Huazhong University of Science and Technology

This study serves as a basic study of the indoor dispersion of pollen particles, simulating the flow field and discussing the behavior of particles of different diameters in different rooms. By comparing the vertical velocity components of particles (w¯p$$ {\overline{w}}_{\mathrm{p}} $$) and the mean flow velocity of z‐direction component (wf$$ {w}_{\mathrm{f}} $$) plus the terminal settling velocity in a gravitational field (Vg$$ {V}_{\mathrm{g}} $$), the differences between w¯p$$ {\overline{w}}_{\mathrm{p}} $$ values and wf$$ {w}_{\mathrm{f}} $$ plus Vg$$ {V}_{\mathrm{g}} $$ values are found to occur mainly at locations close to the opposite wall of the inlet. The location of the differences between w¯p$$ {\overline{w}}_{\mathrm{p}} $$ values and wf$$ {w}_{\mathrm{f}} $$ plus Vg$$ {V}_{\mathrm{g}} $$ values is important findings of this study, which facilitates the improvement of the simulation method at a later stage and the rational design of indoor ventilation patterns to easily remove particles from the room. This figure shows the w¯p−wf+Vg/Uinlet$$ \left({\overline{w}}_{\mathrm{p}}-\left({w}_{\mathrm{f}}+{V}_{\mathrm{g}}\right)\right)/{U}_{\mathrm{inlet}} $$ for different particle diameters at a central plane. We can find w¯p=wf+Vg$$ {\overline{w}}_{\mathrm{p}}={w}_{\mathrm{f}}+{V}_{\mathrm{g}} $$ does not hold in some cases and the differences become significant as the particle size increases.

Wind turbines (WT) are prone to transient instability during weak grid faults, which is caused by their complex interactions. However, it is a challenge to analyze the transient stability, due to high-order and strong nonlinearity. Moreover, the existing works mainly focus on a phase-locked loop (PLL) system while ignoring current control, which cannot fully reflect the transient in stability mechanism. To fill this gap, this paper studies the transient stability of type-3 WT considering both PLL and current control. Firstly, to simplify the full model of type-3 WT, a slow-fast subsystem is established using the singular perturbation. Then, the sixth-order full model is simplified as a second-order slow subsystem and its small disturbance (i.e., fast subsystem). Based on it, the Lyapunov’s direct and indirect methods are adopted to analyze the stability of slow and fast subsystems, respectively. Meanwhile, the influence of various factors (e.g., the fault degree, grid inductance, current references, current controller and PLL controller) on transient stability of type-3 WT are revealed. In addition, the proposed analytical method combining singular perturbation and Lyapunov methods is a new approach to study transient stability, which can also be applied to other renewable energy resources. Finally, the analysis is validated by experiments.

Roll-to-Roll (R2R) printing systems are complex MIMO systems, which makes it difficult to design a register control scheme for them, much less high-precision learning control scheme. In this paper, a decoupling matrix-based simplification scheme is proposed to transform the complex MIMO system to be a simple one. According to the transformed system and the Lyapunov stability theory, a decoupling matrix-based learning control (DMBLC) scheme is proposed for the register control of R2R printing systems, while a data-based evaluation index is designed to assist DMBLC to achieve high register precision through continuous learning. The effectiveness of DMBLC is verified by simulations and experiments. Comparisons among DMBLC, dynamic matrix control and fully decoupled proportional differential control are carried out to show the superior performance of DMBLC.

We prove the global existence and the exponential time decay rates of the mild solutions to the Fokker–Planck–Boltzmann equation near Maxwellians if initial data satisfy some smallness in the function space Lk1LT∞Lv2. Compared with previous results, there are two features in this manuscript. The first is that we don’t need the velocity weight estimates in the work (Duan et al., 2021) with the help of the Fokker–Planck operator. The second is that we only need the low regularity space Lk1LT∞Lv2 rather than Hx,v4 in the work (Xiong et al., 2014). Our analysis is based on Lk1LT∞Lv2 function space introduced by the work of Duan et al. (2021) and the coercivity property of Fokker–Planck operator.

