SEARCH · Search NASA

Results for “dynamic parameter 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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12

All sources NASA NTRS DOE OSTI

DOE OSTI2015

Application of Anaerobic Digestion Model No. 1 for simulating anaerobic mesophilic sludge digestion

Highlights: • The behavior of a anaerobic reactor was evaluated through modeling. • Parametric sensitivity analysis was used to select most sensitive of the ADM1. • The results indicate that the ADM1 was able to predict the experimental results. • Organic load rate above of 35 kg/m{sup 3} day affects the performance of the process. - Abstract: Improving anaerobic digestion of sewage sludge by monitoring common indicators such as volatile fatty acids (VFAs), gas composition and pH is a suitable solution for better sludge management. Modeling is an important tool to assess and to predict process performance. The present study focuses on the application of the Anaerobic Digestion Model No. 1 (ADM1) to simulate the dynamic behavior of a reactor fed with sewage sludge under mesophilic conditions. Parametric sensitivity analysis is used to select the most sensitive ADM1 parameters for estimation using a numerical procedure while other parameters are applied without any modification to the original values presented in the ADM1 report. The results indicate that the ADM1 model after parameter estimation was able to predict the experimental results of effluent acetate, propionate, composites and biogas flows and pH with reasonable accuracy. The simulation of the effect of organic shock loading clearly showed that an organic shock loading rate above of 35 kg/m{sup 3} day affects the performance of the reactor. The results demonstrate that simulations can be helpful to support decisions on predicting the anaerobic digestion process of sewage sludge.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2019

Reverse battery model for anodic arc discharges near atmospheric pressure

In this study, the macroscopic electrical parameters of anodic arc discharges performed with solid carbon and molybdenum anodes are described in terms of an equivalent circuit. The proposed 1D model shows that the plasma volume behaves as a dissipative medium combined with self-generated voltage from the plasma sheaths. We test this model by fitting virtual circuits of resistors and batteries to the measured voltage–current (V–I) characteristics representative of atmospheric arc processes (300 and 500 Torr He), resulting in the identification of two phenomena relevant for arc technology. First, steady DC arc experiments show that a minimal arc voltage (V ≈ 20–30 V) or threshold voltage is necessary to keep the plasma arc on. Second, we prove that pulsed arc discharges excited with rectangular current waveforms (1–5 Hz) are never extinguished but remain ignited during the inactive time of the pulse as long as the aforementioned threshold voltage is maintained. In summary, an atmospheric anodic arc discharge with solid electrodes consumes electrical power as a voltage source opposed to the external voltage supply together with a resistor that accounts for the plasma impedance. This approach permits us to estimate basic plasma parameters from simple electrical diagnostics, as well as to predict how power consumption is distributed within an anodic arc and to understand dynamics of arc plasmas excited by periodic signals.

25 ENERGY STORAGE↗

DOE OSTI2018

An ALMA view of star formation efficiency suppression in early-type galaxies after gas-rich minor mergers

Gas-rich minor mergers contribute significantly to the gas reservoir of early-type galaxies (ETGs) at low redshift, yet the star formation efficiency (SFE; the star formation rate divided by the molecular gas mass) appears to be strongly suppressed following some of these events, in contrast to the more well-known merger-driven starbursts. We present observations with the Atacama Large Millimeter/submillimeter Array (ALMA) of six ETGs, which have each recently undergone a gas-rich minor merger, as evidenced by their disturbed stellar morphologies. These galaxies were selected because they exhibit extremely low SFEs. We use the resolving power of ALMA to study the morphology and kinematics of the molecular gas. The majority of our galaxies exhibit spatial and kinematical irregularities, such as detached gas clouds, warps, and other asymmetries. These asymmetries support the interpretation that the suppression of the SFE is caused by dynamical effects stabilizing the gas against gravitational collapse. Through kinematic modelling we derive high velocity dispersions and Toomre Q stability parameters for the gas, but caution that such measurements in edge-on galaxies suffer from degeneracies. We estimate merger ages to be about 100 Myr based on the observed disturbances in the gas distribution. Furthermore, we determine that these galaxies lie, on average, two orders of magnitude below the Kennicutt–Schmidt relation for star-forming galaxies as well as below the relation for relaxed ETGs. We discuss potential dynamical processes responsible for this strong suppression of star formation surface density at fixed molecular gas surface density.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

