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Critical linear buckling load calculation is one of the possible ways to check structural stability. Structural analysis programs usually model beams and columns with just one element, but this is not enough to obtain an accurate value of the critical buckling load when the buckling mode is associated with an effective length that is less than twice the element length. This paper presents a method for the accurate calculation of the buckling load of frames modeled with only one finite element per structural element. For this purpose, a local correction is applied to some elements a few times until convergence is achieved. The validity of the presented method is confirmed by several examples ranging from simple canonical cases to large structures.

Composite moulds constitute an attractive alternative to classical metallic moulds when used for components fabricated by processes such as Resin Transfer Moulding (RTM). However, there are many factors that have to be accounted for if a correct design of the moulds is sought after. In this paper, the Finite Element Method (FEM) is used to help in the design of the mould. To do so, a thermo-electrical simulation has been performed through MSC-Marc in the preheating phase in order to ensure that the mould is able to be heated, through the Joule’s effect, according to the thermal cycle specified under operating conditions. Mean temperatures of 120 °C and 100 °C are predicted for the lower and upper semi-mould parts, respectively. Additionally, a thermo-electrical-mechanical calculation has been completed with MSC-Marc to calculate the tensile state along the system during the preheating stage. For the filling phase, the filling process itself has been simulated through RTM-Worx. Both the uniform- and non-uniform temperature distribution approaches have been used to assess the resulting effect. It has been found that this piece of software cannot model the temperature dependency of the resin and a numerical trick must have been applied in the second case to overcome it. Results have been found to be very dependent on the approach, the filling time being 73% greater when modelling a non-uniform temperature distribution. The correct behaviour of the mould during the filling stage, as a consequence of the filling pressure, has been also proved with a specific mechanical analysis conducted with MSC-Marc. Finally, the thermo-elastic response of the mould during the curing stage has been numerically assessed. This analysis has been made through MSC-Marc, paying special attention to the curing of the resin and the exothermic reaction that takes place. For the sake of accuracy, a user subroutine to include specific curing laws has been used. Material properties employed are al

In this paper, the design and validation of a heat storage device based on phase change materials are presented, with the focus on improving the thermal control of micro-satellites. The main objective of the development is to provide a system that is able to keep electronics within safe temperature ranges during the operation of manoeuvres, while reducing mass and volume in comparison to other thermal control techniques. Due to the low thermal conductivity of phase change materials, the conductivity of the device as a whole is one of the major challenges of the development. This issue has been solved by means of the use of a lattice of aluminium fins. The thermal behaviour of the proposed solution is assessed with numerical simulation tools, and the results prove that the developed phase change material-based thermal control technique is able to provide the suitable integrated thermal management of micro-satellites. Fabrication challenges found in the project are also explained. Numerical results are validated through a testing stage. The predicted temperature profiles are in good agreement with experimental data and inside the range foreseen for the heat storage device.

The high cooling rates reached during metal additive manufacturing (MAM) generate microstructures very different from those obtained by other conventional manufacturing methods. Therefore, research about the modeling of this type of microstructure is of great interest to the MAM community. In this work, the prediction of the lamellar spacing of an AlSi10Mg sample manufactured by laser powder bed fusion (LPBF), is presented. A multiscale approach is used, combining a CALPHAD (Computer Coupling of Phase Diagrams and Thermochemistry) model to predict the material properties, with a macroscale model of the sample manufacturing and with a microscale model to predict the microstructure. The manufacturing and metallographic characterization of the sample is also included. The results prove that the multiscale strategy followed is a valid approximation to simulate this type of manufacturing process. In addition, it is shown that the use of a generic simulation software focused on metal casting processes can be useful in predicting the lamellar spacing of the microstructure manufactured by LPBF. Finally, the relationship between the cooling rate and the resulting lamellar spacing has been established for this AlSi10Mg under the specific manufacturing conditions considered.

