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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Communications and control for electric power systems

The first section of the report describes the AbNET system, a hardware and software communications system designed for distribution automation (it can also find application in substation monitoring and control). The topology of the power system fixes the topology of the communications network, which can therefore be expected to include a larger number of branch points, tap points, and interconnections. These features make this communications network unlike any other. The network operating software has to solve the problem of communicating to all the nodes of a very complex network in as reliable a way as possible even if the network is damaged, and it has to do so with minimum transmission delays and at minimum cost. The design of the operating protocols is described within the framework of the seven-layer Open System Interconnection hierarchy of the International Standards Organization. Section 2 of the report describes the development and testing of a high voltage sensor based on an electro-optic polymer. The theory of operation is reviewed. Bulk fabrication of the polymer is discussed, as well as results of testing of the electro-optic coefficient of the material. Fabrication of a complete prototype sensor suitable for use in the range 1-20 kV is described. The electro-optic polymer is shown to be an important material for fiber optic sensing applications. Appendix A is theoretical support for this work. The third section of the report presents the application of an artificial neural network, Kohonen's self-organizing feature map, for the classification of power system states. This classifier maps vectors of an N-dimensional space to a 2-dimensional neural net in a nonlinear way preserving the topological order of the input vectors. These mappings are studied using a nonlinear power system model.

Kirkham, H.↗
DOE OSTI2023

Optimization under uncertainty of a hybrid waste tire and natural gas feedstock flexible polygeneration system using a decomposition algorithm

Market uncertainties motivate the development of flexible polygeneration systems that are able to adjust operating conditions to favor production of the most profitable product portfolio. However, this operational flexibility comes at the cost of higher capital expenditure. A scenario-based two-stage stochastic nonconvex Mixed-Integer Nonlinear Programming (MINLP) approach lends itself naturally to optimizing these trade-offs. This work studies the optimal design and operation under uncertainty of a hybrid feedstock flexible polygeneration system producing electricity, methanol, dimethyl ether, olefins or liquefied (synthetic) natural gas. A recently developed C++ based software framework (named GOSSIP) is used for modeling the optimization problem as well as its efficient solution using the Nonconvex Generalized Benders Decomposition (NGBD) algorithm. Two different cases are studied: The first uses estimates of the means and variances of the uncertain parameters from historical data, whereas the second assesses the impact of increased uncertain parameter volatility. The value of implementing flexible designs characterized by the value of the stochastic solution (VSS) is in the range of 260–405 M$ for a scale of approximately 893 MW of thermal input. Increased price volatility around the same mean results in higher expected net present value and VSS as operational flexibility allows for asymmetric exploitation of price peaks.

42 ENGINEERING↗
DOE OSTI2024

A Gaussian process autoregressive model capturing microstructure evolution paths in a Ni–Mo–Nb alloy

Additive manufacturing is increasingly being employed to produce components of complex geometries in structural alloys because of the expected energy savings associated with the near-net-shape capability and the ability to build in novel internal features that are not possible with many conventional manufacturing approaches. However, because of the extreme thermal conditions encountered, the non-equilibrium microstructures produced during powder bed-based additive manufacturing processes must be subjected to custom post-heat treatment processes to recover the target mechanical properties. Phase-field models and simulation techniques have matured to a state where the microstructure evolution paths, and the morphologies of the resulting precipitate phases can be predicted reasonably accurately, considering alloy-specific thermodynamic and kinetic aspects of the nucleation and growth processes. However, phase-field simulations are computationally intensive, which precludes the ability to apply the simulations directly to the length scale of the entire component. Therefore, it is highly desirable to develop low-computational-cost surrogate models that effectively capture the physics at the microstructural length scale, while facilitating the design of optimized processing conditions resulting in location-specific targeted microstructures at the component scale. The work presented here demonstrates the application of the materials knowledge system framework to develop a surrogate model that effectively captures the microstructural path during annealing of a Ni–Mo–Nb alloy containing different Mo and Nb compositions known to segregate during solidification under additive manufacturing conditions. Specifically, the surrogate model built in this work is based on a Gaussian process autoregressive model informed by statistical representation of simulated microstructures using two-point correlations and dimensionality reduction through principal component analysis. In conclusion, this surrogate model is shown to capture the bifurcation of the microstructural path during precipitation, which yields a microstructure dominated by the $\gamma^{\prime\prime}$ phase at high Nb concentrations and the $\delta$ phase at low Nb concentrations.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Visioning a Global Carbon Monitoring System That Can Quantify and Attribute Ocean Carbon Dioxide Removal: Where Are We Now and How Might We Get There?

