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At least 865 records · Page 48

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↗

Validating corrosion models: Influence of physical properties

In chloride containing environments, two metals in physical contact can undergo galvanic corrosion limiting the lifetime of components. Being able to accurately predict galvanic corrosion damage distributions over time has not been widely presented in literature. Therefore, Finite Element Method (FEM) corrosion models were experimentally validated for two galvanic couples as a function of governing equations, environment, anode material, anode:cathode ratio, and time. Carbon steel/stainless steel (CS/SS) and zinc/stainless steel (Zn/SS) galvanic couples were exposed to NaCl solutions at room temperatures for up to 14 days. For the galvanic couples and environments, the Laplace equation with variable conductivity and reactions was sufficient to model the experimental corrosion damage. Increasing the chloride concentration for the CS/SS galvanic couple, regardless of the anode:cathode ratio, decreased the observed and modeled corrosion damage. Decreasing the anode:cathode ratio (i.e., increasing the cathode length), increased the experimentally observed and modeled corrosion damage. For small anode:cathode ratios, the governing equations deviate over long time periods with the Nernst-Plank equation being conservative. For the Zn/SS galvanic couple, the cathode length controls the dominant cathodic reduction reaction. For small cathode lengths, the hydrogen evolution reaction is dominant. For larger cathode lengths, the oxygen reduction reaction is dominant. The results are discussed with regard to the influence of solution chemistry, ohmic drop, and governing reactions. Overall, validated FEM models were presented, and the resultant models, physics, and mechanisms can be applied to other corrosion scenarios with confidence.

Carbon steel↗

Evaluation of Turbulence and Dispersion in Multiscale Atmospheric Simulations over Complex Urban Terrain during the Joint Urban 2003 Field Campaign

Abstract This paper evaluates the representation of turbulence and its effect on transport and dispersion within multiscale and microscale-only simulations in an urban environment. These simulations, run using the Weather Research and Forecasting Model with the addition of an immersed boundary method, predict transport and mixing during a controlled tracer release from the Joint Urban 2003 field campaign in Oklahoma City, Oklahoma. This work extends the results of a recent study through analysis of turbulence kinetic energy and turbulence spectra and their role in accurately simulating wind speed, direction, and tracer concentration. The significance and role of surface heat fluxes and use of the cell perturbation method in the numerical simulation setup are also examined. Our previous study detailed the model development necessary for our multiscale simulations, examined model skill at predicting wind speeds and tracer concentrations, and demonstrated that dynamic downscaling from mesoscale to microscale through a sequence of nested simulations can improve predictions of transport and dispersion relative to a microscale-only simulation forced by idealized meteorology. Here, predictions are compared with observations to assess qualitative agreement and statistical model skill at predicting wind speed, wind direction, tracer concentration, and turbulent kinetic energy at locations throughout the city. We also investigate the scale distribution of turbulence and the associated impact on model skill, particularly for predictions of transport and dispersion. Our results show that downscaled large-scale turbulence, which is unique to the multiscale simulations, significantly improves predictions of tracer concentrations in this complex urban environment. Significance Statement Simulations of atmospheric transport and mixing in urban environments have many applications, including pollution modeling for urban planning or informing emergency response following a hazardous release. These applications include phenomena with spatial scales spanning from millimeters to kilometers. Most simulations resolve flow only within the urban area of interest, omitting larger scales of turbulence and regional influences. This study examines a method that resolves both the small and large-scale flow features. We evaluate simulation accuracy by comparing predictions with observations from an experiment involving the release of a tracer gas in Oklahoma City, Oklahoma, with emphasis on correctly modeling turbulent fluctuations. Our results demonstrate the importance of resolving large-scale flow features when predicting transport and dispersion in urban environments.

42 ENGINEERING↗

Validation of MPACT BWR capabilities against critical experiments

Over the years, significant validation work for the neutronics code MPACT has been performed against zero-power critical benchmarks and measured data from operating nuclear power plants. As a part of the Modeling and Analysis of Exelon BWRs for Eigenvalue and Thermal Limits Predictability project, new validation efforts relevant to boiling water reactor (BWR) core applications have been performed. This paper presents the results of the critical experiment portion of the BWR validation efforts for MPACT. The Kritz-4 experiments and IPEN/MB-01 BWR-relevant configurations are modeled with MPACT. The Kritz-4 BWR critical experiments were performed at both cold and hot conditions, which is a unique feature among other critical experiment facilities. The MPACT results with linear source (LS) Method of Characteristics (MOC) have very good agreement with the measured criticality. When using the 60-group BWR library with LS and P2 scattering, the maximum k{sub eff} error is 109 pcm, and the average cold-hot bias is only -0.11 pcm/K. The fission rate distributions of MPACT are also verified with Serpent calculations. For the IPEN facility, two configurations are considered: one with a large central void, and one with a cruciform control rod. The MPACT k{sub eff} errors are less than 50 pcm for all IPEN problems. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

