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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Bioreactor Optimization through Multi-Phase Flow Models (CRADA Final Report)

Chemical manufacturing uses 29% of energy in the United States and produces 925 million metric tons of CO2 annually. Biomanufacturing offers the potential to leverage America’s rich agricultural resources to produce critical chemicals such as lubricants, pharmaceutical precursors, and components of energetic materials that today are sourced extensively from overseas. The bioreactors used in biomanufacturing applications, such as one developed by Capra Biosciences, involve multiphase flow of biofilm-coated solid support particles that are continuously circulated in a fluidized state within the reactor along with a constant supply of oxygen via an aeration mechanism. In this project, Capra Biosciences and LBNL developed a multiscale modeling framework to simulate the multiphase flows of solid particles in a liquid-gas bubble mixture that occurs in the bioreactor using the current MFIX-Exa software, an opensource multiphase flow solver developed and maintained at LBNL and NETL. By leveraging HPC capabilities, this high-fidelity multiscale model was used to inform design decisions for bioreactor architecture to make them operationally efficient.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Numerical Investigation of Fluid Flow and Space Charge in Liquid Argon Time Projection Chamber (LArTPC) Detectors

Overview This project focused on developing a high-fidelity numerical framework to simulate the multiphysics environment within Liquid Argon Time Projection Chamber (LArTPC) detectors. The primary objective was to characterize the complex interplay between ion transport, background fluid dynamics, and electric field distortions—a critical factor for the calibration and sensitivity of next-generation High Energy Physics experiments, such as DUNE. Technical Achievements The research successfully yielded a hybrid numerical space-charge solver utilizing a Cell-Centered Finite Volume Method (FVM) for ion transport coupled with a Finite Element Method (FEM) for electric potential. Key accomplishments include: • Verification & Validation: The 3-D solver was rigorously verified against 1-D analytical solutions, demonstrating high numerical accuracy in predicting space-charge-induced field deviations. • Field Distortion Analysis: 3D simulations revealed that space charge effects introduce significant non-uniformities in the electric field. Critically, the research identified that background LAr flow velocities, when comparable to ion drift velocities, markedly exacerbate these distortions. • Technology Transfer: The resulting source code and comprehensive user manuals were successfully transferred to collaborators at Fermilab, providing a portable computational tool for the broader scientific community. Challenges and Future Directions While the space-charge solver achieved all performance metrics, the integrated fluid dynamics modeling encountered convergence challenges stemming from the extreme 200-fold disparity in length scales between the detector's 37 mm inlet pipes and the 8-meter global domain. To address this, the project has identified a clear technical pivot toward Hierarchical Geometric Adaptive Mesh Refinement (HG-AMR). By implementing an h-type refinement strategy with hanging nodes, future iterations of this solver will be capable of resolving localized high-gradient inlet flows without the prohibitive computational costs of regular grids. This advancement, combined with data-driven uncertainty quantification based on MicroBooNE-style calibration, will enable the precise modeling of detector responses in large-scale cryogenic environments where direct measurement remains difficult. Impact The computational tools developed under this award provide a foundation for enhancing the energy resolution and spatial reconstruction of noble liquid detectors. By bridging the gap between theoretical fluid dynamics and experimental field calibration, this work supports the DOE’s mission to advance the frontiers of neutrino physics and dark matter detection.

42 ENGINEERING↗
DOE OSTI2025

The Monolithic Heat Pipe Microreactor Reference Plant Model Updates

This work presents the latest improvements to, and investigations performed with, the generic monolithic heat-pipe-cooled microreactor reference plant model for the United States Nuclear Regulatory Commission. This model serves as the foundation for the future detailed design evaluation models based on license applications. This model has been developed with the Comprehensive Reactor Analysis Bundle (BlueCRAB) and its specifications are based on open literature publications for the eVinci™ design . BlueCRAB is the U.S. Nuclear Regulatory Commission non-light-water reactor analysis system based on MOOSE, the Multiphysics Object-Oriented Simulation Environment framework, which can couple the Griffin, BISON, and Sockeye applications to resolve the various physics that are essential for the safety analysis of this type of reactor system. The core specifications include tristructural isotropic fuel, graphite monolith, graphite reflectors, and drums composed of graphite and B 4 C.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Stochastic microstructural analysis of ceramic matrix composites using a high-fidelity multiscale framework

