ACCELERATING THE COMMERCIALIZATION OF COMPOSITE MATERIALS AND STRUCTURES BASED ON SYNERGETICAL APPROACH Zaynetdinov R.I. 1,* Gadolina I.V.2 1 Independent researcher, Moscow, Russia; *zri7755@gmail.com; 2 MERI RAS, Moscow, Russia. Annotation: The theoretical model is developed and the practical method for shortening the commercialization (introduction) time for composite materials and structures is offered. The method is based on synergetical approach, analysis of bifurcation points, as well as managing the flows of materials, energy and information at the input of the being updated system. Key words: accelerating the commercialization, introduction, composite material, composite structure, innovation, bifurcation point, synergetics, informational entropy, lean innovation. Research and development of composite materials and structures are innovative areas of scientific and technical activities, moving towards successful evolution [1 - 3]. In this way, innovations can be introduced in a scenario of gradual replacement of the dominant (basic) technology with one or more innovative ones. In this case, there may be significant delays in the implementation process due to the strong resistance of the replaced technology. Fig. 1 shows as an example, a real trajectory of innovative development, which is associated with the historical fact [4] of a significant delay T of technological substitution of sailing ships with steamships on Transatlantic lines in the period from 1797 to 1964. This is indicative, but not the only example of a long delay in innovation. In this regard, it is important to analyze the possibilities and ways to accelerate the process of introduction of innovative technologies, materials and structures. Market share Time T, year Fig.1. Example of implementation delay T due to strong resistance in the process of replacement of sailing ships technology (line 1) with steamships (line 2). Specific results of innovative activity in modern Russia do not always meet expectations due to underestimation of the importance of scientific management of innovation and investment processes. New opportunities are opened by approaches based on synergetics, identification and analysis of bifurcation points and attractors of technological development. Technological systems in the course of their updating develop as open dissipative steadily nonequilibrium systems capable of self-organization. The availability of energy, information and material flows (which are the flows of investment, scientific and patent information, personnel, equipment, etc.) from external sources to the system and their dissipation are prerequisites for the activity of the updated system. As a critical element of the updated system, the local zone of the increased gradient of the defining parameter X, which limits the mode of existence ("mode of being") for the entire updated system, is considered. To analyze the behavior of the critical element, a model of a bistable element with two stable states – old and new, in each of which it can state long enough, is used. External influences can cause the critical element to switch from one state to another. To cause this transition, the intensity of the impact must exceed some threshold level of Xth. Depending on the ratio of probabilities P0 and P1 of finding the critical element in the old or new states, respectively, three characteristic modes of existence of the updated system are considered: old (P0 > P1), transitional (P0 = P1) and new (P0 < P1). The most important state function of the system is entropy. In open systems, the entropy change can be divided into the sum of two components: the entropy flow, depending on the exchange processes with the environment, and the production of entropy, due to irreversible processes within the system [5]. The certain stages of temporal evolution of the system can occur at a general downturn of entropy. According to the traditional interpretation of entropy as a measure of disorder, this means that during evolution disorder decreases due to the outflow of entropy, self-organization occurs, the system evolves to a more complex structure. In this case, new types of dissipative structures may arise, hierarchy within the system and differentiation of subsystems may deepen, structure and complexity may change. In a stable nonequilibrium state, the positive production of entropy within the system is compensated by a negative flow of entropy, i.e., the influx of information from outside the system or from other hierarchical levels within the system itself [6]. To analyze the evolution of the being updated system, the dynamics of information entropy is studied, which is a measure of the uncertainty of the existence of the system, and is equal to the amount of information on Shannon, needed to remove this uncertainty [7]: . (1) The analytical dependence for the description of the information entropy flow dynamics H (t) in time t is obtained in the form [8]: , (2) where  is the regime parameter for the being updated system;  are the transition intensities of the critical element of the being updated system, respectively, from the old state to the new and vice versa; . Graphs of the information entropy flow H(t) and its velocity dH/dt in the critical element of the being updated system in the implementation of the sequence of innovations are shown in Fig. 2. a) H(t) b) dH/dt Fig.2. Dynamics of the informational entropy flow changes: H(t) (a) and the velocity dH/dt (b) in the case of system innovation (<1; * > 1). Analysis of the information entropy flow and the rate of its change as the response of the being updated system to a change in the conditions of existence, shows that at the initial time interval (t = 0...1.4) the critical element of the being updated system operates in the old mode. The informational entropy flow during the transition process is stabilized at a level corresponding to this regime without passing the bifurcation point. At a conditional time t = 1.4, the system is affected, leading to the transition from the old (<1) to the new (*>1) mode of existence, i.e. to its innovation. Analysis of obtained dependences