A risk analysis is conducted considering an array of release sources located around the NEOM shoreline. The sources are selected close to the coast and in neighboring regions of high marine traffic. The evolution of oil spills released by these sources is simulated using the MOHID model, driven by validated, high-resolution met-ocean fields of the Red Sea. For each source, simulations are conducted over a 4-week period, starting from first, tenth and twentieth days of each month, covering five consecutive years. A total of 48 simulations are thus conducted for each source location, adequately reflecting the variability of met-ocean conditions in the region. The risk associated with each source is described in terms of amount of oil beached, and by the elapsed time required for the spilled oil to reach the NEOM coast, extending from the Gulf of Aqaba in the North to Duba in the South. To further characterize the impact of individual sources, a finer analysis is performed by segmenting the NEOM shoreline, based on important coastal development and installation sites. For each subregion, source and release event considered, a histogram of the amount of volume beached is generated, also classifying individual events in terms of the corresponding arrival times. In addition, for each subregion considered, an inverse analysis is conducted to identify regions of dependence of the cumulative risk, estimated using the collection of all sources and events considered. The transport of oil around the NEOM shorelines is promoted by chaotic circulations and northwest winds in summer, and a dominant cyclonic eddy in winter. Hence, spills originating from release sources located close to the NEOM shorelines are characterized by large monthly variations in arrival times, ranging from less than a week to more than two weeks. Similarly, large variations in the volume fraction of beached oil, ranging from less then 50\% to more than 80\% are reported. The results of this study provide key information regarding the location of dominant oil spill risk sources, the severity of the potential release events, as well as the time frames within which mitigation actions may need to deployed.

Efficient downscaling of large ensembles of coarse-scale information is crucial in several applications, such as oceanic and atmospheric modeling. The determining form map is a theoretical lifting function from the low-resolution solution trajectories of an infinite-dimensional dissipative dynamical system to their corresponding fine-scale counterparts. Recently, Hammoud et al. (2022b) introduced CDAnet a physics-informed deep neural network as a surrogate of the determining form map for efficient downscaling. CDAnet was demonstrated to efficiently downscale noise-free coarse-scale data in a deterministic setting. Herein, the performance of well-trained CDAnet models is analyzed in a stochastic setting involving (i) observational noise, (ii) model noise, and (iii) a combination of observational and model noises. The analysis is performed employing the Rayleigh-Bénard convection paradigm, under three training conditions, namely, training with perfect, noisy, or downscaled data. The effects of observational and model noise on the CDAnet downscaled solutions are analyzed. Furthermore, the effects of the Rayleigh number and the spatial and temporal resolutions of the coarse-scale information on the downscaled fields are examined. The results suggest that the expected l 2 -error of CDAnet behaves quadratically in terms of the standard deviations of the observational and model noises. The results also suggest that CDAnet responds to uncertainties similar to CDA with an additional error overhead due to CDAnet being a surrogate model of the determining form map.

Gasification of heavy petroleum residues can convert low-value feedstock to hydrogen-rich syngas, which can further be used for power generation and/or chemical production. The present work proposed an updated functional-group-based approach (FGMech) to modeling the gasification of a vacuum residue oil (VRO), which is helpful for better understanding the detailed kinetics of the gasification and improving gasifier performance. Elemental, average molecular weight (AMW) and nuclear magnetic resonance (NMR) analyses were conducted experimentally to characterize VRO, including elemental composition, average molecular formula and the functional group distribution, which were further used for model construction. A lumped mechanism for VRO devolatilization was constructed based on the updated FGMech approach: stoichiometric parameters of stable gases, tars and char were obtained from experiments, while those of radicals were based on the multiple linear regression (MLR) correlations; thermodynamic and kinetic parameters were derived from Benson group additivity method and rate rules, respectively. A merged detailed model was adopted for describing the conversion of gases and tars, and a global model was used for char. To test the reliability of the present model approach, Orimulsion gasification experiments from literature were simulated using an integrated perfectly stirred reactor (PSR) and plug flow reactor (PFR) model. It shows that the present model can reasonably predict measured results under various equivalence ratios, and has better performance on the prediction of CH4 compared with most literature models. Based on model analyses, syngas comes from the conversion of C2H4, H2S, CH4 and char in different gasification stages. Benzene, toluene, naphthalene and 1-methylnaphthalene are initial tar species considered in the devolatilization of the VRO. They can undergo hydrogen abstraction acetylene addition (HACA) and C3H3/C5H5 addition reaction pathways to produce large PAHs.

Computational singular perturbation (CSP) has been successfully used in the analysis of complex chemically reacting flows by systematically identifying the intrinsic timescales and slow invariant manifolds that capture the essential subprocesses driving the dynamics of the system. In this article, the analytical and computational framework is applied for the first time to analyze the Lagrangian droplets undergoing evaporation and dispersion in the surrounding gases. First, a rigorous mathematical formulation is derived to adapt the CSP tools into the droplet dynamics equations, including the formal definition of the tangential stretching rate (TSR) that represents the explosive/dissipative nature of the system. Canonical case studies are then conducted to demonstrate the utility of the CSP methodology in identifying various physical mechanisms driving the evolution of the system, such as the distinction of thermal-driven and mass-driven regimes. Various definitions of the importance indices are also examined to provide in-depth analysis of different subprocesses and their interactions in modifying the droplet dynamics.

