Modelling, analysis and experimental verification of air disc brake used in heavy duty vehicles

This paper proposes a reliable mathematical model that can be used for design stage of new air disc brake (ADB) development projects. All three phases of braking mechanism (brake apply, brake release and automatic adjustment) are modelled by Matlab Simulink in consideration of hysteresis and adjuster performance experiments. Firstly, mathematical relations of each friction interfaces of air disc brake components are derived and mathematical equations adapted to the Simulink model. To ensure the accuracy of ADB system model, hysteresis and adjuster performance experiments are conducted on a prototype disc brake mechanism supported by a test fixture. This prototype single piston disc brake mechanism is fitted to wheel size in 17.5″ used in heavy commercial vehicles. The predicted clamping force, mechanical ratio, brake efficiency and adjuster rate results are verified by using experimental data. The maximum deviation in hysteresis results is 3.08%. Besides, the maximum deviation in adjuster performance results is 7.15%. The numerically and experimentally obtained hysteresis and adjuster performance results show good agreement. The proposed model is modified in consideration of mechanism supported by a brake calliper for predicting actual performance of single piston brake mechanism on the brake level. The hysteresis and the adjuster performance analyses are conducted by using modified ADB model to calculate the hysteresis based brake efficiency and the adjuster rate. The brake efficiency of new single piston brake design provides similar efficiency as the twin piston disc brake used in heavy commercial vehicles.

Gas Purging System to Extend Thrust Bearing Life in ESPs

Electric submersible pump (ESP) systems use thrust bearings in the seal section to handle the thrust generated by the pump stages. Thrust bearings are subjected to harsh operating conditions, including high loads, poor oil circulation, and motor oil viscosity degradation. A less-recognized issue is gas becoming centrifugally trapped under the thrust runner. The gas may be present because of incomplete purging of air during filling, permeation of well gas into the motor oil, or gradual gasification of motor oil at high temperatures. Because thrust bearings are such critical components, it is of interest to increase their reliability, which in turn will increase ESP life. A novel gas purging system (GPS) was designed to alleviate stressors on thrust bearings, including gas accumulation, viscosity deterioration and gasification at high temperature, and low working oil volume. GPS circulates oil along with any gas that accumulates under the thrust runner up to a quiet separation chamber. Degassed oil circulates back to the thrust bearing, while accumulated gas eventually purges to the wellbore through relief valves on subsequent on/off cycles. GPS also improves viscosity and reduces gasification by cooling the oil, and it provides a greater working volume of thrust bearing oil to reduce the effects of oil deterioration. This paper details the GPS design principles as well as the optimization of the different design parameters that affect its performance conducted via computational fluid dynamics (CFD). Observations captured on a test fixture built using the final configuration are also presented, validating the intended functionality.

Quantitative Demonstration of a High-Fidelity Oil-Based Mud Resistivity Imager Using a Controlled Experiment

The objective of this paper is to describe and validate a new approach for acquiring images that provides both qualitative and quantitative information on the formation electrical properties using a high-resolution, oil-based mud imager (HROBMI) tool. This new multifrequency imaging tool is able to function at high frequencies (in the MHz range) in oil-based muds. To allow for the quantitative estimation of formation and mud properties from the HROBMI data, a hybrid machine-learning/inversion approach was implemented. In this hybrid approach, machine-learning models corresponding to different candidate mud properties are trained, and the resulting regression functions are stored. For a given measurement data set, predictions of these different models are used to quickly identify an optimum mud candidate. This information is then fed into an inversion algorithm that provides accurate quantitative information on the logging environment of the HROBMI. The accuracy of this algorithm has been verified using a test fixture that enables the change of formation properties in different mud environments. The measurements from the HROBMI are a function of the formation properties: resistivity and permittivity, frequency, and mud properties. The hybrid algorithm can untangle HROBMI data from multiple frequencies to obtain true formation resistivity images independent of the other parameters that affect the tool measurements. In addition, the algorithm provides formation permittivity images as well as a standoff image. The results have been provided from both the controlled experiments in the test fixture and from field logs.

Experimental determination of the acoustical effects of face masks on speech effort

The COVID-19 pandemic has led to a global trend in mask wearing. This study investigates how wearing face masks influence the output levels of the human vocal range. Masks were equipped onto a test fixture to evaluate acoustic insertion loss over whole-octave bands important for vocal transmission. With the exception of face shield, tested masks showed less than 2 dB of insertion loss at frequencies less than 2 kHz and up to 5 dB of attenuation at frequencies above 2 kHz. The face shield showed insertion loss of more than 10 dB in the 4 and 8 kHz octave bands.