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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Retrieval of Spatio-temporal Distributions of Particle Parameters from Multiwavelength Lidar Measurements Using the Linear Estimation Technique and Comparison with AERONET

The results of the application of the linear estimation technique to multiwavelength Raman lidar measurements performed during the summer of 2011 in Greenbelt, MD, USA, are presented. We demonstrate that multiwavelength lidars are capable not only of providing vertical profiles of particle properties but also of revealing the spatio-temporal evolution of aerosol features. The nighttime 3 Beta + 1 alpha lidar measurements on 21 and 22 July were inverted to spatio-temporal distributions of particle microphysical parameters, such as volume, number density, effective radius and the complex refractive index. The particle volume and number density show strong variation during the night, while the effective radius remains approximately constant. The real part of the refractive index demonstrates a slight decreasing tendency in a region of enhanced extinction coefficient. The linear estimation retrievals are stable and provide time series of particle parameters as a function of height at 4 min resolution. AERONET observations are compared with multiwavelength lidar retrievals showing good agreement.

AERONET↗
NASA NTRS2015

Linear Covariance Analysis For Proximity Operations Around Asteroid 2008 EV5

The NASA initiative to collect an asteroid, the Asteroid Robotic Redirect Mission (ARRM), is currently investigating the option of retrieving a boulder from an asteroid, demonstrating planetary defense with an enhanced gravity tractor technique, and returning it to a lunar orbit. Techniques for accomplishing this are being investigated by the Satellite Servicing Capabilities Office (SSCO) at NASA GSFC in collaboration with JPL, NASA JSC, LaRC, and Draper Laboratory, Inc. Two critical phases of the mission are the descent to the boulder and the Enhanced Gravity Tractor demonstration. A linear covariance analysis is done for these phases to assess the feasibility of these concepts with the proposed design of the sensor and actuator suite of the Asteroid Redirect Vehicle (ARV). The sensor suite for this analysis includes a wide field of view camera, LiDAR, and an IMU. The proposed asteroid of interest is currently the C-type asteroid 2008 EV5, a carbonaceous chondrite that is of high interest to the scientific community. This paper presents an overview of the linear covariance analysis techniques and simulation tool, provides sensor and actuator models, and addresses the feasibility of descending to the surface of the asteroid within allocated requirements as well as the possibility of maintaining a halo orbit to demonstrate the Enhanced Gravity Tractor technique.

Navigation↗
NASA NTRS1994

Linear Algorithms for Worst Case Identification in H infinity with Applications to Flexible Structures

This paper is concerned with linear algorithms for identification in which have been studied in [9]. It is shown that the two different linear algorithms in [9] can be unified into a single one which can be further extended to nonuniformly spaced frequency response samples with exponential convergence for the noise free case. Improved upper bounds for the corresponding identification errors are derived. Applications to the identification of lightly damped systems such as flexible structures are also considered.

linear↗
NASA NTRSDate not supplied

Towards Formalization of Advanced Linear Algebra with Applications to Dynamical Systems using PVS

Linear Algebra is essential for numerous aerospace problems of interest. Formal reasoning about hybrid systems that contain variables modeled by differential equations rely on concepts from Linear Algebra such as eigenvalues, matrix decompositions, and matrix valued functions. For example, the long-term dynamics of a system of differential equations depend on the stability/instability of its equilibrium points, which often reduces to an eigenvalue problem. This talk will embark on a quest to formalize theorems and results about eigenvalues and eigenvectors using PVS. We shall start our journey with 2 x 2 complex matrices, where we will apply our PVS code to a simple example of a dynamical system. Since it can be difficult or impossible to give simple expressions of eigenvalues for larger matrices (i.e. 5 x 5 or higher), we then move towards specifying the power method for verified computation of eigenvalue approximations in PVS. This effort requires development of multivariate complex arithmetic. At the end of the day, having such additions to the PVS NASA libraries will help move towards the use of formal methods to verify concepts of control theory and system level verification.

Linear Algebra↗
NASA NTRSDate not supplied

Linear Regression Model for Predictive Service Provider Selection

The increasing number of satellites in orbit has led to a growing reliance on third-party service providers for data transfer between Earth and space. Traditional approaches to managing satellite communications require human intervention, which becomes more burdensome with the escalating number of satellites. This research addresses the need for an efficient and automated system to optimize service provider selection for NASA space communication. Previous research has utilized human-operated approaches for service provider management. Our study fills a gap by developing a cognitive algorithm that automates and optimizes the selection process based on various parameters, such as data volume, priority, quality of service and cost. This novel solution reduces user burden, facilitates service management, and contributes to the development of cognitive spaceflight missions, ultimately supporting NASA’s research into Cognitive Communications technology. The algorithm design consists of three major steps: modeling data, developing a Link Selection Algorithm (LSA) based on a grading system, and applying machine learning using linear regression. The LSA evaluates providers based on user-defined constraints, considering factors such as delivery time, cost, and quality of service. We define a suitability metric which allows our algorithm to make a recommendation to a user regarding which commercial service providers to select. The addition of Linear Regression predicts the future suitability value. Our main findings demonstrate that the resulting algorithm can autonomously manage connections between satellites and providers, maximizing communication channel efficiency. This research has significant implications, as it not only addresses a pressing issue in satellite communication management but also advances the field of cognitive spaceflight missions.

Linear regression↗
NASA NTRSDate not supplied

Evaluating Delta-V Dispersions Using Linear Covariance Techniques with Applications to Rendezvous and Docking

One of the attractive advantages of using linear covariance analysis (LinCov) is that it can accurately produce both navigation errors and trajectory dispersions in a fraction of the time comparable to the standard Monte Carlo analysis approach that is traditionally adopted. It also has the capability of generating delta-v dispersions which is perhaps the most influential performance metric since many aspects of a mission design revolve around the anticipated propellant usage. Accurately capturing this key performance criteria using linear covariance techniques has several subtle caveats raising reasonable doubts and a cautious sense of skepticism. This paper outlines multiple approaches of modeling delta-v usage in LinCov, highlights their limitations and advantages, and ultimately compares their corresponding results to the actual Monte Carlo performance. The theory is also extended to reliably account for an arbitrary thruster configuration and the resultant propellant consumptions due to both translational burns and attitude maneuvers. This provides near instant insight into the impacts of thruster layout design and different vehicle mass properties. These derived techniques are applied and verified using an NRHO rendezvous and docking scenario consistent with upcoming NASA Artemis missions for Orion.

Linear Covariance Analysis↗
NASA NTRS1966

Compact actuator converts rotary to linear motion

Compact motor mounted on a stationary base converts rotary to linear motion. The motor rotates a gear train assembly so that the end of an arm attached to the assembly moves in a linear path.

Ford, A. G.↗
NASA NTRS1969

Linear voltage-to-frequency converter

Voltage-to-frequency converter, with ultra-high input impedance and linear response, is used in analog to digital data conversion systems. Voltage-to-current converter, using MOSFET devices and a multivibrator, has ultra-linear voltage-to-frequency characteristics. It replaces voltage sensitive magnetic-core oscillators.

Lokerson, D. C.↗
NASA NTRS1969

Electrothermal linear actuator

Converting electric power into powerful linear thrust without generation of magnetic fields is accomplished with an electrothermal linear actuator. When treated by an energized filament, a stack of bimetallic washers expands and drives the end of the shaft upward.

Derr, L. J.↗
NASA NTRS1969

On the linear smoothing problem.

Smoothing problem for linear discrete time system, converting problem to special case of standard linear filtering problem

Willman, W. W.↗