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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Solar Engineering of Thermal Processes, Photovoltaics and Wind, Fifth Edition

The updated Fifth Edition of Solar Engineering of Thermal Processes, Photovoltaics and Wind contains the fundamentals of solar energy and explains how we get energy from the sun. The authors - noted experts on the topic - provide an introduction to the technologies that harvest, store, and deliver solar energy, such as photovoltaics, solar heaters, and cells. The book also explores the applications of solar technologies and shows how they are applied in various sectors of the marketplace.

14 SOLAR ENERGY↗
DOE OSTI2024

Mechanical and Electrochemical Implications of Drying Temperature on Lithium‐Ion Battery Electrodes

Abstract Lithium‐ion battery (LIB) electrodes are typically produced with n‐methyl‐2‐pyrrolidone, a toxic solvent that is a known carcinogen and reproductive hazard. Accordingly, aqueous processing has been an expanding area of research interest in the field of LIB manufacturing. Although aqueous processing has been widely successful in anode processing, serious challenges remain in processing the cathode. In this work, the drying mechanics of cathode processed with both solvents is investigated though implementation of a chemical‐engineering‐based model to better understand the utilization of heat provided by experimentally determining the heat and mass transfer coefficients. Electrochemical performance is also evaluated to determine the impact of drying temperature on cycling performance. Binder distribution is determined via various methods to confirm differences in binder homogeneity as a function of both solvent and drying temperature. Identified is the large difference in the efficiency in which the heat is used as well as an ideal drying temperature for both aqueous and non‐aqueous processed cathodes. Also identified is the increased sensitivity to processing temperature for aqueous processed electrodes compared to non‐aqueous processed counterparts, pointing to the possibility of tuned drying regimes which would capitalize on the potential cost savings of aqueous processing for cathodes.

25 ENERGY STORAGE↗
DOE OSTI2024

Anomaly Detection in Materials Digital Twins with Multiscale ICME for Additive Manufacturing

Detecting anomaly in fatigue and fracture experimental materials science is an interesting yet challenging topic. The reasons are threefold. First, the anomalous microstructure feature that gives rise to structural failure is small, sometimes in the order of 10 -7 of the interrogated volume. This, in turn, results in a highly imbalanced classification problem in machine learning (ML). Second, the consequence is high, in the sense that the test specimen is destructed in such case. Third, the convolution between microstructure stochasticity and the small probability of void nucleation, growth, and coalescence makes failure and fracture a hard-to-predict and challenging problem in materials science due to its irreproducibility, even experimentally. In this paper, we developed a materials digital twin and applied anomaly detection methods to detect voids and anomaly in additive manufacturing (AM). The materials digital twin is driven by two integrated computational materials engineering (ICME) models, which are kinetic Monte Carlo (kMC) and crystal plasticity finite element method (CPFEM). In conclusion, we demonstrated that by using anomaly detection, it is possible to detect voids and other defects in materials digital twin, which paves way for future research in integrating materials digital twin with its physical counterpart.

ICME↗
DOE OSTI2021

Techno-economic and life-cycle assessment of fuel production from mixotrophic Galdieria sulphuraria microalgae on hydrolysate

