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Wind is closely associated with the discussion of fairness in ski jumping. To counter-act its influence on the jump length, the International Ski Federation (FIS) has introduced a wind compensation approach. We applied three differently accurate computer models of the flight phase with wind (M1, M2, and M3) to study the jump length effects of various wind scenarios. The previously used model M1 is accurate for wind blowing in direction of the flight path, but inaccuracies are to be expected for wind directions deviating from the tangent to the flight path. M2 considers the change of airflow direction, but it does not consider the associated change in the angle of attack of the skis which additionally modifies drag and lift area time functions. M3 predicts the length effect for all wind directions within the plane of the flight trajectory without any mathematical simplification. Prediction errors of M3 are determined only by the quality of the input data: wind velocity, drag and lift area functions, take-off velocity, and weight. For comparing the three models, drag and lift area functions of an optimized reference jump were used. Results obtained with M2, which is much easier to handle than M3, did not deviate noticeably when compared to predictions of the reference model M3. Therefore, we suggest to use M2 in future applications. A comparison of M2 predictions with the FIS wind compensation system showed substantial discrepancies, for instance: in the first flight phase, tailwind can increase jump length, and headwind can decrease it; this is opposite of what had been anticipated before and is not considered in the current wind compensation system in ski jumping.
A capacitive electrolyte-insulator-semiconductor (EIS) field-effect biosensor for acetoin detection has been presented for the first time. The EIS sensor consists of a layer structure of Al/p-Si/SiO₂/Ta₂O₅/enzyme acetoin reductase. The enzyme, also referred to as butane-2,3-diol dehydrogenase from B. clausii DSM 8716T, has been recently characterized. The enzyme catalyzes the (R)-specific reduction of racemic acetoin to (R,R)- and meso-butane-2,3-diol, respectively. Two different enzyme immobilization strategies (cross-linking by using glutaraldehyde and adsorption) have been studied. Typical biosensor parameters such as optimal pH working range, sensitivity, hysteresis, linear concentration range and long-term stability have been examined by means of constant-capacitance (ConCap) mode measurements. Furthermore, preliminary experiments have been successfully carried out for the detection of acetoin in diluted white wine samples.
Vectrino profiler spatial filtering for shear flows based on the mean velocity gradient equation
(2018)
A new methodology is proposed to spatially filter acoustic Doppler velocimetry data from a Vectrino profiler based on the differential mean velocity equation. Lower and upper bounds are formulated in terms of physically based flow constraints. Practical implementation is discussed, and its application is tested against data gathered from an open-channel flow over a stepped macroroughness surface. The method has proven to detect outliers occurring all over the distance range sampled by the Vectrino profiler and has shown to remain applicable out of the region of validity of the velocity gradient equation. Finally, a statistical analysis suggests that physically obtained bounds are asymptotically representative.
New information regarding the influence of a stepped chute on the hydraulic performance of the United States Bureau of Reclamation (Reclamation) Type III hydraulic jump stilling basin is presented for design (steady) and adverse (decreasing tailwater) conditions. Using published experimental data and computational fluid dynamics (CFD) models, this paper presents a detailed comparison between smooth-chute and stepped-chute configurations for chute slopes of 0.8H:1V and 4H:1V and Froude numbers (F) ranging from 3.1 to 9.5 for a Type III basin designed for F = 8. For both stepped and smooth chutes, the relative role of each basin element was quantified, up to the most hydraulic extreme case of jump sweep-out. It was found that, relative to a smooth chute, the turbulence generated by a stepped chute causes a higher maximum velocity decay within the stilling basin, which represents an enhancement of the Type III basin’s performance but also a change in the relative role of the basin elements. Results provide insight into the ability of the CFD models [unsteady Reynolds-averaged Navier-Stokes (RANS) equations with renormalization group (RNG) k-ϵ turbulence model and volume-of-fluid (VOF) for free surface tracking] to predict the transient basin flow structure and velocity profiles. Type III basins can perform adequately with a stepped chute despite the effects steps have on the relative role of each basin element. It is concluded that the classic Type III basin design, based upon methodology by reclamation specific to smooth chutes, can be hydraulically improved for the case of stepped chutes for design and adverse flow conditions using the information presented herein.
