Search NASA⌕ Search

SEARCH · Search NASA

Results for “scaling effects”

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 91 records · Page 5

Mitigating Transition in the Fermilab Booster Using a Triple Phase Jump

The PIP-II project will significantly enhance neutrino production for DUNE, Fermilab s flagship long-baseline neutrino oscillation experiment, by doubling the beam power delivered by the accelerator complex. To achieve this, the total charge injected from the new PIP-II linac into the Booster rapid cycling synchrotron (RCS) will increase from $4.5\times 10^{12}$ to $6.5\times 10^{12}$ protons per pulse. Simultaneously, the Booster s ramp rate will rise from 15 to 20 Hz, while the injection energy will go from 400 MeV to 800 MeV. The Booster accelerates the beam to 8 GeV and crosses transition at $\gamma_t=5.45$. In current operations, no dedicated $\gamma_t$ jump system is employed; instead, longitudinal emittance growth is controlled via an active quadrupole-mode feedback system. Downstream, the Recycler Ring uses slip-stacking to accumulate beam and increase bunch intensity. However, this process imposes a constraint on the longitudinal emittance at Booster extraction, limiting it to 0.1 eV-s (95\%) to avoid excessive particle loss. Because collective effects scale with intensity, additional measures to mitigate transition crossing may be required to stay below this limit. One potential approach is the so-called triple phase-jump technique. While the method has known limitations, it offers some advantages: it can be implemented using the existing digital low-level RF (LLRF) system, requires no additional magnets or pulsed power supplies, and remains compatible with quadrupole-mode feedback.

Ostiguy, Jean-Francois [Fermilab] (ORCID:000000029↗

MINERvA open-data product

MINERvA is THE neutrino cross section experiment Scintillator tracker/calorimeter ran in the NuMI beam at Fermilab same beam as the MINOS and NOvA oscillation experiments With our data, we are solving systematic shortcomings in neutrino interaction rate/spectra that are the largest part of the systematic uncertainty in today s (and tomorrow s) measurements. Some aspects have NO equivalent in the neutrino program future. Scientific scope includes both particle and nuclear physics GeV scale cross sections, A dependence, MeV scale effects most published measurements for a neutrino experiments ever (well, tied with T2K) with 25% more papers in the pipeline.

Gran, Rik [Minnesota U., Duluth] (ORCID:0000000216↗

Quantum Gravity and Laser Interferometry: Towards Observable Predictions

Understanding quantum gravity remains one of the deepest challenges in modern physics, as direct experimental access to Planck-scale effects is beyond current technological reach. However, recent theoretical advances indicate that quantum fluctuations of spacetime may produce measurable effects in precision experiments, particularly near causal horizons. This opens new avenues for testing quantum gravity phenomena through high-precision measurement techniques. This dissertation develops multiple theoretical models to characterize these effects and examines their potential observational signatures in future gravitational wave interferometers. We begin by investigating the role of quantum fluctuations in near-horizon geometries through the lens of the AdS/CFT correspondence, which provides a powerful framework for understanding the interplay between quantum field theory and general relativity via holographic principles. By modeling stochastic energy-momentum sources in Rindler-AdS spacetime, we demonstrate that vacuum fluctuations transform the Einstein equations into a Langevin-type stochastic differential equation, leading to potentially observable fluctuations in photon traversal times. Extending this approach to Minkowski spacetime, we establish a correspondence between gravitational shockwaves and fluid dynamics, showing that near-horizon perturbations satisfy an equation analogous to that governing incompressible fluids, thereby reinforcing the membrane paradigm and hydrodynamic analogies in the context of the fluid/gravity duality. Furthermore, we construct the covariant phase space of a spherically symmetric causal diamond in Minkowski spacetime, identifying two fundamental charges that govern its evolution. These results provide a foundation for quantizing causal horizons and understanding their microscopic degrees of freedom. Building upon these theoretical developments, we further examine a related stochastic phenomenon: the gravitational wave memory background arising from the cumulative memory steps produced by supermassive black hole mergers. After reviewing the standard stochastic gravitational wave background, gravitational memory effects, and BMS symmetries, we model the stochastic memory background using a Brownian motion framework. We show that while the cumulative memory background initially appears above the sensitivity curve of space-based interferometers like LISA, the realistic subtraction of individually resolvable merger events substantially suppresses the residual signal, making its detection more challenging. This highlights the critical importance of source subtraction when evaluating the detectability of gravitational memory effects. By bridging fundamental theory with experimental prospects, this dissertation contributes to the ongoing effort to uncover the quantum nature of spacetime through precision measurement techniques. Whether through detecting quantum spacetime fluctuations, gravitational memory backgrounds, or probing the symmetries of causal horizons, the pursuit of observable quantum gravity phenomena continues to expand the frontiers of both theory and experiment.

