## 1 Introduction  
A smoke detection system is one of the most critical pieces of equipment for detecting smoke early to reduce the danger of fire, as well as to reduce human casualties. A conventional smoke detector detects smoke from an incipient fire and triggers an alarm system. However, it has some specific problems. In extreme temperature environments, such as a cold warehouse or a hot aisle area, a conventional smoke detection system cannot be applied. In the cold warehouse, high-bay storage can affect the airflow and obstruct the detection and response to a fire event. Besides, the operating temperatures typically range between 8 \({}^{\circ}\)C to \(-\)40 \({}^{\circ}\)C resulting in cold storage environments exhibiting harsh climatic conditions. These extreme temperatures of refrigerated storage facilities are a primary challenge to detecting a cold store fire as most forms of conventional smoke detection are not designed to operate in harsh climatic environments. In addition, high airflows created by blast chiller units and condensation can impede the operation of conventional passive detectors too. For this reason, the aspirating smoke detector (ASD) system has been developed to detect smoke. ASD uses a pipe hole network to draw air from protected areas to the sensing chamber, so it has a quick response. At the sensing chamber, air samples are illuminated with a high intensity light source, which causes smoke particles to reflect light to a solid-state photoreceiver. At the detector, an analog signal is generated to the control unit, which displays the smoke obscuration sensitivity. The two main advantages of the ASD system are the use of the sensitivity setting for incipient fire detection and one ASD system can cover large areas by using the piping network. For the above reasons, research regarding aspirating smoke detection systems and pipe hole networks should be conducted to enhance the efficiency of the system as well as to reduce the transport time of smoke. There are many kinds of research relating to this system. [PERSON] et al. [1] performed a simulation of a sampling pipe hole network with an ASD. They also compared the values between numerical and experimental studies. In that paper, a mathematical model was built to apply a theory to calculate the flow rate and transport time. The results showed that the values from the mathematical model were in accordance with the experiment values. Furthermore, the pipe network has been investigated in many other systems in addition to aspirating smoke detection. [PERSON] et al. [2] investigated the pressure drop in pipelines for pneumatic systems. In that paper, a theoretical analysis was compared with an experimental study. The various upstream pressure and different internal diameters are also used to evaluate the pressure drop in the pipe system. The results showed that the experimental study and theoretical analysis were in good agreement. Nowadays, with the development of technology, numerical studies can also be applied to calculate the pressure loss in the pipe network. [PERSON] et al. [3] carried out a pressure loss analysis of air duct flow using Computational Fluid Dynamics (CFD). They determined the pressure loss in air ducts by hand calculation and computer simulation. The velocity in the pipe changed from 5 m/s to 10, 20, and 40 m/s, respectively. When the velocity increased, the pressure loss also increased. The results obtained from hand calculations and simulations were almost the same. Besides, [PERSON] et al. [4] and [PERSON] et al. [5] have considered the pressure loss coefficient of pipe fittings by CFD. The results were conclusive that a validated CFD model was a cheap and reliable tool for loss coefficient estimation of pipe fitting and complex fluid flow. [PERSON] [6] investigated the airflow in a network used in aspirated smoke detectors. The numerical and experimental study on the flow was carried out in this research.