Steady-state Flow Research Articles

Analytical model and flow velocity control of electrohydrodynamics system with multi-needle corona discharge

For the flow field distribution and control mechanism generated by the electrohydrodynamics (EHD) system with multi-needle corona discharge, this paper takes the multi-needle EHD pump as the research object, establishes different types of physical models through regional division, constructs multi-physical field coupling relationship, and derives a simplified EHD flow velocity equation suitable for the EHD system with multi-needle corona discharge. Combined with the intelligent optimization method of population evolution, a novel and effective intelligent algorithm is designed for the numerical analysis of the velocity profile distribution of a multi-needle EHD pump, and the flow velocity control law of the multi-needle EHD pump is analyzed by quantitative calculation. The validity of the model and analysis is verified by the electric field and flow field simulation of the multi-needle EHD pump system. The calculation results show that the voltage parameter is more dominant than the electrode spacing parameter in the steady-state flow velocity control of the multi-needle EHD pump, and both the maximum flow velocity and the average flow velocity are superlinearly controlled by voltage. In the design of multi-needle EHD pump with an electrode spacing of 1 cm, the simulation results show that the maximum gas flow velocity of 0.82 m/s can be obtained by providing 5000 V voltage, which verifies the design of a miniaturized multi-needle EHD pump and its feasibility in gas lasers and other application scenarios.

Numerical simulation of aluminum-steel clad strip production using horizontal single belt casting process

A 3-D steady-state turbulent flow and solidification model was developed to simulate melt flow in a Horizontal Single Belt Caster for the production of an Al-Steel composite strip. The steel substrate is attached to the moving belt and moves at the same speed as the belt while the aluminum melt is introduced onto the substrate via an extended nozzle melt delivery system. A finite volume method was used to numerically solve the governing equations. In order to model the turbulent flow, a low Reynolds k − ε turbulent model was adopted. The developed numerical model was further employed to investigate the effect of such parameters as clad thickness, casting speed, molten aluminum superheat, and heat extraction rate from the belt surface on fluid flow and temperature fields in the system. It was found that for a certain clad thickness, casting speed and cooling rate should be adjusted properly and outlet strip temperature is independent of Inlet melt superheat.

CFD approach for determining the losses in two-phase flows through the last stage of condensing steam turbine

Analyzing and simulating wet steam flows within steam turbines holds significant importance, especially due to the presence of a liquid phase in the low-pressure stages of the turbine, resulting in consequential losses that demand careful consideration. Considering these conditions, this study employs advanced predictive CFD models to simulate the wet steam flow within the actual 3D geometry of the final stage in a 200 MW steam turbine, which is observed in the least research due to the complexity of modeling and analysis of three-dimensional flows. This advancement promises more precise and reliable results. Employing the ANSYS CFX software, this study engages in numerical simulations of steady-state compressible two-phase flow. Furthermore, the study offers practical equations to quantify the losses within the entire stage, which serves as a valuable metric for assessing loss levels and offers a benchmark for design improvements aimed at loss reduction. Based on the results, 10 % of losses occur along the stator and 1 % along the rotor, and a total of 11 % of losses occur along the entire stage. Finally, the efficiency of the stage is calculated to be 89 %. Steam condensation strengthens the shock waves, changes their location, diminishes Mach number and the flow velocity, and alters the flow angle. It reduces the efficiency of the turbine by 1.27 % and also reduces the work done by the turbine by 13.97 %. This emphasizes the significant influence of condensation on flow characteristics, emphasizing the necessity of conducting comprehensive investigations into this phenomenon.

