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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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DOE OSTI2026

TChem-atm (v2.0.0): scalable performance-portable multiphase atmospheric chemistry

We present TChem-atm, a performance-portable approach that enables efficient simulation of chemically detailed and multiphase atmospheric chemistry on modern heterogeneous computing architectures. Unlike previous efforts that rely on architecture-specific code or focus exclusively on gas-phase chemistry, TChem-atm supports fully coupled gas–aerosol systems with execution across CPUs, NVIDIA GPUs, and AMD GPUs through the Kokkos programming model. It integrates the flexible multiphase capabilities of the Community Atmospheric Model Chemistry Package (CAMP) with the high-performance kinetic routines of TChem, and includes automatic Jacobian construction with support for a range of stiff ODE solvers. In a proof-of-concept integration with the particle-resolved model PartMC, TChem-atm reproduces the existing PartMC–CAMP implementation within solver tolerances and delivers substantial GPU speedups, especially for large particle populations. Performance benchmarks reveal substantial speedups on GPU platforms, particularly for large particle populations, with consistent results across hardware backends. TChem-atm enables performance-portable execution across CPUs and GPUs, though optimal efficiency may require modest architecture-specific tuning (e.g., team and vector sizes), with up to a twofold improvement on the NVIDIA H100. It directly supports sectional and particle-resolved host models, while modal aerosol schemes require minor adaptation to provide particle-scale quantities such as representative diameters. By enabling chemically detailed, multiphase simulations with performance portability and host-model flexibility, TChem-atm facilitates the incorporation of advanced chemistry into atmospheric models.

Díaz-Ibarra, Oscar Homero [Sandia National Laborat↗
DOE OSTI2024

Probabilistic projections of the Amery Ice Shelf catchment, Antarctica, under conditions of high ice-shelf basal melt

Abstract. Antarctica's Lambert Glacier drains about one-sixth of the ice from the East Antarctic Ice Sheet and is considered stable due to the strong buttressing provided by the Amery Ice Shelf. While previous projections of the sea-level contribution from this sector of the ice sheet have predicted significant mass loss only with near-complete removal of the ice shelf, the ocean warming necessary for this was deemed unlikely. Recent climate projections through 2300 indicate that sufficient ocean warming is a distinct possibility after 2100. This work explores the impact of parametric uncertainty on projections of the response of the Lambert–Amery system (hereafter “the Amery sector”) to abrupt ocean warming through Bayesian calibration of a perturbed-parameter ice-sheet model ensemble. We address the computational cost of uncertainty quantification for ice-sheet model projections via statistical emulation, which employs surrogate models for fast and inexpensive parameter space exploration while retaining critical features of the high-fidelity simulations. To this end, we build Gaussian process (GP) emulators from simulations of the Amery sector at a medium resolution (4–20 km mesh) using the Model for Prediction Across Scales (MPAS)-Albany Land Ice (MALI) model. We consider six input parameters that control basal friction, ice stiffness, calving, and ice-shelf basal melting. From these, we generate 200 perturbed input parameter initializations using space filling Sobol sampling. For our end-to-end probabilistic modeling workflow, we first train emulators on the simulation ensemble and then calibrate the input parameters using observations of the mass balance, grounding line movement, and calving front movement with priors assigned via expert knowledge. Next, we use MALI to project a subset of simulations to 2300 using ocean and atmosphere forcings from a climate model for both low- and high-greenhouse-gas-emission scenarios. From these simulation outputs, we build multivariate emulators by combining GP regression with principal component dimension reduction to emulate multivariate sea-level contribution time series data from the MALI simulations. We then use these emulators to propagate uncertainty from model input parameters to predictions of glacier mass loss through 2300, demonstrating that the calibrated posterior distributions have both greater mass loss and reduced variance compared to the uncalibrated prior distributions. Parametric uncertainty is large enough through about 2130 that the two projections under different emission scenarios are indistinguishable from one another. However, after rapid ocean warming in the first half of the 22nd century, the projections become statistically distinct within decades. Overall, this study demonstrates an efficient Bayesian calibration and uncertainty propagation workflow for ice-sheet model projections and identifies the potential for large sea-level rise contributions from the Amery sector of the Antarctic Ice Sheet after 2100 under high-greenhouse-gas-emission scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Influence of wind turbine design parameters on linearized physics-based models in OpenFAST

