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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Biases in preconstruction estimates of wind plant annual energy production

Estimating the energy yield of a wind plant during the preconstruction phase is a historically difficult task, even with industry improvements in these estimations. We build on prior research comparing the realized energy production of wind plants and their estimated annual energy production P50 values (median energy production), using owner-provided energy production and losses. We produced similar results to prior studies but with a slightly increasing bias of overestimating median energy production (a bias between realized and estimated energy production of −7.4 % to −6.6 %, depending on the scenario, as opposed to −6.7 % to −5.5 % from earlier studies). In addition to assessing annual energy production P50 bias, we compared both the 1-year and the long-term annual energy production P90 and uncertainty energy yield assessment estimates to the observed long-term-corrected energy production. We found that neither the energy yield assessment uncertainty nor the P90 is conservative enough compared to the observed distribution of prediction errors, suggesting significant room for improvement in the energy yield assessment process.

17 WIND ENERGY↗
NASA NTRS1993

Aerodynamic flight control to increase payload capability of future launch vehicles

In this report, we provide some examples of French, Russian, Chinese, and Japanese launch vehicles that have utilized fins in their designs. Next, the aerodynamic design of the fins is considered in Section 3. Some comments on basic static stability and control theory are followed by a brief description of an aerodynamic characteristics prediction code that was used to estimate the characteristics of a modified NLS 1.5 Stage vehicle. Alternative fin designs are proposed and some estimated aerodynamic characteristics presented and discussed. Also included in Section 3 is a discussion of possible methods of enhancement of the aerodynamic efficiency of fins, such as vortex generators and jet flaps. We consider the construction of fins for launch vehicles in Section 4 and offer an assessment of the state-of-the-art in the use of composites for aerodynamic control surfaces on high speed vehicles. We also comment on the use of smart materials for launch vehicle fins. The dynamic stability and control of a launch vehicle that utilizes both thrust vector control (engine nozzle gimballing) and movable fins is the subject addressed in Section 5. We give a short derivation of equations of motion for a launch vehicle moving in a vertical plane above a spherical earth, discuss the use of a gravity-turn nominal trajectory, and give the form of the period equations linearized about such a nominal. We then consider feedback control of vehicle attitude using both engine gimballing and fin deflection. Conclusions are stated and recommendations made in Section 6. An appendix contains aerodynamic data in tabular and graphical formats.

Cochran, John E., Jr.↗
NASA NTRS2008

Exploiting Lunar Natural and Augmented Thermal Environments for Exploration and Research

Near the poles of the Moon, there are permanently shadowed craters whose surface temperatures never exceed 100 K. Craters within craters, commonly referred to as double-shaded craters, have areas where even colder regions exist with, in many cases, temperatures that should never exceed 50 K. The presence of water ice possibly existing in permanently shaded areas of the moon has been hypothesized, discussed, and studied since Watson et al. [1] predicted the possibility of ice on the moon. Ingersoll et al. [2] estimated that the maximum sublimation rate for ice is less than 1 cm per billion years for these types of environments. These potential ice stores have many uses for lunar exploration, potentially providing precious water and rocket fuel for any human exploration or future colonization. The temperatures within these regions offer unprecedented high-vacuum cryogenic environments, which in their natural state could support cryogenic applications such as high-temperature superconductors and associated devices that could be derived. The potential application of naturally occurring cryogenic environments in conjunction with simple methods to augment these environments to achieve even colder temperatures opens the potential use of many additional cryogenic techniques. Besides ice stores and the potential for continuous solar illumination for power production, the unique cryogenic conditions at the lunar poles provide an environment that could reduce the power, weight, and total mass that would have to be carried from the Earth to the Moon for lunar exploration and research.

