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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

SU-E-T-348: Verification MU Calculation for Conformal Radiotherapy with Multileaf Collimator Using Report AAPM TG 114

Purpose: The purpose of this work was to develop and validate an open source independent MU dose calculation software for 3D conformal radiotherapy with multileaf high and low resolution according to the report of AAPM TG 11 Methods: Treatment plans were done using Iplan v4.5 BrainLAB TPS. A 6MV photon beam produced by Primus and Novalis linear accelerators equipped with an Optifocus MLC and HDMLC, respectively. TPS dose calculation algorithms were pencil beam and Monte Carlo. 1082 treatments plans were selected for the study. The algorithm was written in free and open source CodeBlocks C++ platform. Treatment plans were imported by the software using RTP format. Equivalent size field is obtained from the positions of the leaves; the effective depth of calculation can be introduced by TPS's dosimetry report or automatically calculated starting from SSD. The inverse square law is calculated by the 3D coordinates of the isocenter and normalization point of the treatment plan. The dosimetric parameters TPR, Sc, Sp and WF are linearly interpolated. Results: 1082 plans of both machines were analyzed. The average uncertainty between the TPS and the independent calculation was −0.43% ± 2.42% [−7.90%, 7.50%]. Specifically for the Primus the variation obtained was −0.85% ± 2.53% and for the Novalis 0.00% ± 2.23%. Data show that 94.8% of the cases the uncertainty was less than or equal to 5%, while 98.9% is less than or equal to 6%. Conclusion: The developed software is appropriate for use in calculation of UM. This software can be obtained upon request.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2021

Computational framework for behind-the-meter DER techno-economic modeling and optimization: REopt Lite

The energy system is undergoing a major transformation with the global emphasis on decarbonization. Distributed generation is projected to play a significant role in the new energy system, and energy models are informing how distributed generation can be integrated reliably and economically. In this work, we present an end-to-end computational framework for distributed energy resource (DER) modeling, REopt Lite™, which captures the interface of technology, economics, and policy in the energy modeling process. We describe the problem space, the building blocks of the model, the scaling capabilities of the design, the optimization formulation, and the extensibility of the model. We present a framework for accelerating the techno-economic analysis of behind-the-meter distributed energy resources to enable rapid planning and decision-making, thereby enabling greater renewable energy deployment. This computation framework is open-sourced to facilitate transparency, flexibility, and wider collaboration opportunities within the worldwide energy modeling community.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Numerical and experimental comparison of tracer particle and averaging techniques for particle velocities in a fluidized bed

Particle tracking methods using emitted radiation show potential for following motion in opaque systems such as granular materials. Leading examples are Positron Emission Particle Tracking (PEPT) and Radioactive Particle Tracking (RPT). The application of such techniques sometimes requires the use of tracer particles which differ in size, density and/or shape from the particles of interest. This study investigates the extent to which such differences affect the result of the study by using the open source MFIX-DEM software to model particle motion in the travelling fluidized bed experiments. The results are compared with previously reported experimental studies using both PEPT and RPT. Consistent numerical results were obtained for both PEPT and RPT tracer particles. In determining averaged velocities using such techniques, there is a choice to be made between averaging velocities of particles crossing a virtual plane over a period of time (the “face-average” approach) or those passing through a defined volume over time (the “volume-average” approach). The differences between results obtained with these two methods are shown to be significant in this case, for both computation and experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

JP-10 combustion studied with shock tube experiments and modeled with automatic reaction mechanism generation

Our research presents shock tube experiments and kinetic modeling efforts on the pyrolysis and combustion of JP-10. The experiments were performed at 6–8 atm using 2000 ppm of JP-10 over a temperature range of 1000–1600 K for pyrolysis and oxidation equivalence ratios from 0.14 to 1.0. This work distinguishes itself from previous studies as GC/MS was used to identify and quantify the products within the shocked samples, enabling the tracking of product yield dependence on equivalence ratio as well as identifying several new intermediates that form during JP-10’s decomposition. A detailed, comprehensive model of JP-10’s combustion and pyrolysis kinetics was constructed with the help of RMG, an open-source reaction mechanism generation software package. The resulting model, which includes 691 species reacting in 15,518 reactions, was extensively validated against the shock tube experimental dataset as well as newly published flow tube pyrolysis data from Ghent. Most of the significant rate coefficients were computed using quantum chemistry. The model succeeds in identifying all major pyrolysis and combustion products and captures key trends in the product distribution. Simulated ignition delays agree within a factor of 4 with most experimental ignition delay data gathered from literature. The proposed experimental work and modeling efforts yield new insights on JP-10’s complex decomposition and oxidation chemistry and identify key pathways towards aromatics formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Matminer: An open source toolkit for materials data mining

