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At least 847 records · Page 47

Large-Signal Impedance Modeling of Three-Phase Voltage Source Converters: Preprint

Resonance problems have become a major hurdle in the large-scale grid integration of renewable energy. It is important to be able to predict the amplitude of resonance-induced distortions for the protection and control design of power electronic converters. We recently presented an impedance-based approach for the prediction of resonance amplitude. It was shown that the impedance response of a converter starts changing with the amplitude of resonance; this blocks the amplitude growth beyond a certain point where the converter forms a limit cycle mode of sustained oscillations. The large-signal impedance of a converter captures the change in its impedance response with the resonance amplitude, and it can be used to predict the resonance amplitude under different operation conditions. This paper presents large-signal sequence impedance modeling for three-phase voltage source converters (VSC) with dq-current control and PLL. Modeling challenges encountered in the absence of the small-signal approximation are addressed by a) leveraging the dominating influence of hard non-linearities such as pulse-width modulation saturation and limiters over soft non-linearities in shaping the converter large-signal behavior and b) modeling the large-signal gain of hard non-linearities using appropriate describing functions. Developed large-signal impedance models are validated using numerical simulations. Measurements of the large-signal impedance responses of a commercial 1-MW VSC-based inverter are also presented to experimentally demonstrate the effects of the injected perturbation amplitude on impedance response as predicted by the developed model.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Integrated model predictions on the impact of substrate damage on gas dynamics during ITER burning-plasma operations

Divertor design and choice of plasma-facing materials (PFM) will be essential to the success of next-generation fusion reactors as they operate under more powerful scenarios. Understanding and controlling interactions between the plasma and PFM is essential to making these choices. Within these plasma–material interactions and especially in tungsten (W), the interplay between the most abundant plasma species (hydrogen isotopes and helium, He) with the wall material alters fuel retention. However, this interplay is yet to be sufficiently understood to confidently project fuel retention levels to future fusion devices. The paper presents a series of integrated simulations of fusion plasmas and their interaction with tungsten. Specifically, this study assesses the impact of He plasma pre-exposure on hydrogenic species retention during 100 s of burning plasma operations (BPO) in ITER. Multiple pre-exposure scenarios are considered, including sub-surface damage resulting from exposures in the linear device PISCES and from early ITER He-operation. The predictions from these consecutive He-BPO exposures show that fuel content and spatial distribution in the material are largely determined by the He-induced damage, as manifest in: (i) changes in surface temperature expected during BPO have little effect on fuel retention in the presence of He-induced damage; (ii) gas content stabilizes quickly in substrates pre-exposed in PISCES, at levels set by the concentration of pre-existing vacancies, while it continues to increase in substrates initially pristine or pre-exposed to ITER He plasmas; (iii) the presence of He and He–V clusters in the near-surface region locally increases hydrogenic retention, but decreases its permeation; this results in hydrogenic species that remain closer to the surface in pre-damaged substrates, while the bulk content is higher for initially pristine cases. In summary, the interaction and binding of D and T with the pre-existing He–V clusters modifies retention and permeation of hydrogen species during ITER BPO.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Permeability variations within mining-induced fractured rock mass and its influence on groundwater inrush

This paper is concerned with the evaluation of permeability of fractured rock mass due to the cover stress re-establishment, which is a major factor in controlling water and gas flow rate induced by mining operations in fractured rock. The case study considered in this paper is based on the results of observations of groundwater inrush and a decrease in water inflow from the fractured roof strata due to mining advancing in the Taiping Coalmine, Shandong Province, China. A conceptual model of an effective porous media was used to assess the permeability distribution in the fractured zone induced by coal mining. The cover stress re-establishment in gob fractured rock mass was evaluated using an empirical formula based on the surface subsidence. A simplified conceptual model of the fractured zone was used to evaluate the deformation of fractured zone along with the evaluation of changes in the rock permeability above the gob due to the cover stress re-establishment. These data were then used to calculate the water inflow rate into the panel. Predicted water inflow rates have been found to be in good agreement with those from monitoring data. This study improved the understanding of the mechanisms of the post-mining cover stress re-establishment on permeability change of the overburden fracture rock strata. These results can then be applied for numerical simulations of the process of overburden failure and consequent groundwater inrush due to coal mining.

