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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Observations of Stably Stratified Flow through a Microscale Gap

This paper reports the findings of a comprehensive field investigation on flow through a mountain gap subject to a range of stably stratified environmental conditions. This study was embedded within the Perdigão field campaign, which was conducted in a region of parallel double-ridge topography with ridge-normal wind climatology. One of the ridges has a well-defined gap (col) at the top, and an array of in situ and remote sensors, including a novel triple Doppler lidar system, was deployed around it. The experimental design was mostly guided by previous numerical and theoretical studies conducted with an idealized configuration where a flow (with characteristic velocity U 0 and buoyancy frequency N ) approaches normal to a mountain of height h with a gap at its crest, for which the governing parameters are the dimensionless mountain height G= (Nh)/U 0 and various gap aspect ratios. Modified forms of G were proposed to account for real-world atmospheric variability, and the results are presented in terms of a gap-averaged value G c . The nature of gap flow was highly dependent on G c , wherein a nearly neutral flow regime (G c <1), a transitional mountain wave regime (G c ~O(1)), and a gap-jetting regime ( G c >O(1)) were identified. The measurements were in broad agreement with previous numerical and theoretical studies on a single ridge with a gap or double ridge topography, although details vary. This is the first ever detailed field study reported on microscale (O(100 m)) gap flows, and provides useful data and insights for future theoretical and numerical studies.

Microscale, Gap, environmental fluid dynamics, win↗
DOE OSTI2023

Band gap predictions of double perovskite oxides using machine learning

Abstract The compositional and structural variety inherent to oxide perovskites spawn wide-ranging applications. In perovskites, the band gap E g , a key material parameter for these applications, can be optimally controlled by varying the composition. Here, we implement a hierarchical screening process in which two cross-validated and predictive machine learning models for band gap classification and regression, trained using exhaustive datasets that span 68 elements of the periodic table, are applied sequentially. The classification model separates wide band gap materials, with E g ≥ 0.5 eV, from materials which have zero or relatively small band gaps, namely E g < 0.5 eV, and the second regression model quantitatively predicts the gap value of the wide band gap compounds. The study down-selects 13,589 cubic oxide perovskite compositions that are predicted to be experimentally formable, thermodynamically stable, and have a wide band gap. Of these, a subset of 310 compounds, which are predicted to be stable and formable with a confidence greater than 90%, are identified for further investigation. Our models are methodically analyzed via performance metrics and inter-dependence of model features to gain physical insight into the band gap prediction problem. Design maps to identify the variation of band gap with substitution of different elements are also presented.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A tunable band gap of the layered semiconductor Zn 3 In 2 S 6 under pressure

The band gap is an important property of a semiconductor, and a candidate material with a highly tunable band gap under external tuning parameters will offer wider applications in optoelectronic devices and photocatalytic fields. Here, we show that the layered semiconductor Zn 3 In 2 S 6 possesses a band gap that is highly tunable with pressure. In situ optical absorption shows that the band gap unexpectedly widens with pressure up to ~13 GPa. Sudden gap narrowing then occurs above 14 GPa, which is followed by progressive gap decreases on further compression and the gap finally closes above 20 GPa. Our study, encompassing X-ray diffraction, Raman spectroscopy experiments and theoretical calculations revealed that the selective responses of the different bonds are responsible for the band gap increase in the low-pressure ranges. We show that the pressure-induced irreversible amorphization is responsible for the sudden gap narrowing whereas the semiconductor–metallic transition is related to the amorphous–amorphous transition at high-pressure due to a change in the local coordination number of Zn atoms. This work demonstrates the high tunability of the electronic and optical properties of layered ternary semiconductors under pressure, providing a potential way for wider applications of this class of materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Impact of symmetry breaking and spin-orbit coupling on the band gap of halide perovskites

