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NASA NTRS1997

Description and Analysis of Core Samples: The Lunar Experience

Although no samples yet have been returned from a comet, extensive experience from sampling another solar system body, the Moon, does exist. While, in overall structure, composition, and physical properties the Moon bears little resemblance to what is expected for a comet, sampling the Moon has provided some basic lessons in how to do things which may be equally applicable to cometary samples. In particular, an extensive series of core samples has been taken on the Moon, and coring is the best way to sample a comet in three dimensions. Data from cores taken at 24 Apollo collection stations and 3 Luna sites have been used to provide insight into the evolution of the lunar regolith. It is now well understood that this regolith is very complex and reflects gardening (stirring of grains by micrometeorites), erosion (from impacts and solar wind sputtering), maturation (exposure on the bare lunar surface to solar winds ions and micrometeorite impacts) and comminution of coarse grains into finer grains, blanket deposition of coarse-grained layers, and other processes. All of these processes have been documented in cores. While a cometary regolith should not be expected to parallel in detail the lunar regolith, it is possible that the upper part of a cometary regolith may include textural, mineralogical, and chemical features which reflect the original accretion of the comet, including a form of gardening. Differences in relative velocities and gravitational attraction no doubt made this accretionary gardening qualitatively much different than the lunar version. Furthermore, at least some comets, depending on their orbits, have been subjected to impacts of the uppermost surface by small projectiles at some time in their history. Consequently, a more recent post-accretional gardening may have occurred. Finally, for comets which approach the sun, large scale erosion may have occurred driven by gas loss. The uppermost material of these comets may reflect some of the features of this erosional process, such as crust formation, and variations with depth might be expected. Overall, the upper few meters of a comet may be as complex in their own way as the upper few meters of the lunar regolith have proven to be, and by analogy, detailed studies of core samples containing this depth information will be needed to understand these processes and the details of the accretional history and the subsequent alteration history of comets.

McKay, David S.↗

DOE OSTI2022

Finite Element Modeling of Electrochemical Polishing of Niobium in Hydrofluoric-Sulfuric Acid Electrolyte

Niobium (Nb) used in superconducting radio-frequency cavities requires smooth surface to achieve optimal performance. In this work, a finite element model that coupled electrochemistry, heat transfer, and fluid dynamics was developed to investigate the electrochemical polishing mechanisms of Nb, using experimentally measured polarization results of coupon samples as validations. The current and potential distribution, oxide growth kinetics of Nb in a complex cavity geometry was investigated as a function of temperature and coolant flow. A low temperature coolant with intermediate flow rate was found to reduce surface current and ensure oxide uniformity. These results could shed light on the design of future particle accelerators.

SRF accelerator cavity↗

DOE OSTI2025

Wide‐Field Bond Quality Evaluation Using Frequency Domain Thermoreflectance with Deep Neural Network Feature Reconstruction

Heterogeneous integration of microelectronic components provides a pathway to improve circuit/component performance; however, this comes with assembly challenges, in particular due to complex interfaces via subsurface bump bonds. The ability of these bonds to transmit electrical signals and conduct heat to the carrier substrate limits component performance. In this work, hyperspectral frequency‐domain thermoreflectance (FDTR) imaging is demonstrated as a robust technique for evaluating the quality of subsurface indium bump bonds in a surrogate microelectronic sample. By performing microscale FDTR imaging with coarse motion image stitching, thermal phase maps that cover a 4 mm by 4 mm field‐of‐view with subsurface feature sensitivity at depths greater than 50 µm are obtained. The resulting FDTR hyperspectral data contains more than three million pixels and reveal the quality of subsurface microbump arrays. Wide‐field analysis of bonded versus gap regions is enabled by deep neural network feature reconstruction, that after training, rapidly provides an interpretable representation of bond quality. Utility of noisy higher frequency FDTR phase maps, i.e., near the computationally predicted sensing depth limit, results in an average prediction error of 11%. Taken together, FDTR with neural network‐based analysis demonstrates subsurface bond monitoring at length scales relevant for heterogeneously integrated microelectronics.

