High-precision nonisothermal transient wellbore drift flow model suitable for the full flow pattern domain and full dip range

A reliable multiphase flow simulator is an important tool to improve wellbore integrity and production decision-making.To develop a multiphase flow model with high adaptability and high accuracy,we first build a multiphase flow database with 3561 groups of data and developed a drift closure relationship with stable continuity and high adaptability.Second,a high-order numerical scheme with strong fault capture ability is constructed by effectively combining MUSCL technology,van Albada slope limiter and AUSMV numerical scheme.Finally,the energy equation is coupled into the AUSMV numerical scheme of the drift flow model in the form of finite difference.A transient non-isothermal wellbore multiphase flow model with wide applicability is formed by integrating the three technologies,and the effects of various factors on the calculation accuracy are studied.The accuracy of the simulator is verified by comparing the measurement results with the blowout experiment of a full-scale experimental well.

Moho depth inversion in the Tibetan Plateau from high-precision gravity data

The Tibetan Plateau(TP)is the youngest orogenic belt resulting from a continental collision on the Earth.It is a natural laboratory for studying continental dynamics,such as continental convergence,plate subduction,and plateau uplift.Investigating the deep structure of the TP has always been a popular issue in geological research.The Moho is the boundary between the crust and the mantle and therefore plays a crucial role in the Earth’s structure.Parameters such as depth and lateral variation,as well as the fine structure of the crust-mantle interface,reveal the lithospheric dynamics in the TP.Two methods are generally employed to study the Moho surface:seismic detection and gravity inversion.Seismic detection has the characteristic of high precision,but it is limited to a few cross-sectional lines and is quite costly.It is not suitable for and cannot be carried out over a large area of the TP.The Moho depth over a large area can be obtained through gravity inversion,but this method is affected by the nature of gravity data,and the accuracy of the inversion method is lower than that of seismic detection.In this work,a high-precision gravity field model was selected.The Parker-Oldenburg interface inversion method was used,within the constraints of seismic observations,and the Bott iteration method was introduced to enhance the inversion efficiency.The Moho depth in the TP was obtained with high precision,consistent with the seismic detection results.The research results showed that the shape of the Moho in the TP is complex and the variation range is large,reaching 60−80 km.In contrast with the adjacent area,a clear zone of sharp variation appears at the edge of the plateau.In the interior of the TP,the buried depth of the Moho is characterized by two depressions and two uplifts.To the south of the Yarlung Zangbo River,the Moho inclines to the north,and to the north,the Moho depresses downward,which was interpreted as the Indian plate subducting to the north below Tibet.The Moho depression on the north side of the Qiangtang block,reaching 72 km deep,may be a result of the southward subduction of the lithosphere.The Moho uplift of the Qiangtang block has the same strike as the Bangong−Nujiang suture zone,which may indicate that the area is compensated by a low-density and low-velocity mantle.

POD Analysis and Low-Dimensional Model Based on POD-Galerkin for Two-Dimensional Rayleigh-Bénard Convection

Direct numerical simulation based on OpenFOAM is carried out for two-dimensional RayleighBénard( RB) convection in a square domain at high Rayleigh number of 107 and Pr = 0.71. Proper orthogonal decomposition( POD) is used to analyze the flow and temperature characteristics from POD energy spectrum and eigenmodes. The results show that the energy spectrum converges fast and the scale of vortex structures captured by eigenmodes becomes smaller as the eigenmode order increases. Meanwhile,a low-dimensional model( LDM) for RB convection is derived based on POD eigenmodes used as a basis of Galerkin project of Navier-Stokes-Boussinesq equations. LDM is built based on different number of eigenmodes and through the analysis of phase portraits,streamline and isothermal predicted by LDM,it is suggested that the error between LDM and DNS is still large.

Data Logic Structure and Key Technologies on Intelligent High-precision Map

Taking autonomous driving and driverless as the research object,we discuss and define intelligent high-precision map.Intelligent high-precision map is considered as a key link of future travel,a carrier of real-time perception of traffic resources in the entire space-time range,and the criterion for the operation and control of the whole process of the vehicle.As a new form of map,it has distinctive features in terms of cartography theory and application requirements compared with traditional navigation electronic maps.Thus,it is necessary to analyze and discuss its key features and problems to promote the development of research and application of intelligent high-precision map.Accordingly,we propose an information transmission model based on the cartography theory and combine the wheeled robot’s control flow in practical application.Next,we put forward the data logic structure of intelligent high-precision map,and analyze its application in autonomous driving.Then,we summarize the computing mode of“Crowdsourcing+Edge-Cloud Collaborative Computing”,and carry out key technical analysis on how to improve the quality of crowdsourced data.We also analyze the effective application scenarios of intelligent high-precision map in the future.Finally,we present some thoughts and suggestions for the future development of this field.

