The Pressure Peaking Phenomenon for Ignited Under-Expanded Hydrogen Jets in the Storage Enclosure: Experiments and Simulations for Release Rates of up to 11.5 g/s

This work focuses on the experimental and numerical investigation of maximum overpressure and pressure dynamics during ignited hydrogen releases in a storage enclosure, e.g., in marine vessel or rail carriage, with limited vent size area, i.e., the pressure peaking phenomenon (PPP) revealed theoretically at Ulster University in 2010. The CFD model previously validated against small scale experiments in a 1 m3 enclosure is employed here to simulate real-scale tests performed by the University of South-Eastern Norway (USN) in a chamber with a volume of 15 m3. The numerical study compares two approaches on how to model the ignited hydrogen release conditions for under-expanded jets: (1) notional nozzle concept model with inflow boundary condition, and (2) volumetric source model in the governing conservation equations. For the test with storage pressure of 11.78 MPa, both approaches reproduce the experimental pressure dynamics and the pressure peak with a maximum 3% deviation. However, the volumetric source approach reduces significantly the computational time by approximately 3 times (CFL = 0.75). The sensitivity analysis is performed to study the effect of CFL number, the size of the volumetric source and number of iterations per time step. An approach based on the use of a larger size volumetric source and uniform coarser grid with a mesh size of a vent of square size is demonstrated to reduce the duration of simulations by a factor of 7.5 compared to the approach with inflow boundary at the notional nozzle exit. The volumetric source model demonstrates good engineering accuracy in predicting experimental pressure peaks with deviation from −14% to +11% for various release and ventilation scenarios as well as different volumetric source sizes. After validation against experiments, the CFD model is employed to investigate the effect of cryogenic temperature in the storage on the overpressure dynamics in the enclosure. For a storage pressure equal to 11.78 MPa, it is found that a decrease of storage temperature from 277 K to 100 K causes a twice larger pressure peak in the enclosure due to the pressure peaking phenomenon.

Data-Driven Spatiotemporal Modeling of Reservoir Pressure Dynamics in a Giant Saturated Oil Field in Libya

This paper aims to explore modern techniques based on artificial intelligence (AI) and data science, in order to produce data-driven workflows to analyze, model, and simulate reservoir pressure dynamics. In this paper, it was investigated a data-driven workflow to model reservoir pressure at any point in space and time from sparse pressure data observed at wells, without building a physics-based numerical model. This workflow was termed as spatiotemporal modelling of reservoir pressure. Spatiotemporal modelling of reservoir pressure was based on a three-step workflow including multivariate analysis of pressure data and relevant explanatory variables (features), pressure modelling and spatiotemporal interpolation. The overall workflow provided a comprehensive method to understand and map the reservoir pressure dynamics using data science tools. Several modelling techniques such as generalized additive models, artificial neural networks and spatiotemporal kriging were investigated for their applicability and accuracy. The workflow was applied to a real oil and gas reservoir case, for which the reservoir pressure prediction accuracy was optimized through a few experiments. The optimum experiment produced highly accurate prediction with a mean absolute error of 26.85 psi measured on the training dataset. Moreover, a portion of data used was kept to evaluate blind test accuracy, which amounted to a mean absolute error of 55 psi, for the optimum case. The proposed data-driven workflow was aimed to improve current methods of reservoir engineering and simulation. The suggested workflow showed high accuracy in reservoir pressure predictions with high efficiency in terms of computational resources and time. Additionally, the proposed workflow was developed using open-source libraries which pose no additional cost to computation, in contrast to extremely expensive industry standard physics-based reservoir simulation software. Finally, this workflow could also be used to model other reservoir variables such as production ratios (Water cut, and Gas-Oil Ratio), contacts (Water-Oil contact and Gas-Oil contact), among others.

An analytic nonlinear model of thermo-poro-elastic pressure transients in porous rocks 2 with application to deep CO2 storage.