Halide perovskite (HP) materials have recently emerged as a class of semiconductors with immense promise for various optoelectronic applications, ranging from solar cells to light-emitting diodes. One of the unique attributes of HPs is their tunable band gaps with different factors governing their value. Furthermore, the first factor is related to relativistic corrections [“mass-Darwin,” connected to the ns 2 lone pairs, and spin-orbit coupling (SOC)] that induce an orbital shift or degeneracy splitting, resulting in a band-gap reduction. The second factor involves the structural configuration: in HPs the local symmetry of each Wyckoff position tends to be broken, inducing an opening of the band gap. Based on high-throughput density functional theory calculations, this paper systematically studies a possible self-cancelation on the band-gap correction for HPs when the polymorphous configuration—structural effects—and the SOC—electronic effects—are included. Our results indicate that the nature of interplay between SOC and symmetry breaking (SB) is that they are independent decoupling effects to describe the band-gap magnitude in halide perovskites. As a result of that, we observe a transitivity of the band-gap description; i.e., if we know the band gap of halide perovskites without SB and SOC, we can independently add the effects of band-gap reduction due to SOC and band-gap opening due to SB, regardless of the order in which these effects are considered.

14 SOLAR ENERGY↗
NASA NTRS2016

Effects of Double-Leakage Tip Clearance Flow on the Performance of a Compressor Stage with a Large Rotor Tip Gap

Effects of a large rotor tip gap on the performance of a one and half stage axial compressor are investigated in detail with a numerical simulation based on LES and available PIV data. The current paper studies the main flow physics, including why and how the loss generation is increased with the large rotor tip gap. The present study reveals that when the tip gap becomes large, tip clearance fluid goes over the tip clearance core vortex and enters into the next blade's tip gap, which is called double-leakage tip clearance flow. As the tip clearance flow enters into the adjacent blade's tip gap, a vortex rope with a lower pressure core is generated. This vortex rope breaks up the tip clearance core vortex of the adjacent blade, resulting in a large additional mixing. This double-leakage tip clearance flow occurs at all operating conditions, from design flow to near stall condition, with the large tip gap for the current compressor stage. The double-leakage tip clearance flow, its interaction with the tip clearance core vortex of the adjacent blade, and the resulting large mixing loss are the main flow mechanism of the large rotor tip gap in the compressor. When the tip clearance is smaller, flow near the end wall follows more closely with the main passage flow and this double-leakage tip clearance flow does not happen near the design flow condition for the current compressor stage. When the compressor with a large tip gap operates at near stall operation, a strong vortex rope is generated near the leading edge due to the double-leakage flow. Part of this vortex separates from the path of the tip clearance core vortex and travels from the suction side of the blade toward the pressure side of the blade. This vortex is generated periodically at near stall operation with a large tip gap. As the vortex travels from the suction side to the pressure side of the blade, a large fluctuation of local pressure forces blade vibration. Nonsynchronous blade vibration occurs due to this vortex as the frequency of this vortex generation is not the same as the rotor. The present investigation confirms that this vortex is a part of separated tip clearance vortex, which is caused by the double-leakage tip clearance flow.

flow↗
NASA NTRS2022

A Novel Machine Learning-Based Gap-Filling of Fine-Resolution Remotely Sensed Snow Cover Fraction Data By Combining Downscaling and Regression

Satellite-based remotely sensed observations of snow cover fraction (SCF) can have data gaps in spatially distributed coverage from sensor and orbital limitations. We mitigate these limitations in the example fine-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) data by gap-filling using auxiliary 1-km datasets that either aid in downscaling from coarser-resolution (5 km) MODIS SCF wherever not fully covered by clouds, or else by themselves via regression wherever fully cloud covered. This study’s prototype predicts a 1-km version of the 500-m MOD10A1 SCF target. Due to noncollocatedness of spatial gaps even across input and auxiliary datasets, we consider a recent gap-agnostic advancement of partial convolution in computer vision for both training and predictive gap-filling. Partial convolution accommodates spatially consistent gaps across the input images, effectively implementing a two-dimensional masking. To overcome reduced usable data from noncollocated spatial gaps across inputs, we innovate a fully generalized three-dimensional masking in this partial convolution. This enables a valid output value at a pixel even if only a single valid input variable and its value exist in the neighborhood covered by the convolutional filter zone centered around that pixel. Thus, our gap-agnostic technique can use significantly more examples for training (∼67%) and prediction (∼100%), instead of only less than 10% for the previous partial convolution. We train an example simple three-layer legacy super-resolution convolutional neural network (SRCNN) to obtain downscaling and regression component performances that are better than baseline values of either climatology or MOD10C1 SCF as relevant. Our generalized partial convolution can enable multiple Earth science applications like downscaling, regression, classification, and segmentation that were hindered by data gaps.

