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Results for “Dynamic State Estimation”

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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Application of the Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA) for Dynamic Systems Analysis

Systems analysis involves steady-state simulations of combined components to evaluate the steady-state performance, weight, and cost of a system; dynamic considerations are not included until later in the design process. The Dynamic Systems Analysis task, under NASAs Fixed Wing project, is developing the capability for assessing dynamic issues at earlier stages during systems analysis. To provide this capability the Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA) has been developed to design a single flight condition controller (defined as altitude and Mach number) and, ultimately, provide an estimate of the closed-loop performance of the engine model. This tool has been integrated with the Commercial Modular Aero-Propulsion System Simulation 40,000 (CMAPSS 40k) engine model to demonstrate the additional information TTECTrA makes available for dynamic systems analysis. This dynamic data can be used to evaluate the trade-off between performance and safety, which could not be done with steady-state systems analysis data. TTECTrA has been designed to integrate with any turbine engine model that is compatible with the MATLAB Simulink (The MathWorks, Inc.) environment.

control↗
DOE OSTI2025

A Trichomonas vaginalis C2-XYPPX-repeat protein with a structured C2 domain displaying dampened flexibility upon binding calcium

C2 domains are ubiquitous membrane-binding modules of ∼130 residues in eukaryotes that are often associated with proteins involved in membrane trafficking and lipid modification. The genome of Trichomonas vaginalis, the most common, non-viral, sexually transmitted human pathogen, encodes eight genes that contain a N-terminal C2 module linked to a XYPPX-repeat domain of more than four XYPPX repeats (C2-XYPPX). While the function of the XYPPX-repeat domain remains unknown, its multiple association with C2 domains in T. vaginalis suggests it is important. Here, the C2 domain from one of these C2-XYPPX-repeat proteins, Tv-C2-1, was structurally and physically characterized using X-ray crystallography and NMR spectroscopy. The crystal structure for Tv-C2-1 shows that this domain shares a fold common to all C2 domains, a compact Greek-key motif composed of eight anti-parallel β-strands in the type-2 topology. An NMR chemical shift perturbation study with Ca 2+ showed that Tv-C2-1 bound two Ca 2+ atoms primarily via two loops (loop-1 and loop-3) on the predicted calcium binding face of the protein with K d s of 58.0 ± 0.1 μM and 232 ± 6 μM. Estimations of the overall rotational correlation time, τ c , in the apo (11.1 ns) and Ca 2+ -bound (9.2 ns) state suggests the protein becomes more compact upon Ca 2+ binding, consistent with a decrease in dynamics in loop-3 and marginally in loop-1 suggested by amide 15 N heteronuclear steady-state { 1 H}- 15 N NOEs. Showing Tv-C2-1 binds calcium and adopts a compact Greek-key motif structure, two primary features of C2 domains, suggests understanding the function of the XYPPX-repeat domain may be warranted.

NMR spectroscopy↗
DOE OSTI2019

Quantifying Resolution Implications for Agent-based Distributed Energy Resource Customer Adoption Models

In this report we explore tradeoffs of top-down and bottom-up methods in their precision and computational burden using NREL's dGen model, an agent-based model of residential and non-residential distributed PV adoption. In particular, we assess the role of agent resolution in instantiating statistically-representative populations in the model--and the resulting variance of model projections at the state, sector and county levels. Running the model for a single state with fixed macroeconomic assumptions, we vary both the number of agents instantiated and the number of unique simulations. Notably, in each run we introduce sources of uncertainty in cumulative DPV adoption results during agent instantiation as we stochastically sample agent attributes from localized building characteristic and solar resource distributions. We find three key trends which guide what can be expected of results. First, precision of the model projections, as measured by the variance of the unique simulations increased as a function of the number of agents sampled, though with diminishing returns to scale. The result is expected given the Law of Large Numbers. Second, the mean or expected value of projections decreased as the number of agents instantiated increased. Empirically, aggregate DPV capacities projected by dGen are 7% lower on average at a 10-agent resolution compared to 1-agent resolutions, and up to 10% lower in the non-residential sector. We attribute this outcome to a system sizing scheme that biases lower cumulative installed capacity as agent resolution increases when roof size and load are not positively correlated. Finally, the variance of model projections differed by sector, where variance was substantially larger in the commercial sector, largely due to differences in parameterization by sector. We explain the larger variance in the non-residential sector as an outcome of the greater variance in building uses and load shapes as compared to the residential sector, and we find that a resolution on the order of 100-agents per county would be necessary to bring non-residential variance in line with residential variance at a 2-agent resolution. We propose that further research explore increasing precision and agent resolution in the non-residential sector. Moreover, given that days of intensive computing may be required to resolve a suitable estimate even at the extent of a single state within acceptable levels of precision, to promote computational efficiency we also suggest more clearly quantifying sources of variability at the county level such that resolution can by dynamically increased where county level results are least precise.

