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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

AutoSIM

AutoSIM enables several instances of an executable to run in parallel on a directory of input files and consolidate results, at scale on the world's fastest supercomputers. The software accomplishes this by balancing compression, transmission, and computation of input files, executables, and output files to allow scalable parallel runs of any executable. The software breaks-up simulations into a configurable number of "churns" or sequential instances of executable invocations on a configurable number of cores/node. It sends the executable, supporting files, and appropriate number of input files to each node for independent execution, and then transfers the executable results to a shared disk for post-processing analysis. This MPI-based code has been demonstrated using EnergyPlus, DOE's flagship whole-building simulation engine, but was architected to allow scalable runtime of any software for any application (e.g. sensitivity analysis and uncertainty quantification). The code has also been demonstrated to scale on the Titan supercomputer using 131,072 processors to run 524,288 EnergyPlus annual simulations, and write 45TB of data to disk in 68 mins 08 secs.

New, Joshua R↗
DOE OSTI2026

Scientific Discovery with Physics-Informed System Identification (Abbreviated Report)

My fellowship research focused on making physics-based simulations faster and more useful through machine learning. Many problems in science and engineering are governed by partial differential equations, but high-fidelity simulations are often too expensive to run repeatedly. I worked on improving Latent Space Dynamics Identification (LaSDI), a reduced-order modeling framework that compresses large simulation data sets into a smaller representation and then learns how that representation evolves over time. The motivation was to develop reduced models that remain accurate for more challenging systems, especially when predictions must remain reliable over long time intervals or when the underlying dynamics are more complicated than standard methods can easily handle. I also contributed to related work on Quandary, a high-performance software effort for simulation and control of open quantum systems, before focusing primarily on Latent Space Dynamics Identification methods. The main outcomes of the fellowship were two new algorithms (both of which were published), Rollout-LaSDI and Higher-Order LaSDI, together with supporting work on multi-stage Latent Space Dynamics Identification. Rollout-LaSDI improved long-term prediction by training the model to stay accurate over extended time horizons, and Higher-Order LaSDI broadened the method so it could model systems with higher-order time dynamics. My contributions to multistage Latent Space Dynamics Identification also helped show that its later training stages could be simplified without losing effectiveness, and that this behavior held across different model architectures and training strategies. Taken together, these advances improved the accuracy, flexibility, and practical value of reduced-order modeling tools for computational science.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Accuracy of Length of Virtual Stents in Treatment of Intracranial Wide-Necked Aneurysms

Background and Purpose: Precise stent deployment is important for successful treatment of intracranial aneurysms by stent-assisted coiling (SAC). We evaluated the accuracy of virtual stents generated using commercial stent planning software by comparing the length of virtual and actually deployed intracranial laser cut stents on three-dimensional digital subtraction angiography (3D-DSA) images. Methods: We retrospectively analyzed the data of 75 consecutive cases of intracranial wide-necked aneurysms treated with the SAC technique using laser cut stents. Based on 3D-DSA images acquired by C-arm CT, stent sizing and placement were intraoperatively simulated by a commercial software application. The difference in length of the stents was estimated by measuring proximal discrepancies between the end points of the virtual and actually deployed stents on fused pre-procedural and post-procedural 3D-DSA images. Discrepancies between distal stent end points were manually minimized. The Kruskal–Wallis test was applied to test whether stent location, type, and length had an effect on difference in length between virtual and real stent. Results: The median difference in length between virtual and real stents was 1.58 mm with interquartile range 1.12–2.12 mm. There was no evidence for an effect of stent location (p = 0.23), stent type (p = 0.33), or stent length (p = 0.53) on difference in length between virtual and real stents. Conclusions: Stent planning software allows 3D simulation of laser cut stents overlain on 3D-DSA images of vessels and may thus be useful for stent selection and deployment of laser cut stents during stent-assisted coiling of intracranial aneurysms.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

