SEARCH · Engineering Papers

Results for “Prior Distribution”

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 55 records · Page 3

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Wind turbine blade design with airfoil shape control using invertible neural networks

Wind turbine blade design is a highly multidisciplinary process that involves aerodynamics, structures, controls, manufacturing, costs, and other considerations. More efficient blade designs can be found by controlling the airfoil cross-sectional shapes simultaneously with the bulk blade twist and chord distributions. Prior work has focused on incorporating panel-based aerodynamic solvers with a blade design framework to allow for airfoil shape control within the design loop in a tractable manner. Including higher fidelity aerodynamic solvers, such as computational fluid dynamics, makes the design problem computationally intractable. In this work, we couple an invertible neural network trained on high-fidelity airfoil aerodynamic data to a turbine design framework to enable the design of airfoil cross sections within a larger blade design problem. We detail the methodology of this coupled framework and showcase its efficacy by aerostructurally redesigning the IEA 15-MW reference wind turbine blade. The coupled approach reduces the cost of energy by 0.9% compared to a more conventional design approach. This work enables the inclusion of high-fidelity aerodynamic data earlier in the design process, reducing cycle time and increasing certainty in the performance of the optimal design.

17 WIND ENERGY↗

DOE OSTI2022

Constraining ΛCDM cosmological parameters with Einstein Telescope mock data

ABSTRACT We investigate the capability of Einstein Telescope to constrain the cosmological parameters of the non-flat ΛCDM cosmological model. Two types of mock data sets are considered depending on whether or not a short gamma-ray burst is detected, and associated with the gravitational wave emitted by binary neutron stars merger, using the THESEUS satellite. Depending on the mock data set, two statistical estimators are applied: one assumes that the redshift is known, while the other marginalizes over it assuming a specific redshift prior distribution. We demonstrate that (i) using mock catalogues collecting gravitational wave signals emitted by binary neutron stars systems to which a short gamma-ray burst has been associated, Einstein Telescope may achieve an accuracy on the cosmological parameters of $\sigma _{H_0}\approx 0.40$ km s−1 Mpc−1, $\sigma _{\Omega _{k,0}}\approx 0.09$, and $\sigma _{\Omega _{\Lambda ,0}}\approx 0.07$; while (ii) using mock catalogues collecting all gravitational wave signals emitted by binary neutron stars systems for which an electromagnetic counterpart has not been detected, Einstein Telescope may achieve an accuracy on the cosmological parameters of $\sigma _{H_0}\approx 0.04$ km s−1 Mpc−1, $\sigma _{\Omega _{k,0}}\approx 0.01$, and $\sigma _{\Omega _{\Lambda ,0}}\approx 0.01$, once the redshift probability distribution of GW events is known from from population synthesis simulations and/or the measure of the tidal deformability parameter. These results show an improvement of a factor 2–75 with respect to earlier results using complementary data sets.

Califano, Matteo↗

DOE OSTI2026

Microscopic constraints for the equation of state and structure of neutron stars: A Bayesian model mixing framework

Bayesian model mixing (BMM) is a statistical technique that can combine constraints from different regions of an input space in a principled way. Here we extend our BMM framework for the equation of state (EOS) of strongly interacting matter from symmetric nuclear matter to asymmetric matter, specifically focusing on zero-temperature, charge-neutral, 𝛽-equilibrated matter. We use Gaussian processes (GPs) to infer constraints on the neutron-star matter EOS at intermediate densities from two different microscopic theories: chiral effective-field theory (𝜒⁢EFT) at baryon densities around nuclear saturation, 𝑛 𝐵 ∼ 𝑛 0 , and perturbative QCD at asymptotically high baryon densities, 𝑛 𝐵 ⩾ 20⁢𝑛 0 . The uncertainties of the 𝜒⁢EFT and pQCD EOSs are obtained using the BUQEYE truncation error model. We demonstrate the flexibility of our framework through the use of two categories of GP kernels: conventional stationary kernels and a nonstationary changepoint kernel. We use the latter to explore potential constraints on the dense matter EOS by including exogenous data representing theory predictions and heavy-ion collision measurements at densities ⩾ 2⁢𝑛 0 . We also use our EOSs to obtain neutron-star mass-radius relations and their uncertainties. Finally, our framework, whose implementation will be available through a GitHub repository, provides a prior distribution for the EOS that can be used in large-scale neutron-star inference frameworks.

