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At least 1,351 records · Page 75

Evidence cross-validation and Bayesian inference of MAST plasma equilibria

In this paper, current profiles for plasma discharges on the mega-ampere spherical tokamak are directly calculated from pickup coil, flux loop, and motional-Stark effect observations via methods based in the statistical theory of Bayesian analysis. By representing toroidal plasma current as a series of axisymmetric current beams with rectangular cross-section and inferring the current for each one of these beams, flux-surface geometry and q-profiles are subsequently calculated by elementary application of Biot-Savart's law. The use of this plasma model in the context of Bayesian analysis was pioneered by Svensson and Werner on the joint-European tokamak [Svensson and Werner,Plasma Phys. Controlled Fusion 50(8), 085002 (2008)]. In this framework, linear forward models are used to generate diagnostic predictions, and the probability distribution for the currents in the collection of plasma beams was subsequently calculated directly via application of Bayes' formula. In this work, we introduce a new diagnostic technique to identify and remove outlier observations associated with diagnostics falling out of calibration or suffering from an unidentified malfunction. These modifications enable a good agreement between Bayesian inference of the last-closed flux-surface with other corroborating data, such as that from force balance considerations using EFIT++[Appel et al., ''A unified approach to equilibrium reconstruction'' Proceedings of the 33rd EPS Conference on Plasma Physics (Rome, Italy, 2006)]. In addition, this analysis also yields errors on the plasma current profile and flux-surface geometry as well as directly predicting the Shafranov shift of the plasma core.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multi-layering of SU-8 exhibits distinct geometrical transitions from circular to planarized profiles

The negative tone photoresist SU-8 permits the creation of micrometer-scale structures by optical lithography. It is also the most used photoresist in soft lithography for the fast-prototyping of microfluidic devices. Despite its importance, the effect of capillary forces on SU-8 multi-layering onto topographical features has not been thoroughly studied. In particular, the profile of the added layer has not been examined in detail. The overlaying process exhibits a set of distinct behaviors, or regimes, depending on the relative thickness of the overlay and the underlying rectangular pattern. We demonstrate how capillary effects control the profile of multi-layer microchannels in a predictable manner. We derive a simple static model to describe the evolution of the overlay as a function of dimensionless geometric parameters. Our study provides a critical understanding of the parameters that govern multi-layer spin coating.

Sauzade, Martin↗

Proteome-wide association study and functional validation identify novel protein markers for pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) remains a lethal malignancy, largely due to the paucity of reliable biomarkers for early detection and therapeutic targeting. Existing blood protein biomarkers for PDAC often suffer from replicability issues, arising from inherent limitations such as unmeasured confounding factors in conventional epidemiologic study designs. To circumvent these limitations, we use genetic instruments to identify proteins with genetically predicted levels to be associated with PDAC risk. Leveraging genome and plasma proteome data from the INTERVAL study, we established and validated models to predict protein levels using genetic variants. By examining 8,275 PDAC cases and 6,723 controls, we identified 40 associated proteins, of which 16 are novel. Functionally validating these candidates by focusing on 2 selected novel protein-encoding genes, GOLM1 and B4GALT1, we demonstrated their pivotal roles in driving PDAC cell proliferation, migration, and invasion. Furthermore, we also identified potential drug repurposing opportunities for treating PDAC.

60 APPLIED LIFE SCIENCES↗

Estimation of Transport and Kinetic Parameters of Vanadium Redox Batteries Using Static Cells

Mathematical models of Redox Flow Batteries (RFBs) can be used to analyze cell performance, optimize battery operation, and control the energy storage system efficiently. Among many other models, physics-based electrochemical models are capable of predicting internal states of the battery, such as temperature, state-of-charge, and state-of-health. In the models, estimating parameters is an important step that can study, analyze, and validate the models using experimental data. A common practice is to determine these parameters either through conducting experiments or based on the information available in the literature. However, it is not easy to investigate all proper parameters for the models through this way, and there are occasions when important information, such as diffusion coefficients and rate constants of ions, has not been studied. Also, the parameters needed for modeling charge-discharge are not always available. In this paper, an efficient way to estimate parameters of physics-based redox battery models will be proposed. Furthermore, this paper also demonstrates that the proposed approach can study and analyze aspects of capacity loss/fade, kinetics, and transport phenomena of the RFB system.