As atmospheric greenhouse gas concentrations and the resulting social costs rise, it is increasingly important to conduct research on technical approaches to remove carbon dioxide from the atmosphere at the gigaton scale. One highly uncertain but perhaps plausible solution is ocean carbon dioxide (CO2) removal (CDR), which encompasses a suite of proposed techniques for increasing the net flux of CO2 from the atmosphere to the ocean. As reflected in a 2022 National Academy of Sciences report, interest in ocean CDR is rapidly growing, and new stakeholders from a wide range of fields want access to air-sea CO2 flux and ocean carbon information to understand the potential risks and benefits of ocean CDR. Moreover, there is an urgent need for research to develop a scientific basis to support these societal needs. At the same time, there is a growing need to vision a global carbon monitoring system that can quantify natural and anthropogenic perturbations in the air-sea CO2 flux to quantify and attribute the impacts of ocean CDR efforts on the ocean carbon sink. Here, we propose to present nascent efforts at the Ames Research Center to leverage NASA's unique remote sensing and computational capabilities and expertise in basic and applied Earth science to meet the needs of the ocean CDR stakeholder community as represented by the OceanVisions network. Specifically we aim to develop a global ocean CDR scenario explorer with two objectives: 1) to make quantitative estimates of the air-sea CO2 flux and its uncertainty more accessible to a wide range of users, and 2) to enable these diverse users to interactively explore the uncertain impacts on air-sea CO2 fluxes in a wide range of ocean CDR scenarios. The information would be provided to users via a public graphical user interface, and the results would be based on a new synthesis of scientific observations and knowledge in a global ocean mixed layer inverse model run on supercomputers. The proposed tool aims to fill a unique and valuable niche for users and the scientific community by balancing tradeoffs between user interests, scientific knowledge, and technical capabilities. We will conclude by visioning the potential implications for a global carbon monitoring system in a world with gigaton scale ocean CDR.

Global↗
DOE OSTI2025

A Comparative Study of Physics‐Informed and Data‐Driven Neural Networks for Compound Flood Simulation at River‐Ocean Interfaces: A Case Study of Hurricane Irene

Simulating compound flooding (CF) at the river-ocean interface within large-scale Earth System Models (ESMs) presents significant challenges due to complex interactions between river discharge, storm surge, and tides. This study assesses the comparative advantages of physics-informed and data-driven machine learning (ML) approaches for enhancing local ESM performance. We systematically compare data-driven neural network models (i.e., CNNs, U-Net, Long Short-Term Memory (LSTM), Gated Recurrent Unit), and physics-informed neural network (PINN) models, including vanilla PINN and a finite-difference-based PINN (FD-PINN). Specifically, FD-PINN is introduced to enhance computational efficiency, accelerating vanilla PINNs by ∼6.5 times while improving accuracy. To enhance data-driven model training, a new data-generation approach is developed to sample historical fluvial and coastal flood events, which ensures a robust data set for extreme event prediction. The models are evaluated using a realistic one-dimensional river domain extracted from an ESM's river mesh and the Hurricane Irene event as an independent test case. Results show that FD-PINN achieves accurate predictions with significantly reduced computational costs relative to vanilla PINNs. Among data-driven models, the best overall performance is achieved by a CNN-LSTM hybrid, which balances accuracy and efficiency. While a fully connected CNN (CNN-FC) provides the best accuracy, it incurs high computational cost. Architectures lacking strong temporal modeling tend to underperform on unseen events. These findings highlight the importance of sequence-aware designs for robust generalization. This study reveals the trade-offs between physics-informed and data-driven models and proposes an adaptive hybrid framework for integrating ML into ESMs to enhance local flood simulations.

