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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Open Source Visualization and Analysis Platform for 3D Reconstructions of Materials by Transmission Electron Microscopy

Three-dimensional characterization of materials at the nano- and meso-scale has become possible with transmission and scanning transmission electron microscopes (S/TEM). Its importance has extended to a wide class of nanomaterials such as hydrogen fuel cells, solar cells, industrial catalysts, new battery materials and semiconductor devices, as well as spanning high-tech industry, universities, and national labs. While capable instrumentation is abundant, this rapidly expanding demand for high-resolution tomography is bottlenecked by software that is instead tailored for lower-dose, biological applications and not optimized for higher-resolution materials applications. Existing tomography fails to utilize the chemical information provided by S/TEM spectrometers. To address this problem, this project delivered a scalable, fully functional, freely-distributable, open Source materials tomography package with a modern user interface that enables automated acquisition, alignment, and real-time reconstruction of raw tomography data, and provides advanced segmentation, three-dimensional chemical visualization and analysis optimized for materials applications. It has established an extendable framework capable of automation for high-throughput for the tomography of materials from data acquisition to visualization. Phase I and II delivered a full-featured, cross-platform, clean and integrated application for S/TEM materials tomography. It can read projection data from the microscope, with graphical tools for alignment of data, tomographic reconstruction, segmentation, and visualization of the reconstructed 3D volume. The entire pipeline can be saved to an XML state file, enabling fully reproducible data processing and analysis with a full Python environment for the development of custom algorithms, processing, and analysis requirements. Phase IIB extended the application to provide real-time tomographic reconstruction, "live updates" as data is processed, analysis of big data, and multi-channel tomography. Here, quantitative assessment of nanomaterials can occur as data is being recorded on a 3D visualization platform that accommodates additional information from multiple channels. We provide unmatched high-throughput tomography, where the complete tomographic pipeline from measurement to 3D visualization can occur rapidly. The project was extended to offer capabilities for micro-CT, X-ray, neutron, focused ion beam, atomic electron tomography and atom probe tomography. With over 600 transmission electron microscopes worldwide and approximately 50 coming online each year, the demand and impact of an open-source tomography tool is large. Significant opportunities exist in high-tech industry, universities, and national labs to enable or enhance three-dimensional imaging at the nanoscale and bring automated high-throughput approaches that will accelerate progress in materials characterization and metrology. The project supports a service based business model by enabling lab-specific acquisition and processing customization and integration-support and development that will be provided into Phase III and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The Cylindrical Implosion Platform: Recent Results and Next Steps [Slides]

LANL has reinvested in a cylindrical implosion platform, enabling direct measurements of instability growth in convergent geometries. Scale-invariant hydrodynamic instability growth is observed in cylindrical implosions at OMEGA and NIF that varied in radial size and implosion time-scale by a factor of 3 (CR=2.25). Greatly improved NIF data at CR=5 are currently being analyzed. The cylindrical implosion platform is growing: Larger scale-4 cylinders will be fielded at the NIF; Point-projection sidelighters for the NIF implosions; Gas-filled designs should increase CR>10; Double cylinders are being pursued for FY22 and beyond; Results will aid in V&V efforts for 3D hydrodynamics in xRAGE.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Future Online Analysis Platform Workshop Report

Recent technology trends, such as the increasing focus on data management technologies and the emergence of sustainable on-demand computing and commercial cloud facilities provide initial steps and potential building blocks for creating such a compute facility. How do we fill the gap between what we have now and the capabilities we need to make the vision of an online data facility a reality? What research challenges need to be addressed – and can be addressed – in the coming 5-10 years? How should we adjust our vision if they are not solved? Is such a facility compatible with the existing and evolving exascale resources and/or how should they evolve to be compatible? How do “beyond Moore’s law” technologies enable advanced data analysis? Those are the challeges that the Future Platform workshop was organized to address. This report is organized as follows. Section 2 summarizes data challenges and patterns related to the exemplar use cases presented during the first half day of the workshop. Section 3 summarizes the requirements presented by those use cases as well as a synthesis of those requirements into a Future Platform definition achieved on the 3rd half day of the workshop (morning of the 2nd day). Section 4 includes area breakout reports from the areas on the 2nd half day of the workshop (afternoon of the 1st day). Finally Section 5 has a report on recommendation for building methodology and metrics. The report concludes in Section 6.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Fast Data Processing for Hyperspectral Sensors on Small Platforms

