Fine Grid Resolution Research Articles

Enhancing subsurface multiphase flow simulation with Fourier neural operator

Accurate numerical modeling of multiphase flow in subsurface oil and gas reservoirs is critical for optimizing hydrocarbon recovery. However, traditional physics-based algorithms face substantial computational hurdles due to the need for fine grid resolution and the inherent geological heterogeneity. To overcome these challenges, data-driven surrogate models solving the flow governing partial differential equations (PDEs) offer a promising alternative to enhance the efficiency of hydrocarbon production operations. In this study, we employ the Fourier Neural Operator (FNO) to extract spectral information from the reservoir properties, thereby facilitating the solution of coupled porous flow PDEs. Our focus is on two-phase flow dynamics, specifically exploring how water injection enhances reservoir pressure and displaces oil. This scenario involves solving a set of nonlinearly coupled PDEs with highly heterogeneous coefficients. Numerical results demonstrate that the developed FNO accurately predicts the reservoir pressure distributions. We further observe that the FNO's zero-shot super-resolution capability is sensitive to abrupt local changes in the reservoir pressure near injection and production wells. To enhance its accuracy, we propose a multi-fidelity FNO model that exhibits better adaptability across various grid configurations. After moderate training on graphics processing units (GPUs), the FNO achieves a speedup of three orders of magnitude compared to traditional numerical PDE solvers. Our experiments confirm the FNO's potential to replace repetitive physics-based simulations, significantly advancing computational efficiency in the uncertainty quantification of reservoir performance.

Influence of Grid Resolution and Assimilation Window Size on Simulating Storm Surge Levels

Grid resolution and assimilation window size play significant roles in storm surge models. In the Bohai Sea, Yellow Sea, and East China Sea, the influence of grid resolution and assimilation window size on simulating storm surge levels was investigated during Typhoon 7203. In order to employ a more realistic wind stress drag coefficient that varies with time and space, we corrected the storm surge model using the spatial distribution of the wind stress drag coefficient, which was inverted using the data assimilation method based on the linear expression Cd = (a + b × U10) × 10−3. Initially, two grid resolutions of 5′ × 5′ and 10′ × 10′ were applied to the numerical storm surge model and adjoint assimilation model. It was found that the influence of different grid resolutions on the numerical model is almost negligible. But in the adjoint assimilation model, the root mean square (RMS) errors between the simulated and observed storm surge levels under 5′ × 5′ and 10′ × 10′ grid resolutions were 11.6 cm and 15.6 cm, and the average PCC and WSS values for 10 tidal stations changed from 89% and 92% in E3 to 93% and 96% in E4, respectively. The results indicate that the finer grid resolution can yield a closer consistency between the simulation and observations. Subsequently, the effects of assimilation window sizes of 6 h, 3 h, 2 h, and 1 h on simulated storm surge levels were evaluated in an adjoint assimilation model with a 5′ × 5′ grid resolution. The results show that the average RMS errors were 11.6 cm, 10.6 cm, 9.6 cm, and 9.3 cm under four assimilation window sizes. In particular, the RMS errors for the assimilation window sizes of 1 h and 6 h at RuShan station were 3.9 cm and 10.2 cm, a reduction of 61.76%. The PCC and WSS values from RuShan station in E4 and E7 separately showed significant increases, from 85% to 98% and from 92% to 99%. These results demonstrate that when the assimilation window size is smaller, the simulated storm surge level is closer to the observation. Further, the results show that the simulated storm surge levels are closer to the observation when using the wind stress drag coefficient with a finer grid resolution and smaller temporal resolution.

