Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “level set”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,027 records · Page 57

A new 181 Ta neutron resolved resonance region evaluation

A new 181 Ta neutron resolved resonance region evaluation has been performed from the thermal energy range up to approximately 2.5 keV. The R-matrix SAMMY code was used with the Reich–Moore approximation to evaluate resonance parameters from several experimental data sets. A Monte Carlo approach was used for resonance spin assignments and generating 59 small fictitious resonance levels which were shown to improve the cumulative level, Porter-Thomas, and Wigner distributions as compared to theoretical predictions. Covariance information was also generated for the entire resolved resonance region. Finally, the positive impact of the new evaluation was validated through benchmark calculations which were sensitive to the 181 Ta cross section and showed improvement in the reactivity bias for several benchmark cases.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Opportunities in multiscale modeling of mosquito-borne flaviviruses

Mosquito-borne flaviviruses, such as Zika, dengue, West Nile, and yellow fever virus, represent a growing public health concern due to their widespread distribution and the severe diseases they cause. These viruses are difficult to control as climate change and urbanization help mosquitoes expand into new areas, increasing the risk of outbreaks. Mathematical models play a key role in understanding their spread, providing insights at every level—from how the virus multiplies inside cells to how it circulates through entire populations. This review examines various approaches used in modeling arboviruses, including microscale models that focus on cellular and molecular dynamics, mesoscale models that address within-host processes, and macroscale models that capture population-level transmission. We briefly summarize the methodology used for models at each scale, which primarily consists of sets of differential equations with parameters that represent physical rates of change for different subprocesses. We particularly highlight how temperature affects virus transmission, which is key to understanding the impact of climate change. We also show how multiscale models can connect viral replication, immune response, and the spread of infection at a larger scale. This is essential for developing better vaccines and treatments, evaluating disease control measures, predicting the impact of climate change, and improving public health responses to outbreaks.

60 APPLIED LIFE SCIENCES↗

The locational value of distributed energy resources: A parcel-level evaluation of solar and wind potential in New York state

We report distributed energy resources (DERs) are poised to play a significant role in evolving power systems because of their flexibility to be sited in areas of high value to the grid. Traditional DER compensation frameworks, specifically net energy metering (NEM), inadequately communicate differences in the locational and temporal value of DER generation to the grid. As a transition from NEM, New York State's (NYS's) Value of Distributed Energy Resources (VDER) framework provides a methodology for calculating different value components that DERs offer the grid. To study the impacts of VDER frameworks on DER deployment, we developed a model to assess the value of distributed solar and wind systems configured as either a behind-the-meter system or a front-of-the-meter system for each parcel of land in NYS. Using parcel-level granularity, we can closely evaluate DER locational value and siting availability, particularly in urban and suburban settings. Our analysis finds while most DER generators would be modestly compensated for deferred transmission and distribution infrastructure upgrades (~0.01 $\$$/kWh for solar PV), a subset of projects receive significant value from this component (0.035 to 0.089 $\$$/kWh for top 5% of parcels for solar PV). Finally, our analysis finds VDER provides less overall compensation than NEM to the average DER generator, however, it increases access to compensation for front-of-the-meter DERs - a large and emerging market.

14 SOLAR ENERGY↗

Search for Wγ resonances in proton-proton collisions at √s=13 TeV using hadronic decays of Lorentz-boosted W bosons

A search for W$\gamma$ resonances in the mass range between 0.7 and 6.0 TeV is presented. The W boson is reconstructed via its hadronic decays, with the final-state products forming a single large-radius jet, owing to a high Lorentz boost of the W boson. The search is based on proton-proton collision data at $\sqrt{s} = $ 13 TeV, corresponding to an integrated luminosity of 137 fb$^{-1}$, collected with the CMS detector at the LHC in 2016-2018. The W$\gamma$ mass spectrum is parameterized with a smoothly falling background function and examined for the presence of resonance-like signals. No significant excess above the predicted background is observed. Model-specific upper limits at 95% confidence level on the product of the cross section and branching fraction to the W$\gamma$ channel are set. Limits for narrow resonances and for resonances with an intrinsic width equal to 5% of their mass, for spin-0 and spin-1 hypotheses, range between 0.17 fb at 6.0 TeV and 55 fb at 0.7 TeV. These are the most restrictive limits to date on the existence of such resonances. In specific narrow-resonance benchmark models, heavy scalar (vector) triplet resonances with masses between 0.75 (1.15) and 1.40 (1.36) TeV are excluded for a range of model parameters. Model-independent limits on the product of the cross section, signal acceptance, and branching fraction to the W$\gamma$ channel are set for minimum W$\gamma$ mass thresholds between 1.5 and 8.0 TeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for the Higgs boson decays to a ρ 0 , ϕ, or K ⁎0 meson and a photon in proton-proton collisions at $\sqrt{s} = 13$ TeV