• Today a CO2 storage/segregation is an important option for a significant enhancing of CO2 sinks, to reduce the net carbon emissions into our planet atmosphere. Such storage/sequestration is a complex process, dealing with many facets of decision about the site selection, taking into consideration the local geological, geothermal, hydrodynamic and hydrocarbon potentials. In such multifaceted context, a thermo-poro-elastic nonlinear analytic model of fluid pressure P in deep rocks, can play an important role. To tackle this dynamics we here examine a nonlinear model of fluid pressure transient also considering convection, thermal dynamics and fluid/rock "frictions”. In addition, we here show that pressure dynamics, induced by an eventual external time or areal forcing can allow simple analytical determinations of pressure transients in these deep porous media. Such processes indeed can have practical impacts on the CO2 evolution for storage in deep rocks and thus influence the final site choice for a deep CO2 injection. In synthesis, this model provides simple characterizations of thermo-poro-elastic transients for CO2 storage. 24 25 26

On trajectory tracking control of fluid-driven actuators

Fluid-driven actuators are not only well-established in automation, but also a promising drive technology for collaborative robots. Their inherent compliance due to the compressibility of suitable fluids such as air, as well as their direct drive properties are advantageous safety features for human-machine collaboration. In this work, we provide an overview of different fluid-driven manipulators, namely fluidic muscle actuated ones, continuum manipulators, and those with rotary joints. For the latter, we introduce the mathematical model including mechanics and pressure dynamics and describe its properties such as strong nonlinearities, which make trajectory tracking control challenging. A model-based nonlinear cascaded controller is presented. Experimental results on a 6 degrees of freedom (DOF) prototype demonstrate the resulting trajectory tracking performance.

Nonlinear energy-based control of soft continuum pneumatic manipulators

This paper investigates the model-based nonlinear control of a class of soft continuum pneumatic manipulators that bend due to pressurization of their internal chambers and that operate in the presence of disturbances. A port-Hamiltonian formulation is employed to describe the closed loop system dynamics, which includes the pressure dynamics of the pneumatic actuation, and new nonlinear control laws are constructed with an energy-based approach. In particular, a multi-step design procedure is outlined for soft continuum manipulators operating on a plane and in 3D space. The resulting nonlinear control laws are combined with adaptive observers to compensate the effect of unknown disturbances and model uncertainties. Stability conditions are investigated with a Lyapunov approach, and the effect of the tuning parameters is discussed. For comparison purposes, a different control law constructed with a backstepping procedure is also presented. The effectiveness of the control strategy is demonstrated with simulations and with experiments on a prototype. To this end, a needle valve operated by a servo motor is employed instead of more sophisticated digital pressure regulators. The proposed controllers effectively regulate the tip rotation of the prototype, while preventing vibrations and compensating the effects of disturbances, and demonstrate improved performance compared to the backstepping alternative and to a PID algorithm.

Local mechanical stimuli shape tissue growth in vertebrate joint morphogenesis

The correct formation of synovial joints is essential for proper motion throughout life. Movement-induced forces are critical to creating correctly shaped joints, but it is unclear how cells sense and respond to these mechanical cues. To determine how mechanical stimuli drive joint morphogenesis, we combined experiments on regenerating axolotl forelimbs with a poroelastic model of bone rudiment growth. Animals either regrew forelimbs normally (control) or were injected with a TRPV4 agonist to impair chondrocyte mechanosensitivity during joint morphogenesis. We quantified growth and shape in regrown humeri from whole mount light sheet fluorescence images of the regenerated limbs. Results revealed statistically significant differences in morphology and cell proliferation between the two groups, indicating that mechanical stimuli play a role in the shaping of the joint. Local tissue growth in our finite element model was dictated by a biological contribution, proportional to chondrocyte density, and a mechanical one, driven by fluid pore pressure dynamics. Computational predictions agreed with experimental outcomes, suggesting that interstitial pressure might promote local tissue growth. Predictive computational models informed by experimental findings allow us to explore potential physical mechanisms and regulatory dynamics involved in tissue growth to advance our understanding of the mechanobiology of joint morphogenesis.

