Results for “Resource management” — Page 20

NASA NTRS1996

UNIX-based operating systems robustness evaluation

Robust operating systems are required for reliable computing. Techniques for robustness evaluation of operating systems not only enhance the understanding of the reliability of computer systems, but also provide valuable feed- back to system designers. This thesis presents results from robustness evaluation experiments on five UNIX-based operating systems, which include Digital Equipment's OSF/l, Hewlett Packard's HP-UX, Sun Microsystems' Solaris and SunOS, and Silicon Graphics' IRIX. Three sets of experiments were performed. The methodology for evaluation tested (1) the exception handling mechanism, (2) system resource management, and (3) system capacity under high workload stress. An exception generator was used to evaluate the exception handling mechanism of the operating systems. Results included exit status of the exception generator and the system state. Resource management techniques used by individual operating systems were tested using programs designed to usurp system resources such as physical memory and process slots. Finally, the workload stress testing evaluated the effect of the workload on system performance by running a synthetic workload and recording the response time of local and remote user requests. Moderate to severe performance degradations were observed on the systems under stress.

Chang, Yu-Ming↗

NASA NTRS1974

TERSSE: Definition of the Total Earth Resources System for the Shuttle Era. Volume 3: Mission and System Requirements for the Total Earth Resources System

Resource management missions to be performed by TERSSE are described. Mission and user requirements are defined along with information flows developed for each major resource management mission. Other topics discussed include: remote sensing platforms, remote sensor requirements, ground system architecture, and such related issues as cloud cover, resolution, orbit mechanics, and aircraft versus satellite.

Source record↗

NASA NTRSDate not supplied

Gateway Autonomy for Enabling Deep Space Exploration

The Gateway spacecraft is an important stepping-stone to exploration of the solar system, integrating commercial and international partners into a tightly coupled system, enabling cislunar activities, and implementing key technologies for missions to Mars. Autonomy is a capability area necessary to handle long communication outages where intervention from Earth is impossible, to prepare to operate with long communication delays that will be common in interplanetary travel, and to make spaceflight more affordable and accessible by reducing sustaining operations costs. The Gateway Concept of Operations states that one of Gateway’s goals is to “focus on infrastructure and systems that will allow autonomous operations aboard the Gateway with robotics, automated systems, advanced communications, and distributed computing.” Gateway’s Vehicle Systems Manager (VSM) and associated Autonomous Spacecraft Management Architecture (ASMA) are key products towards delivering autonomous capability. The primary functions of the control architecture are Mission Management and Timeline Execution, Resource Management, Fault Management, and Vehicle Control and Operation (VCO). In each of these areas, there is an initial level of capability to be delivered at launch, with plans to continue development and grow to greater capability. The initial deployment of VSM will focus on maintaining vehicle safety by focusing on full fault management capabilities and deploying only enough resource and timeline planning functionality to support that. The final deployment of VSM will add significant planning and control optimization functionality to support nominal operations for up to 21 days without ground support, even accommodating fault and failure conditions. While the VSM is the vehicle-level representation of autonomous reasoning, distributed automation is essential to provide the right scope and abstraction of information to process. Module and system support of automation and simplicity of interfaces are two important design paradigms that Gateway is focusing on to garner a systems approach to autonomy. Distribution of reasoning can increase complexity, so Gateway is also taking a strict hierarchical approach to information flow and decision making. VSM is not the only capability necessary to achieve an autonomous spacecraft. Robotics support for maintenance of the spacecraft will be essential to provide continued vehicle functionality even when crew is not present. Technical and programmatic challenges exist when implementing autonomous robotics operations. These challenges include sufficient network flexibility to support data transfer to the rest of the vehicle to coordinate module-to-module robotic walk-offs and finding the proper interfaces to allow sufficient dexterity. Communication system upgrades planned for Gateway include Delay Tolerant Networking to best utilize the complex network of relays that will be part of mature cislunar operations. Distributed computing and management will provide failure tolerance, robustness, and growth of capabilities while still allowing significant reuse of heritage software on heritage systems as well as reuse of common applications across a spacecraft to minimize new development, but this requires adherence to key standards and interfaces. The Gateway program has demonstrated significant progress towards these capabilities and has identified challenges other spacecraft developers should be aware of from the start.

