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DOE OSTI2018

Development of Hot-Isostatic Pressing for Treatment of UK ILW Radioactive Wastes - 18280

Hot-Isostatic Pressing (HIPing) has been proposed as an improved method for the treatment of radioactive wastes in the UK. Sludges and slurries housed on the Sellafield site are a prime candidate for HIP treatment due to their large volumes and issues associated with the use of the baseline cementation strategy. Options have been developed by GeoRoc Ltd to co-process these wastes, including a detailed conceptual plant design. This paper will describe research and development aimed at demonstrating the viability of the concept presented in this design. This paper summarizes two studies performed to address the knowledge gaps identified for treatment of these wastes using HIP technology. The first study related to the poorly characterized nature of the wastes, which requires any treatment option to be flexible in terms of the chemical and physical properties of the waste feed. The second study involved demonstrating that HIPing can be effectively utilized at a scale applicable to treat a waste inventory estimated to be in excess of 5,000 m{sup 3}. The first section of this paper presents a summary of research carried out to determine where variation in the waste stream composition may affect the processing and wasteform produced when HIPing Magnox sludges. This study aimed to qualify where restrictions on the process envelope may exist due to poorly defined waste-stream characteristics. A baseline wasteform was selected with the aim of achieving significant waste volume reduction, while producing a physically and chemically stable wasteform. A glass-bonded magnesium-titanate/magnesium-silicate wasteform was selected as the preferred option for the Magnox sludge wastes. A series of studies investigated the densification and phase formation of waste-forms by altering key variables in the Magnox sludge simulant. To test the extremes of the processable waste loading, samples were produced and characterized at 100 wt% waste-loading for Magnox sludge, Site-Ion Exchange Plant (SIXEP) sand/clinoptilolite and a 50:50 mix of the two waste-streams. Further studies involved a) altering the waste loading to additive mass ratio (to simulate changes in the waste loading/sludge solids content), b) varying the particle size distribution from the datum to include only small or large particulates in the sludge feed; and c) introducing up to 20 wt% metallic Magnox alloy, organic species or carbonate materials (to determine how their inclusion may affect the processing and densification of the materials). A U{sub 3}O{sub 8} loaded sample was also produced using the baseline Magnox sludge formulation. All the tests performed were shown to produce monolithic, well densified waste-forms with substantial volume reductions. Minimal variations from the baseline were noted but the waste-forms produced with these deviations was determined to be of comparable quality to of the baseline product. U{sub 3}O{sub 8} was shown to behave in a similar fashion to the ZrO{sub 2} surrogate used to simulate it in the process envelope studies and was encapsulated in the magnesium titanate/magnesium silicate matrix. This work demonstrates that HIP technology can successfully produce waste-forms across the broad process envelope expected in the Magnox sludge inventory. It is also possible to produce monolithic waste-forms at 100 wt% waste loading from Magnox sludges, SIXEP sand clinoptilolite slurries or a co-processed mixture of the two. The second part of this paper summarizes a commercially relevant demonstration of HIP technology for the treatment of sludge and slurry wastes housed at the Sellafield site (UK). This study culminated in production of the largest HIPed wasteform successfully produced to date. This study was performed in a series of stages. Investigations into formulation and properties of waste-forms were performed at a lab scale to evaluate suitable wasteform systems and identify suitable combinations of additives and waste loadings. Scale up demonstrations were then performed in stages with custom-designed HIP canisters. Scale-up and characterization of key wasteform properties were successfully performed with initial canister volumes of 50 ml, 400 ml and 8 L. Suitable front-end unit operations to produce a granular, free-flowing calcined simulant were demonstrated at an engineering scale. The demonstration was successful in processing a HIP canister with an initial starting volume in excess of 100 L. A 75 % volume reduction from the raw sludge was achieved at scale while demonstrating that HIP is applicable at suitably large scale for immobilization of ILW waste. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2017

