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Advances in Mixed Precision Algorithms: 2021 Edition

Over the last year, the ECP xSDK-multiprecision effort has made tremendous progress in developing and deploying new mixed precision technology and customizing the algorithms for the hardware deployed in the ECP flagship supercomputers. The effort also has succeeded in creating a cross-laboratory community of scientists interested in mixed precision technology and now working together in deploying this technology for ECP applications. In this report, we highlight some of the most promising and impactful achievements of the last year. Among the highlights we present are: Mixed precision IR using a dense LU factorization and achieving a 1.8× speedup on Spock; results and strategies for mixed precision IR using a sparse LU factorization; a mixed precision eigenvalue solver; Mixed Precision GMRES-IR being deployed in Trilinos, and achieving a speedup of 1.4× over standard GMRES; compressed Basis (CB) GMRES being deployed in Ginkgo and achieving an average 1.4× speedup over standard GMRES; preparing hypre for mixed precision execution; mixed precision sparse approximate inverse preconditioners achieving an average speedup of 1.2×; and detailed description of the memory accessor separating the arithmetic precision from the memory precision, and enabling memory-bound low precision BLAS 1/2 operations to increase the accuracy by using high precision in the computations without degrading the performance. We emphasize that many of the highlights presented here have also been submitted to peer-reviewed journals or established conferences, and are under peer-review or have already been published.

97 MATHEMATICS AND COMPUTING↗

Equation-Free Coarse Control of Distributed Parameter Systems via Local Neural Operators

The control of high-dimensional distributed parameter systems (DPS) remains a challenge when explicit coarse-grained equations are unavailable. Classical equation-free (EF) approaches rely on fine-scale simulators treated as black-box timesteppers. However, repeated simulations for steady-state computation, linearization, and control design are often computationally prohibitive, or the microscopic timestepper may not even be available, leaving us with data as the only resource. We propose a data-driven alternative that uses local neural operators, trained on spatiotemporal microscopic/mesoscopic data, to obtain efficient short-time solution operators. These surrogates are employed within Krylov subspace methods to compute coarse steady and unsteady-states, while also providing Jacobian information in a matrix-free manner. Krylov-Arnoldi iterations then approximate the dominant eigenspectrum, yielding reduced models that capture the open-loop slow dynamics without explicit Jacobian assembly. Both discrete-time Linear Quadratic Regulator (dLQR) and pole-placement (PP) controllers are based on this reduced system and lifted back to the full nonlinear dynamics, thereby closing the feedback loop.

93B52, 93C20, 47N70, 65J15, 65M32, 68T07, 68T20, 6↗

Optimizing multichannel luminaire control using a color efficient matrix

The described embodiments relate to multichannel luminaires (102, 212, 404) that employ a color coefficient matrix (CCM) that can be used to adjust an operation of the multichannel luminaires according to their contribution of light to an area (112, 402). The CCM can be generated based on images captured within the area and/or a software simulation that approximates the contribution of light from the multichannel luminaires to the area. Once the CCM has been generated, the CCM can be used to compensate control signals to each multichannel luminaire in order to provide more accurate color rendering and uniform light distribution. Furthermore, feedback from embedded sensors (206) in the multichannel luminaires and/or sensors (116, 208, 210, 418) in the area can provide further basis for compensating control signals according to the qualities of the natural and artificial light entering the area, and the effects of different surfaces (128) on the light.

42 ENGINEERING↗

Analysis of the SBP-SAT Stabilization for Finite Element Methods Part II: Entropy Stability

In the hyperbolic research community, there exists the strong belief that a continuous Galerkin scheme is notoriously unstable and additional stabilization terms have to be added to guarantee stability. In the first part of the series, the application of simultaneous approximation terms for linear problems is investigated where the boundary conditions are imposed weakly. By applying this technique, the authors demonstrate that a pure continuous Galerkin scheme is indeed linearly stable if the boundary conditions are imposed in the correct way. In this work, we extend this investigation to the nonlinear case and focus on entropy conservation. Here, by switching to entropy variables, we provide an estimation of the boundary operators also for nonlinear problems, that guarantee conservation. In numerical simulations, we verify our theoretical analysis.

