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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 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Coupled Thermoelasticity Problem for Multilayer Composite Shells of Revolution. II. Applied Problems

We deduce a system of nonclassical nonlinear differential equations of coupled thermoelasticity for multilayer composite anisotropic shells of revolution in a coordinate system connected with the lines of curvature of the reference surface. The constructed nonclassical model of deformation of a multilayer shell and the nonlinear model of distribution of heat fluxes over the thickness of the shell enable us to take into account the transverse shear strains and guarantee the validity of the conditions of thermal and mechanical conjugation of the layers and the conditions of thermomechanical loading on the faces of the shell. We deduce the linearized differential equations of the axisymmetric coupled problem of thermoelasticity for a conic reinforced multilayer shell and solve the quasistatic problem of thermoelasticity for a two-layer cylindrical shell cross-reinforced in the direction of helical lines. By using the structural approach to the formulation of the criteria of strength for composite materials, we determine the loads of the onset of fracture of the binder and reinforcing elements of a two-layer metal-composite cylindrical shell.

42 ENGINEERING↗
DOE OSTI2018

Workability Limits of Magnesium Alloy AZ31B Subjected to Equal Channel Angular Pressing

Equal channel angular pressing (ECAP) is an important severe plastic deformation process to produce ultrafine grained microstructures in metals and alloys. Magnesium and its alloys generally possess poor workability at temperatures below 250 °C. This investigation examines the influence of different passes and processing routes of ECAP on improving the workability of Mg alloy AZ31B. ECAP was carried out for three passes using a die of angle 120° using processing routes Bc and C. The operating temperature was 523 K for the first pass and 423 K for the subsequent two passes. The resultant microstructure and mechanical properties were determined. Workability of the alloy at 423 K (150 °C) was determined using upsetting experiments on cylindrical specimens machined from the annealed and ECAPed samples. Workability limit diagrams have been constructed for the various processed conditions. The workability data generated were also analyzed using five different workability criteria (also referred to as ductile fracture models) and the material constants for these five models were evaluated. Specimens processed by two passes through route C (pass 2C) exhibits better workability compared to other passes since the workability limit line after this pass shows maximum safe working area and lies above the other workability lines. Among the five different workability criteria investigated, the Freudenthal workability criterion is more suitable for prediction of failure in this alloy.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Mechanisms of degradation in adhesive joint strength: Glassy polymer thermoset bond in a humid environment

The degradation in the strength of napkin-ring (NR) joints bonded with an epoxy thermoset is evaluated in a humid environment. While adherend composition (stainless steel and aluminum) and surface preparation (polished, grit blasted, primed, coupling agent coated) do not affect virgin (time=0) joint strength, they can significantly affect the role of moisture on the strength of the joint. Adherend surface abrasion and corrosion processes are found to be key factors in determining the reliability of joint strength in humid environments. In cases where surface specific joint strength degradation processes are not active, decreases in joint strength can be accounted for by the glass transition temperature, T g , depression of the adhesive associated with water sorption. Under these conditions, joint strength can be rejuvenated to virgin strength by drying. In addition, the decrease in joint strength associated with water sorption can be predicted by the Simplified Potential Energy Clock (SPEC) model by shifting the adhesive reference temperature, T ref , by the same amount as the T g depression. When surface specific degradation mechanisms are active, they can reduce joint strength below that associated with adhesive T g depression, and joint strength is not recoverable by drying. Furthermore, a critical relative humidity (or, potentially, critical water sorption concentration), below which the surface specific degradation does not occur, appears to exist for the polished stainless steel joints.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Phase stability, mechanical properties, and ion irradiation effects in face-centered cubic CrFeMnNi compositionally complex solid-solution alloys at high temperatures

