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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 415 records · Page 23

Unique nanotechnology converts carbon dioxide to valuable products

Carbon capture and management are increasing challenges associated with global warming. Current commercial-scale carbon dioxide (CO 2 ) capture technologies are associated with a heavy economic penalty – they require at least one-third of the plant’s steam and power to operate. The objective of this project was to develop and test an innovative nanotechnology that can utilize CO 2 , from coal-based power systems or other industrial sources, as the primary feedstock to produce commercially valuable products to potentially offset the cost of CO 2 capture. The scope of this project includes conversion of CO 2 to nanomaterials using two unique amino acids in synthetic flue gases and the completion of a process design and techno-economic and lifecycle analyses to demonstrate the economic feasibility and environmental impact of the developed technology. The International Energy Agency predicts that fossil fuels will continue to play a significant role in meeting global energy demand. The goal of the research is to lead to an affordable and transformational CO 2 capture and reuse technology that will reduce the release of CO 2 thereby reducing global climate variability and its enormous impact on our daily lives.

01 COAL, LIGNITE, AND PEAT↗

Using Residential and Office Building Archetypes for Energy Efficiency Building Solutions in an Urban Scale: A China Case Study

Building energy consumption accounts for 36% of the overall energy end use worldwide and is growing rapidly as developing countries continue to urbanize. Understanding the energy use at urban scale will lay the foundation for identification of energy efficiency opportunities to be deployed at speed. China has almost half of global new constructions and plays an important role in building suitability. However, an open source national building energy consumption database is not available in China. To provide data support for building energy consumptions, this paper used a simulation method to develop an urban building energy consumption database for a pilot city in Wuhan, China. First, residential, small, and large office building archetype energy models were created in EnergyPlus to represent typical building energy consumption in Wuhan. The baseline reference model simulation results were further validated using survey data from the literature. Second, stochastic simulations were conducted to consider different design parameters and occupants’ energy usage intensity scenarios, such as thermal properties of the building envelope, lighting power density, equipment power density, HVAC (heating, ventilation and air conditioning) schedule, etc. A building energy consumption database was generated for typical building archetypes. Third, data-driven regression analysis was conducted to support quick building energy consumption prediction using key high- level building information inputs. Finally, a web-based urban energy platform and an interface were developed to support further third-party application development. The research is expected to provide fast energy efficiency building design solutions for urban planning, new constructions as well as building retrofits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Impact of model predictive control-enabled home energy management on large-scale distribution systems with photovoltaics

Residential customers use more than one-quarter of the electricity in the world. Optimally managing home energy consumption is an effective way of easing the operational challenges facing the electric grid with increasing solar photovoltaics (PV). This paper studies the impact of the future proliferation of home energy management systems (HEMS) in the presence of PV on large-scale distribution systems. First, we present a stochastic HEMS model that minimizes residential customers' thermal discomfort and energy costs under uncertainty. The HEMS model schedules the optimal operations of residential appliances in the presence of PV within a mixed-integer linear programming-based model predictive control framework that links the proposed HEMS to a quasi-steady-state time-series simulation tool. Additionally, extensive simulations are conducted for a stand-alone residential home using two tariff structures and for 1977 homes on an 8,500-node distribution feeder. Simulation results quantify the impact of the future proliferation of HEMS on the large-scale distribution system with PV.

14 SOLAR ENERGY↗

Isospin symmetry holds beyond the proton drip line: First observation of excited states in 55Cu

Isospin symmetry, combined with shell-model description, has long been successful in reproducing nuclear structure and predicting mirror energy differences. However, these descriptions have been primarily limited to mirror nuclei with well-bound ground states. As one approaches the proton drip line, coupling to the continuum becomes important. Despite this, little is known about medium-mass nuclei at the drip line. Here we report the measurement of the excitation energies of several unbound states in a nucleus beyond the proton drip line, 55Cu, performed via γ-ray spectroscopy at the Radioactive Isotope Beam Factory (RIKEN). Several low-lying yrast states are observed to decay predominantly by γ-ray emission. In contrast, the state–predicted to be strongly populated in the one-proton knockout reaction–is notably absent, suggesting that it decays primarily via prompt proton emission. We show that even for such an unbound system, shell-model calculations based on a harmonic oscillator potential reproduce the observed mirror energy differences remarkably well in all the observed states. Based on this result, we propose that a general pattern might emerge where, in medium-mass systems at the proton drip line, the stronger Coulomb barrier together with the centrifugal barrier effectively confines the wave functions, so that the shell model is able to describe low-lying states, enabling accurate predictions of mirror energy differences between isobaric analogue states.

