Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Process Scaling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Technology for the Recovery of Lithium from Geothermal Brines

Lithium is the principal component of high-energy-density batteries and is a critical material necessary for the economy and security of the United States. Brines from geothermal power production have been identified as a potential domestic source of lithium; however, lithium-rich geothermal brines are characterized by complex chemistry, high salinity, and high temperatures, which pose unique challenges for economic lithium extraction. The purpose of this paper is to examine and analyze direct lithium extraction technology in the context of developing sustainable lithium production from geothermal brines. In this paper, we are focused on the challenges of applying direct lithium extraction technology to geothermal brines; however, applications to other brines (such as coproduced brines from oil wells) are considered. The most technologically advanced approach for direct lithium extraction from geothermal brines is adsorption of lithium using inorganic sorbents. Other separation processes include extraction using solvents, sorption on organic resin and polymer materials, chemical precipitation, and membrane-dependent processes. The Salton Sea geothermal field in California has been identified as the most significant lithium brine resource in the US and past and present efforts to extract lithium and other minerals from Salton Sea brines were evaluated. Extraction of lithium with inorganic molecular sieve ion-exchange sorbents appears to offer the most immediate pathway for the development of economic lithium extraction and recovery from Salton Sea brines. Other promising technologies are still in early development, but may one day offer a second generation of methods for direct, selective lithium extraction. Initial studies have demonstrated that lithium extraction and recovery from geothermal brines are technically feasible, but challenges still remain in developing an economically and environmentally sustainable process at scale.

58 GEOSCIENCES↗
DOE OSTI2021

Drop Size Distribution Variability in Central Argentina during RELAMPAGO-CACTI

The Remote sensing of Electrification, Lightning, And Meso-scale/micro-scale Processes with Adaptive Ground Observations (RELAMPAGO) and the Cloud, Aerosol, and Complex Terrain Interactions Experiment Proposal (CACTI) field campaigns provided an unprecedented thirteen-disdrometer dataset in Central Argentina during the Intensive (IOP, 15 November to 15 December 2018) and Extended (EOP, 15 October 2018 to 30 April 2019) Observational Periods. The drop size distribution (DSD) parameters and their variability were analyzed across the region of interest, which was divided into three subregions characterized by the differing proximity to the Sierras de Córdoba (SDC), in order to assess the impact of complex terrain on the DSD parameters. A rigorous quality control of the data was first performed. The frequency distributions of DSD-derived parameters were analyzed, including the normalized intercept parameter (logN w ), the mean volume diameter (D 0 ), the mean mass diameter (D m ), the shape parameter (μ), the liquid water content (LWC), and the rain rate (R). The region closest to the SDC presented higher values of logN w , lower D 0 , and higher μ, while the opposite occurred in the farthest region, i.e., the concentration of small drops decreased while the concentration of bigger drops increased with the distance to the east of the SDC. Furthermore, the region closest to the SDC showed a bimodal distribution of D 0 : the lower values of D 0 were associated with higher values of logN w and were found more frequently during the afternoon, while the higher D 0 were associated with lower logN w and occurred more frequently during the night. The data were analyzed in comparison to the statistical analysis of Dolan et al. 2018 and sorted according to the classification proposed in the cited study. The logN w -D 0 and LWC-D 0 two-dimensional distributions allowed further discussion around the applicability of other mid-latitude and global precipitation classification schemes (startiform/convection) in the region of interest. Finally, three precipitation case studies were analyzed with supporting polarimetric radar data in order to relate the DSD characteristics to the precipitation type and the microphysical processes involved in each case.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Future Cost Benefits Analysis for Electrified Vehicles from Advances Due to U.S. Department of Energy Targets

