In-situ enlargement of super-large-span tunnels can intensify excavation-induced unloading in the surrounding rock,increasing deformation demand and failure risk during construction.This study combines laboratory mode...In-situ enlargement of super-large-span tunnels can intensify excavation-induced unloading in the surrounding rock,increasing deformation demand and failure risk during construction.This study combines laboratory model tests with FLAC3D simulations to evaluate the stabilizing role of prestressed anchor cables and to establish an energy-balance framework for support optimization.Comparative model tests of existing and enlarged tunnel sections,with and without anchors,show that reinforcement increases load-carrying capacity,reduces displacement,and confines damage to more localized zones.The numerical simulations reproduce displacement fields,shear-strain localization,and plastic-zone evolution with good agreement against the experimental observations.The energy framework is implemented in the in-situ simulations by quantifying unloading-related energy release in the rock mass and reinforcement work contributed by the anchors,and by introducing an energy release–reinforcement ratio as a stability indicator.Parametric analyses indicate that anchor length,spacing,and prestress influence stability in a nonlinear manner,with diminishing returns once reinforcement extends beyond the mechanically dominant deformation zone.An efficient parameter window is identified that improves deformation and yielding control while avoiding unnecessary reinforcement.The results provide an energy-consistent and design-oriented basis for prestressed anchorage selection in large-span tunnel expansion.展开更多
Some properties of a class of quasi-differentiable functions（the difference of two finite convex functions） are considered in this paper. And the convergence of the steepest descent algorithm for unconstrained and c...Some properties of a class of quasi-differentiable functions（the difference of two finite convex functions） are considered in this paper. And the convergence of the steepest descent algorithm for unconstrained and constrained quasi-differentiable programming is proved.展开更多
This paper derives first order necessary and sufficient conditions for unconstrained coned.c. Programming problems where the underlined space is partially ordered with respect to acone. These conditions are given in t...This paper derives first order necessary and sufficient conditions for unconstrained coned.c. Programming problems where the underlined space is partially ordered with respect to acone. These conditions are given in terms of directional derivatives and subdifferentials of thecomponent functions. Moreover, conjugate duality for cone d.c. Optimization is discussed andweak duality theorem is proved in a more general partially ordered linear topological vectorspace (generalizing the results in [11]).展开更多
线性乘积和规划已出现在工程实践和管理科学等领域,是一类NP-难问题。针对该问题目标函数的特殊结构,将其重构为一个D.C.(difference of convex functions)规划问题。再利用凹函数的凸包络,构造出了一种D.C.松弛问题,并将其分解为两个...线性乘积和规划已出现在工程实践和管理科学等领域,是一类NP-难问题。针对该问题目标函数的特殊结构,将其重构为一个D.C.(difference of convex functions)规划问题。再利用凹函数的凸包络,构造出了一种D.C.松弛问题,并将其分解为两个凸子问题。然后将该D.C.松弛与超矩形的标准二分法相结合,设计了新的分支定界算法,并分析了其理论收敛性和计算复杂度。最后,借助大量数值实验验证了该算法的有效性。展开更多
Metal 3D printing holds great promise for future digitalized manufacturing.However,the intricate interplay between laser and metal powders poses a significant challenge for conventional trial-and-error optimization.Me...Metal 3D printing holds great promise for future digitalized manufacturing.However,the intricate interplay between laser and metal powders poses a significant challenge for conventional trial-and-error optimization.Meanwhile,the“optimized”yet fixed parameters largely limit possible extensions to new designs and materials.Herein,we report a high throughput design coupled with machine learning(ML)guidance to eliminate the notorious cracks and porosities in metal 3D printing for improved corrosion resistance and overall performance.The high throughput methodologies are mostly on obtaining the printed samples and their structural and physical properties,while ML is used for data analysis by model building for prediction(optimization),and understanding.For 316L stainless steel,we concurrently printed 54 samples with different parameters and subjected them to parallel tests to generate an extensive dataset for ML analysis.An ensemble learning model outperformed the other five single learners while Bayesian active learning recommended optimal parameters that could reduce porosity from 0.57%to below 0.1%.Accordingly,the ML-recommended samples showed higher tensile strength(609.28 MPa)and elongation(50.67%),superior anti-corrosion(I_(corr)=4.17×10^(-8) A·cm^(-2)),and stable alkaline oxygen evolution for>100 hours(at 500 mA·cm^(-2)).Remarkably,through the correlation analysis of printing parameters and targeted properties,we find that the influence of hardness on corrosion resistance is second only to porosity.We then expedited optimization in AlSi7Mg using the learned knowledge and feed hardness and relative density,thus demonstrating the method’s general extensibility and efficiency.Our strategy can significantly accelerate the optimization of metal 3D printing and facilitate adaptable design to accommodate diverse materials and requirements.展开更多
