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A Lagrangian analysis of pockets of open cells over the southeastern Pacific
Abstract. Pockets of open cells (POCs) have been shown to develop within closed-cell stratocumulus (StCu), and a large body of evidence suggests that the development of POCs result from changes in small-scale processes internal to the boundary layer rather than large-scale forcings. Precipitation is widely viewed as a key process important to POC development and maintenance. In this study, GOES-16 satellite observations are used in conjunction with MERRA-2 winds to track and compare the microphysical and environmental evolution of two populations of closed-cell StCu selected by visual inspection over the southeastern Pacific Ocean: one group that transitions to POCs and another comparison group (CLOSED) that does not. The high spatiotemporal resolution of the new GOES-16 data allows for a detailed examination of the temporal evolution of POCs in this region. We find that POCs tend to develop near the coast, last tens of hours, are larger than 104 km2, and often (88 % of cases) do not re-close before they exit the StCu deck. Most POCs are observed to form at night and tend to exit the StCu during the day when the StCu is contracting in area. Relative to the CLOSED trajectories, POCs have systematically larger effective radii, lower cloud drop number concentrations, a comparable conditional in-cloud liquid water path, and a higher frequency of more intense precipitation. Meanwhile, no systematic environmental differences other than boundary layer height are observed between POC and CLOSED trajectories. Interestingly, there are no differences in reanalysis aerosol optical depth between both sets of trajectories, which may lead one to the interpretation that differences in aerosol concentrations are not influencing POC development or resulting in a large number that re-close. However, this largely depends on the reanalysis treatment of aerosol–cloud interactions, and the product used in this study has no explicit handling of these important processes. These results support the consensus view regarding the importance of precipitation on the formation and maintenance of POCs and demonstrate the utility of modern geostationary remote sensing data in evaluating the POC life cycle.
Circular plastics technologies: pyrolysis of plastics to fuels and chemicals
Pyrolysis technologies are a staple in plastic chemical recycling because of the robustness to contamination and existing infrastructure. Pyrolysis is already considered to be a reasonably mature technology with numerous pilot plants operating to pyrolyze plastic waste into fuels and chemicals. Here this chapter will describe the pyrolysis process and important process parameters, the types of plastics that are suitable for pyrolysis recycling, the mechanism of pyrolytic degradation of various plastics, the products derived from different plastics, companies that have successfully scaled pyrolysis recycling, and recent innovations in the technology.
Multi-Model and Multi-Scale Global Sensitivity Analysis for Identifying Controlling Processes of Complex Systems
An environmental model consists of multiple process level sub-models, and each sub-model represents a process that is key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this project develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods with variance-based global sensitivity analysis to address uncertainty in process models and parameters. The new method yields three process sensitivity indices. The first one is called first-order process sensitivity index, and it is derived as a single summary measure of relative process importance. Evaluating the index is computationally expensive, because it relies in a Monte Carlo scheme that requires thousands and even millions of model executions. To reduce computational cost, this project develops a computationally efficient, quasi Monte Carlo method, and this method is presented in Chapter 2 of this report with and a numerical example for demonstration. The numerical example shows that the results of the quasi Monte Carlo method are substantially close to those of the full Monte Carlo method, but the computational cost of the quasi Monte Carlo method is only 0.7% of that of the full Monte Carlo method. The second index is called total-effect process sensitivity index, and it measures interactions between different processes. Therefore, this sensitivity index includes the first-order process sensitivity index, and can be used to identify influential processes. On the other hand, the total-effect process sensitivity index can also be used to screen non-influential processes. This is demonstrated by two numerical examples using the Sobol-G* functions and groundwater flow models that consider recharge process, geological process, and snowmelt process. The numerical examples shows that the total-effect process sensitivity index is more informative than the first-order process sensitivity. The derivation of the process sensitivity index and the numerical examples are discussed in Chapter 3. Chapter 4 presents two computationally efficient methods for screening non-influential processes to exclude them from further investigation. The two methods are the multi-model difference-based sensitivity (MMDS) analysis method, which can be implemented using the Latin Hypercube Sampling. The second one is the implementation of MMDS method using a binning method. The numerical example for the Sobol-G* function indicates the two methods are capable of identifying non-influential models, and the numerical examples for the groundwater flow and reactive transport show that the two methods are effective for groundwater problems. However, it should be noted that the two methods are numerical approximations, and they can only be used for screening non-influential processes, not for ranking importance of system processes. All the sensitivity analysis methods are implemented by developing python codes, and the codes are in a software called SAMMPY: a python package for process sensitivity analysis under multiple models. The SAMMPY design and structure are discussed in Chapter 5, and the package is released to the public for free download.
