Optimal Values Of Coefficients Research Articles

Extracting the bulk viscosity of the quark–gluon plasma

We investigate the implications of a nonzero bulk viscosity coefficient on the azimuthal momentum anisotropy of ultracentral relativistic heavy ion collisions at the Large Hadron Collider. We find that, with IP-Glasma initial conditions, a finite bulk viscosity coefficient leads to a better description of the flow harmonics in ultracentral collisions. We then extract optimal values of bulk and shear viscosity coefficients that provide the best agreement with flow harmonic coefficients data in this centrality class.

Surface diffuseness correction in global mass formula

By taking into account the surface diffuseness correction for unstable nuclei, the accuracy of the macroscopic–microscopic mass formula is further improved. The rms deviation with respect to essentially all the available mass data falls to 298 keV, crossing the 0.3 MeV accuracy threshold for the first time within the mean-field framework. Considering the surface effect of the symmetry potential which plays an important role in the evolution of the “neutron skin” toward the “neutron halo” of nuclei approaching the neutron drip line, we obtain an optimal value of the symmetry energy coefficient J=30.16 MeV. With an accuracy of 258 keV for all the available neutron separation energies and of 237 keV for the α-decay Q-values of super-heavy nuclei, the proposed mass formula is particularly important not only for the reliable description of the r process of nucleosynthesis but also for the study of the synthesis of super-heavy nuclei.

New method of calculating adsorption and scattering for Xe-Pt(111) using Direct Simulation Monte Carlo techniques

A new scheme is presented for calculating adsorption and scattering for a gas–surface system in the thermal scattering regime using Direct Simulation Monte Carlo techniques. Results are compared with experimental data for the Xe-Pt(111) gas–surface system at surface temperatures of 95 K (adsorption) and 800 K (scattering). Fair agreement is found for the initial adsorption probability, while good agreement is found for the adsorption probability versus coverage. When implemented with the Cercignani–Lampis–Lord scattering kernel, the new scheme was found to improve scattering properties. Any scattering kernel or method amenable to Direct Simulation Monte Carlo techniques may be applied with the new scheme. Optimal values of accommodation coefficients were also found for the surface (αn = 0.74, αt = 0.60) and the adlayer (αn,ad = 0.89, αt,ad = 0.60).

An optimal hybrid model for atomic power generation prediction in Japan

The grey model GM(1,1), which is based on grey system theory, has become a powerful tool for the prediction problems in power systems. However, the prediction accuracy of grey model is unsatisfying when original data set shows great randomness. In this paper, in order to improve the prediction capability of grey model, the exponential smoothing (ES) method is integrated into GM(1,1) through the preprocessing for original data set. We call the proposed model as ESGM(1,1). The Taylor approximation method is then presented to find the optimal coefficient values of ESGM(1,1). The improved model is defined as T-ESGM(1,1). Finally, Markov chain model is applied to T-ESGM(1,1) for achieving the high prediction accuracy. We call the proposed model as MC-T-ESGM(1,1). A real case of atomic power generation in Japan is used to validate the effectiveness of proposed model.

Optimal output mirror reflection coefficient for powerful InGaAs/AlGaAs laser diode arrays

The optimal value of the output mirror reflection coefficient providing the maximum output power under a constant level of electrical power consumption and the maximum external (slope) lasing efficiency for powerful InGaAs/AlGaAs laser diode arrays (LDA) has been estimated experimentally and theoretically. The LDA active layer overheating and amplified spontaneous emission have been taken into account. For advanced LDAs with the thermal resistance of 0.2K/W and the internal optical loss of 0.5cm−1 the optimal output mirror reflection coefficient is equal to 20%. This value is shifted to the high output mirror reflection coefficient side with a decrease of the LDA excitation level, the LDA thermal resistivity and the internal optical loss. It has been shown that the right selection of the output mirror reflection coefficient optimal value provides the LDA operation with 20% excess of the lasing output power and 10% excess of the external lasing efficiency.

