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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Intersublattice magnetocrystalline anisotropy using a realistic tight-binding method based on maximally localized Wannier functions

Using a realistic tight-binding Hamiltonian based on maximally localized Wannier functions, we investigate the two-ion magnetocrystalline anisotropy energy (MAE) in L 1 0 transition metal compounds. MAE contributions from throughout the Brillouin zone are obtained using magnetic force theorem calculations with and without perturbation theory. The results from both methods agree with each other, and both reflect features of the Fermi surface. The intrasublattice and intersublattice contributions to MAE are evaluated using a Green's function method. We find that the sign of the intersublattice contribution varies among compounds, and that its amplitude may be significant, suggesting MAE can not be resolved accurately in a single-ion manner. The results are further validated by scaling spin-orbit-coupling strength in density functional theory. Altogether, this realistic tight-binding method provides an effective approach to evaluate and analyze MAE while retaining the accuracy of corresponding first-principles methods.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Entanglement maximization in low-energy neutron-proton scattering

The entanglement properties of neutron-proton scattering are investigated using a measure that counts the number of entangled pairs produced by the action of a scattering operator on a given initial neutron-proton state. All phase shifts relevant for scattering at laboratory energies up to 350 MeV are used. Entanglement is found to depend strongly on the initial state. Entanglement is maximized in very low energy scattering if the initial spin state is | ↑ ↓ >, but not if the initial state is | ↑ ↑ > . At such energies the Hamiltonian obeys Wigner SU(4) symmetry, and an entanglement maximum is a sign of that symmetry. At higher energies the angular dependence of entanglement is strong and the entanglement is large for many scattering angles. Furthermore, the tensor force is shown to play a significant role in producing entanglement at laboratory kinetic energies greater than about 50 MeV.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Maximally local two-nucleon interactions at N 3 LO in Δ -less chiral effective field theory

We present new maximally local two-nucleon interactions derived in Δ -less chiral effective field theory up to next-to-next-to-next-to-leading order ( N 3 LO ), which include all contact and pion-exchange contributions to the nuclear Hamiltonian up to this order. Our interactions are fit to nucleon-nucleon phase shifts using a Bayesian statistical approach, and explore a wide cutoff range from 0.6 – 0.9 fm ( ≈ 660 – 440 MeV ). These interactions can be straightforwardly employed in quantum Monte Carlo methods, such as the auxiliary field diffusion Monte Carlo method. Together with local three-nucleon forces, calculations with these new interactions will provide improved benchmarks for the structure of atomic nuclei and serve as crucial input to analyses of astrophysical phenomena of neutron stars, such as binary neutron-star mergers. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Maximally supersymmetric amplitudes at infinite loop momentum

We investigate the asymptotically large loop-momentum behavior of multiloop amplitudes in maximally supersymmetric ($N$ = 4, 8) quantum field theories in four dimensions. We check residue-theorem identities among color-dressed leading singularities in $N$ = 4 supersymmetric Yang-Mills theory to demonstrate the absence of poles at infinity of all n-point MHV amplitudes through three loops. Considering the same test for $N$ = 8 supergravity leads us to discover that this theory does support nonvanishing residues at infinity starting at two loops, and the degree of these poles grow arbitrarily with multiplicity. This causes a tension between simultaneously manifesting ultraviolet finiteness—which would be automatic at two loops for representation obtained by color-kinematic duality—and gauge invariance—which would follow from unitarity-based methods.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Celestial Dual for Maximal Helicity Violating Amplitudes

It is shown that a 2D conformal field theory consisting of a central charge c Liouville theory, a chiral level one, rank N Kac-Moody algebra, and a weight − 3 / 2 free fermion holographically generate 4D maximal helicity violating tree-level scattering amplitudes. The correlators of this 2D conformal field theory give directly the 4D leaf amplitudes associated to a single hyperbolic slice of flat space. The 4D celestial amplitudes arise in a large- N and semiclassical large- c limit, according to the holographic dictionary, as a translationally invariant combination of leaf amplitudes. A step in the demonstration is showing that the semiclassical limit of Liouville correlators are given by contact 3D anti–de Sitter Witten diagrams. Published by the American Physical Society 2024

Physics↗
DOE OSTI2022

WinnowML: Stable feature selection for maximizing prediction accuracy of time-based system modeling

Online deep learning (ODL) has become an important methodology for modeling time-based performance of computer systems. An open problem is the intelligent selection of features from raw workload traces of computer systems. The best methods are overly sensitive to noisy data, causing frequent feature changes and re-training. Using all available features inflates training time and introduces model artifacts if some features should have been dropped. We present WinnowML, a method for automatically determining the most relevant feature subset for a predictive time-series model. WinnowML combines existing feature ranking algorithms and a history of each feature's ranking to iteratively rank a feature set to lower prediction error and maximize long term relevance. From this ranked feature set, the most relevant and stable subset is selected to train a model. Experimentally, we show how WinnowML can lower a model's mean absolute relative error up to 42% on average compared to the closest performing approach. Additionally, we lower the fluctuation in feature ranking and selection up to 65%. We also demonstrate how to combine WinnowML and a model search tool to provide improvements in performance of up to 14.5% when compared to using all the feature available.

