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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 361 records · Page 20

Modular flow in JT gravity and entanglement wedge reconstruction

It has been shown in recent works that JT gravity with matter with two boundaries has a type II ∞ algebra on each side. As the bulk spacetime between the two boundaries fluctuates in quantum nature, we can only define the entanglement wedge for each side in a pure algebraic sense. As we take the semiclassical limit, we will have a fixed long wormhole spacetime for a generic partially entangled thermal state (PETS), which is prepared by inserting heavy operators on the Euclidean path integral. Under this limit, with appropriate assumptions of the matter theory, geometric notions of the causal wedge and entanglement wedge emerge in this background. In particular, the causal wedge is manifestly nested in the entanglement wedge. Different PETS are orthogonal to each other, and thus the Hilbert space has a direct sum structure over sub-Hilbert spaces labeled by different Euclidean geometries. The full algebra for both sides is decomposed accordingly. From the algebra viewpoint, the causal wedge is dual to an emergent type III 1 subalgebra, which is generated by boundary light operators. To reconstruct the entanglement wedge, we consider the modular flow in a generic PETS for each boundary. We show that the modular flow acts locally and is the boost transformation around the global RT surface in the semiclassical limit. It follows that we can extend the causal wedge algebra to a larger type III 1 algebra corresponding to the entanglement wedge. Within each sub-Hilbert space, the original type II ∞ reduces to type III 1 .

2D Gravity↗

Advanced Transmission Technologies – GETs and HPCs Session 2: Advanced Power Flow Control and Transmission Topology Optimization

The INL TADA GETs Cohort Session 2, held on November 7, 2025, conducted in collaboration with ScottMadden, focused on two core Advanced Transmission Technologies (ATTs): Advanced Power Flow Control (APFC) and Transmission Topology Optimization (TTO). These technologies are pivotal in enhancing grid flexibility, reliability, and cybersecurity resilience. APFC, particularly through modular FACTS devices like Modular Static Synchronous Series Compensators (M-SSSCs), enables dynamic voltage injection to reroute power flows. The session highlighted the deployment benefits of APFC, such as rapid installation, minimal civil works, and re-deployability. Regulatory drivers like FERC Order 2023 mandate the inclusion of Grid-Enhancing Technologies (GETs) in interconnection studies. Case studies from Central Hudson, CAISO, and National Grid (UK) demonstrated APFC’s effectiveness in congestion relief and cost savings. The session also addressed cybersecurity concerns, including firmware vulnerabilities, SCADA integration risks, and supply chain dependencies. Participants engaged in interactive exercises to rank cybersecurity and supply chain risks, emphasizing the need for robust digital assurance strategies. TTO involves software-based reconfiguration of transmission networks to optimize power flow without new infrastructure. The session showcased its operational value, with examples from SPP, PJM, and MISO showing significant congestion cost reductions. Cybersecurity vulnerabilities were discussed, particularly in API security and software supply chains, referencing incidents like SolarWinds and attacks on Danish utilities. Digital assurance exercises explored worst-case scenarios, attack paths, and mitigation responsibilities between vendors and utilities. Reliability challenges such as algorithm stability, vendor dependency, and operator trust were also examined. Cross-cutting themes emphasized the importance of digital assurance tools, including Software Bills of Materials (SBOMs) and hardware-in-loop testing. Human performance, training, and operational confidence were identified as critical enablers of technology adoption. The session concluded with a preview of Session 3, which will focus on High Performance Conductors (HPCs) and risk-based cybersecurity tools. Session 2 of 3.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

A Real-Time Optimization with Warm-Start of Multiperiod AC Optimal Power Flows

We present a real-time optimization strategy based on warm-start for solving a moving horizon of multi period AC optimal power flow (ACOPF) problems. In each horizon, ACOPFs are temporally interlinked via generator ramp constraints, and we assume that each horizon needs to be solved every few seconds or minutes. We introduce two approximate tracking schemes that closely follow a solution path consisting of strongly regular points. We present theoretical results bounding the tracking error by the square of the parameter changes between time periods. Experimental results for networks of sizes up to 9K buses show a fast computation time while maintaining a good solution quality, thus making our approach well suited for real-time circumstances.

