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At least 1,045 records · Page 58

Preliminary Techno-Economic Assessment of Gas Switching Reforming (GSR) of Natural Gas for Pure Hydrogen Production and Power Generation with Integrated CO2 Capture

The increasing demand for hydrogen and the CO2 intensity of natural gas (NG) reforming motivate the development of low-carbon-emission hydrogen production technologies. Gas Switching Reforming (GSR) is an advanced auto-thermal reforming technology that produces hydrogen or syngas from natural gas. It integrates inherent CO2 capture by utilizing a specialized oxygen carrier in a single fluidized bed reactor, eliminating the need for complex, energy-intensive post-combustion separation. GSR technology builds upon Chemical Looping Reforming (CLR), an experimentally proven technology with strong potential for scaling up. In this study, select oxygen carriers (OC) (NiO/Al2O3, Fe2O3-CeO2/Al2O3, and magnetite) were tested in methane steam reforming in a fixed bed reactor to determine their relative reactivities under relevant conditions for GSR (800 °C, 7 bar total pressure). Process models were then developed to perform techno-economic analysis (TEA) of GSR for hydrogen production (GSR-H₂) and a combined cycle (GSR-CC) in which high-purity H₂ is fired in a gas turbine to produce electricity. Operating at 10 bar and 1100 °C and with the additional recovery steps implemented increased H₂ production by ~30% and improved efficiency relative to prior studies. For GSR-H₂, the levelized cost of hydrogen (LCOH) is 1.61–1.64 $/kg-H₂, competitive with a reference SMR case, though operating and maintenance costs are higher due to increased electricity demand. GSR-CC has a significantly higher levelized cost of electricity (LCOE) than its reference NGCC (natural gas combined cycle) plant, suggesting it is less competitive; however, increasing production scale could make it more attractive. Life-cycle results for GSR-H2 indicate NG consumption drives ~75% of total global warming impacts (~2.3 kg CO2 eq/kg H2). An environmental, health, and safety screening suggests iron-based carriers are comparatively safer, whereas NiO may pose greater risks. Overall, GSR-H2 is a scalable, competitive option for hydrogen production using nickel and non-nickel OC.

03 NATURAL GAS↗

Preliminary techno-economic assessment of gas switching reforming (GSR) of natural gas for pure hydrogen production and power generation with integrated CO2 capture

The increasing demand for hydrogen and the CO2 intensity of natural gas (NG) reforming motivate the development of low-carbon-emission hydrogen production technologies. Gas Switching Reforming (GSR) with integrated CO2 capture, a technology based on Chemical Looping Reforming (CLR), has been experimentally proven and shows potential for scale-up. In this study, select oxygen carriers (OC) (NiO/Al2O3, Fe2O3-CeO2/Al2O3, and magnetite) were tested in methane steam reforming in a fixed bed reactor to determine their relative reactivities under relevant conditions for GSR (800 °C, 7 bar total pressure). Process models were then developed to perform techno-economic analysis (TEA) of GSR for hydrogen production (GSR-H2) and a combined cycle (GSR-CC) in which high-purity H2 is fired in a gas turbine to produce electricity. Operating at 10 bar and 1100 °C and with the additional recovery steps implemented increased H2 production by ∼ 30% and improved efficiency relative to prior studies. For GSR-H2, the levelized cost of hydrogen (LCOH) is 1.61–1.64 $/kg-H2, competitive with a reference SMR case, though operating and maintenance costs are higher due to increased electricity demand. GSR-CC has a significantly higher levelized cost of electricity (LCOE) than its reference NGCC (natural gas combined cycle) plant, suggesting it is less competitive; however, increasing production scale could make it more attractive. Life-cycle results for GSR-H2 indicate NG consumption drives ∼ 75% of total global warming impacts (∼2.3 kg CO2 eq/kg H2). An environmental, health, and safety screening suggests iron-based carriers are comparatively safer, whereas NiO may pose greater risks. Overall, GSR-H2 is a scalable, competitive option for hydrogen production using nickel and non-nickel OC.

03 NATURAL GAS↗

Power Actuation and Switching Module Development

The Deep Space Avionics (DSA) Project is developing a Power Actuation and Switching Module (PASM). This component enables a modular and scalable design approach for power switching applications, which can result in a wide variety of power switching architectures using this simple building block. The PASM is designed to provide most of the necessary power switching functions of spacecraft for various Deep Space missions including future missions to Mars, comets, Jupiter and its moons. It is fabricated using an A SIC process that is tolerant of high radiation. The development includes two application specific integrated circuits (ASICs) and support circuitry all packaged using High Density Interconnect (HDI) technology. It can be operated in series or parallel with other PASMs, It can be used as a high-side or low-side switch and it can drive thruster valves, pyrotechnic devices such as NASA standard initiators, bus shunt resistors, and regular spacecraft component loads. Each PASM contains two independent switches with internal current limiting and over-current trip-off functions to protect the power subsystem from load faults. During turnon and turnoff each switch can limit the rate of current change (di/dt) to a value determined by the user. Threeway majority-voted On/Off commandability and full switch status telemetry (both analog and digital) are built into the module. This paper describes the development process used to design, model, fabricate, and test these compact and versatile power switches. Preliminary test results from prototype HDI PASM hardware are also discussed.

