A rapid and automated computational approach to the design of multistable soft actuators

We develop an automated computational modeling framework for rapid gradient-based design of multistable soft mechanical structures composed of non-identical bistable unit cells with appropriate geometric parameterization. This framework includes a custom isogeometric analysis-based continuum mechanics solver that is robust and end-to-end differentiable, which enables geometric and material optimization to achieve a desired multistability pattern. We apply this numerical modeling approach in two dimensions to design a variety of multistable structures, accounting for various geometric and material constraints. Our framework demonstrates consistent agreement with experimental results, and robust performance in designing for multistability, which facilities soft actuator design with high precision and reliability

Development of an automated simulation environment for Body in White joining techniques

Parts in the joining station are usually arranged and clamped to result in an assembly that perfectly resembles the CAD0 construction. The perfect set-up is usually determined with the help of numerical optimization. In reality there are imperfections specific for each part, which are usually adjusted in the workshop manually. To do numerical optimization for each part is computationally expensive. Here the need for a more efficient Data mining analysis method arises. The present thesis investigates the metamodeling techniques in order to approximate the geometry response to the change of the joining station parameters. The aim is to provide the evaluation of the model by interpolating between the geometry and station set-up variations. The suitable regressions, which are able to deal with non-linear geometry behaviour, are selected with the help of the literature research. The theory behind the numerical simulation, regressions and sampling is studied to ensure the right choice of the metamodel. An automated simulation environment is programmed to assist with the creation of variation in geometry and joining station, numerical solution and analysis. The chosen regressions - Support Vector Regression and Kernel Ridge Regression - are tested on models of different complexity. The errors are evaluated to provide the quantitative measure of the quality of regressions. Possible improvements of the metamodels are studied, such as Latin Hypercube sampling techniques. The reduced complexity metamodels proved to provide a good approximation, while dealing well with non-linearities. On the other hand, it was shown that models with many design variables require improvement in sampling technique to provide better result within reasonable computational costs. At the same time, Latin Hypercube did not provide visible advancements in the tested cases. The Automated Simulation Environment and the tested metamodels are a base for the future implementation of an Artificial Neural Networks for defining the perfect set-up of Body in White joining stations for imperfect parts

Flexural bending test of topology optimization additively manufactured parts

The aim of this work is to model, manufacture, and test an optimized Messerschmitt-BölkowBlohm beam using additive manufacturing. The implemented method is the Solid Isotropic Material with Penalization of a minimum compliance design. The Taubin smoothing technique was used to attenuate geometric noise and minimize the formation of overhanging angles and residual stresses due to the thermal activity of the selective laser melting process. The optimized model required examination and repair of local errors such as surface gaps, non-manifold vertices, and intersecting facets. A comparison between experimental and numerical results of the linear elastic regimes showed that the additively manufactured structure was less stiff than predicted. Potential contributors are discussed, including the formation of an anisotropic microstructure throughout the layer-by-layer melting process. In addition, the effect of selective laser melting process on the mechanical properties of stainless steel 316l-0407 and its influence on structural performance was described

