Sādhanā最新文献

Multi-body systems, like robotic mechanisms, may frequently encounter impacts while interacting with the environment. These non-linear impacts are often modeled as instantaneous events using discretized time impulse-based approaches. Although, momentum and energy conservation laws are sufficient to determine a solution for frictionless single point impulse problems, additional assumptions are required to solve simultaneous impacts. We propose a novel method (called QPSIM) to solve such simultaneous collision problems in links connected by frictionless joints by generalizing the quadratic programming (QP) based simultaneous impact model for unconstrained rigid bodies presented in the work of Rakshit and Chatterjee [35]. Two constraint equations are derived, which when included in the QP problem, results in a solution containing both collision impulses as well as joint reaction impulses and impulsive moments. Additional constraints depicting the physical laws of contact mechanics are also used in the simultaneous impact problem. A generalized matrix based derivation of the constraints and the impact model is presented which is applicable to both closed-loop and open-chain mechanisms. The solution is formed by the impulse set that minimizes the system’s net change in kinetic energy. QPSIM does not require an impulse propagation sequence to be assumed and is a computationally efficient alternative to the modeling of collisions in a force-based domain. Results for simultaneous collision scenarios in two planar and one spatial mechanisms are presented in this paper. In addition, this method is applied to solve a simultaneous impact problem on a top-hammer drill machine which is often used in mines and quarries. Moreover, the results are compared with results obtained using Linear Complementarity and ADAMS software simulations. The results show that QPSIM never results in an increase in kinetic energy and is able to predict contact separation between bodies having zero pre-impact relative velocity of approach. The solutions also exhibit an acceptable correlation with ADAMS software simulations.

This study investigates the intricate relationship between surface roughness (Ra) and the extent of chip segmentation (Gs) during the milling process of A7075 aluminum alloy across a wide range of cutting speeds. The experimental setup involves variations in feed rate (F) from 0.1 to 0.3 (mm/rev), depth of cut (t) from 0.9 to 1.6 mm, and normal cutting speed (V) ranging from 200 to 500 m/min. By rigorously analyzing experimental data, a robust model is developed, elucidating the complex interdependence of cutting parameters (V, F, t) on surface roughness and chip segmentation. Particularly noteworthy is the significance of this relationship in high-speed machining, specifically ranging from 900 to 1200 m/min. Our clarified findings confirm that feed rate (F) and depth of cut (t) have negligible effects on both surface roughness (Ra) and chip segmentation degree (Gs), while cutting speed (V) significantly influences surface roughness (Ra) and the degree of chip segmentation (Gs) in high-speed machining. This influence becomes particularly prominent at higher speeds, as indicated by ANOVA analysis. Cutting speeds ranging from 900 to 1600 m/min exert an 84.9% influence on chip segmentation degree (Gs) and an 85.4% influence on surface roughness (Ra). The derived mathematical model is rigorously validated under standard and high-speed machining conditions, demonstrating a maximum deviation of 8.58% for Ra and 8.4% for Gs at V = 450 m/min. Notably, this deviation reduces to 4.03% for Ra and 1.92% for Gs at a cutting speed of V = 1200 m/min. To enhance the model's applicability, a comprehensive dataset spanning cutting speeds of 250 to 2000 m/min was utilized. The resulting mathematical relationship between Ra and Gs was rigorously validated against experimental data, revealing evenly distributed bias data with a mean deviation of 3.11% for Gs and 3.54% for Ra.

This article presents a novel approach towards solving the problem of Word Sense Disambiguation (WSD) for Bengali Text. The algorithm used in this work is a modification of Lesk Algorithm. In the original algorithm, the overlap between the “context bag” and the “sense bag” items from the lexical resource (WordNet) are calculated using word pair matching. In the current approach the overlap is calculated by adopting semantic similarity measure using the fastText subword embeddings. The approach can efficiently handle unknown wordforms and discover the latent semantics of words. Significant progress has been made in WSD for English and other European Languages. Indian languages like Bengali still pose a formidable challenge. The dataset used for the work is individual sentences from the Bengali Wikipedia which is a huge collection of Bengali text ( 96 K Webpages with 1700 K sentences), the Indo WordNet for Bengali language and Bengali Online Dictionary. The results of the experiments performed are promising. The target words which have semantically distinct synsets in the WordNet give a high F1 score. The F1 score achieved is 80% which is well over the baseline and shows significant improvement over the other knowledge-based approaches tried on low resource Indian languages.

Counter circuits play a crucial role in Modified Booth Wallace (MBW) tree multiplier architectures, serving as fundamental partial product accumulation circuits. In this paper, we propose a novel architecture for a low-power 7:3 counter based on hybrid full adders (HFAs). Two new designs of HFAs are introduced to realize this counter, enabling the implementation of a 7:3 counter with only 54 transistors. Simulation results demonstrate that the proposed HFA-based 7:3 counter architecture consumes a power of 22.6 µW with a latency of 305 ps, showcasing significant improvements in power-delay-product compared to state-of-the-art designs.

Electric discharge machining (EDM) is a non-conventional manufacturing process that has several variations, one of which is powder mixed EDM that involves adding small particles to the dielectric. In this present experimental study, titanium powder blended in green dielectric, deionized water with different concentrations has been used for die-sinking EDM of Nimonic C-263. In order to obtain enhanced material removal rate, reduced tool wear rate and lesser surface roughness, relevant input parameters are optimized using TOPSIS. Cylindrical copper rod has been used as the tool electrode and a varying flushing pressure is applied to remove the deposited debris from the machining zone. The optimal parametric values are found to be as follows; pulse-on-time = 4 µs, peak current = 10 A, pulse-off-time = 5 µs, flushing pressure = 1 kg/cm², and powder concentration = 9 g/lit. SEM micrographs indicate that a better surface finish is achieved by increasing the concentration of the powder in the dielectric at lower values of peak current.