Simulation of group of droplets evaporation

Droplet evaporation occurs in many natural phenomena and industrial processes; hence, several studies have been conducted on droplet evaporation. In many applications, a group of droplets evaporate and the interaction between them affects the evaporation process. In this paper, the front-tracking method is used to simulate the droplets groups evaporation. Since the front-tracking method uses a Lagrangian grid for each droplet, this method offers good accuracy in predicting the shape, the displacement and the evaporation rate of droplets. The numerical method has been developed to simulate the evaporation of binary droplets. The fluid surrounding the droplets is modeled as a gas mixture, so the numerical method can be used to simulate multiphase-multicomponent problems. The front-tracking method requires very fine grid resolution to simulate flows at high-density ratios; therefore, the method is rarely used at high-density ratios. In this paper, a two-step method is used to move the front at high-density ratios without requiring a very fine grid resolution. First, a static droplet evaporation is simulated, and the results are compared with the analytical solutions; evaporation of a Decane droplet is then simulated, and the results are compared with the experimental data. Subsequently, the evaporation of a binary droplet is modeled. The evaporation of a group of static droplets is also simulated, and the effect of droplets interaction is investigated. Next, the evaporation of three injected droplets is simulated, and the effect of some parameters on droplets interaction is probed. The evaporation rate and displacement of each droplet are calculated and compared with the single droplet. Finally, the evaporation of the groups of droplets is simulated, and the effect of different arrangements of droplets on the evaporation rate is studied. Understanding the droplets interactions is helpful in predicting droplet spray behavior and developing numerical methods. Thus, the presented results are useful to achieve a better understanding of the droplets interaction phenomenon, its outcomes, and the parameters affecting evaporation rate.

Modeling Lobe‐And‐Cleft Instabilities on a River Plume

AbstractThe lobe‐and‐cleft instability is a widely recognized mechanism leading to along‐front structure on density current fronts. Early studies based on laboratory and numerical simulations suggested that the lobe‐and‐cleft instability is due to convective instability in the nose of gravity currents traveling over a nonslip boundary. Horner‐Devine and Chickadel (2017, https://doi.org/10.1002/2017gl072997) reported the presence of lobe‐and‐cleft instabilities at the Merrimack River, which are generated at the river front in the absence of a no‐slip boundary. Hence, the observed lobe‐and‐cleft instabilities must be due to other mechanisms. In this study, we carried out non‐hydrostatic large eddy simulations of a riverine outflow into an idealized 3D domain. With a fine grid resolution of 0.15 × 0.31 m in two horizontal directions and about 0.125 m in the vertical direction, the model reproduced the lobe‐and‐cleft feature, with the magnitude and size of lobes consistent with the field observation. The model results revealed that instabilities start from the primary Kelvin‐Helmholtz instability, followed by the secondary instability through stretching and tilting, generating counter‐rotating streamwise vortices in the plume and at the plume head. The upwelling associated with streamwise vortex cells brings a slower flow to the plume surface, resulting in lobe‐and‐cleft patterns at the front and positive and negative vertical vorticity at the plume surface. The model also predicted a lobe width of about two to three times the plume thickness, consistent with the field observation and the lobe/cleft spacing associated with pairs of counter‐rotating streamwise vortices. Modeled turbulent dissipation rate shows a trend of exponential decay from 10−4 to 10−3 m2/s3 at the frontal head to 10−7 to 10−6 m2/s3 behind the front, similar to the findings in the previous field studies.

Snowfall deposition in mountainous terrain: a statistical downscaling scheme from high-resolution model data on simulated topographies

One of the primary causes of non-uniform snowfall deposition on the ground in mountainous regions is the preferential deposition of snow, which results from the interaction of near-surface winds with topography and snow particles. However, producing high-resolution snowfall deposition patterns can be computationally expensive due to the need to run full atmospheric models. To address this, we developed two statistical downscaling schemes that can efficiently downscale near-surface, low-resolution snowfall data to fine-scale snow deposition accounting for the effect of preferential deposition in mountainous regions. Our approach relies on a comprehensive, model database generated using 3D wind fields from an atmospheric model and a preferential deposition model on several thousand simulated topographies covering a broad range in terrain characteristics. Both snowfall downscaling schemes rely on fine-scale topographic scaling parameters and low-resolution wind speed as input. While one scheme, referred to as the “wind scheme”, further necessitates fine-scale vertical wind components, a second scheme, referred to as the “aspect scheme”, does not require fine-scale temporal input. We achieve this by additionally downscaling near-surface vertical wind speed solely using topographic scaling parameters and low-resolution wind direction. We assess the performance of our downscaling schemes using an independent subset of the model database on simulated topographies, model data on actual terrain, and spatially measured new snow depth obtained through a photogrammetric drone survey following a snowfall event on previously snow-free ground. While the assessments show that our downscaling schemes perform well (relative errors ≤ ±3% with modeled and ≤ ±6% with measured snowfall deposition), they also demonstrate comparable results to benchmark downscaling models. However, our schemes notably outperform the benchmark models in representing fine-scale patterns. Our downscaling schemes possess several key features, including high computational efficiency, versatility enabled by the comprehensive model database, and independence from fine-scale temporal input data (aspect scheme), indicating their potential for widespread applicability. Therefore, our downscaling schemes for near-surface snowfall and vertical wind speed can be beneficial for various applications at fine grid resolutions such as in atmospheric and climate sciences, snow hydrology, glaciology, remote sensing, and avalanche sciences.

