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•1D&3D coupled model for large-scale oil-heating type Mg-based hydrogen storage tank.•The three-dimensional flow of oil was simplified as a 1D nonisothermal pipeline flow.•Dehydriding ...process of large-scale oil-heating type Mg-based tank was first predicted.•Effects of oil velocity and temperature on the dehydriding process were investigated.
A large-scale oil-heating type Mg-based hydrogen storage tank is the key device for the high-efficiency and high-safety Mg-based solid hydrogen storage and transportation. However, the complicated heat and mass transfer in the Mg alloy bed and oil tube during the hydrogen desorption process impede the design of high-performance hydrogen storage tanks. In this work, a one- and three-dimensional coupled model considering the impact of oil velocity and temperature on the internal heat and mass transfer was developed to simulate the hydrogen desorption process of large-scale oil-heating type Mg-based hydrogen storage tanks. This model was then solved by the finite element method, and the simulation results agreed well with the experimental data obtained from an Mg-based hydrogen storage tank. Moreover, simulation results indicate that the oil velocity has a considerable impact on the hydrogen desorption performance of the Mg-based hydrogen storage tank, and a recommended oil velocity of 4 m s−1 was identified. In addition, high oil temperature and low hydrogen desorption pressure benefit the hydrogen desorption performance, thus should be determined by the application scenarios. Besides, the complete hydrogen desorption time was barely affected by the initial bed temperature, which is suggested as ≥ 573 K to meet the high rate requirement of hydrogen supply, otherwise as room temperature to reduce energy costs. The model and simulation results presented in this work provided a foundation for the design of high performance large-scale oil-heating type Mg-based hydrogen storage tanks that can be applied practically in the field of hydrogen energy.
In this work, by mining the experimental data of fast pyrolysis of lignocellulosic biomass in bubbling fluidized bed in previous literature, regression prediction models were established for ...three-phase product distribution and bio-oil heating value (HHV) based on gradient boosting, random forest, support vector machine, and multilayer perceptron algorithms. Comprehensive feedstock characteristics and pyrolysis conditions were considered and compared as input features. Among the several algorithms, random forest is most suitable for the prediction of three-phase product yields and bio-oil HHV with the benefits of high accuracy and good generalization ability. Visual analysis of the model shows that pyrolysis temperature is the most critical factor affecting three-phase product distribution, while bio-oil HHV is more affected by the feedstock characteristics such as the contents of C and H. The highest yield and HHV of bio-oil is obtained at about 480 °C, suggesting 480 °C as the optimum pyrolysis temperature of fast pyrolysis of biomass in a bubbling fluidized bed. As for the feedstock characteristics, high contents of C and H and low content of O are favorable to the enhancement of bio-oil HHV, indicating the crucial importance of feedstock pretreatment such as torrefaction to the quality improvement of bio-oil.
•Different performance of several machine learning algorithms were compared.•Comprehensive feedstock characteristics and pyrolysis conditions were considered and compared.•Random forest models with high accuracy and good generalization ability were established.•Pyrolysis temperature is the most critical factor affecting three-phase product distribution.•Bio-oil heating value is mostly affected by the contents of C and H elements in feedstock.
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•Product distribution and bio-oil heating value from biomass pyrolysis can be predicted using artificial intelligence models.•Nearly 200 correlated samples were collected to ensure ...the applicability of the models and describe biomass pyrolysis.•The link between pyrolytic products and the biomass feedstock and operating conditions was established by deep data mining.
Prediction models for product distribution and bio-oil heating value of biomass pyrolysis, were established in this paper using some artificial intelligence algorithms, i.e. artificial neural network (ANN) and support vector machine (SVM). Correlated samples about biomass pyrolysis were collected as data set. The modeling results showed that both ANN and SVM models can estimate the pyrolytic product yield and bio-oil heating value successfully. In all cases, the ANN model accorded well with the experimental data in the training set while SVMs performed better in the prediction set, which indicated that SVM model has a better predicting performance in biomass pyrolysis. The established prediction model can be used as a good reference of the modeling study of biomass fast pyrolysis.
•Dynamic control of a distillation column with dual steam and hot oil reboilers is explored.•Steam consumption is reduced by using a hot oil liquid stream from an external unit.•Several control ...structures are evaluated.•The Qtotal control structure reduces peak deviations in product purities.
Many distillation columns achieve process intensification by utilizing hot streams from other units in the plant to substitute for some of the utility-supplied steam used in the reboiler. This thermal coupling requires adequate differential temperature driving forces so that heat-exchanger area is not excessive. It also requires that the units are reasonably close together so that piping cost and pressure drops are not too large. There are two reboilers at the base of the column that operate in parallel with the two independent heat sources providing vapor boilup. If the external hot stream is vapor that is condensed in the one reboiler, the heat transferred is latent heat. If the external hot stream is hot liquid, the heat transferred is sensible heat, which requires much larger flowrates. Since pumping liquid is relatively inexpensive, larger flowrates and larger pressure drops are less important than in vapor streams.
This paper explores the dynamic control of dual-reboiler distillation columns in which a hot liquid stream from another unit is fed to one reboiler and steam is fed as needed to the other reboiler. The key simulation implementation issue is how to dynamically model the heat transfer in the hot-oil reboiler since it is governed by log-mean differential temperature driving forces. Several alternative control structures are evaluated.
