Scaling Productivity and Innovation on the Path to Exascale with a ?Team of Teams? Approach.
Abstract not provided.
Raybourn, Elaine M.↗
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Enabling coordinated, distributed development of scientific software: A research agenda for adapting a team of teams approach
The “team of teams” concept is a strategy for coordinating activities within and across organizations, developed by General Stanley McChrystal and his colleagues based on their experiences leading the Joint Special Operations Task Force in Iraq from 2003-2008. These experiences, and the lessons learned from them, are recounted in the books Team of Teams (McChrystal 2015) and One Mission (Fussell 2017) (the authors and contributors to these books will hereafter be jointly referred to as McChrystal et al.). Essentially, their story is one of rapidly adapting a rigid, siloed organization to defeat the flexible, resilient, and fast-moving network of Al Qaeda in Iraq. As described in the books, when McChrystal took over the Task Force, he found a collection of highly competent, efficient teams of analysts and warfighters which nonetheless had difficulty operating in a unified manner due to close internal ties, distrust of outsiders, bureaucratic stove pipes, and cultural differences stemming from the diverse organizations Task Force teams were affiliated with, including Army Special Forces, CIA, and NSA.
97 MATHEMATICS AND COMPUTING↗
“Shoulda, Coulda, Woulda”: Conceptualizing the Differences in Trust Between Human-Human Teaming and Human-Machine Teaming
Intelligent decision support systems (IDSSs) are machine teammates designed to facilitate better human decision-making in high-consequence domains such as health care, power grid operations, and fraud detection. IDSSs identify patterns in datasets and provide intelligent decision-making recommendations to human teammates. However, previous research indicates that humans often trust IDSS recommendations less than the recommendations from their human teammates, even when the machine teammate is more accurate. To conceptualize why trust differs, we review the literature surrounding trust, error, and predictability. Then, we compile and compare participant trust ratings and decision-making in an abridged systematic review of previous studies manipulating teammate type, error rate, and error type. Finally, we conduct a content analysis of participants’ qualitative responses to trust queries from a survey on generative language models. Results suggest that humans may trust IDSS teammates less than other human teammates because of differences in (1) interaction complexity, (2) blame attribution, and (3) swift trust. We conclude that human factors practitioners should collaborate with data scientists and domain experts to build and maintain trust in IDSSs by anthropomorphizing algorithms, matching mental models, and considering individual differences.
97 MATHEMATICS AND COMPUTING↗
Red Teaming in the Age of IOT Thoughts on Framing the Next Generation of Technical Vulnerability Assessment.
Abstract not provided.
Craft, Richard L.↗
Enhancing Productivity and Innovation in ECP with a Team of Teams Approach.
Abstract not provided.
Moulton, David↗
A Data-driven Approach to Rethinking Open Source Software Organizations as a Team of Teams.
Abstract not provided.
Raybourn, Elaine M.↗
Team Dynamics and Development in Chemical Emergency Response
This presentation is focused on Team Dynamics and Development in Chemical Emergency Response. While regulatory requirements focus on defining the performance requirements associated with this category of response team, there is very little information and guidance provided to team leaders on the criticality of team dynamics of development in performance. These elements are essential to achieving successfully integrated team operations. NREL has worked to expand chemical response team participation to include operational personnel from research, support operations, and various technical areas. Since this team expansion has encompassed integration from numerous levels and areas within the organization, a systematic approach was adopted to better understand how organization culture, dynamics, and diversity can be used to be more effective. Benchmarking other organizations and reviewing relevant literature assisted in laying the foundation to develop a strategy that incorporates team development principles, dynamics, and leadership practices to increase the effectiveness of emergency response operations. This presentation focuses on the valuable lessons learned and the team-based approaches that can be used to develop a successful response team.
emergency response↗
ESGF project plan for ramping down development activities and transition the project and data to a new team
This document summarizes the current software development activities carried by the ESGF team with planned delivery dates before the transition of the project to a new team. The work we started on the publishing, search and retrieval, and the backend for indexing and data management that can be deployed using Kubernetes are planned to be delivered within the next three months; however, this assumes that the current team members will continue to work on the project. The activities are listed in Table 1 by priority and in case we lose team members, development of lower priority tasks can be paused and passed to the new team with its current status. Team members can be re-assigned based on their availability and transition work needed. Table 2 below describe activities necessary to help project transition to the new team. Deadlines for these activities are before October 1 st of 2022 or the completion of a successful transition. Support during the transition period assumes that we will have 3 key ESGF members and the ESGF PI supported at the 50% level or less for the duration of the transition. The level of support is an estimate, and it depends on several factors that cannot be decided at this time. The total cost of the proposed work and support activities for fiscal year 2021 is $1,270K with $230K carry over to fiscal year 2022. The cost for the support work listed in Table 2 is the sum of the two rows “HW support” and “project support, maintenance, and transition efforts”, colored blue, in Table1 which adds up to $720K. This cost is included in the $1,270K cost in table 1.
