Search NASA⌕ Search

SEARCH · Search NASA

Results for “Model fitting”

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.

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

At least 1,621 records · Page 90

Modeling of periodic great earthquakes on the San Andreas fault: Effects of nonlinear crustal rheology

We analyze the cycle of great earthquakes along the San Andreas fault with a finite element numerical model of deformation in a crust with a nonlinear viscoelastic rheology. The viscous component of deformation has an effective viscosity that depends exponentially on the inverse absolute temperature and nonlinearity on the shear stress; the elastic deformation is linear. Crustal thickness and temperature are constrained by seismic and heat flow data for California. The models are for anti plane strain in a 25-km-thick crustal layer having a very long, vertical strike-slip fault; the crustal block extends 250 km to either side of the fault. During the earthquake cycle that lasts 160 years, a constant plate velocity v(sub p)/2 = 17.5 mm yr is applied to the base of the crust and to the vertical end of the crustal block 250 km away from the fault. The upper half of the fault is locked during the interseismic period, while its lower half slips at the constant plate velocity. The locked part of the fault is moved abruptly 2.8 m every 160 years to simulate great earthquakes. The results are sensitive to crustal rheology. Models with quartzite-like rheology display profound transient stages in the velocity, displacement, and stress fields. The predicted transient zone extends about 3-4 times the crustal thickness on each side of the fault, significantly wider than the zone of deformation in elastic models. Models with diabase-like rheology behave similarly to elastic models and exhibit no transient stages. The model predictions are compared with geodetic observations of fault-parallel velocities in northern and central California and local rates of shear strain along the San Andreas fault. The observations are best fit by models which are 10-100 times less viscous than a quartzite-like rheology. Since the lower crust in California is composed of intermediate to mafic rocks, the present result suggests that the in situ viscosity of the crustal rock is orders of magnitude less the rock viscosity determined in the laboratory.

Reches, Ze'ev↗

Advanced Solution Methods for Microkinetic Models of Catalytic Reactions: A Methanol Synthesis Case Study

Microkinetic models, combined with experimentally measured reaction rates and orders, play a key role in elucidating detailed reaction mechanisms in heterogeneous catalysis and have typically been solved as systems of ordinary differential equations. In this work, we demonstrate a new approach to fitting those models to experimental data. For the specific example treated here, by reformulating a typical microkinetic model for a continuous stirred tank reactor to a system of nonlinear equations, we achieved a 1000-fold increase in solution speed. The reduced computational cost allows a more systematic search of the parameter space, leading to better fits to the available experimental data. We applied this approach to the problem of methanol synthesis by CO/CO2 hydrogenation over a supported-Cu catalyst, an important catalytic reaction with a large industrial interest and potential for large-scale CO2 chemical fixation.

Environmental Molecular Sciences Laboratory↗

Isotherm, Kinetic, Process Modeling, and Techno-Economic Analysis of a Diamine-Appended Metal-Organic Framework for CO 2 Capture Using Fixed Bed Contactors

In this report, diamine-appended metal-organic frameworks exhibiting step-shaped CO 2 adsorption are exceptional candidates for energy-efficient carbon capture. However, there are few studies examining their performance in real-world capture scenarios, in part due to the challenge inherent in modeling their CO 2 uptake behavior. Here, we develop a dual-site Sips model to fit experimental CO 2 adsorption data for dmpn-Mg 2 (dobpdc) (dmpn = 2,2-dimethyl-1,3-diaminopropane; dobpdc 4- = 4,4'-dioxidobiphenyl-3,3'-dicarboxylate) and develop a linear driving force model for the adsorption kinetics based on available experimental data. These models are used to develop a dynamic, fixed bed, nonisothermal contactor model using shaped particles of the material, which is validated with experimental breakthrough data. We also examine the effects of the high heat of adsorption of the material on CO 2 uptake performance and find that heat removal is essential to maximize capture performance. We finally investigate "basic"(no bed cooling during adsorption) and "modified"(bed cooling during adsorption) temperature swing adsorption (TSA) processes using dmpn-Mg 2 (dobpdc), and their process economics are compared to a state-of-the-art monoethanolamine (MEA) capture system with and without heat recovery. In the absence of heat recovery, the adsorbent systems are more costly than established technology. However, with 85% heat recovery, both adsorbent-based TSA processes are projected to cost less than the MEA system. This work highlights that thermal management is vital for implementation of dmpn-Mg 2 (dobpdc) as a viable CO 2 capture technology. Investigation of other contactor technologies that can provide unique ways to manage system heat represent promising future areas of study.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

