In this study, the influence of a bed on turbidity current propagation and flocculation dynamics has been investigated using a lock-exchange setup. Experiments were performed in saltwater using sediments sampled from a deep-sea mining location in the Clarion Clipperton Zone (CCZ). Results showed that the presence of a bed influenced the propagation velocity of turbidity currents. Flocs were denser and larger than those observed when no bed was present. The floc settling velocities also increased in the presence of a bed. Additionally, in the case of a (freshly) formed bed, sediment resuspension occurred due to the disturbance of organic matter, which contributed to flocculation. This study also sheds light on the role of the age of the bed on turbidity current propagation, with (freshly) formed beds being efficient in reducing sediment spread. These findings are important for predicting the spread of a turbidity current during deep-sea mining activities.

We address the computational challenges of large-scale geospatial mapping with Gaussian process (GP) regression by performing localized computations rather than processing the entire map simultaneously. Traditional approaches to GP regression often involve computational and storage costs that either scale with the number of measurements, or with the spatial extent of the mapped area, limiting their scalability for real-time applications. Our method places a global grid of finite-support basis functions and restricts computations to a local subset of the grid 1) surrounding the measurement when the map is updated, and 2) surrounding the query point when the map is queried. This localized approach ensures that only the relevant area is updated or queried at each timestep, significantly reducing computational complexity while maintaining accuracy. Unlike many existing methods, which suffer from boundary effects or increased computational costs with mapped area, our localized approach avoids discontinuities and ensures that computational costs remain manageable regardless of map size. This approximation to GP mapping provides high accuracy with limited computational budget for the specialized task of performing fast online map updates and fast online queries of large-scale geospatial maps. It is therefore a suitable approximation for use in real-time applications where such properties are desirable, such as real-time simultaneous localization and mapping (SLAM) in large, nonlinear geospatial fields. We show on experimental data with magnetic field measurements that our algorithm is faster and equally accurate compared to existing methods, both for recursive magnetic field mapping and for magnetic field SLAM.

This study investigates the influence of multiple jet parameters on the flow field of translating impinging inclined water jets. We conducted full-scale stereoscopic particle image velocimetry and pressure measurements and three-dimensional computational fluid dynamics simulations for Reynolds numbers in the range of. Considering the complex mechanism of a translating impinging jet, a good concordance is observed between the experimental and numerical results. The translation-to-jet velocity ratio is identified as a critical parameter in determining whether the jet flow predominantly exhibits impinging characteristics or behaves as a jet in cross-flow. It is found that, for, jet impingement is minimal. The stand-off distance to nozzle diameter ratio determines the relative influence of the cross-flow on the jet flow. The effect of is similar to a stationary impinging jet, with the potential core extending up to, but entrainment is enhanced by the relative cross-flow. For an inclined jet, i.e. jet angle, the direction of the jet, either backward or forward, governs the deflection of the flow. Higher pressures are recorded for a backward directed jet compared with a forward directed jet for supplementary angles.

Self-amplifying density waves in hydraulic transport pipelines is a scarcely researched topic. Density waves are in essence the result of a spatial redistributing effect and clustering of solids in hydraulic transport pipelines. Self-amplifying density waves are very undesirable for practical applications, as these waves increasing the risk of pipeline blockages. The two available experimental studies (Talmon et al., 2007; Matoušek and Krupička, 2013) report conflicting properties of the density waves, such as wave length and wave celerity. This new experimental research aims to shed light on the reported differences, by broadly varying particle size and concentration in a new dedicated experiment. The main highlight of this research is that two separate mechanisms were identified that can cause density waves, and Talmon et al. (2007) and Matoušek and Krupička (2013) in hindsight were studying the two different mechanism respectively. Both wave type mechanisms come into effect at mixture velocities close to the deposit limit velocity, and require a stationary bed layer to initiate. The first mechanism is caused by an imbalance of erosion and sedimentation of the bed layer, which is predominant for fine sand particles (∼242μm and ∼308μm in this research). The second mechanism occurs when the bed layer starts sliding, instead of being eroded, and is specific for larger sand sizes (∼617μm and ∼1.08mm in this research). These two mechanisms are clearly distinguishable, having different wave lengths, celerity, amplitudes and amplification rates. The results also show a clear relationship between the mean concentration of a density wave, the wave amplitude and wave celerity specific for each of the two mechanisms.

