钛合金的定量研究进展

钛合金因其优异的综合性能受到国内外研究者和使用者的青睐,其基础和应用技术研究的核心是针对"合金成分-工艺-组织-性能"之间关系的研究。以往钛合金的成分设计、工艺-组织-性能间关系的研究都是定性的,获得了良好的结果,并得到了实际应用。"合金成分-工艺-组织-性能"之间的定量关系研究是近几年国内外钛合金研究的一个热点,已取得一定的进展。综述了高强钛合金的成分定量设计、工艺-组织-性能间定量关系建立的研究进展,主要包含高强钛合金成分的定量设计方法、微观组织的定量表征方法、组织与性能定量关系建立、工艺与性能的定量关系建立等,并通过实际验证。     

深海装备耐压结构用钛合金材料应用研究

本文概述了国内外钛合金深海装备的发展现状,针对深海服役环境特点对耐压结构用钛合金材料的性能要求进行了分析,介绍了典型装备耐压结构钛合金材料研究应用中出现的应力腐蚀和蠕变等技术问题,提出需要针对钛合金材料长期服役时存在的组织演变和性能衰减、冲击环境下的动态响应等基础科学问题开展研究,重点梳理工程应用中的大规格材料、应用评价和高效建造等关键技术。文章建议针对深海领域钛合金装备的迫切需求,进一步加大钛合金材料基础研究和工程化应用力度,推动创新应用,践行海洋强国战略。     

高性能钛合金的关键“基因”及高通量实验与计算技术的应用

加快高性能钛合金的研发速度、降低研发成本对我国高端装备制造至关重要。作为关键结构材料,强度、塑性与韧性是保障钛合金构件安全运行的关键力学性能指标。通过高通量计算可预测合金的模量、比热、热膨胀系数等多种物理性能指标,但是对于强度、塑性与韧性等力学性能指标尚缺少预测模型和公式,原因是力学性能间接依赖合金的化学成分,直接影响力学性能的因素是合金的微观组织。高性能钛合金的关键"基因"是成分、相/组织结构与晶体缺陷。高通量计算和扩散多元节建立合金成分与相的对应关系,相场动力学计算与模拟实现对相与微观组织演化的预测,通过微纳尺度力学性能测试技术获得微观组织结构的力学性能数据。期望通过以上各环节研究结果与数据的有机整合,建立钛合金成分、相与微观组织、力学性能数据库,有助于提升高性能钛合金的研发速度,满足我国关键技术领域对先进钛合金的需求。     

模糊控制与神经网络的研究与应用

模糊控制和神经网络在系统辨识与控制、模式识别、信号处理等各个领域中都获得广泛的应用,尤其在工业控制领域方面获得更加有效的应用。结合模糊控制和神经网络各自的优点,将模糊技术与神经网络技术进行有机结合,从而构造出一种可自动处理模糊信息的神经网络或自适应模糊系统。     

典型α+β钛合金组织对静态和动态性能的影响

α+β钛合金具有优异的综合性能,在航空航天、生物医学、船舶及国防工业等领域得到了广泛的应用.α+β钛合金的强度、塑性、冲击韧性以及断裂韧性主要取决于其内部的显微组织.因此,阐明α+β钛合金组织和性能之间的关系,对设计性能优异的材料至关重要.本文主要综述了TC21、TC4、TC11、TC4-DT等典型两相钛合金的组织与静态和动态力学性能之间关系的研究进展,并指出研究中存在的问题,以期为获得两相钛合金的理想显微组织和优异的力学性能提供理论指导.     

