基于卓越工程师教育的频率特性分析课堂教学研究

频率特性分析在工程应用中具有重要的作用,在电路分析、模拟电子技术、信号与系统、自动控制理论等相关课程中都涉及到相关章节内容,在不同课程中如何根据工程应用和学生学习阶段把握具体的讲解内容和讲解方式非常重要。本文从频率特性的求解方法和具体物理意义角度开展在不同课程中讲解的方法,从时域和频域角度分别讨论其物理意义和具体的分析方法。通过渐进深化的教学过程和教学方法不断提高学生的知识掌握和应用技能,提高学生的工程意识、工程素质和工程创新能力,强化学生对于频率特性课程知识的综合应用能力。     

Susceptor-assisted fast microwave sintering of TiN reinforced SiAlON composites in a single mode cavity

In the present study, 17 wt % TiN reinforced α-β SiAlON composites were sintered at low temperature by susceptor-assisted microwave heating. The effect of TiN addition on dielectrical properties of starting powders, as well as the influence of sintering temperature on phase evolution, microstructure development and mechanical properties of α/β-SiAlON-TiN composites were investigated. The obtained results showed that TiN addition increased the microwave absorbing properties which is reflected in the peak sintering temperature. Thus, the α:β ratio decreased and mechanical properties were improved, especially the fracture toughness of the composites. Furthermore, an estimate of energy consumption during microwave assisted sintering at the laboratory scale is presented. As a result, the highest values for relative density (97.1%), Vickers hardness (13.35 ± 0.47 GPa), and fracture toughness (7.52 ± 0.54 MPa m^1/2) were obtained by microwave sintering for 30 min at 1300 °C.     

企业思想政治教育系统设计

为进一步提升企业思想政治教育工作的信息化水平,本文详细介绍了企业思想政治教育系统的数据库设计方案,以便更加充分地发挥各种多媒体教学设备在企业思想政治教育工作方面的优势。     

A practical development of engineering simulation-assisted educational AR environments

Engineering simulations have opened several gates for today’s chemical engineers. They are powerful tools to provide technical content as physics-based numerical solvers. Augmented reality (AR) and virtual reality (VR), on the other hand, are already underway to digitize environments in many fields. The combination of AR/VR environments and simulations in engineering education has been attracting widespread interest. Literature has demonstrated a massive amount of digital educational environments in several contexts as being complementary to conventional educational methods. Nevertheless, hosting technical content produced by engineering simulations with educational AR/VR is still challenging and requires expertise from multiple disciplines throughout the technical development. Present work provides a facile and agile methodology for low-cost hardware but content-wise rich AR software development. Inspired by the Covid-19 pandemic, a case study is developed to teach chemical-engineering concepts using a liquid-soap synthesis process. Accordingly, we assess and conclude the digital development process to guide inexperienced developers for the digitalization of teaching content. The present contribution serves as an example of the power of integrating AR/VR with traditional engineering simulations for educational purposes. The digital tool developed in this work is shared in the online version.     

致密砂岩油藏能量补充方式评价及优化

针对致密砂岩油藏大规模体积压裂开发后能量补充困难的问题,利用自主设计制作的大型人造三维岩心物理模型和物理模拟实验舱,开展致密砂岩油藏能量补充方式优化研究。实验结果表明:致密砂岩油藏压裂开发过程中,地层能量损耗严重,采取注水或注气的方式可有效进行能量补充;地层中裂缝规模越大,越有利于原油渗流,后续补充能量的传播范围越广,有助于进一步提高原油采收率;从提高驱油效率和扩大波及系数方面优选吞吐渗吸介质,CO₂均优于活性水,CO₂吞吐开发在矿场试验中取得了显著的增油效果,因此,CO₂吞吐作为一种有效的能量补充方式在致密油开发中展现了良好的应用前景。该文分析了致密砂岩储层水平井压裂开发的渗流规律,优选出致密砂岩储层大规模压裂开发后最佳渗吸介质,可为致密砂岩油藏开发设计提供重要的理论依据。     

电磁场与电磁波课程思政教学改革探索与实践

课程思政作为思想政治理论课程的有效补充，是落实立德树人根本任务的重要组成。《电磁场与电磁波》是物理、电类等专业的重要专业基础课程，深入挖掘其课程思政元素,能够发挥专业课程的隐性育人作用，实现知识传授、能力培养与价值引领的有机融合，对于理工科专业课进行课程思政改革具有现实指导作用。     

Effect of utilization of hydrogen-rich reformed biogas on the performance and emission characteristics of common rail diesel engine

