Volume-averaged modeling of multiphase solidification with equiaxed crystal sedimentation in a steel ingot

Macrosegregation is a critical factor that limits the mechanical properties of materials.The impact of equiaxed crystal sedimentation on macrosegregation has been extensively studied,as it plays a significant role in determining the distribution of alloying elements and impurities within a material.To improve macrosegregation in steel connecting shafts,a multiphase solidification model that couples melt flow,heat transfer,microstructure evolution,and solute transport was established based on the volume-averaged Eulerian-Eulerian approach.In this model,the effects of liquid phase,equiaxed crystals,columnar dendrites,and columnar-to-equiaxed transition(CET)during solidification and evolution of microstructure can be considered simultaneously.The sedimentation of equiaxed crystals contributes to negative macrosegregation,where regions between columnar dendrites and equiaxed crystals undergo significant A-type positive macrosegregation due to the CET.Additionally,noticeable positive macrosegregation occurs in the area of final solidification in the ingot.The improvement in macrosegregation is beneficial for enhancing the mechanical properties of connecting shafts.To mitigate the thermal convection of molten steel resulting from excessive superheating,reducing the superheating during casting without employing external fields or altering the design of the ingot mold is indeed an effective approach to control macrosegregation.

Crystallization thermodynamics of 2,4(5)-dinitroimidazole in binary solvents

2,4(5)-Dinitroimidazole(2,4(5)-DNI)is an important organic intermediate,and itself can also be used for energetic material.In this work,the solubility of 2,4(5)-DNI in(methanol+water,acetonitrile+water,acetone+water)binary solvents were measured by using a dynamic test method from 278.15 K to 323.15 K under 101.1 k Pa.The Jouyban–Acree model,van't Hoff–Jouyban–Acree model,Apelblat–Jouyb an–Acree model,Ma model,and Sun model were used to correlate the experimental data.The values of relative average deviation(RAD)and root-mean-square deviation(RMSD)were very small,indicating that the error between the experimental value and the correlated value was very small.The thermodynamic parameters such as dissolution enthalpy,dissolution entropy and Gibbs energy were calculated based on solubility data.High-purity of 2,4(5)-DNI was efficiently obtained by using cooling and dilution crystallization method.

Morphology prediction of dihydroxylammonium 5,5'-bistetrazole-1,1'-diolate (TKX-50) crystal in different solvent systems using modified attachment energy model

In order to theoretically study the growth morphology of dihydroxylammonium 5,5’-bistetrazole-1,1’-dio late(TKX-50)crystal in different solvent systems,crystal–solvent models were established,and then molecular dynamics(MD)methods were adopted as a means to simulate particle motion.Modified attachment energy(MAE)model was employed to calculate the growth morphology of TKX-50.The simulation results demonstrate that COMPASS force field and RESP charge are suitable for molecular dynamics simulation of TKX-50.The morphologically dominant growth surfaces of TKX-50 in vacuum are(020),(011),(11–1),(100)and(120),respectively.In water(H_(2)O)and N,N-dimethylformamide(DMF)solvents,the(11–1)face is the largest in the habit face,the growth rate of(020)face becomes faster.With the increase of temperature,the aspect ratios of TKX-50 crystal in DMF solvent increase,and the areas of the(120)faces decrease.In ethylene glycol/H_(2)O mixed solvent system with volume ratio of 1/1,aspect ratio of TKX-50 is relatively small.In formic acid/H_(2)O mixed solvents with different volume ratios(1/4,1/3,1/2,1/1 and 2/1),aspect ratio of TKX-50 is relatively small when volume ratio is 1/2.