moving horizon↗

D Meson Sensitivity to a System Size Scan at LHC

Experimental measurements in pA collisions indicate no D meson suppression (R pPb ~ 1) but a surprisingly large v 2 . To better understand these results we propose a system size scan at the LHC involving 16 OO, 40 ArAr, 129 XeXe and 208 PbPb collisions. Using Trento+ v-USPhydro+DAB-MOD to make predictions, we find that the R AA tends towards unity when the system size is decreased, but nonetheless, in the most central collisions v 2 {2} is almost independent of the colliding system. Furthermore, these results are analyzed in light of path length and initial eccentricity variations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Accelerated Irradiation Testing and Post-Irradiation Characterization: U.S.-Based Capabilities for Advanced Nuclear Systems and Radioisotope Production

Irradiation experiments and post-irradiation examinations, together referred to as irradiation testing (IRT), are prerequisites for nuclear fuel and material qualification for the deployment of new and advanced reactors, as well as radioisotope production, thereby ensuring regulatory compliance. Qualified research and test reactors (RTRs) and testing facilities are essential to enable IRT to verify performance and safety under prototypical reactor conditions. In the past, qualification of new fuels or structural materials required about 20 years. Synergist strategies, advanced tools, and qualified methods are needed to greatly reduce this timeframe of IRT and radioisotope production. This study, termed accelerated-IRT, focuses on identifying gaps and leveraging U.S.-based RTRs and material testing capabilities, leveraging the preliminary evaluation and qualification of selected RTRs to provide a generic as well as specific-case solution paths forward, ensuring adherence to stringent regulatory standards. Furthermore, IRT and radioisotope production utilizing qualified RTRs necessarily includes modeling and simulation to support the design (i.e. neutronics, thermal, and structural aspects) and manufacturing of irradiation test specimens, vehicles, capsules, apparatuses, and flow loops. In addition, IRT can be improved by applying advanced manufacturing techniques and in-pile sensors and instrumentation, as discussed in this study.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

FY2022 Filter Test for TRU Waste Drum Prototype Unit

Continuing last year’s (fiscal year 2021) work, a prototype instrument and an NPI-6 Integrated Work Document (IWD) were developed to assess the functionality of filters on transuranic waste containers (commonly called 55 Gallon ring-top drums) without requiring the removal of the drum lid. The purpose of this work is to determine the air flow and pressure characteristics associated with filter clogging, filter pressure drop at a fixed flow rate, and leakage around the lid seal. The FY22 objectives included: (A) Development of prototype device, (B) Drafting an IWD document, (C) Defining a filter clogging parameter, (D) Assessing filter damage due to over-pressure events, and (E) A path forward to obtain approval of the system safety filters in compliance with P101-16 Industrial Ventilation – non HVACR (LANL 2022).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Effect of Formation Heterogeneity on CO 2 Dissolution in Subsurface Porous Media

Dissolution trapping is one of the most dominant mechanisms for the secure storage of CO 2 injected in porous subsurface formations saturated with brine. This trapping mechanism is enhanced by convective mixing, which occurs due to the gravitational instability between the different fluid layers in the aquifer. The reservoir permeability also plays a crucial role in the dissolution rate and overall fluid flow dynamics during the density-driven convection in porous media. Herein this study investigates the role of complex heterogeneity, i.e., irregular permeability distribution in CO 2 dissolution, using a novel experimental approach to create medium permeability heterogeneity in Hele–Shaw cells. Complex subsurface transport phenomena such as a preferential dissolution path, CO 2 sweep efficiency, changes in finger morphology, and CO 2 concentration distribution are visualized by creating heterogeneous media. Experimental results showed that reservoir permeability heterogeneity causes significant channeling effects and poor sweep efficiency. A scaling relationship between average finger growth rate (Gr) and permeability (k) was obtained as Gr [m s –1 ] = 266.8k [m 2 ] + 1.20 × 10 –6 . Furthermore, the mass of CO 2 dissolved is calculated using the spectrophotometric method to characterize the convective instability. The convective flux was analyzed by comparing the experimental dissolution flux with the theoretical diffusion flux, calculating a maximum Sherwood number of 6.8. The study’s findings improve the current understanding of the CO 2 convection morphology in heterogeneous media, allowing better assessment of long-term CO 2 storage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rigidity‐Driven Structural Isomers in the NaCl–Ga 2 S 3 System: Implications for Energy Storage