We report two CrFeMnNi face-centered cubic complex concentrated solid-solution alloys (CSA) have been evaluated for phase stability, mechanical properties, and radiation damage effects from heavy ions. Cr 18 Fe 27 Mn 27 Ni 28 and Cr 15 Fe 35 Mn 15 Ni 35 were predicted by thermodynamic calculations to phase separate and maintain a single phase at 700 °C, respectively. Aging experiments at this temperature confirmed varying degrees of precipitation of a body-centered cubic phase in both Cr 18 Fe 27 Mn 27 Ni 28 and Cr 15 Fe 35 Mn 15 Ni 35 . The alloys showed promising strength in tensile deformation at room temperature, with yield strengths of 155 MPa and 151 MPa for Cr 18 Fe 27 Mn 27 Ni 28 and Cr 15 Fe3 5 Mn 15 Ni 35 , respectively. At 500 °C, the yield strength of Cr 18 Fe 27 Mn 27 Ni 28 fell to 93 MPa, and to 100 MPa in Cr 15 Fe3 5 Mn 15 Ni 35 . Unlike Cr 18 Fe 27 Mn 27 Ni 28 , Cr 15 Fe 35 Mn 15 Ni 35 gained some ductility at 500 °C compared to room temperature. The two CSAs were irradiated to 75 dpa at 500 °C in the plateau region of the displacement curve using 3.7 MeV Ni 2+ ions, alongside model alloy 709 as a reference. Irradiation results produced similar densities and sizes of dislocations loops in the two CSAs compared to the reference. However, while large voids form in the plateau region of Cr 18 Fe 27 Mn 27 Ni 28 , small voids form just beyond the displacement peak of Cr 15 Fe 35 Mn 15 Ni 35 . Atom probe tomography and energy dispersive X-ray spectroscopy-equipped scanning transmission electron microscopes were used to characterize the alloys for changes in chemical distribution.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Impact of pairing and neutron-excess on suppression of the above-barrier fusion cross-section in 19 O + 12 C

Fusion excitation functions for 19 O and 19 F + 12 C were simultaneously measured along with 20 O + 12 C using the active-target detector MuSIC@Indiana. Examination of the cross-section just above the barrier reveals a significant suppression of fusion for the 19 O + 12 C system starting at E 12 MeV. This suppression is not simply due to the reduced binding of the unpaired neutron in 19 O as 17 O + 12 C does not exhibit the same sharp suppression of the fusion cross-section. Multiple mean-field models are used as a reference to understand the measured fusion excitation functions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Nano-crystallization induced by high-energy heavy ion irradiation in UO 2

Here, advanced microstructure investigations of the high-burnup structure (HBS) in UO 2 produced by high-dose 84 MeV Xe ion irradiation are reported. Spark plasma sintered micro-grained UO 2 was irradiated to 1357 dpa at 350 degrees C. The characteristic nano-grains and micro-pores of the HBS were formed. The grain size and grain boundary misorientation distributions of the HBS were measured using transmission electron microscopy based orientation imaging microscopy. Grain polygonization due to accumulation of radiation-induced dislocations was found to be the mechanism of nano-crystallization. The morphology of Xe bubbles was quantitatively investigated. Finally, this study provides crucial references for advanced fuel performance modeling of high-burnup UO 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2021

Sensitivity of Carbonaceous Aerosol Properties to the Implementation of a Dynamic Aging Parameterization in the Regional Climate Model RegCM

Freshly emitted soot is hydrophobic, but condensation of secondary aerosols and coagulation with other particles modify its hygroscopic optical properties. This conversion is referred to as “aerosol aging.” Many climate models represent this aging process with a fixed aging time scale, whereas in reality, it is a dynamic process that depends on environmental conditions. Here, we implement a dynamic aging parameterization scheme in the regional climate model RegCM4 in place of the fixed aging timescale of 1.15 days (~27.6 h) and examine its impact on the aerosol life cycle over the Indian subcontinent. The conversion from hydrophobic to hydrophilic aerosol is usually lower than 27.6 h over the entire landmass and lower than 10 h over the polluted Indo-Gangetic Basin (IGB), with seasonal variability. Due to the implementation of the dynamic aging scheme, the column burden and surface mass concentration of carbonaceous aerosols increase during the drier season (December–February) when washout is negligible. The burden is reduced during the wet season (June–September) due to a more efficient washout except over the IGB, where a reduction in precipitation as a result of radiative feedbacks increases the aerosol concentrations. Over the polluted IGB, surface dimming increases due to the dynamic aging scheme, with the top of the atmosphere forcing remaining mostly unchanged. As a result, atmospheric heating increases by at least 1.2 W/m 2 . Our results suggest that climate models should incorporate dynamic aging for a more realistic representation of aerosol simulations, especially in highly polluted regions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Confronting Large‐Eddy Simulations With Stereo Camera Data by Means of Reconstructed Hemispheric Cloud Size Distributions

