The Experts below are selected from a list of 70431 Experts worldwide ranked by ideXlab platform
Dennis Jarmowski - One of the best experts on this subject based on the ideXlab platform.
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Probabilistic Lifetime Assessment Approach of 2%-Cr Steel Considering Material and Loading Profile Scatter
Journal of Engineering for Gas Turbines and Power, 2019Co-Authors: Felix Koelzow, Christian Kontermann, Klaus Helbig, Dennis JarmowskiAbstract:Abstract In regions with high intermittent renewable energy share, thermal plants are forced to operate with greater flexibility beyond their original design intent. Decreasing energy prices and capacity factors will further force these plants to more transient operation with steeper load gradients. Older steam turbine (ST) protections systems on site are often not designed for such flexible operation and do not properly supervise the resulting impact on lifetime consumption. Therefore, precise lifetime management concepts are required to increase plant reliability and flexibility, and to mitigate risks for new implemented operation modes. Several lifetime assessment methods were developed to quantify the damage evolution and the residual lifetime for ST components. Usually, these methods require both input about representative or operated loading profiles and characteristic Material Curves. These characteristic Curves are determined by a number of standardized Material tests. Due to the Material scatter and other different sources of uncertainties, each test is a realization of a stochastic process. Hence, the corresponding characteristic Material Curves inherit these uncertainties and do not represent an absolute limit. The analyses of different loading profiles even for the same plant and same start-up class reveal that the consideration of statistically evaluated specific start-up distributions and further transient events are of major importance. Probabilistic methods are able to quantify all of these uncertainties and compute the probability of failure for a given lifetime or vice versa. Within this paper, at first an extensive and systematic operational profile analysis is carried out and discussed, which acts as an input for a probabilistic lifetime assessment approach. For that, a developed probabilistic workflow is presented to quantify the uncertainties and for lifetime prediction using the generalized damage accumulation rule with focus on creep-fatigue loading. To quantify the characteristic Material Curves, existing experimental data of a 2%-Cr forged steel (23CrMoNiWV8-8) is used. A probabilistic representation of the Wilshire–Scharning equation characterizes the creep rupture behavior. The maximum-likelihood method is used for parameter estimation and to take still running long term creep experiments into account. The end of life in low cycle fatigue experiments is characterized by a macroscopic crack initiation, and the Manson–Coffin–Basquin equation is utilized to represent the characteristic Material Curve. A temperature-modified version of the Manson–Coffin–Basquin equation is used to represent the experimental data. The parameter estimation is done by using the linear regression analysis followed by a comprehensive regression diagnostic. Taking both the Material and the load scatter into account, a reliability analysis is carried out to compute the probability of crack initiation. Finally, different load cases are considered and evaluated against each other.
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Probabilistic Lifetime Assessment Approach of 2%-Cr Steel Considering Material and Loading Profile Scatter
Volume 8: Microturbines Turbochargers and Small Turbomachines; Steam Turbines, 2019Co-Authors: Klaus Helbig, Felix Koelzow, Dennis Jarmowski, Christian KontermannAbstract:Abstract In regions with high intermittent renewable energy share, thermal plants are forced to operate with greater flexibility beyond their original design intent. Decreasing energy prices and capacity factors will further force these plants to more transient operation with steeper load gradients. Older steam turbine (ST) protections systems on site are often not designed for such flexible operation and do not properly supervise the resulting impact on lifetime consumption. Therefore, precise lifetime management concepts are required to increase plant reliability and flexibility, and to mitigate risks for new implemented operation modes. Several lifetime assessment methods were developed to quantify the damage evolution and the residual lifetime for ST components. Usually, these methods require both input about representative or operated loading profiles as well as characteristic Material Curves. These characteristic Curves are determined by a number of standardized Material tests. Due to the Material scatter and other different sources of uncertainties, each test is a realization of a stochastic process. Hence, the corresponding characteristic Material Curves inherit these uncertainties and do not represent an absolute limit. The analyses of different loading profiles even for the same plant and same start-up class reveal that the consideration of statistically evaluated specific start-up distributions and further transient events are of major importance. Probabilistic methods are able to quantify all of these uncertainties and compute the probability of failure for a given lifetime or vice versa. Within this paper, at first an extensive and systematic operational profile analysis is carried out and discussed, which acts as an input for a probabilistic lifetime assessment approach. For that, a developed probabilistic workflow is presented to quantify the uncertainties and for lifetime prediction using the generalized damage accumulation rule with focus on creep-fatigue loading. To quantify the characteristic Material Curves, existing experimental data of a 2%-Cr forged steel (23CrMoNiWV8-8) is used. A probabilistic representation of the Wilshire-Scharning equation characterizes the creep rupture behavior. The maximum-likelihood method is used for parameter estimation and to take still running long term creep experiments into account. The end of life in low cycle fatigue experiments is characterized by a macroscopic crack initiation and the Manson-Coffin-Basquin equation is utilized to represent the characteristic Material Curve. A temperature modified version of the Manson-Coffin-Basquin equation is used to represent the experimental data. The parameter estimation is done by using the linear regression analysis followed by a comprehensive regression diagnostic. Taking both, the Material and the load scatter into account, a reliability analysis is carried out to compute the probability of crack initiation. Finally, different load cases are considered and evaluated against each other.