Alternative energy sources require the search for innovative materials with promising functionalities. Systems with unusual chemical properties represent an insufficiently explored domain, concealing unexpected features. Using diffraction and Raman spectroscopy over a wide temperature range, supported by first‐principles simulations, a rare phenomenon is unveiled: phase‐dependent chemical interactions between binary components in the NaCl–Ga 2 S 3 system. In this unique occurrence, previously intact binary crystalline species transform upon melting into mixed liquid structural isomers, forming bonds with new partners. The chemical combinatorics appears to be fully reversible for stable crystals and liquids. Despite this, rapidly frozen glasses out of thermodynamic equilibrium remain in a metastable isomeric state, offering remarkable properties, particularly a high room‐temperature Na + conductivity, comparable to the best sodium halide superionic conductors and therefore encouraging for sodium solid‐state batteries and energy applications. A rigidity paradigm is responsible for the observed phenomenon, as the extremely constrained Ga 2 S 3 crystal lattice does not survive viscous flow, breaking up at a short‐range level. The removal of rigidity constraints and dense packing leads to a significant increase in empty space, which is the origin of high sodium diffusivity. Broadly, the rigidity‐driven structural isomerism opens up an inspiring path to the discovery of atypical materials.

25 ENERGY STORAGE↗

Criticality analysis of nuclear binding energy neural networks

Machine learning methods, in particular deep learning methods such as artificial neural networks (ANNs) with many layers, have become widespread and useful tools in nuclear physics. However, these ANNs are typically treated as ‘black boxes’, with their architecture (width, depth, and weight/bias initialization) and the training algorithm and parameters chosen empirically by optimizing learning based on limited exploration. We test a non-empirical approach to understanding and optimizing nuclear physics ANNs by adapting a criticality analysis based on renormalization group flows in terms of the hyperparameters for weight/bias initialization, training rates, and the ratio of depth to width. This treatment utilizes the statistical properties of neural network initialization to find a generating functional for network outputs at any layer, allowing for a path integral formulation of the ANN outputs as a Euclidean statistical field theory. We use a prototypical example to test the applicability of this approach: a simple ANN for nuclear binding energies. We find that with training using a stochastic gradient descent optimizer, the predicted criticality behavior is realized, and optimal performance is found with critical tuning. However, the use of an adaptive learning algorithm leads to somewhat superior results without concern for tuning and thus obscures the analysis. Nevertheless, the criticality analysis offers a way to look within the black box of ANNs, which is a first step towards potential improvements in network performance beyond using adaptive optimizers.

artificial neural network↗

A path to intelligent watersheds: coordinating the data to decision pipeline

Operations of multi-reservoir systems are challenged in-part by the interplay of complex physical processes functioning within the watershed. The employment of intelligent systems can be of aid by linking environmental sensing, information technology, data analytics, simulation and decision support to achieve a data-to-decision flow of information. A further challenge is that watershed resources are managed for multiple purposes requiring some level of coordination among numerous resource managers, asset operators and users. System intelligence in this context relies on shared community platforms (data portals, community models), and coordinated communication between decision makers. Opportunities to enrich watershed intelligence has been the subject of a roadmapping exercise for the Department of Energy’s Water Power Technologies Office which has relied on broad stakeholder engagement. Initial phases of engagement involved personal interviews and a series of virtual group meetings, which focused on identifying opportunities to improve the intelligence of the physical infrastructure within our watersheds—examples of feedback include improved sensing of snowpack and runoff, data standards for facilitated data sharing, and better forecasting tools. The latter phase of engagement involved the conduct of a case study in the Upper Colorado River basin where key stakeholders were interviewed to map how their decisions are informed by intelligence from other basin stakeholders. Our presentation will highlight the interdisciplinary flow of information in complex watershed systems and identify physical and institutional opportunities toward the strategic operation of water infrastructure.

