Non-isothermal Crystallization and Thermal Transformation Behaviors of Plasma Sprayed Fe_(48)Cr_(15)Mo_(14)C_(15)B_(6)Y_(2)Amorphous Coating

The non-isothermal crystallization dynamic behavior and mechanism of plasma sprayed Fe_(48)Cr_(15)Mo_(14)C_(15)B_(6)Y_(2)coating were thoroughly studied.The phase transition and crystallization kinetics of the coating were elaborately investigated by differential scanning calorimetry(DSC),X-ray diffraction(XRD),scanning electron microscopy(SEM),and transmission electron microscopy(TEM).The findings reveal that the characteristic temperatures of the coating shift to an elevated temperature at a higher heating rate and the crystallization processes are thermally activated.The 3-rd step of crystallization processes is more susceptible to the continuously increased heating rate while the onset crystallization reaction is less sensitive to the continuously enhanced heating rate.Fe_(23)(C,B)_6 phase is inclined to precipitate than other crystal phases due to the substantial pre-generation ofα-Fe.The onset nucleation and growth ofα-Fe crystals is tough due to a higher onset apparent activation energy.Meanwhile,the transformation from Fe_(23)(C,B)_(6)to FeB is harder in comparison with the precipitation of other crystals.The most parts of the three crystallization processes are dominated by three-dimensional diffusion model due to the fact that most values of local Avrami exponent are higher than 2.5.

Evolution of mechanical properties,localized corrosion resistance and microstructure of a high purity Al-Zn-Mg-Cu alloy during non-isothermal aging

The evolution of mechanical properties,localized corrosion resistance of a high purity Al-Zn-Mg-Cu alloy during non-isothermal aging(NIA)was investigated by hardness test,electrical conductivity test,tensile test,intergranular corrosion test,exfoliation corrosion test,slow strain rate tensile test and electrochemical test,and the mechanism has been discussed based on microstructure examination by optical microscopy,electron back scattered diffraction,scanning electron microscopy and scanning transmission electron microscopy.The NIA treatment includes a heating stage from 40℃to 180℃with a rate of 20℃/h and a cooling stage from 180℃to 40℃with a rate of 10℃/h.The results show that the hardness and strength increase rapidly during the heating stage of NIA since the increasing temperature favors the nucleation and the growth of strengthening precipitates and promotes the transformation of Guinier-Preston(GPI)zones toη'phase.During the cooling stage,the sizes ofη'phase increase with a little change in the number density,leading to a further slight increase of the hardness and strength.As NIA proceeds,the corroded morphology in the alloy changes from a layering feature to a wavy feature,the maximum corrosion depth decreases,and the reason has been analyzed based on the microstructural and microchemical feature of precipitates at grain boundaries and subgrain boundaries.

Exploring the effect of cooling rate on non-isothermal crystallization of copolymer polypropylene by fast scanning calorimetry

Polypropylene is commonly used as a binder for ceramic injection molding,and rapid cooling is often encountered during processing.However,the crystallization behavior of polypropylene shows a strong dependence on cooling rate due to its semi-crystalline characteristics.Therefore,the influence of cooling rate on the quality of final product cannot be ignored.In this study,the fast differential scanning calorimetry(FSC)test was performed to study the influence of cooling rate on the non-isothermal crystallization behavior and non-isothermal crystallization kinetics of a copolymer polypropylene(PP BC03B).The results show that the crystallization temperatures and crystallinity decrease as the cooling rate increases.In addition,two exothermic peaks occur when cooling rate ranges from 30 to 300 K·s^(-1),indicating the formation of another crystal phase.Avrami,Ozawa and Mo equations were used to explore the non-isothermal crystallization kinetics,and it can be concluded that the Mo method is suitable for this study.

