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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

NIRSS Upgrades: Final Report

This year we were able to further the NIRSS program by re-writing the data ingest and display code from LabVIEW to C++ and Java. This was leveraged by a University of Colorado Computer Science Department Senior Project. The upgrade made the display more portable and upgradeable. Comparisons with research aircraft flights conducted during AIRS-2 were also done and demonstrate reasonable skill in determining cloud altitudes and liquid water distribution. Improvements can still be made to the cloud and liquid logic. The icing hazard index was not evaluated here since that represents work in progress and needs to be made compatible with the new CIP-Severity algorithm. CIP is the Current Icing Potential product that uses a combination decision tree/fuzzy logic algorithm to combine numerical weather model output with operational sensor data (NEXRAD, GOES, METARs and voice pilot reports) to produce an hourly icing diagnosis across the CONUS. The new severity algorithm seeks to diagnose liquid water production through rising, cooling air, and depletion by ice processes. The information used by CIP is very different from that ingested by NIRSS but some common ground does exist. Additionally, the role of NIRSS and the information it both needs and provides needs to be determined in context of the Next Generation Air Traffic System (NGATS). The Weather Integrated Products Team has a plan for an Initial Operating Capability (IOC) to take place in 2012. NIRSS is not explicitly a part of that IOC but should be considered as a follow-on as part of the development path to a 2025 full capability.

Politovich, Marcia K.↗
NASA NTRS1998

Numerical Roll Reversal Predictor Corrector Aerocapture and Precision Landing Guidance Algorithms for the Mars Surveyor Program 2001 Missions

This paper describes the development and evaluation of a numerical roll reversal predictor-corrector guidance algorithm for the atmospheric flight portion of the Mars Surveyor Program 2001 Orbiter and Lander missions. The Lander mission utilizes direct entry and has a demanding requirement to deploy its parachute within 10 km of the target deployment point. The Orbiter mission utilizes aerocapture to achieve a precise captured orbit with a single atmospheric pass. Detailed descriptions of these predictor-corrector algorithms are given. Also, results of three and six degree-of-freedom Monte Carlo simulations which include navigation, aerodynamics, mass properties and atmospheric density uncertainties are presented.

Powell, Richard W.↗
NASA NTRS1978

On improving the iterative convergence properties of an implicit approximate-factorization finite difference algorithm

The iterative convergence properties of an approximate-factorization implicit finite-difference algorithm are analyzed both theoretically and numerically. Modifications to the base algorithm were made to remove the inconsistency in the original implementation of artificial dissipation. In this way, the steady-state solution became independent of the time-step, and much larger time-steps can be used stably. To accelerate the iterative convergence, large time-steps and a cyclic sequence of time-steps were used. For a model transonic flow problem governed by the Euler equations, convergence was achieved with 10 times fewer time-steps using the modified differencing scheme. A particular form of instability due to variable coefficients is also analyzed.

Desideri, J. A.↗
NASA NTRS1989

Group implicit concurrent algorithms in nonlinear structural dynamics

During the 70's and 80's, considerable effort was devoted to developing efficient and reliable time stepping procedures for transient structural analysis. Mathematically, the equations governing this type of problems are generally stiff, i.e., they exhibit a wide spectrum in the linear range. The algorithms best suited to this type of applications are those which accurately integrate the low frequency content of the response without necessitating the resolution of the high frequency modes. This means that the algorithms must be unconditionally stable, which in turn rules out explicit integration. The most exciting possibility in the algorithms development area in recent years has been the advent of parallel computers with multiprocessing capabilities. So, this work is mainly concerned with the development of parallel algorithms in the area of structural dynamics. A primary objective is to devise unconditionally stable and accurate time stepping procedures which lend themselves to an efficient implementation in concurrent machines. Some features of the new computer architecture are summarized. A brief survey of current efforts in the area is presented. A new class of concurrent procedures, or Group Implicit algorithms is introduced and analyzed. The numerical simulation shows that GI algorithms hold considerable promise for application in coarse grain as well as medium grain parallel computers.

