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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Connecting ground-state properties of 6 Li to each other and to scattering data

We examine the relationship between the asymptotic normalization coefficient (ANC) of 6 Li and other low-energy observables in the α–deuteron system. Our analysis uses a set of calculations carried out within the ab initio no core shell model with continuum (NCSMC) using a variety of inter-nucleon interactions and basis sizes, and yielding 6 Li deuteron separation energies between 1.3 and 1.8 MeV (Hebborn et al 2022 Phys. Rev. Lett. 129 042503). These NCSMC calculations show that the square of the ANC is strongly correlated with the separation energy over this range. In this work, we investigate the origin of this correlation using the phenomenological R-matrix, a single-channel potential and a perturbative approach. We show that this correlation occurs because the depth of the α–deuteron central potential changes by only a small relative amount as the separation energy varies. We then investigate if the ANC can be accurately extracted from α–deuteron phase shifts in an ideal case in which low-energy data are available and there are no experimental errors. We find that both R-matrix and Coulomb-modified effective-range theory (CM-ERE) yield extracted ANCs close to, although not exactly equal to, the NCSMC value, provided the extrapolation is constrained by the known position of the bound-state pole and at least three terms are included in the fit function. The R-matrix approach converges faster than the CM-ERE as the number of parameters increases and is also more robust against the inclusion of low-energy and high-energy phase shift data. Finally, our study also shows that a naive quantification of uncertainties by comparing different truncations used in both theories is not accurate, and suggests the accuracy of ANCs extracted from phase shift data needs further investigation.

R-matrix↗
DOE OSTI2020

Beam characterization at NSRL for radiobiological experiments—phase 1

An experimental campaign was carried out at the NASA Space Radiation Laboratory to perform an additional, independent dosimetric characterization of the beams of protons, helium and carbon ions for radiobiological experiments. The campaign was undertaken by the request and with the support from the National Cancer Institute, U.S. In this initial phase, the goals were to obtain a first assessment of the dosimetric reproducibility of the beam control system, including analysis of spatial homogeneity and evaluation of ion beam contamination. They should facilitate the design of further experimental campaigns for beam characterization for radiobiological experiments. Measurements included reference dosimetry with comparison of in-house and external ionization chambers and electrometers, lateral-dose profile measurements in air, depth-dose profile in a water tank, evaluation of water equivalent thickness of a HDPE binary range shifter and estimation of impurities of the investigated helium-ion beam. The experiments and results are presented.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Environmental risks and opportunities of orphaned oil and gas wells in the United States

Abstract Hundreds of thousands of documented and undocumented orphaned oil and gas wells exist in the United States (U.S.). These wells have the potential to contaminate water supplies, degrade ecosystems, and emit methane and other air pollutants. Thus, orphaned wells present risks to climate stability and to environmental and human health, which can be reduced by plugging. To quantify environmental risks and opportunities of well plugging at the national level, we analyze data on 81 857 documented orphaned wells across the U.S. We find that > 4.6 million people live within 1 km of a documented orphaned well. 35% of the documented orphaned wells are located within 1 km of a domestic groundwater well, yet only 8% of the wells have groundwater quality data within a 1 km radius. Methane emissions from the documented orphaned wells represent approximately 3%–6% of total U.S. methane emissions from abandoned oil and gas wells, but this estimate is based on measurements at < 0.03% of U.S. abandoned wells. 91% of the documented orphaned wells overlie formations favorable for geologic storage of carbon dioxide and hydrogen, meaning that orphaned well plugging can reduce leakage risks from future storage projects. Finally, we estimate plugging costs for documented orphaned wells to exceed the $4.7 billion federal funding by 30%–80%, emphasizing the importance of prioritizing federal spending on wells with large remediation benefits. Overall, environmental monitoring data are not extensive enough to quantify risks, especially those related to air and water quality and human health. Plugging orphaned wells can provide opportunities for geologic storage of carbon dioxide and hydrogen and geothermal energy development, thereby facilitating efforts to transition to net-zero energy systems. Our analysis on environmental risks and opportunities of orphaned wells provides a framework that can be used to manage the millions of documented and undocumented orphaned wells in the U.S. and abroad.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Probing the origin of the two-component structure of broad-line region by reverberation mapping of an extremely variable quasar