Damping constant estimation in magnetoresistive readers

The damping constant is a key design parameter in magnetic reader design. Its value can be derived from bulk or sheet film ferromagnetic resonance (FMR) line width. However, dynamics of nanodevices is usually defined by presence of non-uniform modes. It triggers new damping mechanisms and produces stronger damping than expected from traditional FMR. This work proposes a device-level technique for damping evaluation, based on time-domain analysis of thermally excited stochastic oscillations. The signal is collected using a high bandwidth oscilloscope, by direct probing of a biased reader. Recorded waveforms may contain different noise signals, but free layer FMR is usually a dominating one. The autocorrelation function is a reflection of the damped oscillation curve, averaging out stochastic contributions. The damped oscillator formula is fitted to autocorrelation data, producing resonance frequency and damping constant values. Restricting lag range allows for mitigation of the impact of other phenomena (e.g., reader instability) on the damping constant. For a micromagnetically modeled reader, the technique proves to be much more accurate than the stochastic FMR line width approach. Application to actual reader waveforms yields a damping constant of ∼0.03.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Towards optimal extraction of cosmological information from nonlinear data

One of the main unsolved problems of cosmology is how to maximize the extraction of information from nonlinear data. If the data are nonlinear the usual approach is to employ a sequence of statistics (N-point statistics, counting statistics of clusters, density peaks or voids etc.), along with the corresponding covariance matrices. However, this approach is computationally prohibitive and has not been shown to be exhaustive in terms of information content. Here we instead develop a hierarchical Bayesian approach, expanding the likelihood around the maximum posterior of linear modes, which we solve for using optimization methods. By integrating out the modes using perturbative expansion of the likelihood we construct an initial power spectrum estimator, which for a fixed forward model contains all the cosmological information if the initial modes are gaussian distributed. We develop a method to construct the window and covariance matrix such that the estimator is explicitly unbiased and nearly optimal. We then generalize the method to include the forward model parameters, including cosmological and nuisance parameters, and primordial non-gaussianity. We apply the method in the simplified context of nonlinear structure formation, using either simplified 2-LPT dynamics or N-body simulations as the nonlinear mapping between linear and nonlinear density, and 2-LPT dynamics in the optimization steps used to reconstruct the initial density modes. We demonstrate that the method gives an unbiased estimator of the initial power spectrum, providing among other a near optimal reconstruction of linear baryonic acoustic oscillations.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Write-up on the analytical formalism for DTL Synchrotron and Betatron frequencies estimates

Appendix A contains tables of the DTL tanks geometry, generated using PARMILA code with input parameters of initial and final energy, accelerating gradient, synchronouse phase, and using DTLfish code (part of the SUPERFISH/POISSON package of codes). Details of the design and generation od the DTL geometry will be presented in a separate report. After generation of the DTL geometry and initial beam dynamics simulations, the analytic estimates of the synchrotron and betatron oscillations, as well as presence of the parametric resonance of first order were done. In present report the analytic background of those estimates, as well as the results of these are presented.

43 PARTICLE ACCELERATORS↗

DOE OSTI2018

Temporal Dynamics of Aerodynamic Canopy Height Derived From Eddy Covariance Momentum Flux Data Across North American Flux Networks

Aerodynamic canopy height ( h a ) is the effective height of vegetation canopy for its influence on atmospheric fluxes and is a key parameter of surface-atmosphere coupling. However, methods to estimate h a from data are limited. This synthesis evaluates the applicability and robustness of the calculation of h a from eddy covariance momentum-flux data. At 69 forest sites, annual h a robustly predicted site-to-site and year-to-year differences in canopy heights ( R 2 = 0.88, 111 site-years). At 23 cropland/grassland sites, weekly h a successfully captured the dynamics of vegetation canopies over growing seasons ( R 2 > 0.70 in 74 site-years). Our results demonstrate the potential of flux-derived h a determination for tracking the seasonal, interannual, and/or decadal dynamics of vegetation canopies including growth, harvest, land use change, and disturbance. The large-scale and time-varying h a derived from flux networks worldwide provides a new benchmark for regional and global Earth system models and satellite remote sensing of canopy structure.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

A dynamic data-driven method for dealing with model structural error in soil moisture data assimilation

