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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Catalytic monoterpenes conversion over Pd and zeolite to sustainable aviation fuel

Waste terpenes from wood drying are typically processed using a Regenerative Thermal Oxidizer (RTO) and converted to CO2 which is then released to the atmosphere. A novel alternative to this approach is to capture these terpenes using Fluidized Bed Concentrator (FBC) technology developed by CaptisAire which provides a useful waste carbon feedstock for subsequent upgrading. We have developed a catalytic approach where these waste terpenes (comprised of pinenes, limonene, and camphene), are converted to aromatic, and cycloalkane hydrocarbons suitable for use as a Sustainable Aviation Fuel (SAF) blendstock without the need for additional hydrogen. This provides a renewable source for aviation fuel aromatics and increases the potential blend content of renewably sourced alkanes from Hydroprocessed Esters and Fatty Acids (HEFA) and Alcohol to Jet (ATJ) processes. Terpenes were converted in a batch reactor at 260 °C and 120 psi N2 using a combination of Pd/C and H-BEA zeolite. Experimental results infer the role of the zeolite Brønsted acid to facilitate isomerization of pinenes and camphene to limonene, which then undergoes subsequent dehydro-aromatization to p-cymene using Pd/C. Hydrogen release from the dehydro-aromatization process, enables inert conversion of monoterpenes to cycloalkanes without additional hydrogen. Monoterpenes conversion to C10 aromatics (60%) and C10 cycloalkanes (40%) in an inert environment, provides a viable route for SAF blendstock sourced directly from captured waste terpenes. Transition to commercial off-the-shelf catalysts, facilitates scale-up of the terpene conversion process and improves commercial viability. We subsequently created hydrocarbon blends using HEFA or ATJ and converted terpenes, providing a 100% SAF blend with potential to replace traditional Jet-A.

Lawal, Ajibola [ORNL] (ORCID:0000000187266570)↗
DOE OSTI2026

SOLPS-ITER modeling of a dedicated divertor for negative triangularity operation on DIII-D

The design of a new dedicated divertor for negative triangularity (NT) operation on DIII-D with neutral baffles and pumping is informed by SOLPS-ITER transport modeling. This dedicated NT divertor is the latest step in a progression of NT shapes with various divertor characteristics explored on DIII-D, including NT shapes at reduced triangularity and a campaign with stronger shaping that included new armored components on the outboard side. SOLPS simulations played a key role in these divertor designs. Interpretive simulations, using cross-field diffusivities constrained by experimental data in the NT Shelf shape were used to inform the design of the 2023 armor campaign components. A similar procedure used armor campaign data to predict conditions for the dedicated NT divertor. The predictive simulations were used to assess the divertor fluxes, detachment threshold, pumped flux, and neutral leakage. For the dedicated NT divertor, SOLPS simulations and two-point-modeling were used to show the relative impact of magnetic topology (mainly longer connection length) and divertor closure on the divertor conditions relative to the armor campaign. It is predicted that the dedicated NT divertor reaches detachment (measured by target ion flux rollover) at a lower upstream density (≈(1.75−−2.4)×1⁢019m−3) as compared to the armor campaign shape. For the preliminary design geometry, divertor closure reduces the neutral leakage by ≈10%. Parametric optimization indicating further ≈20%–60% improvement in the leakage flux and recycled flux crossing the pump entrance is possible for relatively minor changes to the divertor and baffle layout.

Lore, Jeremy [ORNL] (ORCID:000000029192465X)↗
DOE OSTI2025

Alternative mixed integer linear programming optimization for joint job scheduling and data allocation in grid computing

This paper presents a novel approach to the joint optimization of job scheduling and data allocation in grid computing environments. We formulate this joint optimization problem as a mixed integer quadratically constrained program. To tackle the nonlinearity in the constraint, we alternatively fix a subset of decision variables and optimize the remaining ones via Mixed Integer Linear Programming (MILP). We solve the MILP problem at each iteration via an off-the-shelf MILP solver. Our experimental results show that our method significantly outperforms existing heuristic methods, employing either independent optimization or joint optimization strategies. We have also verified the generalization ability of our method over grid environments with various sizes and its high robustness to the algorithm setting.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Organic matter sulfurization and organic carbon burial in the Mesoproterozoic

