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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 OSTI2020

Toward an effective CFT 2 from $ \mathcal{N} $ = 4 super Yang-Mills and aspects of Hawking radiation

Using $ \mathcal{N} $ = 4 supersymmetric Yang-Mills theory we recover important aspects of the near-extremal thermodynamics of AdS 5 black holes including both the outer and the inner horizons with their corresponding entropy and energy. This $ \mathcal{N} $ = 4 supersymmetric Yang-Mills theory approach to black hole thermodynamics leads to an effective CFT 2 interpretation similar to the work by Callan and Maldacena. We corroborate this effective CFT 2 by implementing a particular near-horizon limit that geometrizes the Virasoro algebras as asymptotic symmetries. Using the effective CFT 2 picture, we discuss aspects of the Hawking radiation rate for a region of the near-extremal AdS 5 black hole quantum evolution.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Holographic flows from CFT to the Kasner universe

The Schwarzschild singularity is known to be classically unstable. We demonstrate a simple holographic consequence of this fact, focusing on a perturbation that is uniform in boundary space and time. Deformation of the thermal state of the dual CFT by a relevant operator triggers a nonzero temperature holographic renormalization group flow in the bulk. This flow continues smoothly through the horizon and, at late interior time, deforms the Schwarzschild singularity into a more general Kasner universe. We show that the deformed near-singularity, trans-horizon Kasner exponents determine specific non-analytic corrections to the thermal correlation functions of heavy operators in the dual CFT, in the analytically continued ‘near-singularity’ regime.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Six-point functions and collisions in the black hole interior

In the eternal AdS black hole geometry, we consider two signals sent from the boundaries into the black hole interior shared between the two asymptotic regions. We compute three different out-of-time-order six-point functions to quantify various properties of the collision of these signals behind the horizons: (i) We diagnose the strength of the collision by probing the two-signal state on a late time slice with boundary operators. (ii) We quantify two-sided operator growth, which provides a dual description of the signals meeting in the black hole interior, in terms of the quantum butterfly effect and quantum circuits. (iii) We consider an explicit coupling between the left and right CFTs to make the wormhole traversable and extract information about the collision product from behind the horizon. At a technical level, our results rely on the method of eikonal resummation to obtain the relevant gravitational contributions to Lorentzian six-point functions at all orders in the GN-expansion. We observe that such correlation functions display an intriguing factorization property. We corroborate these results with geodesic computations of six-point functions in two- and three-dimensional gravity.

2D Gravity↗
DOE OSTI2025

Quantum area fluctuations from gravitational phase space

We study the gravitational phase space associated to a stretched horizon within a finite-sized causal diamond in (d + 2)-dimensional spacetimes. By imposing the Raychaudhuri equation, we obtain its constrained symplectic form using the covariant phase space formalism and derive the relevant quantum commutators by inverting the symplectic form and quantizing. Finally, we compute the area fluctuations of the causal diamond by taking a Carrollian limit of the stretched horizon in pure Minkowski spacetime, and derive the relationship $\left\langle {\left(\Delta A\right)}^2\right\rangle \ge \frac{2\pi G}{d}\left\langle A\right\rangle$, showing that the variance of the area fluctuations is proportional to the area itself.

classical theories of gravity↗
DOE OSTI2021

Shocks and information exchange in de Sitter space

We discuss some implications of recent progress in understanding the black hole information paradox for complementarity in de Sitter space. Extending recent work by two of the authors, we describe a bulk procedure that allows information expelled through the cosmological horizon to be received by an antipodal observer. Generically, this information transfer takes a scrambling time t=H- 1 (S ds ). We emphasize that this procedure relies crucially on selection of the Bunch-Davies vacuum state, interpreted as the thermofield double state that maximally entangles two antipodal static patches. The procedure also requires the presence of an (entangled) energy reservoir, created by the collection of Hawking modes from the cosmological horizon. We show how this procedure avoids a cloning paradox and comment on its implications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Resolving black-hole microstructure with new momentum carriers

All known horizonless black-hole microstate geometries correspond to brane sources that acquire a finite size, and hence break the spherical symmetry of the black hole. We construct, for the first time, solutions with zero horizon area that have the same charges as a three-charge F1-NS5-P Type-IIA black hole and preserve this spherical symmetry. The momentum of these solutions is carried by longitudinal D0-D4 density fluctuations inside the NS5-branes. We argue that these solutions should be interpreted as the long-throat limit of a family of smooth, horizonless microstate geometries, called superstrata, where such geometries degenerate. The existence of these geometries indicates that a finite-size horizon does not appear even in the singular corners of the moduli space of three-charge microstate geometries.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Gravitational Cardy limit and AdS black hole entropy

