Combining reinforcement learning with mathematical programming:An approach for optimal design of heat exchanger networks

Heat integration is important for energy-saving in the process industry.It is linked to the persistently challenging task of optimal design of heat exchanger networks(HEN).Due to the inherent highly nonconvex nonlinear and combinatorial nature of the HEN problem,it is not easy to find solutions of high quality for large-scale problems.The reinforcement learning(RL)method,which learns strategies through ongoing exploration and exploitation,reveals advantages in such area.However,due to the complexity of the HEN design problem,the RL method for HEN should be dedicated and designed.A hybrid strategy combining RL with mathematical programming is proposed to take better advantage of both methods.An insightful state representation of the HEN structure as well as a customized reward function is introduced.A Q-learning algorithm is applied to update the HEN structure using theε-greedy strategy.Better results are obtained from three literature cases of different scales.

Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

Accelerating Factor Xa inhibitor discovery with a de novo drug design pipeline

Small-molecule drugs are essential for maintaining human health. The objective of this study is to identify a molecule that can inhibit the Factor Xa protein and be easily procured. An optimization-based de novo drug design framework, Drug CAMD, that integrates a deep learning model with a mixed-integer nonlinear programming model is used for designing drug candidates. Within this framework, a virtual chemical library is specifically tailored to inhibit Factor Xa. To further filter and narrow down the lead compounds from the designed compounds, comprehensive approaches involving molecular docking,binding pose metadynamics(BPMD), binding free energy calculations, and enzyme activity inhibition analysis are utilized. To maximize efficiency in terms of time and resources, molecules for in vitro activity testing are initially selected from commercially available portions of customized virtual chemical libraries. In vitro studies assessing inhibitor activities have confirmed that the compound EN300-331859shows potential Factor Xa inhibition, with an IC_(50)value of 34.57 μmol·L^(-1). Through in silico molecular docking and BPMD, the most plausible binding pose for the EN300-331859-Factor Xa complex are identified. The estimated binding free energy values correlate well with the results obtained from biological assays. Consequently, EN300-331859 is identified as a novel and effective sub-micromolar inhibitor of Factor Xa.

Decomposition of Mathematical Programming Models for Aircraft Wing Design Facilitating the Use of Dynamic Programming Approach

Aircraft designers strive to achieve optimal weight-reliability tradeoffs while designing an aircraft. Since aircraft wing skins account for more than fifty percent of their structural weight, aircraft wings must be designed with utmost care and attention in terms of material types and thickness configurations. In particular, the selection of thickness at each location of the aircraft wing skin is the most consequential task for aircraft designers. To accomplish this, we present discrete mathematical programming models to obtain optimal thicknesses either to minimize weight or to maximize reliability. We present theoretical results for the decomposition of these discrete mathematical programming models to reduce computer memory requirements and facilitate the use of dynamic programming for design purposes. In particular, a decomposed version of the weight minimization problem is solved for an aircraft wing with thirty locations (or panels) and fourteen thickness choices for each location to yield an optimal minimum weight design.

C++程序设计课程“一项三联”教学目标实现新举措

课程思政和OBE理念教学是教育部对新工科教师提出的新要求。为了将C++程序设计的课程教学、课程思政和OBE三者完美融合呈现给学生,该文提出“一项三联”的教学方法,即以一个项目贯穿C++整个授课过程,实现课程教学、课程思政和OBE紧密联系的教学方法,该方法增加学生学以致用的学习兴趣,提升教学、思政效果,实现学生运用计算机编程技术解决复杂实际问题的能力。

Design of Aided Decision-Making Program for Prioritizing Construction Projects in Urban Road Network Planning

The importance and complexity of prioritizing construction projects (PCP) in urban road network planning lead to the necessity to develop an aided decision making program (ADMP). Cost benefit ratio model and stage rolled method are chosen as the theoretical foundations of the program, and then benefit model is improved to accord with the actuality of urban traffic in China. Consequently, program flows, module functions and data structures are designed, and particularly an original data structure of road ...

基于可靠性的液化气体运输船新颖C型货物围护系统设计衡准

从结构可靠性分析方法入手,分析液化气体运输船新颖C型货物围护系统的载荷、抗力和模型的随机性。建立新颖C型货物围护系统的极限状态方程,参照国际船级社协会新编的《C型独立液货舱的屈服、屈曲和疲劳评估的有限元分析流程建议》(Recommendation No.174)的相关要求开展新颖构造货物围护系统有限元计算和可靠度分析方法研究,对新颖C型货物围护系统(双体罐和三体罐)进行应力分析和可靠性计算。采用可靠性的第一水准法构建新颖C型货物围护系统的设计衡准,并确定各分项系数,研究结果为制定符合可靠性标准的新颖C型货物围护系统规范和基于可靠性方法的结构强度准则提供参考。

