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NASA NTRS2012

Using Collaborative Engineering to Inform Collaboration Engineering

Collaboration is a critical competency for modern organizations as they struggle to compete in an increasingly complex, global environment. A large body of research on collaboration in the workplace focuses both on teams, investigating how groups use teamwork to perform their task work, and on the use of information systems to support team processes ("collaboration engineering"). This research essay presents collaboration from an engineering perspective ("collaborative engineering"). It uses examples from professional and student engineering teams to illustrate key differences in collaborative versus collaboration engineering and investigates how challenges in the former can inform opportunities for the latter.

Collaboration Engineering↗

NASA NTRS2014

Brainwave Monitoring Software Improves Distracted Minds

Neurofeedback technology developed at Langley Research Center to monitor pilot awareness inspired Peter Freer to develop software for improving student performance. His company, Fletcher, North Carolina-based Unique Logic and Technology Inc., has gone on to develop technology for improving workplace and sports performance, monitoring drowsiness, and encouraging relaxation.

Source record↗

NASA NTRS2014

International Space Station Noise Constraints Flight Rule Process

Crewmembers onboard the International Space Station (ISS) live in a unique workplace environment for as long as 6 ‐12 months. During these long‐duration ISS missions, noise exposures from onboard equipment are posing concerns for human factors and crewmember health risks, such as possible reductions in hearing sensitivity, disruptions of crew sleep, interference with speech intelligibility and voice communications, interference with crew task performance, and reduced alarm audibility. The purpose of this poster is to describe how a recently‐updated noise constraints flight rule is being used to implement a NASA‐created Noise Exposure Estimation Tool and Noise Hazard Inventory to predict crew noise exposures and recommend when hearing protection devices are needed.

Limardo, Jose G.↗

NASA NTRS2015

Critical Team Composition Issues for Long-Distance and Long-Duration Space Exploration: A Literature Review, an Operational Assessment, and Recommendations for Practice and Research

Prevailing team effectiveness models suggest that teams are best positioned for success when certain enabling conditions are in place (Hackman, 1987; Hackman, 2012; Mathieu, Maynard, Rapp, & Gilson, 2008; Wageman, Hackman, & Lehman, 2005). Team composition, or the configuration of member attributes, is an enabling structure key to fostering competent teamwork (Hackman, 2002; Wageman et al., 2005). A vast body of research supports the importance of team composition in team design (Bell, 2007). For example, team composition is empirically linked to outcomes such as cooperation (Eby & Dobbins, 1997), social integration (Harrison, Price, Gavin, & Florey, 2002), shared cognition (Fisher, Bell, Dierdorff, & Belohlav, 2012), information sharing (Randall, Resick, & DeChurch, 2011), adaptability (LePine, 2005), and team performance (e.g., Bell, 2007). As such, NASA has identified team composition as a potentially powerful means for mitigating the risk of performance decrements due to inadequate crew cooperation, coordination, communication, and psychosocial adaptation in future space exploration missions. Much of what is known about effective team composition is drawn from research conducted in conventional workplaces (e.g., corporate offices, production plants). Quantitative reviews of the team composition literature (e.g., Bell, 2007; Bell, Villado, Lukasik, Belau, & Briggs, 2011) are based primarily on traditional teams. Less is known about how composition affects teams operating in extreme environments such as those that will be experienced by crews of future space exploration missions. For example, long-distance and long-duration space exploration (LDSE) crews are expected to live and work in isolated and confined environments (ICEs) for up to 30 months. Crews will also experience communication time delays from mission control, which will require crews to work more autonomously (see Appendix A for more detailed information regarding the LDSE context). Given the unique context within which LDSE crews will operate, NASA identified both a gap in knowledge related to the effective composition of autonomous, LDSE crews, and the need to identify psychological and psychosocial factors, measures, and combinations thereof that can be used to compose highly effective crews (Team Gap 8). As an initial step to address Team Gap 8, we conducted a focused literature review and operational assessment related to team composition issues for LDSE. The objectives of our research were to: (1) identify critical team composition issues and their effects on team functioning in LDSE-analogous environments with a focus on key composition factors that will most likely have the strongest influence on team performance and well-being, and 1 Astronaut diary entry in regards to group interaction aboard the ISS (p.22; Stuster, 2010) 2 (2) identify and evaluate methods used to compose teams with a focus on methods used in analogous environments. The remainder of the report includes the following components: (a) literature review methodology, (b) review of team composition theory and research, (c) methods for composing teams, (d) operational assessment results, and (e) recommendations.