This paper presents a high-fidelity multiscale framework to simulate the mechanical behavior of ceramic matrix composites (CMCs), accounting for the complex micromorphology captured using detailed material characterization. First, high-resolution micrographs are obtained for the specific carbon fiber silicon-carbide-nitride matrix (C/SiNC) CMC to characterize the variability of the architectural features and manufacturing-induced defects at the microscale. An image processing algorithm is then used to precisely estimate the size and distribution of all subscale features and defects from the micrographs. The information is then used to generate a three-dimensional stochastic representative volume element (SRVE) to reconstruct microscale constituents accounting for the variability. As a result, the generated SRVEs are simulated using the high-fidelity generalized method of cells (HFGMC) micromechanics theory to investigate the effects of defects on the elastic properties of C/SiNC CMCs.

Ceramic Matrix Composites↗
DOE OSTI2025

Housing-Performance Atlas of Baltimore Row Homes: Archetype-Based Multi-Hazard Baseline of Energy, Heat, Survivability, and Durability

Baltimore’s historic row-home neighborhoods face escalating risks to energy, heat, and durability under intensifying climate stress. This study develops a Housing-Performance Atlas that quantifies multi-hazard performance for eight representative archetypes using DesignBuilder/EnergyPlus Version 7.3.1.003, under Baltimore TMY3 boundary conditions. Performance is evaluated across the following four adaptation domains: energy use intensity, passive survivability during 72 h outage events, roof overheating exposure (>150 °F exceedance hours), and material service life derived from ISO 15686 and synthesized into Lean and Full Deficit Indices for comparative resilience ranking. Results show that EUI ranged from 46.7 to 67.6 kBtu ft −2 ·yr −1 , survivability from 0 to 23 h, and roof temperatures exceeded 150 °F for 150–210 h, shortening roof service life by up to 10 years. Composite Lean and Full Deficit Indices ranged 7.8–92.4, ranking Model 5 (end-unit, flat roof, two-story with basement) as the most resilient configuration and Model 8 (end-unit, pitched roof, three-story above-grade) as the least resilient due to compounded overheating and energy losses. Heat-related domains accounted for nearly 70% of overall resilience deficits, confirming thermal safety and roof reflectivity as retrofit priorities. The Housing-Performance Atlas establishes a reproducible diagnostic framework linking simulation, service life, and resilience metrics to guide cost-effective, climate-responsive retrofits in Baltimore’s aging urban housing stock.

Housing-Performance atlas↗
DOE OSTI2016

Cloud structure of galactic OB cluster-forming regions from combining ground- and space-based bolometric observations