The Earth Model Column Collaboratory (EMC 2 ) v1.1: an open-source ground-based lidar and radar instrument simulator and subcolumn generator for large-scale models

Abstract. Climate models are essential for our comprehensive understanding of Earth's atmosphere and can provide critical insights on future changes decades ahead. Because of these critical roles, today's climate models are continuously being developed and evaluated using constraining observations and measurements obtained by satellites, airborne, and ground-based instruments. Instrument simulators can provide a bridge between the measured or retrieved quantities and their sampling in models and field observations while considering instrument sensitivity limitations. Here we present the Earth Model Column Collaboratory (EMC2), an open-source ground-based lidar and radar instrument simulator and subcolumn generator, specifically designed for large-scale models, in particular climate models, but also applicable to high-resolution model output. EMC2 provides a flexible framework enabling direct comparison of model output with ground-based observations, including generation of subcolumns that may statistically represent finer model spatial resolutions. In addition, EMC2 emulates ground-based (and air- or space-borne) measurements while remaining faithful to large-scale models' physical assumptions implemented in their cloud or radiation schemes. The simulator uses either single particle or bulk particle size distribution lookup tables, depending on the selected scheme approach, to perform the forward calculations. To facilitate model evaluation, EMC2 also includes three hydrometeor classification methods, namely, radar- and sounding-based cloud and precipitation detection and classification, lidar-based phase classification, and a Cloud Feedback Model Intercomparison Project Observational Simulator Package (COSP) lidar simulator emulator. The software is written in Python, is easy to use, and can be straightforwardly customized for different models, radars, and lidars. Following the description of the logic, functionality, features, and software structure of EMC2, we present a case study of highly supercooled mixed-phase cloud based on measurements from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE). We compare observations with the application of EMC2 to outputs from four configurations of the NASA Goddard Institute for Space Studies (GISS) climate model (ModelE3) in single-column model (SCM) mode and from a large-eddy simulation (LES) model. We show that two of the four ModelE3 configurations can form and maintain highly supercooled precipitating cloud for several hours, consistent with observations and LES. While our focus is on one of these ModelE3 configurations, which performed slightly better in this case study, both of these configurations and the LES results post-processed with EMC2 generally provide reasonable agreement with observed lidar and radar variables. As briefly demonstrated here, EMC2 can provide a lightweight and flexible framework for comparing the results of both large-scale and high-resolution models directly with observations, with relatively little overhead and multiple options for achieving consistency with model microphysical or radiation scheme physics.

58 GEOSCIENCES↗
DOE OSTI2012

Simulation of catalytic oxidation and selective catalytic NOx reduction in lean-exhaust hybrid vehicles

We utilize physically-based models for diesel exhaust catalytic oxidation and urea-based selective catalytic NOx reduction to study their impact on drive cycle performance of hypothetical light-duty diesel powered hybrid vehicles. The models have been implemented as highly flexible SIMULINK block modules that can be used to study multiple engine-aftertreatment system configurations. The parameters of the NOx reduction model have been adjusted to reflect the characteristics of Cu-zeolite catalysts, which are of widespread current interest. We demonstrate application of these models using the Powertrain System Analysis Toolkit (PSAT) software for vehicle simulations, along with a previously published methodology that accounts for emissions and temperature transients in the engine exhaust. Our results illustrate the potential impact of DOC and SCR interactions for lean hybrid electric and plug-in hybrid electric vehicles.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Modeling variability in porescale multiphase flow experiments

Microfluidic devices and porescale numerical models are commonly used to study multiphase flow in biological, geological, and engineered porous materials. In this work, we perform a set of drainage and imbibition experiments in six identical microfluidic cells to study the reproducibility of multiphase flow experiments. We observe significant variations in the experimental results, which are smaller during the drainage stage and larger during the imbibition stage. We demonstrate that these variations are due to sub-porescale geometry differences in microcells (because of manufacturing defects) and variations in the boundary condition (i.e.,fluctuations in the injection rate inherent to syringe pumps). Computational simulations are conducted using commercial software STAR-CCM+, both with constant and randomly varying injection rate. Stochastic simulations are able to capture variability in the experiments associated with the varying pump injection rate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Feasibility study for measurement of insulation compaction in the cryogenic rocket fuel storage tanks at Kennedy Space Center by fast/thermal neutron techniques

