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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Identifying the mechanisms of cation inhibition of phenol oxidation by acid birnessite

Abstract Many phenolic compounds found as contaminants in natural waters are susceptible to oxidation by manganese oxides. However, there is often variability between oxidation rates reported in pristine matrices and studies using more environmentally relevant conditions. For example, the presence of cations generally results in slower phenolic oxidation rates. However, the underlying mechanism of cation interference is not well understood. In this study, cation co‐solutes inhibit the transformation of four target phenols (bisphenol A, estrone, p ‐cresol, and triclosan) by acid birnessite. Oxidation rates for these compounds by acid birnessite follow the same trend (Na + > K + > Mg 2+ > Ca 2+ ) when cations are present as co‐solutes. We further demonstrate that the same trend applies to these cations when they are absent from solution but pre‐exchanged with the mineral. We analyze valence state, surface area, crystallinity, and zeta potential to characterize changes in oxide structure. The findings of this study show that pre‐exchanged cations have a large effect on birnessite reactivity even in the absence of cation co‐solutes, indicating that the inhibition of phenolic compound oxidation is not due to competition for surface sites, as previously suggested. Instead, the reaction inhibition is attributed to changes in aggregation and the mineral microstructure.

Balgooyen, Sarah↗
DOE OSTI2024

A practical approach to using the Genomic Standards Consortium MIxS reporting standard for comparative genomics and metagenomics

Comparative analysis of (meta)genomes necessitates aggregation, integration, and synthesis of well-annotated data using standards. The Genomic Standards Consortium (GSC) collaborates with the research community to develop and maintain the Minimal Information about any (x) Sequence (MIxS) reporting standard for genomic data. To facilitate use of the GSC’s MIxS reporting standard, we provide a description of the structure and terminology, how to navigate ontologies for required terms in MIxS, and demonstrate practical usage through a soil metagenome example.

standards, metadata, genome, metagenome, schema, v↗
DOE OSTI2017

Effect of nanoparticles size and polyelectrolyte on nanoparticles aggregation in a cellulose fibrous matrix

Controlling nanoparticles (NPs) aggregation in cellulose/NPs composites allows to optimise NPs driven properties and their applications. Polyelectrolytes are used to control NPs aggregation and their retention within the fibrous matrix. Here in this study, we aim at evaluating how a polyelectrolyte (Cationic Polyacrylamide; CPAM, molecular weight: 13 MDa, charge: 50%, Radius of gyration: 30–36 nm) adsorbs and re-conforms onto the surface of silica(SiO 2 ) NPs differing in diameter (8, 22 and 74 nm) and to investigate the respective NPs aggregation in cellulose matrices. SEM shows the local area distribution of NPs in composites. Ultra-SAXS (USAXS) allows to evaluate the average NPs size distribution and the inter-particle interactions at length scale ranging from 1 to 1000 nm. USAXS data analysis reveals that CPAM covers multiple NPs of the smaller diameter (8 nm), presumably with a single chain to form large size NPs aggregates. As the NPs diameter is increased to 22 nm, CPAM re-conforms over NP surface forming a large shell of thickness 5.5 nm. For the composites with NPs of diameter 74 nm, the CPAM chain re-conforms further onto NP surface and the surrounding shell thickness decreases to 2.2 nm. Lastly, structure factor analysis reveals higher structural ordering for NPs as increases their diameter, which is caused by different conformations adopted by CPAM onto NPs surface.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Photoluminescence Induced in Mineral Oil by Ionizing Radiation

We have studied photoluminescence (PL) properties of vacuum pump mineral oil as a function of the type and intensity of ionizing radiation exposure. The mineral oil has a simple aliphatic structure, which possesses no chromophore in the traditional sense. Unexpected PL in the mineral oil has characteristic features such as variation of the emission peak wavelength depending on the excitation wavelength and intensity dramatically increasing with radiation dose. The observed behavior can be understood in the framework of a previously suggested model introducing aggregation-induced PL and the formation of conjugated clusters comprising nontraditional chromophores. Our findings can be used for the development of optical sensors for real-time monitoring of oil utilized in vacuum pumps in nuclear fusion reactors.

