The Experts below are selected from a list of 306 Experts worldwide ranked by ideXlab platform
Luai M Alhems - One of the best experts on this subject based on the ideXlab platform.
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assessment of wind energy potential using wind energy conversion system
Journal of Cleaner Production, 2019Co-Authors: Muhammad Shoaib, I A Siddiqui, Shamim Khan, Shafiqur Rehman, Luai M AlhemsAbstract:Abstract Wind energy, as a renewable resource, is the most rapidly growing source that produces electrical energy using wind turbines. Such a wind energy conversion system is both economical and is environmental friendly. It requires understanding of wind conditions at the site under study. With this intent, wind characteristics of Jhampir (district Thatta Sindh, Pakistan) are investigated and wind energy potential is determined. The study is conducted using 10-min averaged wind speed data obtained from Alternate Energy Development Board of Pakistan for a period of three years (2007–2010). Monthly, seasonal, and yearly analysis is performed by fitting measured wind speed data to a Weibull distribution function. Weibull shape and scale parameters are determined numerically using Maximum Likelihood Method, Modified Maximum Likelihood Method, and Energy Pattern Factor Methods. The suitability of the fit is assessed using goodness-of-fit tests, such as, Root Mean Square Error, Coefficient of Determination (R2), and Chi-Square (χ2) tests. In all three data analysis periods, RMSE values varied between 10−2 and 10−4. Similarly, R2 values varied between 0.989 and 0.996 and χ2-test between 10−4 and 10−8. For entire data set, all the tests showed better performance of Maximum Likelihood and Modified Maximum Likelihood Methods compared to Energy Pattern Factor. In case of monthly analysis, Maximum Likelihood Method performed better compared to Modified Maximum Likelihood Method and Energy Pattern Factor according to root mean square error and χ2 tests results. Seasonal performance of all the methods is found to be similar with marginal superiority of MLM over other methods. A very good agreement is observed between standard deviation values for measured wind speed data distribution and fitted Weibull distribution using Maximum Likelihood Method estimator. Additionally, to understand the optimum directional efficiency, directional wind power densities are calculated. Finally, a wind turbine is used to the seasonal and yearly wind speed data to determine the actual wind energy potential of the site. Extracted wind energy values for four seasons are found to be 1691, 2851, 4572, and 916 kWh with an annual yield of 10054 kWh. Wind energy values obtained for different periods and directions suggest that Jhampir is a suitable site for developing the wind power plant.
Guenter Delling - One of the best experts on this subject based on the ideXlab platform.
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trabecular bone Pattern Factor a new parameter for simple quantification of bone microarchitecture
Bone, 1992Co-Authors: Michael Hahn, M Vogel, M Pompesiuskempa, Guenter DellingAbstract:Abstract The stability of trabecular bone depends not only on the amount of bone tissue, but also on the three-dimensional orientation and connectedness of trabeculae, which is summarized as trabecular microarchitecture. In previous studies we could demonstrate that in three-dimensional bone tissue the relation of trabecular plates to rods is reflected in the ratio of concave to convex surfaces of the bone Pattern in two-dimensional bone sections. For the quantification of the connectedness of these bone Patterns we developed a new histomorphometric parameter called Trabecular Bone Pattern Factor (TBPf). The basic idea is that the connectedness of structures can be described by the relation of convex to concave surfaces. A lot of concave surfaces represent a well connected spongy lattice, whereas a lot of convex surfaces indicate a badly connected trabecular lattice in twodimensional sections. By means of an automatic image analysis system we measure trabecular bone area (A1) and perimeter (P1). A second measurement of these two parameters (now A2 and P2) is done after a simulated dilatation of trabeculae on the screen. This dilatation results in a characteristic change of bone area and perimeter depending on the relation of convex to concave surfaces. TBPf is defined as a quotient of the difference of the first and the second measurement: TBPf = (P1–P2)/(A1–A2). First measurements of TBPf in 192 iliac crest bone biopsies of autopsy cases show that there is not only age-related loss of bone volume, but also a decrease of trabecular connectedness. By means of TBPf we can demonstrate a significant difference in the agerelated loss of trabecular connectivity between male and female individuals.
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Trabecular bone Pattern Factor—a new parameter for simple quantification of bone microarchitecture
Bone, 1992Co-Authors: Michael Hahn, M Vogel, M. Pompesius-kempa, Guenter DellingAbstract:Abstract The stability of trabecular bone depends not only on the amount of bone tissue, but also on the three-dimensional orientation and connectedness of trabeculae, which is summarized as trabecular microarchitecture. In previous studies we could demonstrate that in three-dimensional bone tissue the relation of trabecular plates to rods is reflected in the ratio of concave to convex surfaces of the bone Pattern in two-dimensional bone sections. For the quantification of the connectedness of these bone Patterns we developed a new histomorphometric parameter called Trabecular Bone Pattern Factor (TBPf). The basic idea is that the connectedness of structures can be described by the relation of convex to concave surfaces. A lot of concave surfaces represent a well connected spongy lattice, whereas a lot of convex surfaces indicate a badly connected trabecular lattice in twodimensional sections. By means of an automatic image analysis system we measure trabecular bone area (A1) and perimeter (P1). A second measurement of these two parameters (now A2 and P2) is done after a simulated dilatation of trabeculae on the screen. This dilatation results in a characteristic change of bone area and perimeter depending on the relation of convex to concave surfaces. TBPf is defined as a quotient of the difference of the first and the second measurement: TBPf = (P1–P2)/(A1–A2). First measurements of TBPf in 192 iliac crest bone biopsies of autopsy cases show that there is not only age-related loss of bone volume, but also a decrease of trabecular connectedness. By means of TBPf we can demonstrate a significant difference in the agerelated loss of trabecular connectivity between male and female individuals.
