nonlinear behavior
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2022 ◽  
Vol 8 ◽  
Author(s):  
Michele Di Lecce ◽  
Onaizah Onaizah ◽  
Peter Lloyd ◽  
James H. Chandler ◽  
Pietro Valdastri

The growing interest in soft robotics has resulted in an increased demand for accurate and reliable material modelling. As soft robots experience high deformations, highly nonlinear behavior is possible. Several analytical models that are able to capture this nonlinear behavior have been proposed, however, accurately calibrating them for specific materials and applications can be challenging. Multiple experimental testbeds may be required for material characterization which can be expensive and cumbersome. In this work, we propose an alternative framework for parameter fitting established hyperelastic material models, with the aim of improving their utility in the modelling of soft continuum robots. We define a minimization problem to reduce fitting errors between a soft continuum robot deformed experimentally and its equivalent finite element simulation. The soft material is characterized using four commonly employed hyperelastic material models (Neo Hookean; Mooney–Rivlin; Yeoh; and Ogden). To meet the complexity of the defined problem, we use an evolutionary algorithm to navigate the search space and determine optimal parameters for a selected material model and a specific actuation method, naming this approach as Evolutionary Inverse Material Identification (EIMI). We test the proposed approach with a magnetically actuated soft robot by characterizing two polymers often employed in the field: Dragon Skin™ 10 MEDIUM and Ecoflex™ 00-50. To determine the goodness of the FEM simulation for a specific set of model parameters, we define a function that measures the distance between the mesh of the FEM simulation and the experimental data. Our characterization framework showed an improvement greater than 6% compared to conventional model fitting approaches at different strain ranges based on the benchmark defined. Furthermore, the low variability across the different models obtained using our approach demonstrates reduced dependence on model and strain-range selection, making it well suited to application-specific soft robot modelling.


2022 ◽  
Author(s):  
Yi-Xuan Shan ◽  
Hui-Lan Yang ◽  
Hong-Bin Wang ◽  
Shuai Zhang ◽  
Ying Li ◽  
...  

Abstract Astrocytes have a regulatory function on the central nervous system (CNS), especially in the temperature sensitive hippocampal region. In order to explore the thermosensitive dynamic mechanism of astrocytes in CNS, we establish a neuron-astrocyte minimum system to analyze the synchronization change characteristics based on Hodgkin-Huxley model, in which a pyramidal cell and an interneuron are connected by an astrocyte. Besides, the temperature range set 0°C-40°C to juggle theoretical calculation and reality of brain environment. It is represented that the synchronization of thermosensitive neurons exhibits nonlinear behavior with change of astrocyte parameters. At temperature range of 0°C-18°C, the effects of astrocyte can provide tremendous influence to neurons in synchronization. We found existence of a value for inositol triphosphate (IP3) production rate and feedback intensities of astrocyte to neurons, which can ensure the weak synchronization of two neurons. In addition, it is revealed that the regulation of astrocyte to pyramidal cell is more sensitive than that to interneuron. Finally, it is shown that the synchronization and phase transition of neurons depend on the change of Ca2+ concentration at the temperature of weak synchronization. The results in this paper would provide some enlightenment in mechanism of cognitive dysfunction and neurological disorders with astrocytes.


2022 ◽  
Vol 4 (2) ◽  
Author(s):  
Chen Wen-qiang ◽  
Li Yi-jia

AbstractExisting analytical models usually fail to match with the actual conditions due to ignoring the nonlinear behavior of the surrounding material reaction force, which changes progressively with the joint shear displacement from elastic stage to yield stage. To tackle this problem, this study proposes a new analytical model to describe the bolt deformation and bolt contribution from elastic stage to plastic stage. The developed model is verified by available experimental direct shear tests of bolted joints and compared with existing models. Then, based on this model, the effects of the joint dilation angle, the bolt installation angle, the friction angle, and the surrounding material strength on bolt contribution are also analyzed and its implication is further discussed. Our results show that the proposed model can precisely describe the evolution of bolt contribution from elastic stage to plastic stage. Compared with surrounding material strength, the augmentation of the joint dilation angle and friction angle is more beneficial to increase the bolt contribution and the optimal installation angle. The work presented is to attempt to provide a reference for the understanding of bolting mechanism of jointed rock mass, the development of bolting theories and the practice of bolting engineering.


2022 ◽  
Vol 70 (1) ◽  
pp. 13-30
Author(s):  
Gerwald Lichtenberg ◽  
Georg Pangalos ◽  
Carlos Cateriano Yáñez ◽  
Aline Luxa ◽  
Niklas Jöres ◽  
...  

Abstract The paper introduces a subclass of nonlinear differential-algebraic models of interest for applications. By restricting the nonlinearities to multilinear polynomials, it is possible to use modern tensor methods. This opens the door to new approximation and complexity reduction methods for large scale systems with relevant nonlinear behavior. The modeling procedures including composition, decomposition, normalization, and multilinearization steps are shown by an example of a local energy system with a nonlinear electrolyzer, a linear buck converter and a PI controller with saturation.


Author(s):  
Ata Donmez ◽  
Ahmet Kahraman

Abstract Dynamic response of a gear pair subjected to input and output torque or velocity fluctuations is examined analytically. Such motions are commonly observed in various powertrain systems and identified as gear rattle or hammering motions with severe noise and durability consequences. A reduced-order torsional model is proposed along with a computationally efficient piecewise-linear solution methodology to characterize the system response including its sensitivity to excitation parameters. Validity of the proposed model is established through comparisons of its predictions to measurements from a gear rattle experimental set-up. A wide array of nonlinear behavior is demonstrated through presentation of periodic and chaotic responses in the forms of phase plots, Poincaré maps, and bifurcation diagrams. The severity of the resultant impacts on the noise outcome is also assessed through a rattle severity index defined by using the impact velocities.


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