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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Structured Neural Network Modeling for Developing Digital Twins Models of Hydropower Generation Units

Dynamic modeling is a key part in the development of digital twin (DT) for dynamic systems. This is true for hydropower systems, where whole system modeling including penstock, turbine and generators, etc is important in realizing actuate modeling for the real systems. On the other hand, in response to the large variations of the power demand due to increased penetration of renewables such as wind and solar, hydropower systems are now required to operate in a large power generation range. This situation triggers the nonlinear characteristics of the generation unit with respect to its models. As such, it is imperative to use data driven modeling such as neural networks to learn the nonlinear dynamics of the hydropower generation unit. To achieve this objective, this study constructs a modeling and learning algorithm integrated with multiple structured neural network models for the modeling of turbine shaft speed, penstock pressure, and generator power output based on the generator power control setpoint, field current, and field voltage. In addition, the study uses the hydropower data from Tacoma Public Utilities to train and validate the proposed neural network algorithm. The results have shown that this structured neural network modeling approach can learn the system dynamics effectively by using the real-time data collected from the hydropower system with the desired modeling results.

Wang, Hong↗
DOE OSTI2026

Observed Temperature and Moisture Advection Characteristics in the Southern Great Plains

Until recently, advection profiles in the planetary boundary layer have been difficult to quantify from observations. As a result, not much is known about its basic characteristics, like magnitude and diurnal cycles, or how these differ as a function of large-scale environments. Here, to provide insight into advective characteristics, a Green’s Theorem–based method for calculating profiles of advection in the lowest 3 km from an array of ground-based thermodynamic and kinematic profiling instruments has been applied to 2 years of observations from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observing site. Since advection largely depends on synoptic-scale forcing, a self-organizing map (SOM) was used to classify days based on mean sea level pressure analyses; from that, the diurnal evolution of vertical profiles of advection for different synoptic environments was quantified. The overall mean magnitude of the potential temperature advection is approximately ±3 K h −1 , while the moisture advection is approximately ±1.5 g kg −1 h −1 , with substantial variability in the sign and magnitude of the advective tendencies at different heights and throughout the diurnal cycle. Advection magnitude is strongly connected to the strength of synoptic-scale forcing, which varies depending on the time of year. Variability in advection is larger for potential temperature than it is for moisture, and strongly forced environments, like midlatitude cyclones, feature greater variability in the advection magnitude than weakly forced or quiescent environments.

advection↗
DOE OSTI2024

Sensitivity of thermodynamic profiles retrieved from ground-based microwave and infrared observations to additional input data from active remote sensing instruments and numerical weather prediction models

Accurate and continuous estimates of the thermodynamic structure of the lower atmosphere are highly beneficial to meteorological process understanding and its applications, such as weather forecasting. In this study, the Tropospheric Remotely Observed Profiling via Optimal Estimation (TROPoe) physical retrieval is used to retrieve temperature and humidity profiles from various combinations of input data collected by passive and active remote sensing instruments, in situ surface platforms, and numerical weather prediction models. Among the employed instruments are microwave radiometers (MWRs), infrared spectrometers (IRSs), radio acoustic sounding systems (RASSs), ceilometers, and surface sensors. TROPoe uses brightness temperatures and/or radiances from MWRs and IRSs, as well as other observational inputs (virtual temperature from the RASS, cloud-base height from the ceilometer, pressure, temperature, and humidity from the surface sensors) in a physical iterative retrieval approach. This starts from a climatologically reasonable profile of temperature and water vapor, with the radiative transfer model iteratively adjusting the assumed temperature and humidity profiles until the derived brightness temperatures and radiances match those observed by the MWR and/or IRS instruments within a specified uncertainty, as well as within the uncertainties of the other observations, if used as input. In this study, due to the uniqueness of the dataset that includes all the above-mentioned sensors, TROPoe is tested with different observational input combinations, some of which also include information higher than 4 km above ground level (a.g.l.) from the operational Rapid Refresh numerical weather prediction model. These temperature and humidity retrievals are assessed against independent collocated radiosonde profiles under non-cloudy conditions to assess the sensitivity of the TROPoe retrievals to different input combinations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Chemically Amplified, Dry-Develop Poly(aldehyde) Photoresist