A Modified Embedded-Atom Method Interatomic Potential for U-Si

Uranium-silicide (U-Si) fuels are being pursued as a possible accident tolerant fuel (ATF). This uranium alloy fuel benefits from higher thermal conductivity and higher fissile density compared to UO{sub 2}. 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 semiempirical 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 (U{sub 3}Si{sub 2}), but also a variety of U-Si phases across the composition spectrum.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Refinement and Modeling of a Blackbody-Based Calibration Method in the InfraBREAD Detector

The Broadband Reflector Experiment for Axion Detection (BREAD) is an ongoing collaboration searching for the conversion of yet undiscovered axion-like dark matter particles to photons in the presence of a magnetic field. InfraBREAD, an experiment of BREAD, uses a superconducting nanowire single photon detector (SNSPD), a high-efficiency and low-noise device, to specifically detect infrared-range photons produced by $\mathcal{O}$(eV) axion-like particles. The unique BREAD reflector setup allows for the focusing of converted signal photons to a 1mm $\times$ 1mm SNSPD. However, when the detector is cooled to cryogenic temperatures during operation, uneven thermal contraction of reflector components may lead to a small shift in the location of the focal spot. A novel calibration method using blackbody radiation is proposed to locate the true focal spot of the detector \textit{in situ}. Through ray tracing simulations done in FRED Optical Engineering Software, this method is demonstrated to locate the focus to within $\SI{50}{\micro\metre}$ in the $z$ dimension.

Rao, Shardul↗

DOE OSTI2024

Modeling and Proof-of-Concept of a Blackbody-Based Calibration Method in the InfraBREAD Detector

The Broadband Reflector Experiment for Axion Detection (BREAD) is an ongoing collaboration searching for the conversion of yet undiscovered axion-like dark matter particles to photons in the presence of a magnetic field. InfraBREAD, a pilot experiment realization of BREAD, uses a superconducting nanowire single photon detector (SNSPD), a high-efficiency and low-noise device, to specifically detect infrared-range photons produced by $\mathcal{O}$(eV) axion-like particles. The unique BREAD coaxial reflector setup allows for the focusing of converted signal photons to a 1mm $\times$ 1mm SNSPD. However, when the detector is cooled to cryogenic temperatures during operation, uneven thermal contraction of reflector components may lead to a small shift in the location of the focal spot. A novel calibration method using blackbody radiation is proposed to locate the true focal spot of the detector \textit{in situ}. Through ray tracing simulations done in FRED Optical Engineering Software, this method is demonstrated to locate the focus to within $\SI{50}{\micro\metre}$ in the axial dimension. Additionally, it is demonstrated that the blackbody photon source used in this calibration must be at a temperature of at least $\SI{15}{\kelvin}$ to $\SI{40}{\kelvin}$, depending on the sensitivity of the SNSPD.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

Vortex mode excitation in a multimode fiber by the Laguerre-Gaussian laser beams

The coupling of Laguerre-Gaussian (LG) vortex modes into the Bessel vortex modes in a multimode fiber was analyzed using the vector form of LG beams. A formula for estimating the transmission coefficients of the excited vortex modes was developed. Analytical calculation results show that the coupling coefficients are affected by the focus size. With proper beam waist radius most the power of incident vortex mode can couple into single vortex mode. The numerical simulation was also carried out, and the simulation results are in good agreement with those from the analytical model.

42 ENGINEERING↗

DOE OSTI2019

FEARCE: Fast, Easy, Accurate, and Robust Continuum Engineering Improving fuel efficiency and reducing emissions in combustion engines 2019 R&D 100 Awards

FEARCE investigates and simulates turbulent chemically reactive flows in fuel combustion, such as fuel injection and fuel-air mixing, thermodynamic combustion losses, and combustion–emission formation processes in engines. Our objective is to understand turbulent flows and how they react and interact with other complicating variables, including highly nonlinear heat and mass transfer, small-scale velocity, and chemical kinetics or reactions. Our emphasis is on the fluid dynamics and chemical reactions that take place in all kinds of internal combustion engines, including the reactions between multiple species (such as air, gasoline, carbon dioxide, water, and hundreds of other species) and multiphase (liquid and gas) fluid flow.

