Lifetime Prediction of Rocket Combustion Chamber Wall by Means of Viscoplasticity Coupled With Ductile Isotropic Damage

This paper presents the application of a viscoplastic damage model for the lifetime prediction of a typical rocket combustion chamber structure. The material modeling is motivated by extension of the classical rheological model for elastoplasticity with Armstrong-Frederick kinematic hardening into a viscoplastic model. The coupling with damage is performed using the concept of effective stress and the principle of strain equivalence. The material parameters are identified based on experimental results for the high temperature copper alloy NARloy-Z, which is one of the typical combustion chamber wall materials. Finally the applicability of the model will be shown by means of sequentially coupled thermomechanical analyses.

Numerical Simulation of the Cold Spray Deposition Process for Aluminium and Copper

Cold spray is a rapidly developing coating technology for depositing materials in the solid state. In this deposition process, the spray particles are accelerated to a high velocity by a high-speed gas flow, and then form a dense and high quality coating due to plastic deformation of particles impinged upon the solid surface of substrate. 2D and 3D modelling of particle impacting behaviours in cold spray deposition process by using ABAQUS/Explicit was conducted for four couples of materials (i.e. impacting particle/impacted substrate): copper/aluminium, aluminium/copper, copper/copper, and aluminium/aluminium. A systematic analysis of a single impact was carried out considering different parameters, such as the initial impact velocity, initial temperature and contact angle, which affect the deposition process and subsequently the mechanical properties of coating. Three numerical methods have been evaluated and their performances are discussed for various simulation settings: (i) modelling in a Lagrangian reference frame; (ii) modelling using adaptive remeshing in an Arbitrary Lagrangian Eulerian (ALE) reference frame; and (iii), modelling in a CEL reference frame. It is found that the Coupled Eulerian Lagrangian (CEL) method has more advantages to simulate the large deformation of materials, and is also more efficient to prevent the excessive distortion of the mesh. A comparison between simulation results and experimental data from the literature was performed. Nevertheless, the CEL method is implicitly isothermal for ABAQUS v6.10, whereas the modelling in the classical Lagrangian reference frame does include coupled thermo-mechanical effects with a local increase of the temperature near the interface — due to friction — and for the highly plastically deformed elements — due to the heat dissipation linked to plasticity. A local rise of temperature at the impact surface may also be observed for oblique impacts. Finally a first attempt to simulate the deposition of several particles is made with a 3D CEL model, resulting in the creation of porosity at the interface between particles.

A Regression Based Non-Intrusive Method Using Separated Representation for Uncertainty Quantification

This paper aims at handling high dimensional uncertainty propagation problems by proposing a tensor product approximation method based on regression techniques. The underlying assumption is that the model output functional can be well represented in a separated form, as a sum of elementary tensors in the stochastic tensor product space. The proposed method consists in constructing a tensor basis with a greedy algorithm and then in computing an approximation in the generated approximation space using regression with sparse regularization. Using appropriate regularization techniques, the regression problems are well posed for only few sample evaluations and they provide accurate approximations of model outputs.

Optimum Mandrel Configuration for Efficient Down-Hole Tube Expansion

In the last decade, traditional tube expansion process has found an innovative application in oil and gas well drilling and remediation. The ultimate goal is to replace the conventional telescopic wells to mono-diameter wells with minimum cost, which is still a distant reality. Further to this, large diameters are needed at terminal depths for enhanced production from a single well while keeping the power required for expansion and related costs to a minimum. Progress has been made to realize slim wells by driving a rigid mandrel of a suitable diameter through the tube either mechanically or hydraulically to attain a desirable expansion ratio. This paper presents a finite element model which predicts the drawing force for expansion, the stress field in expanded and pre/post expanded zones, and the energy required for expansion. Through minimization of energy required for expansion, an optimum mandrel configuration i.e. shape, size and angle was obtained which can be used to achieve larger in-situ expansion. It is found that mandrel with elliptical, hemispherical and curved conical shapes have minimum resistance during expansion as compared to the widely used circular cross section mandrel with a cone angle of 10°. However, further manipulation of shape parameters of the circular cross section mandrel revealed an improved efficiency. The drawing force required for expansion reduces by 7% to 10% having minimum dissipated energy during expansion. It is also found that these cones yield less reduction in tube thickness after expansion, which results in higher post-expansion collapse strength. In addition, rotating a mandrel further reduces the energy required for expansion by 7%.

Optimization of the Global Static and Dynamic Performance of a Vehicle Body by Means of Response Surface Models

Concept FE models of the vehicle structure are often used to optimize it in terms of static and dynamic stiffness, as they are parametric and computationally inexpensive. On the other hand they introduce modeling errors with respect to their detailed FE equivalents due to the simplifications made. Even worse, the link between the concept and the detailed FE model can be sometimes lost after optimization. The aim of this paper is to present and validate an alternative optimization approach that uses the detailed FE model of the vehicle body-in-white instead of its concept representation. Structural modifications of this model were applied in two different ways — by local joint modifications and by using mesh morphing techniques. The first choice was motivated by the strong influence of the structural joints on the global vehicle performance. For this type of modification the plate thicknesses of the most influent car body joints were changed. In the second case the overall car dimensions were modified. The drawback of using detailed FE models of the vehicle body is that they can be times bigger than their concept counterparts and can thus require considerably more time for structural analysis. To make the approach proposed in this work a feasible alternative for optimization in the concept phase response surface models were introduced. With them the global static and dynamic performance of the body-in-white was represented by means of approximating polynomials. Optimization on such mathematical models is fast, so the choice of the optimization algorithm is not limited only among local-search strategies. In the current study Genetic Algorithm was used to increase the chances for finding better design alternatives. Two different optimization problems were defined and solved. Their final solutions were presented and compared in terms of structural modifications and resulting responses. The approach in this paper can be successfully used in the concept phase as it is fast and reliable and at the same time it avoids the problems typical for concept models.

