Performance of an electrochemical device for simultaneous carbon dioxide removal and oxygen generation.
Continuous flow, solid state electrochemical device for simultaneous carbon dioxide removal and oxygen generation
SOLID STATE DEVICE↗
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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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Unsupervised Learning Based Interaction Force Model for Nonspherical Particles in Incompressible Flows
This project provides a neural network-based interaction force model for gas-solid flows from low to intermediate Reynolds numbers and concentration, which can be linked to MFiX-DEM. We have constructed a database of the interaction force between the irregular-shaped particles using a spherical harmonic method and the fluid phase based on the particle-resolved direct numerical simulation (PR-DNS) with immersed boundary-based gas kinetic scheme. Unsupervised learning method, i.e., variational auto-encoder (VAE) has been applied to extract the primitive shape factors determining the drag force, lifting forces, and torque. The interaction force model has been trained and validated with a simple but effective multi-layer feed-forward neural network: multi-layer perceptron (MLP), which will be concatenated after the encoder of the previously trained VAE for geometry feature extraction for single, irregular particles. We have trained transpose convolutional neural networks with the PR-DNS data to predict the velocity and pressure gradient of the single particle systems and utilized them to calculate drag force of multi-particle systems. This model can provide high computational efficiency because it does not require collecting multiparticle system data from PR-DNS.
99 GENERAL AND MISCELLANEOUS↗
A machine learning-based interaction force model for non-spherical and irregular particles in low Reynolds number incompressible flows
In this study, interaction force of non-spherical particles in low Reynolds number gas-solid flow is investigated by neural network approaches. An artificial neural network (ANN) model is developed to correlate the non-spherical particle shape and the flow conditions with the interaction force. To define the particle shape, spherical harmonic expansion is applied. Furthermore, variational autoencoder model is then used to extract latent geometric features. The latent vector is utilized as an input with the Reynolds number for the ANN. The interaction force data, which is used as output data of the ANN, is obtained by particle resolved direct numerical simulation for 5200 non-spherical particles. The proposed model enables unsupervised extraction for non-spherical particle shapes and accurate predictions on the interaction force without heavy computation. This study provides the model that can explain complicated shapes of particles and be applied to a large scale, computational fluid dynamics simulation.
01 COAL, LIGNITE, AND PEAT↗
Slush hydrogen flow characteristics and solid fraction upgrading.
Liquid solid mixtures of parahydrogen flow characteristics in pipe, globe valve, orifices and venturi, determining pressure loss
Ludtke, P. R.↗
A continuum framework for coupled solid deformation–fluid flow through anisotropic elastoplastic porous media
We present a continuum framework for coupled solid deformation–fluid flow in anisotropic elastoplastic porous media. A thermodynamic formulation of the coupled processes gives rise to an anisotropic Biot tensor that is a function of drained elastic tangent moduli tensor of the solid skeleton and the intrinsic bulk modulus of the solid constituent. Two effective stress measures emerge from the formulation, namely, σ', which is energy-conjugate to the elastic strain, and σ'', which is energy-conjugate to the plastic strain. For the special case of transverse isotropy that is commonly encountered in natural rocks, the Biot tensor can be expressed in terms of its normal and tangential components to the bedding plane, along with a microstructure tensor. Apart from its thermodynamic consistency, an advantage of this new formulation is that standard mixed finite element formulation can be employed to discretize the domain and solve initial boundary-value problems. We conduct plane strain simulations of coupled solid deformation–fluid flow in a transversely isotropic porous medium to demonstrate the impacts of material anisotropy, stress history, and the Biot tensor on the system response.
42 ENGINEERING↗
Solid rocket booster internal flow analysis by highly accurate adaptive computational methods
The primary objective of this project was to develop an adaptive finite element flow solver for simulating internal flows in the solid rocket booster. Described here is a unique flow simulator code for analyzing highly complex flow phenomena in the solid rocket booster. New methodologies and features incorporated into this analysis tool are described.
