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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Developing New Polymeric Powder Feedstocks for Selective Laser Sintering: Emphasizing Particle Size and Shape

Although selective laser sintering is considered a major player in the additive manufacturing community, significant limitations exist when it comes to processing the polymeric powder feedstocks in the laser sintering machine. While these limitations – such as inadequate and uneven heating and complex thermal phenomena leading to curling and shrinkage – cannot be ignored and are being addressed in the community, it is also vitally important to turn our attention to the expansion of commercially available powder feedstocks. A major drawback of SLS is the lack of available feedstocks. At Los Alamos National Laboratory, a primary desire for advancement in the manufacturing or development of new feedstocks lies in the nuclear weapons applications program. New feedstocks with greater thermal stability and performance would provide the opportunity for insertion of production parts, rather than just prototype parts. Additionally, the ability to print with so-called commodity polymers like polyethylene and polypropylene poses great economic advantages for prototyping and production of large batches of parts. However, a gap exists between the Lab’s needs and what is commercially available – a gap which could be filled by collaboration with the broader industrial sector. Furthermore, connecting with and building relationships with industry partners allows for greater control and input in the developmental process of new powders. This would provide reliable feedstocks, improved quality assurance, and overall higher performance of processes across the additive manufacturing community.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Process for producing redox shuttles

The invention provides a method for preparing 1,4-di-tert-butyl-2,5-bis(2-methoxyethoxy)benzene, the method comprising reacting 2,5-di-tert-butylbenzene-1,4-diol with cesium carbonate and halogenated ether in dimethyl formamide. The method yields 500 gram batches at a time, or multiples thereof. The method enables the industrial production of redox shuttles for use in lithium ion battery systems.

Pupek, Krzysztof Z.↗
DOE OSTI2022

Selective hydrodeoxygenation of 5-hydroxymethylfurfural (HMF) to 2,5-dimethylfuran (DMF) over carbon supported copper catalysts using isopropyl alcohol as a hydrogen donor

Selective hydrodeoxygenation (HDO) of 5-hydroxymethylfurfural to 2,5-dimethylfuran is of great importance. Here, we reveal a simple pathway for green and efficient HDO using readily available copper with in-situ hydrogen generation. A highly dispersed Cu/PBSAC catalyst consisting of small metallic Cu 0 nanoparticles carries out isopropyl alcohol (IPA) dehydrogenation and subsequent HDO of HMF. Density functional theory calculations reveal that the dehydrogenation of IPA is more favorable on Cu(211) with a lower energy barrier of ~0.6 eV. This facet exists in a higher ratio on nanosized catalysts. Batch reactions using Cu/PBSAC at 190 °C exhibited 91.9% HMF conversion and 71.7% DMF selectivity in 6 hr, and > 96% DMF yield in 10 hr. The mechanical strength of the carbon support is ideal for continuous processing for increased productivity; we demonstrate a > 90% DMF yield at 1/WHSV of 2.4 hr. The process demonstrated here can be integrated with upstream HMF separation utilizing carbon adsorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Continuous conditional generative adversarial networks for data-driven solutions of poroelasticity with heterogeneous material properties

Machine learning-based data-driven modeling can allow computationally efficient time-dependent solutions of PDEs, such as those that describe subsurface multiphysical problems. In this work, our previous approach (Kadeethum et al., 2021d) of conditional generative adversarial networks (cGAN) developed for the solution of steady-state problems involving highly heterogeneous material properties is extended to time-dependent problems by adopting the concept of continuous cGAN (CcGAN). The CcGAN that can condition continuous variables is developed to incorporate the time domain through either element-wise addition or conditional batch normalization. Moreover, this framework can handle training data that contain different timestamps and then predict timestamps that do not exist in the training data. As a numerical example, the transient response of the coupled poroelastic process is studied in two different permeability fields: Zinn & Harvey transformation and a bimodal transformation. The proposed CcGAN uses heterogeneous permeability fields as input parameters while pressure and displacement fields over time are model output. Our results show that the model provides sufficient accuracy with computational speed-up. This robust framework will enable us to perform real-time reservoir management and robust uncertainty quantification in poroelastic problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Microbial Sulfate Reduction and Perchlorate Inhibition in a Novel Mesoscale Tank Experiment

