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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Dynamic Spectrum Allocation in Urban Air Transportation System via Deep Reinforcement Learning

The emerging concepts of Urban Air Mobility (UAM) and Advanced Air Mobility (AAM) open a new paradigm for urban air transportation. A big challenge is that these new aerial vehicles will quickly saturate the already crowded aviation spectrum, which is an essential resource to ensure reliable communications for safe operations. In this paper, we consider an air transportation system where multiple aerial vehicles are operated to transport passengers or cargo from different sources to destinations along their pre-defined paths. During the flight, the minimum communication Quality of Service (QoS) requirement must be achieved to ensure flight safety. Our objective is to minimize the average mission completion time by jointly optimizing the velocity selection and spectrum allocation for all aerial vehicles. We formulate the optimization problem as a multi-stage Markov Decision Process (MDP) where the optimization variables are coupled together. A multi-agent Deep Reinforcement Learning (DRL) based solution is proposed where Value Decomposition Networks (VDN) algorithm is utilized to take discrete actions. Additionally, we propose a heuristic greedy algorithm as a baseline solution. Simulation results show that our learning based solution outperforms the heuristic greedy algorithm and another Orthogonal Multiple Access (OMA) solution in minimizing the mission completion time.

Ruixuan Han↗
NASA NTRSDate not supplied

Dynamic Spectrum Allocation in Urban Air Transportation System via Deep Reinforcement Learning

The emerging concepts of Urban Air Mobility (UAM) and Advanced Air Mobility (AAM) open a new paradigm for urban air transportation. A big challenge is that these new aerial vehicles will quickly saturate the already crowded aviation spectrum, which is an essential resource to ensure reliable communications for safe operations. In this paper, we consider an air transportation system where multiple aerial vehicles are operated to transport passengers or cargo from different sources to destinations along their pre-defined paths. During the flight, the minimum communication Quality of Service (QoS) requirement must be achieved to ensure flight safety. Our objective is to minimize the average mission completion time by jointly optimizing the velocity selection and spectrum allocation for all aerial vehicles. We formulate the optimization problem as a multi-stage Markov Decision Process (MDP) where the optimization variables are coupled together. A multi-agent Deep Reinforcement Learning (DRL) based solution is proposed where Value Decomposition Networks (VDN) algorithm is utilized to take discrete actions. Additionally, we propose a heuristic greedy algorithm as a baseline solution. Simulation results show that our learning based solution outperforms the heuristic greedy algorithm and another Orthogonal Multiple Access (OMA) solution in minimizing the mission completion time.

Ruixuan Han↗
NASA NTRS1975

A dynamic packet-switching system for satellite broadcast channels

A new satellite multi-access scheme for packet-switching computer communications combines a dynamic allocation technique with conventional time-division multiplexing to minimize delays and maximize traffic thruput. The scheme is designed to give the shortest delays to short-duration interactive or priority traffic, at the expense of longer delays for large data transfers. Simulation results show markedly improved delay-thruput characteristics over conventional time-division multiplexing for a wide range of traffic mixes, with especially significant performance gains as the traffic imbalance among the nodes increases.

Binder, R.↗
NASA NTRS1975

Minimum acquisition time detection

Two different methods of target detection when the return signal is contaminated with noise are discussed and compared. The first method uses Neyman-Pearson detection philosophy and selects the threshold level to give a desired false alarm probability. The maximum probability of false alarm is constrained by the target cross scan velocity component. The second method (minimum acquisition time detection), which is similar to the ideal observer, selects the threshold level to minimize the expected target acquisition time. The probabilities of false alarm and missed detection are selected so that the errors produced by these effects produce the minimum acquisition time. Three different scan techniques - linear, spiral and two-mode scan - are studied and compared.

Brock, H. I.↗
NASA NTRS1982

Optimum waiting time for acquisition of return link PN signals

The subject of this paper is a model that takes into account the effect that acquisition of a PN signal on the forward link has on the acquisition of a PN signal on the return link. The model is used to determine how long the start of the PN search on the return link should be delayed in order to minimize the combined acquisition time (delay + acquisition time) as a function of desired acquisition probability. It is assumed that the return link a-priori epoch uncertainty information is available. Software has been developed that models the return link PN receiver and incorporates in it the effect of forward link PN acquisition statistics in assessing performance.

