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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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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A segmented approach to modeling building height: Delineating high-rise and low-rise buildings for enhanced height estimation

Understanding building height is imperative to the overall study of energy efficiency, population distribution, urban morphologies, emergency response, among others. Currently, existing approaches for modeling building height at scale are hindered by two pervasive issues. First, there is no consistent approach to quantify what a high-rise building is at a macro scale, leaving researchers unable to accurately compare results across geographies and domains. Second, high-rise buildings represent a small fraction of the built environment, implying data imbalance challenges that negatively affect current approaches. This is a problem of practical relevance since information on high-rise buildings is important for studies on urban heat islands, population dynamics, and pollution dispersion. Here, we introduce a novel approach to map building height which first identifies two distinct distributions within the built environment, with one being composed of low-rise buildings and one composed of high-rise buildings. We then develop an ensemble scheme where discrete specialist models are trained for each subset of low-rise buildings and high-rise buildings to infer building height from morphology features. For experiments mapping heights of 4.85 million buildings in Japan, we show an increase of 34 % in accuracy within 3m error when compared to the current state-of-the-art when modeling high-rise buildings, which based on KNN experimentation we define as any building > 12m . Our findings show that such an ensemble framework outperforms the current state-of-the-art approaches, which is especially relevant in relation to inferring height for high-rise buildings, a prominent issue of existing approaches for mapping the built environment.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Testing and modeling of CLT-to-CLT joints made using hardwood dowels and screws with varying spacing

With the increasing popularity of mass timber, utilizing large-diameter wood screws and hardwood dowels can offer an easy and cost-efficient way to join structural elements. However, the existing research on hardwood dowels is limited to single fastener joints under monotonic loading. No research is available on the group effects of joints with multiple hardwood dowels. Here, this paper presents the results of 96 monotonic and cyclic single-shear plane CLT-to-CLT joint tests with hardwood dowels (Red Oak and Yellow Birch, 25.4 mm diameter) and self-tapping wood screws (8 mm diameter) in Grand-Fir CLT, where screws were inserted both perpendicular and at a 45-degree angle to the grain for comparison to hardwood dowels. The study evaluated the mechanical properties of the joints by changing fastener spacing. Mechanical properties such as yielding and peak strength, displacement, elastic and yielding stiffness, and ductility were evaluated. The results showed equal strength and stiffness properties for hardwood dowels comparable with large-diameter screws. Additionally, the hardwood dowel joints demonstrated moderate ductility properties. The strength and stiffness of the tested joints were compared with analytical equations found in the literature by considering the group action factor of the fasteners. Lastly, a nonlinear force-displacement model was presented and compared to the experimental results and analytical calculations, which gives the possibility to predict and optimize the mechanical behavior of hardwood dowel and screw joints with varying numbers and spacing between fasteners.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The tier system: a host development framework for bioengineering

Development of microorganisms into mature bioproduction host strains has typically been a slow and circuitous process, wherein multiple groups apply disparate approaches with minimal coordination over decades. To help organize and streamline host development efforts, we introduce the Tier System for Host Development, a conceptual model and guide for developing microbial hosts that can ultimately lead to a systematic, standardized, less expensive, and more rapid workflow. The Tier System is made up of three Tiers, each consisting of a unique set of strain development Targets, including experimental tools, strain properties, experimental information, and process models. By introducing the Tier System, we hope to improve host development activities through standardization and systematization pertaining to nontraditional chassis organisms.

09 BIOMASS FUELS↗
DOE OSTI2026

Advancing specialized biofoundries via automated adaptive laboratory evolution

Adaptive laboratory evolution (ALE) is a powerful strategy for improving microbial phenotypes by harnessing natural selection under defined environmental conditions. Through applying selection regimes, beneficial mutations accumulate, enabling the generation of strains with enhanced properties. However, conventional ALE is labor-intensive and difficult to scale, limiting reproducibility and broader discovery of evolutionary principles. Recent advances in robotics, automation, and computational infrastructure are transforming ALE into a scalable, data-rich experimental paradigm. Automated platforms enable standardized and complex protocols, real-time monitoring, and highly parallel evolution campaigns, improving consistency while generating longitudinal datasets that reveal convergent adaptive mechanisms. Here, we discuss the role of specialized biofoundries in advancing automated ALE and enabling large-scale evolutionary engineering. We review major automated ALE formats and outline key design principles for effective ALE biofoundries, highlighting how automated ALE can support autonomous experimentation and AI-guided strain engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

