Total Site Hydrogen Integration with fresh hydrogen of multiple quality and waste hydrogen recovery in refineries

This paper proposes a novel method combining Pinch Methodology and waste hydrogen recovery, aiming to minimise fresh hydrogen consumption and waste hydrogen discharge. The method of multiple-level resource Pinch Analysis is extended to the level of Total Site Hydrogen Integration by considering fresh hydrogen sources with various quality. Waste hydrogen after Total Site Integration is further regenerated. The technical feasibility and economy of the various purification approaches are considered, demonstrated with a case study of a refinery hydrogen network in a petrochemical industrial park. The results showed that fresh hydrogen usage and waste hydrogen discharge could be reduced by 21.3% and 67.6%. The hydrogen recovery ratio is 95.2%. It has significant economic benefits and a short payback period for Total Site Hydrogen Integration with waste hydrogen purification. The proposed method facilitates the reuse of waste hydrogen before the purification process that incurs an additional environmental footprint. In line with the Circular Economy principles, hydrogen resource is retained in the system as long as possible before discharge.     

Parameter estimation for a morphochemical reaction-diffusion model of electrochemical pattern formation

The process of electrodeposition can be described in terms of a reaction-diffusion partial differential equation (PDE) system that models the dynamics of the morphology profile and the chemical composition. Here we fit such a model to the different patterns present in a range of electrodeposited and electrochemically modified alloys using PDE constrained optimization. Experiments with simulated data show how the parameter space of the model can be divided into zones corresponding to the different physical patterns by examining the structure of an appropriate cost function. We then use real data to demonstrate how numerical optimization of the cost function can allow the model to fit the rich variety of patterns arising in experiments. The computational technique developed provides a potential tool for tuning experimental parameters to produce desired patterns.     

A review on MRAS-type speed estimators for reliable and efficient induction motor drives

Induction machines have recently been very popular in variable-speed drives, because of their robust construction and relatively low manufacturing costs (brushless), maintenance-free and well-matured control methods. However, for high-precision control and efficiency optimization one needs the information on the rotor speed which can be measured using different speed sensors. All sensors require a mounting space and cabling, they also generate extra costs and reduce system reliability. Therefore, many of the recent research efforts have been dedicated to sensorless or encoderless electrical drives offering such considerable advantages as: lower cost, reduced size and hardware complexity of the drive system, elimination of sensor cables, lower maintenance requirements, possible operation in aggressive environment, higher noise immunity, reliable and user friendly operation. In this article all well-known sensorless techniques are shortly addressed, but the main focus is on the solutions based on the Model Reference Adaptive System (MRAS) concept. The mathematical models and schemes of all types of MRAS-type speed estimators known from the literature are gathered in this article. The comparative analysis of these speed estimators is done from the following points of view: the speed adaptation mechanism derivation based on the Lyapunov theory, stability problems near zero speed and in the regenerating operation mode, and the sensitivity of MRAS estimators to induction machine parameter changes.     

Preparation,characterization and investigation of molecular films coated on diamond-like carbon substrate

For the successful application of boundary lubrication, detailed investigations about the influence of preparation process on molecular films are needed. In this paper, a specially designed device was used for the film preparation. The scanning electron microscope (SEM) combined with atomic force microscope (AFM) was employed to characterize the surface morphology and nanotribological behavior of molecular films. After the liquid phase deposition, molecular films are randomly and densely distributed over Ti-doped diamond-like carbon (Ti-DLC) substrates. Through rigorous surface treatments, island-like molecular films were finally achieved on substrate surfaces. The surface friction of molecular films is obviously lower than that of Ti-DLC surfaces. Then, pin-on-disk tribotests were performed to study the macrofriction behavior of molecular films under different preparation parameters. Based on the orthogonal experiment, the effect of five preparation parameters (solution weight percent, smearing force and processing time of three smearing steps) on initial friction coefficient of molecular films was investigated. The results indicated that the order of significance levels is as follows: processing time of the second smearing step > solution weight percent > processing time of step 1 > processing time of step 3 > smearing force. For the purpose of friction reduction, the appropriate level ranges are 0.75% (Solution), 2.5 N–15 N (Force), 1 min–10 min (Step 1), 1 min–2 min (Step 2) and 1 min, 2 min, 5 min and 15 min (Step 3). The initial friction coefficient under the optimized conditions is around 0.112, and the equilibrium friction coefficient is around 0.162, which is lower than that of unlubricated Ti-DLC substrates.     

