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At least 1,261 records · Page 70

3D Printing of Liquid Crystal Elastomer Foams for Enhanced Energy Dissipation Under Mechanical Insult

Polymer foams are an essential class of lightweight materials used to protect assets against mechanical insults, such as shock and vibration. Two features are important to enhance their energy absorption characteristics: the foam structure and the matrix phase mechanical behavior. This study investigates novel approaches to control both of these features to enhance the energy absorption capability of flexible lattice foams. First, we consider 3D printing via digital light processing (DLP) as a method to control the foam mesostructure across a suite of periodic unit cells. Second, we introduce an additional energy dissipation mechanism in the solid matrix phase material by 3D printing the lattice foams with polydomain liquid crystal elastomer (LCE), which undergo a mechanically induced phase transition under large strains. This phase transition is associated with LC mesogen rotation and alignment and provides a second mechanism for mechanical energy dissipation in addition to the viscoelastic relaxation of the polymer network. Here, we contrast the 3D printed LCE lattices with conventional, thermomechanically near-equivalent elastomer lattice foams to quantify the energy-absorbing enhancement the LCE matrix phase provides. Under cyclic quasi-static uniaxial compression conditions, the LCE lattices show dramatically enhanced energy dissipation in uniaxial compression compared to the non-LCE equivalent foams printed with a commercially available photocurable elastomer resin. The lattice geometry also plays a prominent role in determining the energy dissipation ratio between the LCE and non-LCE foams. We show that when increasing the lattice connectivity, the foam deformation transitions from bending-dominated to stretching-dominated deformations, which generates higher axial strains in the struts and higher energy dissipation in the lattice foam, as stretching allows greater mesogen rotation than bending. The LCE foams demonstrate superior energy absorption during the repeated dynamic loading during drop testing compared with the non-LCE equivalent foams, demonstrating the potential of LCEs to enhance physical protection systems against mechanical impact.

3D printing↗

Establishment of a National Wind Energy Center at University of Houston

The DOE-supported project objectives are to: establish a national wind energy center (NWEC) at University of Houston and conduct research to address critical science and engineering issues for the development of future large MW-scale wind energy production systems, especially offshore wind turbines. The goals of the project are to: (1) establish a sound scientific/technical knowledge base of solutions to critical science and engineering issues for developing future MW-scale large wind energy production systems, (2) develop a state-of-the-art wind rotor blade research facility at the University of Houston, and (3) through multi-disciplinary research, introducing technology innovations on advanced wind-turbine materials, processing/manufacturing technology, design and simulation, testing and reliability assessment methods related to future wind turbine systems for cost-effective production of offshore wind energy. To achieve the goals of the project, the following technical tasks were planned and executed during the period from April 15, 2010 to October 31, 2014 at the University of Houston: (1) Basic research on large offshore wind turbine systems (2) Applied research on innovative wind turbine rotors for large offshore wind energy systems (3) Integration of offshore wind-turbine design, advanced materials and manufacturing technologies (4) Integrity and reliability of large offshore wind turbine blades and scaled model testing (5) Education and training of graduate and undergraduate students and post- doctoral researchers (6) Development of a national offshore wind turbine blade research facility The research program addresses both basic science and engineering of current and future large wind turbine systems, especially offshore wind turbines, for MW-scale power generation. The results of the research advance current understanding of many important scientific issues and provide technical information for solving future large wind turbines with advanced design, composite materials, integrated manufacturing, and structural reliability and integrity. The educational program have trained many graduate and undergraduate students and post-doctoral level researchers to learn critical science and engineering of wind energy production systems through graduate-level courses and research, and participating in various projects in center’s large multi-disciplinary research. These students and researchers are now employed by the wind industry, national labs and universities to support the US and international wind energy industry. The national offshore wind turbine blade research facility developed in the project has been used to support the technical and training tasks planned in the program to accomplish their goals, and it is a national asset which is available for used by domestic and international researchers in the wind energy arena.

