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Wyszukujesz frazę "Parappagoudar, M. B." wg kryterium: Autor

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    Wyświetlanie 1-4 z 4
    Tytuł:
    Modeling and Analysis of Mechanical Properties in Structural Steel-DOE Approach
    Autorzy:
    Bhatt, A.
    Parappagoudar, M. B.
    Powiązania:
    https://bibliotekanauki.pl/articles/947580.pdf
    Data publikacji:
    2015
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    structural steel
    alloying elements
    linear model
    stal konstrukcyjna
    dodatki stopowe
    model liniowy
    Opis:
    The present work focuses on the modeling and analysis of mechanical properties of structural steel. The effect of major alloying elements namely carbon, manganese and silicon has been investigated on mechanical properties of structural steel. Design of experiments is used to develop linear models for the responses namely Yield strength, Ultimate tensile strength and Elongation. The experiments have been conducted as per the full factorial design where all process variables are set at two levels. The main effect plots showed that the alloying elements Manganese and Silicon have positive contribution on Ultimate tensile strength and Yield strength. However, Carbon and Manganese showed more contribution as compared to Silicon. All three alloying elements are found to have negative contribution towards the response- Elongation. The present work is found to be useful to control the mechanical properties of structural steel by varying the major alloying elements. Minitab software has been used for statistical analysis. The linear regression models have been tested for the statistical adequacy by utilizing ANOVA and statistical significance test. Further, the prediction capability of the developed models is tested with the help of test cases. It is found that all linear regression models are found to be statistically adequate with good prediction capability. The work is useful to foundrymen to choose alloying elements composition to get desirable mechanical properties.
    Źródło:
    Archives of Foundry Engineering; 2015, 15, 4; 5-12
    1897-3310
    2299-2944
    Pojawia się w:
    Archives of Foundry Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Prediction of Secondary Dendrite Arm Spacing in Squeeze Casting Using Fuzzy Logic Based Approaches
    Autorzy:
    Patel, M. G. C.
    Krishna, P.
    Parappagoudar, M. B.
    Powiązania:
    https://bibliotekanauki.pl/articles/380567.pdf
    Data publikacji:
    2015
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    squeeze casting process
    secondary dendrite arm spacing
    fuzzy logic
    adaptive network based fuzzy
    interface system
    prasowanie stopu
    odległość ramion dendrytów
    logika rozmyta
    system interfejsowy
    Opis:
    The quality of the squeeze castings is significantly affected by secondary dendrite arm spacing, which is influenced by squeeze cast input parameters. The relationships of secondary dendrite arm spacing with the input parameters, namely time delay, pressure duration, squeeze pressure, pouring and die temperatures are complex in nature. The present research work focuses on the development of input-output relationships using fuzzy logic approach. In fuzzy logic approach, squeeze cast process variables are expressed as a function of input parameters and secondary dendrite arm spacing is expressed as an output parameter. It is important to note that two fuzzy logic based approaches have been developed for the said problem. The first approach deals with the manually constructed mamdani based fuzzy system and the second approach deals with automatic evolution of the Takagi and Sugeno’s fuzzy system. It is important to note that the performance of the developed models is tested for both linear and non-linear type membership functions. In addition the developed models were compared with the ten test cases which are different from those of training data. The developed fuzzy systems eliminates the need of a number of trials in selection of most influential squeeze cast process parameters. This will reduce time and cost of trial experimentations. The results showed that, all the developed models can be effectively used for making prediction. Further, the present research work will help foundrymen to select parameters in squeeze casting to obtain the desired quality casting without much of time and resource consuming.
    Źródło:
    Archives of Foundry Engineering; 2015, 15, 1; 51-68
    1897-3310
    2299-2944
    Pojawia się w:
    Archives of Foundry Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Multi-Objective Optimization of Squeeze Casting Process using Genetic Algorithm and Particle Swarm Optimization
    Autorzy:
    Patel, G. C. M.
    Krishna, P.
    Vundavilli, P. R.
    Parappagoudar, M. B.
    Powiązania:
    https://bibliotekanauki.pl/articles/379601.pdf
    Data publikacji:
    2016
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    squeeze casting process
    multi-objective optimization
    genetic algorithm
    squeeze casting
    prasowanie stopu
    optymalizacja wielokryterialna
    algorytm genetyczny
    Opis:
    The near net shaped manufacturing ability of squeeze casting process requiresto set the process variable combinations at their optimal levels to obtain both aesthetic appearance and internal soundness of the cast parts. The aesthetic and internal soundness of cast parts deal with surface roughness and tensile strength those can readily put the part in service without the requirement of costly secondary manufacturing processes (like polishing, shot blasting, plating, hear treatment etc.). It is difficult to determine the levels of the process variable (that is, pressure duration, squeeze pressure, pouring temperature and die temperature) combinations for extreme values of the responses (that is, surface roughness, yield strength and ultimate tensile strength) due to conflicting requirements. In the present manuscript, three population based search and optimization methods, namely genetic algorithm (GA), particle swarm optimization (PSO) and multi-objective particle swarm optimization based on crowding distance (MOPSO-CD) methods have been used to optimize multiple outputs simultaneously. Further, validation test has been conducted for the optimal casting conditions suggested by GA, PSO and MOPSO-CD. The results showed that PSO outperformed GA with regard to computation time.
    Źródło:
    Archives of Foundry Engineering; 2016, 16, 3; 172-186
    1897-3310
    2299-2944
    Pojawia się w:
    Archives of Foundry Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Modeling and Optimization of Phenol Formaldehyde Resin Sand Mould System
    Autorzy:
    Chate, G. R.
    Patel, M. G. C.
    Parappagoudar, M. B.
    Deshpande, A. S.
    Powiązania:
    https://bibliotekanauki.pl/articles/381857.pdf
    Data publikacji:
    2017
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    mould hardness
    phenol-formaldehyde resin
    permeability
    desirability function approach
    design of experiments
    masy formierskie
    żywica fenolowo-formaldehydowa
    przepuszczalność
    twardość
    optymalizacja
    Opis:
    Chemical bonded resin sand mould system has high dimensional accuracy, surface finish and sand mould properties compared to green sand mould system. The mould cavity prepared under chemical bonded sand mould system must produce sufficient permeability and hardness to withstand sand drop while pouring molten metal through ladle. The demand for improved values of permeability and mould hardness depends on systematic study and analysis of influencing variables namely grain fineness number, setting time, percent of resin and hardener. Try-error experiment methods and analysis were considered impractical in actual foundry practice due to the associated cost. Experimental matrices of central composite design allow conducting minimum experiments that provide complete insight of the process. Statistical significance of influencing variables and their interaction were determined to control the process. Analysis of variance (ANOVA) test was conducted to validate the model statistically. Mathematical equation was derived separately for mould hardness and permeability, which are expressed as a non-linear function of input variables based on the collected experimental input-output data. The developed model prediction accuracy for practical usefulness was tested with 10 random experimental conditions. The decision variables for higher mould hardness and permeability were determined using desirability function approach. The prediction results were found to be consistent with experimental values.
    Źródło:
    Archives of Foundry Engineering; 2017, 17, 2; 162-170
    1897-3310
    2299-2944
    Pojawia się w:
    Archives of Foundry Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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