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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Application of the operator spline technique to nonlinear estimation and control of moving elastic systems

A bilinear model of the vibrational dynamics of a deformable maneuvering body is described. Estimates of the deformation state are generated through a low dimensional operator spline interpolator of bilinear systems combined with a feedback linearized based observer. Upper bounds on error estimates are also generated through the operator spline, and potential application to shaping control purposes is highlighted.

Karray, Fakhreddine↗
NASA NTRS1998

On-Orbit Model Refinement for Controller Redesign

High performance control design for a flexible space structure is challenging since high fidelity plant models are difficult to obtain a priori. Uncertainty in the control design models typically require a very robust, low performance control design which must be tuned on-orbit to achieve the required performance. A new procedure for refining a multivariable open loop plant model based on closed-loop response data is presented. Using a minimal representation of the state space dynamics, a least squares prediction error method is employed to estimate the plant parameters. This control-relevant system identification procedure stresses the joint nature of the system identification and control design problem by seeking to obtain a model that minimizes the difference between the predicted and actual closed-loop performance. This paper presents an algorithm for iterative closed-loop system identification and controller redesign along with illustrative examples.

Whorton, Mark S.↗
NASA NTRS2005

A Generic Inner-Loop Control Law Structure for Six-Degree-of-Freedom Conceptual Aircraft Design

A generic control system framework for both real-time and batch six-degree-of-freedom (6-DOF) simulations is presented. This framework uses a simplified dynamic inversion technique to allow for stabilization and control of any type of aircraft at the pilot interface level. The simulation, designed primarily for the real-time simulation environment, also can be run in a batch mode through a simple guidance interface. Direct vehicle-state acceleration feedback is required with the simplified dynamic inversion technique. The estimation of surface effectiveness within real-time simulation timing constraints also is required. The generic framework provides easily modifiable control variables, allowing flexibility in the variables that the pilot commands. A direct control allocation scheme is used to command aircraft effectors. Primary uses for this system include conceptual and preliminary design of aircraft, when vehicle models are rapidly changing and knowledge of vehicle 6-DOF performance is required. A simulated airbreathing hypersonic vehicle and simulated high-performance fighter aircraft are used to demonstrate the flexibility and utility of the control system.

Cox, Timothy H.↗
NASA NTRS2005

A Generic Inner-Loop Control Law Structure for Six-Degree-of-Freedom Conceptual Aircraft Design

A generic control system framework for both real-time and batch six-degree-of-freedom simulations is presented. This framework uses a simplified dynamic inversion technique to allow for stabilization and control of any type of aircraft at the pilot interface level. The simulation, designed primarily for the real-time simulation environment, also can be run in a batch mode through a simple guidance interface. Direct vehicle-state acceleration feedback is required with the simplified dynamic inversion technique. The estimation of surface effectiveness within real-time simulation timing constraints also is required. The generic framework provides easily modifiable control variables, allowing flexibility in the variables that the pilot commands. A direct control allocation scheme is used to command aircraft effectors. Primary uses for this system include conceptual and preliminary design of aircraft, when vehicle models are rapidly changing and knowledge of vehicle six-degree-of-freedom performance is required. A simulated airbreathing hypersonic vehicle and simulated high-performance fighter aircraft are used to demonstrate the flexibility and utility of the control system.

Cox, Timothy H.↗
NASA NTRS2019

Technical Challenges Associated with In-Air Wingtip Docking of Aircraft in Forward Flight

Autonomous in-air wingtip docking of aircraft offers significant opportunity for system level performance gains for numerous aircraft applications. Several of the technical challenges facing wingtip docking of fixed-wing aircraft are addressed in this paper, including: close proximity aerodynamic coupling; mechanisms and operations for robust docking; and relative state estimation methods. A simulation framework considering the aerodynamics, rigid-body dynamics, and vehicle controls is developed and used to perform docking sensitivity studies for a system of two 5.5% scale NASA Generic Transport Model aircraft. Additionally, proof of- concept testing of a candidate docking mechanism designed to move the primary wingtip vortex inboard suggests the viability of such an approach for achieving robust docking.

Quinlan, Jesse R.↗
DOE OSTI2015

Pre-Commercial Demonstration of Direct Non-Iterative State Estimator (DNSE+)

