Dealing with uncertainties: Sensitivity analysis of vacuum gas oil hydrotreatment

The so-called lumped reaction networks are extensively used to model complex processes such as hydrocracking. Despite this, studies on the further applicability of these networks during a reactor scale-up and design are notably sparser. The application of a lumped reaction network to solve such problems requires dealing with a wide range of uncertainties, for example, reaction kinetics, the heat of reaction, or pseudocomponent densities. In this work, the design procedure of a trickle-bed hydrocracking reactor with multiple catalyst layers is carried out using a few-step lumped reaction network. The uncertain parameters are considered in a stochastic objective function using uniform probability distributions. Moreover, we extend this approach to catalyst deactivation as well, pointing out that this phenomenon can also be interpreted as a form of uncertainty, instead of estimating the activity using more complex and resource-intensive dynamic simulations. The results obtained by the application of the stochastic design method are compared to the performance of the conventional model-based design as well. An improved test of robustness is applied to evaluate the performance of the reactors under various uncertain conditions. The results indicate that the application of the suggested methods can simplify the structure of the hydrocracking reactor. For example, a fewer number of catalyst layers will be required while retaining the robustness of the reactor at the same time.

Section: ■ Introductionmentioning

confidence: 99%

Uncertainties of Lumped Reaction Networks in Reactor Design

Till

Chován

Varga

2020

“…Duong et al 20 studied the uncertainty quantification (UQ) and SA of chemical processes using the standard polynomial chaos method for systems with a small number of random inputs. Using an efficient-to-evaluate surrogate model, Celse et al 21 investigated the influence of each input on the construction of the model of the hydrodesulfurization/hydrodenitrogenation reaction in a vacuum gas oil hydrotreatment. Duong et al 22 and Minh et al 23 recently developed a two-stage approach using a compressive polynomial chaos method to overcome the computational limitation in a system with a moderate/large number of uncertain parameters.…”

Section: Introductionmentioning

confidence: 99%

Global Sensitivity Analysis and Uncertainty Quantification of Crude Distillation Unit Using Surrogate Model Based on Gaussian Process Regression

Minh

Duong

Lee

2018

This study presents a global sensitivity analysis to simplify a surrogate-model-based uncertainty quantification of a crude distillation unit with a large number of uncertainties. To overcome the computational limitation of a conventional surrogate model-based approach where the number of simulations required grows exponentially as the input dimension increases, a novel two-stage approach was proposed in this study: in the first stage, a multiplicative dimensional reduction method is applied to identify factors that exert the highest influence on the model outputs. In the second stage, the Gaussian process regression is exploited for uncertainty quantification from the simplified model derived in the first stage. As a result, the computational efforts for uncertainty quantification were significantly reduced (approximately more than 95%) compared to the conventional Quasi Monte Carlo, while the predicted density functions by the proposed method closely matched with those from the Quasi Monte Carlo. The proposed two-stage approach was executed for sensitivity analysis and uncertainty quantification of a crude distillation unit by an interface between MATLAB and HYSYS. The economic revenue and the operating cost per unit of crude oil processed were selected as the output of interests for the crude distillation unit. The global sensitivity analysis result showed that the flow rates of crude oil and naphtha products are critical for both the economic revenue and the operating cost.

“…Vacuum gas oil (VGO), one of the atmospheric vacuum distillation cuts of heavy crude oil, has a high boiling point ranging from 370 to 510 °C, which is of inherently poor quality because of the high sulfur and nitrogen contents, high molecular weight, and low API gravity. , To satisfy the growing demand of environment-friendly and high-quality transportation fuels and chemicals, especially for the rapid growth of developing Asian markets, upgrading is an essential step for the VGO conversion . Previously, there are three main upgrading technologies, i.e., hydrocracking, thermal cracking, and catalytic cracking.…”

Section: Introductionmentioning

confidence: 99%

Optimization of a Pilot Hydrocracking Unit To Improve the Yield and Quality of Jet Fuel Together with Heavy Naphtha and Tail Oil

Peng

Cao

et al. 2018

Hydrocracking of vacuum gas oil (VGO) is a commonly used process to produce more high-quality transportation fuels and chemicals. In this work, effects of four different operation modes, i.e., SSOTP, FRTHT, FRTHC, and PRTHT, with different recycling modes of tail oil are comparatively studied on the performance of VGO hydrocracking. The FRTHT and FRTHC give rise to a higher yield and/or quality of jet fuel, heavy naphtha, and tail oil compared with that of the other two modes. Moreover, effects of the distillation−cutting scheme are also studied to further increase the yield and quality of jet fuel. It is found that all four of the operation modes show a much higher yield but a slightly higher smoke point for the jet fuel. The insights revealed here could shed new light on the optimization of VGO hydrocracking to produce more targeted products.