Typically, microbial sulfate reduction occurs ubiquitously in natural environments. In oil and gas reservoirs, the generation of sulfide (also known as souring) can result in the corrosion of steel infrastructure and downgrading of oil quality, among other environmental and health-related concerns. The complex interplay between hydrological, geochemical, and biological processes during souring is poorly understood, preventing effective treatment and mitigation especially in naturally heterogeneous subsurfaces. In this work, three-dimensional flow tank experiments are utilized as a mesoscale experiment that links well-constrained batch and column experiments to field measurements. The mesoscale tank experiment investigating perchlorate treatment of souring is coupled with reactive transport modeling to understand the effects of heterogeneity on souring and effectiveness of perchlorate treatment. Tracer experiments were performed at the start and end of the experiment to constrain flow pathways and heterogeneities. Isotopic, geochemical, and microbial data revealed that perchlorate effectively inhibited sulfidogenesis and the growth of dominant sulfate reducing Desulfobacteraceae . Perchlorate treatment enriched Desulfobulbaceae , a sulfur-oxidizing group of bacteria, and Sulfurimonas , a potential perchlorate reducer. More organisms, including sulfate reducing bacteria, were observed closer to the influent. Results from the three-dimensional reactive transport model indicate horizontal preferential flows, as a result of the permeability contrast, led to faster bacteria growth (sulfate reducing bacteria) and sulfate reduction in fast flow regions. Our work highlights the control that spatial distributions of hydrologic characteristics exert over reservoir souring and treatment.

58 GEOSCIENCES↗
DOE OSTI2017

Factors Governing the Performance of Bauxite for Fluoride Remediation of Groundwater

Globally, 200 million people drink groundwater contaminated with fluoride concentrations exceeding the World Health Organization's recommended level (WHO-MCL = 1.5 mg F - /L). This study investigates the use of minimally processed (dried/milled) bauxite ore as an inexpensive adsorbent for remediating fluoride-contaminated groundwater in resource-constrained areas. Adsorption experiments in synthetic groundwater using bauxites from Guinea, Ghana, U.S., and India as single-use batch dispersive media demonstrated that doses of ~10-23 g/L could effectively remediate 10 mg F - /L. To elucidate factors governing fluoride removal, bauxites were characterized using X-ray fluorescence, X-ray diffraction, gas-sorption analysis, and adsorption isotherms/envelopes. All ores contained gibbsite, had comparable surface areas (~14-17 m 2 /g), had similar intrinsic affinities and capacities for fluoride, and did not leach harmful ions into product water. Fluoride uptake on bauxite -primarily through ion-exchange- was strongly pH-dependent, with highest removal occurring at pH 5.0-6.0. Dissolution of CaCO 3 , present in trace amounts in India bauxite, significantly hindered fluoride removal by increasing solution pH. We also showed that fluoride remediation with the best-performing Guinea bauxite was ~23-33 times less expensive than with activated alumina. In conclusion, overall, our results suggest that bauxite could be an affordable fluoride-remediation adsorbent with the potential to improve access to drinking water for millions living in developing countries.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

