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Digital twin framework for PIP-II linac: AI-driven multi-scale modeling from ion source to 800 MeV
The PIP-II superconducting linac at Fermilab is designed to deliver multi-megawatt proton beams for neutrino physics and other high-intensity applications. To expedite commissioning and enhance operational reliability, we have developed an EPICS-based data flow framework that seamlessly integrates digital twins (DT) with physical twins (PT). These digital twins comprise high-fidelity beam dynamics models or data-driven surrogate models connected to their physical counterparts through real-time diagnostics and advanced machine-learning algorithms.Central to this framework is Linac_Gen, an accelerated simulation tool that incorporates convolutional neural networks, random forests, and genetic algorithms to provide up to a tenfold speedup in optimizing the accelerator geometry model. An EPICS translator layer ensures interoperability by efficiently mapping lattice parameters across diverse simulation platforms.Our EPICS-based framework supports multiple operational modes—monitoring, passive learning, closed-loop control, and online learning—covering the entire machine lifecycle. By leveraging HPC resources and multi-objective optimization techniques, the digital twin enables adaptive trajectory correction, real-time fault detection, and predictive modeling of beam stability. This comprehensive approach paves the way for robust, high-intensity operation and data-driven accelerator R&D at Fermilab.
Multi-scale modeling of dynamics and ignition to flame transitions of high pressure stratified n-heptane/toluene mixtures
Not Available
SCALE HTR-PROTEUS Benchmark Model
This dataset contains input and result files of computational simulations of HTR-PROTEUS benchmark with the latest version of SCALE code system. The simulations cover criticality control rod worth calculations as well as sensitivity analysis and uncertainty quantification. Users wanting to reproduce results from this dataset are required to obtain a license to the SCALE code system for which details on the distribution can be found here: https://www.ornl.gov/scale/releases
Modeling of inertial deposition in scaled models of rat and human nasal airways: Towards in vitro regional dosimetry in small animals
Rodents are routinely used in inhalation toxicology tests as human surrogates. However, in vitro dosimetry tests in rodent casts are still scarce due to small rodent airways and in vitro tests to quantify sub-regional dosimetry are still impractical. We hypothesized that for inertial particles whose deposition is dominated by airflow convection (Reynolds number) and particle inertia (Stokes number), the deposition should be similar among airway replicas of different scales if their Reynolds and Stokes numbers are kept the same. In this study, we aimed to (1) numerically test the hypothesis in three airway geometries: a USP induction port, a human nose model, and a Sprague-Dawley rat nose model, and (2) find the range of applicability of this hypothesis. Five variants of the USP and human nose models and three variants of the rat nose model were tested. Inhalation rates and particle sizes were scaled to match the Reynolds number and Stokes numbers. A low-Reynolds-number k–ω model was used to resolve the airflow and a Lagrangian tracking algorithm was used to simulate the particle transport and deposition. Statistical analysis of predicted doses was conducted using ANOVA. For normal inhalation rates and particle dia- meters ranging from 0.5 to 24 mm, the deposition differences between the life-size and scaled models are insignificant for all airway geometries considered (i.e., human nose, USP, and rat nose). Furthermore, the deposition patterns and exit particle profiles also look similar among scaled models. However, deposition rates and patterns start to deviate if inhalation rates are too low, or particle sizes are too large. For the rat nose, the threshold velocity was found to be 0.71 m/s and the threshold Froude number to be 50. Results of this study provide a theoretical foundation for sub-regional in vitro dosimetry tests in small animals and for interpretation of data from inter-species or intra-species with varying body sizes.
Large-Scale Modeling of Epileptic Seizures: Scaling Properties of Two Parallel Neuronal Network Simulation Algorithms
Our limited understanding of the relationship between the behavior of individual neurons and large neuronal networks is an important limitation in current epilepsy research and may be one of the main causes of our inadequate ability to treat it. Addressing this problem directly via experiments is impossibly complex; thus, we have been developing and studying medium-large-scale simulations of detailed neuronal networks to guide us. Flexibility in the connection schemas and a complete description of the cortical tissue seem necessary for this purpose. In this paper we examine some of the basic issues encountered in these multiscale simulations. We have determined the detailed behavior of two such simulators on parallel computer systems. The observed memory and computation-time scaling behavior for a distributed memory implementation were very good over the range studied, both in terms of network sizes (2,000 to 400,000 neurons) and processor pool sizes (1 to 256 processors). Our simulations required between a few megabytes and about 150 gigabytes of RAM and lasted between a few minutes and about a week, well within the capability of most multinode clusters. Therefore, simulations of epileptic seizures on networks with millions of cells should be feasible on current supercomputers.
