第43卷第3期2024年3月硅㊀酸㊀盐㊀通㊀报BULLETIN OF THE CHINESE CERAMIC SOCIETY Vol.43㊀No.3March,2024FactSage 热力学计算在耐火材料抗渣侵蚀性中的应用郭伟杰1,2,朱天彬1,2,李亚伟1,2,廖㊀宁1,2,桑绍柏1,2,徐义彪1,2,鄢㊀文1,2(1.武汉科技大学省部共建耐火材料与冶金国家重点实验室,武汉㊀430081;2.武汉科技大学高温材料与炉衬技术国家地方联合工程研究中心,武汉㊀430081)摘要:商用热力学计算软件FactSage 在耐火材料抗渣侵蚀性研究中起到重要作用,因此在耐火材料研究中应用越来越广泛㊂本文总结了近15年来热力学计算在耐火材料抗渣侵蚀性研究中的应用,重点介绍了耐火材料抗渣侵蚀研究中常用的热力学计算模型,分析了各种模型的原理㊁特点㊁适用情景㊁精确度与局限性,并给出了详细的运用实例㊂此外,本文介绍了热力学计算与其他方法相结合运用的实例,包含ANSYS㊁动力学分析㊁分子动力学模拟等方法,规避热力学计算的局限性,更加全面地分析熔渣对耐火材料的侵蚀行为㊂最后,本文对热力学计算存在的问题进行了归纳,并基于现有研究现状对其发展前景与方向进行了展望㊂关键词:耐火材料;热力学计算;抗渣侵蚀性;FactSage;热力学模型中图分类号:TQ175㊀㊀文献标志码:A ㊀㊀文章编号:1001-1625(2024)03-1110-13Application of FactSage Thermodynamic Calculation on Slag Corrosion Resistance of RefractoriesGUO Weijie 1,2,ZHU Tianbin 1,2,LI Yawei 1,2,LIAO Ning 1,2,SANG Shaobai 1,2,XU Yibiao 1,2,YAN Wen 1,2(1.The State Key Laboratory of Refractories and Metallurgy,Wuhan University of Science and Technology,Wuhan 430081,China;2.National-Provincial Joint Engineering Research Center of High Temperature Materials and Lining Technology,Wuhan University of Science and Technology,Wuhan 430081,China)Abstract :Commercial thermodynamic calculation software FactSage plays an important role in the analysis of slag corrosion process,therefore it has been widely used in the research of refractories.Application of thermodynamic calculation on slag corrosion resistance of refractories and thermodynamic calculation models which are commonly used in the slag corrosionresistance of refractories were introduced.The mechanisms,characteristics,applicable situations,accuracy and limitations of every model were discussed,and the detailed examples were given.Furthermore,the application examples of FactSage combined with other methods including ANSYS,kinetic analysis and MD simulation were given,aiming to avoid the limitations of thermodynamic calculation and comprehensively analyze the slag corrosion stly,the common problems of thermodynamic calculation were summarized,and the direction of further development was proposed.Key words :refractory;thermodynamic calculation;slag corrosion resistance;FactSage;thermodynamic model 收稿日期:2023-09-27;修订日期:2023-12-06基金项目:国家自然科学基金联合基金重点项目(U21A2058,U1908227,52272071);湖北省自然科学基金项目(2022CFB024)作者简介:郭伟杰(1998 ),男,硕士研究生㊂主要从事耐火材料抗渣性能的研究㊂E-mail:1099255596@通信作者:朱天彬,博士,副教授㊂E-mail:zhutianbin@ 0㊀引㊀言随着计算机技术的高速发展,集成了大量热力学数据的商用热力学计算软件成为研究者的重要工具㊂FactSage [1]最早于1976年提出,2001年加拿大蒙特利尔综合工业大学的FACT-win 软件与德国GTT 公司的ChemSage 软件整合为FactSage,这是目前应用最为广泛的热力学计算软件之一㊂该软件集成了大量热力学数据库,包括溶液㊁化合物㊁纯物质㊁熔盐㊁合金的数据,并整合了以多元相平衡计算为代表的多种功能,是一㊀第3期郭伟杰等:FactSage热力学计算在耐火材料抗渣侵蚀性中的应用1111个综合性集成热力学计算软件[2-3],已在全球800多所大学㊁实验室和企业中应用[4]㊂在耐火材料领域,FactSage热力学计算同样占据着重要地位,已被应用于相图绘制㊁熔渣侵蚀分析㊁液相含量分析㊁黏度计算㊁复杂条件下多元多相体系平衡㊁体系热力学函数计算等诸多方面[5-8]㊂其中,热力学计算能够较好地分析耐火材料抗渣侵蚀性,在熔渣性质㊁热力学平衡相㊁液相组成等方面提供重要参考㊂因此,本文综述了近15年来FactSage热力学计算在耐火材料抗渣侵蚀研究进展,给出了基于热力学计算的抗渣侵蚀性研究案例,以期为相关科研工作者使用热力学计算分析耐火材料抗渣侵蚀机理提供参考和借鉴㊂同时,基于近年来的研究现状,总结FactSage热力学计算在耐火材料抗渣侵蚀性的发展趋势,并对其发展前景进行了展望㊂1㊀耐火材料抗渣侵蚀研究中的热力学计算模型热力学计算中,FactSage的Equilib模块是模拟熔渣与耐火材料反应过程的最常用工具㊂该模块通过原ChemSage的算法,基于吉布斯自由能最低原理[9-10],能够较好地预测熔渣对耐火材料侵蚀过程中的热力学平衡相与液相组成变化㊂使用该模块进行耐火材料抗渣侵蚀性研究的常用过程如图1所示㊂图1㊀使用FactSage的Equilib模块对熔渣-耐火材料侵蚀过程进行分析的主要步骤Fig.1㊀Main steps during the analysis of slag corrosion resistance of refractories using Equilib module of