Bayesian methods↗

DOE OSTI2025

Bayesian model mixing with multireference energy density functional

Reliably predicting nuclear properties across the entire chart of isotopes is important for applications ranging from nuclear astrophysics to superheavy science to nuclear technology. To this day, however, all the theoretical models that can scale at the level of the chart of isotopes remain semiphenomenological. Because they are fitted locally, their predictive power can vary significantly; different versions of the same theory provide different predictions. Bayesian model mixing takes advantage of such imperfect models to build a local mixture of a set of models to make improved predictions. Earlier attempts to use Bayesian model mixing for mass table calculations relied on models treated at single-reference energy density functional level, which fail to capture some of the correlations caused by configuration mixing or the restoration of broken symmetries. In this study we have applied Bayesian model mixing techniques within a multireference energy density functional (MR-EDF) framework. We considered predictions of two-particle separation energies from particle number projection or angular momentum projection with four different energy density functionals—a total of eight different MR-EDF models. We used a hierarchical Bayesian stacking framework with a Dirichlet prior distribution over weights together with an inverse log-ratio transform to enable positive correlations between different models. We found that Bayesian model mixing provides significantly improved predictions compared to the participating models. Published by the American Physical Society 2025

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Concordance

Dimension reduction techniques have long been an important topic in statistics, and active subspaces (AS) have received much attention this past decade in the computer experiments literature. The most common approach towards estimating the AS is to use Monte Carlo with numerical gradient evaluation. This software takes a new approach towards estimating the active subspace, in which Multivariate Adaptive Regression Splines (MARS) is used as a surrogate model, and relevant calculation are obtained analytically. Using a MARS surrogate has many advantages including improved scaling, better estimation of active subspaces in high dimensions and the ability to handle a large number of prior distributions in closed form. This software is also capable of conducting a so-called "concordance analysis", using a generalization of ASs which we refer to as "Co-Active" subspaces.

Rumsey, Kelin↗

DOE OSTI2024

Matilda v1.0: An R package for probabilistic climate projections using a reduced complexity climate model

A primary advantage to using reduced complexity climate models (RCMs) has been their ability to quickly conduct probabilistic climate projections, a key component of uncertainty quantification in many impact studies and multisector systems. Providing frameworks for such analyses has been a target of several RCMs used in studies of the future co-evolution of the human and Earth systems. In this paper, we present Matilda, an open-science R software package that facilitates probabilistic climate projection analysis, implemented here using the Hector simple climate model in a seamless and easily applied framework. The primary goal of Matilda is to provide the user with a turn-key method to build parameter sets from literature-based prior distributions, run Hector iteratively to produce perturbed parameter ensembles (PPEs), weight ensembles for realism against observed historical climate data, and compute probabilistic projections for different climate variables. This workflow gives the user the ability to explore viable parameter space and propagate uncertainty to model ensembles with just a few lines of code. The package provides significant freedom to select different scoring criteria and algorithms to weight ensemble members, as well as the flexibility to implement custom criteria. Additionally, the architecture of the package simplifies the process of building and analyzing PPEs without requiring significant programming expertise, to accommodate diverse use cases. We present a case study that provides illustrative results of a probabilistic analysis of mean global surface temperature as an example of the software application.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1975

Reliability-based optimum inspection and maintenance procedures

The development of reliability-based optimum inspection and maintenance schedules for engines needs an understanding of the fatigue behavior of the engines. Critical areas of the engine structure prone to fatigue damage are usually identified beforehand or after the fleet has been put into operation. In these areas, fatigue cracks initiate after several flight hours, and these cracks grow in length until failure takes place when these cracks attain the critical lengths. Crack initiation time and its growth rate are considered to be random variables. Usually, the inspection (fatigue) or test data from similar engines are used as prior distributions. The existing state-of-the-art is to ignore the different lengths of cracks obserbed at various inspections and to consider only the fact that a crack existed (or did not exist) at the time of inspection. In this paper, a procedure has been developed to obtain the probability of finding a crack of a given size at a certain time if the probability distributions for crack initiation and rates of growth are known. Application of the developed stochastic models to devise optimum procedures for inspection and maintenance are also discussed.

Nanagud, S.↗

NASA NTRS1980

Proportion estimation using prior cluster purities

The prior distribution of CLASSY component purities is studied, and this information incorporated into maximum likelihood crop proportion estimators. The method is tested on Transition Year spring small grain segments.

Terrell, G. R.↗

NASA NTRS1980

The multicategory case of the sequential Bayesian pixel selection and estimation procedure

A Bayesian technique for stratified proportion estimation and a sampling based on minimizing the mean squared error of this estimator were developed and tested on LANDSAT multispectral scanner data using the beta density function to model the prior distribution in the two-class case. An extention of this procedure to the k-class case is considered. A generalization of the beta function is shown to be a density function for the general case which allows the procedure to be extended.