High-resolution hemispheric camera images at a meteorological site in western Germany are used to analyze the multi-dimensional spatial characteristics of continental cumulus cloud fields, and to evaluate Large-Eddy Simulations on this aspect. Traditional non-hemispheric cloud-detecting instruments provide additional reference data. The main model-observation comparison focuses on cloud size distributions (CSDs), employing two methods: (a) directly using three-dimensional model fields, direct CSDs, and (b) using rendered hemispheric images of the model fields as produced by a camera simulator based on path-tracing. In the latter method, both the real and rendered images are used to three-dimensionally reconstruct the cloud fields, yielding hemispheric CSDs. Advantages of hemispheric comparisons over more classic approaches include (a) fair comparisons between model and data, and (b) full use of the enhanced resolutions and hemispheric spatial coverage of the camera imagery. Basic evaluation of the simulations demonstrates good agreement on thermodynamic structure and its diurnal cycle. Cloud heights and cloud cover are intercompared between the model, camera data and other instrumentation, providing insight into their structural differences. A consistent alignment is found between the hemispheric CSDs from both the model and the cameras. Power law fits reveal structurally lower exponents in hemispheric CSDs compared to non-hemispheric CSDs, which particularly caution against directly comparing hemispheric CSDs to non-hemispheric distributions. This result is robust for sample size and fitting method. These findings inform future use of hemispheric camera systems for studying cumulus cloud field morphology and model evaluation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Application-specific machine-learned interatomic potentials: exploring the trade-off between DFT convergence, MLIP expressivity, and computational cost

Machine-learned interatomic potentials (MLIPs) are revolutionizing computational materials science and chemistry by offering an efficient alternative to ab initio molecular dynamics (MD) simulations. However, fitting high-quality MLIPs remains a challenging, time-consuming, and computationally intensive task where numerous trade-offs have to be considered, e.g., How much and what kind of atomic configurations should be included in the training set? Which level of ab initio convergence should be used to generate the training set? Which loss function should be used for fitting the MLIP? Which machine learning architecture should be used to train the MLIP? The answers to these questions significantly impact both the computational cost of MLIP training and the accuracy and computational cost of subsequent MLIP MD simulations. In this study, we use a configurationally diverse beryllium dataset and quadratic spectral neighbor analysis potential. We demonstrate that joint optimization of energy versus force weights, training set selection strategies, and convergence settings of the ab initio reference simulations, as well as model complexity can lead to a significant reduction in the overall computational cost associated with training and evaluating MLIPs. This opens the door to computationally efficient generation of high-quality MLIPs for a range of applications which demand different accuracy versus training and evaluation cost trade-offs.

36 MATERIALS SCIENCE↗
DOE OSTI2014

On the robust optimization to the uncertain vaccination strategy problem

In order to prevent an epidemic of infectious diseases, the vaccination coverage needs to be minimized and also the basic reproduction number needs to be maintained below 1. This means that as we get the vaccination coverage as minimum as possible, thus we need to prevent the epidemic to a small number of people who already get infected. In this paper, we discuss the case of vaccination strategy in term of minimizing vaccination coverage, when the basic reproduction number is assumed as an uncertain parameter that lies between 0 and 1. We refer to the linear optimization model for vaccination strategy that propose by Becker and Starrzak (see [2]). Assuming that there is parameter uncertainty involved, we can see Tanner et al (see [9]) who propose the optimal solution of the problem using stochastic programming. In this paper we discuss an alternative way of optimizing the uncertain vaccination strategy using Robust Optimization (see [3]). In this approach we assume that the parameter uncertainty lies within an ellipsoidal uncertainty set such that we can claim that the obtained result will be achieved in a polynomial time algorithm (as it is guaranteed by the RO methodology). The robust counterpart model is presented.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

The impact of seasonality on multi-scale feature extraction techniques

A key component in constructing a broad-scale, gridded population dataset is fine resolution geospatial data accurately depicting the extent of human activity. Analogous datasets are often developed using a wide range of methods and classification techniques, including the use of spatial features, spectral features, or the coupling of both to identify the presence of man-made structures from high-resolution satellite imagery. By using spatial and textural-based descriptors to generate high-resolution settlement layers for two dissimilar regions at the peak of seasonal disparity, this study attempts to quantify the influence of seasonality on the accuracy of a supervised, multi-scale, feature extraction framework for automated delineation of human settlement. Results generated by numerous models are evaluated against a reference dataset allowing for assessment of seasonal and feature differences in the context of accuracy. Global or regional mapping of human settlement requires the assemblage of high-resolution satellite images with variegated acquisition characteristics (season, sun elevation, off-nadir, etc.) to produce a cloud-free composite image from which features are extracted. Results of this study suggest an emphasis on imagery criteria, in particular acquisition date, could improve classification accuracy when mapping human settlement at scale.

