Semi-Markov adjunction to the Computer-Aided Markov Evaluator (CAME)

The rule-based Computer-Aided Markov Evaluator (CAME) program was expanded in its ability to incorporate the effect of fault-handling processes into the construction of a reliability model. The fault-handling processes are modeled as semi-Markov events and CAME constructs and appropriate semi-Markov model. To solve the model, the program outputs it in a form which can be directly solved with the Semi-Markov Unreliability Range Evaluator (SURE) program. As a means of evaluating the alterations made to the CAME program, the program is used to model the reliability of portions of the Integrated Airframe/Propulsion Control System Architecture (IAPSA 2) reference configuration. The reliability predictions are compared with a previous analysis. The results bear out the feasibility of utilizing CAME to generate appropriate semi-Markov models to model fault-handling processes

Advanced information processing system for advanced launch system: Avionics architecture synthesis

The Advanced Information Processing System (AIPS) is a fault-tolerant distributed computer system architecture that was developed to meet the real time computational needs of advanced aerospace vehicles. One such vehicle is the Advanced Launch System (ALS) being developed jointly by NASA and the Department of Defense to launch heavy payloads into low earth orbit at one tenth the cost (per pound of payload) of the current launch vehicles. An avionics architecture that utilizes the AIPS hardware and software building blocks was synthesized for ALS. The AIPS for ALS architecture synthesis process starting with the ALS mission requirements and ending with an analysis of the candidate ALS avionics architecture is described

Panel 6 : Vaccines

Objective. To review the literature on progress regarding (1) effectiveness of vaccines for prevention of otitis media (OM) and (2) development of vaccine antigens for OM bacterial and viral pathogens. Data Sources. PubMed database of the National Library of Science. Review Methods. We performed literature searches in PubMed for OM pathogens and candidate vaccine antigens, and we restricted the searches to articles in English that were published between July 2011 and June 2015. Panel members reviewed literature in their area of expertise. Conclusions. Pneumococcal conjugate vaccines (PCVs) are somewhat effective for the prevention of pneumococcal OM, recurrent OM, OM visits, and tympanostomy tube insertions. Widespread use of PCVs has been associated with shifts in pneumococcal serotypes and bacterial pathogens associated with OM, diminishing PCV effectiveness against AOM. The 10-valent pneumococcal vaccine containing Haemophilus influenzae protein D (PHiD-CV) is effective for pneumococcal OM, but results from studies describing the potential impact on OM due to H influenzae have been inconsistent. Progress in vaccine development for H influenzae, Moraxella catarrhalis, and OM-associated respiratory viruses has been limited. Additional research is needed to extend vaccine protection to additional pneumococcal serotypes and other otopathogens. There are likely to be licensure challenges for protein-based vaccines, and data on correlates of protection for OM vaccine antigens are urgently needed. Implications for Practice. OM continues to be a significant health care burden globally. Prevention is preferable to treatment, and vaccine development remains an important goal. As a polymicrobial disease, OM poses significant but not insurmountable challenges for vaccine development.Peer reviewe

An Integrated Safety Analysis Methodology for Emerging Air Transport Technologies

For NASA's air transportation research program, we demonstrate an approach to integrating reliability, performance, and operational procedure modeling into a system safety analysis. Our methodology is distinguished by its ability to merge system design/functionality information with the dynamic parameterization of a system's situation to generate accident statistics and measures of reliable system operation. In addition, this approach can be employed to perform sensitivity analyses to identify weak points in the system's operation and design. Our approach to system safety analysis results from the integration of a Reliability model and an Interaction-Response model. The Interaction-Response model provides information regarding the frequency of encounters and the predicted outcome of those encounters as a function of the system's alerting system and ability to resolve encounters. The Reliability model provides, as a function of time, probabilities associated with the critical systems' a..

The NASA STI Program Office provides

Since its founding, NASA has been dedicated to the advancement of aeronautics and space science. The NASA Scientific and Technical Information (STI) Program Office plays a key part in helping NASA maintain this important role. The NASA STI Program Office is operated by Langley Research Center, the lead center for NASA’s scientific and technical information

A Method for Evaluating the Safety Impacts of Air Traffic Automation

this report provides a significant starting point for analyses of terminal area technologies. To meet tight time and resource constraints, we needed to select a portion of CTAS to analyze. Consequently, we chose the approach phase of flight that uses the CTAS Passive Final Approach Spacing Tool (P-FAST) to show a useful level of detail within the limited time and resources available. Within P-FAST, the study concentrates on aircraft operations from the meter gate through to the runway

The NASA STI Program Office provides

Since its founding, NASA has been dedicated to the advancement of aeronautics and space science. The NASA Scientific and Technical Information (STI) Program Office plays a key part in helping NASA maintain this important role. The NASA STI Program Office is operated by Langley Research Center, the lead center for NASA’s scientific and technical information

A System for Integrated Reliability and Safety Analyses

Semi-Markov Specification Interface Tool) provides a flexible, user-friendly interface for the textual description of the system's architecture. The ASSIST program builds the model by recursively applying the transition rules that are defined for the architecture. This Markov model description may then be used within the PAWS reliability analysis program. The PAWS (Pade Approximation With Scaling) program calculates the state probabilities at a given mission time. A wrapper routine (TARAT [3]) iterates through the subsystems and combines the results, yielding the overall functional modes. Surveillance Radar Reliability Model Figure 11 is a simplified top-level diagram of a surveillance radar system. This is a generic diagram representing a system with dual redundant-critical components. The system includes both a primary radar that can track the skin return from any target in its coverage area and a secondary radar, or beacon system, which sends out interrogations that trigger transp..