Fast Fluid Flow Research Articles

Coupled fluid flow, solute transport and dissolution processes in discrete fracture networks: An advanced Discontinuous Galerkin model

Modeling dissolution processes in discrete fracture networks (DFNs) is a challenging task. Challenges are related to the highly nonlinear coupling between flow, mass transport, and reactive processes associated with fracture aperture evolution by dissolution. Further, advection-dominated transport due to fast fluid flow in fractures renders the problem more complex from a computational point of view, as traditional numerical methods may introduce unphysical oscillations or excessive numerical diffusion. The Discontinuous Galerkin (DG) method is known to be suitable for the simulation of advection-dominated transport. In this work, an advanced DG model is developed to model transport with dissolution in DFNs. We propose an upwind formulation to deal with the upstream concentration at the intersection of several fractures. The upstream concentration at an intersection node is calculated based on the average nodal concentrations of all the fractures having an inflow at that node, weighted by the volumetric fluxes of these fractures. The dispersion term is discretized with the Mixed Finite Element (MFE) method, which ensures the continuity of the dispersive flux at the intersection of fractures with different apertures. The obtained nonlinear coupled flow-transport-dissolution equations are discretized in time with a high-order scheme via the method of lines (MOL). Numerical examples and comparisons with standard finite element (FE) and finite volume (FV) solutions are performed to investigate the correctness and efficiency of the developed model. Results show that the new DG-DFN model avoids unphysical oscillations encountered with the standard FE method and strongly reduces the numerical diffusion observed with the upwind FV scheme. The DG-DFN model is then used to investigate the effect of the dissolution rate on the flow, transport, and aperture evolution processes for a single fracture and for a DFN. A quasi-linear evolution of the fracture aperture is observed for low dissolution rates. For high dissolution rates, a funnel-shaped enlargement is observed with a significant widening for the fractures near the inlet and minor effects for those away from the injection location.

Dynamic remodeling of fiber networks with stiff inclusions under compressive loading.

The ability of tissues to sustain and withstand mechanical stress is critical to tissue development and healthy tissue maintenance. The mechanical properties of tissues are typically considered to be dominated by the fibrous extracellular matrix (ECM) component of tissues. Fiber network mechanics can capture certain mechanical features of tissues, such as shear strain stiffening, but is insufficient in describing the compressive response of certain tissues and blood clots that are rich in extracellular matrix. To understand the mechanical response of tissues, we employ a contemporary mechanical model, a fibrous network of fibrin embedded with inert bead inclusions that preserve the volume-conserving constraints of cells in tissues. Combining bulk mechanical rheology and a custom imaging device, we show that the presence of inclusions alters the local dynamic remodeling of the networks undergoing uniaxial compressive strains and demonstrate non-affine correlated motion within a fiber-bead network, predicted to stretch fibers in the network and lead to the ability of the network to stiffen under compression, a key feature of real tissues. These findings have important implications for understanding how local structural properties of cells and ECM fibers impact the bulk mechanical response of real tissues. STATEMENT OF SIGNIFICANCE: To understand why real tissue stiffens under compression, we study a model tissue system which also stiffens: a fibrin network embedded with stiff beads. We design a device that images compression of both fiber and fiber-bead networks. Distinct from previous imaging studies, this setup can dynamically capture network deformation on scales larger than single fibers. From the videos, we see fluid flow and network remodeling are both critical to compression behavior. The fiber-bead network has faster fluid flow, reduced network recovery, and correlated motion during network relaxation. We hypothesize that the beads hinder network relaxation of stretched fibers, thus retaining the applied stress and exhibiting stiffening. Our findings reveal important details for modeling tissue mechanics towards optimizing healthcare.

Numerical Simulation in the Melt Pool Evolution of Laser Powder Bed Fusion Process for Ti6Al4V.

