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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Experimental and Computational Studies of the Flow Over a Sting Mounted Planetary Probe Configuration

This paper summarizes the results of a series of experimental studies in the LENS shock tunnel and computations with DSMC and Navier Stokes codes which have been made to examine the aerothermal and flowfield characteristics of the flow over a sting-supported planetary probe configuration in hypervelocity air and nitrogen flows. The experimental program was conducted in the LENS hypervelocity shock tunnel at total enthalpies of 5and 10 MJkg for a range of reservoir pressure conditions from 70 to 500 bars. Heat transfer and pressure measurements were made on the front and rear face of the probe and along the supporting sting. High-speed and single shot schlieren photography were also employed to examine the flow over the model and the time to establish the flow in the base recirculation region. Predictions of the flowfield characteristics and the distributions of heat transfer and pressure were made with DSMC codes for rarefied flow conditions and with the Navier-Stokes solvers for the higher pressure conditions where the flows were assumed to be laminar. Analysis of the time history records from the heat transfer and pressure instrumentation on the face of the probe and in the base region indicated that the base flow was fully established in under 4 milliseconds from flow initiation or between 35 and 50 flow lengths based on base height. The measurements made in three different tunnel entries with two models of identical geometries but with different instrumentation packages, one prepared by NASA Langley and the second prepared by CUBRC, demonstrated good agreement between heat transfer measurements made with two different types of thin film and coaxial gage instrumentation. The measurements of heat transfer and pressure to the front face of the probe were in good agreement with theoretical predictions from both the DSMC and Navier Stokes codes. For the measurements made in low density flows, computations with the DSMC code were found to compare well with the pressure and heat transfer measurements on the sting, although the computed heat transfer rates in the recirculation region did not exhibit the same characteristics as the measurements. For the 10MJkg and 500 bar reservoir match point condition, the measurements and heat transfer along the sting from the first group of studies were in agreement with the Navier Stokes solutions for laminar conditions. A similar set of measurements made in later tests where the model was moved to a slightly different position in the test section indicated that the boundary layer in the reattachment compression region was close to transition or transitional where small changes in the test environment can result in larger than laminar heating rates. The maximum heating coefficients on the sting observed in the present studies was a small fraction of similar measurements obtained at nominally the same conditions in the HEG shock tunnel, where it is possible for transition to occur in the base flow, and in the low enthalpy studies conducted in the NASA Langley high Reynolds number Mach 10 tunnel where the base flow was shown to be turbulent. While the hybrid Navier- StokedDMSC calculations by Gochberg et al. (Reference 1) suggested that employing the Navier- Stokes calculations for the entire flowfield could be seriously in error in the base region for the 10 MJkg, 500 bar test case, similar calculations performed by Cornell, presented here, do not.

Holden, Michael S.↗
DOE OSTI2024

ML-based Data Assimilation and History Matching: Application to the IBDP CCS Project

It is crucial to monitor the CO2 plume effectively throughout the life cycle of a geologic CO2 sequestration project to ensure safety and storage efficiency. However, the computational cost of existing data assimilation methods can be prohibitively expensive due to the complex physics with multi-component non-isothermal simulation and high dimensionality of large-scale reservoir models. We address this challenge by proposing an accelerated deep learning-based workflow for model calibration and prediction of CO2 plume evolution in the reservoir.The power and efficacy of our workflow is demonstrated by application to the Illinois Basin-Decatur Project (IBDP), a large-scale CO2 storage test in saline aquifer. The data assimilation process is implemented rapidly by the proposed workflow with given field measurements including distributed pressure and temperature sensing (DTS) data at an injection and a monitoring well. CO2 plume evolution is predicted by running the simulations of the calibrated reservoir models.

