For the goals of security and privacy preservation,we propose a blind batch encryption-and public ledger-based data sharing protocol that allows the integrity of sensitive data to be audited by a public ledger and all...For the goals of security and privacy preservation,we propose a blind batch encryption-and public ledger-based data sharing protocol that allows the integrity of sensitive data to be audited by a public ledger and allows privacy information to be preserved.Data owners can tightly manage their data with efficient revocation and only grant one-time adaptive access for the fulfillment of the requester.We prove that our protocol is semanticallly secure,blind,and secure against oblivious requesters and malicious file keepers.We also provide security analysis in the context of four typical attacks.展开更多
With the rapid development of intelligent manufacturing and the changes in market demand,the current manufacturing industry presents the characteristics of multi-varieties,small batches,customization,and a short produ...With the rapid development of intelligent manufacturing and the changes in market demand,the current manufacturing industry presents the characteristics of multi-varieties,small batches,customization,and a short production cycle,with the whole production process having certain flexibility.In this paper,a mathematical model is established with the minimum production cycle as the optimization objective for the dual-resource batch scheduling of the flexible job shop,and an improved nested optimization algorithm is designed to solve the problem.The outer layer batch optimization problem is solved by the improved simulated annealing algorithm.The inner double resource scheduling problem is solved by the improved adaptive genetic algorithm,the double coding scheme,and the decoding scheme of Automated Guided Vehicle(AGV)scheduling based on the scheduling rules.The time consumption of collision-free paths is solved with the path planning algorithm which uses the Dijkstra algorithm based on a time window.Finally,the effectiveness of the algorithm is verified by actual cases,and the influence of AGV with different configurations on workshop production efficiency is analyzed.展开更多
Rockburst is a phenomenon in which free surfaces are formed during excavation,which subsequently causes the sudden release of energy in the construction of mines and tunnels.Light rockburst only peels off rock slices ...Rockburst is a phenomenon in which free surfaces are formed during excavation,which subsequently causes the sudden release of energy in the construction of mines and tunnels.Light rockburst only peels off rock slices without ejection,while severe rockburst causes casualties and property loss.The frequency and degree of rockburst damage increases with the excavation depth.Moreover,rockburst is the leading engineering geological hazard in the excavation process,and thus the prediction of its intensity grade is of great significance to the development of geotechnical engineering.Therefore,the prediction of rockburst intensity grade is one problem that needs to be solved urgently.By comprehensively considering the occurrence mechanism of rockburst,this paper selects the stress index(σθ/σc),brittleness index(σ_(c)/σ_(t)),and rock elastic energy index(Wet)as the rockburst evaluation indexes through the Spearman coefficient method.This overcomes the low accuracy problem of a single evaluation index prediction method.Following this,the BGD-MSR-DNN rockburst intensity grade prediction model based on batch gradient descent and a multi-scale residual deep neural network is proposed.The batch gradient descent(BGD)module is used to replace the gradient descent algorithm,which effectively improves the efficiency of the network and reduces the model training time.Moreover,the multi-scale residual(MSR)module solves the problem of network degradation when there are too many hidden layers of the deep neural network(DNN),thus improving the model prediction accuracy.The experimental results reveal the BGDMSR-DNN model accuracy to reach 97.1%,outperforming other comparable models.Finally,actual projects such as Qinling Tunnel and Daxiangling Tunnel,reached an accuracy of 100%.The model can be applied in mines and tunnel engineering to realize the accurate and rapid prediction of rockburst intensity grade.展开更多