The catalytic decomposition of poly(phthalaldehyde) with a photoacid generator can be used as dry-develop photoresist, where the exposed film depolymerizes into small molecules to allow the development of features via controlled vaporization. Higher temperatures enabled shorter dry-development times, but also promoted faster photoacid diffusion that compromised pattern fidelity. Trihexylamine was used as a base quencher to counteract acid diffusion in a phthalaldehyde-propanal co-polymer photoresist. The propanal co-monomer in the polymer improves the vaporization rate because it has a higher vapor pressure than phthalaldehyde. Addition of the base quencher was found to improve the contrast, pattern fidelity, and ease-of-handling of the dry-develop resist in a direct-write UV lithography tool. The dry-development of 4 μ m features was achieved with no appreciable residue. For large area features, a spatially variable exposure method was used to direct the residue away from the exposed area. The gradient exposure method was used to produce 100 μ m features. Plasma etching after dry-development was also used to achieve residue-free dry-developed patterns. These results show the benefits of incorporating base additives into a dry-develop depolymerizable resist system and highlight the need for addressing residue formation.

Materials Science↗
DOE OSTI2024

Lightweight single-phase Al-based complex concentrated alloy with high specific strength

Developing light yet strong aluminum (Al)-based alloys has been attracting unremitting efforts due to the soaring demand for energy-efficient structural materials. However, this endeavor is impeded by the limited solubility of other lighter components in Al. Here, we propose to surmount this challenge by converting multiple brittle phases into a ductile solid solution in Al-based complex concentrated alloys (CCA) by applying high pressure and temperature. We successfully develop a face-centered cubic single-phase Al-based CCA, Al 55 Mg 35 Li 5 Zn 5 , with a low density of 2.40 g/cm 3 and a high specific yield strength of 344×10 3 N·m/kg (typically ~ 200×10 3 N·m/kg in conventional Al-based alloys). Our analysis reveals that formation of the single-phase CCA can be attributed to the decreased difference in atomic size and electronegativity between the solute elements and Al under high pressure, as well as the synergistic high entropy effect caused by high temperature and high pressure. The increase in strength originates mainly from high solid solution and nanoscale chemical fluctuations. Our findings could offer a viable route to explore lightweight single-phase CCAs in a vast composition-temperature-pressure space with enhanced mechanical properties.

42 ENGINEERING↗
DOE OSTI2024

Precise Motion Control of Hybrid Hydraulic Electric Architecture (HHEA)

Off-highway heavy-duty vehicles have been long-standing users of hydraulic systems for power transmission and control. However, traditional hydraulic systems suffer from significant energy losses which lead to increased operating costs and a larger carbon footprint due to higher CO2 emissions. Improving the efficiency of these mobile machines is crucial not only for reducing their environmental impact but also for saving billions of dollars in operating costs. Currently, the state-of-the-art Load Sensing Architecture uses throttling valves for control, which significantly reduces its efficiency and does not recuperate energy from over-running loads. Researchers have developed several architectures such as Common Pressure Rail systems, Displacement Control, STEAM, and Electrohydraulic Architecture to improve the efficiency of off-road mobile machines. However, each of these architectures has its drawbacks. To increase system efficiency and take advantage of electrification benefits, our research group has developed a novel Hybrid Hydraulic-Electric Architecture (HHEA). The HHEA can significantly improve efficiency, decrease the size of electrical components, and maintain control performance. This new architecture has the potential to revolutionize the off-highway mobile machine industry and lead to a more sustainable future. The HHEA uses a set of common pressure rails to provide the majority of power to the actuators via power-dense hydraulics and uses electric motors for precise control and power modulation. In the context of off-road mobile machines, energy savings are undoubtedly important but it is equally important to consider the machines’ ability to perform tasks with precision and accuracy according to given commands. Therefore, precise motion control is of utmost importance to maintain the utility of Hybrid Hydraulic-Electric Architecture (HHEA). The HHEA presents a unique challenge to motion control due to the discrete pressure changes that occur when the system switches between selected pressure rails. These changes are made to minimize system inefficiencies or to keep the system within the torque capability of the electric motor. Hence, it is important to solve the motion control challenges for HHEA. This thesis aims at developing an effective motion control strategy for HHEA. The dissertation presents a two-tiered control strategy for HHEA, comprising a high-level and a low-level controller. The primary responsibility of the high- level controller is to optimize energy efficiency by making informed pressure rail selections. On the other hand, the low-level controller is focused on achieving precise motion control of the HHEA, which is crucial for realizing the desired reference trajectories. To achieve this, the low-level controller utilizes a passivity-based backstepping integral controller as the nominal control, which handles the motion control between two pressure rail switches. Additionally, a separate least norm controller is utilized as a transition controller to manage motion control during pressure rail transitions. The effectiveness of the combined control strategy is demonstrated through experiments conducted on two hardware-in-the-loop testbeds. Furthermore, the HHEA is installed on the boom and stick actuators of a backhoe arm to build a Human-in-the-Loop system that a human operator can control. A real-time rail switching algorithm is developed to determine pressure rail switching based on present duty cycle information from the operator. Modifications have been made to the human-machine interface to achieve more intuitive control. Modifications include performing control in the task-oriented coordinates, incorporating pressure feedback to enhance control with physical interaction, and using velocity field control to simplify multi-degree-of-freedom tasks and to enable novice operators to perform them with reduced risk, improved efficiency, and productivity. The research in this dissertation makes significant contributions to the field of off-road mobile machine control, providing a novel and effective control strategy for the HHEA, and demonstrating the potential for simplified machine operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Efficiently predicting pressure-composition-temperature diagrams to discover low-stability metal hydrides

