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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Collaborative Research: Understanding air‐sea feedbacks to the MJO through process evaluation of observations and E3SM experiments (Final Technical Report)

This project explored the role of tropical oceans in regulating cloud populations within the Madden-Julian oscillation (MJO)–a large-scale tropical weather disturbance that influences extreme weather events across the globe by affecting the position of the jet stream and patterns of moisture transport. Our project sought to 1) document ocean feedback strength to the MJO in climate models, 2) understand how air-sea interactions affect the intensity, organization, and propagation of MJO convection, 3) utilize existing observations to identify sources of model bias for tropical air-sea interactions, and 4) better understand the effects of slow and fast ocean variability on MJO cloudiness. We found that transfers of heat and moisture across the air-sea interface (i.e., surface fluxes) in most climate models are over-supportive in maintaining MJO convection and under-supportive in propagating MJO convection. This can lead to misrepresentations in the frequency of extreme weather events across the globe through erroneous MJO feedbacks to jet stream position and moisture transport. Furthermore, using observations collected by ocean moorings across the tropical oceans, we showed that most models greatly overestimate surface evaporation in the subtropics, and that this bias is likely one contributor to a pervasive bias among climate models in their ability to simulate the mean state of rainfall over the tropical oceans (i.e., the “double ITCZ bias”). Replacing the default surface flux algorithm in two climate models with a state-of-the-art surface flux algorithm modestly reduced the double ITCZ bias in those models. Our work produced two model diagnostics packages that are now publicly available through DOE and NOAA model diagnostics archives. The first, the Analysis of Scales of Precipitation (ASoP) diagnoses scales of precipitation variability across space and time, with temporal resolution as fine as the model integration timestep. The second, the air-sea flux diagnostic diagnoses model surface fluxes and allows direct comparison of model fluxes to observations without having to recompute fluxes using model output and a state-of-the-art flux algorithm. These diagnostics, which were developed using climate models, can be readily applied to regional and global forecast model output to improve forecasts for the benefit of society.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A case study on parallel HDF5 dataset concatenation for high energy physics data analysis

In High Energy Physics (HEP), experimentalists generate large volumes of data that, when analyzed, helps us better understand the fundamental particles and their interactions. This data is often captured in many files of small size, creating a data management challenge for scientists. In order to better facilitate data management, transfer, and analysis on large scale platforms, it is advantageous to aggregate data further into a smaller number of larger files. However, this translation process can consume significant time and resources, and if performed incorrectly the resulting aggregated files can be inefficient for highly parallel access during analysis on large scale platforms. In this paper, we present our case study on parallel I/O strategies and HDF5 features for reducing data aggregation time, making effective use of compression, and ensuring efficient access to the resulting data during analysis at scale. We focus on NOvA detector data in this case study, a large-scale HEP experiment generating many terabytes of data. Here, the lessons learned from our case study inform the handling of similar datasets, thus expanding community knowledge related to this common data management task.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Initial Development of Fusion Magnet Simulation Capabilities for Performance and Safety Evaluation Using the MOOSE Framework