PM 2.5 Is Insufficient to Explain Personal PAH Exposure

To understand how chemical exposure can impact health, researchers need tools that capture the complexities of personal chemical exposure. In practice, fine particulate matter (PM 2.5 ) air quality index (AQI) data from outdoor stationary monitors and Hazard Mapping System (HMS) smoke density data from satellites are often used as proxies for personal chemical exposure, but do not capture total chemical exposure. Silicone wristbands can quantify more individualized exposure data than stationary air monitors or smoke satellites. However, it is not understood how these proxy measurements compare to chemical data measured from wristbands. In this study, participants wore daily wristbands, carried a phone that recorded locations, and answered daily questionnaires for a 7-day period in multiple seasons. We gathered publicly available daily PM 2.5 AQI data and HMS data. We analyzed wristbands for 94 organic chemicals, including 53 polycyclic aromatic hydrocarbons. Wristband chemical detections and concentrations, behavioral variables (e.g., time spent indoors), and environmental conditions (e.g., PM 2.5 AQI) significantly differed between seasons. Machine learning models were fit to predict personal chemical exposure using PM 2.5 AQI only, HMS only, and a multivariate feature set including PM 2.5 AQI, HMS, and other environmental and behavioral information. On average, the multivariate models increased predictive accuracy by approximately 70% compared to either the AQI model or the HMS model for all chemicals modeled. This study provides evidence that PM 2.5 AQI data alone or HMS data alone is insufficient to explain personal chemical exposures. Our results identify additional key predictors of personal chemical exposure.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

A Kriging-Based Approach to Autonomous Experimentation with Applications to X-Ray Scattering

Abstract Modern scientific instruments are acquiring data at ever-increasing rates, leading to an exponential increase in the size of data sets. Taking full advantage of these acquisition rates will require corresponding advancements in the speed and efficiency of data analytics and experimental control. A significant step forward would come from automatic decision-making methods that enable scientific instruments to autonomously explore scientific problems—that is, to intelligently explore parameter spaces without human intervention, selecting high-value measurements to perform based on the continually growing experimental data set. Here, we develop such an autonomous decision-making algorithm that is physics-agnostic, generalizable, and operates in an abstract multi-dimensional parameter space. Our approach relies on constructing a surrogate model that fits and interpolates the available experimental data, and is continuously refined as more data is gathered. The distribution and correlation of the data is used to generate a corresponding uncertainty across the surrogate model. By suggesting follow-up measurements in regions of greatest uncertainty, the algorithm maximally increases knowledge with each added measurement. This procedure is applied repeatedly, with the algorithm iteratively reducing model error and thus efficiently sampling the parameter space with each new measurement that it requests. We validate the method using synthetic data, demonstrating that it converges to faithful replica of test functions more rapidly than competing methods, and demonstrate the viability of the approach in an experimental context by using it to direct autonomous small-angle (SAXS) and grazing-incidence small-angle (GISAXS) x-ray scattering experiments.

36 MATERIALS SCIENCE↗

Using Bayesian Methodology to Estimate Liquefied Natural Gas Leak Frequencies

This analysis provides estimates on the leak frequencies of nine components found in liquefied natural gas (LNG) facilities. Data was taken from a variety of sources, with 25 different data sets included in the analysis. A hierarchical Bayesian model was used that assumes that the log leak frequency follows a normal distribution and the logarithm of the mean of this normal distribution is a linear function of the logarithm of the fractional leak area. This type of model uses uninformed prior distributions that are updated with applicable data. Separate models are fit for each component listed. Five order-of-magnitude fractional leak areas are considered, based on the flow area of the component. Three types of supporting analyses were performed: sensitivity of the model to the data set used, sensitivity of the leak frequency estimates to differences in the model structure or prior distributions, and sufficiency of sample sized used for convergence. Recommended leak frequency distributions for all component types and leak sizes are given. These leak frequency predictions can be used for quantitative risk assessments in the future.