Preparation of graphene nanoflakes/polymer composites and their performances for actuation and energy harvesting applications

Composites based on polyurethane (PU) or P(VDF-TrFE-CFE) terpolymer (T30) filled with various amounts of 60-nm thick graphene nanoflakes were prepared. The dielectric properties, including relative permittivity, loss tangent, and conductivity over a broad range of frequencies were presented and discussed according to the percolation theory. The percolation threshold was found to differ for the two systems, respectively, 7.2 and 3.0 vol. % for the PU and the T30 composites. Differential scanning calorimetry demonstrated that there was practically no interaction between the polymeric matrix and the fillers. The increase in permittivity could not be related to this very slight modification of the polymer but rather to the space charges induced by the graphene flakes. Moreover, measurements of the thickness strain under an applied electric field demonstrated a twofold increase of the actuation capability. The optimal value of the M33 electrostriction coefficient was for both systems obtained for a filler content somewhat lower than the percolation threshold. The PU-graphene composite exhibited better performances compared to its T30-graphene counterpart and this was attributed to the good ratio of relative permittivity to the Young modulus in addition to the specific morphology of the used polyurethane. The energy harvesting properties were investigated by monitoring the evolution of the current under a DC electric field and under AC mechanical strain. The T30-graphene composite was found to be the best material for energy harvesting as previously predicted based on its high permittivity.

Optimization of PI parameters for DSP-based permanent magnet brushless motor drive using response surface methodology

This paper proposes response surface methodology (RSM) for tuning Proportional Integral (PI) coefficients for a Permanent Magnet Brushless Direct Current (PMBLDC) motor drive. Overshoot and settling time data are obtained from the application circuit for different K p – K i pairs. RSM is a union of statistical and mathematical techniques necessary for developing, improving, and optimizing processes. Therefore, optimal values of PI controller coefficients are obtained using RSM. Motion Control Kit (MCK243) is used to carry out digital motion control applications. The MCK243 kit includes a power module and a three phase brushless motor. TMS320F243 programs for PMBLDC motor speed control. Experimental results are given to show the validity of this method.

EVALUATION OF HYDRAULIC PERFORMANCE OF DOWNSTREAM‐CONTROLLED MAIRA‐PHLC IRRIGATION CANALS UNDER CROP‐BASED IRRIGATION OPERATIONS

ABSTRACTDemand‐based irrigation systems are operated according to crop water requirements. As crop water requirements remain variable throughout the growing season, the discharges in the canal also vary to meet demands. The irrigation system under study is a demand‐based semi‐automatic irrigation system, where flows in the main canal are automatically controlled and secondary canals manually operated. The main canal headworks have been equipped with the SCADA system with proportional integral (PI) discharge controllers and the canal itself has been provided with self‐regulating AVIS/AVIO downstream control gates for flow regulation in the canal. The secondary canals have manually operated sliding gates, which are opened or closed as per crop water requirements of the command area following a crop‐based irrigations operation (CBIO) schedule under which they remain closed for one week after one or several weeks open, depending upon water needs. The flow in the main canal is then automatically adjusted according to the number of open or closed secondary offtakes. These operations result in fluctuating flows in the main canal and if not properly planned can cause serious implications for canal safety and its hydrodynamic performance. The PI discharge controllers regulate discharge releases to the canal in order to satisfy demands. The proper selection of PI coefficients ensures system safety and efficient water delivery. The operation of the secondary canals also plays a key role in defining the performance of the automatic operations. The planned opening and closure of a cluster of offtakes ensures safety of the self‐regulating structures and stability of the flows in the main canal. In this paper various options have been tested using hydrodynamic modelling and we found some optimal values of PI coefficients and defined some rules for secondary canal operations to enhance the operational performance and sustainability of downstream‐controlled irrigation canals. Copyright © 2011 John Wiley & Sons, Ltd.

