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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 919 records · Page 51

Thermal bootstrap of matrix quantum mechanics

We implement a bootstrap method that combines stationary state conditions, thermal inequalities, and semidefinite relaxations of matrix logarithm in the ungauged one-matrix quantum mechanics, at finite rank N as well as in the large N limit, and determine finite temperature observables that interpolate between available analytic results in the low and high temperature limits respectively. We also obtain bootstrap bounds on thermal phase transition as well as preliminary results in the ungauged two-matrix quantum mechanics.

1/N Expansion↗

Contact pressure analysis to allow improved design for the clearing plate in a biomass comminution system

For biomass processing systems, feedstocks with small but equal sizes can improve flowability and thermochemical outputs. The Crumbler rotary shear system was designed to achieve such ideal feedstocks to reduce costs and energy throughout the biomass supply chain. Improving the wear resistance of major components in this system is important to decrease the cost. Accelerating the feedstock flow through the rotary shear machine plays an equivalent role of improving its efficiency. An analytical analysis and a finite-element analysis of the stationary clearing plate are presented in this work. Here, these tools are used to investigate the effect of contact surface curvature on the impact pressure. The optimized new clearing plate design is expected to improve the component’s lifetime and wood chips flowability. The field tests confirm that the trend of the new clearing plate design guided by FEA. The optimization method, model verification, and validation experience applied in this work can also be applied to other static components with similar simple contact wear problems.

09 BIOMASS FUELS↗

Control of Fractional Diffusion Problems via Dynamic Programming Equations

In this study, we explore the approximation of feedback control of integro-differential equations containing a fractional Laplacian term. To obtain feedback control for the state variable of this nonlocal equation, we use the Hamilton–Jacobi–Bellman equation. It is well known that this approach suffers from the curse of dimensionality, and to mitigate this problem we couple semi-Lagrangian schemes for the discretization of the dynamic programming principle with the use of Shepard approximation. This coupling enables approximation of high-dimensional problems. Numerical convergence toward the solution of the continuous problem is provided together with linear and nonlinear examples. The robustness of the method with respect to disturbances of the system is illustrated by comparisons with an open-loop control approach.

97 MATHEMATICS AND COMPUTING↗

I 2 S-LWR microchannel heat exchanger design and experimental validation

The Integral Inherently Safe Light Water Reactor (I 2 S-LWR) includes primary-to-secondary coolant heat exchangers located in the downcomer of the reactor pressure vessel. A microchannel heat exchanger (MCHX) configuration is selected to meet the limited available volume and high heat duty requirements. The design, modeling, and optimization of the liquid-liquid MCHX is outlined. In addition, the performance of a MCHX test section representative of the I 2 S-LWR MCHX design is validated experimentally. Experimental results show that heat transfer and pressure drop correlations developed for larger, macroscale channels lead to accurate predictions of performance. Additionally, this study shows that an MCHX can deliver the required heat duties within the available space and pressure drop constraints of the overall I2 S-LWR design.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Sizing ramping reserve using probabilistic solar forecasts: A data-driven method

Ramping products have been introduced or proposed in several U.S. power markets to mitigate the impact of load and renewable uncertainties on market efficiency and reliability. Current methods often rely on historical data to estimate the requirements of ramping products and fail to take into account the effects of the latest weather conditions and their uncertainties, which could lead to overly conservative or insufficient requirements. This study proposes a k-nearest-neighbor-based method to give weather-informed estimates of ramping needs based on short-term probabilistic solar irradiance forecasts. Forecasts from multiple sites are employed in conjunction with principal component analysis to derive numerical classifiers to characterize system-level weather conditions. In addition, we develop a data-driven method to optimize the model parameters in a rolling-forward manner. By using real-world data from the California Independent System Operator, we design two metrics to evaluate method performance: 1) frequency of shortage and 2) oversupply of ramping product. Our proposed method presents advantages in comparison with the baseline and a set of benchmark methods: without compromising system reliability, it reduces system ramping requirements by up to 25%, therefore improving both system reliability and economics.