42 ENGINEERING↗

DOE OSTI2025

TRUST Contact Thermal Conductance (TRUST-CTC) Report: FY25

The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainties in Simulations and Tests (TRUST) project is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to current and future delivery environments [1]. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are critical to the current and future stockpile. Staff development will include cross-discipline collaboration to provide engineers with experience in both numerical simulations and experimental methods. This work uses and provides feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development.

42 ENGINEERING↗

DOE OSTI2021

Multidimensional Numerical Modeling of Combustion Dynamics in a Non-Premixed Rotating Detonation Engine With Adaptive Mesh Refinement

In the present work, a novel computational fluid dynamics (CFD) methodology was developed to simulate full-scale non-premixed rotating detonation engines (RDEs). A unique feature of the modeling approach was the incorporation of adaptive mesh refinement (AMR) to achieve a good trade-off between model accuracy and computational expense. Here, unsteady Reynolds-averaged Navier–Stokes (RANS) simulations were performed for an Air Force Research Laboratory (AFRL) non-premixed RDE configuration with hydrogen as fuel and air as the oxidizer. The finite-rate chemistry model, along with a ten-species detailed kinetic mechanism, was employed to describe the H 2 -Air combustion chemistry. Three distinct operating conditions were simulated, corresponding to the same global equivalence ratio of unity but different fuel/air mass flowrates. For all conditions, the capability of the model to capture essential detonation wave dynamics was assessed. An exhaustive verification and validation study was performed against experimental data in terms of a number of waves, wave frequency, wave height, reactant fill height, oblique shock angle, axial pressure distribution in the channel, and fuel/air plenum pressure. The CFD model was demonstrated to accurately predict the sensitivity of these wave characteristics to the operating conditions, both qualitatively and quantitatively. A comprehensive heat release analysis was also conducted to quantify detonative versus deflagrative burning for the three simulated cases. The present CFD model offers a potential capability to perform rapid design space exploration and/or performance optimization studies for realistic full-scale RDE configurations.

42 ENGINEERING↗

DOE OSTI2021

Discussion on molecular dynamics (MD) simulations of the asphalt materials

The application of asphalt materials in pavement engineering has been increasingly widespread and sophisticated over the past several decades. Variations in the properties of asphalt binder during mixing, transportation, and paving can affect the performance of asphalt pavement. However, the asphalt material is a non-homogeneous and complex organic substance, consisting of various molecules with widely various molecular weights, elemental compositions, and structures. This complexity leads to difficulties for researchers to clearly and immediately understand the properties of asphalt materials and their variations. The multi-scale research approach combines macroscopic experimental data and microscopic simulation results from a practical engineering perspective. It helps to improve the understanding of asphalt materials. The molecular dynamics (MD) simulation proposes a corresponding molecular model of asphalt material based on experimental data, and the simulation algorithm is able to derive properties similar to those of real asphalt. Here, this paper provides a comprehensive review of the current studies on MD simulation of asphalt materials, including modeling, properties, and multi-scale analysis. As a key part of the computational simulation, this paper discusses the typical asphalt binder and asphalt-aggregate interface models constructed by different groups, and also presents their differences from real samples and their feasibility based on fundamental properties. After the introduction of molecular models, the extensive work made by researchers based on molecular models is categorically reviewed and discussed. The strengths and weaknesses of MD simulation methods in the study of asphalt materials are also summarized in order to provide the reader with a more comprehensive understanding of the relevant contents and to guide subsequent research.

36 MATERIALS SCIENCE↗

DOE OSTI2021

TRUST Contact Thermal Conductance (CTC) Report

The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainties in Simulations and Tests (TRUST) work package is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to current and future delivery environments. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are critical to the current and future stockpile. Staff development will include cross-discipline training to provide engineers with experience in both numerical simulations and experimental methods. This work will use and provide feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development: engineering common model framework (ECMF), engineering quantification of margins and uncertainties (EQMU), and the test information management system (TIMS).