Nagao, Masahiro↗
NASA NTRS1972

Computer acquired performance data from an etched-rhenium, molybdenum planar diode

Performance data from an etched-rhenium, molybdenum thermionic converter are presented. The planar converter has a guard-ringed collector and a fixed spacing of 0.254 mm (10 mils). The data were acquired by using a computer and are available on microfiche as individual or composite parametric current, voltage curves. The parameters are the temperatures of the emitter T sub E, collector T sub C and cesium reservoir T sub R. The composite plots have constant T sub E, and varying T sub C or T sub R, or both. The envelope and composite plots having constant I sub E are presented. The diode was tested at increments between 1500 and 2000 K for the emitter, 750 and 1100 K for the collector, and 540 and 640 K for the reservoir. In all, 774 individual current, voltage curves were obtained.

Manista, E. J.↗
DOE OSTI2024

Mixed Delay/Nondelay Embeddings Based Neuromorphic Computing with Patterned Nanomagnet Arrays

Patterned nanomagnet arrays (PNAs) have been shown to exhibit a strong geometrically frustrated dipole interaction. Some PNAs have also shown emergent domain wall dynamics. Previous works have demonstrated methods to physically probe these magnetization dynamics of PNAs to realize neuromorphic reservoir systems that exhibit chaotic dynamical behavior and high-dimensional nonlinearity. These PNA reservoir systems from prior works leverage echo state properties and linear/nonlinear short-term memory of component reservoir nodes to map and preserve the dynamical information of the input time-series data into nondelay spatial embeddings. Such mappings enable these PNA reservoir systems to imitate and predict/forecast the input time series data. However, these prior PNA reservoir systems are based solely on the nondelay spatial embeddings obtained at component reservoir nodes. As a result, they require a massive number of component reservoir nodes, or a very large spatial embedding (i.e., high-dimensional spatial embedding) per reservoir node, or both, to achieve acceptable imitation and prediction accuracy. These requirements reduce the practical feasibility of such PNA reservoir systems. To address this shortcoming, we present a mixed delay/nondelay embeddings-based PNA reservoir system. Our system uses a single PNA reservoir node with the ability to obtain a mixture of delay/nondelay embeddings of the dynamical information of the time-series data applied at the input of a single PNA reservoir node. Our analysis shows that when these mixed delay/nondelay embeddings are used to train a perceptron at the output layer, our reservoir system outperforms existing PNA-based reservoir systems for the imitation of NARMA 2, NARMA 5, NARMA 7, and NARMA 10 time series data, and for the short-term and long-term prediction of the Mackey Glass time series data.

Ti, Changpeng↗
DOE OSTI2024

Matrix-Free High-Performance Saddle-Point Solvers for High-Order Problems in \(\boldsymbol{H}(\operatorname{\textbf{div}})\)

Here, this work describes the development of matrix-free GPU-accelerated solvers for high-order finite element problems in H(div). The solvers are applicable to grad-div and Darcy problems in saddle-point formulation, and have applications in radiation diffusion and porous media flow problems, among others. Using the interpolation–histopolation basis, efficient matrix-free preconditioners can be constructed for the (1, 1)-block and Schur complement of the block system. With these approximations, block-preconditioned MINRES converges in a number of iterations that is independent of the mesh size and polynomial degree. The approximate Schur complement takes the form of an M-matrix graph Laplacian and therefore can be well-preconditioned by highly scalable algebraic multigrid methods. High-performance GPU-accelerated algorithms for all components of the solution algorithm are developed, discussed, and benchmarked. Numerical results are presented on a number of challenging test cases, including the “crooked pipe” grad-div problem, the SPE10 reservoir modeling benchmark problem, and a nonlinear radiation diffusion test case.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Permeability Prediction Using Vision Transformers

Accurate permeability predictions remain pivotal for understanding fluid flow in porous media, influencing crucial operations across petroleum engineering, hydrogeology, and related fields. Traditional approaches, while robust, often grapple with the inherent heterogeneity of reservoir rocks. With the advent of deep learning, convolutional neural networks (CNNs) have emerged as potent tools in image-based permeability estimation, capitalizing on micro-CT scans and digital rock imagery. This paper introduces a novel paradigm, employing vision transformers (ViTs)—a recent advancement in computer vision—for this crucial task. ViTs, which segment images into fixed-sized patches and process them through transformer architectures, present a promising alternative to CNNs. We present a methodology for implementing ViTs for permeability prediction, its results on diverse rock samples, and a comparison against conventional CNNs. The prediction results suggest that, with adequate training data, ViTs can match or surpass the predictive accuracy of CNNs, especially in rocks exhibiting significant heterogeneity. This study underscores the potential of ViTs as an innovative tool in permeability prediction, paving the way for further research and integration into mainstream reservoir characterization workflows.

