Unsteady Process Research Articles

Interfacial bonding mechanism and length evaluation method of the longitudinal welds in the unsteady deformation process of porthole die extrusion of aluminum alloy profiles

In this work, a porthole die extrusion experiment was carried out on an aluminum alloy profile used for air-conditioning refrigerator ice box. Microstructural characterization and mechanical property tests were performed at different positions of a longitudinal weld in the profile head. The results indicated that, from the unsteady to steady extrusion stage, the number, sizes and depths of the voids gradually decrease. The oxides are gradually broken into flakes and eventually disappear. The grain boundaries gradually cross the welding interfaces to form new grains, and the welding quality is gradually improved. The ultimate tensile strength (UTS) of the longitudinal welds shows an upward trend, the elongation (EL) first rises and then tends to be stable. Before complete welding, the hardness at the welding interface is lower than those of the areas on both sides of the interface. Based on the results of testing and characterization, the interfacial bonding mechanism of the longitudinal welds in the unsteady zones was revealed. A method for predicting the length of the unsteady zones of profiles extruded by porthole die was proposed, by which the length of the unsteady zone of the aluminum alloy profile used for air-conditioning refrigerator ice box was successfully predicted.

Heat storage modeling for air ventilation usage considering freezing of paraffin through a sinusoidal duct

In this article, sinusoidal layers of PCM through air ventilation were employed. Current unsteady process with neglecting gravity impact is simulated by Finite volume method. Temperature of all zones is 303.15 K at t = 0 and PCM zones contain liquid RT28. Six cases were tested and three of them have various configurations for air gap arguments. Dispersing CuO nanoparticles (φ = 0.05) makes the required time for freezing to decrease about 5.55 %. With changing the shape of PCM zone to wavy duct, full solidification time decreases about 23.52 %. With insertion of air gaps, adding CuO nanoparticles (φ = 0.05) and considering sinusoidal duct, the needed time reduces about 44.44 %. The highest case in view of freezing time is first case. With increase of time, temperature of PCM reduces with heat releasing to air. With insertion of air gaps and sinusoidal wall, the outlet temperature decreases about 0.379 % at the end of discharging.

Understanding the influence of unsteady and convection terms in heat transfer model on the predicted heat flux in engines operated under different combustion modes

The aim of current research is to develop an enhanced heat transfer model to accurately predict the heat flux through the cylinder walls during the working process of internal combustion engines operated under different loads and combustion modes. Two enhanced models, i.e., the unsteady model and the steady convective contribution (SCC) model were respectively constructed based on the thermal wall function. The effects of the transient ambient gas temperature and pressure variations, as well as the chemical reaction source term, were included in the unsteady model. Then the contributions of the unsteady terms, such as the temporal derivative of gas temperature, the pressure work, and the chemical heat source in the energy equation were analyzed in detail. The results indicate that the mechanism of the unsteady heat transfer process is different in the engine operated under motored conditions and different combustion modes, including conventional diesel combustion (CDC), homogeneous charge compression ignition (HCCI), and reactivity controlled compression ignition (RCCI). Afterward, the influence of the gas velocity and the pressure difference perpendicular to the walls were included in the SCC model to consider their contributions to the heat fluxes near the chamber walls. It is found that the heat fluxes predicted by the SCC model are in better agreement with the experimental data, especially in the CDC mode under different swirl ratios and loads. The peak of the heat flux predicted by the SCC model shows superiority to that of the previous steady heat transfer models and the unsteady heat transfer model.

Prediction and Analysis of the Force and Shape Parameters in Variable Gauge Rolling

Variable gauge rolling is a new process to obtain a plate for which the thickness changes continuously by continuously and dynamically adjusting the roll gap upward and downward in the rolling process. This technology is an effective method for producing lightweight, low-cost, and economical plates. However, variable gauge rolling is an unsteady process, and the changes in the force and deformation parameters are complex. In this research, based on the minimum energy theory of the variational principle and considering the characteristics of the roll movement and workpiece deformation comprehensively, the internal plastic deformation, friction, shear and tension powers, and the minimum result of the total power functional in upward and downward rolling are obtained with the first integral and then with a variation of adopting the specific plastic power and strain rate vector inner product. The analytical results of the deformation and force parameters are also established using the variational method. Then the precision of this model is certified using the measured values in a medium plate hot rolling plant and the experimental data for Tailor Rolled Blank rolling. Good agreement is found. Additionally, the variation rule of bite angle, neutral angle, and location neutral points are shown, and the change mechanism of the friction parameter on the stress state effect coefficient is given in variable gauge rolling. This research proposes a new mathematical model for rolling process control that provides a scientific basis and technical support for obtaining an accurate section shape in variable gauge rolling production.