We explore the gravitational implementation of the field theory Cardy-like limit recently used in the successful microstate countings of AdS black hole entropy in various dimensions. On the field theory side, the Cardy-like limit focuses on a particular scaling of conserved electric charges and angular momenta and we first translate this scaling to the gravitational side by a limiting procedure on the black hole parameters. We note that the scaling naturally accompanies a near-horizon region for which these black hole solutions are greatly simplified. Applying the Kerr/CFT correspondence to the near-horizon region, we precisely reproduce the Bekenstein-Hawking entropy of asymptotically AdS 4,5,6,7 BPS black holes. Our results explicitly provide a microscopic and universal low energy description for AdS black holes across various dimensions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Bulk entropy is crucial to validate the second law of the extended black hole thermodynamics

The extended black hole thermodynamics in which the cosmological constant plays the role of pressure significantly enriches the phase structure of the theory. In order to understand the extended black hole thermodynamics more precisely, we let the value of the cosmological constant vary dynamically via tunneling from one vacuum to another in a black hole induced vacuum decay. In this process, entropy of the matter/energy released by a black hole is crucial to validate the second law of thermodynamics. In other words, without taking this bulk entropy into account, entropy associated with the black hole and cosmological horizons may not always increase. Since the bulk entropy is not represented by the black hole and the cosmological horizons, this result calls for a more careful interpretation of the holographic principle in which environmental effects are taken into account.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Mixed gauge-global symmetries, elliptic modes, and black hole thermodynamics in Hořava-Lifshitz gravity

In Hořava-Lifshitz gravity, a putative consistent theory of quantum gravity for which there is evidence for both black hole thermodynamics and a holographic construction, spacetime is endowed with a preferred dynamical spacelike foliation. The theory has a leaf reparameterization symmetry that is neither global nor local gauge, hyperbolic and elliptic equations of motion, a lack of splittability, and universal horizon black hole solutions. The reparameterization symmetry is “mixed”: it is a local symmetry in one coordinate yet global on each leaf. More broadly it is an example of both unfree and projectable gauge symmetries. The mixed symmetry and associated charge has not yet been accounted for in calculations of universal horizon thermodynamics in Hořava-Lifshitz gravity. This has led to problems, in particular the failure of the first law in a class of asymptotically AdS solutions where the normal to the leaves of the foliation is not aligned with the time translation Killing vector at infinity. We show how the dynamics of the charge corresponding to this symmetry coupled with the other features above resolves this issue. We then briefly comment how this mixed symmetry, the corresponding charge, and the elliptic equations of motion also conspire to evade recent holographic arguments for only local gauge fields in consistent theories of quantum gravity due to the lack of splittability of the elliptic equation and associated mode.

Global Symmetries↗
DOE OSTI2022

Impacts of climate and disturbance on nutrient fluxes and stoichiometry in mixed-conifer forests

Elucidating climatic impacts on stream nutrient export and stoichiometry will improve the understanding of forest carbon (C) storage in a warmer world. We constructed C, nitrogen (N), and phosphorus (P) budgets in four watersheds within a rain-snow transition site and another four within a higher-elevation, snow-dominated site, in California’s mixed-conifer zone. We used these two sites in a space-for-time substitution to assess the potential effects of warming on nutrient cycles in currently snow-dominated areas that will become more rain-dominated. During a non-drought period (water year (WY) 2004 – 2011), mean annual stream exports of C and N in particulate forms at the transition site were double that at the snow-dominated site, suggesting that sediment-associated nutrient losses may increase with warming. The transition site had 12% lower N but double the P content in mineral horizons, lower N:P mass ratios in organic horizons, and lower stream export of dissolved inorganic N than the snow-dominated site. Furthermore, these differences suggest that montane forests may receive lower supply of N relative to P with warming. In addition, given strong interests in forest thinning to increase drought resiliency, we examined changes in stream nutrient export after thinning and during a major drought period (WY 2013 – 2015). Stream exports of C, N, and P were similar between unthinned and thinned watersheds during drought, suggesting negligible thinning impacts on stream nutrient export during excessively dry periods. Taken together, our results suggest that as the climate warms, California’s montane forests may lose more nutrients through erosion and receive less N input than P.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Fundamental physics opportunities with future ground-based mm/sub-mm VLBI arrays