Bel, Oceane MS↗
DOE OSTI2025

Network-Aware and Welfare-Maximizing Dynamic Pricing for Energy Sharing

The proliferation of behind-the-meter (BTM) distributed energy resources (DER) within the electrical distribution network presents significant supply and demand flexibilities, but also introduces operational challenges such as voltage spikes and reverse power flows. In response, this paper proposes a network-aware dynamic pricing framework tailored for energy-sharing coalitions that aggregate small, but ubiquitous, BTM DER downstream of a distribution system operator's (DSO) revenue meter that adopts a generic net energy metering (NEM) tariff. By formulating a Stackelberg game between the energy-sharing market leader and its prosumers, we show that the dynamic pricing policy induces the prosumers toward a network-safe operation and decentrally maximizes the energysharing social welfare. The dynamic pricing mechanism involves a combination of a locational ex-ante dynamic price and an ex-post allocation, both of which are functions of the energy sharing's BTM DER. The ex-post allocation is proportionate to the price differential between the DSO NEM price and the energy-sharing locational price. Simulation results using real DER data and the IEEE 13-bus test systems illustrate the dynamic nature of network-aware pricing at each bus, and its impact on voltage.

aggregates↗
DOE OSTI2024

How Much Reserve Fuel: Quantifying the Maximal Energy Cost of System Disturbances

Motivated by the design question of additional fuel needed to complete a task in an uncertain environment, this paper introduces metrics to quantify the maximal additional energy used by a control system in the presence of bounded disturbances, compared to a nominal, disturbance-free system. In particular, we consider the task of finite-time stabilization for a linear, time-invariant system. We compare the nominal energy required to achieve this task in the disturbance-free system to the worst-case energy over all feasible disturbances. Solving for the worst-case energy over all disturbances first leads to an optimal control problem with a least-squares solution, and then an infinite-dimensional optimization problem where we derive an upper bound on the solution. The comparison of energies is accomplished using additive and multiplicative metrics, for which we derive bounds. Simulation examples on an ADMIRE fighter jet model demonstrate the practicability of these metrics, and their variation with the distance of the initial condition from the origin and the task completion time.

koopman operator, resilience↗
DOE OSTI2012

A Novel Multithreaded Algorithm For Extracting Maximal Chordal Subgraphs

Chordal graphs are triangulated graphs where any cycle larger than three is bisected by a chord. Many combinatorial optimization problems such as computing the minimum fill-in, the size of the maximum clique and the chromatic number are NP-hard on general graphs but have polynomial time solutions on chordal graphs. In this paper, we present a novel multithreaded algorithm to extract a maximal chordal subgraph from a general graph. Our algorithm is based on an iterative approach where each thread can asynchronously update a subset of edges that are dynamically assigned to it. We implement our algorithm on two different multithreaded architectures – Cray XMT, a massively multithreaded platform, and AMD Magny-Cours, a shared memory multicore platform. In addition to the proof of correctness, we present the performance of our algorithm using a testset of carefully generated synthetical graphs with up to half-a-billion edges and real world networks from gene correlation studies. We demonstrate that our algorithm achieves high scalability for all inputs on both types of architectures.

Halappanavar, Mahantesh↗
DOE OSTI2019

Maximizing the Benefits of Volt/VAR Optimization in the Presence of Community Energy Storage

This paper reports on the need for coordinating smart grid volt/volt-ampere reactive (VAR) control (VVC) and community energy storage (CES) to maximize the benefits of both approaches. It addresses a key application of volt/VAR optimization (VVO): the conservation of voltage reduction (CVR). The lack of coordination among network controls, such as VVO, and asset controls at the community battery storage system can lead to detrimental effects on grid operation. A smart grid-enabled VVC uses the VVO to perform the CVR operation. VVO can perform numerous tasks for advanced distribution management systems with coordination of the system operator. To achieve the optimal VVC solution, we use a particle swarm optimization driven VVO method. The test system has been simulated for two scenarios-during light loading and high loading condition-with and without the CES system. In both scenarios, the operation of CVR and CES have been performed considering different case studies. The outcomes of the simulated results demonstrate that significant improvement in peak load-demand reduction is achieved by the proposed VVC and CES system with reduced system losses.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