Throughout the Proterozoic Era, sedimentary organic carbon burial helped set the pace of global oxygenation and acted as a major modulator of atmospheric CO 2 and climate. Although Proterozoic rocks generally contain low concentrations of organic matter (OM), there are key exceptions to this rule, including the relatively OM-rich Arctic Bay shales from Baffin Island, Canada (Bylot Supergroup, Borden Basin, ~1.05 Ga). The mechanisms driving elevated OM concentrations in these and other Proterozoic shales remain poorly understood. In the Mesozoic and Cenozoic, organic matter sulfurization can be a major driver of enhanced OM burial across a range of redox conditions comparable to those inferred for many Proterozoic environments. Therefore, in this study, we evaluate the role of sulfurization in driving OM preservation in the Mesoproterozoic Borden Basin and discuss its relevance to Proterozoic systems in general. We present the first evidence for syngenetic-to-early-diagenetic OM sulfurization in a Proterozoic basin, which begins to fill a several-billion-year gap in our record of organic S across Earth history. We find that OM sulfurization was particularly extensive in shales from a relatively shallow-water section (Alpha River) but less extensive in shales deposited in deeper water (Shale Valley), which is consistent with models that infer sulfidic ‘wedges’ or O 2 -minimum-zone-type structures on shelf margins at least intermittently at this time. At the shallower site, organic S and pyrite are similarly 34 S-depleted and thus likely formed at roughly the same time near the sediment–water interface under conditions previously interpreted to have been ferruginous to intermittently sulfidic. In contrast, at the deeper-water site, large S-isotope differences between pyrite and organic S along with low apparent OM sulfurization intensities indicate that pyrite formation was favored over OM sulfurization during early sedimentation under variable but primarily ferruginous conditions. Although Mesoproterozoic biomass can be substantially sulfurized, indicators of sulfurization intensity are not correlated with OM concentrations, and therefore sulfurization does not appear to have been the primary driver of enhanced OM concentrations in Arctic Bay Formation shales. The link between sulfurization and total OM preservation may have been modulated during the deposition of Arctic Bay Formation shales by differences in iron availability, nutrient cycling, and particle dynamics in the Mesoproterozoic.

58 GEOSCIENCES↗
DOE OSTI2020

Framework for Large-scale Implementation of Wholesale-Retail Transactive Control Mechanism

Transactive energy is a control technique that uses market mechanisms to achieve desired control objectives. Several simulation studies and field demonstrations were carried out in recent years, but all focused on small scale systems and purpose-built simplified models which are not always capable of pointing out all the advantages and shortcomings of transac- tive energy methods. This work describes a co-simulation framework built on a hierarchical control architecture that allows for conducting studies of the impacts of a very large-scale deployment of transactive energy. The hierarchical transactive control architecture adopted in this work helps with alleviating computation and communication burden to facilitate a more effective large scale real-time market operation among device level resources and the system level operators. The co-simulation framework is evaluated an integrated power sys- tem model of unprecedented scale composed of the Western Electricity Coordination Council (WECC) transmission system with tens of thousands of distribution systems deployed with flexible device-level distributed energy resources (DERs) using off-the-shelf simulators.

Transactive energy, market-based controls, DER int↗
DOE OSTI2021

A deep learning-accelerated data assimilation and forecasting workflow for commercial-scale geologic carbon storage

Fast assimilation of monitoring data to update forecasts of pressure buildup and carbon dioxide (CO 2 ) plume migration under geologic uncertainties is a challenging problem in geologic carbon storage. The high computational cost of data assimilation with a high-dimensional parameter space impedes fast decision-making for commercial-scale reservoir management. We propose to leverage physical understandings of porous medium flow behavior with deep learning techniques to develop a fast data assimilation-reservoir response forecasting workflow. Applying an Ensemble Smoother Multiple Data Assimilation (ES-MDA) framework, the workflow updates geologic properties and predicts reservoir performance with quantified uncertainty from pressure history and CO 2 plumes interpreted through seismic inversion. As the most computationally expensive component in such a workflow is reservoir simulation, we developed surrogate models to predict dynamic pressure and CO 2 plume extents under multi-well injection. The surrogate models employ deep convolutional neural networks, specifically, a wide residual network and a residual U-Net. The workflow is validated against a flat threedimensional reservoir model representative of a clastic shelf depositional environment. Intelligent treatments are applied to bridge between quantities in a true-3D reservoir model and those in a single-layer reservoir model. The workflow can complete history matching and reservoir forecasting with uncertainty quantification in less than one hour on a mainstream personal workstation.