Power Actuation and Switching Module (PASM)↗

Comparative assessment of new oxygen carrier materials for gas switching reforming of natural gas: Techno-economics assessment, life cycle analysis, and experimental insights

The increasing demand for hydrogen and the CO 2 intensity of natural gas (NG) reforming motivate the development of low-carbon-emission hydrogen production technologies. Gas Switching Reforming (GSR) with integrated CO 2 capture, a technology based on Chemical Looping Reforming (CLR), has been experimentally proven and shows potential for scale-up. In this study, select oxygen carriers (OC) (NiO/Al 2 O 3 , Fe 2 O 3 -CeO 2 /Al 2 O 3 , and magnetite) were tested in methane steam reforming in a fixed bed reactor to determine their relative reactivities under relevant conditions for GSR (800 °C, 7 bar total pressure). Process models were then developed to perform techno-economic analysis (TEA) of GSR for hydrogen production (GSR-H 2 ) and a combined cycle (GSR-CC) in which high-purity H 2 is fired in a gas turbine to produce electricity. Operating at 10 bar and 1100 °C and with the additional recovery steps implemented increased H 2 production by ∼ 30% and improved efficiency relative to prior studies. For GSR-H 2 , the levelized cost of hydrogen (LCOH) is 1.61–1.64 $/kg-H 2 , competitive with a reference SMR case, though operating and maintenance costs are higher due to increased electricity demand. GSR-CC has a significantly higher levelized cost of electricity (LCOE) than its reference NGCC (natural gas combined cycle) plant, suggesting it is less competitive; however, increasing production scale could make it more attractive. Life-cycle results for GSR-H 2 indicate NG consumption drives ∼ 75% of total global warming impacts (∼2.3 kg CO 2 eq/kg H 2 ). An environmental, health, and safety screening suggests iron-based carriers are comparatively safer, whereas NiO may pose greater risks. Overall, GSR-H 2 is a scalable, competitive option for hydrogen production using nickel and non-nickel OC.

03 NATURAL GAS↗

High Fidelity CFD Simulations Supporting the KP-FHR

Kairos Power, LLC, is developing its version of the Fluoride-cooled High-temperature Reactor, the KP-FHR. The design uses a pebble bed core with fluoride salt as a coolant. The pebbles used in the KP-FHR have a diameter of 4 cm, with a shell fuel region where TRISO particles are embedded. A Pebble bed core design is adopted by several Gen IV reactors, They boast many benefits, such as fuel integrity, highly efficient heat transfer, and passive safety. However, it is challenging to accurately predict temperature and flow inside a pebble bed. Traditional approaches use the porous media model, which regards the pebble bed as a continuous medium, but with different temperature fields representing different levels, such as the fluid temperature, pebble surface temperature, and pebble center temperature. Empirical heat transfer correlations are adopted to calculate the heat transfer coefficient between different phases. However, empirical correlations are usually validated with experimental data, which usually lacks detail inside the pebble bed. The available experimental data is also generally at a high Reynolds number, which falls outside of the conditions of KP-FHR. Explicit computational fluid dynamics (CFD) simulations of randomly packed pebble beds have only become feasible recently. This is thanks to the rapid development of computational power and scalable algorithms. In this work, we used the Spectral Element Method (SEM) CFD code NekRS to simulate the randomly packed pebble bed in a cylindrical container. NekRS, which is the GPU variant of Nek5000, but refactored to utilize the computational power of GPUs using the OCCA library to run on hybrid architecture high performance computing systems. It was initially developed with the libParamunal library, but truncated and tuned for large-scale turbulence simulation. As a result, the SEM reaches higher precision with the same degrees of freedom by using a high-order Lagrange polynomial basis distributed on Gauss-Lobatto-Legendre quadrature inside each element, compared to lower-order methods, such the Finite Volume Method and Finite Element Method. The report is divided into five parts. We start with a general discussion of the pebble bed reactor, along with a specific investigation into the KP-FHR. The second part presents the numerical methodology. In the third part, we study a modular pebble bed with 1741 pebbles in a container of 7 pebble-diameter radius. Beyond LES simulations done by NekRS, we also leveraged the thermal radiation model in OpenFOAM to study heat transfer under no-forced-flow scenarios. Then, in the fourth part we simulated a pebble bed similar to the size of the Hermes Test Reactor. The total number of pebbles is in these simulations is 34,374. The container radius is 14 pebble-diameters. Finally, the report concludes in part five, with a discussion of future work.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Development and Validation of a Two-Phase Thermal-Hydraulic CFD Code NEK-2P

