge-enhancement and spatiotemporal analysis techniques to ex-tended series of high-resolution images from the Solar Dynamics Observatory’s Atmospheric Imaging Assembly, we determined that the plume was composed of numerous time-evolving filamentary substructures, referred to as “plumelets” in this paper, that accounted for most of the plume emission. The number of simultaneously identifiable plumelets was positively correlated with plume brightness, peaked in the fully formed plume, and remained saturated thereafter. The plumelets had transverse widths of 10 Mm and intermittently supported upwardly propagating periodic disturbances with phase speeds of 190-260 km s−1and longitudinal wavelengths of 55-65 Mm. The characteristic frequency (3.5 mHz) is commensurate with that of solar p-modes. Oscillations in neighboring plumelets are uncorrelated, indicating that the waves could be driven by p-mode flows at spatial scales smaller than the plumelet separation. Multiple independent sources of outflow within a single coronal plume should impart significant fine structure to the solar wind that may be detectable by Parker Solar Probe and Solar Orbiter.

V M Uritsky↗

NASA NTRS2022

Remote Sensing of Coronal Forces During a Solar Prominence Eruption

We present a new methodology—the Keplerian Optical Dynamics Analysis (KODA)—for quantifying the dynamics of erupting magnetic structures in the solar corona. The technique involves adaptive spatiotemporal tracking of propagating intensity gradients and their characterization in terms of time-evolving Keplerian areas swept out by the position vectors of moving plasma blobs. Whereas gravity induces purely ballistic motions consistent with Kepler's second law, noncentral forces such as the Lorentz force introduce nonzero torques resulting in more complex motions. KODA algorithms enable direct evaluation of the line-of-sight component of the net torque density from the image-plane projection of the areal acceleration. The method is applied to the prominence eruption of 2011 June 7, observed by the Solar Dynamics Observatory's Atmospheric Imaging Assembly. Results obtained include quantitative estimates of the magnetic forces, field intensities, and blob masses and energies across a vast region impacted by the postreconnection redistribution of the prominence material. The magnetic pressure and energy are strongly dominant during the early, rising phase of the eruption, while the dynamic pressure and kinetic energy become significant contributors during the subsequent falling phases. Measured intensive properties of the prominence blobs are consistent with those of typical active-region prominences; measured extensive properties are compared with those of the whole pre-eruption prominence and the post-eruption coronal mass ejection of 2011 June 7, all derived by other investigators and techniques. We show that KODA provides valuable information on spatially and temporally dependent characteristics of coronal eruptions that is not readily available via alternative means, thereby shedding new light on the environment and evolution of these solar events.

V M Uritskiy↗

NASA NTRS2024

Characterizing the California Current System through Sea Surface Temperature and Salinity

Characterizing temperature and salinity (T-S) conditions is a standard framework in oceanography to identify and describe deep water masses and their dynamics. At the surface, this practice is hindered by multiple air–sea–land processes impacting T-S properties at shorter time scales than can easily be monitored. Now, however, the unsurpassed spatial and temporal coverage and resolution achieved with satellite sea surface temperature (SST) and salinity (SSS) allow us to use these variables to investigate the variability of surface processes at climate-relevant scales. In this work, we use SSS and SST data, aggregated into domains using a cluster algorithm over a T-S diagram, to describe the surface characteristics of the California Current System (CCS), validating them with in situ data from uncrewed Saildrone vessels. Despite biases and uncertainties in SSS and SST values in highly dynamic coastal areas, this T-S framework has proven useful in describing CCS regional surface properties and their variability in the past and in real time, at novel scales. This analysis also shows the capacity of remote sensing data for investigating variability in land–air–sea interactions not previously possible due to limited in situ data.

Marisol García-Reyes↗

NASA NTRS2021

Revolutionary Vertical Lift Technology (RVLT) Side-By-Side Hybrid Concept Vehicle Powertrain Dynamic Model

The Side-by-Side (SBS) Hybrid is one of several Revolutionary Vertical Lift Technology (RVLT) concept aircraft identified by NASA to investigate Urban Air Mobility (UAM) requirements. This paper presents a dynamic model of the SBS Hybrid powertrain built using the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) and the Electrical Modeling and Thermal Analysis Toolbox (EMTAT). The model consists of the rotors, electrical power system, and turboshaft engines connected through freewheeling clutches, gearboxes, and multiple shafts. This research effort models the complex behavior of the powertrain, including the operation of the freewheeling clutches and electrical power system at the simulation time scale of the shaft dynamics. Several simulations highlight the key features present in the model and demonstrate its operation.

