Constructing Expertise: Surmounting Performance Plateaus by Tasks, by Tools, and by Techniques.

This paper presents a procedure to estimate relative permeability curves together with gridblock porosities and permeabilities by automatic history matching three-phase flow production data using the LBFGS algorithm for optimization and the adjoint method for generating sensitivity coefficients. Both power law and B-splines are considered for the representation of relative permeability curves. Power law is a simple representation; however, B-splines have the advantage of being able to accurately represent any set of relative permeability curves. In the B-spline representation, we provide a simple procedure based on a transformation of parameters (control points) defining the B-splines to ensure that monotonic curves are obtained. Without this transformation, the automatic history-matching process fails. If endpoint saturations are included as parameters, we show how to modify the adjoint procedure to account for the fact that initial conditions are sensitive to endpoint saturations. While the history-matching process is inherently non-unique, we show that reasonable estimates of relative permeability curves and porosity/ permeability fields can be obtained for a synthetic reservoir example. We also show the uncertainty quantification of the model parameters and reservoir performance prediction using the Randomized Maximum Likelihood (RML) method. Introduction Relative permeabilities are important parameters in reservoir performance calculations. Usually the relative permeability curves are obtained from labs through core flood tests. They can also be incorporated into the history matching procedure as model parameters. ARCHER and WONG (1973), and YANG and WATSON (1991) were among the early researchers to consider the estimation of relative permeability curves by history matching laboratory core flood data. A detailed literature review is given in REYNOLDS et al. (2004). REYNOLDS et al. (2004) also discussed the estimation of three-phase relative permeabilities by history matching roduction data. The current work is a natural extension of REYNOLDS et al. (2004). In this paper, we provide an alternative method for relative permeability estimation based on B-spline approximation. Compared to power law representation, Bsplines ave the advantage of being able to accurately represent any set of relative permeability curves. In the B-spline representation, we provide a simple procedure based on logtransformation of parameters (control points) defining the Bsplines to ensure the B-spline curves are monotonic or convex as used in CHEN et al. (2005). Since a reservoir simulator requires monotonic relative permeability curves, without this transformation, the automatic history-matching process may generate non-monotonic relative permeability curves and result in failed reservoir simulation run. A prior model for porosity and absolute permeability and relative permeability parameters is assumed to provide regularization, i.e., Bayesian estimation is applied to generate estimates. Model parameters, which are estimated by automatic history matching of production data, consist of gridblock porosties, gridblock absolute logpermeabilities and the parameters defining the relative permeability curves. We do not assume the endpoint saturations (i.e. irreducible water saturation, critical gas saturation and residual oil saturation) to be known and consider them as independent model parameters in history matching procedure.

Mainstream psychology in the 20th century has been conceived as a nomothetic science, but few psychological "laws" have been proposed. A PsycLit search of journal abstracts from 1900 to 1999 yielded a total of 3,093 "law" citations, or 22 per 10,000 entries, with two psychophysical laws (Weber's law and Stevens's power law) and two learning laws (Herrnstein's matching law and Thorndike's law of effect) as the most frequently cited. The number of law citations has been decreasing throughout the century, to 10 per 10,000 entries in the last decade, with few references to laws of recent origin. This could be the result of increasing doubts about the lawfulness of psychological processes coupled with a general preference for less ambitious terms (such as effects, principles, models, or functions).

This paper deals with the study of the flapwise bending vibration and dynamic stability of rotating functionally graded material plates in thermal environments. A finite element formulation is derived for modal and dynamic stability analyses of rotating functionally graded material plates using first-order shear deformation theory. Temperature-dependent material properties of the plates are considered in the analysis and a simple power law is assumed for composition of constituent materials to vary along the thickness direction. The same power law is also proposed in thermal environments for temperature variation across the thickness of the plate. Some numerical results obtained from the present method are compared with numerical results available in the literature and are found to be in good agreement. Parametric investigation is carried out thoroughly to study the effect of the temperature rise, hub radius, and rotational speed on vibration and the dynamic stability of rotating plate in thermal environment. Bolotin’s method is used to generate the boundaries of stability and instability regions. These instability regions are plotted in the parameter space with the nondimensional dynamic load and excitation frequency. It is observed that the natural frequencies reduce with an increase in temperature rise. Increase in rotational speed and hub radius results in increase of natural frequencies of vibration. The rise in temperature leads to reduction in the dynamic stability of plate. Increase in rotational speed and hub radius enhances the dynamic stability of the rotating plate.

