Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “distributed teams”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

BOREAS TF-4 CO2 and CH4 Soil Profile Data from the SSA

The BOReal Ecosystem-Atmosphere Study Tower Flux (BOREAS TF-4) team measured distributions of carbon dioxide (CO2) and methane (CH4) concentrations for the upper 5 m of soil and unsaturated zone at the mature stand, upper 6 m at the 20-year-old stand, and the upper 1 m at the 8-year-old stand and clear cut area at the BOREAS Southern Study Area (SSA) during August 1993 to March 1995. Particle size and carbon content of the unsaturated deposits, precipitation, soil temperature and moisture, carbon and oxygen isotopes of soil CO2, and soil water chemistry are also presented. The data are stored in tabular ASCII files.

Striegl, Robert↗
NASA NTRS2001

Advanced Engineering Environments: Implications for Aerospace Manufacturing

There are significant challenges facing today's aerospace industry. Global competition, more complex products, geographically-distributed design teams, demands for lower cost, higher reliability and safer vehicles, and the need to incorporate the latest technologies quicker all face the developer of aerospace systems. New information technologies offer promising opportunities to develop advanced engineering environments (AEEs) to meet these challenges. Significant advances in the state-of-the-art of aerospace engineering practice are envisioned in the areas of engineering design and analytical tools, cost and risk tools, collaborative engineering, and high-fidelity simulations early in the development cycle. These advances will enable modeling and simulation of manufacturing methods, which will in turn allow manufacturing considerations to be included much earlier in the system development cycle. Significant cost savings, increased quality, and decreased manufacturing cycle time are expected to result. This paper will give an overview of the NASA's Intelligent Synthesis Environment, the agency initiative to develop an AEE, with a focus on the anticipated benefits in aerospace manufacturing.

Thomas, D.↗
NASA NTRS1997

The Web Interface for Telescience (WITS)

The Web Interface for Telescience (WITS) is an Internet-based tool that enables members of geographically distributed science teams to participate in daily planetary lander and rover mission planning.

rovers sequence generation telescience↗
NASA NTRS2015

Effectiveness of Advanced Collaboration Tools on Crew Communication in Reduced Crew Operations

The present research examines operational performance and verbal communication in airline flight crews under reduced crew operations (RCO). Eighteen two-pilot crews flew six scenarios under three conditions; one condition involved current-day operations while two involved RCO. In RCO flights, the Captain initially operated the simulated aircraft alone but could request remote crewmember support as off-nominal events occurred and workload was expected to increase. In one of the two RCO conditions, crewmembers were provided with advanced prototype collaboration tools designed to alleviate difficulties in crew coordination. Crews successfully solved all challenging events without accident and analyses of operational performance did not reveal any differences among the three conditions. In RCO flights, crew communication increased when tools were available relative to flights in which they were not; specifically, there were more acknowledgements and decision-making communications. These results suggest the collaboration tools enable higher degrees of crewmember awareness andor coordination during distributed operations.

crew resource management↗
NASA NTRS2020

Pattern Identification - A Foundation for Research in the Emphasis of Design Patterns in Systems Engineering and Knowledge Capture

Pattern Language describes the morphology and functionality of a system in the absence of design particulars. Harnessing this capability will provide the Systems Engineering discipline a means of managing the development of increasingly complex systems with increasingly distributed design teams while capturing and retaining knowledge for future generations. Pattern Language is a syntax for describing, and structurally relating, design patterns. Design patterns contextually describe the application of domain knowledge in the engineered solution to the force balance problem. The parallels between pattern recognition and application, as a fundamental stage of human learning, and pattern observation within a complex system, suggests pattern language may be a valuable tool in the capture and dissemination of knowledge. Pattern application has enjoyed considerable study over the last several decades, however much of this work has focused on the replication of design particulars. This work returns to the roots of Pattern Language and explores the utility of patterns as an architectural description and guide, and knowledge capture method, for complex system development beginning with the identification of a time proven design pattern.

Russell, Samuel P.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-14454-DND

FUN3D Core Capabilities - Established as a research code in late 1980’s; now supports numerous internal and external efforts across the speed range - Solves 2D/3D steady and unsteady Euler and RANS equations on node-based mixed element grids for compressible and incompressible flows - General dynamic mesh capability: any combination of rigid / overset / morphing grids, including 6-DOF effects - Aeroelastic modeling using mode shapes, full FEM, CC, etc. - Constrained / multipoint adjoint-based design and mesh adaptation - Distributed development team using agile/extreme software practices including 24/7 regression and performance testing - Capabilities fully integrated, online documentation, training videos, tutorials

