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At least 577 records · Page 32

Computing dissipation for molecular-level turbulence simulations

A major difficulty in the analysis of molecular-level simulations is that macroscopic flow quantities are inherently noisy due to molecular fluctuations. An important example for turbulent flows is the kinetic energy dissipation rate. Traditionally, this quantity is calculated from gradients of the macroscopic velocity field, which exacerbates the noise problem. The inability to accurately compute the dissipation rate makes meaningful comparison of molecular-level and continuum simulation results a serious challenge. Herein, we extend previously developed coarse-graining theories to derive an exact molecular-level expression for the dissipation rate, which would circumvent the need to compute gradients of noisy fields. Although the exact expression cannot feasibly be implemented in Sandia’s direct simulation Monte Carlo (DSMC) code SPARTA, we utilize an approximate “hybrid” approach and compare it to the conventional gradient-based approach for planar Couette flow and the two-dimensional Taylor-Green vortex, demonstrating that the hybrid approach is significantly more accurate. Finally, we explore the possibility of adopting a Lagrangian approach to calculate the energy dissipation rate.

74 ATOMIC AND MOLECULAR PHYSICS↗

Sorbmatech{sup R}Cs, an Innovative Highly Selective Cs Sorbent for Wastewater Decontamination - 20065

The treatment of radioactive wastewater from the operating nuclear industry (energy production, reprocessing of spent fuel, decommissioning of shut-down facilities, etc.) or in case of incidental or accidental situation (such as Fukushima Daichii NPP accident) is an important issue requiring constant improvement of the technologies and techniques used to prevent radioactive releases into the environment and/or to reduce the production of secondary waste. CEA, Orano and CTI are collaborating since 2014, with the support of the French government's program 'investments for the future', to develop Sorbmatech{sup R}Cs, an innovative and patented selective sorbent (Grandjean and Barre 2014) to deal with the removal of radioactive {sup 137}Cs, one of the most hazardous isotope to be managed in nuclear waste, highly efficient either in agitated reactor or in column process. Sorbmatech{sup R}Cs sorbent consists of mesoporous silica particles loaded with potassium-copper hexacyanoferrate nanoparticles (KCu-HCF). This peculiar structure enables much faster sorption kinetics compared to denser crystalline structures, such as Silicotitanate or Zeolite sorbents, whose drawback consists in hindering the diffusion process through the material, and whose larger sorbent particles slow down the ion exchange process. The equilibrium of Sorbmatech{sup R}Cs is reached in few minutes, even at high flow rates in a fixed-bed column process (up to 10 m.h{sup -1} Darcy velocity) with low drop pressure. Moreover, Sorbmatech{sup R}Cs can be used over a wide pH range from 2 to 10 and has a very high selectivity towards {sup 137}Cs even in brine solution (saline, mineral or sea water). This new sorbent also has a K{sub d} higher than 10{sup 5} mL.g{sup -1} depending on the salinity of the wastewater, enabling a highly efficient removal of Cs trace in radioactive wastewater compared to Cs selective sorbent such as Zeolites and Silicotitanates. Its radiological resistance enables the treatment of high, medium and low activity wastewater. The CEA-Orano-CTI/ALSYS partnership leads to the development of a simple and low-cost synthetic route, which demonstrated large-scale manufacturing of the product on a batch of 100 kg. Two products have been developed and are ready for short run market introduction so far with grain size well adapted either for column processes or agitated reactors.. Finally, the industrial implementation has been studied and largely benefits from the properties of the sorbent. Indeed, its high sorption kinetics enable high flow rates resulting in a decrease of operation times, unit sizes, and volumes of secondary waste produced. Moreover, Sorbmatech{sup R}Cs is designed to be combined into a full and integrated solution, ranging from preliminary optimization of operating conditions through numerical dimensioning model, industrial implementation and treatment of the wastewater (through cartridge or preconditioned columns systems developed thanks to Orano's extensive expertise), to long-term stabilization of generated waste (under progress). (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Experimental and Computational Analysis of NEAMS Pebble Bed Reactors

