A bi-layer optimization approach for a hybrid flow shop scheduling problem involving controllable processing times in the steelmaking industry

A steelmaking-continuous casting (SCC) scheduling problem is an example of complex hybrid flow shop scheduling problem (HFSSP) with a strong industrial background. This paper investigates the SCC scheduling problem that involves controllable processing times (CPT) with multiple objectives concerning the total waiting time, earliness/tardiness and adjusting cost. The SCC scheduling problem with CPT is seldom discussed in the existing literature. This study is motivated by the practical situation of a large integrated steel company in which the just-in-time (JIT) and cost-cutting production strategy have become a significant concern. To address this complex HFSSP, the scheduling problem is decomposed into two subproblems: a parallel machine scheduling problem (PMSP) in the last stage and an HFSSP in the upstream stages. First, a hybrid differential evolution (HDE) algorithm combined with a variable neighborhood decomposition search (VNDS) is proposed for the former subproblem. Second, an iterative backward list scheduling (IBLS) algorithm is presented to solve the latter subproblem. The effectiveness of this bi-layer optimization approach is verified by computational experiments on well-designed and real-world scheduling instances. This study provides a new perspective on modeling and solving practical SCC scheduling problems.     

A Complexing Agent to Enable a Wide-Temperature Range Bromine-Based Flow Battery for Stationary Energy Storage

Bromine-based flow batteries (Br-FBs) are considered one of the most promising energy storage systems due to their features of high energy density and low cost. However, they generally suffer from uncontrolled diffusion of corrosive bromine particularly at high temperatures. That is because the interaction between polybromide anions and the commonly used complexing agent (N–methyl–N–ethyl–pyrrolidinium bromide [MEP]) decreases with increasing temperatures, which causes serious self-discharge and capacity fade. Herein, a novel bromine complexing agent, 1–ethyl–2–methyl–pyridinium bromide (BCA), is introduced in Br-FBs to solve the above problems. It is proven that BCA can combine with polybromide anions very well even at a high temperature of 60 °C. Moreover, the BCA contributes to decreasing the electrochemical polarization of Br⁻/Br₂ couple, which in turn improves their power density. As a result, a zinc–bromine flow battery with BCA as the complexing agent can achieve a high energy efficiency of 84% at 40 mA cm⁻², even at high temperature of 60 °C and it can stably run for more than 400 cycles without obvious performance decay. This paper provides an effective complexing agent to enable a wide temperature range Br-FB.     

Effects of structural parameters on water film properties of transpiring wall reactor

Corrosion and salt deposition problems severely restrict the industrialization of supercritical water oxidation. Transpiring wall reactor can effectively weaken these two problems by a protective water film. In this work, methanol was selected as organic matter, and the influences of vital structural parameters on water film properties and organic matter removal were studied via numerical simulation. The results indicate that higher than 99% of methanol conversion could be obtained and hardly affected by transpiration water layer, transpiring wall porosity and inner diameter. Increasing layer and porosity reduced reactor center temperature, but inner diameter's influence was lower relatively. Water film temperature reduced but coverage rate raised as layer, porosity, and inner diameter increased. Notably, the whole reactor was in supercritical state and coverage rate was only approximately 85% in the case of one layer. Increasing reactor length affected slightly the volume of the upper supercritical zone but enlarged the subcritical zone.     

Performance of surface ionic conduction single chamber fuel cell prepared by the sol gel method

The performance of surface ionic conduction single chamber fuel cell (SIC‐SCFC) prepared by the sol gel method was studied on electric characteristics due to the differences of the operating temperature and humidity, the electrode distance and electrolyte film depth, and multiple cells with the series and parallel connections. The SIC–SCFC was arranged the both anode of Pt and cathode of Au on the boehmite electrolyte. The open circuit voltage (OCV) of single cell achieved a maximum of 530mV in the dry gas mixtures of O₂/H₂=50% in room temperature operation, and but it became decrease as over 60%. The OCV was maintained the constant value between operating temperatures of 30°C to 80°C, and but it was decreased sharply at over 90°C because a humidity on the cell became lower as increasing operating temperature. Then, the cell property was improved to 120°C by adding to the humidity of 70% using a humidifier. The electrode distance and the electrolyte film depth of SIC‐SCFC found to be contributed to the reductions of the cell resistance and the surface roughness on the electrode, respectively. Moreover, the power property of SIC‐SCFC was significantly improved by cell stacks comprised of the series or parallel connection of a cell.     