Soni Yatheendradas↗
DOE OSTI2021

Continuous gap measurement

A gap measurement device. The device has a circuit having a variable inductor and a capacitor. The variable inductor has an indicator. The device has a gap that includes a gap measurement and a gap length. The gap measurement is related to the inductance. The gap is configured to receive at least a portion of the variable inductor while the variable inductor moves along the gap length. The movement of the variable inductor along the gap length causes the inductance to change in response to the gap measurement.

Johnson, Joel A.↗
DOE OSTI2021

Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of methane fluxes measured by eddy-covariance require gap-filling to estimate annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for methane, with regards both to the best model algorithms and predictors. In this study, we address the need for standardization by synthesizing results of gap-filling methods applied at 17 wetland sites spanning boreal to tropical regions including all major wetlands classes and two rice paddies. We introduce new procedures for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with robust uncertainty estimates. We tested a conventional method (marginal distribution sampling) and four machine learning algorithms - penalized linear regression, artificial neural networks, random forests, and boosted decision trees - and four predictor sets, including temporal, meteorological, ecosystem carbon and energy flux, and soil predictors. We find that the conventional method can achieve similar median performance to the machine learning models but is worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. Finally, we gap-fill and provide summary evaluation metrics for all 81 sites in the FLUXNET-CH4 community dataset and publicly release the python code for model development, evaluation, and uncertainty estimation.

42 ENGINEERING↗
DOE OSTI2022

Visualizing the interplay of Dirac mass gap and magnetism at nanoscale in intrinsic magnetic topological insulators

In intrinsic magnetic topological insulators, Dirac surface-state gaps are prerequisites for quantum anomalous Hall and axion insulating states. Unambiguous experimental identification of these gaps has proved to be a challenge, however. Here, we use molecular beam epitaxy to grow intrinsic MnBi 2 Te 4 thin films. Using scanning tunneling microscopy/spectroscopy, we directly visualize the Dirac mass gap and its disappearance below and above the magnetic order temperature. We further reveal the interplay of Dirac mass gaps and local magnetic defects. We find that, in high defect regions, the Dirac mass gap collapses. Ab initio and coupled Dirac cone model calculations provide insight into the microscopic origin of the correlation between defect density and spatial gap variations. Finally, this work provides unambiguous identification of the Dirac mass gap in MnBi 2 Te 4 and, by revealing the microscopic origin of its gap variation, establishes a material design principle for realizing exotic states in intrinsic magnetic topological insulators.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Opening band gaps of low-dimensional materials at the meta-GGA level of density functional approximations

The quasiparticle band structure can be properly described by Hedin's GW approximation (GW), at a high computational cost. For band gaps, semilocal density functionals up to the generalized gradient approximation (GGA) level cannot compete with the accuracy of hybrid-based approximations or GW. Meta-GGA density functionals with a strong dependence on the kinetic energy density ingredient can potentially give wider band gaps compared with GGAs. The recent TASK meta-GGA density functional from Aschebrock and Kümmel [ Phys. Rev. Research 1 , 033082 (2019) ], is constructed with an enhanced nonlocality in the generalized Kohn-Sham scheme and therefore harbors great opportunities for band gap prediction. Although this approximation was found to yield excellent band gaps of bulk solids, this accuracy cannot be straightforwardly transferred to low-dimensional materials. Additionally, the reduced screening of these materials results in larger band gaps compared with their bulk counterparts, as an additional barrier to overcome. In this paper we demonstrate how the alteration of this functional affects the band gaps of monolayers and nanoribbons and present accurate band gaps competing with the revised Heyd-Scuseria-Ernzerhof (HSE06) approximation. In order to achieve this goal, we have modified the TASK functional (a) by changing the tight upper bound for one- or two-electron systems ( h X 0 ) from 1.174 to 1.29 and (b) by changing the limit of the interpolation function f X ( α → ∞ ) of the TASK functional that interpolates the exchange enhancement factor F X ( s , α ) from α = 0 to 1. The resulting modified TASK (mTASK) was tested for various materials from three dimensions to two dimensions to one dimension (nanoribbons) and was compared with the results of the higher-level hybrid functional HSE06 or with the G 0 W 0 approximation within many-body perturbation theory. We find that mTASK systematically improves the band gaps and band structures of two-dimensional (2D) and 1D systems, without significantly affecting the accuracy of the original TASK for the bulk 3D materials, when compared with the Perdew-Burke-Ernzerhof (PBE) GGA and the strongly constrained and appropriately normed (SCAN) meta-GGA. We further demonstrate the applicability of mTASK by assessing the band structures of transition metal dichalcogenide nanoribbons with respect to various bending curvatures.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Upward band gap bowing and negative mixing enthalpy in multi-component cubic halide perovskite alloys