Eric J Nielsen↗
NASA NTRS2005

JIMO follow-on mission studies

Team Prometheus is a geographically-distributed, collaborative engineering team composed of representatives from several NASA centers and the Department of Energy (DOE). During the months of April through September 2004, Team Prometheus performed studies of representative Saturn/Titan and Neptune/Triton science missions based on proposed Jupiter Icy Moons Orbiter (JIMO) technology. The principal objectives of these studies were: 1) to assess the feasibility of using direct copies of the baseline JIMO flight system designs to perform these follow-on missions, and 2) to identify and assess technologies or potential enhancements or alterations to the baseline JIMO designs which could reduce the cruise durations to meet NASA Headquarters-specified programmatic goals. A tertiary objective was to provide feedback to the JlMO Project on the suitability of the JIMO reference designs for potential follow-on applications

Satter, Celeste M.↗
NASA NTRSDate not supplied

NASA LaRC Contribution to the High Angle Working Group of the Third Aeroelastic Prediction Workshop: BSCW Shock Buffet

FUN3D Core Capabilities - Established as a research code in late 1980s; now supports numerous internal and external efforts across the speed range - Solves 2D/3D steady and unsteady Euler and RANS equations on node-based mixed element grids for compressible and incompressible flows - General dynamic mesh capability: any combination of rigid / overset / morphing grids, including 6-DOF effects - Aeroelastic modeling using mode shapes, full FEM, etc. - Constrained / multipoint adjoint-based design and mesh adaptation - Distributed development team using agile/extreme software practices including 24/7 regression, performance testing - Capabilities fully integrated, online documentation, training videos, tutorials

Pawel Chwalowski↗
NASA NTRSDate not supplied

Identifying Human Factors Research for Unmanned Aircraft Systems and Advanced Air Mobility

This paper identifies some of the key human factors (HF) challenges when integrating Unmanned Aircraft Systems (UAS) and Advanced Air Mobility (AAM) into the civil airspace. Unique HF considerations—those which are derived from the key differentiating aspects of UAS/AAM compared to conventional aviation—are the primary basis for identifying HF research opportunities. By identifying what makes UAS and AAM fundamentally different from conventional aviation, from a human integration perspective, HF research can be targeted to effectively inform best practices, standards, policy, guidance, and regulations associated with aircraft and air traffic systems and operations. HF research areas are discussed within the following topic areas: Sustained low-altitude operations; loss of natural sensing; novel aircraft; novel operations; link management and lost link; link performance; distributed pilot teams; and increased automation. The identified research descriptions are intended to serve as illustrative examples of what research is fundamental, and why. They are not intended to prescribe, prioritize or exclude research.

AAM↗
NASA NTRSDate not supplied

Identifying Human Factors Research for Unmanned Aircraft Systems (UAS) and Advanced Air Mobility (AAM)

This paper identifies some of the key human factors (HF) challenges when integrating Unmanned Aircraft Systems (UAS) and Advanced Air Mobility (AAM) into the civil airspace. Unique HF considerations—those which are derived from the key differentiating aspects of UAS/AAM compared to conventional aviation—are the primary basis for identifying HF research opportunities. By identifying what makes UAS and AAM fundamentally different from conventional aviation, from a human integration perspective, HF research can be targeted to effectively inform best practices, standards, policy, guidance, and regulations associated with aircraft and air traffic systems and operations. HF research areas are discussed within the following topic areas: Sustained low-altitude operations; loss of natural sensing; novel aircraft; novel operations; link management and lost link; link performance; distributed pilot teams; and increased automation. The identified research descriptions are intended to serve as illustrative examples of what research is fundamental, and why. They are not intended to prescribe, prioritize or exclude research.

AAM↗
NASA NTRS2024

Remote Science at Sea With Remotely Operated Vehicles

Conducting sea-going ocean science no longer needs to be limited to the number of berths on a ship given that telecommunications, computing, and networking technologies onboard ships have become familiar mechanisms for expanding scientists’ reach from onshore. The oceanographic community routinely works with remotely operated vehicles (ROVs) and pilots to access real-time video and data from the deep sea, while onboard a ship. The extension of using an ROV and its host vessel’s live-streaming capabilities has been popularized for almost 3 decades as a telepresence technology. Telepresence-enabled vessels with ROVs have been employed for science, education, and outreach, giving a greater number of communities viewing access to ocean science. However, the slower development of technologies and social processes enabling sustained real-time involvement between scientists on-ship and onshore undermines the potential for broader access, which limits the possibility of increasing inclusivity and discoveries through a diversity of knowledge and capabilities. This article reviews ocean scientists’ use of telepresence for ROV-based deep-sea research and funded studies of telepresence capabilities. The authors summarize these studies findings and conditions that lead to defining the use of telepresence-enabled vessels for “remote science at sea.” Authors define remote science at sea as a type of ocean expedition, an additional capability, not a replacement for all practices by which scientists conduct ocean research. Remote science for ocean research is an expedition at-sea directed by a distributed science team working together from at least two locations (on-ship and onshore) to complete their science objectives for which primary data is acquired by robotic technologies, with connectivity supported by a high-bandwidth satellite and the telepresence-enabled ship’s technologies to support the science team actively engaged before, during, and after dives across worksites. The growth of productive ocean expeditions with remote science is met with social, technical, and logistical challenges that impede the ability of remote scientists to succeed. In this article, authors review telepresence-enabled ocean science, define and situate the adjoined model of remote science at sea, and some infrastructural, technological and social considerations for conducting and further developing remote science at sea.