The Advanced High-Temperature Pebble Bed Reactor concept leverages a particle-based fuel format consisting of discrete spherical graphite pebbles arrayed in a packed bed architecture. Thermal regulation achieved via flow of gas (e.g., helium) or liquid (e.g., molten salt) coolants through the void spaces between pebbles in the bed (characteristic pebble diameters: ~ 6 cm, gas cooled; ~ 3 cm, liquid cooled). This design is of interest owing to inherent advantages including passive safety features and highly efficient heat transfer characteristics that enable high power densities to be achieved. Fully leveraging these advantages requires a fundamental understanding of the complex coolant flow structure within the pebble-shaped fuel bed. Unfortunately, complexities associated with non-invasively probing the micro-scale flow phenomena within the complex network of void spaces between pebbles have hindered efforts to characterize the underlying transport phenomena. Without this fundamental foundation, it becomes challenging to rationally construct macroscopic transport models based upon volume averages of micro-scale parameters that accurately capture the observed flow behavior. Consequently, this lack of fundamental knowledge has limited previous work to coarse comparisons between theory and extremely limited experimental data. Moreover, these comparisons have been made only in terms of integral or macroscopic results. Therefore, multipoint measurements with a high level of spatial and temporal resolution are critically needed to fully map the complex flow patterns and to provide data at high spatial density to permit accurate volume averaging in the pebble bed. For this project, we performed a coordinated experimental and computational effort to quantitatively map the full-field velocity and temperature fields in the interstitial spaces within the pebble bed. The major accomplishments of this project included the important knowledge acquired for the flow mixing and heat transfer in the interstitial pore scales, the effects of flow mixing in the near-wall and far-wall regions, and the by-pass flows of pebble bed systems. The produced high-resolution experimental data (not broadly available in existing literature) were then used for the numerical studies enabling the refinement and validation of standard simulation tools (Nek5000).

42 ENGINEERING↗

Identifying preferential flow from soil moisture time series: Review of methodologies

Abstract Identifying and quantifying preferential flow (PF) through soil—the rapid movement of water through spatially distinct pathways in the subsurface—is vital to understanding how the hydrologic cycle responds to climate, land cover, and anthropogenic changes. In recent decades, methods have been developed that use measured soil moisture time series to identify PF. Because they allow for continuous monitoring and are relatively easy to implement, these methods have become an important tool for recognizing when, where, and under what conditions PF occurs. The methods seek to identify a pattern or quantification that indicates the occurrence of PF. Most commonly, the chosen signature is either (1) a nonsequential response to infiltrated water, in which soil moisture responses do not occur in order of shallowest to deepest, or (2) a velocity criterion, in which newly infiltrated water is detected at depth earlier than is possible by nonpreferential flow processes. Alternative signatures have also been developed that have certain advantages but are less commonly utilized. Choosing among these possible signatures requires attention to their pertinent characteristics, including susceptibility to errors, possible bias toward false negatives or false positives, reliance on subjective judgments, and possible requirements for additional types of data. We review 77 studies that have applied such methods to highlight important information for readers who want to identify PF from soil moisture data and to inform those who aim to develop new methods or improve existing ones. Core Ideas Soil moisture data can be used to identify the occurrence of preferential flow (PF) and its initiating conditions. Various data‐analysis methods to identify PF differ in susceptibility to error, bias, and subjectivity. These methods can utilize vast amounts of data from soil moisture monitoring networks to develop understanding of when, where, and under what conditions PF occurs. Newly developed methods may lead to better accuracy and reliability, and reduce the need for subjective judgments. Plain Language Summary Preferential flow through soil occurs when a large amount of water is suddenly available, as during an intense storm. This type of flow moves rapidly through the soil in distinct narrow pathways rather than moving evenly throughout the body of soil, with major consequences for groundwater resources, ecosystems, spreading of contaminants, and other vital concerns. Methods of detecting preferential flow have been developed that utilize measurements of soil water content made by sensors installed at various depths. This measurement technology has been widely implemented, many locations now having datasets years in length, and various methods have been developed for using these to identify preferential flow. The various methods are based on different features in the soil moisture records and vary in their advantages and shortcomings. In this review, we explain and evaluate these methods, highlighting important information for their implementation to identify preferential flow from soil moisture data and for efforts to develop new methods or improve existing ones.

