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.

Negative Norms in Quantized Strings as Dark Energy Density of the Cosmos

The present short paper is concerned with accurate explanation as well as quantification of the so called missing dark energy of the cosmos. It was always one of the main objectives of any successful general theory of high energy particle physics and quantum cosmology to keep non-physical negative norms, the so called ghosts completely out of that theory. The present work takes the completely contrary view by admitting these supposedly spurious states as part of the physical Hilbert space. It is further shown that rethinking the ghost free condition with the two critical spacetime dimensions D1 = 26 and D2 = 25 together with the corresponding intercept a1 = 1 and a2 ≤ 1 respectively and in addition imposing, as in Gross et al. heterotic superstrings, an overall 496 dimensional exceptional Lie symmetry group, then one will discover that there are two distinct types of energy. The first is positive norm ordinary energy connected to the zero set quantum particles which is very close to the measured ordinary energy density of the cosmos, namely E(O) = mc2/22. The second is negative norm (i.e. ghost) energy connected to the empty set quantum wave and is equal to the conjectured dark energy density of the cosmos E(D) = mc2 (21/22) presumed to be behind the observed accelerated cosmic expansion. That way we were able to not only explain the physics of dark energy without adding any new concepts or novel additional ingredients but also we were able to compute the dark energy density accurately and in full agreement with measurements and observations.

Generating Synthetic Data to Reduce Prediction Error of Energy Consumption

Renewable and nonrenewable energy sources are widely incorporated for solar and wind energy that produces electricity without increasing carbon dioxide emissions.Energy industries worldwide are trying hard to predict future energy consumption that could eliminate over or under contracting energy resources and unnecessary financing.Machine learning techniques for predicting energy are the trending solution to overcome the challenges faced by energy companies.The basic need for machine learning algorithms to be trained for accurate prediction requires a considerable amount of data.Another critical factor is balancing the data for enhanced prediction.Data Augmentation is a technique used for increasing the data available for training.Synthetic data are the generation of new data which can be trained to improve the accuracy of prediction models.In this paper,we propose a model that takes time series energy consumption data as input,pre-processes the data,and then uses multiple augmentation techniques and generative adversarial networks to generate synthetic data which when combined with the original data,reduces energy consumption prediction error.We propose TGAN-skip-Improved-WGAN-GP to generate synthetic energy consumption time series tabular data.We modify TGANwith skip connections,then improveWGANGPby defining a consistency term,and finally use the architecture of improved WGAN-GP for training TGAN-skip.We used various evaluation metrics and visual representation to compare the performance of our proposed model.We also measured prediction accuracy along with mean and maximum error generated while predicting with different variations of augmented and synthetic data with original data.The mode collapse problemcould be handled by TGAN-skip-Improved-WGAN-GP model and it also converged faster than existing GAN models for synthetic data generation.The experiment result shows that our proposed technique of combining synthetic data with original data could significantly reduce the prediction error rate and increase the prediction accuracy of energy consumption.

The Influence of Systematic Errors on the Asian Summer Monsoon Circulation

The systematic errors of wind field associated with the prediction of Asian summer monsoon and their impact on the monsoon circulation have been studied in this paper. The daily operational analyses and fore-casts (up to day-5) of the National Centre for Medium Range Weather Forecasting (NCMRWF), India, over the Asian summer monsoon domain for the period June, July and August of 1995 are made use for the purpose. The systematic errors associated with the low level flow delineate, reduction in the strength of trade winds leading to weakening of cross equatorial flow as well as westerly flow over Indian Ocean. The upper level errors connote weakening of Tibetan anticyclone and reduction in the strength of return flow into the Southern Hemisphere. Further, these errors evince growing tendency with increase in the forecast period. Apart from the general underestimation of kinetic energy budget terms, the model forecasts fail to represent the transient eddies. The forecasts show increasing trend in the conversion of eddy to mean kinetic energy. These errors enfeeble Asian summer monsoon circulation with increase in the forecast period. Key words Monsoon - Systematic errors - Kinetic energy budget The author is grateful to the NCMRWF for providing data and computing facilities to carry out the present study.

Determination of Energy Interchanged on the Tie Lines- Some Practical Issues

The quality of methods for determining energy transits on the tie lines （lines that connect two neighboring power system） can have significant impact on business activity of the TSOs （transmission system operators）. Existing law regulation is not enough precise regarding definition of methods for metering energy transits （energy interchanged between neighboring TSOs）. This paper analyses disadvantages of method for line losses metering with electric meters and suggests introduction of the measured value corrections.

