Nonlinear Modeling and Identification of Structural Joint by Response Control Vibration Test

Components of mechanical product are assembled by structural joints,such as bolting,riveting,welding,etc.Structural joints introduce nonlinearity to some engineering structures,and the nonlinearity need to be modeled precisely.To meet serious quality requirements,it is necessary to detect and identify nonlinearity of mechanical products for structural optimization.Modal test to acquire a dynamic response has been applied for decades,which provides reliable results for finite element(FE)model updating.Here response control vibration test for identification of nonlinearity is presented.A nonlinear system can be regarded as linearity for particular steady state response,and classical linear analysis tool is applicable to extract modal data for particular response.First,its applicability is illustrated by some numerical simulations.Subsequently,it is implemented on experimental setup with structural joints by shaking table.The stiffness and damping function dependent of relative displacement are fitted to describe its inherent nonlinearity.The spring and damping forces are identified by harmonic balance method(HBM)to predict output response.Based on the identified results,the procedure is recommended that it allows a reliable measurement of nonlinearity with a certain accuracy.

Substructure design optimization and nonlinear responses control analysis of the mega-sub controlled structural system (MSCSS) under earthquake action

The newly proposed mega sub-controlled structure system(MSCSS)and related studies have drawn the attention of civil engineers for practice in improving the performance and enhancing the structural effectiveness of mega frame structures.However,there is still a need for improvement to its basic structural arrangement.In this project,an advanced,reasonable arrangement of mega sub-controlled structure models,composed of three mega stories with different numbers and arrangements of substructures,are designed to investigate the control performance of the models and obtain the optimal model configuration(model with minimum acceleration and displacement responses)under strong earthquake excitation.In addition,the dynamic parameters that affect the performance effectiveness of the optimal model of MSCSS are studied and discussed.The area of the relative stiffness ratio RD,with different mass ratio MR,within which the acceleration and displacement of the optimal model of MSCSS reaches its optimum(minimum)value is considered as an optimum region.It serves as a useful tool in practical engineering design.The study demonstrates that the proposed MSCSS configuration can efficiently control the displacement and acceleration of high rise buildings.In addition,some analytical guidelines are provided for selecting the control parameters of the structure.

SUPPRESSION OF TRANSIENT RESPONSE OF A ROTOR IN ACTIVE VIBRATlON CONTROL

Transient response and its influence factors are investigated and a methodfor attenuating the transient response is developed by means of a time varying model.The system gain matrix is obtained by choosing weighting matrices and solving the timevarying Riccati equation. Control forces are applied to the system via a feed back loop.Comparisons of responses with and without control are made. The results show that thetransienl and steady state responses are significantly suppressed in the close loop systemand control forces are very small.

Proactive traffic responsive control based on state-space neural network and extended Kalman filter

The state-space neural network and extended Kalman filter model is used to directly predict the optimal timing plan that corresponds to futuristic traffic conditions in real time with the purposes of avoiding the lagging of the signal timing plans to traffic conditions. Utilizing the traffic conditions in current and former intervals, the network topology of the state-space neural network （SSNN）, which is derived from the geometry of urban arterial routes, is used to predict the optimal timing plan corresponding to the traffic conditions in the next time interval. In order to improve the effectiveness of the SSNN, the extended Kalman filter （EKF） is proposed to train the SSNN instead of conventional approaches. Raw traffic data of the Guangzhou Road, Nanjing and the optimal signal timing plan generated by a multi-objective optimization genetic algorithm are applied to test the performance of the proposed model. The results indicate that compared with the SSNN and the BP neural network, the proposed model can closely match the optimal timing plans in futuristic states with higher efficiency.

Agent-Based Simulation for Interconnection-Scale Renewable Integration and Demand Response Studies

This paper collects and synthesizes the technical requirements, implementation, and validation methods for quasi-steady agent-based simulations of interconnectionscale models with particular attention to the integration of renewable generation and controllable loads. Approaches for modeling aggregated controllable loads are presented and placed in the same control and economic modeling framework as generation resources for interconnection planning studies. Model performance is examined with system parameters that are typical for an interconnection approximately the size of the Western Electricity Coordinating Council(WECC) and a control area about 1/100 the size of the system. These results are used to demonstrate and validate the methods presented.

