scholarly journals Optimization design and experimental study of vortex pump based on orthogonal test

2019 ◽  
Vol 103 (1) ◽  
pp. 003685041988188
Author(s):  
Hui Quan ◽  
Ying Guo ◽  
Rennian Li ◽  
Qingmiao Su ◽  
Yi Chai
Keyword(s):  
Orthogonal Test ◽  
Superior Performance ◽  
Orthogonal Experimental Design ◽  
Test Scheme ◽  
Blade Angle ◽  
Vortex Pump ◽  
Combination Scheme ◽  
Design Value ◽  
Folding Point ◽  
The Impact

To study the effects of the performance of different types of impeller on the vortex pump, orthogonal test design, which is carried out by combining experimental test and numerical calculation, is adopted to optimize the type of design structure for the impeller in vortex pump. To find out the folding blade angle, the position of the folding point in the whole blade, and whether to wedge folding blade, an orthogonal test scheme with three factors and two levels is designed. A numerical simulation test is conducted for each scheme by analyzing the performance curve of orthogonal test plan to find the optimal performance of the program and analyzing the test data of each scheme to obtain the primary and secondary orders of the impact performance in the angle of folding blades of the vortex pump, the position of folding point of blades, and the wedge shape of blades. The results show that the optical blade type combination is the blade angle R30F60, the folding point is at 2/3 of the whole blade, and the blade does not adopt radial wedge. The optimal combination scheme is 36% higher than the design value at the rated flow head, the efficiency is 18.75% higher than the design value, the high-efficiency zone of the vortex pump is wider, and the performance meets the design requirements. Through orthogonal experimental design, the design cycle of vortex pump can be shortened effectively, the design level of vortex pump can be improved, and the hydraulic model with superior performance can be obtained.

scholarly journals Radiomics side experiments and DAFIT approach in identifying pulmonary hypertension using Cardiac MRI derived radiomics based machine learning models

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sarv Priya ◽  
Tanya Aggarwal ◽  
Caitlin Ward ◽  
Girish Bathla ◽  
Mathews Jacob ◽  
...  
Keyword(s):  
Machine Learning ◽  
Pulmonary Hypertension ◽  
Feature Selection ◽  
Subgroup Analysis ◽  
Cardiac Mri ◽  
Intraclass Correlation ◽  
Poor Performance ◽  
Superior Performance ◽  
Feature Filtering ◽  
The Impact

AbstractSide experiments are performed on radiomics models to improve their reproducibility. We measure the impact of myocardial masks, radiomic side experiments and data augmentation for information transfer (DAFIT) approach to differentiate patients with and without pulmonary hypertension (PH) using cardiac MRI (CMRI) derived radiomics. Feature extraction was performed from the left ventricle (LV) and right ventricle (RV) myocardial masks using CMRI in 82 patients (42 PH and 40 controls). Various side study experiments were evaluated: Original data without and with intraclass correlation (ICC) feature-filtering and DAFIT approach (without and with ICC feature-filtering). Multiple machine learning and feature selection strategies were evaluated. Primary analysis included all PH patients with subgroup analysis including PH patients with preserved LVEF (≥ 50%). For both primary and subgroup analysis, DAFIT approach without feature-filtering was the highest performer (AUC 0.957–0.958). ICC approaches showed poor performance compared to DAFIT approach. The performance of combined LV and RV masks was superior to individual masks alone. There was variation in top performing models across all approaches (AUC 0.862–0.958). DAFIT approach with features from combined LV and RV masks provide superior performance with poor performance of feature filtering approaches. Model performance varies based upon the feature selection and model combination.

scholarly journals Braided composite stent for peripheral vascular applications

2020 ◽  
Vol 9 (1) ◽  
pp. 1137-1146
Author(s):  
Qingli Zheng ◽  
Pengfei Dong ◽  
Zhiqiang Li ◽  
Ying Lv ◽  
Meiwen An ◽  
...  
Keyword(s):  
Computational Models ◽  
Surface Coverage ◽  
Mechanical Performance ◽  
Wire Diameter ◽  
Orthogonal Experimental Design ◽  
Braided Composite ◽  
Nitinol Wire ◽  
Radial Strength ◽  
Braiding Angle ◽  
The Impact