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With the characteristics of large inertia, large time delay and time-varying parameters, it is difficult to control accurately the oil heating process in an oil-replenishing device for deep-sea ...hydraulic system. Four temperature control methods are presented and compared in this paper, i.e. proportional–integral–derivative controller(PID controller), fuzzy PID controller, Smith fuzzy PID controller and modified Smith fuzzy PID controller which adds a first order filter in the Smith predictor. They are simulated in MATLAB/SIMULINK based on the cases of transfer function matching and mismatching between the theoretical and the actual model. The results show that, in both cases, the step response curve of the modified Smith fuzzy PID controller has neither the significant oscillation nor the overshoot and requires the minimum time to achieve stabilization as well. Furthermore, this paper applies those four control methods in actual oil heating temperature control process through PIC16F877A micro controller unit (MCU). The experimental data demonstrate that the oil heating system controlled by the modified Smith fuzzy PID controller could stabilize at the expected temperature with nearly no overshoot, which further proves that the modified Smith fuzzy PID controller is able to sufficiently meet the challenges of industrial applications containing varying system parameters.
•The transfer function of oil heating system is established and its parameters are identified.•Four control schemes of oil heating system in an oil-replenishing device are simulated and compared.•The simulation results indicate that the modified Smith fuzzy PID controller has the best control effect.•The experiments further verifies the simulation result.•Modified Smith fuzzy PID controller could accomplish the accurate oil temperature control in an oil-replenishing device.
We describe a novel plasma source developed at the Max Planck Institute for Physics that will be used for a proton driven plasma wakefield accelerator experiment at CERN. Rubidium vapor is confined ...in a 10meter -long, 4cm diameter, oil-heated stainless steel pipe. A laser pulse tunnel ionizes the vapor forming a 10-meter long, ~1mm radius plasma with a range of densities around ~1015cm−3. Access to the source is provided using custom manufactured fast valves. The source is designed to produce a plasma with a density uniformity of at least ~0.2% during the beam–plasma interaction.
This work proposes a mathematical modeling and numerical simulation of a gyp-sum rotary kiln with indirect oil heating in a 3-D transient regime. The mathematical model was based on Fourier's law as ...a constitutive relationship and the principle of energy conservation, applied to a control volume in cylindrical co-ordinates. Furthermore, a bed homogenization model was used to represent the most realistic condition of the physical phenomenon since some rotary kilns have internal fins that aim at homogenizing the gypsum temperature during calcination. This work intends to fill the gap found in heat transfer processes on rotary kilns in transient regime considering 3-D positions, to have an accurate projection of the temperature profile of the kiln and also, given by the numerical model, the possibility of a tool that can be used to the optimization of the control system of rotary kilns considering the actual demand of the material in production, leading to the best energy performance of the equipment's activation source, as well as reaching the temperatures and processing time of the product. The numerical simulation results revealed reasonable agreement with the experimentally deter-mined calcination process in rotary kilns. Furthermore, a parametric analysis of the influence of the mixture on the temperature fields and the calcination time was carried out to verify the energetic balance of the rotary kiln.
•This study focuses on optimization of an air source transcritical CO2 heat pump.•Factors influencing the optimal discharge pressure were examined experimentally.•A correlation formula for the ...optimal discharge pressure was determined.•Compared with the experimental results, the maximum error was less than 10%.•A control strategy for based on degree of superheat correction was proposed.
The compressor discharge pressure is an important parameter for optimizing the performance of a transcritical CO2 heat pump system. In this study, the factors influencing the optimal compressor discharge pressure of an air source transcritical CO2 heat pump system were examined experimentally. The results showed that the optimal compressor discharge pressure is affected by the gas cooler water inlet temperature and gas cooler CO2 outlet temperature. Consequently, a correlation formula for the optimal compressor discharge pressure appropriate for a more comprehensive temperature range and higher prediction accuracy was determined based on the experimental data. Compared with the experimental results, the maximum error was less than 10%, which is minor considering the lower gas cooler CO2 outlet temperature. In addition, a control strategy for the optimal compressor discharge pressure based on the degree of superheat correction was proposed. Subsequently, under variable operating conditions, the air source transcritical CO2 heat pump crude oil heating system was continuously operated based on this control strategy. The results showed that the compressor discharge pressure agreed with the optimal compressor discharge pressure calculated using the new correlation formula. Compared with the control strategy of constant opening under a variable frequency mode, the results showed that the system could operate under the control strategy proposed in this paper, the thermodynamic perfection of the system being higher.
Wax deposition reduces the transportation capacity of oil pipelines and brings major safety hazards to oil production. Heating crude oil with a coil type heater can prevent wax deposition. To study ...the failure mechanism of the connection between the coil pipe and the gathering pipe and then find optimization methods, the microstructures of the welded joint are observed by scanning electron microscopy, and the mechanical properties of the materials are tested. A mechanical model of the interaction between crude oil and coil pipe is constructed for simulation calculations. The relations between mechanical properties and structural parameters are obtained, and the influence of inclination angle of coil pipe on heat transfer performance is found opposite to that on static performance. Based on the comprehensive analysis of heat transfer rate and stress-strain of multi groups of coil pipes, the methods to optimize the overall performance of the coil heater from the aspects of material, structure and processing technology are proposed. The maximum equivalent (von-Mises) stress and shear stress of bell end coil pipe are reduced by 14.81% and 3.22% respectively, and the heat transfer rate is increased by 7.36 kW compared with that of the original structure under the same working condition.
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