scholarly journals Flow Properties Analysis and Identification of a Fly Ash-Waste Rock Mixed Backfilling Slurry

Minerals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 576
Author(s):  
Hanbo Wei ◽  
Bolin Xiao ◽  
Qian Gao
Keyword(s):  
Fly Ash ◽  
Principal Component ◽  
Flow Property ◽  
Binder Content ◽  
Waste Rock ◽  
Analysis Method ◽  
Flow Properties ◽  
Slurry Flow ◽  
Bleeding Rate ◽  
Nonhomogeneous Flow

The use of waste rock as an aggregate in mining backfill is environmentally friendly and cost-saving. The backfill slurry flow property varies with the change in aggregate, binder content, solid concentration, and additives. The slurry flow in a pipeline is governed by its properties, which makes it crucial to study the flow properties and their effects. One example is a fly ash-waste rock mixed slurry in Jinchuan Nickel, China. Tests on the slump, slump flow, mortar consistency, layering degree, and bleeding rate are performed to reveal the effects of the slurry concentration, binder content, and fly ash addition on the flow properties. Those relations are analyzed, and two new indices are derived (F1 and F2) using the principal component analysis method. Finally, the application results show that F1 > 0 indicates a nonhomogeneous flow; F1 < 0 and F2 > 0 indicates a high-density slurry flow; F1 < 0 and F2 < 0 indicates a paste slurry flow.

PENELITIAN DAN PENGEMBANGAN SENSOR AROMATIK SEBAGAI ALAT DETEKSI ALKOHOL PADA PARFUM DAN WEWANGIAN UNTUK AUTENTIKASI PRODUK PARFUM HALAL

2017 ◽  
Vol 18 (2) ◽  
pp. 302-322
Author(s):  
Fajar Hardoyono
Keyword(s):  
Sensor Array ◽  
Principal Component ◽  
Metal Oxide Semiconductor ◽  
Oxide Semiconductor ◽  
Response Patterns ◽  
Data Recording ◽  
Analysis Method ◽  
Sample Group ◽  
Array Pattern ◽  
Group Data

Abstract: The development of aromatic sensor array instrument for the detection of alcohol in perfume. The research was conducted by developing the sensor array using 8 sensors made of metal oxide semiconductor. The sensor types used in this study consisted of TGS 813, TGS 822, TGS 2600, TGS 826, TGS 2611, TGS 2620, TGS 2612 and TGS 2602. Response patterns of 8 sensors formed a sensor array pattern used to detect the aroma of 2 groups of samples perfume made from the essential oil of ginger. The first sample group is pure ginger atsiri oil without mixed alcohol. The second sample group was made from the ginger atsiri oil mixed with alcohol with a level of 0.02 M. The results of the data recording show that the developed instrument is able to dissect the first sample group with the second sample group. Data analysis using principal component analysis method (PCA shows that the instrument is able to distinguish the contaminated alcohol perfume group 0.2 M with the alcohol-free perfume group with 100% accuracy. Keywords: Sensor Aroma, Perfume.

scholarly journals Modeling, comparison and evaluation of one-DOF six-bar bioinspired jumping leg mechanisms

2021 ◽  
Vol 13 (2) ◽  
pp. 168781402199295
Author(s):  
Ziqiang Zhang ◽  
Qi Yang ◽  
Xingkun Liu ◽  
Chuanzhong Zhang ◽  
Jinnong Liao
Keyword(s):  
Center Of Mass ◽  
Principal Component ◽  
Analysis Method ◽  
Index Distribution ◽  
Inertial Moment ◽  
Structure Index ◽  
Mean And Variance ◽  
Research Objects ◽  
Leg Mechanisms ◽  
Selection Of

One degree-of-freedom (DOF) jumping leg has the advantages of simple control and high stiffness, and it has been widely used in bioinspired jumping robots. Compared with four-bar jumping leg, six-bar jumping leg mechanism can make the robot achieve more abundant motion rules. However, the differences among different configurations have not been analyzed, and the choice of configurations lacks basis. In this study, five Watt-type six-bar jumping leg mechanisms were selected as research objects according to the different selection of equivalent tibia, femur and trunk link, and a method for determining the dimension of the jumping leg was proposed based on the movement law of jumping leg of locust in take-off phase. On this basis, kinematics indices (sensitivity of take-off direction angle and trunk attitude angle), dynamics indices (velocity loss, acceleration fluctuation, and mean and variance of total inertial moment) and structure index (distribution of center of mass) were established, and the differences of different configurations were compared and analyzed in detail. Finally, according to the principal component analysis method, the optimal selection method for different configurations was proposed. This study provides a reference for the design of one DOF bioinspired mechanism.

