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At least 1,369 records · Page 76

Host Dark Matter Halos of SDSS Red and Blue Quasars: No Significant Difference in Large-scale Environment

The observed optical colors of quasars are generally interpreted in one of two frameworks: unified models that attribute the color to the random orientation of the accretion disk along the line of sight, and evolutionary models that invoke connections between quasar systems and their environments. We test these schemas by probing the dark matter halo environments of optically selected quasars as a function of g – i optical color by measuring the two-point correlation functions of ~0.34 million eBOSS quasars as well as the gravitational deflection of cosmic microwave background photons around ~0.66 million XDQSO photometric quasar candidates. We do not detect a trend of halo bias with optical color through either analysis, finding that optically selected quasars at 0.8 < z < 2.2 occupy halos of characteristic mass M h ~ 3 × 10 12 h –1 M ⊙ regardless of their color. This result implies that a quasar's large-scale halo environment is not strongly connected to its observed optical color. We also confirm the findings of fundamental differences in the radio properties of red and blue quasars by stacking 1.4 GHz FIRST images at their positions, suggesting the observed differences cannot be attributed to orientation. Instead, the differences between red and blue quasars likely arise on nuclear-galactic scales, perhaps owing to reddening by a nuclear dusty wind. Finally, we show that optically selected quasars' halo environments are also independent of their r – W2 optical–infrared colors, while previous work has suggested that mid-infrared-selected obscured quasars occupy more massive halos. We discuss the implications of this result for models of quasar and galaxy coevolution.

79 ASTRONOMY AND ASTROPHYSICS↗

Combining Planck and SPT Cluster Catalogs: Cosmological Analysis and Impact on the Planck Scaling Relation Calibration

We provide the first combined cosmological analysis of the South Pole Telescope (SPT) and Planck cluster catalogs. The aim is to provide an independent calibration for Planck scaling relations, exploiting the cosmological constraining power of the SPT-SZ cluster catalog and its dedicated weak lensing (WL) and X-ray follow-up observations. We build a new version of the Planck cluster likelihood. In the νΛ CDM scenario, focusing on the mass slope and mass bias of Planck scaling relations, we find ${\alpha }_{\mathrm{SZ}}={1.49}_{-0.10}^{+0.07}$ and ${\left(1-b\right)}_{\mathrm{SZ}}={0.69}_{-0.14}^{+0.07}$, respectively. The results for the mass slope show a ~4 σ departure from the self-similar evolution, α SZ ~ 1.8. This shift is mainly driven by the matter density value preferred by SPT data, Ωm = 0.30 ± 0.03, lower than the one obtained by Planck data alone, ${{\rm{\Omega }}}_{m}={0.37}_{-0.06}^{+0.02}$. The mass bias constraints are consistent both with outcomes of hydrodynamical simulations and external WL calibrations, (1 – b) ~ 0.8, and with results required by the Planck cosmic microwave background cosmology, (1 – b) ~ 0.6. From this analysis, we obtain a new catalog of Planck cluster masses M 500 . We estimate the ratio between the published Planck M SZ masses and our derived masses M 500 , as a "measured mass bias," ${\left(1-b\right)}_{M}$. We analyze the mass, redshift, and detection noise dependence of ${\left(1-b\right)}_{M}$, finding an increasing trend toward high redshift and low mass. These results mimic the effect of departure from self-similarity in cluster evolution, showing different dependencies for the low-mass, high-mass, low-z, and high-z regimes.

