Multiobjective engineering design optimization problems: a sensitivity analysis approach

This paper proposes two new approaches for the sensitivity analysis of multiobjective design optimization problems whose performance functions are highly susceptible to small variations in the design variables and/or design environment parameters. In both methods, the less sensitive design alternatives are preferred over others during the multiobjective optimization process. While taking the first approach, the designer chooses the design variable and/or parameter that causes uncertainties. The designer then associates a robustness index with each design alternative and adds each index as an objective function in the optimization problem. For the second approach, the designer must know, a priori, the interval of variation in the design variables or in the design environment parameters, because the designer will be accepting the interval of variation in the objective functions. The second method does not require any law of probability distribution of uncontrollable variations. Finally, the authors give two illustrative examples to highlight the contributions of the paper.

A firefly dynamic penalty approach for solving engineering design problems

Firefly Algorithm is a recent swarm intelligence method, inspired by the social behavior of fireflies, based on their flashing and attraction characteristics [1, 2]. In this paper, we analyze the implementation of a dynamic penalty approach combined with the Firefly algorithm for solving constrained global optimization problems. In order to assess the applicability and performance of the proposed method, some benchmark problems from engineering design optimization are considered.

Reliability-based design optimization strategies based on FORM: a review

In deterministic optimization, the uncertainties of the structural system (i.e. dimension, model, material, loads, etc) are not explicitly taken into account. Hence, resulting optimal solutions may lead to reduced reliability levels. The objective of reliability based design optimization (RBDO) is to optimize structures guaranteeing that a minimum level of reliability, chosen a priori by the designer, is maintained. Since reliability analysis using the First Order Reliability Method (FORM) is an optimization procedure itself, RBDO (in its classical version) is a double-loop strategy: the reliability analysis (inner loop) and the structural optimization (outer loop). The coupling of these two loops leads to very high computational costs. To reduce the computational burden of RBDO based on FORM, several authors propose decoupling the structural optimization and the reliability analysis. These procedures may be divided in two groups: (i) serial single loop methods and (ii) unilevel methods. The basic idea of serial single loop methods is to decouple the two loops and solve them sequentially, until some convergence criterion is achieved. On the other hand, uni-level methods employ different strategies to obtain a single loop of optimization to solve the RBDO problem. This paper presents a review of such RBDO strategies. A comparison of the performance (computational cost) of the main strategies is presented for several variants of two benchmark problems from the literature and for a structure modeled using the finite element method.

Mechanical design optimization for multi-finger haptic devices applied to virtual grasping manipulation

This paper describes the design of a modular multi-finger haptic device for virtual object manipulation. Mechanical structures are based on one module per finger and can be scaled up to three fingers. Mechanical configurations for two and three fingers are based on the use of one and two redundant axes, respectively. As demonstrated, redundant axes significantly increase workspace and prevent link collisions, which is their main asset with respect to other multi-finger haptic devices. The location of redundant axes and link dimensions have been optimized in order to guarantee a proper workspace, manipulability, force capability, and inertia for the device. The mechanical haptic device design and a thimble adaptable to different finger sizes have also been developed for virtual object manipulation.

Multidisciplinary Design Optimization Application to Conceptual Design of University-class Microsatellite Projects