Earth Systems Modeling↗
DOE OSTI2022

King City Asbestos Corporation (KCAC) Mine Carbon Mineralization Field Test (Final Combined Report)

The overall objective of the KCAC carbon mineralization project is to determine the most successful approaches to CO 2 mineralization of asbestos-bearing serpentinite rocks and mine waste at the closed KCAC asbestos mine. The objectives of Budget Period 1 (BP1) are to characterize the site including, mineralogical and geochemical variability in site materials, baseline conditions including CO 2 flux and local climate, and to establish the designs for the second, experimental phase of the project. As described in Section 3 of this report, all tasks outlined in the Statement of Project Objective (SOPO) have been completed or are on schedule to be completed by the end of BP1. As described in Section 4, all success criteria and milestones have been met or will be met by the end of BP1. We conclude that the findings of BP1 strongly support moving to the second phase of the project to investigate methods to increase the rate of CO 2 mineralization. CO 2 flux monitoring during BP1 established an estimated baseline uptake of CO 2 over the 142,193 m 2 KCAC mine site of 147 and 179 metric tons CO 2 /yr using dynamic closed chamber and eddy covariance monitoring methods, respectively. Mineralogical analysis shows that the loose surficial waste material contains pyroaurite and minor hydromagnesite, indicating past carbon mineralization. Sediment samples at depths below 60 cm contained ~3 wt% brucite and localized high brucite contents of ~24 wt% were measured at depth, indicating significant unreacted material at relatively shallow depths. Together, these results demonstrate that despite prolonged exposure to the atmosphere, reactive material is still present and accessible and is naturally taking up atmospheric CO 2 . However, these natural rates are still well below rates that can be achieved by applying practices that can accelerate the CO 2 mineralization reaction. Designs for the Field-Testing Phase (BP2) of the project have been established, incorporating the findings of BP1. Based on results to date we have selected two methods to accelerate the rate of CO 2 mineralization, which we refer to as the Tilling Method and the Greenhouse Method. We hypothesize that these methods can increase the CO 2 mineralization rate by up to 5 times greater than the natural background rate measured in BP1. An Initial Lifecyle Assessment (LCA) and techno-economic analysis (TEA) were conducted for these two methods. The LCA concluded that the baseline version of the Greenhouse and Tilling methods at commercial scale are expected to achieve a CDR efficiency of 97% and 71%, respectively (cumulative, over 30 years of operation). Incorporating the net CO 2 removal rates calculated in the LCA, the TEA found the levelized, 30-year costs of the baseline Greenhouse and Tilling methods to be $\$$95/t-CO 2 and $\$$119/t-CO 2 , respectively, and that costs could be brought to well below $\$$100/t-CO 2 for either method by scaling up the volume of rock utilized. An initial EH&S Risk Assessment, evaluating the potential EH&S risks of the proposed carbon mineralization methods at commercial scale, was completed by LLNL EH&S professionals for these two methods.

58 GEOSCIENCES↗
NASA NTRS1992

Superplastic forming of ceramic insulation

Superplasticity has been demonstrated in many fine-grained structural ceramics and ceramic composites, including yttria-stabilized tetragonal zirconia polycrystal (YTZP), alumina, and Al2O3-reinforced zirconia (Al2O3/YTZ) duplex composites and SiC-reinforced Si3N4. These superplastic ceramics obviously offer the potential benefit of forming net shape or near net shape parts. This could be particularly useful for forming complicated shapes that are difficult to achieve using conventional forming techniques, or require elaborate, subsequent machining. In the present study, we successfully demonstrated the following: (1) superplastic 3Y-TXP and 20 percent Al2O3/YTZ composite have for the first time been successfully deformed into hemispherical caps via a biaxial gas-pressure forming technique; (2) no experimental difficulty was encountered in applying the required gas pressures and temperatures to achieve the results, thus, it is certain that higher rates of deformation than those presented in this study will be possible by using the current test apparatus at higher temperatures and pressures; and (3) an analytical model incorporating material parameters, such as variations during forming in the strain rate sensitivity exponent and grain growth-induced strain hardening, is needed to model accurately and therefore precisely control the biaxial gas-pressure forming of superplastic ceramics. Based on the results of this study, we propose to fabricate zirconia insulation tubes by superplastic extrusion of zirconia polycrystal. This would not only reduce the cost, but also improve the reliability of the tube products.