25 ENERGY STORAGE↗

Pattern formation on free surfaces via plastic buckling and periodic folding

Spontaneous formation of surface patterns such as folds and creases is widely observed in engineered systems, such as thin films and machined surfaces, as well as in natural systems such as floral petals and leaves. A recognized route for their formation is via surface elastic instabilities. Here we demonstrate an alternate route for their formation —plastic buckling and folding—that occurs when ductile materials are subject to large-strain (>1) deformation. Using in situ imaging of simple-shear deformation of polypropylene, we delineate the mechanics underlying formation of folds and the resulting surface morphology. Here, the fold pattern shows a single wavelength that scales linearly with the size of the plastic zone. An analytical model predicts onset of the plastic buckling instability and characteristics of the folds. Besides obvious applications for controllably generating surface features over large areas, our results suggest a contributing mechanism for origin of surface roughness in solids.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

TEAMER – Harvesting Subsea Water Motion to Provide Clean Electrical Power (Abstract)

Power generation from vortex induced vibration (VIV) is an emerging field with new technologies that are just beginning to be field tested. In this TEAMER project, WITT Energy will be field testing the power production of its pendulum system in two different configurations to evaluate its performance. The amount of power produced by a VIV instrument depend on the frequency at which it vibrates. The vibrational frequency is controlled by the device shape and its interaction with the flow velocity. Computer models are used to predict vibration frequencies as a function of flow velocity but they may be inaccurate due to complicated bathymetry and bottom roughness that is not captures by the models. This project will test the WITT VIV device in the Sequim Bay channel over a range of tidal velocities. Two tests will be completed with different pipe lengths that are expected to vary the vibrational frequency and therefore the power produced. PNNL will use an acoustic doppler current profiler (ADCP) to monitor the flow conditions during the tests. These tests will help WITT Energy evaluate how closely field operations follow computer model predictions and how best to configure their device for electricity production.

16 TIDAL AND WAVE POWER↗

A Computationally Based Approach to Homogenizing Advanced Alloys

We have developed a computationally based approach to optimizing the homogenization heat treatment of complex alloys. The Scheil module within the Thermo-Calc software is used to predict the as-cast segregation present within alloys, and DICTRA (Diffusion Controlled TRAnsformations) is used to model the homogenization kinetics as a function of time, temperature and microstructural scale. We will discuss this approach as it is applied to both Ni based superalloys as well as the more complex (computationally) case of alloys that solidify with more than one matrix phase as a result of segregation. Such is the case typically observed in martensitic steels. With these alloys it is doubly important to homogenize them correctly, especially at the laboratory scale, since they are austenitic at high temperature and thus constituent elements will diffuse slowly. The computationally designed heat treatment and the subsequent verification real castings are presented.

36 MATERIALS SCIENCE↗

In situ determination of lithium ion cathode/electrolyte thickness and composition as a function of charge

In this work we report the first experimental in situ determination of the thickness and estimated composition of a condensed electrode/electrolyte interface at various states of charge for the high voltage Li-ion cathode LiMn1.5Ni0.5O4 by exploiting the power of neutron reflectometry.1 Understanding the electrode/electrolyte interface is critical to developing an understanding of interfacial reactions needed to model transport phenomena and predict more stable electrolytes for electrochemical cells.2,3 However, developing the ability to control interfacial reactions in electrochemical cells is arguably one of the most critical challenges confronting researchers focused on energy storage and conversion reactions as well as liquid phase reactions such as photocatalysts and biomass conversion.2 For example, in electrochemical energy storage systems, such as batteries, the reactions between a solid electrode and a liquid electrolyte can lead to the formation of the solid electrolyte interphase (SEI), which directly mediates the stability, durability and safety of the cell. Controlling these interfacial reactions is essential to developing new, durable, and higher energy storage systems needed in the future.

