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DOE OSTI2020

A transported Livengood-Wu integral model for knock prediction in CFD simulation

This work describes the development of a transported Livengood-Wu (L-W) integral model for computational fluid dynamics (CFD) simulation to predict auto-ignition and engine knock tendency. The currently employed L-W integral model considers both single-stage and two-stage ignition processes, thus can be generally applied to different fuels such as paraffin, olefin, aromatics and alcohol. The model implementation is first validated in simulations of homogeneous charge compression ignition combustion for three different fuels, showing good accuracy in prediction of auto-ignition timing for fuels with either single-stage or two-stage ignition characteristics. Then, the L-W integral model is coupled with G-equation model to indicate end-gas auto-ignition and knock tendency in CFD simulations of a direct injection spark ignition engine. This modeling approach is about 10 times more efficient than the ones that based on detailed chemistry calculation and pressure oscillation analysis. Two fuels with same Research Octane Number (RON) but different octane sensitivity are studied, namely Co-Optima Alkylate and Co-Optima E30. Feed-forward neural network model in conjunction with multi-variable minimization technique is used to generate fuel surrogates with targets of matched RON, octane sensitivity and ethanol content. The CFD model is validated against experimental data in terms of pressure traces and heat release rate for both fuels under a wide range of operating conditions. The knock tendency indicated by the fuel energy contained in the auto-ignited region of the two fuels at different load conditions correlates well with the experimental results and the fuel octane sensitivity, implying the current knock modeling approach can capture the octane sensitivity effect and can be applied to further investigation on composition of octane sensitivity.

Yue, Zongyu↗

DOE OSTI2026

Stochastic fracture generation and thermo-hydro-mechanical modeling in an equivalent continuum framework for enhanced geothermal systems

Enhanced geothermal systems (EGS) involve fracturing low permeability material to establish well connectivity and then injecting and circulating fluid into the fractured subsurface for geothermal power production. Changes in fracture aperture from contraction of the cooling matrix rock may alter network connectivity and risk thermal short-circuiting. Thermo-hydro-mechanical (THM) models are a useful tool to study these processes. However, as fracture networks are complex, and data may be limited, fracture networks in THM models are often stochastically generated. Given reliance on stochastic fracture networks and THM modeling to represent the subsurface and assess productivity of EGS, increased understanding of the influence of such statistically derived fracture networks on flow and heat transport in THM models is needed. Here, a new fracture process model is developed in the reactive transport code PFLOTRAN to stochastically generate fracture families and simulate changes in fracture aperture over time due to temperature changes of the rock matrix. Sixty-four different fracture networks ranging from well to poorly-connected, are modeled in PFLOTRAN with and without mechanical processes (THM vs TH). Results indicate that for well-connected fracture networks, thermal short-circuiting is less of a concern due to the abundance of available alternative flowpaths. For poorly-connected fracture networks, inclusion of mechanical processes showed steep thermal drawdown coincident with increase in fracture aperture along developing colder flowpaths, demonstrating the risk of thermal short-circuiting. Simulations with additional, larger fractures engineered to establish connectivity in a poorly-fractured subsurface, indicate that while stochastic variation of fracture orientation of the background network had limited influence, such variation in the engineered fractures significantly affected flow and heat transport.

Discrete fracture networks (DFN)↗

DOE OSTI2022

Predictive modeling of a subcritical pulverized-coal power plant for optimization: Parameter estimation, validation, and application

As renewable power generation deployment increases, fossil fuel plants are increasingly required to operate more flexibly. Many coal-fired power plants were originally designed to operate at base load and do not operate optimally at partial load. Predictive first-principles plant-wide models can be employed to identify opportunities for flexibility improvements and diagnose low-load operating issues. This paper describes the application of the Institute for the Design of Advanced Energy Systems Integrated Platform (IDAES) to model and optimize flexible power plant operations. The key benefits of using IDAES are that it provides an open-source, fully equation-oriented modeling framework for efficient modular model construction, reuse, and customization, together with a mathematical optimization framework leveraging powerful, state-of-the-art solvers. The process systems engineering workflow from predictive process simulation to parameter estimation, model validation, and plant optimization is applicable to a variety of existing and next-generation energy systems as well as other chemical and environmental processes. Here, to demonstrate this capability, a physics-based, steady-state model was developed to improve full- and part-load performance of the Escalante Generating Station, a 245 MWe (net) subcritical pulverized coal-fired power plant owned and operated by Tri-State Generation and Transmission Association. Specifically, sixty-nine model parameters were simultaneously estimated from several months of operating data enabling prediction of flow rates, temperatures, pressures, and steam quality throughout the plant. The validated model was leveraged by Escalante to reduce the minimum operating load from 90 MW to 50 MW by diagnosing a low-load water-hammer issue, enabling coal usage and emissions reductions during periods of low power demand. Additionally, opportunities for heat rate reduction (i.e., efficiency improvement) through a steeper sliding-pressure approach to load-following and optimization of other boiler operating variables were also identified and quantified. For example, a potential efficiency improvement of 0.7 percentage points was observed at half-load operation.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2022

