Computer prediction system on solid/solid reaction kinetics

A computer software system of kinetic predication of solid/solid reaction, KinPreSSR, was developed using Visual C ++ and FoxPro. It includes two main modules, REACTION and DIFFUSION. KinPreSSR deals with the kinetics on the diffusion in solids as well as solid/solid reactions. The REACTION module in KinPreSSR was mainly described, which has organized the commonly recognized kinetic models, parameters, and employed both numerical and graphical methods for data analyses. The proper combination between the kinetic contents and the analytical methods enables users to use KinPreSSR for the evaluation and prediction of solid/solid reactions interested. As an example to show some of functions of KinPreSSR, the kinetics analysis for the reaction between SrCO 3 and TiO 2 powders to form SrTiO 3 with a series of kinetic data from isothermal measurements was demonstrated. [

Application of multi-component joint inversion in oil and gas exploration:A case study of reservoir and gas saturation prediction of the Xujiahe formation in the PLN area of the central Sichuan Basin

Multi-component seismic exploration is an important technique in the utilization of P-waves and converted S-waves for oil and gas exploration.It has unique advantages in the structural imaging of gas zones,reservoir prediction,lithology,and gas-water identifi cation,and the development direction and degree of fractures.Multi-component joint inversion is one of the most important steps in multi-component exploration.In this paper,starting from the basic principle of multi-component joint inversion,the diff erences between the method and single P-wave inversion are introduced.Next,the technique is applied to the PLN area of the Sichuan Basin,and the P-wave impedance,S-wave impedance,and density are obtained based on multi-component joint inversion.Through the velocity and lithology,porosity,and gas saturation fi tting formulas,prediction results are calculated,and the results are analyzed.Finally,multi-component joint inversion and single P-wave inversion are compared in eff ective reservoir prediction.The results show that multi-component joint inversion increases the constraints on the inversion conditions,reduces the multi-solution of a single P-wave inversion,and is more objective and reliable for the identification of reservoirs,effectively improving the accuracy of oil and gas reservoir prediction and development.

Predicting gas-bearing distribution using DNN based on multi-component seismic data: Quality evaluation using structural and fracture factors

The tight-fractured gas reservoir of the Upper Triassic Xujiahe Formation in the Western Sichuan Depression has low porosity and permeability. This study presents a DNN-based method for identifying gas-bearing strata in tight sandstone. First, multi-component composite seismic attributes are obtained.The strong nonlinear relationships between multi-component composite attributes and gas-bearing reservoirs can be constrained through a DNN. Therefore, we identify and predict the gas-bearing strata using a DNN. Then, sample data are fed into the DNN for training and testing. After optimized network parameters are determined by the performance curves and empirical formulas, the best deep learning gas-bearing prediction model is determined. The composite seismic attributes can then be fed into the model to extrapolate the hydrocarbon-bearing characteristics from known drilling areas to the entire region for predicting the gas reservoir distribution. Finally, we assess the proposed method in terms of the structure and fracture characteristics and predict favorable exploration areas for identifying gas reservoirs.

Kinetic method for enzymatic analysis by predicting background with uricase reaction as model

Objective：To investigate the reliability for kinetic assay of substance with background predicted by the integrated method using uricase reaction as model. Methods： Absorbance before uricase action （Δ0） was estimated by extrapolation with given lag time of steady-state reaction. With Km fixed at 12.5μmol/L, background absorbance （Δb） was predicted by nonlinearly fitting integrated Michaelis-Menten equation to Candida utilis uricase reaction curve. Uric acid in reaction solution was determined by the difference （ΔA） between Δ0 and Δb. Results .Ab usually showed deviation 〈3% from direct assay with residual substrate done fifth of initial substrate for analysis. ΔA showed CV 〈5% with resistance to common interferences except xanthine, and it linearly responded to uric acid with slope consistent to the absorptivity of uric acid. The lower limit was 2.0 μmol/L and upper limit reached 30 μmol/L in reaction solution with data monitored within 8 min reaction at 0. 015 U/ml uricase. Preliminary application to serum and urine gave better precision than the direct equilibrium method without the removal of proteins before analysis. Conclusion .This kinetic method with background predicted by the integrated method was reliable for enzymatic analysis, and it showed resistance to common interferences and enhanced efficiency at much lower cost.

