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At least 361 records · Page 20

System and method of storing and analyzing information

A system and method of storing and analyzing information is disclosed. The system includes a compiler layer to convert user queries to data parallel executable code. The system further includes a library of multithreaded algorithms, processes, and data structures. The system also includes a multithreaded runtime library for implementing compiled code at runtime. The executable code is dynamically loaded on computing elements and contains calls to the library of multithreaded algorithms, processes, and data structures and the multithreaded runtime library.

Feo, John T.↗

Carbon dioxide capture with aqueous amino acids: Mechanistic study of amino acid regeneration by guanidine crystallization and process intensification

CO 2 capture from powerplant-generated flue gas via a phase-changing process involving absorption with aqueous amino acids (e.g., glycine or sarcosine) and bicarbonate crystallization with bis-iminoguanidines (e.g., glyoxal-bis-iminoguanidine or GBIG) is investigated in this paper. This process is of high interest due to its potential to decrease the energy penalty for CO 2 capture by significantly reducing the solvent regeneration energy typically associated with aqueous amine solvents. A critical step in the proposed CO 2 capture mechanism is the regeneration of the amino acid by removal of protons and bicarbonate ions from solution through crystallization of GBIGH 2 2+ bicarbonate salt. Here, we investigated the thermodynamics and kinetics of glycine regeneration by crystallization of GBIGH 2 2+ (HCO 3 – ) 2 (H 2 O) 2 . A theoretical model was developed and compared to experimental data to simulate and predict the glycine regeneration and determine its reaction mechanism. This combined experimental and theoretical study led to the conclusion that, while the GBIGH 2 2+ bicarbonate crystallization step provides most of the thermodynamic driving force for the glycine regeneration, the rate-limiting step is the protonation of GBIG prior to crystallization. The CO 2 loading and amino acid regeneration steps were combined into a single, intensified process using a bubble column reactor. The CO 2 loading capacity of GBIG was experimentally determined to be roughly 1.36 mol CO 2 per mol GBIG. These results provide the fundamental basis for developing an effective carbon capture technology with phase-changing amino acid/guanidine absorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparative Analysis of HEATNETS for Geothermal Network Performance

Thermal energy networks (TENs), also known as 5th generation district energy systems, or more specifically geothermal networks when exchanging heat with geothermal boreholes, are an important technology for decarbonization. In these networks an ambient loop connects buildings and thermal sources, such as a borehole field, to exchange energy and maintain a desired loop temperature. Water-source heat pumps are used at the buildings to connect to the ambient or thermal loop to meet to the building heating and cooling loads and maintain comfort. A semi-transient, reduced-order technical model and techno-economic model, called HEATNETS, has been developed at NREL that captures the flow of energy around a TEN. In this work, a comparison of the HEATNETS technical model and a well-known coding platform used for modeling geothermal networks, TRNSYS, has been completed for a proposed geothermal network as a verification and validation process. Hourly data provided from the TRNSYS simulation included building loads, pumping power, heat pump power, temperature entering and leaving the borehole field, and mass flow rates. The hourly borehole temperatures were used to create a linear regression model utilized in HEATNETS to estimate the borehole field heat exchange. The building loads and mass flow rates were direct inputs to HEATNETS while the pumping power, heat pump power, borehole temperatures, and coefficients of performance were all simulated and calculated by HEATNETS, allowing for direct comparison of the thermal energy transfer HEATNETS considers the full process from design inputs to economic outputs and can provide modeling options for high-level initial system design and operational optimization. This study focuses on a validation of HEATNETS using results from TRNSYS. HEATNETS is not intended to replace other modeling tools, but this work demonstrates, via a comparison with an industry standard code, that HEATNETS can be a unique, high-level and rapid modeling tool for estimating the performance of a full geothermal network system.