54 ENVIRONMENTAL SCIENCES↗

Integrated System Planning: Emerging Software Requirements in the Power Industry

Power system planning software remains fragmented across organizational boundaries, with specialized tools for capacity expansion, production cost modeling, power flow, and dynamic analysis operating on incompatible data models and assumptions. This article argues that the fragmentation is not merely a technical problem but a predictable consequence of Conway's law: software architectures mirror the departmental structures within which they are developed. Regulatory milestones like Federal Energy Regulatory Commission (FERC) Order 888 formalized these divisions, but the roots trace back to the distinct engineering disciplines-mechanical, chemical, and electrical-that staffed generation and transmission planning departments in vertically integrated utilities. As the industry moves toward integrated system planning (ISP) that coordinates generation, transmission, and distribution investment decisions, the software ecosystem must evolve accordingly. We identify five categories of software requirements to enable this transition: coherent data inputs decoupled from individual applications, unified and extensible data schemas, modular component representations that support multiple abstraction levels, lifecycle management of planning datasets, and well-defined application programming interface (API) contracts that separate data exchange from algorithmic control. We examine how these requirements interact with three common workflow patterns-serial gate clearing, sequential multiapplication, and convergence oriented-and discuss the interface design principles each demands. We then outline a vision for platform-based planning architectures where specialized analytical services compose through standardized interfaces and where artificial intelligence (AI)/machine learning (ML) tools augment decision support within a disciplined software infrastructure. The practices proposed here offer a path from today's siloed tool collections toward collaborative planning ecosystems capable of handling the complexity of modern power system transformation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A critical look at the prediction of the temperature field around a laser-induced melt pool on metallic substrates

The study of microstructure evolution in additive manufacturing of metals would be aided by knowing the thermal history. Since temperature measurements beneath the surface are difficult, estimates are obtained from computational thermo-mechanical models calibrated against traces left in the sample revealed after etching, such as the trace of the melt pool boundary. Here we examine the question of how reliable thermal histories computed from a model that reproduces the melt pool trace are. To this end, we perform experiments in which one of two different laser beams moves with constant velocity and power over a substrate of 17-4PH SS or Ti-6Al-4V, with low enough power to avoid generating a keyhole. We find that thermal histories appear to be reliably computed provided that (a) the power density distribution of the laser beam over the substrate is well characterized, and (b) convective heat transport effects are accounted for. Poor control of the laser beam leads to potentially multiple three-dimensional melt pool shapes compatible with the melt pool trace, and therefore to multiple potential thermal histories. Ignoring convective effects leads to results that are inconsistent with experiments, even for the mild melt pools here.

42 ENGINEERING↗

Thermal and electric multidomain dynamic model for integration of power grid distribution with behind-the-meter devices

As renewable energy sources like solar and wind power become more integrated into the grid, coordinated control of behind-the-meter devices is crucial for enhancing grid flexibility and reliability and for meeting cost targets, with standardized models being developed to support this transition. The increasing flexibility and uncertainty of integrated renewable energy grids, along with interactions between various subsystems, make traditional steady-state modeling insufficient to capture transient and dynamic behaviors. Current models (e.g., composite load and battery equivalent models) focus on thermodynamic or electrical characteristics but overlook critical electromechanical interactions. This limits the ability to share performance information for grid services and hampers fast dynamic simulations. In addition, motor stalling is usually triggered by a fault event and attributed to the characteristics of the mechanical torque of the motor, resulting in absorption of a large amount of reactive power during the stalling period. Further, this significant withdrawal of reactive power will deteriorate the dynamic voltage stability of power grids and cause delayed voltage recovery. Therefore, an in-depth modeling of the thermodynamics or mechanical torque is essential to study the impacts of the realistic torque characteristics of those behind-the-meter devices on power system voltage stability. This study developed a dynamic multidomain model for building HVAC systems, such as air-source heat pumps, to simulate their thermal and electrical responses to grid transients. The model can accurately predict power metrics with a mean absolute percentage error of 10%, by validating against with power system computer-aided design performance data. Case studies demonstrate the model capability of capturing the transient response to sudden voltage changes, rapid load fluctuations, and system shutdowns respectively. During a sudden voltage drop (30% for 0.1s), a fully loaded heat pump’s motor speed dropped, continued declining, and shut down after 3.6s, with severe power oscillations and a torque spike. A partially loaded unit experienced temporary oscillations but stabilized. Under higher building loads, compressor speed increased from 64% to 100%, with power and torque rising before stabilizing. In safety-triggered shutdowns, power decreased after minor fluctuations, and torque briefly spiked before dropping to zero.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A 4DCT imaging-based breathing lung model with relative hysteresis