79 ASTRONOMY AND ASTROPHYSICS↗

Farpoint: A High-resolution Cosmology Simulation at the Gigaparsec Scale

Abstract In this paper we introduce the Farpoint simulation, the latest member of the Hardware/Hybrid Accelerated Cosmology Code (HACC) gravity-only simulation family. The domain covers a volume of (1000 h −1 Mpc) 3 and evolves close to two trillion particles, corresponding to a mass resolution of m p ∼ 4.6 × 10 7 h −1 M ⊙ . These specifications enable comprehensive investigations of the galaxy–halo connection, capturing halos down to small masses. Further, the large volume resolves scales typical of modern surveys with good statistical coverage of high-mass halos. The simulation was carried out on the GPU-accelerated system Summit, one of the fastest supercomputers currently available. We provide specifics about the Farpoint run and present an initial set of results. The high mass resolution facilitates precise measurements of important global statistics, such as the halo concentration–mass relation and the correlation function down to small scales. Selected subsets of the simulation data products are publicly available via the HACC Simulation Data Portal.

79 ASTRONOMY AND ASTROPHYSICS↗

diffReplication - An Energy-Aware Fault Tolerance Model for Silent Error Detection and Mitigation in Heterogeneous Extreme-scale Computing Environment

At extreme scale, the frequency of silent errors – a class of errors that remain undetected by low-level error detection mechanisms – increases significantly with the computational complexity of the application and the scale of the computing infrastructure. As hardware and software advances are made to usher in the next scientific era of computing, developing new approaches to mitigate the impact of silent errors remains a challenging problem. In this work, we propose an energy-aware fault-tolerance model, referred to diffReplication to overcome silent errors. In the proposed model, the main process is associated with one replica that executes at the same rate as the main process, and one diffReplica that is executed at a fraction of the main process' execution rate. If the main and its replica reach consensus at the end of a computation phase, the state of the diffReplica is updated and computation is resumed. If the synchronization attempt results in a disagreement, however, the diffReplica increases its execution speed to complete the computation and quickly reach the synchronization barrier. Assuming a single error over any given synchronization interval, a majority voting is used to reach consensus and tolerate silent errors. To further enhance its performance, diffReplication is augmented with speculative execution, whereby the main or its fast replica is selected to continue execution without waiting for the diffReplica. The selection process is based on the previous behaviour of the main and its replica. A performance analysis study is carried out to assess the performance of diffReplication, in terms of the energy saving and time-to-completion reduction achieved by the diffReplication scheme. The experiment shows that speculative execution reduces the time to completion with additional energy, and dynamic decision-making balances the energy consumption and time to completion.

97 MATHEMATICS AND COMPUTING↗

Large-Scale Inference of Multivariate Regression for Heavy-Tailed and Asymmetric Data

Large-scale multivariate regression is a fundamental statistical tool with a wide range of applications. Here, this study considers the problem of simultaneously testing a large number of general linear hypotheses, encompassing covariate-effect analysis, analysis of variance, and model comparisons. The challenge that accompanies a large number of tests is the ubiquitous presence of heavy-tailed and/or highly skewed measurement noise, which is the main reason for the failure of conventional least squares-based methods. For large-scale multivariate regression, we develop a set of robust inference methods to explore data features such as heavy tailedness and skewness, which are not visible to least squares methods. The new testing procedure is based on the data-adaptive Huber regression and a new covariance estimator of regression estimates. Under mild conditions, we show that our methods produce consistent estimates of the false discovery proportion. Extensive numerical experiments and an empirical study on quantitative linguistics demonstrate the advantage of the proposed method over many state-of-the-art methods when the data are generated from heavy-tailed and/or skewed distributions.

97 MATHEMATICS AND COMPUTING↗

Analyzing the Economic and Technical Potential of H2@Scale

H2@Scale is one of EERE's flagship initiatives to enable clean and affordable hydrogen production, storage, distribution, and utilization across multiple sectors in the economy. The January H2IQ hour will discuss results from a recent multi-laboratory analysis report quantifying the technical and economic potential of H2@Scale, given the use of hydrogen as an energy intermediate to integrate sectors in the U.S. energy system. Mark Ruth of the National Renewable Energy Laboratory, the lead author of the report, will discuss specific examples of the role hydrogen can play in industry and transportation sectors, such as steelmaking, synthetic fuels, and blending into natural gas pipelines. He will also explain how hydrogen production can be integrated with the electric grid to monetize low-cost energy and incentivize growth in renewable energy supply. The H2IQ Hour will dive into estimates for future hydrogen consumption in current and emerging sectors, given R&D advances and varying prices of natural gas and electricity.

