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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Scalable Quantum Monte Carlo Method for Polariton Chemistry via Mixed Block Sparsity and Tensor Hypercontraction Method

We present a reduced-scaling auxiliary-field quantum Monte Carlo (AFQMC) framework designed for large molecular systems and ensembles, with or without coupling to optical cavities. Our approach leverages the natural block sparsity of the Cholesky decomposition (CD) of electron repulsion integrals in molecular ensembles and employs tensor hypercontraction (THC) to efficiently compress low-rank Cholesky blocks. By representing the Cholesky vectors in a mixed format, keeping high-rank blocks in block-sparse form and compressing low-rank blocks with THC, we reduce the scaling of exchange-energy evaluation from quartic to robust cubic in the number of molecular orbitals N, while lowering memory from cubic toward quadratic. Benchmark analyses on one-, two-, and three-dimensional molecular ensembles (up to ∼1,200 orbitals) show that (a) the number of nonzeros in Cholesky tensors grows linearly with system size across dimensions; (b) the average numerical rank increases sublinearly and does not saturate at these sizes; and (c) rank heterogeneity─some blocks nearly full rank and many low rank, naturally motivates the proposed mixed block sparsity and THC scheme for efficient calculation of exchange energy. In conclusion, we demonstrate that the mixed scheme yields cubic wall-time scaling with favorable prefactors and preserves AFQMC accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Deep graph representations embed network information for robust disease marker identification

We report that the accurate disease diagnosis and prognosis based on omics data rely on the effective identification of robust prognostic and diagnostic markers that reflect the states of the biological processes underlying the disease pathogenesis and progression. In this article, we present GCNCC, a Graph Convolutional Network-based approach for Clustering and Classification, that can identify highly effective and robust network-based disease markers. Based on a geometric deep learning framework, GCNCC learns deep network representations by integrating gene expression data with protein interaction data to identify highly reproducible markers with consistently accurate prediction performance across independent datasets possibly from different platforms. GCNCC identifies these markers by clustering the nodes in the protein interaction network based on latent similarity measures learned by the deep architecture of a graph convolutional network, followed by a supervised feature selection procedure that extracts clusters that are highly predictive of the disease state. By benchmarking GCNCC based on independent datasets from different diseases (psychiatric disorder and cancer) and different platforms (microarray and RNA-seq), we show that GCNCC outperforms other state-of-the-art methods in terms of accuracy and reproducibility.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Expanding the representation of aerosol, cloud, and precipitation processes with graph network-based simulators

We explored a novel framework for simulating the small-scale processes that drive the evolution of aerosol, cloud, and precipitation particles, which are a critical gap in the predictive understanding of weather and climate. Particle-based methods have emerged as an effective tool for modeling aerosol-cloud-precipitation interactions, but existing particle-based models are computationally too expensive to simulate the large domains relevant for the atmosphere or to represent the full suite of relevant processes. The lack of a comprehensive and efficient reference model is a critical bottleneck in our understanding of cloud and precipitation processes and our ability to parameterize these processes for regional- and global-scale simulations. To address this need, we explored an approach to accelerate and expand particle-based models using a new machine learning approach, graph network-based simulators (GNS). Rather than modeling the evolution of the system by numerically integrating continuity equations, the GNS represents dynamics through learned message passing. Our aim was to develop fast and accurate surrogate models for particle-based simulations. We explored applying GNS to simulate cloud droplet transport, growth, and evaporation under turbulent conditions, but we found the GNS over-smoothed the simulations. We then applied the GNS to simulate aerosol dynamics through gas condensation and found the GNS was able to reproduce the benchmark, physics-based simulation with high accuracy.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

NASA Software Engineering Benchmarking Effort

Benchmarking was very interesting and provided a wealth of information (1) We did see potential solutions to some of our "top 10" issues (2) We have an assessment of where NASA stands with relation to other aerospace/defense groups We formed new contacts and potential collaborations (1) Several organizations sent us examples of their templates, processes (2) Many of the organizations were interested in future collaboration: sharing of training, metrics, Capability Maturity Model Integration (CMMI) appraisers, instructors, etc. We received feedback from some of our contractors/ partners (1) Desires to participate in our training; provide feedback on procedures (2) Welcomed opportunity to provide feedback on working with NASA