Ortiz, M.↗
NASA NTRS2004

Pre-Hardware Optimization and Implementation Of Fast Optics Closed Control Loop Algorithms

One of the main heritage tools used in scientific and engineering data spectrum analysis is the Fourier Integral Transform and its high performance digital equivalent - the Fast Fourier Transform (FFT). The FFT is particularly useful in two-dimensional (2-D) image processing (FFT2) within optical systems control. However, timing constraints of a fast optics closed control loop would require a supercomputer to run the software implementation of the FFT2 and its inverse, as well as other image processing representative algorithm, such as numerical image folding and fringe feature extraction. A laboratory supercomputer is not always available even for ground operations and is not feasible for a night project. However, the computationally intensive algorithms still warrant alternative implementation using reconfigurable computing technologies (RC) such as Digital Signal Processors (DSP) and Field Programmable Gate Arrays (FPGA), which provide low cost compact super-computing capabilities. We present a new RC hardware implementation and utilization architecture that significantly reduces the computational complexity of a few basic image-processing algorithm, such as FFT2, image folding and phase diversity for the NASA Solar Viewing Interferometer Prototype (SVIP) using a cluster of DSPs and FPGAs. The DSP cluster utilization architecture also assures avoidance of a single point of failure, while using commercially available hardware. This, combined with the control algorithms pre-hardware optimization, or the first time allows construction of image-based 800 Hertz (Hz) optics closed control loops on-board a spacecraft, based on the SVIP ground instrument. That spacecraft is the proposed Earth Atmosphere Solar Occultation Imager (EASI) to study greenhouse gases CO2, C2H, H2O, O3, O2, N2O from Lagrange-2 point in space. This paper provides an advanced insight into a new type of science capabilities for future space exploration missions based on on-board image processing for control and for robotics missions using vision sensors. It presents a top-level description of technologies required for the design and construction of SVIP and EASI and to advance the spatial-spectral imaging and large-scale space interferometry science and engineering.

Kizhner, Semion↗
NASA NTRS1989

Numerical results on relations between fundamental constants using a new algorithm

An efficient algorithm is described for finding whether or not certain fundamental mathematical constants satisfy simple algebraic polynomials. The algorithm, which finds whether an integer relation exists for a vector of real numbers, or else establishes bounds within which no relation can exist. The algorithm is implemented on high-speed computers, using multiprecision arithmetic. Numerical results are summarized, and other possible applications for the algorithm are discussed.

Bailey, David H.↗
NASA NTRS2019

Approach for Propagating Radiometric Data Uncertainties Through NASA Ocean Color Algorithms

Spectroradiometric satellite observations of the ocean are commonly referred to as “ocean color” remote sensing. NASA has continuously collected, processed, and distributed ocean color datasets since the launch of the Sea-viewing Wide-field-of-view Sensor (SeaWiFS) in 1997. While numerous ocean color algorithms have been developed in the past two decades that derive geophysical data products from sensor-observed radiometry, few papers have clearly demonstrated how to estimate measurement uncertainty in derived data products. As the uptake of ocean color data products continues to grow with the launch of new and advanced sensors, it is critical that pixel-by-pixel data product uncertainties are estimated during routine data processing. Knowledge of uncertainties can be used when studying long-term climate records, or to assist in the development and performance appraisal of bio-optical algorithms. In this method paper we provide a comprehensive overview of how to formulate first-order first-moment (FOFM) calculus for propagating radiometric uncertainties through a selection of bio-optical models. We demonstrate FOFM uncertainty formulations for the following NASA ocean color data products: chlorophyll-a pigment concentration (Chl), the diffuse attenuation coefficient at 490 nm (K(sub d,490)), particulate organic carbon (POC), normalized fluorescent line height (nflh), and inherent optical properties (IOPs). Using a quality-controlled in situ hyperspectral remote sensing reflectance (R(sub rs,i)) dataset, we show how computationally inexpensive, yet algebraically complex, FOFM calculations may be evaluated for correctness using the more computationally expensive Monte Carlo approach. We compare bio-optical product uncertainties derived using our test R(sub rs) dataset assuming spectrally-flat, uncorrelated relative uncertainties of 1, 5, and 10%. We also consider spectrally dependent, uncorrelated relative uncertainties in R(sub rs). The importance of considering spectral covariances in R(sub rs), where practicable, in the FOFM methodology is highlighted with an example SeaWiFS image. We also present a brief case study of two POC algorithms to illustrate how FOFM formulations may be used to construct measurement uncertainty budgets for ecologically-relevant data products. Such knowledge, even if rudimentary, may provide useful information to end-users when selecting data products or when developing their own algorithms.