Nimmo, John R↗

Gaussian process hydrodynamics

Abstract We present a Gaussian process (GP) approach, called Gaussian process hydrodynamics (GPH) for approximating the solution to the Euler and Navier-Stokes (NS) equations. Similar to smoothed particle hydrodynamics (SPH), GPH is a Lagrangian particle-based approach that involves the tracking of a finite number of particles transported by a flow. However, these particles do not represent mollified particles of matter but carry discrete/partial information about the continuous flow. Closure is achieved by placing a divergence-free GP prior ξ on the velocity field and conditioning it on the vorticity at the particle locations. Known physics (e.g., the Richardson cascade and velocity increment power laws) is incorporated into the GP prior by using physics-informed additive kernels. This is equivalent to expressing ξ as a sum of independent GPs ξ l , which we call modes, acting at different scales (each mode ξ l self-activates to represent the formation of eddies at the corresponding scales). This approach enables a quantitative analysis of the Richardson cascade through the analysis of the activation of these modes, and enables us to analyze coarse-grain turbulence statistically rather than deterministically. Because GPH is formulated by using the vorticity equations, it does not require solving a pressure equation. By enforcing incompressibility and fluid-structure boundary conditions through the selection of a kernel, GPH requires significantly fewer particles than SPH. Because GPH has a natural probabilistic interpretation, the numerical results come with uncertainty estimates, enabling their incorporation into an uncertainty quantification (UQ) pipeline and adding/removing particles (quanta of information) in an adapted manner. The proposed approach is suitable for analysis because it inherits the complexity of state-of-the-art solvers for dense kernel matrices and results in a natural definition of turbulence as information loss. Numerical experiments support the importance of selecting physics-informed kernels and illustrate the major impact of such kernels on the accuracy and stability. Because the proposed approach uses a Bayesian interpretation, it naturally enables data assimilation and predictions and estimations by mixing simulation data and experimental data.

Mathematics↗

Sensitivity Analysis of an Electrospray Dehumidification System

Electrically enhanced condensation achieved by an electrospray system can enhance dehumidification in HVAC applications if successfully scaled up. The first step towards scale-up is identifying critical design and operating parameters that significantly impact dehumidification for the electrospray system. Sensitivity analysis is one approach for identifying critical parameters. This paper presents a methodology that can efficiently perform quantitative sensitivity analysis on a computationally expensive high fidelity simulation model, which is a computational fluid dynamics (CFD) model of the electrospray system. The methodology employs surrogate modeling and Sobol sensitivity analysis. We estimate the main and total effect Sobol sensitivity indices of four operating parameters of the electrospray system. The results reveal that the most important parameter is the size of the sprayed droplets, followed by the volumetric flow rate of the bulk air and injected water in the system. The water injection velocity of the spray was found to have little to no impact on dehumidification.

Young, David↗

Investigation of fouling mechanisms for diesel engine exhaust heat recovery

The effect of diesel engine exhaust fouling on heat and mass exchangers for waste heat recovery is investigated. Experiments are conducted for a range of operating conditions relevant to the use of the waste heat from a diesel engine for powering a 2.71 kW capacity absorption heat pump. Thermal resistances of fouling layers as well as their effects on pressure drop are determined, and the underlying mechanisms for deposition and removal are investigated. Fouling layer effects are most severe for the lowest coolant temperatures and 100% generator load. At these conditions, the fouling thermal resistance is approximately 70% of the total resistance, and the ratio of the steady-state pressure drop to the baseline pressure drop is 3.25. Flow induced shear is found to be the primary growth inhibiting mechanism at high exhaust velocities. Findings from this study can guide heat exchanger design for a variety of waste heat recovery systems.

04 OIL SHALES AND TAR SANDS↗

Simulation of dislocation evolution in microparticle impacts over a wide range of impact velocities

We report the dynamic loading environment created by high velocity microparticle impacts is very difficult to model. The extremely high strain rates, large deformations, and high temperatures affect the flow stress of the material in ways that standard flow stress models cannot capture. Plastic deformation and strain hardening in metals is controlled by the motion of dislocations. Dislocations can be nucleated, stored as forest dislocations, or be annihilated as loading progresses. A comprehensive accounting of dislocation density change is needed to accurately describe rate and temperature dependent dislocation glide and evolution across the wide rage of loading conditions present in microparticle impact problems. Therefore, we implement and apply a newly proposed flow stress model (Hunter and Preston, 2015, 2022) that is then coupled with mobile and immobile dislocation density evolution equations. This model is implemented in Los Alamos National Laboratory’s hydrodynamics code, FLAG, to model copper-on-copper microparticle impacts. This new strength model allows for accurate simulation of particle rebound and flattening across a wide range of impact velocities.