Mean absorption coefficients of air plasmas

Mean absorption coefficients of air (both Planck and Rosseland mean) have been computed for different splitting procedures of the whole frequency interval (1013 – 6×1015 s−1) and various temperatures (1 000 – 30 000 K). Results have been compared and discussed to find the optimal values of mean absorption coefficients for the multigroup method of solution of the equation of radiation transfer.

Modelling, control and Pontryagin Maximum Principle for a two-body wave energy device

Frequency-domain analysis is applied to a wave energy device composed of two coaxial axisymmetric bodies. For each frequency optimal damping coefficient values which maximize absorbed power are obtained. Several displacement amplitude restriction scenarios are considered. A stochastic model to describe the device’s behaviour in irregular waves is developed. Optimal mechanical damping and spring coefficients are computed. Considering different sea state conditions, probability density functions are defined for relevant parameters and time-averaged absorbed power values are obtained.A time domain model is also developed for the device. A non-linear power take-off mechanism configuration, consisting in a hydraulic circuit with low-pressure and high-pressure gas accumulators, is devised. Time-averaged absorbed power is maximized in terms of characteristic mechanism parameter. A sub-optimal method of phase control by latching is applied to the device in order to improve its performance. Analytical development of Pontryagin Maximum Principle is used to establish an algorithm for device’s control.

Off-line tuning of a PI speed controller for a permanent magnet brushless DC motor using DSP

In this paper, a new method of tuning Proportional Integral (PI) coefficients for a permanent magnet brushless DC (PMBLDC) motor drives is proposed. Artificial neural network is used to identify the whole system using maximum overshoot and settling time obtained from the application circuit for different K p– K i pairs. Optimal values of PI controller coefficients are obtained using genetic algorithm. Motion Control Kit (MCK243) is used to carry out digital motion control applications. The MCK243 kit includes a power module and a three-phase brushless motor. TMS320F243 programs are used for PMBLDC motor speed control. Experimental results are given to show the validity of this method.

Applying of genetic algorithm for optimizing methane combustion reactions

PurposeThe aim of this paper is to find the optimal values of the reaction rates coefficients for the combustion of a methane/air mixture for a given reduced reaction mechanism which has a high appropriateness with full reaction mechanism.Design/methodology/approachA multi‐objective genetic algorithm (GA) was used to determine new reaction rate parameters (A's, β's, and Ea's in the non‐Arrhenius expressions). The employed multi‐objective structure of the GA allows for the incorporation of perfectly stirred reactor (PSR), laminar premixed flames, opposed flow diffusion flames, and homogeneous charge compression ignition (HCCI) engine data in the inversion process, thus enabling a greater confidence in the predictive capabilities of the reaction mechanisms obtained.FindingsThe results of this study demonstrate that the GA inversion process promises the ability to assess combustion behaviour for methane, where the reaction rate coefficients are not known. Moreover it is shown that GA can consider a confident method to be applied, straightforwardly, to the combustion chambers, in which complex reactions are occurred.Originality/valueIn this paper, GA is used in more complicated combustion models with fewer assumptions. Another consequence of this study is less CPU time in converging to final solutions.

Application of a hybrid EnKF-OI to ocean forecasting

Abstract. Data assimilation methods often use an ensemble to represent the background error covariance. Two approaches are commonly used; a simple one with a static ensemble, or a more advanced one with a dynamic ensemble. The latter is often non-practical due to its high computational requirements. Some recent studies suggested using a hybrid covariance, which is a linear combination of the covariances represented by a static and a dynamic ensemble. Here, the use of the hybrid covariance is first extensively tested with a quasi-geostrophic model and with different analysis schemes, namely the Ensemble Kalman Filter (EnKF) and the Ensemble Square Root Filter (ESRF). The hybrid covariance ESRF (ESRF-OI) is more accurate and more stable than the hybrid covariance EnKF (EnKF-OI), but the overall conclusions are similar regardless of the analysis scheme used. The benefits of using the hybrid covariance are large compared to both the static and the dynamic methods with a small dynamic ensemble. The benefits over the dynamic methods become negligible, but remain, for large dynamic ensembles. The optimal value of the hybrid blending coefficient appears to decrease exponentially with the size of the dynamic ensemble. Finally, we consider a realistic application with the assimilation of altimetry data in a hybrid coordinate ocean model (HYCOM) for the Gulf of Mexico, during the shedding of Eddy Yankee (2006). A 10-member EnKF-OI is compared to a 10-member EnKF and a static method called the Ensemble Optimal Interpolation (EnOI). While 10 members seem insufficient for running the EnKF, the 10-member EnKF-OI reduces the forecast error compared to the EnOI, and improves the positions of the fronts.