The utilization of renewable gaseous fuels in the diesel engine has gained significant interest in recent years due to its clean-burning nature and higher availability. In this study, hydrogen-rich reformed biogas was used as a gaseous fuel in a common rail diesel engine with diesel as pilot fuel. The hydrogen-rich reformed gas was synthesized through dry-oxidative reforming. The experimentations were performed in the load range from 6 to 24 N m with two different flow rates of gaseous fuel (0.5 and 1.5 kg/h) at a constant speed of 1800 RPM. The effects on engine performance parameters (brake thermal efficiency, brake specific energy consumption, and brake specific diesel consumption), combustion parameters (rate of pressure rise and maximum heat release rate) and emission parameters (Unburnt hydrocarbons, nitrogen oxides, carbon monoxide, and carbon dioxide) were assessed. The induction of gaseous fuel led to an increase in brake thermal efficiency by 10.5%, reduction in brake specific energy consumption by 13.6%, and a reduction of 26.4% in brake specific diesel consumption with a flow rate of 0.5 kg/h when compared to diesel-only mode at 24 N m load. The HC, NO_X and CO₂ emissions were reduced by 18.2%, 7.4% and 1.4% with a flow rate of 0.5 kg/h when compared to diesel-only mode at 24 N m load due to lower availability of carbon content in the combustible mixture. The utilization of renewable fuel like hydrogen-rich reformed biogas has great potential for overcoming the issue related to both biogas and hydrogen in diesel engines. Moreover, the higher diesel substitution also demonstrates the potential for cost-saving and fossil fuel conservation.     

A survey on tracking control of unmanned underwater vehicles: Experiments-based approach

This paper aims to provide a review of the conceptual design and theoretical framework of the main control schemes proposed in the literature for unmanned underwater vehicles (UUVs). Additionally, the objective of the paper is not only to present an overview of the recent control architectures validated on UUVs but also to give detailed experimental-based comparative studies of the proposed control schemes. To this end, the main control schemes, including proportional–integral–derivative (PID) based, sliding mode control (SMC) based, adaptive based, observation-based, model predictive control (MPC) based, combined control techniques, are revisited in order to consolidate the principal efforts made in the last two decades by the automatic control community in the field. Besides implementing some key tracking control schemes from the classification mentioned above on Leonard UUV, several real-time experimental scenarios are tested, under different operating conditions, to evaluate and compare the efficiency of the selected tracking control schemes. Furthermore, we point out potential investigation gaps and future research trends at the end of this survey.     

Deterministic and probabilistic ship pitch prediction using a multi-predictor integration model based on hybrid data preprocessing,reinforcement learning and improved QRNN

The deterministic and probabilistic prediction of ship motion is important for safe navigation and stable real-time operational control of ships at sea. However, the volatility and randomness of ship motion, the non-adaptive nature of single predictors and the poor coverage of quantile regression pose serious challenges to uncertainty prediction, making research in this field limited. In this paper, a multi-predictor integration model based on hybrid data preprocessing, reinforcement learning and improved quantile regression neural network (QRNN) is proposed to explore the deterministic and probabilistic prediction of ship pitch motion. To validate the performance of the proposed multi-predictor integrated prediction model, an experimental study is conducted with three sets of actual ship longitudinal motions during sea trials in the South China Sea. The experimental results indicate that the root mean square errors (RMSEs) of the proposed model of deterministic prediction are 0.0254°, 0.0359°, and 0.0188°, respectively. Taking series #2 as an example, the prediction interval coverage probabilities (PICPs) of the proposed model of probability predictions at 90%, 95%, and 99% confidence levels (CLs) are 0.9400, 0.9800, and 1.0000, respectively. This study signifies that the proposed model can provide trusted deterministic predictions and can effectively quantify the uncertainty of ship pitch motion, which has the potential to provide practical support for ship early warning systems.     

基于改进SOA-VMD的磁声发射信号去噪算法

磁声发射（MAE）是铁磁性材料磁化过程中产生的声发射信号，在构件应力检测和微观损伤检测中有着广泛的应用。针对MAE信号非稳态、复杂性、衰减性等特点，提出海鸥算法结合变分模态分解（SOA-VMD）的去噪方法，为克服海鸥算法求解过程中易陷入局部最优解问题，利用柯西变异算子产生随机迭代过程，使改进算法即柯西变异海欧算法（CVSOA）跳出早熟收敛。采用以幅值谱熵为适应度函数，优化VMD算法中分解模态个数K和二次惩戒因子α两个参数，将含噪声的MAE信号进行VMD分解重构。经仿真信号和实际检测信号分析表明，改进后的CVSOA-VMD算法全局寻优能力和去噪性能优于传统的SOA-VMD算法，降噪后的MAE信号特征值对于不同应力下均方根、偏斜度特征值的重复性更好，可靠性更高。