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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9

Impact of large-scale effects on mass transfer and concentration polarization in Reverse Osmosis membrane systems

Here, we present well-resolved computational fluid dynamics simulations of a large-scale reverse osmosis membrane-spacer configuration (1 m). Our computational model solves the flow and transport equations with variable solute-dependent properties. We utilize a high resolution computational mesh to resolve all relevant length scales associated with spacer-induced mixing and thin concentration boundary layers. An important contribution of this work is the development of a modified mass-transfer correlation that accounts for the development of the concentration boundary layer along the channel. A set of 2D axisymmetric simulations were performed for a spiral wound module layer with varying cross-flow conditions and spacer diameters which indicate a significant entrance length effect for concentration profile development at lower flow rates while mixing effects dominate at higher flow rates. The mass-transfer correlations at higher flow rates compare well with published correlations while a surrogate model for Sherwood number was obtained that depends on an additional similarity variable that accounted for entrance length effects at lower flow rates. Finally, a large-scale membrane-spacer design relevant to high-pressure reverse osmosis is studied with a non-uniform arrangement of spacers, which indicate a substantial saving in pressure drop (~40%) compared to traditional uniformly spaced pattern with minor variations (~2%) in concentration polarization, product water quality (~1%) and water recovery (~7%) compared to a uniform spacer pattern.

97 MATHEMATICS AND COMPUTING↗

Photoelectrons in the Quiet Polar Wind

This study presents a newly coupled model capable of treating the superthermal electron population in the global polar wind solution. The model combines the hydrodynamic Polar Wind Outflow Model (PWOM) with the kinetic SuperThermal Electron Transport (STET) code. The resulting PWOM-STET coupled model is described and then used to investigate the role of photoelectrons in the polar wind. We present polar wind results along single stationary field lines under dayside and nightside conditions, as well as the global solution reconstructed from nearly 1000 moving field lines. The model results show significant day-night asymmetries in the polar wind solution owing to the higher ionization and photoelectron fluxes on the dayside compared to the nightside. Field line motion is found to modify this dependence and create global structure by transporting field lines through different conditions of illumination and through the localized effects of Joule heating.

wind↗

Dendritic Alloy Solidification Experiment (DASE)

A space experiment, and supporting ground-based research, is proposed to study the microstructural evolution in free dendritic growth from a supercooled melt of the transparent model alloy succinonitrile-acetone (SCN-ACE). The research is relevant to equiaxed solidification of metal alloy castings. The microgravity experiment will establish a benchmark for testing of equiaxed dendritic growth theories, scaling laws, and models in the presence of purely diffusive, coupled heat and solute transport, without the complicating influences of melt convection. The specific objectives are to: determine the selection of the dendrite tip operating state, i.e. the growth velocity and tip radius, for free dendritic growth of succinonitrile-acetone alloys; determine the growth morphology and sidebranching behavior for freely grown alloy dendrites; determine the effects of the thermal/solutal interactions in the growth of an assemblage of equiaxed alloy crystals; determine the effects of melt convection on the free growth of alloy dendrites; measure the surface tension anisotropy strength of succinon itrile -acetone alloys establish a theoretical and modeling framework for the experiments. Microgravity experiments on equiaxed dendritic growth of alloy dendrites have not been performed in the past. The proposed experiment builds on the Isothermal Dendritic Growth Experiment (IDGE) of Glicksman and coworkers, which focused on the steady growth of a single crystal from pure supercooled melts (succinonitrile and pivalic acid). It also extends the Equiaxed Dendritic Solidification Experiment (EDSE) of the present investigators, which is concerned with the interactions and transients arising in the growth of an assemblage of equiaxed crystals (succinonitrile). However, these experiments with pure substances are not able to address the issues related to coupled heat and solute transport in growth of alloy dendrites.

Beckermann, C.↗

Upscaling Reactive Transport and Clogging in Shale Microcracks by Deep Learning

Fracture networks in shales exhibit multiscale features. A rock system may contain a few main fractures and thousands of microcracks, whose length and aperture are orders of magnitude smaller than the former. It is computationally prohibitive to resolve all the fractures explicitly for such multiscale fracture networks. One traditional approach is to model the small-scale features (e.g., microcracks in shales) as an effective medium. Although this fracture-matrix conceptualization significantly reduces the problem complexity, there are classes of physical processes that cannot be accurately upscaled by effective medium approximations, e.g., microcrack clogging during mineral reactions. Here, we employ deep learning in place of effective medium theory to upscale physical processes in small-scale features. Specifically, we consider reactive transport in a fracture-microcrack network where microcracks can be clogged by precipitation. A deep learning multiscale algorithm is developed, in which the microcracks are upscaled as a wall boundary condition of the main fractures. The wall boundary condition is constructed by recurrent neural networks, which take concentration histories as input and predict the solute transport from main fractures to microcracks. The deep learning multiscale algorithm is firstly employed in specific scenarios, then a general model is developed which can work under various conditions. The new approach is validated against fully resolved simulations and an analytical solution, providing a reliable and efficient solution for problems that cannot be upscaled by effective medium models.

58 GEOSCIENCES↗

Comparing Constant and Transient Membrane Transport Parameters for Use in Wave Desalination Models

Directly pressurizing seawater for desalination with reverse osmosis membranes via wave motion is a promising and sustainable method for producing freshwater in coastal regions. However, such a system could result in significant pressure fluctuations and a departure from conventional steady-state desalination operations. This study sought to assess if membrane transport parameters (apparent water and salt permeability) should be modeled as transient or constant in solution–diffusion-based modeling efforts of dynamically operated desalination systems, such as those coupled to wave power. Two approaches were used to model membrane transport parameters: one considered each parameter to be a function of the net driving pressure of the system, and the other assumed they were constant across all conditions. A pilot-scale system was used to conduct steady-state and controlled ramping experiments. Data from steady-state experiments were used to calculate transient and constant transport parameters. Parameter combinations were used in a simulation model to predict water flux and effective permeate salinity, and simulation outcomes were compared against experimental ramping results. The transient relationships for both water and salt permeability produced the most accurate results for water flux and comparable results for effective permeate salinity. Development of such relationships would be unique to a specific system but could be valuable in modeling wave-driven desalination systems across the wide range of operating conditions they experience.

13 HYDRO ENERGY↗

spopt: a python package for solving spatial optimization problems in PySAL

Spatial optimization is a major spatial analytical tool in management and planning, the significance of which cannot be overstated. Spatial optimization models play an important role in designing and managing effective and efficient service systems such as transportation, education, public health, environmental protection, and commercial investment among others. To this end, spopt (spatial optimization) is under active development for the inclusion of newly proposed models and methods for regionalization, facility location, and transportation-oriented solutions (Feng et al., 2021). Spopt is a submodule in the open-source spatial analysis library PySAL (Python Spatial Analysis Library) founded by Dr. Sergio J. Rey and Dr. Luc Anselin in 2005 (Rey et al., 2015, 2021; Rey & Anselin, 2007). The goal of developing spopt is to provide management and decision-making support to all relevant practitioners and to further promote the appropriate and meaningful application of spatial optimization models in practice.

97 MATHEMATICS AND COMPUTING↗

A Particle-Based Conditional Sampling Scheme for the Simulation of Transport in Fractured Rock With Diffusion Into Stagnant Water and Rock Matrix

In situ experiments and field-scale characterization studies have pointed out that, in fractured crystalline media, groundwater flow is highly channelized. This implies that, at the scale of a single fracture, only part of the fracture surface area is in contact with flowing water, while the rest of in-plane water is essentially stagnant and can be accessed by solutes via molecular diffusion. Despite their importance for contaminant retention, to date, there are no numerical or analytical approaches that could be used to assess the implication of stagnant water zones on solute transport in realistic large-scale Discrete Fracture Network-based models. In this study, we present an efficient and flexible algorithm for the simulation of transport in fractured rock with diffusion into stagnant water and rock matrix. The algorithm is a generalization of a previously developed numerical framework for time domain particle tracking in sparsely fractured rock. The key of the generalization is that total time in fracture (τ f ) is first evaluated using a Monte Carlo sampling and then a second sampling is performed conditioned on τ f . The algorithm has been successfully validated against existing independent solutions and the implication of diffusion into stagnant water and secondary diffusion into the matrix has been assessed for a realistic modeling scenario. The results show that, due to diffusion into stagnant water, contaminants are more strongly retarded. This increased retention is more significant for sorbing species, as a larger number of sorption sites is accessible. A high sensitivity to the flowing channel/stagnant water zone geometry has also been observed.