AbstractBraided composite stent (BCS), woven with nitinol wires and polyethylene terephthalate (PET) strips, provides a hybrid design of stent. The mechanical performance of this novel stent has not been fully investigated yet. In this work, the influence of five main design factors (number of nitinol wires, braiding angle, diameter of nitinol wire, thickness and stiffness of the PET strip) on the surface coverage, radial strength, and flexibility of the BCS were systematically studied using computational models. The orthogonal experimental design was adopted to quantitatively analyze the sensitivity of multiple factors using the minimal number of study cases. Results have shown that the nitinol wire diameter and the braiding angle are two most important factors determining the mechanical performance of the BCS. A larger nitinol wire diameter led to a larger radial strength and less flexibility of the BCS. A larger braiding angle could provide a larger radial strength and better flexibility. In addition, the impact of the braiding angle decreased when the stent underwent a large deformation. At the same time, the impact of the PET strips increased due to the interaction with nitinol wires. Moreover, the number of PET strips played an important role in the surface coverage. This study could help understand the mechanical performance of BCS stent and provides guidance on the optimal design of the stent targeting less complications.

The Clogging Behavior of a Vortex Pump: An Experimental Study on the Influence of Impeller Designs

2017 ◽  
Author(s):  
Angela Gerlach ◽  
Dorian Perlitz ◽  
Flemming Lykholt-Ustrup ◽  
Christian Brix Jacobsen ◽  
Paul Uwe Thamsen
Keyword(s):  
Experimental Study ◽  
Power Consumption ◽  
Clear Water ◽  
Blade Angle ◽  
Flow Rates ◽  
Blade Number ◽  
Outlet Angle ◽  
Vortex Pump ◽  
Efficiency Losses ◽  
Angle Blade

This paper analyzes the clogging behavior of a vortex pump with different impeller designs. The influence of blade outlet angle, blade number, and impeller diameter were tested. Non-woven textiles in different concentrations served as the clogging material. The results suggest that a smaller outlet blade angle, a higher blade number, and a larger impeller diameter allow pumping more textiles. Impellers that were capable of pumping more textiles, however, were less efficient. Overall, pumping textiles causes efficiency losses. However, this could not be only related to increased power consumption. Flow rates under clogging operation were close to the flow rates under clear water operation irrespective of the amount of clogging material and the impellers design. Further, in all tests clogging material accumulated at the suction mouth in the casing.

scholarly journals Optimization of proppant parameters for CBM extraction using hydrofracturing by orthogonal experimental process

2020 ◽  
Vol 17 (3) ◽  
pp. 493-505 ◽  
Author(s):  
Haoze Li ◽  
Bingxiang Huang ◽  
Qingying Cheng ◽  
Xinglong Zhao
Keyword(s):  
Particle Size ◽  
Orthogonal Test ◽  
Coal Mass ◽  
Tensile Fracture ◽  
Experimental Conditions ◽  
Embedded Value ◽  
Fracture Area ◽  
Creep Time ◽  
Experimental Process ◽  
The Impact

Abstract Proppant placement concentration, particle size and creep time are important factors that affect the embedment of proppant into coal. Based on multistage creep, an orthogonal test is conducted, and an optimal proppant scheme for different closure stresses obtained. The results show that with increased proppant placement concentration, the number of coal fractures increases and the elastic modulus of the fracture area decreases. As the proppant particle size decreases, the plasticity of fracture-proppant assemblies increases gradually. The yield limit is highest when the particle size is 20/40 mesh. During the proppant embedding process, localization or uneven distribution of proppant results in tensile stress parallel to the fracture surface, which induces tensile fracture in the coal. In the fracture-proppant assembly areas, proppant fractures are severe and yield lines appear. As proppant concentration increases, more energy is accumulated during the proppant compaction stage, resulting in energy release producing craters and crevasses. The energy released also causes increased stress in the proppant-coal contact area and fracturing to the coal mass. The longer the creep time, the weaker the impact and the smaller is fluctuation. Moreover, we find that the orthogonal test can effectively analyze the importance of each parameter. Proppant placement concentration was found to have the highest influence on the process of proppant embedding into coal, followed by particle size and then time. Under experimental conditions, the lowest proppant-embedded value in coal samples was observed with proppant placement concentration of 2 kg m−2 and particle size of 20/40 mesh.