17 WIND ENERGY↗

Development of the IES Plug-and-Play Framework

This report discusses the status of the flexible plug-and-play framework development currently ongoing that aims to integrate Modelica/Dymola with the Risk Analysis and Virtual ENvironment (RAVEN) software in terms of both Functional Mock-Up Interface (FMI)/Functional Mock-Up Unit (FMU) construction and repository structures that aim to ease the sharing and simulation of complex dynamic models. This report aims to provide an overview of all the performed activities resolving around the deployment of methods, software infrastructures, guidelines and workflow for the construction and usage of models, encapsulated using the FMI/FMU protocols and standards. In particular, the report is organized in three main macro-subjects, which are connected to each other: - FMI/FMU adaptors for modelica models - HYBRID repository new structure and open-source deployment - RAVEN FMI/FMU exporting capabilities and Artificial Intelligence (AI)-based analysis acceleration. The first part of the report discusses the FMI/FMU adaptors that have been created within the HYBRID repository to allow users to quickly export models, such as FMUs. Several examples are shown that highlight the step-by-step process of converting an existing Modelica model into an FMU for use within the Dymola platform. Simulation results demonstrate that, while minor differences may occur, the overall control, trends, and solution integrity are maintained between standard Modelica simulation and FMU simulation results. However, it is worth noting that, for small systems, the FMU results have a slower simulation time than the Modelica only simulation. Using this process, a company can provide models that contain proprietary information to entities without disclosing any of the information about the model that could be considered business sensitive. Such an ability would allow institutions to bypass the necessity of “whitewashing” data. In the second part of the report, the new structure of the HYBRID repository is discussed with a major focus on the series of updates that has been completed. These updates include the addition of Modelica system-level regression tests and software quality assurance documentation that ensure that modifications to the Modelica models do not alter system-level model results. The third and final part of the report aims to report the work that has been performed for the deployment of methods and workflows for the construction of RAVEN AI-based models compliant with the FMI/FMU standard. Such development represents the key for the deployment of the concept of “Flexible ecosystem” since it allows for the replacement of high-fidelity modelica models (or any other FMI/FMU compliant model) with RAVEN generated AI surrogate models. Overall, extensive work has been completed on developing FMUs and FMIs from existing models, understanding the requirements and limitations of FMUs, and open-sourcing the HYBRID repository with an integrated regression system.

42 ENGINEERING↗

Development of the IES Plug-and-Play Framework

This report discusses the status of the flexible plug-and-play framework development currently ongoing that aims to integrate Modelica/Dymola with the Risk Analysis and Virtual ENvironment (RAVEN) software in terms of both Functional Mock-Up Interface (FMI)/Functional Mock-Up Unit (FMU) construction and repository structures that aim to ease the sharing and simulation of complex dynamic models. This report aims to provide an overview of all the performed activities resolving around the deployment of methods, software infrastructures, guidelines and workflow for the construction and usage of models, encapsulated using the FMI/FMU protocols and standards. In particular, the report is organized in three main macro-subjects, which are connected to each other: - FMI/FMU adaptors for modelica models - HYBRID repository new structure and open-source deployment - RAVEN FMI/FMU exporting capabilities and Artificial Intelligence (AI)-based analysis acceleration. The first part of the report discusses the FMI/FMU adaptors that have been created within the HYBRID repository to allow users to quickly export models, such as FMUs. Several examples are shown that highlight the step-by-step process of converting an existing Modelica model into an FMU for use within the Dymola platform. Simulation results demonstrate that, while minor differences may occur, the overall control, trends, and solution integrity are maintained between standard Modelica simulation and FMU simulation results. However, it is worth noting that, for small systems, the FMU results have a slower simulation time than the Modelica only simulation. Using this process, a company can provide models that contain proprietary information to entities without disclosing any of the information about the model that could be considered business sensitive. Such an ability would allow institutions to bypass the necessity of “whitewashing” data. In the second part of the report, the new structure of the HYBRID repository is discussed with a major focus on the series of updates that has been completed. These updates include the addition of Modelica system-level regression tests and software quality assurance documentation that ensure that modifications to the Modelica models do not alter system-level model results. The third and final part of the report aims to report the work that has been performed for the deployment of methods and workflows for the construction of RAVEN AI-based models compliant with the FMI/FMU standard. Such development represents the key for the deployment of the concept of “Flexible ecosystem” since it allows for the replacement of high-fidelity modelica models (or any other FMI/FMU compliant model) with RAVEN generated AI surrogate models. Overall, extensive work has been completed on developing FMUs and FMIs from existing models, understanding the requirements and limitations of FMUs, and open-sourcing the HYBRID repository with an integrated regression system.

14 SOLAR ENERGY↗

Optimizing Information Automation Using a New Method Based on System-Theoretic Process Analysis: Tool Development and Method Evaluation

