Numerical investigation of sound transmission loss of circular plates embedded with acoustic black hole

The acoustic black hole (ABH) can be utilized to achieve aggregation of flexural wave in structures with the feature that the thickness gradually reduced to zero with a power exponent no less than 2. These characteristics could be applied in vibration reduction, noise attenuation or improving sound insulation. To investigate the sound transmission loss of circular plates embedded with acoustic black hole, series of vibro-acoustic coupling finite element models (FEM) for TL analysis of ABH circular plates were established by automatic matched layer (AML) method in this paper and the simulation results show that the circular plate with a single ABH embedded in the center position can significantly improve the sound transmission loss in stiffness-controlled region, and at the first-order resonance frequency

A sensitivity analysis of the importance of the dynamic parameters on the paver’s performance

In order to research the impact of the vibration on working stability of the vibration compaction system (VCS) and increase the paver’s performance, the acceleration responses at the screed surface under the excitation frequencies of the tampers and vibration screed are analyzed via the root mean square acceleration responses (RMSAR) at the bottom of the screed surface. A non-linear dynamic model of the VCS is then established to research the impact of the VCS’s dynamic parameters on the performance of paver via the objective functions of the vertical, pitch and roll RMSAR of the vibration screed. The dynamic parameters are then optimized based on a multi-objective genetic algorithm to enhance the paver’s performance. The experiment and simulation results show that the dynamic parameters greatly affect the paver’s performance. The compression performance is quickly increased, while the working stability and paving quality are reduced with increasing the angular deviations of tampers and excitation frequencies of both the tampers and vibration screed and vice versa. Also, the paver’s performance is significantly improved by using the optimal parameters of the VCS

Dynamic response analysis in bolted joint structure with viscoelastic layer and experimental investigations

In this paper, the dynamic response characteristics of a common double shear lap joint structure with viscoelastic layer are investigated. Firstly, an analytical model is established in shear vibration based on phenomenological model. The fourth order Runge-Kutta method is employed to calculate the harmonic response, where the effect of Coulomb friction and excitation levels on system are presented. Secondly, a new nonlinear finite element model for the bolted joint structure with viscoelastic layer is developed. The simulation results show good agreement with the corresponding experimental results. Finally, the proposed harmonic excitation experiments with laser vibrometer in tangential direction are carried out to investigate the nonlinear behaviors of system, as well as the influence of bolt preload and viscoelastic material on dynamic characteristics of the bolted joint beam. The results show that the viscoelastic layer help reduce vibration at certain extent, especially in the high frequency region of vibration, and some peak frequencies of system can be changed through the viscoelastic layer

Vibro-acoustic modeling of a rectangular enclosure with a flexible panel in broad range of frequencies and experimental investigations

In this paper, unlike the existing studies, vibro-acoustic modeling and analysis of a rectangular acoustic cavity bounded by a flexible panel is conducted by three modeling techniques in a broad frequency range (up to 6.4 kHz). The finite element method (FEM) and statistical energy analysis (SEA) are employed at the low and high frequency range respectively. For the mid-frequency range, a hybrid FE-SEA method is employed to deal with the drawbacks in application of single deterministic or statistical methods. In this case, studies of the interior sound pressure and panel vibration responses for the structure-acoustic coupled system are made under external normal concentrated force acting at the flexible plate. And then comparisons are used to validate the three models and verify their accuracy through experimental investigations. Deviations between the numerical and test results are also discussed

Traffic-Aware Ecological Cruising Control for Connected Electric Vehicle

The advent of intelligent connected technology has greatly enriched the capabilities of vehicles in acquiring information. The integration of short-term information from limited sensing range and long-term information from cloud-based systems in vehicle motion planning and control has become a vital means to deeply explore the energy-saving potential of vehicles. In this study, a traffic-aware ecological cruising control (T-ECC) strategy based on a hierarchical framework for connected electric vehicles in uncertain traffic environments is proposed, leveraging the two distinct temporal-dimension information. In the upper layer that is dedicated for speed planning, a sustainable energy consumption strategy (SECS) is introduced for the first time. It finds the optimal economic speed by converting variations in kinetic energy into equivalent battery energy consumption based on long-term road information. In the lower layer, a synthetic rolling-horizon optimization control (SROC) is developed to handle real-time traffic uncertainties. This control approach jointly optimizes energy efficiency, battery life, driving safety, and comfort for vehicles under dynamically changing traffic conditions. Notably, a stochastic preceding vehicle model is presented to effectively capture the uncertainties in traffic during the driving process. Finally, the proposed T-ECC is validated through simulations in both virtual and real-world driving conditions. Results demonstrate that the proposed strategy significantly improves the energy efficiency of the vehicle

Experimental research and optimal control of vibration screed system (VSS) based on fuzzy control

To enhance the compression performance and improve the paving quality of the VSS of the pavers, the experimental research of the VSS is performed to assess the VSS’s vibration stability under various excitations of the tampers and vibrator screed. A VSS’s dynamic model is also established to simulate and evaluate the VSS’s working performance. The root-mean-square (RMS) acceleration responses of the vertical and pitching motions at centre of gravity of the screed floor are chosen as the objective functions. In order to increase the VSS’s working performance, the dynamic parameters of the angular deviations of tampers are then controlled based on Fuzzy control. The research results indicate that the RMS value of the vertical screed motion is remarkably increased, concurrently the RMS value of the pitching screed angle is significantly reduced by controlling the angular deviations of tampers under different excitation frequencies of the VSS. Therefore, the VSS’s working performance is significantly improved in comparison without the control of the angular deviations

A multivariate statistical method for risk parameter scenario generation and renewable energy bidding in electricity markets

To maximize the expected profits and manage the risks of renewable energy system under electricity market environment, scenario-based- stochastic optimization model can be established to generate energy bidding strategies, in which the probabilistic scenarios of risk parameters are usually obtained by using statistical or machine learning methods. This paper proposes a practical multivariate statistical method for risk parameter scenario generation, which is used by a wind energy system faced with uncertain electricity prices and wind power productions, and it considers the correlation between dependent risk parameters by using historical data directly. The probabilities of scenarios containing correlated risk parameters are calculated by using multivariate histograms, in which the asymmetric correlation between different parameters existing in the historical data are preserved. Additionally, in order to make the stochastic optimization problem with large numbers of scenarios tractable, a multivariate scenario reduction method is used to trim down the scenario number. By solving the stochastic optimization problem, optimal day-ahead bidding curves for the wind energy system are generated, and Douglas–Peucker algorithm is used to fit the bidding curves according to market requirements. Case studies based on real world data in electricity markets are performed to prove the effectiveness of the proposed risk parameter scenario generation method and energy bidding strategies. Finally, conclusions and practical suggestions on future research works are provided

Experimental modal analysis and optimal design of cab’s isolation system for a single drum vibratory roller

The purpose of this paper is to solve problems about cab’s low-frequency shaking in the direction of forward motion when vibratory roller operates. To solve this problem, a modal test for a single-drum vibratory roller is carried out by the Belgium LMS dynamic testing which is used to identify the model parameters and find out the natural frequency of the vehicle. A Finite Element Analysis (FEA) simulation is carried out to find out the reasons causing the cab’s low-frequency shaking. The model simulation results are found to be in good agreement with the experimental results. Finally, the design parameters of cab’s isolation system are optimized to reach the maximum value of the first-order natural frequency in order to avoid resonance vibration for cab at low frequency and reduce cab’s low-frequency shaking

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve