Parameters Optimization and Performance Evaluation of the Tuned Inerter Damper for the Seismic Protection of Adjacent Building Structures

In order to improve the seismic performance of adjacent buildings,two types of tuned inerter damper(TID)damping systems for adjacent buildings are proposed,which are composed of springs,inerter devices and dampers in serial or in parallel.The dynamic equations of TID adjacent building damping systems were derived,and the H2 norm criterion was used to optimize and adjust them,so that the system had the optimum damping performance under white noise random excitation.Taking TID frequency ratio and damping ratio as optimization parameters,the optimum analytical solutions of the displacement frequency response of the undamped structure under white noise excitation were obtained.The results showed that compared with the classic TMD,TID could obtain a better damping effect in the adjacent buildings.Comparing the TIDs composed of serial or parallel,it was found that the parallel TIDs had more significant advantages in controlling the peak displacement frequency response,while the H2 norm of the displacement frequency response of the damping system under the coupling of serial TID was smaller.Taking the adjacent building composed of two ten-story frame structures as an example,the displacement and energy collection time history analysis of the adjacent building coupled with the optimum design parameter TIDs were carried out.It was found that TID had a better damping effect in the full-time range compared with the classic TMD.This paper also studied the potential power of TID in adjacent buildings,which can be converted into available power resources during earthquakes.

Classification of Conversational Sentences Using an Ensemble Pre-Trained Language Model with the Fine-Tuned Parameter

Sentence classification is the process of categorizing a sentence based on the context of the sentence.Sentence categorization requires more semantic highlights than other tasks,such as dependence parsing,which requires more syntactic elements.Most existing strategies focus on the general semantics of a conversation without involving the context of the sentence,recognizing the progress and comparing impacts.An ensemble pre-trained language model was taken up here to classify the conversation sentences from the conversation corpus.The conversational sentences are classified into four categories:information,question,directive,and commission.These classification label sequences are for analyzing the conversation progress and predicting the pecking order of the conversation.Ensemble of Bidirectional Encoder for Representation of Transformer(BERT),Robustly Optimized BERT pretraining Approach(RoBERTa),Generative Pre-Trained Transformer(GPT),DistilBERT and Generalized Autoregressive Pretraining for Language Understanding(XLNet)models are trained on conversation corpus with hyperparameters.Hyperparameter tuning approach is carried out for better performance on sentence classification.This Ensemble of Pre-trained Language Models with a Hyperparameter Tuning(EPLM-HT)system is trained on an annotated conversation dataset.The proposed approach outperformed compared to the base BERT,GPT,DistilBERT and XLNet transformer models.The proposed ensemble model with the fine-tuned parameters achieved an F1_score of 0.88.

The VCOs in ISSCC 2023 set the new performance frontier of silicon-based oscillators

High-quality frequency generators are one of the fundamental building blocks in high-throughput wireless communication systems.Driven by the fast-growing demand for high data rate communications,the signal generator continues to be an active research topic.Efforts have been dedicated to improving the performance,including but not limited to phase noise,frequency tuning range,power consumption.

The effects of incident light wavelength difference on the collective stimulated Brillouin scattering in plasmas

The first laser–plasma interaction experiment using lasers of eight beams grouped into one octad has been conducted on the Shenguang Octopus facility.Although each beam intensity is below its individual threshold for stimulated Brillouin backscattering(SBS),collective behaviors are excited to enhance the octad SBS.In particular,when two-color/cone lasers with wavelength separation 0.3 nm are used,the backward SBS reflectivities show novel behavior in which beams of longer wavelength achieve higher SBS gain.This property of SBS can be attributed to the rotation of the wave vectors of common ion acoustic waves due to the competition of detunings between geometrical angle and wavelength separation.This mechanism is confirmed using massively parallel supercomputer simulations with the three-dimensional laser–plasma interaction code LAP3D.

