Performance of a Degassing Cyclone with Main and Subsidiary Chambers

Based on the premise that large bubbles are removed in larger cyclones and small bubbles in smaller cyclones, a combined degassing cyclone with main and subsidiary chambers was designed to enhance liquid degassing. The pressure loss, liquid flow rate at the gas outlet, split ratio, gas flow rate at the liquid outlet, and degassing efficiency of the degassing cyclone were measured and calculated. Pressure loss correlations were established which relates the Euler number to the gas and liquid Reynolds numbers in the main chamber. Most cases exhibit a degassing efficiency greater than 0.998 when the liquid flow rate is more than 0.7 m³h^?1. The contours of pressure loss, split ratio, and degassing efficiency provide an effective guidance for designing a degassing cyclone.     

A survey on tracking control of unmanned underwater vehicles: Experiments-based approach

This paper aims to provide a review of the conceptual design and theoretical framework of the main control schemes proposed in the literature for unmanned underwater vehicles (UUVs). Additionally, the objective of the paper is not only to present an overview of the recent control architectures validated on UUVs but also to give detailed experimental-based comparative studies of the proposed control schemes. To this end, the main control schemes, including proportional–integral–derivative (PID) based, sliding mode control (SMC) based, adaptive based, observation-based, model predictive control (MPC) based, combined control techniques, are revisited in order to consolidate the principal efforts made in the last two decades by the automatic control community in the field. Besides implementing some key tracking control schemes from the classification mentioned above on Leonard UUV, several real-time experimental scenarios are tested, under different operating conditions, to evaluate and compare the efficiency of the selected tracking control schemes. Furthermore, we point out potential investigation gaps and future research trends at the end of this survey.     

Thermo-economic analysis of a direct supercritical CO2 electric power generation system using geothermal heat

A comprehensive thermo-economic model combining a geothermal heat mining system and a direct supercritical CO₂ turbine expansion electric power generation system was proposed in this paper. Assisted by this integrated model, thermo-economic and optimization analyses for the key design parameters of the whole system including the geothermal well pattern and operational conditions were performed to obtain a minimal levelized cost of electricity (LCOE). Specifically, in geothermal heat extraction simulation, an integrated wellbore-reservoir system model (T2Well/ECO2N) was used to generate a database for creating a fast, predictive, and compatible geothermal heat mining model by employing a response surface methodology. A parametric study was conducted to demonstrate the impact of turbine discharge pressure, injection and production well distance, CO₂ injection flowrate, CO₂ injection temperature, and monitored production well bottom pressure on LCOE, system thermal efficiency, and capital cost. It was found that for a 100 MW_e power plant, a minimal LCOE of $0.177/kWh was achieved for a 20-year steady operation without considering CO₂ sequestration credit. In addition, when CO₂ sequestration credit is $1.00/t, an LCOE breakeven point compared to a conventional geothermal power plant is achieved and a breakpoint for generating electric power generation at no cost was achieved for a sequestration credit of $2.05/t.     

隧道预应力锚杆锚固结构承载效应及围岩力学分析

隧道中锚杆与围岩作用机理比较复杂，设计多偏于类比法和经验法，以锚杆在连续均匀地层中形成锚固结构为出发点，建立锚固结构承载强度表达式，并确定锚杆设计参数。通过对锚固结构承载特性分析，得到各影响因素对承载强度的贡献程度，在此基础上提出了“支护力放大系数”和“锚固界限强度”概念，再将锚固结构整体考虑并等效成支护力对隧道围岩应力分布、塑性区、位移进行重新求解，最终结合数值模拟和算例验证。研究结果表明：锚固结构对锚杆支护力具有放大作用，对隧道深部围岩也提供一个较强的支护力，锚固结构强度影响程度由大到小依次为力学参数、锚固厚度、支护强度，其中力学参数对锚固承载强度起着至关重要作用，合理锚固厚度为洞径的0.4～0.8倍，进一步提出了围岩稳定性控制原则。数值模拟中锚杆支护、等效力支护与理论结果加以比较，隧道周边的塑性区、应力分布、位移基本一致，可为锚杆支护下隧道围岩控制提供一种科学的分析方法。     

城门山铜矿半自磨优化控制系统

根据城门山铜矿半自磨磨矿工艺流程，研究了以半自磨机为主体的磨矿优化控制策略，建设了由DCS 系统、优化系统、数据分析系统组成 SAB 控制系统。通过工业连续运行试验证明控制策略能够改善磨矿溢流产品粒级分布、同时减少了钢球和电能的消耗。     