Fusion energy holds the promise of being a transformative technology as a carbon-neutral, sustainable source of energy. Whole device modeling and the development of fusion digital twins will be increasingly important for emerging fusion device concepts at both national laboratories and within the commercial fusion industry. However, meeting the challenge of whole device modeling of fusion energy devices requires robust, multiphysics, multiscale modeling and simulation technologies capable of running on large-scale supercomputers. Detailed analysis of individual systems at-scale is also required to ensure safe and efficient operation as well as provide the safety basis for future device designs and licensing activities. In a tokamak, toroidal and poloidal magnets confine and shape the fusion plasma to promote the fusion reaction. High plasma temperatures and high magnetic field requirements in modern design concepts (leading to high amounts of energy stored within each magnet) impose electrical, thermal, and mechanical loads on the magnet components, which in turn impacts the safety considerations of the magnet and their supporting systems. Idaho National Laboratory (INL) has a history of working in this space, including development and benchmarking of the Magnetic System Circuitry Analysis Program (MSCAP) and Magnet Arcing (MAGARC) codes to study magnet quench events; notably, MAGARC was used to study quenching during the ITER Engineering Design Activity. However, these legacy codes and capabilities are not parallel and scalable, and new tools are required for future advances in this area, which leads to the INL-developed Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. Developed originally for fission reactor systems under United States Department of Energy, Office of Nuclear Energy modeling and simulation programs, the MOOSE framework has been well-suited to multiscale, multiphysics modeling and simulation needs for nuclear systems. The framework is open-source, well-tested, under continuous development and deployment, and developed to a Nuclear Quality Assurance, Level 1 software quality standard. MOOSE has also been used in the fusion space previously in several projects: INL’s Tritium Migration Analysis Program, Version 8 (TMAP8) for tritium migration, UK Atomic Energy Authority’s A Unified Resource for OpenMC (fusion) Reactor Applications (AURORA) code for fusion thermo-mechanical and neutronics analysis, and Argonne National Laboratory’s Cardinal for high-fidelity computational fluid dynamics and neutronics. However, to model superconducting magnets, several MOOSE enhancements are required: additions to the current MOOSE electromagnetic capabilities, new material libraries for superconductors of interest (such as YBCO), as well as fusion-specific models for thermo-mechanics. This talk will discuss initial development activities to build these capabilities in MOOSE, focusing on initial validation and benchmarking activities. Proposed coupling workflows and future work to support the simulation of fusion magnets and magnet structural assemblies for performance and safety evaluation in MOOSE will also be discussed.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Failures in Large Scale Systems: Long-term Measurement, Analysis, and Implications

Resilience is one of the key challenges in maintaining high efficiency of future extreme scale supercomputers. Researchers and system practitioners rely on field-data studies to understand reliability characteristics and plan for future HPC systems. In this work, we compare and contrast the reliability characteristics of multiple large-scale HPC production systems. Our study covers more than one billion compute node hours across five different systems over a period of 8 years. We confirm previous findings which continue to be valid, discover new findings, and discuss their implications.

Gupta, Saurabh↗
DOE OSTI2018

Assessing Mountains as Natural Reservoirs With a Multimetric Framework

Anthropogenic climate change will continue to diminish the unique role that mountains perform as natural reservoirs and alter long‐held assumptions of water management. Climate models are important tools to help constrain uncertainty and understand processes that shape this decline. To ensure that climate model estimates provide stakeholder relevant information, the formulation of multimetric model evaluation frameworks informed by stakeholder interactions are critical. In this study, we present one such multimetric framework to evaluate snowpack data sets in the California Sierra Nevada: the snow water equivalent (SWE) triangle. SWE triangle metrics help to describe snowpack characteristics associated with total water volume buildup, peak water availability, and the rate of water release. This approach highlights compensating errors that would not be reflected in conventional large‐scale spatiotemporal analysis. To test our multimetric evaluation framework, we evaluate several publicly available snow products including the Sierra Nevada Snow Reanalysis, Livneh (L15), and the North American Land Data Assimilation System version 2 data sets. We then evaluate regional climate model skill within the North American Coordinated Regional Climate Downscaling Experiment. All data sets analyzed show variation across the various SWE triangle metrics, even within observationally constrained snow products. This spread was especially shown in spring season melt rates. Melt rate biases were prevalent throughout most regional climate model simulations, regardless of snow accumulation dynamics, and will need to be addressed to improve their utility for water stakeholders.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Metabolic Differences in Microbial Cell Populations Revealed by Nanophotonic Ionization

ellular differences are linked to cell differentiation, the proliferation of cancer and to the development of drug resistance in microbial infections. Due to sensitivity limitations, however, large- scale metabolic analysis at the single cell level is only available for cells significantly larger in volume than Saccharomyces cerevisiae (~30 fL). Here we demonstrate that by a nanophotonic ionization platform and mass spectrometry, over one hundred up to 108 metabolites, or up to 18% of the known S. cerevisiae metabolome, can be identified in very small cell populations (n < 100). Under ideal conditions, r Relative quantitation of up to 4% of the metabolites is achieved at the single cell level.

