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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Development of a TRISO assessment case for BISON based on transient experiments in the NSRR

The tristructural isotropic (TRISO) fuel assessment and validation database currently available in BISON is based mainly on steady-state irradiation and high-temperature furnace testing. Transient assessment cases are needed to support ongoing U.S. industry efforts to design and deploy commercial reactors that utilize TRISO fuels. Most available historical transient tests involving TRISO fuels were characterized by power densities, temperatures, and energy depositions that were highly conservative with respect to typical high-temperature gas-cooled reactor (HTGR) accident conditions. Nonetheless, assessment of BISON's predictive capabilities, adaptation of material properties toward high-temperature and high-particle-power regimes, and development of a systematic approach to validating BISON for TRISO transient applications now motivate the modeling of historical transient tests. This work describes the development of 1-D thermal models of transient experiments conducted at the Nuclear Safety Research Reactor (NSRR) in Japan, with BISON predictions of energy deposition, UO2 melting onset, and molten volume fractions being compared against experimental measurements. Melting is accounted for by defining an effective specific heat capacity for UO2—one that leverages the material's heat of melting. BISON's predictions of energy deposition and molten volume fraction are in good agreement with the experimental data from the low-energy-deposition tests; however, BISON tends to overpredict melting at higher energy depositions. Though overly conservative compared to the operating conditions expected for near-term TRISO-fueled reactor applications, these simulations effectively exercise BISON TRISO models over a wider range of conditions than those encompassed by the existing assessment database. Potential contributors to the observed discrepancies are noted and additional future developments proposed.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

A rheological model for loose sands with insights from DEM

A rheological model for loose granular media is developed to capture both solid-like and fluid-like responses during shearing. The proposed model is built by following the mathematical structure of an extended Kelvin–Voigt model, where an elastic spring and plastic slider act in parallel to a viscous damper. This arrangement requires the partition of the total stress into rate-independent and rate-dependent stress components. To model the solid-like behavior, a simple frictional plasticity model is adopted without modifications, thus contributing to the rate-independent stress. Instead, the fluid-like or rate-dependent stress is further decomposed into deviatoric and volumetric parts, by proposing a new formulation based on a combination of the μ(I) relation, originally developed under pressure-controlled shear, with a pressure-shear rate relation derived under volume-controlled shear. The proposed formulation allows the model to capture both the increase in the friction coefficient and the enhanced dilation at high shear rates. High-fidelity simulation data, obtained from discrete element method and multiscale modelling, are used to evaluate the performance of the proposed constitutive model. The model provides accurate results under both drained and undrained simple shear paths across a wide range of shear rates. Furthermore, it successfully reproduces at much lower computational cost the flowslide mobility computed through multiscale simulations, which is primarily regulated by the shear rate dependence of the material properties during the dynamic runout stage.

Elasticity↗
DOE OSTI2023

Solution Structure and Scaling Laws of Cylindrical and Tapered Bottlebrush Polymers

Bottlebrush polymers are a unique class of macromolecular architectures with a plethora of potential industrial and pharmaceutical applications that critically depend on the bottlebrush shape and dimensions. Here, a systematic series of 12 cylindrical and 12 cone-shaped (tapered) bottlebrush polymers with poly(tert-butyl acrylate) (PtBA) or polystyrene (PS) side chains were synthesized using the sequential addition of macromonomers ring-opening metathesis polymerization (SAM-ROMP) grafting-through method. Small-angle neutron scattering (SANS) studies on dilute solutions of the two types of bottlebrush polymers provided noninvasive characterization of their structural dimensions and chain conformations. Simulated SANS traces, generated using coarse-grained molecular dynamics simulations, reproduced the distinctive features observed in the experimental SANS signals and provided necessary validation for data modeling. The combined analysis of experimental and simulated SANS signals yielded key structural and conformational parameters, including the bottlebrush radius, length, and Kuhn length as well as the excluded volume parameter and the correlation length of the polymer side chains. Importantly, the obtained structural parameters followed well-defined scaling laws as a function of the backbone and side chain degrees of polymerization, as predicted by mean field theories. In conclusion, these findings provide clear experimental and computational evidence of the interdependence of structural and conformational properties in an important class of polymer architectures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Application of performance portability solutions for GPUs and many-core CPUs to track reconstruction kernels

