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Results for “Monte Carlo sampling”

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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

An empirical analysis of the quantitative effect of data when fitting quadratic and cubic polynomials

A study is made of the extent to which the size of the sample affects the accuracy of a quadratic or a cubic polynomial approximation of an experimentally observed quantity, and the trend with regard to improvement in the accuracy of the approximation as a function of sample size is established. The task is made possible through a simulated analysis carried out by the Monte Carlo method in which data are simulated by using several transcendental or algebraic functions as models. Contaminated data of varying amounts are fitted to either quadratic or cubic polynomials, and the behavior of the mean-squared error of the residual variance is determined as a function of sample size. Results indicate that the effect of the size of the sample is significant only for relatively small sizes and diminishes drastically for moderate and large amounts of experimental data.

Canavos, G. C.↗
DOE OSTI2024

Optimization using pathwise algorithmic derivatives of electromagnetic shower simulations

Among the well-known methods to approximate derivatives of expectancies computed by Monte-Carlo simulations, averages of pathwise derivatives are often the easiest one to apply. Computing them via algorithmic differentiation typically does not require major manual analysis and rewriting of the code, even for very complex programs like simulations of particle-detector interactions in high-energy physics. However, the pathwise derivative estimator can be biased if there are discontinuities in the program, which may diminish its value for applications. This work integrates algorithmic differentiation into the electromagnetic shower simulation code HepEmShow based on G4HepEm, allowing us to study how well pathwise derivatives approximate derivatives of energy depositions in a sampling calorimeter with respect to parameters of the beam and geometry. We found that when multiple scattering is disabled in the simulation, means of pathwise derivatives converge quickly to their expected values, and these are close to the actual derivatives of the energy deposition. Additionally, we demonstrate the applicability of this novel gradient estimator for stochastic gradient-based optimization in a model example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2011

Advanced Navigation Strategies for an Asteroid Sample Return Mission

The proximity operations phases of a sample return mission to an asteroid have been analyzed using advanced navigation techniques derived from experience gained in planetary exploration. These techniques rely on tracking types such as Earth-based radio metric Doppler and ranging, spacecraft-based ranging, and optical navigation using images of landmarks on the asteroid surface. Navigation strategies for the orbital phases leading up to sample collection, the touch down for collecting the sample, and the post sample collection phase at the asteroid are included. Options for successfully executing the phases are studied using covariance analysis and Monte Carlo simulations of an example mission to the near Earth asteroid 4660 Nereus. Two landing options were studied including trajectories with either one or two bums from orbit to the surface. Additionally, a comparison of post-sample collection strategies is presented. These strategies include remaining in orbit about the asteroid or standing-off a given distance until departure to Earth.

Bauman, J.↗
DOE OSTI2025

Deciphering the Scattering of Mechanically Driven Polymers Using Deep Learning

Here, we present a deep learning approach for analyzing two-dimensional scattering data of semiflexible polymers under external forces. In our framework, scattering functions are compressed into a three-dimensional latent space using a Variational Autoencoder (VAE), and two converter networks establish a bidirectional mapping between the polymer parameters (bending modulus, stretching force, and steady shear) and the scattering functions. The training data are generated using off-lattice Monte Carlo simulations to avoid the orientational bias inherent in lattice models, ensuring robust sampling of polymer conformations. The feasibility of this bidirectional mapping is demonstrated by the organized distribution of polymer parameters in the latent space. By integrating the converter networks with the VAE, we obtain a generator that produces scattering functions from given polymer parameters and an inferrer that directly extracts polymer parameters from scattering data. While the generator can be utilized in a traditional least-squares fitting procedure, the inferrer produces comparable results in a single pass and operates 3 orders of magnitude faster. This approach offers a scalable automated tool for polymer scattering analysis and provides a promising foundation for extending the method to other scattering models, experimental validation, and the study of time-dependent scattering data.