14 SOLAR ENERGY↗
DOE OSTI2020

Multiscale modeling high-order methods and data-driven modeling

Projection-based reduced-order models (ROMs) comprise a promising set of data-driven approaches for accelerating the simulation of high-fidelity numerical simulations. Standard projection-based ROM approaches, however, suffer from several drawbacks when applied to the complex nonlinear dynamical systems commonly encountered in science and engineering. These limitations include a lack of stability, accuracy, and sharp a posteriori error estimators. This work addresses these limitations by leveraging multiscale modeling, least-squares principles, and machine learning to develop novel reduced-order modeling approaches, along with data-driven a posteriori error estimators, for dynamical systems. Theoretical and numerical results demonstrate that the two ROM approaches developed in this work - namely the windowed least-squares method and the Adjoint Petrov - Galerkin method - yield substantial improvements over state-of-the-art approaches. Additionally, numerical results demonstrate the capability of the a posteriori error models developed in this work.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1972

Adaptive control of stochastic linear systems with unknown parameters

The problem of optimal control of linear discrete-time stochastic dynamical system with unknown and, possibly, stochastically varying parameters is considered on the basis of noisy measurements. It is desired to minimize the expected value of a quadratic cost functional. Since the simultaneous estimation of the state and plant parameters is a nonlinear filtering problem, the extended Kalman filter algorithm is used. Several qualitative and asymptotic properties of the open loop feedback optimal control and the enforced separation scheme are discussed. Simulation results via Monte Carlo method show that, in terms of the performance measure, for stable systems the open loop feedback optimal control system is slightly better than the enforced separation scheme, while for unstable systems the latter scheme is far better.

Ku, R. T.↗
NASA NTRS1995

Computations of Axisymmetric Flows in Hypersonic Shock Tubes

A time-accurate two-dimensional fluid code is used to compute test times in shock tubes operated at supersonic speeds. Unlike previous studies, this investigation resolves the finer temporal details of the shock-tube flow by making use of modern supercomputers and state-of-the-art computational fluid dynamic solution techniques. The code, besides solving the time-dependent fluid equations, also accounts for the finite rate chemistry in the hypersonic environment. The flowfield solutions are used to estimate relevant shock-tube parameters for laminar flow, such as test times, and to predict density and velocity profiles. Boundary-layer parameters such as bar-delta(sub u), bar-delta(sup *), and bar-tau(sub w), and test time parameters such as bar-tau and particle time of flight t(sub f), are computed and compared with those evaluated by using Mirels' correlations. This article then discusses in detail the effects of flow nonuniformities on particle time-of-flight behind the normal shock and, consequently, on the interpretation of shock-tube data. This article concludes that for accurate interpretation of shock-tube data, a detailed analysis of flowfield parameters, using a computer code such as used in this study, must be performed.

Sharma, Surendra P.↗
NASA NTRS1999

An Integrated Vehicle Modeling Environment

This paper describes an Integrated Vehicle Modeling Environment for estimating aircraft geometric, inertial, and aerodynamic characteristics, and for interfacing with a high fidelity, workstation based flight simulation architecture. The goals in developing this environment are to aid in the design of next generation intelligent fight control technologies, conduct research in advanced vehicle interface concepts for autonomous and semi-autonomous applications, and provide a value-added capability to the conceptual design and aircraft synthesis process. Results are presented for three aircraft by comparing estimates generated by the Integrated Vehicle Modeling Environment with known characteristics of each vehicle under consideration. The three aircraft are a modified F-15 with moveable canards attached to the airframe, a mid-sized, twin-engine commercial transport concept, and a small, single-engine, uninhabited aerial vehicle. Estimated physical properties and dynamic characteristics are correlated with those known for each aircraft over a large portion of the flight envelope of interest. These results represent the completion of a critical step toward meeting the stated goals for developing this modeling environment.