Rapid tooling by integration of solid freedom fabrication and electrodepostion

Rapid tooling (RT) techniques based on solid freeform fabrication (SFF) are being studied worldwide to speed up the design-production cycle and thus keep manufacturers at a competitive edge. This dissertation presents a novel rapid tooling process that integrates SFF with electrodeposition to produce molds, dies, and electrical discharge machining (EDM) electrodes rapidly, accurately and cost effectively. Experimental investigation, thermornechanical modeling and analysis, as well as case studies reveal that integration of electroforming with solid freeform fabrication is a viable way for metal tool making. The major research tasks and results of this dissertation study are as follows: Rapid electroforming tooling (RET) process development and understanding. 3D CAD model design, metalization, electroforming, separation and backing are studied through experimental and analytical work. Methods of implementation based on the factors of tooling time, cost, and tooling accuracy are developed. Identification of inaccuracy factors in RET process and methods for improving tooling accuracy. The accuracy of the formed mold cavity or EDM electrode depends upon the material and geometry of the RP part, the properties of the electroformed metal, and process parameters. The thermal stress induced by the burnout process that removes the SFF part from the electroform is one of the major inaccuracy sources. Another one is the deformation generated by solidification of the molten metal that is used to back the electroform to form a solid mold cavity or an EDM electrode. FEM based thermomechanical modeling and analysis of the thermal stress during the SFF part burnout process has been performed. The model is implemented in ANSYS software. It is found that a stepped thermal load for the pattern burnout generates much smaller thermal stress than a ramped thermal load. The thermal stress is largely reduced when an SFF part is designed as a hollow or shelled structure\u27, or when the electroform thickness is increased. The wall thickness of SFF part is determined by two criteria. The wall thickness must be thin enough to guarantee that the thermal stresses are smaller than the yield strength of the electroformed metal. On the other hand, the wall thickness must also be large enough to resist the electroforming stress during the electroforming process. The electroform thickness is related to tooling time, cost and tool strength. Strain gage based thermal stress measurements demonstrate that the results obtained from the experiment accurately match the results obtained from the FEM-based thermornechanical analysis model. Thus the model can be used to predict the thermal stress induced during the burnout process. The established thermomechanical model and FEM based numerical simulation provide an effective method that determines the geometry of the SFF part and the electroform thickness for minimizing the manufacturing time and cost while satisfying the tooling accuracy requirement

Hydrodynamic effects on soiled surfaces : an experimental study and theoretical analysis

This thesis presents the findings of an investigation aimed at understanding the effects of hydrodynamic shear stress on soil removal from textile surfaces both inside the washing machine and in closely controlled laboratory conditions. The research has involved developing a technique for the indirect measurement of shear stress based on pressure recordings and small block probes that provide both an indication of shear stress magnitude and direction. The probes have been investigated and calibrated in a purpose-built, rectangular-section, water tunnel in which tests were also carried out on specially prepared soiled cotton textile samples. This has allowed the correlation between shear stress and soil removal efficiency for 15k ≤ Re ≤ 155k. A more general investigation involving the washing machine has also been carried out so as to quantify and compare the effects of detergency, water temperature, time, abrasion, warping and tangential shear force. The hydrodynamic conditions inside the washing machine were investigated providing insight into flow conditions both on the inside and outside of the wash load. This was achieved through the use of a wireless device in the form of a sphere with an on-board pressure-flow sensor and radio transmitter for remote monitoring via radio. This remote data acquisition system was designed, developed and patented by the author. A model of the wash load motion has also been developed and high speed filming techniques employed to qualify and quantify the wash load dynamics. The main outcome of the research may be summarised as follows: - Hydrodynamic shear stress up to 7.7Pa a circa (15k ≤ Re ≤ 155k) is inadequate to remove soil from the standard EMPA textile surfaces. - Only 10-15% of the soil removed in the washing machines can be attributed to abrasion, warping (due to churning) and hydrodynamic shear stress, the rest is attributed to detergency and heat transfer. - There are at least two different flow domains within a horizontal-axis washing machine, one on the inside of the wash load and one on the outside. - Flow conditions on both the inside and outside are turbulent and velocities up to several meters per second have been recorde

