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At least 1,351 records · Page 75

Multiobjective optimization of nuclear microreactor reactivity control system operation with swarm and evolutionary algorithms

To improve the marketability of novel microreactor designs, there is a need for automated and optimal control of these reactors. This paper presents a methodology for performing multiobjective optimization of control drum operation for a microreactor under normal and off-nominal conditions. Here, two different case studies are used where the control drum configuration is optimized for the reactor to be critical with some desired power distribution that would satisfy peaking limits. A surrogate model for power distribution is developed based on a feedforward neural network. The process for determining weights for scalarization of the multiobjective optimization problem is also detailed. Six optimization algorithms: evolutionary strategies, differential evolution, grey wolf optimization, Harris hawks optimization, moth flame optimization and particle swarm optimization, are all applied to these cases and the results analyzed. Although all these algorithms will demonstrate optima-seeking behavior, for real-time control it is necessary to identify the best algorithm to efficiently provide reasonable optima without operator interference. The moth flame optimization algorithm was found to perform particularly well on both cases. Overall, it was found that the algorithms capable of supplying the best optima were also the most consistent. Finally, the found optima were verified with the original model used to train surrogates.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NSR&D FY15 Final Report. Modeling Mechanical, Thermal, and Chemical Effects of Impact

The main goal of this project is to develop a computer model that explains and predicts coupled mechanical, thermal and chemical responses of HE under impact and friction insults. The modeling effort is based on the LANL-developed CartaBlanca code, which is implemented with the dual domain material point (DDMP) method to calculate complex and coupled thermal, chemical and mechanical effects among fluids, solids and the transitions between the states. In FY 15, we have implemented the TEPLA material model for metal and performed preliminary can penetration simulation and begun to link with experiment. Currently, we are working on implementing a shock to detonation transition (SDT) model (SURF) and JWL equation of state.

36 MATERIALS SCIENCE↗

BOPTEST: Initial FRP Test Case Development

To support an emulator model development of Building Optimization Testing (BOPTEST) framework, a team at the US Department of Energy’s Oak Ridge National Laboratory developed a medium-sized office building written in Modelica to serve as a reference test case. The reference test case was modeled based on an actual research platform that represents a typical medium-sized office building. This test case would encourage model-based design and testing of new controllers in which a developer first prototypes and debugs on a model before implementing in the real world. The developed preliminary model and control parameters will be further calibrated and tuned with actual measured data from experiments

42 ENGINEERING↗

Understanding the deformation behavior of the γ rich transformative Fe 38.5 Mn 20 Co 20 Cr 15 Si 5 Cu 1.5 complex concentrated alloy using in situ synchrotron diffraction

In situ tensile testing coupled with synchrotron x-ray diffraction was used to study the deformation behavior of metastability-engineered Fe 38.5 Mn 20 Co 20 Cr 15 Si 5 Cu 1.5 complex concentrated alloy. Monitoring the evolution of phase fraction and strain hardening response allowed the determination of true critical stress for the onset of the transformation-induced plasticity (TRIP) to be ∼375 MPa, preceded by slip starting at ∼255 MPa. In situ EBSD was used to validate the critical stress for transformation at the microstructure level and observe slip traces to confirm prior slip activity before the transformation. Further, a modeling framework based on stacking fault energy (SFE) was developed to predict the critical stress for transformation. Modeling suggested the SFE of the alloy to fall nearly 15 mJ/m 2 , which agrees well with SFE values calculated using synchrotron peak shifting (12 mJ/m 2 ) and thermodynamic calculation (11 mJ/m 2 ). As a result of γ-fcc to ε-hcp phase transformation, new {0002} ε planes emerged parallel to unaligned {111} γ planes with the tensile loading following S-N orientation relationship. Such selective emergence of new diffraction rings corresponding to ε phase is understood based on the reorientation of γ crystals with reference to tensile axis. In conclusion, this approach can be extended to effectively design alloys based on critical stress required for activating different deformation mechanisms to further push the limits of the strength-ductility envelope.