Outdoor photoautotrophic algal growth is limited by light attenuation and attendant respiratory CO 2 losses during dark periods, limiting its productivity potential and carbon use efficiency. Developing a system that leverages mixotrophic growth (combining the benefits of both heterotrophic and photoautotrophic growth) has the potential to dramatically improve the total productivity and economics of the system. However, it is unknown if the productivity gains offset the added costs of outdoor mixotrophic cultivation using cellulosic hydrolysate as the feedstock. In this study, corn stover-derived cellulosic sugars were evaluated as the mixotrophic organic carbon source for the cultivation of Galdieria sulphuraria, which can metabolize both glucose and xylose from corn stover hydrolysate. A techno-economic analysis (TEA) and a life-cycle assessment (LCA) were conducted based on a detailed engineering process model for both glass helical photobioreactor and covered pond cultivation platforms, coupled with downstream conversion and upgrading to renewable diesel through hydrothermal liquefaction. Results show the minimum biomass selling price for cultivation in the photobioreactor design assuming a productivity of 1.575 kg m -3 day -1 and a substrate yield of 0.57 g g -1 is $2869 per dry metric ton. The costs are dramatically reduced in the covered pond design which assumes a productivity of 0.8 kg m -3 day -1 and a substrate yield of 0.7 g g -1 , 921 dollars per dry metric ton. Expanding the system boundary to include downstream processing results in a minimum fuel selling price of 8.24 dollars and 3.32 dollars dm 3 GE -1 for the photobioreactor and covered pond systems, respectively. Finally, life-cycle results demonstrate a global warming potential of 339 and 9.1 gCO 2 -eq. MJ -1 on a well-to-wheels basis and a net energy ratio of 2.21 and 0.25 MJ MJ -1 for the photobioreactor and covered pond systems, respectively. Discussion focuses on a required co-product selling price as a function of biomass diversion to meet economic parity with conventional fuels.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Numerical analysis of soot emissions from gasoline-ethanol and gasoline-butanol blends under gasoline compression ignition conditions

In the present work, computational fluid dynamics (CFD) simulations of a single-cylinder gasoline compression ignition (GCI) engine were performed to investigate the impact of blending two biofuels, ethanol and n-butanol, with gasoline on the trade-off between combustion phasing and soot emissions under low load conditions. Here, in order to represent market gasoline (RD5-87), a four-component toluene primary reference fuel (TPRF) + ethanol (ETPRF) surrogate (with 20% ethanol by mole; E20) was formulated using a neural network based octane predictor such that the surrogate had the same ethanol content, Research Octane Number (RON) and Octane Sensitivity (S). In addition, a novel skeletal kinetic mechanism for ETPRF and TPRF + n-butanol (BTPRF) blends, incorporating polycyclic aromatic hydrocarbon (PAH) chemistry, was developed. A three-dimensional (3D) engine CFD formulation employing the skeletal mechanism, adaptive mesh refinement (AMR), finite-rate chemistry approach, and hybrid method of moments (HMOM) was adopted to capture the in-cylinder combustion phenomena and soot emissions. The engine CFD model was validated against RD5-87 experimental data for a broad range of start-of-injection (SOI) timings (-21/-27/-36/-45 crank angle degrees (CAD) after top-dead center (aTDC)), with respect to in-cylinder pressure, heat release rate, combustion phasing, and soot emissions. The closed-cycle simulation results were analyzed to elucidate the non-monotonic trend of soot emissions versus SOI timing: SOI-36 > SOI-45 > SOI-21 > SOI-27. Thereafter, the validated CFD model was employed to simulate the combustion of a gasoline-ethanol blend with 45% (by mole) ethanol (E45) and a gasoline-butanol blend with 45% (by mole) n-butanol (B45) under the same operating conditions to study the effects of fuel composition and SOI timing on combustion phasing and soot emissions. The sooting propensity followed the trend: B45 > E20 > E45 at all SOI timings. Overall, it was observed that the autoignition propensity was primarily related to fuel chemistry. On the other hand, sooting propensity showed strong coupling with both fuel chemistry and physical properties, with greater impact of fuel physical properties at advanced SOI timings.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Development, validation, and verification of multi-pass thermo-mechanical welding simulations using the open-source MOOSE framework: NeT TG4 benchmark weldment

This study develops and validates a sequentially coupled thermo-mechanical welding simulation for the three-pass 316L stainless steel NeT TG4 benchmark weldment using the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) and the Nuclear Engineering Material model Library (NEML). A diffused ellipsoidal heat source was calibrated against thermocouple data and weld macrographs to accurately model the fusion zone geometry and transient thermal fields. Material hardening is represented using the Lemaitre-Chaboche mixed isotropic-kinematic hardening model, while four annealing models - no annealing, single-stage at 1050 °C and 1300 °C, and two-stage at 800 °C/1300 °C - were implemented to assess the impact of annealing models on the accuracy of the predicted welding-induced plasticity, distortions, and residual stresses. The predictions were validated against experimental measurements and benchmarked against results from commercial software, demonstrating that thermo-mechanical MOOSE welding simulations achieve comparable accuracy with enhanced computational efficiency. This work highlights the potential of using open-source finite element frameworks like MOOSE for advanced manufacturing simulations.