Quantitatively accurate computational predictions of metal hydride thermodynamics are challenging but critical for alloy performance optimization across a multitude of technological domains, including hydrogen storage, compression, purification, and getters. Recent machine learning approaches have demonstrated great success in this area, but can potentially suffer from several shortcomings since they rely on imbalanced experimental training data and can have poor out-of-distribution (ood) test performance. Here, in this study, we circumvent such pitfalls by developing a computationally efficient, first principles-based workflow for direct prediction of metal hydride phase equilibrium, i.e., the pressure-composition-temperature (PCT) diagram. We then demonstrate its utility on predicting low stability hydrides derived from compositionally complex C14 Laves phase AB2 alloys. Specifically, we computationally predict and then experimentally validate an AB 2 alloy series (z < 0.6 for Ti 2−z Zr z CrMnFeNi) with ideal hydriding thermodynamics for a two-stage metal hydride-based compressor for pressurizing boil off from liquefied hydrogen. Importantly, this study lays the groundwork for accurate and efficient discovery/optimization of ood, low-stability hydrides for which purely data-driven approaches lack sufficient accuracy.

08 HYDROGEN↗
DOE OSTI2025

DME-to-Propane Mixture Effects on a Light Duty Compression Ignition Engine

Fuels that can be produced in a sustainable manner are of high interest because they can provide an essential step toward net zero emissions vehicles. This study examines the combustion of two such fuels, Dimethyl Ether (DME) and propane, in a compression ignition, 4-cylinder, 2.2L engine running with mixtures of DME-to-Propane ranging of 100%-0%, 85%-15%, 75%-25%, and 65%-35% by weight. Testing was conducted at 2000rpm - 100Nm, an important representative point in the FTP certification cycle. For each fuel mixture, conditions tested include sweeps of boost, EGR and injection pressure. Here, tests are mainly conducted at a constant combustion timing with CA10 of -1 deg with respect to TDC, with an engine controller combustion feedback system based on in-cylinder sampling of pressure. Trends of NOx, HC, and CO are similar for the range of DME-to-propane, from 100%-0% to 75%-25%. Boost and injection pressures had the most notable impact on the heat release traces. Higher boost, from stoichiometric to lean resulted in approximately a 3-5% increase on cycle efficiency. Fuel injection pressures resulted in about 1% gain per 200bar. Results also illustrated that EGR is effective in reducing NOx but causes notable degradation of cycle efficiency. The emissions for DME-propane mixtures with 65%-35% had a different trend, with CO and HC exceeding the runs with lower propane content by 2 to 3-fold. As propane content increases, the pressure rise rates become higher, and with 65%-35% mixtures, rates easily exceed 12bar/deg. The increased rise rates correlate with early injection timings but the rates can be reduced, with higher boost and lower injection pressures. The result of the approach, however, leads to lower thermal efficiencies, decreasing efficiency by over 5% between neat DME and the highest propane ratios.

