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At least 1,171 records · Page 65

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DOE OSTI2014

CFD Simulations of a Regenerative Process for Carbon Dioxide Capture in Advanced Gasification Based Power Systems

This project describes the work carried out to prepare a highly reactive and mechanically strong MgO based sorbents and to develop a Population Balance Equations (PBE) approach to describe the evolution of the particle porosity distribution that is linked with Computational Fluid Dynamics (CFD) to perform simulations of the CO2 capture and sorbent regeneration. A large number of MgO-based regenerable sorbents were prepared using low cost and abundant dolomite as the base material. Among various preparation parameters investigated the potassium/magnesium (K/Mg) ratio was identified as the key variable affecting the reactivity and CO2 capacity of the sorbent. The optimum K/Mg ratio is about 0.15. The sorbent formulation HD52-P2 was identified as the “best” sorbent formulation and a large batch (one kg) of the sorbent was prepared for the detailed study. The results of parametric study indicate the optimum carbonation and regeneration temperatures are 360° and 500°C, respectively. The results also indicate that steam has a beneficial effect on the rate of carbonation and regeneration of the sorbent and that the reactivity and capacity of the sorbent decreases in the cycling process (sorbent deactivation). The results indicate that to achieve a high CO2 removal efficiency, the bed of sorbent should be operated at a temperature range of 370-410°C which also favors production of hydrogen through the WGS reaction. To describe the carbonation reaction kinetics of the MgO, the Variable Diffusivity shrinking core Model (VDM) was developed in this project, which was shown to accurately fit the experimental data. An important advantage of this model is that the changes in the sorbent conversion with time can be expressed in an explicit manner, which will significantly reduce the CFD computation time. A Computational Fluid Dynamic/Population Balance Equations (CFD/PBE) model was developed that accounts for the particle (sorbent) porosity distribution and a new version of the method of moments, called Finite size domain Complete set of trial functions Method Of Moments (FCMOM) was used to solve the population balance equations. The PBE model was implemented in a commercial CFD code, Ansys Fluent 13.0. The code was used to test the model in some simple cases and the results were verified against available analytical solution in the literature. Furthermore, the code was used to simulate CO2 capture in a packed-bed and the results were in excellent agreement with the experimental data obtained in the packed bed. The National Energy Laboratory (NETL) Carbon Capture Unit (C2U) design was used in simulate of the hydrodynamics of the cold flow gas/solid system (Clark et al.58). The results indicate that the pressure drop predicted by the model is in good agreement with the experimental data. Furthermore, the model was shown to be able to predict chugging behavior, which was observed during the experiment. The model was used as a base-case for simulations of reactive flow at elevated pressure and temperatures. The results indicate that by controlling the solid circulation rate, up to 70% CO2 removal can be achieved and that the solid hold up in the riser is one of the main factors controlling the extent of CO2 removal. The CFD/PBE simulation model indicates that by using a simulated syngas with a composition of 20% CO2, 20% H2O, 30% CO, and 30% H2, the composition (wet basis) in the reactor outlet corresponded to about 60% CO2 capture with and exit gas containing 65% H2. A preliminary base-case-design was developed for a regenerative MgO-based pre-combustion carbon capture process for a 500 MW IGCC power plant. To minimize the external energy requirement, an extensive heat integration network was developed in Aspen/HYSYS® to produce the steam required in the regenerator and heat integration. In this process, liquid CO2 produced at 50 atm can easily be pumped and sequestered or stored. The preliminary economic analyses indicate that the estimated cost of carbon v capture is in the range of $31-$44/ton, suggesting that a regenerative MgO-Based process can be a viable option for pre-combustion carbon dioxide capture in advanced gasification based power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

Photochemical Kinetic Modeling of Degradation of Aqueous Polyvinyl Alcohol in a UV/H{sub 2}O{sub 2} Photoreactor