Ji, Wendy [Australian Nuclear Science and Technolo↗
DOE OSTI2024

Techno-economic and life cycle analysis of synthetic natural gas production from low-carbon H 2 and point-source or atmospheric CO 2 in the United States

Synthetic natural gas (SNG) is of great interest in reducing fossil energy consumption while maintaining compatibility with existing NG infrastructure and end-use applications equipment. SNG can be produced using clean H 2 generated from renewable or nuclear energy and CO 2 captured from stationary sources or the atmosphere. In this study, we develop an engineering process model of SNG production using Aspen Plus® and production scales reported by the industry. We examine the levelized cost and life cycle greenhouse gas (GHG) emissions of SNG production under various CO 2 supply scenarios. Considering the higher cost of H 2 transportation compared with CO 2 transportation, we assume that CO 2 feedstock is transported via pipeline to the H 2 production location, which is collocated with the SNG plant. We also evaluate the cost of CO 2 captured from the atmosphere, assuming the direct air capture process can occur near the SNG facility. Depending on the CO 2 supply chain, the levelized cost of SNG is estimated to be in the range of $\$45–76$ per million British thermal units (MMBtu) on a higher heating value (HHV) basis. The SNG production cost may be reduced to $\$27–57$/MMBtu-HHV by applying a tax credit available in the United States for low-carbon H 2 production (45V). With a lower electricity price of 3¢/kWh for water electrolysis and accounting for a 45V tax credit, the SNG cost reaches parity with the cost of fossil NG. Depending on the CO 2 supply chain, SNG can reduce life cycle GHG emissions by 52–88% compared with fossil NG.

03 NATURAL GAS↗
DOE OSTI2023

The cost of direct air capture and storage can be reduced via strategic deployment but is unlikely to fall below stated cost targets

Carbon dioxide removal (CDR) is necessary to minimize the impact of climate change by tackling hard-toabate sectors and historical emissions. Direct air capture and storage (DACS) is an important CDR technology, but it remains unclear when and how DACS can be economically viable. Here, we use a bottom-up engineering-economic model together with top-down technological learning projections to calculate plant-level cost trajectories for four DACS technologies. Our analysis demonstrates that the costs of these technologies can plateau by 2050 at around $\$$100-600 t-CO 2 -1 mainly via capital cost reduction through aggressive deployment, but still exceed the optimistic targets defined by countries such as the US (i.e., $\$$100 t-CO 2 -1 ). A further analysis of existing policy mechanisms indicates that strong, project-catered policy support will be required to create market opportunities, accelerate DACS scale-up and lower the costs further. Our work suggests that strategic DACS deployment and operation must be coupled with strong policies to minimise the cost of DACS and maximise the opportunity to make a planet-scale climate impact.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Design of a gas-solid-solid separator to remove ash from circulating fluidized bed reactors