Ryan, Robert E.↗
NASA NTRS2018

Effect of Distributed Patch of Smooth Roughness Elements on Transition in a High-Speed Boundary Layer

Surface roughness is known to have a substantial impact on the aerothermodynamic loading of hypersonic vehicles, particularly via its influence on the laminar-turbulent transition process within the boundary layer. Numerical simulations are performed to investigate the effects of a distributed region of densely packed, smooth-shaped roughness elements on the laminar boundary layer over a 7-degree half-angle, circular cone for flow conditions corresponding to a selected trajectory point from the ascent phase of the HIFiRE-1 flight experiment. For peak-to-valley roughness heights of 50 percent or less in comparison with the thickness of the unperturbed boundary layer, the computations converge to a stationary flow, suggesting that the flow is globally stable. Analysis of convective instabilities in the wake of the roughness patch indicates two dominant families of unstable disturbances, namely, a high frequency mode that corresponds to Mack mode waves modified by the wake and a lower frequency mode that corresponds to shear layer instabilities associated with the streaks in the roughness wake. Even though the peak growth rate of the later mode is more than 35 percent greater than the peak growth rates of the Mack modes, the latter modes achieve higher amplification ratios, and hence, are likely to dominate the onset of transition, which is estimated to occur slightly later than that in the unperturbed, i.e., smooth surface boundary layer. Additional computations are performed to investigate the effects of various roughness patch configurations on a Mach 3.5 flat plate boundary layer, to help guide an upcoming experiment in the Mach 3.5 Supersonic Low Disturbance Tunnel at NASA Langley Research Center. In this case, the cumulative reinforcement of basic state distortion over the length of the roughness patch is predicted to yield a significantly earlier transition than that over a smooth plate or a plate with a shorter length roughness patch.

Meelan Choudhari↗
DOE OSTI2020

Mesoscale Modeling to Characterize Eagle Soaring Habitat

Uncovering drivers of risk is crucial to understanding interactions between wildlife and wind turbines, and identifying options for impact minimization. These drivers tie to co-variates linked to behavior and movement patterns that allow us to estimate locations and periods of risk. For volant species, atmospheric flow can have significant influence on flight patterns. For obligate soaring birds, like golden eagles, updraft velocities can inform where eagles are likely to travel, at what altitude, and where conditions are not likely sufficient to sustain soaring flight. This has been an active area of study in recent years, using relatively coarse atmospheric data generally at the 20km x 20km scale or larger. Leveraging a 20-year dataset from the Weather Research and Forecasting Model (WRF) (https://www.mmm.ucar.edu/weather-research-and-forecasting-model), we are quantifying vertical velocities across the continental United States at a 2km x 2km resolution. Wind resource data sets originally were static maps showing the mean annual wind speed over an area. However, for these data sets to be optimally used for various applications they must be high-resolution time series, seamlessly span large geographic contexts, and account for uncertainty in wind speed. The National Renewable Energy Laboratory is producing public available datasets that meet these criteria and will be bias corrected to yield the most accurate wind resource data. This effort is an augment to the current WIND Toolkit which houses a high resolution data set. In the new iteration of the WIND Toolkit, a 20-year dataset will be used to improve the accuracy and estimate uncertainty using ensemble and machine-learning techniques. The resulting product will be the most accurate dataset of its size and at a 2km x 2km spatial and 5-minute temporal resolution. Through this work, a mesoscale vertical velocity layer will be produced by calculating the likelihood of orographic updraft and thermal updraft conditions across the continental United States. Specifically, we will use WRF model output combined with digital elevation maps to predict updrafts and then determine if vertical velocities are sufficient to support Golden Eagle soaring and gliding. Ultimately this data layer will be made available as a GIS layer in the Wind Prospector (maps.nrel.gov/wind-prospector/) tool or a similar framework. Data that will be incorporated include wind speed, direction temperature, relative humidity, barometric pressure, air density, precipitation rate, solar radiation, atmospheric stability, skin temperature, and upward heat flux. These products will advance research on interactions between volant species and wind energy by providing open access to highly resolved data with uncertainty quantification not previously available at this scale.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

3D Deep Learning Joint Inversion of Active Seismic Full Waveform and Passive Seismic Traveltime Data for Reservoir Imaging and Uncertainty Quantification