Background Immunosuppressive M2 macrophages in the tumor microenvironment (TME) can mediate the therapeutic resistance of tumors, and seriously affect the clinical efficacy and prognosis of tumor patients. This study aims to develop a novel drug delivery system for dual-targeting tumor and macrophages to inhibit tumor and induce macrophage polarization. Methods The anti-tumor effects of methyltransferase like 14 (METTL14) were investigated both in vitro and in vivo. The underlying mechanisms of METTL14 regulating macrophages were also explored in this study. We further constructed the cyclic (Arg-Gly-Asp) (cRGD) peptide modified macrophage membrane-coated nanovesicles to co-deliver METTL14 and the TLR4 agonist. Results We found that METTL14 significantly inhibits the growth of tumor in vitro. METTL14 might downregulate TICAM2 and inhibit the Toll-like receptor 4 (TLR4) pathway of macrophages, meanwhile, the combination of METTL14 and the TLR4 agonist could induce M1 polarization of macrophages. Macrophage membrane-coated nanovesicles are characterized by easy modification, drug loading, and dual-targeting tumor and macrophages, and cRGD modification can further enhance its targeting ability. It showed that the nanovesicles could improve the in vivo stability of METTL14, and dual-target tumor and macrophages to inhibit tumor and induce M1 polarization of macrophages. Conclusions This study anticipates achieving the dual purposes of tumor inhibition and macrophage polarization, and providing a new therapeutic strategy for tumors.

Control rod drive mechanism (CRDM) in nuclear reactors powered by two motor generator units running in parallel, an excitation fault in one of the generators will cause the terminal current to rise in another generator, which will cause the overcurrent protection to operate before the loss-of-excitation protection, resulting in nuclear reactor shutdown. To solve the problem of mismatch between loss-of-excitation protection and overcurrent protection, this paper applies the equivalent circuit and phase diagram analysis, obtains the conclusion that the generator terminal current phase after an excitation fault is significantly different from the current phase after a phase-to-phase short circuit fault, based on this, a generator overcurrent protection criterion of compound fundamental current phase difference is constructed, which can solve the maloperation of overcurrent protection under possible excitation fault in actual engineering. Simulation results of PSCAD/EMTDC verify the effectiveness of the proposed methods under different operating modes and fault conditions.

The loop closing operation can decrease the power outages of consumers and enhance the reliability of power supply. In low-voltage distribution network, to scientifically assess the risk of loop closing operation, and obtain the risk grade conclusion, a risk assessment method based on fuzzy comprehensive evaluation is proposed. Firstly, the risk assessment indicator system of loop closing operation is established, with the corresponding weights calculated. Secondly, the risk comment set and the calculation method of subordinate degrees are determined. Finally, the fuzzy method is adopted to obtain the risk grade conclusion of loop closing operation, which provides the rationale and technical support for the comprehensive promotion of loop closing operation in low-voltage distribution network. The method is applied to a 123-bus test system, and the risk of loop closing operation is divided into 5 grades. The assessment results are analyzed to verify the effectiveness and feasibility of the proposed method.

Compared with single-switch open-circuit faults (SOCFs), multiple switches open-circuit faults (MOCFs) of power electronic devices (PEDs) due to high voltage or current stress, false triggering, and manufacturing tolerance have become more challenging. To address this issue, a reconfigurable dual-active-bridge (R-DAB) converter is presented with a fast, accurate, robust, and low-cost fault detection (FD) and fault isolation (FI) scheme to accommodate both SOCFs and MOCFs. Compared with the standard dual active bridge (DAB) topology, the proposed R-DAB will utilize a center-tapped high-frequency transformer and two symmetrical auxiliary inductors, where inherent half-bridge conduction branches are capable of maintaining uninterrupted operations. The proposed FD and FI scheme is straightforward and universal since only the center-tap current in the primary and secondary bridge is monitored as the universal fault signature. Moreover, a simple and low-cost fault diagnostic circuit was designed, which can detect and isolate various open circuit faults (OCFs) of PEDs under varying input and output conditions, without using expensive voltage and current sensors. This sensorless fault diagnosis technique can achieve the fastest fault detection and isolation speed reported so far, which is within a couple of \boldmath $\mu s$ for various OCFs. Experimental results were acquired from an R-DAB prototype under various OCFs to validate the effectiveness of the proposed technique.