This study presents a photochemical kinetics model to describe the degradation of water-soluble PVA (Polyvinyl Alcohol) polymer in a UV/H{sub 2}O{sub 2} batch reactor. Under the effect of UV light, the photolysis of hydrogen peroxide into hydroxyl radicals can generate a series of polymer scission reactions. For a better understanding and analysis of the UV/H{sub 2}O{sub 2} process in the cracking of the PVA macromolecules, a chemical reaction mechanism of the degradation process and a relevant photochemical kinetics model are developed to describe the disintegration of the polymer chains. Taking into account the probabilistic fragmentation of the polymer, the statistical moment approach is used to model the molar population balance of live and dead polymer chains. The model predicts the PVA molecular weight reduction, the acidity of the solution, and hydrogen peroxide residual. In addition to previously published data collected in this laboratory, a new set of experiments were conducted using a 500 mg/L PVA aqueous for different hydrogen peroxide/PVA ratios for model validation. Measurements of average molecular weights of the polymer, hydrogen peroxide concentrations and pH of the PVA solution were determinant factors in constructing a reliable photochemical model of the UV/H{sub 2}O{sub 2} process. Experimental data showed a decrease in the PVA molecular weight and a buildup of the solution acidity. The experimental data also served to determine the kinetics rate constants of the PVA photochemical degradation and validate the model whose predictions are in good agreement with data. The model can provide a comprehensive understanding of the impact of the design and operational variables.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Data-Driven Protection Software to classify fault locations by protective zone in distribution systems with high PV penetration

The software contains (a) the source codes to generate Point-on-Wave (PoW) transient data for any feeder model in Alternative Transient Program (ATP) format. Codes provide options to change different steady state settings, including the loading condition and PV capacity and transient state setting like faults type, location and initiation time (b) data post-processing source code to converted data from native format to COMTRADE, csv, HDF5 (c) Docker container to train CNN to classify fault locations by protective zone. The container takes dataset and other training parameters (sampling rate, training epochs, batch size etc) as input to train CNN. The container writes back the trained CNN model, training and testing metrics and plots to the local workstation

Ramesh, Meghana↗

DOE OSTI2021

CAZymes from the thermophilic fungus Thermoascus aurantiacus are induced by C5 and C6 sugars

Abstract Background Filamentous fungi are excellent lignocellulose degraders, which they achieve through producing carbohydrate active enzymes (CAZymes). CAZyme production is highly orchestrated and gene expression analysis has greatly expanded understanding of this important biotechnological process. The thermophilic fungus Thermoascus aurantiacus secretes highly active thermostable enzymes that enable saccharifications at higher temperatures; however, the genome-wide measurements of gene expression in response to CAZyme induction are not understood. Results A fed-batch system with plant biomass-derived sugars d -xylose, l -arabinose and cellobiose established that these sugars induce CAZyme expression in T. aurantiacus . The C5 sugars induced both cellulases and hemicellulases, while cellobiose specifically induced cellulases. A minimal medium formulation was developed to enable gene expression studies of T. aurantiacus with these inducers. It was found that d-xylose and l -arabinose strongly induced a wide variety of CAZymes, auxiliary activity (AA) enzymes and carbohydrate esterases (CEs), while cellobiose facilitated lower expression of mostly cellulase genes. Furthermore, putative orthologues of different unfolded protein response genes were up-regulated during the C5 sugar feeding together with genes in the C5 sugar assimilation pathways. Conclusion This work has identified two additional CAZyme inducers for T. aurantiacus , l -arabinose and cellobiose, along with d -xylose. A combination of biochemical assays and RNA-seq measurements established that C5 sugars induce a suite of cellulases and hemicellulases, providing paths to produce broad spectrum thermotolerant enzymatic mixtures.

