This work focuses on the effect of the interval between two shocks on the ejecta formation from the grooved aluminum(Al_(1100))surface by using smoothed particle hydrodynamics numerical simulation.Two unsupported shoc...This work focuses on the effect of the interval between two shocks on the ejecta formation from the grooved aluminum(Al_(1100))surface by using smoothed particle hydrodynamics numerical simulation.Two unsupported shocks are obtained by the plate-impact between sample and two flyers at interval,with a peak pressure of approximately 30 GPa for each shock.When the shock interval varies from 2.11 to 7.67 times the groove depth,the bubble velocity reduces to a constant,and the micro jetting factor R_(J) from spike to bubble exhibits a non-monotonic change that decreases initially and then increases.At a shock interval of 3.6 times the groove depth,micro jetting factor R_(J) from spike to bubble reaches its minimum value of approximately 0.6.While,the micro jetting factor R_(F) from spike to free surface decreases linearly at first,and stabilizes around 0.25 once the shock interval surpasses 4.18 times the groove depth.When the shock interval is less than 4.18 times the groove depth,the unloading wave generated by the breakout of the first shock wave is superimpose with the unloading part of the second shock wave to form a large tensile area.展开更多
Interval model updating(IMU)methods have been widely used in uncertain model updating due to their low requirements for sample data.However,the surrogate model in IMU methods mostly adopts the one-time construction me...Interval model updating(IMU)methods have been widely used in uncertain model updating due to their low requirements for sample data.However,the surrogate model in IMU methods mostly adopts the one-time construction method.This makes the accuracy of the surrogate model highly dependent on the experience of users and affects the accuracy of IMU methods.Therefore,an improved IMU method via the adaptive Kriging models is proposed.This method transforms the objective function of the IMU problem into two deterministic global optimization problems about the upper bound and the interval diameter through universal grey numbers.These optimization problems are addressed through the adaptive Kriging models and the particle swarm optimization(PSO)method to quantify the uncertain parameters,and the IMU is accomplished.During the construction of these adaptive Kriging models,the sample space is gridded according to sensitivity information.Local sampling is then performed in key subspaces based on the maximum mean square error(MMSE)criterion.The interval division coefficient and random sampling coefficient are adaptively adjusted without human interference until the model meets accuracy requirements.The effectiveness of the proposed method is demonstrated by a numerical example of a three-degree-of-freedom mass-spring system and an experimental example of a butted cylindrical shell.The results show that the updated results of the interval model are in good agreement with the experimental results.展开更多
Addressing the insufficiency in down-regulation leeway within integrated energy systems stemming from the erratic and volatile nature of wind and solar renewable energy generation,this study focuses on formulating a c...Addressing the insufficiency in down-regulation leeway within integrated energy systems stemming from the erratic and volatile nature of wind and solar renewable energy generation,this study focuses on formulating a coordinated strategy involving the carbon capture unit of the integrated energy system and the resources on the load storage side.A scheduling model is devised that takes into account the confidence interval associated with renewable energy generation,with the overarching goal of optimizing the system for low-carbon operation.To begin with,an in-depth analysis is conducted on the temporal energy-shifting attributes and the low-carbon modulation mechanisms exhibited by the source-side carbon capture power plant within the context of integrated and adaptable operational paradigms.Drawing from this analysis,a model is devised to represent the adjustable resources on the charge-storage side,predicated on the principles of electro-thermal coupling within the energy system.Subsequently,the dissimilarities in the confidence intervals of renewable energy generation are considered,leading to the proposition of a flexible upper threshold for the confidence interval.Building on this,a low-carbon dispatch model is established for the integrated energy system,factoring in the margin allowed by the adjustable resources.In the final phase,a simulation is performed on a regional electric heating integrated energy system.This simulation seeks to assess the impact of source-load-storage coordination on the system’s low-carbon operation across various scenarios of reduction margin reserves.The findings underscore that the proactive scheduling model incorporating confidence interval considerations for reduction margin reserves effectively mitigates the uncertainties tied to renewable energy generation.Through harmonized orchestration of source,load,and storage elements,it expands the utilization scope for renewable energy,safeguards the economic efficiency of system operations under low-carbon emission conditions,and empirically validates the soundness and efficacy of the proposed approach.展开更多