Godfrey, Sally↗
DOE OSTI2013

A Local Incident Flux Response Expansion Transport Method for Coupling to the Diffusion Method in Cylindrical Geometry

A local incident flux response expansion transport method is developed to generate transport solutions for coupling to diffusion theory codes regardless of their solution method (e.g., fine mesh, nodal, response based, finite element, etc.) for reactor core calculations in both two-dimensional (2-D) and three-dimensional (3-D) cylindrical geometries. In this approach, a Monte Carlo method is first used to precompute the local transport solution (i.e., response function library) for each unique transport coarse node, in which diffusion theory is not valid due to strong transport effects. The response function library is then used to iteratively determine the albedo coefficients on the diffusion-transport interfaces, which are then used as the coupling parameters within the diffusion code. This interface coupling technique allows a seamless integration of the transport and diffusion methods. The new method retains the detailed heterogeneity of the transport nodes and naturally constructs any local solution within them by a simple superposition of local responses to all incoming fluxes from the contiguous coarse nodes. A new technique is also developed for coupling to fine-mesh diffusion methods/codes. The local transport method/module is tested in 2-D and 3-D pebble-bed reactor benchmark problems consisting of an inner reflector, an annular fuel region, and a controlled outer reflector. It is found that the results predicted by the transport module agree very well with the reference fluxes calculated directly by MCNP in both benchmark problems.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Prototype Demonstration of an Integration of a Gibbs Energy Minimizer with TRANSFORM for Molten Salt Reactor Mass Accountancy Studies

Mass accountancy in a molten salt reactor (MSR) system is the ability to track and quantify the radioactive species throughout all portions of the reactor, not just the core. This is critical for the design, analysis, and regulation of these novel reactors. This report discusses a chemistry-based approach for understanding the chemical state, physical characteristics, and time-dependent location of a species throughout an MSR system. This report does not represent a completed capability; rather, it indicates that specific activities are needed (i.e., chemistry coupling and benchmark creation) and require sustained support to enable MSR development and deployment.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2015

Online Tools for Uncovering Data Quality (DQ) Issues in Satellite-Based Global Precipitation Products

Data quality (DQ) has many attributes or facets (i.e., errors, biases, systematic differences, uncertainties, benchmark, false trends, false alarm ratio, etc.)Sources can be complicated (measurements, environmental conditions, surface types, algorithms, etc.) and difficult to be identified especially for multi-sensor and multi-satellite products with bias correction (TMPA, IMERG, etc.) How to obtain DQ info fast and easily, especially quantified info in ROI Existing parameters (random error), literature, DIY, etc.How to apply the knowledge in research and applications.Here, we focus on online systems for integration of products and parameters, visualization and analysis as well as investigation and extraction of DQ information.

precipitation↗
DOE OSTI2018

Experimental and Computational Investigations of Plenum-to-Plenum Heat Transfer and Gas Dynamics under Natural Circulation in a Prismatic Very High Temperature Reactor

All the goals and the objectives set for the project were successfully executed and achieved and all the milestones have been successfully completed. The results that have been obtained for the first time advance the scientific and engineering knowledge and understanding of the plenum-to plenum natural convection of prismatic block nuclear reactors that is encountered during accident or abnormal operation. These have been accomplished by developing and implementing for the first time unique and flexible scaled-down separate and integrated effects experimental plenumto- plenum facility (P2PF) with dual channels at this time that has been equipped with sophisticated measurement techniques integrated in a novel way on the heated and cooled channels. The unique facility is an asset now that can be extended to research multiple channels and to study the effects of hot plumes in the plena for future projects if funding will be available. It can also be modified to research natural convection of pebble bed reactors. Hence, it complement the HTTF at Oregon State University. However, in this study, heat transfer coefficients from the inner wall surface to the flowing gas (both helium and air were used) and the radial temperature and gas velocity profiles have been measured and investigated along the height of the heated and cooled channels using in house developed wall flush mounted heat transfer probes, thermocouple with in house developed adjuster for radial movement with 1 mm increment inside the channel and hot wire anemometry with also in house developed adjuster for 1 mm radial movement inside the channel, respectively. Also advanced tracer technique has been developed to quantify also for the first time the dispersion of the gas dynamics of the hot and cold channels. The research has provided new knowledge and new benchmarking data that can be used to validate computational fluid dynamics (CFD) codes with conjugate heat transfer. The work and its results that have been performed within the budget have demonstrated their superior technical effectiveness and high economic feasibility to perform needed studies for safety analysis and assessment at least cost for these types of gas cooled very high temperature 4th generation nuclear reactors. Accordingly, the results obtained in this project and the unique facility and techniques that have been developed will benefit greatly the public by advancing the technology of the prismatic block nuclear reactors toward commercialization and to ensure they will be designed and operated safely by utilizing the obtained knowledge and having well validated CFD simulations integrated with heat transfer computations