Combustion and combustion processes↗
DOE OSTI2024

Flame kinetics at scramjet-engine-relevant conditions: Role of prompt dissociation of weakly-bound radicals

Combustion in high-speed ram-based propulsion engines occurs under distinct thermodynamic conditions of high reactant temperatures (greater than 1000 K) and relatively low pressures (<5 atm). There is a lack of fundamental flame measurements at such conditions that result in adiabatic flame temperatures (T ad ) exceeding 2500 K. In this work, we have measured laminar flame speeds of oxygen-enriched CH 4 /oxidizer mixtures at sub-atmospheric conditions to probe kinetics at high T ad using the isobaric spherically expanding flame approach. Simulations with recent kinetic models revealed increasing differences between data and model predictions with increasing T ad , reaching up to 25 %. Kinetic analyses reveal that at the thermodynamic conditions in these O 2 -enriched flames, i.e., lower pressures and higher T ad , the effects of HCO prompt dissociation are accentuated. In addition to HCO, the prompt dissociations of CH 2 OH and C 2 H 5 are also considered. Here, the prompt dissociations of all three radicals were evaluated and their effects considered in flame speed simulations. Reaction path analysis for the present flames revealed that approximately half of the reaction flux for HCO formation undergoes prompt dissociation to H + CO. Furthermore, these analyses also revealed that the pathways and sensitive reactions are similar between oxygen-enriched fuel/oxidizer mixtures and preheated fuel/air mixtures, if both have similar T ad . Thus, flames of oxygen-enriched mixtures could be a surrogate to probe the flame chemistry of highly preheated mixtures at relatively low pressures that are often encountered in ram-based propulsion engine combustors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

A mathematical design framework for membrane pre-concentration in energy-efficient recovery of fermentation products

Due to the dilute nature of products manufactured via fermentation and cell-free bioprocessing, dewatering is a common unit operation in downstream processing (DSP) for bioproduct recovery, but it is typically energy intensive. To improve DSP energy efficiency for bio-based small molecules, integrating high-pressure membrane pre-concentration is a promising process option. However, this approach is typically constrained by a tradeoff between concentration factor (CF) and product recovery (PR), namely increasing the CF typically results in greater product loss, and vice versa. Here we developed a model that enables process design guidelines to: (i) identify scenarios in which the additional energy consumption and product loss from membrane pre-concentration are justified for use in DSP, and (ii) determine the optimal CF that minimizes process specific energy consumption. We compared the energy consumption of high-pressure membrane-integrated processes to evaporation-only processes and applied the model to an experimental case study for the separation and purification of butyric acid from Clostridium tyrobutyricum fermentation using an in situ product recovery (ISPR) process. The model estimated that integrating a tangential-flow reverse osmosis (RO) pre-concentration unit could reduce process energy consumption up to 45%. The use of advanced membrane pre-concentration technologies, such as negative rejection membranes and organic solvent reverse osmosis (OSRO), have the potential to further reduce the overall process specific energy consumption up to 96%, projected based on modeling. Overall, membrane pre-concentration, especially when strategically integrated prior to an evaporation step with optimized process conditions, holds significant potential for improving DSP energy efficiency, particularly in applications requiring substantial solvent removal for product recovery from dilute mixtures.

09 BIOMASS FUELS↗
DOE OSTI2026

Pressurized Gas-Driven Elemental Redistribution Enables Ultrastable PtNi Catalysts for Heavy-Duty Vehicles

Gas-driven element redistribution, characterized by the preferential enrichment of one element at the surface relative to the bulk, is frequently observed in multicomponent alloys. Using L1 0 -ordered PtNi as a model system, we reveal that gas pressure plays a critical role in governing adsorption-driven surface composition during annealing in reducing gases: low pressure favors Pt surface segregation, while high pressure facilitates Ni surface enrichment. In this study, we developed a high-pressure nitriding (HPN) strategy that modulates the surface structure and composition of PtNi catalysts. The resulting HPN-PtNi exhibits enhanced performance and durability in membrane electrode assemblies for heavy-duty fuel cell applications, maintaining a high current density of 1.19 A cm −2 at 0.7 V after 90,000 voltage cycles. Through a combination of experimental and theoretical analyses, we reveal that the HPN process forms additional stabilizing Ni−N bonds and induces elemental redistribution with Ni surface enrichment and a Ni-deficient Pt subsurface. These modifications alter the atomic coordination environment of the ordered PtNi phase. This work presents a generalizable strategy to design robust and high-performing Pt-based catalysts by controlling gas-pressure-driven elemental redistribution and dopant incorporation.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Dynamic modeling studies of basin-scale pressure interference and CO 2 plume evolution in multi-well geologic CO 2 storage

