NESTEM: A Computational Tool to Perform Probabilistic Structural Analysis of Components Subjected to Uncertain Mechanical and Thermal Loading

1999 ◽  
Author(s):  
Bhogilal M. Patel ◽  
William C. Strack ◽  
Vinod Nagpal ◽  
Shantaram S. Pai ◽  
P. L. N. Murthy
Keyword(s):  
Heat Transfer ◽  
Stress Responses ◽  
Thermal Loading ◽  
Random Variables ◽  
Cost Effective ◽  
Distribution Functions ◽  
Probabilistic Methods ◽  
Cumulative Distribution ◽  
Heat Transfer Analysis ◽  
Design Variables

This paper presents an overview of a newly developed code, NESTEM that analyzes structural components subjected to varying thermal and mechanical loads. This program is an enhanced version of NESSUS and has all the capabilities of NESSUS. In addition, it allows one to perform heat transfer analysis. The basic heat transfer variables can be included as random variables along with the mechanical random variables to quantify risk using probabilistic methods and to perform sensitivity analysis. The analysis capabilities of NESTEM have been demonstrated by analyzing a cylindrical combustor liner. This analysis includes evaluating stresses and their variations at critical points on the liner using material properties, pressure loading and basic heat transfer variables as the random variables. The heat transfer variables are convection temperatures, film coefficients, radiation temperatures, emissivity, absorptivity and conductivity. Cumulative distribution functions and sensitivity factors, for stress responses, for mechanical and thermal random variables are calculated. These results can be used to quickly identify the most critical design variables, in order to optimize the design, to make it cost effective.

Probabilistic finite element analysis in heat transfer to a nuclear fuel rod bumper support

2004 ◽  
Vol 218 (12) ◽  
pp. 1499-1505
Author(s):  
Rama Subba Reddy Gorla
Keyword(s):  
Heat Transfer ◽  
Finite Element ◽  
Nuclear Fuel ◽  
Cost Effective ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Element Analysis ◽  
Transfer Rates ◽  
Fuel Rod ◽  
Design Variables

Heat transfer from a nuclear fuel rod bumper support was computationally simulated by a finite element method and probabilistically evaluated in view of the several uncertainties in the performance parameters. Cumulative distribution functions and sensitivity factors were computed for overall heat transfer rates due to the thermodynamic random variables. These results can be used to identify quickly the most critical design variables in order to optimize the design and to make it cost effective. The analysis leads to the selection of the appropriate measurements to be used in heat transfer and to the identification of both the most critical measurements and the parameters.

scholarly journals Probabilistic Study of Fluid Structure Interaction

2002 ◽  
Author(s):  
Rama S. R. Gorla ◽  
Shantaram S. Pai ◽  
Jeffrey J. Rusick
Keyword(s):  
Stress Responses ◽  
Hoop Stress ◽  
Coefficient Of Thermal Expansion ◽  
Cost Effective ◽  
Distribution Functions ◽  
Flow Coefficient ◽  
Cumulative Distribution ◽  
Design Variables ◽  
Probabilistic Study ◽  
Combustor Liner

A combustor liner was computationally simulated and probabilistically evaluated in view of the several uncertainties in the aerodynamic, structural, material and thermal variables that govern the combustor liner. The interconnection between the computational fluid dynamics code and the finite element structural analysis codes was necessary to couple the thermal profiles with structural design. The stresses and their variations were evaluated at critical points on the liner. Cumulative distribution functions and sensitivity factors were computed for stress responses due to the aerodynamic, mechanical and thermal random variables. It was observed that the inlet and exit temperatures have a lot of influence on the hoop stress. For prescribed values of inlet and exit temperatures, the Reynolds number of the flow, coefficient of thermal expansion, gas emissivity and absorptivity and thermal conductivity of the material have about the same impact on the hoop stress. These results can be used to quickly identify the most critical design variables in order to optimize the design and make it cost effective.

Unsteady Fluid Structure Interaction in a Turbine Blade

2005 ◽  
Author(s):  
Rama Subba Reddy Gorla ◽  
Shantaram S. Pai ◽  
Isaiah Blankson ◽  
Srinivas C. Tadepalli ◽  
Sreekantha Reddy Gorla
Keyword(s):  
Finite Element ◽  
Turbine Blade ◽  
Three Dimensional ◽  
Cost Effective ◽  
Computer Time ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Navier Stokes ◽  
Rotating Frame ◽  
Design Variables