Neutron Reflectometry↗

Systems and methods for controlling an industrial asset in the presence of a cyber-attack

Systems and methods are provided for the control of an industrial asset, such as a power generating asset. Accordingly, a cyber-attack model predicts a plurality of operational impacts on the industrial asset resulting from a plurality of potential cyber-attacks. The cyber-attack model also predicts a corresponding plurality of potential mitigation responses. In operation, a cyber-attack impacting at least one component of the industrial asset is detected via the cyber-attack neutralization module and a protected operational impact of the cyber-attack is identified based on the cyber-attack model. The cyber-attack neutralization module selects at least one mitigation response of the plurality of mitigation responses based on the predicted operational impact and an operating state of the industrial asset is altered based on the selected mitigation response.

D'Amato, Fernando Javier↗

Physical origins of current and temperature controlled negative differential resistances in NbO 2

Negative differential resistance behavior in oxide memristors, especially those using NbO 2 , is gaining renewed interest because of its potential utility in neuromorphic computing. However, there has been a decade-long controversy over whether the negative differential resistance is caused by a relatively low-temperature non-linear transport mechanism or a high-temperature Mott transition. Resolving this issue will enable consistent and robust predictive modeling of this phenomenon for different applications. Here in this paper, we examine NbO 2 memristors that exhibit both a current-controlled and a temperature-controlled negative differential resistance. Through thermal and chemical spectromicroscopy and numerical simulations, we confirm that the former is caused by a ~400 K non-linear-transport-driven instability and the latter is caused by the ~1000 K Mott metal-insulator transition, for which the thermal conductance counter-intuitively decreases in the metallic state relative to the insulating state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impact of ELM control techniques on tungsten sputtering in the DIII-D divertor and extrapolations to ITER

The free-streaming plus recycling model (FSRM) has recently been developed to understand and predict tungsten gross erosion rates from the divertor during edge localized modes (ELMs). In this work, the FSRM was tested against the experimental measurements of W sputtering during ELMs, conducted via fast neutral tungsten (WI) spectroscopy. Good agreement is observed using a variety of controlling techniques, including gas puffing, neutral beam heating, and plasma shaping to modify the pedestal stability boundary and, thus, the ELM behavior. ELM mitigation by pellet pacing was observed to strongly reduce W sputtering by flushing C impurities from the pedestal and reducing the divertor target electron temperature. No reduction of W sputtering was observed during the application of resonant magnetic perturbations (RMPs), in contrast to the prediction of the FSRM. Potential sources of this discrepancy are discussed. Lastly, the framework of the FSRM is utilized to predict intra-ELM W sputtering rates in ITER. It is concluded that W erosion during ELMs in ITER will be caused mainly by free-streaming fuel ions, but free-streaming seeded impurities (N or Ne) may increase the erosion rate significantly if present in the pedestal at even the 1% level. Impurity recycling is not expected to cause critical W erosion in ITER due to the very low target electron temperature.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

CAMPUS: Fully Coupled Multiphysics Modeling and Simulation of LWR and FBR Nuclear Fuel Behavior