The U.S. Department of Energy’s Vehicle Technologies Office (DOE-VTO) supports research and development (R&D), as well as deployment of efficient and sustainable transportation technologies, that will improve energy efficiency and fuel economy and enable America to use less petroleum. To accelerate the creation and adoption of new technologies, DOE-VTO has developed specific targets for a wide range of powertrain technologies (e.g., engine, battery, electric machine, lightweighting, etc.). This paper quantifies the impact of VTO R&D on vehicle energy consumption and cost compared to expected historical improvements across vehicle classes, powertrains, component technologies and timeframes. We have implemented a large scale simulation process to develop and simulate tens of thousands of vehicles on U.S. standard driving cycles using Autonomie, a vehicle simulation tool developed by Argonne National Laboratory. Results demonstrate significant additional reductions in both cost and energy consumption due to the existence of VTO R&D targets compared to predicted historical trends. It is observed that, over time, the fuel consumption of different electrified vehicles is expected to decrease by 40–50% and a reduction of 45–55% for vehicle manufacturing costs owing to significant improvements through various VTO R&D targets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Modeling biological nitrogen fixation in global natural terrestrial ecosystems

Biological nitrogen fixation plays an important role in the global nitrogen cycle. However, the fixation rate has been usually measured or estimated at a particular observational site. To quantify the fixation amount at the global scale, process-based models are needed. This study develops a biological nitrogen fixation model to quantitatively estimate the nitrogen fixation rate by plants in a natural environment. The revised nitrogen module better simulates the nitrogen cycle in comparison with our previous model that has not considered the fixation effects. The new model estimates that tropical forests have the highest fixation rate among all ecosystem types, which decreases from the Equator to the polar region. The estimated nitrogen fixation in global terrestrial ecosystems is 61.5 Tg N yr-1 with a range of 19.8–107.9 Tg N yr-1 in the 1990s. Our estimates are relatively low compared to some early estimates using empirical approaches but comparable to more recent estimates that involve more detailed processes in their modeling. Furthermore, the contribution of nitrogen made by biological nitrogen fixation depends on ecosystem type and climatic conditions. This study highlights that there are relatively large effects of biological nitrogen fixation on ecosystem nitrogen cycling. and the large uncertainty of the estimation calls for more comprehensive understanding of biological nitrogen fixation. More direct observational data for different ecosystems are in need to improve future quantification of fixation and its impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Evaluation of global teleconnections in CMIP6 climate projections using complex networks

In climatological research, the evaluation of climate models is one of the central research subjects. As an expression of large-scale dynamical processes, global teleconnections play a major role in interannual to decadal climate variability. Their realistic representation is an indispensable requirement for the simulation of climate change, both natural and anthropogenic. Therefore, the evaluation of global teleconnections is of utmost importance when assessing the physical plausibility of climate projections. We present an application of the graph-theoretical analysis tool δ-MAPS, which constructs complex networks on the basis of spatio-temporal gridded data sets, here sea surface temperature and geopotential height at 500 hPa. Complex networks complement more traditional methods in the analysis of climate variability, like the classification of circulation regimes or empirical orthogonal functions, assuming a new non-linear perspective. While doing so, a number of technical tools and metrics, borrowed from different fields of data science, are implemented into the δ-MAPS framework in order to overcome specific challenges posed by our target problem. Those are trend empirical orthogonal functions (EOFs), distance correlation and distance multicorrelation, and the structural similarity index. δ-MAPS is a two-stage algorithm. In the first place, it assembles grid cells with highly coherent temporal evolution into so-called domains. In a second step, the teleconnections between the domains are inferred by means of the non-linear distance correlation. We construct 2 unipartite and 1 bipartite network for 22 historical CMIP6 climate projections and 2 century-long coupled reanalyses (CERA-20C and 20CRv3). Potential non-stationarity is taken into account by the use of moving time windows. The networks derived from projection data are compared to those from reanalyses. Our results indicate that no single climate projection outperforms all others in every aspect of the evaluation. But there are indeed models which tend to perform better/worse in many aspects. Differences in model performance are generally low within the geopotential height unipartite networks but higher in sea surface temperature and most pronounced in the bipartite network representing the interaction between ocean and atmosphere.