This report is an update to a prior report that describes progress and findings for a program of research supporting the design and optimization of information automation systems for nuclear power plants. Much of the domestic nuclear fleet is currently focused on modernizing technologies and processes, including transitioning toward digitalization in the control room and throughout the plant, along with a greater interest in the use of automation, artificial intelligence, robotics, and other emerging technologies. While there are significant opportunities to apply these technologies toward greater plant safety, efficiency, and overall cost-effectiveness, optimizing their design and avoiding potential safety and performance risks depends on ensuring that human performance-related organizational and technical design issues are identified and addressed early in the design process. This report describes modeling tools and techniques, based on sociotechnical systems theory, to support these design goals and their application in the current research effort. The report is primarily intended for senior nuclear energy stakeholders, including regulators, corporate management, and senior plant management. We have developed and employed a method to design an optimized information automation ecosystem (IAE) based on the systems-theoretic constructs underlying sociotechnical systems theory in general and the Systems-Theoretic Accident Modeling and Processes (STAMP) approach in particular. We argue that an IAE can be modeled as an interactive information control system whose behavior can be understood in terms of dynamic control, feedback, and communication relationships amongst the system’s technical and organizational components. We have employed two STAMP-based tools in this effort. The first is Causal Analysis based on STAMP (CAST), an accident and incident analysis technique that was used to examine a performance- and safety-related incident at an industry partner’s plant involving the unintentional activation of an emergency diesel generator. This analysis provided insight into the behavior of the plant’s current information control structure within the context of a specific, significant event. The second tool is Systems Theoretic Process Analysis (STPA) which is a proactive risk analysis tool used to examine existing and potential, planned sociotechnical systems. STPA was used to identify risk factors in the current design of a generic nuclear power plant (NPP) preventive maintenance system. Our analyses focused on identifying near-term system improvements and longer-term design requirements for an optimized IAE system. CAST analysis findings indicate an important underlying contributor to the incident under investigation, and a significant risk to information automation system performance, was perceived time and schedule pressure, which exposed weaknesses in interdepartmental coordination between and within responsible plant organizations and challenged the resilience of established plant processes, until a human caused the eventual event. These findings are discussed in terms of their risk to overall system performance and their implications for information automation system resilience and brittleness. STPA findings exposed several areas of concern in the design of current preventive maintenance systems. We also present two preliminary information automation models. The proactive issue resolution (PIR) model is a test case of an information automation concept with significant near-term potential for application and subsequent reduction in significant plant events. The IAE model is a more general representation of a broader, plantwide information automation system and represents an end-state vision for our work. From our results, we have generated an initial set of preliminary system-level requirements and safety constraints for these models. We have also focused on early development of easy to learn, easy to use “transportable” tools for sociotechnical systems analysis. We intend these to be used by NPP personnel as a means of gaining reliable and relatively quick insight into (1) sociotechnical systems factors impacting incidents and accidents, (2) potential sociotechnical risk factors in existing or planned system designs, and (3) potential weaknesses in a system’s safety and/or information control structure. We conclude the report with a set of summary recommendations, a discussion of planned and potential follow-on research and development, and a draft list of system-level requirements and safety constraints for optimized information automation systems.

99 GENERAL AND MISCELLANEOUS↗

Sustainable Shape Memory Elastomers with Reduced Melt Viscosity and Enhanced Stiffness

Melt reactive processing of lignin with nitrile rubber is a promising approach to synthesizing shape memory materials. The strong intramolecular interactions in lignin macromolecular structures, caused by π–π stacking in aromatic rings and hydrogen bonding, often result in large phase separation or low miscibility with rubbers. In this study, we investigated the chemical and molecular characteristics, as well as the stiffness and complex viscosity, of modified kraft lignin melt-reacted with an acrylonitrile/butadiene copolymer containing 41% acrylonitrile (NBR41). To enhance the macromolecular compatibility of kraft lignin with NBR41, kraft lignin was cross-linked with poly(propylene glycol) diglycidyl ether (PPDE) and trimethylolpropane triglycidyl ether (TTE), both rich in epoxy reactive groups capable of forming chemical bonds with hydroxyl and carboxyl groups. Here, our findings demonstrate that the modification of kraft lignin with PPDE and TTE resulted in significantly increased stiffness of the composites. The elastic modulus of NBR41-Kraft lignin-PPDE and NBR41-Kraft lignin-TTE increased by 82 and 162%, respectively. Both the yield strength and Young’s modulus of these two samples showed dramatic improvements. Specifically, the yield strength and Young’s modulus of NBR41-Kraft lignin-TTE increased nearly 4 and 3-fold, respectively, compared to the control sample. Interestingly, despite significant improvements in mechanical properties, the viscosity of NBR41-Kraft lignin-PPDE was substantially lower than that of the control sample. At 210 °C and an angular frequency of 1 rad/s, the complex viscosity of NBR41-Kraft lignin was approximately 100.25 ± 4.77 kPa·s, while that of NBR41-Kraft lignin-PPDE was significantly lower at 56 ± 0.93 kPa·s. These findings were validated through Fourier transform infrared spectroscopy, scanning electron microscopy, dynamic mechanical analysis, thermal characterization, rheological tests, and quasi-elastic neutron scattering techniques.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A finite element/level set model of polyurethane foam expansion and polymerization

Polyurethane foams are used widely for encapsulation and structural purposes because they are inexpensive, straightforward to process, amenable to a wide range of density variations (1 lb/ft3 - 50 lb/ft3), and able to fill complex molds quickly and effectively. Computational model of the filling and curing process are needed to reduce defects such as voids, out-of-specification density, density gradients, foam decomposition from high temperatures due to exotherms, and incomplete filling. This paper details the development of a computational fluid dynamics model of a moderate density PMDI structural foam, PMDI-10. PMDI is an isocyanate-based polyurethane foam, which is chemically blown with water. The polyol reacts with isocyanate to produces the polymer. PMDI- 10 is catalyzed giving it a short pot life: it foams and polymerizes to a solid within 5 minutes during normal processing. To achieve a higher density, the foam is over-packed to twice or more of its free rise density of 10 lb/ft3. The goal for modeling is to represent the expansion, filling of molds, and the polymerization of the foam. This will be used to reduce defects, optimize the mold design, troubleshoot the processed, and predict the final foam properties. A homogenized continuum model foaming and curing was developed based on reaction kinetics, documented in a recent paper; it uses a simplified mathematical formalism that decouples these two reactions. The chemo-rheology of PMDI is measured experimentally and fit to a generalized- Newtonian viscosity model that is dependent on the extent of cure, gas fraction, and temperature. The conservation equations, including the equations of motion, an energy balance, and three rate equations are solved via a stabilized finite element method. The equations are combined with a level set method to determine the location of the foam-gas interface as it evolves to fill the mold. Understanding the thermal history and loads on the foam due to exothermicity and oven curing is very important to the results, since the kinetics, viscosity, and other material properties are all sensitive to temperature. Results from the model are compared to experimental flow visualization data and post-test X-ray computed tomography (CT) data for the density. Several geometries are investigated including two configurations of a mock structural part and a bar geometry to specifically test the density model. We have found that the model predicts both average density and filling profiles well. However, it under predicts density gradients, especially in the gravity direction. Further model improvements are also discussed for future work.