A project is underway to develop, verify and validate an advanced two-phase flow modeling capability for the highly-scalable, high-performance Computational Fluid Dynamics (CFD) code NEK5000. The goal of this work is to verify and validate the two-phase version of the NEK5000 code, named NEK-2P, to simulate the two-phase flow and heat transfer phenomena that occur in a Boiling Water Reactor (BWR) fuel bundle under various operating conditions. The NEK-2P two-phase flow models follow the approach used for the Extended Boiling Framework (EBF) previously developed at Argonne but include more fundamental physical models of boiling phenomena and advanced numerical algorithms for improved computational accuracy, robustness, and computational speed. The development of the NEK-2P two-phase solver and the implementation of the Extended Boiling Framework two-phase models were initially supported by Argonne National Laboratory (Argonne) through a Laboratory Directed Research and Development (LDRD) project during FY2014-2016. The development and validation of the two-phase models through analyses of selected two-phase boiling flow experiments was supported by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program in FY2017-2020. This report focuses on verification and validation of the water-steam boiling model NEK-2P Two-Phase, CFD code. The NEK-2P was validated with Nuclear Power Engineering Corporation (NUPEC) Pressurized Water Reactor (PWR) Sub-channel and Bundle Test (PSBT) void distribution benchmark. Three different simulations were performed and analyzed for various operating conditions such as wall-heat flux and sub-cooled inlet temperatures. Reasonably good agreement with measured data was obtained in predicting the measured void distributions. Simulations were performed for Virginia Tech. (VT) 3x3 rod bundle geometry with and without spacers. The preliminary results were presented for Simplified Spacer Grid (SSG). In addition, the implementation of interface reconstruction model was tested with one of the Becker benchmark Critical Heat Flux (CHF) experiments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Woven TPS - A New Approach to TPS Design and Manufacturing

NASA's Office of the Chief Technologist (OCT) Game Changing Division recently funded an effort to advance a Woven TPS (WTPS) concept. WTPS is a new approach to producing TPS materials that uses precisely engineered 3D weaving techniques to customize material characteristics needed to meet specific missions requirements for protecting space vehicles from the intense heating generated during atmospheric entry. Using WTPS, sustainable, scalable, mission-optimized TPS solutions can be achieved with relatively low life cycle costs compared with the high costs and long development schedules currently associated with material development and certification. WTPS leverages the mature state-of-the-art weaving technology that has evolved from the textile industry to design TPS materials with tailorable performance by varying material composition and properties via the controlled placement of fibers within a woven structure. The resulting material can be designed to perform optimally for a wide range of entry conditions encompassing NASAs current and future mission needs. WTPS enables these optimized TPS designs to be translated precisely into mission-specific, manufactured materials that can substantially increase the efficiency, utility, and robustness of heat shield materials compared to the current state-of-the-art material options. By delivering improved heat shield performance and affordability, this technology will impact all future exploration missions, from the robotic in-situ science missions to Mars, Venus and Saturn to the next generation of human missions. WTPS can change the way NASA develops, certifies, and integrates TPS into mission life cycles - instead of being a mission constraint, TPS will become a mission enabler. It is anticipated that WTPS will have direct impact on SMD, HEOMD and OCT and will be of interest for DoD and COTS applications. This presentation will overview the WTPS concept and present some results from initial testing completed.

Feldman, Jay↗

From natural language to control signals: a conceptual framework for semantic channel finding in complex experimental infrastructure

Modern experimental platforms such as particle accelerators, fusion devices, telescopes, and industrial process control systems expose tens to hundreds of thousands of control and diagnostic channels, accumulated over decades of hardware evolution. Operators and AI systems alike depend on informal expert knowledge, inconsistent naming conventions, and scattered documentation to locate the signals required for monitoring, troubleshooting, and automated control, creating a persistent bottleneck for reliability, scalability, and emerging language-model-driven interfaces. We formalize semantic channel finding, the task of mapping natural-language intent to concrete control-system signals, as a general problem in complex experimental infrastructure, and introduce a four-paradigm conceptual framework to guide architecture selection based on facility-specific data regimes. The paradigms span (i) direct in-context lookup over small, curated channel dictionaries, (ii) constrained hierarchical navigation through structured trees, (iii) interactive agent exploration using iterative reasoning and tool-based database queries, and (iv) ontology-grounded semantic search that decouples channel meaning from facility-specific naming conventions. We demonstrate the practical feasibility of each paradigm through proof-of-concept implementations at four operational facilities spanning two orders of magnitude in scale: from compact free-electron lasers to large synchrotron light sources, operating under diverse control-system architectures ranging from clean hierarchical naming schemes to legacy environments with decades of heterogeneous conventions. Where evaluated against expert-curated operational queries, these instantiations achieve 90%–97% accuracy, validating the framework’s applicability across real-world deployment scenarios. To accelerate adoption across the broader scientific and industrial control-system community, we release open-source, plug-and-play implementations of all three interactive paradigms-direct lookup, hierarchical navigation, and middle-layer exploration-within the Osprey framework, together with tools for channel database generation, interactive testing, and minimal-configuration deployment. This work establishes semantic channel finding as a foundational capability for human-centric and agentic AI interfaces at large-scale facilities, providing both a systematic framework for architecture design and practical resources to enable adoption without building custom infrastructure from scratch.

