Search NASA⌕ Search

SEARCH · Search NASA

Results for “coordinated optimization”

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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Quantification of Powder Spreading Process for Metal Additive Manufacturing

In powder bed additive manufacturing (AM), the powder spreading process can lead to inhomogeneity in layer height, porosity level, and particle size distribution. Hence, creating homogeneous layers is the first task for optimal printing. The conventional assessment methods for powder quality are limited to a measurement of powder morphology, flowability, particle size distribution, surface roughness, and packing density. However, those techniques may not be the most appropriate to quantify the powder bed characteristics since it is not able to capture local particle configuration and does not provide any vectoral information (e.g., arrangement of contacts between particles during spreading). In this project, we: 1) developed a powder spreading model using discrete element method (DEM) for multiple-layered process, 2) experimentally measure powder spreading dynamics including static angle of repose (AOR) and dynamic AOR in order to calibrate and subsequently validate the model, and 3) investigated the effect of particle spreading process parameters on spatial powder bed structure and quality using scalar (e.g., porosity, surface roughness, coordination number, and particle size distribution) and tensorial (e.g., directionality of inter-particle contacts) methods for a comprehensive quantification of powder bed.

36 MATERIALS SCIENCE↗
DOE OSTI2016

A new vertical grid nesting capability in the Weather Research and Forecasting (WRF) Model

Mesoscale atmospheric models are increasingly used for high-resolution (<3 km) simulations to better resolve smaller-scale flow details. Increased resolution is achieved using mesh refinement via grid nesting, a procedure where multiple computational domains are integrated either concurrently or in series. A constraint in the concurrent nesting framework offered by the Weather Research and Forecasting (WRF) Model is that mesh refinement is restricted to the horizontal dimensions. This limitation prevents control of the grid aspect ratio, leading to numerical errors due to poor grid quality and preventing grid optimization. Here, a procedure permitting vertical nesting for one-way concurrent simulation is developed and validated through idealized cases. The benefits of vertical nesting are demonstrated using both mesoscale and large-eddy simulations (LES). Mesoscale simulations of the Terrain-Induced Rotor Experiment (T-REX) show that vertical grid nesting can alleviate numerical errors due to large aspect ratios on coarse grids, while allowing for higher vertical resolution on fine grids. Furthermore, the coarsening of the parent domain does not result in a significant loss of accuracy on the nested domain. LES of neutral boundary layer flow shows that, by permitting optimal grid aspect ratios on both parent and nested domains, use of vertical nesting yields improved agreement with the theoretical logarithmic velocity profile on both domains. Lastly, vertical grid nesting in WRF opens the path forward for multiscale simulations, allowing more accurate simulations spanning a wider range of scales than previously possible.

17 WIND ENERGY↗
DOE OSTI2025

Electrochemical reduction of ammonia-captured CO 2 to CO over a nickel single-atom catalyst

Carbon reactive capture and conversion offers a sustainable route to valuable chemicals and fuels while aiding Green House Gas (GHG) reduction. Direct electrochemical conversion of capture solutions like bicarbonate avoids the energy demands of conventional CO 2 regeneration. Ammonium bicarbonate (NH 4 HCO 3 ) is particularly attractive due to its low decomposition temperature and ability to supply in situ CO 2 from dilute sources without requiring purified CO 2 . Meanwhile, single-atom catalysts (SACs) with nitrogen-coordinated metal sites further enhance CO 2 reduction efficiency using Earth-abundant materials. In this study, we demonstrate a nickel single-atom catalyst (Ni-SAC)-based electrolyzer that utilizes NH 4 HCO 3 as the CO 2 source, achieving significantly improved CO production performance compared to the conventional silver cathodes used in the CO 2 reduction reaction (CO 2 RR) to produce CO. The Ni-SAC cathode exhibited a Faradaic efficiency of 60.1% for CO production at −200 mA cm −2 , while the silver cathode achieved a Faradaic efficiency of only 2%, likely due to ammonium-induced poisoning. Furthermore, the integration of a customized microporous layer onto the electrode significantly increased the Faradaic efficiency from 64% to 83% at −100 mA cm −2 , emphasizing the crucial role of electrode structure optimization in enhancing CO selectivity. These findings demonstrate a sustainable and economically viable strategy for green CO production directly from CO 2 capture solutions.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Advances in Machine and Deep Learning for Modeling and Real-time Detection of Multi-Messenger Sources