A projection method for particle resampling

Particle discretizations of partial differential equations are advantageous for high-dimensional kinetic models in phase-space due to their better scalability than continuum approaches with respect to dimension. Complex processes collectively referred to as particle noise hamper long time simulations with particle methods. One approach to address this problem is particle mesh adaptivity, or remapping, known as particle resampling and remeshing. Here, this work introduces a resampling method that projects particles to and from a (finite element) function space. The method is simple, using standard sparse linear algebra and finite element techniques, and it preserves all moments up to the order of a polynomial represented exactly by the continuum function space. It is distinguished from most other mesh-based methods in that new particle positions and number are decoupled from the mesh, allowing particle and continuum meshes to be adapted relatively independently. While this work is developed with structured particle and continuum phase-space grids on 1X + 1V Vlasov-Poisson models of Landau damping and two-stream instability, the method is well-suited to unstructured grids. Stable long time dynamics are demonstrated up to time T = 500. Reproducibility artifacts and data are publicly available.

Kinetic methods↗
DOE OSTI2026

MFC 5.0: An exascale many-physics flow solver

Many problems of interest in engineering, medicine, and the fundamental sciences rely on high-fidelity flow simulation, making performant computational fluid dynamics solvers a mainstay of the open-source software community. Previous work MFC 3.0 was made a published, documented, and open-source solver via Bryngelson et al. Comp. Phys. Comm. (2021) with numerous physical features, numerical methods, and scalable infrastructure. MFC 5.0 is a significant update to MFC 3.0, featuring a broad set of well-established and novel physical models and numerical methods, as well as the introduction of GPU and APU (or superchip) acceleration. Here, we exhibit state-of-the-art performance and ideal scaling on the first two exascale supercomputers, OLCF Frontier and LLNL El Capitan. Combined with MFC’s single-accelerator performance, MFC achieves exascale computation in practice, and achieved the largest-to-date public CFD simulation at 200 trillion grid points as a 2025 ACM Gordon Bell Prize finalist. New physical features include the immersed boundary method, N-fluid phase change, Euler–Euler and Euler–Lagrange sub-grid bubble models, fluid-structure interaction, hypo- and hyper-elastic materials, chemically reacting flow, two-material surface tension, magnetohydrodynamics (MHD), and more. Numerical techniques now represent the current state-of-the-art, including general relaxation characteristic boundary conditions, WENO variants, Strang splitting for stiff sub-grid flow features, and low Mach number treatments. Weak scaling to tens of thousands of GPUs on OLCF Summit and Frontier and LLNL El Capitan achieves efficiencies within 5% of ideal to over 90% of their respective system sizes. Strong scaling results for a 16-times increase in device count show parallel efficiencies over 90% on OLCF Frontier. MFC’s software stack has undergone further improvements, including continuous integration, which ensures code resilience and correctness through over 300 regression tests; metaprogramming, which reduces code length while maintaining performance portability; and code generation for computing chemical reactions

Computational fluid dynamics↗
DOE OSTI2026

Fast solvers for tokamak fluid models with PETSc

Multigrid (MG) is widely recognized as a highly effective solver for the model problem, the Laplacian, but textbook MG fails on most problems of interest. MG methods have been applied to complex, real-world applications with careful consideration of the physical model and discretization. In this work we develop the first step in applying MG methods to science and engineering relevant magnetohydrodynamics (MHD) tokamak models in the M3D-C1 (https://m3dc1.pppl.gov) fusion energy science code. The semi-implicit time integrator in M3D-C1 is composed of many linear solves. The implicit advance of the momentum equation is the most challenging and is the focus of this work. The current production solver in M3D-C1 is a block Jacobi (BJ) preconditioner within a Krylov solver, where blocks group degrees of freedom on planes of constant toroidal coordinate. BJ convergence degrades as the number of planes increases due to the spectral properties of the matrix preconditioned with BJ. The partially magnetic field-aligned, regular toroidal grid structure in M3D-C1 is amenable to semi-coarsening geometric MG in the toroidal direction. This paper develops such a solver and demonstrates competitive performance on a runaway electron model of a SPARC (https://cfs.energy/technology/sparc) disruption, and superior robustness on a stellarator model on which the BJ solver fails to converge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Nonlinear programming optimization of a single-stack electrodialysis desalination system for cost efficiency

Electrodialysis (ED) presents a competitive method for desalinating brackish waters. In this work, we perform cost optimization of a single-stack ED system across a range of feed salinities and water recoveries while optimizing operating voltage, number of cell pairs, and cell length. The results of our optimization show that the levelized cost of water (LCOW) increases with an increase in feed salinity. The outcomes of our optimization show that cost-optimal design generally increases cell length while decreasing cell pair number and operating voltage with an increase in salinity. These trends are nonlinear, with the number of cell pairs and applied voltage exhibiting local maxima when operating at low salinity and high recovery. We discuss the underlying mechanism for cell length becoming a leveraging design parameter by inspecting the length-dependent profiles of key electrochemical properties of the ED cell. Finally, we present how increasing performance metrics and decreasing costs impact LCOW, demonstrating that innovations that decrease counter-current diffusion have resulted in the highest decrease of LCOW.

