Microstructure Control and Performance Evolution of Aluminum Alloy 7075 by Nano-Treating.

Nano-treating is a novel concept wherein a low percentage of nanoparticles is used for microstructural control and property tuning in metals and alloys. The nano-treating of AA7075 was investigated to control its microstructure and improve its structural stability for high performance. After treatment with TiC nanoparticles, the grains were significantly refined from coarse dendrites of hundreds of micrometers to fine equiaxial ones smaller than 20 μm. After T6 heat treatment, the grains, with an average size of 18.5 μm, remained almost unchanged, demonstrating an excellent thermal stability. It was found that besides of growth restriction factor by pinning behavior on grain boundries, TiC nanoparticles served as both an effective nucleation agent for primary grains and an effective secondary phase modifier in AA7075. Furthermore, the mechanical properties of nano-treated AA7075 were improved over those of the pure alloy. Thus, nano-treating provides a new method to enhance the performance of aluminum alloys for numerous applications

Periodic event-triggered output regulation for linear multi-agent systems

This study considers the problem of periodic event-triggered (PET) cooperative output regulation for a class of linear multi-agent systems. The advantage of the PET output regulation is that the data transmission and triggered condition are only needed to be monitored at discrete sampling instants. It is assumed that only a small number of agents can have access to the system matrix and states of the leader. Meanwhile, the PET mechanism is considered not only in the communication between various agents, but also in the sensor-to-controller and controller-to-actuator transmission channels for each agent. The above problem set-up will bring some challenges to the controller design and stability analysis. Based on a novel PET distributed observer, a PET dynamic output feedback control method is developed for each follower. Compared with the existing works, our method can naturally exclude the Zeno behavior, and the inter-event time becomes multiples of the sampling period. Furthermore, for every follower, the minimum inter-event time can be determined \textit{a prior}, and computed directly without the knowledge of the leader information. An example is given to verify and illustrate the effectiveness of the new design scheme.Comment: 17 pages, 13 figures, submitted to Automatica. accepte

Fourier-Flow model generating Feynman paths

As an alternative but unified and more fundamental description for quantum physics, Feynman path integrals generalize the classical action principle to a probabilistic perspective, under which the physical observables' estimation translates into a weighted sum over all possible paths. The underlying difficulty is to tackle the whole path manifold from finite samples that can effectively represent the Feynman propagator dictated probability distribution. Modern generative models in machine learning can handle learning and representing probability distribution with high computational efficiency. In this study, we propose a Fourier-flow generative model to simulate the Feynman propagator and generate paths for quantum systems. As demonstration, we validate the path generator on the harmonic and anharmonic oscillators. The latter is a double-well system without analytic solutions. To preserve the periodic condition for the system, the Fourier transformation is introduced into the flow model to approach a Matsubara representation. With this novel development, the ground-state wave function and low-lying energy levels are estimated accurately. Our method offers a new avenue to investigate quantum systems with machine learning assisted Feynman Path integral solving

Experimental investigations of CO2 adsorption behavior in shales: Implication for CO2 geological storage

Injecting CO2 into shale reservoirs has dual benefits for enhancing gas recovery and CO2 geological sequestration, which is of great significance to ensuring energy security and achieving the “Carbon Neutrality” for China. The CO2 adsorption behavior in shales largely determined the geological sequestration potential but remained uncharted. In this study, the combination of isothermal adsorption measurement and basic petro-physical characterization methods were performed to investigate CO2 adsorption mechanism in shales. Results show that the CO2 sorption capacity increase gradually with injection pressure before reaching an asymptotic maximum magnitude, which can be described equally well by the Langmuir model. TOC content is the most significant control factor on CO2 sorption capacity, and the other secondary factors include vitrinite reflectance, clay content, and brittle mineral content. The pore structure parameter of BET-specific surface area is a more direct factor affecting CO2 adsorption of shale than BJH pore volume. Langmuir CO2 adsorption capacity positive correlated with the surface fractal dimension (D1), but a significant correlation is not found with pore structure fractal dimension (D2). By introducing the Carbon Sequestration Leaders Forum and Department of Energy methods, the research results presented in this study can be extended to the future application for CO2 geological storage potential evaluation in shales

Holocene Earthquake Cycles of an Active Tectonic Block Boundary Fault Zone: A Case Study in the Qilian–Haiyuan Fault Zone, Northeastern Tibet Plateau

Fault zones along active tectonic block boundaries are a significant source of devastating continental earthquakes. Strong earthquakes produce disruptions of sediment and induce characteristic sediments near the fault, which serve as valuable sedimentary evidence for identifying and dating of paleoearthquakes. In this study, we aimed to reconstruct the earthquake history of the Qilian–Haiyuan fault zone in the northeastern Tibetan Plateau during the Holocene. We reanalyzed forty-four trenches and used the sedimentary sequences, event indicators, and age constraints to determine the earthquake history. Our analysis revealed the paleoearthquakes of 6 subsidiary faults of the Qilian–Haiyuan fault zone with accurate event ages and rupture extents. Based on the spatial and temporal distributions of strong earthquakes since 10 ka, we identified five earthquake clusters around the central-eastern Qilian–Haiyuan fault zone including seven rupture cascades where the earthquakes migrated gradually from east to west. The existing seismic gap reveals that the latest migration may not yet be complete and suggests a high probability of M ≥ 7 earthquakes occurring on the Jinqianghe fault, Maomaoshan fault, and the central part of the Lenglongling faults. We concluded that, in order to better understand earthquake cycles and seismic hazards, it is important to consider a fault zone as a whole, including multiple faults and their interaction on the earthquake triggering between nearby faults