Boundary Layer Multi-Property Flow Measurements Using a Micro-Plasma Sensor

When voltage is applied between two electrodes situated in close proximity to each other (10–100 μm), a weakly ionized, low temperature plasma discharge can be generated. This in turn creates a plasma sheath, an electrically ionized boundary layer (typically of the order of 10’s to 100’s of microns), where space charge effects dominate. The sheath acts like a virtual capacitor, with the plasma behaving as an inductor. Aerodynamic effects influence the plasma morphology (shape, thickness), thus making the plasma the transduction mechanism. The attraction to the use of plasma discharge as a transduction method for fluid flow property measurement stem from the fact that it lends itself to a probe implementation that is simple in design, can be miniaturized, and at the same time offers unmatched capability for handling ultra-high temperature environments. Sensing plasma discharge characteristics and their variation due to flow interaction can be done electrically, but also optically to yield time-varying intensity and spectral information from fluid-plasma interaction. The current paper focuses on the deployment of a micro-plasma sensor system as a new novel multi-parameter sensing approach for surface flow measurement. Results on pressure dynamics, shear flow, and other possible engineering parameters will be discussed in the context of results from several bench-level experiments.

Gas Pressure Dynamics in Small and Mid-Size Lakes

Dissolved gases produce a gas pressure. This gas pressure is the appropriate physical quantity for judging the possibility of bubble formation and hence it is central for understanding exchange of climate-relevant gases between (limnic) water and the atmosphere. The contribution of ebullition has widely been neglected in numerical simulations. We present measurements from six lacustrine waterbodies in Central Germany: including a natural lake, a drinking water reservoir, a mine pit lake, a sand excavation lake, a flooded quarry, and a small flooded lignite opencast, which has been heavily polluted. Seasonal changes of oxygen and temperature are complemented by numerical simulations of nitrogen and calculations of vapor pressure to quantify the contributions and their dynamics in lacustrine waters. In addition, accumulation of gases in monimolimnetic waters is demonstrated. We sum the partial pressures of the gases to yield a quantitative value for total gas pressure to reason which processes can force ebullition at which locations. In conclusion, only a small number of gases contribute decisively to gas pressure and hence can be crucial for bubble formation.

Characterisation and Validation of an Optical Pressure Sensor for Combustion Monitoring at Low Frequency

This paper introduces a novel approach to monitor pressure dynamics in turbomachinery. This innovation is motivated by the need expressed by machine OEMs and end-users to detect and avoid combustion instabilities, as well as lean-blowout (LBO), in low emission combustion systems. Such situations are often characterised by a marked increase of pressure signals in low frequency range. The piezoelectric technology, conventionally used for pressure measurements, presents sensitivity and stability issues at high temperatures and low frequencies. Here a new paradigm for pressure sensing, based on optical interferometry, is characterised and validated. The interferometric sensing system is designed to provide a larger range of measurement frequencies with better performance, in the low frequency range (< 50Hz), while exposed to high temperatures. This unique feature allows the real-time observation of events, such as the specific behaviour of a low frequency flame dynamic, which is characteristic of an imminent LBO. This improved monitoring system will support an optimisation of the machine performance, leading to a safer, cleaner, more flexible and more cost-efficient operation for the end-user. The novel measurement system has been characterised under non-reactive and reactive conditions within the frame of a joint study between Meggitt SA, Combustion Bay One e.U. and FH Joanneum GmbH. The technology is first described, including the relevant hardware and software components of the measurement chain. The different experimental set-ups and conditions are also illustrated. The results of the test campaign and their subsequent analysis are then presented, supporting the expected advantages over piezoelectric technology. In conclusion, a possible strategy for the detection of LBO precursors based on low frequency data is proposed.