Experiments in Fluids最新文献

Droplet impact is a common phenomenon in daily life and various industrial applications. Previous research shows that surface geometry significantly influences impact outcomes. However, there is a gap in systematic research on how convex structures, similar in size to the droplet, influence impact behaviors. To address this, our study focused on producing various targets with different convexity to investigate the morphological evolution of droplet impact. Using high-speed imaging techniques, we examined these impacts with Weber numbers ranging from 5 to 346. The experimental results show that dry convex surfaces increase the maximum spreading diameter of droplets by altering liquid mass redistribution. Reduced air entrapment diminishes the circumferential instability of deformed droplets on these surfaces, as evidenced by fewer fingers formed. This study also proposes a hybrid model to predict the maximum spreading diameter on convex surfaces using the energy conservation method. Benefiting from models for flat surfaces, this new approach accounts for convex surface impacts, which alter the impact characteristics according to the convexity of the impact geometry. The model assumes that the droplet at its maximum spreading diameter resembles either a disc or a rim. Notably, the rim assumption was quite evident in several convex surface impacts, presenting a donut-shaped expansion. These results are combined through weighted summation The hybrid model’s predictions show a superior agreement with the experimental data compared to existing models. Additionally, the model’s weighting factors provide insights into the distribution of liquid mass between the central film and the surrounding rim.

Graphical abstract

In the past years, volumetric velocimetry measurements with helium-filled soap bubbles as tracer particles have been introduced in wind tunnel experiments and performed at large-scale, enabling the study of complex body aerodynamics. A limiting factor is identified in the field of wind engineering, where the flow around ships is frequently investigated. Considering multiple wind directions, the optical access for illumination and 3D imaging rapidly erodes the measurement regions due to shadows and incomplete triangulation. This work formalizes the concepts of volumetric losses and camera redundancy, and examines the performance of multi-directional illumination and imaging for monolithic and partitioned modes. The work is corroborated by experiments around a representative ship model. The study shows that a redundant system of cameras yields the largest measurement volume when partitioned into subsystems. The 3D measurements employing two illumination directions and seven cameras, yield the time-averaged velocity field around the ship. Regions of flow separation and recirculation are revealed, as well as sets of counter-rotating vortices in several stations from the ship bow to the flight–deck. The unsteady regime at the flight–deck is examined by proper orthogonal decomposition, indicating that the technique is suited for the analysis of large-scale unsteady flow features.

Experimental and numerical simulation of launcher base flows are crucial for future launcher design. In experiments, exhaust plume simulation is often limited to cold or slightly heated gases. In numerical simulations, multi-species reactive flow is often neglected due to limited resources. The impact of these simplifications on the relevant flow features, compared to real flight scenarios, needs to be characterized in order to enhance the design process. Experimental and numerical investigations were carried out within the framework of the SFB/TRR 40 Collaborative Research Centre to study the impact of plume and wall temperature on the base flow of a generic small-scale launcher configuration. Wind tunnel tests were performed in the Hot Plume Testing Facility (HPTF) at DLR, Cologne, using subsonic ambient flow and pressurized air or hydrogen–oxygen combustion as exhaust gases. The tests were numerically rebuilt using the DLR TAU code employing a scale-resolved IDDES approach, including thermal coupling and detailed chemistry. The paper combines the experimental and numerical findings from the SFB/TRR 40 base flow studies and highlights the most prominent influences on the mean flow field, the pressure field, the dynamic wake flow motion, and the resulting aerodynamic forces on the nozzle. High-frequency pressure measurements, high-speed schlieren recordings, and time-resolved CFD results are evaluated using spectral and modal analysis of the one- and two-dimensional flow field data.

