Loss Factors and their Effect on Resonance Peaks in Mechanical Systems

The loss factors and their effects on the magnitude and frequency of resonance peaks in various mechanical sys-tems are reviewed for acoustic,vibration,and vibration fatigue applications.The main trends and relationships were obtained for linear mechanical models with hysteresis damping.The well-known features(complex module of elasticity,total loss factor,etc.)are clarified for practical engineers and students,and new results are presented(in particular,for 2-DOF in-series models with hysteresis friction).The results are of both educational and prac-tical interest and may be applied for NVH analysis and testing,mechanical and aeromechanical design,and noise and vibration control in buildings.

Combined Optimal Dispatch of Thermal Power Generators and Energy Storage Considering Thermal Power Deep Peak Clipping and Wind Energy Emission Grading Punishment

Peak load and wind energy emission pressure rise more as wind energy penetration keeps growing,which affects the stabilization of the PS(power system).This paper suggests integrated optimal dispatching of thermal power generators and BESS(battery energy storage system)taking wind energy emission grading punishment and deep peak clipping into consideration.Firstly,in order to minimize wind abandonment,a hierarchical wind abandonment penalty strategy based on fuzzy control is designed and introduced,and the optimal grid-connected power of wind energy is determined as a result of minimizing the peak cutting cost of the system.Secondly,considering BESS and thermal power,the management approach of BESS-assisted virtual peak clipping of thermal power generators is aimed at reducing the degree of deep peak clipping of thermal power generators and optimizing the output of thermal power generators and the charging and discharging power of BESS.Finally,Give an example of how this strategy has been effective in reducing abandonment rates by 0.66% and 7.46% individually for different wind penetration programs,and the daily average can reduce the peak clipping power output of thermal power generators by 42.97 and 72.31 MWh and enhances the effect and economy of system peak clipping.

Physics-informed machine learning model for prediction of ground reflected wave peak overpressure

The accurate prediction of peak overpressure of explosion shockwaves is significant in fields such as explosion hazard assessment and structural protection, where explosion shockwaves serve as typical destructive elements. Aiming at the problem of insufficient accuracy of the existing physical models for predicting the peak overpressure of ground reflected waves, two physics-informed machine learning models are constructed. The results demonstrate that the machine learning models, which incorporate physical information by predicting the deviation between the physical model and actual values and adding a physical loss term in the loss function, can accurately predict both the training and out-oftraining dataset. Compared to existing physical models, the average relative error in the predicted training domain is reduced from 17.459%-48.588% to 2%, and the proportion of average relative error less than 20% increased from 0% to 59.4% to more than 99%. In addition, the relative average error outside the prediction training set range is reduced from 14.496%-29.389% to 5%, and the proportion of relative average error less than 20% increased from 0% to 71.39% to more than 99%. The inclusion of a physical loss term enforcing monotonicity in the loss function effectively improves the extrapolation performance of machine learning. The findings of this study provide valuable reference for explosion hazard assessment and anti-explosion structural design in various fields.

Estimation of peak wave period from surface texture motion in videos

Wave information retrieval from videos captured by a single camera has been increasingly applied in marine observation.However,when the camera observes ocean waves at low grazing angles,the accurate extraction of wave information from videos will be affected by the interference of the fine ripples on the sea surface.To solve this problem,this study develops a method for estimating peak wave periods from videos captured at low grazing angles.The method extracts the motion of the sea surface texture from the video and obtains the peak wave period via the spectral analysis.The calculation results captured from real-world videos are compared with those obtained from X-band radar inversion and tracking buoy movement,with maximum deviations of 8%and 14%,respectively.The analysis of the results shows that the peak wave period of the method has good stability.In addition,this paper uses a pinhole camera model to convert the displacement of the texture from pixel height to actual height and performs moving average filtering on the displacement of the texture,thus conducting a preliminary exploration of the inversion of significant wave height.This study helps to extend the application of sea surface videos.