Comparative analysis of isothermal and non-isothermal solidification of binary alloys using phase-field model

Based on the entropy function, a two-dimensional phase field model of binary alloys was established. Meanwhile, an explicit difference method with uniform grid was adopted to solve the phase field and solute field controlled equations. And the alternating direction implicit(ADI) algorithm for solving temperature field controlled equation was also employed to avoid the restriction of time step. Some characteristics of the Ni-Cu alloy were captured in the process of non-isothermal solidification, and the comparative analysis of the isothermal and the non-isothermal solidification was investigated. The simulation results indicate that the non-isothermal model is favorable to simulate the real solidification process of binary alloys, and when the thermal diffusivity decreases, the non-isothermal phase-field model is gradually consistent with the isothermal phase-field model.

采用STAMP-24Model的多组织事故分析

安全生产事故往往由多组织交互、多因素耦合造成,事故原因涉及多个组织。为预防和遏制多组织生产安全事故的发生,基于系统理论事故建模与过程模型(Systems-Theory Accident Modeling and Process,STAMP)、24Model,构建一种用于多组织事故分析的方法,并以青岛石油爆炸事故为例进行事故原因分析。结果显示:STAMP-24Model可以分组织,分层次且有效、全面、详细地分析涉及多个组织的事故原因,探究多组织之间的交互关系;对事故进行动态演化分析,可得到各组织不安全动作耦合关系与形成的事故失效链及管控失效路径,进而为预防多组织事故提供思路和参考。

基于改进24Model-ISM-SNA建筑工人不安全行为关联路径研究

建筑施工现场环境复杂,为有效控制不安全行为发生,基于行为安全“2-4”模型对360份具有代表性的建筑安全事故调查报告进行分析,提取出22个不安全行为的主要影响因素。利用灰色关联分析方法(GRA)改进的集成ISM-SNA模型,将不安全行为风险因素划分为表层、过渡层与深层,然后对风险因素进行可视化分析、中心度分析及凝聚子群分析,揭示了各致因因素间的关联关系和传导路径。结果表明,建筑工人不安全行为影响因素可划分成7级3阶的多级递阶结构,安全意识、现场监管、外部环境是建筑工人不安全行为的关键影响因素,同时现场监管和隐患排查到位能有效降低不安全行为的发生。

基于24Model的地铁内涝事故原因分析与评估

为降低地铁内涝事故灾害风险,基于事故致因“2-4”模型,分析了地铁内涝事故致灾因子,采用层次分析法构建了地铁内涝事故原因分析指标体系,确定了各风险因子的权重,并利用模糊综合评价法对地铁内涝事故进行了定量评估,识别出关键的影响因素。结果表明:地铁内涝事故一级指标中不安全动作与物态因素最重要,其中影响最大的指标包括擅自更改建筑设计、未按照要求检查水位情况、未及时排水、出入口不符合防汛标准等因素;习惯性不安全行为的权重位居第二,表明该指标因素较为重要,同时安全管理体系得分位居第二,表明该指标因素较易发生。对关键指标采取防范措施,可有效降低风险,从而减少地铁内涝事故的发生。

基于24Model-D-ISM的地铁站火灾疏散影响因素研究

为预防地铁站火灾事故,深入了解地铁站火灾人员疏散影响因素间的内在联系与层次结构,基于第6版“2-4”模型(24Model)分析63起地铁站火灾疏散事故,充分考虑各个因素之间的交互作用,提取19个影响地铁站人员疏散的关键因素,建立地铁站火灾人员疏散影响因素指标体系;采用算子客观赋权法(C-OWA)改进决策试验与评价实验法(DEMATEL),确定地铁站火灾人员疏散的重要影响因素;在此基础上,采用解释结构模型(ISM)分析各个因素间的层次结构及相互作用路径,构建地铁站火灾人员疏散影响因素的多级递阶结构模型。研究结果表明:疏散引导、恐慌从众行为、人员拥挤为地铁站火灾人员疏散的关键影响因素;地铁站火灾人员疏散受表层因素、中间层因素、深层因素共同作用的影响,其中,疏散教育与培训、设施维护与检查、疏散预案等因素是根源影响因素,重视根源影响因素的改善有利于从本质上预防和控制事故的发生。

