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DOE OSTI2025

Dark Energy Survey Supernova 5YR Data Release

This data set was generated by the Dark Energy Survey (DES) team, and was used for the cosmological analysis in the DES key supernova cosmology paper (arXiv:2401.02929). When using this data please cite both the data release paper (Sanchez et al. 2024, ApJ, arXiv:2406.05046) and the DES key paper (Dark Energy Survey Collaboration 2024, ApJL, arXiv:2401.02929). At DES-SN5YR Github Repo (https://github.com/des-science/DES-SN5YR), we provide a comprehensive list of references for the different data products (SALT3 light-curve model, calibration, DCR corrections, SN classification, SN distances and uncertainties covariance matrix). If you have questions, post an issue on the DES-SN5YR Github repository and/or get in touch with the contact people indicated on the Github repository.

Contractor, Fermilab [Fermilab]↗
DOE OSTI2025

ERA5-Land Data for LASSO-CACTI Overview Paper

The European Centre for Medium-Range Weather Forecasts (ECMWF) generated a soil reanalysis dataset for the land component of the fifth generation of European ReAnalysis (ERA5), referred to as ERA5-Land. This is a model-generated dataset, with the original version available for the period 1950 to present. The version archived in this DOE ARM product is a subset of the data is for the period of the CACTI field campaign plus several preceding months, specifically from August 1, 2018 through March 22, 2019 with hourly intervals. The ARM copy is also a sub-region of the original global product; the ARM copy is for -60 to -5 °N by -105 to -30 °W. Only variables necessary to drive the WRF-Hydro model are included, which are the 2-m temperature and specific humidity, 10-m wind components, surface pressure, rain rate, and downward surface short and longwave radiation. These data have been obtained from the Copernicus Data Store.

10m wind u-component↗
DOE OSTI2016

Effect of soil property uncertainties on permafrost thaw projections: a calibration-constrained analysis: Modeling Archive

This dataset contains an ensemble of thermal-hydro soil parameters including porosity, thermal conductivity, thermal conductivity shape parameters, and residual saturation of peat and mineral soil. The ensemble was generated using a Null-Space Monte Carlo analysis of parameter uncertainty based on a calibration to soil temperatures collected at the Barrow Environmental Observatory site by the NGEE team. The micro-topography of ice wedge polygons present at the site is included in the analysis using three 1D column models to represent polygon center, rim and trough features. The Arctic Terrestrial Simulator (ATS) was used in the calibration to model multiphase thermal and hydrological processes in the subsurface. This dataset includes one zipped file, one pdf file, and one csv file.This Modeling Archive is in support of an NGEE Arctic publication. The citation for that publication can be found within the references section.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

ResStock Measure Documentation: Residential Two-Stage Geothermal Heat Pump (4.0 COP, 20.5 EER) With Envelope Improvements and Advanced Air Sealing

The goal of this work is to develop energy efficiency, demand flexibility, and other retrofit end-use load shapes (electricity, gas, propane, or fuel oil) that cover a majority of the high-impact, market-ready (or nearly market-ready) measures. "Measures" refers to retrofits that can be applied to buildings during modeling. An "end-use savings shape" is the difference in energy consumption between a baseline building and a building with an energy efficiency, demand flexibility, or other retrofit measure applied. It results in a time-series profile that is broken down by end use and fuel (electricity or on-site gas, propane, or fuel oil use) at each time step. ResStock is a highly granular, physics-based, bottom-up model that uses multiple data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual subhourly energy consumption of the residential building stock across the United States. The baseline model intends to represent the U.S. residential building stock as it existed in 2018. Technical documentation for the inputs and assumptions in the baseline building stock model is available in Reyna et al. (2025). Calibration and validation of the baseline model results are available in the final technical report of the End-Use Load Profiles project (Wilson, et al. 2022). This document focuses on a single end-use savings shape measure: Residential Two-Stage Geothermal Heat Pump (GHP) (4.0 COP, 20.5 EER) With Envelope Improvements. This measure combines a two-stage GHP with envelope improvements as a single package. As this package is a combination of two other measures, this document focused on documenting the results associated with this combination of technologies, with individual measure documents for two-stage GHPs and envelope improvements providing the information on the details of these measures. When the two technologies are combined, envelope improvements can modestly reduce energy consumption by a further 10%-15%, but also reduce the required size of the ground heat exchanger and heat pump by approximately 33% on average across all sites. The cost of installing envelope improvements in these homes is likely to be more than paid for by the reduction in equipment and drilling costs in these buildings for the majority of the stock.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