This research employs numerical modeling to analyze how CO 2 plumes and pressure fronts evolve when CO 2 is injected into a single storage formation from multiple projects located in proximity. Here, this analysis also evaluates the extent to which injection well spacing alleviates pressure buildup in the absence of active pressure management tactics. The simulation approach was based on a single, homogenous saline aquifer in which CO 2 injection occurs under a one-injector baseline case and several multi-well cases where well spacing varies. Analysis results show that the extent of pressure buildup is in the range of tens or a few hundreds of kilometers and contingent upon the defining pressure buildup demarcating the front edge. For the geological setting evaluated in this paper, our analysis suggests that without active basin pressure management strategies, commercial-scale projects would likely need to be sited far apart to avoid pressure interference from one another. Analysis results show the radius of CO 2 plume varies approximately from 2 to 3 km from injection wells (each injecting 1 Mt/year for 30 years) depending on cases and modeling parameters assumed. Given the pressure interference, this paper thus draws attention to the importance of greater coordination among storage operators and regulatory stakeholders. Because this analysis assumes a very specific geologic setting, this exploratory analysis bears further investigations across other geologic scenarios.

42 ENGINEERING↗
DOE OSTI2024

Development of a high-temperature Inconel 625 heat exchanger by model design and binder jetting additive manufacturing

A nickel-based Inconel 625 superalloy heat exchanger for high-temperature applications was developed via binder jetting additive manufacturing. The material properties were characterized first on printed and sintered parts. Two sintering temperatures were used to investigate the effects of the temperature on densification and microstructure. For channel geometry design, the heat transfer capabilities of the heat exchanger were optimized for the cross-section geometry of fluid flow channels in a counterflow configuration, and a stress analysis was conducted to investigate the effects of channel geometry. After headers were incorporated into the heat exchanger as a one-piece component, a prototype was printed. A complete depowdering was achieved via compressed air blowing, and sintering was performed with the developed profile. Ultimately, a one-piece heat exchanger with a nearly full density was obtained. Heat transfer tests were performed on this unit, and the results were compared with those from the simulations. In this study, systematic processes were developed for an additively manufactured Inconel-based heat exchanger for high-pressure, high-temperature heat transfer applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Bicarbonate-Carbonate Selectivity through Nanofiltration for Direct Air Capture of Carbon Dioxide

Direct air capture (DAC) of carbon dioxide is one approach among many proposed that is capable of offsetting hard-to-avoid emissions. In previous work, we developed the alkalinity concentration swing (ACS) method, which is driven through concentrating an alkaline solution that has been loaded with atmospheric CO 2 by desalination technologies, such as reverse osmosis or capacitive deionization. Though the ACS is promising in terms of energy usage and implementation, its absorption rate and water requirements are infeasible for a large-scale DAC process. Here, we propose an improvement on the ACS, the bicarbonate-enriched alkalinity concentration swing (BE-ACS), which selects bicarbonate ions from a stream of aqueous alkaline solution that has absorbed atmospheric CO 2 . The bicarbonate-rich stream is then concentrated, which greatly increases its CO 2 partial pressure, and then CO 2 is extracted from solution. We experimentally investigate the use of pressure-driven nanofiltration (NF) membrane-based separation to select bicarbonate ions over carbonate ions. We screen commercial membranes and select one high-performance membrane for detailed studies, quantifying its bicarbonate-carbonate selectivity factor and bicarbonate-passage factor. Feed pH, the combined concentration of aqueous CO 2 , bicarbonate, and carbonate species (or dissolved inorganic carbon), alkalinity, and permeation flux are systematically varied to study NF separation properties. We find that the selectivity factor, which exceeds 30 times in certain regimes, increases with higher feed pH and higher alkalinity. Lastly, the performance metrics of the selected NF membrane are input into a theoretical BE-ACS cycle analysis, and the required energy input and cycle capacity output are evaluated. Ideal cycle energy is found to be as low as around 250 kJ/mol, with opportunities identified for further decreases through process engineering and forward osmosis energy recovery.