Abstract. While most physics involved in wind energy are nonlinear, linearization of the underlying nonlinear wind system equations is often important for understanding the system response and exploiting well-established methods and tools for analyzing linear systems. Linearized models are important for eigenanalysis (to derive structural natural frequencies, damping ratios, and mode shapes), controls design (based on linear state-space models), etc. In controls co-design, wherein methods often rely on linearized time-domain models of the physics, the physical structure (often called the plant) and controller are designed and optimized concurrently, so it is important to understand how changes to the physical design affect the linearized system. This work summarizes efforts done to understand the impact of design parameter variations in the physical system (e.g., mass, stiffness, geometry, and aerodynamic and hydrodynamic coefficients) on the linearized system using OpenFAST.

17 WIND ENERGY↗
DOE OSTI2023

Natural Fracture Pattern Development Using 3D Coupled Numerical Model: Mechanics and Diagenesis

In the earth's crust, while tectonic processes can mechanically create natural fractures, cementation can simultaneously grow on the surfaces of the fractures. This crystallization can affect the growth of the fractures. To more accurately address the modeling of natural fracture development, both mechanical deformation and chemical diagenesis should be carried out in an integrated manner. Here, we achieve this with a three-dimensional (3D) simulator that couples mechanical and chemical processes for natural fracture pattern development in layer confined situations. Tectonic loading over geologic time is mimicked by displacement driven boundary conditions in a 3D displacement discontinuity method (DDM) scheme. Quartz diagenesis competes with mechanical fracture opening, resulting in three different cementation conditions - open, bridging or fully infilled – which define fracture element stiffness that is used as feedback within the 3D-DDM code during propagation. An important milestone of this work is that this coupled structural diagenetic model can reproduce power-law aperture population statistics which cannot be generated using mechanics alone. More accurately estimated mechanical fracture apertures and their cementation condition is a critical step toward better permeability estimation and fluid path analysis for subsurface reservoirs.

58 GEOSCIENCES↗
DOE OSTI2026

Multibody for Everybody (M4E) - A Linearization Approach to Enable Frequency Domain Analysis, Time Integration and Control Co-Design

1.1 Background/Objectives: Marine energy represents a promising yet underexploited source of power. To increase the harvested power, significant efforts have been made to improve wave energy converter (WEC) modeling capabilities and optimize power take-off (PTO) performance; however, these efforts have often treated WEC dynamics, PTO design, and controller development sequentially. In contrast, control co-design (CCD) is emerging as a promising strategy to address these issues directly, creating a growing need for fast analysis tools suitable for repeated simulation and parametric studies [1]. To support this need, this work presents the Multibody for Everybody (M4E) [2] linearization module, which employs a symbolic toolbox to provide deeper insight of WEC design parameters. The objective is to demonstrate that a minimal-coordinate linearization of articulated WEC dynamics can provide accurate wave response predictions and substantial computational savings relative to nonlinear time-domain simulation, while preserving compatibility with broader wave-energy analysis workflows, enabling CCD. 1.2 Approach/Activities: The proposed approach linearizes the equations of motion, generated by M4E, in minimal coordinates about a selected operating point and combines the resulting system with frequencydomain hydrodynamic terms to incorporate the reduced mass, damping, stiffness, and forcing operators. The linearized model is used for both impedance-based response amplitude operator (RAO) prediction and rapid regular-wave time integration. The methodology is demonstrated on a single-flap device and a FOSWEC configuration, with linearized M4E responses compared against the corresponding nonlinear M4E simulations and WEC-Sim results. Regular-wave time histories, RAO trends, and runtime differences are assessed. The framework is also compatible with broader wave-energy workflows, including coupling to WecOptTool, although that capability is not the focus of this work [3]. 1.3 Results/Lessons: The linearized M4E model reproduces key regularwave response characteristics such as integration and Response Amplitude over multiple frequencies. This module matches nonlinear M4E and WEC-Sim results while substantially reducing integration cost. Thus, the proposed framework can serve as a rapid analysis layer for articulated WEC design, parameter studies, and controls-oriented workflows. The analysis is most appropriate in the near-equilibrium regime, about the linearization point.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Bi-fated tendon-to-bone attachment cells are regulated by shared enhancers and KLF transcription factors