Complex concentrated alloy↗

Application of a spring-dashpot system to clinical lung tumor motion data

Purpose: The treatment efficacy of radiation therapy for lung tumors can be increased by compensating for breath-induced tumor motion. In this study, we quantitatively examine a mathematical model of pseudomechanical linkages between an external surrogate signal and lung tumor motion. Methods: A spring-dashpot system based on the Voigt model was developed to model the correlation between abdominal respiratory motion and tumor motion during lung radiotherapy. The model was applied to clinical data obtained from 52 treatments ('beams') from 10 patients, treated on the Mitsubishi Real-Time Radiation Therapy system, Sapporo, Japan. In Stage 1, model parameters were optimized for individual patients and beams to determine reference values and to investigate how well the model can describe the data. In Stage 2, for each patient the optimal parameters determined for a single beam were applied to data from other beams to investigate whether a beam-specific set of model parameters is sufficient to model tumor motion over a course of treatment. Results: In Stage 1, the baseline root mean square (RMS) residual error for all individually optimized beam data was 0.90 {+-} 0.40 mm (mean {+-} 1 standard deviation). In Stage 2, patient-specific model parameters based on a single beam were found to model the tumor position closely, even for irregular beam data, with a mean increase with respect to Stage 1 values in RMS error of 0.37 mm. On average, the obtained model output for the tumor position was 95% of the time within an absolute bound of 2.0 and 2.6 mm in Stages 1 and 2, respectively. The model was capable of dealing with baseline, amplitude and frequency variations of the input data, as well as phase shifts between the input abdominal and output tumor signals. Conclusions: These results indicate that it may be feasible to collect patient-specific model parameters during or prior to the first treatment, and then retain these for the rest of the treatment period. The model has potential for clinical application during radiotherapy treatment of lung tumors.

60 APPLIED LIFE SCIENCES↗

Behavior of Aging, Micro-Void, and Self-Healing of Glass/Ceramic Materials and Its Effect on Mechanical Properties

This chapter first describes tests to investigate the temporal evolution of the volume fraction of ceramic phases, the evolution of micro-damage, and the self-healing behavior of the glass ceramic sealant used in SOFCs, then a phenomenological model based on mechanical analogs is developed to describe the temperature dependent Young’s modulus of glass ceramic seal materials. It was found that after the initial sintering process, further crystallization of the glass ceramic sealant does not stop, but slows down and reduces the residual glass content while boosting the ceramic crystalline content. Under the long-term operating environment, distinct fibrous and needle-like crystals in the amorphous phase disappeared, and smeared/diffused phase boundaries between the glass phase and ceramic phase were observed. Meanwhile, the micro-damage was induced by the cooling-down process from the operating temperature to the room temperature, which can potentially degrade the mechanical properties of the glass/ceramic sealant. The glass/ceramic sealant self-healed upon reheating to the SOFC operating temperature, which can restore the mechanical performance of the glass/ceramic sealant. The phenomenological model developed here includes the effects of continuing aging and devitrification on the ceramic phase volume fraction and the resulted mechanical properties of glass ceramic seal material are considered. The effects of micro-voids and self-healing are also considered using a continuum damage mechanics (CDM) model. The formulation is for glass/ceramic seal in general, and it can be further developed to account for effects of various processing parameters. This model was applied to G18, and the temperature-dependent experimental measurements were used to calibrate the modeling parameters and to validate the model prediction.

aging↗

EpiK: A Knowledge Base for Epidemiological Modeling and Analytics of Infectious Diseases