The liquid hydrogen and oxygen cryogenic storage tanks at John F. Kennedy Space Center (KSC) use expanded perlite as thermal insulation. Some of the perlite may have compacted over time, compromising the thermal performance and also the structural integrity of the tanks. Neutrons can readily penetrate through the 1.75 cm outer steel shell and through the entire 120 cm thick perlite zone. Neutrons interactions with materials produce characteristic gamma rays which are then detected. In compacted perlite the count rates in the individual peaks in the gamma ray spectrum will increase. Portable neutron generators can produce neutron simultaneous fluxes in two energy ranges: fast (14 MeV) and thermal (25 meV). Fast neutrons produce gamma rays by inelastic scattering which is sensitive to Si, Al, Fe and O. Thermal neutrons produce gamma rays by radiative capture in prompt gamma neutron activation (PGNA), which is sensitive to Si, Al, Na, K and H among others. The results of computer simulations using the software MCNP and measurements on a test article suggest that the most promising approach would be to operate the system in time-of-flight mode by pulsing the neutron generator and observing the subsequent die away curve in the PGNA signal.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Surface plasmon resonance phenomenon of the insulating state polyaniline

Surface Plasmon Resonance (SPR) phenomenon of the insulating polyaniline (PANI) is has been observed. Surface Plasmon (SP) is the traveled electromagnetic wave that passes through the interface of dielectric metal and excited by attenuated total reflection (ATR) method in Kretschmannn configuration (Au-PANI prism). The resonance condition is observed through the angle of SPR in such condition that SP wave is coupled by the evanescent constant of laser beam. In this research, the laser beam was generated by He–Ne and its wavelength (λ) was 632,8 nm. SPR curve is obtained through observation of incidence angles of the laser beam in prism. SPR phenomenon at the boundary between Au – PANI layer has showed by reflection dip when the laser beam passes through the prism. In this early study, the observation was carried out through simulation Winspall 3.02 software and preliminary compared with some experimental data reported in other referred literatures. The results shows that the optimum layer of Au and polyaniline are 50 and 1,5 nm thick respectively. Our own near future experimental work would be further performed and reported elsewhere.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

pvlib python: 2023 project update

pvlib python is a community-developed, open-source software toolbox for simulating the performance of solar photovoltaic (PV) energy components and systems. It provides reference implementations of over 100 empirical and physics-based models from the peer-reviewed scientific literature, including solar position algorithms, irradiance models, thermal models, and PV electrical models. In addition to individual low-level model implementations, pvlib python provides high-level workflows that chain these models together like building blocks to form complete “weather-to-power” photovoltaic system models. It also provides functions to fetch and import a wide variety of weather datasets useful for PV modeling. pvlib python has been developed since 2013 and follows modern best practices for open-source python software, with comprehensive automated testing, standards-based packaging, and semantic versioning. Its source code is developed openly on GitHub and releases are distributed via the Python Package Index (PyPI) and the conda-forge repository. pvlib python’s source code is made freely available under the permissive BSD-3 license. Here we (the project’s core developers) present an update on pvlib python, describing capability and community development since our 2018 publication (Holmgren, Hansen, & Mikofski, 2018).

