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Nuclear magnetic resonance rheology (Rheo-NMR) is a valuable tool for studying the transport of suspended non-colloidal particles, important in many commercial processes. The Rheo-NMR imaging technique directly and quantitatively measures fluid displacement as a function of radial position. However, the high field magnets typically used in these experiments are unsuitable for the industrial environment and significantly hinder the measurement of shear stress. We introduce a low field Rheo-NMR instrument ( 1 H resonance frequency of 10.7 MHz ), which is portable and suitable as a process monitoring tool. This system is applied to the measurement of steady-state velocity profiles of a Newtonian carrier fluid suspending neutrally-buoyant non-colloidal particles at a range of concentrations. The large particle size (diameter > 200 μ m ) in the system studied requires a wide-gap Couette geometry and the local rheology was expected to be controlled by shear-induced particle migration. The low-field results are validated against high field Rheo-NMR measurements of consistent samples at matched shear rates. Additionally, it is demonstrated that existing models for particle migration fail to adequately describe the solid volume fractions measured in these systems, highlighting the need for improvement. The low field implementation of Rheo-NMR is complementary to shear stress rheology, such that the two techniques could be combined in a single instrument. [ABSTRACT FROM AUTHOR]

Many industrial flow processes are sensitive to changes in the rheological behaviour of process fluids, and there therefore exists a need for methods that provide online, or inline, rheological characterisation necessary for process control and optimisation over timescales of minutes or less. Nuclear magnetic resonance (NMR) offers a non-invasive technique for this application, without limitation on optical opacity. We present a Bayesian analysis approach using pulsed field gradient (PFG) NMR to enable estimation of the rheological parameters of Herschel-Bulkley fluids in a pipe flow geometry, characterised by a flow behaviour index n , yield stress τ 0 , and consistency factor k , by analysis of the signal in q -space. This approach eliminates the need for velocity image acquisition and expensive gradient hardware. We investigate the robustness of the proposed Bayesian NMR approach to noisy data and reduced sampling using simulated NMR data and show that even with a signal-to-noise ratio (SNR) of 100, only 16 points are required to be sampled to provide rheological parameters accurate to within 2% of the ground truth. Experimental validation is provided through an experimental case study on Carbopol 940 solutions (model Herschel-Bulkley fluids) using PFG NMR at a 1 H resonance frequency of 85.2 MHz; for SNR > 1000, only 8 points are required to be sampled. This corresponds to a total acquisition time of <60 s and represents an 88% reduction in acquisition time when compared to MR flow imaging. Comparison of the shear stress-shear rate relationship, quantified using Bayesian NMR, with non-Bayesian NMR methods demonstrates that the Bayesian NMR approach is in agreement with MR flow imaging to within the accuracy of the measurement. Furthermore, as we increase the concentration of Carbopol 940 we observe a change in rheological characteristics, probably due to shear history-dependent behaviour and the different geometries used. This behaviour highlights the need for online, or inline, rheological characterisation in industrial process applications. [ABSTRACT FROM AUTHOR]

[Display omitted] • A portable magnetic resonance instrument is used to measure the flow behaviour indices of non-Newtonian fluids. • Velocity induced phase interference leads to a rheological dependence of signal magnitude. • Measured values of the flow behavior indices are in close agreement with literature values. • Various procedures for calibration and data analysis outlined and compared. In this work, we expand on past portable magnetic resonance flow methods and propose a novel method for characterizing circular (laminar) Couette flow of non-Newtonian fluids. Symmetry of the flow system combined with a constant magnetic field gradient leads to phase interference, affecting the signal magnitude, and net phase cancellation when averaging across the excited slice, preventing the use of phase-sensitive methods. Therefore, we utilize the dependence of signal magnitude at variable echo times and shear rates to characterize rheological properties. Theoretical equations governing the velocity distributions of fluids that obey a simple power-law model are used to obtain integral expressions for signal magnitude. Integral expressions can be simplified by approximating a thin excited slice or complete excitation of the Couette cell depending on experimental parameters. With simple data acquisition and analysis procedures employed, our measurements of the flow behavior indices of non-Newtonian xanthan gum dispersions are in close agreement with conventional rheological magnetic resonance measurements. [ABSTRACT FROM AUTHOR]

Conventional rheological characterisation using nuclear magnetic resonance (NMR) typically utilises spatially-resolved measurements of velocity. We propose a new approach to rheometry using pulsed field gradient (PFG) NMR which readily extends the application of MR rheometry to single-axis gradient hardware. The quantitative use of flow propagators in this application is challenging because of the introduction of artefacts during Fourier transform, which arise when realistic sampling strategies are limited by experimental and hardware constraints and when particular spatial and temporal resolution are required. The method outlined in this paper involves the cumulant analysis of the acquisition data directly, thereby preventing the introduction of artefacts and reducing data acquisition times. A model-dependent approach is developed to enable the pipe-flow characterisation of fluids demonstrating non-Newtonian power-law rheology, involving the use of an analytical expression describing the flow propagator in terms of the flow behaviour index. The sensitivity of this approach was investigated and found to be robust to the signal-to-noise ratio (SNR) and number of acquired data points, enabling an increase in temporal resolution defined by the SNR. Validation of the simulated results was provided by an experimental case study on shear-thinning aqueous xanthan gum solutions, whose rheology could be accurately characterised using a power-law model across the experimental shear rate range of 1–100 s −1 . The flow behaviour indices calculated using this approach were observed to be within 8% of those obtained using spatially-resolved velocity imaging and within 5% of conventional rheometry. Furthermore, it was shown that the number of points sampled could be reduced by a factor of 32, when compared to the acquisition of a volume-averaged flow propagator with 128 gradient increments, without negatively influencing the accuracy of the characterisation, reducing the acquisition time to only 3% of its original value. [ABSTRACT FROM AUTHOR]

Abstract: In a Newtonian fluid, vorticity diffuses at a rate determined by the kinematic viscosity. Here we use rapid NMR velocimetry, based on a RARE sequence, to image the time-dependent velocity field on startup of a fluid-filled cylinder and therefore measure the diffusion of vorticity. The results are consistent with the solution to the vorticity diffusion equation where the angular velocity on the outside surface of the fluid, at the cylinder’s rotating wall, is fixed. This method is a means of measuring kinematic viscosity for low viscosity fluids without the need to measure stress. [Copyright &y& Elsevier]