Interactive re-design of a novel variable geometry bicycle saddle to prevent neurological pathologies

Sequenzia, Gaetano; Fatuzzo, Gabriele; Oliveri, S. M.; Barbagallo, Raffaele

doi:10.1007/s12008-015-0293-0

Cited by 18 publications

(9 citation statements)

References 33 publications

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“…A linear elastic model is not able to catch the finite deformation of the pipe [37]. All of that is also considered in the design of complex mechanical systems [38][39][40] that involved models with hysteresis [41,42] aimed to solve thermodynamic problems [43] and to perform dynamic analysis [44][45][46] and optimization [47][48][49] evaluating also the structural displacements.…”

Section: Mathematical Modelmentioning

confidence: 99%

Fluid–Structure Interaction Modeling Applied to Peristaltic Pump Flow Simulations

et al. 2019

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In this study, fluid–structure interaction (FSI) modeling was applied for predicting the fluid flow in a specific peristaltic pump, composed of one metallic roller and a hyperelastic tube pumping a viscous Newtonian fluid. Hyperelastic material dynamics and turbulence flow dynamics were coupled in order to describe all the physics of the pump. The commercial finite element software ABAQUS 6.14 was used to investigate the performance of the pump with a 3D transient model. By using this model, it was possible to predict the von Mises stresses in the tube and flow fluctuations. The peristaltic pump generated high pressure and flow pulses due to the interaction between the roller and the tube. The squeezing and relaxing of the tube during the operative phase allowed the liquid to have a pulsatile behavior. Numerical simulation data results were compared with one cycle pressure measurement obtained from pump test loop data, and the maximum difference between real and simulated data was less than 5%. The applicability of FSI modeling for geometric optimization of pump housing was also discussed in order to prevent roller and hose parts pressure peaks. The model allowed to investigate the effect of pump design variations such as tube occlusion, tube diameter, and roller speed on the flow rate, flow fluctuations, and stress state in the tube.

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Section: Mathematical Modelmentioning

confidence: 99%

Fluid–Structure Interaction Modeling Applied to Peristaltic Pump Flow Simulations

et al. 2019

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“…This effect as a function of the length-to-thickness ratio. It has been noted by different authors [25][26][27][28] that the transverse shear effect:…”

Section: Testingmentioning

confidence: 99%

Vibration-Based Experimental Identification of the Elastic Moduli Using Plate Specimens of the Olive Tree

et al. 2019

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Mechanical parameters of the olive wood plate have been computed by data inversion of vibrational experimental tests. A numerical-experimental method has allowed the evaluation of the two transverse shear moduli and the four in-plane moduli of a thick orthotropic olive tree plate. Therefore, the natural flexural vibration frequencies of olive trees plates have been evaluated by the impulse technique. For our purposes, we define the objective function as the difference between the numerical computation data and the experimental ones. The Levenberg-Marquardt algorithm was chosen as optimization strategy in order to minimize the matching error: the evaluation of the objective function has required a complete finite element simulation by using the ANSYS code. As input, we have used the uniaxial test data results obtained from the olive plates. The converged elastic moduli with n = 10 natural modes were E 1 = 14.8 GPa, E 2 = 1.04 GPa, G 12 = 4.45 GPa, G 23 = 4.02 GPa, G 13 = 4.75 GPa, ν 12 = 0.42, and ν 13 = 0.42. The relative root mean square (RMS) errors between the experimental frequencies and the computed one is 9.40%. Then, it has been possible to obtain a good agreement between the measured and calculated frequencies. Therefore, it has been found that for plates of moderate thickness the reliability of the estimated values of the transverse shear moduli is good.

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“…Finally, the third constraint is related to the surface accuracy, since the RMS error must be lower than the desired design value RMS target . This is a typical constrained optimization problem, largely used in the design optimization of complex systems [46][47][48][49] and mechanisms [50][51][52]. The optimization problem can be summarised as follows:…”

Section: Rigid Ring Truss Support: Tie Calibrationmentioning

confidence: 99%

Tie-System Calibration for the Experimental Setup of Large Deployable Reflectors

et al. 2019

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The trade-off between the design phase and the experimental setup is crucial in satisfying the accuracy requirements of large deployable reflectors. Manufacturing errors and tolerances change the root mean square (RMS) of the reflecting surface and require careful calibration of the tie-rod system to be able to fit into the initial design specifications. To give a possible solution to this problem, two calibration methods—for rigid and flexible ring truss supports, respectively—are described in this study. Starting from the acquired experimental data on the net nodal co-ordinates, the initial problem of satisfying the static equilibrium with the measured configuration is described. Then, two constrained optimization problems (for rigid or flexible ring truss supports) are defined to meet the desired RMS accuracy of the reflecting surface by modifying the tie lengths. Finally, a case study to demonstrate the validity of the proposed methods is presented.

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Interactive re-design of a novel variable geometry bicycle saddle to prevent neurological pathologies

Cited by 18 publications

References 33 publications

Fluid–Structure Interaction Modeling Applied to Peristaltic Pump Flow Simulations

Fluid–Structure Interaction Modeling Applied to Peristaltic Pump Flow Simulations

Vibration-Based Experimental Identification of the Elastic Moduli Using Plate Specimens of the Olive Tree

Tie-System Calibration for the Experimental Setup of Large Deployable Reflectors

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