The objective of this DOE co-funded project is to demonstrate functionality and performance of a production-grade Direct Non-iterative State Estimator (DNSE) through its integration with NYPA’s Energy Management System (EMS) and an enhanced Real Time Dynamics Monitoring System (RTDMS) synchrophasor platform from Electric Power Group (EPG). A production-grade DNSE aims to overcome a major obstacle to the operational use of synchrophasor data in Synchro-Phasor Management Systems (SPMS) by providing SPMS applications with a consistent and a complete synchrophasor data foundation in the same way that a traditional EMS State Estimator (SE) provides to EMS applications. Specifically, the DNSE uses synchrophasor measurements and Supervisory Control and Data Acquisition (SCADA) measurements, together with the complete power system model, to simultaneously obtain the complete state of the entire utility’s operating model at rates that are close to the synchrophasor data rates. The full system coverage property is what distinguishes the DNSE from the linear synchrophasor SEs (which cover only parts of the operating model that are visible through synchrophasor measurements), and DNSE differs from traditional EMS SE in that the solution is obtained without iterations, without initial values (hence the “direct” in the name), and at a much higher execution rate. This presentation provides an overview of the project objectives, a brief description of the main tasks including the development work to productize and optimize DNSE from its current MATLAB code base, RTDMS enhancement for interfacing with the DNSE, factory acceptance testing, field installation, testing and demonstration, as well as the current status of the project execution.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Large-scale Nonlinear Approaches for Inference of Reporting Dynamics and Unobserved SARS-CoV-2 Infections

This work focuses on estimation of unknown states and parameters in a discrete-time, stochastic, SEIR model using reported case counts and mortality data. An SEIR model is based on classifying individuals with respect to their status in regards to the progression of the disease, where S is the number individuals who remain susceptible to the disease, E is the number of individuals who have been exposed to the disease but not yet infectious, I is the number of individuals who are currently infectious, and R is the number of recovered individuals. For convenience, we include in our notation the number of infections or transmissions, T, that represents the number of individuals transitioning from compartment S to compartment E over a particular interval. Similarly, we use C to represent the number of reported cases.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1972

Estimation of nonlinear pilot model parameters including time delay.

Investigation of the feasibility of using a Kalman filter estimator for the identification of unknown parameters in nonlinear dynamic systems with a time delay. The problem considered is the application of estimation theory to determine the parameters of a family of pilot models containing delayed states. In particular, the pilot-plant dynamics are described by differential-difference equations of the retarded type. The pilot delay, included as one of the unknown parameters to be determined, is kept in pure form as opposed to the Pade approximations generally used for these systems. Problem areas associated with processing real pilot response data are included in the discussion.

Schiess, J. R.↗
NASA NTRS1959

Effect of the Proximity of the Wing First-Bending Frequency and the Short-Period Frequency on the Airplane Dynamic-Response Factor

The results are presented in the form of preliminary design charts which give a comparison between the dynamic-response factors of the semi-rigid case and the airplane longitudinal short-period case and between the dynamic-response factors of the semi-rigid case and the steady-state value of the airplane longitudinal short-period response. These charts can be used to estimate the first-order effects of the addition of a wing-bending degree of freedom on the short-period dynamic-response factor and on the maximum dynamic-response factor when compared with the steady-state response of the system.

Huss, Carl R.↗
DOE OSTI2017

Galaxy Cluster Mass Reconstruction Project – III. The impact of dynamical substructure on cluster mass estimates

With the advent of wide-field cosmological surveys, we are approaching samples of hundreds of thousands of galaxy clusters. While such large numbers will help reduce statistical uncertainties, the control of systematics in cluster masses is crucial. Here we examine the effects of an important source of systematic uncertainty in galaxy-based cluster mass estimation techniques: the presence of significant dynamical substructure. Dynamical substructure manifests as dynamically distinct subgroups in phase-space, indicating an ‘unrelaxed’ state. This issue affects around a quarter of clusters in a generally selected sample. We employ a set of mock clusters whose masses have been measured homogeneously with commonly used galaxy-based mass estimation techniques (kinematic, richness, caustic, radial methods). We use these to study how the relation between observationally estimated and true cluster mass depends on the presence of substructure, as identified by various popular diagnostics. We find that the scatter for an ensemble of clusters does not increase dramatically for clusters with dynamical substructure. However, we find a systematic bias for all methods, such that clusters with significant substructure have higher measured masses than their relaxed counterparts. This bias depends on cluster mass: the most massive clusters are largely unaffected by the presence of significant substructure, but masses are significantly overestimated for lower mass clusters, by ~ 10 percent at 10 14 and ≳ 20 percent for ≲ 10 13.5 . Finally, the use of cluster samples with different levels of substructure can therefore bias certain cosmological parameters up to a level comparable to the typical uncertainties in current cosmological studies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Regional carbon fluxes from land use and land cover change in Asia, 1980–2009

