BR 
EN In multiobjective decision-making problems, it is common to encounter nondominated alternatives. In these situations, the decision-making process becomes complex, as each alternative offers better outcomes for some objectives and worse outcomes for others simultaneously. However, DMs still must choose a single alternative that provides an acceptable balance between the conflicting objectives, which can become exceedingly challenging. To address this scenario, our work introduces a decision-making framework aimed at supporting such decisions. Our proposed framework draws upon concepts from the field of Multi-Criteria Decision Making, and combines a novel simplex-like weight generation method with expert insights and machine learning data-driven procedures to establish an intuitive methodology that empowers DMs to select a single alternative from a range of alternatives. In this paper, we illustrate the effectiveness of our methodology through an example and two real-world decision cases from the oil and gas industry, each involving 128 alternatives and five distinct objectives.
Mês: fevereiro 2025
Estimation of distribution algorithms for well placement optimization in petroleum fields
Optimizing well placement is one of the primary challenges in oil field development. The number and positions of wells must be carefully considered, as it is directly related to the infrastructure cost and the profits over the field’s life cycle. In this paper, we propose three estimation of distribution algorithms to optimize well placement with the objective of maximizing the net present value. The methods are guided by an elite set of solutions and are able to obtain multiple local optima in a single run. We also present an auxiliary regression model to preemptively discard candidate solutions with poor performance prediction, thus avoiding running computationally expensive simulations for unpromising candidates. The model is trained with the data obtained during the search process and does not require previous training. Our algorithms yielded a significant improvement compared to a state-of-the-art reference method from the literature, as evidenced by computational experiments with two benchmarks.
A benchmark generator for scenario-based discrete optimization
Multi-objective evolutionary algorithms (MOEAs) are a practical tool to solve non-linear problems with multiple objective functions. However, when applied to expensive black-box scenario-based optimization problems, MOEA’s performance becomes constrained due to computational or time limitations. Scenario-based optimization refers to problems that are subject to uncertainty, where each solution is evaluated over an ensemble of scenarios to reduce risks. A primary reason for MOEA’s failure is that algorithm development is challenging in these cases as many of these problems are black-box, high-dimensional, discrete, and computationally expensive. For this reason, this paper proposes a benchmark generator to create fast-to-compute scenario-based discrete test problems with different degrees of complexity. Our framework uses the structure of the Multi-Objective Knapsack Problem to create test problems that simulate characteristics of expensive scenario-based discrete problems. To validate our proposition, we tested four state-of-the-art MOEAs in 30 test instances generated with our framework, and the empirical results demonstrate that the suggested benchmark generator can analyze the ability of MOEAs in tackling expensive scenario-based discrete optimization problems.
A comparative numerical study of finite element methods resulting in mass conservation for Poisson’s problem: Primal hybrid, mixed and their hybridized formulations
This paper presents a numerical comparison of finite-element methods resulting in local mass conservation at the element level for Poisson’s problem, namely the primal hybrid and mixed methods. These formulations result in an indefinite system. Alternative formulations yielding a positive-definite system are obtained after hybridizing each method. The choice of approximation spaces yields methods with enhanced accuracy for the pressure variable, and results in systems with identical size and structure after static condensation. A regular pressure precision mixed formulation is also considered based on the classical RTk space. The simulations are accelerated using Open multi-processing (OMP) and Thread-Building Blocks (TBB) multithreading paradigms alongside either a coloring strategy or atomic operations ensuring a thread-safe execution. An additional parallel strategy is developed using C++ threads, which is based on the producer-consumer paradigm, and uses locks and semaphores as synchronization primitives. Numerical tests show the optimal parallel strategy for these finite-element formulations, and the computational performance of the methods are compared in terms of simulation time and approximation errors. Additional results are developed during the process. Numerical solvers often fail to find an accurate solution to the highly indefinite systems arising from finite-element formulations, and this paper documents a matrix ordering strategy to stabilize the resolution. A procedure to enable static condensation based on the introduction of piecewise constant functions that also fulfills Neumann’s compatibility condition, and yet computes an average pressure per element is presented.
A two-level semi-hybrid-mixed model for Stokes–Brinkman flows with divergence-compatible velocity–pressure elements
A two-level version for a recent semi-hybrid-mixed finite element approach for modeling Stokes and Brinkman flows is proposed. In the context of a domain decomposition of the flow region Ω, composite divergence-compatible finite elements pairs in H(div,Ω)×L2(Ω) are utilized for discretizing velocity and pressure fields, using the same approach previously adopted for two-level mixed Darcy and stress mixed elasticity models. The two-level finite element pairs of spaces in the subregions may have richer internal resolution than the boundary normal trace. Hybridization occurs by the introduction of an unknown (traction) defined over element boundaries, playing the role of a Lagrange multiplier to weakly enforce tangential velocity continuity and Dirichlet boundary condition. The well-posedness of the method requires a proper choice of the finite element space for the traction multiplier, which can be achieved after a proper velocity FE space enrichment with higher order bubble fields. The method is strongly locally conservative, yielding exact divergence-free velocity fields, demonstrating pressure robustness, and facilitating parallel implementations by limiting the communication of local common data to at most two elements. Easier coupling strategies of finite elements regarding different polynomial degree or mesh widths are permitted, provided that mild mesh and normal trace consistency properties are satisfied. Significant improvement in computational performance is achieved by the application of static condensation, where the global system is solved for coarse primary variables. The coarse primary variables are a piecewise constant pressure variable over the subregions, velocity normal trace and tangential traction over subdomain interfaces, as well as a real number used as a multiplier ensuring global zero-mean pressure. Refined details of the solutions are represented by secondary variables, which are post-processed by local solvers. Numerical results are presented for the verification of convergence histories of the method.