Huang, C. Y.↗
Multiresolution GPC-Structured Control of a Single-Loop Cold-Flow Chemical Looping Testbed
Chemical looping is a near-zero emission process for generating power from coal. It is based on a multi-phase gas-solid flow and has extremely challenging nonlinear, multi-scale dynamics with jumps, producing large dynamic model uncertainty, which renders traditional robust control techniques, such as linear parameter varying H ∞ design, largely inapplicable. This process complexity is addressed in the present work through the temporal and the spatiotemporal multiresolution modeling along with the corresponding model-based control laws. Namely, the nonlinear autoregressive with exogenous input model structure, nonlinear in the wavelet basis, but linear in parameters, is used to identify the dominant temporal chemical looping process dynamics. The control inputs and the wavelet model parameters are calculated by optimizing a quadratic cost function using a gradient descent method. The respective identification and tracking error convergence of the proposed self-tuning identification and control schemes, the latter using the unconstrained generalized predictive control structure, is separately ascertained through the Lyapunov stability theorem. The rate constraint on the control signal in the temporal control law is then imposed and the control topology is augmented by an additional control loop with self-tuning deadbeat controller which uses the spatiotemporal wavelet riser dynamics representation. The novelty of this work is three-fold: (1) developing the self-tuning controller design methodology that consists in embedding the real-time tunable temporal highly nonlinear, but linearly parametrizable, multiresolution system representations into the classical rate-constrained generalized predictive quadratic optimal control structure, (2) augmenting the temporal multiresolution loop by a more complex spatiotemporal multiresolution self-tuning deadbeat control loop, and (3) demonstrating the effectiveness of the proposed methodology in producing fast recursive real-time algorithms for controlling highly uncertain nonlinear multiscale processes. The latter is shown through the data from the implemented temporal and augmented spatiotemporal solutions of a difficult chemical looping cold flow tracking control problem.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Solid propellant rocket motor
The characteristics of a solid propellant rocket engine with a controlled rate of thrust buildup to a desired thrust level are discussed. The engine uses a regressive burning controlled flow solid propellant igniter and a progressive burning main solid propellant charge. The igniter is capable of operating in a vacuum and sustains the burning of the propellant below its normal combustion limit until the burning propellant surface and combustion chamber pressure have increased sufficiently to provide a stable chamber pressure.
Dowler, W. L.↗
Beyond conventional batteries: a review on semi-solid and redox targeting flow batteries-LiFePO{sub 4} as a case study.
Clean and sustainable energy is becoming increasingly crucial to tackle the current energy crisis. However, the intermittent nature of renewable energy sources presents a challenge for their effective implementation. Redox flow batteries (RFBs) have emerged as a promising solution to this problem, as they can help enhance the stability of grid networks and promote the use of renewable energy sources. RFBs are highly modular and scalable systems that can be customized to meet the power and energy requirements of different renewable energy plants. Moreover, they offer several advantages over conventional battery technologies, including cost and safety concerns. However, conventional RFBs have limited energy densities due to the low solubility of their active species in electrolyte. To overcome this limitation, semi-solid (SSRFBs) and redox targeting (RTFBs) flow batteries have been proposed. These systems feature high concentrations of active species and impressive energy densities, making them highly attractive for renewable energy applications. LiFePO4 (LFP) is a highly promising active material for semi-solid and targeting flow batteries. One of the key advantages of LFP is its low raw materials cost, as it is composed of Earth-abundant elements such as iron and phosphorus. This makes it an attractive option for large-scale battery production. The recent developments in SSRFBs and RTFBs using LFP as catholyte hold great promise for the future of sustainable energy storage. The combination of LFP's low cost, safety, durability, and high energy density with the modularity and scalability of flow battery systems make for a compelling solution to the challenges of intermittent renewable energy sources. Ongoing research and development in this area will likely yield even further improvements in the performance and efficiency of LFP-based flow batteries, opening exciting new possibilities for sustainable energy storage.