54 ENVIRONMENTAL SCIENCES↗

Experimental and numerical study of the effects of solution concentration and temperature on concrete under external sulfate attack

The work reports on an experimental programme, conducted to validate comprehensively our previously proposed coupled chemo-transport model for external sulfate attack on concrete. Specifically, the effects of the concentration of sulfate solution and temperature on the distribution of sulfate ions in concrete are experimentally investigated and used to demonstrate the accuracy of the modeling framework. Further, the profile of aluminate depletion and the leaching depth numerically are investigated. For all cases the model predictions are in good agreement with the experimental results, showing increases of the concentration of sulfate ions in concrete with higher concentrations of sulfate solution and higher temperatures. It is concluded that higher sulfate solution concentration and temperature enhance the processes involved in the external sulfate attack on concrete, namely diffusion of sulfate ions and their chemical reactions with concrete. It is found that these parameters affect the external sulfate attack predominantly via the chemical reaction process.

36 MATERIALS SCIENCE↗

Comparison of CFD and DSMC Using Calibrated Transport Parameters

Hypersonic re-entry flows span a wide range of length scales where regions of both rarefied and continuum flow exist. Traditional computational fluid dynamics (CFD) techniques do not provide an accurate solution for the rarefied regions of such ‘mixed’ flow fields. Although direct simulation Monte Carlo (DSMC) can be used to accurately capture both the continuum and rarefied features of ‘mixed’ flow fields, they are computationally expensive when employed to simulate the low Knudsen number continuum regimes. Thus, a hybrid framework for seamlessly combining the two methodologies, CFD and DSMC, continues to be a topic of significant research effort. Ensuring consistency in the reaction kinetics and transport models employed within CFD and DSMC is a crucial requirement for obtaining a reliable solution from a hybrid framework for combined continuum/rarefied high speed flows. This paper represents one of the first studies to utilize the calibrated transport parameters developed to ensure consistency between CFD and DSMC solvers. The new variable soft sphere (VSS) parameters are compared to both previous “standard” variable hard sphere (VHS) parameters and also to solutions from the CFD transport properties that the new parameters were developed to reproduce.

Liechty, D. S.↗

Permeate fluxes from desalination of brines and produced waters: A reactive transport modeling study

The increasing interest in the use of membrane systems to desalinate inland brackish water, agricultural drainage, and industrially produced wastewater demands improved means of predicting desalination system performance under variable feedwater compositions. The interaction among water flow, solute transport, and chemical composition in these systems impacts permeate flux evolution. Here, an established multicomponent reactive transport simulator that accounts for these coupled processes is applied to compute osmotic pressure and permeate fluxes in reverse osmosis (RO) systems. The model is first validated by predicting permeate fluxes for a set of benchtop crossflow experiments subject to a range of feed flow rates and compositions, under fouling and non-fouling conditions. Results compare favorably with measured data that show that solutions with similar total dissolved solids concentrations but different compositions result in different permeate fluxes. The model is then applied to predict permeate fluxes from the desalination of produced waters using a commercial spiral wound RO module. For NaCl-dominant brines, at total dissolved salt concentrations (TDS) below about 70 g/L, permeate fluxes are inversely proportional to water mole fraction as the latter is a reasonable approximation of water activity (i.e. ideal mixing). In the case of Ca–Cl-, Na–CO3- and Na–SO4-dominant brines below about 70 g/L TDS, this relationship does not hold as well and tends to overpredict osmotic pressure and thus underpredict permeate fluxes. However, the opposite becomes true at higher TDS values for typical produced waters. The scaling potential of these waters is also computed by allowing the precipitation of minerals above their saturation limit on the RO membrane. This work demonstrates how reactive transport models developed for the analysis of waters from geological systems can be extended to improve process design, optimization, and control in desalination systems from produced waters and beyond.

