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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Global 3D Data Visualization and Analysis Platform with Advanced Machine Learning Capabilities in Support of Lunar Exploration

Introduction: The science goals for NASA’s Artemis program include: a) Understanding the character and origin of lunar polar volatiles, b) Conducting experimental science in the lunar environment and c) Investigating and mitigating exploration risks. The permanently shadowed regions (PSRs) on the Lunar south pole are expected to host large quantities of water-ice and volatiles that are important for sustainable Lunar exploration. There are several missions such as onboard Korea Pathfinder Lunar Orbiter (KPLO: Korean name Danuri) with onboard ShadowCam camera, Astrobotic Peregrine Mission One [4], and other efforts underway to obtain high resolution topographic, minerals, volatiles and other information on the moon. We envision a need in immediate future for platforms to integrate these data sets, provide rendering and visualization capabilities in the context of a 3D Lunar globe for easier information access and analysis. NASA's Celestial Mapping System (CMS) is developed to address the need for 3D tools for planetary science investigations, mission planning, in-situ operations, in a 3D-first design constructed around a unified view of a planetary globe. At present CMS provides many critical functionalities that include: 1) equipment planning and optimized placement on Lunar surface 2) line-of-sight (LOS) analysis 3) powerful measurement tools based on 3D terrain with realistic 3D models to represent rovers, astronauts and equipment 4) visualization of derived mapping products (e.g. resource maps), and 5) a data engine for hosting new observations that are not available in other contemporary lunar data tools. Planetary Data Ingestion: CMS can consume and analyze data from locally hosted and external third party sources. It is compatible with Open Geospatial Consortium (OGC) data and file standards and currently integrates datasets from the Astrogeology Science Center of USGS. This includes global and local data acquired from NASA (LRO, Clementine, Lunar Orbiter) and JAXA (SELENE/Kaguya), with capability of integrating more datasets. In addition, users can specify other WMS-hosted data endpoints, which CMS can then query and stream data from automatically. To set-up an automated process for ingestion and accurate rendering, visualization and analysis of external 3rd party planetary datasets within CMS, we initiated the process of ingesting unique dataset of super-enhanced images of the permanently shadowed regions (PSRs) at the lunar poles which were produced by the Hyper-effective nOise Removal U-net Software (HORUS) tool. This tool was developed to enhance the extremely low-light images of the interior of PSRs and provide the ability to see within these regions at and discern surface features (i.e. boulders and craters) down to 3 meters in size. We focused on the Nobile region on the Lunar south pole, selected site for VIPER mission and stitched several images to create a high-resolution map within one of the PSR of Nobile crater. Figure 1 shows the dark PSR zone form the original NAC layer of LRO as the base layer (left image) and the illuminated areas within that crater (center) which was created by ingesting and merging several of HORUS generated images. At present we employ a semi-automated process to ensure spatial accuracy and merger of several overlapping zones. However, we are in the process of completely automating this process by employing AI based techniques that would rank, sort, and stack the images based on their information density. The georectification of the images would employ selected features. Analysis on Ingested Planetary Datasets: Once an external planetary data-set is successfully ingested, georectified and merged seamlessly as a data-layer; CMS’ numerous analysis tools can be used on this data. A Line of Sight (LOS) tool has been developed for CMS which analyzes terrain profiles and obstructions to determine visibility for remote observers. Figure 1 (right image) shows the viewshed analysis on the same PSR in the Nobile region. The yellow pin shows the observer location outside the PSR. The yellow area shows the visible part of PSR. The obstructed area with no visibility for the observer is shown in red. The Measurements tool allows the user to take area and distance measurements of features on the terrain using various shapes. Measurement type can be specified in a number of ways: Line, Path, Polygon, Circle, Ellipse, Square, Rectangle or Freehand. Once the shape is specified, elevation information can then be extracted along each of these shapes. Figure 2 (left) shows the measurements performed on a crater n illuminated PSR in Nobile region. The equipment placement tool allows the user to place a 3D equipment model at a desired location and analyze its coverage area. The equipment placement tool is coupled with LOS to determine the coverage. Figure 2 (right) shows an equipment placed on the Lunar terrain and it’s coverage area. The red rays are blocked sight lines and the green rays are non-obstructed sight lines with the cyan lines showing the point of intersection with the terrain. More details are provided in the video demonstrations in Reference 5. Overcoming Polar Distortions: 3D geospatial applications exhibit significant distortions in polar imagery due to several reasons: 1) distortions in the source imagery, 2) incompatible tessellation algorithms at the poles, and 3) map projections. We are leveraging new tessellation algorithms and reprojecting data using projections that are better suited for Lunar poles. The goal is to seamlessly switch to polar projections while maintaining 3D view and navigation.