This research assessed the environmental impact of cement silos emission on the existing concrete batching facilities in M35-Mussafah, Abu Dhabi, United Arab Emirates. These assessments were conducted using an air qua...This research assessed the environmental impact of cement silos emission on the existing concrete batching facilities in M35-Mussafah, Abu Dhabi, United Arab Emirates. These assessments were conducted using an air quality dispersion model (AERMOD) to predict the ambient concentration of Portland Cement particulate matter less than 10 microns (PM<sub>10</sub>) emitted to the atmosphere during loading and unloading activities from 176 silos located in 25 concrete batching facilities. AERMOD was applied to simulate and describe the dispersion of PM<sub>10</sub> released from the cement silos into the air. Simulations were carried out for PM<sub>10</sub> emissions on controlled and uncontrolled cement silos scenarios. Results showed an incremental negative impact on air quality and public health from uncontrolled silos emissions and estimated that the uncontrolled PM<sub>10</sub> emission sources contribute to air pollution by 528958.32 kg/Year. The modeling comparison between the controlled and uncontrolled silos shows that the highest annual average concentration from controlled cement silos is 0.065 μg/m<sup>3</sup>, and the highest daily emission value is 0.6 μg/m<sup>3</sup>;both values are negligible and will not lead to significant air quality impact in the entire study domain. However, the uncontrolled cement silos’ highest annual average concentration value is 328.08 μg/m<sup>3</sup>. The highest daily emission average value was 1250.09 μg/m<sup>3</sup>;this might cause a significant air pollution quality impact and health effects on the public and workers. The short-term and long-term average PM<sub>10</sub> pollutant concentrations at these receptors predicted by the air dispersion model are discussed for both scenarios and compared with local and international air quality standards and guidelines.展开更多
基于Aspen Batch Process Developer软件对原料药工程设计进行应用研究。在某原料药项目中,通过软件建立工艺流程模拟模型,分析批次操作时间、年生产批次、年生产规模、物料衡算、设备选型和利用率、公用工程消耗等,在满足生产需求的情...基于Aspen Batch Process Developer软件对原料药工程设计进行应用研究。在某原料药项目中,通过软件建立工艺流程模拟模型,分析批次操作时间、年生产批次、年生产规模、物料衡算、设备选型和利用率、公用工程消耗等,在满足生产需求的情况下,达到优化生产排班、设备选型和公用工程量的目的。展开更多
This research study quantifies the PM<sub>10</sub> emission rates (g/s) from cement silos in 25 concrete batching facilities for both controlled and uncontrolled scenarios by applying the USEPA AP-42 guide...This research study quantifies the PM<sub>10</sub> emission rates (g/s) from cement silos in 25 concrete batching facilities for both controlled and uncontrolled scenarios by applying the USEPA AP-42 guidelines step-by-step approach. The study focuses on evaluating the potential environmental impact of cement dust fugitive emissions from 176 cement silos located in 25 concrete batching facilities in the M35 Mussafah industrial area of Abu Dhabi, UAE. Emission factors are crucial for quantifying the PM<sub>10</sub> emission rates (g/s) that support developing source-specific emission estimates for areawide inventories to identify major sources of pollution that provide screening sources for compliance monitoring and air dispersion modeling. This requires data to be collected involves information on production, raw material usage, energy consumption, and process-related details, this was obtained using various methods, including field visits, surveys, and interviews with facility representatives to calculate emission rates accurately. Statistical analysis was conducted on cement consumption and emission rates for controlled and uncontrolled sources of the targeted facilities. The data shows that the average cement consumption among the facilities is approximately 88,160 (MT/yr), with a wide range of variation depending on the facility size and production rate. The emission rates from controlled sources have an average of 4.752E<sup>-04</sup> (g/s), while the rates from uncontrolled sources average 0.6716 (g/s). The analysis shows a significant statistical relationship (p < 0.05) and perfect positive correlation (r = 1) between cement consumption and emission rates, indicating that as cement consumption increases, emission rates tend to increase as well. Furthermore, comparing the emission rates from controlled and uncontrolled scenarios. The data showed a significant difference between the two scenarios, highlighting the effectiveness of control measures in reducing PM<sub>10</sub> emissions. The study’s findings provide insights into the impact of cement silo emissions on air quality and the importance of implementing control measures in concrete batching facilities. The comparative analysis contributes to understanding emission sources and supports the development of pollution control strategies in the Ready-Mix industry.展开更多
China set a quota for the second batch of rare earth mining in 2023 at 120,000 tonnes,with a quota for smelting and separation at 115,000 tonnes,according to a joint statement by the Ministry of Industry and Informati...China set a quota for the second batch of rare earth mining in 2023 at 120,000 tonnes,with a quota for smelting and separation at 115,000 tonnes,according to a joint statement by the Ministry of Industry and Information Technology(MIIT)and the Ministry of Natural Resources.展开更多