Bliznyuk, Valery N.↗
NASA NTRS1990

The effects of compositional inhomogeneities and fractal dimension on the optical properties of astrophysical dust

Mathis and Whiffen (1989) have recently suggested that interstellar dust particles are fluffy aggregates of submicron-size particles composed of various astronomical minerals. These dust particles should exhibit optical properties that are quite different from standard dust, characterized by spherical particles of various homogeneous mineral composition. In this paper, the discrete dipole approximation (DDA) method is used to examine the effects of chemical inhomogeneities and spatial structure on the optical properties of interstellar Mathis-Whiffen-type dust particles. The spatial structure of the dust is represented by its fractal dimension, and the chemical inhomogeneities are simulated by randomly assigning the composition of the occupied sites in the structure to be either carbon or silicate. It is found that compositional inhomogeneities are the dominant parameter affecting the shape of the 9.7 and 18 micron silicate bands. Some bands-shape variations can be attributed to the fractal dimension of the dust. The results derived here can be used to explain or constrain variations in these parameters among various astronomical objects.

Bazell, David↗
NASA NTRS1999

Induction of Three-Dimensional Growth of Human Liver Cells in Simulated Microgravity

We previously reported that a NASA-developed bioreactor that simulates microgravity environment and creates the unique environment of low shear force and high-mass transfer is conducive for maintaining long term 3-D cell cultures of functional hepatocytes (60 days). However, significant further expansion of liver mass, or the remodeling of liver in vitro was jeopardized by the appearance of apoptotic zones in the center of large cell aggregates. To optimize oxygenation and nutritional uptake within growing cellular aggregates we cultured primary human liver cells (HLC) in a bioreactor in the presence or absence of microcarriers and biodegradable scaffolds. Also, to promote angiogenesis, HLC were cultured with or without microvascular endothelial cells. HLC were harvested from human livers by collagenase perfusion. While microcarriers did not affect cell growth, HLC cultured with biodegradable scaffolds made from polyglycolic acid (PGA) formed aggregates up to 3 cm in length. Culturing cells with PGA scaffolds increased the efficiency of cell self-assembly and the formation of larger cell aggregates. Based on histological evaluation it appears that the degree of apoptotic cells was diminished as compared to cultures without scaffolds. Histology of HLC with PGA-scaffolds revealed cell distribution between the fibers of the scaffolds, and cell-cell and cell-fiber interactions. Analyses of HLC spheroids revealed tissue-like structures comprised of hepatocytes, biliary epithelial cells and/or progenitor liver cells that were arranged as bile duct-like structures along nascent vascular sprouts. Electron microscopy revealed groups of cohesive hepatocytes and bile canaliculi with multiple microvilli and tight cellular junctions. Hepatocytes were further organized into tight clusters surrounded by complex stromal structures and reticulin fibers. Also, we observed higher levels of albumin mRNA expression when hepatocytes were co-cultured with endothelial cells. To evaluate viability and microsomal deethylation activity of hepatocytes we assessed the metabolism of midazolam by gas chromatography. Samples that were collected from HLC cultured in the bioreactor contained higher levels of midazolam metabolites (1-OH-midazolam and 4-OH-midazolam) than samples collected from conventional cultures. In summary, we have shown that co-culture of HLC with endothelial cells and/or culturing in the presence of PGA scaffolds provides additional advantages in maintaining functional activity of 3-D hepatocyte cultures that resemble liver tissue. This cell culture system may facilitate studies of liver regeneration and cell-to-cell interactions that occur in vivo and suggest the feasibility of using this approach for pre-clinical metabolic screening of novel drug candidates.

Pellis, Neal R.↗
NASA NTRS2003

Interannual Variability of the Tropical Water Cycle: Capabilities in the TRMM Era and Challenges for GPM