Bell, Suzanne T.↗

NASA NTRS2016

Tailoring a Human Reliability Analysis to Your Industry Needs

Companies at risk of accidents caused by human error that result in catastrophic consequences include: airline industry mishaps, medical malpractice, medication mistakes, aerospace failures, major oil spills, transportation mishaps, power production failures and manufacturing facility incidents. Human Reliability Assessment (HRA) is used to analyze the inherent risk of human behavior or actions introducing errors into the operation of a system or process. These assessments can be used to identify where errors are most likely to arise and the potential risks involved if they do occur. Using the basic concepts of HRA, an evolving group of methodologies are used to meet various industry needs. Determining which methodology or combination of techniques will provide a quality human reliability assessment is a key element to developing effective strategies for understanding and dealing with risks caused by human errors. There are a number of concerns and difficulties in "tailoring" a Human Reliability Assessment (HRA) for different industries. Although a variety of HRA methodologies are available to analyze human error events, determining the most appropriate tools to provide the most useful results can depend on industry specific cultures and requirements. Methodology selection may be based on a variety of factors that include: 1) how people act and react in different industries, 2) expectations based on industry standards, 3) factors that influence how the human errors could occur such as tasks, tools, environment, workplace, support, training and procedure, 4) type and availability of data, 5) how the industry views risk & reliability, and 6) types of emergencies, contingencies and routine tasks. Other considerations for methodology selection should be based on what information is needed from the assessment. If the principal concern is determination of the primary risk factors contributing to the potential human error, a more detailed analysis method may be employed versus a requirement to provide a numerical value as part of a probabilistic risk assessment. Industries involved with humans operating large equipment or transport systems (ex. railroads or airlines) would have more need to address the man machine interface than medical workers administering medications. Human error occurs in every industry; in most cases the consequences are relatively benign and occasionally beneficial. In cases where the results can have disastrous consequences, the use of Human Reliability techniques to identify and classify the risk of human errors allows a company more opportunities to mitigate or eliminate these types of risks and prevent costly tragedies.

DeMott, D. L.↗

NASA NTRS2015

NASA Ames Sustainability Initiatives: Aeronautics, Space Exploration, and Sustainable Futures

In support of the mission-specific challenges of aeronautics and space exploration, NASA Ames produces a wealth of research and technology advancements with significant relevance to larger issues of planetary sustainability. NASA research on NexGen airspace solutions and its development of autonomous and intelligent technologies will revolutionize both the nation's air transporation systems and have applicability to the low altitude flight economy and to both air and ground transporation, more generally. NASA's understanding of the Earth as a complex of integrated systems contributes to humanity's perception of the sustainability of our home planet. Research at NASA Ames on closed environment life support systems produces directly applicable lessons on energy, water, and resource management in ground-based infrastructure. Moreover, every NASA campus is a 'city'; including an urbanscape and a workplace including scientists, human relations specialists, plumbers, engineers, facility managers, construction trades, transportation managers, software developers, leaders, financial planners, technologists, electricians, students, accountants, and even lawyers. NASA is applying the lessons of our mission-related activities to our urbanscapes and infrastructure, and also anticipates a leadership role in developing future environments for living and working in space.