Magnetic field dragging in filamentary molecular clouds

Context. Maps of polarized dust emission of molecular clouds reveal the morphology of the magnetic field associated with star-forming regions. In particular, polarization maps of hub-filament systems show the distortion of magnetic field lines induced by gas flows onto and inside filaments. Aims. We aim to understand the relation between the curvature of magnetic field lines associated with filaments in hub-filament systems and the properties of the underlying gas flows. Methods. We consider steady-state models of gas with finite electrical resistivity flowing across a transverse magnetic field. We derive the relation between the bending of the field lines and the flow parameters represented by the Alfvén Mach number and the magnetic Reynolds number. Results. We find that, on the scale of the filaments, the relevant parameter for a gas of finite electrical resistivity is the magnetic Reynolds number, and we derive the relation between the deflection angle of the field from the initial direction (assumed perpendicular to the filament) and the value of the electrical resistivity, due to either Ohmic dissipation or ambipolar diffusion. Conclusions. Application of this model to specific observations of polarized dust emission in filamentary clouds shows that magnetic Reynolds numbers of a few tens are required to reproduce the data. Despite significant uncertainties in the observations (the flow speed, the geometry and orientation of the filament), and the idealization of the model, the specific cases considered show that ambipolar diffusion can provide the resistivity needed to maintain a steady state flow across magnetic fields of significant strength over realistic time scales.

Effect of Fe and Mn on structure, mechanical properties, and oxidation resistance of lightweight intermetallic Al55Cr23Ti22 complex concentrated alloy

In this study, we analysed the effect of Fe, Mn, or Fe and Mn additions (5 or 10 at%) on the structure, mechanical properties, deformation behaviour, including microstructure evolution, and oxidation resistance of a lightweight (density of 3.92 g/cm3) intermetallic Al55Cr23Ti22 complex concentrated alloy (CCA) with a L12 + C11b structure. The additions of Fe, Mn, or Fe and Mn (at the expense of Cr) retained the density below 4 g/cm3 and resulted in forming a D8a phase (Th6Mn23-prototype; cF120; Fm-3m) in all the alloys, except for the Al55Cr18Ti22Mn5 alloy. The D8a phase nucleated with a different morphology within or adjacent to the C11b phase, and adopted an orientation relationship of (110)C11b || (4‾4‾ 0)D8a, [3 3‾ 1]C11b || [1‾ 11‾]D8a, which provided coherent C11b/D8a interfaces. Alloying with Mn or Fe and Mn had either neutral or negative effect on the mechanical properties, while the Fe additions boosted the strength along with some decrease in the compressive plasticity at room temperature. Specifically, the Al55Cr13Ti22Fe10 alloy showed a yield strength of 250 MPa at 1000°С, which was 60 % higher compared to the Al55Cr23Ti22 alloy. During plastic deformation, all the alloys demonstrated pronounced strain hardening at T ≤ 800 °C and steady state flow at 1000 °C. Post-deformation observation of the microstructure of the Al55Cr13Ti22Fe10 alloy showed the inhomogeneous distribution of the strain-induced defects between the L12 matrix and (C11b + D8a) regions at 800 °C and partial recrystallisation of these phases at 1000 °C. All the alloys exhibited complex oxidation behaviour with multistage oxidation kinetics. The addition of 5 at% of Fe or Mn was beneficial for the oxidation resistance, while the further increase in their contents intensified the mass gain after a certain time. The latter effect was more pronounced in the Al55Cr13Ti22Mn10 alloy than in the Al55Cr13Ti22Fe10 alloy, because of forming a loose Al2O3 oxide layer. All the alloys investigated exhibited a superior synergy of 1000°C-specific yield strength and compressive plasticity at room temperature, as well as a lower mass gain after 100 h at 1000 °C, compared to both lightweight and the most oxidation-resistant refractory CCAs.