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Development of a Novel Gas Pressurized Stripping Process-Based Technology for CO₂ Capture from Post-Combustion Flue Gases

A novel Gas Pressurized Stripping (GPS) post-combustion carbon capture (PCC) process has been developed by Carbon Capture Scientific, LLC, CONSOL Energy Inc., Nexant Inc., and Western Kentucky University in this bench-scale project. The GPS-based process presents a unique approach that uses a gas pressurized technology for CO₂ stripping at an elevated pressure to overcome the energy use and other disadvantages associated with the benchmark monoethanolamine (MEA) process. The project was aimed at performing laboratory- and bench-scale experiments to prove its technical feasibility and generate process engineering and scale-up data, and conducting a techno-economic analysis (TEA) to demonstrate its energy use and cost competitiveness over the MEA process. To meet project goals and objectives, a combination of experimental work, process simulation, and technical and economic analysis studies were applied. The project conducted individual unit lab-scale tests for major process components, including a first absorption column, a GPS column, a second absorption column, and a flasher. Computer simulations were carried out to study the GPS column behavior under different operating conditions, to optimize the column design and operation, and to optimize the GPS process for an existing and a new power plant. The vapor-liquid equilibrium data under high loading and high temperature for the selected amines were also measured. The thermal and oxidative stability of the selected solvents were also tested experimentally and presented. A bench-scale column-based unit capable of achieving at least 90% CO₂ capture from a nominal 500 SLPM coal-derived flue gas slipstream was designed and built. This integrated, continuous, skid-mounted GPS system was tested using real flue gas from a coal-fired boiler at the National Carbon Capture Center (NCCC). The technical challenges of the GPS technology in stability, corrosion, and foaming of selected solvents, and environmental, health and safety risks have been addressed through experimental tests, consultation with vendors and engineering analysis. Multiple rounds of TEA were performed to improve the GPS-based PCC process design and operation, and to compare the energy use and cost performance of a nominal 550-MWe supercritical pulverized coal (PC) plant among the DOE/NETL report Case 11 (the PC plant without CO₂ capture), the DOE/NETL report Case 12 (the PC plant with benchmark MEA-based PCC), and the PC plant using GPS-based PCC. The results reveal that the net power produced in the PC plant with GPS-based PCC is 647 MWe, greater than that of the Case 12 (550 MWe). The 20-year LCOE for the PC plant with GPS-based PCC is 97.4 mills/kWh, or 152% of that of the Case 11, which is also 23% less than that of the Case 12. These results demonstrate that the GPS-based PCC process is energy-efficient and cost-effective compared with the benchmark MEA process.

Chen, Shiaoguo↗
NASA NTRS2011

Flowfield Analysis of a Small Entry Probe (SPRITE) Tested in an Arc Jet

Results of simulations of flow of an arc-heated stream around a 14-inch diameter 45 sphere-cone configuration are presented. Computations are first benchmarked against pressure and heat flux measurements made using copper slug calorimeters of different shapes and sizes. The influence of catalycity of copper on computed results is investigated. Good agreements between predictions and measurements are obtained by assuming the copper slug to be partially catalytic to atomic recombination. With total enthalpy estimates obtained from these preliminary computations, calculations are then performed for the test article, with the nozzle and test article considered as an integrated whole the same procedure adopted for calorimeter simulations. The resulting heat fluxes at select points on the test article (points at which fully instrumented plugs were placed) are used in material thermal response code calculations. Predicted time histories of temperature are compared against thermocouple data from the instrumented plugs, and recession determined. Good agreement is obtained for in-depth thermocouples.

