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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

𝑁-dimensional maximum-entropy tomography via particle sampling

We propose a modified maximum-entropy (MENT) algorithm for six-dimensional phase space tomography. The algorithm uses particle sampling and low-dimensional density estimation to approximate large sets of high-dimensional integrals in the original MENT formulation. We implement this approach using Markov Chain Monte Carlo (MCMC) sampling techniques and demonstrate convergence of six-dimensional MENT on both synthetic and measured data.

Hoover, Austin [Oak Ridge National Laboratory (ORN↗
DOE OSTI2025

A Cost-Effective Wave Energy Harvesting System with Maximum Power Point Tracking Capability

In this paper, we propose a low-cost bidirectional four-switch inverter that transfers three-phase energy between a permanent magnet synchronous generator (PMSG) driven by a wave energy collector and the power grid or a local ac load. To achieve high control performance, the machine-side inverter uses a high-gain observer for rotor position estimation and a Lyapunov-based approach for torque control. For the gridside inverter control, we estimate the filter capacitor voltage with a model reference adaptive system and control the dc-link voltage with a Lyapunov-based energy function. We also track the maximum power point from the sea waves with an integral control law that actively matches the generator impedance with that of the wave collection device. The proposed system supports both grid-following/forming modes. We validate our control design with simulation results on a 3-kW hardware setup.

wave energy, power systems integration, control de↗
DOE OSTI2023

A Modified Maximum Entropy Inverse Reinforcement Learning Approach for Microgrid Energy Scheduling

Increasing popularity of integrating distributed energy resources (DERs) into the power system brings a challenge to optimize the microgrid dispatch policy. The reinforcement learning methods suffer from a long-time problem with the theoretical assumption of the objective/reward function for the microgrid system. Although the traditional inverse reinforcement learning (IRL) approaches can solve this problem to some extent, they encounter a limitation of complex computations for state visitation frequency in the large and continuous state space. To alleviate this limitation, we propose a modified maximum entropy IRL (MMIRL) method to extract the reward function from the expert demonstrations for solving the microgrid energy scheduling problem. The proposed MMIRL algorithm is promising in recovering the reward function and learning the dispatch policy compared to conventional approaches. Case studies are performed in an energy arbitrage problem and a microgrid system with DERs. Results substantiate that the proposed MMIRL approach can learn the dispatch policy with more than 99% efficiency and outperforms other comparative methods.

artificial intelligence, reinforcement learning, m↗
DOE OSTI2025

Evaluation of Maximum Allowable Working Pressure and Svensson Burst Pressure Recommended in API 579-1 2021 Edition

Abstract API 579-1/ASME FFS-1 2021 Edition provides the minimum wall thickness, the maximum allowable working pressure (MAWP), and the membrane stress equations for thin and thick-walled cylindrical shells subject to internal pressure in Section 2C.3.3.1 of Appendix 2C – Thickness, MAWP, and Stress Equations for an FFS Assessment. The minimum wall thickness and MAWP are determined using the hoop stress and the Tresca yield criterion. Section 2C.7 – Estimation of Burst Pressure newly added the Svensson method for calculating burst pressure of cylindrical shells under internal pressure, where the plastic yielding is characterized by the von Mises yield criterion. For thin-walled cylinders, the von Mises flow solution of burst pressure in Equation (2C.179) was recommended. For thick-walled cylinders, an implicit burst pressure solution in an integral equation (2C.176) was recommended. But this integral equation is inconvenient to use in practice. It is well known that the classic plasticity theory includes the Tresca and von Mises yield criteria, with the Tresca criterion predicting a lower bound solution and the von Mises criteria predicting an upper bound solution. In addition, the present author developed an average shear stress yield criterion that can determine more accurate limit and burst pressures for thin and thick-walled cylinders. This work uses these three yield criteria to evaluate the minimum required wall thickness, MAWP and Svensson burst pressure recommended in the API 579 code.

