Results for “data base for model validation” — Page 40

NASA NTRS2019

PIV and Rotational Raman-Based Temperature Measurements for CFD Validation of a Perforated Plate Cooling Flow: Part I

Film cooling is used in a wide variety of engineering applications for protection of surfaces from hot or combusting gases. The design of more efficient film cooling geometries/configurations could be facilitated by an ability to accurately model and predict the effectiveness of current designs using computational fluid dynamics (CFD) code predictions. Hence, a benchmark set of flow field property data were obtained for use in assessing current CFD capabilities and for development of better modeling approaches for these turbulent flow fields where accurate calculation of turbulent heat flux is important. Both Particle Image Velocimetry (PIV) and spontaneous rotational Raman scattering (SRS) spectroscopy were used to acquire high quality, spatially-resolved measurements of the mean velocity, turbulence intensity as well as the mean temperature and root mean square (rms) temperatures in a film cooling flow field. In addition to off-body flow field measurements, infrared thermography (IR) and thermocouple measurements on the plate surface enabled estimates of the film effectiveness. Raman spectra in air were obtained across a matrix of axial locations downstream from a 68.07 mm square nozzle blowing heated air over a range of temperatures (up to TR = 2.7) and Mach numbers (up to M0.9), across a 30.48 cm long plate equipped with three patches of 45 small (~1 mm) diameter cooling holes arranged in a staggered configuration. In addition, both centerline streamwise 2-component PIV and cross-stream 3-component Stereo PIV data at 14 axial stations were collected in the same flows. Only a subset of the data collected in the test program is included in this Part I report and are available from the NASA STI office. The final portion of the data will be published in a future report, Part II, along with CFD predictions of the complex cooling film flow.

IR camera Measurments↗

NASA NTRS2020

PIV and Rotational Raman-Based Temperature Measurements for CFD Validation of a Perforated Plate Cooling Flow: Part I

Film cooling is used in a wide variety of engineering applications for protection of surfaces from hot or combusting gases. The design of more efficient film cooling geometries/configurations could be facilitated by an ability to accurately model and predict the effectiveness of current designs using computational fluid dynamics (CFD) code predictions. Hence, a benchmark set of flow field property data was obtained to assess current CFD capabilities and develop better modeling approaches for these turbulent flow fields where accurate calculation of turbulent heat flux is important. Both Particle Image Velocimetry (PIV) and spontaneous rotational Raman scattering (SRS) spectroscopy were used to acquire high quality, spatially-resolved measurements of the mean and root mean square (rms) velocities as well as the mean and rms temperatures in a film cooling flow field. In addition to off-body flow field measurements, infrared thermography (IR) and thermocouple measurements on the plate surface enabled estimates of the film effectiveness. Raman spectra in air were obtained across a matrix of axial locations downstream from a 68.07 mm square nozzle blowing heated air over a range of temperatures (up to TR = 2.7) and Mach numbers (up to Mach 0.9), across a 30.48 cm long plate equipped with three patches of 45 small (~1 mm) diameter cooling holes arranged in a staggered configuration. In addition, both streamwise 2-component PIV (on the plate centerline) and cross-stream 3-component Stereo PIV data at 14 axial stations were collected in the same flows. Only a subset of the data collected in the test program is included in this Part I report. The rest of the data will be published in a future report, Part II, along with planned CFD predictions of the complex cooling film flow. The entire data set of Raman temperature data, PIV velocity data and IR camera data covering the Set Points 23 and 49 in the test matrix in Table 1 is available in an accompanying DVD (available online from www.sti.nasa.gov) for those interested in further analysis.

Nozzle↗

NASA NTRSDate not supplied

High School Citizen Scientists Use AI/ML to Predict Intra-Ocular Pressure From Gene Expression Data for Spaceflown Mice

