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三峡电站 1

严重事故 1

临界热流密度 1

压水堆 1

地质灾害 1

块体加固 1

布置 1

排沙排漂 1

泥石流 1

浅埋 1

滑坡 1

熔池形成 1

熔池热工水力学 1

熔融物堆内滞留 1

碎片云；超高速撞击；图像处理；损伤估计 1

碎片床再熔化 1

碎片床形成 1

蜗壳埋设 1

超高速撞击；变分贝叶斯；稀疏表示；损伤评估 1

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Windborne debris damage prediction analysis

Fangfang SONG, Jinping OU,

《结构与土木工程前沿（英文）》 2010年第4卷第3期页码 326-330 doi: 10.1007/s11709-010-0067-5

摘要： Windborne debris is one of the most important causes of the envelop destruction according to the post-damage investigations. The problem of windborne debris damage could be summarized as three parts, including windborne debris risk analysis, debris flying trajectories, and impact resistance of envelope analysis. The method of debris distribution is developed. The flying trajectories of compact and plate-like debris are solved by using a numerical method according to the different aerodynamic characteristics. The impact resistance of the envelopes is also analyzed. Besides, the process of windborne debris damage analysis is described in detail. An example of industrial building is given to demonstrate the whole method by using the observed data of typhoon Chanchu (2006). The method developed in this paper could be applied to risk assessment of windborne debris for structures in wind hazard.

关键词： typhoon windborne debris structural envelopes damage estimation

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GIS-based numerical simulation of Amamioshima debris flow in Japan

Jian WU, Guangqi CHEN, Lu ZHENG, Yingbin ZHANG

《结构与土木工程前沿（英文）》 2013年第7卷第2期页码 206-214 doi: 10.1007/s11709-013-0198-6

摘要： Debris flow is a rapid flow which could lead to severe flooding with catastrophic consequences such as damage to properties and loss of human lives. It is important to study the movement of debris flow. Since during a debris flow process, the erosion and deposition processes are important, the no entrainment assumption is not acceptable. In this study, first we considered the debris flow as equivalent fluid and adopted the depth-averaged govern equations to simulate the movements and evolution of river bed. Secondly, the set of partial differential equations was solved numerically by means of explicit staggered leap-frog scheme that is accurate in space and time. The grid of difference scheme was derived from GIS raster data. Then the simulation results can be displayed by GIS and easily used to form the hazard maps. Finally, the numerical model coupled with GIS is applied to simulate the debris flow occurred on Oct. 20th, 2010, in Amamioshima City, Japan. The simulation reproduces the movement, erosion and deposition. The results are shown to be consistent with the field investigation.

关键词： debris flow numerical simulation GIS movement erosion deposition

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Analysis of molten metal spreading and solidification behaviors utilizing moving particle full-implicit method

《能源前沿（英文）》 2021年第15卷第4期页码 959-973 doi: 10.1007/s11708-021-0753-0

摘要： To retrieve the fuel debris in Fukushima Daiichi Nuclear Power Plants (1F), it is essential to infer the fuel debris distribution. In particular, the molten metal spreading behavior is one of the vital phenomena in nuclear severe accidents because it determines the initial condition for further accident scenarios such as molten core concrete interaction (MCCI). In this study, the fundamental molten metal spreading experiments were performed with different outlet diameters and sample amounts to investigate the effect of the outlet for spreading-solidification behavior. In the numerical analysis, the moving particle full-implicit method (MPFI), which is one of the particle methods, was applied to simulate the spreading experiments. In the MPFI framework, the melting-solidification model including heat transfer, radiation heat loss, phase change, and solid fraction-dependent viscosity was developed and implemented. In addition, the difference in the spreading and solidification behavior due to the outlet diameters was reproduced in the calculation. The simulation results reveal the detailed solidification procedure during the molten metal spreading. It is found that the viscosity change and the solid fraction change during the spreading are key factors for the free surface condition and solidified materials. Overall, it is suggested that the MPFI method has the potential to simulate the actual nuclear melt-down phenomena in the future.