14 SOLAR ENERGY↗
DOE OSTI2023

Quarknet Project: Simulating Double-Source Plane Lenses and Einstein Rings for Domain Adaptation

Double-Source Plane Lenses (DSPLs) are a form of strong gravitational lensing that can be used to uniquely constrain cosmological parameters like the dark energy equation of state. These objects are exceedingly rare: to date, only four have been discovered in astronomical surveys, like the Sloan Digital Sky Survey and the HyperSuprimeCam Survey. Additionally, the main features of these objects are typically co-located sets of arcs, which look like Einstein Rings of single-source galaxy-galaxy lenses. Larger astronomical surveys typically have low image resolution, which significantly exacerbates issues when trying to find DSPLs. Future surveys are likely to include many more of these objects and have higher image resolution. Traditional methods for finding strong lenses struggle to identify simple galaxy-galaxy lenses. Recently, neural networks have become the standard for lens identification, but these tools have not yet been used to search for DSPLs. In this work, we use the software deeplenstronomy to simulate varied images of DSPLs and Einstein Rings – with and without noise and artifacts of observational surveys, forming a comprehensive benchmark dataset of 40,000 images. We utilise this dataset to perform experiments with convolutional neural networks to discern between the two phenomena. Sofia Grimm and Jerry Zhou are co-first authors on this work.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

SU-E-QI-03: Compartment Modeling of Dynamic Brain PET - The Effect of Scatter and Random Corrections On Parameter Errors

Purpose: To investigate the effects of corrections for random and scattered coincidences on kinetic parameters in brain tumors, by using ten Monte Carlo (MC) simulated dynamic FLT-PET brain scans. Methods: The GATE MC software was used to simulate ten repetitions of a 1 hour dynamic FLT-PET scan of a voxelized head phantom. The phantom comprised six normal head tissues, plus inserted regions for blood and tumor tissue. Different time-activity-curves (TACs) for all eight tissue types were used in the simulation and were generated in Matlab using a 2-tissue model with preset parameter values (K1,k2,k3,k4,Va,Ki). The PET data was reconstructed into 28 frames by both ordered-subset expectation maximization (OSEM) and 3D filtered back-projection (3DFBP). Five image sets were reconstructed, all with normalization and different additional corrections C (A=attenuation, R=random, S=scatter): Trues (AC), trues+randoms (ARC), trues+scatters (ASC), total counts (ARSC) and total counts (AC). Corrections for randoms and scatters were based on real random and scatter sinograms that were back-projected, blurred and then forward projected and scaled to match the real counts. Weighted non-linearleast- squares fitting of TACs from the blood and tumor regions was used to obtain parameter estimates. Results: The bias was not significantly different for trues (AC), trues+randoms (ARC), trues+scatters (ASC) and total counts (ARSC) for either 3DFBP or OSEM (p<0.05). Total counts with only AC stood out however, with an up to 160% larger bias. In general, there was no difference in bias found between 3DFBP and OSEM, except in parameter Va and Ki. Conclusion: According to our results, the methodology of correcting the PET data for randoms and scatters performed well for the dynamic images where frames have much lower counts compared to static images. Generally, no bias was introduced by the corrections and their importance was emphasized since omitting them increased bias extensively.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Joint Development of SAS4A Code in Application to Oxide-fueled LFR Severe Accident Analysis

The scope of this project was to pursue specific SAS4A liquid-metal cooled reactor (LMR) safety analysis software extensions to simulate postulated accidents with fuel failures for oxide-fueled Lead-cooled Fast Reactors (LFRs). Since most U.S. LMR experience is on sodium-cooled fast reactor options based on past testing and operation experience with EBR-II and FFTF, the DOE’s legacy fast reactor safety analysis capabilities were focused on metal-fueled pool-type concepts with sodium coolant. In recent years, Westinghouse Electric Company (WEC) has decided to pursue an LFR design as one of their next generation nuclear technology options because of its favorable safety and economics attributes. Oxide fuel is considered among other fuel options due to previous WEC experience with this fuel form. Development of this new technology requires the availability of adequately accurate computational tools, some of which can be adapted from versions of similar software used for analysis of other LMRs. Although Argonne National Laboratory’s (ANL) SAS4A/SASSYS-1 safety analysis software suite (shortened as SAS4A code hereafter for brevity) has the basic capabilities to model LFR system designs, the SAS4A code modules used in the analysis of accidents with fuel/cladding failures lack appropriate models for the unique phenomena that govern as-irradiated oxide-fuel damage mechanisms in lead coolant. Therefore, the objective of this project was to extend the capabilities of SAS4A with mechanistic oxide-fuel failure models in lead coolant for margin to failure assessments, analysis of failure modes, location and timing of failures under different accident scenarios consistent with the whole-plant dynamic response including the reactivity feedback, and assessment of the potential for fuel damage propagation due to potential fission gas jet and fuel-fragment/molten fuel impingement to neighboring fuel pins in an assembly. This report provides mainly a summary of Argonne’s technical contributions in the joint project, but the reports and publications by the Participant team are included as references at the end of the report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Optical analysis of nanoparticle packing after drying in microdroplets