Molly Anderson↗

NASA NTRSDate not supplied

Gateway Autonomy for Enabling Deep Space Exploration

The Gateway spacecraft is an important stepping-stone to exploration of the solar system, integrating commercial and international partners into a tightly coupled system, enabling cislunar activities, and implementing key technologies for missions to Mars. Autonomy is a capability area necessary to handle long communication outages where intervention from Earth is impossible, to prepare to operate with long communication delays that will be common in interplanetary travel, and to make spaceflight more affordable and accessible by reducing sustaining operations costs. The Gateway Concept of Operations states that one of Gateway’s goals is to “focus on infrastructure and systems that will allow autonomous operations aboard the Gateway with robotics, automated systems, advanced communications, and distributed computing.” Gateway’s Vehicle Systems Manager (VSM) and associated Autonomous Spacecraft Management Architecture (ASMA) are key products towards delivering autonomous capability. The primary functions of the control architecture are Mission Management and Timeline Execution, Resource Management, Fault Management, and Vehicle Control and Operation (VCO). In each of these areas, there is an initial level of capability to be delivered at launch, with plans to continue development and grow to greater capability. The initial deployment of VSM will focus on maintaining vehicle safety by focusing on full fault management capabilities and deploying only enough resource and timeline planning functionality to support that. The final deployment of VSM will add significant planning and control optimization functionality to support nominal operations for up to 21 days without ground support, even accommodating fault and failure conditions. While the VSM is the vehicle-level representation of autonomous reasoning, distributed automation is essential to provide the right scope and abstraction of information to process. Module and system support of automation and simplicity of interfaces are two important design paradigms that Gateway is focusing on to garner a systems approach to autonomy. Distribution of reasoning can increase complexity, so Gateway is also taking a strict hierarchical approach to information flow and decision making. VSM is not the only capability necessary to achieve an autonomous spacecraft. Robotics support for maintenance of the spacecraft will be essential to provide continued vehicle functionality even when crew is not present. Technical and programmatic challenges exist when implementing autonomous robotics operations. These challenges include sufficient network flexibility to support data transfer to the rest of the vehicle to coordinate module-to-module robotic walk-offs and finding the proper interfaces to allow sufficient dexterity. Communication system upgrades planned for Gateway include Delay Tolerant Networking to best utilize the complex network of relays that will be part of mature cislunar operations. Distributed computing and management will provide failure tolerance, robustness, and growth of capabilities while still allowing significant reuse of heritage software on heritage systems as well as reuse of common applications across a spacecraft to minimize new development, but this requires adherence to key standards and interfaces. The Gateway program has demonstrated significant progress towards these capabilities and has identified challenges other spacecraft developers should be aware of from the start.

Molly Anderson↗

NASA NTRSDate not supplied

Supporting Aquaculture in the Chesapeake Bay Using Artificial Intelligence to Detect Poor Water Quality with Remote Sensing

Reliable information on water quality is not currently available at the space and time scales that are required for aquaculture and other resource management needs. For example, shellfish growing areas maybe impacted by harmful algal blooms or runoff from land that increases turbidity, lowers salinity, or introduces contaminants. Shellfish resource managers in the Chesapeake Bay are especially concerned with sources of bacteria from land such as failing onsite waste systems, failing wastewater infrastructure, and concentrated animal feeding operations. There is an urgent need for remote sensing of water quality indicators beyond chlorophyll-a and suspended sediments to augment field sampling programs. Artificial Intelligence trained with simultaneous in situ and satellite observations is explored in preparation for future hyperspectral satellite missions, which offer potential to detect additional water quality indicators not previously possible. This first step identifies and develops a method to harmonize disparate, unlinked aquatic datasets to derive information about where water quality is likely degraded.

Stephanie Schollaert Uz↗

DOE OSTI2021

Federal Water Management Planning Manual

This Federal Water Management Resource Guide provides direction to Federal agencies on how optimize water use at Federal facilities, use water balance analysis methods, identify design elements and procurement best practices, and expand use of alternative water. It provides best practices for managing water to be considered when developing or improving an effective facility water management program. PNNL developed this guide for the Federal Energy Management Program (FEMP). FEMP was directed by the Council on Environmental Quality (CEQ) to develop a Federal Water Management Resource Guide per the Implementing Instructions for Executive Order (E.O.) 13834, Efficient Federal Operations. This document serves to satisfy this requirement in order to provide best water management practices within the Federal Government.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Federal Water Management Planning Manual