Shrinkage estimation for the difference between a control and treatment mean

Estimation for the difference between a control and treatment mean in the one-way model when it is suspected but uncertain that the two mean values are equal is studied. A preliminary-test (pre-test) estimator and a shrinkage estimator after pre-test are proposed. Both the optimal level of significance for the pre-test estimator and optimal value of shrinkage coefficient for the pre-test shrinkage estimator are obtained on the basis of a regret function. The pre-test estimator performs better than the pre-test shrinkage estimator over a small region around the origin; however, the pre-test shrinkage estimator performs better than the pre-test estimator outside the dominance region, and the dominance region of the pre-test shrinkage estimator is larger than that of the pre-test estimator. Therefore, if the performance outside the dominance region and the size of dominance region are taken into account for comparison, then the pre-test shrinkage estimator is preferable to the pre-test estimator.

Automated Energy/Performance Macromodeling of Embedded Software

This paper presents an automatic methodology to perform characterization-based high-level software macromodeling. Macromodeling-based estimation can be used to speed up simulation-based software-performance/energy estimation. High-level software macromodels, which are significantly faster to evaluate than detailed models of the target hardware platform, can be used instead of the latter during simulation, resulting in orders-of-magnitude simulation speedup. However, in order to realize this potential, significant challenges need to be overcome in both the generation and use of macromodels-including how to identify the parameters to be used in the macromodel, how to define the template function to which the macromodel is fitted, etc. The authors' methodology attempts to address the aforementioned issues. Given a subprogram to be macromodeled for execution time and/or energy consumption, the proposed methodology automates the steps of parameter identification, data collection through detailed simulation, macromodel template selection, and fitting. The authors propose a novel technique to identify potential macromodel parameters and perform data collection, which draws from the concept of data-structure serialization used in distributed programming. They utilize symbolic-regression techniques to concurrently filter out irrelevant macromodel parameters, construct a macromodel function, and derive the optimal coefficient values to minimize fitting error. Experiments with several realistic benchmarks suggest that the proposed methodology improves estimation accuracy and enables wide applicability of macromodeling to complex embedded software, while realizing its potential for estimation speedup

On the direct osmotic concentration of liquid foods: Part II. Development of a generalized model

The performance of a pilot scale, direct osmotic (membrane) concentration unit was modeled in physical terms. Based on the fundamental equation for cross-flow mass transfer diffusion through membranes and an adequate set of experimental measurements, a generalized mathematical model for direct osmotic concentrators was successfully developed. The required number of independent equations was more than three times the number of the unknown parameters (constants) of the proposed model, in order to allow for modern non-linear problem solvers to converge to a satisfactory solution. A Non-Linear Regression software package was used to determine optimal values for coefficients and exponents appearing in the proposed model. The validity of the emerging physical model was properly verified. The defined model provided an insight on the relative importance of several experimental parameters and membrane compaction in controlling direct osmotic flux values. The proposed model and the described modeling approach could be used to develop physically meaningful models for other membrane processes.