14 SOLAR ENERGY↗

Reconstructing porous media using generative flow networks

One area of intense scientific interest for the study of sandstones, carbonates, and shale at the pore scale is the use of limited image and petrophysical data to generate multiple realizations of a rock’s pore structure. Such images aid efforts to quantify uncertainty in petrophysical properties, including porosity–permeability transforms. We develop and evaluate a deep learning-based method to synthesize porous media volumes using a so-called generative flow model trained on x-ray microscope images of rock texture and pore structure. These models are optimized on a log-likelihood objective and they synthesize large and realistic three-dimensional images. Further, we demonstrate the rapid generation of sandstone image volumes that display realism as gauged by quantitative comparison of topological features using Minkowski functionals of porosity, specific surface area, and the Euler–Poincaré characteristic (i.e., pore connectivity). We also evaluate the single-phase permeability using Navier–Stokes and lattice Boltzmann methods and show that transport properties of the generated samples match measured trends.

58 GEOSCIENCES↗

Jacobian-based model diagnostics and application to equation oriented modeling of a carbon capture system

It can be difficult to identify the specific variables or equations responsible for convergence issues in large mathematical programming models. The Institute for the Design of Advanced Energy Systems Integrated Platform (IDAES-IP) contains a tool to identify poorly scaled constraints and variables by searching for rows and columns of the Jacobian matrix with small L2-norms. A singular value decomposition is then performed to identify degenerate sets of equations and remaining scaling issues. Here, this work presents a flowsheet developed for post-combustion carbon capture using a monoethanolamine (MEA) solvent system as a case study. This work takes the reader through the entire process of model diagnostics and reformulation, from a basic introduction to the mathematics behind these model diagnostics to the reformulations necessary to make the model numerically robust, including a significantly modified enhancement factor model.

IDAES↗

Improving operational flexibility of integrated energy system with uncertain renewable generations considering thermal inertia of buildings

Insufficient flexibility in system operation caused by traditional "heat-set" operating modes of combined heat and power (CHP) units in winter heating periods is a key issue that limits renewable energy consumption. In order to reduce the curtailment of renewable energy resources through improving the operational flexibility, a novel optimal scheduling model based on chance-constrained programming (CCP), aiming at minimizing the lowest generation cost, is proposed for a small-scale integrated energy system (IES) with CHP units, thermal power units, renewable generations and representative auxiliary equipments. In this model, due to the uncertainties of renewable generations including wind turbines and photovoltaic units, the probabilistic spinning reserves are supplied in the form of chance-constrained; from the perspective of user experience, a heating load model is built with consideration of heat comfort and inertia in buildings. To solve the model, a solution approach based on sequence operation theory (SOT) is developed, where the original CCP-based scheduling model is tackled into a solvable mixed-integer linear programming (MILP) formulation by converting a chance constraint into its deterministic equivalence class, and thereby is solved via the CPLEX solver. We report the simulation results on the modified IEEE 30-bus system demonstrate that the presented method manages to improve operational flexibility of the IES with uncertain renewable generations by comprehensively leveraging thermal inertia of buildings and different kinds of auxiliary equipments, which provides a fundamental way for promoting renewable energy consumption.

30 DIRECT ENERGY CONVERSION↗

Using Thermodynamic Availability to Predict the Transitional Film Reynolds Number between the Droplet and Jet Modes in Falling Liquid between Horizontal Tubes

The objective of this paper is to propose and validate a model for predicting the transitional film Reynolds number between the droplet and jet modes of falling film flows. The proposed model relies on thermodynamic availability with no fitting to mode transition data. The model directly predicts the numerical values of the transitional film Reynolds numbers at different operating conditions. The results of the model are validated against 43 experimental data points from the literature, which cover 10 working fluids and a wide range of tube geometries. The accuracy of the proposed model in predicting the validation data is -on average- more than 20 % better than that of the widely used Re = a (Ga) b and Re = a (Ga) b (S/ξ) c models. The model also achieves low computation time (less than 30 seconds for the 43 validation data points). The model presented in this paper has the potential of integration with heat transfer, mass transfer, and pressure drop models for optimizing the design and operation of falling film heat and mass exchangers.