CIOFC1.0: a common parallel input/output framework based on C-Coupler2.0

Abstract. As earth system modeling develops ever finer grid resolutions, the inputting and outputting (I/O) of the increasingly large data fields becomes a processing bottleneck. Many models developed in China, as well as the community coupler (C-Coupler), do not fully benefit from existing parallel I/O supports. This paper reports the design and implementation of a common parallel input/output framework (CIOFC1.0) based on C-Coupler2.0. The CIOFC1.0 framework can accelerate the I/O of large data fields by parallelizing data read/write operations among processes. The framework also allows convenient specification by users of the I/O settings, e.g., the data fields for I/O, the time series of the data files for I/O, and the data grids in the files. The framework can also adaptively input data fields from a time series dataset during model integration, automatically interpolate data when necessary, and output fields either periodically or irregularly. CIOFC1.0 demonstrates the cooperative development of an I/O framework and coupler, and thus enables convenient and simultaneous use of a coupler and an I/O framework.

Forced-motion simulations of vortex-induced vibrations of wind turbine blades – a study of sensitivities

Abstract. Vortex-induced vibrations on wind turbine blades are a complex phenomenon not predictable by standard engineering models. For this reason, higher-fidelity computational fluid dynamics (CFD) methods are needed. However, the term CFD covers a broad range of fidelities, and this study investigates which choices have to be made when wanting to capture the vortex-induced vibration (VIV) phenomenon to a satisfying degree. The method studied is the so-called forced-motion (FM) approach, where the structural motion is imposed on the CFD blade surface through mode shape assumptions rather than fully coupled two-way fluid–structure interaction. In the study, two independent CFD solvers, EllipSys3D and Ansys CFX, are used and five different turbulence models of varying fidelities are tested. Varying flow scenarios are studied with low to high inclination angles, which determine the component of the flow in the spanwise direction. In all scenarios, the cross-sectional component of the flow is close to perpendicular to the chord of the blade. It is found that the low-inclination-angle and high-inclination-angle scenarios, despite having a difference equivalent to up to only a 30∘ azimuth, have quite different requirements of both grid resolution and turbulence models. For high inclination angles, where the flow has a large spanwise component from the tip towards the root, satisfying results are found from quite affordable grid sizes, and even with unsteady Reynolds-averaged Navier–Stokes (URANS) k–ω turbulence, the result is quite consistent with models resolving more of the turbulent scales. For low inclination, which has a high degree of natural vortex shedding, the picture is the opposite. Here, even for scale-resolving turbulence models, a much finer grid resolution is needed. This allows us to capture the many incoherent vortices, which have a large impact on the coherent vortices, which in turn inject power into the blade or extract power. It is found that a good consistency is seen using different variations of the higher-fidelity hybrid RANS–large eddy simulation (LES) turbulence models, like improved delayed detached eddy simulation (IDDES), stress-blended eddy simulation (SBES) and k–ω scale-adaptive simulation (SAS) models, which agree well for various flow conditions and imposed amplitudes. This study shows that extensive care and consideration are needed when modeling 3D VIVs using CFD, as the flow phenomena, and thereby solver requirements, rapidly change for different scenarios.

Modeling sensitivities of thermally and hydraulically driven ice stream surge cycling

Abstract. Modeling ice sheet instabilities is a numerical challenge of potentially high real-world relevance. Yet, differentiating between the impacts of model physics, numerical implementation choices, and numerical errors is not straightforward. Here, we use an idealized North American geometry and climate representation (similarly to the HEINO (Heinrich Event INtercOmparison) experiments – Calov et al., 2010) to examine the process and numerical sensitivity of ice stream surge cycling in ice flow models. Through sensitivity tests, we identify some numerical requirements for a more robust model configuration for such contexts. To partly address model-specific dependencies, we use both the Glacial Systems Model (GSM) and the Parallel Ice Sheet Model (PISM). We show that modeled surge characteristics are resolution dependent, though they converge (decreased differences between resolutions) at finer horizontal grid resolutions. Discrepancies between fine and coarse horizontal grid resolutions can be reduced by incorporating sliding at sub-freezing temperatures. The inclusion of basal hydrology increases the ice volume lost during surges, whereas the dampening of basal-temperature changes due to a bed thermal model leads to a decrease.