An Expectation-Maximization Method for Calibrating Synchronous Machine Models

The accuracy of a power system dynamic model is essential to its secure and efficient operation. Lower confidence in model accuracy usually leads to conservative operation and lowers asset usage. To improve model accuracy, this paper proposes an expectation-maximization (EM) method to calibrate the synchronous machine model using phasor measurement unit (PMU) data. First, an extended Kalman filter (EKF) is applied to estimate the dynamic states using measurement data. Then, the parameters are calculated based on the estimated states using maximum likelihood estimation (MLE) method. The EM method iterates over the preceding two steps to improve estimation accuracy. The proposed EM method’s performance is evaluated using a single-machine infinite bus system and compared with a method where both state and parameters are estimated using an EKF method. Sensitivity studies of the parameter calibration using EM method are also presented to show the robustness of the proposed method for different levels of measurement noise and initial parameter uncertainty.

EM Algorithms↗
DOE OSTI2018

Tuning Superhydrophilic Nanostructured Surfaces to Maximize Water Droplet Evaporation Heat Transfer Performance

Spraying water droplets on air fin surfaces is often used to augment the performance of air-cooled Rankine power plant condensers and wet cooling tower heat exchangers for building air-conditioning systems. To get the best performance in such processes, the water droplets delivered to the surface should spread rapidly into an extensive, thin film and evaporate with no liquid leaving the surface due to recoil or splashing. This paper presents predictions of theoretical/computational modeling and results of experimental studies of droplet spreading on thin-layer, nanostructured, superhydrophilic surfaces that exhibit very high wicking rates (wickability) in the porous layer. Analysis of the experimental data in the model framework illuminates the key aspects of the physics of the droplet-spreading process and evaporation heat transfer. This analysis also predicts the dependence of droplet-spreading characteristics on the nanoporous surface morphology and other system parameters. The combined results of this investigation indicate specific key strategies for design and fabrication of surface coatings that will maximize the heat transfer performance for droplet evaporation on heat exchanger surfaces. The implications regarding wickability effects on pool boiling processes are also discussed.

Engineering↗
DOE OSTI2020

A Framework for Optimal Placement of Rooftop Photovoltaic: Maximizing Solar Production and Operational Cost Savings in Residential Communities

Optimizing the placement of photovoltaic (PV) panels on residential buildings has the potential to significantly increase energy efficiency benefits to both homeowners and communities. Strategic PV placement can lower electricity costs by reducing the electricity fed from the grid during on-peak hours, while maintaining PV panel efficiency in terms of the amount of solar radiation received. In this article, we present a framework that identifies the ideal location of PV panels on residential rooftops. Our framework combines energy and environmental simulation, parametric modeling, and optimization to inform PV placement as it relates to and affects the entire community (in terms of both energy use and financial cost), as well as individual buildings. Ensuring that our framework accounts for shading from nearby buildings, different utility rate structures, and different buildings’ energy demand profiles means that existing communities and future housing developments can be optimized for energy savings and PV efficiency. The framework comprises two workflows, each contributing to optimal PV placement with a unique target: (a) maximizing PV panel efficiency (i.e., solar generation) and (b) minimizing operational energy cost considering utility rate structures for operational energy. We apply our framework to a residential community in Fort Collins, Colorado, to demonstrate the optimal PV placement, considering the two workflow targets. Here, we present our results and illustrate the effect of PV location and orientation on solar energy production efficiency and operational energy cost.

14 SOLAR ENERGY↗
DOE OSTI2016

SU-G-BRA-04: Simulation of Errors in Maximal Intensity Projection (MIP)-Based Lung Tumor Internal Target Volumes (ITV) Using Real-Time 2D MRI and Deformable Image Registration Based Lung Tumor Tracking

Purpose: To evaluate the effect of inter- and intra-fractional tumor motion on the error in four-dimensional computed tomography (4DCT) maximal intensity projection (MIP)–based lung tumor internal target volumes (ITV), using deformable image registration of real-time 2D-sagital cine-mode MRI acquired during lung SBRT treatments. Methods: Five lung tumor patients underwent free breathing SBRT treatment on the ViewRay, with dose prescribed to PTV (4DCT MIP-based ITV+3–6mm margin). Sagittal slice cine-MR images (3.5×3.5mm pixels) were acquired through the center of the tumor at 4 frames per second throughout the treatments (3–4 fractions of 21–32 minutes duration). Tumor GTVs were contoured on the first frame of the cine and tracked throughout the treatment using off-line optical-flow based deformable registration implemented on a GPU cluster. Pseudo-4DCT MIP-based ITVs were generated from MIPs of the deformed GTV contours limited to short segments of image data. All possible pseudo-4DCT MIP-based ITV volumes were generated with 1s resolution and compared to the ITV volume of the entire treatment course. Varying pseudo-4DCT durations from 10-50s were analyzed. Results: Tumors were covered in their entirety by PTV in the patients analysed here. However, pseudo-4DCT based ITV volumes were observed that were as small as 29% of the entire treatment-ITV, depending on breathing irregularity and the duration of pseudo-4DCT. With an increase in duration of pseudo-4DCT from 10–50s the minimum volume acquired from 95% of all pseudo-4DCTs increased from 62%–81% of the treatment ITV. Conclusion: A 4DCT MIP-based ITV offers a ‘snap-shot’ of breathing motion for the brief period of time the tumor is imaged on a specific day. Real time MRI over prolonged periods of time and over multiple treatment fractions shows that the accuracy of this snap-shot varies according to inter- and intra-fractional tumor motion. Further work is required to investigate the dosimetric effect of these results.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-CD-206-01: Expectation-Maximization Algorithm-Based Tissue Mixture Quantification for Perfusion MRI