Dynamic pressure measurements are indispensable in the field of fluid mechanics. Attaching tubing as a transmission line to the pressure transducer is often unavoidable but significantly reduces the usable bandwidth of the measurement system. Complex fluid-wall interactions and potential outgassing of air are present within systems with water-filled tubes. Comprehensive studies aiding researchers in selecting suitable transmission line parameters (i.e., material, length, and diameter) are not available. A simple calibration apparatus is designed for the frequency response characterization of multiple pressure transducers simultaneously applying a pressure step. The setup is thoroughly characterized and a detailed description is provided to optimize the bandwidth. A piezoresistive pressure transducer attached to water-filled tubes, as commonly used in hydrodynamic experiments, is characterized in the low-frequency range (i.e., (f le {300}) Hz). Tube-related effects, such as length, diameter, and material are investigated. The impact of entrapped air within the tubing is analyzed. The feasibility of substituting water with silicone oil to fill the tubes is explored. To optimize the usable bandwidth of the pressure measurement system for dynamic applications, it is essential to maintain short tubing that is as rigid as possible and free from entrapped air. Pressure wave propagation speed is reduced by two orders of magnitude in elastic transmission lines made of silicone. Pressure corrections through dynamic calibration are challenging due to the system’s sensitivity to various parameters affecting the dynamic response.

High spatial resolution and high accuracy estimation of 3D velocity fields are important for tomographic particle image velocimetry (Tomo-PIV), especially when measuring complex flow fields with delicate 3D structures. However, the widely used cross-correlation-based methods have limited spatial resolution, while the recently developed optical flow-based methods have low robustness and are sensitive to particle volume reconstruction errors. Therefore, 3D velocity estimation methods that simultaneously exhibit high resolution and robustness must be developed. In this study, we propose a novel velocity estimation method for Tomo-PIV measurement using the guided filter-based 3D hybrid variational optical flow (GF-HVOF) method to achieve high spatial resolution and highly accurate measurement of 3D flow field structure. First, we propose a novel L1-norm regularization term based on the Helmholtz decomposition theorem to preserve the divergence and vorticity of the fluid flow. Second, we propose a guided-filter-based constraint term using the result of the cross-correlation-based method as the guided flow field to improve the robustness of the optical flow method. Third, we propose a hybrid constraint term based on particle tracking velocimetry (PTV) method and a spatially weighted data term to reduce the effect of ghost particles and discrete errors generated during the reconstruction of particle volumes. The newly proposed hybrid method combines the advantages of optical-flow-based and cross-correlation-based methods and corrects the flow field using the PTV method. Velocity fields are estimated over synthetic and experimental particle volumes. The results show that the newly proposed GF-HVOF method achieves better performance and greater measurement accuracy than existing 3D fluid motion estimation methods.

The intermittency characteristics in transitional and turbulent flows can provide critical information on the underlying mechanisms and dynamics. While time–frequency (TF) analysis serves as a valuable tool for assessing intermittency, existing methods suffer from resolution issues and interference artifacts in the TF representation. As a result, no suitable or accepted methods currently exist for assessing intermittency. In this work, we address this gap by presenting a novel TF method—a Fourier-decomposed wavelet-based transform—which yields improved spatial and temporal resolution by leveraging the advantages of both integral transforms and data-driven mode decomposition-based TF methods. Specifically, our method combines a Fourier-windowing component with wavelet-based transforms such as the continuous wavelet transform (CWT) and superlet transform, a super-resolution version of the CWT. Using a peak-detection algorithm, we extract the first, second, and third most dominant instantaneous frequency (IF) components of a signal. We compared the accuracy of our method to traditional TF methods using analytical signals as well as an experimental particle image velocimetry (PIV) dataset capturing transition to turbulence in pulsatile pipe flows. Error analysis with the analytical signals demonstrated that our method maintained superior resolution, accuracy, and, as a result, specificity of the instantaneous frequencies. Additionally, with the pulsatile flow dataset, we demonstrate that IF components of the fluctuating velocities extracted by our method decompose energy cascade components in the flow. Additional investigations into corresponding spatial frequency structures resulted in detailed observations of the inherent scaling mechanisms of transition in pulsatile flows.