Ding, Lijie [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2025

Investigation of the Effect of Framework Flexibility on CO 2 Adsorption in SIFSIX-3-Cu Using a Machine-Learned Force Field

Metal–organic frameworks (MOFs) offer promise as selective CO 2 sorbents, but successful MOF sorbent materials need high CO 2 binding affinity and selectivity for CO 2 over water. This work focuses on the use of machine-learned force fields (MLFFs) to model CO 2 adsorption in flexible MOFs, with a focus on SIFSIX-3-Cu, an anion-pillared MOF known for its high CO 2 affinity. A preliminary high-throughput screening of over 900 anion-pillared MOFs was performed using rigid UFF+DDEC6 force fields to predict zero-loading heats of adsorption for CO 2 and H 2 O. SIFSIX-3-Cu was selected for further computational study due to its predicted CO 2 heat of adsorption and experimental relevance. A DeePMD-based MLFF was trained to reproduce DFT (PBE+D3) energies and forces, with an iterative sampling scheme combining molecular dynamics, geometry optimization, random geometric insertion, and NVT Monte Carlo-based configuration generation to capture both attractive and repulsive regions of the potential energy surface. Flexibility of the MOF was explicitly included, contrasting with previous models that approximated the MOF as rigid. Hybrid Monte Carlo/molecular dynamics (MC/MD) simulations with the MLFF produced CO 2 adsorption isotherms in good agreement with experimental data at direct air capture (DAC) pressures (e.g., 40 Pa), in contrast to previous overestimations of CO 2 sorption by models with rigid structures. Bond and angle histogram analysis showed that MOF flexibility increased the variance of fluorine–fluorine diagonal distances at adsorption sites, resulting in a lower predicted sorption for flexible, asymmetric SIFSIX-3-Cu pore geometries compared to the rigid, symmetric DFT-optimized SIFSIX-3-Cu pore geometry. A detailed description of flexibility afforded by the MLFF resulted in an accurately predicted CO 2 uptake (0.88 mmol/g) at low pressure (40 Pa) compared to the experimentally measured value (1.24 mmol/g). In conclusion, these results underscore the importance of including framework flexibility when modeling adsorption phenomena in MOFs, particularly for low-pressure applications.

adsorption↗
NASA NTRS1986

A Monte Carlo study of Weibull reliability analysis for space shuttle main engine components

The incorporation of a number of additional capabilities into an existing Weibull analysis computer program and the results of Monte Carlo computer simulation study to evaluate the usefulness of the Weibull methods using samples with a very small number of failures and extensive censoring are discussed. Since the censoring mechanism inherent in the Space Shuttle Main Engine (SSME) data is hard to analyze, it was decided to use a random censoring model, generating censoring times from a uniform probability distribution. Some of the statistical techniques and computer programs that are used in the SSME Weibull analysis are described. The methods documented in were supplemented by adding computer calculations of approximate (using iteractive methods) confidence intervals for several parameters of interest. These calculations are based on a likelihood ratio statistic which is asymptotically a chisquared statistic with one degree of freedom. The assumptions built into the computer simulations are described. The simulation program and the techniques used in it are described there also. Simulation results are tabulated for various combinations of Weibull shape parameters and the numbers of failures in the samples.

Abernethy, K.↗
NASA NTRS1993

Double troughs in broad absorption line quasars and Ly-alpha-N V line-locking

It was investigated whether the double trough (DT) structure in the mean C IV BAL trough reported by Weymann et al. (1991) is real or due to statistical fluctuations of BAL troughs over random outflow velocities in a limited sample. A sample of 72 BAL QSOs with C IV BAL troughs was analyzed. It is found that only 22 percent of the sample explicitly exhibits the DT feature; when present the DTs are deep. A Monte Carlo simulation of the mean C IV BAL suggests that the DT feature is real at only the 95-98 percent level.

Korista, Kirk T.↗
NASA NTRS1999

Entry Dispersion Analysis for the Genesis Sample Return Capsule

Genesis will be the first mission to return samples from beyond the Earth-Moon system. The spacecraft will be inserted into a halo orbit about the L1 (Sun- Earth) libration point where it will remain for two years collecting solar wind particles. Upon Earth return, the sample return capsule, which is passively controlled, will descend under parachute to Utah. The present study describes the analysis of the entry, descent, and landing scenario of the returning sample cap- sule. The robustness of the entry sequence is assessed through a Monte Carlo dispersion analysis where the impact of off-nominal conditions is ascertained. The dispersion results indicate that the capsule attitude excursions near peak heating and drogue chute deployment are within Genesis mission limits. Additionally, the size of the resulting 3-sigma landing ellipse is 47.8 km in downrange by 15.2 km in crossrange, which is within the Utah Test and Training Range boundaries.