In order to track the free interface of the melt pool and understand the evolution of the melt pool, the flow of fluid, and the interface behavior of gas and liquid, a physical model is developed by using the VOF method in this paper. Its characteristics are a combined heat source model, including a parabolic rotation and a cylindrical distribution, and a powder bed stochastic distributed model with powder particle size. The unit interface between the metallic and gas phase in the laser-powder interaction zone can only be loaded by the heat source. Only the first and second laser scanning tracks are simulated to reduce the calculation time. The simulation results show that process parameters such as laser power and scanning speed have significant effects on the fluid flow and surface morphology in the melt pool, which are in good agreement with the experimental results. Compared with the first track, the second track has larger melt pool geometry, higher melt temperature, and faster fluid flow. The melt flows intensely at the initial position due to the high flow rate in the limited melt space. Because there is enough space for the metal flow, the second track can obtain smooth surface morphology more easily compared to the first track. The melt pool temperature at the laser beam center fluctuates during the laser scanning process. This depends on the effects of the interaction between heat conduction or heat accumulation or the interaction between heat accumulation and violent fluid flow. The temperature distribution and fluid flow in the melt pool benefit the analysis and understanding of the evolution mechanism of the melt pool geometry and surface topography and further allow regulation of the L-PBF process of Ti6Al4V.

Powder sintered flat micro-heat pipe with wettability modification

Flat micro-Heat Pipe (FHP) provides an excellent solution to the heat dissipation problem of an electronic chip by the gas–liquid two-phase flow. Therefore, the liquid channels and the gas channels are part of the FHP. It determines the performance of the FHP. To this end, these channels were optimized by infiltration modification to accelerate the gas-liquid circulation. In this work, the wick underwent hydrophilic treatment by chemical corrosion and the solutions selected were KOH and (NH4)2S2O8. The shell surface undergoes hydrophobic treatment by electrodeposition with a mixture of zinc-nickel ions. The thermal transfer performance of the Hydrophilic Wick FHP (HW-FHP) and the Hydrophobic Shells FHP (HS-FHP) was analyzed. The results show that the maximum thermal power of the HW-FHP is 10.8 W, 9.1% higher than that of the Untreated FHP (UFHP). The HS-FHP is 11.9 W, 20% higher than that of the UFHP. The HW has a high capillary force, resulting in faster fluid flow. The vapor flow channels made up of the HS have a low resistance to the vapor flow. The hydrophobic surface can reduce the droplet diameter and prevent blocked vapor flow channels.

Assessment of the high-temperature aquifer thermal energy storage (HT-ATES) potential in naturally fractured geothermal reservoirs with a stochastic discrete fracture network model

High-temperature aquifer thermal energy storage (HT-ATES) is a cost-effective and suitable technology to store large amounts of energy. HT-ATES has been demonstrated to be an efficient and stable tool to buffer seasonal imbalances and significantly reduce greenhouse gas emissions. Fractured reservoirs are widespread in sedimentary basins worldwide. However, naturally fractured reservoirs have received little attention as potential formations for HT-ATES. The main concern regarding thermal energy storage in naturally fractured formations is the high fracture permeability, which may result in fast fluid flow and an increase in thermal losses. Therefore, quantification of the effects of fracture flow is essential to HT-ATES site verification.An HT-ATES system in a generic fractured reservoir is simulated with a 3D stochastically generated discrete fracture network (DFN) model combined with a fluid flow and heat transport model. The pressure and temperature evolutions at the well are analyzed, and the total extracted energy and thermal recovery efficiency are evaluated. The results confirm that the presence of the DFNs enhances thermal loss and thereby results in a lower thermal recovery efficiency compared with those of an unfractured reservoir. Such a decrease can reach 20%. However, simulations show that naturally fractured reservoirs might be potential candidates for HT-ATES due to a larger injectivity. A further discussion is conducted to characterize the relative importance of the hydrogeological properties of the fractures and fracture network structure on the thermal behavior of the HT-ATES system.This study provides preliminary insights into the impacts of complex natural DFN on the thermal performance of HT-ATES in fractured reservoirs.

