Alternative sweetener from curculigo fruits

This study gives an overview on the advantages of Curculigo Latifolia as an alternative sweetener and a health product. The purpose of this research is to provide another option to the people who suffer from diabetes. In this research, Curculigo Latifolia was chosen, due to its unique properties and widely known species in Malaysia. In order to obtain the sweet protein from the fruit, it must go through a couple of procedures. First we harvested the fruits from the Curculigo trees that grow wildly in the garden. Next, the Curculigo fruits were dried in the oven at 50 0C for 3 days. Finally, the dried fruits were blended in order to get a fine powder. Curculin is a sweet protein with a taste-modifying activity of converting sourness to sweetness. The curculin content from the sample shown are directly proportional to the mass of the Curculigo fine powder. While the FTIR result shows that the sample spectrum at peak 1634 cm–1 contains secondary amines. At peak 3307 cm–1 contains alkynes

Bilevel optimisation with embedded neural networks: Application to scheduling and control integration

Scheduling problems requires to explicitly account for control considerations in their optimisation. The literature proposes two traditional ways to solve this integrated problem: hierarchical and monolithic. The monolithic approach ignores the control level's objective and incorporates it as a constraint into the upper level at the cost of suboptimality. The hierarchical approach requires solving a mathematically complex bilevel problem with the scheduling acting as the leader and control as the follower. The linking variables between both levels belong to a small subset of scheduling and control decision variables. For this subset of variables, data-driven surrogate models have been used to learn follower responses to different leader decisions. In this work, we propose to use ReLU neural networks for the control level. Consequently, the bilevel problem is collapsed into a single-level MILP that is still able to account for the control level's objective. This single-level MILP reformulation is compared with the monolithic approach and benchmarked against embedding a nonlinear expression of the neural networks into the optimisation. Moreover, a neural network is used to predict control level feasibility. The case studies involve batch reactor and sequential batch process scheduling problems. The proposed methodology finds optimal solutions while largely outperforming both approaches in terms of computational time. Additionally, due to well-developed MILP solvers, adding ReLU neural networks in a MILP form marginally impacts the computational time. The solution's error due to prediction accuracy is correlated with the neural network training error. Overall, we expose how - by using an existing big-M reformulation and being careful about integrating machine learning and optimisation pipelines - we can more efficiently solve the bilevel scheduling-control problem with high accuracy.Comment: 18 page

Computer-aided HAZOP of batch processes

The modern batch chemical processing plants have a tendency of increasing technological complexity and flexibility which make it difficult to control the occurrence of accidents. Social and legal pressures have increased the demands for verifying the safety of chemical plants during their design and operation. Complete identification and accurate assessment of the hazard potential in the early design stages is therefore very important so that preventative or protective measures can be integrated into future design without adversely affecting processing and control complexity or capital and operational costs. Hazard and Operability Study (HAZOP) is a method of systematically identifying every conceivable process deviation, its abnormal causes and adverse hazardous consequences in the chemical plants. [Continues.

Process Monitoring and Data Mining with Chemical Process Historical Databases

Modern chemical plants have distributed control systems (DCS) that handle normal operations and quality control. However, the DCS cannot compensate for fault events such as fouling or equipment failures. When faults occur, human operators must rapidly assess the situation, determine causes, and take corrective action, a challenging task further complicated by the sheer number of sensors. This information overload as well as measurement noise can hide information critical to diagnosing and fixing faults. Process monitoring algorithms can highlight key trends in data and detect faults faster, reducing or even preventing the damage that faults can cause. This research improves tools for process monitoring on different chemical processes. Previously successful monitoring methods based on statistics can fail on non-linear processes and processes with multiple operating states. To address these challenges, we develop a process monitoring technique based on multiple self-organizing maps (MSOM) and apply it in industrial case studies including a simulated plant and a batch reactor. We also use standard SOM to detect a novel event in a separation tower and produce contribution plots which help isolate the causes of the event. Another key challenge to any engineer designing a process monitoring system is that implementing most algorithms requires data organized into “normal” and “faulty”; however, data from faulty operations can be difficult to locate in databases storing months or years of operations. To assist in identifying faulty data, we apply data mining algorithms from computer science and compare how they cluster chemical process data from normal and faulty conditions. We identify several techniques which successfully duplicated normal and faulty labels from expert knowledge and introduce a process data mining software tool to make analysis simpler for practitioners. The research in this dissertation enhances chemical process monitoring tasks. MSOM-based process monitoring improves upon standard process monitoring algorithms in fault identification and diagnosis tasks. The data mining research reduces a crucial barrier to the implementation of monitoring algorithms. The enhanced monitoring introduced can help engineers develop effective and scalable process monitoring systems to improve plant safety and reduce losses from fault events