A novel discretized physics-informed neural network model applied to the Navier–Stokes equations

The advancement of scientific machine learning (ML) techniques has led to the development of methods for approximating solutions to nonlinear partial differential equations (PDE) with increased efficiency and accuracy. Automatic differentiation has played a pivotal role in this progress, enabling the creation of physics-informed neural networks (PINN) that integrate relevant physics into machine learning models. PINN have shown promise in approximating the solutions to the Navier–Stokes equations, overcoming the limitations of traditional numerical discretization methods. However, challenges such as local minima and long training times persist, motivating the exploration of domain decomposition techniques to improve it. Previous domain decomposition models have introduced spatial and temporal domain decompositions but have yet to fully address issues of smoothness and regularity of global solutions. In this study, we present a novel domain decomposition approach for PINN, termed domain-discretized PINN (DD-PINN), which incorporates complementary loss functions, subdomain-specific transformer networks (TRF), and independent optimization within each subdomain. By enforcing continuity and differentiability through interface constraints and leveraging the Sobolev (H 1) norm of the mean squared error (MSE), rather than the Euclidean norm (L 2), DD-PINN enhances solution regularity and accuracy. The inclusion of TRF in each subdomain facilitates feature extraction and improves convergence rates, as demonstrated through simulations of threetest problems: steady-state flow in a two-dimensional lid-driven cavity, the time-dependent cylinder wake, and the viscous Burgers equation. Numerical comparisons highlight the effectiveness of DD-PINN in preserving global solution regularity and accurately approximating complex phenomena, marking a significant advancement over previous domain decomposition methods within the PINN framework.

Stratified numerical heat and mass transport mechanism in MHD Maxwell fluid flow with nonuniform heat source/sink

The present boundary layer flow of Maxwell fluid over a stretching sheet has good number of practical applications in metallurgy, drawing of plastics, polymer sheet extrusion including hot rolling extrusion, glass blowing, spinning of fibers, rubber and plastic sheets, crystal growing and many more. Due to these extensive applications of Maxwell fluid in engineering, medicine and manufacturing industries including the above-mentioned applications, authors have motived, inspired and investigated the present problem. However, in this research paper, the influences of Soret and Dufour effects on the steady-state Maxwell fluid flow past a stretching sheet with nonuniform heat source/sink are considered numerically. The thermal and concentration stratifications impacts are also incorporated. The viscous dissipation and magnetic field effects are also included in the respective governing equations. The main novelty and uniqueness of this numerical research is to generalize the earlier studies and describe the salient features of magneto-thermo visco-elastic dissipative Maxwell fluid motion about a stretching sheet with cross-diffusion effects under the influence of double stratification phenomena. To differentiate the non-Newtonian fluids from those of Newtonian fluids, a well-known Maxwell fluid flow model is used in the present study. The investigated physical problem results the highly nonlinear coupled partial differential equations (PDEs) and which are not amenable to any of the direct methods. Suitable similarity transformations are deployed to reduce the highly complex PDEs into the system of ordinary differential equations (ODEs). A robust BVP4C Matlab function is employed to solve the rendered dimensionless system of ODEs. The numerically generated computed data is plotted in terms of velocity, temperature and concentration profiles including engineering quantities of interest such as skin-friction, Nusselt and Sherwood numbers in the flow region. It is evident from the current analysis that, the amplified magnetic field decreases the velocity field and increases the thermal and concentration distribution fields. Accelerating Maxwell’s number diminished the flow velocity and increased the temperature field. Increasing Soret and Dufour numbers enhances the concentration and temperature fields, respectively. Amplifying Maxwell’s number raises the skin-friction coefficient and enlarging the thermal stratification parameter magnifies the thermal transport rate. The mass transport rate amplified with a raise in concentration stratification number in the flow region. Finally, it is provided that, the current results are excellently matching with earlier published results in the literature and it confirms the accuracy of the used numerical method and the produced similarity solutions.

Safe mud weight window in wellbore with mud-cake: A simple solution and verification

Under overbalanced drilling condition, a layer of particulates from drilling mud, called mud-cake or filter-cake, is often formed on the wellbore surface as the drilling fluid seeps through the surrounding geological formation. Mud-cake acts like a soft filter reducing the fluid pressure exerted on the wellbore surface by the fluid in the well. In this work, the safe mud weight window for wellbores with mud-cake is analytically derived by combining the long-term poroelastic wellbore stress solutions with steady-state flow solution for a two-layer cylindrical well. Parametric study on mud-cake permeability and thickness verifies that a wellbore with mud-cake transits smoothly from permeable wellbore to impermeable wellbore as the mud-cake accumulates. The new solution of breakdown pressure is also validated by a hydromechanical interaction numerical simulation.