Computational epidemiology seeks to develop computational methods to study the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems. Recent advances in computing and data sciences have led to the development of innovative modeling environments to support this important goal. The datasets used to drive the dynamic models as well as the data produced by these models presents unique challenges owing to their size, heterogeneity and diversity. These datasets form the basis of effective and easy to use decision support and analytical environments. As a result, it is important to develop scalable data management systems to store, manage and integrate these datasets. In this paper, we develop EpiK —a knowledge base that facilitates the development of decision support and analytical environments to support epidemic science. An important goal is to develop a framework that links the input as well as output datasets to facilitate effective spatio-temporal and social reasoning that is critical in planning and intervention analysis before and during an epidemic. The data management framework links modeling workflow data and its metadata using a controlled vocabulary. The metadata captures information about storage, the mapping between the linked model and the physical layout, and relationships to support services. EpiK is designed to support agent-based modeling and analytics frameworks—aggregate models can be seen as special cases and are thus supported. We use semantic web technologies to create a representation of the datasets that encapsulates both the location and the schema heterogeneity. The choice of RDF as a representation language is motivated by the diversity and growth of the datasets that need to be integrated. A query bank is developed—the queries capture a broad range of questions that can be posed and answered during a typical case study pertaining to disease outbreaks. The queries are constructed using SPARQL Protocol and RDF Query Language (SPARQL) over the EpiK. EpiK can hide schema and location heterogeneity while efficiently supporting queries that span the computational epidemiology modeling pipeline: from model construction to simulation output. As a result, we show that the performance of benchmark queries varies significantly with respect to the choice of hardware underlying the database and resource description framework (RDF) engine.

60 APPLIED LIFE SCIENCES↗

Dual Phase Soft Magnetic Laminates for Low-cost, Non/Reduced-Rare-Earth Containing Electrical Machines

To accelerate the mass market adoption of electric drive vehicles, the key technology barriers in electric motors are (1) magnet cost and rare-earth element price volatility; (2) non-rare-earth electric motor performance; and (3) materials property optimization. The goal of this project was to address these barriers by advancing a unique and innovative dual phase soft magnetic material technology and demonstrating the material in a 30-kW synchronous reluctance motor without using any permanent magnet for electric vehicles. Dual phase magnetic materials offer the electric motor designer the ability to locally control the magnetic saturation level in a motor laminate, while at the same time enhancing the mechanical strength of the laminate material, resulting in an enhancement in motor performance and efficiency. Scalable dual phase soft magnetic laminates manufacturing technologies were developed in collaboration with multiple US manufacturers. 1000 lbs of alloy sheet with a thickness of 0.25mm and width of 280 mm was manufactured within the specifications. Batch sizes of up to 240 laminates per run were produced from the alloy sheet. Two prototype motors with dual phase soft magnetic laminates were designed, built, and tested. The major goal of building the subscale prototype as a pathway to develop scalable manufacturing technologies for the dual phase soft magnetic laminates was met. The additional goal of building and testing the subscale prototype in order to validate the calculated performance with the tested motor performance was also met. For the full-scale 30kW continuous power synchronous reluctance motor prototype, the tested performance met the targets in terms of continuous power at the operating speeds up to 8000 rpm. Post-test studies were conducted and the root causes for the discrepancy between the predicted and tested peak power, continuous power at high speed range, and efficiency were identified. Further modeling study showed that the dual phase rotor machine has a 27% higher torque to active weight ratio than an equivalent performance silicon steel rotor machine. Application space and multiple discussions with traction motor and electric vehicle manufacturers for commercialization of the dual phase soft magnetic material technology were identified and conducted. An initial cost model was established based on the developed manufacturing technologies with the US manufacturers. Future paths for further cost reduction were identified, including increasing the market volume by broadening the applications of the dual phase soft magnetic laminate technology for electric machines in other energy sections such as oil & gas, heating, ventilation, and air conditioning (HVAC), and power generation.

33 ADVANCED PROPULSION SYSTEMS↗

MCNP Super Lattice Method for VHTR ORIGEN2.2 Nuclear Library Improvement Based on ENDF/B-VII