Experiments and model development of p-nitrochlorobenzene and naphthalene purification in a continuous tower melting crystallizer

With the increasing demand for high-purity products,the industrial application of melt crystallization technology has been highly concerned.In this study,the purification process of nitrochlorobenzene binary eutectic system(NBES)and naphthalene–benzothiophene solid solution system(NBSSS)in tower melting crystallizer is analyzed,and a mathematical model of crystallization process is established.The key parameters in terms of feed concentration,crystal bed height,reflux ratio and stirring speed effi-ciency on purification effects were discussed by the established model.The results show that the concentration of p-nitrochlorobenzene was purified from 90.85%to 99.99%,when the crystal bed height is 600 mm,the reflux ratio is 2.5,and the stirring speed is 12 rmin^(-1).The naphthalene concentration is purified from 95.89%to 99.99%,when the crystal bed height is 400 mm,the reflux ratio is 1.43,and the stirring speed is 16 rmin^(-1).The quality of the model is evaluated by the ARD(average relative deviation).The minimum ARD values of the NBES and NBSSS are 2.39%and 5.22%,respectively,indicating the model satisfactorily explains the purification process.

Effects of heavy metal ions Cu^(2+)/Pb^(2+)/Zn^(2+)on kinetic rate constants of struvite crystallization

Struvite(MAP)crystallization technology is widely used to treat ammonia nitrogen in waste effluents of its simple operation and good removal efficiency.However,the presence of heavy metal ions in the waste effluents causes problems such as slow crystallization rate and small crystal size,limiting the recovery rate and economic value of the MAP.The present study was conducted to investigate the effects of concentrations of three heavy metal ions(Cu^(2+),Zn^(2+),and Pb^(2+))on the crystal morphology,crystal size,average growth rate,and crystallization kinetics of MAP.A relationship was established between the kinetic rate constant Ktcalculated by the chemical gradient model and the concentrations of heavy metal ions.The results showed that low concentrations of heavy metal ions in the solution created pits on the MAP surface,and high level of heavy metal ions generated flocs on the MAP surface,which were composed of metal hydroxides,thus inhibiting crystal growth.The crystal size,average growth rate,MAP crystallization rate,and kinetic rate constant Ktdecreased with the increase in heavy metal ion concentration.Moreover,the Ktdemonstrated a linear relationship with the heavy metal concentration ln(C/C~*),which provided a reference for the optimization of the MAP crystallization process in the presence of heavy metal ions.

Towards a semi-empirical model of the sea ice thickness based on hyperspectral remote sensing in the Bohai Sea

Sea ice thickness is one of the most important input parameters for the prevention and mitigation of sea ice disasters and the prediction of local sea environments and climates. Estimating the sea ice thickness is currently the most important issue in the study of sea ice remote sensing. With the Bohai Sea as the study area, a semiempirical model of the sea ice thickness（SEMSIT） that can be used to estimate the thickness of first-year ice based on existing water depth estimation models and hyperspectral remote sensing data according to an optical radiative transfer process in sea ice is proposed. In the model, the absorption and scattering properties of sea ice in different bands（spectral dimension information） are utilized. An integrated attenuation coefficient at the pixel level is estimated using the height of the reflectance peak at 1 088 nm. In addition, the surface reflectance of sea ice at the pixel level is estimated using the 1 550–1 750 nm band reflectance. The model is used to estimate the sea ice thickness with Hyperion images. The first validation results suggest that the proposed model and parameterization scheme can effectively reduce the estimation error associated with the sea ice thickness that is caused by temporal and spatial heterogeneities in the integrated attenuation coefficient and sea ice surface. A practical semi-empirical model and parameterization scheme that may be feasible for the sea ice thickness estimation using hyperspectral remote sensing data are potentially provided.

Simulation of Gas Oil Hydrotreater Heat Exchange Tube and Crystallization Prediction of NH_(4)Cl by Thermodynamic Equilibrium