With the remarkable growth of renewable energy resources, the grid-forming (GFM) inverter with the function of grid voltage/frequency support attracts much attention. Due to the inverter-grid interaction, the stability of the GFM inverter is a critical issue. The passivity-based analysis approach, which was widely applied to the conventional grid-following inverter, has been proved to be promising. Yet, its application to the GFM inverter is still insufficient. To this end, this paper conducts a comprehensive passivity-based analysis for the GFM inverter with single-loop voltage control. It finds that the two indices of the passivity-based stability criterion, i.e., the individual stability and the output impedance passivity, bring identical constraints on the voltage controller, and the passivity cannot be ensured with typical voltage controllers. To shrink the unexpected non-passive frequency ranges, a generic grid-current feedforward scheme is explored, and the proper feedforward functions compatible with different voltage controllers are derived. With the proposed scheme, the passivity can be guaranteed up to the Nyquist frequency. Finally, experimental results from a 6-kVA prototype are provided to verify the theoretical analysis.

Acquiring accurate knowledge of nonlinear friction and load torque is of great interest for optimizing the control behavior of permanent-magnet synchronous motor (PMSM) drives. In this work, a friction-and-load adaptive identification scheme based on a parallel-observer-based network with model compensation (POBN-MC) is presented. The developed network possesses a parallel structure consisting of the designed two novel observers, which involve a gain-adaptation super-twisting load torque observer and a variable-learning-rate Adaline inertia observer. A non-empirical friction model is proposed to capture friction, forming the model compensation part that is exploited for correcting the torque input of the network. With a two-step mechanism derived from the POBN-MC, the proposed scheme attains the online adaptive identification of the friction and load torque in a manner that integrates both accuracy and simplicity. In the first step, an explicit mapping relationship between the nonlinear friction torque and the rotor speed is determined with the speed response triggered by the natural deceleration. The second step accomplishes the online observation with regard to friction-and-load information matching the real-time operating conditions. Sufficient theoretical analyses, as well as the validations of numerous simulations and experiments, are presented to support the suggested scheme.

The synchronous-switching dead-time optimization is critical for high-frequency SiC-based converters operating in the synchronous rectification mode. In previous research, the constant input capacitance C <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">iss</sub> from the datasheet was typically utilized for dead time optimization, which is obtained with a zero gate-source voltage ( V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">gs</sub> = 0). In practice, however, C <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">iss</sub> is strongly dependent on V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">gs</sub> and cannot be regarded as a constant during synchronous turn-off transient. Thus, this letter proposes an analytical model integrating V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">gs</sub> -dependent gate capacitance for optimal dead time design. Experimental results show that the proposed model can accurately predict the optimal dead time, with an average error less than 2 ns under all operating conditions for three types of SiC MOSFETs with different gate structures.

In the setting of federated optimization, where a global model is aggregated periodically, step asynchronism occurs when participants conduct model training by efficiently utilizing their computational resources. It is well acknowledged that step asynchronism leads to objective inconsistency under non-i.i.d. data, which degrades the model's accuracy. To address this issue, we propose a new algorithm FedaGrac , which calibrates the local direction to a predictive global orientation. Taking advantage of the estimated orientation, we guarantee that the aggregated model does not excessively deviate from the global optimum while fully utilizing the local updates of faster nodes. We theoretically prove that FedaGrac holds an improved order of convergence rate than the state-of-the-art approaches and eliminates the negative effect of step asynchronism. Empirical results show that our algorithm accelerates the training and enhances the final accuracy.

An efficient immersed boundary–lattice Boltzmann method (IB-LBM) is proposed for fully resolved simulations of suspended solid particles in viscoelastic flows. Stress LBM based on Giesekus and Oldroyd-B constitutive equation are used to model the viscoelastic stress tensor. A boundary thickening-based direct forcing IB method is adopted to solve the particle–fluid interactions with high accuracy for non-slip boundary conditions. A universal law is proposed to determine the diffusivity constant in a viscoelastic LBM model to balance the numerical accuracy and stability over a wide range of computational parameters. An asynchronous calculation strategy is adopted to further improve the computing efficiency. The method was firstly applicated to the simulation of sedimentation of a single particle and a pair of particles after good validations in cases of the flow past a fixed cylinder and particle migration in a Couette flow against FEM and FVM methods. The determination of the asynchronous calculation strategy and the effect of viscoelastic stress distribution on the settling behaviors of one and two particles are revealed. Subsequently, 504 particles settling in a closed cavity was simulated and the phenomenon that the viscoelastic stress stabilizing the Rayleigh–Taylor instabilities was observed. At last, simulations of a dense flow involving 11001 particles, the largest number of particles to date, were performed to investigate the instability behavior induced by elastic effect under hydrodynamic interactions in a viscoelastic fluid. The elasticity-induced ordering of the particle structures and fluid bubble structures in this dense flow is revealed for the first time. These simulations demonstrate the capability and prospects of the present method for aid in understanding the complex behaviors of viscoelastic particle suspensions.