ABSTRACT The physical origins of quasar components, such as the broad-line region (BLR) and dust torus, remain under debate. To gain insights into them, we focused on changing-state quasars (CSQs) which provide a unique perspective through structural changes associated with accretion disc state transitions. We targeted SDSS J125809.31+351943.0, an extremely variable CSQ, to study its central core structure and kinematics. We conducted reverberation mapping with optical spectroscopy to explore the structure of the BLR and estimate the black hole mass. The results from Hβ reverberation mapping indicated a black hole mass of $10^{9.64^{+0.11}_{-0.20}}\rm {M_\odot }$. Additionally, we analysed variations in the optical to X-ray spectral indices, αox, before and after the state transition, to investigate the accretion disc. These variations in αox and the Eddington ratio (from 0.4 per cent to 2.4 per cent) exhibitied behaviour similar to state transitions observed in X-ray binary systems. Spectral analysis of Hβ revealed a predominantly double-peaked profile during dim periods, transitioning to include a single-peaked component as the quasar brightened, suggesting that Hβ contains a mixture of two components. Each of these components has its distinct characteristics: the first is a double-peaked profile that remains stable despite changes in the accretion rate, while the second is a variable single-peaked profile. Using time-lags from reverberation mapping, we estimated the spatial relationships between these BLR components, the accretion disc, and the dust torus. Our results suggest that the BLR consists of two distinct components, each differing in location and origin.

Nagoshi, Shumpei (ORCID:0000000326504322)↗
DOE OSTI2022

A Scalable Pipeline for Gigapixel Whole Slide Imaging Analysis on Leadership Class HPC Systems

Whole Slide Imaging (WSI) captures microscopic details of a patient's histopathological features at multiple res-olutions organized across different levels. Images produced by WSI are gigapixel-sized, and saving a single image in memory requires a few gigabytes which is scarce since a complicated model occupies tens of gigabytes. Performing a simple met-ric operation on these large images is also expensive. High-performance computing (HPC) can help us quickly analyze such large images using distributed training of complex deep learning models. One popular approach in analyzing these images is to divide a WSI image into smaller tiles (patches) and then train a simpler model with these reduced-sized but large numbers of patches. However, we need to solve three pre-processing challenges efficiently for pursuing this patch-based approach. 1) Creating small patches from a high-resolution image can result in a high number (hundreds of thousands per image) of patches. Storing and processing these images can be challenging due to a large number of I/O and arithmetic operations. To reduce I/Oand memory accesses, an optimal balance between the size and number of patches must exist to reduce I/O and memory accesses. 2) WSI images may have tiny annotated regions for cancer tissue and a significant portion with normal and fatty tissues; correct patch sampling should avoid dataset imbalance. 3) storing and retrieving many patches to and from disk storage might incur I/O latency while training a deep learning model. An efficient distributed data loader should reduce I/O latency during the training and inference steps. This paper explores these three challenges and provides empirical and algorithmic solutions deployed on the Summit supercomputer hosted at the Oak Ridge Leadership Computing Facility.

Dash, Sajal↗
DOE OSTI2025

Hierarchical Speed Planner for Automated Vehicles: A Framework for Lagrangian Variable Speed Limit in Mixed-Autonomy Traffic

Here, this article presents a novel hierarchical speed planning framework for variable speed limits in mixed-autonomy traffic environments, leveraging server-side macroscopic control and vehicle-side microscopic execution. The framework integrates real-time traffic state estimation (TSE) and reinforcement learning (RL)-based control to mitigate congestion and improve traffic flow. A TSE enhancement module combines macroscopic data from sources like INRIX with high-resolution observations from connected autonomous vehicles (CAVs), enabling predictive modeling to address latency and noise. The target speed design module employs kernel smoothing and a buffer zone strategy to optimize traffic density and flow around bottlenecks. The proposed system was validated in the largest open-road test to date with 100 CAVs, demonstrating an overall 8% traffic density decrease, with a specific decrease of 7% upstream, 10% downstream, and a 52% decrease during the congestion formation phase at bottlenecks.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

FPGA Computing

The articles in this special section focus on cutting-edge research on topics that relate to field programmable gate arrays (FPGA) in computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Methods for Analysis and Quantification of Power System Resilience