To reproduce realistic airway motion and airflow, the authors developed a deforming lung computational fluid dynamics (CFD) model based on four-dimensional (4D, space and time) dynamic computed tomography (CT) images. A total of 13 time points within controlled tidal volume respiration were used to account for realistic and irregular lung motion in human volunteers. Because of the irregular motion of 4DCT-based airways, we identified an optimal interpolation method for airway surface deformation during respiration, and implemented a computational solid mechanics-based moving mesh algorithm to produce smooth deforming airway mesh. In addition, we developed physiologically realistic airflow boundary conditions for both models based on multiple images and a single image. Furthermore, we examined simplified models based on one or two dynamic or static images. By comparing these simplified models with the model based on 13 dynamic images, we investigated the effects of relative hysteresis of lung structure with respect to lung volume, lung deformation, and imaging methods, i.e., dynamic vs. static scans, on CFD-predicted pressure drop. The effect of imaging method on pressure drop was 24 percentage points due to the differences in airflow distribution and airway geometry. - Highlights: • We developed a breathing human lung CFD model based on 4D-dynamic CT images. • The 4DCT-based breathing lung model is able to capture lung relative hysteresis. • A new boundary condition for lung model based on one static CT image was proposed. • The difference between lung models based on 4D and static CT images was quantified.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Power peaking with small modular reactors to support deep penetration of renewable energy sources - 192

As inherently intermittent sources of renewable energy more fully penetrate the US grid, peaking power is largely being supplied by carbon-emitting natural gas turbines. Significant greenhouse gas emissions can be avoided if these plants are replaced with carbon-neutral nuclear facilities to provide peaking power to complement renewable generation and meet overall power demand. There is a great deal of previous work regarding reactor power shaping with control rod movement for both currently operating nuclear power plants and proposed plants, but the literature on load-following to meet less predictable, more rapidly varying power demand is less comprehensive. We have chosen the Westinghouse IRIS integral PWR as our candidate for modeling, simulation, and control studies. A nodal model of the IRIS integral PWR, partially adapted from a MATLAB/Simulink model constructed by prior students at the University of Tennessee in Knoxville, has been constructed in Modelica. Currently the model includes the reactor vessel and steam generator system and simple assumptions for the balance of plant. The control scheme for the load-following operation of an IRIS integral PWR model would ultimately lead to the development of real operational mechanisms and principles in a grid with significant renewables capacity. In the future the model will be integrated with sophisticated grid and hybrid energy systems. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

BENCHMARK TESTS FOR MARKOV CHAIN MONTE CARLO FITTING OF EXOPLANET ECLIPSE OBSERVATIONS

Ground-based observations of exoplanet eclipses provide important clues to the planets' atmospheric physics, yet systematics in light curve analyses are not fully understood. It is unknown if measurements suggesting near-infrared flux densities brighter than models predict are real, or artifacts of the analysis processes. We created a large suite of model light curves, using both synthetic and real noise, and tested the common process of light curve modeling and parameter optimization with a Markov Chain Monte Carlo algorithm. With synthetic white noise models, we find that input eclipse signals are generally recovered within 10% accuracy for eclipse depths greater than the noise amplitude, and to smaller depths for higher sampling rates and longer baselines. Red noise models see greater discrepancies between input and measured eclipse signals, often biased in one direction. Finally, we find that in real data, systematic biases result even with a complex model to account for trends, and significant false eclipse signals may appear in a non-Gaussian distribution. To quantify the bias and validate an eclipse measurement, we compare both the planet-hosting star and several of its neighbors to a separately chosen control sample of field stars. Re-examining the Rogers et al. Ks-band measurement of CoRoT-1b finds an eclipse 3190{sup +370}{sub -440} ppm deep centered at {phi}{sub me} = 0.50418{sup +0.00197}{sub -0.00203}. Finally, we provide and recommend the use of selected data sets we generated as a benchmark test for eclipse modeling and analysis routines, and propose criteria to verify eclipse detections.

