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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Artificial intelligence-based predictive modeling for imaging neutral particle analyzers on the DIII-D tokamak

The Imaging Neutral Particle Analyzer (INPA) at DIII-D is a diagnostic system used to accurately resolve the energy and spatial distributions of fast ions in fusion plasmas. A novel artificial intelligence (AI) technique named INPA-net is based on Reservoir Computing Networks and developed here to predict active and passive signals produced by charge-exchange reactions from injected and edge-cold neutrals, respectively, in magnetically confined fusion plasmas. This model is trained using a set of 21 time domain signals between 0 s to 3.35 s that includes injected beam and thermal plasma information, and 6444 real 2D experimental images of the INPA in 12 plasma discharges at DIII-D. The trained neural network is able to forecast experimental images in real-time. The model achieves an R-squared value of 0.91, which is higher than the 0.83 value achieved by a simple linear regression model. This improvement highlights the model's enhanced predictive accuracy for measured images from the validation set. This AI approach is valuable due to its rapid response times and potential for integration into real-time plasma control systems. A version of this model capable of generating syntehic images would be useful for the real-time monitoring of fast-ion transport. A comprehensive sensitivity study reveals that INPA-net maintains high performance even with variations in the input parameters, indicating the model's robustness and reliability. While developed for the INPA, the underlying architecture is adaptable and may be applied to various 2D imaging diagnostics in fusion research.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Cross-section measurements to low-lying excited final states in the 24 M(α,p) 27 Al*(γ) reaction as an energy source for x-ray bursts

Energy production in Type Ia x-ray bursts depends on a number of nuclear reactions that become efficient in a hot environment (up to 2 GK). Model sensitivity studies have been performed in an effort to better identify the reactions that have the largest effect, but these efforts are hampered by the high level of complexity of the astrophysical model and large nuclear physics uncertainties. In a recent study, the 24 Mg(α,p) 27 Al reaction was found to significantly affect the energy generation in x-ray bursts. This manuscript reports the first study of the 24 Mg(α,p 1,2 γ) 27 Al reaction at energies relevant for x-ray bursts. In conclusion, the branches to the 27 Al excited states increase to a small degree the estimates of the total astrophysical 24 Mg(α,p) 27 Al reaction rate.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Proton capture on 34 S in the astrophysical energy regime of O-Ne novae

Nuclear reaction sensitivity studies have shown that the final isotopic abundance of O-Ne nova nucleosynthesis is dependent on the 34 S(p,γ) 35 Cl reaction at astrophysical energies corresponding to peak nova burning temperatures of 0.1–0.4 GK. Isotopic ratios of the S, Cl, and Ar products are all used in various methods of cosmochemical analysis of presolar meteoritic grains. Due to the lack of direct experimental data, the 34 S+p reaction rate has been estimated using statistical modeling or information from indirect nucleon transfer experiments. In order to provide direct reaction information, here the resonance strengths of several low energy resonances, E c.m. = 272–495 keV, in the 34 S(p,γ) 35 Cl reaction were measured for the first time in inverse kinematics using the DRAGON recoil separator located at TRIUMF, Canada’s Particle Accelerator Centre in Vancouver.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Measurement of the Mo 100 ( α , x n ) cross section at weak r -process energies

Here, the weak r process in neutrino-driven winds following a core-collapse supernova is thought to contribute to the cosmic abundances of the first r-process peak elements between Se and Ag. Sensitivity studies have found that the early nucleosynthesis in the weak r process is primarily driven by (α, xn) reactions due to the high temperatures, and that current nuclear physics uncertainties in the (α, xn) rates result in significant uncertainties of the calculated abundances. The weak r-process path proceeds several nuclei away from stability where (α, xn) reaction cross sections have not yet been measured. In this paper we report the 100 Mo (α, xn) cross section (between 8.9 and 13.2 MeV in the center of mass, corresponding to 3.5–6.8 GK) in inverse kinematics using the Multi-Sampling Ionization Chamber (MUSIC) detector at the Argonne Tandem Linac Accelerator System (ATLAS) facility. With this first measurement of the 100 Mo (α, xn) cross section, we have demonstrated the ability of MUSIC to measure (α, xn) cross sections for A up to 100, therefore paving the way for further measurements with radioactive beams at ATLAS or the Facility for Rare Isotope Beams.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Population of the giant pairing vibration