animal feed↗
DOE OSTI2024

Iodine solid sorbent design: a literature review of the critical criteria for consideration

Designing sorbents for iodine capture in different conditions requires selection and optimization of a large and diverse range of variables. These variables fall into general categories (or features) of sorbent activity, sorbent stability, and the fate of the loaded material in terms of the disposal (waste form) options available. To illustrate, silver-loaded, high-porosity sorbents make for maximized iodine capture and less pressure drop in a column-based sorption system approach, however, this high porosity can lead to less mechanically stable sorbents. Additionally, waste forms containing silver must also be compliant with additional criteria for hazardous waste disposal. Thus, all these aspects must be considered simultaneously when selecting a sorbent for utilization under specific conditions. Information is given for different types of sorbent design considerations for different operating conditions and some emphasis is also given on promising alternatives for silver as the active (chemisorption-based) getter metal. Discussion is given around demonstrated options for waste forms for different metal-iodide compounds.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Polytype selection in the antisolvent-free crystallization of formamidinium lead iodide using alkylammonium chlorides

This work presents a systematic study of how the size of the C 0 –C 4 alkylammonium chloride additive directs the crystallization pathway in antisolvent-free FAPbI 3 films. We find that larger cations promote the intermediate formation of hexagonal polytypes, correlating with enhanced film crystallinity. Understanding the nucleation, crystallization, and phase transition mechanisms in perovskite thin films produced without antisolvent quenching is crucial for improving phase stability and optoelectronic performance at scale. By means of in situ grazing incidence wide-angle X-ray scattering experiments, we show that the nature of alkylammonium chloride (RACl) additives significantly influences the crystallization dynamics and temperature-dependent stability of formamidinium lead iodide (FAPbI 3 ) perovskite films formed using antisolvent-free processes. The in situ experiments reveal that the effective radius of the RA + cation and the vapor pressure of the RA 0 conjugate base are critical factors affecting the crystallization pathway and film morphology. C 2 –C 3 additives with moderate chain lengths may strike a balance between promoting the early crystallization of the cubic 3C phase while suppressing unwanted phases. This balance promotes the formation of highly crystalline cubic perovskite phase with well-oriented structure and better optoelectronic properties. These findings provide guidance regarding the design of additives to crystallize more stable and efficient perovskite films for optoelectronic applications.

Marchezi, Paulo E↗
DOE OSTI2025

Towards more accurate sound field verification using directional acoustic filtering

Attributing omnidirectional sound levels to a specific source in the ocean can be challenging when there are multiple competing sources of sound such as boats, or biological activity. Here, we present a method to directionally filter acoustic measurements based on vector measurements of acoustic pressure and particle velocity. The directional discrimination is applied to estimate sound energy from two marine energy sources: sound generated during the decommissioning of an oil platform and those from an operating tidal energy converter. The application of a directional mask leads to distinctly different spectra and some differences in energy, relative to the unmasked scenarios.

Barosin, Emily (ORCID:0009000765495939)↗
DOE OSTI2025

Real-Time Bayesian Inference at Extreme Scale: A Digital Twin for Tsunami Early Warning Applied to the Cascadia Subduction Zone

We present a Bayesian inversion-based digital twin that employs acoustic pressure data from seafloor sensors, along with 3D coupled acoustic–gravity wave equations, to infer earthquake-induced spatiotemporal seafloor motion in real time and forecast tsunami propagation toward coastlines for early warning with quantified uncertainties. Our target is the Cascadia subduction zone, with one billion parameters. Computing the posterior mean alone would require 50 years on a 512 GPU machine. Instead, exploiting the shift invariance of the parameter-to-observable map and devising novel parallel algorithms, we induce a fast offline–online decomposition. The offline component requires just one adjoint wave propagation per sensor; using MFEM, we scale this part of the computation to the full El Capitan system (43,520 GPUs) with 92% weak parallel efficiency. Moreover, given real-time data, the online component exactly solves the Bayesian inverse and forecasting problems in 0.2 seconds on a modest GPU system, a ten-billion-fold speedup.

97 MATHEMATICS AND COMPUTING↗