Pigliapoco, S [Dipartimento di Fisica e Astronomia↗

A satellite investigation of energy flux and inferred potential drop in auroral electron energy spectra

Because predicted relationship (epsilon directly varies with V squared) between auroral electron energy flux (epsilon) and the inferred acceleration potential drop (V) for accelerated Maxwellian distributions was favorably tested by other using sounding rocket data for the limiting case of eVE 1 (where Ec is the characteristic energy of the accelerated Maxwellian distribution) and for a single inverted-V observed by the Injun 5 satellite, data from Atmosphere D were used to extend these studies over the range .2 eV/Ec 5 and for a wide range of latitudes and local times on both the nightside and the dayside. Results show good agreement with the full accelerated Maxwellian model. An analytical approximation to the electron energy flux was derived which better describes the data over the range .2 eV/Ec approximated 3. Analyses of individual energy spectra at small and large pitch angles through well-defined inverted-V structures suggest that the altitude of the inferred potential drop maximizes near the center of the inverted-V's.

Meniett, J. D.↗

Laser powder bed fusion parameter estimation with k-NN

Abstract Laser powder bed fusion (L-PBF) is a technique within additive manufacturing that uses a high power density laser to build parts from fused powdered metal alloy. This technology is well equipped to produce complex parts with otherwise impossible features, such as hidden voids or lattice structures. Alongside capability, reliability and quality are key characteristics considered when choosing a manufacturing method, and these are gaining attention as this method becomes more prevalent in industry. One main indicator of a stable L-PBF process is consistent melt pool geometry, and the properties of which are likely to determine the quality of the part produced. As computing power and sensing technologies become more advanced, this melt pool geometry could be studied in real time. This work addresses the challenge by leveraging a k-nearest neighbor (k-NN) model to identify key features within melt pool imagery and predict the energy density. The k-NN model was trained on data provided by the National Institute of Standards and Technology (NIST). Data preprocessing was performed on the images to extract features that were used in the k-NN model. This approach was used to accurately infer the energy density of unseen layers within the same part. The algorithm was subsequently tested with unique scan strategies and found to reasonably estimate the energy density of different parts. A fivefold cross validation found the algorithm to be consistently predicting the class of 91.4% of the in situ melt pool images.

Jung, Patrick (ORCID:0000000267890859)↗

Solar wind halo electrons from 1-4 AU

Observations from the Ulysses solar wind electron spectrometer are used to make a first examination of the evolution of the solar wind suprathermal or halo electron population as a function of heliocentric distance beyond 1 AU. As the core population cools with increasing heliocentric distance, no gap is formed between the core and halo populations. Rather, the halo electrons extend to increasingly lower energies. As predicted previously on theoretical grounds, the ratio of the core electron temperature to the low energy cutoff of the halo population appears to be roughly constant with a value of about 7.5. The total integrated heat flux drops rapidly with increasing heliocentric distance; a best fit power law of R exp -2.36 is found. In addition, it is found that the ratio of the halo to core densities is roughly constant over heliocentric distance with the halo representing 4 percent of the total electron distribution. These results suggest that the halo population may not consist of truly noninteractive test particles over the heliocentric range of 1-4 AU.

Mccomas, D. J.↗

Quantification of Energy Release in Composite Structures

Energy release rate is usually suggested as a quantifier for assessing structural damage tolerance. Computational prediction of energy release rate is based on composite mechanics with micro-stress level damage assessment, finite element structural analysis and damage progression tracking modules. This report examines several issues associated with energy release rates in composite structures as follows: Chapter I demonstrates computational simulation of an adhesively bonded composite joint and validates the computed energy release rates by comparison with acoustic emission signals in the overall sense. Chapter II investigates the effect of crack plane orientation with respect to fiber direction on the energy release rates. Chapter III quantifies the effects of contiguous constraint plies on the residual stiffness of a 90 deg ply subjected to transverse tensile fractures. Chapter IV compares ICAN and ICAN/JAVA solutions of composites. Chapter V examines the effects of composite structural geometry and boundary conditions on damage progression characteristics.