On-treatment predictions of success in peg-interferon/ribavirin treatment using a novel formula

AIM:To predict treatment success using only simple clinical data from peg-interferon plus ribavirin therapy for chronic hepatitis C. METHODS:We analyzed the clinical data of 176 patients with chronic hepatitis and hepatitis C virus genotype 1 who received 48 wk standard therapy, derived a predictive formula to assess a sustained virological response of the individual patient using a logistic regression model and confirmed the validity of this formula.The formula was constructed using data from the first 100 patients enrolled and validated using data from the remaining 76 patients. RESULTS:Sustained virological response was obtained in 83(47.2%)of the patients and we derived formulae to predict sustained virological response at pretreatment and weeks 4,12 and 24.The likelihood of sustained virological response could be predicted effectively bythe formulae at weeks 4,12 and 24(the area under the curve of the receiver operating characteristic:0.821, 0.802,and 0.891,respectively),but not at baseline (0.570).The formula at week 48 was also constructed and validation by test data achieved good prediction with 0.871 of the area under the curve of the receiver operating characteristic.Prediction by this formula was always superior to that by viral kinetics. CONCLUSION:These results suggested that our formula combined with viral kinetics provides a clear direction of therapy for each patient and enables the best tailored treatment.

Synthesis, characterization of monodispersed MgO microspheres and thermal decomposition kinetics of its precusor

Monodispersed MgO microspheres were successfully synthesized by a simple solvothermal method using PEG-400 as solvent. The samples were characterized by X-ray diffraction(XRD) and scanning electron microscopy(SEM). The results reveal that the precusor was monoclinic Mg5(CO3)4(OH)2·4H2O and composed of nanosheets with the thickness of about 250 nm. By calcining the precusor at 500 °C for 5 min, cubic MgO with similar morphology was obtained. According to the SEM images, it is found that the volume ratio of PEG-400 to deionized water is considered as a crucial factor in the evolution of the morphology. Based on the SEM images obtained under different experimental conditions, a possible growth mechanism which involves self-assembly process was proposed. The thermal decomposition process of MgO precusor was studied by thermogravimetry-differential thermogravimetry(TG-DTG) at different heating rates in air. Thermal analysis kinetics results show that the most probale mechanism models of MgO precusor are An and D3, respectively. In addition, isothermal prediction was studied to quantitatively characterize the thermal decomposition process.

A kinetic model for predicting shelf-life of fresh extruded rice-shaped kernels(FER)

Fresh extruded rice-shaped kernels(FER) are remoulded rice products from cereals or seed flours, which have the advantages of safety, nutrition, health and time saving. However, the finished products are easy to react with oxygen, so it is necessary to develop a fast, simple and reliable approach to monitor and predict the shelf-life of FER. A comprehensive mathematical model of FER shelf-life prediction was developed using a dynamic modelling approach based on real supply chain conditions. This predictive model was developed to determine four key indexes including acid value, iodine blue value, water uptake ratio and peroxide value. The results showed that when the peroxide value was 1.6849, the FER lost its edible value, nutritional value and commodity value. Moreover, the acid value and peroxide value of FER were used to establish a first-order kinetic model, and the iodine blue value of FER was suited for a zero-order kinetic model. The validation experiment of predicted and measured shelf life showed that the relative error was 3.12%, which was less than 5%. Therefore, this kinetic model could be used to predict the shelf-life of FER quickly and conveniently. The kinetic-based shelf-life prediction model proposed in this study is rapid and practical, providing theoretical basis and guidance for the establishment of quality monitoring and quality evaluation systems of FER during the production, storage, transport and marketing.

A coupled model of temperature and pressure based on hydration kinetics during well cementing in deep water

Considering the complicated interactions between temperature,pressure and hydration reaction of cement,a coupled model of temperature and pressure based on hydration kinetics during deep-water well cementing was established.The differential method was used to do the coupled numerical calculation,and the calculation results were compared with experimental and field data to verify the accuracy of the model.When the interactions between temperature,pressure and hydration reaction are considered,the calculation accuracy of the model proposed is within 5.6%,which can meet the engineering requirements.A series of numerical simulation was conducted to find out the variation pattern of temperature,pressure and hydration degree during the cement curing.The research results show that cement temperature increases dramatically as a result of the heat of cement hydration.With the development of cement gel strength,the pore pressure of cement slurry decreases gradually to even lower than the formation pressure,causing gas channeling;the transient temperature and pressure have an impact on the rate of cement hydration reaction,so cement slurry in the deeper part of wellbore has a higher rate of hydration rate as a result of the high temperature and pressure.For well cementing in deep water regions,the low temperature around seabed would slow the rate of cement hydration and thus prolong the cementing cycle.

