科创中国

“百名科学家讲党课”

主题：新型建造模式与工程装备

主讲人：卞永明

中国工程机械学会 理事长

同济大学 教授

国家级机械实验教学示范中心 主任

重大工程施工技术与装备教育部工程研究中心 主任

“青托人才沙龙”

报告一：形状记忆合金组织调控、响应预测与高性能制造

Microstructure regulation, response prediction and high-performance manufacturing of shape memory alloy

主讲人：萧遥 博士

同济大学  研究员

中国科协第八届青年托举人才工程入选者

摘要：金属材料是人类生产和生活的重要物质基础。在智能化的时代背景下，形状记忆合金作为一种典型的智能材料在航天航空、临床医疗、机械传动、土木工程等领域的驱动、感知、控制、减震等方面得到了越来越多的应用。本次报告将概述形状记忆合金的变形机制、发展现状与应用场景；介绍形状记忆合金功能疲劳以及基于微结构调节的控抑方法；阐述考虑力学失稳的形状记忆合金本构理论，用于揭示该材料复杂的热力响应演化行为；分享形状记忆合金增材制造的最新突破。

Metallic materials are the fundamental basis for production and life of human beings. In the historical background of intellectualization, shape memory alloy, which is a typical intelligent material, is increasingly applied as actuator, sensor, controller and damper in aerospace, clinical medicine, mechanical transmission, civil engineering and other fields. In this speech, deformation mechanisms, development status and application scenarios of shape memory alloys will be overviewed; the functional fatigue of shape memory alloy and the control method based on microstructure regulation will be introduced; constitutive theory of shape memory alloy that considers mechanical instability will be presented to reveal the complex evolution of thermomechanical response; the most recent breakthrough in additive manufacturing of shape memory alloy will be shared.

报告二：群系统可靠性工程与应用

Cluster-system reliability engineering and application

主讲人：蔡伟 博士

燕山大学  讲师

中国科协第九届青年托举人才工程入选者

摘要：提出复杂系统可靠性领域新的研究思路“群系统”，克服传统寿命预测方法对研究经验、样本数量和故障数据的依赖，实现复杂系统寿命实时分析，成果服务中国天眼、千吨级桥梁运载施工装备的可靠性保障。

The research team has proposed a new research approach in the field of complex system reliability called "cluster-system", which overcomes the dependence of traditional life prediction methods on research experience, sample size, and fault data. It achieves real-time analysis of complex system life. The results serve the reliability guarantee of FAST telescope and thousand ton bridge construction equipment.

报告三：超精密全陶瓷轴承关键技术

Key Technology of Ultra-Precision Full Ceramic Bearings

主讲人：闫广宇 博士

沈阳建筑大学  副教授

中国科协第九届青年托举人才工程入选者

摘要：氮化硅/氧化锆等工程陶瓷材料具有重量轻、热膨胀系数低、抗磁干扰、绝缘性能高、耐磨损、耐腐蚀、耐高温等优良特性。全陶瓷球轴承是指内外圈及滚动体均为工程陶瓷材料，该类轴承可广泛应用于机床工业、航空航天、海洋科技、核工业、医疗器械、低温工程等新技术领域，应用前景广阔。课题组面向新一代飞行器在超低温、真空极端工况下对超高精度全陶瓷轴承的需求，开展全陶瓷轴承关键组件的精密加工及装配工艺研究，研究其服役性能，获得抑制裂纹扩展、防止发生断裂的临界加工条件。研究陶瓷滚动体精密研磨方法与研磨工艺。围绕工程陶瓷基体金刚石-石墨自润滑涂层制备技术及服役性能展开应用基础研究。针对结构复杂、性能优异、应用广泛的全陶瓷球轴承搭建试验平台，为全面提升我国超高精度全陶瓷轴承制造及检测水平提供先进基础工艺和产业技术基础。

Engineering ceramics such as silicon nitride/zirconia have excellent characteristics such as light weight, low coefficient of thermal expansion, anti magnetic interference, high insulation performance, wear resistance, corrosion resistance, and high temperature resistance. Full ceramic ball bearings refer to engineering ceramic materials used for both the inner and outer rings and rolling elements. This type of bearing can be widely used in new technological fields such as machine tool industry, aerospace, marine technology, nuclear industry, medical equipment, low-temperature engineering, etc., with broad development prospects. The research group aims to meet the demand of the new generation of aircraft for ultra-precision full ceramic bearings under extreme conditions of ultra-low temperature and vacuum. The research group conducts precision machining and assembly technology research on key components of full ceramic bearings, studies their service performance, and obtains critical machining conditions to suppress crack propagation and prevent fracture. The precision grinding methods and processes for ceramic rolling elements, basic research on the preparation technology and service performance of diamond-graphite self-lubricating coatings on engineering ceramic substrates are conducted. To build a testing platform for full ceramic ball bearings with complex structures, excellent performance, and wide applications, which provide advanced basic processes and industrial technology foundation for improving the manufacturing and testing level of ultra-high precision full ceramic bearings in our country.

报告四：面向工业控制的端到端决控技术研发与应用

End-to-End Decision and Control Technology for Industrial Control

主讲人：段京良 博士

北京科技大学  副教授

中国科协第九届青年托举人才工程入选者

摘要：无人化是地面运载与作业装备的发展趋势。现阶段智能驾驶作业系统智能化水平较低，但是决策、规划、控制等模块仍然严重依赖人工规则和在线优化，缺乏利用数据进行闭环迭代的能力，这导致行车作业过程的智能性仍然不足。与之相比，以全模块神经网络化为特征的“端到端”自动驾驶作业系统，因神经网络具有充分的训练自由度，使得全栈模块具备利用数据闭环进行快速更新的能力，这为高级别自动驾驶作业的智能性提升提供一条全新的技术路径。面向这一技术发展趋势，申请人重点突破决策、规划与控制领域的神经网络设计与训练难题，研发了综合性能国际领先的数据驱动强化学习算法（DSAC），设计了具有动作平滑特性的控制型神经网络架构（LipsNet），开发了自主知识产权的最优控制策略近似求解器（GOPS）。以此为基础，研制了首个从传感器原始数据到执行器控制指令的全栈神经网络化自动驾驶系统，完成了城市工况开放道路的实车测试验证。此外，相关工作正在向以铲运机、掘进台车为代表的凿岩设备拓展。

Unmanned operation is the trend in the development of ground transportation and operating equipment. At the current stage, the level of intelligence in autonomous driving operation systems is relatively low. Modules such as decision-making, planning, and control still heavily rely on manual rules and online optimization, lacking the capability to utilize data for closed-loop iteration, which results in insufficient intelligence in driving operations. In contrast, "end-to-end" autonomous driving operation systems characterized by full-module neural network implementation, due to the neural network's extensive training flexibility, enable full-stack modules to utilize data in a closed loop for rapid updates, providing a novel technical pathway for enhancing intelligence in high-level autonomous driving operations.In line with this technological trend, the applicant has made key breakthroughs in the challenges of neural network design and training within the fields of decision-making, planning, and control. They have developed a data-driven reinforcement learning algorithm (DSAC) with internationally leading comprehensive performance, designed a control-type neural network architecture (LipsNet) with smooth action characteristics, and developed an optimal control policy solver (GOPS) with independent intellectual property rights. Based on this, the first full-stack neural network automated driving system, from raw sensor data to actuator control commands, has been developed and tested in real vehicle trials on open urban roads. Additionally, related work is expanding to rock drilling equipment represented by loaders and drill jambo.