Simplified Approximations of Direct Cumulus Entrainment and Detrainment
Abstract In recent years, direct calculations of simulated cumulus entrainment and detrainment have facilitated new physical insights into these highly elusive but critically important processes. However, these calculations require substantial computational resources that may limit their widespread usage. To facilitate such calculations, two simplified approximations of direct cumulus entrainment and detrainment are examined herein. The first approximation, termed the “semidirect” method, follows a standard bulk approach but makes more realistic assumptions about the sources of entrained and detrained air near the cloud edges. In contrast, the second approximation (the “projection” method) uses the governing equations of motion to project whether grid points near the cloud edge will entrain or detrain as the mean cloud ascends by one grid point. Verification exercises using large-eddy simulations reveal that both methods generally agree better with corresponding direct entrainment/detrainment estimates than the traditional bulk formulation, with the projection method outperforming the semidirect method. The two methods can be used in a synergistic fashion, with the semidirect method helping to optimize the projection method, to suit a wide range of applications. Because the latter incorporates the essential dynamics of entrainment and detrainment at the local scale, it can be used to gain physical insight into the causal mechanisms regulating these complex processes.
Important ice processes are missed by the Community Earth System Model (CESM) in Southern Ocean mixed–phase clouds: Bridging SOCRATES observations to model developments
Global climate models (GCMs) are challenged by difficulties in simulating cloud phase and cloud radiative effect over the Southern Ocean (SO). Some of the new generation GCMs predict too much liquid and too little ice in mixed-phase clouds. This misrepresentation of cloud phase in GCMs results in weaker negative cloud feedback over the SO and a higher climate sensitivity. Based on a model comparison with observational data obtained during the Southern Ocean Cloud Radiation and Aerosol Transport Experimental Study (SOCRATES), this study addresses a key uncertainty in the Community Earth System Model version 2 (CESM2) related to cloud phase, namely ice formation in pristine remote SO clouds. It is found that sea spray organic aerosols (SSOA) are the most important type of ice nucleating particles (INPs) over the SO with concentrations one order of magnitude higher than those of dust INPs based on measurements and CESM2 simulations. Secondary ice production (SIP) which includes riming splintering, rain droplet shattering, and ice-ice collisional fragmentation as implemented in CESM2 is the dominant ice production process in moderately cold clouds with cloud temperatures greater than –20°C. SIP enhances the in-cloud ice number concentrations (Ni) by 1-3 orders of magnitude and predicts more mixed-phase (with percentage occurrence increased from 15% to 21%), in better agreement with the observations. Finally, this study highlights the importance of accurately representing cloud phase over the pristine remote SO by considering the ice nucleation of SSOA and SIP processes, which are currently missing in most GCM cloud microphysics parameterizations.
CFD-DEM Modeling of Autothermal Pyrolysis of Corn Stover with a Coupled Particle- and Reactor-Scale Framework
Autothermal operation of fast pyrolysis is an efficient process-intensification technique wherein exothermic oxidation reactions are used to overcome the heat-transfer bottleneck of conventional pyrolysis. The development of accurate, reliable modeling toolsets is imperative to generating a deeper understanding of biomass autothermal pyrolysis systems to support scale-up and industrial deployment. This modeling effort describes the development of single-particle and reactor models which incorporate detailed reaction schemes and simultaneous exothermic oxidation reactions. The particle-scale model was parameterized for corn stover feedstock with particle morphology, density, ash content, and biopolymer composition, all of which impact the emergent conversion characteristics during pyrolysis. Results were then used to parameterize a reactor-scale autothermal pyrolysis model, which was developed using a coarse-grained computational fluid dynamic-discrete element method. The simulation results compared well with experimental results, with the predicted bio-oil, light gas, and biochar yield within 3.0 wt% of the experimental yields. Further analyses were performed to test the influence of equivalence ratio, biomass injection position, and particle size distribution on autothermal pyrolysis. The analysis of the physio-chemical properties of the fluid and solid phase inside the reactor and at the reactor outlet help reveal important process interactions of autothermal pyrolysis.
