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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Development of Efficient Process for Manufacturing of Thermoplastic Composites with Tailored Properties (CRADA 511)

This is a collaborative effort between Battelle Memorial Institute as manager and operator of Pacific Northwest National Laboratory (PNNL) and ESI North America Inc. (“ESI” or “Participant”) to apply computation and data analytics to the challenge of light weighting with a focus on the battery enclosures of electric vehicles (EVs). EVs use heavy batteries to increase range and power. A complex-shaped battery enclosure is required to meet a host of challenging performance requirements. The ability to virtually develop composite parts such as battery enclosure with tailored properties to meet required performance will be highly valuable to the automotive industry. However, efficient simulation of composite-manufacturing processes remains a challenging issue since simulation involves multiscale models in space and time, highly non-linear and anisotropic behavior, strongly coupled multi-physics, and complex geometries. This work will advance the state of the art by reducing the computational burden of composite optimization by using simulation data from a limited number of configurations off-line and then developing a reduced order model (ROM) using data analytics and machine learning (ML). Develop a data driven approach to link features of the material and manufacturing processes to the mechanical properties of thermoplastic composite parts.

42 ENGINEERING↗
DOE OSTI2021

CSRI Summer Proceedings 2021

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia National Laboratories for focused collaborative research on Department of Energy (DOE) computer and computational science problems. The institute provides an opportunity for university researches to learn about problems in computer and computational science at DOE laboratories, and help transfer results of their research to programs at the labs. Some specific CSRI research interest areas are: scalable solvers, optimization, algebraic preconditioners, graph-based, discrete, and combinatorial algorithms, uncertainty estimation, validation and verification methods, mesh generation, dynamic load-balancing, virus and other malicious-code defense, visualization, scalable cluster computers, beyond Moore’s Law computing, exascale computing tools and application design, reduced order and multiscale modeling, parallel input/output, and theoretical computer science. The CSRI Summer Program is organized by CSRI and includes a weekly seminar series and the publication of a summer proceedings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

CSRI Summer Proceedings 2021

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia National Laboratories for focused collaborative research on Department of Energy (DOE) computer and computational science problems. The institute provides an opportunity for university researches to learn about problems in computer and computational science at DOE laboratories, and help transfer results of their research to programs at the labs. Some specific CSRI research interest areas are: scalable solvers, optimization, algebraic preconditioners, graph-based, discrete, and combinatorial algorithms, uncertainty estimation, validation and verification methods, mesh generation, dynamic load-balancing, virus and other malicious-code defense, visualization, scalable cluster computers, beyond Moore’s Law computing, exascale computing tools and application design, reduced order and multiscale modeling, parallel input/output, and theoretical computer science. The CSRI Summer Program is organized by CSRI and includes a weekly seminar series and the publication of a summer proceedings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Enabling Efficient Water Splitting with Advanced Materials Designed for High pH Membrane Interface

This project was focused on developing the durable, high-performance materials and interfaces for advanced water splitting, enabling a clear pathway for achieving <$2/Kg H2 (on scale) with efficiency of 43 kWh/kg H 2 via anion exchange membrane (AEM)-based electrolysis. We aimed to advance these final goals via an improved fundamental understanding of both hydrogen and oxygen evolution reactions (HER/OER) leading to novel platinum group metal (PGM)-free catalyst materials in conjunction with critical improvements in membrane and ionomers and gas evolution electrodes with corresponding characterization and testing. Northeastern University (NU) lead this effort focusing on catalyst development and characterization (both in situ and ex situ) while project partners lead improvements in ionomer and membrane materials and will aid in the development of specialized electrode and membrane electrode assemblies. In addition, close collaboration occured with the HydroGEN Energy Materials Network (EMN) National Laboratory consortium including efforts related to use of advanced ionomers, durability protocols and validation of electrolyzer materials (e.g. NREL), multiscale modeling and computation (e.g. LBNL), and molecular dynamics (MD) simulations of the membrane catalyst interface (e.g. SNL). The interactions with HydroGEN included exchange of data and materials as needed to facilitate project success.

