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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 1,297 records · Page 72

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NASA NTRS2003

Risk-based analysis and decision making in multi-disciplinary environments

A risk-based decision-making process conceived of and developed at JPL and NASA, has been used to help plan and guide novel technology applications for use on spacecraft. These applications exemplify key challenges inherent in multi-disciplinary design of novel technologies deployed in mission-critical settings. 1) Cross-disciplinary concerns are numerous (e.g., spacecraft involve navigation, propulsion, telecommunications). These concems are cross-coupled and interact in multiple ways (e.g., electromagnetic interference, heat transfer). 2) Time and budget pressures constrain development, operational resources constrain the resulting system (e.g., mass, volume, power). 3) Spacecraft are critical systems that must operate correctly the first time in only partially understood environments, with no chance for repair. 4) Past experience provides only a partial guide: New mission concepts are enhanced and enabled by new technologies, for which past experience is lacking. The decision-making process rests on quantitative assessments of the relationships between three classes of information - objectives (the things the system is to accomplish and constraints on its operation and development), risks (whose occurrence detracts from objectives), and mitigations (options for reducing the likelihood and or severity of risks). The process successfully guides experts to pool their knowledge, using custom-built software to support information gathering and decision-making.

technology↗

NASA NTRS2020

Modeling Whitecaps on Global Scale

Whitecaps play an important role in the surface-atmosphere interactions across the ocean. They are directly linked to the energy dissipation rate during wave breaking and transfer of heat, momentum, and gas/aerosol exchange from the wind to the sea surface. Although the first models of W were dependent only on wind speeds, a large number of diverse models based on wind and sea state which include wave height, wave age, friction velocity, and stability effects have been proposed since then. However, it is recognized that most of the proposed W models have strong systematic (e.g., zonal bias) and random errors when compared against observations. This is partly due to the differences in environmental conditions, measurement techniques, and geographical locations among these studies. But, some of these biases are linked to the inability of the proposed models to capture the variability in W in certain wind/wave regimes. Despite the knowledge of existing biases, W residual relationships from the models with wind and wave fields remain highly uncertain, with residual trends varying between the published studies. Here, we take advantage of the availability of relatively dense observations of W from WindSat microwave satellite retrievals in combination with the University of Miami wave model which was recently incorporated within the NASA GMAO/GEOS system (GEOS-UMWM). We use Windsat W retrievals to assess and constrain the previously published W models and understand the relationships of residuals from models in different wind/wave regimes. We link these unexplained residual variations to additional factors such as swell index, drag coefficient etc and add information to the existing whitecap models. Since Windsat retrievals cover wide range of environmental conditions, it helps to reduce the uncertainties associated with differences in measurement techniques. Regression of wind-wave fields against all Windsat data points (CTL) results in larger residuals for lower wave age and W is overestimated upto ~4% for wave age < 10 and underestimated by upto ~2% as wave age increases. We attest to this bias by considering two approaches. One is to perform regression separately for different stages of wave development such as developing sea, fully developed, and wind sea regimes thereby understanding the sensitivity of regression coefficients to sea state (EXP1). Another is to derive coefficients of W models in EXP1 as a function of additional wind/wave factors such as swell index, drag coefficient, and mean squared slope, deriving more nonlinear W models (EXP2). EXP2 provides reduction in Root Mean Squared Error (RMSE) by 0.1-0.3%. Sea surface drag has a stronger relationship with regression coefficients compared to swell index.These additional factors provide improved parameterizations in different wind and wave age regimes, with smaller unexplained/residual variations in W that has been a major concern in the W community.

