A synthetic case study of measuring the misfit between 4D seismic data and numerical reservoir simulation models through the Momenta Tree
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Soriano-Vargas, Aurea (ORCID:0000000284294119)↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Use of a controlled experiment and computational models to measure the impact of sequential peer exposures on decision making
It is widely believed that one’s peers influence product adoption behaviors. This relationship has been linked to the number of signals a decision-maker receives in a social network. But it is unclear if these same principles hold when the “pattern” by which it receives these signals vary and when peer influence is directed towards choices which are not optimal. To investigate that, we manipulate social signal exposure in an online controlled experiment using a game with human participants. Each participant in the game decides among choices with differing utilities. We observe the following: (1) even in the presence of monetary risks and previously acquired knowledge of the choices, decision-makers tend to deviate from the obvious optimal decision when their peers make a similar decision which we call the influence decision, (2) when the quantity of social signals vary over time, the forwarding probability of the influence decision and therefore being responsive to social influence does not necessarily correlate proportionally to the absolute quantity of signals. To better understand how these rules of peer influence could be used in modeling applications of real world diffusion and in networked environments, we use our behavioral findings to simulate spreading dynamics in real world case studies. We specifically try to see how cumulative influence plays out in the presence of user uncertainty and measure its outcome on rumor diffusion, which we model as an example of sub-optimal choice diffusion. Together, our simulation results indicate that sequential peer effects from the influence decision overcomes individual uncertainty to guide faster rumor diffusion over time. However, when the rate of diffusion is slow in the beginning, user uncertainty can have a substantial role compared to peer influence in deciding the adoption trajectory of a piece of questionable information.
97 MATHEMATICS AND COMPUTING↗
Across‐model spread and shrinking in predicting peatland carbon dynamics under global change
Abstract Large across‐model spread in simulating land carbon (C) dynamics has been ubiquitously demonstrated in model intercomparison projects (MIPs), and became a major impediment in advancing climate change prediction. Thus, it is imperative to identify underlying sources of the spread. Here, we used a novel matrix approach to analytically pin down the sources of across‐model spread in transient peatland C dynamics in response to a factorial combination of two atmospheric CO 2 levels and five temperature levels. We developed a matrix‐based MIP by converting the C cycle module of eight land models (i.e., TEM, CENTURY4, DALEC2, TECO, FBDC, CASA, CLM4.5 and ORCHIDEE) into eight matrix models. While the model average of ecosystem C storage was comparable to the measurement, the simulation differed largely among models, mainly due to inter‐model difference in baseline C residence time. Models generally overestimated net ecosystem production (NEP), with a large spread that was mainly attributed to inter‐model difference in environmental scalar. Based on the sources of spreads identified, we sequentially standardized model parameters to shrink simulated ecosystem C storage and NEP to almost none. Models generally captured the observed negative response of NEP to warming, but differed largely in the magnitude of response, due to differences in baseline C residence time and temperature sensitivity of decomposition. While there was a lack of response of NEP to elevated CO 2 (eCO 2 ) concentrations in the measurements, simulated NEP responded positively to eCO 2 concentrations in most models, due to the positive responses of simulated net primary production. Our study used one case study in Minnesota peatland to demonstrate that the sources of across‐model spreads in simulating transient C dynamics can be precisely traced to model structures and parameters, regardless of their complexity, given the protocol that all the matrix models were driven by the same gross primary production and environmental variables.
Hou, Enqing↗
Hybrid Simulations of FRC Merging and Compression
An improved understanding of field-reversed configuration (FRC) merging and stability in high acceleration and compression magnetic fields is needed to speed up the development of the pulsed fusion concept developed at Helion Energy. All previous theoretical and simulation work on FRC merging and compression was performed using two-dimensional (2D) magnetohydrodynamic (MHD) models. The results of novel 2D hybrid simulations (fluid electrons and full-orbit kinetic ions) of FRC merging and compression are presented. Results of kinetic and MHD simulations, computed using the HYM code, are compared and analyzed. In cases without axial magnetic compression, both the MHD and hybrid simulations show a high sensitivity to the initial parameters (i.e. FRC separation, velocity, normalized separatrix radius, and plasma viscosity), showing that FRCs with large elongation and separatrix radius either do not merge or merge partially, forming a doublet FRC. In conclusion, application of a mirror coil field at the FRC ends with increasing strength is shown to lead to fast and complete merging of the FRCs in MHD and kinetic simulations.
