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This paper presents the development of secondary controlled hydraulic pressure forming of sheet metal for both potential energy saving and electric motor power consumption reduction.
Proper regulation of the system parameters lead to optimization of energy recovery and drastic reduction of the electric motor power input to the system load.
Experimental results from data 1 and 2 shows that hydraulic accumulators aid the electric motor in power reduction during pressing/punching stroke of the ram.
The energy saving efficiency of the system is expressed as: , (22) The efficiency of the system from data 1 and 2 is 0.74 Where — energy consumption of the system with hydraulic accumulator circuit —Energy consumption of the system without hydraulic accumulator circuit.

The ESFQR [26, 27] and ZDD metrics [28] characterize the near-edge geometry from a measured thickness- and height-data arrays, respectively.
The measured data were presented as frontside or backside ZDD depending on the reference plane selected [31, 32].
In this study, LPDs caused by wafer handling (edge-gripping) were investigated by using the geometric data measured from the 300 mm Si wafers.
This study aims to verify the possibility of predicting wafer-handling caused point defects using the measured edge geometric data of Si wafers.
Based on these data, there was no correlation between the ESFQR and the defective condition found in both defective and non-defective groups (Fig. 7).

Statistical analysis carried out on the experimental data indicated that the effective moisture diffusivity and specific energy consumption were significantly influenced only by the IR source temperature, which had a positive linear effect on Deff and a negative linear effect on SEC.
From results in Table 1 it can also be noted that decreasing air velocity helps to increase seed temperature at the end of the process, resulting in a slight reduction of the equilibrium moisture content.
TIR (oC) vair (m/s) TS (oC) Xeq (d.b.) 45 0.4 26.7 ± 0.8 0.111 ± 0.002 65 0.4 36.6 ± 1.6 0.071 ± 0.004 85 0.4 48.5 ± 3,0 0.061± 0.012 45 1.2 24.5 ± 0.5 0.132 ± 0.007 65 1.2 35.6 ± 0.7 0.084 ± 0.001 85 1.2 45.0 ± 2.0 0.078 ± 0.008 Typical data of drying time versus moisture content at different air velocities with IR source temperature of 45 and 85oC are shown in Fig. 5(a) and 5(b), respectively.
At the higher IR temperatures, 65 oC (data not shown) and 85oC, the drying behavior was found to be independent on the air velocity.
It can be noted a reduction of about 34% in the energy consumption of the process with the increase of the air velocity from 0.4 to 1.2 m/s, for the drying at IR source temperature of 45°C.

Anthropometric data got form measurement and experiments.
Customers samples are chosen to measure anthropometric data, and these data are used to evaluate comfort index.
Anthropometric data supported product design is shown in Fig. 3.
Anthropometric Data Acquisition.
So designers should measure coustomers' anthropometric data and model a regression to find the origin data for its ultimate customers.

Through a review of reference data, it was confirmed that elevated temperatures significantly reduce concrete strength, potentially leading to structural failure.
The study demonstrates that using the Schmidt hammer, with proper calibration and error consideration, provides reliable data for determining the origin of the fire and for making informed decisions on structural repair or reinforcement. 1 Introduction Targeted attacks on infrastructure such as warehouses, industrial plants, energy facilities, and residential buildings are often accompanied by fires caused by direct hits from shells, missiles, or debris [1].
Interaction of high temperatures with building materials Material Temperature limit of change, [°C] Nature of exposure to high temperatures Concrete 300–600 Loss of strength, appearance of microcracks, delamination of the protective layer, dewatering of cement stone, expansion of reinforcement Reinforced concrete 300–600 Concrete-reinforcement bond degradation, reinforcement corrosion, load-bearing capacity decrease, cracking Ceramic brick 600–1000 Color change, cracks, loss of geometry, in the case of long-acting - a decrease in strength Silicate brick 300–400 Loss of strength, structure destruction, lime sintering Steel structures 400–600 Significant decrease in strength and modulus of elasticity, plastic deformations, threat of loss of stability Wood 200–300 Surface charring, burning, reduction of section, reduction of bearing capacity Foams and polymers 100–250 Deformation, melting, toxic smoke emission, complete combustion Drywall 100–150 Moisture evaporation, deformation, delamination
Reference data on changes in the structure and physico-chemical properties of concrete under temperature effects were analyzed.
The obtained material strength data reflect the degree of changes in the physical properties of the concrete.