Effect of test parameters on the stability of fabric shape retention indexes increase recovery testing

2021 ◽  
pp. 004051752110242
Author(s):  
Qianhui Tang ◽  
Lei Wang ◽  
Weidong Gao ◽  
Ruru Pan
Keyword(s):  
Standard Deviation ◽  
Sample Size ◽  
Orthogonal Test ◽  
Test Scheme ◽  
Optimal Test ◽  
Pressure Time ◽  
Test Parameters ◽  
Shape Retention ◽  
The Stability ◽  
Retention Indexes

Fabric shape retention is a crucial property that impacts the durability and usability of fabric and which needs a convenient and accurate evaluation method. In the previous research, the automated crease recovery testing method was used to obtain fabric crease recovery information and evaluate the property of shape retention. Based on the previous research, an orthogonal test method was adopted to investigate the effect of different test parameters on the stability of shape retention detection in this paper. First, three factors, that of sample size, pressure, and pressure time, and three different levels of each factor were determined by the L9(34) orthogonal test table. Next, the fabric shape retention indexes were detected by nine different test schemes, and the comprehensive score of shape retention index standard deviation was obtained as the evaluation criterion of the orthogonal test results. Finally, the optimal test scheme was determined by visual analysis and variance analysis. The results show that the sample size has a certain effect on the stability of shape retention indexes, while the pressure time and the pressure have no significant influence. The optimal test scheme is that the sample size is 30 cm × 30 cm, the pressure time is 60 s, and the pressure is 40 N. The test result measured by the optimal test parameters reveals excellent stability when the vertex angle standard deviation is 2.0°, the height standard deviation is 0.06 cm, and the shape retention area standard deviation is 0.16 cm2. This paper provides an experimental basis for improving the accuracy of fabric shape retention evaluation method.

Predictive Modeling and Optimization of Cutting Forces Through RSM and Taguchi Techniques in the Turning of ASTM B574 (Hastelloy C-22)

2018 ◽  
pp. 398-417
Author(s):  
İsmail Kırbaş ◽  
Musa Peker ◽  
Gültekin Basmacı ◽  
Mustafa Ay
Keyword(s):  
Feed Rate ◽  
Cutting Forces ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Rake Angle ◽  
Orthogonal Experimental Design ◽  
Depth Of Cut ◽  
Effective Parameters ◽  
Factors Affecting ◽  
The Impact

In this chapter, the impact of cutting parameters (depth of cut, cutting speed, feed, flow, rake angle, lead angle) on cutting forces in the turning process with regard to ASTM B574 (Hastelloy C-22) material has been investigated. Variance analysis has been applied in order to determine the factors affecting the cutting forces. The optimization of the parameters affecting the surface roughness has been obtained using response surface methodology (RSM) based on the Taguchi orthogonal experimental design. The accuracy of the developed models required for the estimation of the force values (Fx, Fy, Fz) is quite successful. In this study, where the R2 value has been used as the criterion/measure, accuracy values of 93.35%, 95.03%, and 95.09% have been achieved for Fx, Fy, and Fz, respectively. As a result of the ANOVA analysis, the most effective parameters for Fx at a 95% confidence interval are depth of cut, feed rate, flow, and rake angle. The most effective parameter for Fy is depth of cut, while the most effective parameters for Fz are depth of cut, feed rate, and flow, respectively.

Dynamic Programming Approach for Online Freeway Flow Propagation Adjustment

2002 ◽  
Vol 1802 (1) ◽  
pp. 263-270 ◽  
Author(s):  
Xuesong Zhou ◽  
Hani S. Mahmassani
Keyword(s):  
Dynamic Programming ◽  
Control Method ◽  
Dynamic Programming Algorithm ◽  
Superior Performance ◽  
Programming Algorithm ◽  
Programming Approach ◽  
Base Case ◽  
Solution Quality ◽  
Flow Propagation ◽  
The Impact

An optimization framework for online flow propagation adjustment in a freeway context was proposed. Instead of performing local adjustment for individual links separately, the proposed framework considers the interconnectivity of links in a traffic network. In particular, dynamic behavior in the mesoscopic simulation is approximated by the finite-difference method at a macroscopic level. The proposed model seeks to minimize the deviation between simulated density and anticipated density. By taking advantage of the serial structure of a freeway, an efficient dynamic programming algorithm has been developed and tested. The experiment results compared with analytic results as the base case showed the superior performance of dynamic programming methods over the classical proportion control method. The effect of varying update intervals was also examined. The simulation results suggest that a greedy method considering the impact of inconsistency propagation achieves the best trade-off in terms of computation effort and solution quality.