97 MATHEMATICS AND COMPUTING↗
Savannah River National Laboratory Collaborative Innovation Pilot Team - 17560
The Collaborative Innovation (COIN) program was established by the Savannah River National Laboratory (SRNL) in March 2016. The goal of the SRNL COIN program is to identify innovative options to significantly reduce program and project risks (improve safety, reduce schedule and cost) of high priority Department of Energy Environmental Management, National Nuclear Security Administration, and Nuclear Energy missions. The COIN Advisory Board selected as the target outcome of the first COIN effort a 50% improvement to the Savannah River Site (SRS) H-Canyon spent nuclear fuel (SNF) processing 'baseline,' or current plan, as defined in the SRS Nuclear Materials Planning Roadmap. A small team of SRNL and Savannah River Nuclear Solutions personnel with pertinent experience and expertise was co-located and largely sequestered for eight weeks to identify improvements to H-Canyon processing of SNF. Following the process defined in the SRNL COIN Charter, the COIN Pilot Team analyzed the baseline for processing SNF through H Canyon; generated alternative ideas; tested seemingly viable ideas by reaching out to other subject-matter experts; and identified options for consideration for implementation by the COIN Advisory Board. The COIN Pilot produced a number of important outcomes, including important lessons learned for subsequent COIN efforts. The two principal outcomes are these: 1. The COIN Pilot Team conducted a comprehensive examination of the individual unit operations, the integrated system, and external interfaces to produce a timeline of H-Canyon processing and sampling times that had not previously existed. The general timeline served as the baseline from which the Pilot Team identified processing improvements. In addition, the timeline has already been employed in other planning efforts. 2. The COIN Pilot Team determined that innovations to the H-Canyon Dissolving unit operation alone could increase the number of SNF bundles processed through H Canyon by the target of 50%, but with little margin for error. To ensure that the gains in throughput in the Dissolving unit operation would be maintained throughout the facility, the Pilot Team identified four additional improvements to create greater efficiency and flexibility in downstream H-Canyon unit operations. The COIN Pilot Team's innovations reduce the processing time of a single batch of SNF through H Canyon from about 70 days to about 50 days. This talk will review the COIN process and the results of the pilot of the process. (authors)
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Collaborative Management for Complex Closure Teams - 19246
The closure documentation for government waste management sites requires a multidisciplinary approach to achieve success. This approach is necessary and similar to approaches utilized across remediation projects in the private and public sectors [1]. Closure documentation for government projects can range from tens of pages to upwards of thousands of pages. They normally take more than six months to put together - although, in many cases, it takes years - with multiple revisions. These documents, while all unique, share common themes with regards to communication and conflict with the other waste management projects. This paper explores the challenges in management and leadership approaches for generating technical documents, such as those found in the closure missions at government hazardous waste management sites. These matrixed teams are composed of many different members with varying expertise and experience, each with different stakeholder backgrounds. These teams experience challenges not only from using a matrixed approach - where the majority of the members are only partially engaged in the project - but also from integrating each of their respective stakeholder group's cultural individualities [2]. The Project Leads, who head up these highly matrixed projects, operate in environments comprised of virtual project teams- or more specifically in this context, intensive virtual project teams. Most of the participants are within the same city, but all of the document project teams operate with some level of organizational dispersion. Moreover, the larger a project becomes the more dispersed the team becomes. The frequent addition of sub-contracting resources by Project Leads further disperses the group and dilutes communication. The difficulties in communication derive from complications in the goal setting stages of a project and can manifest across the project team in the form of motivational issues, disengagement, quality expectations, and a loss of understanding. This puts a considerable amount of importance on a Project Lead to establish goals through the appropriate tools and methodology. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Team Massachusetts & Central America Solar Decathlon 2015 Final Technical Report
Our team was Team MASSCA (Massachusetts and Central America), which was a partnership of Western New England University (WNE) located in Massachusetts USA, The Technological University of Panama (UTP), and Central American Technological University (UNITEC) of Honduras. Together we had a group of 6 faculty members and approximately 30 undergraduate students. Our house is ‘The EASI’ House, which stands for Efficient, Affordable, Solar Innovation. The EASI house is rectangular with two bedrooms and one bath, and offers a total square footage of 680. Based on competition estimates, The EASI house costs roughly $121,000. The EASI house has a 5kW solar system. Faculty and students from all three institutions were represented at the competition in Irvine California. Team MASSCA did well considering this was our first entry in the Solar Decathlon competition. Team MASSCA won the following awards: First Place – Affordability Contest Second Place – Energy Balance Contest. The competition provided a great experience for our students (and faculty as well). This competition provided leadership, endurance, and technical knowledge/skills for our students, and was the single most important hands-on experience during their undergraduate years. We are extremely pleased with the awards we received. At the same time we have learned from our efforts and would do better if we were to compete in the future. Furthermore, as a result of our team’s Inter-Americas collaborative effort, UTP and WNE have partnered to form Team PANAMASS (PANAma and MASSachusetts) and have developed The 3 SMART House for the inaugural Solar Decathlon Latin America & Caribbean competition held in Colombia.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Characterizing Interaction Uncertainty in Human-Machine Teams
With the increasing use and adoption of artificial intelligence (AI), the reliability of modern data systems will be driven by a tighter teaming between human experts and intelligent machine teammates. As in the case of human-human teams, the success of human-machine teams will also rely on clear communication about mutual goals and actions. In this paper, we combine related literature from cognitive psychology, human-machine teaming, uncertainty in data analysis, and multi-agent systems to propose a new form of uncertainty: interaction uncertainty for characterizing bidirectional communication in human-machine teams. We map the causes and effects of interaction uncertainty and outline potential ways to mitigate uncertainty for mutual trust in a high-consequence real-world scenario.
