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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Systems Engineering Design Via Experimental Operation Research: Complex Organizational Metric for Programmatic Risk Environments (COMPRE)

Unique and innovative graph theory, neural network, organizational modeling, and genetic algorithms are applied to the design and evolution of programmatic and organizational architectures. Graph theory representations of programs and organizations increase modeling capabilities and flexibility, while illuminating preferable programmatic/organizational design features. Treating programs and organizations as neural networks results in better system synthesis, and more robust data modeling. Organizational modeling using covariance structures enhances the determination of organizational risk factors. Genetic algorithms improve programmatic evolution characteristics, while shedding light on rulebase requirements for achieving specified technological readiness levels, given budget and schedule resources. This program of research improves the robustness and verifiability of systems synthesis tools, including the Complex Organizational Metric for Programmatic Risk Environments (COMPRE).

Mog, Robert A.↗
NASA NTRS2010

The Golden Gate: Building Bridges Between Research and Operations

Previous research has discussed the ongoing dilemma of implementing research-based findings in an applied setting. This panel will discuss lessons learned from various examples where bridges have been forged between research and operations, and examine ways to promote and achieve similar collaborations in other areas in the future.

Schmidt, Lacey L.↗
NASA NTRS2011

Co-Operative Advances in Behavioral Health and Performance Research and Operations

In organizations that engage in both operations and applied research, with operational needs guiding research questions and research informing improved operations, the ideal goal is a synergy of ideas and information. In reality, this ideal synergy is often lacking. Real-time operational needs driving day-to-day decisions, lack of communication, lag time in getting research advances plugged into operations can cause both areas to suffer from this gap between operations and research. At Johnson Space Center, the Behavior Health and Performance group (BHP) strives to bridge this gap by following a Human Research Program framework: Expectations of future operational needs identify the knowledge gaps; the gaps in turn guide research leading to a product that is transitioned into operations. Thus, the direction those of us in research take is in direct response to current and future needs of operations. Likewise, those of us in operations actively seek knowledge that is supported by evidence-based research. We make an ongoing effort to communicate across the research and operations gap by working closely with each other and making a conscious effort to keep each other informed. The objective of the proposed panel discussion is to demonstrate through the following presentations the results of a successful collaboration between research and operations and to provide ASMA members with more practical knowledge and strategies for building these bridges to serve our field of practice well. The panel will consist of six presenters from BHP operations, internal BHP research, and external research instigated by BHP who together represent the entire BHP Research Transition to Operations Framework

VanderArk, Stephen T.↗
NASA NTRS2017

ICAO RPAS Symposium: NASA RPAS Operational and Research Activities

NASA RPAS Operational and Research Activities presentation discusses the UAS flight operations. UAS vehicles are discussed along with the missions they supported. This is a high level overview of UAS operations at NASA being presented to the RPAS (Remotely Piloted Aircraft Systems) Symposium.

Johnson, Chuck↗
NASA NTRS2010

Harnessing the Risk-Related Data Supply Chain: An Information Architecture Approach to Enriching Human System Research and Operations Knowledge

NASA's Human Research Program (HRP) and Space Life Sciences Directorate (SLSD), not unlike many NASA organizations today, struggle with the inherent inefficiencies caused by dependencies on heterogeneous data systems and silos of data and information spread across decentralized discipline domains. The capture of operational and research-based data/information (both in-flight and ground-based) in disparate IT systems impedes the extent to which that data/information can be efficiently and securely shared, analyzed, and enriched into knowledge that directly and more rapidly supports HRP's research-focused human system risk mitigation efforts and SLSD s operationally oriented risk management efforts. As a result, an integrated effort is underway to more fully understand and document how specific sets of risk-related data/information are generated and used and in what IT systems that data/information currently resides. By mapping the risk-related data flow from raw data to useable information and knowledge (think of it as the data supply chain), HRP and SLSD are building an information architecture plan to leverage their existing, shared IT infrastructure. In addition, it is important to create a centralized structured tool to represent risks including attributes such as likelihood, consequence, contributing factors, and the evidence supporting the information in all these fields. Representing the risks in this way enables reasoning about the risks, e.g. revisiting a risk assessment when a mitigation strategy is unavailable, updating a risk assessment when new information becomes available, etc. Such a system also provides a concise way to communicate the risks both within the organization as well as with collaborators. Understanding and, hence, harnessing the human system risk-related data supply chain enhances both organizations' abilities to securely collect, integrate, and share data assets that improve human system research and operations.