Physical properties intermediate between constituents of alloys can be achieved as downward convex positive bowing, upward concave negative bowing, or zero bowing. Such bowing effects are essential for band gap engineering in semiconductor alloys. Upward band gap bowing effects are rather rare, hindering the exploration on half of the available physical property space of alloys. Part of this being a rare event is related to the need to stabilize an alloy with low mixing enthalpy, so it does not phase separate. Here, in this paper, we find via density functional theory that one can satisfy the simultaneous conditions of negative mixing enthalpy and upward band gap bowing in four-component AB⁢X 3 halide perovskite alloys in the cubic perovskite structure. Such perovskite alloys have the B-site occupied by a mixture of group IVB and IIB elements that have the IVB-𝑠 and IIB-s states in the valence bands and conduction bands, respectively, leaving the delocalized 𝑠 states to strongly repel each other. This 𝑠−𝑠 repulsion leads to the upward band gap bowing and negative mixing enthalpies simultaneously. Remarkably, we identify a perovskite alloy that has a band gap much larger than all its components. Analogous trends of upward band gap bowing and negative mixing enthalpy also appear in the corresponding three-component and two-component AB⁢X 3 halide perovskite alloys. These observations of upward band gap bowing and negative mixing enthalpy will significantly accelerate the design of stable upward band gap bowing alloys in a broad range of material families.

14 SOLAR ENERGY↗
DOE OSTI2020

Investigating Core Gaps and the Development of Subcomponent Validation Methods for Wind Turbine Blades: Preprint

Core gaps are a common manufacturing defect observed in wind blade composite sandwich constructions, which occur when sheets of core material are not properly butted up against each other in the mold. The aim of this study was to characterize core gaps in composite sandwich constructions at the coupon scale. This was to gain an initial understanding of the defect before developing appropriate methodologies for more complex subcomponents as part of a much broader wind blade structural validation and damage tolerance program. Long beam flexure in 4-point-bending was chosen as the most appropriate loading scenario. Beam specimens were characterized with and without 10 mm core gaps in fiberglass/balsa sandwich beams. The core gaps were characterized with two separate resin systems; a Hexion epoxy and Arkema's Elium resins system (a novel, infusible thermoplastic). Results showed that the Elium beams without the core gaps were had a 15% lower static strength than their epoxy counterparts. The introduction of the core gap to the epoxy beams reduced their static strength by 35%. The Elium beams, however, exhibited negligible strength reductions with the inclusion of the core gap. Overall, this characterization study provided pertinent information with regards to core gaps as a manufacturing defect to allow for continued development of damage tolerance and subcomponent validation methodologies with the inclusion of manufacturing defects.

17 WIND ENERGY↗
NASA NTRS2003

Gap junctional communication modulates gene transcription by altering the recruitment of Sp1 and Sp3 to connexin-response elements in osteoblast promoters

Loss-of-function mutations of gap junction proteins, connexins, represent a mechanism of disease in a variety of tissues. We have shown that recessive (gene deletion) or dominant (connexin45 overexpression) disruption of connexin43 function results in osteoblast dysfunction and abnormal expression of osteoblast genes, including down-regulation of osteocalcin transcription. To elucidate the molecular mechanisms of gap junction-sensitive transcriptional regulation, we systematically analyzed the rat osteocalcin promoter for sensitivity to gap junctional intercellular communication. We identified an Sp1/Sp3 containing complex that assembles on a minimal element in the -70 to -57 region of the osteocalcin promoter in a gap junction-dependent manner. This CT-rich connexin-response element is necessary and sufficient to confer gap junction sensitivity to the osteocalcin proximal promoter. Repression of osteocalcin transcription occurs as a result of displacement of the stimulatory Sp1 by the inhibitory Sp3 on the promoter when gap junctional communication is perturbed. Modulation of Sp1/Sp3 recruitment also occurs on the collagen Ialpha1 promoter and translates into gap junction-sensitive transcriptional control of collagen Ialpha1 gene expression. Thus, regulation of Sp1/Sp3 recruitment to the promoter may represent a potential general mechanism for transcriptional control of target genes by signals passing through gap junctions.

