Prediction of Polymer Wear—An Analytical Model and Experimental Validation

Because of its industrial relevance, wear of engineering polymers has been studied extensively both experimentally and theoretically. The wear mechanism of polymers is complex due to the influence of numerous parameters and it has long been realized that a predicting tool for wear of polymers in dry and lubricated sliding is of practical importance. Polymer wear models hitherto have been largely done by fitting the experimental data to an empirical equation and some major contributions have been made by a number of authors in this area. However, a more fundamental approach would be to analyze the experimental evidence collectively on the basis of the variables involved and the mechanisms leading to particle detachment. Although some progress has been made in this direction, a need exists to consolidate the major experimental findings in order to develop a comprehensive analytical wear model. The present work attempts to develop such a wear model and validate the proposed model experimentally. The wear equations are presented in two groups, one representing primarily abrasive wear and the other the fatigue mechanism, since the two mechanisms operate in distinct roughness ranges. Each group consists of four equations representing different contact speed and temperature ranges. The results indicate that the surface forces dominate in the low roughness range while at the higher roughness ranges abrasive wear is predominant. Among other observations the results also indicate that a unique value of the ratio of equivalent elastic modulus to hardness (E^//H) exists where wear may either be insignificant or very large depending on the parametric combination. These predictions are likely to be of practical importance.     

Economic evaluation of floating gardening as a means of adapting to climate change in Bangladesh

This paper offers an economic evaluation of the floating garden as a means of adapting to climate change in Bangladesh. The study showed that the monthly income of some farmers using such gardens increased from US$12.02 to US$48.08. These folk farmers lacked alternative work especially during the monsoon period. The floating garden uses available natural resources, adjusts to wet conditions and helps the flood-prone people to earn a living, and can be an adaptive response to frequent disaster events in Bangladesh.     

Network virtualization: state of the art and research challenges [Topics in Network and Service Management]

Recently network virtualization has been pushed forward by its proponents as a long-term solution to the gradual ossification problem faced by the existing Internet and proposed to be an integral part of the next-generation networking paradigm. By allowing multiple heterogeneous network architectures to cohabit on a shared physical substrate, network virtualization provides flexibility, promotes diversity, and promises security and increased manageability. However, many technical issues stand in the way of its successful realization. This article investigates the past and the state of the art in network virtualization along with the future challenges that must be addressed to realize a viable network virtualization environment.     

Growth and differentiation potentials in confluent state of culture of human skeletal muscle myoblasts

The transitional behaviors of myoblasts toward differentiation were investigated in the cultures at the low and high seeding densities (respectively, X₀ = 1.0 × 10³ and 2.0 × 10⁵ cells/cm²). In the culture at the low seeding density, an increase in confluence degree accompanied a decrease in growth potential (R_p), being R_p = 0.85 and 0.11 at t = 48 and 672 h, respectively. Myoblasts seeded at the high density resulted in the immediate cessation of growth with keeping the low range of R_p = 0.02–0.09 throughout the culture. The reduction of R_p led to the generation of three subpopulations of cells in proliferative, quiescent and differentiated states. Close cell contacts in the confluent state of high seeding culture induced cell quiescence to a higher extent with suppressing differentiation.     

Reliability analysis of uncertain dynamical systems using correlated function expansion

Reliability analysis of uncertain dynamical systems is considered. The excitations are modeled as non-stationary Gaussian processes, whereas parametric uncertainties due to structural randomness are modeled as non-Gaussian random variables. The structural responses are, therefore, non-Gaussian processes. The limit state is formulated in terms of the extreme value distribution of the response process. Developing these extreme value statistics analytically is not straightforward, which makes failure probability estimations difficult. An alternative procedure is investigated for computing exceedance probabilities. Proposed approach involves generating a full functional operational model, which approximates the original limit surface. Once the approximate form of the original limit state is defined, the failure probability can be obtained by statistical simulation. Thus, the method can be integrated with commercial finite element software, which permits uncertainty analysis of large structures with complexities that include material and geometric nonlinear behavior.     

Intelligent and Efficient Strategy for Unstructured Environment Sensing Using Mobile Robot Agents

In field environments it is not usually possible to provide robots in advance with valid geometric models of its task and environment. The robot or robot teams need to create these models by scanning the environment with its sensors. Here, an information-based iterative algorithm to plan the robot's visual exploration strategy is proposed to enable it to most efficiently build 3D models of its environment and task. The method assumes mobile robot (or vehicle) with vision sensors mounted at a manipulator end-effector (eye-in-hand system). This algorithm efficiently repositions the systems' sensing agents using an information theoretic approach and fuses sensory information using physical models to yield a geometrically consistent environment map. This is achieved by utilizing a metric derived from Shannon's information theory to determine optimal sensing poses for the agent(s) mapping a highly unstructured environment. This map is then distributed among the agents using an information-based relevant data reduction scheme. This method is particularly well suited to unstructured environments, where sensor uncertainty is significant. Issues addressed include model-based multiple sensor data fusion, and uncertainty and vehicle suspension motion compensation. Simulation results show the effectiveness of this algorithm.     

Twinning-induced sluggish evolution of texture during recrystallization in AISI 316L stainless steel after cold rolling

This paper deals with the evolution of texture in AISI 316L austenitic stainless steel during annealing after 95 pct cold rolling. After 95 pct cold rolling, the texture is mainly of the brass type {110}〈112〉, along with a scatter toward the S orientation {123}〈634〉 and Goss orientation {011}〈100〉. Weak evidence of Cu component is observed at this high deformation level. During annealing, recovery is observed before any detectable recrystallization. Recrystallization proceeds through nucleation of subgrain by twinning within the deformed matrix and, later, preferential growth of those to consume the deformed matrix. After recrystallization, the overall texture intensity was weak; however, there are some discernible texture components. There was no existence of the brass component at this stage. Major components are centered on Goss orientation and Cu component {112}〈111〉 as well as the BR component {236}〈385〉. Also, a few orientations come up after recrystallization (i.e., {142}〈2−11〉 and {012}〈221〉). With increase in annealing temperature, the textural evolution shows emergence of weak texture with another new component, {197}〈211〉. The evolution of texture was correlated with the deformation texture through twin chain reaction.