This paper summarizes the report prepared by an IEEE PES Task Force. Resilience is a fairly new technical concept for power systems, and it is important to precisely delineate this concept for actual applications. As a critical infrastructure, power systems have to be prepared to survive rare but extreme incidents (natural catastrophes, extreme weather events, physical/cyber-attacks, equipment failure cascades, etc.) to guarantee power supply to the electricity-dependent economy and society. Thus, resilience needs to be integrated into planning and operational assessment to design and operate adequately resilient power systems. Quantification of resilience as a key performance indicator is important, together with costs and reliability. Quantification can analyze existing power systems and identify resilience improvements in future power systems. Given that a 100% resilient system is not economic (or even technically achievable), the degree of resilience should be transparent and comprehensible. Several gaps are identified to indicate further needs for research and development.

42 ENGINEERING↗
DOE OSTI2024

Adaptive Power Flow Approximations With Second-Order Sensitivity Insights

The power flow equations are fundamental to power system planning, analysis, and control. However, the inherent non-linearity and non-convexity of these equations present formidable obstacles in problem-solving processes. To mitigate these challenges, recent research has proposed adaptive power flow linearizations that aim to achieve accuracy over wide operating ranges. The accuracy of these approximations inherently depends on the curvature of the power flow equations within these ranges, which necessitates considering second-order sensitivities. In this paper, we leverage second-order sensitivities to both analyze and improve power flow approximations. We evaluate the curvature across broad operational ranges and subsequently utilize this information to inform the computation of various sample-based power flow approximation techniques. Additionally, we leverage second-order sensitivities to guide the development of rational approximations that yield linear constraints in optimization problems. In conclusion, this approach is extended to enhance accuracy beyond the limitations of linear functions across varied operational scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

A General Framework for Human-in-the-Loop Cognitive Digital Twins

Modelling and analysis of systems that are equipped with sensors and connected to the Internet are becoming more automated and less human-dependent. However, bringing expert knowledge into the loop along with data obtained from Internet of Thing (IoT) devices minimizes the risk of making poor and unexplainable decisions and helps to assess the impact of different strategies before applying them in reality. While Digital Twins are more of a data-driven simulation of the physical system, Cognitive Digital Twins bring the human dimension into the modelling and simulation. In this paper, we aim to emphasize the crucial role of explainability and the underlying rationale behind automated or interactive decision-making processes. Furthermore, we propose an initial framework that delineates the specific points within the feedback loop of a cognitive digital twin where human involvement can be incorporated.

Niloofar, Parisa↗
DOE OSTI2020

Performance of an Isobaric Hybrid Compressed Air Energy Storage System at Minimum Entropy Generation

Efficient, large-scale, and cost-effective energy storage systems provide a means of managing the inherent intermittency of renewable energy sources and drastically increasing their utilization. Compressed air energy storage (CAES) and its derivative architectures have received much attention as a viable solution; however, optimization objectives for these systems have not been thoroughly investigated in the literature. In this work, a hybrid thermal and compressed air energy storage (HT-CAES) system is investigated that mitigates the shortcomings of the otherwise attractive conventional CAES systems and its derivatives—shortcomings such as strict geological locations, low energy densities, and the production of greenhouse gas emissions. The HT-CAES system allows a portion of the available energy to operate a compressor and the remainder to be converted and stored in the form of heat through joule/resistive heating in a high-temperature, sensible, thermal energy storage medium. Internally reversible and irreversible HT-CAES system assumptions were investigated, in addition to regenerative and non-regenerative design configurations. Several system optimization criteria were examined—including maximum energy efficiency, maximum exergy efficiency, maximum work output, and minimum entropy generation—with a focus on whether the latter may lead to conclusive design guidelines in a real system. It is shown that an HT-CAES system designed based on a minimum entropy generation objective may operate at a lower energy and exergy efficiency as well as lower output power than otherwise achievable. Furthermore, optimization objective equivalence is shown to be limited to certain design conditions.