The mechanical challenge of attaching elastic tendons to stiff bones is solved by the formation of a unique transitional tissue. Here, we show that murine tendon-to-bone attachment cells are bi-fated, activating a mixture of chondrocyte and tenocyte transcriptomes, under regulation of shared regulatory elements and Krüppel-like factors (KLFs) transcription factors. High-throughput bulk and single-cell RNA sequencing of humeral attachment cells revealed expression of hundreds of chondrogenic and tenogenic genes, which was validated by in situ hybridization and single-molecule ISH. ATAC sequencing showed that attachment cells share accessible intergenic chromatin areas with either tenocytes or chondrocytes. Epigenomic analysis revealed enhancer signatures for most of these regions. Transgenic mouse enhancer reporter assays verified the shared activity of some of these enhancers. Finally, integrative chromatin and motif analyses and transcriptomic data implicated KLFs as regulators of attachment cells. Indeed, blocking expression of both Klf2 and Klf4 in developing limb mesenchyme impaired their differentiation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Quantifying experimental edge plasma evolution via multidimensional adaptive Gaussian process regression

The edge density and temperature of tokamak plasmas are strongly correlated with energy and particle confinement and their quantification is fundamental to understanding edge dynamics. These quantities exhibit behaviours ranging from sharp plasma gradients and fast transient phenomena (e.g. transitions between low and high confinement regimes) to nominal stationary phases. Analysis of experimental edge measurements therefore require robust fitting techniques to capture potentially stiff spatiotemporal evolution. Additionally, fusion plasma diagnostics inevitably involve measurement errors and data analysis requires a statistical framework to accurately quantify uncertainties. This paper outlines a generalized multidimensional adaptive Gaussian process routine capable of automatically handling noisy data and spatiotemporal correlations. We focus on the edge-pedestal region in order to underline advancements in quantifying time-dependent plasma profiles including transport barrier formation on the Alcator C-Mod tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Method and precision nanopositioning apparatus with compact vertical and horizontal linear nanopositioning flexure stages for implementing enhanced nanopositioning performance

An enhanced method and precision nanopositioning apparatus for implementing enhanced nanopositioning performance is provided. The nanopositioning apparatus includes a vertical linear nanopositioning flexure stage and a horizontal linear nanopositioning flexure stage. The vertical linear nanopositioning flexure stage includes a stage base, a symmetrically configured flexure linear guiding mechanism with precision motion enhancement structure, and a stage carriage. The horizontal linear nanopositioning flexure stage is mounted on the stage carriage of the vertical linear nanopositioning flexure stage, and includes a middle-bar relative position control mechanism to enhance the stiffness of a flexure linear guiding mechanism.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Progressive collapse analysis of stiffened panel structure with consideration of actual welding distortion and residual stresses

To date, inclusion of welding distortion and residual stresses in determining the strength of marine structures is based on empirical formulations due to welding complexity. In this study, a more feasible numerical model was developed from the perspective of inherent strain theory. The accuracy of this simplified numerical model was confirmed by transient thermo-elastic–plastic finite element analysis using a novel dynamic mesh refining and iterative substructure method which is 50 times faster than conventional finite element method. Welding distortion by the two numerical approaches was validated with experimental measurement. The collapse analyses indicated that the inherent strain model predicted a compressive strength and load-displacement curve with high accuracy, as validated by the transient thermo-mechanical model. The global stiffness and the ultimate strength of the welded structure would be overestimated by about 22% if no welding effects were considered. The proposed computation procedure for determining the ultimate strength of welded structures is accurate, simple, and practical and enables improvement of ultimate strength through optimization of welding joint design to reduce the welding residual stress and distortion.