We live in momentous times. The science community is empowered with an arsenal of cosmic messengers to study the universe in unprecedented detail. Gravitational waves, electromagnetic waves, neutrinos, and cosmic rays cover a wide range of wavelengths and timescales. Combining and processing these datasets that vary in volume, speed, and dimensionality requires new modes of instrument coordination, funding, and international collaboration with a specialized human and technological infrastructure. In tandem with the advent of large-scale scientific facilities, the last decade has experienced an unprecedented transformation in computing and signal-processing algorithms. The combination of graphics processing units, deep learning, and the availability of open source, high-quality datasets has powered the rise of artificial intelligence. This digital revolution now powers a multibillion dollar industry, with far-reaching implications in technology and society. In this chapter, we describe pioneering efforts to adapt artificial intelligence algorithms to address computational grand challenges in multi-messenger astrophysics. We review the rapid evolution of these disruptive algorithms, from the first class of algorithms introduced in early 2017 to the sophisticated algorithms that now incorporate domain expertise in their architectural design and optimization schemes. We discuss the importance of scientific visualization and extreme-scale computing in reducing time-to-insight and obtaining new knowledge from the interplay between models and data.

Artificial Intelligence↗
DOE OSTI2023

High-Temperature Rotating Disk Electrode Study of Platinum Bimetallic Catalysts in Phosphoric Acid

Understanding the H 3 PO 4 effect on the catalyst’s activity under a relevant condition is important for high-temperature polymer electrolyte membrane fuel cell (HT-PEMFC) catalyst research. Here, we report a high-temperature rotating disk electrode (HT-RDE) study of oxygen reduction reaction (ORR) in H 3 PO 4 . With the regular electrochemical protocol, we found that H 3 PO 4 reduction could occur during cyclic voltammetry study and form a reductive species—phosphorus acid (H 3 PO 3 ). Further, to obtain reliable ORR measurement, we optimized the protocol to avoid the H 3 PO 3 generation. The ORR activity of carbon-supported PtM (M = Fe, Co, Ni, Ru, Pd, and Ir) bimetallic alloy catalysts measured with this HT-RDE method showed higher ORR activity than Pt. To understand the alloying effect, we combine experiments in diluted solutions to distinguish the alloying effect on Pt–O binding and Pt–H 3 PO 4 binding. The results indicate that H 3 PO 4 mainly reduces available sites for ORR, with little effect on neighboring site’s Pt–O binding via Pt–H 3 PO 4 interaction, which is also supported by the density functional theory calculation of the Pt–O binding energy with/without H 2 PO 4 . Further study in a phosphoric acid-doped quaternary ammonium-biphosphate ion pair coordinated polyphenylene (PA-QAPOH) membrane electrode assembly (MEA) shows that the active alloy catalyst has better performance in both the HT-RDE and MEA. Also, the MEA gives higher ORR activity than the HT-RDE because of the higher pressure and less phosphoric acid content of the MEA. Yet, the gap between the HT-RDE and MEA is significantly smaller than that between the room temperature (RT)-RDE and MEA, suggesting the importance of temperature and H 3 PO 4 concentration in understanding ORR in HT-PEMFCs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Impact of Building-Level Motor Protection on Power System Transient Behaviors

Transmission and distribution system level protection strategies have been extensively investigated to advise better coordination of physical protection devices. A diversity of functional motors with dedicated protection schemes are popularized in increasing number of commercial, residential and industrial buildings. This paper focuses on implementing several most popular protection schemes on Eletro-Magnetic Transient Program (EMTP) simulation for three-phase and single-phase induction motors that exist in commercial buildings connected to typical distribution feeders. Voltage depressions are played in at the head of the feeder fully loaded with functional induction motors to investigate the behaviors of single-phase motor stalling, the action of motor protection and reconnection, and the impacts of device-level protection on system-level dynamics. Several distribution feeders are represented in standard IEEE 39-bus transmission system to simulate fault-induced delayed voltage recovery (FIDVR) and explore mitigation strategies by optimally configuring the building-level motor protection settings.