An unsteady, three dimensional Navier-Stokes solution in rotating frame formulation for turbomachinery applications has been described. Casting the governing equations in a rotating frame enables the freezing of grid motion and results in substantial savings in computer time. Heat transfer to a gas turbine blade was computationally simulated by finite element methods and probabilistically evaluated in view of the several uncertainties in the performance parameters. The interconnection between the CFD code and finite element structural analysis code was necessary to couple the thermal profiles with the structural design. The stresses and their variations were evaluated at critical points on the turbine blade. Cumulative distribution functions and sensitivity factors were computed for stresses due to the aerodynamic, geometric, material and thermal random variables. These results can be used to quickly identify the most critical design variables in order to optimize the design and make it cost effective. The analysis leads to the selection of the appropriate materials to be used and to the identification of both the most critical measurements and parameters.

scholarly journals Probabilistic Analysis of Solid Oxide Fuel Cell Based Hybrid Gas Turbine System

2003 ◽  
Author(s):  
Rama S. R. Gorla ◽  
Shantaram S. Pai ◽  
Jeffrey Rusick
Keyword(s):  
Fuel Cell ◽  
Gas Turbine ◽  
Thermodynamic Cycle ◽  
Cost Effective ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Specific Power ◽  
Cell Systems ◽  
Design Variables ◽  
Thermodynamic Performance

The emergence of fuel cell systems and hybrid fuel cell systems requires the evolution of analysis strategies for evaluating thermodynamic performance. A gas turbine thermodynamic cycle integrated with a fuel cell was computationally simulated and probabilistically evaluated in view of the several uncertainties in the thermodynamic performance parameters. Cumulative distribution functions and sensitivity factors were computed for the overall thermal efficiency and net specific power output due to the uncertainties in the thermodynamic random variables. These results can be used to quickly identify the most critical design variables in order to optimize the design and make it cost effective. The analysis leads to the selection of criteria for gas turbine performance.

scholarly journals Distributions of the Ratio and Product of Two Independent Weibull and Lindley Random Variables

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
N. J. Hassan ◽  
A. Hawad Nasar ◽  
J. Mahdi Hadad
Keyword(s):  
Hypergeometric Functions ◽  
Special Functions ◽  
Random Variables ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Parabolic Cylinder ◽  
Generalized Hypergeometric Functions ◽  
Confluent Hypergeometric Functions ◽  
Parabolic Cylinder Functions ◽  
The Moment

In this paper, we derive the cumulative distribution functions (CDF) and probability density functions (PDF) of the ratio and product of two independent Weibull and Lindley random variables. The moment generating functions (MGF) and the k-moment are driven from the ratio and product cases. In these derivations, we use some special functions, for instance, generalized hypergeometric functions, confluent hypergeometric functions, and the parabolic cylinder functions. Finally, we draw the PDF and CDF in many values of the parameters.

scholarly journals Branching-stable point measures and processes

2018 ◽  
Vol 50 (4) ◽  
pp. 1294-1314
Author(s):  
Jean Bertoin ◽  
Aser Cortines ◽  
Bastien Mallein
Keyword(s):  
Asymptotic Behavior ◽  
Classical Theory ◽  
Branching Processes ◽  
Random Variables ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Scaling Exponent ◽  
Stable Point ◽  
Cumulative Distribution Functions ◽  
Stable Random Variables

Abstract We introduce and study the class of branching-stable point measures, which can be seen as an analog of stable random variables when the branching mechanism for point measures replaces the usual addition. In contrast with the classical theory of stable (Lévy) processes, there exists a rich family of branching-stable point measures with a negative scaling exponent, which can be described as certain Crump‒Mode‒Jagers branching processes. We investigate the asymptotic behavior of their cumulative distribution functions, that is, the number of atoms in (-∞, x] as x→∞, and further depict the genealogical lineage of typical atoms. For both results, we rely crucially on the work of Biggins (1977), (1992).

scholarly journals Meta-Models and Genetic Algorithm Application to Approximate Optimization with Discrete Variables for Fire Resistance Design of A60 Class Bulkhead Penetration Piece

2021 ◽  
Vol 11 (7) ◽  
pp. 2972
Author(s):  
Woo Chang Park ◽  
Chang Yong Song
Keyword(s):  
Neural Network ◽  
Heat Transfer ◽  
Radial Basis Function ◽  
Fire Resistance ◽  
Basis Function ◽  
Heat Transfer Analysis ◽  
Discrete Variables ◽  
Approximate Optimization ◽  
Design Variables ◽  
Discrete Design Variables