Ammonia is a molecule that has been essential to human activities for centuries. It is widely used as a feedstock for fertilizers, industrial chemicals, and emissions after-treatment systems. The properties of ammonia have led to its interest as a carrier for hydrogen in energy applications. The combustion of ammonia for power and propulsion offers direct applications of this molecule in energy and transportation applications. However, there are significant challenges related to ammonia combustion, including low flammability and potentially high emissions. Blending of ammonia with hydrogen or hydrocarbons offers opportunities to improve combustibility. This mini review discusses challenges related to ammonia combustion and current state-of-the-art approaches to overcoming these challenges with research into chemical kinetics, laminar and turbulent flames, and engine and turbine systems. This paper seeks to introduce and summarize recent results on ammonia combustion by highlighting pertinent aspects of this rich and rapidly increasing body of information.

Manually reading and logging gauge data is time inefficient, and the effort increases according to the number of gauges available. We present a computer vision pipeline that automates the reading of analog gauges. We propose a two-stage CNN pipeline that identifies the key structural components of an analog gauge and outputs an angular reading. To facilitate the training of our approach, a synthetic dataset is generated thus obtaining a set of realistic analog gauges with their corresponding annotation. To validate our proposal, an additional real-world dataset was collected with 4.813 manually curated images. When compared against state-of-the-art methodologies, our method shows a significant improvement of 4.55 in the average error, which is a 52% relative improvement.

PMoA/G5 catalyst was synthesized, and its oxidative desulfurization (ODS) performance on model oil was studied. The catalyst and oxidation-extraction-adsorption system was used for the ODS of Arabian Extra light oil (AXL). Acetonitrile and methanol were chosen as different extractants for the extraction of sulfones (O2S and O2S4). The distribution of sulfone was first reported in detail at each of the three-stage extraction solvents at the molecular level analyzed by the Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS), proton, and 13C nuclear magnetic resonance (1H NMR,13C NMR). The FT-ICR MS results show that the extracted proportion of macromolecular sulfone compounds increases with the extraction stages. Acetonitrile exhibited better selectivity than methanol for polyaromatic sulfone with a high carbon number for the O2S species with double bond equivalent (DBE) = 12–15 and O2S2 species with DBE = 11–16. The NMR results reveal that polyaromatics with naphthenic rings and a low carbon number (<30) can be easily extracted due to their high polarity. The excellent performance of the PMoA/G5 catalyst makes it a promising candidate in the ODS reaction, and the research results give guidelines for ODS technology.

Ozone has been widely used for its disinfection properties ever since its efficient production was made possible by plasma discharges. To-date, many experimental and modeling studies have been—and still are—dedicated to further improve the O3 production efficiency. Early on, it became clear that heat has a detrimental effect. Hence, little attention has been paid to the temperature-dependence of the plasma chemistry. However, with the increased use of O2 as (co-)reactant for plasma-based processes at elevated temperatures, this becomes essential. Therefore, we developed a reaction mechanism to study the temperature-dependence of the O2/O3 (plasma) chemistry. Here, we present the experimental validation of this mechanism and an analysis of the different O3 production trends as a function of gas temperature (300–590 K) and discharge power (5–20 W). Through improving key ozone reactions and electron impact dissociation processes, our mechanism could well-predict all experimentally observed trends. Our analysis revealed the importance of the electronic excited states of O2 and how the temperature-dependence of the plasma-based O3 production is highly dependent on the discharge power. Therefore, we believe that this work can contribute to a better understanding of the underlying physicochemical mechanisms of any O2/O3-containing (plasma) process operating at elevated temperatures. Nevertheless, our work also revealed the need for more accurate and comprehensive data with respect to the production and consumption of the electronic excited states of O2.

This study investigates the factors that affect the lifetime and popping location of surface bubbles. The experiment was conducted using three different liquids (water, Sodium Dodecyl Sulfate, and Decane) with varying bubble sizes, using three different needle sizes. Each setup was tested 50 times. For pure water bubbles, the foot of the bubble is the most critical location because it typically has the highest temperature gradient, which creates a localized Marangoni flow that thins the film and eventually leads to the bubble bursting at the foot. When SDS was added to water, the bubble lifetime increased significantly. This is because the Marangoni stresses were reduced, and the bubble film thinned mainly due to curvature-driven drainage flow. The lifetime of the SDS bubble had a positive correlation with increasing bubble size. For Decane bubbles, the volatility of the liquid plays a significant role in the lifetime and popping location of the bubble. When the Decane was heated to 40°C, the lifetime of the bubbles increased significantly from 0-20 seconds to 8-12 minutes. This is because the high volatility of the Decane caused rapid evaporation of the bubble cap at the interface, which cooled the surface of the liquid. This temperature difference creates a difference in surface tension, which causes the liquid to flow from the bulk liquid into the apex of the bubble, thickening the cap film until it cools down. Then, it pops from the top due to the curvature-driven drainage.

The temporal linear stability of plane Poiseuille flow modified by spanwise forcing applied at the walls is considered. The forcing consists of a stationary streamwise distribution of spanwise velocity that generates a steady transversal Stokes layer, known to reduce skin-friction drag in a turbulent flow with little energetic cost. A large numerical study is carried out, where the effects of both the physical and the discretization parameters are thoroughly explored, for three representative subcritical values of the Reynolds number Re. Results show that the spanwise Stokes layer significantly affects the linear stability of the system. For example, at Re=2000 the wall forcing is found to more than double the negative real part of the least-stable eigenvalue, and to decrease by nearly a factor of four the maximum transient growth of perturbation energy. These observations are Re-dependent and further improve at higher Re. Comments on the physical implications of the obtained results are provided, suggesting that spanwise forcing might be effective to obtain at the same time a delayed transition to turbulence and a reduced turbulent friction.