针对部分机电产品在概念设计阶段未综合考虑客户和环境的需求,进而影响产品详细设计的问题,提出了一种基于功能—结构—客户和环境需求(function‒structure‒requirements of customer and environment,FSRce)模型的机电产品绿色概念设...针对部分机电产品在概念设计阶段未综合考虑客户和环境的需求,进而影响产品详细设计的问题,提出了一种基于功能—结构—客户和环境需求(function‒structure‒requirements of customer and environment,FSRce)模型的机电产品绿色概念设计方案生成方法。首先,从案例库中选择合适的功能和结构对现有产品设计树中的节点进行扩展和关联;同时通过数据挖掘、专家打分等方法获得产品的客户和环境需求重要度,以构建基于FSRce模型的产品概念设计空间。然后,先利用加权区间粗糙数法对客户和环境需求重要度进行分析,得到需求相对重要度,再运用模糊质量功能展开(fuzzy quality function deployment,FQFD)将需求相对重要度转化为产品的工程特性权重。最后,利用物元理论构建基于工程特性的产品物元域和各结构物元集,并结合工程特性权重得到各结构的满意度分值,通过比较满意度优选得到满足客户和环境需求的产品概念设计方案。以某小型工业吹风机为例,基于上述方法对其概念设计方案进行优化。相比于原始方案,优化后的吹风机在能源消耗上降低了15.38%,在碳排放上降低了15.32%,且客户满意度提高了44.66%,由此验证了所提出方法的可行性与有效性。所提出的方法为机电产品概念设计方案的生成提供了一种新思路,能更好地辅助设计人员实现对机电产品的绿色设计。展开更多
为改善传统N-Calculator模型的局限性,加强食物氮足迹核算结果与环境影响的联系,提高活性氮管理预见性,将N-Calculator模型与食物系统养分流动(Nutrient Flows in Food Chains,Environment and Resources Use,NUFER)模型进行耦合,以估...为改善传统N-Calculator模型的局限性,加强食物氮足迹核算结果与环境影响的联系,提高活性氮管理预见性,将N-Calculator模型与食物系统养分流动(Nutrient Flows in Food Chains,Environment and Resources Use,NUFER)模型进行耦合,以估算我国2001—2020年人均食物氮足迹,建立组合预测体系。结果显示:2001—2020年,我国人均食物氮足迹由16.04 kg N/a增至18.95 kg N/a;全国食物氮足迹由20.47 Mt N/a增至26.76 Mt N/a;居民饮食结构正由以植物源食物为主的低氮消费模式转向以动物源食物为主的高氮消费模式;食物生产过程产生的活性氮的最终归宿为大气(64.3%)、水体和深层土壤(35.7%);我国食物氮足迹与人均可支配收入、城市化率、动物源食物消费氮占比呈正相关性,与恩格尔系数呈负相关性;未来10 a我国人均食物氮足迹呈增长趋势,预测结果显示年均增幅为0.16 kg N/a。展开更多
基金supported by the Doctoral Research Launch Foundation of Liaoning Province(Grant No.2022-BS-185),Chinathe Science Challenge Project(Grant No.TZ2016001),China+2 种基金the National Natural Science Foundation of China(Grant Nos.11972092,12172056,12002049),Chinathe key Laboratory of Computational Physics(Gant No.HX02021-24)720-24)Shenyang Ligong University Talent Introduction Support Fund,China。
文摘This work focuses on the effect of the interval between two shocks on the ejecta formation from the grooved aluminum(Al_(1100))surface by using smoothed particle hydrodynamics numerical simulation.Two unsupported shocks are obtained by the plate-impact between sample and two flyers at interval,with a peak pressure of approximately 30 GPa for each shock.When the shock interval varies from 2.11 to 7.67 times the groove depth,the bubble velocity reduces to a constant,and the micro jetting factor R_(J) from spike to bubble exhibits a non-monotonic change that decreases initially and then increases.At a shock interval of 3.6 times the groove depth,micro jetting factor R_(J) from spike to bubble reaches its minimum value of approximately 0.6.While,the micro jetting factor R_(F) from spike to free surface decreases linearly at first,and stabilizes around 0.25 once the shock interval surpasses 4.18 times the groove depth.When the shock interval is less than 4.18 times the groove depth,the unloading wave generated by the breakout of the first shock wave is superimpose with the unloading part of the second shock wave to form a large tensile area.
基金Project supported by the National Natural Science Foundation of China(Nos.12272211,12072181,12121002)。
文摘Interval model updating(IMU)methods have been widely used in uncertain model updating due to their low requirements for sample data.However,the surrogate model in IMU methods mostly adopts the one-time construction method.This makes the accuracy of the surrogate model highly dependent on the experience of users and affects the accuracy of IMU methods.Therefore,an improved IMU method via the adaptive Kriging models is proposed.This method transforms the objective function of the IMU problem into two deterministic global optimization problems about the upper bound and the interval diameter through universal grey numbers.These optimization problems are addressed through the adaptive Kriging models and the particle swarm optimization(PSO)method to quantify the uncertain parameters,and the IMU is accomplished.During the construction of these adaptive Kriging models,the sample space is gridded according to sensitivity information.Local sampling is then performed in key subspaces based on the maximum mean square error(MMSE)criterion.The interval division coefficient and random sampling coefficient are adaptively adjusted without human interference until the model meets accuracy requirements.The effectiveness of the proposed method is demonstrated by a numerical example of a three-degree-of-freedom mass-spring system and an experimental example of a butted cylindrical shell.The results show that the updated results of the interval model are in good agreement with the experimental results.