Zhang, Yiwen [Caltech] (ORCID:0000000323559416)↗

Revisiting Huffman Coding: Toward Extreme Performance on Modern GPU Architectures

Today's high-performance computing (HPC) applications are producing vast volumes of data, which are challenging to store and transfer efficiently during the execution, such that data compression is becoming a critical technique to mitigate the storage burden and data movement cost. Huffman coding is arguably the most efficient Entropy coding algorithm in information theory, such that it could be found as a fundamental step in many modern compression algorithms such as DEFLATE. On the other hand, today's HPC applications are more and more relying on the accelerators such as GPU on supercomputers, while Huffman encoding suffers from low throughput on GPUs, resulting in a significant bottleneck in the entire data processing. In this paper, we propose and implement an efficient Huffman encoding approach based on modern GPU architectures, which addresses two key challenges: (1) how to parallelize the entire Huffman encoding algorithm, including codebook construction, and (2) how to fully utilize the high memory-bandwidth feature of modern GPU architectures. The detailed contribution is fourfold. (1) We develop an efficient parallel codebook construction on GPUs that scales effectively with the number of input symbols. (2) We propose a novel reduction based encoding scheme that can efficiently merge the codewords on GPUs. (3) We optimize the overall GPU performance by leveraging the state-of-the-art CUDA APIs such as Cooperative Groups. (4) We evaluate our Huffman encoder thoroughly using six real-world application datasets on two advanced GPUs and compare with our implemented multithreaded Huffman encoder. Experiments show that our solution can improve the encoding throughput by up to 5.0× and 6.8× on NVIDIA RTX 5000 and V100, respectively, over the state-of-the-art GPU Huffman encoder, and by up to 3.3× over the multithread encoder on two 28-core Xeon Platinum 8280 CPUs.

Tian, Jiannan↗

Rare Lepton Decays and Differentiable Hadronization Models - From Signatures of New Physics to Data-driven Event Generation

This dissertation is partitioned into two parts: phenomenological studies focused on rare lepton decays as probes of heavy and light new physics, and the development of differentiable, data-driven hadronization models. Part I develops the phenomenology of new physics signatures stemming from rare charged lepton flavor violating decays probed by experiments at the intensity frontier. These include interactions mediated by both high-scale effective operators and light new physics, manifesting in multi-lepton final states ($\mu \to 5e$), elastic nuclear transitions ($\mu \to e$ conversion), baryon-number-violating muon capture, and time-dependent signals from ultralight dark matter ($\mu \to e \phi, \tau \to \ell \phi$). Part II develops two distinct strategies for advancing differentiable and data-driven hadronization models. One involves comprehensive reweighting frameworks for hadronization that enable efficient uncertainty estimation, facilitate parameter tuning, and interface naturally with differentiable programming paradigms. The other introduces machine-learning-based methods for extracting microscopic fragmentation dynamics directly from macroscopic observables through the deformation of existing models -- effectively providing solutions to the inverse problem of hadronization. Altogether, these studies advance the interpretability, flexibility, and precision of theoretical predictions for both high-intensity and high-energy experiments.