Felix Koelzow - One of the best experts on this subject based on the ideXlab platform.
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Probabilistic Lifetime Assessment Approach of 2%-Cr Steel Considering Material and Loading Profile Scatter
Journal of Engineering for Gas Turbines and Power, 2019Co-Authors: Felix Koelzow, Christian Kontermann, Klaus Helbig, Dennis JarmowskiAbstract:Abstract In regions with high intermittent renewable energy share, thermal plants are forced to operate with greater flexibility beyond their original design intent. Decreasing energy prices and capacity factors will further force these plants to more transient operation with steeper load gradients. Older steam turbine (ST) protections systems on site are often not designed for such flexible operation and do not properly supervise the resulting impact on lifetime consumption. Therefore, precise lifetime management concepts are required to increase plant reliability and flexibility, and to mitigate risks for new implemented operation modes. Several lifetime assessment methods were developed to quantify the damage evolution and the residual lifetime for ST components. Usually, these methods require both input about representative or operated loading profiles and characteristic Material Curves. These characteristic Curves are determined by a number of standardized Material tests. Due to the Material scatter and other different sources of uncertainties, each test is a realization of a stochastic process. Hence, the corresponding characteristic Material Curves inherit these uncertainties and do not represent an absolute limit. The analyses of different loading profiles even for the same plant and same start-up class reveal that the consideration of statistically evaluated specific start-up distributions and further transient events are of major importance. Probabilistic methods are able to quantify all of these uncertainties and compute the probability of failure for a given lifetime or vice versa. Within this paper, at first an extensive and systematic operational profile analysis is carried out and discussed, which acts as an input for a probabilistic lifetime assessment approach. For that, a developed probabilistic workflow is presented to quantify the uncertainties and for lifetime prediction using the generalized damage accumulation rule with focus on creep-fatigue loading. To quantify the characteristic Material Curves, existing experimental data of a 2%-Cr forged steel (23CrMoNiWV8-8) is used. A probabilistic representation of the Wilshire–Scharning equation characterizes the creep rupture behavior. The maximum-likelihood method is used for parameter estimation and to take still running long term creep experiments into account. The end of life in low cycle fatigue experiments is characterized by a macroscopic crack initiation, and the Manson–Coffin–Basquin equation is utilized to represent the characteristic Material Curve. A temperature-modified version of the Manson–Coffin–Basquin equation is used to represent the experimental data. The parameter estimation is done by using the linear regression analysis followed by a comprehensive regression diagnostic. Taking both the Material and the load scatter into account, a reliability analysis is carried out to compute the probability of crack initiation. Finally, different load cases are considered and evaluated against each other.
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Probabilistic Lifetime Assessment Approach of 2%-Cr Steel Considering Material and Loading Profile Scatter
Volume 8: Microturbines Turbochargers and Small Turbomachines; Steam Turbines, 2019Co-Authors: Klaus Helbig, Felix Koelzow, Dennis Jarmowski, Christian KontermannAbstract:Abstract In regions with high intermittent renewable energy share, thermal plants are forced to operate with greater flexibility beyond their original design intent. Decreasing energy prices and capacity factors will further force these plants to more transient operation with steeper load gradients. Older steam turbine (ST) protections systems on site are often not designed for such flexible operation and do not properly supervise the resulting impact on lifetime consumption. Therefore, precise lifetime management concepts are required to increase plant reliability and flexibility, and to mitigate risks for new implemented operation modes. Several lifetime assessment methods were developed to quantify the damage evolution and the residual lifetime for ST components. Usually, these methods require both input about representative or operated loading profiles as well as characteristic Material Curves. These characteristic Curves are determined by a number of standardized Material tests. Due to the Material scatter and other different sources of uncertainties, each test is a realization of a stochastic process. Hence, the corresponding characteristic Material Curves inherit these uncertainties and do not represent an absolute limit. The analyses of different loading profiles even for the same plant and same start-up class reveal that the consideration of statistically evaluated specific start-up distributions and further transient events are of major importance. Probabilistic methods are able to quantify all of these uncertainties and compute the probability of failure for a given lifetime or vice versa. Within this paper, at first an extensive and systematic operational profile analysis is carried out and discussed, which acts as an input for a probabilistic lifetime assessment approach. For that, a developed probabilistic workflow is presented to quantify the uncertainties and for lifetime prediction using the generalized damage accumulation rule with focus on creep-fatigue loading. To quantify the characteristic Material Curves, existing experimental data of a 2%-Cr forged steel (23CrMoNiWV8-8) is used. A probabilistic representation of the Wilshire-Scharning equation characterizes the creep rupture behavior. The maximum-likelihood method is used for parameter estimation and to take still running long term creep experiments into account. The end of life in low cycle fatigue experiments is characterized by a macroscopic crack initiation and the Manson-Coffin-Basquin equation is utilized to represent the characteristic Material Curve. A temperature modified version of the Manson-Coffin-Basquin equation is used to represent the experimental data. The parameter estimation is done by using the linear regression analysis followed by a comprehensive regression diagnostic. Taking both, the Material and the load scatter into account, a reliability analysis is carried out to compute the probability of crack initiation. Finally, different load cases are considered and evaluated against each other.
