新一轮科技革命和产业革命的深入推进，正不断重塑全球创新版图，数字化治理已经成为社会治理、经济治理、国防与军队建设等各领域的时代要求。“十四五”规划指出：“迎接数字时代，激活数据要素潜能，推进网络强国建设，加快建设数字经济、数字社会、数字政府，以数字化转型整体驱动生产方式、生活方式和治理方式变革。”面对数字治理这一时代命题，需要从复杂系统理论认知入手，分析数字治理复杂性的基本特征及方法论需求。数字孪生（Digital Twin）把系统工程理论与科学前沿相结合，将作为一种新的技术引擎推动社会治理等关键领域数字治理模式的深刻变革。
一、基于复杂系统理论的数字治理
1. 数字治理的内涵
数字治理是在数字技术条件下，以政府为主导，平台与企业、社会组织、社群、公民个人等多元主体协同参与相关事务的过程和制度安排。它是包含发展的治理，是以公共利益增进、个人福祉提升为目标的治理，是多元主体协同参与、数字化赋能的治理，涉及数字经济、数字社会、数字政府、数字城市等多个领域，呈现出高维度、强关联、多层次、开放性、全局性等特点。
2. 数字治理的复杂性特征
复杂系统理论为解析数字治理问题提供了支点。从系统科学的角度看来，数字治理的主体与对象构成的系统均具备复杂适应系统的特征。一方面，这些系统由大量具备适应性的主体构成，主体能够与环境以及其他主体进行交互，“学习”和“积累经验”，并根据学到的“经验”改变自身结构和行为方式以更好地适应环境。例如，社会系统中的主体——人通过千姿百态的合作、竞争、矛盾、冲突关系，演绎出复杂的交互行为，造就了社会系统的复杂性。另一方面，系统的演进呈现不确定性。不确定性导致“因果不再一一对应，也不会是完全唯一”。经济运行过程受多因素影响且难以准确预测就是复杂系统不确定性的例证。在此情形下，治理的目的是通过化解不确定性来作出更有利的决策。除适应性和不确定性外，治理系统还呈现出层次涌现的特点，即低层次的主体通过相互作用组成更高层次、更复杂的组织，这些组织拥有低层次主体本身不具备的特性。城市本身体现了这种层次涌现性：从小尺度（微观）看，城市的各个子系统（如交通系统）由众多结构各异、行为高度不确定的主体构成，需要大量信息才能描述，复杂度非常高；但从大尺度（宏观）看，我们又可以找到一些简单优美的规律来描述城市，比如城市的规模与其对基础设施需求之间的幂律关系等。
3. 解决复杂性问题的方法论要求
解决复杂性问题需要革新性的方法论。解决复杂的数字治理问题的方法论应当满足以下四个方面的需求：
（1）本质认知
建立复杂系统的科学逻辑，从全局的、联系的、动态的视角，关注治理对象局部与整体、短期与长期、无序与有序、竞争与发展之间的关系，提炼其演化的共性规律。
（2）开放系统
封闭的复杂系统最终会趋于崩溃或消亡，开放的系统才能从周围环境获取能量、正向演进、发展、跃迁。因此在数字治理过程中，要构建开放架构，实现系统要素的有机关联与流动。
（3）虚实共生
数字治理方法应当构建虚实结合的平行系统建模框架，用动态的真实数据支撑对系统运行规律的解析。
（4）动态演进
关注治理对象系统全生命周期演进的过程，提升回顾过去、把握现在、预测未来的能力，为全生命周期的数字治理提供辅助决策支持。
二、数字孪生解决方案
1. 数字孪生的起源
数字孪生最早起源于复杂航天系统工程探索。从1969年NASA的“阿波罗计划”实体孪生体构造，到2003年提出装备数字孪生体来描述实体全生命周期的运行轨迹，2009年DARPA探讨提出“数字孪生范式”，再到现在的广义数字孪生阶段，数字孪生逐步成为一种改造现实世界的通用目的技术。
2. 数字孪生的本质内涵
数字孪生出现的几十年间，得到了学术界、标准化组织、企业的广泛关注，但目前尚无公认的标准定义。理解数字孪生的内涵可从其特征入手。
如图，从对象域看，人、装备、组织、环境、产业或者抽象对象均可作为数字孪生的对象；从要素域看，数字孪生体的属性包括结构、属性、状态、机理、活动、行为及其联系等；从作用域看，物理实体通过建模和物联数据驱动数字孪生体，数字孪生体则依托AI、大数据、仿真等技术，实现对物理实体的反向控制；从成果形式来看，数字孪生体在伴随现实世界运行过程中产生的数据、模型、系统和标准构成与现实世界对应的数字资产，数字孪生体在物理实体真实数据的“喂养”下，成长为自循环、自适应、自学习、自演进的“数字生命体”。
综上，数字孪生具有虚实共生、数据驱动、数字资产、开放架构、生命特征五大特点。它并非单一特定技术，而是提供了一种开放、灵活、弹性的技术框架来不断承载新兴技术，进而涌现出单项技术所不具备的能力，驱动孪生对象不断进化，构造出与现实世界虚实映射的数字空间，在数字空间回溯历史、把握现在、预测未来，提高对复杂系统全生命周期动态演化机理与规律的洞察力与控制力。
3. 数字孪生在不同领域的形态
数字孪生这一方法论与不同领域结合后呈现出不同形态。根据孪生对象的物理特征，可分为部件级、系统级、体系级；根据孪生对象的时空特性，分为历史态、实时态、未来态；根据孪生对象的运行机理，可分为设计态、制造态、运行态。不同行业领域依据其关注的重点，构建不同层级、不同时态、不同状态的数字孪生体，满足不同行业对象全生命周期管理的弹性需求。
4. 数字孪生发展演进
数字孪生是尚处于发展进程中的方法体系，数字孪生应用也存在不同的成熟度等级。当前应用最广的是几何孪生，如在数字孪生城市、数字孪生工厂中运用三维建模工具，描述产品形状、尺寸、位置、装配关系等几何参数，实现“以虚仿实”；在几何孪生之上，融合数据与规则，构建具备较为完整的运动和控制逻辑的模型，接收物理世界的真实数据，实现“以虚控实”；通过数据驱动数字模型与物理实体共生长、共进化，形成可应对不确定性的，具备自学习、自演进能力的数字生命体，“以虚预实”、“以虚优实”，最终达到自主动态孪生的理想状态，实现“虚实共生”。