FactSage选择合适的热力学计算模型是获取准确的热力学计算结果的前提㊂不同的热力学计算模型具有不同的侧重点,应当基于当前研究体系的特点,选取合适的模型以达到较好的模拟效果㊂目前,经过国内外研究者的长期研究,以界面反应模型为代表的热力学计算模型被广泛开发,并经过了大量实验验证,具有较高的准确度与可信度㊂下面对常用的热力学计算模型分别进行介绍㊂1.1㊀物相-温度模型图2为物相-温度模型的示意图㊂物相-温度模型是一种常用的计算模型,能够较好地反映物相随温度的变化情况㊂物相-温度模型的示意图如图2(a)所示,熔渣与耐火材料的质量恒定(常设定为100gʒ100g),在该模型中温度是唯一的变量,通过计算得到物相-温度曲线(见图2(b)),从而反映物相随温度的变化过程㊂该模型常用于分析温度对耐火材料抗渣侵蚀性的影响以及高熔点相在耐火材料内的生成温度等情况㊂此外,该模型变量较少㊁上手门槛较低,适用于大多数耐火材料抗渣侵蚀性分析㊂图2㊀物相-温度模型的示意图Fig.2㊀Schematic diagram of phase-temperature thermodynamic model在Gehre等[11]关于含硫渣对尖晶石耐火材料的侵蚀行为的研究中,通过设定30g熔渣与10g耐火材料在强还原气氛下进行反应,得到了尖晶石㊁CaMg2Al16O27相在800~1450ħ的变化趋势(见图3),较好地描述了固相随温度降低逐渐析出的过程㊂类似地,在刚玉尖晶石浇注料体系中,Ramult等[12]在1112㊀耐火材料硅酸盐通报㊀㊀㊀㊀㊀㊀第43卷图3㊀矿物相与熔渣含量与温度的函数关系[11]Fig.3㊀Functional relationship between mineral phase,slag content and temperature [11]1200~1700ħ设定50%(文中均为质量分数)耐火材料与50%钢渣反应,比较了三种不同碱度的熔渣对浇筑料侵蚀后的产物区别㊂该方法同样在铜工业用无铬耐火材料中运用,Jastrzębska 等[13]通过将50g 的不同种类铜渣与50g 的Al 2O 3-MgAl 2O 4耐火材料进行计算,发现尖晶石能够在较大温度范围内稳定存在,证实了该种耐火材料对铜渣具有较好的抵抗能力㊂而在炉渣的固相分数分析中,Anton 等[14]则使用该模型计算了熔渣的完全融化温度,发现碱度不随固体析出而变化㊂物相-温度模型对熔渣-耐火材料体系内固相的析出温度具有良好的精确度,并能够准确判断固相在高温下的稳定情况,且可以确定产生液相的温度点㊂此外,这种热力学模型以温度作为变量,适合于描述较大温度范围内的熔渣侵蚀情况,能够提供从升温到降温的全过程熔渣侵蚀产物分析㊂然而,该种模型具有明显的局限性㊂众所周知,熔渣侵蚀耐火材料的过程中,熔渣含量变化导致系统物相组成不断变化,熔渣侵蚀耐火材料的过程是一个渐进的过程㊂使用温度-物相模型时,由于熔渣与耐火材料组分未引入变量,采用了固定值进行计算,导致其计算结果是对熔渣侵蚀最终结果的预测,而无法渐进㊁全面地展现熔渣对耐火材料的侵蚀过程㊂侵蚀过程描述的缺失使得中间相的产生机理无法较好地被描述(如浇注料体系中二铝酸钙(CA 2)与六铝酸钙(CA 6)相的含量变化),导致复杂体系的精确度较差㊂1.2㊀溶解模型图4为溶解模型示意图,图5为不同气氛下镁铬耐火材料-冰铜渣系统的热力学平衡相㊂溶解模型也是耐火材料抗渣侵蚀研究中一种常用的模型,如图4(a)所示,该模型设定耐火材料的质量恒定不变,熔渣质量线性增加㊂在该模型中,定义质量比A =m S /m R (m S 为熔渣质量,m R 为耐火材料质量),对系统内各组分使用表达式<m R +m S ˑA >进行描述,即随着A 值的增加,在耐火材料质量不变的情况下,熔渣质量从0开始不断线性增加,从而模拟熔渣量从少到多的侵蚀过程㊂如图4(b)所示,该模型较好地反映了组分在熔渣内的溶解速率情况与稳定程度,通过物相质量-A 曲线的斜率定性反映溶解速率,通过曲线归零时所需A 的绝对值反映该物相在熔渣内的稳定程度㊂图4㊀溶解模型示意图Fig.4㊀Schematic diagrams of dissolution model 溶解模型由于具有较好的普适性而被广泛运用于耐火材料抗渣侵蚀研究中㊂在Liu 等[15]㊁王恭一等[16]和程艳俏等[17]针对镁铬质耐火材料抗渣侵蚀性的研究中,根据如图5所示的热力学计算,发现镁铬尖晶石㊁镁铁尖晶石以及镁橄榄石在系统内可以稳定存在;而在还原气氛下(见图5(b)),镁橄榄石的含量明显下㊀第3期郭伟杰等:FactSage热力学计算在耐火材料抗渣侵蚀性中的应用1113降,且生成了Pb(g),从而解释了还原气氛下耐火材料抗渣侵蚀性下降的原因㊂在评价耐火骨料抗渣侵蚀性的研究中,金胜利等[18]分别计算了高炉钛渣对棕刚玉㊁电熔刚玉㊁亚白刚玉㊁镁铝尖晶石以及特级矾土的侵蚀,通过比较刚玉相完全消失时的A值分析了五种常见骨料的抗侵蚀能力㊂桑绍柏等[19]通过热力学计算发现SiC能够与含Ti熔渣反应生成稳定的FeSi与TiC相,且SiC在A=4.5时才完全消耗,证明了SiC在该体系内具有良好的稳定性㊂吕晓东等[20]通过该模型计算发现SiC㊁钛尖晶石在钛渣中具有较好的稳定性,这与静态坩埚法得到的结果一致㊂马三宝等[21]也计算了钢包渣对轻质方镁石-尖晶石耐火材料的侵蚀,得出尖晶石的溶解速率大于方镁石㊂而李真真等[22]使用该模型研究了氧化钛对镁砂抗渣渗透性能的影响,发现生成的CaTiO3在熔渣内比镁砂更加稳定㊂图5㊀不同气氛下镁铬耐火材料-冰铜渣系统的热力学平衡相[15]Fig.5㊀Equilibrium phases of magnesia chromite refractories-matte slag system under different atmospheres[15]该模型对高熔点物相在熔渣体系内的稳定度预测展现出较为良好的精确度㊂由于该模型中引入了变量A=m S/m R,特定物相消失时的A值反映了该物相在熔渣内的稳定程度,因此该模型能够较好地发现特定熔渣体系内的高熔点相(如尖晶石相㊁CaTiO3相与方镁石相),为针对性地开发具有优异抗渣侵蚀性的耐火材料提供依据㊂并且,该种模型能够有效地对比不同耐火材料体系在特定熔渣下的稳定程度,从而针对酸性渣㊁碱性渣㊁富钛渣㊁富锰渣等不同熔渣体系挑选对应的耐火材料,满足特定条件的需求㊂然而,该种模型仍具有一定局限性,虽然能够良好地预测高熔点㊁高稳定相的生成,却缺乏定性地描述这些物相在侵蚀区域相对位置的能力,例如其能够精确地预测刚玉骨料外侧生成CA2与CA6相,但难以定性地描述两相在骨料外侧的位置㊂因此,使用该种模型时需结合SEM㊁EDS等表征手段进行深入分析㊂此外,在真实的熔渣侵蚀过程中,由于耐火材料组分向熔渣中逐渐溶解,熔渣的组分受到耐火材料的影响而不断改变,因此熔渣组分处于 不断更新 的状态㊂而该模型中熔渣组分恒定不变,即恒定保持初始化学组分㊁仅逐步提升熔渣的质量,无法精确地描述熔渣与耐火材料之间的组分交换㊂因此,该种模型适合对静态坩埚抗渣法等熔渣组分变化不大的情景进行分析,对感应炉抗渣㊁回转窑抗渣㊁钢包渣线抗渣等组分交换剧烈㊁熔渣处于动态情景的模拟精确度较低㊂1.3㊀界面反应模型界面反应模型能够有效地模拟熔渣-耐火材料界面处的相互作用过程,被广泛应用于多种耐火材料体系中,其计算结果经过了广泛验证,是目前常用㊁可信的模型之一㊂该模型最早由Berjonneau等[23]于2009年提出,最初用于模拟恒定温度㊁压力条件下二次冶金钢包渣对Al2O3-MgO耐火材料的侵蚀㊂界面反应模型的示意图如图6所示,在该模型中定义了反应度B=w R/(w S+w R),并满足w R+w S=1,其中w R为耐火材料质量分数,w S为熔渣的质量分数,对系统内的组分采用表达式<m S-(m S-m