A Simulation Test Bed for Evaluating Data Analytic Predictors of Disinformation Flow.
Abstract not provided.
Lakkaraju, Kiran↗
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Results for “simulation analytics”
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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Modeling thermal radiation waves in silica plasmas for the Mooncat NIF experiment
The Mooncat experiment on the National Ignition Facility uses a laser-driven hohlraum to create a thermal radiation wave in a titanium-doped silica plasma. The titanium dopant enables absorption spectroscopy measurements to infer the temperature of the wave as it propagates. This measurement can be used to constrain multi-physics simulation codes to better understand when simulations do not match an experiment. In this paper, we present radiation-hydrodynamics simulations of the thermal radiation wave in the first full-platform shots of the Mooncat experiment. We examine the important parameters of the simulation, focusing on the radiation temperature source, the material model of the silica plasma as it pertains to radiation transport, and lateral leakage through a beryllium tube enclosing the silica. We compare different simulation modeling strategies to an analytic model of diffusive radiation transport and find that the simulation agrees with the analytic model when it is sufficiently simplified. These simulations show how radiation energy couples to matter to develop a shock wave in a radiative heat wave, an important topic in astrophysics and nuclear fusion plasmas.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Development and Test of Simulation Tools for EIC Beam-Beam Interaction (Final Technical Report)
This final technical report summarizes the work of the Michigan State University (MSU) team supported by grant # DE-SC0018973 awarded by the Office of Nuclear Physics, Department of Energy. The awarded proposal is a joint effort of Brookhaven National Laboratory (BNL, led by Dr. Yun Luo), Lawrence Berkeley National Laboratory (LBNL, led by Dr. Ji Qiang), Thomas Jefferson National Accelerator Facility (TJNAF, led by Dr. Yves Roblin) and MSU (led by Dr. Yue Hao). The MSU personnel supported by the grant include Dr. Yue Hao and Dr. Derong Xu, who is hired as a postdoctoral research fellow. MSU team ‘s work in this proposal focused on the beam dynamics study and numerical simulation of crabbed collision with crab cavities. Analytical calculations and numerous simulations have been done to identify beam dynamics effect out of numerical noises, study the synchro-betatron resonance in the crab crossing scheme, evaluate the effects of non-ideal settings for crab cavity and the effects of the crab crossing noises. The results have been published in journals and as conference proceedings. From the results of the proposal, we gained a clear understanding of the beam-beam interaction in the EIC designs and provided robust countermeasures to possible beam-beam interaction related to beam lifetime reduction, beam emittance growth, beam instabilities, and luminosity degradation, which significantly mitigate the technical risks associated with the EIC accelerator designs.
43 PARTICLE ACCELERATORS↗
Data on erosion and hydrogen fuel retention in Beryllium plasma-facing materials
ITER will use beryllium as a plasma-facing material in the main chamber, covering a total surface area of about 620 m 2 . Given the importance of beryllium erosion and co-deposition for tritium retention in ITER, significant efforts have been made to understand the behaviour of beryllium under fusion-relevant conditions with high particle and heat loads. This paper provides a comprehensive report on the state of knowledge of beryllium behaviour under fusion-relevant conditions: the erosion mechanisms and their consequences, beryllium migration in JET, fuel retention and dust generation. The paper reviews basic laboratory studies, advanced computer simulations and experience from laboratory plasma experiments in linear simulators of plasma–wall interactions and in controlled fusion devices using beryllium plasma-facing components. A critical assessment of analytical methods and simulation codes used in beryllium studies is given. The overall objective is to review the existing set of data with a broad literature survey and to identify gaps and research needs to broaden the database for ITER.
Erosion–deposition↗
The Critical Stack Pressure to Alter Void Generation at Li/Solid-Electrolyte Interfaces during Stripping
The lithium stripping process generates vacancies, which may accumulate as voids and lead to uneven current distribution and dendrite growth in the following plating cycles. A stack pressure is typically required during stripping, but how to optimize the stack pressure is not clear. In this work, extremely lithiophilic Li/Li 2 O and lithiophobic Li/LiF interfaces were used to reveal the combining effect of interface interaction and stack pressure induced lithium creep on the stripping critical current density (CCD). A multiscale simulation scheme with Density Functional Theory (DFT), kinetic Monte Carlo (KMC) simulations, and an analytical model was developed. The analytical model predicted lithiophobic interfaces require a higher stack pressure than lithiophilic interfaces to reach the same CCD. The KMC simulations also showed higher stack pressure is needed at lithiophobic interfaces to accelerate Li vacancy diffusion into the bulk and maintain a flat surface. This stack pressure needs to be high enough to alter the Li forward-and-backward hopping barriers at the interface. This multiscale simulation scheme illustrates the importance to include the chemical-mechanical effects during Li stripping morphology evolution. It can be used to design ideal interlayer coating materials to maintain a flat Li surface during cycling.