This Federal Water Management Resource Guide provides direction to Federal agencies on how optimize water use at Federal facilities, use water balance analysis methods, identify design elements and procurement best practices, and expand use of alternative water. It provides best practices for managing water to be considered when developing or improving an effective facility water management program. PNNL developed this guide for the Federal Energy Management Program (FEMP). FEMP was directed by the Council on Environmental Quality (CEQ) to develop a Federal Water Management Resource Guide per the Implementing Instructions for Executive Order (E.O.) 13834, Efficient Federal Operations. This document serves to satisfy this requirement in order to provide best water management practices within the Federal Government.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Improving seasonal precipitation forecasts in the Western United States through statistical downscaling

Abstract Seasonal precipitation forecasts in the western United States are critical resources for water resource management, especially during winter. While current seasonal forecasting systems provide monthly precipitation forecasts operationally, their coarse resolution limits their effectiveness in capturing the localized precipitation patterns and snowpack conditions essential for water resource managers in the mountainous regions. Here, analog statistical downscaling is demonstrated as an effective approach to enhance the spatial resolution of operational seasonal forecasts provided by the North American Multi-Model Ensemble. Downscaling was performed by building an analog ‘library’, in which corresponding model forecasts and observed values during the training period were stored. In the testing period, unseen model forecasts referenced the closest historical forecast from the analog library and applied the corresponding observational value for each point. This analysis indicates that downscaled products can capture localized features more accurately than the original coarse resolution forecasts, reducing forecast error across the western United States. Moreover, downscaling individual ensemble members—rather than downscaling the ensemble mean—further reduces forecasting error for their multi-model ensemble mean products. The greatest error reductions in the downscaled product, measured by root mean squared error (RMSE), were observed at low to mid-elevations (500–2000 meters), with 50%–70% improvement relative to the original forecasts. In the higher elevations (2000 meters and above), changes in RMSE relative to the original forecast were limited to 10%–30% improvements. The improvement is more substantial for forecast systems with 10 ensemble members compared to that with 4 members, but this relationship does not hold for the system with 24 ensemble members. These findings show that analog statistical downscaling can effectively address the spatial limitations of seasonal precipitation forecasts with minimal computational cost, providing a valuable framework for enhancing coarse resolution forecasting products while providing insights into the timing of ensemble mean calculations during the downscaling process.

Vernon, B. (ORCID:0009000891670689)↗

NASA NTRS2005

Discovering the Regulatory Considerations of the Federal Aviation Administration: Interviewing the Aviation Rulemaking Advisory Committee

Maintenance Resource Management (MRM) training for aviation mechanics has become mandatory in many industrialized countries since 1998. Yet, to date, MRM training remains optional in the U.S. Interestingly, a similar safety discipline, namely Crew/Cockpit Resource Management (CRM), is mandatory for pilots, flight engineers, flight attendants, and dispatchers and is regulated in the Federal Aviation Administration s (FAA) Federal Aviation Regulations (FARs). If MRM training is important to enhance aviation technicians working behavior, the rationale to not regulate it opens a window for study. This research aims to inductively investigate the FAA s regulatory rationale concerning MRM training based on direct inputs from the FAA s Aviation Rulemaking Advisory Committee (ARAC) members. Delphi methodology associated with purposive sampling technique was adopted. The result revealed that the FAA cannot regulate MRM because the aviation industry is strongly opposed to it due to the lack of training budgets, the need of a quantifiable cost-effect analysis, concern over the FAA s inspection workforce, an ongoing voluntary alternative called the Air Transportation Surveillance System (ATOS), the government s lower priority on maintenance after 9/11, and the airlines tight embracement of operational flexibility without regulation.