Prabhu, Dinesh K.↗
DOE OSTI2023

Evaluating precipitation distributions at regional scales: a benchmarking framework and application to CMIP5 and 6 models

Abstract. As the resolution of global Earth system models increases, regional-scale evaluations are becoming ever more important. This study presents a framework for quantifying precipitation distributions at regional scales and applies it to evaluate Coupled Model Intercomparison Project (CMIP) 5 and 6 models. We employ the Intergovernmental Panel on Climate Change (IPCC) sixth assessment report (AR6) climate reference regions over land and propose refinements to the oceanic regions based on the homogeneity of precipitation distribution characteristics. The homogeneous regions are identified as heavy-, moderate-, and light-precipitating areas by K-means clustering of Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) version 6 final run product (IMERG) precipitation frequency and amount distributions. With the global domain partitioned into 62 regions, including 46 land and 16 ocean regions, we apply 10 established precipitation distribution metrics. The collection includes metrics focused on the maximum peak, lower 10th percentile, and upper 90th percentile in precipitation amount and frequency distributions; the similarity between observed and modeled frequency distributions; an unevenness measure based on cumulative amount; average total intensity on all days with precipitation; and number of precipitating days each year. We apply our framework to 25 CMIP5 and 41 CMIP6 models, as well as six observation-based products of daily precipitation. Our results indicate that many CMIP5 and 6 models substantially overestimate the observed light-precipitation amount and frequency, as well as the number of precipitating days, especially over midlatitude regions outside of some land regions in the Americas and Eurasia. Improvement from CMIP5 to 6 is shown in some regions, especially in midlatitude regions, but it is not evident globally, and over the tropics most metrics point toward degradation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Hierarchically Porous Multimetal‐Based Carbon Nanorod Hybrid as an Efficient Oxygen Catalyst for Rechargeable Zinc–Air Batteries

Abstract The lack of efficient strategies to address the intrinsic activity, site accessibility, and structural stability issues of metal‐carbon hybrid catalysts is restricting their real‐world implementation on the basis of rechargeable zinc–air batteries. Herein, a dual metal–organic frameworks (MOFs) pyrolysis strategy is developed to regulate the intrinsic activity and porous structure of the derived catalysts, where a Fe 2 Ni_MIL‐88@ZnCo_zeolitic imidazolate framework (ZIF), with a hierarchically porous structure, multifunctional components, and an integrated architecture, acts as an ideal precursor to obtain multimetal based porous nanorod (FeNiCo@NC‐P). Benefitting from the synergetic effect of the multimetal components, facilitated reactant accessibility, and the well‐retained integrated structure, the resultant FeNiCo@NC‐P catalyst exhibits an oxygen reduction reaction half‐wave potential of 0.84 V as well as an oxygen evolution reaction potential of 1.54 V at 10 mA cm –2 . Furthermore, the practical application of FeNiCo@NC‐P in the zinc–air battery displays a low voltage gap and long‐term durability (over 130 h at a current density of 10 mA cm –2 ), which outperforms the commercial noble metal benchmarks. This work not only affords a competitive bifunctional oxygen electrocatalyst for zinc–air batteries but also paves a new way to design and fabricate MOF‐derived materials with tunable catalytic properties.

