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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Phase space effects on fast ion distribution function modeling in tokamaks

Integrated simulations of tokamak discharges typically rely on classical physics to model energetic particle (EP) dynamics. However, there are numerous cases in which energetic particles can suffer additional transport that is not classical in nature. Examples include transport by applied 3D magnetic perturbations and, more notably, by plasma instabilities. Focusing on the effects of instabilities, ad-hoc models can empirically reproduce increased transport, but the choice of transport coefficients is usually somehow arbitrary. New approaches based on physics-based reduced models are being developed to address those issues in a simplified way, while retaining a more correct treatment of resonant wave-particle interactions. The kick model implemented in the tokamak transport code TRANSP is an example of such reduced models. It includes modifications of the EP distribution by instabilities in real and velocity space, retaining correlations between transport in energy and space typical of resonant EP transport. The relevance of EP phase space modifications by instabilities is first discussed in terms of predicted fast ion distribution. Results are compared with those from a simple, ad-hoc diffusive model. It is then shown that the phase-space resolved model can also provide additional insight into important issues such as internal consistency of the simulations and mode stability through the analysis of the power exchanged between energetic particles and the instabilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Current developments in soil organic matter modeling and the expansion of model applications. A review

It is important to note that Soil organic matter (SOM) is a great natural resource. It is fundamental to soil and ecosystem functions across a wide range of scales, from site-specific soil fertility and water holding capacity to global biogeochemical cycling. It is also a highly complex material that is sensitive to direct and indirect human impacts. In our SOM research, simulation models play an important role by providing a mathematical framework to integrate, examine, and test the understanding of SOM dynamics. Simulation models of SOM are also increasingly used in more ‘applied’ settings to evaluate human impacts on ecosystem function, and to manage SOM for greenhouse gas mitigation, improved soil health, and sustainable use as a natural resource. Within this context, there is a need to maintain a robust connection between scientific developments in SOM modeling approaches and SOM model applications. This need forms the basis of this review. In this review we first provide an overview of SOM modeling, focusing on SOM theory, data-model integration, and model development as evidenced by a quantitative review of SOM literature. Second, we present the landscape of SOM model applications, focusing on examples in climate change policy. Finally, we conclude by discussing five areas of recent developments in SOM modeling including: (1) microbial roles in SOM stabilization; (2) modeling SOM saturation kinetics; (3) temperature controls on decomposition; (4)SOM dynamics in deep soil layers; and (5)SOM representation in earth system models. Our aim is to comprehensively connect SOM model development to its applications, revealing knowledge gaps in need of focused interdisciplinary attention and exposing pitfalls that, if avoided, can lead to best use of SOM models to support policy initiatives and sustainable land management solutions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

A revised dosimetric characterization of the model S700 electronic brachytherapy source containing an anode-centering plastic insert and other components not included in the 2006 model