油气开发用钛合金油井管选材及工况适用性研究进展

钛合金材料由于具有高比强度、低弹性模量,优异的韧性、疲劳性能和耐蚀性,已经成为严酷工况环境下油井管和海洋开发工具的热门候选材料。目前国内外很多研究机构和学者都开展了用于油气开发领域的钛合金材料的研究,包括钛合金石油管的可行性、钛合金管材的制备加工、实验室内钛合金性能评价以及钛合金管材的现场应用等方面。然而,我国油气开发环境较为恶劣,油井管在井下服役不但要面临高温高压的挑战,还要经受硫化氢、二氧化碳、高浓度盐水/完井液、单质硫和强酸等腐蚀环境的共同作用,因此我国对油井管的要求高于国外一般水平。此外,钛合金是钛含量大于50%的金属的总称,仅我国国标所列举的不同成分钛合金就多达76种。这些已经标准化的钛合金材料大多用于航空航天、石化炼化、生物医学、船舶以及海洋工程领域,这些应用环境和油气开发环境具有巨大的区别,已有牌号的钛合金能否适用于油气开发工况尚不得而知。国内有关钛合金油井管在硫化氢、二氧化碳、高浓度盐水/完井液、单质硫和强酸环境下服役的研究报道和应用经验都较为缺乏,导致油气开发油井管用钛合金材料在选择和使用上存在风险,为了防止钛合金在应用时出现大的安全事故而造成生命财产的损失,迫切需要结合国内外研究经验对可用于油气开发环境的钛合金材料进行筛选和评价,明确每种钛合金材料的工况适用性和使用极限,以保证其使用的安全可靠性。本文在国外近30年已发表的钛合金油井管相关研究成果和国内钛合金油井管最新研究进展的基础上,总结了油气开发用钛合金油井管选材经验,并对七种典型钛合金材料在油气开发工况下的适用性和使用极限做出了归纳总结,分析了钛合金油井管要真正实现大规模应用面临的问题并展望了前景,以期为油气开发用钛合金材料的选用提供参考。     

航空用损伤容限型钛合金研究与应用

为了满足新型飞机的大尺寸、高减重、长寿命和低成本的设计与应用需求,采用损伤容限型钛合金材料及其应用技术是一条重要途径。国外发达国家已经在新型损伤容限型钛合金材料研制和在先进飞机上的应用方面走在了前列,特别是像中强度的Ti-6Al-4VELI和高强度的Ti-6-22-22S等,已经成功地应用在了美国F-22/F-35,C-17等新一代飞机中,大大地提高了飞机的使用寿命和战斗力。这几年我国先后自主创新发展了中强度损伤容限型钛合金TC4-DT和高强度损伤容限型钛合金TC21,建立了损伤容限型钛合金的β处理加工技术,为我国新型飞机的研制奠定了材料应用技术基础。通过分析国内外损伤容限型钛合金材料及其新型加工工艺技术的研究发展情况,结合我国新型损伤容限型钛合金材料研究进展,重点探讨了新型损伤容限型钛合金的材料特点、性能水平和应用前景。     

不锈钢和钛合金异种金属焊接研究进展

不锈钢和钛合金异种焊接在化工、航空和核工业等领域均有广泛的应用,但不锈钢和钛合金因理化性能的差异,焊接界面常形成大量脆性金属间化合物,无法得到优质的焊接结果。以扩散焊、激光焊和电子束焊为主总结了不同焊接方法的工艺参数和接头组织成分对不锈钢和钛合金焊接质量的影响,展望了不锈钢与钛合金异种金属焊接的发展趋势。     

生物医用亚稳β钛合金的研究进展EI北大核心

钛及钛合金具有高比强度、低的弹性模量、无磁性以及优异的生物相容性和耐腐蚀性能等特点,被认为是理想的生物医用金属材料。以无毒性的Nb,Mo,Ta,Zr和Sn等作为主要合金化元素,并具有更低弹性模量的亚稳β型钛合金是新一代医用钛合金材料的重点发展方向。本文综述了生物医用钛合金的基本特性和发展概况,并以Ti-Nb基医用钛合金为例,介绍了新型亚稳β生物医用钛合金的成分设计方法、合金化原理、研究现状和制备技术。最后指出进一步降低弹性模量,提高强度、疲劳性能和功能特性等综合性能是生物医用β钛合金重点的发展方向,今后可以针对合金化元素的交互作用机理、合金成分设计与组织性能调控方法以及微观力学机制等问题开展深入研究。     