Nuclear fuels operate in an environment that involves complex multiphysics phenomena, and the multiphysics behavior is often tightly coupled. The prediction of fuel behavior under irradiation involves very complex material behavior that is not seen in any other engineering discipline. Understanding and predicting the evolving material properties and phenomenal behaviors of nuclear fuels are major challenges for fuel design and behavior prediction. The multiphysics behavior is often a tightly coupled thermal, mechanical and chemical phenomenon associated with a large number of control parameters and uncertainties, which requires an advanced fuel performance modeling and simulation capability to improve the existing reactors performance, to address environmental and reactor safety concerns. Nuclear fuel performance modeling and simulation capability is necessary as a result of the high cost and difficulty in experimental measurements. So, a fuel performance code called CityU Advanced Multiphysics Nuclear Fuels Performance with User-defined Simulations (CAMPUS) was developed to predict both light water reactor and fast reactor fuel behavior. An effective approach was developed using self-defined multiphysics models based on the framework of COMSOL Multiphysics to manage the nonlinearities associated with light water reactor and fast reactor fuels performance analysis. The modelling and simulations approach is of particular importance since it demonstrates highly interrelated and nonlinear fuel performance models can be developed and implemented into a multiphysics platform, and thus more efforts can be put into physics model development and improvement. The modelling results can be used to identify the important phenomena and parameters, to direct and design experiments and to assist in post analysis of expensive nuclear experiments for light water reactor and fast reactor nuclear fuel performance analysis. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Demonstration of Data Center Energy Use Prediction Software

This report documents a demonstration of a software modeling tool from Romonet that was used to predict energy use and forecast energy use improvements in an operating data center. The demonstration was conducted in a conventional data center with a 15,500 square foot raised floor and an IT equipment load of 332 kilowatts. It was cooled using traditional computer room air handlers and a compressor-based chilled water system. The data center also utilized an uninterruptible power supply system for power conditioning and backup. Electrical energy monitoring was available at a number of locations within the data center. The software modeling tool predicted the energy use of the data center's cooling and electrical power distribution systems, as well as electrical energy use and heat removal for the site. The actual energy used by the computer equipment was recorded from power distribution devices located at each computer equipment row. The model simulated the total energy use in the data center and supporting infrastructure and predicted energy use at energy-consuming points throughout the power distribution system. The initial predicted power levels were compared to actual meter readings and were found to be within approximately 10 percent at a particular measurement point, resulting in a site overall variance of 4.7 percent. Some variances were investigated, and more accurate information was entered into the model. In this case the overall variance was reduced to approximately 1.2 percent. The model was then used to predict energy use for various modification opportunities to the data center in successive iterations. These included increasing the IT equipment load, adding computer room air handler fan speed controls, and adding a water-side economizer. The demonstration showed that the software can be used to simulate data center energy use and create a model that is useful for investigating energy efficiency design changes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The role of geography in the complex diffusion of innovations

The urban–rural divide is increasing in modern societies calling for geographical extensions of social influence modelling. Improved understanding of innovation diffusion across locations and through social connections can provide us with new insights into the spread of information, technological progress and economic development. In this work, we analyze the spatial adoption dynamics of iWiW, an Online Social Network (OSN) in Hungary and uncover empirical features about the spatial adoption in social networks. During its entire life cycle from 2002 to 2012, iWiW reached up to 300 million friendship ties of 3 million users. We find that the number of adopters as a function of town population follows a scaling law that reveals a strongly concentrated early adoption in large towns and a less concentrated late adoption. We also discover a strengthening distance decay of spread over the life-cycle indicating high fraction of distant diffusion in early stages but the dominance of local diffusion in late stages. The spreading process is modelled within the Bass diffusion framework that enables us to compare the differential equation version with an agent-based version of the model run on the empirical network. Although both model versions can capture the macro trend of adoption, they have limited capacity to describe the observed trends of urban scaling and distance decay. We find, however that incorporating adoption thresholds, defined by the fraction of social connections that adopt a technology before the individual adopts, improves the network model fit to the urban scaling of early adopters. Controlling for the threshold distribution enables us to eliminate the bias induced by local network structure on predicting local adoption peaks. Finally, we show that geographical features such as distance from the innovation origin and town size influence prediction of adoption peak at local scales in all model specifications.

