针对风力发电机组频发的火灾事故,首先从人-机-环-管角度出发,通过统计分析近20年来全球81起风力发电机组火灾事故案例,得到了21项风力发电机组火灾事故的影响因素;然后通过事故树分析(fault tree analysis,FTA)法演绎推理得到了风力发...针对风力发电机组频发的火灾事故,首先从人-机-环-管角度出发,通过统计分析近20年来全球81起风力发电机组火灾事故案例,得到了21项风力发电机组火灾事故的影响因素;然后通过事故树分析(fault tree analysis,FTA)法演绎推理得到了风力发电机组火灾事故各基本事件的逻辑关系,并根据结构重要度进行了火灾事故致因的定性分析;接着采用模糊层次分析(fuzzy analytic hierarchy process,FAHP)法,将事故树的基本事件从人、机、环、管4个方面整合,构建出风力发电机组火灾事故致因评价指标体系,并以结构重要度系数的顺序为模糊判断矩阵的赋值依据,进行了火灾事故致因的定量分析;最后,根据综合分析结果提出了风力发电机组火灾事故的对策措施。结果表明:机和环境的不安全因素是引发火灾事故的主要致因;电气设备故障和雷击是最主要因素。该研究成果可为风力发电机组的火灾防治提供理论参考。展开更多
为了客观评价地下空间开发地质适宜性并为评价工作提供一种新思路和参考,提出了一种基于三角模糊数的模糊层次分析法(fuzzy analytic hierarchy process based on triangular fuzzy numbers,FAHP)和优劣解距离法(technique for order pr...为了客观评价地下空间开发地质适宜性并为评价工作提供一种新思路和参考,提出了一种基于三角模糊数的模糊层次分析法(fuzzy analytic hierarchy process based on triangular fuzzy numbers,FAHP)和优劣解距离法(technique for order preference by similarity to ideal solution,TOPSIS)相结合的评价方法。通过地质调查研究构建基于土体工程地质性质、水文地质条件、不良地质作用、地形地貌等影响因素为主的层次分析关系模型。基于专家判别利用FAHP计算各评价因素的权重,以各评价指标层的分级临界值作为典型评价样本,利用TOPSIS法对适宜性等级进行非等分划分,基于区间值优化的TOPSIS法建立最终评价模型,通过ArcGIS的空间分析功能等确定每个评价单元适宜性等级。该方法与传统方法相比一定程度上减少了评价过程中专家评判的过多主观影响,评价过程更倾向于定量化,结果更为客观。利用该方法对无锡市区浅层地下空间开发地质适宜性进行评价,评价结果与实际工程经验相符,证明了该方法的有效性,因此该方法对地下空间开发适宜性评价工作具有一定借鉴意义。展开更多
Recent reports suggest that aging is not solely a physiological process in living beings;instead, it should be considered a pathological process or disease(Amorim et al., 2022). Consequently, this process involves a w...Recent reports suggest that aging is not solely a physiological process in living beings;instead, it should be considered a pathological process or disease(Amorim et al., 2022). Consequently, this process involves a wide range of factors, spanning from genetic to environmental factors, and even includes the gut microbiome(GM)(Mayer et al., 2022). All these processes coincide at some point in the inflammatory process, oxidative stress, and apoptosis, at different degrees in various organs and systems that constitute a living organism(Mayer et al., 2022;AguilarHernández et al., 2023).展开更多
Sinter is the core raw material for blast furnaces.Flue pressure,which is an important state parameter,affects sinter quality.In this paper,flue pressure prediction and optimization were studied based on the shapley a...Sinter is the core raw material for blast furnaces.Flue pressure,which is an important state parameter,affects sinter quality.In this paper,flue pressure prediction and optimization were studied based on the shapley additive explanation(SHAP)to predict the flue pressure and take targeted adjustment measures.First,the sintering process data were collected and processed.A flue pressure prediction model was then constructed after comparing different feature selection methods and model algorithms using SHAP+extremely random-ized trees(ET).The prediction accuracy of the model within the error range of±0.25 kPa was 92.63%.SHAP analysis was employed to improve the interpretability of the prediction model.The effects of various sintering operation parameters on flue pressure,the relation-ship between the numerical range of key operation parameters and flue pressure,the effect of operation parameter combinations on flue pressure,and the prediction process of the flue pressure prediction model on a single sample were analyzed.A flue pressure optimization module was also constructed and analyzed when the prediction satisfied the judgment conditions.The operating parameter combination was then pushed.The flue pressure was increased by 5.87%during the verification process,achieving a good optimization effect.展开更多
Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the p...Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.展开更多
文摘为了客观评价地下空间开发地质适宜性并为评价工作提供一种新思路和参考,提出了一种基于三角模糊数的模糊层次分析法(fuzzy analytic hierarchy process based on triangular fuzzy numbers,FAHP)和优劣解距离法(technique for order preference by similarity to ideal solution,TOPSIS)相结合的评价方法。通过地质调查研究构建基于土体工程地质性质、水文地质条件、不良地质作用、地形地貌等影响因素为主的层次分析关系模型。基于专家判别利用FAHP计算各评价因素的权重,以各评价指标层的分级临界值作为典型评价样本,利用TOPSIS法对适宜性等级进行非等分划分,基于区间值优化的TOPSIS法建立最终评价模型,通过ArcGIS的空间分析功能等确定每个评价单元适宜性等级。该方法与传统方法相比一定程度上减少了评价过程中专家评判的过多主观影响,评价过程更倾向于定量化,结果更为客观。利用该方法对无锡市区浅层地下空间开发地质适宜性进行评价,评价结果与实际工程经验相符,证明了该方法的有效性,因此该方法对地下空间开发适宜性评价工作具有一定借鉴意义。
基金funded by CONAHCYT grant(252808)to GFCONAHCYT’s“Estancias Posdoctorales por México”program(662350)to HTB。
文摘Recent reports suggest that aging is not solely a physiological process in living beings;instead, it should be considered a pathological process or disease(Amorim et al., 2022). Consequently, this process involves a wide range of factors, spanning from genetic to environmental factors, and even includes the gut microbiome(GM)(Mayer et al., 2022). All these processes coincide at some point in the inflammatory process, oxidative stress, and apoptosis, at different degrees in various organs and systems that constitute a living organism(Mayer et al., 2022;AguilarHernández et al., 2023).
基金supported by the General Program of the National Natural Science Foundation of China(No.52274326)the China Baowu Low Carbon Metallurgy Innovation Foundation(No.BWLCF202109)the Seventh Batch of Ten Thousand Talents Plan of China(No.ZX20220553).
文摘Sinter is the core raw material for blast furnaces.Flue pressure,which is an important state parameter,affects sinter quality.In this paper,flue pressure prediction and optimization were studied based on the shapley additive explanation(SHAP)to predict the flue pressure and take targeted adjustment measures.First,the sintering process data were collected and processed.A flue pressure prediction model was then constructed after comparing different feature selection methods and model algorithms using SHAP+extremely random-ized trees(ET).The prediction accuracy of the model within the error range of±0.25 kPa was 92.63%.SHAP analysis was employed to improve the interpretability of the prediction model.The effects of various sintering operation parameters on flue pressure,the relation-ship between the numerical range of key operation parameters and flue pressure,the effect of operation parameter combinations on flue pressure,and the prediction process of the flue pressure prediction model on a single sample were analyzed.A flue pressure optimization module was also constructed and analyzed when the prediction satisfied the judgment conditions.The operating parameter combination was then pushed.The flue pressure was increased by 5.87%during the verification process,achieving a good optimization effect.
基金supported by the National Natural Science Foundation of China(51767017)the Basic Research Innovation Group Project of Gansu Province(18JR3RA133)the Industrial Support and Guidance Project of Universities in Gansu Province(2022CYZC-22).
文摘Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.
