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A common observation made when computing chemically reacting flows is how central processing unit (CPU)-intensive these are in comparison to cold flow cases. The update of tens or hundreds of species with hundreds or thousands of reactions can easily consume more than 95% of the total CPU time. In many cases, the region where reactions (combustion) are actually taking place comprises only a very small percentage of the volume. Typical examples are flame fronts propagating through a domain. In such cases, only a small fraction of points/cells needs a full chemistry update. This leads to extreme load imbalances on parallel machines. The purpose of the present work is to develop a methodology to balance the work in an optimal way.

Points that require a full chemistry update are identified, gathered and distributed across the network, so that work is evenly distributed. Once the chemistry has been updated, the unknowns are gathered back.

The procedure has been found to work extremely well, leading to optimal load balance with insignificant communication overheads.

In many production runs, the procedure leads to a reduction in CPU requirements of more than an order of magnitude. This allows much larger and longer runs, improving accuracy and statistics.

The procedure has allowed the calculation of chemically reacting flow cases that were hitherto not possible.

To the authors’ knowledge, this type of load balancing has not been published before.

It is of paramount importance to ensure safe and fast evacuation routes in cities in case of natural disasters, environmental accidents or acts of terrorism. The same applies to large-scale events such as concerts, sport events and religious pilgrimages as airports and to traffic hubs such as airports and train stations. The prediction of pedestrian is notoriously difficult because it varies depending on circumstances (age group, cultural characteristics, etc.). In this study, the Ensemble Kalman Filter (EnKF) data assimilation technique, which uses the updated observation data to improve the accuracy of the simulation, was applied to improve the accuracy of numerical simulations of pedestrian flow.

The EnKF, one of the data assimilation techniques, was applied to the in-house numerical simulation code for pedestrian flow. Two cases were studied in this study. One was the simplified one-directional experimental pedestrian flow. The other was the real pedestrian flow at the Kaaba in Mecca. First, numerical simulations were conducted using the empirical input parameter sets. Then, using the observation data, the EnKF estimated the appropriate input parameter sets. Finally, the numerical simulations using the estimated parameter sets were conducted.

The EnKF worked on the numerical simulations of pedestrian flow very effectively. In both cases: simplified experiment and real pedestrian flow, the EnKF estimated the proper input parameter sets which greatly improved the accuracy of the numerical simulation. The authors believe that the technique such as EnKF could also be used effectively in other fields of computational engineering where simulations and data have to be merged.

This technique can be used to improve both design and operational implementations of pedestrian and crowd dynamics predictions. It should be of high interest to command and control centers for large crowd events such as concerts, airports, train stations and pilgrimage centers.

To the authors’ knowledge, the data assimilation technique has not been applied to a numerical simulation of pedestrian flow, especially to the real pedestrian flow handling millions pedestrian such as the Mataf at the Kaaba. This study validated the capability and the usefulness of the data assimilation technique to numerical simulations for pedestrian flow.

The purpose of this paper is to determine the reason for the discrepancy in estimated and observed damage caused by fragmenting charges in closed environments.

A series of carefully conducted physical and numerical experiments was conducted. The results were analyzed and compared.

The analysis shows that for fragmenting charges in closed environments, dust plays a far larger role than previously thought, leading to much lower pressures and damage.

In light of these findings, many assumptions and results for fragmenting charges in closed environments need to be reconsidered.

This implies that for a far larger class of problems than previously estimated it is imperative to take into consideration dust production and its effect on the resulting pressures.

This is the first time such a finding has been reported in this context.