Sylvie Castagne

Numerical Method for Cost-Weight Optimization of Stringer-Skin Panels

The presented work addresses the need to integrate cost into the early product definition process as an engineering parameter. The methodology developed is generic and fundamental in developing causal predictions of manufacturing cost that are driven by the design parameters which give rise to the main elements of that cost relative to process capability. The manufacturing cost modelling is original and relies on a genetic-causal method of 1) classifying the generic cost elements that are linked to particular genetic identifiers relating to materials, processes and form; 2) developing causal parametric relations that link those genetic identifiers to a parent manufacturing cost. The application studied is a fuselage panel that is typical to commercial transport regional jets. Consequently, a semi-empirical numerical analysis using ESDU reference data was coupled to model the structural integrity of thin-walled structures with regard to material failure and buckling: skin, stringer, flexural and inter-rivet. The optimisation process focuses on Direct Operating Cost (DOC) as a function of acquisition cost and fuel burn. It was found that the ratio of acquisition cost to fuel burn was typically 4:3 and that there was a 10% improvement on the DOC for the minimal DOC condition over the minimal weight condition; due to the manufacturing cost saving from having a reduced number of larger- area stringers and a slightly thicker skin than preferred by the minimal weight condition. It is also noteworthy that the minimal manufacturing cost condition was slightly better than the minimal weight condition, which highlights the key finding: the traditional minimal weight condition is a dated and sub-optimal approach to airframe structural design.

Integrating Aircraft Cost Modeling into Conceptual Design

The article presents cost modeling results from the application of the Genetic-Causal cost modeling principle. Industrial results from redesign are also presented to verify the opportunity for early concept cost optimization by using Genetic-Causal cost drivers to guide the conceptual design process for structural assemblies. The acquisition cost is considered through the modeling of the recurring unit cost and non-recurring design cost. The operational cost is modeled relative to acquisition cost and fuel burn for predominately metal or composites designs. The main contribution of this study is the application of the Genetic-Causal principle to the modeling of cost, helping to understand how conceptual design parameters impact on cost, and linking that to customer requirements and life cycle cost.

Aircraft Cost Modelling using the Genetic Causal Technique within a Systems Engineering Approach

The paper is primarily concerned with the modelling of aircraft manufacturing cost. The aim is to establish an integrated life cycle balanced design process through a systems engineering approach to interdisciplinary analysis and control. The cost modelling is achieved using the genetic causal approach that enforces product family categorisation and the subsequent generation of causal relationships between deterministic cost components and their design source. This utilises causal parametric cost drivers and the definition of the physical architecture from the Work Breakdown Structure (WBS) to identify product families. The paper presents applications to the overall aircraft design with a particular focus on the fuselage as a subsystem of the aircraft, including fuselage panels and localised detail, as well as engine nacelles. The higher level application to aircraft requirements and functional analysis is investigated and verified relative to life cycle design issues for the relationship between acquisition cost and Direct Operational Cost (DOC), for a range of both metal and composite subsystems. Maintenance is considered in some detail as an important contributor to DOC and life cycle cost. The lower level application to aircraft physical architecture is investigated and verified for the WBS of an engine nacelle, including a sequential build stage investigation of the materials, fabrication and assembly costs. The studies are then extended by investigating the acquisition cost of aircraft fuselages, including the recurring unit cost and the non-recurring design cost of the airframe sub-system. The systems costing methodology is facilitated by the genetic causal cost modeling technique as the latter is highly generic, interdisciplinary, flexible, multilevel and recursive in nature, and can be applied at the various analysis levels required of systems engineering. Therefore, the main contribution of paper is a methodology for applying systems engineering costing, supported by the genetic causal cost modeling approach, whether at a requirements, functional or physical level.

Integrating Manufacturing Cost and Structural Requirements in a Systems Engineering Approach to Aircraft Design

The paper addresses the issue of linking cost into the structural design process in order to meet customer requirement. Rather than only looking at manufacturing cost, Direct Operating Cost (DOC) is also considered in terms of the impact of weight on fuel burn, in addition to the acquisition cost to be born by the operator. Ultimately, there is a trade-off between driving design according to minimal weight and driving it according to reduced manufacturing cost. The analysis of cost is facilitated with a Genetic-Causal cost modelling methodology and the structural analysis is driven by numerical expressions of appropriate failure modes that utilize ESDU reference data. However, a key contribution of the paper is to investigate the modelling of uncertainty and to perform a sensitivity analysis to investigate the robustness of the optimization methodology. Stochastic distributions are used to characterize manufacturing cost distributions and Monte Carlo analysis is performed in modelling the impact of uncertainty on the cost modelling. The results are then used in a sensitivity analysis that incorporates the optimization methodology. In addition to investigating manufacturing cost variance, the sensitivity of the optimization to fuel burn cost and structural loading are also investigated. It is found that the consideration of manufacturing cost does make an impact and results in a different optimal design configuration from that delivered by the minimal weight method. However, it was shown that at lower applied loads there is a threshold fuel burn cost at which the optimization process wishes to reduce weight, this threshold decreasing with increasing load. The new optimal solution results in lower DOC with a predicted saving of 660