Esta tesis se ha realizado en el contexto del proyecto UPMSat-2, que es un microsatélite diseñado, construido y operado por el Instituto Universitario de Microgravedad "Ignacio Da Riva" (IDR / UPM) de la Universidad Politécnica de Madrid. Aplicación de la metodología Ingeniería Concurrente (Concurrent Engineering: CE) en el marco de la aplicación de diseño multidisciplinar (Multidisciplinary Design Optimization: MDO) es uno de los principales objetivos del presente trabajo. En los últimos años, ha habido un interés continuo en la participación de los grupos de investigación de las universidades en los estudios de la tecnología espacial a través de sus propios microsatélites. La participación en este tipo de proyectos tiene algunos desafíos inherentes, tales como presupuestos y servicios limitados. Además, debido al hecho de que el objetivo principal de estos proyectos es fundamentalmente educativo, por lo general hay incertidumbres en cuanto a su misión en órbita y cargas útiles en las primeras fases del proyecto. Por otro lado, existen limitaciones predeterminadas para sus presupuestos de masa, volumen y energía, debido al hecho de que la mayoría de ellos están considerados como una carga útil auxiliar para el lanzamiento. De este modo, el costo de lanzamiento se reduce considerablemente. En este contexto, el subsistema estructural del satélite es uno de los más afectados por las restricciones que impone el lanzador. Esto puede afectar a diferentes aspectos, incluyendo las dimensiones, la resistencia y los requisitos de frecuencia. En la primera parte de esta tesis, la atención se centra en el desarrollo de una herramienta de diseño del subsistema estructural que evalúa, no sólo las propiedades de la estructura primaria como variables, sino también algunas variables de nivel de sistema del satélite, como la masa de la carga útil y la masa y las dimensiones extremas de satélite. Este enfoque permite que el equipo de diseño obtenga una mejor visión del diseño en un espacio de diseño extendido. La herramienta de diseño estructural se basa en las fórmulas y los supuestos apropiados, incluyendo los modelos estáticos y dinámicos del satélite. Un algoritmo genético (Genetic Algorithm: GA) se aplica al espacio de diseño para optimizaciones de objetivo único y también multiobjetivo. El resultado de la optimización multiobjetivo es un Pareto-optimal basado en dos objetivo, la masa total de satélites mínimo y el máximo presupuesto de masa de carga útil. Por otro lado, la aplicación de los microsatélites en misiones espaciales es de interés por su menor coste y tiempo de desarrollo. La gran necesidad de las aplicaciones de teledetección es un fuerte impulsor de su popularidad en este tipo de misiones espaciales. Las misiones de tele-observación por satélite son esenciales para la investigación de los recursos de la tierra y el medio ambiente. En estas misiones existen interrelaciones estrechas entre diferentes requisitos como la altitud orbital, tiempo de revisita, el ciclo de vida y la resolución. Además, todos estos requisitos puede afectar a toda las características de diseño. Durante los últimos años la aplicación de CE en las misiones espaciales ha demostrado una gran ventaja para llegar al diseño óptimo, teniendo en cuenta tanto el rendimiento y el costo del proyecto. Un ejemplo bien conocido de la aplicación de CE es la CDF (Facilidad Diseño Concurrente) de la ESA (Agencia Espacial Europea). Está claro que para los proyectos de microsatélites universitarios tener o desarrollar una instalación de este tipo parece estar más allá de las capacidades del proyecto. Sin embargo, la práctica de la CE a cualquier escala puede ser beneficiosa para los microsatélites universitarios también. En la segunda parte de esta tesis, la atención se centra en el desarrollo de una estructura de optimización de diseño multidisciplinar (Multidisciplinary Design Optimization: MDO) aplicable a la fase de diseño conceptual de microsatélites de teledetección. Este enfoque permite que el equipo de diseño conozca la interacción entre las diferentes variables de diseño. El esquema MDO presentado no sólo incluye variables de nivel de sistema, tales como la masa total del satélite y la potencia total, sino también los requisitos de la misión como la resolución y tiempo de revisita. El proceso de diseño de microsatélites se divide en tres disciplinas; a) diseño de órbita, b) diseño de carga útil y c) diseño de plataforma. En primer lugar, se calculan diferentes parámetros de misión para un rango práctico de órbitas helio-síncronas (sun-synchronous orbits: SS-Os). Luego, según los parámetros orbitales y los datos de un instrumento como referencia, se calcula la masa y la potencia de la carga útil. El diseño de la plataforma del satélite se estima a partir de los datos de la masa y potencia de los diferentes subsistemas utilizando relaciones empíricas de diseño. El diseño del subsistema de potencia se realiza teniendo en cuenta variables de diseño más detalladas, como el escenario de la misión y diferentes tipos de células solares y baterías. El escenario se selecciona, de modo de obtener una banda de cobertura sobre la superficie terrestre paralelo al Ecuador después de cada intervalo de revisita. Con el objetivo de evaluar las interrelaciones entre las diferentes variables en el espacio de diseño, todas las disciplinas de diseño mencionados se combinan en un código unificado. Por último, una forma básica de MDO se ajusta a la herramienta de diseño de sistema de satélite. La optimización del diseño se realiza por medio de un GA con el único objetivo de minimizar la masa total de microsatélite. Según los resultados obtenidos de la aplicación del MDO, existen diferentes puntos de diseños óptimos, pero con diferentes variables de misión. Este análisis demuestra la aplicabilidad de MDO para los estudios de ingeniería de sistema en la fase de diseño conceptual en este tipo de proyectos. La principal conclusión de esta tesis, es que el diseño clásico de los satélites que por lo general comienza con la definición de la misión y la carga útil no es necesariamente la mejor metodología para todos los proyectos de satélites. Un microsatélite universitario, es un ejemplo de este tipo de proyectos. Por eso, se han desarrollado un conjunto de herramientas de diseño para encarar los estudios de la fase inicial de diseño. Este conjunto de herramientas incluye diferentes disciplinas de diseño centrados en el subsistema estructural y teniendo en cuenta una carga útil desconocida a priori. Los resultados demuestran que la mínima masa total del satélite y la máxima masa disponible para una carga útil desconocida a priori, son objetivos conflictivos. En este contexto para encontrar un Pareto-optimal se ha aplicado una optimización multiobjetivo. Según los resultados se concluye que la selección de la masa total por satélite en el rango de 40-60 kg puede considerarse como óptima para un proyecto de microsatélites universitario con carga útil desconocida a priori. También la metodología CE se ha aplicado al proceso de diseño conceptual de microsatélites de teledetección. Los resultados de la aplicación del CE proporcionan una clara comprensión de la interacción entre los requisitos de diseño de sistemas de satélites, tales como la masa total del microsatélite y la potencia y los requisitos de la misión como la resolución y el tiempo de revisita. La aplicación de MDO se hace con la minimización de la masa