42 ENGINEERING↗
DOE OSTI2025

Modeling of multi-component precipitation and crystallization for zero-liquid-discharge desalination

This study proposes novel ZLD treatment trains that integrate multi-component chemical precipitation and multi-effect evaporative crystallization for efficient brine management. The methodology emphasizes sustainability by integrating CO₂ for chemical precipitation and reducing environmental impact, exemplified with two case studies: produced water that includes industrial waste heat utilization by adopting the emerging vacuum air-gapped membrane distillation (VAGMD) technology, and brackish groundwater that is abundant in sulphate which undergoes treatment by low-salt-rejection reverse osmosis (LSRRO) with interstage chemical precipitation. Here, this study is the first of its kind to simultaneously account for reducing risk of mineral scaling and effective recovery of valuable solids when incorporating VAGMD and LSRRO in ZLD treatment trains. Using Reaktoro and WaterTAP, both Python-based, open-source platforms, we model the recovery of high-purity magnesium, calcium, and sodium salts while optimizing energy consumption and operational efficiency in proposed ZLD pathways for case studies of produced water and brackish desalination brine management. Validation with experimental and reference data confirms the reliability of the models used. In both case studies, the optimized ZLD process achieves recovery rates of 97%, 99%, and 90% for Mg, Ca, and Na, with purities exceeding 99%, and brine volume reduced to less than 4% of the initial feed flow.

3D CT scans↗
DOE OSTI2025

Incorporating corrosion design constraints in desalination process optimization: A case study in mechanical vapor compression

Corrosion is an expensive and complex challenge for desalination, yet current design approaches do not explicitly account for corrosion mechanisms in process modeling and technoeconomic analysis. Here, to address this gap, we present a workflow for incorporating corrosion design constraints directly into desalination process optimization models. We develop surrogate models for general and localized corrosion metrics as functions of temperature, pH, salinity, dissolved oxygen, and material using data from OLI Systems’ Corrosion Analyzer. We then integrate these surrogates as corrosion design constraints in a cost-optimization MVC model that minimizes the levelized cost of water (LCOW). For a case study of mechanical vapor compression (MVC) treating seawater across a range of recoveries, we find dissolved oxygen (DO) is the dominant driver of localized corrosion, and thus of cost-optimal material choice and operating conditions. Reducing the DO from 8 mg/L to 0.5 mg/L reduces the LCOW by 15-35%, informing the breakeven costs for implementing DO removal or selecting highly corrosion-resistant alloys. This framework is broadly applicable across corrosion types, materials, and components and enables desalination process design that minimizes capital costs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Consistent performance of large language models in rare disease diagnosis across ten languages and 4917 cases

Background Large language models (LLMs) are increasingly used medicine for diverse applications including differential diagnostic support. The training data used to create LLMs such as the Generative Pretrained Transformer (GPT) predominantly consist of English-language texts, but LLMs could be used across the globe to support diagnostics if language barriers could be overcome. Initial pilot studies on the utility of LLMs for differential diagnosis in languages other than English have shown promise, but a large-scale assessment on the relative performance of these models in a variety of European and non-European languages on a comprehensive corpus of challenging rare-disease cases is lacking. Methods We created 4917 clinical vignettes using structured data captured with Human Phenotype Ontology (HPO) terms with the Global Alliance for Genomics and Health (GA4GH) Phenopacket Schema. These clinical vignettes span a total of 360 distinct genetic diseases with 2525 associated phenotypic features. We used translations of the Human Phenotype Ontology together with language-specific templates to generate prompts in English, Chinese, Czech, Dutch, French, German, Italian, Japanese, Spanish, and Turkish. We applied GPT-4o, version gpt-4o-2024-08-06, and the medically fine-tuned Meditron3-70B to the task of delivering a ranked differential diagnosis using a zero-shot prompt. An ontology-based approach with the Mondo disease ontology was used to map synonyms and to map disease subtypes to clinical diagnoses in order to automate evaluation of LLM responses. Findings For English, GPT-4o placed the correct diagnosis at the first rank 19.9% and within the top-3 ranks 27.0% of the time. In comparison, for the nine non-English languages tested here the correct diagnosis was placed at rank 1 between 16.9% and 20.6%, within top-3 between 25.4% and 28.6% of cases. The Meditron3 model placed the correct diagnosis within the first 3 ranks for 20.9% of cases in English and between 19.9% and 24.0% for the other nine languages. Interpretation The differential diagnostic performance of LLMs across a comprehensive corpus of rare-disease cases was largely consistent across the ten languages tested. This suggests that the utility of LLMs in clinical settings may extend to non-English clinical settings.