Ren, Dezhang↗
DOE OSTI2025

The Fluid Dynamics Uncertainty Quantification Challenge Problem: XFOIL vs. MFOIL

Uncertainty quantification (UQ) has become more critical in aerospace engineering due to the growing dependence on computational tools for design optimization and performance analyses of aerospace vehicles. Even though the significance of UQ in assessing the credibility of computational analyses is well recognized, its costs and complexity impede its integration into standard practices, particularly in computational fluid dynamics (CFD) and other fluid analyses. This paper presents a UQ study for low-fidelity computational aerodynamics analyses with XFOIL and mfoil (i.e., the MATLAB version of XFOIL with several implementation modifications); these tools are utilized widely in both research and education. The main contributions of this paper are as follows: 1) improved precision in quantifying the uncertainty of the baseline Monte Carlo results used to benchmark surrogate modeling techniques for UQ, 2) quantification of the effect of the implementation differences between XFOIL and mfoil on solution quantities of interest (QoIs), such as lift and pitching moment coefficients, and 3) development of an open-source UQ library for use with XFOIL and mfoil, which has educational values and helps promote UQ for fluid analyses with aerospace applications. Results and discussions revolve around cases 1-4 of the challenge problem posed by the AIAA Fluid Dynamics Technical Committee’s Uncertainty Quantification Discussion Group (UQDG). In case 3, this work employs CFDverify, an open-source solution verification software, to quantify the discretization error and evaluate the extrapolated QoIs based on the grid convergence index (GCI). This UQ study differentiates itself from previous studies in the rigor of handling baseline Monte Carlo uncertainty and in including mfoil, which is a more accessible alternative to XFOIL. Finally, despite the growing computing power, low-fidelity computational tools remain valuable, such as for aerodynamic shape optimization at Mach numbers below 0.65 and low-to-mid Reynolds numbers.

Lay, Aidan S [University of Tennessee, Knoxville (↗
DOE OSTI2019

Nuclear Data and Benchmarking Program: Nuclear Data Performance Assessment for Advanced Reactors

Over the last several Evaluated Nuclear Data File (ENDF)/B releases, many updates have been introduced to the nuclear data libraries that can significantly change computational results. These changes can be particularly important for advanced reactor concepts, which are not as thoroughly investigated as those used in light water reactor (LWR) systems. Therefore, a performance assessment of the ENDF/B libraries using the SCALE 6.2.3 code package was conducted under the auspices of the U.S., Department of Energy Office of Nuclear Energy (DOE-NE). The following systems relevant to the advanced reactor community were chosen as subject for investigation in this report: sodium cooled fast reactor systems, graphite moderated high temperature gas-cooled reactors, and several molten salt reactor models. At first, the similarity of the integral performance of the ENDF/B-VII.1 and ENDF/B-VIII.0 nuclear data libraries caused by compensating errors in important differential data was demonstrated. In calculations for a shipping container of high-assay low enriched uranium, the data of individual isotopes were systematically swapped between the two ENDF/B libraries. An eigenvalue difference of up to 450 pcm was found due to the use of 235 U and 238 U from one library and 1 H and 16 O from the other library. This clearly demonstrates a cross-correlation between reaction data sets of different isotopes within a library that should be reported in the evaluations. For sodium-cooled fast reactor (SFR) fuel assemblies, significant eigenvalue (k inf ) differences (200– 450 pcm) were found between calculations using the 2011 ENDF/B-VII.1 data and 2018 ENDF/B-VIII.0 data. These differences were mainly caused by updates of 238 U and 239 Pu neutron cross sections. Results from the multigroup (MG) calculations further revealed that the group structure of the applied MG library strongly influences the MG bias due to the importance of an appropriate energy resolution of the resonances in higher energy ranges. The application of previously used MG libraries requires new verification for advanced reactor simulation in comparisons with reference continuous-energy calculations. Nuclear data uncertainty analyses of these SFR systems resulted in eigenvalue uncertainties between 1,400 and 1,800 pcm, which are three to four times higher than corresponding uncertainties in light water reactor (LWR) systems. The main contributor to this uncertainty was found to be inelastic scattering on 238 U, which shows an uncertainty of up to 50% in the fast energy range. Other important contributors are the scattering reactions of 56 Fe and 23 Na which have so far not appeared in LWR analysis. Since the largest contribution to the eigenvalue uncertainty of SFR systems is coming from scattering reactions, it is expected that uncertainties in the angular scattering distributions also have a significant impact. Those uncertainties are, however, not available for the majority of nuclides, and the capabilities to determine sensitivities to this data are currently underdeveloped. For two graphite moderated high temperature gas-cooled reactor (HTGR) benchmarks, only the ENDF/BVII. 1 calculations resulted in consistent eigenvalues (k eff ) with the corresponding experimental measurements. Eigenvalue differences of about 1,000 pcm were found between the 2006 ENDF/B-VII.0 data and the 2011 ENDF/B-VII.1 data, primarily due to an updated carbon capture cross section in the thermal energy range in the later ENDF/B release. The ENDF/B-VIII.0 eigenvalue was larger than the ENDF/B-VII.1 eigenvalue by about 300 pcm mainly due to updates in multiple 235 U neutron cross sections, with offsetting updates in the 238 U cross sections. With ENDF/B-VIII.0, graphite can be modeled as perfect crystal or with two different porosities. The choice of the graphite evaluation can have a significant influence of the eigenvalue. For a HTGR benchmark, maximum eigenvalue differences as high as 650 pcm due to different porosities were observed. More detailed studies of the impact of the porosity are necessary while considering that the graphite porosity can vary between the used materials and changes as a function of neutron fluence. xii The uncertainty of the HTGR eigenvalues due to nuclear data uncertainties was found between 500 and 600 pcm, with the top contributor being the neutron multiplicity of 235 U. A gap in the form of missing uncertainties in graphite thermal scattering data, that might have significant impact on HTGR reactors, was identified. This gap is being investigated by the DOE-NE Nuclear Data and Benchmarking Program, as documented in a separate report The fast spectrum molten salt reactor calculations revealed similar comparisons as for the SFR assemblies. The eigenvalue uncertainties were significantly influenced by inelastic scattering on 238 U, while the impact of angular scattering distributions is unknown. For the graphite and zirconium hydride moderated system, eigenvalue uncertainties of up to 700 pcm were observed, requiring in depth analyses of the cross sections and corresponding uncertainties of the included materials. In general, it was observed that the flux spectra of the various molten salt reactor systems show significant differences, even between a fresh state and a depleted state. The choice of the energy group structure of MG calculations is therefore highly relevant; the applicability of previously used MG libraries needs to be verified. Due the unavailability of pin power measurements of advanced reactor systems, pin power calculations with both ENDF/B-VII.1 and VIII.0 data were performed for a light water reactor and compared to corresponding measurements. Both calculations show good agreement with the measurements. A comparison between the ENDF/B-VII.1 and VIII.0 results revealed small differences, mostly in the range of about 0.2%.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Linac_Gen: Integrating Machine Learning and Particle-in-Cell Methods for Enhanced Beam Dynamics at Fermilab

