Surendra N. Singhal

Coupled multi-disciplinary simulation of composite engine structures in propulsion environment

A computational simulation procedure is described for the coupled response of multi-layered multi-material composite engine structural components which are subjected to simultaneous multi-disciplinary thermal, structural, vibration, and acoustic loadings including the effect of hostile environments. The simulation is based on a three dimensional finite element analysis technique in conjunction with structural mechanics codes and with acoustic analysis methods. The composite material behavior is assessed at the various composite scales, i.e., the laminate/ply/constituents (fiber/matrix), via a nonlinear material characterization model. Sample cases exhibiting nonlinear geometrical, material, loading, and environmental behavior of aircraft engine fan blades, are presented. Results for deformed shape, vibration frequency, mode shapes, and acoustic noise emitted from the fan blade, are discussed for their coupled effect in hot and humid environments. Results such as acoustic noise for coupled composite-mechanics/heat transfer/structural/vibration/acoustic analyses demonstrate the effectiveness of coupled multi-disciplinary computational simulation and the various advantages of composite materials compared to metals.

Quantification of uncertainties in composites

An integrated methodology is developed for computationally simulating the probabilistic composite material properties at all composite scales. The simulation requires minimum input consisting of the description of uncertainties at the lowest scale (fiber and matrix constituents) of the composite and in the fabrication process variables. The methodology allows the determination of the sensitivity of the composite material behavior to all the relevant primitive variables. This information is crucial for reducing the undesirable scatter in composite behavior at its macro scale by reducing the uncertainties in the most influential primitive variables at the micro scale. The methodology is computationally efficient. The computational time required by the methodology described herein is an order of magnitude less than that for Monte Carlo Simulation. The methodology has been implemented into the computer code PICAN (Probabilistic Integrated Composite ANalyzer). The accuracy and efficiency of the methodology/code are demonstrated by simulating the uncertainties in the heat-transfer, thermal, and mechanical properties of a typical laminate and comparing the results with the Monte Carlo simulation method and experimental data. The important observation is that the computational simulation for probabilistic composite mechanics has sufficient flexibility to capture the observed scatter in composite properties.

Network based parallelism of probabilistic composite structural analysis

Probabilistic structural analysis (PSA) is essential to ascertain the reliability of composite structures to meet the challenge posed by future aeropropulsion systems. The probabilistic method should account for all naturally-occurring uncertainties including those in constituent material properties, fabrication variables, structure geometry and loading conditions. In this paper, parallel computing of probabilistic structural analysis is described and demonstrated to reduce the computational time. The parallelism is accomplished by integrating the computer code IPACS (Integrated Probabilistic Assessment of Composite Structures) with a software system PVM (Parallel Virtual Machine) for heterogeneous concurrent computing in network based computing environments. NASA Lewiss LACE (Lewis Advanced Cluster Environment) computer system which combines 33 IBM Risk/6000 workstations is the testbed for the study and Ethernet system is used for message passing. Two composite structures are analyzed using a probabilistic method with parallel computing for demonstration. It is found that turnaround times of peak-hour runs range from one to two and half times of that of benchmark run in this study. Using 32 workstations for parallel computing, about 90% turnaround time reduction of benchmark run and about 70 to 80% turnaround time reduction of peak-hour cases (comparing with the time of benchmark run using single workstation) can be achieved. It is also found that additional computational time reduction is insignificant (2%) when workstations are increased from seventeen to thirty two. This is because of data transfer congestion. Therefore high speed data transfer system such as FDDI (Fiber Distributed Data Interface) interface (which is ten times faster than Ethernet system) is recommended. Overall, it is concluded that network based parallelism is an efficient and effective approach to speed up the PSA computation.

Multidisciplinary tailoring of hot composite structures

A computational simulation procedure is described for multidiscipllnary analysis and tailoring of layered multi-material hot composite engine structural components subjected to simultaneous multiple discipline-specific thermal, structural, vibration, and acoustic loads. The effect of aggressive environments is also simulated. The simulation is based on a three dimensional finite element analysis technique in conjunction with structural mechanics codes, thermal/acoustic analysis methods, and tailoring procedures. The integrated multidisciplinary simulation procedure is general-purpose including the coupled effects of nonlinearities in structure geometry, material, loading, and environmental complexities. The composite material behavior is assessed at all composite scales, i.e., laminate/ply/constituents (fiber/matrix), via a nonlinear material characterizationhygro-thermo-mechanical model. Sample tailoring cases exhibiting nonlinear material loading environmental behavior of aircraft engine fan blades, are presented. The various multidisciplinary loads lead to different tailored designs, event hose competing with each other, as in the case of minimum material cost versus minimum structure weight and in the case of minimum vibration frequency versus minimum acoustic noise.