Cyclones are one of the most common types of gas-solid separators used in circulating fluidized bed boilers. However, cyclones typically do not allow ash to leave the system through the cyclone exit, causing ash to build up in the fluidized bed and necessitating additional systems to remove ash that builds up in the bed. In this study, an alternative “disengager” gas-solid separator is proposed as a way of inherently separating small and large solids, resulting in a gas-solid-solid separation system where ash is allowed to leave the system along with gas while the desired fluidized bed material is retained. Unlike cyclones, which rely on centrifugal force to separate solids and gas, the disengager separates based on entrainment velocity of the particles. Upwards-flowing gas and particles strike a deflection plate and enter the disengaging chamber where particles with low terminal velocity such as ash fines flow with the gas, while larger particles such as sand fall to the bottom of the separator and are returned to the fluidized bed. In this study, several different proposed disengager configurations are simulated and compared to a typical cyclone using computational fluid dynamic (CFD) simulations. Furthermore, it was found that separation efficiency in the disengager is strongly influenced by the size of the deflection plate, rather than by the size of the unit itself. The predicted separation efficiency showed that compared to a cyclone, the disengager design allows significantly more ash to exit the system but retains a similar amount of desirable material. Additionally, the disengager was predicted to not suffer significantly more erosion that a cyclone.

42 ENGINEERING↗
DOE OSTI2022

Towards multi-fidelity deep learning of wind turbine wakes

We report engineering wake models that accurately predict wake in a computationally efficient manner are very important for tasks such as layout optimization and control of wind farms. In this paper, we explore an application of deep learning (DL) to learn the wake model from hierarchies of physics-based approaches ranging from analytical models to an approximate form of the Reynolds-averaged Navier-Stokes equations. We first illustrate the application of principal component analysis to obtain a lower-dimensional representation that allows a computationally tractable training and deployment of DL models. Then, the DL model is trained to learn the mapping from input parameter space to the principal components, which are then used to reconstruct the three-dimensional flow field. Additionally, we investigate a composite framework consisting of two neural networks to learn the correlation between low- and high-fidelity data with Gauss and curl models treated as proxies for low- and high-fidelity models, respectively. The prediction from both DL models matches well with the high-fidelity data with a maximum relative percentage error for the kinetic energy flux of <1%. This work opens up possibilities for data-efficient construction of surrogate models for wake prediction that can be used to study the influence of wind speed and yaw angles on wind farm power production.

17 WIND ENERGY↗
DOE OSTI2021

Efimov-like states and quantum funneling effects on synthetic hyperbolic surfaces

Engineering lattice models with tailored inter-site tunnelings and onsite energies could synthesize essentially arbitrary Riemannian surfaces with highly tunable local curvatures. Here, we point out that discrete synthetic Poincaré half-planes and Poincaré disks, which are created by lattices in flat planes, support infinitely degenerate eigenstates for any nonzero eigenenergies. Such Efimov-like states exhibit a discrete scaling symmetry and imply an unprecedented apparatus for studying quantum anomaly using hyperbolic surfaces. Furthermore, all eigenstates are exponentially localized in the hyperbolic coordinates, signifying the first example of quantum funneling effects in Hermitian systems. As such, any initial wave packet travels towards the edge of the Poincaré half-plane or its equivalent on the Poincaré disk, delivering an efficient scheme to harvest light and atoms in two dimensions. Furthermore, our findings unfold the intriguing properties of hyperbolic spaces and suggest that Efimov states may be regarded as a projection from a curved space with an extra dimension.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Techno-economic performances and life cycle greenhouse gas emissions of various ammonia production pathways including conventional, carbon-capturing, nuclear-powered, and renewable production

