Structural damage in heterogeneousmaterials typically originates frommicrostructures where stress concentration occurs.Therefore,evaluating the magnitude and location of localized stress distributions within microstru...Structural damage in heterogeneousmaterials typically originates frommicrostructures where stress concentration occurs.Therefore,evaluating the magnitude and location of localized stress distributions within microstructures under external loading is crucial.Repeating unit cells(RUCs)are commonly used to represent microstructural details and homogenize the effective response of composites.This work develops a machine learning-based micromechanics tool to accurately predict the stress distributions of extracted RUCs.The locally exact homogenization theory efficiently generates the microstructural stresses of RUCs with a wide range of parameters,including volume fraction,fiber/matrix property ratio,fiber shapes,and loading direction.Subsequently,the conditional generative adversarial network(cGAN)is employed and constructed as a surrogate model to establish the statistical correlation between these parameters and the corresponding localized stresses.The stresses predicted by cGAN are validated against the remaining true data not used for training,showing good agreement.This work demonstrates that the cGAN-based micromechanics tool effectively captures the local responses of composite RUCs.It can be used for predicting potential crack initiations starting from microstructures and evaluating the effective behavior of periodic composites.展开更多
This paper is a first pioneering attempt to apply the concept of resilience to the analysis of the public finance systems of local governments, a concept already used and "abused" in various disciplines and fields o...This paper is a first pioneering attempt to apply the concept of resilience to the analysis of the public finance systems of local governments, a concept already used and "abused" in various disciplines and fields of science. In particular, it proposes an attempt to estimate the recovery capacity of Italian Municipalities in a crucial period of our country's financial history, between 1992 and 2000, or between the currency crisis and the introduction of the Euro. However, the analysis also involved the subsequent trends, in order to demonstrate that the current vulnerability of the municipal public finance system, in particular of the Municipalities of Southern Italy, depends not only on the economic cycle but also on the continuous and incessant changes in the financing mechanisms of local governments established by the central government. The analysis showed a lower financial resilience of the Municipalities of the Mezzogiorno (island and continental) compared to those of the Center-North. The determinants of this phenomenon were found, for one part, through the analysis of the financial data of the Italian Municipalities - as presented by the SVIMEZ in its annual reports on the economy of the Mezzogiomo - and, for another part, through the critical synthesis of significant economic events which occurred during the period examined.展开更多
基金the support from the National Key R&D Program of China underGrant(Grant No.2020YFA0711700)the National Natural Science Foundation of China(Grant Nos.52122801,11925206,51978609,U22A20254,and U23A20659)G.W.is supported by the National Natural Science Foundation of China(Nos.12002303,12192210 and 12192214).
文摘Structural damage in heterogeneousmaterials typically originates frommicrostructures where stress concentration occurs.Therefore,evaluating the magnitude and location of localized stress distributions within microstructures under external loading is crucial.Repeating unit cells(RUCs)are commonly used to represent microstructural details and homogenize the effective response of composites.This work develops a machine learning-based micromechanics tool to accurately predict the stress distributions of extracted RUCs.The locally exact homogenization theory efficiently generates the microstructural stresses of RUCs with a wide range of parameters,including volume fraction,fiber/matrix property ratio,fiber shapes,and loading direction.Subsequently,the conditional generative adversarial network(cGAN)is employed and constructed as a surrogate model to establish the statistical correlation between these parameters and the corresponding localized stresses.The stresses predicted by cGAN are validated against the remaining true data not used for training,showing good agreement.This work demonstrates that the cGAN-based micromechanics tool effectively captures the local responses of composite RUCs.It can be used for predicting potential crack initiations starting from microstructures and evaluating the effective behavior of periodic composites.
文摘This paper is a first pioneering attempt to apply the concept of resilience to the analysis of the public finance systems of local governments, a concept already used and "abused" in various disciplines and fields of science. In particular, it proposes an attempt to estimate the recovery capacity of Italian Municipalities in a crucial period of our country's financial history, between 1992 and 2000, or between the currency crisis and the introduction of the Euro. However, the analysis also involved the subsequent trends, in order to demonstrate that the current vulnerability of the municipal public finance system, in particular of the Municipalities of Southern Italy, depends not only on the economic cycle but also on the continuous and incessant changes in the financing mechanisms of local governments established by the central government. The analysis showed a lower financial resilience of the Municipalities of the Mezzogiorno (island and continental) compared to those of the Center-North. The determinants of this phenomenon were found, for one part, through the analysis of the financial data of the Italian Municipalities - as presented by the SVIMEZ in its annual reports on the economy of the Mezzogiomo - and, for another part, through the critical synthesis of significant economic events which occurred during the period examined.