Purpose: The model S700 Axxent electronic brachytherapy source by Xoft, Inc., was characterized by Rivard et al. in 2006. Since then, the source design was modified to include a new insert at the source tip. Current study objectives were to establish an accurate source model for simulation purposes, dosimetrically characterize the new source and obtain its TG-43 brachytherapy dosimetry parameters, and determine dose differences between the original simulation model and the current model S700 source design. Methods: Design information from measurements of dissected model S700 sources and from vendor-supplied CAD drawings was used to aid establishment of an updated Monte Carlo source model, which included the complex-shaped plastic source-centering insert intended to promote water flow for cooling the source anode. These data were used to create a model for subsequent radiation transport simulations in a water phantom. Compared to the 2006 simulation geometry, the influence of volume averaging close to the source was substantially reduced. A track-length estimator was used to evaluate collision kerma as a function of radial distance and polar angle for determination of TG-43 dosimetry parameters. Results for the 50 kV source were determined every 0.1 cm from 0.3 to 15 cm and every 1° from 0° to 180°. Photon spectra in water with 0.1 keV resolution were also obtained from 0.5 to 15 cm and polar angles from 0° to 165°. Simulations were run for 10{sup 10} histories, resulting in statistical uncertainties on the transverse plane of 0.04% at r = 1 cm and 0.06% at r = 5 cm. Results: The dose-rate distribution ratio for the model S700 source as compared to the 2006 model exceeded unity by more than 5% for roughly one quarter of the solid angle surrounding the source, i.e., θ ≥ 120°. The radial dose function diminished in a similar manner as for an {sup 125}I seed, with values of 1.434, 0.636, 0.283, and 0.0975 at 0.5, 2, 5, and 10 cm, respectively. The radial dose function ratio between the current and the 2006 model had a minimum of 0.980 at 0.4 cm, close to the source sheath and for large distances approached 1.014. 2D anisotropy function ratios were close to unity for 50° ≤ θ ≤ 110°, but exceeded 5% for θ < 40° at close distances to the sheath and exceeded 15% for θ > 140°, even at large distances. Photon energy fluence of the updated model as compared to the 2006 model showed a decrease in output with increasing distance; this effect was pronounced at the lowest energies. A decrease in photon fluence with increase in polar angle was also observed and was attributed to the silver epoxy component. Conclusions: Changes in source design influenced the overall dose rate and distribution by more than 2% in several regions. This discrepancy is greater than the dose calculation acceptance criteria as recommended in the AAPM TG-56 report. The effect of the design change on the TG-43 parameters would likely not result in dose differences outside of patient applicators. Adoption of this new dataset is suggested for accurate depiction of model S700 source dose distributions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Comparison and Assessment of Three Advanced Land Surface Models in Simulating Terrestrial Water Storage Components over the United States

In preparation for next generation North American Land Data Assimilation System (NLDAS), 3 three advanced land surface models (CLM4.0, Noah-MP, and CLSM-F2.5) were run from 1979 4 to 2014 within the NLDAS-based framework. Monthly total water storage anomaly (TWSA) and 5 its individual water storage components were evaluated against satellite-based and in situ 6 observations, and reference reanalysis products at basin-wide and statewide scales. In general, all 7 three models are able to reasonably capture the monthly and interannual variability and 8 magnitudes for TWSA. However, contributions of the anomalies of individual water 9 components to TWSA are very dependent on the model and basin. A major contributor to the 10 TWSA is the anomaly of total column soil moisture content (SMCA) for CLM4.0 and Noah-MP 11 or groundwater storage anomaly (GWSA) for CLSM-F2.5 although other components such as 12 the anomaly of snow water equivalent (SWEA) also play some role. For each individual water 13 storage component, the models are able to capture broad features such as monthly and 14 interannual variability. However, there are large inter-model differences and quantitative 15 uncertainties in this study. Therefore, it should be thought of as a preliminary synthesis and 16 analysis.

58 GEOSCIENCES↗
DOE OSTI2024

Rapid measurement of soluble xylo-oligomers using near-infrared spectroscopy (NIRS) and multivariate statistics: calibration model development and practical approaches to model optimization

Rapid monitoring of biomass conversion processes using techniques such as near-infrared (NIR) spectroscopy can be substantially quicker and less labor-, resource-, and energy-intensive than conventional measurement techniques such as gas or liquid chromatography (GC or LC) due to the lack of solvents and preparation methods, as well as removing the need to transfer samples to an external lab for analytical evaluation. The purpose of this study was to determine the feasibility of rapid monitoring of a biomass conversion process using NIR spectroscopy combined with multivariate statistical modeling, and to examine the impact of (1) subsetting the samples in the original dataset by process location and (2) reducing the spectral range used in the calibration model on model performance. We develop multivariate calibration models for the concentrations of soluble xylo-oligosaccharides (XOS), monomeric xylose, and total solids at multiple points in a biomass conversion process which produces and then purifies XOS compounds from sugar cane bagasse. A single model using samples from multiple locations in the process stream showed acceptable performance as measured by standard statistical measures. However, compared to the single model, we show that separate models built by segregating the calibration samples according to process location show improved performance. We also show that combining an understanding of the sample spectra with simple multivariate analysis tools can result in a calibration model with a substantially smaller spectral range that provides essentially equal performance to the full-range model. We demonstrate that real-time monitoring of soluble xylo-oligosaccharides (XOS), monomeric xylose, and total solids concentration at multiple points in a process stream using NIR spectroscopy coupled with multivariate statistics is feasible. Segregation of sample populations by process location improves model performance. Models using a reduced spectral range containing the most relevant spectral signatures show very similar performance to the full-range model, reinforcing the importance of performing robust exploratory data analysis before beginning multivariate modeling.