Planetary futures↗

NASA NTRS2011

Human Factors Throughout the Life Cycle: Lessons Learned from the Shuttle Program

With the ending of the Space Shuttle Program, it is critical that we not forget the Human Factors lessons we have learned over the years. At every phase of the life cycle, from manufacturing, processing and integrating vehicle and payload, to launch, flight operations, mission control and landing, hundreds of teams have worked together to achieve mission success in one of the most complex, high-risk socio-technical enterprises ever designed. Just as there was great diversity in the types of operations performed at every stage, there was a myriad of human factors that could further complicate these human systems. A single mishap or close call could point to issues at the individual level (perceptual or workload limitations, training, fatigue, human error susceptibilities), the task level (design of tools, procedures and aspects of the workplace), as well as the organizational level (appropriate resources, safety policies, information access and communication channels). While we have often had to learn through human mistakes and technological failures, we have also begun to understand how to design human systems in which individuals can excel, where tasks and procedures are not only safe but efficient, and how organizations can foster a proactive approach to managing risk and supporting human enterprises. Panelists will talk about their experiences as they relate human factors to a particular phase of the shuttle life cycle. They will conclude with a framework for tying together human factors lessons-learned into system-level risk management strategies.

human factors↗

NASA NTRS2017

Aerosol Sampling Experiment on the International Space Station

The International Space Station (ISS) is a unique indoor environment which serves as both home and workplace to the astronaut crew. There is currently no particulate monitoring, although particulate matter requirements exist. An experiment to collect particles in the ISS cabin was conducted recently. Two different aerosol samplers were used for redundancy and to collect particles in two size ranges spanning from 10 nm to hundreds of micrometers. The Active Sampler is a battery operated thermophoretic sampler with an internal pump which draws in air and collects particles directly on a transmission electron microscope grid. This commercial-off-the-shelf device was modified for operation in low gravity. The Passive Sampler has five sampling surfaces which were exposed to air for different durations in order to collect at least one sample with an optimal quantity of particles for microscopy. These samples were returned to Earth for analysis with a variety of techniques to obtain long-term average concentrations and identify particle emission sources. Results are compared with the inventory of ISS aerosols which was created based on sparse data and the literature. The goal of the experiment is to obtain data on indoor aerosols on ISS for future particulate monitor design and development.

Aerosol↗

NASA NTRS2018

Creating Innovative Frameworks to Spur Cultural Change at NASA Armstrong Flight Research Center

Changing the culture of an organization is a monumental task that often takes years and has no set formula. Steps can be taken, however, to spur cultural change by creating spaces and infrastructure to serve as the initial driving force. An innovation space and a bicycle sharing (bike share) program were implemented at the National Aeronautics and Space Administration (NASA) Armstrong Flight Research Center (AFRC) (Edwards, California) with a vision toward connecting Center personnel, fostering collaboration and innovation, retaining newer employees, promoting flexibility, and improving the culture and workplace atmosphere. This paper discusses the steps taken, challenges faced, novel culture-change-focused design elements, lessons learned, acquired metrics, and how these initiated cultural change at AFRC. For both the innovation space and the bike share program, funding was negotiated and provided through the NASA Convergent Aeronautics Solutions (CAS) project, which was seeking to improve the innovation and collaboration capabilities at each of the four NASA aeronautics Centers. Key stakeholders across AFRC from upper management, facilities, safety, engineering, and procurement were identified early in the process and were consulted and included throughout execution to ensure that any encountered roadblocks could be easily navigated. Research was then conducted by attending conferences and visiting culture-changing organizations both inside and outside United States Government agencies. Distilling the research, identifying available space, and deciding on specific design elements for the space was conducted by a subset of individuals of diverse backgrounds to enable quick, effective decision-making. Decisions were made with the intent to increase usage and diversity of users of the space; care was taken to ensure a well-crafted atmosphere that would foster the desired culture change. The allocated physical space required major structural modifications, new furniture, and new capabilities that would bring people in. Decisions and desires underwent a rapid reiterative process in order to stay within budget and short deadlines, while holding firm to what was seen as fundamental elements of an innovation space. The framework for cultural change being established, the more difficult task began: incubating the desired culture. Intentional workday use of the innovation space was encouraged, and organized events coordinated in order to truly foster culture change. Such incubation supports the organic spread of culture change to all areas of AFRC. This framework was complemented and expanded by the implementation of the bike share program. Steps for implementation included bike selection based on lessons learned, creating bike stations and signage, implementing bike share rules, and building a volunteer maintenance infrastructure. A novel user-reporting feedback system at each bike station is a low-impact method of capturing usage metrics. Due to the nature of the work conducted at AFRC, the bike share program and feedback system were negotiated and vetted through various organizations including legal, safety, and operations. The innovation space and the bike share program together are an effective initial framework for innovation and collaboration. Culture change takes time, but the innovation space and the bike share program are already showing signs of making a positive impact on the AFRC workforce.