58 GEOSCIENCES↗
DOE OSTI2023

A reactive tracer method for predicting EGS reservoir geometry and thermal lifetime: development and field validation

The project summarized here (DOE Award No. DE-EE0006764) was intended to develop a methodology for predicting advective heat transfer in fracture-dominated crystalline rock. Our goal was to determine if a combination of inert and reactive tracers could adequately constrain the effective heat transfer surface area between an injection-production well pair. Our approach consisted of: 1. developing a novel computational framework; 2. Performing heat and tracer experiments at meso-scale; and 3. Comparing predictions of advective heat transfer to the “true” thermal breakthrough measured at the Altona site. Below is a summary of project activities/findings, a summary of project tasks, and a conclusion

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

BiGEST

Natural products have provided a rich reservoir of beneficial compounds in public health including antibiotics, therapeutics, and immunosuppressants. These natural products are synthesized by enzymes encoded by Biosynthetic Gene Clusters (BGCs), clusters of co-localized biosynthetic genes. Computational detection of BGCs has become a crucial step in natural product discovery. While this process has been facilitated in bacterial and fungal organisms thanks to the currently available tools (e.g., antiSMASH), a large spectrum of eukaryotic organisms have been neglected by these existing tools due to the scarcity and incompleteness of genome annotation resources. Here, we introduce Biosynthetic Gene cluster Extensive Search Tool (BiGEST) to provide an extensive annotation-free search for BGCs in diverse eukaryotic organisms. As a result, BiGEST uncovers eukaryotic BGCs that could be undetected by other BGC detection tools.

Adriani, Lisa↗
DOE OSTI2023

Legacy Well Leakage Risk Analysis at the Farnsworth Unit Site

This paper summarizes the results of the risk analysis and characterization of the CO 2 and brine leakage potential of Farnsworth Unit (FWU) site wells. The study is part of the U.S. DOE’s National Risk Assessment Partnership (NRAP) program, which aims to quantitatively evaluate long-term environmental risks under conditions of significant geologic uncertainty and variability. To achieve this, NRAP utilizes risk assessment and computational tools specifically designed to quantify uncertainties and calculate the risk associated with geologic carbon dioxide (CO 2 ) sequestration. For this study, we have developed a workflow that utilizes physics-based reservoir simulation results as input to perform leakage calculations using NRAP Tools, specifically NRAP-IAM-CS and RROM-Gen. These tools enable us to conduct leakage risk analysis based on ECLIPSE reservoir simulation results and to characterize wellbore leakage at the Farnsworth Unit Site. We analyze the risk of leakage from both individual wells and the entire field under various wellbore integrity distribution scenarios. The results of the risk analysis for the leakage potential of FWU wells indicate that, when compared to the total amount of CO 2 injected, the highest cemented well integrity distribution scenario (FutureGen high flow rate) exhibits approximately 0.01% cumulative CO 2 leakage for a 25-year CO 2 injection duration at the end of a 50-year post-injection monitoring period. In contrast, the highest possible leakage scenario (open well) shows approximately 0.1% cumulative CO 2 leakage over the same time frame.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1977