FDTR↗

DOE OSTI2018

Plakophilin3 loss leads to an increase in lipocalin2 expression, which is required for tumour formation

Highlights: • Plakophilin3 loss leads to an increase in LCN2 expression in multiple cell types. • The increase in LCN2 expression is dependent on the activity of p38 MAPK. • Plakophilin3 inhibits LCN2 expression by restricting p38 MAPK to the cytoplasm. • The increase in LCN2 expression is required for tumour formation upon plakophilin3 loss. An increase in tumour formation and metastasis are observed upon plakophilin3 (PKP3) loss. To identify pathways downstream of PKP3 loss that are required for increased tumour formation, a gene expression analysis was performed, which demonstrated that the expression of lipocalin2 (LCN2) was elevated upon PKP3 loss and this is consistent with expression data from human tumour samples suggesting that PKP3 loss correlates with an increase in LCN2 expression. PKP3 loss leads to an increase in invasion, tumour formation and metastasis and these phenotypes were dependent on the increase in LCN2 expression. The increased LCN2 expression was due to an increase in the activation of p38 MAPK in the HCT116 derived PKP3 knockdown clones as LCN2 expression decreased upon inhibition of p38 MAPK. The phosphorylated active form of p38 MAPK is translocated to the nucleus upon PKP3 loss and is dependent on complex formation between p38 MAPK and PKP3. WT PKP3 inhibits LCN2 reporter activity in PKP3 knockdown cells but a PKP3 mutant that fails to form a complex with p38 MAPK cannot suppress LCN2 promoter activity. Further, LCN2 expression is decreased upon loss of p38β, but not p38α, in the PKP3 knockdown cells. These results suggest that PKP3 loss leads to an increase in the nuclear translocation of p38 MAPK and p38β MAPK is required for the increase in LCN2 expression.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Structural basis of differential gene expression at eQTLs loci from high-resolution ensemble models of 3D single-cell chromatin conformations

Abstract Motivation Techniques such as high-throughput chromosome conformation capture (Hi-C) have provided a wealth of information on nucleus organization and genome important for understanding gene expression regulation. Genome-Wide Association Studies have identified numerous loci associated with complex traits. Expression quantitative trait loci (eQTL) studies have further linked the genetic variants to alteration in expression levels of associated target genes across individuals. However, the functional roles of many eQTLs in noncoding regions remain unclear. Current joint analyses of Hi-C and eQTLs data lack advanced computational tools, limiting what can be learned from these data. Results We developed a computational method for simultaneous analysis of Hi-C and eQTL data, capable of identifying a small set of nonrandom interactions from all Hi-C interactions. Using these nonrandom interactions, we reconstructed large ensembles (×105) of high-resolution single-cell 3D chromatin conformations with thorough sampling, accurately replicating Hi-C measurements. Our results revealed many-body interactions in chromatin conformation at the single-cell level within eQTL loci, providing a detailed view of how 3D chromatin structures form the physical foundation for gene regulation, including how genetic variants of eQTLs affect the expression of associated eGenes. Furthermore, our method can deconvolve chromatin heterogeneity and investigate the spatial associations of eQTLs and eGenes at subpopulation level, revealing their regulatory impacts on gene expression. Together, ensemble modeling of thoroughly sampled single-cell chromatin conformations combined with eQTL data, helps decipher how 3D chromatin structures provide the physical basis for gene regulation, expression control, and aid in understanding the overall structure-function relationships of genome organization. Availability and implementation It is available at https://github.com/uic-liang-lab/3DChromFolding-eQTL-Loci.

Du, Lin (ORCID:0009000289869812)↗

DOE OSTI2025

Adaptive Computing for Scale-Up Problems

Adaptive Computing is an application-agnostic outer loop framework to strategically deploy simulations and experiments to guide decision making for scale-up analysis. Resources are allocated over successive batches, which makes the allocation adaptive to some objective such as optimization or model training. The framework enables the characterization and management of uncertainties associated with predictive models of complex systems when scale-up questions lead to significant model extrapolation. A key advancement of this framework is its integration of multi-fidelity surrogate modeling, uncertainty management, and automated orchestration of various computing and experimentation resources into a single integrated software package. This enables efficient multi-fidelity modeling across multiple computing resources by incorporating real-world constraints such as relative queue times and throughput on individual machines into the multi-fidelity sampling decision. We discuss applications of this framework to problems in the renewable energy space, including biofuels production, material synthesis, perovskite crystal growth, and building electrical loads.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Characterization of Complex Interactions at the Gas–Solid Interface with in Situ Spectroscopy: The Case of Nitrogen-Functionalized Carbon