09 BIOMASS FUELS↗

DOE OSTI2018

Exploration of Processing Parameters of Vacuum Assisted Micelle Confinement Synthesis of Spherical CL-20 Microparticles

We recently developed a vacuum assisted micelle confinement synthesis for spherical microparticles of CL-20 with outstanding monodispersity. These microparticles are promising energetic material for explosive devices with enhanced and predictable performances. In this paper, to facilitate further development and application of this synthesis, the particle growth process was monitored by in-situ dynamic light scattering measurements. The result was interpreted by a finite element model to obtain critical parameters. Finally, these parameters were then used to predict the behavior and product quality of batch synthesis under various operation conditions.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Preparing NERSC users for Cori, a Cray XC40 system with Intel many integrated cores

The newest NERSC supercomputer Cori is a Cray XC40 system consisting of 2,388 Intel Xeon Haswell nodes and 9,688 Intel Xeon-Phi “Knights Landing” (KNL) nodes. Compared to the Xeon-based clusters NERSC users are familiar with, optimal performance on Cori requires consideration of KNL mode settings; process, thread, and memory affinity; fine-grain parallelization; vectorization; and use of the high-bandwidth MCDRAM memory. This paper describes our efforts preparing NERSC users for KNL through the NERSC Exascale Science Application Program, Web documentation, and user training. We discuss how we configured the Cori system for usability and productivity, addressing programming concerns, batch system configurations, and default KNL cluster and memory modes. Here, system usage data, job completion analysis, programming and running jobs issues, and a few successful user stories on KNL are presented.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Synergistic maximization of the carbohydrate output and lignin processability by combinatorial pretreatment

Lignocellulosic biorefineries have gained much attention worldwide as a potential solution to the challenges of energy demand and global climate change. However, the industrial implementation of biorefineries has been hindered by low fermentable sugar yields and low lignin processability. Combinatorial pretreatments with a low holding temperature were investigated in an effort to synergistically improve the carbohydrate output and lignin processability from corn stover. Upon combinatorial pretreatment with 1% H 2 SO 4 for 30 min followed by 1% NaOH for 60 min at 120 °C, glucan and xylan conversion increased by 11.2% and 8.3% respectively relative to single pretreatment. This combinational pretreatment removed the amorphous portion, disrupted the rigid structure, and increased the water holding capacity of corn stover, thus increasing the hydrolysis performance. With whole fractionation by combinatorial pretreatment, glucose and xylose yields were 88.4% and 72.6%, respectively, representing increases of 10.0% and 8.1%. The lignin yield was 19.7% in the solid residue and 77.6% in the liquid stream, which increased by 33.4%. When grown in fed-batch fermentation mode, a record level of polyhydroxyalkanoate (PHA) concentration (1.0 g l –1 ) was obtained using lignin as a carbon source by Pseudomonas putida KT2440. Lignin characterization results showed that combinatorial pretreatment increased the G- and H-lignin content, reduced the β–β and β-O-4 groups, and fractionated more aromatic monomers, thus facilitating lignin processability into PHA. Furthermore, these results highlighted the use of combinational pretreatment at a low holding temperature as a means to synergistically maximize the carbohydrate output and lignin processability, which provides a unique set of features to improve the biorefining performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Tetrafluoroboric Acid Digestion for Accurate Determination of Rare Earth Elements in Coal and Fly Ash by ICP-MS Analysis

Coal and coal-related fly ash often contain rare earth elements (REEs) that have the potential to be utilized as valuable mineral resources. Accurately determining the REE content in coal and fly ash is crucial for resource evaluation. The conventional approach involves using hydrofluoric acid (HF) to dissolve silicates and release REEs, which, however, prolongs the digestion process due to the additional step of complexing fluoride ions (F−) with boric acid (H3BO3). Determining the correct amount of H3BO3 for neutralization can be challenging, and in some instances, the binding of fluoride ions with certain lanthanides (Lns) hampers the accurate determination of all 14 naturally occurring rare earth elements in a single digestion batch by inductively coupled plasma mass spectrometry (ICP-MS). In this study, we present an alternative method that achieves the accurate determination of all 14 naturally occurring REEs using tetrafluoroboric acid (HBF4) followed by ICP-MS analysis. This approach eliminates the need for an F− complexing step. We tested this method on certified REE reference materials, including NIST 1632e (coal) and NIST 1633c (fly ash), as well as the REE geological reference material USGS AGV-1 (andesite). Our results demonstrated excellent recovery rates (relative standard deviation, RSD < ±10%), with a correlation coefficient (r2) exceeding 0.99. Using this method, we investigated the concentrations of all 14 REEs in coal and fly ash samples collected from various locations in the southwestern USA. This improved digestion technique streamlines the analysis process and enhances the accuracy of REE determination, facilitating a more comprehensive evaluation of REE-rich coal and fly ash deposits for resource exploration.

