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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

A stereo triangulation system for structural identification: Analytical and experimental results

Identification of large space structures' distributed mass, stiffness, and energy dissipation characteristics poses formidable analytical, numerical, and implementation difficulties. Development of reliable on-orbit structural identification methods is important for implementing active vibration suppression concepts which are under widespread study in the large space structures community. Near the heart of the identification problem lies the necessity of making a large number of spatially distributed measurements of the structure's vibratory response and the associated force/moment inputs with sufficient spatial and frequency resolution. In the present paper, we discuss a method whereby tens of active or passive (retro-reflecting) targets on the structure are tracked simultaneously by the focal planes of two or more video cameras mounted on an adjacent platform. Triangulation (optical ray intersection) of the conjugate image centroids yield inertial trajectories of each target on the structure. Given the triangulated motion of the targets, we apply and extend methodology developed by Creamer, Junkins, and Juang to identify the frequencies, mode shapes, and updated estimates for the mass/stiffness/damping parameterization of the structure. The methodology is semi-automated, for example, the post experiment analysis of the video imagery to determine the inertial trajectories of the targets typically requires less than thirty minutes of real time. Using methodology discussed herein, the frequency response of a large number of points on the structure (where reflective targets are mounted) on the structure can be determined from optical measurements alone. For comparison purposes, we also utilize measurements from accelerometers and a calibrated impulse hammer. While our experimental work remains in a research stage of development, we have successfully tracked and stereo triangulated 20 targets (on a vibrating cantilevered grid structure) at a sample frequency of 200 HZ, and have established conclusively the feasibility and desirability of this approach. We discuss, in summary, recent advances in analog and digital video processing methodology, actuation methods, and bring them to bear on the structural identification problem. We include a brief discussion of our experimental hardware and some recent experimental results which support the practical feasibility of this structural vibration sensing approach.

Junkins, J. L.↗
DOE OSTI2022

Implementation of a practical Markov chain Monte Carlo sampling algorithm in PyBioNetFit

Abstract Summary Bayesian inference in biological modeling commonly relies on Markov chain Monte Carlo (MCMC) sampling of a multidimensional and non-Gaussian posterior distribution that is not analytically tractable. Here, we present the implementation of a practical MCMC method in the open-source software package PyBioNetFit (PyBNF), which is designed to support parameterization of mathematical models for biological systems. The new MCMC method, am, incorporates an adaptive move proposal distribution. For warm starts, sampling can be initiated at a specified location in parameter space and with a multivariate Gaussian proposal distribution defined initially by a specified covariance matrix. Multiple chains can be generated in parallel using a computer cluster. We demonstrate that am can be used to successfully solve real-world Bayesian inference problems, including forecasting of new Coronavirus Disease 2019 case detection with Bayesian quantification of forecast uncertainty. Availability and implementation PyBNF version 1.1.9, the first stable release with am, is available at PyPI and can be installed using the pip package-management system on platforms that have a working installation of Python 3. PyBNF relies on libRoadRunner and BioNetGen for simulations (e.g. numerical integration of ordinary differential equations defined in SBML or BNGL files) and Dask.Distributed for task scheduling on Linux computer clusters. The Python source code can be freely downloaded/cloned from GitHub and used and modified under terms of the BSD-3 license (https://github.com/lanl/pybnf). Online documentation covering installation/usage is available (https://pybnf.readthedocs.io/en/latest/). A tutorial video is available on YouTube (https://www.youtube.com/watch?v=2aRqpqFOiS4&t=63s). Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Vortex Structure of Head Bubble in Convective Cloud Starting Plume

Abstract A developing cumulus cloud (Cu) was modeled, and dynamic, thermodynamic, and microphysical properties of an ascending head bubble reproducing the upper part of a developing Cu were investigated. The data for analysis are taken from 10-m-resolution LES of trade wind Cu under BOMEX conditions. The detection of a rising bubble is carried out using wavelet filtering of the velocity fields and microphysical fields, while a low-frequency signal of the filtering is associated with the convective-scale structure of cloud. We substantiate and discuss the representation of the bubble as a vortex ring, and estimate the parameters of this vortex ring. The simplest Hill’s vortex was chosen as a model of a vortex ring inside cloud. Analytical approximations of the radial profiles of the vertical velocity and of conservative quantities (such as total water mixing ratio and liquid water potential temperature inside and outside the bubble) are obtained. The spatial structure of these quantities is investigated using analytical expressions. Analytical models for spatial distributions of liquid water content (LWC) and adiabatic fraction (AF) are also designed and analyzed. The results demonstrate the existence of a cloud core with high values of LWC and AF up to the height of 1800 m. The horizontally averaged value of the adiabatic fraction, calculated analytically using the Hill’s vortex concept, is evaluated as 0.39, which is the typical AF value in the upper parts of such Cu. The vertical profiles of different important quantities characterizing cloud structure are presented. The analysis performed in this study allows us to conclude that a rising vortex ring plays the dominating role in formation of the thermodynamic and microphysical structure of developing Cu. Significance Statement 1) Dynamic and thermodynamic fields of a developing cumulus cloud simulated by high-resolution LES with spectral bin microphysics are separated into convective and turbulent components by means of the wavelet technique. 2) The analysis of convective component of the cloud revealed the existence of a vortex ring at the developing stage of the cloud and evaluate its parameters. 3) The analysis performed in this study allows us to conclude that a rising vortex ring plays the important role in formation of the thermodynamic and microphysical structure of developing Cu. 4) The study provides a novel insight into the cloud–environment interaction. 5) The approximating equations describing the vortex ring can be usefully applied for developing new schemes of convective parameterization.