The hydrotreater system heat exchanger is one of the main pieces of heat exchange equipment in petrochemical enterprises.In recent years,oil resources have shown a deterioration trend of high sulfur and high acid content,with corrosion risk being prominent in oil processing.Taking the multi-medium flow corrosion risk of the hydrotreater heat exchanger pipeline in a petrochemical enterprise as the research object,based on the parameter characteristics of corrosive NH_(3) and HCl media under a high-temperature and high-pressure environment,the ammonium salt crystallization and deposition mechanism under multi-phase flow is revealed.The thermodynamic equilibrium curve is modified based on the thermodynamic principle and fugacity coefficient variation,and the prediction model of ammonium chloride crystallization in hydrotreater heat exchanger under high temperature and high pressure is constructed according to the modification.This study uses the mixture model,the flow-thermal coupling method,and the discrete phase model method to carry out the numerical simulation of multiphase flow and the numerical prediction of particle distribution characteristics in the heat exchanger pipeline of the hydrotreater heat exchange equipment,so as to realize the quantitative prediction of the particle crystallization deposition distribution in the pipeline.The results show that with the decrease of temperature,the crystallization occurs first on both sides of the center of the tube bundle,and more crystallization occurs in the lower half of the U-shaped tube,which may seriously lead to problems such as pipe blockage and under-deposit corrosion.

Comparative Study among Different Semi-Empirical Models for Soil Salinity Prediction in an Arid Environment Using OLI Landsat-8 Data

Salt-affected soils, caused by natural or human activities, are a common environmental hazard in semi-arid and arid landscapes. Excess salts in soils affect plant growth and production, soil and water quality and, therefore, increase soil erosion and land degradation. This research investigates the performance of five different semi-empirical predictive models for soil salinity spatial distribution mapping in arid environment using OLI sensor image data. This is the first attempt to test remote sensing based semi-empirical salinity predictive models in this area: the Kingdom of Bahrain. To achieve our objectives, OLI data were standardized from the atmosphere interferences, the sensor radiometric drift, and the topographic and geometric distortions. Then, the five semi-empirical predictive models based on the Normalized Difference Salinity Index (NDSI), the Salinity Index-ASTER (SI-ASTER), the Salinity Index-1 (SI-1), the Soil Salinity and Sodicity Index-1 and Index-2 (SSSI-1 and SSSI-2), developed for slight and moderate salinity in agricultural land, were implemented and applied to OLI image data. For validation purposes, a fieldwork was organized and different important spots-locations representing different salinity levels were visited, photographed, and localized using an accurate GPS (σ ≤ ±30 cm). Based on this a priori knowledge of the soil salinity, six validation sites were selected to reflect non-saline, low, moderate, high and extreme salinity classes, descriptive statistics extracted from polygons and/or transects over these sites were used. The obtained results showed that the models based on NDSI, SI-1 and SI-ASTER all failed to detect salinity bounds for both extreme salinity (Sabkhah) and non-saline conditions. In Fact, NDSI and SI-ASTER gave respectively only 35% dS/m and 25% dS/m in extreme salinity validation site, while SI-1 and SI-ASTER indicated 38% dS/m and 39% dS/m in non-saline validation site. Therefore, these three models were deemed inadequate for the study site. However, both SSSI-1 and SSSI-2 allowed a detection of the previous salinity bounds and furthermore described similarly and correctly the urban-vegetation areas and the open-land areas. Their predicted EC is around 10% dS/m for non-saline urban soil, about 25% dS/m for low salinity urban-vegetation soil, approximately 30% to 75% dS/m, respectively, for moderate to high salinity soils. SSSI-2 based semi-empirical salinity models was able to differentiate the high salinity versus extreme salinity in areas where both exist and was very accurate to highlight the pure salt where SSSI-1 has reach saturation for both salinity classes. In conclusion, reliable salinity map was produced using the model based on SSSI-2 and OLI sensor data that allows a better characterization of the soil salinity problem in an Arid Environment.