58 GEOSCIENCES↗

DOE OSTI2025

Isolation and conversion of electrolyte components into a value-added product

The overall objective of this work was to develop a process for effectively (i) recycling the electrolyte components from the end-of-life batteries and reduce the environmental hazard, (ii) understand the fundamental differences between pristine and recycled electrolyte components, (iii) electrochemically and analytically evaluate the recycled electrolyte components and (iv) establish deviations from the pristine electrolyte, and effectively separation of value-added product. We focused on determining scaling up the electrolyte recovery process by distillation of end-of-life batteries to get yield enough to use it for electrolyte formulation of reuse in the battery cell. The used cells from the ORNL battery manufacture facility (BMF)as well as received from the industry partner, Austin Elements Inc., was scaled to 10 used multilayered pouch cells in each batch of distillation and systematically separated and identified the electrolyte components of the used cells with FTIR and NMR studies. We were able to recovery 10g of solvent mass from the used pouch cells. NMR spectroscopy showed that the solvent was pure EMC,DMC and the sample was used to make a new battery cell. The end-of-life battery, it was noted that some cells were visually drier than the other cells and were more advanced in aged. In that case, even though the same distillation conditions were utilized, no usable mass of electrolyte solvent was recovered. It is expected that most of the solvent was decomposed during the battery charge-discharge cycling. The solid salt residue was separated by chemical and water treatment processes. Components of resulting solid product was analyzed by XRD and XPS measurements. The solid products are very much related to the salts used in the electrolyte solution.

25 ENERGY STORAGE↗

DOE OSTI2025

Isolation and Conversion of Electrolyte Components into a Value-Added Product

The overall objective of this work was to develop a process for effectively (i) recycling the electrolyte components from the end-of-life batteries and reduce the environmental hazard, (ii) understand the fundamental differences between pristine and recycled electrolyte components, (iii) electrochemically and analytically evaluate the recycled electrolyte components and (iv) establish deviations from the pristine electrolyte, and effectively separation of value-added product. We focused on determining scaling up the electrolyte recovery process by distillation of end-of-life batteries to get yield enough to use it for electrolyte formulation of reuse in the battery cell. The used cells from the ORNL battery manufacture facility (BMF) as well as received from the industry partner, Austin Elements Inc., was scaled to 10 used multilayered pouch cells in each batch of distillation and systematically separated and identified the electrolyte components of the used cells with FTIR and NMR studies. We were able to recovery 10g of solvent mass from the used pouch cells. NMR spectroscopy showed that the solvent was pure EMC, DMC and the sample was used to make a new battery cell. The end-of-life battery, it was noted that some cells were visually drier than the other cells and were more advanced in aged. In that case, even though the same distillation conditions were utilized, no usable mass of electrolyte solvent was recovered. It is expected that most of the solvent was decomposed during the battery charge-discharge cycling. The solid salt residue was separated by chemical and water treatment processes. Components of resulting solid product was analyzed by XRD and XPS measurements. The solid products are very much related to the salts used in the electrolyte solution.