Ground thermal tests are always mandatory before any space mission is flown into space. The collected results of these tests are mainly temperatures of the different parts of the spacecraft (nodes) for different mission scenarios. The measured temperatures always show differences with the expected values coming from the computer thermal mathematical models. The origin of these differences is partially related to the inherent error coming from physical measurements. The thermal parameters that compose the computer thermal mathematical models must always be correlated with the results coming from tests. This paper studies, through three thermal models, the difficulties that are found in the correlation process when the measured temperatures reach a certain level of error. Thermal parameters become more difficult to be identified when the measurement error level increases. However, the temperature fields obtained with these poor thermal parameters are good enough for the mission thermal analysis. Several error levels, different load cases and correlation for steady-state and transient cases are studied to probe these findings.

There are always differences between the computer predicted temperatures of a spacecraft thermal model and the temperatures measured during the mandatory laboratory thermal tests. As a consequence, the model must be correlated before the spacecraft is launched to space, in order to identify the correct parameters that match the experimentally measured temperatures. A new technique is presented to identify the parameters, based on the minimization of the error of the transient equations which governs the heat transfer in the spacecraft. The steady state minimization was pre-sented in a previous work, but the transient techniques presented hereafter enable a better and more extended identification of parameters despite the higher complexity of the computational problem. The use of a set of available subroutines (TOLMIN), which permits the constrained optimization of a general function, makes possible to ensure that the obtained parameters are non-negative, a requirement to have physical sense. The gradient function must be calculated for each problem, but this can be done automatically. Results show that for small and medium size transient Thermal Mathematical Models (TMM), a good corre-lation of thermal parameters can be achieved even if some of the nodes temperatures are not measured in the thermal tests.

Simulation is a very useful tool in the design of the part and process conditions of high-pressure die casting (HPDC), due to the intrinsic complexity of this manufacturing process. Usually, physics-based models solved by finite element or finite volume methods are used, but their main drawback is the long calculation time. In order to apply optimization strategies in the design process or to implement online predictive systems, faster models are required. One solution is the use of surrogate models, also called metamodels or grey-box models. The novelty of the work presented here lies in the development of several metamodels for the HPDC process. These metamodels are based on a gradient boosting regressor technique and derived from a physics-based finite element model. The results show that the developed metamodels are able to predict with high accuracy the secondary dendrite arm spacing (SDAS) of the cast parts and, with good accuracy, the misrun risk and the shrinkage level. Results obtained in the predictions of microporosity and macroporosity, eutectic percentage, and grain density were less accurate. The metamodels were very fast (less than 1 s); therefore, they can be used for optimization activities or be integrated into online prediction systems for the HPDC industry. The case study corresponds to several parts of aluminum cast alloys, used in the automotive industry, manufactured by high-pressure die casting in a multicavity mold.

The main objective of this study is to establish a fire protection design method for pultruded Glass Fiber Reinforced Polymer (GFRP) structures exposed to fire. The method is based on the development of tables similar to those already available for steel structures. The structural designer may use these tables to determine the minimum required thickness (of any type of insulation), so that the structure maintains its mechanical properties above the over-dimensioning coefficient. The method used to draw up these tables follows four steps; i) First, the limit temperatures are determined or the temperature ranges within which the application of pultruded GFRP is permitted; ii) Second, the behavior of certain physical properties (density, specific heat, thermal conductivity, emissivity…) are defined as a function of the temperature; iii) Third, the method to determine the fire resistance temperature of the pultruded profile sections is defined; iv) Finally, the mechanical properties and ultimate resistance values of these profiles at different temperatures are also estimated. The behavior of the mechanical properties is analyzed as a function of the massivity of each section and the ratio between the thermal conductivity of the insulation and its thickness. In addition, a practical example is given of the application of the tables to a pultruded GFRP structure

The use of optimization algorithms to adjust the numerical models with experimental values has been applied in other fields, but the efforts done in metal casting sector are much more limited. The advances in this area may contribute to get metal casting adjusted models in less time improving the confidence in their predictions and contributing to reduce tests at laboratory scale. This work compares the performance of four algorithms (compass search, NEWUOA, genetic algorithm (GA) and particle swarm optimization (PSO)) in the adjustment of the metal casting simulation models. The case study used in the comparison is the multiscale simulation of the hypereutectic ductile iron (SGI) casting solidification. The model fitting criteria is the value of the tensile strength. Four different situations have been studied: model fitting based in 2, 3, 6 and 10 variables. Compass search and PSO have succeeded in reaching the error target in the four cases studied, while NEWUOA and GA have failed in some cases. In the case of the deterministic algorithms, compass search and NEWUOA, the use of a multiple random initial guess has been clearly beneficious.