03 NATURAL GAS↗

Multi-wavelength Spectral Analysis of Ellerman Bombs Observed by FISS and IRIS

Ellerman bombs (EBs) are a kind of solar activity that is suggested to occur in the lower solar atmosphere. Recent observations using the Interface Region Imaging Spectrograph (IRIS) show connections between EBs and IRIS bombs (IBs), which imply that EBs might be heated to a much higher temperature (8 × 10{sup 4} K) than previous results. Here we perform a spectral analysis of EBs simultaneously observed by the Fast Imaging Solar Spectrograph and IRIS. The observational results show clear evidence of heating in the lower atmosphere, indicated by the wing enhancement in H α , Ca ii 8542 Å, and Mg ii triplet lines and also by brightenings in images of the 1700 Å and 2832 Å ultraviolet continuum channels. Additionally, the intensity of the Mg ii triplet line is correlated with that of H α when an EB occurs, suggesting the possibility of using the triplet as an alternative way to identify EBs. However, we do not find any signal in IRIS hotter lines (C ii and Si iv). For further analysis, we employ a two-cloud model to fit the two chromospheric lines (H α and Ca ii 8542 Å) simultaneously, and obtain a temperature enhancement of 2300 K for a strong EB. This temperature is among the highest of previous modeling results, albeit still insufficient to produce IB signatures at ultraviolet wavelengths.

79 ASTRONOMY AND ASTROPHYSICS↗

New generalized rheological model for lubrication of a ball spinning in a nonconforming groove

The elastohydrodynamic theory for predicting the spinning friction of a ball in a nonconforming groove was modified to incorporate a rheological model. The rheological model is based on the exponential pressure viscosity relation for low shear stresses, but at high shear rates and pressures, the relation is altered to one in which the shear stress is porportional to the normal stress. The model was fitted to experimental spinning torques for four different lubricants: a synthetic paraffinic lubricant, di-2-ethylhexyl sebacate, a super-refined naphthenic mineral oil, and a polyphenyl ether (5P4E). Good agreement between the model and experiment was found.

Allen, C. W.↗

Observations of A0535 + 26 with the SMM satellite

An examination of archival data from the hard X-ray instruments on the Solar Maximum Mission (SMM) satellite has revealed a previously undetected outburst from the recurrent X-ray transient, A0535 + 26. The outburst occurred in June 1983 and reached a peak intensity of about 2 crab units in the energy range 32-91 keV. The outburst was detected over a span of 18 days, and the pulse period was observed to spin-up with an average rate of about -6 x 10 to the -8th s/s. A recently proposed model for A0535 + 26 has a pulsar powered by a short-lived accretion disk. A thin accretion disk model is fitted to the present data, assuming an orbital period of 111 days. Two solutions to the magnetic moment of the neutron star are derived. The slow rotator solution is more consistent with the model than the fast rotator, on the grounds that the conditions for the formation of an accretion disk are more favorable for a lower magnetic field strength.

Sembay, S.↗

The X-ray Halo of GX5-1

Using Chandra observations we have measured the energy-resolved dust-scattered X-ray halo around the low-mass X-ray binary GX5-1, detecting for the first time multiply scattered X-rays from interstellar dust. % e compared the observed X-ray halo at various energies to predictions from a range of dust models. These fits used both smoothly-distributed dust as well as dust in clumped clouds, with CO and 21 cm observations helping to determine the position of the clouds along the line of sight. We found that the BARE-GR-B model of Zubko, Dwek & Arendt (2004) generally led to the best results, although inadequacies in both the overall model and the data limit our conclusions. We did find that the composite dust models of Zubko, Dwek & Arendt (2004), especially the "no carbon" models, gave uniformly poor results. Although models using cloud positions and densities derived naively from CO and 21 cm data gave generally poor results, plausible adjustments to the distance of the largest cloud and the mass of a cloud in the expanding 3 kpc Arm lead to significantly improved fits. We suggest that combining X-ray halo, CO, and 21 cm observations will be a fruitful method to improve our understanding of both the gas and dust phases of the interstellar medium.

