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Large Eddy Simulations (LES) of film cooling flows were conducted to investigate the impact of high turbulence intensity in the main flow, representative of jet-engine combustor conditions. A comparison was made with LES simulations at zero turbulence at the main flow inlet boundary. The study investigated three different film cooling configurations, which involved cylindrical holes and two variations with holes embedded in trenches known as transverse and segmented trench. Different momentum ratios (I = 3.5 and 8.3) relevant to combustor flows in jet-engines were applied. The LES simulations utilized OpenFOAM and solved the energy and passive scalar transport equations to determine film cooling efficiency (η), heat transfer coefficient (h f), and net heat flux reduction (N H F R). The numerical results were validated through comparison with experimental data. The mean and instantaneous results revealed that high turbulence intensity in the main flow significantly influenced film cooling performance. The film cooling efficiency was found to decrease with increased turbulence intensity, while for the ordinary film cooling design exhibiting jet lift-off, the increased mixing led to higher η. The heat transfer coefficient increased with turbulence intensity and momentum ratio, with turbulence intensity having a greater impact on ordinary designs and momentum ratio on trenched designs. Moreover, increasing turbulence intensity or momentum ratio resulted in lower N H F R for all designs. Hot spots were observed in the instantaneous results, with spatial variations depending on the film cooling design. • Unsteady high turbulence boundary condition. • Ordinary and trenched film cooling designs. • Heat transfer coefficient. • Net heat flux reduction. • Unsteady effects near the wall. [ABSTRACT FROM AUTHOR]

• Neural network RANS GEKO coefficients. • Bayesian optimization. • High turbulence boundary condition. • Novel film cooling designs. • Reduction of hot gas entrainment. In this numerical study an optimized trench film cooling design is determined using a Bayesian algorithm and neural network trained RANS model. Three objective functions were considered, the area-averaged film cooling efficiency, spatial standard deviation of film cooling efficiency and hot gas ingestion into the trench. Nine geometrical design parameters were varied to allow for a 3D trench shape and to find an optimal trench design based on the initial parametrization of the trench. Jet-engine like inflow boundary conditions with respect to turbulence intensity and length scales were applied. The investigated momentum ratios (I) were 1 and 8 at a main flow Reynolds number (R e D) of 2500. For each design the steady state Reynolds Averaged Navier-Stokes (RANS) equations were solved using the commercial Computational Fluid Dynamics (CFD) code Ansys Fluent V2022 R1. The turbulence model coefficients of the generalized k − ω (GEKO) model were tuned to approximate the time-averaged 3D temperature field from a predictive Large Eddy Simulation (LES) and trained by a neural network to improve the prediction capability. The tuned GEKO model shows improved agreement with experimental data of a literature case compared to the standard GEKO model. With this tuned RANS model optimized trench designs are found and validated by additional LES's. The optimized designs include angled side walls to improve former trench designs, particularly in mitigating hot gas entrainment into the trench, which could be omitted almost entirely. [Display omitted] [ABSTRACT FROM AUTHOR]

Summary The integration of visual stimuli and motor feedback is critical for successful visually guided navigation. These signals have been shown to shape neuronal activity in the primary visual cortex (V1), in an experience-dependent manner. Here, we examined whether visual, reward, and self-motion-related inputs are integrated in order to encode behaviorally relevant locations in V1 neurons. Using a behavioral task in a virtual environment, we monitored layer 2/3 neuronal activity as mice learned to locate a reward along a linear corridor. With learning, a subset of neurons became responsive to the expected reward location. Without a visual cue to the reward location, both behavioral and neuronal responses relied on self-motion-derived estimations. However, when visual cues were available, both neuronal and behavioral responses were driven by visual information. Therefore, a population of V1 neurons encode behaviorally relevant spatial locations, based on either visual cues or on self-motion feedback when visual cues are absent. Graphical Abstract Highlights • Most V1 L2/3 neurons show task-related activity after learning a rewarded task • A subset of neurons became responsive to an expected reward location • Without visual cues, behavioral and neuronal responses rely on self-motion signals • With visual cues, behavioral and neuronal responses rely on visual information Pakan et al. show that spatial locations that are relevant for a behavioral task are represented in the primary visual cortex. Both neuronal and behavioral responses to an expected reward location primarily rely on visual information. Without visual landmarks, both neuronal and behavioral responses are driven by self-motion derived information. [ABSTRACT FROM AUTHOR]