Artificial Intelligence (AI) and Machine Learning (ML) have increasingly become pivotal in biological and biomedical research, largely due to the culture of open data sharing and its associated benefits. The methodologies inherent in AI/ML are particularly adept at identifying and forecasting biological phenotypes from the vast amounts of data generated by next-generation sequencing technologies. These techniques offer substantial promise for advancing research in space biosciences and for the development of automated systems for monitoring space health. Nevertheless, there are crucial aspects to consider when training, validating, and testing machine learning models in both biological research and clinical contexts. It is essential that Open Science principles, including data sharing and the availability of open-source code, are complemented by high-quality, publicly accessible training resources. These resources should focus on best practices and include modules based on real-world scientific cases and data to ensure that future AI/ML practitioners gain practical experience with genuine problems. Addressing this knowledge gap, we have designed, developed, and delivered both interactive and self-paced training programs for citizen scientists worldwide, enabling them to utilize AI/ML for space biology research. This initiative was made possible through generous funding from a Transformation to Open Science Training grant. The interactive training sessions, conducted this summer, utilized AI/ML techniques to analyze data from the Open Science Data Repository, specifically targeting the effects of spaceflight on ocular structure and function. The dataset OSD-583, from the Rodent Research 9 mission, provides experimental data detailing the ocular responses of mice subjected to a 35-day spaceflight, compared with ground control counterparts. Using OSD-583 as observational data, our summer training participants applied AI/ML methods to predict intraocular pressure from RNA-seq data and identify the genes most predictive of the observed responses. Further analysis through pathway enrichment and gene set enrichment revealed that these genes are involved in molecular and cellular processes contributing to retinal degeneration.

James Casaletto↗

NASA NTRS2017

Mapping 2000 2010 Impervious Surface Change in India Using Global Land Survey Landsat Data

Understanding and monitoring the environmental impacts of global urbanization requires better urban datasets. Continuous field impervious surface change (ISC) mapping using Landsat data is an effective way to quantify spatiotemporal dynamics of urbanization. It is well acknowledged that Landsat-based estimation of impervious surface is subject to seasonal and phenological variations. The overall goal of this paper is to map 200-02010 ISC for India using Global Land Survey datasets and training data only available for 2010. To this end, a method was developed that could transfer the regression tree model developed for mapping 2010 impervious surface to 2000 using an iterative training and prediction (ITP) approach An independent validation dataset was also developed using Google Earth imagery. Based on the reference ISC from the validation dataset, the RMSE of predicted ISC was estimated to be 18.4%. At 95% confidence, the total estimated ISC for India between 2000 and 2010 is 2274.62 +/- 7.84 sq km.

Wang, Panshi↗

NASA NTRS2005

Assessment of the Broadleaf Crops Leaf Area Index Product from the Terra MODIS Instrument

The first significant processing of Terra MODIS data, called Collection 3, covered the period from November 2000 to December 2002. The Collection 3 leaf area index (LAI) and fraction vegetation absorbed photosynthetically active radiation (FPAR) products for broadleaf crops exhibited three anomalies (a) high LAI values during the peak growing season, (b) differences in LAI seasonality between the radiative transfer-based main algorithm and the vegetation index based back-up algorithm, and (c) too few retrievals from the main algorithm during the summer period when the crops are at full flush. The cause of these anomalies is a mismatch between reflectances modeled by the algorithm and MODIS measurements. Therefore, the Look-Up-Tables accompanying the algorithm were revised and implemented in Collection 4 processing. The main algorithm with the revised Look-Up-Tables generated retrievals for over 80% of the pixels with valid data. Retrievals from the back-up algorithm, although few, should be used with caution as they are generated from surface reflectances with high uncertainties.

Tan, Bin↗

NASA NTRS2017

Estimating Surface Soil Moisture from SMAP Observations Using a Neural Network Technique

A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to March 2017 with a 2-3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observing System Model version 5 (GEOS-5) land modeling system, and Moderate Resolution Imaging Spectroradiometer-based vegetation water content. The NN was trained on GEOS-5 soil moisture target data, making the NN estimates consistent with the GEOS-5 climatology, such that they may ultimately be assimilated into this model without further bias correction. Evaluated against in situ soil moisture measurements, the average unbiased root mean square error (ubRMSE), correlation and anomaly correlation of the NN retrievals were 0.037 m(exp. 3)m(exp. -3), 0.70 and 0.66, respectively, against SMAP core validation site measurements and 0.026 m(exp. 3)m(exp. -3), 0.58 and 0.48, respectively, against International Soil Moisture Network (ISMN) measurements. At the core validation sites, the NN retrievals have a significantly higher skill than the GEOS-5 model estimates and a slightly lower correlation skill than the SMAP Level-2 Passive (L2P) product. The feasibility of the NN method was reflected by a lower ubRMSE compared to the L2P retrievals as well as a higher skill when ancillary parameters in physically-based retrievals were uncertain. Against ISMN measurements, the skill of the two retrieval products was more comparable. A triple collocation analysis against Advanced Microwave Scanning Radiometer 2 (AMSR2) and Advanced Scatterometer (ASCAT) soil moisture retrievals showed that the NN and L2P retrieval errors have a similar spatial distribution, but the NN retrieval errors are generally lower in densely vegetated regions and transition zones.