36 MATERIALS SCIENCE↗

Frequency choice of eRHIC SRF linac

eRHIC is a FFAG lattice-based multipass ERL. The eRHIC SRF linac has been decided to change from 422 MHz 5-cell cavity to 647 MHz 5-cell cavity. There are several considerations affecting the frequency choice for a high-current multipass-ERL: the beam structure, bunch length, energy spread, beam-break-up (BBU) threshold, SRF loss considerations. Beyond the physics considerations, cost and complexity or risk is an important consideration for the frequency choice, especially when we are designing a machine to be built in a few years. Although there are some benefits of using a 422 MHz cavity for eRHIC ERL, however, there are some very critical drawbacks, including lack of facilities to fabricate a 422 MHz 5-cell cavity, very few facilities to process such a cavity and no existing facility to test the cavity anywhere. As the cavity size is big and its weight is large, it is difficult to handle it during fabrication, processing and testing, and no one has experience in this area. As the cavity size is large, the cryomodule becomes big as well. All of these considerations drive the risk of building eRHIC ERL with 422 MHz cavities to a very high level. Therefore, a decision was made to change the frequency of main linac to be 647 MHz 5-cell cavities. This note will compare these two linacs: 422MHz 5-cell cavity linac and 647Mz 5-cell cavity SRF linac, from both practical point of view and physics point of view.

43 PARTICLE ACCELERATORS↗

Iodine capture with mechanically robust heat-treated Ag-Al-Si-O xerogel sorbents

Silver-loaded heat-treated aluminosilicate xerogels (Ag-HTX) were evaluated as sorbents for iodine [I2(g)] capture. The heat treatment step was performed to help increase the mechanical integrity of the gels. The synthesized xerogels were characterized using powder X-ray diffraction, scanning electron microscopy, energy-dispersive X-ray spectroscopy, transmission electron microscopy, Brunauer-Emmett-Teller analysis, gravimetric iodine loading, nanoindentation, and dynamic mechanical analysis. The structural and chemical analyses of Ag-HTX showed uniform distribution of Ag throughout the gel network after Ag-exchange. After I2(g) capture, the AgI crystallites were observed in the sorbent verifying chemisorption as the iodine capture mechanism. Iodine loading of this xerogel was 0.43 g g-1 at 150°C over 1 d and 0.52 g g-1 at 22°C over 33 d. The specific surface area of Ag-HTX was 202 m2 g-1 and decreased to 87 m2 g-1 after iodine loading. The hardness of the heat-treated xerogel was 160 times higher than heat-treated aerogel of the same composition. The heat-treatment process increased the modulus value to 40.77 MPa from 6.99 MPa of as-made xerogel, demonstrating the need for this added step in the synthesis process. These results show that Ag-HTX is a promising sorbent for I2(g) capture with good loading capacity and mechanical stability.

xerogels, aerogels, iodine capture, hardness testi↗

Modeling and simulation of transitional Rayleigh–Taylor flow with partially averaged Navier–Stokes equations

In this work, the partially averaged Navier–Stokes (PANS) equations are used to predict the variable-density Rayleigh–Taylor (RT) flow at Atwood number 0.5 and maximum Reynolds number 500. This is a prototypical problem of material mixing, featuring laminar, transitional, and turbulent flow, instabilities and coherent structures, density fluctuations, and production of turbulence kinetic energy by both shear and buoyancy mechanisms. These features pose numerous challenges to modeling and simulation, making the RT flow ideal to develop the validation space of the recently proposed PANS Besnard–Harlow–Rauenzahn-linear eddy viscosity model closure. The numerical simulations are conducted at different levels of physical resolution and test three approaches to set the parameters $f_\phi$ defining the range of physically resolved scales. The computations demonstrate the efficiency (accuracy vs cost) of the PANS model predicting the spatiotemporal development of the RT flow. Results comparable to large-eddy simulations and direct numerical simulations are obtained at significantly lower physical resolution without the limitations of the Reynolds-averaged Navier–Stokes equations in these transitional flows. The data also illustrate the importance of appropriate selection of the physical resolution and the resolved fraction of each dependent quantity $\phi$ of the turbulent closure, $f_\phi$. These two aspects determine the ability of the model to resolve the flow phenomena not amenable to modeling by the closure and, as such, the computations’ fidelity.

