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Seeking for advanced catalytic systems for the CO2 methanation reaction, the use of Ni supported catalysts over redox materials is often proposed. Profiting the superior redox properties described for layered perovskite systems, this work has investigated a series Ni supported YMn1-xAlxO3 (x = 0, 0.2, 0.5, 0.8, 1) perovskite catalysts.
The obtained results evidenced the impact of the support nature on the systems redox properties and Ni-support interactions. Within the catalysts series, the greater methanation rates displayed by Ni/YMn0.5Al0.5O3 catalyst (0.748 mmolCO2,conv.s–1 gNi –1 at 400 ◦C and 60 L/gh) were associated to the interplay between the support redox
properties and superior Ni dispersion. The improved redox behavior attained through the Al-incorporation (up to x = 0.5) was associated to the layered perovskite structures which, being distorted and constituted by smaller crystal sizes, facilitated the behavior of Mn redox couples as surface species readily interconverted. Exhibiting
catalytic performances comparable to precious metals based catalysts, this work proposes the Ni/YMn0.5Al0.5O3 catalyst as an effective system for the CO2 methanation reaction.
CO2 methanation: on the modeling of reacting laminar flows in structured Ni/MgAl2O4 catalysts
(2022)
CO2 methanation: on the modeling of reacting laminar flows in structured Ni/MgAl2O4 catalysts
(2022)
State-of-the-art approaches for membrane cleaning scheduling have focused on the Mixed-Integer Nonlinear Programming (MINLP) formulation so far, a strategy leading to a combinatorial problem that does not capture accurately the dynamic behaviour of the system. In this work, the Reverse Osmosis (RO) cleaning scheduling problem is solved using a novel approach based on the Multistage Integer Nonlinear Optimal Control Problem (MSINOCP) formulation. The approach produces an automated solution for the membrane cleaning scheduling, which also obviates the need for any form of combinatorial optimisation. Two different simulations, for 26 and 52 periods of operation (each period with a duration of one week), are carried out to illustrate the application of the proposed framework and the total cost is 1.17 and 2.48 10⁷ €, respectively. The RO network configuration considers 2 stages, each with 3 individual RO modules. The results show evidently that the new proposed solution framework can solve successfully this type of problems, even for large scale configurations, long time horizons and arbitrary realistic complexity of the underlying dynamic model of the RO process considered.
Various pests which diminish the quality of the fruit have a big influence on the organic banana production in the Piura region of Peru (and not only) and prevent it from being sold on the international market. In this study, a framework for facilitating the prediction of the pest incidence in organic banana crops is developed. To achieve this, a data acquisition system with smart sensors is implemented to monitor the meteorological variables that influence the growth of the pests. The proposed framework is utilised for the assessment of various mathematical representations of the pest incidence. These models are adapted from population growth functions and built in such way as to predict the behaviour of the insects at non-regular time intervals. A hybrid approach, combining mechanistic and data-based methods is utilised for the development of the models. Both linear and nonlinear dynamic relationships with the temperature are assumed. The results show that nonlinear model representations have greater accuracy (a fit index of more than 70%), which provides a basis for improving pest management actions on the organic banana farms.
In this contribution, a dynamic first principles model of an existing 3.01 MW natural gas fired water bath heater (WBH) in operation at the Takoradi Distribution Station (TDS) in Ghana is developed primarily to predict the outlet temperature of the natural gas stream being heated. The model is intended to be applied during operations to provide useful data to optimise material and energy consumption, as well as minimise CO2 emissions. Due to the low thermal efficiencies of WBHs, even small improvements in efficiency can result in significant savings. The firetube and process coils are both modelled as onedimensional (1D) thin-walled tubes and the entire model incorporates mass and energy conservation equations, heat transfer rate relations and rigorous thermodynamic p-V-T relations. In contrast to what commonly exists in literature, this model accurately estimates the enthalpy change of the natural gas stream being heated by accounting for its enthalpy departure correction term due to pressure, in addition to the ideal gas heat capacity relation which is a function of only temperature. The coupled ordinary differential and algebraic equations are implemented using gPROMS® ModelBuilder® V4.2.0, a commercial modelling and simulation software. Verification of the model results showed good agreement between the model predictions and actual on field measurements. With excess air at 15%, the simulation results closely approximate measured data with an absolute error of about 0.31 %. More importantly, the results show that significant savings of up to 30% per annum can be made through optimal operation of the water bath heater.
A first contribution of this paper is an overview of the research efforts and contributions over several decades in the area of scheduling maintenance optimization for decaying performance dynamic processes. Following breakthrough ideas and implementation in the area of heat exchanger networks for optimal scheduling of cleaning actions subject to exchanger surface fouling, these concepts were transferred successfully to the area of scheduling catalyst replacement actions in catalytic reactor networks. This necessary overview leads to the main, second contribution aimed with this work: its application to restorative maintenance scheduling in the area of RON regeneration actions planning, as well as point to new areas where this approach can be fruitfully applied to and extended into in the near future – particularly enhancing model descriptions that include general types of planning uncertainty. The effectiveness and efficacy of the approach is demonstrated computationally in this work.
Spray drying is a basic unit operation in several process industries such as food, pharmaceutical, ceramic, and others. In this work, a Eulerian-Lagrangian three-phase simulation is presented to study the drying process of barbotine slurry droplets for the production of ceramic tiles. To this end, the simulated velocity field produced by a spray nozzle located at the Institute of Ceramic Technology in Castelló (Spain) is benchmarked against measurements obtained by means of laser Doppler anemometry in order to validate the numerical model. Also, the droplet size distribution generated by the nozzle is obtained at operating conditions by means of laser diffraction and the data obtained are compared qualitatively to those found in the literature. The characteristic Rosin-Rammler droplet size from the distribution is introduced thereafter in the three-phase simulation to analyse the drying kinetics of individual droplets. The model predicts the theoretical linear evolution of the square diameter (D²-law), and the temperature and mass exchange with the environment. The proposed model is intended to support the design and optimization of industrial spray dryers.
Nature has provided some of the most ingenious and elegant solutions to complex problems over millions of years of refining through evolution. The adaptation of Nature´s solutions to engineering problems is a recent trend which has opened opportunities for improvement in many areas ranging from Architecture to Chemical Engineering. In particular, the use of fractal geometries on heat exchangers is a recent design trend. Recent investigations highlight the benefit of implementing fractal-based geometries on the tube side of shell and tube heat exchangers. A complete evaluation of such devices by assessing the performance of the shell side has not been undertaken, though. Here, we present a systematic numerical assessment of the shell side of a tree-like shaped heat exchanger. Key performance parameters, i.e. temperature change, pressure drop and coefficient of performance, are obtained and compared to those of a straight tube, in order to fully understand the potential of the application of fractal-based shapes to the design of heat exchangers.
Traditional food supply chains are often centralised and global in nature. Moreover they require a large amount of resource which is an issue in a time with increasing need for more sustainable food supply chains. A solution is to use localised food supply chains, an option theorised to be more sustainable, yet not proven. Therefore, this paper compares the two systems to investigate which one is more environmentally friendly, cost efficient and resilient to disruption risks. This comparison between the two types of supply chains, is performed using MILP models for an ice cream supply chain for the whole of England over the period of a year. The results obtained from the models show that the localised model performs best environmentally and economically, whilst the traditional, centralised supply chain performs best for resilience.