浅谈21世纪的化学工程

在参考我国化工界已有战略研究的基础上,进一步分析了当前我国社会经济发展需求和世界科技发展的趋势,指出我国化学工程科学正面临难得的发展机遇,同时也面临多方位的挑战。化学工程作为一个共性的工程学科,既要适应其应用领域的扩展,更要充分利用科学技术发展带来的机遇,扩展深化自身的知识基础,为各种物质转化相关领域提供共性的理论、方法和技术。复杂系统理论的发展、计算技术的进步以及测试技术的提升,为化学工程科学的发展提供了新的动力;经济社会的进步,能源、资源与环境问题的突显以及高技术的发展,大大扩展了化学工程服务的领域。我们应当抓住这一机遇,适应这一变化,为解决能源、资源和环境等领域的瓶颈问题,推动高技术的发展做出贡献,开创化学工程新的发展阶段。     

化学产品工程再认识

化学产品工程作为化学工程学科的一个新方向或化学工程学科的新范式已提出很多年,但学术界对其学科内涵理解不一。本文对化学产品工程的学科内涵进行了分析和探讨,认为其核心是通过过程和设备对产品的纳微结构和复杂大分子结构进行调控;化学产品工程仍隶属过程工程,是面向高附加值产品、实现产品结构可控、定向、高效制备的过程工程。通过与传统的以满足市场需求和提高生产效率为目标的过程开发和放大的化学工程研究类比,提出了化学产品工程的主要研究内容,并讨论了其研究的方法论问题,以推动相关的基础研究工作。     

Whither chemical engineering?

The 1988 Amundson Report on research needs in chemical engineering encouraged the pursuit of frontier areas in chemical engineering with the warning, however, that attention to core areas must be preserved. Indeed, the strong core base in chemical engineering during the latter half of the 20th century enabled chemical engineers to contribute extensively to many areas outside of the traditional. The depth of such involvement has led researchers to confront questions much more engaging to the field of application. This effort has led to adopting and cultivating expertise more native to the field of application than to secure chemical engineering as a discipline. It therefore seems appropriate to ask if the warning voiced in the Amundson Report needs to be reiterated. If chemical engineering research must leave a strong trail of fundamental understanding through developed methodologies to ensure continuing progress, then this article yields considerable scope for discussion.     

化学工业多尺度融合的智能制造模式——互联化工

化工过程通过物质和能量的可控转化和传递来实现化工产品制备,具有多相性、非线性、非平衡、多尺度和多时空域等特性,化工行业智能制造发展的关键是实现多尺度条件下的互联协同与过程高效。一方面,化工过程多尺度互联机制的认识和调控是化工过程系统的安全可靠运行的关键;另一方面,实现化工过程多尺度下的互联、融合与协同是化工产业绿色发展的路径。鉴于此,本文提出了化学工业面向多尺度融合的智能制造模式——互联化工,给出了“互联化工”的概念、目标、特点和架构,并讨论了互联化工的相关关键技术,包括化学工业多层级的信息物理系统、云制造,以及全生命周期的安全管理技术、耦合互锁机制下的动态安全监控与决策模型、基于区块链的互联化工数据安全技术。     

Mastering digitized chemical engineering

This paper highlights the importance of digitalization in chemical engineering industries, in the frame of Industry 4.0, and the consequences on the employability and profession of chemical engineers. Training content must necessarily evolve to meet industry expectations and maintain the level of innovation required to meet the challenges of the future such as competitiveness, global warming, or depletion of resources. Higher Education Institutions must evolve, and digitalization also makes it possible to provide new training methods and tools that will help the teachers to face these challenges.     

A paradigm-based evolution of chemical engineering

A short presentation of chemical engineering evolution,as guided by its paradigms,is exposed.The first paradigm–unit operations–has emerged as a necessity of systematization due to the explosion of chemical industrial applications at the end of 19th century.The birth in the late 1950s of the second paradigm–transport phenomena–was the consequence of the need for a deep,scienti fic knowledge of the phenomena that explain what happens inside of unit operations.In the second part of 20th century,the importance of chemical product properties and qualities has become essentially in the market fights.Accordingly,it was required with additional and even new fundamental approaches,and product engineering was recognized as the third paradigm.Nowadays chemical industry,as a huge materials and energy consumer,and with a strong ecological impact,couldn't remain outside of sustainability requirements.The basics of the fourth paradigm–sustainable chemical engineering–are now formulated.     

辐射化工培养模式的实践与探索

人才培养的关键之一是要有一个适合的培养模式。针对辐射化工的特殊性,从课程体系设置、创新思维、课程设计、仿真和实践教学等方面分析了如何培养学生的积极性和主动性,为培养创新性的辐射化工应用型人才奠定基础。     