Data-Driven Model Identification and Control of the Inertial Systems

In the synthesis of the control algorithm for complex systems, we are often faced with imprecise or unknown mathematical models of the dynamical systems, or even with problems in finding a mathematical model of the system in the open loop. To tackle these difficulties, an approach of data-driven model identification and control algorithm design based on the maximum stability degree criterion is proposed in this paper. The data-driven model identification procedure supposes the finding of the mathematical model of the system based on the undamped transient response of the closed-loop system. The system is approximated with the inertial model, where the coefficients are calculated based on the values of the critical transfer coefficient, oscillation amplitude and period of the underdamped response of the closed-loop system. The data driven control design supposes that the tuning parameters of the controller are calculated based on the parameters obtained from the previous step of system identification and there are presented the expressions for the calculation of the tuning parameters. The obtained results of data-driven model identification and algorithm for synthesis the controller were verified by computer simulation.

Real-Time Observation of Instantaneous ac Stark Shift of a Vacuum Using a Zeptosecond Laser Pulse

Based on the numerical solution of the time-dependent Dirac equation,we propose a method to observe in real time the ac Stark shift of a vacuum driven by an ultra-intense laser field.By overlapping the ultra-intense pump pulse with another zeptosecond probe pulse whose photon energy is smaller than 2mc^(2),electron–positron pair creation can be controlled by tuning the time delay between the pump and probe pulses.Since the pair creation rate depends sensitively on the instantaneous vacuum potential,one can reconstruct the ac Stark shift of the vacuum potential according to the time-delay-dependent pair creation rate.

Conceptual design of a 714-MHz RFQ for compact proton injectors and development of a new tuning algorithm on its aluminium prototype

Radio frequency quadrupoles(RFQs),which are crucial components of proton injectors,significantly affect the performance of proton accelerator facilities.An RFQ with a high frequency of 714 MHz dedicated to compact proton injectors for medi-cal applications is designed in this study.The RFQ is designed to accelerate proton beams from 50 keV to 4 MeV within a short length of 2 m and can be matched closely with the downstream drift tube linac to capture more particles through a preliminary optimization.To develop an advanced RFQ,challenging techniques,including fabrication and tuning method,must be evaluated and verified using a prototype.An aluminium prototype is derived from the conceptual design of the RFQ and then redesigned to confirm the radio frequency performance,fabrication procedure,and feasibility of the tuning algorithm.Eventually,a new tuning algorithm based on the response matrix and least-squares method is developed,which yields favorable results based on the prototype,i.e.,the errors of the dipole and quadrupole components reduced to a low level after several tuning iterations.Benefiting from the conceptual design and techniques obtained from the prototype,the formal mechanical design of the 2-m RFQ is ready for the next manufacturing step.

CoFeAl水滑石超薄纳米片的能带调控及其高效光催化分解水制氢性能

利用双滴法合成了厚度仅为1.86nm的超薄CoFeAl水滑石纳米片(CoFeAl-LDH),发现其具有优异的光催化产氢性能。利用X射线衍射仪、透射电子显微镜、原子力显微镜和紫外-可见吸收光谱等多种表征方法,研究了其晶体结构、形貌和能带结构。实验结果表明,CoFeAl-LDH在400~800nm的可见光区域内均具有较好的光吸收能力,而且通过调变Co∶Fe∶Al的摩尔比例,实现了CoFeAl-LDH的能带调控。系统考查了不同Co∶Fe∶Al摩尔比例对其光催化产氢性能的影响,发现Co_(6)Fe_(3)Al_(3)-LDH催化剂展现出最好的产氢活性,产氢速率达到576μmol/g·h,高产氢活性主要是由于其具备更强的还原氢质子能力,以及更优的光生载流子分离效率。

Vibration attenuation performance of wind turbine tower using a prestressed tuned mass damper under seismic excitation