We have developed an iterative procedure to systematically combine the millimeter and submillimeter images of OB cluster-forming molecular clouds, which were taken by ground-based (CSO, JCMT, APEX, and IRAM-30 m) and space telescopes (Herschel and Planck). For the seven luminous (L>10{sup 6} L {sub ⊙}) Galactic OB cluster-forming molecular clouds selected for our analyses, namely W49A, W43-Main, W43-South, W33, G10.6-0.4, G10.2-0.3, and G10.3-0.1, we have performed single-component, modified blackbody fits to each pixel of the combined (sub)millimeter images, and the Herschel PACS and SPIRE images at shorter wavelengths. The ∼10″ resolution dust column density and temperature maps of these sources revealed dramatically different morphologies, indicating very different modes of OB cluster-formation, or parent molecular cloud structures in different evolutionary stages. The molecular clouds W49A, W33, and G10.6-0.4 show centrally concentrated massive molecular clumps that are connected with approximately radially orientated molecular gas filaments. The W43-Main and W43-South molecular cloud complexes, which are located at the intersection of the Galactic near 3 kpc (or Scutum) arm and the Galactic bar, show a widely scattered distribution of dense molecular clumps/cores over the observed ∼10 pc spatial scale. The relatively evolved sources G10.2-0.3 and G10.3-0.1 appear to be affected by stellar feedback, and show a complicated cloud morphology embedded with abundant dense molecular clumps/cores. We find that with the high angular resolution we achieved, our visual classification of cloud morphology can be linked to the systematically derived statistical quantities (i.e., the enclosed mass profile, the column density probability distribution function (N-PDF), the two-point correlation function of column density, and the probability distribution function of clump/core separations). In particular, the massive molecular gas clumps located at the center of G10.6-0.4 and W49A, which contribute to a considerable fraction of their overall cloud masses, may be special OB cluster-forming environments as a direct consequence of global cloud collapse. These centralized massive molecular gas clumps also uniquely occupy much higher column densities than what is determined by the overall fit of power-law N-PDF. We have made efforts to archive the derived statistical quantities of individual target sources, to permit comparisons with theoretical frameworks, numerical simulations, and other observations in the future.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Observing Exoplanets with High Dispersion Coronagraphy. I. The Scientific Potential of Current and Next-generation Large Ground and Space Telescopes

Direct imaging of exoplanets presents a formidable technical challenge owing to the small angular separation and high contrast between exoplanets and their host stars. High Dispersion Coronagraphy (HDC) is a pathway to achieve unprecedented sensitivity to Earth-like planets in the habitable zone. Here, we present a framework to simulate HDC observations and data analyses. The goal of these simulations is to perform a detailed analysis of the trade-off between raw star light suppression and spectral resolution for various instrument configurations, target types, and science cases. We predict the performance of an HDC instrument at Keck observatory for characterizing directly imaged gas-giant planets in near-infrared bands. We also simulate HDC observations of an Earth-like planet using next-generation ground-based (TMT) and spaced-base telescopes (HabEx and LUVOIR). We conclude that ground-based ELTs are more suitable for HDC observations of an Earth-like planet than future space-based missions owing to the considerable difference in collecting area. For ground-based telescopes, HDC observations can detect an Earth-like planet in the habitable zone around an M-dwarf star at 10{sup −4} star light suppression level. Compared to the 10{sup −7} planet/star contrast, HDC relaxes the star light suppression requirement by a factor of 10{sup 3}. For space-based telescopes, detector noise will be a major limitation at spectral resolutions higher than 10{sup 4}. Considering detector noise and speckle chromatic noise, R = 400 (1600) is the optimal spectral resolutions for HabEx (LUVOIR). The corresponding star light suppression requirement to detect a planet with planet/star contrast = 6.1×10{sup −11} is relaxed by a factor of 10 (100) for HabEx (LUVOIR).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Bioverse: A Comprehensive Assessment of the Capabilities of Extremely Large Telescopes to Probe Earth-like O 2 Levels in Nearby Transiting Habitable-zone Exoplanets

Molecular oxygen is a strong indicator of life on Earth and may indicate biological processes on exoplanets too. Recent studies proposed that Earth-like O 2 levels might be detectable on nearby exoplanets using high-resolution spectrographs on future extremely large telescopes (ELTs). However, these studies did not consider constraints like relative velocities, planet occurrence rates, and target observability. We expanded on past studies by creating a homogeneous catalog of 286,391 main-sequence stars within 120 pc using Gaia DR3 and used the Bioverse framework to simulate the likelihood of finding nearby transiting Earth analogs. We also simulated a survey of M dwarfs within 20 pc accounting for η ⊕ estimates, transit probabilities, relative velocities, and target observability to determine how long ELTs and theoretical 50–100 m ground-based telescopes need to observe to probe for Earth-like O 2 levels with an R = 100,000 spectrograph. This would only be possible within 50 yr for up to ~21% of nearby M-dwarf systems if a suitable transiting habitable-zone Earth analog was discovered, assuming signals from every observable partial transit from each ELT can be combined. If so, Earth-like O 2 levels could be detectable on TRAPPIST-1 d–g within 16–55 yr, respectively, and about half that time with an R = 500,000 spectrograph. These results have important implications for whether ELTs can survey nearby habitable-zone Earth analogs for O 2 via transmission spectroscopy. Our work provides the most comprehensive assessment to date of the ground-based capabilities to search for life beyond the solar system.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