Considerable uncertainty surrounds the issue of whether precipitation over the tropical oceans (30" NE) systematically changes with interannual sea-surface temperature (SST) anomalies that accompany El Nino (warm) and La Nina (cold) events. Although it is well documented that El Nino-Southern Oscillation (ENSO) events with marked SST changes over the tropical oceans, produce significant regional changes in precipitation, water vapor, and radiative fluxes in the tropics, we still cannot yet adequately quantify the associated net integrated changes to water and heat balance over the entire tropical oceanic or land sectors. Robertson et al., [2001 GRL] for example, showed that substantial disagreement exists among contemporary satellite estimates of interannual variations in tropical rainfall that are associated with SST changes. Berg et al., [2002 J. Climate] have documented the distinct differences between precipitation structure over the eastern and western Pacific ITCZ and noted how various satellite precipitation algorithms may respond quite differently to ENSO modulations of these precipitation regimes. Resolving this uncertainty is important since precipitation and latent heat release variations over land and ocean sectors are key components of the tropical heat balance in its most aggregated form. Rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) averaged over the tropical oceans have not solved this issue and, in fact, show marked differences with estimates from two TRMM Microwave Imager (TMI) passive microwave algorithms. In this paper we will focus on findings that uncertainties in microphysical assumptions necessitated by the single-frequency PR measurement pose difficulties for detecting climate-related precipitation signals. Recent work has shown that path-integrated attenuation derived from the effects of precipitation on the radar return from the ocean surface exhibits interannual variability that agrees closely with the TMI time series, yet the PR rainfall interannual variability (and attenuation derived predominantly from reflectivity) differs even in sign. We will explore these apparent inconsistencies and detail their impact on estimates of how ENSO events perturb the tropical rainfall. We will place these results in perspective by considering requirements for precipitation accuracy for global climate variability and change studies involving ENSO, monsoon dynamics and variations, and climate model improvement and validation. The discussion will conclude with an assessment of the implications of these findings for Global Precipitation Mission (GPM) requirements.

Robertson, Franklin R.↗
NASA NTRS2009

Multiscale Computer Simulation of Tensile and Compressive Strain in Polymer- Coated Silica Aerogels

While the low thermal conductivities of silica aerogels have made them of interest to the aerospace community as lightweight thermal insulation, the application of conformal polymer coatings to these gels increases their strength significantly, making them potentially useful as structural materials as well. In this work we perform multiscale computer simulations to investigate the tensile and compressive strain behavior of silica and polymer-coated silica aerogels. Aerogels are made up of clusters of interconnected particles of amorphous silica of less than bulk density. We simulate gel nanostructure using a Diffusion Limited Cluster Aggregation (DLCA) procedure, which produces aggregates that exhibit fractal dimensions similar to those observed in real aerogels. We have previously found that model gels obtained via DLCA exhibited stress-strain curves characteristic of the experimentally observed brittle failure. However, the strain energetics near the expected point of failure were not consistent with such failure. This shortcoming may be due to the fact that the DLCA process produces model gels that are lacking in closed-loop substructures, compared with real gels. Our model gels therefore contain an excess of dangling strands, which tend to unravel under tensile strain, producing non-brittle failure. To address this problem, we have incorporated a modification to the DLCA algorithm that specifically produces closed loops in the model gels. We obtain the strain energetics of interparticle connections via atomistic molecular statics, and abstract the collective energy of the atomic bonds into a Morse potential scaled to describe gel particle interactions. Polymer coatings are similarly described. We apply repeated small uniaxial strains to DLCA clusters, and allow relaxation of the center eighty percent of the cluster between strains. The simulations produce energetics and stress-strain curves for looped and nonlooped clusters, for a variety of densities and interaction parameters.

Good, Brian↗
NASA NTRS2010

Coarse, Intermediate and High Resolution Numerical Simulations of the Transition of a Tropical Wave Critical Layer to a Tropical Storm

Recent work has hypothesized that tropical cyclones in the deep Atlantic and eastern Pacific basins develop from within the cyclonic Kelvin cat's eye of a tropical easterly wave critical layer located equatorward of the easterly jet axis. The cyclonic critical layer is thought to be important to tropical cyclogenesis because its cat's eye provides (i) a region of cyclonic vorticity and weak deformation by the resolved flow, (ii) containment of moisture entrained by the developing flow and/or lofted by deep convection therein, (iii) confinement of mesoscale vortex aggregation, (iv) a predominantly convective type of heating profile, and (v) maintenance or enhancement of the parent wave until the developing proto-vortex becomes a self-sustaining entity and emerges from the wave as a tropical depression. This genesis sequence and the overarching framework for describing how such hybrid wave-vortex structures become tropical depressions/storms is likened to the development of a marsupial infant in its mother's pouch, and for this reason has been dubbed the "marsupial paradigm". Here we conduct the first multi-scale test of the marsupial paradigm in an idealized setting by revisiting the Kurihara and Tuleya problem examining the transformation of an easterly wave-like disturbance into a tropical storm vortex using the WRF model. An analysis of the evolving winds, equivalent potential temperature, and relative vertical vorticity is presented from coarse (28 km), intermediate (9 km) and high resolution (3.1 km) simulations. The results are found to support key elements of the marsupial paradigm by demonstrating the existence of rotationally dominant region with minimal strain/shear deformation near the center of the critical layer pouch that contains strong cyclonic vorticity and high saturation fraction. This localized region within the pouch serves as the "attractor" for an upscale "bottom up" development process while the wave pouch and proto-vortex move together.

