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The purpose of this paper is to present the status of the on-going development of the new computerized environment for aircraft synthesis and integrated optimization methods (CEASIOM) and to compare results of different aerodynamic tools. The concurrent design of aircraft is an extremely interdisciplinary activity incorporating simultaneous consideration of complex, tightly coupled systems, functions and requirements. The design task is to achieve an optimal integration of all components into an efficient, robust and reliable aircraft with high performance that can be manufactured with low technical and financial risks, and has an affordable life-cycle cost.

CEASIOM (www.ceasiom.com) is a framework that integrates discipline-specific tools like computer-aided design, mesh generation, computational fluid dynamics (CFD), stability and control analysis and structural analysis, all for the purpose of aircraft conceptual design.

A new CEASIOM version is under development within EU Project AGILE (www.agile-project.eu), by adopting the CPACS XML data-format for representation of all design data pertaining to the aircraft under development.

Results obtained from different methods have been compared and analyzed. Some differences have been observed; however, they are mainly due to the different physical modelizations that are used by each of these methods.

This paper summarizes the current status of the development of the new CEASIOM software, in particular for the following modules: CPACS file visualizer and editor CPACSupdater (Matlab) Automatic unstructured (Euler) & hybrid (RANS) mesh generation by sumo Multi-fidelity CFD solvers: Digital Datcom (Empirical), Tornado (VLM), Edge-Euler & SU2-Euler, Edge-RANS & SU2-RANS Data fusion tool: aerodynamic coefficients fusion from variable fidelity CFD tools above to compile complete aero-table for flight analysis and simulation.

We investigate the application of a least squares finite element method for the solution of fluid flow problems. The least squares finite element method is based on the minimization of the L2 norm of the equation residuals. Upon discretization, the formulation results in a symmetric, positive definite matrix system which enables efficient iterative solvers to be used. The other motivations behind the development of least squares finite element methods are the applicability of higher order elements and the possibility of using the norm associated to the least squares functional for error estimation. For steady incompressible flows, we develop a method employing linear and quadratic triangular elements and compare their respective accuracy. For steady compressible flows, an implicit conservative least squares scheme which can capture shocks without the addition of artificial viscosity is proposed. A refinement strategy based upon the use of the least squares residuals is developed and several numerical examples are used to illustrate the capabilities of the method when implemented on unstructured triangular meshes.

The purpose of this paper is to conduct a survey on research in fabric and cloth simulation using mass spring model. Also in this paper some of the common methods in process of fabric simulation in mass spring model are discussed and compared.

This paper reviews and compares presented mesh types in mass spring model, forces applied on model, super elastic effect and ways to settle the super elasticity problem, numerical integration methods for solving equations, collision detection and its response. Some of common methods in fabric simulation are compared to each other. And by using examples of fabric simulation, advantages and limitations of each technique are mentioned.

Mass spring method is a fast and flexible technique with high ability to simulate fabric behavior in real time with different environmental conditions. Mass spring model has more accuracy than geometrical models and also it is faster than other physical modeling.

In the edge of digital, fabric simulation technology has been considered into many fields. 3D fabric simulation is complex and its implementation requires knowledge in different fields such as textile engineering, computer engineering and mechanical engineering. Several methods have been presented for fabric simulation such as physical and geometrical models. Mass spring model, the typical physically based method, is one of the methods for fabric simulation which widely considered by researchers.

The goal for this paper is to bring the easy‐to‐use geometry drawing software RDS to a “solid” mesh, which could be analyzed and simulated in CEASIOM, to enhance both CEASIOM and RDS's capabilities.

The RDS‐SUMO interface is developed based on the feature that both RDS and SUMO define their geometric model using cross‐sectional information, i.e. their “universe” shapes are close to each other.

The translation is automated and allows the engineer to easily modify and augment the geometry in the process. Two test cases are shown, with their high quality Euler mesh and CFD computations. The A321‐look‐alike test case tests the mesh quality for transonic aerodynamics, such as high‐speed trim and drag divergence; the twin‐prop asymmetric aircraft is a “diffi+cult” non‐conventional configuration analyzed for yaw stability in one‐engine out mode.

This paper shows that the CFD solutions based on solid grids could be obtained once the design is proposed and the RDS wire‐frame model is available. The aerodynamic properties can then be predicted in early design stage, which is very efficient for preliminary aircraft design.

This fast meshing tool could obtain “working” grids of a new design within hours.

An implicit method for the solution of transonic flows modelled by the time‐dependent Euler equations is presented. The method is characterized by a robust linearization for first‐ and second‐order versions of Roe's flux‐difference splitting scheme, an implicit treatment of the boundary conditions and the implementation of an adaptive grid strategy for global efficiency. The performance of the method is investigated for the GAMM test circular‐arc bump configuration and for the RAE 2822 aerofoil.

An upwind unstructured grid cell‐centred scheme for the solution of the compressible Euler and Navier‐Stokes equations in two dimensions is presented. The algorithm employs a finite volume formulation. Calculation of the inviscid fluxes is based on the approximate Riemann solver of Roe. Viscous fluxes are obtained from solution gradients computed by a variational recovery procedure. Higher order accuracy is achieved through performing a monotonic linear reconstruction of the solution over each cell. The steady state is obtained by a point implicit time integration of the unsteady equations using local time stepping. For supersonic inviscid flow an alternative space marching algorithm is proposed. This latter approach is applicable to supersonic flow fields containing regions of local subsonic flow. Numerical results are presented to show the performance of the proposed scheme for inviscid and viscous flows.

A collaborative design environment is needed for multidisciplinary design optimization (MDO) process, based on all the modules those for different design/analysis disciplines, and a systematic coupling should be made to carry out aerodynamic shape optimization (ASO), which is an important part of MDO.

Computerized environment for aircraft synthesis and integrated optimization methods (CEASIOM)-ASO is developed based on loosely coupling all the existing modules of CEASIOM by MATLAB scripts. The optimization problem is broken down into small sub-problems, which is called “sequential design approach”, allowing the engineer in the loop.

CEASIOM-ASO shows excellent design abilities on the test case of designing a blended wing body flying in transonic speed, with around 45 per cent drag reduction and all the constraints fulfilled.

Authors built a complete and systematic technique for aerodynamic wing shape optimization based on the existing computational design framework CEASIOM, from geometry parametrization, meshing to optimization.

CEASIOM-ASO provides an optimization technique with loosely coupled modules in CEASIOM design framework, allowing engineer in the loop to follow the “sequential approach” of the design, which is less “myopic” than sticking to gradient-based optimization for the whole process. Meanwhile, it is easily to be parallelized.