09 BIOMASS FUELS↗
DOE OSTI2020

Validation and Recalibration of the Solubility Models in Support of the Heater Test in Salt Formations

The US Department of Energy Office of Nuclear Energy is conducting a brine availability heater test to characterize the thermal, mechanical, hydrological and chemical response of salt at elevated temperatures. In the heater test, brines will be collected and analyzed for chemical compositions. In order to support the geochemical modeling of chemical evolutions of the brines during the heater test, we are recalibrating and validating the solubility models for the mineral constituents in salt formations up to 100°C, based on the solubility data in multiple component systems as well as simple systems from literature. In this work, we systematically compare the model-predicted values based on the various solubility models related to the constituents of salt formations, with the experimental data. As halite is the dominant constituent in salt formations, we first test the halite solubility model in the Na-Mg-Cl dominated brines. We find the existing halite solubility model systematically over-predict the solubility of halite. We recalibrate the halite model, which can reproduce halite solubilities in Na-Mg-Cl dominated brines well. As gypsum/anhydrite in salt formations controls the sulfate concentrations in associated brines, we test the gypsum solubility model in NaCl solutions up to 5.87 mol•kg –1 from 25 ° C to 50 ° C. The testing shows that the current gypsum solubility model reproduces the experimental data well when NaCl concentrations are less than 1 mol•kg –1 . However, at NaCl concentrations higher than 1, the model systematically overpredicts the solubility of gypsum. In the Na + —Cl – —SO 4 2– —CO 3 2– system, the validation tests up to 100 ° C demonstrate that the model excellently reproduces the experimental data for the solution compositions equilibrated with one single phase such as halite (NaCl) or thenardite (Na 2 SO 4 ), with deviations equal to, or less than, 1.5 %. The model is much less ideal in reproducing the compositions in equilibrium with the assemblages of halite + thenardite, and of halite + thermonatrite (Na 2 CO 3 •H 2 O), with deviations up to 31 %. The high deviations from the experimental data for the multiple assemblages in this system at elevated temperatures may be attributed to the facts that the database has the Pitzer interaction parameters for Cl – —CO 3 2– and SO 4 2– —CO 3 2– only at 25 ° C. Finally, in the Na + —Ca 2+ —SO 4 2– —HCO 3 – system, the validation tests also demonstrate that the model reproduces the equilibrium compositions for one single phase such as gypsum better than the assemblages of more than one phase.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Multiscale Modeling of CO 2 Migration and Trapping in Fractured Reservoirs with Validation by Model Comparison and Real-Site Applications (Final Technical Report)