FRC↗
Lefschetz thimble quantum Monte Carlo for spin systems
Monte Carlo simulations are useful tools for modeling quantum systems, but in some cases they suffer from a sign problem, leading to an exponential slow down in their convergence to a value. While solving the sign problem is generically NP hard, many techniques exist for mitigating the sign problem in specific cases; in particular, the technique of deforming the Monte Carlo simulation's plane of integration onto Lefschetz thimbles (complex hypersurfaces of stationary phase) has seen significant success in the context of quantum field theories. We extend this methodology to spin systems by utilizing spin coherent state path integrals to reexpress the spin system's partition function in terms of continuous variables. Using some toy systems, we demonstrate its effectiveness at lessening the sign problem in this setting, despite the fact that the initial mapping to spin coherent states introduces its own sign problem. The standard formulation of the spin coherent path integral is known to make use of uncontrolled approximations; despite this, for large spins they are typically considered to yield accurate results, so it is somewhat surprising that our results show significant systematic errors. Furthermore, possibly of independent interest, our use of Lefschetz thimbles to overcome the intrinsic sign problem in spin coherent state path integral Monte Carlo enables a novel numerical demonstration of a breakdown in the spin coherent path integral.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
The influence of wind veer and drivetrain flexibility on fatigue loading for large floating wind turbines
To reduce costs, offshore wind turbines are expected to be designed with significantly increased rotor diameters. Larger turbines become more flexible and span a larger portion of the atmospheric boundary layer. With these changes, the validity of traditional modeling assumptions should be investigated. This work challenges two common assumptions: (1) that the drivetrain can be considered rigid (except in torsion) and does not couple with the rotor and tower and 2) that wind directional change with height (veer) does not greatly influence the fatigue damage in the tower, blades and drivetrain. Two large semi-submersible floating wind turbines are considered: a 15 and a 22 MW reference turbine. Both use direct-drive generators. Aero-hydro-servo-elastic simulations are performed using OpenFAST, with drivetrain bending flexibility and main bearing response implemented in the coupled analysis. The turbines are subjected to a set of load cases at below-, near- and above-rated mean wind speeds, assembled based on the 3 km Norwegian reanalysis (NORA3) hourly wind and wave hindcast data for Utsira Nord, off the coast of Norway. In each load case, conditions with and without veer are simulated to evaluate the influence of veer on damage equivalent loads (DELs) of the turbine tower, blades and main bearings. Further, these load cases are applied to evaluate the influence of drivetrain flexibility on aero-elastic turbine response. The results indicate that, depending on the veer gradient, mean wind speed, operating regime and turbine size, veer can be very important for tower-top DELs and the fluctuations of main bearing radial loads, while main bearing and blade-root flapwise DELs are less affected. Considering these specific load cases and turbine models, drivetrain flexibility is found to significantly influence tower-top DELs of the largest turbine: the tower-top fore-aft and torsional damage equivalent moments of the 22 MW turbine are reduced by more than 20 % at near-rated wind speeds when the drivetrain is modeled as flexible.
17 WIND ENERGY↗
Interleaved Cuk Converter Wave Energy System With Advanced Control and Grid Support Functions for Seamless Integration: Preprint
This paper presents an innovative wave energy conversion system employing an interleaved Cuk converter and advanced nonlinear control for seamless integration with the grid. The proposed system utilizes the interleaved Cuk converter for efficient power extraction on the DC side, while an inverter facilitates power transfer to the grid or load on the AC side. A sophisticated nonlinear control architecture based on Lyapunov energy functions ensures stable and optimal operation under varying wave conditions. Case study results demonstrate the effectiveness of the proposed system, highlighting its ability to efficiently harness wave energy and seamlessly integrate with the grid, thus paving the way for sustainable and reliable renewable energy generation. The overall system is verified via computer simulations based on MATLAB/Simulink and various case study results are presented.