Minnetyan, Levon↗

Quantification of Energy Release in Composite Structures

Energy release rate is usually suggested as a quantifier for assessing structural damage tolerance. Computational prediction of energy release rate is based on composite mechanics with micro-stress level damage assessment, finite element structural analysis and damage progression tracking modules. This report examines several issues associated with energy release rates in composite structures as follows: Chapter I demonstrates computational simulation of an adhesively bonded composite joint and validates the computed energy release rates by comparison with acoustic emission signals in the overall sense. Chapter II investigates the effect of crack plane orientation with respect to fiber direction on the energy release rates. Chapter III quantifies the effects of contiguous constraint plies on the residual stiffness of a 90 ply subjected to transverse tensile fractures. Chapter IV compares ICAN and ICAN/JAVA solutions of composites. Chapter V examines the effects of composite structural geometry and boundary conditions on damage progression characteristics.

Minnetyan, Levon↗

Wind Energy Accomplishments & Midyear Performance Report: Fiscal Year 2022

2022 marks 43 years of innovation through the National Wind Technology Center at the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL) Flatirons Campus. Scientists, engineers, analysts, and researchers continue to build on NREL's legacy of innovation at this world-class hub for wind energy technology research and development. Today, the nation's goals to tackle climate change and revitalize the U.S. economy through increased investment in clean energy - particularly in land-based, offshore, and distributed wind energy - are more ambitious than ever. From advancing wind energy science, technologies, and materials to demonstrating thought leadership on a worldwide scale, NREL's Wind Energy Program played a powerful role in maximizing the impact of wind energy in the first half of Fiscal Year (FY) 2022. NREL's technical expertise, research capabilities, and industry understanding continued to support DOE's efforts to champion clean energy, addressing market and deployment barriers and driving down costs with more efficient, reliable, and predictable wind energy systems. This report provides an overview of the achievements NREL made on behalf of DOE's Wind Energy Technologies Office (WETO) and other partners between October 1, 2021, and March 31, 2022.

accomplishments↗

Autonomous Emergency Landing for Fixed-Wing Aircraft with Energy-Constrained Closed-Loop Prediction

Here this paper presents a new approach for autonomous motion planning for aircraft suffering from a loss-of-thrust emergency. Specifically, we show how modifications to the Closed-Loop Rapidly exploring Random Trees (CL-RRT) framework combined with controlled energy dissipation can enable rapid and effective kinodynamic motion planning. This CL-RRT Glide algorithm uses closed-loop prediction not only for node connections but also to estimate the remaining energy and prune infeasible paths. This greatly speeds up the search process, which is essential for emergency situations. In addition, we improve the ability of the gliding aircraft to reach a goal position and energy state. We do so by creating a Dissipative Total Energy Control Scheme (TECS). Dissipative TECS enables the glider to lose excess altitude in order to reach a desired energy level. Simulation results illustrate how the proposed methods enable faster motion planning. We also integrate the system into a small unmanned aerial vehicle system and experimentally demonstrate autonomous glide planning and execution during a motor-failure event. This type of algorithm can primarily benefit unmanned aircraft but can also serve to assist pilots in stressful emergency situations.

42 ENGINEERING↗

Computationally Guided and Experimentally Validated Design of Custom Chelators for Critical Mineral Recovery

Selective, high throughput separation of target critical metals from complex environments such as fly ash leachates and mining process streams presents a significant challenge for economical production. Custom chelators and sorbents are an attractive technology for selective metal extraction, however it can be difficult to predict their performance, and significant experimental efforts are often required to develop chelating technologies. Here, we present a computational strategy focused on modelling chelator-metal binding interactions and benchmark these results versus experimental data. A computational pipeline combining forcefield, semiempirical, and meta-GGA methods with a thermodynamic framework optimized for error cancellation has been developed to predict binding energies of chelator complexes towards critical mineral recovery applications. This approach, originally validated on [2.2.2] cryptates binding mono- and divalent cations, demonstrated robust predictive capabilities with an R2 of 0.850 against experimental aqueous binding energies. The workflow includes metadynamics for exploring high-dimensional potential energy surfaces and a cluster-continuum model for accurate yet computationally efficient solvation modeling. Error cancellation between solvation energies of free and chelator-coordinated ions enables faster convergence, even with finite cluster sizes. Initial studies on the cryptates revealed consistent metal-ligand coordination patterns, with systematic variations influenced by ion size and charge, highlighting key structural features linked to binding selectivity. Further studies of a proprietary chelator have resulted in identification of previously unreported selectivity towards economically significant metals, which in-house experiments have confirmed, demonstrating the feasibility of this approach. By applying this methodology to new chelators targeting critical minerals such as lithium, cobalt, nickel and other strategic metals, we aim to accelerate the discovery of next-generation chelators for efficient recovery, recycling, and separation processes. This computational framework serves as the backbone of a high-throughput design pipeline tailored for sustainable resource utilization and may be applied to a wide range of systems to meet experimental needs.

