Reliability analysis and prediction Moog model 17-200B mechanical feedback servoactuator GMSFC, NASA part no. 50M35008, rev. B
Reliability prediction and failure mode analyses for mechanical feedback servoactuator
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Reliability prediction and failure mode analyses for mechanical feedback servoactuator
The ground tracks and S190 swaths are presented of selected revolutions over areas containing earth resources experiment package (EREP) sites. The following eight EREP disciplines are shown: sensor performance evaluation, forestry, geology, hydrology, land use mapping, oceanography, pollution, and weather. Most of the data reported consists of passes over the continental United States.
Ground tracks with s190 swaths of selected revolutions as they pass over areas containing EREP sites are presented. Most of the data consists of passes over the continental United States; several are shown over Australia and South America. The S190 is a 6-channel high precision 70 mm camera facility.
The aeroheating characteristics of the X-38 Revision 3.1 lifting-body configuration have been experimentally examined in the Langley 20-inch Mach 6 Tunnel. Global surface heat transfer distributions, surface streamline patterns, and shock shapes were measured on a 0.0362-scale model of a proposed Space Station Crew Return Vehicle at Mach 6 in air. Parametric variations include angles-of-attack of 20 deg, 30 deg, and 40 deg; Reynolds numbers based on model length of 0.9 to 3.7 million; and body-flap deflections of O deg, 20 deg, 25 deg, and 30 deg. The effects of discrete roughness elements, which included trip height, location, size, and orientation, as well as multiple-trip parametrics, were investigated. This document is intended to serve as a quick release of preliminary data to the X-38 program; analysis is limited to observations of the experimental trends in order to expedite dissemination.
Measurements and predictions of the X-33 turbulent aeroheating environment have been performed at Mach 6, perfect-gas air conditions. The purpose of this investigation was to compare measured turbulent aeroheating levels on smooth models, models with discrete trips, and models with arrays of bowed panels (which simulate bowed thermal protections system tiles) with each other and with predictions from two Navier-Stokes codes, LAURA and GASP. The wind tunnel testing was conducted at free stream Reynolds numbers based on length of 1.8 x 10(exp 6) to 6.1 x 10(exp 6) on 0.0132 scale X-33 models at a = 40-deg. Turbulent flow was produced by the discrete trips and by the bowed panels at ill but the lowest Reynolds number, but turbulent flow on the smooth model was produced only at the highest Reynolds number. Turbulent aeroheating levels on each of the three model types were measured using global phosphor thermography and were found to agree to within .he estimated uncertainty (plus or minus 15%) of the experiment. Computations were performed at the wind tunnel free stream conditions using both codes. Turbulent aeroheating levels predicted using the LAURA code were generally 5%-10% lower than those from GASP, although both sets of predictions fell within the experimental accuracy of the wind tunnel data.
This document is a compendium of the WFF TOPEX Software Development Team's knowledge regarding Geophysical Data Record (GDR) Processing. It includes many elements of a requirements document, a software specification document, a software design document, and a user's manual. In the more technical sections, this document assumes the reader is familiar with TOPEX and instrument files.
This document provides instructions about how to configure the Eclipse IDE to build GMAT on Windows based PCs. The current instructions are preliminary; the Windows builds using Eclipse are currently a bit crude. These instructions are intended to give you enough information to get Eclipse setup to build wxWidgets based executables in general, and GMAT in particular.
After the April 20th explosion aboard the Deepwater Horizon drilling rig in the Gulf of Mexico, the world witnessed one of the worst oil spill catastrophes in global history. In an effort to mitigate the disaster, the U.S. government moved quickly to establish a unified command for responding to the spill. Some of the command's most immediate needs were to track the movement of the surface oil slick, establish a baseline measurement of pre-oil coastal ecosystem conditions, and assess potential air quality and water hazards related to the spill. To help address these needs and assist the Federal response to the disaster, NASA deployed several of its airborne and satellite research sensors to collect an unprecedented amount of remotely-sensed data over the Gulf of Mexico region. Although some of these data were shared with the public via the media, much of the NASA data on the disaster was not well known to the Gulf Coast community. The need existed to inform the general public about these datasets and help improve understanding about how NASA's science research was contributing to oil spill response and recovery. With its extensive experience conducting community-oriented remote sensing projects and close ties to organizations around Gulf of Mexico, the NASA DEVELOP National Program stood in a unique position to meet this need.