The Bay of Bengal and Arabian Sea are annually exposed to severe tropical cyclones, which impose massive infrastructure damages and cause the loss of life in coastal regions. Cyclone Shaheen originally generated in the Bay of Bengal in 2021 and translated a rare east-to-west path toward the Arabian Sea. Although the cyclone’s wind field can be obtained from reanalysis datasets such as ERA5 (fifth generation European Centre for Medium-Range Weather Forecasts), the wind speed cannot be reproduced with realistic details in the regions close to the center of cyclone due to spatial resolution. In this study, to address this problem, the high-resolution advanced Weather Research and Forecasting (WRF) model is used for simulation of Shaheen’s wind field. As a critical part of the study, the sensitivity of the results to the planetary boundary layer (PBL) parameterization in terms of the track, intensity, strength and structure of the cyclone Shaheen is investigated. Five experiments are considered with five PBL schemes: Yonsei University (YSU); Mellor–Yamada–Janjić (MYJ); Mellor–Yamada–Nakanishi–Niino level 2.5 (MYNN); Asymmetric Convective Model version 2 (ACM2); Quasi-Normal Scale Elimination (QNSE). The track, intensity, and strength of the experiments are compared with the wind fields obtained from the Joint Typhoon Warning Centre (JTWC) dataset. The results imply the high dependency of the track, intensity, and strength of the cyclone to the PBL parameterization. Simulated tracks with non-local PBL schemes (YSU and ACM2) outperformed those of the local PBL schemes (MYJ, MYNN, and QNSE), especially during the rapid intensification phase of Shaheen before landfall. The YSU produced highly intensified storm, while the ACM2 results are in better agreement with the JTWC data. The most accurate track was obtained from the ERA5 data; however, this dataset overestimated the spatial size and underestimated the wind speed. The WRF model using either YSU or ACM2 overestimated the wind speed compared to that of the altimeter data. The YSU and ACM2 schemes were able to reproduce the observed increase in wind speed and pressure drop at in situ stations. The wind data from EAR5 and cyclone parametric model were applied to the SWAN model to simulate the wave regime in the Arabian Sea during the time that Shaheen was translating across the region. Janssen formulation for wind input and whitecapping dissipation source terms in combination with both ERA5 and hybrid wind were used and the minimum combined error in the prediction of significant wave height (Hs) and zero up-crossing wave period (Tz) was examined. The maximum significant wave height for hybrid wind is higher than that of ERA5, while the cyclone development was successfully inferred from the wave field of the hybrid data.

In straight-through centrifugal pumps, a grooved seal acts as a balance piston to equilibrate the full pressure rise across the pump. As the groove pattern breaks the development of fluid swirl, this seal type offers lesser leakage and lower cross-coupled stiffnesses than a similar size and clearance annular seal. Bulk-flow models (BFMs) predict expediently the static and dynamic force characteristics of annular seals; however they lack accuracy for grooved seals. Computational fluid dynamics (CFD) methods give more accurate results, but are not computationally efficient. This paper presents a modified BFM to predict the rotordynamic force coefficients of shallow depth, circumferentially grooved liquid seals with an accuracy comparable to a CFD solution but with a simulation time of bulk-flow analyses. The procedure utilizes the results of CFD to evaluate the bulk flow velocity field and the friction factors for a 73 grooves annular seal (depth/clearance dg/Cr = 0.98 and length/diameter L/D = 0.9) operating under various sets of axial pressure drop and rotor speed. In a groove, the flow divides into a jet through the film land and a strong recirculation zone. The penetration angle (α), specifying the streamline separation in the groove cavity, is a function of the operating conditions; an increase in rotor speed or a lower pressure difference increases α. This angle plays a prominent role to evaluate the stator friction factor and has a marked influence on the seal direct stiffness. In the bulk-flow code, the friction factor model (f = nRem) is modified with the CFD extracted penetration angle (α) to account for the flow separation in the groove cavity. The flow rate predicted by the modified bulk-flow code shows good agreement with the measured result (6% difference). A perturbation of the flow field is performed on the bulk-flow equations to evaluate the reaction forces on the rotor surface. Compared to the rotordynamic force coefficients derived from the CFD results, the modified bulk-flow code predicts rotordynamic force coefficients within 10%, except that the cross-coupled damping coefficient is over-predicted up to 14%. An example test seal with a few grooves (L/D = 0.5, dg/Cr = 2.5) serves to further validate the predictions of the modified BFM. Compared to the original bulk-flow analysis, the current method shows a significant improvement in the predicted rotordynamic force coefficients, the direct stiffness and damping coefficients, in particular.