Here, we present deep learning (DL) networks for three-dimensional (3D) joint inversion of active seismic full waveform and passive seismic traveltime data to image reservoirs and their properties and quantify imaging uncertainties. Active seismic full-waveform data can provide high-resolution monitoring images but are collected only intermittently because of their high acquisition cost. In contrast, passive seismic data can be gathered at relatively low cost between regular active surveys, although their imaging quality can be compromised by factors such as low signal-to-noise ratios and limited ray coverage of the target. Although these datasets are routinely acquired together at CO 2 storage sites, their combined inversion within a 3D DL framework has not been previously demonstrated. To our knowledge, this is the first study to address this gap, combining the strength of both data types. For efficient data storage and DL training with large 3D seismic datasets, we use a 3D data matrix in which a random number of passive seismic traveltime data are stored as parabolic envelopes using one-hot encoding and a 3D full-waveform data matrix in which multiple shot gathers are summed. Two network architectures are evaluated: a single-encoder U-Net for single-data type inversion and a dual-encoder U-Net for joint inversion of active and passive seismic data. We also evaluate the single-encoder U-Net for joint inversion by concatenating full-waveform data and traveltime data. We propose a systematic approach for selecting an optimal dropout rate that balances regularization during training and Monte Carlo dropout-based uncertainty quantification during prediction by examining the correlation coefficient between standard deviation and prediction error, along with the training misfit, across a range of dropout rates. 3D DL inversion experiments include five different network configurations, with evaluations under ideal, noisy and dropout-enabled conditions. Both model and data uncertainties are assessed, as well as their combined effects. Across all conditions, the networks consistently predict accurate CO 2 saturation models with low prediction errors, such as a structural similarity index of 0.993 and CO 2 difference of 1.1%. Uncertainty estimates show strong spatial correlation with prediction errors, confirming the effectiveness of the proposed dropout selection approach. The results demonstrate that our DL approach, utilizing compact data representations and appropriate uncertainty quantification, yields accurate subsurface images under various inversion conditions and provides valuable insights into the reliability of predictions.

Um, Evan Schankee [Lawrence Berkeley National Labo↗
DOE OSTI2026

Knowledge Graph of RB-Tnseq Data from Fitness Browser (KP-DP1)

Motivation: Predicting microbial gene fitness across environmental conditions remains a central challenge for predictive phenomics and autonomous experimentation. Fitness assays generate large volumes of genotype–phenotype measurements difficult to integrate with experimental metadata and biological function in a form that supports mechanistic reasoning. Knowledge graphs offer a semantic framework for unifying modalities and enabling context-aware inference. Results: We build GIMME (Graph Inference for Microbial Metabolism Exploration), a semantically grounded knowledge graph that unifies gene fitness measurements spanning 10 Pseudomonas species with experimental metadata and biological context. Media are decomposed into chemical components and experiments carry structured links to natural-language descriptions. The resulting graph supports two inference modes: (1) symbolic graph traversal to surface candidate gene–environment and gene–chemical associations, and (2) learned inference using heterogeneous graph neural networks that propagate information across neighborhoods. We formulate link regression over (gene, media, experiment) triplets, combining learned gene embeddings with pretrained LLM sourced text embeddings of node descriptions to predict gene fitness. We then augment a baseline MLP with an auxiliary message-passing encoder (GraphSAGE/GAT) that propagates information over gene–protein–function and media–chemical subgraphs, and fuse the two pathways with a gated residual connection. This approach produces strong agreement with held-out fitness measurements (GraphSAGE Pearson r 0.74) while also highlighting inference challenges in extreme-fitness regimes. We aggregate GAT edge-attention weights by relation type and layer to estimate which biological and environmental relations most influence fitness predictions. Conclusion: This work explores using knowledge graphs as “context graphs” for microbial phenotype prediction. They provide a rich substrate which enables explainable retrieval of supporting evidence, and provides a natural bridge to autonomous workflows that prioritize the next experiment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Semitauonic b-hadron decays: A lepton flavor universality laboratory

The study of lepton flavor universality violation (LFUV) in semitauonic b-hadron decays has become increasingly important in light of long-standing anomalies in their measured branching fractions, and the large datasets anticipated from the LHC experiments and Belle II. Here, in this review, a comprehensive survey of the experimental environments and methodologies for semitauonic LFUV measurements at the B factories and LHCb is undertaken, along with an overview of the theoretical foundations and predictions for a wide range of semileptonic decay observables. The future prospects of controlling systematic uncertainties down to the percent level, matching the precision of standard model (SM) predictions, are examined. Furthermore, new perspectives and caveats on combinations of the LFUV data are discussed and the world averages for the R(D(*)) ratios are revisited. Here it is demonstrated that different treatments for the correlations of uncertainties from D** excited states can vary the current 3σ tension with the SM within a 1σ range. Prior experimental overestimates of D**τν contributions may further exacerbate this. The precision of future measurements is also estimated; their power to exploit full differential information, and solutions to the inherent difficulties in self-consistent new physics interpretations of LFUV observables, are explored.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1974

