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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Modeling of Rolling Element Bearing Mechanics: Computer Program Updates

The Rolling Element Bearing Analysis System (REBANS) extends the capability available with traditional quasi-static bearing analysis programs by including the effects of bearing race and support flexibility. This tool was developed under contract for NASA-MSFC. The initial version delivered at the close of the contract contained several errors and exhibited numerous convergence difficulties. The program has been modified in-house at MSFC to correct the errors and greatly improve the convergence. The modifications consist of significant changes in the problem formulation and nonlinear convergence procedures. The original approach utilized sequential convergence for nested loops to achieve final convergence. This approach proved to be seriously deficient in robustness. Convergence was more the exception than the rule. The approach was changed to iterate all variables simultaneously. This approach has the advantage of using knowledge of the effect of each variable on each other variable (via the system Jacobian) when determining the incremental changes. This method has proved to be quite robust in its convergence. This technical memorandum documents the changes required for the original Theoretical Manual and User's Manual due to the new approach.

Ryan, S. G.↗
NASA NTRS1997

TBIEM3D: A Computer Program for Predicting Ducted Fan Engine Noise

This document describes the usage of the ducted fan noise prediction program TBIEM3D (Thin duct - Boundary Integral Equation Method - 3 Dimensional). A scattering approach is adopted in which the acoustic pressure field is split into known incident and unknown scattered parts. The scattering of fan-generated noise by a finite length circular cylinder in a uniform flow field is considered. The fan noise is modeled by a collection of spinning point thrust dipoles. The program, based on a Boundary Integral Equation Method (BIEM), calculates circumferential modal coefficients of the acoustic pressure at user-specified field locations. The duct interior can be of the hard wall type or lined. The duct liner is axisymmetric, locally reactive, and can be uniform or axially segmented. TBIEM3D is written in the FORTRAN programming language. Input to TBIEM3D is minimal and consists of geometric and kinematic parameters. Discretization and numerical parameters are determined automatically by the code. Several examples are presented to demonstrate TBIEM3D capabilities.

Dunn, M. H.↗
NASA NTRS2004

WAMI: A Menu-Driven Computer Program for the Estimation of Weight and Moments of Inertia of Earth-to-Orbit Transports

A program, entitled Weights, Areas, and Mass Properties (or WAMI) is centered around an array of menus that contain constants that can be used in various mass estimating relationships for the ultimate purpose of obtaining the mass properties of Earth-to-Orbit Transports. The current Shuttle mass property data was relied upon heavily for baseline equation constant values from which other options were derived.

MacConochie, Ian O.↗
NASA NTRS1990

EZDESIT: A Computer Program for Structural Element Sizing and Vehicle Weight Prediction

A method is presented for formulating stiffness terms and thermal coefficients of fiber reinforced composite, stiffened panels for input to finite element analysis (FEA). The method is robust enough to handle panels with general cross sectional shapes, including those which are unsymmetric and/or unbalanced. New thermal coefficients are introduced to quantify panel response from through-the-thickness temperature gradients. Equations are defined for stiffness, thermal expansion, and thermal bending that consider the full complement of membrane, bending, membrane-bending coupling, and transverse shear behavior. A technique of implementing this capability with a single plane of shell finite elements using the MSC/NASTRAN™ FEA program is revealed. Finally, an example of a composite, hat-stiffened panel is included to demonstrate errors that occur when an unsymmetric panel is symmetrically formulated as traditionally done. These erroneous values and the correct ones produced from the presented method are listed for the panel's stiffness matrices, thermal expansion and bending vectors, and the forces and moments that are thermally induced from in-plane and through-the-thickness temperature gradients.

Jeffrey A Cerro↗
NASA NTRS2014

Field Programmable Gate Array Apparatus, Method, and Computer Program

An apparatus is provided that includes a plurality of modules, a plurality of memory banks, and a multiplexor. Each module includes at least one agent that interfaces between a module and a memory bank. Each memory bank includes an arbiter that interfaces between the at least one agent of each module and the memory bank. The multiplexor is configured to assign data paths between the at least one agent of each module and a corresponding arbiter of each memory bank based on the assigned data path. The at least one agent of each module is configured to read data from the corresponding arbiter of the memory bank or write modified data to the corresponding arbiter of the memory bank.

Morfopoulos, Arin C.↗
NASA NTRS1963

Lunar Flight Study Series: Volume 8. Earth-Moon Transit Studies Based on Ephemeris Data and Using Best Available Computer Program. Part 3: Analysis of Some Lunar Landing Site Problems Utilizing Two Fundamental Principles

This report presents two fundamental properties of lunar trajectories and makes use of these properties to solve various lunar landing site problems. Not only are various problems treated and solved but the properties and methods are established for use in the solution of other problems. This report presents an analysis of lunar landing site problems utilizing the direct mission mode as well as the orbital mission mode. A particular landing site is then specified and different flight profiles are analyzed for getting an exploration vehicle to that landing site. Rendezvous compatible lunar orbits for various stay-times at the landing site are treated. Launch opportunities are discussed for establishing rendezvous compatible lunar orbits without powered plane changes. Then, the minimum required plane changes for rendezvous in the lunar orbit are discussed for launching from earth on any day. On days that afford rendezvous compatible opportunities, there are no powered plane change requirements in the operations from launch at AMR through the rendezvous in lunar orbit, after the stay at the lunar site.

Tucker, W. B.↗
DOE OSTI2020

Systems, methods and computer program products for self-tuning sensor data processing

Systems and methods are disclosed that include tools that utilize Dynamic Detector Tuning (DDT) software that identifies near-optimal parameter settings for each sensor using a neuro-dynamic programming (reinforcement learning) paradigm. DDT adapts parameter values to the current state of the environment by leveraging cooperation within a neighborhood of sensors. The key metric that guides the dynamic tuning is consistency of each sensor with its nearest neighbors: parameters are automatically adjusted on a per station basis to be more or less sensitive to produce consistent agreement of detections in its neighborhood. The DDT algorithm adapts in near real-time to changing conditions in an attempt to automatically self-tune a signal detector to identify (detect) only signals from events of interest. The disclosed systems and methods reduce the number of missed legitimate detections and the number of false detections, resulting in improved event detection.

Draelos, Timothy J.↗
DOE OSTI2024

Computer program product for classifying materials

Systems and methods for classifying materials utilizing one or more sensor systems, which may implement a machine learning system in order to identify or classify each of the materials, which may then be sorted into separate groups based on such an identification or classification. The machine learning system may utilize a neural network, and be previously trained to recognize and classify certain types of materials.

Kumar, Nalin↗