Interactions at the gas-solid interface drive physicochemical processes in many energy and environmental applications; yet, the challenges associated with characterization and development of these dynamic interactions in complex systems limit progress in developing effective materials. Thus, structure-property-performance correlations greatly depend on the development of advanced techniques and analysis methods for the investigation of gas-solid interactions. In this work, adsorption behavior of O 2 and humidified O 2 on nitrogen-functionalized carbon (N-C) materials was investigated to provide a better understanding of the role of nitrogen species in the oxygen reduction reaction (ORR). N-C materials were produced by solvothermal synthesis and N-ion implantation, resulting in a set of materials with varied nitrogen amount and speciation in carbon matrices with different morphologies. Adsorption behavior of the N-C samples was characterized by in situ diffuse reflectance infrared Fourier-transform spectroscopy (DRIFTS) and ambient pressure X-ray photoelectron spectroscopy (AP-XPS) experiments. A novel analysis approach for the interpretation of AP-XPS data was developed, allowing both the determination of overall adsorption behavior of each N-C material and identification of which nitrogen species were responsible for adsorption. The complementary information provided by in situ DRIFTS and AP-XPS suggests that O 2 adsorption primarily takes place on either electron-rich nitrogen species like pyridine, hydrogenated nitrogen species, or graphitic nitrogen. Adsorption of O 2 and H 2 O occurs competitively on solvothermally prepared N-Cs, whereas adsorption of H 2 O and O 2 occurs at different sites on N-ion implanted N-Cs, highlighting the importance of tuning the composition of N-C materials to promote the most efficient ORR pathway.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1999

Determination of the Corrosive Conditions Present within Aircraft Lap-Splice Joints

The complexity of airframe structure lends itself to damage resulting from crevice corrosion. Fuselage lap-splice joints are a particularly important structural detail in this regard because of the difficulty associated with detection and measurement of corrosion in these occluded regions. The objective of this work is to develop a laboratory corrosion test protocol to identify the chemistry to which lap joints are exposed and to develop a model of the corrosion within the joints. A protocol for collecting and identifying the chemistry of airframe crevice corrosion has been developed. Capillary electrophoresis (CE) is used to identify the ionic species contained in corrosion product samples removed from fuselage lap splice joints. CE analysis has been performed on over sixty corrosion product samples removed from both civilian and military aircraft. Over twenty different ions have been detected. Measurements of pH of wetted corroded surfaces indicated an alkaline occluded solution. After determining the species present and their relative concentrations, the resultant solution was reproduced in bulk and electrochemical tests were performed to determine the corrosion rate. Electrochemical analyses of the behavior of AA2024-T3 in these solutions gave corrosion rates of up to 250 microns per year (10 mpy). Additional tests have determined the relative importance of each of the detected ions in model solutions used for future predictive tests. The statistically significant ions have been used to create a second generation solution. Laboratory studies have also included exposure tests involving artificial lap joints exposed to various simulated bulk and crevice environments. The extent and morphology of the attack in artificial lap joints has been compared to studies of corroded samples from actual aircraft. Other effects, such as temperature and potential, as well as the impact of the environment on fatigue crack growth have also been studied.

Lewis, Karen S.↗

NASA NTRS2010

Comparison of the Organic Composition of Cometary Samples with Residues Formed from the UV Irradiation of Astrophysical Ice Analogs

The NASA Stardust mission successfully collected material from Comet 81P/Wild 2 [1], including authentic cometary grains [2]. X-ray absorption near-edge structure (XANES) spectroscopy analysis of these samples indicates the presence of oxygen-rich and nitrogen-rich organic materials, which contain a broad variety of functional groups (carbonyls, C=C bonds, aliphatic chains, amines, arnides, etc.) [3]. One component of these organics appears to contain very little aromatic carbon and bears some similarity to the organic residues produced by the irradiation of ices of interstellar/cometary composition, Stardust samples were also recently shown to contain glycine, the smallest biological amino acid [4]. Organic residues produced froth the UV irradiation of astrophysical ice analogs are already known to contain a large suite of organic molecules including amino acids [5-7], amphiphilic compounds (fatty acids) [8], and other complex species. This work presents a comparison between XANES spectra measured from organic residues formed in the laboratory with similar data of cometary samples collected by the Stardust mission

