Energy efficient control and optimisation techniques for distillation processes

PhD ThesisDistillation unit is one of the most energy intensive processes and is among the major CO2 emitter in the chemical and petrochemical industries. In the quest to reduce the energy consumption and hence the environmental implications of unutilised energy, there is a strong motivation for energy saving procedures for conventional columns. Several attempts have been made to redesign and heat integrate distillation column with the aim of reducing the energy consumption of the column. Most of these attempts often involve additional capital costs in implementing. Also a number of works on applying the second law of thermodynamics to distillation column are focused on quantifying the efficiency of the column. This research aims at developing techniques of increasing the energy efficiency of the distillation column with the application of second law using the tools of advanced control and optimisation. Rigorous model from the fundamental equations and data driven models using Artificial neural network (ANN) and numerical methods (PLS, PCR, MLR) of a number of distillation columns are developed. The data for the data driven models are generated from HYSYS simulation. This research presents techniques for selecting energy efficient control structure for distillation processes. Relative gain array (RGA) and relative exergy array (REA ) were used in the selection of appropriate distillation control structures. The viability of the selected control scheme in the steady state is further validated by the dynamic simulation in responses to various process disturbances and operating condition changes. The technique is demonstrated on two binary distillation systems. In addition, presented in this thesis is optimisation procedures based on second law analysis aimed at minimising the inefficiencies of the columns without compromising the qualities of the products. ANN and Bootstrap aggregated neural network (BANN) models of exergy efficiency were developed. BANN enhances model prediction accuracy and also provides model prediction confidence bounds. The objective of the optimisation is to maximise the exergy efficiency of the column. To improve the reliability of the optimisation strategy, a modified objective function incorporating model prediction confidence bounds was presented. Multiobjective optimisation was also explored. Product quality constraints introduce a measure of penalization on the optimisation result to give as close as possible to what obtains in reality. The optimisation strategies developed were applied to binary systems, multicomponents system, and crude distillation system. The crude distillation system was fully explored with emphasis on the preflash unit, atmospheric distillation system (ADU) and vacuum distillation system (VDU). This study shows that BANN models result in greater model accuracy and more robust models. The proposed ii techniques also significantly improve the second law efficiency of the system with an additional economic advantage. The method can aid in the operation and design of energy efficient column.Commonwealth scholarship commissio

Recikliranje ekspandiranog polistirena kao učinkovitog adsorbensa naftalena iz vodene otopine

Batch adsorption process factors [contact time (20–150 min), adsorbent dosage (0.5–1.5 g), adsorbate concentration (5–30 mg l–1), and agitation rate (100–250 rpm)] were optimised based on D-optimal Design under the Response Surface Methodology (RSM) of the Design-Expert Software (7.6.8) for the removal of naphthalene from aqueous solution using adsorbent developed from Acetylated Waste Expanded Polystyrene (AWEPs). The maximum adsorption capacity (5.6608 mg g–1) achieved was well fitted to Dubinin-Radushkevich Isotherm (R2 = 0.9949). The SSE (< 0.05) and ARE (< 4.0 %) indicated pseudo-second-order as the most suitable model. This research has demonstrated the effectiveness of the WEPs for the removal of naphthalene from the aqueous solution. This work is licensed under a Creative Commons Attribution 4.0 International License.Šaržni faktori procesa adsorpcije [vrijeme kontakta (20 – 150 min), doziranje adsorbenta (0,5 – 1,5 g), koncentracija adsorbata (5–30 mg l–1) i brzina miješanja (100–250 min–1)] optimizirani su na temelju D-optimalnog dizajna primjenom metodologije odzivne površine (RSM) programa Design-Expert (7.6.8) za uklanjanje naftalena iz vodene otopine pomoću adsorbenta razvijenog iz acetiliranog otpadnog ekspandiranog polistirena (AWEP). Ostvareni maksimalni adsorpcijski kapacitet (5,6608 mg g–1) dobro je prilagođen izotermi Dubinin-Radushkevich (R2 = 0,9949). SSE (< 0,05) i ARE (< 4,0 %) označili su pseudo-drugi red kao najprikladniji model. Ovo istraživanje pokazalo je učinkovitost WEP-a za uklanjanje naftalena iz vodene otopine. Ovo djelo je dano na korištenje pod licencom Creative Commons Imenovanje 4.0 međunarodna

Thermodynamic assessment of crude distillation units: case studies of Nigeria refineries

This paper presents the results of thermodynamic analysis of the crude distillation units of two refineries in Nigeria. The analysis was intended to assess the thermodynamic efficiencies of the refineries and proffer methods of improving the efficiencies. Presented results show the atmospheric distillation units of the refineries have 33.3% and 31.6% exergetic efficiencies and 86.5% and 74.6% energetic efficiencies, respectively. Modifications of the operating and feed conditions of the refineries resulted in increased exergetic efficiencies for as much as 62.3% and 38.7% for the refineries. Thermodynamic analysis of the refineries can bring about efficiency improvement and effectiveness of the refineries

Arduino microcontroller based real-time monitoring of haemodialysis process for patients with kidney disease

The efficient and precise monitoring of the haemodialysis process is critical for the well-being of patients suffering from end-stage renal disease (ESRD). In this work, a comprehensive study on the utilization of Arduino microcontroller-based systems for real-time monitoring, data acquisition and control of the haemodialysis process is presented. Arduino instrumentation unit was developed for an in vitro Haemodialysis (HD) system using Atmega 328 and Arduino nano microcontrollers. Haemodialysis process was conducted using in vitro haemodialysis system. Temperature probes (model DS18B20), conductivity probes (model EC-PPM-TDS) and weight sensor (load cell type HX711, 10 kg max stain gauge type) were used for real-time measuring and monitoring blood and dialysate temperatures, conductivities, and blood weight respectively. Simulink interface embedded in MATLAB software R.2019 was used as microcontroller software interface. In vitro HD result of the real-time monitoring indicated that initial and final measurement for blood temperatures gave 32.8 – 36.5 °C at set dialysate temperature 37 °C respectively, blood and dialysate conductivity 2 - 3.5 mS/cm and intradialytic blood weight 187.5 g – 147.5 g. This paper offers valuable insights into the implementation of Arduino microcontrollers for real-time monitoring of the haemodialysis process, with a strong emphasis on patient safety, data generation and data security. The research presented contributes to the advancement of technology in the field of nephrology and has the potential to significantly impact the quality of life for ESRD patients undergoing haemodialysis