Learning continuum-scale models from micro-scale dynamics via Operator Regression.
Abstract not provided.
Pore Scale Modeling of the Reactive Transport of Chromium in the Cathode of a Solid Oxide Fuel Cell
We present a pore scale model of a solid oxide fuel cell (SOFC) cathode. Volatile chromium species are known to migrate from the current collector of the SOFC into the cathode where over time they decrease the voltage output of the fuel cell. A pore scale model is used to investigate the reactive transport of chromium species in the cathode and to study the driving forces of chromium poisoning. A multi-scale modeling approach is proposed which uses a cell level model of the cathode, air channel and current collector to determine the boundary conditions for a pore scale model of a section of the cathode. The pore scale model uses a discrete representation of the cathode to explicitly model the surface reactions of oxygen and chromium with a cathode material. The pore scale model is used to study the reaction mechanisms of chromium by considering the effects of reaction rates, diffusion coefficients, chromium vaporization, and oxygen consumption on chromium’s deposition in the cathode. The study shows that chromium poisoning is most significantly affected by the chromium reaction rates in the cathode and that the reaction rates are a function of the local current density in the cathode.
Verification and Validation of Model-Scale Turbine Performance and Control Strategies for the IEA Wind 15 MW Reference Wind Turbine
To enable the fast growth of the floating offshore wind industry, simulation models must be validated with experimental data. Floating wind model-scale experiments in wind–wave facilities have been performed over the last two decades with varying levels of fidelity and limitations. However, the turbine controls in these experiments have considered only limited control strategies and implementations. To allow for control co-design, this research focuses on implementing and experimentally validating more advanced turbine control actions and strategies in a wind–wave basin for a 1:70-scale model of the International Energy Agency’s wind 15 MW reference wind turbine. The control strategies analyzed include torque control, collective pitch control, and transition region control (setpoint smoothing). Our experimental and numerical results include the effects of varying rotor speeds, blade pitches, and wind environments on the turbine thrust and torque. Numerical models from three different software tools are presented and compared to the experimental results. Their ability to effectively represent the aero-dynamic response of the wind turbine to the control actions is successfully validated. Finally, turbine controller tuning parameters based on the derivatives of thrust and torque are derived to allow for improved offshore wind turbine dynamics and to validate the ability of modeling tools to model the dynamics of floating offshore wind turbines with control co-design.
Fragmentation Prediction for a Brittle Ceramic: An Integrated Two-Scale Model Approach
A new implementation of a multi-scale fragmentation model is introduced that combines existing independent macro and micro-scale models into a single material model within the Library of Advanced Materials for Engineering (LAME) that can be used directly by the finite element structural mechanics code SIERRA/SM, developed at Sandia National Laboratories. The implementation not only joins existing independent fragmentation models into a single framework, but also enables further development by virtue of being integrated into SIERRA/SM. Integration with a finite element structural mechanics code for a true two-way coupling of the fragmentation models that were previously independent. Hereafter, the prior implementation will be referred to as the sequentially applied fragmentation model. In contrast, the newly developed model will be called the integrated two-scale model. The sequentially applied fragmentation model consists of two independent models applied sequentially to account for the macro-scale and microscale fragmentation. The macro-scale fragmentation behavior is calculated using an elastic gradient damage explicit material model developed to model fracture in brittle materials. The micro-scale fragmentation model is an implementation of the 1D cohesive-zone model developed by Zhou, et al. The micro-scale model is implemented by post-processing the macro-scale data that provides initial conditions for the 1D analysis. The micro-scale model is necessary to predict the resulting fragment size distribution at length scales inaccessible to the finite element based macro-scale model. The full range of fragmentation behavior is then predicted by combining the results from the two independent models. The sequentially applied fragmentation model was used to predict the fragments that result from impact loading of a brittle material, which in that case was a ceramic cylinder of commercial UO{sub 2} nuclear fuel. Understanding the fragmentation behavior of such materials is important for evaluating the risk of airborne particulate release under impact loading scenarios. This work will verify the implementation of the integrated two-scale model using the same experiment modeled by the existing sequentially applied model. The purpose of this manuscript is to introduce the new integrated two-scale fragmentation model and validate the implementation against the existing sequentially applied model for a specific case of impact loading of a brittle material. This validation case will not fully utilize the benefits of having the model integrated into the finite element code as a material model. Rather, this study will demonstrate consistency between the two fragmentation models to ensure that the success of the sequentially applied model will be duplicated by the integrated two-scale approach. Once validated, further development of the model can be made by utilizing the integration into the finite element code to create a fully two-way coupled fragmentation model that will be extended to include higher fidelity models.