Milam, S. N.↗

NASA NTRSDate not supplied

Material Property Estimation in Thin Battery Components Using Guided Wave Measurement, Experimental Dispersion Curve Extraction and Finite Element Modeling

At NASA, we are investigating nondestructive evaluation (NDE) and structural health monitoring (SHM) techniques to detect precursors of thermal runaway failure in lithium metal based lithium ion batteries (LIB). The approach is centered on computational simulation models to guide inspection and aid in interpretation of results. Since lithium metal LIBs have combinations of solid and fluid-filled porous materials, obtaining accurate material properties is both challenging and critical for successful simulation of battery inspection. To this end, we investigated a multi-verification approach for material characterization of thin battery components. First, a laser Doppler vibrometer (LDV) was used to measure guided wave fields in thin (microns-thick) battery components subject to broadband excitation. The time-space wavefield data was converted to frequency-wave number data to extract guided wave dispersion curves. A data visualization and post processing graphics user interface (GUI) was developed at NASA to aid the data exploration and analysis. Due to the thinness of the samples, low frequency-thickness-product plate wave approximations allowed for the calculation of closed-form solutions for material elastic property estimation. These approximations were then verified by calculating the Lamb wave solutions using the previously obtained material properties. Finally, the estimated elastic material properties were implemented in a COMSOL simulation model, and dispersion curves were extracted from simulation results. The dispersion curves and derived material properties were then compared to the analysis results from the experimental data. These comparisons informed on the accuracy of the measured material properties and helped demonstrate the accuracy of the finite element analysis (FEA) computational models. This assessment will prove vital when we start simulating more complex multi-layer components and poroelastic media. This paper gives a brief background of the problem space, outlines the workflow for data analysis and verification, shows results from the workflow, and gives an overview of future plans for simulation of lithium metal LIB inspection.

Peter Juarez↗

DOE OSTI2025

Precision Local Burnup Assessment Through Dynamic Peak Fitting in Atom Probe Tomography for Depleted, Enriched, and Irradiated Metallic and Ceramic Fuels

Abstract Burnup estimation in nuclear fuels is vital for evaluating fuel performance, transportation, and safe fuel storage. Accurate assessments of burnup from service period and spent fuels involve tracking the consumption of fissile isotopes of uranium (U) offering a direct insight into energy changes within the fuels especially for thermal spectrum reactors. In current approach, mass spectroscopic technique in atom probe tomography (APT) is utilized for accurate quantification of U isotopes. Quantification of U peaks in mass spectrum is performed on asymmetric shapes due to delayed signals, known as thermal tails, particularly for poorly conducting samples analyzed in laser mode. In this study, we introduce a novel quantification tool for isotopic analysis from APT datasets by developing a fitting algorithm based on shapes of the peaks. A MATLAB-based dynamic peak fitting toolbox is developed and designed to adapt to various peak shapes, ensuring accurate quantification of U isotopes. The effectiveness of this approach is demonstrated in standard Ni-Cr sample, depleted and enriched U samples, and U-based fuels with different burnup levels. The viability of this approach for isotopic quantification is demonstrated on both metallic and ceramic fuels.

Burnup↗

DOE OSTI2019

Plutonium Particles in Samples Extracted from Hanford Tank Waste TX-118 and SY-102 (Interim Report)

This is an interim report on the characterization of plutonium particles from Hanford wastes. Plutonium-bearing particles were located in Hanford Waste Tank solids, SY-102 and TX-118. The particles in SY-102 were small, typically < 5 to 10 µm in length, and were crystalline plutonium oxide with an association of other elements at minor levels, including bismuth, phosphate, and iron based on Sanning Electron Microscopy (SEM) observations. Plutonium particles from SY-102 were extracted from the surface mount using the SEM-Focused Ion Beam (FIB) and prepared for Scanning Transmission Electron Microscopy (STEM). This was the first time that this type of analysis of Hanford tank waste solids has been attempted. The STEM analysis indicated a complex co-precipitation of plutonium oxide with bismuth and phosphate. Diffraction and imaging only partially matched with a PuO 2 phase. Pockets of phosphate and bismuth reside within the plutonium oxide suggesting that these phases formed at the same time. The SEM analysis indicated that the plutonium particles from TX-118 were a mixed bismuth-phosphate phase and plutonium oxide. These particles will be examined with SEM-FIB at a later time and then will undergo more detailed examination in the STEM.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Faraday detector uranium isotope ratio measurement: Insights from solution- and laser ablation-based sampling methodologies on the Neoma MC-ICP-MS

