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， i=c，f，p (1) The methods of data collection for formula (1) are described in table 1.
Methods for estimating energy consumption and GHG emission reduction.
Methods of data collection for formula (1) Para-meter Methods of data collection M1.5 Investigating the ethanol production cost in pilot plants applying 1.5th G technology, M1.5=C1.5+BTS1.5‒Gi M2 Investigating and referring to the production cost of lingocellulosic ethanol, M2=C2+BTS2 BTS2 Investigating the cost of feedstock collection, transport and storage during the process of lingocellulosic ethanol production from corn and wheat stalks.
So benefits are gained in terms of CO2 emissions reduction [30].
Calculations are made to estimate carbon emission reduction as follows.

The results of our tests were first compared with the data in literature.
Thus we can state that the studied heat No. 278 719 shows a creep resistance fully comparable with literary data.
The differences between the results of PC and PF technologies are not obvious and therefore we will assess them as the only set of data.
[3] Hald, J.: ECCC data sheet.
[4] ECCC Recommendation 2001: Creep data validation and assessment procedures, UK, 2001

This is in agreement with XRD data on the presence of both Cu2+ and monovalent Cu+ ions in structure.
Temperature-programmed reaction CO In Fig. 5a the TPR-CO profiles with TCD and MS data obtained from the CZP-700 sample after TPO pre-treatment is shown.
According to MS data, CO2 evaluation occurred in a narrow temperature range of 100–170 oC with maximum at 122oC (Fig. 5b, m/z 44).
XRD data indicated formation of copper-zirconium phosphates such as CuZr4P6O24, Cu1.25Zr1.75P3O11.75, and CuZr2P3O12.
Agrawal, Synthesis and X-ray data of M(TiCr)P3O12, Cu(I)Ti2P3O12 and Cu(I)1+2xZr2-xCu(II)xP3O12-x, J.

The measured vibration data needs to be processed by means of suitable and smart algorithms to obtain the requested monitoring output.
In this case the measured data do not include enough information to distinguish between all possible causes of that measured effect.
Such a structure is always used for compressing data, e.g. wavelet transformation of images or Fourier transformation of sounds.
These data are filtered by a 100 Hz analog low-pass filter.
Very often the deviations of measurement data r is not expressed directly by the change of the measured time history signals, instead an intermediate step is introduced to extract characteristic features of the system such as modal data, FRFs, etc.

Despite the growing body of research on the use of glass fibre reinforced polymers (GFRP) composites in repairing and retrofitting the important structures such as oil and gas pipelines, the lack of comprehensive data on the long-term degradation mechanism for these materials is still impeding their widespread use in open-air structures repairs particularly in tropical climate locations such as Malaysia.
The standard deviation is preceded by a plus-minus symbol (±) indicating the data variability around the average value of the entire samples.
The maximum reduction of the tensile strength of GFRP composite was 18% under effect of seasonal condition (winter) in Switzerland however, this reduction occurred after 8.5 years of exposure.
Furthermore, the tensile strength reduction of GFRP composite after 3.5 years of exposure to urban environment in Lisbon, Portugal was 14%.
On the other hand, significant loss of modulus of elasticity was only noticed for the GFRPs exposed to the natural aging urban environment in Lisbon, Portugal with 33% of Young’s Modulus reduction for E-glass/ polyester GFRP pultruded profile and 24% reduction for E-glass /vinylester GFRP pultruded profile.

Overall Maintenance Time reduction by optimizing the distance of Service center in manufacturing unit through Single Facility Location Planning Manish Vishwakarma, V.K.Khare Department of Mechanical Engineering, Maulana Azad National Institute of Technology Bhopal M.P (INDIA) email : manish_v11@rediffmail.com Keywords : New Single facility location, Maintenance time reduction, Distance Optimization.
• Squared Euclidean distance d(X, pi ) = (x − ai )2 +(y − bi )2 • Euclidean distance d(X, pi ) = √(x − ai )2 +(y − bi )2 Rectilinear Facility Location Problem – We use the following notation: X= (x, y) location of the new facility P= (ai , bi) location of existing machines, i=1,2,3 ………..m Wi "weight" associated with maintenance hours and distance between Existing facility & machine i=1,2,3…….m In a rectilinear model, the distances are measured by the sum of the absolute difference in their coordinates, that is, SINGLE –FACILITY MINISUM LOCATION PROBLEM The minisum location problem is formulated as follows: Since above Equation is written in such a way that terms involving x are separate from terms involving y, the optimum values of x and y can be obtained independently. [13] LIST OF CRITICAL MACHINE AND DATA COLLECTION All data is been collected from SCR block (block no-4) BHEL, Bhopal.
The data is been collected is 1 year record of maintenance.
DATA FOR CALCULATIONS Machine no.
· (59.5, 52.5), (59.5, 70), (77,70) (77,52.5) As observed from past data an average maintenance personals make 2 trips per hour between maintenance department (existing facility center) and machines.

