PARAMETRIC IDENTIFICATION OF THE DIFFERENTIAL MODEL OF HEAT EXCHANGE IN A GASIFIER

На основе одномерной дифференциальной модели теплообмена в газификаторе закрытого типа сформулирована задача параметрической идентификации модели на основе измерений на штатном оборудовании промышленной газификационной установки. Модель включает в себя дополнительное интегральное условие и самосогласованно определяемую подвижную границу, отделяющую зону обледенения трубки испарителя. С применением метода сглаживания особенности разработан алгоритм итерационного решения уравнений модели, использующий метод сквозного счета для решения уравнения переноса на одной итерации. Для параметрической идентификации модели использована смешанная стратегия. Часть идентифицируемых параметров (теплоемкость испарителя, мощность нагревателя, массовая производительность насоса, коэффициент теплоотдачи в окружающую среду) определялась на основе специально организованных измерений: нагрева испарителя без прокачки сверхкритического флюида, газификации в условиях теплоизолированности корпуса испарителя, газификации в стационарном режиме работы. Остальные параметры (коэффициенты теплоотдачи в теплоноситель и сверхкритический флюид) идентифицировались в пассивных измерениях с различными производительностями насоса. Отмечено, что ввиду плохой обусловленности задачи и ограниченности вариаций коэффициентов применение регрессионных методов в данной модели неэффективно. На основе метода стрельбы разработан способ идентификации, заключающийся в определении параметров по измерениям с предельными производительностями с построением функциональной связи между идентифицируемыми параметрами, с последующей верификацией на промежуточных измерениях. Метод апробирован на примере штатной газификационной установки СГУ-7КМ-У We formulated the problem of parametric identification of the model based on measurements on the standard equipment of an industrial gasification plant on the basis of a one-dimensional differential model of heat transfer in a closed-type gasifier. The model includes an additional integral condition and a self-consistently defined movable boundary separating the icing zone of the evaporator tube. Using the method of smoothing the singularity, we developed an algorithm for iterative solution of the model equations, using the end-to-end counting method to solve the transfer equation in one iteration. We used a mixed strategy for parametric identification of the model. We determined some of the identified parameters (evaporator heat capacity, heater power, mass pump capacity, heat transfer coefficient to the environment) on the basis of specially organized measurements: heating of the evaporator without pumping supercritical fluid, gasification under conditions of thermal insulation of the evaporator body, gasification in stationary operation. We identified the remaining parameters (heat transfer coefficients to the coolant and supercritical fluid) in passive measurements with different pump capacities. We noted that due to the poor conditionality of the problem and the limited variation of coefficients, the use of regression methods in this model is ineffective. Based on the ballistic method, we developed an identification method, which consists in determining parameters by measurements with marginal performance with the construction of a functional relationship between the identified parameters, followed by verification on intermediate measurements. We tested the method on the example of a standard gasification plant SGU-7KM-U

Multispectral Image Enhancement Based on the Dark Channel Prior and Bilateral Fractional Differential Model

Compared with single-band remote sensing images, multispectral images can obtain information on the same target in different bands. By combining the characteristics of each band, we can obtain clearer enhanced images; therefore, we propose a multispectral image enhancement method based on the improved dark channel prior (IDCP) and bilateral fractional differential (BFD) model to make full use of the multiband information. First, the original multispectral image is inverted to meet the prior conditions of dark channel theory. Second, according to the characteristics of multiple bands, the dark channel algorithm is improved. The RGB channels are extended to multiple channels, and the spatial domain fractional differential mask is used to optimize the transmittance estimation to make it more consistent with the dark channel hypothesis. Then, we propose a bilateral fractional differentiation algorithm that enhances the edge details of an image through the fractional differential in the spatial domain and intensity domain. Finally, we implement the inversion operation to obtain the final enhanced image. We apply the proposed IDCP_BFD method to a multispectral dataset and conduct sufficient experiments. The experimental results show the superiority of the proposed method over relative comparison methods.

A Neuro-Evolution Heuristic Using Active-Set Techniques to Solve a Novel Nonlinear Singular Prediction Differential Model

In this study, a novel design of a second kind of nonlinear Lane–Emden prediction differential singular model (NLE-PDSM) is presented. The numerical solutions of this model were investigated via a neuro-evolution computing intelligent solver using artificial neural networks (ANNs) optimized by global and local search genetic algorithms (GAs) and the active-set method (ASM), i.e., ANN-GAASM. The novel NLE-PDSM was derived from the standard LE and the PDSM along with the details of singular points, prediction terms and shape factors. The modeling strength of ANN was implemented to create a merit function based on the second kind of NLE-PDSM using the mean squared error, and optimization was performed through the GAASM. The corroboration, validation and excellence of the ANN-GAASM for three distinct problems were established through relative studies from exact solutions on the basis of stability, convergence and robustness. Furthermore, explanations through statistical investigations confirmed the worth of the proposed scheme.