rooms↗

NASA NTRS2018

Evaluation of the Validity of Bio-Mathematical Models in Predicting Fatigue in an Operational Environment

During long-duration spaceflight missions, crewmembers and ground-support staff experience irregular sleep schedules, erratic natural light patterns, and high workload due to mission demands. Such conditions can cause circadian misalignment and sleep loss, which in turn cause deficits in cognitive performance. While bio-mathematical models have been implemented within workplace settings to predict fatigue profiles, the accuracy of sleep-wake models under conditions of non-traditional shiftwork is little known. Thus, the present study aims to evaluate the validity of four sleep-wake models (e.g., SAFTE-FAST, the Unified Model of Performance, the Adenosine-Circadian Model, and the State-Space Model) designed to predict human performance and fatigue levels against objective measures of performance in a spaceflight analog. To accomplish this aim, we will collect Psychomotor Vigilance Task (PVT) data from four crews (n=16) in the Human Exploration Research Analog (HERA) over 45 days. HERA is a closed, 3-story habitat at Johnson Space Center where inhabitants are exposed to extreme space exploration scenarios under varying sleep-wake conditions. The PVT is a simple reaction time test that involves minimal learning, making it sensitive to the effects of sleep loss and circadian misalignment. Findings from this study will help inform work scheduling and implementation of effective countermeasures (e.g., caffeine, lighting) to improve work efficiency and combat fatigue, as well as offer valuable insight into the applicability of bio-mathematical fatigue models in future space exploration missions.

fatigue↗

NASA NTRS2019

Preparing Students to Work in Diverse Settings and Across Distance: Inter-University, Interdisciplinary Capstone Teams

NASA's Psyche Mission is engaged with a growing number of capstone teams pursuing topics relevant to the mission, including partnering with four universities to trial cross-university teaming. Creating interdisciplinary capstone teams with students from different universities provides an opportunity to prepare students to engage with a diversity of disciplines and collaborate in remote teams in the workplace. Additionally, through such capstones, universities may gain access to non-local, specialized technical mentors and to disciplines not offered at their institutions. An added benefit is providing greater fidelity to NASA space missions, which involve teams working together at a distance. We discuss early lessons learned from the first three inter-university, interdisciplinary capstone teams participating with the Psyche mission and discuss plans for improvement and future expansion.