Molins, Sergi↗

Transport of solar flare protons: Comparison of a new analytic model with spacecraft measurements

An analytic solution was obtained to the complete Fokker-Planck equation including the effects of convection, interplanetary deceleration and acceleration, corotation, and anisotropic diffusion. The solution yields a time to maximum for the particle flux of about 10 h and an exponential decay time of about 5 h. Several solar flare particle events were observed with the solar and galactic cosmic ray experiment on OGO-6. Comparisons of the calculated time dependence of the fluxes with these observations of 1 to 70 MeV protons show that the model adequately describes both the rise and decay times.

Lupton, J. E.↗

Bubble migration under the combined action of buoyancy and thermocapillarity

The migration of a gas bubble under the combined action of buoyancy and a downward temperature gradient is analyzed. Inertial effects are considered negligible, but allowance is made for convective transport of energy in the model. Results from a numerical solution of the governing equations are presented and discussed.

Merritt, Randy M.↗

LAVA Simulations for the AIAA Sonic Boom Prediction Workshop

Computational simulations using the Launch Ascent and Vehicle Aerodynamics (LAVA) framework are presented for the First AIAA Sonic Boom Prediction Workshop test cases. The framework is utilized with both structured overset and unstructured meshing approaches. The three workshop test cases include an axisymmetric body, a Delta Wing-Body model, and a complete low-boom supersonic transport concept. Solution sensitivity to mesh type and sizing, and several numerical convective flux discretization choices are presented and discussed. Favorable comparison between the computational simulations and experimental data of nearand mid-field pressure signatures were obtained.

Simulations↗

A Scalable Multi-Modal Framework for High-Fidelity Distributed Human Mobility Simulations

The development of data-driven models for human mobility in urban settings requires access to substantial and diverse real-world data. However, existing historical data often presents challenges such as limited volume, variety, and veracity, as well as missing data and privacy preservation concerns. Also, urban mobility modeling is inherently time-variant, complex, and multi-modal, encompassing everything from individual walking and running to private road travel and large-scale public transportation. These challenges call for innovative solutions to overcome data limitations and compute needs to model mobility behaviors accurately. To address these challenges, we propose a distributed, co-simulation-based architecture DURMOSim that integrates real-world data with scalable, high-fidelity simulations, demonstrating distributed co-simulation feasibility with existing mobility models. DURMOSim underpins a modular integration that would enable using any available mobility simulators for greater extensibility and scalability in performing various urban scenarios. In this paper, we present the design, implementation, and performance evaluation of DURMOSim, highlighting its capability to model population-scale mobility patterns. Our initial results show its ability to dynamically synchronize multiple simulation models at runtime with negligible computational overhead. We believe DURMOSim could be a robust tool for advancing urban mobility research and intelligent transportation systems.

Yoginath, Srikanth [ORNL] (ORCID:0000000184236050)↗

Coupled Monte Carlo Probability Density Function/ SPRAY/CFD Code Developed for Modeling Gas-Turbine Combustor Flows

The success of any solution methodology for studying gas-turbine combustor flows depends a great deal on how well it can model various complex, rate-controlling processes associated with turbulent transport, mixing, chemical kinetics, evaporation and spreading rates of the spray, convective and radiative heat transfer, and other phenomena. These phenomena often strongly interact with each other at disparate time and length scales. In particular, turbulence plays an important role in determining the rates of mass and heat transfer, chemical reactions, and evaporation in many practical combustion devices. Turbulence manifests its influence in a diffusion flame in several forms depending on how turbulence interacts with various flame scales. These forms range from the so-called wrinkled, or stretched, flamelets regime, to the distributed combustion regime. Conventional turbulence closure models have difficulty in treating highly nonlinear reaction rates. A solution procedure based on the joint composition probability density function (PDF) approach holds the promise of modeling various important combustion phenomena relevant to practical combustion devices such as extinction, blowoff limits, and emissions predictions because it can handle the nonlinear chemical reaction rates without any approximation. In this approach, mean and turbulence gas-phase velocity fields are determined from a standard turbulence model; the joint composition field of species and enthalpy are determined from the solution of a modeled PDF transport equation; and a Lagrangian-based dilute spray model is used for the liquid-phase representation with appropriate consideration of the exchanges of mass, momentum, and energy between the two phases. The PDF transport equation is solved by a Monte Carlo method, and existing state-of-the-art numerical representations are used to solve the mean gasphase velocity and turbulence fields together with the liquid-phase equations. The joint composition PDF approach was extended in our previous work to the study of compressible reacting flows. The application of this method to several supersonic diffusion flames associated with scramjet combustor flow fields provided favorable comparisons with the available experimental data. A further extension of this approach to spray flames, three-dimensional computations, and parallel computing was reported in a recent paper. The recently developed PDF/SPRAY/computational fluid dynamics (CFD) module combines the novelty of the joint composition PDF approach with the ability to run on parallel architectures. This algorithm was implemented on the NASA Lewis Research Center's Cray T3D, a massively parallel computer with an aggregate of 64 processor elements. The calculation procedure was applied to predict the flow properties of both open and confined swirl-stabilized spray flames.

