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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Demand Capacity Balancing at Vertiports for Initial Strategic Conflict Management of Urban Air Mobility Operations

Demand Capacity Balancing (DCB) can be applied in strategic conflict management for safe Urban Air Mobility (UAM) operations. Even when the operational tempo is low, traffic demand can locally exceed the capacity at airspace resources like vertiports. This paper proposes a DCB algorithm to manage the UAM traffic demand strategically, given the capacity at vertiports. The DCB algorithm is evaluated with traffic scenarios at Dallas/Fort Worth urban area in terms of various metrics such as demand distribution changes, pre-departure delay, and the number of simultaneous operations in the air. With the same experiment setup, more extended studies are also conducted to investigate how the UAM flight scheduling based on the DCB algorithm is affected by various conditions that can occur in a practical UAM environment, including vertiport capacity changes, a slot size parameter in capacity constraint, differences in operational policy between operators like lead time for flight plan submission and cruise flight speed, and uncertainties in actual departure and arrival times.

Urban Air Mobility↗
NASA NTRSDate not supplied

Demand Capacity Balancing at Vertiports for Urban Air Mobility

Demand Capacity Balancing (DCB) can be applied in strategic conflict management for safe Urban Air Mobility (UAM) operations. Even when the operational tempo is low, traffic demand can locally exceed the capacity at airspace resources like vertiports. This paper proposes a DCB algorithm to manage the UAM traffic demand strategically, given the capacity at vertiports. The DCB algorithm is evaluated with traffic scenarios at Dallas/Fort Worth urban area in terms of various metrics such as demand distribution changes, pre-departure delay, and the number of simultaneous operations in the air. With the same experiment setup, more extended studies are also conducted to investigate how the UAM flight scheduling based on the DCB algorithm is affected by various conditions that can occur in a practical UAM environment, including vertiport capacity changes, a slot size parameter in capacity constraint, differences in operational policy between operators like lead time for flight plan submission and cruise flight speed, and uncertainties in actual departure and arrival times.

Urban Air Mobility↗
NASA NTRS1987

An integrated approach to space station power system autonomous control

Space Station electrical power management must be accomplished autonomously in order to decrease both airborne and ground support costs. Attention is presently given to the augmentation of terrestrial utility algorithmic decision aids for power dispatching for space station use, using expert systems to direct power demand analyses and the integration of results into operational decisions. Functions to be thus managed encompass power scheduling, energy allocation, failure cause diagnoses, goal proposal and plan preparation, consequence evaluation, and execution plan selection. The operating states of the system are normal, preventive, emergency, and restorative.

Dolce, James L.↗
NASA NTRS2017

Heuristic Area Cost Estimation for Observational Coverage Schedulers

This paper presents a comparison of heuris- tics used to estimate the amount of time it would take for a spacecraft to image an area using Boustrophedon decomposition (Choset and Pignon 1998). Machine learning tech- niques are used to characterize algorithmic performance of coverage algorithms. It is shown that an ordinary least-squares linear model is among the most accurate in a set of constant and linear order regression models both in terms of memory consumption and schedule duration. These are demonstrated using the ASPEN planning system (Fukunaga et al. 1997) on the Eagle Eye domain.

Knight, Russell↗
NASA NTRS2018

Area Coverage Planning with 3-axis Steerable, 2D Framing Sensors

Existing algorithms for Agile Earth Observing Satellites((Lemaitre et al. 2002)) were largely created for 1D line sensors that acquire images in linear swaths. However, imaging satellites increasingly use 2D framing sensors (cameras) that capture discrete rectangular images. We describe tiling step-stare approaches that are more suited to rectangular image footprints than are 1D swath-based algorithms. Optimal area planning for these 2D framing instruments is an NPcomplete problem and intractable for large areas, so we present four approximation algorithms. Strategies are compared against a prior 2D framing instrument algorithm (Knight 2014) in three computational experiments. The impact of observer agility on schedule makespan is examined. Makespans vary more as observer agility decreases toward a critical point, then vary less after the critical point, suggesting a possible problem phase transition.

Chien, Steve↗
NASA NTRS1990

A two-level structure for advanced space power system automation

The tasks to be carried out during the three-year project period are: (1) performing extensive simulation using existing mathematical models to build a specific knowledge base of the operating characteristics of space power systems; (2) carrying out the necessary basic research on hierarchical control structures, real-time quantitative algorithms, and decision-theoretic procedures; (3) developing a two-level automation scheme for fault detection and diagnosis, maintenance and restoration scheduling, and load management; and (4) testing and demonstration. The outlines of the proposed system structure that served as a master plan for this project, work accomplished, concluding remarks, and ideas for future work are also addressed.

Loparo, Kenneth A.↗
NASA NTRS1998

Distribution of a Generic Mission Planning and Scheduling Toolkit for Astronomical Spacecraft

This 2-year report describes the progress made to date on the project to package and distribute the planning and scheduling toolkit for the SWAS astronomical spacecraft. SWAS was scheduled to be launched on a Pegasus XL vehicle in fall 1995. Three separate failures in the launch vehicle have delayed the SWAS launch. The researchers have used this time to continue developing scheduling algorithms and GUI design. SWAS is expected to be launched this year.