Study on the Determinants of Energy Demand in China

Based on the modern economic theory and the characteristics of China's energy consumption, this paper analyzes the determinants of energy demand in China, builds up a China's energy demand model, and examines the long-run relationship between China's aggregate energy consumption and the main economic variables such as GDP by using the Johansen multivariate approach. It is found that there exists unique long-run relationship among the variables in the model over the sampling period. An error-correction model provides an appropriate framework for forecasting the short-run fluctuations in the aggregate demand of China.

The Average Errors for Linear Combinations of Bernstein Operators on the Wiener Space

In this paper, we discuss the average errors of function approximation by linear combinations of Bernstein operators. The strongly asymptotic orders for the average errors of the combinations of Bernstein operators sequence are determined on the Wiener space.

OPTIMAL ERROR ESTIMATE IN L~∞(J;L^2(Ω)) NORM OF FEM FOR A MODEL FOR COMPRESSIBLE MISCIBLE DISPLACEMENT IN POROUS MEDIA

We’ll study the FEM for a model for compressible miscible displacement in porous media which includes molecular diffusion and mechanical dispersion in one-dimensional space.A class of vertices-edges-elements interpolation operator ink is introduced.With the help of ink(not elliptic projection),the optimal error estimate in L∞(J;L2(Ω)) norm of FEM is proved.

Design and fabrication of button-style beam position monitors for the HEPS synchrotron light facility

At the High Energy Photon Source (HEPS),a high orbital stability of typically 10% of the beam size and angular divergence must be achieved.The beam size at the insertion devices is 10μm horizontally and 1μm vertically,which implies that the beam orbit must be stabilized to the sub-micrometer level.This results in stringent tolerance and quality control requirements for the series production of beam position monitor (BPM) pickups.In this study,analytical formulas were used and CST simulations were performed to analyze the effects of the mechanical tolerances of BPM pickups on beam position measurement.The results of electromagnetic?eld simulations revealed how various mechanical errors,such as button size and location accuracy,as well as the related button capacitance,exert different in?uences on the beam position measurement.The performance of an actual BPM pickup was measured,along with an assessment of the error on the beam position measurement.Additionally,a wake?eld analysis,including an investigation of trapped resonant modes and related thermal deformation,was conducted.

Energy efficiency enhancement of two-way amplifier forward relaying with channel estimation error

In order to save energy consumption of two-way amplifier forward(AF) relaying with channel estimation error, an energy efficiency enhancement scheme is proposed in this work. Firstly, through the analysis of two-way AF relaying mode with channel estimation error, the resultant instantaneous SNRs at end nodes is obtained. Then, by using a high SNR approximation, outage possibility is acquired and its simple closed-form expression is represented. Specially, for using the energy resource more efficiently, a low-complexity power allocation and transmission mode selection policy is proposed to enhance the energy efficiency of two-way AF relay system. Finally, relay priority region is identified in which cooperative diversity energy gain can be achieved. The computer simulations are presented to verify our analytical results, indicating that the proposed policy outperforms direct transmission by an energy gain of 3 dB at the relative channel estimation error less than 0.001. The results also show that the two-way AF relaying transmission loses the two-way AF relaying transmission loses its superiority to direct transmission in terms of energy efficiency when channel estimation error reaches 0.03.

Effect of non-Gaussian properties of the sea surface on the low-incidence radar backscatter and its inversion in terms of wave spectra by an ocean wave spectrometer

The principle of ocean wave spectrometers was first presented several decades ago to detect the directional wave spectrum with real-aperture radar(Jackson,1981). To invert wave spectra using an ocean wave spectrometer,for simplicity,the hydrodynamic forcing and wave-wave interaction effect are neglected and a Gaussian slope probability density function(pdf) is used to calculate the normalized backscattering cross-section( σ 0) of the ocean surface. However,the real sea surface is non-Gaussian. It is not known whether the non-Gaussian property of the sea surface will affect the performance of the inversion of the wave spectrum if following existing inversion steps and methods. In this paper,the pdf of the sea surface slope is expressed as a Gram-Charlier fourth-order expansion,which is quasi-Gaussian. The modulation transfer function(MTF) is derived for a non-Gaussian slope pdf. The effects of non-Gaussian properties of the sea surface slope on the inversion process and result are then studied in a simulation of the SWIM(Surface Waves Investigation and Monitoring) instrument configuration to be used on the CFOSAT(China-France Oceanography Satellite) mission. The simulation results show that the mean trend of σ 0 depends on the sea slope pdf,and the peakedness and skewness coefficients of the slope pdf affect the shape of the mean trend of σ 0 versus incidence and azimuth; owing to high resolution of σ 0 in the range direction,MTF obtained using the mean trend of σ 0 is almost as accurate as that set in the direct simulation; in the inversion,if ignoring the non-Gaussian assumption,the inversion performances for the wave spectrum decrease,as seen for an increase in the energy error of the inverted wave slope spectrum. However,the peak wavelength and wave direction are the same for inversions that consider and ignore the non-Gaussian property.