Evidential Study of Relationship between Flexible Drift of Fuel Nozzle Performance and Hot-End Failure of X Engine

2014 ◽  
Vol 651-653 ◽  
pp. 724-728
Author(s):  
Yong Gang Xu ◽  
Qiang Wang
Keyword(s):  
Abrupt Change ◽  
Initial Period ◽  
Flow Property ◽  
Analysis Method ◽  
Comparison Analysis ◽  
Fuel Nozzle ◽  
Converging Flow ◽  
The Relationship ◽  
Relative Scarcity ◽  
Engine Start

By means of the fountain-convergence analysis method of FRRU (Flow Resistance-Rigidity Uniformity) index defined by the author, evidential comparison analysis study has been made to the relationship between flexible drift of flow performance of WTD (Weight Type Distributor) valves of fuel nozzles of X engine and hot-end failures of X engine. The results show that during the initial period of engine start, because of the relative scarcity of air in the combustor, a convergence characteristic, due to its converging flow property ofmultiple to one, can lead to such hot-end failures as turbine blade fusion break which is characterized byabrupt change, while a fountain characteristic, due to its diffusing flow property ofone tomultiple, cannot result in any hot-end failures.

Study on the Effect Factors of Non-Perormance Loan Ratio of Chinese Commerical Banks

2011 ◽  
Vol 50-51 ◽  
pp. 728-732
Author(s):  
Ping Li ◽  
Ming Ying Zhuo ◽  
Li Chao Feng ◽  
Rui Zhang
Keyword(s):  
Principal Component Analysis ◽  
Commercial Banks ◽  
Principal Component ◽  
Component Analysis ◽  
Analysis Method ◽  
Analysis Model ◽  
Principal Component Analysis Model ◽  
Effect Factors ◽  
Financial Indicator ◽  
Commerical Banks

Non-performance loan ratio is one of the important assessment criteria of the security of credit assets. It is also an important financial indicator to evaluate the general strength of commercial banks. Using principal component analysis method and statistical software SPSS16.0 and based on the non-performance loan ratio and relative data of some commercial banks in China in 2007, this paper provided a principal component analysis model for the non-performance loan ratio of China’s commercial banks. The factors that affect the non-performance loan ratio were refined in this paper. Finally, the characteristics of effect factors of each bank were analyzed and compared in detail.

scholarly journals Application of Principal Component Analysis Method to Determine Prediction Indexes Sensibility Sequence

2011 ◽  
Vol 26 ◽  
pp. 1346-1351
Author(s):  
Yang Guo-liang ◽  
Wang Can-zhao ◽  
Wu Shi-yue ◽  
Jia Li-qing ◽  
Zhang Sheng-zhu
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Analysis Method ◽  
Principal Component Analysis Method

scholarly journals Input data preprocessing method for exchange rate forecasting via neural network

2014 ◽  
Vol 11 (4) ◽  
pp. 597-608
Author(s):  
Dragan Antic ◽  
Miroslav Milovanovic ◽  
Stanisa Peric ◽  
Sasa Nikolic ◽  
Marko Milojkovic
Keyword(s):  
Neural Network ◽  
Input Data ◽  
Principal Component ◽  
Economic Systems ◽  
Data Sets ◽  
Foreign Exchange Rates ◽  
Analysis Method ◽  
Feed Forward Neural Network ◽  
Parameters Selection ◽  
Neural Network Input

The aim of this paper is to present a method for neural network input parameters selection and preprocessing. The purpose of this network is to forecast foreign exchange rates using artificial intelligence. Two data sets are formed for two different economic systems. Each system is represented by six categories with 70 economic parameters which are used in the analysis. Reduction of these parameters within each category was performed by using the principal component analysis method. Component interdependencies are established and relations between them are formed. Newly formed relations were used to create input vectors of a neural network. The multilayer feed forward neural network is formed and trained using batch training. Finally, simulation results are presented and it is concluded that input data preparation method is an effective way for preprocessing neural network data.

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