MOF-enzyme hybrid nanosystem decorated 3D hollow fiber membranes for in-situ blood separation and biosensing array

Modified metal–organic frameworks (MOFs) doping with enzymes exhibit high enzyme stability and catalytic performance, which is a research hotspot in the field of enzyme-based sensing. Although the MOF-enzyme constitutes a 3D structure in the nanoscale, the macroscopic assembly configuration still stays in 1D or 2D structures, limiting sensing applications towards complex biological targets. Herein, the MOF-enzyme hybrid nanosystem was assembled into 3D porous conductive supports via a controllable physical embedding method, displaying high enzymatic loading, stability and cascade catalytic performance. The modified MOFs combing with enzymes served as a sensing reaction system, and the conductive hollow fiber membranes (HFMs) served as a functional platform. The multifunctional device integrates pumpless hydrodynamic transport, interconnected conductive polymer, and blood separation modules, showing fast capillary fluid flow, trace sampling (3 μL), high selectivity and accuracy. The linear sensing range was in 2–24 mM glucose, 0.05–6 mM lactic acid, and 0.1–10 mM cholesterol, respectively, with sensitivities of 24.2, 150, 73.6 nA mM−1. Furthermore, this strategy of modular assembly of biosensing array can easily implement multiplex metabolites detection simultaneously.

Kinetic Prediction for the Composition of Inclusions in the Molten Steel During the Electroslag Remelting

A mathematical model coupled with the penetration theory, the ion and molecule coexistence theory, and thermodynamic equilibrium was proposed for predicting the composition evolution of inclusions in the molten steel during the electroslag remelting process. The model was used to evaluate the transformation of composition of inclusions in a plain carbon steel and the mechanism of the transformation of inclusions was accurately revealed, which was mainly the mass transfer of aluminum through steel/slag reactions. The rate of the transformation of inclusions composition was the lowest in the metal pool, while that in the slag pool was the fastest which was due to the acceleration of reactions by higher temperature and faster fluid flow. Inclusions with smaller diameter had faster transformation rate, but had less content of Al2O3 in the final composition. The size of droplet showed little influence on the transformation of composition of inclusions. When the content of Al2O3 in the slag increased from 20 to 50 wt pct, the calculated content of Al2O3 in the final inclusions increased from 79 to 90 wt pct, approximately. The low content of Al2O3 in the slag was beneficial to the removal of aluminum in the steel, while the high content of Al2O3 in the slag increased the content of total aluminum in the steel.

Capillary-driven blood separation and in-situ electrochemical detection based on 3D conductive gradient hollow fiber membrane

It is essential to develop portable, versatile, and reliable diagnostic devices in point-of-care testing (POCT). The detection of biomarkers requires selective separation and large specific surface for high sensitivity and accuracy at trace levels in whole blood samples using POCT devices. Herein, a kind of 3D electrochemical biosensors were designed via in-situ synthesizing polyaniline (PANI) and platinum nanoparticles (Pt NPs) on polysulfone hollow fiber membrane (HFM) scaffolds with gradient porous structure. The gradient porous HFMs scaffolds provide uniform capillary flow, self-driven blood separation and sufficient enzyme immobilization sites. Simultaneously, the in-situ deposited materials fulfill interconnected conductive networks, thus ensuring accurate and rapid detection of the sensors without hindering capillary progress. These sensors display ultralow sampling (~3 μL), fast fluid flow (>1 μL/ms), wide linear range (glucose: 0–24 mM, R2=0.992; cholesterol: 0–9 mM, R2=0.999), high sensitivity and accuracy especially under different hematocrits in POCT applications towards glucose and cholesterol. The innovative integration of POCT biosensors with interconnected conductive nanoparticles, selective blood separation and gradient porous structures can find wide application in resource-limited regions, large population screening, and public health emergencies.