15 GEOTHERMAL ENERGY↗

Identifying electrochemical processes by distribution of relaxation times in proton exchange membrane electrolyzers

Distribution of relaxation time (DRT) is used to interpret electrochemical impedance spectroscopy (EIS) for proton exchange membrane (PEM) water electrolyzers, with an attempt to separate overlapped relaxation processes in Nyquist plots. By varying operating conditions and catalyst loadings, four main relaxation peaks arising from EIS can be identified and successfully separated from low to high frequencies as (P1) mass transport, (P2) oxygen evolution reaction kinetics, (P3) reaction kinetics (with faster time constant than P2), and (P4) ionic transport. Here, the shape, height, and frequency of the DRT peaks change with different membrane electrode assembly (MEA) configurations. Electron microscopy reveals distinct features from the cross-sectioned MEAs which verify critical DRT results in that increasing the iridium (Ir)-anode loading from 0.2 mgIr/cm 2 to 1.5 mgIr/cm 2 reduces kinetic losses due to higher site-access; a thick and compacted anode, however, also triggers higher ohmic resistances from membrane/catalyst layer hydration and increases transport losses due to longer ionomer pathways. DRT provides higher resolution to EIS for deconvoluting processes with different relaxation times and the quantification of DRT peaks improves the accounting of total losses from each process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparative Analysis of HEATNETS for Geothermal Network Performance: Preprint

Thermal energy networks (TENs), also known as 5th generation district energy systems, or more specifically geothermal networks when exchanging heat with geothermal boreholes, are an important technology for decarbonization. In these networks an ambient loop connects buildings and thermal sources, such as a borehole field, to exchange energy and maintain a desired loop temperature. Water-source heat pumps are used at the buildings to connect to the ambient or thermal loop to meet to the building heating and cooling loads and maintain comfort. A semi-transient, reduced-order technical model and techno-economic model, called HEATNETS, has been developed at NREL that captures the flow of energy around a TEN. In this work, a comparison of the HEATNETS technical model and a well-known coding platform used for modeling geothermal networks, TRNSYS, has been completed for a proposed geothermal network as a verification process. Hourly data provided from the TRNSYS simulation included building loads, pumping power, heat pump power, temperature entering and leaving the borehole field, and mass flow rates. The hourly borehole temperatures were used to create a linear regression model utilized in HEATNETS to estimate the borehole field heat exchange. The building loads and mass flow rates were direct inputs to HEATNETS while the pumping power, heat pump power, borehole temperatures, and coefficients of performance were all simulated and calculated by HEATNETS, allowing for direct comparison of the thermal energy transfer, rather than also comparing control systems responses. HEATNETS considers the full process from design inputs to economic outputs and can provide modeling options for high-level initial system design and operational optimization. This study shows that HEATNETS, while not intended to replace other modeling tools, can be a unique modeling tool for the performance of a full geothermal network system.

15 GEOTHERMAL ENERGY↗

Enriching Load Data Using Micro-PMUs and Smart Meters

In modern distribution systems, load uncertainty can be fully captured by micro-PMUs, which can record high-resolution data; however, in practice, micro-PMUs are installed at limited locations in distribution networks due to budgetary constraints. In contrast, smart meters are widely deployed but can only measure relatively low-resolution energy consumption, which cannot sufficiently reflect the actual instantaneous load volatility within each sampling interval. In this paper, we have proposed a novel approach for enriching load data for service transformers that only have low-resolution smart meters. The key to our approach is to statistically recover the high-resolution load data, which is masked by the low-resolution data, using trained probabilistic models of service transformers that have both high- and low-resolution data sources, i.e., micro-PMUs and smart meters. The overall framework consists of two steps: first, for the transformers with micro-PMUs, a Gaussian Process is leveraged to capture the relationship between the maximum/minimum load and average load within each low-resolution sampling interval of smart meters; a Markov chain model is employed to characterize the transition probability of known high-resolution load. Next, the trained models are used as teachers for the transformers with only smart meters to decompose known low-resolution load data into targeted high-resolution load data. The enriched data can recover instantaneous load uncertainty and significantly enhance distribution system observability and situational awareness. Here, we have verified the proposed approach using real high- and low-resolution load data.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Sorbmatech{sup R}Cs, an Innovative Highly Selective Cs Sorbent for Wastewater Decontamination - 20065