The Development of a Physical Conservation Fidelity Global Spectral Model-From Dynamic Framework to a Full Model

The fidelity scheme of physical conservation laws has been applied in the dynamic framework of a global spectral model. In this study, a set of diabatic physical processes are also involved. Based on six 30-day numerical integrations of real-time data, we show that the full model is able to reproduce the primary features of global energy cycle and hydrological distribution. Additionally, the root-mean-square error is dramatically decreased when diabatic processes are considered. Another advantage is that the false structure of ＂double Intertropical Convergence Zone （ITCZ）＂ is not seen in the result, although the orecioitation rate becomes lower.

Improving the BER performance of turbo codes with short frame size based on union bound

timizing the formula, the energy for every bit of the codeword is optimized to achieve the minimum BER at high SNR region. At last, an adjustable parameter is employed to compensate the degrada- tions of BER at low and moderate SNR regions. Case studies indicate that the improvements of BER for turbo codes with short frame size are significant at a wide range of SNR

COARSE-MESH-ACCURACY IMPROVEMENT OF BILINEAR Q_4-PLANE ELEMENT BY THE COMBINED HYBRID FINITE ELEMENT METHOD

The combined hybrid finite element method is of an intrinsic mechanism of enhancing coarse-mesh-accuracy of lower order displacement schemes. It was confirmed that the combined hybrid scheme without energy error leads to enhancement of accuracy at coarse meshes, and that the combination parameter plays an important role in the enhancement. As an improvement of conforming bilinear Q(4)-plane element, the combined hybrid method adopted the most convenient quadrilateral displacements-stress mode, i.e.,the mode of compatible isoparametric bilinear displacements and pure constant stresses. By adjusting the combined parameter, the optimized version of the combined hybrid element was obtained and numerical tests indicated that this parameter-adjusted version behaves much better than Q(4)-element and is of high accuracy at coarse meshes. Due to elimination of stress parameters at the elemental level, this combined hybrid version is of the same computational cost as that of Q(4)-element.

Studies on absorption coefficients of dual-energy γ-rays and measur-ing error correction for multiphase fraction determination

In this article, principle and mathematical method of determining the phase fractions of multiphase flows by using a dual-energy γ -ray system have been described. The dual-energy γ -ray device is composed of radioactive isotopes of 241Am and 137Cs with γ -ray energies of 59.5 and 662 keV, respectively. A rational method to calibrate the absorption coefficient was introduced in detail. The modified arithmetic is beneficial to removing the extra Compton scattering from the measured value. The result shows that the dual-energy γ -ray technique can be used in three-phase flow with average accuracy greater than 95%, which enables us to determine phase fractions almost independent of the flow regime. Improvement has been achieved on measurement accuracy of phase fractions.

Security Regulations in Mexican Renewable Energies: Case of Geothermal Projects

A review of natural resources existing in México is done. The description of the renewable energies for electricity generation operating at date along the country, includes hydro, wind, solar, biomass and geothermal, among others. The installed capacity (to 2012) in México for electric generation from renewable energies is equivalent to 22% of total generation capacity. México has geothermal resources, which can be classified as high and low enthalpy, and of hot dry rock. To date, the exploitation has focused mainly on high enthalpy geothermal fields. Geothermal power plants do not burn fuel, preventing gas emissions helping to reduce global warming and greenhouse effect. Security risks in México geothermal fields, as a part of renewable energies linked to Smart Grids, are described emphasizing their geographical locations to facilitate the exposure to dangerous events. The results about research on Mexican Official Norms protecting environment related with geothermal operation projects are shown. The Mexican geothermal projects have developed under rules that provide security to workers and people, avoiding impacts on the environment. However, it was found that it necessarily emphasized previsions to damages and remedial actions for grids due to risks by natural contingencies (cyclones, winds, earthquakes) and by artificial causes such as vandalism (grids breaking, fire, explosions, etc.). Unfortunately, there are no preventive norms against natural risks. After all the analyses carried out, security must be considered by nature a dynamic and ever-changing process.

