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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

In-situ synchrotron micro-diffraction study of surface, interface, grain structure, and strain/stress evolution during Sn whisker/hillock formation

We have performed X-ray synchrotron micro-diffraction measurements to study the processes controlling the formation of hillocks and whiskers in Sn layers on Cu. The studies were done in real-time on Sn layers that were electro-deposited immediately before the X-ray measurements were started. This enabled a region of the sample to be monitored from the as-deposited state until after a hillock feature formed. In addition to measuring the grain orientation and deviatoric strain (via Laue diffraction), the X-ray fluorescence was monitored to quantify the evolution of the Sn surface morphology and the formation of intermetallic compound (IMC) at the Sn-Cu interface. The results capture the simultaneous growth of the feature and the corresponding film stress, grain orientation, and IMC formation. The observations are compared with proposed mechanisms for whisker/hillock growth and nucleation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

The NREL Sensor Laboratory: Status and Future Directions for Hydrogen Detection

The NREL Hydrogen Sensor Laboratory was commissioned in 2010 as a resource for the national and international hydrogen community to ensure the availability and proper use of hydrogen sensors. Since then, the Sensor Laboratory has provided unbiased verification of hydrogen sensor performance for sensor developers, end-users, and regulatory agencies and has also provided active support for numerous code and standards development organizations. Although sensor performance assessment remains a core capability, the mission of the NREL Sensor Laboratory has expanded toward a more holistic approach regarding the role of hydrogen detection and its implementation strategy for both assurance of facility safety as well as for process control applications. Active monitoring for detection of unintended releases has been identified by the NFPA 2 Storage Task Group as a viable approach for improving facility safety and lowering setbacks. The current research program for the Sensor Laboratory addresses both conventional and advanced developing detection strategies in response to the emerging large-scale markets, such as those envisioned by H2@Scale. These emerging hydrogen applications may require alternative detection strategies that supplement and may ultimately supplant the use of traditional sensors for monitoring hydrogen releases. Research focus areas for the NREL Sensor Laboratory now encompasses the characterization of released hydrogen behavior to optimize detection strategies for both indoor and outdoor applications, advanced methods of hydrogen leak detection such as hydrogen wide area monitoring approaches for large scale and distributed applications, the incorporation of active monitoring as a risk reduction strategy to improve safety at hydrogen facilities, and continuing support of hydrogen safety codes and standards. In addition to assurance of safety, detection will be critical for process control applications, such as hydrogen fuel quality verification for fuel cell vehicle applications and for monitoring and controlling of hydrogen-natural gas blend composition.