Reaction behavior and non-isothermal kinetics of suspension magnetization roasting of limonite and siderite

In order to develop limonite and decrease CO_(2) emissions,siderite is proposed as a clean reductant for suspension magnetization roasting(SMR) of limonite.An iron concentrate(iron grade:65.92wt%,iron recovery:98.54wt%) was obtained by magnetic separation under the optimum SMR conditions:siderite dosage 40wt%,roasting temperature 700℃,roasting time 10 min.According to the magnetic analysis,SMR achieved the conversion of weak magnetic minerals to strong magnetic minerals,thus enabling the recovery of iron via magnetic separation.Based on the phase transformation analysis,during the SMR process,limonite was first dehydrated and converted to hematite,and then siderite decomposed to generate magnetite and CO,where CO reduced the freshly formed hematite to magnetite.The microstructure evolution analysis indicated that the magnetite particles were loose and porous with a destroyed structure,making them easier to be ground.The non-isothermal kinetic results show that the main reaction between limonite and siderite conformed to the two-dimension diffusion mechanism,suggesting that the diffusion of CO controlled the reaction.These results encourage the application of siderite as a reductant in SMR.

24Model与LCM原因因素定义对比研究

为探究损失致因模型(LCM)原因因素定义与事故致因“2-4”模型(24Model)存在的异同和优缺点,梳理2个模型各层面原因和结果的定义,对比定义内容及其对事故原因分析等安全实务的指导作用,并以一起瓦斯爆炸事故为例加以实证分析,获得二者分析结果之间的差异。研究结果表明:LCM是首个将管理因素纳入事故致因分析的一维事件序列模型,可明确各层面原因因素的定义和因素间的逻辑关系,但部分定义存在交叉重复的问题,并没有揭示安全工作指导思想等深层次事故致因因素;24Model作为系统性事故致因模型,对各类因素的定义均以组织为主体,描述事件、事故、安全的概念内涵,划分个体安全动作、安全能力和组织安全管理体系的类别并给出含义解析,探究组织安全文化层面的问题并以32个元素体现;2个模型的事故原因分析方法均建立在对各层级原因因素定义的基础上,并适用于模型理论体系本身。

Effects of non-isothermal annealing on microstructure and mechanical properties of severely deformed aluminum samples:Modeling and experiment

In order to investigate the evolution of microstructure and flow stress during non-isothermal annealing,aluminum samples were subjected to strain magnitudes of 1, 2 and 3 by performing 2, 4 and 6 passes of multi-directional forging. Then, the samples were non-isothermally annealed up to 150, 200, 250, 300 and 350 ℃. The evolution of dislocation density and flow stress was studied via modeling of deformation and annealing stages. It was found that 2, 4 and 6 passes multi-directionally forged samples show thermal stability up to temperatures of 250, 250 and 300 ℃, respectively. Modeling results and experimental data were compared and a reasonable agreement was observed. It was noticed that 2 and 4 passes multi-directionally forged samples annealed non-isothermally up to 350 ℃ have a lower experimental flow stress in comparison with the flow stress achieved from the model.The underlying reason is that the proposed non-isothermal annealing model is based only on the intragranular dislocation density evolution, which only takes into account recovery and recrystallization phenomena. However, at 350℃ grain growth takes place in addition to recovery and recrystallization,which is the source of discrepancy between the modeling and experimental flow stress.