showed that the being updated system reacts to a strong impact leading to a new mode of existence, by a sharp increase in the informational entropy flow from the achieved under the previous conditions of the stationary level of HST to a maximum of H*max = 1 at the point t*b of bifurcation. In this case, the rate dH*/dt* of the entropy flow increment drops sharply to zero, becomes negative, passes the minimum and tends to zero when the being updated system enters a new stationary state. After passing the bifurcation point t*b, the informational entropy flow decreases and stabilizes at a new stationary level H*ST, corresponding to the scale of innovation. Additional analysis showed that at the bifurcation point corresponding to the time moment t*b, the variance Dx of the defining parameter X of the updated system also reaches a maximum. This fact allows using Dx as a diagnostic parameter of the updated system [6,8]. Point t*b, which is the stochastic analogue of bifurcation points are associated with the process of self-organization, i.e. the destruction of the old dissipative structure that has exhausted its capabilities, and the emergence of a new structure corresponding to the changed conditions of existence as a result of innovation, the transition of the updated system to a new level of development. The open system adapts to new conditions by improving the structure and returns to a steady state due to the outflow of entropy and the flow of information from outside or from other hierarchical levels of the updated system. The obtained [6,8] mathematical expressions allow to predict the moment of occurrence of t*b bifurcation points and the critical state of the updated system, when it is expedient to take measures to facilitate the rapid adaptation of the updated system to new conditions and accelerate the process of introduction of innovative technologies. The dependence of the mode of existence of the being updated system and the time of passage of the point of bifurcation on the distribution function of a random process of external influences on the being updated system, its input flows, for example, investment and information flows. Figure 3 shows a graph of the dependence of the parameter  for the mode of existence of the being updated system on the change of parameters (mean X and standard deviation Sx) of the normal (Gaussian) random process at the input of the being updated system. With the purposeful change of parameters of input flows (material, energy and information), which in the case of innovation are the flows of investments, scientific and patent information, personnel, equipment, etc. from external sources to the being updated system, - it is possible to influence the time of overcoming by the critical element of the innovation system of the point t*b of bifurcation (or cascade of bifurcations). The ability to assess the time of passage by the innovation system through this state, characterized by the highest risks, allows you to take measures to facilitate the rapid passage of the being updated system through the critical point of bifurcation and the successful adaptation of the Fig. 3. Change of the regime parameter  depending on the parameters X and Sx of random process at the input of the being updated system. system to the new state. During this period of time, it is advisable to create the most favorable conditions for the successful passage of the being updated system by the bifurcation point in the desired direction by rational management of the flows included in the being updated system, as well as to take all possible measures to direct the being updated system to the desired favorable path of development. Potential opportunities that arise at the time of bifurcation attract the development of the being updated system; it self-organizes, improves its structure, and moves to a new level of development. This implies the idea that technological development is determined not so much by the initial conditions and the "heavy legacy of the past" as by the future possible states, i.e. attractors of technological development, to which the being updated technological system, aspires after bifurcation, and these processes are irreversible [9]. The attractor is understood as a relatively stable state of the being updated system, attracting a lot of trajectories of technological development, potentially possible after the passage of the bifurcation point by the system. Time is an irreplaceable resource, therefore, the proposed method designed to reduce the time of innovation implementation, in our opinion, should be considered as one of the important and useful tools of the concept of "Lean (Frugal) Innovation" [10, 11]. Summary 1. Specific results of innovative activity in modern Russia do not always meet expectations due to underestimation of the importance of scientific management of the innovation processes. 2. The theoretical model is developed and the practical method for shortening the introduction time for composite materials and structures is offered. The method is based on synergetic approach, analysis of bifurcation points, as well as managing the flows (random processes) at the input of the being updated system. 3. When changing the parameters of input flows (materials, energy and information), which in the case of innovations, are the flows of investment, scientific and patent information, personnel, motivation, equipment, etc. from external (or internal) sources to the being updated system, it is possible to influence the time t*b of overcoming by the innovation system the bifurcation point (or cascade of bifurcations). 4. Practical approbation of the developed method for composite materials and structures recommended. Proposals for cooperation please send to E-mail: zri7755@gmail.com to professor Zainetdinov R.I. 1. Dumanskii A.M., Komarov V.A., Alimov M.A., Radchenko A.A. On the effect of fiber rotation upon deformation of carbon-fiber angle-ply laminates // Polymer Science. Series D – 2017. – Vol.10. Issue 2. P.197-199. 2. Рогов Д.А., Русин М.Ю., Саввин А.И., Думанский А.М., Русланцев А.Н. 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