Curve Decomposition for Large Deflection Analysis of Fixed-Guided Beams With Application to Statically Balanced Compliant Mechanisms

Statically balanced compliant mechanisms require no holding force throughout their range of motion while maintaining the advantages of compliant mechanisms. In this paper, a postbuckled fixed-guided beam is proposed to provide the negative stiffness to balance the positive stiffness of a compliant mechanism. To that end, a curve decomposition modeling method is presented to simplify the large deflection analysis. The modeling method facilitates parametric design insight and elucidates key points on the force-deflection curve. Experimental results validate the analysis. Furthermore, static balancing with fixed-guided beams is demonstrated for a rectilinear proof-of-concept prototype.

A Metric to Evaluate and Synthesize Distributed Compliant Mechanisms

Compliant mechanisms with evenly distributed stresses have better load-bearing ability and larger range of motion than mechanisms with compliance and stresses lumped at flexural hinges. In this paper, we present a metric to quantify how uniformly the strain energy of deformation and thus the stresses are distributed throughout the mechanism topology. The resulting metric is used to optimize cross-sections of conceptual compliant topologies leading to designs with maximal stress distribution. This optimization framework is demonstrated for both single-port mechanisms and single-input single-output mechanisms. It is observed that the optimized designs have lower stresses than their nonoptimized counterparts, which implies an ability for single-port mechanisms to store larger strain energy, and single-input single-output mechanisms to perform larger output work before failure.

Sensitivity Gains, Linearity, and Spectral Reproducibility in Nonuniformly Sampled Multidimensional MAS NMR Spectra of High Dynamic Range

Recently, we have demonstrated that considerable inherent sensitivity gains are attained in MAS NMR spectra acquired by nonuniform sampling (NUS) and introduced maximum entropy interpolation (MINT) processing that assures the linearity of transformation between the time and frequency domains. In this report, we examine the utility of the NUS/MINT approach in multidimensional datasets possessing high dynamic range, such as homonuclear C-13-C-13 correlation spectra. We demonstrate on model compounds and on 1-73-(U-C-13,N-15)/74-108-(U-N-15) E. coli thioredoxin reassembly, that with appropriately constructed 50 % NUS schedules inherent sensitivity gains of 1.7-2.1-fold are readily reached in such datasets. We show that both linearity and line width are retained under these experimental conditions throughout the entire dynamic range of the signals. Furthermore, we demonstrate that the reproducibility of the peak intensities is excellent in the NUS/MINT approach when experiments are repeated multiple times and identical experimental and processing conditions are employed. Finally, we discuss the principles for design and implementation of random exponentially biased NUS sampling schedules for homonuclear C-13-C-13 MAS correlation experiments that yield high-quality artifact-free datasets.