codes and standards↗
DOE OSTI2024

Hydrogen Detection Strategies to Support H2@SCALE - The NREL Sensor Laboratory

Hydrogen represents a major pathway to decarbonize and stabilize the national and international energy industry and select manufacturing markets. To facilitate the development of hydrogen markets, the US Department of Energy initiated H2@Scale to bring together stakeholders to advance affordable hydrogen production, transport, storage, and utilization to increase revenue opportunities in multiple energy sectors. One major impediment to hydrogen implementation is cost. To expedite the use of hydrogen in energy and other markets, the United States announced in 2021 the Hydrogen Shot, which seeks to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). As the cost of hydrogen drops, new applications will emerge that will require unique configurations of existing equipment and infrastructure, and eventually lead to advances in the generation and utilization of hydrogen. As the hydrogen economy expands, sensors and detection methods will need to adapt to changing infrastructure demands to address the primary targets of health & safety, emissions monitoring, and process control. The NREL Sensor Laboratory is playing a pivotal role in advancing the use of hydrogen sensors and detection methodologies in each of these categories to support DOE's mission for safe and efficient utilization in emerging markets. Health & safety monitors are required to ensure that operators and facilities can react to unintended hydrogen releases, either as GH2, LH2, or as a constituent of blends (e.g., natural gas or ammonia). Current detection methodologies focus on safety applications to detect near its lower flammable limit (4 vol %), and typically include point sensors in applications such as fixed or mobile detectors (e.g., personal gas monitors). Methodologies amenable for area detection include acoustic, emerging optical imaging methods, and flame detectors. Comparable detection strategies can be utilized for emissions monitoring and quantization, however few methods can simultaneously cover both low (emissions) and high (health & safety) levels. Deployment of emission level detectors will be required to 1) reduce product loss through small but potentially significant leaks from an environmental or cost perspective, 2) reduce downtime of high demand systems by early identification of eminent system failures (leaks through pump or compressor seals indicative of impending failure), and 3) address potential emission monitoring requirements that may be set by regulating bodies. The first two points should be adopted by industry to reduce the cost-of-goods-sold. The third main category for hydrogen detection relates to process control and may be advantageous for many existing applications. Two main applications are emerging. For example, the purity requirements for hydrogen that is dispensed from refueling systems for hydrogen fuel cell electric vehicles (FCEV) is rigorously regulated by the Standard SAE J2719, which prescribes maximum allowable levels of multiple impurities in the hydrogen fuel and must be verified by a regulatory body. Hydrogen contaminant detectors (HCD) integrated to the fueling station can assure this compliance. HCDs must be able operate in 100% H2 backgrounds and be able to distinguish between multiple contaminants at low ppm to low ppb levels. Secondly, as a strategy to decarbonize the natural gas grid, there are proposals to blend hydrogen with natural gas. This blending will affect transport applications (pipeline infrastructure), stationary combustion systems (turbines), and consumer and commercial appliances. In the short-term, hydrogen levels up to 20% are proposed. Variations in the hydrogen level can have dramatic impact on the combustion process and on the potential response of safety sensors. These mixtures may be regulated so that the concentration at a delivery point must be monitored with high precision. However, routine maintenance may introduce background gases such as ambient air (with water) or maintenance gases (introduced with welding processes or adhesive outgassing.) Therefore, the detection methodology must be robust enough to recover or respond to various contaminants. Several reviews can be found in literature addressing sensing and detection technologies, including their limitations and applications. However, for most applications, limitations can be alleviated by combining various detection techniques either through system integration or implementation of machine learning methods (artificial intelligence). In this presentation, we will discuss several applications, highlight their current approach for hydrogen detection, and suggest detection strategies to supplement their limitations.

ENERGY STORAGE,HYDROGEN↗
DOE OSTI2015

Optical emission diagnostics of plasmas in chemical vapor deposition of single-crystal diamond

A key aspect of single crystal diamond growth via microwave plasma chemical vapor deposition is in-process control of the local plasma–substrate environment, that is, plasma gas phase concentrations of activated species at the plasma boundary layer near the substrate surface. Emission spectra of the plasma relative to the diamond substrate inside the microwave plasma reactor chamber have been analyzed via optical emission spectroscopy. The spectra of radical species such as CH, C{sub 2}, and H (Balmer series) important for diamond growth were identified and analyzed. The emission intensities of these electronically excited species were found to be more dependent on operating pressure than on microwave power. Plasma gas temperatures were calculated from measurements of the C{sub 2} Swan band (d{sup 3}Π → a{sup 3}Π transition) system. The plasma gas temperature ranges from 2800 to 3400 K depending on the spatial location of the plasma ball, microwave power and operating pressure. Addition of Ar into CH{sub 4}+H{sub 2} plasma input gas mixture has little influence on the Hα, Hβ, and Hγ intensities and single-crystal diamond growth rates.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Use of multiscale zirconium alloy deformation models in nuclear fuel behavior analysis

Accurate prediction of cladding mechanical behavior is a key aspect of modeling nuclear fuel behavior, especially for conditions of pellet-cladding interaction (PCI), reactivity-initiated accidents (RIA), and loss of coolant accidents (LOCA). Current approaches to fuel performance modeling rely on empirical constitutive models for cladding creep, growth and plastic deformation, which are limited to the materials and conditions for which the models were developed. To improve upon this approach, a microstructurally-based zirconium alloy mechanical deformation analysis capability is being developed within the United States Department of Energy Consortium for Advanced Simulation of Light Water Reactors (CASL). Specifically, the viscoplastic self-consistent (VPSC) polycrystal plasticity modeling approach, developed by Lebensohn and Tomé [1], has been coupled with the BISON engineering scale fuel performance code to represent the mechanistic material processes controlling the deformation behavior of light water reactor (LWR) cladding. A critical component of VPSC is the representation of the crystallographic nature (defect and dislocation movement) and orientation of the grains within the matrix material and the ability to account for the role of texture on deformation. A future goal is for VPSC to obtain information on reaction rate kinetics from atomistic calculations to inform the defect and dislocation behavior models described in VPSC. The multiscale modeling of cladding deformation mechanisms allowed by VPSC far exceed the functionality of typical semi-empirical constitutive models employed in nuclear fuel behavior codes to model irradiation growth and creep, thermal creep, or plasticity. This paper describes the implementation of an interface between VPSC and BISON and provides initial results utilizing the coupled functionality.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