The treatment of radioactive wastewater from the operating nuclear industry (energy production, reprocessing of spent fuel, decommissioning of shut-down facilities, etc.) or in case of incidental or accidental situation (such as Fukushima Daichii NPP accident) is an important issue requiring constant improvement of the technologies and techniques used to prevent radioactive releases into the environment and/or to reduce the production of secondary waste. CEA, Orano and CTI are collaborating since 2014, with the support of the French government's program 'investments for the future', to develop Sorbmatech{sup R}Cs, an innovative and patented selective sorbent (Grandjean and Barre 2014) to deal with the removal of radioactive {sup 137}Cs, one of the most hazardous isotope to be managed in nuclear waste, highly efficient either in agitated reactor or in column process. Sorbmatech{sup R}Cs sorbent consists of mesoporous silica particles loaded with potassium-copper hexacyanoferrate nanoparticles (KCu-HCF). This peculiar structure enables much faster sorption kinetics compared to denser crystalline structures, such as Silicotitanate or Zeolite sorbents, whose drawback consists in hindering the diffusion process through the material, and whose larger sorbent particles slow down the ion exchange process. The equilibrium of Sorbmatech{sup R}Cs is reached in few minutes, even at high flow rates in a fixed-bed column process (up to 10 m.h{sup -1} Darcy velocity) with low drop pressure. Moreover, Sorbmatech{sup R}Cs can be used over a wide pH range from 2 to 10 and has a very high selectivity towards {sup 137}Cs even in brine solution (saline, mineral or sea water). This new sorbent also has a K{sub d} higher than 10{sup 5} mL.g{sup -1} depending on the salinity of the wastewater, enabling a highly efficient removal of Cs trace in radioactive wastewater compared to Cs selective sorbent such as Zeolites and Silicotitanates. Its radiological resistance enables the treatment of high, medium and low activity wastewater. The CEA-Orano-CTI/ALSYS partnership leads to the development of a simple and low-cost synthetic route, which demonstrated large-scale manufacturing of the product on a batch of 100 kg. Two products have been developed and are ready for short run market introduction so far with grain size well adapted either for column processes or agitated reactors.. Finally, the industrial implementation has been studied and largely benefits from the properties of the sorbent. Indeed, its high sorption kinetics enable high flow rates resulting in a decrease of operation times, unit sizes, and volumes of secondary waste produced. Moreover, Sorbmatech{sup R}Cs is designed to be combined into a full and integrated solution, ranging from preliminary optimization of operating conditions through numerical dimensioning model, industrial implementation and treatment of the wastewater (through cartridge or preconditioned columns systems developed thanks to Orano's extensive expertise), to long-term stabilization of generated waste (under progress). (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Evaluation of the Room Temperature Field Quality Measurements of HL-LHC MQXFA Magnet Assemblies

As a member of the multi-lab U.S. High Luminosity LHC Accelerator Upgrade Project (HL-LHC AUP), Lawrence Berkeley National Laboratory (LBNL) is assembling high-field Nb3Sn low-beta MQXFA quadrupole magnets for eventual installation at CERN as part of the HL-LHC upgrade. Each magnet undergoes room temperature magnetic measurements at two points during the assembly process: once after completion of the coil pack sub-assembly and once after the magnet is fully assembled and pre-loaded. Beyond its use to verify that each magnet assembly can meet operational requirements, the data from this two-stage measurement process allow for investigation into the impact of the pre-loading operation on field quality. Recent measurements on magnet rebuilds as well as exploratory coil pack reconfigurations also provide an opportunity to see in isolation the effects of changes to a magnet’s coil selection or coil layout. In this work, we present the magnetic measurement results of MQXFA magnets assembled or currently in process, focusing particularly on magnets with data corresponding to multiple builds, and discuss trends and insights which may be beneficial for the remaining MQXFA magnet production or for future Nb3Sn accelerator magnets.