MARBLE: A Multi-GPU Aware Job Scheduler for Deep Learning on HPC Systems

Deep learning (DL) has become a key tool for solving complex scientific problems. However, managing the multi-dimensional large-scale data associated with DL, especially atop extant multiple graphics processing units (GPUs) in modern supercomputers poses significant challenges. Moreover, the latest high-performance computing (HPC) architectures bring different performance trends in training throughput compared to the existing studies. Existing DL optimizations such as larger batch size and GPU locality-aware scheduling have little effect on improving DL training throughput performance due to fast CPU-to-GPU connections. Additionally, DL training on multiple GPUs scales sublinearly. Thus, simply adding more GPUs to a system is ineffective. To this end, we design MARBLE, a first-of-its-kind job scheduler, which considers the non-linear scalability of GPUs at the intra-node level to schedule an appropriate number of GPUs per node for a job. By sharing the GPU resources on a node with multiple DL jobs, MARBLE avoids low GPU utilization in current multi-GPU DL training on HPC systems. Our comprehensive evaluation in the Summit supercomputer shows that MARBLE is able to improve DL training performance by up to 48.3% compared to the popular Platform Load Sharing Facility (LSF) scheduler. Compared to the state-of-the-art of DL scheduler, Optimus, MARBLE reduces the job completion time by up to 47%.

Han, Jingoo↗
DOE OSTI2018

Cold Commissioning Simulant Selection for the Hanford Tank Waste Treatment Plant LAW Facility - 18465

Commissioning the Low-Activity Waste (LAW) Facility of the Hanford Tank Waste Treatment and Immobilization Plant (WTP) will require large volumes (∼2,000,000 liters) of a non-radioactive, chemically analogous waste simulant. Cold commissioning will provide for operator training in an integrated facility, demonstration of mechanical process equipment capacity, environmental performance demonstration of emissions control systems, and process control systems shakedown and tuning. Selection of the cold commissioning simulant is following a structured four-phase process to arrive at the preferred composition and recipe. Phases I, II and III are complete. Phase I laid the framework for decision making with preparation of a Project Management Plan, an update to the Simulant Development, Approval, Validation, and Documentation procedure, and a kickoff meeting to gather stakeholder input into the simulant definition and selection criteria. Phase II consisted of a comprehensive literature search and compilation of LAW simulant recipes, followed by initial screening against the selection criteria identified in Phase I. This process identified 72 candidate simulant recipes and down-selected 9 for further study. Phase III studies involved a) statistical comparisons of the similarity of candidate simulant compositions to the tank waste feed vector, b) process modelling of the commissioning sequence with each simulant to estimate glass former and simulant material consumption, offgas and effluent volumes and compositions, and product glass volumes and compositions, and c) evaluation of simulants against the immobilized LAW glass composition algorithm to determine allo able waste loading to ensure compliance with product specifications and process constraints. The results of these studies identified two of the candidate recipes to be carried forward to full-scale testing. Phase IV consists of testing these two recipes at vendor facilities to determine scalability, fabricability, and stability of the simulants when produced at industrial scale. Scalability is the ability to take a recipe from bench scale (1 to 40 liters) batch size to full scale (>35,000 liters) batch size. Fabricability is the ability of a recipe to be prepared in large batches without the need for complex or expensive mechanical equipment, heating, or cooling systems. Stability is the ability of a simulant to withstand long term storage and variations in environmental conditions without unacceptable changes in key characteristics (the set of chemical, physical, and rheological parameters that the simulant is intended to exhibit during cold commissioning tests). Simulants will also be tested for compatibility with other startup material (i.e., frit), tuning simulants, and environmental performance demonstration test spiking solutions to ensure against unexpected situations. Using a structured process is essential when making high impact decisions such as waste simulant selection. Proper planning and a clear explanation of how the decision process will unfold is key to obtaining stakeholder buy-in as more information is gathered. The documentation resulting from this structured selection process will be compiled and summarized in a Cold Commissioning Simulant Definition deliverable due to the Department of Energy 24 months before the start of Cold Commissioning. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Lab-scale Development of a Hybrid Capture System with Advanced Membrane, Solvent system, and Process Integration