Huang, Hui↗
DOE OSTI2020

Big Sky Regional Carbon Sequestration Partnership (Phase III Final Scientific/Technical Report)

The Big Sky Carbon Sequestration Partnership (BSCSP) pursued a Phase III demonstration project at Kevin Dome in north central Montana. Kevin Dome covers approximately 700 square miles and is a naturally occurring CO 2 reservoir that is flanked by oil and gas fields. The carbon dioxide (CO 2 ) is in the upper Devonian Duperow (carbonate) formation and does not reach the spill point of the dome; therefore, the dome has potential as a CO 2 sequestration reservoir, a CO 2 supply, or as both if anthropogenic sources and enhanced oil recovery (EOR) operations are associated with the dome. Kevin Dome could potentially act as a buffer to continue accepting anthropogenic CO 2 when EOR flooding operations are interrupted or completed. The project objective was to produce one million tonnes of CO 2 from the gas cap of Kevin Dome, pipe it laterally, inject, and re-store it in the brine leg of the same formation to test the hub / buffer storage concept. This was to be accomplished by drilling up to five production wells, building a short pipeline and compression facilities, and drilling an injection well and several monitoring wells. BSCSP commenced outreach and site characterization activities including acquiring baseline data for near-surface insurance monitoring, acquiring 3-dimensional, 9-component surface seismic over the project area, drilling two test wells (one in the production area and one in the injection area), coring key intervals, and performing comprehensive logging. Well tests of those wells revealed two barriers to the project. The production (Danielson 33-17) well was perforated in multiple zones but failed to produce any significant CO 2 . This was despite being drilled in the near vicinity of a historic well that had produced 3700 MCF per day in a drill stem test. Modeling indicated that this was likely due to a phase change during production causing a temperature drop resulting in hydrate and/or water ice formation that clogged the formation. Tests of the injection zone (Wallewein 22-1) well indicated total dissolved solids (TDS) slightly below the EPA required 10,000 parts per million (ppm) for a Class VI underground injection control permit. While the project was initiated before Class VI rules were promulgated, and this was an experimental project (seemingly qualified for a Class V permit), the Environmental Protection Agency (EPA) indicated that injection would require a Class VI permit. The low salinity result was unexpected as contours plotted based on regional formation water quality data indicated an expected TDS above 20,000 ppm, and wells between the recharge zone and the Wallewein well tested above 10,000 ppm. Faced with the inability to obtain an injection permit, the demonstration project could not proceed. However, the project had generated valuable samples and data on a large natural analog including 32 sq. mi. of 3-D, 9-C seismic, 430 ft. of carbonate core covering seven different depositional environments taken from areas with, and without the presence of CO 2 , 30 ft. of core of two caprocks, a tight carbonate and an anhydrite, a full set of modern logs on both wells, and well tests. DOE decided to re-scope the project around completing studies utilizing this data. This report covers both the initial scope and the re-scope (Task / Section numbers preceded with an R). While the report covers a wide range of project activities, highlights of this work include: Development of a geostatic model using neural nets to match well logs to facies and using multi-waveform seismic to inform reservoir heterogeneity; Unique mechanical testing of permeability – stress relationship in two caprock materials; Development of full waveform inversion to generate a high resolution velocity model; Model development for dual permeability (fracture and matrix) systems to better account for matrix-matrix interactions; Joint seismic wave inversion (including the first quadr-joint inversion) exhibiting better imaging of a challenging reservoir zone in stiff rock; Core flow and core flood results on a reactive carbonate; and Innovative laboratory measurements of seismic response of fractured core as a function of fluid fill.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Nonlinear controller for nonlinear wave energy converters

The present invention is directed to a nonlinear controller for nonlinear wave energy converters (WECs). As an example of the invention, a nonlinear dynamic model is developed for a geometrically right-circular cylinder WEC design for the heave-only motion, or a single degree-of-freedom (DOF). The linear stiffness term is replaced by a nonlinear cubic hardening spring term to demonstrate the performance of a nonlinear WEC as compared to an optimized linear WEC. By exploiting the nonlinear physics in the nonlinear controller, equivalent power and energy capture, as well as simplified operational performance is observed for the nonlinear cubic hardening spring controller when compared to an optimized linear controller.

