Failure mode transition and energy dissipation in naturally occurring composites

The microstructural aspects of compressive inelastic deformation in balsa wood are investigated with emphasis on the failure mode transition and its effects on energy dissipation characteristics. The architectural features as well as the composite character of cell wall ultrastructure are discussed in a framework to understand the complex interrelationship between microstructure and macroscopic behavior in this extremely lightweight cellular biocomposite. Based on this discussion and experimental results, it is concluded that the biomimetic approach may prove to be a viable strategy in designing composite structures with high specific energy absorption capacity.     

Replacement of beef fat in Frankfurters by interesterified palm,cottonseed and olive oils

Three interesterified vegetable oils (IVOs) prepared from palm, cottonseed, and olive oil, respectively, have been studied for application to Frankfurters. Beef fat (10%) was replaced by one of the IVOs at 20, 60 or 100%. Fatty acid composition of the lipid fraction in the Frankfurters and saturated/unsaturated ratios were established for all batches. We found that total or partial replacement of beef fat by IVOs did not lead to significant changes in appearance, colour, texture, flavour or sensory score. We conclude that IVOs may be successfully applied as beef fat substitutes in Frankfurters.     

On methods of defuzzification of parametrically represented fuzzy numbers

A comparative analysis of such methods of defuzzification of fuzzy numbers as WABL (Weighted Averaging Based on Levels), centroid, and mean of maxima (MOM) is presented in the study. Analytic formulas are presented for calculating the defuzzification values for parametrically represented fuzzy numbers of triangular and trapezoidal form.     

Face relighting using discriminative 2D spherical spaces for face recognition

As part of the face recognition task in a robust security system, we propose a novel approach for the illumination recovery of faces with cast shadows and specularities. Given a single 2D face image, we relight the face object by extracting the nine spherical harmonic bases and the face spherical illumination coefficients by using the face spherical spaces properties. First, an illumination training database is generated by computing the properties of the spherical spaces out of face albedo and normal values estimated from 2D training images. The training database is then discriminately divided into two directions in terms of the illumination quality and light direction of each image. Based on the generated multi-level illumination discriminative training space, we analyze the target face pixels and compare them with the appropriate training subspace using pre-generated tiles. When designing the framework, practical real-time processing speed and small image size were considered. In contrast to other approaches, our technique requires neither 3D face models nor restricted illumination conditions for the training process. Furthermore, the proposed approach uses one single face image to estimate the face albedo and face spherical spaces. In this work, we also provide the results of a series of experiments performed on publicly available databases to show the significant improvements in the face recognition rates.     

Production of NiO,NiO/Ag,NiO/Au,and NiO/Pt hollow spheres by using block copolymer stabilized microspheres as a template

Hollow spheres of nickel oxide (NiO) and silver, gold, and platinum nanoparticle loaded NiO composites were successfully produced by using polystyrene (PS) latexes as hard template. Due to the presence of tertiary amine based diblock copolymer stabilizer on the surface of PS, the tertiary amine functional groups provided homogene deposition of nickel hydroxide, and then the precursor NiO salt production on the surface of PS latexes with a controlled precipitation technique. Then, NiO and NiO/metal NP hollow spheres were produced by calcination at 600 °C. Thermogravimetric analysis indicated that the amounts of NiO and NiO-composite after calcination were in the range of 21.1–29.7 wt%. The diameters of metal oxide spheres were in the range of 2.0–2.7 μm and the shell thickness were in the range of 250–350 nm. These structures had very low densities due to their porous and hollow structures and had outer layers with highly rough surfaces due to formation of nanosheets, which may offer important advantages for catalysis studies.     