79 ASTRONOMY AND ASTROPHYSICS↗

Biogeochemical modeling at mass extinction boundaries

The causes of major mass extinctions is a subject of considerable interest to those concerned with the history and evolution of life on earth. The primary objectives of the proposed plan of research are: (1) to develop quantitative time-dependent biogeochemical cycle models, coupled with an ocean atmosphere in order to improve the understanding of global scale physical, chemical, and biological processes that control the distribution of elements important for life at times of mass extinctions; and (2) to develop a comprehensive data base of the best available geochemical, isotopic, and other relevant geologic data from sections across mass extinction boundaries. These data will be used to constrain and test the biogeochemical model. These modeling experiments should prove useful in: (1) determining the possible cause(s) of the environmental changes seen at bio-event boundaries; (2) identifying and quantifying little-known feedbacks among the oceans, atmosphere, and biosphere; and (3) providing additional insights into the possible responses of the earth system to perturbations of various timescales. One of the best known mass extinction events marks the Cretaceous/Tertiary (K/T) boundary (66 Myr ago). Data from the K/T boundary are used here to constrain a newly developed time-dependent biogeochemical cycle model that is designed to study transient behavior of the earth system. Model results predict significant fluctuations in ocean alkalinity, atmospheric CO2, and global temperatures caused by extinction of calcareous plankton and reduction in the sedimentation rates of pelagic carbonates and organic carbon. Oxygen-isotome and other paleoclimatic data from K/T time provide some evidence that such climatic fluctuations may have occurred, but stabilizing feedbacks may have acted to reduce the ocean alkalinity and carbon dioxide fluctuations.

Rampino, M. R.↗

Modeling the effects of exercise during 100% oxygen prebreathe on the risk of hypobaric decompression sickness

BACKGROUND: Several previous studies indicated that exercise during prebreathe with 100% O2 decreased the incidence of hypobaric decompression sickness (DCS). We report a meta-analysis of these investigations combined with a new study in our laboratory to develop a statistical model as a predictive tool for DCS. HYPOTHESIS: Exercise during prebreathe increases N2 elimination in a theoretical 360-min half-time compartment decreasing the incidence of DCS. METHODS: A dose-response probability tissue ratio (TR) model with 95% confidence limits was created for two groups, prebreathe with exercise (n = 113) and resting prebreathe (n = 113), using nonlinear regression analysis with maximum likelihood optimization. RESULTS: The model predicted that prebreathe exercise would reduce the residual N2 in a 360-min half-time compartment to a level analogous to that in a 180-min compartment. This finding supported the hypothesis. The incidence of DCS for the exercise prebreathe group was significantly decreased (Chi-Square = 17.1, p < 0.0001) from the resting prebreathe group. CONCLUSIONS: The results suggested that exercise during prebreathe increases tissue perfusion and N2 elimination approximately 2-fold and markedly lowers the risk of DCS. Based on the model, the prebreathe duration may be reduced from 240 min to a predicted 91 min for the protocol in our study, but this remains to be verified. The model provides a useful planning tool to develop and test appropriate prebreathe exercise protocols and to predict DCS risks for astronauts.