Doyle, Jennifer [LBNL, Berkeley] (ORCID:0009000079↗

Evaluation Of Glass Density to Support the Estimation of Fissile Mass Loadings in Sludge Batch 10 Glasses

Per a directive from the Department of Energy Savannah River Operations Office (DOE-SR) in 2008, the fissile mass loading concentration must remain below 897 g/m 3 in each high-level waste (HLW) glass canister produced by the Defense Waste Processing Facility (DWPF). To support Sludge Batch 5 (SB5) processing, the Savannah River National Laboratory (SRNL) developed a technical basis that facilitates the evaluation of fissile mass loading of the glass product. The calculation is based on the iron (Fe) concentration in the glass as determined by measurements from the Slurry Mix Evaporator acceptability analysis as well as the glass density. In April 2022, a subsequent DOE-SR directive increased the fissile mass loading limit to 2500 g/m 3 beginning with Sludge Batch 11. Thus, the 897 g/m 3 limit still applies to Sludge Batch 10 (SB10) processing. For SB5 through initial Sludge Batch 9 (SB9) processing prior to coupled operation with the Salt Waste Processing Facility (SWPF), SRNL provided DWPF a bounding glass density value that was based on a statistical evaluation of density measurements. To eliminate the need for experimental work, a composition-based density model for HLW glasses was developed at SRNL in 2019. The objective of this report is to present the bounding glass density determined with the composition-based density model for SB10 sludge-only (SO) and coupled processing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Evaluation of Glass Density to Support the Estimation of Fissile Mass Loadings in Sludge Batch 10 Glasses

Per a directive from the Department of Energy Savannah River Operations Office (DOE-SR) in 2008, the fissile mass loading concentration must remain below 897 g/m 3 in each high-level waste (HLW) glass canister produced by the Defense Waste Processing Facility (DWPF). To support Sludge Batch 5 (SB5) processing, the Savannah River National Laboratory (SRNL) developed a technical basis that facilitates the evaluation of fissile mass loading of the glass product. The calculation is based on the iron (Fe) concentration in the glass as determined by measurements from the Slurry Mix Evaporator acceptability analysis as well as the glass density. In April 2022, a subsequent DOE-SR directive increased the fissile mass loading limit to 2500 g/m 3 beginning with Sludge Batch 11. Thus, the 897 g/m 3 limit still applies to Sludge Batch 10 (SB10) processing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Palladium-Percolated Networks Enabled by Low Loadings of Branched Nanorods for Enhanced H 2 Separations

Nanoparticles (NPs) at high loadings are often used in mixed matrix membranes (MMMs) to improve gas separation properties, but they can lead to defects and poor processability that impede membrane fabrication. Herein, it is demonstrated that branched nanorods (NRs) with controlled aspect ratios can significantly reduce the required loading to achieve superior gas separation properties while maintaining excellent processability, as demonstrated by the dispersion of palladium (Pd) NRs in polybenzimidazole for H 2 /CO 2 separation. Increasing the aspect ratio from 1 for NPs to 40 for NRs decreases the percolation threshold volume fraction by a factor of 30, from 0.35 to 0.011. An MMM with percolated networks formed by Pd NRs at a volume fraction of 0.039 exhibits H 2 permeability of 110 Barrer and H 2 /CO 2 selectivity of 31 when challenged with simulated syngas at 200 °C, surpassing Robeson's upper bound. In conclusion, this work highlights the advantage of NRs over NPs and nanowires and shows that right-sizing nanofillers in MMMs is critical to construct highly sieving pathways at minimal loadings. In conclusion, this work paves the way for this general feature to be applied across materials systems for a variety of chemical separations.