Kolata, W.↗
NASA NTRS2015

Experimental Validation of the Dynamic Inertia Measurement Method to Find the Mass Properties of an Iron Bird Test Article

The mass properties of an aerospace vehicle are required by multiple disciplines in the analysis and prediction of flight behavior. Pendulum oscillation methods have been developed and employed for almost a century as a means to measure mass properties. However, these oscillation methods are costly, time consuming, and risky. The NASA Armstrong Flight Research Center has been investigating the Dynamic Inertia Measurement, or DIM method as a possible alternative to oscillation methods. The DIM method uses ground test techniques that are already applied to aerospace vehicles when conducting modal surveys. Ground vibration tests would require minimal additional instrumentation and time to apply the DIM method. The DIM method has been validated on smaller test articles, but has not yet been fully proven on large aerospace vehicles.

moments of inertia↗
NASA NTRS2018

Identification of Safety Metrics for Airport Surface Operations

A large fraction of safety incidents occurs on the ground during airport surface operations. Although these incidents are mostly non-fatal with a few exceptions, they are high profile incidents that remain a source of concern for the National Transportation Safety Board (NTSB), the Federal Aviation Administration (FAA), major airlines, and other stakeholders of the National Airspace System (NAS). These incidents have historically been mitigated by implementing changes to regulations, policies, and procedures over time. This approach has minimized but not eliminated the risk of occurrences. It is thus important to develop integrated techniques to assess, model, and prevent these incidents by analyzing the risk and likelihood of occurrence and communicating results of the analysis to decision-making personnel who can mitigate and prevent incidents in real time. The research presented in this report builds on prior work of researchers at the NASA Ames Research Center who developed an automated framework, Real-Time Safety Monitoring (RTSM), to enable monitoring and prediction of the safety of the NAS. In the RTSM framework, hazards to flight are translated to safety metrics such as wake vortex encounters or loss of separation, that can be modeled and analyzed offline and also predicted and monitored in real time (online). The intent of this report is to integrate predictable incidents that occur during surface and ground operations into the safety portfolio of the RTSM project by (i) identifying suitable information sources from which ground incidents can be studied, (ii) developing safety metrics correlated with surface operations, and (iii) recommending suitable data sources that can be quantified and used for the computation of pertinent safety metrics.

ground operations↗
NASA NTRS2018

Identification of Safety Metrics for Airport Surface Operations

A large fraction of safety incidents occurs on the ground during airport surface operations. Although these incidents are mostly non-fatal with a few exceptions, they are high profile incidents that remain a source of concern for the National Transportation Safety Board (NTSB), the Federal Aviation Administration (FAA), major airlines, and other stakeholders of the National Airspace System (NAS). These incidents have historically been mitigated by implementing changes to regulations, policies, and procedures over time. This approach has minimized but not eliminated the risk of occurrence of safety incidents. It is thus important to develop integrated techniques to assess, model, and prevent these incidents by analyzing the risk and likelihood of occurrence and communicating results of the analysis to decision-making personnel who can mitigate and prevent incidents in real time. The work presented in this paper builds on a previously developed architecture for safety, Real-Time Safety Monitoring (RTSM), to enable monitoring and prediction of the safety of the NAS. In the RTSM framework, hazards to flight are translated to safety metrics such as wake vortex encounters or loss of separation, that can be modeled and analyzed offline and also predicted and monitored in real time (online). The intent of this paper is to integrate predictable incidents that occur during surface and ground operations into the safety portfolio of the RTSM project by (i) identifying suitable information sources from which ground incidents can be studied, (ii) developing safety metrics correlated with surface operations, and (iii) recommending suitable data sources that can be quantified and used for the computation of pertinent safety metrics.

safety↗
NASA NTRS1986

A magnetospheric simulation at the space station

It is proposed that a strong magnet (terrella) be flown at or near the Space Station to create an artificial magnetosphere in a laboratory setting. The relative flow of the ionosphere past the terrella will constitute a plasma wind that will interact with the magnetic field of the terrella to produce a localized magnetosphere. This object could then be extensively studied using diagnostic probes attached to the Space Station, or with free flyers. The space and storage requirements would be minimal, since the experiment would be conducted outside the space station. The total equipment would consist of several terrella (with varying surface conductivities), approximately 3 small magnetometer/plasma diagnostic packages, and several gas canisters for upstream seeding. Power requirements would be approximately 60 watts. Several track mounted tethers, each approximately or 200 m long in length, with track parallel to the orbital motion and 100 m long, are also needed. Astronaut time needed would be minimal in the tethered configuration (approximately 4 man hours/week). A free flying configuration, while not needing the tether track, would require much more human interaction.