Description of martensitic transformation kinetics in Fe-C-X(X = Ni,Cr,Mn,Si) system by a modified model

Controlling the content of athermal martensite and retained austenite is important to improving the mechanical properties of high-strength steels,but a mechanism for the accurate description of martensitic transformation during the cooling process must be addressed.At present,frequently used semi-empirical kinetics models suffer from huge errors at the beginning of transformation,and most of them fail to exhibit the sigmoidal shape characteristic of transformation curves.To describe the martensitic transformation process accurately,based on the Magee model,we introduced the changes in the nucleation activation energy of martensite with temperature,which led to the varying nucleation rates of this model during martensitic transformation.According to the calculation results,the relative error of the modified model for the martensitic transformation kinetics curves of Fe-C-X(X = Ni,Cr,Mn,Si) alloys reached 9.5% compared with those measured via the thermal expansion method.The relative error was approximately reduced by two-thirds compared with that of the Magee model.The incorporation of nucleation activation energy into the kinetics model contributes to the improvement of its precision.

Applicability of Johnson-Mehl-Avrami model to crystallization kinetics of Zr_(60)Al_(15)Ni_(25) bulk amorphous alloy

The applicability of Johnson-Mehl-Avrami(JMA)model to the crystallization kinetics of Zr60Al15Ni25 bulk amorphous alloy is investigated by differential scanning calorimetry(DSC)under isochronal and isothermal conditions.A criterion xm,at which a defined function z(x)exhibits the maximum value,is introduced to check the validity of JMA model to the kinetics analysis.The value of xm has a constant of 0.632 for JMA model.It is found that the values of xm at different isothermal annealing temperatures(743,748,753 and 758 K)are almost near 0.632,which indicates that the isothermal crystallization kinetics can be modeled by JMA equation.However,the values of xm at different heating rates(10,20,30 and 40 K/min)are about 0.52,implying that JMA model is not valid to the isochronal crystallization kinetics.The reason why the JMA model is not valid to the isochronal crystallization kinetics is discussed.

Modelling of composite crystallization

Metal matrix composites(MMCs)have received much attention due to their promising advanced mechanical properties.The aim of this work is to create a micro-macro model of composite crystallization.The developed model is coupled with the process of heat flow in the macroscopic scale,resulting from the heat emission during the nucleation and the growth of grains.Taking into account both of these phenomena,the proposed model is distinguished by a good reflection of reality.Moreover,the presented model assumes that the function of grain density depends on the maximal supercooling and the mass volume of the reinforcement phase particles.The knowledge of the equations,describing the function of grain density depending on the degree of supercooling,is necessary in the,more and more often used,numerical modelling of the casting structure.

An improved semi-empirical friction model for gas-liquid two-phase flow in horizontal and near horizontal pipes

Pressure drop and liquid hold-up are two very important fluid flow parameters in design and control of multiphase flow pipelines.Friction factors play an important role in the accurate calculation of pressure drop.Various empirical and semi-empirical closure relations exist in the literature to calculate the liquid-wall,gas-wall and interfacial friction in two-phase pipe flow.However most of them are empirical correlations found under special experimental conditions.In this paper by modification of a friction model available in the literature,an improved semiempirical model is proposed.The proposed model is incorporated in the two-fluid correlations under equilibrium conditions and solved.Pressure gradient and velocity profiles are validated against experimental data.Using the improved model,the pressure gradient deviation from experiments diminishes by about 3%;the no-slip condition at the interface is satisfied and the velocity profile is predicted in better agreement with the experimental data.

Adaptive semi-empirical model for non-contact atomic force microscopy

Non-contact atomic force microscope is a powerful tool to investigate the surface topography with atomic resolution.Here we propose a new approach to estimate the interaction between its tips and samples,which combines a semi-empirical model with density functional theory(DFT)calculations.The generated frequency shift images are consistent with the experiment for mapping organic molecules using CuCO,Cu,CuCl,and CuO_(x)tips.This approach achieves accuracy close to DFT calculation with much lower computational cost.