A Verification and Validation Approach for COMSOL Multiphysics to Support High Flux Isotope Reactor (HFIR)
Over the last several decades, many reactors have successfully been converted from high enriched uranium (HEU) to low enriched uranium (LEU) fuels in United States in support of its global non-proliferation objectives. Of the reactors slated for conversion, five high-performance research reactors (HPRRs) remain. The high-flux isotope reactor (HFIR) at Oak Ridge National Laboratory (ORNL) is one of the five. Conversion of HFIR requires the qualification of a new fuel. To aid in the conversion process as well as improve safety margins, COMSOL Multiphysics was chosen to support and eventually supplement the steady-state heat-transfer code (SSHTC). In order to use COMSOL as a supplementary tool, i.e. one used for safety basis calculations, the code needs to undergo a verification and validation process. Verification and validation are important processes for the use of any software; however, physics-based solvers have a unique challenge, in that the validation is much more rigorous and its domain is only applicable to the general scope of the problem. This document details the verification and validation of COMOSL for analysis of HFIR. This report is intended for two different users: (1) current and future users of COMSOL for HFIR and (2) for individuals interested in assessing the scope of the validation of COMSOL for HFIR. This report is divided into six sections. The first of which details the process of verification and validation. Section one provides an overview of key concepts from ASME V&V 10, 20, and 40 and how these concepts are used to provide a validation of any multiphysics software. Section two covers the approach needed in order to validate multiphysics software for a given HFIR analysis. Parts three through five split up the key concepts highlighted in section two. The final section provides concluding remarks which demonstrate the scope and limitations of the validation study and how these may be expanded and improved.
Development of a reliable Potting process for Photoconductive Semiconductor Switches (PCSS)
Electrical potting is an important process to protect semiconductor devices from damaging external elements (mechanical stress, moisture, high voltage, etc.) and provides structural support for delicate devices for electrical connectivity to a larger platform. This internship will focus on the development of a universal potting jig for photoconductive semiconductor switches (PCSS). The goal is to design a reliable compression jig that is cross compatible with various PCSS designs that allow for easy potting of devices with a high dielectric breakdown strength material. The challenge with the current potting jig is that the design is only compatible with one style of PCSS and applies uneven pressure that can lead to leakage of potting material. Our approach is to move from a design that applies pressure by binder clip to utilizing a micrometer based compressing jig for a reliable packaging process that can pot a variety of devices without having to have a unique compressing jig for each of style of PCSS. Possible roadblocks with the new design include epoxy leakage into the optical path and misalignment of the electrode – metal contact bond.
Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions
Abstract Wetlands are the largest natural source of methane (CH 4 ) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH 4 , but interpreting its spatiotemporal variations is challenging due to the co‐occurrence of CH 4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data‐model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data‐constrained model—iPEACE—reasonably reproduced CH 4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH 4 production appeared to be the most important process, followed by oxidation in explaining inter‐site variations in CH 4 emissions. Based on a sensitivity analysis, CH 4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant‐mediated transport appeared to be the major pathway for CH 4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH 4 production and CH 4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH 4 production, plant‐mediated transport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH 4 emissions across biomes. These processes and associated parameters for CH 4 emissions among and within the wetlands provide useful insights for interpreting observed net CH 4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH 4 fluxes.
Quantile regression-enriched event modeling framework for dropout analysis in high-temperature superconductor manufacturing
High-temperature superconductor (HTS) tapes have shown promising characteristics of high critical current, which are prerequisites for applications in high-field magnets. Due to the unstable growth conditions in the HTS manufacturing process, however, the frequent occurrences of dropouts in the critical current impede the consistent performance of HTS tapes. To manufacture HTS tapes with large scale, high yield, and uniform performance, it is essential to develop novel data analysis approaches for modeling the dropouts and identifying the related important process parameters. Conventional methods for modeling recurrent events, such as the point process, require the extraction of events from quality measurements. As the critical current is a continuous process, it may not comprehensively represent the drop patterns by transforming the time-series measurements into a set of events. Here, to solve this issue, we develop a novel quantile regression-enriched event modeling (QREM) framework that integrates the non-homogeneous Poisson process for modeling the occurrence of dropouts and the quantile regression for capturing the drop patterns. By incorporating the feature selection and regularization, the proposed framework identifies a set of significant process parameters that can potentially cause the dropouts of HTS tapes. The proposed method is tested on real HTS tapes produced using an advanced manufacturing process, successfully identifying important parameters that influence dropout events including the substrate temperature and voltage. The results demonstrate that the proposed QREM method outperforms the standard point process in predicting the occurrence of dropouts.
