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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A systematic feature extraction and selection framework for data-driven whole-building automated fault detection and diagnostics in commercial buildings

In data-driven automated fault detection and diagnostics (AFDD) modeling for building energy systems, feature engineering is a critical process of extracting information from high-dimensional and noisy sensor measurement and turning it into informative and representative inputs or features for data-driven modeling. However, few studies specifically discuss the feature engineering, especially the interactions between feature extraction and feature selection in whole-building AFDD. We developed a systematic feature extraction and selection framework for whole-building AFDD. In this framework, features are aggressively extracted from raw sensor data using statistical feature extraction techniques with various window sizes and statistics. With many features extracted, a hybrid feature selection algorithm that combines the filter and wrapper method then selects the best feature set. The framework considers diversity in the duration of fault behavior among fault types in whole-building AFDD, thus achieving high model generalization. We implemented our developed framework in a virtual testbed calibrated with measured data from Oak Ridge National Laboratory's Flexible Research Platform designed to mimic the operation of a typical small commercial building. The AFDD model is trained by the simulation data generated from the virtual testbed. The results show that (1) the developed framework improves the generalization of the AFDD model by 10.7% compared with literature-reported feature extraction and selection methods and (2) features with diverse window sizes and statistics are selected, providing insight into physical systems beyond the current understanding of buildings and faults and improving the detection and diagnostics of multiple fault types.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

An energy-based coupling approach to nonlocal interface problems.

Nonlocal models provide accurate representations of physical phenomena ranging from fracture mechanics to complex subsurface flows, settings in which traditional partial differential equation models fail to capture effects caused by long-range forces at the microscale and mesoscale. However, the application of nonlocal models to problems involving interfaces, such as multimaterial simulations and fluid-structure interaction, is hampered by the lack of a physically consistent interface theory which is needed to support numerical developments and, among other features, reduces to classical models in the limit as the extent of nonlocal interactions vanish. In this paper, we use an energy-based approach to develop a formulation of a nonlocal interface problem which provides a physically consistent extension of the classical perfect interface formulation for partial differential equations. Numerical examples in one and two dimensions validate the proposed framework and demonstrate the scope of our theory.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

A technical analog of the cosmological constant problem and a solution thereof

The near vanishing of the cosmological constant is one of the most puzzling open problems in theoretical physics. We consider a system, the so-called framid, that features a technically similar problem. Its stress-energy tensor has a Lorentz-invariant expectation value on the ground state, yet there are no standard, symmetry-based selection rules enforcing this, since the ground state spontaneously breaks boosts. We verify the Lorentz invariance of the expectation value in question with explicit one-loop computations. These, however, yield the expected result only thanks to highly nontrivial cancellations, which are quite mysterious from the low-energy effective theory viewpoint.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Digital Twin Empowered PV Power Prediction

The accurate prediction of photovoltaic (PV) power generation is significant to ensure the economic and safe operation of power systems. To this end, the paper proposes a new digital twin (DT) empowered PV power prediction framework that is capable of ensuring reliable data transmission and employing the DT to achieve high accuracy of power prediction. With this framework, considering potential data contamination in the collected PV data, a generative adversarial network is employed to restore the historical data set, which offers a prerequisite to ensure accurate mapping from the physical space to the digital space. Further, a new DT empowered PV power prediction method is proposed. Therein, we model a DT that encompasses a digital physical model for reflecting the physical operation mechanism and a neural network model (i.e., a parallel network of convolution and bidirectional long-short-term memory model) for capturing the hidden spatial-temporal features. The proposed method enables the use of the DT to take advantages of the digital physical model and the neural network model, resulting in enhanced prediction accuracy. Finally, a real data set is conducted to access the effectiveness of the proposed method.