Next generation High-Energy Physics (HEP) experiments are presented with significant computational challenges, both in terms of data volume and processing power. Using compute accelerators, such as GPUs, is one of the promising ways to provide the necessary computational power to meet the challenge. The current programming models for compute accelerators often involve using architecture-specific programming languages promoted by the hardware vendors and hence limit the set of platforms that the code can run on. Developing software with platform restrictions is especially unfeasible for HEP communities as it takes significant effort to convert typical HEP algorithms into ones that are efficient for compute accelerators. Multiple performance portability solutions have recently emerged and provide an alternative path for using compute accelerators, which allow the code to be executed on hardware from different vendors. We apply several portability solutions, such as Kokkos, SYCL, C++17 std::execution::par, Alpaka, and OpenMP/OpenACC, on two mini-apps extracted from the mkFit project: p2z and p2r. These apps include basic kernels for a Kalman filter track fit, such as propagation and update of track parameters, for detectors at a fixed z or fixed r position, respectively. The two mini-apps explore different memory layout formats. We report on the development experience with different portability solutions, as well as their performance on GPUs and many-core CPUs, measured as the throughput of the kernels from different GPU and CPU vendors such as NVIDIA, AMD and Intel.

Kwok, Ka Hei Martin↗
DOE OSTI2020

Control of Weld Residual Stress in a Thin Steel Plate through Low Transformation Temperature Welding Consumables

Low transformation temperature welding (LTTW) consumables are characterized by a low martensite start temperature and a large fraction of martensite forming in the weld. It can efficiently reduce the tensile residual stress because the volume expansion associated with the martensitic transformation compensates for the thermal contraction during cooling. In this work, a LTTW wire, designated as EH200B, was created for the arc welding of advanced high-strength steel thin plates. In comparison to conventional ER70S-3 wires, this LTTW wire generated an opposite distortion pattern. Neutron diffraction measurements along the center thickness of the welded plates showed the maximum residual stress along the longitudinal direction (LD) in the weld region, and the heat-affected zone (HAZ) immediately adjacent to the weld region was reduced from ~330 MPa to below 240 MPa by using the LTTW wire. A finite element (FE) model was developed to predict the residual stress distributions of the plates welded under these two wires. The simulation results showed reasonable agreement with the volume-average neutron diffraction data. Compressive residual stress in the weld region using the LTTW wire was predicted by the FE method. Electron backscattered diffraction and x-ray diffraction measurements confirmed ~90% martensite was present in the LTTW weld. The fatigue life of DP980 steel lap joint panels using EH200B wire nearly doubled that of ER70S-3 wire. This improvement was attributed to the high strength and low LD residual stress in the weld and HAZ immediately adjacent to the weld.

36 MATERIALS SCIENCE↗
DOE OSTI2021

GPU-Accelerated Machine Learning Inference as a Service for Computing in Neutrino Experiments

Machine learning algorithms are becoming increasingly prevalent and performant in the reconstruction of events in accelerator-based neutrino experiments. These sophisticated algorithms can be computationally expensive. At the same time, the data volumes of such experiments are rapidly increasing. The demand to process billions of neutrino events with many machine learning algorithm inferences creates a computing challenge. We explore a computing model in which heterogeneous computing with GPU coprocessors is made available as a web service. The coprocessors can be efficiently and elastically deployed to provide the right amount of computing for a given processing task. With our approach, Services for Optimized Network Inference on Coprocessors (SONIC), we integrate GPU acceleration specifically for the ProtoDUNE-SP reconstruction chain without disrupting the native computing workflow. With our integrated framework, we accelerate the most time-consuming task, track and particle shower hit identification, by a factor of 17. This results in a factor of 2.7 reduction in the total processing time when compared with CPU-only production. For this particular task, only 1 GPU is required for every 68 CPU threads, providing a cost-effective solution.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Application of performance portability solutions for GPUs and many-core CPUs to track reconstruction kernels