Colorado River↗

Formation and Diagnostics of Collisionless Shocks in Laser-Produced Plasmas (Final Report)

Collisions of supersonic flows occur frequently in astrophysics, and the resulting shock waves are responsible for the properties of many astrophysical phenomena, such as supernova remnants, Gamma Ray Bursts and jets from Active Galactic Nuclei. Because of the low density of astrophysical plasmas, the mean free path due to Coulomb collisions is typically very large; therefore, most shock waves in astrophysics are “collisionless” and form due to plasma instabilities and self-generated magnetic fields. Laboratory experiments at DOE high energy density (HED) facilities can achieve the conditions necessary for the formation of collisionless shocks and will provide a unique avenue for studying the nonlinear physics of shock waves. This project investigates the parameters and experimental configurations needed for the creation of collisionless shocks in the laboratory experiments. This study is being performed with state of the art 3D kinetic plasma simulations. Recent advances in ab-initio particle-in-cell (PIC) simulations of astrophysical shocks enable us to simulate shock formation on timescales and in geometries relevant to the laboratory experiments. The main goal of the proposal is to ascertain which signatures of shock physics can be extracted from the realistic experiments, accounting for limitations imposed by finite spatial and time scales in the lab. To aid the interpretation of current and future experimental data, PIC simulation data have been analyzed using the same diagnostic techniques as used in the laboratory, such as proton radiography and neutronics, to unambiguously predict the experimental signatures of relevant collisionless shock phenomena.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Mixing Pathways in Simple Box Models

Abstract Tracer variance budgets can be used to estimate bulk mixing in a control volume. For example, simple, analytical, bulk formulations of salt mixing, defined here as the destruction of salinity variance, can be found for estuaries with a riverine source of freshwater and a two-layer exchange flow at the mouth using salinity as a representative tracer. For a steady case, the bulk salt mixing M can be calculated as , where S in and S out are the representative salinities in the estuarine exchange flow, and Q R and Q in are the river and landward volume fluxes, respectively. The bulk salt mixing M can be considered as the sum of mixing pathways, where each pathway has a mixing of Q (Δ S ) 2 , where Q is the volume transport and Δ S is the salinity difference across the pathway. For the estuary case, one mixing path is associated with the river inflow, and the other is associated with the inflow of salty, oceanic water. This concept of linking mixing to input–output pathways is extended, in simple box models, from estuaries to scenarios with multiple inputs/outputs, as might be found in a complex estuarine/fjord network, in a region on a continental shelf, or any other control volume with multiple exchanges. This approach allows for the estimation of the relative contributions of each input–output pathway to the total mixing within a control volume.

54 ENVIRONMENTAL SCIENCES↗

Predicting the potential for mineral scale precipitation in unconventional reservoirs due to fluid-rock and fluid mixing geochemical reactions

Mineral precipitation within hydraulically fractured shale may affect fluid flow pathways and impact longterm hydrocarbon production. The ability to predict geochemical reactions that lead to problematic mineral precipitation will lead to active reservoir management strategies to improve overall production. Using the Marcellus Shale as a case study, a combination of laboratory experiments and reaction path modeling was applied to determine which reactions are likely to occur upon introduction of hydraulic fracturing fluid into the shale reservoir. Experimental results indicate that contact between fracturing fluid and shale will result in dissolution of primary minerals (quartz, feldspars, kaolinite, chlorite, pyrite) and secondary mineral precipitation over time periods of less than one week. Precipitation of barite, Fe-oxides, feldspars, amorphous silica and clay is likely to occur within the reservoir during shut in and early flowback due to mixing between fracturing fluid and reservoir brine as based on modeling saturation indices using experimental fluid data. Reaction path modeling of the experimental scenarios corroborates the specific dissolution and precipitation reactions observed experimentally. Comparison of the results to injected and produced waters from a Marcellus Shale well pad in Greene County, PA, USA, shows that the mineral reactions occur during the hydraulic fracturing, shut in, and early flowback periods. The results presented in this paper demonstrate the value in applying experimental approaches to identify mineral precipitation/dissolution reactions that may significantly impact reservoir performance. The good agreement between geochemical models and experimental results provides confidence that numerical models can be applied to screen the potential fluid-mineral and fluid-mixing reactions in unconventional reservoirs that result in undesired mineral scale precipitation.