97 MATHEMATICS AND COMPUTING↗

Binary operations on neuromorphic hardware with application to linear algebraic operations and stochastic equations

Abstract Non-von Neumann computational hardware, based on neuron-inspired, non-linear elements connected via linear, weighted synapses—so-called neuromorphic systems—is a viable computational substrate. Since neuromorphic systems have been shown to use less power than CPUs for many applications, they are of potential use in autonomous systems such as robots, drones, and satellites, for which power resources are at a premium. The power used by neuromorphic systems is approximately proportional to the number of spiking events produced by neurons on-chip. However, typical information encoding on these chips is in the form of firing rates that unarily encode information. That is, the number of spikes generated by a neuron is meant to be proportional to an encoded value used in a computation or algorithm. Unary encoding is less efficient (produces more spikes) than binary encoding. For this reason, here we present neuromorphic computational mechanisms for implementing binary two’s complement operations. We use the mechanisms to construct a neuromorphic, binary matrix multiplication algorithm that may be used as a primitive for linear differential equation integration, deep networks, and other standard calculations. We also construct a random walk circuit and apply it in Brownian motion simulations. We study how both algorithms scale in circuit size and iteration time.

97 MATHEMATICS AND COMPUTING↗

Adaptive variational quantum eigensolvers for highly excited states

Highly excited states of quantum many-body systems are central objects in the study of quantum dynamics and thermalization that challenge classical computational methods due to their volume-law entanglement content. In this work, we explore the potential of variational quantum algorithms to approximate such states. We propose an adaptive variational quantum eigensolver (VQE) for excited states (X) that self-generates a variational ansatz for arbitrary eigenstates of a many-body Hamiltonian H by attempting to minimize the energy variance with respect to H. We benchmark the method by applying it to an Ising spin chain with integrable and nonintegrable regimes, where we calculate various quantities of interest, including the total energy, magnetization density, and entanglement entropy. We also compare the performance of adaptive VQE-X to an adaptive variant of the folded-spectrum method. For both methods, we find a strong dependence of the algorithm's performance on the choice of operator pool used for the adaptive construction of the ansatz. In particular, an operator pool including long-range two-body gates accelerates the convergence of both algorithms in the nonintegrable regime. Here, we also study the scaling of the number of variational parameters with system size, finding that an exponentially large number of parameters may be necessary to approximate individual highly excited states. Nevertheless, we argue that these methods lay a foundation for the use of quantum algorithms to study finite-energy-density properties of many-body systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Williston Basin Resource Study for Commercial-Scale Subsurface Hydrogen Storage