Generally, the RGO films are obtained from Graphene Oxide (GO) films which are then treated using thermal reduction or photo reduction process.
Level of reduction by provided irradiation time was examined using SEM/EDS measurement.
At the beginning, attempts to reduce oxygen groups were carried out by chemical reduction using a chemical reducing reagents such as hydrazine, and thermal reduction[16].
The color change effect has also been observed in several studies on GO photo reduction [9,10].
So, the EDS data support the optical characteristics that in the UV oven spraying technique the film deposition and photoreduction taken place simultaneously.

Currently, domestic and foreign scholars have conducted a lot of researches on green and low-carbon evaluation system, and evaluation methods mainly include input-output, analytic hierarchy process (AHP), fuzzy comprehensive evaluation, data envelopment analysis (DEA), and principal component analysis (PCA) etc.[5, 6].
(2) Evaluation basis and standards: primary data of evaluation indexes mainly comes from China Transport Statistical Yearbook and Collection of National Transport Statistical Data; statistical data of transportation and ports of provinces or cities; major enterprise monitoring and typical survey data etc.
Data of evaluation index system mainly comes from Collection of Transport Statistical Data, Guangzhou Statistical Yearbook by Guangzhou Statistical Bureau, Guangzhou Transport Development White Paper by Guangzhou Municipal Commission of Transport, Guangzhou Port Shipping Development Report by Guangzhou Port Authority, and statistical data of Guangzhou Port Group; and data of port energy consumption statistical monitoring and typical surveys etc.
Establish specialized energy-saving and emission reduction management department, and specialized management staffs are equipped; energy saving and emission reduction goals responsibility evaluation and appraisal system is built, and evaluation results are linked with energy saving and emission reduction rewards and punishment; build an energy-saving and emission reduction technological innovation mechanism to reward achievements such as invention and creation, technical transformation, technical innovation and innovative application etc. including energy saving and emission reduction.
Peng, China port “12th Five Year Plan" Energy Saving and Emission Reduction Work Plan.

In this paper, firstly, a tidal flow and pollutant transport numerical model based on Delft 3D-FLOW was established and verified by measured data to simulate and analyze phosphate distribution in Caofeidian sea area.
Based on the model calibration from measured data, the horizontal viscosity coefficient of 10m2/s and the Manning coefficient range of 0.013~0.016, according to the bed sediment particle size distribution, are used in this numerical model.
The verification of tidal flow model is carried through by three times measured data, including neap tide in spring season (2008.5.13~2008.5.15), neap tide in summer season (2008.7.11~2008.7.13) and spring tide in summer season (2008.7.16~2008.7.18) at tide station of Caofeidian and Jingtang Port for tidal level verification and at stations #1~ #6 for tidal current verification.
Fig.3 shows that simulated flow velocity and direction match that of measured data well in velocity magnitude and phase at a representative observation station #2.
The phosphate allowed discharge amount, present discharge amount, needed reduction amount and reduction rate for eight river outlets are shown in Table 1.

This work is focused on the reduction of the aerodynamic resistance of a microbus.
The computed results can give a reference for study of the aerodynamic resistance reduction on a microbus for energy saving.
Introduction The present investigation is directed at energy conservation through an effective reduction in aerodynamic resistance of a typical microbus configuration.
Recognizing that 50-70% of the microbus’s power (at 70-80 km/h speed) is consumed in overcoming aerodynamic resistance, compared to around 20-30% for rolling friction and 10-15% lost in the transmission system; a simple analysis of this data set suggests that even 1% reduction in the aerodynamic drag can amount to a significant saving in the fuel cost [1].
This is most important for drag reduction research of microbus.