Meteorology & Atmospheric Sciences↗
NASA NTRS2009

Thermal-Structural Analysis of PICA Tiles for Solar Tower Test

Thermal protection materials used in spacecraft heatshields are subjected to severe thermal and mechanical loading environments during re-entry into earth atmosphere. In order to investigate the reliability of PICA tiles in the presence of high thermal gradients as well as mechanical loads, the authors designed and conducted solar-tower tests. This paper presents the design and analysis work for this tests series. Coupled non-linear thermal-mechanical finite element analyses was conducted to estimate in-depth temperature distribution and stress contours for various cases. The first set of analyses performed on isolated PICA tile showed that stresses generated during the tests were below the PICA allowable limit and should not lead to any catastrophic failure during the test. The tests results were consistent with analytical predictions. The temperature distribution and magnitude of the measured strains were also consistent with predicted values. The second test series is designed to test the arrayed PICA tiles with various gap-filler materials. A nonlinear contact method is used to model the complex geometry with various tiles. The analyses for these coupons predict the stress contours in PICA and inside gap fillers. Suitable mechanical loads for this architecture will be predicted, which can be applied during the test to exceed the allowable limits and demonstrate failure modes. Thermocouple and strain-gauge data obtained from the solar tower tests will be used for subsequent analyses and validation of FEM models.

Agrawal, Parul↗
NASA NTRS2006

Dynamic Analysis of Large In-Space Deployable Membrane Antennas

This paper presents a vibration analysis of an eight-meter diameter membrane reflectarray antenna, which is composed of a thin membrane and a deployable frame. This analysis process has two main steps. In the first step, a two-variable-parameter (2-VP) membrane model is developed to determine the in-plane stress distribution of the membrane due to pre-tensioning, which eventually yields the differential stiffness of the membrane. In the second step, the obtained differential stiffness is incorporated in a dynamic equation governing the transverse vibration of the membrane-frame assembly. This dynamic equation is then solved by a semi-analytical method, called the Distributed Transfer Function Method (DTFM), which produces the natural frequencies and mode shapes of the antenna. The combination of the 2-VP model and the DTFM provides an accurate prediction of the in-plane stress distribution and modes of vibration for the antenna.

vibrations↗
NASA NTRS1992

Bivariate extreme value distributions

In certain engineering applications, such as those occurring in the analyses of ascent structural loads for the Space Transportation System (STS), some of the load variables have a lower bound of zero. Thus, the need for practical models of bivariate extreme value probability distribution functions with lower limits was identified. We discuss the Gumbel models and present practical forms of bivariate extreme probability distributions of Weibull and Frechet types with two parameters. Bivariate extreme value probability distribution functions can be expressed in terms of the marginal extremel distributions and a 'dependence' function subject to certain analytical conditions. Properties of such bivariate extreme distributions, sums and differences of paired extremals, as well as the corresponding forms of conditional distributions, are discussed. Practical estimation techniques are also given.