The Ministry of Industry and Information Technology(MIIT)and the Ministry of Natural Resources jointly released the third batch of quota for rare earth mining at 15,000 tons and quota for rare earth smelting and separ...The Ministry of Industry and Information Technology(MIIT)and the Ministry of Natural Resources jointly released the third batch of quota for rare earth mining at 15,000 tons and quota for rare earth smelting and separation at 13,850 tons on December 15,2023.According to MIIT,the third batch of rare earth quotas were issued to China Rare Earth Group and China Northern Rare Earth Group,respectively.China Rare Earth Group was allocated a quota of 5,850tons REO,including 3,000 tons REO of mineral products and 2,850 tons REO of smelting&separation products.China Northern Rare Earth(Group)received a quota of 23,000 tons REO,containing 12,000tons REO of mineral products and 11,000 tons REO of smelting&separation products.展开更多
间歇生产过程具有弹性大、灵活等特点,其市场适应性较强。化工生产中间歇生产过程占相当比例,文章就间歇生产工艺的模拟与优化进行介绍,利用Aspen Batch Process Developer模拟间歇工艺过程,可以快速地得到工艺流程的物料衡算、热量衡...间歇生产过程具有弹性大、灵活等特点,其市场适应性较强。化工生产中间歇生产过程占相当比例,文章就间歇生产工艺的模拟与优化进行介绍,利用Aspen Batch Process Developer模拟间歇工艺过程,可以快速地得到工艺流程的物料衡算、热量衡算、操作时间、公用工程和成本估算等结果。同时,还可以对模拟结果进行分析,找出制约生产工艺的瓶颈,并对生产周期、生产规模、生产设备等进行优化,提高工艺设计效率,降低生产成本。展开更多
In order to solve the flexible job shop scheduling problem with variable batches,we propose an improved multiobjective optimization algorithm,which combines the idea of inverse scheduling.First,a flexible job shop pro...In order to solve the flexible job shop scheduling problem with variable batches,we propose an improved multiobjective optimization algorithm,which combines the idea of inverse scheduling.First,a flexible job shop problem with the variable batches scheduling model is formulated.Second,we propose a batch optimization algorithm with inverse scheduling in which the batch size is adjusted by the dynamic feedback batch adjusting method.Moreover,in order to increase the diversity of the population,two methods are developed.One is the threshold to control the neighborhood updating,and the other is the dynamic clustering algorithm to update the population.Finally,a group of experiments are carried out.The results show that the improved multi-objective optimization algorithm can ensure the diversity of Pareto solutions effectively,and has effective performance in solving the flexible job shop scheduling problem with variable batches.展开更多
美罗培南是一种新型碳青霉烯类抗生素,具有广阔的市场前景,其生产过程为间歇生产。文章利用Aspen Batch Process Developer 7.2对年产25吨的美罗培南原料药生产工艺流程进行模拟,得到生产过程中的物料衡算结果误差为0.8%,生产时间甘德...美罗培南是一种新型碳青霉烯类抗生素,具有广阔的市场前景,其生产过程为间歇生产。文章利用Aspen Batch Process Developer 7.2对年产25吨的美罗培南原料药生产工艺流程进行模拟,得到生产过程中的物料衡算结果误差为0.8%,生产时间甘德图表明,生产周期为48小时,并得到该生产过程的公用工程消耗量,对实际的工艺设计具有一定的参考价值。展开更多
基金partially supported by the National Natural Science Foundation of China under grant no.62372245the Foundation of Yunnan Key Laboratory of Blockchain Application Technology under Grant 202105AG070005+1 种基金in part by the Foundation of State Key Laboratory of Public Big Datain part by the Foundation of Key Laboratory of Computational Science and Application of Hainan Province under Grant JSKX202202。
文摘For the goals of security and privacy preservation,we propose a blind batch encryption-and public ledger-based data sharing protocol that allows the integrity of sensitive data to be audited by a public ledger and allows privacy information to be preserved.Data owners can tightly manage their data with efficient revocation and only grant one-time adaptive access for the fulfillment of the requester.We prove that our protocol is semanticallly secure,blind,and secure against oblivious requesters and malicious file keepers.We also provide security analysis in the context of four typical attacks.
文摘With the rapid development of intelligent manufacturing and the changes in market demand,the current manufacturing industry presents the characteristics of multi-varieties,small batches,customization,and a short production cycle,with the whole production process having certain flexibility.In this paper,a mathematical model is established with the minimum production cycle as the optimization objective for the dual-resource batch scheduling of the flexible job shop,and an improved nested optimization algorithm is designed to solve the problem.The outer layer batch optimization problem is solved by the improved simulated annealing algorithm.The inner double resource scheduling problem is solved by the improved adaptive genetic algorithm,the double coding scheme,and the decoding scheme of Automated Guided Vehicle(AGV)scheduling based on the scheduling rules.The time consumption of collision-free paths is solved with the path planning algorithm which uses the Dijkstra algorithm based on a time window.Finally,the effectiveness of the algorithm is verified by actual cases,and the influence of AGV with different configurations on workshop production efficiency is analyzed.
