Browse Topic: Hoses and tubes
Static electricity is an electrical imbalance on the surface of a material which can interact with other components having same or different materials. Fluid flow within the hose assembly generates static voltage due to friction caused by fluid flow in pipes, that needs to be appropriately quantified and dissipated. Accumulation of such static charge may lead to sudden discharge leading to spark generation. Spark generation around fuel flow might lead to system failure and failure in aircraft engines. Test experiments were conducted to analyze static voltage generated in hose assembly due to fuel flow with the objective that voltage achieved is within the acceptable range to avoid ESD (Electrostatic Discharge) failure. Procedure includes flow rate monitoring and voltage measurement using fuel as test fluid. The testing revealed that the curvature of the hose affects the readings, highlighting the importance of consistent meter alignment. Using a grounding strap is essential to prevent electrical damage and ensure accurate reading. Other functional factors such as proper set up and cleaning methods are crucial were also studied. It's important to check electrical continuity using an ohmmeter before testing. Initial results showed static voltage values beyond acceptable limits which may have resulted in ESD failure. The readings were optimized through electrical grounding and changes in the cleaning process. The revised static voltage readings increased with the flow rate non-linearly emphasizing that voltage testing is critical for aircraft safety.
The outwash flow of a VTOL aircraft in near-ground operation is a serious risk for surrounding objects or personnel, and has been investigated for a long time. The current paper contributes to this topic by revisiting quantitative outwash measurement techniques and evaluation strategies suitable for full-scale flight experiments. An array of purpose-built ultrasonic anemometers, a pitot tube rake, and fiber-film sensors were applied during outwash tests with a hovering Eurocopter EC135, complemented by accompanying numerical simulations with the Vorticity Transport Model (VTM). A focus is set on an analysis of the flow unsteadiness, revealing large fluctuations at low frequencies which require careful data post-processing. The fluctuations limit the application of pitot tubes to measure the mean flow due to their angular sensitivity, and ultrasonic anemometers are recommended as a particularly suitable and convenient measurement method with a sufficient frequency response. Furthermore, the experimental and numerical results are compared to semi-empirical outwash models, and the importance of simultaneous measurements of the ambient wind conditions is demonstrated.
Industries are following a tedious product development cycle for developing their product. In product development major steps includes design ideas, Drawings, CAD, CAE, Testing and design improvement cycle. This is a monotonous process and takes time which impacts on its time to deliver product and cost on development. Now a days industries are fast growing and targeting to reduce development cycle time and cost. AI&ML is impacting almost all areas in the industry and significantly reducing efforts time and cost. To make use of AI&ML in CAE, Altair Physics AI is an effective tool. To ensure the design of product traditional way is to develop a CAD of the product, develop, perform CAE and analyze performance. If we consider CAE procedure it is time consuming process which includes FEA model build, applying boundary conditions, running simulation and analyzing results which could take minutes to hours. By using ML with Physics AI we can make predictions on new design of the product in seconds and significantly save time and cost. To demonstrate the CAE acceleration process with physic AI we have solved two case studies. The first case study is head impact on hood where ML tool will predict deformation contour of the hood, acceleration and displacement curve of the impactor. The second case study is Tube crush analysis where prediction of tube deformation pattern, force and energy curve for different tube length and impact velocity is carried out. For both Case studies we have used TCS inhouse data to train test and prediction of the ML model. For Head impact case study, it gives lower training loss with more than 90 percent prediction accuracy. Similarly for tube crush study it gives good accuracy and predicts comparable behavior patten with CAE results. Physic AI ML tool accelerates the design and development cycle and can be utilized in different product development. Implementation of ML accelerates the CAE process in design and development of products. It saves a lot of time in multiple design iteration study. Similar method can be implemented for different CAE cases.