Montgomery, M. T.↗
NASA NTRS1987

High-resolution synchrotron X-ray study of the structure of La(1.8)Ba(0.2)CuO(4-y)

X-ray diffraction of La(1.8)Ba(0.2)CuO(4-y) reveals two macroscopically segregated tetragonal (K2NiF4-type) phases of nearly identical lattice parameter. Many peaks show additional broadening upon cooling. This broadening is consistent with a spontaneous monoclinic distortion, with an onset temperature of about 150 K, and is possibly relevant to the superconducting properties. Small single crystals of about 70 micron diameter within the powder aggregate are also studied and show a similar two-phase constituency and a resolvable peak splitting at low temperature.

Moss, S. C.↗
DOE OSTI2020

A highly stable Cu(OH) 2 -Poly(vinyl alcohol) nanocomposite membrane for dramatically enhanced direct borohydride fuel cell performance

Nano-additive aggregation, limited performance, and unclear modification mechanisms are the main obstacles in developing nanocomposite anion exchange membranes (AEMs). In this work, for the first time, an effective and highly stable Poly(vinyl alcohol) (PVA)-based AEMs with dispersive Cu(OH)$_2$ nanoclusters (Cu-AEMs) are prepared by a simple and eco-friendly three-step method: ‘CuCl$_2$ doping-casting-KOH immersing’. The doped Cu$^{2+}$ ions chemically combine with OH- ions to form anionic conductive Cu(OH)2 nanoclusters intermediated by attaching resins. The PVA skeletons wrap around Cu(OH)$_2$ while the hydroxyl groups expose to bulk water, forming Cu(OH)$_2$-PVA complex, which avoids nano-additive aggregation, increases anionic channels, and strengthens additive-matrix connection. A direct borohydride fuel cell using Cu-AEM with 0.56 wt % CuCl$_2$ possess the highest power density of 403.3 mW cm$^{-2}$ at 60 °C and a life span of over 200 h. The high-performance and durability come from the unique structure of Cu(OH)$_2$ nanoclusters-PVA complex. ‘Vehicle’ theory is considered to be the dominant mechanism for enhancing such nanocomposite Cu-AEMs. This work demonstrates a new concept for preparing the stable AEMs toward high-performance fuel cells. The synthetic chemistry involved can be broadly extended for fabricating versatile AEMs.

25 ENERGY STORAGE↗
DOE OSTI2020

Particle size of several plutonium-238 oxide fuel samples from oxalate precipitation processes

Particle size of 238 PuO 2 powders is an important factor in determining the structural integrity of fuel pellets hot-pressed from the oxide powder. Understanding the evolution of particle size during aqueous processing is a first step in assuring control of particle size throughout the pellet formation process. Measured particle sizes are reported here, and discussed in terms of measured particle size changes occurring during calcining, observed aggregation of particulate, and particle morphology. Morphology and aggregation are related to surface energy, which governs granule formation and hot pressing behavior. Results are discussed in terms of reported dependence of oxide morphology on process temperatures and reagent concentrations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Evaluating the effect of alternative carbon allocation schemes in a land surface model (CLM4.5) on carbon fluxes, pools, and turnover in temperate forests