42 ENGINEERING↗

DOE OSTI2021

TRUST End-of-Year Report

42 ENGINEERING↗

DOE OSTI2021

TRUST Nonlinear Dynamics (ND) Report

42 ENGINEERING↗

DOE OSTI2025

Evaluating Chemical Kinetics Predictions for Propane Using 3-D and 0-D Models in a Boosted Spark-Ignited Engine

Propane has been shown to be a promising alternative fuel to reduce emissions while simultaneously achieving high efficiencies in medium- and heavy-duty engines. These high-power density applications require boosted engines which, combined with high compression ratio, can lead to auto-ignition and knock. While three-dimensional (3-D) computational fluid dynamics (CFD) models are often used for resolving the complex fluid flow in engines, these models can become computationally expensive when simulating detailed chemical kinetics. Likewise, zero-dimensional (0-D) models are computationally concise enough for kinetics development, but lack any flow-field information which governs the flame propagation processes in spark ignition (SI) engines. This work presents a comprehensive comparison between 3-D and 0-D closed cycle simulations at knocking conditions in a high compression ratio high stroke-to-bore ratio propane engine. In order to initialize the flow-field for the 3-D closed cycle (intake valve closing, (IVC) to exhaust valve opening, (EVO)) simulation, a motored multi-cycle 3-D model was run using Converge to create a map at IVC, reducing the computational time. The map allowed a non-homogeneous 3-D closed cycle simulation to be satisfactorily validated against experiments, while a homogeneous case using only the turbulence field mapping was also simulated, mimicking 0-D modeling. The 3-D simulations were used to prescribe the initial conditions (e.g., IVC thermodynamics, speciation, burn-rate profile) for a 2-zone 0-D SI engine model in Chemkin Pro for both cases. It was found that 2-zone 0-D modeling underpredicted the knock onset timing, likely due to the lack of thermal stratification in the unburned gas region. Future work will carry multi-zone 0-D modeling to capture the fuel auto-ignition in the unburned region.

Douvry-Rabjeau, Julien [Oakland University, Roches↗

DOE OSTI2018

Machine Learning–Based Reduce Order Crystal Plasticity Modeling for ICME Applications

Abstract Crystal plasticity simulation is a widely used technique for studying the deformation processing of polycrystalline materials. However, inclusion of crystal plasticity simulation into design paradigms such as integrated computational materials engineering (ICME) is hindered by the computational cost of large-scale simulations. In this work, we present a machine learning (ML) framework using the material information platform, Open Citrination, to develop and calibrate a reduced order crystal plasticity model for face-centered cubic (FCC) polycrystalline materials, which can be both rapidly exercised and easily inverted. The reduced order model takes crystallographic texture, constitutive model parameters, and loading condition as inputs and returns the stress-strain curve and final texture. The model can also be inverted and take a stress-strain curve, loading condition, and final texture as inputs and return the initial texture and constitutive model parameters as outputs. Principal component analysis (PCA) is used to develop an efficient description of the crystallographic texture. A viscoplastic self-consistent (VPSC) crystal plasticity solver is used to create the training data by modeling the stress-strain behavior and evolution of texture during deformation processing.

Yuan, Mengfei↗

DOE OSTI2025

Significantly enhanced near-field coupling via tip engineering

The ability to significantly enhance near-field coupling between light and matter at the nanoscale is crucial for advancing the fields of nanophotonics and nanopolariotonics. However, conventional probes face challenges in achieving optimal light–matter interaction. In this study, we propose a novel, to the best of our knowledge, simulation-based strategy that leverages tip engineering to dramatically amplify the scattering field through tailored double-layer geometries. By employing a core-shell structure with a thin shell layer optimized for specific dielectric permittivity and effective polarizability, we demonstrate a near-field enhancement of up to 10 times compared to conventional probes. Our findings highlight exciting new possibilities for optimizing near-field interactions through probe designs with customized resonances, paving the way for substantially improved nano-optical sensing, imaging, and detection.