A60 class bulkhead penetration piece is a fire-resistance apparatus installed on bulkhead compartments to protect lives and to prevent flame diffusion in case of fire accident in ships and offshore plants. In this study, approximate optimization with discrete variables was carried out for the fire-resistance design of an A60 class bulkhead penetration piece (A60 BPP) using various meta-models and multi-island genetic algorithms. Transient heat transfer analysis was carried out to evaluate the fire-resistance design of the A60 class bulkhead penetration piece, and we verified the results of the analysis via a fire test. The design of the experiment’s method was applied to generate the meta-models to be used for the approximate optimization, and the verified results of the transient heat transfer analysis were integrated with the design of the experiment’s method. The meta-models used in the approximate optimization were response surface model, Kriging, and radial basis function-based neural network. In the approximate optimization, the bulkhead penetration piece length, diameter, material type, and insulation density were applied to discrete design variables, and constraints that were considered include temperature, productivity, and cost. The approximate optimum design problem based on the meta-model was formulated such that the discrete design variables were determined by minimizing the weight of the A60 class bulkhead penetration piece subject to the limit values of constraints. In the context of approximate accuracy, the solution results from the approximate optimization were compared to actual analysis results. It was concluded that the radial basis function-based neural network, among the meta-models used in the approximate optimization, showed the most accurate optimum design results for the fire-resistance design of the A60 class bulkhead penetration piece.

scholarly journals Sensitivity analysis of conformal CCs for injection molds: 2D Transient Heat Transfer Analysis

2021 ◽  
Author(s):  
Hugo Miguel Silva ◽  
Tiago Noversa ◽  
Leandro Fernandes ◽  
Hugo Rodrigues ◽  
António Pontes
Keyword(s):  
Sensitivity Analysis ◽  
Injection Molding ◽  
Thermal Stresses ◽  
Parametric Design ◽  
Cost Effective ◽  
Heat Transfer Analysis ◽  
Ejection Time ◽  
Cooling Channels ◽  
Design Variables ◽  
Optimization Methodology

Abstract Conformal Cooling Channels (CCCs) have gotten easier and more economical to manufacture in recent years. This was largely due to recent developments in additive manufacturing. The usage of CCCs in engineering applications involving injection molding provides for superior cooling performance than straight drilled channels, which have traditionally been utilized in injection molding. The fundamental reason for this is that CCCs are able to follow the molded geometry's trajectories. With the use of CCC’s, the cooling time, total injection time, thermal stresses, and warpage can all be considerably reduced. Nonetheless, the CCC design process is more difficult than that of traditional channels. The integration of computer-aided engineering (CAE) simulations is critical for achieving an effective, cost-effective design. This paper focuses the sensitivity analysis of design variables, with the intention of implementing a design optimization methodology in the future. The ultimate goal is to optimize the placement of Cooling Channels (CCs) to minimize the ejection time and maximize the uniformity of temperature distribution. It can be concluded that the parametrization done in ANSYS Parametric Design Language (APDL), as well as the selected design variables are feasible and might be useful for future optimization methodologies.

scholarly journals RELIABILITY ANALYSIS OF RHS STEEL TRUSSES JOINTS BASED ON THE P-BOXES APPROACH

2021 ◽  
Vol 17 (1) ◽  
pp. 87-97
Author(s):  
Anastasia Soloveva ◽  
Sergey Solovev
Keyword(s):  
Reliability Analysis ◽  
Epistemic Uncertainty ◽  
Random Variables ◽  
Random Variable ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Interval Estimate ◽  
Structural Elements ◽  
Aleatory And Epistemic Uncertainty ◽  
Steel Trusses

Reliability is one of the main indicators of structural elements mechanical safety. The choice of stochastic models is an important task in reliability analysis for describing the variability of random variables with aleatory and epistemic uncertainty. The article proposes a method for the reliability analysis of RHS (rectangular hollow sections) steel truss joints based on p-boxes approach. The p-boxes consist of two boundary distribution functions that create an area of possible distribution functions of a random variable. The using of p-boxes make possible to model random variables without making unreasonable assumptions about the exact cumulative distribution functions (CDF) or the exact values of the CDF parameters. The developed approach allows to give an interval estimate of the non-failure probability of the truss joints, which is necessary for a comprehensive (system) reliability analysis of the entire truss.

scholarly journals A Note on the Central Limit Theorems for Dependent Random Variables

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Yilun Shang
Keyword(s):  
Central Limit ◽  
Limit Theorems ◽  
Random Variables ◽  
Distribution Functions ◽  
Central Limit Theorems ◽  
Cumulative Distribution ◽  
Characteristic Functions ◽  
Mixing Conditions ◽  
Cumulative Distribution Functions ◽  
Probability And Statistics

Classical central limit theorem is considered the heart of probability and statistics theory. Our interest in this paper is central limit theorems for functions of random variables under mixing conditions. We impose mixing conditions on the differences between the joint cumulative distribution functions and the product of the marginal cumulative distribution functions. By using characteristic functions, we obtain several limit theorems extending previous results.

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