Pore, M. D.↗

NASA NTRS1986

A stopping theoretic approach to minimal time detection of system parameter change

The problem of minimal time detection of abrupt parameter changes in linear stochastic systems considered. The problem is posed as an optimal stopping problem for the detection in change of the induced probability measure. Under the assumption of a prior distribution for the time of change (or disruption) a stopping rule is given which minimizes the average detection delay when there is knowledge of the new measure after the change. When the new induced measure is unknown, a stopping rule is given, based only on the noisy observations and is shown to be better than the a priori knowlege of the disruption time.

Mazumdar, Ravi R.↗

NASA NTRS1991

Development of a Weibull posterior distribution by combining a Weibull prior with an actual failure distribution using Bayesian inference

A Bayesian inference process for system logistical planning is presented which provides a method for incorporating actual failures with prediction data for an ongoing and improving reliability estimates. The process uses the Weibull distribution, and provides a means for examining and updating logistical and maintenance support needs.

Giuntini, Michael E.↗

NASA NTRS1999

A Multiwavelength Search for Correlated Time Variations in the Brightest Egret Blazers

The February 1996 flare of 3C279 peaked at the highest gamma-ray intensity ever recorded for this object. Compton Gamma Ray Observatory (CGRO), Rossi X-Ray Timing Explorer (RXTE), Advanced Satellite For Cosmology and Astrophysics (ASCA), Roentgen Satellite (ROSAT), International Ultraviolet Explorer (IUE), Hubble Space Telescope (HST), Infrared Space Observatory (ISO) and 18 ground-based observatories participated in observations at various times during January and February 1996. The CGRO EGRET and RXTE light curves are correlated during the flare without any lag larger than the temporal resolution of about 1 day. We present simultaneous spectral energy distributions prior to and near the flare peak. The gamma-rays vary by more than the square of the observed infrared-optical flux change, which poses some problems for specific blazar models.

Urry, C. Megan↗

NASA NTRS2007

Plasma Measurements in an Integrated-System FARAD Thruster

Pulsed inductive plasma accelerators are spacecraft propulsion devices in which energy is stored in a capacitor and then discharged through an inductive coil. The device is electrodeless, inducing a current sheet in a plasma located near the face of the coil. The propellant is accelerated and expelled at a high exhaust velocity (order of 10 km/s) through the interaction of the plasma current and the induced magnetic field. The Faraday Accelerator with RF-Assisted Discharge (FARAD) thruster[1,2] is a type of pulsed inductive plasma accelerator in which the plasma is preionized by a mechanism separate from that used to form the current sheet and accelerate the gas. Employing a separate preionization mechanism allows for the formation of an inductive current sheet at much lower discharge energies and voltages than those used in previous pulsed inductive accelerators like the Pulsed Inductive Thruster (PIT). A benchtop FARAD thruster was designed following guidelines and similarity performance parameters presented in Refs. [3,4]. This design is described in detail in Ref. [5]. In this paper, we present the temporally and spatially resolved measurements of the preionized plasma and inductively-accelerated current sheet in the FARAD thruster operating with a Vector Inversion Generator (VIG) to preionize the gas and a Bernardes and Merryman circuit topology to provide inductive acceleration. The acceleration stage operates on the order of 100 J/pulse. Fast-framing photography will be used to produce a time-resolved, global view of the evolving current sheet. Local diagnostics used include a fast ionization gauge capable of mapping the gas distribution prior to plasma initiation; direct measurement of the induced magnetic field using B-dot probes, induced azimuthal current measurement using a mini-Rogowski coil, and direct probing of the number density and electron temperature using triple probes.

Polzin, K. A.↗

NASA NTRS2010

Behavioral Health and Performance (BHP) Standing Review Panel (SRP) Final Report

The first meeting of the Behavioral Health and Performance (BHP) Standing Review Panel (SRP) was held in Houston, TX on November 1-3, 2009. Our task was to assess the Integrated Research Plan (IRP) related to the fields covered in the SRP charge (see section VIII). Having considered and discussed the extensive materials distributed prior to the meeting, and the highly informative briefings by the NASA BHP Human Research Program (HRP) personnel during the site visit, the SRP agreed that the IRP is comprehensive and was developed carefully. Question and answer periods with the presenters were particularly productive and helpful to the SRP. The presenters' willingness to share information and positive responses to the SRP's suggestions were greatly appreciated. Although the IRP and related documents are impressive, the SRP does have a number of recommendations regarding both the overall plan and its component parts.

Suedfeld, Peter↗

NASA NTRS2010

JSC Safety and Mission Assurance Data Analysis Overview

These slides describe the data analysis methods that are used to determine inputs for probabilistic risk models supporting the Space Shuttle Program. Other applications can follow a similar path probably using different data sources. Statistical approaches are different and not addressed here. Topics included here: 1) Prior Distribution; 2) Likelihood Data; 3) Bayesian Updating; and 4) Uncertainty and Error. Note: This is a high-level discussion and is not intended to be a tutorial.