The Energy & Environmental Research Center (EERC), in partnership with the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL), the EERC’s State Energy Research Center (SERC), MPLX Operations LLC, and TC Energy Development Holdings Inc. (a subsidiary of TC Energy Corporation), studied the potential for subsurface hydrogen storage and recovery in the Williston Basin of western North Dakota. The project’s goal was to evaluate the feasibility of large-scale, secure geologic H 2 storage to support future hydrogen generation, storage, and use. This work included laboratory testing, H 2 –rock–fluid exposure experiments, literature reviews on H 2 embrittlement, and reservoir modeling and simulations. The study included an assessment of storage potential across three types of storage reservoirs using both reservoir simulation and DOE’s web-based tool SHASTA-HELP (Subsurface Hydrogen Assessment, Storage, and Technology Acceleration – Hydrogen Estimator for Logistical Planning), as well as investigation of potential H 2 production and markets for commercial-scale deployment. Building on prior EERC gas storage research, three storage options were selected for detailed evaluation: the Broom Creek Formation (a clastic saline reservoir), the Dickinson Lodgepole Mounds (DLM) complex (carbonate mud mound structures) of the Lodgepole Formation (an active oil and gas producing reservoir), and the Dunham Salt Interval of the Piper Formation (to be used for engineered salt cavern development). These targets were prioritized based on prior EERC research using datasets related to seal capacity, reservoir quality, mechanical integrity, and injectivity. Exposure tests on Broom Creek and DLM samples showed mineral dissolution and precipitation that increased brine salinity and altered reservoir rock surfaces. Although these results provide useful insight, they are limited by small sample sizes and short-term (30-day) exposure, requiring further study to assess long-term storage integrity. Salt formations were not tested because of their known nonreactivity and established mechanical stability. Results of reservoir simulations performed for a single site demonstrated that the Broom Creek Formation may be capable of receiving up to 42,000 tonnes of injected H 2 over 7 months via one well. H 2 recovery took place over 5 months, resulting in approximately 26,000 tonnes (~62% without cushion gas [CG]). This work suggests water production may be important and subsequent cycles of injection and production may perform more efficiently; however, significant site-specific work in the future is needed to assess actual reservoir performance of injection and withdrawal of H 2 storage. For oil reservoir potential, a multiple-well model was used to simulate injection of approximately 32,000 tonnes of H 2 into a single wellbore while simultaneously producing in place reservoir fluids from four offset wells to maintain reservoir pressure. The simulation results suggested a high recovery (~98%); in addition, cost advantages through existing infrastructure could be realized. Challenges in this reservoir include vi managing gas purity and leakage risks. In both scenarios, production of H 2 takes place in a single-well scenario with 10 cycles (7 months of injection and 5 months of production) over 10 years. Finally, the use of engineered caverns in the Dunhan Salt was evaluated, and the results suggest that while they have a smaller capacity (<1000 tonnes per cavern), they exhibit nearly complete gas recovery (>99%), fast response times, and low purity risk. While caverns in North Dakota may be smaller in capacity, fields can be developed in galleries to accommodate the volumetric needs and rapid turnaround times necessary to meet market demands. Geographic limitations and thin salt intervals in North Dakota may represent less total storage potential than salt domes elsewhere, but significant opportunities exist to expand this market for gas storage in North Dakota. A basinwide assessment was performed to estimate a first-of-its-kind value for H 2 storage on a large scale. DOE’s SHASTA-HELP, combined with EERC simulation work, was used to perform the assessment. Estimated H 2 storage potential varied widely for each formation type. The Broom Creek saline formation was estimated to have a storage potential of approximately 1.7–90.5 million tonnes (MMt). The DLM oil reservoirs were estimated to have 0.07–0.19 MMt of capacity. Notably, each of these estimates relies on significant assumptions regarding reservoir thickness, porosity, permeability, and CG needed for operation. Much research is needed to understand the true site-specific storage resource potential of each formation. Using the Dunham Salt Interval for cavern development may result in as much as 4.79 MMt (up to 2.87 MMt working gas) of H 2 storage potential. An important note for consideration is that the values presented here need significantly more geological characterization and engineering assessments prior to gaining confidence in performance. This will be a focal point for future research and development needs. The basinwide evaluation also indicated that North Dakota has significant H 2 generation potential, with estimates up to a possible 13 MMt annually, suggesting a substantial opportunity for H 2 market development and thus the need for commercial-scale H 2 storage to facilitate growth and resilience. Key Recommendations 1. Conduct detailed site characterization (3D seismic, well logs, core sampling) to reduce geologic uncertainty. 2. Perform techno-economic analyses incorporating market, regulatory, and incentive frameworks. 3. Investigate long-term interactions among H 2 , CGs, well materials, and formations to assess risks. 4. Develop pilot- and field-scale demonstrations to validate models and establish best practices.