Powertrain↗

NASA NTRS2021

Revolutionary Vertical Lift Technology (RVLT) Side-By-Side Hybrid Concept Vehicle Powertrain Dynamic Model

powertrain↗

DOE OSTI2019

Deep learning analysis of defect and phase evolution during electron beam-induced transformations in WS2

Abstract Recent advances in scanning transmission electron microscopy (STEM) allow the real-time visualization of solid-state transformations in materials, including those induced by an electron beam and temperature, with atomic resolution. However, despite the ever-expanding capabilities for high-resolution data acquisition, the inferred information about kinetics and thermodynamics of the process, and single defect dynamics and interactions is minimal. This is due to the inherent limitations of manual ex situ analysis of the collected volumes of data. To circumvent this problem, we developed a deep-learning framework for dynamic STEM imaging that is trained to find the lattice defects and apply it for mapping solid state reactions and transformations in layered WS 2 . The trained deep-learning model allows extracting thousands of lattice defects from raw STEM data in a matter of seconds, which are then classified into different categories using unsupervised clustering methods. We further expanded our framework to extract parameters of diffusion for sulfur vacancies and analyzed transition probabilities associated with switching between different configurations of defect complexes consisting of Mo dopant and sulfur vacancy, providing insight into point-defect dynamics and reactions. This approach is universal and its application to beam-induced reactions allows mapping chemical transformation pathways in solids at the atomic level.

36 MATERIALS SCIENCE↗

DOE OSTI2018

The Role of Dimensionality in Understanding Granuloma Formation

Within the first 2–3 months of a Mycobacterium tuberculosis (Mtb) infection, 2–4 mm spherical structures called granulomas develop in the lungs of the infected hosts. These are the hallmark of tuberculosis (TB) infection in humans and non-human primates. A cascade of immunological events occurs in the first 3 months of granuloma formation that likely shapes the outcome of the infection. Understanding the main mechanisms driving granuloma development and function is key to generating treatments and vaccines. In vitro, in vivo, and in silico studies have been performed in the past decades to address the complexity of granuloma dynamics. This study builds on our previous 2D spatio-temporal hybrid computational model of granuloma formation in TB (GranSim) and presents for the first time a more realistic 3D implementation. We use uncertainty and sensitivity analysis techniques to calibrate the new 3D resolution to non-human primate (NHP) experimental data on bacterial levels per granuloma during the first 100 days post infection. Due to the large computational cost associated with running a 3D agent-based model, our major goal is to assess to what extent 2D and 3D simulations differ in predictions for TB granulomas and what can be learned in the context of 3D that is missed in 2D. Our findings suggest that in terms of major mechanisms driving bacterial burden, 2D and 3D models return very similar results. For example, Mtb growth rates and molecular regulation mechanisms are very important both in 2D and 3D, as are cellular movement and modulation of cell recruitment. The main difference we found was that the 3D model is less affected by crowding when cellular recruitment and movement of cells are increased. Overall, we conclude that the use of a 2D resolution in GranSim is warranted when large scale pilot runs are to be performed and if the goal is to determine major mechanisms driving infection outcome (e.g., bacterial load). To comprehensively compare the roles of model dimensionality, further tests and experimental data will be needed to expand our conclusions to molecular scale dynamics and multi-scale resolutions.

2D vs. 3D↗

NASA NTRS1990

Combined design of structures and controllers for optimal maneuverability

Approaches to the combined design of structures and controllers for achieving optimal maneuverability are presented. A maneuverability index which directly reflects the minimum time required to perform a given set of maneuvers is introduced. By designing the flexible appendages, the maneuver time of the spacecraft is minimized under the constraints of structural properties, and post maneuver spillover is kept within a specified bound. The spillover reduction is achieved by making use of an appropriate reduced order model. The distributed parameter design problem is approached using assumed shape functions, and finite element analysis with dynamic reduction. Solution procedures have been investigated. Approximate design methods have been developed to overcome the computational difficulties. Some new constraints on the modal frequencies of the spacecraft are introduced in the original optimization problem to facilitate the solution process. It is shown that the global optimal design may be obtained by tuning the natural frequencies to satisfy specific constraints. Researchers quantify the difference between a lower bound to the solution for maneuver time associated with the original problem and the estimate obtained from the modified problem, for a specified application requirement. Numerical examples are presented to demonstrate the capability of this approach.

