Pedro Romero-Gomez

Pore-Scale and Multiscale Numerical Simulation of Flow and Transport in a Laboratory-Scale Column

Pore-scale models are useful for studying relationships between fundamental processes and phenomena at larger (i.e., Darcy) scales. However, the size of domains that can be simulated with explicit pore-scale resolution is limited by computational and observational constraints. Direct numerical simulation of pore-scale flow and transport is typically performed on millimeter-scale volumes at which X-ray computed tomography (XCT), often used to characterize pore geometry, can achieve micrometer resolution. In contrast, laboratory experiments that measure continuum properties are typically performed on decimeter-scale columns. At this scale, XCT resolution is coarse (tens to hundreds of micrometers) and prohibits characterization of small pores and grains. We performed simulations of pore-scale processes over a decimeter-scale volume of natural porous media with a wide range of grain sizes, and compared to results of column experiments using the same sample. Simulations were conducted using high-performance codes executed on a supercomputer. Two approaches to XCT image segmentation were evaluated, a binary (pores and solids) segmentation and a ternary segmentation that resolved a third category (porous solids with pores smaller than the imaged resolution). We used a multiscale Stokes-Darcy simulation method to simulate the combination of Stokes flow in large open pores and Darcy-like flow in porous solid regions. Flow and transport simulations based on the binary segmentation were inconsistent with experimental observations because of overestimation of large connected pores. Simulations based on the ternary segmentation provided results that were consistent with experimental observations, demonstrating our ability to successfully model pore-scale flow over a column-scale domain.

Experimental Verification of Incomplete Solute Mixing in a Pressurized Pipe Network with Multiple Cross Junctions

Water quality models based on accurate mixing data at cross junctions are important for estimating concentrations of chemical species in municipal water distribution systems. Recent studies indicate that the instantaneous complete (thus “perfect”) mixing assumption potentially can result in an erroneous prediction of water quality. The present study examines the updated “incomplete” solute mixing model at cross junctions in a network having multiple cross junctions. The model performance in predicting solute transport was evaluated through a series of tracer experiments in a pressurized 5×5 network with 9 cross junctions. The perfect mixing model consistently overestimated solute dilution at cross junctions and predicted evenly distributed solute concentration throughout the network. In contrast, the incomplete mixing model demonstrated uneven distribution patterns with a distinct solute plume, and the corresponding results were significantly more accurate than those based on the perfect mixing assumption...

Axial Dispersion Coefficients in Laminar Flows of Water-Distribution Systems

Because longitudinal dispersion is becoming increasingly germane to the problem of accurately determining water quality, water-resource managers and engineers seeking to represent solute transport in drinking-water systems must be able to compute relevant dispersion coefficients. Accordingly, the present study was undertaken to develop and experimentally verify a modified advection-dispersion-reaction transport equation as well as the formulas used to calculate the axial dispersion coefficient. The analysis assumes laminar flows, constant mean velocities, and short travel times (dimensionless time, T<0.01). With regard to the modified transport equation, the dispersion term was assumed to be direction-dependent. Thus, two distinct dispersion rates (forward and backward) were recognized and quantified as opposed to the single value used in conventional dispersion models. With the dimensionless travel time taken to be the independent variable, the developed dispersion coefficients increased at about one-fou...

Sensor network design with improved water quality models at cross junctions

Single- and multi-objective sensor network designs have relied on water quality models that assume instantaneous and complete mixing of species at junctions. However, recent findings show that the perfect mixing assumption at pipe junctions potentially results in erroneous outcomes in predicting water quality in pipe networks. The latest studies, through a series of computational and experimental approaches, provide a higher-accuracy water quality model. In the present study, sensor network designs in water distribution networks are reexamined using both the perfect mixing and non-perfect mixing assumptions. The optimization algorithm minimizes the number of sensors needed for detecting potential contaminant intrusions at all the nodes (100% detection coverage), while maximizing the redundancy of sensor coverage. Extended-period simulations of a set of contamination events were performed on two water quality models and resulted in two distinct contamination-event matrices. Comparisons of the required number of sensors and corresponding locations indicate that incomplete mixing at pipe junctions has a significant impact on the optimal sensor placement. Therefore, the improvement of water quality modeling will improve the effectiveness of early warning detection systems in the event of accidental or deliberate contamination.

Analysis of Greenhouse Natural Ventilation Under the Environmental Conditions of Central Mexico

Because of the rapid growth of the greenhouse industry in Mexico and the increasing need for relevant information about structural design and management, the internal microclimate of a naturally ventilated greenhouse in central Mexico was investigated. In order to quantify the ventilation rates resulting from inside and outside environmental conditions, tracer gas (TG) experiments were carried out. Properties of an insect screen were determined by a series of wind tunnel experiments. The same experimental conditions were then used to calculate the air exchange rate by means of computational fluid dynamics (CFD). The results showed a significant correlation between ventilation rate and wind speed (R2 = 0.7079). For instances when only roof vents are kept open, high wind speeds (>4.5 m s-1) are required to provide a recommended air exchange rate of one greenhouse volume per minute (6.64 × 10-2 m3 m-2 s-1). The correlation between CFD-simulated and TG-measured ventilation rates was 0.7065 at wind speeds higher than 2 m s-1.