Cloud droplets scavenging of gaseous pollutant from the atmosphere: Nonlinear modelling and analyses

The principle of how hazardous pollutants are annulled by rain, dew or precipitations has been a subject of interest in addressing environmental challenges and climate change. This scavenging process when studied generates nonlinear dynamic models that require robust techniques for obtaining their solutions before use for predictions. Consequently, this work presents analytical solutions to such unsteady processes using PADE-Homotopy perturbation method (PADE-HPM) and Multi-step differential transform method (MSDTM). The obtained solutions are verified via a numerical finite difference method (FDM). These methods demonstrate adequate aptitude for predicting the scavenging processes. Furthermore, the study of the controlling parameters shows that reduction in the formation rate of the annulling agents causes a corresponding decrease in the density of the available raindrop for scavenging. Meanwhile, augmentation in formation rate rapidly neutralizes pollutants from the atmosphere. A synonymous impact is realized for growth rate parameter. In addition, it is established that as the transformation rates of hazardous gases reduce while scavenging processes are augmented, the threat posing pollutants would be completely annulled. It is envisaged that the present study will find usage in overcoming one of the dares facing the world at large on scavenging of hazardous pollutants.

A Transfer Learning‐Based Method for Facilitating the Prediction of Unsteady Crystal Growth

AbstractReal‐time prediction and dynamic control systems that can adapt to an unsteady environment are necessary for material fabrication processes, especially crystal growth. Recent studies have demonstrated the effectiveness of machine learning in predicting an unsteady crystal growth process, but its wider application is hindered by the large amount of training data required for sufficient accuracy. To address this problem, this study investigates the capability of transfer learning to predict geometric evolution in an unsteady silicon carbide (SiC) solution growth system based on a small amount of data. The performance of transferred models is discussed regarding the effect of the transfer learning method, training data amount, and time step length. The transfer learning strategy yields the same accuracy as that of training from scratch but requires only 20% of the training data. The accuracy is stably inherited through successive time steps, which demonstrates the effectiveness of transfer learning in reducing the required amount of training data for predicting evolution in an unsteady crystal growth process. Moreover, the transferred models trained with relatively more data (no more than 100%) further improve the accuracy inherited from the source model through multiple time steps, which broadens the application scope of transfer learning.

Applying the Random Forest Method to Improve Burner Efficiency

Fuel power plants are one of the main sources of pollutant emissions, so special attention should be paid to improving the efficiency of the fuel combustion process. The mathematical modeling of processes in the combustion chamber makes it possible to reliably predict and find the best dynamic characteristics of the operation of a power plant, in order to quantify the emission of harmful substances, as well as the environmental and technical and economic efficiency of various regime control actions and measures, and the use of new types of composite fuels. The main purpose of this article is to illustrate how machine learning methods can play an important role in modeling and predicting the performance and control of the combustion process. The paper proposes a mathematical model of an unsteady turbulent combustion process, presents a model of a combustion chamber with a combined burner, and performs a numerical study using the STAR-CCM+ multidisciplinary platform. The influence of various input indicators on the efficiency of burner devices, which is evaluated by several parameters at the output, is investigated. In this case, three possible states of the burners are assumed: optimal, satisfactory and unsatisfactory.

Expedition of solidification with dispersing nanoparticles utilizing numerical method

To show the efficacy of size of nanoparticles, numerical modeling for current article has been developed based on homogeneous approximation for nanomaterial. Energy equation with considering one term denoting the phase change process should be solved for illustration of discharging process. The properties of material should be changed according to formulation of homogeneous mixture. The efficacy of size has been added in formula of conductivity factor. Galerkin method for such unsteady process has been applied with incorporating implicit approach. With utilizing adaptive mesh the accuracy of method increases and good agreement has been reported according to validation test. With dispersing nanoparticles, the speed of process increases and changing the size of powder can affect the behavior of system. As diameter of nanoparticles changes about 10 nm from 30 nm, the required time reduces about 19.21%. Required time augments by 18.64% with changing the size of particles from 30 nm to 50 nm. Augmenting the nanoparticles fraction can improves the freezing rate by 66.88%.

Experimental investigation of monodisperse solids drying in a gas-fluidized bed

Fluidized bed drying is an unsteady process where particle and gas properties evolve in time. The bed hydrodynamics and its interplay with mass and heat transfer changes in time. In this study, experiments in a pseudo-2D fluidized bed setup are performed to obtain insight in this complex behavior. A coupled particle image velocimetry infrared thermography technique provides solids velocity and temperature fields in the bed. Significant hydrodynamic changes due to the evaporation of water from the porous γ-Al2O3 material for three superficial velocities were observed. The 1.25 umf case resulted in an fixed bed state, but after drying for 580 s a bed inversion took place. The 1.50 and 1.75 umf experiments showed an increase in bed expansion over time. Furthermore, clear asymmetrical solids volume fluxes were observed for the wet material that became more symmetrical over time when the material dried.