A novel qualitative prospective methodology to assess human error during accident sequences

Numerous theoretical models and techniques to assess human error were developed since the 60's. Most of these models were developed for the nuclear, military, and aviation sectors. These methods have the following weaknesses that limit their use in industry: the lack of analysis of underlying causal cognitive mechanisms, need of retrospective data for implementation, strong dependence on expert judgment, focus on a particular type of error, and/or analysis of operator behaviour and decision-making without considering the role of the system in such decisions. The purpose of the present research is to develop a qualitative prospective methodology that does not depend exclusively on retrospective information, that does not require expert judgment for implementation and that allows predicting potential sequences of accidents before they occur. It has been proposed for new (or existent) small and medium- scale facilities, whose processes are simple. To the best of our knowledge, a methodology that meets these requirements has not been reported in literature thus far. The methodology proposed in this study was applied to the methanol storage area of a biodiesel facility. It could predict potential sequences of accidents, through the analysis of information provided by different system devices and the study of the possible deviations of operators in decision-making. It also enabled the identification of the shortcomings in the human-machine interface and proposed an optimization of the current configuration.Fil: Calvo Olivares, Romina Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Cuyo. Facultad de Ingenieria. Instituto de Capacitación Especial y Desarrollo de Ingeniería Asistida por Computadora; ArgentinaFil: Rivera, Selva Soledad. Universidad Nacional de Cuyo. Facultad de Ingenieria. Instituto de Capacitación Especial y Desarrollo de Ingeniería Asistida por Computadora; ArgentinaFil: Núñez Mc Leod, Jorge Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Cuyo. Facultad de Ingenieria. Instituto de Capacitación Especial y Desarrollo de Ingeniería Asistida por Computadora; Argentin

Modelling, safety verification and design of discrete/continuous processing systems.

Imperial Users onl

A feasibility study for reset control of an industrial batch reactor

Includes abstract.Includes bibliographical references (leaves 128-133).A feasibility study for the application of reset control to the temperature control loop of a pressurized exothermic batch leach reactor in the hydrometallurgical Precious Group Metals (PGM) industry is carried out. Keywords: Reset control; Clegg integrator; initial states; industrial batch reactor; temperature control; exothermic reactions; multiple reactions; dissolve; leach; hydrometallurgy; platinum; Precious Group Metals (PGMs)

The development of a weighted directed graph model for dynamic systems and application of Dijkstra’s algorithm to solve optimal control problems.