uncertainty, data analytics, interaction, trust, h↗
Level-2 Milestone 5588: Deliver Strategic Plan and Initial Scalability Assessment by Advanced Architecture and Portability Specialists Team
This report documents the fact that the work in creating a strategic plan and beginning customer engagements has been completed. The description of milestone is: The newly formed advanced architecture and portability specialists (AAPS) team will develop a strategic plan to meet the goals of 1) sharing knowledge and experience with code teams to ensure that ASC codes run well on new architectures, and 2) supplying skilled computational scientists to put the strategy into practice. The plan will be delivered to ASC management in the first quarter. By the fourth quarter, the team will identify their first customers within PEM and IC, perform an initial assessment and scalability and performance bottleneck for next-generation architectures, and embed AAPS team members with customer code teams to assist with initial portability development within standalone kernels or proxy applications.
97 MATHEMATICS AND COMPUTING↗
Using AI Simulations to Dynamically Model Multi-agent Multi-team Energy Systems
The complexity of energy systems is well known as they are complex and intricate systems. As a result, many extant studies have used many simplifications or generalizations that do not accurately reflect the nature of this complex system. In particular, most HVAC systems are modeled as a single unit, or several large units, rather than as a hierarchical composite (e.g., as a floor rather than as a collection of disparate rooms). The net result of this is that the simulations are too generic to perform meaningful analysis, machine learning, or integrated simulation. We propose using a multi-agent multi-team strategic simulations framework called SiMAMT to better define, model, simulate, and learn the HVAC environment. SiMAMT allows us to create distinct models for each type of room, hierarchically aggregate them into units (like floors, or sections), and then into larger sets (like buildings or a campus), and then perform a simulation that interacts with each sub-element individually, the teams of sub-elements collectively, and the entire set in aggregation. Further, and most importantly, we additionally model another ‘team’ within the simulation framework - the users of the systems. Again, each individual is modeled distinctly, aggregated into sub-sets, then collected into large sets. Each user, or agent, is performing on their own but with respect to the larger team goals. This provides a simulation that has a much higher model fidelity and more applicable results that match the real-world.
Franklin, D. Michael↗
Review Team Focused Modeling Analysis of Radial Collector Well Operation on the Hypersaline Groundwater Plume beneath the Turkey Point Site near Homestead, Florida
Researchers at Pacific Northwest National Laboratory served as members of a U.S. Nuclear Regulatory Commission review team for the Florida Power & Light Company’s application for two combined construction permits and operating licenses (combined licenses or COLs) for two proposed new reactor units—Turkey Point Units 6 and 7. The review team evaluated the environmental impacts of the proposed action based on the October 29, 2014 revision of the COL application, including the Environmental Report, responses to requests for additional information, and supplemental information. As part of this effort, team members tasked with assessing the environmental effects of proposed construction and operation of Units 6 and 7 at the Turkey Point site reviewed two separate modeling studies that analyzed the interaction between surface water and groundwater that would be altered by the operation of radial collector wells (RCWs) at the site. To further confirm their understanding of the groundwater hydrodynamics and to consider whether certain actions, proposed after the two earlier modeling studies were completed, would alter the earlier conclusions documented by the review team in their draft environmental impact statement (EIS; NRC 2015), a third modeling analysis was performed. The third modeling analysis is discussed in this report.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