One way to increase the thermal efficiency of heat exchangers is to structure the heat transfer surfaces with dimples, resulting in an enlarged surface area and intensified turbulence in the fluid flow. The increased turbulence also causes higher wall shear stress, which potentially suppresses the deposition of particles and supports a self-cleaning of the surface. For a deeper understanding of these phenomena, the flow dynamics inside the dimple were observed experimentally with Stereoscopic Micro-Particle Image Velocimetry (Stereo µPIV). The formation of an unsteady oscillating vortex, which leads to an asymmetric trail downstream of the dimple, is visualized. The significant influence of the dimple geometry on heat transfer enhancement is shown, and the most beneficial geometric ratio of the spherical dimple regarding its ability to increase turbulence is identified. A comparison of the local flow velocities with the results of the numerically and experimentally observed patterns of the deposited particles caused by the dimple’s self-cleaning effect shows a good match.

Liquid organic hydrogen carrier (LOHC) systems offer a particularly interesting option for chemical hydrogen storage. In order to characterize and understand the endothermal hydrogen release from the carrier liquid and to evaluate suitable catalyst materials, knowledge of the temperature fields in the dehydrogenation reactor is important. One suitable technique for planar temperature sensing in reacting systems is phosphor thermometry. It is based on the excitation of a luminescent material by a laser pulse and detection of the subsequent phosphorescence signal. We investigated the luminescence of the thermographic phosphor (Sr,Ca)SiAIN₃:Eu²⁺ (“SCASN:Eu²⁺”) dispersed in the H0-DBT / H18-DBT LOHC system in a temperature range from 400 to 600 K. A measurement cell enables repeatable and homogeneous measurement conditions of the hydrogen release reaction. A catalytic plate was put inside the heated LOHC. Temperature fields during the hydrogen release reaction were measured for the first time using the phosphorescence decay time (PDT) and the phosphorescence intensity ratio method (PIR). As expected, a strong cooling at the catalyst surface during the endothermal hydrogen release reaction could be observed, which was quantified to be in the range of 40 K.

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A combined positron emission particle tracking (PEPT) and X-ray computed tomography (CT) technique is presented, and its utility is demonstrated through investigation of flow in a pipe with twisted tape swirl insert with varying flow conditions (diameter-based Reynolds numbers 16,300–63,300). A description of this technique is given, as well as data handling practices used to relate geometric information captured by CT to fluid flow data gathered via PEPT. It is found that the CT component is readily capable of capturing the stainless steel insert geometry in this present system, but the use of combined plastic and metal materials leads to artifacts in imaging of the plastic surface. Nonetheless, CT data are related to PEPT flow measurements, and average velocity fields are calculated via a pseudo-framing and interpolation scheme and used to visualize and interrogate key flow phenomena within the system. Radial velocity profiles of the mean flow characteristics are seen to collapse to a nearly common form across all flow conditions considered. Helical vortices are seen propagating through the flow field, generated by bypass flow around the gap between the insert and pipe wall, with additional coherent secondary flow structures seen in the higher Reynolds number cases. These findings enhance the understanding of the mixing mechanisms in these swirl flows and encourage the continued development of PEPT-CT methodologies for 3D flow measurements in optically inaccessible systems.

This paper explores integrating artificial intelligence (AI) segmentation models, particularly the Segment Anything Model (SAM), into fluid mechanics experiments. SAM’s architecture, comprising an image encoder, prompt encoder, and mask decoder, is investigated for its application in detecting and segmenting objects and flow structures. Additionally, we explore the integration of natural language prompts, such as BERT, to enhance SAM’s performance in segmenting specific objects. Through case studies, we found that SAM is robust in object detection in fluid experiments. However, segmentations related to flow properties, such as scalar turbulence and bubbly flows, require fine-tuning. To facilitate the application, we have established a repository (https://github.com/AliRKhojasteh/Flow_segmentation) where models and usage examples can be accessed.