We present a synthesis of the land-atmosphere carbon flux from land use and land cover change (LULCC) in Asia using multiple data sources and paying particular attention to deforestation and forest regrowth fluxes. The data sources are quasi-independent and include the U.N. Food and Agriculture Organization-Forest Resource Assessment (FAO-FRA 2015; country-level inventory estimates), the Emission Database for Global Atmospheric Research (EDGARv4.3), the 'Houghton' bookkeeping model that incorporates FAO-FRA data, an ensemble of 8 state-of-the-art Dynamic Global Vegetation Models (DGVM), and 2 recently published independent studies using primarily remote sensing techniques. The estimates are aggregated spatially to Southeast, East, and South Asia and temporally for three decades, 1980–1989, 1990–1999 and 2000–2009. Since 1980, net carbon emissions from LULCC in Asia were responsible for 20%–40% of global LULCC emissions, with emissions from Southeast Asia alone accounting for 15%–25% of global LULCC emissions during the same period. In the 2000s and for all Asia, three estimates (FAO-FRA, DGVM, Houghton) were in agreement of a net source of carbon to the atmosphere, with mean estimates ranging between 0.24 to 0.41 Pg C yr -1 , whereas EDGARv4.3 suggested a net carbon sink of -0.17 Pg C yr -1 . Three of 4 estimates suggest that LULCC carbon emissions declined by at least 34% in the preceding decade (1990–2000). Spread in the estimates is due to the inclusion of different flux components and their treatments, showing the importance to include emissions from carbon rich peatlands and land management, such as shifting cultivation and wood harvesting, which appear to be consistently underreported.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

Dynamic Adjustment of Simulation Parameters for Efficient Vehicle Prognostics

Model-based diagnostics and prognostics rely on state estimation and uncertainty management algorithms to produce useful information for system operators and maintainers. This information enables more informed operational decisions, condition-based maintenance, and overall mission safety assurance. Typically, uncertainty is associated with vehicle state-of-health estimation and prediction results because of modeling errors, internal or external sources of noise, and sensor inaccuracy. Probabilistic uncertainty management methods including Sequential Monte Carlo simulation are commonly used to reason about state-of-health estimates and predictions in the presence of these sources of uncertainty. However, such algorithms can be computationally expensive as they require a very large number of samples to obtain a sufficiently accurate quantification of the end of life probability distribution. As a result, highly mobile autonomous systems that leverage the prognostic results for mission-level replanning are often constrained in their processing capability because of these computationally expensive simulation approaches. Therefore, in this paper, we investigate algorithmic methods for dynamically adjusting simulation time step as well as number of samples to achieve highly efficient prognostic results while maintaining results accuracy. Results obtained from simulated flight experiments of an electric unmanned aerial vehicle are presented to verify the efficacy of such algorithms.

Prognostics↗
NASA NTRS2006

MEASURING THE MASS OF 4UO900-40 DYNAMICALLY

Accurate measurements of neutron star masses are needed to constrain the equation of state of neutron star matter - of importance to both particle physics and the astrophysics of neutron stars - and to identify the evolutionary track of the progenitor stars that form neutron stars. The best measured values of the mass of 4UO900-40 (= Vela XR-l), 1.86 +/- 0.16 Msun (Barziv et al. 2001) and 1.93 +/- 0.20 Msun (Abubekerov et al. 2004), make it a leading candidate for the most massive neutron star known. The direct relationship between the maximum mass of neutron stars and the equation of state of ultra-dense matter makes 4UO900-40 an important neutron star mass to determine accurately. The confidence interval on previous mass estimates, obtained from observations that include parameters determined by non-dynamical methods, are not small enough to significantly restrict possible equations of state. We describe here a purely dynamical method for determining the mass of 4UO900-40, an X-ray pulsar, using the reprocessed UV pulses emitted by its BO.5Ib companion. One can derive the instantaneous radial velocity of each component by simultaneous X-ray and UV observations at the two quadratures of the system. The Doppler shift caused by the primary's rotational velocity and the illumination pattern of the X-rays on the primary, two of the three principal contributors to the uncertainty on the derived mass of the neutron star, almost exactly cancel by symmetry in this method. A heuristic measurement of the mass of 4UO900-40 using observations obtained previously with the High Speed Photometer on HST is given in Appendix A.

Dolan, J. F.↗
NASA NTRS2013

Simultaneous Estimation of Model State Variables and Observation and Forecast Biases Using a Two-Stage Hybrid Kalman Filter

In this paper, we present a two-stage hybrid Kalman filter to estimate both observation and forecast bias in hydrologic models, in addition to state variables. The biases are estimated using the discrete Kalman filter, and the state variables using the ensemble Kalman filter. A key issue in this multi-component assimilation scheme is the exact partitioning of the difference between observation and forecasts into state, forecast bias and observation bias updates. Here, the error covariances of the forecast bias and the unbiased states are calculated as constant fractions of the biased state error covariance, and the observation bias error covariance is a function of the observation prediction error covariance. In a series of synthetic experiments, focusing on the assimilation of discharge into a rainfall-runoff model, it is shown that both static and dynamic observation and forecast biases can be successfully estimated. The results indicate a strong improvement in the estimation of the state variables and resulting discharge as opposed to the use of a bias-unaware ensemble Kalman filter. Furthermore, minimal code modification in existing data assimilation software is needed to implement the method. The results suggest that a better performance of data assimilation methods should be possible if both forecast and observation biases are taken into account.

