NobleBlocks

NASA Safety Center

facilityCleveland, United States

Research output, citation impact, and the most-cited recent papers from NASA Safety Center. Aggregated across the NobleBlocks index of 300M+ scholarly works.

Total works
2
Citations
13
h-index
1
i10-index
1
Also known as
NASA Safety Center

Top-cited papers from NASA Safety Center

Reliability and probabilistic risk assessment — How they play together
Fayssal M. Safie, Richard G. Stutts, Zhaofeng Huang
201512doi:10.1109/rams.2015.7105058

Since the Space Shuttle Challenger accident in 1986, NASA and aerospace industry has extensively used Probabilistic Risk Assessment (PRA) methods to assess, understand, and communicate the risk of space launch vehicles, especially manned space flight missions. Another area that was given a lot of emphasis at NASA is reliability engineering. Both PRA and reliability are probabilistic in nature; however; the reliability engineering is a broad design discipline that deals with loss of function, while PRA is a system scenario based risk assessment process that deals with Loss of Mission (LOM), Loss of Vehicle (LOV), and Loss of Crew (LOC). This paper discusses the PRA process and the reliability engineering discipline in details. It discusses their differences and similarities and how they are used as complementary analyses to support design and flight decisions. In summary: 1) Reliability Engineering is a discipline that involves the application of engineering principles to the design and processing of products; both hardware and software intended to minimize the loss of functions. 2) PRA at NASA is a process that deals with system risk focusing on understanding the system risk scenarios that could lead to LOM, LOV, and LOC. 3) PRA and reliability engineering are two different areas serving different functions in supporting the design and operation of launch vehicles. However, PRA as a risk assessment, and reliability as a metric could play together in a complementary manner in assessing the risk and reliability of launch vehicles. 4) In general, reliability analyses should be used as a critical data source for PRA.

NASA’s Safety, Reliability, and Mission Assurance Digital Future
Anthony DiVenti, Matthew Forsbacka, Kevin Rainbolt, Steven L. Cornford +1 more
20231doi:10.1109/rams51473.2023.10088205

SUMMARY & CONCLUSIONSThe evolution from "document-centric" to "data-centric" and "model-centric" information leveraging structured data and model-based approaches is at the heart of digital engineering transformational efforts underway across industry and government. It is these approaches that pave the way for data lakes, Authoritative Sources of Truth (ASOTs), and systems-of-systems interoperability and the corresponding transformational benefits thereof. Such benefits include increased data availability, data access equity, data traceability, real-time analytics, batch analytics, and (most importantly) acceleration of the time-to-value and time-to-insights associated with engineering products and analyses. The longer-term benefits of reusability, customization and traceability are even more promising.For Safety and Mission Assurance (SMA), and Mission Success (SMS) activities; realization of such benefits is essential to provide engineers and analysts alike vital information when needed to support critical decision making throughout the entire life cycle. The SMA community often operate in parallel with engineering activities, for which information exchange with relevant context is paramount. Far too often, such information lags key decision points and/or is absent of the robust, integrated, knowledge needed, given inherent barriers associated with traditional document-centric means to data sharing, analysis, and reporting.This paper provides an overview of how NASA’s Office of Safety and Mission Assurance (OSMA) is evolving its policies, standards, guidance, and training to transform to eliminate such barriers, thus realizing the benefits emerging in this new digital era. A roadmap for achieving this digital future is presented along with key building blocks involving use and implementation of concepts such as: Objectives-Hierarchies, Objective-Driven Requirements, Accepted Standards, Safety and Assurance Cases, data digitization (i.e., ontologies, structured data, and model-centric data), FAIR (Findable, Accessible, Interoperable, & Reusable) and/or FAIRUST (Findable, Accessible, Interoperable, Reusable, Understandable, Secure, and Trusted) principles [1]. This paper also describes how OSMA, leveraging the Agency’s overall commitment to Digital Transformation (DT), is using the power of Policy, "Digital" Domain representation, Product Evolution, and Community Outreach and Engagement as part of a strategic vision and roadmap to evolve and transform its SMA organizations to become better able to serve its stakeholders and customers. Future publications will elaborate on these building blocks and deeper concepts.