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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Universality in the Near-Side Energy-Energy Correlator

We investigate the energy-energy correlator (EEC) of hadrons produced on the same side in e + e − annihilation or in leading jets in p p collisions. We observe a remarkable universality of the correlator. Using a nonperturbative transverse momentum dependent (TMD) fragmentation function to model the transition from the “free-hadron” region to the perturbative collinear region, we are able to describe the near-side shapes and peaks over a wide range of energy for both the e + e − annihilation and the p p jet substructure measurements in terms of just two parameters. We present further predictions for the ratio of the projected three-point energy correlator to the EEC. The excellent agreement between our calculations and the experimental data may provide new insights into the role of nonperturbative physics for EECs, and suggests the possibility of exploring nonperturbative TMDs using theoretical tools developed for the energy correlators. Published by the American Physical Society 2025

Liu, Xiaohui (ORCID:0000000277011205)↗
DOE OSTI2020

Transverse energy–energy correlations of jets in the electron–proton deep inelastic scattering at HERA

We study the event shape variables, transverse energy–energy correlation TEEC (cosφ) and its asymmetry ATEEC (cosφ) in deep inelastic scattering (DIS) at the electron–proton collider HERA, where φ is the angle between two jets defined using a transverse-momentum (k T ) jet algorithm. At HERA, jets are defined in the Breit frame, and the leading nontrivial transverse energy–energy correlations arise from the 3-jet configurations. With the help of the NLOJET++, these functions are calculated in the leading order (LO) and the next-to-leading order (NLO) approximations in QCD at the electron–proton center-of-mass energy $\sqrt{s}$ = 314 GeV. We restrict the angular region to -0.8 ≤ cosφ ≤ 0.8, as the forward- and backward-angular regions require resummed logarithmic corrections, which we have neglected in this work. Following experimental jet-analysis at HERA, we restrict the DIS-variables x, y = Q 2 /(xs), where Q 2 = -q 2 is the negative of the momentum transfer squared q 2 , to 0 ≤ x ≤ 1, 0.2 ≤ y ≤ 0.6, and the pseudo-rapidity variable in the laboratory frame (η lab ) to the range -1 ≤ η lab ≤ 2.5. The TEEC and ATEEC functions are worked out for two ranges in Q 2 , defined by 5.5GeV 2 ≤ Q 2 ≤ 80GeV 2 , called the low-Q 2 -range, and 150GeV 2 ≤ Q 2 ≤ 1000GeV 2 , called the high-Q 2 -range. We show the sensitivity of these functions on the parton distribution functions (PDFs), the factorization (μ F ) and renormalization (μ R ) scales, and on α s (M$^2_Z$). Of these the correlations are stable against varying the scale μ F and the PDFs, but they do depend on μ R . For the choice of the scale μ R =$\sqrt{\langle ET \rangle^2+Q^2}$, advocated in earlier jet analysis at HERA, the shape variables TEEC and ATEEC are found perturbatively robust. These studies are useful in the analysis of the HERA data, including the determination of α s (M$^2_Z$) from the shape variables.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

2024 OES-Environmental 2024 State of the Science Report, Chapter 1: Marine Renewable Energy and Ocean Energy Systems-Environmental

For many countries, marine renewable energy (MRE) is the most recent entry into their renewable energy portfolio. MRE involves the generation of energy from the movement of seawater including tides, waves, and persistent ocean currents, as well as from the gradients of temperature and salinity in the oceans. Some countries also include energy generation from the open waters of large rivers as part of MRE. Each MRE resource requires a different type of device to harvest that energy, placed in the appropriate portion and depth of the ocean or large river and secured to the seabed either by weight or by anchors. At full scale, these devices are large; Figure 1.1 puts the size of these devices in the context of other technologies and well-known landmarks for scale. The MRE devices generally represent the largest devices available.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Assessing Ground State Energy of Molecules and Energy Profile of the NH3 Capturing CO2 System Using the Quantum Computing Algorithms