As materials data sets grow in size and scope, the role of data mining and statistical learning methods to analyze these materials data sets and build predictive models is becoming more important. This manuscript introduces matminer, an open-source, Python-based software platform to facilitate data-driven methods of analyzing and predicting materials properties. Matminer provides modules for retrieving large data sets from external databases such as the Materials Project, Citrination, Materials Data Facility, and Materials Platform for Data Science. It also provides implementations for an extensive library of feature extraction routines developed by the materials community, with 47 featurization classes that can generate thousands of individual descriptors and combine them into mathematical functions. Finally, matminer provides a visualization module for producing interactive, shareable plots. These functions are designed in a way that integrates closely with machine learning and data analysis packages already developed and in use by the Python data science community. We explain the structure and logic of matminer, provide a description of its various modules, and showcase several examples of how matminer can be used to collect data, reproduce data mining studies reported in the literature, and test new methodologies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Cost optimization of low-salt-rejection reverse osmosis

Low-salt-rejection reverse osmosis (LSRRO) is an emerging membrane-based desalination technology for concentrating brines with potentially lower energy consumption and cost than thermally driven processes. We assess the technoeconomic performance of LSRRO by using an optimization model that minimizes the levelized cost of water (LCOW). We develop detailed models for the RO module and other equipment using WaterTAP (Water treatment Technoeconomic Assessment Platform), an open-source simulation and optimization software for water treatment. We improve upon previous LSRRO cost optimization studies by optimizing the salt permeability for each stage, which has significant implications for technoeconomic performance. We present the cost-optimal design, operation, and performance for three cases: 35 g/L TDS feed at 70% recovery, 70 g/L at 55%, and 125 g/L at 35%. The cost-optimal LCOW and specific energy consumption (SEC) for these cases are 0.70, 1.89, and 7.41 $/m 3 and 3.9, 8.4, and 30.4 kWh/m 3 , respectively. For each case, we use sensitivity analyses to provide guidance on key factors that impact economic viability. We also present the cost-optimal LCOW and SEC for feed concentrations between 5 and 220 g/L TDS and recoveries between 30 and 90%. So, we compare LSRRO to other high-salinity desalination technologies and find that it may be cost-competitive below feed concentrations of 125 g/L.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Multiscale modeling of twinning and detwinning behavior of HCP polycrystals

A multiscale scheme is presented here to capture the twinning and detwinning mechanisms during cyclic loading of HCP polycrystals. In the current framework, the crystal plasticity finite element (CPFE) method is employed at the microstructural scale. The response of twinned regions at a material point is calculated using a novel homogenization scheme via a Taylor-type model. The homogenized behavior is then used in the CPFE to obtain the response of a polycrystal. An efficient rate-independent crystal plasticity model that has been incorporated into the open source PRISMS-Plasticity software is introduced here to capture the response of the twinned region. Accordingly, the corresponding algorithmic tangent modulus is derived. Finally, this multiscale scheme is validated against data available for the cyclic response of Mg alloy ZK60A. The results show that the multiscale model can capture the key elements of the sample response observed during the experiment.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Nonintrusive Uncertainty Quantification of Computational Fluid Dynamics Simulations of a Bench-Scale Fluidized-Bed Gasifier

