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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Massively Parallel Assimilation of TOGA/TAO and Topex/Poseidon Measurements into a Quasi Isopycnal Ocean General Circulation Model Using an Ensemble Kalman Filter

A massively parallel ensemble Kalman filter (EnKF)is used to assimilate temperature data from the TOGA/TAO array and altimetry from TOPEX/POSEIDON into a Pacific basin version of the NASA Seasonal to Interannual Prediction Project (NSIPP)ls quasi-isopycnal ocean general circulation model. The EnKF is an approximate Kalman filter in which the error-covariance propagation step is modeled by the integration of multiple instances of a numerical model. An estimate of the true error covariances is then inferred from the distribution of the ensemble of model state vectors. This inplementation of the filter takes advantage of the inherent parallelism in the EnKF algorithm by running all the model instances concurrently. The Kalman filter update step also occurs in parallel by having each processor process the observations that occur in the region of physical space for which it is responsible. The massively parallel data assimilation system is validated by withholding some of the data and then quantifying the extent to which the withheld information can be inferred from the assimilation of the remaining data. The distributions of the forecast and analysis error covariances predicted by the ENKF are also examined.

Keppenne, Christian L.↗
DOE OSTI2026

Single-Phase to Split-Phase Inverters with Advanced Grid Support Functions for Grid-Interactive Applications

This work presents a cost-effective single-phase to split-phase inverter with a reduced switch count, achieving grid interactive performance while maintaining operational efficiency. The proposed system integrates an Andronov-Hopf oscillator based secondary controller, which inherently embeds a nonlinear resistive droop architecture, ensuring rapid dynamic response. A Lyapunov energy function-based primary control enhances transient stability and regulation, while an internal model-based point of common coupling voltage estimation enables cost optimization without additional sensors. Equipped with advanced grid support functionalities, the inverter facilitates seamless distribution system operation with enhanced robustness. The effectiveness of the proposed architecture and control strategy is validated through MATLAB/Simulink and PLECS simulations, demonstrating its feasibility for high-performance grid-supportive applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2007

An Experimental System for a Global Flood Prediction: From Satellite Precipitation Data to a Flood Inundation Map

Floods impact more people globally than any other type of natural disaster. It has been established by experience that the most effective means to reduce the property damage and life loss caused by floods is the development of flood early warning systems. However, advances for such a system have been constrained by the difficulty in estimating rainfall continuously over space (catchment-. national-, continental-. or even global-scale areas) and time (hourly to daily). Particularly, insufficient in situ data, long delay in data transmission and absence of real-time data sharing agreements in many trans-boundary basins hamper the development of a real-time system at the regional to global scale. In many countries around the world, particularly in the tropics where rainfall and flooding co-exist in abundance, satellite-based precipitation estimation may be the best source of rainfall data for those data scarce (ungauged) areas and trans-boundary basins. Satellite remote sensing data acquired and processed in real time can now provide the space-time information on rainfall fluxes needed to monitor severe flood events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models, which can be parameterized by a tailored geospatial database. An example that is a key to this progress is NASA's contribution to the Tropical Rainfall Measuring Mission (TRMM), launched in November 1997. Hence, in an effort to evolve toward a more hydrologically-relevant flood alert system, this talk articulates a module-structured framework for quasi-global flood potential naming, that is 'up to date' with the state of the art on satellite rainfall estimation and the improved geospatial datasets. The system is modular in design with the flexibility that permits changes in the model structure and in the choice of components. Four major components included in the system are: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM, topography-derived hydrologic parameters such as flood direction. flow accumulation, basin, and river network etc.; 3) spatially distributed hydrological models to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay thc input data to the models and display the flood inundation results to the users and decision-makers. Early results appear reasonable in terms of location and frequency of events. Case studies of this experimental system are evaluated with surface runoff data and other river monitoring systems. such as Dartmouth Flood Observatory's "Surface Water Watch" array of river reaches that are measured daily via other satellite remote sensing data. A major outcome of this progress will be the availability of a global overview of flood alerts that should consequently improve the performance of Decision Support System. We expect these developments in utilization of satellite remote sensing technology to offer a practical solution to the challenge of building a cost-effective early warning system for data scarce and under-developed areas.