Development of modified vibration test criteria for qualifying space vehicle components

Simplified methods are described to estimate the test criteria of primary structures at component attachment points subjected to broadband random acoustic excitations. The current method utilizes a constant smeared component mass attenuation factor across the frequency range of interest. The developed method indicates that the attenuation factor is based on a frequency dependent ratio of the mechanical impedances of both the component and primary structures. The procedures used to predict the structural responses are considered as the present state-of-the-art and provide satisfactory prediction results. Example problems are used to illustrate the application procedures of the two methods and to compare the significant difference. It was found that the lower test criteria obtained by the impedance ratio method is due to the results of considering the effects of component/primary structure interaction.

Chang, K. Y.↗
NASA NTRS1979

Analysis of visual estimation of system state from arbitrary displays

A method is presented for implementing the state estimator of the manual control model when the system output is a visual display of arbitrary form; that is, the display may be pictorial, including real world, or made up of dials and pointers. The method is used to provide error criteria for a look-point controller that appears to be capable of modeling human scanning behavior. This model, if combined with a model of the control process, should be useful in predicting effects of changes in displays on performance of flight tasks.

Gainer, P. A.↗
NASA NTRS1980

Optimum thermal infrared bands for mapping general rock type and temperature from space

A study was carried out to determine quantitatively the number and location of spectral bands required to perform general rock type discrimination from spaceborne imaging sensors using only thermal infrared measurements. Beginning with laboratory spectra collected under idealized conditions from relatively well-characterized homogeneous samples, a radiative transfer model was used to transform ground exitance values into the corresponding spectral radiance at the top of the atmosphere. Taking sensor noise into account, analysis of these data revealed that three 1 micron wide spectral bands would permit independent estimations of rock type and sample temperature from a satellite infrared multispectral scanner. This study, which ignores the mixing of terrain elements within the instantaneous field of view of a satellite scanner, indicates that the location of three spectral bands at 8.1-9.1, 9.5-10.5, and 11.0-12.0 microns, and the employment of appropriate preprocessing to minimize atmospheric effects makes it possible to predict general rock type and temperature for a variety of atmospheric states and temperatures.

Holmes, Q. A.↗
NASA NTRS1982

Metallic bond effects on mean excitation energies for stopping powers

Mean excitation energies for first row metals are evaluated by means of the local plasma approximation. Particle corrections based on Pines' (1953) procedure and the Wigner Seitz (1934) model of the metallic state are included. The agreement with experimental values is remarkably good. In contrast to previous work, the calculations given here estimate shifts in the plasma frequency according to the theory for plane wave states in an extended plasma as calculated by Pines. It is demonstrated that the effects of the metallic bond in lithium and beryllium are quite large and that they appear mainly as a result of collective oscillations in the 'free' electron gas formed from the valence electrons. The usefulness of the plasma frequency shift derived for a degenerate electron gas in predicting the plasma frequency shift within the ion core is considered surprising.

Wilson, J. W.↗
NASA NTRS1988

Data requirements to model creep in 9Cr-1Mo-V steel

Models for creep behavior are helpful in predicting response of components experiencing stress redistributions due to cyclic loads, and often the analyst would like information that correlates strain rate with history assuming simple hardening rules such as those based on time or strain. On the one hand, much progress has been made in the development of unified constitutive equations that include both hardening and softening through the introduction of state variables whose evolutions are history dependent. Although it is difficult to estimate specific data requirements for general application, there are several simple measurements that can be made in the course of creep testing and results reported in data bases. The issue is whether or not such data could be helpful in developing unified equations, and, if so, how should such data be reported. Data produced on a martensitic 9Cr-1Mo-V-Nb steel were examined with these issues in mind.