Three rare decay processes of the Higgs boson to a ρ(770) 0 , Φ(1020), or K ⁎ (892) 0 meson and a photon are searched for using $\sqrt{s} = 13$ TeV proton-proton collision data collected by the CMS experiment at the LHC. Events are selected assuming the mesons decay into a pair of charged pions, a pair of charged kaons, or a charged kaon and pion, respectively. Depending on the Higgs boson production mode, different triggering and reconstruction techniques are adopted. The analyzed data sets correspond to integrated luminosities up to 138 fb -1 , depending on the reconstructed final state. After combining various data sets and categories, no significant excess above the background expectations is observed. Upper limits at 95% confidence level on the Higgs boson branching fractions into ρ(770) 0 $γ$, Φ(1020)$γ$, and K ⁎ (892) 0 are determined to be 3.7 x 10 -4 , 3.0 x 10 -4 , and 3.0 x 10 -4 , respectively. In case of the ρ(770) 0 $γ$ and Φ(1020)$γ$ channels, these are the most stringent experimental limits to date.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Capturing CO 2 in Quadrupolar Binding Pockets: Broadband Microwave Spectroscopy of Pyrimidine-(CO 2 ) n , n = 1,2

Pyrimidine has two in-plane CH(δ+)/N̈(δ–)/CH(δ+) binding sites that are complementary to the (δ–/2δ+/δ–) quadrupole moment of CO 2 . For this study, we recorded broadband microwave spectra over the 7.5–17.5 GHz range for pyrimidine-(CO 2 ) n with n = 1 and 2 formed in a supersonic expansion. Based on fits of the rotational transitions, including nuclear hyperfine splitting due to the two 14 N nuclei, we have assigned 313 hyperfine components across 105 rotational transitions for the n = 1 complex and 208 hyperfine components across 105 rotational transitions for the n = 2 complex. The pyrimidine-CO 2 complex is planar, with CO 2 occupying one of the quadrupolar binding sites, forming a structure in which the CO 2 is stabilized in the plane by interactions with the C–H hydrogens adjacent to the nitrogen atom. This structure is closely analogous to that of the pyridine-CO 2 complex studied previously by (Doran, J. L. J. Mol. Struct. 2012, 1019, 191–195). The fit to the n = 2 cluster gives rotational constants consistent with a planar cluster of C 2v symmetry in which the second CO 2 molecule binds in the second quadrupolar binding pocket on the opposite side of the ring. The calculated total binding energy in pyrimidine-CO 2 is –13.7 kJ mol –1 , including corrections for basis set superposition error and zero-point energy, at the CCSD(T)/ 6-311++G(3df,2p) level, while that in pyrimidine-(CO 2 ) 2 is almost exactly double that size, indicating little interaction between the two CO 2 molecules in the two binding sites. The enthalpy, entropy, and free energy of binding are also calculated at 300 K within the harmonic oscillator/rigid-rotor model. This model is shown to lack quantitative accuracy when it is applied to the formation of weakly bound complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine Learning Classification Strategy to Improve Streamflow Estimates in Diverse River Basins in the Colorado River Basin

Streamflow in the Colorado River Basin (CRB) is significantly altered by human activities including land use/cover alterations, reservoir operation, irrigation, and water exports. Climate is also highly varied across the CRB which contains snowpack-dominated watersheds and arid, precipitation-dominated basins. Recently, machine learning methods have improved the generalizability and accuracy of streamflow models. Previous successes with LSTM modeling have primarily focused on unimpacted basins, and few studies have included human impacted systems in either regional or single-basin modeling. We demonstrate that the diverse hydrological behavior of river basins in the CRB are too difficult to model with a single, regional model. We propose a method to delineate catchments into categories based on the level of predictability, hydrological characteristics, and the level of human influence. Lastly, we model streamflow in each category with climate and anthropogenic proxy data sets and use feature importance methods to assess whether model performance improves with additional relevant data. Overall, land use cover data at a low temporal resolution was not sufficient to capture the irregular patterns of reservoir releases, demonstrating the importance of having high-resolution reservoir release data sets at a global scale. On the other hand, the classification approach reduced the complexity of the data and has the potential to improve streamflow forecasts in human-altered regions.