NASA Program Environmental Health↗

Effect of spatial sampling from European flux towers for estimating carbon and water fluxes with artificial neural networks

Abstract Empirical modeling approaches are frequently used to upscale local eddy covariance observations of carbon, water, and energy fluxes to regional and global scales. The predictive capacity of such models largely depends on the data used for parameterization and identification of input‐output relationships, while prediction for conditions outside the training domain is generally uncertain. In this work, artificial neural networks (ANNs) were used for the prediction of gross primary production (GPP) and latent heat flux (LE) on local and European scales with the aim to assess the portion of uncertainties in extrapolation due to sample selection. ANNs were found to be a useful tool for GPP and LE prediction, in particular for extrapolation in time (mean absolute error MAE for GPP between 0.53 and 1.56 gC m −2 d −1 ). Extrapolation in space in similar climatic and vegetation conditions also gave good results (GPP MAE 0.7–1.41 gC m −2 d −1 ), while extrapolation in areas with different seasonal cycles and controlling factors (e.g., the tropical regions) showed noticeably higher errors (GPP MAE 0.8–2.09 gC m −2 d −1 ). The distribution and the number of sites used for ANN training had a remarkable effect on prediction uncertainty in both, regional GPP and LE budgets and their interannual variability. Results obtained show that for ANN upscaling for continents with relatively small networks of sites, the error due to the sampling can be large and needs to be considered and quantified. The analysis of the spatial variability of the uncertainty helped to identify the meteorological drivers driving the uncertainty.

Papale, Dario↗

Minimizing Segregation during the Controlled Directional Solidification of Dendric Alloys

Gravity-driven convection induced in the liquid by density gradients of temperature or composition disrupts uniform dendritic growth during controlled directional solidification and promotes severe macrosegregation. The solute-rich region about the dendrite tip appears to play a pivotal role in channel initiation. Allen and Hunt referred to this region as an "initial transient" or dynamic region constituting steep concentration gradients. Experimental investigation also point to the role the tip region plays in developing microstructure. Hellawell and co-workers showed that flow-through dendritic channels could be effectively disrupted, and segregation minimized, during the gradient freezing of bulk castings by rotating the melt through a slight angle with respect to Earth's gravity vector. Adapting this principle to controlled directional solidification, it has been shown" that segregation in dendritic alloys can be minimized, and properties improved, by processing the sample near horizontal in conjunction with a slow axial rotation of the crucible. It is postulated that the observed microstructural uniformity arises by maintaining the developing solute field about the dendrite tip. Solute rejected during vertical directional solidification will rise or sink parallel to the primary dendrite arms during axial rotation setting the stage for accumulation, instabilities, and segregation. In contrast, during horizontal growth, the rejected solute will sink or rise perpendicular to the primary dendrite. Now, in the presence of a slight axial rotation, solute that was initially sinking (or rising) will find itself above (or below) its parent dendrite, i.e., still about the tip region. The following is intended to experimentally demonstrate the viability of this concept in coordination with a model that gives predictive insight regarding solute distribution about growing dendrites. Alloys based on the lead-tin eutectic system were used in this study. The system is well characterized, the constituent metals are available in a very pure form, and the thermophysical properties are well known. During solidification of hypoeutectic alloys, e.g., 55 wt pct Pb, the primary dendrites reject the less dense tin, and for the hypereutectic alloys, e.g., 75 wt pct Sn, the primary dendrites reject denser lead. Alloys were prepared by melting appropriate amounts of lead and tin in a glass crucible after which the homogeneous liquid was sucked directly into 5-mm i.d. glass tubes. The sample tube, containing approximately 30 cm of alloy, was then mechanically driven into the directional solidification furnace assembly and positioned such that approx. 20 cm of the sample was remelted. Subsequently, directional solidification was initiated by withdrawing the sample through a water-cooled jacket at a constant growth velocity of 2 ,microns/s. After 5 to 6 cm of growth, the sample was quickly removed from the furnace and quenched in a water bath to preserve the solid-liquid interface. Samples were directionally solidified vertically upward, nearly horizontally, and some in conjunction with an applied axial rotation of the crucible. Temperature gradients at the solid-liquid interface were measured with an in-siru K-type thermocouple. Solidified samples were cut perpendicular and parallel to the growth direction and conventionally prepared for microscopic examination.