Soil Moisture Remote Sensing↗

NASA NTRS2004

Simulation of Hyperspectral Images

A software package generates simulated hyperspectral imagery for use in validating algorithms that generate estimates of Earth-surface spectral reflectance from hyperspectral images acquired by airborne and spaceborne instruments. This software is based on a direct simulation Monte Carlo approach for modeling three-dimensional atmospheric radiative transport, as well as reflections from surfaces characterized by spatially inhomogeneous bidirectional reflectance distribution functions. In this approach, "ground truth" is accurately known through input specification of surface and atmospheric properties, and it is practical to consider wide variations of these properties. The software can treat both land and ocean surfaces, as well as the effects of finite clouds with surface shadowing. The spectral/spatial data cubes computed by use of this software can serve both as a substitute for, and a supplement to, field validation data.

Richsmeier, Steven C.↗

NASA NTRS2020

Evaluation and Validation of a High Spatial Resolution Satellite Soil Moisture Product over the Continental United States

The soil moisture (SM) data retrieved from the Soil Moisture Active and Passive (SMAP) satellite are available at a 9 km grid spacing since April 2015. This product can provide valuable information for research and applications in hydrology and other related fields. However, the resolution may be too coarse for applications at catchment or field scale. In this study, an established downscaling methodology, which had a major modification regarding its application on the SMAP 33 km domain, was implemented to develop a 1 km soil moisture product based on the SMAP 9 km data. The algorithm proposed here is based on the thermal inertia principle and developed by modeling the relationship between surface temperature difference and SM for different Normalized Difference Vegetation Index (NDVI) classes. The model functions were established and tuned using data from the NASA’s Land Information System (LIS) North America Land Data Assimilation System (NLDAS) and remotely sensed VISible/InfRared (VIS/IR) reflectance data from Long Term Data Record (LTDR) AVHRR (Advanced Very High Resolution Radiometer) for the growing season months of April-September 1981–2018. These were then implemented using the MODIS (Moderate Resolution Imaging Spectroradiometer) data over the Continental United States (CONUS) domain. Validation activities were carried out using in situ measurements distributed through the International Soil Moisture Network (ISMN). The validation results computed using the 1 km SM data showed that the R2, unbiased RMSE (root mean square error) and bias were improved relative to the 9 km SMAP product by 0.045, 0.018m3/m3 and 0.001m3/m3, respectively. The 1 km SM also exhibited a strong time-series autocorrelation. Further accuracy assessment analyses indicated that precipitation might contribute to the uncertainties in both the 9 km SMAP and 1 km downscaled SMAP SM products.

SMAP↗

NASA NTRS2019

PIV and Rotational Raman-Based Temperature Measurements for CFD Validation of a Perforated Plate Cooling Flow: Part 1

Film cooling is used in a wide variety of engineering applications for protection of surfaces from hot or combusting gases. The design of more efficient film cooling geometries/configurations could be facilitated by an ability to accurately model and predict the effectiveness of current designs using computational fluid dynamics (CFD) code predictions. Hence, a benchmark set of flow field property data were obtained for use in assessing current CFD capabilities and for development of better modeling approaches for these turbulent flow fields where accurate calculation of turbulent heat flux is important. Both Particle Image Velocimetry (PIV) and spontaneous rotational Raman scattering (SRS) spectroscopy were used to acquire high quality, spatially-resolved measurements of the mean velocity, turbulence intensity as well as the mean temperature and root mean square (rms) temperatures in a film cooling flow field. In addition to off-body flow field measurements, infrared thermography (IR) and thermocouple measurements on the plate surface enabled estimates of the film effectiveness. Raman spectra in air were obtained across a matrix of axial locations downstream from a 68.07 mm square nozzle blowing heated air over a range of temperatures (up to TR = 2.7) and Mach numbers (up to M0.9), across a 30.48 cm long plate equipped with three patches of 45 small (~1 mm) diameter cooling holes arranged in a staggered configuration. In addition, both centerline streamwise 2-component PIV and cross-stream 3-component Stereo PIV data at 14 axial stations were collected in the same flows. Only a subset of the data collected in the test program is included in this Part I report and are available from the NASA STI office. The final portion of the data will be published in a future report, Part II, along with CFD predictions of the complex cooling film flow.