03 NATURAL GAS↗

Quantum-classical tradeoffs and multi-controlled quantum gate decompositions in variational algorithms

The computational capabilities of near-term quantum computers are limited by the noisy execution of gate operations and a limited number of physical qubits. Hybrid variational algorithms are well-suited to near-term quantum devices because they allow for a wide range of tradeoffs between the amount of quantum and classical resources used to solve a problem. This paper investigates tradeoffs available at both the algorithmic and hardware levels by studying a specific case – applying the Quantum Approximate Optimization Algorithm (QAOA) to instances of the Maximum Independent Set (MIS) problem. We consider three variants of the QAOA which offer different tradeoffs at the algorithmic level in terms of their required number of classical parameters, quantum gates, and iterations of classical optimization needed. Since MIS is a constrained combinatorial optimization problem, the QAOA must respect the problem constraints. This can be accomplished by using many multi-controlled gate operations which must be decomposed into gates executable by the target hardware. We study the tradeoffs available at this hardware level, combining the gate fidelities and decomposition efficiencies of different native gate sets into a single metric called the gate decomposition cost .

Tomesh, Teague↗

Hydropower Geotechnical Foundations: Current Practice and Innovation Opportunities for Low-Head Applications

Hydropower is a renewable energy resource that produces electricity from flowing water under pressure. Engineered hydropower structures, such as dams, are used to create a hydraulic head, enabling a turbinegenerator unit to convert pressurized flow into electricity. While hydropower has been a source of renewable energy since antiquity, new development in the United States has slowed in recent decades. Based on recent resource assessments, the largest opportunity to expand hydropower in the United States is from new stream-reach development (i.e., new hydropower development along stream-reaches that do not currently have hydroelectric facilities or other forms of infrastructure, such as dams). Roughly 75% of identified new stream-reach development potential is from low-head sites (less than 30 ft of head), which typically suffer from smaller power densities and higher normalized costs, given economies of scale. Hydropower developers and other stakeholders are thus interested in strategies to reduce initial capital costs while practicing sustainable development to maximize environmental compatibility with minimal disruption to natural aquatic life, sediment, and water flows. Historically, civil works have represented a significant cost driver for new hydropower development, with the foundation system representing a major cost component and source of uncertainty. The foundation system is the collection of engineered structural features (e.g. cutoff trenches, walls, grouting, anchors) constructed at or below the preconstruction ground surface that interfaces between the overlying structures (superstructures) and the bed material below (subsurface). Development of a hydropower foundation system must consider the various characteristics of the surrounding stream environment and subsurface while adhering to the engineering requirements of the superstructure that it supports. The care of water, excavation, and other construction activities are important features of foundation design and construction. The design and construction cost of the foundation system is largely dependent on the site geology and riverbed composition and is influenced by the level of geotechnical assessment required and conducted. Thus, a hydropower facility’s geotechnical foundation is often highly site-specific, with proper site selection and assessment being important to project success. The foundation system is designed to provide structural stability (of the foundation and dam), limit seepage, ensure public safety, and maintain functionality for the project life, during both construction and facility operations. Inadequate foundation or dam design can result in dam failure and the uncontrolled release of significant volumes of water, which could cause a high number of casualties and extensive property damage downstream of the failure. According to the Association of State Dam Safety Officials, approximately 30% of all historical dam failures in the United States are attributed to foundation or abutment defects, and another 20% are attributed to piping or seepage through the embankment, foundation, or abutment. To ameliorate these safety considerations, foundations often require massive amounts of construction material (e.g., grout, concrete, engineered dam fill) and long construction times. Foundation design also requires significant analysis prior to construction because the initial in-stream and abutment subsurface conditions are site-specific, and sufficient data for them often are lacking. Current practice requires on-site assessment, using expensive drilling and invasive and non-invasive investigation methods, to determine the expected cost of foundation material and treatment. Additionally, foundation construction often requires site dewatering (and other care of water activities), which involves constructing temporary diversion structures upstream and often downstream, called cofferdams, and water diversion systems that route water around the construction site. Cofferdams and water diversion systems can drastically increase construction costs and contribute to environmental disruption, including modification of flow patterns and benthic habitats. Given the technical, economic, and environmental challenges associated with hydropower foundations, opportunities exist to improve the current state of practice and to develop new and innovative solutions to Hydropower is a renewable energy resource that produces electricity from flowing water under pressure. Engineered hydropower structures, such as dams, are used to create a hydraulic head, enabling a turbinegenerator unit to convert pressurized flow into electricity. While hydropower has been a source of renewable energy since antiquity, new development in the United States has slowed in recent decades. Based on recent resource assessments, the largest opportunity to expand hydropower in the United States is from new stream-reach development (i.e., new hydropower development along stream-reaches that do not currently have hydroelectric