三、数字孪生驱动数字治理
如前文所述，针对数字治理复杂系统的基本特征，我们可以充分利用数字孪生“由实生虚、以虚控实、虚实互动、共生演进”的特点优势，沿着“理解、认知、计算、模拟、赋能”的链条，用数字孪生驱动数字治理，为数字治理提供基于数字孪生的整体解决方案。
（1）理解
以复杂适应系统理论为基础，挖掘经济、政治、文化、社会、生态文明建设等各个领域数字治理对象的内在复杂规律，使自上而下的数字治理模型与治理对象的发展逻辑与规律相匹配。
（2）认知
从复杂系统运行角度，利用传感器采集、数据融合、数字建模等方法，构建与物理空间实时动态映射的数字空间，形成实体控制环与虚拟试验环双环耦合驱动的系统运行模式。
（3）计算
在虚实映射、双环驱动的过程中，将物理空间反馈的数据、现象、事件等多源异构信息间的逻辑关系转化为可理解、可应用的知识，反映系统内在规律，挖掘“隐秩序”。
（4）模拟
充分发挥数字孪生系统可见、连接、假设、预测的优势，构建经济、社会、城市等治理对象的数字孪生体，实现回顾过去、把握现在、预测未来的治理目标。
（5）赋能
通过上述工作，构建可感知、可理解、可计算、可决策、可进化的数字治理系统，突破当前治理条块分割的现状，众筹群智，统筹协调经济、社会、城市治理，解决应急、交通、防疫、城市生命线等行业痛点问题，提升治理能力体系现代化水平。
四、数字治理实践
截至目前，数字孪生已在国内外顶层战略规划中多次出现，如美国《数字工程战略》，英国《国家数字孪生体原则》、俄罗斯《俄罗斯联邦数字经济规划》、德国工业4.0平台、我国《“十四五”规划》、《数字经济发展规划》等。同时，数字孪生技术已在航空航天、军事作战、工业制造、城市管理、社会治理等领域得到广泛应用，涌现了“机体数字孪生”、“虚拟宙斯盾”、“虚拟新加坡”、“数字孪生生产线”等一系列项目，数字孪生技术应用正焕发勃勃生机。
面向数字治理多个领域需求，航天数字孪生团队从复杂系统全生命周期动态运行视角出发，以数字孪生为引擎，融合人工智能、泛在感知、区块链等前沿技术，打造了数字孪生操作系统（Digital Twin Operating System）——DTOS。
DTOS是运用数字孪生理念设计研发的广义操作系统，以统一的架构和技术规范，集成IoT、AI、仿真、区块链等前沿技术，打通虚实空间壁垒，形成可支撑多领域智慧应用的智能底座。基于DTOS，我们在国家“双智”（智慧城市基础设施与智能网联汽车协同发展）、市域社会治理、数字政府等领域落地应用。构建了城市建筑、车辆、道路、基础设施、社会人群、装备等治理对象的孪生体，不断挖掘、沉淀对各个领域系统的认知，并在此基础上，探索复杂性场景下的系统建模、演化与控制机制，基于“可感、可知、可视、可控”理念，搭建了自适应、自响应、正态反馈的智能化管理系统，支持实时感知-虚实互生-智能分析-一体化指挥运营-一体化交互展示，有效促进了城市交通、地下生命线系统、市域社会治理、低空安全等治理对象的全生命周期管理与服务。
五、结语
数字孪生技术方兴未艾，与数字治理的融合既符合复杂问题的破题需求，又是技术发展的大势所趋。期待与数字孪生技术应用工作委员会以及业界同仁共同探讨，共同推动数字孪生技术在数字治理领域纵深发展。
翻译：
The deepening of the new round of technological and industrial revolution is reshaping the global innovation landscape. Digital governance has become a requirement of The Times in social governance, economic governance, national defense and military construction. The 14th Five-Year Plan points out: “Embrace the digital age, activate the potential of data elements, promote the construction of a strong cyber country, accelerate the construction of digital economy, digital society and digital government, and drive the transformation of the mode of production, way of life and way of governance through digital transformation.”
In the face of the proposition of digital governance, we need to start from the theoretical cognition of complex systems to analyze the basic characteristics and methodological requirements of the complexity of digital governance. Digital Twin combines systems engineering theory with scientific frontier, and will serve as a new technology engine to promote the profound reform of digital governance mode in social governance and other key fields.