The Planetary Accretion Shock. I. Framework for Radiation-hydrodynamical Simulations and First Results

The key aspect determining the postformation luminosity of gas giants has long been considered to be the energetics of the accretion shock at the surface of the planet. We use one-dimensional radiation-hydrodynamical simulations to study the radiative loss efficiency and to obtain postshock temperatures and pressures and thus entropies. The efficiency is defined as the fraction of the total incoming energy flux that escapes the system (roughly the Hill sphere), taking into account the energy recycling that occurs ahead of the shock in a radiative precursor. We focus in this paper on a constant equation of state (EOS) to isolate the shock physics but use constant and tabulated opacities. While robust quantitative results will have to await a self-consistent treatment including hydrogen dissociation and ionization, the results presented here show the correct qualitative behavior and can be understood from semianalytical calculations. The shock is found to be isothermal and supercritical for a range of conditions relevant to the core accretion formation scenario (CA), with Mach numbers M≳3. Across the shock, the entropy decreases significantly by a few times k{sub B}/baryon. While nearly 100% of the incoming kinetic energy is converted to radiation locally, the efficiencies are found to be as low as roughly 40%, implying that a significant fraction of the total accretion energy is brought into the planet. However, for realistic parameter combinations in the CA scenario, we find that a nonzero fraction of the luminosity always escapes the Hill sphere. This luminosity could explain, at least in part, recent observations in the young LkCa 15 and HD 100546 systems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Dust Polarization Maps from TIGRESS: E/B Power Asymmetry and TE Correlation

We present the first large set of all-sky synthetic dust polarization maps derived directly from a self-consistent magnetohydrodynamics simulation using the TIGRESS framework. Turbulence in this simulation is predominantly driven by supernova explosions, with rates that are self-consistently regulated by feedback loops. The simulation covers both the outer scale and inertial range of turbulence with uniformly high resolution. The shearing-box utilized in the simulation, in concert with resolved supernova-driven turbulence, enables the capturing of generation, growth, and saturation of both turbulent and mean magnetic fields. We construct polarization maps at 353 GHz, as seen by observers inside a model of the multiphase, turbulent, magnetized interstellar medium (ISM). To fully sample the simulated ISM state, we use 350 snapshots spanning over $\sim 350\,\mathrm{Myr}$ (more than six feedback loops) and nine representative observers. The synthetic skies show a prevalent E/B power asymmetry (${EE}\gt {BB}$) and positive TE correlation in broad agreement with observations by the Planck satellite. However, the ranges of ${EE}/{BB}\sim 1.4\mbox{-}1.7$ and ${TE}/{({TT}\cdot {EE})}^{1/2}\sim 0.2\mbox{-}0.3$ are generally lower than those measured by Planck. We find large fluctuations of E/B asymmetry and TE correlation depending on the observer's position and temporal fluctuations of ISM properties due to bursts of star formation. The synthetic maps are made publicly available to provide novel models of the microwave sky.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Dwarf Galaxies at Cosmic Noon: New JWST Constraints on Satellite Models and Subhalo Tidal Evolution