Integrated wellbore-reservoir modeling based on 3D Navier–Stokes equations with a coupled CFD solver

The occurrence of fluid flow near a wellhead is the major concern of the petroleum industry, as pressure drop, loss of formation, and other variables of interest are mostly affected in this region. The fluid flows from the hydrocarbon reservoir to the wellbore can be characterized as laminar to turbulent; thus, it is important to model this phenomenon with the integrated wellbore-reservoir model. Using 3D Navier–Stokes equations, an integrated wellbore-reservoir model is created in this study, and it incorporates the formation damage zone. For the porous-porous and porous-fluid interfaces, the General Grid Interface (GGI) approach is applied in conjunction with the conservative mass flux interface model. Model equations are solved using a velocity-pressure coupling solver that is pressure-based. For reliable and quick results, the system of equations is solved using an algebraic multigrid approach. The pressure diffusivity equation’s analytical solution under steady-state flow circumstances is used to validate the model. The integrated wellbore-reservoir model is applied to different reservoir scenarios, for example, different production rates, formation zones, and reservoir formation conditions. The results indicate that the present Computational Fluid Dynamics (CFD) model can be extended to simulate the real field scale model. integrated wellbore-reservoir modeling based on 3D Navier–Stokes equations with efficient computational techniques can lead the field of petroleum industries to advance current knowledge.

A deep learning-based surrogate model for trans-dimensional inversion of discrete fracture networks

Fractures and their geometrical patterns are usually required to analyze the mechanical and flow properties of porous media in the subsurface. Fracture characterization is therefore regarded of crucial importance for optimizing production management or achieving maximum storage capacity. In this research, we propose to invert the fracture networks under the Bayesian framework for the uncertainty quantification. In particular, the number of fractures in the modelling system is treated as unknown, leading to a trans-dimensional inverse problem, and the reversible jump Markov chain Monte Carlo algorithm is applied to sample the model space with possible model moves proposed in the sampling process. A deep learning network is further applied as a surrogate model in the sampling process for increasing the computational efficiency, instead of using the physical forward simulator. We apply the proposed methodology to estimate the spatial distribution of fracture networks based on the head measurements from the steady-state flow simulation. The prior distributions of fracture parameters such as position, orientation and length are described using the discrete fracture networks approach that is deeply rooted in stochastic modelling. Due to the high non-uniqueness, the correct spatial distribution of fracture patterns cannot be successfully recovered in this case study, even a good match between observed and simulated head data is reached. More analysis could be performed in the future with the production historical data or more informative priors.

Steady-state flow under surface recharge through unconfined aquifer with depth-decaying hydraulic conductivity: Analytical results

This paper presents some analytical results related to groundwater flow through an unconfined horizontal aquifer induced by areal recharge on the top and a decaying hydraulic conductivity. Under steady-state conditions, and in the context of Boussinesq equation, exact analytical solutions describing drainage into one or two penetrating channels at the aquifer boundaries have been derived in closed forms. The analytical expressions have been used to investigate the existence of water divide inside the unconfined aquifer. Based on the derived analytical solutions, a closed-form analytical formula is developed for calculating groundwater transit time within Dupuit-type flow system. The analytical transit time expression is simply expressed in terms of common mathematical functions. Analytical results are verified against a numerical model and show excellent agreements. The analytical transit time is validated against a numerical one obtained from a two-dimensional model representing a rectangular unconfined aquifer. Based on the explicit closed-form solution, a fully analytical inverse problem to estimate the decay parameter is proposed using a least-square objective function. The solution of the inverse problem simply corresponds to the solution of a nonlinear algebraic equation obtained from the definition of the objective function and the form of the analytical solution.