54 ENVIRONMENTAL SCIENCES↗

Application of the AI2 Climate Emulator to E3SMv2's Global Atmosphere Model, With a Focus on Precipitation Fidelity

Abstract Can the current successes of global machine learning‐based weather simulators be generalized beyond 2‐week forecasts to stable and accurate multiyear runs? The recently developed AI2 Climate Emulator (ACE) suggests this is feasible, based upon 10‐year simulations with a network trained on output from a physics‐based global atmosphere model using a grid spacing of approximately 110 km and forced by a repeating annual cycle of sea‐surface temperature. Here we show that ACE, without modification, can be trained to emulate another major atmospheric model, EAMv2, run at a comparable grid spacing for at least 10 years with similarly small climate biases—a prerequisite to wider applicability. With an analysis that combines multiple temporal, spatial, and frequency domain perspectives, we show that ACE faithfully represents the spatiotemporal structure of EAMv2 precipitation and related variables. Finally, we show that a pretrained ACE network is able to adapt to a new global climate model simulation data set with 10 fewer training steps than when starting from random initialization, all while still maintaining low levels of climate bias. Further analysis of these fine‐tuning experiments reveal ACE's intriguing ability to interpolate between distinct global climate models.

Duncan, James P. C.↗

Quantum fluctuations drive nonmonotonic correlations in a qubit lattice

Abstract Fluctuations may induce the degradation of order by overcoming ordering interactions, consequently leading to an increase of entropy. This is particularly evident in magnetic systems characterized by nontrivial, constrained disorder, where thermal or quantum fluctuations can yield counterintuitive forms of ordering. Using the proven efficiency of quantum annealers as programmable spin system simulators, we present a study based on entropy postulates and experiments on a platform of programmable superconducting qubits to show that a low level of uncertainty can promote ordering in a system impacted by both thermal and quantum fluctuations. A set of experiments is proposed on a lattice of interacting qubits arranged in a triangular geometry with precisely controlled disorder, effective temperature, and quantum fluctuations. Our results demonstrate the creation of ordered ferrimagnetic and layered anisotropic disordered phases, displaying characteristics akin to the elegant order-by-disorder phenomenon. Extensive experimental evidence is provided for the role of quantum fluctuations in lowering the total energy of the system by increasing entropy and defect clustering. Our thorough and comprehensive application of an intentionally introduced noise on a quantum platform provides insight into the dynamics of defects and fluctuations in quantum devices, which may help to reduce the cost associated with quantum processing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Search for Majorana neutrinos exploiting millikelvin cryogenics with CUORE

The possibility that neutrinos may be their own antiparticles, unique among the known fundamental particles, arises from the symmetric theory of fermions proposed by Ettore Majorana in 1937. Given the profound consequences of such Majorana neutrinos, among which is a potential explanation for the matter–antimatter asymmetry of the universe via leptogenesis, the Majorana nature of neutrinos commands intense experimental scrutiny globally; one of the primary experimental probes is neutrinoless double beta (0νββ) decay. Here we show results from the search for 0νββ decay of 130 Te, using the latest advanced cryogenic calorimeters with the CUORE experiment3. CUORE, operating just 10 millikelvin above absolute zero, has pushed the state of the art on three frontiers: the sheer mass held at such ultralow temperatures, operational longevity, and the low levels of ionizing radiation emanating from the cryogenic infrastructure. We find no evidence for 0νββ decay and set a lower bound of the process half-life as 2.2 × 10 25 years at a 90 percent credibility interval. We discuss potential applications of the advances made with CUORE to other fields such as direct dark matter, neutrino and nuclear physics searches and large-scale quantum computing, which can benefit from sustained operation of large payloads in a low-radioactivity, ultralow-temperature cryogenic environment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Ground and excited state properties of ThBe and AcBe

In this work, the ground and excited states of ThBe and AcBe were investigated by performing high-level multireference and single-reference coupled-cluster quantum chemical calculations with large correlation consistent basis sets. Full potential energy curves (PECs), chemical bonding patterns, energetics, spectroscopic parameters (T e , r e , ω e , and ω e x e ), and spin–orbit effects of 13 and 8 electronic states of ThBe and AcBe, respectively, are reported. The ground electronic states of ThBe and AcBe are single-reference 1 3 Σ − (1σ 2 2σ 2 1π 2 ) and 1 2 Π (1σ 2 2σ 2 1π 1 ), respectively, and originate from their corresponding ground state fragments. The chemical bonding of ThBe (1 3 Σ − ) and AcBe (1 2 Π) are π-dative in character and are formed by d-electron transfers from Th/Ac to the empty 2p x and 2p y of the Be atom. The electron populations of the f-orbitals of both ThBe (1 3 Σ − ) and AcBe (1 2 Π) are minor which exhibit their “transition-metal-like” nature. The estimated bond energies of the spin–orbit ground states of ThBe (1 3 Σ − 0+ ) and AcBe (1 2 Π 1/2 ) are 12.79 and 11.02 kcal mol −1 , respectively. Finally, the bond energy of ThBe was used to estimate its heat of formation ΔH 0 f (298 K) of 869.61 ± 6 kJ mol −1 .