Velocity Measurement of Fast Flows Inside Small Structures with Tagged MRI

Velocity is one of the most important parameters to study in complex fluid flow systems. Magnetic resonance imaging (MRI) is a non-invasive tool for quantitative visualization of fast fluid flows. Many of the flow studies by MRI measure the velocity of a fluid media using either phase encoding or time of flight (TOF) measurements. Until now, motion-sensitized SPRITE is the best method for the velocity assessment of very fast flows when the structure is large enough compared to flow displacement during the encoding time ($$t_{{\text{p}}}$$). However, when displacement during the encoding time becomes greater than the pixel size, velocity misregistration takes place. To detect the velocity with accuracy, we need to reduce the encoding time. There is a restriction on the encoding time reduction in motion-sensitized SPRITE: both the velocity encoding, and spatial encoding times take place simultaneously, causing longer encoding time. If these two steps are separated, it is possible to reduce the encoding time. In this paper, we demonstrate how this can be achieved by applying a TOF approach where the fluid is labeled by a spatially periodic modulation of the magnetization. The modulation part is performed when the liquid is still moving slowly, and the imaging part does not require the bipolar gradient to be switched on and off. This leads to a reduction of the encoding time and greater accuracy in the detection of the fast flow velocity.

PoreFlow-Net: A 3D convolutional neural network to predict fluid flow through porous media

We present the PoreFlow-Net, a 3D convolutional neural network architecture that provides fast and accurate fluid flow predictions for 3D digital rock images. We trained our network to extract spatial relationships between the porous medium morphology and the fluid velocity field. Our workflow computes simple geometrical information from 3D binary images to train a deep neural network (the PoreFlow-Net) optimized to generalize the problem of flow through porous materials. Our results show that the extracted information is sufficient to obtain accurate flow field predictions in less than a second, without performing expensive numerical simulations providing a speed-up of several orders of magnitude. We also demonstrate that our model, trained with simple synthetic geometries, is able to provide accurate results in real samples spanning granular rocks, carbonates, and slightly consolidated media from a variety of subsurface formations, which highlights the ability of the model to generalize the porous media flow problem. The workflow presented here shows the successful application of a disruptive technology (physics-based training of machine learning models) to the digital rock physics community.

Study on the melting characteristics of steel scrap in molten steel

ABSTRACTSteel scrap is of great benefit for environmental protection. In converter steelmaking, bottom carbon injection was applied to enhance the scrap ratio and in EAF steelmaking, submerged carbon powder injection was used to accelerate the smelting of scrap. In these two cases, carbon powder is directly injected into molten metal to improve the scrap melting with effective carburization capacity and intense stirring effect. In this study, the induction furnace experiments were carried out to study the melting characteristics of steel scrap with different carbon contents and bottom-blowing gas flow rates. The results show that larger carbon content and faster fluid flow can promote scrap melting because the carburizing reaction can be accelerated by larger carbon concentration gradient and the heat transfer can be enhanced by larger stirring intensity. Finally, the convective mass transfer coefficient and heat transfer coefficient between steel bar and molten metal were also calculated.

Numerical Modeling of Reactive Transport and Self-Sealing Processes in the Fault-Controlled Geothermal System of the Guide Basin, China

Strong chemical reactions in the geothermal systems may cause sealing of fractures, which reduces the permeability in the reservoir and subsequently affects the heat production. However, it is difficult to reveal the sealing range in a deeply buried reservoir based on a limited number of downhole logs. This study recreated the sealing processes of the fault-controlled geothermal system in the Guide Basin, China, by reactive transport modeling. The modeling domain was discretized based on multiple interacting continua (MINC) approach, to address the nonequilibrium heat transport processes between the matrix and conduit in the fractured fault damage zone. Once the model was validated by observations of major ions in spring water and downhole temperature logs in the discharge area, it was used to determine the coupled processes of fluid, heat, and chemical transport in the reservoir and the resultant sealing ranges. It was found that the dissolution of albite and K-feldspar leads to the precipitation of smectite-Ca and illite in the middle and bottom of the fault under the condition of high concentration of Ca2+ and Mg2+ in the recharge water. Calcite veins were formed in discharge zone, because the horizontal fast flow in shallow subsurface zone supplied abundant Ca2+ and HCO3-. As a consequence, the permeability in the discharge zone reduced by 15% when compared to the original permeability of 100 mD. Moreover, another three self-sealing areas were formed near the recharge zone, the deep upgradient zone, and the downgradient area where the fast upward fluid flow occurred. Self-sealing subsequently prevented the deep circulation of the flow and heat absorption, which tends to make the fault-controlled geothermal system inactive.