Attributing to the flexibility in considering various types of observation error and model error, data assimilation has been increasingly applied to dynamically improve soil moisture modeling in many hydrological practices. However, accurate characterization of model error, especially the part caused by defective model structure, presents a significant challenge to the successful implementation of data assimilation. Model structural error has received limited attention relative to parameter and input errors, mainly due to our poor understanding of structural inadequacy and the difficulties in parameterizing structural error. In this paper, we present a dynamic data-driven approach to estimate the model structural error in soil moisture data assimilation without the need for identifying error generation mechanism or specifying particular form for the error model. The error model is based on the Gaussian process regression and then integrated into the ensemble Kalman filter (EnKF) to form a hybrid method for dealing with multi-source model errors. Two variants of the hybrid method in terms of two different error correction manners are proposed. The effectiveness of the proposed method is tested through a suit of synthetic cases and a real-world case. Results demonstrate the potential of the proposed hybrid method for estimating model structural error and providing improved model predictions. Compared to the traditional EnKF without explicitly considering the model structural error, parameter compensation issue is obviously reduced and soil moisture retrieval is substantially improved.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

A STUDY OF DUST AND GAS AT MARS FROM COMET C/2013 A1 (SIDING SPRING)

Although the nucleus of comet C/2013 A1 (Siding Spring) will safely pass Mars in 2014 October, the dust in the coma and tail will more closely approach the planet. Using a dynamical model of comet dust, we estimate the impact fluence. Based on our nominal model no impacts are expected at Mars. Relaxing our nominal model's parameters, the fluence is no greater than ∼10{sup –7} grains m{sup –2} for grain radii larger than 10 μm. Mars-orbiting spacecraft are unlikely to be impacted by large dust grains, but Mars may receive as many as ∼10{sup 7} grains, or ∼100 kg of total dust. We also estimate the flux of impacting gas molecules commonly observed in comet comae.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Consideration of the Impact of the Environmental Conditions when Designing Heat-Receiving Systems of the Solar Cylindrical Parabolic Modules

The aerohydrodynamic and heat exchange characteristics in the cylindrical heat receiver of a solar cylindrical parabolic concentrating module are investigated. The mathematical model is based on the Navier- Stokes equation system for a laminar flow in a channel. The model is implemented using the control volume method. The created computer algorithm allows carrying out parametric studies and revealing the most rational geometric, dynamic, and power parameters of the process. The proposed model describes the general physical outlines of the heat exchange in a cylindrical heat receiver which allows estimating the influence of the environment—wind velocity, ambient temperature, etc.—on it.

14 SOLAR ENERGY↗

DOE OSTI2015

HO x radical chemistry in oxidation flow reactors with low-pressure mercury lamps systematically examined by modeling

Oxidation flow reactors (OFRs) using OH produced from low-pressure Hg lamps at 254 nm (OFR254) or both 185 and 254 nm (OFR185) are commonly used in atmospheric chemistry and other fields. OFR254 requires the addition of externally formed O 3 since OH is formed from O 3 photolysis, while OFR185 does not since O 2 can be photolyzed to produce O 3 , and OH can also be formed from H 2 O photolysis. In this study, we use a plug-flow kinetic model to investigate OFR properties under a very wide range of conditions applicable to both field and laboratory studies. We show that the radical chemistry in OFRs can be characterized as a function of UV light intensity, H 2 O concentration, and total external OH reactivity (OHR ext , e.g., from volatile organic compounds (VOCs), NO x , and SO 2 ). OH exposure is decreased by added external OH reactivity. OFR185 is especially sensitive to this effect at low UV intensity due to low primary OH production. OFR254 can be more resilient against OH suppression at high injected O 3 (e.g., 70 ppm), as a larger primary OH source from O 3 , as well as enhanced recycling of HO 2 to OH, make external perturbations to the radical chemistry less significant. However if the external OH reactivity in OFR254 is much larger than OH reactivity from injected O 3 , OH suppression can reach 2 orders of magnitude. For a typical input of 7 ppm O 3 (OHR O 3 = 10 s −1 ), 10-fold OH suppression is observed at OHR ext ~ 100 s −1 , which is similar or lower than used in many laboratory studies. The range of modeled OH suppression for literature experiments is consistent with the measured values except for those with isoprene. The finding on OH suppression may have important implications for the interpretation of past laboratory studies, as applying OH exp measurements acquired under different conditions could lead to over a 1-order-of-magnitude error in the estimated OH exp . The uncertainties of key model outputs due to uncertainty in all rate constants and absorption cross-sections in the model are within ±25 % for OH exposure and within ±60 % for other parameters. These uncertainties are small relative to the dynamic range of outputs. Uncertainty analysis shows that most of the uncertainty is contributed by photolysis rates of O 3 , O 2 , and H 2 O and reactions of OH and HO 2 with themselves or with some abundant species, i.e., O 3 and H 2 O 2 . OH exp calculated from direct integration and estimated from SO 2 decay in the model with laminar and measured residence time distributions (RTDs) are generally within a factor of 2 from the plug-flow OH exp . However, in the models with RTDs, OH exp estimated from SO 2 is systematically lower than directly integrated OH exp in the case of significant SO 2 consumption. We thus recommended using OH exp estimated from the decay of the species under study when possible, to obtain the most appropriate information on photochemical aging in the OFR. Using HO x -recycling vs. destructive external OH reactivity only leads to small changes in OH exp under most conditions. Changing the identity (rate constant) of external OH reactants can result in substantial changes in OH exp due to different reductions in OH suppression as the reactant is consumed. We also report two equations for estimating OH exposure in OFR254. We find that the equation estimating OH exp from measured O 3 consumption performs better than an alternative equation that does not use it, and thus recommend measuring both input and output O 3 concentrations in OFR254 experiments. This study contributes to establishing a firm and systematic understanding of the gas-phase HO x and O x chemistry in these reactors, and enables better experiment planning and interpretation as well as improved design of future reactors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Parameter choices for a muon recirculating linear accelerator from 5 to 63 GeV