Numerical Study of Unstable Shock-Induced Combustion with Different Chemical Kinetics and Investigation of the Instability Using Modal Decomposition Technique

An unstable shock-induced combustion (SIC) case around a hemispherical projectile has been numerically studied which experimentally produced a regular oscillation. Comparison of detailed H2/O2 reaction mechanisms is made for the numerical simulation of SIC with higher-order numerical schemes intended for the use of the code for the hypersonic propulsion and supersonic combustion applications. The simulations show that specific reaction mechanisms are grid-sensitive and produce spurious reactions in the high-temperature region, which trigger artificial instability in the oscillating flow field. The simulations also show that specific reaction mechanisms develop such spurious oscillations only at very fine grid resolutions. The instability mechanism is investigated using the dynamic mode decomposition (DMD) technique and the spatial structure of the decomposed modes are further analyzed. It is found that the instability triggered by the high-temperature reactions strengthens the reflecting compression wave and pushes the shock wave further and disrupts the regularly oscillating mechanism. The spatial coherent structure from the DMD analysis shows the effect of this instability in different regions in the regularly oscillating flow field.

An investigation on the wake flow of a generic ship using IDDES: The effect of computational parameters

The study of the ship airwake is critical as it explores the effect of unsteady wake flow on helicopter operations. This paper studied the near-wake flow topology of a generic ship at Re = 8 × 104 to assess the capability of a hybrid RANS/LES (Reynolds-averaged Navier–Stokes/large-eddy simulation) approach, known as IDDES (improved delayed detached-eddy simulation). The impact of computational parameters, including the mesh grid, residual level, time-step size, momentum discretization scheme and transient formulation, on the wake flow was investigated. The numerical results were validated by using the previous experimental data and LES results. The results show that except of the mesh resolution all other computational parameters varied in the current study do not have significant effect on the global drag forces, but showing large differences on the prediction of the local wake flow structures. This point has not been evidently reported in the previous work. The finer grid resolution is sufficient to produce an accurate qualitative and quantitative prediction of the flow structures, while using a poor grid resolution (coarse mesh) leads to inaccurate prediction of the flow topology. The recommended parameters for the time-step size (7.5 × 10−5s) and residual level (1 × 10−4) provide sufficient accuracy of wake predictions, showing good agreement with reference studies. For the convective term of the momentum equation in IDDES, the bounded central differencing scheme is proposed for its discretization, while the bounded second-order implicit is proposed to be adopted as the transient formulation.

Analysis of numerical factors affecting large eddy simulation of pollutant diffusion around buildings

In recent years, Large Eddy Simulation (LES) has been often used for predicting the pollutant diffusion around buildings. However, due to the numerical discretization error and the sub-grid scale modeling error, some empirical factors related to LES have not yet formed with completion for the best practice. This study focused on LES simulation of the airflow and pollutant diffusion around building with a synthetic inflow turbulence method and Wall-Adapting Local Eddy-Viscosity (WALE) model, discuss LES empirical factors, such as effects of grid resolution, sub-grid scale (SGS) WALE model with coefficient Cw and the sub-grid scale Schmidt number ScSGS in details. The results indicate that the numerical wind tunnel created by LES can better reproduce the characteristics of the airflow and concentration field around buildings while keeping predicted physical fields are in line with the evaluation index. In addition, the results also indicate that the solution with the finest grid resolution may not have the best agreement with the experimental data, the flow field is more sensitive to the change of SGS model coefficient Cw when the grid resolution is lower, which shows a trend that the larger coefficient Cw has better simulation in the windward sides of the building, while the value of the coefficient Cw shows an opposite trend in the recycling area at the rear of the building.