facilities or other forms of infrastructure, such as dams). Roughly 75% of identified new stream-reach development potential is from low-head sites (less than 30 ft of head), which typically suffer from smaller power densities and higher normalized costs, given economies of scale. Hydropower developers and other stakeholders are thus interested in strategies to reduce initial capital costs while practicing sustainable development to maximize environmental compatibility with minimal disruption to natural aquatic life, sediment, and water flows. Historically, civil works have represented a significant cost driver for new hydropower development, with the foundation system representing a major cost component and source of uncertainty. The foundation system is the collection of engineered structural features (e.g. cutoff trenches, walls, grouting, anchors) constructed at or below the preconstruction ground surface that interfaces between the overlying structures (superstructures) and the bed material below (subsurface). Development of a hydropower foundation system must consider the various characteristics of the surrounding stream environment and subsurface while adhering to the engineering requirements of the superstructure that it supports. The care of water, excavation, and other construction activities are important features of foundation design and construction. The design and construction cost of the foundation system is largely dependent on the site geology and riverbed composition and is influenced by the level of geotechnical assessment required and conducted. Thus, a hydropower facility’s geotechnical foundation is often highly site-specific, with proper site selection and assessment being important to project success. The foundation system is designed to provide structural stability (of the foundation and dam), limit seepage, ensure public safety, and maintain functionality for the project life, during both construction and facility operations. Inadequate foundation or dam design can result in dam failure and the uncontrolled release of significant volumes of water, which could cause a high number of casualties and extensive property damage downstream of the failure. According to the Association of State Dam Safety Officials, approximately 30% of all historical dam failures in the United States are attributed to foundation or abutment defects, and another 20% are attributed to piping or seepage through the embankment, foundation, or abutment. To ameliorate these safety considerations, foundations often require massive amounts of construction material (e.g., grout, concrete, engineered dam fill) and long construction times. Foundation design also requires significant analysis prior to construction because the initial in-stream and abutment subsurface conditions are site-specific, and sufficient data for them often are lacking. Current practice requires on-site assessment, using expensive drilling and invasive and non-invasive investigation methods, to determine the expected cost of foundation material and treatment. Additionally, foundation construction often requires site dewatering (and other care of water activities), which involves constructing temporary diversion structures upstream and often downstream, called cofferdams, and water diversion systems that route water around the construction site. Cofferdams and water diversion systems can drastically increase construction costs and contribute to environmental disruption, including modification of flow patterns and benthic habitats. Given the technical, economic, and environmental challenges associated with hydropower foundations, opportunities exist to improve the current state of practice and to develop new and innovative solutions to challenges frequently encountered with traditional approaches. With this understanding, it is critically important to understand and document the current state of practice for hydropower geotechnical foundations, identify key challenges, and define opportunities for innovative solutions. To this end, this report documents the current state of practice across the three main phases of geotechnical foundation development: (1) geotechnical site assessment, (2) design, and (3) construction for hydropower systems. It also describes the major challenges with conventional approaches and identifies opportunities for innovation to reduce hydropower foundations costs, timelines, and risks. Key takeaways from this report include the following: Approximately 80% of available low-head sites are expected to have foundations on soil beds rather than rock beds, suggesting that rockfill and earthfill dams may be the most cost-effective conventional dam type for new projects.; Geotechnical and geologic investigation activities are time-consuming and expensive but are essential to define the parameters and criteria needed for foundation design.; Certain riverbed soil and bedrock types present significant technical challenges or require expensive foundation construction, which can prove financially prohibitive for low-head project development.; Modular hydropower design and prefabricated modular foundations represent a promising but unproven paradigm for new hydropower development. Design and construction approaches using optimized and highly repeatable, reliable components would benefit project cost, time, and risk but require additional research and development.; Temporary construction features for foundations, including cofferdams, water diversion, and water control systems, can prove costly and have inherent construction risk.; For economically viable development, hydropower geotechnical foundations should be limited to 4 to 15% of the project’s total initial capital costs. Many proposed projects have experienced cost overruns attributable to foundation difficulties or surprises during construction. These overruns may have been due to inadequate investigations, lack of adequate engineering effort to tailor the structures to site geology and topography, and/or contractual terms, among other considerations.; Challenges for hydropower foundations and opportunities for innovative technology solutions are identified in the following areas (consistent with the three main phases of foundation development): Geotechnical site assessment, Foundation design and materials, Construction methods and technology. Ultimately, this report aims to provide information about geotechnical foundations for low-head hydropower and to motivate transformative technologies to support hydropower growth.