The scaling law of deep learning, which governs the relationship between model size and performance, has led to critical concerns regarding efficiency and sustainability. To address these challenges, this study presents a computational approach using self-organized submillimeter-long tungsten disulfide nanotube cluster as a 3D very-large-scale physical reservoir. The reservoir, with its 0D van der Waals interfaces on the order of 108, or 1.0×1010 mm-3, matches the synaptic quantity and density of the fruit fly's brain. The reservoir demonstrates the capability to perform a wide range of tasks from monomodal challenges to multimodal endeavors such as speech-to-image and medical image generation. The photosensitive mimetic synaptic connections in the very large scale reservoir emulate the optogenetic modulation of neuron circuits in in-vivo biological systems. By integrating the principles of the scaling law, multimodal task capabilities, and mimetic optogenetic mechanisms, this research paves a path toward advanced computing architectures tailored for next-generation energy-efficient artificial intelligence.

For nearly 5 decades, the global semiconductor industry has followed Moore's law, which employs the iterative concept of transistor scaling in silicon-based technology. Though this approach has been massively successful at maintaining consistent increases in computational speed and power, silicon technology is quickly approaching its physical limitations with respect to continued scaling. In recent years, a growing effort has been adopted to pursue new materials and technologies as alternative platforms for information processing. Complex oxides are a potential candidate material system for next generation electronic devices due to their rich material properties such as metal-insulator transitions, high T_c superconductivity, and colossal magnetoresistance. In particular, there is growing interest to understand and control the unique electronic properties of complex oxides for applications in transistor-like devices. This dissertation is focused on understanding the growth, characterization and application of La_[1/3]Sr_[2/3]FeO₃ (LSFO) thin films, which are known to undergo an abrupt charge ordering phase transition at 190 K in bulk materials. This phase transition is accompanied by an order of magnitude increase in resistivity going from a conductive to insulating state as well as the spontaneous ordering of charge and antiferromagnetic spin structure along the [111] direction. Isocompositional cation-ordered superlattices of LSFO were synthesized via oxygen-assisted molecular beam epitaxy and explored through synchrotron X-ray diffraction, electronic transport, and density functional theory modeling. By adjusting the cation ordering of LaFeO₃ (LFO), an antiferromagnetic insulator, and SrFeO₃ (SFO), a conductor with a helical magnetic ground state, three isocompositional systems of LSFO were investigated. The superlattices were found to exhibit a charge ordering phase transition similar to LSFO for two of the three structures, as measured by an abrupt discontinuity in the temperature-dependent resistivity. Carrier behavior within the superlattices was also explored by fitting the temperature dependent resistivity to common conduction models. The conduction mechanism fits show that the transport at high temperatures is dominated by weakly insulating behavior due to small polaron conduction and at low temperatures the resistivity can be fit to both a novel power law and 3-dimensional variable range hopping. Additionally, reversible changes of the structural and electronic transport properties of La_[1/3]Sr_[2/3]FeO_[3-[delta]]/Gd-doped CeO₂ (GDC) heterostructures arising from the manipulation of [delta] are presented. Thermally induced oxygen loss leads to a c-axis lattice expansion and an increase in resistivity in an LSFO film capped with GDC. In a three-terminal device where a gate bias is applied across the GDC layer to alter the LSFO oxygen stoichiometry, the ferrite channel is shown to undergo an order of magnitude change in resistance using gate voltages of less than 1 V applied at 500 K. The changes in resistance remain upon cooling to room temperature, in the absence of a gate bias, suggesting solid state ionic gating of perovskite oxides as a promising platform for applications in non-volatile, multistate devices. Along with the experiments of controlling [delta] in a device format, the kinetics of oxygen loss as a function of biaxial strain was investigated.

