Sort by:
Publication Type:
Open access:
Publication Date:
Periodicals:
Search results
Online since: June 2004
Authors: N.S. Saks, Sei Hyung Ryu
Here
we describe an approach to analyze the Hall data in order to obtain a correct value for the mobility
in the surface accumulation layer of the BC device.
This complicates analysis of the Hall data.
Hall data: Measurements of Hall mobility µHall in the same BC and SC devices as Fig. 2 are shown in Fig. 3.
In Fig. 3, analysis of the Hall data in the BC device for Vgate ≤ Vth is simple because all electrons are carried only in the buried channel and all have nearly the same mobility.
Fig. 4 The differential Hall mobility µdiff in BC and SC devices calculated from the data in Fig. 3 (see text).
This complicates analysis of the Hall data.
Hall data: Measurements of Hall mobility µHall in the same BC and SC devices as Fig. 2 are shown in Fig. 3.
In Fig. 3, analysis of the Hall data in the BC device for Vgate ≤ Vth is simple because all electrons are carried only in the buried channel and all have nearly the same mobility.
Fig. 4 The differential Hall mobility µdiff in BC and SC devices calculated from the data in Fig. 3 (see text).
Online since: December 2014
Authors: Sherkhon M. Sultonov, Yuri A. Sekretarev, Sergey V. Mitrofanov
This paper proposes a reduction in the deficit of electricity in the energy system in Tajikistan, by optimizing the operating conditions of hydroelectric power plants of the power system.
However, after the launch of the next unit and the corresponding reduction of the load of each of the operating units, the incremental rate in each of them, therefore, in the entire station is significantly reduced.
Incremental rate obtained for Nurek, Baipazinskaya, Sangtuda-1, Sangtuda-2, Golovnaya and Kayrakum hydroelectric power plants are the main source data using the method of Lagrange for optimization of the energy system of Tajikistan.
However, after the launch of the next unit and the corresponding reduction of the load of each of the operating units, the incremental rate in each of them, therefore, in the entire station is significantly reduced.
Incremental rate obtained for Nurek, Baipazinskaya, Sangtuda-1, Sangtuda-2, Golovnaya and Kayrakum hydroelectric power plants are the main source data using the method of Lagrange for optimization of the energy system of Tajikistan.
Online since: August 2013
Authors: Ameen H. El-Sinawi, Omar A. Awad, Abdulaziz H. El-Sinawi
El-Sinawi3,c
1,2American University of Sharjah, 26666, UAE-Sharjah
3King Faisal University, 31982, Saudi Arabia-Ahssa
aaelsinawi@aus.edu, bb00028381@aus.edu, caelsinawi@kfu.edu.sa
Keywords: FEA, Modes of vibration, RF-MEMS impact force, Modal reduction, RF-MEMS switch, Squeeze film
Abstract.
RF-MEMS switch data Geometry of the RF-MEMS switch under consideration is identical to the one reported in [1] and all analysis is done in reference to it.
The reduction is based on Hankel norm values where modes with the highest norms are retained and the remaining modes are truncated.
Table 2: Calculated Model Parameters Permittivity of Air () Net area of the membrane () Experimental switch voltage () V=35 [V], Pull-in Voltage= 29 [V] 0.5 0.71 9 [N/m] 2256 [N/m] 14.86 [kHz] Simulation Results For the switch under consideration, our model predicted that the pull-in voltage values is 29 Volts , this is in excellent agreement with the experimental data reported for the same switch.
Simulation is carried out at 35 V, and the results are in excellent agreement with the experimental data published in [1].
RF-MEMS switch data Geometry of the RF-MEMS switch under consideration is identical to the one reported in [1] and all analysis is done in reference to it.
The reduction is based on Hankel norm values where modes with the highest norms are retained and the remaining modes are truncated.
Table 2: Calculated Model Parameters Permittivity of Air () Net area of the membrane () Experimental switch voltage () V=35 [V], Pull-in Voltage= 29 [V] 0.5 0.71 9 [N/m] 2256 [N/m] 14.86 [kHz] Simulation Results For the switch under consideration, our model predicted that the pull-in voltage values is 29 Volts , this is in excellent agreement with the experimental data reported for the same switch.