Navier Stokes equations↗

Belowground Carbohydrate Reserves of Mature Southern Pines Reflect Seedling Strategy to Evolutionary History of Disturbance

Carbohydrate reserves provide advantages for mature trees experiencing frequent disturbances; however, it is unclear if selective pressures operate on this characteristic at the seedling or mature life history stage. We hypothesized that natural selection has favored carbohydrate reserves in species that have an evolutionary history of frequent disturbance and tested this using three southern pine species that have evolved across a continuum of fire frequencies. Longleaf pine (Pinus palustris) roots exhibited higher maximum starch concentrations than slash (P. elliottii) and loblolly (P. taeda), which were similar. Longleaf also relied on starch reserves in roots more than slash or loblolly, depleting 64, 41, and 23 mg g -1 of starch, respectively, between seasonal maximum and minimum, which represented 52%, 45%, and 26% of reserves, respectively. Starch reserves in stems did not differ among species or exhibit temporal dynamics. Our results suggest that an evolutionary history of disturbance partly explains patterns of carbohydrate reserves observed in southern pines. However, similarities between slash and loblolly indicate that carbohydrate reserves do not strictly follow the continuum of disturbance frequencies among southern pine, but rather reflect the different seedling strategies exhibited by longleaf compared to those shared by slash and loblolly. We propose that the increased carbohydrate reserves in mature longleaf may simply be a relic of selective pressures imposed at the juvenile stage that are maintained through development, thus allowing mature trees to be more resilient and to recover from chronic disturbances such as frequent fire.

59 BASIC BIOLOGICAL SCIENCES↗

Toward Molecular Engineering of Polymer Glasses

Glass formation has been central to fabrication technologies since the dawn of civilization. Glasses not only encompass window panes, the insulation in our homes, the optical fibers supplying our cable TV, and vessels for eating and drinking, but they also include a vast array of ‘‘plastic’’ polymeric materials. Glasses find applications in high technology (e.g., producing microelectronic materials, etc., amorphous semiconductors), and recent advances have created ‘‘plastic metallic glasses’’ that are promising for fabricating everyday structural materials. Many commercially relevant systems, such as microemulsions and colloidal suspensions, have complex molecular structures and thus solidify by glass formation. Despite the importance of understanding the fundamental nature of glass formation for the synthesis of new materials, a predictive molecular theory has been lacking. Much of our understanding of glass formation derives from the analysis of experimental data, a process that has uncovered a number of interesting universal behaviors, namely, relations between properties that are independent of molecular details. However, these empirically derived relations and their limitations remain to be understood on the basis of theories, and, more importantly, there is strong need for theories of the explicit variation with molecular system to enable the rational design and tailoring of new materials. We have recently developed the generalized entropy theory, the only analytic, theory that enables describing the dependence of the properties of glass-formation on monomer molecular structures. These properties include the two central quantities of glass formation, the glass transition temperature and the glass fragility parameter, material dependent properties that govern how a material may be processed (e.g., by extrusion, ink jet, molding, etc.) Our recent works, which are further described below, extend the studies of glass formation in polymer systems to test the theory by directly comparing between the predictions of our generalized entropy theory with experiment and with simulations and to expand the vistas of the theory to describe a wider range of important systems (e.g. glass formation in binary blends and systems with specific interactions) and phenomena that are describable by the generalized entropy theory. In addition, we have addressed longstanding fundamental problems associated with the validity of the Adam-Gibbs theory, one of the underpinnings of the general entropy theory. Theoretical advances to enable describing the properties of glass-formation over a wider class of important polymeric systems, included semi-flexible systems, the more general situation of specific interactions, and more. Our recent work removes the simplest approximation uses the simplest model in which the interaction is approximated by a single, monomer average. Thus, the theory has been extended to allow some variations of the energy parameters between the atoms within the monomers. The theory has also been extended to include all the contributions from chain semi-flexibility. Both projects are extremely difficult, but the payback is that the process of solving the problems developed strong theoretical skills in Dr. Xu, who has recently begun a postdoc position at ORNL. The theory has also been extended to describe glass formation in partially miscible blends, with good general agreement with experiment. Again, the development of the theory presented an extremely difficult problem, but the payback is the development of a theory for a very important class of systems. Another project provides an extremely simple approximation for certain properties of glass formation in polymer melts and should make the theory more accessible to everyone.

36 MATERIALS SCIENCE↗

Winter rye as a bioenergy feedstock: impact of crop maturity on composition, biological solubilization and potential revenue