ResStock Measure Documentation: Residential Single-Stage Geothermal Heat Pump (3.8 COP, 18.6 EER)

The goal of this work is to develop energy efficiency, demand flexibility, and other retrofit end-use load shapes (electricity, gas, propane, or fuel oil) that cover a majority of the high-impact, market-ready (or nearly market-ready) measures. "Measures" refers to retrofits that can be applied to buildings during modeling. An "end-use savings shape" is the difference in energy consumption between a baseline building and a building with an energy efficiency, demand flexibility, or other retrofit measure applied. It results in a time-series profile that is broken down by end use and fuel (electricity or on-site gas, propane, or fuel oil use) at each time step. ResStock is a highly granular, physics-based, bottom-up model that uses multiple data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual subhourly energy consumption of the residential building stock across the United States. The baseline model intends to represent the U.S. residential building stock as it existed in 2018. Technical documentation for the inputs and assumptions in the baseline building stock model is available in Reyna et al. (2025). Calibration and validation of the baseline model results are available in the final technical report of the End-Use Load Profiles project (Wilson et al. 2022). This documentation focuses on a single end-use savings shape measure: Residential Single-Stage Geothermal Heat Pump (GHP).?Single-stage GHPs are able to reduce energy consumption by 31% for the entire stock. Additional results provided below detail how savings changes for sections of the housing stock with different base heating fuel and in different climate zones, as well as the savings potential by state for both heating and cooling. Utility bills and electric panel impacts are also shown and discussed.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

ResStock Measure Documentation: Residential Variable-Speed Geothermal Heat Pump (4.4 COP, 30.9 EER)

The goal of this work is to develop energy efficiency, demand flexibility, and other retrofit end-use load shapes (electricity, gas, propane, or fuel oil) that cover a majority of the high-impact, market-ready (or nearly market-ready) measures. "Measures" refers to retrofits that can be applied to buildings during modeling. An "end-use savings shape" is the difference in energy consumption between a baseline building and a building with an energy efficiency, demand flexibility, or other retrofit measure applied. It results in a time-series profile that is broken down by end use and fuel (electricity or on-site gas, propane, or fuel oil use) at each time step. ResStock (TM) is a highly granular, physics-based, bottom-up model that uses multiple data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual subhourly energy consumption of the residential building stock across the United States. The baseline model intends to represent the U.S. residential building stock as it existed in 2018. Technical documentation for the inputs and assumptions in the baseline building stock model is available in Reyna et al. (2025). Calibration and validation of the baseline model results are available in the final technical report of the End-Use Load Profiles project (Wilson et al. 2022). This documentation focuses on a single end-use savings shape measure: Residential Variable-Speed Geothermal Heat Pump (GHP). This document provides the relevant new modeling information for variable-speed systems not previously covered in either the single-stage or two-stage documents. Variable-speed GHPs represent the most efficient option available for this technology: They provide the most savings, with up to 46% for the applicable portion of the housing stock, compared to 31% for less efficient single-stage GHPs. Additional results shown here detail how the savings change for sections of the housing stock with different base heating fuels and in different climate zones, and they show the savings potential by state for both heating and cooling. Utility bills and electric panel impacts are also shown and discussed.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

ResStock Measure Documentation: Residential Two-Stage Geothermal Heat Pump (4.0 COP, 20.5 EER)