R)ˑB>进行描述㊂B反映了耐火材料-熔渣界面的反应程度,当B接近0时,系统中熔渣比例较高,反应程度较低,反之B接近1时,系统中耐火材料占比较高,反应程度越高㊂如图6(b)所示,反应度B可以近似为熔渣-耐火材料接触的界面层的相对位置,B趋近于1时,生成的物相越接近耐火材料表层,而其趋近于0时物相靠近熔渣侧㊂这一特性使得该模型能较好地反映了侵蚀过程中固相的相对位置与生成量,因此尤其适合模拟保护层的生成情况㊂1114㊀耐火材料硅酸盐通报㊀㊀㊀㊀㊀㊀第43卷图6㊀界面反应模型的示意图[21]Fig.6㊀Schematic diagrams of interlayer reaction model[21]溶解模型在耐火材料抗渣领域得到了广泛应用,并被大量实验证明具有良好的精确度㊂Berjonneau 等[23]通过实验验证了该模型的精确度,计算结果与实际侵蚀区域的微观结构呈良好的对应关系(见图7(a)),并得出了CA2和CA6相的形成机理(图7(b))㊂Tang等[24]使用该模型对Al2O3坩埚的侵蚀行为进行了分析和实验验证,发现热力学计算预测的熔渣㊁CA2㊁CA6㊁尖晶石以及刚玉骨料的位置与实际实验结果一致㊂在蒋旭勇等[25]的研究中,通过该模型计算了铝镁质浇注料对不同Al2O3含量的CaO-SiO2-Al2O3渣的物相生成量,发现高Al2O3含量的熔渣能够促进形成更厚的隔离层㊂在高纯度镁质耐火材料对富铁渣的抗渣侵蚀性研究中,Betsis等[26]利用该模型发现,富铁渣将方镁石转化为MgO-Fe x O,且发现液相中FeO含量上升㊂类似地,Oh等[6]也观测到了MgO-Fe x O层,且MgO㊁FeO相对含量与显微结构观察一致㊂李艳华等[27]使用该模型对LF渣对ρ-Al2O3结合铝镁质浇注料的侵蚀行为进行了分析,通过FactSage软件得到了尖晶石的组成,结果显示生成的尖晶石中含有一定量的MnAl2O4和FeAl2O4,即熔渣中的Mn2+㊁Fe2+生成了复合尖晶石㊂Guo等[28]使用该模型计算了熔渣侵蚀钙镁铝酸盐(CMA)骨料产生的热力学平衡相,发现CMA骨料内的一铝酸钙(CA)㊁CA2相在高温下转化为液相,提高了熔渣的Al2O3含量㊂图7㊀熔渣对刚玉骨料的侵蚀的热力学计算结果[21]Fig.7㊀Thermodynamic calculation results of corrosion of slag to corundum aggregate[21]㊀第3期郭伟杰等:FactSage热力学计算在耐火材料抗渣侵蚀性中的应用1115溶解模型不仅可以预测物相组成的变化,还常用于预测熔渣侵蚀过程中液相组成的变化与黏度变化[29]㊂Wang等[30]使用该模型对ZrO2耐火材料对高碱度精炼渣的侵蚀行为进行了研究,图8为ZrO2耐火材料的侵蚀过程的热力学计算结果㊂EDS线扫描中ZrO2含量从耐火材料到过渡层逐渐降低,CaO含量随着渣层到过渡层逐渐降低,其趋势与热力学计算结果一致㊂鄢文等[31]研究了熔渣对刚玉尖晶石浇注料侵蚀的热力学模型,结果显示,侵蚀层到耐火材料内部SiO2㊁CaO含量逐渐降低,而SiO2的含量则先降低后增加,这与A值介于0.66至0.84之间的曲线相吻合㊂此外,Peng等[32]计算了轻质方镁石-尖晶石浇注料与熔渣反应过程中的液相黏度变化,证明了该种耐火材料优秀的抗渣渗透性能㊂图8㊀ZrO2耐火材料侵蚀过程的热力学计算结果[27]Fig.8㊀Thermodynamic calculation results of corrosion process of ZrO2refractories[27]作为最常用的抗渣模型之一,界面反应模型最大的优势为能够生动地描述物相的生成机理㊁生成位置㊂由于变量B=w R/(w S+w R)的引入,界面反应模型能够细致地描述熔渣对耐火材料侵蚀的全过程,详细地展现各热力学平衡相的含量变化,其良好的精确度与泛用性使得其被广大研究者所使用,助力了许多研究成果的产出,并得到了广泛的实验验证㊂然而,该模型同样具有一定的局限性㊂如前文所述,熔渣对耐火材料侵蚀是一个动态的过程,渣组分会随侵蚀程度的改变不断变化,Zhang等[33]指出,该模型忽略了耐火材料溶解对熔渣化学组分变化,使得其对动态渣蚀的模拟存在一定的误差㊂在真实熔渣侵蚀过程中,耐火材料的损毁常是由溶解㊁化学反应与渗透共同导致的㊂该模型虽然能够较好地描述熔渣-耐火材料界面上的化学反应,却不能很好地胜任熔渣渗透过程的模拟㊂此外,受制于热力学计算的局限性,界面反应模型无法展现耐火材料表面形貌㊁扩散速率㊁熔体冲刷等因素对抗渣侵蚀性的影响㊂1.4㊀逐步迭代模型在实际侵蚀过程中,熔渣化学组分会随着熔渣与耐火材料的反应而发生变化,从而影响熔渣的侵蚀能力,而溶解模型与界面反应模型忽略了这一变化,且两者均不能较好地模拟熔渣的渗透过程㊂针对以上问题,Luz等[34]设计了一个新的模型,迭代模型的示意图如图9所示㊂该模型具有一个迭代程序,其原理如图9(a)所示,设定第一反应阶段初始耐火材料质量与熔渣质量均为100g(S为熔渣,R为耐火材料),将反应后将得到的改性渣(S1)再次与相同质量的耐火材料进行二次迭代计算得到新的改性渣(S2),不断重复该过程直至熔渣量归零或达到饱和,通过该迭代程序,每一次循环后熔渣组分都会改变㊂该模型同样可以用于描述熔渣对耐火材料的渗透过程(图9(b)),即更大的迭代计算次数对应更长的熔渣渗透距离[31]㊂Calvo等[35]在钢包用铝碳质耐火材料的用后分析中使用该模型分析了熔渣对耐火材料的渗透,其热力学计算结果与用后耐火材料的显微结构如图10所示(MA为镁铝尖晶石)㊂热力学计算结果显示,随着熔渣渗透深度的增加,尖晶石和六铝酸钙将会依次生成㊂从侵蚀区图像中可以看出,从工作面到耐火材料内部依次为镁铝尖晶石㊁二铝酸钙和六铝酸钙,基本与热力学计算一致㊂类似地,在Muñoz等[36]对铝镁碳耐火材料抗渣侵蚀性研究中,该模型计算结果与熔渣渗透区的显微结构吻合程度较高㊂此外,该模型仍可以较为精确1116㊀耐火材料硅酸盐通报㊀㊀㊀㊀㊀㊀第43卷地预测物相的生成情况,并非专用于描述熔渣对耐火材料的渗透情况㊂在Luz等[37]针对尖晶石浇注料的熔渣侵蚀研究中,该模型预测了CA2和CA6相的存在,并通过显微结构验证了热力学计算的准确性㊂Han 等[38]使用该模型计算得到了MgO-Fe x O层,这与侵蚀后试样的显微结构一致㊂在Luz等[39]对镁碳质耐火材料的抗渣侵蚀的研究中,通过该模型计算发现MgO溶解量随着熔渣碱度降低而增加,证明了低碱度渣对镁碳质耐火材料的侵蚀更加强烈㊂图9㊀迭代模型的示意图[31]Fig.9㊀Schematic diagram of the iterative corrosion model[31]图10㊀用后铝碳质耐火材料的热力学计算结果[32]Fig.10㊀Thermodynamic calculation results of spent Al2O3-C