3D hydrogeophysical characterization of managed aquifer recharge basins

Aquifers are increasingly stressed. Managed aquifer recharge provides a potential solution to mitigate this stress and provide sustainable groundwater resources. Subsurface properties are known to have a strong control on the infiltration rates that can be achieved. However, these properties are often highly heterogeneous and difficult to assess with conventional probing techniques. Here, we show the application of 3D geophysical imaging to assess the recharge potential and its variation across several basins used for managed aquifer recharge. We link in-situ measurements of saturated hydraulic conductivity with the electrical resistivity of the subsurface to establish petrophysical relationships and use those relationships to estimate the distribution of hydraulic conductivity throughout the five recharge basins. Our results show a considerable variability in the hydraulic properties, i.e., soil texture and saturated hydraulic conductivity, that have a direct impact on potential infiltration rates. We use the 3D hydraulic property distributions to model groundwater recharge and provide estimates for infiltration rates and volumes, and use this approach to assess the impact of management activities on groundwater recharge performance. Having such data not only enables us to predict infiltration rates, but also provides means for optimizing such water infrastructure.

54 ENVIRONMENTAL SCIENCES↗

Probabilistic projections of the Amery Ice Shelf catchment, Antarctica, under conditions of high ice-shelf basal melt

Abstract. Antarctica's Lambert Glacier drains about one-sixth of the ice from the East Antarctic Ice Sheet and is considered stable due to the strong buttressing provided by the Amery Ice Shelf. While previous projections of the sea-level contribution from this sector of the ice sheet have predicted significant mass loss only with near-complete removal of the ice shelf, the ocean warming necessary for this was deemed unlikely. Recent climate projections through 2300 indicate that sufficient ocean warming is a distinct possibility after 2100. This work explores the impact of parametric uncertainty on projections of the response of the Lambert–Amery system (hereafter “the Amery sector”) to abrupt ocean warming through Bayesian calibration of a perturbed-parameter ice-sheet model ensemble. We address the computational cost of uncertainty quantification for ice-sheet model projections via statistical emulation, which employs surrogate models for fast and inexpensive parameter space exploration while retaining critical features of the high-fidelity simulations. To this end, we build Gaussian process (GP) emulators from simulations of the Amery sector at a medium resolution (4–20 km mesh) using the Model for Prediction Across Scales (MPAS)-Albany Land Ice (MALI) model. We consider six input parameters that control basal friction, ice stiffness, calving, and ice-shelf basal melting. From these, we generate 200 perturbed input parameter initializations using space filling Sobol sampling. For our end-to-end probabilistic modeling workflow, we first train emulators on the simulation ensemble and then calibrate the input parameters using observations of the mass balance, grounding line movement, and calving front movement with priors assigned via expert knowledge. Next, we use MALI to project a subset of simulations to 2300 using ocean and atmosphere forcings from a climate model for both low- and high-greenhouse-gas-emission scenarios. From these simulation outputs, we build multivariate emulators by combining GP regression with principal component dimension reduction to emulate multivariate sea-level contribution time series data from the MALI simulations. We then use these emulators to propagate uncertainty from model input parameters to predictions of glacier mass loss through 2300, demonstrating that the calibrated posterior distributions have both greater mass loss and reduced variance compared to the uncalibrated prior distributions. Parametric uncertainty is large enough through about 2130 that the two projections under different emission scenarios are indistinguishable from one another. However, after rapid ocean warming in the first half of the 22nd century, the projections become statistically distinct within decades. Overall, this study demonstrates an efficient Bayesian calibration and uncertainty propagation workflow for ice-sheet model projections and identifies the potential for large sea-level rise contributions from the Amery sector of the Antarctic Ice Sheet after 2100 under high-greenhouse-gas-emission scenarios.