Effective properties of semitransparent radiative cooling materials with spectrally variable properties

Radiative cooling is a promising solid-state, non-vapor-compression technology for passive refrigeration and air conditioning. Although this phenomenon occurs naturally, achieving a significant amount of cooling to make it a technically and economically viable technology requires highly engineered, spectrally selective radiative surfaces. These characteristics make radiative cooling difficult to estimate, particularly when it is integrated with other systems such as photovoltaic panels or building envelopes. The complexity further increases when the substrate also participates in the radiative cooling (along with the radiative coating). Energy estimation is becoming increasingly critical because of the recent focus on the semitransparent radiative coatings that transmit a variety of colors to enhance the aesthetic appeal of the system. In this work, we propose an iterative method to calculate the effective radiative properties, which provides the same net radiative cooling that would be observed using the spectral properties at both the coating and substrate surfaces. Compared to traditional methods that rely on either computationally expensive full spectral analysis or methods for averaging each radiative surface parameter locally, our proposed method focuses on calculating effective properties that provide the same the net cooling effect as a full spectral analysis by accounting the emissivity, absorptivity, and transmissivity collectively, thereby providing an overall estimation error of less than 0.2%. We believe that this study will be beneficial to the engineering communities that employ complex simulation codes and require lumped solar and thermal radiation related parameters.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Reliable extrapolation of deep neural operators informed by physics or sparse observations

Deep neural operators can learn nonlinear mappings between infinite-dimensional function spaces via deep neural networks. As promising surrogate solvers of partial differential equations (PDEs) for real-time prediction, deep neural operators such as deep operator networks (DeepONets) provide a new simulation paradigm in science and engineering. Pure data-driven neural operators and deep learning models, in general, are usually limited to interpolation scenarios, where new predictions utilize inputs within the support of the training set. However, in the inference stage of real-world applications, the input may lie outside the support, i.e., extrapolation is required, which may result to large errors and unavoidable failure of deep learning models. Here, we address this challenge of extrapolation for deep neural operators. First, we systematically investigate the extrapolation behavior of DeepONets by quantifying the extrapolation complexity, via the 2-Wasserstein distance between two function spaces and propose a new strategy of bias–variance trade-off for extrapolation with respect to model capacity. Subsequently, we develop a complete workflow, including extrapolation determination, and we propose five reliable learning methods that guarantee a safe prediction under extrapolation by requiring additional information—the governing PDEs of the system or sparse new observations. The proposed methods are based on either fine-tuning a pre-trained DeepONet or multifidelity learning. We demonstrate the effectiveness of the proposed framework for various types of parametric PDEs. Furthermore, our systematic comparisons provide practical guidelines for selecting a proper extrapolation method depending on the available information, desired accuracy, and required inference speed.

42 ENGINEERING↗

DOE OSTI2025

3D mesh regularization within an ALE code using a weighted line sweeping method

The Lagrangian formalism is widely used to simulate hydrodynamic responses in complex engineering applications, particularly those involving strong shock waves. However, as the mesh moves with the fluid, it can become highly distorted, requiring a regularization step. This involves constructing a new grid and remapping conservative quantities onto it to restore mesh quality. This work introduces a regularization method for block-structured meshes within a 3D ALE (Arbitrary Lagrangian-Eulerian) code. The proposed approach prevents mesh tangling while preserving the anisotropic features of the initial Lagrangian mesh. This regularization technique incorporates aspect ratio-based weights to control mesh smoothing. Unlike uniform rezoning techniques, this weighted approach maintains proximity to the Lagrangian mesh while improving mesh quality. Here, the method effectively handles concave geometries by mitigating the grid attraction phenomenon, which typically leads to mesh concentration along concave edges. Numerical experiments demonstrate its efficiency in regularizing severely deformed meshes, and its integration within the ALE framework is validated on challenging hydrodynamic test cases, including the triple point problem.