Housekeeping in the space industry? You may think the idea isn't technical enough for the shuttle program. Yet, eliminating Foreign Object Debris or FOD is an important goal for USA and NASA. The justification for this effort is based on data from the aeronautics industry. Experience has shown that if debris is not controlled, it may later cause a variety of in-flight issues. FOD can result in material damage, or make systems and equipment inoperable unsafe, or less efficient
This software is designed to predict large active mirror performance at various stages in the fabrication lifecycle of the mirror. It was developed for 1-meter class powered mirrors for astronomical purposes, but is extensible to other geometries. The package accepts finite element model (FEM) inputs and laboratory measured data for large optical-quality mirrors with active figure control. It computes phenomenological contributions to the surface figure error using several built-in optimization techniques. These phenomena include stresses induced in the mirror by the manufacturing process and the support structure, the test procedure, high spatial frequency errors introduced by the polishing process, and other process-dependent deleterious effects due to light-weighting of the mirror. Then, depending on the maturity of the mirror, it either predicts the best surface figure error that the mirror will attain, or it verifies that the requirements for the error sources have been met once the best surface figure error has been measured. The unique feature of this software is that it ties together physical phenomenology with wavefront sensing and control techniques and various optimization methods including convex optimization, Kalman filtering, and quadratic programming to both generate predictive models and to do requirements verification. This software combines three distinct disciplines: wavefront control, predictive models based on FEM, and requirements verification using measured data in a robust, reusable code that is applicable to any large optics for ground and space telescopes. The software also includes state-of-the-art wavefront control algorithms that allow closed-loop performance to be computed. It allows for quantitative trade studies to be performed for optical systems engineering, including computing the best surface figure error under various testing and operating conditions. After the mirror manufacturing process and testing have been completed, the software package can be used to verify that the underlying requirements have been met.
JSC 66320, Revision A, Optical Property Requirements for Glasses, Ceramics, and Plastics in Spacecraft Window Systems, lists several quantitative requirements that spacecraft windowpanes must meet. Recently, we were asked to establish a capability at the Kennedy Space Center to perform these measurements on category B plastic panes, i.e., plastic panes that could be used on a spacecraft for long-focal-length photography and piloting. Two of the criteria, normal wavefront and 30-degree wavefront attributes, can be measured with existing equipment and processes (see NASA TM NESC-RP-14-00951, April 2016) and are not discussed in this document. However, the other six criteria-haze, wedge angle, birefringence, reflectance, transmittance, and color balance-required substantial development and are the subject of this document. In this document, we do not discuss the rationale behind the requirements, but we did engage in discussions with the authors of JSC 66320 in order to better understand the requirements and the verifications being imposed on windows and their testing. Accordingly, this document presents our best understanding of the requested requirements and verifications. We also present our methodology for performing each of the six measurements, along with applicable mathematics and a description, with photos, of the hardware used. In addition, we supply the results of a test on a low-quality in-house plastic window as an example of the system operation. Only requirements that can be met by acceptance test and analysis, as opposed to optical inspection, are considered in this document.
This Annex to NASA-STD-8719.24 is a template and starting point for developing project range safety requirements. This Annex provides technical safety requirements for unmanned orbital and unmanned deep space payloads that fly onboard Expendable Launch Vehicles (ELVs).
This presentation discusses the JSC 63322 changes and updates to accompanying OCAD.
This document describes data product formats and content that are produced primarily by the TESS Science Processing Operations Center (SPOC) at NASA Ames Research Center for archival to the Mikulski Archive for Space Telescopes (MAST) .
A group of encounter sets is evaluated as a standard for defining and refining both performance-based and functional-based terminal area MOPS requirements. DAIDALUS-alerting is used together with a variety of sensor configurations: (1) ADS-B level surveillance, (2) TCAS II, (3) ground-based RADAR with three different sets of error parameters.