The SafeAmpCase is an innovative 3D-printed solution developed to address critical challenges in transporting and storing fragile glass drug ampoules during emergencies.This study employs a multidisciplinary approach...The SafeAmpCase is an innovative 3D-printed solution developed to address critical challenges in transporting and storing fragile glass drug ampoules during emergencies.This study employs a multidisciplinary approach—integrating biomedical engineering,advanced materials science,and emergency medicine expertise—to develop a compact,durable,and user-friendly ampoule case.A key innovation lies in the strategic selection of thermoplastic polyurethane(TPU)as the material,leveraging its superior impact resistance,flexibility,and noise-damping characteristics to ensure reliability under performance in demanding real-world conditions.To optimize the 3D printing process,key parameters,including printing temperature(220-250℃),volumetric flow rate(3-20 mm^(3)/s),retraction speed(30-90 mm/s),and retraction length(0.4-1.2 mm),were systematically adjusted using calibration models.The final optimized parameters(245℃,7 mm^(3)/s,90 mm/s,and 1.2 mm)reduced production time by 43%while preserving structural integrity.American Society for Testing and Materials(ASTM)international standard drop tests confirmed the case’s exceptional impact resistance,demonstrating a 90%reduction in ampoule breakage compared to polylactic acid plus.Further refinements,guided by feedback from 25 emergency professionals,resulted in medicationspecific color coding and an enhanced locking mechanism for usability in high-pressure situations.The final SafeAmpCase model withstood 18 consecutive drop trials without ampoule breakage,confirming its robustness in field conditions.This research underscores the transformative potential of additive manufacturing in developing customized,high-performance solutions for critical healthcare applications,setting a new benchmark for biomedical device design and rapid prototyping.展开更多
Increasing the texture complexity of high-performance surfaces can enhance their antifriction properties by altering their distribution and retention of lubricating oils.When a fluid flows through a fish-scale texture...Increasing the texture complexity of high-performance surfaces can enhance their antifriction properties by altering their distribution and retention of lubricating oils.When a fluid flows through a fish-scale texture,a lubricating layer is formed,effectively reducing friction.In this study,a bionic fish-scale structure is proposed,and ceramic components are fabricated and analyzed using micro/nano additive-manufacturing technology.First,the effects of various parameters on the antifriction performance of the fish-scale texture under hydrodynamic lubrication conditions are investigated.Then,the pressure distribution of the oil film—including both positive and negative pressures—is simulated by adjusting parameters such as the angleα,ratio of textured area to total surface area,and depth of the fish-scale texture.The results indicate that for a textured area that accounts for 20%of the total surface,texture depth of 150μm,and angleαof 30°,the pressure differential reaches its maximum.Finally,based on the optimized parameters,the designed fish-scale structure is fabricated using micro/nano ceramic three-dimensional-printing technology.Friction and wear tests are conducted on the sintered samples.The experimental results align well with the simulation data,indicating that the structure can reduce the friction coefficient by approximately 15%,thereby significantly improving the antifriction performance.This study provides a valuable reference for the surface engineering of other high-performance functional structures.展开更多
本文是D.C.隶属函数模糊集及其应用系列研究的第二部分。指出在实际问题中普遍选用的三角形、半三角形、梯形、半梯形、高斯型、柯西型、S形、Z形、π形隶属函数模糊集等均为D.C.隶属函数模糊集,建立了D.C.隶属函数模糊集对模糊集的万...本文是D.C.隶属函数模糊集及其应用系列研究的第二部分。指出在实际问题中普遍选用的三角形、半三角形、梯形、半梯形、高斯型、柯西型、S形、Z形、π形隶属函数模糊集等均为D.C.隶属函数模糊集,建立了D.C.隶属函数模糊集对模糊集的万有逼近性。探讨了D.C.隶属函数模糊集与模糊数之间的关系,给出了用D.C.隶属函数模糊集逼近模糊数的-εC e llina逼近形式,得到模糊数与D.C.函数之间的一个对应算子,指出了用模糊数表示D.C.函数的问题。展开更多
沙戈荒区域丰富的风光热资源有利于支撑高能耗数据中心集群快速发展,但会使其面临算力负载强时变性、风光出力间歇性及恶劣天气离网运行可靠性的多重挑战。为此,该文提出一种考虑任务负载需求响应及源荷不确定性的数据中心集群微网电-...沙戈荒区域丰富的风光热资源有利于支撑高能耗数据中心集群快速发展,但会使其面临算力负载强时变性、风光出力间歇性及恶劣天气离网运行可靠性的多重挑战。为此,该文提出一种考虑任务负载需求响应及源荷不确定性的数据中心集群微网电-热设备容量协同优化配置方法。首先,根据计算任务对时延的敏感性,精细化建模可推迟可中断、可推迟不可中断及不可推迟3类任务负载的时间约束,在此基础上综合源荷不确定性建立数据中心集群微网“并网-离网”2阶段分布鲁棒优化模型,采用列与约束生成(column and constraint generation,C&CG)算法求解。以青海某实际数据中心为案例的分析结果表明:所提出的方法可使微网容量配置成本下降约25.8%,弃风率下降约56%,并大幅提高数据中心集群微网离网运行可靠性。该文研究为沙戈荒区域绿色低碳数据中心建设提供了理论支撑。展开更多
基金funded by the National Key R&D Program of China,China(No.2024YFF0507903)the National Key Research and Development Program of China(Grant No.2024YFF0507904)the National Natural Science Foundation of China,China(Grant No.52379114).These supports are gratefully acknowledged.