refractories[32]与溶解模型㊁界面反应模型相比,迭代模型能够模拟耐火材料组分对熔渣侵蚀能力的影响㊂每次迭代时,熔渣组分都会被耐火材料所改变,改性渣再次与新的耐火材料反应,这个过程模拟熔渣组分更新,因此该模型对动态渣蚀具有更加良好的模拟精确度㊂此外,该种模型能够定性地描述渗透过程,反映熔渣渗透过程中熔渣组分的变化与物相的变化,从而为耐火材料用后分析㊁熔渣渗透行为分析提供重要的参考㊂在真实的熔渣渗透过程中,熔渣的渗透行为除了受到熔渣的组分和黏度的影响外,还会受到接触角㊁气孔孔径㊁晶界渗透㊁渗透时间等诸多因素的影响,而该模型仅能从热力学的角度预测熔渣组分变化㊁黏度变化和物相变化,对物理过程缺乏描述的能力㊂因此将该模型用于描述熔渣渗透过程时,迭代次数仅能够定性地反映渗透深度,不能够精确地给出渗透距离㊂此外,随着熔渣深入耐火材料内部,耐火材料工作面与内部之间的温度梯度也会影响熔渣的渗透行为,而该种模型设定耐火材料内外温度恒定,导致对耐火材料深处的物相的预测存在一定的偏差㊂并且,该种模型中引入了迭代程序,使得计算量大幅增加,部分体系中甚至需要十几次以上的循环计算才能使熔渣完全耗尽或达到饱和,对模型使用者造成了较重的负担㊂这些因素制约了该模型的普及与发展,因此较少研究使用该种模型进行热力学模拟㊂1.5㊀其他热力学计算模型除上述四种最常用的热力学计算模型外,国内外研究者针对不同熔渣侵蚀过程的特点,针对性地开发了新的热力学计算模型,从而更加精确地预测耐火材料侵蚀过程㊂㊀第3期郭伟杰等:FactSage热力学计算在耐火材料抗渣侵蚀性中的应用1117针对迭代模型的局限性,Sagadin等[40]使用FactSage与SimuSage[41]开发了一种新型耐火材料侵蚀模型,用于模拟镍铁渣对镁质耐火材料的侵蚀,并对气孔率和温度梯度的影响进行了模拟,具体如图11所示㊂如图11(a)所示,该模型将耐火材料分为了十个区域,温度从外到内线性递减,每个区域均含有定量的耐火材料与气孔㊂图11(b)为该模型单个区域的运算流程,耐火材料与熔渣首先进行计算,产物被 物相分离器 分离为固体与熔体㊂由于耐火材料的气孔仅能允许一部分熔渣向深处渗透,因此研究者使用SimuSage设计了 熔体分离器 ,将熔体分离为可以进入下一区域的熔体A与被阻碍在该区域的熔体B㊂熔体B与固体氧化物组成混合体并在该区域内再次计算,而熔体A则进入下一区域㊂该模型不仅能够描述熔渣化学组分的变化,还考虑了耐火材料气孔率对熔渣渗透的影响[42]㊂并且,由于温度梯度的存在,橄榄石等能够在材料深处的低温区域稳定存在,这在恒定温度的模型中是无法实现的㊂图11㊀基于FactSage与SimuSage的耐火材料侵蚀模型[37]Fig.11㊀Corrosion model based on FactSage and SimuSage[37]在感应炉抗渣法中,熔渣由于电磁场的作用剧烈地冲刷耐火材料,熔渣的组分由于耐火材料的损毁和熔渣的对流运动而不断混合和改变,并且耐火材料基质与骨料的侵蚀速率不同,导致两者对熔渣组分的改变能力不同,因此需要新的热力学计算模型描述动态条件下的熔渣侵蚀过程㊂在轻量化MgO-Al2O3浇注料的抗渣侵蚀性研究中,邹阳[43]提出了一种新的热力学计算模型,这种模型中熔渣组分受到耐火材料侵蚀的影响,并可以反映骨料与基质的侵蚀速率差别㊂该模型将熔渣侵蚀过程分为了n个相等的时间段,在每个Δt内,熔渣分别与骨料㊁基质进行计算,得到新的液相加和,即为 更新 后的熔渣组分㊂图12为动态熔渣侵蚀下的热力学计算模型㊂相较于其他模型,该模型能够形象地显示骨料㊁基质抗侵蚀能力的差异,且由于受到了骨料㊁基质的共同影响而不断 更新 ,其具有更高的精确度,更加符合动态熔渣条件下熔渣受到对流而不断混合的实际情况㊂图12㊀动态熔渣侵蚀下的热力学计算模型[40]Fig.12㊀Thermodynamic calculation model of dynamic slag corrosion condition[40]综合来看,以上模型在现有的经典模型基础上进行了一定程度的改进,使之能够更好地描述熔渣侵蚀过程,展现熔渣侵蚀模型的改进潜力㊂然而,这些改进模型计算方式复杂,或需要使用其他软件,导致其难以掌握㊂同时,这些模型提出较晚,未在大量研究中被广泛使用,缺乏实验数据的验证㊂受制于热力学计算本身的局限性,这些模型还是仅能从热力学角度描述化学反应过程㊁物相变化,对湍流㊁扩散等现象造成的影响无法给出预测㊂。
Package‘gfcanalysis’October11,2023Version1.8.0Date2023-10-09Language en-usTitle Tools for Working with Hansen et al.Global Forest ChangeDatasetDepends R(>=3.5.0),raster,methodsImports sf,terra,geosphere,RCurl,plyr,ggplot2,grid,stringr,animation,rasterVisEncoding UTF-8Description Supports analyses using the Global Forest Change dataset released by Hansen et al.gfcanalysis was originally written for the Tropical Ecology Assessment and Monitoring(TEAM)Network.For additional details on the Global Forest Change dataset,see:Hansen,M.et al.2013.``High-Resolution Global Maps of21st-Century Forest Cover Change.''Science342(15November):850-53.The forest change data and more information on theproduct is available at<>. License GPL(>=3)URL https:///azvoleff/gfcanalysisBugReports https:///azvoleff/gfcanalysis/issues LazyData trueRoxygenNote7.2.3NeedsCompilation noAuthor Alex Zvoleff[aut],Matthew Cooper[cre]Maintainer Matthew Cooper<*******************>Repository CRANDate/Publication2023-10-1112:20:02UTC12animate_annual R topics documented:animate_annual (2)annual_stack (3)calc_gfc_tiles (4)calc_pixel_areas (5)check_aoi (5)download_tiles (6)extract_gfc (7)gfc_stats (8)gfc_tiles (9)plot_gfc (9)scale_by_pixel_area (10)scale_toar (10)test_poly (11)threshold_gfc (11)utm_zone (13)Index15 animate_annual Plot an animation of forest change within a given area of interest(AOI)DescriptionProduces an animation of annual forest change in the area bounded by the extent of a given AOI,or AOIs.The AOI polygon(s)is(are)also plotted on the image.The gfc_stack must be pre-calculated using the annual_stack function.The animation can be either an animated GIF(if type is set to ’gif’)or a series of’.png’files with a corresponding’.html’webpage showing