08 HYDROGEN↗
DOE OSTI2022

Physics-based Multiscale Additively Manufactured Superalloy Design for Optimized High Cycle Fatigue Life (Final Report)

The objectives of this project are to: (i) Gain fundamental understandings towards the microscopic damage mechanisms, as impacted by pertinent materials properties (e.g. stacking fault energy (SFE) and microstructure (e.g., grain size), leading to high-cycle fatigue (HCF) damage to AM Ni-based superalloy parts; (ii) Provide scientific insight into the effect of testing frequency on damage mechanisms and fatigue life of AM Ni-based superalloy parts under HCF regime, thereby establishing an appropriate correlation between accelerated testing and materials’ true service life; (iii) Devise an accurate, experimentally validated multiscale model across atomic, micro- and meso-scales, to predict the cyclic stress-strain responses and fatigue damage accumulation for AM Ni-based superalloys under various loading frequencies.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Abstract for CRADA between National Energy Technology Laboratory and Blacksand Technology, LLC

The National Energy Technology Laboratory (NETL) and Black Sand Technology, LLC (Participant) will collaborate in the optimization of low-cost manufacturing routes to produce ultralow-oxygen reactive metal powders of M=Ti, Zr, and Nb using Mg or Ca as reduction agents. Reactive metals have a strong chemical affinity to oxygen, making it very challenging to produce high-purity metal powders of these elements with extremely low oxygen content. This project integrates multiscale modeling and experimental validation to provide fundamental understanding of the thermodynamic limits on the deoxygenation process through HDH and optimize the key deoxygenation parameters to achieve ultralow oxygen content ≤0.1 wt.% in the reactive metal powders. The collaboration will significantly expedite the optimization of deoxygenation processes, reducing the timeline for refining deoxygenation techniques for Ti, Zr and Nb and other reactive refractory metals by about 0.5 and 2 years, respectively. This accelerated timeline translates to substantial cost savings estimated at $\$$3 million in research and development expenditures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Development of a High-Rate Lithium-Air Battery Using a Gaseous CO 2 Reactant

Li-air batteries are considered a potential alternative to Li-ion batteries for transportation applications due to their high theoretical specific energy. Most works in this area focus on use of O 2 as the reactant. However, newer concepts for using gaseous reactants (such as CO 2 , which has a theoretical specific energy density of 1,876 Wh/kg) provide opportunities for further exploration. The main objective of this project was the development of a novel strategy that enables operation of Li-CO 2 batteries at high-capacity and high-rate, with a long-cycle-life. The team was able to: (1) Synthesize two novel transition metal chalcogenide (TMC) catalysts that work in synergy with ionic liquid-based electrolytes to enhance the efficiency of reactions during discharge and charge processes; (2) Fabricate high-porosity cathode electrodes with 3D printing to increase electrode surface area and gas permeability; (3) Develop a multiscale modeling framework that integrates Density Functional Theory (DFT), Ab-Initio Molecular Dynamics (AIMD), classical Molecular Dynamics (MD), and Finite Element Analysis (FEA) to investigate atomic and cell-level properties of Li-CO 2 batteries; (4) Assemble a stackable Li-CO 2 pouch-cell able to deliver a capacity of >200 mAh. These achievements were realized through an integrated approach based on materials synthesis, testing, characterization, analysis, and computation. This project produced a thorough understanding of key chemical, electronic, and kinetic parameters that govern the operation of Li- CO 2 batteries in realistic conditions. The methodologies employed, and the insight generated, will be valuable beyond advancing the field of Li-CO 2 batteries

25 ENERGY STORAGE↗
DOE OSTI2025

MuSIKAL: Multiphysics Simulations and Knowledge Discovery through AI/ML Technologies

Under the MuSiKAL project, we developed a framework for a coastal digital twin (DT) platform capable of integrating diverse data resources, configuring multiscale model simulations, performing SciML‐accelerated predictions, with applications primarily driven by storm surge and heavily rainfall events impacting the Gulf Coast of the U.S.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The Circular Economy Lifecycle Assessment and Visualization Framework: A Case Study of Wind Blade Circularity in Texas