Uncertainty quantification (UQ) analysis is increasingly becoming one of the major requirements of simulation-based engineering to assess the confidence in the results and make better-informed decisions based on the insight derived from the simulations. In an earlier study, Bayesian UQ analysis was applied to existing bench-scale fluidized-bed gasifier experiment results. In the current study, a series of simulations were carried over with the open-source computational fluid dynamics software MFiX to reproduce the experimental conditions, where three operating factors, i.e., coal flow rate, coal particle diameter, and steam-to-oxygen ratio, were systematically varied to understand their effect on the syngas composition. Bayesian UQ analysis was this time performed on the numerical results for comparison purposes. This is part of ongoing research efforts to explore the applicability of advanced UQ methods and processes such as Bayesian methods for large-scale complex multiphase flow simulations. As part of Bayesian UQ analysis, a global sensitivity analysis was performed based on the simulation results, which shows that the predicted syngas composition is strongly affected not only by the steam-to-oxygen ratio (which was observed in experiments as well) but also by variation in the coal flow rate and particle diameter (which was not observed in experiments). The carbon monoxide mole fraction is underpredicted at lower steam-to-oxygen ratios and overpredicted at higher steam-to-oxygen ratios. The opposite trend is observed for the carbon dioxide mole fraction. These discrepancies are attributed to either excessive segregation of the phases that leads to the fuel-rich or -lean regions or alternatively the selection of reaction models, where different reaction models and kinetics can lead to different syngas compositions throughout the gasifier.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2018

Electronic Excitations in Complex Molecular Environments: Many-Body Green’s Functions Theory in VOTCA-XTP

Many-body Green’s functions theory within the GW approximation and the Bethe-Salpeter Equation (BSE) is implemented in the open-source VOTCA-XTP software, aiming at the calculation of electronically excited states in complex molecular environments. Based on Gaussian-type atomic orbitals and making use of resolution of identity techniques, the code is designed specifically for nonperiodic systems. Application to a small molecule reference set successfully validates the methodology and its implementation for a variety of excitation types covering an energy range from 2 to 8 eV in single molecules. Further, embedding each GW-BSE calculation into an atomistically resolved surrounding, typically obtained from Molecular Dynamics, accounts for effects originating from local fields and polarization. Using aqueous DNA as a prototypical system, different levels of electrostatic coupling between the regions in this GW-BSE/MM setup are demonstrated. Particular attention is paid to charge-transfer (CT) excitations in adenine base pairs. It is found that their energy is extremely sensitive to the specific environment and to polarization effects. The calculated redshift of the CT excitation energy compared to a nucelobase dimer treated in vacuum is of the order of 1 eV, which matches expectations from experimental data. Predicted lowest CT energies are below that of a single nucleobase excitation, indicating the possibility of an initial (fast) decay of such an UV excited state into a binucleobase CT exciton. Furthermore, the results show that VOTCA-XTP’s GW-BSE/MM is a powerful tool to study a wide range of types of electronic excitations in complex molecular environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Excited-state electronic structure of molecules using many-body Green’s functions: Quasiparticles and electron–hole excitations with VOTCA-XTP

Here, we present the open-source VOTCA-XTP software for the calculation of the excited-state electronic structure of molecules using many-body Green’s function theory in the GW approximation with the Bethe–Salpeter equation (BSE). This work provides a summary of the underlying theory and discusses the details of its implementation based on Gaussian orbitals, including resolution-of-identity techniques and different approaches to the frequency integration of the self-energy or acceleration by offloading compute-intensive matrix operations using graphics processing units in a hybrid OpenMP/Cuda scheme. A distinctive feature of VOTCA–XTP is the capability to couple the calculation of electronic excitations to a classical polarizable environment on an atomistic level in a coupled quantum- and molecular-mechanics (QM/MM) scheme, where a complex morphology can be imported from Molecular Dynamics simulations. The capabilities and limitations of the GW–BSE implementation are illustrated with two examples. First, we study the dependence of optically active electron–hole excitations in a series of diketopyrrolopyrrole-based oligomers on molecular-architecture modifications and the number of repeat units. Second, we use the GW–BSE/MM setup to investigate the effect of polarization on localized and intermolecular charge-transfer excited states in morphologies of low-donor content rubrene–fullerene mixtures. These showcases demonstrate that our implementation currently allows us to treat systems with up to 2500 basis functions on regular shared-memory workstations, providing accurate descriptions of quasiparticle and coupled electron–hole excited states of various characters on an equal footing.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Accurate frozen core approximation for all-electron density-functional theory