Roelant, Henk↗

NASA NTRS2013

Downscaling Satellite Precipitation with Emphasis on Extremes: A Variational 1-Norm Regularization in the Derivative Domain

The increasing availability of precipitation observations from space, e.g., from the Tropical Rainfall Measuring Mission (TRMM) and the forthcoming Global Precipitation Measuring (GPM) Mission, has fueled renewed interest in developing frameworks for downscaling and multi-sensor data fusion that can handle large data sets in computationally efficient ways while optimally reproducing desired properties of the underlying rainfall fields. Of special interest is the reproduction of extreme precipitation intensities and gradients, as these are directly relevant to hazard prediction. In this paper, we present a new formalism for downscaling satellite precipitation observations, which explicitly allows for the preservation of some key geometrical and statistical properties of spatial precipitation. These include sharp intensity gradients (due to high-intensity regions embedded within lower-intensity areas), coherent spatial structures (due to regions of slowly varying rainfall),and thicker-than-Gaussian tails of precipitation gradients and intensities. Specifically, we pose the downscaling problem as a discrete inverse problem and solve it via a regularized variational approach (variational downscaling) where the regularization term is selected to impose the desired smoothness in the solution while allowing for some steep gradients(called 1-norm or total variation regularization). We demonstrate the duality between this geometrically inspired solution and its Bayesian statistical interpretation, which is equivalent to assuming a Laplace prior distribution for the precipitation intensities in the derivative (wavelet) space. When the observation operator is not known, we discuss the effect of its misspecification and explore a previously proposed dictionary-based sparse inverse downscaling methodology to indirectly learn the observation operator from a database of coincidental high- and low-resolution observations. The proposed method and ideas are illustrated in case studies featuring the downscaling of a hurricane precipitation field.

Hurricanes↗

NASA NTRS2020

Bayesian Approach for Determining Microlens System Properties with High-angular resolution Follow-up Imaging

We present the details of the Bayesian analysis of the planetary microlensing event MOA-2016-BLG-227, whose excess ﬂux is likely due to a source/lens companion or an unrelated ambient star, as well as of the assumed prior distributions. Furthermore, we apply this method to four reported planetary events, MOA-2008-BLG-310, MOA2011-BLG-293, OGLE-2012-BLG-0527, and OGLE-2012-BLG-0950, where adaptive optics observations have detected excess ﬂux at the source star positions. For events with small angular Einstein radii, our lens mass estimates are more uncertain than those of previous analyses, which assumed that the excess was due to the lens. Our predictions for MOA-2008-BLG-310 and OGLE-2012-BLG-0950 are consistent with recent results on these events obtained via Keck and Hubble Space Telescope observations when the source star is resolvable from the lens star. For events with small angular Einstein radii, we ﬁnd that it is generally difﬁcult to conclude whether the excess ﬂux comes from the host star. Therefore, it is necessary to identify the lens star by measuring its proper motion relative to the source star to determine whether the excess ﬂux comes from the lens star. Even without such measurements, our method can be used to statistically test the dependence of the planet-hosting probability on the stellar mass.

Naoki Koshimoto↗

NASA NTRSDate not supplied

rHEALTH Laboratory Analyzer - ISS Increment 66 Tech Demo

A multilateral, web-based symposium, featuring ISS Increment 66 investigations will be held on December 14, 15 and 16, 2021 beginning at 0600 CST each day. The purpose of this event is for Principal Investigators to present their science objectives, testing approach, and measurement methods to agency scientists, managers, and other investigators. Participation is encouraged to gather a global picture of the science planned to be performed on ISS during Increment 66. Please note that only Increment 66 new investigations and those that have not been covered by previous science symposia will be included. We will be in touch with the investigations’ POCs to confirm the presentations and identify the speakers as we develop the preliminary agenda for the Symposium. The agenda and additional details will be distributed prior to the symposium. Presentations will be organized by discipline and will be allotted 15 minutes to highlight the main contributions of their experiment. There will be a short question and answer period after each discipline group session is complete. Please include back-up material as needed. The presentations may be made available to ISS crew members as review material for on-orbit science preparation and/or public outreach activities. Therefore, please ensure a comprehensive presentation (additional back-up material may be provided). The presentations should briefly cover the following: - Science background and hypothesis - Investigation goals and objectives - Measurement approach - Importance and reason for ISS - Expected results and how they will advance the field - Earth benefits/spin-off applications Please note that all presentations and discussions should be limited to content approved for export and information that can be shared with participants and the general public.

Laboratory Analysis↗