HYDRO ENERGY,TIDAL AND WAVE POWER↗
Microscale THMC Modeling of Pressure Solution in Salt Rock: Impacts of Geometry and Temperature
Abstract Pressure solution, a mechanism that involves tight coupling between the geometry and thermal-hydro-mechanical-chemical (THMC) processes, plays an important role in diagenesis. In this study, we make the first attempt to conduct microscale THMC modeling to understand and quantify the impacts of geometry and temperature on pressure solution, taking natural salt rock as an example. This modeling capability is achieved by expanding a novel MC code that we developed previously (Hu et al. J Geophys Res: Solid Earth 126:e2021JB023112, 2021) to include temperature effects. We first conduct a simulation of an example that involves a single brine inclusion within a single halite grain and find that the temperature impact is limited for that case. We then extract geometry from an image of a natural salt rock and conduct simulations with different cases: (A) only temperature and no stress, (B) only stress and no temperature, and (C) with both stress and temperature. These different cases result in quite different phenomena. In case A, dissolution and precipitation occur across the entire system due to isolated pore space reaching a localized mass balance between dissolution, precipitation, and diffusion. In case B, intense geometric features (e.g., major asperities, inclusions) in one area undergo stress concentration, thus dominating pressure solution in that area. In case C, pressure solution is spread out at contacting highly stressed geometric features close to the hotter side. We conclude that geometric features dominate stress distribution, thus dominating pressure solution in a natural salt rock that may be affected by the temperature if a sufficient temperature gradient is applied.
58 GEOSCIENCES↗
Effect of Packing Nonuniformity at the Fiber Bundle–Case Interface on Performance of Hollow Fiber Membrane Gas Separation Modules
High-fidelity simulations of momentum and mass transfer within a hollow fiber gas separation membrane module are here reported. The simulations capture the potential detrimental effects of poor fiber packing at the bundle–case interface on fluid distribution and performance. Results are presented for both circular and planar fiber bundles. The length over which bundle–case gaps affects flow is determined. The length increases dramatically with increasing fiber packing fraction. As the packing fraction approaches 0.6, the impact extends over the entire bundle diameter for small modules (<1000 fibers). The results clearly demonstrate the detrimental effect of poor packing along the case and can be used to develop module manufacturing guidelines. To reduce computational costs, an equivalent planar bundle module approximation is developed. The approximate simulations agree well with results from full 3-D simulations and can reduce computational costs without sacrificing fidelity.
42 ENGINEERING↗
Deciphering the Cofilin Oligomers via Intermolecular Disulfide Bond Formation: A Coarse-Grained Molecular Dynamics Approach to Understanding Cofilin’s Regulation on Actin Filaments
Cofilin, a key actin-binding protein, orchestrates the dynamics of the actomyosin network through its actin-severing activity and by promoting the recycling of actin monomers. Recent experimental work suggests that cofilin also forms functionally distinct oligomers through thiol post-translational modification (PTM) that encourages actin nucleation and assembly. Despite these advances, the structural conformations of cofilin oligomers that modulate actin activity remain elusive because there are combinatorial ways to oxidize thiols in cysteines to form disulfide bonds rapidly. This study employs molecular dynamics simulations to investigate human cofilin 1 as a case study for exploring cofilin dimers via disulfide bond formation. Using the free energy profiling, our simulations unveil a range of probable cofilin dimer structures not represented in current Protein Data Bank entries. These candidate dimers are characterized by their distinct population distributions and relative free energies. Of particular note is a dimer featuring an interface between cysteines 139 and 147 residues, which demonstrates stable free energy characteristics and intriguingly symmetrical geometry. In contrast, the experimentally proposed dimer structure exhibits a less stable free energy profile. Here, we also evaluate frustration quantification based on the energy landscape theory in the protein-protein interactions at the dimer interfaces. Notably, the 39-39 dimer configuration emerges as a promising candidate for forming cofilin tetramers, as substantiated by frustration analysis. Additionally, docking simulations with actin filaments further evaluate the stability of these cofilin dimer-actin complexes. Our findings thus offer a computational framework for understanding the role of thiol post-translational modification cofilin proteins in regulating oligomerization, and the subsequent cofilin-mediated actin dynamics in the actomyosin network.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