Master of Science (Chemical Engineering). University of KwaZulu-Natal. Durban, 2017.Optimal control problems are frequently encountered in chemical engineering process control applications as a result of the drive for more regulatory compliant, efficient and economical operation of chemical processes. Despite the significant advancements that have been made in Optimal Control Theory and the development of methods to solve this class of optimization problems, limitations in their applicability to non-linear systems inherent in chemical process unit operations still remains a challenge, particularly in determining a globally optimal solution and solutions to systems that contain state constraints. The objective of this thesis was to develop a method for modelling a chemical process based dynamic system as a graph so that an optimal control problem based on the system can be solved as a shortest path graph search problem by applying Dijkstra’s Algorithm. Dijkstra’s algorithm was selected as it is proven to be a robust and global optimal solution based algorithm for solving the shortest path graph search problem in various applications. In the developed approach, the chemical process dynamic system was modelled as a weighted directed graph and the continuous optimal control problem was reformulated as graph search problem by applying appropriate finite discretization and graph theoretic modelling techniques. The objective functional and constraints of an optimal control problem were successfully incorporated into the developed weighted directed graph model and the graph was optimized to represent the optimal transitions between the states of the dynamic system, resulting in an Optimal State Transition Graph (OST Graph). The optimal control solution for shifting the system from an initial state to every other achievable state for the dynamic system was determined by applying Dijkstra’s Algorithm to the OST Graph. The developed OST Graph-Dijkstra’s Algorithm optimal control solution approach successfully solved optimal control problems for a linear nuclear reactor system, a non-linear jacketed continuous stirred tank reactor system and a non-linear non-adiabatic batch reactor system. The optimal control solutions obtained by the developed approach were compared with solutions obtained by the variational calculus, Iterative Dynamic Programming and the globally optimal value-iteration based Dynamic Programming optimal control solution approaches. Results revealed that the developed OST Graph-Dijkstra’s Algorithm approach provided a 14.74% improvement in the optimality of the optimal control solution compared to the variational calculus solution approach, a 0.39% improvement compared to the Iterative Dynamic Programming approach and the exact same solution as the value–iteration Dynamic Programming approach. The computational runtimes for optimal control solutions determined by the OST Graph-Dijkstra’s Algorithm approach were 1 hr 58 min 33.19 s for the nuclear reactor system, 2 min 25.81s for the jacketed reactor system and 8.91s for the batch reactor system. It was concluded from this work that the proposed method is a promising approach for solving optimal control problems for chemical process-based dynamic systems

Development and validation of the HarsMeth NP methodology for the assessment of chemical reaction hazards.