Peak Shaving Strategy of Concentrating Solar Power Generation Based on Multi-Time-Scale and Considering Demand Response

According to the multi-time-scale characteristics of power generation and demand-side response(DR)resources,as well as the improvement of prediction accuracy along with the approaching operating point,a rolling peak shaving optimization model consisting of three different time scales has been proposed.The proposed peak shaving optimization model considers not only the generation resources of two different response speeds but also the two different DR resources and determines each unit combination,generation power,and demand response strategy on different time scales so as to participate in the peaking of the power system by taking full advantage of the fast response characteristics of the concentrating solar power(CSP).At the same time,in order to improve the accuracy of the scheduling results,the combination of the day-ahead peak shaving phase with scenario-based stochastic programming can further reduce the influence of wind power prediction errors on scheduling results.The testing results have shown that by optimizing the allocation of scheduling resources in each phase,it can effectively reduce the number of starts and stops of thermal power units and improve the economic efficiency of system operation.The spinning reserve capacity is reduced,and the effectiveness of the peak shaving strategy is verified.

Assessment of Axial Power Peaking Factors in GHARR-1 LEU Core: A Decadal Simulation Analysis

This study aims to thoroughly investigate the axial power peaking factors (PPF) within the low-enriched uranium (LEU) core of the Ghana Research Reactor-1 (GHARR-1). This study uses advanced simulation tools, like the MCNPX code for analysing neutron behavior and the PARET/ANL code for understanding power variations, to get a clearer picture of the reactor’s performance. The analysis covers the initial six years of GHARR-1’s operation and includes projections for its whole 60-year lifespan. We closely observed the patterns of both the highest and average PPFs at 21 axial nodes, with measurements taken every ten years. The findings of this study reveal important patterns in power distribution within the core, which are essential for improving the safety regulations and fuel management techniques of the reactor. We provide a meticulous approach, extensive data, and an analysis of the findings, highlighting the significance of continuous monitoring and analysis for proactive management of nuclear reactors. The findings of this study not only enhance our comprehension of nuclear reactor safety but also carry significant ramifications for sustainable energy progress in Ghana and the wider global context. Nuclear engineering is essential in tackling global concerns, such as the demand for clean and dependable energy sources. Research on optimising nuclear reactors, particularly in terms of safety and efficiency, is crucial for the ongoing advancement and acceptance of nuclear energy.

Analysis of factors influencing carbon emissions in the Yangtze River Delta region and projections of carbon peak scenarios

Based on the supply-side perspective,the improved STIRPAT model is applied to reveal the mechanisms of supply-side factors such as human,capital,technology,industrial synergy,institutions and economic growth on carbon emissions in the Yangtze River Delta(YRD)through path analysis,and to forecast carbon emissions in the YRD from the baseline scenario,factor regulation scenario and integrated scenario to reach the peak.The results show that:(1)Jiangsu's high carbon emission pattern is the main reason for the YRD hindering the synergistic regulation of carbon emissions.(2)Human factors,institutional factors and economic growth factors can all contribute to carbon emissions in the YRD region,while technological and industrial factors can generally suppress carbon emissions in the YRD region.(3)Under the capital regulation scenario,the YRD region has the highest level of carbon emission synergy,with Jiangsu reaching its peak five years earlier.Under the balanced regulation scenario,the YRD region as a whole,Jiangsu,Zhejiang and Anhui reach the peak as scheduled.

Analysis of Smooth Cepstral Peak Prominence in Hypokinetic Dysarthria Associated With Parkinson’s Disease

Smoothed cepstral peak prominence(CPPs)is a measurement of the distance from the prominent cepstral peak to the linear regression line directly beneath it.Variations of CPPs data acquisition and analysis lead to the complexity of the clinical cut-off values,and there are no agreeable values for a specific voice disorder,such as hypokinetic dysarthria associated with Parkinson’s disease(PD).This study examined the CPPs in people with hypokinetic dysarthria associated with PD compared with healthy participants.Results demonstrated significant differences in speech tasks of sustained vowel and connected speech,with CPPs of connected speech more sensitive to dysphonia and gender difference in PD participants.Males in PD participants presented higher CPPs for sustained vowels and lower CPPs for connected speech than females.It is implied that a consistent clinical application protocol is necessary,and multiple acoustic measures are needed to ensure the accuracy of clinical decisions.