Maps↗
DOE OSTI2022

A spatial superstructure approach to the optimal design of modular processes and supply chains

Modularity is a design principle that aims to provide flexibility for spatio-temporal assembly/disassembly and reconfiguration of systems. This design principle can be applied to multiscale (hierarchical) manufacturing systems that connect units, processes, facilities, and entire supply chains. Designing modular systems is challenging because of the need to capture spatial interdependencies that arise between system components due to product exchange/transport between components and due to product transformation in such components. In this work, we propose an optimization framework to facilitate the design of modular manufacturing systems. Central to our approach is the concept of a spatial superstructure, which is a graph that captures all possible system configurations and interdependencies between components. The spatial superstructure is a generalization of the notion of a superstructure and of a p-graph used in process design, in that it encodes spatial (geographical) context of the system components. Here, we show that this generalization facilitates the simultaneous design and analysis of processes, facilities, and of supply chains. Our framework aims to select the system topology from the spatial superstructure that minimizes design cost and that maximizes design modularity. We show that this design problem can be cast as a mixed-integer, multi-objective optimization formulation. We demonstrate these capabilities using a case study arising in the design of a plastic waste upcycling supply chain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Tuning Gold Nanoparticle Size with Fixed Interparticle Spacing in Large-Scale Arrays: Implications for Plasmonics and Nanoparticle Etching Masks

Gold nanoparticles play an important role in plasmonic arrays, including, but not limited to, photovoltaic, biomedical, sensing, optical, and catalytic applications. For plasmonic arrays, control over spatial variables of the array, such as nanoparticle size and spacing, must be judiciously cared for. In this work, we present here a multistep deposit/dewet process for nanoparticle ensemble fabrication that exploits thermally driven solid-state diffusional dewetting, coupled with Ostwald ripening, to tune the nanoparticle size or area coverage for a particular particle–particle spacing. The initial dewetting process defines the spatial period of the array, with subsequent dewetting steps growing the nanoparticles while adhering to the “seeded” period from the first dewetting. Following the fifth deposit/dewet cycle, relative to the first cycle, the mean nanoparticle height exhibited a percent increase of 90 and 66% for 5 and 7.5 nm multistep deposit/dewet processes, respectively, while minimally impacting the ensemble period. This provides unprecedented control over the spatial parameters of large-scale nanoparticle ensembles for plasmonic and etching-mask applications where a particular particle size and spacing are desired. Due to the simplicity of the technique and its area scalability, the cyclic deposition/dewetting process is shown here to be a method that can be easily scaled up to apply to large-area (up to meter-size) applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Kinetic Modeling of Secondary Organic Aerosol in a Weather-Chemistry Model: Parameterizations, Processes, and Predictions for GOAmazon

Secondary organic aerosol (SOA) forms and evolves in the atmosphere through many pathways and processes, over diverse spatial and time scales. Hence, there is a need to represent these widely-varying kinetic processes in large-scale atmospheric models to allow for accurate predictions of the abundance, properties, and impacts of SOA. In this work, we integrated a kinetic, process-level model (simpleSOM-MOSAIC) into a weather-chemistry model (WRF-Chem) to simulate the oxidation chemistry and microphysics of atmospheric SOA. simpleSOM-MOSAIC simulates multigenerational gas-phase chemistry, autoxidation reactions, heterogeneous oxidation, oligomerization, and phase-state-influenced gas/particle partitioning of SOA. As a case study, the integrated WRF-Chem-simpleSOM-MOSAIC (WC-SSM) model was used to simulate the photochemical evolution downwind of a large city (Manaus, Brazil) in the Amazon and, in turn, study the anthropogenic and biogenic interactions in an otherwise pristine environment. Consistent with previous work, we found that OA was enhanced by up to a factor of four in the urban plume due to elevated hydroxyl radical (OH) concentrations, relative to the background, and that this OA was dominated by SOA from biogenic precursors (80%). Further, in addition to accurately simulating the OA enhancement in the urban plume, the model reproduced the magnitude of the OA oxygen-to-carbon (O:C) ratio and broadly tracked the evolution of the aerosol size distribution. Our work highlights the importance of including an integrated, kinetic representation of SOA processes in an atmospheric model

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1973

Automation of measurement of spatial damping parameters

A traveling wave unit was built to process measurement data on spatial damping parameters and to simplify statistical treatment of the results. Mean values of the loss coefficient, lengths of flexual waves, and wave propagation velocities for a given set of discrete functions were determined. Results are given in a table.

