Analysis of temporal jitter in a copper vapor laser system

Temporal jitter in a magnetic pulse compression based copper vapor laser (CVL) system is analyzed by considering ripple present in the input dc power supply and ripple present in the magnetic core resetting power supply. It is shown that the jitter is a function of the ratio of operating voltage to the designed voltage, percentage ripple, and the total propagation delay of the magnetic pulse compression circuit. Experimental results from a CVL system operating at a repetition rate of 9 kHz are presented.     

Soft computing-based approaches to predict energy consumption and stability margin of six-legged robots moving on gradient terrains

Soft computing-based approaches have been developed to predict specific energy consumption and stability margin of a six-legged robot ascending and descending some gradient terrains. Three different neuro-fuzzy and one neural network-based approaches have been developed. The performances of these approaches are compared among themselves, through computer simulations. Genetic algorithm-tuned multiple adaptive neuro-fuzzy inference system is found to perform better than other three approaches for predicting both the outputs. This could be due to a more exhaustive search carried out by the genetic algorithm in comparison with back-propagation algorithm and the use of two separate adaptive neuro-fuzzy inference systems for two different outputs. A designer may use the developed soft computing-based approaches in order to predict specific energy consumption and stability margin of the robot for a set of input parameters, beforehand.     

Composite indicator for railway infrastructure management

Railway Engineering Science - The assessment and analysis of railway infrastructure capacity is an essential task in railway infrastructure management carried out to meet the required quality and...     

A multi-step linearization technique for a class of boundary value problems in non-linear mechanics

Non-linear finite element analyses of structures (such as beams) involve construction of weak solutions for the governing equations. While a weak approach weakens the differentiability requirements of the so-called shape functions, the governing equations are only satisfied in an integral sense and not point-wise, or, even path-wise. Moreover, use of a finite mesh leads to a stiffening of the numerical model. While strong solutions obtained through some of the existing mesh-free collocation methods overcomes some of these lacunae to an extent, the quality of the numerical solutions would be considerably improved if the computational algorithm were able to faithfully reproduce (or approximate or preserve) certain geometrical features of the response surfaces or manifolds. This paper takes the first step towards realizing this objective and proposes a multi-step transversal linearization (MTL) technique for a class of non-linear boundary value problems, which are treated as conditionally dynamical systems. Numerical explorations are performed, to a limited extent, through applications to large deflection analyses of planar beams with or without plastic deformations.     

Cashing in on Caching: An Architecture for Time-Bounded Knowledge-Based Problem Solving

Knowledge-based computing, in general, suffers from an inherent open-endedness that precludes its application in time-bounded domains where an answer must be computed within a stipulated time limit. We examine a two-way improvement of the shortcomings: a knowledge representation scheme that provides easy access to relevant knowledge and thereby reduces search time, and a reasoning scheme that is algorithmic in nature and thus makes computational requirements meaningfully estimable.In this work, we offer a cache-based architecture that is capable of both storing knowledge in different formats (e.g. rules, cases), and invoking an appropriate reasoning scheme to fit the available computing time. The cache helps in retrieving the most relevant pieces of knowledge (not only exact matches) required for solving a given problem. This cache relies on a reasoning tactic, knowledge interpolation, that can generate a solution from two near-matches in an algorithmic way, to generate time-bounded solutions. We illustrate the design of such a cache for solving resource allocation problems in the domain of shortwave radio transmission and evaluate its performance in observing imposed temporal bounds.