The advanced Very High Temperature gas-cooled Reactor (VHTR) achieves simplification of safety through reliance on innovative features and passive systems. One of the VHTRs innovative features is the reliance on ceramic-coated fuel particles to retain the fission products under extreme accident conditions. The effect of the random fuel kernel distribution in the fuel prismatic block creates a double-heterogeneous lattice, which needs to be addressed through the use of the newly developed prismatic super Kernel-by-Kernel Fuel (KbKF) lattice model method. Based on the new ENDF/B-VII nuclear cross section evaluated data, the developed KbKF super lattice model was then used with MCNP to calculate the material isotopes neutron reaction rates, such as, (n,?); (n,n’); (n,2n’); (n,f); (n,p); (n,?). Then, the MCNP-calculated results are rearranged to generate a set of new libraries “VHTRXS.lib,” for the ORIGEN2.2 isotopes depletion and build-up analysis code. The libraries contain one group cross section data for the structural light elements, actinides, and fission products that can be applied in the VHTR related fuel burnup and material transmutation analysis codes. The efficiency and ease of use of the MCNP method to generate and update the ORIGEN2.2 one-group spectrum weighed cross section library for VHTR was demonstrated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Modeling Analysis of Ball-Milling Process for Battery-Electrode Synthesis

The mechanical alloying process is a promising method for synthesizing electrode materials for batteries owing to its benefits such as the ability to produce nanostructured, high-performing electrode alloys, no adverse effects on the solid electrolyte for solid-state batteries, stable production of thick electrodes, simple processing steps, and low processing costs. It is gaining intensive attention in the battery industry as one of the best methods to replace the conventional wet-slurry-solvent method, and its application is rapidly increasing these days. However, the operation is currently conducted purely based on trial-and-error methods without fully utilizing the features of its functions. Here, this may be attributed to a lack of understanding of the effect of operating parameters on the alloying process and final products. Surprisingly, there is a scarcity of the literature conducting fundamental research to comprehend the underlying physics of the entire mechanical alloying process, resulting in a significant knowledge gap. To address this knowledge gap, extensive research was conducted. The existing literature on mechanical alloying was reviewed to comprehend the current state of understanding and to discuss the direction for future research. Mathematical expressions were developed to create physics-based models capable of capturing the entire mechanical alloying process, including milling kinetics and defect-enhanced phase evolution. These methods were then applied to investigate the impact of operating parameters such as milling frequency, initial mole ratio of the alloyed materials, density of grinding balls, and energy required for the powders to become amorphous (i.e., the amorphization energy threshold). This research aimed not only to comprehend the direct effects of these operating parameters but also to unveil the physics underlying the ball-milling process. The results of our study can serve as crucial information for the battery industry in designing or operating the ball-milling process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Time-dependent density-functional-theory calculations of the nonlocal electron stopping range for inertial confinement fusion applications

Nonlocal electron transport is important for understanding laser-target coupling for laser-direct-drive (LDD) inertial confinement fusion (ICF) simulations. Current models for the nonlocal electron mean free path in radiation-hydrodynamic codes are based on plasma-physics models developed decades ago; improvements are needed to accurately predict the electron conduction in LDD simulations of ICF target implosions. Here we utilized time-dependent density functional theory (TD-DFT) to calculate the electron stopping power (SP) in the so-called conduction-zone plasmas of polystyrene in a wide range of densities and temperatures relevant to LDD. Compared with the modified Lee-More model, the TD-DFT calculations indicated a lower SP and a higher stopping range for nonlocal electrons. We fit these electron SP calculations to obtain a global analytical model for the electron stopping range as a function of plasma conditions and the nonlocal electron kinetic energy. This model was implemented in the one-dimensional radiation-hydrodynamic code LILAC to perform simulations of LDD ICF implosions, which are further compared with simulations by the standard modified Lee-More model. In conclusion, results from these integrated simulations are discussed in terms of the implications of this TD-DFT-based mean-free-path model to ICF simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Potential Environmental Impacts of Hydrogen-based Transportation and Power Systems (Final Report)