Elshamy, M.↗
NASA NTRS2000

Finite Gyroradius Effects Observed in Pickup Oxygen Ions at Venus

On the dayside of Venus, the hot oxygen corona extending above the ionopause is the principal source of pickup oxygen ions. The ions are born here and picked up by the ionosheath plasma as it is deflected around the planet. These pickup ions have been observed by the Orbiter Plasma Analyzer (OPA) throughout the Pioneer Venus Orbiter (PVO) mission. They were observed over a region extending from their dayside source to great distances downstream (about 10 Venus radii), in the solar wind wake, as PVO passed through apoapsis. Finite gyroradius effects in the velocity distribution of the oxygen pickup ions are expected in the source region because the gyroradius is several times larger than the scale height of the hot oxygen source. Such effects are also expected in those regions of the ionosheath where the scale lengths of the magnetic field and the ambient plasma velocity field are less than the pickup ion gyroradius. While explicitly accounting for the spatial distribution of the hot oxygen source, an analytic expression for the pickup oxygen ion velocity distribution is developed to study how it is affected by finite gyroradii. The analysis demonstrates that as the gyroradius increases by factors of three to six above the hot oxygen scale height, the peak of the pickup oxygen ion flux distribution decreases 25 to 50% below the maximum allowed speed, which is twice the speed of the ambient plasma times the sine of the angle between the magnetic field and the flow velocity. The pickup oxygen ion flux distribution observed by OPA is shown to follow this behavior in the source region. It is also shown that this result is consistent with the pickup ion distributions observed in the wake, downstream of the source, where the flux peaks are usually well below the maximum allowed speed.

Hartle, Richard E.↗
NASA NTRS2016

Ball Bearing Analysis with the ORBIS Tool

Ball bearing design is critical to the success of aerospace mechanisms. Key bearing performance parameters, such as load capability, stiffness, torque, and life all depend on accurate determination of the internal load distribution. Hence, a good analytical bearing tool that provides both comprehensive capabilities and reliable results becomes a significant asset to the engineer. This paper introduces the ORBIS bearing tool. A discussion of key modeling assumptions and a technical overview is provided. Numerous validation studies and case studies using the ORBIS tool are presented. All results suggest the ORBIS code closely correlates to predictions on bearing internal load distributions, stiffness, deflection and stresses.

Halpin, Jacob D.↗
NASA NTRS1996

Phase Distribution Phenomena for Simulated Microgravity Conditions: Experimental Work

This report summarizes the work accomplished at Rensselaer to study phase distribution phenomenon under simulated microgravity conditions. Our group at Rensselaer has been able to develop sophisticated analytical models to predict phase distribution in two-phase flows under variety of conditions. These models are based on physics and data obtained from carefully controlled experiments that are being conducted here. These experiments also serve to verify the models developed.

Singhal, Maneesh↗
NASA NTRS1996

Phase Distribution Phenomena for Simulated Microgravity Conditions: Experimental Work

This report summarizes the work accomplished at Rensselaer to study phase distribution phenomenon under simulated microgravity conditions. Our group at Rensselaer has been able to develop sophisticated analytical models to predict phase distribution in two-phase flows under a variety of conditions. These models are based on physics and data obtained from carefully controlled experiments that are being conducted here. These experiments also serve to verify the models developed.

Singhal, Maneesh↗
NASA NTRS2022

Optimal Estimation Framework for Ocean Color Atmospheric Correction and Pixel-level Uncertainty Quantification

Ocean color remote sensing requires compensation for atmospheric scattering and absorption (aerosol, Rayleigh, and trace gases), referred to as atmospheric correction (AC). AC allows inference of parameters such as spectrally resolved remote sensing reflectance ( R rs )(λ) ; sr 1 ) at the ocean surface from the top-of-atmosphere reflectance. Often, the uncertainty of this process is not fully explored. Bayesian inference techniques provide a simultaneous AC and uncertainty assessment via a full posterior distribution of the relevant variables, given the prior distribution of those variables and the radiative transfer (RT) likelihood function. Given uncertainties in the algorithm inputs, the Bayesian framework enables better constraints on the AC process by using the complete spectral information compared to traditional approaches that use only a subset of bands for AC. This paper investigates a Bayesian inference research method (Optimal Estimation, OE) for ocean color AC by simultaneously retrieving atmospheric and ocean properties using all visible and near-infrared spectral bands. The OE algorithm analytically approximates the posterior distribution of parameters based on normality assumptions and provides a potentially viable operational algorithm with a reduced computational expense. We developed a Neural Network (NN) RT forward model look-up-table-based emulator to increase algorithm efficiency further and thus speed up the likelihood computations. We then applied the OE algorithm to synthetic data and observations from the MODerate resolution Imaging Spectroradiometer (MODIS) on NASA’s Aqua spacecraft. We compared the R rs )(λ) retrieval and its uncertainty estimates from the OE method with in-situ validation data from the SeaWiFS Bio-optical Archive and Storage System (SeaBASS) and Aerosol Robotic Network Ocean Color (AERONET-OC) datasets. The OE algorithm improved R rs )(λ) estimates relative to the NASA standard operational algorithm by improving all statistical metrics at 443, 555, and 667 nm. Unphysical negative R rs )(λ) , which often appear in complex water conditions, was reduced by a factor of 3. The OE-derived pixel-level R rs )(λ) uncertainty estimates were also assessed relative to in-situ data and were shown to have skill.