2D Dam-Break Analysis of L Lake and PAR Pond Dams Using HEC-RAS
In 1991 a dam-break study was conducted for the high hazard dams located at L Lake and PAR Pond on the Savannah River Site. Two scenarios were considered, over topping from a Probable Maximum Flood (PMF), and a fair weather dam-break for either or both dams. Unfortunately, no inundation map was developed from the study. The purpose of this project was to redo the original dam-break study with improved data and methodology to generate Inundation maps to assist with emergency response and evacuation plans. The Hydrologic Engineering Center's River Analysis System (HEC-RAS) is a free to download river analysis modeling program developed by the US Army Corps of Engineers capable of 1D and 2D hydraulic calculations. Version 5.0.7 (released March 2019) was used for this project. Digital elevation models for the area were retrieved from the US Geological Survey database and converted to a .hdf file within the program. Then the 2D flood area was identified from the contours. Both L Lake and PAR Pond were inputted as 1D storage areas because DEM data does not contain elevation values under water bodies. An elevation vs volume curve was available for both storage areas. Initial elevations were set for both scenarios. Both dams are earthen dams. The Steel Creek dam at L Lake has 6 ft diameter conduit with an upper and lower sluice gate. PAR pond dam consist of a weir and sluice gate connected to an 8 x 8 ft channel. Both outlets were modeled with a pool elevation vs discharge curve. The steel creek dam sluice gates were assumed to be fully open in all cases. As in the previous study, the dams were set to breach when they were overtopped by 1.5 ft during PMF conditions (Figure 1). A fair weather breach was set to be due to a piping failure (Figure 1). In the dual dam break during fair weather conditions the PAR pond dam fails 3 hours after Steel Creek to achieve maximum flooding in the down stream reaches. Simulation was run 3 days for each case and with a 1 minute computational interval. Maximum flooding occurs under PMF conditions with the failure of both dams. PAR pond dam fails first 16 hours and 32 minutes after the start of the simulation with the Steel creek dam failing 6 minutes later. In all cases, the bridges and roads spanning Steel Creek and Lower Three Runs will be inundated and potentially washed away. The Burtons Ferry Highway south of the storage areas will be partially flooded during PMF failure, dual fair weather failure, and PAR pond failure under fair weather conditions.
54 ENVIRONMENTAL SCIENCES↗
Ensemble‐Based, Large‐Eddy Reconstruction of Wind Turbine Inflow in a Near‐Stationary Atmospheric Boundary Layer Through Generative Artificial Intelligence
ABSTRACT To validate the second‐by‐second dynamics of turbines in field experiments, it is necessary to accurately reconstruct the winds going into the turbine. Current time‐resolved inflow reconstruction techniques estimate wind behavior in unobserved regions using relatively simple spectral‐based models of the atmosphere. Here, we develop a technique for time‐resolved inflow reconstruction that is rooted in a large‐eddy simulation model of the atmosphere. Our “large‐eddy reconstruction” technique blends observations and atmospheric model information through a diffusion model machine learning algorithm, allowing us to generate probabilistic ensembles of reconstructions for a single 10‐min observational period. Our generated inflows can be used directly by aeroelastic codes or as inflow boundary conditions in a large‐eddy simulation. We verify the second‐by‐second reconstruction capability of our technique in three synthetic field campaigns, finding positive Pearson correlation coefficient values () between ground‐truth and reconstructed streamwise velocity, as well as smaller positive correlation coefficient values for unobserved fields (spanwise velocity, vertical velocity, and temperature). We validate our technique in three real‐world case studies by driving large‐eddy simulations with reconstructed inflows and comparing to independent inflow measurements. The reconstructions are visually similar to measurements, follow desired power spectra properties, and track second‐by‐second behavior ().