Adler, Robert↗
NASA NTRS2010

Downscaling Soil Moisture in the Southern Great Plains Through a Calibrated Multifractal Model for Land Surface Modeling Applications

Accounting for small-scale spatial heterogeneity of soil moisture (theta) is required to enhance the predictive skill of land surface models. In this paper, we present the results of the development, calibration, and performance evaluation of a downscaling model based on multifractal theory using aircraft!based (800 m) theta estimates collected during the southern Great Plains experiment in 1997 (SGP97).We first demonstrate the presence of scale invariance and multifractality in theta fields of nine square domains of size 25.6 x 25.6 sq km, approximately a satellite footprint. Then, we estimate the downscaling model parameters and evaluate the model performance using a set of different calibration approaches. Results reveal that small-scale theta distributions are adequately reproduced across the entire region when coarse predictors include a dynamic component (i.e., the spatial mean soil moisture ) and a stationary contribution accounting for static features (i.e., topography, soil texture, vegetation). For wet conditions, we found similar multifractal properties of soil moisture across all domains, which we ascribe to the signature of rainfall spatial variability. For drier states, the theta fields in the northern domains are more intermittent than in southern domains, likely because of differences in the distribution of vegetation coverage. Through our analyses, we propose a regional downscaling relation for coarse, satellite-based soil moisture estimates, based on ancillary information (static and dynamic landscape features), which can be used in the study area to characterize statistical properties of small-scale theta distribution required by land surface models and data assimilation systems.

Mascaro, Giuseppe↗
DOE OSTI2018

Glimpse of the highly obscured HMXB IGR J16318-4848 with Hitomi*

We report a Hitomi observation of IGR J16318–4848, a high-mass X-ray binary system with an extremely strong absorption of N H ~ 10 24 cm -2 . Previous X-ray studies revealed that its spectrum is dominated by strong fluorescence lines of Fe as well as continuum emission. For physical and geometrical insight into the nature of the reprocessing material, we utilize the high spectroscopic resolving power of the X-ray microcalorimeter (the soft X-ray spectrometer; SXS) and the wide-band sensitivity by the soft and hard X-ray imager (SXI and HXI) aboard Hitomi. Even though photon counts are limited due to unintended off-axis pointing, the SXS spectrum resolves Fe Kα 1 and Kα 2 lines and puts strong constraints on the line centroid and width. The line width corresponds to the velocity of $160_{-70}^{+300}$ km s -1 . This represents the most accurate, and smallest, width measurement of this line made so far from any X-ray binary, much less than the Doppler broadening and shift expected from speeds which are characteristic of similar systems. Combined with the K-shell edge energy measured by the SXI and HXI spectra, the ionization state of Fe is estimated to be in the range of Fe I–IV. Considering the estimated ionization parameter and the distance between the X-ray source and the absorber, the density and thickness of the materials are estimated. The extraordinarily strong absorption and the absence of a Compton shoulder component is confirmed. These characteristics suggest reprocessing materials which are distributed in a narrow solid angle or scattering primarily with warm free electrons or neutral hydrogen. This measurement was achieved using the SXS detection of 19 photons. This provides strong motivation for follow-up observations of this and other X-ray binaries using the X-ray Astrophysics Recovery Mission, and other comparable future instruments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Short-Term Forecasting of Inertial Response from a Wind Power Plant

The total inertia stored in all rotating masses (synchronous generators, induction motors, etc.) connected to a power system grid is an essential force that keeps the system stable after disturbances. Power systems have been experiencing reduced inertia during the past few decades [1]. This trend will continue as the level of renewable generation (e.g., wind and solar) increases. Wind power plants (WPPs) and other renewable power plants with power electronic interfaces are capable of delivering frequency response (both droop and/or inertial response) by a control action; thus, the reduction in available online inertia can be compensated by designing the plant control to include frequency response. The source of energy to be delivered as inertial response is determined by the type of generation (wind, photovoltaic, concentrating solar power, etc.) and the control strategy chosen. The importance of providing ancillary services to ensure frequency control within a power system is evidenced from many recent publications with different perspectives (manufacturer, system operator, regulator, etc.) [2]-[6]. This paper is intended to provide operators with a method for the real-time assessment of the available inertia of a WPP. This is critical to managing power system stability and the reserve margin. In many states, modern WPPs are required to provide ancillary services (e.g., frequency regulation via governor response and inertial response) to the grid. This paper describes the method of estimating the available inertia and the profile of the forecasted response from a WPP.