Shiravi, H.↗

DOE OSTI2025

Modeling Offshore Wind Farm Performance in Coastal Low-Level Jets Using Coupled Mesoscale-Microscale Large Eddy Simulations

Accurately predicting wind farm reliability under complex offshore atmospheric conditions remains a key challenge, particularly during noncanonical meteorological events such as coastal low-level jets (LLJs). LLJs, characterized by strong nonmonotonic vertical shear and directional veer, depart significantly from the simplified inflow assumptions embedded in conventional design standards, low-fidelity engineering models, and microscale large eddy simulations of the atmospheric boundary layer. In this work, we use the virtual wind farm framework—an exascale, graphics processing unit–accelerated large eddy simulation platform coupled with high-fidelity aeroservoelastic turbine models and advanced mesoscale-microscale coupling via the ExaWind software stack—to investigate turbine responses under realistic LLJ forcing. Simulations are performed over the U.S. North Atlantic offshore domain with the use of meteorological inputs from New York State Energy Research and Development Authority buoy data, focusing on a representative LLJ case impacting the International Energy Agency 15 MW reference turbine. Our results show that LLJs can cause up to 50% power deficits in downstream turbine rows and significantly amplify low-speed shaft and tower loads through nonlinear coupling between complex inflow characteristics and turbine structural dynamics. Two primary mechanisms drive these load amplifications: (1) unique LLJ inflow features—including veer and vertical/lateral shear—and (2) the downstream evolution of the flow under stable thermal stratification, which suppresses turbulence mixing and alters wake recovery. These mechanisms produce streamwise variations in turbine loading not captured by standard hub height–based metrics or existing design load case (DLC) definitions. This study highlights the critical role of rotor-scale flow gradients in driving fatigue and system-level aeroelastic responses, challenging current DLC and control strategies. We advocate the integration of full-flow field, environment-aware wind inputs into load modeling and control algorithms. By leveraging exascale computing to resolve mesoscale-microscale coupling, this work lays the groundwork for next-generation offshore wind turbine design and operation in meteorologically complex marine environments.

17 WIND ENERGY↗

DOE OSTI2017

Numerical Simulation of Twin Jets using LES with the Nek5000 Code

The twin jet activity, a joint effort between Texas A and M University, University of Tennessee - Knoxville, and Argonne National Laboratory, is being used to analyze the performance of various computational fluid dynamics (CFD) code packages. The twin jet water facility (TJWF) is based off a semi-classical problem of combining planar turbulent jets in a large free-shear environment or enclosure. The problem is similar to physics seen in advanced reactor designs such as in the large upper plena of a sodium fast reactor. Utilizing the experimental data sets created using laser Doppler velocimetry (LDV) and particle image velocimetry (PIV), the Nek5000 code, among others, is qualitatively compared to the experimental work. This effort is a starting point for determining the appropriate simulation techniques needed for resolving the twin jet physics.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

Design and Closed‐Loop Motion Planning of an Untethered Swimming Soft Robot Using 2D Discrete Elastic Rods Simulations

Despite tremendous progress in the development of untethered soft robots in recent years, existing systems lack the mobility, model‐based control, and motion planning capabilities of their piecewise rigid counterparts. As in conventional robotic systems, the development of versatile locomotion of soft robots is aided by the integration of hardware design and control with modeling tools that account for their unique mechanics and environmental interactions. Here, a framework for physics‐based modeling, motion planning, and control of a fully untethered swimming soft robot is introduced. This framework enables offline co‐design in the simulation of robot parameters and gaits to produce effective open‐loop behaviors and enables closed‐loop planning over motion primitives for feedback control of a frog‐inspired soft robot testbed. This pipeline uses a discrete elastic rods (DERs) physics engine that discretizes the soft robot as many stretchable and bendable rods. On hardware, an untethered aquatic soft robot that performs frog‐like rowing behaviors is engineered. Hardware validation verifies that the simulation has sufficient accuracy to find the best candidates for sets of parameters offline. The simulator is then used to generate a trajectory library of the robot's motion in simulation that is used in real‐time closed‐loop path following experiments on hardware.

Huang, Xiaonan↗