Mass Inertia Effect Based Vibration Control Systems for Civil Engineering Structure and Infrastructure

This chapter introduces some recent research works carried out in the Blast Resistance and Protective Engineering laboratory of Harbin Institute of Technology (HIT-BRPE) during the past few years. The EMD control system is shown to be effective and feasible for vibration control of civil engineering structures subjected to, such as earthquake, excitations. The DDVC based AMD control system is suitable for low frequency vibration and motion control. The innovative passive TRID system is applicable for rotation and swing motion control, whereas linear TMD system is shown to be invalid for structural swinging motion. All of the control systems mentioned in this chapter, whatever active or passive or hybrid, have a common characteristic, which is to utilize the mass inertia effect either to provide counter force support for functioning of actuator, e.g. AMD subsystem, or to provide gyrus or rotary inertia for anti-swinging motion of suspended structure. Traditionally, these systems have been called Active Mass Damper/Driver (AMD) or Tuned Mass Damper (TMD), herein we want to emphasize the mass inertia effect and its functions. The basic is to be a necessary component of a control system, and more important is its way of working in the subsystem

Computer-Aided Analysis of Flow in Water Pipe Networks after a Seismic Event

This paper proposes a framework for a reliability-based flow analysis for a water pipe network after an earthquake. For the first part of the framework, we propose to use a modeling procedure for multiple leaks and breaks in the water pipe segments of a network that has been damaged by an earthquake. For the second part, we propose an efficient system-level probabilistic flow analysis process that integrates the matrix-based system reliability (MSR) formulation and the branch-and-bound method. This process probabilistically predicts flow quantities by considering system-level damage scenarios consisting of combinations of leaks and breaks in network pipes and significantly reduces the computational cost by sequentially prioritizing the system states according to their likelihoods and by using the branch-and-bound method to select their partial sets. The proposed framework is illustrated and demonstrated by examining two example water pipe networks that have been subjected to a seismic event. These two examples consist of 11 and 20 pipe segments, respectively, and are computationally modeled considering their available topological, material, and mechanical properties. Considering different earthquake scenarios and the resulting multiple leaks and breaks in the water pipe segments, the water flows in the segments are estimated in a computationally efficient manner.ope

Expressions of Cyr61 and WISP-3 in Non-small Cell Lung Cancer and Its Clinical Significance

Background and objective Cysteine-rich protein 61 (Cyr61) plays a role as a tumor suppressor in non-small cell lung cancer (NSCLC). Cyr61 and WISP-3 have a very significant sequence homology, belonging to the same CCN gene family. The aim of this study is to investigate the expressions of Cyr61 and WISP-3 in NSCLC, and explore the relationship between their expressions and tumor's clinicopathological characteristics. Methods The expressions of Cyr61 and WISP-3 were detected in 54 cases with primary NSCLC and their corresponding normal lung tissues in control group by immunohistochemical staining (SP), and the clinical data were analyzed. Results Down-regulation of Cyr61 and up-regulation of WISP-3 were both found in lung cancer tissue compared with the corresponding normal lung tissue (both P < 0.001); The expression of Cyr61 was negatively correlated with the expression of WISP-3 (r=-0.395, P=0.003); Cyr61 expression levels was closely correlated with tumor grade, tumor type, clinical stage, family history, smoking and metastasis (P < 0.05). Also, WISP-3 was closely correlated with tumor grade, clinical stage and age (P < 0.05). Conclusion The expressions of Cyr61 and/or WISP-3 may be important biological markers in reflecting the progression, biological behaviors, metastatic potential and prognosis of NSCLC

A Distributed Computation Model Based on Federated Learning Integrates Heterogeneous models and Consortium Blockchain for Solving Time-Varying Problems