A Novel On-Site-Real-Time Method for Identifying Characteristic Parameters Using Ultrasonic Echo Groups and Neural Network

On-site and real-time non-destructive measurement of elastic constants for materials of a component in a in-service structure is a challenge due to structural complexities,such as ambiguous boundary,variable thickness,nonuniform material properties.This work develops for the first time a method that uses ultrasound echo groups and artificial neural network(ANN)for reliable on-site real-time identification of material parameters.The use of echo groups allows the use of lower frequencies,and hence more accommodative to structural complexity.To train the ANNs,a numerical model is established that is capable of computing the waveform of ultrasonic echo groups for any given set of material properties of a given structure.The waveform of an ultrasonic echo groups at an interest location on the surface the structure with material parameters varying in a predefined range are then computed using the numerical model.This results in a set of dataset for training the ANN model.Once the ANN is trained,the material parameters can be identified simultaneously using the actual measured echo waveform as input to the ANN.Intensive tests have been conducted both numerically and experimentally to evaluate the effectiveness and accuracy of the currently proposed method.The results show that the maximum identification error of numerical example is less than 2%,and the maximum identification error of experimental test is less than 7%.Compared with currently prevailing methods and equipment,the proposefy the density and thickness,in addition to the elastic constants.Moreover,the reliability and accuracy of inverse prediction is significantly improved.Thus,it has broad applications and enables real-time field measurements,which has not been fulfilled by any other available methods or equipment.

High-precision simulation and experimental verification of residual stress and surface topography of cylindrical surface shot peening

Shot peening is commonly employed for surface deformation strengthening of cylindrical surface part.Therefore,it is critical to understand the effects of shot peening on residual stress and surface topography.Compared to flat surface,cylindrical surface shot peening has two significant features:(i)the curvature of the cylindrical surface and the scattering of the shot stream cause dis-tributed impact velocities;(i)the rotation of the part results in a periodic variation of the impact velocity component.Therefore,it is a challenge to quickly and accurately predict the shot peening residual stress and surface topography of cylindrical surface.This paper developed a high-precision model which considers the more realistic shot peening process.Firstly,a kinematic analysis model was developed to simulate the relative movement of numerous shots and cylindrical surface.Then,the spatial distribution and time-varying impact information was calculated.Subsequently,the impact information was used for finite element modeling to predict residual stress and surface topography.The proposed kinematic analysis method was validated by comparison with the dis-crete element method.Meanwhile,9310 high strength steel rollers shot peening test verified the effectiveness of the model in predicting the residual stress and surface topography.In addition,the effects of air pressure and attack angle on the residual stress and surface topography were investigated.This work could provide a functional package for efficient prediction of the surface integrity and guide industrial application in cylindrical surface shot peening.

Experimental and modeling study of surface topography generation considering tool-workpiece vibration in high-precision turning

High-precision turning(HPT)is a main processing method for manufacturing rotary high-precision components,especially for metallic parts.However,the generated vibration between tool tip and workpiece during turning may seriously deteriorate the surface integrity.Therefore,exploring the effect of vibration on turning surface morphology and quality of copper parts using 3D surface topography regeneration model is crucial for predicting HPT performance.This developed model can update the machined surface topology in real time.In this study,the effects of tool arc radius,feed rate,radial vibration,axial vibration and tangential vibration on the surface topography and surface roughness were explored.The results show that the effect of radial vibration on surface topography is greater than that of axial vibration and tangential vibration.The radial vibration frequency is also critical.When vibration frequency changes,the surface topography profile presents three different types:the standard sinusoidal curve,the sinusoidal curve whose lowfrequency signal envelopes high-frequency signal,and the oscillation curve whose low-frequency signal superimposes high-frequency signal.In addition,HPT experiment was carried out to validate the developed model.The surface roughness obtained in the experiment was Ra=53 nm,while the roughness obtained by the simulation was Ra=46 nm,achieving a prediction accuracy of 86.7%.Received 4 September 2022;revised 3 October 2022;accepted 17 October 2022.