25 ENERGY STORAGE↗
DOE OSTI2020

Measurement of Convective Heat Transfer Coefficients With Supercritical CO 2 Using the Wilson-Plot Technique

This paper describes the measurement of convective heat transfer coefficients and friction factors for sCO 2 flowing in a smooth tube and compares the results with published correlations for validation. The paper also describes the Heat Exchange and Experimental Testing (HEET) rig recently designed and built at the U.S. Department of Energy’s (DoE’s) National Energy Technology Laboratory (NETL) in Morgantown, WV. Here, the Wilson-plot technique used for measuring the heat transfer coefficients is described along with the data reduction process. The Wilson-plot technique was chosen as the basis for the design of NETL’s HEET rig. Advantages of the Wilson-plot technique include the (1) ability to measure high convective heat transfer coefficients accurately, (2) ability to measure average heat transfer coefficient for complicated heat exchange geometries like those produced using additive manufacturing, (3) ability to measure heat transfer coefficients on both sides of a heat exchanger independently, and (4) simplicity of experimental setup. Capabilities of the HEET rig include pressure to 24 MPa (3500 psig), temperature to 538 °C (1000 °F), mass flow rate to 1.5 kg/s (3 lb/s), and Re to 500,000. The rig is designed to operate with pure CO 2 or a mixture of CO 2 and up to 10% N2 by volume to study the impact of gas mixtures typical of direct-fired sCO 2 power cycles on the convective heat transfer and pressure drop. Preliminary tests in the HEET rig were performed with smooth stainless-steel tube and pure CO 2 , and the results were compared with published correlations for Nusselt number (Nu) and friction factor. Over a Reynolds number (Re) range from 58,000 to 228,000, measured Nu was compared to predictions using the Dittus and Boelter equation (Kreith and Bohn, 1993, “Principles of Heat Transfer, West Publishing Company”) within 5% and measured friction factors were compared to predictions using the McAdams correlation (“McAdams, 1954, “Heat Transmission,” 3rd ed., McGraw Hill, New York)” for smooth tube to be within 5%.

42 ENGINEERING↗
DOE OSTI2020

Co-Pyrolysis of Chicken and Cow Manure

Conventional pyrolysis is a relatively simple way for biochar production; however, a single biomass feedstock approach is not promising for the development of multiple properties of biochar used in various applications. Here, this study provides a detailed comparison in terms of pyrolysis kinetics between the cow manure and chicken manure, in addition to the co-pyrolysis by mixing the two livestock at different ratios. Eight different heating rates were tested, 5–40 °C/min with 5 °C/min step, on both livestock using the nitrogen as a gas agent with a flowrate of 50 ml/min. The initial results show that for the slow heating rates, 5 °C/min, the thermal degradation of the cow manure is different compared to that obtained from chicken manure. For the cow manure, the first peak, associated with hemicellulose decomposition, is higher than the second peak, associated with cellulose decomposition, which is the other way around for chicken manure. At 5 °C /min, the hemicellulose decomposition took place at 250 °C and 300 °C for the chicken manure and cow manure, respectively. The cellulose decomposition was started at 300 °C for chicken manure and 470 °C for cow manure. The lowest heat rate was selected for the co-pyrolysis case study to allow a quasi-equilibrium state to avoid measurement errors and heat transfer limitation in terms of thermal lag. Co-pyrolysis is studied with different blend ratios between the chicken and cow manure, where the 40% cow manure shows a positive result in terms of keeping an exothermic reaction over the co-pyrolysis process.

09 BIOMASS FUELS↗
DOE OSTI2020

The Power Reclamation of Utilizing Micro-Hydro Turbines in the Aeration Basins of Wastewater Treatment Plants

Upgrading the aeration basin technology can improve the oxygen transfer efficiency (OTE), while keeping the energy consumption at its minimum level. Therefore, this paper introduces a new idea of installing micro-propeller turbines in the aeration basin of a wastewater treatment plant (WWTP) to extract power from the high-velocity location in the water column. This extracted power can be used to operate a mixer at the top of the membrane to induce the mixing in that region, which will drive the less oxygenated wastewater into the water column. The rest of the extracted power will rotate microturbine rotors for electric power generation. By applying the proposed microturbines to the 13 audited facilities, it was demonstrated to achieve a gross annual energy-savings of 3,836.9 MWh, a gross annual cost-saving of $260,497, and total CO 2 emissions that would be reduced by 2,714 metric tons/year. Generally, the addition of the proposed microturbines can save up to 15.7% of the annual plant electricity consumption (1.3–12.8% of the plant annual electricity bills).

13 HYDRO ENERGY↗