With the rapid development of large megawatt wind turbines,the operation environment of wind turbine towers(WTTs)has become increasingly complex.In particular,seismic excitation can create a resonance response and cause excessive vibration of the WTT.To investigate the vibration attenuation performance of the WTT under seismic excitations,a novel passive vibration control device,called a prestressed tuned mass damper(PS-TMD),is presented in this study.First,a mathematical model is established based on structural dynamics under seismic excitation.Then,the mathematical analytical expression of the dynamic coefficient is deduced,and the parameter design method is obtained by system tuning optimization.Next,based on a theoretical analysis and parameter design,the numerical results showed that the PS-TMD was able to effectively mitigate the resonance under the harmonic basal acceleration.Finally,the time-history analysis method is used to verify the effectiveness of the traditional pendulum tuned mass damper(PTMD)and the novel PS-TMD device,and the results indicate that the vibration attenuation performance of the PS-TMD is better than the PTMD.In addition,the PS-TMD avoids the nonlinear effect due to the large oscillation angle,and has the potential to dissipate hysteretic energy under seismic excitation.

An Optimized Approach to Deep Learning for Botnet Detection and Classification for Cybersecurity in Internet of Things Environment

The recent development of the Internet of Things(IoTs)resulted in the growth of IoT-based DDoS attacks.The detection of Botnet in IoT systems implements advanced cybersecurity measures to detect and reduce malevolent botnets in interconnected devices.Anomaly detection models evaluate transmission patterns,network traffic,and device behaviour to detect deviations from usual activities.Machine learning(ML)techniques detect patterns signalling botnet activity,namely sudden traffic increase,unusual command and control patterns,or irregular device behaviour.In addition,intrusion detection systems(IDSs)and signature-based techniques are applied to recognize known malware signatures related to botnets.Various ML and deep learning(DL)techniques have been developed to detect botnet attacks in IoT systems.To overcome security issues in an IoT environment,this article designs a gorilla troops optimizer with DL-enabled botnet attack detection and classification(GTODL-BADC)technique.The GTODL-BADC technique follows feature selection(FS)with optimal DL-based classification for accomplishing security in an IoT environment.For data preprocessing,the min-max data normalization approach is primarily used.The GTODL-BADC technique uses the GTO algorithm to select features and elect optimal feature subsets.Moreover,the multi-head attention-based long short-term memory(MHA-LSTM)technique was applied for botnet detection.Finally,the tree seed algorithm(TSA)was used to select the optimum hyperparameter for the MHA-LSTM method.The experimental validation of the GTODL-BADC technique can be tested on a benchmark dataset.The simulation results highlighted that the GTODL-BADC technique demonstrates promising performance in the botnet detection process.

Stability and accuracy of central difference method for real-time dynamic substructure testing considering mass participation coefficient

For real-time dynamic substructure testing(RTDST),the influence of the inertia force of fluid specimens on the stability and accuracy of the integration algorithms has never been investigated.Therefore,this study proposes to investigate the stability and accuracy of the central difference method(CDM)for RTDST considering the specimen mass participation coefficient.First,the theory of the CDM for RTDST is presented.Next,the stability and accuracy of the CDM for RTDST considering the specimen mass participation coefficient are investigated.Finally,numerical simulations and experimental tests are conducted for verifying the effectiveness of the method.The study indicates that the stability of the algorithm is affected by the mass participation coefficient of the specimen,and the stability limit first increases and then decreases as the mass participation coefficient increases.In most cases,the mass participation coefficient will increase the stability limit of the algorithm,but in specific circumstances,the algorithm may lose its stability.The stability and accuracy of the CDM considering the mass participation coefficient are verified by numerical simulations and experimental tests on a three-story frame structure with a tuned liquid damper.