Christian Kontermann - One of the best experts on this subject based on the ideXlab platform.
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Probabilistic Lifetime Assessment Approach of 2%-Cr Steel Considering Material and Loading Profile Scatter
Journal of Engineering for Gas Turbines and Power, 2019Co-Authors: Felix Koelzow, Christian Kontermann, Klaus Helbig, Dennis JarmowskiAbstract:Abstract In regions with high intermittent renewable energy share, thermal plants are forced to operate with greater flexibility beyond their original design intent. Decreasing energy prices and capacity factors will further force these plants to more transient operation with steeper load gradients. Older steam turbine (ST) protections systems on site are often not designed for such flexible operation and do not properly supervise the resulting impact on lifetime consumption. Therefore, precise lifetime management concepts are required to increase plant reliability and flexibility, and to mitigate risks for new implemented operation modes. Several lifetime assessment methods were developed to quantify the damage evolution and the residual lifetime for ST components. Usually, these methods require both input about representative or operated loading profiles and characteristic Material Curves. These characteristic Curves are determined by a number of standardized Material tests. Due to the Material scatter and other different sources of uncertainties, each test is a realization of a stochastic process. Hence, the corresponding characteristic Material Curves inherit these uncertainties and do not represent an absolute limit. The analyses of different loading profiles even for the same plant and same start-up class reveal that the consideration of statistically evaluated specific start-up distributions and further transient events are of major importance. Probabilistic methods are able to quantify all of these uncertainties and compute the probability of failure for a given lifetime or vice versa. Within this paper, at first an extensive and systematic operational profile analysis is carried out and discussed, which acts as an input for a probabilistic lifetime assessment approach. For that, a developed probabilistic workflow is presented to quantify the uncertainties and for lifetime prediction using the generalized damage accumulation rule with focus on creep-fatigue loading. To quantify the characteristic Material Curves, existing experimental data of a 2%-Cr forged steel (23CrMoNiWV8-8) is used. A probabilistic representation of the Wilshire–Scharning equation characterizes the creep rupture behavior. The maximum-likelihood method is used for parameter estimation and to take still running long term creep experiments into account. The end of life in low cycle fatigue experiments is characterized by a macroscopic crack initiation, and the Manson–Coffin–Basquin equation is utilized to represent the characteristic Material Curve. A temperature-modified version of the Manson–Coffin–Basquin equation is used to represent the experimental data. The parameter estimation is done by using the linear regression analysis followed by a comprehensive regression diagnostic. Taking both the Material and the load scatter into account, a reliability analysis is carried out to compute the probability of crack initiation. Finally, different load cases are considered and evaluated against each other.