The advent of JWST has revolutionized the study of faint satellite galaxies at z ≳ 1, enabling statistical constraints on galaxy evolution and the galaxy–halo connection in a previously unexplored mass and redshift regime. We compare satellite abundances at 1 < z < 3.5 from recent JWST observations with predictions from cosmological dark-matter-only zoom-in simulations. We identify and quantify several sources of biases that can impact theoretical satellite counts, finding that assumptions about subhalo tidal evolution introduce the largest uncertainty in predictions for the satellite mass function. Using a flexible galaxy disruption model, we explore a range of disruption scenarios, spanning hydrodynamically motivated and idealized prescriptions, to bracket plausible physical outcomes. We show that varying galaxy durability can change the predicted satellite mass functions by a factor of ∼3.5. The JWST data and our fiducial model are consistent within 1σ–2σ across the full redshift (1 < z < 3.5) and stellar mass (M⋆ > 10 7 M ⊙ ) range probed. We find evidence that subhalos are at least as long-lived as predicted by hydrodynamic simulations. Our framework will enable robust constraints on the tidal evolution of subhalos with future observations. This work presents the first direct comparison between cosmological models and observations of the high-redshift satellite population in this low-mass regime. These results showcase JWST’s emerging power to test structure formation in the first half of the Universe in a new domain and to constrain the physical processes driving the evolution of low-mass galaxies across cosmic time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Multigroup Thermal Radiation Transport with Tensor Trains

We investigate the application of tensor-train (TT) algorithms to multigroup thermal radiation transport (i.e., photon radiation transport). The TT framework enables simulations at discretizations that might otherwise be computationally infeasible on conventional hardware. We show that solutions to certain multigroup problems possess an intrinsic low-rank structure, which the TT representation leverages effectively. This enables us to solve problems where the discretized solution size exceeds a trillion parameters on a single node. The solver is evaluated on a range of test problems with varying levels of complexity, consistently achieving compression factors greater than 100× and speedups exceeding 2×. We also investigate alternative TT topologies by analyzing the low-rank structure of the merged spatio-spectral core to assess the potential for greater compression. This analysis suggests that compression gains could increase by factors as large as 7. Our results indicate that the low-rank structure of the merged spatio-spectral core captures the spatio-spectral complexity of the solution, largely driven by the opacity structure of the medium. Beyond identifying opportunities for improved compression, this analysis highlights the types of errors that may arise in angle-integrated quantities when exploiting this low-rank structure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Propagating Uncertainties in the SALT3 Model-training Process to Cosmological Constraints

Type Ia supernovae (SNe Ia) are standardizable candles that must be modeled empirically to yield cosmological constraints. To understand the robustness of this modeling to variations in the model-training procedure, we build an end-to-end pipeline to test the recently developed SALT3 model. We explore the consequences of removing pre-2000s low-z or poorly calibrated U-band data, adjusting the amount and fidelity of SN Ia spectra, and using a model-independent framework to simulate the training data. We find that the SALT3 model surfaces are improved by having additional spectra and U-band data, and can be shifted by ~5% if host-galaxy contamination is not sufficiently removed from SN spectra. We find that resulting measurements of w are consistent to within 2.5% for all of the training variants explored in this work, with the largest shifts coming from variants that add color-dependent calibration offsets or host-galaxy contamination to the training spectra and those that remove pre-2000s low-z data. These results demonstrate that the SALT3 model-training procedure is largely robust to reasonable variations in the training data, but that additional attention must be paid to the treatment of spectroscopic data in the training process. We also find that the training procedure is sensitive to the color distributions of the input data—the resulting w measurement can be biased by ~2% if the color distribution is not sufficiently wide. Future low-z data, particularly u-band observations and high signal-to-noise ratio SN Ia spectra, will help to significantly improve SN Ia modeling in the coming years.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A robust approach to Gaussian process implementation

