Biodiesel as a Plasticizer of a SBR-Based Tire Tread Formulation

The solubility parameter of a series of methyl esters of fatty acids, the components of biodiesel, was calculated using the group incremental method proposed by Van Krevelen. The solubility parameter of biodiesel was compared with that of a series of rubbers like EPDM, butyl rubber, polyisoprene, polybutadiene, SBR (with different content of styrene), and nitrile rubber (with different content of acrylonitrile) showing that biodiesel is an effective solvent of all the above mentioned rubbers with the exclusion of nitrile rubber. Indeed, it was experimentally verified that polyisoprene, polybutadiene and SBR are easily soluble in biodiesel while polystyrene gives a cloudy solution. Considerations on the solubility parameter of the biodiesel and of a series of rubbers have led to the conclusion that biodiesel behaves essentially as an internal lubricant in a diene rubber matrix, the same situation occurs with the common aromatic mineral oil plasticizer known as T-RAE. The experimental evaluation of biodiesel as plasticizer in an SBR-based rubber compound in comparison to an aromatic mineral oil have led to the primary conclusion that biodiesel is reactive with the sulphur curing agent subtracting sulphur to the crosslinking polymer chains and leading to a vulcanizatewith lower moduli, tensile and hardness and higher elongationsin comparison to a reference compound fully plasticized with an aromatic mineral oil. However, biodiesel seems a good low temperature plasticizer because the low elastic modulus observed is desired in a winter tire tread for a good grip on snow and ice. The present work is only an exploratory work, and the tire tread formulation with biodiesel was not optimized

Low-cost electrochemical impedance spectroscopy system for corrosion monitoring of metallic antiquities and works of art

Electrochemical impedance spectroscopy (EIS) is recognized to be a powerful and noninvasive technique to test the integrity of protective coatings on memorials, but commercial EIS systems are rather costly though versatile devices. This paper describes a low cost and portable EIS system that is based on a compact digital signal processor (DSP) board and embeds the potentiostatic function so that it can be used without requiring an external potentiostat. The software that runs on the DSP is designed to analyze the electrochemical impedance only in a reduced frequency range in order to produce a simple corrosion alert result. The device is equipped with a digital interface and can be connected to a personal computer to carry out a complete frequency analysis and perform a more complex data processing

Exposure-Tolerant Imaging Solution forCultural Heritage Monitoring

This paper describes a simple and cheap solution specifically designed for monitoring the degradation of thin coatings employed for metal protection. The proposed solution employs a commercial photocamera and a frequency-domain-based approach that is capable of highlighting the surface uniformity changes due to initial corrosion. Even though the proposed solution is specifically designed to monitor the long-time performance of protective coatings employed for the restoration of silver artifacts, it can be successfully used also for assessing the conservation state of other ancient metallic works of art. The proposed solution is made tolerant to exposure changes by using a procedure for sensor nonlinearity identification and correction, does not require a precise lighting control, and employs only free open-source software, so that its overall cost is very low and can be used also by not specifically trained operator

Value Matters: The Long-run Behavior of Stock Index Returns

We present a simple dynamical model of stock index returns grounded on the ability of the Cyclically Adjusted Price Earning valuation ratio devised by Robert Shiller to predict long-horizon performances of the market. Specifically, within the model returns are driven by a fundamental term and an autoregressive component perturbed by external random disturbances. The autoregressive component arises from the agents\u2019 belief that expected returns are higher in bullish markets than in bearish ones. The fundamental value, towards which fundamentalists expect that the current price should revert, varies in time and depends on the initial averaged Price-to- Earnings ratio. We demonstrate both analytically and by means of numerical experiments that the long-run behavior of the stylized dynamics agrees with empirical evidences reported in literature

Incrementality and Hierarchies in the Enrollment of Multiple Synergies for Grasp Planning