25 ENERGY STORAGE↗
DOE OSTI2022

A multi-criteria CCUS screening evaluation of the Gulf of Mexico, USA

Continued research into reservoir characterization along with offshore carbon dioxide (CO 2 ) transportation and infrastructure assets is needed to facilitate development of safe and successful carbon capture, utilization, and storage (CCUS) projects. This paper outlines a multi-criteria evaluation methodology that incorporates disparate sets of quantitative, spatially variable data into a decision-making framework for screening the Gulf of Mexico (GOM) outer continental shelf (OCS) for potentially viable CO 2 storage and enhanced oil recovery (EOR) sites. Criteria categories include favorable geologic characteristics, logistics, and potential risks. Data compiled for 14 criteria from several publicly available geographic information system (GIS) layers was aggregated over 2559 spatially balanced points across the study area using the National Energy Technology Laboratory (NETL)-developed Cumulative Spatial Impact Layers™ (CSIL) GIS tool. Criteria are weighted by qualitative expert opinion relative to their perceived importance to given scenarios— the output of combined criteria values and weights enables regional CO 2 storage suitability differentiation. The methodology considers both technical and non-technical factors impacting CCUS decision-making. The flexible methodology enables a systematic approach to regional ranking at high spatial resolution over a large study domain. Additionally, the framework enables high-grading of priority sites that warrant further characterization and follow-on analysis. Areas along the Louisiana coast and Mississippi River Delta consistently rank high for all scenarios largely a result of the favorable geology with the potential for stacked storage, as well as the density of existing pipelines and platforms, and proximity to several onshore CO 2 sources. High-graded regions for the CO 2 EOR-related scenarios are typically located further offshore towards the middle and edge of the OCS compared to higher priority regions for the geologic storage scenarios which fall closer to the Louisiana coastline.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Excipient screening by lyophilization provides insights into spray drying formulations for nanoparticle vaccines

Nanoparticles have shown great promise as delivery platforms in the development of tunable and safe vaccines. Nanolipoprotein particles (NLPs), also known as nanodiscs, are discoidal nanoparticles composed of a lipid bilayer stabilized at their periphery by apolipoproteins. Under the right conditions, the NLP self-assembly process is highly customizable in terms of lipids and apolipoprotein constituents, allowing for tunable physical and chemical characteristics. This flexibility allows a wide range of vaccine antigens and adjuvants to be incorporated onto the NLP platform for tailored vaccine design. The stability of NLPs during long term storage is a very important factor in developing a vaccine delivery platform suitable for widespread global use. When stored in a solution for extended periods of time, NLPs dissociate into their corresponding lipids and protein constituents, leading to particle degradation. Proper stabilization of NLPs can often be achieved by lyophilization (i.e. freeze-drying), a method widely used for various applications including pharmaceuticals. This process, however, can be damaging to particles without the presence of lyoprotectants or excipients that help maintain particle stability during lyophilization. Another method used to stabilize vaccines and pharmaceuticals is spray drying, a process that converts liquid formulations into dry powders through controlled heating and airflow. While spray drying is rapid, scalable, and cost-effective, lyophilization is typically a gentler process that better retains biomolecule structure and function. Both processes use excipients for particle stabilization, so lyophilization can be used as a surrogate to test stability of NLPs, to down-select formulations that may withstand the harsher conditions of spray drying. To screen different formulations, NLPs were synthesized and purified to homogeneity by size exclusion chromatography (SEC) and samples were prepared with a wide range of lyoprotectants and/or excipients. To assess the protective effects of excipients on NLPs upon spray drying, both pre- and post-lyophilized samples were analyzed by SEC. To assess the protective effects upon heating (encountered during the spray drying process), NLP samples were incubated at elevated temperatures prior to SEC analysis. The lyoprotectants and excipients evaluated in this study had different efficiencies in protecting NLPs during lyophilization and heating tests. Trehalose, for example, exhibits stabilization on NLPs both upon lyophilization and heating whereas leucine accelerated NLP dissociation. Although some lyoprotectants are effective by themselves, different combinations can decrease the stabilization of NLPs. Shelf-stable vaccines that do not require cold-chain storage are essential for global accessibility and our findings provide fundamental insight into how to advance NLP-based vaccines for these applications.

