Instantaneous Mixing Research Articles

Towards a hybrid turbulent mixing model based on hierarchical parcel‐swapping and one‐dimensional turbulence

AbstractOne‐dimensional turbulence (ODT) based models are able to generate good results for canonical flow problems compared to Direct Numerical Simulations. ODT has been successfully implemented as a sub‐grid scale model for LES problems (ODTLES) delivering promising results. However, due to the computational cost of the ODT model in this scope, there is a need for an even faster model for real world parameter regimes. The Hierarchical Parcel Swapping (HiPS) algorithm used in combination with the ODT model to simulate a channel flow recently provided results with an acceptable quality in a fraction of the time of an ODT simulation. HiPS uses a binary tree to define the fluid domain, and stochastic eddy events are sampled in this tree. A local instantaneous and complete mixing of the cells is performed when an eddy event happens at the Kolmogorov scale. The biggest limitation of this model is that the viscosity of the solution is implicitly defined by the number of cells in a mesh. Further development of HiPS is planned in order to create a computationally cheaper alternative for the ODT model to be used in ODTLES flow simulations.

Quantum walks over a square lattice

Quantum random walk finds application in efficient quantum algorithms as well as in quantum network theory. Here we study the mixing time of a discrete quantum walk over a square lattice in the presence of dynamic percolation and decoherence. We consider bit-flip and phase damping noise, and evaluate the instantaneous mixing time for both the cases. Using numerical analysis we show that, in the case of phase damping noise, the probability distribution of walker's position is sufficiently close to the uniform distribution after infinite time. However, during the action of bit-flip noise, even after infinite time the total variational distance between the two probability distributions is large enough.

Effect of Porous Baffles on the Energy Performance of Contact Tanks in Water Treatment

Three-dimensional numerical simulations are performed to evaluate the effect of porous baffles on the efficiency of water treatment contact tanks. A second-order accurate numerical model is employed for the solutions of unsteady flow and tracer transport through the porous baffles. The flow through the porous medium is characterized while using the Darcy-Forchheimer relationship. Large Eddy Simulation (LES) model is used to simulate the instantaneous mixing of the tracer in the chambers of the contact tank. Three different porosities are considered to evaluate the effect of porosity on the hydraulic and mixing efficiencies of the contact tank. Simulated time-averaged flow field shows that porous baffles that are placed at the entrance of each chamber could successfully mitigate short-circuiting and yield plug-flow conditions through the system for low porosities. Flow in the contact tank becomes laminar as the flow velocities decrease due to viscous effects and inertial resistance in the porous zone. For this case, the tracer is transported with bulk flow through the system and leaves the contact tank with a high peak seen in the Residence Time Distribution (RTD) plot. Porous layer increases the hydraulic efficiency of the conventional design from “poor” to “good” according to the baffling factor and increases the overall efficiency from “compromising” to “good” according to the AD index. Comparison of the performance of the porous layer with the previously developed slot-baffle design shows that the slot-baffle design increases the efficiency of the tank with increasing dispersion effects, whereas the porous design increases hydraulic efficiency and reduces the dispersion effects. While the porous design reduces energy efficiency by 33% due to a drastic increase in drag in the flow through porous zone, the slot-baffle design increases the energy efficiency of the conventional design by 67%.

Discretization of continuous-time quantum walks via the staggered model with Hamiltonians

We characterize a close connection between the continuous-time quantum-walk model and a discrete-time quantum-walk version, based on the staggered model with Hamiltonians in a class of Cayley graphs, which can be considered as a discretization of continuous-time quantum walks. This connection provides examples of perfect state transfer and instantaneous uniform mixing in the staggered model. On the other hand, we provide some more examples of perfect state transfer and instantaneous uniform mixing in the staggered model that cannot be reproduced by the continuous-time model.

Nonnegative Matrix Factorization for identification of unknown number of sources emitting delayed signals.