Smith, Randall K.↗

The diffuse galactic far-ultraviolet sky

We present an all-sky map of the diffuse Galactic far ultraviolet (1344-1786 Å) background using Galaxy Evolution Explorer data, covering 65% of the sky with 11.79 arcmin{sup 2} pixels. We investigate the dependence of the background on Galactic coordinates, finding that a standard cosecant model of intensity is not a valid fit. Furthermore, we compare our map to Galactic all-sky maps of 100 μm emission, N {sub H} {sub I} column, and Hα intensity. We measure a consistent low level far-UV (FUV) intensity at zero points for other Galactic quantities, indicating a 300 photons cm{sup –2} s{sup –1} sr{sup –1} Å{sup –1} non-scattered isotropic component to the diffuse FUV. There is also a linear relationship between FUV and 100 μm emission below 100 μm values of 8 MJy sr{sup –1}. We find a similar linear relationship between FUV and N {sub H} {sub I} below 10{sup 21} cm{sup –2}. The relationship between FUV and Hα intensity has no such constant cutoff. For all Galactic quantities, the slope of the linear portion of the relationship decreases with Galactic latitude. A modified cosecant model, taking into account dust scattering asymmetry and albedo, is able to accurately fit the diffuse FUV at latitudes above 20°. The best fit model indicates an albedo, a, of 0.62 ± 0.04 and a scattering asymmetry function, g, of 0.78 ± 0.05. Deviations from the model fit may indicate regions of excess FUV emission from fluorescence or shock fronts, while low latitude regions with depressed FUV emission are likely the result of self-shielding dusty clouds.

79 ASTRONOMY AND ASTROPHYSICS↗

A measurement of the high-mass $\tau \overline{\tau}$ production cross-section at $\sqrt{s}=13$ TeV with the ATLAS detector and constraints on new particles and couplings

The production cross-section of high-mass τ-lepton pairs is measured as a function of the dilepton visible invariant mass, using 140 fb −1 of $\sqrt{s}=13$ TeV proton-proton collision data recorded with the ATLAS detector at the Large Hadron Collider. The measurement agrees with the predictions of the Standard Model. A fit to the invariant mass distribution is performed as a function of b-jet multiplicity, to constrain the non-resonant production of new particles described by an effective field theory or in models containing leptoquarks or Z′ bosons that couple preferentially to third-generation fermions. The constraints on new particles improve on previous results, and the constraints on effective operators include those affecting the anomalous magnetic moment of the τ-lepton.

beyond Standard Model↗

Simultaneous parameter optimization of x-ray and neutron reflectivity data using genetic algorithms

X-ray and neutron reflectivity are two non destructive techniques which provide a wealth of information on thickness, structure and interracial properties in nanometer length scale. Combination of X-ray and neutron reflectivity is well suited for obtaining physical parameters of nanostructured thin films and superlattices. Neutrons provide a different contrast between the elements than X-rays and are also sensitive to the magnetization depth profile in thin films and superlattices. The real space information is extracted by fitting a model for the structure of the thin film sample in reflectometry experiments. We have applied a Genetic Algorithms technique to extract depth dependent structure and magnetic in thin film and multilayer systems by simultaneously fitting X-ray and neutron reflectivity data.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

SU-F-J-199: Predictive Models for Cone Beam CT-Based Online Verification of Pencil Beam Scanning Proton Therapy

Purpose: To utilize online CBCT scans to develop models for predicting DVH metrics in proton therapy of head and neck tumors. Methods: Nine patients with locally advanced oropharyngeal cancer were retrospectively selected in this study. Deformable image registration was applied to the simulation CT, target volumes, and organs at risk (OARs) contours onto each weekly CBCT scan. Intensity modulated proton therapy (IMPT) treatment plans were created on the simulation CT and forward calculated onto each corrected CBCT scan. Thirty six potentially predictive metrics were extracted from each corrected CBCT. These features include minimum/maximum/mean over and under-ranges at the proximal and distal surface of PTV volumes, and geometrical and water equivalent distance between PTV and each OARs. Principal component analysis (PCA) was used to reduce the dimension of the extracted features. Three principal components were found to account for over 90% of variances in those features. Datasets from eight patients were used to train a machine learning model to fit these principal components with DVH metrics (dose to 95% and 5% of PTV, mean dose or max dose to OARs) from the forward calculated dose on each corrected CBCT. The accuracy of this model was verified on the datasets from the 9th patient. Results: The predicted changes of DVH metrics from the model were in good agreement with actual values calculated on corrected CBCT images. Median differences were within 1 Gy for most DVH metrics except for larynx and constrictor mean dose. However, a large spread of the differences was observed, indicating additional training datasets and predictive features are needed to improve the model. Conclusion: Intensity corrected CBCT scans hold the potential to be used for online verification of proton therapy and prediction of delivered dose distributions.