17 WIND ENERGY↗
NASA NTRS2011

Lessons Learned from Assimilating Altimeter Data into a Coupled General Circulation Model with the GMAO Augmented Ensemble Kalman Filter

Satellite altimetry measurements have provided global, evenly distributed observations of the ocean surface since 1993. However, the difficulties introduced by the presence of model biases and the requirement that data assimilation systems extrapolate the sea surface height (SSH) information to the subsurface in order to estimate the temperature, salinity and currents make it difficult to optimally exploit these measurements. This talk investigates the potential of the altimetry data assimilation once the biases are accounted for with an ad hoc bias estimation scheme. Either steady-state or state-dependent multivariate background-error covariances from an ensemble of model integrations are used to address the problem of extrapolating the information to the sub-surface. The GMAO ocean data assimilation system applied to an ensemble of coupled model instances using the GEOS-5 AGCM coupled to MOM4 is used in the investigation. To model the background error covariances, the system relies on a hybrid ensemble approach in which a small number of dynamically evolved model trajectories is augmented on the one hand with past instances of the state vector along each trajectory and, on the other, with a steady state ensemble of error estimates from a time series of short-term model forecasts. A state-dependent adaptive error-covariance localization and inflation algorithm controls how the SSH information is extrapolated to the sub-surface. A two-step predictor corrector approach is used to assimilate future information. Independent (not-assimilated) temperature and salinity observations from Argo floats are used to validate the assimilation. A two-step projection method in which the system first calculates a SSH increment and then projects this increment vertically onto the temperature, salt and current fields is found to be most effective in reconstructing the sub-surface information. The performance of the system in reconstructing the sub-surface fields is particularly impressive for temperature, but not as satisfactory for salt.

Keppenne, Christian↗
DOE OSTI2021

Measurement placement in electric power transmission and distribution grids: Review of concepts, methods, and research needs

Sensing and measurement systems are quintessential to the safe and reliable operation of electric power grids. Their strategic placement is of ultimate importance because it is not economically viable to install measurement systems on every node and branch of a power grid, though they need to be monitored. An overwhelming number of strategies have been developed to meet oftentimes multiple conflicting objectives. The prime challenge in formulating the problem lies in developing a heuristic or an optimisation model that, though mathematically tractable and constrained in cost, leads to trustworthy technical solutions. Further, large-scale, long-term deployments pose additional challenges because the boundary conditions change as technologies evolve. For instance, the advent of new technologies in sensing and measurement, as well as in communications and networking, might impact the cost and performance of available solutions and shift initially set conditions. Also, the placement strategies developed for transmission grids might not be suitable for distribution grids, and vice versa, because of unique characteristics; therefore, the strategies need to be flexible, to a certain extent, because no two power grids are alike. Despite the extensive literature on the present topic, the focus of published works tends to be on a specific subject, such as the optimal placement of measurements to ensure observability in transmission grids. There is a dearth of work providing a comprehensive picture for developing optimal placement strategies. Because of the ongoing efforts on the modernisation of electric power grids, there is a need to consolidate the status quo while exposing its limitations to inform policymakers, industry stakeholders, and researchers on the research-and-development needs to push the boundaries for innovation. Accordingly, this paper first reviews the state-of-the-art considering both transmission and distribution grids. Then, it consolidates the key factors to be considered in the problem formulation. Finally, it provides a set of perspectives on the measurement placement problem, and it concludes with future research directions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Online State Estimation for Time-Varying Systems

