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[Display omitted] • Conducting eight laterally loaded composite T-joint tests with different molding processes. • Applying network-free renormalization to characterize composite T-joints' cracking/failure. • Applying clustering algorithm to reveal composite T-joints' phase transition loads. • Verifying phase transition loads of composite T-joints from a renormalization perspective. Delamination or crack are standard failure patterns of composite T-joints. Most existing studies focus on pull-off loaded composite T-joint cracking but little focus on adverse conditions such as lateral loading. The mainstream composite T-joint research predicts the macroscale failure based on the composite's microscale/mesoscale crack starting and evolution. However, the cracking process is within the microscale, mesoscale, and macroscale, making detecting its starting based on phenomena complicated. This work attempts to directly model the macroscale deformation distribution from a thermodynamic perspective to reveal the cracking/failure evolution of a laterally loaded composite T-joint. Firstly, we conducted eight laterally loaded composite T-joint tests with different molding processes. Then, network-free renormalization was applied to construct Matrices (Modes) and Hamiltonians (Characteristic parameters) that can characterize their cracking evolution process. Further, a clustering algorithm was applied to reveal the cracking starting points (phase transition loads) embedded in the macroscale deformation distribution. We can verify its rationality by comparing the composite T-joints localized and systematic phase transition loads based on Wilson's phase transition theory. In summary, this work applies network-free renormalization and clustering algorithms from a thermodynamic perspective to reveal the cracking starting point embedded in the macroscale deformation distribution of the laterally loaded composite T-joints. [ABSTRACT FROM AUTHOR]

I-section carbon fiber reinforced polymer (I-CFRP) laminates are widely used as hatch and cargo doors of wide-body airliners. However, estimating the loading capacity of I-CFRP laminates has always been empirically dependent since there is no uniform failure criterion for composite materials. This study attempts to reveal the failure characteristic points of I-CFRP laminates from a thermodynamic perspective. First, the test strain data can be modeled as state variables, thus equating the loaded engineering structure to a thermodynamic system. Based on the relation of state variables, matrices (Modes) and Hamiltonians (Characteristic parameters) that characterize the overall stressing state evolution of the specimen can be established. Integrating the Hamiltonians of each part into the whole is similar to the group representation and renormalization of Wilson's phase transition theory. Applying the clustering analysis (CA) criterion in combination with the bifurcation and transition of the mode and characteristic parameter curves reveals the phase transformation loads of the specimen. The accuracy and stability can be verified for the phase transition loads before and after the renormalization transformation. In conclusion, this study reveals the deformation-failure law of I-CFRP laminates from the thermodynamic perspective, which provides a new reference and method for the design of composite laminates. [Display omitted] • Eleven I-CFRP laminates axial compression tests were conducted. • Modeling the behavior of I-CFRP laminates from a thermodynamic perspective. • Propose a matrix representation (Mode) and Hamiltonian (Characteristic parameter) of the I-CFRP laminates' stressing state. • Reveal the phase transition point of I-CFRP laminates: EPB and FS points. [ABSTRACT FROM AUTHOR]

The increasing global air traffic has placed higher demands on airport pavement design. However, the behavior of rigid concrete airport pavement (RCAP) under traffic loading is very complex, and the existing reliability theory and empirical concrete pavement analysis methods cannot detect the precise RCAP failure point. Based on this background, this paper attempts to study the failure of RCAP under traffic loading from a thermodynamic perspective. It selects the Federal Aviation Administration (FAA) test in Construction Cycle 8 (CC8) phase 3 as the research material. We apply the structural stressing state theory to equate the RCAP under traffic loading to a thermodynamic system with a phase transition, i.e., we model the whole process strain data as state variables. Then, analogous to the renormalization group method of Wilson's phase transition theory to reveal the critical point of the system, this study establishes matrixes (Modes) and Hamiltonians (Characteristic parameters) that can characterize the RCAP full-process stressing state evolution under traffic loading by accumulating the difference of state variables. We attempted to verify the effectiveness of this method under such complex working conditions, which can also be applied to many other high-speed time-variant loading conditions. By applying the clustering analysis criterion, we can reveal the phase transition points of the RCAP: elastoplastic branch (EPB), failure starting (FS), and progressive failure (PF) points, respectively. Taking the NW group as an example, the variances of EPB, FS, and PF points revealed by the mode and characteristic parameter curves conducted by the two homogeneous measured point selections, respectively, are 7.7,6.4, and 6.4, which are of exceptionally high stability. We also used thermodynamic modeling to reveal the phase transition points of the remaining three RCAPs and compared the effect of different joints on the phase transition points. Finally, this study also explores the feasibility of EPB-based concrete airport pavement design. [Display omitted] • Proposing to model the stressing state of RCAP from a thermodynamic perspective. • The stressing state matrixes and Hamiltonians of the RCAP are proposed. • Applying the clustering analysis criterion revealed the phase transition points of RCAP. • Compare the EPB and FS points for different joint types of RCAP. [ABSTRACT FROM AUTHOR]

China has promised to reduce its CO 2 emissions per gross domestic product (GDP) by 60–65% relative to 2005 emissions by 2030, which puts higher requirements for the quality of China's future economic development. Meanwhile, using current methods to scientifically analyze the realization path of CO 2 emission reduction while ensuring future economic development remains a challenge. This study develops a new inverse data envelopment analysis (DEA) method to analyze the annual realization path of CO 2 emission reduction and economic growth targets in China from 2020 to 2030. This method not only considers undesirable output and frontier changes but also analyzes the realization path of CO 2 emission reduction on the premise of ensuring economic growth. Moreover, the proposed method can analyze resource optimization allocation to achieve the corresponding goals, and its contributions to sustainable development are discussed. The results indicate that (1) In terms of CO 2 emission reduction, the eastern region will face the largest pressure of CO 2 emission reduction, accounting for 52.85% of the total CO 2 emission reduction, followed by the central region, accounting for 37.2%, and the western region will face the least pressure, accounting for 9.95%; whereas in terms of the change trend of CO 2 emission reduction, the eastern and central regions show opposite CO 2 emission reduction trends, while the trend in the western region is relatively stable. (2) At provincial level, CO 2 emission reduction shows a polarized distribution. Many provinces, such as Jiangsu, Guangdong, Hunan, and Chongqing, undertake great pressure to reduce CO 2 emission. However, some provinces, such as Shandong, Shanxi, and Yunnan, almost have no potential to reduce CO 2 emission while maintaining economic growth. (3) The increasement of human and energy resources input in the future is key to achieving CO 2 emission reduction and economic development goals. Finally, some useful implications are summarized by analyzing the results to provide powerful decision support for achieving CO 2 emission reduction and economic growth targets of China in 2030. • A new inverse DEA with undesirable output and frontier changes is developed. • Realization paths of CO 2 emission reduction and economic growth targets are analyzed. • Resource optimization plan for achieving the corresponding targets is discussed. • CO 2 emission reduction potential shows a spatial difference characteristic. • Targeted suggestions are summarized for the realization of China's CO 2 reduction. [ABSTRACT FROM AUTHOR]