1,720,992 research outputs found
Experimental Analysis of non-Newtonian Droplets Generated in Silicone Oil Flows through a Micro Cross-Junction
No full textGeneration of Newtonian droplets in Newtonian and non-Newtonian carrier flows in micro T-junctions under opposed-flow configuration
No full textIn this paper the generation of Newtonian microdroplets in both Newtonian and non-Newtonian carrier fluids through a commercial micro T-junction under an opposed-flow configuration is analyzed experimentally. Pure deionized water and 0.2 wt% aqueous Xanthan gum solution in presence or absence of surfactant (Tween 20) have been considered as carrier fluids and the silicone oil is employed as the dispersed phase. The role of surfactant as a promoter of the generation of a droplet-based flow at the outlet of the T-junction is analyzed. Squeezing, dripping, jetting and parallel flow regimes have been generated by varying the flow rates of the dispersed and continuous phases at the inlets of the junction. A series of flow maps is presented in order to facilitate the design prediction of the droplet flow patterns generated at the outlet of the junction by varying the Capillary number and/or the inlet volumetric flow rates of Newtonian and non-Newtonian fluids. In the current paper, detailed information about the typical values of the droplet breakup distance from the center of the T- junction is demonstrated and the typical droplet length and polydispersity values are studied as a function of the inlet flow rate ratio and Capillary number
Experimental Characterization of a Generator of Non-Newtonian droplets based on a Micro Cross-Junction
Full text linkMicro Droplets of non-Newtonian Solutions in Silicone Oil Flow through a Hydrophobic Micro Cross-Junction
Full text linkIn this paper the generation of non-Newtonian droplets of aqueous Xanthan gum solution (0.3, 0.5 wt%) in a silicone oil flow through a micro cross-junction is experimentally analyzed. A commercial glass cross-junction microchip with hydrophobic walls has been employed to study the droplet generation mechanism. The cross-section of the channel is stadium-shaped, the width of the junction varies between 195 to 390 mu m while the height of the channel is fixed at 190 mu m. Tween 20 (2 wt%), as a surfactant, has been added to the dispersed phase to avoid the coalescence of the droplets and to enhance the droplet formation. With the aim to follow the time evolution of the droplets inside the channel a specific experimental setup has been implemented. The post-processing of the recorded images has been carried out by means of an "in-house" Matlab code. The typical flow patterns obtained by imposing different flow rates at the inlets of the cross-junction have been observed. The effect of the continuous and dispersed phase flow rates as well as the concentration of Xanthan gum solution on the main droplet characteristics has been studied in detail
Silicon Oil Droplet Generation in Water in an Opposed-Flow Micro T-Junction with or without Surfactant
No full textExperimental Investigation of Dripping and Jetting Regimes in a Micro Cross-Junction with Newtonian and Non-Newtonian Dispersed Phases in Silicon Oil
No full textBranch-price-and-cut algorithms for the vehicle routing problem with stochastic and correlated travel times
Full text linkIn this paper, we consider a version of the capacitated vehicle routing problem (CVRP) where travel times are assumed to be uncertain and statistically correlated (CVRP-SCT). In particular, we suppose that travel times follow a multivariate probability distribution whose first and second moments are known. The main purpose of the CVRPCST is to plan vehicle routes whose travel times are reliable, in the sense that observed travel times are not excessively dispersed with respect to their expected value. To this scope we adopt a mean-variance approach, where routes with high travel time variability are penalized. This leads to a parametric binary quadratic program for which we propose two alternative set partitioning reformulations and show how to exploit the structure of the correlation matrix when there is correlation only between adjacent links. For each model, we develop an exact branch-price-and-cut algorithm, where the quadratic component is dealt with either in the column generation master problem or in its subproblem. We tested our algorithms on a rich collection of instances derived from well-known data sets. Computational results show that our algorithms can efficiently solve problem instances with up to 75 customers. Furthermore, the obtained solutions significantly reduce the time variability when compared with standard CVRP solutions. Copyright
Single Allocation Hub Location with Heterogeneous Economies of Scale
No full textWe study the single allocation hub location problem with heterogeneous economies of scale (SAHLP-h). The SAHLP-h is a generalization of the classical single allocation hub location problem (SAHLP), in which the hub-hub connection costs are piecewise linear functions of the amounts of flow. We model the problem as an integer nonlinear program, which we then reformulate as a mixed integer linear program (MILP) and as a mixed integer quadratically constrained program (MIQCP). We exploit the special structures of these models to develop Benders-type decomposition methods with integer subproblems. We use an integer L-shaped decomposition to solve the MILP formulation. For the MIQCP, we dualize a set of complicating constraints to generate a Lagrangian function, which offers us a subproblem decomposition and a tight lower bound. We develop linear dual functions to underestimate the integer subproblem, which helps us obtain optimality cuts with a convergence guarantee by solving a linear program. Moreover, we develop a specialized polynomial-time algorithm to generate enhanced cuts. To evaluate the efficiency of our models and solution approaches, we perform extensive computational experiments on both uncapacitated and capacitated SAHLP-h instances derived from the classical Australian Post data set. The results confirm the efficacy of our solution methods in solving large-scale instances
Demand Management by Aggregation: The Case of Spare Parts
No full textDemand management is a hierarchical process encompassing various levels of decision making. It spans from inventory control at the individual order line level to strategic planning. Aggregation offers a distinct opportunity to improve demand management practices, which essentially rely upon a combination of information along three dimensions: products, customers and time. Product and customer aggregation have been extensively addressed in the pertinent academic literature and equally considered by practitioners and software package developers. However, neither the time dimension nor the combined effects of aggregation across the three dimensions have been adequately studied and empirical evidence in this area is lacking. In this paper, we consider empirically the effects of aggregation on demand management. An extensive dataset composed of 18,937 series related to 2,422 stock keeping units (SKUs) is utilised for this purpose and the simulation structure allows the assessment of 27 realistic aggregation scenarios. Our work emphasises the case of spare parts where the intermittent nature of demand renders aggregation a natural strategy to reduce dispersion and increase predictability. The results allow insights to be gained on the effects of aggregation and tangible suggestions are being made to demand planners. The implications of this work for the theory and practice of OM are explicitly addressed and we conclude with an extensive discussion on the next steps of research in this are
A convex reformulation and an outer approximation for a large class of binary quadratic programs
Full text linkIn this paper, we propose a general modeling and solving framework for a large class of binary quadratic programs subject to variable partitioning constraints. Problems in this class have a wide range of applications as many binary quadratic programs with linear constraints can be represented in this form. By exploiting the structure of the partitioning constraints, we propose mixed-integer nonlinear programming (MINLP) and mixedinteger linear programming (MILP) reformulations and show the relationship between the two models in terms of the relaxation strength. Our solution methodology relies on a convex reformulation of the proposed MINLP and a branch-and-cut algorithm based on outer approximation cuts, in which the cuts are generated on the fly by efficiently solving separation subproblems. To evaluate the robustness and efficiency of our solution method, we perform extensive computational experiments on various quadratic combinatorial optimization problems. The results show that our approach outperforms the state-of-the-art solver applied to different MILP reformulations of the corresponding problems
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