Robust optimal operation of continuous catalytic reforming process under feedstock uncertainty

The continuous catalytic regenerative (CCR) reforming process is one of the most significant sources of hydrogen production in the petroleum refining process. However, the fluctuations in feedstock composition and flow rate could significantly affect both product distribution and energy consumption. In this study, a robust deviation criterion based multi-objective optimization approach is proposed to perform the optimal operation of CCR reformer under feedstock uncertainty, with simultaneous maximization of product yields and minimization of energy consumption. Minimax approach is adopted to handle these uncertain objectives, and the Latin hypercube sampling method is then used to calculate these robust deviation criteria. Multi-objective surrogate-based optimization methods are next introduced to effectively solve the robust operational problem with high computational cost. The level diagram method is finally utilized to assist in multi-criteria decision-making. Two robust operational optimization problems with different objectives are solved to demonstrate the effectiveness of the proposed method for robust optimal operation of the CCR reforming process under feedstock uncertainty.     

Review of electrospun hydrogel nanofiber system: Synthesis,Properties and Applications

Hydrogel-based nanofibers or vice versa are a relatively new class of nanomaterials, in which hydrogels are structured in nanofibrous form. Structure and size of the material directly governs its functionality, therefore, in hydrogel science, the nanofibrous form of hydrogels enables its usage in targeted applications. Hydrogel nanofiber system combines the desirable properties of both hydrogel and nanofiber like flexibility, soft consistency, elasticity, and biocompatibility due to high water content, large surface area to volume ratio, low density, small pore size and interconnected pores, high stiffness, tensile strength, and surface functionality. Swelling behavior is a critical property of hydrogels that is significantly increased in hydrogel nanofibers due to their small size. Electrospinning is the most popular method to fabricate “hydrogel nanofibers,” while other processes like self-assembly, solution blowing and template synthesis also exist. Merging the characteristics of both hydrogels and nanofibers in one system allows applications in drug delivery, tissue engineering, actuation, wound dressing, photoluminescence, light-addressable potentiometric sensor (LAPS), waterproof breathable membranes, and enzymatic immobilization. Treatment of wastewater, detection, and adsorption of metal ions are also emerging applications. In this review paper, we intend to summarize in detail about electrospun “hydrogel nanofiber” in relation to its synthesis, properties, and applications.     

Robust optimisation of sustainable food grain transportation with uncertain supply and intentional disruptions

The proliferating need for sustainability intervention in food grain transportation planning is anchoring the attention of researchers in the interests of stakeholders and environment at large. Uncertainty associated with food grain supply further intensifies the problem steering the need for designing robust, cost-efficient and sustainable models. In line with this, this paper aims to develop a robust and sustainable intermodal transportation model to facilitate single type of food grain commodity shipments while considering procurement uncertainty, greenhouse gas emissions, and intentional hub disruption. The problem is designed as a mixed integer non-linear robust optimisation model on a hub and spoke network for evaluating near optimal shipment quantity, route selection and hub location decisions. The robust optimisation approach considers minimisation of total relative regret associated with total cost subject to several real-time constraints. A version of Particle Swarm Optimisation with Differential Evolution is proposed to tackle the resulting NP-hard problem. The model is tested with two other state-of the art meta-heuristics for small, medium, and large datasets subject to different procurement scenarios inspired from real time food grain operations in Indian context. Finally, the solution is evaluated with respect to total cost, model and solution robustness for all instances.     

Output feedback controller for polytopic systems exploiting the direct searching of the design space

This paper deals with the problem of designing a robust static output feedback controller for polytopic systems. The current research that tackled this problem is mainly based on LMI method, which is conservative by nature. In this paper, a novel approach is proposed, which considers the design space of the controller parameters and iteratively partitions the space to small simplexes. Then, by assessing the stability in each simplex, the solution space for design parameters is directly determined. It has been theoretically proved that, if there exists a feasible solution in the design space, the algorithm can find it. To validate the result of the proposed approach, comparative simulation examples are given to illustrate the performance of the design methodology as compared to those of previous approaches.     

Robust predictive extended state observer for a class of nonlinear systems with time-varying input delay

ABSTRACT

This paper deals with asymptotic stabilisation of a class of nonlinear input-delayed systems via dynamic output feedback in the presence of disturbances. The proposed strategy has the structure of an observer-based control law, in which the observer estimates and predicts both the plant state and the external disturbance. A nominal delay value is assumed to be known and stability conditions in terms of linear matrix inequalities are derived for fast-varying delay uncertainties. Asymptotic stability is achieved if the disturbance or the time delay is constant. The controller design problem is also addressed and a numerical example with an unstable system is provided to illustrate the usefulness of the proposed strategy.     

Simultaneous process optimization and heat integration based on rigorous process simulations

This paper introduces a simultaneous process optimization and heat integration approach, which can be used directly with the rigorous models in process simulators. In this approach, the overall process is optimized utilizing external derivative-free optimizers, which interact directly with the process simulation. The heat integration subproblem is formulated as an LP model and solved simultaneously during optimization of the flowsheet to update the minimum utility and heat exchanger area targets. A piecewise linear approximation for the composite curve is applied to obtain more accurate heat integration results. This paper describes the application of this simultaneous approach for three cases: a recycle process, a separation process and a power plant with carbon capture. Case study results indicate that this simultaneous approach is relatively easy to implement and achieves higher profit and lower operating cost and, in the case of the power plant example, higher net efficiency than the sequential approach.     

Impact of shape representation schemes used in discrete element modelling of particle packing

In different computer models, shape is represented using different methodologies, to varying degrees of precision. This paper examines two approaches to shape representation, and their effects on accuracy in the context of cylindrical particle packing. Two discrete element method (DEM) based software packages are used. A X-ray CT scan of a packed bed provides the experimental measurements for comparison. Eight sphere-composite representations of the same cylindrical pellet were tested. Two of these gave results that quantitatively follow experimental measurements. A range of factors that in theory could affect accuracy of the simulation results are examined, including edge roundedness, surface roughness and restitutional behaviour as a function of sphere-composite representations. The conclusion is that, for packing at least, matching the object's overall shape and dimensions is not enough. Only when a high enough resolution is applied to corners and edges, could the sphere-composite approach possibly match the experimental data quantitatively.     

A semicontinuous approach for heterogeneous azeotropic distillation processes

The separation of azeotropes has substantial energy and investment costs, and the available methods require high capital costs for reconstruction of process plants. As an alternative, a semicontinuous configuration that utilizes an existing plant with minor modifications has been explored. In this paper, a semicontinuous, heterogeneous azeotropic distillation process is proposed and acetic acid dehydration process is used as a case study. To carry out the simulation work, Aspen HYSYS^® simulation software is used along with MATLAB^® and an interface program to handle the mode-transition of the semicontinuous process. Sensitivity analyses on operating parameters are performed to identify the process limits. Comparisons are made to conventional heterogeneous azeotropic distillation, and dividing-wall distillation column on the annual cost. The results proved that the semicontinuous system is the best setup in terms of total annual costs and energy requirements.