Totah, Joseph J.↗
NASA NTRS2013

Aerodynamic Stability and Performance of Next-Generation Parachutes for Mars Descent

The Low Density Supersonic Decelerator Project is developing a next-generation supersonic parachute for use on future Mars missions. In order to determine the new parachute configuration, a wind tunnel test was conducted at the National Full-scale Aerodynamics Complex 80- by 120-foot Wind Tunnel at the NASA Ames Research Center. The goal of the wind tunnel test was to quantitatively determine the aerodynamic stability and performance of various canopy configurations in order to help select the design to be flown on the Supersonic Flight Dynamics tests. Parachute configurations included the diskgap- band, ringsail, and ringsail-variant designs referred to as a disksail and starsail. During the wind tunnel test, digital cameras captured synchronized image streams of the parachute from three directions. Stereo hotogrammetric processing was performed on the image data to track the position of the vent of the canopy throughout each run. The position data were processed to determine the geometric angular history of the parachute, which were then used to calculate the total angle of attack and its derivatives at each instant in time. Static and dynamic moment coefficients were extracted from these data using a parameter estimation method involving the one-dimensional equation of motion for a rotation of parachute. The coefficients were calculated over all of the available canopy states to reconstruct moment coefficient curves as a function of total angle of attack. From the stability curves, useful metrics such as the trim total angle of attack and pitch stiffness at the trim angle could be determined. These stability metrics were assessed in the context of the parachute's drag load and geometric porosity. While there was generally an inverse relationship between the drag load and the stability of the canopy, the data showed that it was possible to obtain similar stability properties as the disk-gap-band with slightly higher drag loads by appropriately tailoring the geometric porosity distribution.

Low Density Supersonic Decelerator (LDSD)↗
DOE OSTI2026

Neural network potentials with effective charge separation for non-equilibrium dynamics of ionic solids: a ZnO case study

Developing neural network potentials (NNPs) accurate under non-equilibrium dynamics is challenging, as such systems require extensive sampling beyond equilibrium phases. Here we construct high-fidelity NNPs for zinc oxide (ZnO), a polymorphic ionic solid, using density functional theory (DFT) reference data. To efficiently capture transitional configurations, we combine enhanced-sampling molecular dynamics with empirical potentials, data distillation, and pretraining on short-range atomic energies (A-Train), followed by transfer learning with DFT-relabeled datasets. This hierarchical approach improves transferability across polymorphs and stress states. We further introduce effective charge separation, treating long-range Coulombic terms analytically while short-range residual interactions are learned by the NNP. The optimal effective charges fall in the range 0.5–1.0 q e , consistent with dielectric-screened values derived from formal charges but distinct from Bader estimates. Motivated by this observation, we propose a simple data-driven protocol in which effective charges are optimized by comparing DFT reference energies with explicit Coulomb calculations, without additional NNP training. This strategy improves accuracy and transferability in DFT-level predictions of energies, forces, and stress. Together, these results provide a practical charge-selection framework for robust NNP development in ionic solids, enabling reliable simulation of polymorphic phase transformations and non-equilibrium dynamics.

Chemistry↗
DOE OSTI2024

Comparison of Global Aboveground Biomass Estimates From Satellite Observations and Dynamic Global Vegetation Models

The global forest carbon stocks represent the amount of carbon stored in woody vegetation and are important for quantifying the ability of the global forests to sequester atmospheric CO 2 and to provide ecosystem services (e.g., timber) under climate change. The forest ecosystem carbon pool estimates are highly variable and poorly quantified in areas lacking forest inventory estimates. Here, we compare and analyze aboveground biomass (AGB) estimates from five satellite-based global data sets and nine dynamic global vegetation models (DVGMs). We find that across the data sets, mean AGB exhibits the largest variability around the tropical area. In addition, AGB shows a similar latitudinal trend but large variability among the data sets. Satellite-based AGB estimates are lower than those simulated by DVGMs. The divergence among the satellite-based AGB estimates can be driven by the methodology, input satellite products, and the forested areas used to estimate AGB. The modeled NPP, autotrophic respiration, and carbon allocation mostly drive the variability of AGB simulated by DGVMs. The future availability of a high-quality global forest area map is anticipated to improve AGB estimate accuracy and to reduce the discrepancies among different satellite- and model-based AGB estimates. Furthermore, we suggest the carbon-modeling community reexamine the methodology used to estimate AGB and forested areas for a more robust global forest carbon stock estimation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Probabilistic Discrete‐Time Models for Spreading Processes in Complex Networks: A Review