42 ENGINEERING↗

DOE OSTI2017

Detailed assessment of diesel spray atomization models using visible and X-ray extinction measurements

The physical mechanisms characterizing the breakup of a diesel spray into droplets are still unknown. This gap in knowledge has largely been due to the challenges of directly imaging this process or quantitatively measuring the outcomes of spray breakup, such as droplet size. Recent x-ray measurements by Argonne National Laboratory, utilized in this work, provide needed information about the spatial evolution of droplet sizes in selected regions of the spray under a range of injection pressures (50–150 MPa) and ambient densities (7.6–22.8 kg/m3) relevant for diesel operating conditions. Ultra-small angle x-ray scattering (USAXS) measurements performed at the Advanced Photon Source are presented, which quantify Sauter mean diameters (SMD) within optically thick regions of the spray that are inaccessible by conventional droplet sizing measurement techniques, namely in the near-nozzle region, along the spray centerline, and within the core of the spray. To quantify droplet sizes along the periphery of the spray, a complementary technique is proposed and introduced, which leverages the ratio of path-integrated x-ray and visible laser extinction (SAMR) measurements to quantify SMD. The SAMR and USAXS measurements are then utilized to evaluate current spray models used for engine computational fluid dynamic (CFD) simulations. We explore the ability of a carefully calibrated spray model, premised on aerodynamic wave growth theory, to capture the experimentally observed trends of SMD throughout the spray. The spray structure is best predicted with an aerodynamic primary and secondary breakup process that is represented with a slower time constant and larger formed droplet size than conventionally recommended for diesel spray models. Additionally, spray model predictions suggest that droplet collisions may not influence the resultant droplet size distribution along the spray centerline in downstream regions of the spray.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Predicting extreme anisotropy and shape variations in impact testing of tantalum single crystals

We report recent Taylor cylinder impact tests carried out for Ta single crystals showed strong variations in dimensional changes for different crystallographic directions aligned with the cylindrical axis. In order to capture the effect of crystallography on the deformation characteristics and final shapes of the impacted cylinders, a single crystal material subroutine is adapted and embedded in the solid mechanics/dynamics Finite Element solver Abaqus to simulate the aforementioned single crystal Ta Taylor impact experiments. Details of the coupled model implementation, and insights on the role played by single crystal anisotropic flow on the deformation behavior across a broad range of strain rates and temperatures for different single crystal orientations are presented and discussed. We demonstrate the predictive capability of the adopted crystal plasticity model to capture the significant role played by crystal orientation-induced anisotropy, as well as strain hardening and adiabatic heating, on the dynamic deformation response of crystalline materials. This re-emphasizes the need of microstructure-aware models to improve the accuracy of simulations for high-consequence engineering design.

36 MATERIALS SCIENCE↗

DOE OSTI2017

A modified Embedded-Atom Method interatomic potential for uranium-silicide

Uranium-silicide (U-Si) fuels are being pursued as a possible accident tolerant fuel (ATF). U-Si fuels benefit from higher thermal conductivity and higher fissile density compared to UO2. In order to perform engineering scale nuclear fuel performance simulations, the material properties of the fuel must be known. Currently, the experimental data available for U-Si fuels is rather limited. Thus, multiscale modeling efforts are underway to address this gap in knowledge. In this study, a semi-empirical Modified Embedded Atom Method (MEAM) potential is presented for the description of the U-Si system. The potential accurately describes not only the primary phase of interest (U3Si2), but also a variety of U-Si phases across the composition spectrum.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Molecular Origin of Wettability Alteration of Subsurface Porous Media upon Gas Pressure Variations

Upon extraction/injection of a large quantity of gas from/into a subsurface system in shale gas production or carbon sequestration, the gas pressure varies remarkably, which may significantly change the wettability of porous media involved. Mechanistic understanding of such changes is critical for designing and optimizing a related subsurface engineering process. Using molecular dynamics simulations, in this work we have calculated the contact angle of a water droplet on various solid surfaces (kerogen, pyrophyllite, calcite, gibbsite, and montmorillonite) as a function of CO 2 or CH 4 gas pressure up to 200 atm at a temperature of 300 K. The calculation reveals a complex behavior of surface wettability alteration by gas pressure variation depending on surface chemistry and structure, and molecular interactions of fluid molecules with surfaces. As the CO 2 gas pressure increases, a partially hydrophilic kerogen surface becomes highly hydrophobic, while a calcite surface becomes more hydrophilic. Considering kerogen and calcite being the major components of a shale formation, we postulate that the wettability alteration of a solid surface induced by a gas pressure change may play an important role in fluid flows in shale gas production and geological carbon sequestration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

