为了探究高速空气燃料热喷涂(activated combustion-high velocity air fuel,AC-HVAF)过程中喷涂粒子撞击基材后的沉积特性。采用AC-HVAF热喷涂技术在AZ80镁合金基体上沉积WC-10Co-4Cr硬质涂层。通过离散沉积实验获得薄层沉积粒子,探讨...为了探究高速空气燃料热喷涂(activated combustion-high velocity air fuel,AC-HVAF)过程中喷涂粒子撞击基材后的沉积特性。采用AC-HVAF热喷涂技术在AZ80镁合金基体上沉积WC-10Co-4Cr硬质涂层。通过离散沉积实验获得薄层沉积粒子,探讨各种沉积形貌的种类、形成原因、结合机制及射流中粒子的径向和轴向分布。结果表明:在AC-HVAF粒子沉积过程中,嵌入型沉积为主要的沉积形貌,同时包含少量的破碎型与空腔型沉积粒子。在涂层的形成过程中,嵌入型沉积对涂层/基体结合性能起重要作用;空腔型沉积的小颗粒及破碎型沉积的大颗粒是造成沉积效率下降的主要原因。喷涂粒子主要集中在射流中心,越靠近射流边缘,空腔型沉积粒子越多,最终导致AC-HVAF粒子射流呈现出空间分布特征。展开更多
为探究^(60)Co-γ辐照对苦荞麸皮中黄酮类物质提取效率的影响,本研究采用不同剂量(0、6、12、18、24、30 k Gy)的^(60)Co-γ对苦荞麸皮进行辐照预处理,通过热回流法提取苦荞黄酮,比较^(60)Co-γ辐照对苦荞黄酮提取得率、主要黄酮类物质...为探究^(60)Co-γ辐照对苦荞麸皮中黄酮类物质提取效率的影响,本研究采用不同剂量(0、6、12、18、24、30 k Gy)的^(60)Co-γ对苦荞麸皮进行辐照预处理,通过热回流法提取苦荞黄酮,比较^(60)Co-γ辐照对苦荞黄酮提取得率、主要黄酮类物质单体含量和总含量、抑菌活性及苦荞麸皮微观结构的影响。结果表明,6~30 k Gy剂量的^(60)Co-γ辐照预处理可提高苦荞黄酮提取得率,其中12 k Gy组提取得率最高,为6.97%,较对照组的3.27%提高3.70个百分点;6~30 k Gy剂量的^(60)Co-γ辐照预处理可提高提取物中芦丁含量,12、18、30 k Gy剂量的预处理可提高提取物中烟花苷含量,其中12 k Gy组含量最高,芦丁和烟花苷含量分别为84.52、3.92 mg·g^(-1),较对照组的53.12、3.54 mg·g^(-1)分别提高59.11%与10.73%;6~24 k Gy剂量的^(60)Co-γ辐照预处理可提高苦荞主要黄酮总含量,其中12 k Gy组最高,为89.40 mg·g^(-1),较对照组的57.95 mg·g^(-1)提高54.27%。此外,^(60)Co-γ辐照可有效破坏苦荞麸皮组织结构,有助于苦荞黄酮的溶出;6~18 k Gy剂量的^(60)Co-γ辐照预处理增强了提取物对大肠杆菌的抑菌活性,其中18 k Gy剂量组的抑菌活性最强,抑菌圈直径达9.93 mm;12~24 k Gy剂量的^(60)Co-γ辐照预处理增强了提取物对金黄色葡萄球菌的抑菌活性,其中12 k Gy剂量组的抑菌活性最强,抑菌圈直径达10.30 mm。本研究可为苦荞黄酮的高效提取提供研究基础与技术参考。展开更多
Large cavity structures are widely employed in aerospace engineering, such as thin-walled cylinders, blades andwings. Enhancing performance of aerial vehicles while reducing manufacturing costs and fuel consumptionhas...Large cavity structures are widely employed in aerospace engineering, such as thin-walled cylinders, blades andwings. Enhancing performance of aerial vehicles while reducing manufacturing costs and fuel consumptionhas become a focal point for contemporary researchers. Therefore, this paper aims to investigate the topologyoptimization of large cavity structures as a means to enhance their performance, safety, and efficiency. By usingthe variable density method, lightweight design is achieved without compromising structural strength. Theoptimization model considers both concentrated and distributed loads, and utilizes techniques like sensitivityfiltering and projection to obtain a robust optimized configuration. The mechanical properties are checked bycomparing the stress distribution and displacement of the unoptimized and optimized structures under the sameload. The results confirm that the optimized structures exhibit improved mechanical properties, thus offering keyinsights for engineering lightweight, high-strength large cavity structures.展开更多