Hyperspectral imaging is a very promising technology for nuclear proliferation detection. However, due to size and weight restrictions, small hyperspectral platforms such as satellites and small drones lack the on-board computing resources for accurate, real-time analysis of the enormous flow of data that a continuously operating hyperspectral sensor generates. This severely limits satellite systems, which can collect far more data than what they can telemeter, and hinders the ability of all platforms to adapt their missions on the fly in response to observations. This program addresses the hyperspectral data processing challenge through development of new, fast and accurate algorithms that produce data products in real time. The algorithms circumvent the major computational bottlenecks in existing processing streams, and would be incorporated in lightweight, power-efficient single-board computer systems. The toolkit of fast algorithms will be immediately useful in current and future hyperspectral systems being built by the Government and by private industry, including drone-based systems and satellite constellations that acquire timely global imagery.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

Smart Microbial Cell Technology: A high-throughput platform to optimize biocatalysts

Los Alamos National Laboratory developed an ultra-high-throughput screening platform to engineer custom biocatalysts that enhance the rate of chemical reactions critical in pharmaceuticals, renewable energy, and environmental cleanup. Current methods to find biocatalysts are slow. This platform scans genetic variations to optimize a single enzyme or microbial cell to generate a product efficiently. It selects rare mutations needed for biocatalyst optimization orders of magnitude faster than current screening methods. A custom sensor reporter gene circuit causes cells to fluoresce when they are making the target product. When coupled to flow cytometry, a million biocatalyst variants can be screened in hours.

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

PLATFORM for Product Launch

Pecan Street Inc. (PSI) and its partners set out in 2017 to validate the PLATFORM for Product Launch, a new model for improving the effectiveness of investments in clean energy technologies and accelerating market entry of disruptive technologies. In partnership with a newly formed Innovation Advisory Council, PSI recruited fourteen companies with new hardware-based technologies that enable or create clean energy opportunities. Pecan Street carried out product evaluations and conducted market research with stakeholders and target customers to develop recommendations on product optimization opportunities for all companies, and created third party performance evaluation reports that include environmental metrics, such as water and energy savings potential, to assist in creating investment confidence and to unlock additional sources of funding, such as impact investments. Pecan Street set-up the product testing environment, performed small-batch field testing, and provided a verified third-party performance report on the product of twelve companies. PSI Street and its partners leveraged the performance evaluations and insights from the newly formed PRI toolkit to raise over $1.5M across five companies, and garner interest for private sector adoption of the PLATFORM for Product Launch.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

The Multiphysics on Advanced Platforms Project

In 2015, the Lawrence Livermore National Laboratory started development of next-generation multiphysics simulation capabilities for the National Nuclear Security Administration under the Advanced Technologies Development and Mitigation (ATDM) element of the Advanced Simulation and Computing program in collaboration with the Exascale Computing Project (ECP). A key driver for this effort across the NNSA tri-lab was the emergence of advanced high performance computing (HPC) architectures based on heterogeneous compute capabilities, including GPU based systems, as part of the national drive toward exascale computing platforms at multiple Department of Energy (DOE) facilities. Developing a multiphysics code capable of meeting the various simulation needs of the NNSA as defined by the current generation of integrated codes (or ICs), initially developed as part of the Accelerated Strategic Computing Initiative (ASCI) program beginning in 1996, and able to scale to the current 100 petaflop class pre-exascale systems, as well the forthcoming exaflop class computers, is a daunting challenge. To accomplish this ambitious goal, LLNL has embraced two key themes: use of high-order numerical methods and a modular approach to code development. The LLNL next generation effort is organized under the Multi-Physics on Advanced Platforms Project (MAPP). A foundational component of MAPP is the Axom computer science (CS) toolkit which provides infrastructure for the development of modular, performance portable, multi-physics application codes. MARBL is a next-generation application code built on the Axom base to address the modeling needs of the high energy density physics (HEDP) community for simulating high-explosive, magnetic or laser driven experiments such as inertial confinement fusion (ICF), pulsed-power magneto-hydrodynamics (MHD), equation of state (EOS) and material strength studies as part of the NNSA’s stockpile stewardship program (SSP).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Automated Cyber Security Testing Platform for Industrial Control Systems

Nuclear Power Plants (NPPs) are a complex system of coupled physics controlled by a network of Programmable Logic Controllers (PLCs). These PLCs communicate process data across the network to coordinate control actions with each other and inform the operators of process variables and control decisions. Networking the PLCs allows more effective process control and provides the operator more information which results in more efficient plant operation. This interconnectivity creates new security issues, as operators have more access to the plant controls, so will bad actors. As plant networks become more digitized and encompass more sophisticated controllers, the network surface exposed to cyber interference grows. Understanding the dynamics of these coupled systems of physics, control logic, and network communications is critical to their protection. The research into the cybersecurity of the Operational Technologies of NPPs is developing and requires a platform that can allow high fidelity physics simulations to interact with digital networks of controllers. This will require three main components: a network simulation environment, a physics simulator, and virtual PLCs (vPLC) that represent typical industry hardware. A platform that incorporates these three components to provide the most accurate representation of actual NPP networks and controllers is developed in this paper.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Integrated process for commercial production of farnesene, a versatile platform chemical, from domestic lignocellulosic feedstock (Final Report)

Final Report summaries of integrated process for commercial production of farnesene, a versatile platform chemical, from domestic lignocellulosic feedstock project. The prime contractor for this project was Amyris, Inc. and the subcontractors were Renmatix Inc. and Total Raffinage Chimie. The aim of the MegaBio program has been to develop a cost-effective and environmentally sustainable process for manufacturing the versatile platform chemical farnesene from renewable cellulosic feedstocks in the United States.