The paper investigates the problem of estimating the state of a time-varying system with a linear measurement model; in particular, the paper considers the case where the number of measurements available can be smaller than the number of states. In lieu of a batch linear least-squares (LS) approach well-suited for static networks, where a sufficient number of measurements could be collected to obtain a full-rank design matrix the paper proposes an online algorithm to estimate the possibly time-varying state by processing measurements as and when available. The design of the algorithm hinges on a generalized LS cost augmented with a proximal-point-type regularization. With the solution of the regularized LS problem available in closed-form, the online algorithm is written as a linear dynamical system where the state is updated based on the previous estimate and based on the new available measurements. Conditions under which the algorithmic steps are in fact a contractive mapping are shown, and bounds on the estimation error are derived for different noise models. Numerical simulations are provided to corroborate the analytical findings.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Phase curves of small bodies from the SLOAN Moving Objects Catalog

Extensive photometric surveys continue to produce enormous stores of data on small bodies. These data are typically sparsely obtained at arbitrary (or unknown) rotational phases. Therefore, new methods for processing such data need to be developed to make the most of these vast catalogs. We aim to produce a method of recreating the phase curves of small bodies by considering the uncertainties introduced by the nominal errors in the magnitudes and the effect introduced by rotational variations. Here, we use the SLOAN Moving Objects Catalog data as a benchmark to construct phase curves of all small bodies in u', g', r', i', and z' filters. From the phase curves, we obtain the absolute magnitudes and we use them to set up the absolute colors, which are the colors of the asteroids that are not affected by changes in the phase angle. We selected objects with ≥3 observations taken in at least one filter and spanning over a minimum of 5 degrees in the phase angle. We developed a method that combines Monte Carlo simulations and Bayesian inference to estimate the absolute magnitudes using the HG 12 * photometric system. We obtained almost 15 000 phase curves, with about 12 000 of these including all five filters. The absolute magnitudes and absolute colors are compatible with previously published data that support our method. The method we developed is fully automatic and well suited for a run based on large amounts of data. Moreover, it includes the nominal uncertainties in the magnitudes and the whole distribution of possible rotational states of the objects producing what are possibly less precise values, that is, larger uncertainties, but more accurate, namely, closer to the actual value. To our knowledge, this work is the first to include the effect of rotational variations in such a manner.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Characterizing Complexity of Containerized Cargo X-ray Images

X-ray imaging can be used to inspect cargos imported into the United States. In order to better understand the performance of X-ray inspection systems, the X-ray characteristics (density, complexity) of cargo need to be quantified. In this project, an image complexity measure called integrated power spectral density (IPSD) was studied using both DNDO engineered cargos and stream-of-commerce (SOC) cargos. A joint distribution of cargo density and complexity was obtained. A support vector machine was used to classify the SOC cargos into four categories to estimate the relative fractions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Planning for a Distributed Disruption: Innovative Practices for Incorporating Distributed Solar into Utility Planning

The rapid growth of distributed solar photovoltaics (DPV) has critical implications for U.S. utility planning processes. This report informs utility planning through a comparative analysis of roughly 30 recent utility integrated resource plans or other generation planning studies, transmission planning studies, and distribution system plans. It reveals a spectrum of approaches to incorporating DPV across nine key planning areas, and it identifies areas where even the best current practices might be enhanced. (1) Forecasting DPV deployment: Because it explicitly captures several predictive factors, customer-adoption modeling is the most comprehensive forecasting approach. It could be combined with other forecasting methods to generate a range of potential futures. (2) Ensuring robustness of decisions to uncertain DPV quantities: using a capacity-expansion model to develop least-cost plans for various scenarios accounts for changes in net load and the generation portfolio; an innovative variation of this approach combines multiple per-scenario plans with trigger events, which indicate when conditions have changed sufficiently from the expected to trigger modifications in resource-acquisition strategy. (3) Characterizing DPV as a resource option: Today's most comprehensive plans account for all of DPV's monetary costs and benefits. An enhanced approach would address non-monetary and societal impacts as well. (4) Incorporating the non-dispatchability of DPV into planning: Rather than having a distinct innovative practice, innovation in this area is represented by evolving methods for capturing this important aspect of DPV. (5) Accounting for DPV's location-specific factors: The innovative propensity-to-adopt method employs several factors to predict future DPV locations. Another emerging utility innovation is locating DPV strategically to enhance its benefits. (6) Estimating DPV's impact on transmission and distribution investments: Innovative practices are being implemented to evaluate system needs, hosting capacities, and system investments needed to accommodate DPV deployment. (7) Estimating avoided losses associated with DPV: A time-differentiated marginal loss rate provides the most comprehensive estimate of avoided losses due to DPV, but no studies appear to use it. (8) Considering changes in DPV's value with higher solar penetration: Innovative methods for addressing the value changes at high solar penetrations are lacking among the studies we evaluate. (9) Integrating DPV in planning across generation, transmission, and distribution: A few states and regions have started to develop more comprehensive processes that link planning forums, but there are still many issues to address.

