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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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DOE OSTI2024

Skeletal reaction models for methane combustion

A local-sensitivity-analysis technique is employed to generate new skeletal reaction models for methane combustion from the foundational fuel chemistry model (FFCM-1). Here, the sensitivities of the thermo-chemical variables with respect to the reaction rates are computed via the forced-optimally time dependent (f-OTD) methodology. In this methodology, the large sensitivity matrix containing all local sensitivities is modeled as a product of two low-rank time-dependent matrices. The evolution equations of these matrices are derived from the governing equations of the system. The modeled sensitivities are computed for the auto-ignition of methane at atmospheric and high pressures with different sets of initial temperatures, and equivalence ratios. These sensitivities are then analyzed to rank the most important (sensitive) species. A series of skeletal models with different number of species and levels of accuracy in reproducing the FFCM-1 results are suggested. The performances of the generated models are compared against FFCM-1 in predicting the ignition delay, the laminar flame speed, and the flame extinction. The results of this comparative assessment suggest the skeletal models with 24 and more species generate the FFCM-1 results with an excellent accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Revenue prediction for integrated renewable energy and energy storage system using machine learning techniques

Revenue estimation for integrated renewable energy and energy storage systems is important to support plant owners or operators’ decisions in battery sizing selection that leads to maximized financial performances. A common approach to optimizing revenues of a hybrid hydro and energy storage system is using mixed-integer linear programming (MILP). Although MILP models can provide accurate production cost estimations, they are typically very computationally expensive. To provide a fast yet accurate first-step information to hydropower plant owners or operators who consider integrating energy storage systems, we propose an innovative approach to predicting optimal revenues of an integrated energy generation and storage system. In this study, we examined the performance of two prediction techniques: Generalized Additive Models (GAMs) and machine learning (ML) models developed based on artificial neural networks (ANN). Predictive equations and models are generated based on optimized solutions from a market participation optimization model, the Conventional Hydropower Energy and Environmental Resource System (CHEERS) model. The two predicting techniques reduce the computational time to evaluate annual revenue for one set of battery configurations from 3 h to 1 to 4 min per run while also being implementable with significantly less data. The model validation prediction errors of developed GAMs and ML models are generally below 5%; for model testing predictions, the ML models consistently outperform the regression equations in terms of root mean square errors. This new approach allows plant owners, operators, or potential investors to quickly access multiple battery configurations under different energy generation and market scenarios. This new revenue prediction method will therefore help reduce the barriers, and thereby promoting the deployment of battery hybridization with existing renewable energy sources.

13 HYDRO ENERGY↗

DOE OSTI2021

On the Symmetry of Blast Waves

This paper presents a brief historical review of G. I. Taylor’s solution of the point blast wave problem which was applied to the Trinity test of the first atomic bomb. Lie group symmetry techniques (also referred to throughout this paper as geometric techniques) are used to derive Taylor’s famous two-fifths law that relates the position of a blast wave to the time after the explosion and the total energy released. The theory of exterior differential systems is combined with the method of characteristics to demonstrate that the solution of the blast wave problem is directly related to the basic relationships that exist between the symmetry (or geometry) and the physics of wave propagation through the equations of motion. The point blast wave model is cast in terms of two exterior differential systems, and both systems are shown to be integrable with local solutions for the velocity, pressure, and density along curves in space and time behind the blast wave. This work is dedicated to the memory of Professor Roy Axford, who introduced many of his students to the topic of symmetry analysis of differential equations.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2024

Towards accelerating particle-resolved direct numerical simulation with neural operators

In this paper, we present our ongoing work aimed at accelerating a particle-resolved direct numerical simulation model designed to study aerosol–cloud–turbulence interactions. The dynamical model consists of two main components—a set of fluid dynamics equations for air velocity, temperature, and humidity, coupled with a set of equations for particle (i.e., cloud droplet) tracing. Rather than attempting to replace the original numerical solution method in its entirety with a machine learning (ML) method, we consider developing a hybrid approach. We exploit the potential of neural operator learning to yield fast and accurate surrogate models and, in this study, develop such surrogates for the velocity and vorticity fields. We discuss results from numerical experiments designed to assess the performance of ML architectures under consideration as well as their suitability for capturing the behavior of relevant dynamical systems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Fast All-sky Radiation Model for Solar applications (FARMS) [SWR-16-18]

The Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute cloudy irradiance. Radiative transfer (RT) models simulating broadband solar radiation have been widely used by atmospheric scientists to model solar resources for various energy applications such as operational forecasting. Due to the complexity of solving the RT equation, the computation under cloudy conditions can be extremely time consuming though many approximations (e.g. two-stream approach and delta-M truncation scheme) have been utilized. Thus, a more efficient RT model is crucial for model developers as a new option for approximating solar radiation at the land surface with minimal loss of accuracy. We have developed a fast all-sky radiation model for solar applications (FARMS) using the simplified clear-sky RT model, REST2, and simulated cloud transmittances and reflectances from the Rapid Radiation Transfer Model (RRTM) with a sixteen-stream Discrete Ordinates Radiative Transfer (DISORT). Simulated lookup tables (LUTs) of cloud transmittances and reflectances were created by varying cloud optical thicknesses, cloud particle sizes, and solar zenith angles. Equations with optimized parameters were fitted to the cloud transmittances and reflectances to develop the model. Using this model the all-sky solar irradiance at the land surface can be computed rapidly by combining REST2 with the cloud transmittances and reflectances. This new RT model is more than 1000 times faster than those currently utilized in solar resource assessment and forecasting since it does not explicitly solve the RT equation for each individual cloud condition. Our results indicate the accuracy of the fast radiative transfer model is comparable to or better than two-stream approximation in term of computing cloud transmittance and solar radiation.

Xie, Yu↗

DOE OSTI2023

Fast All-sky Radiation Model for Solar applications (FARMS) 2023 [SWR-16-18]

Xie, Yu↗

DOE OSTI2025

Mapping Incidence and Prevalence Peak Data for SIR Modeling Applications

Infectious disease modeling and forecasting have played a key role in helping assess and respond to epidemics and pandemics. Recent work has leveraged data on disease peak infection and peak hospital incidence to fit compartmental models for the purpose of forecasting and describing the dynamics of a disease outbreak. Incorporating these data can greatly stabilize a compartmental model fit on early observations, where slight perturbations in the data may lead to model fits that forecast wildly unrealistic peak infection. We introduce a new method for incorporating historic data on the value and time of peak incidence of hospitalization into the fit for a Susceptible-Infectious-Recovered (SIR) model by formulating the relationship between an SIR model’s starting parameters and peak incidence as a system of two equations that can be solved computationally. We demonstrate how to calculate SIR parameter estimates – which describe disease dynamics such as transmission and recovery rates – using this method, and determine that there is a noticeable loss in accuracy whenever prevalence data is misspecified as incidence data. To exhibit the modeling potential, we update the Dirichlet-Beta State Space modeling framework to use hospital incidence data, as this framework was previously formulated to incorporate only data on total infections. This approach is assessed for practicality in terms of accuracy and speed of computation via simulation.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

The context dependence of physics identity: Examining the role of performance/competence, recognition, interest, and sense of belonging for lower and upper female physics undergraduates

Abstract While there is a growing body of work that examines disciplinary identity development, unlike qualitative work in this area, quantitative research has not fully incorporated the importance of different contexts, nor has it uniquely focused on underrepresented groups (in this case, women in physics). This study examines how the constructs posited by prior work as important for physics identity, as well as an additional theorized construct, may interrelate and affect female students' physics identity differently depending on the context. Context in this study refers to two different experiential levels in college. The constructs examined include performance/competence, recognition, and interest, as well as sense of belonging. In particular, we used structural equation modeling to examine the effect that these constructs have on the physics identity of two groups of female physics undergraduates: first year students and senior year students. The results reveal that the relationship of the theorized constructs with physics identity vary between the two groups as well as compared to prior research with broad college student populations (not just physics majors). Unlike broad college student populations, for our sample of female physics undergraduates, interest did not have a direct effect on physics identity while sense of belonging was significant only for senior year students. These results exemplify the importance of examining context or different types of student experiences when studying disciplinary identity development rather than generalizing previous frameworks to all contexts.

Hazari, Zahra↗

DOE OSTI2025

DOE-ICoM/RIFT

Rapid Infrastructure Flood Tool (RIFT) is a two-dimensional hydrodynamic model based on the complete shallow water equations. RIFT has specifically been designed with rapid simulation in mind by utilizing commodity high performance computing technology and best-available nation-wide data. RIFT is used to predict the movement of water over land and resolve the spatial and temporal variability of flood depths, extent, and velocity. RIFT can be applied to many flood situations and has primarily been used to quantify flood extents from dam/levee failure or inland rainfall flooding.