A high-precision hydrodynamic model coupled with the hydrological habitat suitability model to reveal estuarine vegetation distribution

In this paper,based on the finite volume method,a high-precision hydrodynamic model coupled with the habitat suitability model is established,and the computational efficiency of the coupled model is improved by a graphics processing unit(GPU)-accelerated technology.The coupled model is used to solve the problem of the non-conservation of mass that may be caused by the nearshore hydrodynamic model in the processing of wetting and drying,while avoiding the unphysical high velocities at the wetting and drying boundaries.The coupled model is applied to simulate the high-precision hydrodynamic process of the Liao River estuary(LRE)and the hydrological habitat suitability of the estuarine vegetation(Suaeda heteroptera)growing in the LRE.The simulated values of the hydrological variables(the water level,the water depth,the current velocity and direction)are highly consistent with the measured values.The root mean square errors(RMSE)of the hydrological variables are 0.10m,0.12m/s and 17.24°,respectively.Furthermore,the simulated combined suitability index(CSI)distribution of Suaeda heteroptera(S.heteroptera)matches with the distribution of S.heteroptera obtained from the high-resolution remote sensing satellite images during the same time period.The ratio of the simulated weighted usable area(WUA)of S.heteroptera to the area obtained from the remote sensing satellite images during the same period is 81.9%.This study reveals the phenomenon that the distribution of S.heteroptera in the LRE is highly correlated with the high-precision hydrodynamic processes,and provides a scientific basis and a valuable reference for the conservation and the restoration of the estuarine vegetation.

The proper orthogonal decomposition method for the Navier-Stokes equations

The proper orthogonal decomposition (POD) method for the instationary Navier-Stokes equations is considered. Several numerical approaches to evaluating the POD eigenfunctions are presented. The POD eigenfunctions are applied as a basis for a Galerkin projection of the instationary Navier-Stokes equations. And a low-dimensional ordinary differential models for fluid flows governed by the instationary Navier-Stokes equations are constructed. The numerical examples show that the method is feasible and efficient for optimal control of fluids.

A refined design method for precoolers with consideration of multi-parameter variations based on low-dimensional analysis

The precooler is a distinctive component of precooled air-breathing engines but constitutes a challenge to conventional thermal design methods.The latter are based upon assumptions that often reveal to be limited for precooler design.In this paper,a refined design method considering the variations of fluid thermophysical properties,flow area and thermal parameters distortion,was proposed to remediate their limitations.Firstly,the precooler was discretized into a fixed number of sub-microtubes based on a new discretization criterion.Next,in-house one-dimensional(1D)and two-dimensional(2D)segmented models were established for rapid thermal design and precooler rating with non-uniform airflow,respectively.The heat transfer experimental studies of supercritical hydrocarbon fuel were performed to verify the Jackson correlation for precooler design and the in-house models were validated against the reported data from open literature.On this basis,the proposed method was employed for the design analysis of hydrocarbon fuel precoolers for precooled-Turbine Based Combined Cycle(TBCC)engines.The results show that the local performance of precoolers is intrinsically impacted by the aforementioned three variations.In the case study,the local heat transfer performance is drastically affected by coolant flow transition.While the circumferential temperature distortion of airflow is weakened by heat transfer.With consideration of additional parameter variations,this novel method improves design accuracy and shortens the design time.

Fabrication and photoluminescence characteristics of In_2O_3 nanohillocks

Uniformly distributed polycrystalline indium nanohillocks are synthesized on silicon substrates with Au catalyst by using the radio frequency magnetic sputtering technique. The results show that the Au catalyst plays a key role in the formation of indium nanohillocks. After thermally oxidizing the indium nanohillocks at 500 °C in air for 5 h, the indium nanohillocks totally transform into In2O3 nanohillocks. The energy-dispersive X-ray spectroscopy result indicates that many oxygen vacancies and oxygen-indium vacancy pairs exist in the In2O3 nanohillocks. Photoluminescence spectra under an Ne laser excitation at 280 nm show broad emissions at 420 nm and 470 nm with a shoulder at 450 nm related to oxygen vacancies and oxygen-indium vacancies at room temperature.