Akolzin, A. N.↗
DOE OSTI2023

Cross-Scale Land-Atmosphere Experiment (CSLAEX) (Final Report)

It is now well recognized that land-atmosphere interactions play an important role in both weather and climate. These interactions take place over a wide range of spatial and temporal scales. Most of the current formulations of the momentum, heat and moisture transport laws are informed by observations with a limited temporal or spatial scale, and hence may have limited applicability. The objective of this work is to improve the multi-scale representation of the near-surface heat transfer in the ground and in the atmosphere using a combination of modeling and field observations. Our knowledge and predictive capacity in land-atmosphere coupling is limited by our capacity to observe the full-scale spectrum at play. In order to bridge this fundamental gap in our observation capacity I will work to: create the first long-term Integrated Cross-Scale land-Atmosphere Experiment (CSLAEX) since I will work to: measure the components of the surface energy balance at a spatial scale relevant to remote sensing and meteorological applications (5km), along with observations of the nested subscale processes with Distributed Temperature Sensors (DTS). This proposal aims to fill the gaps in modeling and observing land-atmosphere interactions across scales via a novel Cross-Scale Land-Atmosphere Experiment (CSLAEX) to be implemented as part of the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site near Lamont, Oklahoma. The proposed research effort aims at exploring land-atmosphere processes across multiple spatial scales and to investigate the effect of landscape heterogeneity using Distributed Temperature Sensor measurements. The novel instrumentation of the Surface Energy Balance and simultaneous observations of the atmospheric state (boundary layer, cloud, convection) available at the DOE ARM SGP site will be used to create CSLAEX. This dataset will be used to frame and evaluate new transport laws and parameterizations for the boundary layer and the land surface, which can be implemented into the Weather and Research Forecasting (WRF) model and Community Atmospheric Model (CAM). The result of this study should impact multiple fields: meteorology, climate, and hydrology.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1995

Two cis elements collaborate to spatially repress transcription from a sea urchin promoter

The expression pattern of many territory-specific genes in metazoan embryos is maintained by an active process of negative spatial regulation. However, the mechanism of this strategy of gene regulation is not well understood in any system. Here we show that reporter constructs containing regulatory sequence for the SM30-alpha gene of Stronglyocentrotus purpuratus are expressed in a pattern congruent with that of the endogenous SM30 gene(s), largely as a result of active transcriptional repression in cell lineages in which the gene is not normally expressed. Chloramphenicol acetyl transferase assays of deletion constructs from the 2600-bp upstream region showed that repressive elements were present in the region from -1628 to -300. In situ hybridization analysis showed that the spatial fidelity of expression was severely compromised when the region from -1628 to -300 was deleted. Two highly repetitive sequence motifs, (G/A/C)CCCCT and (T/C)(T/A/C)CTTTT(T/A/C), are present in the -1628 to -300 region. Representatives of these elements were analyzed by gel mobility shift experiments and were found to interact specifically with protein in crude nuclear extracts. When oligonucleotides containing either sequence element were co-injected with a correctly regulated reporter as potential competitors, the reporter was expressed in inappropriate cells. When composite oligonucleotides, containing both sequence elements, were fused to a misregulated reporter, the expression of the reporter in inappropriate cells was suppressed. Comparison of composite oligonucleotides with oligonucleotides containing single constituent elements show that both sequence elements are required for effective spatial regulation. Thus, both individual elements are required, but only a composite element containing both elements is sufficient to function as a tissue-specific repressive element.