channel finding↗

Next-Generation Optical Sensing Technologies for Exploring Ocean Worlds - NASA FluidCam, MiDAR, and NeMO-Net

We highlight three emerging NASA optical technologies that enhance our ability to remotely sense, analyze, and explore ocean worlds–FluidCam and fluid lensing, MiDAR, and NeMO-Net. Fluid lensing is the first remote sensing technology capable of imaging through ocean waves without distortions in 3D at sub-cm resolutions. Fluid lensing and the purpose-built FluidCam CubeSat instruments have been used to provide refraction-corrected 3D multispectral imagery of shallow marine systems from unmanned aerial vehicles (UAVs). Results from repeat 2013 and 2016 airborne fluid lensing campaigns over coral reefs in American Samoa present a promising new tool for monitoring fine-scale ecological dynamics in shallow aquatic systems tens of square kilometers in area. MiDAR is a recently-patented active multispectral remote sensing and optical communications instrument which evolved from FluidCam. MiDAR is being tested on UAVs and autonomous underwater vehicles (AUVs) to remotely sense living and non-living structures in light-limited and analog planetary science environments. MiDAR illuminates targets with high-intensity narrowband structured optical radiation to measure an object’s spectral reflectance while simultaneously transmitting data. MiDAR is capable of remotely sensing reflectance at fine spatial and temporal scales, with a signal-to-noise ratio 10-10(exp 3) times higher than passive airborne and spaceborne remote sensing systems, enabling high-framerate multispectral sensing across the ultraviolet, visible, and near-infrared spectrum. Preliminary results from a 2018 mission to Guam show encouraging applications of MiDAR to imaging coral from airborne and underwater platforms whilst transmitting data across the air-water interface. Finally, we share NeMO-Net, the Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment. NeMO-Net is a machine learning technology under development that exploits high-resolution data from FluidCam and MiDAR for augmentation of low-resolution airborne and satellite remote sensing. NeMO-Net is intended to harmonize the growing diversity of 2D and 3D remote sensing with in situ data into a single open-source platform for assessing shallow marine ecosystems globally using active learning for citizen-science based training. Preliminary results from four-class Q17 coral classification have an accuracy of 94.4%. Together, these maturing technologies present promising scalable, practical, and cost-efficient innovations that address current observational and technological challenges in optical sensing of marine systems.

Ved Chirayath↗

Investigation of Flux Spreading in a Light-Trapping, Planar-Cavity Receiver for Enclosed Solar Particle Heating

Concentrating solar thermal power (CSP) technology development has recently focused on increasing the operating temperatures to accommodate high efficiency power cycles and thermochemical processes. Inert solid particles as heat transfer media enable solar receivers to operate above 700 degrees Celsius resulting in increased system thermal efficiency compared to the conventional molten salt based CSP system. An open-cavity falling-particle solar receiver that can efficiently heat particles by direct heating from concentrated solar radiation faces challenges with large particle losses from wind and unable to support thermochemical reactions. A light-trapping, planar cavity reiver (LTPCR) where particles are indirectly heated can significantly minimize the particle losses during the operation, support thermochemical reactions, and offer scalability potential. The LTPCR features an array of vertical planar receiver/absorber panels arranged within a cavity configuration. Concentrated solar radiation from heliostats is focused onto the receiver walls, where heat is indirectly transferred to solid particles flowing inside the receiver channels. Heat transfer occurs through direct contact between the receiver panel walls and particles, and can be enhanced by fluidizing particles with air. This fluidization increases particle-wall contact and extends particle residence time, maximizing heat transfer efficiency. The unique vertical planar receiver structure originated from a near-blackbody tubular light absorber, effectively distributing the incoming solar beam spread across the panel walls and trapping light. This flux spreading effect, driven by cosine projection, converts high incident solar flux into a lower, more uniform heat flux on the panel walls. This redistribution enhances heat transfer efficiency between particle-wall or reaction gases-wall, while preventing localized overheating of the receiver panel. Indirect planar cavity solar receivers completely separate solid particles from the ambient environment that can greatly reduce the thermal losses in heated particles resulting in high efficiency at high temperatures above 700 degrees Celsius. This design ensures no particle losses to the environment during the operation while open-cavity designs can experience significant particle losses from wind. An experimental investigation was conducted to observe flux spreading on the receiver panel wall. A lab-scale prototype planar receiver, fabricated using Haynes 230 alloy, was tested under direct concentrated solar radiation using the high-flux solar furnace (HFSF) facility at NREL. The experiment was performed under normal peak radiative heat fluxes ranging from 800 to 1900 kW/m2. A temperature distribution on the panel wall was measured using a thermal imaging camera (FLIR A 6600). To prevent overheating at the receiver front tip, prism-shaped heat shields (Zircar UNIFROM C1) were placed in front of the receiver, and their influence on flux spreading was also studied. Absorbed flux distribution on the panel wall was modeled using SolTrace. The total solar power and flux distributions delivered from HFSF were determined based on the heliostat mirror optical properties, direct normal irradiance (DNI) on the on-sun testing days, peak flux measurement during the on-sun testing, and shutter/attenuator settings Due to the large incident angles of the solar beam on the panel wall, the angular optical properties of Haynes 230 alloy and Zircar heat shields were incorporated into the model. This flux distribution model was then integrated into a computational fluid dynamics (CFD) simulation to predict the receiver panel wall temperature, which was compared with the experimental measurements. Both prediction and measurements identified a temperature hotspot at the backside of the panel, indicating that the incident solar beam can fully reach to the rear of the receiver. The heat shields positioned at the front of the receiver effectively reduced the excessive temperature rise at the receiver front tip. Overall, the temperature was well distributed over the panel wall, with a minor hotspot at the back of the receiver. The model slightly overpredicted the temperature, possibly due to discrepancies in optical properties of the panel and an underprediction of thermal loss in the receiver. The advancement of the particle LTPCR offers a viable alternative to open-cavity receivers by addressing particle loss issues. Additionally, it presents a pathway for enabling solar thermochemical processes, extending CSP technology beyond power generation to fuel and chemical production.