Desai, Prasun, N.↗
NASA NTRS2010

Optical Imaging and Radiometric Modeling and Simulation

OPTOOL software is a general-purpose optical systems analysis tool that was developed to offer a solution to problems associated with computational programs written for the James Webb Space Telescope optical system. It integrates existing routines into coherent processes, and provides a structure with reusable capabilities that allow additional processes to be quickly developed and integrated. It has an extensive graphical user interface, which makes the tool more intuitive and friendly. OPTOOL is implemented using MATLAB with a Fourier optics-based approach for point spread function (PSF) calculations. It features parametric and Monte Carlo simulation capabilities, and uses a direct integration calculation to permit high spatial sampling of the PSF. Exit pupil optical path difference (OPD) maps can be generated using combinations of Zernike polynomials or shaped power spectral densities. The graphical user interface allows rapid creation of arbitrary pupil geometries, and entry of all other modeling parameters to support basic imaging and radiometric analyses. OPTOOL provides the capability to generate wavefront-error (WFE) maps for arbitrary grid sizes. These maps are 2D arrays containing digital sampled versions of functions ranging from Zernike polynomials to combination of sinusoidal wave functions in 2D, to functions generated from a spatial frequency power spectral distribution (PSD). It also can generate optical transfer functions (OTFs), which are incorporated into the PSF calculation. The user can specify radiometrics for the target and sky background, and key performance parameters for the instrument s focal plane array (FPA). This radiometric and detector model setup is fairly extensive, and includes parameters such as zodiacal background, thermal emission noise, read noise, and dark current. The setup also includes target spectral energy distribution as a function of wavelength for polychromatic sources, detector pixel size, and the FPA s charge diffusion modulation transfer function (MTF).

Ha, Kong Q.↗
NASA NTRSDate not supplied

Adaptive Stress Testing of Trajectory Predictions in Flight Management Systems

To find failure events and their likelihoods in flight-critical systems, we investigate the use of an advanced black-box stress testing approach called adaptive stress testing. We analyze a trajectory predictor from a developmental commercial flight management system which takes as input a collection of lateral waypoints and en-route environmental conditions. Our aim is to search for failure events relating to inconsistencies in the predicted lateral trajectories. The intention of this work is to find likely failures and report them back to the developers so they can address and potentially resolve shortcomings of the system before deployment. To improve search performance, this work extends the adaptive stress testing formulation to be applied more generally to sequential decision-making problems with episodic reward by collecting the state transitions during the search and evaluating at the end of the simulated rollout. We use a modified Monte Carlo tree search algorithm with progressive widening as our adversarial reinforcement learner. The performance is compared to direct Monte Carlo simulations and to the cross-entropy method as an alternative importance sampling baseline. The goal is to find potential problems otherwise not found by traditional requirements-based testing. Results indicate that our adaptive stress testing approach finds more failures and finds failures with higher likelihood relative to the baseline approaches.

adaptive stress testing↗
NASA NTRS1981

Incorporating partially identified sample segments into acreage estimation procedures: Estimates using only observations from the current year

Several methods of estimating individual crop acreages using a mixture of completely identified and partially identified (generic) segments from a single growing year are derived and discussed. A small Monte Carlo study of eight estimators is presented. The relative empirical behavior of these estimators is discussed as are the effects of segment sample size and amount of partial identification. The principle recommendations are (1) to not exclude, but rather incorporate partially identified sample segments into the estimation procedure, (2) try to avoid having a large percentage (say 80%) of only partially identified segments, in the sample, and (3) use the maximum likelihood estimator although the weighted least squares estimator and least squares ratio estimator both perform almost as well. Sets of spring small grains (North Dakota) data were used.

Sielken, R. L., Jr.↗
NASA NTRS1997

Energy Calibration of the Scintillating Optical Fiber Calorimeter Chamber (SOFCAL)

The Scintillating Optical Fiber Calorimeter (SOFCAL) detector is designed to make direct measures of the primary cosmic ray spectrum from -200 GeV/amu - 20 TeV/amu. The primary particles are resolved into groups according to their charge (p, He, CNO, Medium Z, Heavy Z) using both active and passive components integrated into the detector. The principal part of SOFCAL is a thin ionization calorimeter that measures the electromagnetic cascades that result from these energetic particles interacting in the detector. The calorimeter is divided into two sections: a thin passive emulsion/x-ray film calorimeter, and a fiber calorimeter that uses crossing layers of small scintillating optical fibers to sample the energy deposition of the cascades. The energy determination is made by fitting the fiber data to transition curves generated by Monte Carlo simulations. The fiber data must first be calibrated using the electron counts from the emulsion plates in the calorimeter for a small number of events. The technique and results of this calibration will be presented together with samples of the data from a balloon flight.