文摘In-situ enlargement of super-large-span tunnels can intensify excavation-induced unloading in the surrounding rock,increasing deformation demand and failure risk during construction.This study combines laboratory model tests with FLAC3D simulations to evaluate the stabilizing role of prestressed anchor cables and to establish an energy-balance framework for support optimization.Comparative model tests of existing and enlarged tunnel sections,with and without anchors,show that reinforcement increases load-carrying capacity,reduces displacement,and confines damage to more localized zones.The numerical simulations reproduce displacement fields,shear-strain localization,and plastic-zone evolution with good agreement against the experimental observations.The energy framework is implemented in the in-situ simulations by quantifying unloading-related energy release in the rock mass and reinforcement work contributed by the anchors,and by introducing an energy release–reinforcement ratio as a stability indicator.Parametric analyses indicate that anchor length,spacing,and prestress influence stability in a nonlinear manner,with diminishing returns once reinforcement extends beyond the mechanically dominant deformation zone.An efficient parameter window is identified that improves deformation and yielding control while avoiding unnecessary reinforcement.The results provide an energy-consistent and design-oriented basis for prestressed anchorage selection in large-span tunnel expansion.
基金Supported by the State Foundations of Ph.D.Units(20020141013)Supported by the NSF of China(10001007)
文摘Some properties of a class of quasi-differentiable functions（the difference of two finite convex functions） are considered in this paper. And the convergence of the steepest descent algorithm for unconstrained and constrained quasi-differentiable programming is proved.
文摘This paper derives first order necessary and sufficient conditions for unconstrained coned.c. Programming problems where the underlined space is partially ordered with respect to acone. These conditions are given in terms of directional derivatives and subdifferentials of thecomponent functions. Moreover, conjugate duality for cone d.c. Optimization is discussed andweak duality theorem is proved in a more general partially ordered linear topological vectorspace (generalizing the results in [11]).
文摘线性乘积和规划已出现在工程实践和管理科学等领域,是一类NP-难问题。针对该问题目标函数的特殊结构,将其重构为一个D.C.(difference of convex functions)规划问题。再利用凹函数的凸包络,构造出了一种D.C.松弛问题,并将其分解为两个凸子问题。然后将该D.C.松弛与超矩形的标准二分法相结合,设计了新的分支定界算法,并分析了其理论收敛性和计算复杂度。最后,借助大量数值实验验证了该算法的有效性。
基金sponsored by the National Key Research and Development Program of China(No.2023YFB4604800,2021YFA1202300)the Natural and Science Foundation of China(Grant Nos.52201041,52275331,52205358)+1 种基金the Key Research and Development Program of Hubei Province(Nos.2024BCB091,2022CFA031)the Hong Kong Scholars Program(No.XJ2022014)。
文摘Metal 3D printing holds great promise for future digitalized manufacturing.However,the intricate interplay between laser and metal powders poses a significant challenge for conventional trial-and-error optimization.Meanwhile,the“optimized”yet fixed parameters largely limit possible extensions to new designs and materials.Herein,we report a high throughput design coupled with machine learning(ML)guidance to eliminate the notorious cracks and porosities in metal 3D printing for improved corrosion resistance and overall performance.The high throughput methodologies are mostly on obtaining the printed samples and their structural and physical properties,while ML is used for data analysis by model building for prediction(optimization),and understanding.For 316L stainless steel,we concurrently printed 54 samples with different parameters and subjected them to parallel tests to generate an extensive dataset for ML analysis.An ensemble learning model outperformed the other five single learners while Bayesian active learning recommended optimal parameters that could reduce porosity from 0.57%to below 0.1%.Accordingly,the ML-recommended samples showed higher tensile strength(609.28 MPa)and elongation(50.67%),superior anti-corrosion(I_(corr)=4.17×10^(-8) A·cm^(-2)),and stable alkaline oxygen evolution for>100 hours(at 500 mA·cm^(-2)).Remarkably,through the correlation analysis of printing parameters and targeted properties,we find that the influence of hardness on corrosion resistance is second only to porosity.We then expedited optimization in AlSi7Mg using the learned knowledge and feed hardness and relative density,thus demonstrating the method’s general extensibility and efficiency.Our strategy can significantly accelerate the optimization of metal 3D printing and facilitate adaptable design to accommodate diverse materials and requirements.