Abstract. Gaussian process (GP) regression is a flexible modeling technique used to predict outputs and to capture uncertainty in the predictions. However, the GP regression process becomes computationally intensive when the training spatial dataset has a large number of observations. To address this challenge, we introduce a scalable GP algorithm, termed MuyGPs, which incorporates nearest-neighbor and leave-one-out cross-validation during training. This approach enables the evaluation of large spatial datasets with state-of-the-art accuracy and speed in certain spatial problems. Despite these advantages, conventional quadratic loss functions used in the MuyGPs optimization, such as root mean squared error (RMSE), are highly influenced by outliers. We explore the behavior of MuyGPs in cases involving outlying observations and, subsequently, develop a robust approach to handle and mitigate their impact. Specifically, we introduce a novel leave-one-out loss function based on the pseudo-Huber function (LOOPH) that effectively accounts for outliers in large spatial datasets within the MuyGPs framework. Our simulation study shows that the LOOPH loss method maintains accuracy despite outlying observations, establishing MuyGPs as a powerful tool for mitigating unusual observation impacts in the large data regime. In the analysis of US ozone data, MuyGPs provides accurate predictions and uncertainty quantification, demonstrating its utility in managing data anomalies. Through these efforts, we advance the understanding of GP regression in spatial contexts.

Mukangango, Juliette↗
DOE OSTI2025

A new biogeochemical modelling framework (FLaMe-v1.0) for lake methane emissions on the regional scale: development and application to the European domain

This study presents a new physical-biogeochemical modelling framework for simulating lake methane (CH 4 ) emissions at regional scales. The new model, FLaMe-v1.0 (Fluxes of Lake Methane), rests on an innovative, computationally efficient lake clustering approach that enables the simulation of CH 4 emissions across a large number of lakes. Building on the Canadian Small Lake Model (CSLM) that simulates the lake physics, we develop a suite of biogeochemical modules to simulate transient dynamics of organic Carbon (C), Oxygen (O 2 ), and CH 4 . We first test the performance of FLaMe-v1.0 by analyzing physical and biogeochemical processes in two theoretical lakes with characteristics that can be considered representative for many lakes (an oligotrophic, deep lake driven by cold climate versus a eutrophic, shallow lake driven by warm climate). Next, we evaluate the model by comparing simulated and observed timeseries of CH 4 emissions in four well-surveyed lakes. We then apply FLaMe-v1.0 at the European scale to evaluate simulated diffusive and ebullitive lake CH 4 fluxes against in-situ measurements in both boreal and central European regions. Finally, we provide a first assessment of the spatio-temporal variability in CH 4 emissions from European lakes with a surface area comprised between 0.1–1000 km 2 (n= 108 407, total area = 1.33 × 105 km 2 ), indicating a total emission of 0.97 ± 0.23 Tg CH 4 yr −1 , with the uncertainty constrained by combining FLaMe-v1.0 and machine learning techniques. Moreover, 30 % and 70 % of these CH 4 emissions are through diffusive and ebullitive pathways, respectively. Annually averaged CH 4 emission rates per unit lake area during 2010–2016 have a South-to-North decreasing gradient, resulting in a mean over the European domain as 7.39 g CH 4 m −2 yr −1 . Our simulations reveal a strong seasonality (with ice-blocking effects accounted for) in European lake CH 4 emissions, with nearly ten times higher emissions during late summer than during winter. This pronounced seasonal variation highlights the importance of accounting for the sub-annual variability in CH 4 emissions to accurately constrain regional CH 4 budgets. In the future, FLaMe-v1.0 could be embedded into Earth System Models to investigate the feedback between climate warming and global lake CH 4 emissions.