Here, we introduce Linac_Gen, a tool developed at Fermilab, which combines machine learning algorithms with Particle-in-Cell methods to advance beam dynamics in linacs. Linac_Gen employs techniques such as Random Forest, Genetic Algorithms, Support Vector Machines, and Neural Networks, achieving a tenfold increase in speed for phase-space matching in Linacs over traditional methods, through the use of genetic algorithms. Crucially, Linac_Gen's adept handling of 3D field maps elevates the precision and realism in simulating beam instabilities and resonances, marking a key advancement in the field. Benchmarked against established codes, Linac_Gen demonstrates not only improved efficiency and precision in beam dynamics studies but also in the design and optimization of Linac systems, as evidenced in its application to Fermilab's PIP-II Linac project. This work represents a notable advancement in accelerator physics, marrying ML with PIC methods to set new standards for efficiency and accuracy in accelerator design and research. Linac_Gen exemplifies a novel approach in accelerator technology, offering substantial improvements in both theoretical and practical aspects of beam dynamics.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Linac_Gen: integrating machine learning and particle-in-cell methods for enhanced beam dynamics at Fermilab

Here, we introduce Linac_Gen, a tool developed at Fermilab, which combines machine learning algorithms with Particle-in-Cell methods to advance beam dynamics in linacs. Linac_Gen employs techniques such as Random Forest, Genetic Algorithms, Support Vector Machines, and Neural Networks, achieving a tenfold increase in speed for phase-space matching in linacs over traditional methods through the use of genetic algorithms. Crucially, Linac_Gen's adept handling of 3D field maps elevates the precision and realism in simulating beam instabilities and resonances, marking a key advancement in the field. Benchmarked against established codes, Linac_Gen demonstrates not only improved efficiency and precision in beam dynamics studies but also in the design and optimization of linac systems, as evidenced in its application to Fermilab's PIP-II linac project. This work represents a notable advancement in accelerator physics, marrying ML with PIC methods to set new standards for efficiency and accuracy in accelerator design and research. Linac_Gen exemplifies a novel approach in accelerator technology, offering substantial improvements in both theoretical and practical aspects of beam dynamics.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Degradation in Photovoltaic Encapsulant Transmittance: Results of the Second PVQAT TG5 Artificial Weathering Study