Kleiner, Steven C.↗
NASA NTRS2006

NAS Demand Predictions, Transportation Systems Analysis Model (TSAM) Compared with Other Forecasts

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Viken, Jeff↗
NASA NTRS2006

Utilizing Traveler Demand Modeling to Predict Future Commercial Flight Schedules in the NAS

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Viken, Jeff↗
NASA NTRS2010

Autonomous Precision Landing and Hazard Avoidance Technology (ALHAT) Project Status as of May 2010

This paper includes the current status of NASA s Autonomous precision Landing and Hazard Avoidance Technology (ALHAT) Project. The ALHAT team has completed several flight tests and two major design analysis cycles. These tests and analyses examine terrain relative navigation sensors, hazard detection and avoidance sensors and algorithms, and hazard relative navigation algorithms, and the guidance and navigation system using these ALHAT functions. The next flight test is scheduled for July 2010. The paper contains results from completed flight tests and analysis cycles. ALHAT system status, upcoming tests and analyses is also addressed. The current ALHAT plans as of May 2010 are discussed. Application of the ALHAT system to landing on bodies other than the Moon is included

Striepe, Scott A.↗
NASA NTRS2003

Self-Directed Cooperative Planetary Rovers

The project is concerned with the development of decision-theoretic techniques to optimize the scientific return of planetary rovers. Planetary rovers are small unmanned vehicles equipped with cameras and a variety of sensors used for scientific experiments. They must operate under tight constraints over such resources as operation time, power, storage capacity, and communication bandwidth. Moreover, the limited computational resources of the rover limit the complexity of on-line planning and scheduling. We have developed a comprehensive solution to this problem that involves high-level tools to describe a mission; a compiler that maps a mission description and additional probabilistic models of the components of the rover into a Markov decision problem; and algorithms for solving the rover control problem that are sensitive to the limited computational resources and high-level of uncertainty in this domain.

Zilberstein, Shlomo↗
NASA NTRS2011

Efficient Spectral Endmember Detection Onboard the EO-1 Spacecraft

Spaceflight and planetary exploration place severe constraints on the available bandwidth for downlinking large hyperspectral images. In addition, communications with spacecraft often occur intermittently, so mission-relevant hyperspectral data must wait for analysis on the ground before it can inform spacecraft activity planning. Onboard endmember detection can help alleviate these problems. It enables novelty detection and target identification for scheduling follow-up activities such as additional observation by narrow field of view instruments. Additionally, endmember analysis can facilitate data summary for downlink. This work describes a planned experiment of selective downlink by the EO-1 autonomous spacecraft. Here an efficient superpixel endmember detection algorithm keeps to the limited computational constraints of the flight processor. Tests suggest the procedure could enable significant improvements in downlink efficiency.

Endmember Detection↗
NASA NTRS1996

SEDSAT 1 Technologies

The original goals of this project were to support the development of SEDSAT 1 for a tethered launch in July of 1997. This specifically required: (1) Monitoring development progress against a comprehensive delivery plan; (2) Incremental development and release of CDS and SEASIS software; (3) Supporting the integration of version 1.0 SEASIS software that will allow minimal autonomous operation without a software reload. These algorithms would include image quality evaluation, attitude determination, and autonomous earth imaging; and (4) Developing software requirements and design for ground segment software, concentrating on command and data download capability; and interface to external development efforts for a more comprehensive software suite to be used after the initial mission. Because of an unfavorable space shuttle safety review of the SEDS-3 tether deployer, and cost and schedule problems in upgrading the deployer, the mission was changed to an independent launch of SEDSAT. The original plan was to do a tether-less deployment from the space shuttle. Since this would have resulted in an unacceptable orbital lifetime, the mission was changed again to a tethered launch from a Delta II in June 1998. As a result of Marshall Space Flight Center's redirection of the SEDS-3 mission away from a tether launch, the whole question of a tether endmass had to be reconsidered. The net result of these multiple changes was twofold. First, we completed work needed to define some aspects of ground software on SEDSAT 1 that would remain constant no matter the launch mode. Second, we developed a set of concepts for using SEDSAT 1 technology to support alternative endmass missions on SEDS-3. Both of these are included.

Maier, Mark W.↗
NASA NTRS1987

Range and mission scheduling automation using combined AI and operations research techniques

Ground-based systems for Satellite Command, Control, and Communications (C3) operations require a method for planning, scheduling and assigning the range resources such as: antenna systems scattered around the world, communications systems, and personnel. The method must accommodate user priorities, last minute changes, maintenance requirements, and exceptions from nominal requirements. Described are computer programs which solve 24 hour scheduling problems, using heuristic algorithms and a real time interactive scheduling process.