Discrete Boltzmann modeling of detonation: Based on the Shakhov model

A Discrete Boltzmann Model(DBM) based on the Shakhov model for detonation is proposed. Compared with the DBM based on the Bhatnagar–Gross–Krook (BGK) model, the current model has a flexible Prandtl numbers and consequently can be applied to a much wider range of detonation phenomena. Besides the Hydrodynamic Non-Equilibrium (HNE) behaviors usually investigated by the Navier–Stokes model, the most relevant Thermodynamic Non-Equilibrium (TNE) effects can be probed by the current model. The model is validated by some well-known benchmarks, and some steady and unsteady detonation processes are investigated. As for the von Neumann peak relative to the wave front, it is found that (i) (within the range of numerical experiments) the peak heights of pressure, density, and flow velocity increase exponentially with the Prandtl number, the maximum stress increases parabolically with the Prandtl number, and the maximum heat flux decreases exponentially with the Prandtl number and (ii) the peak heights of pressure, density, temperature and flow velocity, and the maximum stress within the peak are parabolically increase with the Mach number, the maximum heat flux decreases exponentially with the Mach number.

Numerical study of unsteady flow and cooling characteristics of turbine blade cutback trailing edges integrated with pin fins and film holes

Accurate prediction of the unsteady flow mixing process and its effects on cooling performance in the turbine blade trailing edge (TE) is essential to improving TE cooling designs. This paper used high accuracy transient Scale Adaptive Simulation (SAS) method to investigate the unsteady flow and cooling characteristics of two novel turbine blades cutback TEs under blowing ratios BRs=0.65 and 1.25. The two novel TEs have five rows of pin fins in the cooling slot and two rows of either cylindrical or fan-shaped film holes on the pressure side upstream of the cutback region. The results were compared against those of the baseline TE with only pin fins and the data obtained from Shear Stress Transport (SST) k-ω model.The results revealed that: 1) the coolant issued from upstream cylindrical or fan-shaped holes has significantly disturbed the Brown-Roshko vortices shedding off the lip of the top wall, but only largely reduced the magnitude of normal velocity fluctuation in the cutback region. The alternating vortices in the cutback region are stretched flat. The changes brought to the flow structures are more significant by the fan-shaped holes than the cylindrical holes; 2) Although increasing blowing ratio enhances flow unsteadiness in the cutback region of the three TEs, the differences in the magnitude of velocity fluctuations are much reduced among the three TEs; 3) The TE cutback with fan-shaped holes achieves a higher adiabatic wall cooling effectiveness ηaw on the cutback wall at BR=0.65, and also a lower reduction in ηaw at BR=1.25 than the TE cutback with cylindrical holes; 4) Transient SAS method demonstrates a better agreement of ηaw with the experimental data for the baseline TE on the cutback wall, and higher values of ηaw than the results of the SST k-ω model on the top wall.

Model predictive control of long Transfer-line cooling process based on Back-Propagation neural network

• A model predictive control (MPC) method based on back-propagation (BP) neural network as a surrogate inversion model was designed to improve the automation of the long transfer-line pre-cooling process. • A one-dimensional simulation model based on unsteady flow and heat transfer process was used to generate training datasets for BP neural networks, and reasonable cleaning rules are the key to obtain better training results. • Simulation and test results show that the MPC method can be applied to the automatic control of nonlinear large hysteresis dynamical systems such as the long transfer-line pre-cooling process. As the scale of large cryogenic systems continues to expand, the thermal inertia and nonlinear characteristics of the pre-cooling process of long-distance cryogenic transfer-line become obvious, and the traditional control methods are less effective in controlling such nonlinear large hysteresis time-varying systems. To improve the automation of the pre-cooling process, a Model Predictive Control (MPC) method based on Back-Propagation (BP) neural network as a surrogate inversion model was designed and deployed on a large helium cryogenic system of the Platform of Advanced Photon Source (PAPS). Simulation and test results show that the MPC method can be applied to the automatic control of nonlinear large hysteresis dynamical systems; the BP neural network as a surrogate model can invert the one-dimensional flow heat transfer model better. The actual test results on the PAPS cryogenic system show that the method can realize the automatic pre-cooling of long transfer-line, and the overall cooling effect is stable and efficient, with the maximum absolute temperature difference of no more than 3.2 K and the maximum relative temperature difference of no more than 2.1% from the ideal cooling line.