Structure–Composition Relationships for Mg–Ni and Mg–Fe Olivine
Olivine is a dynamic and important mineral in the crust and mantle with relevance to processes important to climate change technology, such as geologic carbon storage and critical mineral recovery. In this work, we critically evaluated and compiled a new database of olivine diffraction data, lattice parameters, and composition to enable rapid Ni-Mg-Fe olivine composition determination. A compilation of olivine X-ray diffraction data and chemical compositions from both the literature and the International Centre for Diffraction Data (ICDD) powder database was assembled to plot both the forsterite-fayalite and forsterite-liebenbergite solid solution lines. Here we present an expanded dataset to delineate equations and relationships used for quantifying the correlations between olivine lattice parameters and chemical compositions in Mg 2 SiO 4 -Fe 2 SiO 4 (forsterite-fayalite) and Mg 2 SiO 4 -Ni 2 SiO 4 (forsterite-liebenbergite) olivine solid solution series.
Sulfur cycling at natural hydrocarbon and sulfur seeps in Santa Paula Creek, CA
Biogeochemical cycling of sulfur is relatively understudied in terrestrial environments compared to marine environments. However, the comparative ease of access, observation, and sampling of terrestrial settings can expand our understanding of organisms and processes important in the modern sulfur cycle. Furthermore, these sites may allow for the discovery of useful process analogs for ancient sulfur-metabolizing microbial communities at times in Earth's past when atmospheric O 2 concentrations were lower and sulfide was more prevalent in Earth surface environments. Here, we identified a new site at Santa Paula Creek (SPC) in Ventura County, CA—a remarkable freshwater, gravel-bedded mountain stream charged with a range of oxidized and reduced sulfur species and heavy hydrocarbons from the emergence of subsurface fluids within the underlying sulfur- and organic-rich Miocene-age Monterey Formation. SPC hosts a suite of morphologically distinct microbial biofacies that form in association with the naturally occurring hydrocarbon seeps and sulfur springs. We characterized the geology, stream geochemistry, and microbial facies and diversity of the Santa Paula Creek ecosystem. Using geochemical analyses and 16S rRNA gene sequencing, we found that SPC supports a dynamic sulfur cycle that is largely driven by sulfide-oxidizing microbial taxa, with contributions from smaller populations of sulfate-reducing and sulfur-disproportionating taxa. This preliminary characterization of SPC revealed an intriguing site in which to study geological and geochemical controls on microbial community composition and to expand our understanding of sulfur cycling in terrestrial environments.
A microscopic and crystallographic study of proton irradiated alloy 718
Solution annealing and age hardening are important processes for achieving good engineering and chemical properties of alloy 718. The composition of alloy 718 also plays an important role as it can affect both mechanical (γ”- and γ’-phase formation) and irradiation behaviors. Therefore, in this study five different sets of alloy 718 samples with two different chemical compositions were fabricated using different processing conditions and irradiated up to 4 dpa. Based on the effects of irradiation on the microstructural data of γ”- and γ’-phases, irradiation-induced dislocation statistics, and crystallographic data, it can be inferred that the samples processed at high solution annealing temperature (1093°C) behave better under irradiation compared to the samples processed at low solution annealing temperatures (945 and 1065°C).
Testing to Evaluate Processes Expected to Occur during MSR Salt Spill Accidents
Obtaining a license for a new nuclear reactor requires the identification and assessment of the potential consequences of specified accident scenarios, which are achieved using accident progression models. Those models need to be parameterized and validated using experimental data, but existing experimental data addressing processes relevant to molten salt reactor accidents are sparse. Specifically, experimental data that quantify the sensitives of important processes to the initial conditions of the spill, the ambient environment, and the containment features are needed to parameterize individual process models. Integrated experiments that simulate accident scenarios are also needed to provide data for model validation, but these experiments will require the use of proven methods to quantify the processes under evaluation. The overarching objectives of this work are to develop the methods for simulating the targeted processes, to determine the effectiveness of the methods in producing the data required for model development, to generate data that can be used to parameterize individual process models, and to provide key insights into the behavior of spilled molten salt that should be considered in models. Experimental methods were designed to quantify aspects of individual processes expected to occur during or after a molten salt spill accident that will affect the fate of spilled molten salt and the radionuclides within. These processes include 1) molten salt spreading and heat transfer, 2) molten salt flowing and freezing in tubing, 3) stainless steel corrosion kinetics in molten salt, and 4) molten salt splashing and aerosol generation. The initial tests described in this report were conducted using eutectic FLiNaK to demonstrate the test methods, the data that are generated, and the analyses of the data to derive values needed for modeling. The primary variables that were tested include initial salt temperature and the presence of volatile surrogate fission products (e.g., cesium and iodine). The developed methods are shown to be effective in quantifying the desired processes and can be applied to study more complex salt compositions of interest to molten salt reactor developers, a wide range of environmental conditions of interest to modelers, and additional variables relevant to salt spill accidents. The developed methods and insights gained from laboratory tests can also be incorporated in future large-scale integrated tests used to simulate molten salt spill accidents.