Mathematical and computational studies of equilibrium capillary free surfaces

The results of several independent studies are presented. The general question is considered of whether a wetting liquid always rises higher in a small capillary tube than in a larger one, when both are dipped vertically into an infinite reservoir. An analytical investigation is initiated to determine the qualitative behavior of the family of solutions of the equilibrium capillary free-surface equation that correspond to rotationally symmetric pendent liquid drops and the relationship of these solutions to the singular solution, which corresponds to an infinite spike of liquid extending downward to infinity. The block successive overrelaxation-Newton method and the generalized conjugate gradient method are investigated for solving the capillary equation on a uniform square mesh in a square domain, including the case for which the solution is unbounded at the corners. Capillary surfaces are calculated on the ellipse, on a circle with reentrant notches, and on other irregularly shaped domains using JASON, a general purpose program for solving nonlinear elliptic equations on a nonuniform quadrilaterial mesh. Analytical estimates for the nonexistence of solutions of the equilibrium capillary free-surface equation on the ellipse in zero gravity are evaluated.

Albright, N.↗
NASA NTRS1992

Computer Program For Variable-Conductance Heat Pipes

VCHPDA provides accurate mathematical models of transient as well as steady-state performance of variable-conductance heat pipes over wide range of operating conditions. Applies to heat pipes with either cold, wicked or hot, nonwicked gas reservoirs and uses ideal-gas law and "flat-front" (negligible vapor diffusion) gas theory. Calculates length of gas-blocked region and temperature of vapor in active portion of heat pipe by solving set of nonlinear equations for conservation of energy and mass. Written in FORTRAN 77.

Antoniuk, D.↗
DOE OSTI2020

A Model Tree Generator (MTG) Framework for Simulating Hydrologic Systems: Application to Reservoir Routing

Data-driven algorithms have been widely used as effective tools to mimic hydrologic systems. Unlike black-box models, decision tree algorithms offer transparent representations of systems and reveal useful information about the underlying process. A popular class of decision tree models is model tree (MT), which is designed for predicting continuous variables. Most MT algorithms employ an exhaustive search mechanism and a pre-defined splitting criterion to generate a piecewise linear model. However, this approach is computationally intensive, and the selection of the splitting criterion can significantly affect the performance of the generated model. These drawbacks can limit the application of MTs to large datasets. To overcome these shortcomings, a new flexible Model Tree Generator (MTG) framework is introduced here. MTG is equipped with several modules to provide a flexible, efficient, and effective tool for generating MTs. The application of the algorithm is demonstrated through simulation of controlled discharge from several reservoirs across the Contiguous United States (CONUS).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Hydropower Scheduling Toolchains: Comparing Experiences in Brazil, Norway, and USA and Implications for Synergistic Research

While hydropower scheduling is a well-defined problem, there are institutional differences that need to be identified to promote constructive and synergistic research. We study how established toolchains of computer models are organized to assist operational hydropower scheduling in Brazil, Norway, and the United States’ Colorado River System (CRS). These three systems have vast hydropower resources, with numerous, geographically widespread, and complex reservoir systems. Although the underlying objective of hydropower scheduling is essentially the same, the systems are operated in different market contexts and with different alternative uses of water, where the stakeholders’ objectives clearly differ. This in turn leads to different approaches when it comes to the scope, organization, and use of models for operational hydropower scheduling and the information flow between the models. Here, we describe these hydropower scheduling toolchains, identify the similarities and differences, and shed light on the original ideas that motivated their creation. We then discuss the need to improve and extend the current toolchains and the opportunities to synergistic research that embrace those contextual differences.

13 HYDRO ENERGY↗
DOE OSTI2021

Connect the Dots: In Situ 4-D Seismic Monitoring of CO 2 Storage With Spatio-Temporal CNNs

