Posted by Kashyap Vyas on January 24th, 2017
For more than a decade engineers used equations to evaluate engineering solutions to given problems, the one we fondly know as “analytical modeling”. However; the challenge was that underlying equations became more complex on attempting to model phenomena with multiple complexities, making it a barrier to solve equations with help of analytical mathematics. On the other hand computational fluid dynamics – CFD modeling is now used extensively to predict and simulate detailed three dimensional behaviors of complex and multi-component flows for a wide plethora of industrial application. This it seems has worked out be a befitting solution to the challenges of analytical modelling.
With its inception in the late 1960s, CFD made its impact wide felt only in the early years of 1980s, first in the aerospace industry and then adopted by the automotive industry. The capabilities of CFD to use differential equations for analyzing fluid flows such as heat transfer, chemical reactions, phase changes or pipework configurations, it seems has contributed at large to its popularity.
What was thought to be impossible a few years ago in the oil and gas industry, empowering engineers to conveniently tackle complex challenges and optimizing designs on time scale, is what CFD has made possible. The advent of computer technology, clubbed with high performance computing – HPC; have tremendously enhanced the amount of detailing that can be done and included in advanced models.
As against physical testing, CFD modeling knows no size or weight limits and if the model is complex, the limitation would be the availability of the computational power. And not only this, it has proved its prowess in developing equipments used in the field. Computer simulations done with help of CFD, before physical testing, enables to test the model for multiple variables, at very lost cost compared to physical testing; ultimately highlighting potential issues in the early stage of the project lifecycle.
Physical testing is mostly very complex. Also it is really expensive to measure and control parameters including fluid film thickness, droplet size and sand particle concentration. However; if you are using CFD to “measure”, it allows you with the convenience to use numerous parameters as you require. This also ensures that the data produced by CFD analysis is likely to be more accurate, precise and comprehensive as compared otherwise.
CFD analysis for oil plants and refineries helps in predicting performance and lifespan of various components. Maldistribution of flow results in costly to recover catalyst exhaustion. Optimizing the critical process of separation with help of CFD analysis is also been opted for. Enhancing the uptime to attain maximum profit is the main goal when operating a refinery, as unplanned downtime is likely to have daunting impact on operating margins; but can be eliminated or kept minimal by comprehensive CFD analysis of the refinery/plant.
CFD is used extensively to assess the temperature distribution across the mixing tanks, and the outcome is then coupled with Finite Element analysis – FEA, in order to predict the lifetime of the tank adhering to the conditions taken in consideration while modeling. Taking these results into consideration while deriving the maintenance schedules and can be changed even before the failure occurs. An oil and gas plant, if to be operated successfully, needs each component of the process to operate at optimum level.
Each and every component of the process needs to perform at optimum efficiency in order to operate a plant, successfully. Increasing demand of creating stranded gas reserves as a result of growing number of floating liquefied natural gas – FLNG projects in Africa and Southeast Asia, leading remote offshore locations, it has become imperative to pay due attention to safety aspects to such operating facilities. In such scenarios, CFD is used extensively to model the layout and spacing of vessels and equipments. This minimizes the risk of explosions, fire exposure and overpressure damage. And not only this, CFD is also used for performance predictions of proposed designs, for external as well as internal fluid flow.
Flare metering accuracy on both floating production storage and offloading vessels and refineries, needless to say the kind of importance that it carries; and CFD is used successfully for it. Till recent past, single path ultrasonic flow meters were used for flare metering, but because these are very sensitive to disturbances in the flow profile, often resulted in humongous metering errors. Positioning the flow meter in an ideal location is a big challenge, considering the physical limitations of a plant, making metering errors – unavoidable.
However; CFD proved to be a game changer. Today it is used extensively to compare the flow profile of the as installed case as compared to ideal installation, resulting in correction factor as the output applicable to the meter, enabling it to be used in the non-ideal location. The only drawback is that it can be executed conveniently for flare gas systems, but not applicable for custody transfer meters; owing to the degree of uncertainty.
Engineers capable of performing sophisticated conjugate simulations, taking into consideration a wider range of physical phenomena in a single simulation for replicating filed conditions in a better way, is all due to the advent of computers. This is a real leap in the condition that existed merely five years back. Previously, models used to comprise of a million cells in total, if compared to the situation today, where computational meshes are in tens of millions. This no doubt is a huge and futuristic step in enabling the oil and industry professionals to address challenges, the ones which were unthinkable. However; the drawback here is that the understanding of numerical methods and why they need to apply it to a particular challenge; is fading fast.
Increased use of modern software and computers with infinite computation abilities is a strong indication that the industry is getting over dependent on technology. Engineers are losing their ability to make engineering predictions, apart from what the technology suggests them to be an “appropriate solution”. The convenience of running simulations immediately, with minimal or no formal training, makes way for possibilities of masking the underlying complexities of the problem. It also means that the engineers will make efforts to handle challenges without comprehensive understanding of the overall issue.
The issue of numerical modeling getting more complex, making it all the more difficult to handle the sensitivity of the solution for numerical methods, boundary conditions, solution controls etc., stands as is. Would you want to have this kind of a grave engineering experience and not be confident of reaching out to an appropriate solution? No one would want to.
This makes it mandatory for CFD modelers to understand the physics that is solved by the software fundamentally, in order to reach out to accurate predictions. If this is followed religiously, and it is ensured that models are not utilized over and above the operational range; reduced modeling errors should not be a farfetched possibility.
Companies before reaching a conclusion to use the modeling approach for a real world application, should also be confident about the method that they are opting for, is appropriate. Upon ascertaining it, to add up to the confidence, reduce levels of error, physical test data can be used for model validation purpose. Inputs for the model chosen, are supposed to be accurate, or else the resultant solution to the challenge will be inaccurate. Also, if the model is validated correctly, there is always an assurance that the degree of error has taken in consideration acceptable safety margins, applicable while modeling and designing pipeline systems.
Of various ways, in which a CFD model can be validated; comparing it against analytical calculations that are simple, is one of them. It also can be cross-checked with help of multiple software and several modeling approaches. If validation results are more or less similar, the CFD model is believed to be reliable. No doubts about the fact that engineering skills and knowledge of the professional, with help of engineering judgement and experience, is and can be one of the measures to validate the CFD model – whether it is logical and roughly correct.
Though a lot of professionals find CFD to be complex, it can be used for a wide plethora of applications. It has the capability to increase the accuracy, reducing the time and money spent by companies on testing; as test matrix would be conducted numerically with need for a validation test, in order to streamline the testing phase. This may seem to be a distant possibility, the positive coordination and collaboration between numerical modeling and physical testing, is what engineers and engineering firms are counting on.
In absence of clear and traceable model validation, in no way a solution can be assessed to be accurate; making the inclusion of numerical modeling in some or other form – more than important.
About Author: Kashyap Vyas is an Engineer at Hi-Tech and holds a Master’s degree in Thermal Engineering with several research papers to his credit. He covers CAD and CAE topics for the engineering industry. His contributions are primarily focused on encouraging manufacturers and suppliers to adopt virtual product development tools to build efficient products with reduced time-to-market.
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