Digital governance based on complex system theory
Connotation of digital governance
Under the condition of digital technology, digital governance is a process and institutional arrangement in which the government takes the lead and the platform, enterprises, social organizations, communities, individual citizens and other multiple subjects participate in relevant affairs cooperatively. It is a governance that includes development and aims to enhance public interests and individual well-being. It is a governance that involves the collaborative participation of multiple entities and enables digital empowerment. It involves digital economy, digital society, digital government, digital city and other fields.
Complexity of digital governance
Complex system theory provides a fulcrum for analyzing digital governance problems. From the point of view of system science, the system composed of the subject and object of digital governance has the characteristics of complex adaptive system.
The system composed of the subject and object of digital governance has the characteristics of complex adaptive system.
On the one hand, these systems are composed of a large number of adaptive agents, who can interact with the environment and other agents, “learn” and “accumulate experience”, and according to the “experience” learned, change their structure and behavior to better adapt to the environment. For example, people, the subject of the social system, deduce complex interactive behaviors through various kinds of cooperation, competition, contradiction and conflict relations, resulting in the complexity of the social system.
On the other hand, the evolution of the system presents uncertainty. Uncertainty leads to “cause and effect are no longer one-to-one, nor are they completely unique”. The uncertainty of complex system is exemplified by the fact that the economic operation process is affected by many factors and difficult to predict accurately. In this case, the purpose of governance is to resolve uncertainty to make more favorable decisions. In addition to adaptability and uncertainty, governance systems also show the characteristics of hierarchical emergence, that is, lower-level subjects interact with each other to form higher-level and more complex organizations, which have the characteristics that lower-level subjects themselves do not have.