FINAL REPORT: Mechanistically-Base Field Scale Models of Uranium Biogeochemistry from Upscaling Pore-Scale Experiments and Models
Biogeochemical reactive transport processes in the subsurface environment are important to many contemporary environmental issues of significance to DOE. Quantification of risks and impacts associated with environmental management options, and design of remediation systems where needed, require that we have at our disposal reliable predictive tools (usually in the form of numerical simulation models). However, it is well known that even the most sophisticated reactive transport models available today have poor predictive power, particularly when applied at the field scale. Although the lack of predictive ability is associated in part with our inability to characterize the subsurface and limitations in computational power, significant advances have been made in both of these areas in recent decades and can be expected to continue. In this research, we examined the upscaling (pore to Darcy and Darcy to field) the problem of bioremediation via biofilms in porous media. The principle idea was to start with a conceptual description of the bioremediation process at the pore scale, and apply upscaling methods to formally develop the appropriate upscaled model at the so-called Darcy scale. The purpose was to determine (1) what forms the upscaled models would take, and (2) how one might parameterize such upscaled models for applications to bioremediation in the field. We were able to effectively upscale the bioremediation process to explain how the pore-scale phenomena were linked to the field scale. The end product of this research was to produce a set of upscaled models that could be used to help predict field-scale bioremediation. These models were mechanistic, in the sense that they directly incorporated pore-scale information, but upscaled so that only the essential features of the process were needed to predict the effective parameters that appear in the model. In this way, a direct link between the microscale and the field scale was made, but the upscaling process helped inform potential users of the model what kinds of information would be needed to accurately characterize the system.
1:52 Scale Testing of the First US Commercial Scale Floating Wind Turbine, VolturnUS: Testing Overview and the Evolution of Scale Model Testing Methods
Over the past 6 years, the University of Maine (UMaine) has been an active contributor in research and scale-model testing of floating offshore wind turbines (FOWTs). This paper serves to share the evolution of UMaine’s scale-model testing pedigree by exploring the various test campaigns at a high level, culminating with the design validation of the VolturnUS floating platform. These model test campaigns have each provided key insights into the behavior of FOWT platforms as well as improving the ability to perform model tests of FOWTs. In 2011, the UMaine-led DeepCwind Consortium carried out 1/50-scale model tests of a generic tension leg platform (TLP), a semi-submersible (semi), and a spar-buoy (spar) floating platform at the Maritime Research Institute Netherlands (MARIN) test facility. The designs were Froude-scaled and supported a scaled version of the 5-MW National Renewable Energy Laboratory (NREL) offshore research turbine. Data from these tests has been used extensively for numerical simulation validation efforts using NREL’s computer-aided engineering software FAST and laid the foundation for UMaine’s design efforts on VolturnUS. In 2013, UMaine conducted another test campaign at MARIN using the original semi-submersible from 2011 with an improved turbine as well as a 1:50-scale model of the VolturnUS concrete semi-submersible design. The improved DeepCwind semi-submersible data is currently being utilized in the validation of a large number of other analysis codes as part of the International Energy Agency’s OC5 project. In 2015, UMaine opened its own Wind/Wave test facility, the Alfond Wind/Wave Ocean Engineering Laboratory (W2). Utilizing this new facility, UMaine tested the 1:50-scale model DeepCwind semi-submersible, repeating the tests from MARIN, to validate the experimental equipment and procedures as well as demonstrate the capability of the W2. In 2016 UMaine carried out testing of a 1:52-scale model of the 100% design of the VolturnUS with a 6-MW topside as a final design validation to support the US Department of Energy-supported, full-scale Aqua Ventus demonstration project scheduled to be connected to the grid in 2019. A newly designed 6-MW scale model turbine was used in this test and the performance-matched turbine design methodology is described. Selected results from the test campaign and preliminary numerical comparisons are discussed as well as key lessons learned from the model test campaigns are presented.
Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth
The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction–diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction–diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge of front, which cannot be accounted for by the coarse-grained model. Such fluctuations have non-trivial effects on the wave velocity. Beyond the development of a new hybrid method, we thus conclude that birth-rate fluctuations are central to a quantitatively accurate description of invasive phenomena such as tumour growth. - Highlights: • A hybrid method for stochastic multi-scale models of cells populations that extends existing hybrid methods for reaction–diffusion system. • Our analysis unveils non-trivial macroscopic effects triggered by noise at the level of structuring variables. • Our hybrid method hugely speeds up age-structured SSA simulations while preserving stochastic effects.
Understanding Precipitation Bias Sensitivities in E3SM-Multi-Scale Modeling Framework From a Dilution Framework
We investigate a set of Energy Exascale Earth System Model Multi-scale modeling framework (MMF) (E3SM-MMF) simulations that vary the dimensionality and momentum transport configurations of the embedded cloud-resolving models (CRMs), including unusually ambitious 3D configurations. Issues endemic to all MMF simulations include too much Intertropical Convergence Zone rainfall and too little over the Amazon. Systematic MMF improvements include more on-equatorial rainfall across the Warm Pool. Interesting sensitivities to the CRM domain are found in the regional time-mean precipitation pattern over the tropics. The 2D E3SM-MMF produces an unrealistically rainy region over the northwestern tropical Pacific; this is reduced in computationally ambitious 3D configurations that use 1,024 embedded CRM grid columns per host cell. Trajectory analysis indicates that these regional improvements are associated with desirably fewer tropical cyclones and less extreme precipitation rates. To understand why and how the representation of precipitation improved in 3D, we propose a framework that dilution is stronger in 3D. This viewpoint is supported by multiple indirect lines of evidence, including a delayed moisture-precipitation pickup, smaller precipitation efficiency, and amplified convective mass flux profiles and more high clouds. We also demonstrate that the effects of varying embedded CRM dimensionality and momentum transport on precipitation can be identified during the first few simulated days, providing an opportunity for rapid model tuning without high computational cost. Meanwhile the results imply that other less computationally intensive ways to enhance dilution within MMF CRMs may also be strategic tuning targets.
BiGG Models: A platform for integrating, standardizing and sharing genome-scale models
In this study, genome-scale metabolic models are mathematically structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scale metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data.
Multi-Scale Modeling Framework for Mercury Biogeochemistry
Multi-Scale modeling of mercury (Hg) geochemical speciation and reactions has been performed by integrating atomistic quantum chemical calculations with continuum scale speciation models. Major progress has been made in the improvement of quantum chemical models to calculate critical thermodynamic data for Hg complexes in aquatic environments. Rapid and reliable quantum chemical approaches have been developed for calculating acid dissociation constants (pK a ) and stability constants (log K), with calculated mean unsigned errors of 0.5 and 1.5 log units, respectively for ligand molecules and Hg complexes. At the continuum scale, systematic analysis of uncertainty propagation in mercury (Hg) speciation modeling has been conducted and was used to identify environmental conditions under which thermodynamic constant uncertainties are significant and recommended to be accounted for. The integrated framework for multi-scale modeling of mercury geochemistry is open to the research community through the web-based multiscale modeling aqueous speciation resource, AQUA-MER. The improved quantum chemical approaches for thermodynamic constant calculations are accessible through AQUA-MER and can be used to provide the missing constants in the continuum scale speciation calculations. In addition to low molecular mass Hg complex speciation, modeling natural aquatic environments also involve the transport of high molecular weight dissolved organic matter (DOM) in reactive flows simultaneously with equilibrium and kinetic reactions. To this end, atomistic MD simulations were performed to capture the details of aggregation, mechanisms and distribution of functional groups in DOM at the molecular level. The elemental composition and calculated bulk properties of the DOM models are in close agreement with experimental measurements. A travel-time based reactive transport model in the hyporheic zone of stream corridors was established for the multicomponent Hg-DOM-S system and implemented through PFLOTRAN.