Raman, Aishwarya↗

DOE OSTI2017

Morphological and behavioral responses of zebrafish after 24 h of ketamine embryonic exposure

Ketamine, one anesthetic used as an illicit drug, has been detected both in freshwater and marine ecosystems. However, knowledge of its impact on aquatic life is still limited. This study aimed to test its effects in zebrafish embryos by analyzing its time- and dose-dependent developmental toxicity and long-term behavioral changes. The 24 h-LC{sub 50} was calculated from percent survival using probit analysis. Based on the 24 h-LC{sub 50} (94.4 mg L{sup −1}), embryos (2 hour post-fertilization - hpf) were divided into four groups, including control, and exposed for 24 h to ketamine concentrations of 50, 70 or 90 mg L{sup −1}. Developmental parameters were evaluated on the course of the experimental period, and anatomical abnormalities and locomotor deficits were analyzed at 144 hpf. Although the portion of ketamine transferred into the embryo was higher in the lowest exposed group (about 0.056 ± 0.020 pmol per embryo), the results showed that endpoints such as increased mortality, edema, heart rate alterations, malformation and abnormal growth rates were significantly affected. At 144 hpf, the developmental abnormalities included thoracic and trunk abnormalities in the groups exposed to 70 and 90 mg L{sup −1}. Defects in cartilage (alcian blue) and bone (calcein) elements also corroborated the craniofacial anomalies observed. A significant up-regulation of the development-related gene nog3 was detected by qRT-PCR at 8 hpf. Early exposure to ketamine also resulted in long-term behavioral changes, such as an increase in thigmotaxis and disruption of avoidance behavior at 144 hpf. Altogether, this study provides new evidence on the ketamine teratogenic potential, indicating a possible pharmacological impact of ketamine in aquatic environments. - Highlights: • 24 h exposure to ketamine increases mortality. • Morphological changes were observed after exposure. • Exposure to ketamine leads to severe craniofacial anomalies. • Developmental gene expression changes in response to ketamine. • Developmental ketamine exposure produces lasting behavioral changes.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1993

Application of a two-stream radiative transfer model for leaf lignin and cellulose concentrations from spectral reflectance measurements, part 2

We used the Kubelka-Munk theory of diffuse spectral reflectance in layers to analyze influences of multiple chemical components in leaves. As opposed to empirical approaches to estimation of plant chemistry, the full spectral resolution of laboratory reflectance data was retained in an attempt to estimate lignin or other constituent concentrations from spectral band positions. A leaf water reflectance spectrum was derived from theoretical mixing rules, reflectance observations, and calculations from theory of intrinsic k- and s-functions. Residual reflectance bands were then isolated from spectra of fresh green leaves. These proved hard to interpret for composition in terms of simple two component mixtures such as lignin and cellulose. We next investigated spectral and dilution influences of other possible components (starch, protein). These components, among others, added to cellulose in hypothetical mixtures, produce band displacements similar to lignin, but will disguise by dilution the actual abundance of lignin present in a multicomponent system. This renders interpretation of band positions problematical. Knowledge of end-members and their spectra, and a more elaborate mixture analysis procedure may be called for. Good observational atmospheric and instrumental conditions and knowledge thereof are required for retrieval of expected subtle reflectance variations present in spectra of green vegetation.

Conel, James E.↗

DOE OSTI2024

Advances in the photon avalanche luminescence of inorganic lanthanide-doped nanomaterials

Photon avalanche (PA)—where the absorption of a single photon initiates a ‘chain reaction’ of additional absorption and energy transfer events within a material—is a highly nonlinear optical process that results in upconverted light emission with an exceptionally steep dependence on the illumination intensity. Over 40 years following the first demonstration of photon avalanche emission in lanthanide-doped bulk crystals, PA emission has been achieved in nanometer-scale colloidal particles. The scaling of PA to nanomaterials has resulted in significant and rapid advances, such as luminescence imaging beyond the diffraction limit of light, optical thermometry and force sensing with (sub)micron spatial resolution, and all-optical data storage and processing. In this review, we discuss the fundamental principles underpinning PA and survey the studies leading to the development of nanoscale PA. Finally, we offer a perspective on how this knowledge can be used for the development of next-generation PA nanomaterials optimized for a broad range of applications, including mid-IR imaging, luminescence thermometry, (bio)sensing, optical data processing and nanophotonics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Mammograms restoration by using Wiener filter

