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Full-Text Articles in Engineering
Parallel Decomposition Methods For Biomechanical Optimization, B. I. Koh, Jeffrey A. Reinbolt, B. J. Fregly, A. D. George
Parallel Decomposition Methods For Biomechanical Optimization, B. I. Koh, Jeffrey A. Reinbolt, B. J. Fregly, A. D. George
Jeffrey A. Reinbolt
No abstract provided.
Estimation Of Body Segment Parameters From Three-Dimensional Gait Data Using Optimization, B. J. Fregly, Jeffrey A. Reinbolt
Estimation Of Body Segment Parameters From Three-Dimensional Gait Data Using Optimization, B. J. Fregly, Jeffrey A. Reinbolt
Jeffrey A. Reinbolt
No abstract provided.
Zu-Gengs Axiom Vs Cavalieris Theory, Ji-Huan He
Allometric Scaling And Instability In Electrospinning, Ji-Huan He, Yu-Qin Wan, Jian-Yong Yu
Allometric Scaling And Instability In Electrospinning, Ji-Huan He, Yu-Qin Wan, Jian-Yong Yu
Ji-Huan He
The regulation of scale and bifurcation-like instability in electrospinning are intriguing and enduring problems after the technology was invented by Formhals in 1934. Regulatory mechanisms for controlling the radius of electrospun fibers are clearly illustrated in the different states. Generally, the relationship between radius r of jet and the axial distance z from nozzle can be expressed as an allometric equation of the form , the values of the scaling exponent (b) for the initial steady stage, instability stage, and terminal stage are respectively –1/2, –1/4, and 0. Allometry in economy, biology, turbulence, astronomy, neural resistance, conductive textile, and macromolecule …
Evaluation Of Parallel Decomposition Methods For Biomechanical Optimizations, J. F. Schutte, Jeffrey A. Reinbolt, B. J. Fregly, R. T. Haftka, A. D. George
Evaluation Of Parallel Decomposition Methods For Biomechanical Optimizations, J. F. Schutte, Jeffrey A. Reinbolt, B. J. Fregly, R. T. Haftka, A. D. George
Jeffrey A. Reinbolt
As the complexity of musculoskeletal models continues to increase, so will the computational demands of biomechanical optimizations. For this reason, parallel biomechanical optimizations are becoming more common. Most implementations parallelize the optimizer. In this study, an alternate approach is investigated that parallelizes the analysis function (i.e., a kinematic or dynamic simulation) called repeatedly by the optimizer to calculate the cost function and constraints. To evaluate this approach, a system identification problem involving a kinematic ankle joint model was solved using a gradientbased optimizer and three parallel decomposition methods: gradient calculation decomposition, analysis function decomposition, or both methods combined. For a …
Parallel Global Optimization With The Particle Swarm Algorithm, J. F. Schutte, Jeffrey A. Reinbolt, B. J. Fregly, R. T. Haftka, A. D. George
Parallel Global Optimization With The Particle Swarm Algorithm, J. F. Schutte, Jeffrey A. Reinbolt, B. J. Fregly, R. T. Haftka, A. D. George
Jeffrey A. Reinbolt
Present day engineering optimization problems often impose large computational demands, resulting in long solution times even on a modern high-end processor. To obtain enhanced computational throughput and global search capability, we detail the coarse-grained parallelization of an increasingly popular global search method, the particle swarm optimization (PSO) algorithm. Parallel PSO performance was evaluated using two categories of optimization problems possessing multiple local minima—large-scale analytical test problems with computationally cheap function evaluations and medium-scale biomechanical system identification problems with computationally expensive function evaluations. For load-balanced analytical test problems formulated using 128 design variables, speedup was close to ideal and parallel efficiency …