The Event Horizon Telescope (EHT) Collaboration recently published the first images of the supermassive black holes in the cores of the Messier 87 and Milky Way galaxies. These observations have provided a new means to study supermassive black holes and probe physical processes occurring in the strong-field regime. We review the prospects of future observations and theoretical studies of supermassive black hole systems. Current ground-based very-long-baseline interferometry (VLBI) arrays like the EHT and proposed future extensions like the next-generation Event Horizon Telescope will greatly enhance the capabilities of black-hole imaging interferometry. These enhancements will open up several previously inaccessible avenues of investigation, thereby providing important new insights into the properties of supermassive black holes and their environments. This review describes the current state of knowledge for five key science cases, summarising the unique challenges and opportunities for fundamental physics investigations that future mm/sub-mm VLBI developments will enable.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Building thermal load prediction through shallow machine learning and deep learning

Building thermal load prediction informs the optimization of cooling plant and thermal energy storage. Physics-based prediction models of building thermal load are constrained by the model and input complexity. In this study, we developed 12 data-driven models (7 shallow learning, 2 deep learning, and 3 heuristic methods) to predict building thermal load and compared shallow machine learning and deep learning. The 12 prediction models were compared with the measured cooling demand. It was found XGBoost (Extreme Gradient Boost) and LSTM (Long Short Term Memory) provided the most accurate load prediction in the shallow and deep learning category, and both outperformed the best baseline model, which uses the previous day's data for prediction. Then, we discussed how the prediction horizon and input uncertainty would influence the load prediction accuracy. Major conclusions are twofold: first, LSTM performs well in short-term prediction (1 h ahead) but not in long term prediction (24 h ahead), because the sequential information becomes less relevant and accordingly not so useful when the prediction horizon is long. Second, the presence of weather forecast uncertainty deteriorates XGBoost's accuracy and favors LSTM, because the sequential information makes the model more robust to input uncertainty. Training the model with the uncertain rather than accurate weather data could enhance the model's robustness. Finally, our findings have two implications for practice. First, LSTM is recommended for short-term load prediction given that weather forecast uncertainty is unavoidable. Second, XGBoost is recommended for long term prediction, and the model should be trained with the presence of input uncertainty.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Dispatch optimization of a concentrating solar power system under uncertain solar irradiance and energy prices

The integration of thermal energy storage into a concentrating solar power system allows for mitigating some of the risk associated with uncertain solar irradiance and uncertain energy prices. We solve a 48 h dispatch optimization model with continually updated conditional point forecasts of both direct normal irradiance (DNI) and electricity prices with a rolling-horizon scheme at hourly resolution over the course of a year. Joint, conditional forecasts for DNI and prices are formed using an autoregressive moving-average time series model with exogenous weather predictors. We guide dispatch using a mixed-integer programming model, but in order to evaluate performance we use the System Advisor Model (SAM) of the National Renewable Energy Laboratory. SAM is a techno-economic simulation model that accounts for plant thermodynamics with higher fidelity. Our conditional DNI forecasts improve annual revenue by 4%–12% over using historical forecasts based on data from previous years. Conditional price forecasts improve annual revenue by 6%–19% in the real-time market over analogous historical forecasts. Updating these forecasts every six hours, rather than every 24 h, further improves annual revenue by 5%–6%. Here, we also investigate a method that values terminal inventory in our dispatch optimization model, again when used in a rolling-horizon scheme.

14 SOLAR ENERGY↗
DOE OSTI2024

Agent-based modeling for multimodal transportation of CO 2 for carbon capture, utilization, and storage: CCUS-agent

Here, to understand the system-level interactions between the entities in Carbon Capture, Utilization, and Storage (CCUS), an agent-based foundational modeling tool, CCUS-Agent, is developed for a large-scale study of transportation flows and infrastructure in the United States. Key features of the tool include (i) modular design, (ii) multiple transportation modes, (iii) capabilities for extension, and (iv) testing against various system components and networks of small and large sizes. Five matching algorithms for CO 2 supply agents (e.g., powerplants and industrial facilities) and demand agents (e.g., storage and utilization sites) are explored: Most Profitable First Year (MPFY), Most Profitable All Years (MPAY), Shortest Total Distance First Year (SDFY), Shortest Total Distance All Years (SDAY), and Shortest distance to long-haul transport All Years (ACAY). Before matching, the supply agent, demand agent, and route must be available, and the connection must be profitable. A profitable connection means the supply agent portion of revenue from the 45Q tax credit must cover the supply agent costs and all transportation costs, while the demand agent revenue portion must cover all demand agent costs. A case study employing over 5500 supply and demand agents and multimodal CCUS transportation infrastructure in the contiguous United States is conducted. The results suggest that it is possible to capture over 9 billion tonnes (GT) of CO 2 from 2025 to 2043, which will increase significantly to 22 GT if the capture costs are reduced by 40 %. The MPFY and SDFY algorithms capture more CO 2 earlier in the time horizon, while the MPAY and SDAY algorithms capture more later in the time horizon.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

When do different scenarios of projected electricity demand start to meaningfully diverge?