216 p., Los tratamientos de superficie basados en tecnologías de plasma ofrecen un amplio abanico de posibilidades para el desarrollo de soluciones a problemas tribológicos (fricción, desgaste, etc.). Por otra parte, la combinación del desarrollo de procesos de tratamiento y recubrimiento basados en tecnología de plasma con técnicas de estudio de las propiedades electro-tribológicas, donde además de las propiedades tribológicas se monitorizan propiedades eléctricas tales como la resistencia de contacto eléctrica, ofrece una potencialidad añadida, especialmente para i) monitorizar en línea de forma continua el estado y deterioro de las superficies en contacto; y ii) estudiar el comportamiento de los recubrimientos en aplicaciones eléctricas, p.ej. en superficies conductoras o dieléctricas en movimiento relativo.En esta línea, se han investigado en el marco de la tesis procesos de tratamiento de nitruración por plasma con rejilla activa y efecto de cátodo hueco sobre aleaciones austeníticas y martensíticas de acero inoxidable, con el objeto de lograr un mejor compromiso entre las propiedades tribológicas y de resistencia a la corrosión. En este caso, se han estudiado las propiedades electro-tribológicas como una posible técnica de monitorización de forma continua del estado de la superficie.Adicionalmente, se ha investigado el comportamiento electro-tribológico de recubrimientos conductores eléctricos y dieléctricos depositados mediante la técnica de PVD por magnetron sputtering (MS-Physical Vapour Deposition), destinados a aplicaciones eléctricas en componentes en movimiento relativo. En el primer caso, recubrimientos conductores eléctricos, se han estudiado capas de AgAl tanto en cuanto a su comportamiento tribológico como a su deterioro en condiciones de inmersión en aceite aislante, realizándose una comparativa respecto al comportamiento al aire. En el segundo, recubrimientos dieléctricos, se han estudiado recubrimientos semi-diamantinos (Dimanod Like Carbon - DLC), en di

251 p., Las condiciones ambientales en el espacio exterior son muy extremas. Por ello cualquier equipo que es enviado al espacio cuenta con un sistema de control térmico (TCS) cuyo propósito es mantener los distintos componentes del equipo dentro de sus intervalos admisibles de temperatura. El diseño del TCS se realiza mediante modelos térmicos matemáticos (TMMs). Uno de los requerimientos que debe cumplir, es la correlación de los resultados de los TMMs con los resultados obtenidos en los ensayos térmicos. Se entiende por correlación la correspondencia entre las predicciones obtenidas de los TMMs y las temperaturas medidas en los ensayos térmicos.En esta tesis se ha desarrollado un método innovador, basado en un algoritmo genético, que permite realizar la correlación de los TMMs de sistemas espaciales de un modo semi-automatizado. Para ello se ha desarrollado el programa GAC-TM, el cual permite realizar la correlación entre los TMMs y los resultados de los ensayos térmicos de modo semiautomático, para modelos correspondientes a casos estacionarios o transitorios. GAC-TM permite realizar la correlación simultánea de distintos casos de funcionamiento del vehículo espacial con el objeto de mejorar la calidad de los resultados. Además de los casos de validación, se han realizado algunos análisis complementarios con el objeto de profundizar en la problemática de la correlación de TMMs y en el comportamiento del algoritmo desarrollado

The correlation of the thermalmathematical models (TMMs) of spacecrafts with the results of the thermal test is a demanding task in terms of time and effort. Theoretically, it can be automatized by means of optimization techniques, although this is a challenging task. Previous studies have shown the ability of genetic algorithms to perform this task in several cases, although some limitations have been detected. In addition, gradient-based methods, although also presenting some limitations, have provided good solutions in other technical fields. For this reason, the performance of genetic algorithms and gradient-based methods in the correlation of TMMs is discussed in this paper to compare the pros and cons of them. The case of study used in the comparison is a real space instrument flown aboard the International Space Station.