In this study we utilize an all-faraday cup detector configuration on the Neoma MC-ICP-MS to perform uranium isotope ratio determinations from certified reference materials and a nuclear fuel precursor material via solution and laser ablation based sampling methodologies. The goal in performing these measurements is primarily to demonstrate that the all-faraday cup method can produce highly precise and accurate isotope ratios even at relatively low signal intensity levels while also developing a preliminary understanding of how the complex interplay between different amplifier resistor levels (e.g. 10 11 vs 10 13 Ω) and integration times impacts the precision and accuracy of different types of measurements. Our results show that the faraday cups with 1013 Ω resistors in their amplifier feedback loops can be used to produce accurate and relatively precise isotope ratios for ion beams down to ~5 K cps. However, at the lower end of the signal intensities observed in this study, longer integration times are necessary to mitigate the impact of ion beam instability that can occur during laser ablation based sampling. Despite this potential limitation, the all-faraday cup method is highly versatile as exemplified by the analysis of a collection of uranium reference materials with highly variable uranium isotopic compositions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

Best practices and benchmarks for intact protein analysis for top-down mass spectrometry

One gene can give rise to many functionally distinct proteoforms, each of which has a characteristic molecular mass. Many laboratories, however, forgo the challenging mass analysis of intact proteins. Instead, these researchers resort to well-established methods for proteolytic digests. In this work, the Consortium for Top-Down Proteomics (CTDP) addresses the unmet need for robust protocols for obtaining intact protein mass spectra. We quantify and rationalize the signal suppression associated with common interfering substances. A decision tree, based upon sample composition and experimental goals, guides researchers to a given protocol. Cross-platform analytical benchmarks are provided to allow users to gauge their proficiency and to promote method standardization. This work should permit users at any experience level to obtain high-quality intact mass spectra of native and denatured proteins from mixtures of varying complexity, including intact antibodies and membrane proteins.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2017

The Evolution of the Orbiting Sample Container for a Future Mars Sample Return

Although NASA has no specific plans at this time to return samples from Mars, the Program Formulation Office of the Mars Exploration Program sponsors ongoing mission concept studies, systems analyses, and technology investments which explore different strategies for the potential return of samples from Mars, consistent with the charter of the program and stated priorities of the science community. A critical component of such a campaign would be an Orbiting Sample container (OS), which would contain the Mars samples to be returned to Earth. This paper discusses the most recent efforts by the JPL’s Mars Formulation Office to mature an OS design planned for use on a potential Mars Sample Return (MSR) mission. Similar to the “Decadal Study Architecture” [1], the current MSR architecture envisions as a three-mission campaign with each mission serving a critical role towards returning Martian rock and atmospheric samples back to Earth. An OS would be a central piece of hardware in the proposed MSR architecture due to its interfaces to all the three missions of the potential campaign. Additionally, numerous stakeholders and subsystems such as science and planetary protection impose challenging requirements on the OS’s functions and capabilities. As a result, designing an OS that meets all the requirements is challenging and quite complex. The story of the OS’s evolution from black box concept thru to the current-and-still-maturing baseline design is the focus of this paper. From the OS’s launch off Earth aboard a Sample Retrieval Lander (SRL) through to return to Earth, the design and functional requirements generated by and for each stage of the OS’s mission are discussed. Then, with an understanding of what the OS would be required to do, a mapping of the main requirements to the design features of the current OS concept is explained. Many tests and analyses have been conducted to support and validate the current OS design. Results from test and analysis in the areas of aerothermal, impact dynamics, optical tracking, and radio electromagnetics are presented.