marine technology↗
NASA NTRS2003

NASA Team Collaboration Pilot: Enabling NASA's Virtual Teams

Most NASA projects and work activities are accomplished by teams of people. These teams are often geographically distributed - across NASA centers and NASA external partners, both domestic and international. NASA "virtual" teams are stressed by the challenge of getting team work done - across geographic boundaries and time zones. To get distributed work done, teams rely on established methods - travel, telephones, Video Teleconferencing (NASA VITS), and email. Time is our most critical resource - and team members are hindered by the overhead of travel and the difficulties of coordinating work across their virtual teams. Modern, Internet based team collaboration tools offer the potential to dramatically improve the ability of virtual teams to get distributed work done.

Prahst, Steve↗
NASA NTRS1986

An experimental paradigm for team decision processes

The study of distributed information processing and decision making is presently hampered by two factors: (1) The inherent complexity of the mathematical formulation of decentralized problems has prevented the development of models that could be used to predict performance in a distributed environment; and (2) The lack of comprehensive scientific empirical data on human team decision making has hindered the development of significant descriptive models. As a part of a comprehensive effort to find a new framework for multihuman decision making problems, a novel experimental research paradigm was developed involving human terms in decision making tasks. Attempts to construct parts of an integrated model with ideas from queueing networks, team theory, distributed estimation and decentralized resource management are described.

Serfaty, D.↗
NASA NTRS2010

Simulation of a Lunar Surface Base Power Distribution Network for the Constellation Lunar Surface Systems

The Lunar Surface Power Distribution Network Study team worked to define, breadboard, build and test an electrical power distribution system consistent with NASA's goal of providing electrical power to sustain life and power equipment used to explore the lunar surface. A testbed was set up to simulate the connection of different power sources and loads together to form a mini-grid and gain an understanding of how the power systems would interact. Within the power distribution scheme, each power source contributes to the grid in an independent manner without communication among the power sources and without a master-slave scenario. The grid consisted of four separate power sources and the accompanying power conditioning equipment. Overall system design and testing was performed. The tests were performed to observe the output and interaction of the different power sources as some sources are added and others are removed from the grid connection. The loads on the system were also varied from no load to maximum load to observe the power source interactions.

Mintz, Toby↗
NASA NTRS2022

Lithological variation of asteroid Ryugu samples returned by the Hayabusa 2 spacecraft: Assessment from the 18 particles distributed to the initial analysis “Stone” team

JAXA’s Hayabusa2 spacecraft successfully returned~5.4g of C-type asteroid Ryugu materials on Dec. 2020 [e.g., 1] and the recovered samples were extensively analyzed by initial analysis teams and Phase2 curation teams. The reported results show that Ryugu samples are similar to CI chondritesin chemistry and mineralogy, showing evidence for aqueous alteration in the parent body [e.g., 2,3]. As a “stone” team of the initial analysis, we received 18coarse particles (>1 mm) of Ryugu samples to characterize their mineralogy and petrology. We found that the samples were breccias of mm-to-sub mm size clasts. All of the clasts are mainly composed of Mg-Fe phyllosilicates, but the alteration degree appears slightly different from one clast to another. Here we report a lithological variation of Ryugu samples to propose their reasonable lithological classification based upon different mineral assemblages and to discuss the formation and evolution of the Ryugu parent body.

Michael E Zolensky↗
NASA NTRS2006

Implementing distributed operations : a comparison of two Deep Space Missions

Two very different deep space exploration missions—Mars Exploration Rover and Cassini—have made use of distributed operations for their science teams. In the case of MER, the distributed operations capability was implemented only after the prime mission was completed, as the rovers continued to operate well in excess of their expected mission lifetimes; Cassini, designed for a prime mission of four years, had planned for distributed operations from its inception. The rapid command turnaround timeline of MER, as well as many of the operations features implemented to support it, have proven to be conducive to distributed operations. These features include: a single science team leader during the tactical operations timeline, highly integrated science and engineering teams, processes and file structures designed to permit multiple team members to work in parallel to deliver sequencing products, web-based spacecraft status and planning reports for team-wide access, and near-elimination of paper products from the operations process.

Larsen, Barbara↗