Finite element simulation of additive manufacturing with enhanced accuracy

Tesi en modalitat de compendi de publicacionsThis thesis develops numerical methods to improve the accuracy and computational efficiency of the part-scale simulation of Additive Manufacturing (AM) (or 3D printing) metal processes. AM is characterized by multiple scales in space and time, as well as multiple complex physics that occur in three-dimensional growing-in-time geometries, making its simulation a remarkable computational challenge. To this end, the computational framework is built by addressing four key topics: (1) a Finite Element technology with enhanced stress/strain accuracy including the incompressible limit; (2) an Adaptive Mesh Refinement (AMR) strategy accounting for geometric and solution accuracies; (3) a coarsening correction strategy to avoid loss of information in the coarsening AMR procedure, and (4) a GCodebased simulation tool that uses the exact geometric and process parameters data provided to the actual AM machinery. In this context, the mixed displacement/deviatoric-strain/pressure u/e/p FE formulation in (1) is adopted to solve incompressible problems resulting from the isochoric plastic flow in the Von Mises criterion typical of metals. The enhanced stress/strain accuracy of the u/e/p over the standard and u/p FE formulations is verified in a set of numerical benchmarks in iso-thermal and non-isothermal conditions. A multi-criteria AMR strategy in (2) is used to improve computational efficiency while keeping the number of FEs controlled and without the strictness of imposing the commonly adopted 2:1 balance scheme. Avoiding this enables to use high jumps on the refinement level between adjacent FEs; this improves the mesh resolution on the region of interest and keeps the mesh coarse elsewhere. Moving the FE solution from a fine mesh to a coarse mesh introduces loss of information. To prevent this, a coarsening correction strategy presented in (3) restores the fine solution in the coarse mesh, providing computational cost reduction and keeping the accuracy of the fine mesh solution accuracy. Lastly, design flexibility is one of the main advantages of AM over traditional manufacturing processes. This flexibility is observed in the design of complex components and the possibility to change the process parameters, i.e. power input, speed, waiting pauses, among others, throughout the process. In (4) a GCode-based simulation tool that replicates the exact path travelled and process parameters delivered to the AM machiney is developed. Furthermore, the GCode-based tool together with the AMR strategy allows to automatically generate an embedded fitted cartesian FE mesh for the evolving domain and removes the challenging task of mesh manipulation by the end-user. The FE framework is built on a high-performance computing environment. This framework enables to accelerate the process-to-performance understanding and to minimize the number of trial-and-error experiments, two key aspects to exploit the technology in the industrial environment.Esta tesis tiene como objetivo desarrollar métodos numéricos para mejorar la precisión y eficiencia computacionales en simulaciones de piezas fabricadas mediante Manufactura Aditiva (MA), también conocida como Impresión 3D. La manufactura aditiva es un problema complejo que involucra múltiples fenómenos físicos, que se desarolla en múltiples escalas, y cuya geometría evoluciona en el tiempo. Para tal fin, se plantean cuatro objetivos: (1) Desarrollo de una tecnología de elementos finitos para capturar con mayor precisión tanto tensiones como deformaciones en casos en el que el material tiene comportamiento isocórico; (2) Una estrategia de adaptividad de malla (AMR), que busca modificar la malla teniendo en cuenta la geometría y los errores en la solución numérica; (3) Una estrategia para minimizar la aproximación numérica durante el engrosamiento (coarsening) de la malla, crucial en la reducción de tiempos de cómputo en casos de piezas de grandes dimensiones; y (4) Un marco de simulación basado en la lectura de ficheros GCode, ampliamente usado por maquinaria de impresión en procesos de manufactura aditiva, un formato que no sólo proporciona los datos asociados a la geometría, sino también los parámetros de proceso. Con respecto a (1), esta tesis propone el uso de una formulación mixta en desplazamientos /deformación-desviadora / presión (u/e/p), para simular la deposición de materiales con deformación inelástica isocórica, como ocurre en los metales. En cuanto a la medición de la precisión en el cálculo de las tensiones y las deformaciones, en esta tesis se realiza un amplio número de experimentos tanto en condiciones isotérmicas como no isotérmicas para establecer una comparativa entre las dos formulaciones mixtas, u/e/p y u/p. Con respecto a (2), para mejorar la eficiencia computacional manteniendo acotado el número total de elementos finitos, se desarrolla una novedosa estrategia multicriterio de refinamiento adaptativo. Esta estrategia no se restringe a mallas con balance 2:1, permitiendo así tener saltos de nivel mayores entre elementos adyacentes. Por otra parte, para evitar la pérdida de información al proyectar la solución a mallas más gruesas, se plantee una corrección en (3), que tiene como objetivo recuperar la solución de la malla fina, garantizando así que la malla gruesa conserve la precisión obtenida en la malla fina. El proceso de manufactura aditiva se distingue por su gran flexibilidad comparándolo con otros métodos tradicionales de manufactura. Esta flexibilidad se observa en la posibilidad de construir piezas de gran complejidad geométrica, optimizando propiedades mecánicas durante el proceso de deposición. Por ese motivo, (4) se propone la lectura de ficheros en formato GCode que replica la ruta exacta del recorrido del láser que realiza la deposición del material. Los ingredientes lectura de comandos escritos en lenguaje Gcode, multicriterio de adaptividad de malla y el uso de mallas estructuradas basadas en octrees, permiten capturar con gran precisión el dominio discreto eliminando así la engorrosa tarea de generar un dominio discreto ad-hoc para la pieza a modelar. Los desarrollos de esta tesis se realizan en un entorno de computación de altas prestaciones (HPC) que permite acelerar el estudio de la ejecución del proceso de impresión y por ende reducir el número de experimentos destructivos, dos aspectos clave que permiten explorar y desarrollar nuevas técnicas en manufactura aditiva de piezas industriales.Postprint (published version