The optical spectra of nanostructured patterns with different degrees of order, obtained by dehydration self-assembly of nanoparticles in solution microdroplets placed on a planar substrate, have been analyzed. The reflectance spectrum of the best-ordered pattern contains a characteristic peak, the position of which is determined by the average lattice period in the layer. It is shown that the height of this peak depends on the degree of order of the pattern structure. Patterns with different degrees of order have been simulated using a software for modeling the self-assembly process, which takes into account the properties of particles, substrate, and solvent, as well as the contact line dynamics during solvent evaporation. A peak occurs in the reflectance spectrum due to the resonance Rayleigh scattering in the ordered layer. The described technique for optical diagnostics can be used to analyze the degree of particle order in a pattern.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Computationally inexpensive part-scale thermal history of additive friction-stir deposition

This study presents an analytical model for steady-state power generation and tool heat loss in additive friction-stir deposition (AFSD), developed to enable part-scale thermal simulation while remaining computationally inexpensive. The model predicts total generated power, yielding 3.7–4.7 kW across deposition temperature setpoints of 400–460 °C for the deposition of AA6061 with a Be-Cu tool. This corresponds to 90–95% of the reported spindle power. Tool heat loss is experimentally determined by calibrating a steady-state energy balance between the generated power, the substrate-deposition thermal gradient, and a temperature dependent tool heat loss term: q tool (T) = a + b (T - 400°C) with a = 2.7 x 10 6 Wm -2 and b = 9.5 x 10 3 Wm -2 K -1 . The calibration indicates that about 69% of the generated heat is conducted into the tool for this configuration, which is much higher than previously reported. The calibrated heat-source is implemented in finite element software (Adamantine) to simulate the transient thermal history of a 100 cm 3 representative build in 8 min on a standard desktop (at 0.635 mm build-height resolution). For the first three layers, the substrate temperatures between simulation and experiment are within 10% mean absolute percentage error. Sensitivity analysis indicates that uncertainties in average deposition temperature and deformation localization (stir-zone geometry, depth, and spatial dependance of strain-rate and flow stress) dominate model variance, motivating additional experimental verification.

Additive Friction-Stir Deposition↗
DOE OSTI2014

High quantum efficiency photocathode simulation for the investigation of novel structured designs

A computer model in CST Studio Suite has been developed to evaluate several novel geometrically enhanced photocathode designs. This work was aimed at identifying a structure that would increase the total electron yield by a factor of two or greater in the 1–30 keV range. The modeling software was used to simulate the electric field and generate particle tracking for several potential structures. The final photocathode structure has been tailored to meet a set of detector performance requirements, namely, a spatial resolution of <40 μm and a temporal spread of 1–10 ps. We present the details of the geometrically enhanced photocathode model and resulting static field and electron emission characteristics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

