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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

The NASA DEVELOP Model: Multidisciplinary Teams Conduct Interdisciplinary Projects to Produce Transdisciplinary Outcomes

The DEVELOP Program, part of NASA’s Earth Applied Sciences’ Capacity Building Program, conducts 50-70 feasibility studies each year that utilize Earth observations to address local decision-making challenges and help inform action. DEVELOP uses these projects as the mechanism to build skills in its participants and partner organizations to assess and apply satellite data insights to environmental decision-making processes. While organized by thematic focus (ex. water resource management, ecological forecasting, disaster management), projects use a multidisciplinary team approach with teams of students, recent graduates, early career professionals, and transitioning career professionals, bringing different disciplines, life experience, and perspectives to execute projects that have been collaboratively designed with end-user partner organizations (federal agencies, state and local governments, non-profit and for-profit organizations, and international organizations). Projects are interdisciplinary in nature as they integrate methods from multiple disciplines, with a focus on the incorporation of satellite data with other data sources such as socioeconomic and demographic data, in situ measurements, model outputs, and partners’ knowledge, and take place under the guidance of science advisors from NASA, academia, and other partner organizations. The culmination of these multidisciplinary teams working on projects that draw from interdisciplinary methods and approaches, is a transdisciplinary solution for the partner organizations to explore further for potential adoption. This presentation will highlight the DEVELOP model of co-production and collaboration, lessons learned integrating people and project methodologies, and impact assessment activities surrounding the program’s efforts.

Capacity Building↗
NASA NTRSDate not supplied

Artemis Internal Science Team: Mission Planning Update

As eloquently outlined in the Artemis III Science Definition Team (A3SDT) Report, the definitive statement of science priorities for the first crewed landing of the Artemis program, the return of astronauts to the surface of the Moon is expected to yield paradigm-shifting scientific advances across a wide array of scientific disciplines while facilitating the creation of a thriving cislunar economy. To help establish a cohesive management for the Artemis campaign, the NASA Science Mission Directorate (SMD) and the Exploration Systems Development Mission Directorate (ESDMD) have established an Artemis Internal Science Team to complement future competed surface geology and payload science teams while executing critical programmatic functions at the point of hardware element interface decisions. Here, we describe aspects of Artemis III mission planning, specifically the current progress towards selection of candidate exploration regions for the Artemis III mission.

Artemis↗
DOE OSTI2019

System and method for operator control of heterogeneous unmanned system teams

A control architecture and associated control methods are under development to allow a single user to control a team of multiple heterogeneous UMS as they conduct multi-faceted (i.e. multi-objective) missions in real time is disclosed. The control architecture is hierarchical, modular and layered and enables operator interaction at each layer, ensuring the human operator is in close control of the unmanned team at all times. The architecture and key data structures are introduced. Two approaches to distributed collaborative control of heterogeneous unmanned systems are described, including an extension of homogeneous swarm control and a novel application of distributed model predictive control. Initial results are presented, demonstrating heterogeneous UMS teams conducting collaborative missions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