We report that winter annual crops such as winter rye (Secale cereale L) can produce biomass feedstock on seasonally fallow land that continues to provide high-value food and feed from summer annuals such as corn and soybeans. As energy double crops, winter grasses are likely to be harvested while still immature and thus structurally different from the fully senesced plant material typically used for biofuels. This study investigates the dynamic trends in biomass yield, composition, and biological solubilization over the course of a spring harvest season. The water soluble fraction decreased with increasing maturity while total carbohydrate content stayed roughly constant at about 65%. The protein mass fraction decreased with increasing maturity, but was counterbalanced by increasing harvest yield resulting in similar total protein across harvest dates. Winter rye was ground and autoclaved then fermented at 15 g/L total solids by either (1) Clostridium thermocellum or (2) simultaneous saccharification and cofermentation (SSCF) using commercial cellulases (CTec2 and HTec2) and a xylose-fermenting Saccharomyces cerevisiae strain. Solubilization of total carbohydrate dropped significantly as winter rye matured for both C. thermocellum (from approximately 80% to approximately 50%) and SSCF (from approximately 60% to approximately 30%). C. thermocellum achieved total solubilization 33% higher than that of SSCF for the earliest harvest date and 50% higher for the latest harvest date. Potential revenue from protein and bioethanol was stable over a range of different harvest dates, with most of the revenue due to ethanol. In a crop rotation with soybean, recovery of the soluble protein from winter rye could increase per hectare protein production by 20 to 35%. Double-cropping winter rye can produce significant biomass for biofuel production and feed protein as coproduct without competing with the main summer crop. During a 24-day harvest window, the total carbohydrate content remained relatively constant while the early-harvest yielded much higher carbohydrate solubilization for both C. thermocellum fermentation and SSCF. C. thermocellum fermentation achieved higher carbohydrate solubilization than SSCF across all growth stages tested. In conclusion, although winter rye’s yield, composition, and biological reactivity change rapidly in the spring, it offers a substantial and stable income across the harvest season and thus flexibility for the farmer.

60 APPLIED LIFE SCIENCES↗

HIMMELI v1.0: HelsinkI Model of MEthane buiLd-up and emIssion for peatlands

Wetlands are one of the most significant natural sources of methane (CH 4 ) to the atmosphere. They emit CH 4 because decomposition of soil organic matter in waterlogged anoxic conditions produces CH 4 , in addition to carbon dioxide (CO 2 ). Production of CH 4 and how much of it escapes to the atmosphere depend on a multitude of environmental drivers. Models simulating the processes leading to CH 4 emissions are thus needed for upscaling observations to estimate present CH 4 emissions and for producing scenarios of future atmospheric CH 4 concentrations. Aiming at a CH 4 model that can be added to models describing peatland carbon cycling, we composed a model called HIMMELI that describes CH 4 build-up in and emissions from peatland soils. It is not a full peatland carbon cycle model but it requires the rate of anoxic soil respiration as input. Driven by soil temperature, leaf area index (LAI) of aerenchymatous peatland vegetation, and water table depth (WTD), it simulates the concentrations and transport of CH 4 , CO 2 , and oxygen (O 2 ) in a layered one-dimensional peat column. Here, we present the HIMMELI model structure and results of tests on the model sensitivity to the input data and to the description of the peat column (peat depth and layer thickness), and demonstrate that HIMMELI outputs realistic fluxes by comparing modeled and measured fluxes at two peatland sites. As HIMMELI describes only the CH 4 -related processes, not the full carbon cycle, our analysis revealed mechanisms and dependencies that may remain hidden when testing CH 4 models connected to complete peatland carbon models, which is usually the case. Our results indicated that (1) the model is flexible and robust and thus suitable for different environments; (2) the simulated CH 4 emissions largely depend on the prescribed rate of anoxic respiration; (3) the sensitivity of the total CH 4 emission to other input variables is mainly mediated via the concentrations of dissolved gases, in particular, the O 2 concentrations that affect the CH 4 production and oxidation rates; (4) with given input respiration, the peat column description does not significantly affect the simulated CH 4 emissions in this model version.

54 ENVIRONMENTAL SCIENCES↗

Solute effects upon dislocation motion and recovery in Mg alloys (Final Report)