14 SOLAR ENERGY↗
DOE OSTI2021

The impact of different parameterizations on the interpretation of CP violation in neutrino oscillations

CP violation in the lepton mass matrix will be probed with good precision in upcoming experiments. The amount of CP violation present in oscillations can be quantified in numerous ways and is typically parameterized by the complex phase δ PDG in the standard PDG definition of the lepton mixing matrix. There are additional parameterizations of the lepton mixing matrix as well. Through various examples, we explore how, given the current data, different parameterizations can lead to different conclusions when working with parameterization dependent variables, such as δ. We demonstrate how the smallness of |U e3 | governs the scale of these results. We then demonstrate how δ can be misleading and argue that the Jarlskog is the cleanest means of presenting the amount of CP violation in the lepton sector. We also confirm that, among the different parameterizations considered, the standard PDG parameterization has a number of convenient features.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Evolution of low-lying M1 modes in germanium isotopes

Magnetic dipole strength functions are determined for the series of germanium isotopes from N=Z=32 to N = 48 on the basis of a large number of transition strengths calculated within the shell model. The evolution of the strength with increasing neutron number in the 1g 9/2 orbital is analyzed. A bimodal structure comprising an enhancement toward low transition energy and a resonance in the region of the scissors mode is identified. The low-energy enhancement is strongest near closed shells, in particular at the almost completely filled 1g 9/2 orbital, while the scissorslike resonance is most pronounced in the middle of the open shell, which correlates with the magnitude of the also deduced electric quadrupole transition strengths. The results are consistent with previous findings for the shorter series of iron isotopes and prove the occurrence and correlation of the two low-lying magnetic dipole modes as a global structural feature.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

REopt Lite Tutorial: International Locations

NREL’s REopt Lite web tool helps users evaluate the economic viability of distributed photovoltaic (PV), wind, battery storage, combined heat and power, and thermal energy storage systems. REopt Lite was designed for locations within the United States; however, with appropriate adjustments, it is possible to use most of its features for international locations.

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

Evaluation of H-Canyon Ventilation Exhaust Tunnel Inspection at the Savannah River Site - 20052

The Department of Energy (DOE) H-Canyon Facility at the Savannah River Site (SRS) is operated by Savannah River Nuclear Solutions (SRNS). The Facility Structural Integrity Program [1] provides a process to inspect, evaluate, and document the conditions of passive safety related structural systems and components, their degradation mechanisms and their impact on the safety envelope. The Structural Integrity Program performs periodic visual inspections to confirm the systems and components can perform their safety function and recommend corrective actions before the function is compromised. The H-Canyon Exhaust Tunnel is part of the H-Canyon Ventilation System and is periodically inspected under the Structural Integrity Program. The Tunnel performs a Safety Class passive design feature function that is available 100% of the time. The underground reinforced concrete Tunnel directs Canyon process air from the Canyon to the Sand Filter System. The radiological and chemical airborne activity coupled with the physical configuration of the tunnel precludes a manned entry into the tunnel to perform the inspection. Unlike active systems that can be subjected to physical testing to confirm capability, qualification calculations, including modeling, is performed to assess passive design feature capabilities relative to operational, accident and natural phenomena hazards events. Input for these calculations come from knowledge of field conditions, design drawings and conservative assumptions. The knowledge of field conditions comes from concrete and soil testing activities as well as inspection data. The use of cameras on crawlers to obtain inspection data and how that data is used in qualification calculations is the focus of this discussion. Remote Tunnel inspections have been performed using cameras on a stick, referred to as pole cameras, prior to Calendar Year 2003 (CY2003). Since CY2003, six camera equipped crawlers have been used. Crawlers have evolved and improved by incorporating lessons learned from the previous inspections. The latest 2019 crawler successfully traveled the entire length of the tunnel between the Canyon and Sand Filter System and captured images that were previously unseen, thus providing key visual data for the Structural Integrity Program report [2]. The inspection data serves as 1) input to qualification calculations, 2) validates current conditions remain bounded by qualification calculations, and 3) documents a record of change over time. This data is vital for the effective evaluation of the tunnel structure and aids with predicting the life cycle service life safety envelope to protect the public, environment, and facility worker. The goal of the 2019 deployment was to use a more robust vehicle to ensure travel over obstacles, perform the inspection with higher resolution cameras, and have the ability to elevate the cameras to view surfaces previously obscured by abandon-in-place ducts in the tunnel. The inspection information will serve to strengthen the input basis for qualification calculations, versus using excessive conservative calculation assumptions. This 2019 inspection was compared with previous crawler visual evidence to identify change over time to project remaining service life and confirm field conditions remain bounded by qualification calculations. The results of the 2019 Exhaust Tunnel inspection continue to improve and provide a firm basis to make sound engineering judgements regarding tunnel capability and approaches in projecting remaining service life with an aging system and component. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Signals of a New Gauge Boson from IceCube and Muon g-2