17 WIND ENERGY↗
Internal Model-Based Active Damping Strategy for a Back-to-Back Modular Multilevel Converter System for Advanced Grid Support: Preprint
The proposed work focuses on the possibility of achieving the reduction in the size of the interfacing filter for the grid connection for a back-to-back modular multilevel converter system with the use of third order LCL filters. To achieve the same attenuation, it is possible to reduce the size of the interfacing filters by the usage of third order filters. However, this kind of filtering comes with the limitation of having sustained oscillations due to lack of damping especially during transient changes. Therefore, in this work, a methodology has been proposed based on the principle of internal model to cater for this unwanted oscillations. The third order system is modeled inside the microcontroller with the damping enabled. The error between the output from the model and the actual are compared and the error is utilized to accomplish the active damping strategy. The proposed architecture is verified via computer simulations based on MATLAB/Simulink domain and various case study results along with their discussion is presented in this paper.
dq control↗
Laser wavelength dependence of particle acceleration mechanisms in high intensity laser–solid density plasma interactions
We investigate the generation of relativistic electrons and the subsequent ion acceleration due to target-normal sheath acceleration when ultra-intense ( I > 10 18 W/cm 2 ) short pulse ( τ L < 10ps) lasers are incident onto solid density targets as laser wavelength is varied. Scaling laws for the hot electron temperature, T hot , and the maximum ion energy, E max , are recast as a function of laser wavelength. These predictions are compared to results from particle-in-cell computer simulations in a variety of geometries, including cases where realistic plasma density profiles as determined by a radiation hydrodynamics code are used. It is found that the wavelength dependence observed in simulation is less pronounced than what is predicted from the well-established scaling laws. An assessment of how switching to longer laser wavelengths, specifically 2 μm Tm:YLF technology, would impact current high energy density science applications and diagnostics is made.
Electromagnetism↗
PythonFOAM: In-situ data analyses with OpenFOAM and Python
Here, we outline the development of a general-purpose Python-based data analysis tool for OpenFOAM. Our implementation relies on the construction of OpenFOAM applications that have bindings to data analysis libraries in Python. Double precision data in OpenFOAM is cast to a NumPy array using the NumPy C-API and Python modules may then be used for arbitrary data analysis and manipulation on flow-field information. We highlight how the proposed wrapper may be used for an in-situ online singular value decomposition (SVD) implemented in Python and accessed from the OpenFOAM solver PimpleFOAM. Here, 'in-situ' refers to a programming paradigm that allows for a concurrent computation of the data analysis on the same computational resources utilized for the partial differential equation solver. In addition, to demonstrate parallel deployments, we deploy a distributed SVD, which collects snapshot data across the ranks of a distributed simulation to compute the global left singular vectors. Crucially, both OpenFOAM and Python share the same message passing interface (MPI) communicator for this deployment which allows Python objects and functions to exchange NumPy arrays across ranks. Subsequently, we provide scaling assessments of this distributed SVD on multiple nodes of Intel Broadwell and KNL architectures for canonical test cases such as the large eddy simulations of a backward facing step and a channel flow at friction Reynolds number of 395. Finally, we demonstrate the deployment of a deep neural network for compressing the flow-field information using an autoencoder to demonstrate an ability to use state-of-the-art machine learning tools in the Python ecosystem.
97 MATHEMATICS AND COMPUTING↗
Comparison of measurement and simulation of ATLAS cavern radiation background
Sixteen Medipix2 pixel detector based (MPX) devices were operated at various positions within the ATLAS detector and cavern continuously from early 2008 up to 2013. In addition to photons, each MPX detector is capable to detect charged particles, and neutrons as it is covered with a mask of converter materials dividing its area into regions sensitive to thermal or fast neutrons. The MPX detector network was effectively used for real-time measurements of the spectral characteristics and composition of complex radiation fields in ATLAS. This article reports comparison of the results of measurements performed with MPX detectors during the LHC operation period in 2010 and 2011 with Monte Carlo simulations results from the FLUGG and GCALOR codes. For the purpose of this comparison, the MPX detectors were operated in tracking mode with low threshold (8–10 keV) allowing one to distinguish among particle categories based on the recognition of track patterns left by the particles in the MPX sensitive layer. The comparison of measurements with simulations shows that the agreement between measured and simulated data is satisfactory in most cases within a factor of two.
