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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

NASA DEVELOP’s User-Centric Approach to Building Capacity to Use Earth Observations for Decision Making

The DEVELOP Program, part of NASA’s Applied Sciences, conducts 50-60 feasibility studies annually that center on user needs. Each project is tailored to its partner’s decision making processes with the goal of identifying and implementing opportunities for Earth observation data and information to be integrated into environmental decision making processes. These projects are conducted by a team of early career professionals through a 10-week term where the DEVELOP team rapidly iterates with partners culminating in a “recipe” for using NASA Earth observations. This presentation will introduce the DEVELOP model for user-centered design of projects, share the program's iterative approach to project execution, highlight multiple case studies, and lessons learned in the program’s model evolution.

Capacity Building↗
NASA NTRSDate not supplied

Building Sustainable Capacity within Under-Represented Communities Through A Deep Partnership Model

Despite varied programmatic inducements and the documented benefits of Diversity Equity & Inclusion (DE&I), participation rates of underrepresented communities within NASA’s planetary sciences activities have remained low and nearly unchanged over the last decade. The lack of success of various efforts may be attributable to factors identified in social science research. First, the proportionality of under-represented groups has been shown to be critical to achieving the positive impacts of DE&I. When under-represented groups make up less than ~30%, group dynamics such as assimilation or tokenism routinely appear, with destructive and counter-productive results. Additionally, if participation only occurs within limited segments of an organization, benefits may be limited. Proportionality must extend across all levels or layers of the organization for the benefits of DE&I to accrue. Second, the inclusion of “Third Spaces” in the planning and support of DE&I efforts is critical to the long-term success or “stickiness” of DE&I activities. Third Spaces are those beyond home (First Space) and work (Second Space) where informal, community-building activities occur. Examples include conferences, after-work activities, and weekend social engagements. Without explicitly acknowledging and including “Third Space” interactions, DE&I efforts can fall short of their long-term goals. In 2014, the Laboratory for Atmospheric and Space Physics (LASP) at the University of Colorado Boulder began a partnership with the United Arab Emirates to develop and fly a space mission to Mars. The scientific mission had an explicit goal of training scientists and engineers, and creating a sustainable ecosystem that would spark and accelerate the UAE’s space economy. To accomplish this, LASP and the UAE set up a program that matched scientists and engineers in one-on-one mentorship relationships, at all levels of the organization. Over the course of the roughly 4-year project, those partnering relationships fostered not only strong professional relationships and knowledge transfer, but also personal friendships that extended into “Third Spaces.” The UAE/LASP partnership now continues through the co-development of an asteroid mission currently in definition phase. In collaboration with NASA Ames Research Center, LASP is developing the conceptual frame work to extend this deep partnership model to domestic opportunities. By implementing a planetary science mission that employs an analogous one-on-one partnership model across all elements of the organization, this project will demonstrate how proportionality and Third Space relationships can enable the development of localized, sustainable communities that are explicitly and deeply engaged with the NASA ecosystem.

Capacity Building↗
NASA NTRSDate not supplied

Effect of Airspace Characteristics on Urban Air Mobility Airspace Capacity

As interest in urban air mobility grows, increasingly high density traffic poses a challenge for the transition to safe, efficient, and timely operations. Hundreds of simultaneously demanded flights will need to share the same fleet, infrastructure, and constrained airspace. This paper investigates the feasibility of effectively managing high density traffic in congested urban environments by optimizing the design of airspace route structures. Demand estimations for the Dallas-Fort Worth and Los Angeles areas are used to evaluate potential improvements to airspace route design with the goal to accommodate the projected level of demand.

Urban Air Mobility↗
NASA NTRSDate not supplied

Effect of Airspace Characteristics on Urban Air Mobility Airspace Capacity

As interest in urban air mobility grows, increasingly high density traffic poses a challenge for the transition to safe, efficient, and timely operations. Hundreds of simultaneously demanded flights will need to share the same fleet, infrastructure, and constrained airspace. This paper investigates the feasibility of effectively managing high density traffic in congested urban environments by optimizing the design of airspace route structures. Demand estimations for the Dallas-Fort Worth and Los Angeles areas are used to evaluate potential improvements to airspace route design with the goal to accommodate the projected level of demand.

Urban Air Mobility↗
NASA NTRSDate not supplied

Demand-Capacity Balancing Algorithms for Urban Air Mobility Operations

This paper proposes new Demand/Capacity Balancing (DCB) algorithms that resolve imbalances at enroute waypoints, such as crossing, merging, and UAM corridor entry or exit waypoints, in addition to vertiports; we refer to this algorithm as DCB-Waypoint, still using pre-departure delay as the sole resolution mechanism. Like DCB-Vertiport, DCB-Waypoint takes one flight at a time and resolves imbalances one waypoint at a time, starting from the origin vertiport followed by the sequence of constrained waypoints and, finally, the destination vertiport. The next advancement assigns airborne delays, in addition to pre-departure delays at vertiports. This algorithm, called DCB-Airborne-Delays, uses information on flight speeds to ensure that the assigned delays are feasible, meaning that variations in flight speeds are within feasible aircraft speed ranges. The proposed algorithms are being implemented in a new fast-time simulation tool developed especially for simulating UAM operations. The full paper will provide additional details of the new DCB algorithms that have been developed, as well as the results from simulations using these algorithms. Finally, the DCB algorithms will be compared against one another to obtain insights and recommendations for the future development of more advanced DCB algorithms.

urban air mobility, demand-capacity balancing↗
NASA NTRSDate not supplied

Demand-Capacity Balancing Algorithms for Urban Air Mobility Operations

This paper proposes new Demand/Capacity Balancing (DCB) algorithms that resolve imbalances at enroute waypoints, such as crossing, merging, and UAM corridor entry or exit waypoints, in addition to vertiports; we refer to this algorithm as DCB-Waypoint, still using pre-departure delay as the sole resolution mechanism. Like DCB-Vertiport, DCB-Waypoint takes one flight at a time and resolves imbalances one waypoint at a time, starting from the origin vertiport followed by the sequence of constrained waypoints and, finally, the destination vertiport. The next advancement assigns airborne delays, in addition to pre-departure delays at vertiports. This algorithm, called DCB-Airborne-Delays, uses information on flight speeds to ensure that the assigned delays are feasible, meaning that variations in flight speeds are within feasible aircraft speed ranges. The proposed algorithms are being implemented in a new fast-time simulation tool developed especially for simulating UAM operations. The full paper will provide additional details of the new DCB algorithms that have been developed, as well as the results from simulations using these algorithms. Finally, the DCB algorithms will be compared against one another to obtain insights and recommendations for the future development of more advanced DCB algorithms.

urban air mobility↗