An enhanced differential evolution-based inverse radiation transport model for identification of unknown shielding layer thicknesses with gamma-ray spectrum

Identifying the geometric information of an object by analyzing the detected radiation fields is an important problem for national and global security.In the present work,an inverse radiation transport model,based on the enhanced differential evolution algorithm with global and local neighborhoods(IRT-DEGL),is developed to estimate the unknown layer thickness of the source/shield system with the gamma-ray spectrum.The framework is briefly introduced with the emphasis on handling the enhanced differential evolution algorithm.Using the simulated gamma-ray spectra,the numerical precision of the IRT-DEGL model is evaluated for one-dimensional source systems.Using the detected gamma-ray spectra,the inverse investigations for the unknown thicknesses of multiple shielding layers are performed.By comparing with the traditional gamma-ray absorption method,it is shown that the IRT-EDGL model can provide a much more accurate result and has great potential to be applied for the complicated systems.

Inverse method for the determination of elastic properties of coating layers by the surface ultrasonic waves

As the coated materials are widely applied in engineering, estimation of the elastic properties of coating layers is of great practical importance. This paper presents an inversion algorithm for determining the elastic properties of coating layers from the given velocity dispersion of surface ultrasonic waves. Based on the dispersive equation of surface waves in layered half space, an objective function dependent on coating material parameters is introduced. The density and wave velocities, which make the object function minimum, are taken as the inversion results. Inverse analyses of two parameters (longitudinal and transverse velocities) and three parameters (the density, longitudinal and transverse velocities) of the coating layer were made.

Application of the Adaptive Shrinkage Genetic Algorithm in the Feasible Region to TEM Conductive Thin Layer Inversion

Combining the adaptive shrinkage genetic algorithm in the feasible region with the imaging of apparent vertical conductance differential, we have inverted the TEM conductive thin layer. The result of the inversion demonstrates that by adaptive shrinkage in the feasible region, the calculation speed accelerates and the calculation precision improves. To a certain extent, in this method we surmount the transient electromagnetic sounding equivalence and reduced equivalence scope. Comparison of the inverted result with the forward curve clearly shows that we can image the conductive thin layer.

Identification of the unknown shielding parameters with gammaray spectrum using a derivative-free inverse radiation transport model

Identifying the unknown geometric and material information of a multi-shield object by analyzing the radiation signature measurements is always an important problem in national and global security. In order to identify the unknown shielding layer thicknesses of a source/shield system with gamma-ray spectra, we have developed a derivative-free inverse radiation transport model based on a differential evolution algorithm with global and local neighbourhoods(IRT-DEGL). In the present paper, the IRT-DEGL model is further extended for estimating the unknown thicknesses with random initial guesses and material mass densities of multi-shielding layers as well as their combinations. Using the detected gamma-ray spectra,the illustration of inverse studies is implemented and the main influence factors for inverse results are also analyzed.

Analysis of Meteorological Causes of Serious Air Pollution in Xingtai City Based on Inversion Layer

Based on meteorological sounding data in 2011 -2014 and air pollution data in 2013 and 2014 from an environmental monitoring station in Xingtai City, the characteristics of inversion layer and air pollution and their correlation in Xingtai City were discussed. The results show that term perature inversion was very serious at 07：00 in Xingtai City, and days with temperature inversion accounted for above 90%. There were obvious seasonal variations in air pollution in Xingtai City, and air pollution was the most serious in winter but the slightest in summer. The primary air pollu- tants in Xingtai City are PM10 and PM2.5, and the primary air pollutants and AQI had close correlation with parameters of inversion layer. Stable ground inversion layer could hinder air convection and air capacity, so that air pollution become more serious with the discharge of pollutants. Inversion layer nearly appearing all the year around is an important meteorological reason for serious air pollution in Xingtai City.

Statistics of the Tropopause Inversion Layer over Beijing

High resolution radiosonde data from Beijing, China in 2002 are used to study the strong tropopause inversion layer （TIL） in the extratropical regions in eastern Asia. The analysis, based on the tropopause- based mean （TB-mean） method, shows that the TIL over Beijing has similar features as over other sites in the same latitude in Northern America. The reduced values of buoyancy frequency in 13-17 km altitude in winter-spring are attributed to the higher occurrence frequency of the secondary tropopause in this season. In the monthly mean temperature profile relative to the secondary tropopause, there also exists a TIL with somewhat enhanced static stability directly over the secondary sharp thermal tropopause, and a 4 km thickness layer with reduced values of buoyancy frequency just below the tropopause, which corresponds to the 13-17 km layer in the first TB-mean thermal profile. In the monthly mean temperature profile relative to the secondary tropopause, a TIL also exists but it is not as strong. For individual cases, a modified definition of the TIL, focusing on the super stability and the small distance from the tropopause, is introduced. The analysis shows that the lower boundary of the newly defined TIL is about 0.42 km above the tropopause, and that it is higher in winter and lower in summer; the thickness of the TIL is larger in winter-spring.

