Evaluating the Applicability of Analytical Models for Silicone Tube Mckibben Actuators through Soft Computing

2021 ◽  
Author(s):  
Debadrata Sarkar ◽  
Shounak Dasgupta ◽  
Soumen Sen ◽  
Shibendu Shekhar Roy ◽  
Aman Arora
Keyword(s):  
Soft Computing ◽  
Analytical Models ◽  
Silicone Tube ◽  
Mckibben Actuators

scholarly journals Geomatics and Soft Computing Techniques for Infrastructural Monitoring

2020 ◽  
Vol 12 (4) ◽  
pp. 1606 ◽  
Author(s):  
Vincenzo Barrile ◽  
Antonino Fotia ◽  
Giovanni Leonardi ◽  
Raffaele Pucinotti
Keyword(s):  
Soft Computing ◽  
Structural Model ◽  
Control Unit ◽  
Machine Learning Techniques ◽  
Analytical Models ◽  
Risk Level ◽  
Behavior Monitoring ◽  
Learning Techniques ◽  
Soft Computing Techniques ◽  
The One

Structural Health Monitoring (SHM) allows us to have information about the structure under investigation and thus to create analytical models for the assessment of its state or structural behavior. Exceeded a predetermined danger threshold, the possibility of an early warning would allow us, on the one hand, to suspend risky activities and, on the other, to reduce maintenance costs. The system proposed in this paper represents an integration of multiple traditional systems that integrate data of a different nature (used in the preventive phase to define the various behavior scenarios on the structural model), and then reworking them through machine learning techniques, in order to obtain values to compare with limit thresholds. The risk level depends on several variables, specifically, the paper wants to evaluate the possibility of predicting the structure behavior monitoring only displacement data, transmitted through an experimental transmission control unit. In order to monitor and to make our cities more “sustainable”, the paper describes some tests on road infrastructure, in this contest through the combination of geomatics techniques and soft computing.

A Comprehensive Literature Review on Nature-Inspired Soft Computing and Algorithms

2020 ◽  
pp. 1851-1885
Author(s):  
Bilal Ervural ◽  
Beyzanur Cayir Ervural ◽  
Cengiz Kahraman
Keyword(s):  
Soft Computing ◽  
Bat Algorithm ◽  
Computing Methods ◽  
Analytical Models ◽  
Grey Wolf Optimizer ◽  
Particle Swarm Algorithm ◽  
Bee Colony ◽  
Soft Computing Techniques ◽  
Soft Computing Methods ◽  
Firefly Optimization

Soft Computing techniques are capable of identifying uncertainty in data, determining imprecision of knowledge, and analyzing ill-defined complex problems. The nature of real world problems is generally complex and their common characteristic is uncertainty owing to the multidimensional structure. Analytical models are insufficient in managing all complexity to satisfy the decision makers' expectations. Under this viewpoint, soft computing provides significant flexibility and solution advantages. In this chapter, firstly, the major soft computing methods are classified and summarized. Then a comprehensive review of eight nature inspired – soft computing algorithms which are genetic algorithm, particle swarm algorithm, ant colony algorithms, artificial bee colony, firefly optimization, bat algorithm, cuckoo algorithm, and grey wolf optimizer algorithm are presented and analyzed under some determined subject headings (classification topics) in a detailed way. The survey findings are supported with charts, bar graphs and tables to be more understandable.

A Comprehensive Literature Review on Nature-Inspired Soft Computing and Algorithms

2017 ◽  
pp. 34-68
Author(s):  
Bilal Ervural ◽  
Beyzanur Cayir Ervural ◽  
Cengiz Kahraman
Keyword(s):  
Soft Computing ◽  
Bat Algorithm ◽  
Computing Methods ◽  
Analytical Models ◽  
Grey Wolf Optimizer ◽  
Particle Swarm Algorithm ◽  
Bee Colony ◽  
Soft Computing Techniques ◽  
Soft Computing Methods ◽  
Firefly Optimization

Soft Computing techniques are capable of identifying uncertainty in data, determining imprecision of knowledge, and analyzing ill-defined complex problems. The nature of real world problems is generally complex and their common characteristic is uncertainty owing to the multidimensional structure. Analytical models are insufficient in managing all complexity to satisfy the decision makers' expectations. Under this viewpoint, soft computing provides significant flexibility and solution advantages. In this chapter, firstly, the major soft computing methods are classified and summarized. Then a comprehensive review of eight nature inspired – soft computing algorithms which are genetic algorithm, particle swarm algorithm, ant colony algorithms, artificial bee colony, firefly optimization, bat algorithm, cuckoo algorithm, and grey wolf optimizer algorithm are presented and analyzed under some determined subject headings (classification topics) in a detailed way. The survey findings are supported with charts, bar graphs and tables to be more understandable.

Pressurized artificial muscles

2011 ◽  
Vol 23 (3) ◽  
pp. 255-268 ◽  
Author(s):  
Zhiye Zhang ◽  
Michael Philen
Keyword(s):  
Sliding Mode ◽  
Virtual Work ◽  
Variable Stiffness ◽  
Analytical Models ◽  
Artificial Muscles ◽  
Operational Life ◽  
Potential Applications ◽  
Manufacturing Techniques ◽  
Mckibben Actuators ◽  
Flexible Matrix Composite

Pressurized artificial muscles are reviewed. These actuators consist of stiff reinforcing fibers surrounding an elastomeric bladder and operate using a pressurized internal fluid. The pressurized artificial muscles, known as McKibben actuators or flexible matrix composite actuators, can be applied to a wide array of applications, including prosthetics/orthotics, robots, morphing wing technologies, and variable stiffness structures. Analytical models for predicting the response behavior have used both virtual work methods and continuum mechanics. Various nonlinear control algorithms have been developed, including sliding mode control (SMC), adaptive control, neural networks, etc. In addition to traditional fluid-driving methods, innovative techniques such as chemical and electrical driving techniques are reviewed. With improved manufacturing techniques, the operational life of pressurized artificial muscles has been significantly extended, thus making them suitable for a vast range of potential applications.