Atmospheric correction↗
DOE OSTI2021

Sensor enabled data-driven predictive analytics for modeling and control with high penetration of DERs in distribution systems

The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.

DER integration↗
NASA NTRS2009

Analytic Confusion Matrix Bounds for Fault Detection and Isolation Using a Sum-of-Squared- Residuals Approach

Given a system which can fail in 1 or n different ways, a fault detection and isolation (FDI) algorithm uses sensor data in order to determine which fault is the most likely to have occurred. The effectiveness of an FDI algorithm can be quantified by a confusion matrix, which i ndicates the probability that each fault is isolated given that each fault has occurred. Confusion matrices are often generated with simulation data, particularly for complex systems. In this paper we perform FDI using sums of squares of sensor residuals (SSRs). We assume that the sensor residuals are Gaussian, which gives the SSRs a chi-squared distribution. We then generate analytic lower and upper bounds on the confusion matrix elements. This allows for the generation of optimal sensor sets without numerical simulations. The confusion matrix bound s are verified with simulated aircraft engine data.

Simon, Dan↗
DOE OSTI2023

Energy I-Corps 2023: Distributed Wind Energy Toolkit

This presentation covers the purpose and scope of an Energy I-Corps project focused on refining a suite of analytical tools designed to support distributed wind deployment. These tools - the Distributed Generation Market Demand (dGen), Distributed Wind Tools Assessing Performance (TAP), and the Hybrid Optimization and Performance Platform (HOPP) - combine to provide users with the ability to simulate consumer purchasing behavior, accurately assess wind resource to better predict turbine performance, and effectively design and optimize hybrid systems that include distributed wind.

deployment↗
NASA NTRS1978

Gaussian step-pressure loading of rigid viscoplastic plates

The response of a thin, rigid viscoplastic plate subjected to a spatially axisymmetric Gaussian step pressure impulse loading was studied analytically. A Gaussian pressure distribution in excess of the collapse load was applied to the plate, held constant for a length of time, and then suddenly removed. The plate deforms with monotonically increasing deflections until the dynamic energy is completely dissipated in plastic work. The simply supported plate of uniform thickness obeys the von Mises yield criterion and a generalized constitutive equation for rigid viscoplastic materials. For the small deflection bending response of the plate, the governing system of equations is essentially nonlinear. Transverse shear stress is neglected in the yield condition and rotary inertia in the equations of dynamic equilibrium. A proportional loading technique, known to give excellent approximations of the exact solution for the uniform load case, was used to linearize the problem and to obtain the analytical solutions in the form of eigenvalue expansions. The effects of load concentration, of an order of magnitude change in the viscosity of the plate material, and of load duration were examined while holding the total impulse constant.

Hayduk, R. J.↗
NASA NTRS1994

Design and Implementation of a Distributed Version of the NASA Engine Performance Program

Distributed NEPP is a new version of the NASA Engine Performance Program that runs in parallel on a collection of Unix workstations connected through a network. The program is fault-tolerant, efficient, and shows significant speed-up in a multi-user, heterogeneous environment. This report describes the issues involved in designing distributed NEPP, the algorithms the program uses, and the performance distributed NEPP achieves. It develops an analytical model to predict and measure the performance of the simple distribution, multiple distribution, and fault-tolerant distribution algorithms that distributed NEPP incorporates. Finally, the appendices explain how to use distributed NEPP and document the organization of the program's source code.

Cours, Jeffrey T.↗
NASA NTRS1994

A new approach for determining fully empirical altimeter wind speed model functions

A statistical technique is developed for determining fully empirical model functions relating altimeter backscatter (sigma(sub 0)) measurements to near-surface neutral stability wind speed. By assuming that sigma(sub 0) varies monotonically and uniquely with wind speed, the method requires knowledge only of the separate, rather than joint distribution functions of sigma(sub 0) and wind speed. Analytic simplifications result from using a Weibull distribution to approximate the global ocean wind speed distribution; several different wind data sets are used to demonstrate the validity of the Weibull approximation. The technique has been applied to 1 year of Geosat data. Validation of the new and historical model functions using an independent buoy data set demonstrates that the present model function not only has small overall bias and root mean square (RMS) errors, but yields smaller systematic error trends with wind speed and pseudowave age than previously published models. The present analysis suggests that generally accuracte altimeter model functions can be derived without the use of colocated measurements, nor is additional significant wave height information measured by the altimeter necessary.

Freilich, M. H.↗