14 SOLAR ENERGY↗
DOE OSTI2016

Planning for a Distributed Disruption: Innovative Practices for Incorporating Distributed Solar into Utility Planning

The rapid growth of distributed solar photovoltaics (DPV) has critical implications for U.S. utility planning processes. This report informs utility planning through a comparative analysis of roughly 30 recent utility integrated resource plans or other generation planning studies, transmission planning studies, and distribution system plans. It reveals a spectrum of approaches to incorporating DPV across nine key planning areas, and it identifies areas where even the best current practices might be enhanced. 1) Forecasting DPV deployment: Because it explicitly captures several predictive factors, customer-adoption modeling is the most comprehensive forecasting approach. It could be combined with other forecasting methods to generate a range of potential futures. 2) Ensuring robustness of decisions to uncertain DPV quantities: using a capacity-expansion model to develop least-cost plans for various scenarios accounts for changes in net load and the generation portfolio; an innovative variation of this approach combines multiple per-scenario plans with trigger events, which indicate when conditions have changed sufficiently from the expected to trigger modifications in resource-acquisition strategy. 3) Characterizing DPV as a resource option: Today’s most comprehensive plans account for all of DPV’s monetary costs and benefits. An enhanced approach would address non-monetary and societal impacts as well. 4) Incorporating the non-dispatchability of DPV into planning: Rather than having a distinct innovative practice, innovation in this area is represented by evolving methods for capturing this important aspect of DPV. 5) Accounting for DPV’s location-specific factors: The innovative propensity-to-adopt method employs several factors to predict future DPV locations. Another emerging utility innovation is locating DPV strategically to enhance its benefits. 6) Estimating DPV’s impact on transmission and distribution investments: Innovative practices are being implemented to evaluate system needs, hosting capacities, and system investments needed to accommodate DPV deployment. 7) Estimating avoided losses associated with DPV: A time-differentiated marginal loss rate provides the most comprehensive estimate of avoided losses due to DPV, but no studies appear to use it. 8) Considering changes in DPV’s value with higher solar penetration: Innovative methods for addressing the value changes at high solar penetrations are lacking among the studies we evaluate. 9) Integrating DPV in planning across generation, transmission, and distribution: A few states and regions have started to develop more comprehensive processes that link planning forums, but there are still many issues to address.

14 SOLAR ENERGY↗
NASA NTRS1974

MEGASTAR: The Meaning of Energy Growth: An Assessment of Systems, Technologies, and Requirements

A methodology for the display and analysis of postulated energy futures for the United States is presented. A systems approach that includes the methodology of technology assessment is used to examine three energy scenarios--the Westinghouse Nuclear Electric Economy, the Ford Technical Fix Base Case and a MEGASTAR generated Alternate to the Ford Technical Fix Base Case. The three scenarios represent different paths of energy consumption for the present to the year 2000. Associated with these paths are various mixes of fuels, conversion, distribution, conservation and end-use technologies. MEGASTAR presents the estimated times and unit requirements to supply the fuels, conversion and distribution systems for the postulated end uses for the three scenarios and then estimates the aggregate manpower, materials, and capital requirements needed to develop the energy system described by the particular scenario. The total requirements and the energy subsystems for each scenario are assessed for their primary impacts in the areas of society, the environment, technology and the economy.

Source record↗
NASA NTRS1974

MEGASTAR: The meaning of growth. An assessment of systems, technologies, and requirements

A methodology for the display and analysis of postulated energy futures for the United States is presented. A systems approach methodology including the methodology of technology assessment is used to examine three energy scenarios--the Westinghouse Nuclear Electric Economy, the Ford Technical Fix Base Case and a MEGASTAR generated Alternate to the Ford Technical Fix Base Case. The three scenarios represent different paths of energy consumption from the present to the year 2000. Associated with these paths are various mixes of fuels, conversion, distribution, conservation and end-use technologies. MEGASTAR presents the estimated times and unit requirements to supply the fuels, conversion and distribution systems for the postulated end uses for the three scenarios and then estimates the aggregate manpower, materials, and capital requirements needed to develop the energy system described by the particular scenario.