Artificial intelligence↗
DOE OSTI2026

Interactive effects of precipitation, temperature, and grazing pressure on the net ecosystem carbon balance of grazing lands across the continental United States

Grazing lands cover approximately one-third of the contiguous United States, support much of the nation's beef production, and are an important component of the U.S. terrestrial carbon budget. In this study, we quantified net ecosystem carbon balance (NECB), the net status of grazing lands as a carbon sink (C-sink) or source (C-source) and a key determinant of soil health and productivity. Our primary objective was to synthesize multiple years of annual NECB across heterogeneous grazing lands across the continental U.S and evaluate annual NECB against physical drivers (mean annual precipitation (MAP), mean annual temperature (MAT), vegetation, and moisture condition) and management practices (grazing pressure index (GPI) and fertilization history). We hypothesized that (1) NECB is higher in mesic and fertilized grasslands; (2) NECB increases with MAP and MAT but decreases with GPI; and (3) interactive effects exist among MAP, MAT, and GPI. Using carbon fluxes measured by eddy covariance towers and methane emissions including both enteric methane and manure derived from stocking rates across seven USDA Long-term Agroecosystem Research Network sites, we found: (1) grazing lands were a C-sink or carbon neutral at most sites; (2) vegetation type, moisture conditions, or fertilization had no significant effect on NECB; (3) NECB increased with MAP and MAT, but decreased with a higher GPI; and (4) MAT had a significant positive effect on NECB when MAP exceeded 750 mm (greater water availability). The effect of GPI on NECB was significantly negative when MAP was below 1000 mm, significantly negative when MAT < 12 °C and significantly positive when MAT > 16 °C. Thus, most grazing lands in our study acted as C-sinks unless water deficit, low temperature, or heavy grazing were interactively present. Understanding how climate and management influence NECB of grazing lands is key to maintaining resilient agroecosystems that secure beef production and sustain rural prosperity.

LTAR↗
DOE OSTI2025

Bridging interfacial properties and cell performance: A multiscale model for proton-exchange-membrane fuel cells

Here, to elucidate the impact of local interfaces on mass-transport resistance and overall cell performance of low-loaded proton-exchange-membrane fuel cells (PEMFCs), we present a multiscale modeling framework incorporating a novel modified agglomerate model. The model considers three distinct Pt-electrolyte interfaces: Pt on the carbon surface covered by either ionomer or water film and Pt inside carbon nanopores. Detailed mass-transport voltage-loss breakdowns reveal that coupled agglomerate-interface-scale mass transport dominates the mass-transport loss. The ionomer poisons the exterior-Pt surface through suppressing O 2 adsorption and intrinsic ORR activity, leading to low current-density performance. Conversely, interior-Pt interface enhances the kinetic performance but limits high current-density performance due to its low interfacial permeability. The exterior-Pt/water interface demonstrates superior kinetic performance and mass transport, though its practical implementation requires ensuring proton transport. By coupling the multiscale CL properties with ink parameters, the model identifies an optimal I to C ratio of approximately 0.5, a moderate value where the ionomer content is sufficient to guarantee proton transport without fully covering the Pt surface and forming large agglomeration, thus allowing the utilization of the Pt-water interface and avoiding high mass-transport loss. Overall, the model helps unravel limiting phenomena across different operating regimes and provides routes for optimizing performance.

Cell diagnostic↗
DOE OSTI2025

Fabrication of porous transport electrodes: Development of quantitative approach for quality control