Menzo, Tony [Cincinnati U.] (ORCID:000000022013457↗

Informing field-scale CO 2 storage simulations with sandbox experiments: The effect of small-scale heterogeneities

Small-scale heterogeneities can significantly affect the fate of the CO 2 plume and trapping during CO 2 migration. We conducted geologic carbon storage field-scale simulations to investigate the impact of small-scale heterogeneities on plume dynamics and trapping performance. Small-scale heterogeneities have been shown to increase the amount of trapped CO 2 during buoyancy-driven flow. The trapped CO 2 saturation is validated by previous sandbox experimental work during buoyancy-driven flow in realistic heterogeneous domains and is implemented through the critical CO 2 saturation parameter (i.e., the first non-zero value in the drainage CO 2 relative permeability curve). Depending on the type and degree of heterogeneity, various critical CO 2 saturation values are exhibited. Furthermore, we investigated the effect of small-scale heterogeneities when multiple capillary pressure models are employed. This study demonstrates that an increase in critical CO 2 saturation reduces the CO 2 plume size and lateral extent, accompanying an increase in residual trapping and a decrease in solubility trapping. Lastly, we show that independent of the capillary pressure model used, an increase in critical saturation leads to similar CO 2 plume dynamics distribution and trapping performance. These results emphasize the importance of quantifying the effect of small-scale heterogeneity as they affect the large-scale behavior of the CO 2 plume.

58 GEOSCIENCES↗

Incorporating the Effect of Large‐Scale Vertical Motion on Convection Through Convective Mass Flux Adjustment in E3SMv2

Abstract Recent observational studies suggest that the large‐scale dynamical forcing (vertical motion) plays important roles in deep convection development. In this study we propose a convective mass flux adjustment (MAdj) approach to represent the dynamical effects of large‐scale vertical motion on convection in the Department of Energy's Energy Exascale Earth System Model version 2 (E3SMv2). With MAdj, convection is enhanced (suppressed) when there is large‐scale ascending (descending) motion at the planetary boundary layer top. The coupling of convection with large‐scale circulation significantly improves the simulation of climate variability in E3SMv2 across multiple scales from the diurnal cycle, convectively coupled equatorial waves, to the Madden‐Julian Oscillation (MJO). The standard E3SMv2 tends to simulate overly weak diurnal amplitude of precipitation and overly weak variance of convectively coupled equatorial Kelvin and westward inertio‐gravity (WIG) waves. It also fails to simulate the essential characteristics of the MJO: continuous eastward propagation. With MAdj, the amplitude of diurnal cycle of precipitation is systematically increased and its probability density distribution is much closer to observations. The MAdj can also simulate more realistic eastward propagation of the MJO and much stronger convectively coupled Kelvin and WIG waves. Moreover, the MAdj approach slightly improves the climatology simulations in precipitation, cloud, radiation, circulation, temperature, and moisture fields, with overall root‐mean‐square error (RMSE) of major climatological fields reduced by about 2%. The MAdj approach suppresses excessive grid‐scale precipitation, reducing precipitation wet biases over South China Sea, Philippine Sea, Himalayas, and South Pacific Convergence Zone in western Pacific in summer.

54 ENVIRONMENTAL SCIENCES↗

Exploring the origins of the indentation size effect at submicron scales

Significance Downscaling material structure into ever-decreasing levels for modern technological advancements demands small-scale mechanical characterizations of materials, such as nanoindentation. Thus, a comprehensive understanding of indentation size effect (ISE) has a far-reaching impact, but such understanding remains incomplete at the submicron scale despite a decades-long quest since the 1980s. Here, we explored the origins of this effect experimentally by linking dislocation behavior evolution with nanoindentation mechanical data at various depths. Importantly, the dislocation behavior is found to be strongly depth dependent and gives rise to subgrain formation progressively. Aided by subgrain boundaries, the ISE mechanism transitions from dislocation source starvation to dislocation interaction as indentation depth increases. The critical mechanism transition elucidates the distinctive ISE behavior at the submicron scale.