WE-H-207A-07: Image-Based Versus Atlas-Based Internal Dosimetry

Purpose: Monte Carlo (MC) simulation is known as the gold standard method for internal dosimetry. It requires radionuclide distribution from PET or SPECT and body structure from CT for accurate dose calculation. The manual or semi-automatic segmentation of organs from CT images is a major obstacle. The aim of this study is to compare the dosimetry results based on patient’s own CT and a digital humanoid phantom as an atlas with pre-specified organs. Methods: SPECT-CT images of a 50 year old woman who underwent bone pain palliation with Samarium-153 EDTMP for osseous metastases from breast cancer were used. The anatomical date and attenuation map were extracted from SPECT/CT and three XCAT digital phantoms with different BMIs (i.e. matched (38.8) and unmatched (35.5 and 36.7) with patient’s BMI that was 38.3). Segmentation of patient’s organs in CT image was performed using itk-SNAP software. GATE MC Simulator was used for dose calculation. Specific absorbed fractions (SAFs) and S-values were calculated for the segmented organs. Results: The differences between SAFs and S-values are high using different anatomical data and range from −13% to 39% for SAF values and −109% to 79% for S-values in different organs. In the spine, the clinically important target organ for Samarium Therapy, the differences in the S-values and SAF values are higher between XCAT phantom and CT when the phantom with identical BMI is employed (53.8% relative difference in S-value and 26.8% difference in SAF). However, the whole body dose values were the same between the calculations based on the CT and XCAT with different BMIs. Conclusion: The results indicated that atlas-based dosimetry using XCAT phantom even with matched BMI for patient leads to considerable errors as compared to image-based dosimetry that uses the patient’s own CT Patient-specific dosimetry using CT image is essential for accurate results.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Demonstrate multi-turbine simulation with hybrid-structured / unstructured-moving-grid software stack running primarily on GPUs and propose improvements for successful KPP-2

The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines, capturing the thin boundary layers, and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources.

17 WIND ENERGY↗
DOE OSTI2020

A deep insight on the coal ash-to-slag transformation behavior during the entrained flow gasification process

Recent research provided deep insight on the coal ash-to-slag transformation characterization during the entrained flow gasification process, with experimentation on a 40 kg/hr (dry basis) coal-fed opposed multi-burner (OMB) entrained flow gasifier and simulation via FactSage™ software. A general mechanism is presented to relate the gasifier design temperature, ash fluid temperature, and operating temperature with the degree of the slag polymerization. The change of the high temperature zone, the corresponding particle residence time in the high temperature zone, and syngas composition have obvious effects on the slag mineral transformation behavior. Mineral types formed on the wall of the gasifier chamber were mainly anorthite (CaAl 2 Si 2 O 8 ), aluminum oxide (Al 2 O 3 ), and calcium sulfide (CaS). These minerals transformed to anorthite and diopside (CaMgSi 2 O 6 ) at the slag hole zone, while the minerals at the lock hopper were anorthite, orthoclase (KAlSi 3 O 8 ), quartz (SiO 2 ), gypsum (CaSO 4 ), calcite (CaCO 3 ), and halite (NaCl). FactSage™ predicted minerals as anorthite, diopside, orthoclase, and albite (NaAlSi 3 O 8 ), etc., where the slag temperature was below the ash fluid temperature and when the ratios of CO/CO 2 and (CO + H 2 )/CO 2 were lower than 1.0 and 2.0, respectively. By simulation, residual carbon was found to be the dominant factor over syngas composition to cause mineral transformation, and this was verified experimentally. The Ca-based crystals, typically anorthite, was shifted to diopside, near the slag hole zone, and a linear relationship was found between the content ratios of diopside/(anorthite + diopside), CaO/SiO 2 , and (CaO + MgO)/SiO 2 . A dimensionless number, θ, was defined to characterize the changing chemical composition and the degree of slag polymerization, with temperature deviation from the design condition. Three zones of θ were identified and related to the deviation between the actual gasification condition from the design condition. Finally, a low slag polymerization degree corresponded with a higher temperature deviation between the actual condition and design condition, and this proved that increased residual carbon content and changing iron valence state increased the mineral types when the slag temperature was below the ash fluid temperature.

01 COAL, LIGNITE, AND PEAT↗