The case for digital twins in metal additive manufacturing

The digital twin (DT) is a relatively new concept that is finding increased acceptance in industry. A DT is generally considered as comprising a physical entity, its virtual replica, and two-way digital data communications in-between. Its primary purpose is to leverage the process intelligence captured within digital models—or usually their faster-solving surrogates—towards generating increased value from the physical entities. The surrogate models are created using machine learning based on data obtained from the field, experiments and digital models, which may be physics-based or statistics-based. Anomaly detection and correction, and diagnostic closed-loop process control are examples of how a process DT can be deployed. In the manufacturing industry, its use can achieve improvements in product quality and process productivity. Metal additive manufacturing (AM) stands to gain tremendously from the use of DTs. This is because the AM process is inherently chaotic, resulting in poor repeatability. However, a DT acting in a supervisory role can inject certainty into the process by actively keeping it within bounds through real-time control commands. Closed-loop feedforward control is achieved by observing the process through sensors that monitor critical parameters and, if there are any deviations from their respective optimal ranges, suitable corrective actions are triggered. The type of corrective action (e.g. a change in laser power or a modification to the scanning speed) and its magnitude are determined by interrogating the surrogate models. Because of their artificial intelligence (AI)-endowed predictive capabilities, which allow them to foresee a future state of the physical twin (e.g. the AM process), DTs proactively take context-sensitive preventative steps, whereas traditional closed-loop feedback control is usually reactive. Apart from assisting a build process in real-time, a DT can help with planning the build of a part by pinpointing the optimum processing window relevant to the desired outcome. Again, the surrogate models are consulted to obtain the required information. In this article, we explain how the application of DTs to the metal AM process can significantly widen its application space by making the process more repeatable (through quality assurance) and cheaper (by getting builds right the first time).

36 MATERIALS SCIENCE↗
DOE OSTI2017

Fabrication of oxide dispersion strengthened bond coats with low Al 2 O 3 content [Fabrication of ODS bond coats with low Al 2 O 3 content]

Here, nanoscale oxide dispersions have long been used to increase the oxidation and wear resistance of alloys used as bond coatings in thermal barrier coatings. Their manufacturing via mechanical alloying is often accompanied by difficulties regarding their particle size, homogeneous distribution of the oxide dispersions inside the powder, involving considerable costs, due to cold welding of the powder during milling. A significant improvement in this process can be achieved by the use of process control agent (PCA) to achieve the critical balance between cold welding and fracturing, thereby enhancing the process efficiency. In this investigation, the influence of the organic additive stearic acid on the manufacturing process of Al 2 O 3 -doped CoNiCrAlY powder was investigated. Powders were fabricated via mechanical alloying at different milling times and PCA concentrations. The results showed a decrease in particle size, without hindering the homogeneous incorporation of the oxide dispersions. Two powders manufactured with 0.5 and 1.0 wt.% PCA were deposited by high velocity oxygen fuel (HVOF) spraying. Results showed that a higher content of elongated particles in the powder with the higher PCA content led to increased surface roughness, porosity and decreased coating thickness, with areas without embedded oxide particles.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Controlling atomistic processes on Pb films via quantum size effects and lattice rotation

The two main techniques used to record the data in this dissertation were Spot Profile Analysis - Low Energy Electron Diffraction (SPA-LEED) and Scanning Tunneling Microscopy (STM). A specific data analysis technique for LEED data called G(S) curves is described in depth. G(S) curves can provide a great deal of structural information about the surface; including step heights, island size, and island separation. The effects of quantum size effects (QSE) on the diffusion and critical island sizes of Pb and In on Pb films are reported. Pb depositions on the 2D In phases {radical}3 and {radical}31 to see how the phases affect the Pb growth and its strong QSE are reported.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Annual Report: Carbon Capture Simulation Initiative (CCSI) (30 September 2013)