58 GEOSCIENCES↗
DOE OSTI2025

NCAR-RAL Surface Hydrometeorological Observation Network Data for LASSO-CACTI Overview Paper

This data set contains the 15 minute resolution surface meteorology and soils data from the 15 NCAR/RAL weather stations that were operated around central Argentina during the RELAMPAGO (Remote sensing of Electrification, Lightning, And Meso-scale/micro-scale Processes with Adaptive Ground Observations) Extended Observing Period (EOP). Data providence, citation, and acknowledgement This ARM data set is a copy of v1.0 of the NCAR data set obtained in June 2024 from https://doi.org/10.26023/KW8Z-F2WX-H0Y. The citation for the original data source is: Gochis, D., et al. 2019. NCAR-RAL Surface Hydrometeorological Observation Network Data. Version 1.0. UCAR/NCAR - Earth Observing Laboratory. https://doi.org/10.26023/KW8Z-F2WX-H0Y Accessed June 2024. In addition to the citation reference and any other acknowledgements, please acknowledge NCAR/EOL in your publications with text such as: “Data provided by NCAR/EOL under the sponsorship of the National Science Foundation. https://data.eol.ucar.edu/”

air temperature↗
DOE OSTI2020

FX Hg Fogging Fixative Deployment for Mercury Vapor Suppression

Idaho National Laboratory’s (INL) FX Hg fixative solution was deployed at the Y-12 Complex in Oak Ridge, Tennessee to support disposal of mercury-contaminated metal debris. The fixative was dispensed via fogging. Fogging infiltrates non-line-of-sight areas improving fixative coating on complex geometries such as debris piles. FX Hg is the mercury vapor controlling derivative of INL’s FX2 fixative. FX2 was jointly developed with the National Nuclear Laboratory of the United Kingdom, and INL developed the FX Hg derivative to suppress mercury vapor generation. The Y-12 deployment was performed in concert with cleanup contractor UCOR. A dumpster filled with debris was fogged with FX Hg. The material was acceptable as municipal landfill waste, save for the mercury vapor levels measured. If the mercury vapor generation rate could be sufficiently reduced, disposal costs for this waste would be dramatically reduced. FX Hg had previously proven effective at significantly reducing mercury vapor generation rates in bench scale testing at INL. This deployment was the first field scale deployment of the method. Efficacy results were underwhelming, but interpretation of the outcome is complicated by a paucity of hard data. Methods for improving data capture and analysis are analyzed. Operational difficulties associated with scaling the process up and process improvements for future deployments are discussed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

FCIC Task 5--Preprocessing

the objective of this project is to develop science-based design and operation principles (as informed by TEA and LCA), which result in preprocessing units to operate predictably and reliably, and are capable of scalable performance.

09 BIOMASS FUELS↗
DOE OSTI2023

Morphology Control of Growth by Hydride Vapor Phase Epitaxy on Faceted GaAs Substrates Produced by Controlled Spalling for Low Cost III-V Devices

In this work, we apply the morphology control of hydride vapor phase epitaxial (HVPE) growth to planarize faceted, non-planar substrates. Controlled spalling is a promising high-throughput substrate reuse technology that could reduce substrate costs for III-V devices; however, the spalling fracture for (100)-oriented GaAs substrates produces a regularly corrugated surface of facets that are 5-20 um in height. We discuss how to planarize these surfaces using only a few minutes of HVPE growth and how to minimize the impact on throughput when integrating faceted wafers into a potential manufacturing process at scale.

epitaxy↗
DOE OSTI2025

The Profiled Feldman-Cousins Method for Confidence Interval Construction for the Nova 3-Flavor Oscillation Analysis

The small interaction cross-section of neutrinos makes experimental neutrino physics particularly responsive to technological advancements. A significant development leveraged by the NOvA experiment is large-scale parallel processing, enabling novel computational approaches to longstanding experimental challenges. Central to managing the resulting high-throughput data is NOvA’s implementation of the Freight Train model, designed for efficient data production and handling.This dissertation details the methodology and execution of the NOvA 2024 3-Flavor Oscillation Analysis, supported by a comprehensive dataset spanning ten years. It emphasizes frequentist results refined through the Feldman-Cousins (FC) technique, specifically addressing confidence interval corrections in parameter estimation. The computational intensity associated with Feldman-Cousins arises from extensive Monte Carlo simulations, which were substantially mitigated through parallel computing on the Perlmutter supercomputer at the National Energy Research Scientific Computing Center (NERSC), employing the MPI framework.To further enhance computational efficiency, an Importance Sampling method is introduced and evaluated, demonstrating significant potential to reduce complexity, particularly in exploring extreme parameter space regions. This thesis presents both the successful application of advanced computational resources and the development of sophisticated statistical techniques, aiming to enhance the precision and scope of neutrino oscillation analyses.