Bowman, C. D. D.↗

NASA NTRS2019

Characterization and Measurement of Spacecraft Airborne Particulate Matter

The International Space Station (ISS) gives a 6-member astronaut crew the ability to live and work in low Earth orbit. It is a unique indoor environment, which has served as both home and workplace to over 230 people since the year 2000. In this low gravity environment, smoke does not rise and cookie crumbs do not settle the way they do on Earth, causing airborne particulate matter, or aerosols, to behave differently and pose unique hazards for crew members. In its existence, virtually the same volume of ISS air has been continuously conditioned and ‘revitalized,’ including the removal of particles by filtration. While gaseous constituents of ISS air are monitored meticulously, sparse data exists on the indoor aerosols. The quantity and types of ISS airborne debris have been investigated in NASA’s Aerosol Sampling Experiment. Both active and passive samplers successfully collected airborne particulate matter in U.S. segments of the ISS, which were returned to Earth for characterization by microscopy and other techniques. The resulting data has informed the design of candidate particle instruments for spacecraft. In 2020, a reference-quality aerosol instrument will be flown to ISS, and will provide real-time data of particle concentrations in various modules. Smaller, more compact instruments will be necessary in future space missions, for example, in smaller vehicles, in habitats on lunar and planetary surfaces with ubiquitous dust, and also for use as wearable technology throughout missions. Miniaturized aerosol sensors, though lower fidelity than reference-quality instruments, can monitor the environment well when calibrated appropriately. Indoor air quality in spacecraft is fundamentally important to human health and comfort, and several particulate monitoring technologies will be at sufficient technology readiness levels for operational use within the next two years. Results of the Aerosol Sampling Experiment will be presented, along with the status of NASA’s aerosol instrument technology demonstrations on ISS.

Meyer, Marit E.↗

NASA NTRS2018

Working at the Speed of Innovation: Impedance Mismatch in Rapid and Innovation Projects

In this paper we report on the results of an ethnographic study of a rapid design innovation (RDI) experiment in NASA Aeronautics. This work is based on the study of the Aeronautics Autonomy Testbed Capability (AATC) team in the Convergent Aeronautics Solutions (CAS) project. This paper focuses on and summarizes one of the key over-arching findings from the study: there is a significant mismatch in the organizational culture in the rest of the organization compared with that required for RDI. And, if this organizational cultural mismatch is not addressed, the likelihood of any organization being able to advance a new and different type of work (such as RDI) will be jeopardized. We delineate several aspects of the two different cultures identified in order to enable leaders and practitioners to better understand what contributes to the cultural dissonance and the implications of the differences in the cultures. As well, we identify ways in which those differences can be addressed. Research from organization and other social sciences are incorporated to highlight the differences. The implications of the research suggest that the significant cultural differences trigger a strong and resistive response from the dominant culture that may negate leadership’s strategy to build the new capacity for RDI. While the research results noted the pervasive nature of innovation throughout the workplace, the type of innovation envisioned in RDI is a rare type of innovation that requires significantly new methods, work processes, tools, and skills such that approaches used in the dominate culture cannot be adopted by expediting the existing approaches. Examples include: innovation teaming and leadership; the need for adaptive leadership that changes the relationship of a research leader to the other researchers; and, an interdisciplinary teaming approach which shapes team relationships and activities. Each of these aspects requires new teaming, tools, and skills in order to succeed. Thus, when introducing RDI activities where there is a different dominant culture, teams need to be: well trained; protected; recognized and rewarded. And, team leaders must also be trained in the unique types of teaming and innovation tools used in RDI. Both RDI teaming and team leadership must be sanctioned, supported, and rewarded by leadership. Because of the cultural mismatch, in some organizations looking to add RDI to their existing and established organizations, sep to avoid or mitigate the negative impact of the culture mismatch.

Crain, Cathleen↗

NASA NTRSDate not supplied

A Machine-Learning Approach to Assess Aircraft Engine System Performance

Artificial intelligence (AI)/machine learning, and big data are transforming the global business environment. They have become the most disruptive technologies for organizations to improve workplace efficiency and productivity. This work explored the application of machine learning-based predictive analytics that would enable aircraft engine designers to estimate engine system performance quickly during the conceptual design stage. Supervised machine-learning algorithm was employed to study patterns in an existing database of production and research turbofan engines, and built predictive analytics for use in predicting system performance of new turbofan designs. Specifically, the author developed deep-learning analytics to predict turbofan system weight, using turbofan design parameters as the input. The predictive analytics were trained and deployed in Keras, an open-source neural networks API (application program interface) written in Python, with TensorFlow (an open-source artificial AI library developed by Google) serving as the backend engine. The current engine-weight prediction results, together with those for the TSFC (thrust specific fuel consumption) and core-size predictions that were studied previously by the author, show that machine learning-based predictive analytics can be an effective, time-saving tool for aircraft engine design-space exploration during the conceptual design stage. It would enable expeditious identification of the best engine design amongst several candidates.