58 GEOSCIENCES↗
DOE OSTI2020

Urbanization drives convergence in soil profile texture and carbon content

Urban development has driven extensive modification of the global landscape. This shift in land use and land cover alters ecological functioning, and thereby affects sustainable management agendas. Urbanization fundamentally reshapes the soils that underlay landscapes, and throughout the soil profile, extends impacts of urbanization far below the landscape surface. The impacts of urbanization on deeper soils that are beyond the reach of regular land management are largely unknown, and validation of general theories of convergent ecosystem properties are thwarted by a dearth of both level of measurement effort and the substantial heterogeneity in soils and urban landscapes. Here, we examined two soil properties with strong links to ecological functioning—carbon and mineral-fraction particle size—measured in urban soils, and compared them to their pre-urbanization conditions across a continental gradient encompassing global soil diversity. We hypothesized that urbanization drove convergence of soils properties from heterogeneous pre-urban conditions towards homogeneous urban conditions. Based on our observations, we confirm the hypothesis. Both soil carbon and particle size converged toward an intermediate value in the full data distribution, from pre-urban to urban conditions. These outcomes in urban soils were observed to uniformly be fine textured soils with overall lower carbon content. Although these properties are desirable for supporting urban infrastructure (e.g. buildings, pipes), they constrain the potential to render ecosystem services. Since soil profile texture and carbon content were convergent and observed across 11 cities, we suggest that these property profiles can be used as a universal urban soil profile to: 1) provide a clear prediction for how urbanization will shift soil properties from pre-urban conditions, 2) facilitate the adoption of commonly-accepted soil profiles for process models, and 3) offer a reference point to test against urban management strategies and how they impact soil resources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Transforming Science Through Software: Improving While Delivering 100×

The U.S. Department of Energy (DOE) Exascale Computing Project (ECP) funded the development of new (and the transformation of important existing) applications, libraries, and tools that realized improvement in performance and capabilities of often 100 times or more on emerging exascale computers. This exceptional gain inspired the title of this special issue: Transforming Science through Software: Improving while delivering 100X. The term 100X refers to advancing capabilities in modeling, simulation, and analysis by a factor of 100 or more using some combination of new algorithms, optimization techniques, software libraries, and programming models, coupled with the next generation of hardware for high-performance computing (HPC). The papers in this issue share experiences with the practice and science of scientific software development, with an emphasis on developing a coherent, portable, and sustainable HPC software ecosystem for next-generation computational science. Finally, we hope to foster expanded community efforts related to the fundamental role of sustainable scientific software ecosystems in advancing the computing sciences.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Utility-Scale Lithium-Ion Storage Cost Projections for Use in Capacity Expansion Models

This work presents U.S. utility-scale battery storage cost projections for use in capacity expansion models. We create battery cost projections based on a survey of literature cost projections of battery packs and balance of system costs, with a focus on lithium-ion batteries. Low, mid, and high cost trajectories are created for the overnight capital costs and the operating and maintenance costs. We then demonstrate the impact of these cost projections in the Regional Energy Deployment System (ReEDS) capacity expansion model. We find that under reference scenario conditions, lower battery costs can lead to increased penetration of variable renewable energy, with solar photovoltaics (PV) seeing the largest increase. We also find that additional storage can reduce renewable energy curtailment, although that comes at the expense of additional storage losses.

25 ENERGY STORAGE↗
DOE OSTI2026

Binary pseudo-random array standard for extreme ultraviolet lithography tool characterization

Extreme ultraviolet (EUV) imaging tools play a crucial role in EUV lithography. Achieving high accuracy in EUV metrology is essential for advanced semiconductor manufacturing. A thorough characterization of the instrumentation in use is required. Binary pseudo-random arrays (BPRAs) are an established standard for calibrating and characterizing optical instruments in the frequency domain. Here, we expand the BPRA standard to applications in EUV imaging. To extend the technology to the EUV spectral range, a high-resolution BPRA target with the smallest feature size of 40 nm is developed. The EUV BPRA target establishes an in situ and portable calibration and alignment standard for EUV imaging. The target is patterned by means of electron-beam lithography, using a nickel absorber with a thickness of 39 nm. The substrate is a 4″ silicon wafer with a molybdenum/silicon multilayer coating. To demonstrate the efficacy of the target and develop the instrument calibration protocol, the target is imaged on the Sharp Hyper-NA Actinic Reticle Review Project EUV mask microscope. Power spectral density (PSD) data are presented. The characteristics of the imaging system are imprinted on the PSD. The modulation transfer function is extracted from the PSD data. A partially coherent imaging model is used as a reference to the experimental results.