Bio-optics↗
DOE OSTI2025

Engineering Privacy at the Edge: A Practical Guide to Differential Privacy in System Architectures

The rapid expansion of distributed and edge computing platforms—spanning autonomous vehicles, IoT sensors, and healthcare monitors—has heightened concerns about data privacy. Differential Privacy (DP) offers a rigorous mathematical framework to protect sensitive information while retaining analytical utility. This tutorial introduces the foundations of DP for both numerical and categorical datasets and extends the discussion to correlation-aware techniques tailored for structured and high-dimensional data. Hands-on demonstrations will begin with the PETINA (Privacy prEservaTIoN Algorithms) package for numerical data and continue with MIC-DP (Maximum Information Correlated Differential Privacy) for tabular data. Designed for researchers and practitioners in secure systems, embedded architectures, and AI accelerators, the tutorial emphasizes practical and scalable methods for integrating DP into real-world system designs.

Kotevska, Olivera [ORNL] (ORCID:0000000316772243)↗
NASA NTRS1992

Asymptotic integration algorithms for first-order ODEs with application to viscoplasticity

When constructing an algorithm for the numerical integration of a differential equation, one must first convert the known ordinary differential equation (ODE), which is defined at a point, into an ordinary difference equation (O(delta)E), which is defined over an interval. Asymptotic, generalized, midpoint, and trapezoidal, O(delta)E algorithms are derived for a nonlinear first order ODE written in the form of a linear ODE. The asymptotic forward (typically underdamped) and backward (typically overdamped) integrators bound these midpoint and trapezoidal integrators, which tend to cancel out unwanted numerical damping by averaging, in some sense, the forward and backward integrations. Viscoplasticity presents itself as a system of nonlinear, coupled first-ordered ODE's that are mathematically stiff, and therefore, difficult to numerically integrate. They are an excellent application for the asymptotic integrators. Considering a general viscoplastic structure, it is demonstrated that one can either integrate the viscoplastic stresses or their associated eigenstrains.

Freed, Alan D.↗
NASA NTRS1987

Theoretical analysis of the electrical aspects of the basic electro-impulse problem in aircraft de-icing applications

A method of modelling a system consisting of a cylindrical coil with its axis perpendicular to a metal plate of finite thickness, and a simple electrical circuit for producing a transient current in the coil, is discussed in the context of using such a system for de-icing aircraft surfaces. A transmission line model of the coil and metal plate is developed as the heart of the system model. It is shown that this transmission model is central to calculation of the coil impedance, the coil current, the magnetic fields established on the surfaces of the metal plate, and the resultant total force between the coil and the plate. FORTRAN algorithms were developed for numerical calculation of each of these quantities, and the algorithms were applied to an experimental prototype system in which these quantities had been measured. Good agreement is seen to exist between the predicted and measured results.

Henderson, Robert A.↗
NASA NTRS1991

Distributed Minimal Residual (DMR) method for acceleration of iterative algorithms

A new method for enhancing the convergence rate of iterative algorithms for the numerical integration of systems of partial differential equations was developed. It is termed the Distributed Minimal Residual (DMR) method and it is based on general Krylov subspace methods. The DMR method differs from the Krylov subspace methods by the fact that the iterative acceleration factors are different from equation to equation in the system. At the same time, the DMR method can be viewed as an incomplete Newton iteration method. The DMR method was applied to Euler equations of gas dynamics and incompressible Navier-Stokes equations. All numerical test cases were obtained using either explicit four stage Runge-Kutta or Euler implicit time integration. The formulation for the DMR method is general in nature and can be applied to explicit and implicit iterative algorithms for arbitrary systems of partial differential equations.