36 MATERIALS SCIENCE↗

Tracking Dendritic Growth in Hydrogen-Based Hematite Reduction via Computer Vision

The reduction of hematite to metallic iron using hydrogen (H2) as a reducing agent presents a promising pathway for decarbonizing steel production. In this study, we employ a combination of in situ confocal scanning laser microscopy (CSLM) and advanced computer vision techniques to quantitatively analyze dendritic growth of ferrite during H2-based reduction of iron oxide at high temperatures. A workflow integrating Watershed Image Segmentation (WIS) and Lucas-Kanade Optical Flow (LKOF) is developed to extract both global and local kinetic information from time-resolved micrograph sequences. H2 reduction experiments conducted at 1400 degrees C and 1500 degrees C demonstrate a clear correlation between temperature and reduction rate, as evidenced by accuracy of fitted Johnson-Mehl-Avrami-Kolmogorov (JMAK) parameters. Optical flow analysis further elucidates the anisotropic and branched nature of dendritic growth, providing spatially resolved velocity fields that correlate well with global transformation kinetics. The proposed methodology demonstrates strong agreement with experimental measurements and literature values, offering a robust framework for automated image-based analysis to study kinetics through microstructural evolution in the reduction of iron ore, and likely other reaction-diffusion phenomena.

08 HYDROGEN↗

Role of Inlet Boundary Conditions on Fuel-Air Mixing at Supercritical Conditions

Advanced engine design and alternative fuels present the possibility of fuel injection at purely supercritical conditions in diesel engines and gas turbines. The complex interactions that govern this phenomenon still need significant research, particularly the boundary conditions for fuel injection are critical for accurate simulation. However, the flow inside the injector itself is often omitted to reduce the computational efforts, and thus, velocity, mass flux, or total pressure is specified at the injector exit (or domain inlet), often with simplified velocity profiles and turbulence levels. This simplified inlet boundary treatment has minimal effects on results for conventional fuel injection conditions, however, the validity of this approach at supercritical conditions has not been assessed. Comprehensive real-gas and binary fluid mixing models have been implemented for computational fluid dynamics (CFD) analysis of fuel-air mixing at supercritical conditions. The model is verified using prior CFD results from the literature. The model is used to investigate the effects of the shape of axial velocity and mass fraction profiles at the inlet boundary with the goal to improve the comparison of predictions to experimental data. Results show that the boundary conditions have a significant effect on the predictions, and none of the cases match precisely with experimental data. Furthermore, the study reveals that the physical location of the inlet boundary might be difficult to infer correctly from the experiments and highlights the need for high-quality, repeatable measurements at supercritical conditions to support the development of relevant high-fidelity models for fuel-air mixing.

02 PETROLEUM↗

Convective and turbulent motions in non-precipitating Cu. Part 1: Method of separation of convective and turbulent motions

Atmospheric motions in clouds and cloud surroundings have a wide range of scales, from several kilometers to centimeters. These motions have different impacts on cloud dynamics and microphysics. Larger-scale motions (hereafter referred to as convective motions) are responsible for mass transport over distances comparable with cloud scale, while motions of smaller scales (hereafter referred to as turbulent motions) are stochastic and responsible for mixing and cloud dilution. This distinction substantially simplifies the analysis of dynamic and microphysical processes in clouds. The present research is Part I of the study aimed at describing the method for separating the motion scale into a convective component and a turbulent component. An idealized flow is constructed, which is a sum of an initially prescribed field of the convective velocity with updrafts in the cloud core and downdrafts outside the core, and a stochastic turbulent velocity field obeying the turbulent properties, including the -5/3 law and the 2/3 structure function law. A wavelet method is developed allowing separation of the velocity field into the convective and turbulent components, with parameter values being in a good agreement with those prescribed initially. The efficiency of the method is demonstrated by an example of a vertical velocity field of a cumulus cloud simulated using the System for Atmospheric Modeling (SAM) with bin microphysics and resolution of 10 m. It is shown that vertical velocity in clouds indeed can be represented as a sum of convective velocity (forming zone of cloud updrafts and subsiding shell) and a stochastic velocity obeying laws of homogeneous and isotropic turbulence.