Walker, Bennett↗
DOE OSTI2024

Characterization of Porous Transport Layers Towards the Development of Efficient Proton Exchange Membrane Water Electrolysis

The current goals for implementing the hydrogen economy have highlighted a need to further optimize water-splitting technologies for clean hydrogen production. Proton exchange membrane water electrolysis (PEMWE) is a leading technology, but further optimizations of anode materials including the porous transport layer (PTL) and the adjacent catalyst layer (CL) are required to increase overall cell performance and reduce cost. This literature review describes advances in PTL development and characterization, highlighting early PTL characterization work and most common methods including capillary flow porometry and mercury intrusion porometry, optical imaging, neutron and x-ray radiography, and x-ray computed tomography. The article also discusses PTL protective coatings and their characterizations, focusing on platinum group metal (PGM)-based coatings, alternative non-PGM-based coatings, post-treated PTLs, and investigations into thin PGM-based coatings. Furthermore, it highlights the integration of the PTL and the adjacent CL along with associated characterization challenges. Lastly, this review discusses future developments in the characterization needed to improve PEMWE's performance and long-term durability are discussed.

08 HYDROGEN↗
DOE OSTI2020

Evolutionary history, potential intermediate animal host, and cross-species analyses of SARS-CoV-2

To investigate the evolutionary history of the recent outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China, a total of 70 genomes of virus strains from China and elsewhere with sampling dates between 24 December 2019 and 3 February 2020 were analyzed. To explore the potential intermediate animal host of the SARS-CoV-2 virus, we reanalyzed virome data sets from pangolins and representative SARS-related coronaviruses isolates from bats, with particular attention paid to the spike glycoprotein gene. We performed phylogenetic, split network, transmission network, likelihood-mapping, and comparative analyses of the genomes. Additionally, based on Bayesian time-scaled phylogenetic analysis using the tip-dating method, we estimated the time to the most recent common ancestor and evolutionary rate of SARS-CoV-2, which ranged from 22 to 24 November 2019 and 1.19 to 1.31 × 10 -3 substitutions per site per year, respectively. Our results also revealed that the BetaCoV/bat/Yunnan/RaTG13/2013 virus was more similar to the SARS-CoV-2 virus than the coronavirus obtained from the two pangolin samples (SRR10168377 and SRR10168378). We also identified a unique peptide (PRRA) insertion in the human SARS-CoV-2 virus, which may be involved in the proteolytic cleavage of the spike protein by cellular proteases, and thus could impact host range and transmissibility. Interestingly, the coronavirus carried by pangolins did not have the RRAR motif. Therefore, we concluded that the human SARS-CoV-2 virus, which is responsible for the recent outbreak of COVID-19, did not come directly from pangolins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

III-Vs at Scale: A PV Manufacturing Cost Analysis of the Thin Film Vapor-Liquid-Solid Growth Mode

The authors present a manufacturing cost analysis for producing thin-film indium phosphide modules by combining a novel thin-film vapor-liquid-solid (TF-VLS) growth process with a standard monolithic module platform. The example cell structure is ITO/n-TiO2/p-InP/Mo. For a benchmark scenario of 12% efficient modules, the module cost is estimated to be $0.66/W(DC) and the module cost is calculated to be around $0.36/W(DC) at a long-term potential efficiency of 24%. The manufacturing cost for the TF-VLS growth portion is estimated to be ~$23/m2, a significant reduction compared with traditional metalorganic chemical vapor deposition. The analysis here suggests the TF-VLS growth mode could enable lower-cost, high-efficiency III-V photovoltaics compared with manufacturing methods used today and open up possibilities for other optoelectronic applications as well.