total de microsatélite. Los resultados de la aplicación de MDO aclaran la relación clara entre los diferentes requisitos de diseño del sistema y de misión, así como que permiten seleccionar las líneas de base para el diseño óptimo con el objetivo seleccionado en las primeras fase de diseño. ABSTRACT This thesis is done in the context of UPMSat-2 project, which is a microsatellite under design and manufacturing at the Instituto Universitario de Microgravedad “Ignacio Da Riva” (IDR/UPM) of the Universidad Politécnica de Madrid. Application of Concurrent Engineering (CE) methodology in the framework of Multidisciplinary Design application (MDO) is one of the main objectives of the present work. In recent years, there has been continuing interest in the participation of university research groups in space technology studies by means of their own microsatellites. The involvement in such projects has some inherent challenges, such as limited budget and facilities. Also, due to the fact that the main objective of these projects is for educational purposes, usually there are uncertainties regarding their in orbit mission and scientific payloads at the early phases of the project. On the other hand, there are predetermined limitations for their mass and volume budgets owing to the fact that most of them are launched as an auxiliary payload in which the launch cost is reduced considerably. The satellite structure subsystem is the one which is most affected by the launcher constraints. This can affect different aspects, including dimensions, strength and frequency requirements. In the first part of this thesis, the main focus is on developing a structural design sizing tool containing not only the primary structures properties as variables but also the satellite system level variables such as payload mass budget and satellite total mass and dimensions. This approach enables the design team to obtain better insight into the design in an extended design envelope. The structural design sizing tool is based on the analytical structural design formulas and appropriate assumptions including both static and dynamic models of the satellite. A Genetic Algorithm (GA) is applied to the design space for both single and multiobejective optimizations. The result of the multiobjective optimization is a Pareto-optimal based on two objectives, minimum satellite total mass and maximum payload mass budget. On the other hand, the application of the microsatellites is of interest for their less cost and response time. The high need for the remote sensing applications is a strong driver of their popularity in space missions. The satellite remote sensing missions are essential for long term research around the condition of the earth resources and environment. In remote sensing missions there are tight interrelations between different requirements such as orbital altitude, revisit time, mission cycle life and spatial resolution. Also, all of these requirements can affect the whole design characteristics. During the last years application of the CE in the space missions has demonstrated a great advantage to reach the optimum design base lines considering both the performance and the cost of the project. A well-known example of CE application is ESA (European Space Agency) CDF (Concurrent Design Facility). It is clear that for the university-class microsatellite projects having or developing such a facility seems beyond the project capabilities. Nevertheless practicing CE at any scale can be beneficiary for the university-class microsatellite projects. In the second part of this thesis, the main focus is on developing a MDO framework applicable to the conceptual design phase of the remote sensing microsatellites. This approach enables the design team to evaluate the interaction between the different system design variables. The presented MDO framework contains not only the system level variables such as the satellite total mass and total power, but also the mission requirements like the spatial resolution and the revisit time. The microsatellite sizing process is divided into the three major design disciplines; a) orbit design, b) payload sizing and c) bus sizing. First, different mission parameters for a practical range of sun-synchronous orbits (SS-Os) are calculated. Then, according to the orbital parameters and a reference remote sensing instrument, mass and power of the payload are calculated. Satellite bus sizing is done based on mass and power calculation of the different subsystems using design estimation relationships. In the satellite bus sizing, the power subsystem design is realized by considering more detailed design variables including a mission scenario and different types of solar cells and batteries. The mission scenario is selected in order to obtain a coverage belt on the earth surface parallel to the earth equatorial after each revisit time. In order to evaluate the interrelations between the different variables inside the design space all the mentioned design disciplines are combined in a unified code. The integrated satellite system sizing tool developed in this section is considered as an application of the CE to the conceptual design of the remote sensing microsatellite projects. Finally, in order to apply the MDO methodology to the design problem, a basic MDO framework is adjusted to the developed satellite system design tool. Design optimization is done by means of a GA single objective algorithm with the objective function as minimizing the microsatellite total mass. According to the results of MDO application, there exist different optimum design points all with the minimum satellite total mass but with different mission variables. This output demonstrates the successful applicability of MDO approach for system engineering trade-off studies at the conceptual design phase of the design in such projects. The main conclusion of this thesis is that the classical design approach for the satellite design which usually starts with the mission and payload definition is not necessarily the best approach for all of the satellite projects. The university-class microsatellite is an example for such projects. Due to this fact an integrated satellite sizing tool including different design disciplines focusing on the structural subsystem and considering unknown payload is developed. According to the results the satellite total mass and available mass for the unknown payload are conflictive objectives. In order to find the Pareto-optimal a multiobjective GA optimization is conducted. Based on the optimization results it is concluded that selecting the satellite total mass in the range of 40-60 kg can be considered as an optimum approach for a university-class microsatellite project with unknown payload(s). Also, the CE methodology is applied to the remote sensing microsatellites conceptual design process. The results of CE application provide a clear understanding of the interaction between satellite system design requirements such as satellite total mass and power and the satellite mission variables such as revisit time and spatial resolution. The MDO application is done with the total mass minimization of a remote sensing satellite. The results from the MDO application clarify the unclear relationship between different system and mission design variables as well as the optimum design base lines according to the selected objective during the initial design phases.