Abstract. How carbon (C) is allocated to different plant tissues (leaves, stem, and roots) determines how long C remains in plant biomass and thus remains a central challenge for understanding the global C cycle. We used a diverse set of observations (AmeriFlux eddy covariance tower observations, biomass estimates from tree-ring data, and leaf area index (LAI) measurements) to compare C fluxes, pools, and LAI data with those predicted by a land surface model (LSM), the Community Land Model (CLM4.5). We ran CLM4.5 for nine temperate (including evergreen and deciduous) forests in North America between 1980 and 2013 using four different C allocation schemes: i. dynamic C allocation scheme (named "D-CLM4.5") with one dynamic allometric parameter, which allocates C to the stem and leaves to vary in time as a function of annual net primary production (NPP); ii. an alternative dynamic C allocation scheme (named "D-Litton"), where, similar to (i), C allocation is a dynamic function of annual NPP, but unlike (i) includes two dynamic allometric parameters involving allocation to leaves, stem, and coarse roots; iii.–iv. a fixed C allocation scheme with two variants, one representative of observations in evergreen (named "F-Evergreen") and the other of observations in deciduous forests (named "F-Deciduous"). D-CLM4.5 generally overestimated gross primary production (GPP) and ecosystem respiration, and underestimated net ecosystem exchange (NEE). In D-CLM4.5, initial aboveground biomass in 1980 was largely overestimated (between 10 527 and 12 897 g C m −2 ) for deciduous forests, whereas aboveground biomass accumulation through time (between 1980 and 2011) was highly underestimated (between 1222 and 7557 g C m −2 ) for both evergreen and deciduous sites due to a lower stem turnover rate in the sites than the one used in the model. D-CLM4.5 overestimated LAI in both evergreen and deciduous sites because the leaf C–LAI relationship in the model did not match the observed leaf C–LAI relationship at our sites. Although the four C allocation schemes gave similar results for aggregated C fluxes, they translated to important differences in long-term aboveground biomass accumulation and aboveground NPP. For deciduous forests, D-Litton gave more realistic C stem ∕ C leaf ratios and strongly reduced the overestimation of initial aboveground biomass and aboveground NPP for deciduous forests by D-CLM4.5. We identified key structural and parameterization deficits that need refinement to improve the accuracy of LSMs in the near future. These include changing how C is allocated in fixed and dynamic schemes based on data from current forest syntheses and different parameterization of allocation schemes for different forest types. Our results highlight the utility of using measurements of aboveground biomass to evaluate and constrain the C allocation scheme in LSMs, and suggest that stem turnover is overestimated by CLM4.5 for these AmeriFlux sites. Understanding the controls of turnover will be critical to improving long-term C processes in LSMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Nondestructive Evaluation of Concrete Specimens Representative of Nuclear Power Plants Containing Known Defects

Many known defects that develop in concrete over time threaten the safety and security of the infrastructure in nuclear power plants (NPPs). These defects also exist in other concrete infrastructures, but the harsher nuclear environment adds significant difficulty to their detection and correction. To monitor the structural health of a concrete facility, coring and other destructive testing methods are typically employed, but this is not the ideal solution for NPP concrete infrastructure. Developing a reliable nondestructive evaluation (NDE) method to evaluate the damage in these structures will greatly improve the long-term operation and safety of NPPs. The University of Tennessee, in collaboration with Oak Ridge National Laboratory, developed a large-scale experiment to study one known defect due to the reaction between hydroxyl ions of the alkalis in cement paste and the siliceous minerals present in some aggregates known as alkali-silica reactions (ASRs). Alkali-silica gel forms and swells due to its hygroscopic characteristic, causing cracking and material failure. This paper discusses the NDE measurements performed on the large concrete specimens and the reconstructed images from these measurements.

Ezell, N Dianne↗
DOE OSTI2023

Electric Vehicle Charging Analytics and Reporting Tool (EV-ChART): Data Format and Preparation Guidance, Version 2.0

The Joint Office of Energy and Transportation maintains the Electric Vehicle Charging Analytics and Reporting Tool (EV-ChART), which provides a centralized hub for submitting electric vehicle (EV) charging infrastructure data directed by the Federal Highway Administration (23 CFR 680.112) EV-ChART will provide a streamlined data submission process and an integrated set of analytic tools, connect to other data sources, and empower data sharing and access across stakeholders, including the public. Any data shared publicly will be aggregated and anonymized to stay in accordance with 23 CFR 680. This EV-ChART Data Format and Preparation Guidance provides a comprehensive overview of the data reporting requirements as authorized under 23 CFR 680.112. The guidance is intended to be used alongside the EV-ChART Data Input Template, which defines the tabular data structure that these data submissions must follow.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗
DOE OSTI2020

Using FLAC{sup R} Modeling Software to Analyze the Stability of a LLRW Disposal Facility - 20031

Waste Control Specialists (WCS) wished to amend its existing LLRW disposal license such that it might use gravel aggregate instead of concrete as backfill around large component (LC) parts from decommissioned nuclear reactors. A classical mechanics evaluation of the strength of the LCs was presented to the Texas Commission on Environmental Quality (TCEQ), demonstrating that the LCs had adequate capacity to withstand the loads within the facilities, and that concrete was unnecessary for structural support. TCEQ requested that additional analyses of the LCs within the facilities be performed using FLAC{sup R} finite difference modeling software. Because FLAC{sup R} has the capability of modeling the support provided by the lateral earth pressures, the factors of safety against failure for the LCs increased. TCEQ found the FLAC{sup R} analyses presented in this report to be satisfactory, and granted WCS' license amendment request. This work demonstrates that FLAC{sup R} may be used advantageously to more accurately represent the complexities of the physical situation being modeled. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Material Extrusion Printing of Poly(Acrylonitrile‐Styrene‐Acrylate) and Poly(Acrylonitrile‐Butadiene‐Styrene) Structures Reinforced with Poly(Phenylene Oxide) Additives for Improved Thermomechanical Properties and their Surface Analysis by Time‐of‐Flight Secondary Ion Mass Spectrometry