Spencer, David↗

NASA NTRSDate not supplied

Characterization of NU-LHT-4M Lunar Regolith Simulant Using Different Raman Configurations

As much as possible, structures to help sustain a long-term human presence on the moon will be constructed via in-situ resource utilization (ISRU) from lunar regolith. Various processes have been proposed to make lunar regolith-based construction materials, but one complication is that the lunar regolith is relatively complex in terms of composition and can vary quite significantly from one site to another. Some of these methods to make lunar regolith-based construction materials are quite sensitive to the composition and so in-situ methods for evaluating the composition of the lunar regolith could be critical. Various analytical instrumentation has been proposed for in-situ characterization of the composition of regolith on planetary bodies. Raman spectroscopy has been suggested and has some advantages over other in-situ techniques, such as potential for relatively high spatial resolution, direct determination of the mineralogy (while other methods may only infer the mineralogy), nondestructive analysis, relatively simple instrument configurations, and minimal sample preparation/handling. For example, Raman instrumentation has already been deployed in rover-based missions to Mars. Previously, we developed the Standoff Ultracompact Micro-Raman Sensor (SUCR), which is a portable Raman spectroscopy instrument capable to be integrated into a rover or onto a lander. Here, we present work on Raman spectroscopy measurements of NU-LHT-4M lunar simulant using three different Raman instruments with different configurations for collecting Raman data with the goal to explore the effect of these different configurations on the results, especially for use in a lunar environment.

Raman Spectroscopy↗

DOE OSTI2021

Role of scan strategies and heat treatment on grain structure evolution in Fe-Si soft magnetic alloys made by laser-powder bed fusion

A major goal in printing soft magnetic Fe-Si steels using additive manufacturing is to take advantage of the potential for complex geometric designs and site-specific grain control. One major step in the processing of these alloys is understanding how processing parameters might impact how the as-built microstructure responds to annealing (i.e. the annealing response). The impact of scan strategy on the annealing response for thin wall geometries is specifically explored. Two scan strategies were explored for a thin wall geometry that produced a strongly columnar grain structure and equiaxed grain structure. Additionally, samples from both scan strategies annealed at 1200 °C showed a marked difference in annealing response with the more equiaxed sample seeing full recrystallization and grain growth, while the more columnar grain structure saw little change in microstructure. After analysis through characterization techniques and thermal-mechanical simulations Differences in internal energy within the grains were ruled out because calculated GND density values were similar for both samples. The formation of secondary particles was ruled out as a contributing factor due to the type of oxide formations and their size. It was concluded that the contributing factor to the difference in the annealing response were a difference in the resulting grain size and the density of high angle grain boundaries. These two differences were largely attributed to differences in the thermal gradient conditions due to grains preferentially growing in the direction of the steepest thermal gradient.

36 MATERIALS SCIENCE↗

DOE OSTI2021

On the feasibility of using physics-informed machine learning for underground reservoir pressure management

In this work, we evaluate the feasibility of using physics-informed machine learning (PIML) for underground energy-related pressure management. To this end, we develop a PIML framework to manage underground reservoir pressures by training neural networks to determine fluid extraction rates for dedicated extraction wells during fluid injection operations given a range of reservoir conditions (e.g., transmissivity and storativity). We implement an automatically-differentiable analytical physics model of fluid flow in porous media within the PIML framework as a proxy for more complicated models. This allows us to execute a sufficient number of training scenarios to fully evaluate the feasibility of using PIML to support pressure management activities. We quantify the number of physics-model parameters required for automatic differentiation to become more efficient than finite-difference gradient calculations. We use a simple scenario with a single injector, extractor, and critical location for our feasibility analysis. We evaluate the effect of the size of the training dataset (i.e., the number of reservoir condition samples) on the accuracy and efficiency of the PIML framework. For an equivalent number of model evaluations, the larger training dataset took less time to train and produced a neural network that was able to more accurately manage reservoir pressures. We also evaluate the effect of the training dataset batch size (i.e., number of reservoir condition samples used to update the neural network coefficients during training; i.e., how the training dataset is partitioned). While training ran faster with larger batch sizes, they produced neural networks that managed pressures less accurately. We demonstrate the approach on a more complex scenario involving 10 injectors, 10 extractors, and 4 critical locations (a relatively high well density of 20 wells/km2). We provide the number of forward and adjoint model evaluations required in each case as an indication of the feasibility of using PIML for pressure management when more complicated physics models with longer execution times are used.

54 ENVIRONMENTAL SCIENCES↗