Engineering Papers⌕ Search

Engineering topics

Pai, Shantaram S.

Publications and source records attributed to Pai, Shantaram S..

31 records · Page 2

Probabilistic Study of Fluid Structure Interaction

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.

Gorla, Rama S. R.↗

Multidisciplinary Probabilistic Heat Transfer/Structural Analysis Code Developed: NESTEM

High-Speed Civil Transport (HSCT) engine combustor liners are subjected to complex thermal environments and have to endure these for thousands of hours with assured reliability. In the past, several deterministic analyses have been performed, including detailed heat transfer analyses to obtain thermal profiles and deterministic stress analyses to identify critical locations of high stresses. Actual rig tests also have been performed for segments by simulating these loading situations as closely as possible. However, it is well known that many uncertainties exist in loading (primarily thermal loads due to heat transfer), boundary conditions (end fixity unknowns), and material properties (moduli, thermal-expansion coefficients, and conductivities). The present in-house effort at the NASA Lewis Research Center is directed toward accounting for these in a formal way to assess the performance of liner components under complex and uncertain loading conditions as well as subject to other geometry- and material-related uncertainties.

Murthy, Pappu L. N.↗

Probabilistic progressive buckling of trusses

A three-bay, space, cantilever truss is probabilistically evaluated to describe progressive buckling and truss collapse in view of the numerous uncertainties associated with the structural, material, and load variables that describe the truss. Initially, the truss is deterministically analyzed for member forces, and members in which the axial force exceeds the Euler buckling load are identified. These members are then discretized with several intermediate nodes, and a probabilistic buckling analysis is performed on the truss to obtain its probabilistic buckling loads and the respective mode shapes. Furthermore, sensitivities associated with the uncertainties in the primitive variables are investigated, margin of safety values for the truss are determined, and truss end node displacements are noted. These steps are repeated by sequentially removing buckled members until onset of truss collapse is reached. Results show that this procedure yields an optimum truss configuration for a given loading and for a specified reliability.

PROBABILISTIC BUCKLING ANALYSI↗

Probabilistic Assessment of Adaptive Space Truss Configurations for Thermal Buckling Resistance

A three-bay, cantilever truss of a type typically used in space structures, is probabilistically evaluated to configure adaptive/smart/intelligent behavior for resisting thermal buckling. This buckling is due to nonuniform thermal loads and a combination of these loads with applied loads and moments (mechanical loads). For each behavior the scatter (ranges) in buckling loads and member axial forces are probabilistically determined. Sensitivities associated with uncertainties in the structural and material variables that describe the truss, as well as scatter in mechanical and thermal loads, are determined for different probabilities. The relative magnitude of these sensitivities are used to identify significant truss variables that control/classify the truss behavior and cause it to respond as an adaptive/smart/ intelligent structure. Results show that the probabilistic buckling loads increase for adaptive and intelligent truss classifications, with a substantial increase for intelligent trusses. Similarly, the probabilistic member axial forces decrease for each truss classification.

Pai, Shantaram S.↗

Probabilistic structural analysis of adaptive/smart/intelligent space structures

A three-bay, space, cantilever truss is probabilistically evaluated for adaptive/smart/intelligent behavior. For each behavior, the scatter (ranges) in buckling loads, vibration frequencies, and member axial forces are probabilistically determined. Sensitivities associated with uncertainties in the structure, material and load variables that describe the truss are determined for different probabilities. The relative magnitude for these sensitivities are used to identify significant truss variables that control/classify its behavior to respond as an adaptive/smart/intelligent structure. Results show that the probabilistic buckling loads and vibration frequencies increase for each truss classification, with a substantial increase for intelligent trusses. Similarly, the probabilistic member axial forces reduce for adaptive and intelligent trusses and increase for smart trusses.

Pai, Shantaram S.↗

Probabilistic assessment of space trusses subjected to combined mechanical and thermal loads

A three-bay, space, cantilever truss is probabilistically evaluated to quantify the range of uncertainties of buckling loads and member forces due to nonuniform thermal loads, applied loads and moments (mechanical loads), and combination of both. The truss members are assumed to be made from Aluminum tubes or high modulus graphite-fiber/intermediate modulus epoxy-matrix composite tubes. Cumulative distribution function results show that certain combinations of thermal loads with mechanical loads reduce the probabilistic buckling loads and increase the magnitude of the member axial forces for the aluminum truss. The same trend is observed for the composite truss as well, as however, the thermal effects on the probabilistic buckling loads and member axial forces are not as substantial as that for an aluminum truss. This can be attributed to the large differences in the values of coefficient of thermal expansion. Finally, the sensitivities associated with the uncertainties in the structural, material, and load variables (primitive variables) are investigated. They show that buckling loads and member axial forces are most sensitive to the uncertainties in spacial (geometry) variables.

Pai, Shantaram S.↗

Nonuniform thermal environmental effects on space truss structural reliability

A three-bay, space, cantilever truss is probabilistically evaluated to quantify the range of uncertainties of buckling loads and member forces due to nonuniform thermal loads, applied loads and moments (mechanical loads), and combination of both. The truss members are assumed to be made from (1) aluminum tubes or (2) high modulus graphite-fiber/intermediate modulus epoxy-matrix composite tubes. Cumulative distribution function results show that certain combinations of thermal loads with mechanical loads reduce the probabilistic buckling loads and increase the magnitude of the member axial forces for aluminum truss. However, the reverse is true for composite truss due to very low coefficient of thermal expansion and higher stiffness of the composite. Finally, the sensitivities associated with the uncertainties in the structural, material, and load variables (primitive variables) are investigated. They show that buckling loads and member axial forces are most sensitive to the uncertainties in spacial (geometry) variables.