A novel hierarchical bowl-like [email protected]2[email protected]⁰ nanohybrid catalyst ([email protected]2[email protected]⁰) was synthesized for removing sulfamethoxazole (SMX) through catalytic activation of peroxymonosulfate (PMS). It was found that this catalyst exhibited excellently high catalytic activity. Under optimized reaction conditions, all the added SMX (12 mg/L) could be completely degraded within 5 min. The SMX degradation followed pseudo first order kinetics with a rate constant k of 0.89 min⁻¹, being 1.38, 4.51, 8.99 and 35.6 times greater than that of other catalysts including Fe⁰ (0.644 min⁻¹ in the very initial stage), bowl-like iron-doped CuS (B-FeCuS, 0.197 min⁻¹), bowl-like CuS (B-CuS, 0.099 min⁻¹) and Cu2O (0.025 min⁻¹), respectively. During the degradation, several reactive oxygen species (·OH, SO4·⁻ and ¹O2) were generated with ·OH as the main one as confirmed by electron paramagnetic resonance analysis. The SMX degradation in the present system included both radical and non-radical mediated processes. A possible mechanistic insight of the PMS activation by bowl Fe⁰ decorated [email protected]2S-based catalyst was proposed according to X-ray photoelectron spectroscopic (XPS) analysis, and the degradation pathway of SMX was speculated by monitoring the degradation intermediates with liquid chromatography coupled with mass spectrometry (LC-MS).

Environmental exposure to crystalline silica particles can lead to silicosis, which is one of the most serious pulmonary interstitial fibrosis around the world. Unfortunately, the exact mechanism on silicosis is unclear, and the effective treatments are lacking to date. In this study, we aim to explore the molecular mechanism by which interleukin-11 (IL-11) affects silica particles-induced lung inflammation and fibrosis. We observed that IL-11 expressions in mouse lungs were significantly increased after silica exposure, and maintained at high levels across both inflammation and fibrosis phase. Immunofluorescent dual staining further revealed that the overexpression of IL-11 mainly located in mouse lung epithelial cells and fibroblasts. Using neutralizing anti-IL-11 antibody could effectively alleviate the overexpression of pro-inflammatory cytokines (i.e., interleukin-6 and tumor necrosis factor-α) and fibrotic proteins (i.e., collagen type I and matrix metalloproteinase-2) induced by silica particles. Most importantly, the expressions of IL-11 receptor subunit α (IL-11Rα), Glycoprotein 130 (GP130), and phosphorylated extracellular signal-regulated kinase (p-ERK) were significantly increased in response to silica, whereas blocking of IL-11 markedly reduced their levels. All findings suggested that the overexpression of IL-11 was involved in the pathological of silicosis, while neutralizing IL-11 antibody could effectively alleviate the silica-induced lung inflammation and fibrosis by inhibiting the IL-11Rα/GP130/ERK signaling pathway. IL-11 might be a promising therapeutic target for lung inflammation and fibrosis caused by silica particles exposure.

Cloud Manufacturing (CMfg) has gained significant attention owing to its capability in reshaping the cooperation paradigm among multiple geographically dispersed enterprises, which is conducive to handle a complex production task flexibly through the industrial internet platform. Cloud Service Assembly (CSA) is concerned with integrating a series of services together for serving a complex manufacturing task, which, as one of bottlenecks for CMfg, plays a critical role in efficient utilization of resources. Evolutionary Algorithms (EAs) have been widely used in resolving CSA in the past. However, they are always executed from scratch for tackling a single task in each run, whereas handling a batch of tasks collectively via leveraging inter-task knowledge transfer has been scarcely studied. Notably, CMfg is often faced with situation of multiple tasks arriving dynamically. In light of this, we propose a Multi-task Transfer EA (MTEA), where several service collaboration tasks are optimized jointly to speed up the search efficiency by exploiting knowledge extraction among tasks. Specifically, data models derived from evolving populations are learned to capture valuable knowledge for transfer so as to boost problem-solving efficacy, a parameter online learning strategy is utilized to tune the intensity of knowledge transfer across tasks. Extensive experiments are conducted on a series of CSA instances, results prove the feasibility and competence of MTEA against state-of-the-art peers.