Spatiotemporal variations of ecosystem services and driving factors in the Tianchi Bogda Peak Natural Reserve of Xinjiang,China

Nature reserves play a significant role in providing ecosystem services and are key sites for biodiversity conservation.The Tianchi Bogda Peak Natural Reserve(TBPNR),located in Xinjiang Uygur Autonomous Region,China,is an important ecological barrier area in the temperate arid zone.The evaluation of its important ecosystem services is of great significance to improve the management level and ecological protection efficiency of the reserve.In the present study,we assessed the spatiotemporal variations of four ecosystem services(including net primary productivity(NPP),water yield,soil conservation,and habitat quality)in the TBPNR from 2000 to 2020 based on the environmental and social data using the Integrated Valuation of Ecosystem Services and Trade-offs(InVEST)model.In addition,the coldspot and hotspot areas of ecosystem services were identified by hotspot analysis,and the trade-off and synergistic relationships between ecosystem services were analyzed using factor analysis in a geographic detector.During the study period,NPP and soil conservation values in the reserve increased by 48.20%and 25.56%,respectively;conversely,water yield decreased by 16.56%,and there was no significant change in habitat quality.Spatially,both NPP and habitat quality values were higher in the northern part and lower in the southern part,whereas water yield showed an opposite trend.Correlation analysis revealed that NPP showed a synergistic relationship with habitat quality and soil conservation,and exhibited a trade-off relationship with water yield.Water yield and habitat quality also had a trade-off relationship.NPP and habitat quality were affected by annual average temperature and Normalized Difference Vegetation Index(NDVI),respectively,while water yield and soil conservation were more affected by digital elevation model(DEM).Therefore,attention should be paid to the spatial distribution and dynamics of trade-off and synergistic relationships between ecosystem services in future ecological management.The findings of the present study provide a reference that could facilitate the sustainable utilization of ecosystem services in the typical fragile areas of Northwest China.

Overlapped peaks resolution for linear sweep polarography using Gaussian-like distribution

A resolution method based on Gaussian-like distribution for overlapped linear sweep polarographic peaks was proposed to simultaneously detect the polymetallic components, such as Zn（Ⅱ） and Co（Ⅱ）, coexisting in the leaching solution of zinc hydrometallurgy. A Gaussian-like distribution was constructed as the sub-model of overlapped peaks by analyzing the characteristics of linear sweep polarographic curve. Then, the abscissas of each peak and trough were pinpointed through multi-resolution wavelet decomposition, the curve and its derivative curves were fitted by using nonlinear weighted least squares （NWLS）. Finally, overlapped peaks were resolved into independent sub-peaks based on fitted reconstruction parameters. The experimental results show that the relative error of half-wave potential pinpointed by multi-resolution wavelet decomposition is less than 1% and the accuracy of Ip fitted by NWLS is higher than 96%. The proposed resolution method is effective for overlapped linear sweep polarographic peaks of Zn（Ⅱ） and Co（Ⅱ）.