Simulation is carried out at 35 V, and the results are in excellent agreement with the experimental data published in [1].
Online since: August 2013
Authors: Ismael Rodríguez Maestre, Pascual Álvarez Gómez, F. Javier González Gallero, J. Daniel Mena Baladés
Policies for energy saving and carbon dioxide emission reduction have enouraged the use of efficient technologies in building thermal conditioning, like geothermal source heat pumps [1].
Outer weather conditions have been set by using synthetic hourly weather data and considering all of the heat transfer phenomena involved.
Introduction In 2008 the European Union put in place the Climate and Energy Package to combat climate change, whose targets are known as ‘20-20-20’: 20% reduction in greenhouse gas emissions, raising the share of EU energy consumption produced from renewable sources to 20% and 20% improvement in the EU’s energy efficiency [3].
Outer weather conditions have been set by using synthetic hourly weather data and considering all of the heat transfer phenomena involved.
Introduction In 2008 the European Union put in place the Climate and Energy Package to combat climate change, whose targets are known as ‘20-20-20’: 20% reduction in greenhouse gas emissions, raising the share of EU energy consumption produced from renewable sources to 20% and 20% improvement in the EU’s energy efficiency [3].
Online since: March 2010
Authors: Yi Min Xia, Xi Wen Zhou, Jing Xue, De Zhi Luo
The analysis showed that under the same conditions, the stress distribution of the
improved structure was more symmetrical and the maximum stress and maximum deformation also
had a remarkable reduction.
And the results could provide basic data for the structure design of cutter-head.
The studies show that the improvements of cutters arrangement are effective, and that the maximum stress and displacement of the cutter-head under the same conditions have a remarkable reduction, which will help improve the performance of cutter-head.
And the results could provide basic data for the structure design of cutter-head.
The studies show that the improvements of cutters arrangement are effective, and that the maximum stress and displacement of the cutter-head under the same conditions have a remarkable reduction, which will help improve the performance of cutter-head.
Online since: October 2015
Authors: Mohd Khairul Azuan Muhammad, Farah Alwani Wan Chik, Noram I. Ramli, S.N.C. Deraman, Majid Taksiah A.
Data Collection
Field surveys conducted after the thunderstorm occurred.
Table 1 shows the data of roof failure for northern area of peninsular Malaysia from 2012 until 2015.
Table 1: Summary data recorded during field survey.
Conclusion Based on field survey data, 73 % of roof failure for non–engineered building are due to connections failure.
The impact of structural damage in Jamaica due to hurricane Gilbert and the prospects for disaster reduction.
Table 1 shows the data of roof failure for northern area of peninsular Malaysia from 2012 until 2015.
Table 1: Summary data recorded during field survey.
Conclusion Based on field survey data, 73 % of roof failure for non–engineered building are due to connections failure.
The impact of structural damage in Jamaica due to hurricane Gilbert and the prospects for disaster reduction.
Online since: March 2012
Authors: Zhen Fu Chen, Rui Zhang, Yuan Chu Gan, Qiu Wang Tao
In order to analysis the FRFs, universal files were imported to ME’scope VES visualization modal analysis software, basic modal parameters were carried out by curve fitting function built in ME’ scope, data of the first 4 modes were extracted.
COMAC relates to the stiffness reduction at each degree of freedom.
This abnormal trend may relate to the noisy data.
The noisy data were not filtered out and it could affect the prediction of damage region.
Due to the employment of central difference operator, data at marginal points (1 and 15) could not be obtained.
COMAC relates to the stiffness reduction at each degree of freedom.
This abnormal trend may relate to the noisy data.
The noisy data were not filtered out and it could affect the prediction of damage region.
Due to the employment of central difference operator, data at marginal points (1 and 15) could not be obtained.
Online since: July 2015
Authors: Ari Sandhyavitri
A Projected of Cash in-out Flow of SPAM Project capacity of 500 l/second
Source: Data Analyses, 2014
Risk analysis quantifies the effects of identified risks on economic parameters.
Investment expenditures by construction plants (Without debt) Source: Data Analyses, 2014 The highest investment cost was to construct pipe transmission lines (Rp. 200.7 billion), and water treatment plant facilities (Rp. 100 billion).