Background: We present that the giant pairing vibration (GPV), a correlated two-nucleon mode in the second shell above the Fermi surface, has long been predicted and expected to be strongly populated in two-nucleon transfer cross sections similar to those of the normal pairing vibration. Recent experiments have provided evidence for this mode in 14,15 C but, despite sensitive studies, it has not been definitively identified in either Sn or Pb nuclei where pairing correlations are known to play a crucial role. Purpose: Our aim is to test whether features inherent to the mixing of bound and unbound levels might account for this and to study the effect in a simple and intuitively clear approach. Method: We study the mixing of unbound levels in a set of toy models that capture the essential physics of the GPV, along with a more realistic calculation including distorted-wave Born approximation transfer amplitudes. Results: The calculated (relative) cross section to populate a simulated GPV state is effectively low, compared to the case of bound levels with no widths Conclusions: The mixing turns out to be only a minor contributor to the weak population. Rather, the main reason is the melting of the GPV peak due to the width it acquires from the low orbital angular momentum single-particle states playing a dominant role in two-nucleon transfer amplitudes. Lastly, this effect, in addition to a severe Q-value mismatch, may account for the elusive nature of this mode in (t,p) and (p,t) reactions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

α -unbound levels in Ar 34 from Ar 36 ( p , t ) Ar 34 reaction measurements and implications for the astrophysical S 30 ( α , p ) Cl 33 reaction rate

The S 30 ( α , p ) Cl 33 reaction has been identified in several type-1 x-ray burst (XRB) sensitivity studies as a significant reaction within the α , p process, potentially influencing not only the abundances of burst ashes but also the bolometric shape of double-peaked light curves coming from certain XRB systems. Given the dearth of experimental data on the S 30 ( α , p ) Cl 33 reaction at burst temperatures, we have performed high energy-resolution forward-angle Ar 36 ( p , t ) Ar 34 measurements in order to identify levels in 34 Ar that could appear as resonances in the S 30 ( α , p ) Cl 33 reaction Energies of levels identified in this research, along with model-based assumptions for spin assignments and spectroscopic factors, were then used to determine a rate for the S 30 ( α , p ) Cl 33 reaction based on a narrow-resonance formalism. The rates determined in this work are then compared with two standard Hauser-Feshbach model predictions over a range of XRB temperatures.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Isomeric yield ratios of fission products: A missing piece in reactor antineutrino summation calculations

The calculation of the spectrum of antineutrinos ($\bar{v}_e$) from a reactor is a complicated problem requiring several nuclear data and physics inputs. Many of these have been investigated thoroughly to improve calculations and properly account for uncertainties. One input which has heretofore escaped consideration is the fission-yield distribution between ground and isomeric states. Here, in this work, we explore the effect of incorporating newly evaluated isomeric yield ratios (IYR) for 43 fission products into summation calculations and identify the disproportionate importance of certain isotopes, particularly at higher energies. Our analysis indicates that updated IYRs contribute to a significant increase in the $\bar{v}_e$ spectrum around and above 7 MeV, with increases of more than 50% at higher energies. Through a detailed sensitivity study, we highlight a number of isotopes for which the IYR has a substantial effect on the $\bar{v}_e$ spectrum. This work stresses the critical role of isomeric yields in calculations of reactor $\bar{v}_e$ spectra and points to the necessity for their accurate experimental determination, especially for key fission products, in order to refine our understanding and address the observed anomalies between measured and calculated $\bar{v}_e$ spectra.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Parameter Co-optimization for Hybrid Electric Vehicles Powertrain System Leveraging V2V/V2I Information

A parameter tuning based co-optimization scheme for the hybrid electric vehicles (HEV) powertrain system is designed to maximize the fuel efficiency. The optimization controlled input parameters are chosen based on sensitivity study of powertrain control parameters. The vehicle to vehicle (V2V) and vehicle to infrastructure information is another optimization input, to have the driving conditions taking in to considerations for maximizing fuel efficiency. The catalyst temperature is considered as an additional constraint as the speed to reach light-off temperature should not decrease during optimized operation. Neural network is used to develop a simplified yet equivalent model for the optimization problem model. We have achieved an average of 9.22% fuel savings for a random driving cycle on a Toyota Prius test model.