Spatial learning requires estimates of location that may be obtained by path integration or from positional cues. Grid and other spatial firing patterns of neurons in the superficial medial entorhinal cortex (MEC) suggest roles in behavioral estimation of location. However, distinguishing the contributions of path integration and cue-based signals to spatial behaviors is challenging and the roles of identified MEC neurons are unclear. We use virtual reality to dissociate linear path integration from other strategies for behavioral estimation of location. We find that mice learn to path integrate using motor-related self-motion signals, with accuracy that decreases steeply as a function of distance. We show that inactivation of stellate cells in superficial MEC impairs spatial learning in virtual reality and in a real world object location recognition task. Our results quantify contributions of path integration to behavior and corroborate key predictions of models in which stellate cells contribute to location estimation. [ABSTRACT FROM AUTHOR]

Recently, a novel test bench was developed at the Bundeswehr University of Munich in order to study secondary near-wall reactions caused by cold injection of methane into an oxygen-rich hot crossflow. The available measurements of the experiment, namely Laser Induced Fluorescence (LIF) of OH allowed to locate the reaction zone and to estimate the autoignition length, while the heat load prediction at the wall was calculated from the thermocouple readings using the inverse heat transfer method. A numerical investigation of this test bench is presented in this work. In the first part, non-reactive Large Eddy Simulations (LES) are used to evaluate the turbulent boundary conditions of the reactive test rig. The use of LES provides an insight in the distribution of velocity, turbulence intensity, temperature and species within the hot flow generator (burner), the fuel injection nozzles and the inlet of the reactive test rig. In the second part, reactive LES computations are used for comparison of the autoignition length and the wall heat fluxes with the experimental data, based on the boundary conditions provided by the non-reactive LES. The results show that in this configuration the autoignition length is more strongly affected by the hot gas inlet temperature than by the turbulent fluctuations of the crossflow. The qualitative comparison with the autoignition length assessed from the experiment is satisfactory and a wall heat flux distribution similar to the experimental distribution is obtained downstream the fuel injection nozzles. [ABSTRACT FROM AUTHOR]

Near-wall reacting jets can occur in different engineering applications, such as rocket combustion chambers and in gas turbine combustors and turbines. This work presents results of experimental investigations of reacting gaseous fuel jets (hydrogen, methane, propane) injected normally into a hot oxygen-rich cross-flow using OH laser-induced fluorescence and OH* chemiluminescence diagnostics. RANS CFD simulations with EDC combustion model are performed for comparison. To determine the surface heat fluxes, the inverse heat conduction method was applied using measured wall temperature data as input. It was observed, that hydrogen jets ignite directly at the injection location and caused a higher surface heat flux than the hydrocarbon jets, where jet-like diffusion flames emerged. With the latter fuels, a significant ignition delay length was observed. Operation with methane fuel showed the least stability, least reactivity and the lowest surface heat flux. Increasing the jet momentum ratio led to a reduced ignition delay length due to enhanced jet-crossflow interaction, and to a reduction of surface heat flux as the reacting jet detached more from the surface. CFD results using the Eddy-Dissipation Concept (EDC) combustion model predicted ignition delay lengths and reaction zone shapes in qualitative agreement with the experiment but with a trend of overestimating combustion temperatures. [ABSTRACT FROM AUTHOR]

Abstract: Background: Stents seeded with genetically modified endothelial cells (EC) may provide an attractive therapeutic modality for treating vascular diseases by combining the mechanical properties of the metallic stent with the biologic activity of native or genetically engineered ECs. The clinical feasibility of implanting seeded stents depends on the ability to achieve adequate stent coverage within a clinically applicable time frame. We tested the hypothesis that this goal could be achieved by seeding stents with human ECs overexpressing vascular endothelial growth factor (VEGF) and by using an efficient gene transfer system. Methods and results: Efficiency of gene transfer to human ECs using an amphotropic retroviral vector and a gibbon ape leukemia virus (GALV) pseudo-typed retroviral vector was examined and compared. For assessment of transduction rates, LacZ-encoding vectors were used and β-galactosidase activity was determined 48 h after gene transfer. The transduction rate of primary human ECs using the amphotropic retroviral vector encoding the LacZ gene was low (2.9±2% of cells). Under the same conditions, the GALV pseudo-typed vector encoding LacZ transduced 94±2% of cells (P<.001). To test the effect of VEGF gene transfer on stent coverage, we transduced ECs using a bicistronic GALV pseudo-typed retroviral vector encoding either GFP alone or both VEGF and GFP. Since all transduced cells expressed GFP, stent coverage by ECs could be assessed by fluorescent inverted microscopy, which demonstrated that stent coverage by ECs overexpressing VEGF was more rapid and effective than coverage by ECs overexpressing GFP. Progressively increasing quantities of VEGF protein were detected in the conditioned medium of stents seeded with endothelia cells expressing VEGF 2, 3, and 5 days after seeding. Conclusions: High-rate gene transfer to human primary ECs was observed 48 h after transduction with GALV pseudo-typed retroviral vectors, eliminating the need for the time-consuming process of cell selection. Seeding with ECs overexpressing VEGF improved stent coverage and was associated with continuing secretion of the protein. The findings provide support for the feasibility of implanting genetically engineered biologically active cellular-coated stents. [Copyright &y& Elsevier]