Serrano, Litzay J [Lawrence Livermore National Lab↗
DOE OSTI2022

Dynamic calibration of differential equations using machine learning, with application to turbulence models

We present a methodology for calibration of parametric ordinary and partial differential equation models, using off-the-shelf software for back-propagation in Neural Networks (NN). As a prototypical example, we consider calibration of a Reynolds-averaged Navier-Stokes (RANS) turbulence closure model, against ground truth data from direct numerical simulations (DNS) of two different turbulent flows. Numerical time integration is represented as a custom NN, where only the RANS model parameters are trainable. A loss function is defined to quantify the mismatch between the NN prediction and the ground truth over a predefined, finite time integration window. This loss function is then minimized using a gradient descent method utilizing the back-propagation algorithm. Furthermore, this dynamic approach to training is to be contrasted with a static approach, wherein a least square regression estimate for parameters is obtained in the limit of an infinitesimal time integration window. In a first test of static and dynamic approaches against ground truth data generated by the model, the former proves to be significantly faster and more accurate than the latter at recovering the parameters. When both calibration approaches are tested against DNS data, for which it is known that the model cannot achieve a perfect fit, the static approach yields a good prediction only for short times, while the dynamic approach results in physical and stable predictions over the entire integration window. After optimization of the dynamic approach for time step, spatial resolution, stability, and physics-based constraints, we obtain a 50% improvement of outcomes over those obtained from the existing, manually calibrated set of parameters, demonstrating the merits of this systematic and automated procedure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A mass conservative, well balanced, tangency preserving and energy decaying method for the shallow water equations on a sphere

Here a fully discrete surface finite element method is proposed for solving the viscous shallow water equations in a bounded Lipschitz domain on the sphere based on a general triangular mesh. The method consists of a modified Crank–Nicolson method in time and a Galerkin surface finite element method in space for the fluid thickness H and the fluid velocity u. A finite element space tangential to the sphere at all finite element nodes is proposed to approximate the fluid velocity u. The proposed method has second-order accuracy in time and first-order accuracy in space, and preserves mass conservation, well balancedness, tangency of velocity to the sphere, and energy decay. Numerical experiments are presented to illustrate the accuracy of the proposed method and the preservation of the physical properties, including mass conservation, well balancedness, and energy decay. A numerical simulation of ocean mesoscale activity on a circular basin with a continental shelf is provided.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A scalable DG solver for the electroneutral Nernst-Planck equations

The robust, scalable simulation of flowing electrochemical systems is increasingly important due to the synergy between intermittent renewable energy and electrochemical technologies such as energy storage and chemical manufacturing. The high Péclet regime of many such applications prevents the use of off-the-shelf discretization methods. In this work, we present a high-order Discontinuous Galerkin scheme for the electroneutral Nernst-Planck equations. The chosen charge conservation formulation allows for the specific treatment of the different physics: upwinding for advection and migration, and interior penalty for diffusion of ionic species as well the electric potential. Similarly, the formulation enables different treatments in the preconditioner: AMG for the potential blocks and ILU-based methods for the advection-dominated concentration blocks. Here we evaluate the convergence rate of the discretization scheme through numerical tests. Strong scaling results for two preconditioning approaches are shown for a large 3D flow-plate reactor example.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Effects of carbonitrides and carbides on microstructure and properties of castable nanostructured alloys

In this work, to develop advanced reduced-activation ferritic-martensitic (RAFM) steels for fusion reactor structural applications, both carbonitride- and carbide-strengthened castable nanostructured alloys (CNAs) were explored for higher densities of MX (M = Ti/Ta/V/etc. and X = C/N) nanoprecipitates. Additionally, systematic comparisons between the two types of CNAs indicated generally similar microstructures and comparable tensile properties and creep resistance. However, the carbide-CNAs did show some advantages over the carbonitride-CNAs in terms of the uniformly distributed higher density of MC nanoprecipitates, greater Charpy impact upper shelf energies, less deuterium retention and swelling, and potentially less transmutation-induced composition changes and consequently thermodynamically more stable carbides. The carbide-CNAs showed the best-balanced high performance in the examined properties, in contrast to the significantly varied performance of oxide-dispersion-strengthened alloys and the generally lower performance of current RAFM steels.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Microstructures and mechanical properties of a modified 9Cr ferritic-martensitic steel in the as-built condition after additive manufacturing

A newly developed nano-structured high-Mn 9Cr ferritic-martensitic (FM) steel designed for additive manufacturing (Additive-manufactured Nanostructured Alloy, ANA) was fabricated via the direct energy deposition method. The as-printed ANA2 showed tensile properties (strength and elongation) and Charpy impact toughness (upper-shelf energy and ductile-brittle transition temperature) comparable to oxide-dispersion-strengthened (ODS) Eurofer and PM2000. Compared with wrought P91, the as-built ANA2 showed significantly higher yield strength but inferior Charpy impact toughness and ductility. Microstructural characterization revealed uniformly distributed sub-micron pores, an extremely high dislocation density, and a high density of ultrafine nano-structured precipitates in the matrix. The microstructures indicated the dislocations as the dominant strengthening element and the ultrafine precipitates as the primary contribution to estimated irradiation sink density. This work demonstrates the ability to exploit the unique consolidation properties of additive manufacturing to fabricate steels which marry the benefits of both ODS alloys and conventionally processed FM steels.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Scaleup and manufacturability of symmetric-structured metal-supported solid oxide fuel cells