Molecule size correlates with the number of electrons on electronic energies and strength of anharmonicity on vibrational properties, however, it is challenging to address using classical computing. In this study, variational quantum eigensolver (VQE) algorithm was implemented on a quantum simulator to quantify electronic and vibrational energies and reaction pathways of CO2 + NH3 = NH2COOH. The VQE-based Hartree-Fock-Embedding algorithm was adopted to benchmark electronic energies for a series of molecules (doi.org/10.1063/5.0188249) and quantify the reaction energy profile of the CO2 capture reaction (doi.org/10.1116/5.0137750). The generated reaction profile is in good agreement with the classical high-level Coupled-Cluster-Singles-and-Doubles (CCSD) results. The quantum computing algorithm also helps enhance the calculation of vibrational ground-state energies by considering the many-body coupling using the Vibrational Self-Consistent Field method, providing results for CO2 and NH3 molecules with accuracy comparable to the direct diagonalization method. Our approach indicates quantum computing can be applied to solve practical problems.

Lee, Yueh-Lin↗
DOE OSTI2020

RL-HEMS: Reinforcement Learning Based Home Energy Management System for HVAC Energy Optimization

Heating, ventilation, and air conditioning (HVAC) is one of the major energy consumers in the residential sector. It is important to be able to monitor and control the energy consumed to provide utility services such as load shaping while satisfying the comfort and economic constraints of the homeowner. The objective of this work is to create the optimal schedule for HVAC operation to reduce the cost while satisfying the home-owner and equipment’s constraints using a model-free Reinforcement Learning (RL)-based optimization. The specific goal is to find the right balance between reducing energy cost, consumption, and customer comfort level. Our research effort addresses this optimization problem using multiple components: the development of initial learning test-bed and implementation of RL techniques on a real home. This will enable the rapid evaluation of the RL techniques and provide an early baseline to train before implementation on site. The RL algorithm is designed to learn the energy use patterns and generate the optimized schedule for HVAC within an acceptable time-interval to satisfy the homeowner’s comfort and minimize the energy usage. Our preliminary results are promising and we have observed a 17% reduction in the total cost and a 15% reduction in the power utilization using our RL-based HVAC model—RL-HEMS.

Kotevska, Olivera↗
DOE OSTI2020

A Novel High Energy Density Sorption-based Thermal Battery for Low-grade Thermal Energy Storage

Thermal energy storage (TES) can alleviate peak demand on the electricity grid by offsetting building thermal loads, increasing the grid’s reliability and resilience. However, low energy density and poor energy performance of existing TES technologies limit their applications. Sorption-based thermal battery (STB) system is thus developed using three-phase sorption technology to harvest low-temperature heat, store it with a much higher energy density than common TES systems and dehumidify air or provide space cooling in buildings. Although STB has been experimentally proved to be feasible, influencing factors on its performance are still unknown by far. Therefore, this paper conducted a parametric analysis on crystallization and crystal dissolution performance of a developed STB test rig. The crystallization results showed that the energy density of the STB increased with reducing the solution flow rate and the cooling water temperature. The dissolution results showed that a higher discharge rate of the STB can be achieved with increasing the flow rate and temperature of inlet diluted solution. The work in this study is helpful to the optimal design and operation of the STB system.

Wang, Lingshi↗
DOE OSTI2021

Market-based Co-optimization of Energy and Ancillary Services with Distributed Energy Resource Flexibilities

Energy storage systems and flexible loads have attracted significant interests due to their capabilities to provide various grid services. In this paper, the flexibilities are optimally allocated among multiple distributed energy resource aggregators with energy storage systems and flexible buildings by the utility coordinator through market-based co-optimization. An iterative market clearing algorithm is developed to determine the optimal energy and ancillary service prices, with consideration of both local dynamics and network constraints. Simulation results demonstrate the effectiveness of the proposed algorithm and the benefits of co-optimizing the energy and ancillary service markets.

Ma, Ke↗
DOE OSTI2024

Transforming Energy Through Computational Excellence: NREL HPC Resources for High Performance Computing for Energy Innovation (HPC4EI) Program

NREL hosts computing facilities for the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE). In 2024, NREL introduced Kestrel, the 3rd generation, EERE-sponsored supercomputer dedicated to renewable energy and energy efficiency research. Kestrel has already been used for hundreds of research projects by NREL, other national laboratories, and university partners. This includes HPC4EI-sponsored industrial partnerships.

high-performance computing↗
DOE OSTI2026

Constraints on Dynamical Dark Energy from Multiple Probes in the Full Dark Energy Survey