Moving the current linear economy toward circularity is expected to have environmental, economic, and social impacts. Various modeling methods, including economic input-output modeling, life cycle assessment, agent-based modeling, and system dynamics, have been used to examine circular supply chains and analyze their impacts. This work describes the newly developed Circular Economy Lifecycle Assessment and Visualization (CELAVI) framework, which is designed to model how the impacts of supply chains might change as circularity increases. We first establish the framework with a discussion of modeling capabilities that are needed to capture circularity transitions; these capabilities are based on the fact that supply chains moving toward circularity are dynamic and therefore not at steady state, may encompass multiple industrial sectors or other interdependent supply chains and occupy a large spatial area. To demonstrate the capabilities of CELAVI, we present a case study on end-of-life wind turbine blades in the U.S. state of Texas. Our findings show that depending on exact process costs and transportation distances, mechanical recycling could lead to 69% or more of end-of-life turbine blade mass being kept in circulation rather than being landfilled, with only a 7.1% increase in global warming potential over the linear supply chain. We discuss next steps for framework development.

17 WIND ENERGY↗
DOE OSTI2018

Parametrization of Combined Quantum Mechanical and Molecular Mechanical Methods: Bond-Tuned Link Atoms

Combined quantum mechanical and molecular mechanical (QM/MM) methods are the most powerful available methods for high-level treatments of subsystems of very large systems. The treatment of the QM-MM boundary strongly affects the accuracy of QM/MM calculations. For QM/MM calculations having covalent bonds cut by the QM-MM boundary, it has been proposed previously to use a scheme with system-specific tuned fluorine link atoms. Here, we propose a broadly parametrized scheme where the parameters of the tuned F link atoms depend only on the type of bond being cut. In the proposed new scheme, the F link atom is tuned for systems with a certain type of cut bond at the QM-MM boundary instead of for a specific target system, and the resulting link atoms are call bond-tuned link atoms. In principle, the bond-tuned link atoms can be as convenient as the popular H link atoms, and they are especially well adapted for high-throughput and accurate QM/MM calculations. Here, we present the parameters for several kinds of cut bonds along with a set of validation calculations that confirm that the proposed bond-tuned link-atom scheme can be as accurate as the system-specific tuned F link-atom scheme.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Influence of Surface and Bulk Water Ice on the Reactivity of a Water-forming Reaction

On the surface of icy dust grains in the dense regions of the interstellar medium, a rich chemistry can take place. Due to the low temperature, reactions that proceed via a barrier can only take place through tunneling. The reaction H+H{sub 2}O{sub 2}⟶H{sub 2}O+OH is such a case with a gas-phase barrier of ∼26.5 kJ mol{sup −1}. Still, the reaction is known to be involved in water formation on interstellar grains. Here, we investigate the influence of a water ice surface and of bulk ice on the reaction rate constant. Rate constants are calculated using instanton theory down to 74 K. The ice is taken into account via multiscale modeling, describing the reactants and the direct surrounding at the quantum mechanical level with density functional theory (DFT), while the rest of the ice is modeled on the molecular mechanical level with a force field. We find that H{sub 2}O{sub 2} binding energies cannot be captured by a single value, but rather they depend on the number of hydrogen bonds with surface molecules. In highly amorphous surroundings, the binding site can block the routes of attack and impede the reaction. Furthermore, the activation energies do not correlate with the binding energies of the same sites. The unimolecular rate constants related to the Langmuir–Hinshelwood mechanism increase as the activation energy decreases. Thus, we provide a lower limit for the rate constant and argue that rate constants can have values up to two order of magnitude larger than this limit.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

A Data Analysis Framework for Earth System Simulation within an In-Situ Infrastructure

This paper presents a generic procedure to implement a scalable and high performance data analysis framework for large-scale scientific simulation within an in-situ infrastructure. It demonstrates a unique capability for global Earth system simulations using advanced computing technologies (i.e ., automated code analysis and instrumentation), in-situ infrastructure (i.e ., ADIOS) and big data analysis engines (i.e ., SciKit-learn). This paper also includes a useful case that analyzes a globe Earth System simulations with the integration of scalable in-situ infrastructure and advanced data processing package. Finally, the in-situ data analysis framework can provides new insights on scientific discoveries in multiscale modeling paradigms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

When Do Different Scenarios of Future Electricity Demand Start to Meaningfully Diverge?