54 ENVIRONMENTAL SCIENCES↗

Engine-Scale Combustor Rig Designed, Fabricated, and Tested for Combustion Instability Control Research

Low-emission combustor designs are prone to combustor instabilities. Because active control of these instabilities may allow future combustors to meet both stringent emissions and performance requirements, an experimental combustor rig was developed for investigating methods of actively suppressing combustion instabilities. The experimental rig has features similar to a real engine combustor and exhibits instabilities representative of those in aircraft gas turbine engines. Experimental testing in the spring of 1999 demonstrated that the rig can be tuned to closely represent an instability observed in engine tests. Future plans are to develop and demonstrate combustion instability control using this experimental combustor rig. The NASA Glenn Research Center at Lewis Field is leading the Combustion Instability Control program to investigate methods for actively suppressing combustion instabilities. Under this program, a single-nozzle, liquid-fueled research combustor rig was designed, fabricated, and tested. The rig has many of the complexities of a real engine combustor, including an actual fuel nozzle and swirler, dilution cooling, and an effusion-cooled liner. Prior to designing the experimental rig, a survey of aircraft engine combustion instability experience identified an instability observed in a prototype engine as a suitable candidate for replication. The frequency of the instability was 525 Hz, with an amplitude of approximately 1.5-psi peak-to-peak at a burner pressure of 200 psia. The single-nozzle experimental combustor rig was designed to preserve subcomponent lengths, cross sectional area distribution, flow distribution, pressure-drop distribution, temperature distribution, and other factors previously found to be determinants of burner acoustic frequencies, mode shapes, gain, and damping. Analytical models were used to predict the acoustic resonances of both the engine combustor and proposed experiment. The analysis confirmed that the test rig configuration and engine configuration had similar longitudinal acoustic characteristics, increasing the likelihood that the engine instability would be replicated in the rig. Parametric analytical studies were performed to understand the influence of geometry and condition variations and to establish a combustion test plan. Cold-flow experiments verified that the design values of area and flow distributions were obtained. Combustion test results established the existence of a longitudinal combustion instability in the 500-Hz range with a measured amplitude approximating that observed in the engine. Modifications to the rig configuration during testing also showed the potential for injector independence. The research combustor rig was developed in partnership with Pratt & Whitney of West Palm Beach, Florida, and United Technologies Research Center of East Hartford, Connecticut. Experimental testing of the combustor rig took place at United Technologies Research Center.

DeLaat, John C.↗

Aero-Propulsive Modeling for eVTOL Aircraft Using Wind Tunnel Testing with Multisine Inputs

A novel approach for modeling the aero-propulsive characteristics of an electric vertical takeoff and landing (eVTOL) aircraft was developed and demonstrated in wind tunnel testing. The approach was applied to the NASA LA-8 tandem tilt-wing eVTOL aircraft, using an efficient, hybrid experiment design composed of a static I-optimal response surface design for slowly-varying test variables, and dynamic orthogonal phase-optimized multisine excitations for the control surfaces and electric propulsors. Both the static and dynamic experiment designs were executed simultaneously to collect informative data for model identification. Statistically-weighted multivariate orthogonal function modeling was used to combine local modeling results computed in the frequency domain using data collected with dynamic excitations operating on the control effectors to form an aggregate aero-propulsive model. The final identified model exhibited good predictive capability when compared to validation data acquired separately from the data used to develop the model. The required test time using these new techniques was reduced by at least a factor of five compared to previous static wind tunnel testing for the LA-8 aircraft, while providing more informative data, greater parameterization flexibility, and high-quality models.

system identification↗

A voxel-based multiscale model to simulate the radiation response of hypoxic tumors