14 SOLAR ENERGY↗

Exploration Medical System Demonstration

BACKGROUND: Exploration class missions will present significant new challenges and hazards to the health of the astronauts. Regardless of the intended destination, beyond low Earth orbit a greater degree of crew autonomy will be required to diagnose medical conditions, develop treatment plans, and implement procedures due to limited communications with ground-based personnel. SCOPE: The Exploration Medical System Demonstration (EMSD) project will act as a test bed on the International Space Station (ISS) to demonstrate to crew and ground personnel that an end-to-end medical system can assist clinician and non-clinician crew members in optimizing medical care delivery and data management during an exploration mission. Challenges facing exploration mission medical care include limited resources, inability to evacuate to Earth during many mission phases, and potential rendering of medical care by non-clinicians. This system demonstrates the integration of medical devices and informatics tools for managing evidence and decision making and can be designed to assist crewmembers in nominal, non-emergent situations and in emergent situations when they may be suffering from performance decrements due to environmental, physiological or other factors. PROJECT OBJECTIVES: The objectives of the EMSD project are to: a. Reduce or eliminate the time required of an on-orbit crew and ground personnel to access, transfer, and manipulate medical data. b. Demonstrate that the on-orbit crew has the ability to access medical data/information via an intuitive and crew-friendly solution to aid in the treatment of a medical condition. c. Develop a common data management framework that can be ubiquitously used to automate repetitive data collection, management, and communications tasks for all activities pertaining to crew health and life sciences. d. Ensure crew access to medical data during periods of restricted ground communication. e. Develop a common data management framework that allows for scalability, extensibility, and interoperability of data sources and data users. f. Lower total cost of ownership for development and sustainment of peripheral hardware and software that use EMSD for data management. g. Provide a better standard of healthcare for crew members through reductions in the time required by crew and ground personnel to provide medical treatment and the number of crew errors experienced during treatment.

Rubin, D. A.↗

Machine-learning-based estimates of global natural vegetated wetland methane emissions (2000–2025)

Wetlands are the largest natural source of atmospheric methane (CH 4 ), yet comprehensive global budgets are typically delayed by years, preventing a timely understanding of CH 4 sources, sinks, and trends. To reduce this delay, we present a model emulator-driven framework and accompanying workflow that enable timely, continuous emission updates using a machine-learning emulator to reconstruct spatially explicit monthly emission fields at 1° × 1° resolution. We apply this framework to a global dataset of natural vegetated wetland CH 4 emissions to extend the most recent Global Methane Budget (GMB; Saunois et al., 2025) record that covers the 2000–2020 emissions through 2025. In the test data (∼ 30 % of the total dataset), the emulator achieved a global R 2 of 0.65 ± 0.003 (mean ± 95 % CI, hereafter) and an RMSE of 5.49 ± 0.12×10 -3 Tg CH 4 yr −1 . The emulator is trained on 35 GMB model estimates, including 22 process-based models and 13 atmospheric inversions, paired with 10 ensemble realizations of 11 gridded climate predictor variables from atmospheric reanalyses. Our results show that the global mean predicted wetland CH 4 emissions for 2021–2025 (157.8 ± 2.4 Tg CH 4 yr −1 ) are not significantly higher (∼ 0.05 Tg CH 4 yr −1 ) than the 2000–2020 baseline. However, this stability masks a significant hemispheric redistribution of emissions. We detect an increase in Northern Hemisphere (NH) emissions in 2021–2025, with mid- and high-latitudes increasing by 0.76 ± 0.07 and 0.35 ± 0.03 Tg CH 4 yr −1 , respectively, while the tropics and Southern Hemisphere (SH) extratropics show offsetting negative trends (−0.95 ± 0.19 and -0.11 ± 0.02 Tg CH 4 yr −1 , respectively). The predicted emissions are able to capture the low emissions in 2023 in South America linked to El Niño-related drought, as reported by recent studies (Ciais et al., 2026; Quinn et al., 2025). Furthermore, we identify a distinct seasonal amplification of global emission trends that peaks in late boreal summer. This new modeled dataset and operational framework bridge the gap between the latest updated budgets and low-latency monitoring, providing a scalable capacity to frequently update global emission estimates and critical early warnings of regional wetland feedback loops. The data are publicly available at https://doi.org/10.5281/zenodo.18870108 (Li et al., 2026).