Multiscale optimisation of dynamic properties for additively manufactured lattice structures

A framework for tailoring the dynamic properties of functionally graded lattice structures through the use of multiscale optimisation is presented in this thesis. The multiscale optimisation utilises a two scale approach to allow for complex lattice structures to be simulated in real time at a similar computational expense to traditional finite element problems. The micro and macro scales are linked by a surrogate model that predicts the homogenised material properties of the underlying lattice geometry based on the lattice design parameters. Optimisation constraints on the resonant frequencies and the Modal Assurance Criteria are implemented that can induce the structure to resonate at specific frequencies whilst simultaneously tracking and ensuring the correct mode shapes are maintained. This is where the novelty of the work lies, as dynamic properties have not previously been optimised for in a multiscale, functionally graded lattice structure. Multiscale methods offer numerous benefits and increased design freedom when generating optimal structures for dynamic environments. These benefits are showcased in a series of optimised cantilever structures. The results show a significant improvement in dynamic behavior when compared to the unoptimised case as well as when compared to a single scale topology optimised structure. The validation of the resonant properties for the lattice structures is performed through a series of mechanical tests on additive manufactured lattices. These tests address both the micro and the macro scale of the multiscale method. The homogeneous and surrogate model assumptions of the micro scale are investigated through both compression and tensile tests of uniform lattice samples. The resonant frequency predictions of the macro scale optimisation are verified through mechanical shaker testing and computed tomography scans of the lattice structure. Sources of discrepancy between the predicted and observed behavior are also investigated and explained.Open Acces

Prognostic-based Life Extension Methodology with Application to Power Generation Systems

Practicable life extension of engineering systems would be a remarkable application of prognostics. This research proposes a framework for prognostic-base life extension. This research investigates the use of prognostic data to mobilize the potential residual life. The obstacles in performing life extension include: lack of knowledge, lack of tools, lack of data, and lack of time. This research primarily considers using the acoustic emission (AE) technology for quick-response diagnostic. To be specific, an important feature of AE data was statistically modeled to provide quick, robust and intuitive diagnostic capability. The proposed model was successful to detect the out of control situation when the data of faulty bearing was applied. This research also highlights the importance of self-healing materials. One main component of the proposed life extension framework is the trend analysis module. This module analyzes the pattern of the time-ordered degradation measures. The trend analysis is helpful not only for early fault detection but also to track the improvement in the degradation rate. This research considered trend analysis methods for the prognostic parameters, degradation waveform and multivariate data. In this respect, graphical methods was found appropriate for trend detection of signal features. Hilbert Huang Transform was applied to analyze the trends in waveforms. For multivariate data, it was realized that PCA is able to indicate the trends in the data if accompanied by proper data processing. In addition, two algorithms are introduced to address non-monotonic trends. It seems, both algorithms have the potential to treat the non-monotonicity in degradation data. Although considerable research has been devoted to developing prognostics algorithms, rather less attention has been paid to post-prognostic issues such as maintenance decision making. A multi-objective optimization model is presented for a power generation unit. This model proves the ability of prognostic models to balance between power generation and life extension. In this research, the confronting objective functions were defined as maximizing profit and maximizing service life. The decision variables include the shaft speed and duration of maintenance actions. The results of the optimization models showed clearly that maximizing the service life requires lower shaft speed and longer maintenance time