Simulation of a DI Diesel Engine Performance Fuelled on Biodiesel Using a Semi-Empirical 0D Model

Diesel engines have proven over the years important in terms of efficiency and fuel consumption to power generation ratio. Many research works show the potential of biodiesel as a substitute for conventional gasoil. Mainly, previous and recent researches have focused on experimental investigation of diesel engine performance fuelled by biodiesel. Researches on the mathematical description of diesel engine process running on biodiesel are scarce, and mostly about chemical and thermodynamic description of the combustion process of biodiesel rather than performance studies. This work describes a numerical investigation on the performance analysis of a diesel engine fuelled by palm oil biodiesel. The numerical investigation was made using a semi empirical 0D model based on Wiebe’s and Watson’s model which was implemented via the open access numerical calculation software Scilab. The model was validated first by comparing with experimental pressure and performance data of a one cylinder engine at rated speed and secondly by comparing with a six cylinders engine performance data at various crankshaft rotational speeds. Simulations were then made to analyze the engine performance when running on biodiesel. The calculations were made at constant combustion duration and constant coefficient of excess air. Results showed that the model matches the overall experimental data, such as the power output and peak cylinder pressure. The ignition delay was somehow underestimated by the model for the first experiment, which caused a slight gap on in cylinder pressure curve, whereas it predicted the average ignition delay fairly well for the second set of validation. The simulations of engine performance when running on biodiesel confirmed results obtained in previous experimental researches on biodiesel. The model will be further investigated for engine control when shifting to biodiesel fuel.

Process Modeling for Batch Cooling Crystallization

The general mathematical model for batch cooling crystallization was established based on the population balance equation considering the change of slurry volume, and simulated with crystallization thermodynamics,kinetics and mass balance employing bed voidage. In the system of vitamin C-water-ethanol, reliability of this model was verified by comparison between simulation results and experimental data. The effects of operation parameters on product quality can be systematically investigated by modeling simulation.

Salt-Affected Soil Mapping in an Arid Environment Using Semi-Empirical Model and Landsat-OLI Data

The aim of this research is to map the salt-affected soil in an arid environment using an advanced semi-empirical predictive model, Operational Land Imager (OLI) data, a digital elevation model (DEM), field soil sampling, and laboratory and statistical analyses. To achieve our objectives, the OLI data were atmospherically corrected, radiometric sensor drift was calibrated, and distortions of topography and geometry were corrected using a DEM. Then, the soil salinity map was derived using a semi-empirical predictive model based on the Soil Salinity and Sodicity Index-2 (SSSI-2). The vegetation cover map was extracted from the Transformed Difference Vegetation Index (TDVI). In addition, accurate DEM of 5-m pixels was used to derive topographic attributes (elevation and slope). Visual comparisons and statistical validation of the semi-empirical model using ground truth were undertaken in order to test its capability in an arid environment for moderate and strong salinity mapping. To accomplish this step, fieldwork was organized and 120 soil samples were collected with various degrees of salinity, including non-saline soil samples. Each one was automatically labeled using a digital camera and an accurate global positioning system (GPS) survey (σ ≤ ± 30 cm) connected in real time to the geographic information system (GIS) database. Subsequently, in the laboratory, the major exchangeable cations (Ca2+, Mg2+, Na+, K+, Cl- and SO42-), pH and the electrical conductivity (EC-Lab) were extracted from a saturated soil paste, as well as the sodium adsorption ratio (SAR) being calculated. The EC-Lab, which is generally accepted as the most effective method for soil salinity quantification was used for statistical analysis and validation purposes. The obtained results demonstrated a very good conformity between the derived soil salinity map from OLI data and the ground truth, highlighting six major salinity classes: Extreme, very high, high, moderate, low and non-saline. The laboratory chemical analyses corroborate these results. Furthermore, the semi-empirical predictive model provides good global results in comparison to the ground truth and laboratory analysis (EC-Lab), with correlation coefficient (R2) of 0.97, an index of agreement (D) of 0.84 (p < 0.05), and low overall root mean square error (RMSE) of 11%. Moreover, we found that topographic attributes have a substantial impact on the spatial distribution of salinity. The areas at a relatively high altitude and with hard bedrock are less susceptible to salinity, while areas at a low altitude and slope (≤2%) composed of Quaternary soil are prone to it. In these low areas, the water table is very close to the surface (≤1 m), and the absence of an adequate drainage network contributes significantly to waterlogging. Consequently, the intrusion and emergence of seawater at the surface, coupled with high temperature and high evaporation rates, contribute extensively to the soil salinity in the study area.