This report documents the accomplishments achieved during the project titled “Multiscale Modeling of CO 2 Migration and Trapping in Fractured Reservoirs with Validation by Model Comparison and Real-Site Applications” funded by the US Department of Energy, Office of Fossil Energy. The objectives of the project were to develop modeling capabilities for predicting CO 2 and brine migration in fractured reservoirs during geologic carbon storage and to investigate the feasibility of carbon storage in fractured reservoirs using the newly developed modeling capabilities. To achieve these objectives new mass transfer functions were developed to adapt existing dual-continuum approaches – a commonly used approach in hydrocarbon reservoir modeling – to the CO 2 -brine system. In the dual-continuum approach the undisturbed rock matrix and the fractures are modeled as two separate continua, which are coupled through mass exchange of CO 2 and brine between the two continua. Mass transfer functions represent the mass exchange between fractures and the rock matrix, without requiring highly resolved numerical grids of individual fractures, thus allowing large modeling domains relevant to geologic carbon storage questions (tens of meters to hundreds of kilometers). Mass transfer functions for the exchange of both free-phase CO 2 and brine between fractures and rock matrix were developed for both the injection phase and the post-injection phase. During the injection phase the fractures are filled with CO 2 , while the rock matrix is initially filled with brine. Therefore, a mass transfer function was developed that is based on vertical displacement of brine by CO 2 in the rock matrix due to gravitational forces. Once CO 2 injection ceases and CO 2 migrates away from the direct vicinity of the injection site, the fractures will begin to re-fill with brine, while the rock matrix will have high CO 2 saturations. For these conditions a mass transfer functions was developed that is based on spontaneous imbibition, as the pore spaces in the rock matrix are much smaller than in the fractures. For formations with low permeability or high capillary entry pressure of the rock matrix, free-phase CO 2 may not be able to enter the rock matrix. However, free-phase CO 2 at the interface between fractures and rock matrix can dissolve into brine resident in the rock matrix. Therefore, additional mass transfer functions were developed based on aqueous-phase diffusion of CO 2 through the rock matrix. These mass transfer functions are based on existing solutions for diffusion and were expanded to be applicable to a variety of block shapes relevant to dual-continuum modeling. Implementations of the newly developed mass transfer functions showed that they give accurate results when compared to highly resolved models. In addition to developing new transfer functions, a new vertically-integrated dual-continuum modeling framework was developed. This development takes advantage of fast vertical segregation of CO 2 and brine in the fractures due to the density difference between CO 2 and brine and the high permeability of the fractures. Therefore, a vertically-integrated vertical equilibrium model for the fractures is coupled with a vertically-distributed model for the rock matrix. The newly developed approach significantly reduces the computational effort, but is only accurate for fracture permeabilities of 100 mD or higher. Finally, the newly developed models were applied to real and hypothetical geologic carbon storage sites to investigate the feasibility of using fractured reservoirs for carbon storage. The general results were, that storage of CO 2 – both as free-phase and dissolved – is feasible, but that storage capacities are likely lower than in unfractured systems. While the high permeability of the fractures reduces the injection pressure (or permits higher injection rates), fast migration of CO 2 may limit the overall storage volume, because CO 2 may escape laterally with not enough of the rock matrix being swept for effective storage.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Challenge Problem 1: Preliminary Model Development and Assessment of Flexible Heat Transfer Modeling Approaches

This report presents the modeling progress of a university consortium studying flexible modeling for turbulent heat transfer. In the context of advanced nuclear reactor design, where challenges include non-unity Prandtl fluids, free and mixed convection, and transitional flow, computational fluid dynamics methods are underutilized due to low confidence in modeling approaches and high computational cost. This report evaluates the performance of engineering CFD models in diabatic, buoyant turbulent flow. It finds that all turbulence models including several variants of the k-ε and k-ω models struggle to predict accurate turbulent momentum and heat transfer in such flows. The Nusselt numbers have been compared between the models and the DNS data, where calculations have been performed for each case and trends have shown a good agreement between DNS estimated Nusselt numbers and available correlations as well as experimental data. A novel DNS correlation for high Pr cases as they are transitioning from mixed convection to natural convection has been proposed. While Nusselt number errors relative to DNS range from 20% to 50%, the models capture similar trends to DNS with respect to Nusselt suppression and amplification under varying levels of buoyancy effect. This report also highlights model form error as a significant contributor to CFD predictions and proposes a framework for quantifying model error and improving confidence in CFD calculations. To improve the predictive capability of engineering CFD models, data-driven approaches for turbulence models are investigated. Theoretical frameworks based on the invariant tensor / vector basis neural networks for prediction of Reynolds stresses and turbulent heat fluxes are employed. The models are developed using direct numerical simulations data for forced convection flows of different fluids in vertical planar channel domain. The framework is implemented in spectral element solvers Nek5000 / nekRS and has shown a potential for future development and consideration of mixed convection flows.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Efficient surrogate modeling methods for large-scale Earth system models based on machine-learning techniques