Factor analysis is broadly used as a powerful unsupervised machine learning tool for reconstruction of hidden features in recorded mixtures of signals. In the case of a linear approximation, the mixtures can be decomposed by a variety of model-free Blind Source Separation (BSS) algorithms. Most of the available BSS algorithms consider an instantaneous mixing of signals, while the case when the mixtures are linear combinations of signals with delays is less explored. Especially difficult is the case when the number of sources of the signals with delays is unknown and has to be determined from the data as well. To address this problem, in this paper, we present a new method based on Nonnegative Matrix Factorization (NMF) that is capable of identifying: (a) the unknown number of the sources, (b) the delays and speed of propagation of the signals, and (c) the locations of the sources. Our method can be used to decompose records of mixtures of signals with delays emitted by an unknown number of sources in a nondispersive medium, based only on recorded data. This is the case, for example, when electromagnetic signals from multiple antennas are received asynchronously; or mixtures of acoustic or seismic signals recorded by sensors located at different positions; or when a shift in frequency is induced by the Doppler effect. By applying our method to synthetic datasets, we demonstrate its ability to identify the unknown number of sources as well as the waveforms, the delays, and the strengths of the signals. Using Bayesian analysis, we also evaluate estimation uncertainties and identify the region of likelihood where the positions of the sources can be found.

Characterization of selected conservative and non-conservative isotopes in mine effluent and impacted surface waters: Implications for tracer applications at the mine-site scale

Effluent from Europe's largest active gold mine is discharged to the adjacent River Seurujoki via natural treatment wetlands in Lapland Finland. Site waters, including two sources of mine effluent, treatment wetland surface water and Seurujoki river water were chemically and isotopically characterized. The results of isotopic characterization were evaluated to determine the effectiveness of selected environmental conservative isotopes (δ18O, δD,87Sr/86Sr) as tracers of water/solute source. Non-conservative isotopes (δ7Li, δ26Mg, δ25Mg, δ34SSO4) were evaluated as tracers of fractionation inducing processes that provide insight to contaminant attenuation and mobility mechanisms. The two sources of mine effluent were chemically distinct, and the impacts of mine effluent were persistent in downstream river water to at least 12.8 km. Sr isotope-based estimates of mine effluent discharge to the river were in good agreement with Cl concentration-based estimates, and suggest effluent comprised approximately 4% of river discharge in both June 2013 and June 2015. These instantaneous mixing results were applied in a multi-isotope approach to characterize non-conservative solute and isotopic behavior for Li and SO4. In 2015 7Li was enriched in downstream river water by approximately 3‰ with no discernible concentration change, suggesting ongoing in-stream ion exchange reactions with oxy-hydroxide precipitates. While SO4 was attenuated by over 50% in the downstream direction, the observed 34SSO4 depletion indicates that bacterial sulfate reduction was not a driver of in-stream attenuation. Further, depletion of 18O and deuterium in treatment wetland 4 indicated that fresh meteoric water comprised approximately 25% of the treatment wetland discharge in March 2015. The contemporaneous flushing of numerous contaminants (Na, Ca, Mg, SO4, Mn, and Li) from the wetland supports the conceptual model in which disruption of contaminant concentration gradients will lead to contaminant leaching from the wetlands.

Lock-exchange release density currents over three-dimensional regular roughness elements

A fundamental study has been conducted to understand the front characteristics and the mixing in the flow of density currents over rough surfaces. A large-eddy simulation (LES) has been performed for lock-exchange release density currents over rough walls to shed light on the unsteady mixing processes. A volume-penalization method, which is a special case of the immersed-boundary method, has been implemented to realize the bottom-mounted rough topology. In this study, the LES has been conducted in a channel with a lower wall covered with three-dimensional cube- and pyramid-shaped roughness elements, such that all cases have the same base area, but differences in the roughness solidity and volume fraction of roughness. Both cases of identical roughness elements and those with randomness in height have been considered. The maximum roughness height for all cases is kept at a constant fraction (10 %) of the total channel height. The study focuses on the instantaneous mixing processes in lock-exchange release currents over rough surfaces. An important contribution of the work is that qualitative and quantitative analysis has been conducted to demonstrate additional mixing mechanisms due to the presence of surface roughness that enhances dilution of the current. Enhanced mixing due to roughness is related to the strength of the shear layer resulting from the roughness, and hence depends on friction Reynolds number ($Re_{\unicode[STIX]{x1D70F}}$). The combined role of current characteristics and $Re_{\unicode[STIX]{x1D70F}}$ together dictate the mixing processes and extent of dilution in density currents over surface roughness.

