TECHNO-ECONOMIC COMPARISON OF SOLAR-DRIVEN SCO2 BRAYTON CYCLES USING COMPONENT COST MODELS BASELINED WITH VENDOR DATA AND ESTIMATES.
Abstract not provided.
Carlson, Matthew David↗
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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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Analysis of compositional uniformity in Al{sub x}Ga{sub 1−x}N thin films using atom probe tomography and electron microscopy
Calculated frequency distributions of atom probe tomography reconstructions (∼80 nm field of view) of very thin Al{sub x}Ga{sub 1−x}N (0.18 ≤ x ≤ 0.51) films grown via metalorganic vapor phase epitaxy on both (0001) GaN/AlN/SiC and (0001) GaN/sapphire heterostructures revealed homogeneous concentrations of Al and chemically abrupt Al{sub x}Ga{sub 1−x}N/GaN interfaces. The results of scanning transmission electron microscopy and selected area diffraction corroborated these results and revealed that neither superlattice ordering nor phase separation was present at nanometer length scales.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Using all energy in a battery
Controlled electrode structure improves energy utilization [Also see Report by Kirshenbaum et al. ]
25 ENERGY STORAGE↗
Scalable Matrix Computations on Large Scale-Free Graphs Using 2D Graph Partitioning.
Abstract not provided.
Boman, Erik G.↗
Denoising 400-kHz ?Postage-Stamp PIV? using Uncertainty Quantification.
Abstract not provided.
Beresh, Steven J.↗
Drivers of Change in Managed Water Resources: Modeling the Impacts of Climate and Socioeconomic Changes Using the US Midwest as a Case Study
A global integrated assessment model including a water-demand model driven by socio-economics, is coupled in a one-way fashion with a land surface hydrology – routing – water resources management model. The integrated modeling framework is applied to the U.S. Upper Midwest (Missouri, Upper Mississippi, and Ohio) to advance understanding of the regional impacts of climate and socio-economic changes on integrated water resources. Implications for future flow regulation, water supply, and supply deficit are investigated using climate change projections with the B1 and A2 emission scenarios, which affect both natural flow and water demand. Changes in water demand are driven by socio-economic factors, energy and food demands, global markets and prices. The framework identifies the multiple spatial scales of interactions between the drivers of changes (natural flow and water demand) and the managed water resources (regulated flow, supply and supply deficit). The contribution of the different drivers of change are quantified regionally, and also evaluated locally, using covariances. The integrated framework shows that water supply deficit is more predictable over the Missouri than the other regions in the Midwest. The predictability of the supply deficit mostly comes from long term changes in water demand although changes in runoff has a greater contribution, comparable to the contribution of changes in demand, over shorter time periods. The integrated framework also shows that spatially, water demand drives local supply deficit. Using elasticity, the sensitivity of supply deficit to drivers of change is established. The supply deficit is found to be more sensitive to changes in runoff than to changes in demand regionally. It contrasts with the covariance analysis that shows that water demand is the dominant driver of supply deficit over the analysed periods. The elasticity indicates the level of mitigation needed to control the demand in order to reduce the vulnerability of the integrated system in future periods. The elasticity analyses also emphasize the need to address uncertainty with respect to changes in natural flow in integrated assessment.
climate change, water resources management, socio-↗
Fabrication of Nanoporous Alumina Ultrafiltration Membrane with Tunable Pore Size Using Block Copolymer Templates
Control over nanopore size and 3D structure is necessary to advance membrane performance in ubiquitous separation devices. Here, inorganic nanoporous membranes are fabricated by combining the assembly of cylinder-forming poly(styrene-block-methyl methacrylate) (PS-b-PMMA) block copolymer and sequential infiltration synthesis (SIS). A key advance relates to the use of PMMA majority block copolymer films and the optimization of thermal annealing temperature and substrate chemistry to achieve throughfilm vertical PS cylinders. The resulting morphology allows for direct fabrication of nanoporous AlOx by selective growth of Al2O3 in the PMMA matrix during the SIS process, followed by polymer removal using oxygen plasma. Control over the pore diameter is achieved by varying the number of Al2O3 growth cycles, leading to pore size reduction from 21 to 16 nm. 3D characterization, using scanning transmission electron microscopy tomography, reveals that the AlOx channels are continuous through the film and have a gradual increase in pore size with depth. Finally, the ultrafiltration performance of the fabricated AlOx membrane for protein separation as a function of protein size and charge is demonstrated.
block copolymers↗
Use of the ERD for administrative monitoring of Theta
Monitoring the state of an HPC cluster in a timely and accurate fashion is critical to most system administration functions. For many Cray users, the first step in monitoring is ingestion of log files. Unfortunately, log parsing is an inherently inefficient process, requiring multiple software components to read and write from files on disk. Cray's own utilities use a message bus, the Event Router Daemon (ERD), for a wide variety of purposes. At the Argonne Leadership Computing Facility (ALCF), we have begun to use this message bus for monitoring via a client library written in Go, allowing us to read in structured data directly from Cray's services and, in many instances, bypass log files entirely. In this paper, we will examine the implementation and utilization of this approach on our 4392 node XC40, Theta, as well as the overall benefits and drawbacks to using the ERD for real-time monitoring.