Ensemble Cloud Model Application in Simulating the Catastrophic Heavy Rainfall Event

An attempt has been made in the present research to simulate a deadly flash-flood event over the City of Skopje, Macedonia on 6 August 2016. A cloud model ensemble forecast method is developed to simulate a super-cell storm's initiation and evolutionary features. Sounding data are generated using an ensemble approach, that utilizes a triple-nested WRF model. A three-dimensional (3-D) convective cloud model (CCM) with a very fine horizontal grid resolution of 250-m is initialized, using the initial representative sounding data, derived from the WRF 1-km forecast outputs. CCM is configured and run with an open lateral boundary conditions LBC, allowing explicit simulation of convective scale processes. This preliminary study showed that the ensemble approach has some advantages in the generation of the initial data and the model initialization. The applied method minimizes the uncertainties and provides a more qualitative-quantitative assessment of super-cell storm initiation, cell structure, evolutionary properties, and intensity. A high-resolution 3-D run is capable to resolve detailed aspects of convection, including high-intensity convective precipitation. The results are significant not only from the aspect of the cloud model's ability to provide a qualitative-quantitative assessment of intense precipitation but also for a deeper understanding of the essence of storm development, its vortex dynamics, and the meaning of micro-physical processes for the production and release of large amounts of precipitation that were the cause of the catastrophic flood in an urban area. After a series of experiments and verification, such a system could be a reliable tool in weather services for very short-range forecasting (nowcasting) and early warning of weather disasters.

Volume penalization method for solving coupled radiative-conductive heat transfer problems in complex geometries

A novel immersed boundary method for simulating coupled radiative-conductive heat transfer based on a volume penalization method is proposed and verified. A smooth source/sink term is introduced to the governing equations for radiative and conductive heat transfer in order to take into account the absorption, reflection and emission at a solid surface. The proposed algorithm is successfully implemented into an open-source CFD solver, OpenFOAM with adaptive mesh refinement to guarantee sufficiently fine grid resolution near solid surfaces. Benchmark problems of pure radiation and combined conduction-radiation are considered for verifying the proposed method. The present simulation results under various absorption and emission conditions show good agreement with analytical solutions as well as existing literature data within around 5% errors. In addition to its superior performance in terms of accuracy, the present approach does not require special treatments around the solid surface with arbitrary complex geometry to impose boundary conditions for radiative heat transfer, and thereby wide applicability in scientific and engineering problems.

Large-Eddy Simulations of Wind-Driven Cross Ventilation, Part1: Validation and Sensitivity Study

Natural ventilation is gaining popularity in response to an increasing demand for a sustainable and healthy built environment, but the design of a naturally ventilated building can be challenging due to the inherent variability in the operating conditions that determine the natural ventilation flow. Large-eddy simulations (LES) have significant potential as an analysis method for natural ventilation flow, since they can provide an accurate prediction of turbulent flow at any location in the computational domain. However, the simulations can be computationally expensive, and few validation and sensitivity studies with respect to simulation parameters such as grid resolution and boundary conditions have been reported. The objectives of this study are to validate LES of wind-driven cross-ventilation and to quantify the sensitivity of the solution to the grid resolution and the inflow boundary conditions. We perform LES for an isolated building with two openings, using three different grid resolutions and two different inflow conditions with varying turbulence intensities. Predictions of the ventilation rate are compared to a reference wind-tunnel experiment available from literature, and we also quantify the age of air and ventilation efficiency. For the cross-ventilation case modeled in this paper, the prediction of the mean ventilation flow rate is very robust, showing negligible sensitivity to the grid resolution or the inflow characteristics with the maximum error of 1.9 and 1.3% for each sensitivity study. However, a sufficiently fine grid resolution is required to obtain accurate predictions of the detailed flow pattern and the age of air as they show comparably larger errors of 10 and 20% in the grid sensitivity study, and the standard deviation of the instantaneous ventilation rate is affected by the turbulence in the inflow condition with showing 44% difference.