The performance of the novel ammonium chemical ionization time of flight mass spectrometer (NH 4 + -CI3–TOF) utilizing NH 4 + adduct ion chemistry to measure first generation oxidized product molecules (OMs) as well as highly oxidized organic molecules (HOMs) was investigated for the first time. The gas-phase ozonolysis of cyclohexene served as a first test system. Experiments have been carried out in the TROPOS free-jet flow system at close to atmospheric conditions. Product ion signals were simultaneously observed by the NH 4 + -CI3-TOF and the acetate chemical ionization atmospheric pressure interface time of flight mass spectrometer (acetate-CI-API-TOF). Both instruments are in remarkable good agreement within a factor of two for HOMs. For OMs not containing an OOH group the acetate technique can considerably underestimate OM concentrations by 2–3 orders of magnitude. First steps of cyclohexene ozonolysis generate ten different main products, detected with the ammonium-CI3-TOF, comprising 93% of observed OMs. The remaining 7% are distributed over several minor products that can be attributed to HOMs, predominately to highly oxidized RO 2 radicals. Summing up, observed ammonium-CI3-TOF products yield 5.6 × 10 9 molecules cm − ³ in excellent agreement with the amount of reacted cyclohexene of 4.5 × 10 9 molecules cm − ³ for reactant concentrations of [O 3 ] = 2.25 × 10 12 molecules cm − ³ and [cyclohexene] = 2.0 × 10 12 molecules cm − ³ and a reaction time of 7.9 s. NH 4 + adduct ion chemistry is a promising CIMS technology for achieving carbon-closure due to the unique opportunity for complete detection of the whole product distribution including also peroxy radicals, and consequently, for a much better understanding of oxidation processes. [ABSTRACT FROM AUTHOR]

Abstract: High resolution peripheral quantitative computed tomography (HR-pQCT) permits the non-invasive assessment of cortical and trabecular bone density, geometry, and microarchitecture. Although researchers have developed various post-processing algorithms to quantify HR-pQCT image properties, few of these techniques capture image features beyond global structure-based metrics. While 3D-texture analysis is a key approach in computer vision, it has been utilized only infrequently in HR-pQCT research. Motivated by high isotropic spatial resolution and the information density provided by HR-pQCT scans, we have developed and evaluated a post-processing algorithm that quantifies microarchitecture characteristics via texture features in HR-pQCT scans. During a training phase in which clustering was applied to texture features extracted from each voxel of trabecular bone, three distinct clusters, or trabecular microarchitecture classes (TMACs) were identified. These TMACs represent trabecular bone regions with common texture characteristics. The TMACs were then used to automatically segment the voxels of new data into three regions corresponding to the trained cluster features. Regional trabecular bone texture was described by the histogram of relative trabecular bone volume covered by each cluster. We evaluated the intra-scanner and inter-scanner reproducibility by assessing the precision errors (PE), intra class correlation coefficients (ICC) and Dice coefficients (DC) of the method on 14 ultradistal radius samples scanned on two HR-pQCT systems. DC showed good reproducibility in intra-scanner set-up with a mean of 0.870±0.027 (no unit). Even in the inter-scanner set-up the ICC showed high reproducibility, ranging from 0.814 to 0.964. In a preliminary clinical test application, the TMAC histograms appear to be a good indicator, when differentiating between postmenopausal women with (n=18) and without (n=18) prevalent fragility fractures. In conclusion, we could demonstrate that 3D-texture analysis and feature clustering seems to be a promising new HR-pQCT post-processing tool with good reproducibility, even between two different scanners. [Copyright &y& Elsevier]