Parameter inversion and location determination of evolutionary weak layer for open-pit mine slope

In light of the complex and dynamic mechanical properties of evolving weak strata in open-pit mines,and the consequent difficulty of determining their mechanical parameters,this study uses the ultimate balance theory,along with the back analysis method combined with monitoring data on field displacement,to carry out parameter inversion using the FLAC3D numerical simulation software.The edge slope of a working pit of the Weijiamao open-pit mine was used as research object to this end.As the results obtained by the constitutive model were consistent with the field monitoring data,the evolving weak strata in the slope and the position of the landslide in the mine could be obtained.The landslide was directed northeast.The mechanism of the edge slope of the working pit was identified as unloading shear failure,and the feasibility of the method of parameter inversion was verified.The internal friction angle φand cohesion C of evolving weak strata in the slope of the open-pit mine were also obtained,where this compensated for the deficiency of laboratory tests and enabled the transformation from qualitative to quantitative analysis.This can provide a reliable basis for the safe operation of open-pit mines.

Bayesian Rayleigh wave inversion with an unknown number of layers

Surface wave methods have received much attention due to their efficient, flexible and convenient characteristics. However, there are still critical issues regarding a key step in surface wave inversion. In most existing methods, the number of layers is assumed to be known prior to the process of inversion. However, improper assignment of this parameter leads to erroneous inversion results. A Bayesian nonparametric method for Rayleigh wave inversion is proposed herein to address this problem. In this method, each model class represents a particular number of layers with unknown S-wave velocity and thickness of each layer. As a result, determination of the number of layers is equivalent to selection of the most applicable model class. Regarding each model class, the optimization search of S-wave velocity and thickness of each layer is implemented by using a genetic algorithm. Then, each model class is assessed in view of its efficiency under the Bayesian framework and the most efficient class is selected. Simulated and actual examples verify that the proposed Bayesian nonparametric approach is reliable and efficient for Rayleigh wave inversion, especially for its capability to determine the number of layers.

Inversion of thicknesses of multi-layered structures from eddy current testing measurements

Luquire et al. ' s impedance change model of a rectangular cross section probe coil above a structure with an arbitrary number of parallel layers was used to study the principle of measuring thicknesses of multi-layered structures in terms of eddy current testing voltage measurements. An experimental system for multi-layered thickness measurement was developed and several fitting models to formulate the relationships between detected impedance/voltage measurements and thickness are put forward using least square method. The determination of multi-layered thicknesses was investigated after inversing the voltage outputs of the detecting system. The best fitting and inversion models are presented.

Occam Inversion of Transient Electromagnetic Data in a Layered Medium with Azimuthal Anisotropy

In recent years, the anisotropic study has become a hot topic in the field of electromagnetics. Currently, inversion technologies of transient electromagnetic sounding data are mainly based on the case of an isotropic medium. However, the actual underground electrical structure tends to be complicated and anisotropic. It is often found that the isotropic inversion technologies do not lead to good results for field transient electromagnetic sounding data. We have developed an algorithm for calculating the transient electromagnetic response in a layered medium with azimuthal anisotropy. An occam inversion algorithm has also been implemented to invert the transient electromagnetic data induced by a grounded horizontal electric dipole in a layered medium with azimuthal anisotropy. Synthetic examples demonstrate the stability and validity of the inversion algorithm. Experimental results show different data for inverting have great influence on the inversion results.

Applying Neural Network Architecture for Inverse Kinematics Problem in Robotics

One of the most important problems in robot kinematics and control is, finding the solution of Inverse Kinematics. Inverse kinematics computation has been one of the main problems in robotics research. As the Complexity of robot increases, obtaining the inverse kinematics is difficult and computationally expensive. Traditional methods such as geometric, iterative and algebraic are inadequate if the joint structure of the manipulator is more complex. As alternative approaches, neural networks and optimal search methods have been widely used for inverse kinematics modeling and control in robotics This paper proposes neural network architecture that consists of 6 sub-neural networks to solve the inverse kinematics problem for robotics manipulators with 2 or higher degrees of freedom. The neural networks utilized are multi-layered perceptron (MLP) with a back-propagation training algorithm. This approach will reduce the complexity of the algorithm and calculation (matrix inversion) faced when using the Inverse Geometric Models implementation (IGM) in robotics. The obtained results are presented and analyzed in order to prove the efficiency of the proposed approach.