The objective of the project is to achieve lab-scale demonstration of a transformational hybrid membrane/solvent system for the capture of CO 2 from flue gas. A novel process integration scheme was proposed to overcome the low partial pressure of CO 2 present in flue gas. This scheme takes advantage of the potential synergies inherent in the membrane and solvent capture systems. The proposed hybrid technology replaces the second-stage membrane with a solvent capture process. The combustion air is used as a sweeping gas in the solvent stripper. This overall configuration has the major advantages of requiring much less air and eliminating the problems associated with oxygen slip in the membrane-based systems. Even more importantly, because of the presence of the air sweep in the stripper, much lower temperatures are required for solvent regeneration, which enables heat integration to the point that no process steam is required. This project was to perform lab-scale demonstration of Liquid Ion Solutions (LIS) transformational hybrid membrane/solvent system for post-combustion CO 2 capture while demonstrating significant progress toward achievement of the overall fossil energy performance goals of 90% CO 2 capture rate with 95% CO 2 purity at a cost of electricity 30% less than baseline capture approaches. This report is written chronologically based on budget periods. Each budget period discusses the work performed and its results. At the end of each budget period the milestone charts are provided to show the progress. This project was not able to meet its stated goals. The performances of the power plant equipped with the hybrid process and Baseline Case B12B were compared. The simulation results showed that the power plant equipped with hybrid CO2 capture process has an improved thermal efficiency of 33.4% compared to the Baseline Case B12B, which is 32.5%. However, the COE for the hybrid process is $146.3/MWh which is higher than the $142.8/MWh for Case B12B. If this process were to be applied as a retrofit, it may make sense to use this configuration as it does not require any change in an existing plant configuration and steam cycle. However, for a new powerplant the capital cost is higher than the Case B12B. On the membrane development side, we successfully showed that interfacially-controlled envelope (ICE) membranes work. The inclusion of surface modified nano-particles results in much higher gas diffusivities. The Gen-1 ICE membrane developed under this project showed exceptional improved permeability for CO 2 . However, we ran into major problems which were associated with the scalability and reproducibility of the poly(phosphozene) polymers. The issues with scale-up are and batch to batch variability is also discussed. At the end of this report we have provided our recommendations on materials development for better membrane materials and alluded to the use of much simpler chemistry while keeping the concept of ICE membrane intact. It is also clear that vacuum and compression equipment is costly. If a process which can eliminate the use of vacuum and compression equipment would significantly decrease the overall cost of capture. Some thoughts regarding such system is also provided in the outlook portion of this report.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2012

U(VI) Sorption and Reduction Kinetics on the Magnetite (111) Surface

Sorption of contaminants onto mineral surfaces is an important process that can restrict their transport in the environment. In the current study, uranium (U) uptake on magnetite (111) was measured as a function of time and solution composition (pH, [CO 3 ]T, [Ca]) under continuous batch-flow conditions. We observed, in real-time and in situ, adsorption and reduction of U(VI) and subsequent growth of UO 2 nanoprecipitates using atomic force microscopy (AFM) and newly developed batch-flow U LIII-edge grazing-incidence X-ray absorption spectroscopy near-edge structure (GI-XANES) spectroscopy. U(VI) reduction occurred with and without CO 3 present, and coincided with nucleation and growth of UO 2 particles. When Ca and CO 3 were both present no U(VI) reduction occurred and the U surface loading was lower. In situ batch-flow AFM data indicated that UO 2 particles achieved a maximum height of 4–5 nm after about 8 h of exposure, however, aggregates continued to grow laterally after 8 h reaching up to about 300 nm in diameter. The combination of techniques indicated that U uptake is divided into three-stages; (1) initial adsorption of U(VI), (2) reduction of U(VI) to UO 2 nanoprecipitates at surface-specific sites after 2–3 h of exposure, and (3) completion of U(VI) reduction after ~6–8 h. U(VI) reduction also corresponded to detectable increases in Fe released to solution and surface topography changes. Redox reactions are proposed that explicitly couple the reduction of U(VI) to enhanced release of Fe(II) from magnetite. Although counterintuitive, the proposed reaction stoichiometry was shown to be largely consistent with the experimental results. In addition to providing molecular-scale details about U sorption on magnetite, this work also presents novel advances for collecting surface sensitive molecular-scale information in real-time under batch-flow conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Calcined Mg-Fe layered double hydroxide as an absorber for the removal of methyl orange

