Analytical Modelling of Shot-peening Residual Stress on Welding Carbon Steel Surface Layer

The residual stress distribution was studied by an analytical model, due to shot peening on the welding carbon steel surface layer. The initial welding residual stresses before shot peening were taken into consideration in this analytical model. The Hertzian elastic contact theory was used to get the elastic compression stress state after impact on the surface layer. The initial welding stress field and the shot peening stress field would superpose and the welding surface layer would yield based on the elastic-plastic evaluation, then the residual stress after shot peening can be achieved. The influence of initial welding residual stress on the stress distribution after shot peening was analyzed and discussed. A series of experiments were carried out and the residual stress on the welding surface was determined by X-ray diffractometer before and after shot peening. The calculation results of the analytical model are consistent with the experimental results. The critical shot velocities when welding surface layer yielded and reverse yielded were calculated. While the welded joint surface material reversely yielded, the maximum compressive residual stress would not obviously increase with the increase of shot velocity, the thickness of the compressive stress layer would be increased. Welding residual tensile stress can enlarge the thickness of the compressive stress layer at the same shot velocity when reverse yield appeared.

A station-data-based model residual machine learning method for fine-grained meteorological grid prediction

Fine-grained weather forecasting data,i.e.,the grid data with high-resolution,have attracted increasing attention in recent years,especially for some specific applications such as the Winter Olympic Games.Although European Centre for Medium-Range Weather Forecasts(ECMWF)provides grid prediction up to 240 hours,the coarse data are unable to meet high requirements of these major events.In this paper,we propose a method,called model residual machine learning(MRML),to generate grid prediction with high-resolution based on high-precision stations forecasting.MRML applies model output machine learning(MOML)for stations forecasting.Subsequently,MRML utilizes these forecasts to improve the quality of the grid data by fitting a machine learning(ML)model to the residuals.We demonstrate that MRML achieves high capability at diverse meteorological elements,specifically,temperature,relative humidity,and wind speed.In addition,MRML could be easily extended to other post-processing methods by invoking different techniques.In our experiments,MRML outperforms the traditional downscaling methods such as piecewise linear interpolation(PLI)on the testing data.

Assessment of composite failure and ultimate strength without experiment on composite

This paper attempts to estimate the ultimate strength of a laminated composite only based on its con- stituent properties measured independently. Three important issues involved have been systematically addressed, i.e., stress calculation for the constituent fiber and matrix materials, failure detection for the lamina and laminate upon the internal stresses in their constituents, and input data determination of the constituents from monolithic measurements. There are three important factors to influence the accuracy of the strength prediction. One is the stress concentration factor （SCF） in the matrix. Another is matrix plasticity. The third is thermal residual stresses in the constituents. It is these three factors, however, that have not been sufficiently well realized in the composite community. One can easily find out the elastic and strength parameters of a great many laminae and laminates in the current literature. Unfortunately, necessary information to determine the SCF, the matrix plasticity, and the thermal residual stresses of the composites is rare or incomplete. A useful design methodology is demonstrated in the paper.

Refinement of Bouguer anomalies derived from the EGM2008 model,impact on gravimetric signatures in mountainous region:Case of Cameroon Volcanic Line,Central Africa

Global geopotential models have not included the very high frequencies of the Earth’s external gravity field.This is called omission error.This omission error becomes more important in mountainous areas(areas with highly variable topography).The work reported here consists in reducing the omission error in measurements of Bouguer gravity anomalies,by refining the global geopotential model EGM2008 using the spectral enhancement method.This method consists in computing the residual terrain effects and then coupling them to the gravimetric signal of the global geopotential model.To compute the residual terrain effects,we used the Residual Terrain Model(RTM)technique.To refine it required a reference surface(ETOPO1)developed up to degree 2190(the maximum degree of the EGM2008 model)and a detailed elevation model(AW3D30).Computation was performed with the TC program of the GRAVSOFT package.The topography of the study area was assumed to have a constant density of 2670 kg/m3.For the inner and outer zones,the respective integration radii of 10 km and 200 km have been chosen.We obtained very important RTM values ranging from−53.59 to 34.79 mGal.These values were added to the gravity anomalies grid of the EGM2008 model to improve accuracy at high frequencies.On a part of the Cameroon Volcanic Line and its surroundings(mountainous area),we made a comparison between the residual Bouguer anomalies before and after refinement.We report differences ranging from−37.40 to 26.40 mGal.We conclude that the impact of omission error on gravimetric signatures is observed especially in areas with high variable topography,such as on the Cameroon Volcanic Line and around the localities of Takamanda,Essu,Dumbo,and Ngambe.This finding illustrates the great influence that topography has on accurate measurement of these gravity anomalies,and thus why topography must be taken into account.We can conclude that in preparing a global geopotential model,a high resolution DTM must be used to decrease the omission error:the degree of expansion has to increase in order to take the higher frequencies into account.The refined Bouguer anomalies grid presented here can be used in addition to terrestrial gravity anomalies in the study area,especially in mountainous areas where gravimetric data are very sparse or nonexistent.