Lee, Seungsoo↗
NASA NTRSDate not supplied

Performance Analysis of SmallSat Aerocapture at Venus

Aerocapture is a method of spacecraft orbital insertion that has the potential to provide mass savings as compared to aerobraking. In particular, aerocapture at Venus is desirable due to high atmospheric density and potential for science return. While promising, accurate orbital insertion by means of aerocapture requires an active guidance, navigation, and control architecture. This paper documents the initial assessment of the performance of two guidance algorithms, a generalized numerical predictor corrector and the Fully-Numeric Predictor- corrector for Aerocapture Guidance, applied to smallsat aerocapture at Venus using two different simulation environments with equivalent simulation inputs. Nominal trajectory performance is assessed. In addition, Monte Carlo analysis is performed to compare each guidance algorithm’s performance under uncertainty.

aerocapture↗
NASA NTRS1994

Numerical Simulation of the Instability of an Inviscid Liquid Jet in a Coflowing Compressible Airstream

The nonlinear interfacial instability of a liquid jet in a coflowing compressible airstream is studied numerically. A high-resolution scheme which has second-order accuracy in space and time is coupled with a Lagrangian marker particle algorithm to visualize the large-scale motion of the interfaces in compressible flow. A numerical algorithm based on an approximate equation of state of a compressible liquid is developed to allow this two-fluid system to be governed by the nonlinear unsteady Euler equations in conservative form. The initial growth of small disturbances given by the simulations agrees well with linear theory. The process of jet disruption in compressible flow is demonstrated to consist of the formation of liquid spikes, interweaving of the gas and liquid and stretching and detachment of the liquid main center core.

Li, H. -S.↗
NASA NTRSDate not supplied

Performance Analysis of SmallSat Aerocapture at Venus

Aerocapture is a method of spacecraft orbital insertion that has the potential to provide mass savings as compared to aerobraking. In particular, aerocapture at Venus is desirable due to high atmospheric density and potential for science return. While promising, accurate orbital insertion by means of aerocapture requires an active guidance, navigation, and control architecture. This paper documents the initial assessment of the performance of two guidance algorithms, a generalized numerical predictor corrector and the Fully-Numeric Predictor-corrector for Aerocapture Guidance, applied to smallsat aerocapture at Venus using two different simulation environments with equivalent simulation inputs. Nominal trajectory performance is assessed. In addition, Monte Carlo analysis is performed to compare each guidance algorithm’s performance under uncertainty.

aerocapture↗
NASA NTRS1986

High-accuracy computation of Delta V magnitude probability densities - Preliminary remarks

This paper describes an algorithm for the high accuracy computation of some statistical quantities of the magnitude of a random trajectory correction maneuver (TCM). The trajectory correction velocity increment Delta V is assumed to be a three-component random vector with each component being a normally distributed random scalar having a possibly nonzero mean. Knowledge of the statitiscal properties of the magnitude of a random TCM is important in the planning and execution of maneuver strategies for deep-space missions such as Galileo. The current algorithm involves the numerical integration of a set of differential equations. This approach allows the computation of density functions for specific Delta V magnitude distributions to high accuracy without first having to generate large numbers of random samples. Possible applications of the algorithm to maneuver planning, planetary quarantine evaluation, and guidance success probability calculations are described.

Chadwick, C.↗
NASA NTRS1991

Advanced rotorcraft control using parameter optimization

A reliable algorithm for the evaluation of a quadratic performance index and its gradients with respect to the controller design parameters is presented. The algorithm is part of a design algorithm for an optimal linear dynamic output feedback controller that minimizes a finite time quadratic performance index. The numerical scheme is particularly robust when it is applied to the control law synthesis for systems with densely packed modes and where there is a high likelihood of encountering degeneracies in the closed loop eigensystem. This approach through the use of a accurate Pade series approximation does not require the closed loop system matrix to be diagonalizable. The algorithm has been included in a control design package for optimal robust low order controllers. Usefulness of the proposed numerical algorithm has been demonstrated using numerous practical design cases where degeneracies occur frequently in the closed loop system under an arbitrary controller design initialization and during the numerical search.

Vansteenwyk, Brett↗