Hydrogen (H 2 ) offers advantages as an energy carrier: minimal discharge of pollutants, production from multiple sources, increased thermodynamic efficiencies compared to fossil fuels, and reduced dependence on foreign oil. However, potential impacts from the H 2 generation processes, transport and distribution of H 2 , and releases of H 2 into the atmosphere have been proposed. The goal of this project was to analyze the effects of emissions of hydrogen, the six criteria pollutants and greenhouse gases on climate, human health, materials and structures. This project was part of a larger effort by DOE to assess the life-cycle costs and benefits and environmental impacts to inform decisions regarding future hydrogen research. Technical Approach: A modeling approach was developed and used to evaluate the potential environmental effects associated with the conversion of the on-road vehicle fleet from fossil-fuel vehicles to hydrogen fuel cell vehicles. GATOR-GCMOM was the primary tool used to predict atmospheric concentrations of gases and aerosols for selected scenarios. This model accounts for all feedbacks among major atmospheric processes based on first principles. The future scenarios and the emission rates selected for this analysis of hydrogen environmental effects are based on the scenarios developed by IPCC. The scenarios selected for the model simulations are a 2000 and 2050 A1B base cases, and a 2050 A1B case with hydrogen fuel cell vehicles (HFCVs). The hydrogen fuel cell scenario assumed conversion of 90% of fossil-fuel on-road vehicles (FFOV) in developed countries and 45% of FFOVs vehicles in other countries to HFCVs, with the H 2 produced by steam-reforming of natural gas (SHFCVs). Simulations were conducted to examine the effect of converting the world's FFOVs to HFCVs, where the H 2 is produced by wind-powered electrolysis (WHFCVs). In all scenarios a 3% leakage of H 2 consumed was assumed. Two new models were developed that provide the ability to evaluate a wider range of conditions and address some of the uncertainties that exist in the evaluation of hydrogen emissions. A simplified global hydrogen cycle model that simulates hydrogen dynamics in the troposphere and stratosphere was developed. A Monte Carlo framework was developed to address hydrogen uptake variability for different types of ecosystems. Findings 1. Converting vehicles worldwide in 2050 to SHFCVs at 90% penetration in developed countries and 45% penetration in other countries is expected to reduce NO x , CO, CO 2 , CH 4 , some other organic gases, ozone, PAN, black carbon, and other particle components in the troposphere, but may increase some other organic gases, depending on emissions. Conversion to SHFCVs is also expected to cool the troposphere and warm the stratosphere, but to a lesser extent than WHFCVs. Finally, SHFCVs are expected to increase UTLS ozone while decreasing upper stratospheric ozone, but to a lesser extent than WHFCVs. 2. The predicted criteria pollutant concentrations from the GATOR-GCMOM simulations indicated that near-surface annual mean concentrations in the US are likely to increase from the 2000 base case to the 2050 A1B base case for CO 2 and ozone due to the increased economic activity, but to decrease for CO, NO 2 , SO 2 , and PM 10 due to improved pollution control equipment and energy efficiencies. The shift to SHFCVs in 2050 was predicted to result in decreased concentrations for all the criteria pollutants, except for SO 2 and PM 10 . The higher predicted concentrations for SO 2 and PM 10 were attributed to increased emissions using the steam-reforming method to generate H 2 . If renewable methods such as wind-based electrolysis were used to generate H 2 , the emissions of SO 2 and PM 10 would be lower. 3. The effects on air quality, human health, ecosystem, and building structures were quantified by comparing the GATOR-GCMOM model output and accepted health and ecosystem effects levels and ambient air quality criteria. Shifting to HFCVs is expected to result in improved air quality and benefits to human health. Shifting to HFCVs is unlikely to result in damage to buildings. 4. Results are thought to be robust for larger leakage rates of H 2 and for greater penetrations of HFCVs, since the controlling factor for stratospheric ozone impacts is the reduction in fossil-fuel greenhouse gases and the resulting surface cooling, which reduces water vapor emissions and stratospheric warming, which increases tropopause stability reducing water vapor transport to the stratosphere. 5. The supplemental modeling results were generally supportive of the results from the GATOR-GCMOM simulations, and recommendations for additional analyses were made. Extending the duration of the simulation to coincide with the time required for hydrogen mixing ratios to attain a steady state condition was recommended. Further evaluation of algorithms to describe hydrogen uptake in the model was also recommended.

