An artificial neural network model for prediction of quality characteristics of apples during convective dehydration

In this study, the effects of hot-air drying conditions on color, water holding capacity, and total phenolic content of dried apple were investigated using artificial neural network as an intelligent modeling system. After that, a genetic algorithm was used to optimize the drying conditions. Apples were dried at different temperatures (40, 60, and 80 °C) and at three air flow-rates (0.5, 1, and 1.5 m/s). Applying the leave-one-out cross validation methodology, simulated and experimental data were in good agreement presenting an error < 2.4 %. Quality index optimal values were found at 62.9 °C and 1.0 m/s using genetic algorithm.Centro de Investigación y Desarrollo en Criotecnología de AlimentosFacultad de Ingenierí

An artificial neural network model for prediction of quality characteristics of apples during convective dehydration

In this study, the effects of hot-air drying conditions on color, water holding capacity, and total phenolic content of dried apple were investigated using artificial neural network as an intelligent modeling system. After that, a genetic algorithm was used to optimize the drying conditions. Apples were dried at different temperatures (40, 60, and 80 °C) and at three air flow-rates (0.5, 1, and 1.5 m/s). Applying the leave-one-out cross validation methodology, simulated and experimental data were in good agreement presenting an error < 2.4 %. Quality index optimal values were found at 62.9 °C and 1.0 m/s using genetic algorithm.Centro de Investigación y Desarrollo en Criotecnología de AlimentosFacultad de Ingenierí

Designing the appearance of environmentally sustainable products

The study presented in this paper uses a mathematical model to measure the degree in which a product will be perceived as environmentally friendly from its physical attributes. A model based on genetic algorithms and neural networks was developed to predict the judgement of the users about environmental friendliness of different tables. Opinions of real users about a large set of tables were used to train the model. The results of the study suggest that, using this procedure in advanced stages of product design process, designers can determine the set of product's physical attributes that best convey the idea of environmentally sustainable to the customer. The analysis of the obtained model allows establishing how different product's attributes influence users' perception. From these results, the utilization of users' affective response models to design the appearance of environmentally sustainable products is discussed.Diego-Mas, JA.; Poveda Bautista, R.; Alcaide Marzal, J. (2016). Designing the appearance of environmentally sustainable products. Journal of Cleaner Production. 135(1):784-793. doi:10.1016/j.jclepro.2016.06.173S784793135

Model-based approach for the plant-wide economic control of fluid catalytic cracking unit

Fluid catalytic cracking (FCC) is one of the most important processes in the petroleum refining industry for the conversion of heavy gasoil to gasoline and diesel. Furthermore, valuable gases such as ethylene, propylene and isobutylene are produced. The performance of the FCC units plays a major role on the overall economics of refinery plants. Any improvement in operation or control of FCC units will result in dramatic economic benefits. Present studies are concerned with the general behaviour of the industrial FCC plant, and have dealt with the modelling of the FCC units, which are very useful in elucidating the main characteristics of these systems for better design, operation, and control. Traditional control theory is no longer suitable for the increasingly sophisticated operating conditions and product specifications of the FCC unit. Due to the large economic benefits, these trends make the process control more challenging. There is now strong demand for advanced control strategies with higher quality to meet the challenges imposed by the growing technological and market competition. According to these highlights, the thesis objectives were to develop a new mathematical model for the FCC process, which was used to study the dynamic behaviour of the process and to demonstrate the benefits of the advanced control (particularly Model Predictive Control based on the nonlinear process model) for the FCC unit. The model describes the seven main sections of the entire FCC unit: (1) the feed and preheating system, (2) reactor, (3) regenerator, (4) air blower, (5) wet gas compressor, (6) catalyst circulation lines and (7) main fractionators. The novelty of the developed model consists in that besides the complex dynamics of the reactorregenerator system, it includes the dynamic model of the fractionator, as well as a new five lump kinetic model for the riser, which incorporates the temperature effect on the reaction kinetics; hence, it is able to predict the final production rate of the main products (gasoline and diesel), and can be used to analyze the effect of changing process conditions on the product distribution. The FCC unit model has been developed incorporating the temperature effect on reactor kinetics reference construction and operation data from an industrial unit. The resulting global model of the FCC unit is described by a complex system of partial-differential-equations, which was solved by discretising the kinetic models in the riser and regenerator on a fixed grid along the height of the units, using finite differences. The resulting model is a high order DAE, with 942 ODEs (142 from material and energy balances and 800 resulting from the discretisation of the kinetic models). The model offers the possibility of investigating the way that advanced control strategies can be implemented, while also ensuring that the operation of the unit is environmentally safe. All the investigated disturbances showed considerable influence on the products composition. Taking into account the very high volume production of an industrial FCC unit, these disturbances can have a significant economic impact. The fresh feed coke formation factor is one of the most important disturbances analysed. It shows significant effect on the process variables. The objective regarding the control of the unit has to consider not only to improve productivity by increasing the reaction temperature, but also to assure that the operation of the unit is environmentally safe, by keeping the concentration of CO in the stack gas below a certain limit. The model was used to investigate different control input-output pairing using classical controllability analysis based on relative gain array (RGA). Several multi-loop control schemes were first investigated by implementing advanced PID control using anti-windup. A tuning approach for the simultaneous tuning of multiple interacting PID controllers was proposed using a genetic algorithm based nonlinear optimisation approach. Linear model predictive control (LMPC) was investigated as a potential multi-variate control scheme applicable for the FCCU, using classical square as well as novel non-square control structures. The analysis of the LMPC control performance highlighted that although the multivariate nature of the MPC approach using manipulated and controlled outputs which satisfy controllability criteria based on RGA analysis can enhance the control performance, by decreasing the coupling between the individual low level control loops operated by the higher level MPC. However the limitations of using the linear model in the MPC scheme were also highlighted and hence a nonlinear model based predictive control scheme was developed and evaluated.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Single users' affective responses models for product form design