Advanced Optimization of Industrial Large-Scale Roll-to-Roll Systems Under Parametric Uncertainties

In industrial plants some parameters can not be evaluated properly or they are varying with time. These parametric uncertainties has to be taken into account during the design process of industrial systems. In this work, the developped optimization approach is applied on an industrial roll-to-roll sytem. Such systems are commonly used to handle materials as polymer, metal, paper and textile. The key challenge is to move the web at the expected speed while maintaining the web tension in an acceptable range around its reference. Moreover, the Young’s modulus of the web is difficult to evaluate and it is varying with time due to temperature and moisture variations. This paper deals with the web tension controller synthesis on a large-scale roll-to-roll system with uncertain Young’s modulus. To synthesize web tension controllers, an H∞ approach is applied and adapted to the system with parametric uncertainties using multi-objective robust design optimization.

Effects of Actuators and Sensors Position on Independent Modal Control Performance

Independent modal control technique allows to change the eigenvalues of a system, without changing its eigenvectors. From a mechanical point of view, it means it is possible to modify the natural frequencies and the damping of a n-DoF system, letting modal shapes unchanged. Independent modal control can be profitably used in active vibration control increasing the damping of the system without changing its natural frequencies and vibration modes. A control of this type can improve the dynamic performance, reduce the vibratory phenomenon (and the resulting acoustic noise) and increase the fatigue strength of the system. This work demonstrates how the performance of the control depends on the number and position of sensors and actuators used besides, obviously, on the reduced model used to synthesize the control itself. Finally the paper suggests a simple optimum function to minimize the spillover effects due to unmodeled modes. Theoretical aspects are supported by numerical simulations.

Identification of a Steady-State Flow in Porous Media Using Artificial Neural Networks

For a steady state convection problem, assuming given concentration field values in a few measurement points and hydraulic head values in the same piezometers, the source of the concentration, and its intensity are deduced using Artificial Neural Networks (ANNs). ANNs are trained with data extracted from Finite Difference (FD) solution of a classical convection problem for small Peclet number. The numerical analysis is exemplified for vanishing, homogeneous and non-homogeneous field of velocity. It is shown that the diffusivity vector can also be identified. The complexity of the problem is discussed for each studied case.

Visualization of Urban Prediction Using Augmented Maps

In this paper, we explore a visualization method using augmented maps for urban prediction. Our implementation allows users to determine the location for prediction in a paper map. As an application example, we examine an area before and after new train station is built. We use the difference between two maps for simulating the changes or predicting the impact if a new train station is built on a location in a paper map. In off-line phase, we gather knowledge data from several reference locations by comparing two aerial maps (before and after the train station is built). We then analyze the difference of green spaces between those two maps using color extraction. We observe that the green space around the new train station mostly decreases due to the area development. This information is then stored for prediction reference. In on-line phase, we use a monocular setup that consists of one camera and a monitor display. A paper map is captured using a web camera and tracked using its geometrical features. These features can be provided using the available data from Geographical Information Systems (GIS) or automatically extracted from the texture. The map is then matched with the reference map in database. When the map is matched, we can overlay the simulation on how the green space will change due to the existence of new train stations on a new location inputted by the user.

Electromechanical Coupled Response of the AC Electric Arc Furnace Structures During the Scrap Melting Process

Prediction of structural dynamics of the Electric Arc Furnace (EAF) is rather difficult, because of a number of phenomena occurring during the scrap melting process. Three large electrodes, corresponding to each phase of a AC circuit, are lowered by the main mast towards the scrap to activate the melting process, induced by the electric arc. Electric current fed to each electrode produces a strong magnetic field and applies an electromechanical force on the other electrodes. Arc voltage looks irregular upon time, even because of the scrap motion within the vessel and temperature growth. The vertical position of the mast is controlled by an hydraulic actuator. Nevertheless, a heavy vibration of the structures affects the regularity of the melting process. A fully coupled model of the whole system is herein proposed, through a multi-physics approach. A first analytical approach, describing the electric circuit of the whole system, is implemented into a Multi Body Dynamics (MBD) model of the EAF, while a reduced Finite Element Method (FEM) model of the flexible structures is used for a preliminary optimization of the design parameters. Electromechanical forces due to the mutual induction among the electrodes are computed and the dynamic response of the system is investigated. Proposed model allows a first refinement of the EAF design, although a complete experimental validation on the real machine has to be performed, in spite of problems due the extremely difficult accessibility of structures during the melting process.