burst pressure↗
DOE OSTI2022

Maximum strength and dislocation patterning in multi–principal element alloys

Multi–principal element alloys (MPEAs) containing three or more components in high concentrations render a tunable chemical short-range order (SRO). Leveraging large-scale atomistic simulations, we probe the limit of Hall-Petch strengthening and deformation mechanisms in a model CrCoNi alloy and unravel chemical ordering effects. The presence of SRO appreciably increases the maximum strength and lowers the propensity for faulting and structure transformation, accompanied by intensification of planar slip and strain localization. Deformation grains exhibit notably different microstructures and dislocation patterns that prominently depend on their crystallographic orientation and the number of active slip planes. Grain of single-planar slip attains the highest volume fraction of deformation-induced structure transformation, and grain with double-slip planes develops the densest dislocation network. These results advancing the fundamental understanding of deformation mechanisms and dislocation patterning in MPEAs suggest a mechanistic strategy for tuning mechanical behavior through simultaneously tailoring grain texture and local chemical order.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Quantum optimization of maximum independent set using Rydberg atom arrays

Realizing quantum speedup for practically relevant, computationally hard problems is a central challenge in quantum information science. Using Rydberg atom arrays with up to 289 qubits in two spatial dimensions, we experimentally investigate quantum algorithms for solving the maximum independent set problem. We use a hardware-efficient encoding associated with Rydberg blockade, realize closed-loop optimization to test several variational algorithms, and subsequently apply them to systematically explore a class of graphs with programmable connectivity. We find that the problem hardness is controlled by the solution degeneracy and number of local minima, and we experimentally benchmark the quantum algorithm’s performance against classical simulated annealing. On the hardest graphs, we observe a superlinear quantum speedup in finding exact solutions in the deep circuit regime and analyze its origins.

Science & Technology - Other Topics↗
DOE OSTI2023

Offshore-onshore record of Last Glacial Maximum–to–present grounding line retreat at Pine Island Glacier, Antarctica

Pine Island Glacier, West Antarctica, is the largest Antarctic contributor to global sea-level rise and is vulnerable to rapid retreat, yet our knowledge of its deglacial history since the Last Glacial Maximum is based largely on marine sediments that record a retreat history ending in the early Holocene. Using a suite of 10 Be exposure ages from onshore glacial deposits directly adjacent to Pine Island Glacier, we show that this major glacier thinned rapidly in the early to mid-Holocene. Our results indicate that Pine Island Glacier was at least 690 m thicker than present prior to ca. 8 ka. We infer that the rapid thinning detected at the site farthest downstream records the arrival and stabilization of the retreating grounding line at that site by 8–6 ka. By combining our exposure ages and the marine record, we extend knowledge of Pine Island Glacier retreat both spatially and temporally: to 50 km from the modern grounding line and to the mid-Holocene, providing a data set that is important for future numerical ice-sheet model validation.

58 GEOSCIENCES↗
DOE OSTI2023

Extending the predictive power of perturbative QCD using the principle of maximum conformality and the Bayesian analysis

In addition to the evaluation of high-order loop contributions, the precision and predictive power of perturbative QCD (pQCD) predictions depends on two important issues: (1) how to achieve a reliable, convergent fixed-order series, and (2) how to reliably estimate the contributions of unknown higher-order terms. The recursive use of renormalization group equation, together with the Principle of Maximum Conformality (PMC), eliminates the renormalization scheme-and-scale ambiguities of the conventional pQCD series. The result is a conformal, scale-invariant series of finite order which also satisfies all of the principles of the renormalization group. In this paper we propose a novel Bayesian-based approach to estimate the size of the unknown higher order contributions based on an optimized analysis of probability distributions. We show that by using the PMC conformal series, in combination with the Bayesian analysis, one can consistently achieve high degree of reliability estimates for the unknown high order terms. Thus the predictive power of pQCD can be greatly improved. We illustrate this procedure for two pQCD observables: R e+e– and R τ , which are each known up to four loops in pQCD. Numerical analyses confirm that by using the scale-independent and more convergent PMC conformal series, one can achieve reliable Bayesian probability estimates for the unknown higher-order contributions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Advances for QCD and the standard model: color-confining light-front holography and the principle of maximum conformality

Here, I review how the application of superconformal quantum mechanics and light-front holography leads to new insights into the physics of color confinement, the spectroscopy and dynamics of hadrons, as well as surprising supersymmetric relations between the masses of mesons, baryons, and tetraquarks. Spontaneous chiral symmetry breaking is automatically fulfilled by supersymmetric Light-Front QCD. The light-front holographic approach (HLFQCD) also predicts the behavior of the QCD running coupling and other observables from the nonperturbative color-confining domain to the perturbative domain. One can determine the QCD running coupling to high precision from the data of just a single experiment over the entire perturbative regime by using the Principle of Maximum Conformality (PMC). The PMC, which generalizes the conventional Gell-Mann-Low method for scale-setting in perturbative QED to non-Abelian QCD, provides a rigorous method for achieving unambiguous scheme-independent, fixed-order Standard Model predictions, consistent with the principles of the renormalization group. I also briefly review a novel feature of hadronic physics predicted by QCD: intrinsic heavy quarks.