Liu, Yuan↗
DOE OSTI2025

Highly dense atomic Fe–Ni dual metal sites for efficient CO 2 to CO electrolyzers at industrial current densities

Carbon-supported, atomically dispersed, nitrogen-coordinated metal sites (e.g., Fe and Ni) are arguably the most promising catalysts for the electrochemical reduction of CO 2 to CO due to their unique catalytic properties and the use of earth-abundant elements. However, conventional single metal sites are constrained by their structural simplicity, causing either too weak or too strong absorption/desorption of multiple critical intermediates (e.g., *COOH and *CO). Current catalysts also suffer from ultra-low loadings (<1.0 wt%) of atomic metal active sites in catalysts, leading to inadequate performance for CO 2 -to-CO conversion. Here, we develop dual Ni/Fe metal site catalysts with significantly increased atomically dispersed metal loadings (up to 4.8 wt%). A gas-phase chemical vapor deposition (CVD) approach to introducing single Ni sites was integrated with Fe 2 O 3 /ZIF-8 precursors, followed by an optimal thermal activation. The optimized CVD-Ni/Fe–N–C catalyst exhibited remarkable electrocatalytic performance for the CO 2 reduction to CO in a continuous membrane-electrode-assembly electrolyzer, achieving a maximum CO faradaic efficiency (FE CO ) of 96% at a current density of 700 mA cm −2 in a near-neutral electrolyte. Furthermore, a desirable but challenging acidic flow-cell electrolyzer was designed using this dual metal site catalyst to improve CO 2 utilization, accomplishing a FE CO of up to 95% at a CO partial current density close to 600 mA cm −2 . Density functional theory (DFT) calculations suggest a synergetic effect between Fe–Ni pairs facilitating *COOH intermediate formation and *CO desorption simultaneously during CO 2 to CO conversion. This is key to breaking the linear scaling relationship of conventional single-metal site catalysts during the CO 2 reduction reaction.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Optimal nitrogen and phosphorus codoping carbon dots towards white light-emitting device

Through a one-step fast microwave-assisted approach, nitrogen and phosphorus co-doped carbon dots (N,P-CDs) were synthesized using ammonium citrate (AC) as a carbon source and phosphates as additive reagent. Under the condition of an optimal reaction time of 140 s, the influence of additive with different N and P content on fluorescent performance of N,P-CDs was further explored. It was concluded that high nitrogen content and moderate phosphorus content are necessary for obtaining high quantum yield (QY) N,P-CDs, among which the TAP-CDs (CDs synthesized using ammonium phosphate as additive reagent) show high quantum yield (QY) of 62% and red-green-blue (RGB) spectral composition of 51.67%. Besides, the TAP-CDs exhibit satisfying thermal stability within 180 °C. By virtue of good optical and thermal properties of TAP-CDs, a white light-emitting device (LED) was fabricated by combining ultraviolet chip with TAP-CDs as phosphor. The white LED emits bright warm-white light with the CIE chromaticity coordinate of (0.38, 0.35) and the corresponding color temperature (CCT) of 4450 K, indicating the potential of TAP-CDs phosphor in white LED.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Long plasma duration operation analyses with an international multi-machine (tokamaks and stellarators) database

Combined high-fusion performance and long-pulse operation is one of the key integration challenges for fusion energy development in magnetic devices. Addressing these challenges requires an integrated vision of physics and engineering aspects with the purpose of simultaneously increasing time duration and fusion performance. Significant progress has been made in tokamaks and stellarators, including very recent achievement in duration and/or performance. This progress is reviewed by analyzing the experimental data (109 plasma pulses with a total of 3200 data points, i.e. on average 29 data per pulse) provided by ten tokamaks (in alphabetical order: Axially Symmetric Divertor Experiment Upgrade, DIII-D, Experimental Advanced Superconducting Tokamak, Joint European Torus, JT-60 Upgrade, Korea Superconducting Tokamak Advanced Research, tokamak à configuration variable, Tokamak Fusion Test Reactor, Tore Supra, W Environment in Steady-State Tokamak) and two stellarators (Large Helical Device and Wendelstein 7-X) expanding the pioneering work of Kikuchi (Kikuchi M. and Azumi M. 2015 Frontiers in Fusion Research II: Introduction to Modern Tokamak Physics (Springer)). Data have been gathered up to January 2022 and coordination has been provided by the recently created International Energy Agency-International Atomic Energy Agency international Coordination on International Challenges on Long duration OPeration group. By exploiting the multi-machine international database, recent progress in terms of injected energies (e.g. 1730 MJ in L-mode, 425 MJ in H-mode), durations (1056 s in L-mode, 101 s in H-mode), injected powers, and sustained performance will be reviewed. Progress has been made to sustain long-pulse operation in tokamaks and stellarators with superconducting coils, actively cooled components, and/or with metallic walls. The graph of the fusion triple products as a function of duration shows a dramatic reduction of, at least two orders of magnitude when increasing the plasma duration from less than 1 s to 100 s. Indeed, long-pulse operation is usually reached in dominant electron-heating modes at reduced density (current drive optimization) but with low ion temperatures ranging from 1 to 3 keV for discharges above 100 s. Difficulties in extending the duration may arise from coupling high heating powers over long durations and the evolving plasma-wall interaction towards an unstable operational domain. Possible causes limiting the duration and critical issues to be addressed prior to ITER operation and DEMO design are reported and analyzed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Artificial intelligence models, photos, and data associated with the manuscript “Quantifying Streambed Grain Size, Uncertainty, and Hydrobiogeochemical Parameters Using Machine Learning Model YOLO” (v2)