Computational model for predicting the effect of process parameters on surface characteristics of mass finished components

/m

Finite element modelling of superplastic-like forming using a dislocation density-based model for AA5083

Purpose – Mass finishing is a commonly employed surface finishing process for improving surface characteristics of aerospace engineering components. Optimization of surface characteristics of such critical components require an explicit computational model that can describe the surface characteristics of the finished component. The purpose of this paper is to develop an explicit computational model that can describe the surface roughness as a function of various process parameters which influence the mass finishing process. Design/methodology/approach – In the present work, the authors propose to study the roughness characteristics using a combined evolutionary computing approach based on Multi-Adaptive Regression Splines and Genetic Programming (GP) techniques. Findings – The authors conducted sensitivity and parametric analysis to capture the dynamics of surface characteristics by unveiling dominant input variables and hidden non-linear relationships. It is found that by regulating the process time and ...

Application of a Damage Model to an Aluminum Alloy

Superplastic-like forming is a newly improved sheet forming process that combines the mechanical pre-forming (also called hot drawing) with gas-driven blow forming (gas forming). Non-superplastic grade aluminium alloy 5083 (AA5083) was successfully formed using this process. In this paper, a physical-based material model with dislocation density and vacancy concentration as intrinsic foundations was employed. The model describes the overall flow stress evolution of AA5083 from ambient temperature up to 550??C and strain rates from 10?4 up to 10?1?s?1. Experimental data in the form of stress?strain curves were used for the calibration of the model. The calibrated material model was implemented into simulation to model the macroscopic forming process. Hereby, finite element modelling (FEM) was used to estimate the optimum strain-rate forming path, and experiments were used to validate the model. In addition, the strain-rate controlled forming was conducted for the purpose of maintaining the gas forming with an average strain rate of 2???10?3?s?1. The predicted necking areas closely approximate the localized thinning observed in the part. Strain rate gradients as a result of geometric effects were considered to be the main reason accounting for thinning and plastic straining, which were demonstrated during hot drawing and gas forming by simulations.

Uncertainty and Sensitivity Analysis in Aircraft Operating Costs in Structural Design Optimization

An energy-based isotropic elastoplastic model coupled to damage is implemented in the finite element code LAGAMINE developed for more than fifteen years in the M&S department. In this model, based on the local approach of ductile fracture, effective stresses associated to damage variables are introduced. The damage law allows a continuous description of crack appearance. After a brief description of the model, its identification and its validation for an aluminum alloy are presented. Finally, the research of a global rupture criterion associated to this model is introduced.

Digital Lean Manufacturing (DLM) for Competitive Advantage

The paper focuses on the development of an aircraft design optimization methodology that models uncertainty and sensitivity analysis in the tradeoff between manufacturing cost, structural requirements, and aircraft direct operating cost. Specifically, rather than only looking at manufacturing cost, direct operating cost is also considered in terms of the impact of weight on fuel burn, in addition to the acquisition cost to be borne by the operator. Ultimately, there is a tradeoff between driving design according to minimal weight and driving it according to reduced manufacturing cost. The analysis of cost is facilitated with a genetic-causal cost-modeling methodology, and the structural analysis is driven by numerical expressions of appropriate failure modes that use ESDU International reference data. However, a key contribution of the paper is to investigate the modeling of uncertainty and to perform a sensitivity analysis to investigate the robustness of the optimization methodology. Stochastic distributions are used to characterize manufacturing cost distributions, and Monte Carlo analysis is performed in modeling the impact of uncertainty on the cost modeling. The results are then used in a sensitivity analysis that incorporates the optimization methodology. In addition to investigating manufacturing cost variance, the sensitivity of the optimization to fuel burn cost and structural loading are also investigated. It is found that the consideration of manufacturing cost does make an impact and results in a different optimal design configuration from that delivered by the minimal-weight method. However, it was shown that at lower applied loads there is a threshold fuel burn cost at which the optimization process needs to reduce weight, and this threshold decreases with increasing load. The new optimal solution results in lower direct operating cost with a predicted savings of 640/m 2 of fuselage skin over the life, relating to a rough order-of-magnitude direct operating cost savings of

Digital Design Synthesis of Virtual Lean Manufacture

500,000 for the fuselage alone of a small regional jet. Moreover, it was found through the uncertainty analysis that the principle was not sensitive to cost variance, although the margins do change.