The goal of this work is to develop energy efficiency, demand flexibility, and other retrofit end-use load shapes (electricity, gas, propane, or fuel oil) that cover a majority of the high-impact, market-ready (or nearly market-ready) measures. "Measures" refers to retrofits that can be applied to buildings during modeling. An "end-use savings shape" is the difference in energy consumption between a baseline building and a building with an energy efficiency, demand flexibility, or other retrofit measure applied. It results in a time-series profile that is broken down by end use and fuel (electricity or on-site gas, propane, or fuel oil use) at each time step. ResStock is a highly granular, physics-based, bottom-up model that uses multiple data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual subhourly energy consumption of the residential building stock across the United States. The baseline model intends to represent the U.S. residential building stock as it existed in 2018. Technical documentation for the inputs and assumptions in the baseline building stock model is available in Reyna et al. (2025). Calibration and validation of the baseline model results are available in the final technical report of the End-Use Load Profiles project (Wilson et al. 2022). This document focuses on a single end-use savings shape measure: Residential Two-Stage Geothermal Heat Pump (4.0 COP, 20.5 EER). This document builds on details established in the single-stage document (Maguire et al. 2025) to detail differences in the approach to modeling this higher efficiency, but more commonly deployed, type of geothermal heat pump. Specific EnergyPlus objects and product specific curves used are highlighted along with showing the results of this measure compared to the baseline and single-speed geothermal heat pumps. Two-speed geothermal heat pumps are able to save even more energy and on utility bills than single-speed products, albeit at the expense of a higher first cost.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Search for Hidden-Charm Pentaquark with CLAS12

LHCb recently announced the discovery of two exotic structures in the J/?+p decay channel, which have been referred to as charmonium-pentaquark states. Resolving differences between models for these states, clarifying the nature of the discovered hidden-charm pentaquark peaks, and discovery of any similar states with other quantum numbers, will require further experimental studies. It is natural to expect that such pentaquark states should be produced in the photoproduction process ?+p-> Pc -> J/?+p, where they will appear as s-channel resonances at photon energy around 10 GeV. The energy and luminosity of the Jefferson Lab CLAS12 photon beam will permit detailed studies of the production and decay properties of such pentaquark resonances. This presentation will discuss a search for these pentaquark states which is currently underway with CLAS12.

Kubarovsky, Valery↗
DOE OSTI2016

Further Investigation of Employing Binomial Small-Sample Estimator in M-LROM

Reduced Order Modeling (ROM) is essential to enable the identification of the so-called active parameter subspace for high-fidelity models that are employed in computationally intensive analyses such as uncertainty characterization and data assimilation. Given the complexity of models for real-world application, brute force methods to identify the active subspace may not be computationally efficient to realize the value of reduction, since in realistic problems, the full scale model must be executed few hundred times, which may be computationally taxing. Earlier work has introduced a new approach, which represents a further development of our previous work on ROM, referred to as multi-level ROM (M-LROM). In M-LROM, approximate models are employed to identify the active subspace instead of the full scale model. In this summary, we present our recent results on M-LROM, specifically in regard to the construction of reliable error metrics that can bound the errors resulting from the reduction. The idea is to employ a lower fidelity model, i.e., an approximation of the full scale or high fidelity model, to build the active subspace, and via the proposed error bound, the quality of the active subspace can be determined by calculating an upper bound on the errors resulting from the reduction. For this approach to be practical, the error bound must be realistic, implying that it should be close to the actual errors expected, and not much higher. Therefore, an important goal of this summary is to compare different error bounds in terms of the relation between their estimated bounds to the actual errors. In particular, we compare the proposed error bound which numerically construct an estimator using binomial distribution to the widely used small-sample norm estimators. Unlike most probabilistic error estimation methods, the proposed bound employs a binomial distribution to construct the estimator whereas in other conventional methods, the distribution employed is typically the standard Gaussian, normalized over a unit hypersphere as initially proposed by the seminal paper of J. Dixon on random matrix theory. Previous publications provided evidence that the binomial distribution calculates more realistic bounds as compared to the Gaussian distribution, which tends to be conservative, implying that the bound is much bigger than the actual errors, which diminishes the value of the reduction, as now must increase the size of the active subspace to reach the desired upper bound on the reduction errors. This work has provided a rigorous approach by which error bounds on the reduction errors can be established without having to execute the high fidelity model during the construction of the active subspace. The high fidelity model is only need to test the error bound using small number of executions. This methodology paves the way for a more efficient application of ROM to complex engineering models, where standard ROM techniques may be too taxing to optimally realize their value in practical situations. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

H2@Scale CRADA: CA Research Consort. (Ref. Station, Fueling Perf. Test Device, Station Cap Model)

In support of DOE's H2@Scale initiative, this project leverages with national lab capabilities at SNL, NREL, and ANL with collaboration and funding cost share from California agencies (CEC, South Coast AQMD, and GO-Biz) to enable the build-out of heavy-duty (HD) hydrogen fueling stations with large dispensing capacity and high flow rates by providing tools and information that lead to more efficient design, acceptance, and commissioning. In this presentation, we describe the progress as related to the subtasks of: HD Reference Station Design, HD Station Test Device Design, and the Station Capacity Model.