基金funded by State Key Laboratory for GeoMechanics and Deep Underground Engineering&Institute for Deep Underground Science and Engineering,Grant Number XD2021021BUCEA Post Graduate Innovation Project under Grant,Grant Number PG2023092.
文摘Rockburst is a phenomenon in which free surfaces are formed during excavation,which subsequently causes the sudden release of energy in the construction of mines and tunnels.Light rockburst only peels off rock slices without ejection,while severe rockburst causes casualties and property loss.The frequency and degree of rockburst damage increases with the excavation depth.Moreover,rockburst is the leading engineering geological hazard in the excavation process,and thus the prediction of its intensity grade is of great significance to the development of geotechnical engineering.Therefore,the prediction of rockburst intensity grade is one problem that needs to be solved urgently.By comprehensively considering the occurrence mechanism of rockburst,this paper selects the stress index(σθ/σc),brittleness index(σ_(c)/σ_(t)),and rock elastic energy index(Wet)as the rockburst evaluation indexes through the Spearman coefficient method.This overcomes the low accuracy problem of a single evaluation index prediction method.Following this,the BGD-MSR-DNN rockburst intensity grade prediction model based on batch gradient descent and a multi-scale residual deep neural network is proposed.The batch gradient descent(BGD)module is used to replace the gradient descent algorithm,which effectively improves the efficiency of the network and reduces the model training time.Moreover,the multi-scale residual(MSR)module solves the problem of network degradation when there are too many hidden layers of the deep neural network(DNN),thus improving the model prediction accuracy.The experimental results reveal the BGDMSR-DNN model accuracy to reach 97.1%,outperforming other comparable models.Finally,actual projects such as Qinling Tunnel and Daxiangling Tunnel,reached an accuracy of 100%.The model can be applied in mines and tunnel engineering to realize the accurate and rapid prediction of rockburst intensity grade.
文摘This research assessed the environmental impact of cement silos emission on the existing concrete batching facilities in M35-Mussafah, Abu Dhabi, United Arab Emirates. These assessments were conducted using an air quality dispersion model (AERMOD) to predict the ambient concentration of Portland Cement particulate matter less than 10 microns (PM<sub>10</sub>) emitted to the atmosphere during loading and unloading activities from 176 silos located in 25 concrete batching facilities. AERMOD was applied to simulate and describe the dispersion of PM<sub>10</sub> released from the cement silos into the air. Simulations were carried out for PM<sub>10</sub> emissions on controlled and uncontrolled cement silos scenarios. Results showed an incremental negative impact on air quality and public health from uncontrolled silos emissions and estimated that the uncontrolled PM<sub>10</sub> emission sources contribute to air pollution by 528958.32 kg/Year. The modeling comparison between the controlled and uncontrolled silos shows that the highest annual average concentration from controlled cement silos is 0.065 μg/m<sup>3</sup>, and the highest daily emission value is 0.6 μg/m<sup>3</sup>;both values are negligible and will not lead to significant air quality impact in the entire study domain. However, the uncontrolled cement silos’ highest annual average concentration value is 328.08 μg/m<sup>3</sup>. The highest daily emission average value was 1250.09 μg/m<sup>3</sup>;this might cause a significant air pollution quality impact and health effects on the public and workers. The short-term and long-term average PM<sub>10</sub> pollutant concentrations at these receptors predicted by the air dispersion model are discussed for both scenarios and compared with local and international air quality standards and guidelines.