Wire and arc additive manufacturing (WAAM) is an emerging manufacturing technology that is widely used in different manufacturing industries. To achieve fully automated production, WAAM requires a dependable, efficient, and automatic defect detection system. Although machine learning is dominant in the object detection domain, classic algorithms have defect detection difficulty in WAAM due to complex defect types and noisy detection environments. This paper presents a deep learning-based novel automatic defect detection solution, you only look once (YOLO)-attention, based on YOLOv4, which achieves both fast and accurate defect detection for WAAM. YOLO-attention makes improvements on three existing object detection models: the channel-wise attention mechanism, multiple spatial pyramid pooling, and exponential moving average. The evaluation on the WAAM defect dataset shows that our model obtains a 94.5 mean average precision (mAP) with at least 42 frames per second. This method has been applied to additive manufacturing of single-pass, multi-pass deposition and parts. It demonstrates its feasibility in practical industrial applications and has potential as a vision-based methodology that can be implemented in real-time defect detection systems.

Sharp abrasion of the abrasive belt always causes surface quality to deteriorate in the robotic grinding of thin-walled blades, which has stymied the further advancement of robot machining technology. A novel belt wear prediction approach based on the acoustic emissions (AE) signal is presented in this study to monitor belt wear conditions to achieve the expected machining result. A time-varying model of belt wear height and tangential force is initially established by employing the force analysis for various belt wear states. Next, a relationship between AE signal power and belt wear height is established utilizing the energy principle. Finally, robotic machining experiments on Ti-6Al-4V alloy workpieces are performed to achieve accurate belt wear prediction of an average error of approximately 10%, and the influence analysis of belt wear on the surface quality is further investigated to extend effective service life of abrasive belt by about 20% and realize the desired blade’s machining quality of surface roughness Ra<0.4 μm and contour accuracy ≤ ±0.17mm.

In the earlier paper, it is known that the solution accuracy usually can not be monotonically increased as the temporal discretization interval decreases when the standard finite element method (FEM) with the conventional temporal discretization approach is exploited for elastodynamics, hence the time integration step should be carefully determined for sufficiently fine solutions. The present work aims to investigate the behaviors of the classical element-free Galerkin method (EFGM), which is a typical meshless approach, with the Bathe temporal discretization scheme for elastodynamics. The main insights are that we explicitly show the total numerical dispersion errors in the computed numerical results actually consists of two different parts corresponding to the spatial and temporal discretization, respectively; both of them are responsible for solution accuracy. By performing the dispersion analysis, how the solution accuracy is affected by temporal and spatial discretization is shown, it is seen that we can improve the solution accuracy monotonically as the temporal step size decreases as long as the spatial dispersion error is sufficiently small and the related mathematical proofs are also given. From several supporting numerical examples, we can clearly see that the EFGM with the Bathe time integration scheme can basically provide monotonically convergent solutions as long as the reasonable node arrangement pattern and sufficiently large shape function supports are employed, namely the monotonic convergence property with respect to the temporal discretization interval can be achieved. This attractive and important feature makes the EFGM more competitive than the FE approach for elastodynamics.

Transition metal oxides, especially MnO2 nanoparticles, are often used as cathode of dry batteries and catalysts. They are also promising materials for ultrafast laser applications due to their strong absorption in visible light and near-infrared wavelength range. In this work, high-concentration MnO2 nanoparticles dispersions embedded in the hole cladding of dual-hole photonic crystal fiber is fabricated as a saturable absorber with a modulation depth of 4 % and a saturation intensity of 25 MW/cm². Strong MnO2-light interaction occurs due to enhanced evanescent-field strength (over 10 cm) of the SA could enable stable mode locking operation at 1.55 μm region. By inserting a Sagnac fiber filter in the cavity, multi-state solitons are experimentally demonstrated with identical layout, respectively, which greatly improves the versatility of this laser. This study proves that MnO2 nanoparticles possess excellent nonlinear optical properties in the near-infrared band. The simple in-line structure of the proposed nanoparticles-deposited device could pave a way for high power and all-fiber applications of photonics.