Li, Mengze [National University of Singapore (Sing↗

MFC 5.0: An exascale many-physics flow solver

Many problems of interest in engineering, medicine, and the fundamental sciences rely on high-fidelity flow simulation, making performant computational fluid dynamics solvers a mainstay of the open-source software community. Previous work MFC 3.0 was made a published, documented, and open-source solver via Bryngelson et al. Comp. Phys. Comm. (2021) with numerous physical features, numerical methods, and scalable infrastructure. MFC 5.0 is a significant update to MFC 3.0, featuring a broad set of well-established and novel physical models and numerical methods, as well as the introduction of GPU and APU (or superchip) acceleration. Here, we exhibit state-of-the-art performance and ideal scaling on the first two exascale supercomputers, OLCF Frontier and LLNL El Capitan. Combined with MFC’s single-accelerator performance, MFC achieves exascale computation in practice, and achieved the largest-to-date public CFD simulation at 200 trillion grid points as a 2025 ACM Gordon Bell Prize finalist. New physical features include the immersed boundary method, N-fluid phase change, Euler–Euler and Euler–Lagrange sub-grid bubble models, fluid-structure interaction, hypo- and hyper-elastic materials, chemically reacting flow, two-material surface tension, magnetohydrodynamics (MHD), and more. Numerical techniques now represent the current state-of-the-art, including general relaxation characteristic boundary conditions, WENO variants, Strang splitting for stiff sub-grid flow features, and low Mach number treatments. Weak scaling to tens of thousands of GPUs on OLCF Summit and Frontier and LLNL El Capitan achieves efficiencies within 5% of ideal to over 90% of their respective system sizes. Strong scaling results for a 16-times increase in device count show parallel efficiencies over 90% on OLCF Frontier. MFC’s software stack has undergone further improvements, including continuous integration, which ensures code resilience and correctness through over 300 regression tests; metaprogramming, which reduces code length while maintaining performance portability; and code generation for computing chemical reactions

Computational fluid dynamics↗

Development of a Robust and Efficient Parallel Solver for Unsteady Turbomachinery Flows

The traditional design and analysis practice for advanced propulsion systems relies heavily on expensive full-scale prototype development and testing. Over the past decade, use of high-fidelity analysis and design tools such as CFD early in the product development cycle has been identified as one way to alleviate testing costs and to develop these devices better, faster and cheaper. In the design of advanced propulsion systems, CFD plays a major role in defining the required performance over the entire flight regime, as well as in testing the sensitivity of the design to the different modes of operation. Increased emphasis is being placed on developing and applying CFD models to simulate the flow field environments and performance of advanced propulsion systems. This necessitates the development of next generation computational tools which can be used effectively and reliably in a design environment. The turbomachinery simulation capability presented here is being developed in a computational tool called Loci-STREAM [1]. It integrates proven numerical methods for generalized grids and state-of-the-art physical models in a novel rule-based programming framework called Loci [2] which allows: (a) seamless integration of multidisciplinary physics in a unified manner, and (b) automatic handling of massively parallel computing. The objective is to be able to routinely simulate problems involving complex geometries requiring large unstructured grids and complex multidisciplinary physics. An immediate application of interest is simulation of unsteady flows in rocket turbopumps, particularly in cryogenic liquid rocket engines. The key components of the overall methodology presented in this paper are the following: (a) high fidelity unsteady simulation capability based on Detached Eddy Simulation (DES) in conjunction with second-order temporal discretization, (b) compliance with Geometric Conservation Law (GCL) in order to maintain conservative property on moving meshes for second-order time-stepping scheme, (c) a novel cloud-of-points interpolation method (based on a fast parallel kd-tree search algorithm) for interfaces between turbomachinery components in relative motion which is demonstrated to be highly scalable, and (d) demonstrated accuracy and parallel scalability on large grids (approx 250 million cells) in full turbomachinery geometries.