The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and academic institutions that is developing and deploying state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. The CCSI Toolset will provide end users in industry with a comprehensive, integrated suite of scientifically validated models, with uncertainty quantification (UQ), optimization, risk analysis and decision making capabilities. The CCSI Toolset incorporates commercial and open-source software currently in use by industry and is also developing new software tools as necessary to fill technology gaps identified during execution of the project. Ultimately, the CCSI Toolset will (1) enable promising concepts to be more quickly identified through rapid computational screening of devices and processes; (2) reduce the time to design and troubleshoot new devices and processes; (3) quantify the technical risk in taking technology from laboratory-scale to commercial-scale; and (4) stabilize deployment costs more quickly by replacing some of the physical operational tests with virtual power plant simulations. CCSI is led by the National Energy Technology Laboratory (NETL) and leverages the Department of Energy (DOE) national laboratories’ core strengths in modeling and simulation, bringing together the best capabilities at NETL, Los Alamos National Laboratory (LANL), Lawrence Berkeley National Laboratory (LBNL), Lawrence Livermore National Laboratory (LLNL), and Pacific Northwest National Laboratory (PNNL). The CCSI’s industrial partners provide representation from the power generation industry, equipment manufacturers, technology providers and engineering and construction firms. The CCSI’s academic participants (Carnegie Mellon University, Princeton University, West Virginia University, Boston University and the University of Texas at Austin) bring unparalleled expertise in multiphase flow reactors, combustion, process synthesis and optimization, planning and scheduling, and process control techniques for energy processes. During Fiscal Year (FY) 13, CCSI announced the initial release of its first set of computational tools and models during the October 2012 meeting of its Industry Advisory Board. This initial release led to five companies licensing the CCSI Toolset under a Test and Evaluation Agreement this year. By the end of FY13, the CCSI Technical Team had completed development of an updated suite of computational tools and models. The list below summarizes the new and enhanced toolset components that were released following comprehensive testing during October 2013. 1. FOQUS. Framework for Optimization and Quantification of Uncertainty and Sensitivity. Package includes: FOQUS Graphic User Interface (GUI), simulation-based optimization engine, Turbine Client, and heat integration capabilities. There is also an updated simulation interface and new configuration GUI for connecting Aspen Plus or Aspen Custom Modeler (ACM) simulations to FOQUS and the Turbine Science Gateway. 2. A new MFIX-based Computational Fluid Dynamics (CFD) model to predict particle attrition. 3. A new dynamic reduced model (RM) builder, which generates computationally efficient RMs of the behavior of a dynamic system. 4. A completely re-written version of the algebraic surrogate model builder for optimization (ALAMO). The new version is several orders of magnitude faster than the initial release and eliminates the MATLAB dependency. 5. A new suite of high resolution filtered models for the hydrodynamics associated with horizontal cylindrical objects in a flow path. 6. The new Turbine Science Gateway (Cluster), which supports FOQUS for running multiple simulations for optimization or UQ using a local computer or cluster. 7. A new statistical tool (BSS-ANOVA-UQ) for calibration and validation of CFD models. 8. A new basic data submodel in Aspen Plus format for a representative high viscosity capture solvent, 2-MPZ system. 9. An updated RM tool for CFD (REVEAL) that can create a RM from MFIX. A new lightweight, stand-alone version will be available in late 2013. 10. An updated RM integration tool to convert the RM from REVEAL into a CAPE-OPEN or ACM model for use in a process simulator. 11. An updated suite of unified steady-state and dynamic process models for solid sorbent carbon capture included bubbling fluidized bed and moving bed reactors. 12. An updated and unified set of compressor models including steady-state design point model and dynamic model with surge detection. 13. A new framework for the synthesis and optimization of coal oxycombustion power plants using advanced optimization algorithms. This release focuses on modeling and optimization of a cryogenic air separation unit (ASU). 14. A new technical risk model in spreadsheet format. 15. An updated version of the sorbent kinetic/equilibrium model for parameter estimation for the 1st generation sorbent model. 16. An updated process synthesis superstructure model to determine optimal process configurations utilizing surrogate models from ALAMO for adsorption and regeneration in a solid sorbent process. 17. Validation models for NETL Carbon Capture Unit utilizing sorbent AX. Additional validation models will be available for sorbent 32D in 2014. 18. An updated hollow fiber membrane model and system example for carbon capture. 19. An updated reference power plant model in Thermoflex that includes additional steam extraction and reinjection points to enable heat integration module. 20. An updated financial risk model in spreadsheet format.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2015

Office of River Protection Advanced Low-Activity Waste Glass Research and Development Plan