computational materials↗

Deep Learning with Reflection High-Energy Electron Diffraction Images to Predict Cation Ratio in Sr 2 x Ti 2(1– x ) O 3 Thin Films

Machine learning (ML) with in-situ diagnostics offers a transformative approach to accelerate, understand, and control thin film synthesis by uncovering relationships between synthesis conditions and material properties. In this study, we demonstrate the application of deep learning to predict the stoichiometry of Sr 2x Ti 2(1–x) O 3 thin films using reflection high-energy electron diffraction images acquired during pulsed laser deposition. A gated convolutional neural network trained for regression of the Sr atomic fraction achieved accurate predictions with a small dataset of 31 samples. Explainable AI techniques revealed a previously unknown correlation between diffraction streak features and cation stoichiometry in Sr 2x Ti 2(1–x) O 3 thin films. Here, our results demonstrate how ML can be used to transform a ubiquitous in-situ diagnostic tool, that is usually limited to qualitative assessments, into a quantitative surrogate measurement of continuously valued thin film properties. Such methods are critically needed to enable real-time control, autonomous workflows, and accelerate traditional synthesis approaches.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

The Electronic Structure of Zirconium and Hafnium Monochalcogenides

High-level ab initio CCSD(T) and spin–orbit icMRCI+Q calculations were used to predict potential energy curves (PECs) for the lowest-lying states of ZrO, ZrS, HfO, and HfS. The prediction of the ground state is basis set dependent at the icMRCI+Q level for ZrO and ZrS due to the small singlet–triplet splitting between the lowest 1 Σ + and 3 Δ states. CCSD(T) with a spin orbit correction predicted the 1 Σ + ground state in agreement with experiment. New all-electron basis sets were developed for Hf to improve the results over those predicted by use of effective core potentials (ECPs) that subsume the 4f electrons into the definition of the core. The use of the new DK-4f basis sets rather than ECPs became more important for HfO and HfS where there is a lack of a good core–valence separation. icMRCI+Q, CCSD(T), and DFT calculations for the spectroscopic parameters of ZrO, ZrS, HfO, and HfS were benchmarked with available experimental data. Bond dissociation energies (BDEs) of these four systems were calculated at the Feller–Peterson–Dixon (FPD) level to be 762.1 (ZrO), 543.5 (ZrS), 803.8 (HfO), and 575.1 kJ/mol (HfS), in excellent agreement with experiment. The HfS BDE was remeasured using the R3PI method, providing an updated experimental measurement of D 0 (HfS) = 5.978 ± 0.002 eV = 576.8 ± 0.2 kJ/mol. This experimental value, combined with experimental measurements of the ionization energies of Hf and HfS, gives the cationic BDE of D 0 (Hf + -S) = 5.124 ± 0.002 eV = 494.4 ± 0.2 kJ/mol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mobility and Energy Improvements Realized through Prediction-based Vehicle Powertrain Control and Traffic Management (Research Performance Final Report)

The goal of this project was to utilize individual vehicle and systems-level transportation big data to develop real-world implementable techniques for energy efficiency. We collected a real world dataset in Fort Collins, CO using technology that is currently available. This dataset was used to (1) create individual vehicle prediction models and emissions models using cutting-edge artificial intelligence (AI) techniques, (2) create traffic prediction models, (3) create boundary condition constraints for optimal trajectory derivation, and (4) develop a novel Mobility Energy Productivity (MEP) model for Fort Collins, CO at a fidelity and flexibility which did not previously exist. Each of these techniques is novel but the most interesting results occurred from the intersection of all techniques. It was found that when optimal vehicle control is combined with optimal traffic light control, that significant energy efficiency improvements that do not compromise travel time are available.