Restoration of digital mammograms, as a pre-processing tool, using deconvolution procedures, is analysed. It implies, knowing Modulation Transfer Function (MTF) of the mammography device and the estimation of the mammogram’s noise. Wiener filter is used, as the most objective in mammograms restoration by deconvolution. Using MATLAB program the deconvolution procedures are conducted in two ways with different level of approximation. The first method approximates the noise/signal power ratio by a constant and the second method uses autocorrelation functions of the noise and signals. Abilities and limitations of the methods are analysed and checked by using the raw images of the bar-pattern due to better visualisation of the obtained results. The raw images are obtained at a Computed Radiography (CR) mammography device in Clinical Centre in Podgorica. It is found that quality of the restored image highly depends of knowledge of type and magnitude of noise. In the both methods spatial resolution of the restored images are improved, but much better in a case where autocorrelation functions of the noise and signal are used. This procedure is proposed as an objective pre-processing tool to put back imperfectness of mammography devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS2012

Characterization of Spectral Absorption Properties of Aerosols Using Satellite Observations

The wavelength-dependence of aerosol absorption optical depth (AAOD) is generally represented in terms of the Angstrom Absorption Exponent (AAE), a parameter that describes the dependence of AAOD with wavelength. The AAE parameter is closely related to aerosol composition. Black carbon (BC) containing aerosols yield AAE values near unity whereas Organic carbon (OC) aerosol particles are associated with values larger than 2. Even larger AAE values have been reported for desert dust aerosol particles. Knowledge of spectral AAOD is necessary for the calculation of direct radiative forcing effect of aerosols and for inferring aerosol composition. We have developed a satellitebased method of determining the spectral AAOD of absorbing aerosols. The technique uses high spectral resolution measurements of upwelling radiation from scenes where absorbing aerosols lie above clouds as indicated by the UV Aerosol Index. For those conditions, the satellite measured reflectance (rho lambda) is approximately given by Beer's law rho lambda = rho (sub 0 lambda) e (exp -mtau (sub abs lambda)) where rho(sub 0 lambda) is the cloud reflectance, m is the geometric slant path and tau (sub abs lambda) is the spectral AAOD. The rho (sub 0 lambda) term is determined by means of radiative transfer calculations using as input the cloud optical depth derived as described in Torres et al. [JAS, 2012] that accounts for the effects of aerosol absorption. In the second step, corrections for molecular and aerosol scattering effects are applied to the cloud reflectance term, and the spectral AAOD is then derived by inverting the equation above. The proposed technique will be discussed in detail and application results will be presented. The technique can be easily applied to hyper-spectral satellite measurements that include UV such as OMI, GOME and SCIAMACHY, or to multi-spectral visible measurements by other sensors provided that the aerosol-above-cloud events are easily identified.

Torres, O.↗

DOE OSTI2021

A pre-training and self-training approach for biomedical named entity recognition

Named entity recognition (NER) is a key component of many scientific literature mining tasks, such as information retrieval, information extraction, and question answering; however, many modern approaches require large amounts of labeled training data in order to be effective. This severely limits the effectiveness of NER models in applications where expert annotations are difficult and expensive to obtain. In this work, we explore the effectiveness of transfer learning and semi-supervised self-training to improve the performance of NER models in biomedical settings with very limited labeled data (250-2000 labeled samples). We first pre-train a BiLSTM-CRF and a BERT model on a very large general biomedical NER corpus such as MedMentions or Semantic Medline, and then we fine-tune the model on a more specific target NER task that has very limited training data; finally, we apply semi-supervised self-training using unlabeled data to further boost model performance. We show that in NER tasks that focus on common biomedical entity types such as those in the Unified Medical Language System (UMLS), combining transfer learning with self-training enables a NER model such as a BiLSTM-CRF or BERT to obtain similar performance with the same model trained on 3x-8x the amount of labeled data. We further show that our approach can also boost performance in a low-resource application where entities types are more rare and not specifically covered in UMLS.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2013