25 ENERGY STORAGE↗
Accurate shear estimation with fourth-order moments
ABSTRACT As imaging surveys progress in exploring the large-scale structure of the Universe through the use of weak gravitational lensing, achieving sub-per cent accuracy in estimating shape distortions caused by lensing, or shear, is imperative for precision cosmology. In this paper, we extend the Fourier power function shapelets (FPFS) shear estimator using fourth-order shapelet moments and combine it with the original second-order shear estimator to reduce galaxy shape noise. We calibrate this novel shear estimator analytically to a sub-per cent level-accuracy using the AnaCal framework. This higher order shear estimator is tested with realistic image simulations, and after analytical correction for the detection/selection bias and noise bias, the multiplicative shear bias $|m|$ is below $3\times 10^{-3}$ (99.7 per cent confidence interval) for both isolated and blended galaxies. Once combined with the second-order FPFS shear estimator, the shape noise is reduced by $\sim 35~{{\ \rm per\ cent}}$ for isolated galaxies in simulations with Hyper Suprime-Cam and Vera C. Rubin Observatory Legacy Survey of Space and Time observational conditions. However, for blended galaxies, the effective number density does not significantly improve with the combination of the two estimators. Based on these results, we recommend exploration of how this framework can further reduce the systematic uncertainties in shear due to point spread function leakage and modelling error, and potentially provide improved precision in shear inference in high-resolution space-based images.
79 ASTRONOMY AND ASTROPHYSICS↗
Precision measurements of EFT parameters and BAO peak shifts for the Lyman- α forest
We present precision measurements of the bias parameters of the one-loop power spectrum model of the Lyman- α (Ly- α ) forest, derived within the effective field theory (EFT) of large-scale structure. We fit our model to the three-dimensional flux power spectrum measured from the ACCEL 2 hydrodynamic simulations. The EFT model fits the data with an accuracy of below 2% up to k = 2 h Mpc − 1 . Further, we analytically derive how nonlinearities in the three-dimensional clustering of the Ly- α forest introduce biases in measurements of the baryon acoustic oscillations (BAOs) scaling parameters in radial and transverse directions. From our EFT parameter measurements, we obtain a theoretical error budget of Δ α ∥ = − 0.2 % ( Δ α ⊥ = − 0.3 % ) for the radial (transverse) parameters at redshift z = 2.0 . This corresponds to a shift of − 0.3 % (0.1%) for the isotropic (anisotropic) distance measurements. We provide an estimate for the shift of the BAO peak for Ly- α -quasar cross-correlation measurements assuming analytical and simulation-based scaling relations for the nonlinear quasar bias parameters resulting in a shift of − 0.2 % ( − 0.1 % ) for the radial (transverse) dilation parameters, respectively. This analysis emphasizes the robustness of Ly- α forest BAO measurements to the theory modeling. We provide informative priors and an error budget for measuring the BAO feature—a key science driver of the currently observing Dark Energy Spectroscopic Instrument (DESI). Our work paves the way for full-shape cosmological analyses of Ly- α forest data from DESI and upcoming surveys such as the Prime Focus Spectrograph, WEAVE-QSO, and 4MOST. Published by the American Physical Society 2025
de Belsunce, Roger (ORCID:0000000336604028)↗
A Visual Analytic Platform for Interactive Validation of Human Mobility Simulations
Human mobility insights guide domain experts in an array of decisions, including critical infrastructure design, disaster response, epidemic modeling, national security, and policy making. Due to the inherent noise and privacy concerns in real-world individual-level mobility data, it is often preferred to leverage simulators that generate synthetic mobility data instead. However, it is critical to inspect and validate the output of such simulators to ensure the synthetic data is aligned with the characteristics of the population and the area of interest known to domain experts. While there exist many quantitative approaches for validating synthetic data, we argue it is also important to also validate such data qualitatively to capture aspects that are known to domain experts but difficult to quantify. In this work, we demonstrate a visual analytic platform that empowers domain experts to interact with their simulation outputs along spatial and temporal dimensions. By augmenting automated techniques and human skills, our visual analytic platform is a step towards interactive capabilities for model steering and quality control of mobility simulators.