Purpose: In radiotherapy, it is important to predict the response of tumors to irradiation prior to the treatment. This is especially important for hypoxic tumors, which are known to be highly radioresistant. Mathematical modeling based on the dose distribution, biological parameters, and medical images may help to improve this prediction and to optimize the treatment plan. Methods: A voxel-based multiscale tumor response model for simulating the radiation response of hypoxic tumors was developed. It considers viable and dead tumor cells, capillary and normal cells, as well as the most relevant biological processes such as (i) proliferation of tumor cells, (ii) hypoxia-induced angiogenesis, (iii) spatial exchange of cells leading to tumor growth, (iv) oxygen-dependent cell survival after irradiation, (v) resorption of dead cells, and (vi) spatial exchange of cells leading to tumor shrinkage. Oxygenation is described on a microscopic scale using a previously published tumor oxygenation model, which calculates the oxygen distribution for each voxel using the vascular fraction as the most important input parameter. To demonstrate the capabilities of the model, the dependence of the oxygen distribution on tumor growth and radiation-induced shrinkage is investigated. In addition, the impact of three different reoxygenation processes is compared and tumor control probability (TCP) curves for a squamous cells carcinoma of the head and neck (HNSSC) are simulated under normoxic and hypoxic conditions. Results: The model describes the spatiotemporal behavior of the tumor on three different scales: (i) on the macroscopic scale, it describes tumor growth and shrinkage during radiation treatment, (ii) on a mesoscopic scale, it provides the cell density and vascular fraction for each voxel, and (iii) on the microscopic scale, the oxygen distribution may be obtained in terms of oxygen histograms. With increasing tumor size, the simulated tumors develop a hypoxic core. Within the model, tumor shrinkage was found to be significantly more important for reoxygenation than angiogenesis or decreased oxygen consumption due to an increased fraction of dead cells. In the studied HNSSC-case, the TCD{sub 50} values (dose at 50% TCP) decreased from 71.0 Gy under hypoxic to 53.6 Gy under the oxic condition. Conclusions: The results obtained with the developed multiscale model are in accordance with expectations based on radiobiological principles and clinical experience. As the model is voxel-based, radiological imaging methods may help to provide the required 3D-characterization of the tumor prior to irradiation. For clinical application, the model has to be further validated with experimental and clinical data. If this is achieved, the model may be used to optimize fractionation schedules and dose distributions for the treatment of hypoxic tumors.

60 APPLIED LIFE SCIENCES↗

Improved Modeling Tools Development for High Penetration Solar

One of the significant objectives of the High Penetration solar research is to help the DOE understand, anticipate, and minimize grid operation impacts as more solar resources are added to the electric power system. For Task 2.2, an effective, reliable approach to predicting solar energy availability for energy generation forecasts using the University of California, San Diego (UCSD) Sky Imager technology has been demonstrated. Granular cloud and ramp forecasts for the next 5 to 20 minutes over an area of 10 square miles were developed. Sky images taken every 30 seconds are processed to determine cloud locations and cloud motion vectors yielding future cloud shadow locations respective to distributed generation or utility solar power plants in the area. The performance of the method depends on cloud characteristics. On days with more advective cloud conditions, the developed method outperforms persistence forecasts by up to 30% (based on mean absolute error). On days with dynamic conditions, the method performs worse than persistence. Sky Imagers hold promise for ramp forecasting and ramp mitigation in conjunction with inverter controls and energy storage. The pre-commercial Sky Imager solar forecasting algorithm was documented with licensing information and was a Sunshot website highlight.

14 SOLAR ENERGY↗

THE ROLE OF CORE MASS IN CONTROLLING EVAPORATION: THE KEPLER RADIUS DISTRIBUTION AND THE KEPLER-36 DENSITY DICHOTOMY

We use models of coupled thermal evolution and photo-evaporative mass loss to understand the formation and evolution of the Kepler-36 system. We show that the large contrast in mean planetary density observed by Carter et al. can be explained as a natural consequence of photo-evaporation from planets that formed with similar initial compositions. However, rather than being due to differences in XUV irradiation between the planets, we find that this contrast is due to the difference in the masses of the planets' rock/iron cores and the impact that this has on mass-loss evolution. We explore in detail how our coupled models depend on irradiation, mass, age, composition, and the efficiency of mass loss. Based on fits to large numbers of coupled evolution and mass-loss runs, we provide analytic fits to understand threshold XUV fluxes for significant atmospheric loss, as a function of core mass and mass-loss efficiency. Finally we discuss these results in the context of recent studies of the radius distribution of Kepler candidates. Using our parameter study, we make testable predictions for the frequency of sub-Neptune-sized planets. We show that 1.8-4.0 R{sub ⊕} planets should become significantly less common on orbits within 10 days and discuss the possibility of a narrow 'occurrence valley' in the radius-flux distribution. Moreover, we describe how photo-evaporation provides a natural explanation for the recent observations of Ciardi et al. that inner planets are preferentially smaller within the systems.