V2V, Cooptimization↗
DOE OSTI2016

Design Flexibility for Uncertain Distributed Generation from Photovoltaics

Uncertainty in the future adoption patterns for distributed energy resources (DERs) introduces a challenge for electric distribution system planning. This paper explores the potential for flexibility in design - also known as real options - to identify design solutions that may never emerge when future DER patterns are treated as deterministic. A test case for storage system design with uncertain distributed generation for solar photovoltaics (DGPV) demonstrates this approach and is used to study sensitivities to a range of techno-economic assumptions.

14 SOLAR ENERGY↗
DOE OSTI2020

A Nonlinear Regression Method for Composite Protection Modeling of Induction Motor Loads

Protection equipment are used to prevent damages to induction motor loads by isolating those from the power network in the event of severe faults. Modeling the response of induction motor loads and their protection is vital for power system planning and operation, especially in understanding system's response moments after a fault has occurred. This article proposes an optimization based framework to generate composite protection models for commercial building motor loads. Introducing a mathematical abstraction, the task of finding a suitable (simplified) model of the composite protection scheme is formulated as a nonlinear regression problem. Numerical examples are provided to illustrate the application of the framework.

Kundu, Soumya↗
DOE OSTI2021

The Sensitivity Analysis of Coil Misalignment for a 200-kW Dynamic Wireless Power Transfer System with an LCC-S and LCC-P Compensation

The dynamic wireless power transfer systems may reduce the battery size of electric vehicles while maintaining the travel range. Similar to the stationary wireless power transfer systems, the compensation networks are desired in dynamic wireless charging systems at the primary and secondary sides to reduce the reactive power requirement from the source and improve the efficiency. Consequently, it is essential to understand the behavior of the compensation networks, especially the sensitivity to misalignments. This paper presents a sensitivity analysis of LCC-S and LCC-P compensation networks for a 200-kW power transfer with variations in the coupling coefficient due to the electric vehicle travel and misalignments between the pads. The sensitivity study combines the electromagnetic finite element analysis and circuit analysis to determine the impact of misalignments on the wireless power transfer system characteristics. The theoretical analysis is verified by conducting circuit simulations at discrete points to verify the accuracy of the mathematical model.

Kavimandan, Utkarsh↗
DOE OSTI2019

HTS Dipole Prototype Magnet for NSLS X13A Endstation

This article reports the design, three-dimensional magnetostatic simulation results, coil fabrication, assembly, and low-temperature test results of a C-frame, iron-dominated high-temperature superconductor dipole magnet for ultra high vacuum magnetic-sensitive spectroscopy techniques at the National Synchrotron Light Source (NSLS) at Brookhaven National Laboratory. The magnet is required to provide fields up to ~1 T along two spatial directions. With an added capability to rotate about its vertical axis of symmetry, the magnet system is capable of delivering field along all three principal axes. The combination of this magnet and fast-switched, elliptically polarized soft X-rays produced by the NSLS elliptically polarized wiggler forms the basis for an excellent tool for polarization-sensitive studies of magnetic materials. The prototype magnet consists of a set of pancake coils fabricated from BSCCO tape reinforced with stainless steel. Those pancake coils are clamped in a low-carbon AISI 1006 grade steel pole and yoke assembly. For testing purposes, a cold He gas environment provided cooling the superconducting magnet to subtransition temperatures; for operation in an ultra high vacuum endstation environment, cooling can be provided by an external cryocooler. The low-temperature tests establish the safe-operating parameters needed to achieve the target magnetic field values. The measured magnetic field values are in close agreement with the magnetic simulation results, thereby confirming that the magnet design fulfills the performance requirements. Here, the final section of this article lists some suggestions to improve the magnet performance.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Quench Simulation and Validation for EIC Direct Wind Magnets