Abstract Research into network dynamics of spreading processes typically employs both discrete and continuous time methodologies. Although each approach offers distinct insights, integrating them can be challenging, particularly when maintaining coherence across different time scales. This review focuses on the Microscopic Markov Chain Approach (MMCA), a probabilistic f ramework originally designed for epidemic modeling. MMCA uses discrete dynamics to compute the probabilities of individuals transitioning between epidemiological states. By treating each time step—usually a day—as a discrete event, the approach captures multiple concurrent changes within this time frame. The approach allows to estimate the likelihood of individuals or populations being in specific states, which correspond to distinct epidemiological compartments. This review synthesizes key findings from the application of this approach, providing a comprehensive overview of its utility in understanding epidemic spread.

Granell, Clara↗
DOE OSTI2021

Electron-Induced Proton Transfer

The pathway of activationless proton transfer induced by an electron-transfer reaction is studied theoretically. Long-range electron transfer produces highly nonequilibrium medium polarization that can drive proton transfer through an activationless transition during the process of thermalization, dynamically altering the screening of the electron–proton Coulomb interaction by the medium. The cross electron–proton reorganization energy is the main energy parameter of the theory, which exceeds in magnitude the proton-transfer reorganization energy roughly by the ratio of the electron-transfer to proton-transfer distance. This parameter, which can be either positive or negative, is related to the difference in pK a values in two electron-transfer states. The relaxation time of the medium is on the (sub)picosecond time scale, which establishes the characteristic time for activationless proton transfer. Microscopic calculations predict substantial retardation of the collective relaxation dynamics compared to the continuum estimates due to the phenomenology analogous to de Gennes narrowing. As a result, nonequilibrium medium configuration promoting proton transfer can be induced by either thermal or photoinduced charge transfer.

14 SOLAR ENERGY↗
DOE OSTI2026

ObstacleSense: Low-Power Neuromorphic Vision for Corridor Obstacle Awareness in Low-Level ADAS

The automotive industry’s pursuit of Level 5 autonomy is constrained by substantial perception-compute power requirements, often reaching 1, 000 + watts in full autonomy stacks. Reducing this energy burden requires rethinking perception not only at the high-end autonomy level, but also at the foundational Advanced Driver Assistance Systems (ADAS) level where low-power, safety-critical sensing can have broad impact. Neuromorphic vision provides a promising starting point: HD Dynamic Vision Sensors (DVS) can operate below 100 mW at the sensor level by reporting only asynchronous brightness changes. However, low-power sensing alone is insufficient if downstream perception reintroduces dense, energy-intensive computation. In particular, many event-driven object-detection pipelines still rely on CNN backbones, while purely spiking alternatives often trade away accuracy or ignore deployment constraints. We introduce ObstacleSense, a highly compact, CNN-free hybrid ANN–SNN framework for Level 0–1 forward-corridor obstacle awareness. Instead of performing full-scene object detection with a convolutional feature backbone, ObstacleSense targets the safety-critical question of whether the ego corridor is occupied and how far the nearest obstacle is. The architecture combines polarity-conditioned event encoding, lightweight temporal spiking dynamics, axial spatial mixing, and coarse-to-fine range estimation within a regular fixed-grid compute pattern. This design avoids the dense CNN backbone commonly used in event-based detection while maintaining a small state footprint suitable for eventual small-FPGA deployment. Before hardware mapping, we evaluate the software implementation using a model-side power proxy derived from MACs, weight and activation traffic, and spiking state updates under shared FP16 assumptions. On simulated CARLA event corpora, the deployment-oriented model achieves 0.9464 objectness F1, 0.9978 grid-level mAP, and 0.8987 m distance Mean Absolute Error at an estimated 1.92 mW proxy cost, while maintaining performance on unseen generalization test sequences.

