The paper investigates the medium-term self-healing performance of fiber reinforced cementitious composites with intrinsic crack-width control capability under natural weathering. The pre-cracked specimens with different damage levels are exposed to various humidity conditions, namely, water submersion, natural weathering, and a laboratory environment with constant humidity. The medium-term self-healing performance is evaluated using a resonant frequency test, tensile test, SEM, and EDX. It is concluded that the medium-term cracked specimens can moderately recover their mechanical properties within 90 days after being submerged in water or exposed to natural weathering. In particular, they are able to resume the multiple cracking behavior and exhibit a reloading strength larger than the preloading strength. Furthermore, the identified compositions of the medium-term healing products for specimens exposed to water and natural weathering conditions are similarly characterized. The reported results imply that effective medium-term self-healing can be realized in fiber reinforced cementitious composites with intrinsic crack-width control capability under natural weathering. 相似文献
During high-temperature compression tests on intermetallic Mo5SiB2, the dislocation microstructures vary with increasing temperature and strain rate. At 1400 °C, an increasing tendency exists for slip planes to be of an unexpected type (e.g., {143) and {523)) as a function of the decreasing strain rate and increasing strain that originates from a dislocation climb. As the temperature increases to 1600 °C, the internal strain rate of 6.07 × 10− 3 s− 1 from the dislocation climb at 4% strain exceeds the applied value of 1.67 × 10− 3 s− 1, and thus, the climb mainly controls the plastic strain, as evidenced by a strength that is lower than that at 1200 °C under the same conditions. 相似文献
Activated carbons (ACs) are widely used in the purification of drinking water without almost any knowledge about the adsorption mechanisms of the persistent organic pollutants. Chlordecone (CLD, Kepone) is an organochlorinated synthetic compound that has been used mainly as agricultural insecticide. CLD has been identified and listed as a persistent organic pollutant by the Stockholm Convention. The selection of the best suited AC for this type of contaminants is mainly an empirical and costly process. A theoretical study of the influence of AC surface groups (SGs) on CLD adsorption is done in order to help understanding the process. This may provide a first selection criteria for the preparation of AC with suitable surface properties. A model of AC consisting of a seven membered ring graphene sheet (coronene) with a functional group on the edge was used to evaluate the influence of the SGs over the adsorption. Multiple Minima Hypersurface methodology (MMH) coupled with PM7 semiempirical Hamiltonian was employed in order to study the interactions of the chlordecone with SGs (hydroxyl and carboxyl) at acidic and neutral pH and different hydration conditions. Selected structures were re-optimized using CAM-B3LYP to achieve a well-defined electron density to characterize the interactions by the Quantum Theory of Atoms in Molecules approach. The deprotonated form of surface carboxyl and hydroxyl groups of AC models show the strongest interactions, suggesting a chemical adsorption. An increase in carboxylic SGs content is proposed to enhance CLD adsorption onto AC at neutral pH conditions. 相似文献
The joint optimal operation of cascade reservoir system can greatly improve the utilization of water resources. However, the complex high-dimensional and non-linear features and calculated costs often hinder the refined operation and management of reservoirs. Recently, the local parallel computing has become an effective way to alleviate the "curse of dimensionality". Current local parallel computing has hardware limitations, which is difficult to adapt to large-scale computing. This study proposes a novel parallel dynamic programming algorithm based on Spark (PDPoS) via cloud computing. The simulation experiments are carried out for a comparative analysis of the solution efficiency, influence factors and stability of cloud computing. The results are as follows: (1) The efficiency of the cloud-based PDPoS is related to some factors; the number of CPU cores is the main influencing factor, followed by the operator, and the architecture has the least influence. (2) The runtime variance of cloud computing is 2.03, indicating cloud computing has high stability. (3) Under the same configuration (i.e., CPU and memory), the runtime of cloud computing is 41.5%?~?110.3% longer than that of physical machines. However, cloud computing has rich resources, good scalability, and good portability of online operations, which is an attractive alternative for optimal operation of large-scale reservoir system.