Non-NASA Center↗
DOE OSTI2021

Assessing the Effects of Temperature and Oxygen Vacancy on Band Gap Renormalization in LaCrO 3-δ : First-Principles and Experimental Corroboration [plus supplemental information]

Understanding the temperature dependence of functional properties in high-temperature gas sensors is vital for applications in combustion environments. Temperature effect on the electronic structure due to electron-phonon coupling is a key property of interest as this influences other responses of sensors. In this work, we assess the impact of temperature on band gap renormalization of pristine and oxygen-vacant LaCrO 3–δ perovskite employing Allen–Heine–Cardona theory with first-principles simulations and corroborate with experimental observation. Antiferromagnetic cubic LaCrO 3 shows a direct ground-state band gap of 2.62 eV that is reduced by over 1 eV due to the presence of oxygen vacancies, which can form endothermically. We find excellent agreement in temperature-dependent band gap shift in LaCrO 3 between theory and an in-house experiment, proving that the theory can adequately predict renormalization on the band gap in a magnetic system. Band gaps in cubic LaCrO 3–δ are found to monotonically narrow by 1.13 eV in pristine and by around 0.62 eV in oxygen-vacant structures as temperature increases from 0 to 1500 K. The predicted band gap variations are rationalized using an analytical model. Furthermore, the experimental zero-temperature band gaps are extracted from the model fits that can provide useful insights on the simulated band gaps.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Alloying multiple halide perovskites on the same sublattice in search of stability and target band gaps

Single-component halide perovskites (HPs) rarely satisfy all the necessary criteria for optoelectronic applications, such as achieving an optimal band gap while maintaining high chemical and structural stability. Alloying halide perovskites has emerged as a promising strategy, not only to enhance stability but also to fine-tune their electronic and optical properties. In this work, we explore multiple degrees of freedom in alloy design, considering different substitution sublattices sites (A, B, or X in ABX3 perovskites), various chemical species (isovalent and hetero-valent elements), and multi-component compositions on a given sublattice. Using first-principles calculations based on density functional theory (DFT), we investigate how compositional variations influence the electronic (band gap) and structural properties (mixing enthalpy) of HP alloys. Our approach employs the polymorphous cell model, allowing full local relaxation which breaks local symmetry while preserving global cubic symmetry—an essential framework for accurately modeling HPs. Our results reveal that X-site mixing (halogen substitution) primarily affects the valence band maximum, allowing target band gap engineering. Additionally, variations in halogen radii introduce internal strain through octahedral distortions, influencing the mixing enthalpy. A-site substitution, while not directly contributing to the band edge states, modifies structural stability via volume effects, indirectly impacting the band gap. B-site alloying plays a dominant role in band gap modulation, leading to either positive or negative band gap bowing. Specifically, isovalent B-site mixing (Sn–Pb) induces strong positive bowing, where the alloy band gap is smaller than the average gap of parent compounds, whereas hetero-valent mixing (Cd–Pb) results in pronounced negative bowing. As an aside, we investigate the competition between the excess energy of disordered alloys vs. that of long-range ordered double perovskites of the same compositions, seeking examples of ordered phases emerging from disordered alloys. Furthermore, our findings provide fundamental insights into the electronic and structural behavior of HP alloys, offering valuable design principles for the development of stable and efficient materials for next-generation photovoltaic and optoelectronic devices.