Cray↗
Independent confirmation of global land warming without the use of station temperatures
Confidence in estimates of anthropogenic climate change is limited by known issues with air temperature observations from land stations. Station siting, instrument changes, changing observing practices, urban effects, land cover, land use variations, and statistical processing have all been hypothesized as affecting the trends presented by the Intergovernmental Panel on Climate Change and others. Any artifacts in the observed decadal and centennial variations associated with these issues could have important consequences for scientific understanding and climate policy. We use a completely different approach to investigate global land warming over the 20th century. We have ignored all air temperature observations and instead inferred them from observations of barometric pressure, sea surface temperature, and sea-ice concentration using a physically based data assimilation system called the 20th Century Reanalysis. This independent data set reproduces both annual variations and centennial trends in the temperature data sets, demonstrating the robustness of previous conclusions regarding global warming.
54 ENVIRONMENTAL SCIENCES↗
Use of a Lignin-Based Admixture for Tailoring the Rheological Properties of Mortars for 3D Printing: Preprint
Efforts toward decarbonizing construction materials and industrial processes related to cement and concrete can be aided via multifaceted approaches that target alternative admixtures as well as precision control of fabrication. Chemical admixtures for water reduction have played a crucial role in the development of advanced concrete mixtures. Newer biomass processing techniques developed for aviation fuel production from corn stover biomass produce a more reactive lignin byproduct that is suitable for chemical modifications to mimic the properties of polycarboxylate ether admixtures with a smaller carbon footprint. The present study examines the use of lignin-based water-reducing admixture in cement pastes and mortar mixtures for 3D printing. The experimental program explores the use of different dosages of lignin-based admixture to produce 3D-printed samples with appropriate extrudability and buildability. The rheological characterization was performed to determine the flow curve of various mixtures. Finally, the heat of hydration of cement pastes was monitored via isothermal calorimetry to assess the impact of lignin-based admixtures on the hydration process of cement. The results of this study indicate that the use of biomass by-products, such as lignin-based admixtures have great potential to effectively control the fresh-state properties of cement-based materials.
bio-based admixtures↗
A Comparison of Reduced Order Modeling Techniques Used in Dynamic Substructuring [PowerPoint]
Experimental dynamic substructuring is a means whereby a mathematical model for a substructure can be obtained experimentally and then coupled to a model for the rest of the assembly to predict the response. Recently, various methods have been proposed that use a transmission simulator to overcome sensitivity to measurement errors and to exercise the interface between the substructures; including the Craig-Bampton, Dual Craig-Bampton, and Craig-Mayes methods. This work compares the advantages and disadvantages of these reduced order modeling strategies for two dynamic substructuring problems. The methods are first used on an analytical beam model to validate the methodologies. Then they are used to obtain an experimental model for structure consisting of a cylinder with several components inside connected to the outside case by foam with uncertain properties. This represents an exceedingly difficult structure to model and so experimental substructuring could be an attractive way to obtain a model of the system.
97 MATHEMATICS AND COMPUTING↗
Balancing global water availability and use at basin scale in an integrated assessment model
Water is essential for the world’s food supply, for energy production, including bioenergy and hydroelectric power, and for power system cooling. Water is already scarce in many regions of the world and could present a critical constraint as society attempts simultaneously to mitigate climate forcing and adapt to climate change, and to provide for a larger and more prosperous human population. Numerous studies have pointed to growing pressures on the world’s scarce fresh water resources from population and economic growth, and climate change. This study goes further. We use the Global Change Assessment Model to analyze interactions between population, economic growth, energy, land and water resources simultaneously in a dynamically evolving system where competing claims on water resources from all claimants—energy, land, and economy—are reconciled with water resource availability—from renewable water, non-renewable groundwater sources and desalinated water—across 14 geopolitical regions, 151 agriculture-ecological zones, and 235 major river basins. We find that previous estimates of global water withdrawal projections are overestimated. Model simulations show that it is more economical in some basins to alter agricultural and energy activities rather than utilize non-renewable groundwater or desalinated water. This study highlights the importance of accounting for water as a binding factor in agriculture, energy and land use decisions in IAMs and implications for global responses to water scarcity, particularly in the trade of agricultural commodities and land-use decisions.
basin↗
Simulation of Subsurface Multiphase Contaminant Extraction Using a Bioslurping Well Model
Subsurface simulation of multiphase extraction from wells is notoriously difficult. Explicit representation of well geometry requires small grid resolution, potentially leading to large computational demands. To reduce the problem dimensionality, multiphase extraction is mostly modeled using vertically-averaged approaches. In this paper, a multiphase well model approach is presented as an alternative to simplify the application. The well model, a multiphase extension of the classic Peaceman model, has been implemented in the STOMP simulator. The numerical solution approach accounts for local conditions and gradients in the exchange of fluids between the well and the aquifer. Advantages of this well model implementation include the option to simulate the effects of well characteristics and operation. Simulations were conducted investigating the effects of extraction location, applied vacuum pressure, and a number of hydraulic properties. The obtained results were all consistent and logical. A major outcome of the test simulations is that, in contrast with common recommendations to extract from either the gas-NAPL or the NAPL-aqueous phase interface, the optimum extraction location should be in between these two levels. Further, the new model implementation was also used to simulate extraction at a field site in Brazil. The simulation shows a good match with the field data, suggesting that the new STOMP well module may correctly represent oil removal. The field simulations depend on the quality of the site conceptual model, including the porous media and contaminant properties and the boundary and extraction conditions adopted. The new module may potentially be used to design field applications and analyze extraction data.