Next generation High-Energy Physics (HEP) experiments are presented with significant computational challenges, both in terms of data volume and processing power. Using compute accelerators, such as GPUs, is one of the promising ways to provide the necessary computational power to meet the challenge. The current programming models for compute accelerators often involve using architecture-specific programming languages promoted by the hardware vendors and hence limit the set of platforms that the code can run on. Developing software with platform restrictions is especially unfeasible for HEP communities as it takes significant effort to convert typical HEP algorithms into ones that are efficient for compute accelerators. Multiple performance portability solutions have recently emerged and provide an alternative path for using compute accelerators, which allow the code to be executed on hardware from different vendors. We apply several portability solutions, such as Kokkos, SYCL, C++17 std::execution::par and Alpaka, on two mini-apps extracted from the mkFit project: p2z and p2r. These apps include basic kernels for a Kalman filter track fit, such as propagation and update of track parameters, for detectors at a fixed z or fixed r position, respectively. The two mini-apps explore different memory layout formats. We report on the development experience with different portability solutions, as well as their performance on GPUs and many-core CPUs, measured as the throughput of the kernels from different GPU and CPU vendors such as NVIDIA, AMD and Intel.

Kwok, Ka Martin↗
DOE OSTI2022

Local stress within a granular molecular solvent matrix, a mechanism for individual ion hydration

The activity of water is important in many natural systems and directed processes. To better understand water activity, the hydration of individual ions is approximated for a recently developed speciation-based solution model. Here a matrix of values for hydration of complete salts (anion and cation) was used as source data to calculate individual ion hydration values. Some electrolytes were excluded from calculations of individual ion hydration due to the prevalence of ion pairing and resulting liberation of water upon ion pairing. Evaluation of the periodic trends emerging from individual ion hydration values suggests that ionic volume, relative to the volume of molecular water, dictates both modeled hydration requirements (related to vapor-liquid-equilibrium-derived activity) as well as properties historically described by hydrodynamic radius (ion diffusion and solution viscosity). When water is conceptualized as a granular three-dimensional matrix, solutes may function as substitutional defects (dilation or constriction) inducing local compressive or tensile stress. These results have implications on the mechanism of the Hofmeister series and series reversals.

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

Fragment-based determination of a proteinase K structure from MicroED data using ARCIMBOLDO_SHREDDER

Structure determination of novel biological macromolecules by X-ray crystallography can be facilitated by the use of small structural fragments, some of only a few residues in length, as effective search models for molecular replacement to overcome the phase problem. Independence from the need for a complete pre-existing model with sequence similarity to the crystallized molecule is the primary appeal of ARCIMBOLDO , a suite of programs which employs this ab initio algorithm for phase determination. Here, the use of ARCIMBOLDO is investigated to overcome the phase problem with the electron cryomicroscopy (cryoEM) method known as microcrystal electron diffraction (MicroED). The results support the use of the ARCIMBOLDO_SHREDDER pipeline to provide phasing solutions for a structure of proteinase K from 1.6 Å resolution data using model fragments derived from the structures of proteins sharing a sequence identity of as low as 20%. ARCIMBOLDO_SHREDDER identified the most accurate polyalanine fragments from a set of distantly related sequence homologues. Alternatively, such templates were extracted in spherical volumes and given internal degrees of freedom to refine towards the target structure. Both modes relied on the rotation function in Phaser to identify or refine fragment models and its translation function to place them. Model completion from the placed fragments proceeded through phase combination of partial solutions and/or density modification and main-chain autotracing using SHELXE . The combined set of fragments was sufficient to arrive at a solution that resembled that determined by conventional molecular replacement using the known target structure as a search model. This approach obviates the need for a single, complete and highly accurate search model when phasing MicroED data, and permits the evaluation of large fragment libraries for this purpose.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Co-Firing Switchgrass and Waste Coal in A Power Plant: A Techno-Economic and Life Cycle Evaluation for The Ohio River Valley (SWITCH) (Final Technical Report for Ohio State/FE0032204)