Data Assimilation↗
DOE OSTI2022

Joint neutron/molecular dynamics vibrational spectroscopy reveals softening of HIV-1 protease upon binding of a tight inhibitor

Biomacromolecules are inherently dynamic, and their dynamics are interwoven into function. The fast collective vibrational dynamics in proteins occurs in the low picosecond timescale corresponding to frequencies of ~5-50 cm -1 . This sub-to-low THz frequency regime covers the low-amplitude collective breathing motions of a whole protein and vibrations of the constituent secondary structure elements, such as α-helices, β-sheets and loops. We have used inelastic neutron scattering experiments in combination with molecular dynamics simulations to demonstrate the vibrational dynamics softening of HIV-1 protease, a target of HIV/AIDS antivirals, upon binding of a tight clinical inhibitor darunavir. Changes in the vibrational density of states of matching structural elements in the two monomers of the homodimeric protein are not identical, indicating asymmetric effect of darunavir on the vibrational dynamics. Three of the 11 major secondary structure elements contribute over 40% to the overall changes in the vibrational density of states upon darunavir binding. Molecular dynamics simulations informed by experiments allowed us to estimate that the altered vibrational dynamics of the protease would contribute -3.6 kcal/mol -1 at 300 K, or 25%, to the free energy of darunavir binding. As HIV-1 protease drug resistance remains a concern, our results open a new avenue to help establish a direct quantitative link between protein vibrational dynamics and drug resistance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Distributed State Estimation Over Time-Varying Graphs: Exploiting the Age-of-Information

Here, we study the problem of designing a distributed observer for an LTI system over a time-varying communication graph. The limited existing work on this topic imposes various restrictions either on the observation model or on the sequence of communication graphs. In contrast, we propose a single-time-scale distributed observer that works under mild assumptions. Specifically, our communication model only requires strong-connectivity to be preserved over non-overlapping, contiguous intervals that are even allowed to grow unbounded over time. We show that under suitable conditions that bound the growth of such intervals, joint observability is sufficient to track the state of any discrete-time LTI system exponentially fast, at any desired rate. We also develop a variant of our algorithm that is provably robust to worst-case adversarial attacks, provided the sequence of graphs is sufficiently connected over time. The key to our approach is the notion of a "freshness-index" that keeps track of the age-of-information being diffused across the network. Such indices enable nodes to reject stale estimates of the state, and, in turn, contribute to stability of the error dynamics.

42 ENGINEERING↗
NASA NTRS1987

Precision positioning of earth orbiting remote sensing systems

Decimeter tracking accuracy is sought for a number of precise earth sensing satellites to be flown in the 1990's. This accuracy can be achieved with techniques which use the Global Positioning System (GPS) in a differential mode. A precisely located global network of GPS ground receivers and a receiver aboard the user satellite are needed, and all techniques simultaneously estimate the user and GPS satellite states. Three basic navigation approaches include classical dynamic, wholly nondynamic, and reduced dynamic or hybrid formulations. The first two are simply special cases of the third, which promises to deliver subdecimeter accuracy for dynamically unpredictable vehicles down to the lowest orbit altitudes. The potential of these techniques for tracking and gravity field recovery will be demonstrated on NASA's Topex satellite beginning in 1991. Applications to the Shuttle, Space Station, and dedicated remote sensing platforms are being pursued.

Melbourne, William G.↗
NASA NTRS2000

Filtering in Hybrid Dynamic Bayesian Networks

We implement a 2-time slice dynamic Bayesian network (2T-DBN) framework and make a 1-D state estimation simulation, an extension of the experiment in (v.d. Merwe et al., 2000) and compare different filtering techniques. Furthermore, we demonstrate experimentally that inference in a complex hybrid DBN is possible by simulating fault detection in a watertank system, an extension of the experiment in (Koller & Lerner, 2000) using a hybrid 2T-DBN. In both experiments, we perform approximate inference using standard filtering techniques, Monte Carlo methods and combinations of these. In the watertank simulation, we also demonstrate the use of 'non-strict' Rao-Blackwellisation. We show that the unscented Kalman filter (UKF) and UKF in a particle filtering framework outperform the generic particle filter, the extended Kalman filter (EKF) and EKF in a particle filtering framework with respect to accuracy in terms of estimation RMSE and sensitivity with respect to choice of network structure. Especially we demonstrate the superiority of UKF in a PF framework when our beliefs of how data was generated are wrong. Furthermore, we investigate the influence of data noise in the watertank simulation using UKF and PFUKD and show that the algorithms are more sensitive to changes in the measurement noise level that the process noise level. Theory and implementation is based on (v.d. Merwe et al., 2000).

Andersen, Morten Nonboe↗