Morphological disruption and visual tuning alterations in the primary visual cortex in glaucoma(DBA/2J)mice

Glaucoma is a leading cause of irreve rsible blindness wo rldwide,and previous studies have shown that,in addition to affecting the eyes,it also causes abnormalities in the brain.However,it is not yet clear how the primary visual cortex(V1)is altered in glaucoma.This study used DBA/2J mice as a model for spontaneous secondary glaucoma.The aim of the study was to compare the electrophysiological and histomorphological chara cteristics of neurons in the V1between 9-month-old DBA/2J mice and age-matched C57BL/6J mice.We conducted single-unit recordings in the V1 of light-anesthetized mice to measure the visually induced responses,including single-unit spiking and gamma band oscillations.The morphology of layerⅡ/Ⅲneurons was determined by neuronal nuclear antigen staining and Nissl staining of brain tissue sections.Eighty-seven neurons from eight DBA/2J mice and eighty-one neurons from eight C57BL/6J mice were examined.Compared with the C57BL/6J group,V1 neurons in the DBA/2J group exhibited weaker visual tuning and impaired spatial summation.Moreove r,fewer neuro ns were observed in the V1 of DBA/2J mice compared with C57BL/6J mice.These findings suggest that DBA/2J mice have fewer neurons in the VI compared with C57BL/6J mice,and that these neurons have impaired visual tuning.Our findings provide a better understanding of the pathological changes that occur in V1 neuron function and morphology in the DBA/2J mouse model.This study might offer some innovative perspectives regarding the treatment of glaucoma.

The Optimal Design of TMD for Offshore Structures

This paper presents the optimal design procedure of Tuned Mass Damper (TMD) for reducing vibration of an actual steel jacket offshore platform excited by random wave loading. In this study, a frequency domain is taken. The force on the structure is determined by use of the linearized Morison equation for an input Power Spectral Density (PSD) of wave elevation. The sensitivity of optimum values of TMD to characteristic parameters of random wave spectrum is analyzed. An optimized TMD design for the modeled platform is given based on design conditions and the findings of the study.

Optimization of the Tuned Mass Damper for Chatter Suppression in Turning

The tuned mass damper（TMD） has been successfully applied to the vibration control in machining, while the most widely adopted tuning is equal peaks, which splits the magnitude of the frequency response function（FRF） into equal peaks. However, chatter is a special self-excited problem and a chatter-flee machining is determined by FRF at the cutting zone. A TMD tuning aiming at achieving the maximum chatter stability is studied, and it is formulated as an optimization problem of maximizing the minimum negative real part of FRF. By employing the steepest descend method, the optimum frequency and damping ratio of TMD are obtained, and they are compared against the equal peaks tuning. The advantage of the proposed tuning is demonstrated numerically by comparing the minimum point of the negative real part, and is further verified by damping a flexible mode from the fixture of a turning machine. A TMD is designed and placed on the fixture along the vibration of the target mode after performing modal analysis and mode shape visualization. Both of the above two ttmings are applied to modify the tool point FRF by tuning TMD respectively. Chatter stability chart of the turning shows that the proposed tuning can increase the critical depth of cut 37% more than the equal peaks. Cutting tests with an increasing depth of cut are conducted on the turning machine in order to distinguish the stability limit. The tool vibrations during the machining are compared to validate the simulation results. The proposed damping design and optimization routine are able to further increase the chatter suppression effect.

Contribution of tuned liquid column gas dampers to the performance of offshore wind turbines under wind, wave, and seismic excitations

The main intention of the present study is to reduce wind, wave, and seismic induced vibrations of jacket- type offshore wind turbines （JOWTs） through a newly developed vibration absorber, called tuned liquid column gas damper （TLCGD）. Using a Simulink-based model, an analytical model is developed to simulate global behavior of JOWTs under different dynamic excitations. The study is followed by a parametric study to explore efficiency of the TLCGD in terms of nacelle acceleration reduction under wind, wave, and earthquake loads. Study results indicate that optimum frequency of the TLCGD is rather insensitive to excitation type. In addition, while the gain in vibration control from TLCGDs with higher mass ratios is generally more pronounced, heavy TLCGDs are more sensitive to their tuned frequency such that ill-regulated TLCGD with high mass ratio can lead to destructive results. It is revealed that a well regulated TLCGD has noticeable contribution to the dynamic response of the JOWT under any excitation.