Sensitivity of O&M and the construction investment parameters versus project Source: Data Analyses, 2014.
Source: Data Analyses, 2014 It was identified that project NPV was in the rage of -Rp. 6.68 billion up to Rp. 18.01 billion.
Source: Data Analyses, 2014 The use of the risk analyses within the regional water supply projects in Riau has demonstrated that both financial and technical performances of a project should be put into consideration.
Investment expenditures by construction plants (Without debt) Source: Data Analyses, 2014 The highest investment cost was to construct pipe transmission lines (Rp. 200.7 billion), and water treatment plant facilities (Rp. 100 billion).
Sensitivity of O&M and the construction investment parameters versus project Source: Data Analyses, 2014.
Source: Data Analyses, 2014 It was identified that project NPV was in the rage of -Rp. 6.68 billion up to Rp. 18.01 billion.
Source: Data Analyses, 2014 The use of the risk analyses within the regional water supply projects in Riau has demonstrated that both financial and technical performances of a project should be put into consideration.
Online since: May 2006
Authors: A.J. Pontes, António Sergio Pouzada
In this study, the as-moulded shrinkage and pressure data are obtained experimentally
and compared with numerical simulations.
Also, it was observed that the pressure predictions are qualitatively in good agreement with the experimental data.
During the processing the pressure evolution was acquired using a data acquisition system.
Some data are also compared with predictions where the effect of pressure on viscosity was neglected (standard data).
The results are also reported in figure 5 (full lines) and, as expected, become much closer to the experimental data.
Also, it was observed that the pressure predictions are qualitatively in good agreement with the experimental data.
During the processing the pressure evolution was acquired using a data acquisition system.
Some data are also compared with predictions where the effect of pressure on viscosity was neglected (standard data).
The results are also reported in figure 5 (full lines) and, as expected, become much closer to the experimental data.
Online since: September 2013
Authors: Jian Sheng Zhang, Yong Hua Zhang, Peng Fei Song
In view of the grid has a large number of harmonics, serious interference power quality, but the existing harmonic detection has many disadvantages, this paper uses genetic algorithm to optimize the BP neural network (GA-BP),Combined with fanaticism, independent component technique in the separation technology, achieve rapid separation and accurate fitting for harmonic reduction.
The method to solve the problem of slow convergence speed of BP neural network and easier to fall into local optimal solution; Separation, independent component analysis in the signal could not accurate reduction the source signal.
According to the observed data vector, fanaticism separation determine a transformation to restore the original signal or source[6].The fundamental as follows: Suppose a signal is composed of several independent signals,the aliasing signal can be expressed as: (5) Where;is aliasing matrix;.
C.Implementation Steps of GA-BP (1) Initialized the signal samples, and determined the fundamental frequency and the BP network topology structure; (2) Encode the initial value of the BP network, and data preprocessing; (3) With the BP neural network training error to do fitness values,do selection,crossover and mutation,calculate the fitness value; (4) Determine whether it meet the end conditions or not.YES,jump to step(5);NO,jump to step(3); (5) Obtain the optimal weights and thresholds; (6) Calculation error, and update the weights and thresholds; (7) Judgment whether it meet the end conditions or not.YES,jump to step(5);NO,jump to step(3); (8) The simulation forecast, get results.
The method to solve the problem of slow convergence speed of BP neural network and easier to fall into local optimal solution; Separation, independent component analysis in the signal could not accurate reduction the source signal.
According to the observed data vector, fanaticism separation determine a transformation to restore the original signal or source[6].The fundamental as follows: Suppose a signal is composed of several independent signals,the aliasing signal can be expressed as: (5) Where;is aliasing matrix;.
C.Implementation Steps of GA-BP (1) Initialized the signal samples, and determined the fundamental frequency and the BP network topology structure; (2) Encode the initial value of the BP network, and data preprocessing; (3) With the BP neural network training error to do fitness values,do selection,crossover and mutation,calculate the fitness value; (4) Determine whether it meet the end conditions or not.YES,jump to step(5);NO,jump to step(3); (5) Obtain the optimal weights and thresholds; (6) Calculation error, and update the weights and thresholds; (7) Judgment whether it meet the end conditions or not.YES,jump to step(5);NO,jump to step(3); (8) The simulation forecast, get results.