Isolation of the contribution of viscous flow to initiation of pentaerythritol tetranitrate during sub-shock impact

The drop weight impact experiment is used routinely to provide an initial screening of the handling sensitivity of new explosives. Despite the ubiquity and simplicity of the drop weight impact test, the physical mechanisms responsible for generating temperatures sufficiently high for the initiation of explosive reactions are not well understood. Preliminary work has shown that temperatures sufficient for ignition are in theory achievable in steady-state Poiseuille flow at the flow velocities observed experimentally with temperature-dependent shear viscosities. However, it is far from certain that such steady-state flow conditions can be achieved in the drop weight impact test because of its short duration. Therefore, here we study heat generation both experimentally and numerically to quantify the temperature distributions in molten pentaerythritol tetranitrate (PETN). Drop weight experiments have been performed starting with PETN that has been melted on a transparent anvil. The experimental results are consistent with our finite element calculations that indicate that the temperature does not approach the level needed for ignition on the time scales of the experiment. Interestingly, ignition regularly occurs in solid samples under the same conditions, so we discuss the phenomenology of ignition of both solid and molten PETN in the drop weight test and provide constraints to numerical simulations.

Unified approach for describing rheological behavior of soil and mineral substrates modified with polymers

Studies in the rheology of natural aqueous dispersions (soils and their mineral substrates) as well as the approaches to control rheological parameters of these systems are of the prime importance to progress in the modern agricultural technologies, geoengineering, construction, etc. To advance in these fundamental and applied directions both original processing of the experimental results and search for the promising modifying agents are required. In this paper, rheological behavior of a representative range of virgin and modified aqueous soils, quartz sand and clays was studied. Modification of the above aqueous dispersed systems with polyelectrolytes and their complexes provided variation of the basic viscoelastic parameters corresponding to the linear viscoelastic region (initial storage modulus G0′, initial loss modulus G0", and strain γ0) and to the transition to steady-state flow (storage modulus Gin′ and strain γin) within 1 – 2 orders of magnitude. For samples studied, correlations for these mechanical characteristics were found – with the growth in the values of G0′ and G0′′, the increase in the values of Gin′ and decrease in the values of γ0 and γin were observed. Based on these correlations the master curves for the strain dependences of storage and loss modulus as well as for loss tangent were constructed. The appearance of the master curves reflected the unified regularities of the rheological response of dispersed systems which were attributed to the general features of structural evolution caused by the mechanical loading. Procedure for prediction of the rheological behavior of aqueous soil samples based on the experimental measurement of only two experimental characteristics (initial values of storage and loss modulus G0′ and G0′′ respectively) was proposed. The validity of this approach was tested using independent experimental data. The original approach obtained can be used for express analysis of the rheology of natural aqueous dispersed materials.

Quasi-Newton positivity-preserving scheme for the Spalart-Allmaras turbulence model using unstructured grids

A new implicit method for solving the Spalart-Allmaras (SA) turbulence model is proposed using a formal second-order upwind scheme on unstructured grids for steady-state flows. The mean-flow set of equations and the SA model equation are solved in a loosely coupled manner. While the Jacobian of the mean-flow equations is derived from a low-order approximation of the residual (i.e. the defect-correction approach), the SA Jacobian is obtained by modifying a direct linearization of the second-order residual. The modified Jacobian is designed to form an M-matrix without the artificial time derivative commonly used for steady-state problems. Namely, no time step is involved in solving the SA model equation. Thanks to a special design of the M-matrix, the positivity of the SA model working variable and the convergence of the SA model linearized problem (fixed-point iterative problem) is guaranteed. To further enhance the overall stability of the flow solver, the Runge-Kutta implicit algorithm is employed, allowing CFL numbers as high as one to two thousand for the mean-flow equations. A second-order upwind scheme is achieved with a least-square method using a limiter to suppress oscillation in the solution. However, second-order upwind scheme discretization of turbulence models may lack robustness, especially when using unstructured grids. The limiter can hinder the convergence of the non-linear iterations, especially of the turbulence model. A square root transformation is applied to the dependent variable of a baseline SA model to improve the non-linear convergence characteristics. Three variants of the SA model are implemented and tested together with two limiters. Numerical simulations of a broad range of aerodynamic applications are conducted. The transformed variant exhibits the least sensitivity to the limiter type.