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Probabilistic Lifetime Assessment Approach of 2%-Cr Steel Considering Material and Loading Profile Scatter
Volume 8: Microturbines Turbochargers and Small Turbomachines; Steam Turbines, 2019Co-Authors: Klaus Helbig, Felix Koelzow, Dennis Jarmowski, Christian KontermannAbstract:Abstract In regions with high intermittent renewable energy share, thermal plants are forced to operate with greater flexibility beyond their original design intent. Decreasing energy prices and capacity factors will further force these plants to more transient operation with steeper load gradients. Older steam turbine (ST) protections systems on site are often not designed for such flexible operation and do not properly supervise the resulting impact on lifetime consumption. Therefore, precise lifetime management concepts are required to increase plant reliability and flexibility, and to mitigate risks for new implemented operation modes. Several lifetime assessment methods were developed to quantify the damage evolution and the residual lifetime for ST components. Usually, these methods require both input about representative or operated loading profiles as well as characteristic Material Curves. These characteristic Curves are determined by a number of standardized Material tests. Due to the Material scatter and other different sources of uncertainties, each test is a realization of a stochastic process. Hence, the corresponding characteristic Material Curves inherit these uncertainties and do not represent an absolute limit. The analyses of different loading profiles even for the same plant and same start-up class reveal that the consideration of statistically evaluated specific start-up distributions and further transient events are of major importance. Probabilistic methods are able to quantify all of these uncertainties and compute the probability of failure for a given lifetime or vice versa. Within this paper, at first an extensive and systematic operational profile analysis is carried out and discussed, which acts as an input for a probabilistic lifetime assessment approach. For that, a developed probabilistic workflow is presented to quantify the uncertainties and for lifetime prediction using the generalized damage accumulation rule with focus on creep-fatigue loading. To quantify the characteristic Material Curves, existing experimental data of a 2%-Cr forged steel (23CrMoNiWV8-8) is used. A probabilistic representation of the Wilshire-Scharning equation characterizes the creep rupture behavior. The maximum-likelihood method is used for parameter estimation and to take still running long term creep experiments into account. The end of life in low cycle fatigue experiments is characterized by a macroscopic crack initiation and the Manson-Coffin-Basquin equation is utilized to represent the characteristic Material Curve. A temperature modified version of the Manson-Coffin-Basquin equation is used to represent the experimental data. The parameter estimation is done by using the linear regression analysis followed by a comprehensive regression diagnostic. Taking both, the Material and the load scatter into account, a reliability analysis is carried out to compute the probability of crack initiation. Finally, different load cases are considered and evaluated against each other.
Klaus Helbig - One of the best experts on this subject based on the ideXlab platform.
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Probabilistic Lifetime Assessment Approach of 2%-Cr Steel Considering Material and Loading Profile Scatter
Journal of Engineering for Gas Turbines and Power, 2019Co-Authors: Felix Koelzow, Christian Kontermann, Klaus Helbig, Dennis JarmowskiAbstract:Abstract In regions with high intermittent renewable energy share, thermal plants are forced to operate with greater flexibility beyond their original design intent. Decreasing energy prices and capacity factors will further force these plants to more transient operation with steeper load gradients. Older steam turbine (ST) protections systems on site are often not designed for such flexible operation and do not properly supervise the resulting impact on lifetime consumption. Therefore, precise lifetime management concepts are required to increase plant reliability and flexibility, and to mitigate risks for new implemented operation modes. Several lifetime assessment methods were developed to quantify the damage evolution and the residual lifetime for ST components. Usually, these methods require both input about representative or operated loading profiles and characteristic Material Curves. These characteristic Curves are determined by a number of standardized Material tests. Due to the Material scatter and other different sources of uncertainties, each test is a realization of a stochastic process. Hence, the corresponding characteristic Material Curves inherit these uncertainties and do not represent an absolute limit. The analyses of different loading profiles even for the same plant and same start-up class reveal that the consideration of statistically evaluated specific start-up distributions and further transient events are of major importance. Probabilistic methods are able to quantify all of these uncertainties and compute the probability of failure for a given lifetime or vice versa. Within this paper, at first an extensive and systematic operational profile analysis is carried out and discussed, which acts as an input for a probabilistic lifetime assessment approach. For that, a developed probabilistic workflow is presented to quantify the uncertainties and for lifetime prediction using the generalized damage accumulation rule with focus on creep-fatigue loading. To quantify the characteristic Material Curves, existing experimental data of a 2%-Cr forged steel (23CrMoNiWV8-8) is used. A probabilistic representation of the Wilshire–Scharning equation characterizes the creep rupture behavior. The maximum-likelihood method is used for parameter estimation and to take still running long term creep experiments into account. The end of life in low cycle fatigue experiments is characterized by a macroscopic crack initiation, and the Manson–Coffin–Basquin equation is utilized to represent the characteristic Material Curve. A temperature-modified version of the Manson–Coffin–Basquin equation is used to represent the experimental data. The parameter estimation is done by using the linear regression analysis followed by a comprehensive regression diagnostic. Taking both the Material and the load scatter into account, a reliability analysis is carried out to compute the probability of crack initiation. Finally, different load cases are considered and evaluated against each other.
