Effect of FeSi additive in dual-chamber sample cup on thermal analysis characteristic values and vermiculating rate of compacted graphite iron

Thermal analysis plays a key role in the online inspection of molten iron quality.Different solidification process of molten iron can be reflected by thermal analysis curves,and silicon is one of important elements affecting the solidification of molten iron.In this study,FeSi75 was added in one chamber of the dual-chamber sample cup,and the influences of FeSi75 additive on the characteristic values of thermal analysis curves and vermiculating rate were investigated.The results show that with the increase of FeSi75,the start temperature of austenite formation TALfirstly decreases and then increases,but the start temperature of eutectic growth TSEF,the lowest eutectic temperature TEU,temperature at maximum eutectic reaction rate TEM,and highest eutectic temperature TERkeep always an increase.The temperature at final solidification point TEShas little change.The FeSi75 additive has different influences on the vermiculating rate of molten iron with different vermiculation,and the vermiculating rate increases for lower vermiculation molten iron while decreases for higher one.According to the thermal analysis curves obtained by a dual-chamber sample cup with 0.30wt.%FeSi75 additive in one chamber,the vermiculating rate of molten iron can be evaluated by comparing the characteristic values of these curves.The time differenceΔtERcorresponding to the highest eutectic temperature TERhas a closer relationship with the vermiculating rate,and a parabolic regression curve between the time differenceΔtERand vermiculating rateηhas been obtained within the range of 65%to 95%,which is suitable for the qualified melt.

Feasibility of measuring moisture content of green sand by a low frequency multiprobe detector based on dielectric characteristics

Green sand is a mixture of silica sand,bentonite,water and coal powder,and other additives.Moisture content is an important index to characterize the properties of green sand.Based on the dielectric characteristics of green sand and transmission line theory,a method for rapidly measuring the moisture content of green sand by means of a low frequency multiprobe detector was proposed.A system was constructed,where six detectors with different arrangements and probes were designed.The experimental results showed that the voltage difference of transmission line increases with the increasing frequency before 29 MHz while decreases after 35 MHz.A voltage difference platform occurs in the range of 29-35 MHz,which is suitable for measuring the moisture content due to its insensitivity to frequency.The electric field intensity gradually decreases with the increase of the probe depth,and the intensity of central probe is always greater than that of the edge probe.When the distance of the probe away from the sand sample surface is 80 mm,the electric field intensity of the edge probe is found to be very weak.The optimal excitation frequency for measuring the moisture content of green sand is 29-33 MHz.The optimal detector is the one with one center probe and three edge probes,and their lengths are 80 mm and 60 mm,respectively.The distance between the center and edge probes is 25 mm,and the diameter of probes is 5 mm.Taking the voltage difference of transmission line,bentonite content,coal powder content and compactability as parameters of the input layer,and the moisture content as a parameter of the output layer,a three-layer BP artificial neural network model for predicting the moisture content of green sand was constructed according to the experimental results at 33 MHz.The prediction error of the model is not higher than 3.3% when the moisture content of green sand is within the range of 3wt.%-7wt.%.

Effect of printing parameters on properties of 3D printing sand samples

Three-dimensional sand printing(3DSP)is widely applied in sand mold fabrication.In this study,the effects of printing parameters including the resolution of printehead holes,activator content,layer thickness,and recoating speed on the tensile and bending strengths,gas evolution,and loss-on-ignition(LOI)of 3DSP samples were investigated by changing single parameter,and the dimension deviation was also measured.As the resolution increases,the tensile strength,bending strength,gas evolution,LOI,and deviations at X-and Y-axis directions decrease gradually while the deviation at Z-axis direction firstly increases and then deceases.The gas evolution and LOI drops by 13.02%and 8.13%respectively,but the strength only reduces by 2.2% when the resolution increases from 0.08 mm to 0.09 mm.The strengths of samples rise at first and then decline while the gas evolution and LOI rise gradually with the increasing activator content or recoating speed.The activator content is found to have little effect on the gas evolution as the activator increases from 0.14%to 0.34%,the gas evolution is increased by 7.3%which is far less than the LOI increment of 24.1%.As the layer thickness increases,the tensile and bending strengths firstly rise and then drop while gas evolution and LOI descend.Under the optimal printing parameters of 0.09 mm resolution,0.18%activator,-10.28 mm layer thickness and 160 mm·s^(-1) recoating speed,the tensile strengths for X-sample and Y-sample are 1.48 MPa and 1.37 MPa,the bending strengths are 1.84 MPa and 1.75 MPa,the gas evolution and LOI are-19.62 mL·g^(-1) and 1.92%,respectively.