A parametrically programmable delay line for microwave photons

Delay lines that store quantum information are crucial for advancing quantum repeaters and hardware efficient quantum computers. Traditionally, they are realized as extended systems that support wave propagation but provide limited control over the propagating fields. Here, we introduce a parametrically addressed delay line for microwave photons that provides a high level of control over the stored pulses. By parametrically driving a three-wave mixing circuit element that is weakly hybridized with an ensemble of resonators, we engineer a spectral response that simulates that of a physical delay line, while providing fast control over the delay line’s properties. We demonstrate this novel degree of control by choosing which photon echo to emit, translating pulses in time, and even swapping two pulses, all with pulse energies on the order of a single photon. We also measure the noise added from our parametric interactions and find it is much less than one photon.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Making metals linear super-elastic with ultralow modulus and nearly zero hysteresis

We demonstrate a novel materials design approach to achieve unprecedented properties by utilizing nanoscale chemo-mechanical coupling. In particular, by using computer simulations we demonstrate how to engineer ultralow modulus (12 GPa), nearly hysteresisfree, and linear super-elastic metals with a giant elastic strain limit (2.7%) by creating appropriate concentration modulations (CMs) at the nanoscale in the parent phase and by pre-straining to regulate the stress-induced martensitic transformation (MT). The nanoscale CMs created via spinodal decomposition produce corresponding phase stability modulations, suppress autocatalysis in nucleation, impose nano-confinements on growth, and hinder long-range ordering of transformation strain during the MT, which changes the otherwise sharp first-order transition into a smeared, macroscopically continuous transition over a large stress range. The pre-straining generates retained martensitic particles that are stable at the test temperature after unloading and act as operational nuclei in subsequent load cycles, eliminating the stress–strain hysteresis and offering an ultralow apparent Young’s modulus. Materials with a high strength and an ultralow apparent Young’s modulus have great potential for application in orthopaedic implants.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Spiral-like multi-beam emission via transformation electromagnetics

Transformation electromagnetics offers an unconventional approach for the design of novel radiating devices. Here, we propose an electromagnetic metamaterial able to split an isotropic radiation into multiple directive beams. By applying transformations that modify distance and angles, we show how the multiple directive beams can be steered at will. We describe transformation of the metric space and the calculation of the material parameters. Different transformations are proposed for a possible physical realization through the use of engineered artificial metamaterials. Full wave simulations are performed to validate the proposed approach. The idea paves the way to interesting applications in various domains in microwave and optical regimes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Grassy ELM regime at low pedestal collisionality in high-power tokamak plasma

Spontaneous mitigation of giant ELMs and appearance of grassy ELMs have been observed repeatedly at low pedestal collisionality (${\nu }_{\mathrm{e},\mathrm{p}\mathrm{e}\mathrm{d}}^{{\ast}}\sim 0.15$) in the high-power (P inj > 13 MW) hybrid scenario in DIII-D. Higher β p and higher q 95 appear to be beneficial to achieving the grassy ELM regime. The grassy ELM H-mode plasma shows high energy confinement performance (H 98y2 up to over 1.5) under the conditions of high neutral beam torque and high core rotation. The pedestal width appears to exceed the EPED1.0 model prediction by more than 50%. Pedestal stability analysis performed with the ELITE code indicates that the stability against low-n kink/peeling modes is improved with increased auxiliary heating power and the operational point in the grassy ELM regime is located near the ballooning boundary. The pedestal stability characteristics during the grassy ELM crashes have been investigated in comparison with the giant ELM crashes based on plasma profiles experimentally measured with high resolution and accuracy. It has been found that the underlying mechanism for the observed small-amplitude ELM crashes is mainly the expansion of the ballooning stability boundary induced by an initial radially localized collapse in the pedestal, which helps to stop the growth of instabilities and further collapse of the pedestal. The effect of electron density pedestal on mitigating edge localized instabilities has been analyzed by numerical simulation, suggesting that the electron density pedestal characterized by high n e,sep /n e,ped and low density gradient helps to stabilize peeling-ballooning modes because of a low pressure pedestal gradient and to lower the ballooning boundary mainly because of a low ion diamagnetic frequency in the pedestal region, thus triggering ballooning instabilities and producing the intrinsic grassy ELMs. Numerical simulation of the Chinese fusion engineering test reactor (CFETR) with the SOLPS code indicates that the separatrix density might be insensitive to the electron diffusivity in the pedestal region and increase with the power flowing from the core region to the edge region. Furthermore, pedestal stability analysis suggests that the flat density pedestal with high separatrix density obtained in the high-power plasma in CFETR would make the operational point close to the ballooning boundary, which is considered to help destabilize ballooning instabilities and facilitate the access to the grassy ELM regime.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2016