74 ATOMIC AND MOLECULAR PHYSICS↗

Toward accelerating rare-earth metal extraction using equivariant neural networks

The separation of rare-earth metals, vital for numerous advanced technologies, is hampered by their similar chemical properties, making ligand discovery a significant challenge. Traditional experimental and quantum chemistry approaches for identifying effective ligands are often resource-intensive. We introduce a machine learning protocol based on an equivariant neural network, Allegro, for the rapid and accurate prediction of binding energies in rare-earth complexes. Key to this work is our newly curated dataset of rare-earth metal complexes—made publicly available to foster further research—systematically generated using the Architector program. This dataset distinctively features functionalized derivatives of proven rare-earth-chelating scaffolds, hydroxypyridinone (HOPO), catecholamide (CAM), and their thio-analogues, selected for their established efficacy in binding these elements. Trained on this valuable resource, our Allegro models demonstrate excellent performance, particularly when trained to directly predict DFT-level binding energies, yielding highly accurate results that closely correlate with theoretical calculations on a diverse test set. Furthermore, this strategy exhibited strong out-of-sample generalization, accurately predicting binding energies for an isomeric HOPO-derivative ligand not seen during training. By substantially reducing computational demands, this machine learning framework, alongside the provided dataset, represent powerful tools to accelerate the high-throughput screening and rational design of novel ligands for efficient rare-earth metal separation.

Gupta, Ankur K. [Lawrence Berkeley National Labora↗

Gyrokinetic simulations of momentum flux parasitic to free-energy transfer

Ion Landau damping interacts with a portion of the E × B drift to cause a nondiffusive outward flux of co-current toroidal angular momentum. Quantitative evaluation of this momentum flux requires nonlinear simulations to determine f L , the fraction of fluctuation free energy that passes through ion Landau damping, in fully developed turbulence. Nonlinear gyrokinetic simulations with the GKW code confirm the presence of the systematic symmetry-breaking momentum flux. For simulations with adiabatic electrons, f L scales inversely with the ion temperature gradient, because only the ion curvature drift can transfer free energy to the electrostatic potential. Although kinetic electrons should, in principle, relax this restriction, the ion Landau damping measured in collisionless kinetic-electron simulations remained at low levels comparable with ion-curvature-drift transfer, except when magnetic shear $\hat{s}$ was strong. A set of simulations scanning the electron pitch-angle scattering rate showed only a weak variation of f L with the electron collisionality. Still, collisional-electron simulations with electron temperature greater than ion temperature unambiguously showed electron-curvature-drift transfer supporting ion Landau damping, leading to a corresponding enhancement of the symmetry-breaking momentum flux.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

First Search for Dark Sector 𝑒 + ⁢𝑒 − Explanations of the MiniBooNE Anomaly at MicroBooNE

We present MicroBooNE’s first search for dark sector 𝑒 + ⁢𝑒 − explanations of the long-standing MiniBooNE anomaly. The MiniBooNE anomaly has garnered significant attention over the past 20 years including previous MicroBooNE investigations into both anomalous electron and photon excesses, but its origin still remains unclear. In this Letter, we provide the first direct test of dark sector models in which dark neutrinos, produced through neutrino-induced scattering, decay into missing energy and visible 𝑒 + ⁢𝑒 − pairs comprising the MiniBooNE anomaly. Many such models have recently gained traction as a viable solution to the anomaly while evading past bounds. Using an exposure of 6.87 × 10 20 protons-on-target in the Booster Neutrino Beam, we implement a selection targeting forward-going, coherently produced 𝑒 + ⁢𝑒 − events. After unblinding, we observe 95 events, which we compare with the constrained background-only prediction of 69.7 ±17.3. This analysis sets the world’s first direct limits on these dark sector models and, at the 95% confidence level, excludes the entirety of the single dark neutrino and majority of the dual dark neutrino, parameter space that is viable as a solution to the MiniBooNE anomaly.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for Fractionally Charged Particles with CUORE