Acoustic-electrical properties and rock physics models for shale-oil formations:prediction of reservoir properties of interbedded sandstone and shale layers

In recent years,the Yanchang shale-oil formations of the Ordos Basin are rich in reserves with complex lithology and structure characteristics,low porosity and low permeability,and weak anomalies for oil and water discriminations,have been the key targets of unconventional oil/gas resource exploration and development in the relevant areas.The joint acoustic-electrical(AE)properties can be used to interpret reservoir lithology,mineralogy,pore structure,and fluid saturation.To conduct tests of thin section analysis,X-ray diff raction,and ultrasonic and electrical experiments at diff erent pressures and saturation degrees,cores from the shale-oil formations in the Q area of the basin are collected.The variations in AE properties with respect to clay content,porosity,pressure(microfracture),and saturation are analyzed.The experimental results indicate that the rock physics behaviors of sandstones with diff erent clay contents vary significantly.The AE properties of clean sandstones are basically dependent on the microfractures(pressure),while for muddy sandstones,the clay content is an important factor affecting the responses.The target reservoir consists of interbedded sandstone and shale layers.The AE equivalent medium equations and the Gurevich theory are applied to establish the joint models for the diff erent lithologies and simulate the variations in AE properties with respect to fluid type,pore structure,and mineral components.The three-dimensional joint templates of clean and muddy sandstones,as well as shale,are developed based on the elastic and electrical attributes and then calibrated using the experimental and well-log data.The reservoir properties are estimated with the templates and validated by the log data.The results indicate that the joint templates based on lithology characteristics can eff ectively characterize the properties of interbedded sandstone and shale layers.Furthermore,the combined application of AE data provides more beneficial information for the assessment of rock properties,leading to precise estimates that conform with the actual formation conditions.

Recent progress on Sn_(3)O_(4)nanomaterials for photocatalytic applications

Tin(IV)oxide(Sn_(3)O_(4))is layered tin and exhibits mixed valence states.It has emerged as a highly promising visible-light pho-tocatalyst,attracting considerable attention.This comprehensive review is aimed at providing a detailed overview of the latest advance-ments in research,applications,advantages,and challenges associated with Sn_(3)O_(4)photocatalytic nanomaterials.The fundamental con-cepts and principles of Sn_(3)O_(4)are introduced.Sn_(3)O_(4)possesses a unique crystal structure and optoelectronic properties that allow it to ab-sorb visible light efficiently and generate photoexcited charge carriers that drive photocatalytic reactions.Subsequently,strategies for the control and improved performance of Sn_(3)O_(4)photocatalytic nanomaterials are discussed.Morphology control,ion doping,and hetero-structure construction are widely employed in the optimization of the photocatalytic performance of Sn_(3)O_(4)materials.The effective imple-mentation of these strategies improves the photocatalytic activity and stability of Sn_(3)O_(4)nanomaterials.Furthermore,the review explores the diverse applications of Sn_(3)O_(4)photocatalytic nanomaterials in various fields,such as photocatalytic degradation,photocatalytic hydro-gen production,photocatalytic reduction of carbon dioxide,solar cells,photocatalytic sterilization,and optoelectronic sensors.The discus-sion focuses on the potential of Sn_(3)O_(4)-based nanomaterials in these applications,highlighting their unique attributes and functionalities.Finally,the review provides an outlook on the future development directions in the field and offers guidance for the exploration and de-velopment of novel and efficient Sn_(3)O_(4)-based nanomaterials.Through the identification of emerging research areas and potential avenues for improvement,this review aims to stimulate further advancements in Sn_(3)O_(4)-based photocatalysis and facilitate the translation of this promising technology into practical applications.

The Asymptotic Study of Smooth Entropy Support Vector Regression

In this paper, a novel formulation, smooth entropy support vector regression (SESVR), is proposed, which is a smooth unconstrained optimization reformulation of the traditional linear programming associated with an ε-insensitive support vector regression. An entropy penalty function is substituted for the plus function to make the objective function con- tinuous ,and a new algorithm involving the Newton-Armijo algorithm proposed to solve the SESVR converge globally to the solution. Theoretically, we give a brief convergence proof to our algorithm. The advantages of our presented algorithm are that we only need to solve a system of linear equations iteratively instead of solving a convex quadratic program, as is the case with a conventional SVR, and lessen the influence of the penalty parameter C in our model. In order to show the efficiency of our algorithm, we employ it to forecast an actual electricity power short-term load. The experimental results show that the presented algorithm, SESVR, plays better precisely and effectively than SVMlight and LIBSVR in stochastic time series forecasting.