43,897 research outputs found
Eco-efficient process based on conventional machining as an alternative technology to chemical milling of aeronautical metal skin panels
El fresado químico es un proceso diseñado para la reducción de peso de pieles metálicas que, a
pesar de los problemas medioambientales asociados, se utiliza en la industria aeronáutica desde los
años 50. Entre sus ventajas figuran el cumplimiento de las estrictas tolerancias de diseño de piezas
aeroespaciales y que pese a ser un proceso de mecanizado, no induce tensiones residuales. Sin
embargo, el fresado químico es una tecnología contaminante y costosa que tiende a ser sustituida.
Gracias a los avances realizados en el mecanizado, la tecnología de fresado convencional permite
alcanzar las tolerancias requeridas siempre y cuando se consigan evitar las vibraciones y la flexión
de la pieza, ambas relacionadas con los parámetros del proceso y con los sistemas de utillaje
empleados.
Esta tesis analiza las causas de la inestabilidad del corte y la deformación de las piezas a través
de una revisión bibliográfica que cubre los modelos analíticos, las técnicas computacionales y las
soluciones industriales en estudio actualmente. En ella, se aprecia cómo los modelos analíticos y las
soluciones computacionales y de simulación se centran principalmente en la predicción off-line de
vibraciones y de posibles flexiones de la pieza. Sin embargo, un enfoque más industrial ha llevado al
diseño de sistemas de fijación, utillajes, amortiguadores basados en actuadores, sistemas de rigidez
y controles adaptativos apoyados en simulaciones o en la selección estadística de parámetros.
Además se han desarrollado distintas soluciones CAM basadas en la aplicación de gemelos virtuales.
En la revisión bibliográfica se han encontrado pocos documentos relativos a pieles y suelos
delgados por lo que se ha estudiado experimentalmente el efecto de los parámetros de corte en su
mecanizado. Este conjunto de experimentos ha demostrado que, pese a usar un sistema que
aseguraba la rigidez de la pieza, las pieles se comportaban de forma diferente a un sólido rígido en
términos de fuerzas de mecanizado cuando se utilizaban velocidades de corte cercanas a la alta
velocidad. También se ha verificado que todas las muestras mecanizadas entraban dentro de
tolerancia en cuanto a la rugosidad de la pieza. Paralelamente, se ha comprobado que la correcta
selección de parámetros de mecanizado puede reducir las fuerzas de corte y las tolerancias del
proceso hasta un 20% y un 40%, respectivamente. Estos datos pueden tener aplicación industrial en
la simplificación de los sistemas de amarre o en el incremento de la eficiencia del proceso.
Este proceso también puede mejorarse incrementando la vida de la herramienta al utilizar
fluidos de corte. Una correcta lubricación puede reducir la temperatura del proceso y las tensiones
residuales inducidas a la pieza. Con este objetivo, se han desarrollado diferentes lubricantes, basados
en el uso de líquidos iónicos (IL) y se han comparado con el comportamiento tribológico del par de
contacto en seco y con una taladrina comercial. Los resultados obtenidos utilizando 1 wt% de los
líquidos iónicos en un tribómetro tipo pin-on-disk demuestran que el IL no halogenado reduce
significativamente el desgaste y la fricción entre el aluminio, material a mecanizar, y el carburo de
tungsteno, material de la herramienta, eliminando casi toda la adhesión del aluminio sobre el pin, lo
que puede incrementar considerablemente la vida de la herramienta.Chemical milling is a process designed to reduce the weight of metals skin panels. This process
has been used since 1950s in the aerospace industry despite its environmental concern. Among its
advantages, chemical milling does not induce residual stress and parts meet the required tolerances.
However, this process is a pollutant and costly technology. Thanks to the last advances in
conventional milling, machining processes can achieve similar quality results meanwhile vibration
and part deflection are avoided. Both problems are usually related to the cutting parameters and the
workholding.