47 OTHER INSTRUMENTATION↗
A generalized approximate control variate framework for multifidelity uncertainty quantification
We describe and analyze a variance reduction approach for Monte Carlo (MC) sampling that accelerates the estimation of statistics of computationally expensive simulation models using an ensemble of models with lower cost. These lower cost models — which are typically lower fidelity with unknown statistics — are used to reduce the variance in statistical estimators relative to a MC estimator with equivalent cost. We derive the conditions under which our proposed approximate control variate framework recovers existing multifidelity variance reduction schemes as special cases. We demonstrate that existing recursive/nested strategies are suboptimal because they use the additional low-fidelity models only to efficiently estimate the unknown mean of the first low-fidelity model. As a result, they cannot achieve variance reduction beyond that of a control variate estimator that uses a single low-fidelity model with known mean. However, there often exists about an order-of-magnitude gap between the maximum achievable variance reduction using all low-fidelity models and that achieved by a single low-fidelity model with known mean. We show that our proposed approach can exploit this gap to achieve greater variance reduction by using non-recursive sampling schemes. The proposed strategy reduces the total cost of accurately estimating statistics, especially in cases where only low-fidelity simulation models are accessible for additional evaluations. Several analytic examples and an example with a hyperbolic PDE describing elastic wave propagation in heterogeneous media are used to illustrate the main features of the methodology.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Data-model files associated with the manuscript "Modeling the Effects of Wetland Restoration on Coastal Hydrology: A Case Study of Elkhorn Slough Watershed, California"
This package contains the data, simulation setups, notebooks and figures used in “Modeling the Effects of Wetland Restoration on Coastal Hydrology: A Case Study of Elkhorn Slough Watershed, California” (Xu et al., 2025). In this study, we selected Elkhorn Slough, a tidal estuary, in California, to investigate the impact of wetland restoration and sea level rise on coastal hydrology using the process-based coastal hydrologic model, Advanced Terrestrial Simulator (ATS), informed by site-specific data. We designed a novel modeling workflow for incorporating wetland restoration features into land cover and soil properties for the model parameterization. The validation results demonstrate a strong agreement between modeled and observed data. We studied the characteristics of coastal watershed hydrology, then focused on the surface water dynamics at two wetland sites within Elkhorn Slough, a reference site and a restored site. Our simulation results indicate that the restored site successfully maintains surface elevation, resulting in reduced surface inundation. We also examined the impact of wetland restoration under expected sea level rise over the next few decades. The low-lying Yampah Marsh, the reference site, is likely to be inundated due to future sea level rise when highest tides arrive; while a higher percentage of Hester Marsh, the restored site, would retain marsh vegetation in coming decades, regardless of tidal conditions. Our study provides important information for examining the outcome of restoration practices that include surface elevation in tidal wetlands under climate changes.Several files can be found from this data package.1. README.md: This file describes the title, journal, co-authors, abstract, repository structure and model version.2. Simulation_Setups.zip: The file contains the model configuration files (XML format) for ATS. 3. Notebooks.zip: The file contains the Jupyter notebooks for generating the pre- and post-restoration meshes and the meshes of future scenarios. 4. Figures.zip: The file contains the figures used in the manuscript.5. Data.zip: The file contains the data used to drive the model simulations, including watershed and wetlands boundaries, mesh files and references to additional datasets (e.g., meteorological forcing, tidal dataset, DEMs, land cover, soil properties). Also, it contains water level observations at the restored wetland.
54 ENVIRONMENTAL SCIENCES↗