14 SOLAR ENERGY↗
DOE OSTI2022

Topological alloy engineering and locally linearized gap dependence on concentration

Alloy engineering is a well-established approach to tune various materials’ properties, but its application to topological alloys remains rudimentary. Of special interest is the band gap, the most defining property of topological materials; however, the concentration dependence of energy gaps in topological alloys remains unknown. Here we systematically investigate the band gap evolution of a topological alloy as a function of alloy concentration, using KZnSb 1-x Bi x as a prototype, based on first-principles calculations. In contrast to the well-established smooth bowing curve for a trivial gap in semiconductor alloys, we found that the topological gap evolves generally with a complex fragmented pattern due to topological phase transitions, and most strikingly a linear dependence on concentration locally in each distinct phase. Such gap linearization is fundamentally rooted in the linear dependence on alloy concentration of spin-orbit coupling (SOC) that predominantly determines a topological gap. Furthermore, we demonstrate topological alloy engineering as a general approach to tune the topological order by modulating the band edge composition and degeneracy through the alloying-induced interplay of SOC and atomic orbital on-site energy, while the linear gap dependence on alloy concentration remains independent of the degree of topological order.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Characterization and repair of core gap manufacturing defects for wind turbine blades

Various wind turbine blade components, such as shear webs and skins, commonly use fiber-reinforced composite sandwich structures with a core material like balsa or foam. During manufacturing, core gap defects may result from the misalignment of adjacent foam or balsa core sheets in the blade mold. It is important to understand the influence that core gaps have on the structural integrity of wind turbine blades and how to mitigate their influence. This research characterized the effects of core gap defects at the manufacturing and mechanical levels for both epoxy and next-generation thermoplastic composites. Common repair methods were assessed and compared. Multiple defect sizes were compared using temperature data gathered with thermocouples embedded during manufacturing to core gap defect characteristics obtained using image-mapping techniques, optical microscopy, and mechanical characterization by long beam flexure. Results showed that peak exothermic temperatures during curing were closely related to core gap size. The long beam flexure tests determined that transverse core gaps under pure bending loads can have a substantial effect on the ultimate facesheet strength of both epoxy and thermoplastic composite sandwich structures (up to 25% strength reduction), although the size of the defect itself had less of an influence on the magnitude of the strength reduction. The supporting image-mapping techniques indicated that the distortion of the composite facesheets by the core gaps contributed to the premature failures. The repair methods used in this study did very little to improve the ultimate strength of the sandwich panels that previously had core gap defects. The repair of the thermoplastic panel resulted in a further loss in ultimate facesheet strength. This research demonstrated that there is a vital need for the development of a compatible thermoplastic polymer repair resin system and appropriate resin specific repair procedures for the next generation of recyclable thermoplastic wind blades.

17 WIND ENERGY↗
DOE OSTI2022

Technical note: Using long short-term memory models to fill data gaps in hydrological monitoring networks

Abstract. Quantifying the spatiotemporal dynamics in subsurface hydrological flows over a long time window usually employs a network of monitoring wells. However, such observations are often spatially sparse with potential temporal gaps due to poor quality or instrument failure. In this study, we explore the ability of recurrent neural networks to fill gaps in a spatially distributed time-series dataset. We use a well network that monitors the dynamic and heterogeneous hydrologic exchanges between the Columbia River and its adjacent groundwater aquifer at the U.S. Department of Energy's Hanford site. This 10-year-long dataset contains hourly temperature, specific conductance, and groundwater table elevation measurements from 42 wells with gaps of various lengths. We employ a long short-term memory (LSTM) model to capture the temporal variations in the observed system behaviors needed for gap filling. The performance of the LSTM-based gap-filling method was evaluated against a traditional autoregressive integrated moving average (ARIMA) method in terms of error statistics and accuracy in capturing the temporal patterns of river corridor wells with various dynamics signatures. Our study demonstrates that the ARIMA models yield better average error statistics, although they tend to have larger errors during time windows with abrupt changes or high-frequency (daily and subdaily) variations. The LSTM-based models excel in capturing both high-frequency and low-frequency (monthly and seasonal) dynamics. However, the inclusion of high-frequency fluctuations may also lead to overly dynamic predictions in time windows that lack such fluctuations. The LSTM can take advantage of the spatial information from neighboring wells to improve the gap-filling accuracy, especially for long gaps in system states that vary at subdaily scales. While LSTM models require substantial training data and have limited extrapolation power beyond the conditions represented in the training data, they afford great flexibility to account for the spatial correlations, temporal correlations, and nonlinearity in data without a priori assumptions. Thus, LSTMs provide effective alternatives to fill in data gaps in spatially distributed time-series observations characterized by multiple dominant frequencies of variability, which are essential for advancing our understanding of dynamic complex systems.

54 ENVIRONMENTAL SCIENCES↗