The U.S. Department of Energy Office of River Protection (ORP) has initiated and leads an integrated Advanced Waste Glass (AWG) program to increase the loading of Hanford tank wastes in glass while meeting melter lifetime expectancies and process, regulatory, and product performance requirements. The integrated ORP program is focused on providing a technical, science-based foundation for making key decisions regarding the successful operation of the Hanford Tank Waste Treatment and Immobilization Plant (WTP) facilities in the context of an optimized River Protection Project (RPP) flowsheet. The fundamental data stemming from this program will support development of advanced glass formulations, key product performance and process control models, and tactical processing strategies to ensure safe and successful operations for both the low-activity waste (LAW) and high-level waste vitrification facilities. These activities will be conducted with the objective of improving the overall RPP mission by enhancing flexibility and reducing cost and schedule.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Office of River Protection Advanced Low-Activity Waste Glass Research and Development Plan

The U.S. Department of Energy Office of River Protection (ORP) has initiated and leads an integrated Advanced Waste Glass (AWG) program to increase the loading of Hanford tank wastes in glass while meeting melter lifetime expectancies and process, regulatory, and product performance requirements. The integrated ORP program is focused on providing a technical, science-based foundation for making key decisions regarding the successful operation of the Hanford Tank Waste Treatment and Immobilization Plant (WTP) facilities in the context of an optimized River Protection Project (RPP) flowsheet. The fundamental data stemming from this program will support development of advanced glass formulations, key product performance and process control models, and tactical processing strategies to ensure safe and successful operations for both the low-activity waste (LAW) and high-level waste vitrification facilities. These activities will be conducted with the objective of improving the overall RPP mission by enhancing flexibility and reducing cost and schedule. The purpose of this advanced LAW glass research and development plan is to identify the near-term, mid-term, and longer-term research and development activities required to develop and validate advanced LAW glasses, property-composition models and their uncertainties, and an advanced glass algorithm to support WTP facility operations, including both Direct Feed LAW and full pretreatment flowsheets. Data are needed to develop, validate, and implement 1) new glass property-composition models and 2) a new glass formulation algorithm. Hence, this plan integrates specific studies associated with increasing the Na2O and SO3/halide concentrations in glass, because these components will ultimately dictate waste loadings for LAW vitrification. Of equal importance is the development of an efficient and economic strategy for 99Tc management. Specific and detailed studies are being implemented to understand the fate of Tc throughout the WTP flowsheet and the underlying mechanisms that dictate its partitioning between streams within the LAW vitrification facility. These studies are aimed at increasing the single-pass Tc retention in glass and the potential use of high-temperature mineral phases to capture Tc. The Tc-bearing mineral phases would be thermally stable and resistant to Tc release during feed melting reactions or they could serve as alternative waste forms. The LAW glass research and development is focused on reducing the total volume of LAW glass produced and minimizing the impact of (or potentially eliminating) the need for recycle.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Final Technical Report: The effects of climate, forest age, and disturbance history on carbon and water processes at AmeriFlux sites across gradients in Pacific Northwest forests

Investigate the effects of disturbance and climate variables on processes controlling carbon and water processes at AmeriFlux cluster sites in semi-arid and mesic forests in Oregon. The observations were made at three existing and productive AmeriFlux research sites that represent climate and disturbance gradients as a natural experiment of the influence of climatic and hydrologic variability on carbon sequestration and resulting atmospheric CO 2 feedback that includes anomalies during the warm/ dry phase of the Pacific Decadal Oscillation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Co-Decontamination Dynamic Modeling to Support the Experimental Campaign

The Co-Decontamination (CoDCon) Demonstration experiment at Pacific Northwest National Laboratory (PNNL) is designed to test the separation of a mixed U and Pu product from dissolved spent nuclear fuel. The primary purpose of the project is to demonstrate control of the Pu/U ratio throughout the entire process without producing a pure Pu stream. In addition, the project is quantifying the accuracy and precision to which a Pu/U mass ratio can be achieved. The system includes an on-line monitoring system using spectroscopy to monitor the ratios throughout the process. A dynamic model of the CoDCon flowsheet and the on-line monitoring system was developed to augment the experimental work. This model is based in MATLAB Simulink and provides the ability to expand the range of scenarios that can be examined for process control and determine overall measurement uncertainty. Experimental results have been used to inform and benchmark the model so that it can accurately simulate various transient scenarios. The results of the experimental benchmarking are presented here along with modeled scenarios to demonstrate the control and process monitoring of the system.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