Nieh, T. G.↗
DOE OSTI2022

Optimization of key energy and performance metrics for drug product manufacturing

During the development of pharmaceutical manufacturing processes, detailed systems-based analysis and optimization are required to control and regulate critical quality attributes within specific ranges, to maintain product performance. As discussions on carbon footprint, sustainability, and energy efficiency are gaining prominence, the development and utilization of these concepts in pharmaceutical manufacturing are seldom reported, which limits the potential of pharmaceutical industry in maximizing key energy and performance metrics. Based on an integrated modeling and techno-economic analysis framework previously developed by the authors, this study presents the development of a combined sensitivity analysis and optimization approach to minimize energy consumption while maintaining product quality and meeting operational constraints in a pharmaceutical process. The optimal input process conditions identified were validated against experiments and good agreement resulted between simulated and experimental data. Here, the results also allowed for a comparison of the capital and operational costs for batch and continuous manufacturing schemes under nominal and optimized conditions. Using the nominal batch operations as a basis, the optimized batch operation results in a 71.7% reduction of energy consumption, whereas the optimized continuous case results in an energy saving of 83.3%.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1992

Pulmonary and leg VO2 during submaximal exercise: implications for muscular efficiency

Insights into muscle energetics during exercise (e.g., muscular efficiency) are often inferred from measurements of pulmonary gas exchange. This procedure presupposes that changes of pulmonary O2 (VO2) associated with increases of external work reflect accurately the increased muscle VO2. The present investigation addressed this issue directly by making simultaneous determinations of pulmonary and leg VO2 over a range of work rates calculated to elicit 20-90% of maximum VO2 on the basis of prior incremental (25 or 30 W/min) cycle ergometry. VO2 for both legs was calculated as the product of twice one-leg blood flow (constant-infusion thermodilution) and arteriovenous O2 content difference across the leg. Measurements were made 3-5 min after each work rate imposition to avoid incorporation of the VO2 slow component above the lactate threshold. For all 17 subjects, the slope of pulmonary VO2 (9.9 +/- 0.2 ml O2.W-1.min-1) was not different (P greater than 0.05) from that for leg VO2 (9.2 +/- 0.6 ml O2.W-1.min-1). Estimation of "delta" efficiency (i.e., delta work accomplished divided by delta energy expended, calculated from slope of VO2 vs. work rate and a caloric equivalent for O2 of 4.985 cal/ml) using pulmonary VO2 measurements (29.1 +/- 0.6%) was likewise not significantly different (P greater than 0.05) from that made using leg VO2 measurements (33.7 +/- 2.4%). These data suggest that the net VO2 cost of metabolic "support" processes outside the exercising legs changes little over a relatively broad range of exercise intensities. Thus, under the conditions of this investigation, changes of VO2 measured from expired gas reflected closely those occurring within the exercising legs.

Non-NASA Center↗
NASA NTRS2008

A Review of Radiolysis Concerns for Water Shielding in Fission Surface Power Applications

This paper presents an overview of radiolysis concerns with regard to water shields for fission surface power. A review of the radiolysis process is presented and key parameters and trends are identified. From this understanding of the radiolytic decomposition of water, shield pressurization and corrosion are identified as the primary concerns. Existing experimental and modeling data addressing concerns are summarized. It was found that radiolysis of pure water in a closed volume results in minimal, if any net decomposition, and therefore reduces the potential for shield pressurization and corrosion. With the space program focus m emphasize more on permanent return to the Moon and eventually manned exploration of Mars, there has been a renewed look at fission power to meet the difficult technical & design challenges associated with this effort. This is due to the ability of fission power to provide a power rich environment that is insensitive to solar intensity and related aspects such as duration of night, dusty environments, and distance from the sun, etc. One critical aspect in the utilization of fission power for these applications of manned exploration is shielding. Although not typically considered for space applications, water shields have been identified as one potential option due to benefits in mass savings and reduced development cost and technical risk (Poston, 2006). However, the water shield option requires demonstration of its ability to meet key technical challenges including such things as adequate natural circulation for thermal management and capability for operational periods up to 8 years. Thermal management concerns have begun to be addressed and are not expected to be a problem (Pearson, 2007). One significant concern remaining is the ability to maintain the shield integrity through its operational lifetime. Shield integrity could be compromised through shield pressurization and corrosion resulting from the radiolytic decomposition of water.