Microscale Metabolic, Redox and Abiotic Reactions in Hanford 300 Area Subsurface Sediments

The Hanford 300 Area is a unique site due to periodic hydrologic influence of river water resulting in changes in groundwater elevation and flow direction. This area is also highly subject to uranium remobilization, the source of which is currently believed to be the region at the base of the vadose zone that is subject to period saturation due to the changes in the water levels in the Columbia River. We found that microbial processes and redox and abiotic reactions which operate at the microscale were critical to understanding factors controlling the macroscopic fate and transport of contaminants in the subsurface. The combined laboratory and field research showed how microscale conditions control uranium mobility and how biotic, abiotic and redox reactions relate to each other. Our findings extended the current knowledge to examine U(VI) reduction and immobilization using natural 300 Area communities as well as selected model organisms on redox-sensitive and redox-insensitive minerals. Using innovative techniques developed specifically to probe biogeochemical processes at the microscale, our research expanded our current understanding of the roles played by mineral surfaces, bacterial competition, and local biotic, abiotic and redox reaction rates on the reduction and immobilization of uranium.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Evaluation of the Potential for Precipitation of Solids during Storage of Non-Aluminum SNF Solutions

Non-aluminum clad spent nuclear fuels (NASNF) stored in the L-Area basin will be dissolved in H-Canyon using the 6.3D electrolytic dissolver. The solutions will be stored in either the hot or warm canyon until the preparation of a sludge batch for the Defense Waste Processing Facility. Spent nuclear fuel solutions could be stored for 1-2 years before transfer to the H-Area Tank Farm depending on the interval between sludge batches. The solution level in the storage tanks will be maintained; therefore, precipitation of solids due to evaporation is not an issue. However, the precipitation of solids from completely dissolved SNF due to solution instabilities has been observed during intermediate storage of solutions generating hydrated oxides.The presence of fissile material in these solids is generally associated with zirconium molybdate, which is known to act as a host lattice for Pu and can carry the actinides upon precipitation. The formation of zirconium molybdate solids which carry fissile material is a potential concern for the storage of NASNF solutions. To address this concern, the Savannah River National Laboratory performed a literature review to identify knowledge gaps which may require experimental work to determine if the formation of solids is a concern during storage of these solutions. Based on the literature review, the precipitation of zirconium molybdate solids from the Campaign 1 NASNF solutions during intermediatestorage is expected. This conclusion is supported by the identification of zirconium molybdate solids found on the H-Canyon 6.1D Dissolver MK-12 insert spacer. The formation of the zirconium molybdate solids is attributed to hydrolysis and radiolytic processes in the nitric acid solution. As the molybdate solids form, U and Pu can substitute for Zr in the crystal lattice resulting in co-precipitation. Generally, the Pu substitutes directly into the crystal lattice during precipitation while the U associated with the molybdate solids more likely absorbs from the solution. The U in the NASNF solutions is present as uranyl nitrate, a 2+ cation which will not substitute as easily into the molybdate crystal lattice for the Zr 4+ ion.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Guidelines for Publicly Archiving Terrestrial Model Data to Enhance Usability, Intercomparison, and Synthesis