This data package is associated with the manuscript “Quantifying Streambed Grain Size, Uncertainty, and Hydrobiogeochemical Parameters Using Machine Learning Model YOLO” published in Water Resources Research (Chen et al., 2024). This data package includes the training, validation, testing, and prediction data used by the artificial intelligence (AI) model for automated grain size and hydro-biogeochemistry quantification using streambed photos. The grain size data are extracted for each photo using You Look Only Once (YOLO), a pre-trained object detection model. This data package was originally published in October 2023. It was updated August 2025 (v2; new and modified files). File and folder names were not revised to indicate changes. See the change history section in the readme for more details. Please see flmd.csv for a list of all files contained in this data package and descriptions for each. Please see dd.csv for a data dictionary that defines the column headers of .csv files in the data package. This dataset is comprised of one data folder containing (1) file-level metadata; (2) data dictionary; (3) readme; and (4) six subfolders. Subfolders 1 to 4 include the training, validation, testing, and prediction data. Subfolder 5_Summary includes the summary results of different combinations of training, validation, testing, and prediction data. Subfolder 6_SupplementalData includes additional data downloaded from public sources (Kaufman et al., 2023a; Kaufman et al., 2023b; Garefalakis et al., 2023; Mair et al., 2024; https://github.com/river-corridors-sfa/Geospatial_variables). In total, the data package includes 110 folders and 44,283 files. These files include 9,047 .jpg photos, 1 .png photo, 3 .tif photos; 26,639 photo labels and individual grain sizes and probability from AI (.txt); 8,447 grain size distribution data (.dat); and 126 CSV files for results summary, and 14 required metadata files (.xlsx). The summary CSV files contain 68 columns and approximately 2,200 rows that represent photo names, site locations, recording time, GPS coordinates, grains sizes (D10, D50, D60, and D84), number of grains, and additional hydro-biogeochemical data such as water depth, flow velocity, Manning’s coefficient, friction factor, hydraulic conductivity, permeability, streambed interstitial velocity magnitude, mass transfer rate, and nitrate uptake velocity. The photos were obtained from 75 sites in the Yakima River Basin and the Columbia River shorelines, and other associated data from samples and sensors obtained when the photos were taken are publicly available (Fulton et al. 2022; Grieger et al. 2023). All files are .csv, .txt, .dat, .jpg, or .pdf. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected some of these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

On the Feasibility of Market Manipulation and Energy Storage Arbitrage via Load-Altering Attacks

Around the globe, electric power networks are transforming into complex cyber–physical energy systems (CPES) due to the accelerating integration of both information and communication technologies (ICT) and distributed energy resources. While this integration improves power grid operations, the growing number of Internet-of-Things (IoT) controllers and high-wattage appliances being connected to the electric grid is creating new attack vectors, largely inherited from the IoT ecosystem, that could lead to disruptions and potentially energy market manipulation via coordinated load-altering attacks (LAAs). In this article, we explore the feasibility and effects of a realistic LAA targeted at IoT high-wattage loads connected at the distribution system level, designed to manipulate local energy markets and perform energy storage (ES) arbitrage. Realistic integrated transmission and distribution (T&D) systems are used to demonstrate the effects that LAAs have on locational marginal prices at the transmission level and in distribution systems adjacent to the targeted network.