High Performance Teams Enable Mission Success for SRNL - 16363

The accomplishment of the DOE EM mission of cleaning up the radioactive waste generated as a byproduct of the development and maintenance of nuclear materials over the last 60 years is a daunting task. SRNL specializes in working directly with the 'owners' of the cleanup challenges to identify the desired outcome and develop a solution that can be put into practice. 'We put science to work' is not just a 'tag line' rather it is a concise statement of our values and approach to applying science and engineering to the cleanup objectives. The management of radioactive waste poses multi-decade challenges to DOE EM and the Nation. The ability to harness the depth of knowledge, experience, expertise and passion for safely and effectively solving the technical challenges has reached a critical junction. Perhaps too late to be a natural and organic transition the industry finds itself critically devoid of resources to effectively and efficiently keep focused on the highest order task: cleanup. When project managers plan the resources necessary to perform the planned scope they typically are focused on financial, human, and industrial resources that would be beneficial to project execution. The critical shortage we will be evaluating is experienced and skilled leaders, mentors and coaches in the workforce. The production of educated scientists and engineers is a primary focus at all levels of educational institutions with Science Technology Engineering and Mathematics (STEM) focused curricula beginning in elementary school. The need for leaders who are skilled in inspiring organizational creativity, adept in harnessing and focusing individual energy while effectively communicating to the work force and the clientele equally compelling messages, has never been greater, or their absence in the workforce more ominous. Managers trained in the classical management theory (insert references here) are aging out of the workforce. In many cases these managers have not retained close connection to advancements in their primary field of study but rather have succumbed to the administrivia burdens that typify highly regulated work. The current technically trained workforce while interested in the 'perks' of management (i.e. visibility, pay increases, advancing status) are driven to keep close connection to their technical 'roots' as a fall-back plan should they need to change their career path either by choice or necessity. The challenge is how to achieve the productive hum of a finely tuned organizational model that blends executive vision and drive with technical leadership and excellence in execution. If any of these three tenets of a high performance team falters the ability to recover erodes the performance of the team and begins to weaken the cultural foundation essential to sustaining high performance work teams. At SRNL, recognition of the need to adapt the management dynamics and the business model and to harness the energy of the workforce to sustain - and in fact increase - the level of performance is a driving force in the transformation of the organization. Examples of changes in organizations structure, business systems and employee engagement are discussed as they relate to the impact on accomplishing the cleanup mission and fostering the next generation of great leaders and innovators. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Environmental Management Waste Management Facility Operations Team Commitment to Safety - 18546

The Environmental Management Waste Management Facility (EMWMF) is an above-grade waste disposal facility that is owned by DOE and operated by URS | CH2M Oak Ridge LLC (UCOR), a contractor to DOE's Oak Ridge Office of Environmental Management. The EMWMF landfill is located on the Oak Ridge Reservation (ORR) and has a 2.18 M cubic yard capacity. EMWMF is a key component of the cost-effective ORR cleanup program and accepts remediation waste from across the ORR. Multiple low-level and low-level mixed CERCLA waste streams are disposed at EMWMF, mostly as direct-dumped demolition and remediation debris. EMWMF receives and disposes of a myriad of contaminated waste streams and waste types, including massive structural steel from some of the largest buildings ever constructed, contaminated soils from legacy disposal areas, containers that must be grouted under negative pressure, and special waste that must be tightly controlled. Support activities include managing several million gallons of landfill wastewater per year and driving around 20,000 miles per year to transport leachate to a treatment facility. Even with the wide range of waste accepted and the diversity of support activities, EMWMF Operations has maintained an impressive safety record of no lost workday cases in nearly 16 years of continuous operation and was recently awarded the National Safety Council's Superior Safety Performance Award. This safety record is a testament to the commitment to safety by both workers and management. Several factors are key to the EMWMF Operations safety record. UCOR senior management established safety as a priority and allocates proper funding and resources. EMWMF Operations management embraces safety as an integral part of the work and also 'walks the talk'-emphasizing safety over productivity and showing personal commitment to safety. A stable workforce promotes a culture where safety is valued and helps train new personnel in this culture. The UCOR integrated safety management approach to work control is fully embraced, where worker feedback is highly valued and used to better identify and control job hazards. Finally, job supervisors actively encourage input. Worker concerns, suggestions, and observations are encouraged and positively addressed. As a result, the entire Operations Team is committed to identifying and mitigating hazards. This team commitment to safety results in a culture where safety is not only valued, but is expected. Safety concerns are identified and addressed proactively, and communication is encouraged. This strong safety culture and outstanding safety record have also proven to be good business, with the facility available to receive waste 99.6% of available work hours and outstanding turnaround times on waste shipments. The EMWMF Operations team commitment to safety can be used in other environments to develop an engaged, safety-conscious workforce. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Report of the 2025 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science