We implement and benchmark the frozen core approximation, a technique commonly adopted in electronic structure theory to reduce the computational cost by means of mathematically fixing the chemically inactive core electron states. The accuracy and efficiency of this approach are well controlled by a single parameter, the number of frozen orbitals. Explicit corrections for the frozen core orbitals and the unfrozen valence orbitals are introduced, safeguarding against seemingly minor numerical deviations from the assumed orthonormality conditions of the basis functions. A speedup of over twofold can be achieved for the diagonalization step in all-electron density-functional theory simulations containing heavy elements, without any accuracy degradation in terms of the electron density, total energy, and atomic forces. This is demonstrated in a benchmark study covering 103 materials across the Periodic Table and a large-scale simulation of CsPbBr3 with 2560 atoms. Our study provides a rigorous benchmark of the precision of the frozen core approximation (sub-meV per atom for frozen core orbitals below −200 eV) for a wide range of test cases and for chemical elements ranging from Li to Po. The algorithms discussed here are implemented in the open-source Electronic Structure Infrastructure software package.

Yu, Victor Wen-zhe↗
DOE OSTI2018

Visualizing effective potentials and using the IBM-Q to study quantum field theory models in 0+1 dimensions

This work explores the utility of two novel techniques applied to studying quantum field theory, namely quantum computing and visualizing effective potentials. We studied the ground state properties of the anharmonic oscillator and the Wess-Zumino model using the variational quantum eigensolver algorithm. We performed calculations for three and four qubit systems using IBM’s open source quantum computing simulation software. Using effective potentials, we study a simple dark mat-ter system with a Higgs and dark Higgs like particle interacting through a porthole fermion.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

PV Hosting Capacity Estimation: Experiences with Scalable Framework

Hosting capacity is an indication of the amount of solar photovoltaics (PV) that can be hosted in a distribution system without additional changes to infrastructure or oper-ations. This paper presents a framework for estimating the PV hosting capacity at scale. First, we analyze computational, modeling and other key challenges of performing relevant, large-scale simulations, provided along with the experiences and lessons learned. Then, we develop two open-source Python-based software tools to conduct repeatable distribution analyses: the Distribution Integration Solution Cost Options (DISCO) for configuring and analyzing simulations and the Job Automation and Deployment Engine (JADE) for parallelizing jobs on high-performance computing clusters. A case study of hosting capacity estimation for the SMART-DS San Francisco (SFO) 2000+ synthetic feeders, is used to demonstrate the capability of the developed DISCO+JADE framework and tools. The framework and tools can help utilities assess the overall hosting capacity of their service territory, which can help them better plan for the overall upgrade costs to integrate more PV in the future. The experiences are shared to aid the tool users and researchers to conduct relevant studies and research.

distributed energy resources↗
DOE OSTI2016

A surface ice module for wind turbine dynamic response simulation using FAST

It is a fact that developing offshore wind energy has become more and more serious worldwide in recent years. Many of the promising offshore wind farm locations are in cold regions that may have ice cover during wintertime. The challenge of possible ice loads on offshore wind turbines raises the demand of modeling capacity of dynamic wind turbine response under the joint action of ice, wind, wave, and current. The simulation software FAST is an open source computer-aided engineering (CAE) package maintained by the National Renewable Energy Laboratory. In this paper, a new module of FAST for assessing the dynamic response of offshore wind turbines subjected to ice forcing is presented. In the ice module, several models are presented which involve both prescribed forcing and coupled response. For conditions in which the ice forcing is essentially decoupled from the structural response, ice forces are established from existing models for brittle and ductile ice failure. For conditions in which the ice failure and the structural response are coupled, such as lock-in conditions, a rate-dependent ice model is described, which is developed in conjunction with a new modularization framework for FAST. In this paper, analytical ice mechanics models are presented that incorporate ice floe forcing, deformation, and failure. For lower speeds, forces slowly build until the ice strength is reached and ice fails resulting in a quasi-static condition. For intermediate speeds, the ice failure can be coupled with the structural response and resulting in coinciding periods of the ice failure and the structural response. A third regime occurs at high speeds of encounter in which brittle fracturing of the ice feature occurs in a random pattern, which results in a random vibration excitation of the structure. An example wind turbine response is simulated under ice loading of each of the presented models. This module adds to FAST the capabilities for analyzing the response of wind turbines subjected to forces resulting from ice impact on the turbine support structure. The conditions considered in this module are specifically addressed in the International Organization for Standardization (ISO) standard 19906:2010 for arctic offshore structures design consideration. Special consideration of lock-in vibrations is required due to the detrimental effects of such response with regard to fatigue and foundation/soil response. Finally, the use of FAST for transient, time domain simulation with the new ice module is well suited for such analyses.