关键词： molten metal spreading solidification particle method severe accident fuel debris decommissioning

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基于图像处理的超高速撞击碎片云的动态建模与损伤估计 Research Article

曾入,宋燕,吕伟臻

《信息与电子工程前沿（英文）》 2022年第23卷第4期页码 555-570 doi: 10.1631/FITEE.2100049

摘要：由于难以从实验中获得高质量碎片云图像，对薄板上超高速撞击产生的碎片云进行轨迹建模和有效损伤估计一直是一项具有挑战性的任务。为提高超高速撞击对典型双层板防护结构损伤的估计精度，本文结合传统数值分析结果，利用图像处理技术，研究了连续阴影图中碎片云的分布特征。本文的目标是从图像处理获取的阴影图中提取碎片云的目标运动参数，并构建轨迹模型用来估计损伤。在超高速撞击实验中，我们从超高速序列激光阴影成像设备中获得8个连续阴影图片帧，从中选择4个具有代表性的帧用于后续特征分析。然后，利用去噪和分割等图像处理技术，从连续图像帧中提取特殊碎片特征。在提取的信息基础上，进行碎片图像匹配，并根据匹配的碎片对碎片云的轨迹进行建模。本文方法获得的结果与传统数值推导结果的对比表明，从图像处理中获取超高速撞击实验数据的方法可以为改进数值模拟方法提供关键信息。最后，基于所构建的模型，提出一种改进的后壁损伤估计方法。估计的损坏与后墙实际损坏情况的对比证明了所提模型的有效性。

关键词：碎片云；超高速撞击；图像处理；损伤估计

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压水堆熔融物堆内滞留策略：历史回顾与研究展望 Review

马卫民,元一单,Bal Raj Sehgal

《工程（英文）》 2016年第2卷第1期页码 103-111 doi: 10.1016/J.ENG.2016.01.019

摘要：

本文对广泛应用于第三代压水堆的严重事故缓解措施——熔融物堆内滞留(IVR)进行了历史回顾。IVR策略最早源自于第二代反应堆Lovissa VVER-440的改进设计，以应对堆芯熔化事故。随后，IVR策略被应用于许多新设计的反应堆，如西屋的AP1000、韩国的APR1400以及中国的先进压水堆CAP1400和华龙一号。对IVR策略有效性影响最大的因素分别为堆内堆芯熔化进程、熔融物加载于压力容器壁面的热流密度和压力容器外部冷却。对于堆芯熔化进程，过去人们一直仅关注压力容器下腔室内熔池的换热行为。但通过回顾与分析，本文认为堆内的其他现象，如堆芯的降级和迁移、碎片床的形成及其可冷却性以及熔池的动态形成过程等，可能也会对熔池的最终状态及其作用于下封头的热负荷产生影响。通过对相关研究的回顾，本文希望找出IVR策略的研究中有待完善的部分，并据目前发展水平提出未来IVR研究的需求。

关键词：压水堆严重事故熔融物堆内滞留碎片床形成碎片床再熔化熔池形成熔池热工水力学临界热流密度

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人工智能在空间碎片对航天器损伤评估中的应用 Editorial