Scientific communities are increasingly publishing data to evaluate, accredit, and build on published research. However, guidelines for curating data for publication are sparse for model-related research, limiting the usability of archived simulation data. In particular, there are no established guidelines for archiving data related to terrestrial models that simulate land processes and their coupled interactions with climate. Terrestrial modelers have a unique set of challenges when publishing data due to the diversity of scientific domains, research questions, and the types and scales of simulations. Researchers in the U.S. Department of Energy’s (DOE) projects use a variety of multiscale models to advance robust predictions of terrestrial and subsurface ecosystem processes. Here, we synthesize archiving needs for data associated with different DOE models, and provide guidelines for publishing terrestrial model data components following FAIR (Findable, Accessible, Interoperable, Reusable) principles. The guidelines recommend archiving model inputs and testing data used in final simulation runs along with associated codes, workflow scripts, and metadata in public repositories. Researchers should consider archiving model outputs if they are within the storage limits of the repository. We also provide considerations for how to bundle files into different data publications with citable digital object identifiers. Finally, we identify repository features and tools that would enable storage and reuse of model data. Given the diversity of DOE terrestrial models, these guidelines are transferable to other model types and will enable efficient reuse of simulation data for purposes such as model intercomparisons, initialization, benchmarking, synthesis, and comparisons with field observations.

58 GEOSCIENCES↗

NASA NTRSDate not supplied

Solar Absorptivity Degradation of Spacecraft Materials Due to UV and Charged Particles in the Gateway Environment

Traditionally, most of the data accumulated for material optical property degradation in space has been in the Low Earth Orbit (LEO) environment. However, Gateway is a new space station that will be assembled and flown in Near Rectilinear Halo Orbit (NRHO) for 15 years. Additionally, some Gateway modules will have a slow transit from Earth to NRHO that will take over a year to pass through the Van Allen Belts, which contain damaging charged particles. The environments Gateway modules will encounter are not well characterized. Environmental factors such as charged particles and ultraviolet (UV) radiation have been shown to significantly increase solar absorptivity (α) for some thermal control materials and coatings. Since α will impact thermal performance over the mission, the Gateway Passive Thermal Control System (PTCS) Group has identified charged particle and UV degradation of Gateway materials as a knowledge gap. Candidate materials and coatings were subjected to expected mission charged particle environments and over 5000 Equivalent Solar Hours (ESH) of UV at NASA Goddard Space Flight Center (GSFC). In situ change in reflectivity was observed at specified intervals during testing such that change in α could be plotted as a function of time of solar exposure.

Optical Property↗

DOE OSTI2017

High Conductivity and Electron-Transfer Validation in an n-Type Fluoride-Anion-Doped Polymer for Thermoelectrics in Air

Air-stable and soluble tetrabutylammonium fluoride (TBAF) is demonstrated as an efficient n-type dopant for the conjugated polymer ClBDPPV. Electron transfer from F - anions to the π-electron-deficient ClBDPPV through anion–π electronic interactions is strongly corroborated by the combined results of electron spin resonance, UV–vis–NIR, and ultraviolet photoelectron spectroscopy. Doping of ClBDPPV with 25 mol% TBAF boosts electrical conductivity to up to 0.62 S cm -1 , among the highest conductivities that have been reported for solution-processed n-type conjugated polymers, with a thermoelectric power factor of 0.63 µW m -1 K -2 in air. Importantly, the Seebeck coefficient agrees with recently published correlations to conductivity. Moreover, the F - -doped ClBDPPV shows significant air stability, maintaining the conductivity of over 0.1 S cm -1 in a thick film after exposure to air for one week, to the best of our knowledge the first report of an air-stable solution-processable n-doped conductive polymer with this level of conductivity. The result shows that using solution-processable small-anion salts such as TBAF as an n-dopant of organic conjugated polymers possessing lower LUMO (lowest unoccupied molecular orbital), less than -4.2 eV) can open new opportunities toward high-performance air-stable solution-processable n-type thermoelectric (TE) conjugated polymers.