基金supported by the Science and Technology Project of State Grid Inner Mongolia East Power Co.,Ltd.:Research on Carbon Flow Apportionment and Assessment Methods for Distributed Energy under Dual Carbon Targets(52664K220004).
文摘Addressing the insufficiency in down-regulation leeway within integrated energy systems stemming from the erratic and volatile nature of wind and solar renewable energy generation,this study focuses on formulating a coordinated strategy involving the carbon capture unit of the integrated energy system and the resources on the load storage side.A scheduling model is devised that takes into account the confidence interval associated with renewable energy generation,with the overarching goal of optimizing the system for low-carbon operation.To begin with,an in-depth analysis is conducted on the temporal energy-shifting attributes and the low-carbon modulation mechanisms exhibited by the source-side carbon capture power plant within the context of integrated and adaptable operational paradigms.Drawing from this analysis,a model is devised to represent the adjustable resources on the charge-storage side,predicated on the principles of electro-thermal coupling within the energy system.Subsequently,the dissimilarities in the confidence intervals of renewable energy generation are considered,leading to the proposition of a flexible upper threshold for the confidence interval.Building on this,a low-carbon dispatch model is established for the integrated energy system,factoring in the margin allowed by the adjustable resources.In the final phase,a simulation is performed on a regional electric heating integrated energy system.This simulation seeks to assess the impact of source-load-storage coordination on the system’s low-carbon operation across various scenarios of reduction margin reserves.The findings underscore that the proactive scheduling model incorporating confidence interval considerations for reduction margin reserves effectively mitigates the uncertainties tied to renewable energy generation.Through harmonized orchestration of source,load,and storage elements,it expands the utilization scope for renewable energy,safeguards the economic efficiency of system operations under low-carbon emission conditions,and empirically validates the soundness and efficacy of the proposed approach.
文摘针对部分机电产品在概念设计阶段未综合考虑客户和环境的需求,进而影响产品详细设计的问题,提出了一种基于功能—结构—客户和环境需求(function‒structure‒requirements of customer and environment,FSRce)模型的机电产品绿色概念设计方案生成方法。首先,从案例库中选择合适的功能和结构对现有产品设计树中的节点进行扩展和关联;同时通过数据挖掘、专家打分等方法获得产品的客户和环境需求重要度,以构建基于FSRce模型的产品概念设计空间。然后,先利用加权区间粗糙数法对客户和环境需求重要度进行分析,得到需求相对重要度,再运用模糊质量功能展开(fuzzy quality function deployment,FQFD)将需求相对重要度转化为产品的工程特性权重。最后,利用物元理论构建基于工程特性的产品物元域和各结构物元集,并结合工程特性权重得到各结构的满意度分值,通过比较满意度优选得到满足客户和环境需求的产品概念设计方案。以某小型工业吹风机为例,基于上述方法对其概念设计方案进行优化。相比于原始方案,优化后的吹风机在能源消耗上降低了15.38%,在碳排放上降低了15.32%,且客户满意度提高了44.66%,由此验证了所提出方法的可行性与有效性。所提出的方法为机电产品概念设计方案的生成提供了一种新思路,能更好地辅助设计人员实现对机电产品的绿色设计。
文摘为改善传统N-Calculator模型的局限性,加强食物氮足迹核算结果与环境影响的联系,提高活性氮管理预见性,将N-Calculator模型与食物系统养分流动(Nutrient Flows in Food Chains,Environment and Resources Use,NUFER)模型进行耦合,以估算我国2001—2020年人均食物氮足迹,建立组合预测体系。结果显示:2001—2020年,我国人均食物氮足迹由16.04 kg N/a增至18.95 kg N/a;全国食物氮足迹由20.47 Mt N/a增至26.76 Mt N/a;居民饮食结构正由以植物源食物为主的低氮消费模式转向以动物源食物为主的高氮消费模式;食物生产过程产生的活性氮的最终归宿为大气(64.3%)、水体和深层土壤(35.7%);我国食物氮足迹与人均可支配收入、城市化率、动物源食物消费氮占比呈正相关性,与恩格尔系数呈负相关性;未来10 a我国人均食物氮足迹呈增长趋势,预测结果显示年均增幅为0.16 kg N/a。
