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Online since: August 2021
Authors: Ramilya F. Tazieva, Anna N. Akhmetova, Svetlana S. Vinogradova
The more specific the data regarding the bullet operation conditions, the narrower the range of possible values, while no data leads to the necessity of including the widest possible range of inputs into calculations.
Based on the data obtained, the risk value was assessed.
Simulation Data Based on the probabilistic model, we developed a software environment intended for calculating the efficiency of the horizontal settler sacrificial protection and for calculating the risk of non-achieving the required protection level (Fig. 1).
Based on the data obtained, we constructed the sacrificial protection efficiency histogram shown in Fig. 3.
Rules for Determining and Methods for Calculating Statistical Characteristics from Sample Data.
Based on the data obtained, the risk value was assessed.
Simulation Data Based on the probabilistic model, we developed a software environment intended for calculating the efficiency of the horizontal settler sacrificial protection and for calculating the risk of non-achieving the required protection level (Fig. 1).
Based on the data obtained, we constructed the sacrificial protection efficiency histogram shown in Fig. 3.
Rules for Determining and Methods for Calculating Statistical Characteristics from Sample Data.
Online since: October 2012
Authors: Hui Yuan, Feng Shan Wang, Hou Qing Lu
Bayesian theory was applied into the damage problems of military engineering, adapted to the uncertain, incomplete damage problem, but whose flaws and hidden information was difficult to show in the sample data [1].
Set the damage sample data of component units as , in which described the physical damage value of component unit, and then could be expressed as a set form, namely .
Set as the threshold of the damage measurement about any component unit of military engineering, and carry on the knowledge reduction about the component units in accordance with the compare from the damage sample to threshold, namely: (6) Here, denoted the improved entropy value of component unit, called "rough entropy", which derived the classification of component units from the damage sample data.
Thus, carry on the metamorphic power weight of component unit under the damage sample data, namely: , (7) Where, showed the weight parameters under this particular damage environment, whose set was erected as , namely .
From the model, simulation, evaluation point, the damage simulation and effect assessment system was designed for military engineering, which provided the sample data for the functional damage reason on the system level
Set the damage sample data of component units as , in which described the physical damage value of component unit, and then could be expressed as a set form, namely .
Set as the threshold of the damage measurement about any component unit of military engineering, and carry on the knowledge reduction about the component units in accordance with the compare from the damage sample to threshold, namely: (6) Here, denoted the improved entropy value of component unit, called "rough entropy", which derived the classification of component units from the damage sample data.
Thus, carry on the metamorphic power weight of component unit under the damage sample data, namely: , (7) Where, showed the weight parameters under this particular damage environment, whose set was erected as , namely .
From the model, simulation, evaluation point, the damage simulation and effect assessment system was designed for military engineering, which provided the sample data for the functional damage reason on the system level
Online since: December 2013
Authors: A.S. Sekhar, N. Harish Chandra
Hong et.al [4] used Lipchitz exponents for the detection of singularities in beam modal data.
Hoelder Exponent (or) Lipschitz Constant The Hoelder exponent (HE) is a mathematical tool that can provide degree of change in distributed data.
Daubachies wavelets were found extremely compatible with data.
Slope of Lipchitz equation v/s crack depth Conclusions Different damage cases are simulated and modal analysis data is processed by wavelet transforms.
The peaks corresponding to edges appeared in 3D-plots are clearly visible in case of strain mode data than displacement mode data.
Hoelder Exponent (or) Lipschitz Constant The Hoelder exponent (HE) is a mathematical tool that can provide degree of change in distributed data.
Daubachies wavelets were found extremely compatible with data.
Slope of Lipchitz equation v/s crack depth Conclusions Different damage cases are simulated and modal analysis data is processed by wavelet transforms.
The peaks corresponding to edges appeared in 3D-plots are clearly visible in case of strain mode data than displacement mode data.
Online since: February 2019
Authors: Jeong Whan Yoon, Ru Gang Chai, Yan Shan Lou
Introduction
Lightweight metals are increasingly utilized in automobile and aerospace industries to satisfy the requirement of weight reduction, improvement in fuel efficiency, and the omission decrease of greenhouse gas.
All of these six fracture criteria were calibrated firstly, and then both of 2D and 3D fracture loci were constructed and compared with the experimental fracture data.
Experimental data of AA2024-T351 Bao and Wierzbicki [7] performed a series of tests on AA2024-T351, which covered a wide range of stress triaxiality from -0.3 to 0.9.
Comparison and Evaluation The accuracy of each fracture criterion discussed above is schematically assessed by comparing the constructed fracture loci to experimental data points as presented in Fig. 1.
The error between predicted EPSF and experimental data is calculated by using the least square method and compared in Table 2.
All of these six fracture criteria were calibrated firstly, and then both of 2D and 3D fracture loci were constructed and compared with the experimental fracture data.
Experimental data of AA2024-T351 Bao and Wierzbicki [7] performed a series of tests on AA2024-T351, which covered a wide range of stress triaxiality from -0.3 to 0.9.
Comparison and Evaluation The accuracy of each fracture criterion discussed above is schematically assessed by comparing the constructed fracture loci to experimental data points as presented in Fig. 1.
The error between predicted EPSF and experimental data is calculated by using the least square method and compared in Table 2.
Online since: February 2013
Authors: Jongh Wan Kwon, Soon Hyun Hwang, Balho H. Kim
At the same time, efforts to improve the efficiency of energy usage and the reduction of energy consumption will be carried out.
Power expansion planning model outline
3.2 Input data and basic premise
Information in 5th Power Expansion Planning was used for input data for analysis and 2015~2030 were target period to derive Power Expansion Planning.
Then, based on these data, energy supply cost was derived.
Detailed input data are as follows
- Review period : 2015~2030 (16years) - Discount Rate : 7.5% - Demand Data : Using the standard demand prospectivity of the 5th Power Expansion Planning (Demand after 2024 is estimated by applying 2.3% which is the average demand increasing rate) Data for each electric power source
Fuel
cost
(won/kWh)
O&M
cost
(won/kW)
Construction cost
(won/kW)
Unit
capacity
(MW)
avail-ability rate
(%)
LNG
64.4
-
784,000
700
-
Oil
88.1
-
1,254,000
800
-
Coal
23.0
-
1,134,000
1000
-
Nuke
3.3
-
2,042,000
1400
-
IGCC
33.8
44,708
2,905,539
300
-
Wind
0
35,038
2,223,546
100
34
Solar
0
13,504
6,979,401
50
25
Scenario for analysis were composed with disposal/maintenance of nuclear-power plants and the proportion of renewable energy in the total power generation based on 2015.
Then, based on these data, energy supply cost was derived.
Detailed input data are as follows
- Review period : 2015~2030 (16years) - Discount Rate : 7.5% - Demand Data : Using the standard demand prospectivity of the 5th Power Expansion Planning (Demand after 2024 is estimated by applying 2.3% which is the average demand increasing rate)