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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 37 records · Page 2
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DOE OSTI2024

Extended Fayans energy density functional: optimization and analysis

The Fayans energy density functional (EDF) has been very successful in describing global nuclear properties (binding energies, charge radii, and especially differences of radii) within nuclear density functional theory. In a recent study, supervised machine learning methods were used to calibrate the Fayans EDF. Building on this experience, in this work we explore the effect of adding isovector pairing terms, which are responsible for different proton and neutron pairing fields, by comparing a 13D model without the isovector pairing term against the extended 14D model. At the heart of the calibration is a carefully selected heterogeneous dataset of experimental observables representing ground-state properties of spherical even–even nuclei. To quantify the impact of the calibration dataset on model parameters and the importance of the new terms, we carry out advanced sensitivity and correlation analysis on both models. The extension to 14D improves the overall quality of the model by about 30%. The enhanced degrees of freedom of the 14D model reduce correlations between model parameters and enhance sensitivity.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Bayesian calibration of viscous anisotropic hydrodynamic simulations of heavy-ion collisions

Owing to large pressure gradients at early times, standard hydrodynamic model simulations of relativistic heavy-ion collisions do not become reliable until O(1) fm/c after the collision. To address this one often introduces a prehydrodynamic stage that models the early evolution microscopically, typically as a conformal, weakly interacting gas. In such an approach the transition from the prehydrodynamic to the hydrodynamic stage is discontinuous, introducing considerable theoretical model ambiguity. Alternatively, fluids with large anisotropic pressure gradients can be handled macroscopically using the recently developed viscous anisotropic hydrodynamics (VAH). In high-energy heavy-ion collisions VAH is applicable already at very early times, and at later times transitions smoothly into conventional second-order viscous hydrodynamics. Here we present a Bayesian calibration of the VAH model with experimental data for Pb-Pb collisions at the LHC at $\sqrt{^{S}NN}$ = 2.76 A TeV. We find that the VAH model has the unique capability of constraining the specific viscosities of the quark-gluon plasma at higher temperatures than other previously used models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Reanalysis of the 𝛽− $\overline{v}$ 𝑒 Angular Correlation Measurement from the aSPECT Experiment with New Constraints on Fierz Interference

On the basis of revisions of some of the systematic errors, we reanalyzed the electron-antineutrino angular correlation (𝑎 coefficient) in free neutron decay inferred from the recoil energy spectrum of the protons which are detected in 4⁢𝜋 by the aSPECT spectrometer. With 𝑎=−0.104 02⁢(82), the new value differs only marginally from the one published in 2020. Here, the experiment also has sensitivity to 𝑏, the Fierz interference term. From a correlated (𝑏,𝑎) fit to the proton recoil spectrum, we derive a limit of 𝑏 =−0.0098⁢(193) which translates into a somewhat improved 90% confidence interval region of −0.041 ≤ 𝑏 ≤ 0.022 on this hypothetical term. Tighter constraints on 𝑏 can be set from a combined analysis of the PERKEO III (𝛽 asymmetry) and aSPECT measurement which suggests a finite value of 𝑏 with 𝑏 (𝑐) =−0.0181 ± 0.0065 deviating by 2.82⁢𝜎 from the standard model.

Beta decay↗
DOE OSTI2021

Parallelized POD-based suboptimal economic model predictive control of a state-constrained Boussinesq approximation

Motivated by an energy efficient building application, we want to optimize a quadratic cost functional subject to the Boussinesq approximation of the Navier-Stokes equations and to bilateral state and control constraints. Since the computation of such an optimal solution is numerically costly, we design an efficient strategy to compute a sub-optimal (but applicationally acceptable) solution with significantly reduced computational effort. We employ an economic Model Predictive Control (MPC) strategy to obtain a feedback control. The MPC sub-problems are based on a linear-quadratic optimal control problem subjected to mixed control and state constraints and a convection-diffusion equation, reduced with proper orthogonal decomposition. Finally, to solve each sub-problem, we apply a primal-dual active set strategy. The method can be fully parallelized, which enables the solution of large problems with real-world parameters.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Deep learning of free boundary and Stefan problems

Free boundary problems appear naturally in numerous areas of mathematics, science and engineering. These problems present a great computational challenge because they necessitate numerical methods that can yield an accurate approximation of free boundaries and complex dynamic interfaces. In this work, we propose a multi-network model based on physics-informed neural networks to tackle a general class of forward and inverse free boundary problems called Stefan problems. Specifically, we approximate the unknown solution as well as any moving boundaries by two deep neural networks. Besides, we formulate a new type of inverse Stefan problems that aim to reconstruct the solution and free boundaries directly from sparse and noisy measurements. We demonstrate the effectiveness of our approach in a series of benchmarks spanning different types of Stefan problems, and illustrate how the proposed framework can accurately recover solutions of partial differential equations with moving boundaries and dynamic interfaces. All code and data accompanying this manuscript are publicly available at https://github.com/PredictiveIntelligenceLab/DeepStefan.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Wind turbine response in waked inflow: A modelling benchmark against full-scale measurements

Predicting the power and loads of wind turbines in waked inflow conditions still presents a major modelling challenge. It requires the accurate modelling of the atmospheric flow conditions, wakes of upstream turbines and the response of the turbine of interest. Rigorous validations of model frameworks against measurements of utility-scale wind turbines in such scenarios remain limited to date. In this study, six models of different fidelity are compared against measurements from the DanAero experiment. The two benchmark cases feature a full-wake and partial-wake scenario, respectively. The simulations are compared against local pressure forces and inflow velocities measured on several blade sections of the downstream turbine, as well as met mast measurements and standard SCADA data. Regardless of the model fidelity, reasonable agreements are found in terms of the wake characteristics and turbine response. For instance, the azimuth variation of the mean aerodynamic forces acting on the blade was captured with a mean relative error of 15-20%. Additionally, while various model-specific deficiencies could be identified, the study highlights the need for further full-scale measurement campaigns with even more extensive instrumentation. Furthermore, it is concluded that validations should not be limited to integrated and/or time-averaged quantities that conceal characteristic spatial or temporal variations.

17 WIND ENERGY↗
DOE OSTI2022

Numerical investigation of thermomechanical response of multiscale porous Ultra-High Temperature Ceramics

Recent advances in Ultra-High Temperature Ceramics (UHTC) manufacturing have permitted the development of multiscale porous UHTC microstructures. Within the target application of hypersonic vehicles, dense UHTCs are suitable for thermal protection on leading edges, whereas porous UHTCs may find a role in providing thermally insulated interfaces for temperature-sensitive interior components. Designing vehicles incorporating porous UHTCs requires a characterization of their thermomechanical properties across the full range of expected operating temperatures spanning –20 °C–2500 °C. This research represents a preliminary study in performing this characterization. Several numerical experiments are performed using a coupled thermomechanical implementation of the Material Point Method to determine the temperature dependence of effective material properties both with and without damage. Furthermore, complex time-dependent boundary conditions derived from known hypersonic flight profiles are simulated in order to probe the various couplings between deformation, damage and heat transfer. It is shown that the model reveals the importance of micro-buckling in determining effective material stiffness and thermal conductivity.

36 MATERIALS SCIENCE↗