scholarly journals Mn-Mediated Alpha-Radical Addition of Carbonyls to Olefins: Systematic Study, Scope, and Electrocatalysis

2021 ◽  
Author(s):  
Sylvain CHARVET ◽  
Maurice MÉDEBIELLE ◽  
Julien VANTOUROUT
Keyword(s):  
Predictive Model ◽  
Carbonyl Compound ◽  
Systematic Study ◽  
Initial Study ◽  
Radical Addition ◽  
Carbonyl Groups ◽  
Model Based ◽  
The Creation ◽  
Coupling Partner

A systematic study of the manganese-mediated alpha-radical addition of carbonyl groups to olefins is presented. After an in-depth investigation of the parameters that govern the reaction, a first round of optimization allowed the development of a unified stoichiometric set of conditions which was subsequently assessed during the exploration of the scope. Due to observed limitations, the knowledge accumulated during the initial study was reengaged to quickly optimize promising substrates that were so far inaccessible under previously reported conditions. Altogether these results led to the creation of a predictive model based on the pKa of the carbonyl compound and both the substitution and geometry of the alkene coupling partner. Finally, a departure from the use of stoichiometric manganese was enabled through the development of a robust and practical electrocatalytic version of the reaction.

The Application of Local Mean Decomposition and Variable Predictive Model-Based Class Discriminate in Gear Fault Diagnosis

2014 ◽  
Vol 1014 ◽  
pp. 510-515 ◽  
Author(s):  
You Cai Xu ◽  
Xin Shi Li ◽  
Ran Tao ◽  
Shu Guo ◽  
Min Gou ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Predictive Model ◽  
Feature Vector ◽  
Local Mean Decomposition ◽  
Outer Race ◽  
Model Based ◽  
Gear Fault ◽  
Local Mean ◽  
Gear Fault Diagnosis ◽  
Non Stationary Signal

The time-domain energy message conveyed by vibration signals of different gear fault are different, so a method based on local mean decomposition (LMD) and variable predictive model-based class discriminate (VPMCD) is proposed to diagnose gear fault model. The vibration signal of gear which is the research object in this paper is decomposed into a series of product functions (PF) by LMD method. Then a further analysis is to select the PF components which contain main fault information of gear, the energy feature parameters of the selected PF components are used to form a fault feature vector. The variable predictive model-based class discriminate is a new multivariate classification approach for pattern recognition, through taking fully advantages of the fault feature vector. Finally, gear fault diagnosis is distinguished into normal state, inner race fault and outer race fault. The results show that LMD method can decompose a complex non-stationary signal into a number of PF components whose frequency is from high to low. And the method based on LMD and VPMCD has a high fault recognition function by analyzing the fault feature vector of PF.

scholarly journals ANALYTICAL METHODS FOR CALCULATING FAN AERODYNAMICS

2015 ◽  
Vol 55 (6) ◽  
pp. 373
Author(s):  
Jan Dostal ◽  
Jan Kuzel
Keyword(s):  
Mathematical Model ◽  
Analytical Methods ◽  
Preliminary Design ◽  
Computer Programme ◽  
Aerospace Research ◽  
Model Based ◽  
The Creation ◽  
The Mathematical Model ◽  
Measuring Unit

This paper presents results obtained between 2010 and 2014 in the field of fan aerodynamics at the Department of Composite Technology at the VZLÚ aerospace research and experimental institute in Prague – Letnany. The need for rapid and accurate methods for the preliminary design of blade machinery led to the creation of a mathematical model based on the basic laws of turbomachine aerodynamics. The mathematical model, the derivation of which is briefly described below, has been encoded in a computer programme, which enables the theoretical characteristics of a fan of the designed geometry to be determined rapidly. The validity of the mathematical model is assessed continuously by measuring model fans in the measuring unit, which was developed and manufactured specifically for this purpose. The paper also presents a comparison between measured characteristics and characteristics determined by the mathematical model as the basis for a discussion on possible causes of measured deviations and calculation deviations.

Energy-Efficient Operation of a Utility Plant via Predictive Model-Based Optimization Technology

2013 ◽  
Vol 53 (13) ◽  
pp. 5274-5283
Author(s):  
Bijan Sayyar-Rodsari ◽  
Alexander B. Smith ◽  
Apurva Samudra
Keyword(s):  
Predictive Model ◽  
Energy Efficient ◽  
Efficient Operation ◽  
Model Based ◽  
Utility Plant

scholarly journals Effects of the Instructional Model Based on Creative Problem-Solving Principles with Social Media to Promote the Creation of Educational Innovation for Pre-service Teachers

2021 ◽  
Vol 11 (3) ◽  
pp. 56
Author(s):  
Thapanee Seechaliao ◽  
Phamornpun Yurayat
Keyword(s):  
Social Media ◽  
Problem Solving ◽  
Statistical Significance ◽  
Educational Innovation ◽  
Instructional Model ◽  
Creative Problem Solving ◽  
Educational Innovations ◽  
Model Based ◽  
Creative Problem ◽  
The Creation

The main research purpose focused on the effects of conducting the instructional model based on the principles of creative problem solving with social media to promote the creation of educational innovation for pre-service teachers. The participants consisted of twelve pre-service teachers. Research instruments were 1) the instructional model based on the principles of creative problem solving with social media, 2) the test of knowledge and creation of educational innovation, 3) the creation of educational innovation’s evaluation form, and 4) the questionnaires’ conducting this instructional model. Collected data were analyzed with statistics and categorized into key issues based on literature. The results were presented through the form of Shapiro-Wilk, Wilcoxon signed-ranks test, arithmetic mean, standard deviation, and descriptive analysis. The research findings were presented as follows: 1) the effects of conducting the instructional model that was conducted sixteen weeks on the course 0537211 Innovation in Educational Technology and Communications in the first semester of 2020. The research hypothesizes were followed the established as follows; 1.1) the pre-service teachers had post-test scores’ the knowledge and creation of educational innovation higher than pre-test with statistical significance at the .01 level. 1.2) they had post-learning scores for creating educational innovations’ processes at the overall excellent level (M = 92.83, S.D. = 11.78), and their educational innovations were be post-learning at the overall good level (M = 48.33, S.D. = 7.45) 2) the opinions’ pre-service teachers toward conducting this instructional model that they have positive opinions to this conduct at the overall excellent level (M = 4.92, S.D. = 0.25).

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