On the Misunderstanding of the Ziegler-Nichols's Formulae Usage

In the Ziegler-Nichols' s method of reaction curve,the proportional gain should be calculated as an inverse relation of the plant steady-state gain. One of the reasons behind this is to avoid an excessively high loop gain, which can jeopardize many required characteristics of the closed loop. However, many reports, scientific papers and books have been neglecting such gain compensation in the tuning formulae.This brief presents a comprehensive discussion about such uncompensated tuning rules. The main paper finding is that either the stability margin or the disturbance rejection is reduced in this case. A theoretical analysis is performed to obtain the main result. Moreover, a consistent simulation study is also performed to show the impact of the lack of compensation on performance.

Torsional Response of the Offshore Platform with TMD

It is pointed out in this paper that the offshore platform could be controlled by means of the Tuned Mass Damper (TMD) if there is torsional vibration in the system. The effectiveness of the location of TMD is quantified with the help of the response ratio between the peak responses of the system in the presence and in the absence of TMD. In addition, the parameters of frequency and damping ratio of TMD are optimized.

Optimal design theories of tuned mass dampers with nonlinear viscous damping

Optimal design theory for linear tuned mass dampers （TMD） has been thoroughly investigated, but is still under development for nonlinear TMDs. In this paper, optimization procedures in the time domain are proposed for design of a TMD with nonlinear viscous damping. A dynamic analysis of a structure implemented with a nonlinear TMD is conducted first. Optimum design parameters for the nonlinear TMD are searched using an optimization method to minimize the performance index. The feasibility of the proposed optimization method is illustrated numerically by using the Taipei 101 structure implemented with TMD. The sensitivity analysis shows that the performance index is less sensitive to the damping coefficient than to the frequency ratio. Time history analysis is conducted using the Taipei 101 structure implemented with different TMDs under wind excitation. For both linear and nonlinear TMDs, the comfort requirements for building occupants are satisfied as long as the TMD is properly designed. It was found that as the damping exponent increases, the relative displacement of the TMD decreases but the damping force increases.

Dynamic Performance Analysis of the Tuned Heave Plate System for Semi-Submersible Platform

Logistical supply is costly for the deepwater oil and gas exploitation, thereby it is necessary to develop a novel power supply solution to improve the offshore structure’s self-holding capacity. The two-body point absorbers, as a renewable energy device, have achieved a rapid development. Heave plate is used to constrain the truss’ s motion in the two-body point absorber, and the floater moves along the truss up and down. This two-body point absorber can be considered to be an essentially mass-spring-damper system. And it is well known that the heave plates have been widely used in the Spar platform to suppress the heave motions. So if the two-body point absorber can be modified to combine with offshore floating structures, this system can not only offer electric power to support operations or daily lives for the platform, but also control the large motions in the vertical plane. Following this concept, a novel tuned heave plate(THP) system is proposed for the conventional semi-submersible platform. In order to investigate the dynamic performances of the single THP, two experiments are conducted in this paper. First, the hydrodynamic coefficients of the heave plates are studied, and then the THP experiments are carried out to analyze its dynamic performance. It can be concluded that this THP is feasible and achieves the design objective.

Tuning PID Parameters Based on a Combination of the Expert System and the Improved Genetic Algorithms

a new strategy combining an expert system and improved genetic algorithms is presented for tuning proportional-integral-derivative （PID） parameters for petrochemical processes. This retains the advantages of genetic algorithms, namely rapid convergence and attainment of the global optimum. Utilization of an orthogonal experiment method solves the determination of the genetic factors. Combination with an expert system can make best use of the actual experience of the plant operators. Simulation results of typical process systems examples show a good control performance and robustness.