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EN
Purpose: The literature abounds with many distinct topology optimisation methods, many of which share common parameter configurations. This study demonstrates that alternative parameter configurations may produce better results than common parameters. Additionally, we try to answer two fundamental questions: identifying the most effective topology optimisation method and determining the optimal parameter selection within this optimisation method. In order to respond to these questions, we conducted a comparative and objective analysis of topology optimisation methods. Design/methodology/approach: This paper evaluates four prominent topology optimisation methodologies, SIMP, RAMP, BESO, and LSM, based on three essential criteria: structural strength, topology quality, and computational cost. We conducted an in-depth examination of 12,500 topology optimisation results spanning a broad range of critical parameter values. These outcomes were generated using MATLAB codes. In the meantime, we comprehensively compared our findings with the existing literature on this subject. Findings: As predicted, our chosen parameters had a substantial effect on the topology quality, structural strength, and computational cost of the topology optimisation outcomes. Across the 12,500 results, many parameter combinations appeared to produce favourable results compared to conventional parameters commonly found in the existing literature. Research limitations/implications: This study focuses exclusively on four specific topology optimisation methods; however, its findings may be extrapolated to apply to other methodologies. Additionally, while it extensively examines the effects of parameters on topology quality, strength, and computational cost, it does not encompass an exploration of these parameters' impacts on other performance criteria. Originality/value: Novel parameter configurations for topology optimisation have been identified, yielding enhanced outcomes in terms of topology quality, structural strength, and computational efficiency.
PL
W artykule przedstawiono metodę optymalizacji topologicznej wybranych korpusów układu suportowego obrabiarki do kolejnictwa. Na przykładzie suwaka głównego przeprowadzono optymalizację topologiczną mającą na celu zredukowanie objętości obszarów biernych. Obliczenia numeryczne uwzględniają działanie sił skrawania, zapewniając dostateczną sztywność węzła.
EN
he article presents a method of topology optimisation of the selected carriage bodies of a railway machine tool. Based on the example of the main slider, topology optimization was performed to reduce the volume of passive areas. Numerical calculations take into account the action of cutting forces, which ensures a sufficient rigidity of the node.
EN
Among past years interest in robot‐assisted rehabilitation arose significantly; thus, constructions such as exoskele‐ tons are involved in this process much more often. As pa‐ tient’s bio‐signals may be included in a control loop of these devices, they may be also used to support the mo‐ tion of extremities in an everyday life. Therefore, a field of control over them stays a popular research topic. For this reason, an exoskeleton described in a paper was de‐ signed. The most important aim of a project was to ena‐ ble all anatomical movements within ranges required for the lifting of an object while minimising a mass of the device. The following paper consist of a concept of an exoskeleton and description of FEM simulations and to‐ pology optimisation applied to decrease the amount of material needed. Moreover, as an exoskeleton was built with FFF 3‐D printing technology, created parts are mo‐ delled orthotopically based on nominal mechanical para‐ meters of filaments and directions of their beams. The de‐ sign is complemented with a short description of control with EMG signals and analysis of load on a user’s muscu‐ loskeletal system.
4
Content available remote Topology optimisation as a tool for obtaining a multimaterial structure
EN
Topology optimisation problem solutions are generally presented in such a way that ultimately a material/ void (1/0) distribution is obtained in the design domain. For this purpose, filtering techniques are usually used or post-processing is applied in the optimisation process. As a rule, the result is quasi-optimal since no minimum value of the objective functional is then obtained. In this study an optimal body topology is determined. Its characteristic feature is that besides normal material and voids there is a material with poorer and varied parameters in the design domain. The latter material is often distributed in the form of a layer around the axis of each member of the construction and gets weaker with the distance from the axis. This means that the construction is multimaterial and individual layers can be distinguished in its members. In this sense, the construction is a layered one. The compliance functional is minimized under constraints imposed on the body mass, which means that the initially available mass is kept constant throughout the optimisation process. Looking for the functional stationary point one gets the following dependence: material density in a particular material point for the considered iteration is proportional to the strain energy accumulated in this point. A discretely updated Young modulus is used in the successive steps in the construction of stiffness matrices. The update for the individual material points in the successive iterations is based on the strain energy distribution in the previous step. The problem was solved numerically using FEM and identifying body material points with finite elements.
PL
Rozwiązania problemu optymalizacji topologii są najczęściej przedstawiane w ten sposób, że ostatecznie w obszarze projektowym mamy do czynienie z rozkładem typu materiał - pustka. W pracy wykazano, że rzeczywista optymalna konstrukcja to konstrukcja warstwowa składająca się z różnych materiałów, w której twardy rdzeń pręta otoczony jest coraz słabszymi warstwami. Zastosowano podejście energetyczne minimalizując funkcjonał podatności przy więzach nałożonych na masę ciała. Implementację numeryczną wykonano przy wykorzystaniu metody elementów skończonych.
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