Received 13 November 2018DOI:https://doi.org/10.1103/PhysRevFluids.3.129901©2018 American Physical SocietyPhysics Subject Headings (PhySH)Research AreasDrop interactionsDrops & bubblesMicrofluidicsFluid Dynamics

The increasing of AVs’ market penetration rate (MPR) changes the traffic behavioural pattern and ultimately influences pavement. Pavement condition, in turn, influences microscopic behaviours. The above bidirection influencing mechanism has not been investigated fully yet. This research fill this gap by modelling the linkage between multi-level microscopic behaviour and pavement sustainability. Three levels of behaviour are considered: travel behaviour, microscopic traffic behaviour, and driving behaviour. The latter two are modelled using stochastic lateral movement model, while the former one is captured by a mixed autonomous traffic assignment model. Microscopic behaviours’ influence on pavement is described by a data-driven model, while the reverse counterpart is described by connecting pavement condition with link wandering and disutility. Our analysis results reveal that at link level, AVs can cause extra 50% drop in free flow speed due to pavement deterioration. Neglecting pavement evolution in strategic assignments leads to a 0.2% increase in network cost.

To study the effect of higher axial sheath velocities on neutron production, the geometry of the inner electrode (anode) of a 3-kJ Mather-type plasma focus device was modified. Double-stage stepped-anode configurations were tested with a speed-enhanced region long enough for a significant increase in speed but not long enough to allow the development of force-field flow-field separation at the end of the axial phase. Peak axial speeds up to 15 cm/μs were achieved without modifying the deuterium filling pressure and charging voltage. The neutron and soft X-ray productions were found to be dependent on sheath velocity. A new scaling law for the nonbeam component of the neutron yield was proposed.

We develop a stochastic model for the time-evolution of scalar concentrations and temporal gradients in concentration experienced by observers moving within inhomogeneous plumes that are dispersing within turbulent flows. In this model, scalar concentrations and their gradients evolve jointly as a Markovian process. Underlying the model formulation is a natural generalisation of Thomson’s well mixed condition [Thomson DJ (1987) J Fluid Mech 180:529–556]. As a consequence model outputs are necessarily compatible with statistical properties of scalars observed in experiment that are used here as model input. We then use the model to examine how insects aloft within the atmospheric boundary-layer can locate odour sources by modulating their flight patterns in response to odour cues. Mechanisms underlying odour-mediated flights have been studied extensively at laboratory-scale but an understanding of these flights over landscape scales is still lacking. Insect flights are simulated by combining the stochastic model with a simple model of insect olfactory response. These simulations show the strong influence of wind speed on the distributions of the times taken by insects to locate the source. In accordance with experimental observations [Baker TC, Vickers NJ (1997) In: Insect pheromone research: new directions, pp 248–264; Mafra-Neto A, Carde RT (1994) Nature 369:142–144], flight patterns are predicted to become straighter and shorter, and source location is predicted to become more likely as the mean wind speed increases. The most probable arrival time to the source decreases with the mean wind speed. It is shown that scale-free movement patterns arising from olfactory-driven foraging stem directly from the power-law distribution of concentration excursion times above/below a threshold level and are robust with respect to variations in Reynolds number. Flight lengths are well represented by a power law distribution in agreement with the observed patterns of foraging bumblebees [Heinrich B (1979) Oecologia 40(3):235–245].

Dynamics of droplets in an electrified medium is largely dictated by an intricate interplay between interfacial charge convection and Ohmic conduction within the bulk. The extent of this interaction is quantified by the electric Reynolds number, ReE, delineating their relative strengths. The reported asymptotic theories consider vanishingly low values of ReE, i.e., negligible surface charge convection as compared to the bulk Ohmic conduction, which, in turn, enables decoupling of the contributions of drop deformation and charge convection. This, however, is grossly inaccurate toward establishing an appropriate inter-connection between surface charge convection and morpho-dynamic evolution of the drop beyond such limiting conditions. Circumventing these limits, here we present a theoretical approach that is capable of bringing out the underlying physics beyond low ReE limits. We realize this by incorporating nonlinear charge-convection effects in the leading-order and first-order problem. The present analytical model not only predicts the drop speed accurately but also shows noticeable improvement over the predictive capabilities of the existing asymptotic models. Our results demonstrate that convection of charges can lead to a substantial increase or decrease in gravitational settling speed, depending on the relative electrical properties of the droplet and the carrier. In sharp contrast to previously reported findings, we show that sufficiently strong charge convection can overwhelm the effect of deformation and hence can reverse the trends in the settling speed reported earlier. Comparison with results from full-scale numerical simulations justifies the accuracy of our analytical approach up to a fair level of high asymmetric deformation.