Christl, M. C.↗
NASA NTRS1985

The composition of cosmic rays near the Bend (10 to the 15th power eV) from a study of muons in air showers at sea level

The distribution of muons near shower cores was studied at sea level at Fermilab using the E594 neutrino detector to sample the muon with E testing 3 GeV. These data are compared with detailed Monte Carlo simulations to derive conclusions about the composition of cosmic rays near the bend in the all particle spectrum. Monte Carlo simulations generating extensive air showers (EAS) with primary energy in excess of 50 TeV are described. Each shower record contains details of the electron lateral distribution and the muon and hadron lateral distributions as a function of energy, at the observation level of 100g/cm. The number of detected electrons and muons in each case was determined by a Poisson fluctuation of the number incident. The resultant predicted distribution of muons, electrons, the rate events are compared to those observed. Preliminary results on the rate favor a heavy primary dominated cosmic ray spectrum in energy range 50 to 1000 TeV.

Goodman, J. A.↗
NASA NTRS1993

Improving the chi-squared approximation for bivariate normal tolerance regions

Let X be a two-dimensional random variable distributed according to N2(mu,Sigma) and let bar-X and S be the respective sample mean and covariance matrix calculated from N observations of X. Given a containment probability beta and a level of confidence gamma, we seek a number c, depending only on N, beta, and gamma such that the ellipsoid R = (x: (x - bar-X)'S(exp -1) (x - bar-X) less than or = c) is a tolerance region of content beta and level gamma; i.e., R has probability gamma of containing at least 100 beta percent of the distribution of X. Various approximations for c exist in the literature, but one of the simplest to compute -- a multiple of the ratio of certain chi-squared percentage points -- is badly biased for small N. For the bivariate normal case, most of the bias can be removed by simple adjustment using a factor A which depends on beta and gamma. This paper provides values of A for various beta and gamma so that the simple approximation for c can be made viable for any reasonable sample size. The methodology provides an illustrative example of how a combination of Monte-Carlo simulation and simple regression modelling can be used to improve an existing approximation.

Feiveson, Alan H.↗
DOE OSTI2026

D$e^+e^-$ffusion: Capturing the Beam-Beam Physics of $e^+e^-$ Collisions with Diffusion Models

Beam-induced backgrounds at high-luminosity $e^+e^-$ colliders, such as the FCC-ee, are dominated by incoherent pair creation (IPC), and require computationally expensive simulations with dedicated Monte Carlo (MC) event generators. Reliable detector and machine-detector interface studies necessitate event samples that are several orders of magnitude larger than what is practically attainable with existing MC. To alleviate this bottleneck, we present D$e^+e^-$ffusion, a denoising diffusion probabilistic model that operates as a permutation-equivariant, set-valued surrogate for fast IPC simulation. Trained on a small GuineaPig++ sample, D$e^+e^-$ffusion faithfully reproduces the marginal and joint kinematic, angular, and positional distributions of all three IPC production processes. In addition, we assess the fidelity at the detector level by propagating both Geant4 and D$e^+e^-$ffusion events through a Geant4 simulation of the CLD vertex detector and by training a transformer-based two-sample classifier; the classifier achieves an area under the ROC curve of $0.553 \pm 0.016$. The trained model generates events nearly four orders of magnitude faster than Geant4, paving the way for a fast-simulation surrogate for FCC-ee design studies.

Chahine, Antonio [Imperial Coll., London]↗
NASA NTRS2004

Simulations of Hyperthermal Oxygen Beam Exposures

Pulsed sources of hyper-thermal O-atoms are now being extensively used to simulate low-earth orbit (LEO) surface exposure environments. The peak flux of these sources is many orders of magnitude larger than the corresponding LEO flux. Although it is desirable to accelerate the test by using higher fluxes than found in LEO, even commonly used fluxes are large enough to produce multi-collision effects by causing a build-up of gas at the sample surface. In this paper we characterize the physical consequences to the experiment using the direct simulation Monte Carlo (DSMC) method, DSMC allows us to extract the distributions of energy and impact angle for the O-atoms that reach the surface, and to record how strongly the gas build-up at the target assembly deflects flux from downstream instrumentation. By considering a range of source fluxes, we determine the onset conditions and severity of these multi-collision effects. We find that even at common experimental fluxes with a normally incident beam string a flat surface sample, the energy distribution of incident O-atoms broadens and develops a significant low-energy tail. The angular distributions also broaden significantly. The number of O-atoms that reach downstream instrumentation is decreased by approximately 50%. These simulations will aid in the calibration of ground-based O-atom measurements,a nd provide a model for the energy and angular distributions of O-atoms that actually impinge on surface samples.

Finchum, A.↗