Lu, Chien-tsung↗

DOE OSTI2020

Policy Innovation and Governance for Irrigation Sustainability in the Arid, Saline San Joaquin River Basin

This paper provides a chronology and overview of events and policy initiatives aimed at addressing irrigation sustainability issues in the San Joaquin River Basin (SJRB) of California. Although the SJRB was selected in this case study, many of the same resource management issues are being played out in arid, agricultural regions around the world. The first part of this paper provides an introduction to some of the early issues impacting the expansion of irrigated agriculture primarily on the west side of the San Joaquin Valley and the policy and capital investments that were used to address salinity impairments to the use of the San Joaquin River (SJR) as an irrigation water supply. Irrigated agriculture requires large quantities of water if it is to be sustained, as well as supply water of adequate quality for the crop being grown. The second part of the paper addresses these supply issues and a period of excessive groundwater pumping that resulted in widespread land subsidence. A joint federal and state policy response that resulted in the facilities to import Delta water provided a remedy that lasted almost 50 years until the Sustainable Groundwater Management Act of 2014 was passed in the legislature to address a recurrence of the same issue. The paper describes the current state of basin-scale simulation modeling that many areas, including California, are using to craft a future sustainable groundwater resource management policy. The third section of the paper deals with unique water quality issues that arose in connection with the selenium crisis at Kesterson Reservoir and the significant threats to irrigation sustainability on the west side of the San Joaquin Valley that followed. The eventual policy response to this crisis was incremental, spanning two decades of University of California-led research programs focused on finding permanent solutions to the salt and selenium contamination problems constraining irrigated agriculture, primarily on the west side. Arid-zone agricultural drainage-induced water quality problems are becoming more ubiquitous worldwide. One policy approach that found traction in California is an innovative variant on the traditional Total Maximum Daily Load (TMDL) approach to salinity regulation, which has features in common with a scheme in Australia’s Hunter River Basin. The paper describes the real-time salinity management (RTSM) concept, which is geared to improving coordination of west side agricultural and wetland exports of salt load with east side tributary reservoir release flows to improve compliance with river salinity objectives. RTSM is a concept that requires access to continuous flow and electrical conductivity data from sensor networks located along the San Joaquin River and its major tributaries and a simulation model-based decision support designed to make salt load assimilative capacity forecasts. Web-based information dissemination and data sharing innovations are described with an emphasis on experience with stakeholder engagement and participation. The last decade has seen wide-scale, global deployment of similar technologies for enhancing irrigation agriculture productivity and protecting environmental resources.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1973

Interchance and cooperation with user agencies

It is apparent that the rate of remote sensing technique development is increasing at a much faster pace than is the rate at which these same techniques are being put to practical use by earth resource managers and inventory specialists. It has become increasingly important to bridge this widening gap between remote sensing specialists and potential users. Members of the University of California project on remote sensing of earth resources have been actively participating in efforts to overcome this gap by maintaining library facilities, disseminating research findings, training remote sensing specialists, and interacting with resource managers.

Lauer, D. T.↗

DOE OSTI2025

Securing the Modern Grid: Federal Investments, Digitization, and Supply Chain Strategy

Across the United States (U.S.) grid expansion and modernization is underway, paving the way for accelerated load growth and intelligent resource management. Digitization of the grid is supported by several state and federal programs, providing support for utilities installing advanced metering infrastructure (AMI), AI-powered analytics systems, battery energy storage systems (BESS), and distributed energy resource management systems (DERMS) to transform the grid from a one-way power delivery system into an intelligent, responsive network that will enable faster load growth and power expansion of data centers for advanced artificial intelligence (AI) applications. The digital transformation of America's grid presents opportunity for increased efficiency and resiliency but also introduces new digital risks that require careful management. Digital equipment often contains several vulnerabilities such as unencrypted communication protocols, and persistent remote access capabilities that could be exploited to manipulate device settings, coordinate service disruptions, or inject false data into grid operations. These digital risks become particularly important as the grid must rapidly scale to support AI-driven data centers, which the administration has identified as essential for maintaining U.S. technological leadership and economic competitiveness. These vulnerabilities are compounded by supply chain realities: Chinese manufacturers currently produce 70-90% of essential grid components including inverters, batteries, and control systems, with the U.S. lacking domestic manufacturing capacity for critical assets like extra-high voltage transformers. Recent federal legislation has established Foreign Entity of Concern (FEOC) restrictions to address these risks, requiring projects to achieve escalating thresholds of non-FEOC content to receive tax credits while utilities work to expand sourcing channels for their supply chains and strengthen security measures. These restrictions arrive precisely when utilities face unprecedented electricity demand growth driven by the rapid growth in data centers, creating a considerable challenge: rapidly expanding infrastructure while navigating complex compliance requirements while lacking viable alternatives for many critical components. Idaho National Laboratory (INL) and its partners have developed practical approaches to help utilities navigate these intersecting challenges as they leverage federal investment to strengthen and grow the grid. These solutions include Cyber-Informed Engineering (CIE) principles that build resilience directly into systems, the Cirrus tool for secure cloud migration, and enhanced procurement guidance that embeds security requirements throughout equipment lifecycles. Federal initiatives, such as the Technical Assistance for Digital Assurance (TADA) project, provide direct support to utilities implementing these approaches while facilitating knowledge sharing across the industry. While these tools and frameworks cannot eliminate all risks inherent in foreign supply chain dependencies, they offer pragmatic pathways for strengthening security posture without sacrificing the deployment momentum essential to meeting surging electricity demand. Ultimately, securing America's digital energy infrastructure demands dedicated coordination across multiple fronts: building domestic supply chains, implementing robust digital assurance practices, and maintaining the aggressive modernization timeline necessary for reliability, resilience, and energy independence.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1994

