Luis Rojas-Solórzano

EULERIAN-EULERIAN MODELING OF DISPERSE TWO-PHASE FLOW IN A GAS-LIQUID CYLINDRICAL CYCLONE

This work presents a three-dimensional computational fluid dynamics (CFD) study of a two-phase flow field in a gas-liquid cylindrical cyclone (GLCC) using CFX4.3 ™, a commercial code based on the finite volume method. The numerical analysis was made for air-water mixtures at near atmospheric conditions, while both liquid and gas flow rates were changed. The two-phase flow behavior is modeled using an Eulerian-Eulerian approach, considering both phases as an interpenetrating continuum. This method computed the inter-phase phenomena by including a source term in the momentum equation to consider the drag between the liquid and gas phases. The gas phase is modeled as a bimodal bubble size distribution to allow for the presence of free- and entrapment gas, simultaneously. The results (free surface shape and liquid angular velocity) show a reasonable match with experimental data. The CFD technique here proposed demonstrates to satisfactorily reproduce angular velocities of the phases and their spatial distribution inside the GLCC. Computed results also proved to be useful in forecasting bubble and droplet trajectories, from which gas carry under (GCU) and liquid carry over might be estimated. Nevertheless, moderate differences found between the computed GCU and experimental measurements suggest that new adjustments may be done to the numerical model to improve its accuracy.

Causes of energy poverty in a cold and resource-rich country: evidence from Kazakhstan

ABSTRACT Kazakhstan is an upper-middle-income country and one of the coldest countries in the world with rich energy resources and energy prices considerably lower than in developed countries. This paper presents the first comprehensive overview of household fuel use in Kazakhstan and assesses the causes and extent of energy poverty using the Households Living Conditions Survey dataset of 12,000 households. The results show that there is an overwhelming reliance on coal in Kazakhstan: 40% of all surveyed households use coal for heating, cooking and other needs. In general, liquefied petroleum gas is mainly used for cooking, coal and firewood for heating, while electricity is rarely used for heating. Energy poverty was less prevalent in oil and gas rich regions, due to low gas prices and higher income levels in those regions, while households located in the North Kazakhstan, Central and East Kazakhstan mainly suffer from lack of cleaner fuel options, income poverty, longer and colder winters and consequently energy affordability. Despite low energy prices in Kazakhstan, the results demonstrate that 28% of surveyed households spend more than 10% of their income on energy. Gas and district heating infrastructure coverage and income inequality across its regions contributed the most to energy poverty in Kazakhstan. Energy prices are regulated and indirectly subsidised. Removing energy subsidies alone may worsen energy affordability of households. Offering direct subsidies to cover part of the energy expenditures may not fully solve the problem, but subsidies, interventions for efficient technologies and fuels, dwelling energy-efficiency improvements are necessary.

CFD Modeling of Chamber Filling in a Micro-Biosensor for Protein Detection

Tuberculosis (TB) remains one of the main causes of human death around the globe. The mortality rate for patients infected with active TB goes beyond 50% when not diagnosed. Rapid and accurate diagnostics coupled with further prompt treatment of the disease is the cornerstone for controlling TB outbreaks. To reduce this burden, the existing gap between detection and treatment must be addressed, and dedicated diagnostic tools such as biosensors should be developed. A biosensor is a sensing micro-device that consists of a biological sensing element and a transducer part to produce signals in proportion to quantitative information about the binding event. The micro-biosensor cell considered in this investigation is designed to operate based on aptamers as recognition elements against Mycobacterium tuberculosis secreted protein MPT64, combined in a microfluidic-chamber with inlet and outlet connections. The microfluidic cell is a miniaturized platform with valuable advantages such as low cost of analysis with low reagent consumption, reduced sample volume, and shortened processing time with enhanced analytical capability. The main purpose of this study is to assess the flooding characteristics of the encapsulated microfluidic cell of an existing micro-biosensor using Computational Fluid Dynamics (CFD) techniques. The main challenge in the design of the microfluidic cell lies in the extraction of entrained air bubbles, which may remain after the filling process is completed, dramatically affecting the performance of the sensing element. In this work, a CFD model was developed on the platform ANSYS-CFX using the finite volume method to discretize the domain and solving the Navier–Stokes equations for both air and water in a Eulerian framework. Second-order space discretization scheme and second-order Euler Backward time discretization were used in the numerical treatment of the equations. For a given inlet–outlet diameter and dimensions of an in-house built cell chamber, different inlet liquid flow rates were explored to determine an appropriate flow condition to guarantee an effective venting of the air while filling the chamber. The numerical model depicted free surface waves as promoters of air entrainment that ultimately may explain the significant amount of air content in the chamber observed in preliminary tests after the filling process is completed. Results demonstrated that for the present design, against the intuition, the chamber must be filled with liquid at a modest flow rate to minimize free surface waviness during the flooding stage of the chamber.