Purpose: To investigate the feasibility of estimating the tissue mixture perfusions and quantifying cerebral blood flow change in arterial spin labeled (ASL) perfusion MR images. Methods: The proposed perfusion MR image analysis framework consists of 5 steps: (1) Inhomogeneity correction was performed on the T1- and T2-weighted images, which are available for each studied perfusion MR dataset. (2) We used the publicly available FSL toolbox to strip off the non-brain structures from the T1- and T2-weighted MR images. (3) We applied a multi-spectral tissue-mixture segmentation algorithm on both T1- and T2-structural MR images to roughly estimate the fraction of each tissue type - white matter, grey matter and cerebral spinal fluid inside each image voxel. (4) The distributions of the three tissue types or tissue mixture across the structural image array are down-sampled and mapped onto the ASL voxel array via a co-registration operation. (5) The presented 4-dimensional expectation-maximization (4D-EM) algorithm takes the down-sampled three tissue type distributions on perfusion image data to generate the perfusion mean, variance and percentage images for each tissue type of interest. Results: Experimental results on three volunteer datasets demonstrated that the multi-spectral tissue-mixture segmentation algorithm was effective to initialize tissue mixtures from T1- and T2-weighted MR images. Compared with the conventional ASL image processing toolbox, the proposed 4D-EM algorithm not only generated comparable perfusion mean images, but also produced perfusion variance and percentage images, which the ASL toolbox cannot obtain. It is observed that the perfusion contribution percentages may not be the same as the corresponding tissue mixture volume fractions estimated in the structural images. Conclusion: A specific application to brain ASL images showed that the presented perfusion image analysis method is promising for detecting subtle changes in tissue perfusions, which is valuable for the early diagnosis of certain brain diseases, e.g. multiple sclerosis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Increasing the revenue from lignocellulosic biomass: Maximizing feedstock utilization

The production of renewable chemicals and biofuels must be cost- and performance- competitive with petroleum-derived equivalents to be widely accepted by markets and society. We propose a biomass conversion strategy that maximizes the conversion of lignocellulosic biomass (up to 80% of the biomass to useful products) into high-value products that can be commercialized, providing the opportunity for successful translation to an economically viable commercial process. Our fractionation method preserves the value of all three primary components: (i) cellulose, which is converted into dissolving pulp for fibers and chemicals production; (ii) hemicellulose, which is converted into furfural (a building block chemical); and (iii) lignin, which is converted into carbon products (carbon foam, fibers, or battery anodes), together producing revenues of more than $500 per dry metric ton of biomass. Once de-risked, our technology can be extended to produce other renewable chemicals and biofuels.

09 BIOMASS FUELS↗
DOE OSTI2015

Maximal design basis accident of fusion neutron source DEMO-TIN

When analyzing the safety of nuclear (including fusion) facilities, the maximal design basis accident at which the largest release of activity is expected must certainly be considered. Such an accident is usually the failure of cooling systems of the most thermally stressed components of a reactor (for a fusion facility, it is the divertor or the first wall). The analysis of safety of the ITER reactor and fusion power facilities (including hybrid fission–fusion facilities) shows that the initial event of such a design basis accident is a large-scale break of a pipe in the cooling system of divertor or the first wall outside the vacuum vessel of the facility. The greatest concern is caused by the possibility of hydrogen formation and the inrush of air into the vacuum chamber (VC) with the formation of a detonating mixture and a subsequent detonation explosion. To prevent such an explosion, the emergency forced termination of the fusion reaction, the mounting of shutoff valves in the cooling systems of the divertor and the first wall or blanket for reducing to a minimum the amount of water and air rushing into the VC, the injection of nitrogen or inert gas into the VC for decreasing the hydrogen and oxygen concentration, and other measures are recommended. Owing to a continuous feed-out of the molten-salt fuel mixture from the DEMO-TIN blanket with the removal period of 10 days, the radioactivity release at the accident will mainly be determined by tritium (up to 360 PBq). The activity of fission products in the facility will be up to 50 PBq.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