Raman Scattering↗

NASA NTRS2015

V-SUIT Model Validation Using PLSS 1.0 Test Results

The dynamic portable life support system (PLSS) simulation software Virtual Space Suit (V-SUIT) has been under development at the Technische Universitat Munchen since 2011 as a spin-off from the Virtual Habitat (V-HAB) project. The MATLAB(trademark)-based V-SUIT simulates space suit portable life support systems and their interaction with a detailed and also dynamic human model, as well as the dynamic external environment of a space suit moving on a planetary surface. To demonstrate the feasibility of a large, system level simulation like V-SUIT, a model of NASA's PLSS 1.0 prototype was created. This prototype was run through an extensive series of tests in 2011. Since the test setup was heavily instrumented, it produced a wealth of data making it ideal for model validation. The implemented model includes all components of the PLSS in both the ventilation and thermal loops. The major components are modeled in greater detail, while smaller and ancillary components are low fidelity black box models. The major components include the Rapid Cycle Amine (RCA) CO2 removal system, the Primary and Secondary Oxygen Assembly (POS/SOA), the Pressure Garment System Volume Simulator (PGSVS), the Human Metabolic Simulator (HMS), the heat exchanger between the ventilation and thermal loops, the Space Suit Water Membrane Evaporator (SWME) and finally the Liquid Cooling Garment Simulator (LCGS). Using the created model, dynamic simulations were performed using same test points also used during PLSS 1.0 testing. The results of the simulation were then compared to the test data with special focus on absolute values during the steady state phases and dynamic behavior during the transition between test points. Quantified simulation results are presented that demonstrate which areas of the V-SUIT model are in need of further refinement and those that are sufficiently close to the test results. Finally, lessons learned from the modelling and validation process are given in combination with implications for the future development of other PLSS models in V-SUIT.

Olthoff, Claas↗

NASA NTRS1986

Three dimensional unsteady aerodynamics and aeroelastic response of advanced turboprops

A method for the prediction of steady and unsteady aerodynamic loads and aeroelastic response of advanced turboprops is presented. The aerodynamic analysis uses three dimensional unsteady linearized compressible flow theory to compute the blade pressure distribution. The aeroelastic analysis is based on a normal mode representation of the structure. The method is applicable to both conventional and advanced turbo-prop configurations, provided that blade stall and transonic shock waves are not important factors. Aerodynamic results are presented which validate the model in various limits by comparisons to alternative theories and experimental data. Finally, results of a stability analysis of an advanced turboprop are given, with comparisons to measurements made at NASA Lewis Research Center.

Williams, M. H.↗

NASA NTRS1990

Expert systems and imaging - NASA's start-up work in intelligent image management

The problem of image management for NASA's Space Shuttle program and the future role of expert systems are considered. The difficulties involved in the storage and retrieval of the estimated 100,000 color photographs used for verification of essential installation, test, and repair procedures for Space Shuttle prelaunch are discussed. It is noted that the collection, classification, storage, and retrieval of high-quality pictoral images is possible through the use of pixels and an expert systems-assisted relational data base management system. The development of a query by pictorial example process is discussed. The NASA Intelligent Interactive Visual Data Base Management Systems project is detailed. It aims to conduct a systems analysis of a large-scale traditional image processing operation, collect data on critical human performance factors in the areas of image creation, processing, classification, storage, and retreival, and validate the attributes identified through the creation and testing of prototype models.

Ragusa, James M.↗

NASA NTRS1992

Combustion of LOX with H2(sub g) under subcritical, critical, and supercritical conditions and experimental observation of dense spray and mixing of impinging jets