El Halya, Nabil↗
Navier-Stokes analysis of solid propellant rocket motor internal flows
A multidimensional implicit Navier-Stokes analysis that uses numerical solution of the ensemble-averaged Navier-Stokes equations in a nonorthogonal, body-fitted, cylindrical coordinate system has been applied to the simulation of the steady mean flow in solid propellant rocket motor chambers. The calculation procedure incorporates a two-equation (k-epsilon) turbulence model and utilizes a consistently split, linearized block-implicit algorithm for numerical solution of the governing equations. The code was validated by comparing computed results with the experimental data obtained in cylindrical-port cold-flow tests. The agreement between the computed and experimentally measured mean axial velocities is excellent. The axial location of transition to turbulent flow predicted by the two-equation (k-epsilon) turbulence model used in the computations also agrees well with the experimental data. Computations performed to simulate the axisymmetric flowfield in the vicinity of the aft field joint in the Space Shuttle solid rocket motor using 14,725 grid points show the presence of a region of reversed axial flow near the downstream edge of the slot.
Sabnis, J. S.↗
Thermochemical reduction modeling in a high-temperature moving-bed reactor for energy storage: 1D model
The design of robust and efficient high-temperature thermochemical reactors and determination of operating conditions are critical steps toward enabling high-efficiency long-duration solar energy storage. This work presents a computational model for the thermal reduction of a metal oxide material (Mg-Mn-O) up to 1450 °C and the coupled complex transport phenomena in a novel tubular thermal reactor design that features the capability for a high extent-of-reduction (high energy storage density) and inherent heat recuperation. A one-dimensional model coupling counter-current gas–solid flow, two-phase heat transfer, thermochemical redox reactions, and species transport in a moving-bed reactor is developed. Simplified versions of the model are validated with published results in the literature for packed beds with both inert and reactive particles; the fully coupled model is also validated with experimental measurements of a moving-bed reactor in terms of local temperatures and oxygen release at the exit. Detailed comparisons on the effects of different boundary conditions in the reaction zone (prescribed wall temperature vs. heat flux conditions) and formulations based on a simple uniform flow assumption vs. plug flow using Ergun equation for gas flow are investigated. The results are compared with experimental measurements, and for all cases, the energy flow components in the reactor system and the thermal to chemical conversion efficiency and overall system efficiency are computed. Finally, the predicted high thermal-to-chemical efficiency ~95% and system efficiency ~30% agree with experimental measurements.
25 ENERGY STORAGE↗
Towards chemical equilibrium in thermochemical water splitting. Part 1: Thermal reduction
The efficiency of many processes strongly depends on their thermodynamic reversibility, i.e., proximity to equilibrium throughout the process. In thermochemical cycles for water and/or carbon dioxide splitting, thermochemical air separation, and thermochemical energy storage, operating near equilibrium means that the oxygen chemical potential of the solid and gas phases must not differ significantly. Herein we show that approaching this ideal is possible in thermal reduction only if the reaction step occurs at a specific, reaction coordinate- and material-dependent temperature. The resulting thermal reduction temperature profile also depends on the ratio of gas and solid flows.
08 HYDROGEN↗
Machine Learning-Enhanced Multiphase CFD for Carbon Capture Modeling Run Data
Repository for the data generated as part of the 2023-2024 ALCC project "Machine Learning-Enhanced Multiphase CFD for Carbon Capture Modeling." The data was generated with MFIX-Exa's CFD-DEM model. The problem of interest is gravity driven, particle-laden, gas-solid flow in a triply-periodic domain of length 2048 particle diameters with an aspect ratio of 4. The mean particle concentration ranges from 1% to 40% and the Archimedes number ranges from 18 to 90. The particle-to-fluid density ratio, particle-particle restitution and friction coefficients and domain aspect ratio are held constant at values of 1000, 0.9, 0.25 and 4, respectively. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231 using NERSC award ALCC-ERCAP0025948.