Magnesium(Mg),being the lightest structural metal,holds immense potential for widespread applications in various fields.The development of high-performance and cost-effective Mg alloys is crucial to further advancing ...Magnesium(Mg),being the lightest structural metal,holds immense potential for widespread applications in various fields.The development of high-performance and cost-effective Mg alloys is crucial to further advancing their commercial utilization.With the rapid advancement of machine learning(ML)technology in recent years,the“data-driven''approach for alloy design has provided new perspectives and opportunities for enhancing the performance of Mg alloys.This paper introduces a novel regression-based Bayesian optimization active learning model(RBOALM)for the development of high-performance Mg-Mn-based wrought alloys.RBOALM employs active learning to automatically explore optimal alloy compositions and process parameters within predefined ranges,facilitating the discovery of superior alloy combinations.This model further integrates pre-established regression models as surrogate functions in Bayesian optimization,significantly enhancing the precision of the design process.Leveraging RBOALM,several new high-performance alloys have been successfully designed and prepared.Notably,after mechanical property testing of the designed alloys,the Mg-2.1Zn-2.0Mn-0.5Sn-0.1Ca alloy demonstrates exceptional mechanical properties,including an ultimate tensile strength of 406 MPa,a yield strength of 287 MPa,and a 23%fracture elongation.Furthermore,the Mg-2.7Mn-0.5Al-0.1Ca alloy exhibits an ultimate tensile strength of 211 MPa,coupled with a remarkable 41%fracture elongation.展开更多
文摘为了探究高速空气燃料热喷涂(activated combustion-high velocity air fuel,AC-HVAF)过程中喷涂粒子撞击基材后的沉积特性。采用AC-HVAF热喷涂技术在AZ80镁合金基体上沉积WC-10Co-4Cr硬质涂层。通过离散沉积实验获得薄层沉积粒子,探讨各种沉积形貌的种类、形成原因、结合机制及射流中粒子的径向和轴向分布。结果表明:在AC-HVAF粒子沉积过程中,嵌入型沉积为主要的沉积形貌,同时包含少量的破碎型与空腔型沉积粒子。在涂层的形成过程中,嵌入型沉积对涂层/基体结合性能起重要作用;空腔型沉积的小颗粒及破碎型沉积的大颗粒是造成沉积效率下降的主要原因。喷涂粒子主要集中在射流中心,越靠近射流边缘,空腔型沉积粒子越多,最终导致AC-HVAF粒子射流呈现出空间分布特征。
文摘为探究^(60)Co-γ辐照对苦荞麸皮中黄酮类物质提取效率的影响,本研究采用不同剂量(0、6、12、18、24、30 k Gy)的^(60)Co-γ对苦荞麸皮进行辐照预处理,通过热回流法提取苦荞黄酮,比较^(60)Co-γ辐照对苦荞黄酮提取得率、主要黄酮类物质单体含量和总含量、抑菌活性及苦荞麸皮微观结构的影响。结果表明,6~30 k Gy剂量的^(60)Co-γ辐照预处理可提高苦荞黄酮提取得率,其中12 k Gy组提取得率最高,为6.97%,较对照组的3.27%提高3.70个百分点;6~30 k Gy剂量的^(60)Co-γ辐照预处理可提高提取物中芦丁含量,12、18、30 k Gy剂量的预处理可提高提取物中烟花苷含量,其中12 k Gy组含量最高,芦丁和烟花苷含量分别为84.52、3.92 mg·g^(-1),较对照组的53.12、3.54 mg·g^(-1)分别提高59.11%与10.73%;6~24 k Gy剂量的^(60)Co-γ辐照预处理可提高苦荞主要黄酮总含量,其中12 k Gy组最高,为89.40 mg·g^(-1),较对照组的57.95 mg·g^(-1)提高54.27%。此外,^(60)Co-γ辐照可有效破坏苦荞麸皮组织结构,有助于苦荞黄酮的溶出;6~18 k Gy剂量的^(60)Co-γ辐照预处理增强了提取物对大肠杆菌的抑菌活性,其中18 k Gy剂量组的抑菌活性最强,抑菌圈直径达9.93 mm;12~24 k Gy剂量的^(60)Co-γ辐照预处理增强了提取物对金黄色葡萄球菌的抑菌活性,其中12 k Gy剂量组的抑菌活性最强,抑菌圈直径达10.30 mm。本研究可为苦荞黄酮的高效提取提供研究基础与技术参考。
基金the National Natural Science Foundation of China and the Natural Science Foundation of Jiangsu Province.It was also supported in part by Young Elite Scientists Sponsorship Program by CAST.