42 ENGINEERING↗
Towards High-Resolution Tissue Imaging Using Nanospray Desorption Electrospray Ionization Mass Spectrometry Coupled to Shear Force Microscopy
Constant mode ambient mass spectrometry imaging (MSI) of tissue sections with high lateral resolution of better than 10 μm was performed by combining shear force microscopy with nanospray desorption electrospray ionization (nano-DESI). Shear force microscopy enabled precise control of the distance between the sample and nano-DESI probe during MSI experiments and provided information on sample topography. Proof-of-concept experiments were performed using lung and brain tissue sections representing spongy and dense tissues, respectively. Topography images obtained using shear force microscopy were comparable to the results obtained using contact profilometry over the same region of the tissue section. Variations in tissue height were found to be dependent on the tissue type and were in the range of 0–5 μm for lung tissue and 0–3 μm for brain tissue sections. Ion images of phospholipids obtained in this study are in good agreement with literature data. Normalization of nano-DESI MSI images to the signal of the internal standard added to the extraction solvent allowed us to construct high-resolution ion images free of matrix effects. .
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Hydroxamate column-based purification of zirconium-89 (89Zr) using an automated fluidic platform
Zirconium-89 (89Zr) is a long-lived (t1/2 = 78.4 h) positron-emitting isotope that is useful for positron emission tomography (PET) based diagnostic imaging using radiolabeled antibodies. Hydroxamate resin columns are predominantly used for the purification of 89Zr from cyclotron bombarded natY targets dissolved in strong HCl. 89Zr is conventionally eluted from the resin in 1 M oxalic acid (H2C2O4), a complexant that is conducive to follow-on binding of 89Zr through a transchelation process to the deferoxamine siderophore. In the present study, we determined that a lower concentration of H2C2O4 eluent (0.8 M) is adequate to efficiently remove 89Zr from a column containing 100 mg hydroxamate resin. As a result, less buffering agents are needed to be added to the 89Zr product fraction prior to labeling. A simple automated fluidic system prototype has been developed to perform the steps required for 89Zr purification using a hydroxamate resin column (column conditioning in HCl, Y target dissolution, dissolved target solution load onto column, column washes using HCl and water, and 89Zr elution). The system performance was evaluated using several cyclotron bombarded Y targets; 89Zr product fractions demonstrated excellent chemical recoveries from these targets, with 1.0 mL product volumes yielding 89±2% of the column elution peak activity and 84±2% of 89Zr recovered from the target (at EOB). These results compare favorably with previously published 89Zr product volumes and yields, despite the lower concentration of H2C2O4 eluent employed. Transchelation of resulting 89Zr product fractions was performed to assess product quality. The effective specific activity (ESA) ranged between 44(7) and 109(22) TBq·mmole-1, while the bindable metals concentration, a metric introduced for assessing and comparing product purity, ranged between 43(7) and 115(27) nmole·g-1.
zirconium-89, 89Zr, ImmunoPET, medical isotope, au↗
Enhanced Data Efficiency Using Deep Neural Networks and Gaussian Processes for Aerodynamic Design Optimization
Adjoint-based optimization methods are attractive for aerodynamic shape design primarily due to their computational costs being independent of the dimensionality of the input space and their ability to generate high-fidelity gradients that can then be used in a gradient-based optimizer. This makes them very well suited for high-fidelity simulation based aerodynamic shape optimization of highly parametrized geometries such as aircraft wings. However, the development of adjoint-based solvers involve careful mathematical treatment and their implementation require detailed software development. Furthermore, they can become prohibitively expensive when multiple optimization problems are being solved, each requiring multiple restarts to circumvent local optima. In this work, we propose a machine learning enabled, surrogate-based framework that replaces the expensive adjoint solver, without compromising on predicting predictive accuracy. Specifically, we first train a deep neural network (DNN) from training data generated from evaluating the high-fidelity simulation model on a model-agnostic design of experiments on the geometry shape parameters. The optimum shape may then be computed by using a gradient-based optimizer coupled with the trained DNN. Subsequently, we also perform a gradient-free Bayesian optimization, where the trained DNN is used as the prior mean. We observe that the latter framework (DNN-BO) improves upon the DNN-only based optimization strategy for the same computational cost. Overall, this framework predicts the true optimum with very high accuracy, while requiring far fewer high-fidelity function calls compared to the adjoint-based method. Furthermore, we show that multiple optimization problems can be solved with the same machine learning model with high accuracy, to amortize the offline costs associated with constructing our models. Our methodology finds applications in the early stages of aerospace design. (C) 2021 Published by Elsevier Masson SAS.
Renganathan, S. Ashwin↗