Gauging the muon lepton flavor minus the tau lepton flavor number, which is a global symmetry of the SM, introduces a new gauge boson Z' upon symmetry breaking. Interestingly, it offers an economical solution to the long-standing g_µ-2 anomaly, confirmed and strengthened by recent measurements at Fermilab. Here, we revisit the impact of such a Z' on the spectrum of high-energy astrophysical neutrinos, as measured by the IceCube experiment. This spectrum has been observed to exhibit a dip-like feature at sub-PeV energies, which could plausibly arise from the physics of the sources themselves, but could also be the consequence of high-energy neutrinos resonantly scattering with the cosmic neutrino background, mediated by a Z' with a mass on the order of m_Z’ ~ 10 MeV. In this study, we calculate the impact of such a Z' on the high-energy neutrino spectrum for a variety of model parameters and source distributions. For couplings that can resolve the g-2 anomaly, we find that this model could self-consistently produce a spectral feature that is consistent with IceCube's measurement, in particular if the neutrinos observed by IceCube predominantly originate from high-redshift sources. We also briefly discuss a possible scenario where Z' could act as a portal to a dark sector.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Non-compact gauge groups, tensor fields and Yang-Mills-Einstein amplitudes

Abstract Scattering amplitudes in Yang-Mills-Einstein theories have been investigated mostly for compact gauge groups. While non-compact gauge groups are not physically viable in Yang-Mills theory, non-compact gaugings feature prominently in the supergravity literature, where any choice of perturbative vacuum spontaneously breaks the gauge group to a compact subgroup. In this paper, we formulate double-copy constructions for several five-dimensional$$ \mathcal{N} $$ N = 2 supergravities with non-compact gauge groups. On one side of the double copy, we employ amplitudes from a super-Yang-Mills theory with a massive hypermultiplet. On the other, we use amplitudes from particular non-supersymmetric Yang-Mills-scalar theories with massive fermions, chosen to obey constraints coming from color/kinematics duality. Supergravities with massive self-dual tensors in five dimensions are also considered, showing that tensors are straightforwardly realized as double copies of gauge-theory fermions with suitable choices of signs in the corresponding solutions of the Dirac equation. We present several examples of these constructions, noting in particular the appearance of Heisenberg groups in the supergravity gauge symmetry and, in some cases, the possibility of exotic tensor-vector matter couplings.

Physics↗
DOE OSTI2020

Neural-network accelerated coupled core-pedestal simulations with self-consistent transport of impurities and compatible with ITER IMAS

pedestal structure, current profile, and plasma equilibrium physics has been developed and tested against a DIII-D discharge. Here, key features of the achieved core-pedestal coupled workflow are its ability to account for the transport of impurities in the plasma self-consistently, as well as its use of machine learning accelerated models for the pedestal structure and for the turbulent transport physics. Notably, the coupled workflow is implemented within the OMFIT framework, and makes use of the ITER integrated modeling and analysis suite (IMAS) data structure for exchanging data among the physics codes that are involved in the simulations. Such technical advance has been facilitated by the development of a new numerical library named OMAS.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