We present results on dark energy evolution, assuming a time-dependent equation of state $w(a)=w_0+w_a(1-a)$, from growth and geometric probes using the full six-year Dark Energy Survey dataset: type Ia supernovae, baryon acoustic oscillations, and weak gravitational lensing and galaxy clustering (3$\times$2pt). The combination yields $w_0=-0.84^{+0.10}_{-0.10}$ and $w_a=-0.44^{+0.60}_{-0.55}$, the tightest constraints ever obtained from a single survey, with $2.2σ$ deviation from a cosmological constant. Adding the DESI DR2 BAO data yields $w_0=-0.84^{+0.06}_{-0.07}$ and $w_a=-0.53^{+0.33}_{-0.28}$, representing the most stringent low-redshift-only test of dynamical dark energy to date, with a $2.3σ$ deviation. In this combination, adding 3$\times$2pt doubles the constraining power. Finally, when combined with primary CMB information, we obtain $w_0=-0.82^{+0.05}_{-0.05}$, $w_a=-0.63^{+0.21}_{-0.18}$, with a $3.0σ$ deviation. We find that including 3$\times$2pt in the previously studied SN + DESI BAO + CMB combination leaves the significance essentially unchanged ($3.2 σ$ to $3.0σ$) while improving the figure of merit by $\sim$10%. We systematically investigate the impact of leaving out each one of the probes and find that the significance of the deviation from a cosmological constant ranges from 2.3 to 3.2$σ$, with best-fit parameters consistently in the region $w_0 >-1$ and $w_a <0$. Excluding SN from the all data combination yields a $2.6σ$ departure from $Λ$CDM, providing a cross-check independent of supernova photometric calibration. These results support the weak preference for evolving dark energy reported by several recent cosmological analyses. By combining growth and geometric probes from a single survey, this work realizes the multi-probe dark energy program envisioned at the inception of DES.

Abbott, T. M.C. [Cerro-Tololo InterAmerican Obs.] ↗
DOE OSTI2026

Prioritizing Transformative Energy Efficiency Technologies in the Pulp and Paper Sector Through Levelized Cost of Conserved Energy

This presentation explores how the U.S. pulp and paper sector can prioritize energy efficiency (EE) technologies using the Levelized Cost of Conserved Energy (LCCE) metric. As mills face market shifts and rising costs, technologies such as advanced drying, membrane concentration, waste heat recovery, and recovery boiler replacements offer potential savings but face economic barriers. LCCE enables consistent comparison of technologies by calculating cost per unit of energy saved, including capital, operating, and potentially non-energy benefits like productivity, maintenance, and safety improvements. Preliminary findings show economies of scale significantly influence recovery boiler replacement feasibility, with larger systems achieving lower LCCE values. Ongoing work incorporates non-energy benefits to provide a more comprehensive cost-effectiveness assessment and guide research, development, and deployment priorities for underutilized and emerging technologies.

Kamath, Dipti [ORNL] (ORCID:0000000278739994)↗
DOE OSTI2023

Enhancing the Chemical Energy Flux in a High-Temperature Tubular Counterflow Solid Fuel Synthesis Reactor Using a Bypass

Redox reactions of metal oxides offer a path towards using intermittent renewable resources for high-density thermochemical energy storage. Thermochemical energy storage often involves the flow of a particulate media. We describe a novel method to increase the throughput in a gravity-driven high-temperature thermochemical storage reactor flowing pelletized MgMnO. The moving bed reactor operates under counter-flow conditions and encounters particle flowability problems at temperatures of 1500 °C leading to sintering of the bed. Inertial forces of a counter-flowing gas can overcome the gravitational forces on the particles and limit the chemical energy storage rate of the reactor. We found that the insertion of a gas bypass (a slotted tube) into the reactor results in a 100% increase of the flow rates and achieved a 50% higher chemical energy storage flux compared to the operation without a bypass tube while mitigating the effects of sintering on the particles. As a result, the higher solid flow rates require a longer heated zone to reach a comparable residence time and extent of reduction compared to the lower flow rates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Reserve Model of Energy Storage in Day-ahead Joint Energy and Reserve Markets: A Stochastic UC Solution