Abandoned coal mine lands (AMLs) represent one of the most persistent environmental challenges in the United States. Prior to the enactment of the Surface Mining Control and Reclamation Act (SMCRA) in 1977, coal mining operations were not legally required to reclaim disturbed lands, leaving behind approximately 500,000 AML sites nationwide. These sites pose severe environmental and health risks, including acid mine drainage, soil and water contamination, and spontaneous combustion of waste coal piles. Millions of Americans live within one mile of these AMLs, underscoring the urgency of remediation. Traditional reclamation practices, such as planting cool-season grasses, often fail to fully restore ecological function or leverage the economic potential of these lands. This project addressed these challenges by developing integrated strategies for resource recovery, land reclamation, and sustainable energy production. This project evaluated an integrated strategy to convert this liability into an opportunity by recovering waste coal and co-firing it with switchgrass (Panicum virgatum L.) cultivated on reclaimed or marginal AML areas in existing coal-fired power plants. Switchgrass not only provides a renewable feedstock but also aids in land reclamation and carbon sequestration. 1) Remote Sensing and Machine Learning for Waste Coal Identification Using Sentinel-2 satellite imagery and supervised classification, we applied four machine learning models to detect historical waste coal piles. Random Forest achieved the highest accuracy (precision: 86%, recall: 77%). Time-series analysis revealed gradual vegetation recovery since 1986, indicating natural reclamation processes in historical sites, while active mining areas showed ongoing disturbance. This workflow enables scalable monitoring and prioritization of reclamation efforts. 2) UAS-Based Stockpile Volume Estimation To quantify recoverable waste coal, we evaluated Unmanned Aerial Systems (UAS) equipped with Light Detection and Ranging (LiDAR) and multispectral sensors. Structure-from-Motion (SfM) photogrammetry combined with interpolated Digital Terrain Models (DTMs) achieved strong agreement with LiDAR reference volumes (Root Mean Square Error (RMSE) ≈147 m 3 , Mean Absolute Percentage Error (MAPE) ≈2%). Sensitivity analysis confirmed that spatial resolution significantly influences accuracy, emphasizing the need for high-resolution data for precise volume estimation. This approach offers a scalable, cost-effective, and accurate alternative to conventional ground-based surveys. 3) Switchgrass Cultivation for Bioenergy and Water Quality Improvement We assessed the hydrological and water quality impacts of converting AMLs to switchgrass production areas using the Soil and Water Assessment Tool (SWAT). Results showed that converting 10% of the watershed area into the switchgrass production zone reduced streamflow by 3.1%, total suspended solids by 18.1%, total nitrogen by 7.6%, and total phosphorus by 6.2%, while achieving biomass yields of 8.6–9.2 metric tons per hectare. These findings highlight switchgrass as a dual-benefit strategy for land reclamation and bioenergy feedstock production. 4) Integrated Co-Firing and CCS for Carbon-Negative Power Generation We modeled co-firing scenarios using the Power Plant Flexible Model (PPFM) to evaluate plant efficiency, greenhouse gas (GHG) emissions, and levelized cost of electricity (LCOE). Without carbon capture and storage (CCS), increasing switchgrass co-firing ratios reduced LCOE from $\$$150/MWh at 0% biomass to $\$$110/MWh at full substitution. Under CCS, costs remained higher (~$\$$250/MWh at 0% biomass) but decreased to $\$$200/MWh at 100% biomass, while enabling net-zero or carbon-negative electricity due to switchgrass sequestration benefits. Although CCS introduced efficiency penalties, pairing it with biomass co-firing offset these impacts and maximized climate benefits. Overall, optimizing co-firing ratios between 60-100%, supported by reliable logistics and storage strategies, emerged as a practical pathway to balance affordability, sustainability, and net-zero or negative GHG emissions while promoting productive reuse of AMLs.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Resolving experimental biases in the interpretation of diffusion experiments with a user-friendly numerical reactive transport approach

The reactive transport code CrunchClay was used to derive effective diffusion coefficients (D e ), clay porosities (ε), and adsorption distribution coefficients (K D ) from through-diffusion data while considering accurately the influence of unavoidable experimental biases on the estimation of these diffusion parameters. These effects include the presence of filters holding the solid sample in place, the variations in concentration gradients across the diffusion cell due to sampling events, the impact of tubing/dead volumes on the estimation of diffusive fluxes and sample porosity, and the effects of O-ring-filter setups on the delivery of solutions to the clay packing. Doing so, the direct modeling of the measurements of (radio)tracer concentrations in reservoirs is more accurate than that of data converted directly into diffusive fluxes. While the above-mentioned effects have already been described individually in the literature, a consistent modeling approach addressing all these issues at the same time has never been described nor made easily available to the community. A graphical user interface, CrunchEase, was created, which supports the user by automating the creation of input files, the running of simulations, and the extraction and comparison of data and simulation results. While a classical model considering an effective diffusion coefficient, a porosity and a solid/solution distribution coefficient (D e –ε–K D ) may be implemented in any reactive transport code, the development of CrunchEase makes it easy to apply by experimentalists without a background in reactive transport modeling. CrunchEase makes it also possible to transition more easily from a D e –ε–K D modeling approach to a state-of-the-art process-based understanding modeling approach using the full capabilities of CrunchClay, which include surface complexation modeling and a multi-porosity description of the clay packing with charged diffuse layers.

