The paper presents the results of experimental-simulation tests of expansion-shrinkage phenomena occurring in cast iron castings. The tests were based on the standard test for inspecting the tendency of steel-carbon alloys to create compacted discontinuities of the pipe shrinkage type. The cast alloy was a high-silicone ductile iron of GJS -600 -10 grade. The validation regarding correctness of prognoses of the shrinkage defects was applied mostly to the simulation code (system) NovaFlow & Solid CV (NFS CV). The obtained results were referred to the results obtained using the Procast system (macro-and micromodel). The analysis of sensitivity of the modules responsible for predicting the shrinkage discontinuities on selected pre-processing parameters was performed, focusing mostly on critical fractions concerning the feeding flows (mass and capillary) and variation of initial temperature of the alloy in the mould and heat transfer coefficient (HTC) on the casting -chill interface.

Abstract:Cushioning is an important aspect in hydraulic cylinder performance. The piston has to be decelerated before it strikes the end cap in order to avoid stresses in the cylinder components and reduce vibration that can be transmitted to the machine. One of the least-studied methods is internal cushioning by grooves in the piston. In this method, the flow is throttled with adequately designed grooves when the piston reaches the outlet port position. The purpose of the present work is to present a method to estimate the pressure-drop coefficients for a certain design of piston grooves in order to provide a model to develop a dynamic system simulation of the cushion system. The method is based on a computational fluid dynamic simulation of flow through piston grooves to the outlet port for each piston's static position. The results are compared with experimental measurements, and a correction, based on Reynolds number, is proposed. Good agreement, below 16%, was obtained for all the positions but particularly for the last grooves, for which the numerical result's deviation to the experimental measurements was less than 10%. In general, the numerical simulation tended to underestimate the pressure drop for the first grooves and overestimate the calculation for the last grooves.

The fatigue of a hydraulic component inherently varies due to various factors that can be divided into two categories: structural and load spectrum variability. The effects of both variabilities must be considered when determining fatigue life. Compared with the structural variability, determining the variability in the load spectrums is more difficult because the service conditions are complicated and the measurements of the load parameters are slow and expensive. The problem that arises when studying the fatigue behaviour of such components is the transferability of short data samples from real-life load histories, which are application-dependant, to laboratory test methods. Derived from the experimental background and know-how of the authors, this paper proposes a methodology that allows the definition and establishment of the hydraulic cylinder design specificactions, while taking into account the probabilistic characterisation of the load spectrum variability. This methodology could be extrapolated to other hydraulic or mechanical components.

In recent years, much research has focused on reducing the power consumption of mobile hydraulic machines due to rising fuel costs, regulations on combustion engine emissions and the need to reduce the size and weight of the storage devices in hybrid drives. Current approaches to improve the energy efficiency of a hydraulic system can be classified into four basic groups: reduction of the energy demand, recovery of part of the supplied energy (ERS systems), regeneration of part of the supplied energy and reuse of the recovered and regenerated energy (hybrid systems). Today’s mobile hydraulic systems are often complex, perform different tasks and work under different load conditions, which makes it difficult to analyse energy losses. A study of the energy losses of a hydraulic system from different points of view, such as an energy balance for a complete machine cycle, an analysis of the individual cycle phases and a power analysis for the different operation quadrants of the actuators, can give an global picture of the energy losses, being very useful to rate its energy efficiency, identify main power losses and decide which of the different energy-saving techniques to apply. This paper describes the data collection process, its analysis from various points of view and the summary of the results in easy to understand charts as useful tools to identify and quantify the main energy losses. Only system architecture losses are considered. Losses in the ICE engine or the electric motor, hydraulic pump losses and mechanical losses are outside the scope of this study.

Mobile machinery manufacturers must face and deal with reducing fuel consumption, rising prices, and environmental pollution. The development of methods to evaluate the efficiency and effectiveness of the energy performance of hydraulically actuated systems has become a priority for researchers and OEMs, Original Equipment Manufacturers. In this paper, a new methodology that is based on Key Performance Indicators, KPI, is proposed with different goals: (i) to evaluate the energy performance and the monitoring of its evolution in the different stages of its life cycle (design, commissioning, optimization, retrofit, etc.); (ii) compare the energy levels between machines of different sizes and different brands in a benchmarking process; and (iii) establish a database that is state of the art, which facilitates setting achievable goals or limits for improvement. These KPI values can be deduced simply from the energy balances that were made from the experimental study of various machines over a relatively long period. This methodology has been applied to typical hydraulic systems for lifting and lowering loads that are used in a wide variety of mobile machines of different mechanical designs and sizes. Still, it can be included in the generic name of “loaders”. A KPI’s values for the three machines are presented in a dashboard as a decision-making tool.