AMR↗
DOE OSTI2024

Machine learning enhanced characterization and optimization of photonic cured MAPbI 3 for efficient perovskite solar cells

Photonic curing (PC) can facilitate high-speed perovskite solar cell (PSC) manufacturing because it uses high-intensity light pulses to crystallize perovskite films in milliseconds. However, optimizing PC conditions is challenging due to its many variables, and using power conversion efficiency (PCE) as the optimization metric is both time-consuming and labor-intensive. This work presents a machine learning (ML) approach to optimize PC conditions for fabricating methylammonium lead iodide (MAPbI 3 ) films by quantitatively comparing their ultraviolet-visible (UV-vis) absorbance spectra to thermal annealed (TA) films using four similarity metrics. We perform Bayesian optimization coupled with Gaussian process regression (BO-GP) to minimize the similarity metrics. Refining PC conditions using active learning based on BO-GP models, we achieve a PC MAPbI3 film with an absorbance spectrum closely matching a TA reference film, which is further verified by its crystalline and morphological properties. Thus, we demonstrate that the UV-vis absorption spectrum can accurately proxy film quality. Additionally, we use an AI-based segmentation model for a more efficient grain size analysis. However, when we use the optimized PC condition to fabricate PSCs, we find that interaction between MAPbI 3 and the hole transport layer (HTL) during PC critically degrades the PSC performance. By adding a buffer layer between the HTL and MAPbI 3 , the optimized PC PSCs produce a champion PCE of 11.8%, comparable to the TA reference of 11.7%. Using UV-vis similarity metrics instead of device PCE as the objective in our BO-GP method accelerates the optimization of PC processing conditions for MAPbI 3 films.

14 SOLAR ENERGY↗
DOE OSTI2019

Solar Resource Calibration, Measurement, and Dissemination: Final Report FY 2016-FY 2018

The Solar Resource Calibration, Measurement, and Dissemination project supports the U.S. Department of Energy's Solar Energy Technologies Office (SETO) initiative to make solar energy cost-competitive with other forms of electricity by improving the tools and methods to measure and model solar radiation and therefore reduce uncertainty in predicting solar output and improve the bankability of solar projects. This project has three tasks that conduct research on advancing solar resource measurements and modeling: Task 1: Applied solar Radiation Measurements. Task 2: National Solar Radiation Data Base (NSRDB). Task 3: Knowledge Sharing. The National Renewable Energy Laboratory's (NREL's) Solar Radiation Research Laboratory (SRRL) activities ensure traceable solar measurements throughout the United States that are essential for project feasibility, due diligence, financing, and plant operations. The SRRL houses NREL's Baseline Measurement System (BMS), which provides a platform for improving the accuracy of solar measurements through research to improve the calibration and characterization of instruments and enable the development of new measurement technology and standards. The platform contains a variety of instruments measuring solar radiation and other meteorological parameters. Following best practices, BMS instruments are calibrated to ensure traceability to the World Radiometric Reference in compliance with ISO/IEC 17025 accreditation requirements. The BMS data sets are quality-controlled and made publicly available through the Measurement and Instrumentation Data Center website. The NSRDB is the most accessed public database of solar irradiance and associated weather parameters for use in energy modeling. It supports SETO's goals of reducing barriers to high penetrations of solar technologies by providing easy access to high-quality, foundational data essential for innovative product development and downstream modeling through the NSRDB website. Data are currently available for the contiguous United States and beyond for 20 years covering 1998-2017. The Physical Solar Model (PSM) that underpins the current NSRDB data sets is a unique physics-based model that has been developed at NREL and has opened the door to the use of next-generation satellite data sets for solar resource assessment and forecasting. Through the American Society for Testing Materials (ASTM) International and other international standards organizations, NREL continues to provide leadership in the development of standards that are relevant to the measurement and modeling of solar radiation for solar energy applications. Standards developed cover the calibration method of pyrheliometers (direct normal irradiance measurements), pyranometers (global horizontal irradiance measurements), spectroradiometers, ultraviolet radiometers, correct field deployment of these instruments, spectral distribution reference tables for photovoltaic modeling, and transfer of indoor calibrations. Further, NREL leads the International Energy Agency (IEA) Photovoltaic Power Systems Programme Task 16: Subtask 1, which focuses on the evaluation of current and emerging resource assessment methodologies. NREL and the IEA updated the Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications, which is widely used by the solar industry.