54 ENVIRONMENTAL SCIENCES↗

Strongly Heated Turbulent Flow in a Channel with Pin Fins

Large-eddy simulations (LES) were performed to study the turbulent flow in a channel of height H with a staggered array of pin fins with diameter D = H/2 as a function of heating loads that are relevant to the cooling of turbine blades and vanes. The following three heating loads were investigated—wall-to-coolant temperatures of Tw/Tc = 1.01, 2.0, and 4.0 - where the Reynolds number at the channel inlet was 10,000 and the back pressure at the channel outlet was 1 bar. For the LES, two different subgrid-scale models—the dynamic kinetic energy model (DKEM) and the wall-adapting local eddy-viscosity model (WALE)—were examined and compared. This study was validated by comparing with data from direct numerical simulation and experimental measurements. The results obtained show high heating loads to create wall jets next to all heated surfaces that significantly alter the structure of the turbulent flow. Results generated on effects of heat loads on the mean and fluctuating components of velocity and temperature, turbulent kinetic energy, the anisotropy of the Reynolds stresses, and velocity-temperature correlations can be used to improve existing RANS models.

42 ENGINEERING↗

Ensemble average and nearest particle statistics in disperse multiphase flows

A relation between the ensemble average and the nearest particle statistics is derived. The relation accounts for interactions among all the particles, not only the nearest one, and can be used to study long-range particle interactions without the difficulty of a divergent integral. As an example, this relation is applied to calculate the particle sedimentation velocity to the first order of the particle volume fraction. Using the relation, an important particle–fluid–particle stress is introduced for general multiphase flows.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Computationally Aided Design of a Small-Scale Waste-Glass Melter - 20452

To provide mission support to the WTP for the vitrification of legacy nuclear tank waste at the Hanford site, a reduced-scale vitrification pilot system is being designed to process simulated and actual radioactive tank wastes. The waste stored in underground tanks will be separated into HLW and LAW fractions, where the majority is LAW by mass (approximately 90%) and HLW by activity (greater than 95%). The first tank waste to be processed at the WTP will be LAW. Because Hanford tank waste and the resultant melter feed compositions are known to vary widely, pilot-scale operations are essential to identify potential problems, provide needed data, confirm assumptions, and determine impacts to full-scale melters and off-gas systems from these different feeds. In addition, the reduced-scale melter system must be capable of quickly providing results to operations without the typically high cost of full-scale radioactive operations and to provide an engineering platform in close proximity to local operations staff. The objectives of this computational modeling effort are to produce process conditions like those encountered in the WTP LAW melters and to minimize the volume of radioactive waste necessary for the evaluations. To this end, melter design features are being explored to increase production without significantly increasing surface area or melter-glass volumes or compromising data quality. In support of these objectives, a set of computational fluid dynamic models was developed to provide insight into the flow patterns within these small melters and evaluate design features to increase production without significantly increasing glass inventory. Computed velocities were evaluated at the interface between the cold cap and the molten-glass pool and within the bulk-glass pool. Since melt rate correlates with the velocity underneath the cold cap, this information can be used to select design features that produce the highest gains. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Gravitomagnetic vorticity generation in black hole accretion discs: a potential spatial constraint on plasma flow stability

We calculate the vorticity generation rate in the accretion disc near a slowly rotating black hole in the low-velocity, weak-field limit of general relativity. Specifically, we find that the frame-dragging effect due to the black hole’s rotation – manifested through the gravitomagnetic field – can generate vorticity in a moving plasma in the accretion disc. The mechanism remains operational as long as the accretion disc has non-negligible vertical height and is independent of the exact thermodynamical profile of the disc. The enstrophy density generation rate, as a measure of turbulence and dissipation, is presented, which indicates that the frame-dragging effect can disrupt the stability of the disc away from the z = 0 plane.