Effect of Field Spread on Resting-State Magneto Encephalography Functional Network Analysis: A Computational Modeling Study.

A popular way to analyze resting-state electroencephalography (EEG) and magneto encephalography (MEG) data is to treat them as a functional network in which sensors are identified with nodes and the interaction between channel time series and the network connections. Although conceptually appealing, the network-theoretical approach to sensor-level EEG and MEG data is challenged by the fact that EEG and MEG time series are mixtures of source activity. It is, therefore, of interest to assess the relationship between functional networks of source activity and the ensuing sensor-level networks. Since these topological features are of high interest in experimental studies, we address the question of to what extent the network topology can be reconstructed from sensor-level functional connectivity (FC) measures in case of MEG data. Simple simulations that consider only a small number of regions do not allow to assess network properties; therefore, we use a diffusion magnetic resonance imaging-constrained whole-brain computational model of resting-state activity. Our motivation lies behind the fact that still many contributions found in the literature perform network analysis at sensor level, and we aim at showing the discrepancies between source- and sensor-level network topologies by using realistic simulations of resting-state cortical activity. Our main findings are that the effect of field spread on network topology depends on the type of interaction (instantaneous or lagged) and leads to an underestimation of lagged FC at sensor level due to instantaneous mixing of cortical signals, instantaneous interaction is more sensitive to field spread than lagged interaction, and discrepancies are reduced when using planar gradiometers rather than axial gradiometers. We, therefore, recommend using lagged interaction measures on planar gradiometer data when investigating network properties of resting-state sensor-level MEG data.

Three-dimensional simulation of a LBLOCA in an AP1000® containment building

AP1000® is a Generation III+ reactor in which all safety systems relay on passive elements. AP1000 containment includes an In-containment Refueling Water Storage Tank (IRWST), a stainless steel liner that acts as a heat sink, and a Passive Residual Heat Removal System (PRHRS). In a containment Design Basis Accident (DBA) all these components are involved in the evolution of the accident and interact between each other. It is more difficult to model an AP1000 containment in comparison to other nuclear containments. The containment DBA modelling has been historically performed with Lumped Parameters Models (LPMs). The LPMs include several assumptions and hypotheses such as instantaneous mixing of the fluid inside a control volume, instantaneous contact of all thermal structures with the fluid inside a volume or neglecting three dimensional effects of the flow patterns, which can reduce the accuracy of the simulation in a complex containment like the AP1000. For this reason a three dimensional model of the AP1000 containment has been created with the GOTHIC code. A DBA is simulated in this model and results of pressure and temperature are obtained and analyzed. These results must be correctly treated and interpreted in order to compare them with LPM simulations. The results show that pressure distribution is homogeneous during the full transient, but temperature is not. These differences can be important enough to be a starting point for the developing of a new and needed three dimensional analysis methodology.

Uniform Mixing and Association Schemes

We consider continuous-time quantum walks on distance-regular graphs. Using results about the existence of complex Hadamard matrices in association schemes, we determine which of these graphs have quantum walks that admit uniform mixing.First we apply a result due to Chan to show that the only strongly regular graphs that admit instantaneous uniform mixing are the Paley graph of order nine and certain graphs corresponding to regular symmetric Hadamard matrices with constant diagonal. Next we prove that if uniform mixing occurs on a bipartite graph $X$ with $n$ vertices, then $n$ is divisible by four. We also prove that if $X$ is bipartite and regular, then $n$ is the sum of two integer squares. Our work on bipartite graphs implies that uniform mixing does not occur on $C_{2m}$ for $m \geq 3$. Using a result of Haagerup, we show that uniform mixing does not occur on $C_p$ for any prime $p$ such that $p \geq 5$. In contrast to this result, we see that $\epsilon$-uniform mixing occurs on $C_p$ for all primes $p$.