09 BIOMASS FUELS↗
DOE OSTI2021

Surrogate Model of Flexible Research Platform EnergyPlus Models to Enable Sensitivity Analysis

This letter report describes the surrogate models developed from the EnergyPlus model of Oak Ridge National Laboratory’s Flexible Research Platform. Two data-driven black-box models were developed, and the outputs of the surrogate models were compared with the EnergyPlus model. The two models developed are a multilayer perceptron deep learning model, and a long short-term memory (LSTM) neural network model. The three factors for selecting the black-box models are scalability, computation time, and accuracy. A total of 107 input variables were the dominant variables in determining the outputs of building energy consumptions and thermal comfort. A total of 54 output variables were identified as the prediction targets, including the system- and zone-level outputs. The large set of the simulation cases were generated by integrating sensor errors into an emulator based on EnergyPlus and Python EMS, which includes advanced control sequences from ASHRAE Guideline 36-2018: High-Performance Sequences of Operation. The surrogate models were developed based on a set of large-scale simulation runs (i.e., 4,000 runs) on a cloud platform. The comparison analysis shows that the two black-box models had good accuracy for predicting new outputs for sensitivity analysis using the root mean square error metric. As a next step, the developed surrogate models will be used to perform sensitivity analysis for different sensor impacts (e.g., sensor types, sensor locations).

42 ENGINEERING↗
DOE OSTI2021

High-Luminance LED Platform for Improved Efficacy in Directional Applications (Final Technical Report)

In this project, Lumileds developed a platform of high-luminance LEDs and LED light engines to increase efficacy and reduce energy consumption of directional lighting applications. The platform was developed through innovations in three key areas: (1) epi and device architectures optimized for high drive current density, breaking through the tradeoff in efficacy (lm/W) vs. emittance (lm/mm 2 ) exhibited by state-of-the-art products; (2) a compact chip-scale package allowing high packing density and thus high overall luminance in multi-emitter arrays; and (3) phosphor technology to enable correlated color temperature (CCT) tuning in multi-emitter arrays with optimized LED utilization, efficacy, color uniformity and color quality. Directional indoor and outdoor lighting applications make up a major portion of the total lighting energy consumption in the U.S, accounting for >40% of the energy savings potential of solid-state lighting. Success of this project helps accelerate the realization of these energy savings both through higher system efficacy and adoption due to new functionality, and thus contributes significantly to realizing the DOE Lighting program goals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

A Platform-Independent X-ray Diffraction Diagnostic for Phase Transition Kinetics in Traditional and Synthetic Microstructure Materials (LDRD Project 213088 Final Report)

Pulsed-power generators using the magnetic loading technique are able to produce well-controlled continuous ramp compression of condensed matter for high-pressure equation-of-state studies. X-ray diffraction (XRD) data from dynamically compressed samples provide direct measurements of the elastic compression of the crystal lattice, onset of plastic flow, strength-strain rate dependence, structural phase transitions, and density of crystal defects such as dislocations. Here, we present a cost effective, compact X-ray source for XRD measurements on pulsed-power-driven ramp-loaded samples. This combination of magnetically-driven ramp compression of materials with single, short-pulse XRD diagnostic will be a powerful capability for the dynamic materials community. The success in fielding this new XRD diagnostic dramatically improves our predictive capability and understanding of rate-dependent behavior at or near phase transition. As Sandia plans the next-generation pulse-power driver platform, a key element needed to deliver new state-of-the-art experiments will be having the necessary diagnostic tools to probe new regimes and phenomena. These diagnostics need to be as versatile, compact, and portable as they are powerful. The development of a platform-independent XRD diagnostic gives Sandia researchers a new window to study the microstructure and phase dynamics of materials under load. This project has paved the way for phase transition research in a variety of materials with mission interest.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Development of Membrane Platforms to Interrogate Host-Pathogen Interactions