Multi-analyte biosensors may offer the opportunity to perform cost-effective and rapid analysis with reduced sample volume, as compared to electrochemical biosensing of each analyte individually. This work describes the development of an enzyme-based biosensor system for multi-parametric determination of four different organic acids. The biosensor array comprises five working electrodes for simultaneous sensing of ethanol, formate, d-lactate, and l-lactate, and an integrated counter electrode. Storage stability of the biosensor was evaluated under different conditions (stored at +4 °C in buffer solution and dry at −21 °C, +4 °C, and room temperature) over a period of 140 days. After repeated and regular application, the individual sensing electrodes exhibited the best stability when stored at −21 °C. Furthermore, measurements in silage samples (maize and sugarcane silage) were conducted with the portable biosensor system. Comparison with a conventional photometric technique demonstrated successful employment for rapid monitoring of complex media.
A light-addressable potentiometric sensor (LAPS) is a field-effect-based potentiometric device, which detects concentration changes of an analyte solution on the sensor surface in a spatially resolved way. It uses a light source to generate electron–hole pairs inside the semiconductor, which are separated in the depletion region due to an applied bias voltage across the sensor structure and hence, a surface-potential-dependent photocurrent can be read out. However, depending on the beam angle of the light source, scattering effects can occur, which influence the recorded signal in LAPS-based differential measurements. To solve this problem, a novel illumination unit based on a field programmable gate array (FPGA) consisting of 16 small-sized tunable infrared laser-diode modules (LDMs) is developed. Due to the improved focus of the LDMs with a beam angle of only 2 mrad, undesirable scattering effects are minimized. Escherichia coli (E. coli) K12 bacteria are used as a test microorganism to study the extracellular acidification on the sensor surface. Furthermore, a salt bridge chamber is built up and integrated with the LAPS system enabling multi-chamber differential measurements with a single Ag/AgCl reference electrode.
A chip-based amperometric biosensor referring on using the bioelectrocatalytical amplification principle for the detection of low adrenaline concentrations is presented. The adrenaline biosensor has been prepared by modification of a platinum thin-film electrode with an enzyme membrane containing the pyrroloquinoline quinone-dependent glucose dehydrogenase and glutaraldehyde. Measuring conditions such as temperature, pH value, and glucose concentration have been optimized to achieve a high sensitivity and a low detection limit of about 1 nM adrenaline measured in phosphate buffer at neutral pH value. The response of the biosensor to different catecholamines has also been proven. Long-term stability of the adrenaline biosensor has been studied over 10 days. In addition, the biosensor has been successfully applied for adrenaline detection in human blood plasma for future biomedical applications. Furthermore, preliminary experiments have been carried to detect the adrenaline-concentration difference measured in peripheral blood and adrenal venous blood, representing the adrenal vein sampling procedure of a physician.
The Dry-Low-NOx (DLN) Micromix combustion technology has been developed as low emission combustion principle for industrial gas turbines fueled with hydrogen or syngas. The combustion process is based on the phenomenon of jet-in-crossflow-mixing (JICF). Fuel is injected perpendicular into the air-cross-flow and burned in a multitude of miniaturized, diffusion-like flames. The miniaturization of the flames leads to a significant reduction of NOx emissions due to the very short residence time of reactants in the flame. In the Micromix research approach, computational fluid dynamics (CFD) analyses are validated toward experimental results. The combination of numerical and experimental methods allows an efficient design and optimization of DLN Micromix combustors concerning combustion stability and low NOx emissions. The paper presents a comparison of several numerical combustion models for hydrogen and hydrogen-rich syngas. They differ in the complexity of the underlying reaction mechanism and the associated computational effort. The performance of a hybrid eddy-break-up (EBU) model with a one-step global reaction is compared to a complex chemistry model and a flamelet generated manifolds (FGM) model, both using detailed reaction schemes for hydrogen or syngas combustion. Validation of numerical results is based on exhaust gas compositions available from experimental investigation on DLN Micromix combustors. The conducted evaluation confirms that the applied detailed combustion mechanisms are able to predict the general physics of the DLN-Micromix combustion process accurately. The FGM method proved to be generally suitable to reduce the computational effort while maintaining the accuracy of detailed chemistry.