The Electron-Ion Collider (EIC), a new facility to be built in the United States at the U.S. Department of Energy’s Brookhaven National Laboratory in collaboration with Thomas Jefferson National Accelerator Facility-will be the only new particle collider in the U.S. for the next 10∼20 years. The EIC project will investigate the origin of mass and building blocks of the Universe. It will accelerate and collide beams of electrons with protons and nuclei. Unlike any collider that has ever existed before, both EIC’s particle beams will be polarized, meaning their spins will be aligned in a controlled way to allow for precision measurements. Different types of new superconducting magnets will be required near the interaction region (IR) of EIC. A 6-around-1 NbTi cable will be used for some of those new superconducting magnets. Given the relatively smaller conductors used for those direct wind magnets, the overall engineering current density will be 2–3 times higher in comparison to traditional collared superconducting magnets in other accelerator magnets. This is technically challenging and potentially represents high risks for quench protection. Here, in this paper we use different tools and methods for quench simulation for several EIC direct wind magnets. We also present results of a sensitivity study, exploring different material properties and Jc curves. This paper also discusses and validates the quench simulation results with measurement results from a small-scale serpentine magnet tested at BNL in October 2024.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Hierarchical Convolutional Neural Networks for Event Classification on PMU Measurements

Event classification is one of the central components of automated disturbance analysis based on PMU measurements. Obtaining high-quality event labels remains a challenge for supervised learning-based classification of local and system-wide events in power grids due to its labor-intensive requirement. We present a sensitivity study considering rapidly refined, partially and fully inspected event labels that leads to evidence that hierarchical convolutional neural networks (HCNNs) outperform traditional classification models regardless of the quality of the available event labels. Furthermore, it is demonstrated that performance similar to the one obtained using entirely domain-driven labeling can be achieved as long as the involved expert does not mislabel more than ~5% of the event data captured by PMU measurements.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Potential seal bypass and caprock storage produced by deformation-band-to-opening-mode-fracture transition at the reservoir/caprock interface

Here, we examined the potential impact on CO 2 transport of zones of deformation bands in reservoir rock that transition to opening-mode fractures within overlying caprock. Sedimentological and petrophysical measurements were collected along an approximately 5 m × 5 m outcrop of the Slick Rock and Earthy Members of the Entrada Sandstone on the eastern flank of the San Rafael Swell, Utah, USA. Measured deformation band permeability (2 mD) within the reservoir facies is about three orders of magnitude lower than the host sandstone. Average permeability of the caprock facies (0.0005 mD) is about seven orders of magnitude lower than the host sandstone. Aperture-based permeability estimates of the opening-mode caprock fractures are high (3.3 × 10 7 mD). High-resolution CO 2 –H 2 O transport models incorporate these permeability data at the millimeter scale. We then varied fault properties at the reservoir/caprock interface between open fractures and deformation bands as part of a sensitivity study. Numerical modeling results suggest that zones of deformation bands within the reservoir strongly compartmentalize reservoir pressures largely blocking lateral, cross-fault flow of supercritical CO 2 . Significant vertical CO 2 transport into the caprock occurred in some scenarios along opening-mode fractures. The magnitude of this vertical CO 2 transport depends on the small-scale geometry of the contact between the opening-mode fracture and the zone of deformation bands, as well as the degree to which fractures penetrate caprock. Finally, the presence of relatively permeable units within the caprock allows storage of significant volumes of CO 2 , particularly when the fracture network does not extend all the way through the caprock.