Brodsky, Stanley J. [SLAC National Accelerator Lab↗
DOE OSTI2025

Dataset for manuscript "Equipartition and the temperature of maximum density of TIP4P/2005 water"

We simulate TIP4P/2005 water in the temperature range of 257 K to 318 K with time-steps 0.25, 0.50, 1.00, 2.00, and 4.00 fs. The density-temperature behavior obtained using 0.25 or 0.50 fs are in excellent agreement with each other but differ from those obtained using time-steps that have been shown earlier to lead to a breakdown of equipartition. The temperature of maximum density (TMD) is 277.15 K with time-step 0.25 or 0.50 fs, but is shifted to progressively lower values for longer time-steps, a trend that holds for different thermostat/barostat combinations. Enhancing the water-water dispersion interaction, as has been recommended for simulating disordered proteins in TIP4P/2005, degrades the description of the liquid-vapor phase envelope. We present a simple physically transparent reasoning to highlight the separation of the time-scales between translational and rotational motion. We also develop a metric, Chi, that we term the equipartition anomaly, to detect equipartition violations in simulations that include molecules that are treated as rigid objects. Calculating Chi is shown to be straightforward and sensitive to equipartition violations. A key takeaway from this study is that using sufficiently short time-steps (less than or equal to 0.5 fs) to preserve equipartition is essential for obtaining meaningful liquid water properties and for producing reliable simulation data, as correct-ensemble sampling is fundamental to ensure reproducibility across codes and simulation alogrithms. The included dataset provides the raw data used in the preparation of the graphs noted in the manuscript.

36 MATERIALS SCIENCE↗
DOE OSTI2022

PMC$_\infty$: Infinite-Order Scale-Setting method using the Principle of Maximum Conformality and preserving the Intrinsic Conformality

We show results for Thrust and C-parameter in e^+ e^- e + e − annihilation to 3 jets obtained using the recently developed new method for eliminating the scale ambiguity and the scheme dependence in pQCD namely the Infinite-Order Scale-Setting method using the Principle of Maximum Conformality (PMC _\infty ∞ ). This method preserves an important underlying property of gauge theories: intrinsic Conformality (iCF). It leads to a remarkably efficient method to eliminate the conventional renormalization scale ambiguity at any order in pQCD. A comparison with Conventional Scale Setting method (CSS) is also shown.

Di Giustino, Leonardo↗
DOE OSTI2020

Effects of increasing the initial nitric acid concentration from a maximum of 7.5 to 8.5 M during the dissolution of aluminum spent nuclear fuel

H-Canyon is blending solutions from the dissolution of High Flux Isotope Reactor (HFIR) and Material Test Reactor (MTR) fuels with Target Residue Material (TRM) to prepare feed solution for the 1st Cycle of solvent extraction. The initial acid concentration for HFIR fuel dissolution is limited to 7.5 M by the flowsheet; however, an increase in the initial concentration is desirable to more easily achieve the target acidity for solvent extraction using the current blending strategy. To provide flexibility in batching the highly enriched uranium (HEU) solutions, the Savannah River National Laboratory (SRNL) was requested to evaluate the potential for increasing the maximum HNO3 concentration for HFIR fuel dissolution from 7.5 to 8.5 M. In response to this request, a literature review was performed to evaluate the impact of a higher starting HNO3 concentration on the dissolution of aluminum spent nuclear fuels (ASNF) including both HFIR and MTR fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Accelerated Basin De-Inventory Maximum Fissile Estimate

The Accelerated Basin De-inventory (ABD) program increases processing of Spent Nuclear Fuel (SNF) in H-Canyon to accelerate the closure of L Basin. The dissolved SNF will be dispositioned to Sludge Batches that will be processing in the Defense Waste Processing Facility and converted to glass. The fissile glass loading directly impacts the amount of glass canisters made. This memorandum provides an estimated maximum quantity of total fissile expected to be transferred to a Sludge Batch to support increasing the fissile glass loading and thus reducing the number of canisters created across the lifetime of the ABD mission.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Thermal Calculations to Determine Maximum Zircaloy Temperatures During Reactor Operations for Campaign 1 Fuel Assemblies