Analysis of energy losses and head produced by a radial impeller using particle image velocimetry
Centrifugal pumps play a crucial role in industrial operations involving fluid transport. The quest for optimizing efficiency and reducing energy usage is a driving force behind research into their performance. The literature continues to offer opportunities for the creation of models that accurately depict the head generated by pumps, with a particular focus on impellers. The current pumps, however, are still far from being completely optimized. The idea of this paper is to conduct an analysis of energy losses and propose a mathematical expression to represent the head produced by a radial impeller, P23 model, working with water flow, considering that head is influenced by losses due to recirculation, shock/incidence, internal friction. The head losses are quantitatively evaluated from experimental data acquired via particle image velocimetry, which provides information on velocity vector direction and wall shear stress, both useful for the analysis. Our results reveal that the loss due to friction is the most significant, accounting for 40–90% of the total head loss, while shock and recirculation losses are restricted to 35% and 25%, respectively. Friction factors vary from 1.0 to 26 depending on the flow rate, as a result of wall shear stresses reaching up to 430 N/m2, mainly influenced by pressure and pseudoforces. The head calculated through the new proposed expression is finally compared with the actual head generated by the impeller, measured via experiments dedicated to assess the pump performance. According to our results, the relative deviations between the calculated and measured heads are limited to 5%. Although our results have been validated for a single P23 impeller geometry, the methodology developed here can be extended to other impellers in the future. The results may thus represent a step forward for designing more efficient and power-saving pumps.
Experimental and theoretical modeling of droplet break-up on W/O emulsion flow in ESPs
The behavior of water-in-oil emulsions flow within Electrical Submersible Pumps (ESPs) is of significant interest in the oil and gas industry due to its complex rheological characteristics, which are influenced by operational parameters and the chemical properties of both phases. Operational parameters such as dispersed phase fraction, temperature, flow rate, and pump design were investigated experimentally in this work. Improved semi-empirical models for mean and maximum droplet diameter estimation were also proposed. Through extensive experimentation and statistical analysis, this study reveals that smaller droplets form with increasing dispersed phase fraction and the flow geometry significantly affects droplet breakage intensity. The proposed models integrate the dispersed phase fraction, dimensionless flow rate, specific speed, and energy dissipation rate, exhibiting commendable alignment with experimental findings. This not only helps predict effective viscosity but offers valuable insights for further analyses, particularly regarding catastrophic phase inversion (CPI) prediction. These aspects have significant importance in the oil and gas industry and can enable the optimization of production systems and processing facilities.
Theoretical and numerical comparison between the pseudopotential and the free energy lattice Boltzmann methods
The pseudopotential and free energy models are two popular extensions of the lattice Boltzmann method for multiphase flows. Until now, they have been developed apart from each other in the literature. However, important questions about whether each method performs better needs to be solved. In this work, we perform a theoretical and numerical comparison between both methods. This comparison is only possible because we developed a novel approach for controlling the interface thickness in the pseudopotential method independently on the equation of state. In this way, it is possible to compare both methods maintaining the same equilibrium densities, interface thickness, surface tension and equation of state parameters. The well-balanced approach was selected to represent the free energy. We found that the free energy one is more practical to use, as it is not necessary to carry out previous simulations to determine simulation parameters (interface thickness, surface tension, etc). In addition, the tests proofed that the free energy model is more accurate than the pseudopotential model. Furthermore, the pseudopotential method suffers from a lack of thermodynamic consistency even when applying the corrections proposed in the literature. On the other hand, for both static and dynamic tests we verified that the pseudopotential method is more stable than the free energy one, allowing simulations with lower reduced temperatures. We hope that these results will guide authors in the use of each method.
Particle image velocimetry in the impeller of a centrifugal pump: Relationship between turbulent flow and energy loss
Turbulent flows play a dominant role in the operation of centrifugal pumps, which find widespread use in industrial settings and various aspects of human life. The dissipation rate of turbulent kinetic energy emerges as a key parameter within these devices, with its local values exerting a significant influence on centrifugal pump performance. Recent advances in particle image velocimetry (PIV) techniques have expanded the ability to analyze complex turbulent flows across a broad spectrum of scales. In this context, this paper aims to deepen our understanding of the turbulent flow field and its correlation with energy loss in centrifugal pump impellers. To achieve this, experiments were conducted using PIV on a transparent pump operating under different conditions. Statistics of the turbulent flow were then obtained from phase-ensemble averages of velocities, vorticity, turbulence production, and local dissipation of turbulent kinetic energy. To overcome the limited spatial resolution constraint of PIV, the large-eddy PIV (LES-PIV) method was employed to estimate the local dissipation rate. In this method, it is assumed that the motion of larger scales is measured by the PIV technique, while the smaller scales (unresolved scales) are modeled by a sub-grid scale model, calculated from the strain rate tensors obtained from the measured fields. Energy losses in the impeller were studied using two methodologies: (i) a conventional method based on power measurements, and (ii) an alternative approach based on the budget of turbulent kinetic energy. Our results reveal that turbulent loss caused by turbulence production is the main source of energy loss in the pump impeller, and it is particularly pronounced in low-flow operating conditions characterized by large-scale structures. On the other hand, in situations where flow rates exceed the best efficiency point (BEP) condition, the predominant flow structures are marked by small-scale features, mainly attributed to local dissipation of turbulence. Our findings clarify the characteristics of energy losses in centrifugal pump impellers and their relationship with the turbulent flow field, and, in addition, providing a methodology for calculating the local turbulent dissipation rate and its limitations when derived from PIV measurements.