Source record↗
NASA NTRS1995

Hopkins Ultraviolet Telescope observations of H2 toward the planetary nebula NGC 1535

We have observed the far-ultraviolet spectrum (912-1860 A) of the bright high-excitation planetary nebula NGC 1535 with approximately 3 A resolution using the Hopkins Ultraviolet Telescope (HUT) aboard the Astro-1 space shuttle pmission in 1990 December. We see strong continuum emission down to the Lyman limit and strong P Cygni profiles from high-excitation lines such as C IV wavelength 1549, N V wavelength 1240, O V wavelength 1371, and O VI wavelength 1035. Below 1150 A strong absorption bands of H2 are seen, which were unanticipated by us because of the low reddening and high galactic latitude of the object and the absence of detected H2 emission in the infrared. We construct model H2 spectra and convolve them to the HUT resolution for comparison with the NGC 1535 data. We find good agreement with a population distribution characterized by a single temperature (T = 300 K) or a two-temperature model (T = 144/500 K), and determine limits on the H2 column density. While both inter-stellar and circumstellar origins for the observed H2 absorption are plausible, we ascribe the material to the planetary nebula in order to estimate the conditions of excitation and place upper limits on the mass of both H2 and H1 in this system. Because the UV transitions are ground-state connected, we determine a stringent upper limit of 0.03 d(sup 2)(sub 1.6) solar mass on the mass of H2, where d(sub 1.6) is the distance relative to an assumed distance of 1.6 kpc. This value is less model-dependent than IR estimates. Along with the central star and nebular masses, these estimates allow us to limit the main-sequence mass of the progenitor star to less than 1.8 solar mass. This upper limit is consistent with a relatively low-mass extended thick disk or Population II progenitor, as expected for an object approximately 1 kpc off the galactic plane.

Bowers, Charles W.↗
NASA NTRS2011

Multiple Damage Progression Paths in Model-Based Prognostics

Model-based prognostics approaches employ domain knowledge about a system, its components, and how they fail through the use of physics-based models. Component wear is driven by several different degradation phenomena, each resulting in their own damage progression path, overlapping to contribute to the overall degradation of the component. We develop a model-based prognostics methodology using particle filters, in which the problem of characterizing multiple damage progression paths is cast as a joint state-parameter estimation problem. The estimate is represented as a probability distribution, allowing the prediction of end of life and remaining useful life within a probabilistic framework that supports uncertainty management. We also develop a novel variance control mechanism that maintains an uncertainty bound around the hidden parameters to limit the amount of estimation uncertainty and, consequently, reduce prediction uncertainty. We construct a detailed physics-based model of a centrifugal pump, to which we apply our model-based prognostics algorithms. We illustrate the operation of the prognostic solution with a number of simulation-based experiments and demonstrate the performance of the chosen approach when multiple damage mechanisms are active

Daigle, Matthew↗
NASA NTRSDate not supplied

AEGIS: Autonomous Entity Global Intelligence System for Urban Air Mobility

This paper presents a global intelligence system that synthesizes aerial vehicles’ real-time physical data, planned actions, and historical behavior into engineered data frames representing the collective state of the airspace and suitable for efficient machine learning consumption. These data frames are then learnt by a deep neural net to build a prediction model that estimates the expected evolution path of the current state, thereby identifying potential future conflicts. This approach lends itself to an automated early warning system that the aerial vehicles can implement onboard with a suitable edge computing module more efficiently and effectively than non-AI methods, and eventually take preventive or corrective measures towards self/collaborative resolution of the issues. Contrary to a centralized early warning system where all vehicles’ task-space eventually converges to a global optimum state, the presented distributed global intelligence system brings in a balance between local utility functions of each vehicle and the global operating framework. This contributes to effectively handle the potential massive scaling in urban air mobility in the near future.

Artificial Intelligence↗