An analytic resolution to the competition between Lyman–Werner radiation and metal winds in direct collapse black hole hosts

A near pristine atomic cooling halo close to a star forming galaxy offers a natural pathway for forming massive direct collapse black hole (DCBH) seeds which could be the progenitors of the $z>6$ redshift quasars. The close proximity of the haloes enables a sufficient Lyman-Werner flux to effectively dissociate H$_2$ in the core of the atomic cooling halo. A mild background may also be required to delay star formation in the atomic cooling halo, often attributed to distant background galaxies. In this letter we investigate the impact of metal enrichment from both the background galaxies and the close star forming galaxy under extremely unfavourable conditions such as instantaneous metal mixing. We find that within the time window of DCBH formation, the level of enrichment never exceeds the critical threshold (Z$_{cr} \sim 1 \times 10^{-5} \ \rm Z_{\odot})$, and attains a maximum metallicity of Z $\sim 2 \times 10^{-6} \ \rm Z_{\odot}$. As the system evolves, the metallicity eventually exceeds the critical threshold, long after the DCBH has formed.

A Shell Model for Optimal Mixing

What is the maximum mixing efficiency of an incompressible flow? To address this question we introduce a shell model—a reduced model mimicking the kinematics of advection and diffusion—to study the evolution of an initially inhomogeneous tracer concentration carried by a given incompressible fluid on a periodic spatial domain. We pose the mixing task as an optimization problem: Find the divergence-free velocity field (the control variable) that produces a well-mixed tracer concentration field (the state variable). We consider two alternative objectives: local-in-time optimization (maximize the instantaneous mixing rate) and global-in-time optimization (maximize mixing at a prescribed final time). Throughout, we use a shell-model analog of the $$H^{-1}$$ mix-norm to measure mixing. In addition, lower bounds on the mix-norm are obtained and rule out perfect mixing in finite time in particular cases.

Two-compartment modeling of tissue microcirculation revisited.

Conventional two-compartment modeling of tissue microcirculation is used for tracer kinetic analysis of dynamic contrast-enhanced (DCE) computed tomography or magnetic resonance imaging studies although it is well-known that the underlying assumption of an instantaneous mixing of the administered contrast agent (CA) in capillaries is far from being realistic. It was thus the aim of the present study to provide theoretical and computational evidence in favor of a conceptually alternative modeling approach that makes it possible to characterize the bias inherent to compartment modeling and, moreover, to approximately correct for it. Starting from a two-region distributed-parameter model that accounts for spatial gradients in CA concentrations within blood-tissue exchange units, a modified lumped two-compartment exchange model was derived. It has the same analytical structure as the conventional two-compartment model, but indicates that the apparent blood flow identifiable from measured DCE data is substantially overestimated, whereas the three other model parameters (i.e., the permeability-surface area product as well as the volume fractions of the plasma and interstitial distribution space) are unbiased. Furthermore, a simple formula was derived to approximately compute a bias-corrected flow from the estimates of the apparent flow and permeability-surface area product obtained by model fitting. To evaluate the accuracy of the proposed modeling and bias correction method, representative noise-free DCE curves were analyzed. They were simulated for 36 microcirculation and four input scenarios by an axially distributed reference model. As analytically proven, the considered two-compartment exchange model is structurally identifiable from tissue residue data. The apparent flow values estimated for the 144 simulated tissue/input scenarios were considerably biased. After bias-correction, the deviations between estimated and actual parameter values were (11.2±6.4) % (vs. (105±21) % without correction) for the flow, (3.6±6.1) % for the permeability-surface area product, (5.8±4.9) % for the vascular volume and (2.5±4.1) % for the interstitial volume; with individual deviations of more than 20% being the exception and just marginal. Increasing the duration of CA administration only had a statistically significant but opposite effect on the accuracy of the estimated flow (declined) and intravascular volume (improved). Physiologically well-defined tissue parameters are structurally identifiable and accurately estimable from DCE data by the conceptually modified two-compartment model in combination with the bias correction. The accuracy of the bias-corrected flow is nearly comparable to that of the three other (theoretically unbiased) model parameters. As compared to conventional two-compartmentmodeling, this feature constitutes a major advantage for tracer kinetic analysis of both preclinical and clinical DCE imaging studies.

