The high efficiency, low cost, and reduced pollution advantages of prefabricated buildings have resulted in the construction market fully realizing the efficiency and advantages of prefabricated building construction in emergency situations. When COVID-19 broke out in China in 2020, Huoshenshan Hospital and Leishenshan Hospital were built in only 10 days. With the rapid development of China’s economy, the level of urbanization is further accelerating and prefabricated construction is rapidly developing owing to its advantages of low carbon emissions, environmental efficiency, high technological content, and management innovation. The findings of this study can provide a theoretical basis for the rational planning of evacuation passages at the construction sites of prefabricated buildings and assist the management of construction site safety. Because it is required that the safety evacuation time (T REST) < available safe evacuation time (T ASET), the results are in line with the emergency evacuation requirements. The results of the second simulation reveal that the safe evacuation time (T REST) is 355.2 s. The evacuation time can be effectively reduced by re-planning the stacking positions of prefabricated construction site components, construction equipment, and other items, and reducing the number of personnel in the construction plane. The required safe evacuation time (T REST) > available safe evacuation time (T ASET), and the original site layout cannot facilitate the safe evacuation of all construction workers. The first emergency evacuation simulation took 398.7 s. The crashing time of the building was 360 s, which is the critical point for casualties. At 400 s, the visibility at the escape exit of the prefabricated apartment construction site was lower than 5 m. The data collected by the temperature sensor, CO concentration sensor, and visibility sensor reveal that the visibility and crash time are the key factors restricting the efficiency of personnel avoidance and evacuation. The time required for safe evacuation was determined and the factors influencing the evacuation time, such as the quantity and location of stacked prefabricated components, machinery, and appliances, and the number of on-site construction personnel, were analyzed.
#Pyrosim multiple grid sizes software
Moreover, the Pathfinder software was used for simulation in combination with the physical attributes of personnel, evacuation speed, and personnel proportions. The variation rules of smoke visibility, CO concentration, and ambient temperature in the construction site of prefabricated buildings were analyzed and the available safe evacuation time was determined. To ensure the safe construction of prefabricated buildings and improve the efficiency of the safe evacuation of construction personnel after a fire caused by improper operation during construction, this study used the PyroSim software to numerically simulate a fire situation based on the size and volume of a prefabricated building construction site. Now mock up some simple dummy data to save to our file. We first load the numpy and h5py modules. Getting h5py is relatively painless in comparison, just use your favourite package manager. You’ll need HDF5 installed, which can be a pain. We’ll create a HDF5 file, query it, create a group and save compressed data. Here’s a quick intro to the h5py package, which provides a Python interface to the HDF5 data format. It provides parallel IO, and carries out a bunch of low level optimisations under the hood to make queries faster and storage requirements smaller. It’s a powerful binary data format with no upper limit on the file size. The kinds of cosmological simulations that I run generate huge amounts of data, and to analyse them I need to be able access the exact data that I want quickly and painlessly. If you’re storing large amounts of data that you need to quick access to, your standard text file isn’t going to cut it.