14 SOLAR ENERGY↗
DOE OSTI2025

OptiBench: An Optimization Benchmark Tool for Renewable Energy Problems

We propose a benchmark framework and visualization tool, OptiBench, for analyzing the performance of state-of-the-art optimization solvers across a variety of optimization problems in renewable energy research. Our framework is designed from the ground up in the Julia programming language and enables analysis at scale on high performance computing (HPC) systems. Our visualization tool allows effortless evaluation of optimization solver performance, robustness, and accuracy through intuitive plots, e.g., performance profiles, heat maps, and distribution plots. We have tested three benchmark suites relevant to the modeling of renewable energy systems, viz., CUTEst, PGLib-OPF, and WaterTAP water treatment optimization problems. We illustrate benchmarking of CUTEst using OptiBench on the National Renewable Energy Laboratory's (NREL) HPC Kestrel. Our findings indicate that MA57 HSL linear solver demonstrated the best overall performance for an experimental IPOPT implementation. Our work is ongoing and we intend to add support for more optimization solvers and benchmark test suites in the future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Information flows in strongly coupled ABJM theory

We use holographic methods to characterize the RG flow of quantum information in a Chern-Simons theory coupled to massive fermions. First, we use entanglement entropy and mutual information between strips to derive the dimension of the RG-driving operator and a monotonic c-function. We then display a scaling regime where, unlike in a CFT, the mutual information between strips changes non-monotonically with strip width, vanishing in both IR and UV but rising to a maximum at intermediate scales. The associated information transitions also contribute to non-monotonicity in the conditional mutual information which characterizes the independence of neighboring strips after conditioning on a third. Finally, we construct a measure of extensivity which tests to what extent information that region A shares with regions B and C is additive. In general, mutual information is super-extensive in holographic theories, and we might expect super-extensivity to be maximized in CFTs since they are scale-free. Surprisingly, our massive theory is more super-extensive than a CFT in a range of scales near the UV limit, although it is less super-extensive than a CFT at all lower scales. Our analysis requires the full ten-dimensional dual gravity background, and the extremal surfaces computing entanglement entropy explore all of these dimensions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

PRRT2 inhibits the proliferation of glioma cells by modulating unfolded protein response pathway

Accumulating studies reported mutations in the gene encoding the proline-rich transmembrane protein 2 (PRRT2) to be causative for several paroxysmal neurological disorders, including paroxysmal kinesigenic dyskinesia (PKD), PKD combined with infantile seizures (ICCA), and benign familial infantile seizures (BFIS). However, the impact of PRRT2 in tumorigenesis is not known. Based on a large-scale data analysis, we found that PRRT2 was down-regulated in glioma tumor tissues compared with normal brain tissue. Dysregulation of PRRT2 was not induced by mutation, copy number variation and epigenetic modification, but modulated by microRNA-30a-5p. Overexpression of PRRT2 strongly impaired the cell viability and promoted cell apoptosis and these anti-tumor effects could be largely reversed by microRNA-30a-5p. Mechanistically, PRRT2 expression was closely correlated genes involved in unfolded protein response (UPR) pathway and introduction of PRRT2 inhibited gene expression in the three branches of UPR, including PERK axis, IRE1 axis and ATF6 axis. Taken together, our findings identify PRRT2 as a tumor suppressor in glioma and provide a promising target for potential therapeutic intervention. - Highlights: • PRRT2 is decreased in glioma and is targeted by miR-30a-5p. • PRRT2 exhibits tumor-suppressive effects on glioma cells. • PRRT2 correlates genes involved in unfolded protein response. • Over-expressed PRRT2 induces unfolded protein response in glioma in vitro.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Aquaporin 3 facilitates tumor growth in pancreatic cancer by modulating mTOR signaling

Aquaporins (AQP) have been demonstrated to be dysregulated in many human cancers and is thought to be involved in pancreatic carcinogenesis and progression. However, the oncogenic roles and underlying mechanism of AQP in pancreatic ductal adenocarcinoma (PDAC) remain largely unknown. In this study, by data mining of TCGA dataset and CCLE database, we identified that AQP3 is the major AQP expressed in PDAC. Then, the microRNA-874, was demonstrated to be a key regulator of AQP3 expression in PDAC cells. Genetic silencing of AQP3 expression had pronounced effects on cell proliferation and apoptosis of the PDAC cell lines BXPC3 and HPAFII. Introduction of microRNA-874 suppressed cell proliferation and promoted cell apoptosis, whereas inhibition of microRNA-874 had the opposite effect. Mechanistically, by a large-scale proteomic analysis, we revealed that AQP3 was significantly associated the activity of mTOR signaling. Moreover, modulation of AQP3 or microRNA-874 altered mTOR activity as demonstrated by the phosphorylation level of mTOR and its downstream target S6. Taken together, our data, as a proof of principle, suggest that AQP3 can promote tumor growth of pancreatic cancer cells by activating the Mtor signaling pathway and provide a potential therapeutic target in the treatment of PDAC. - Highlights: • Dysregulated expression of AQP3 is induced by miR-874 in pancreatic cancer. • miR-874-AQP3 axis is involved in cell proliferation and apoptosis of pancreatic cancer cells. • AQP3 correlates increased mTOR activity in pancreatic cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Two-stage dilute-acid and organic-solvent lignocellulosic pretreatment for enhanced bioprocessing