Quantitative multi-phase-field modeling of non-isothermal solidification in hexagonal multicomponent alloys

A quantitative multi-phase-field model for non-isothermal and polycrystalline solidification was developed and applied to dilute multicomponent alloys with hexagonal close-packed structures.The effects of Lewis coefficient and undercooling on dendrite growth were investigated systematically.Results show that large Lewis coefficients facilitate the release of the latent heat,which can accelerate the dendrite growth while suppress the dendrite tip radius.The greater the initial undercooling,the stronger the driving force for dendrite growth,the faster the growth rate of dendrites,the higher the solid fraction,and the more serious the solute microsegregation.The simulated dendrite growth dynamics are consistent with predictions from the phenomenological theory but significantly deviate from the classical JMAK theory which neglects the soft collision effect and mutual blocking among dendrites.Finally,taking the Mg-6Gd-2Zn(wt.%)alloy as an example,the simulated dendrite morphology shows good agreement with experimental results.

Projecting Wintertime Newly Formed Arctic Sea Ice through Weighting CMIP6 Model Performance and Independence

Precipitous Arctic sea-ice decline and the corresponding increase in Arctic open-water areas in summer months give more space for sea-ice growth in the subsequent cold seasons. Compared to the decline of the entire Arctic multiyear sea ice,changes in newly formed sea ice indicate more thermodynamic and dynamic information on Arctic atmosphere–ocean–ice interaction and northern mid–high latitude atmospheric teleconnections. Here, we use a large multimodel ensemble from phase 6 of the Coupled Model Intercomparison Project(CMIP6) to investigate future changes in wintertime newly formed Arctic sea ice. The commonly used model-democracy approach that gives equal weight to each model essentially assumes that all models are independent and equally plausible, which contradicts with the fact that there are large interdependencies in the ensemble and discrepancies in models' performances in reproducing observations. Therefore, instead of using the arithmetic mean of well-performing models or all available models for projections like in previous studies, we employ a newly developed model weighting scheme that weights all models in the ensemble with consideration of their performance and independence to provide more reliable projections. Model democracy leads to evident bias and large intermodel spread in CMIP6 projections of newly formed Arctic sea ice. However, we show that both the bias and the intermodel spread can be effectively reduced by the weighting scheme. Projections from the weighted models indicate that wintertime newly formed Arctic sea ice is likely to increase dramatically until the middle of this century regardless of the emissions scenario.Thereafter, it may decrease(or remain stable) if the Arctic warming crosses a threshold(or is extensively constrained).

Anisotropic time-dependent behaviors of shale under direct shearing and associated empirical creep models

Understanding the anisotropic creep behaviors of shale under direct shearing is a challenging issue.In this context,we conducted shear-creep and steady-creep tests on shale with five bedding orientations (i.e.0°,30°,45°,60°,and 90°),under multiple levels of direct shearing for the first time.The results show that the anisotropic creep of shale exhibits a significant stress-dependent behavior.Under a low shear stress,the creep compliance of shale increases linearly with the logarithm of time at all bedding orientations,and the increase depends on the bedding orientation and creep time.Under high shear stress conditions,the creep compliance of shale is minimal when the bedding orientation is 0°,and the steady-creep rate of shale increases significantly with increasing bedding orientations of 30°,45°,60°,and 90°.The stress-strain values corresponding to the inception of the accelerated creep stage show an increasing and then decreasing trend with the bedding orientation.A semilogarithmic model that could reflect the stress dependence of the steady-creep rate while considering the hardening and damage process is proposed.The model minimizes the deviation of the calculated steady-state creep rate from the observed value and reveals the behavior of the bedding orientation's influence on the steady-creep rate.The applicability of the five classical empirical creep models is quantitatively evaluated.It shows that the logarithmic model can well explain the experimental creep strain and creep rate,and it can accurately predict long-term shear creep deformation.Based on an improved logarithmic model,the variations in creep parameters with shear stress and bedding orientations are discussed.With abovementioned findings,a mathematical method for constructing an anisotropic shear creep model of shale is proposed,which can characterize the nonlinear dependence of the anisotropic shear creep behavior of shale on the bedding orientation.