13 HYDRO ENERGY↗

Identification and Online Updating of Dynamic Models for Demand Response of an Industrial Air Separation Unit

Demand-response operation of air separation units requires frequent changes in production rate(s), and scheduling calculations must explicitly consider process dynamics to ensure feasibility of the solutions. To this end, scale-bridging models (SBMs) approximate the scheduling-relevant dynamics of a process and its controller in a low-order representation. In contrast to previous works that have employed nonlinear SBMs, this paper proposes linear SBMs, developed using time-series analysis, to facilitate online scheduling computations. Using a year-long industrial dataset, we nd that compact linear SBMs are suitable approximations over typical scheduling horizons, but that their accuracies are unpredictable over time. We introduce a strategy for online updating of the SBMs, based on Kalman ltering schemes for online parameter estimation. The approach greatly improves the accuracy of SBM predictions and will enable the use of linear SBM-based demand-response scheduling in the future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Photon-Sparse, Poisson Light-Sheet Microscopy

Light-sheet microscopy has revolutionized bioimaging by enabling approximately an order of magnitude reduction in specimen irradiance compared to confocal imaging. Here, we introduce a light-sheet imaging system that enables an additional order of magnitude reduction in specimen irradiance by operating at the Poisson limit. To operate at this limit, we integrated classical illumination with single-photon detection and wavelet-based image reconstruction. This integration enabled brightness quantification and object recognition from fewer than one detected photon per image pixel, corresponding to more than 10-fold lower irradiance levels than modern systems. We demonstrate how such photon-sparse imaging can eradicate photobleaching and enable both dim and bright object imaging, thus, further enhancing the related gains of light-sheet microscopy.

60 APPLIED LIFE SCIENCES↗

DarkSide-20k sensitivity to light dark matter particles

The dual-phase liquid argon time projection chamber is presently one of the leading technologies to search for dark matter particles with masses below 10 GeV c$^{−2}$. This was demonstrated by the DarkSide-50 experiment with approximately 50 kg of low-radioactivity liquid argon as target material. The next generation experiment DarkSide-20k, currently under construction, will use 1,000 times more argon and is expected to start operation in 2027. Based on the DarkSide-50 experience, here we assess the DarkSide-20k sensitivity to models predicting light dark matter particles, including Weakly Interacting Massive Particles (WIMPs) and sub-GeV c$^{−2}$ particles interacting with electrons in argon atoms. With one year of data, a sensitivity improvement to dark matter interaction cross-sections by at least one order of magnitude with respect to DarkSide-50 is expected for all these models. A sensitivity to WIMP–nucleon interaction cross-sections below 1 × 10$^{−42}$ cm$^{2}$ is achievable for WIMP masses above 800 MeV c$^{−2}$. With 10 years exposure, the neutrino fog can be reached for WIMP masses around 5 GeV c$^{−2}$.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Light transport with weak angular dependence in fog