Wilson, David G.↗
DOE OSTI2020

Halbach-array levitating passive magnetic bearing configuration

Novel configurations of levitating passive magnetic bearing configurations are described. Such configurations can be used for the precise control of the magnitude and sign of the bearing stiffness, thereby facilitating the overall design of the system in ways that are not possible with conventional attractive or repelling bearing elements.

Post, Richard F.↗
DOE OSTI2020

Systems and methods for micromechanical displacement-based logic circuits

The present disclosure relates to a micromechanical displacement logic, signal propagation system that makes use of first and second bistable elements, and first and second mounting structures arranged adjacent opposing surfaces of the first bistable element. A plurality of pivotal lever arms are used to support the first bistable element in either one of two positions of equilibrium. A support structure and a compressible flexure element disposed between the support structure and the first mounting structure apply a preload force to the first mounting structure, which imparts the preload force to the first bistable element. The first bistable element is moveable from one of the two stable equilibrium positions to the other in response to an initial signal applied thereto. The preload force, at least one stiffness characteristic of the lever arms, and a compressibility of a compressible coupling element which links the second bistable element to the first, are all selected to tune signal propagation from the first bistable element to the second bistable element.

Panas, Robert Matthew↗
DOE OSTI2021

Evaluation of Stripping Resistance of Organoclay-Modified Asphalt Binder and Aggregate Systems Using an Optical Contact Angle Analyzer

Organoclays, often referred to as nanoclays (NCs), are organically modified phyllosilicates. They are derived from naturally occurring clay minerals and possess unique characteristics in improving the physical and mechanical properties of polymers and rubbers. Recently, NCs have drawn interest in the modification of asphalt binders as micro-scale fillers. A few recent studies have revealed that the addition of NCs in asphalt binders improved binders’ stiffness, aging characteristics, and fatigue resistance. This study aims to evaluate the changes in moisture resistance of different NC-modified asphalt binders through the surface free energy (SFE) technique. This technique estimates SFE properties of binders and aggregates from static contact angle (SCA) data measured from an optical contact angle analyzer (OCA). Further, this study examines the changes in chemical compositions (functional groups) of binders due to the addition of selected NCs by using the Fourier Transformation Infrared (FTIR) technique. To this end, a commonly used performance grade (PG) binder (PG 64-22) modified with four different types (shape and size) of NCs, namely, Cloisite® 15 (C-15), Cloisite® 20 (C-20), Cloisite® Na+ (C-Na), and Cloisite® Ca++ (C-Ca) were evaluated in this study. The SFE data of five different types of aggregates from Oklahoma, namely, Davis Limestone (DL), Snyder Granite (SG), Dolese-Cooperton Limestone (DCL), Hanson-Davis Rhyolite (HDR), and Martin-Marietta-Mill-Creek Granite (MMMG), were used to perform their compatibility with the aforementioned NC-modified binders. The FTIR spectra revealed the presence of various alcohols, ethers, and esters in NC-modified asphalt binders. The moisture susceptibility analysis shows that the addition of NC results in an increase of SFE and cohesive energy of an asphalt binder, which are desired for improved moisture resistance. The addition of NC also shows improved compatibility in cases of all aggregates. Among the five aggregates, MMMCG showed the highest compatibility with all binders, followed by DCL, HDR, DL, and SG. In regard to NCs, the C-15 sample showed the highest compatibility followed by C-20, C-Na, and C-Ca.