Flow state monitoring of gas-water two-phase flow using multi-Gaussian mixture model based on canonical variate analysis

As a highly complex and time-varying process, gas-water two-phase flow is commonly encountered in industries. It has a variety of typical flow states and transition flow states. Accurate identification and monitoring of flow states is not only beneficial to further study of two-phase flow but also helpful for stable operation and economic efficiency of process industry. Combining canonical variate analysis (CVA) and Gaussian mixture model (GMM), a strategy called multi-CVA-GMM is proposed for flow state monitoring in gas-water two-phase flow. CVA is used to extract flow state features from the perspective of correlation between historical data and future data, which solves the cross correlation and temporal correlation of multi-sensor measurement data. GMM calculates the possibility that the current flow state belongs to each typical flow pattern and judges the current flow state by probability indicators. It is conducive to follow-up use of Bayesian inference probability and Mahalanobis distance-based (BID) indicator for flow state monitoring, which avoids repeated traversal of multiple CVA-GMM models and improves the efficiency of the monitoring process. The probability indicators can also be used to analyze transition flow states. The method combining the probabilistic idea of GMM with the deterministic idea of multimodal modeling can accurately identify the current flow state and effectively monitor the evolution of flow state. The multi-CVA-GMM method is validated by using the measured data of the horizontal flow loop of gas-water two-phase flow experimental facility, and its effectiveness is proved.     

Comments on “Study and application of discharge calibration for submerged radial gates” by Guo X., Guo Y., Wang T., Fu H., Li J. Flow Meas. Instrum. 78 (2021) 101912, https://doi.org/10.1016/j.flowmeasinst.2021.101912

This paper discusses the capability of Guo et al.'s (2021) equations to determine the discharge of radial gates under submerged flow conditions. It was concluded that Guo et al.'s (2021) equations are associated with error reduction compared to the Incomplete Self-Similarity (ISS) theory and the calibration method. However, it does not have a significant advantage over Energy-Momentum (E-M) approach. Employing E-M principles, new equations were proposed to determine the discharge of radial gates, which has some advantages compared to Guo et al. (2021), such as (1) error reduction under partially and fully submerged flow conditions, (2) least dependence on the empirical constants, (3) uniformity of form over the entire submerged condition, and (4) no need to classify the submerged flow. Field calibration showed that the proposed equations in the present study for a single gate predict the discharge of parallel radial gates with a mean absolute error of less than 4.5% subject to the submerged operation of all open gates.     

Computational modelling of water flow inside laboratory Knelson concentrator bowl

Enhanced gravity concentrators such as Knelson concentrator (KC) are extensively used in the mineral processing industry. The complexities of KC bowl geometry and variation of feed characteristics have forced process engineers to design empirically new units using laboratory and pilot-scale Knelson concentrators. However, numerical modelling methods such as computational fluid dynamics (CFD) and discrete element method (DEM) provide a better insight of flow behaviour of fluid and particulate solid phases inside these processing units. This article reports findings of CFD simulations for single-phase water flow inside the laboratory KC. An available standard 7.5-cm laboratory KC bowl was numerically simulated using realisable k-ε turbulence model to resolve the turbulence dispersion of existing transitional flow regime. The effects of relative centrifugal force (RCF) intensity and bed fluidisation water flow rate on the water velocity and pressure distributions were studied. Simulations confirmed the swirling flow pattern governing inside the bowl. The results revealed that the impact of RCF intensity on the water field values is greater than that of bed fluidisation water flow rate. Both velocity and pressure variations inside the bowl rings followed a linear trend.     

A modified cross-correlation algorithm for PIV image processing of particle-fluid two-phase flow

PIV (Particle Image Velocimetry) technique for flow field measurement has achieved popular self-identify through over ten years development, and its application range is becoming wider and wider. PIV post-processing techniques have a great influence on the success of particle-fluid two-phase flow field measurement and thus become a hot and difficult topic. In the present study, a Phase Respective Identification Algorithm (PRIA) is introduced to separate low-density solid particles or bubbles and high-density tracer particles from the PIV image of particle-fluid two-phase flow. PTV (Particle Tracking Velocimetry) technique is employed to calculate the velocity fields of low-density solid particles or bubbles. For the velocity fields of high-density solid particles or bubble phase and continuous phase traced by high-density smaller particles, based on the thought of wavelet transform and multi-resolution analysis and the theory of cross-correlation of image, a delaminated processing algorithm (MCCWM) is presented to conquer the limitation of conventional Fourier transform. The algorithm is firstly testified on synthetic two-phase flows, such as uniform steady flow, shearing flow and rotating flow, and the computational results from the simulated particle images are in reasonable agreement with the given simulated data. The algorithm is then applied to images of actual bubble-liquid two-phase flow and jet flow, and the results also confirmed that the algorithm proposed in the present study has good performance and reliability for post-processing PIV images of particle-fluid two-phase flow.     

The use of bio-diesel based additive as rheology improver and pour point depressant of Nigerian waxy crude

The chemical method has proved to be the most effective mitigating method of wax deposition in petroleum system as it deals with the root cause of wax formation. Most of the commercial chemicals in the industry are very expensive and toxic. This paper aims the use of biodiesel based additives for improving the rheological behavior and pour points of waxy crude from Nigeria field. The biodiesels derived additives gave better performance than the commercial chemical and the seed oils as greatly improvement in rheology and pour point values of the waxy crude were observed