This report summarizes insights from the 2025 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science, which convened more than 40 experts from national laboratories, academia, industry, and community organizations to chart a path toward more powerful, sustainable, and collaborative scientific software ecosystems. To address urgent challenges at the intersection of high-performance computing (HPC), AI, and scientific software, participants envisioned agile, robust ecosystems built through socio-technical co-design—the intentional integration of social and technical components as interdependent parts of a unified strategy. This approach combines advances in AI, HPC, and software with new models for cross-disciplinary collaboration, training, and workforce development. Key recommendations include building modular, trustworthy AI-enabled scientific software systems; enabling scientific teams to integrate AI systems into their workflows while preserving human creativity, trust, and scientific rigor; and creating innovative training pipelines that keep pace with rapid technological change. Pilot projects were identified as near-term catalysts, with initial priorities focused on hybrid AI/HPC infrastructure, cross-disciplinary collaboration and pedagogy, responsible AI guidelines, and prototyping of public-private partnerships. This report presents a vision of next-generation ecosystems for scientific computing where AI, software, hardware, and human expertise are interwoven to drive discovery, expand access, strengthen the workforce, and accelerate scientific progress.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Function allocation for humans and automation in the context of team dynamics

Within Human Factors Engineering, a decision-making process called function allocation (FA) is used during the design life cycle of complex systems to distribute the system functions, often identified through a functional requirements analysis, to all human and automated machine agents (or teammates) involved in controlling the system. Most FA methods make allocation decisions primarily by comparing the capabilities of humans and automation, but then also by considering secondary factors such as cost, regulations, and the health and safety of workers. The primary analysis of the strengths and weaknesses of humans and machines, however, is almost always considered in terms of individual human or machine capabilities. Yet, FA is fundamentally about teamwork in that the goal of the FA decision-making process is to determine what are the optimal allocations of functions among agents. Given this framing of FA, and the increasing use of and sophistication of automation, there are two related social psychological issues that current FA methods need to address more thoroughly. First, many principles for effective human teamwork are not considered as central decision points or in the iterative hypothesis and testing phase in most FA methods, when it is clear that social factors have numerous positive and negative effects on individual and team capabilities. Second, social psychological factors affecting team performance and can be difficult to translate to automated agents, and most FA methods currently do not account for this effect. The implications for these issues are discussed.

Automation↗
DOE OSTI2022

A branch-and-price algorithm for a team orienteering problem with fixed-wing drones

This paper formulates a team orienteering problem with multiple fixed-wing drones and develops a branch-and-price algorithm to solve the problem to optimality. Fixed-wing drones, unlike rotary drones, have kinematic constraints associated with them, thereby preventing them to make on-the-spot turns and restricting them to a minimum turn radius. This paper presents the implications of these constraints on the drone routing problem formulation and proposes a systematic technique to address them in the context of the team orienteering problem. Furthermore, a novel branch-and-price algorithm with branching techniques specific to the constraints imposed due to fixed-wing drones are proposed. Extensive computational experiments on benchmark instances corroborating the effectiveness of the algorithms are also presented.

42 ENGINEERING↗
DOE OSTI2026

Report of the 2026 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science

Scientific computing is undergoing rapid transformation as advances in artificial intelligence, heterogeneous computing, automation, and data-intensive research reshape not only computational tools but also the institutions, workforce models, and collaborative practices that support scientific discovery. This report synthesizes insights from the 2026 Workshop on Next-Generation Ecosystems for Scientific Computing, the second in a three-year series focused on strengthening scientific computing ecosystems through socio-technical co-design. Workshop discussions identified four interdependent strategic themes: software ecosystems for AI-enabled scientific discovery; trust, validation, and traceability; human-AI teaming and paradigm shifts; and workforce, pedagogy, and governance. The report translates these themes into eight priorities for community action spanning shared research infrastructure, trust and traceability, user experience, human-AI teaming, workforce development, cross-sector coordination, stewardship and sustainability, and evaluation of scientific value. Together, these priorities outline directions for building scientific computing ecosystems that remain trustworthy, sustainable, innovative, and resilient as AI assumes a growing role in scientific work.