79 ASTRONOMY AND ASTROPHYSICS↗

A Pilot-Scale Evaluation of Natural Gas-Based Foam at Elevated Pressure and Temperature Conditions

Abstract Nitrogen (N2) and Carbon Dioxide (CO2) foams have been used as hydraulic fracturing fluids for several decades to reduce water usage and minimize damage in water-sensitive reservoirs. These foam treatments require gases to be liquefied and transported to site. An alternative approach would be to use natural gas (NG) that is readily available from nearby wells, pipelines, and processing facilities as the internal, gaseous phase to create a NG-based foam. Hydraulic fracturing with NG foam is a relatively inexpensive option, makes use of an abundant and often wasted resource, and may even provide production benefits in certain reservoirs. As part of an ongoing development project sponsored by the Department of Energy (DOE), the surface process to create NG foam is being developed and the properties of NG foam are being explored. This paper presents recent results from a rigorous pilot-scale demonstration of NG foam over a range of operating scenarios relevant to surface and bottomhole conditions with a variety of base-fluid mixtures. The Pilot-scale Foam Test Facility (PFTF) used in these investigations is first described. The PFTF is capable of generating foamed fluids at pressures up to 7,500 psig and at temperatures in excess of 300°F. Then, results from several investigations aimed at proving NG foam at conditions relevant to the field are presented. NG foam was characterized using rheology measurements and flow visualization techniques. Experiments were performed to investigate the texture and stability of NG foam generated by two different mixing methods: one using a custom designed tee to match mixing velocities in the field where the gas phase is jetted into the aqueous stream, and another to ensure comprehensive mixing for laboratory analysis. Parametric studies were conducted to explore the effects of flow rate, foam quality, and temperature on the stability of NG foam. Moreover, different fluid preparations were used to investigate the effect of base fluid and additive concentrations on the stability of NG foams. Additional laboratory studies that investigated foam stability with produced water and multicomponent NG mixtures are also reported. The NG foams explored in these investigations exhibited typical, shear-thinning behavior observed in rheological studies of N2- and CO2-based foams. The measured viscosity and observed stability indicate that NG foams are well suited for fracturing applications. Like other foams, NG foam exhibits sensitivity to operating temperature characterized by a decrease in apparent viscosity as temperature increases. Rapid foam breakdown was observed at significantly elevated temperatures exceeding 290°F. In addition to fluid characterization, these investigations also yielded several key lessons that should be applied to future field demonstrations of NG foam.

Beck, Griffin↗

FLOW Estimation and Rose Superposition (FLOWERS): an integral approach to engineering wake models

Abstract. Annual energy production (AEP) is often the objective function in wind plant layout optimization studies. The conventional method to compute AEP for a wind farm is to first evaluate power production for each discrete wind direction and speed using either computational fluid dynamics simulations or engineering wake models. The AEP is then calculated by weighted-averaging (based on the wind rose at the wind farm site) the power produced across all wind directions and speeds. We propose a novel formulation for time-averaged wake velocity that incorporates an analytical integral of a wake deficit model across every wind direction. This approach computes the average flow field more efficiently, and layout optimization is an obvious application to exploit this benefit. The clear advantage of this new approach is that the layout optimization produces solutions with comparable AEP performance yet is completed 2 orders of magnitude faster. The analytical integral and the use of a Fourier expansion to express the wind speed and wind direction frequency create a relatively smooth solution space for the gradient-based optimizer to excel in comparison to the existing weighted-averaging power calculation.

17 WIND ENERGY↗

Lab Collaboration Project (LCP) for Marine Energy: Quantifying Collision Risk for Fish and Turbines Final Technical Report (Task 10)

A persistent environmental concern for the widespread deployment of tidal turbines is the potential for fish and marine mammals to collide with rotating blades (Copping et al. 2016, Copping and Hemery 2020). This is a consequence of well-documented bird and bat mortalities around wind turbines (Smallwood 2007, Thompson et al. 2017), as well as fish mortality at conventional hydropower dams (Pracheil et al. 2016) and tidal barrages (Dadswell and Rulifson 1994). However, unlike hydropower dams or barrages, tidal turbines do not involve structures that channel all flow through the turbines. Similarly, while functionally similar to wind turbines, tidal turbines often operate at lower relative velocities and, depending on the end-use application, may be significantly smaller than utility-scale wind turbines. Both of these factors reduce the likelihood and severity of collision, but the knowledge base on this topic remains limited.

13 HYDRO ENERGY↗