Source record↗

Iterative solution of the multistream electron transport equation. I - Comparison with laboratory beam injection experiments

The Neumann iteration method presently used for solving the electron transport equation in which energy, attitude, and pitch angle are independent variables is fast, and can compute numerical point-response-function solutions of the electron transport equation. Because both the inelastic cross sections and angular elastic cross sections of the model are empirically based, the solutions obtained represent a test of compatibility between various sets of cross sections and energy deposition measurements. The use of a numerical quadrature based on analytic phase function forms yields accurate phase function integrals at low computational cost.

Porter, H. S.↗

Diffusional aspects of the high-temperature oxidation of protective coatings

The role of diffusional transport associated with the high-temperature oxidation of coatings is examined, with special attention given to the low-pressure plasma spraying MCrAl-type overlay coatings and similar Ni-base alloys which form protective AlO3 scales. The use of diffusional analysis to predict the minimum solute concentration necessary to form and grow a solute oxide scale is illustrated. Modeling procedures designed to simulate the diffusional transport in coatings and substrates are presented to show their use in understanding coating degradation, predicting the protective life of a coating, and evaluating various coating parameters to guide coating development.

Nesbitt, J. A.↗

BioRT‐HBV 1.0: A Biogeochemical Reactive Transport Model at the Watershed Scale

Abstract Reactive Transport Models (RTMs) are essential tools for understanding and predicting intertwined ecohydrological and biogeochemical processes on land and in rivers. While traditional RTMs have focused primarily on subsurface processes, recent watershed‐scale RTMs have integrated ecohydrological and biogeochemical interactions between surface and subsurface. These emergent, watershed‐scale RTMs are often spatially explicit and require extensive data, computational power, and computational expertise. There is however a pressing need to create parsimonious models that require minimal data and are accessible to scientists with limited computational background. To that end, we have developed BioRT‐HBV 1.0, a watershed‐scale, hydro‐biogeochemical RTM that builds upon the widely used, bucket‐type HBV model known for its simplicity and minimal data requirements. BioRT‐HBV uses the conceptual structure and hydrology output of HBV to simulate processes including advective solute transport and biogeochemical reactions that depend on reaction thermodynamics and kinetics. These reactions include, for example, chemical weathering, soil respiration, and nutrient transformation. The model uses time series of weather (air temperature, precipitation, and potential evapotranspiration) and initial biogeochemical conditions of subsurface water, soils, and rocks as input, and output times series of reaction rates and solute concentrations in subsurface waters and rivers. This paper presents the model structure and governing equations and demonstrates its utility with examples simulating carbon and nitrogen processes in a headwater catchment. As shown in the examples, BioRT‐HBV can be used to illuminate the dynamics of biogeochemical reactions in the invisible, arduous‐to‐measure subsurface, and their influence on the observed stream or river chemistry and solute export. With its parsimonious structure and easy‐to‐use graphical user interface, BioRT‐HBV can be a useful research tool for users without in‐depth computational training. It can additionally serve as an educational tool that promotes pollination of ideas across disciplines and foster a diverse, equal, and inclusive user community.

Sadayappan, Kayalvizhi↗