Postural hand synergies or eigenpostures are joint angle covariation patterns observed in common grasping tasks. A typical definition associates the geometry of synergy vectors and their hierarchy (relative statistical weight) with the principal component analysis of an experimental covariance matrix. In a reduced complexity representation, the accuracy of hand posture reconstruction is incrementally improved as the number of synergies is increased according to the hierarchy. In this work, we explore whether and how hierarchy and incrementality extend from posture description to grasp force distribution. To do so, we study the problem of optimizing grasps w.r.t. hand/object relative pose and force application, using hand models with an increasing number of synergies, ordered according to a widely used postural basis. The optimization is performed numerically, on a data set of simulated grasps of four objects with a 19-DoF anthropomorphic hand. Results show that the hand/object relative poses that minimize (possibly locally) the grasp optimality index remain roughly the same as more synergies are considered. This suggests that an incremental learning algorithm could be conceived, leveraging on the solution of lower dimensionality problems to progressively address more complex cases as more synergies are added. Second, we investigate whether the adopted hierarchy of postural synergies is indeed the best also for force distribution. Results show that this is not the case

Optimal Control for Articulated Soft Robots

Soft robots can execute tasks with safer interactions. However, control techniques that can effectively exploit the systems' capabilities are still missing. Differential dynamic programming (DDP) has emerged as a promising tool for achieving highly dynamic tasks. But most of the literature deals with applying DDP to articulated soft robots by using numerical differentiation, in addition to using pure feed-forward control to perform explosive tasks. Further, underactuated compliant robots are known to be difficult to control and the use of DDP-based algorithms to control them is not yet addressed. We propose an efficient DDP-based algorithm for trajectory optimization of articulated soft robots that can optimize the state trajectory, input torques, and stiffness profile. We provide an efficient method to compute the forward dynamics and the analytical derivatives of series elastic actuators (SEA)/variable stiffness actuators (VSA) and underactuated compliant robots. We present a state-feedback controller that uses locally optimal feedback policies obtained from DDP. We show through simulations and experiments that the use of feedback is crucial in improving the performance and stabilization properties of various tasks. We also show that the proposed method can be used to plan and control underactuated compliant robots, with varying degrees of underactuation effectively.Comment: 14 pages, 15 figures, IEEE Transaction on Robotics (TRO

Glass and Jamming Rheology in Soft Particles Made of PNIPAM and Polyacrylic Acid

The phase behaviour of soft colloids has attracted great attention due to the large variety of new phenomenologies emerging from their ability to pack at very high volume fractions. Here we report rheological measurements on interpenetrated polymer network microgels composed of poly(N-isopropylacrylamide) (PNIPAM) and polyacrylic acid (PAAc) at fixed PAAc content as a function of weight concentration. We found three different rheological regimes characteristic of three different states: a Newtonian shear-thinning fluid, an attractive glass characterized by a yield stress, and a jamming state. We discuss the possible molecular mechanisms driving the formation of these states

A microstrip gas avalanche chamber with two-dimensional readout

Abstract A microstrip gas avalanche chamber with a 200 μm anode pitch has been built and successfully tested in our laboratory. A gas gain of 104 and an energy resolution of 18% (FWHM) at 6 keV have been measured using a gas mixture of argon-CO2 at atmospheric pressure. A preliminary measurement of the positional sensitivity indicates that a spatial resolution of 50 μm can be obtained

On the motion/stiffness decoupling property of articulated soft robots with application to model-free torque iterative learning control

This paper tackles the problem of controlling articulated soft robots (ASRs), i.e., robots with either fixed or variable elasticity lumped at the joints. Classic control schemes rely on high-authority feedback actions, which have the drawback of altering the desired robot softness. The problem of accurate control of ASRs, without altering their inherent stiffness, is particularly challenging because of their complex and hard-to-model nonlinear dynamics. Leveraging a learned anticipatory action, Iterative Learning Control (ILC) strategies do not suffer from these issues. Recently, ILC was adopted to perform position control of ASRs. However, the limitation of position-based ILC in controlling variable stiffness robots is that whenever the robot stiffness profile is changed, a different input action has to be learned. Our first contribution is to identify a wide class of ASRs, whose motion and stiffness adjusting dynamics can be proved to be decoupled. This class is described by two properties that we define: strong elastic coupling - relative to motors and links of the system, and their connections - and homogeneity - relative to the characteristics of the motors. Furthermore, we design a torque-based ILC scheme that, starting from a rough estimation of the system parameters, refines the torque needed for the joint positions tracking. The resulting control scheme requires minimum knowledge of the system. Experiments on variable stiffness robots prove that the method effectively generalizes the iterative procedure w.r.t. the desired stiffness profile and allows good tracking performance. Finally, potential restrictions of the method, e.g., caused by friction phenomena, are discussed