基金Open access funding provided by Ben-Gurion University.
文摘The SafeAmpCase is an innovative 3D-printed solution developed to address critical challenges in transporting and storing fragile glass drug ampoules during emergencies.This study employs a multidisciplinary approach—integrating biomedical engineering,advanced materials science,and emergency medicine expertise—to develop a compact,durable,and user-friendly ampoule case.A key innovation lies in the strategic selection of thermoplastic polyurethane(TPU)as the material,leveraging its superior impact resistance,flexibility,and noise-damping characteristics to ensure reliability under performance in demanding real-world conditions.To optimize the 3D printing process,key parameters,including printing temperature(220-250℃),volumetric flow rate(3-20 mm^(3)/s),retraction speed(30-90 mm/s),and retraction length(0.4-1.2 mm),were systematically adjusted using calibration models.The final optimized parameters(245℃,7 mm^(3)/s,90 mm/s,and 1.2 mm)reduced production time by 43%while preserving structural integrity.American Society for Testing and Materials(ASTM)international standard drop tests confirmed the case’s exceptional impact resistance,demonstrating a 90%reduction in ampoule breakage compared to polylactic acid plus.Further refinements,guided by feedback from 25 emergency professionals,resulted in medicationspecific color coding and an enhanced locking mechanism for usability in high-pressure situations.The final SafeAmpCase model withstood 18 consecutive drop trials without ampoule breakage,confirming its robustness in field conditions.This research underscores the transformative potential of additive manufacturing in developing customized,high-performance solutions for critical healthcare applications,setting a new benchmark for biomedical device design and rapid prototyping.
基金supported by Shanghai Collaborative Innovation Project(Grant No.XTCX-KJ-2024-01)the National Natural Science Foundation of China(Grant No.52205493).
文摘Increasing the texture complexity of high-performance surfaces can enhance their antifriction properties by altering their distribution and retention of lubricating oils.When a fluid flows through a fish-scale texture,a lubricating layer is formed,effectively reducing friction.In this study,a bionic fish-scale structure is proposed,and ceramic components are fabricated and analyzed using micro/nano additive-manufacturing technology.First,the effects of various parameters on the antifriction performance of the fish-scale texture under hydrodynamic lubrication conditions are investigated.Then,the pressure distribution of the oil film—including both positive and negative pressures—is simulated by adjusting parameters such as the angleα,ratio of textured area to total surface area,and depth of the fish-scale texture.The results indicate that for a textured area that accounts for 20%of the total surface,texture depth of 150μm,and angleαof 30°,the pressure differential reaches its maximum.Finally,based on the optimized parameters,the designed fish-scale structure is fabricated using micro/nano ceramic three-dimensional-printing technology.Friction and wear tests are conducted on the sintered samples.The experimental results align well with the simulation data,indicating that the structure can reduce the friction coefficient by approximately 15%,thereby significantly improving the antifriction performance.This study provides a valuable reference for the surface engineering of other high-performance functional structures.
文摘本文是D.C.隶属函数模糊集及其应用系列研究的第二部分。指出在实际问题中普遍选用的三角形、半三角形、梯形、半梯形、高斯型、柯西型、S形、Z形、π形隶属函数模糊集等均为D.C.隶属函数模糊集,建立了D.C.隶属函数模糊集对模糊集的万有逼近性。探讨了D.C.隶属函数模糊集与模糊数之间的关系,给出了用D.C.隶属函数模糊集逼近模糊数的-εC e llina逼近形式,得到模糊数与D.C.函数之间的一个对应算子,指出了用模糊数表示D.C.函数的问题。
文摘沙戈荒区域丰富的风光热资源有利于支撑高能耗数据中心集群快速发展,但会使其面临算力负载强时变性、风光出力间歇性及恶劣天气离网运行可靠性的多重挑战。为此,该文提出一种考虑任务负载需求响应及源荷不确定性的数据中心集群微网电-热设备容量协同优化配置方法。首先,根据计算任务对时延的敏感性,精细化建模可推迟可中断、可推迟不可中断及不可推迟3类任务负载的时间约束,在此基础上综合源荷不确定性建立数据中心集群微网“并网-离网”2阶段分布鲁棒优化模型,采用列与约束生成(column and constraint generation,C&CG)算法求解。以青海某实际数据中心为案例的分析结果表明:所提出的方法可使微网容量配置成本下降约25.8%,弃风率下降约56%,并大幅提高数据中心集群微网离网运行可靠性。该文研究为沙戈荒区域绿色低碳数据中心建设提供了理论支撑。