Geometric predictors of abdominal aortic aneurysm maximum wall stress

Abdominal aortic aneurysm (AAA) is a dilation of the abdominal aorta (above 50 % of its original diameter), which can cause death upon rupturing. It usually grows asymptomatically leading to late clinical intervention. The medical criteria to indicate surgery are based on measuring the diameter and growth rate, but in many cases aneurysms fail at uncharacterized critical values. In search of a more efficient technique in predicting AAA failure, there is consensus on the importance of studying its geometric characteristics and estimation of the wall stress, but no fully successful correlation has been found between the two yet. This work examines the relationship between a parameterized geometry (18 input variables and 10 dependent indices) and 1 output variable: the maximum wall stress. Design of Experiments (DOE) techniques are used to generate 183 geometric configurations, for which Finite Element Analyses are performed using ANSYS™ state-of-the-art solver with a hyperelastic, isotropic and homogeneous arterial model for the wall, considering systolic internal pressure (steady state) and the restriction of longitudinal movement at the blood vessel end-sections. Due to the large number of independent parameters to consider, a preliminary Parameters Correlation analysis was performed to determine if a correlation between all input parameters and the maximum stress existed. The correlations between input parameters and the output variable were determined using the Spearman Rank correlation. Correlations with the maximum wall stress for: maximum diameter (ρ = 0.46), wall thickness (ρ = 0.35), dc parameter (ρ = 0.21) and tortuosity (ρ = 0.55) were found. The response surface function between geometry and maximum wall stress was estimated by three models: Universal Kriging geostatistical regression (18 parameters), multiple linear regression (4 parameters) and multiple exponential regression (4 parameters). The models accounted for the stress variance by 99 %, 61 % and 66 %, respectively, with average percentage errors of 0.12 %, 16 % and 17 %, respectively. The solution spaces obtained from this study might provide physicians with a better estimation of the AAA rupture potential and thus, facilitate safer and anticipated treatments of the condition.

Evaluation of interphase drag models for the determination of gas hold-up of an air-water system in a spouted bed using CFD

The hydrodynamics of a dispersed air-water system within a spouted column with a concentric draft tube and a conical base is simulated using CFD based on a two-fluid Euler-Euler E-E modeling framework and k-e two-equation turbulence closure. The interaction between the dispersed gas phase and the continuous liquid phase is characterized by bubble-liquid interphase forces drag, turbulent dispersion and lift forces. The Ishii-Zuber drag model [1] and Grace adjusted drag model [2], the latter represented by: C_D^{Grace,dense} = υ _g^p C_D^{Grace}, are compared for their capability to match experimental gas hold-up. Numerical results of Reynolds-averaged Navier-Stokes equations with k-e two-equation turbulence closure model when compared with Pironti experimental data [3] indicated that both drag models, predicted the air hold-up within experimental errors. Furthermore, Ishii-Zuber liquid-gas drag model consistently provided better agreement with experimental results; it correctly determines the hold-up within 0.14%. Numerical agreement with adjusted Grace liquid-gas drag model, is exponent dependent 4 ≤ p ≤-0.5, turning down that the best computed hold-up is within 0.44% for p=0.5.

CFD Simulation of Air-water in a Spouted Bed

Computational fluid dynamics (CFD) is employed to simulate the air-water system in a spouted column with a draft tube. Numerical results of Reynolds-averaged Navier-Stokes (RANS) equations using the k-ε and k-ω two-equation turbulence models are compared with Pironti at al. (1995) experimental data. CFD predictions of the k-ε and k-ω turbulence models are in good agreement with the reported experimental data. The interfacial momentum transfer in modeling air-water system in the spouted bed indicated the importance of using turbulent dispersion force besides the most often used drag and lift forces to better predict flow behavior and air hold-up. Ishii-Zuber liquid-gas drag model with the lift and turbulent dispersion forces yields very good results; it correctly determines a hold up within 1% when used along with the k-ε turbulence model, while it under-predicts the hold-up by 4.08% when used with the k-ω model.