This paper presents a neural network based approach to modeling consumers' affective responses for product form design. A theoretical framework for a single user's perception is developed. On the basis of this theoretical framework, a mathematical model which enables single users' responses to different products to be predicted was developed. The results obtained show that the mathematical models developed achieved highly accurate predictions. For the purpose of obtaining a global model various individual mathematical models were created, which were based on the opinions of users representing different groups of opinion. The results suggest that, under some conditions, the combined use of various models of individual users can perform as well as a single model generated on the basis of mean market responses.Diego-Mas, JA.; Alcaide Marzal, J. (2016). Single users' affective responses models for product form design. International Journal of Industrial Ergonomics. 53:102-114. doi:10.1016/j.ergon.2015.11.005S1021145

Prediction the individual component distillation curves of the blended feed using a hybrid GDM-PcLE method

A comprehensive knowledge of the properties and characterisations of the individual component in the blended feed is primary importance because different feedstock blending yields different products palate. Crude oil / condensate distillation unit optimization is an uphill task because unavailability of cheaper and reliable on line feed and product analyzers. Furthermore, laboratory analysis for feedstock characterization is very costly and time consuming. Alternatively, feed synthesis technique is used to reconcile the entire range of feed distillation curves by back blending the product streams from the actual column operation. The TBP and SG correlation are widely been used to estimate other bulk properties because they give the most accurate results. Due to highly nonlinear behaviour, methods like linear regression, non linear regression and rigorous models are adopted to predict TBP and SG distillation curves. The latter could give better accuracy results, but it is more complex, lengthy and costly to be implemented. In addition, the rigorous model commercially available such as PetrosimTM and Hysis 3.1TM are only being used to predict blended feed distillation curves, not for the individual component. Thus, a hybrid approach is proposed to overcome the deficiency of current methods and practices. The proposed method integrates the most versatile General Distribution Model (GDM) with a Pseudo-component Linear Equation (PcLE) method to predict the entire range individual component TBP and SG distillation curves of the blended feed from the readily available plant data, which are routinely taken by refiners. The predicted results given by hybrid GDM-PcLE model are almost agreeable with the lab results. A case study using the proposed short cut feed synthesis procedure and hybrid GDM-PcLE model showed additional 5% Naphtha yield can be achieved by changing the current feed blending ratio and product cut points. The accuracy of the predicting results can be improved if the distillates samples are to be carried out simultaneously and the flow meters are calibrated and corrected the measurements to density and temperature of the measuring devices. Since PcLE method is simple and open application, it can be easily integrated with iCONTM to enhance its application predicting the pure component TBP and other distillation curves from blended feed

PSecurity Specification Language for Distributed Health Information System (DiHIS)

The introduction of policy based management which to manage distributed, complex and numerous systems is widely accepted and used in various sectors. The policy creators create policies that suit best for their operations and management. Since there are numerous of policies, this research focuses on the security policies only which are appointed to the distributed system of health information system. In order to implement the security policies, we need a language that can represent the security policies for distributed health information system completely. From the literature review conducted, there are numerous of security languages have been introduced since two decades ago. Those languages carry their own approaches representing the security policy and some of them do not support the characteristics of distributed system. There is no security language to implement the security policy for distributed health information system. This thesis introduces and initiates a security language to implement security policies in distributed health information system called DiHIS. Adding to that, there are three existing security languages used for discussion and comparison with the proposed DiHIS security language. They are ASL, LaSCO and Ponder. DiHIS security language has shown that it is able to represent the Security Policy Model for Clinical Information System completely compares to those three security languages. This language also has an added value when it covers the Need To Know Policy which other security languages do not. Need To Know Policy is one of the crucial issues in the health sector. DiHIS security language has also been tested with the application domain in health information system. The strength of the language can be seen with the ability of DiHIS to represent the security policies in various connections between various organizations involved in distributed health information system