4-D seismic imaging has been widely used in CO 2 sequestration projects to monitor the fluid flow in the volumetric subsurface region that is not sampled by wells. Ideally, real-time monitoring and near-future forecasting would provide site operators with great insights to understand the dynamics of the subsurface reservoir and assess any potential risks. However, due to obstacles such as high deployment cost, availability of acquisition equipment, exclusion zones around surface structures, only very sparse seismic imaging data can be obtained during monitoring. That leads to an unavoidable and growing knowledge gap over time. The operator needs to understand the fluid flow throughout the project lifetime and the seismic data are only available at a limited number of times. This is insufficient for understanding reservoir behavior. To overcome those challenges, we have developed spatio-temporal neural-network-based models that can produce high-fidelity interpolated or extrapolated images effectively and efficiently. Specifically, our models are built on an autoencoder, and incorporate the long short-term memory (LSTM) structure with a new loss function regularized by optical flow. We validate the performance of our models using real 4-D post-stack seismic imaging data acquired at the Sleipner CO 2 sequestration field. We employ two different strategies in evaluating our models. Numerically, we compare our models with different baseline approaches using classic pixel-based metrics. We also conduct a blind survey and collect a total of 20 responses from domain experts to evaluate the quality of data generated by our models. Finally, via both numerical and expert evaluation, we conclude that our models can produce high-quality 2-D/3-D seismic imaging data at a reasonable cost, offering the possibility of real-time monitoring or even near-future forecasting of the CO 2 storage reservoir.

4-D seismic imaging↗
DOE OSTI2022

Quantitative interpretation of time-lapse seismic data at Farnsworth field unit: Rock physics modeling, and calibration of simulated time-lapse velocity responses

Here, this study investigates the contribution of fluid saturation variation to the time-lapse velocity response by performing fluid substitution modeling. The methodology is exemplified by the time-lapse seismic monitoring of carbon dioxide at Farnsworth field unit (FWU). In order to evaluate the fluid distribution in a matured oil reservoir, the Southwest Regional Partnership (SWP) acquired multiple vertical seismic profile (VSP) surveys at different times during the CO 2 –water alternatinggas (WAG) injection period. In this work, we present a thorough methodology for computing the elastic response of the saturated rock for different fluid saturations using a site-specific petro-elastic model (PEM). The output from the PEM was combined with results from a fluid compositional model to compute the seismic velocities at times corresponding to each VSP survey. To produce a calibrated simulated response, the measured time-lapse seismic velocities were integrated into the numerical simulation model. The mismatches between the predicted and measured time-lapse velocities were minimized through an iterative calibration process using a trained artificial neural network proxy (ANN) coupled with a particle swarm optimizer (PSO). Our study indicates that the hybrid optimization workflow can effectively perform the history matching. With an accurate prediction of the hydrodynamic properties, the migration of CO 2 within the subsurface was modeled by predicting the spatial velocity distribution for a radius of 305 m around the injection well. The technology demonstrated and the expertise gained from this study can guide similar CO 2 -WAG projects.

58 GEOSCIENCES↗
DOE OSTI2026

Finite-element boundary-integral simulation of thin wires and inhomogeneous penetrable bodies in subsurface multilayered anisotropic media

With the prevailing presence of drilling wells near the subsurface in mature oil and gas fields, the application of electromagnetic methods can be particularly challenging where the electromagnetic field is affected by the steel casing. In the past decades, borehole-to-surface and crosswell electromagnetic methods have been utilized for monitoring of reservoir and underground CO 2 storage. This paper presents a unified finite-element boundary-integral (FEBI) method capable of simultaneously modeling the complex electromagnetic interactions between thin metallic wires (representing steel casings) with 3D trajectory and arbitrary 3D inhomogeneous penetrable bodies (such as CO 2 plumes or hydrocarbon reservoirs) within anisotropic multilayered subsurface environments. Unlike existing approaches that treat these components separately or require dense discretization, or are limited to vertical wells, our unified formulation preserves flexible electromagnetic coupling while delivering improved computational efficiency. Assuming the background formation is multilayered anisotropic media, the surface integral equation method is applied to model the thin wires and boundaries of the inhomogeneous bodies. Meanwhile, the finite element method is applied to model the volume of inhomogeneous bodies. Here, the performance of the proposed FEBI method is assessed through comparison with reference numerical results and its practical significance is demonstrated through CO 2 plume monitoring scenarios.

97 MATHEMATICS AND COMPUTING↗