Design optimization of modern machine drive systems for maximum fault tolerant and optimal operation

Modern electric machine drives, particularly three phase permanent magnet machine drive systems represent an indispensable part of high power density products. Such products include; hybrid electric vehicles, large propulsion systems, and automation products. Reliability and cost of these products are directly related to the reliability and cost of these systems. The compatibility of the electric machine and its drive system for optimal cost and operation has been a large challenge in industrial applications. The main objective of this dissertation is to find a design and control scheme for the best compromise between the reliability and optimality of the electric machine-drive system. The effort presented here is motivated by the need to find new techniques to connect the design and control of electric machines and drive systems. ^ A highly accurate and computationally efficient modeling process was developed to monitor the magnetic, thermal, and electrical aspects of the electric machine in its operational environments. The modeling process was also utilized in the design process in form finite element based optimization process. It was also used in hardware in the loop finite element based optimization process. The modeling process was later employed in the design of a very accurate and highly efficient physics-based customized observers that are required for the fault diagnosis as well the sensorless rotor position estimation. Two test setups with different ratings and topologies were numerically and experimentally tested to verify the effectiveness of the proposed techniques. ^ The modeling process was also employed in the real-time demagnetization control of the machine. Various real-time scenarios were successfully verified. It was shown that this process gives the potential to optimally redefine the assumptions in sizing the permanent magnets of the machine and DC bus voltage of the drive for the worst operating conditions. ^ The mathematical development and stability criteria of the physics-based modeling of the machine, design optimization, and the physics-based fault diagnosis and the physics-based sensorless technique are described in detail. ^ To investigate the performance of the developed design test-bed, software and hardware setups were constructed first. Several topologies of the permanent magnet machine were optimized inside the optimization test-bed. To investigate the performance of the developed sensorless control, a test-bed including a 0.25 (kW) surface mounted permanent magnet synchronous machine example was created. The verification of the proposed technique in a range from medium to very low speed, effectively show the intelligent design capability of the proposed system. Additionally, to investigate the performance of the developed fault diagnosis system, a test-bed including a 0.8 (kW) surface mounted permanent magnet synchronous machine example with trapezoidal back electromotive force was created. The results verify the use of the proposed technique under dynamic eccentricity, DC bus voltage variations, and harmonic loading condition make the system an ideal case for propulsion systems.^