R. Byron Bird: The integration of transport phenomena into chemical engineering

This article, as is this issue of the AIChE Journal, is a tribute to R. Byron Bird, who has had a profound impact on the discipline of chemical engineering, playing a dominant role in the chemical engineering science paradigm shift that occurred around 1960. His textbook, Transport Phenomena, with Warren Stewart and Edwin Lightfoot, fundamentally changed the way chemical engineers are taught fluid mechanics, heat transfer, and mass transfer. By showing the interconnections among molecular, microscopic, and macroscopic treatments of these three transport processes, as well as the underlying similarities among the three transport processes, he has enabled chemical engineers to contribute to many new areas. In his research he has focused on polymeric fluids – their rheology and fluid mechanics – again spanning molecular to macroscopic problems. Bird is also known throughout the profession as a superb teacher and lecturer. He is gifted in languages and music, and he has a great love of the outdoors. In this article, I try to highlight some of Bird's history and accomplishments in these many areas. His influence is clear in the papers that follow. © 2014 American Institute of Chemical Engineers AIChE J, 60: 1219–1224, 2014     

Electro-membrane reactor: A powerful tool for green chemical engineering

Electro-membrane reactors use electro-membranes for preferentially diffusive/electrophoretic migration or electroosmotic separation of in-situ reactive products, thereby maximizing the reaction rate and transport efficiencies of the products. These reactors are widely employed in the chemical engineering sectors such as green chemical synthesis, biorefining, electrocatalytic reduction/oxidation, and water treatment. In this review article, we provide an overview of the recent advances in three categories of electro-membrane reactors in chemical engineering sectors from three categories: (1) Electro-membrane reactors based on stacked ion-exchange membranes for resources recovery; (2) Electro-membrane reactors via Faraday reactions on functional anodes/cathodes for substance transformation; and (3) Closed-loop chemical reactions and substance separation via coupling of Faraday reactions and stacked membranes. The increasing demand for low-carbon economy has accelerated the advancement of environmentally friendly chemical engineering and sustainable processes and necessitates the use of electro-membrane processes. The macro perspective provides a timely reference for researchers and engineers.     

试论绿色化工技术在化学工程与工艺中的应用

绿色化工技术是基于生态理念基础上产生的新技术,在化工工程生产与工业生产中应用具有重要作用。通过强化绿色化工技术合理应用,能满足化工生产与工艺生产各项要求,对环境污染等各项问题进行有效调控。     

材料化学工程的应用及发展趋势研究

我国社会经济的快速发展得益于各项科学技术地进步,而其中有一种全世界都非常关注的科学技术,那就是材料化学,其对于国家的国防实力和能源发展都有着积极的意义。良好的材料化学工程发展,一方面增强了国防的实力,另一方面能够提升能源利用效率。因此,相关研究人员关注材料化学工程的应用及发展趋势的研究,对于促进其发展进步有着极强的现实意义,可以为更好地发掘材料化学工程价值,提供更多资料。从材料化学工程的应用说起,介绍了材料化学工程的实验室,分析了材料化学工程发展前景。     

化工园区多Agent协同应急智能决策体系

在应急响应不同阶段中,化工园区路网均处于应急救援与应急疏散等多种智能体（Agent）同步异构的活动状态,仅考虑单Agent在特定阶段的应急决策,难以为园区应急响应提供全方位支持。为探究园区应急响应全过程中各Agent的决策模型及其信息协同关系,本文基于混合式多Agent系统思想构建化工园区多Agent协同应急智能决策体系。首先,对应急响应4个等级进行改进,提出混合式智能决策体系框架;其次,对化工园区多Agent应急决策时空变化关系进行了分析,将园区多Agent应急响应全过程分为园区企业内部应急响应、园区内部应急响应、园区内外协同应急响应3个阶段;最后,基于混合式多Agent系统（MAS）与协同理论,构建基于三层应急智能决策模型的化工园区多Agent信息共享关系与协同模式,所提出的化工园区混合式三层多Agent应急响应全过程智能决策体系能够为化工园区应急决策提供重要的理论基础和技术支持。     

科研成果向《化工原理》课程内容的二次转化

为了发挥石油院校的行业特色,结合本校在精馏技术及设备、流态化工程及装备等方面的科研成果,对化工原理课程内容进行了更新,对丰富教材内容、激发学生的求知欲、培养师资队伍等方面起到了积极作用。     

数值积分在化工计算中的应用

本文介绍了数值积分的必要性和几种常用的数值积分方法,列举了数值积分在吸收塔填料层高度计算和反应器有效体积计算中的应用,说明了数值积分在化工计算中的意义。     

Convolutional neural nets in chemical engineering: Foundations,computations, and applications

In this article, we review the mathematical foundations of convolutional neural nets (CNNs) with the goals of: (i) highlighting connections with techniques from statistics, signal processing, linear algebra, differential equations, and optimization, (ii) demystifying underlying computations, and (iii) identifying new types of applications. CNNs are powerful machine learning models that highlight features from grid data to make predictions (regression and classification). The grid data object can be represented as vectors (in 1D), matrices (in 2D), or tensors (in 3D or higher dimensions) and can incorporate multiple channels (thus providing high flexibility in the input data representation). CNNs highlight features from the grid data by performing convolution operations with different types of operators. The operators highlight different types of features (e.g., patterns, gradients, geometrical features) and are learned by using optimization techniques. In other words, CNNs seek to identify optimal operators that best map the input data to the output data. A common misconception is that CNNs are only capable of processing image or video data but their application scope is much wider; specifically, datasets encountered in diverse applications can be expressed as grid data. Here, we show how to apply CNNs to new types of applications such as optimal control, flow cytometry, multivariate process monitoring, and molecular simulations.