Maisonnier, Manon [Free Univ. of Brussels (Belgium↗
DOE OSTI2026

Runoff evaluation in an Earth System Land Model for permafrost regions in Alaska

Modeling of hydrological runoff is essential for accurately capturing spatiotemporal feedbacks within the land–atmosphere system, particularly in sensitive regions such as permafrost landscapes. However, substantial uncertainties persist in the terrestrial runoff parameterization schemes used in Earth system and land surface models. This is particularly true in permafrost regions, where landscape heterogeneity is high and reliable observational data are scarce. In this study, we evaluate the performance of runoff parameterization schemes in the Energy Exascale Earth System Model (E3SM) land model (ELM). Our proposed framework leverages simulation results from the Advanced Terrestrial Simulator (ATS), which is a physics-based integrated surface/subsurface hydrologic model that has been successfully evaluated previously in Arctic tundra regions. We used ATS to simulate runoff from 22 representative hillslopes in the Sagavanirktok River basin, located on the North Slope of Alaska, then compared the output with ELM's parameterized representation of total runoff. Results show that (1) ELM's total runoff was the same order of magnitude as the ATS simulations, and both models were similarly variable over time; (2) minor adjustments to coefficients in ELM's runoff parameterization improved the match between the ATS simulation and ELM's parameterized representation of annual and seasonal total runoff; (3) overall, runoff responses in ATS and ELM are more similar in flat hillslope environments compared to steep hillslopes; and (4) shallower active layer thicknesses and higher precipitation simulations resulted in lower correlations between the two models due to greater total runoff. By incorporating the optimized runoff coefficients from the Sagavanirktok River basin into ELM, the simulated total runoff better matched the streamflow observations at a small watershed located on the Seward Peninsula of Alaska. Our findings revealed important insights into the effectiveness of runoff parameterizations in land surface models and pathways for improving runoff coefficients in typical Arctic regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Xanthos-Lake Model Source Code

This repository contains the source code for Xanthos-Lake, a lake-modeling extension of the Xanthos framework that introduces a coupled lake component comprising the Xanthos-Lake Snow and Ice Model (xLSIM) and the Xanthos-Lake Water Balance Model (xLWBM). xLSIM is a basin-aware machine-learning model for lake snow, ice, and thermal conditions. It predicts monthly lake ice thickness, snow depth, snow-cover fraction, mixing-layer temperature, and lake ice fraction from meteorological forcing and lake surface-area information. It uses sequence-based deep-learning architectures, including Transformer and hybrid Long Short-Term Memory–Transformer (LSTM–Transformer) models, together with seasonal encoding, multi-lake learning, physical masking, and basin-level cryospheric and non-cryospheric classification. The training workflow uses Ray for scalable execution and includes optional Ray Tune hyperparameter optimization. Model predictions, observations, diagnostics, and feature-importance outputs are written in NetCDF. xLWBM is the water-balance component of the new lake framework. It simulates monthly lake storage, surface area, evaporation, inflow, outflow, and lake–groundwater exchange. It combines physical water-balance equations with calibrated bathymetric relationships, weir-based outlet flow, modified Penman open-water evaporation, groundwater head relaxation, Penman–Monteith snow and ice sublimation, and snow, ice, and thermal conditions supplied by xLSIM. The model calibrates lake parameters against satellite-derived surface-area data, using evaporation-based calibration where surface-area data are unavailable, and supports small, medium, and large lake classes. For large lakes, xLWBM is integrated with the managed-routing workflow so that lake storage and outflow interact directly with downstream river routing and reservoir operations. Together, xLSIM and xLWBM provide Xanthos with a coupled lake-modeling capability. xLSIM supplies the snow, ice, and thermal conditions that affect lake evaporation and snow- and ice-related water exchanges, while xLWBM translates those conditions into dynamic lake storage, surface area, evaporation, and discharge. In return, xLWBM supplies evolving lake surface area to xLSIM. This coupling enables Xanthos to represent lakes as active hydrologic components within basin-scale water-availability and routing simulations.

Machine Learning↗
DOE OSTI2016

Urban Renewable Building And Neighborhood Optimization

URBANopt is a user interface for creating and running district and city scale building energy simulations. The framework is built around the OpenStudio Urban Measures which are part of the OpenStudio project. Building footprints, building height, building type, and other data can be imported from public records or other sources. Footprints and locations for new buildings and district systems can also be specified. OpenStudio Measures are used to create starting point energy models and to model energy design features and efficiency measures for each building. URBANopt allows a user to pose several scenarios such as “what if 30% of the commercial retail buildings added roof top solar” or “what if all elementary schools converted to ground source heat pumps” and then visualize the impacts at a district or city scale. URBANopt is capable of modeling existing buildings, new construction, and district energy systems. URBANopt can be used to explore options for achieving Zero Energy across a collection of buildings (e.g., Zero Energy Districts).

Source record↗