Non-NASA Center↗
DOE OSTI2023

Spectroscopic measurement of increases in hydrogen molecular rotational temperature with plasma-facing surface temperature and due to collisional-radiative processes in tokamaks

Abstract Spatially resolved rotational temperature of ground state hydrogen molecules desorbed from plasma-facing surface was measured in QUEST, LTX-β, and DIII-D tokamaks, and the increases of the rotational temperature with the surface temperature and due to collisional-radiative processes in the plasmas were evaluated. The increase due to collisional-radiative processes was calculated by solving rate equations considering electron and proton collisional excitation and deexcitation and spontaneous emission. The calculation results suggest a high sensitivity for the rotational temperature to electron and proton densities, but a negligible sensitivity to the electron, proton, and surface temperatures. In the three tokamaks with different plasma parameters and plasma-facing surface materials, the spatial profile of the rotational temperature was estimated using Fulcher-α emission lines (600–608 nm). In QUEST, the spatial profile of the rotational temperature was estimated from spatially resolved spectra. In the other tokamaks, the rotational temperature was evaluated assuming a single point emission with a location determined from the Fulcher-α emission profile as measured with a filtered camera. In metal-walled devices QUEST and LTX-β, the rotational temperature increased with the surface temperature, and the calculated collisional-radiative increase is consistent with measured increase assuming that the rotational temperature at the surface is approximately 500–600 K higher than the surface temperature. In DIII-D with carbon walls, a larger collisional-radiative increase than the other tokamaks was observed because of the higher density leading to a large difference from the calculated increase compared to the other smaller tokamaks. Measurement of the Fulcher-α emission profile with higher spatial resolution in DIII-D may reduce the difference and reveal the effect of the surface temperature on the rotational temperature. These results show the increases in the rotational temperature with the surface temperature and due to the collisional-radiative processes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Efficient light harvesting and photon sensing via engineered cooperative effects

Abstract Efficient devices for light harvesting and photon sensing are fundamental building blocks of basic energy science and many essential technologies. Recent efforts have turned to biomimicry to design the next generation of light-capturing devices, partially fueled by an appreciation of the fantastic efficiency of the initial stages of natural photosynthetic systems at capturing photons. In such systems extended excitonic states are thought to play a fundamental functional role, inducing cooperative coherent effects, such as superabsorption of light and supertransfer of photoexcitations. Inspired by this observation, we design an artificial light-harvesting and photodetection device that maximally harnesses cooperative effects to enhance efficiency. The design relies on separating absorption and transfer processes (energetically and spatially) in order to overcome the fundamental obstacle to exploiting cooperative effects to enhance light capture: the enhanced emission processes that accompany superabsorption. This engineered separation of processes greatly improves the efficiency and the scalability of the system.

42 ENGINEERING↗
DOE OSTI2023

Robust reconstruction of single-cell RNA-seq data with iterative gene weight updates

Single-cell RNA-sequencing technologies have greatly enhanced our understanding of heterogeneous cell populations and underlying regulatory processes. However, structural (spatial or temporal) relations between cells are lost during cell dissociation. These relations are crucial for identifying associated biological processes. Many existing tissue-reconstruction algorithms use prior information about subsets of genes that are informative with respect to the structure or process to be reconstructed. When such information is not available, and in the general case when the input genes code for multiple processes, including being susceptible to noise, biological reconstruction is often computationally challenging. We propose an algorithm that iteratively identifies manifold-informative genes using existing reconstruction algorithms for single-cell RNA-seq data as subroutine. We show that our algorithm improves the quality of tissue reconstruction for diverse synthetic and real scRNA-seq data, including data from the mammalian intestinal epithelium and liver lobules.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2017

Experimental Setup for the Laboratory Investigation of Micrometeoroid Ablation Using a Dust Accelerator

A facility has been developed to simulate the ablation of micrometeoroids in laboratory conditions. An electrostatic dust accelerator is used to generate iron particles with velocities of 10-70 kilometers. The particles are then introduced into a chamber pressurized with a target gas, where the pressure is adjustable between 0.01 and 0.5 Torr, and the particle partially or completely ablates over a short distance. An array of biased electrodes above and below the ablation path is used to collect the generated ions/electrons with a spatial resolution of 2.6 centimeters along the ablating particles path, thus allowing the study of the spatiotemporal evolution of the process. For completely ablated particles, the total collected charge directly yields the ionization coefficient of a given dust material-target gas combination. The first results of this facility measured the ionization coefficient of iron atoms with N2, air, CO2, and He target gases for impact velocities greater than 20 kilometers per second, and are reported by Thomas et al. The ablation chamber is also equipped with four optical ports that allow for the detection of the light emitted by the ablating particle. A multichannel photomultiplier tube system is used to observe the ablation process with a spatial and temporal resolution of 0.64 centimeters and 90 nanoseconds. The preliminary results indicate that it is possible to calculate the velocity of the ablating particle from the optical observations, and in conjunction with the spatially resolved charge measurements allow for experimental validation of ablation models in future studies.