25 ENERGY STORAGE↗
DOE OSTI2018

A linear array of position-sensitive virtual Frisch-grid CdZnTe for low-energy gamma rays

Large-area arrays of position-sensitive virtual Frisch-grid CdZnTe (CZT) detectors with enhanced energy resolution and high efficiency have been proposed for spectroscopy and imaging of gamma-ray sources. We present the design and test results of a linear array of such detectors optimized for use in handheld instruments. There are several application areas for such detectors including uranium enrichment measurements, storage monitoring, dosimetry and other nuclear safeguards related tasks. The array configuration provides a large area with minimum number of readout channels, which potentially allows the developers to avoid using ASIC-based readout electronics by substituting it with hybrid preamplifiers followed by digitizers. The array prototype consists of 6 5 x 7 x 25 mm 3 CZT detectors side-oriented with respect to the source to achieve the maximum area. Each detector is furnished with 5 mm-wide charge-sensing pads placed near the anode. As an option, the pads can be grouped together to reduce the number of readout channels. The same can be done with the cathodes. The pads signals are converted into X–Y coordinates and combined with the cathode signals (for the Z coordinates) to give 3D positional information of each interaction point. This information is used to correct the response non-uniformity caused by material inhomogeneity, which allows the developers to use standard grade (unselected) CZT crystals, while retaining high spectroscopic performance.

3D position-sensitive virtual Frisch-grid detector↗
DOE OSTI2025

Bridging Atomic Solvation Environment with Electrochemical Properties for the Bis(trifluoromethylsulfonyl)imide-Based Divalent Cation Electrolytes for the Next-Generation Energy Storage Systems

A deep molecular-level understanding of the multivalent electrolyte and its correlation with the electrochemical properties is crucial for designing optimized electrolytes for next-generation rechargeable batteries. Comprehensive knowledge of the atomic level of the solvation structure and its connection with electrochemical stability and ion transport properties is especially critical. However, the interaction of these three components coupled with clear atomistic insights is lacking in the literature. Here, our current contribution evaluates representative electrolytes with the bis(trifluoromethanesulfonyl)imide (TFSI) anions for multivalent cations of Mg, Ca, and Zn, at different ionic conditions with and without a cosolvated environment in ether-based solvent. Two critical problems are investigated: first, resolving the solvation structures in the electrolyte solutions as a function of concentrations through pair distribution function analysis and the corresponding electrochemical transport properties; second, unmasking the quantitative correlation of the atomistic environment with both electrochemical kinetics and cation dependence. We discovered that the magnesium- and calcium-based electrolytes display versatile coordination lengths but poor average anodic stability due to ion pairing with TFSI - . On the contrary, the zinc-based electrolytes show the shortest solvent coordination lengths, shielding the Zn cation from rigid solvent interactions and resulting in the highest anodic stabilities. Calcium-based electrolytes exhibit the longest and most concentration-independent coordination lengths. This work provides valuable insights into the molecular structural and electrochemical features of diverse multivalent electrolyte systems with cations in various solvation environments, emphasizing the importance of the solvation structure and construction in designing high-performance electrolytes.

cation coordination↗
DOE OSTI2017

Slipstream pilot-scale demonstration of a novel amine-based post-combustion technology for carbon dioxide capture from coal-fired power plant flue gas