Development of physics-based models and design optimization of power electronic conversion systems

The main objective for physics based modeling of the power converter components is to design the whole converter with respect to physical and operational constraints. Therefore, all the elements and components of the energy conversion system are modeled numerically and combined together to achieve the whole system behavioral model. Previously proposed high frequency (HF) models of power converters are based on circuit models that are only related to the parasitic inner parameters of the power devices and the connections between the components. This dissertation aims to obtain appropriate physics-based models for power conversion systems, which not only can represent the steady state behavior of the components, but also can predict their high frequency characteristics. The developed physics-based model would represent the physical device with a high level of accuracy in predicting its operating condition. The proposed physics-based model enables us to accurately develop components such as; effective EMI filters, switching algorithms and circuit topologies [7]. One of the applications of the developed modeling technique is design of new sets of topologies for high-frequency, high efficiency converters for variable speed drives. The main advantage of the modeling method, presented in this dissertation, is the practical design of an inverter for high power applications with the ability to overcome the blocking voltage limitations of available power semiconductor devices. Another advantage is selection of the best matching topology with inherent reduction of switching losses which can be utilized to improve the overall efficiency. The physics-based modeling approach, in this dissertation, makes it possible to design any power electronic conversion system to meet electromagnetic standards and design constraints. This includes physical characteristics such as; decreasing the size and weight of the package, optimized interactions with the neighboring components and higher power density. In addition, the electromagnetic behaviors and signatures can be evaluated including the study of conducted and radiated EMI interactions in addition to the design of attenuation measures and enclosures.

Probabilistic design optimization of horizontal axis wind turbine rotors

Considerable interest in renewable energy has increased in recent years due to the concerns raised over the environmental impact of conventional energy sources and their price volatility. In particular, wind power has enjoyed a dramatic global growth in installed capacity over the past few decades. Nowadays, the advancement of wind turbine industry represents a challenge for several engineering areas, including materials science, computer science, aerodynamics, analytical design and analysis methods, testing and monitoring, and power electronics. In particular, the technological improvement of wind turbines is currently tied to the use of advanced design methodologies, allowing the designers to develop new and more efficient design concepts. Integrating mathematical optimization techniques into the multidisciplinary design of wind turbines constitutes a promising way to enhance the profitability of these devices. In the literature, wind turbine design optimization is typically performed deterministically. Deterministic optimizations do not consider any degree of randomness affecting the inputs of the system under consideration, and result, therefore, in an unique set of outputs. However, given the stochastic nature of the wind and the uncertainties associated, for instance, with wind turbine operating conditions or geometric tolerances, deterministically optimized designs may be inefficient. Therefore, one of the ways to further improve the design of modern wind turbines is to take into account the aforementioned sources of uncertainty in the optimization process, achieving robust configurations with minimal performance sensitivity to factors causing variability. The research work presented in this thesis deals with the development of a novel integrated multidisciplinary design framework for the robust aeroservoelastic design optimization of multi-megawatt horizontal axis wind turbine (HAWT) rotors, accounting for the stochastic variability related to the input variables. The design system is based on a multidisciplinary analysis module integrating several simulations tools needed to characterize the aeroservoelastic behavior of wind turbines, and determine their economical performance by means of the levelized cost of energy (LCOE). The reported design framework is portable and modular in that any of its analysis modules can be replaced with counterparts of user-selected fidelity. The presented technology is applied to the design of a 5-MW HAWT rotor to be used at sites of wind power density class from 3 to 7, where the mean wind speed at 50 m above the ground ranges from 6.4 to 11.9 m/s. Assuming the mean wind speed to vary stochastically in such range, the rotor design is optimized by minimizing the mean and standard deviation of the LCOE. Airfoil shapes, spanwise distributions of blade chord and twist, internal structural layup and rotor speed are optimized concurrently, subject to an extensive set of structural and aeroelastic constraints. The effectiveness of the multidisciplinary and robust design framework is demonstrated by showing that the probabilistically designed turbine achieves more favorable probabilistic performance than those of the initial baseline turbine and a turbine designed deterministically.