Perkins, Bill [Pacific Northwest National Laborato↗

DOE OSTI2023

MAGNET Scaling and Methodology

The purpose of this study was to analyze the heat transfer of the Microreactor Agile Non-nuclear Experimental Testbed (MAGNET) within the Dynamic Energy Transport and Integration Laboratory (DETAIL) and develop scaling equations and models to couple with other systems. Hierarchical Two-Tiered Scaling (H2TS) methodologies were applied to DETAIL’s MAGNET facility to scale and project data sets while conserving the observed behavior based on first principles. The MAGNET system was successfully scaled using H2TS and multiple system parameters were determined or calculated from experimental data including steady state and transient data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

A fourth-order phase-field fracture model: Formulation and numerical solution using a continuous/discontinuous Galerkin method

Modeling crack initiation and propagation in brittle materials is of great importance to be able to predict sudden loss of load-carrying capacity and prevent catastrophic failure under severe dynamic loading conditions. Second-order phase-field fracture models have gained wide adoption given their ability to capture the formation of complex fracture patterns, e.g. via crack merging and branching, and their suitability for implementation within the context of the conventional finite element method. Higher-order phase-field models have also been proposed to increase the regularity of the exact solution and thus increase the spatial convergence rate of its numerical approximation. However, they require special numerical techniques to enforce the necessary continuity of the phase field solution. In this paper, we derive a fourth-order phase-field model of fracture in two independent ways; namely, from Hamilton’s principle and from a higher-order micromechanics-based approach. The latter approach is novel, and provides a physical interpretation of the higher-order terms in the model. In addition, we propose a continuous/discontinuous Galerkin (C/DG) method for use in computing the approximate phase-field solution. This method employs Lagrange polynomial shape functions to guarantee -continuity of the solution at inter-element boundaries, and enforces the required regularity with the aid of additional variational and interior penalty terms in the weak form. Finally, the phase-field equation is coupled with the momentum balance equation to model dynamic fracture problems in hyper-elastic materials. Two benchmark problems are presented to compare the numerical behavior of the C/DG method with mixed finite element methods.

42 ENGINEERING↗

DOE OSTI2022

Nonlinear quantum behavior of ultrashort-pulse optical parametric oscillators

The quantum features of ultrashort-pulse optical parametric oscillators (OPOs) are investigated theoretically in the nonlinear regime near and above threshold. Viewing the pulsed OPO as a multimode open quantum system, we rigorously derive a general input-output model that features nonlinear coupling among many cavity (i.e., system) signal modes and a broadband single-pass (i.e., reservoir) pump field. Under appropriate assumptions, our model produces a Lindblad master equation with multimode nonlinear Lindblad operators describing two-photon dissipation and a multimode four-wave-mixing Hamiltonian describing a broadband, dispersive optical cascade, which we show is required to preserve causality. To simplify the multimode complexity of the model, we employ a supermode decomposition to perform numerical simulations in the regime where the pulsed supermodes experience strong single-photon nonlinearity. We find that the quantum nonlinear dynamics induces pump depletion as well as corrections to the below-threshold squeezing spectrum predicted by linearized models. We also observe the formation of non-Gaussian states with Wigner-function negativity and show that the multimode interactions with the pump, both dissipative and dispersive, can act as effective decoherence channels. Finally, we briefly discuss some experimental considerations for potentially observing such quantum nonlinear phenomena with ultrashort-pulse OPOs on nonlinear nanophotonic platforms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

A phase-field method for boiling heat transfer

Here we present a phase field method for heat transfer in two-phase flow with boiling. The vapor/liquid interface evolution is modeled by the Cahn-Hilliard equation. The phase change rate is determined by accounting for the heat conduction balance on either vapor or liquid side of the interfacial area, depending on which side the temperature is assumed to be maintained at the saturation temperature during boiling. The velocity correction scheme proposed by Dong & Shen [27] is extended to solve the Navier-Stokes equations for a non-solenoidal velocity field, and the entropy viscosity method is employed for stabilization. The phase change model is verified by two-dimensional simulations of a vapor bubble growing in super-heated liquid and in film boiling. In both cases, mesh independence of the results is systematically performed. Subsequently, the method is applied to predict the growth of three-dimensional vapor bubble in a rectangular microchannel with boiling flow, achieving good agreement with experimental measurements and available simulation results using the level-set method. The numerical experiments demonstrate that the required mesh resolution for the phase field method is comparable with that of volume of fluid (VoF) and level-set methods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Multiscale modeling for high burnup structure formation and associated pulverization

This report summarizes the lower length scale modeling work performed in the fiscal year 2023 under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to capture the microstrutural evolution and associated pulverization criteria in the high burnup regions. This year, the resolution mechanisms within the cluster dynamics code has been updated and it influence on the bubble growth in HBS regions at the mesoscale is studied. To improve the accuracy of phase-field models of fission gas bubble growth, a new Helmholtz free energy for high-density Xe gas is derived from a virial equation of state. Two previously used strategies for representing net vacancy production in phase-field models of fission gas bubble growth are compared with each other and with analytical models of bubble growth. The vacancy source only model is found to be more convenient to parameterize realistically compared with the vacancy source+sink model. Furthermore, the phase-field-fracture simulation have been performed using MD- informed failure stress values and realistic HBS structure obtained from the phase-field simulations. We also present the uncertainty bands on prediction of the critical stress to account for the effect of the lower length scale variabilities on the failure criteria at the mesoscale. It is observed that pulverization may occur in partially restructured regions with restructuring fraction as low as 17%. In light of this, an update to the BISON’s pulverization criteria is recommended.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Theoretical methods to design and test quantum simulators for the compact Abelian Higgs model