Влияние периодической макрошероховатости на развитие турбулентной свободной конвекции у внезапно нагреваемой вертикальной пластины

The results of numerical simulation of unsteady free convection developing near a suddenly heated plate, on which protrusions in the form of adiabatic cylinders of double height with respect to the diameter are arranged in a checkerboard pattern, are presented. The calculations were performed according to the Reynolds equations using a differential model of turbulent stresses. The range of variation of the Grashof number (plotted according to the thickness of the free convective flow), in which a significant intensification of heat transfer can be achieved, has been determined. It is shown that the best conditions for intensification are created if the longitudinal pitch in the array of protrusions is approximately twenty times the diameter of the latter.

Adaptation and Calibration of the Faulting Model for Thin Concrete Pavements

Joint faulting is a pavement distress that affects the comfort level of jointed plain concrete pavements. The appearance of joint faulting usually occurs in areas of high traffic of trucks at high speed. Variables such as level of rainfall and the erodibility of the subbase increases the magnitude of this phenomenon. To predict joint faulting in Thin Concrete Pavements, the design software OptiPave2, launched in 2012, used the same model developed for the Mechanistic Empirical Pavement Design Guide (MEPDG), which uses an energy differential model. After 6 years of the release of the software and after 10 years since the construction of some thin concrete pavement projects, there are pavements with clear signs of joint faulting and others without. For this reason, the OptiPave2 model was reviewed and compared with field data, concluding that the faulting model needed to be adjusted This new model was calibrated with the data from existing concrete pavement projects.

Asymptotic limits for a nonlinear integro-differential equation modelling leukocytes’ rolling on arterial walls

We consider a nonlinear integro-differential model describing z, the position of the cell center on the real line presented in Grec et al (2018 J. Theor. Biol. 452 35–46). We introduce a new ɛ-scaling and we prove rigorously the asymptotics when ɛ goes to zero. We show that this scaling characterizes the long-time behavior of the solutions of our problem in the cinematic regime (i.e. the velocity z ˙ tends to a limit). The convergence results are first given when ψ, the elastic energy associated to linkages, is convex and regular (the second order derivative of ψ is bounded). In the absence of blood flow, when ψ, is quadratic, we compute the final position z ∞ to which we prove that z tends. We then build a rigorous mathematical framework for ψ being convex but only Lipschitz. We extend convergence results with respect to ɛ to the case when ψ′ admits a finite number of jumps. In the last part, we show that in the constant force case [see model 3 in Grec et al (2018 J. Theor. Biol. 452 35–46), i.e. ψ is the absolute value)] we solve explicitly the problem and recover the above asymptotic results.

Differential model of friction based on bristle model and phase-transition theory

For high-precision position and angle control in robots, it is essential to compensate for the hysteretic behaviour caused by friction when the motion direction is reversed. An accurate friction model which is suitable for control system analysis and implementation is highly desirable. A differential model is proposed in the current paper for the modelling of hysteresis effects caused by friction phenomena. The model is constructed by employing a phenomenological phase-transition theory to mimic the friction mechanism. The bristle friction mechanism is adapted. The switching between static and dynamic friction is regarded as a reversible phase-transition phenomenon, which could be characterized by the local minima of a non-convex potential energy function. The Stribeck effect and the hysteretic relation between friction and velocity are modelled by a nonlinear ordinary differential equation. The comparison of the numerical simulation results and existing experimental friction data are presented. It is illustrated that the friction hysteresis loops are well captured, the capability of the proposed model is verified.

Three-dimensional integro-differential model of unstationary hydrodynamic process in a liquid-metal pool of underwater arc welding

Wet underwater arc welding is now widely used. At the same time, obtaining high-quality welds with this welding method is an urgent scientific and technical problem due to their saturation with hydrogen and oxygen and the formation of pores. One of the promising directions for solving this issue is the use of an external electromagnetic effect on the liquid metal in the weld pool in order to control the movements of the molten metal flows to improve the degassing processes of welded joints. It is possible to estimate the parameters and efficiency of external electromagnetic influence by means of mathematical modeling of related electromagnetic, hydrodynamic and thermal processes occurring in the welding installation. The article proposes a three-dimensional integro-differential model of a non-stationary hydrodynamic process occurring in the liquid metal of a weld pool in an underwater arc welding system with an external electromagnetic effect. For the equations of hydrodynamics boundary value problems are formed, which, using potential theory, are reduced to a system of integro-differential equations for the vorticity function in the volume of a liquid conductor and a simple vector layer on its surface. For a numerical solution, the resulting system of integro-differential equations is approximated by an algebraic system according to the Krylov-Bogolyubov method. This system of equations makes it possible to determine the velocity field in the liquid metal of the weld pool for any welding modes.