Buquo, Lynn↗
NASA NTRS2023

The Community Radiative Transfer Model (CRTM): Community-Focused Collaborative Model Development Accelerating Research to Operations

The Joint Center for Satellite Data Assimilation (JCSDA) Community Radiative Transfer Model (CRTM) is a fast, 1-D radiative transfer model used in numerical weather prediction, calibration/validation, etc. across multiple federal agencies and universities. The key benefit of the CRTM is that it is a satellite simulator. It provides a highly accurate representation of satellite radiances by using the specific sensor response functions convolved with a line-by-line radiative transfer model (LBLRTM). CRTM covers the spectral ranges consistent with all present operational and most research satellites, from visible to microwave. The capability to simulate ultraviolet radiances and support space-based radar sensors is being added over the next two years in CRTM Version 3.0. In addition to simulated radiances, the CRTM also provides Jacobian outputs needed to interpret satellite observations for numerical weather prediction. The Jacobian estimates how changes in geophysical parameters affect simulated measurements from satellite sensors. Using the Jacobian in modeling and weather prediction improves the accuracy and efficiency of data analysis, leading to better weather predictions. The CRTM model's success and growth depend on community contributions and evaluation. To facilitate this, we have made the CRTM highly accessible through modular programming, clear documentation and tutorials, public domain licensing, unfettered public access via Github, and a clear path to operational implementation for innovative research. We encourage and welcome contributions from the community to help us continue to improve the CRTM.

Benjamin T Johnson↗
NASA NTRS2011

Examination of Communication Delays on Team Performance: Utilizing the International Space Station (ISS) as a Test Bed for Analog Research

Operational conjectures about space exploration missions of the future indicate that space crews will need to be more autonomous from mission control and operate independently. This is in part due to the expectation that communication quality between the ground and exploration crews will be more limited and delayed. Because of potential adverse effects on communication quality, both researchers and operational training and engineering experts have suggested that communication delays and the impact these delays have on the quality of communications to the crew will create performance decrements if crews are not given adequate training and tools to support more autonomous operations. This presentation will provide an overview of a research study led by the Behavioral Health and Performance Element (BHP) of the NASA Human Research Program that examines the impact of implementing a communication delay on ISS on individual and team factors and outcomes, including performance and related perceptions of autonomy. The methodological design, data collection efforts, and initial results of this study to date will be discussed . The results will focus on completed missions, DRATS and NEEMO15. Lessons learned from implementing this study within analog environments will also be discussed. One lesson learned is that the complexities of garnishing a successful data collection campaign from these high fidelity analogs requires perseverance and a strong relationship with operational experts. Results of this study will provide a preliminary understanding of the impact of communication delays on individual and team performance as well as an insight into how teams perform and interact in a space-like environment . This will help prepare for implementation of communication delay tests on the ISS, targeted for Increment 35/36.