Dye ajdye11190@gmail.com, Andrew Joseph [Mississip↗
DOE OSTI2026

Techno-Economic Assessment of Data Center Load Demand Powered by Small Modular Reactors and Distributed Energy Resources

The rapid increase in data center energy demand, driven by AI and large-scale data processing, poses significant challenges to global energy infrastructure. Data centers require substantial and reliable energy for continuous operations and high-performance computing. Current electrical grids face issues such as transmission bottlenecks and aging infrastructure, making it difficult to meet these demands. Integrating inverter-based-resources (IBRs) like solar and wind presents both opportunities and challenges due to their intermittent nature. Small Modular Reactors (SMRs) offer a promising solution with their enhanced safety, modularity, reliability, and scalability, providing consistent base load power ideal for data center operations. This study presents a comprehensive techno-economic assessment of powering data center load demand using a combination of SMRs and IBRs with grid-connected and islanded mode. This study utilized Idaho National Laboratory’s (INL) HPC data center hourly load profiles and Xendee microgrid optimization platform to conduct the analysis. In this configuration, SMRs serves as the primary base load power source, consistently providing a steady supply of electricity necessary to meet the minimum load demand of the data center with support from the IBRs. Key performance indicators such as Levelized Cost of Electricity (LCOE), Net Present Value (NPV) has been calculated to assess the economic feasibility. The findings from this research will underscore the strategic benefits of integrating SMR plant with DERs – particularly for critical infrastructure load such as data centers.

14 - SOLAR ENERGY↗
DOE OSTI2023

COMMUNITY AND INFRASTRUCTURE ADAPTION TO CLIMATE CHANGE

(SF-23-046) The CIACC tool labels a large number of documents using a weak-supervision-based NLP technique that makes use of semantic similarity between categories and documents. This method allows the labeling process to scale across multiple GPU's in a computing cluster at the Argonne Leadership Computing Facility.

Verner, Duane↗
DOE OSTI2021

Tailoring Cementitious Materials Towards Value-Added Use of Large CO 2 Volumes

Hydraulic cements with alternative chemistries were developed for large-volume and value-added use of carbon dioxide. The hydraulic cements were processed using the energy-efficient mechanochemical technique at room temperature and atmospheric pressure. Carbon dioxide was captured directly from combustion emissions during processing. For this purpose, mechanochemical processing of hydraulic cements was accomplished under a flow of combustion emissions prior to the release of emissions to the atmosphere. The process removed a significant fraction of carbon dioxide from combustion emissions. The hydraulic cements captured carbon dioxide at about 10% of their weight. Two hydraulic cement chemistries were developed, and their mechanochemical processing was successfully scaled-up. The characteristic feature of one chemistry was its relatively low (near-neutral) pH where the integration of carbon dioxide yielded clear value. The second cement chemistry was based on alkali activation of industrial wastes. This chemistry could make value-added use of carbon dioxide, but it had to be refined to control the pH drop caused by CO 2 integration. These two cements render binding effects upon hydration by forming a combination of stable carbonates and aluminosilicates or phosphates. Efforts to develop cement chemistries based solely on carbonates were not successful. The mechanochemical process was found to integrate carbon dioxide into the alternative cement chemistries in the form of disordered and metastable carbonates. During hydration reactions, the disordered/metastable carbonates are either transformed into stable carbonate phases with desired binding efforts, or carbonates get integrated into the primary inorganic binders (hydrates). When compared with mechanochemical processing in pure carbon dioxide, mechanochemical processing in combustion emissions produced hydraulic cements with improved engineering properties. The mechanochemical process was scaled-up, and its variables as well as the raw materials formulations were optimized for implementation at pilot scale. Scale-up was found to enhance the carbon capture potential and the engineering qualities of the resulting hydraulic cements. This was because scale-up raises the intensity of mechanical energy input to raw materials. Certain mechanochemical phenomena cannot be induced, irrespective of the cumulative mechanical energy input, unless the intensity of impact is raised above a minimum level that cannot be achieved in laboratory-scale implementation of the process. Due to this effect, the duration of the mechanochemical process as well as its energy demand could be reduced significantly (by an order of magnitude) upon transition from laboratory to pilot scale, with the hydraulic cements produced at pilot scale offering engineering properties that were superior to those realized in laboratory-scale mechanochemical processing. The hydraulic cements produced at pilot scale via mechanochemical processing under a flow of combustion emissions were thoroughly characterized. They were found to meet standard requirements for ‘General Use’ hydraulic cements. They were compatible with the industrial-scale concrete production and construction practices that are used with the currently prevalent hydraulic cements. The new hydraulic cements with integrated carbon dioxide were found to offer distinct advantages over the currently prevalent Portland cement in terms of net carbon footprint and energy content. The combined raw materials and energy costs of the new hydraulic cements are competitive, and major cost savings can be realized because of the simplified production process that significantly lowers the capital investment in cement production plants. Mechanochemical processing of the new hydraulic cements under a flow of combustion emissions can be implemented using some existing components of cement manufacturing plants; this facilitates adoption of the technology by the cement industry.