Grugel, Richard N.↗

The coyote universe extended: Precision emulation of the matter power spectrum

Modern sky surveys are returning precision measurements of cosmological statistics such as weak lensing shear correlations, the distribution of galaxies, and cluster abundance. To fully exploit these observations, theorists must provide predictions that are at least as accurate as the measurements, as well as robust estimates of systematic errors that are inherent to the modeling process. In the nonlinear regime of structure formation, this challenge can only be overcome by developing a large-scale, multi-physics simulation capability covering a range of cosmological models and astrophysical processes. As a first step to achieving this goal, we have recently developed a prediction scheme for the matter power spectrum (a so-called emulator), accurate at the 1% level out to k ∼ 1 Mpc{sup –1} and z = 1 for wCDM cosmologies based on a set of high-accuracy N-body simulations. It is highly desirable to increase the range in both redshift and wavenumber and to extend the reach in cosmological parameter space. To make progress in this direction, while minimizing computational cost, we present a strategy that maximally reuses the original simulations. We demonstrate improvement over the original spatial dynamic range by an order of magnitude, reaching k ∼ 10 h Mpc{sup –1}, a four-fold increase in redshift coverage, to z = 4, and now include the Hubble parameter as a new independent variable. To further the range in k and z, a new set of nested simulations run at modest cost is added to the original set. The extension in h is performed by including perturbation theory results within a multi-scale procedure for building the emulator. This economical methodology still gives excellent error control, ∼5% near the edges of the domain of applicability of the emulator. A public domain code for the new emulator is released as part of the work presented in this paper.

79 ASTRONOMY AND ASTROPHYSICS↗

Towards a Scalable and Adaptive Application Support Platform for Large-Scale Distributed E-Sciences in High-Performance Network Environments

The advent of large-scale collaborative scientific applications has demonstrated the potential for broad scientific communities to pool globally distributed resources to produce unprecedented data acquisition, movement, and analysis. System resources including supercomputers, data repositories, computing facilities, network infrastructures, storage systems, and display devices have been increasingly deployed at national laboratories and academic institutes. These resources are typically shared by large communities of users over Internet or dedicated networks and hence exhibit an inherent dynamic nature in their availability, accessibility, capacity, and stability. Scientific applications using either experimental facilities or computation-based simulations with various physical, chemical, climatic, and biological models feature diverse scientific workflows as simple as linear pipelines or as complex as a directed acyclic graphs, which must be executed and supported over wide-area networks with massively distributed resources. Application users oftentimes need to manually configure their computing tasks over networks in an ad hoc manner, hence significantly limiting the productivity of scientists and constraining the utilization of resources. The success of these large-scale distributed applications requires a highly adaptive and massively scalable workflow platform that provides automated and optimized computing and networking services. This project is to design and develop a generic Scientific Workflow Automation and Management Platform (SWAMP), which contains a web-based user interface specially tailored for a target application, a set of user libraries, and several easy-to-use computing and networking toolkits for application scientists to conveniently assemble, execute, monitor, and control complex computing workflows in heterogeneous high-performance network environments. SWAMP will enable the automation and management of the entire process of scientific workflows with the convenience of a few mouse clicks while hiding the implementation and technical details from end users. Particularly, we will consider two types of applications with distinct performance requirements: data-centric and service-centric applications. For data-centric applications, the main workflow task involves large-volume data generation, catalog, storage, and movement typically from supercomputers or experimental facilities to a team of geographically distributed users; while for service-centric applications, the main focus of workflow is on data archiving, preprocessing, filtering, synthesis, visualization, and other application-specific analysis. We will conduct a comprehensive comparison of existing workflow systems and choose the best suited one with open-source code, a flexible system structure, and a large user base as the starting point for our development. Based on the chosen system, we will develop and integrate new components including a black box design of computing modules, performance monitoring and prediction, and workflow optimization and reconfiguration, which are missing from existing workflow systems. A modular design for separating specification, execution, and monitoring aspects will be adopted to establish a common generic infrastructure suited for a wide spectrum of science applications. We will further design and develop efficient workflow mapping and scheduling algorithms to optimize the workflow performance in terms of minimum end-to-end delay, maximum frame rate, and highest reliability. We will develop and demonstrate the SWAMP system in a local environment, the grid network, and the 100Gpbs Advanced Network Initiative (ANI) testbed. The demonstration will target scientific applications in climate modeling and high energy physics and the functions to be demonstrated include workflow deployment, execution, steering, and reconfiguration. Throughout the project period, we will work closely with the science communities in the fields of climate modeling and high energy physics including Spallation Neutron Source (SNS) and Large Hadron Collider (LHC) projects to mature the system for production use.