25 ENERGY STORAGE↗

DOE OSTI2022

Comparative Study of Flash and Acid Hydrolysis of Microalgae (Scenedesmus sp.) for the Recovery of Biochemicals and Production of Porous Biocarbon Nanosheets

An integrated biorefinery concept is a novel and economical process intensification methodology for efficient utilization of biomass components. In this research, microalgae (Scenedesmus sp.) slurry with biomass concentration of 8.5 wt.% was parallelly fractionated using two techniques: 'flash hydrolysis (FH)' and 'acid hydrolysis (AH)'. FH was performed at 240 degrees C with a residence time of 10 +/- 2 s in a continuous flow reactor, whereas AH was performed at 155 degrees C and reaction time of 15 min in a batch reactor. About 63% of microalgal biomass was solubilized in liquid hydrolysate through both FH and AH. However, AH had an advantage over FH in recovering microalgae proteins and carbohydrates. FAME recovery through solvent extraction from FH and AH derived wet solids (insoluble microalgae) was 40 and 63%, respectively. Finally, the FH- and AH-derived post extraction solid residue was thermally activated using K2CO3 to produce highly microporous biocarbon nanosheets with BET surface areas of 712 and 1289 m2 g-1, respectively. Overall, an integrated process was developed using two potential hydrolysis techniques to maximize utilization of microalgae components.

BASIC BIOLOGICAL SCIENCES,BIOMASS FUELS↗

DOE OSTI2016

Analysis Of Condensate Samples In Support Of The Antifoam Degradation Study

The degradation of Antifoam 747 to form flammable decomposition products has resulted in declaration of a Potential Inadequacy in the Safety Analysis (PISA) for the Defense Waste Processing Facility (DWPF). Savannah River National Laboratory (SRNL) testing with simulants showed that hexamethyldisiloxane (HMDSO), trimethylsilanol (TMS), and 1-propanal are formed in the offgas from the decomposition of the antifoam. A total of ten DWPF condensate samples from Batch 735 and 736 were analyzed by SRNL for three degradation products and additional analytes. All of the samples were analyzed to determine the concentrations of HMDSO, TMS, and propanal. The results of the organic analysis found concentrations for propanal and HMDSO near or below the detection limits for the analysis. The TMS concentrations ranged from below detection to 11 mg/L. The samples from Batch 736 were also analyzed for formate and oxalate anions, total organic carbon, and aluminum, iron, manganese, and silicon. Most of the samples contained low levels of formate and therefore low levels of organic carbon. These two values for each sample show reasonable agreement in most cases. Low levels of all the metals (Al, Fe, Mn, and Si) were present in most of the samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

ANALYSIS OF CONDENSATE SAMPLES IN SUPPORT OF THE ANTIFOAM DEGRADATION STUDY

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Production of Low Enriched Uranium Nitride Kernels for TRISO Particle Irradiation Testing

A large batch of UN microspheres to be used as kernels for TRISO particle fuel was produced using carbothermic reduction and nitriding of a sol-gel feedstock bearing tailored amounts of low-enriched uranium (LEU) oxide and carbon. The process parameters, established in a previous study, produced phasepure NaCl structure UN with dissolved C on the N sublattice. The composition, calculated by refinement of the lattice parameter from X-ray diffraction, was determined to be UC 0.27 N 0.73 . The final accepted product weighed 197.4 g. The microspheres had an average diameter of 797±1.35 μm and a composite mean theoretical density of 89.9±0.5% for a solid solution of UC and UN with the same atomic ratio; both values are reported with their corresponding calculated standard error.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

A dictionary learning algorithm for compression and reconstruction of streaming data in preset order

