The Program is taking shape.

If a component in the aerospace sector is fatigue-critical, subjected to high stresses, or classified as safety-critical, it is highly likely to have undergone shot peening. The shot peening process involves bombarding the workpiece surface with small spherical media (shots) accelerated by pressurized air. The localized plastic deformation caused by the impact of these shots induces compressive residual stresses and enhances surface integrity.

A key parameter, referred to as “coverage,” is defined as the percentage of the surface area that has been plastically deformed by at least one shot, thereby indicating the completeness of the treatment. The presented novel models consider several input parameters — including machine geometry, air pressure, and nozzle geometry — to accurately simulate shot trajectories. These models can subsequently be employed to optimize robotic path planning, achieve homogeneous surface coverage, and predict the resulting residual stress distribution after the peening process.

This paper presents a novel simulation framework for oil cooling systems characterized by wall-flows and free-flows. A coupled Moving Particle Semi-implicit – Finite Volume Method is introduced to accurately resolve wall-flows, while a simplified Moving Particle Semi-implicit approach is adopted for the free-flow regions. Given the well-known limitations of the method in capturing wall-flow behavior with sufficient accuracy, the study demonstrates that the proposed coupled methodology restores solution precision in these critical regions.

Several modeling strategies are evaluated, and the most reliable approach is identified as a function of technology maturity. The validity of the methodology is assessed through experimental testing, with quantitative and qualitative comparisons between numerical and experimental results — showing excellent agreement. Finally, practical observations are provided to guide the design and proper operation of the considered cooling system.

Thermal analysis of a reciprocating pump operating at a fixed working point. The objective is to identify potential hot spots within the system and to verify that the resulting thermal levels remain within acceptable limits for the piston seals.

The first phase consists of an isothermal sloshing analysis of the oil inside the pump housing, used to compute the heat transfer coefficient (HTC) distribution on the internal walls — subsequently applied as a boundary condition in the second phase. The second phase is a steady-state conjugate heat transfer (CHT) analysis: frictional losses from the dynamic analysis of the crank mechanism are applied to the relevant contact regions as heat sources, and heat transfer is evaluated between the solid components, the external environment, and the prescribed HTC and temperature boundary conditions. CFD results are compared and validated against experimental thermocouple measurements.

Hydropower is essential for grid stability but faces growing challenges from increased sediment transport driven by climate change, which induces erosion affecting turbine efficiency, wear, and maintenance costs. Pelton turbines are particularly vulnerable, with nozzle tips and runner buckets suffering erosion-related efficiency losses. Predicting such losses with traditional CFD is difficult due to complex free-surface, high-velocity flows and rotating components.

Meshless methods, especially Moving Particle Simulation (MPS), offer promising alternatives enhanced by GPU computing. This study uses scans of real erosion geometries from runners at different life stages (new, mid-life, end-of-life). Simulations at best efficiency conditions with a single jet configuration show torque drops of 6% and 6.6% for mid-life and end-of-life runners. The findings confirm the capability of MPS to accurately capture performance losses due to realistic erosion patterns. Future work will focus on experimental validation and scaling the methodology to larger Pelton turbines.

The calculation of the heat transfer coefficient (HTC) in Particleworks provides a new way of quickly estimating convective HTCs on bearing components. These HTCs are coupled with SKF internal tools such as BEAST to calculate bearing temperatures, enhancing the accuracy and robustness of bearing thermal analysis.

This work presents a detailed evaluation of Particleworks' capability to predict HTCs under flow conditions relevant to rolling-element bearings. Simplified benchmark cases were considered, including heat transfer on a sphere in a uniform flow and between rotating concentric cylinders (Taylor vortices). Particleworks results are compared with well-established HTC correlations from the literature as well as solutions from ANSYS Fluent. The findings contribute to SKF's ongoing efforts to improve the thermal modelling capabilities of rolling bearings.

Air entrainment in oils is a critical factor influencing the efficiency, reliability and lifetime of gearings and hydraulic systems. This contribution presents a direct air-in-oil measurement approach based on optical machine vision, enabling the direct detection and quantification of air bubbles in lubricants and hydraulic fluids. A central objective is to generate reliable measurement data that can be transferred from laboratory investigations to field applications — providing the physical input needed to describe real air-in-oil behavior in simulations more accurately.

By connecting direct optical measurements with simulation models, uncertainties in assumptions and boundary conditions can be reduced, improving the prediction of system behavior under aerated oil conditions. The availability of validated measurement data can also reduce the number of required simulation and design-iteration steps, making development faster while supporting optimized efficiency and reliability. Overall, the approach highlights how direct air-in-oil measurement can serve as an enabler for accurate simulation, condition monitoring and system optimization.

In the context of undercarriage systems engineering, the continuous increase in operational speeds and applied loads requires increasingly advanced design strategies to ensure maximum component reliability and operator safety. One of the most critical components is the track/carrier roller, which is subjected not only to severe mechanical wear but also to overheating induced by internal friction and interaction with adjacent components.

This study presents an analysis model to evaluate the lubrication of a carrier roller, investigating both fluid-dynamic and thermal aspects. Field operating conditions were considered and replicated within the model to analyze the lubricant's behavior inside the roller layout. The model was validated through bench testing, where roller temperatures were monitored up to thermal convergence; a comparison between these experimental measurements and the proposed CFD model results showed good correlation.

Gear lubrication in gearboxes is a critical design aspect; however, the oil behavior involving splashing and churning is highly complex, making it difficult to evaluate in the early design stage using conventional analytical approaches or CFD.

Particleworks is well suited for simulating free-surface flows and can effectively handle the oil churning behavior caused by gears. Taking advantage of this capability, it has been applied to lubrication studies in the early design phase. As a result, visualization of lubrication conditions and comparison between design options have become possible, contributing to improved evaluation efficiency.

In parallel with these applications, the effects of airflow on gear lubrication are being investigated as part of ongoing R&D activities. In this presentation, the details of these efforts will be introduced.

Air entrainment in gear oils significantly affects lubrication performance, efficiency and durability in electric drivetrains. This study investigates the formation, transport, coalescence and dissolution of air bubbles in the gear oil of an electric 3-speed commercial vehicle drivetrain using the IAV Particle Explorer.

High-speed imaging and particle-based analysis enable a detailed quantification of bubble dynamics under representative operating conditions. The results reveal characteristic bubble size distributions, preferred transport paths within the transmission and dissolution behavior.

The findings provide valuable insights into air–oil interaction mechanisms and support the optimization of transmission design, lubrication systems and overall drivetrain efficiency.