In this work, methyl orange (MO) was effectively removed from aqueous solution with the calcined product of hydrothermal synthesized Mg/Fe layered double hydroxide (Mg/Fe-LDH). The structure, composition, morphology and textural properties of the Mg/Fe-LDH before and after adsorption were characterized by X-ray diffraction, Fourier transformation infrared spectroscopy, transmission electron microscopy, nitrogen adsorption apparatus and X-ray photoelectron spectroscopy. It was confirmed that MO had been absorbed by calcined Mg/Fe-LDH which had strong interactions with MO. The adsorption of MO onto the Mg/Fe-LDH was systematically investigated by batch tests. The adsorption capacity of the Mg/Fe-LDH toward MO was found to be 194.9 mg • g{sup −1}. Adsorption kinetics and isotherm studies revealed that the adsorption of MO onto Mg/Fe-LDH was a spontaneous and endothermic process. These results indicate that Mg/Fe-LDH is a promising material for the removal of MO.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Preparation and Characterization of Eu{sup 3+}-Doped Transparent Oxyfluoride Glasses

A process has been proposed for the preparation of oxyfluoride glasses based on the SiO{sub 2}–B{sub 2}O{sub 3}–Bi{sub 2}O{sub 3}–ZnO–CaF{sub 2} system at various ratios of batch components, and transparent glasses have been obtained at a temperature below 1000°C. According to X-ray diffraction data, all of the glasses are X-ray amorphous. The surface morphology of the glasses has been examined and their glass transition temperatures have been determined. Their local structure has been studied by IR spectroscopy and it has been shown that, independent of composition, the glasses contain complex polyborate anions formed by [BO{sub 3}] and [BO{sub 4}] groups. Bismuth is incorporated into the glass network to form Bi–O–Si bonds and [BiO{sub 6}] network-formers.

36 MATERIALS SCIENCE↗
DOE OSTI2016

SHINE and Mini-SHINE Column Designs for Recovery of Mo from 140 g-U/L Uranyl Sulfate

Argonne is assisting SHINE Medical Technologies (SHINE) in their efforts to develop an accelerator-driven process that utilizes a uranyl-sulfate solution for the production of fission Mo-99. In an effort to design a Mo-recovery system for the SHINE project using low-enriched uranium (LEU), we conducted batch, breakthrough, and pulse tests to determine the Mo isotherm, mass-transfer zone (MTZ), and system parameters for a 130 g-U/L uranyl sulfate solution at pH 1 and 80°C, as described previously. The VERSE program was utilized to calculate the MTZ under various loading times and velocities. The results were then used to design Mo separation and recovery columns employing a pure titania sorbent (110-μm particles, S110, and 60 Å pore size). The plant-scale column designs assume Mo will be separated from 271 L of a 141 g-U/L uranyl sulfate solution, pH 1, containing 0.0023 mM Mo. The VERSE-designed recovery systems have been tested and verified in laboratory-scale experiments, and this approach was found to be very successful.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2017

Waste Water for Power Generation via Energy Efficient Selective Silica Separations

Silica is ubiquitous in produced and industrial waters, and plays a major disruptive role in water recycle. Herein we have investigated the use of mixed oxides for the removal of silica from these waters, and their incorporation into a low cost and low energy water purification process. High selectivity hydrotalcite (HTC, (Mg 6 Al 2 (OH) 16 (CO 3 )•4H 2 O)), is combined in series with high surface area active alumina (AA, (Al 2 O 3 )) as the dissolved silica removal media. Batch test results indicated that combined HTC/AA is a more effective method for removing silica from industrial cooling tower wasters (CTW) than using HTC or AA separately. The silica uptake via ion exchange on the mixed oxides was confirmed by Fourier transform infrared (FTIR), and Energy dispersive spectroscopy (EDS). Furthermore, HTC/AA effectively removes silica from CTW even in the presence of large concentrations of competing anions, such as Cl - , NO 3 - HCO 3 - , CO 3 2- and SO 4 2- . Similar to batch tests, Single Path Flow Through (SPFT) tests with sequential HTC/AA column filtration has very high silica removal too. Technoeconomic Analysis (TEA) was simultaneously performed for cost comparisons to existing silica removal technologies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Adaptive, Active Learning, and Multifidelity Monte Carlo Methods in the MOOSE Stochastic Tools Module