58 GEOSCIENCES↗
DOE OSTI2018

The role of fault-zone architectural elements and basal altered zones on pore pressure propagation and induced seismicity

Here, we used hydrogeologic models to assess how fault-zone properties promote or inhibit the downward propagation of fluid overpressures from a basal reservoir injection well (150 m from fault zone, Q = 5000 m 3 /day) into the underlying crystalline basement rocks. We varied the permeability of the fault-zone architectural components and a crystalline basement weathered layer as part of a numerical sensitivity study. Realistic conduit-barrier style fault zones effectively transmit elevated pore pressures associated with four years of continuous injection to depths of ~2.5 km within the crystalline basement while compartmentalizing fluid flow within the injection reservoir. The presence of a laterally continuous, relatively low-permeability altered/weathered basement horizon (k altered layer = 0.1 × k basement ) can limit the penetration depth of the pressure front to ~500 m. On the other hand, the presence of a discontinuous altered/weathered horizon that partially confines the injection reservoir without blocking the fault fluid conduit promotes downward propagation of pressures. Permeability enhancement via hydromechanical failure was found to increase the depth of early-time pressure front migration by a factor of 1.3 to 1.85. Dynamic permeability models may help explain seismicity at depths of >10 km such as is observed within the Permian Basin, NM.

58 GEOSCIENCES↗
DOE OSTI2024

Optimization of a High Pressure Turbine Blade and Sector-Based Annular Rig Design for Supercritical CO2 Power Cycle Representative Testing

Abstract As part of the ongoing research into the design of hardware for zero emission cycles, a first-stage high-pressure turbine (HPT) blade is optimized for a 300 MWe supercritical CO2 (sCO2) power cycle using the surrogate-assisted genetic algorithm optimizer in Numeca FINE/Design three-dimensional with objectives of increasing efficiency and decreasing heat load to the blade. Supercritical CO2 property tables are constructed from NIST REFPROP data for the condensable gas simulation in FINE/Turbo. A detailed mesh sensitivity study is performed for a baseline design to identify the proper-grid refinement and efficiently allocate resources for the optimization. Seventy design variables are selected for the initial population generation. Self-organizing maps are then used to focus the design variables on the most important ones affecting the objective functions. The optimization results in approximately 3000 three-dimensional Reynolds Averaged Navier Stokes simulations of different blade shapes with increases in efficiency of up to 0.85% and decreases in heat load of 14%. Families of blade shapes are identified for experimental testing in an annular rig at the Purdue Experimental Turbine Aerothermal Laboratory. A design to adapt the annular cascade for testing optimized geometries is introduced, which features eccentric radius sectors allowing for scaled-up geometries of sCO2 optimized blade profiles to be tested at design cycle representative conditions at high Reynolds numbers in dry air. Analysis into the effects of Reynolds number, working fluid, and geometric relations are presented to prove the efficacy of the test method.

Engineering↗
DOE OSTI2024

Material Model Parameters Optimization in Liquid Mercury Target Dynamics Simulation With Machine Learning Surrogates

A pulsed spallation target is subjected to very short (∼0.7μs) but intense loads (23.3 kJ) from repeated proton pulses, which knock away neutrons from the mercury atoms’ nuclei for a wide range application in physics, engineering, medicine, petroleum exploration, biology, chemistry, etc. The effect of this pulsed loading on the stainless-steel target module which contains the flowing mercury target material is difficult to predict not only due to its short but intense explosive-like physical reaction, but also the nonlinear material behavior of the liquid mercury in the structure. Injecting small helium bubbles in the mercury has been an efficient method of mitigating the pressure wave at high power level stage. However, prediction of the resultant loading on the target is more difficult when helium gas is intentionally injected into the mercury. A 2-phase material model that incorporates the Rayleigh-Plesset (R-P) model is expected to address this complex multi-physics dynamics problem by including the bubble dynamics in the liquid mercury. A parameter sensitivity study was firstly employed to understand their impact on the simulation strains. The investigated parameters included E, μ, γ, σ, n, VFgas, and gas cumulative volume curve control parameters a and b. Verification and validation results from sparse polynomial expansions (SPE) method and directional Gaussian smoothing (DGS) optimization show that the surrogate model had training error of ∼7% and validation error of ∼15%, indicating that machine learning methods and surrogate models can help optimize the uncertain parameters in the complex 2-phase material model. This approach is expected to fill the knowledge gap between unknown liquid-gas mixture material model and measured vessel strain responses.

Lin, Lianshan↗