The city itself reflects this level of emergence:
From a small scale (micro) perspective, each subsystem of the city (such as traffic system) is composed of a large number of subjects with different structures and highly uncertain behaviors, which requires a large amount of information to describe, and is very complex. However, from the large-scale (macro) perspective, we can find some simple and beautiful laws to describe the city, such as the power law relationship between the size of a city and its demand for infrastructure.
Methodological requirements for solving complex problems
Solving complex problems requires innovative methodologies. A methodology for solving complex digital governance problems should address the following four needs:
(1) Essential cognition
Establish the scientific logic of complex systems, focus on the relationship between local and whole, short-term and long-term, disorder and order, competition and development of governance objects from a global, relational and dynamic perspective, and extract the common rules of their evolution.
(2) Open system
The closed complex system will eventually tend to collapse or die out, and only the open system can obtain energy from the surrounding environment, evolve forward, develop and transition. Therefore, in the process of digital governance, an open architecture should be built to realize the organic correlation and flow of system elements.
(3) symbiosis between virtual and real
Digital governance method should build a parallel system modeling framework combining virtual and real data, and use dynamic real data to support the analysis of system operation rules.
(4) Dynamic evolution
Pay attention to the evolution process of the whole life cycle of the governance object system, improve the ability to review the past, grasp the present and predict the future, and provide auxiliary decision support for the whole life cycle of digital governance.
Digital twin solution
Origin of digital twinning
Digital twinning originated from complex space system engineering exploration. From NASA’s “Apollo Project” physical twin construction in 1969, to the proposal of equipped digital twin to describe the operation trajectory of the whole life cycle of the entity in 2003, DARPA discussed and proposed the “digital twin paradigm” in 2009, and then to the present generalized digital twin stage, digital twin has gradually become a general purpose technology to transform the real world.
Essential Connotation of digital twinning
In the past few decades, digital twinning has been widely concerned by academia, standardization organizations and enterprises, but there is no accepted standard definition at present. The connotation of digital twinning can be understood from its characteristics.
As shown in the figure, from the object domain, people, equipment, organization, environment, industry or abstract objects can be regarded as digital twin objects; From the perspective of factor domain, the attributes of digital twins include structure, attribute, state, mechanism, activity, behavior and relation. From the perspective of scope, the physical entity drives the digital twin through modeling and iot data, while the digital twin realizes the reverse control of the physical entity by relying on AI, big data, simulation and other technologies. In terms of the form of results, the data, models, systems and standards generated during the operation of the real world constitute the digital assets corresponding to the real world. The digital twins grow into a self-cycling, self-adaptive, self-learning and self-evolving “digital life” under the “feeding” of the real data of the physical entity.
To sum up, digital twinning has five characteristics: virtual-real symbiosis, data-driven, digital assets, open architecture, and life characteristics. It is not a single specific technology, but provides an open, flexible and elastic technical framework to continuously carry emerging technologies, and then emerge the capabilities that single technologies do not have, drive the continuous evolution of twin objects, construct a digital space mapped with the real world, and in the digital space, recall history, grasp the present and predict the future. Improve the insight and control of dynamic evolution mechanism and law of complex system in the whole life cycle.
The forms of digital twinning in different fields
The methodology of digital twinning shows different forms when combined with different fields. According to the physical characteristics of twin objects, they can be divided into component level, system level and system level. According to the space-time characteristics of the twin objects. They can be divided into historical state, real tense and future state. According to the operation mechanism of the twin object. It can be divided into design state, manufacturing state and running state. According to the focus of different industries, digital twins of different levels, tenses and states are constructed to meet the elastic requirements of the whole life cycle management of objects in different industries.
Development and evolution of digital twin
Digital twinning is a method system still in the process of development. And the application of digital twinning has different maturity levels. At present, geometric twinning is the most widely used. For example, 3D modeling tools are used in digital twinning city and digital twinning factory to describe geometric parameters. Such as product shape, size, position and assembly relation, realizing “imitating real with virtual”.
On the basis of geometric twining, data and rules are fused to build a model with relatively complete motion and control logic. And the real data of the physical world is received to realize “virtual control real”. Through data-driven digital model and physical entity co-grow and co-evolve. A digital living organism capable of self-learning and self-evolution can be formed to cope with uncertainties, “preform reality with virtual” and “optimize reality with virtual”. And finally achieve the ideal state of autonomous dynamic twinism and realize “symbiosis between virtual and reality”.
