Preisach model is widely used in modeling of smart materials. Although first order reversal curves （FORCs） have often found applications in the fields of physics and geology, they are able to serve to identify Preis...Preisach model is widely used in modeling of smart materials. Although first order reversal curves （FORCs） have often found applications in the fields of physics and geology, they are able to serve to identify Preisach model. In order to clarify the relationship between the Preisach model and the first order reversal curves, this paper is directed towards： （1） giving the reason a first order reversal curve is introduced; （2） presenting, for identifying Preisach model, two discrete methods, which are analytically based on first order reversal curves. Herein also is indicated the solution＇s uniqueness of these two identifying methods. At last, the validity of these two methods is verified by simulating a real smart actuator both methods have been applied to.展开更多
为了突破工程结构数字孪生系统中物理传感覆盖度有限的瓶颈,提出了一种基于人工智能增强型降阶模型(AI-Reduced Order Model, AI-ROM)的虚拟传感技术,能够融合多源物理传感数据,实现复杂结构全域响应的实时推演。方法上,基于降阶模型理...为了突破工程结构数字孪生系统中物理传感覆盖度有限的瓶颈,提出了一种基于人工智能增强型降阶模型(AI-Reduced Order Model, AI-ROM)的虚拟传感技术,能够融合多源物理传感数据,实现复杂结构全域响应的实时推演。方法上,基于降阶模型理论将结构响应视为一组降阶基的线性组合,从而将虚拟传感等效为实测响应数据约束下的降阶基组合系数优化问题,依此构造了可考虑跨力学场虚拟传感的深度学习损失函数,提出了基于标准注意力机制的组合系数智能预测模型,利用局部监测数据完成结构全域响应的精准重构。依托狮子洋大桥钢板-混凝土组合塔壁足尺压弯试验,验证智能虚拟传感方法的有效性。利用精细数值模型生成压弯工况下下全过程响应数据训练部署AI-ROM模型,将试验中的6个位移计与17个应变计实测数据作为响应重构约束条件。结果表明:AI-ROM模型成功实现了基于有限传感数据的跨力学场全域响应重构,即使对于离散性较高的应变场,AI-ROM重构的相对误差为9.1%,相较于精细有限元结果,精度提升了63.5%;借助智能虚拟传感技术,进一步提出了考虑分析区域分片聚类的传感器优化布置算法,通过迭代评估响应重构精度确定关键监测点空间分布,在塔壁足尺试验中,该算法可使应变传感器数量减少58.8%。提出的智能虚拟传感技术有助于实现工程结构数字孪生广域感知-实时仿真一体化要求,为建筑与基础设施运维安全风险评价提供了更为全面的信息支持。展开更多
This paper presents some recent developments in modelling and numerical analysis of piezoelectric systems and controlled smart structures based on a ?nite element formulation with embedded control. The control aims at...This paper presents some recent developments in modelling and numerical analysis of piezoelectric systems and controlled smart structures based on a ?nite element formulation with embedded control. The control aims at vibration suppression of the structure subjected to external disturbances, like wind and noise, under the presence of model inaccuracies, using the available measurements and controls. A smart structure under dynamic loads is analysed and comparison between results for beam with and without control is made. The numerical results show that the control strategy is very effective and suppresses the vibrations of the structure.展开更多
随着区块链技术的广泛应用,智能合约的安全性问题日益突出.交易顺序依赖(transaction order dependency,TOD)漏洞是一种常见且危害性极大的漏洞,可能引发严重的经济损失.现有漏洞检测方法主要分为静态分析和动态分析,但仍存在误报率高...随着区块链技术的广泛应用,智能合约的安全性问题日益突出.交易顺序依赖(transaction order dependency,TOD)漏洞是一种常见且危害性极大的漏洞,可能引发严重的经济损失.现有漏洞检测方法主要分为静态分析和动态分析,但仍存在误报率高、关键路径覆盖不足及对固定规则依赖等局限性.为此,本文提出了一种基于函数依赖指导的TOD漏洞检测框架FuncFuzz.该框架通过静态分析模块提取合约的关键函数依赖,精准定位脆弱区域,提升测试用例生成的针对性;设计多样化的交易变异策略,扩展测试用例的覆盖范围;并引入基于状态的一致性判定机制,以突破传统固定模式的限制,动态适应复杂或未知的漏洞场景.实验结果表明,FuncFuzz在检测TOD漏洞的有效性方面优于现有工具,同时函数依赖指导有效增强了检测效果.展开更多
基金National Natural Science Foundation of China (50674005)
文摘Preisach model is widely used in modeling of smart materials. Although first order reversal curves （FORCs） have often found applications in the fields of physics and geology, they are able to serve to identify Preisach model. In order to clarify the relationship between the Preisach model and the first order reversal curves, this paper is directed towards： （1） giving the reason a first order reversal curve is introduced; （2） presenting, for identifying Preisach model, two discrete methods, which are analytically based on first order reversal curves. Herein also is indicated the solution＇s uniqueness of these two identifying methods. At last, the validity of these two methods is verified by simulating a real smart actuator both methods have been applied to.