A computational investigation was carried out using SimericsMP+ to analyze oil distribution and aeration behavior in a V6 engine oil pan during severe vehicle maneuvers. The model accounted for the crankshaft/camshaft rotations and piston motions, which allows for capturing realistic oil distribution in cylinder head drainbacks, engine bay and sump after initializing the crankcase with prescribed oil levels to establish baseline aeration prior to applying dynamic maneuver profiles. Of particular interest was the response of the main oil gallery (MOG) pressure and the exposure of the oil pickup tube during kickoff conditions at multiple fill levels. Both a baseline configuration and a modified sump featuring a containment “doghouse” were examined. Results obtained from the kickoff maneuver show complete uncovering of the pickup tube in the baseline design, leading to unstable lubrication. The first doghouse design only delayed pickup tube uncovering briefly, as oil pooled at the rear gap and air ingestion still occurred. Full fill avoids air ingestion; however, high interaction with the crank shaft results in higher oil aeration longer term after kickoff maneuver ends. The findings highlight the complexity of oil behavior in engine environments, where unpredictable interactions during dynamic maneuvers can easily lead to ingestion and aeration. Despite this complexity, the computational strategy developed in this study was able to accurately reproduce and predict these events which were seen in the test scenario as well in the form of pressure readings at the pump inlet. Since these high-aeration events were validated against experimental measurements, this simulation approach proves to be highly valuable for guiding product design and optimization, allowing engineers to identify risks early and improve lubrication performance in the engines before physical testing.
The global medical tubing market is enjoying strong growth, with analysts forecasting compound annual growth rates (CAGR) ranging from 6 to 9 percent over the next several years. Demand is being propelled by more-frequent or extended treatments for cancers and chronic diseases; increases in minimally or noninvasive surgery, home-based care, and patient wearables; and innovations such as sensor-enabled smart catheters and other advanced tubing applications.
The shift from batch to continuous bioprocessing is reshaping the way fluid handling systems are designed, specified, and validated in biopharmaceutical manufacturing. Continuous processing promises higher productivity, reduced footprint, and improved product consistency, but it also places new and sustained demands on every component in the fluid path. Among the most critical — and often underestimated — elements is peristaltic pump tubing.
In today's dynamic driving environments, reliable rear wiping functionality is essential for maintaining safe rearward visibility. This study sharing the next-generation rear wiper motor assembly that seamlessly integrates the washer nozzle, delivering improved performance alongside key benefits such as better Buzz, Squeak, and Rattle (BSR) characteristics, reduced system complexity, cost savings, and enhanced perceived quality. This integrated design simplifies the hose routing which improves the compactness and the efficiency of the design. This also enhances the spray coverage and minimizes the dry wiping unlike the traditional systems that position the washer nozzle separately. A non-return valve (NRV) is incorporated to eliminate spray delays ass it maintains consistent water flow giving cleaning effectiveness. Since this makes the nonfunctional parts completely leak proof due to the advanced sealing, it increases the durability and reliability in long run. As this proposal offers a sustainable solution, it can be considered as the new benchmark in rear wiper technology.
In this paper, a systematic and in-depth study is carried out on the key engineering problem of the accurate calculation of the flexural capacity of L-shaped concrete-filled steel tubular columns. Based on the basic framework of mechanics theory, the basic design principle of reinforced concrete members is integrated, and the nonlinear characteristics of steel and concrete materials in the process of stress are mainly considered, such as steel yield strengthening, concrete compression damage, etc., and the ultimate bending moment calculation model which is more suitable for the actual stress state is constructed. Through rigorous theoretical derivation and multi-parameter comparative analysis, the final formula for calculating the bearing capacity of special-shaped columns not only has clear mechanical concept support, but also systematically defines the scope of application of the calculation method. The verification results show that the established calculation method not only meets the requirements of the current engineering specifications, but also clarifies the influence of key factors such as section size, material strength and reinforcement ratio on the bearing capacity through parametric analysis. The calculation process has the rigor of the theoretical system and the convenience of engineering application: the designer only needs to input the geometric parameters of the component such as the section size, the thickness of the steel tube and the material properties such as the yield strength of the steel and the compressive strength of the concrete cube, and can directly apply the formula to complete the bearing capacity check, which greatly simplifies the traditional calculation process.
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