Fatigue reliability based on residual strength model with hybrid uncertain parameters

The aim of this paper is to evaluate the fatigue reliability with hybrid uncertain parameters based on a residual strength model. By solving the non-probabilistic setbased reliability problem and analyzing the reliability with randomness, the fatigue reliability with hybrid parameters can be obtained. The presented hybrid model can adequately consider all uncertainties affecting the fatigue reliability with hybrid uncertain parameters. A comparison among the presented hybrid model, non-probabilistic set-theoretic model and the conventional random model is made through two typical numerical examples. The results show that the presented hybrid model, which can ensure structural security, is effective and practical.

An Application of the Modified Shear Lag Model to Study the Influence of Thermal Residual Stresses on the Stiffness and Yield Strength of Short Fiber Reinforced Metal Matrix Composites

The modified shear lag model proposed recently was applied to calculate thermal residual stresses and subsequent stress distributions under tensile and compressive loadings. The expressions for the elastic moduli and the yield strengths under tensile and compressive loadings were derived which take account of thermal residual stresses. The asymmetries in the elastic modulus and the yield strength were interpreted using the derived expressions and the obtained results of the stress calculations. The model predictions have exhibited good agreements with the experimental results and also with the other theoretical predictions

Bark-Band Residual Noise Model for Parametric Audio Coding

A Bark-band residual noise model integrated with the human hearing mechanism is proposed to efficiently complement sinusoidal model in parametric audio coding. The time-varying spectrum of the residual noise is retrieved by Bark-scale piecewise constant magnitude estimates along with random phases. In the proposed noise model, Bark bands information is obtained by short-time FFT method and window overlap-add technique is exploited to remove boundary discontinuities. SVQ is also incorporated into parameter quantization process for the low bit-rate coding demand. Simulation results and informal listening tests show that when the sinusoidal model is combined with the Bark-band noise model, better synthesis audio quality can be achieved compared with the original sinusoidal modeling audio codec.

Pricing Power of China's Cocoon and Silk Products in International Market:An Empirical Analysis Based on International Market Power

Do China＇s silk products only have advantage in number but no pricing power in international market？ In this paper, we used the residual demand elasticity model to estimate the international market power of China＇s silk products. The empirical results revealed that China＇s raw material products such as natural silk products and semi-finished products such as satin products had certain market power in the main export markets, but the finished silk products such as woman＇s blouse or shirts and shawls had no market power in the target markets including USA and Germany. The scale economy from resource endowment and great market share are the base of the international market power of natural silk products. The advantage from industry agglomeration and great market share are the source of the international market power of satin products. Technical bottlenecks and inefficiency in brand building are the cause of unobvious international market power of China＇s finished silk products, and the competition from Italy and France has increased the difficulty to enhance market power. In order to consolidate and improve the international market power of China＇s silk products, it is suggested to stabilize the production scale and strengthen industrial base, to speed up the resources integration and optimize the industrial distribution, to strengthen science and technology innovation and adjust product structure, to speed up the brand construction and enhance the influence of brand, and to enlarge the scale of organization and achieve scale economies.

Forecasting Gas Consumption Based on a Residual Auto-Regression Model and Kalman Filtering Algorithm

Consumption of clean energy has been increasing in China.Forecasting gas consumption is important to adjusting the energy consumption structure in the future.Based on historical data of gas consumption from 1980 to 2017,this paper presents a weight method of the inverse deviation of fitted value,and a combined forecast based on a residual auto-regression model and Kalman filtering algorithm is used to forecast gas consumption.Our results show that:(1)The combination forecast is of higher precision:the relative errors of the residual auto-regressive model,the Kalman filtering algorithm and the combination model are within the range(–0.08,0.09),(–0.09,0.32)and(–0.03,0.11),respectively.(2)The combination forecast is of greater stability:the variance of relative error of the residual auto-regressive model,the Kalman filtering algorithm and the combination model are 0.002,0.007 and 0.001,respectively.(3)Provided that other conditions are invariant,the predicted value of gas consumption in 2018 is 241.81×10~9 m^3.Compared to other time-series forecasting methods,this combined model is less restrictive,performs well and the result is more credible.