The objective the research was to develop a firmer understanding of the interactions between substitutional solute atoms and dislocations within Mg alloys. These interactions govern the absolute and relative mobilities of various types of dislocations in Mg (e.g., basal < a>, non-basal < a>, and pyramidal < c+a>). Furthermore, they have an impact on dislocation recovery processes (e.g., cross-glide, climb, rearrangement, and annihilation). Ultimately, solute-dislocation interactions strongly impact a) strain hardening, b) strain rate sensitivity, c) plastic anisotropy of textured polycrystals, d) texture evolution, e) dislocation substructures evolution, and even f) recrystallization behavior. It is broadly known that Mg alloys exhibit poor low temperature formability. Since formability is largely governed by properties (a) – (c) in this list, it is critical to develop a better understanding of solute-dislocation interactions, if one hopes to improve the situation. While the theory of static solute strengthening is well developed, especially for alloys with face centered cubic (FCC) crystal structures, there are outstanding questions related to applications to hexagonal close packed (HCP) crystal structures and dynamic strain aging (DSA) in materials of various structures. DSA has far-reaching implications for metal formability and, in the case of Mg alloys, appears to correlate with the so-called rare-earth (RE) texture which has been shown to benefit formability. The Portevin-Le Chatelier (PLC) effect, and associated negative strain rate sensitivity, occur at higher temperatures (>100℃) in Mg alloys as compared with similar Al alloys, even though they have similar melting points and solute diffusivities. Our preliminary research has shown that modern, physics-based models of DSA can be tuned to describe the behavior of Mg alloys if a rather higher activation enthalpy is assumed for cross-core diffusivity. While this partially explains the delay in DSA to higher temperatures, it is also hypothesized that this delay is due in part to the intrinsically more thermally activated (rate sensitive) nature of non-basal < a> dislocation motion which is required for macroscopic flow of Mg alloys, whereas octahedral slip in many FCC metals like aluminum is essentially athermal at room temperature. It was originally proposed to employ a combination of in-situ diffraction-based experimental characterization to validate existing theory. It was envisioned to perform in-situ transmission electron microscopy (TEM) to assess individual dislocation behavior and in-situ high-energy X-ray diffraction (HEXRD) techniques which were showing great promise for elucidating collective dislocation behavior, 2 including recovery, especially if the contributions to various forms of diffraction peak broadening (𝜂𝜂,𝜔𝜔,and 2𝜃𝜃) can be effectively integrated. Finally, it was envisioned to perform discrete dislocation dynamics (DDD) modeling approaches to aide in the interpretation of both TEM and HEXRD experiments. In the end, mechanical tests were performed on more complex Mg alloys which exhibited evidence of dynamic strain aging, and this led to the establishment of another project. Mechanical test data obtained at McMaster University served as the basis of an assessment of the applicability of Bazinski’s “stress equivalence” theory of solute strengthening to polycrystalline alloys of Mg. Although we did not succeed in applying the approach to Mg alloys, we did develop expertise with the HEXRD approach using a BCC, β-Ti alloy and demonstrated numerous new capabilities that may be applied to any polycrystalline material in collaboration with researchers at CHESS and around the world: (1) assessment of details of the elastoplastic transition (yielding) using a combination of HEXRD and full-field polycrystal plasticity modeling, (2) the first-ever experimental observation of strong stress rotation within the individual grains of a polycrystalline material, and (3) a comprehensive analysis of the grain-level dislocation density evolution based upon diffraction peak broadening along 𝜂𝜂,𝜔𝜔,and 2𝜃𝜃 directions. This final aspect allowed us to confirm that dislocations were gliding on multiple plane types and not restricted to {110} type planes, and it also provided clues as to why some grains were unloading during straining, with surprising implications for our understanding of the effects of geometrically necessary dislocations (GNDs). Finally, graduate student, Mohammed Shabana, developed a MATLAB code which confirmed the conclusions of Prof. Catalin Picu (Rensallear Polytechnic Institute, RPI) regarding the effect of solute-trapped, forest dislocations on the breaking stress of Lomer lock junctions in FCC metal alloys. He applied the same anisotropic line-tension model to a variety of dislocation junction configurations and found an inconsistency in the widely cited results of Dupuy and Fivel regarding the Hirth Lock, and he outlined an approach to extend these finding to HCP Mg alloys that we are still pursuing with discretionary fundings at UVA.

36 MATERIALS SCIENCE↗

Computation of Air Discharge into a Water Pool by Using Volume-of-Fluid Method

Suppression tanks, in-containment refueling water storage tanks (IRWSTs) and filtered containment venting systems (FCVSs) of nuclear power plants use water pools to accommodate high-pressure and high-temperature discharge of non-condensable gases and/or steam. Dynamic behavior of gas bubbles inside a water pool determines pressure and temperature loading to the system and thus we need validated method for applications. The underlying physics relevant to these problems is still a difficult issue due to the complicated nature of gas- liquid interfacial transfers of mass, momentum, and energy in a two-phase flow. Therefore, notwithstanding many studies performed over the past two or three decades, two-fluid theory is still a formidable task and direct numerical simulation (DNS) needs huge computing cost. Pellegrini et al. analyzed steam condensation and chugging in the water pool of the PPOOLEX STB-24 test by using STAR-CCM+ code implemented with two-phase interface model based on the Rayleigh-Taylor instability theory (RTI) which triggers steam depressurization. For the solution of the fine interface, they used Eulerian-Eulerian model for the fluid domain since the volume-of-fluid (VOF) model requires larger mesh points. The RTI resulted in complete steam condensation consistent with the experiment. The fluid tank was open to the atmosphere. They reported the volume fraction distributions in the pool, not the pool temperature or pressure history. For non-condensing gas discharges, however, the VOF is still a good alternative to the Eulerian two-fluid or the DNS approaches. The spatial distribution of each phase is defined in terms of volume fractions and the cell physical properties are obtained from linear combinations of those of constituent phases weighted by each volume fraction. Therefore, conditions where thermal and phase change effects become important are less likely to be simulated realistically. The VOF model is suited for the simulation of flows where each phase constitutes a large structure with a relatively small total contact area between phases. Present work is also interested in this VOF method for application to air discharge into a water pool which occurs in the early operating stages of the said facilities. Our purpose is to validate the VOF method against an existing air discharge experiment of PPOOLEX by using a commercial CFD code, STAR-CCM+ version 10.04, in terms of macroscopic flow properties. Effect of turbulence is also discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

High temperature high velocity direct power extraction using an open-cycle oxy-combustion system