INTEGRATED WATER QUALITY MODELING OF WATER DISTRIBUTION SYSTEMS

An accurate water quality modeling tool will be essential for many municipalities that must design or upgrade distribution systems. If network models are to remain effective tools for designing, operating, and managing drinking water distribution systems, it will become necessary to expand existing water quality algorithms so as to properly account for mixing at pipe junctions and unsteady dispersion along pipe links. While these upgrades would present new challenges for water quality modeling in water distribution networks, they would also provide an urgently needed second-generation modeling capability. In this study, we focus primarily on integrating both junction mixing and axial dispersion phenomena with the following steps: First, we use hydraulic calculations in a selected network to provide the database for the water quality simulations that involve incomplete mixing at junctions. Second, we employ a one-dimensional dispersion-advection model, integrated with recently developed coefficients, to produce transient water quality results for the network. The results are then quantitatively compared with those obtained based on the conventional assumptions; i.e., complete mixing and advection-only solute transport. Overall, this study outlines ongoing research efforts aimed at implementing the nodal mixing and dispersive behavior of soluble matter in steady and unsteady pipe flow regimes into the water quality model.

Assessment of MS-2 phage and salt tracers to characterize axial dispersion in water distribution systems.

The present study investigates the axial dispersion and retardation patterns of viruses in a pressurized water distribution pipe using MS-2 as a surrogate. The results were obtained by using computational fluid dynamics (CFD), along with a hydraulic and water quality model. These models included the plug flow assumption and were first used to estimate transport mechanisms along a pipe. These prediction–model results were compared to experimental data using sodium chloride as a chemical tracer. Significant axial dispersion and retardation (or tailing) was found to exist under laminar flow conditions with high dispersion coefficients (E) estimated by CFD runs and salt tracer experiments. A similar dispersion pattern was also observed for MS-2, along with a long tailing pattern, which is particularly unique. The commonly used water quality model showed no axial dispersion (E = 0) under any flow regimes; thus, the plug flow assumption could produce significant errors in predicting the transport phenomena of chemical and biological constituents in water distribution systems. On the other hand, the dispersion curves predicted by the plug flow model and CFD are in good agreement with the experimental data in the turbulent flow regime, although using computational methods to predict microbial retardation is intrinsically difficult. Because the MS-2 demonstrated considerable temporal retardation and because its detection limit is much lower than that of the salt tracer, MS-2 should make an excellent tracer for characterizing viral transport in water distribution systems.

Movement and collision of Lagrangian particles in hydro-turbine intakes: a case study

ABSTRACT Studies of the stress/survival of migratory fish during downstream passage through operating hydro-turbines are normally conducted to determine the fish-friendliness of the hydro-turbine units. This study applies a modelling strategy based on flow simulations using computational fluid dynamics and Lagrangian particle tracking to represent the travel of live fish and autonomous sensor devices through hydro-turbine intakes. For the flow field calculation, the simulations were conducted using a Reynolds-averaged Navier–Stokes turbulence model and an eddy-resolving technique. For the particle-tracking calculation, different modelling assumptions for turbulence forcing, mass formulation, buoyancy, and release conditions were tested. The modelling assumptions are evaluated with respect to datasets collected using a laboratory physical model and an autonomous sensor device deployed at Ice Harbor Dam (Snake River, State of Washington, USA) at the same discharge and release point modelled in the present work. We found acceptable agreement between the simulated results and observed data and discuss relevant features of Lagrangian particle movement that are critical in turbine design and in the experimental design of field studies.

PREDICTION OF CONTAMINANTS IN WATER DISTRIBUTION SYSTEMS USING ARTIFICIAL NEURAL NETWORKS

Transport phenomena of contaminants in water distribution systems are examined using Artificial Neural Networks (ANNs). First, a contaminant is introduced in the reservoir, and its concentration throughout the system is predicted as a function of water demands at regional levels. For this purpose, a back-propagation ANN is trained, tested and validated with data obtained from both experiments in an actual water system and EPANET. Next, the most likely location of the chemical’s intrusion point is tracked based on readings collected from several sensors placed in the water network. In order to minimize intrinsic errors, several parameters of the architecture and functions of these ANNs were thoroughly tested: a number of processing units in hidden layers, transfer functions, and learning rules, to name a few. The present study provides relevant information for alertness and preparedness in potential intentional and accidental contamination events.

Mixing at junctions in water distribution systems: an experimental study

Abstract The accurate prediction of solute transport in water distribution systems has become a critical component of efforts aimed at delivering clean drinking water safely to large urban populations. One of the central assumptions that water quality models have traditionally relied upon dictates that, in a four-way junction, two incoming flows of differing quality will mix perfectly to produce two outgoing flows of equal quality, and that such complete mixing occurs irrespective of the specific assemblage characteristics of any particular four-way junction. In this study, laboratory experiments were conducted in order to characterize solute mixing patterns at double-tee and wye junctions, both of which are commonly found in urban water distribution systems. Results show that mixing at double-tee junctions tends to be less than complete when the tee connectors are located adjacent to each other and mix to a greater degree than flows at cross junctions.