Schoenfeld, Michael P.↗
NASA NTRS2018

Evaluation of Opportunistic Contact Graph Routing in Random Mobility Environments

Routing in networks where nodes move randomly is particularly challenging due their potentially unpredictable, and rapidly changing topology. Several routing algorithms have been presented in the literature to address the needs of such networks, most of them implementing variants of controlled network flooding in the hope of successful data delivery. In this note, we compare the results of previous routing algorithms with Opportunistic Contact Graph Routing (OCGR), an enhanced version of Contact Graph Routing (CGR) that is suitable for networks where contacts cannot always be scheduled ahead of time. To perform the benchmark, we simulate a network of nodes moving in a certain space according to the Random Waypoint Mobility Model, and then take measurements of bundle delivery probabilty and overhead ratio as metrics of performance and cost respectively. Through this exercise, we demonstrate that the performance of OCGR is highly dependent on the type of network under consideration (e.g. very sparse vs. densely connected) and the assumed mobility model.

Burleigh, Scott↗
NASA NTRS1995

Minimum fan turbine inlet temperature mode evaluation

Measured reductions in turbine temperature which resulted from the application of the F-15 performance seeking control (PSC) minimum fan turbine inlet temperature (FTIT) mode during the dual-engine test phase is presented as a function of net propulsive force and flight condition. Data were collected at altitudes of 30,000 and 45,000 feet at military and partial afterburning power settings. The FTIT reductions for the supersonic tests are less than at subsonic Mach numbers because of the increased modeling and control complexity. In addition, the propulsion system was designed to be optimized at the mid supersonic Mach number range. Subsonically at military power, FTIT reductions were above 70 R for either the left or right engines, and repeatable for the right engine. At partial afterburner and supersonic conditions, the level of FTIT reductions were at least 25 R and as much as 55 R. Considering that the turbine operates at or very near its temperature limit at these high power settings, these seemingly small temperature reductions may significantly lengthen the life of the turbine. In general, the minimum FTIT mode has performed well, demonstrating significant temperature reductions at military and partial afterburner power. Decreases of over 100 R at cruise flight conditions were identified. Temperature reductions of this magnitude could significantly extend turbine life and reduce replacement costs.

Orme, John S.↗
DOE OSTI2022

A novel approach to build algal consortia for sustainable biomass production

In the last decade, microalgae have reemerged as a feedstock for biofuels and a diverse suite of bioproducts. Yet, considerable challenges must be overcome before algal biofuels and bioproducts become technoeconomically viable. At present, single algal strain selected for particular phenotypic traits, such as maximum specific growth rate or lipid content, are commonly scaled for cultivation in open, outdoor raceway ponds due to the low capital costs of these systems. Although this monoculture approach may maximize the production of end products, monocultures are particularly susceptible to crashes associated with environmental and biological variability. An approach that has been proposed to generate more productive and stable microalgal crops is the use of eco-engineered communities, or consortia. Yet, attempts to construct productive consortia have not been consistently successful. We argue that failures stem from the lack of an eco-engineering approach to design species combinations. Here, we used an in silico method to build consortia before testing their performance against monocultures. Focusing on consortia of Nannochloropsis and Microchloropsis, we measured growth of strains along gradients of light, temperature, and salinity and used a functional dispersion approach to generate over 8000 functionally-diverse consortia combinations. We tested the 50 most functionally diverse consortia in a laboratory experiment and found that consortia overwhelmingly outperformed monocultures. Indeed, overyielding (OY) and a positive net biodiversity effect (NBE) was found respetively in 8%-86% and 88-92% of consortia combinations over the different experimental phases. To our knowledge, this is the first application of an in silico approach to design functionally diverse consortia before laboratory and field testing. Furthermore, our results highlight the importance of employing a functional diversity approach for consortia design.