This thesis analyses the causes of the cutting instability and part deformation through a literature
review that covers analytical models, computational techniques and industrial solutions. Analytics
and computational solutions are mainly focused on chatter and deflection prediction and industrial
approaches are focused on the design of workholdings, fixtures, damping actuators, stiffening
devices, adaptive control systems based on simulations and the statistical parameters selection, and
CAM solutions combined with the use of virtual twins applications.
In this literature review, few research works about thin-plates and thin-floors is found so the
effect of the cutting parameters is also studied experimentally. These experiments confirm that even
using rigid workholdings, the behavior of the part is different to a rigid body at high speed machining.
On the one hand, roughness values meet the required tolerances under every set of the tested
parameters. On the other hand, a proper parameter selection reduces the cutting forces and process
tolerances by up to 20% and 40%, respectively. This fact can be industrially used to simplify
workholding and increase the machine efficiency.
Another way to improve the process efficiency is to increase tool life by using cutting fluids.
Their use can also decrease the temperature of the process and the induced stresses. For this purpose,
different water-based lubricants containing three types of Ionic Liquids (IL) are compared to dry and
commercial cutting fluid conditions by studying their tribological behavior. Pin on disk tests prove
that just 1wt% of one of the halogen-free ILs significantly reduces wear and friction between both
materials, aluminum and tungsten carbide. In fact, no wear scar is noticed on the ball when one of
the ILs is used, which, therefore, could considerably increase tool life
Human Motion Trajectory Prediction: A Survey
With growing numbers of intelligent autonomous systems in human environments,
the ability of such systems to perceive, understand and anticipate human
behavior becomes increasingly important. Specifically, predicting future
positions of dynamic agents and planning considering such predictions are key
tasks for self-driving vehicles, service robots and advanced surveillance
systems. This paper provides a survey of human motion trajectory prediction. We
review, analyze and structure a large selection of work from different
communities and propose a taxonomy that categorizes existing methods based on
the motion modeling approach and level of contextual information used. We
provide an overview of the existing datasets and performance metrics. We
discuss limitations of the state of the art and outline directions for further
research.Comment: Submitted to the International Journal of Robotics Research (IJRR),
37 page
Tuning the Level of Concurrency in Software Transactional Memory: An Overview of Recent Analytical, Machine Learning and Mixed Approaches
Synchronization transparency offered by Software Transactional Memory (STM) must not come at the expense of run-time efficiency, thus demanding from the STM-designer the inclusion of mechanisms properly oriented to performance and other quality indexes. Particularly, one core issue to cope with in STM is related to exploiting parallelism while also avoiding thrashing phenomena due to excessive transaction rollbacks, caused by excessively high levels of contention on logical resources, namely concurrently accessed data portions. A means to address run-time efficiency consists in dynamically determining the best-suited level of concurrency (number of threads) to be employed for running the application (or specific application phases) on top of the STM layer. For too low levels of concurrency, parallelism can be hampered. Conversely, over-dimensioning the concurrency level may give rise to the aforementioned thrashing phenomena caused by excessive data contention—an aspect which has reflections also on the side of reduced energy-efficiency. In this chapter we overview a set of recent techniques aimed at building “application-specific” performance models that can be exploited to dynamically tune the level of concurrency to the best-suited value. Although they share some base concepts while modeling the system performance vs the degree of concurrency, these techniques rely on disparate methods, such as machine learning or analytic methods (or combinations of the two), and achieve different tradeoffs in terms of the relation between the precision of the performance model and the latency for model instantiation. Implications of the different tradeoffs in real-life scenarios are also discussed
Automated user modeling for personalized digital libraries
Digital libraries (DL) have become one of the most typical ways of accessing any kind of digitalized information. Due to this key role, users welcome any improvements on the services they receive from digital libraries. One trend used to
improve digital services is through personalization. Up to now, the most common approach for personalization in digital libraries has been user-driven. Nevertheless, the design of efficient personalized services has to be done, at least in part, in
an automatic way. In this context, machine learning techniques automate the process of constructing user models. This paper proposes a new approach to construct digital libraries that satisfy user’s necessity for information: Adaptive Digital Libraries, libraries that automatically learn user preferences and goals and personalize their interaction using this information
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