基于VB的滚动轴承CAPP系统设计与实现

为了提高滚动轴承工艺设计效率和准确性,利用Access建立轴承工艺标准数据库,实现轴承工艺数据信息的存储和管理,利用VB编程语言对Access系统内存储的数据信息进行关联调用,最终以Excel形式呈现,并通过设计友好的人机交互界面,实现用户与软件系统的良好沟通,最终开发出VB和Access两者有机结合的滚动轴承工艺设计与管理应用软件,实现轴承工艺数据信息的存储、查询、更新、生成与应用,进一步提升轴承工艺设计、管理的质量和效率。

基于C++的金属丝线屈服曲线的设计与实现

在工业生产实践中,金属丝线折弯成型是常见的加工工艺过程.例如:弹簧机将钢丝压出弹簧,眼镜绕框机将框丝绕出眼镜框型等.该类设备都有一个送丝机构,将直的金属丝推入由动、静轮为主要部件构成的成型机构中挤压变形,从而加工出不同形状、不同大小的框型产品.以自动眼镜绕框机系统为例,说明金属框丝形变与动轮压力角度之间函数关系的建立及使用C++语言实现过程.

基于机器视觉和PLC的活体小龙虾分拣控制系统

针对目前小龙虾人工分拣精度不够,成本过高的问题,构建了一种基于视觉检测的小龙虾分拣系统,对小龙虾分拣系统的原理进行简要分析,完成了系统各部分的硬件选型,设计了基于Linux系统的上位机与PLC的通讯程序,采集小龙虾图片样本并识别小龙虾种类,编写PLC程序实现了对小龙虾种类的准确识别与快速分选。实验结果表明,该系统识别准确率高,自动化程度高,能节约大量的人力成本与时间成本。

碳笼负载镍基磁性催化剂Ni@Cage-C的制备与性能研究

以自然结晶法制备的ZIF-67为前驱体,采用包裹-刻蚀-碳化策略,得到大小均匀的纳米碳笼(Cage-C),再于液相条件下以碳笼为载体负载上活性金属镍(Ni),成功制备了非贵金属磁性催化剂Ni@Cage-C,并应用于对硝基苯酚催化还原反应以考察其多相催化性能。结果表明:优化条件下制备的Ni@Cage-C催化剂为碳笼包裹单质镍结构,其平均颗粒大小为550 nm;将Ni@Cage-C用于对硝基苯酚催化还原反应时,催化性能明显优于参照催化剂雷尼镍(Raney-Ni)。质量反应速率常数kM为6.11 mg^(-1)·min^(-1),催化效率达到98.87%,循环反应十圈后活性仍高于初始活性的85%。

基于TouchDesigner视觉编程技术的粤剧数字化设计创新

目的探究TouchDesigner视觉化编程技术于粤剧当代发展中的数字化设计创新路径。方法分析粤剧的数字化发展现状,探讨TouchDesigner视觉化编程技术与粤剧的数字化转换关系,从而研究粤剧的可数字化元素及TouchDesigner技术的数据转换方法。分析当下数字技术介入粤剧的研究现状,并总结特点与不足,从中发现TouchDesigner编程技术之于粤剧的数字化创新突破口。最后通过TouchDesigner介入粤剧的数字化设计实践与案例剖析,探索多元交互与沉浸式表现技术中的粤剧多重感官体验形式,探究粤剧数字化设计的多维表达方式。结论为粤剧的当代发展提供一种融媒体、跨感官的交互式数字化设计创新方法,实现粤剧数字化创新表达,同时,也为传统文化的数字化设计注入中国式血液,进而引发对未来智能场景下粤剧数字化设计创新的新思考。

流程图转换在C语言翻转课堂教学中的应用研究

“C语言程序设计”是高等院校计算机相关专业的必修基础课,具有很强的理论性和实践性。在教学中应用流程图转换方法,研究C语言学习认知过程中的记忆形成规律,对正强化学习模式、翻转课堂教学的构建和形成具有重要意义。这有助于帮助学生形成自主学习的有效方法,实现探究型学习,使其获得学习成就感,激发学生自主学习的兴趣和积极性,并促进学生形成编程素养。

基于C#的最佳抵偿高程面选取软件设计与应用

规范规定建立或选择平面坐标系统的前提条件是测区内投影所引起的长度变形不大于25 mm/km。某测区公路工程施工控制网采用国家坐标系不能满足这一要求,为减小高斯投影长度变形所带来的影响,本研究选用膨胀椭球与重心坐标不变法建立工程抵偿坐标系,并基于C#语言进行抵偿坐标系最佳抵偿面选取软件设计。研究结果表明,该计算方法严密、可靠,软件计算结果快速准确,可以实现抵偿坐标计算的自动化处理,能够满足规范要求,可直接应用于工程生产。

基于C语言的高校虚拟实验室平台研究

伴随着信息技术的迅猛进步,我国高校实验教学领域面临资源紧张、教学模式单一等挑战。为了提高实验教学品质,推动教学革新,文章设计并实现了一套基于C语言的高校虚拟实验室平台。该平台通过模拟实际实验环境,为高校学生提供了便捷且高效的实验学习体验。文章阐述了平台的设计理念、基础架构、功能模块以及实现流程,对平台性能进行了测试和优化。