Effect of CR and FT-paraffin versus SBS modification in terms of conventional and rheological properties

In this study, the rheological and conventional properties of binders prepared with crumb rubber (CR) and FT-paraffin were compared to styrene-butadiene-styrene (SBS)-modified binders’ properties. The objective of this study was to determine which modified binders in different combinations of the CR and the FT-paraffin exhibited better performance than the SBS-modified binders, in terms of conventional and rheological properties. Results showed that the additives exhibited different performances for different types of tests. Many of the combinations including the common usage of the CR and the FT-paraffin performed better at high temperature than the SBS modification. Overall, the test results show that the binders prepared by 6% CR with 3 and 4% FT-paraffin and those prepared with 8% CR with 3% FT-paraffin were better binders than the 4% SBS-modified binder, in terms of low and high temperature properties.     

Control of underactuated planar pronking through an embedded spring-mass Hopper template

Autonomous use of legged robots in unstructured, outdoor settings requires dynamically dexterous behaviors to achieve sufficient speed and agility without overly complex and fragile mechanics and actuation. Among such behaviors is the relatively under-studied pronking (aka. stotting), a dynamic gait in which all legs are used in synchrony, usually resulting in relatively slow speeds but long flight phases and large jumping heights. Instantiations of this gait for robotic systems have been mostly limited to open-loop strategies, suffering from severe pitch instability for underactuated designs due to the lack of active feedback. However, both the kinematic simplicity of this gait and its dynamic nature suggest that the Spring-Loaded Inverted Pendulum model (SLIP) would be a good basis for the implementation of a more robust feedback controller for pronking. In this paper, we describe how template-based control, a controller structure based on the embedding of a simple dynamical “template” within a more complex “anchor” system, can be used to achieve very stable pronking for a planar, underactuated hexapod robot. In this context, high-level control of the gait is regulated through speed and height commands to the SLIP template, while the embedding controller ensures the stability of the remaining degrees of freedom. We use simulation studies to show that unlike existing open-loop alternatives, the resulting control structure provides explicit gait control authority and significant robustness against sensor and actuator noise.     

An assessment of total RMR classification system using unified simulation model based on artificial neural networks

Engineering design has great importance in the cost and safety of engineering structures. Rock mass rating (RMR) system has become a reliable and widespread pre-design system for its ease of use and variety in engineering applications such as tunnels, foundations, and slopes. In RMR system, six parameters are employed in classifying a rock mass: uniaxial compressive strength of intact rock material (UCS), rock quality designation (RQD), spacing of discontinuities (SD), condition of discontinuities (CD), condition of groundwater (CG), and orientation of discontinuities (OD). The ratings of the first three parameters UCS, RQD, and SD are determined via graphic readings where the last three parameters CD, CG, and OD are estimated by the tables that are composed of interval valued linguistic expressions. Because of these linguistic expresions, the estimated rating values of the last three become fuzzy especially when the related conditions are close to border of any two classes. In such cases, these fuzzy situations could lead up incorrect rock class estimations. In this study, an empirical database based on the linguistic expressions for CD, CG, and OD is developed for training Artificial Neural Network (ANN) classifiers. The results obtained from graphical readings and ANN classifiers are unified in a simulation model (USM). The data obtained from five different tunnels, which were excavated for derivation purpose, are used to evaluate classification results of conventional method and proposed model. Finally, it is noted that more accurate and realistic ratings are reached by means of proposed model.     

Parallel force measurement with a polymeric microbeam array using an optical microscope and micromanipulator

An image analysis method and its validation are presented for tracking the displacements of parallel mechanical force sensors. Force is measured using a combination of beam theory, optical microscopy, and image analysis. The primary instrument is a calibrated polymeric microbeam array mounted on a micromanipulator with the intended purpose of measuring traction forces on cell cultures or cell arrays. One application is the testing of hypotheses involving cellular mechanotransduction mechanisms. An Otsu-based image analysis code calculates displacement and force on cellular or other soft structures by using edge detection and image subtraction on digitally captured optical microscopy images. Forces as small as 250+/-50 nN and as great as 25+/-2.5 microN may be applied and measured upon as few as one or as many as hundreds of structures in parallel. A validation of the method is provided by comparing results from a rigid glass surface and a compliant polymeric surface.