Swindeman, R. W.↗
NASA NTRS1989

Lifetime predictions for the Solar Maximum Mission (SMM) and San Marco spacecraft

Lifetime prediction techniques developed by the Goddard Space Flight Center (GSFC) Flight Dynamics Division (FDD) are described. These techniques were developed to predict the Solar Maximum Mission (SMM) spacecraft orbit, which is decaying due to atmospheric drag, with reentry predicted to occur before the end of 1989. Lifetime predictions were also performed for the Long Duration Exposure Facility (LDEF), which was deployed on the 1984 SMM repair mission and is scheduled for retrieval on another Space Transportation System (STS) mission later this year. Concepts used in the lifetime predictions were tested on the San Marco spacecraft, which reentered the Earth's atmosphere on December 6, 1988. Ephemerides predicting the orbit evolution of the San Marco spacecraft until reentry were generated over the final 90 days of the mission when the altitude was less than 380 kilometers. The errors in the predicted ephemerides are due to errors in the prediction of atmospheric density variations over the lifetime of the satellite. To model the time dependence of the atmospheric densities, predictions of the solar flux at the 10.7-centimeter wavelength were used in conjunction with Harris-Priester (HP) atmospheric density tables. Orbital state vectors, together with the spacecraft mass and area, are used as input to the Goddard Trajectory Determination System (GTDS). Propagations proceed in monthly segments, with the nominal atmospheric drag model scaled for each month according to the predicted monthly average value of F10.7. Calibration propagations are performed over a period of known orbital decay to obtain the effective ballistic coefficient. Progagations using plus or minus 2 sigma solar flux predictions are also generated to estimate the despersion in expected reentry dates. Definitive orbits are compared with these predictions as time expases. As updated vectors are received, these are also propagated to reentryto continually update the lifetime predictions.

Smith, E. A.↗
NASA NTRS1992

Theoretical simulation of a 2 micron airborne solid state laser anemometer

In the near future, military aircraft will need to know precisely their true airspeed in order to optimize flight conditions. In comparison with classical anemometer probes, an airborne Doppler lidar allows measurement of the air velocity without influence from aircraft aerodynamic disturbance. While several demonstration systems of heterodyne detection using a CO2 laser have been reported, improvements in the technology of solid state lasers have recently opened up the possibility that these devices can be used as an alternative to CO2 laser systems. In particular, a diode pumped Tm:Ho:YAG laser allows a reliable compact airborne system with an eye safe wavelength (lambda = 2.09 microns) to be achieved. The theoretical study of performances of a coherent lidar using a solid state diode pumped Tm:Ho:YAG laser, caled SALSA, for measuring aircraft airspeed relative to atmospheric aerosols is described. A computer simulation was developed in order to modelize the Doppler anemometer in the function of atmospheric propagation and optical design. A clever analysis of the power budget on the detector area allows optical characteristic parameters of the system to be calculated, and then it can be used to predict performances of the Doppler system. Estimating signal to noise ratios (SNR) and heterodyne efficiency provides the available energy of speed measurement as well as a useful measurement of the alignment of the backscattered and reference fields on the detector.

Imbert, Beatrice↗
NASA NTRS1993

Experimental partitioning of Zr, Ti, and Nb between silicate liquid and a complex noble metal alloy and the partitioning of Ti between perovskite and platinum metal

El Goresy et al.'s observation of Nb, Zr, and Ta in refractory platinum metal nuggets (RPMN's) from Ca-Al-rich inclusions (CAI's) in the Allende meteorite led them to propose that these lithophile elements alloyed in the metallic state with noble metals in the early solar nebula. However, Grossman pointed out that the thermodynamic stability of Zr in the oxide phase is vastly greater than metallic Zr at estimated solar nebula conditions. Jones and Burnett suggested this discrepancy may be explained by the very non-ideal behavior of some lithophile transition elements in noble metal solutions and/or intermetallic compounds. Subsequently, Fegley and Kornacki used thermodynamic data taken from the literature to predict the stability of several of these intermetallic compounds at estimated solar nebula conditions. Palme and Schmitt and Treiman et al. conducted experiments to quantify the partitioning behavior of certain lithophile elements between silicate liquid and Pt-metal. Although their results were somewhat variable, they did suggest that Zr partition coefficients were too small to explain the observed 'percent' levels in some RPMN's. Palme and Schmitt also observed large partition coefficients for Nb and Ta. No intermetallic phases were identified. Following the work of Treiman et al., Jurewicz and Jones performed experiments to examine Zr, Nb, and Ti partitioning near solar nebula conditions. Their results showed that Zr, Nb, and Ti all have an affinity for the platinum metal, with Nb and Ti having a very strong preference for the metal. The intermetallic phases (Zr,Fe)Pt3, (Nb,Fe)Pt3, and (Ti,Fe)Pt3 were identified. Curiously, although both experiments and calculations indicate that Ti should partition strongly into Pt-metal (possibly as TiPt3), no Ti has ever been observed in any RPMN's. Fegley and Kornacki also noticed this discrepancy and hypothesized that the Ti was stabilized in perovskite which is a common phase in Allende CAI's.