39 EE - Hydrogen and Fuel Cell Technologies (EE-3F↗

Process Intensification and Scale-Up of a Continuous Enzymatic Hydrolysis and Separation Process

Combining separate unit operations into one where the best of each part can be maximized is one of the benefits of process intensification. An example is the combination of lignocellulosic biomass enzymatic hydrolysis with the downstream solid-liquid separation step to produce clarified sugars ready for fermentation or catalytic upgrading. The productivity and endpoint yield of enzymatic hydrolysis both enjoy the benefits of reduced feedback inhibition through the continuous removal of sugars by incorporating separations into the reactor. Likewise, the efficiency of recovering clarified sugars from the enzymatic hydrolysis slurry can be enhanced by operating separations equipment at steady-state conditions simultaneously with the continuously fed hydrolysis process. A key parameter that enables greater processing capacity while also raising the risks of failure is the solids loading or concentration. Higher solids loading allows for smaller reactor vessels and results in clarified sugars of higher concentration; however, required pumping power increases, reactor agitation may become ineffective, and membrane flux suffers. Feedstock material attributes influenced by upstream pretreatment must also be scrutinized more carefully: dilute-acid pretreated and deacetylated-and-disc-refined feedstocks exhibit different characteristics that affect agitation and pumping. The authors invite you to further explore the process science enabling the scale-up of this technology from conceptual work at the bench to pilot-scale industrially-relevant equipment where the challenges and solutions of integration and process optimization are expounded upon.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Integration of Dynamical System Scaling to RAVEN and Facility Application

As part of the design optimization and model validation effort within the hybrid energy systems program, the research to implement dynamical system scaling (DSS) code to RAVEN is funded under the Integrated Energy System program in collaboration with the Digital Reactor Technology & Development department. The DSS data processing algorithm has been coded within the RAVEN framework along with other metrics and postprocessing models. The implemented code was tested using a gravity-driven draining tank draining case modeled in RELAP5-3D and generated data was successfully postprocessed based on the scaling analyses defined by DSS. Postprocessed data concluded less agreement for the tank exit velocity and indicated that the modeled input deck for RELAP5-3D requires modification to enforce minimal pressure differential effects to the draining process.

97 MATHEMATICS AND COMPUTING↗

Creation of the VADER Code in SCALE [Abstract]

The VADER (Validation Analysis Data Evaluation Resource) is a new module in SCALE 6.3 that has been derived from the legacy USLSTATS program. VADER is a tool that allows the determination of bias and bias uncertainty for criticality safety computational methods. The older USLSTATS program, written in Java, existed outside of SCALE and provided tools to calculate only the confidence band with administrative margin (sometimes called USL-1) and the single-sided uniform width closed interval (USL-2). For normality testing it only offered a crude chi- squared normality test that had no user-configurable options and presented a simple pass/no-pass functionality.

97 MATHEMATICS AND COMPUTING↗

Hydrogen Production, Grid Integration, and Scaling for the Future

The Hydrogen Production, Grid Integration, and Scaling for the Future project will inform clean hydrogen production deployment across the planning, procurement, and operation stages of hydrogen production on the grid. Hydrogen production from renewables is a clean source of fuel which is near zero for greenhouse gas emissions and criteria pollutants. The results from this project will inform entities looking to build clean energy projects that produce good paying jobs in manufacturing, installation, maintenance and operation of these facilities. This project provides system characterization examples, multiple configurations, optimizations, and suggested metering and custody transfer points through multiple scenarios and hardware testing of NREL's state-of-the-art 1.25 MW polymer electrolyte membrane (PEM) electrolyzer system to characterize system performance in relevant scenarios. This work also creates a digital twin for emulation in the Advanced Research on Integrated Systems (ARIES) virtual environment and performs hardware-in-the-loop (HIL) testing of pilot-scale, decentralized, and centralized hydrogen systems.