Transient Two-Phase-Flow Model for Predicting Column Formation in Intermittent Gas Lift Systems

The intermittent gas lift (IGL) method has experimented a continuous growth due to well depletion and so is expected from its technology. IGL is a periodic transient process with two major stages: firstly, a liquid column or slug is accumulated at the bottom of the well. Secondly, the slug is displaced by pressurized gas lift to the surface. Current models estimate the height of the fluid column based on single-phase behavior due to the lack of multiphase transient models. These models underestimate dramatically the column when the operating gas lift valve is located far away from the perforations. To improve this model a study focused on a twophase flow behavior during the accumulation stage is required. In order to achieve this objective a special multiphase flow facility was assembled and more than 200 steady and transient tests were run. Continuous and transient tests were performed with flow conditions and fluid properties selected from typical fields. The collected data allowed identifying the variables that govern the phenomena and establishing a methodology to determine the mixture density, pressure gradient and column’s height. Since no previous correlation matched, a new correlation for transient hold up was generated using qualitative and dimensionless analysis. As part of the approach proposed here, time was included implicitly into the equations in order to reduce their complexity. The analysis showed that Reynolds’s number, homogeneous liquid holdup and dimensionless viscosity govern the phenomenon. The model was validated with field data . The correlation applies to slug and churn flow patterns because those are the expected patterns for typical field conditions. The accuracy obtained with field data suggests applying this approach for designing and optimizing IGL installations.

A New Model to Simulate Gas Injection in Gas Chamber Pumps

Currently, there exist large heavy-oil reserves in countries like Venezuela and Canada. In Venezuela, heavy oil represents 69% of the reserves, and its exploitation is not always feasible using traditional pumping technologies. In particular, this is the case of some in-lake oil wells in Venezuela, which are impossible to exploit by means of any known efficient way of oil lifting. An alternative is the gas-chamber pumping (GCP), an intermittent artificial lift method used in diverse areas of USA, in shallow wells with heavy oil and in areas where a source of high-pressure gas exists. Few works are reported on the modeling of the phenomena associated to GCP, the most rigorous being the one published by PDVSA-Intevep in the year 2000. This model, however, omits some key aspects related with gas injection, which affects its precision to simulate or design GCP systems. The present work develops a model to rigorously simulate the stage of gas injection into the chamber, incorporating aspects like the flow of gas from the supply manifold up to the wellhead, the gas expansion within the injection valve, the descending flow along a coiled tubing, and the heat transfer associated. The pressurization process and chamber venting are also modeled. The model predictions are in excellent agreement with experimental data [1].

Eulerian-Eulerian Modeling of Disperse Two-Phase Flow in a Gas-Liquid Cylindrical Cyclone

This work presents a three-dimensional CFD study of a two-phase flow field in a Gas-Liquid Cylindrical Cyclone (GLCC) using CFX4.3™, a commercial code based on the finite volume method. The numerical analysis was made for air-water mixtures at near atmospheric conditions, while both liquid and gas flow rates were changed. The two-phase flow behavior is modeled using an Eulerian-Eulerian approach, considering both phases as an interpenetrating continuum. This method computed the inter-phase phenomena by including a source term in the momentum equation to consider the drag between the liquid and gas phases. The gas phase is modeled as a bimodal bubble size distribution to allow for the presence of free- and entrapment gas, simultaneously. The results (free surface shape and liquid angular velocity) show a reasonable match with experimental data. The CFD technique here proposed, demonstrates to satisfactorily reproduce angular velocities of the phases and their spatial distribution inside the GLCC. Computed results also proved to be useful in forecasting bubble and droplet trajectories, from which gas carry under (GCU) and liquid carry over (LCO) might be estimated. Nevertheless, moderate differences found between the computed GCU and experimental measurements, suggests that new adjustments may be done to the numerical model to improve its accuracy.Copyright

Long-Term Climate Change Mitigation in Kazakhstan in a Post Paris Agreement Context

Under the Paris Agreement, Kazakhstan’s nationally determined contribution (NDC) target is to reduce its greenhouse gas emissions (GHG) by between 15 and 25% by 2030 compared with 1990 levels. Kazakhstan’s energy system is highly carbon intensive and GHG emissions continue to steadily grow, indicating insufficient progress towards achieving the NDC emissions reductions announced under the Paris Agreement. This chapter presents modelling analysis that assesses a least-cost long term (2050) pathway towards achieving these NDC targets. An additional scenario with a ban on coal across all sectors is also considered. We utilize a TIMES-based sub-national disaggregated 16-region energy systems model for Kazakhstan. The results demonstrate how ambitious a 25% GHG emissions reduction pathway is compared with the current energy policies and mitigation actions. Such a reduction requires an almost full phase-out of coal consumption in power generation by 2050. The share of renewable energy (including hydro) could represent half of the electricity generation mix, the other half being attributed to gas-fired power plants. In other words, the overall target as set by Kazakhstan’s Strategy 2050 and Green Economy Concept to reach 50% of renewable and alternative energy sources by 2050 is very close to the least-cost 25% emissions reduction pathway. The corresponding abatement costs reach levels as high as 59 USD (constant prices of 2013) per tonne of CO2 eq. in 2030 and 281 USD per tonne of CO2 eq. in 2050. A coal ban alone is not sufficient to reduce GHGs, additional actions are needed to promote renewables.