A two stage pretreatment approach for biomass is developed in the current work in which dilute acid (DA) pretreatment is followed by a solvent based pretreatment (N-methyl morpholine N oxide -- NMMO). When the combined pretreatment (DAWNT) is applied to sugarcane bagasse and corn stover, the rates of hydrolysis and overall yields (>90%) are seen to dramatically improve and under certain conditions 48 h can be taken off the time of hydrolysis with the additional NMMO step to reach similar conversions. DAWNT shows a 2-fold increase in characteristic rates and also fractionates different components of biomass -- DA treatment removes the hemicellulose while the remaining cellulose is broken down by enzymatic hydrolysis after NMMO treatment to simple sugars. The remaining residual solid is high purity lignin. Lastly, future work will focus on developing a full scale economic analysis of DAWNT for use in biomass fractionation.

09 BIOMASS FUELS↗
DOE OSTI2018

A high-pressure X-ray diffraction study of the crystalline phases in calcium aluminate cement paste

Calcium aluminate cement (CAC) has wide application in civil engineering and castable refractory materials. The main binding phases of hardened CAC paste, CaO·Al{sub 2}O{sub 3}·10H{sub 2}O (CAH{sub 10}), inevitably converts to 2CaO·Al{sub 2}O{sub 3}·8H{sub 2}O (C{sub 2}AH{sub 8}), 3CaO·Al{sub 2}O{sub 3}·6H{sub 2}O (C{sub 3}AH{sub 6}) and Al(OH){sub 3} (AH{sub 3}), leading to a significant change in the mechanical properties of the CAC matrix. This work investigates the mechanical properties of the main crystalline components in hydrated and/or converted CAC systems, using synchrotron-radiation-based high-pressure X-ray diffraction. The anisotropic deformations of CaAl{sub 2}O{sub 4} (CA), CAH{sub 10} and C{sub 3}AH{sub 6} along each crystallographic direction are investigated, along with their bulk moduli. The density-driven stiffening hypothesis is validated for the studied phases and other cement-based minerals. An atom-scale topological analysis is proposed to explain the unusually high stiffness of CAH{sub 10}. The results provide fundamental information to understand the mechanical properties of single cement-based phases at molecular level, and enable predicting the changing mechanical properties of converted CAC matrix using homogenization models.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Scaling Relations for Intercalation Induced Damage in Electrodes

Mechanical degradation, owing to intercalation induced stress and microcrack formation, is a key contributor to the electrode performance decay in lithium-ion batteries (LIBs). The stress generation and formation of microcracks are caused by the solid state diffusion of lithium in the active particles. Here in this work, scaling relations are constructed for diffusion induced damage in intercalation electrodes based on an extensive set of numerical experiments with a particle-level description of microcrack formation under disparate operating and cycling conditions, such as temperature, particle size, C-rate, and drive cycle. The microcrack formation and evolution in active particles is simulated based on a stochastic methodology. A reduced order scaling law is constructed based on an extensive set of data from the numerical experiments. The scaling relations include combinatorial constructs of concentration gradient, cumulative strain energy, and microcrack formation. Lastly, the reduced order relations are further employed to study the influence of mechanical degradation on cell performance and validated against the high order model for the case of damage evolution during variable current vehicle drive cycle profiles.

25 ENERGY STORAGE↗