Efficient modelling of solute transport in heterogeneous media with discrete event simulation

To address the problem of different time scales present in the simulation of solute transport through systems with a complex permeability structure such as fractured porous rocks, we propose a parallel discrete event simulation (DES) algorithm based on local time stepping criteria, specifically developed for the hybrid finite-element node-centred finite volume (FV) framework. A preemptive-event-processing (PEP) approach is applied to synchronise discrete events with sufficiently close time stamps, thereby facilitating the parallelisation for shared memory architectures. The accuracy of the presented DES-PEP scheme is first verified against the analytical solution of a 1D advection equation with spatially variable coefficients. The DES scheme is then applied to simulate tracer advection through a 3D model of highly heterogeneous fractured rock represented by an unstructured adaptively refined mesh with over 1 million elements. DES produces results comparable to those of a conventional time-driven simulation (TDS), but uses less than 1% of the execution time. Analysis of event distributions shows that updates occur almost exclusively in a small number of FV cells marked by order-of-magnitudes faster fluid flow and advection-dominated transfer, while slow-flowing cells remain inactive and excluded from computations. This focusing of the computational effort leads to high simulation efficiency while simultaneously diminishing round-off errors. Scalability tests with a parallel version of DES on shared memory demonstrate further computational speedups mirroring the increased number of threads. With the use of 20 threads, execution time is reduced from 42.5 days (with TDS) to only 1.5 hours, equivalent to a speedup of over 670. This parallel DES algorithm therefore enables efficient multi-core simulation of solute transport in heterogeneous geologically realistic systems.

Numerical simulation of calcite vein formation and its impact on caprock sealing efficiency – Case study of a natural CO2 reservoir

For the long-term CO2 geological storage, the evolution of the caprock sealing efficiency has received increasing attention. In this paper, the Huangqiao CO2 gas field in Jiangsu Province, China, where the calcite veins have been found in the lower part of mudstone caprock, is considered as a natural analogue site for CO2 geological sequestration (CCS). To ascertain the dynamic formation process of calcite vein and its impact on the evolution of caprock sealing efficiency, a one-dimensional model was designed to represent the fractured reservoir-caprock system. Numerical simulations were performed using the multiphase reactive transport program TOUGHREACT. Sensitivity analyses of fracture permeability and calcite reaction rate were made. The simulation results illustrate that calcium bicarbonate decomposes to form calcium carbonate and release CO2 from solution due to the pressure decay as the CO2-rich fluids migrate upwards along the fracture. The formation of calcite vein decreases the porosity and permeability significantly, which can enhance the integrity and sealing efficiency of caprock. Sensitivity analyses indicate that the formation of calcite vein is facilitated by the fast fluid flow, and calcite vein tends to form in the vicinity of reservoir-caprock interface under the slow-flow condition as the decrease of fracture permeability. Information currently available in Huangqiao CO2 gas field and some other area describing the formation of calcite vein shows good agreement with our simulation results. The mudstone caprock with fractures and faults is able to keep CO2 from leaking for a long time as the case of Huangqiao area. The methods and analyses presented here may be useful for CO2 storage sites with similar conditions.