Three dimensional phase-field simulation for non-isothermal binary alloy solidification: Comparison with LKT theory

Using the advanced algorithm combining parallel computing,adaptive mesh re-griding and multigrid methods,quantitative 3D phase-field simulations of non-isothermal solidification of binary alloy were carried out.The 3D phase-field simulation results were compared with the analytical LKT(Lipton,Kurz and Trivedi)theory.For comparison,the simulation and analytical results for 2D cases were also given.The 3D phase-field simulation results support the transport portion of the LKT theory.However,the tip radius and tip velocity predicted by the simulations are not in good agreement with the LKT theory over the whole range of undercooling.The stability parameter calculated from phase-field simulations varies significantly with the Peclet number,indicating that the stability criterion,which assumes that the stability parameter is constant,is invalid.

Evolution and Prospects of Foundation Models: From Large Language Models to Large Multimodal Models

Since the 1950s,when the Turing Test was introduced,there has been notable progress in machine language intelligence.Language modeling,crucial for AI development,has evolved from statistical to neural models over the last two decades.Recently,transformer-based Pre-trained Language Models(PLM)have excelled in Natural Language Processing(NLP)tasks by leveraging large-scale training corpora.Increasing the scale of these models enhances performance significantly,introducing abilities like context learning that smaller models lack.The advancement in Large Language Models,exemplified by the development of ChatGPT,has made significant impacts both academically and industrially,capturing widespread societal interest.This survey provides an overview of the development and prospects from Large Language Models(LLM)to Large Multimodal Models(LMM).It first discusses the contributions and technological advancements of LLMs in the field of natural language processing,especially in text generation and language understanding.Then,it turns to the discussion of LMMs,which integrates various data modalities such as text,images,and sound,demonstrating advanced capabilities in understanding and generating cross-modal content,paving new pathways for the adaptability and flexibility of AI systems.Finally,the survey highlights the prospects of LMMs in terms of technological development and application potential,while also pointing out challenges in data integration,cross-modal understanding accuracy,providing a comprehensive perspective on the latest developments in this field.

Development and validation of a prediction model for early screening of people at high risk for colorectal cancer

BACKGROUND Colorectal cancer(CRC)is a serious threat worldwide.Although early screening is suggested to be the most effective method to prevent and control CRC,the current situation of early screening for CRC is still not optimistic.In China,the incidence of CRC in the Yangtze River Delta region is increasing dramatically,but few studies have been conducted.Therefore,it is necessary to develop a simple and efficient early screening model for CRC.AIM To develop and validate an early-screening nomogram model to identify individuals at high risk of CRC.METHODS Data of 64448 participants obtained from Ningbo Hospital,China between 2014 and 2017 were retrospectively analyzed.The cohort comprised 64448 individuals,of which,530 were excluded due to missing or incorrect data.Of 63918,7607(11.9%)individuals were considered to be high risk for CRC,and 56311(88.1%)were not.The participants were randomly allocated to a training set(44743)or validation set(19175).The discriminatory ability,predictive accuracy,and clinical utility of the model were evaluated by constructing and analyzing receiver operating characteristic(ROC)curves and calibration curves and by decision curve analysis.Finally,the model was validated internally using a bootstrap resampling technique.RESULTS Seven variables,including demographic,lifestyle,and family history information,were examined.Multifactorial logistic regression analysis revealed that age[odds ratio(OR):1.03,95%confidence interval(CI):1.02-1.03,P<0.001],body mass index(BMI)(OR:1.07,95%CI:1.06-1.08,P<0.001),waist circumference(WC)(OR:1.03,95%CI:1.02-1.03 P<0.001),lifestyle(OR:0.45,95%CI:0.42-0.48,P<0.001),and family history(OR:4.28,95%CI:4.04-4.54,P<0.001)were the most significant predictors of high-risk CRC.Healthy lifestyle was a protective factor,whereas family history was the most significant risk factor.The area under the curve was 0.734(95%CI:0.723-0.745)for the final validation set ROC curve and 0.735(95%CI:0.728-0.742)for the training set ROC curve.The calibration curve demonstrated a high correlation between the CRC high-risk population predicted by the nomogram model and the actual CRC high-risk population.CONCLUSION The early-screening nomogram model for CRC prediction in high-risk populations developed in this study based on age,BMI,WC,lifestyle,and family history exhibited high accuracy.