Abstract. Improving predictive understanding of Earth system variability and change requires data–model integration. Efficient data–model integration for complex models requires surrogate modeling to reduce model evaluation time. However, building a surrogate of a large-scale Earth system model (ESM) with many output variables is computationally intensive because it involves a large number of expensive ESM simulations. In this effort, we propose an efficient surrogate method capable of using a few ESM runs to build an accurate and fast-to-evaluate surrogate system of model outputs over large spatial and temporal domains. We first use singular value decomposition to reduce the output dimensions and then use Bayesian optimization techniques to generate an accurate neural network surrogate model based on limited ESM simulation samples. Our machine-learning-based surrogate methods can build and evaluate a large surrogate system of many variables quickly. Thus, whenever the quantities of interest change, such as a different objective function, a new site, and a longer simulation time, we can simply extract the information of interest from the surrogate system without rebuilding new surrogates, which significantly reduces computational efforts. We apply the proposed method to a regional ecosystem model to approximate the relationship between eight model parameters and 42 660 carbon flux outputs. Results indicate that using only 20 model simulations, we can build an accurate surrogate system of the 42 660 variables, wherein the consistency between the surrogate prediction and actual model simulation is 0.93 and the mean squared error is 0.02. This highly accurate and fast-to-evaluate surrogate system will greatly enhance the computational efficiency of data–model integration to improve predictions and advance our understanding of the Earth system.

58 GEOSCIENCES↗
NASA NTRS1989

The determination of third order linear models from a seventh order nonlinear jet engine model

Results are presented that demonstrate how good reduced-order models can be obtained directly by recursive parameter identification using input/output (I/O) data of high-order nonlinear systems. Three different methods of obtaining a third-order linear model from a seventh-order nonlinear turbojet engine model are compared. The first method is to obtain a linear model from the original model and then reduce the linear model by standard reduction techniques such as residualization and balancing. The second method is to identify directly a third-order linear model by recursive least-squares parameter estimation using I/O data of the original model. The third method is to obtain a reduced-order model from the original model and then linearize the reduced model. Frequency responses are used as the performance measure to evaluate the reduced models. The reduced-order models along with their Bode plots are presented for comparison purposes.

Lalonde, Rick J.↗
NASA NTRS1990

Model compilation: An approach to automated model derivation

An approach is introduced to automated model derivation for knowledge based systems. The approach, model compilation, involves procedurally generating the set of domain models used by a knowledge based system. With an implemented example, how this approach can be used to derive models of different precision and abstraction is illustrated, and models are tailored to different tasks, from a given set of base domain models. In particular, two implemented model compilers are described, each of which takes as input a base model that describes the structure and behavior of a simple electromechanical device, the Reaction Wheel Assembly of NASA's Hubble Space Telescope. The compilers transform this relatively general base model into simple task specific models for troubleshooting and redesign, respectively, by applying a sequence of model transformations. Each transformation in this sequence produces an increasingly more specialized model. The compilation approach lessens the burden of updating and maintaining consistency among models by enabling their automatic regeneration.

Keller, Richard M.↗
NASA NTRS1999

Model Experiments and Model Descriptions

The Second Workshop on Stratospheric Models and Measurements Workshop (M&M II) is the continuation of the effort previously started in the first Workshop (M&M I, Prather and Remsberg [1993]) held in 1992. As originally stated, the aim of M&M is to provide a foundation for establishing the credibility of stratospheric models used in environmental assessments of the ozone response to chlorofluorocarbons, aircraft emissions, and other climate-chemistry interactions. To accomplish this, a set of measurements of the present day atmosphere was selected. The intent was that successful simulations of the set of measurements should become the prerequisite for the acceptance of these models as having a reliable prediction for future ozone behavior. This section is divided into two: model experiment and model descriptions. In the model experiment, participant were given the charge to design a number of experiments that would use observations to test whether models are using the correct mechanisms to simulate the distributions of ozone and other trace gases in the atmosphere. The purpose is closely tied to the needs to reduce the uncertainties in the model predicted responses of stratospheric ozone to perturbations. The specifications for the experiments were sent out to the modeling community in June 1997. Twenty eight modeling groups responded to the requests for input. The first part of this section discusses the different modeling group, along with the experiments performed. Part two of this section, gives brief descriptions of each model as provided by the individual modeling groups.