97 MATHEMATICS AND COMPUTING↗

Moore vs. Murphy: Tradeoffs between complexity and reliability in distributed energy system scheduling using software-as-a-service

Software-based optimization of building control strategies, including scheduling, has the potential to improve the performance of existing complex heating, ventilation, and air conditioning (HVAC), storage, and other systems—especially if temporally variable energy production, such as solar thermal or photovoltaics, is included. If reductions in energy bills can be achieved using optimized control strategies that take advantage of cost-saving opportunities, such as time-of-use pricing, the additional bill savings can cover further efficiency investment costs. As computer processing becomes cheaper over time (Moore's Law), opportunities to perform complex control optimization become more abundant, and these can be performed remotely as software-as-a-service (SaaS). However, by “perfecting” our control strategies, we run an increased risk that when something unexpected happens (Murphy's Law), the consequences of failure are greater. This study used simulation to explore the potential benefits of HVAC schedule optimization, delivery, and implementation using a SaaS paradigm, at various levels of complexity. Implementing optimal schedules in a model of an efficient building's HVAC system, the study predicts energy cost savings of up to 10% compared to the naïve reference control strategy. Optimizing more system control variables increases the potential energy cost savings; however, these savings could be compromised by failures in communication inherent in delivering schedules via SaaS. The additional cost of energy resulting from the risk of increased demand charges generally increased with increased communication failure to a much larger extent than the risk of increased energy use charges. This work suggests that moderate improvements in performance, achieved at low cost by simple means, may be more effective than highly optimized schemes, which are more susceptible to failure due to their dependence on complex interactions between systems.

42 ENGINEERING↗

On the Low Risk of SSR in Type III Wind Turbines Operating with Grid-Forming Control

We have shown in previous work that the risk of subsynchronous resonance between wind power plants with Type III wind turbines and series-compensated transmission lines is low when the wind turbines are operated in grid-forming (GFM) mode instead of the standard grid-following mode. This paper explains the fundamental mechanism behind the improved damping characteristics by modeling the positive- and negative-sequence impedances of Type III wind turbines in GFM control mode. Here it is discovered that the GFM control naturally acts against the negative resistance behavior of Type III wind turbines at subsynchronous frequencies that results from an interaction between the rotor-side converter current controller and negative slip. The developed impedance models in the sequence domain and the improved damping behavior are verified using PSCAD simulations of a 2.5-MW Type III GFM wind turbine. The modeling predictions are also supported by experimentally measuring the impedance response of a 2.5-MW Type III wind turbine in GFM mode.

17 WIND ENERGY↗

Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region: Modeled Productivity in Permafrost Regions

Realistic projection of future climate-carbon (C) cycle feedbacks requires better understanding and an improved representation of the C cycle in permafrost regions in the current generation of Earth system models. Here we evaluated 10 terrestrial ecosystem models for their estimates of net primary productivity (NPP) and responses to historical climate change in permafrost regions in the Northern Hemisphere. In comparison with the satellite estimate from the Moderate Resolution Imaging Spectroradiometer (MODIS; 246 ± 6 g C m -2 yr -1 ), most models produced higher NPP (309 ± 12 g C m -2 yr -1 ) over the permafrost region during 2000–2009. By comparing the simulated gross primary productivity (GPP) with a flux tower-based database, we found that although mean GPP among the models was only overestimated by 10% over 1982–2009, there was a twofold discrepancy among models (380 to 800 g C m -2 yr -1 ), which mainly resulted from differences in simulated maximum monthly GPP (GPP max ). Most models overestimated C use efficiency (CUE) as compared to observations at both regional and site levels. Further analysis shows that model variability of GPP and CUE are nonlinearly correlated to variability in specific leaf area and the maximum rate of carboxylation by the enzyme Rubisco at 25°C (Vc max_25 ), respectively. The models also varied in their sensitivities of NPP, GPP, and CUE to historical changes in climate and atmospheric CO 2 concentration. In conclusion, these results indicate that model predictive ability of the C cycle in permafrost regions can be improved by better representation of the processes controlling CUE and GPP max as well as their sensitivity to climate change.

54 ENVIRONMENTAL SCIENCES↗