Learning the Physics of Particle Transport via Transformers

Particle physics simulations are the cornerstone of nuclear engineering applications. Among them radiotherapy (RT) is crucial for society, with 50% of cancer patients receiving radiation treatments. For the most precise targeting of tumors, next generation RT treatments aim for real-time correction during radiation delivery, necessitating particle transport algorithms that yield precise dose distributions in sub-second times even in highly heterogeneous patient geometries. This is infeasible with currently available, purely physics based simulations. In this study, we present a data-driven dose calculation algorithm predicting the dose deposited by mono-energetic proton beams for arbitrary energies and patient geometries. Our approach frames particle transport as sequence modeling, where convolutional layers extract important spatial features into tokens and the transformer self-attention mechanism routes information between such tokens in the sequence and a beam energy token. We train our network and evaluate prediction accuracy using computationally expensive but accurate Monte Carlo (MC) simulations, considered the gold standard in particle physics. Our proposed model is 33 times faster than current clinical analytic pencil beam algorithms, improving upon their accuracy in the most heterogeneous and challenging geometries. With a relative error of 0.34±0.2% and very high gamma pass rate of 99.59±0.7% (1%, 3 mm), it also greatly outperforms the only published similar data-driven proton dose algorithm, even at a finer grid resolution. Offering MC precision 4000 times faster, our model could overcome a major obstacle that has so far prohibited real-time adaptive proton treatments and significantly increase cancer treatment efficacy. Its potential to model physics interactions of other particles could also boost heavy ion treatment planning procedures limited by the speed of traditional methods.

On high-order numerical schemes for viscous relativistic hydrodynamics through the Kelvin–Helmholtz instability

ABSTRACT This work assesses the dissipative properties of high-order numerical methods for relativistic hydrodynamics. A causal theory of physical dissipation is included within a finite volume high-resolution shock-capturing framework based on the Israel–Stewart theory to study high-order WENO (weighted-essentially non-oscillatory) schemes for simulating the relativistic Kelvin–Helmholtz instability. We provide an estimation of the numerical dissipation of high-order schemes based on results obtained both with and without physically resolved dissipation and determine an empirical relationship between the numerical dissipation and the grid resolution. We consider the appearance of secondary flow features within the evolution of the Kelvin–Helmholtz instability and determine that they are numerical artifacts — this is partly based on arguments presented in terms of a frame-dependent form of the relativistic Reynolds number. There is a potential advantage of using high-order schemes in terms of their accuracy and computational cost on coarser grid resolutions when directly compared to low-order schemes on a fine grid in the presence of physical viscosity. It is possible to find reasonable agreement between numerical results that employ lower-order schemes using a finer grid resolution and results that employ higher order schemes at a coarser grid resolution when sufficient viscosity is present. Overall, the present analysis gives an insight into the numerical dissipation of high-order shock-wave capturing schemes which can be relevant to computational studies of astrophysical phenomena in the relativistic regime. The results presented herein are problem and scheme-dependent and serve to highlight the different roles of numerical and physical dissipation.

Technology Focus: Heavy Oil (April 2022)

Heavy oils are characterized by high density, high viscosity, and high-heavy-fraction components. Because of high viscosity and lower API gravity than conventional crude oil, primary recovery of some of these crude oil types requires thermal stimulation of the reservoirs. Most of the technologies that deal with heavy oil need to address the mobility ratio or viscous forces before any flooding. In general, poor recovery is caused by physical reasons or geological reasons. Physical reasons can be categorized as capillary forces (existence of the interfacial tension between oil and water, wettability) or viscous forces (high mobility ratio between water and oil). Geological reasons are heterogeneities in reservoir rock and exist in all petroleum oil systems. In heavy oil reservoirs, enhanced oil recovery (EOR) intends to reduce the capillary forces and interfacial tension to improve microscopic displacement efficiency or improve the sweep efficiency (macroscopic) by reducing the mobility ratio between injected fluid and displaced fluid. Improving the mobility ratio is achieved by increasing the viscosity of water using polymers or by reducing the oil viscosity using heat. In general, all technologies need to address the capillary and viscous forces to improve oil recovery. Paper SPE 207361 discusses improving of the efficiency of the flood by near-wellbore conformance and improving the vertical sweep efficiency. The use of fiber-optic sensors, as addressed in paper SPE 199023, is intended to gather better data and avoid misinterpretation during falloff tests and injectivity tests. Traditionally, for heavy oil EOR simulation, because of the addition of chemical species or heat to the flow equations as well as the need for a finer grid resolution, the use of the full-field model in most cases was limited and the use of sector models and local grid refinement to obtain a reasonable accuracy has been applied in the industry. Sector modeling conditions must be satisfied to establish the reliability and the trade-off between accuracy (sector models) and computational expediency (full-field model). Recent development of hardware and software [graphics-processing-unit (GPU) -based simulators] has provided the industry with the tools to achieve a full-field model simulation in most fields by taking advantage of GPU solvers and using a fine-grid model to predict full-field performance. Recommended additional reading at OnePetro: www.onepetro.org. SPE 200279 - Field Application of the Autonomous Inflow Control Device for Optimized Heavy Oil Production in South Sultanate of Oman by Ali Al-Jumah, Petroleum Development Oman, et al. SPE 203012 - More Oil and Less Water: Autonomous Inflow Control Devices in New and Old Producers in Heavy Oil Fields From South of Oman by Ameera Al Harrasi, Petroleum Development Oman, et al. SPE 207684 - Game Changer in Dealing With Hard Scale Using a Slickline Torque Action Debris Breaker by Mahmoud Mohamed Koriesh, Dragon Oil, et al.