a simple viewer and the forest change animation(if type is set to’html’).The HTML option is recommended as it requires no additional software to produce it.The animated GIF option will only work if the imagemagicK software package is installed beforehand(this is done outside of R).Usageanimate_annual(aoi,gfc_stack,out_dir=getwd(),out_basename="gfc_animation",site_name="",type="html",height=3,width=3,dpi=300,dataset="GFC-2022-v1.10")annual_stack3Argumentsaoi one or more AOI polygons as a SpatialPolygonsDataFrame or sf object.If there is a’label’field in the dataframe,it will be used to label the polygons inthe plots.If the AOI is not in the WGS84geographic coordinate system,it willbe reprojected to WGS84.gfc_stack a GFC product subset as a RasterStack(as output by annual_stack)out_dir folder for animation outputout_basename basename to use when naming animationfilessite_name name of the site(used in making title)type type of animation to make.Can be either"gif"or"html"height desired height of the animation GIF in incheswidth desired width of the animation GIF in inchesdpi dots per inch for the output imagedataset which version of the Hansen data to use annual_stack was runSee Alsoannual_stackannual_stack Generate an annual stack of forest change from GFC productDescriptionUses thresholded GFC data as output by threshold_gfc to make an annualized layer stack of forest change.See Details for the class codes used in the annual raster stack.The animate_annual function can be used to produce an animation of forest change from the generated layer stack.Usageannual_stack(gfc,dataset="GFC-2022-v1.10")Argumentsgfc thresholded extract of GFC product for a given AOI(see threshold_gfc) dataset which version of the Hansen data to use4calc_gfc_tilesDetailsThe output raster stack uses the following codes to describe forest change at each pixel:Nodata0Forest1Non-forest2Forest loss3Forest gain4Forest loss and gain5Water6See Alsothreshold_gfc,animate_annualcalc_gfc_tiles Calculate the GFC product tiles needed for a given AOIDescriptionIntersects an AOI with the GFC product grid to determine what tiles are need to cover the AOI.Usagecalc_gfc_tiles(aoi)Argumentsaoi an Area of Interest(AOI)as a SpatialPolygons*or sf object.If the AOI is not in the WGS84geographic coordinate system,it will be reprojected to WGS84.Valuea sf of the GFC tiles needed to cover the AOIExamplestiles<-calc_gfc_tiles(test_poly)plot(tiles)plot(test_poly,lt=2,add=TRUE)calc_pixel_areas5 calc_pixel_areas Calculates the pixel area for each line of a rasterDescriptionCalculates the pixel area for each line of a rasterUsagecalc_pixel_areas(x)Argumentsx a Raster*objectValuea vector with the area in square meters of the pixels in each line of x(vector has length equal tonrow(x))check_aoi Check if aoi is an sf or sp type object If sp,convert to sf and returnDescriptionCheck if aoi is an sf or sp type object If sp,convert to sf and returnUsagecheck_aoi(aoi)Argumentsaoi the area of interest object6download_tiles download_tiles Download a set of GFC tilesDescriptionThis functionfirst checks whether each tile in a set GFC product tiles is present locally,and that localfile sizes match thefile sizes of thefiles available on the Google server hosting the GFC product.Next,the function