36 MATERIALS SCIENCE↗

DOE OSTI2021

A case study on parallel HDF5 dataset concatenation for high energy physics data analysis

In High Energy Physics (HEP), experimentalists generate large volumes of data that, when analyzed, helps us better understand the fundamental particles and their interactions. This data is often captured in many files of small size, creating a data management challenge for scientists. In order to better facilitate data management, transfer, and analysis on large scale platforms, it is advantageous to aggregate data further into a smaller number of larger files. However, this translation process can consume significant time and resources, and if performed incorrectly the resulting aggregated files can be inefficient for highly parallel access during analysis on large scale platforms. In this paper, we present our case study on parallel I/O strategies and HDF5 features for reducing data aggregation time, making effective use of compression, and ensuring efficient access to the resulting data during analysis at scale. We focus on NOvA detector data in this case study, a large-scale HEP experiment generating many terabytes of data. Here, the lessons learned from our case study inform the handling of similar datasets, thus expanding community knowledge related to this common data management task.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Role of inner solvation sheath within salt–solvent complexes in tailoring electrode/electrolyte interphases for lithium metal batteries

Functional electrolyte is the key to stabilizing the highly reductive lithium (Li) metal anode (LMA) and high voltage cathode for long life, high energy-density rechargeable Li metal batteries (LMBs). However, fundamental knowledge of the interaction principles between reactive electrodes and electrolytes is still limited. Recently localized high-concentration electrolytes (LHCEs) are emerging as promising electrolyte design strategies for LMBs. They can also serve as an ideal platform for understanding the reactivity characteristics of the inner solvation sheath on electrode surfaces due to their unique solvation structures. Here, we study the effects of a series of LHCEs with model electrolyte solvents (carbonate, sulfone, phosphate and ether) in high voltage LMBs. Varied electrode stabilities exhibited in different LHCEs indicate the intricate synergies between the salt and the solvent on electrode surfaces. Experimental and theoretical analyses reveal an intriguing general rule that the strong interactions between the salt and the solvent in the inner solvation sheath promote their intermolecular proton/charge transfer reactions, which dictates the properties of the electrode/electrolyte interphases and thus the battery performances.

Solvation sheath, salt-solvent complex, electrode/↗

NASA NTRS1988

RF surface resistance of YBa2Cu3O(7-x) thin films

The excitement engendered by the discovery of the new T sub c oxide superconductors has led to much speculation about practical applications of thin films of these materials in digital and analog electronic devices. Most of these envisioned applications involve high frequency signals for which a detailed knowledge of the surface impedance of the novel superconductors is very important. We have measured the surface resistance of thin films of YBaCuO in the frequency range 0.5 less than f less than 17 GHz using a stripline-resonator method. The stripline procedure also was used to measure the surface resistance of high quality gold and aluminum films; the resistance values obtained agree with values predicted from the measured dc resistance using the Pippard formalism for the anomalous skin effect. The YBaCuO were produced by a multilayer deposition process. The films are formed by e-beam evaporation of 24 layers of Y, Ba, and Cu. Films with the highest transition temperature were obtained using yttria-stabilized zirconia (YSZ) substrates. After deposition, the films are transferred to a furnace where they are annealed in flowing O2 at 850 C for 2h. The furnace then is turned off and allowed to cool to 100 C in about 16 h. Auger profiling of the films made by this process shows that the concentrations of Y, Ba, Cu, and O are uniform to within 1 percent throughout the thickness of the film.