Improved design of reconfigurable frequency response masking filters based on second-order cone programming

In order to improve the design results for the reconfigurable frequency response masking FRM filters an improved design method based on second-order cone programming SOCP is proposed.Unlike traditional methods that separately design the proposed method takes all the desired designing modes into consideration when designing all the subfilters. First an initial solution is obtained by separately designing the subfilters and then the initial solution is updated by iteratively solving a SOCP problem. The proposed method is evaluated on a design example and simulation results demonstrate that jointly designing all the subfilters can obtain significantly lower minimax approximation errors compared to the conventional design method.

基于密封特性的弹簧金属C形环结构参数优化

C形环在密封过程中存在低应力区,这些区域难以保证密封可靠性,因此研究C形环密封特性时,需要分析有效接触应力和区域。选取外径为318 mm的C形环为研究对象,利用等效壁厚代替螺旋弹簧丝径,建立C形环等效模型,通过压缩回弹试验验证了模型的合理性。利用有限元方法研究银层厚度、包覆层厚度以及等效壁厚(弹簧丝径)对C形环密封性能的影响。结果表明:银层表面有效接触宽度随着银层厚度、包覆层厚度的增加而增大,有效接触应力随银层厚度、包覆层厚度的增加而减小,等效壁厚的增加可同时增加有效接触宽度和有效接触应力。采用正交试验对C形环的结构参数进行优化设计。结果表明:银层厚度和等效壁厚对有效接触应力和有效接触宽度影响显著。C形环最优设计方案为银层厚度0.2 mm,包覆层厚度0.5 mm,弹簧丝径3.1 mm,泄漏率试验结果表明,优化后C形环具有更好的密封性能。

Detecting Design Patterns in Object-Oriented Program Source Code by Using Metrics and Machine Learning

Detecting well-known design patterns in object-oriented program source code can help maintainers understand the design of a program. Through the detection, the understandability, maintainability, and reusability of object-oriented programs can be improved. There are automated detection techniques;however, many existing techniques are based on static analysis and use strict conditions composed on class structure data. Hence, it is difficult for them to detect and distinguish design patterns in which the class structures are similar. Moreover, it is difficult for them to deal with diversity in design pattern applications. To solve these problems in existing techniques, we propose a design pattern detection technique using source code metrics and machine learning. Our technique judges candidates for the roles that compose design patterns by using machine learning and measurements of several metrics, and it detects design patterns by analyzing the relations between candidates. It suppresses false negatives and distinguishes patterns in which the class structures are similar. As a result of experimental evaluations with a set of programs, we confirmed that our technique is more accurate than two conventional techniques.

宇航用总线型上注刷新ASIC的设计

当前宇航任务中,SRAM型FPGA易受到单粒子效应的影响,造成非预期的功能失效。为消减单粒子效应的影响、减小FPGA在轨维护重复开发和测试的工作量,设计了一款支持多种总线、适配多型FPGA和存储器的上注刷新ASIC芯片,用于完成FPGA的程序加载、动态刷新、程序上注等操作。首先介绍了ASIC系统层级、模块层级设计、工作流程规划,并简述了ASIC抗单粒子原理。通过对通信协议的兼容设计,ASIC同时支持CAN总线、RS485总线;通过对FPGA配置位流结构分析,ASIC支持9种FPGA的加载和刷新,并实现国产兼容;通过对存储器数据格式转换,ASIC能够在BPI Flash、SPI Flash、PROM等多种存储器中存储配置位流;对刷新的触发、SEFI检测、刷新的执行进行了论述。对影响ASIC上注速度的因素进行了分析和仿真验证;使用原型验证板、ASIC验证板配合可插拔的FPGA、存储器上浮小板完成流片前后的各项功能验证,验证结果符合预期。评估刷新的效果并与其他在轨维护方案进行对比,总线型FPGA上注刷新ASIC具有一定优势,可以高效、可靠地满足宇航FPGA的多种在轨维护需求。

基于CFD模拟与数学规划法的熔融聚合物流动管道设计优化

在满足产能和合理的管道压降范围下,如何降低熔融聚合物在熔体管道中黏度降问题是熔体流动管道设计的关键因素。本研究基于计算流体力学(CFD)的方法,对熔体流经管道发生热降解过程进行数值模拟,并在此基础上提出了混合整数非线性规划(MINLP)模型和非连续性非线性规划(DNLP)模型,分别对熔体管道进行设计与布局优化。分析实际算例的数值模拟结果发现,优化后的管道相较于原管道黏度降减小3.48%,同时出口的压降分布范围减小了60.47%,出口的压降分布更加均匀。结果表明,综合利用模拟方法与数学规划模型可实现熔融聚合物流动管道的自动化设计及优化。