包为民1,殷春2,黄雪刚3,易伟4,Sara DADRAS5

《信息与电子工程前沿（英文）》 2022年第23卷第4期页码 511-514 doi: 10.1631/FITEE.2220000

摘要： Since the first artificial satellite was launched in 1957, increasing human space activities have led to a deteriorating space debris environment. A huge amount of tiny space debris (from millimeter to micron level) appears in the Earth’s orbit, and its hypervelocity impact will cause serious damage to the structure and functional units of the spacecraft, including cabin’s outer surface, thermal barrier materials, thermal control coatings, solar panels, pipes, and cables. To ensure the safe operation of spacecraft and the completion of space missions, it is necessary to detect and evaluate the impact damage caused by space debris to provide risk warning and timely repair. Due to the complex outer surface materials of spacecraft and the unpredictability of impact damage events, the collected damage detection data present various complex characteristic information. Traditional damage identification and evaluation methods based on manual extraction of feature parameters have difficulty in accurately describing the above complex feature information. In recent years, the application of artificial intelligence (AI) technology in space debris impact perception, damage detection, risk assessment, etc. has begun to receive extensive attention from scholars and engineers, and some breakthroughs have been made in solving such very difficult engineering and technical problems. However, there are still many difficult problems to be solved in the application of AI technology to deal with the issue of space debris. With this background, several important tendencies have emerged in the use of AI methods for spacecraft damage detection and evaluation. 1. Various AI learning algorithms (such as neural networks and deep learning) are used and combined to effectively detect and classify damage features. AI learns in a variety of ways, and each learning algorithm is good at solving different problems. Combining multiple AI learning algorithms in different scenarios can improve detection efficiency and classify damage features. 2. Modifications and enhancements to the learning algorithm are explored to perform damage pattern recognition and evaluation more accurately and effectively. To improve the performance of the learning algorithm, modifications and enhancements are essential. Modifications and enhancements to the algorithm itself, including the setting of the loss function, optimization of iterative steps, and judgment of termination conditions, will have a significant impact on the performance of the learning algorithm. In addition, the complex learning algorithm network itself has a large number of parameters that need to be optimized. In fact, the optimization method of network parameters has become one of the core factors that determine the performance of the learning algorithm. 3. AI learning algorithms and models should preferably be extended to suit spacecraft damage detection and evaluation systems. In combination with specific spacecraft damage detection and assessment systems, existing learning algorithms and models can be extended by, e.g., preprocessing the actual input test data to obtain better algorithm iterative calculation results, classifying different damage detection scenarios, applying different optimization modules to obtain better performance comparison test results, and giving reasonable classification criteria for damage assessment results. 4. AI technology is used to analyze the data characteristics of various spacecraft impact damage samples to guide the space debris protection design of spacecraft. The advantage of AI technology is that it can analyze typical characteristics from a large number of data samples. By analyzing the impact damage samples of various types of spacecraft and according to the detection data characteristics under different impact conditions, researchers can obtain the damage type and damage degree of the spacecraft’s space debris protection structure. Therefore, engineers can improve the safety of spacecraft in orbit by optimizing the protective structure of the spacecraft. 5. AI technology is used to model and analyze space debris to realize the monitoring, early warning, mitigation, and removal of space debris to reduce the impact of space debris on spacecraft. Using AI technology to model and analyze space debris has a stronger expressive ability, which can express complex and qualitative empirical knowledge that is difficult to describe with mathematical formulas. AI modeling can be modified and expanded according to the new understanding of space debris model knowledge, and the system can be more flexible to adapt to new needs. The clearer the modeling and analysis results of space debris are, the more accurate the monitoring, early warning, mitigation, and removal of debris impacts are, thereby greatly reducing the impact of space debris on spacecraft. In short, spacecraft damage feature extraction and damage assessment are critical to the development of the aerospace industry, and these challenges call for new methods and techniques to stimulate the continuous efforts of aerospace equipment research, pattern recognition, and AI. In this context, the journal has organized a special feature on the application of AI in the space environment and spacecraft. This special feature focuses on spacecraft damage detection and assessment methods based on AI learning from detection data, including the hierarchical correlation analysis of spacecraft damage characteristics and detection data, and the construction of spacecraft damage assessment models based on AI analysis methods. After a rigorous review process, five research articles were selected for this feature.

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跨学科的地质灾害预警工程

姚学祥,徐晶

《中国工程科学》 2004年第6卷第6期页码 9-14

摘要：

滑坡、泥石流等地质灾害受多种因素的影响，地质灾害预报警报工程体系的建立需要多部门、多学科的合作。2003年6月1日中国气象局和国土资源部联合启动了全国地质灾害气象预警业务，取得了很好的社会和经济效益。分析了我国滑坡泥石流等地质灾害的时空分布特点及其与降雨等多因素、多学科的关系。介绍了国家级地质灾害预报警报业务系统的有关技术，并分析了存在的问题，结合国内外的技术发展现状和趋势，提出了从地球系统5大圈层相互作用的角度研究地质灾害，建立多学科多部门合作的地质灾害监测、预报、警报和防治体系等建议。