基于BP神经网络的陈皮干燥含水率预测

为探索陈皮的热泵干燥特性,并实现热泵干燥过程中陈皮的含水率预测,研究了不同干燥温度(50、55、60℃)、干燥风速(1.0、2.0、3.0m/s)、堆叠厚度(20、30、40mm)对陈皮干燥时间和干燥速率的影响。将干燥温度、干燥风速、堆叠厚度和干燥时间作为输入层,隐藏层个数为10,陈皮的干燥含水率为输出层,搭建一个BP神经网络预测模型。研究结果表明:干燥温度、干燥风速和堆叠厚度都是影响陈皮干燥含水率的重要因素,提高干燥温度、增加干燥风速和减少堆叠厚度能够提高陈皮的干燥速率,缩短干燥时间。基于陈皮热泵干燥特性构建结构为“4-10-1”的BP神经网络模型,含水率预测值与实测值之间的均方误差MSE为0.00421,决定系数R^(2)=0.997,模型运行稳定,含水率预测结果准确且快速,能够为陈皮干燥过程中的含水率在线预测提供科学依据。

ESP工艺下DP600热轧双相钢铁素体相变模型

为了建立ESP工艺条件下DP600热轧双相钢的铁素体相变动力学数学模型,采用动态相变膨胀仪对实验钢分别进行等温相变和连续冷却相变实验.基于实测的铁素体相变孕育期和铁素体体积分数,在变形温度以上结合经典形核理论计算铁素体相变孕育期,变形温度以下通过实验数据拟合△GV计算铁素体相变孕育期.考虑冷却速度的影响对可加性法则进行修正并基于此计算了连续冷却条件下的铁素体相变开始温度和体积分数.结果表明:修正后的相变模型计算的铁素体相变开始温度和体积分数与实测值吻合良好,可用于预测ESP工艺下DP600钢的铁素体相变行为.

计及风力发电机转速安全约束的DFIG一次调频模型预测控制策略

针对传统方法控制双馈感应发电机(DFIG)的调频效果过于依赖参数整定的问题,该文提出了一种基于模型预测控制(MPC),计及转速安全约束的风力发电机参与一次调频控制策略。该方法结合风力发电机动力学模型与频率响应模型建立预测模型,通过线性回归方法变参考值将风力发电机转速的稳定性纳入考虑。相较于虚拟惯性控制等方法将系统频率偏差与转子动能直接关联,该文方法通过建立全新的预测模型,实时统筹考虑整个系统的状态信息,无需反复调整参数,在考虑转速安全性的同时兼顾全局性能。最后,通过实际算例分析验证了该文调频策略的有效性以及相对现有方法的优越性。

温度对黑皮鸡枞菌贮藏品质的影响及货架期的预测模型

本试验模拟了黑皮鸡枞菌(Oudemansiella raphanipies)采后贮藏流通的三种温度(2、4、8℃),并测定了黑皮鸡枞菌贮藏期间感官评分、腐烂指数、质量损失率、白度、可溶性蛋白含量、丙二醛含量、多酚氧化酶活性、过氧化物酶活性、超氧化物歧化酶活性、抗坏血酸和还原糖含量等理化指标。结果表明,2℃低温贮藏能更有效降低子实体质量损失率、丙二醛含量及过氧化物酶和多酚氧化酶活性,维持子实体白度和可溶性蛋白、还原糖、抗坏血酸含量以及超氧化物歧化酶活性,对黑皮鸡枞菌的保鲜有积极作用。使用ASLT方法,结合动力学模型和Arrhenius方程,建立了基于腐烂指数、质量损失率、白度、抗坏血酸含量的货架期预测模型,决定系数R2均大于0.90,模型拟合精度高且预测误差均小于10%,其中以质量损失率预测货架期具最高精度。用此模型能够方便快捷地预测黑皮鸡枞菌在采后某一时期的剩余货架期,可为食用菌采后贮藏流通控制提供理论依据。

山核桃油在贮藏期间的品质变化规律及货架期预测

为了对山核桃油产品流转过程中的品质控制提供理论基础,探究山核桃油在贮藏期间的品质变化规律及其货架期预测方法。对在5、20、35℃下贮藏的山核桃油进行感官评定,测定其酸值、过氧化值,并进行动力学分析,应用Arrhenius方程进行拟合,建立货架期预测模型。结果表明:山核桃油感官品质与酸值、过氧化值呈极强的相关性,随着贮藏时间的延长和温度的升高,山核桃油感官品质下降,酸值和过氧化值升高,且温度越高酸值和过氧化值的变化速率越快,过氧化值变化速率小于酸值;酸值和过氧化值的变化规律均符合一级反应动力学模型,建立的山核桃油货架期预测模型准确率在±10%以内。山核桃油在贮藏期间品质下降,通过酸值、过氧化值可较为准确地对5~35℃条件下贮藏的山核桃油货架期进行预测。