36 MATERIALS SCIENCE↗
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 OSTI2025

High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) towards CMIP7

Abstract. Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. Consequently, the role of enhanced horizontal resolution in improved process representation in all components of the climate system continues to be of great interest. Recent simulations suggest the possibility of significant changes in both large-scale aspects of the ocean and atmospheric circulations and in the regional responses to climate change, as well as improvements in representations of small-scale processes and extremes, when resolution is enhanced. The first phase of the High-Resolution Model Intercomparison Project (HighResMIP1) was successful at producing a baseline multi-model assessment of global simulations with model grid spacings of 25–50 km in the atmosphere and 10–25 km in the ocean, a significant increase when compared to models with standard resolutions on the order of 1° that are typically used as part of the Coupled Model Intercomparison Project (CMIP) experiments. In addition to over 250 peer-reviewed manuscripts using the published HighResMIP1 datasets, the results were widely cited in the Intergovernmental Panel on Climate Change report and were the basis of a variety of derived datasets, including tracked cyclones (both tropical and extratropical), river discharge, storm surge, and impact studies. There were also suggestions from the few ocean eddy-rich coupled simulations that aspects of climate variability and change might be significantly influenced by improved process representation in such models. The compromises that HighResMIP1 made should now be revisited, given the recent major advances in modelling and computing resources. Aspects that will be reconsidered include experimental design and simulation length, complexity, and resolution. In addition, larger ensemble sizes and a wider range of future scenarios would enhance the applicability of HighResMIP. Therefore, we propose the High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) to improve and extend the previous work, to address new science questions, and to further advance our understanding of the role of horizontal resolution (and hence process representation) in state-of-the-art climate simulations. With further increases in high-performance computing resources and modelling advances, along with the ability to take full advantage of these computational resources, an enhanced investigation of the drivers and consequences of variability and change in both large- and synoptic-scale weather and climate is now possible. With the arrival of global cloud-resolving models (currently run for relatively short timescales), there is also an opportunity to improve links between such models and more traditional CMIP models, with HighResMIP providing a bridge to link understanding between these domains. HighResMIP also aims to link to other CMIP projects and international efforts such as the World Climate Research Program lighthouse activities and various digital twin initiatives. It also has the potential to be used as training and validation data for the fast-evolving machine learning climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Overlap junctions for superconducting quantum electronics and amplifiers

Due to their unique properties as lossless, nonlinear circuit elements, Josephson junctions lie at the heart of superconducting quantum information processing. Previously, we demonstrated a two-layer, submicrometer-scale overlap junction fabrication process suitable for qubits with long coherence times. Here, we extend the overlap junction fabrication process to micrometer-scale junctions. This allows us to fabricate other superconducting quantum devices. For example, we demonstrate an overlap junction-based Josephson parametric amplifier that uses only two layers. This efficient fabrication process yields frequency-tunable devices with negligible insertion loss, a gain of ∼30 dB, and quantum limited noise performance. Compared to other processes, the overlap junction allows for fabrication with minimal infrastructure, high yield, and state-of-the-art device performance.

Bal, Mustafa (ORCID:0000000307516774)↗