Jurewicz, Stephen R.↗
NASA NTRS2003

Monitoring of Observation Errors in the Assimilation of Satellite Ozone Data

The stratospheric ozone layer protects life on Earth from the harmful effects of solar ultravioiet radiation. The ozone layer is currently in a fragile state because of depletion caused by man-made chemicals, especially chlorofluorocarbons. The state of the ozone layer is being monitored and evaluated by scientific experts around the world, in order to help policy makers assess the impacts of international protocols that control the production and release of ozone depleting chemicals. Scientists use a variety ozone measurements and models in order to form a comprehensive picture about the current state of the ozone layer, and to predict the future behavior (expected to be a recovery, as the abundance of the depleting chemicals decreases). Among the data sets used, those from satellite-borne instruments have the advantage of providing a wealth of information about the ozone distribution over most of the globe. Several instruments onboard American and international satellites make measurements of the properties of the atmosphere, from which atmospheric ozone amounts are estimated; long-term measurement programs enable monitoring of trends in ozone. However, the characteristics of satellite instruments change in time. For example, the instrument lenses through which measurements are made may deteriorate over time, or the satellite orbit may drift so that measurements over each location are made later and later in the day. These changes may increase the errors in the retrieved ozone amounts, and degrade the quality of estimated ozone amounts and of their variability. Our work focuses on combining the satellite ozone data with global models that capture atmospheric motion and ozone chemistry, using advanced statistical techniques: this is known as data assimilation. Our method provides a three-dimensional global ozone distribution that is consistent with both the satellite measurements and with our understanding of processes (described in the models) that control ozone distribution. Through the monitoring of statistical properties of the agreement between the data and the model, this approach also enables us to detect changes in the quality of ozone data retrieved from satellite-borne instrument measurements. This paper demonstrates that calculations of the changes in satellite data quality, and the impact these changes on the estimates of the global ozone distribution, can assist in maintaining the uniform quality of the satellite ozone data throughout the lifetime of these instruments, thus contributing to our understanding of long-term ozone change.

Stajner, Ivanka↗
DOE OSTI2025

Artificial neural networks estimate evapotranspiration for Miscanthus × giganteus as effectively as empirical model but with fewer inputs

Estimating actual evapotranspiration (ET) is particularly crucial for addressing how vegetation affects the water balance of ecosystems. ET estimation can be complex with empirical models due to their many parameters and reliance on aridity. In contrast, artificial neural networks (ANNs) could potentially estimate ET with fewer and more common meteorological parameters. In this study, we trained two ANNs, one using a feed-forward approach (FFN) and the other a nonlinear auto-regressive network (NARX), to predict ET and compared them to the commonly used empirical model Granger and Gray (GG). We trained our models on a nine-year eddy covariance (EC) dataset for Miscanthu s × giganteus ( M . × giganteus ) from Illinois (UIEF), then tested them using out-of-sample data from both UIEF and a different location in Iowa (SABR) to compare the accuracy of FFN, NARX, and GG models in estimating daily ET. A combination of air temperature (T a ) and solar radiation (R s ) was chosen as inputs due to the highest R 2 for FFN (R 2 = 0.79, 0.81, and 0.79 for training, testing, and validation, respectively) and only T a for NARX (R 2 = 0.70 for out-of-sample validation). The predictive power of the FFN model was superior to the NARX and GG models at the UIEF site (R 2 = 0.84, 0.70, and 0.83 for out-of-sample validation, respectively). Our analysis showed that ANN approaches are as accurate as empirical approaches for estimating ET but use fewer inputs.

54 ENVIRONMENTAL SCIENCES↗