During 2014 and 2015, NASA's Neutron star Interior Composition Explorer (NICER) mission proceeded successfully through Phase C, Design and Development. An X-ray (0.2-12 keV) astrophysics payload destined for the International Space Station, NICER is manifested for launch in early 2017 on the Commercial Resupply Services SpaceX-11 flight. Its scientific objectives are to investigate the internal structure, dynamics, and energetics of neutron stars, the densest objects in the universe. During Phase C, flight components including optics, detectors, the optical bench, pointing actuators, electronics, and others were subjected to environmental testing and integrated to form the flight payload. A custom-built facility was used to co-align and integrate the X-ray "concentrator" optics and silicon-drift detectors. Ground calibration provided robust performance measures of the optical (at NASA's Goddard Space Flight Center) and detector (at the Massachusetts Institute of Technology) subsystems, while comprehensive functional tests prior to payload-level environmental testing met all instrument performance requirements. We describe here the implementation of NICER's major subsystems, summarize their performance and calibration, and outline the component-level testing that was successfully applied.
The emergence of model-based engineering, with Model-Based Systems Engineering (MBSE) leading the way, is transforming design and analysis methodologies. [7] The recognized benefits to systems development include moving from document-centric information systems and documentcentric project communication to a model-centric environment in which control of design changes in the life cycles is facilitated. In addition, a "single source of truth" about the system, that is up-to-date in all respects of the design, becomes the authoritative source of data and information about the system. This promotes consistency and efficiency in regard to integration of the system elements as the design emerges and thereby may further optimize the design. Therefore Reliability Engineers (REs) supporting NASA missions must be integrated into model-based engineering to ensure the outputs of their analyses are relevant and value-needed to the design, development, and operational processes for failure risks assessment and communication.Effective model-based Reliability must be analyst/ modeler-agnostic while still efficiently producing complete, accurate, and more consistent Reliability Artifacts (e.g., Failure Modes, Effects, and Criticality Analysis (FMECA), Limited Life Analysis (LLA), Fault Tree Analysis (FTA), Maintainability/Availability Analysis and Probabilistic Risk Assessment (PRA)) than traditional methods to allow engineers greater time for analysis, risk assessment, system behavior investigation (simulation), and risk-based project decisionmaking support. However, to achieve this, a robust and unified modeling process that includes considerations from all disciplines must be developed, implemented, and tested.In order to include Reliability, a discipline of Mission Assurance, in the development of this unified modeling process, an agency-sponsored team at Goddard Space Flight Center (GSFC) has completed the Reliability study of modeling and testing as part of the Model-Based Safety and Mission Assurance Initiative (MBSMAI). In this study, GSFC Reliability experts developed models of mission subsystems (EUROPA Propulsion, Wallops Flight Facility (WFF) Sounding Rocket Attitude Control System (ACS), & International Space Station (ISS) Evaporator) using a representative Commercial Off-The-Shelf tool, MADe (Maintenance Aware Design environment from PHM Technology-Siemens), and SysML/ MagicDraw (Systems Modeling Language (SysML) based tool from NoMagic) that was supported by Reliability plugins from Tietronix Software Inc. These models and their ability to support Reliability Analysis were then evaluated for accuracy, consistency, and efficiency to better connect and define MBSE/MBSMA modeling process best practices and modeling environment necessities that support traditional SMA analyses and milestone artifact generation so that failure risks can be assessed and communicated. Model-Based Engineering is found to be valid and useable forReliability Engineering for NASA Safety and Mission Assurance if adequate modeling processes and...
A reliability trend/growth analysis methodology for satellite systems is suggested. A satellite system usually consists of many satellites successively launched over many years, and its satellites typically belong to different satellite generations. This paper suggests an approach to reliability trend/growth data analysis for the satellite systems based on grouped data and the Power Law (Crow-AMSAA) Non- Homogeneous Poisson process model, for both one (time) and two (time and generation) variables. Based on the data specifics, the maximum likelihood estimates for the Power Law model parameters are obtained. In addition, the Cumulative Intensity Function (CIF) of a family of satellite systems was analyzed to assess its similarity to that of a repairable system. The suggested approaches are illustrated by a case study based on Tracking and Data Relay Satellite System (TDRSS) and Geostationary Operational Environmental Satellite (GOES) data.
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