Lopez, R. E.↗
NASA NTRS1987

A magnetospheric simulation at the Space Station

It is proposed that a strong magnet (terrella) be flown at or near the Space Station to create an artificial magnetosphere in a laboratory setting. The relative flow of the ionosphere past the terrella will constitute a plasma wind that will interact with the magnetic field of the terrella to produce a localized magnetosphere. This object could then be extensively studied using diagnostic probes attached to the Space Station or with free flyers. The space and storage requirements would be minimal, since the experiment would be conducted outside the Space Station. The total equipment would consist of several terrella (with varying surface conductivities), approximately 3 small magnetometer/plasma diagnostic packages, and several gas canisters for upstream seeding. Power requirements would be approximately 60 watts. Several track mounted tethers, each approximately or 200 m long in length, with track parallel to the orbital motion and 100 m long, are also needed. Astronaut time needed would be minimal in the tethered configuration (approximately 4 man hours/week). A free flying configuration, while not needing the tether track, would require much more human interaction.

Lopez, R. E.↗
NASA NTRS1992

Front-End Processor For Metrology-Information System

Front-end processor for NASA Metrology Information System (NMIS) is real-time relational data-base computer system designed to distribute processing for NMIS mainframe system or run as stand-alone local-area-network data-base system. System used in large calibration laboratories for work control and to maintain records of calibration, repair, costs, manpower usage, traceability, and other pertinent facts about instruments supported by laboratories. Provides enhancements to existing NASA Metrology Information System and batches upload to minimize mainframe I/O at times of heavy usage.

Muse, Walter S.↗
NASA NTRS2009

Local-in-Time Adjoint-Based Method for Optimal Control/Design Optimization of Unsteady Compressible Flows

.We study local-in-time adjoint-based methods for minimization of ow matching functionals subject to the 2-D unsteady compressible Euler equations. The key idea of the local-in-time method is to construct a very accurate approximation of the global-in-time adjoint equations and the corresponding sensitivity derivative by using only local information available on each time subinterval. In contrast to conventional time-dependent adjoint-based optimization methods which require backward-in-time integration of the adjoint equations over the entire time interval, the local-in-time method solves local adjoint equations sequentially over each time subinterval. Since each subinterval contains relatively few time steps, the storage cost of the local-in-time method is much lower than that of the global adjoint formulation, thus making the time-dependent optimization feasible for practical applications. The paper presents a detailed comparison of the local- and global-in-time adjoint-based methods for minimization of a tracking functional governed by the Euler equations describing the ow around a circular bump. Our numerical results show that the local-in-time method converges to the same optimal solution obtained with the global counterpart, while drastically reducing the memory cost as compared to the global-in-time adjoint formulation.

Yamaleev, N. K.↗
NASA NTRS2011

Probabilistic Path Planning of Montgolfier Balloons in Strong, Uncertain Wind Fields

Lighter-than-air vehicles such as hot-air balloons have been proposed for exploring Saturn s moon Titan, as well as other bodies with significant atmospheres. For these vehicles to navigate effectively, it is critical to incorporate the effects of surrounding wind fields, especially as these winds will likely be strong relative to the control authority of the vehicle. Predictive models of these wind fields are available, and previous research has considered problems of planning paths subject to these predicted forces. However, such previous work has considered the wind fields as known a priori, whereas in practical applications, the actual wind vector field is not known exactly and may deviate significantly from the wind velocities estimated by the model. A probabilistic 3D path-planning algorithm was developed for balloons to use uncertain wind models to generate time-efficient paths. The nominal goal of the algorithm is to determine what altitude and what horizontal actuation, if any is available on the vehicle, to use to reach a particular goal location in the least expected time, utilizing advantageous winds. The solution also enables one to quickly evaluate the expected time-to-goal from any other location and to avoid regions of large uncertainty. This method is designed for balloons in wind fields but may be generalized for any buoyant vehicle operating in a vector field. To prepare the planning problem, the uncertainty in the wind field is modeled. Then, the problem of reaching a particular goal location is formulated as a Markov decision process (MDP) using a discretized space approach. Solving the MDP provides a policy of what actuation option (how much buoyancy change and, if applicable, horizontal actuation) should be selected at any given location to minimize the expected time-to-goal. The results provide expected time-to-goal values from any given location on the globe in addition to the action policy. This stochastic approach can also provide insights not accessible by deterministic methods; for example, one can evaluate variability and risk associated with different scenarios, rather than only viewing the expected outcome.

Wolf, Michael↗
NASA NTRS2013

Development Status of the WetLab-2 Project: New Tools for On-orbit Real-time Quantitative Gene Expression.