West, Jeff↗

Recovery of Natural Gas Equipment Emissions into Gas Compression Engines for the Reduction of Potential Greenhouse Gas Emissions

Since the turn of the millennium, the United States (U.S.) oil and natural gas (ONG) industry has nearly doubled its natural gas production rate. As a result, the ONG industry has recently come under increasing scrutiny for its contributions to greenhouse gas (GHG) emissions. Consequently, various solutions to this problem have been proposed and formulated to reduce the impacts of GHG emissions on the environment. West Virginia University (WVU) have found it important to research the impacts of recovering vented gas streams into prime-mover engines. The U.S. Department of Energy (DOE) and National Energy Technology Laboratory (NETL) have granted WVU funding to research and develop a “Methane Mitigator” (M2) - a “Scalable Vent Mitigation Strategy to Simultaneously Reduce Methane Emissions and Fuel Consumption from the Compression Industry.” One of the main areas of interest for this research was the collection of emissions from natural gas equipment into a Caterpillar G3508J natural gas compression engine. The parameters being analyzed from the engine were brake-specific emissions and power output. The emissions sources considered for this research were pneumatic controllers (PCs), reciprocating compressor vents, and the engine’s open crankcase breather. The compressor vent and PC emissions were simulated using a mass flow controller (MFC) and flowed into the engine using two separate methods: (1) directly into the air intake, and (2) through a retrofitted closed crankcase ventilation system (CCV), serving as a buffer volume. The crankcase emissions were quantified without the CCV, and the impact on exhaust emissions from circulating the crankcase gases into the intake was measured. The simulated compressor vent and PC flows from the MFC had limited effect on the steady state operation of the engine and resulting performance. When the simulated flows were fed directly into the engine’s air intake, the changes within the engine’s continuous performance and emission parameters were larger but lasted for shorter durations. Conversely, when the simulated flows were fed into the CCV before entering the air intake, the changes in the engine’s performance and emission parameters were less pronounced for continuous analysis but lasted for longer durations. In either case, the continuous emission changes in both emissions and performance varied in size depending on the test scenario being run, but the cycle average changes in emissions and performance showed little impact overall compared to the engine’s baseline operation. As a result, the inclusion of a CCV shows a decrease in baseline carbon dioxide equivalent (CO2-eq.) engine emissions (from combined exhaust and open crankcase) of almost 4%. Likewise, the CCV inclusion reduced baseline total methane (CH4) from combined exhaust and open crankcase by upwards of 16%. These atmospheric emissions only decreased further with the inclusions of collected PC and compressor vent flows. The resulting changes in time-averaged rated exhaust behavior (or lack thereof) prove that the proposed M2 system could likely be deployed at sites with modern lean-burn natural gas engines as a viable option for reducing and eliminating potential GHG sources that would have otherwise been unutilized as energy sources.

03 NATURAL GAS↗

5G Enabled Energy Innovation: Advanced Wireless Networks for Science (Workshop Report)

Rapidly expanding, new telecommunications infrastructure based on 5G technologies will disrupt and transform how we design, build, operate, and optimize scientific infrastructure and the experiments and services enabled by that infrastructure, from continental-scale sensor networks to centralized scientific user facilities, from intelligent Internet of Things devices to supercomputers. Concurrently, 5G will introduce, or exacerbate, challenges related to protecting infrastructure and associated scientific data as well as to fully leveraging opportunities related to expanded infrastructure scale and complexity. The U.S. Department of Energy (DOE) Office of Science operates scientific infrastructure, supporting some of the nation’s most advanced intellectual discoveries, spanning the country and including 30 world-class user facilities from supercomputers to accelerators. Along with field experiments and remote observatories, every aspect of DOE’s scientific enterprise will be affected by 5G, which amounts to a complete renovation of the underpinnings of the nation’s information infrastructure. In this report we explore the scientific opportunities and new research challenges associated with 5G, ranging from scalability to heterogeneity to cybersecurity. The rapid commercial deployment of 5G opens the opportunity to rethink and reinvent DOE’s scientific infrastructure and experimentation, from intelligent sensor networks at unprecedented scales to a digital continuum of cyberinfrastructure spanning low-power sensors, high-performance computing embedded within and at the edge of the network, and DOE’s large-scale user instrument and computing facilities. New programming paradigms, workflow and data frameworks, and AI-based system design, operation, and autonomous adaptation and optimization will be necessary in order to exploit these new opportunities. Field deployments and centralized scientific instruments can also be revolutionized, moving (without traditional performance penalties) from wired to wireless connectivity for data and control systems, improving flexibility, and opening new sensing modalities, including the use of the 5G electromagnetic spectrum itself as an environmental probe. For DOE science, in contrast to commercial 5G applications and settings, devices will be deployed in extreme environments such as cryogenically cooled instrument control systems and in remote settings with harsh conditions, requiring the design of new materials for RF communication and edge processing to operate in these regimes. Concurrently, 5G infrastructure comprises both hardware and sophisticated software systems - currently closed and proprietary. The cybersecurity challenges to 5G-empowered reinvention mirror the complexity and variety of new 5G features, from virtualization to private network slices to ubiquitous access. Research is also needed in order to accelerate the development of secure and open 5G software infrastructure, reducing reliance on hardware and software produced outside the United States and providing the transparency and rigorous evaluation and testing afforded through open software. Twelve broad research thrusts are laid out in four chapters, with a companion fifth chapter (and three additional research thrusts) underscoring the needs and opportunities for an aggressive testbed program co-designed by networking experts and scientists involved in the 15 research thrusts. The urgency of undertaking this research is fueled by a global, accelerating deployment of new telecommunications infrastructure that is designed for entertainment and commercial applications - barely scratching the surface of what 5G can do to extend U.S. leadership in scientific discovery.