There has been an emerging interest in developing and applying dictionary learning (DL) to process massive datasets in the last decade. Many of these efforts, however, focus on employing DL to compress and extract a set of important features from data, while considering restoring the original data from this set a secondary goal. On the other hand, although several methods are able to process streaming data by updating the dictionary incrementally as new snapshots pass by, most of those algorithms are designed for the setting where the snapshots are randomly drawn from a probability distribution. In this paper, we present a new DL approach to compress and denoise massive dataset in real time, in which the data are streamed through in a preset order (instances are videos and temporal experimental data), so at any time, we can only observe a biased sample set of the whole data. Here, our approach incrementally builds up the dictionary in a relatively simple manner: if the new snapshot is adequately explained by the current dictionary, we perform a sparse coding to find its sparse representation; otherwise, we add the new snapshot to the dictionary, with a Gram-Schmidt process to maintain the orthogonality. To compress and denoise noisy datasets, we apply the denoising to the snapshot directly before sparse coding, which deviates from traditional dictionary learning approach that achieves denoising via sparse coding. Compared to full-batch matrix decomposition methods, where the whole data is kept in memory, and other mini-batch approaches, where unbiased sampling is often assumed, our approach has minimal requirement in data sampling and storage: i) each snapshot is only seen once then discarded, and ii) the snapshots are drawn in a preset order, so can be highly biased. Through experiments on climate simulations and scanning transmission electron microscopy (STEM) data, we demonstrate that the proposed approach performs competitively to those methods in data reconstruction and denoising.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1978

User's guide to SFTRAN/1100

Extensions and improvements were made to SFTRAN, a structured programming language. This language was implemented as a precompiler that translates from SFTRAN to FORTRAN. It was available to batch and conversational users of the UNIVAC 1100 computer system. The SFTRAN language and its use are described. In addition, conversational time-sharing system command subroutines were implemented that eliminated the complications of dealing with extra files and processing steps that the use of a precompiler would otherwise require. These command subroutines are reported, and their use is illustrated by examples.

Ford, W. F.↗

DOE OSTI2021

BETO 2021 Peer Review - ChemCatBio Data Hub 2.6.2.500

The goal of the ChemCatBio DataHub project is to accelerate the catalyst and process development cycle by developing transformational tools for prediction and collaboration in catalyst R&D. The project is currently focused on the development of the Catalyst Property Database (CPD), a free and public resource released in September 2020. The CPD was designed in response to the observation that when data, such as computed reaction energetics, is used in catalyst design, it is almost always generated by the researchers seeking to use it, even if similar data has been published previously. One barrier to data reuse that results in this duplication of effort is the difficult process of finding and applying published data, which can be slow, error-prone, and manual. The CPD seeks to overcome these challenges by creating a centralized, searchable database of quality catalyst property data. At present, the CPD contains computed adsorption energies for intermediates along catalytic pathways. During FY21 and FY22, development of the CPD continues with a focus on external users and meeting their requirements. A batch upload capability, training and curation procedures, user interviews, and a demonstration of the CPD's utility in accelerating catalyst research are planned. Overall, the Data Hub project and CPD aim to reduce the time and cost of catalyst research by harnessing the power of data in catalyst discovery.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Effects of Metal and Metal Ion on Biomethane Productivity during Anaerobic Digestion of Dairy Manure

To overcome major limiting factors of microbial processes in anaerobic digestion (AD), metal and metal ions have been extensively studied. However, there is confusion about the effects of metals and metal ions on biomethane productivity in previous research. In this study, Zn and Zn 2+ were selected as representatives of metals and metal ions, respectively, to investigate the effects on biomethane productivity. After the metals and metal ions at different concentrations were added to the batch AD experiments under the same mesophilic conditions, a Zn dose of 1 g/L and a Zn 2+ dose of 4 mg/L were found to cause the highest biomethane production, respectively. The results indicate that metal (Zn) and metal ion (Zn 2+ ) have different mechanisms to improve AD performance. There may be two possible explanations. To act as conductive materials in interspecies electron transfer (IET), relatively high doses of metals (e.g., 1 g/L of Zn, 10 g/L of Fe) are needed to bridge the electron transfer from syntrophic bacteria to methanogenic archaea in the AD process. As essential mineral nutrients, the AD system requires relatively low doses of metal ions (e.g., 4 mg/L of Zn 2+ , 5 mg/L of Fe 2+ ) to supplement the component of various enzymes that catalyze anaerobic reactions and transformations. This research will provide clear insight for selecting appropriate amounts of metals or metal ions to enhance biomethane productivity for industrial AD processes.

09 BIOMASS FUELS↗