Multiscale Modeling Provides Differentiated Insights to Fluid Flow-Driven Stimulation of Bone Cellular Activities

Both the shape of bone organs and the micro-architecture of bone tissue are significantly influenced by the prevailing mechanical loading. In this context, several of the most striking and hence also most debated issues relate to the question how bone is actually able to sense and process its mechanical environment. Among other stimuli, it has been hypothesized that the macroscopic mechanical loading induces pressure gradients in the pore spaces of bone tissue, and that these pressure gradients lead to fluid flow exciting the cells that are located in the pore spaces. Since in vitro tests confirmed that cells subjected to the flow of the surrounding fluid indeed respond in form of altered expression activities, the scientific community has in large part embraced the ``fluid flow-hypothesis''. However, direct experimental evidence as to the actual occurrence of sufficiently fast fluid flow (in order to reach the cell responses observed in vitro) has not been attained so far. In this paper, a multiscale modeling strategy is presented (inspired by the well-established concept of continuum micromechanics), allowing for upscaling (or homogenization) of the fluid flow contributions in the canalicular, lacunar, and vascular pores in terms of a corresponding macroscopic permeability of bone tissue. The same model also allows for proceeding the opposite way, namely for downscaling macroscopically acting pressure gradients to the pore levels. Thus, physiologically relevant mechanical loading conditions can be related straightforwardly to the correspondingly arising pore-scale pressure gradients, and, through considering the resulting pressure gradients in suitable transport laws, also to related fluid velocities. When comparing the such computed fluid velocities with the fluid velocities that were shown to efficiently excite bone cells in vitro, it turns out that pressure-driven fluid flow in the canalicular pores is probably not a potent mechanical stimulus for osteocytes, whereas fluid flow in the vascular pores may indeed reach the required fluid velocities and hence excite the therein residing osteoblasts, osteoclasts, and bone lining cells. In conclusion, the work presented in this thesis provides important, unprecedented insights as to the observation scale-specific cellular mechanosensation in bone.

Quantification of Viscous Creep Influence on Storage Capacity of Caprock

In the light of growing concerns for the climate change, it is of particular interest for governments to encourage efficient capture and safe storage of large amounts of carbon dioxide in the subsurface. In this perspective and in order to accurately predict the short and long-term response of the reservoir, a precise characterization of the geomechanical properties has to be carried out. In addition to the classical poroelastic properties, time-dependent deformation, such as viscous creep should also be considered. Storage capacity of a caprock may be seriously affected by local creep deformation allowing fast vertical fluid flow through an a priori very impermeable formation. Within this study, we investigate the ease to creep of Opalinus clay (Jurassic shale) under shallow geological storage conditions and predict the propagation of high porosity channels at operational time scales. The effective poroviscoelastic parameters of rock are inferred from the novel laboratory experiments that allow evaluation of time-dependent deformation. The bulk viscosity of the shale is found to be ∼ 1014 - 1015 Pa·s and it decreases with rise of temperature and pore fluid pressure to total mean stress ratio. Furthermore, the propagation speed of high porosity channels (porosity waves) is calculated to be on the order of the centimeters per year.

A Mechanism for Cytoplasmic Streaming: Kinesin-Driven Alignment of Microtubules and Fast Fluid Flows