downloads all tiles that either are not present locally,or that are present but havefile sizes differing from thefile on the Google server.Usagedownload_tiles(tiles,output_folder,images=c("treecover2000","lossyear","gain","datamask"),dataset="GFC-2022-v1.10")Argumentstiles sf with GFC product tiles to download,as calculated by the calc_gfc_tilesfunction.output_folder the folder to save output data inimages which images to download.Can be any of’treecover2000’,’loss’,’gain’,’lossyear’,’datamask’,’first’,and’last’.dataset which version of the Hansen data to useSee Alsoextract_gfcExamples##Not run:output_folder<- H:/Data/TEAM/GFC_Producttiles<-calc_gfc_tiles(test_poly)download_tiles(tiles,output_folder)##End(Not run)extract_gfc7 extract_gfc Extracts GFC data for a given AOIDescriptionThis function extracts a dataset for a given AOI from a series of pre-downloaded GFC tiles.The download_tiles function should be used beforehand in order to download the necessary data to the specified data_folder.Note that the outputfile format isfixed as GeoTIFF with LZW com-pression.Usageextract_gfc(aoi,data_folder,to_UTM=FALSE,stack="change",dataset="GFC-2022-v1.10",...)Argumentsaoi an Area of Interest(AOI)as a sf object.If the AOI is not in WGS1984 (EPSG:4326),it will be reprojected to WGS84.data_folder folder where downloaded GFC product tiles are located(see download_tiles function.to_UTM if TRUE,then reproject the output into the UTM zone of the AOI centroid.If FALSE,retain the original WGS84projection of the GFC tiles.stack the layers to extract from the GFC product.Defaults to"change".See Details.dataset which version of the Hansen data to use...additional arguments as for writeRaster,such as filename,or overwrite. DetailsThe stack option can be"change"(the default),"first",or"last".When set to"change",the forest change layers(treecover2000,loss,gain,lossyear,and datamask)will be extracted for the given aoi.The"first"and"last"options will mosaic the2000or last year composite top of atmosphere (TOA)reflectance images(respectively).ValueRasterStack with GFC layersSee Alsodownload_tiles,annual_stack,gfc_stats8gfc_stats gfc_stats Produce a table of forest cover change statistics for a given AOIDescriptionFor a given AOI,this function produces two tables:an annual forest loss table(in hectares,by default),and a table specifying1)the total area of pixels that experienced forest gain and,2)the total area of pixels that experienced both loss and gain over the full period(from2000through the end date of the specific product you are using,depending on the chosen dataset).Note that forest gain and combined loss and gain are not available in the GFC product on an annualized e extract_gfc to extract the GFC data for the AOI,and threshold it using threshold_gfc prior to running this function.Usagegfc_stats(aoi,gfc,scale_factor=1e-04,dataset="GFC-2022-v1.10") Argumentsaoi one or more Area of Interest(AOI)polygon(s)as a SpatialPolygons*.See Details.gfc extract of GFC product for a given AOI(see extract_gfc),recoded using threshold_gfc.scale_factor how to scale the output data(from meters).Defaults to.0001for output in hectares.dataset which version of the Hansen data to useDetailsIf the aoi object is not in the coordinate system of gfc,it will be