36 MATERIALS SCIENCE↗

Ammonia Fiber Expansion (AFEX) Pretreatment of Lignocellulosic Biomass

Lignocellulosic materials are plant-derived feedstocks, such as crop residues (e.g., corn stover, rice straw, and sugar cane bagasse) and purpose-grown energy crops (e.g., miscanthus, and switchgrass) that are available in large quantities to produce biofuels, biochemicals, and animal feed. Plant polysaccharides (i.e., cellulose, hemicellulose, and pectin) embedded within cell walls are highly recalcitrant towards conversion into useful products. Ammonia fiber expansion (AFEX) is a thermochemical pretreatment that increases accessibility of polysaccharides to enzymes for hydrolysis into fermentable sugars. These released sugars can be converted into fuels and chemicals in a biorefinery. Here, we describe a laboratory-scale batch AFEX process to produce pretreated biomass on the gram-scale without any ammonia recycling. The laboratory-scale process can be used to identify optimal pretreatment conditions (e.g., ammonia loading, water loading, biomass loading, temperature, pressure, residence time, etc.) and generates sufficient quantities of pretreated samples for detailed physicochemical characterization and enzymatic/microbial analysis. The yield of fermentable sugars from enzymatic hydrolysis of corn stover pretreated using the laboratory-scale AFEX process is comparable to pilot-scale AFEX process under similar pretreatment conditions. This paper is intended to provide a detailed standard operating procedure for the safe and consistent operation of laboratory-scale reactors for performing AFEX pretreatment of lignocellulosic biomass.

09 BIOMASS FUELS↗

Tailoring compatibilization potential of maleic anhydride–grafted polypropylene by sequential rheochemical processing of polypropylene and polyamide 66 blends

Reactive compatibilization of immiscible polymer blends using a preferred compatibilizer leaves the following question: How much loading of a compatibilizer is good enough and what maximum properties can be achieved? A good understanding of the process can help solve the reutilization of mixed waste plastics. Here, the reactive compatibilization of polypropylene-graft-maleic anhydride (PP-g-MAH) on polypropylene/polyamide 66 (PP/PA66) blends is quantitatively assessed using thermorheological, microoptical, spectroscopic, and x-ray scattering-based characterization tools. The overall compositions of all PP(60%)/PA66(30%)/PP-g-MAH(10%) blends are kept constant while systematically controlling the degree of the chemical reaction by varying the sequential addition of PP-g-MAH to the melt mixture. The first feeding of PP-g-MAH (x%, 0 ≤ x ≤ 10) is conducted at 280°C and the second feeding of (10–x)% is at 200°C. During the first step, a larger amount of chemical activity is observed up to 4%–6% addition of PP-g-MAH. Furthermore, the constant chemical composition allows a systematic comparison of the compatibilizer-dependent thermal, rheological, morphological, and mechanical properties. With an increased degree of interfacial reaction, the size of dispersed PA66 domains decreases to register improved interfacial adhesion with the PP matrix, yielding enhanced Young's modulus and absolute failure strength of the isotropic matrix.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Direct ink writing of boron carbide monoliths

Direct ink writing – an extrusion-based additive manufacturing process – followed by pressureless sintering was investigated to produce boron carbide monoliths. The effects of ceramic powder loading and Pluronic binder concentration on the rheology of boron carbide pastes were studied and linked to both processing behaviour and final outcome in terms of sintered density and hardness. The effects of printing parameters, in particular orifice diameter and printing speed, were also investigated. Reducing the size of the extrusion nozzle from 584 μm to 406 μm led to significantly better shape retention, lower surface roughness, as well as higher density and hardness. A 203 μm printing orifice was also trialled but was unsuccessful due to faster drying kinetics that occurred with smaller ceramic struts resulting in rapid warping and nozzle clogging. Carbon-black – 8 wt% relative to B 4 C – acted as an effective sintering aid to increase both density and hardness. After optimisation of feedstock and printing parameters, few-layer samples (3–5 layers) had a density as high as ~ 97 % TD and a hardness of ~ 30 GPa. On the other hand, 18-layer specimens had a sintered density of ~ 87 % TD, despite a fully dense microstructure, due to the formation of a 3D array of inter-strut pores. Nevertheless, several issues that arose during manufacturing and post-processing were detrimental to the density and structural integrity of printed specimens; these issues were identified, discussed, and suggestions for future work are provided in this report.