79 ASTRONOMY AND ASTROPHYSICS↗

Study on 3D Internal Magnetic Field Distribution and Dynamic Mechanics of a Giant Magnetostrictive Actuator

The three-dimensional (3D) coupled magneto-elastic dynamic model of a giant magnetostrictive actuator (GMA) was built based on Maxwell’s equations, elasticity, and vibration theories. The general analytical expressions for the 3D internal magnetic field distribution of GMA were derived, and the corresponding analytical solutions were obtained. This analytical model is able to predict the internal magnetic field distribution and the output displacement of GMA system with different physical parameters under external excitations. The dynamic behaviors, such as the amplitude vs. frequency responses and the time domain waveforms of the GMA, were also studied. Analytical solutions showed that the internal magnetic field has a prominent end effect along the axial direction of a giant magnetostrictive material (GMM) rod, whereas a minimal skin effect along its radial direction, which are matched very well with the FEM results. The amplitude-frequency relationship exhibited prominent resonance and anti-resonance characteristic, which is a typical hysteresis feature of the GMA system. In order to testify the validity of the model prediction, a GMA testing system was also established. Excellent agreement was found between the experiment measurements and model predictions in the range of our research (frequency is lower than 300 Hz). The analytical results of the present study have potential applications in the fields of active vibration control and other precision machining of the GMA system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Inferring Atmospheric Release Characteristics in a Large Computer Experiment using Bayesian Adaptive Splines

An atmospheric release of hazardous material, whether accidental or intentional, can be catastrophic for those in the path of the plume. Predicting the path of a plume based on characteristics of the release (location, amount and duration) and meteorological conditions is an active research area highly relevant for emergency and long-term response to these releases. As a result, researchers have developed particle dispersion simulators to provide plume path predictions that incorporate release characteristics and meteorological conditions. However, since release characteristics and meteorological conditions are often unknown, the inverse problem is of great interest, that is, based on all the observations of the plume so far, what can be inferred about the release characteristics? This is the question we seek to answer using plume observations from a controlled release at the Diablo Canyon Nuclear Power Plant in Central California. With access to a large number of evaluations of a computationally expensive particle dispersion simulator that includes continuous and categorical inputs and spatio-temporal output, building a fast statistical surrogate model (or emulator) presents many statistical challenges, but is an essential tool for inverse modeling and sensitivity analysis. We achieve accurate emulation using Bayesian adaptive splines to model weights on empirical orthogonal functions. Here, we use this emulator as well as appropriately identifiable simulator discrepancy and observational error models to calibrate the simulator, thus finding a posterior distribution of characteristics of the release. Since the release was controlled, these characteristics are known, making it possible to compare our findings to the truth.

54 ENVIRONMENTAL SCIENCES↗

Multi-Sensor Optimal Motion Planning for Radiological Contamination Surveys by Using Prediction-Difference Maps

Distributed and networked mobile sensor platforms using unmanned aerial and/or ground vehicles to survey areas of interest offer a safer and more efficient method for radiological contamination mapping; however, most applications rely on uniformly sweeping of the area in a raster-type motion without utilizing the information available in a dynamic sense. We have developed a fully autonomous optimal motion planning procedure for networks with two or more mobile sensors. The procedure utilizes well-established concepts of Gaussian processes in combination with control laws based on centroidal Voronoi tessellations to achieve optimal next-iteration sensor movements. A new method of informing optimal motion planning is proposed, whereby the absolute difference between the prior and current full-map prediction, referred to as the prediction-difference map, is used as the spatial density function within each Voronoi cell, providing immediate and iterative feedback for dynamic use of available information. The Gaussian process regression model used to estimate the contamination in unvisited locations also provides prediction uncertainties, and can be used as a quantitative metric to assess the confidence in the calculated contamination map; these estimates and prediction uncertainties are unavailable for standard uniform survey routines as they can only produce maps in the vicinity of observed locations. We present through simulation the achievable performance gains from using this new method by directly comparing to a uniform survey method. Results show that using the prediction-difference maps to inform motion planning procedures offers a faster rate of producing an accurate and convergent map relative to a uniform survey route.

47 OTHER INSTRUMENTATION↗

Exhaust Simulation Testing of a Hypersonic Airbreathing Model at Transonic Speeds

An experimental study was performed to examine jet-effects for an airframe-integrated, scramjet-rocket combined-cycle vehicle configuration at transonic test conditions. This investigation was performed by testing an existing exhaust simulation wind tunnel model, known as Model 5B, in the NASA Langley 16-Ft. Transonic Tunnel. Tests were conducted at freestream Mach numbers from 0.7 to 1.2, at angles of attack from 2 to +14 degrees, and at up to seven nozzle static pressure ratio values for a set of horizontal-tail and body-flap deflections. The model aftbody, horizontal tails, and body flaps were extensively pressure instrumented to provide an understanding of jet-effects and control-surface/plume interactions, as well as for the development of analytical methodologies and calibration of computational fluid dynamic codes to predict this type of flow phenomenon. At all transonic test conditions examined, the exhaust flow at the exit of the internal nozzle was over-expanded, generating an exhaust plume that turned toward the aftbody. Pressure contour plots for the aftbody of Model 5B are presented for freestream transonic Mach numbers of 0.70, 0.95, and 1.20. These pressure data, along with shadowgraph images, indicated the impingement of an internal plume shock and at least one reflected shock onto the aftbody for all transonic conditions tested. These results also provided evidence of the highly three-dimensional nature of the aftbody exhaust flowfield. Parametric testing showed that angle-of-attack, static nozzle pressure ratio, and freestream Mach number all affected the exhaust-plume size, exhaust-flowfield shock structure, and the aftbody-pressure distribution, with Mach number having the largest effect. Integration of the aftbody pressure data showed large variations in the pitching moment throughout the transonic regime.