Thomas, Evan↗
NASA NTRS2004

Scientific Objectives, Measurement Needs, and Challenges Motivating the PARAGON Aerosol Initiative

Aerosols are involved in a complex set of processes that operate across many spatial and temporal scales. Understanding these processes, and ensuring their accurate representation in models of transport, radiation transfer, and climate, requires knowledge of aerosol physical, chemical, and optical properties and the distributions of these properties in space and time. To derive aerosol climate forcing, aerosol optical and microphysical properties and their spatial and temporal distributions, and aerosol interactions with clouds, need to be understood. Such data are also required in conjunction with size-resolved chemical composition in order to evaluate chemical transport models and to distinguish natural and anthropogenic forcing. Other basic parameters needed for modeling the radiative influences of aerosols are surface reflectivity and three-dimensional cloud fields. This large suite of parameters mandates an integrated observing and modeling system of commensurate scope. The Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) concept, designed to meet this requirement, is motivated by the need to understand climate system sensitivity to changes in atmospheric constituents, to reduce climate model uncertainties, and to analyze diverse collections of data pertaining to aerosols. This paper highlights several challenges resulting from the complexity of the problem. Approaches for dealing with them are offered in the set of companion papers.

optical depth↗
DOE OSTI2025

High-energy transient gas pinholes via saturated absorption

This Letter presents a spatial filter based on saturated absorption in gas as an alternative to the solid pinhole in a lens–pinhole–lens filtering system. We develop an analytic model that describes this process and demonstrate spatial filtering with simulations and experiments. We show that an ultraviolet laser pulse focused through ozone will have its spatial profile cleaned if its peak fluence rises above the ozone saturation fluence. Specifically, we demonstrate that a 5 ns 266 nm beam with 4.2 mJ of the initial energy can be effectively cleaned by focusing through a 1.4% ozone–oxygen mixture, with about 76% of the main beam energy transmitted and 89% of the sidelobe energy absorbed. In conclusion, this process can be adapted to other gases and laser wavelengths, providing alignment-insensitive and damage-resistant pinholes for high-repetition-rate high-energy lasers.

Ou, K. [Stanford Univ., CA (United States)] (ORCID↗
NASA NTRS1985

Cometary atmospheres: Modeling the spatial distribution of observed neutral radicals

Progress on modeling the spatial distributions of cometary radicals is described. The Monte Carlo particle-trajectory model was generalized to include the full time dependencies of initial comet expansion velocities, nucleus vaporization rates, photochemical lifetimes and photon emission rates which enter the problem through the comet's changing heliocentric distance and velocity. The effect of multiple collisions in the transition zone from collisional coupling to true free flow were also included. Currently available observations of the spatial distributions of the neutral radicals, as well as the latest available photochemical data were re-evaluated. Preliminary exploratory model results testing the effects of various processes on observable spatial distributions are also discussed.

Combi, M. R.↗
NASA NTRS1992

Analysis of CCD images of the coma of comet P/Halley

The modeling analysis objective of this project is to make use of the skill acquired in the development of Monte Carlo particle trajectory models for the distributions of gas species in cometary comae as a basis for a new dust coma model. This model will include a self-consistent picture of the time-dependent dusty-gas dynamics of the inner coma and the three-dimensional time-dependent trajectories of the dust particles under the influence of solar gravity and solar radiation pressure in the outer coma. Our purpose is to use this model as a tool to analyze selected images from two sets of data of the comet P/Halley with the hope that we can help to understand the effects of a number of important processes on the spatial morphology of the observed dust coma. The study will proceed much in the same way as our study of the spatially extended hydrogen coma where we were able to understand the spatial morphology of the Lyman-alpha coma in terms of the partial thermalization of the hot H atoms produced by the photodissociation of cometary H2O and OH. The processes of importance to the observed dust coma include: (1) the dust particle size distribution function; (2) the terminal velocities of various sized dust particles in the inner coma; (3) the radiation scattering properties of dust particles, which are important both in terms of the observed scattered radiation and the radiation pressure acceleration on dust particles; (4) the fragmentation and/or vaporization of dust particles; (5) the relative importance of CHON and silicate dust particles as they contribute both to the dusty-gas dynamics in the inner coma (that produce the dust particle terminal velocities) and to the observed spatial morphology of the outer dust coma; and (6) the time and direction dependence of the source of dust.

