Big pipe timeslice generator#
Big pipe timeslice code#

These are detailed below and in manuscript appended to this executive summary. The main accomplishments of more » this project include the record for dynamic range for velocimetry, highest accuracy obtained with this technique, successful deployment in an IET leading to new validation matrix for CFD. This was a collaborative effort between co-PIs at The George Washington University (GW), Oregon State University (OSU), and NASA Langley Research Center. This campaign required the development of a new laser spectroscopic diagnostic to measure velocity in the challenging conditions of the HTTF: low speed (~1 m/s) gas flows at HTGR prototypical temperature and 1/10th pressure. The HTTF simulates Depressurized and Pressurized Conduction Cooldowns (DCC and PCC). « lessĪ validation experimental campaign was conducted in an Integral Effect Test (IET) facility of High Temperature Gas Reactors (HTGR), the High-Temperature Test Facility (HTTF) at Oregon State University (OSU). The largest time steps produce results that are inconsistent with the results produced by the smaller time steps. As the scale of the time step increases, the variability in these performance measures decreases. Variation in all three performance measures is greatest at the shortest time step sizes. The model performance measures examined are the distribution of the Reynolds number, the variation in the center of mass of the solute across time, and the transport path and timing of the solute through the network. However, variation in demands along the solute transport path contribute to both removal and distortion of the injected pulse. The transport equations within EPANET assume perfect mixing of the solute within a parcel of water and therefore physical dispersion cannot occur. Solute is introduced at a tank and at three different network nodes and concentrations are modeled through the system using the Lagrangian transport scheme within EPANET.

Big pipe timeslice generator#

Variable demands are simulated for these different time step sizes using a previously developed Poisson rectangular pulse (PRP) demand generator that considers demand at a node to be a combination of exponentially distributed arrival times with log-normally distributed intensities and durations. We show that variable demands at short time scales can have the following effects: smoothing of a pulse of tracer injected into a distribution network and increasing the variability of both the transport pathway and transport timing through more » the network. We simulate flow and transport in a small water distribution network using EPANET to explore the effect of variable demand on solute transport across a range of hydraulic time step scales from 1 minute to 2 hours. The effect of variable demands at short time scales on the transport of a solute through a water distribution network has not previously been studied. Preliminary comparison between dynamic pilot data and EPANET-BAM is also = , The impact of a storage tank on pipe mixing in a combined pipe-tank network during diurnal fill-and-drain cycles is assessed.

Big pipe timeslice code#

A new version EPANET code was developed to yield better mixing predictions.

Macroscopic mixing rules based on flow momentum balance are also explored, and in some cases, implemented in EPANET. High resolution analysis of turbulence mixing is carried out via high speed photography as well as 3D finite-volume based Large Eddy Simulation turbulence models. The experimental effort involves measurement of extent of mixing within different configurations of pipe networks, measurement of dynamic mixing in a single mixing tank, and measurement of dynamic solute mixing in a combined network-tank configuration. This report summarizes the experimental and modeling effort undertaken to understand solute mixing in a water distribution network conducted during the last year of a 3-year project.