Gaussian process based independent analysis for temporal source separation in fMRI

Functional Magnetic Resonance Imaging (fMRI) gives us a unique insight into the processes of the brain, and opens up for analyzing the functional activation patterns of the underlying sources. Task-inferred supervised learning with restrictive assumptions in the regression set-up, restricts the exploratory nature of the analysis. Fully unsupervised independent component analysis (ICA) algorithms, on the other hand, can struggle to detect clear classifiable components on single-subject data. We attribute this shortcoming to inadequate modeling of the fMRI source signals by failing to incorporate its temporal nature. fMRI source signals, biological stimuli and non-stimuli-related artifacts are all smooth over a time-scale compatible with the sampling time (TR). We therefore propose Gaussian process ICA (GPICA), which facilitates temporal dependency by the use of Gaussian process source priors.On two fMRI data sets with different sampling frequency, we show that the GPICA-inferred temporal components and associated spatial maps allow for a more definite interpretation than standard temporal ICA methods. The temporal structures of the sources are controlled by the covariance of the Gaussian process, specified by a kernel function with an interpretable and controllable temporal length scale parameter. We propose a hierarchical model specification, considering both instantaneous and convolutive mixing, and we infer source spatial maps, temporal patterns and temporal length scale parameters by Markov Chain Monte Carlo. A companion implementation made as a plug-in for SPM can be downloaded from https://github.com/dittehald/GPICA.

Implementation of Blind Speech Separation for Intelligent Humanoid Robot using DUET Method

Nowadays, there are many efforts in building intelligent humanoid robot and adding advanced ability such as Blind Speech Separation (BSS). BSS is a problem of separation of several speech signals in a real world from mono or stereo audio record. In this research, we implement BSP system using DUET algorithm which allow to separate any number of sources by using only stereo (two) mixtures. The DUET (Degenerate Unmixing Estimation Technique) algorithm replaces our previous FastICA (Fast Independent Component Analysis) method only success in simulation but failed in the implementation. The main problem of FastICA is that it assumes instantaneous mixing without time delay in the recording process. To deals with audio record in the presence of inevitable time delays, it has to be replaced with DUET algorithm to separate well in real time. Finally, the DUET algorithm is implemented to humanoid robot which is developed using Raspberry Pi and equipped with RaspPi Cam to detect human face. Furthermore, the Cirrus Logic Audio Card is stacked to Raspberry Pi in order to record stereo audio. In our experiments, there are three controlled variables to evaluate algorithm performance, that is: distance, number of sources, and subject’s name. Robot will record stereo audio for four seconds after face is detected by system. The recording is then separated by DUET algorithm and produce two source estimations with average computation time 1.8 seconds. With Google API, the recognition accuracy of separated speech is varying between 40%-70%.

Enhanced Reaction Efficiency in Continuous Flow

AbstractContinuous flow reactors are enabling tools that can significantly benefit chemical reactions, especially those that are path length dependent (e.g., photochemical), mixing or transport dependent (e.g., gas‐liquid), exothermic, or utilize hazardous or unstable intermediates. In this review, it is demonstrated how the nearly instantaneous mixing, exceptionally fast mass transfer, safe access to high temperatures and pressures, and high surface area to volume ratio can be leveraged to improve product yield, reaction rates and/or selectivity. By showcasing five synthetic methodologies examined by our group, it is hoped that the reader will gain an appreciation of the accessible and transformative nature of flow chemistry for improving existing transformations, enabling rapid optimization, and for developing new methodologies that depend on precise parameter controls.