The H-Canyon Facility plans on processing bundles from Non-Aluminum Spent Nuclear Fuel (NASNF) Risk Group 1 (UO 2 core fuels). Uranium-zirconium (UZr) alloys and zirconium clad UO 2 fuel containing UZr intermetallic compound have the potential to cause explosions during dissolution. UZr intermetallic typically only forms when uranium and zirconium (or zirconium alloy) cladding are in contact at high temperatures. Thermal modeling was performed to determine the maximum cladding temperature for Campaign 1 Zircoloy cladded fuel assembles during reactor operation to help determine if the UZr intermetallic compound could have formed during reactor operations. The temperature of 350°C was chosen as a conservative minimum value for the possible formation of intermetallic UZr compound. The modeling approach, inputs, and results are outlined in this document.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

A Latent-Variable Formulation of the Poisson Canonical Polyadic Tensor Model: Maximum Likelihood Estimation and Fisher Information

We establish parameter inference for the Poisson canonical polyadic (PCP) tensor model through a latent-variable formulation. Our approach exploits the observation that any random PCP tensor can be derived by marginalizing an unobservable random tensor of one dimension larger. The loglikelihood of this larger dimensional tensor, referred to as the “complete” loglikelihood, is comprised of multiple rank one PCP loglikelihoods. Using this methodology, we first derive maximum likelihood estimators for the PCP model and demonstrate that several existing algorithms for fitting non-negative matrix and tensor factorizations are Expectation-Maximization algorithms. Next, we derive the observed and expected Fisher information matrices for the PCP model. The Fisher information provides us crucial insights into the well-posedness of the tensor model, such as the role that tensor rank plays in identifiability and indeterminacy. For the special case of rank one PCP models, we demonstrate that these results are greatly simplified.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Use of Digital Real-Time Simulation and Optimization to Identify Maximum Real Power Injection on Banshee Distribution Network

This study investigates the hosting capacity of the Banshee Distribution Network by optimizing the real power injection at carefully selected Distributed Energy Resource (DER) locations. The analysis is conducted within the framework of power system operational constraints, including bus voltage ranges, thermal line ratings, and transformer loading limits. A Python-based Genetic Algorithm (GA), implemented using the PyGAD library, is employed to iteratively identify the optimal power injection configuration that maximizes network utilization while preserving system reliability. The methodology integrates a real-time simulation environment using the Real-Time Digital Simulator (RTDS), allowing high-fidelity evaluation of power flow and voltage behavior under each proposed injection scenario. By coupling the optimization algorithm with real-time simulation feedback, this approach ensures that both static and dynamic constraints are enforced during the evaluation process. The GA leverages evolutionary operators such as selection, crossover, and mutation to navigate the nonlinear search space efficiently. The results of the study delineate the feasible hosting capacity at three targeted buses, reflecting maximum real power levels that can be injected without causing voltage violations, transformer overloading, or line congestion. These findings provide a decision- support tool for distribution planners and utilities aiming to integrate higher penetrations of DERs in existing infrastructure. Additionally, the work lays the foundation for extending such optimization techniques to multi-objective formulations, including economic dispatch and reactive power coordination, in future studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Pumped Thermal Energy Storage Using Low-Cost Particles and a Fluid Bed Heat Exchanger for Maximum Power Efficiency

Robust, efficient, cost-effective long-duration electricity storage (LDES) solutions can enhance grid resiliency, support existing transmission and distribution infrastructure, and enable a greater share of low-cost, variable alternative energy sources to penetrate the market. To meet this need, the project team at the National Renewable Energy Laboratory developed a transformative LDES system based on pumped thermal energy storage (TES) using low-cost particles and a fluid bed heat exchanger for maximum power efficiency (PUMP). The PUMP system is composed of high-temperature, low-cost particle TES coupled with an advanced pressurized fluid bed heat exchanger (PFB HX) that supports a high-efficiency pumped thermal energy storage (PTES) system integrated with concentrating solar thermal power (CSP). The PUMP project developed and de-risked a PFB HX and particle CSP system intended to be integrated with reversible turbomachinery and a modeling tool to assess PTES cost and performance.

14 SOLAR ENERGY↗