Ammonia (NH 3 ) is conventionally produced using fossil natural gas (NG) for hydrogen production through steam reformation and synthesis in the Haber–Bosch (HB) process. The global conventional ammonia production contributes more than 420 million tons of CO 2 emissions annually. Here, in this work, we investigated the techno-economics and well-to-plant-gate (WTG) greenhouse gas (GHG) emissions of conventional NG-based, carbon-capturing, nuclear-powered, and renewable ammonia production by developing an engineering process model for each. Carbon-capturing ammonia production refers to the NG-based ammonia production while capturing CO 2 and transporting it via pipelines for storage or utilization. Nuclear-powered and renewable ammonia production represents an alternative ammonia production through water electrolysis, air separation, and the HB process using carbon-free energy sources. Nuclear and renewable energy sources are assumed to be used for nuclear-powered and renewable ammonia production, respectively. Sensitivity analyses are performed for CO 2 pipeline transport distances, potential carbon capture tax credits, and clean H 2 production cost. Carbon-capturing ammonia production reduces WTG GHG emissions by 55–70% compared to conventional NG-based ammonia production methods. Nuclear-powered and renewable ammonia production almost eliminate GHG emissions since energy supply is either zero carbon or near-zero carbon. However, when $4.16–4.83 per kg is the cost assumed for clean H 2 production using state-of-the-art electrolysis technologies, the levelized costs of nuclear-powered and renewable ammonia are calculated to be $0.92–1.06 per kg NH 3 , which are approximately four times higher than the conventional NG-based ammonia production cost. The cost of CO 2 emission avoidance is estimated in the range of $266–318 per metric ton of CO 2 for nuclear-powered and renewable ammonia production. The clean H 2 production cost is the major contributor to the levelized costs of nuclear-powered and renewable ammonia production. A lower production cost, near $1 per kg H 2 , for clean H 2 is required for nuclear-powered and renewable ammonia production to be cost-competitive with conventional NG-based ammonia production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

High-Fidelity Simulation of the Light-to-Dense Stratification Transient in the HiRJET Facility

Density stratification in a large enclosure is a crucial phenomenon to heat transfer and sustainable passive heat removal of a sodium fast reactor during reactivity transients. However, engineering turbulence models were identified to have unsatisfactory performance in predicting propagation of a stratified front. Yet, the scarcity of high-resolution data for stratification hampers the development of models. To explor e applications of leveraging direct numerical simulation (DNS) data to support turbulence model development, this work conducted DNS using NekRS to study a long stratification transient in the High-Resolution Jet (HiRJET) experimental facility. Here, this work considers an experiment run where light fluid is injected into a tank containing a denser fluid with a relative density difference of 1.5%. Formation of the stratified layer is identified as impingement of the buoyant jet promoting mixing of the two fluids. Based on the transient statistics, transport of the concentration can be characterized by regions with dominating effects of turbulent mixing, buoyant dissipation, and molecular diffusion, respectively, as moving away from the elevation of jet impingement. Concentration near the stratified front also exhibits oscillation at Brunt-Väisälä frequency. Preliminary validation of the simulation showed encouraging agreement of the concentration distribution with the reference experiment.

buoyant mixing↗
DOE OSTI2022

3D ion gyro-orbit heat load predictions for NSTX-U

Abstract High power tokamaks operate with divertor heat loads capable of destroying the plasma facing components (PFCs). High fidelity heat load predictions are necessary to ascertain the PFC state for design and during operation. Typical heat flux calculations are 2D, time invariant, and assume that power flows directly along the magnetic field lines (the optical approximation). These assumptions neglect the complex 3D geometries employed to protect the PFCs, the time varying nature of the plasma and PFC thermal state, and the helical trajectories of ions with finite Larmor radii (the gyro-orbit approximation). An integrated software framework, the heat flux engineering analysis toolkit (HEAT), was developed to generate time varying optical heat loads applied to real engineering computer aided design (CAD) (Looby et al 2022 Fusion Sci. Technol. 78 10–27). Recently, an ion-gyro orbit module has been added to HEAT. This module calculates the helical trajectories of ions as they gyrate about the magnetic field lines using kinetic theory macro-particles to accelerate the calculation. First, the new gyro-orbit module will be presented. Next, a comparison to existing research is performed. Finally, an analysis of the gyro-orbit heat loads for NSTX-U is presented for diverted discharges using the engineering CAD models utilized for PFC fabrication. Including these gyro-orbit effects can enhance the PFC performance by ‘smearing’ out the magnetic shadows associated with the castellated fish-scaled geometry. Simultaneously, the helical trajectories can degrade performance when they load narrow regions on edges and corners with high heat fluxes. Analysis of the trade-offs between these competing effects is included, and regions for further investigation are identified.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