With many favorable advantages including fast response ability in particular, utility-level energy storage systems (ESS) are being integrated into energy and reserve markets to help mitigate uncertain renewable resources and fluctuant demands. This paper discusses a stochastic unit commitment (UC) model to explore capabilities of ESSs in providing valuable grid services by simultaneously joining energy and reserve markets. The proposed reserve model of ESSs presents the following features: (i) two constraints are proposed to formulate ESS’s reserve provision ability in each hour via six operation modes, namely increasing/reducing the level of charge, switching to discharge, increasing/reducing the level of discharge, switching to charge; (ii) as an energy-limited asset, constraints on ESS’s reserve deliverability across multiple hours is introduced to hold enough state of charge (SOC) headroom and floor room, guaranteeing that reserves cleared in individual hours are continuously deliverable over multiple successive hours without violating operation limits. Furthermore, a scenario-based UC model, which addresses uncertainties of renewables and demands, is adopted to evaluate reserves provided by ESSs and generators. To effectively solve the stochastic UC problem, the progressive hedging algorithm with heuristic approaches is discussed. A 6-bus system and a modified IEEE 118-bus system are used to illustrate effectiveness of the proposed approaches.

25 ENERGY STORAGE↗
DOE OSTI2021

The Importance of Weather and Climate to Energy Systems: A Workshop on Next Generation Challenges in Energy–Climate Modeling

More than 80 international participants, representing weather, climate, and energy systems research, joined two 4-hour remote sessions to highlight and prioritize ongoing and future challenges in energy-climate modelling. The workshop had two primary goals: to build a deeper engagement across the “energy” and “climate” research communities, and to identify and begin to address the scientific challenges associated with modelling climate risk in energy systems.

17 WIND ENERGY↗
DOE OSTI2020

Planning Considerations for Energy Storage in Resilience Applications. Outcomes from the NELHA Energy Storage Conference's Policy and Regulatory Workshop

This report presents the proceedings and lessons learned at a conference workshop that discussed the role of energy storage in supporting electric system resilience, which took place at the Natural Energy Laboratory of Hawaii Authority’s (NELHA) Conference on Energy Storage Trends and Opportunities in December 2018. Staff from the Pacific Northwest National Laboratory (PNNL) made two presentations on the topic of resilience: the first covering a conceptual framework for incorporating resilience into resource planning processes, and the second covering a tool developed for microgrid planning that can assist in identifying resource mixes that will meet site-specific resilience needs. Throughout the presentations, presenters and workshop participants discussed the obstacles to improving electric system resilience and potential solutions for overcoming them. Following the workshop, the authors conducted additional research to further contextualize the topics discussed at the workshop and to frame the resulting recommendations for future engagement on this subject by the Department of Energy and the national laboratories.

25 ENERGY STORAGE↗
DOE OSTI2025

Leading Energy Analysis: Data-Driven Insights That Power Our Energy Future

Energy analysts at the National Renewable Energy Laboratory (NREL) use a broad set of expertise and cutting-edge tools to capture the complexities of our interconnected energy system. Decision-makers rely on these insights to drive cost savings, enhance grid reliability, support long-term innovation, and bolster America's energy workforce and global competitiveness. This fact sheet highlights some of NREL's high-impact analyses, data, and tools, largely focusing on power grid analysis.

data↗
DOE OSTI2026

Energy 101 Marine Energy [Slides]

The Energy 101: Marine presentation, developed for the Energy Technology Innovation Partnership Project (ETIPP), provides an overview of marine energy. It covers technology fundamental concepts, opportunities, and case studies.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

The wave energy converter control competition (WECCCOMP): Wave energy control algorithms compared in both simulation and tank testing

The wave energy control competition established a benchmark problem which was offered as an open challenge to the wave energy system control community. The competition had two stages: In the first stage, competitors used a standard wave energy simulation platform (WEC-Sim) to evaluate their controllers while, in the second stage, competitors were invited to test their controllers in a real-time implementation on a prototype system in a wave tank. The performance function used was based on converted energy across a range of standard sea states, but also included aspects related to economic performance, such as peak/average power, peak force, etc. This paper compares simulated and experimental results and, in particular, examines if the results obtained in a linear system simulation are borne out in reality. Overall, within the scope of the device tested, the range of sea states employed, and the performance metric used, the conclusion is that high-performance WEC controllers work well in practice, with good carry-over from simulation to experimentation. However, the availability of a good WEC mathematical model is deemed to be crucial.

16 TIDAL AND WAVE POWER↗