Prediction of bedload transport inside vegetation canopies with natural morphology

Due to vegetation drag and vegetation-generated turbulence,bedload transport in vegetated channels is more complicated than that in nonvegetated channels.It is challenging to obtain accurate predictions of bedload transport in vegetated channels.Previous studies generally used rigid circular cylinders to simulate vegetation,and the impact of plant morphology on bedload transport was typically ignored;these methods deviate from natural scenarios,resulting in prediction errors in transport rates of more than an order of magnitude.This study measured bedload transport rates inside P.australis,A.calamus and T.latifolia canopies and in arrays of rigid cylinders for comparison.The impact of plant morphology on bedload transport in vegetated channels was examined.Inside the canopies of natural morphology,the primary factor driving bedload transport is the near-bed turbulent kinetic energy(TKE),which consists of both bed-generated and vegetation-generated turbulence.A method was proposed to predict the near-bed TKE inside canopies with natural morphology.For the same solid volume fraction of plants,the transport rate inside canopies with a natural morphology is greater than or equal to that within an array of rigid cylinders,depending on the plant shape.This finding indicates that plant morphology has a significant impact on transport rates in vegetated regions and cannot be ignored,which is typical in practice.Four classic bedload transport equations(the Meyer-Peter-Müller,Einstein,Engelund and Dou equations),which are suitable for bare channels(no vegetation),were modified in terms of the near-bed TKE.The predicted near-bed TKE was inserted into these four equations to predict the transport rate in canopies with natural morphology.A comparison of the predictions indicated that the Meyer-Peter-Müller equation had the highest accuracy in predicting the transport rate in vegetated landscapes.

柴油加氢脱氮集总动力学模型及应用

采用气相色谱-质谱(GC-MS)对柴油加氢过程中含氮化合物的类型进行识别,结合含氮化合物在氮化学发光检测器(NCD)上的保留及响应特性,得到不同工艺条件下含氮化合物的类型分布。基于咔唑侧链甲基数的不同,建立了包含反应温度、反应压力、液时空速、氢/油体积比以及杂质含量(硫化氢、碱性氮化物和非碱性氮化物)等影响因素的五集总Langmuir-Hinshelwood加氢脱氮(HDN)动力学模型;模型采用Levenberg-Marquardt方法求解,验证结果表明拟合值与实验值相吻合。动力学模型可用于HDN过程工艺条件的优化,结果表明,当反应温度为350℃、反应压力为6.4 MPa和氢/油体积比为300条件下,氮化物的脱除效果最优。

预测典型变形高温合金均匀化动力学的新模型

提出一种基于扩散距离概念的变形高温合金均匀化动力学新预测模型。通过定量电子探针(EPMA)分析,系统研究典型镍基变形高温合金(GH4141)的微观偏析和均匀化动力学。研究发现,基于残余偏析指数模型预测的均匀化动力学与实际测量结果之间存在一定差异。实验和理论分析均表明,考虑了过去通常被忽略的扩散方向因子的一维扩散距离模型可以合理地预测均化动力学。新模型在只需知道原始枝晶臂间距和扩散系数前提下即可完成预测计算,这为变形高温合金均匀化动力学预测提供了一种新的选择。

不同贮藏温度下鲜百合关键质量属性研究及保质期预测

目的探究不同储藏温度对兰州百合鲜品关键质量属性的影响,并建立保质期预测模型。方法选取大小均匀的兰州百合鳞茎片,分别在4、25和37℃下储藏。考察外观性状、水分含量、水分活度和微生物含量的变化,利用动力学模型和微生物生长模型进行保质期预测。结果鲜百合的感官品质、水分含量和水分活度均随贮藏时间延长而下降。水分含量和水分活度指标关于Arrhenius方程的线性拟合系数R^(2)均大于0.99。此外,微生物一级模型线性拟合精度较高,能够准确预测贮藏过程中细菌生长趋势及数量变化。结论基于水分含量、水分活度和微生物总数构建的预测模型均可用于鲜百合保质期准确预测。此研究为鲜百合采后品质和保质期的研究提供了参考依据,并对鲜百合的生产、贮藏和运输具有重要的实践指导意义。