Source record↗

NASA NTRS1991

Systems engineering studies of on-orbit assembly operation

While the practice of construction has a long history, the underlying theory of construction is relatively young. Very little has been documented as to techniques of logistic support, construction planning, construction scheduling, construction testing, and inspection. The lack of 'systems approaches' to construction processes is certainly one of the most serious roadblocks to the construction of space structures. System engineering research efforts at CSC are aimed at developing concepts and tools which contribute to a systems theory of space construction. The research is also aimed at providing means for trade-offs of design parameters for other research areas in CSC. Systems engineering activity at CSC has divided space construction into the areas of orbital assembly, lunar base construction, interplanetary transport vehicle construction, and Mars base construction. A brief summary of recent results is given. Several models for 'launch-on-time' were developed. Launch-on-time is a critical concept to the assembly of such Earth-orbiting structures as the Space Station Freedom, and to planetary orbiters such as the Mars transfer vehicle. CSC has developed a launch vehicle selection model which uses linear programming to find optimal combinations of launch vehicles of various sizes (Atlas, Titan, Shuttles, HLLV's) to support SEI missions. Recently, the Center developed a cost trade-off model for studying on orbit assembly logistics. With this model it was determined that the most effective size of the HLLV would be in the range of 120 to 200 metric tons to LEO, which is consistent with the choices of General Stafford's Synthesis Group Report. A second-generation Dynamic Construction Activities Model ('DYCAM') process model has been under development, based on our past results in interruptability and our initial DYCAM model. This second-generation model is built on the paradigm of knowledge-based expert systems. It is aimed at providing answers to two questions: (1) what are some necessary or sufficient conditions for judging conceptual designs of spacecraft?, and (2) can a methodology be formulated such that these conditions may be used to provide computer-aided tools for evaluating conceptual designs and planning for space assembly sequences? Early simulation results indicate that the DYCAM model has a clear ability to emulate and simulate human orbital construction processes.

Morgenthaler, George W.↗

DOE OSTI2025

Baseflow Identification via Explainable AI With Kolmogorov‐Arnold Networks

Abstract Hydrological models often involve constitutive laws that may not be optimal in every application. We propose to replace such laws with the Kolmogorov‐Arnold networks (KANs), a class of neural networks designed to identify symbolic expressions. We demonstrate KAN's potential on the problem of baseflow identification, a notoriously challenging task plagued by significant uncertainty. KAN‐derived functional dependencies of the baseflow components on the aridity index outperform their original counterparts; they demonstrate that water availability, rather than potential evapotranspiration, drives baseflow by constraining actual evapotranspiration under arid conditions. On a test set, they increase the Nash‐Sutcliffe efficiency (NSE) by 65%, decrease the root mean squared error by 29%, and increase the Kling‐Gupta efficiency by 34%. This superior performance is achieved while reducing the number of fitting parameters from three to two. Next, we use data from 378 catchments across the continental United States to refine the water‐balance equation at the mean‐annual scale. The KAN‐derived equations based on the refined water balance outperform both the current aridity index model, with up to a 105% increase in NSE, and the KAN‐derived equations based on the original water balance. While the performance of our model and tree‐based machine learning methods is similar, KANs offer the advantage of simplicity and transparency and require no specific software or computational tools. This case study focuses on the aridity index formulation, but the approach is flexible and transferable to other hydrological processes. Plain Language Summary Equations used in hydrologic model are often suboptimal, resulting in reduced prediction accuracy and efficiency. We implemented Kolmogorov‐Arnold networks (KAN), a machine learning algorithm for deriving symbolic formulations, to estimate groundwater recharge and showed that it outperforms an existing state‐of‐the‐art semi‐empirical formulation. In hydrology, Nash‐Sutcliffe efficiency (NSE), root mean squared error (RMSE), and Kling‐Gupta efficiency (KGE) are commonly used to evaluate model performance. Higher NSE and KGE values indicate better performance, while lower RMSE values are preferable. Our results show that NSE increased by 71%, RMSE decreased by 32%, and KGE improved by 25%. In addition, KAN identifies an optimal functional form and can be used to derive new analytical formulas using the prior knowledge. The KAN‐inspired equation outperformed the original formulation and reduced the fitting parameters. Furthermore, we refined the water‐balance equation at the mean‐annual scale and showed that, based on the new water‐balance equation, KAN can derive new formulations that are superior to the original aridity index formulations (up to 105% increase in NSE) and KAN‐derived equations based on the original water balance. These findings highlight the significant potential of KAN to advance the scientific understanding of a wide range of hydrologic processes. Key Points Kolmogorov‐Arnold networks (KANs) enhance interpretability of machine‐learned hydrological models KAN‐derived symbolic formulations outperform state‐of‐the‐art semi‐empirical aridity indices KAN‐identified functional form yields an analytical index with fewer fitting parameters and improved performance

baseflow↗