Membrane fusion is a critical step in enveloped virus entry and infection; however, molecular understanding of enveloped virus entry and treatment options remain limited. In recent decades, advances in imaging have facilitated the development of methods to study single virus events and membrane organization providing insight towards entry mechanisms. Through these advances, membrane composition and organization have been shown to play a critical role in the entry process. This LDRD uses model membrane platforms and basic biophysics to investigate entry mechanisms of enveloped viruses and understand membrane-based delivery technologies. This team has established foundations for using membrane-based platforms and biophysical techniques at Sandia to characterize membrane fusion.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

MIRACL Co-Simulation Platform Lab assets and tools integration

Pacific Northwest National Laboratory's (PNNL) co-simulation platform (CSP) for the Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) project, also known as MIRACL-CSP, is a functional layer designed and developed to oversee the operational exchanges of data at the application level to and from different resources residing on the MIRACL Data Hub shared platform. MIRACL-CSP allows virtual interactions between various data hub resources during co-simulation runtime.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Development of Anabaena 33047, a Fast-Growing N 2 -Fixing Cyanobacterium, as a Carbon Neutral Bioproduction Platform

Cyanobacteria, oxygenic photosynthetic prokaryotes, are emerging as promising platforms for cost effective conversion of sunlight and CO 2 into high value end products. Anabaena sp. ATCC 33047, a heterocystous cyanobacterium, stands out in this category of fast-growing cyanobacteria for its ability to utilize atmospheric N 2 in addition to CO 2 and generate biomass at unprecedented rates. Developing such a strain as a chassis can eliminate the need for fixed nitrogen in bioproduction systems, a significant step towards replacement of petroleum derived products. Our work aimed to develop Anabaena 33047 into such a bioproduction platform. Despite its many appealing traits, Anabaena 33047 remained largely unexplored due to its recalcitrance to any genetic manipulation. During this project, we have developed a method that has enabled targeted genome modification of this strain. We also constructed a genome scale metabolic model i AnC892, which captures the diazotrophic life cycle of Anabaena 33047 by accounting for both vegetative and heterocyst cell types. The model provided insight into the importance of light dependent electron transport in the heterocyst and revealed pathway combinations that can supply reducing equivalents and ATP in the appropriate ratio for optimal N2 fixation. To validate the existing metabolic models and to have a better understanding of the metabolism of Anabaena 33047 under different growth conditions, we performed a series of stable-isotope tracing experiments and quantified metabolic fluxes using state-of-the-art tools for 13C-metabolic flux analysis. Using our novel engineering strategy and based on our model predictions, we performed targeted deletion in the strain and generated a mutant with modified light harvesting properties in heterocysts. The mutant exhibited better light utilization and increased rates of nitrogen fixation. Overall, this project has laid the foundation for developing the non-model cyanobacterium Anabaena 33047 into a highly efficient chassis for conversion of solar energy, atmospheric CO 2 and N 2 into high value bio products.

09 BIOMASS FUELS↗
DOE OSTI2023

Data Archive and Portal (DAP) Platform for Solid Phase Processing Technologies

The scale and speed of data generated by modern scientific experiments have constantly challenged the research community to store, curate, manage and optimally use it to drive scientific discoveries. In this work, we have developed a data archive and portal (DAP) platform including analytics capabilities to collect, curate, and manage data and metadata stream for solid phase processing (SPP) techniques. We successfully hosted around ~347K files of data related to processing parameters, microscopic images, and spectroscopic data related to solid phase processing. The DAP platform for SPP will establish an enduring capability to support machine learning and grow collaboration at the intersection of materials science and data science.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Helium-3 Piping and Gas Handling Implementation for the Colossus milli-Kelvin Platform at Fermilab

Colossus is a large millikelvin platform that has a two-meter diameter mixing chamber plate. This uniquely large millikelvin platform utilizes a cryogenics plant to maintain progressively lower temperatures at each of the three upper stages and precool the lower three stages of the system. At the millikelvin stages, Colossus employs multiple commercially available dilution units to achieve millikelvin temperatures at the 100 mK and 20 mK stages. The incoming helium-3/helum-4 process fluid mixture for each dilution unit flows through tubes wrapped around copper posts attached to each of the upper stages of the system. These tubes function as capillary heat exchanger to reduce the temperature of the incoming helium mixture to the appropriate temperature at each stage.

James, C.↗
DOE OSTI2023

Pressurized-Water Reactor Core Design Demonstration with Genetic Algorithm Based Multi-Objective Plant Fuel Reload Optimization Platform

LWRS M3 milestone report due September 15, 2023. This report summarizes development and demonstration activities of PRLO optimization platform built in Risk Analysis and Virtual ENviroment (RAVEN), specifically: (1) Improvement of multi-objective non-dominated sorting genetic algorithm II (NSGA-II) to handle large size of objectives and constraints, (2) Demonstration of pressurized water reactor core design with NSGA-II multi-objective optimization platform, and (3) Single-objective optimized core design including system analysis and fuel performance feedback.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