An individualised 3D computational flow and particle model to predict the deposition of inhaled medicines - A case study using a nebuliser.

BACKGROUND AND OBJECTIVE: Drug inhalation is generally accepted as the preferred administration method for treating respiratory diseases. To achieve effective inhaled drug delivery for an individual, it is necessary to use an interdisciplinary approach that can cope with inter-individual differences. The paper aims to present an individualised pulmonary drug deposition model based on Computational Fluid and Particle Dynamics simulations within a time frame acceptable for clinical use. METHODS: We propose a model that can analyse the inhaled drug delivery efficiency based on the patient's airway geometry as well as breathing pattern, which has the potential to also serve as a tool for a sub-regional diagnosis of respiratory diseases. The particle properties and size distribution are taken for the case of drug inhalation by using nebulisers, as they are independent of the patient's breathing pattern. Finally, the inhaled drug doses that reach the deep airways of different lobe regions of the patient are studied. RESULTS: The numerical accuracy of the proposed model is verified by comparison with experimental results. The difference in total drug deposition fractions between the simulation and experimental results is smaller than 4.44% and 1.43% for flow rates of 60 l/min and 15 l/min, respectively. A case study involving a COVID-19 patient is conducted to illustrate the potential clinical use of the model. The study analyses the drug deposition fractions in relation to the breathing pattern, aerosol size distribution, and different lobe regions. CONCLUSIONS: The entire process of the proposed model can be completed within 48 h, allowing an evaluation of the deposition of the inhaled drug in an individual patient's lung within a time frame acceptable for clinical use. Achieving a 48-hour time window for a single evaluation of patient-specific drug delivery enables the physician to monitor the patient's changing conditions and potentially adjust the drug administration accordingly. Furthermore, we show that the proposed methodology also offers a possibility to be extended to a detection approach for some respiratory diseases.

Electromagnetic force investigation of electromagnets with variable pole area in an electromagnetic diaphragm pump.

Electromagnetic diaphragm pump is a kind of widely applied diaphragm pump that has promising sealing performance, simple structure and low power loss. Planar pole electromagnet is a significant component of the electromagnetic diaphragm pump. However, the sharply changing displacement-force characteristics of the planar pole electromagnet do not match the constant load characteristics of the electromagnetic diaphragm pump. Herein, an electromagnet with variable pole area is put forward. A theoretical relationship between structural parameters, the Ampere turns and the electromagnetic force of the electromagnet with variable pole area is determined by analyzing the equivalent magnetic circuit of the electromagnet with variable pole area. The experimental results imply that the initial electromagnetic force of the electromagnet with variable pole area is 32.51% larger than the planar pole electromagnet, the engaging electromagnetic force of the electromagnet with variable pole area is 22.3% smaller than the planar pole electromagnet and the displacement-force characteristics of the electromagnet with variable pole area match the constant load characteristics of the electromagnetic diaphragm pump.

Effects of operation conditions and suction pipeline parameters on flow characteristics and metering accuracy for selective catalytic reduction air-assisted urea dosing system.

Selective catalytic reduction is the main technology to reduce oxides of nitrogen of diesel exhaust. As an important part of the selective catalytic reduction system, the air-assisted urea dosing system regulates the flow rate by adjusting the pump speed, and the flow rate and its metering accuracy directly affect the efficiency of oxides of nitrogen conversion. A mathematical model coupled with the air-assisted urea dosing system and the suction pipeline was built, and the influences of the discharge pressure, pump speed, suction pipeline length, and diameter on the flow characteristics and metering accuracy of the air-assisted urea dosing system were analyzed. The flow rate and metering accuracy of a prototype of the air-assisted urea dosing system were tested under different conditions on a test rig. Results show that the flow stability and metering accuracy of the prototype elevate with increasing the discharge pressure when the prototype has no overfeeding, and it gets down under any discharge pressure when the prototype occurs overfeeding. The flow stability and metering accuracy of the prototype improve with increasing the pump speed, and increase significantly when the suction pipeline length becomes shorter and the diameter gets larger. The metering accuracy of the prototype can achieve to ±2% by optimizing the suction pipeline parameters. The experimental results prove that the proposed mathematical model is effective.