MOOSE is an open-source computational platform for constructing multi-physics models and executing them in a massively parallel fashion. It has a stochastic tools module (STM) for forward/inverse uncertainty quantification (UQ) and surrogate modeling. This presentation details some recent developments to the STM with respect to the implementation of adaptive, active learning, and multifidelity Monte Carlo methods for forward UQ of computational models. Specifically, the adaptive Monte Carlo methods include Markov Chain Monte Carlo (MCMC)-driven algorithms like adaptive importance sampling and parallelized subset simulation for statistical QoI estimation, rare events analysis, and stochastic gradient-free optimization. The active learning methods include Gaussian Process (GP) surrogates and their training via Adam optimization, design of acquisition functions, and integration with samplers like Monte Carlo, adaptive importance, and parallelized subset simulation. These active learning methods are also designed to work in a batch mode, wherein, the required calls to the full computational model are executed in parallel whenever a user-specified batch size is met. The multifidelity methods in STM are broadly divided into two categories: hierarchical, where a defined hierarchy exists among the low-fidelity models, and peer, where all the low-fidelity models are treated equally. A GP surrogate is used to learn the differences between the low- and high-fidelity models in both multifidelity categories, and acquisition functions from the active learning classes are used to decide whether to rely on a low-fidelity model or call the expensive high-fidelity model. Alongside the software description and usage, applications are also presented to nuclear engineering computational models including a TRISO nuclear fuel particle, a reactor pressure vessel, and a heat-pipe microreactor.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Composition-Based Density Model for High Level Waste Glasses

In this report, the Savannah River National Laboratory (SRNL) provides a first-principles model capable of predicting the density of high-level waste (HLW) glass based on the glass composition. The model relies on the additivity of the specific volume of bound glass oxides to obtain a quantitative evaluation of the approximate glass density. A database of glass densities and compositions was compiled from various sources including previous Defense Waste Processing Facility (DWPF) variability study glasses, HLW studies from other institutions, and literature references. There are a total of 1104 glass compositions in the database with densities ranging from 2.224 g/cm 3 to 3.997 g/cm 3 . The breadth of the compositional coverage space is reported as well. A predictive method was investigated in which the glass density was calculated as a function of the weighted partial molar volumes of the individual glass oxides and the molar mass of the glass. This method yielded a high correlation between the predicted density and the measured density. In addition, a linear regression of these predictions indicated that the predicted value was equal to the measured within the bounds of analytical uncertainty. The following conclusions were drawn from the results of these analyses: 1. Measured glass density is highly correlated with glass composition (R 2 ≈ 0.95). 2. The correlation between glass density and glass composition can be expressed as either: a. A weighted sum of the individual oxide glass-component densities, or b. A weighted sum of the individual oxide glass-component partial molar volumes. 3. A linear regression of the predicted density via partial molar volume method to the measured density yields a slope of 0.9975 and an intercept of -0.0007 – the uncertainty interval associated with these coefficients contain one and zero, respectively. 4. The fitted coefficients and associated uncertainty intervals of the linear regression of the predicted density via the partial molar volume method to the measured density suggest that the predicted theoretical density is, within analysis uncertainty, equal to the measured density of the glass. It is recommended that glass density measurements included with the variability study for each sludge batch be discontinued. In their place, SRNL will calculate a bounding glass density value for the frit/sludge system using the model. It is also recommended that DWPF implement the density model as part of the fissile loading determination portion of the SME acceptability process. Details for implementation are provided in this report.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
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↗