The Cryogenic Underground Observatory for Rare Events (CUORE) is a detector array comprised by 988 5 cm × 5 cm × 5 cm TeO 2 crystals held below 20 mK, primarily searching for neutrinoless double-beta decay in 130 Te. Unprecedented in size among cryogenic calorimetric experiments, CUORE provides a promising setting for the study of exotic throughgoing particles. Using the first tonne year of CUORE’s exposure, we perform a search for hypothesized fractionally charged particles (FCPs), which are well-motivated by various standard model extensions and would have suppressed interactions with matter. Across the searched range of charges 𝑒/24−𝑒/2 no excess of FCP candidate tracks is observed over background, setting leading limits on the underground FCP flux with charges 𝑒/24 −𝑒/5 at 90% confidence level. Using the low background environment and segmented geometry of CUORE, we establish the sensitivity of tonne-scale subkelvin detectors to diverse signatures of new physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for neutron decay into an antineutrino and a neutral kaon in 0.401 megaton-years exposure of Super-Kamiokande

We searched for bound neutron decay via 𝑛 → $\bar{𝜈}$ +𝐾 0 predicted by the grand unified theories in 0.401 Mton·years exposure of all pure water phases in the Super-Kamiokande detector. About 4.4 times more data than in the previous search have been analyzed by a new method including a spectrum fit to kaon invariant mass distributions. No significant data excess has been observed in the signal regions. As a result of this analysis, we set a lower limit of 7.8 × 10 32 years on the neutron lifetime at a 90% confidence level.

Cherenkov detectors↗

Multi‐hypothesis comparison of Farquhar and Collatz photosynthesis models reveals the unexpected influence of empirical assumptions at leaf and global scales

Abstract Mechanistic photosynthesis models are at the heart of terrestrial biosphere models (TBMs) simulating the daily, monthly, annual and decadal rhythms of carbon assimilation ( A ). These models are founded on robust mathematical hypotheses that describe how A responds to changes in light and atmospheric CO 2 concentration. Two predominant photosynthesis models are in common usage: Farquhar (FvCB) and Collatz (CBGB). However, a detailed quantitative comparison of these two models has never been undertaken. In this study, we unify the FvCB and CBGB models to a common parameter set and use novel multi‐hypothesis methods (that account for both hypothesis and parameter variability) for process‐level sensitivity analysis. These models represent three key biological processes: carboxylation, electron transport, triose phosphate use (TPU) and an additional model process: limiting‐rate selection. Each of the four processes comprises 1–3 alternative hypotheses giving 12 possible individual models with a total of 14 parameters. To broaden inference, TBM simulations were run and novel, high‐resolution photosynthesis measurements were made. We show that parameters associated with carboxylation are the most influential parameters but also reveal the surprising and marked dominance of the limiting‐rate selection process (accounting for 57% of the variation in A vs. 22% for carboxylation). The limiting‐rate selection assumption proposed by CBGB smooths the transition between limiting rates and always reduces A below the minimum of all potentially limiting rates, by up to 25%, effectively imposing a fourth limitation on A . Evaluation of the CBGB smoothing function in three TBMs demonstrated a reduction in global A by 4%–10%, equivalent to 50%–160% of current annual fossil fuel emissions. This analysis reveals a surprising and previously unquantified influence of a process that has been integral to many TBMs for decades, highlighting the value of multi‐hypothesis methods.

54 ENVIRONMENTAL SCIENCES↗

Functional Traits Resolve Mechanisms Governing the Assembly and Distribution of Nitrogen-Cycling Microbial Communities in the Global Ocean

Microorganisms drive much of the marine nitrogen (N) cycle, which jointly controls the primary production in the global ocean. However, our understanding of the microbial communities driving the global ocean N cycle remains fragmented. Focusing on “who is doing what, where, and how?”, this study draws a clear picture describing the global biogeography of marine N-cycling microbial communities by utilizing the Tara Oceans shotgun metagenomes. The marine N-cycling communities are highly variable taxonomically but relatively even at the functional trait level, showing clear functional redundancy properties. The functional traits and taxonomic groups are shaped by the same set of geo-environmental factors, among which, depth is the major factor impacting marine N-cycling communities, differentiating mesopelagic from epipelagic communities. Latitudinal diversity gradients and distance-decay relationships are observed for taxonomic groups, but rarely or weakly for functional traits. The composition of functional traits is strongly deterministic as revealed by null model analysis, while a higher degree of stochasticity is observed for taxonomic composition. Integrating multiple lines of evidence, in addition to drawing a biogeographic picture of marine N-cycling communities, this study also demonstrated an essential microbial ecological theory—determinism governs the assembly of microbial communities performing essential biogeochemical processes; the environment selects functional traits rather than taxonomic groups; functional redundancy underlies stochastic taxonomic community assembly.

59 BASIC BIOLOGICAL SCIENCES↗