Peaks-pro2的结构以及在蓝光刻录机上的应用

Peaks-pro2(Peaks-Processor2)是专门对应蓝光及数字广播产品而开发的一款顶级家庭AV处理用主控芯片。该芯片集高品位AV、低功耗、实时、安全技术于一体,兼容SD、BD/DVD、HDD等多媒体驱动,可对数字广播信号进行2通道同时刻录及播放。该款Peaks-pro2芯片的推出促进了家庭AV行业的飞速发展。

Artificial ground motion compatible with specified ground shaking peaks and target response spectrum

This article describes a hybrid simulation method to generate artificial ground motion time histories that are compatible with specified peak seismic acceleration, velocity and displacement as well as the target response spectrum of absolute acceleration. First, based on traditional methods that match the target spectrum in the frequency domain, an initial acceleration time history was synthesized to satisfy the specified peak acceleration, target spectral acceleration and intensity envelope. Second, by using the inversion formula of the seismic input to a linear single-degree-of-freedom system and by superimposing a series of narrow-band time histories in the time domain, the initial time history is further modified to allow its peak velocity and displacement to approach the targets and improve its matching precision with the target spectrum. Numerical examples are provided to demonstrate that the proposed method achieves good agreement with the target values.

A NOVEL ALGORITHM FOR SIDE PEAKS SUPPRESSION OF AMBIGUITY FUNCTION FOR PASSIVE RADAR BASED ON CHINESE DTTB SIGNAL

The ambiguity function of Chinese standard Digital Television Terrestrial Broadcasting (DTTB) signals for passive radar contains one main peak and many side peaks. The side peaks may cause the false alarms. The relative positions and the reasons for the side peaks are analyzed and a new algorithm for side peaks suppression is proposed in this paper. The algorithm, in consideration of the characteristics of the structure of the frame, can eliminate the side peaks completely in the valid Doppler observation interval by setting the reference signals to zero at equal intervals. Both the simulative and experimental results show that this algorithm can improve the performance of target detection of the passive radar based on DTTB signal.

Wave height estimation using the singular peaks in the sea echoes of high frequency radar

The popular methods to estimate wave height with high-frequency（HF） radar depend on the integration over the second-order spectral region and thus may come under from even not strong external interference. To improve the accuracy and increase the valid detection range of the wave height measurement, particularly by the smallaperture radar, it is turned to singular peaks which often exceed the power of other frequency components. The power of three kinds of singular peaks, i.e., those around ±1,±√2 and ±1√2 times the Bragg frequency, are retrieved from a one-month-long radar data set collected by an ocean state monitoring and analyzing radar,model S（OSMAR-S）, and in situ buoy records are used to make some comparisons. The power response to a wave height is found to be described with a new model quite well, by which obvious improvement on the wave height estimation is achieved. With the buoy measurements as reference, a correlation coefficient is increased to 0.90 and a root mean square error（RMSE） is decreased to 0.35 m at the range of 7.5 km compared with the results by the second-order method. The further analysis of the fitting performance across range suggests that the peak has the best fit and maintains a good performance as far as 40 km. The correlation coefficient is 0.78 and the RMSE is 0.62 m at 40 km. These results show the effectiveness of the new empirical method, which opens a new way for the wave height estimation with the HF radar.

Reconsideration of Anelastic Relaxation Peaks in Pure Aluminium

The temperature dependence of internal friction （ T- tan φ curves） in pure aluminium （Al） is measured at sixteen different frequencies. Based on T- tan φ curves, the frequency dependence of internal friction （f -tan φ curves） is also obtained by the interpolation method. An internal friction peak is observed in both the T - tan φ curves and the f - tan φ curves. The activation energy of the peak in the f - tan φ curves is found to be 2.08 ± 0.02 eV and compared to the value of 1.60 ± 0.04 eV in the T - tan φ curves. It is suggested that the change of relaxation strength with temperature should be considered when one calculates the activation energy of the peak in T- tan φ curves.