Scheduling distributed flowshops with flexible assembly and set-up time to minimise makespan

The scheduling problems under distributed production or flexible assembly settings have achieved increasing attention in recent years. This paper considers scheduling the integration of these two environments and proposes an original distributed flowshop scheduling problem with flexible assembly and set-up time. Distributed production stage is deployed several homogeneous flowshop factories that process the jobs to be assembled into final products in the flexible assembly stage. The objective is to find a schedule, including a production subschedule for jobs and an assembly subschedule for products, to minimise the makespan. Such a scheduling problem involves four successive decisions: assigning jobs to production factories, sequencing jobs at every factory, designating an assembly machine for each product and sequencing products on each assembly machine. The computational model is first established, and then a constructive heuristic (TPHS) and two hybrid metaheuristics (HVNS and HPSO) are proposed. Numerical experiments have been carried out and results validate the algorithmic feasibility and effectiveness. TPHS can obtain reasonable solutions in a shorter time, while metaheuristics can report better solutions using more yet acceptable time. HPSO is statistically comparable yet less robust compared with HVNS for small-scale instances. For the large-scale case, HPSO outperforms HVNS on both effectiveness and robustness.     

Methodology for dependence-based integrated constitutive modelling: An illustrative application to SiCp/Al composites

In industrial forming and machining process, the large plastic deformation of material takes place in wide loading ranges of strain-rate and forming temperature. A satisfactory modelling of quasi-static and dynamic material behaviors is of great importance for understanding physical process and processes optimization. A dependence-based integrated methodology, together with an improved weighted multi-objective parameter identification strategy is presented for the development of phenomenological constitutive model and the parameter identification using experimental data from quasi-static and dynamic tests with instantaneous strain rate variations and plastic strain-related temperature changes. The improved multi-objective parameter identification model is reformulated by introducing three weighting factors for valuing different measure errors and fit standard errors in individual objective function corresponding to each test, considering the sampling point number and active material parameter number under different loading conditions, and balancing optimization opportunity of quasi-static and dynamic sub-objective functions. The methodology is verified for feasibility through illustrative constitutive identification for SiC_p/Al composites. This may provide a methodology of constitutive modelling for predicting material behaviors in quasi-static and dynamic modes equally well.     

Hybrid self-inertia weight adaptive particle swarm optimisation with local search using C4.5 decision tree classifier for feature selection problems

ABSTRACT

Feature selection is an important task to improve the classifier’s accuracy and to decrease the problem size. A number of methodologies have been presented for feature selection problems using metaheuristic algorithms. In this paper, an improved self-adaptive inertia weight particle swarm optimisation with local search and combined with C4.5 classifiers for feature selection algorithm is proposed. In this proposed algorithm, the gradient base local search with its capacity of helping to explore the feature space and an improved self-adaptive inertia weight particle swarm optimisation with its ability to converge a best global solution in the search space. Experimental results have verified that the SIW-APSO-LS performed well compared with other state of art feature selection techniques on a suit of 16 standard data sets.     

State feedback integral control for a rotary direct drive servo valve using a Lyapunov function approach

This paper concerns a state feedback integral control using a Lyapunov function approach for a rotary direct drive servo valve (RDDV) while considering parameter uncertainties. Modeling of this RDDV servovalve reveals that its mechanical performance is deeply influenced by friction torques and flow torques; however, these torques are uncertain and mutable due to the nature of fluid flow. To eliminate load resistance and to achieve satisfactory position responses, this paper develops a state feedback control that integrates an integral action and a Lyapunov function. The integral action is introduced to address the nonzero steady-state error; in particular, the Lyapunov function is employed to improve control robustness by adjusting the varying parameters within their value ranges. This new controller also has the advantages of simple structure and ease of implementation. Simulation and experimental results demonstrate that the proposed controller can achieve higher control accuracy and stronger robustness.     

Integer programming methods for large-scale practical classroom assignment problems

In this paper we present an integer programming method for solving the Classroom Assignment Problem in University Course Timetabling. We introduce a novel formulation of the problem which generalises existing models and maintains tractability even for large instances. The model is validated through computational results based on our experiences at the University of Auckland, and on instances from the 2007 International Timetabling Competition. We also expand upon existing results into the computational difficulty of room assignment problems.