Quantifying the Impact of Vertical Resolution on the Representation of Marine Boundary Layer Physics for Global-Scale Models
Abstract While GCM horizontal resolution has received the majority of scale improvements in recent years, ample evidence suggests that a model’s vertical resolution exerts a strong control on its ability to accurately simulate the physics of the marine boundary layer. Here we show that, regardless of parameter tuning, the ability of a single-column model (SCM) to simulate the subtropical marine boundary layer improves when its vertical resolution is improved. We introduce a novel objective tuning technique to optimize the parameters of an SCM against profiles of temperature and moisture and their turbulent fluxes, horizontal winds, cloud water, and rainwater from large-eddy simulations (LES). We use this method to identify optimal parameters for simulating marine stratocumulus and shallow cumulus. The novel tuning method utilizes an objective performance metric that accounts for the uncertainty in the LES output, including the covariability between model variables. Optimization is performed independently for different vertical grid spacings and value of time step, ranging from coarse scales often used in current global models (120 m, 180 s) to fine scales often used in parameterization development and large-eddy simulations (10 m, 15 s). Uncertainty-weighted disagreement between the SCM and LES decreases by a factor of ∼5 when vertical grid spacing is improved from 120 to 10 m, with time step reductions being of secondary importance. Model performance is shown to converge at a vertical grid spacing of 20 m, with further refinements to 10 m leading to little further improvement. Significance Statement In successive generations of computer models that simulate Earth’s atmosphere, improvements have been mainly accomplished by reducing the horizontal sizes of discretized grid boxes, while the vertical grid spacing has seen comparatively lesser refinements. Here we advocate for additional attention to be paid to the number of vertical layers in these models, especially in the model layers closest to Earth’s surface where climatologically important marine stratocumulus and shallow cumulus clouds reside. Our experiments show that the ability of a one-dimensional model to represent physical processes important to these clouds is strongly dependent on the model’s vertical grid spacing.
Chapter 4 - Pretreatment Technologies for Lignocellulosic Biomass Refineries
Pretreatment is a critical step in processing lignocellulosic biomass into biofuel and bioproducts and is considered the energy and cost center of the biomass conversion process. Although a large number of pretreatment technologies have been developed, not all the techniques are viable on a commercial scale at this stage. Moreover, the technology choice and process conditions depend highly on the type of biomass and the overall biorefinery scheme. This chapter provides an overview of different pretreatment methods, including their mechanism, important process parameters, current status, and challenges. The opportunities associated with new technologies and approaches are presented. Emphasis is placed on low-severity thermal pretreatment technologies. The chapter also provides a brief discussion of the challenges to achieving the economic viability of the technologies on a commercial scale.
Enhanced internal condensation of R1233zd(E) on micro- and nanostructured copper and aluminum surfaces
In-tube condensation of refrigerants is an important process which affects thermal efficiency in many applications, ranging from refrigeration and air conditioning to electronics thermal management. In-tube heat transfer and pressure drop are important to heat exchanger sizing and design. Here, in this work, micro- and nanostructured surfaces are applied to the internal wetted areas of copper and aluminum mini-channels to enhance the condensation heat transfer coefficient of hydrofluorocarbon R1233zd(E) refrigerant. To achieve scalable nanomanufacturing, surfaces were uniformly structured by relying on hydrochloric acid etching of aluminum and chemical oxidation of copper. The etched aluminum surfaces exhibited a 150% increase in heat transfer coefficient compared to smooth aluminum channels at specific qualities, with a 66% heat transfer coefficient improvement for complete phase change from saturated vapor to saturated liquid. Copper oxide structures showed no discernable difference in thermal-hydraulic performance when compared to smooth copper channels. Critical dimensionless parameters governing the heat transfer enhancement were identified by varying the tube internal diameter (2.3 mm to 4.7 mm), refrigerant mass flux (50 to 300 kg/(m 2 ·s)), and refrigerant quality (0 to 1). The dimensionless parameters include the Bond number normalized to the condensate film thickness, and the Weber number modified by the vapor friction factor. The relatively small increase in pressure drop (< 10%) associated with these surface enhancements further supports the promise of this method. The scalable and cost-effective techniques used to create these aluminum microstructures may reduce manufacturing cost when compared with current enhancement approaches such as extrusion, drawing, and welding.