08 HYDROGEN↗

Quasiparticle-phonon nuclear model for odd-mass nuclei — Recent developments

An enhanced theory, based on the Extended Boson Approximation, for the lowest-lying states in odd-mass nuclei is presented. Our approach has built on the Quasi-particle Phonon Model extending it to take into account the ground state correlations due to the action of the Pauli principle more accurately than in the conventional theory.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A renewable lignin-based thermoplastic adhesive for steel joining

Adhesive bonding of metals has become increasingly relevant in recent years due to the demand for reducing weight and improving performance in structural applications such as automobiles and aerospace. We developed renewable thermoplastic adhesives from technical organosolv lignin isolated from hardwood biomass and acrylonitrile butadiene co-polymer rubber (NBR) for joining steel substrates. NBR33, NBR41 and NBR51 with acrylonitrile molar ratios of 33, 41 and 51%, respectively, were blended with lignin to form two-phase thermoplastic adhesives, and their adhesion, viscoelastic and surface properties were measured. Lignin content in the compositions were varied, ranging from 40% to 80% (w/w), to alter toughness, stiffness, and surface energy characteristics of the material. Better interaction or reactivity between the lignin and NBR phases was observed with greater nitrile content in NBR, leading to greater modulus and stiffness of the adhesive. Simultaneously, increasing the proportion of lignin reduced toughness and improved stiffness, with the highest adhesive strength of 13.1 MPa measured in a 60% lignin loading ratio with NBR51. Surface energy measurements revealed that total surface energy (sum of polar and dispersive surface energy) raised with lignin loading, suggesting that both surface energy and matrix strength play a critical role in the adhesive properties of the synthesized materials. A finite element-based cohesive zone model (CZM) was developed and implemented to study the failure strength of the adhesively bonded joint. Here, this study demonstrates the viability of lignin as a valuable building block for adhesives, not only due to its inherent chemical structure and rigidity, but also for its surface energy characteristics.

36 MATERIALS SCIENCE↗

Dust Aerosol Impact on North Africa Climate: A GCM Investigation of Aerosol-Cloud-Radiation Interactions Using A-Train Satellite Data

The climatic effects of dust aerosols in North Africa have been investigated using the atmospheric general circulation model (AGCM) developed at the University of California, Los Angeles (UCLA). The model includes an efficient and physically based radiation parameterization scheme developed specifically for application to clouds and aerosols. Parameterization of the effective ice particle size in association with the aerosol indirect effect based on cloud and aerosol data retrieved from A-Train satellite observations have been employed in the climate model simulations. Offline simulations reveal that the direct solar, IR, and net forcings by dust aerosols generally increase with increasing aerosol optical depth (AOD). When the dust semi-direct effect is included with the presence of ice clouds, positive IR radiative forcing is enhanced, since ice clouds trap substantial IR radiation, while the positive solar forcing with dust aerosols alone has been changed to negative values due to the strong reflection of solar radiation by clouds, indicating that cloud forcing could exceed aerosol forcing. With the aerosol indirect effect, the net cloud forcing is generally reduced for ice water path (IWP) larger than 20 g m-2. The magnitude of the reduction increases with IWP. AGCM simulations show that the reduced ice crystal mean effective size due to the aerosol first indirect effect result in less OLR and net solar flux at the top of the atmosphere over the cloudy area of the North Africa region because ice clouds with smaller size trap more IR radiation and reflect more solar radiation. The precipitation in the same area, however, increases due to the aerosol indirect effect on ice clouds, corresponding to the enhanced convection as indicated by reduced OLR. The increased precipitation seems to be associated with enhanced ice water contents in this region. The 200 mb radiative heating rate shows more cooling with the aerosol indirect effect since greater cooling is produced at the cloud top with smaller ice crystal size. The 500 mb omega indicates strong upward motion, which, together with the increased cooling effect, results in the increased ice water contents. Adding the aerosol direct effect into the model simulation reduces the precipitation in the normal rainfall band over North Africa, where precipitation is shifted to the south and the northeast produced by the absorption of sunlight and the subsequent heating of the air column by dust particles. As a result, rainfall is drawn further inland to the northeast. This study represents the first attempt to quantify the climate impact of aerosol indirect effect using a GCM in connection with A-train satellite data. The parameterization for the aerosol first indirect effect developed in this study can be readily incorporated for application to any other GCMs.