Progress made during the period of February 1 to October 15, 1992 is reported. The overall objective of Task 1 of the investigation is to achieve a better understanding of the combustion processes of liquid oxygen and gaseous hydrogen under subcritical, critical, and supercritical conditions. Specific objectives of the research program are: (1) to determine the evaporation- and burning-rate characteristics of LOX in hydrogen/helium environments under broad ranges of operating conditions; (2) to measure species concentration profile and surface temperature of LOX employing the gas chromatography and fine-wire thermocouples under non-reacting flow situations; (3) to perform a fugacity-based multicomponent thermodynamic phase equilibrium analysis for examining the high-pressure vapor-liquid equilibrium behavior at the liquid surface of LOX; (4) to formulate and solve a theoretical model for simulating the evaporation and combustion processes in a LOX/H2/He system; and (5) to validate the theoretical model with the measured experimental data. Task 2 of the investigation is described. Observation of a like-on-like injector element in the near-injector region performed in the previous phase of this project has identified the existence of a high Reynolds number regime in which the pre-impingement jets are fully turbulent and undergoing surface breakup. The new spray regime, which has not been observed by previous investigators, is characterized by the presence of many fine droplets and the disappearance of the well-defined liquid breakup wave pattern in the post-impingement region. It is speculated that a cavitating region may be present within the orifice so that it could induce strong turbulence, leading to an onset of atomization of the jets prior to impingement. To further investigate the dense spray behavior of the impinging jets in the high Reynolds number region, experiments were conducted using Plexiglas injector components for direct internal flow observation. The main objective is to determine under what conditions a cavitating region would form and whether or not the cavitation is reponsible for the development of the high Reynolds number spray regime. The procedure and major findings of the injector cavitation study are described.

Kuo, Kenneth K.↗

NASA NTRS1990

Validation of the dynamic response of a blade-element UH-60 simulation model in hovering flight

The dynamic fidelity of an operational blade-element simulation model of the UH-60A helicopter is assessed for the hovering and low-speed flight regimes. Nonparametric frequency-response identification techniques and time-history comparisons are used to determine the validity of vehicle responses. Frequency-domain methods are applied to the model to isolate deficiencies and verify refinements and corrections. A dedicated flight-test program was conducted to provide data used in the analyses. Model deficiencies are also identified by using side-by-side pilot assessments of a motion-based simulation and of a test aircraft. Model refinements are found to improve fidelity significantly in the frequency range of interest to handling-qualities research. The applicability of the model to high-bandwidth flight-control research is also discussed.

Ballin, Mark G.↗

NASA NTRS1998

Design and Operational Characteristics of the Shuttle Coherent Wind Lidar

NOAA has identified the measurement of atmospheric wind velocities as one of the key unmet data sets for its next generation of sensing platforms. The merits of coherent lidars for the measurement of atmospheric winds from space platforms have been widely recognized; however, it is only recently that several key technologies have advanced to a point where a compact, high fidelity system could be created. Advances have been made in the areas of the diode-pumped, eye-safe, solid state lasers and room temperature, wide bandwidth, semiconductor detectors operating in the near-infrared region. These new lasers can be integrated into efficient and compact optical systems creating new possibilities for the development of low-cost, reliable, and compact coherent lidar systems for wind measurements. Over the past five years, the University of Alabama in Huntsville (UAH) has been working toward further advancing the solid state coherent lidar technology for the measurement of atmospheric winds from space. As part of this effort, UAH had established the design characteristics and defined the expected performance for three different proposed space-based instruments: a technology demonstrator, an operational prototype, and a 7-year lifetime operational instrument. SPARCLE is an ambitious project that is intended to evaluate the suitability of coherent lidar for wind measurements, demonstrate the maturity of the technology for space application, and provide a useable data set for model development and validation. This paper describes the SPARCLE instrument's major physical and environmental design constraints, optical and mechanical designs, and its operational characteristics.

Amzajerdian, Farzin↗

NASA NTRS2012

Validation of MODIS FLH and In Situ Chlorophyll a from Tampa Bay, Florida (USA)