09 BIOMASS FUELS↗
DOE OSTI2023

Natural Gas Community of the Future (Final Report)

Nicor Gas, a subsidiary of Southern Company Gas and its parent company Southern Company, is developing the concept of the Carbon-neutral, Affordable, Resilient, and Equitable Community ("CARE Community") to address the challenges of accessibility and affordability of grid-interactive efficient buildings in historically disadvantaged communities. The CARE Community is a new construction net-zero energy and carbon neutral residential neighborhood consisting of 50 homes with electricity and natural gas services in South Suburban Chicago, built as low-income affordable housing. The National Renewable Energy Laboratory (NREL) is assisting Southern Company to explore how energy efficiency, renewable technologies, and the reliability and resilience of natural gas can be combined and optimized in an islandable energy system as part of a broader effort to understand the role natural gas plays in future communities integrated with renewable energy and improved energy efficiency. The CARE Community will demonstrate how energy efficiency, distributed energy resources (DERs), and advanced controls can be combined with existing natural gas infrastructure to serve historically disadvantaged communities in a cold climate with low energy cost for affordable housing programs and enhanced resilience to withstand extreme weather. Homes will be a part of an islandable energy system, integrating multiple DER technologies such as solar panels, natural gas fuel cells, reciprocating natural gas engines, and battery storage. The CARE Community will provide a replicable template that affordable housing developers and energy companies can adopt throughout the United States. In this report, we present the design and modeling of the community and potential approaches for integrating DERs. We analyze and discuss annual simulations under normal operating conditions and week-long simulations under electric power grid outage conditions.

03 NATURAL GAS↗
NASA NTRS1999

LANDSAT 7: Early on-Orbit Results

As this article was being submitted in mid-March, 1999, Landsat 7 had been cleared for an official launch date of April, 15, 1999, approximately 4 - 5 weeks prior to the Portland ASPRS conference. Although it is hoped that the presentation in Portland will be the first public status report on the in-orbit performance of the Landsat 7 spacecraft and the ETM+ instrument, it is impossible to discuss "early on-orbit performance" prior to launch. Therefore, we have chosen to summarize the overarching salient features of the Landsat 7 program, and we will point to some web sites where additional information about the program can be found (e.g., http://geo.arc.nasa.gov/sge/landsat/landsat. html). At this time, the Landsat Project Science Office is pleased to report that the performance of the ETM+ instrument appears to be very good. In addition to excellent instrument performance, a robust data acquisition plan has been developed with the goal of acquiring a seasonally-refreshed archive of global land observations at the EROS Data Center annually. A ground processing system is being implemented at EROS that will be capable of capturing, processing and archiving 250 Landsat scenes per day, and delivering 100 scene products to users each day. The cost of a systematically-processed Level 1 product will be less than $600, and there will be no copyright protection on the data. The net result is that the use of remote sensing data in our daily lives is expected to grow dramatically. This growth is expected to benefit all facets of the land remote sensing community.

Williams, D. L.↗
NASA NTRS2011

Allowing for Horizontally Heterogeneous Clouds and Generalized Overlap in an Atmospheric GCM

While fully accounting for 3D effects in Global Climate Models (GCMs) appears not realistic at the present time for a variety of reasons such as computational cost and unavailability of 3D cloud structure in the models, incorporation in radiation schemes of subgrid cloud variability described by one-point statistics is now considered feasible and is being actively pursued. This development has gained momentum once it was demonstrated that CPU-intensive spectrally explicit Independent Column Approximation (lCA) can be substituted by stochastic Monte Carlo ICA (McICA) calculations where spectral integration is accomplished in a manner that produces relatively benign random noise. The McICA approach has been implemented in Goddard's GEOS-5 atmospheric GCM as part of the implementation of the RRTMG radiation package. GEOS-5 with McICA and RRTMG can handle horizontally variable clouds which can be set via a cloud generator to arbitrarily overlap within the full spectrum of maximum and random both in terms of cloud fraction and layer condensate distributions. In our presentation we will show radiative and other impacts of the combined horizontal and vertical cloud variability on multi-year simulations of an otherwise untuned GEOS-5 with fixed SSTs. Introducing cloud horizontal heterogeneity without changing the mean amounts of condensate reduces reflected solar and increases thermal radiation to space, but disproportionate changes may increase the radiative imbalance at TOA. The net radiation at TOA can be modulated by allowing the parameters of the generalized overlap and heterogeneity scheme to vary, a dependence whose behavior we will discuss. The sensitivity of the cloud radiative forcing to the parameters of cloud horizontal heterogeneity and comparisons of CERES-derived forcing will be shown.

