Linde (Germany)

Antibiotic-loaded cement spacers play a crucial role in two-stage revision arthroplasty of infected total hip and knee prostheses. There is still controversy regarding whether the elution from antibiotic-loaded cement spacers is greater than the MIC for a prolonged time between stages. Therefore, the aim of the current review was to determine how long spacers elute antibiotics above the MIC for most causative microorganisms, as well as to evaluate what factors influence that elution. Independent of methodological differences and weaknesses of the studies themselves, several study results indicate that after an early peak of antibiotic release from the spacer in the first 1 to 2 days (followed by a gradual decline), a sufficient release above the MIC for most causative bacteria continues for 6 to 12 weeks.

Abstract The electrification of process heat generation will be a key to achieving carbon neutrality in the coming decades. One of the most promising approaches is to replace conventional heat supply systems with high-temperature heat pumps (HTHPs). A promising heat pump concept is based on the reverse Rankine cycle that uses water as its working fluid. By using turbomachinery for the compression process in this cycle, the performance of the HTHP can be increased compared to the volumetric displacement systems, like screw or piston compressors. Although the design of the compressor geometry can be done sequentially in relation to the HTHP cycle design, better results can be obtained by an approach that integrates turbomachinery and the thermodynamic cycle design. Against this background, an automated optimization method for a reverse Rankine HTHP with two radial turbo-compressors in series is presented. In contrast to the current state of the art, the presented novel optimization approach uses 3D computational fluid dynamics data to calculate the compressor’s performance. Furthermore, the integration of low-fidelity compressor specific reduced-order models are used to accelerate the gradient-free optimization process by a CO-Kriging surrogate model. The advantages of the novel approach are justified by comparing the numerical effort and the final values of the optimization objectives.

Abstract Today, the distribution of liquid hydrogen (LH2) from the liquefier facility to the consumer is almost entirely performed by road trailers. Significant growth in the global LH2 production in recent years demands efficient processes in the distribution chain. To minimize the losses in today’s LH2 supply chain, as well as for an efficient future LH2 infrastructure, it is essential to understand the underlying thermodynamic processes. In this work, the LH2 distribution by trailer is explained and the different occurring process steps are defined. Two rigorous models based on first principle are introduced to describe the thermodynamic extrema of complete phase-equilibrium and adiabatic separation of the gaseous and the liquid phase in the trailer. By performing two simulations of a generic LH2 trailer distribution route, the study aims to explore these thermodynamic boundaries and their influence on the losses.

Abstract In the second part of this three-paper series, high-fidelity simulations of the transonic cascade TEAMAero at the aerodynamic design point with Rein=1.35×106 and Main=1.21 are presented. A high-order discontinuous Galerkin spectral element method with finite-volume subcell shock capturing is employed to simulate the flow based on an implicit large eddy simulation (LES) scheme and advanced over several buffeting cycles to reliably capture the shock unsteadiness. A study on the spanwise domain size shows that the shock oscillation amplitude decreases with increasing span, although its frequency and mean location remain fixed through the simulations. By comparing high- and low-resolution LES results, it is further presented that deviations from under-resolution are mostly limited to the separated region past the shock, where the high-fidelity results match experimental results more closely. In addition to the LES, low-fidelity unsteady Reynolds-averaged Navier–Stokes is shown to capture the shock unsteadiness correctly, but at a reduced amplitude and fails to match the force distributions on the blade surface. Through examination of instantaneous flow features, space–time relations and spectral proper orthogonal decomposition, a basic analysis of the shock–boundary layer interaction is presented and indicates that velocity perturbations travel upstream through the subsonic boundary layer and periodically cause oblique shock waves, transporting the information from the boundary layer into the passage.

In model predictive control, fully data-driven prediction models can be used besides common (non-)linear prediction models based on first-principles. Although no process knowledge is required while relying only on sufficient data, they suffer in their extrapolation capability which is shown in the present work for the control of an air separation unit. In order to compensate for the deficits in the extrapolation behavior, a further data source, here a digital twin, is deployed for additional data generation. The plant data set is augmented with the artificially generated data giving rise to a hybrid model in terms of data generation. It is shown that this model can significantly improve the prediction quality in former extrapolation areas of the plant data set. Even conclusions about the uncertainty behavior of the prediction model can be found.

In path planning, anytime almost-surely asymptotically optimal planners dominate the benchmark of sampling-based planners. A notable example is Batch Informed Trees (BIT*), where planners iteratively determine paths to batches of vertices within the exploration area. However, utilizing a consistent batch size is inefficient for initial pathfinding and optimal performance, it relies on effective task allocation. This paper introduces Flexible Informed Trees (FIT*), a sampling-based planner that integrates an adaptive batch-size method to enhance the initial path convergence rate. FIT* employs a flexible approach in adjusting batch sizes dynamically based on the inherent dimension of the configuration spaces and the hypervolume of the n-dimensional hyperellipsoid. By applying dense and sparse sampling strategy, FIT* improves convergence rate while finding successful solutions faster with lower initial solution cost. This method enhances the planner’s ability to handle confined, narrow spaces in the initial finding phase and increases batch vertices sampling frequency in the optimization phase. FIT* outperforms existing single-query, sampling-based planners on the tested problems in R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> to R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">8</sup>, and was demonstrated on a real-world mobile manipulation task.

During the powder bed fusion of metals using a laser beam (PBF-LB/M), an inert atmosphere is maintained in the build chamber to avoid reactions of the liquid metal with ambient air leading to the creation of oxides or nitrides, which alter the mechanical properties of the processed part. A continuous gas flow is guided over the process zone to remove spatters and fumes. This flow induces a convective heat transfer from the molten metal to the gas, which, depending on the level of the heat flow, may alter the melt pool dimensions by influencing the cooling rate. The present work investigated these phenomena with single-line trials, both experimentally and numerically. For this reason, a smoothed-particle hydrodynamics model was utilized to investigate the temperatures of the melt pool, cooling rates, and the integral heat balance with various gas atmospheres. In parallel, an on-axis pyrometer was set up on an experimental PBF-LB/M machine to capture the surface emissions of the melt pool. The atmosphere in the simulations and experiments was varied between argon, helium, and two mixtures thereof. The results showed a slight increase in the cooling rates with an increasing fraction of helium in the process gas. Consistently, a slight decrease in the melt pool temperatures and dimensions was found.

The main objective of this work was to propose and evaluate a methodology for shielding-gas selection in additive manufacturing assisted by wire arc additive manufacturing (WAAM) with an austenitic stainless steel as feedstock. To validate the proposed methodology, the impact of multi-component gases was valued using three different Ar-based blends recommended as shielding gas for GMA (gas metal arc) of the target material, using CMT (cold metal transfer) as the process version. This assessment considered features that potentially affect the building of the case study of thin walls, such as metal transfer regularity, deposition time, and geometrical and metallurgical characteristics. Different settings of wire-feed speeds were conceived to maintain a similar mean current (first constraint for comparison's sake) among the three gas blends. This approach implied different mean wire-feed speeds and simultaneously forced a change in the deposition speed to maintain the same amount of material deposited per unit of length (second comparison constraint). The composition of the gases affects the operational performance of the shielding gases. It was concluded that by following this methodology, shielding-gas selection decision-making is possible based on the perceived characteristics of the different commercial blends.