High-performance data format for scientific data storage and analysis

Here, in this article, we present the High-Performance Output (HiPO) data format developed at Jefferson Laboratory for storing and analyzing data from Nuclear Physics experiments. The format was designed to efficiently store large amounts of experimental data, utilizing modern fast compression algorithms. The purpose of this development was to provide organized data in the output, facilitating access to relevant information within the large data files. The HiPO data format has features that are suited for storing raw detector data, reconstruction data, and the final physics analysis data efficiently, eliminating the need to do data conversions through the lifecycle of experimental data. The HiPO data format is implemented in C++ and JAVA, and provides bindings to FORTRAN, Python, and Julia, providing users with the choice of data analysis frameworks to use. In this paper, we will present the general design and functionalities of the HiPO library and compare the performance of the library with more established data formats used in data analysis in High Energy and Nuclear Physics (such as ROOT and Parquete). In columnar data analysis, HiPO surpasses established data formats in performance and can be effectively applied to data analysis in other scientific fields.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Exploration of Rayleigh-Taylor seeding mechanisms in laser- and pulsed-power-driven inertial fusion

The ubiquitous Rayleigh-Taylor instability (RTI) has been observed in fluids and plasmas in a wide range of parameter regimes from astrophysical to laboratory plasmas. In high-energy-density (HED) laboratory plasmas, such as laser-driven inertial confinement fusion (ICF) plasmas, the RTI can have a detrimental impact on achieving fusion ignition through the generation of hydrodynamic mix. Hence, an understanding of the seeding mechanisms that produce the RTI and identifying ways to mitigate hydrodynamic mix is of critical importance. Appropriately aligned magnetic fields have been known to stabilize short-wavelength RTI. A number of numerical and experimental studies have demonstrated the benefits of using imposed magnetic fields in laser-driven ICF to achieve higher ion temeratures, higher neutron yields, and a relaxation of the ignition criteria. This work addresses seeding mechanisms in laser-driven implosions to understand critical early-stage physics that ultimately leads to substantial growth of the RTI along with mechanisms for mitigation of this growth. Surface perturbations due to machining tolerances and single-feature seeds (for example due to fill tubes) can produce substantial RTI growth in the ignition-relevant high-convergence ratio targets for laser- driven ICF implosions. RTI growth from single-feature seeding in laser-based implosions has the potential to be mitigated through appropriately aligned externally applied magnetic fields and the goal of this work has been to quantify that numerically and experimentally. Resistive-magnetohydrodynamic (MHD) simu- lations are used to study the seeding and evolution of the RTI leveraging previous support from the DOE HEDLP program. Furthermore, experimental data has been obtained and applied towards code validation of unmagnetized and magnetized evolution of single-feature seeded RTI growth.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Mechanical Behavior of Additively Manufactured Molybdenum and Fabrication of Microtextured Composites

Refractory metals are a class of high-melting-temperature materials suitable for use in extreme environment applications. Interestingly, during additive manufacturing many pure refractory metals exhibit a switch from (001) to (111) build direction fiber preference with increasing surface energy density. Here we exploit this solidification physics to fabricate material with “mesoscale composite” engineered structures consisting of features with contrasting (001) and (111) build direction microtextures. Separately, elevated temperature tensile testing of EBM fabricated material with a randomized distribution of mixed (001)/(111)-fiber grains is shown to exhibit excellent properties. These results are utilized to build a crystal plasticity model for evaluating the local inelastic response of the composite mesoscale structures. Analysis of printed microstructures and microstructure-scale simulations indicate that both macro-scale and localized material behavior may be tailored. This strategy can be potentially used to synthesize materials with optimized performance for high-temperature applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An active learning high-throughput microstructure calibration framework for solving inverse structure–process problems in materials informatics