生物医用亚稳β钛合金的研究进展

钛及钛合金具有高比强度、低的弹性模量、无磁性以及优异的生物相容性和耐腐蚀性能等特点，被认为是理想的生物医用金属材料。以无毒性的Nb, Mo, Ta, Zr和Sn等作为主要合金化元素，并具有更低弹性模量的亚稳β型钛合金是新一代医用钛合金材料的重点发展方向。本文综述了生物医用钛合金的基本特性和发展概况，并以Ti-Nb基医用钛合金为例，介绍了新型亚稳β生物医用钛合金的成分设计方法、合金化原理、研究现状和制备技术。最后指出进一步降低弹性模量，提高强度、疲劳性能和功能特性等综合性能是生物医用β钛合金重点的发展方向，今后可以针对合金化元素的交互作用机理、合金成分设计与组织性能调控方法以及微观力学机制等问题开展深入研究。     

A study on the prediction of mechanical properties of titanium alloy based on adaptive fuzzy-neural network

An important trend in material research is to predict mechanical properties for a new titanium alloy before committing experimental resources. Often the prediction of mechanical properties of these alloys changes depending on their chemical composition and processing methods. Therefore, modeling the relationship between composition and property is crucial to the engineering. This study employs an adaptive fuzzy-neural network approach to predict the mechanical properties of titanium alloys. In adaptive fuzzy-neural network, to reduce the complexity of fuzzy models while keeping good model accuracy, a fuzzy clustering algorithm and a back-propagation learning algorithm are introduced to improve the accuracy of the simple model. For purpose of constructing this model, experimental results for 57 specimens with 14 different chemical compositions were gathered from the literature. The chemical composition contents were employed as the inputs while yield strength, tensile strength, elongation and reduction of area, which were employed as the outputs. Thus, the model can be trained by using the prepared training set. After training process, the testing data were used to verify model accuracy. It is found that there is insignificant difference between predict results and experimental value and the maximum relative error is less than 9%. It proved that the predictive performance of the clustering-based adaptive fuzzy-neural network modeling is available and effective in simulating the composition content and predicting the mechanical properties of titanium alloys.     

空调系统神经模糊控制器——结构和算法

提出了一种适用于空调系统控制的新型神经模糊控制器。这种神经模糊控制器将神经网络和模糊控制紧密结合，是一种以神经网络表示模糊控制规则的模糊控制系统，控制推理基于模糊推理的精确值法，神经网络采用后向传播（BP）学习算法。本文论述这种神经模糊控制器的结构和算法，其仿真和优化将另文论述。     

Influence of parameters of modifying oxygen-containing atmosphere on oxynitriding of titanium alloys

We study the influence of the parameters of modifying oxygen-containing atmosphere (the degree of rarefaction, temperature and time of modification) on the oxynitriding of titanium alloys. It is shown that, as the degree of rarefaction of the atmosphere increases and the temperature of modification decreases, the process of phase formation on the surface of titanium alloys evolves in the direction of formation of oxynitrides, whereas the period of modification does not affect the structural and phase state. As the oxygen content decreases, the composition of titanium oxynitride approaches the equiatomic composition. This guarantees the increase in surface microhardness and the improvement of the corrosion resistance of titanium alloys in oxygen-free acids.     

生物医学钛合金的研究现状及发展趋势

本文在回顾生物医学钛合金发展历史的基础上 ,综述了国外近年来新开发的生物医学钛合金的组成及性能 ,提出了我国生物医学钛合金的发展方向。     

MOCVD外延生长Ga_(1-x)Al_xAs_(1-y)Sb_y半导体薄膜气固平衡和人工神经网络预报

本文研究了ＭＯＣＶＤ外延生长Ｇａ１－ｘＡｌｘＡｓ１－ｙＳｂｙ半导体薄膜的生长条件与外延层组成的关系，并用人工神经网络法总结有关气固平衡规律。结果表明，用气相组成，载气流量和生长温度等影响外延层组成的主要参数作为人工神经网络的输入，以固相Ｇａ１－ｘＡｌｘＡｓ１－ｙＳｂｙ中的Ａｌ和Ｓｂ的含量ｘ、ｙ作为输出，训练的人工神经网络可以预报固相组成ｘ、ｙ，得到满意结果。     

Optimization of chemical composition for TC11 titanium alloy based on artificial neural network and genetic algorithm

It is quite difficult for materials to develop the quantitative model of chemical elements and mechanical properties, because the relationship between them presents the multivariable and non-linear. In this work, the combined approach of artificial neural network (ANN) and genetic algorithm (GA) was employed to synthesize the optimum chemical composition for satisfying mechanical properties for TC11 titanium alloy based on the large amount of experimental data. The chemical elements (Al, Mo, Zr, Si, Fe, C, O, N and H) were chosen as input parameters of the ANN model, and the output parameters are mechanical properties, including ultimate tensile strength, yield strength, elongation and reduction of area. The fitness function for GA was obtained from trained ANN model. It is found that the percentage errors between experimental and predicted are all within 5%, which suggested that the ANN model has excellent generalization capability. The results strongly indicated that the proposed optimization model offers an optimal chemical composition for TC11 titanium alloy, which implies it is a novel and effective approach for optimizing materials chemical composition.     