AI↗
NASA NTRS2018

Human Automation Teaming: Lessons Learned and Future Directions

Full autonomy seems to be the goal for system developers in almost every area of the economy. However, as we move from automated systems to autonomous systems, designers have needed to insert humans to oversee automation that has traditionally been brittle or incomplete. This creates its own problems as the operator is usually out of the loop when the automation hands over problems that it cannot handle. To better handle these situations, it has been proposed that we develop human automation teams that have shared goals and objectives to support task performance. This paper will describe an initial model of Human Automation Teaming (HAT) which has three elements: transparency, bi-directional communications, and human-directed execution. Transparency in our model is a method for giving insight into the reasoning behind automated recommendations and actions, bi-directional communication allows the operator to communicate directly with the automation, and finally the automation defers execution to the human. The model was implemented through a number of features on an electronic flight bag (EFB) which are described in the paper. The EFB was installed in a mid-fidelity flight simulator and used by 12 airline pilots to support diversion decisions during off-nominal flight scenarios. Pilots reported that working with the HAT automation made diversion decisions easier and reduced their workload. They also reported that the information provided about diversion airports was similar to what they would receive from ground dispatch, thus making coordination with dispatch easier and less time consuming. These HAT features engender more trust in the automation when appropriate, and less when not, allowing improved supervision of automated functions by flight crews.

Human-Autonomy Teaming↗
NASA NTRSDate not supplied

Problem Complexity and LLM: H-M Team Reliability in Challenging Environments

In traditional human-machine operations, the functional decomposition of actions and responsibilities among various agents is assigned a priori. For instance, in current air traffic operations, although assisted by software, human pilots have the ultimate control of aircraft. Multiagent human-machine and machine-machine systems will face problems of varying and potentially unpredicted complexity in future challenging scenarios of planetary, en route, and orbital activities. Hence, it is important to enable dynamic transfer of decision-making to appropriate team members, human or machine, depending on which agent is best equipped to solve that specific problem on a time budget. In this paper, we consider aspects of problem-solving and its modeling that affect the outcomes of decision-making as a function of solution quality and the likelihood of solving the problem on a required time budget. We focus on Large Language Models (LLM) as potential machine teammates and conclude that practical, predictive modeling of their performance, at the current stage of their development, is infeasible. Simple examples help us illustrate that current LLM will require fundamental advancements to provide reliable support in team decision-making, especially in safety-critical and time-critical domains. The study is not meant to diminish the value of the remarkable capabilities of LLM, but rather to gain a better understanding of the technology’s appropriate use and the needed additions.

function allocation↗
DOE OSTI2019

Opportunities and Challenges for Human-Machine Teaming in Cybersecurity Operations [Panel Discussion]

Many of the challenges associated with cybersecurity operations are also ripe opportunities for the application of human-machine teaming. Advances in cognitive science, artificial intelligence, and machine learning promise the technology to achieve the level of intelligence and sophistication necessary to create a true intelligent teammate. This panel gathers experts from across the community to discuss the challenges and opportunities for human-machine teaming in cybersecurity operations.

Cybersecurity, Human-Machine Teaming↗
DOE OSTI2018

Graphics to facilitate informative discussion and team decision making

Everyone knows the expression “A picture is worth a thousand words,” and this effectively summarizes the ability of graphical summaries to convey information and persuade. However, in many cases, the goal for the right visualization is to encourage and guide discussion while helping focus a team to make carefully considered, defensible, and data-driven decisions. The aims of graphics differ if we are trying to communicate the merits of a single choice versus outlining several contending alternatives for further comparison and discussion. These choices each have their own strengths and weaknesses depending on how we value different criteria. They also serve different purposes at various stages of decision making. Often the role of statisticians is not to provide a single answer but to provide rich information and summaries in a manageable and compact form to enable productive discussion among team members. Through a series of diverse examples, this work present principles and strategies for encouraging discussion and informed decision making and discuss how they can be integrated with versatile use of graphical tools for examining multiple objectives, framing trade-offs between alternatives, and examining the impact of subjective priorities and uncertainty on the final decision.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2018