Metal-supported solid oxide fuel cells with symmetric architecture, having metal supports on both sides of the cell, are scaled up from button cell size to large 50 cm 2 active area cell size. The cells remain flat after sintering assisted by the symmetric structure. Equivalent performance is achieved for button cells and large cells, and thermal cycling and redox cycling tolerance are demonstrated for the large cells. The catalyst infiltration process is improved to enable high-throughput manufacturing. The cumbersome lab-scale molten nitrate infiltration process is replaced with a room-temperature process in which a shelf-stable aqueous solution of nitrate salts is applied to the cell by spraying, painting, or other scalable techniques. Here, a fast-ramp thermal conversion of the nitrate salts to the final oxide catalyst composition is implemented, allowing many infiltration cycles to be accomplished in a single work shift. Increasing the number of infiltration cycles from 5 to 10 led to an increase in peak power density from approximately 0.3 to 0.52 W cm -2 .

25 ENERGY STORAGE↗
DOE OSTI2025

Modeling gas, hydrates, and slope stability on the U.S. Atlantic margin during Pleistocene glacial cycles

Changes in temperature and sea level can cause dissociation of methane hydrates in shallow marine sediments, leading to seafloor destabilization. Along the U.S. Atlantic margin, there exists a well-documented history of slope failure and numerous recorded occurrences of gas seeps. Several studies have linked slope failure in the region to gas seepage and hydrate dissociation driven by glacial-interglacial transitions, but this linkage has not been quantitatively demonstrated. Along the shelf edge, in an area where shallow methane gas seeps have been identified, we modeled methane gas and hydrate formation using a one-dimensional fluid flow model. Methane gas formation was modeled over the last 120,000 years to simulate a glacial-interglacial cycle. Here, we ran this model at 16,044 individual locations in the region between 29° N – 45° N and 82° W – 66° W at a resolution of 1 x 1 arcminutes, focusing specifically on water depths between 200 and 1000 m that bracket the seafloor outcrop of the base of the hydrate stability zone. Using historic temperature and pressure records from the last 120,000 years, sediment properties in the area, and factor of safety calculations, we found that hydrate dissociation alone is unlikely to cause sediment failure in the region, implying that an additional driving force would be necessary for failure to occur.

Hydrate dissociation↗
DOE OSTI2026

Servomotor-driven leveling elements for machine tool frame-to-floor alignment

This paper presents the results of aligning the frame to concrete floor of a large 5-axis machine tool by leveling element adjustments using servomotors instead of manual operation. The machine tool leveling elements used in this study are mechanical devices that attach the machine tool frame to the concrete foundation. These leveling elements are also adjustable so that each location along the machine tool can be uniquely adjusted such that the geometric errors of the frame are minimized, and the accuracy of the machine tool is improved. Off-the-shelf servomotors and connection equipment were installed at each of 12 leveling element locations for a precision 5-axis machine tool at Oak Ridge National Laboratory. The servomotors allow a technician to align the machine tool frame remotely, instead of crawling under the machine tool to iteratively manually adjust each of the 12 leveling elements. The open-loop servomotor-leveling element system design is presented in this paper as well as machine tool frame alignment results. The servomotor system significantly reduces leveling element adjustment time, eliminates the need for under-machine access, reduces technician physical strain, and significantly improves the adjustment repeatability.

Honeycutt, Andrew [ORNL]↗
DOE OSTI2025

Faster solutions to the interdiction defense problem using suboptimal solutions

The interdiction defense (ID) problem solves a defender-attacker-defender model where the defender and attacker share the same set of components to harden and target. Here, we build upon the best response intersection (BRI) algorithm by developing the BRI with suboptimal solutions (BRI-SS) algorithm to solve the ID problem. The BRI-SS algorithm utilizes off-the-shelf optimization solvers that return suboptimal solutions at no additional computation cost. We derive novel cuts from suboptimal solutions, reducing the number of iterations required for the algorithm to converge while maintaining optimality guarantees. We also present a heuristic that utilizes all obtained suboptimal solutions to select the next defense to evaluate at each iteration. We perform computational experiments applied to power grid interdiction on standard test cases. Our results demonstrate that the BRI-SS algorithm consistently outperforms the BRI algorithm across all test cases.

Computer science↗