Implementation of Frequency Domain Approach Using Instantaneous Mixing Auto Recursive for Separation of Speech Signals

In the present work a novel algorithmic rule by taking the speech from two different microphones and separate these speeches by prediction of separating speech mixtures that is predicated on separation matrices is planned. In multi-talker applications so as to boost individual speech sources from their mixtures is done by Blind source Separation (BSS) ways. From the previous published works of separation of speech signals, the main disadvantage is that the incidence of distortion present within the signal that affects separated signal with loud musical noise. The idea for speech separation in standard BSS ways is simply one sound source in a single room. The proposed methodology uses as a network that has the parameters of the IMAR model for the separation matrices over the complete frequency vary. An attempt has been made to estimate the best values of the IMAR model parameters, ΦW and ΦG by suggests that of the maximum-likelihood estimation methodology. Based on the values of these parameters, the source spectral part vectors are estimated. The entire set of TIMIT corpus is employed for speech materials in evolution results. The Signal to Interference magnitude Relation (SIR) improves by a median of 6 dB sound unit over a frequency domain BSS approach.

Nonlethal predator effects on the turn-over of wild bird flocks.

Nonlethal predator effects arise when individuals of a prey species adjust their behaviour due to the presence of predators. Non-lethal predator effects have been shown to affect social group structure and social behaviour as well as individual fitness of the prey. In this experimental study, we used model sparrowhawks to launch attacks on flocks of wild great tits and blue tits whilst monitoring their social dynamics. We show that nonlethal attacks caused instantaneous turn-over and mixing of group composition within foraging flocks. A single experimental ‘attack’ lasting on average less than three seconds, caused the amount of turn-over expected over three hours (2.0–3.8 hours) of undisturbed foraging. This suggests that nonlethal predator effects can greatly alter group composition within populations, with potential implications for social behaviour by increasing the number of potential interaction partners, as well as longer-term consequences for pair formation and emergent effects determined by social structure such as information and disease transmission. We provide the first evidence, to our knowledge, based on in depth monitoring of a social network to comprehensively support the hypothesis that predators influence the social structure of groups, which offers new perspectives on the key drivers of social behaviour in wild populations.

Aerosol Flow in the Vitrocell 24/48 Exposure System: Flow Mixing and Aerosol Coalescence

In vitro exposure systems are increasingly used in modern toxicology assessment studies. An understanding of the functioning of these complex systems and their characterization ensures well-controlled delivery of substances to cell cultures and reliable biological response of cells to the given external conditions. In this work, we present the flow-mixing efficiency of the dilution unit in the Vitrocell® 24/48 (VC24/48) exposure system, together with the role of thermal coalescence. We adopted a computational fluid dynamics approach with integrated aerosol dynamics to analyze the dilution system using high-resolution simulations. We performed simulations for three total flow rates through the system: 3, 6, and 12 L/min, to investigate the influence of turbulent mixing and thermal coalescence on the aerosol characteristics. We found that for all simulated flow rates, instantaneous and localized turbulent mixing is induced by the two opposing dilution jets. We found the aerosol to be uniformly mixed and the flow to be laminarized upstream of the location of the first aerosol sampling trumpet. In summary, the design of the double-tee junction, serving as the dilution unit of the VC24/48 system, guarantees efficient and localized mixing/dilution of the aerosol, while still delivering laminar flow toward deposition wells, when operated under these high flow-rate conditions. In addition, we showed that thermal coalescence effects do not influence the aerosol droplet size distribution during the dilution process for the studied simulation conditions.

Enhancing the Acetylene Yield from Methane by Decoupling Oxidation and Pyrolysis Reactions: A Comparison with the Partial Oxidation Process

The partial oxidation (POX) of methane is one of the most important processes to produce acetylene and syngas. The reaction pathway analysis using a detailed chemical mechanism (modified GRI 3.0) showed that the exothermal oxidation and endothermic pyrolysis reactions were highly coupled in the original POX process, which limited the yield of acetylene. A new process that physically separated the heat supply and pyrolysis reactions was proposed to increase the acetylene yield. The maximum yield of acetylene was enhanced from 33% to 52% in the theoretical calculations assuming inert and instantaneous mixing. A jet-in-cross-flow (JICF) reactor was designed to realize this new process. The computational fluid dynamics (CFD) method coupled with the modified GRI 3.0 was applied to simulate the complex interaction between turbulent mixing and reactions. The results showed that a high acetylene yield of 41% could be obtained in the JICF reactor. The optimization of the reactor indicated that the optimum number o...