Post-combustion CO 2 capture (PCC) technology offers flexibility to treat the flue gas from both existing and new coal-fired power plants and can be applied to treat all or a portion of the flue gas. Solvent-based technologies are today the leading option for PCC from commercial coal-fired power plants as they have been applied in large-scale in other applications. Linde and BASF have been working together to develop and further improve a PCC process incorporating BASF’s novel aqueous amine-based solvent technology. This technology offers significant benefits compared to other solvent-based processes as it aims to reduce the regeneration energy requirements using novel solvents that are very stable under the coal-fired power plant feed gas conditions. BASF has developed the desired solvent based on the evaluation of a large number of candidates. In addition, long-term small pilot-scale testing of the BASF solvent has been performed on a lignite-fired flue gas. In coordination with BASF, Linde has evaluated a number of options for capital cost reduction in large engineered systems for solvent-based PCC technology. This report provides a summary of the work performed and results from a project supported by the US DOE (DE-FE0007453) for the pilot-scale demonstration of a Linde-BASF PCC technology using coal-fired power plant flue gas at a 1-1.5 MWe scale in Wilsonville, AL at the National Carbon Capture Center (NCCC). Following a project kick-off meeting in November 2011 and the conclusion of pilot plant design and engineering in February 2013, mechanical completion of the pilot plant was achieved in July 2014, and final commissioning activities were completed to enable start-up of operations in January 2015. Parametric tests were performed from January to December 2015 to determine optimal test conditions and evaluate process performance over a variety of operation parameters. A long-duration 1500-hour continuous test campaign was performed from May to August 2016 at a selected process condition to evaluate process performance and solvent stability over a longer period similar to how the process would operate as a continuously running large-scale PCC plant. The pilot plant integrated a number of unique features of the Linde-BASF technology aimed at lowering overall energy consumption and capital costs. During the overall test period including startup, parametric testing and long-duration testing, the pilot plant was operated for a total of 6,764 hours out of which testing with flue gas was performed for 4,109 hours. The pilot plant testing demonstrated all of the performance targets including CO 2 capture rate exceeding 90%, CO 2 purity exceeding 99.9 mol% (dry), flue gas processing capacity up to 15,500 lbs/hr (equivalent to 1.5 MWe capacity slipstream), regeneration energy as low as 2.7 GJ/tonne CO 2 , and regenerator operating pressure up to 3.4 bara. Excellent solvent stability performance data was measured and verified by Linde and BASF during both test campaigns. In addition to process data, significant operational learnings were gained from pilot tests that will contribute greatly to the commercial success of PCC. Based on a thorough techno-economic assessment (TEA) of the Linde-BASF PCC process integrated with a 550 MWe supercritical coal-fired power plant, the net efficiency of the integrated power plant with CO 2 capture is increased from 28.4% with the DOE/NETL Case 12 reference to 30.9% with the Linde-BASF PCC plant previously presented utilizing the BASF OASE® blue solvent [Ref. 4], and is further increased to 31.4% using a Linde-BASF PCC plant with BASF OASE® blue solvent and an advanced stripper interstage heater (SIH) configuration. The Linde-BASF PCC plant incorporating the BASF OASE® blue solvent also results in significantly lower overall capital costs, thereby reducing the cost of electricity (COE) and cost of CO 2 captured from $147.25/MWh and $56.49/MT CO 2 , respectively, for the reference DOE/NETL Case 12 plant, to $128.49/MWh and $41.85/MT CO2 for process case LB1, respectively, and $126.65/MWh and $40.66/MT CO 2 for process case SIH, respectively. With additional innovative Linde-BASF PCC process configuration improvements, the COE and cost of CO 2 captured can be further reduced to $125.51/MWh and $39.90/MT CO 2 for a further optimized PCC process defined as LB1-CREB. Most notably, the Linde-BASF process options assessed have already demonstrated the potential to lower the cost of CO 2 captured below the DOE target of $40/MT CO 2 at the 550 MWe scale for second generation PCC technologies. Project organization, structure, goals, tasks, accomplishments, process criteria and milestones will be presented in this report along with highlights and key results from parametric and long-duration testing of the Linde-BASF PCC pilot. The parametric and long-duration testing campaigns were aimed at validating the performance of the PCC technology against targets determined from a preliminary techno-economic assessment. The stability of the solvent with extended operation in a realistic power plant setting was measured with performance verified. Additionally, general solvent classification information, process operating conditions, normalized solvent performance data, solvent stability test results, flue gas conditions data, CO 2 purity data in the gaseous product stream, steam requirements and process flow diagrams, and updated process economic data for a scaled-up 550 MWe supercritical power plant with CO 2 capture are presented and discussed in this report.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Actinide Molten Salts: A Machine-Learning Potential Molecular Dynamics Study

We know that actinide molten salts represent a class of important materials in nuclear energy. Understanding them at a molecular level is critical to proper and optimal design of relevant technological applications. Yet, owing to the complexity of electronic structure due to the 5f orbitals, computational studies of heavy elements in condensed phases using ab initio potentials to study the structure and dynamics of these elements embedded in molten salts are difficult. This lack of efficient computational protocols makes it difficult to obtain information on properties that require extensive statistical sampling like transport. To tackle this problem, we adopted a machine-learning approach to study ThCl 4 -NaCl and UCl 3 -NaCl binary systems. The machine-learning potential, with the density functional theory accuracy, allows us to obtain long molecular dynamics trajectories (ns) for large systems (10 3 atoms) at a considerably low computing cost, thereby efficiently gaining information about their bonding structures, thermodynamics, and dynamics at a range of temperature. We observed a considerable change in the coordination environments of actinide elements and their characteristic coordination-sphere lifetime. Our study also suggests that actinides in molten salts may not follow well known entropy-scaling laws.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Distributionally Robust Decentralized Volt-Var Control With Network Reconfiguration