FAST APPROXIMATE INVERSION OF MAGNETOTELLURIC(FAIMT) DATA FOR A HORIZONTALLY LAYERED EARTH WITH NEAR-SURFACE INHOMOGENEITIES

This paper discusses use of approximations and the Integral Mean Value Theorem to show that 6 coefficients approximately describe the distortions of near surface inhomogeneities on the MT field of a horizontally layered earth model. When these 6 coefficients are considered together with those of the magnetic field of a horizontally layered earth model,the analytic and approximate wave impedance equations can be derived for the MT response of a horizontally layered earth model with near-surface 2-D and 3-D inhomogeneities. These approximate wave impedance equations are used with inverted MT data for 2-D and 3-D forward modelling. Although these 6 coefficients cannot be determined before inversion,initial estimates can be used. The 6 coefficients and the asistivity and thickness of each layer of a horizontally layered earth can be obtained by using published inversion methods. The 6 coefficients give important informaion (depths and resistivities) on the near-surface inhomogenelties.The authors inverted 2-D and 3-D theoretical models for Fast Approximate Inversion of Magnetotelluric (FAIMT) data for a horizontally layered earth with near-surface inhomogeneities compares favorably with traditional invrsion methods, especially for inverting regional or basin structures. This method simplifies computation and gives a reasonable 1 -D geological model with fewer nonuniquenas problems.

Physical mechanism and numerical simulations of surface layer temperature inversion in tropical ocean

The one-dimensional Kraus- Turner mixed layer model improved by Liu is developed to consider the effect of salinity and the equa- tions of temperature and salinity under the mixed layer. On this basis, the processes of growth and death of surface layer temperature inversion is numerically simulated under different environmental parameters. At the same time, the physical mechanism is preliminari- ly discussed combining the observations at the station of TOGA- COARE 0°N, 156°E. The results indicate that temperature inversion sensitively depends on the mixed layer depth, sea surface wind speed and solar shortwave radiation, etc., and appropriately meteoro- logical and hydrological conditions often lead to the similarly periodical occurrence of this inversion phenomenon.

Inverse estimation for unknown fouling geometry on inner wall of forced-convection pipe

A conjugate gradient method （CGM） based on the inverse algorithm is used to estimate the unknown fouling-layer profile on the inner wall of a pipe system using simulated temperature measurements taken within the pipe wall. It is assumed that no prior information is available about the functional form of the unknown profile. Therefore, the procedure is classified as the function estimation in inverse calculation. The temperature data obtained from the direct problem are used to simulate the temperature measurements. The accuracy of the inverse analysis is examined using the simulated exact and inexact temperature measurements. The results show that the excellent estimation of the fouling-layer profile can be obtained for the test case considered in this study. The technique presented in this study can be used in a warning system to call for pipe maintenance when the thickness of fouling exceeds a predefined criterion.

Research on Thin Layer Structure Identification and Sedimentary Facies of Middle and Deep Layers Based on Reflection Coefficient Inversion—By Taking Dongying Formation of CFD Oilfield in Bohai Offshore as an Example

The sand layer B of Dongying Formation of CFD oilfield in Bohai offshore belongs to the middle deep layer of buried hill overlap deposit. Its reservoir distribution has the characteristics of large burial depth, thin thickness and rapidly lateral change. Because of low resolution of seismic data and overlying sand layer. It is difficult to identify and interpret the structure of sand layer accurately. The uncertainty of structure and reservoir restricts the fine development of B sand layer. In order to identify the top surface of reservoir effectively. The seismic data are processed by using the reflection coefficient inversion method. The results show that the inversion resolution of reflection coefficient is significantly higher than that of original data. The top surface of sand layer B and its overlying sand layer can be well identified and traced. Carrying out structural interpretation of B sand layer based on reflection coefficient inversion data and the microstructure and the formation tip extinction point are implemented. Based on the constraint of new interpretation level, the sedimentary facies plane distribution of B sand layer is described and make prediction of dominant reservoir development area in detail combining with sedimentary paleogeomorphology, along layer attribute section and limited drilling data. The research shows that the study area is mainly from the northwest material sources, the slope belt in the northwest is close to the lake shoreline with a gentle slope and shallow water depositional environment, which is located on the main transport and deposition channels. The shallow water gentle slope landform is suitable for forming large-area sand bar deposition, mainly composed of underwater distributary channel and debouch bars facies, which is the dominant reservoir development area. The research conclusion guides the deployment and implementation of the development well location effectively.