36 MATERIALS SCIENCE↗

The cosmological analysis of the SDSS/BOSS data from the Effective Field Theory of Large-Scale Structure

The Effective Field Theory of Large-Scale Structure is a formalism that allows us to predict the clustering of Cosmological Large-Scale Structure in the mildly non-linear regime in an accurate and reliable way. In this paper, after validating our technique against several sets of numerical simulations, we perform the analysis for the cosmological parameters of the DR12 BOSS data. We assume Λ CDM, a fixed value of the baryon/dark-matter ratio, Ω b /Ω c , and of the tilt of the primordial power spectrum, n s , and no significant input from numerical simulations. By using the one-loop power spectrum multipoles, we measure the primordial amplitude of the power spectrum, A s , the abundance of matter, Ω m , and the Hubble parameter, H 0 , {to about 13% , 3.2% and 3.2% respectively, obtaining ln (10 10 A s )=2.72± 0.13 , 0Ω m =0.309± 0.01 , H 0 =68.5± 2.2 km/(s Mpc) at 68% confidence level. If we then add a CMB prior on the sound horizon, the error bar on H 0 is reduced to 1.6% .} These results are a substantial qualitative and quantitative improvement with respect to former analyses, and suggest that the EFTofLSS is a powerful instrument to extract cosmological information from Large-Scale Structure.

79 ASTRONOMY AND ASTROPHYSICS↗

Ecological connectivity and habitat loss shape patterns of genetic diversity in a threatened salamander

Context The maintenance of genetic diversity is essential for preserving adaptive potential in populations, yet it is increasingly threatened by landscape alteration. The field of landscape genetics offers a framework for assessing how patch-level landscape conditions, modeled at multiple scales, influence genetic diversity. Objectives We sought to assess how local environmental features and connectivity influence genetic diversity across 74 four-toed salamander (Hemidactylium scutatum) breeding wetlands in the southeastern United States. Methods Using next-generation sequencing data and hierarchical Bayesian models, we examined genome-wide heterozygosity in relation to local landscape features and ecological connectivity. We also assessed the scale of effect of landscape features and tested for temporal lag effects. Results Genetic diversity was lower in wetlands with higher levels of historic deforestation and lower connectivity. An interaction between deforestation and connectivity indicated that deforestation had stronger negative effects in isolated wetlands but weaker effects in well-connected wetlands. Accounting for scale of effect and temporal lags was critical for detecting these relationships. Conclusions Our analyses highlight the importance of assessing the spatial scale (scale of effect) and temporal lag of landscape features to detect key drivers of genetic diversity. In line with population genetic theory, our results indicate that the genetic consequences of habitat loss do not affect populations uniformly and are most severe in isolated populations where gene flow cannot buffer against loss of diversity. Altogether, we highlight the importance of considering the interaction of habitat loss and connectivity in conservation genetic management.