centralized hydrogen production↗

Evaluating Scaling Effects of Steam Condensation Physics-based Model for Small Modular Reactor

This study focused on assessing condensation heat transfer (CHT) models for enhancing the passive safety of small modular reactors (SMRs). It also encompassed a review of the theoretical and semi-theoretical CHT models and correlations. Condensation models such as the degradation factor, heat and mass transfer analogy (HMTA), and boundary layer models are used to study advanced nuclear reactor PCCS. The previous CHT models were developed for small tube geometries, which differ from the containment of SMR. This study examined the scaled relations of a physics-based CHT model for analyzing laminar and turbulent film condensation downward flow conditions inside scaled tube geometries.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Multiphysics Computational-Fluid-Dynamics (CFD) for Design and Scale-Up of Gas Bioreactors that Utilize CO2

Gas fermentation technology offers sustainable and high carbon-efficiency routes to fuels and chemicals. However, efficiently delivering low-solubility substrate gases to production-scale bioreactors is a significant technical challenge that could limit productivity. We perform fundamental and applied multiphysics computational fluid dynamics (CFD) research targeting specific challenges of gas delivery in fermentation systems that utilize varied gas-compositions, for e.g. CO2/CO/CH4/H2 substrates: bubble dynamics, coupled mass-transfer and reaction, that can lead to optimal reactor designs at scale. This work will support BETO goals towards greenhouse gas reduction, derisking technologies toward commercialization/deployment and sustainable-aviation-fuel synthesis targets.

BIOMASS FUELS↗

Presentation: Evaluating scaling effects of steam condensation physics-based model for small modular reactors safety

This study focused on assessing condensation heat transfer (CHT) models for enhancing the passive safety of small modular reactors (SMRs). It also encompassed a review of the theoretical and semi-theoretical CHT models and correlations. Condensation models such as the degradation factor, heat and mass transfer analogy (HMTA), and boundary layer models are used to study advanced nuclear reactor PCCS. The previous CHT models were developed for small tube geometries, which differ from the containment of SMR. This study examined the scaled relations of a physics-based CHT model for analyzing laminar and turbulent film condensation downward flow conditions inside scaled tube geometries.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Influence of Thermal Energy Storage Integration Strategy on System Performance and Refrigerant Charge for Small-Scale R290 Heat Pumps

As small-scale (2.5 – 5 kW) heat pumps across the US increase straining the grid during peak hours, integrated heat pump thermal energy storage (HP-TES) systems can assist by load shifting. However, challenges arise when assembling these systems, as direct refrigerant-phase change material (PCM) heat exchangers (HXs) increase refrigerant charge, and indirect secondary loops degrade HP-TES performance. In this work, direct and indirect HP-TES configurations were sized using commercially available HXs to compare the available load shift time and performance at similar refrigerant charges. For the same indirect 5 kW HP-TES refrigerant charge, directly HP-TES can operate up to 72 and 145 minutes in cooling and heating modes, respectively, using small diameter tubes. Using Modelica, COP increases for direct and indirect HP-TES were 22% and 9%, respectively, given the parasitic losses in the indirect HP-TES. Overall, small-scale direct HP-TES can have comparable refrigerant charges with indirect HP-TES maximizing COP improvements.

25 ENERGY STORAGE↗

Modeling Continuous Online Refueling with SCALE 6.3.1 and Serpent-2 in the EIRENE Novel Molten Salt Reactor Design