This work focuses on porous transport electrodes (PTEs), which integrate the anodic catalyst with the adjacent Ti porous transport layer (PTL). Challenges in catalyst deposition on PTLs, particularly at low loadings, motivated this study to evaluate various fabrication methods and characterization approaches. This work investigated Pt-treated PTLs coated with Ir-based catalysts using several common methods, including airbrush coating, rod coating, ultrasonic spray coating, electrodeposition, and sputter deposition, with catalyst loadings ranging from 2.9 to 0.1 mg/cm 2 , providing the opportunity for comparisons across a large set of samples produced by different methods. Two widely accessible characterization techniques: X-ray computed tomography (XCT) and scanning electron microscopy energy dispersive X-ray spectroscopy (SEM-EDS) were explored. Initial evaluation of selected samples with XCT provided qualitative insights into catalyst distribution, however comprehensive quantitative analysis was limited. SEM-EDS enabled detailed information on the catalyst distribution both qualitatively and quantitatively using two metrics. Atomic and surface area % ratios of Pt:Ir and Ti:Ir revealed trends in catalyst loading and losses into the PTL pores, as well as evaluating the homogeneity of catalyst coatings. The analysis demonstrated that ultrasonic spray coating, electrodeposition, and sputter coating produced the most homogeneous coatings, with minimal catalyst losses observed for electrodeposition and sputter coating. By adapting common techniques with novel, standardized methodologies, this work establishes a universally applicable framework for cross-study comparison of PTEs. The SEM-EDS approach provides a practical, accessible tool for PTE characterization and contributes a reference dataset supporting both research development and rapid quality control.

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

Comparative assessment of new oxygen carrier materials for gas switching reforming of natural gas: Techno-economics assessment, life cycle analysis, and experimental insights

The increasing demand for hydrogen and the CO 2 intensity of natural gas (NG) reforming motivate the development of low-carbon-emission hydrogen production technologies. Gas Switching Reforming (GSR) with integrated CO 2 capture, a technology based on Chemical Looping Reforming (CLR), has been experimentally proven and shows potential for scale-up. In this study, select oxygen carriers (OC) (NiO/Al 2 O 3 , Fe 2 O 3 -CeO 2 /Al 2 O 3 , and magnetite) were tested in methane steam reforming in a fixed bed reactor to determine their relative reactivities under relevant conditions for GSR (800 °C, 7 bar total pressure). Process models were then developed to perform techno-economic analysis (TEA) of GSR for hydrogen production (GSR-H 2 ) and a combined cycle (GSR-CC) in which high-purity H 2 is fired in a gas turbine to produce electricity. Operating at 10 bar and 1100 °C and with the additional recovery steps implemented increased H 2 production by ∼ 30% and improved efficiency relative to prior studies. For GSR-H 2 , the levelized cost of hydrogen (LCOH) is 1.61–1.64 $/kg-H 2 , competitive with a reference SMR case, though operating and maintenance costs are higher due to increased electricity demand. GSR-CC has a significantly higher levelized cost of electricity (LCOE) than its reference NGCC (natural gas combined cycle) plant, suggesting it is less competitive; however, increasing production scale could make it more attractive. Life-cycle results for GSR-H 2 indicate NG consumption drives ∼ 75% of total global warming impacts (∼2.3 kg CO 2 eq/kg H 2 ). An environmental, health, and safety screening suggests iron-based carriers are comparatively safer, whereas NiO may pose greater risks. Overall, GSR-H 2 is a scalable, competitive option for hydrogen production using nickel and non-nickel OC.

03 NATURAL GAS↗
DOE OSTI2025

Development of a River Dynamical Core for E3SM to simulate compound flooding on Exascale-class heterogeneous supercomputers

Flooding events pose significant risk to human life, property, and infrastructure. Physically-consistent quantification of altered flood risks in global models requires hyper-resolution (~1 km) or fine flood simulations using two-dimensional (2D) physics schemes, both of which are unavailable in the current generation Earth System Models. Here, in this work, we have developed the River Dynamical Core (RDycore), which is an open-source, 2D shallow water equation (SWE) library for the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM). RDycore uses PETSc and libCEED libraries that allows it to run efficiently on CPUs and GPUs, as well as select a time-integration algorithm at runtime without requiring any code modifications. RDycore achieves spatial error convergence rates for problems with analytical and manufactured solutions similar to those reported previously in the literature, or consistent with the implemented first-order spatial discretization scheme. RDycore's accuracy in predicting flooding for a well-studied dam break problem is comparable to existing SWE models. For a problem with 471 million grid cells, RDycore achieves a speedup of 6.6x and 7.6x on GPUs compared to CPUs when using 320 compute nodes on DOE's Perlmutter and Frontier supercomputers, respectively. The one-way coupling of the RDycore library within E3SM is demonstrated by performing multiple 5-day flooding simulations during Hurricane Harvey driven by five precipitation datasets. The E3SM--RDycore simulations at 30 m spatial resolution accurately simulate maximum water height during the hurricane when benchmarked against a previously published study and achieve a speedup of 15x (Perlmutter) and 21x (Frontier) on GPUs relative to CPUs. The work presented here is the foundational step in providing hardware and algorithmic portability framework for simulating kilometer-scale river dynamics within E3SM.

Flood Simulation↗