文摘基于Aspen Batch Process Developer软件对原料药工程设计进行应用研究。在某原料药项目中,通过软件建立工艺流程模拟模型,分析批次操作时间、年生产批次、年生产规模、物料衡算、设备选型和利用率、公用工程消耗等,在满足生产需求的情况下,达到优化生产排班、设备选型和公用工程量的目的。
文摘This research study quantifies the PM<sub>10</sub> emission rates (g/s) from cement silos in 25 concrete batching facilities for both controlled and uncontrolled scenarios by applying the USEPA AP-42 guidelines step-by-step approach. The study focuses on evaluating the potential environmental impact of cement dust fugitive emissions from 176 cement silos located in 25 concrete batching facilities in the M35 Mussafah industrial area of Abu Dhabi, UAE. Emission factors are crucial for quantifying the PM<sub>10</sub> emission rates (g/s) that support developing source-specific emission estimates for areawide inventories to identify major sources of pollution that provide screening sources for compliance monitoring and air dispersion modeling. This requires data to be collected involves information on production, raw material usage, energy consumption, and process-related details, this was obtained using various methods, including field visits, surveys, and interviews with facility representatives to calculate emission rates accurately. Statistical analysis was conducted on cement consumption and emission rates for controlled and uncontrolled sources of the targeted facilities. The data shows that the average cement consumption among the facilities is approximately 88,160 (MT/yr), with a wide range of variation depending on the facility size and production rate. The emission rates from controlled sources have an average of 4.752E<sup>-04</sup> (g/s), while the rates from uncontrolled sources average 0.6716 (g/s). The analysis shows a significant statistical relationship (p < 0.05) and perfect positive correlation (r = 1) between cement consumption and emission rates, indicating that as cement consumption increases, emission rates tend to increase as well. Furthermore, comparing the emission rates from controlled and uncontrolled scenarios. The data showed a significant difference between the two scenarios, highlighting the effectiveness of control measures in reducing PM<sub>10</sub> emissions. The study’s findings provide insights into the impact of cement silo emissions on air quality and the importance of implementing control measures in concrete batching facilities. The comparative analysis contributes to understanding emission sources and supports the development of pollution control strategies in the Ready-Mix industry.
文摘China set a quota for the second batch of rare earth mining in 2023 at 120,000 tonnes,with a quota for smelting and separation at 115,000 tonnes,according to a joint statement by the Ministry of Industry and Information Technology(MIIT)and the Ministry of Natural Resources.
文摘The Ministry of Industry and Information Technology(MIIT)and the Ministry of Natural Resources jointly released the third batch of quota for rare earth mining at 15,000 tons and quota for rare earth smelting and separation at 13,850 tons on December 15,2023.According to MIIT,the third batch of rare earth quotas were issued to China Rare Earth Group and China Northern Rare Earth Group,respectively.China Rare Earth Group was allocated a quota of 5,850tons REO,including 3,000 tons REO of mineral products and 2,850 tons REO of smelting&separation products.China Northern Rare Earth(Group)received a quota of 23,000 tons REO,containing 12,000tons REO of mineral products and 11,000 tons REO of smelting&separation products.
文摘间歇生产过程具有弹性大、灵活等特点,其市场适应性较强。化工生产中间歇生产过程占相当比例,文章就间歇生产工艺的模拟与优化进行介绍,利用Aspen Batch Process Developer模拟间歇工艺过程,可以快速地得到工艺流程的物料衡算、热量衡算、操作时间、公用工程和成本估算等结果。同时,还可以对模拟结果进行分析,找出制约生产工艺的瓶颈,并对生产周期、生产规模、生产设备等进行优化,提高工艺设计效率,降低生产成本。
基金supported by the National Key R&D Plan(2020YFB1712902)the National Natural Science Foundation of China(52075036).
文摘In order to solve the flexible job shop scheduling problem with variable batches,we propose an improved multiobjective optimization algorithm,which combines the idea of inverse scheduling.First,a flexible job shop problem with the variable batches scheduling model is formulated.Second,we propose a batch optimization algorithm with inverse scheduling in which the batch size is adjusted by the dynamic feedback batch adjusting method.Moreover,in order to increase the diversity of the population,two methods are developed.One is the threshold to control the neighborhood updating,and the other is the dynamic clustering algorithm to update the population.Finally,a group of experiments are carried out.The results show that the improved multi-objective optimization algorithm can ensure the diversity of Pareto solutions effectively,and has effective performance in solving the flexible job shop scheduling problem with variable batches.
文摘美罗培南是一种新型碳青霉烯类抗生素,具有广阔的市场前景,其生产过程为间歇生产。文章利用Aspen Batch Process Developer 7.2对年产25吨的美罗培南原料药生产工艺流程进行模拟,得到生产过程中的物料衡算结果误差为0.8%,生产时间甘德图表明,生产周期为48小时,并得到该生产过程的公用工程消耗量,对实际的工艺设计具有一定的参考价值。