36 MATERIALS SCIENCE↗

Divertor Plasma Detachment Control Neural Network

DivControlNN is a state-of-the-art software tool that leverages advanced machine learning techniques to predict and control divertor plasma behavior in fusion reactors. Plasma, a highly energetic and electrically charged gas, requires meticulous management to protect reactor components and maintain optimal energy production. Conventional simulation methods, although extremely detailed, typically demand extensive computational time-making them unsuitable for real-time control scenarios. DivControlNN addresses this challenge by learning from tens of thousands of high-fidelity simulations, thereby creating a rapid surrogate model that can deliver near-instantaneous predictions. At the core of its functionality is a sophisticated technique known as latent space mapping, which condenses complex, high-dimensional plasma data into a compact, lower-dimensional representation. This streamlined representation enables the system to quickly forecast essential plasma properties and determine the precise conditions required for effective detachment. Detachment is a crucial process in which the plasma is cooled before reaching the divertor plates, thereby reducing heat loads and mitigating material erosion. In recent experiments conducted on the KSTAR tokamak in South Korea, DivControlNN successfully guided the detachment process without any fine-tuning-even when applied to a new tungsten divertor configuration. By achieving a computational speed-up of over one hundred million times compared to traditional simulation methods while maintaining low prediction errors, DivControlNN stands to significantly enhance real-time control and diagnostic capabilities in future fusion reactors. This breakthrough paves the way for safer, more reliable reactor operation and represents a major advancement toward realizing fusion energy as a practical, sustainable, and clean power source.

Xu, Xueqiao [Lawrence Livermore National Laborator↗

2.3.3.404 - National Lab and University Collaboration for MHK Instrumentation and Data Processing Tools

Field and laboratory validation, testing, demonstration, and operation are critical steps for increasing the technology readiness level of marine energy (ME) converters because they provide high-quality testing and performance data that are critical information used to feed all aspects of technology development. This project, in partnership with industry, enables the marine and hydrokinetic energy (MHK) community to reliably and efficiently collect, process, manage, and share quality data by facilitating access to and development of instrumentation, guidelines and data processing/QA tools. Under this project, open-source data processing code (MHKiT) and tools (ME Data Pipeline, MRE Code Hub, PRIMRE Code Catalog), instrumentation (loads measurements), data acquisition systems (miniDAQ), and measurement guidance tools (Telesto, high EMI guidance) were developed to facilitate the collection and processing of quality laboratory and field data. Overall, this project is intended to improve the quality of the data collected during laboratory and field demonstration projects by standardizing the collection and processing techniques, as well as by improving access to instrumentation, code, and measurement guidance. Quality data will, in turn, lead to improved knowledge capture following ME device testing.

data processing↗

Arbitrary Order Virtual Element Methods for High‐Order Phase‐Field Modeling of Dynamic Fracture

ABSTRACT Accurate modeling of fracture nucleation and propagation in brittle and ductile materials subjected to dynamic loading is important in predicting material damage and failure under extreme conditions. Phase‐field fracture models have garnered a lot of attention in recent years due to their success in representing damage and fracture processes in a wide class of materials and under a variety of loading conditions. Second‐order phase‐field fracture models are by far the most popular among researchers (and increasingly, among practitioners), but fourth‐order models have started to gain broader acceptance since their more recent introduction. The exact solution corresponding to these high‐order phase‐field fracture models has higher regularity. Thus, numerical solutions of the model equations can achieve improved accuracy and higher spatial convergence rates. In this work, we develop a virtual element framework for the high‐order phase‐field model of dynamic fracture. The virtual element method (VEM) can be regarded as a generalization of the classical finite element method. In addition to many other desirable characteristics, the VEM allows computing on polytopal meshes. Here, we use ‐conforming virtual elements and the generalized‐ time integration method for the momentum balance equation, and adopt ‐conforming virtual elements for the high‐order phase‐field equation. We verify our virtual element framework using classical quasi‐static benchmark problems and demonstrate its capabilities with the aid of numerical simulations of dynamic fracture in brittle materials.

42 ENGINEERING↗