58 GEOSCIENCES↗

Superconducting metamaterials - the first step toward a microwave quantum bus

Coherent manipulation of quantum states is at the core of quantum information science (QIS). Many state-of-the-art quantum systems rely on microwave fields for quantum operations. As such, the microwave electromagnetic fields serve as the ideal "quantum bus" to integrate different types of QIS systems into a hybrid quantum system. Superconducting metamaterials are artificial materials consisting of arrays of superconducting resonant microstructures with sizes much smaller than the microwave wavelengths of interest. Superconducting metamaterials are a strong candidate medium for the microwave quantum bus, because the effective impedance, field distributions, and frequency response can all be controlled by engineering the microstructures, electrical bias, and magnetic flux while maintaining extremely low loss. In this project, we investigate the fundamental unit of a superconducting metamaterial - a resonator with physical dimensions much smaller than the microwave wavelengths - using NbTiN as the working superconductor, whose high operating temperatures and magnetic fields are desirable attributes for compatibility with a wide variety of quantum systems. We first studied the properties of sputtered NbTiN thin films by correlating the film thickness with the normal state resistivity, superconducting transition temperature, and resonances of transmission line resonators made from these films. We developed a process flow and designed a coplanar waveguide platform for studying small resonators. The platform significantly shortens the turnaround times of the resonator fabrication and testing cycles. Several resonators with different designs were fabricated and tested at 4 Kelvin. Resonances were observed in some resonator testers. Potential paths for improvements and future directions are discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Microfabricated ion trap chip with an integrated microwave antenna

An ion trap chip, which may be used for quantum information processing and the like, includes an integrated microwave antenna. The antenna is formed as a radiator connected by one of its ends to the center trace of a microwave transmission line and connected by its other end to a current return path through a ground trace of the microwave transmission line. The radiator includes several parallel, coplanar radiator traces connected in series. The radiator traces are connected such that they all carry electric current in the same direction, so that collectively, they simulate a single, unidirectionally flowing sheet of current. In embodiments, induced currents in underlying metallization planes are suppressed by parallel slots that extend in a direction perpendicular to the radiator traces.

Nordquist, Christopher↗

Incorporating dynamic recrystallization into a crystal plasticity model for high-temperature deformation of Ti-6Al-4V

During hot deformation of (α + β) titanium alloys, the simultaneous action of strain and temperature in the (α + β) regime facilitates dynamic recovery, dynamic recrystallization (DRX), and phase transformations via non-equilibrium paths. DRX is manifested in the form of fine recrystallized α or β grains. Here, in the present study, a two-phase crystal plasticity finite element framework (CP-DRX) has been developed which incorporates DRX kinetics into the crystal plasticity (CP) model to predict the flow characteristics of Ti-6Al-4V alloys during thermo-mechanical processing. The CP slip system parameters, as well as elastic properties from both α and β phases of Ti, are calibrated for different strain rate conditions. An EBSD-informed two-phase microstructure representation has been utilized in the CP-DRX framework to explore the time-dependent evolution of DRX microstructure and crystal orientation for different strain rate conditions. The proposed CP-DRX can capture the evolution of crystal orientation and plastic flow stress–strain response of polycrystalline Ti-6Al-4V during the deformation process. Furthermore, the proposed model is able to capture the softening behavior, observed in average stress–strain response from experiments performed using a Gleeble thermomechanical simulator and predict the recrystallization texture.

(α+ β)-Titanium (Ti) Alloys↗

Pyomo.GDP: an ecosystem for logic based modeling and optimization development

We present three core principles for engineering-oriented integrated modeling and optimization tool sets—intuitive modeling contexts, systematic computer-aided reformulations, and flexible solution strategies—and describe how new developments in Pyomo.GDP for Generalized Disjunctive Programming (GDP) advance this vision. We describe a new logical expression system implementation for Pyomo.GDP allowing for a more intuitive description of logical propositions. The logical expression system supports automated reformulation of these logical constraints to linear constraints. We also describe two new logic-based global optimization solver implementations built on Pyomo.GDP that exploit logical structure to avoid “zero-flow” numerical difficulties that arise in nonlinear network design problems when nodes or streams disappear. These new solvers also demonstrate the capability to link to external libraries for expanded functionality within an integrated implementation. We present these new solvers in the context of a flexible array of solution paths available to GDP models. Finally, we present results on a new library of GDP models demonstrating the value of multiple solution approaches.

42 ENGINEERING↗