scholarly journals Leveraging Logistics Competence in New Product Sourcing: The Role of Strategic Intent and Impact on Performance

Logistics ◽  
2020 ◽  
Vol 4 (4) ◽  
pp. 24
Author(s):  
Myung Kyo Kim ◽  
Ram Narasimhan ◽  
Tobias Schoenherr
Keyword(s):  
Superior Performance ◽  
Strategic Intent ◽  
South Korean ◽  
Selection Decisions ◽  
Path Modelling ◽  
Construct Measurement ◽  
And Performance ◽  
The Impact ◽  
Moderating Role

The purpose of the present research is to examine and compare product and logistics competencies in supplier selection decisions, which can serve as a crucial building block for competitive differentiation, in the context of the unique private label (PL) supply chain. This study also hypothesizes about the impact of product and logistics competence on the retailer’s financial performance. Lastly, the moderating role of the product type in the proposed research model is explored. Partial least squares path modelling is used to analyze the dataset drawn from major South Korean retailers, due to the exploratory nature of the research and the use of both reflective and formative construct measurement items. Overall, the results of this study demonstrate that relationships between the desire for a particular strategic intent and performance are more complex than previous studies have implied. The findings of this research offer possible explanations on an important but understudied aspect of PL success: why not all PLs (even of the same retailer) are thriving even in a rapidly growing PL industry. We further elicit strategic recommendations for retailers in selecting PL suppliers and for PL manufacturers to differentiate themselves and achieve a superior performance.

Impact of CEO Overconfidence on Firm Performance: An Evidence from S&P BSE 200

2019 ◽  
Vol 23 (3) ◽  
pp. 234-243
Author(s):  
Hardeep Singh Mundi ◽  
Parmjit Kaur
Keyword(s):  
Firm Performance ◽  
Superior Performance ◽  
Annual Reports ◽  
Tobin’S Q ◽  
Return On Assets ◽  
Tobin's Q ◽  
Full Sample ◽  
Forecasting Error ◽  
Research Article ◽  
The Impact

The current research article considers the impact of CEO overconfidence on firm performance for S&P BSE 200 firms. The CEO overconfidence is measured using revealed beliefs (holder 67, long holder and net buyer), press coverage and forecasting error proxies of CEO overconfidence. CEO Overconfidence measures are constructed as per the methodology of Malmendier and Tate (2005b, 2008). Firm performance is measured using Tobin’s Q and return on assets. The data are collected from the Centre for Monitoring Indian Economy (CMIE) prowess, S&P Capital IQ and the annual reports of the sample firms over a period of 15 years starting from 1 April 2000 to 31 March 2015. Regression results for each of the proxy of CEO overconfidence with the proxies of firm performance indicate that large Indian firms with overconfident CEOs enjoy a higher return on assets and Tobin’s Q as compared to the full sample firms. Overconfident CEOs consider themselves better-than-average, are involved with over-investment and show superior performance for the firm. The overconfident CEOs increase firm performance by following optimal levels of investments in the firm.

scholarly journals A Robust Diffusion Minimum Kernel Risk-Sensitive Loss Algorithm over Multitask Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2339 ◽  
Author(s):  
Xinyu Li ◽  
Qing Shi ◽  
Shuangyi Xiao ◽  
Shukai Duan ◽  
Feng Chen
Keyword(s):  
Sensor Networks ◽  
Gaussian Noise ◽  
Impulsive Noise ◽  
Estimation Algorithm ◽  
Distributed Estimation ◽  
Superior Performance ◽  
Mean Square ◽  
Unknown Parameters ◽  
Risk Sensitive ◽  
The Impact

Distributed estimation over sensor networks has attracted much attention due to its various applications. The mean-square error (MSE) criterion is one of the most popular cost functions used in distributed estimation, which achieves its optimality only under Gaussian noise. However, impulsive noise also widely exists in real-world sensor networks. Thus, the distributed estimation algorithm based on the minimum kernel risk-sensitive loss (MKRSL) criterion is proposed in this paper to deal with non-Gaussian noise, particularly for impulsive noise. Furthermore, multiple tasks estimation problems in sensor networks are considered. Differing from a conventional single-task, the unknown parameters (tasks) can be different for different nodes in the multitask problem. Another important issue we focus on is the impact of the task similarity among nodes on multitask estimation performance. Besides, the performance of mean and mean square are analyzed theoretically. Simulation results verify a superior performance of the proposed algorithm compared with other related algorithms.

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