Combi, Michael R.↗
DOE OSTI2024

In-situ qualification and physics-based process design for aerosol jet printing via spatially correlated light scattering measurements

Aerosol jet printing is a contactless, digital, and additive technique broadly used for manufacturing flexible, hybrid, and conformal electronics. However, batch-to-batch variability has hindered widespread industry adoption and scaling to production volumes. Recently, light scattering measurements have emerged as a tool to measure aerosol volume fraction – a key parameter determining deposition rate – and have proven an effective feedback source for closed loop control on timescales ranging from minutes to hours. Here, the efficacy of light scattering measurements as a tool for in-situ qualification over shorter time durations is explored. To be the linear relationship between light scattering measurements and deposition rate was validated at 500 ms time intervals, allowing deposition rate to be mapped to positional coordinates and providing a new data stream to drive quality control assessments. Because light scattering measurements are indicative of a physical process parameter, they were substituted into equations for resistance and sheet resistance, resulting in predictions nominally within 10% of measured values for sets of printed devices. Finally, to highlight a more active utility, light scattering measurements were employed in a print repair framework, successfully repairing prints with randomly induced defects to within 5% of the measured resistance of a control set.

36 MATERIALS SCIENCE↗
NASA NTRS1983

Monitoring tropical vegetation succession with LANDSAT data

The shadowing problem, which is endemic to the use of LANDSAT in tropical areas, and the ability to model changes over space and through time are problems to be addressed when monitoring tropical vegetation succession. Application of a trend surface analysis model to major land cover classes in a mountainous region of the Phillipines shows that the spatial modeling of radiance values can provide a useful approach to tropical rain forest succession monitoring. Results indicate shadowing effects may be due primarily to local variations in the spectral responses. These variations can be compensated for through the decomposition of the spatial variation in both elevation and MSS data. Using the model to estimate both elevation and spectral terrain surface as a posteriori inputs in the classification process leads to improved classification accuracy for vegetation of cover of this type. Spatial patterns depicted by the MSS data reflect the measurement of responses to spatial processes acting at several scales.

Robinson, V. B.↗
DOE OSTI2022

A gradient-based deep neural network model for simulating multiphase flow in porous media

We report simulation of multiphase flow in porous media is crucial for the effective management of subsurface energy and environment-related activities. The numerical simulators used for modeling such processes rely on spatial and temporal discretization of the governing mass and energy balance partial-differential equations (PDEs) into algebraic systems via finite-difference/volume/element methods. These simulators usually require dedicated software development and maintenance, and suffer low efficiency from a runtime and memory standpoint for problems with multi-scale heterogeneity, coupled-physics processes or fluids with complex phase behavior. Therefore, developing cost-effective, data-driven models can become a practical choice, and in this work, we choose deep learning approaches as they can handle high dimensional data and accurately predict state variables with strong nonlinearity. In this paper, we describe a gradient-based deep neural network (GDNN) constrained by the physics related to multiphase flow in porous media. We tackle the nonlinearity of flow in porous media induced by rock heterogeneity, fluid properties, and fluid-rock interactions by decomposing the nonlinear PDEs into a dictionary of elementary differential operators. We use a combination of operators to handle rock spatial heterogeneity and fluid flow by advection. Since the augmented differential operators are inherently related to the physics of fluid flow, we treat them as first principles prior knowledge to regularize the GDNN training. We use the example of pressure management at geologic CO 2 storage sites, where CO 2 is injected in saline aquifers and brine is produced, and apply GDNN to construct a predictive model that is trained with physics-based simulation data and emulates the physics process. We demonstrate that GDNN can effectively predict the nonlinear patterns of subsurface responses, including the temporal and spatial evolution of the pressure and saturation plumes. We also successfully extend the GDNN to convolutional neural network (CNN), namely gradient-based CNN (GCNN), and validate its capability to improve the prediction accuracy. GDNN has great potential to tackle challenging problems that are governed by highly nonlinear physics and enable the development of data-driven models with higher fidelity.

42 ENGINEERING↗