Facilitated migration of cells from a transected peripheral nerve over collagen fibers: in vivo observations

1989 ◽  
Vol 47 ◽  
pp. 888-889
Author(s):  
Arthur J. Wasserman ◽  
Azam Rizvi ◽  
George Zazanis ◽  
Frederick H. Silver
Keyword(s):  
Sciatic Nerve ◽  
Peripheral Nerve ◽  
Collagen Gel ◽  
Collagen Fibers ◽  
Control Group ◽  
Guide Tube ◽  
Sprague Dawley ◽  
Silicone Tube ◽  
Thin Sections

In cases of peripheral nerve damage the gap between proximal and distal stumps can be closed by suturing the ends together, using a nerve graft, or by nerve tubulization. Suturing allows regeneration but does not prevent formation of painful neuromas which adhere to adjacent tissues. Autografts are not reported to be as good as tubulization and require a second surgical site with additional risks and complications. Tubulization involves implanting a nerve guide tube that will provide a stable environment for axon proliferation while simultaneously preventing formation of fibrous scar tissue. Supplementing tubes with a collagen gel or collagen plus extracellular matrix factors is reported to increase axon proliferation when compared to controls. But there is no information regarding the use of collagen fibers to guide nerve cell migration through a tube. This communication reports ultrastructural observations on rat sciatic nerve regeneration through a silicone nerve stent containing crosslinked collagen fibers.Collagen fibers were prepared as described previously. The fibers were threaded through a silicone tube to form a central plug. One cm segments of sciatic nerve were excised from Sprague Dawley rats. A control group of rats received a silicone tube implant without collagen while an experimental group received the silicone tube containing a collagen fiber plug. At 4 and 6 weeks postoperatively, the implants were removed and fixed in 2.5% glutaraldehyde buffered by 0.1 M cacodylate containing 1.5 mM CaCl2 and balanced by 0.1 M sucrose. The explants were post-fixed in 1% OSO4, block stained in 1% uranyl acetate, dehydrated and embedded in Epon. Axons were counted on montages prepared at a total magnification of 1700x. Montages were viewed through a dissecting microscope. Thin sections were sampled from the proximal, middle and distal regions of regenerating sciatic plugs.

Soft Computing in Electromagnetics

2015 ◽  
Author(s):  
Balamati Choudhury ◽  
Rakesh Mohan Jha
Keyword(s):  
Soft Computing

Mechanism of irregular crack-propagation in thermal controlled fracture of ceramics induced by microwave

2020 ◽  
Vol 21 (6) ◽  
pp. 610
Author(s):  
Xiaoliang Cheng ◽  
Chunyang Zhao ◽  
Hailong Wang ◽  
Yang Wang ◽  
Zhenlong Wang
Keyword(s):  
Crack Propagation ◽  
Industrial Application ◽  
Ceramic Materials ◽  
Advanced Technology ◽  
Analytical Models ◽  
Propagation Mechanism ◽  
Unstable Crack ◽  
Fracture Simulation ◽  
Initial Stage ◽  
Controlled Fracture

Microwave cutting glass and ceramics based on thermal controlled fracture method has gained much attention recently for its advantages in lower energy-consumption and higher efficiency than conventional processing method. However, the irregular crack-propagation is problematic in this procedure, which hinders the industrial application of this advanced technology. In this study, the irregular crack-propagation is summarized as the unstable propagation in the initial stage, the deviated propagation in the middle stage, and the non-penetrating propagation in the end segment based on experimental work. Method for predicting the unstable propagation in the initial stage has been developed by combining analytical models with thermal-fracture simulation. Experimental results show good agreement with the prediction results, and the relative deviation between them can be <5% in cutting of some ceramics. The mechanism of deviated propagation and the non-penetrating propagation have been revealed by simulation and theoretical analysis. Since this study provides effective methods to predict unstable crack-propagation in the initial stage and understand the irregular propagation mechanism in the whole crack-propagation stage in microwave cutting ceramics, it is of great significance to the industrial application of thermal controlled fracture method for cutting ceramic materials using microwave.

Classifying the Past: Discriminant Analysis and its Application to Medieval Farming Systems

1996 ◽  
Vol 8 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Ken Bartley
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Processing Time ◽  
Farming Systems ◽  
Frame Of Reference ◽  
Analytical Models ◽  
Successful Implementation ◽  
Medieval Period ◽  
The Past ◽  
Livestock Management

This paper discusses the need for nationally based analytical models of the medieval period. The use of cluster analysis as a method for classifying demesne farms, by the crops they grew and their livestock management, is explained. Successful implementation of cluster analysis requires both the existence of a large base sample, to permit isolation of specific groupings within the data, and access to considerable processing time. The paper concludes by demonstrating how discriminant analysis can provide an efficient and systematic way of classifying even a single manor within a national frame of reference.

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