Hemidactylium scutatum↗

Effect of Temperature on the Pilot-Scale Catalytic Pyrolysis of Loblolly Pine

A pilot-scale biomass catalytic pyrolysis unit with a nominal throughput of one tonne of biomass per day (1TPD) has been in operation since 2013 to investigate the process parameters that have the largest influence on biocrude yield, oxygen content, and chemical composition. A parametric study was conducted to investigate the effect of pyrolysis temperature, ranging from 433 to 581 °C, on biocrude yield and quality. A locally sourced loblolly pine feedstock and a commercially available, spray dried, nonzeolitic γ-Al 2 O 3 catalyst were used in individual experiments conducted at each pyrolysis temperature to achieve a minimum of 4 h of steady-state continuous operation. Typically, 600–800 kg of biomass was fed over a 12-h period, with one experiment extended to almost 29 h (1144-kg biomass fed) and one experiment interrupted by a process upset after just 7 h (411-kg biomass fed). Comprehensive analysis of collected gas, liquid, and solid products were used to calculate carbon balances (77% to 107%) for each experiment. The biocrude yield ranged from 12 to 18 wt % C and, in general, decreased with increasing pyrolysis temperature. The average steady-state biocrude yield as a function of temperature translated to a biocrude production rate between 40 and 50 gallons per dry ton. The biocrude oxygen content varied between 21 and 31 wt %, on a dry basis, and as expected, decreased with increasing pyrolysis temperature. The identified components in the semivolatile biocrude products are mostly methoxyphenols and other multiphenolic compounds. The multiphenolic compounds are demethoxylated at pyrolysis temperatures above 500 °C, producing biocrudes with higher concentrations of monophenols and polycyclic aromatic hydrocarbons. The concentration of anhydrosugars, like levoglucosan in the biocrudes, decreased with increasing pyrolysis temperature from ∼15 to ∼1 vol %.

biofuels↗

Multiscale Dynamics of Reactive Fronts in the Subsurface

Understanding and predicting flow and reactive transport in rocks (i.e. geologic porous media) is critical to many technologies at the heart of the energy transition, including CO 2 sequestration and H2 storage. However, accurate modeling and prediction of these systems is very complex because physico-chemical processes that occur at very small spatial scales, i.e. in the pores of the rocks, can dramatically control the system performance at the field scale (km). For example, precipitation reactions at the pore-scale can lead to large permeability changes at the field scale and dramatically alter the migration of stored gases. Properly accounting for multi-scale coupling effects is critical to achieve predictivity and confidence in model outputs, which then can guide design and optimization at the system-scale. This can be achieved through the development of rigorous mathematical models that can appropriately account for fine-scale effects at the large scale. The final report of the Early Career award DE-SC0019075 “Multiscale dynamics of reactive fronts in the subsurface” summarizes the mathematical, numerical and experimental advancements to study and predict reactive transport in geologic porous media across scales.

58 GEOSCIENCES↗

SiC Substrate Composition Effect on TGO Scale Growth in EBC Systems During High‐Temperature Steam Exposure

A systematic investigation was conducted on the oxidation behavior of silicon-bond coats within environmental barrier coating (EBC) systems applied to Si-carbide (SiC) substrates, aiming to understand how different underlying SiC substrates influence the bond coat's thermally grown oxide (TGO) and its properties. The study examined (Y/Yb) 2 Si 2 O 7 /Si coatings on three cost-effective surrogate SiC substrates (chemical vapor deposition [CVD]-grown β-SiC, sintered α-SiC, and reaction-bonded [RB] SiC) for SiC fiber /SiC matrix ceramic matrix composites (CMCs). Discrepancies in TGO growth were observed, with noticeably higher growth rates reported for the coated CMC specimens than for the four monolithic SiC specimens. The CMC samples produce an amorphous TGO, whereas the other monolithic substrates formed a crystalline TGO, which lowered the oxygen permeability through the SiO 2 scale. In conclusion, the vitrification of the TGO in the (Y/Yb) 2 Si 2 O 7 /Si/CMC system resulted from the migration of boron species from the CMC substrate to the SiO 2 scale, leading to network modification via boron doping.

EBC↗

Investigation of Farm-to-Farm Interactions and Blockage Effects from AWAKEN using Large-Scale Numerical Simulations

A large-scale numerical computation of five wind farms was performed as a part of the American Wake Experiment (AWAKEN). This high-fidelity computation used the ExaWind/AMR-Wind LES solver to simulate a 100km × 100km domain containing 541 turbines under unstable atmospheric conditions matching previous measurements. The turbines were represented by Joukowski and OpenFAST coupled actuator disk models. Results of this qualitative comparison illustrate the interactions with wind farms with large scale ABL structures in the flow, as well as the extent of downstream wake penetration in the flow and blockage effects around wind farms.

Cheung, Lawrence C.↗