BPRA↗
DOE OSTI2014

SU-E-T-523: On the Radiobiological Impact of Lateral Scatter in Proton Beams

Introduction: In proton therapy, justified concern has been voiced with respect to an increased efficiency in cell kill at the distal end of the Bragg peak. This coupled with range uncertainty is a counter indication to use the Bragg peak to define the border of a treated volume with a critical organ. An alternative is to use the lateral edge of the proton beam, obtaining more robust plans. We investigate the spectral and biological effects of the lateral scatter . Methods: A general purpose Monte Carlo simulation engine (MCNPX 2.7c) installed on a Scientific Linux cluster, calculated the dose deposition spectrum of protons, knock on electrons and generated neutrons for a proton beam with maximal kinetic energy of 200MeV. Around the beam at different positions in the beam direction the spectrum is calculated in concentric rings of thickness 1cm. The deposited dose is converted to a double strand break map using an analytical expression.based on micro dosimetric calculations using a phenomenological Monte Carlo code (MCDS). A strict version of RBE is defined as the ratio of generation of double strand breaks in the different modalities. To generate the reference a Varian linac was modelled in MCNPX and the generated electron dose deposition spectrum was used . Results: On a pristine point source 200MeV beam the RBE before the Bragg peak was of the order of 1.1, increasing to 1.7 right behind the Bragg peak. When using a physically more realistic beam of 10cm diameter the effect was smaller. Both the lateral dose and RBE increased with increasing beam depth, generating a dose deposition with mixed biological effect. Conclusions: The dose deposition in proton beams need to be carefully examined because the biological effect will be different depending on the treatment geometry. Deeply penetrating proton beams generate more biologically effective lateral scatter.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2014

The general low-frequency prediction for asymptotically nonlinear material functions in oscillatory shear

We use a fourth-order fluid expansion to make general predictions for asymptotically nonlinear material functions in oscillatory shear, a characterization protocol sometimes known as medium-amplitude oscillatory shear. The calculation applies to any viscoelastic fluid in the terminal regime defined by the limit of Deborah number much less than one. Two viscous nonlinearities appear at third order, with shear stress scaling as ω 3 , and are interrelated by a constant multiplicative factor. Two elastic nonlinearities appear at fourth order, with shear stress scaling as ω 4 , and are also interrelated by a constant multiplicative factor. These nonlinear measures are decoupled from the linear material functions G' and G" because they depend on different expansion coefficients. Experimental measurements are presented for all four asymptotic shear material functions using a linear and well-entangled homopolymer of polyisoprene. Here, the experimental observations are consistent with both the predicted frequency scaling and the predicted interrelations in the terminal regime. Signs and magnitudes cannot be universally predicted, leaving these as free parameters that depend on the specifics of the material microstructure or constitutive model. These general results explain previous observations involving different materials and constitutive models, and provide an important reference for future experiments, analytical results, and numerical computations of these rheological fingerprints.

42 ENGINEERING↗
DOE OSTI2024

Hyperparameter Studies for Vision Transformers Trained on High-Fidelity Simulations

This library is a collection of python modules that define, train, and analyze vision-transformer (ViT) machine learning models. The code implements, with mild modifications, ViT models that have been made publicly available through publication and GitHub code. The training data for these models is hydrodynamic simulation output in the form of numpy arrays. This library contains code to train these ViT models on the hydrodynamic simulation output with a variety of hyperparameters, and to compare the results of such models. Furthermore, the library contains definitions of simple convolutional neural network (CNN) machine learning architectures which can be trained on the same hydrodynamic simulation output. These are included as a reference point to compare the ViT models to. Additionally, the library includes trained ViT and CNN models and example input data for demonstration purposes. The code is based on the PyTorch python library.

Callis, Skylar↗