14 SOLAR ENERGY↗
DOE OSTI2021

MELCOR Code Change History: Revision 18019 to 21402

This document summarily provides brief descriptions of the MELCOR code enhancement made between code revision number 18019and 21440. Revision 18019 represents the previous official code release; therefore, the modeling features described within this document are provided to assist users that update to the newest official MELCOR code release, 21440. Along with the newly updated MELCOR Users’ Guide [2] and Reference Manual [3], users are aware and able to assess the new capabilities for their modeling and analysis applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Reactive transport modelling of a cement backfill for radioactive waste disposal

Cementitious materials are included in many geological disposal facilities for radioactive wastes, including the UK candidate backfill material Nirex Reference Vault Backfill (NRVB). As part of an ongoing programme of work to assess NRVB performance, 1-D reactive-transport models have been constructed to simulate reaction with different illustrative groundwater compositions. Variant cases were also produced to explore the effect of model assumptions on the predicted behaviour of the backfill. Depending on groundwater composition, cement alteration pathways included: carbonation; external sulphate attack; chloride attack; the formation of magnesium-rich solids; and the precipitation of secondary aluminosilicate minerals. In general, the models suggest that the pore space in backfill associated with radioactive waste disposal systems is likely to become clogged (to some degree) over time close to backfill-rock interfaces resulting in a reduction in capacity for solute transport. However, the models do not include all relevant process couplings which is potentially, an area for further work.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Hammett neural networks: prediction of frontier orbital energies of tungsten–benzylidyne photoredox complexes

The successful application of Hammett parameters as input features for regressive machine learning models is demonstrated and applied to predict energies of frontier orbitals of highly reducing tungsten–benzylidyne complexes of the form W($\equiv$]CArR)L 4 X. Using a reference molecular framework and the meta- and para-substituent Hammett parameters of the ligands, the models predict energies of frontier orbitals that correlate with redox potentials. The regressive models capture the multivariate character of electron-donating trends as influenced by multiple substituents even for non-aryl ligands, harnessing the breadth of Hammett parameters in a generalized model. We find a tungsten catalyst with tetramethylethylenediamine (tmeda) equatorial ligands and axial methoxyl substituents that should attract significant experimental interest since it is predicted to be highly reducing when photoactivated with visible light. The utilization of Hammett parameters in this study presents a generalizable and compact representation for exploring the effects of ligand substitutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Regional Analysis of Building Distributed Energy Costs and CO2 Abatement: A U.S. - China Comparison