Monadjemi, Shayan↗
Estimation of the time for steam generator trip due to cyber intrusions
The time required to trip a pressurized water reactor (PWR) by inserting malicious signals into its steam generator (SG) control system has been studied using the Generic PWR (GPWR) Simulator. A semi-analytical model is developed to approximately reproduce the simulator response and understand the dynamics of the control unit. A series of two proportional-integral controllers determines control action according to preset constants, the readings from the feedwater level sensor, and those from feedwater and steam flowrate transmitters. It is observed that the most important factor that determines whether a trip will occur is how much additional water is added to or withheld from the SG over time compared to normal operating conditions. In order to determine the effects of control action on the SG, changes in mass inventory are considered. This approach models the SG water level as a function of mass inventory and has a backward temporal memory. A Python interface is developed for the GPWR framework to automatically simulate different spoofing scenarios and post-process the related data. We observe that the trip times predominantly depend on flow mismatch and/or level errors. Controller parameters, including the integral time and gain constants, either speed up or slow down the rate of progression to a trip setpoint but do not cause a trip by themselves. The reactor can trip on a high-level signal when the reading crosses above 78%, increased from its reference level of 57%, or a low-level reading when it is below 25%. The present results show roughly how long the operators would have to respond to an attack, given a specific set of spoofing signals within the issue space analyzed. Furthermore, we have generated a simple surface by fitting a combination of exponential functions to the data obtained from the GPWR Simulator. In general, trips on a low level have been observed to occur faster than those on a high level.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Analytical and Numerical Analysis of Lithium Plating Onset in Single and Bilayer Graphite Electrodes during Fast Charging
Lithium plating is commonly observed in anodes charged at fast rates, and can lead to capacity loss and battery safety issues. The increased risk of plating has been attributed to transport limitations, and architectured electrodes may reduce plating risk. However, while theoretical studies have shown that reaction non-uniformity arises due to interplay of transport limitations, anode open circuit voltage behavior and reaction kinetics, its effect on lithium plating has not been studied. We use analytic and numerical simulations to predict onset of plating in graphite anode half-cells at high C-rates and demonstrate how anodes with layered porosities can delay plating. Simplified analytical models identify trends for plating onset and predictions are calibrated against numerical models. A calibrated numerical model of graphite demonstrates qualitative agreement with analytical model predictions. This reaction inhomogeneity mechanism occurs in the absence of lithium ion depletion, indicating that these mechanisms may contribute to capacity loss independently or simultaneously. A bilayer model of graphite exhibits delayed plating onset, and an optimization procedure is presented. This theoretical work presents quantitative and mechanistic insight on how reaction inhomogenity affects lithium metal plating onset and can be used as a guide to engineer anodes resistant to lithium plating.
Mijailovic, Aleksandar S.↗
A Data-Driven Global Sensitivity Analysis Framework for Three-Phase Distribution System with PVs
Global sensitivity analysis (GSA) of distribution systems with respect to stochastic PV and load variations plays an important role in designing optimal voltage control schemes. This paper proposes a data-driven framework for GSA of distribution systems. In particular, two representative surrogate modeling-based approaches are developed, including the traditional Gaussian process-based and the analysis of variance (ANOVA) kernel ones. The key idea is to develop a surrogate model that captures the hidden global relationship between voltage and real and reactive power injections from the historical data. With the surrogate model, the Sobol indices can be conveniently calculated through either the sampling-based method or the analytical method to assess the global sensitivity of voltage to variations of PV and load power injections. The sampling-based method approximates the Sobol indices using Monte Carlo simulations while the analytical method calculates them by resorting to the ANOVA expansion framework. Comparison results with other model-based GSA methods on the unbalanced three-phase IEEE 37-bus and 123-bus distribution systems show that the proposed framework can achieve much higher computational efficiency with negligible loss of accuracy. The results on a real 240-node distribution system using actual smart meter data further validate the feasibility and scalability of the proposed framework.