Longitudinally Vibrating Elastic Rods with Locally and Non-Locally Reacting Viscous Dampers

Eigencharacteristics of a longitudinally vibrating elastic rod with locally and non-locally reacting damping are analyzed. The rod is considered as a continuous system and complex eigenfrequencies are determined as solution of a characteristic equation. The variation of the damping ratios with respect to damper locations and damping coefficients for the first four eigenfrequencies are obtained. It is shown that at any mode of locally or non-locally damped elastic rod, the variation of damping ratio with damper location is linearly proportional to absolute value of the mode shape of undamped system. It is seen that the increasing damping coefficient does not always increase the damping ratio and there are optimal values for the damping ratio. Optimal values for external damping coefficients of viscous dampers and locations of the dampers are presented.

Competitiveness analysis of agricultural enterprises in Slovakia

Competitiveness can be analysed at various levels of the economy: at the product level, the enterprise level, the sector level, or the level of the entire economy. Several measures exist for each of these levels. This paper focuses on those used for the analysis of enterprises, particularly agricultural enterprises farming in Slovakia. Our research has been done on a selected sample of agricultural enterprises farming in Slovakia. Using “Recourse Cost Ratio” (RCR coefficient) has allowed investigating the differences in competitiveness between co-operatives and business companies, between the enterprises farming in better and worse soil and natural conditions as well as among various size groups of 111 agricultural enterprises. The research has proved that the optimal values of RCR coefficient revealed, that the common feature of all the competitive enterprises was their type of production oriented on solely plant production, possibly plant and meat production (there was no case of competitive enterprise with solely meat production). As for the different legal forms, we found out that more competitive were business companies than co-operatives. Considering different soil and natural conditions, there were better results observed in the group of enterprises farming in better soil and natural conditions.

704 粘性絞りを有する空気バネの特性

In this study we make clear the characteristics of an air suspension with a viscous damping restriction and a reservoir tank. In low frequency region, the damping caused by viscousity of restrictotion relatively large. In high frequency region, restrictor chokes due to the compressibility of air and only the main cylinder acts as an air suspension. In order to reducing resonance amplitude and variance of amplitude, it is necessary to increase the volume of the reservoir tank. In these case, we can choose the optimal value of flow coefficient of viscous restriction to minimize resonance amplitude or variance of amplitude.

낙동강 유역에서의 확정론적 및 추계학적 수질해석

하천에서의 수질변동을 예측하기 위해 FOEA(First-Order Error-Analysis)와 Monte Carlo 모의를 적용한 추계학적 모형을 개발하였다. 영향메트릭스(Influential matrix)를 이용한 민감도 분석을 실시하여 주요 반응계수를 결정하였고, BFGS(Broyden-Fletcher-Goldfarb-Shanno) 최적화 기법을 사용하여 주요 반응계수 값을 산정하였다. 본 모형을 확정론적 수질해석과 동일한 실제 하도구간에 적용하여 추계학적 수질해석을 실시하였고, 그 결과는 확정론적 해석결과와 잘 일치하였다. 유량과 수질, 반응계수 등에 포함된 불확실도가 하류단의 불확실도에 끼치는 영향을 산정하기 위해 상류단과 지류의 유량 및 수질에 대한 불확실도, 그리고 반응계수의 불확실도에 대한 분석과정이 모형에 포함되었다. 모의수행 결과로부터 각 변수들이 가지고 있는 불확실도가 총 불확실도에 끼치는 영향에 대한 기여도를 산정 할 수 있었다. A stochastic model using FOEA(First-Order Error-Analysis) and Monte Carlo Method is developed to predict water quality variation in a river. A sensitivity analysis using influential matrix is performed to determine the significant reaction coefficients. Also the BFGS (Broyden-Fletcher-Goldfarb-Shanno) optimization method is applied to estimate the optimal values of the major reaction coefficients. The developed stochastic model is applied to the real study reach and the results are agreed well with those of deterministic analysis. The process for analyzing the uncertainties of the discharge, water quality and reaction coefficients of headwater and tributaries is included in the model to estimate the influence on the water quality variation at downstream. The extents of contribution of the uncertainties influencing on the total uncertainty can be evaluated from the results of the model.