Trajectory of COVID-19 response and management strategy in China:scientific rationale driven strategy adjustments

The pneumonia caused by novel coronavirus SARS-CoV-2 infection in early December 2019,which was later named coronavirus disease 2019(COVID-19)by the World Health Organization(WHO),rapidly spread across the world.China has made extraordinary efforts to this unprecedented pandemic,put its response and control at a very high level of infectious disease management(Category B but with measures for Category A),given top priority to the people and their lives,and balanced the pandemic control and socio-economic development.After more than three years’fighting against this disease,China downgraded the management of COVID-19 to Category B infectious disease on January 8,2023 and the WHO declared the end of public health emergency on May 5,2023.However,the ending of pandemic does not mean that the disease is no longer a health threat.Experiences against COVID-19 from China and the whole world should be learned to prepare well for the future public health emergencies.This article gives a systematic review of the trajectory of COVID-19 development in China,summarizes the critical policy arrangements and provides evidence for the adjustment during policy making process,so as to share experiences with international community and contribute to the global health for all humanity.

Study on seismic response control of a single-tower self-anchored suspension bridge with elastic-plastic steel damper

Elastic-plastic steel damper(EPSD) is a new device controlling seismic responses.The mechanical principle of EPSD was presented and a comparison was conducted between the theoretical formulas and finite element(FE) simulation of damper units.The verified force-displacement hysteretic curve of the damper system was obtained with reference to tests.The Nanjing Jiangxinzhou Bridge(NJB) was subsequently taken as the case to investigate the seismic response control effect of EPSDs on single-tower self-anchored suspension bridges.A 3-dimensional FE model of the bridge was established in ANSYS and the dynamic and static analyses of the bridge were conducted,the control effect of EPSDs under different seismic waves was further investigated through nonlinear time-history analysis based on the validated model.Results showed that both the simplified theoretical and FE simulation methods can preferable reflect the mechanical performance of EPSD,and that seismic responses of NJB with EPSDs are better than those with elastic connection device or fluid viscous damper.However,the control effect of EPSDs is influenced by seismic wave characteristics.

Machine learning-based fast frequency response control for a VSC-HVDC system

HVDC system can realize a very fast frequency response to the disturbed system under a contingency because its active power control is decoupled from the frequency deviation.However,most of existing HVDC frequency control strategies are coupled with system primary frequency control and secondary frequency control.Since the traditional system frequency control is dominated by the thermal generators,the advantage of the fast response of the HVDC system is not made fully used.The development of a frequency response estimation based on a machine learning algorithm provides another approach to improve the frequency response capability of the HVDC system.Different from other frequency deviation tracking strategies,a machine learning based HVDC frequency response control can directly increase the power flow of a HVDC system by estimation of the system generator or load lost.In this paper,a fast frequency response control using a HVDC system for a large power system disturbance based on the multivariate random forest regression(MRFR)algorithm is proposed.The simulation is carried out with an integrated power system model based on the North American interconnections.The simulation results indicate that the proposed MRFR based frequency response control can significantly improve the frequency low point during an event,while stabilizing the frequency in advance.

Simple PID Parameter Tuning Method Based on Outputs of the Closed Loop System

Most of the existing PID parameters tuning methods are only effective with pre-known accurate system models, which often require some strict identification experiments and thus infeasible for many complicated systems. Actually, in most practical engineering applications, it is desirable for the PID tuning scheme to be directly based on the input-output response of the closed-loop system. Thus, a new parameter tuning scheme for PID controllers without explicit mathematical model is developed in this paper. The paper begins with a new frequency domain properties analysis of the PID controller. After that, the definition of characteristic frequency for the PID controller is given in order to study the mathematical relationship between the PID parameters and the open-loop frequency properties of the controlled system. Then, the concepts of M-field and θ-field are introduced, which are then used to explain how the PID control parameters influence the closed-loop frequency-magnitude property and its time responses. Subsequently, the new PID parameter tuning scheme, i.e., a group of tuning rules, is proposed based on the preceding analysis. Finally, both simulations and experiments are conducted, and the results verify the feasibility and validity of the proposed methods. This research proposes a PID parameter tuning method based on outputs of the closed loop system.

Cross-Regional Collective Response Mechanism for Major Epidemic Control and Treatment

It is essential for cross-regional control and treatment of major epidemics to establish a collaborative,efficient,and precise collective response mechanism.Based on the observation of the COVID-19 epidemic,this paper concludes major measures and experience of cross-regional collective response for epidemic control and treatment,compares the difference between localities at home and abroad,and puts forwards major strategies for a cross-regional collective response,hoping to provide policy-making references to improve the modernization level of public health,epidemic prevention,and emergency management in China.