Jackman, Charles H.↗
NASA NTRS2009

Evaluating Effectiveness of Modeling Motion System Feedback in the Enhanced Hess Structural Model of the Human Operator

In order to use the Hess Structural Model to predict the need for certain cueing systems, George and Cardullo significantly expanded it by adding motion feedback to the model and incorporating models of the motion system dynamics, motion cueing algorithm and a vestibular system. This paper proposes a methodology to evaluate effectiveness of these innovations by performing a comparison analysis of the model performance with and without the expanded motion feedback. The proposed methodology is composed of two stages. The first stage involves fine-tuning parameters of the original Hess structural model in order to match the actual control behavior recorded during the experiments at NASA Visual Motion Simulator (VMS) facility. The parameter tuning procedure utilizes a new automated parameter identification technique, which was developed at the Man-Machine Systems Lab at SUNY Binghamton. In the second stage of the proposed methodology, an expanded motion feedback is added to the structural model. The resulting performance of the model is then compared to that of the original one. As proposed by Hess, metrics to evaluate the performance of the models include comparison against the crossover models standards imposed on the crossover frequency and phase margin of the overall man-machine system. Preliminary results indicate the advantage of having the model of the motion system and motion cueing incorporated into the model of the human operator. It is also demonstrated that the crossover frequency and the phase margin of the expanded model are well within the limits imposed by the crossover model.

Zaychik, Kirill↗
NASA NTRS2013

Coupled Vortex-Lattice Flight Dynamic Model with Aeroelastic Finite-Element Model of Flexible Wing Transport Aircraft with Variable Camber Continuous Trailing Edge Flap for Drag Reduction

This paper presents a coupled vortex-lattice flight dynamic model with an aeroelastic finite-element model to predict dynamic characteristics of a flexible wing transport aircraft. The aircraft model is based on NASA Generic Transport Model (GTM) with representative mass and stiffness properties to achieve a wing tip deflection about twice that of a conventional transport aircraft (10% versus 5%). This flexible wing transport aircraft is referred to as an Elastically Shaped Aircraft Concept (ESAC) which is equipped with a Variable Camber Continuous Trailing Edge Flap (VCCTEF) system for active wing shaping control for drag reduction. A vortex-lattice aerodynamic model of the ESAC is developed and is coupled with an aeroelastic finite-element model via an automated geometry modeler. This coupled model is used to compute static and dynamic aeroelastic solutions. The deflection information from the finite-element model and the vortex-lattice model is used to compute unsteady contributions to the aerodynamic force and moment coefficients. A coupled aeroelastic-longitudinal flight dynamic model is developed by coupling the finite-element model with the rigid-body flight dynamic model of the GTM.

Flexible Aicraft↗
NASA NTRS2012

Atmospheric Dust Modeling from Meso to Global Scales with the Online NMMB/BSC-Dust Model Part 2: Experimental Campaigns in Northern Africa

The new NMMB/BSC-Dust model is intended to provide short to medium-range weather and dust forecasts from regional to global scales. It is an online model in which the dust aerosol dynamics and physics are solved at each model time step. The companion paper (Perez et al., 2011) develops the dust model parameterizations and provides daily to annual evaluations of the model for its global and regional configurations. Modeled aerosol optical depth (AOD) was evaluated against AERONET Sun photometers over Northern Africa, Middle East and Europe with correlations around 0.6-0.7 on average without dust data assimilation. In this paper we analyze in detail the behavior of the model using data from the Saharan Mineral dUst experiment (SAMUM-1) in 2006 and the Bodele Dust Experiment (BoDEx) in 2005. AOD from satellites and Sun photometers, vertically resolved extinction coefficients from lidars and particle size distributions at the ground and in the troposphere are used, complemented by wind profile data and surface meteorological measurements. All simulations were performed at the regional scale for the Northern African domain at the expected operational horizontal resolution of 25 km. Model results for SAMUM-1 generally show good agreement with satellite data over the most active Saharan dust sources. The model reproduces the AOD from Sun photometers close to sources and after long-range transport, and the dust size spectra at different height levels. At this resolution, the model is not able to reproduce a large haboob that occurred during the campaign. Some deficiencies are found concerning the vertical dust distribution related to the representation of the mixing height in the atmospheric part of the model. For the BoDEx episode, we found the diurnal temperature cycle to be strongly dependant on the soil moisture, which is underestimated in the NCEP analysis used for model initialization. The low level jet (LLJ) and the dust AOD over the Bodélé are well reproduced. The remaining negative AOD bias (due to underestimated surface wind speeds) can be substantially reduced by decreasing the threshold friction velocity in the model.