关键词：地质灾害泥石流滑坡预警工程

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三峡工程电站设计

周述达,谢红兵

《中国工程科学》 2011年第13卷第7期页码 78-84

摘要：

利用物理模型和数值模拟技术，系统研究了三峡电站布置、排沙及排漂措施、进水口形式、机组蜗壳埋设方式，以及地下电站洞室群布置、块体加固等技术问题。研究表明，三峡电站采用两岸坝后厂房+右岸地下厂房的布置及单孔小孔口进水口体型技术经济最优，采用分散排沙和排漂孔可较好解决电站的泥沙和漂污问题，蜗壳采用保温保压、垫层及组合埋设技术均可保证机组稳定运行，采用新型变顶高尾水洞优于设置尾水调压室。同时提出了与蜗壳埋设方式相关的技术标准，并对大型不利块体的加固进行了探讨，提出了利用阻滑键及结构面法向压应力加固块体的新思路。

关键词：三峡电站布置排沙排漂蜗壳埋设浅埋块体加固

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基于变分贝叶斯多稀疏成分提取的空间碎片超高速撞击损伤重构方法研究 Research Article

黄雪刚,石安华,罗庆,罗锦阳

《信息与电子工程前沿（英文）》 2022年第23卷第4期页码 530-541 doi: 10.1631/FITEE.2000575

摘要：为提高在轨航天器抵御空间碎片撞击的生存能力，提出一种撞击损伤评估方法。首先，建立一个针对红外热图像序列数据的多区域损伤挖掘模型，用于描述处于不同空间层的撞击损伤。采用变分贝叶斯推理来求解模型参数，从而有效地从红外热图像数据中识别不同类型撞击损伤。然后，提出一种图像处理框架，包括具有能量函数的图像分割算法和具有稀疏表示的图像融合方法，以消除变异贝叶斯误差并比较不同类型损伤的位置。在试验部分，将上述方法用于评估二次碎片云对Whipple防护结构的复杂撞击损伤。实验结果证明本文提出的方法可以对空间碎片超高速撞击造成的不同类型复杂损伤进行有效识别与评估。

关键词：超高速撞击；变分贝叶斯；稀疏表示；损伤评估

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预处理技术——家庭生物废弃物处理过程中的微塑料制造者 Article

Tian Hu, Fan Lü, Zhan Yang, Zhenchao Shi, Yicheng Yang, Hua Zhang, Pinjing He

《工程（英文）》 2024年第32卷第1期页码 117-127 doi: 10.1016/j.eng.2023.11.010

摘要：

Mechanical pretreatment is an indispensable process in biological treatment plants that remove plastics and other impurities from household biogenic waste (HBW). However, the imperfect separation of plastics in these pretreatment methods has raised concerns that they pose a secondary formation risk for microplastics (MPs). To validate this presumption, herein, quantities and properties of plastic debris and MPs larger than 50 μm were examined in the full chain of three different pretreatment methods in six plants. These facilities received HBW with or without prior depackaging at the source. The key points in the secondary formation of MPs were identified. Moreover, flux estimates of MPs were released, and an analysis of MPs sources was provided to develop an overview of their fate in HBW pretreatment. Pretreated output can contain a maximum of (1673 ± 279) to (3198 ± 263) MP particles per kilogram of wet weight (particles·kg⁻¹ ww) for those undepackaged at source, and secondary MPs formation is primarily attributed to biomass crushers, biohydrolysis reactors, and rough shredders. Comparatively, HBW depackaged at the source can greatly reduce MPs by 8%–72%, regardless of pretreatment processes. Before pretreatment, 4.6–205.6 million MP particles were present in 100 tonnes of HBW. MPs are produced at a rate of 741.11–33 124.22 billion MP particles annually in anaerobic digester feedstock (ADF). This study demonstrated that HBW pretreatment is a competitive source of MPs and emphasized the importance of implementing municipal solid waste segregation at the source. Furthermore, depackaging biogenic waste at the source is recommended to substantially alleviate the negative effect of pretreatment on MPs formation.

关键词： Microplastics Plastic debris Household biogenic waste Depackage Pretreatment