The optical degradation of encapsulants from ultraviolet (UV) radiation has historically resulted in a significant loss in performance throughout the life of a photovoltaic (PV) module. International Electrotechnical Commission (IEC) test methods have recently been developed to screen for PV encapsulants prone to loss in optical performance. The present study was performed to benchmark polymeric packaging materials relative to IEC 62788-1-4 (covering the measurement of optical transmittance) and IEC 62788-1-7 (on the durability of transmittance), provide feedback toward improvement of the methods, and develop insight regarding optical degradation. Contemporary materials were examined, including poly(ethylene-co-vinyl acetate) (EVA), thermoplastic polyolefin (TPO), polyolefin elastomer (POE), and polyvinyl butyral (PVB) encapsulants; a poly(ethene-co-tetrafluoroethene)/poly(ethylene terephthalate) (ETFE/PET) transparent backsheet; and a polystyrene (PS) working reference material. The use of silica-, specialty-, and rolled-glass was also compared in laminated coupons. Specimen size was separately examined from 2.5 to 12.5 cm. Weathering was performed with a xenon source, using IEC TS 62788-7-2 methods A2, A3, A4, and A5 (chamber temperature of 55 degrees C, 65 degrees C, 75 degrees C, or 85 degrees C), respectively. Characterizations were made using a UV-visible-near-infrared (UV-VIS-NIR) spectrophotometer (transmittance and reflectance, with and without an integrating sphere), a UV-VIS fluorescence spectrophotometer, a camera, and an optical microscope. Performance was analyzed, including solar weighted transmittance, yellowness index, UV cut-off wavelength, and haze (scattering). Separate Arrhenius analyses were performed to assess retention of transmittance and changes in yellowness index. The activation energy for both characteristics was found to range from 15-80 kJ mol-1, with an average of 48 kJ mol-1, similar to the average of 45 kJ mol-1 identified in the previous international PV Quality Assurance Task Force (PVQAT) Task Group 5 (TG5) study of more traditional encapsulants. The separate degradation modes of discoloration and scattering were distinguished in the encapsulants using a comprehensive spectral characterization. Based on these results, the IEC 62788-1-7 pass/fail criteria of 5% change in transmittance was confirmed to identify a known bad encapsulant.

durability↗
DOE OSTI2018

Search for top-squark pair production in final states with one lepton, jets, and missing transverse momentum using 36 fb -1 of $\sqrt{s}=13 $ TeV pp collision data with the ATLAS detector

The results of a search for the direct pair production of top squarks, the supersymmetric partner of the top quark, in final states with one isolated electron or muon, several energetic jets, and missing transverse momentum are reported. The analysis also targets spin-0 mediator models, where the mediator decays into a pair of dark-matter particles and is produced in association with a pair of top quarks. The search uses data from proton-proton collisions delivered by the Large Hadron Collider in 2015 and 2016 at a centre-of-mass energy of s√=13 TeV and recorded by the ATLAS detector, corresponding to an integrated luminosity of 36 fb -1 . A wide range of signal scenarios with different mass-splittings between the top squark, the lightest neutralino and possible intermediate supersymmetric particles are considered, including cases where the W bosons or the top quarks produced in the decay chain are off-shell. No significant excess over the Standard Model prediction is observed. The null results are used to set exclusion limits at 95% confidence level in several supersymmetry benchmark models. For pair-produced top-squarks decaying into top quarks, top-squark masses up to 940 GeV are excluded. In conclusion, stringent exclusion limits are also derived for all other considered top-squark decay scenarios. For the spin-0 mediator models, upper limits are set on the visible cross-section.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