文摘Large cavity structures are widely employed in aerospace engineering, such as thin-walled cylinders, blades andwings. Enhancing performance of aerial vehicles while reducing manufacturing costs and fuel consumptionhas become a focal point for contemporary researchers. Therefore, this paper aims to investigate the topologyoptimization of large cavity structures as a means to enhance their performance, safety, and efficiency. By usingthe variable density method, lightweight design is achieved without compromising structural strength. Theoptimization model considers both concentrated and distributed loads, and utilizes techniques like sensitivityfiltering and projection to obtain a robust optimized configuration. The mechanical properties are checked bycomparing the stress distribution and displacement of the unoptimized and optimized structures under the sameload. The results confirm that the optimized structures exhibit improved mechanical properties, thus offering keyinsights for engineering lightweight, high-strength large cavity structures.
基金supported by the National Natural the Science Foundation of China(51971042,51901028)the Chongqing Academician Special Fund(cstc2020yszxjcyj X0001)+1 种基金the China Scholarship Council(CSC)Norwegian University of Science and Technology(NTNU)for their financial and technical support。
文摘Magnesium(Mg),being the lightest structural metal,holds immense potential for widespread applications in various fields.The development of high-performance and cost-effective Mg alloys is crucial to further advancing their commercial utilization.With the rapid advancement of machine learning(ML)technology in recent years,the“data-driven''approach for alloy design has provided new perspectives and opportunities for enhancing the performance of Mg alloys.This paper introduces a novel regression-based Bayesian optimization active learning model(RBOALM)for the development of high-performance Mg-Mn-based wrought alloys.RBOALM employs active learning to automatically explore optimal alloy compositions and process parameters within predefined ranges,facilitating the discovery of superior alloy combinations.This model further integrates pre-established regression models as surrogate functions in Bayesian optimization,significantly enhancing the precision of the design process.Leveraging RBOALM,several new high-performance alloys have been successfully designed and prepared.Notably,after mechanical property testing of the designed alloys,the Mg-2.1Zn-2.0Mn-0.5Sn-0.1Ca alloy demonstrates exceptional mechanical properties,including an ultimate tensile strength of 406 MPa,a yield strength of 287 MPa,and a 23%fracture elongation.Furthermore,the Mg-2.7Mn-0.5Al-0.1Ca alloy exhibits an ultimate tensile strength of 211 MPa,coupled with a remarkable 41%fracture elongation.