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Probabilistic Lifetime Assessment Approach of 2%-Cr Steel Considering Material and Loading Profile Scatter
Volume 8: Microturbines Turbochargers and Small Turbomachines; Steam Turbines, 2019Co-Authors: Klaus Helbig, Felix Koelzow, Dennis Jarmowski, Christian KontermannAbstract:Abstract In regions with high intermittent renewable energy share, thermal plants are forced to operate with greater flexibility beyond their original design intent. Decreasing energy prices and capacity factors will further force these plants to more transient operation with steeper load gradients. Older steam turbine (ST) protections systems on site are often not designed for such flexible operation and do not properly supervise the resulting impact on lifetime consumption. Therefore, precise lifetime management concepts are required to increase plant reliability and flexibility, and to mitigate risks for new implemented operation modes. Several lifetime assessment methods were developed to quantify the damage evolution and the residual lifetime for ST components. Usually, these methods require both input about representative or operated loading profiles as well as characteristic Material Curves. These characteristic Curves are determined by a number of standardized Material tests. Due to the Material scatter and other different sources of uncertainties, each test is a realization of a stochastic process. Hence, the corresponding characteristic Material Curves inherit these uncertainties and do not represent an absolute limit. The analyses of different loading profiles even for the same plant and same start-up class reveal that the consideration of statistically evaluated specific start-up distributions and further transient events are of major importance. Probabilistic methods are able to quantify all of these uncertainties and compute the probability of failure for a given lifetime or vice versa. Within this paper, at first an extensive and systematic operational profile analysis is carried out and discussed, which acts as an input for a probabilistic lifetime assessment approach. For that, a developed probabilistic workflow is presented to quantify the uncertainties and for lifetime prediction using the generalized damage accumulation rule with focus on creep-fatigue loading. To quantify the characteristic Material Curves, existing experimental data of a 2%-Cr forged steel (23CrMoNiWV8-8) is used. A probabilistic representation of the Wilshire-Scharning equation characterizes the creep rupture behavior. The maximum-likelihood method is used for parameter estimation and to take still running long term creep experiments into account. The end of life in low cycle fatigue experiments is characterized by a macroscopic crack initiation and the Manson-Coffin-Basquin equation is utilized to represent the characteristic Material Curve. A temperature modified version of the Manson-Coffin-Basquin equation is used to represent the experimental data. The parameter estimation is done by using the linear regression analysis followed by a comprehensive regression diagnostic. Taking both, the Material and the load scatter into account, a reliability analysis is carried out to compute the probability of crack initiation. Finally, different load cases are considered and evaluated against each other.
R Velmurugan - One of the best experts on this subject based on the ideXlab platform.
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experimental and theoretical studies on buckling of thin spherical shells under axial loads
International Journal of Mechanical Sciences, 2008Co-Authors: N K Gupta, Mohamed N Sheriff, R VelmuruganAbstract:Abstract In this paper we present experiments, simulation as well as analysis of the collapse behaviour of thin spherical shells under quasi-static loading. Various aluminium spherical shells with variation in geometrical parameters were manufactured by spinning. Experiments were performed on these shells in a universal testing machine and their load–compression histories were obtained on the machine chart recorder. Three-dimensional numerical simulations were carried out for all the specimens tested under quasi-static loading using ANSYS ® . All the stages of collapse of the shell including non-symmetrical lobe formation were simulated. Material, geometric and contact nonlinearities were incorporated in the analysis. The stress–strain Curves of standard samples made from the Material were used as input. Piecewise linearity was taken in the plastic region of the Material Curve. Results thus obtained compared with the experiments well. An analysis was also carried out to study the behaviour of shells under axial compression based on the formation of rolling and stationary plastic hinges. These hinges were also simulated numerically and results match the experiments well.
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a study on buckling of thin conical frusta under axial loads
Thin-walled Structures, 2006Co-Authors: N K Gupta, Mohamed N Sheriff, R VelmuruganAbstract:Abstract Experiments were performed wherein conical frusta of aluminium of thicknesses between 0.7 and 1.62 mm and semi-apical angles range of 16–29° were axially compressed in a universal testing machine. The load–deformation Curves and deformed shapes of specimens were recorded. These deformed in axisymmetric concertina mode and non-symmetric diamond modes. A three dimensional numerical simulation was carried out for all samples tested under quasi-static loading using ANSYS®. Various stages of collapse of the shell, including non-symmetrical lobe formation were simulated for the first time, and Material, geometric and contact non-linearities were incorporated. The plastic region of the Material Curve was assumed to be piecewise linear. Tensile tests were performed on standard samples to obtain stress–strain Curves. Results thus obtained compared well with the experiments. Based on the formation of rolling and stationary plastic hinges an analysis was also carried out to study the behaviour of shells under axial compression and results were compared with experimental and numerical results.