97 MATHEMATICS AND COMPUTING↗

Numerical analysis of three complex three-dimensional shock wave / turbulent boundary layer interaction flows

A set of Reynolds-averaged Navier-Stokes (RANS) computations with turbulence closure provided by the Spalart-Allmaras (SA) model have been carried out for prediction of shock-induced three-dimensional (3D) turbulent separated flows. The experimental data for different aerodynamic test configurations have been used for assessing credibility of the numerical method employed. Particularly, shock wave / turbulent boundary layer interactions (SWTBLI) in the vicinity of an asymmetric sharp double-fin (DF) with different (7° and 11°) deflection angles mounted on a flat plate and two conically sharp cylindrical bodies at varying interbody distances and nose cone angles 60° and 40° mounted over a flat plate at freestream Mach number 4, as well as a transonic fan stage operating in the near-stall regime are considered. The gas dynamic structure and topology of 3D separated flows, surface flow patterns, and pressure distributions as well as body aerodynamic force prediction are analyzed. A transonic fan stage operating in the near-stall regime and a possibility of applying flow control is investigated. High Performance Computing was employed to make high resolution computations of these flows possible, and advanced 3D visualization techniques were employed in order to improve understanding of the separating flow phenomena.

42 ENGINEERING↗

CFD Study of NACA 0018 Airfoil with Flow Control

The abilities of two different Reynolds-Averaged Navier-Stokes codes to predict the effects of an active flow control device are evaluated. The flow control device consists of a blowing slot located on the upper surface of an NACA 0018 airfoil, near the leading edge. A second blowing slot present on the airfoil near mid-chord is not evaluated here. Experimental results from a wind tunnel test show that a slot blowing with high momentum coefficient will increase the lift of the airfoil (compared to no blowing) and delay flow separation. A slot with low momentum coefficient will decrease the lift and induce separation even at low angles of attack. Two codes, CFL3D and FUN3D, are used in two-dimensional computations along with several different turbulence models. Two of these produced reasonable results for this flow, when run fully turbulent. A more advanced transition model failed to predict reasonable results, but warrants further study using different inputs. Including inviscid upper and lower tunnel walls in the simulations was found to be important in obtaining pressure distributions and lift coefficients that best matched experimental data. A limited number of three-dimensional computations were also performed.

Eggert, Christopher A.↗

Potential distribution of an invasive pest, Eu platypus parallelus , in China as predicted by Maxent

Abstract BACKGROUND Eu platypus parallelus is a highly polyphagous invasive pest native to Central and South America. In recent years it has invaded many countries in Africa and Asia and resulted in considerable economic loss. In China it has been reported to have invaded Taiwan, and been also recorded in Hainan Province. Until now there has been no invasion into the mainland. In order to better manage this invasive pest, here we predicted the suitable area of E. parallelus in China by the Maxent model. RESULTS The Maxent model predicted the potential distribution of E. parallelus with a test AUC value of 0.962 and a training AUC value of 0.978. Temperature seasonality (Bio_04), annual temperature range (Bio_07), annual precipitation (Bio_12) and mean temperature of the coldest quarter (Bio_11) were the strongest predictors of E. parallelus distribution with 32.1%, 19.8%, 15% and 10.4% contributions, respectively. The potential suitable area for E. parallelus was mainly distributed in the southeastern coast, the southwestern border, and Taiwan and Hainan provinces in China, and the highly suitable areas were located in the northern coast of Hainan Province and the southwestern coast of Taiwan Province. This pest prefers a stable, warm and rainy climate, which indicates that tropics and subtropics would be its ideal area. CONCLUSION Eu platypus parallelus has invaded Hainan and Taiwan in China. Measures should be taken to prevent it from spreading on these two islands. Moreover, strict quarantine, biological study and control measures are necessary to block its spread, invasion and damage, especially in these climate‐suitable areas. © 2018 Society of Chemical Industry

Tang, Jihong↗