Dynamics and Chaos of Convective Fluid Flow

In this paper, a mathematical model of fluid flows in a convective thermal system is developed, and a five-dimensional dynamical system is developed for the investigation of the convective fluid dynamics. The analytical solutions of periodic motions to chaos of the convective fluid flows are developed for steady-state vortex flows, and the corresponding stability and bifurcations of periodic motions in the five-dimensional dynamical system are studied. The harmonic frequency-amplitude characteristics for periodic flows are obtained, which provide energy distribution in the parameter space. Analytical homoclinic orbits for the convective fluid flow systems are developed for the asymptotic convection through the infinite-many homoclinic orbits in the five-dimensional dynamical system. The dynamics of fluid flows in the convective thermal systems are revealed, and one can use such methodology to predict atmospheric and oceanic phenomena through thermal convections.

Fluid-to-fluid similarity and CFD predictions of surrogate fluid as a replacement for R11 refrigerant used in a subcooled flow boiling analysis: Validation against reference experimental data

In this study, we present the possibility of substituting the primary fluid Freon 11 (CCl3F, R11) used in the experimental thermohydraulic test facility which offers the advantage to obtain phase change at relatively low heat fluxes and pressure if compared to water working fluid. Nevertheless, R11 is a CFC (Chlorofluorocarbures) part of the gases that contribute to the degradation of the ozone layer.For this purpose, four working fluids (non-CFC) are judiciously selected to replace the R11, namely the R123, R134a, R143a and CO2, and this through multidimensional Computational Fluid Dynamics (CFD) modeling of steady state flow boiling phenomenon. The calculation model covers a wide range of mass fluxes (435 – 1443 kg/m2s) and heat fluxes (1.2– 36 W/cm2); it predicts the heat transfer rates and transitions points for each flow regime. In this research, the experiment's data were compared to the outcomes of Ansys-CFX computations, using a steady Reynolds-Averaged Navier-Stokes (Steady-RANS) model, to investigate the best replacement refrigerant for R11. The turbulence effects on the mean flow and near wall are taken into consideration using the Shear Stress Transport (SST k-ω) turbulence model. The results from the four fluids were transposed to their water equivalent and compared to those deduced from the experimentation and correlations available in the literature to select the appropriate substitution fluid. The results qualitative and quantitative for vertical and horizontal subcooled boiling flow at the CHF location show that, the most effective surrogate fluid is R123 (HCFC), is still widely used in the refrigeration and air-conditioning industry, then R134a (HFC), then R143a (HFC).

Localization estimation of two leaks in pipelines through Monte Carlo simulations and hydraulic-spatial constraints

The problem of localizing two leaks using only flow rate and pressure measurements at the boundaries of a pipeline, and under steady-state flow conditions, is ill-posed due to the undetermined nature of the inverse problem, which involves two coupled equations with four unknowns associated with the presence of the leaks: two emitter coefficients and two locations. Therefore, attempting to solve this problem using any method without imposing additional constraints leads to an unbounded solution space, which contains solutions that may be physically meaningless. In this article, we propose a four-algorithm method that incorporates both spatial and hydraulic constraints to filter out physically infeasible solutions. The proposed method is based on Monte Carlo simulations, which use input data from hydraulic instruments installed at the boundaries of the pipeline, as well as random values with predefined probabilities that are bounded by the hydraulic-spatial constraints. The outputs of the method are probability distributions for the four unknowns. To demonstrate the feasibility of the method, results obtained through simulations and experimental testing on a test bed are presented.