Satellite observation of phytoplankton concentration or chlorophyll-a (chla) is an important characteristic, critically integral to monitoring coastal water quality. However, the optical properties of estuarine and coastal waters are highly variable and complex and pose a great challenge for accurate analysis. Constituents such as suspended solids and dissolved organic matter and the overlapping and uncorrelated absorptions in the blue region of the spectrum renders the blue-green ratio algorithms for estimating chl-a inaccurate. Measurement of suninduced chlorophyll fluorescence, on the other hand, which utilizes the near infrared portion of the electromagnetic spectrum may, provide a better estimate of phytoplankton concentrations. While modelling and laboratory studies have illustrated both the utility and limitations of satellite algorithms based on the sun induced chlorophyll fluorescence signal, few have examined the empirical validity of these algorithms or compared their accuracy against bluegreen ratio algorithms . In an unprecedented analysis using a long term (2003-2011) in situ monitoring data set from Tampa Bay, Florida (USA), we assess the validity of the FLH product from the Moderate Resolution Imaging Spectrometer against a suite of water quality parameters taken in a variety of conditions throughout this large optically complex estuarine system. . Overall, the results show a 106% increase in the validity of chla concentration estimation using FLH over the standard chla estimate from the blue-green OC3M algorithm. Additionally, a systematic analysis of sampling sites throughout the bay is undertaken to understand how the FLH product responds to varying conditions in the estuary and correlations are conducted to see how the relationships between satellite FLH and in situ chlorophyll-a change with depth, distance from shore, from structures like bridges, and nutrient concentrations and turbidity. Such analysis illustrates that the correlations between FLH and in situ chla measurements increases with increasing distance between monitoring sites and structures like bridges and shore. Due probably to confounding factors, expected improvement in the FLH- chla relationship was not clearly noted when increasing depth and distance from shore alone (not including bridges). Correlations between turbidity and nutrient concentrations are discussed further and principle component analyses are employed to address the relationships between the multivariate data sets. A thorough understanding of how satellite FLH algorithms relate to in situ water quality parameters will enhance our understanding of how MODIS s global FLH algorithm can be used empirically to monitor coastal waters worldwide.

Fischer, Andrew↗

NASA NTRS2017

Predicting the Operational Acceptability of Route Advisories

NASA envisions a future Air Traffic Management system that allows safe, efficient growth in global operations, enabled by increasing levels of automation and autonomy. In a safety-critical system, the introduction of increasing automation and autonomy has to be done in stages, making human-system integrated concepts critical in the foreseeable future. One example where this is relevant is for tools that generate more efficient flight routings or reroute advisories. If these routes are not operationally acceptable, they will be rejected by human operators, and the associated benefits will not be realized. Operational acceptance is therefore required to enable the increased efficiency and reduced workload benefits associated with these tools. In this paper, the authors develop a predictor of operational acceptability for reroute advisories. Such a capability has applications in tools that identify more efficient routings around weather and congestion and that better meet airline preferences. The capability is based on applying data mining techniques to flight plan amendment data reported by the Federal Aviation Administration and data on requested reroutes collected from a field trial of the NASA developed Dynamic Weather Routes tool, which advised efficient route changes to American Airlines dispatchers in 2014. 10-Fold cross validation was used for feature, model and parameter selection, while nested cross validation was used to validate the model. The model performed well in predicting controller acceptance or rejection of a route change as indicated by chosen performance metrics. Features identified as relevant to controller acceptance included the historical usage of the advised route, the location of the maneuver start point relative to the boundaries of the airspace sector containing the maneuver start (the maneuver start sector), the reroute deviation from the original flight plan, and the demand level in the maneuver start sector. A random forest with forty trees was the best performing of the five models evaluated in this paper.

route advisories↗

NASA NTRS2017

Predicting the Operational Acceptability of Route Advisories

NASA envisions a future Air Traffic Management system that allows safe, efficient growth in global operations, enabled by increasing levels of automation and autonomy. In a safety-critical system, the introduction of increasing automation and autonomy has to be done in stages, making human-system integrated concepts critical in the foreseeable future. One example where this is relevant is for tools that generate more efficient flight routings or reroute advisories. If these routes are not operationally acceptable, they will be rejected by human operators, and the associated benefits will not be realized. Operational acceptance is therefore required to enable the increased efficiency and reduced workload benefits associated with these tools. In this paper, the authors develop a predictor of operational acceptability for reroute advisories. Such a capability has applications in tools that identify more efficient routings around weather and congestion and that better meet airline preferences. The capability is based on applying data mining techniques to flight plan amendment data reported by the Federal Aviation Administration and data on requested reroutes collected from a field trial of the NASA developed Dynamic Weather Routes tool, which advised efficient route changes to American Airlines dispatchers in 2014. 10-Fold cross validation was used for feature, model and parameter selection, while nested cross validation was used to validate the model. The model performed well in predicting controller acceptance or rejection of a route change as indicated by chosen performance metrics. Features identified as relevant to controller acceptance included the historical usage of the advised route, the location of the maneuver start point relative to the boundaries of the airspace sector containing the maneuver start (the maneuver start sector), the reroute deviation from the original flight plan, and the demand level in the maneuver start sector. A random forest with forty trees was the best performing of the five models evaluated in this paper.

operational acceptability↗