Arbabi, Mansur↗
NASA NTRS1991

The evolution of synthetic aperture radar systems and their progression to the EOS SAR

The authors describe the evolution of the spaceborne imaging radar starting with the Seasat SAR, through the SIR-A, SIR-B, and SIR-C/X-SAR missions, to the Earth Observing System (EOS) SAR which is scheduled for launch as part of EOS in the late 1990s. A summary of the planned international missions, which may produce a permanent active microwave capability in space starting as early as 1991, is also presented, along with a description of the airborne systems which will be essential to the algorithm development and long-term calibration of the spaceborne data. A brief summary of the planetary missions utilizing SAR and a comparison of their imaging capabilities with those available on Earth are presented.

Way, Jobea↗
NASA NTRS2012

Performance Considerations for the SIMPL Single Photon, Polarimetric, Two-Color Laser Altimeter as Applied to Measurements of Forest Canopy Structure and Composition

The Slope Imaging Multi-polarization Photon-counting Lidar (SIMPL) is a multi-beam, micropulse airborne laser altimeter that acquires active and passive polarimetric optical remote sensing measurements at visible and near-infrared wavelengths. SIMPL was developed to demonstrate advanced measurement approaches of potential benefit for improved, more efficient spaceflight laser altimeter missions. SIMPL data have been acquired for wide diversity of forest types in the summers of 2010 and 2011 in order to assess the potential of its novel capabilities for characterization of vegetation structure and composition. On each of its four beams SIMPL provides highly-resolved measurements of forest canopy structure by detecting single-photons with 15 cm ranging precision using a narrow-beam system operating at a laser repetition rate of 11 kHz. Associated with that ranging data SIMPL provides eight amplitude parameters per beam unlike the single amplitude provided by typical laser altimeters. Those eight parameters are received energy that is parallel and perpendicular to that of the plane-polarized transmit pulse at 532 nm (green) and 1064 nm (near IR), for both the active laser backscatter retro-reflectance and the passive solar bi-directional reflectance. This poster presentation will cover the instrument architecture and highlight the performance of the SIMPL instrument with examples taken from measurements for several sites with distinct canopy structures and compositions. Specific performance areas such as probability of detection, after pulsing, and dead time, will be highlighted and addressed, along with examples of their impact on the measurements and how they limit the ability to accurately model and recover the canopy properties. To assess the sensitivity of SIMPL's measurements to canopy properties an instrument model has been implemented in the FLIGHT radiative transfer code, based on Monte Carlo simulation of photon transport. SIMPL data collected in 2010 over the Smithsonian Environmental Research Center, MD are currently being modelled and compared to other remote sensing and in situ data sets. Results on the adaptation of FLIGHT to model micropulse, single'photon ranging measurements are presented elsewhere at this conference. NASA's ICESat-2 spaceflight mission, scheduled for launch in 2016, will utilize a multi-beam, micropulse, single-photon ranging measurement approach (although non-polarimetric and only at 532 nm). Insights gained from the analysis and modelling of SIMPL data will help guide preparations for that mission, including development of calibration/validation plans and algorithms for the estimation of forest biophysical parameters.

Dabney, Philip W.↗
NASA NTRS2014

APGEN Scheduling: 15 Years of Experience in Planning Automation

In this paper, we discuss the scheduling capability of APGEN (Activity Plan Generator), a multi-mission planning application that is part of the NASA AMMOS (Advanced Multi- Mission Operations System), and how APGEN scheduling evolved over its applications to specific Space Missions. Our analysis identifies two major reasons for the successful application of APGEN scheduling to real problems: an expressive DSL (Domain-Specific Language) for formulating scheduling algorithms, and a well-defined process for enlisting the help of auxiliary modeling tools in providing high-fidelity, system-level simulations of the combined spacecraft and ground support system.

sequencing↗
NASA NTRS1990

Automation in the Space Station module power management and distribution Breadboard

The Space Station Module Power Management and Distribution (SSM/PMAD) Breadboard, located at NASA's Marshall Space Flight Center (MSFC) in Huntsville, Alabama, models the power distribution within a Space Station Freedom Habitation or Laboratory module. Originally designed for 20 kHz ac power, the system is now being converted to high voltage dc power with power levels on a par with those expected for a space station module. In addition to the power distribution hardware, the system includes computer control through a hierarchy of processes. The lowest level process consists of fast, simple (from a computing standpoint) switchgear, capable of quickly safing the system. The next level consists of local load center processors called Lowest Level Processors (LLP's). These LLP's execute load scheduling, perform redundant switching, and shed loads which use more than scheduled power. The level above the LLP's contains a Communication and Algorithmic Controller (CAC) which coordinates communications with the highest level. Finally, at this highest level, three cooperating Artificial Intelligence (AI) systems manage load prioritization, load scheduling, load shedding, and fault recovery and management. The system provides an excellent venue for developing and examining advanced automation techniques. The current system and the plans for its future are examined.

Walls, Bryan↗