Coordinated scheduling for dynamic real-time systems

In this project, we addressed issues in coordinated scheduling for dynamic real-time systems. In particular, we concentrated on design and implementation of a new distributed real-time system called R-Shell. The design objective of R-Shell is to provide computing support for space programs that have large, complex, fault-tolerant distributed real-time applications. In R-shell, the approach is based on the concept of scheduling agents, which reside in the application run-time environment, and are customized to provide just those resource management functions which are needed by the specific application. With this approach, we avoid the need for a sophisticated OS which provides a variety of generalized functionality, while still not burdening application programmers with heavy responsibility for resource management. In this report, we discuss the R-Shell approach, summarize the achievement of the project, and describe a preliminary prototype of R-Shell system.

Natarajan, Swaminathan↗

DOE OSTI2022

MARS: Malleable Actor-Critic Reinforcement Learning Scheduler

In this paper, we introduce MARS, a new scheduling system for HPC-cloud infrastructures based on a cost-aware, flexible reinforcement learning approach, which serves as an intermediate layer for next generation HPC-cloud resource manager. MARS ensembles the pre-trained models from heuristic workloads and decides on the most cost-effective strategy for optimization. A whole workflow application would be split into several optimizable dependent sub-tasks, then based on the pre- defined resource management plan, a reward will be generated after executing a scheduled task. Lastly, MARS updates the Deep Neural Network (DNN) model based on the reward. MARS is designed to optimize the existing models through reinforcement mechanisms. MARS adapts to the dynamics of workflow applications, selects the most cost-effective scheduling solution among pre-built scheduling strategies (backfilling, SJF, etc.) and self- learning deep neural network model at run-time. We evaluate MARS with different real-world workflow traces. MARS can achieve 5%-60% increased performance compare to state-of-the- art approaches.

Baheri, Betis↗

NASA NTRS2008

Cassini Information Management System in Distributed Operations Collaboration and Cassini Science Planning

Launched on October 15, 1997, the Cassini-Huygens spacecraft began its ambitious journey to the Saturnian system with a complex suite of 12 scientific instruments, and another 6 instruments aboard the European Space Agencies Huygens Probe. Over the next 6 1/2 years, Cassini would continue its relatively simplistic cruise phase operations, flying past Venus, Earth, and Jupiter. However, following Saturn Orbit Insertion (SOI), Cassini would become involved in a complex series of tasks that required detailed resource management, distributed operations collaboration, and a data base for capturing science objectives. Collectively, these needs were met through a web-based software tool designed to help with the Cassini uplink process and ultimately used to generate more robust sequences for spacecraft operations. In 2001, in conjunction with the Southwest Research Institute (SwRI) and later Venustar Software and Engineering Inc., the Cassini Information Management System (CIMS) was released which enabled the Cassini spacecraft and science planning teams to perform complex information management and team collaboration between scientists and engineers in 17 countries. Originally tailored to help manage the science planning uplink process, CIMS has been actively evolving since its inception to meet the changing and growing needs of the Cassini uplink team and effectively reduce mission risk through a series of resource management validation algorithms. These algorithms have been implemented in the web-based software tool to identify potential sequence conflicts early in the science planning process. CIMS mitigates these sequence conflicts through identification of timing incongruities, pointing inconsistencies, flight rule violations, data volume issues, and by assisting in Deep Space Network (DSN) coverage analysis. In preparation for extended mission operations, CIMS has also evolved further to assist in the planning and coordination of the dual playback redundancy of highvalue data from targets such as Titan and Enceladus. This paper will outline the critical role that CIMS has played for Cassini in the distributed ops paradigm throughout operations. This paper will also examine the evolution that CIMS has undergone in the face of new science discoveries and fluctuating operational needs. And finally, this paper will conclude with theoretical adaptation of CIMS for other projects and the potential savings in cost and risk reduction that could potentially be tapped into by future missions.