The lattice compact Abelian Higgs model is a nonperturbative regularized formulation of low-energy scalar quantum electrodynamics. In 1+1 dimensions, this model can be quantum simulated using a ladder-shaped optical lattice with Rydberg-dressed atoms. In this setup, one spatial dimension is used to carry the angular momentum of the quantum rotors. One can use truncations corresponding to spin-2 and spin-1 to build local Hilbert spaces associated with the links of the lattice. We argue that ladder-shaped configurable arrays of Rydberg atoms can be used for the same purpose. We make concrete proposals involving two and three Rydberg atoms to build one local spin-1 space (a qutrit). We show that the building blocks of the Hamiltonian calculations are models with one and two spins. We compare target and simulators using perturbative and numerical methods. The two-atom setup provides an easily controllable simulator of the one-spin model while the three-atom setup involves solving nonlinear equations. We discuss approximate methods to couple two spin-1 spaces. The article provides analytical and numerical tools necessary to design and build the proposed simulators with current technology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Improving Common PV Module Temperature Models by Incorporating Radiative Losses to the Sky

PV module operating temperature is the second-most important factor influencing PV system yield–after irradiance–and a substantial contributor to uncertainty in energy system yield predictions. Models commonly used to predict operating temperature in system simulations are based on a simplified energy balance that lumps together different heat loss mechanisms–including radiation–and assumes an overall linear behavior. Radiative heat loss to the sky is usually substantial, but modeling it accurately requires additional information about down-welling long-wave radiation or sky temperature and increases the complexity of temperature model equations. In this work we show how radiative losses to the sky can be separated into two parts to improve the accuracy of modeling without additional complexity. We also predict and demonstrate the variation of these losses at different tilt angles and show that the effective view factor is reduced by the non- isotropic distribution of down-welling long-wave radiation. Finally, we demonstrate substantial reduction in bias (MBE) and scatter (RMSE) when the new radiative loss term is added to the Faiman model using one year of measurements at Sandia National Labs.

14 SOLAR ENERGY↗

DOE OSTI2025

Validating corrosion models: A comparison of governing equations

Experimental validation of Finite Element Method (FEM) models varying electrochemical governing equations, inclusion of chemical reactions, and time on the resultant damage profile for two galvanic couples is explored. Two anode materials (Magnesium AZ31 and Carbon Steel) in contact with a cathode (Stainless Steel 304 L) were modeled in/exposed to NaCl (1 and 0.1 M respectively for the anode materials) for up to one week. The physics approach, inclusion of chemical reactions, and the boundary conditions required to accurately represent the damage profile in FEM models depended on the galvanic couple materials and, ultimately, the corrosion rate. For high rates of corrosion (i.e., magnesium anode), the Nernst-Planck equation with Electroneutrality was sufficient to describe the damage, while, for low rates of corrosion (i.e., carbon steel anode), the Laplace equation was sufficient. In all cases, the most complete governing equation (Nernst-Planck-Poisson Equation) was not necessary to accurately describe the damage. Precipitation reactions in solution also played a critical role in the predicted damage profile, especially for high corrosion rate systems. Finally, for short time periods (< 6 h), the choice of governing equations does not significantly influence damage profile results. Overall, the choice of physics to reduce error in simulations relies on the boundary conditions, geometry, conductivity of the solution, electrochemical potential differences, and time of exposure. The above results are discussed with regard to accuracy and computational savings.

Carbon steel↗

DOE OSTI2022

FECM/NETL CO 2 Transport Cost Model (2022): Description and User’s Manual

The FECM/NETL CO 2 Transport Cost Model (CO 2 _T_COM) is an Excel spreadsheet model that calculates the cost of transporting CO 2 from the beginning to the end of a pipeline. This document provides two main functions. First, the document describes the equations and algorithms that are used by the model to calculate technical quantities (such as the minimum inner pipe diameter needed to transport a user-specified CO 2 mass flow rate a specified distance) and engineering-economic quantities (such as capital costs, operating costs and cash flows). Second, the document is a user’s manual for the model that describes the procedures the user must follow to run the model. The document also describes input variables and output variables (i.e., results) for the model.

42 ENGINEERING↗