Rejoinder to “Graphics to facilitate informative discussion and team decision-making”

We would like to thank Dr Dae-Heung Jang and Dr Jennifer Van Mullekom for their thoughtful discussions. We are encouraged that they share our vision for highlighting and expanding the role of graphics for improving team discussion and decision-making. Here we would like to respond to several comments that they made in their discussions: (1) how the availability of the third dimension in graphics can improve team members' ability to properly visualize and connect with the data, (2) the importance of developing dynamic and interactive graphics to allow exploration of questions as they emerge during the discussion, (3) the role of process and relationships in helping reach good decisions based on the developed objectives, and (4) the benefits of building a body of case studies on which those new to the methods can draw understanding.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2018

Bi-objective approaches for home healthcare medical team planning and scheduling problem

In this paper, we study the medical team planning and scheduling in home healthcare within a weekly horizon, including the planning of nursing visits and the daily traveling route scheduling. Two objectives are considered: the first one is to minimize the total operation cost of the healthcare agency and the second one is to maximize the patient satisfaction. The problem is formulated as a mixed integer program, to seek for a trade-off between two objectives, with the characteristics of the patient requirements including nursing types, nursing frequency and service length considered. Medical team types, available service days and overwork penalty are also respected in the model. Then an ϵ-constraint method is adopted to obtain exact non-dominated solutions. To address large-scale problem instances, three heuristic approaches are developed to generate approximate Pareto fronts in a reasonable time. The set of non-dominated solutions are valuable for decision-making. Computational experiments are conducted and the results demonstrate the efficiency of the approaches.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Challenges of and Opportunities for a Large Diverse Software Team

A large software team consisting of members with different expertise, skillsets, personalities, ethnicities, and involving collaboration on a large and complex software product presents many technical and cultural challenges, but also provides unique opportunities. In this article, we discuss the essential issues we faced when successfully transforming a collection of various independently developed software libraries into one large integrated product: the eXtreme-scale scientific Software Development Kit (xSDK). Furthermore, we argue it is just as important to pay attention to cultural challenges, such as establishment of reliable communication channels that considers, among others, differences in personalities and backgrounds as well as overcoming geographical separation and time-zone distribution when collaborating, as technical challenges. Finally, we discuss opportunities stemming from participating in a large diverse software team, such as increased internal expertise, variety of skillsets, broadened connections to external experts, and access to a larger pool of ideas or solutions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Dynamic Charging Rendezvous and Motion Planning for a Multi-AGV Team Including a Mobile Charging Host

Teams of automated battery-powered electric vehicles have the potential to execute complex mission tasks in off-road environments for agriculture, military, and other applications. Limited onboard energy reserves hinder their adoption in large-scale resource-constrained environments, where recharging is a necessity. It may be infeasible to install a network of static charging stations in off-road environments. For this reason, dedicated mobile host vehicles with charging capabilities are proposed as a means to increase range and capabilities of the multivehicle team. Here, in this study, we consider an ad hoc planning framework, where results from a high-confidence trajectory planner are leveraged to plan charging rendezvous between a host and other worker vehicles in a receding horizon fashion to provide high confidence that energy reserves will not be prematurely exhausted. The core problem is posed so as to minimize the impact of recharging on the mission in terms of task delays, overall energy utilization, and costs of fast charging. Through extensive Monte Carlo simulations of an off-road mission, we show a decrease in task delays without substantial increases in energy needs by updating the charging rendezvous plan during the mission. However, if updates are made too often, model mismatch may cause unnecessary cycling and mission failure.

Energy constraints↗