A recirculating linear accelerator (RLA) has been proposed to accelerate muons from 5 to 63 GeV for a muon collider. It should be usable both for a Higgs factory and as a stage for a higher energy collider. First, the constraints due to the beam loading are computed. Next, an expression for the longitudinal emittance growth to lowest order in the longitudinal emittance is worked out. After finding the longitudinal expression, a simplified model that describes the arcs and their approximate expression for the time of flight dependence on energy in those arcs is found. Finally, these results are used to estimate the parameters required for the RLA arcs and the linac phase.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Multiscale ACI Satellite Database

The SATELLITE_EAGLES_PNNL NetCDF dataset contains a suite of satellite- and reanalysis-derived atmospheric and surface parameters on a regular latitude–longitude grid. The dataset includes core geophysical fields such as land fraction, aerosol optical depth at multiple wavelengths (465, 550, 667, and 865 nm), sea surface temperature, estimated inversion strength, and various thermodynamic and dynamic quantities (e.g., relative humidity, vertical velocity, boundary-layer height, and surface fluxes) from both MERRA and ERA reanalysis products, provided as daily-mean and instantaneous values. A major component of the dataset consists of MODIS-retrieved cloud microphysical properties, including cloud droplet number concentration, cloud effective radius, optical thickness, and liquid water path, provided for three compositing regimes (“All,” “Q06,” and “G18”). Corresponding cloud-top parameters—temperature, height, and pressure—along with total and domain-mean cloud fraction fields are also included. The file further integrates additional satellite data from AMSR-E (for cloud water, rain water, and surface precipitation retrievals) and CERES (for top-of-atmosphere radiative fluxes, cloud fractions, and albedo). This dataset is designed to evaluate aerosol–cloud interactions in warm clouds, emphasizing the use of MODIS for deriving cloud droplet number concentration and liquid water path statistics. The complementary satellite and reanalysis fields are co-located and time-matched to the same instantaneous MODIS observations, enabling consistent comparisons between cloud properties, aerosol loading, and large-scale meteorological conditions. The dataset is recently featured in Christensen et al. (2025), Machine Learning Reveals Strong Grid-Scale Dependence in the Satellite Nd–LWP Relationship, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-3850, 2025.

Christensen, Matthew [Pacific Northwest National L↗

DOE OSTI2025

Multiscale ACI Satellite Database

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Enhancing quantum clocks and sensors with randomization and decoherence

This letter shows how incoherent dynamics can lead to metrological advantages in quantum sensing. The results rely on the fact that incoherent dynamics lead to an additive contribution to the quantum Fisher information about time. Such an additive contribution can reduce the error of optimal estimation protocols, as implied by the quantum Cramér–Rao bound. I characterize regimes in which the estimation of a time interval or a frequency is enhanced by decoherence, thereby identifying cases in which incoherent dynamics serve as a metrological resource. The decoherence processes that yield enhanced precision of quantum sensors can be engineered by randomized Hamiltonian dynamics. I illustrate the results with protocols that display improved sensing of time intervals or global fields by qubit and photonic sensors. Enhanced precision of time intervals is achieved with Hamiltonians that include randomized global parameters. Enhanced precision in field estimation is obtained by randomized sensing times.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2018