14 SOLAR ENERGY↗
Wall heating by subcritical energetic electrons generated by the runaway electron avalanche source *
Abstract Subcritical energetic electrons (SEEs) produced by the runaway electron (RE) avalanche source at energies below the runaway threshold are found to be the primary contributor to surface heating of plasma-facing components (PFCs) during final loss events. This finding is supported by theoretical analysis, computational modeling with the Kinetic Orbit Runaway electrons Code (KORC), and qualitative agreement with DIII-D experimental observations. The avalanche source generates significantly more secondary electrons below the runaway threshold, which thermalize rapidly when well-confined. However, during a final loss event, the RE beam impacts the first wall, and SEEs are deconfined before they can thermalize. Additionally, because the energy deposition length decreases faster than energy, the deposited energy density, and thus the maximum PFC surface temperature change, is larger for SEEs than REs. KORC simulations employ an analytic first wall to model particle deconfinement onto a non-axisymmetric wall composed of individual tiles. PFC surface heating is calculated using a 1D model extended to include an energy-dependent deposition length scale. Simulations of DIII-D qualitatively agree with infrared (IR) imaging only when SEEs from the avalanche source are included. These results demonstrate that SEEs are the dominant contributor to PFC surface heating and indicate that the avalanche source plays a critical role in the PFC damage caused during final loss events. The prominence of SEEs also has important implications for interpreting IR imaging, one of the primary diagnostics for RE-wall interaction diagnosis, despite REs dominating the energy and current density. This result improves predictions of wall damage due to post-disruption REs to estimate material lifetime and design RE mitigation systems for ITER and future reactors.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Including Neutrino-driven Convection in the Force Explosion Condition to Predict Explodability of Multidimensional Core-collapse Supernovae (FEC+)
Abstract Most massive stars end their lives with core collapse. However, it is not clear which explode as a core-collapse supernova (CCSN), leaving behind a neutron star, and which collapse to a black hole, aborting the explosion. One path to predict explodability without expensive multidimensional simulations is to develop analytic explosion conditions. These analytic conditions also provide a deeper understanding of the explosion mechanism and they provide some insight into why some simulations explode and some do not. The analytic force explosion condition (FEC) reproduces the explosion conditions of spherically symmetric CCSN simulations. In this follow-up manuscript, we include the dominant multidimensional effect that aids explosion—neutrino-driven convection—in the FEC. This generalized critical condition (FEC+) is suitable for multidimensional simulations and has potential to accurately predict explosion conditions of two- and three-dimensional CCSN simulations. We show that adding neutrino-driven convection reduces the critical condition by ∼30%, which is consistent with previous multidimensional simulations.
Gogilashvili, Mariam (ORCID:0000000269448052)↗
Learning to simulate high energy particle collisions from unlabeled data
In many scientific fields which rely on statistical inference, simulations are often used to map from theoretical models to experimental data, allowing scientists to test model predictions against experimental results. Experimental data is often reconstructed from indirect measurements causing the aggregate transformation from theoretical models to experimental data to be poorly-described analytically. Instead, numerical simulations are used at great computational cost. We introduce Optimal-Transport-based Unfolding and Simulation (OTUS), a fast simulator based on unsupervised machine-learning that is capable of predicting experimental data from theoretical models. Without the aid of current simulation information, OTUS trains a probabilistic autoencoder to transform directly between theoretical models and experimental data. Identifying the probabilistic autoencoder’s latent space with the space of theoretical models causes the decoder network to become a fast, predictive simulator with the potential to replace current, computationally-costly simulators. Here, we provide proof-of-principle results on two particle physics examples, Z-boson and top-quark decays, but stress that OTUS can be widely applied to other fields.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
X-composer: enabling cross-environments in-situ workflows between HPC and cloud
As large-scale scientific simulations and big data analyses become more popular, it is increasingly more expensive to store huge amounts of raw simulation results to perform post-analysis. To minimize the expensive data I/O, "in-situ" analysis is a promising approach, where data analysis applications analyze the simulation generated data on the fly without storing it first. However, it is challenging to organize, transform, and transport data at scales between two semantically different ecosystems due to the distinct software and hardware difference. To tackle these challenges, we design and implement the X-Composer framework. X-Composer connects cross-ecosystem applications to form an "in-situ" scientific workflow, and provides a unified approach and recipe for supporting such hybrid in-situ workflows on distributed heterogeneous resources. X-Composer reorganizes simulation data as continuous data streams and feeds them seamlessly into the Cloud-based stream processing services to minimize I/O overheads. For evaluation, we use X-Composer to set up and execute a cross-ecosystem workflow, which consists of a parallel Computational Fluid Dynamics simulation running on HPC, and a distributed Dynamic Mode Decomposition analysis application running on Cloud. Our experimental results show that X-Composer can seamlessly couple HPC and Big Data jobs in their own native environments, achieve good scalability, and provide high-fidelity analytics for ongoing simulations in real-time.
