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The manufacturing sector is one of the biggest energy consumers. The iron and steel markets in China are growing very fast. Several studies have been performed to evaluate the Chinese steel sector in terms of energy savings and CO₂ emissions. The results of the studies showed that the major energy savings expected within 2020 and 2030 timeframe will be from industrial furnaces in steel mills. For the Swedish steel industry, it is important to be very efficient in order to remain competitive. The hot rolling process in the steel industry is a long process, where big slabs are heated in a furnace above the recrystallization temperature to roll the metal into a thin sheet and then the sheet is cooled at the Runout table using water. The amount of energy used during the process directly influences the price of the products. Moreover, the government policy on energy usage and CO₂ emissions, the competitive market and the water scarcity, demand an optimal process operation to reduce energy consumption and greenhouse gas emission. Computer simulation is the best and most convenient way to approximate real-world processes; therefore, there is a need to have a real-time online simulation tool for process optimisation, decision support and diagnostics in different industries.

Computational fluid dynamics (CFD) is a robust tool for simulating almost any kind of real-world process related to fluid flow, heat transfer and combustion. However, simulating real-world processes in real-time using CFD is very challenging due to the complexity involved in the physical phenomena studied. In this thesis, CFD simulations have been performed in small scale to understand the physics and perceive the complexity involved in the heating process of steel slabs and the cooling process of the steel sheets at hot rolling steel industries. The results from the simulations are successfully validated using experimental and theoretical results published in open literature. Past experience suggests using mesh-based commercial CFD solvers for simulating industrial processes, only if accurate and detail results are desired. However, the computational performance of these solvers shows limitations from a real-time perspective and indicates the need for alternative CFD methods and solvers. In the literature review performed as part of the first stage of this work, we have identified different alternative methods which can be used to perform CFD simulations in real-time or near real-time for large industrial processes. The thesis discusses the limitations of different types of CFD methods and points out the difficulties and challenges in utilising these methods for simulating large industrial processes. Our preliminary simulation work brings light towards the goal of multi-phase multi-physics real-time simulations.

Tillverkningsindustrin är en av de största energikonsumenterna.  Järn och stålindustrin i Kina växer väldigt fort. Flera studier har genomförts för att utvärdera den kinesiska stålindustrisektorn vad gäller energieffektivisering och utsläpp av CO₂. Resultaten av studierna visade att de stora energibesparingarna som kan genomföras mellan 2020 – 2030 kommer från industriella ugnar i stålverken. För den svenska stålindustrin är det viktigt att vara mycket effektiv för att bibehålla konkurrenskraft. Varmvalsningsprocessen i stålindustrin är en lång process, där stora skivor hettas upp i en ugn över den temperatur där materialet rekristalliseras och metallen valsas sedan i tunna skivor. Skivorna kyls sedan på utrullningsbordet med vatten. Energimängden som används under processen påverkar direkt priset på produkterna. Dessutom kräver stränga statliga bestämmelser, en konkurrenskraftig marknad och bristen på vatten optimala processförhållanden för att reducera energikonsumtionen och utsläppen av klimatgaser. Datasimulering är det bästa och mest pålitliga verktyget att approximera en verkliga processer. Det finns därför ett behov att ha ett online simuleringsverktyg för processoptimering, beslutsstöd och diagnostik i olika industrier.

CFD-simulering (Computational fluid dynamics) är ett robust simuleringsverktyg för nästan alla typer av verkliga processer relaterade till vätskeflöde, värmeöverföring och förbränning. Dock är simulering av verkliga processer med CFD mycket utmanande på grund av komplexiteten i de fysikaliska fenomenen som ska studeras.  I den här avhandlingen har CFD-simulering använts i liten skala för att förstå fysikaliska egenskaper och komplexiteten i värmningsprocesser av stålskivor och kylningsprocessen av de tunna stålplåtarna vid varmvalsningsprocessen i stålindustrin. Resultaten från simuleringarna är framgångsrikt validerade från experimentella och teoretiska resultat publicerade i litteraturen. Tidigare erfarenheter föreslår nätverksbaserade kommersiella CFD verktyg för att simulera industriella processer om korrekta och detaljerade resultat ska fås. Dock är prestandan för dessa verktyg begränsade ur ett verklighetsperspektiv och indikerar behovet av alternativa CFD-metoder och verktyg. Det första steget i detta arbete var att genomföra en litteraturgenomgång av tidigare studier. Vi identifierade då alternativa metoder som skulle kunna användas för att genomföra CFD-simulering i realtid och i nära realtid för stora industriella processer. Avhandlingen diskuterar begränsningar av olika CFD-metoder och synliggör svårigheter och utmaning i att utnyttja dessa metoder för att simulera stora industriella processer. Vårt preliminära simuleringsarbete är ett litet steg på vägen i målet att producera flerfasiga och multifysikaliska realtidssimuleringar.

Optimal process control can significantly enhance energy efficiency of heating and cooling processes in many industries. Process control systems typically rely on measurements and so called grey or black box models that are based mainly on empirical correlations, in which the transient characteristics and their influence on the control parameters are often ignored. A robust and reliable numerical technique, to solve fluid flow and heat transfer problems, such as computational fluid dynamics (CFD), which is capable of providing a detailed understanding of the multiple underlying physical phenomena, is a necessity for optimization, decision support and diagnostics of complex industrial systems. The thesis focuses on performing high-fidelity CFD simulations of a wide range of industrial applications to highlight and understand the complex nonlinear coupling between the fluid flow and heat transfer. The industrial applications studied in this thesis include cooling and heating processes in a hot rolling steel plant, electric motors, heat exchangers and sloshing inside a ship carrying liquefied natural gas. The goal is to identify the difficulties and challenges to be met when simulating these applications using different CFD tools and methods and to discuss the strengths and limitations of the different tools.

The mesh-based finite volume CFD solver ANSYS Fluent is employed to acquire detailed and accurate solutions of each application and to highlight challenges and limitations. The limitations of conventional mesh-based CFD tools are exposed when attempting to resolve the multiple space and time scales involved in large industrial processes. Therefore, a mesh-free particle method, smoothed particle hydrodynamics (SPH) is identified in this thesis as an alternative to overcome some of the observed limitations of the mesh-based solvers. SPH is introduced to simulate some of the selected cases to understand the challenges and highlight the limitations. The thesis also contributes to the development of SPH by implementing the energy equation into an open-source SPH flow solver to solve thermal problems. The thesis highlights the current state of different CFD approaches towards complex industrial applications and discusses the future development possibilities.

The overall observations, based on the industrial problems addressed in this thesis, can serve as decision tool for industries to select an appropriate numerical method or tool for solving problems within the presented context. The analysis and discussions also serve as a basis for further development and research to shed light on the use of CFD simulations for improved process control, optimization and diagnostics.