Fused filament fabrication offers the ability to 3D print complex geometries made from plastic filament materials; however, these parts are mechanically outperformed by parts created by traditional fabrication methods. To overcome this challenge, a high-performance polymer poly(2,6-dimethyl-1,4-phenylene oxide) (PPO) is incorporated as an additive into two common engineering thermoplastics, poly(acrylonitrile-styrene-acrylate) (ASA) and poly(acrylonitrile-butadiene-styrene) (ABS). Structures printed from these polymer blends are more mechanically robust compared to those prepared from the parent polymers, with low loading levels (1–5 wt%) of PPO improving the elastic strength by up to ≈30% relative to the parent terpolymers. Even at higher loading levels (10 and 20 wt% PPO), there is no evidence of additive aggregation in the model thin films, which is supported by compositional analysis of the copolymers and chemical analysis via time-of-flight secondary ion mass spectrometry. The enhancements in mechanical properties of ASA and ABS blends appear to be a consequence of homogeneous incorporation of the PPO additive. In conclusion, this work explores expanding materials-property space using miscible blends of engineering thermoplastics to improve mechanical performance as a general approach to overcoming challenges with parts created by melt-based material extrusion printing.

additive manufacturing↗
DOE OSTI2025

Denoising Autoencoder for Reconstructing Sensor Observation Data and Predicting Evapotranspiration: Noisy and Missing Values Repair and Uncertainty Quantification

Abstract Machine learning (ML) methods applied in scientific research often deal with interrelated features in high‐dimensional data. Reducing data noise and redundancy is needed to increase prediction accuracy and efficiency especially when dealing with data from field sensors. We explored an unsupervised learning method, the denoising autoencoder (DAE), to extract the underlying data structure from noisy raw data in the context of predicting hydrologic quantities from multiple field sensors. These sensors have intrinsic instrumental noise and occasional malfunctions that cause missing values. Our DAE neural network reconstructed meteorological sensor data containing noise and missing values to predict evapotranspiration in a mountainous watershed. The DAE reconstructed the sensor variables with a mean coefficient of determination value of 0.77 across 15 dimensions representing individual sensors. It reduced variance and bias uncertainties compared to a classical autoencoder model. The reconstruction quality varied across dimensions depending on their cross‐correlation and alignment with the underlying data structure. Uncertainties arising from the model structure were overall higher than those resulting from data corruption. We attached the DAE structure to a downstream ET‐prediction neural network in three formats and achieved reasonably accurate ET predictions . The use of the DAE notably reduced variance uncertainty in ET prediction. However, excessive variance reduction may be accompanied by an increase in bias due to the intrinsic bias‐variance tradeoff. Our method of evaluating and reducing uncertainties in aggregated data from different sources can be used to improve predictive models, process understanding, and uncertainty quantification for better water resource management. Plain Language Summary We present a machine learning method, namely the denoising autoencoder, which reduces the effects of data noise and missing values typically present in scientific data sets collected through sensor measurements. This method selects the most relevant information from noisy raw data collected by the instruments and fills in missing values. To demonstrate the effectiveness of our method, we applied it to predict evapotranspiration, a hydrologic variable that represents the water moved from the land surface to the atmosphere through a combination of evaporation and plant water use (transpiration). We also used a random sampling technique (the Monte Carlo method) to compare the uncertainty in the predictions when using the raw and noisy data versus the reconstructed data. The denoising process produced more accurate predictions of evapotranspiration with less uncertainty. Improved predictions of evapotranspiration can lead to a better understanding and accounting of water budgets. This ML approach is broadly suitable for a wide variety of applications that involve noisy sensor data with missing values. Key Points We used a denoising autoencoder (DAE) neural network to reduce noise in meteorological and soil sensor observations by on average We used Monte Carlo sampling to estimate the bias and variance of all model outputs, including uncertainty sources from data and the model We attached the DAE component to a downstream neural network to predict ET with the variance reduced by , compared to that without the DAE

denoising autoencoder↗