Lee, D.↗
DOE OSTI2026

3D Deep Learning Joint Inversion of Active Seismic Full Waveform and Passive Seismic Traveltime Data for Reservoir Imaging and Uncertainty Quantification

Here, we present deep learning (DL) networks for three-dimensional (3D) joint inversion of active seismic full waveform and passive seismic traveltime data to image reservoirs and their properties and quantify imaging uncertainties. Active seismic full-waveform data can provide high-resolution monitoring images but are collected only intermittently because of their high acquisition cost. In contrast, passive seismic data can be gathered at relatively low cost between regular active surveys, although their imaging quality can be compromised by factors such as low signal-to-noise ratios and limited ray coverage of the target. Although these datasets are routinely acquired together at CO 2 storage sites, their combined inversion within a 3D DL framework has not been previously demonstrated. To our knowledge, this is the first study to address this gap, combining the strength of both data types. For efficient data storage and DL training with large 3D seismic datasets, we use a 3D data matrix in which a random number of passive seismic traveltime data are stored as parabolic envelopes using one-hot encoding and a 3D full-waveform data matrix in which multiple shot gathers are summed. Two network architectures are evaluated: a single-encoder U-Net for single-data type inversion and a dual-encoder U-Net for joint inversion of active and passive seismic data. We also evaluate the single-encoder U-Net for joint inversion by concatenating full-waveform data and traveltime data. We propose a systematic approach for selecting an optimal dropout rate that balances regularization during training and Monte Carlo dropout-based uncertainty quantification during prediction by examining the correlation coefficient between standard deviation and prediction error, along with the training misfit, across a range of dropout rates. 3D DL inversion experiments include five different network configurations, with evaluations under ideal, noisy and dropout-enabled conditions. Both model and data uncertainties are assessed, as well as their combined effects. Across all conditions, the networks consistently predict accurate CO 2 saturation models with low prediction errors, such as a structural similarity index of 0.993 and CO 2 difference of 1.1%. Uncertainty estimates show strong spatial correlation with prediction errors, confirming the effectiveness of the proposed dropout selection approach. The results demonstrate that our DL approach, utilizing compact data representations and appropriate uncertainty quantification, yields accurate subsurface images under various inversion conditions and provides valuable insights into the reliability of predictions.

Um, Evan Schankee [Lawrence Berkeley National Labo↗
DOE OSTI2021

Simulation of the supercritical CO 2 recompression Brayton power cycle with a high-temperature regenerator

The supercritical carbon dioxide (sCO 2 ) recompression Brayton cycle promises higher efficiency and lower capital cost than traditional steam Rankine power cycles. However, achieving high efficiency requires large, highly effective recuperators. Regenerators may be a low-cost alternative to printed circuit and micro-tube heat exchangers for recuperation in sCO 2 power cycles. Regenerators are a periodic heat exchanger in which thermal energy is extracted from the hot stream, stored in solid media, and then released to the cold stream at a later time. Fixed bed regenerators with valves to direct fluid are the preferred method for implementing regenerators in power cycles, but the inherently transient nature of these systems has not been characterized for this application. This study presents the simulation of a high-temperature regenerator within a 10 MWe sCO 2 recompression Brayton cycle. A transient, one-dimensional regenerator model presented in a previous study is used to simulate the regenerator. Dynamic heat exchanger models are also developed for the precooler, low-temperature recuperator, and primary heat exchanger, and the compressors and the turbine are modeled with off-design performance maps. We assess two regenerator-valve design options; one for fast switching, and one for reduced flow rate fluctuations. System simulation finds that both designs see significant fluctuations in turbomachinery flow rate, turbomachinery and system power, and regenerator discharge process outlet temperature. While designing the regenerator-valve subsystem for lower fluctuations is possible, the regenerator cold discharge temperature and net power still fluctuate by ±77.6°C and 6%, respectively. Increasing buffer volume is not effective at sufficiently reducing these fluctuations, but adding a packed bed in between the regenerator and the primary heat exchanger can reduce regenerator discharge process outlet temperature fluctuations to 6.4°C. Further reductions could be possible by increasing the size of this packed bed.

42 ENGINEERING↗