reprojected.If there is a"label"attribute,it will be used to label the output statistics.Otherwise,unique names("AOI1","AOI2", etc.)will be generated and used to label the output.If multiple AOIs share the same labels,statistics will be provided for the union of these AOIs.Valuelist with two elements"loss_table",a data.frame with statistics on forest loss,and"gain_table", with the area of forest gain,and area that experienced both loss and gain.The units of the output are hectares(when scale_factor is set to.0001).See Alsoextract_gfc,threshold_gfcgfc_tiles9 gfc_tiles Grid of tiles used for the GFC productDescriptionContains a SpatialPolygonsDataFrame with a10x10degree grid in WGS84coordinate system, covering the area from180W-180E and80N-60S,the tile system used by the GFC Product.plot_gfc Plot forest change(relative to2000)for a given yearDescriptionPlots a single layer of forest change from a layer stack output by annual_stack.Usageplot_gfc(fchg,aoi,title_string="",size_scale=1,maxpixels=50000)Argumentsfchg a forest change raster layer(a single layer of the layer stack output by annual_stack aoi one or more AOI polygons as a SpatialPolygonsDataFrame or sf object.Ifthere is a’label’field in the dataframe,it will be used to label the polygons inthe plots.If the AOI is not in WGS1984(EPSG:4326),it will be reprojected toWGS84.title_string the plot titlesize_scale a number used to scale the size of the plot textmaxpixels the maximum number of pixels from fchg to use in plottingSee Alsoannual_stack,animate_annual10scale_toar scale_by_pixel_area Scales a raster by the area of each pixel in metersDescriptionCalculates the area(in meters)of each pixel in a raster,scales the value of each pixel by the area, applies the desired scale factor,and returns the result as a eful for calculating class areas based on a classified raster in a geographic coordinate system.Assumes that raster is not rotated(latitudes of every pixel in a given row are identical).Processes block by block to support handling very large rasters.Usagescale_by_pixel_area(x,filename,datatype,pixel_areas=NULL,scale_factor=1)Argumentsx a Raster*objectfilename(optional)filename for output rasterdatatype(optional)datatype for output raster see dataType NOT YET SUPPORTED pixel_areas a vector giving the area of each cell in a single column of the raster.See calc_pixel_areas.If NULL,this vector will be calculated based on the coor-dinate system of x.scale_factor a value to scale the results byValueRasterLayer with pixel areas(in meters)scale_toar Scale thefirst or last top of atmosphere(TOA)reflectance imagesDescriptionThis function applies the scale factors provided by Hansen et al.to rescale thefirst and last TOA reflectance images from integer tofloating point.The following scale factors are used:band3,508;band4,254;band5,363;band7,423.The output datatype is FLT4S.test_poly11Usagescale_toar(x,...)Argumentsx the"first"or"last"image for a given aoi as a RasterStack(see stack option for extract_gfc)....additional arguments as for writeRaster,such as filename,or overwrite. ValueRasterStack of TOA reflectance valuesSee Alsoextract_gfctest_poly Polygon outlining TEAM site in Caxiuanã,BrazilDescriptionContains a SpatialPolygonsDataFrame with a simplified polygon of the area