Three methodologies for the calibration of industrial manipulators: Experimental results on a SCARA robot

This article presents and compares three algorithms for the geometric parameter identification of industrial robots to increase its accuracy (static calibration). The estimation is based on the measure of the gripper pose errors when the robot follows suitable trajectories. The algorithms are general and can be applied to any robot providing that its kinematics is known. After a theoretical introduction to the general methodologies, these are applied to a selective compliance assembly robot arm (SCARA) robot analyzing its performance (precision, efficiency). Experimental results obtained with three methodologies are presented and discussed. The measure of the gripper pose error is based on a laser triangulation technique whose working principles are also recalled. © 2000 John Wiley & Sons, Inc.     

A deadlock detection tool for concurrent Java programs

This paper presents some issues related to the design and implementation of a concurrency analysis tool able to detect deadlock situations in Java programs that make use of multithreading mechanisms. An abstract formal model is generated from the Java source using the Java2Spin translator. The model is expressed in the PROMELA language, and the SPIN tool is used to perform its formal analysis. The paper mainly focuses on the design of the Java2Spin translator. A set of experiments, carried out to evaluate the performances of the analysis tool, is also presented. Copyright © 1999 John Wiley & Sons, Ltd.     

Characterisation of white vinegars of different sources with artificial neural networks

Wine and cider vinegars currently attract growing interest from consumers, giving rise to a consequent increase in supply. A full appreciation of their quality is only possible, however, through recognition of their superior quality when compared with vinegars produced from raw materials of inferior quality. Therefore, it is necessary to pinpoint the parameters that define the quality of these products. Chemico-physical and sensory analysis has been used to draw up artificial neural networks (ANNs), on the basis of a vast sampling of vinegars from various countries, produced from a variety of raw materials, that was already subjected to multivariate statistical analysis. Among the chemical parameters, polyalcohols and other elements such as pH, tartaric acid and proline proved to be highly reliable, whereas other volatile substances and the results of sensory analysis were not very discriminating and could not be used to re-classify samples of unknown origin. The positive results obtained indicate that ANNs are a powerful mathematical tool, since they can be used to construct models that predict the botanical origin of the product and to re-classify samples of unknown origin, without any initial restrictive hypothesis. © 1998 Society of Chemical Industry.     

A bulk tungsten divertor row for the outer strike point in JET

In the frame of the ITER-like wall project, a new row of divertor tiles has been developed which consists of 96 bulk tungsten load-bearing septum replacement plates (LB-SRP). Exposed to the outer strike point for most ITER-relevant, high triangularity configurations, they shall be subject to high power loads (locally 10 MW/m² and above). These conditions are demanding, particularly for an inertially cooled design as prescribed. The expected erosion rates are high as well as the risk of melting, especially with transients and repetitive ELM loads. The development is also a real challenge with respect to the inevitable excursions of the tungsten material through the so-called DBTT, ductile-to-brittle transition temperature.A lamella design has been selected to fulfil the requirements with respect to the thermo-mechanical and electromagnetic loads during disruptions (∂T/∂z ≤ 5 × 10⁴ K/m vertically, induction rate of change ∂B/∂t ≤ 100 T/s, and I_halo ≤ 18 kA/module). Care is taken to act on refractory metals solely with compressive forces to a large extent. The dedicated clamping concept is described. Results of a test exposure to an electron beam around 70 MJ/m² substantiate the resort to ‘high temperature’ materials like – among others – high-grade Nimonic^® alloys, molybdenum or ceramic coatings.     

Redispersible Polymer Powders with High Bio-Based Content from Core–Shell Nanoparticles

Redispersible polymer powders (RDPPs), i.e., additives obtained from core–shell nanoparticles and commercialized in the form of a dry powder, find intensive application in the concrete industry. However, they are mainly produced from fossil resources. Therefore, the development of bio-based RDPPs is important to reduce the carbon footprint of these additives. In this work, two types of core–shell nanoparticles with a high percentage of bio-based content are synthesized and show to be good candidates as RDPPs. In the first case, up to 75% of bio-based content is obtained by combining lauryl acrylate, derived from coconut and palm kernel oil, as main core material, with isobornyl methacrylate, coming from pine resin, exploited to create the outer harder shell. In the second case, a degradable macromonomer obtained by the ring opening polymerization of lactide using 2-hydroxyethyl methacrylate as initiator is used as the core-forming monomer to obtain degradable RDPPs. In both cases, the particles are synthesized with a two-step emulsion polymerization process conducted in one pot and then spray-dried to obtain the RDPPs of interest. The morphology and redispersibility of the powders are characterized. Finally, their use as concrete additives is preliminarily assessed by evaluating their effect on changes in the surface morphologies of concrete specimens.