54 ENVIRONMENTAL SCIENCES↗

Agro-waste shaped porous Al2O3/Ni composites: Corrosion resistance performance and artificial neural network modelling

Highlights: • Porous Al{sub 2}O{sub 3}/Ni composites were developed with agro-waste pore-forming agents. • The RH and SCB graded composites showed Ni{sub 3}Al{sub 2}SiO{sub 8} and NiAl{sub 2}O{sub 4} spinels respectively. • Superior chemical stability was demonstrated by the Al{sub 2}O{sub 3}-2Ni-RH composite. • The ANN model demonstrated a good performance with R{sup 2} value of approx. 0.99. - Abstract: In the present study, an analysis on the combined effect of nickel (Ni) reinforcement and pore former type in characterizing the corrosion behavior of composite porous alumina ceramics was performed. In order to showcase the potential of the new porous ceramics, pore-forming agents (PFAs) from rice husk (RH) and sugarcane bagasse (SCB) were used in shaping the plain and composite porous alumina samples having sample formulation of Al{sub 2}O{sub 3}-xNi-PFA; x = 0, 2, 4, 6 and 8 wt%. Results showed that the emergence of a highly stable Ni{sub 3}Al{sub 2}SiO{sub 8} spinelloid phase in the RH-graded composites enhanced their chemical stability in the corrosive mediums (10 wt% NaOH and 20 wt% H{sub 2}SO{sub 4}) relative to the plain and the corresponding SCB-graded counterparts. An artificial neural network (ANN) model has been developed for predicting the corrosion behavior of the plain and composite porous alumina ceramics based on the experimental data. The developed ANN model satisfactorily predicted the percent mass losses of the porous ceramics in strong alkali and strong acid solutions with coefficient of determination (R{sup 2}) of approximately 0.99.

36 MATERIALS SCIENCE↗

Physics-informed machine learning of the Lagrangian dynamics of velocity gradient tensor

Reduced models describing the Lagrangian dynamics of the velocity gradient tensor (VGT) in homogeneous isotropic turbulence (HIT) are developed under the physics-informed machine learning (PIML) framework. We consider the VGT at both Kolmogorov scale and coarse-grained scale within the inertial range of HIT. Building reduced models requires resolving the pressure Hessian and subfilter contributions, which is accomplished by constructing them using the integrity bases and invariants of the VGT. The developed models can be expressed using the extended tensor basis neural network (TBNN) introduced by Ling et al. [J. Fluid Mech. 807, 155 (2016)]. Physical constraints, such as Galilean invariance, rotational invariance, and incompressibility condition, are thus embedded in the models explicitly. Our PIML models are trained on the Lagrangian data from a high-Reynolds number direct numerical simulation (DNS). To validate the results, we perform a comprehensive out-of-sample test. We observe that the PIML model provides an improved representation for the magnitude and orientation of the small-scale pressure Hessian contributions. Statistics of the flow, as indicated by the joint PDF of second and third invariants of the VGT, show good agreement with the “ground-truth” DNS data. A number of other important features describing the structure of HIT are reproduced by the model successfully. We have also identified challenges in modeling inertial range dynamics, which indicates that a richer modeling strategy is required. This helps us identify important directions for future research, in particular towards including inertial range geometry into the TBNN.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Plasma flow healing of magnetic islands in stellarators

Recent experiments from the large helical device (LHD) demonstrate a correlation between the 'healing' of vacuum magnetic islands in stellarators and changes in the plasma flow. A model explaining this phenomenon is developed based on self-consistent torque balance and island evolution equations. In conventional stellarators, neoclassical flow damping physics plays an important role in establishing the flow profiles. The balance of neoclassical damping and cross-field viscosity produces a radial boundary layer for the plasma rotation profile outside the separatrix of a locked magnetic island. The width of this boundary layer decreases as the plasma becomes less collisional. Associated with these flow effects are plasma currents flowing in the island region that attempt to suppress island formation. These currents are enhanced as the collisionality drops making magnetic island healing occur more readily in high temperature conventional stellarators. The analytic theory produces a critical {beta} for healing that scales monotonically with collisionality and is in qualitative agreement with LHD observations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