within the Tropical Ecology Assessment and Monitoring(TEAM)network site in Caxiuanã,Brazil.threshold_gfc Threshold the GFC productDescriptionUses the GFC data output from extract_gfc to make an thresholded layer stack withfive layers: treecover2000,loss,gain,lossyear,and datamask layers.See Details for the coding used in each layer.Note that the outputfile format isfixed as GeoTIFF with LZW compression.Usagethreshold_gfc(gfc,forest_threshold=25,...)Argumentsgfc extract of GFC product for a given AOI(see extract_gfc)forest_thresholdpercent woody vegetation to use as a threshold for mapping forest/non-forest ...additional arguments as for writeRaster,such as filename or overwrite12threshold_gfcDetailsThe output uses the following codes to describe forest change at each pixel:Band1(forest2000)Non-forest0Forest1Band2(lossyear)No loss0Loss in20011Loss in20022Loss in20033Loss in20044Loss in20055Loss in20066Loss in20077Loss in20088Loss in20099Loss in201010Loss in201111Loss in201212Loss in201313Loss in201414Note that lossyear is zero for pixels that were not forested in2000,and that the2013and2014loss layers are not available in the original2013Hansen dataset(the2013loss layer is available in the 2014and2015updates,while the2014loss layer is available in the2015update only).Band3(gain)No gain0Gain1Note that gain is zero for pixels that were forested in2000Band4(lossgain)No loss and gain0Loss and gain1Note that loss and gain is difficult to interpret from the thresholded product,as the original GFC product does not provide information on the sequence(loss then gain,or gain then loss),or the levels of canopy cover reached prior to loss(for gain then loss)or after loss(for loss then gainpixels).The layer is calculated here as:lossgain<-gain&(lossyear!=0),where loss year and gain are the original GFC gain and lossyear layers,respectively.Band5(datamask)No data0Land1Water2ValueRasterBrick with thresholded GFC product(see details above)See Alsoextract_gfcutm_zone Given a spatial object,calculate the UTM zone of the centroidDescriptionFor a line or polygon,the UTM zone of the centroid is given,after reprojecting the object into WGS-84.Usageutm_zone(x,y,proj4string=FALSE)##S4method for signature numeric,numericutm_zone(x,y,proj4string=FALSE)##S4method for signature Spatial,missingutm_zone(x,proj4string)Argumentsx a longitude(with western hemisphere longitudes negative),or a Spatial object y a latitude(with southern hemisphere latitudes negative),or missing(if x is a Spatial object)proj4string if FALSE(default)return the UTM zone as a string(for example"34S"for UTM Zone34South).If TRUE,return a proj4string using the EPSG code as aninitialization string.DetailsBased on the code on at http://bit.ly/17SdcuN.Examplesutm_zone(45,10)utm_zone(45,-10)utm_zone(45,10,proj4string=TRUE)Indexanimate_annual,2,3,4,9annual_stack,2,3,3,7,9calc_gfc_tiles,4calc_pixel_areas,5,10check_aoi,5dataType,10download_tiles,6,7extract_gfc,6,7,8,11,13gfc_stats,7,8gfc_tiles,9plot_gfc,9scale_by_pixel_area,10scale_toar,10test_poly,11threshold_gfc,3,4,8,11utm_zone,13utm_zone,numeric,numeric,logical-method(utm_zone),13utm_zone,numeric,numeric-method(utm_zone),13utm_zone,Spatial,missing,logical-method(utm_zone),13utm_zone,Spatial,missing-method(utm_zone),13writeRaster,7,1115。