Kinetic Modeling of Isothermal or Non-isothermal Adsorption in a Pellet：Application to Adsorption Heat Pumps

Understanding the interaction between a fluid and a solid phase is of fundamental importance to the design of an adsorption process.Because the heat effects associated with adsorption are comparatively large,the as-sumption of isothermal behavior is a valid approximation only when uptake rates are relatively slow.In this article,we propose to determine when it is needed to choose the isothermal or non-isothermal assumption according to two physical parametersα（ratio convection/capacity） andβ（quantity of energy/capacity） .The proposed problem is solved by a mathematical method in the Laplace domain.Whenα→∞（infinitely high heat transfer coefficient） or β→0（infinitely large heat capacity） ,the limiting case is isothermal.When the diffusion is rapid（α10） the kinetics of sorption is controlled entirely by heat transfer.If the adsorption process is to be used as a heat pump,it shall be represented by an isotherm model withαandβas high as possible.

Geostatistical seismic inversion and 3D modelling of metric flow units,porosity and permeability in Brazilian presalt reservoir

Flow units(FU)rock typing is a common technique for characterizing reservoir flow behavior,producing reliable porosity and permeability estimation even in complex geological settings.However,the lateral extrapolation of FU away from the well into the whole reservoir grid is commonly a difficult task and using the seismic data as constraints is rarely a subject of study.This paper proposes a workflow to generate numerous possible 3D volumes of flow units,porosity and permeability below the seismic resolution limit,respecting the available seismic data at larger scales.The methodology is used in the Mero Field,a Brazilian presalt carbonate reservoir located in the Santos Basin,who presents a complex and heterogenic geological setting with different sedimentological processes and diagenetic history.We generated metric flow units using the conventional core analysis and transposed to the well log data.Then,given a Markov chain Monte Carlo algorithm,the seismic data and the well log statistics,we simulated acoustic impedance,decametric flow units(DFU),metric flow units(MFU),porosity and permeability volumes in the metric scale.The aim is to estimate a minimum amount of MFU able to calculate realistic scenarios porosity and permeability scenarios,without losing the seismic lateral control.In other words,every porosity and permeability volume simulated produces a synthetic seismic that match the real seismic of the area,even in the metric scale.The achieved 3D results represent a high-resolution fluid flow reservoir modelling considering the lateral control of the seismic during the process and can be directly incorporated in the dynamic characterization workflow.

耦合优化蚁群算法与P-Median model的选址模型设计

为节省城建部门对于公共体育设施的投入成本以及提高城市人民生活质量,以运动场所优化选址为例,提出一种新型设施选址模型。该模型主要基于P-Median model(最小化阻抗模型)根据需求点数量从全部候选设施选址中选择设施空间位置,让用户达到离自己最近设施距离成本总和最小的目的,对选址的基本原则和实际情况提出要求,构造目标函数用于优化后蚁群算法求解进行选址工作。优化蚁群算法实现基于Python语言模块,通过改进蚁群原始信息素,提升原有算法的收敛速度,求出目标函数最优解,可以很好地模拟对于运动场所的选址。用二者耦合进行优势互补所设计的选址模型来搜寻研究区蚁群信息素浓度残留最大的栅格像元,从而确定未被已有设施点服务半径覆盖的最佳设施点建立位置。实验结果表明,该新型选址模型相较于最小化阻抗模型与最大化覆盖模型,新增优化设施点使整体服务半径覆盖率分别高出10.42%和6.95%,适合求解较为精确且小规模空间下的选址问题。