Assessing the effects of model parameter assumptions on surface-wave inversion results

Surface-wave inversion is a powerful tool for revealing the Earth's internal structure.However,aside from shear-wave velocity(v_(S)),other parameters can influence the inversion outcomes,yet these have not been systematically discussed.This study investigates the influence of various parameter assumptions on the results of surface-wave inversion,including the compressional and shear velocity ratio(v_(P)/v_(S)),shear-wave attenuation(Q_(S)),density(ρ),Moho interface,and sedimentary layer.We constructed synthetic models to generate dispersion data and compared the obtained results with different parameter assumptions with those of the true model.The results indicate that the v_(P)/v_(S) ratio,Q_(S),and density(ρ) have minimal effects on absolute velocity values and perturbation patterns in the inversion.Conversely,assumptions about the Moho interface and sedimentary layer significantly influenced absolute velocity values and perturbation patterns.Introducing an erroneous Mohointerface depth in the initial model of the inversion significantly affected the v_(S) model near that depth,while using a smooth initial model results in relatively minor deviations.The assumption on the sedimentary layer not only affects shallow structure results but also impacts the result at greater depths.Non-linear inversion methods outperform linear inversion methods,particularly for the assumptions of the Moho interface and sedimentary layer.Joint inversion with other data types,such as receiver functions or Rayleigh wave ellipticity,and using data from a broader period range or higher-mode surface waves,can mitigate these deviations.Furthermore,incorporating more accurate prior information can improve inversion results.

Parameter Inversions of Multi-Layer Media of Mars Polar Region with Validation of SHARAD Data

HF (high frequency) radar sounder technology has been developed for several missions of Mars surface/subsurface exploration. This paper presents a model of rough surface and stratified sub-surfaces to describe the multi-layer structure of Mars polar deposits. Based on numerical simulation of radar echoes from rough surface/stratified interfaces, an inversion approach is developed to obtain the parameters of Polar Layered Deposits, i.e. layers thickness and dielectric constants. As a validation example, the SHARAD radar sounder data of the Promethei Lingula of Mars South Polar region is adopted for parameters inversion. The result of stratification is also analyzed and compared with the optical photo of the deep cliff of Chasma Australe canyon. Dielectric inversions show that the deposit media are not uniform, and the dielectric constants of the Promethei Lingula surfaces are large, and become reduced around the depth of 20 m - 30 m, below where most of the deposits are nearly pure ice, except a few thin layers with a lot of dust.

Boundary Layer Characteristics and Numerical Simulation Analysis of Winter Dense Fog in Nanjing

Based on the boundary layer data of winter dense fog in 2007 from Nanjing University of Information Science & Technology,the profile characteristics of temperature,wind direction,wind speed and humidity in a dense fog weather on December 13-14 in 2007 were analyzed,as well as their evolution laws in the formation and dispersion of fog,and the boundary layer characteristics of winter dense fog in Nanjing were revealed,while the development of fog was simulated by means of mesoscale numerical model.The results showed that the formation and dispersion of fog was greatly affected by inversion and humidity in the surface layer,and the wind direction in the surface layer also had effect on the formation and dispersion of advection fog.Mesoscale numerical model could preferably simulate the evolution of temperature,humidity,vertical speed in the development of fog,and the simulation of water vapor content in the fog could forecast the formation and dispersion of fog.

Frequency-domain elastic full-waveform multiscale inversion method based on dual-level parallelism

The complexity of an elastic wavefield increases the nonlinearity of inversion, To some extent, multiscale inversion decreases the nonlinearity of inversion and prevents it from falling into local extremes. A multiscale strategy based on the simultaneous use of frequency groups and layer stripping method based on damped wave field improves the stability of inversion. A dual-level parallel algorithm is then used to decrease the computational cost and improve practicability. The seismic wave modeling of a single frequency and inversion in a frequency group are computed in parallel by multiple nodes based on multifrontal massively parallel sparse direct solver and MPI. Numerical tests using an overthrust model show that the proposed inversion algorithm can effectively improve the stability and accuracy of inversion by selecting the appropriate inversion frequency and damping factor in low- frequency seismic data.

A robust behavior of Feed Forward Back propagation algorithm of Artificial Neural Networks in the application of vertical electrical sounding data inversion

The applications of intelligent techniques have increased exponentially in recent days to study most of the non-linear parameters. In particular, the behavior of earth resembles the non- linearity applications. An efficient tool is needed for the interpretation of geophysical parameters to study the subsurface of the earth. Artificial Neural Networks （ANN） perform certain tasks if the structure of the network is modified accordingly for the purpose it has been used. The three most robust networks were taken and comparatively analyzed for their performance to choose the appropriate network. The single- layer feed-forward neural network with the back propagation algorithm is chosen as one of the well- suited networks after comparing the results. Initially, certain synthetic data sets of all three-layer curves have been taken tk^r training the network, and the network is validated by the field datasets collected from Tuticorin Coastal Region （78°7＇30＂E and 8°48＇45＂N）, Tamil Nadu, India. The interpretation has been done successfully using the corresponding learning algorithm in the present study. With proper training of back propagation networks, it tends to give the resistivity and thickness of the subsurface layer model of the field resistivity data concerning the synthetic data trained earlier in the appropriate network. The network is trained with more Vertical Electrical Sounding （VES） data, and this trained network is demon- strated by the field data. Groundwater table depth also has been modeled.