Helical flow of non-Newtonian fluids in concentric and eccentric annuli is of great interest in oil/gas well drilling. Experimental results and field measurements demonstrated that frictional pressure loss in the annulus can be affected substantially by the rotation of the drillpipe. Previous studies indicated that the influence of pipe rotation on annular friction pressure loss is affected by fluid properties, flow regime, annular diameter ratio and eccentricity.This article presents results of in-depth experimental and theoretical investigations conducted on the flow of yield power law (Herschel Buckley) fluids in concentric and eccentric annuli with pipe rotation. The aim of this study is to develop a reliable hydraulic model that accounts for the effect of pipe rotation in annular pressure loss calculations.Extensive flow experiments with polymer-based fluids were carried out using a newly developed testing facility. Four different annular geometries have been considered for the investigation. Five different formulations of test fluid were prepared by varying concentrations of Xanthan Gum (XG) and Polyanionic Cellulose (PAC) for each annular geometry. Accurate fluid characterization was made using the horizontal pipe sections and a rotational viscometer. In addition to the experimental work, theoretical analysis of helical flows in concentric annuli was carried out.Experimental results indicate the strong presence of shear thinning and inertial effects when inner pipe rotates. In highly eccentric annuli, inertial effects dominate the phenomenon of shear thinning and result in increased pressure loss as the speed increases. Inertial effects can be generated due eccentricity and/or geometric irregularities of the annulus that substantially influence the velocity field as the pipe rotates. The experimental measurements and theoretical analysis presented in this investigation are very useful for hydraulic program optimization and well control, particularly for managed pressure drilling (MPD) operations.

By analyzing by scanning tunnelling microscopy (STM) the amount of material which is removed during grazing incidence ion bombardment from a Pt(111) sample, it was possible to determine the different sputtering yields of ions impinging either on ascending step edges or hitting onto flat terraces. From the analysis of damage patterns of single ion impacts and low fluence experiments it was possible to elaborate a model to explain pattern formation during grazing incidence ion bombardment. For temperatures T < 450K the development of the patterns is solely due to the effects of the ion beam, which removes preferentially material at ascending step edges. At higher temperatures T > 450 K diffusion processes overshadow the effects of the ion beam. In this temperature regime ions channelling underneath the topmost layer create chains of vacancy islands. These islands coalesce preferentially along the ion beam direction and are therefore essential fort he formation of the ripple patterns. Temperature dependent measurements reveal that the ripple formation is only possible within a temperature window. This temperature range can be divided into two distinct ranges: for T < 450 a pattern with a constant wavelength forms while for T > 450 K the wavelength increases rapidly with rising temperatures. The RMS roughness increases up to T = 550 K and decreases for higher temperatures. The temperature dependence of the rescaled defect densities behaves similar to the wavelength. The increase for T > 450 K is related to the onset of step edge diffusion at this temperature. The fluence dependency is analyzed for different sample temperatures. The RMS roughness follows in each case a power law. The wavelength too follows a power law up to an ion fluence of 70 monolayers. For even higher ion fluences the coarsening speed increases. Founded on the higher sputtering yield at ascending step edges a coarsening model based on the erasure of ripples is developed. Changing the angle of incidence reveals that the wavelength depends only slightly onto the angle of incidence while the RMS roughness changes much strongly with increasing angles of incidence. Both behaviours are explained by the decrease of the removed material with increasing angle of incidence. The wavelength as well as the RMS roughness increases linearly with increasing ion energy. The increase of the RMS roughness can be explained by solely considering the increase of the removed material by increasing the ion energy. To explain the behaviour of the wavelength additionally to the increase of the removed material, the initial wavelength, which is energy dependent, has to be considered.

Numerical simulation of flow behavior of particles in a gas-solid stirred fluidized bed