58 GEOSCIENCES↗
DOE OSTI2023

Three-dimensional phenotyping of peach tree-crown architecture utilizing terrestrial laser scanning

Tree training systems for temperate fruit have been developed throughout history by pomologists to improve light interception, fruit yield, and fruit quality. These training systems direct crown and branch growth to specific configurations. Quantifying crown architecture could aid the selection of trees that require less pruning or that naturally excel in specific growing/training system conditions. Regarding peaches [Prunus persica (L.) Batsch], access tools such as branching indices have been developed to characterize tree-crown architecture. However, the required branching data (BD) to develop these indices are difficult to collect. Traditionally, BD have been collected manually, but this process is tedious, time-consuming, and prone to human error. These barriers can be circumnavigated by utilizing terrestrial laser scanning (TLS) to obtain a digital twin of the real tree. TLS generates three-dimensional (3D) point clouds of the tree crown, wherein every point contains 3D coordinates (x, y, z). To facilitate the use of these tools for peach, we selected 16 young peach trees scanned in 2021 and 2022. These 16 trees were then modeled and quantified using the open-source software TreeQSM. As a result, “in silico” branching and biometric data for the young peach trees were calculated to demonstrate the capabilities of TLS phenotyping of peach tree-crown architecture. The comparison and analysis of field measurements (in situ) and in silico BD, biometric data, and quantitative structural model branch uncertainty data were utilized to determine the reconstructive model’s reliability as a source substitute for field measurements. Mean average deviation when comparing young tree (YT) height was approx. 5.93%, with crown volume was approx. 13.26% across both 2021 and 2022. All point clouds of the YTs in 2022 showed residuals lower than 12 mm to cylinders fitted to all branches, and mean surface coverage greater than 40% for both the trunk and primary branching orders.

09 BIOMASS FUELS↗
DOE OSTI2022

Methane liquefaction with an active magnetic regenerative refrigerator

This manuscript reports liquefaction of methane using an active magnetic regenerative refrigerator (AMRR). The AMRR used to cool from 285 K to 135 K has two identical regenerators fabricated with adjacent layers of four ferromagnetic refrigerants, each with sequentially lower Curie temperatures and lesser masses from hot to cold temperatures. The dual multilayer regenerators were assembled in opposition with a single cold region between them. For this set of experiments equal mass of helium gas was pumped through all layers of the regenerators during the two flow steps of the four-step AMR cycle. After successfully reaching 135 K, a compact condensing coil-fin tube heat exchanger (HEX) with a small storage vessel was mounted in the cold region of the dual regenerator assembly to be cooled during the hot-to-cold helium flow from alternatively demagnetized regenerators. The cold HEX was used to cool and liquefy a process stream of methane gas supplied at 295 K and different pressures in different runs. Further, by measuring time to liquefy a known volume of methane at three different pressures, cooling powers of the AMRR as a function of temperature were determined. The resultant data were compared to those predicted by the AMRR performance model. Conclusions from these experiments and suggestions for future work are presented.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Electrical conductivity of porous binary powder mixtures

Simultaneous data of the quasi-static compaction and electrical conductivity of porous, binary powder mixtures have been collected as a function of bulk density. The powder mixtures consist of a metal conductor, either titanium or iron, an insulator, and pores filled with ambient air. The data show a dependency of the conductivity in terms of relative bulk density and metal volume fraction on conductor type and conductor particle characteristics of size and shape. Finally, finite element models using particle domains generated by discrete element method are used to simulate the bulk conductivity near its threshold while the general effective media equation is used to model the conductivity across the compression regime.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Development of a BISON validation case for the TRISO transient irradiations in NSRR using effective heat capacity methods