Determining a process–structure–property relationship is the holy grail of materials science, where both computational prediction in the forward direction and materials design in the inverse direction are essential. Problems in materials design are often considered in the context of process–property linkage by bypassing the materials structure, or in the context of structure–property linkage as in microstructure-sensitive design problems. However, there is a lack of research effort in studying materials design problems in the context of process–structure linkage, which has a great implication in reverse engineering. In this paper, given a target microstructure, we propose an active learning high-throughput microstructure calibration framework to derive a set of processing parameters, which can produce an optimal microstructure that is statistically equivalent to the target microstructure. The proposed framework is formulated as a noisy multi-objective optimization problem, where each objective function measures a deterministic or statistical difference of the same microstructure descriptor between a candidate microstructure and a target microstructure. Furthermore, to significantly reduce the physical waiting wall-time, we enable the high-throughput feature of the microstructure calibration framework by adopting an asynchronously parallel Bayesian optimization to exploit high-performance computing resources. Case studies in additive manufacturing and grain growth are used to demonstrate the applicability of the proposed framework, where kinetic Monte Carlo (kMC) simulation is used as a forward predictive model, such that for a given target microstructure, the target processing parameters that produced this microstructure are successfully recovered.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Multi-scale and multi-physics analysis, design optimization, and experimental validation of heat exchangers utilizing high performance, non-round tubes

Air-to-refrigerant heat exchangers (HXs) are fundamental components in HVAC&R systems, and considerable research has been dedicated designing continually smaller, lighter, and more efficient HX designs. In recent years, researchers have leveraged advancements in Computational Fluid Dynamics (CFD), Finite Element Analysis (FEA), and optimization algorithms to consider primary tube shape and topology optimization to design highly compact, high performance HXs for a multitude of applications. In this research, we present a computationally efficient, comprehensive, multi-scale, and multi-physics analysis and optimization method for air-to-refrigerant HXs featuring automated CFD and FEA simulations and approximation-assisted optimization. This methodology was utilized to design HXs with shape-optimized, non-round tubes which outperform current state-of-the-art tube-fin HXs without compromising structural integrity. The optimal HXs were shown to deliver similar thermal performance to the baseline HXs while also achieving more than 20% reductions in airside pressure drop and core envelope volume and more than 30% reduction in internal volume. Comprehensive experimental validation of the optimization methodology was conducted through the testing of two prototypes in a standardized wind tunnel facility under multiple operating conditions. For prototype #1 under dry evaporator conditions, the predicted heat load agreed within ± 10% of measured values and the predicted airside pressure drop agreed within ± 30%, while for dehumidifying conditions, the predicted sensible and latent heat loads agreed within ± 10% and ± 20% of the measured values, respectively. For prototype #2, the predicted condenser heat load agreed within ± 3.0% of measured values, and the predicted airside pressure drop agreed within ± 27%. The acceptable agreement between simulation and experimental results for the present application highlights the flexibility of the novel optimization methodology to design next generation HXs with improved performance and reduced volume, weight, and environmental impact.

42 ENGINEERING↗
DOE OSTI2023

Physics-based adaptivity of a spectral method for the Vlasov–Poisson equations based on the asymmetrically-weighted Hermite expansion in velocity space

We propose a spectral method for the 1D-1V Vlasov–Poisson system where the discretization in velocity space is based on asymmetrically-weighted Hermite functions, dynamically adapted via a scaling α and shifting u of the velocity variable. Specifically, at each time instant an adaptivity criterion selects new values of α and u based on the numerical solution of the discrete Vlasov–Poisson system obtained at that time step. Once the new values of the Hermite parameters α and u are fixed, the Hermite expansion is updated and the discrete system is further evolved for the next time step. The procedure is applied iteratively over the desired temporal interval. The key aspects of the adaptive algorithm are: the map between approximation spaces associated with different values of the Hermite parameters that preserves total mass, momentum and energy; and the adaptivity criterion to update α and u based on physics considerations relating the Hermite parameters to the average velocity and temperature of each plasma species. For the discretization of the spatial coordinate, we rely on Fourier functions and use the implicit midpoint rule for time stepping. The resulting numerical method possesses intrinsically the property of fluid-kinetic coupling, where the low-order terms of the expansion are akin to the fluid moments of a macroscopic description of the plasma, while kinetic physics is retained by adding more spectral terms. Moreover, the scheme features conservation of total mass, momentum and energy associated in the discrete, for periodic boundary conditions. A set of numerical experiments confirms that the adaptive method outperforms the non-adaptive one in terms of accuracy and stability of the numerical solution.

97 MATHEMATICS AND COMPUTING↗