On divergence- and gradient-preserving coarse-graining for finite volume primitive equation ocean models

We consider the problem of coarse-graining in the context of finite-volume fluid models. If a variable is defined on a high-resolution grid it may be coarse-grained so that it is defined on a grid of lower resolution. In general this will cause some information about the variable to be lost. In particular, horizontal divergences, gradients or other operators calculated on the coarse grid after projecting may differ from those calculated on the fine grid. In some cases we are able to choose averaging weights for coarse-graining such that the coarse-grid operators will give a result approximating that of the corresponding fine-grid operators applied on the fine grid. In this work we derive general conditions on the averaging weights that allow the divergence and gradient to be preserved. These conditions are applied to a regular triangular mesh with B-grid variable placement in which the fine-grid resolution is some integer multiple N of the coarse-grid resolution. For this case we find particular values for the averaging weights that preserve the divergence, and a set of different averaging weights that preserve the gradient. We observe that the vertical component of the curl is also preserved by the same coarse-graining that preserves divergence. These coarse-grainings are applied to data from FESOM2 simulations and we demonstrate that using the particular coarse-grainings derived herein gives an overall reduction in L1 error when compared with other methods.

The Potential of Harnessing Real-Time Occupancy Data for Improving Energy Performance of Activity-Based Workplaces

Currently, the available studies on the prediction of building energy performance and real occupancy data are typically characterized by aggregated and averaged occupancy patterns or large thermal zones of reference. Despite the increasing diffusion of smart energy management systems and the growing availability of longitudinal data regarding occupancy, these two domains rarely inform each other. This research aims at understanding the potential of employing real-time occupancy data to identify better cooling strategies for activity-based-working (ABW)-supportive offices and reduce the overall energy consumption. It presents a case study comparing the energy performance of the office when different resolutions of occupancy and thermal zoning are applied, ranging from the standard energy certification approach to real-time occupancy patterns. For the first time, one year of real-time occupancy data at the desk resolution, captured through computer logs and Bluetooth devices, is used to investigate this issue. Results show that the actual cooling demand is 9% lower than predicted, unveiling the energy-saving potential to be achieved from HVAC systems for non-assigned seating environments. This research demonstrates that harnessing real-time occupancy data for demand-supply cooling management at a fine-grid resolution is an efficient strategy to reduce cooling consumption and increase workers’ comfort. It also emphasizes the need for more data and monitoring campaigns for the definition of more accurate and robust energy management strategies.

WAVERYS: a CMEMS global wave reanalysis during the altimetry period

As part of the Copernicus Marine Service, WAVERYS is the multi-year wave reanalysis that provides global wave data with a fine grid resolution of 1/5°. This wave reanalysis covers the period 1993–2019 and disseminates 3-h integrated wave parameters describing the sea state at the ocean surface. The wave model used is the version 4 of the model MFWAM, which is driven by sea ice fraction and wind provided by the atmospheric reanalysis ERA5. The WAVERYS includes the assimilation of altimeter wave data and directional wave spectra provided by Sentinel-1. The wave reanalysis includes also wave-current interactions by using 3-h surface current forcing provided by the ocean reanalysis GLORYS. This paper highlights the assessment of wave parameters provided by the WAVERYS. The validation has been performed with independent altimeter significant wave heights and buoy wave data. The results show the good accuracy of scatter index of SWH (significant wave height) which is 8.7% in comparison with HY-2A altimeter. Moreover, we point out that scatter index of SWH from the WAVERYS is improved by about 9% with respect to the ERA5 wave dataset. We also indicate the good accuracy of swell propagation thanks to the assimilation of directional wave spectra. An analysis has been conducted for wave-current interactions and also discussions about extreme values and trend of time series are suggested.