DDPG-based continuous thickness and tension coupling control for the unsteady cold rolling process

Cold rolling is an important part of the iron and steel industry, and the unsteady rolling process of cold rolling usually brings significant influences on the stability of product quality. In the unsteady rolling process, various disturbances and uncertainties such as variable lubrication state, variable equipment working conditions lead to difficulties in the establishment of state space model of thickness and tension, which has become a thorny problem in thickness and tension control. In this paper, we present a model-free controller based on Deep Deterministic Policy Gradient (DDPG), which can continuously control the thickness tension of the unsteady rolling process without the mathematical model. We first formulate the thickness and tension control problem to Markov Decision Process (MDP). We apply strategies such as dividing state space variables with the mechanism model, defining reward function and state normalization, the random disturbance and complex uncertainties of the unsteady cold rolling process are coped with by utilizing the DDPG controller. In addition, these strategies also ensure the learning performance and stability of DDPG controller under random disturbance. Simulations and experiments show that the proposed the DDPG controller does not require any prior knowledge of uncertain parameters and can operate without knowing unsteady rolling mathematical models, which has better accuracy, stability, and rapidity for thickness and tension in the unsteady rolling process than proportional integral (PI) controller. The artificial intelligence–based controller brings both product quality improvement and intelligence to cold rolling.

Analysis of the effect of unsteady reservoir flow and sand excavation on the channel conditions of the Yangtze River (Yibin-Chongqing)

This paper systematically describes the current research methods for analyzing unsteady flows in an open channel. In particular, it focuses on elaborating a discrete method to solve the one-dimensional Saint–Venant equations for unsteady flow in an open channel, compares the advantages and disadvantages of different discrete methods, and proposes a new implicit iterative mathematical model applicable to the calculation of the multiwavelength unsteady flow in the Yangtze River from Yibin to Chongqing. This paper also simulates three typical unsteady flow processes and analyzes the effect of sand excavation on the water level in the upper reaches of the Yangtze River from Yibin to Chongqing considering flood, normal-water, and low-water conditions. The spreading characteristics of the daily adjusted unsteady flow were obtained in the Shuifu-Chongqing river reach. Under the conditions of the daily minimum unsteady discharge flow rate, the designed water level of the reach from Yibin to Chongqing increases by 0.19 m compared to the natural water level. With the increase in concentrated sand excavation in the upper reaches of the Yangtze River, a large number of shingle beaches have disappeared, and the riverbed has been drastically lowered. Affected by the excessive and unordered sand excavation in the river channel, the water level of the upper reaches of the Yangtze River from Chongqing to Yibin has decreased by 0.5–2.0 m.

Rock dynamic fracture of a novel semi-circular-disk specimen

The relationship between velocity, acceleration, and dynamic fracture toughness during rapid crack propagation is difficult to effectively capture. In this study, a novel semi-circular holed disc bend is proposed to achieve a long fracture path. Hopkinson pressure rods with crack growth and strain gauges are used to impact the semi-circular holed disc bend specimens and to monitor the cracking process of a mode-I fracture. The experiments show that the crack growth speed increases to a critical value after crack initiation and then oscillates as a result of the reflected stress wave. The dynamic propagation fracture toughness ( K IC d ) increases with increasing crack velocity for steady crack propagation; however, this does not apply for unsteady propagation. An experimental–numerical–analytical method is developed to determine the dynamic stress intensity factor , which initially increases with time, then decreases, and ultimately increases again. The acceleration ( v ˙ ) can be used to investigate the unsteady crack propagation process. K IC d values for v ˙ < 0 are greater than those for v ˙ > 0. An energy release rate formula related to v ˙ and the crack propagation velocity ( v ) is proposed and verified by the experiments. A thorough understanding of v , v ˙ , and K IC d is important to analyze high-speed fault rupture processes.

Numerical investigation of the effect of the rectangle-type cavitating-bubble generator on the sheet/cloud cavitating flow around the NACA66 hydrofoil

The objective of this work is to present the effect mechanism of a passive control method using a spanwise rectangle-type cavitating-bubble generator (CG) on the unsteady partial cavitation based on the simulation. First of all, the numerical method using a Partially-averaged Navier–Stokes (PANS) turbulence model was validated and showed the good agreement with the experiment. Then the effects of CG on different cavitation stages were studied separately. It is found that the CG has a significant effect on the unsteady process of sheet cavity, and it can effectively mitigate or suppress the cavity shedding behavior, especially for the incipient cavitation stage with larger cavitation numbers. Correspondingly, the time-fluctuation amplitude of the wall-pressure, lift and drag for the hydrofoil with CG are reduced dramatically. In addition, the time-averaged lift-to-drag ratio of hydrofoil is improved desirably after using the CG. The conclusion of this work will be promising for the cavity dynamic controlling field.