60 APPLIED LIFE SCIENCES↗

A consensus mathematical model of vaccine-induced antibody dynamics for multiple vaccine platforms and pathogens

Introduction: Vaccine platforms used in successful, licensed vaccines have varied among pathogens. However, antibody level is still the main clinical correlate of protection in most approved vaccines. Decisions as to the best vaccine platform to pursue for a given pathogen may be informed through improved understanding of the process of antibody generation and its temporal dynamics, as well as the relationship between these processes and the type of vaccine. Methods: We have analyzed the dynamics of antibody generation for different vaccine platforms against diverse pathogens, and developed a consensus mathematical model that captures antibody dynamics across these diverse systems. Initially, the model was fitted to a rich dataset of antibody and immune cell concentrations in a SARS-CoV-2 vaccine experiment. We then used concepts from machine learning, such as transfer learning, to apply the same model to a variety of systems, involving different pathogens, vaccine platforms, and booster dose use/timing, fixing most parameter values relating to the dynamics of the immune system. Results: The model includes B cell proliferation and differentiation, as well as the generation of plasma cells, which secrete large amounts of antibody, and memory B cells. Overall, the model describes antibody generation in all systems tested well and shows that the main differences across platforms are related to the dynamics of antigen presentation. Discussion: This model can be used to predict antibody generation in pairs of vaccine platform/pathogen, allowing for the use of in silico results to narrow down experimental burden in vaccine development.

59 BASIC BIOLOGICAL SCIENCES↗

Land surface model parameter optimisation using in situ flux data: comparison of gradient-based versus random search algorithms (a case study using ORCHIDEE v1.9.5.2)

Land surface models (LSMs), which form the land component of earth system models, rely on numerous processes for describing carbon, water and energy budgets, often associated with highly uncertain parameters. Data assimilation (DA) is a useful approach for optimising the most critical parameters in order to improve model accuracy and refine future climate predictions. In this study, we compare two different DA methods for optimising the parameters of seven plant functional types (PFTs) of the ORCHIDEE LSM using daily averaged eddy-covariance observations of net ecosystem exchange and latent heat flux at 78 sites across the globe. We perform a technical investigation of two classes of minimisation methods – local gradient-based (the L-BFGS-B algorithm, limited memory Broyden–Fletcher–Goldfarb–Shanno algorithm with bound constraints) and global random search (the genetic algorithm) – by evaluating their relative performance in terms of the model–data fit and the difference in retrieved parameter values. We examine the performance of each method for two cases: when optimising parameters at each site independently (“single-site” approach) and when simultaneously optimising the model at all sites for a given PFT using a common set of parameters (“multi-site” approach). We find that for the single site case the random search algorithm results in lower values of the cost function (i.e. lower model–data root mean square differences) than the gradient-based method; the difference between the two methods is smaller for the multi-site optimisation due to a smoothing of the cost function shape with a greater number of observations. The spread of the cost function, when performing the same tests with 16 random first-guess parameters, is much larger with the gradient-based method, due to the higher likelihood of being trapped in local minima. When using pseudo-observation tests, the genetic algorithm results in a closer approximation of the true posterior parameter value in the L-BFGS-B algorithm. We demonstrate the advantages and challenges of different DA techniques and provide some advice on using it for the LSM parameter optimisation.

58 GEOSCIENCES↗

Aerodynamic Measurements of a Gulfstream Aircraft Model With and Without Noise Reduction Concepts

Steady and unsteady aerodynamic measurements of a high-fidelity, semi-span 18% scale Gulfstream aircraft model are presented. The aerodynamic data were collected concurrently with acoustic measurements as part of a larger aeroacoustic study targeting airframe noise associated with main landing gear/flap components, gear-flap interaction noise, and the viability of related noise mitigation technologies. The aeroacoustic tests were conducted in the NASA Langley Research Center 14- by 22-Foot Subsonic Wind Tunnel with the facility in the acoustically treated open-wall (jet) mode. Most of the measurements were obtained with the model in landing configuration with the flap deflected at 39º and the main landing gear on and off. Data were acquired at Mach numbers of 0.16, 0.20, and 0.24. Global forces (lift and drag) and extensive steady and unsteady surface pressure measurements were obtained. Comparison of the present results with those acquired during a previous test shows a significant reduction in the lift experienced by the model. The underlying cause was traced to the likely presence of a much thicker boundary layer on the tunnel floor, which was acoustically treated for the present test. The steady and unsteady pressure fields on the flap, particularly in the regions of predominant noise sources such as the inboard and outboard tips, remained unaffected. It is shown that the changes in lift and drag coefficients for model configurations fitted with gear/flap noise abatement technologies fall within the repeatability of the baseline configuration. Therefore, the noise abatement technologies evaluated in this experiment have no detrimental impact on the aerodynamic performance of the aircraft model.

Neuhart, Dan H.↗