The primary objective of NASA Ames Research Centers WetLab-2 Project is to place on the ISS a research platform to facilitate gene expression analysis via quantitative real-time PCR (qRT-PCR) of biological specimens grown or cultured on orbit. The WetLab-2 equipment will be capable of processing multiple sample types ranging from microbial cultures to animal tissues dissected on-orbit. In addition to the logistical benefits of in-situ sample processing and analysis, conducting qRT-PCR on-orbit eliminates the confounding effects on gene expression of reentry stresses and shock acting on live cells and organisms. The system can also validate terrestrial analyses of samples returned from ISS by providing quantitative on-orbit gene expression benchmarking prior to sample return. The ability to get on orbit data will provide investigators with the opportunity to adjust experimental parameters for subsequent trials based on the real-time data analysis without need for sample return and re-flight. Finally, WetLab-2 can be used for analysis of air, surface, water, and clinical samples to monitor environmental contaminants and crew health. The verification flight of the instrument is scheduled to launch on SpaceX-5 in Aug. 2014.Progress to date: The WetLab-2 project completed a thorough study of commercially available qRT-PCR systems and performed a downselect based on both scientific and engineering requirements. The selected instrument, the Cepheid SmartCycler, has advantages including modular design (16 independent PCR modules), low power consumption, and rapid ramp times. The SmartCycler has multiplex capabilities, assaying up to four genes of interest in each of the 16 modules. The WetLab-2 team is currently working with Cepheid to modify the unit for housing within an EXPRESS rack locker on the ISS. This will enable the downlink of data to the ground and provide uplink capabilities for programming, commanding, monitoring, and instrument maintenance. The project is currently designing a module that will lyse the cells and extract RNA of sufficient quality for use in qRT-PCR reactions while using a housekeeping gene to normalize RNA concentration and integrity. Current testing focuses on two promising commercial products and chemistries that allow for RNA extraction with minimal complexity and crew time.

quantitative PCR↗
NASA NTRS1990

An averaging approach to optimal adaptive control of large space structures

Averaging methods are applied to analyzing the transient response associated with adaptive control of large space structures. Using a dominant mode approximation to the plant, an analytical bound is found on the envelope of the adaptive response, characterizing many of the features of the response useful for control design (e.g., peak values, quadratic costs, settling times, etc.). An optimal adaptive design problem is formulated based on minimizing the product of the settling time and peak torque requirement. The resulting nonlinear constrained optimization problem is solved in closed form, and several properties of the optimal adaptive design are discussed.

Bayard, D. S.↗
NASA NTRS2010

Improving Customer Waiting Time at a DMV Center Using Discrete-Event Simulation

Virginia's Department of Motor Vehicles (DMV) serves a customer base of approximately 5.6 million licensed drivers and ID card holders and 7 million registered vehicle owners. DMV has more daily face-to-face contact with Virginia's citizens than any other state agency [1]. The DMV faces a major difficulty in keeping up with the excessively large customers' arrival rate. The consequences are queues building up, stretching out to the entrance doors (and sometimes even outside) and customers complaining. While the DMV state employees are trying to serve at their fastest pace, the remarkably large queues indicate that there is a serious problem that the DMV faces in its services, which must be dealt with rapidly. Simulation is considered as one of the best tools for evaluating and improving complex systems. In this paper, we use it to model one of the DMV centers located in Norfolk, VA. The simulation model is modeled in Arena 10.0 from Rockwell systems. The data used is collected from experts of the DMV Virginia headquarter located in Richmond. The model created was verified and validated. The intent of this study is to identify key problems causing the delays at the DMV centers and suggest possible solutions to minimize the customers' waiting time. In addition, two tentative hypotheses aiming to improve the model's design are tested and validated.

Arnaout, Georges M.↗
NASA NTRS2010

Lunar Daylight Exploration

With 1 rover, 2 astronauts and 3 days, the Apollo 17 Mission covered over 30 km, setup 10 scientific experiments and returned 110 kg of samples. This is a lot of science in a short time and the inspiration for a barebones, return-to-the-Moon strategy called Daylight Exploration. The Daylight Exploration approach poses an answer to the question, What could the Apollo crew have done with more time and today s robotics? In contrast to more ambitious and expensive strategies that create outposts then rely on pressurized rovers to drive to the science sites, Daylight Exploration is a low-overhead approach conceived to land near the scientific site, conduct Apollo-like exploration then leave before the sun goes down. A key motivation behind Daylight Exploration is cost reduction, but it does not come at the expense of scientific exploration. As a goal, Daylight Exploration provides access to the top 10 science sites by using the best capabilities of human and robotic exploration. Most science sites are within an equatorial band of 26 degrees latitude and on the Moon, at the equator, the day is 14 Earth days long; even more important, the lunar night is 14 days long. Human missions are constrained to 12 days because the energy storage systems required to operate during the lunar night adds mass, complexity and cost. In addition, short missions are beneficial because they require fewer consumables, do not require an airlock, reduce radiation exposure, minimize the dwell-time for the ascent and orbiting propulsion systems and allow a low-mass, campout accommodations. Key to Daylight Exploration is the use of piloted rovers used as tele-operated science platforms. Rovers are launched before or with the crew, and continue to operate between crew visits analyzing and collecting samples during the lunar daylight

Griffin, Brand Norman↗