Random scattering and absorption of light by tiny particles in aerosols, like fog, reduce situational awareness and cause unacceptable down-time for critical systems or operations. Computationally efficient light transport models are desired for computational imaging to improve remote sensing capabilities in degraded optical environments. To this end, we have developed a model based on a weak angular dependence approximation to the Boltzmann or radiative transfer equation that appears to be applicable in both the moderate and highly scattering regimes, thereby covering the applicability domain of both the small angle and diffusion approximations. An analytic solution was derived and validated using experimental data acquired at the Sandia National Laboratory Fog Chamber facility. The evolution of the fog particle density and size distribution were measured and used to determine macroscopic absorption and scattering properties using Mie theory. A three-band (0.532, 1.55, and 9.68 µ m) transmissometer with lock-in amplifiers enabled changes in fog density of over an order of magnitude to be measured due to the increased transmission at higher wavelengths, covering both the moderate and highly scattering regimes. The meteorological optical range parameter is shown to be about 0.6 times the transport mean free path length, suggesting an improved physical interpretation of this parameter.

74 ATOMIC AND MOLECULAR PHYSICS↗

Flexible FlueCO2

Carbon dioxide (CO2) emission reductions remain a significant challenge on the path to clean energy. There are increasing legislative, social, and environmental factors motivating CO2 emissions reduction from power plants with carbon capture and storage (CCS). CCS in natural gas combined cycle (NGCC) power plants is critical to achieve a net-zero carbon electricity grid. Enhanced 45Q tax credits provide new incentives, but currently available technologies are unable to profitably operate in grids with deep variable renewable penetration which require flexible NGCC operation. Luna Labs has developed the FlueCO2 membrane to enable a profitable NGCC-CCS process. The FlueCO2 membrane couples steam transport across the membrane to CO2 transport in the opposite direction, enabling high capture efficiencies and low energy costs even at low CO2 concentrations. The dual-phase membrane can operate in the range of typical flue gas temperatures and pressures and does not require temperature or pressure cycling. Luna Labs’ FlueCO2 technology enables flexible and profitable operation of NGCC plants with lower capital investment and impact on electricity prices. In this Phase 1 project, Luna Labs utilized experimental testing, modeling, process simulation, and standardized costing methodologies to evaluate the techno-economic value of a 650 MW greenfield NGCC plant with FlueCO2 (NGCC-FlueCO2). Key design requirements for operation were established and plant performance under load-leveling conditions was validated through computational fluid dynamics and process modeling. Luna Labs developed a dynamic modeling tool which modeled plant operational modes across a variety of tax structures and electricity pricing scenarios to project the overall Net Present Value (NPV) of the NGCC-FlueCO2. FlueCO2 minimizes the impact of CCS integration on plant operation by integrating directly into the NGCC heat recovery steam generator (HRSG). By tapping into the plant’s low-pressure (LP) steam, operators can divert LP steam to the greenfield NGCC and/or CCS process in response to dynamic markets. Since FlueCO2 will not significantly affect HRSG (or NGCC) operation, CCS only turns off during peak power demand (>$250/MWh). Under baseload conditions, FlueCO2 lowers the capital (37%), energy (36%) and carbon capture (<$40/tonne) costs and can increase the overall plant lifetime NPV by approximately ~$1B in comparison with NGCC solvent-based capture reference cases (NETL Case 31B). Luna Labs has shared its costing tools with several interested partners and customers, which follows a generalizable approach to costing analysis.