Titanium alloy production technology,market prospects and industry development

Titanium alloy with a low density, high specific strength, corrosion resistance and good process performance, is the ideal structural materials for the aerospace engineering. Based on the microstructure of titanium alloys, it can be divided into α-type titanium alloys (heat-resistant titanium alloys), β-type titanium alloys and α + β-type titanium alloys. The research scopes also include the fabrication technology of titanium alloys, powder metallurgy, rapid solidification technology, and other military and civilian applications of titanium alloys. Titanium and its alloys have become the ideal structural materials used for the fuselage, and accounted for a significant part of the structural quality in most military aircrafts. Titanium’s future market expectations need to be considered in the macro level market. Apart from the supply and demand trends of titanium market, it is necessary to consider the impact of technological innovations that can help to reduce the cost of titanium production.     

Self-organizing maps for pattern recognition in design of alloys

A combined experimental–computational methodology for accelerated design of AlNiCo-type permanent magnetic alloys is presented with the objective of simultaneously extremizing several magnetic properties. Chemical concentrations of eight alloying elements were initially generated using a quasi-random number generator so as to achieve a uniform distribution in the design variable space. It was followed by manufacture and experimental evaluation of these alloys using an identical thermo-magnetic protocol. These experimental data were used to develop meta-models capable of directly relating the chemical composition with desired macroscopic properties of the alloys. These properties were simultaneously optimized to predict chemical compositions that result in improvement of properties. These data were further utilized to discover various correlations within the experimental dataset by using several concepts of artificial intelligence. In this work, an unsupervised neural network known as self-organizing maps was used to discover various patterns reported in the literature. These maps were also used to screen the composition of the next set of alloys to be manufactured and tested in the next iterative cycle. Several of these Pareto-optimized predictions out-performed the initial batch of alloys. This approach helps significantly reducing the time and the number of alloys needed in the alloy development process.     

Prediction of the mechanical properties of forged Ti–10V–2Fe–3Al titanium alloy using FNN

In this paper, a fuzzy neural network (FNN) prediction model has been employed to establish the relationship between processing parameters and mechanical properties of Ti–10V–2Fe–3Al titanium alloy. In establishing these relationships, deformation temperature, degree of deformation, solution temperature and aging temperature are entered as input variables while the ultimate tensile strength, yield strength, elongation and area reduction are used as outputs, respectively. After the training process of the network, the accuracy of fuzzy model was tested by the test samples and compared with regression method. The obtained results with fuzzy neural network show that the predicted results are much better agreement with the experimental results than regression method and the maximum relative error is less than 7%. And the optimum matching processing parameters can be quickly selected to achieve the desired mechanical property based on the fuzzy model. It proved that the model has a good precision and excellent ability of predicting.     

定向凝固钛铝合金熔体与铸型界面反应研究展望

钛铝合金是性能优异的高温合金,在航空航天领域有广泛的应用前景,但由于其熔体具有较高的活性,制备时熔体与所有已知的铸型材料会发生不同程度的反应,限制了钛铝合金铸件的发展.定向凝固技术作为制备高精度钛铝合金的新工艺,使铸件组织定向排列,可以进一步提高钛铝合金的使用性能,因此如何调控凝固过程中钛铝合金熔体与铸型材料间的界面反应成为目前有关定向凝固钛铝合金研究的一个热点.从目前国内外关于钛铝合金熔体与铸型材料间界面反应的研究出发,综述了定向凝固过程中铸型材料、涂层成分、工艺参数及合金元素等对界面反应的影响,介绍了界面反应的理论水平,系统收集了界面反应的各项研究结果.