The following paper conducts a regional analysis of the U.S. and Chinese buildings? potential for adopting Distributed Energy Resources (DER). The expected economics of DER in 2020-2025 is modeled for a commercial and a multi-family residential building in different climate zones. The optimal building energy economic performance is calculated using the Distributed Energy Resources Customer Adoption Model (DER CAM) which minimizes building energy costs for a typical reference year of operation. Several DER such as combined heat and power (CHP) units, photovoltaics, and battery storage are considered. The results indicate DER have economic and environmental competitiveness potential, especially for commercial buildings in hot and cold climates of both countries. In the U.S., the average expected energy cost savings in commercial buildings from DER CAM?s suggested investments is 17percent, while in Chinese buildings is 12percent. The electricity tariffs structure and prices along with the cost of natural gas, represent important factors in determining adoption of DER, more so than climate. High energy pricing spark spreads lead to increased economic attractiveness of DER. The average emissions reduction in commercial buildings is 19percent in the U.S. as a result of significant investments in PV, whereas in China, it is 20percent and driven by investments in CHP. Keywords: Building Modeling and Simulation, Distributed Energy Resources (DER), Energy Efficiency, Combined Heat and Power (CHP), CO2 emissions 1. Introduction The transition from a centralized and fossil-based energy paradigm towards the decentralization of energy supply and distribution has been a major subject of research over the past two decades. Various concerns have brought the traditional model into question; namely its environmental footprint, its structural inflexibility and inefficiency, and more recently, its inability to maintain acceptable reliability of supply. Under such a troubled setting, distributed energy resources (DER) comprising of small, modular, electrical renewable or fossil-based electricity generation units placed at or near the point of energy consumption, has gained much attention as a viable alternative or addition to the current energy system. In 2010, China consumed about 30percent of its primary energy in the buildings sector, leading the country to pay great attention to DER development and its applications in buildings. During the 11th Five Year Plan (FYP), China has implemented 371 renewable energy building demonstration projects, and 210 photovoltaics (PV) building integration projects. At the end of the 12th FYP, China is targeting renewable energy to provide 10percent of total building energy, and to save 30 metric tons of CO2 equivalents (mtce) of energy with building integrated renewables. China is also planning to implement one thousand natural gas-based distributed cogeneration demonstration projects with energy utilization rates over 70percent in the 12th FYP. All these policy targets require significant DER systems development for building applications. China?s fast urbanization makes building energy efficiency a crucial economic issue; however, only limited studies have been done that examine how to design and select suitable building energy technologies in its different regions. In the U.S., buildings consumed 40percent of the total primary energy in 2010 [1] and it is estimated that about 14 billion m2 of floor space of the existing building stock will be remodeled over the next 30 years. Most building?s renovation work has been on building envelope, lighting and HVAC systems. Although interest has emerged, less attention is being paid to DER for buildings. This context has created opportunities for research, development and progressive deployment of DER, due to its potential to combine the production of power and heat (CHP) near the point of consumption and delivering multiple benefits to customers, such as cost

25 ENERGY STORAGE↗
DOE OSTI2017

Implementation of a pressure correction term in the CTF sub-channel code

CTF [1] is a modernized and improved version of the legacy subchannel code, COBRA-TF [2], that is being jointly developed and maintained by Oak Ridge National Laboratory (ORNL) and North Carolina State University. The code was adopted by ORNL for use in the Consortium for Advanced Simulation of Light Water Reactors (CASL) in 2012 for aiding in addressing CASL challenge problems. Since that time, activities related to CTF have included implementing software quality assurance measures, implementing new features and models, performing validation and verification testing, establishing and supporting a CTF User Group, and developing the code for use in coupled applications [3, 4, 5]. CTF is applicable to single- and two-phase flows in light water reactor geometries at normal and accident operating conditions. The two-phase flow model consists of the six-equation two-phase flow model [6] augmented by equations for the droplet field and also includes appropriate source terms. This work focuses on the numerical stability of the six-equation two-phase flow model and is part of a recent eort to improve CTF capabilities for simulating flows in boiling nuclear reactors (BWRs). As it is of common knowledge among the thermodynamic community, the six-equation two-phase flow model is not strongly hyperbolic, meaning some of its eigenvalues are either not real or not distinct [7]. In a Cauchy sense and for an initial-value problem, strong hyperbolicity was found to be equivalent to well-posedness which ensures uniqueness of the solution in the space-time used. This concept is also of importance when designing high-order numerical methods and also when implementing boundary conditions that rely on real eigenvalues such as Riemann solvers. A tremendous amount of research is available in the literature on how to hyperbolize the six-equation two-phase flow model by adding ad hoc terms to the system of equations often referred to as virtual mass or interfacial pressure correction term. From a mathematical prospective, the main idea driving this approach is to add terms to the phasic momentum equation containing first-order partial derivatives of the unknowns to modify the Jacobian matrix and thus canceling the imaginary part of the eigenvalues.For this work it was chosen to implement a interfacial pressure correction (IPC) term on the same model as what was done for the CATHARE system code [8], that allows to recover a two-pressure formulation. In the following, the six-equation two-phase flow model is recalled along with the IPC term and its influence on the eigenvalues. Then, numerical results and convergence studies are presented for a water-faucet problem [9] at a pressure of 10 bar. Finally, conclusions and future work are addressed.

Delchini, Marco↗