Modeling the systematic behavior at the micro and nano length scales

The assessment of the systematic behavior based on frequentist statistics was analyzed in the context of micro/nano metrology. The proposed method is in agreement with the well-known GUM recommendations. The investigation assessed three different case studies with definition of model equations and establishment of the traceability. The systematic behavior was modeled in Sq roughness parameters and step height measurements obtained from different types of optical microscopes, and in comparison with a calibrated contact instrument. The sequence of case studies demonstrated the applicability of the method to micrographs when their elements are averaged. Moreover, a number of influence factors, which are typical causes of inaccuracy at the micro and nano length scales, were analyzed in relation to the correction of the systematic behavior, viz. the amount of repeated measurements, the time sequence of the acquired micrographs and the instrument-operator chain. The possibility of applying the method individually to the elements of the micrographs was instead proven not convenient and too onerous for the industry. Eventually, the method was also examined against the framework of the metrological characteristics defined in ISO 25178-600 with hints on possible future developments.

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

Centrifugal spinning of viscoelastic nanofibres

The centrifugal spinning method is a recently invented technique to extrude polymer melts/solutions into ultra-fine nanofibres. Here, we present a superior integrated string-based mathematical model, to quantify the nanofibre fabrication performance in the centrifugal spinning process. Our model enables us to analyse the critical flow parameters covering an extensive range, by incorporating the angular momentum equations, the Giesekus viscoelastic constitutive model, the air-to-fibre drag effects and the energy equation into the string model equations. Using the model, we can analyse the dynamic behaviour of polymer melt/solution jets through the dimensionless flow parameters, namely, the Rossby ( $Rb$ ), Reynolds ( $Re$ ), Weissenberg ( $Wi$ ), Weber ( $We$ ), Froude ( $Fr$ ), air Péclet ( $Pe^*$ ) and air Reynolds ( $Re^*$ ) numbers as well as the viscosity ratio ( $\delta _s$ ), corresponding to rotational, inertial, viscous, viscoelastic, surface tension, gravitational, air thermal diffusivity, aerodynamic and viscosity ratio effects. We find that the nonlinear rheology remarkably affects the fibre trajectory, radius and normal stresses. Increasing $Wi$ leads to a thicker fibre, whereas increasing $\delta _s$ shows an opposite trend. In addition, by increasing $Wi$ , the fibre curvature is enhanced, causing the fibre to spiral closer to the rotation centre.

Design and Structural Simulations of a Custom Li-Po Accumulator for Low Range, Lightweight, Single-Seater, Open Cockpit, and Open-Wheeled Racecar

Electric, hybrid, and fuel cell vehicles are the future of the automobile industry, and power source design is one of the most crucial steps in designing these vehicles. This paper aims to design and structurally simulate a custom accumulator—which powers an electric vehicle, for a lightweight, single-seater formula-style racecar. The work is dependent on the model-based design and CAD model approach. Mathematical modeling on SCILAB is used to model equations to get the characteristics of the accumulator, such as the energy, capacity, current, voltage, state of charge, and discharge rates. The output of this model gives the configuration of the battery pack as several cells in series and parallel to adequately power the tractive system. An accumulator container is designed to safeguard the cells from external impacts and vibrational loads, which otherwise can lead to safety hazards. Following this, the Finite Element Analysis (FEA) performed on the accumulator resulted in maximum peak deformation of 0.56 mm, ensuring the safety check against various external loads. Further, the finer stability of the battery pack was virtually validated after performing the vibrational analysis, resulting in a deformation of 3.5493 mm at a 1760.8 Hz frequency.

A Sensor Data Processing Algorithm for Wind Turbine Hydraulic Pitch System Diagnosis

Modern wind turbines depend on their blade pitch systems for start-ups, shutdowns, and power control. Pitch system failures have, therefore, a considerable impact on their operation and integrity. Hydraulic pitch systems are very common, due to their flexibility, maintainability, and cost; hence, the relevance of diagnostic algorithms specifically targeted at them. We propose one such algorithm based on sensor data available to the vast majority of turbine controllers, which we process to fit a model of the hydraulic pitch system to obtain significant indicators of the presence of the critical failure modes. This algorithm differs from state-of-the-art, model-based algorithms in that it does not numerically time-integrate the model equations in parallel with the physical turbine, which is demanding in terms of in situ computation (or, alternatively, data transmission) and is highly susceptible to drift. Our algorithm requires only a modest amount of local sensor data processing, which can be asynchronous and intermittent, to produce negligible quantities of data to be transmitted for remote storage and analysis. In order to validate our algorithm, we use synthetic data generated with state-of-the-art aeroelastic and hydraulic simulation software. The results suggest that a diagnosis of the critical wind turbine hydraulic pitch system failure modes based on our algorithm is viable.