42 ENGINEERING↗

Screening and evaluation of biomass upgrading strategies for sustainable transportation fuel production with biomass-derived volatile fatty acids

Biomass conversion to fuels and chemicals is crucial to decarbonization, but choosing an advantageous upgrading pathway out of many options is challenging. Rigorously evaluating all candidate pathways (process simulation, product property testing) requires a prohibitive amount of research effort; even simple upgrading schemes have hundreds of possible permutations. We present a method enabling high-throughput screening by approximating upgrading unit operations and drop-in compatibility of products (e.g., fuel properties) and apply it to volatile fatty acid (VFA) conversion to liquid transportation fuels via a MATLAB script, VFA Upgrading to Liquid Transportation fUels Refinery Estimation (VULTURE). VULTURE selects upgrading configurations that maximize fuel blend bio-derived content. We validate VULTURE's approximations through surrogate fuel property testing and process simulation. Techno-economic and life cycle analyses suggest that VFA upgrading processes down-selected by VULTURE are profitable and have low carbon intensities, demonstrating the potential for the strategy to accelerate process development timelines at decreased costs.

09 BIOMASS FUELS↗

Electrochemical behavior of SnCl 2 and influence of Cu and Ni ions in molten LiCl−KCl−CaCl 2 eutectic

Reliable transport and thermodynamic data for multivalent ions in complex molten salts are scarce, limiting model fidelity for electrorefining and impurity control. Here, we report a comprehensive electrochemical characterization of SnCl₂ in LiCl–KCl–CaCl₂ (50.5–44.2–5.3 mol%) at 685 K, including the effects of Ni 2+ and Cu + impurities. Using cyclic voltammetry (CV), chronoamperometry (CA), and chronopotentiometry (CP), we quantified Sn 2+ and Ni 2+ diffusion with exceptional agreement across methods: Sn 2+ averaged (1.03 ± 0.10) × 10 −5 cm 2 s −1 , and Ni 2+ averaged (0.75 ± 0.19) × 10 −5 cm 2 s −1 . The tight confidence-interval overlap across CV, CA, and CP strengthens confidence in these values and is uncommon in molten chloride studies. Open-circuit-potential measurements provided standard apparent reduction potentials that closely match LiCl–KCl literature, indicating minimal shift with CaCl₂ present. The Sn 2+ /Sn couple behaves as a reversible two-electron soluble–insoluble process at 685 K; the Sn 4+ /Sn 2+ couple transitions to soluble–soluble behavior near 788 K, which may correlate with the decomposition of surface bound chlorostannates, though direct characterization remains to be established. In mixed systems, Cu+/Cu overlaps Sn 2+ /Sn, limiting Cusingle bondSn electroseparation, whereas the larger potential gap between Ni 2+ /Ni and Sn 2+ /Sn supports selective Ni removal. These internally consistent transport and thermodynamic data establish a validated basis for process modeling and optimization of Sn electrorefining and impurity management in LiCl–KCl–CaCl₂.

Berzins-Delahay↗

Near-field passive sensor for the monitoring of high-temperature oxidative corrosion of metals

This study reports on the development and testing of a passive wireless device designed to track temperature and corrosion behavior in SS304H stainless steel under elevated temperatures. The ANSYS HFSS software was utilized to model and optimize the design of an inductor-capacitor (LC) resonator passive wireless sensors fabricated using platinum designs printed onto an aluminum oxide support operating at frequencies between (50–190 MHz). The optimal LC wireless sensor designs were then fabricated using screen-printing and sintering methods. Here, the sensors were tested by placing the sensor onto polished SS304H flat substrates and heated to 900–1050 °C in air. Wireless acquisition of sensor data during heating, cooling, and isothermal stages was achieved through a Pt loop antenna connected to an RF signal generator and a network analyzer.