42 ENGINEERING↗

Advances in polycrystalline thin-film photovoltaics for space applications

Polycrystalline, thin-film photovoltaics represent one of the few (if not the only) renewable power sources which has the potential to satisfy the demanding technical requirements for future space applications. The demand in space is for deployable, flexible arrays with high power-to-weight ratios and long-term stability (15-20 years). In addition, there is also the demand that these arrays be produced by scalable, low-cost, high yield, processes. An approach to significantly reduce costs and increase reliability is to interconnect individual cells series via monolithic integration. Both CIS and CdTe semiconductor films are optimum absorber materials for thin-film n-p heterojunction solar cells, having band gaps between 0.9-1.5 ev and demonstrated small area efficiencies, with cadmium sulfide window layers, above 16.5 percent. Both CIS and CdTe polycrystalline thin-film cells have been produced on a laboratory scale by a variety of physical and chemical deposition methods, including evaporation, sputtering, and electrodeposition. Translating laboratory processes which yield these high efficiency, small area cells into the design of a manufacturing process capable of producing 1-sq ft modules, however, requires a quantitative understanding of each individual step in the process and its (each step) effect on overall module performance. With a proper quantification and understanding of material transport and reactivity for each individual step, manufacturing process can be designed that is not 'reactor-specific' and can be controlled intelligently with the design parameters of the process. The objective of this paper is to present an overview of the current efforts at MMC to develop large-scale manufacturing processes for both CIS and CdTe thin-film polycrystalline modules. CIS cells/modules are fabricated in a 'substrate configuration' by physical vapor deposition techniques and CdTe cells/modules are fabricated in a 'superstrate configuration' by wet chemical methods. Both laser and mechanical scribing operations are used to monolithically integrate (series interconnect) the individual cells into modules. Results will be presented at the cell and module development levels with a brief description of the test methods used to qualify these devices for space applications. The approach and development efforts are directed towards large-scale manufacturability of established thin-film, polycrystalline processing methods for large area modules with less emphasis on maximizing small area efficiencies.

Lanning, Bruce R.↗

Molecular Simulations in Astrobiology

One of the main goals of astrobiology is to understand the origin of cellular life. In the absence of any record of the earliest ancestors of contemporary cells, protocells, the most direct way to test our understanding of their characteristics is to construct laboratory models of protocells. Such efforts, currently underway in the NASA Astrobiology Program, are accompanied by computational studies aimed at explaining self-organization of simple molecules into ordered structures and developing designs of molecules that are capable of performing protocellular functions. Many of these functions, such as importing nutrients, capturing and storing energy, and responding to changes in the environment, are carried out by proteins bound to membranes. We use computer simulations to address the following, questions about these proteins: (1) How do small proteins (peptides) organize themselves into ordered structures at water-membrane interfaces and insert into membranes? (2) How do peptides aggregate to form membrane-spannin(y structures (e.g., channels)? (3) By what mechanisms do such aggregates perform their functions? The simulations are performed using the molecular dynamics (MD) method. In this method, Newton's equations of motion for each atom in the system are solved iteratively. At each time step, the forces exerted on each atom by the remaining atoms are evaluated by dividing them into two parts. Short-range forces are calculated directly in real space while long-range forces are evaluated in reciprocal space, usually using a particle-mesh algorithm which is of order O(NlnN). Currently, a time step of 2 femtoseconds is typically used, thereby making studies of problems occurring on multi-nanosecond time scales (10(exp 6) - 10(exp 8) time steps) accessible. To address a broader range of problems, simulations need to be extended by three orders of magnitude. Such an extension requires both algorithmic improvements and codes scalable to a large number of parallel processors. Work in this direction is in progress. Two specific series of simulations that demonstrate how peptides self-organize and function in membranes are discussed. In one series of simulations, it was shown that nonpolar peptides, disordered in water, translocate to the nonpolar interior of the membrane and, simultaneously, fold into two different helical structures, which remain in equilibrium. Once in the membrane, the peptides can readily change their orientation, especially in response to local electric fields. This structural and orientational flexibility of peptides with changing conditions may have provided a mechanism of transmitting signals between the environment and the interior of the protocell. In another series of simulations, the mechanism by which a simple protein channel efficiently mediates proton transport across membranes was investigated. This process is a key step in cellular bioenergetics. In the channel under study, proton transport is gated by four histidines that occlude the channel pore. The simulations demonstrate that protons move through the gate by a "shuttle" mechanism, wherein one histidine is protonated on the extracellular side and, subsequently, the proton bound on the opposite side is released.

Pohorille, Andrew↗