Journal of Bionic Engineering

A “Living” Machine

N.R. Bogatyrev

J4. 2004, 1 (2): 79-87. DOI:

Abstract ( 1826 )

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Biomimetics (or bionics) is the engineering discipline that constructs artificial systems using biological principles. The ideal final result in biomimetics is to create a living machine. But what are the desirable and non-desirable properties of biomimetic product? Where can natural prototypes be found? How can technical solutions be transferred from nature to technology? Can we use living nature like LEGO bricks for construction our machines? How can biology help us? What is a living machine? In biomimetic practice only some “part” (organ, part of organ, tissue) of the observed whole organism is utilized. A possible template for future super-organism extension for biomimetic methods might be drawn from experiments in holistic ecological agriculture (ecological design, permaculture, ecological engineering, etc.). The necessary translation of these rules to practical action can be achieved with the Russian Theory of Inventive Problem Solving (TRIZ), specifically adjusted to biology. Thus, permaculture, reinforced by a TRIZ conceptual framework, might provide the basis for Super-Organismic Bionics, which is hypothesized as necessary for effective ecological engineering. This hypothesis is supported by a case studythe design of a sustainable artificial nature reserve for wild pollinators as a living machine.

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Analysis of Maneuvering Flight of an Insect

Sunada S. ¹, Wang H. ² , Zeng Lijiang ², Kawachi K. ³

J4. 2004, 1 (2): 88-101. DOI:

Abstract ( 1351 )

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Wing motion of a dragonfly in the maneuvering flight, which was measured by Wang et al.^[1] was investigated. Equations of motion for a maneuvering flight of an insect were derived. These equations were applied for analyzing the maneuvering flight. Inertial forces and moments acting on a body and wings were estimated by using these equations and the measured motions of the body and the wings. The results indicated the following characteristics of this flight: (1)The phase difference in flapping motion between the two fore wings and two hind wings, and the phase difference between the flapping motion and the feathering motion of the four wings are equal to those in a steady forward flight with the maximum efficiency. (2)The camber change and the feathering motion were mainly controlled by muscles at the wing bases.

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The Hydrodynamic Analysis of C-start in Crucian Carp

Jun Jing, Xiezhen Yin, Xiyun Lu

J4. 2004, 1 (2): 102-107. DOI:

Abstract ( 1350 )

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The kinematics of turning maneuvers of startled Crucian Carp (Carassius auratus ) are presented. All escape responses observed are C-type fast-starts. The position of the center of mass and the moment of inertia of the fish are calculated. The results show that the position of the center of mass is always at 35% of the length of the fish from the head and the position of the center of mass and moment of inertia can be considered unchanged during C-start of Crucian Carp. Hydrodynamic analysis of the C-start is given based on the kinematics data from our experiments. The C-start consists of three stages. In stage 1, the tail fin of fish rapidly flaps in one direction, and a large moment acts on the fish's body, which rotates around the center of mass with an angular acceleration. I n stage 2, the tail fin flaps more slowly in the opposite direction at slower speed, the fish's body rotates around the center of mass with angular deceleration and the center of mass of the fish moves along an arc. In stage 3, the moment approximately equals zero, the fish's body stops rotating and the center of mass the moves along a straight line.

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Computation of Unsteady Flow past a Biomimetic Fin

Hao Liu ¹, Naomi Kato ²

J4. 2004, 1 (2): 108-120. DOI:

Abstract ( 1334 )

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The unsteady hydrodynamics of a biomimetic fin attached to a cylindrical body ha s been studied numerically using a computational fluid dynamic (CFD) simulator based on an in-house solver of the Navier-Stokes equations, combined with a recently developed multi-block, overset grid method. The fin-body CFD model is based on a mechanical pectoral fin device, which consists of a cylindrical body and an asymmetric fin and can mimic flapping, rowing and feathering motions of the pectoral fins in fishes. First the multi-block, overset grid method incorporated into the NS solver was verified through an extensive study of unsteady flows past a single fin undergoing rowing and feathering motion. Then unsteady flows past the biomimetic fin-body model undergoing the same motions were computed and compared with the measurements of forces of the mechanical pectoral fin, which shows good agreement in both time-varying and time-averaged hydrodynamic forces. The relationship between force generation and vortex dynamics points to the importance of the match in fin kinematics between power and recovery strokes and implies that an optimal selection of parameters of phase lags between and amplitudes of rowing and feathering motions can improve the performance of labriform propulsion in terms of either maximum force generation or minimum mechanical power.

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Means, Advantages and Limits of Merging Biology with Technology

O. A. Bogatyreva, A.-K. Pahl., N.R. Bogatyrev, J.F.V.Vincent

J4. 2004, 1 (2): 121-132. DOI:

Abstract ( 1320 )

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The natural world spent billions of years in solution-finding during evolution, which could benefit Technology. How do we put that in a nutshell? Biological systems are more complex than the most complex current technology. An y given function and effect are simultaneously coordinated and linked with others at many levels of biological organisationfrom cell organelle to organism, to population and ecosystem. Technology does not have tools to deal with the complexity and “goal-intendedness” of living systems. But limits for interaction exist on both sides-Biological science itself is also too empirical and not mature enough to provide a solid base for correlating living with technical systems. Moving towards a synthesis, where engineers can utilize the vast amount of available biological data, we suggest using a tool called "Theory of Inventive Problem Solving" (TRIZ) and clarifying some important methodological issue s, which have not previously been recognised in bionic engineering: 1) Requirement for more appropriate definitions of "system", "effect", "function", "law" and "rule". 2) Requirement for understanding or even measuring the degree of contradiction or analogy between functions in biological and artificial and/or nonliving engineering systemthere is no simple direct correlation between what engineers find useful and what biology does.

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Study of a Bionic Pattern Classifier Based on Olfactory Neural System

Xu Li ¹, Guang Li ¹, Le Wang ¹, Walter J.Freeman ²

J4. 2004, 1 (2): 133-140. DOI:

Abstract ( 1268 )

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Simulating biological olfactory neural system, KⅢ network, which is a high-dimensional chaotic neural network, is designed in this paper. Different from conventional artificial neural network, the KⅢ network works in its chaotic trajectory. It can simulate not only the output EEG waveform observed in electrophysiological experiments, but also the biological intelligence for pattern classification. The simulation analysis and application to the recognition of handwriting numerals are presented here. The classification performance of the KⅢ network at different noise levels was also investigated.

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