Keeton, K. E.↗
NASA NTRS2009

Research to Operations: The Critical Transition

Space Life Sciences Directorate (SLSD) specializes in transitioning technology and knowledge to medical operations. This activity encompasses funding a spectrum of research and technology efforts, such as understanding fundamental biological mechanisms altered by microgravity and executing technology watches for state of the art diagnostic imaging equipment. This broad spectrum approach to fulfilling the need to protect crewmember health and performance during long and short duration missions to the International Space Station, moon and Mars is made possible by having a line of site between research and operations. Currently, SLSD's line of site is articulated in a transition to medical practice (TMP) process. This process is designed to shepherd information and knowledge gained through fundamental and mechanistic research toward the development of an operational solution such as a pre-flight selection criteria; an in-flight countermeasure, monitoring capability or treatment; or a post-flight reconditioning program. The TMP process is also designed to assist with the customization of mature hardware or technology for NASA specific use. The benefits of this process are that the concept of operational usability is interjected early in the research, design, or acquisition phase, and stakeholders are involved early to identify requirements and also periodically asked to assess requirements compliance of research or technology development project. Currently a device known as the actiwatch is being assessed for the final transition to operational use. Specific examples of research to operations transition success help to illustrate the process and bolster communication between the research and medical operations communities.

Fogarty, Jennifer A.↗
NASA NTRS2012

Space Environments and Effects Concept: Transitioning Research to Operations and Applications

The National Aeronautics and Space Administration (NASA) is embarking on a course to expand human presence beyond Low Earth Orbit (LEO) while expanding its mission to explore the solar system. Destinations such as Near Earth Asteroids (NEA), Mars and its moons, and the outer planets are but a few of the mission targets. NASA has established numerous offices specializing in specific space environments disciplines that will serve to enable these missions. To complement these existing discipline offices, a concept focusing on the development of space environment and effects application is presented. This includes space climate, space weather, and natural and induced space environments. This space environment and effects application is composed of 4 topic areas; characterization and modeling, engineering effects, prediction and operation, and mitigation and avoidance. These topic areas are briefly described below. Characterization and modeling of space environments will primarily focus on utilization during Program mission concept, planning, and design phases. Engineering effects includes materials testing and flight experiments producing data to be used in mission planning and design phases. Prediction and operation pulls data from existing sources into decision-making tools and empirical data sets to be used during the operational phase of a mission. Mitigation and avoidance will develop techniques and strategies used in the design and operations phases of the mission. The goal of this space environment and effects application is to develop decision-making tools and engineering products to support the mission phases of mission concept through operations by focusing on transitioning research to operations. Products generated by this space environments and effects application are suitable for use in anomaly investigations. This paper will outline the four topic areas, describe the need, and discuss an organizational structure for this space environments and effects application.

Edwards, David L.↗
NASA NTRS2010

The Applied Meteorology Unit: Nineteen Years Successfully Transitioning Research into Operations for America's Space Program

The Applied Meteorology Unit (AMU) provides technology transition and technique development to improve operational weather support to the Space Shuttle and the entire American space program. The AMU is funded and managed by NASA and operated by a contractor that provides five meteorologists with a diverse mix of advanced degrees, operational experience, and associated skills including data processing, statistics, and the development of graphical user interfaces. The AMU's primary customers are the U.S. Air Force 45th Weather Squadron at Patrick Air Force Base, the National Weather Service Spaceflight Meteorology Group at NASA Johnson Space Center, and the National Weather Service Melbourne FL Forecast Office. The AMU has transitioned research into operations for nineteen years and worked on a wide range of topics, including new forecasting techniques for lightning probability, synoptic peak winds,.convective winds, and summer severe weather; satellite tools to predict anvil cloud trajectories and evaluate camera line of sight for Space Shuttle launch; optimized radar scan strategies; evaluated and implemented local numerical models; evaluated weather sensors; and many more. The AMU has completed 113 projects with 5 more scheduled to be completed by the end of 2010. During this rich history, the AMU and its customers have learned many lessons on how to effectively transition research into operations. Some of these lessons learned include collocating with the operational customer and periodically visiting geographically separated customers, operator submitted projects, consensus tasking process, use of operator primary advocates for each project, customer AMU liaisons with experience in both operations and research, flexibility in adapting the project plan based on lessons learned during the project, and incorporating training and other transition assistance into the project plans. Operator involvement has been critical to the AMU's remarkable success and many awards from NASA, the National Weather Association, and two citations from the Navy's Center of Excellence for Best Manufacturing Practices. This paper will present the AMU's proven methods and explain how they may be applied by other organizations to effectively transition research into operations.

Madura, John T.↗