Response surface modeling-based source contribution analysis and VOC emission control policy assessment in a typical ozone-polluted urban Shunde,China

To develop a sound ozone（O_3） pollution control strategy,it is important to well understand and characterize the source contribution due to the complex chemical and physical formation processes of O_3.Using the ＂Shunde＂ city as a pilot summer case study,we apply an innovative response surface modeling（RSM） methodology based on the Community Multi-Scale Air Quality（CMAQ） modeling simulations to identify the O_3 regime and provide dynamic analysis of the precursor contributions to effectively assess the O_3 impacts of volatile organic compound（VOC） control strategy.Our results show that Shunde is a typical VOC-limited urban O_3 polluted city.The ＂Jiangmen＂ city,as the main upper wind area during July 2014,its VOCs and nitrogen oxides（NO_x） emissions make up the largest contribution（9.06%）.On the contrary,the contribution from local（Shunde） emission is lowest（6.35%） among the seven neighbor regions.The local VOCs industrial source emission has the largest contribution comparing to other precursor emission sectors in Shunde.The results of dynamic source contribution analysis further show that the local NO_x control could slightly increase the ground O_3 under low（10.00%） and medium（40.00%）reduction ratios,while it could start to turn positive to decrease ground O_3 under the high NO_x abatement ratio（75.00%）.The real-time assessment of O_3 impacts from VOCs control strategies in Pearl River Delta（PRD） shows that the joint regional VOCs emission control policy will effectively reduce the ground O_3 concentration in Shunde.

Optimal placement of dampers and actuators based on stochastic approach

A general method is developed for optimal application of dampers and actuators by installing them at optimal location on seismic-resistant structures.The study includes development of a statistical criterion,formulation of a general optimization problem and establishment of a solution procedure.Numerical analysis of the seismic response in time-history of controlled structures is used to verify the proposed method for optimal device application and to demonstrate the effectiveness of seismic response control with optimal device location.This study shows that the proposed method for the optimal device application is simple and general,and that the optimally applied dampers and actuators are very efficient for seismic response reduction.

The Effect of Gum Acacia on Post-Prandial Glucose and Insulin Levels in Healthy Subjects

This double-blind, controlled, randomized, three-way cross-over study evaluates the effect of 40 g (D1 group) and 20 g (D2 group) of acacia gum (AG) versus no treatment (NT group) on post-prandial glucose (PPG) levels in normal-weight and overweight subjects. Additionally, post-prandial insulin (PPI) levels as well as the safety and tolerability of gum acacia were assessed. 35 healthy subjects aged 25 - 60 years, body mass index 18.5 kg/m2 - 29.9 kg/m2, received one treatment of 20 g, 40 g, or 0 g of AG each. Glucose and insulin values were determined at -15 min and prior to the intake (time “0”) as well as 15, 30, 45, 60, 90 120, and 180 min after the “0 min” blood draw. The mean PPG levels were lower (34% in D1 group, p = 0.003;35% in D2 group, p = 0.005) than in the NT group. PPI concentration was statistically significantly lower at all time points except baseline in both treatment groups compared to NT groups. Global benefit and tolerability were rated as “very good” or “good” by 100% of subjects in the treatment groups. This study provides robust evidence of the significant benefits of AG consumption on PPG and PPI levels in healthy subjects. Moreover, very good tolerability was demonstrated.

Development and case study of a science-based software platform to support policy making on air quality

This article describes the development and implementations of a novel software platform that supports real-time, science-based policy making on air quality through a user-friendly interface. The software, RSM-VAT, uses a response surface modeling（RSM） methodology and serves as a visualization and analysis tool（VAT） for three-dimensional air quality data obtained by atmospheric models. The software features a number of powerful and intuitive data visualization functions for illustrating the complex nonlinear relationship between emission reductions and air quality benefits. The case study of contiguous U.S.demonstrates that the enhanced RSM-VAT is capable of reproducing the air quality model results with Normalized Mean Bias 〈 2% and assisting in air quality policy making in near real time.

Cross-seam Hybrid MTDC System for Integration and Delivery of Large-scale Renewable Energy

To better utilize the diversity of renewable energies in the U. S., this paper proposes a cross-seam hybrid multi-terminal high-voltage direct current(MTDC) system for the integration of different types of renewable energies in the U. S.Based on a developed station-hybrid converter design, the proposed hybrid MTDC system further investigates the connection methods of renewable energies and develops novel flexible power flow control strategies for realizing uninterrupted integration of renewable energies. In addition, the frequency response control of the hybrid MTDC system is proposed by utilizing the coordination between the converters in the hybrid MTDC system.The feasibility of the hybrid MTDC system and the performance of its corresponding control strategies are conducted in the PSCAD/EMTDC simulation. The simulation results indicate that the proposed hybrid MTDC system could realize the uninterrupted integration of renewable energies and flexible power transmission to both coasts of U.S.