Study on Restart Safety of Waxy Crude Pipelines Based on Reliability Principle under Constant Flow.

The restart process of waxy crude pipelines is an unsteady thermo-hydraulic coupling process, which mainly includes two modes of the constant flow and constant pressure in industry. However, some parameters involved in the restart process have obvious uncertainties, such as the operating parameters, physical parameters of crude oil, environmental parameters, and pipeline parameters, resulting in the traditional deterministic method that cannot scientifically describe the safety of the pipeline restart process. To do this, this study introduces the reliability-based limit state method and interference principle into the safety evaluation of waxy crude pipelines during the restart process. Considering the random fluctuation characteristics of the mentioned parameters, the restart physical process, the flow and heat transfer mathematical model, and the restart failure limit state function were established. On this basis, the failure probability during the restart process for one waxy crude pipeline under constant flow was determined. This research has realized the quantitative evaluation of restart safety of waxy crude pipelines.

Analysis of the Loss Production Mechanism Due to Cavity–Main Flow Interaction in a Low-Pressure Turbine Stage

Abstract In the present work, URANS simulations are presented to describe the unsteady interaction process between the flow ingested/ejected from a cavity system and the main flow evolving into a low-pressure turbine stage. Particular care is posed on the analysis of the loss generation mechanisms acting outside the stator row and in the rear part of the axial gap separating the cavity flow ejection section and the leading edge plane of the downstream rotor row. The simulated geometry reproduces a typical engine cavity configuration, with upstream and downstream rotor rows reproduced by means of moving bars. Experimental results have been used to validate the simulations. These experimental data cannot explain and quantify alone the overall interaction process between the cavity flows and the main flow. The results of a simulation made by removing the domain of the cavity have been employed in order to better highlight and quantify the effects due to main flow and cavity flows interaction on total pressure loss. A deep inspection of the loss amount along the axial direction makes evident that losses generated in the vane row are basically increased prior to entering into the downstream rotor bars, due to cavity main flow interaction.

One-Dimensional Modeling for Pulsed Flow Twin-Entry Turbine

Abstract One-dimensional (1D) modeling is critical for turbomachinery unsteady performance prediction and system response assessment of internal combustion engines. This paper uses a novel 1D modeling (TURBODYNA) and proposes two additional features for the application to a twin-entry turbocharger turbine. Compared to single-entry turbines, twin-entry turbines enhance turbocharger transient response and reduce engine exhaust valve overlap periods. However, out-of-phase high-frequency pulsating pressure waves lead to an unsteady mixing process from the two flows and pose great challenges to traditional 1D modeling. The present work resolves the mixing problem by directly solving mass, momentum, and energy conservation equations during the mixing process instead of applying constant pressure assumption at the limb–rotor joint. Comparisons of TURBODYNA and an experimentally validated CFD suggest that TURBODYNA cannot only provide a very good agreement on turbine performance but also accurately capture unsteady features due to flow field inertial and pressure wave propagation. Levels of accuracy achieved by TURBODYNA have proved superior to traditional 1D modeling on turbine performance and the generality of the current 1D modeling has been explored by extending the application to other turbine featuring distinct characteristics.

High-speed imaging of magnetized plasmas: When electron temperature matters

High-speed camera imaging is a powerful tool to probe the spatiotemporal features of unsteady processes in plasmas, usually assuming light fluctuations to be a proxy for the plasma density fluctuations. In this article, we systematically compare high-speed camera imaging with simultaneous measurements of the plasma parameters—plasma density, electron temperature, and floating potential—in a modestly magnetized Argon plasma column at low pressure (1 mTorr, magnetic fields ranging from 160 to 640 G). The light emission was filtered around 488 ± 5, 750 ± 5, and 810 ± 5 nm. We show that the light intensity cannot be interpreted as a proxy for the plasma density, and that the electron temperature cannot be ignored when interpreting high-speed imaging, both for the time-averaged profiles and for the fluctuations. The features of plasma parameter fluctuations are investigated, with a focus on ion acoustic waves (at frequency around 70 kHz) at low magnetic field and low-frequency azimuthal waves (around a few kHz) at larger magnetic fields. An excellent match is found between the high-speed images fluctuations and an Arrhenius law functional form, which incorporates fluctuations of the plasma density and of the electron temperature. These results explain the discrepancies between ion saturation current and narrow-band imaging measurements previously reported in the literature.