photometers↗
NASA NTRS2016

Validation for Global Solar Wind Prediction Using Ulysses Comparison: Multiple Coronal and Heliospheric Models Installed at the Community Coordinated Modeling Center

The prediction of the background global solar wind is a necessary part of space weather forecasting. Several coronal and heliospheric models have been installed and/or recently upgraded at the Community Coordinated Modeling Center (CCMC), including the Wang-Sheely-Arge (WSA)-Enlil model, MHD-Around-a-Sphere (MAS)-Enlil model, Space Weather Modeling Framework (SWMF), and Heliospheric tomography using interplanetary scintillation data. Ulysses recorded the last fast latitudinal scan from southern to northern poles in 2007. By comparing the modeling results with Ulysses observations over seven Carrington rotations, we have extended our third-party validation from the previous near-Earth solar wind to middle to high latitudes, in the same late declining phase of solar cycle 23. Besides visual comparison, wehave quantitatively assessed the models capabilities in reproducing the time series, statistics, and latitudinal variations of solar wind parameters for a specific range of model parameter settings, inputs, and grid configurations available at CCMC. The WSA-Enlil model results vary with three different magnetogram inputs.The MAS-Enlil model captures the solar wind parameters well, despite its underestimation of the speed at middle to high latitudes. The new version of SWMF misses many solar wind variations probably because it uses lower grid resolution than other models. The interplanetary scintillation-tomography cannot capture the latitudinal variations of solar wind well yet. Because the model performance varies with parameter settings which are optimized for different epochs or flow states, the performance metric study provided here can serve as a template that researchers can use to validate the models for the time periods and conditions of interest to them.

Jian, L. K.↗
DOE OSTI2020

Land Model Testbed: Accelerating Development, Benchmarking and Analysis of Land Surface Models

A Land Model Testbed (LMT), designed to provide a computational framework for systematically assessing model fidelity and supporting rapid development of complex multiscale models, offers a general-purpose workflow for conducting large ensemble simulations of multiple land surface models, post-processing large volumes of model output, and evaluating model results. It leverages existing tools for launching model simulations and the International Land Model Benchmarking (ILAMB) package for assessing model fidelity through comparison with best-available observational datasets. Increased complexity and proliferation of uncertain parameters in process representations in land surface models has driven the need for frequent and intensive testing and evaluating of models to quantify uncertainties and optimize parameters such that results are consistent with observations. The LMT described here meets these needs by providing tools to run thousands of ensemble simulations simultaneously and post-process their output files, by automating execution of an enhanced version of ILAMB with site-specific benchmarks and multivariate functional relationships, and by offering ensemble diagnostics and a customizable dashboard for displaying model performance metrics and associated graphics. We envision the LMT capabilities will serve as a foundational computational resource for a proposed user facility focused on terrestrial multiscale model--data integration.

Sreepathi, Sarat↗
DOE OSTI2024

Evaluating the Hybrid Modelling Competition: A Step Towards Developing Good Modelling Practice

Hybrid modelling, a combination of mechanistic and data-driven modelling, is a promis¬ing approach to advance current mathematical models towards improved deci¬sion support tools for today's water-related challenges. Researchers have been develop¬ing guidelines or references for good modelling practices in the water field for mecha¬nistic (Rieger et al., 2012) and data-driven (Zhu et al., 2023) modelling, respectively. However, good modelling practices for hybrid modelling are currently missing (Schneider et al., 2022). Therefore, the International Water Association’s (IWA) hybrid modelling working group initiated the first competition on a data science competition platform (i.e. Kaggle) for water resource recovery modelling at the Watermatex con¬ference in September 2023 in Quebec. The main objective of this competition was to gain insights and experience to create good modelling practices. Further goals were to motivate students, researchers, and practitioners model, foster a vibrant and engaged community, and evaluate the efficacy of com¬petitions in solving modelling challenges within the water domain. Our next goal is that facilities will measure and gather relevant data for future competitions to solve their challenges from a modeller’s perspective.

Schneider, Mariane↗