Onder Guler - One of the best experts on this subject based on the ideXlab platform.
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a novel energy Pattern Factor method for wind speed distribution parameter estimation
Energy Conversion and Management, 2015Co-Authors: Seyit Ahmet Akdag, Onder GulerAbstract:Abstract Power output of wind turbine depends on many Factors. Among them, the most crucial one is wind speed. Since wind speed data is a significant Factor for wind energy analyses, it should be modeled accurately. Weibull distribution has been used extensively to model variation of wind speed. Therefore, the most appropriate distribution parameter estimation method selection is critical in order to minimize data set modeling errors. In this context, a novel, robust, efficient and better method than standard methods to estimate Weibull parameters is presented for the first time in this paper. The accuracy of the proposed method is verified using different data sets. Also, developed method is compared with Graphic Method (GM), Maximum Likelihood Method (MLM), Alternative Maximum Likelihood Method (AMLH), Modified Maximum Likelihood Method (MMLH), Moment Method (MM), Justus Moment Method (JMM), WAsP Method (WM) and Power Density Method (PD). The results indicate that the proposed novel method is adequate to determine Weibull distribution parameters.
Hukam Chand Mongia - One of the best experts on this subject based on the ideXlab platform.
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Engineering Aspects of Complex Gas Turbine Combustion Mixers Part IV: Swirl cup
9th Annual International Energy Conversion Engineering Conference, 2011Co-Authors: Hukam Chand MongiaAbstract:An overview is given on the use of several complex multi-swirler devices in gas turbine combustion and attendant technological advances in emissions, cooling, Pattern Factor, operability and overall temperature increase across the combustor. The emphasis of this paper is on the development and innovative applications of twin-concentric richand lean-direct injection mixers, their use in the dual-annular combustors, and finally making its extension to premixed mixers for the Dry Low Emissions, DLE twin and triple annular combustors.
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an advanced spray model for application to the prediction of gas turbine combustor flow fields
Numerical Heat Transfer Part A-applications, 2000Co-Authors: Anil K Tolpadi, Suresh K Aggarwal, Hukam Chand MongiaAbstract:It is well known that fuel preparation, its method of injection into a combustor, and its atomization characteristics have a significant impact on emissions. A simple dilute spray model, which assumes that droplet heating and vaporization occur in sequence, has been implemented in the past within computational fluid dynamics (CFD) codes at General Electric (GE) and has been used extensively for combustion applications. This spray model coupled with an appropriate combustion model makes reasonable predictions of the combustor Pattern Factor and emissions. To improve upon this predictive ability, a more advanced quasi-steady droplet vaporization model has been considered. This article describes the evaluation of this advanced model. In this new approach, droplet heating and vaporization take place simultaneously (which is more realistic). In addition, the transport properties of both the liquid and vapor phases are allowed to vary as a function of pressure, gas phase temperature, and droplet temperature. Th...
Muhammad Shoaib - One of the best experts on this subject based on the ideXlab platform.
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assessment of wind energy potential using wind energy conversion system
Journal of Cleaner Production, 2019Co-Authors: Muhammad Shoaib, I A Siddiqui, Shamim Khan, Shafiqur Rehman, Luai M AlhemsAbstract:Abstract Wind energy, as a renewable resource, is the most rapidly growing source that produces electrical energy using wind turbines. Such a wind energy conversion system is both economical and is environmental friendly. It requires understanding of wind conditions at the site under study. With this intent, wind characteristics of Jhampir (district Thatta Sindh, Pakistan) are investigated and wind energy potential is determined. The study is conducted using 10-min averaged wind speed data obtained from Alternate Energy Development Board of Pakistan for a period of three years (2007–2010). Monthly, seasonal, and yearly analysis is performed by fitting measured wind speed data to a Weibull distribution function. Weibull shape and scale parameters are determined numerically using Maximum Likelihood Method, Modified Maximum Likelihood Method, and Energy Pattern Factor Methods. The suitability of the fit is assessed using goodness-of-fit tests, such as, Root Mean Square Error, Coefficient of Determination (R2), and Chi-Square (χ2) tests. In all three data analysis periods, RMSE values varied between 10−2 and 10−4. Similarly, R2 values varied between 0.989 and 0.996 and χ2-test between 10−4 and 10−8. For entire data set, all the tests showed better performance of Maximum Likelihood and Modified Maximum Likelihood Methods compared to Energy Pattern Factor. In case of monthly analysis, Maximum Likelihood Method performed better compared to Modified Maximum Likelihood Method and Energy Pattern Factor according to root mean square error and χ2 tests results. Seasonal performance of all the methods is found to be similar with marginal superiority of MLM over other methods. A very good agreement is observed between standard deviation values for measured wind speed data distribution and fitted Weibull distribution using Maximum Likelihood Method estimator. Additionally, to understand the optimum directional efficiency, directional wind power densities are calculated. Finally, a wind turbine is used to the seasonal and yearly wind speed data to determine the actual wind energy potential of the site. Extracted wind energy values for four seasons are found to be 1691, 2851, 4572, and 916 kWh with an annual yield of 10054 kWh. Wind energy values obtained for different periods and directions suggest that Jhampir is a suitable site for developing the wind power plant.