Wang, Dali↗
Facilitating Staging-based Unstructured Mesh Processing to Support Hybrid In-Situ Workflows
In-situ and in-transit processing alleviate the gap between the computing and I/O capabilities by scheduling data analytics close to the data source. Hybrid in-situ processing splits data analytics into two stages: the data processing that runs in-situ aims to extract regions of interest, which are then transferred to staging services for further in-transit analytics. To facilitate this type of hybrid in-situ processing, the data staging service needs to support complex intermediate data representations generated/consumed by the in-situ tasks. Unstructured (or irregular) mesh is one such derived data representation that is typically used and bridges simulation data and analytics. However, how staging services efficiently support unstructured mesh transfer and processing remains to be explored. This paper investigates design options for transferring and processing unstructured mesh data using staging services. Using polygonal mesh data as an example, we show that hybrid in-situ workflows with staging-based unstructured mesh processing can effectively support hybrid in-situ workflows, and can significantly decrease data movement overheads.
data-driven↗
Kinematic Evidence for an Embedded Planet in the IM Lupi Disk
Abstract We test the hypothesis that an embedded giant planet in the IM Lupi protostellar disk can produce velocity kinks seen in CO line observations as well as the spiral arms seen in scattered light and continuum emission. We inject planets into 3D hydrodynamics simulations of IM Lupi, generating synthetic observations using Monte Carlo radiative transfer. We find that an embedded planet of 2–3 M Jup can reproduce non-Keplerian velocity perturbations, or “kinks”, in the 12 CO J = 2–1 channel maps. Such a planet can also explain the spiral arms seen in 1.25 mm dust continuum emission and 1.6 μ m scattered-light images. We show that the wake of the planet can be traced in the observed peak velocity map, which appears to closely follow the morphology expected from our simulations and from analytic models of planet–disk interaction.
79 ASTRONOMY AND ASTROPHYSICS↗
On the shear-current effect: toward understanding why theories and simulations have mutually and separately conflicted
ABSTRACT The shear-current effect (SCE) of mean-field dynamo theory refers to the combination of a shear flow and a turbulent coefficient β21 with a favourable negative sign for exponential mean-field growth, rather than positive for diffusion. There have been long-standing disagreements among theoretical calculations and comparisons of theory with numerical experiments as to the sign of kinetic ($\beta ^u_{21}$) and magnetic ($\beta ^b_{21}$) contributions. To resolve these discrepancies, we combine an analytical approach with simulations, and show that unlike $\beta ^b_{21}$, the kinetic SCE $\beta ^u_{21}$ has a strong dependence on the kinetic energy spectral index and can transit from positive to negative values at $\mathcal {O}(10)$ Reynolds numbers if the spectrum is not too steep. Conversely, $\beta ^b_{21}$ is always negative regardless of the spectral index and Reynolds numbers. For very steep energy spectra, the positive $\beta ^u_{21}$ can dominate even at energy equipartition urms ≃ brms, resulting in a positive total β21 even though $\beta ^b_{21}\lt 0$. Our findings bridge the gap between the seemingly contradictory results from the second-order-correlation approximation versus the spectral-τ closure, for which opposite signs for $\beta ^u_{21}$ have been reported, with the same sign for $\beta ^b_{21}\lt 0$. The results also offer an explanation for the simulations that find $\beta ^u_{21}\gt 0$ and an inconclusive overall sign of β21 for $\mathcal {O}(10)$ Reynolds numbers. The transient behaviour of $\beta ^u_{21}$ is demonstrated using the kinematic test-field method. We compute dynamo growth rates for cases with or without rotation, and discuss opportunities for further work.
79 ASTRONOMY AND ASTROPHYSICS↗