Hossain, Zahid↗
DOE OSTI2021

Air-buoyant structures and vehicles

Air-buoyant structures, and vehicles incorporating air-buoyant structures, are provided. Hollow, air-buoyant structures may include a shell of ultra-low density aerogel material, foam material, or vapor-expanded material that is strong and stiff enough to withstand atmospheric pressure and lightweight enough to achieve buoyancy in air under evacuation. The shell may be reinforced with a suitable reinforcing material, such as helical nanofibers. The air-buoyant structures may also include vacuum pumps and valves operably connected to or integrated with the hollow shell. The vacuum pumps and valves may be configured to pump air out of the hollow shell and allow air back into the hollow shell to control buoyancy.

Beaux, II, Miles Frank↗
DOE OSTI2021

Anisotropic inelastic materials milestone 2021

The focus on new fuel and cladding models are drivers for several new capabilities at the MOOSE and BISON levels. Since these materials are anisotropic, they require an extension of our inelastic mechanics capabilities, which currently heavily rely on radial return mapping and the assumption of isotropic stiffness. We plan to add additional code paths to support fully anisotropic materials, without degrading the performance for modeling isotropic materials.

42 ENGINEERING↗
DOE OSTI2021

Additive Manufacturing Case Study

Geothermal technologies include an extremely wide range of products required for well construction, completion, production, intervention and surface energy conversion activities. Many of these products are geometrically complex, require multi-step and highly specialized fabrication processes, and are expensive due to the low production numbers typically associated with the geothermal market. These challenges along with the high temperature demands of the geothermal environment have also hindered the adoption of many tools routinely used in the oil & gas industry.Recent advancements in Additive Manufacturing (AM) materials of construction, build volumes and part quality have transitioned the technology from primarily cosmetic prototyping applications to the point where AM can be used to make production parts, even for the most demanding applications. These improved AM capabilities along with the inherent ability of AM to produce complex parts and, in some cases, geometries that cannot be manufactured using conventional casting, machining and joining fabrication approaches motivate an exploration of its potential to positively impact geothermal well construction and operations technologies.Sandia National Labs collaborated with Oak Ridge National Laboratory on a case study examining additive manufacturing opportunities for Geothermal applications. The study focused on designing components with improved performance characteristics that cannot be fabricated conventionally. A rotor for a downhole motor was chosen based on the potential for improving its rotational dynamics. Topology optimization was used as a design method to reduce the rotational inertia of the part while preserving sufficient rotational stiffness to transmit the torque required for the drilling application. The optimization resulted in a nearly 50% reduction in polar moment of inertia while maintaining other desired performance characteristics. The design developed using the topology optimization approach was fabricated using additive manufacturing and cannot be fabricated conventionally. This paper will discuss the design approach, performance improvements and manufacturing methods used to produce the part.

Polsky, Yarom↗
DOE OSTI2021

Confronting Domain Shift in Trained Neural Networks

Neural networks (NNs) are known as universal function approximators and can interpolate nonlinear functions between observed data points. However, when the target domain for deployment shifts from the training domain and NNs must extrapolate, the results are notoriously poor. Prior work Martinez et al. (2019) has shown that NN uncertainty estimates can be used to correct binary predictions in shifted domains without retraining the model. We hypothesize that this approach can be extended to correct real-valued time series predictions. As an exemplar, we consider two mechanical systems with nonlinear dynamics. The first system consists of a spring-mass system where the stiffness changes abruptly, and the second is a real experimental system with a frictional joint that is an open challenge for structural dynamicists to model efficiently. Our experiments will test whether 1) NN uncertainty estimates can identify when the input domain has shifted from the training domain and 2) whether the information used to calculate uncertainty estimates can be used to correct the NN’s time series predictions. While the method as proposed did not significantly improve predictions, our results did show potential for modifications that could improve models’ predictions and play a role in structural health monitoring systems that directly impact public safety.

97 MATHEMATICS AND COMPUTING↗