INFINITELY MANY SOLUTIONS WITH PEAKS FOR A FRACTIONAL SYSTEM IN R^N

In this article,we consider the following coupled fractional nonlinear Schrödinger system in R^{(−Δ)su+P(x)u=μ1|u|^2p−2u+β|u|p|u|p−2u,x∈RN,(−Δ)sv+Q(x)v=μ2|v|^2p−2v+β|v|p|v|p−2v,x∈RN,u,v∈Hs(RN),where N≥2,0<s<1,1<p<NN−2s,μ1>0,μ2>0 andβ∈R is a coupling constant.We prove that it has infinitely many non-radial positive solutions under some additional conditions on P(x),Q(x),p andβ.More precisely,we will show that for the attractive case,it has infinitely many non-radial positive synchronized vector solutions,and for the repulsive case,infinitely many non-radial positive segregated vector solutions can be found,where we assume that P(x)and Q(x)satisfy some algebraic decay at infinity.

Estimate of Peaks of Carbon Emissions and Pricing of Carbon Emission Permit in China

With the aid of Matlab software, the peaks of China＇s carbon emissions and their appearing time in three situations were simulated, and the shallow price of carbon emission permit and its effects on China＇s economic growth were analyzed. The results show that it is most effective and feasible to reduce energy consumption per GDP by 25%, and the peak of China＇s carbon emissions will appear in 2017. As a result, energy conser- vation and emission reduction is realized, and China＇s international talk power about carbon emission will improved. However, the shallow price and permit rate of carbon emission permit calculated in the situation are the lowest, and the adverse impact of the initial price of carbon emissions on China＇s economic growth is the largest. Therefore, consideration should be given to both the promotion of pricing and trading of carbon emission permit to reduction of carbon emissions and their adverse effects on GDP in China.

Modeling of Energy Consumption and Effluent Quality Using Density Peaks-based Adaptive Fuzzy Neural Network

Modeling of energy consumption(EC) and effluent quality(EQ) are very essential problems that need to be solved for the multiobjective optimal control in the wastewater treatment process(WWTP). To address this issue, a density peaks-based adaptive fuzzy neural network(DP-AFNN) is proposed in this study. To obtain suitable fuzzy rules, a DP-based clustering method is applied to fit the cluster centers to process nonlinearity.The parameters of the extracted fuzzy rules are fine-tuned based on the improved Levenberg-Marquardt algorithm during the training process. Furthermore, the analysis of convergence is performed to guarantee the successful application of the DPAFNN. Finally, the proposed DP-AFNN is utilized to develop the models of EC and EQ in the WWTP. The experimental results show that the proposed DP-AFNN can achieve fast convergence speed and high prediction accuracy in comparison with some existing methods.

Peaks over Manifold (POM): A Novel Technique to Analyze Extreme Events over Surfaces

We present a novel method to analyze extreme events of flows over manifolds called Peaks Over Manifold (POM). Here we show that under general and realistic hypotheses, the distribution of affectation measures converges to a Generalized Pareto Distribution (GPD). The method is applicable to floods, ice cover extent, extreme rainfall or marine heatwaves. We present an application to a synthetic data set on tide height and to real ice cover data in Antartica.

K-means Find Density Peaks in Molecular Conformation Clustering

Performing cluster analysis on molecular conformation is an important way to find the representative conformation in the molecular dynamics trajectories.Usually,it is a critical step for interpreting complex conformational changes or interaction mechanisms.As one of the density-based clustering algorithms,find density peaks(FDP)is an accurate and reasonable candidate for the molecular conformation clustering.However,facing the rapidly increasing simulation length due to the increase in computing power,the low computing efficiency of FDP limits its application potential.Here we propose a marginal extension to FDP named K-means find density peaks(KFDP)to solve the mass source consuming problem.In KFDP,the points are initially clustered by a high efficiency clustering algorithm,such as K-means.Cluster centers are defined as typical points with a weight which represents the cluster size.Then,the weighted typical points are clustered again by FDP,and then are refined as core,boundary,and redefined halo points.In this way,KFDP has comparable accuracy as FDP but its computational complexity is reduced from O(n^(2))to O(n).We apply and test our KFDP method to the trajectory data of multiple small proteins in terms of torsion angle,secondary structure or contact map.The comparing results with K-means and density-based spatial clustering of applications with noise show the validation of the proposed KFDP.