RISK-BASED MULTIOBJECTIVE PATH PLANNING AND DESIGN OPTIMIZATION FOR UNMANNED AERIAL VEHICLES

Safe operation of unmanned aerial vehicles (UAVs) over populated areas requires reducing the risk posed by a UAV if it crashed during its operation. We considered several types of UAV risk-based path planning problems and developed techniques for estimating the risk to third parties on the ground. The path planning problem requires making trade-offs between risk and flight time. Four optimization approaches for solving the problem were tested; a network-based approach that used a greedy algorithm to improve the original solution generated the best solutions with the least computational effort. Additionally, an approach for solving a combined design and path planning problems was developed and tested. This approach was extended to solve robust risk-based path planning problem in which uncertainty about wind conditions would affect the risk posed by a UAV.

Multi-criteria design optimization study of solvent extraction in mixer–settler units

Solvent extraction is considered as a multi-criteria optimization problem, since several chemical species with similar extraction kinetic properties are frequently present in the aqueous phase and the selective extraction is not practicable. This optimization, applied to mixer–settler units, considers the best parameters and operating conditions, as well as the best structure or process flow-sheet. Global process optimization is performed for a specific flow-sheet and a comparison of Pareto curves for different flow-sheets is made. The positive weight sum approach linked to the sequential quadratic programming method is used to obtain the Pareto set. In all investigated structures, recovery increases with hold-up, residence time and agitation speed, while the purity has an opposite behaviour. For the same treatment capacity, counter-current arrangements are shown to promote recovery without significant impairment in purity. Recycling the aqueous phase is shown to be irrelevant, but organic recycling with as many stages as economically feasible clearly improves the design criteria and reduces the most efficient organic flow-rate.

Design optimization of cruciform specimens for biaxial fatigue loading

In order to correctly assess the biaxial fatigue material properties one must experimentally test different load conditions and stress levels. With the rise of new in-plane biaxial fatigue testing machines, using smaller and more efficient electrical motors, instead of the conventional hydraulic machines, it is necessary to reduce the specimen size and to ensure that the specimen geometry is appropriated for the load capacity installed. At the present time there are no standard specimen’s geometries and the indications on literature how to design an efficient test specimen are insufficient. The main goal of this paper is to present the methodology on how to obtain an optimal cruciform specimen geometry, with thickness reduction in the gauge area, appropriated for fatigue crack initiation, as a function of the base material sheet thickness used to build the specimen. The geometry is optimized for maximum stress using several parameters, ensuring that in the gauge area the stress is uniform and maximum with two limit phase shift loading conditions. Therefore the fatigue damage will always initiate on the center of the specimen, avoiding failure outside this region. Using the Renard Series of preferred numbers for the base material sheet thickness as a reference, the reaming geometry parameters are optimized using a derivative-free methodology, called direct multi search (DMS) method. The final optimal geometry as a function of the base material sheet thickness is proposed, as a guide line for cruciform specimens design, and as a possible contribution for a future standard on in-plane biaxial fatigue tests. © 2014, Gruppo Italiano Frattura. All rights reserved.

Development of procedures for the design, optimization and manufacturing of customized orthopaedic and trauma implants: Geometrical/anatomical modelling from 3D medical imaging

Tese de Doutoramento (Programa Doutoral em Engenharia Biomédica)

Ingeniería de glicanos: diseño de inmunógenos y ligandos de lectinas. Glycan engineering: design of immunogens and ligand of lectins.

La ingeniería de glicanos es un área de investigación emergente, la que posee múltiples aplicaciones en medicina. Mediante esta herramienta se intentará reducir la flexibilidad de las uniones glicosídicas de antígenos tumorales, como la del antígeno T (Galbeta3GalNAcalfa-Ser/Thr). Aquí se realizarán las menores alteraciones posibles en la topología de glicanos que generen la mejor respuesta inmune hacia el antígeno de interés. Por otra parte, se buscará ligandos de alta afinidad que interaccionen con lectinas involucradas en diseminación de metástasis. Mediante ensayos teóricos de Docking se tratará de hallar modificaciones topológicas de glicanos que potencialmente tengan propiedades anti-adhesivas para células tumorales. Este proyecto constará de tres etapas: una teórica, utilizando programas de cálculos para ensayos de Docking y mínimos energéticos de glicanos. Otra de síntesis, generando los glicoconjugados sugeridos en la etapa anterior. En la última, se verificará si estos glicanos rediseñados adquirieron las propiedades biológicas deseadas. Así se determinará si generan una respuesta inmune que reconozca antígenos y células tumorales. También, se analizarán las propiedades anti-adhesivas de los glicanos utilizando diferentes modelos experimentales. Finalmente, se determinará si los inmunógenos producidos y/o glicoconjugados rediseñados poseen efecto en el desarrollo tumoral y sobrevida animal.