Digital twinning drives digital governance
As mentioned above, in view of the basic characteristics of the complex system of digital governance. We can make full use of the characteristics and advantages of digital twinning of “generating virtual from real, controlling real with virtual, interacting with virtual and symbiotic evolution”, drive digital governance with digital twinning along the chain of “understanding, cognition, calculation, simulation and empowerment”, and provide an overall solution based on digital twinning for digital governance.
Digital twinning is used to drive digital governance, and an integrated solution based on digital twinning is provided for digital governance.
(1) Understanding
Based on the theory of complex adaptive system, the internal complex laws of digital governance objects in various fields. Such as economy, politics, culture, society and ecological civilization construction are excavated. So as to match the top-down digital governance model with the development logic and laws of governance objects.
(2) Cognition
From the perspective of complex system operation, using sensor acquisition, data fusion, digital modeling and other methods. The digital space of real-time dynamic mapping with physical space is constructed. And the system operation mode driven by the coupling of physical control ring and virtual test ring is formed.
(3) Calculation
In the process of virtual and real mapping and double ring drive, the logical relationship between data, phenomena, events and other heterogeneous information from physical space feedback is transformed into understandable and applicable knowledge, reflecting the internal laws of the system and mining the “hidden order”.
(4) Simulation
Give full play to the advantages of the digital twin system in visibility, connection, hypothesis and prediction, construct the digital twin of governance objects such as economy, society and city. And realize the governance goals of reviewing the past, grasping the present and predicting the future.
(5) Empowerment
Through the above work, we will build a digital governance system that can be perceived, understood, calculated, decisionable and evolved, break through the current fragmented governance status, crowdfund wisdom, coordinate economic, social and urban governance, solve pain points in emergency response, transportation, epidemic prevention, urban lifeline and other industries, and modernize the governance capacity system.
Digital Governance practices
Up to now, digital twinning has appeared many times in top-level strategic planning at home and abroad. Such as the Digital Engineering Strategy of the United States, the National Principle of Digital Twinning of the United Kingdom, the Digital Economy Planning of the Russian Federation of Russia, the Industry 4.0 platform of Germany, the 14th Five-Year Plan and the Digital Economy Development Plan of China. At the same time, digital twin technology has been widely used in aerospace, military operations, industrial manufacturing, urban management, social governance and other fields. A series of projects such as “Organism digital twin”, “Virtual Aegis”, “Virtual Singapore” and “digital twin Production line” have emerged, and the application of digital twin technology is full of vitality.
To meet the needs of multiple fields of Digital governance, the aerospace digital Twin team, starting from the perspective of dynamic operation of complex systems throughout their life cycle, uses digital twin as the engine and integrates cutting-edge technologies. Such as artificial intelligence, ubiquitous perception and blockchain to create a Digital Twin Operating System (DTOS).
DTOS is a generalized operating system designed and developed with the concept of digital twin.
It integrates frontier technologies such as IoT, AI, simulation and blockchain with unified architecture and technical specifications to break through the barriers of virtual and real space and form an intelligent base that can support intelligent applications in multiple fields. Based on DTOS, we have applied in the fields of national “double intelligence” (coordinated development of smart city infrastructure and smart connected vehicles), municipal social governance and digital government.
It constructs twin governance objects. Such as urban buildings, vehicles, roads, infrastructure, social groups and equipment, constantly excavates and precipitates the cognition of systems in various fields. And on this basis, explores the system modeling, evolution and control mechanism in complex scenes. Based on the concept of “perceptible, knowable, visible and controllable”. An intelligent management system with adaptive, self-response and normal feedback is built. Which supports real-time perception, virtual and real interaction, intelligent analysis, integrated command and operation, and integrated interactive display, effectively promoting the whole-life cycle management and service of urban traffic, underground lifeline system, municipal social governance, low-altitude safety and other governance objects.
Conclusion
Digital twin technology is in the ascendant, and the integration of digital governance not only meets the need of solving complex problems. But also the trend of technological development. We look forward to discussing with the Working Committee on the Application of Digital Twin Technology and colleagues in the industry to jointly promote the in-depth development of digital twin technology in the field of digital governance.
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