Here, this paper presents a decentralized volt-var optimization (VVO) and network reconfiguration strategy to address the challenges arising from the growing integration of distributed energy resources, particularly photovoltaic (PV) generation units, in active distribution networks. To reconcile control measures with different time resolutions and empower local control centers to handle intermittency locally, the proposed approach leverages a two-stage distributionally robust optimization; decisions on slow-responding control measures and set points that link neighboring subnetworks are made in advance while considering all plausible distributions of uncertain PV outputs. We present a decomposition algorithm with an acceleration scheme for solving the proposed model. Numerical experiments on the IEEE 123 bus distribution system are given to demonstrate its outstanding out-of-sample performance and computational efficiency, which suggests that the proposed method can effectively localize uncertainty via risk-informed proactive timely decisions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

A continuous surface reconstruction method on point cloud captured from a 3D surface photogrammetry system

Purpose: To accurately and efficiently reconstruct a continuous surface from noisy point clouds captured by a surface photogrammetry system (VisionRT). Methods: The authors have developed a level-set based surface reconstruction method on point clouds captured by a surface photogrammetry system (VisionRT). The proposed method reconstructs an implicit and continuous representation of the underlying patient surface by optimizing a regularized fitting energy, offering extra robustness to noise and missing measurements. By contrast to explicit/discrete meshing-type schemes, their continuous representation is particularly advantageous for subsequent surface registration and motion tracking by eliminating the need for maintaining explicit point correspondences as in discrete models. The authors solve the proposed method with an efficient narrowband evolving scheme. The authors evaluated the proposed method on both phantom and human subject data with two sets of complementary experiments. In the first set of experiment, the authors generated a series of surfaces each with different black patches placed on one chest phantom. The resulting VisionRT measurements from the patched area had different degree of noise and missing levels, since VisionRT has difficulties in detecting dark surfaces. The authors applied the proposed method to point clouds acquired under these different configurations, and quantitatively evaluated reconstructed surfaces by comparing against a high-quality reference surface with respect to root mean squared error (RMSE). In the second set of experiment, the authors applied their method to 100 clinical point clouds acquired from one human subject. In the absence of ground-truth, the authors qualitatively validated reconstructed surfaces by comparing the local geometry, specifically mean curvature distributions, against that of the surface extracted from a high-quality CT obtained from the same patient. Results: On phantom point clouds, their method achieved submillimeter reconstruction RMSE under different configurations, demonstrating quantitatively the faith of the proposed method in preserving local structural properties of the underlying surface in the presence of noise and missing measurements, and its robustness toward variations of such characteristics. On point clouds from the human subject, the proposed method successfully reconstructed all patient surfaces, filling regions where raw point coordinate readings were missing. Within two comparable regions of interest in the chest area, similar mean curvature distributions were acquired from both their reconstructed surface and CT surface, with mean and standard deviation of (μ{sub recon} = − 2.7 × 10{sup −3} mm{sup −1}, σ{sub recon} = 7.0 × 10{sup −3} mm{sup −1}) and (μ{sub CT} = − 2.5 × 10{sup −3} mm{sup −1}, σ{sub CT} = 5.3 × 10{sup −3} mm{sup −1}), respectively. The agreement of local geometry properties between the reconstructed surfaces and the CT surface demonstrated the ability of the proposed method in faithfully representing the underlying patient surface. Conclusions: The authors have integrated and developed an accurate level-set based continuous surface reconstruction method on point clouds acquired by a 3D surface photogrammetry system. The proposed method has generated a continuous representation of the underlying phantom and patient surfaces with good robustness against noise and missing measurements. It serves as an important first step for further development of motion tracking methods during radiotherapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Incentive-Based Voltage Regulation in Distribution Networks

This paper considers distribution networks fea- turing distributed energy resources, and designs incentive-based mechanisms that allow the network operator and end-customers to pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. Two different network-customer coordination mechanisms that require different amounts of information shared between the network operator and end-customers are developed to identify a solution of a well-defined social-welfare maximization prob- lem. Notably, the signals broadcast by the network operator assume the connotation of prices/incentives that induce the end- customers to adjust the generated/consumed powers in order to avoid the violation of the voltage constraints. Stability of the proposed schemes is analytically established and numerically corroborated.

24 POWER TRANSMISSION AND DISTRIBUTION↗