In this paper, an innovative solution to minimize noise emission, acting on the flow ripple, in a prototype External Gear Pump (EGP) is presented. Firstly, a new tool capable to completely simulate this pump’s typologies, called EgeMATor, is presented; the hydraulic model, adopted for the simulation, is based on a lumped parameter method using a control volume approach. Starting from the pump drawing, thanks to different subroutines developed in different environments interconnected, it is possible to analyze an EGP. Results have been compared with the outputs of a three-dimensional CFD numerical model built up using a commercial code, already used with success by the authors. In the second section, an innovative solution to reduce the flow ripple is implemented. This technology is called Alternative Capacitive Volumes (ACV) and works by controlling and uniformizing the reverse flow, performing a consistent reduction of flow non-uniformity amplitude. In particular, a high reduction of the flow non-uniformity is notable in the frequency domain on the second fundamental frequency. The technology is easy to accommodate in a pump housing, especially for high-pressure components, and it helps with reducing the fluid-borne noise.

This research presents a lumped parameter numerical model aimed at designing and optimizing an axial piston pump. For the first time, it has been shown that a lumped parameter model can accurately model axial piston pump dynamics based on a comparison with computational fluid dynamic (CFD) models and experimental results. Since the method is much more efficient than CFD, it can optimize the design. Both steady-state and dynamic behaviors have been analyzed. The model results have been compared with experimental data, showing a good capacity in predicting the pump performance, including pressure ripple. The swashplate dynamics have been investigated experimentally, measuring the dynamic pressure which controls the pump displacement; a comparison with the numerical model results confirmed the high accuracy. An optimization process has been conducted on the valve-plate geometry to control fluid-born noise by flow ripple reduction. The nonlinear programming by quadratic Lagrangian (NLPQL) algorithm is used since it is suitable for this study. The objective function to minimize is the well-known function, the nonuniformity grade (NUG), a parameter directly correlated with flow ripple. A prototype of the best design has been realized and tested, confirming a reduction in the pressure ripple. An endurance test was also conducted. As predicted from the numerical model, a significant reduction of cavitation erosion was observed.

The performance of spool valves can deteriorate and noise can occur due to cavitation. The noise sound levels caused by cavitation are influenced by many parameters, among which the most important is not-optimal geometry of components. In this article, a two ways—two positions directional control valve was studied using experimental and numerical approaches. Tests were performed on a plexiglass body and steel spool analyzing the cavitating area that develops in U-notches. A dedicated test rig was equipped with a high-speed camera placed directly in front of the area of interest where cavitation occurs. Different working conditions were tested by varying the upstream pressure to encourage the development of cavitation. Images were acquired and postprocessed, focusing the contour extraction between the liquid and gaseous phases. The images were compared with results from three-dimensional computational fluid dynamic numerical simulations performed using commercial software. The numerical estimation of flow characteristics corroborated the results from investigations carried out using a fast camera, including periodic cavitation structures. This study demonstrates the importance and usefulness of using a three-dimensional computational fluid dynamic approach during the prototyping phase to create quieter component designs

The aviation sector is firmly committed to reducing harmful emissions and electric propulsion promises to tackle both pollution and noise at the same time. More Electric Aircrafts are progressively giving way to full electric aircraft that are expected to represent the next revolution in aviation. As is known, electric propulsion can be based on different electrochemical sources; nowadays, the widely used systems are developed on lithium battery packs, especially in automotive, where requirements in terms of gravimetric and volumetric energy densities are not so stringent compared to the aeronautical sector. Systems based on hydrogen fuel cells exhibit better performance in terms of range and endurance. In this article, a numerical study is presented on a lightweight electric aircraft, whose battery-based architecture is converted to a fuel cell-based architecture with the contribution of a battery pack that essentially intervenes in the take-off phase and, in addition, of a pack of ultracapacitors to prevent high discharge rate of the battery. The final intent is to explore the range extension without an increase in maximum take-off weight. The lumped parameter numerical models of the two propulsion systems have been developed in Simcenter Amesim where a set of simulations has been launched. It is shown that even under the constraint on the maximum take-off weight a significant extension of the range is obtained when adopting an electric propulsion system based on hydrogen fuel cells.

The objective of this paper is to show how a completely virtual optimization approach is useful to design new geometries in order to improve the performance of industrial components, like valves. The standard approach for optimization of an industrial component, as a valve, is mainly performed with trials and errors and is based on the experience and knowledge of the engineer involved in the study. Unfortunately, this approach is time consuming and often not affordable for the industrial time-to-market. The introduction of computational fluid dynamic (CFD) tools significantly helped reducing time to market; on the other hand, the process to identify the best configuration still depends on the personal sensitivity of the engineer. Here a more general, faster and reliable approach is described, which uses a CFD code directly linked to an optimization tool. CAESES^® associated with SimericsMP+^® allows us to easily study many different geometrical variants and work out a design of experiments (DOE) sequence that gives evidence of the most impactful aspects of a design. Moreover, the result can be further optimized to obtain the best possible solution in terms of the constraints defined.