A synthetic semi-empirical physical model of secondary electron yield of metals under E-beam irradiation

Calculations of secondary electron yield（SEY） by physical formula can hardly accord with experimental results precisely. Simplified descriptions of internal electron movements in the calculation and complex surface contamination states of real sample result in notable difference between simulations and experiments. In this paper, in order to calculate SEY of metal under complicated surface state accurately, we propose a synthetic semi-empirical physical model. The processes of excitation of internal secondary electron（SE） and movement toward surface can be simulated using this model.This model also takes into account the influences of incident angle and backscattering electrons as well as the surface gas contamination. In order to describe internal electronic states accurately, the penetration coefficient of incident electron is described as a function of material atom number. Directions of internal electrons are set to be uniform in each angle. The distribution of internal SEs is proposed by considering both the integration convergence and the cascade scattering process.In addition, according to the experiment data, relationship among desorption gas quantities, sample ultimate temperature and SEY is established. Comparing with experiment results, this synthetic semi-empirical physical model can describe the SEY of metal better than former formulas, especially in the aspect of surface contaminated states. The proposed synthetic semi-empirical physical model and presented results in this paper can be helpful for further studying SE emission, and offer an available method for estimating and taking advantage of SE emission accurately.

Improvement of Bare Soil Semi-Empirical Radar Backscattering Models (Oh and Dubois) with SAR Multi-Spectral Satellite Data (X-, C- and L-Bands)

The objective of this study is to improve the performance of semi-empirical radar backscatter models, which are mainly used in microwave remote sensing (Oh 1992, Oh 2004 and Dubois). The study is based on satellite and ground data collected on bare soil surfaces during the Multispectral Crop Monitoring experimental campaign of the CESBIO laboratory in 2010 over an agricultural region in southwestern France. The dataset covers a wide range of soil (viewing top soil moisture, surface roughness and texture) and satellite (at different frequencies: X-, C- and L-bands, and different incidence angles: 24.3° to 53.3°) configurations. The proposed methodology consists in identifying and correcting the residues of the models, depending on the surface properties (roughness, moisture, texture) and/or sensor characteristics (frequency, incidence angle). Finally, one model has been retained for each frequency domain. Results show that the enhancements of the models significantly increase the simulation performances. The coefficient of correlation increases of 23% in mean and the simulation errors (RMSE) are reduced to below 2 dB (at the X and C-bands) and to 1 dB at the L-band, compared to the initial models. At the X- and C-bands, the best performances of the modified models are provided by Dubois, whereas Oh 2004 is more suitable for the L-band (r is equal to 0.69, 0.65 and 0.85). Moreover, the modified models of Oh 1992 and 2004 and Dubois, developed in this study, offer a wider domain of validity than the initial formalism and increase the capabilities of retrieving the backscattering signal in view of applications of such approaches to stronglycontrasted agricultural surface states.

Unifying the crystallization behavior of hexagonal and square crystals with the phase-field-crystal model

By employing the phase-field-crystal models, the atomic crystallization process of hexagonal and square crystals is investigated with the emphasis on the growth mechanism and morphological change. A unified regime describing the crystallization behavior of both crystals is obtained with the thermodynamic driving force varying. By increasing the driving force,, both crystals （in the steady-state） transform from a faceted polygon to an apex-bulged polygon, and then into a symmetric dendrite. For the faceted polygon, the interface advances by a layer-by-layer （LL） mode while for the apex-bulged polygonal and the deridritic crystals, it first adopts the LL mode and then transits into the multi-layer （ML） mode in the later stage. In particular, a shift of the nucleation sites from the face center to the area around the crystal tips is detected in the early growth stage of both crystals and is rationalized in terms of the relation between the crystal size and the driving force distribution. Finally, a parameter characterizing the complex shape change of square crystal is introduced.