This is the same kind of data transfer used in finite element codes supporting remeshing.
Data Transfer Theory.
The general requirements for a data transfer method are that it should 1.
Example of data transfer.
Data transfer for 3-D adaptive thermal-elasto-plastic finite element analysis in NUMIFORM'95. 1995.

Deformations were predicted for the plain weave unit cell in tension, compression, shear and bending, utilising their measured equivalents for individual yarns as input data.
On application of appropriate periodic boundary conditions, the method was shown to give good agreement with experimental data for a carbon/epoxy composite.
Broadly these aim to predict in-plane and/or through-thickness permeability as input data for macro-scale models of resin infusion during composites manufacture or water permeability for clothing fabrics.
Using the average values for width and height of warp, weft and binder yarns gives reasonably close agreement with experimental data.
In addition, TexGen has automated functions to discretise the model, assign material orientations and properties to elements, and export the model to external analysis software in several data formats.

At this step, the data regarding input/output material and energy flows of the S-PVC resin manufacturing process collected in 2010 are analyzed.
The resulting life cycle inventory data of the case study is presented in a consistent way to GaBi Education 4.4 background data as shown in Table 1.
This LCI data will be used in the stage of life cycle impact assessment (LCIA) to understand the water use associated with the PVC production case study.
Table 1 Life Cycle Inventory Data of 1 Kg of PVC Resin Order Inputs Quantity [Kg] Order Outputs Quantity [Kg] 1 NaCl 0.075613 1 S-PVC 1.0 2 Process Water (Demin) 0.352077 2 NaOH as 50%wt 0.056922 3 18% Hydrochloric acid *** 3 NaOH as 24%wt 0.010636 4 98% Sulfuric acid *** 4 Waste Water *** 5 Sodium Sulfite (Na2SO3) *** 5 Waste Sludge *** 6 Industrial Water 0.005934 6 Others *** 7 Steam 0.025801 7 8 Ethylene 0.304748 9 Oxygen 0.148705 10 Fuel Gas 0.006105 11 Others *** *** Proprietary data Impact Assessment and Interpretation.
Any reduction in the use of process water would effectively reflect in a smaller burden on local water resources caused by the S-PVC resin manufacturing process.

The EBSD data was acquired in the radius (R) plane, i.e. the plane containing the Z and rotation (θ) specimen directions (as shown in Fig. 1), using an FEI Sirion FEGSEM equipped with a HKL Nordlys CCD camera controlled by HKL Channel 5 acquisition software.
The EBSD acquisition data for all analysis specimens were collected with a step size of 2µm with the total area analysed being approximately 1 mm 2.
Subsequent data analysis was performed using HKL Channel 5 software. .
The major affect of the reduction in stored energy (i.e. misorientation) was only to proportionally slow the growth rate.
The current data set is insufficient to come to these same conclusions but the trend looks similar.

BIM is based on three-dimensional digital technology, which integrates all relevant information construction project engineering data model[3].
All of those studies the basic premise is the process for the civil construction of different participants ( such as architects , structural engineers , builders , etc. ) to provide a platform for mutual cooperation to facilitate timely information for the data to update or revise such as processing, enhanced design coordination and construction feasibility.
Lean production is a reduction of the enterprise in order to maximize the resources and reduce management and operational costs as the main target of production.
Overseas data show that the cost of the cause, and 80% of the product is formed in the product design stage, therefore, the cost of planning should go through the whole process of product development.
Sources of data through automated online cost estimates, timely and frequent assessment to generate an unlimited number of combinations of components to fully evaluate the cost impact , and cost trade-offs of different options to ensure maximum customer value . 5.