Analyzing the thermal performance of transient heat transfer mechanism due to the combined effects of solar energy and variable surface temperature: Growing applications of solar energy in co-axial pipes

The current analysis is carried out to study the laminar convective heat transfer characteristics that change with time in the co-axial pipes along the impact of heat radiation and variable surface temperature. The flow is assumed along the axial direction of the pipe, and variable boundary condition is assumed at the surface of the pipe due to the variable surface temperature. A two-dimensional mathematical model made up of non-linear partial differential equations is solved using the implicit finite difference method. The project involves predicting the thermal efficiency of a pipe's time dependent flow across a number of flow model-relevant parameter ranges. Graphical representations highlighted the derived predictions. After separating the numerical solutions into the time independent and the time dependent components, the time dependent energy and surface shearness were found using the data from the time independent component. Comprehensive detail of the obtained results for the non-dimensional parameters included in the flow formulation is predicted for steady state velocity, temperature distribution, time dependent surface sheerness, and time dependent energy sheerness, which is given in results and discussion section of the manuscript. Major focus is given on the influence of the radiation parameter on the above-mentioned primary measures. Furthermore, it is concluded that in all cases, the steady state flow is as R→∞ and velocity profile as U→1 and θ→0, which ensured the accuracy of the obtained results by satisfying the boundary conditions. For various values of the fluid's absorption parameter D = 1.0, 3.0, 5.0, and 10.0, the flow profile is increased and U→1 as R→∞. Simultaneously, thermal distribution also increases and θ→0 as R→∞.

Flow rate influence on sediment depth estimation in sewers using temperature sensors.

Enhancing sediment accumulation monitoring techniques in sewers will enable a better understanding of the build-up processes to develop improved cleaning strategies. Thermal sensors provide a solution to sediment depth estimation by passively monitoring temperature fluctuations in the wastewater and sediment beds, which allows evaluation of the heat-transfer processes in sewer pipes. This study analyses the influence of the flow conditions on heat-transfer processes at the water-sediment interface during dry weather flow conditions. For this purpose, an experimental campaign was performed by establishing different flow, temperature patterns, and sediment depth conditions in an annular flume, which ensured steady flow and room-temperature conditions. Numerical simulations were also performed to assess the impact of flow conditions on the relationships between sediment depth and harmonic parameters derived from wastewater and sediment-bed temperature patterns. Results show that heat transfer between water and sediment occurred instantaneously for velocities greater than 0.1 m/s, and that sediment depth estimations using temperature-based systems were barely sensitive to velocities between 0.1 and 0.4 m/s. A depth estimation accuracy of ±7 mm was achieved. This confirms the ability of using temperature sensors to monitor sediment build-up in sewers under dry weather conditions, without the need for flow monitoring.

Egg-free mayonnaise-type emulsions stabilized with proteins derived from the larvae of Tenebrio molitor

In view of demanding alternative protein sources to replace the conventional ones, egg-yolk free mayonnaise-type emulsions were made from protein preparations extracted from Tenebrio molitor larvae by applying alkaline extraction (ASP), alkaline extraction followed by isoelectric precipitation (AIP) and salt-assisted treatment followed by dialysis (SSP). Their droplet size, microstructure and rheological properties were compared with egg-yolk mayonnaise (CEY). All emulsions exhibited similar droplet size distribution, with the CEY-mayonnaise having a broader range. SSP showed the smallest mean droplet size acting as a more effective emulsifier. Steady-state flow properties and dynamic oscillatory experiments within the linear viscoelastic region of mayonnaise-type emulsions were performed. The higher value of G′ compared to the value of G″ indicated the elastic character of all samples. Both moduli were no-highly frequency dependent, which was in line with their solid-like nature. The thixotropic behaviour of the emulsions was evaluated by three-interval thixotropy tests revealing higher recovery rate in the case of CEY and ASP. Temperature sweeps were also performed and revealed that AIP and SSP showed less temperature dependence, indicating their lower sensitivity to temperature variations. Overall, the results of this study suggest that the protein preparations extracted from Tenebrio molitor larvae have the potential for producing egg yolk-free mayonnaise-type emulsions.