低压静电场辅助冷冻对竹笋品质的影响

为研究低压静电场辅助冷冻对竹笋冻结特性的影响，以冻结曲线、硬度、水分损失率、水分迁移、冰晶形态和组织微观结构为指标，探究低压静电场辅助冷冻（－35 ℃）和普通冷冻（－35 ℃）条件下竹笋品质的变化规律。结果表明：低压静电场辅助冷冻提高了冻结效率，改变了冰晶形态及分布，减轻了组织微观结构破损程度，改善了解冻汁液流失情况。与静电板间距10、20、30、40 cm处的冷冻竹笋解冻后水分损失率分别为14.16%、12.58%、9.73%、10.44%，显著低于对照组（21.01%）（P＜0.05），硬度分别为461.19、507.48、496.65 g和455.31 g，显著高于对照组（350.70 g）（P＜0.05）。低场核磁共振分析结果表明，在低压静电场辅助冷冻下竹笋解冻后汁液流失减少，扫描电子显微镜观察结果显示，竹笋纤维排列整齐，组织微观结构保持较好。低压静电场辅助冷冻可有效改善竹笋品质，可为利用低压静电场进行果蔬的冷冻贮藏和冷链运输提供参考。     

Coordination of Networked Nonlinear Multi-Agents Using a High-Order Fully Actuated Predictive Control Strategy

This paper is concerned with the coordinative control problem of networked nonlinear multi-agents (NNM) with communication delays. A high-order fully actuated (HOFA) model is introduced to describe the nonlinear multi-agents. Based on this model, a HOFA predictive coordination method is proposed to compensate for the communication delays actively and achieve simultaneous stability and consensus. This method largely simplifies the design of networked nonlinear multi-agents and makes the control performance be same for networked nonlinear multi-agents with and without communication delays. The analysis on the closed-loop systems derives the simultaneous stability and consensus criteria of networked nonlinear multi-agents using the HOFA predictive coordination method. With the presented way of designing HOFA predictive coordination controllers, a simulated example demonstrates the advantages of the proposed method.      

Process knowledge-based random forest regression for model predictive control on a nonlinear production process with multiple working conditions

In process industry, predictive control approaches have been widely used for nonlinear production processes. Practically, the predictor in a predictive controller is extremely important since it provides future states for the optimization problem of controllers. The conventional predictive controller with precise mathematical predictors approximating the state space of physical systems is difficult and time-consuming for nonlinear production processes, and it performs poorly over a wide range of working conditions and with significant disturbances. To address the challenges, the trend of applying artificial intelligence emerges. However, the industrial process-specific knowledge is ignored in most cases. In this study, a predictive controller with a control process knowledge-based random forest (RF) model is proposed. Specifically, working data are clustered at first to handle diverse working conditions. Then, a process knowledge-based forest predictor, namely MIW-RF model with a redesigned cascading RF structure, is proposed to incorporate control process knowledge into modeling. Thus, future states of controlled variables could be more accurately acquired for the optimizer. A simplified version of the predictive model is also developed with quick model training and updating. The proposed predictive methods are finally introduced into the controller design. According to the empirical results, the proposed methods deliver a better control performance against benchmarks, including more accurate anticipated controlled-variable responses, better set-point tracking and disturbance rejection capability.     

A lattice Boltzmann exploration of two-phase displacement in 2D porous media under various pressure boundary conditions

While experimental designs developed in recent decades have contributed to research on dynamic nonequilibrium effects in transient two-phase flow in porous media, this problem has been seldom investigated using direct numerical simulation (DNS). Only a few studies have sought to numerically solve Navier–Stokes equations with level-set (LS) or volume-of-fluid (VoF) methods, each of which has constraints in terms of meniscus dynamics for various flow velocities in the control volume (CV) domain. The Shan–Chen multiphase multicomponent lattice Boltzmann method (SC-LBM) has a fundamental mechanism to separate immiscible fluid phases in the density domain without these limitations. Therefore, this study applied it to explore two-phase displacement in a single representative elementary volume (REV) of two-dimensional (2D) porous media. As a continuation of a previous investigation into one-step inflow/outflow in 2D porous media, this work seeks to identify dynamic nonequilibrium effects on capillary pressure–saturation relationship (P_c–S) for quasi-steady-state flow and multistep inflow/outflow under various pressure boundary conditions. The simulation outcomes show that P_c, S and specific interfacial area (a_nw) had multistep-wise dynamic effects corresponding to the multistep-wise pressure boundary conditions. With finer adjustments to the increase in pressure over more steps, dynamic nonequilibrium effects were significantly alleviated and even finally disappeared to achieve quasi-steady-state inflow/outflow conditions. Furthermore, triangular wave-formed pressure boundary conditions were applied in different periods to investigate dynamic nonequilibrium effects for hysteretical P_c–S. The results showed overshoot and undershoot of P_c to S in loops of the nonequilibrium hysteresis. In addition, the flow regimes of multistep-wise dynamic effects were analyzed in terms of Reynolds and capillary numbers (Re and Ca). The analysis of REV-scale flow regimes showed higher Re (1 < Re < 10) for more significant dynamic nonequilibrium effects. This indicates that inertia is critical for transient two-phase flow in porous media under dynamic nonequilibrium conditions.