L'objectiu d'aquest treball es centra en el desenvolupament, comprovació i millora d'una metodologia per l'assessorament del perill tèrmic de les reaccions químiques, orientada especialment a les petites i mitjanes empreses. La metodologia està basada en un sistema de llistes de comprovació per identificar els perills, així com en altres eines senzilles d'entendre per a personal no expert en seguretat. Els orígens del desenvolupament de la metodologia es basen en dos eines existents, HarsMeth i Check Cards for Runaway. S'han pres diferents enfocaments per tal d'aconseguir una metodologia d'assessorament fiable. En primer lloc s'ha verificat l'eficàcia d'ambdues metodologies en diferents empreses dedicades al desenvolupament de productes de química fina, per determinar els punts forts i els punts febles de cada una de elles, i per aprofitar els avantatges identificats per tal de crear una unica metodologia anomenada HarsMeth version 2. A continuació, s'ha provat aquesta versió exhaustivament en dos empreses químiques per tal de millorarla, detectant fallades i allargant les llistes de comprovació amb la finalitat de cobrir el màxim número possible de qüestions per l'assessorament. Altres activitats s'han centrat en el desenvolupament d'eines per a la determinació teòrica de entalpies de reacció i per la identificació de perills tèrmics en equips de procés. La versió final de la metodologia que s'ha desenvolupat, anomenada HarsMeth New Process, està estructurada per tal de realitzar l'assessorament seguint els passos lògics en el desenvolupament d'un procés químic, començant per el disseny de la reacció química en el laboratori, seguit per l'anàlisi de la estabilitat i compatibilitat dels reactius, l'anàlisi de la perillositat de la reacció, l'escalat del procés, i la determinació de les mesures de seguretat necessàries per implementar el procés a escala industrial en funció dels perills identificats anteriorment. Un altre estratègia seguida per millorar la metodologia ha estat analitzar els accidents químics inclosos en la base de dades MARS amb la finalitat de determinar lliçons per aprendre dels accidents, així com per identificar quins aspectes de la metodologia haurien ajudat a prevenir els accidents, i a posar de relleu quins aspectes de la seguretat quimica s'han de tenir especialment en compte a les indústries de procés.El objetivo de este trabajo se centra en el desarrollo, comprobación y mejora de una metodología para el asesoramiento del peligro térmico de las reacciones químicas, orientada especialmente a las pequeñas y medianas empresas. La metodología está basada en un sistema de listas de comprobación para identificar los peligros, así como en otras herramientas fáciles de entender para personal no experto en seguridad. Los orígenes del desarrollo de la metodología se basan en dos herramientas existentes, HarsMeth y Check Cards for Runaway. Se han seguido diferentes enfoques para llegar a una metodología de asesoramiento fiable. En primer lugar se ha verificado la eficacia de ambas metodologías en diferentes empresas dedicadas al desarrollo de productos de química fina, para determinar las fuerzas y debilidades de cada una de ellas, y para aprovechar las ventajas identificadas para crear una única metodología llamada HarsMeth version 2. A continuación, se ha probado esta versión exhaustivamente en dos empresas químicas para mejorarla, detectando fallos y expandiendo las listas de comprobación con el fin de cubrir el máximo número de cuestiones posibles en el asesoramiento. Otras actividades se han centrado en el desarrollo de herramientas para la determinación teórica de entalpías de reacción y para la identificación de peligros térmicos en equipos de proceso. La versión final de la metodología que se ha desarrollado, llamada HarsMeth New Process, está estructurada para realizar el asesoramiento siguiendo los pasos lógicos del desarrollo de un proceso químico, empezando por el diseño de la reacción química en el laboratorio, siguiendo con el análisis de la estabilidad y compatibilidad de los reactivos, el análisis de la peligrosidad de la reacción, el escalado del proceso y la determinación de medidas de seguridad necesarias para implementar el proceso a escala industrial en función de los peligros identificados anteriormente. Otra estrategia seguida para mejorar la metodología ha sido analizar los accidentes químicos incluidos en la base de datos MARS con el fin de determinar lecciones a aprender de los accidentes, así como identificar qué aspectos cubiertos por la metodología podrían haber ayudado a prevenir los accidentes, y a enfatizar qué aspectos de la seguridad química deben tener especialmente presentes las industrias de proceso.The aim of this work is focused on the development, testing and improvement of a methodology for the assessment of thermal hazards of chemical reactions, mainly oriented to be used at small and medium enterprises. The methodology consists on a checklist based system to identify thermal hazards, including tools easy to be followed by non experts in the field of safety. The origins of the development are two already existing tools known as HarsMeth and Check Cards for Runaway. Different approaches have been followed in order to come up with a reliable assessment tool. In the first place, the two mentioned methodologies were tested at different companies working on fine chemical production, which gave the possibility to determine strengths and weaknesses for both methodologies, and to profit from the identified strengths to combine them to create one single tool called HarsMeth version 2. Later, this version was thoroughly tested at two different companies to improve it, by detecting flaws and expanding the checklists in order to cover as many issues as possible in the assessment. Further work performed aimed at the development of tools for the theoretical estimation of reaction enthalpies and for the identification of thermal hazards in process equipment. A final version of the methodology was produced, called HarsMeth New Process, structured to perform the hazard assessment at every step followed in the development of a chemical process, starting from the design of the chemical reaction at the laboratory, followed by the study of stability and compatibility of the reactants involved, the bench scale analysis of the synthesis path chosen, the scale up of the process and the determination of the necessary safety measures for the implementation of the process at industrial scale in accordance with the hazards identified. Another strategy followed in order to improve the methodology has been to analyse the chemical accidents reported to the MARS database in order to establish lessons learned from such accidents, and to identify what topics of the methodology could have helped to prevent the accidents and to emphasize what aspects of chemical safety need to be taken into account by the process industries