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Heat exchanger fault simulation is conducted to generate performance degradation data, through which the proposed methods are validated.
Faults Symptom of fault Diagnostic strategy Leakage Sudden reduction of mass flow(or) monitor changes ofγ2 orγ4 Blocking Decrease of heat transfer coefficient(or) monitor changes of γ1 or γ3 Fouling Significant change of effective flow area (or) monitor changes of γ2 or γ4 Fig. 3 The process of the methodology Headings Methodology Procedures of the Methodology.
Simulation Results and Discussion In this section, the effectiveness of the proposed fault diagnosis method is thoroughly studied through simulated data from the cross-flow heat exchanger in case the flight altitude is 2 km.

Firstly, plans are generalisable to reasonable deviations from demonstration data.
Per-frame recognition and estimation, however, does not rely on a consistent sequence of data.
In developing the method, a 3D camera is used to acquire a stream of data.
Each frame of data is registered as a 3D point cloud.
Each cloud (P) of points () contains important Cartesian data (, and RGB colour data (, where.

To search a way for researching, the Weibull distributions of critical current and n-value in turns of a model double-pancake (DP), made of coated conductor, are numerically calculated based on anisotropic empirical models obtained by fitting the experimental data in the temperature of 77 K.
By fitting the experiment data shown as Fig. 1 and Fig. 2, the calculation models of critical current and n-value are obtained which are shown in (1) and (2)
The reason is that generation heat in inner turns can not be transferred to liquid nitrogen in time and then it induces the local temperature rise resulting in the reduction of local critical current and the n-value.

Requirements for the analysis sequence and the accuracy of the measurement data are the result of a compromise between the consumer and the supplier of the analysis.
Requirements put forward to the sequence of the analysis and the accuracy of the measuring data are the result of a compromise between the consumer and the supplier of the analysis.
Saes, From time-based competition (TBC) to quick response manufacturing (QRM): the evolution of research aimed at lead time reduction, The International Journal of Advanced Manufacturing Technology. 64 (5) (2013) 1177–1191

The study concentrates on three tasks: analytical investigation; test of compressive strength of bricks; comparatively studies using two PMCAD models with emphasis on ratio of resistance to effect, and data of inter-story displacement angle.
To contribute to reduction of losses and the improvement of safety, the new Code for Seismic Design of Buildings requires higher seismic fortification intensity and more strict seismic construction measures[2].
This paper only presents data of the first, second and fifth story considering the biggest effects of torsion generally behaves on first story, the representative of the second story and particularity of the fifth story.

The results of flow analysis for an axial compressor with smooth casing are validated in comparison with experimental data for the pressure ratio and adiabatic efficiency.
Validation of Numerical Results The three-dimensional RANS results have been validated in comparison with experimental data [9] by the previous work [12].
In comparison with the smooth casing, the circumferential casing grooves contribute to a significant reduction of the near-stall mass flow except for case 1, and thus to the enhancement in the stall margin.

This includes a comparison of obtained data against normative requirements dealing with shrinkage, and a subsequent a comparison of samples, since the observations are done under the exact same boundary conditions Introduction The aim of this paper is to take a closer look at shrinkage of industrial concrete floors and to explain and name the several types of volumetric changes.
High water ratio leads to a reduction of volume because of a subsequent evaporation of water from the concrete mixture.
Data acquired from the measurement can be stored and subsequently processed graphically.

The data comes from 2012 China statistical year-book, China’s environmental statistical year-book, China energy statistical year-book and so on.
For some data that can't get directly, we obtain it through calculating the related data.
This article uses SPSS17.0 to dispose data.
Therefore using the method of factor analysis for dimensionality reduction, twiddling and naming factors prepares for subsequent analysis.
But it should be pointed out that negative exists in the grading index of data.

Results and Discussion Analysis of X-ray Diffraction Data.
Nitrogen adsorption/desorption isotherms data (a), and pore size distribution data (b) of activated carbon electrode.
Porosity data for activated carbon electrode.
Analysis of Self-Discharge Data.
The data in Fig. 5(a), plotted as the voltage decay against the sqrt(t) is shown Fig. 5(b).

I.Index Selection and Data Sources A.Index selection In this paper, the industrial emissions intensity index is not doing research.
According to the domestic the research results and the scholars paper data collection and analysis, and finally picked industrial energy consumption, with industrial energy intensity, industrial carbon dioxide emissions,industrial carbon emissions intensity and industrial carbon productivity have different in index analyzing.
B.dData sources 1985 ~ 2007 national industrial energy consumption, industrial added value, can source total consumption data are from the 1985 ~ 2010 China statistical yearbook,the new China 60 years statistics compiled 1949-2007, "China's energy statistics yearbook, after correction finally get papers than required raw data, each year value added of industry in 2005 by calculating the price.
(t check value and F check value are through the show the sexual inspection), through with real data contrast prediction results effective, prediction "fruit such as shown in table 4.
Although Chinese industry has to low carbonization direction, but because of the energy consumption is larger, and according to the results of data processing in nearly 9 years of industrial waste gas emission intensity is still rising stage,2008 just alleviates somewhat, industrial low carbon economic transition pressure is still large, further work is required.