Gas-Solid Flow in a Fluidized-Particle Tubular Solar Receiver: Off-Sun Experimental Flow Regimes Characterization

The fluidized particle-in-tube solar receiver concept is promoted as an attractive solution for heating particles at high temperature in the context of the next generation of solar power tower. Similar to most existing central solar receivers, the irradiated part of the system, the absorber, is composed of tubes in which circulate the fluidized particles. In this concept, the bottom tip of the tubes is immersed in a fluidized bed generated in a vessel named the dispenser. A secondary air injection, called aeration, is added at the bottom of the tube to stabilize the flow. Contrary to risers, the particle mass flow rate is controlled by a combination of the overpressure in the dispenser and the aeration air velocity in the tube. This is an originality of the system that justifies a specific study of the fluidization regimes in a wide range of operating parameters. Moreover, due to the high value of the aspect ratio, the particle flow structure varies along the tube. Experiments were conducted with Geldart Group A particles at ambient temperature with a 0.045 m internal diameter and 3 m long tube. Various temporal pressure signal processing methods, applied in the case of classical risers, are applied. Over a short acquisition time, a cross-reference of the results is necessary to identify and characterize the fluidization regimes. Bubbling, slugging, turbulent and fast fluidization regimes are encountered and the two operation modes, without and with particle circulation, are compared.

The Effect of Navigation Demand on Decision Making in a Dynamic, Sport-Inspired Virtual Environment

Athletes commonly make decisions about the passability of closing gaps when navigating sport environments. This study examined whether increased temporal pressure to arrive at a desired location modifies these decisions. Thirty participants navigated toward a waypoint in a virtual, sport-inspired environment. To do so, they had to decide whether they could pass through closing gaps of virtual humans (and take the shortest route) or steer around them (and take a longer route). The decision boundary of participants who were time pressured to arrive at a waypoint was biased toward end gaps of smaller sizes and was less reliably defined, resulting in a higher number of collisions. Effects of temporal pressure were minimized with experience in the experimental task. Results indicate that temporal pressure affects perceptual–motor processes supporting information pickup and shapes the information–action coupling that drives compliance with navigation demands. Theoretical and practical implications are discussed.

Neural Network-Based Model Reduction of Hydrodynamics Forces on an Airfoil

In this paper, an artificial neural network (ANN)-based reduced order model (ROM) is developed for the hydrodynamics forces on an airfoil immersed in the flow field at different angles of attack. The proper orthogonal decomposition (POD) of the flow field data is employed to obtain pressure modes and the temporal coefficients. These temporal pressure coefficients are used to train the ANN using data from three different angles of attack. The trained network then takes the value of angle of attack (AOA) and past POD coefficients as an input and predicts the future temporal coefficients. We also decompose the surface pressure modes into lift and drag components. These surface pressure modes are then employed to calculate the pressure component of lift CLp and drag CDp coefficients. The train model is then tested on the in-sample data and out-of-sample data. The results show good agreement with the true numerical data, thus validating the neural network based model.

FlowHaptics: MidairHaptic Representation of Liquid Flow

Water is an essential substance for humans in their daily lives. There are many opportunities for us to come in contact with water, such as cooking, bathing, and swimming. However, few studies have reproduced the sensation of water touching the skin. This study aims to propose a novel midair haptic device, named FlowHaptics, that reproduces the feeling of the force of flowing water over human fingers using multiple air jets. We first estimated the temporal pressure distribution change of water in two-dimensional space using machine-learning-accelerated fluid simulation. We controlled the airflow based on the pressure distribution change obtained from the fluid simulation to reproduce the feeling of flowing water over the fingers using our proposed device, which can control multiple air jets in real time. We performed a psycho-physical evaluation of different flow velocities and a subjective evaluation of different velocity profiles. We found that FlowHaptics reliably created the illusion of the pressure distribution of flowing water on the fingers where the flow velocity could be distinguished within the range of 8.42% to 13.05%, and our estimated flow velocity profile with the configuration of three air jets felt more similar to flowing water when compared to a constant velocity profile according to the users.