The recurrent neural network has been greatly developed for effectively solving time-varying problems corresponding to complex environments. However, limited by the way of centralized processing, the model performance is greatly affected by factors like the silos problems of the models and data in reality. Therefore, the emergence of distributed artificial intelligence such as federated learning (FL) makes it possible for the dynamic aggregation among models. However, the integration process of FL is still server-dependent, which may cause a great risk to the overall model. Also, it only allows collaboration between homogeneous models, and does not have a good solution for the interaction between heterogeneous models. Therefore, we propose a Distributed Computation Model (DCM) based on the consortium blockchain network to improve the credibility of the overall model and effective coordination among heterogeneous models. In addition, a Distributed Hierarchical Integration (DHI) algorithm is also designed for the global solution process. Within a group, permissioned nodes collect the local models' results from different permissionless nodes and then sends the aggregated results back to all the permissionless nodes to regularize the processing of the local models. After the iteration is completed, the secondary integration of the local results will be performed between permission nodes to obtain the global results. In the experiments, we verify the efficiency of DCM, where the results show that the proposed model outperforms many state-of-the-art models based on a federated learning framework

Experimental investigation on semi-active control of base isolation system using magnetorheological dampers for concrete frame structure

The traditional passive base isolation is the most widely used method in the engineering practice for structural control, however, it has the shortcoming that the optimal control frequency band is significantly limited and narrow. For the seismic isolation system designed specifically for large earthquakes, the structural acceleration response may be enlarged under small earthquakes. If the design requirements under small earthquakes are satisfied, the deformation in the isolation layer may become too large to be accepted. Occasionally, it may be destroyed under large earthquakes. In the isolation control system combined with rubber bearing and magnetorheological (MR) damper, the MR damper can provide instantaneous variable damping force to effectively control the structural response at different input magnitudes. In this paper, the control effect of semi-active control and quasi-passive control for the isolation control system is verified by the shaking table test. In regard to semi-active control, the linear quadratic regulator (LQR) classical linear optimal control algorithm by continuous control and switch control strategies are used to control the structural vibration response. Numerical simulation analysis and shaking table test results indicate that isolation control system can effectively overcome the shortcoming due to narrow optimum control band of the passive isolation system, and thus to provide optimal control for different seismic excitations in a wider frequency range. It shows that, even under super large earthquakes, the structure still exhibits the ability to maintain overall stability performance

Image Super-resolution with An Enhanced Group Convolutional Neural Network

CNNs with strong learning abilities are widely chosen to resolve super-resolution problem. However, CNNs depend on deeper network architectures to improve performance of image super-resolution, which may increase computational cost in general. In this paper, we present an enhanced super-resolution group CNN (ESRGCNN) with a shallow architecture by fully fusing deep and wide channel features to extract more accurate low-frequency information in terms of correlations of different channels in single image super-resolution (SISR). Also, a signal enhancement operation in the ESRGCNN is useful to inherit more long-distance contextual information for resolving long-term dependency. An adaptive up-sampling operation is gathered into a CNN to obtain an image super-resolution model with low-resolution images of different sizes. Extensive experiments report that our ESRGCNN surpasses the state-of-the-arts in terms of SISR performance, complexity, execution speed, image quality evaluation and visual effect in SISR. Code is found at https://github.com/hellloxiaotian/ESRGCNN

Characterization of a Ag+-Selective Electrode Based on Naphthalimide Derivative as Ionophore

A naphthalimide derivative has been explored as neutral ionophore for Ag+-selective electrode. Potentiometric response revealed that electrode based on the proposed ionophore with 2-nitrophenyl octyl ether as solvent in a poly (vinyl chloride) membrane matrix shows a measuring range of 1.0×10-6-1.0×10-2 M with a slope of 50.4±0.3 mV/decade. This electrode has high selectivity to Ag+ with respect to alkaline, alkaline earth and other heavy metal ions

Research on reconfigurable control for a hovering PVTOL aircraft

This paper presents a novel reconfigurable control method for the planar vertical take-off and landing (PVTOL) aircraft when actuator faults occur. According to the position subsystem within the multivariable coupling, and the series between subsystems of position and attitude, an active disturbance rejection controller (ADRC) is used to counteract the adverse effects when actuator faults occur. The controller is cascade and ensures the input value of the controlled system can be tracked accurately. The coordinate transformation method is used for model decoupling due to the severe coupling. In addition, the Taylor differentiator is designed to improve the control precision based on the detailed research for tracking differentiator. The stability and safety of the aircraft is much improved in the event of actuator faults. Finally, the simulation results are given to show the effectiveness and performance of the developed method