42 ENGINEERING↗

Experimental Investigation of Melting and Solidification Processes of Phase Change Material Heat Exchanger

Rapid development and validation of PCM embedded heat exchangers (PCM-HX) concepts warrant a purpose-built test bench. This paper describes a test facility built for testing various PCM-HX configurations and phase change temperatures that will serve to validate the performance of novel PCM-HX designs. The entire test rig is placed in a temperature-controlled environmental chamber. Inside the PCM-HX containers, up to 48 T-type thermocouples can be spatially distributed on and around the tubes depending on the HX type to capture the phase change process over time. In this paper, a straight tube embedded in PCM having a phase change temperature of 37°C in cylindrical containers is tested. The PCM-HX uses water as an in-tube working fluid. Based on the measured data, the energy balance is analyzed, and its temperature distribution is presented. Here, the maximum deviation between the predicted stored energy and the energy stored calculated from experimental measurements is less than 5%.

36 MATERIALS SCIENCE↗

A View of the Lunar Interior Through Lunar Laser Range Analysis

Laser ranges between observatories on the Earth and retroreflectors on the Moon started in 1969 and continue to the present. Recent range accuracies are 2 cm while earliest ranges are an C, order of magnitude less certain. Four retroreflectors are ranged: three located at the Apollo 11, 14, and 15 sites and one on the Lunakhod 2 rover. Accurate analysis of the range data determines a number of lunar science parameters. The lunar interior variables include a fluid core parameter. The Lunar Laser Ranging effort is reviewed elsewhere. Many parameters are detected through their influence on rotation. Also detected are solid-body tides and accurate selenocentric reflector locations. Determined through the rotation are moment-of-inertia differences, gravitational harmonics, potential Love number, and dissipation effects due to tides and molten core. The rotation of the Moon is not at its minimum energy state; some recently active process has caused free librations. The moment differences contributed to the recent improvement of the Moon's moment of inertia from the Lunar Prospector gravity field. The Love numbers provide bulk elastic properties. Future possibilities for measurement include oblateness of the core-mantle boundary and core moment. A study of dissipation signatures in the rotation determines tidal Q vs. frequency and concludes that the Moon has a molten core. At 1 month the tidal Q is 37 and at 1 yr it is 60. The core radius is < or = 352 km for Fe and < or = 374 km for the Fe-FeS eutectic. The core detection exceeds 3x its uncertainty. The spin of the core is not aligned with the spin of the mantle and torque arises from the velocity difference at the boundary. Yoder's turbulent boundary layer theory is used to compute the radii. The present heat generation from tides and core interaction is minor compared to radiogenic heating. The heating for ancient times is more interesting. Peale and Cassen investigated lunar tidal heating while the lunar orbit expanded due to tides on Earth. Their calculations predate the measurement of Q and should be multiplied by 3.45 to match the lunar-laser-determined Love number and monthly Q. Tidal-heating computations depend on how fast the lunar orbit evolved and whether the tidal dissipation is localized. Neither is known, but plausible assumptions lead to early central region temperature increases of several hundred degrees. Most of the energy is deposited early in the Moon's history. The turbulent boundary layer theory allows a prediction of energy dissipated at the core-mantle boundary during orbit evolution. Under the assumption that the properties of the early core are the same as at present, the energy dissipated by core-mantle interaction is about the same as for tidal dissipation, but it is deposited in a smaller volume. This source of energy is capable of promoting convection in an early fluid core and driving a dynamo. This is a transient phase with a duration depending on the rate of orbit evolution. Plausible assumptions lead to a duration of a few hundred million years. Thus, the remnant magnetization of many lunar rocks is compatible with a brief global magnetic field powered by dynamical energy dissipation. Analysis of the lunar laser ranges is providing information on lunar geophysics. Future data will improve accuracies of present solution parameters, and several more interior effects should be detectable.

Williams, J. G.↗

Sensitivity of an energy balance climate model with predicted snowfall rates

A snowfall parameterization and a polar-ice-sheet model are developed and applied to the two-level zonally averaged seasonal energy-balance climate model of Held and Suarez (1979), and sensitivity experiments involving changes in insolation are performed both with and without ice sheets. The results are presented in tables and graphs, and the hydrological-cycle response to insolation changes is found to be similar to that predicted by global-circulation models employing prescribed precipitation levels, with a somewhat higher sensitivity in the snow line. The area covered by ice sheets in the ice-sheet models is shown to be greater than that covered by permanent snow in the models without ice sheets, an effect attributed to lower surface temperatures over the ice. It is inferred that an increase in the solar constant can cause increased high-latitude precipitation but not an ice age.

Bowman, K. P.↗