Two Energy-Preserving Compact Finite Difference Schemes for the Nonlinear Fourth-Order Wave Equation

In this paper,two fourth-order compact finite difference schemes are derived to solve the nonlinear fourth-order wave equation which can be viewed as a generalized model from the nonlinear beam equation.Differing from the existing compact finite difference schemes which preserve the total energy in a recursive sense,the new schemes are proved to per-fectly preserve the total energy in the discrete sense.By using the standard energy method and the cut-off function technique,the optimal error estimates of the numerical solutions are established,and the convergence rates are of O(h^(4)+τ^(2))with mesh-size h and time-step τ.In order to improve the computational efficiency,an iterative algorithm is proposed as the outer solver and the double sweep method for pentadiagonal linear algebraic equations is introduced as the inner solver to solve the nonlinear difference schemes at each time step.The convergence of the iterative algorithm is also rigorously analyzed.Several numerical results are carried out to test the error estimates and conservative properties.

Convergence Analysis of the Fully Decoupled Linear Scheme for Magnetohydrodynamic Equations

In this paper, we propose a fully decoupled and linear scheme for the magnetohydrodynamic (MHD) equation with the backward differential formulation (BDF) and finite element method (FEM). To solve the system, we adopt a technique based on the “zero-energy-contribution” contribution, which separates the magnetic and fluid fields from the coupled system. Additionally, making use of the pressure projection methods, the pressure variable appears explicitly in the velocity field equation, and would be computed in the form of a Poisson equation. Therefore, the total system is divided into several smaller sub-systems that could be simulated at a significantly low cost. We prove the unconditional energy stability, unique solvability and optimal error estimates for the proposed scheme, and present numerical results to verify the accuracy, efficiency and stability of the scheme.

STAP method based on atomic norm minimization with array amplitude-phase error calibration

In this paper,a space-time adaptive processing(STAP)method is proposed for the airborne radar with the array amplitude-phase error considered,which is based on atomic norm minimization(ANM).In the conventional ANM-based STAP method,the influence of the array amplitude-phase error is not considered and restrained,which inevitably causes performance deterioration.To solve this problem,the array amplitude-phase error is firstly estimated.Then,by pre-estimating the array amplitude-phase error information,a modified ANM model is built,in which the array amplitude-phase error factor is separated from the clutter response and the clutter covariance matrix(CCM)to improve the estimation accuracy of the CCM.To prove that the atomic norm theory is applicable in the presence of the array amplitude-phase error,the clutter sparsity is analyzed in this paper.Meanwhile,simulation results demonstrate that the proposed method is superior to the state-of-the-art STAP method.Moreover,the measured data is used to verify the effectiveness of the proposed method.

Adaptive Error Curve Learning Ensemble Model for Improving Energy Consumption Forecasting

Despite the advancement within the last decades in the field of smart grids,energy consumption forecasting utilizing the metrological features is still challenging.This paper proposes a genetic algorithm-based adaptive error curve learning ensemble(GA-ECLE)model.The proposed technique copes with the stochastic variations of improving energy consumption forecasting using a machine learning-based ensembled approach.A modified ensemble model based on a utilizing error of model as a feature is used to improve the forecast accuracy.This approach combines three models,namely CatBoost(CB),Gradient Boost(GB),and Multilayer Perceptron(MLP).The ensembled CB-GB-MLP model’s inner mechanism consists of generating a meta-data from Gradient Boosting and CatBoost models to compute the final predictions using the Multilayer Perceptron network.A genetic algorithm is used to obtain the optimal features to be used for the model.To prove the proposed model’s effectiveness,we have used a four-phase technique using Jeju island’s real energy consumption data.In the first phase,we have obtained the results by applying the CB-GB-MLP model.In the second phase,we have utilized a GA-ensembled model with optimal features.The third phase is for the comparison of the energy forecasting result with the proposed ECL-based model.The fourth stage is the final stage,where we have applied the GA-ECLE model.We obtained a mean absolute error of 3.05,and a root mean square error of 5.05.Extensive experimental results are provided,demonstrating the superiority of the proposed GA-ECLE model over traditional ensemble models.