The Molten Salt Reactor (MSR) is a Generation IV advanced fission reactor design in which the coolant, and in some cases the fuel itself, is in the form of liquid molten alkali-halide salts with a fluoride or chloride ionic base. In liquid-fueled MSRs, reactor refueling may be performed online, where fresh fuel salt is added to the core during operation without the need for shutdown periods. Refueling for these reactor designs is typically modeled using either a batch or continuous refueling approach, both of which can be simulated with the SCALE 6.3.1 and Serpent-2 code systems. However, the specific manner in which they are implemented can vary depending upon the desired rate of refueling, whether the refueling rate is constant or variable, and consideration of salt drainage for systems where the in-core salt volume is kept constant. In a novel MSR fuel cycle concept termed the “Sourdough” fuel cycle, fuel salt is allowed to “grow” within the core, with excess salt either being transferred to an external holding tank to maintain a constant core volume or diverted to an upper plenum within the core to allow for volume growth. In this work, continuous refueling was modeled in a thermal-spectrum, LEU-fueled, small MSR design operating with the Sourdough fuel cycle using the SCALE 6.3.1 and Serpent-2 codes. Two different continuous refueling approaches were simulated, with the performance of each being compared to determine which is most suitable for use with the Sourdough fuel cycle concept.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Performance Evaluation of Different Parallel Programming Models in SCALE-Shift Sequences for Criticality and Shielding Applications [Abstract]

The SCALE code system has been widely used for nuclear criticality safety, reactor physics, radiation shielding, source term generation, and inventory analyses by researchers, industry, and regulatory bodies. Although limited support for shared- and distributed-memory parallel processing was introduced via C++ threading, OpenMP, and MPI, a hybrid parallel programming model with both distributed- and shared-memory parallelism has not been fully supported in the SCALE code system.

Nuclear Criticality Safety Program (NCSP)↗

Dynamic Scaling Analysis of Accelerated Irradiation Testing on Additive Manufacturing Materials by Positron Annihilation

The timely applications of Additive Manufacturing (AM) materials in nuclear environments require accelerated irradiation tests, mainly ion irradiation to enable rapid prototyping. Low dose ion irradiation would cause sub-nanostructure changes by generation of lattice defects, vacancies, vacancy clusters and voids and void swelling caused by cellular dislocations. Positron Annihilation Lifetime (PAL), a novel technology, sensitive towards sub-nanostructure morphology with high accuracy (about 10-7 vacancy per atom), supported by Transition Electron Microscope (TEM) would be applied to identify the type and total size of the defects. The subsequent PAL measurements and TEM surface studies would be followed by PAL analysis that includes sophisticated trapping model. The PAS results would become an input to dynamic scaling analysis (that predicts radiation effects from low dose studies for high dose effects), which incorporate mean-field theory model. The final effect is an in-depth understanding of the microstructure evolution of AM materials under ion irradiation which can be extrapolated to the studies of neutron irradiation, since ion-irradiation takes less time and do not cause the irradiation hazard. The working hypothesis is that PAL technology, that have excellent sensitivity to low-defect concentration would help to identify ion-induced material damage on the atomic and nano-scale level, which then could be extrapolated to understand the neutron damage better.

accelerated irradiation testing↗

Data readiness pipeline patterns for scientific AI at scale: Insights from climate, fusion, life sciences, and materials

This article examines how data readiness for AI principles apply to large scientific datasets used to train foundation models. We analyze archetypal workflows across four representative domains—climate, nuclear fusion, life sciences, and materials—to identify common preprocessing patterns and domain‐specific constraints. We introduce a two‐dimensional readiness model that combines canonical preprocessing patterns with a five‐level operational readiness scale, both tailored to high‐performance computing (HPC) environments. This construct helps outline key challenges in transforming large‐scale scientific data into formats suitable for scalable AI training. Together, these dimensions form a conceptual maturity matrix that characterizes scientific data readiness and guides infrastructure development toward standardized, cross‐domain support for scalable and reproducible AI for science. Finally, we evaluate this maturity matrix in the context of case studies including ClimaX (climate), AFLOW (materials), OpenFold (proteomics), and DIII‐D fusion disruption‐prediction workflows, from which we distill lessons learned and provide recommendations to guide practitioners in developing robust AI‐readiness pipelines. Finally, we discuss remaining cross‐cutting challenges that persist across scientific domains.

97 MATHEMATICS AND COMPUTING↗