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This study aims to investigate the rarefaction effects on flow and thermal performances of an equivalent sand-grain roughness model for aerodynamic thrust bearing.

In this study, a model of gas lubrication thrust bearing was established by modifying the wall roughness and considering rarefaction effect. The flow and lubrication characteristics of gas film were discussed based on the equivalent sand roughness model and rarefaction effect.

The boundary slip and the surface roughness effect lead to a decrease in gas film pressure and temperature, with a maximum decrease of 39.2% and 8.4%, respectively. The vortex effect present in the gas film is closely linked to the gas film’s pressure. Slip flow decreases the vortex effect, and an increase in roughness results in the development of slip flow. The increase of roughness leads to a decrease for the static and thermal characteristics.

This work uses the rarefaction effect and the equivalent sand roughness model to investigate the lubrication characteristics of gas thrust bearing. The results help to guide the selection of the surface roughness of rotor and bearing, so as to fully control the rarefaction effect and make use of it.

This study aims to investigate the potential of the decorated boron nitride nanocage (BNNc) with transition metals for capturing carbon monoxide (CO) as a toxic gas in the air.

BNNc was modeled in the presence of doping atoms of titanium (Ti), vanadium (V), chromium (Cr), cobalt (Co), copper (Cu) and zinc (Zn) which can increase the gas sensing ability of BNNc. In this research, the calculations have been accomplished by CAM–B3LYP–D3/EPR–3, LANL2DZ level of theory. The trapping of CO molecules by (Ti, V, Cr, Co, Cu, Zn)–BNNc has been successfully incorporated because of binding formation consisting of C → Ti, C → V, C → Cr, C → Co, C → Cu, C → Zn.

Nuclear quadrupole resonance data has indicated that Cu-doped or Co-doped on pristine BNNc has high fluctuations between Bader charge versus electric potential, which can be appropriate options with the highest tendency for electron accepting in the gas adsorption process. Furthermore, nuclear magnetic resonance spectroscopy has explored that the yield of electron accepting for doping atoms on the (Ti, V, Cr, Co, Cu, Zn)–BNNc in CO molecules adsorption can be ordered as follows: Cu > Co >> Cr > Zn ˜ V> Ti that exhibits the strength of the covalent bond between Ti, V, Cr, Co, Cu, Zn and CO. In fact, the adsorption of CO gas molecules can introduce spin polarization on the (Ti, V, Cr, Co, Cu, Zn)–BNNc which specifies that these surfaces may be used as magnetic-scavenging surface as a gas detector. Gibbs free energy based on IR spectroscopy for adsorption of CO molecules adsorption on the (Ti, V, Cr, Co, Cu, Zn)–BNNc have exhibited that for a given number of carbon donor sites in CO, the stabilities of complexes owing to doping atoms of Ti, V, Cr, Co, Cu, Zn can be considered as: CO →Cu–BNNc >> CO → Co–BNNc > CO → Cr–BNNc > CO → V–BNNc > CO → Zn–BNNc > CO → Ti–BNNc.

This study by using materials modeling approaches and decorating of nanomaterials with transition metals is supposed to introduce new efficient nanosensors in applications for selective sensing of carbon monoxide.

Gas insulated systems, such as gas insulated lines (GIL), use insulating gas, mostly sulfur hexalfluoride (SF₆), to enable a higher dielectric strength compared to e.g. air. However, under high voltage direct current conditions, charge accumulation and electric field stress may occur, which may lead to partial discharge or system failure. Therefore, numerical simulations are used to design the system and determine the electric field and charge distribution. Although the gas conduction shows a more complex current–voltage characteristic compared to solid insulation, the electric conductivity of the SF₆ gas is set as constant in most works. The purpose of this study is to investigate different approaches to address the conduction in the gas properly for numerical simulations.

In this work, two approaches are investigated to address the conduction in the insulating gas and are compared to each other. One method is an ion-drift-diffusion model, where the conduction in the gas is described by the ion motion in the SF₆ gas. However, this method is computationally expensive. Alternatively, a less complex approach is an electro-thermal model with the application of an electric conductivity model for the SF₆ gas. Measurements show that the electric conductivity in the SF₆ gas has a nonlinear dependency on temperature, electric field and gas pressure. From these measurements, an electric conductivity model was developed. Both methods are compared by simulation results, where different parameters and conditions are considered, to investigate the potential of the electric conductivity model as a computationally less expensive alternative.

The simulation results of both simulation approaches show similar results, proving the electric conductivity for the SF₆ gas as a valid alternative. Using the electro-thermal model approach with the application of the electric conductivity model enables a solution time up to six times faster compared to the ion-drift-diffusion model. The application of the model allows to examine the influence of different parameters such as temperature and gas pressure on the electric field distribution in the GIL, whereas the ion-drift-diffusion model enables to investigate the distribution of homo- and heteropolar charges in the insulation gas.

This work presents numerical simulation models for high voltage direct current GIL, where the conduction in the SF₆ gas is described more precisely compared to a definition of a constant electric conductivity value for the insulation gas. The electric conductivity model for the SF₆ gas allows for consideration of the current–voltage characteristics of the gas, is computationally less expensive compared to an ion-drift diffusion model and needs considerably less solution time.

This paper investigates the impact of CO2 vs CO2 “equivalents” (CO2e) by analyzing fugitive emissions, with a particular focus on Fluorinated gases (F-gases), arising from refrigerant leakages in buildings. F-gases are an especially powerful set of GHGs with a global warming potential hundreds to thousands of times greater than that of CO2.

The significant impact of CO2e is tested by means of an empirical study with current consumption data from German food retail warehouses. This evaluation involves the analysis of the Carbon Risk Real Estate Monitor's country- and property-type specific pathway, coupled with a paired samples t-test to examine the hypotheses. The assessment is undertaken by evaluating the type of gas and the amount of leakage reported in the baseline year, subsequently converting these values to CO2e units.

On average, F-gases account for 40% of total building emissions and nearly 45% of cumulative emissions until 2050. In light of ongoing climate change and the rising number of Cooling Degree Days (CDDs), it becomes imperative to assess both the environmental and economic impact of F-gases and to transition toward environmentally friendly refrigerants.

The analysis sheds light on the seldom-addressed threats posed by CO2e emissions stemming from refrigerant losses. By identifying these threats, investors can devise strategies to mitigate potential future costs and carbon risks.

Gas transmission pipelines are at constant risk of gas leakage or fire due to various atmospheric environments, corrosion on pipe metal surfaces and other external factors. This study aims to reduce the human and financial risks associated with gas transmission by regularly monitoring pipeline performance, controlling situations and preventing disasters.

Facility managers can monitor the status of gas transmission lines in real-time by integrating sensor information into a building information modeling (BIM) 3D model. Using the Monitoring Panel plugin, coded in C# programming language and operated through Navisworks software, the model provides up-to-date information on pipeline safety and performance.

By collecting project information on the BIM and installing critical sensors, this approach allows facility manager to observe the real-time safety status of gas pipelines. If any risks of gas leakage or accidents are identified by the sensors, the BIM model quickly shows the location of the incident, enabling facility managers to make the best decisions to reduce financial and life risks. This intelligent gas transmission pipeline approach changes traditional risk management and inspection methods, minimizing the risk of explosion and gas leakage in the environment.

This research distinguishes itself from related work by integrating sensor data into a BIM model for real-time monitoring and providing facility managers with up-to-date safety information. By leveraging intelligent gas transmission pipelines, the system enables quick identification and location of potential hazards, reducing financial and human risks associated with gas transmission.