Johnson-Scott, Zac [ORNL]↗
DOE OSTI2022

Cost Update: Commercial and Advanced Heliostat Collectors

The research team performed a detailed bottom-up manufacturing cost estimate for 2 heliostat designs: i) a commercially available design, the Stellio; and ii) an advanced heliostat design, the Drop-C. The Drop-C is designed and developed by Solar Dynamics (SD) of the United States, whilst the Stellio has been developed primarily by Schlaich Bergermann Und Partner, Sonne Gmbh (sbp) of Germany. The Stellio heliostat has been deployed at commercial scale and is being used at the Hami CSP 50-megawatt electric (MW e ) power tower plant in China. For each design, this includes all components for manufacturing and assembly in a manufacturing facility (e.g., struts and frame) using Design for Manufacturing and Assembly (DFMA), and the purchased parts (e.g., mirrors, control systems, and drives). The field-assembly and construction activities are also considered to determine the installed cost of the modelled solar fields.

14 SOLAR ENERGY↗
NASA NTRS1973

Suboptimal stochastic controller for an n-body spacecraft

The problem is studied of determining a stochastic optimal controller for an n-body spacecraft. The approach used in obtaining the stochastic controller involves the application, interpretation, and combination of advanced dynamical principles and the theoretical aspects of modern control theory. The stochastic controller obtained for a complicated model of a spacecraft uses sensor angular measurements associated with the base body to obtain smoothed estimates of the entire state vector, can be easily implemented, and enables system performance to be significantly improved.

Larson, V.↗
NASA NTRS1975

Prediction of axial-flow instabilities in a turbojet engine by use of a multistage compressor simulation on the digital computer

A method of estimating the undistorted stall line for an axial-flow compressor by using the digital computer is presented. The method involves linearization of nonlinear dynamic equations about an operating point on a speed line, and then application of the first method of Lyapunov to determine the stability of the nonlinear system from the stability of the linear system. The method is applied to a simulation of the J85 compressor, which utilizes stage stacking and lumped volume techniques for the interstage regions to simulate steady-state and dynamic compressor performance. The stability boundary predicted by the digital simulation compares quite well with the stall line predicted by a dynamic simulation of the J85 compressor programmed on the analog computer. Since previous studies have shown that the analog-predicted stall line agrees well with the stall line of the compressor, the digital method presented is also a good means of estimating the stall line.

Daniele, C. J.↗
NASA NTRS1985

Heat transfer in a real engine environment

The hot section facility at the Lewis Research Center was used to demonstrate the capability of instruments to make required measurements of boundary conditions of the flow field and heat transfer processes in the hostile environment of the turbine. The results of thermal scaling tests show that low temperature and pressure rig tests give optimistic estimates of the thermal performance of a cooling design for high pressure and temperature application. The results of measuring heat transfer coefficients on turbine vane airfoils through dynamic data analysis show good comparison with measurements from steady state heat flux gauges. In addition, the data trends are predicted by the STAN5 boundary layer code. However, the magnitude of the experimental data was not predicted by the analysis, particularly in laminar and transitional regions near the leading edge. The infrared photography system was shown capable of providing detailed surface thermal gradients and secondary flow features on a turbine vane and endwell.

Gladden, Herbert J.↗
NASA NTRS1997

Extraction of Lateral-Directional Stability and Control Derivatives for the Basic F-18 Aircraft at High Angles of Attack

The results of parameter identification to determine the lateral-directional stability and control derivatives of an F-18 research aircraft in its basic hardware and software configuration are presented. The derivatives are estimated from dynamic flight data using a specialized identification program developed at NASA Dryden Flight Research Center. The formulation uses the linearized aircraft equations of motions in their continuous/discrete form and a maximum likelihood estimator that accounts for both state and measurement noise. State noise is used to model the uncommanded forcing function caused by unsteady aerodynamics, such as separated and vortical flows, over the aircraft. The derivatives are plotted as functions of angle of attack between 3 deg and 47 deg and compared with wind-tunnel predictions. The quality of the derivative estimates obtained by parameter identification is somewhat degraded because the maneuvers were flown with the aircraft's control augmentation system engaged, which introduced relatively high correlations between the control variables and response variables as a result of control motions from the feedback control system.

Iliff, Kenneth W.↗