文摘为了突破工程结构数字孪生系统中物理传感覆盖度有限的瓶颈,提出了一种基于人工智能增强型降阶模型(AI-Reduced Order Model, AI-ROM)的虚拟传感技术,能够融合多源物理传感数据,实现复杂结构全域响应的实时推演。方法上,基于降阶模型理论将结构响应视为一组降阶基的线性组合,从而将虚拟传感等效为实测响应数据约束下的降阶基组合系数优化问题,依此构造了可考虑跨力学场虚拟传感的深度学习损失函数,提出了基于标准注意力机制的组合系数智能预测模型,利用局部监测数据完成结构全域响应的精准重构。依托狮子洋大桥钢板-混凝土组合塔壁足尺压弯试验,验证智能虚拟传感方法的有效性。利用精细数值模型生成压弯工况下下全过程响应数据训练部署AI-ROM模型,将试验中的6个位移计与17个应变计实测数据作为响应重构约束条件。结果表明:AI-ROM模型成功实现了基于有限传感数据的跨力学场全域响应重构,即使对于离散性较高的应变场,AI-ROM重构的相对误差为9.1%,相较于精细有限元结果,精度提升了63.5%;借助智能虚拟传感技术,进一步提出了考虑分析区域分片聚类的传感器优化布置算法,通过迭代评估响应重构精度确定关键监测点空间分布,在塔壁足尺试验中,该算法可使应变传感器数量减少58.8%。提出的智能虚拟传感技术有助于实现工程结构数字孪生广域感知-实时仿真一体化要求,为建筑与基础设施运维安全风险评价提供了更为全面的信息支持。
文摘This paper presents some recent developments in modelling and numerical analysis of piezoelectric systems and controlled smart structures based on a ?nite element formulation with embedded control. The control aims at vibration suppression of the structure subjected to external disturbances, like wind and noise, under the presence of model inaccuracies, using the available measurements and controls. A smart structure under dynamic loads is analysed and comparison between results for beam with and without control is made. The numerical results show that the control strategy is very effective and suppresses the vibrations of the structure.
文摘随着区块链技术的广泛应用,智能合约的安全性问题日益突出.交易顺序依赖(transaction order dependency,TOD)漏洞是一种常见且危害性极大的漏洞,可能引发严重的经济损失.现有漏洞检测方法主要分为静态分析和动态分析,但仍存在误报率高、关键路径覆盖不足及对固定规则依赖等局限性.为此,本文提出了一种基于函数依赖指导的TOD漏洞检测框架FuncFuzz.该框架通过静态分析模块提取合约的关键函数依赖,精准定位脆弱区域,提升测试用例生成的针对性;设计多样化的交易变异策略,扩展测试用例的覆盖范围;并引入基于状态的一致性判定机制,以突破传统固定模式的限制,动态适应复杂或未知的漏洞场景.实验结果表明,FuncFuzz在检测TOD漏洞的有效性方面优于现有工具,同时函数依赖指导有效增强了检测效果.