Long-lived neutral-kaon flux measurement for the KOTO experiment

The KOTO(K 0 at Tokai) experiment aims to observe the CP-violating rare decay K L → π 0 νν¯ over bar by using a long-lived neutral-kaon beam produced by the 30 GeV proton beam at the Japan Proton Accelerator Research Complex. The K L flux is an essential parameter for the measurement of the branching fraction. Three K L neutral decay modes, K L → 3 π 0 , K L → 2 π 0 , and K L → 2γ, were used to measure the K L flux in the beam line in the 2013 KOTO engineering run. A Monte Carlo simulation was used to estimate the detector acceptance for these decays. Agreement was found between the simulation model and the experimental data, and the remaining systematic uncertainty was estimated at the 1.4% level. Here, the K L flux was measured as (4.183 ± 0.017 stat. ± 0.059 sys. ) x 10 7 K L per 2 x 10 14 protons on a 66-mm-long Au target.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Privacy Preservation from High-Performance Computing to Autonomous Science [Industrial and Governmental Activities]

High-Performance Computing (HPC) and Leadership-Class Supercomputing are driving forces behind scientific advancements, enabling researchers to tackle complex challenges in physics, chemistry, biology, and engineering. These systems power vast simulations and data analyses, fueling discoveries in fields ranging from materials science to climate modeling. However, their use often involves processing sensitive data—such as proprietary industry simulations, biomedical records, and national security computations—posing significant privacy concerns. In conclusion, this issue is amplified in collaborative environments like Department of Energy (DOE) user facilities, where HPC resources are shared across institutions to foster innovation.

Kotevska, Olivera [Oak Ridge National Laboratory (↗

DOE OSTI2016

Assessment of semi-empirical potentials for the U-Si system

Accident tolerant fuels (ATF) are being developed in response to the Fukushima Daiichi accident in Japan. One of the options being pursued is U-Si fuels, such as the U 3 Si 2 and U 3 Si 5 compounds, which benefit from high thermal conductivity (metallic) compared to the UO2 fuel (semi-conductor) used in current Light Water Reactors (LWRs). The U-Si fuels also have higher fissile density. In order to perform meaningful engineering scale nuclear fuel performance simulations, the material properties of the fuel, including the response to irradiation environments, must be known. Unfortunately, the data available for U-Si fuels are rather limited, in particular for the temperature range where LWRs would operate. The ATF HIP is using multi-scale modeling and simulations to address this knowledge gap. Even though Density Functional Theory (DFT) calculations can provide useful answers to a subset of problems, they are computationally too costly for many others, including properties governing microstructure evolution and irradiation effects. For the latter, semi-empirical potentials are typically used. Unfortunately, there is currently no potential for the U-Si system. In this brief report we present initial results from the development of a U-Si semi-empirical potential based on the Modified Embedded Atom Method (MEAM). The potential should reproduce relevant parts of the U-Si phase diagram as well as defect properties important in irradiation environments. This work also serves as an assessment of the general challenges associated with the U-Si system, which will be valuable for the efforts to develop a U-Si Tersoff potential undertaken by Idaho National Laboratory (also part of the ATF HIP). Going forward the main potential development activity will reside at INL and the work presented here is meant to provide input data and guidelines for that activity. The main focus of our work is on the U 3 Si 2 and U3Si 5 compounds, because they are the main nuclear fuel candidates. U 3 Si 5 is derived from USi 2 in the AlB 2 structure by creating 1/6 vacant sites on Si sublattice. The ordering of these vacancies will not be studied in any detail here.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2016

Density functional theory calculations of defect and fission gas properties in U-Si fuels

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