A unifying approach in simulating the shot peening process using a 3D random representative volume finite element model

Using a modified 3D random representative volume（RV）finite element model,the effects of model dimensions（impact region and interval between impact and representative regions）,model shapes（rectangular,square,and circular）,and peening-induced thermal softening on resultant critical quantities（residual stress,Almen intensity,coverage,and arc height）after shot peening are systematically examined.A new quantity,i.e.,the interval between impact and representative regions,is introduced and its optimal value is first determined to eliminate any boundary effect on shot peening results.Then,model dimensions are respectively assessed for all model shapes to reflect the actual shot peening process,based on which shape-independent critical shot peening quantities are obtained.Further,it is found that thermal softening of the target material due to shot peening leads to variances of the surface residual stress and arc height,demonstrating the necessity of considering the thermal effect in a constitutive material model of shot peeing.Our study clarifies some of the finite element modeling aspects and lays the ground for accurate modeling of the SP process.

Society's support for the aged in China:a cultural perspective

This article is concerned with the influence of welfare culture on society＇s old age support institutions and practice. It examines the development of old age support programs in contemporary China from a cultural perspective in an attempt to reveal the interaction between social welfare patterns for the elderly and social policy-makers＇ conception of social welfare and traditional social welfare culture. What stands in the way of the transition of Chinese social welfare for the elderly fi＇om a residual to an institutional model is a value system founded on restrictions and lack of awareness of civil fights. These factors limit the role of social welfare in narrowing the gaps between different social strata in the aged population and lead to inequitable welfare resource distribution. Although an aging population and the diffusion of welfare state culture are pushing the Chinese social welfare system toward diversified development, its final establishment still depends on a reexamination by the public and policy-makers of the relationship between individual citizens and the state.

STOCHASTIC VARIATIONAL INEQUALITY APPROACHES TO THE STOCHASTIC GENERALIZED NASH EQUILIBRIUM WITH SHARED CONSTRAINTS

In this paper,we consider the generalized Nash equilibrium with shared constraints in the stochastic environment,and we call it the stochastic generalized Nash equilibrium.The stochastic variational inequalities are employed to solve this kind of problems,and the expected residual minimization model and the conditional value-at-risk formulations defined by the residual function for the stochastic variational inequalities are discussed.We show the risk for different kinds of solutions for the stochastic generalized Nash equilibrium by the conditional value-at-risk formulations.The properties of the stochastic quadratic generalized Nash equilibrium are shown.The smoothing approximations for the expected residual minimization formulation and the conditional value-at-risk formulation are employed.Moreover,we establish the gradient consistency for the measurable smoothing functions and the integrable functions under some suitable conditions,and we also analyze the properties of the formulations.Numerical results for the applications arising from the electricity market model illustrate that the solutions for the stochastic generalized Nash equilibrium given by the ERM model have good properties,such as robustness,low risk and so on.

A New Complementarity Function and Applications in Stochastic Second-Order Cone Complementarity Problems

This paper considers the so-called expected residual minimization(ERM)formulation for stochastic second-order cone complementarity problems,which is based on a new complementarity function called termwise residual complementarity function associated with second-order cone.We show that the ERM model has bounded level sets under the stochastic weak R0-property.We further derive some error bound results under either the strong monotonicity or some kind of constraint qualifications.Then,we apply the Monte Carlo approximation techniques to solve the ERM model and establish a comprehensive convergence analysis.Furthermore,we report some numerical results on a stochastic second-order cone model for optimal power flow in radial networks.

XCO_2 satellite retrieval experiments in short-wave and infrared spectra with SCIATRAN model for Sahara Desert

The spectra of O_2 A-band(0.76 μm) and CO_2 near-infrared emissions(1.6 μm) are simulated by the SCIATRAN radiative transfer model(V3.1.23), and compared with those observed by GOSAT-FTS(Greenhouse gases Observing SATellite-Fourier Transform Spectrometer). Systematic deviations between the observed and simulated spectra are found to exist,especially for the O_2 A-band. The discrepancies are characterized by their mean differences averaged over the observed spectral ranges. A correction is applied to the observed GOSAT-FTS L1B(V141.141) spectra by scaling the spectral intensity measured by TANSO-FTS(Thermal and Near infrared Sensor for carbon Observation Fourier Transform Spectrometer) onboard GOSAT.The average columnar CO_2 concentrations(XCO_2) are retrieved from the observed and the corrected GOSAT-FTS spectra by using the SCIATRAN inversion algorithm. Compared with the GOSAT-FTS L2 XCO_2 data products retrieved from the observed spectra of GOSAT-FTS, the SCIATRAN retrievals from the corrected spectra show a much better agreement, with the relative error less than 1%. But the results of GOSAT TANSO-FTS(V161.160) show smaller residuals than GOSAT TANSO-FTS(V141.141) without mean residual correction. The results indicate that the mean residual correction would increase the precision of XCO_2 retrieval for spectra with systematic deviations.