Uncertainty Quantification and Global Sensitivity Analysis of Subsurface Flow Parameters to Gravimetric Variations During Pumping Tests in Unconfined Aquifers

We study the contribution of typically uncertain subsurface flow parameters to gravity changes that can be recorded during pumping tests in unconfined aquifers. We do so in the framework of a Global Sensitivity Analysis and quantify the effects of uncertainty of such parameters on the first four statistical moments of the probability distribution of gravimetric variations induced by the operation of the well. System parameters are grouped into two main categories, respectively, governing groundwater flow in the unsaturated and saturated portions of the domain. We ground our work on the three-dimensional analytical model proposed by Mishra and Neuman (2011), which fully takes into account the richness of the physical process taking place across the unsaturated and saturated zones and storage effects in a finite radius pumping well. The relative influence of model parameter uncertainties on drawdown, moisture content, and gravity changes are quantified through (a) the Sobol' indices, derived from a classical decomposition of variance and (b) recently developed indices quantifying the relative contribution of each uncertain model parameter to the (ensemble) mean, skewness, and kurtosis of the model output. Our results document (i) the importance of the effects of the parameters governing the unsaturated flow dynamics on the mean and variance of local drawdown and gravity changes; (ii) the marked sensitivity (as expressed in terms of the statistical moments analyzed) of gravity changes to the employed water retention curve model parameter, specific yield, and storage, and (iii) the influential role of hydraulic conductivity of the unsaturated and saturated zones to the skewness and kurtosis of gravimetric variation distributions. The observed temporal dynamics of the strength of the relative contribution of system parameters to gravimetric variations suggest that gravity data have a clear potential to provide useful information for estimating the key hydraulic parameters of the system.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

A dynamic kinetic model captures cell-free metabolism for improved butanol production

Cell-free systems are useful tools for prototyping metabolic pathways and optimizing the production of various bioproducts. Mechanistically-based kinetic models are uniquely suited to analyze dynamic experimental data collected from cell-free systems and provide vital qualitative insight. However, to date, dynamic kinetic models have not been applied with rigorous biological constraints or trained on adequate experimental data to the degree that they would give high confidence in predictions and broadly demonstrate the potential for widespread use of such kinetic models. In this work, we construct a large-scale dynamic model of cell-free metabolism with the goal of understanding and optimizing butanol production in a cell-free system. Using a combination of parameterization methods, the resultant model captures experimental metabolite measurements across two experimental conditions for nine metabolites at timepoints between 0 and 24 hours. Here, we present analysis of the model predictions, provide recommendations for butanol optimization, and identify the aldehyde/alcohol dehydrogenase as the primary bottleneck in butanol production. Sensitivity analysis further reveals the extent to which various parameters are constrained, and our approach for probing valid parameter ranges can be applied to other modeling efforts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Provably accurate simulation of gauge theories and bosonic systems

Quantum many-body systems involving bosonic modes or gauge fields have infinite-dimensional local Hilbert spaces which must be truncated to perform simulations of real-time dynamics on classical or quantum computers. To analyze the truncation error, we develop methods for bounding the rate of growth of local quantum numbers such as the occupation number of a mode at a lattice site, or the electric field at a lattice link. Our approach applies to various models of bosons interacting with spins or fermions, and also to both abelian and non-abelian gauge theories. We show that if states in these models are truncated by imposing an upper limit Λ on each local quantum number, and if the initial state has low local quantum numbers, then an error at most ϵ can be achieved by choosing Λ to scale polylogarithmically with ϵ − 1 , an exponential improvement over previous bounds based on energy conservation. For the Hubbard-Holstein model, we numerically compute a bound on Λ that achieves accuracy ϵ , obtaining significantly improved estimates in various parameter regimes. We also establish a criterion for truncating the Hamiltonian with a provable guarantee on the accuracy of time evolution. Building on that result, we formulate quantum algorithms for dynamical simulation of lattice gauge theories and of models with bosonic modes; the gate complexity depends almost linearly on spacetime volume in the former case, and almost quadratically on time in the latter case. We establish a lower bound showing that there are systems involving bosons for which this quadratic scaling with time cannot be improved. By applying our result on the truncation error in time evolution, we also prove that spectrally isolated energy eigenstates can be approximated with accuracy ϵ by truncating local quantum numbers at Λ = polylog ( ϵ − 1 ) .

Tong, Yu↗