Equils, Douglas J.↗

NASA NTRS2010

NASA Ames DEVELOP Interns: Helping the Western United States Manage Natural Resources One Project at a Time

The western half of the United States is made up of a number of diverse ecosystems ranging from arid desert to coastal wetlands and rugged forests. Every summer for the past 7 years students ranging from high school to graduate level gather at NASA Ames Research Center (ARC) as part of the DEVELOP Internship Program. Under the guidance of Jay Skiles [Ames Research Center (ARC) - Ames DEVELOP Manager] and Cindy Schmidt [ARC/San Jose State University Ames DEVELOP Coordinator] they work as a team on projects exploring topics including: invasive species, carbon flux, wetland restoration, air quality monitoring, storm visualizations, and forest fires. The study areas for these projects have been in Washington, Utah, Oregon, Nevada, Hawaii, Alaska and California. Interns combine data from NASA and partner satellites with models and in situ measurements to complete prototype projects demonstrating how NASA data and resources can help communities tackle their Earth Science related problems.

Justice, Erin↗

DOE OSTI2023

Typologies of actionable climate information and its use

Developing actionable climate information and integrating it into decision-making are two crucial elements for promoting effective societal responses to climate change. However, what constitutes actionable climate information, and how it is used, varies based on the actors, systems, and scales that are relevant to specific decisions. Yet, the terms ‘actionable climate information’ or ‘use of climate information’ are used abstractly. There is a lack of holistic understanding of the various types of information that can be deemed as usable by different users, and the different ways in which they may be used in decision-making. Typologies or generalizable categorizations can help both knowledge producers and users to better envision the entire landscape of climate information and its uses and can help to reduce the time and cost of actionable knowledge production. Through systematic coding and analysis of ~ 4 years of co-production engagements between climate scientists and resource managers, this paper presents empirically derived typologies of actionable climate information and its use, and explores whether certain uses are better informed by specific types of climate information. These typologies provide a valuable starting point for climate information producers, users, and boundary spanners working on climate-informed resource management, to reduce some of the time-intensive elements of the process.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2018

Addressing Human Error in International Space Station Flight Control Teams: Advances in Ground Training for Science Operators

In flight control, as with any human in the loop system, operator error is an inevitable reality. On the International Space Station (ISS) where crew time and physical resources are precious and often irreplaceable, operator errors can result in significant, irreversible consequences. Flight controllers at the Payload Operations Integration Center (POIC) located at NASA’s Marshall Space Flight Center (MSFC) in Huntsville, Alabama know this reality well. At the POIC, operator errors can be caused by a variety of factors, from poor hardware or software design to environmental factors such as time pressure or fatigue. The most difficult errors to address, however, are those which result from ineffective teamwork.Academic research in teamwork has resulted in the identification of many factors which make cross-functional teaming difficult, including leadership, trust building, and communication challenges. These factors, especially when combined with the challenging environmental factors flight control teams must contend with daily, make the goal of minimizing operator errors in payload operations challenging to achieve. To address such teamwork errors, trainers at the POIC have drawn best practices from high reliability industries such as commercial aviation, healthcare, and nuclear power plants, as well as from our sister ISS control center in Houston, Texas, to develop and institute a new training program focused specifically on teamwork skills.This training program, called the Team Skills Curriculum, is based on the concept of Crew Resource Management (CRM) which was developed by NASA in the 1970s for the commercial aviation industry in response to a series of aviation disasters resulting from ineffective teamwork. CRM was later tailored by the Johnson Space Center (JSC) for use in astronaut and flight control training. The result, called Space Flight Resource Management (SFRM) was formally introduced into manned spaceflight training in the late 90s. SFRM has evolved over the years, but the focus has remained on helping operators develop the skills needed to work as part of an effective team. Using these concepts as well as the latest research in cross-functional teaming and data on specific errors occurring at the POIC, trainers in the integrated flight control training branch created a custom training program for both new and certified payload operations specialists.

Harris, Samantha S.↗