Multi-contact vertical ladder climbing with an HRP-2 humanoid

We describe the research and the integration methods we developed to make the HRP-2 humanoid robot climb vertical industrial-norm ladders. We use our multi-contact planner and multi-objective closed-loop control formulated as a QP (quadratic program). First, a set of contacts to climb the ladder is planned off-line (automatically or by the user). These contacts are provided as an input for a finite state machine. The latter builds supplementary tasks that account for geometric uncertainties and specific grasps procedures to be added to the QP controller. The latter provides instant desired states in terms of joint accelerations and contact forces to be tracked by the embedded low-level motor controllers. Our trials revealed that hardware changes are necessary, and parts of software must be made more robust. Yet, we confirmed that HRP-2 has the kinematic and power capabilities to climb real industrial ladders, such as those found in nuclear power plants and large scale manufacturing factories (e.g. aircraft, shipyard) and construction sites.     

Shear Stress in Smooth Rectangular Open-Channel Flows

The average bed and sidewall shear stresses in smooth rectangular open-channel flows are determined after solving the continuity and momentum equations. The analysis shows that the shear stresses are function of three components: (1) gravitational; (2) secondary flows; and (3) interfacial shear stress. An analytical solution in terms of series expansion is obtained for the case of constant eddy viscosity without secondary currents. In comparison with laboratory measurements, it slightly overestimates the average bed shear stress measurements but underestimates the average sidewall shear stress by 17% when the width–depth ratio becomes large. A second approximation is formulated after introducing two empirical correction factors. The second approximation agrees very well (R2>0.99 and average relative error less than 6%) with experimental measurements over a wide range of width–depth ratios.     

Environmental Fatigue and Static Behavior of RC Beams Strengthened with Carbon-Fiber-Reinforced Polymer

Many countries around the world have tremendous needs to repair and strengthen their transportation infrastructure. Almost everywhere, traffic loads have reached levels largely exceeding design expectations. Northern countries also experience severe winter conditions that are combined with an extensive use of deicing salts and accelerate structural deterioration. In Canada, the extent of deterioration has prompted many authorities, including the federal and provincial governments, to investigate the potential use of fiber-reinforced polymer products to extend the life of their existing structures. However, it is widely recognized that the large-scale implementation of these products is often impaired by the lack of data on their durability. This paper presents an experimental project undertaken in order to assess the durability of reinforced concrete beams externally strengthened with two types of carbon-fiber-reinforced polymer (CFRP). The beams were first exposed to either wet-dry cycles or continuous immersion in water and then were loaded in fatigue. Finally, they were tested quasi-statically under four-point bending up to failure. The test results presented here provide some insights on the potential long-term performance of CFRP-strengthened beams exposed to severe environmental conditions.     

Oxydation De L'alliage De Titane Ta6V4 Par L'oxygene Sec Entre 700°C Et 1000°C—I. Resultats Experimentaux

The oxidation kinetics of the titanium-base alloy Ti4V6Al was studied between 700 and 1000°C at several pressures of pure oxygen. The result shows a difference in oxidation behaviour between the Ti4V6A1 alloy and pure Ti at high temperatures. (The distinct kinetic law reported has numerous stages corresponding to successive accelerations and reductions in corrosion rate.) The study of the products formed (microscopic observation of cross-sections, examination of the distribution of elements with the microprobe) showed a stratified scale structure with several sublayers of A1₂O₃ parallel to the reaction front.     

Numerical modelling of interfacial soil erosion with viscous incompressible flows

The aim of this study is to develop a numerical model for simulating surface erosion occurring at a fluid/soil interface subject to a flow process. Balance equations with jump relations are used. A penalization procedure including a fictitious domain method is used to compute the Stokes flow around obstacles, in order to avoid body-fitted unstructured meshes and instead use fast and efficient finite volume approximations on Cartesian meshes. The evolution of the water/soil interface is described by using a level set function. The ability of the model to predict the interfacial erosion of soils is confirmed by several numerical simulations.     

Effects of photoperiod and pair-feeding on lactation of cows fed corn or barley grain in total mixed rations

Effects of photoperiod and type of grain were assessed using 47 cows (wk 1; 59.5 d of lactation) exposed daily to 16 h of light (long day) and fed randomly one of two diets containing an equal amount of cracked corn or rolled barley. During wk 5, cows were assigned within each diet to long day and ad libitum feeding, short day (8 h of light: 2 h of dark: 2 h of light: 12 h of dark) and ad libitum feeding, or long day and ad libitum feeding (wk 5 to 8) followed by pair feeding with short day cows between wk 9 and 16. Milk composition was not affected by treatments. Between wk 9 and 16, long day cows fed for ad libitum consumption or pair fed produced 5 to 11% more milk than cows exposed to short day; feed intake of long day cows fed for ad libitum consumption was greater than short short day and long day cows pair fed cows. Milk yield and total feed intake were not affected by type of grain in the diet. In conclusion, long day photoperiod increased milk yield and feed intake.     

POLYBiNN: Binary Inference Engine for Neural Networks using Decision Trees

Journal of Signal Processing Systems - Convolutional Neural Networks (CNNs) and Deep Neural Networks (DNNs) have gained significant popularity in several classification and regression applications....