Huebner, Lawrence D.↗

A New Method for Predicting Turbulent Flow Reattachment Location: Application of Stratford Criterion for Reattaching Flows

A new method for predicting turbulent flow reattachment location has been developed. The method predicts the reattachment location using the surface static pressure distribution and requires only a single empirical parameter. The method is based on the well-known Stratford’s flow separation criterion, which results from an approximate solution to the equations of motion within the boundary layer. Because of the large pressure rise, the original Stratford separation criterion is not valid for reattaching flows. In order to apply the Stratford criterion for reattaching flows, the reference location was moved to the pressure drop conditions instead of pressure rise conditions. In addition, the pressure distribution was scaled using a technique that was originally introduced for supersonic base flows. A new empirical parameter was also obtained for the modified Stratford criterion. The method has been tested for 30 different separated flow configurations from the literature. The variety of test cases include subsonic flows, transonic flows, 2D flows, and axisymmetric flows, with experimental as well as high resolution numerical simulation results. The flow reattachment predictions with the new method agree very well with the reported data. The error is less than 5% and typically about 2%. The new method is an extremely simple and a quick way of finding the reattachment location. Given the complexities of the existing experimental techniques for finding the reattachment location, the method easily and quickly provides the flow reattachment location, which could be used to estimate the physical extent of separation bubbles, as a performance index for flow control methods, or to assess the predictive capability of turbulence models.

Flow reattachment location↗

The distribution, orientation, and characteristics of natural fractures for Experiment 1 of the EGS Collab Project, Sanford Underground Research Facility

The EGS Collab project is focused on understanding and predicting permeability enhancement and evolution in crystalline rocks. To accomplish this, the project is creating a suite of intermediate-scale (~10-20 m) field test beds coupled with stimulation and interwell flow tests that will provide a basis to better understand the fracture geometries and processes that control heat transfer between rock and stimulated fractures. As part of the site characterization effort for the first experimental test bed, our team has worked on mapping the distribution, orientation, and nature of open and healed fractures exposed along the drift wall and within the eight bore holes drilled for this test bed. The fractures have been characterized through detailed description of continuous cores obtained from these boreholes, evaluation of televiewer logs, and mapping of fractures and seeps exposed along the drift wall. The fracture data are being compiled and interpreted for slip and dilation tendencies, and will be incorporated into coupled-process geomechanical flow and transport models to better constrain the planned flow and tracer tests.

15 GEOTHERMAL ENERGY↗

The impact of halo concentration on the Sunyaev Zel’dovich effect signal from massive galaxy clusters

ABSTRACT The Sunyaev Zel’dovich (SZ) effect is sensitive to the pressure of ionized gas inside galaxy clusters, which is in turn controlled largely by the gravitational potential of the cluster. Changing the concentration parameter describing the cluster mass distribution impacts the gravitational potential and thus the cluster SZ signal, with implications for cosmological and other analyses of SZ-selected clusters. We investigate the concentration–SZ relation in theory and simulations. We find that the impact of concentration on the inner SZ profile (R ≲ 0.75R200c) can be captured with standard polytropic gas models. However, we find that such models do a poor job of reproducing the outer SZ profiles (R ≳ 0.75R200c) and the relation between the integrated SZ signal, Y, and concentration. This disagreement results from a sharp truncation of the gas pressure profile near the splashback radius, likely caused by virial shocks. We develop a simple description of the truncation that leads to a good match with the simulated SZ profiles out to several R200c for clusters of varying mass and concentration, and that also accurately predicts the concentration–Y relationship. Finally, we determine how inference of the linear bias parameter and splashback radius for SZ-selected clusters can be biased by ignoring the concentration dependence of the SZ signal, finding that bias to the former is essentially negligible, while bias to the latter can be as much as 2 per cent.

Astronomy & Astrophysics↗