A convex pattern surface is proposed and optimized to mitigate the sliding wear of bulk handling equipment caused by interaction with bulk solids. This work investigates the effectiveness of the convex pattern surface on wear reduction during interactions with non-spherical particles. Multiple representative particles, obtained through a sampling method, are reconstructed using a photogrammetry technique. Two contact parameters between particles are calibrated through shear box and drawdown tests to ensure flow behavior similar to the real material. The numerical results indicate that the convex pattern surface can effectively reduce wear compared to a plain sample when involving both spherical and non-spherical particles. For a plain sample, the wear volume remains independent of particle shapes and increases linearly with numerical revolutions. For the convex pattern surface, the wear volume demonstrates a quadratic relationship with the test revolutions as the deformation of convex elements weakens the effectiveness of the sample on wear reduction. The particle flow behavior analysis reveals that the convex pattern surface experiences the lowest wear volume when in contact with non-spherical particles. This can be attributed to the non-spherical particles sliding shorter distances and rotating with higher angular velocities on the convex pattern surface.

A convex pattern surface has been proposed and optimized to reduce sliding wear of bulk handling equipment by adjusting the flow behaviour of bulk material. This study aims at modelling the surface deformation of the convex pattern sample to investigate how effectively the sample reduces sliding wear. Archard wear model and a deformable geometry technique are combined to capture the sample deformation. A short-time laboratory wear experiment is performed as a benchmark to validate the numerical model. The simulation resutls indicate that there is a linear relation between the wear volume of a plain sample and the simulated revolutions, while the convex pattern sample has a quadratic trend. The wear distribution displays that the convex pattern accounts for the majority of wear of the sample. The contact behaviour demonstrates that the convex pattern facilitates the rolling of particles, resulting in the reduction of sliding distance. The numerical results indicate that the deformed convex pattern sample leads to lower overall sliding wear than a plain sample, although its effectiveness weakens as wear evolves.

In this paper, model-based systems engineering (MBSE) and discrete event simulation (DES) are combined to assess the performance of an offshore production system at an early stage. Various systems engineering tools are applied to an industrial case concerning the retrieval of deep-sea minerals, and a simulation engine is developed to calculate the annual production output. A mean production of 1 Million tonnes of ore per year is estimated for an operation in the Norwegian Sea using Monte Carlo simulation. Depending on the limiting design wave height of the marine operations, the estimated production output ranges from 280,000 tonnes to 1.8 Million tonnes per year. The constrained parameter of the production system is particularly the wave height operational limit of the ship-to-ship transfer operation. We present the learning outcome from applying MBSE and DES to this case and discuss important aspects for improved performance.

We have developed and investigated a hydrodynamic model of Deep-Sea Mining (DSM) collector turbidity flows that captures sediment particle aggregation and breakup. Flocculation is expected to have a significant impact on determining the spread patterns of the turbidity flows and the resulting turbidity currents. The recently validated drift-flux model by Elerian et al. (2022) has been coupled to the Population Balance Equation (PBE) for modelling real-life discharge scenarios. This advanced approach accounts for the dynamics of flocculation and offers a comprehensive simulation of discharge systems. We hypothesize that this will produce a more accurate representation of DSM turbidity flows in the near-field region, where the turbulence mixing is expected to be the highest. Particular emphasis is placed on the settling velocity closure, as the flocs that form are porous and have a complex geometry. The flocculation parameters are calibrated using the experiments of Gillard et al. (2019). Finally, we investigate the effect of flocculation in the near-field region by numerically solving the new model in a computational domain of the near-field region. The results indicate that aggregation is the primary mechanism, however, it does not have a visible impact on the turbidity flow in the immediate vicinity, but it is likely to have a substantial effect on the far-field region.

Accurately estimating the positions of multi-agent systems in indoor environments is challenging due to the lack of Global Navigation Satelite System (GNSS) signals. Noisy measurements of position and orientation can cause the integrated position estimate to drift without bound. Previous research has proposed using magnetic field simultaneous localization and mapping (SLAM) to compensate for position drift in a single agent. Here, we propose two novel algorithms that allow multiple agents to apply magnetic field SLAM using their own and other agents' measurements.Our first algorithm is a centralized approach that uses all measurements collected by all agents in a single extended Kalman filter. This algorithm simultaneously estimates the agents' position and orientation and the magnetic field norm in a central unit that can communicate with all agents at all times. In cases where a central unit is not available, and there are communication drop-outs between agents, our second algorithm is a distributed approach that can be employed.We tested both algorithms by estimating the position of magnetometers carried by three people in an optical motion capture lab with simulated odometry and simulated communication dropouts between agents. We show that both algorithms are able to compensate for drift in a case where single-agent SLAM is not. We also discuss the conditions for the estimate from our distributed algorithm to converge to the estimate from the centralized algorithm, both theoretically and experimentally. Our experiments show that, for a communication drop-out rate of 80%, our proposed distributed algorithm, on average, provides a more accurate position estimate than single-agent SLAM. Finally, we demonstrate the drift-compensating abilities of our centralized algorithm on a real-life pedestrian localization problem with multiple agents moving inside a building.