Michael T Tong↗

NASA NTRSDate not supplied

Conducting Feasibility Studies in a Virtual World: Lessons Learned and Emerging Best Practices from the NASA DEVELOP Program

In response to new workplace realities, the NASA DEVELOP National Program pivoted from co-locating students, emerging professionals, and science advisors to bringing together virtual teams from across the United States. In its spring 2020 term, rapidly evolving circumstances required an ad-hoc roll-out of a virtual approach to complete the spring projects. Based on the experience from the spring term and a few weeks of planning, DEVELOP then conducted a fully virtual summer term with features such as 1) online collaboration tools, 2) virtual machines for analysis, and 3) streamed training offerings, including DEVELOP’s first ever program-wide Software Carpentry workshop. This full term of bringing together remote actors to select, build, and manage teams brought many challenges. Summer feedback has influenced planning for the fall 2020 term and process improvement is ongoing. This presentation will highlight lessons learned throughout this period of rapid change. Feedback from spring and summer terms and the Software Carpentry workshop will be summarized. Beyond participant impacts, there will also be discussion of effects on project results and partner experience. Final takeaways will focus on best practices that have been distilled for virtually-conducted feasibility studies.

NASA DEVELOP↗

NASA NTRS2021

NASA Space Cancer Risk Model: 2020 Operational Implementation

Astronauts are exposed to increased radiation from the space environment and from biomedical research studies conducted in the workplace. Federal requirements mandate that these exposures be limited to provide adequate radiation protection1. This report summarizes the National Aeronautics and Space Administration (NASA) Space Cancer Risk (NSCR) model as implemented in 2020 for calculation of risk of exposure-induced death (REID) and risk of exposure-induced cancer (REIC) following occupational radiation exposures for astronauts.

space radiation↗

NASA NTRS2021

COVID-19 Lockdowns Drive Decline in Active Fires in Southeastern United States

Fire is a common ecosystem process in forests and grasslands worldwide. Increasingly, ignitions are controlled by human activities either through suppression of wildfires or intentional ignition of prescribed fires. The Southeastern United States leads the nation in prescribed fire, burning ca. 80% of the countries extent annually. The COVID-19 pandemic radically changed human behavior as workplaces implemented social-distancing guidelines and provided an opportunity to evaluate relationships between humans and fire as fire management plans were postponed or cancelled. Using active fire data from satellite-based observations, we found that in the Southeastern United States, COVID-19 led to a 21% reduction in fire activity compared to the 2003-2019 average. The reduction was more pronounced for federally managed lands, up to 41% below average compared to the past 20-years (38% below average compared to the past decade). Declines in fire activity were partly affected by an unusually wet February before the COVID-19 shutdown began in mid-March 2020. Despite the wet spring, the predicted number of active fire detections was still lower than expected, confirming a COVID-19 signal on ignitions. In addition, prescribed fire management statistics, reported by US federal agencies, confirmed the satellite observations, and showed that following the wet February and before the mid-March COVID-19 shutdown, cumulative burned area was approaching record highs across the region. With fire return intervals in the Southeastern United States as frequent as 1-2 years, COVID-19 fire impacts will contribute to an increasing backlog in necessary fire management activities, affecting biodiversity and future fire danger.

Biological Sciences↗

NASA NTRSDate not supplied

Braving Diversity

Organizations benefit when the workplace climate is inclusive and supportive of diverse staff. A healthy workforce climate benefits from increased staff awareness of potential issues, examining cultural norms and traditions, and an active willingness to discuss uncomfortable topics with care and respect.

C Shupla↗