20 FOSSIL-FUELED POWER PLANTS↗

Effect of alloying on intrinsic ductility in WTaCrV high entropy alloys

Tungsten (W) exhibits desirable properties for extreme applications, such as the divertor in magnetic fusion reactors, but its practicality remains limited due to poor formability and insufficient irradiation resistance. In this work, we study the intrinsic ductility of body-centered cubic WTaCrV based high entropy alloys (HEAs), which are known to exhibit excellent irradiation resistance. The ductility evaluations are carried out using a criterion based on the competition between the critical stress intensity factors for emission (K Ie ) and cleavage (K Ic ) in the {110} slip planes and {110} crack planes, which are evaluated within the linear elastic fracture mechanics framework and computed using density functional theory. The results suggest that increasing the alloying concentrations of V and reducing the concentrations of W can significantly improve the ductility in these HEAs. The elastic anisotropy for these HEAs is analyzed using the Zener anisotropy ratio and its correlation with the concentration of W in the alloys is studied. Results indicate that these alloys tend to be fairly isotropic independently from the concentration of W in them. The computed data for the elastic constants of these HEAs is also compared against available experimental data. The results are in good agreement, validating the robustness and accuracy of the computational methods. Multiple phenomenological ductility metrics were also computed and analyzed against the analytical model. Some metrics, mainly the surrogate D parameter, show a good correlation with the Rice model. The potential of these empirical metrics to serve as surrogate screening models for optimizing the compositional space is also discussed.

Anisotropy↗

Experimental study on kinetic oxidation of graphite IG-110 by steam

Graphite is proposed for use in High-temperature Gas-cooled Reactors (HTGRs) as the fuel matrix, neutron moderator/reflector, and core structural material. One important property of nuclear grade graphite is their resistance to oxidation in high-temperature environment. Extensive investigation has been performed in the literature for graphite oxidation by air. However, available experimental data are still limited for graphite oxidation by steam under conditions comparable to a postulated steam ingress accident in HTGRs. In this study, the oxidation rate of graphite IG-110 by steam was measured at temperatures from 850 to 1100 °C with the steam partial pressure varying from 0.5 to 20.0 kPa and the hydrogen partial pressure varying from 0 to 2.0 kPa. Further analysis confirms the oxidation process in this present study is dominated by the chemical kinetics, which lends credit to the data for being used to develop numerical models. It was observed that the increase of the kinetic oxidation rate with the steam partial pressure tends to become less apparent if the steam partial pressure keeps increasing. In addition, it was found that the partitioning of hydrogen inhibits the graphite-steam reaction process even with the steam partial pressure up to 20.0 kPa. However, this inhibiting effect starts to become saturated when the hydrogen partial pressure exceeds 1.0 kPa. The oxidation rates were fitted to the conventional Langmuir-Hinshelwood (LH) and Boltzmann-enhanced Langmuir-Hinshelwood (BLH) models by a multivariable optimization algorithm. The BLH model exhibits a better accuracy than the LH model within the specified experimental conditions. The predicted oxidation rate using the BLH model shows a mean relative difference of about 24% with the maximum difference of about 55% when compared with our experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Intersections of Disadvantaged Communities and Renewable Energy Potential: Data Set and Analysis to Inform Equitable Investment Prioritization in the United States

Renewable energy development can bolster local economies through job creation, local tax revenues, and reduced energy costs; however, communities most in need of economic development and employment opportunities often see lower levels of renewable energy deployment. We sought to identify areas where disadvantaged community indicators and high generation potential from cost-effective renewable energy opportunities intersect and deployment could lead to economic development and job creation. This presentation will highlight several of our findings. This research and the associated county-level data set are intended to inform national- and state-level energy-related assistance programs, economic development efforts, and infrastructure programs seeking to prioritize investments in disadvantaged communities.

community energy planning↗