Ling, Jer↗

DOE OSTI2021

Modeling atmospheric data and identifying dynamics Temporal data-driven modeling of air pollutants

Atmospheric modelling has recently experienced a surge with the advent of deep learning. Most of these models, however, predict concentrations of pollutants following a data-driven approach in which the physical laws that govern their behaviors and relationships remain hidden. Furthermore, with the aid of real-world air quality data collected hourly in different stations throughout Madrid, we present a case study using a series of data-driven techniques with the following goals: (1) Find systems of ordinary differential equations that model the concentration of pollutants and their changes over time; (2) assess the performance and limitations of our model using stability analysis; (3) reconstruct the time series of chemical pollutants not measured in certain stations using delay coordinate embedding results.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Dynamics of Fungal and Bacterial Biomass Carbon in Natural Ecosystems: Site-level Applications of the CLM-Microbe Model

Explicitly representing microbial processes has been recognized as a key improvement to Earth system models for the realistic projections of soil carbon (C) and climate dynamics. The CLM-Microbe model builds upon the CLM4.5 and explicitly represents two major soil microbial groups, fungi and bacteria. Based on the compiled time-series data of fungal (FBC) and bacterial (BBC) biomass C from nine biomes, we parameterized and validated the CLM-Microbe model, and further conducted sensitivity analysis and uncertainty analysis for simulating C cycling. The model performance was evaluated with mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2) for relative change in FBC and BBC. The CLM-Microbe model is able to reasonably capture the seasonal dynamics of FBC and BBC across biomes, particularly for tropical/subtropical forest, temperate broadleaf forest, and grassland, with MAE < 0.49 for FBC and <0.36 for BBC and RMSE <0.52 FBC and <0.39 for BBC, while R2 values are relatively smaller in some biomes (e.g., shrub) due to small sample sizes. We found good consistencies between simulated and observed FBC (R 2 =0.70, P<0.001) and BBC (R 2 =0.26, P<0.05) on average across biomes, but the model is not able to fully capture the large variation in observed FBC and BBC. Sensitivity analysis shows the most critical parameters are turnover rate, carbon-to-nitrogen ratio of fungi and bacteria, and microbial assimilation efficiency. This study confirms that the explicit representation of soil microbial mechanisms enhances model performance in simulating C variables such as heterotrophic respiration and soil organic C density. The further application of the CLM-Microbe model would deepen our understanding of microbial contributions to the global C cycle.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Measurement-based Power System Dynamic Model Reductions

Interconnected power systems have experienced a significant increase in its size and complexity, due to continuous topology and operating condition changes. It is computationally burdensome to represent entire system models in detail to conduct power system analysis. In the large-scale power system dynamic simulations, the models in the study area need to be retained in detail while the external area can be reduced without compromising accuracy, which can preserve the full system dynamic properties. This paper develops measurement-based continuous-time dynamic equivalents for power systems in order to both improve the model accuracy of the reduced system and increase the speed of dynamic simulation. Our method is based on a set of measurements at the boundary nodes between the study area and external area. Case studies demonstrate that the measurement-based model can capture the full system behavior sufficiently, and improve computational efficiency.Interconnected power systems experienced a significant increase in size and complexity. It is computationally burdensome to represent the entire system in detail to conduct power system analysis. Therefore, the model of the study system must be retained in detail while the external system can be reduced using system reduction techniques. This paper proposes a measurement-based dynamic equivalent in order to increase both model accuracy and simulation speed. The proposed method uses a set of measurements at the boundary nodes between the study area and external area for model parameter identification. Case studies demonstrate that the measurement-based technique can capture the main system behaviors accurately and improve computational efficiency.

Xue, Yaosuo↗