The implementation of oxy-fuel technology in fossil-fuel power plants may contribute to increased system efficiencies and a reduction of pollutant emissions. One technology that has potential to utilize the temperature of undiluted oxy-combustion flames is open-cycle magnetohydrodynamic (MHD) power generators. These systems can be configured as a topping cycle and provide high enthalpy, electrically conductive flows for direct conversion of electricity. This report presents the design and modeling strategies of a MHD combustor operating at temperatures exceeding 3000 K. Throughout the study, computational fluid dynamics (CFD) models were extensively used as a design and optimization tool. A lab-scale 60 kWth model was designed, manufactured and tested as part of this project. A fully-coupled numerical method was developed in ANSYS FLUENT to characterize the heat transfer in the system. This study revealed that nozzle heat transfer may be predicted through a 40% reduction of the semi-empirical Bartz correlation. Experimental results showed good agreement with the numerical evaluation, with the combustor exhibiting a favorable performance when tested during extended time periods. A transient numerical method was employed to analyze fuel injector geometries for the 60-kW combustor. The ANSYS FLUENT study revealed that counter-swirl inlets achieve a uniform pressure and velocity ratio when the ports of the injector length to diameter ratio (L/D) is 4. An angle of 115 degrees was found to increase distribution efficiency. The findings show that this oxy-combustion concept is capable of providing a high-enthalpy environment for seeding, in order to render the flow to be conductive. Based on previous findings, temperatures in the range of 2800-3000 K may enable magnetohydrodynamic power extraction. The heat loss fraction in this oxy-combustion system, based on CFD and analytical calculations, at optimal operating conditions, was estimated to be less than 10 percent. Furthermore, the heat transfer design removed approximately 7 MW/m2. The results observed in the lab-scale system were employed to develop a 1-MW scaled prototype. Scaling methods were based on critical design criteria found in similar systems, aimed at replicating combustion flow fields and reducing possible instabilities. A numerical simulation of the combustor wall was developed for a combined thermal steady model and static structural model. This combined model was developed predict combined stress parameters within the wall during testing conditions. Both models were developed within ANSYS FEA software package. The relative accuracy presented as well major performance parameters are discussed to assess the design's validity and ensure safety. The scaled prototype was manufactured through selective laser melting (SLM)-based additive manufacturing to reduce lead times and increase geometrical complexity. Additional CFD models were developed to optimize coolant manifold system parameters and perform a parametric study on channel geometry. An investigation on coolant manifold geometry demonstrated improvements in channel flow distribution when enlarging manifold lengths and increasing the number of tubes feeding into the flow. A three-dimensional model based on a single channel was developed to capture the effect of variable properties and thermal stratification. All cases in the simulation exhibited higher wall temperatures and lower convective coefficients than those determined through 1-D analytical equations. This implies that pressure and velocity safety factors must be implemented during system operation. Overall, the findings made in this investigation are thought to be of value to researchers and industrial practitioners when designing oxy-fuel direct power extraction systems operating at temperatures exceeding 3000 K. In addition to this, the implementation of the developed technology at pilot and commercial scales could result in a significant improvement in the efficiencies of heritage and next-generation power cycles.

03 NATURAL GAS↗

Motion Planning Algorithms for Safety and Quantum Computing Efficiency

Motion planning remains a fundamental problem in robotics. Sampling-based algorithms use randomization to allow efficient solutions to this complex problem. As mobile robots and autonomous vehicles become more prevalent in everyday life, motion planning must be applied to increasingly challenging scenarios. Safety has become a paramount concern in motion planning for ensuring robotic applications enrich human lives. To date, many motion planning techniques to increase safety in the face of uncertain and dynamic environments have been developed. This dissertation first addresses distributional safety of Rapidly-Exploring Random Trees (RRT) through our algorithm W-Safe RRT. To acknowledge distributional uncertainty and poor modeling, W-Safe RRT uses the Wasserstein metric to provide a probabilistic bound on the distributional distance between a robot and obstacles. Human-interpretable environmental agent classification allows online safety margin adaptation. We propose and analyze an integrating region method for online classification that increases actor labeling accuracy based on behavioral feature values when compared to state of the art methods. The method performs class assignments based on local maximum likelihood in a created behavioral feature-space, allowing a notion of classification uncertainty. Model-based methods with safety guarantees can quickly become computationally in tractable, especially with multiple agents, higher dimensions, and plentiful unknowns. Sampling based algorithms have been parallelized for computation with multi-core computers and GPUs. We consider the use of quantum algorithms and computers for sampling-based motion planning for the first time. Quantum computing performs operations on superpositions of states and can solve certain problems much more efficiently than classical computers, but introduces previously unseen challenges. With Quantum-RRT, we recast the motion planning problem into a database-search structure and use Quantum Amplitude Amplification to find reachable states in the database with a quadratic performance increase over classical methods. We address two error sources with this method: quantum measurement and quantum oracle errors. We then extend this method to Parallel Quantum-RRT, which uses a manager-worker architecture with multiple parallel quantum workers to increase database search efficiency. We compare algorithm architectures and characterize probabilities of multiple workers finding solutions. Lastly, we test in simulation the quantum algorithms against classical versions in a wide variety of scenarios, concluding that a similar parallelization improvement is to be found in the quantum case as was found in the parallelization of classical RRT.

97 MATHEMATICS AND COMPUTING↗