非肌层浸润性膀胱癌患者膀胱肿瘤等离子电切术后复发的预测模型构建

目的构建一个预测非肌层浸润性膀胱癌患者接受膀胱肿瘤等离子电切术后复发风险的预测模型,帮助临床医生进行个体化的风险评估和管理。方法回顾性分析2015年3月至2019年3月间于苏州市立医院收治的非肌层浸润性膀胱癌患者106例,统计以上患者一般临床资料,包括年龄、性别、吸烟史、糖尿病史、心血管疾病史、高血压史、肿瘤数目、直径、分级、体质指数(BMI)、预后营养指数(PNI)、白蛋白(ALB)、淋巴细胞计数(LYM)、血小板计数(PLT)、血小板分布宽(PDW)、平均血小板体积(MPV)水平等。基于上述患者一般临床资料与患者术后是否复发绘制相关连续变量受试者工作特征曲线(ROC曲线),根据具有显著性的影响因素的最佳截断值进行二分类分组,绘制非肌层浸润性膀胱癌患者术后复发的生存曲线。采用Cox比例风险回归分析非肌层浸润性膀胱癌患者术后复发独立危险因素,并根据分析结果构建Nomogram预测模型。对预测模型进行内部验证及决策曲线分析。结果相关连续变量ROC曲线分析显示PNI、肿瘤直径、组织分级、PLT、MPV、膀胱癌抗原4(BLCA-4)、膀胱肿瘤抗原(BTA)、核基质蛋白22(NMP22)、癌胚抗原(CEA)的AUC面积分别为:0.965、0.636、0.687、0.994、0.670、0.997、0.995、0.632、0.872。最佳截断值分别为40.50%、2.49 cm、—、251.50×10^(9)/L、12.55 fL、143.03 ng/mg、7.32 U/mg、6.99μg/mg、1.96 ng/mg。Cox单因素分析显示,PNI、肿瘤直径、组织分级、PLT、MPV、BLCA-4、BTA、CEA为独立危险因素(P<0.05)。Cox回归多因素分析显示PNI、肿瘤直径、组织分级、PLT、MPV、BLCA-4、BTA、NMP22、CEA为术后复发危险因素(P<0.05)。验证结果显示Nomogram预测模型预测效果良好。结论非肌层浸润性膀胱癌患者术后复发风险的预测模型准确性高,具有良好的临床应用潜力,可以为膀胱癌患者的个体化管理和后续治疗提供重要的决策支持。

统一动力学三维分区模型预测含能材料的晶体生长

为了研究黑索今(RDX)、奥克托今(HMX)和六硝基茋(HNS)晶体的形貌特征,采用了统一动力学三维分区方法对这3种含能材料晶体的实时生长形貌进行了模拟,研究了结晶生长条件对晶体外形和晶面拓扑结构的影响。研究结果表明,RDX预测的晶形呈现类菱形,主要晶面包括(010)、(100)和(110)面;HMX晶体呈柱状,主要晶面包括(011)、(010)和(11−1)面;而HNS晶体呈薄片状,其中(100)面的显露面积最大,所预测的含能材料晶体外形与实验结果吻合。当RDX、HMX和HNS晶体呈现二维成核和外延生长模式时,较高的驱动力(Δμ=418.59 kJ·mol^(−1))导致晶体的分子层不断堆叠,呈现分层生长;而温度较低时,生长单元首先附着在晶面平台区域,逐渐形成“岛状”集聚,随后进行外延生长;当晶面足够大时,可能出现多个大小不同的“岛状”结构,并随时间增长逐渐合并。在较低驱动力下(Δμ=27.21 kJ·mol^(−1)),HNS晶体呈现螺旋位错生长,其中(100)晶面通过一个螺旋轴引发片层生长,形成“梯田”型晶面。通过附着能力分析发现,螺旋的扭结位和台阶面具有较强的吸附能力,而平台上的位点吸附能力较弱。

新街台格庙矿区首采井田矿井水水化学特征及数值模拟预测

基于内蒙古新街台格庙矿区首采井田中地下水和岩石样品取样分析,探讨了矿区充水含水层水化学特征及空间分布规律,并利用地下水模型系统(GMS)软件对矿井水中典型水化学组分进行了预测。研究结果表明,新街台格庙矿区首采井田充水含水层为直罗组延安组,地下水阳离子以钠离子为主,组分平均含量为906.4 mg/L;阴离子以硫酸根为主,其含量均值为2289.3 mg/L。直罗组延安组砂岩去离子水反应使得pH值增加,逐渐趋于碱性,且离子组分浓度逐渐增大,其中阳离子中增幅较大的为钙离子和钠离子。阴离子中增幅较大的为重碳酸根离子和硫酸根离子,最终水化学类型为SO_(4)·HCO_(3)Ca·Na型。通过模型预测了台格庙矿区首采井田矿井水涌水水质,阳离子包括钾离子、钠离子、钙离子和镁离子,浓度分别为3.2~15.8、385~765、143.6~194.5、30.5~45.5 mg/L;阴离子包括硫酸根离子和氯离子,浓度范围分别为1170~1900、82.07~91.08 mg/L。