17 WIND ENERGY↗
DOE OSTI2024

Novel principal component analysis tool based on python for analysis of complex spectra of time-of-flight secondary ion mass spectrometry

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a powerful surface analysis tool, which can simultaneously provide elemental, isotopic, and molecular information with part per million (ppm) sensitivity. However, each spectrum may be composed of hundreds of ion signals, which makes the spectra data complex. Principal component analysis (PCA) is a multivariate analysis technique that has been widely used to figure out the variances among samples in ToF-SIMS spectra data analysis and is showing great success in the explanation of complex ToF-SIMS spectra. So far, several software tools have been developed for PCA of ToF-SIMS spectra; however, none of them are freely available. Such a situation leads to some difficulties in extending applications of PCA to various research fields. More importantly, it has long been challenging for common researchers to understand PCA plots and extract chemical differences among samples. In this work, we developed a new and flexible software tool (named “advanced spectra pca toolbox”) based on python for PCA of complex ToF-SIMS spectra along with an easy-to-read manual. It can generate data analysis reports automatically to explain chemical differences among samples, allowing less experienced researchers to easily understand tricky PCA results. Moreover, it is expandable and compatible with artificial intelligence/machine learning functions. Pure goethite and different lignin adsorbed goethite samples were used as a model system to demonstrate our new software tool, proving that our software tool can be readily used in complex spectra data processing. Our new software tool is open-source, convenient, flexible, and expandable. We expect this open-source tool will benefit the ToF-SIMS community.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

TU-AB-BRA-06: BEST IN PHYSICS (JOINT IMAGING-THERAPY): An MRI Compatible Externally and Internally Deformable Lung Motion Phantom for Multi-Modality IGRT

Purpose: MRI has become an attractive tool for tumor motion management. Current MR-compatible phantoms are only capable of reproducing translational motion. This study describes the construction and validation of a more realistic, MRI-compatible lung phantom that is deformable internally as well as externally. We demonstrate a radiotherapy application of this phantom by validating the geometric accuracy of the open-source deformable image registration software NiftyReg (UCL, UK). Methods: The outer shell of a commercially-available dynamic breathing torso phantom was filled with natural latex foam with eleven water tubes. A rigid foam cut-out served as the diaphragm. A high-precision programmable, in-house, MRI-compatible motion platform was used to drive the diaphragm. The phantom was imaged on a 3T scanner (Philips, Ingenia). Twenty seven tumor traces previously recorded from lung cancer patients were programmed into the phantom and 2D+t image sequences were acquired using a sparse-sampling sequence k-t BLAST (accn=3, resolution=0.66×0.66×5mm3; acquisition-time=110ms/slice). The geometric fidelity of the MRI-derived trajectories was validated against those obtained via fluoroscopy using the on board kV imager on a Truebeam linac. NiftyReg was used to perform frame by frame deformable image registration. The location of each marker predicted by using NiftyReg was compared with the values calculated by intensity-based segmentation on each frame. Results: In all cases, MR trajectories were within 1 mm of corresponding fluoroscopy trajectories. RMSE between centroid positions obtained from segmentation with those obtained by NiftyReg varies from 0.1 to 0.21 mm in the SI direction and 0.08 to 0.13 mm in the LR direction showing the high accuracy of deformable registration. Conclusion: We have successfully designed and demonstrated a phantom that can accurately reproduce deformable motion under a variety of imaging modalities including MRI, CT and x-ray fluodoscopy, making it an invaluable research tool for validating novel motion management strategies. This work was partially supported through research funding from National Institutes of Health (R01CA169102).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Kinetic Monte Carlo for semiconductor surface science v.1

SAND2020-14229 O This software builds on an open source Kinetic Monte Carlo library to evaluate the incorporation rate of semiconductor dopant atoms in an Atomic Precision Advanced Manufacturing (APAM) process. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525

Campbell, Quinn↗