Modeling Skin Conductance Response Time Series during Consecutive Rapid Decision-Making under Concurrent Temporal Pressure and Information Ambiguity

Emergency situations promote risk-taking behaviors associated with anxiety reactivity. A previous study using the Iowa Gambling Task (IGT) has demonstrated that prespecified state anxiety predicts moderate risk-taking (middle-risk/high-return) after salient penalty events under temporal pressure and information ambiguity. Such moderate risk-taking can be used as a behavioral background in the case of fraud damage. We conducted two psychophysiological experiments using the IGT and used a psychophysiological modeling approach to examine how moderate risk-taking under temporal pressure and information ambiguity is associated with automatic physiological responses, such as a skin conductance response (SCR). The first experiment created template SCR functions under concurrent temporal pressure and information ambiguity. The second experiment produced a convolution model using the SCR functions and fitted the model to the SCR time series recorded under temporal pressure and no temporal pressure, respectively. We also collected the participants’ anxiety profiles before the IGT experiment. The first finding indicated that participants with higher state anxiety scores yielded better model fitting (that is, event-related physiological responses) under temporal pressure. The second finding demonstrated that participants with better model fitting made consecutive Deck A selections under temporal pressure more frequently. In summary, a psychophysiological modeling approach is effective for capturing overlapping SCRs and moderate risk-taking under concurrent temporal pressure and information ambiguity is associated with automatic physiological and emotional reactivity.

Pump-probe X-ray holographic imaging of laser-induced cavitation bubbles with femtosecond FEL pulses

Cavitation bubbles can be seeded from a plasma following optical breakdown, by focusing an intense laser in water. The fast dynamics are associated with extreme states of gas and liquid, especially in the nascent state. This offers a unique setting to probe water and water vapor far-from equilibrium. However, current optical techniques cannot quantify these early states due to contrast and resolution limitations. X-ray holography with single X-ray free-electron laser pulses has now enabled a quasi-instantaneous high resolution structural probe with contrast proportional to the electron density of the object. In this work, we demonstrate cone-beam holographic flash imaging of laser-induced cavitation bubbles in water with nanofocused X-ray free-electron laser pulses. We quantify the spatial and temporal pressure distribution of the shockwave surrounding the expanding cavitation bubble at time delays shortly after seeding and compare the results to numerical simulations.

Simplified Transition and Turbulence Modeling for Oscillatory Pipe Flows

One-dimensional unsteady Reynolds-averaged Navier–Stokes computations were performed for oscillatory transitional and turbulent pipe flows and the results were validated against existing experimental data for a wide variety of oscillatory Reynolds and Womersley numbers. An unsteady version of the Johnson–King model was implemented with optional near-wall modification to account for temporal pressure gradient variations, and the predictions were compared with those of the Spalart–Allmaras and k–ε turbulence models. Transition and relaminarization were based on empirical Womersley number correlations and assumed to occur instantaneously: in the former case, this assumption was valid, but in the latter case, deviations between data and predictions were observed. In flows where the oscillatory Reynolds numbers are substantially higher than the commonly accepted steady critical value (~2000), fully or continuously turbulent models produced the best correspondence with experimental data. Critically and conditionally turbulent models produced slightly inferior correspondence, and no significant benefit was observed when near-wall pressure gradient effects were implemented or when common one- and two-equation turbulence models were employed. The turbulent velocity profiles were mainly unaffected by the oscillations and this was explained by noting that the turbulent viscosity is significantly higher than its laminar counterpart. Thus, a turbulent Womersley number was proposed for the analysis and categorization of oscillatory pipe flows.

Whole-body plethysmography revisited

Whole-body plethysmography (WBP) is an established method to determine physiological parameters and pathophysiological alteration of breathing in animals and animal models of a variety of diseases, reaching from pulmonary diseases to complex neurological syndromes. Although frequently used, there is ongoing debate about what exactly is measured by whole-body-plethysmography and how reliable the data derived from this method are? Here, we designed a simple device that can serve as an artificial lung model that enables a thorough evaluation of different predictions about and around whole-body plethysmography. Using our lung model, we confirmed that during WBP two components contribute to the pressure changes detected in the chamber: 1) the increase of the pressure due to heating and moistening of the air, termed as conditioning, during inspiration; 2) changes of chamber pressure that depend on airway resistance. Both components overlap and contribute to the temporal pressure-profile measured in the chamber or across the wall of the chamber. Our data showed that a precise measurement of the breathing volume appears to be hindered by at least two factors: 1) the unknown relative contribution of each of these components; 2) not only the air in the inspired volume is conditioned during inspiration, but also air within the residual volume and death space that is recruited during inspiration. Moreover, our data suggest that the expiratory negative pressure peak that is used to determine the so called “enhanced pause” (Penh) parameter is not a measure for airway resistance as such but rather a consequence of the animal’s response to the airway resistance, using active expiration to overcome the resistance by a higher thoracic pressure.