Process simulation of modelled reverse osmosis for desalination of seawater

Model equations for prediction of process parameters of reverse osmosis for desalination of seawater were developed via mathematical derivation from basic equations for reverse osmosis process. A model equation relating the interfacial solute concentration () with the process pressure difference () was developed. Taking the of a reverse osmosis as the basic independent variable, further model equations relating other process parameters such as the solute concentration polarity , water flux , osmotic pressure , water output rate (q), power density (Pd) and specific energy consumption (SEC) were developed. Simulation of a hypothetical reverse osmosis data using Microsoft Excel Worksheet and a Microsoft Windows 10 on a 64-bit operating system was carried out. Simulation results showed that the optimum fluid bulk concentration was = 0.0004 mole/cm3. The optimum rate of increase in the solute rejection factor per unit rise in ΔP was 0.45%. The optimum solute rejection factor was 97.6%. The optimum water output rate, specific energy consumption and power density were 103.2 L/h, 3.65 kWh/m3 and 6.09 W/m2, respectively.

Studies on impurity seeding and transport in edge and SOL of tokamak plasma

We present numerical simulation studies on impurity seeding using Nitrogen, Neon, and Argon gases. These impurity gases are ionized by the electron impact ionization. These ions can be at multiply ionized states, recombine again with the plasma electrons, and radiate energy. The radiation losses are estimated using a non-coronal equilibrium model. A set of 2D model equations to describe their self-consistent evolution are derived using interchange plasma turbulence in the edge and SOL regions and solved using BOUT++. It is found that impurity ions (with single or double-positive charges) move in the inward direction with a velocity ∼ 0.02cs so that these fluxes are negative. These fluxes are analyzed for different strengths of an effective gravity that help to understand the impurity ion dynamics. Increased gravity shows an accumulation of certain charged species in the edge region. The radiation loss is seen to have a fluctuation in time with frequency 5-20 kHz that closely follows the behavior of the interchange plasma turbulence. The simulation results on the radiated power and its frequency spectrum compare favourably with observations on the Aditya-U tokamak. The negative fluxes of the impurity ions, their dynamics in the edge region, and the fluctuating nature of the radiation loss are the most important results of this work.

Analytical Solution of a New SEIR Model Based on Latent Period-Infectious Period Chronological Order

The Susceptible-Infectious-Recovered (SIR) and SIR derived epidemic models have been commonly used to analyze the spread of infectious diseases. The underlying assumption in these models, such as Susceptible-Exposed-Infectious-Recovered (SEIR) model, is that the change in variables E, I or R at time t is dependent on a fraction of E and I at time t. This means that after exposed on a day, this individual may become contagious or even recover on the same day. However, the real situation is different: an exposed individual will become infectious after a latent period (l) and then recover after an infectious period (i). In this study, we proposed a new SEIR model based on the latent period-infectious period chronological order (Liu X., Results Phys. 2021; 20:103712). An analytical solution to equations of this new SEIR model was derived. From this new SEIR model, we obtained a propagated curve of infectious cases under conditions l>i. Similar propagated epidemic curves were reported in literature. However, the conventional SEIR model failed to simulate the propagated epidemic curves under the same conditions. For l<i, the new SEIR models generated bell-shaped curves for infectious cases, and the curve is near symmetrical to the vertical line passing the curve peak. This characteristic can be found in many epidemic curves of daily COVID-19 cases reported from different countries. However, the curve generated from the conventional SEIR model is a right-skewed bell-shaped curve. An example for applying the analytical solution of the new SEIR model equations to simulate the reported daily COVID-19 cases was also given in this paper.

Study on Parameters of Two Widely Used Cohesive Soils Erosion Models

The erosion rate of cohesive soils was typically modeled with the excess shear stress model and the Wilson model. Several kinds of research have been conducted to determine the erodibility parameters of the two models, but few attempts have been made hitherto to investigate the general trends and range of the erodibility parameter values obtained by the commonly used Erosion Function apparatus. This paper collected a database of 177 erosion function apparatus tests to indicate the variability of all erodibility parameters; the range of erodibility parameters is determined by data statistics and parameter theoretical value derivation. The critical shear stress (τc) and erodibility coefficient (Z0) in the over-shear stress model have a positive proportional relationship when the data samples are sufficient. However, there is no such relationship between the erodibility coefficient (b0) and erodibility coefficient (b1) in the Wilson model. It is necessary to express the soil erosion resistance by considering all erosion parameters in the erosion model. Equations relating erodibility parameters to water content, plasticity index, and median particle size were developed by regression analysis.