A Novel Low-Dimensional Method for Analytically Solving Partial Differential Equations

This paper is concerned with a low-dimensional dynamical system model for analytically solving partial differential equations(PDEs).The model proposed is based on a posterior optimal truncated weighted residue(POT-WR)method,by which an infinite dimensional PDE is optimally truncated and analytically solved in required condition of accuracy.To end that,a POT-WR condition for PDE under consideration is used as a dynamically optimal control criterion with the solving process.A set of bases needs to be constructed without any reference database in order to establish a space to describe low-dimensional dynamical system that is required.The Lagrangian multiplier is introduced to release the constraints due to the Galerkin projection,and a penalty function is also employed to remove the orthogonal constraints.According to the extreme principle,a set of ordinary differential equations is thus obtained by taking the variational operation of the generalized optimal function.A conjugate gradient algorithm by FORTRAN code is developed to solve the ordinary differential equations.The two examples of one-dimensional heat transfer equation and nonlinear Burgers’equation show that the analytical results on the method proposed are good agreement with the numerical simulations and analytical solutions in references,and the dominant characteristics of the dynamics are well captured in case of few bases used only.

Analysis of flow structures in supersonic plane mixing layers using the POD method

The proper orthogonal decomposition(POD) method was applied to analyzing the database obtained from the direct numerical simulation(DNS) of supersonic plane mixing layers.The effect of different forms of the inner products in the POD method was investigated.It was observed that the mean flow contributes to a predominant part of the total flow energy,and the energy spectrum of the turbulence fluctuations covers a wide range of POD modes.The patterns of leading(high energy) POD modes reveal that the flow structures exhibit spanwise counter rotating rolls,as well as oblique vortices.These flow patterns are insensitive to the velocity of the observer.As the convective Mach number increases,the energy spectrum be-comes wider,the leading POD modes contain more complicated structures,and the flow becomes more chaotic.

Geoscience knowledge graph in the big data era

Since the beginning of the 21 st century,the geoscience research has been entering a significant transitional period with the establishment of a new knowledge system as the core and with the drive of big data as the means.It is a revolutionary leap in the research of geoscience knowledge discovery from the traditional encyclopedic discipline knowledge system to the computer-understandable and operable knowledge graph.Based on adopting the graph pattern of general knowledge representation,the geoscience knowledge graph expands the unique spatiotemporal features to the Geoscience knowledge,and integrates geoscience knowledge elements,such as map,text,and number,to establish an all-domain geoscience knowledge representation model.A federated,crowd intelligence-based collaborative method of constructing the geoscience knowledge graph is developed here,which realizes the construction of high-quality professional knowledge graph in collaboration with global geo-scientists.We also develop a method for constructing a dynamic knowledge graph of multi-modal geoscience data based on in-depth text analysis,which extracts geoscience knowledge from massive geoscience literature to construct the latest and most complete dynamic geoscience knowledge graph.A comprehensive and systematic geoscience knowledge graph can not only deepen the existing geoscience big data analysis,but also advance the construction of the high-precision geological time scale driven by big data,the compilation of intelligent maps driven by rules and data,and the geoscience knowledge evolution and reasoning analysis,among others.It will further expand the new directions of geoscience research driven by both data and knowledge,break new ground where geoscience,information science,and data science converge,realize the original innovation of the geoscience research and achieve major theoretical breakthroughs in the spatiotemporal big data research.

Propagation dynamics on the Fermi-Pasta-Ulam lattices

The spatiotemporal propagation of a momentum excitation on the finite Fermi-Pasta-Ulam lattices is investigated. The competition between the solitary wave and phonons gives rise to interesting propagation behaviors. For a moderate nonlinearity, the initially excited pulse may propagate co- herently along the lattice for a long time in a solitary wave manner accompanied by phonon tails. The lifetime of the long-transient propagation state exhibits a sensitivity to the nonlinear parameter. The solitary wave decays exponentially during the final loss of stability, and the decay rate varying with the nonlinear parameter exhibits two different scaling laws. This decay is found to be related to the largest Lyapunov exponent of the corresponding Hamiltonian system, which manifests a transition from weak to strong chaos. The mean-free-path of the solitary waves is estimated in the strong chaos regime, which may be helpful to understand the origin of anomalous conductivity in the Fermi-Pasta Ulam lattice.