Climate and population change are known to influence electricity demand, but what is the impact of uncertainty in climate and population projections on electricity demand in the United States (U.S.) over the next 30 years? This question has important implications for investment decisions in the energy sector, which are typically made using a 15- to 30-year time horizon. Simply put, if future climate and population scenarios do not lead to meteorological conditions and subsequent energy demands that are distinctly different within the first 30 years then, for the purposes of investment decisions, it may not matter which potential pathway we are most likely on. The Integrated, Multisector, Multiscale Modeling (IM3) project has generated a wide, yet plausible range of 21st century high-resolution climate and population scenarios for the U.S. The IM3 projections span two climate scenarios (Representative Concentration Pathways 4.5 and 8.5) and two population scenarios (Shared Socioeconomic Pathways 3 and 5). For each of the climate scenarios, we reflect a range of climate model uncertainty by using boundary conditions from a set of climate models that are hotter and colder than the multi-model mean. In total there are eight (2 x 2 x 2) IM3 scenarios. This work explores a basic question: When do future climate and energy outcomes start to meaningfully diverge across the eight scenarios? The analysis is done on both the raw meteorology time-series from each scenario as well as a time-series of projected total electricity demand generated using IM3's Total ELectricity Loads (TELL) model. We also explore the spatial heterogeneity of the divergence signal to identify regions of the country that may be more or less path dependent.

Climate Change↗
DOE OSTI2023

GCAM-USA electricity demand results for National Climate Assessment 5

Overview This dataset includes GCAM-USA v 5.3 outputs for the percent change in electricity demand in the U.S. from 2020 to 2050 and from 2020 to 2100 for the thermodynamic global warming scenario "RCP8.5_hotter" and the SSP5 socioeconomic scenario. These results were produced as part of the Integrated Multisector, Multiscale Modeling (IM3) project. Detailed Information The electricity demand is calculated based on the IM3 GCAM-USA simulations. For the purpose of reproducibility, we provide the following data: 1. Raw data: the annual electricity demand for CONUS simulated by IM3 GCAM-USA for the scenario RCP8.5 Hotter - SSP5. 2. R scripts: process raw data, calculate percent change of electricity demand from 2020 to 2050 and from 2020 to 2100, and plot the data over CONUS. 3. Results: figures provided for NCA-5 and the corresponding data table from the R scripts.

Climate Change↗
DOE OSTI2023

Version of GCAM-USA used for National Climate Assessment 5, Chapter 5: GCAM-USA-v5.3-IM3-NCA5

Overview GCAM-USA-v5.3-IM3-NCA5 is developed using GCAM-USA-v5.3 as its core, with the impact of the thermodynamic global warming scenario "RCP8.5_hotter" on runoff, heating and cooling degree-hours, and agricultural yield and the SSP5 socioeconomic scenario. These scenarios were produced as part of the Integrated Multisector, Multiscale Modeling (IM3) project and used by National Climate Assessment 5. Detailed Information This software package includes the output dataset, which is located in "output/database_rcp85hotter_ssp5". For reproducibility, the model is setup and ready to run for the selected IM3 scenario "rcp85hotter_ssp5". To execute the model, double click "exe/run-gcam.bat".

Climate Change↗
NASA NTRS2005

Prediction of Mechanical Properties of Polymers With Various Force Fields

The effect of force field type on the predicted elastic properties of a polyimide is examined using a multiscale modeling technique. Molecular Dynamics simulations are used to predict the atomic structure and elastic properties of the polymer by subjecting a representative volume element of the material to bulk and shear finite deformations. The elastic properties of the polyimide are determined using three force fields: AMBER, OPLS-AA, and MM3. The predicted values of Young s modulus and shear modulus of the polyimide are compared with experimental values. The results indicate that the mechanical properties of the polyimide predicted with the OPLS-AA force field most closely matched those from experiment. The results also indicate that while the complexity of the force field does not have a significant effect on the accuracy of predicted properties, small differences in the force constants and the functional form of individual terms in the force fields determine the accuracy of the force field in predicting the elastic properties of the polyimide.

Odegard, Gregory M.↗