The transport of cytoplasmic components can be profoundly affected by hydrodynamics. Cytoplasmic streaming in Drosophila oocytes offers a striking example. Forces on fluid from kinesin-1 are initially directed by a disordered meshwork of microtubules, generating minor slow cytoplasmic flows. Subsequently, to mix incoming nurse cell cytoplasm with ooplasm, a subcortical layer of microtubules forms parallel arrays that support long-range, fast flows. To analyze the streaming mechanism, we combined observations of microtubule and organelle motions with detailed mathematical modeling. In the fast state, microtubules tethered to the cortex form a thin subcortical layer and undergo correlated sinusoidal bending. Organelles moving in flows along the arrays show velocities that are slow near the cortex and fast on the inward side of the subcortical microtubule layer. Starting with fundamental physical principles suggested by qualitative hypotheses, and with published values for microtubule stiffness, kinesin velocity, and cytoplasmic viscosity, we developed a quantitative coupled hydrodynamic model for streaming. The fully detailed mathematical model and its simulations identify key variables that can shift the system between disordered (slow) and ordered (fast) states. Measurements of array curvature, wave period, and the effects of diminished kinesin velocity on flow rates, as well as prior observations on f-actin perturbation, support the model. This establishes a concrete mechanistic framework for the ooplasmic streaming process. The self-organizing fast phase is a result of viscous drag on kinesin-driven cargoes that mediates equal and opposite forces on cytoplasmic fluid and on microtubules whose minus ends are tethered to the cortex. Fluid moves toward plus ends and microtubules are forced backward toward their minus ends, resulting in buckling. Under certain conditions, the buckling microtubules self-organize into parallel bending arrays, guiding varying directions for fast plus-end directed fluid flows that facilitate mixing in a low Reynolds number regime.

Water and methane in shale rocks: Flow pattern effects on fluid transport and pore structure

Using molecular dynamics simulations, the two‐phase flow of water and methane through slit‐shaped nanopores carved from muscovite is studied. The simulations are designed to investigate the effect of flow patterns on fluids transport and on pore structure. The results indicate that the Darcy's law, which describes a linear relation between flow rate and pressure drop, can be violated when the flow pattern is altered. This can happen when the driving force, that is, the pressure drop, increases above a pore‐size dependent threshold. Because the system considered here contains two phases, when the fluid structure changes, the movement of methane with respect to that of water changes, leading to the violation of the Darcy's law. Our results illustrate the importance of the capillary force, due to the formation of water bridges across the model pores, not only on the fluid flow, but also on the pore structure, in particular its width. When the water bridges are broken, perhaps because of fast fluid flow, the capillary force vanishes leading to significant pore expansion. Because muscovite is a model for illite, a clay often found in shale rocks, these results advance our understanding regarding the mechanism of water and gas transport in tight shale gas formations. © 2015 American Institute of Chemical Engineers AIChE J, 61: 2993–2999, 2015

An Iterative CT Reconstruction Algorithm for Fast Fluid Flow Imaging.

The study of fluid flow through solid matter by computed tomography (CT) imaging has many applications, ranging from petroleum and aquifer engineering to biomedical, manufacturing, and environmental research. To avoid motion artifacts, current experiments are often limited to slow fluid flow dynamics. This severely limits the applicability of the technique. In this paper, a new iterative CT reconstruction algorithm for improved a temporal/spatial resolution in the imaging of fluid flow through solid matter is introduced. The proposed algorithm exploits prior knowledge in two ways. First, the time-varying object is assumed to consist of stationary (the solid matter) and dynamic regions (the fluid flow). Second, the attenuation curve of a particular voxel in the dynamic region is modeled by a piecewise constant function over time, which is in accordance with the actual advancing fluid/air boundary. Quantitative and qualitative results on different simulation experiments and a real neutron tomography data set show that, in comparison with the state-of-the-art algorithms, the proposed algorithm allows reconstruction from substantially fewer projections per rotation without image quality loss. Therefore, the temporal resolution can be substantially increased, and thus fluid flow experiments with faster dynamics can be performed.

Refractometric monitoring of dissolution and fluid flow with distributed feedback dye laser sensor.

Monitoring the dissolution of solid material in liquids and monitoring of fluid flow is of significant interest for applications in chemistry, food production, medicine, and especially in the fields of microfluidics and lab on a chip. Here, real-time refractometric monitoring of dissolution and fast fluid flow with DFB dye laser sensors with an optical imaging spectroscopy setup is presented. The dye laser sensors provide both low detection limits and high spatial resolution. It is demonstrated how the materials NaCl, sucrose, and bovine serum albumin show characteristic dissolution patterns. The unique feature of the presented method is a high frame rate of up to 20 Hz, which is proven to enable the monitoring of fast flow of a sucrose solution jet into pure water.