The current tristructural isotropic (TRISO) fuel assessment and validation database in BISON primarily covers steady- state irradiation and high-temperature furnace testing. Transient assessment cases are potentially needed to support U.S. industry efforts in designing and deploying commercial reactors using TRISO fuels. Historical transient tests in- volving TRISO fuels used highly conservative conditions compared to the typical high-temperature gas-cooled reactor accident scenarios. Despite this, modeling historical transient tests is fundamental for evaluating BISON’s predictive capabilities, adapting material properties for high-temperature and high-particle-power regimes, and developing a sys- tematic validation approach for TRISO transient applications. This work developed a 1D model of transient experiments carried out at the Nuclear Safety Research Reactor using BISON. BISON’s predictions of energy deposition, UO 2 melting onset, and molten volume fractions are compared against experimental measurements. Melting was modeled using an effective specific heat capacity model for UO 2 . We found that BISON’s predictions are in reasonable agreement with experimental data for low-energy-deposition cases, and that BISON overpredicts melting at higher energy depositions. We also discuss the potential causes of discrepancies between the simulated and measured results and propose ways to further develop the model. Although these simulations used conservative conditions compared to those expected for actual TRISO-fueled reactors, they extended the range of conditions reflected in the data in the existing BISON database for TRISO fuels.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Characterization of ELM pacing via vertical jogs on DIII-D

Edge localized mode (ELM) pacing via vertical plasma oscillations or jogging has been successfully demonstrated on DIII-D. Rapid vertical movement of the plasma toward the X-point has been shown to effectively trigger ELMs. By vertically oscillating the plasma at a rate of 10 Hz, the ELM frequency increased from ~5 Hz, the natural ELM frequency in similar DIII-D discharges, to 20 Hz. Downward jogs have been observed to trigger multiple ELMs in one cycle. ELMs triggered at higher than natural frequencies lead to smaller decreases in stored energy, from 8% to as little as below 1%. As a consequence, the peak heat flux to the divertor has been observed to be reduced by a factor of ~2. In addition, a reduction in the carbon impurity concentration has been observed. During downward jogs in the lower single null (LSN) configuration, the X-point movement is slower and smaller than the top of the plasma. As a result, a reduction in the plasma cross-section and hence volume has been observed. To understand the mechanism of ELM triggering by jogging, a toy model of the edge toroidal current has been built and tested with DIII-D experiment data. The experimental data and model suggest that when the plasma moves down toward the X-point, a net positive toroidal current is locally induced in the edge region. ELITE stability analysis suggests that this current pushes the plasma state across the peeling side of the peeling–ballooning stability boundary into the unstable region triggering ELMs.

ELM pacing↗
DOE OSTI2022

CompF2: Theoretical Calculations and Simulation Topical Group Report

This report summarizes the work of the Computational Frontier topical group on theoretical calculations and simulation for Snowmass 2021. We discuss the challenges, potential solutions, and needs facing six diverse but related topical areas that span the subject of theoretical calculations and simulation in high energy physics (HEP): cosmic calculations, particle accelerator modeling, detector simulation, event generators, perturbative calculations, and lattice QCD (quantum chromodynamics). The challenges arise from the next generations of HEP experiments, which will include more complex instruments, provide larger data volumes, and perform more precise measurements. Calculations and simulations will need to keep up with these increased requirements. The other aspect of the challenge is the evolution of computing landscape away from general-purpose computing on CPUs and toward special-purpose accelerators and coprocessors such as GPUs and FPGAs. These newer devices can provide substantial improvements for certain categories of algorithms, at the expense of more specialized programming and memory and data access patterns.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Improved Upper Limit on Degree-scale CMB B -mode Polarization Power from the 670 Square-degree POLARBEAR Survey

We report an improved measurement of the degree-scale cosmic microwave background B-mode angular-power spectrum over 670 deg 2 sky area at 150 GHz with Polarbear. In the original analysis of the data, errors in the angle measurement of the continuously rotating half-wave plate, a polarization modulator, caused significant data loss. By introducing an angle-correction algorithm, the data volume is increased by a factor of 1.8. We report a new analysis using the larger data set. We find the measured B-mode spectrum is consistent with the ΛCDM model with Galactic dust foregrounds. We estimate the contamination of the foreground by cross-correlating our data and Planck 143, 217, and 353 GHz measurements, where its spectrum is modeled as a power law in angular scale and a modified blackbody in frequency. We place an upper limit on the tensor-to-scalar ratio r < 0.33 at 95% confidence level after marginalizing over the foreground parameters.

79 ASTRONOMY AND ASTROPHYSICS↗