Resource adequacy studies look at balancing electricity supply and demand on 10- to 15-year time horizons while asset investment planning typically evaluates returns on 20- to 40-year time horizons. Projections of electricity demand are factored into the decision-making in both cases. Climate, energy policy, and socioeconomic changes are key uncertainties known to influence electricity demands, but their relative importance for demands over the next 10-40 years is unclear. The power sector would benefit from a better understanding of the need to characterize these uncertainties for resource adequacy and investment planning. In this study, we quantify when projected United States (U.S.) electricity demands start to meaningfully diverge in response to a range of climate, energy policy, and socioeconomic drivers. Here we use a wide yet plausible range of 21st century scenarios for the U.S. The projections span two population/economic growth scenarios (Shared Socioeconomic Pathways 3 and 5) and two climate/energy policy scenarios, one including climate mitigation policies and one without (Representative Concentration Pathways 4.5 and 8.5). Each climate/energy policy scenario has two warming levels to reflect a range of climate model uncertainty. We show that the socioeconomic scenario matters almost immediately – within the next 10 years, the climate/policy scenario matters within 25-30 years, and the climate model uncertainty matters only after 50+ years. This work can inform the power sector working to integrate climate change uncertainties into their decision-making.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Reducing the computational burden of a microgrid energy management system

As renewable technology advances and decreases in cost, microgrids are becoming an appealing means of distributed generation both for isolated communities and integrated with existing electrical grid systems. Due to their small size, however, microgrids may have financial limitations which preclude them from using commercial software to optimize control of their assets. Open-source optimization solvers are a viable alternative, but increase computation time. This work expands on a rolling horizon optimization framework for economic dispatch within an existing residential microgrid located in Hoover, Alabama. The microgrid has an open-source solver requirement and a need for quick solution time on a rolling horizon as opposed to a day-ahead commitment. We present a method of reducing integer variables by relaxation which completes two goals: reduction in computation time for real-time operations, and reduction in daily operational cost for the microgrid. Seasonal data for load and photovoltaic (PV) power was also collected from the microgrid to facilitate simulation testing. Computation time was successfully reduced using multiple variations of the relaxation method, while obtaining solution quality with operational cost similar to or better than the original model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

A FETI approach to domain decomposition for meshfree discretizations of nonlocal problems

We propose a domain decomposition method for the efficient simulation of nonlocal problems. Our approach is based on a multi-domain formulation of a nonlocal diffusion problem where the subdomains share “nonlocal” interfaces of the size of the nonlocal horizon. This system of nonlocal equations is first rewritten in terms of minimization of a nonlocal energy, then discretized with a meshfree approximation and finally solved via a Lagrange multiplier approach in a way that resembles the finite element tearing and interconnect method. Specifically, we propose a distributed projected gradient algorithm for the solution of the Lagrange multiplier system, whose unknowns determine the nonlocal interface conditions between subdomains. Several two-dimensional numerical tests on problems as large as 191 million unknowns illustrate the strong and the weak scalability of our algorithm, which outperforms the standard approach to the distributed numerical solution of the problem. Finally, this work is the first rigorous numerical study in a two-dimensional multi-domain setting for nonlocal operators with finite horizon and, as such, it is a fundamental step towards increasing the use of nonlocal models in large scale simulations.

42 ENGINEERING↗
DOE OSTI2022

Data-driven modeling of power generation for a coal power plant under cycling

Increased penetration of renewables for power generation has negatively impacted the dynamics of conventional fossil fuel-based power plants. The power plants operating on the base load are forced to cycle, to adjust to the fluctuating power demands. This results in an inefficient operation of the coal power plants, which leads up to higher operating losses. To overcome such operational challenge associated with cycling and to develop an optimal process control, this work analyzes a set of models for predicting power generation. Moreover, the power generation is intrinsically affected by the state of the power plant components, and therefore our model development also incorporates additional power plant process variables while forecasting the power generation. We present and compare multiple state-of-the-art forecasting data-driven methods for power generation to determine the most adequate and accurate model. We also develop an interpretable attention-based transformer model to explain the importance of process variables during training and forecasting. The trained deep neural network (DNN) LSTM model has good accuracy in predicting gross power generation under various prediction horizons with/without cycling events and outperforms the other models for long-term forecasting. The DNN memory-based models show significant superiority over other state-of-the-art machine learning models for short, medium and long range predictions. The transformer-based model with attention enhances the selection of historical data for multi-horizon forecasting, and also allows to interpret the significance of internal power plant components on the power generation. This newly gained insights can be used by operation engineers to anticipate and monitor the health of power plant equipment during high cycling periods.

01 COAL, LIGNITE, AND PEAT↗