Kelly, Jesse↗

Post-2026 Environmental Impact Statement Rate Analysis for the Colorado River Storage Project

The Glen Canyon Dam (GCD) is a principal power-generating asset within the Colorado River Storage Project (CRSP), accounting for approximately 70–80% of CRSP power production over the past two decades. In June 2023, the U.S. Bureau of Reclamation (Reclamation) issued a Notice of Intent to prepare an Environmental Impact Statement (EIS) outlining operational guidelines and strategies for Colorado River Basin reservoirs after 2026 (Reclamation, 2023). Power generation is among CRSP’s statutory purposes under the Colorado River Storage Project Act of 1956 (U.S. Congress, 1956). Assessing how alternative policy frameworks affect CRSP power production and the resulting electricity rates for U.S. customers is therefore essential to inform decision-making. This report evaluates projected electricity rates and the market value of electricity from the Western Area Power Administration (WAPA) CRSP GCD under multiple post-2026 policy scenarios to support Reclamation’s EIS development. Results from advanced econometric and machine learning models indicate that the Enhanced Coordination alternative (EnhanCoor), Maximum Operational Flexibility alternative (CCA), and Supply Driven - 55 alternative (SD55) alternatives yield more favorable hydropower generation and capacity outcomes, which are objectives outlined in Reclamation’s documentations (Reclamation, 2007; Reclamation, 2016). Specifically, these scenarios are associated with higher electricity production, lower projected rate trajectories, and greater economic value to the U.S. power system from CRSP generation. The remaining five scenarios generally produce lower generation, higher rate trajectories, and reduced long-term market values.

13 HYDRO ENERGY↗

Feasibility and Compatibility of Alternative Fuels in the U.S. Rail Sector: Technoeconomic, Lifecycle, and Supply Chain Analysis

The U.S. rail sector is a cornerstone of the United States’ freight transportation system, responsible for moving approximately 40% of long-distance freight ton-miles each year (AAR, 2025). Freight demand is projected to grow over time (BTS, 2017) thereby necessitating the investigation of alternative fuels that can sustain operational efficiency while reducing emissions and cost impacts. At the same time, it is important to explore alternative fuels as new sources of energy that can increase energy security and resilience for this sector. This report investigates the feasibility and compatibility of seven alternative fuels in the U.S. rail sector, focusing on biofuels and fuels from other renewable energy sources. The study evaluates alternative fuel pathways, considering their technical, economic, and environmental aspects to provide stakeholders with a comprehensive understanding of potential solutions.

09 BIOMASS FUELS↗

The Deep Underground Neutrino Experiment (DUNE) Program

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino oscillation experiment aimed at determining the neutrino mass hierarchy and the CP-violating phase. The DUNE physics program also includes the detection of astrophysical neutrinos and the search for signatures beyond the Standard Model, such as nucleon decays. DUNE consists of a near detector complex located at Fermilab and four 17 kton Liquid Argon Time Projection Chamber (LArTPC) far detector modules to be built 1.5 km underground at SURF, approximately 1300 km away. The detectors are exposed to a wideband neutrino beam generated by a 1.2 MW proton beam with a planned upgrade to $>$ 2 MW. Two 770 ton LArTPCs (ProtoDUNEs) have been operated at CERN for over 2 years as a testbed for DUNE far detectors and have been optimized to take new cosmic and test-beam data in 2024-2025. The DUNE and ProtoDUNE experiments and physics goals, as well as recent progress and results, are presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Inference, Prediction, & Entropy-Rate Estimation of Continuous-Time, Discrete-Event Processes

Inferring models, predicting the future, and estimating the entropy rate of discrete-time, discrete-event processes is well-worn ground. However, a much broader class of discrete-event processes operates in continuous-time. Here, we provide new methods for inferring, predicting, and estimating them. The methods rely on an extension of Bayesian structural inference that takes advantage of neural network’s universal approximation power. Based on experiments with complex synthetic data, the methods are competitive with the state-of-the-art for prediction and entropy-rate estimation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