AMReX↗
Design and Technoeconomic Analysis of High-Temperature Particle Conveyance Components for a 100 MW e Concentrating Solar Power Plant
Levelized costs of electricity (LCOE) approaching the U.S. Department of Energy Solar Energy Technologies Office 2030 goal of 0.05 $/kWh may be achievable using Brayton power cycles that use supercritical CO2 as the working fluid and flowing solid particles with temperatures >700° C as the heat transfer media. The handling and conveyance of bulk solid particles at these temperatures in an insulated environment is a critical technical challenge that must be solved for this approach to be used. A design study was conducted at the National Solar Thermal Test Facility (NSTTF) at Sandia National Laboratories in Albuquerque, NM, with the objective of identifying the technical readiness level, performance limits, capital and O&M costs, and expected thermal losses of particle handling and conveyance components in a particle-based CSP plant. Key findings indicated that chutes can be a low-cost option for particle handling but uncertainties in tower costs make it difficult to know whether they can be cost effective in areas above the receiver if tower heights must then be increased. Skips and high temperature particle conveyance technology are available for moving particles up to 640° C. This limits the use of mechanical conveyance above the heat exchanger and suggests vertical integration of the hot storage bin and heat exchanger to facilitate direct gravity fed handling of particles.
14 SOLAR ENERGY↗
Granular Temperature Modeling with Large-Scale CFD-DEM Data
The granular temperature is a measure of solids-phase fluctuating kinetic energy in particle-laden gas-solid flows. This report focuses on reduced-order models of granular temperature in triply-periodic cluster induced turbulent flow. The granular temperature data was generated by post-processing large-scale CFD-DEM simulations that were carried out as part of an ALCC awarded study. The algebraic model of Tang et al, originally fit to DNS data, was found to be amenable to the present data. The results of several regression analyses are presented building on the original expression. This work was performed in part through the National Nuclear Security Administration (NNSA) Minority Serving Institutions Internship Program (MSIIP).
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Developing Drag Models for Non-Spherical Particles through Machine Learning
The overarching goal of this project is to produce comprehensive experimental and numerical datasets for gas-solid flows in well-controlled settings to understand the aerodynamic drag of non-spherical particles in the dense regime. The datasets and the gained knowledge will be utilized to train deep neural networks in TensorFlow to formulate a general drag model for use directly in NETL MFiX-DEM module in order to help to advance the accuracy and prediction fidelity of the computational tools that will be used in designing and optimizing fluidized beds and chemical looping reactors.
42 ENGINEERING↗
The role of particle collisions in pneumatic transport
A model of dilute gas-solid flow in vertical risers is developed in which the particle phase is treated as a granular material, the balance equations for rapid granular flow are modified to incorporate the drag force from the gas, and boundary conditions, based on collisional exchanges of momentum and energy at the wall, are employed. In this model, it is assumed that the particle fluctuations are determined by inter-particle collisions only and that the turbulence of the gas is unaffected by the presence of the particles. The model is developed in the context of, but not limited to, steady, fully developed flow. A numerical solution of the resulting governing equations provides concentration profiles generally observed in dilute pneumatic flow, velocity profiles in good agreement with the measurements of Tsuji, et al. (1984), and an explanation for the enhancement of turbulence that they observed.
Mastorakos, E.↗
An Experimental Study of the Flow Emerging from Porous Walls
The fluid mechanics of air flow exiting from porous materials is investigated. Porous walls with filter ratings differing by about three orders of magnitude are studied. The flow behavior is investigated for its spatial and temporal stability. The measurements show that coalescence effects cause jet development which gives rise to a stable, spatial velocity non-uniformity termed pseudo-turbulence. Beyond a critical mean velocity, the pseudo-turbulence shows a leveling trend and the flow exhibits jets whose dimensions are independent of wall porosity and provide a unique length scale for this type of flow field (approx. 1 mm). A correlation is developed to predict the onset of fully developed jets. The impact of using porous wall materials in cold flow solid rocket motor testing is addressed.
Ramachandran, N.↗