Pai, Shantaram S.↗

Probabilistic structural analysis of space truss structures for nonuniform thermal environmental effects

A three-bay, space, cantilever truss is probabilistically evaluated to quantify the range of uncertainties of vibration frequencies and truss free end vertical displacements due to nonuniform thermal loads, applied loads and moments (mechanical loads), and combination of both. The truss members are assumed to be made from (1) aluminum tubes or (2) high modulus graphite-fiber/intermediate modulus epoxy-matrix composite tubes. Cumulative distribution function results show that certain combination of thermal loads with mechanical loads reduce the probabilistic vibration frequencies and increase the magnitude of the truss free end vertical displacements for the aluminum truss. However, for the composite truss, the thermal effects on the probabilistic vibration frequencies are not as substantial as that for an aluminum truss. This can be attributed to the large differences in the values of coefficient of thermal expansion. Finally, the sensitivities associated with the uncertainties in the structural, material and load variables (primative variables) are investigated. Results indicate that vibration frequencies and truss free end vertical displacements are sensitive to the uncertainties in spacial (geometry) variables as well as member modulus.

Pai, Shantaram S.↗

Probabilistic progressive buckling of trusses

A three-bay, space, cantilever truss is probabilistically evaluated to describe progressive buckling and truss collapse in view of the numerous uncertainties associated with the structural, material, and load variables (primitive variables) that describe the truss. Initially, the truss is deterministically analyzed for member forces, and member(s) in which the axial force exceeds the Euler buckling load are identified. These member(s) are then discretized with several intermediate nodes and a probabilistic buckling analysis is performed on the truss to obtain its probabilistic buckling loads and respective mode shapes. Furthermore, sensitivities associated with the uncertainties in the primitive variables are investigated, margin of safety values for the truss are determined, and truss end node displacements are noted. These steps are repeated by sequentially removing the buckled member(s) until onset of truss collapse is reached. Results show that this procedure yields an optimum truss configuration for a given loading and for a specified reliability.

Pai, Shantaram S.↗

Probabilistic progressive buckling of trusses

A three-bay, space, cantilever truss is probabilistically evaluated to describe progressive buckling and truss collapse in view of the numerous uncertainties associated with the structural, material, and load variables (primitive variables) that describe the truss. Initially, the truss is deterministically analyzed for member forces, and member(s) in which the axial force exceeds the Euler buckling load are identified. These member(s) are then discretized with several intermediate nodes and a probabilistic buckling analysis is performed on the truss to obtain its probabilistic buckling loads and respective mode shapes. Furthermore, sensitivities associated with the uncertainties in the primitive variables are investigated, margin of safety values for the truss are determined, and truss end node displacements are noted. These steps are repeated by sequentially removing the buckled member(s) until onset of truss collapse is reached. Results show that this procedure yields an optimum truss configuration for a given loading and for a specified reliability.

Pai, Shantaram S.↗

Probabilistic structural analysis of adaptive/smart/intelligent space structures

A three-bay, space, cantilever truss is probabilistically evaluated for adaptive/smart/intelligent behavior. For each behavior, the scatter (ranges) in buckling loads, vibration frequencies, and member axial forces are probabilistically determined. Sensitivities associated with uncertainties in the structure, material and load variables that describe the truss are determined for different probabilities. The relative magnitude for these sensitivities are used to identify significant truss variables that control/classify its behavior to respond as an adaptive/smart/intelligent structure. Results show that the probabilistic buckling loads and vibration frequencies increase for each truss classification, with a substantial increase for intelligent trusses. Similarly, the probabilistic member axial forces reduce for adaptive and intelligent trusses and increase for smart trusses.

Pai, Shantaram S.↗

Probabilistic structural analysis of a truss typical for space station

A three-bay, space, cantilever truss is probabilistically evaluated using the computer code NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) to identify and quantify the uncertainties and respective sensitivities associated with corresponding uncertainties in the primitive variables (structural, material, and loads parameters) that defines the truss. The distribution of each of these primitive variables is described in terms of one of several available distributions such as the Weibull, exponential, normal, log-normal, etc. The cumulative distribution function (CDF's) for the response functions considered and sensitivities associated with the primitive variables for given response are investigated. These sensitivities help in determining the dominating primitive variables for that response.

Pai, Shantaram S.↗

Calculation of Weibull strength parameters and Batdorf flow-density constants for volume- and surface-flaw-induced fracture in ceramics

The calculation of shape and scale parameters of the two-parameter Weibull distribution is described using the least-squares analysis and maximum likelihood methods for volume- and surface-flaw-induced fracture in ceramics with complete and censored samples. Detailed procedures are given for evaluating 90 percent confidence intervals for maximum likelihood estimates of shape and scale parameters, the unbiased estimates of the shape parameters, and the Weibull mean values and corresponding standard deviations. Furthermore, the necessary steps are described for detecting outliers and for calculating the Kolmogorov-Smirnov and the Anderson-Darling goodness-of-fit statistics and 90 percent confidence bands about the Weibull distribution. It also shows how to calculate the Batdorf flaw-density constants by uing the Weibull distribution statistical parameters. The techniques described were verified with several example problems, from the open literature, and were coded. The techniques described were verified with several example problems from the open literature, and were coded in the Structural Ceramics Analysis and Reliability Evaluation (SCARE) design program.

Pai, Shantaram S.↗