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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Enhancement of HLW glass property-composition models

Since the WTP compositional space of HLW glasses is extremely large, development of HLW property-composition models is a multi-year task consisting of multiple phases. The primary focus of this work was to enhance the WTP HLW models of interest including PCT releases, spinel crystallization (T1%), viscosity, electrical conductivity, and TCLP-Cd response. Model development to predict nepheline formation upon CCC is the subject of a separate task. In particular, the earlier work has produced property-composition models for glass melt viscosity and glass melt electrical conductivity that showed good performance, while models for PCT releases and spinel crystallization (T1%) required improvement. Therefore, more efforts were directed in the present work to collect data and improve model performance for HLW glass PCT releases and spinel crystallization than for other properties. The present work is a continuation of earlier development phases and is responsive to the applicable Test Plan.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

A more natural composite Higgs model

Composite Higgs models provide an attractive solution to the hierarchy problem. However, many realistic models suffer from tuning problems in the Higgs potential. There are often large contributions from the UV dynamics of the composite resonances to the Higgs potential, and tuning between the quadratic term and the quartic term is required to separate the electroweak breaking scale and the compositeness scale. We consider a composite Higgs model based on the SU(6)/Sp(6) coset, where an enhanced symmetry on the fermion resonances can minimize the Higgs quadratic term. Moreover, a Higgs quartic term from the collective symmetry breaking of the little Higgs mechanism can be realized by the partial compositeness couplings between elementary Standard Model fermions and the composite operators, without introducing new elementary fields beyond the Standard Model and the composite sector. The model contains two Higgs doublets, as well as several additional pseudo-Nambu-Goldstone bosons. To avoid tuning, the extra Higgs bosons are expected to be relatively light and may be probed in the future LHC runs. The deviations of the Higgs couplings and the weak gauge boson couplings also provide important tests as they are expected to be close to the current limits in this model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Glass Property-Composition Models for Support of Hanford WTP LAW Facility Operation

Current plans for the River Protection Project envision starting to vitrifying low-activity waste (LAW) by 2023 using a Direct Feed Low-Activity Waste (DFLAW) approach and subsequently using a full-pretreatment approach. The Hanford Tank Waste Treatment and Immobilization Plant (WTP) LAW Facility will be operated and controlled using a LAW glass formulation algorithm (GFA), which requires several inputs based on research and development results. LAW glass property-composition models for several product quality and processing properties are key inputs for the LAW GFA. It is envisioned that the preliminary LAW GFA discussed by Kim and Vienna (2012) will be used for commissioning and initial radioactive operations of the WTP LAW Facility under Bechtel National, Inc. using the DFLAW approach. Then, an updated LAW GFA will be developed for implementation by the WTP operating contractor that takes over after WTP LAW Facility commissioning. This report documents the enhanced LAW glass property-composition models developed for use in the updated LAW GFA. The properties for which models were developed include Product Consistency Test (PCT) response, Vapor Hydration Test (VHT) response, viscosity at 1150 °C, electrical conductivity at 1150 °C, melter SO 3 tolerance at 1150 °C, and K-3 refractory corrosion at 1208 °C. Table S.1 lists the tables in this report that contain the recommended models for each of these properties. The model types recommended include partial quadratic mixture (PQM) models for viscosity, electrical conductivity, melter SO 3 tolerance and K-3 corrosion, bias corrected PQM model (bcPQM) for PCT, and logistic PQM model for VHT. The fits of model and validation subsets were found to be well predicted by the recommended models.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Glass Property-Composition Models for Support of Hanford WTP LAW Facility Operation

Current plans for the River Protection Project envision starting to vitrifying low-activity waste (LAW) by 2023 using a Direct Feed Low-Activity Waste (DFLAW) approach and subsequently using a full-pretreatment approach. The Hanford Tank Waste Treatment and Immobilization Plant (WTP) LAW Facility will be operated and controlled using a LAW glass formulation algorithm (GFA), which requires several inputs based on research and development results. LAW glass property-composition models for several product quality and processing properties are key inputs for the LAW GFA. It is envisioned that the preliminary LAW GFA discussed by Kim and Vienna (2012) will be used for commissioning and initial radioactive operations of the WTP LAW Facility under Bechtel National, Inc. using the DFLAW approach. Then, an updated LAW GFA will be developed for implementation by the WTP operating contractor that takes over after WTP LAW Facility commissioning. This report documents the enhanced LAW glass property-composition models developed for use in the updated LAW GFA. The properties for which models were developed include Product Consistency Test (PCT) response, Vapor Hydration Test (VHT) response, viscosity at 1150 °C, electrical conductivity at 1150 °C, melter SO3 tolerance at 1150 °C, and K-3 refractory corrosion at 1208 °C. Table S.1 lists the tables in this report that contain the recommended models for each of these properties. The model types recommended include partial quadratic mixture (PQM) models for viscosity, electrical conductivity, melter SO 3 tolerance and K-3 corrosion, bias corrected PQM model (bcPQM) for PCT, and logistic PQM model for VHT. The fits of model and validation subsets were found to be well predicted by the recommended models.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Development of Property Composition Models For RPP-WTP LAW Glasses (Final Report)

This report describes the development of property-composition models for low-activity waste (LAW) glasses for the River Protection Project Waste Treatment Plant (RPP-WTP) at the Hanford site. The RPP-WTP will separate Hanford tank wastes into LAW and high-level waste (HLW) streams and each stream will be vitrified separately. The development of LAW and HLW glass formulations for the RPP-WTP has been reported previously and is an ongoing activity. Acceptable formulations must meet a variety of processability, product quality, and waste loading requirements that are dictated either by the RPP-WTP contract or by the characteristics of the particular treatment processes that have been selected. These requirements amount to constraints on the acceptable ranges of certain glass properties. These properties are determined first and foremost by the composition of the glass or glass melt. Thus, while there is no direct way of controlling the glass properties of interest during production, there are simple and extremely effective methods of achieving the same result by instead controlling the glass composition. This basic principle is no different from that used to produce enormous volumes of commercial glass to meet exacting product specifications. An essential difference in waste vitrification, however, is that one of the raw materials (the waste itself) can be subject to considerable compositional uncertainty and variability. Thus, waste vitrification facilities and associated process control systems (of which, the operating envelope in glass formulation space is a key part) must, of course, be designed to be robust with respect to such variations. The determination of quantitative relationships between the glass properties that must be controlled and the glass composition can play an important role in the development of such facilities.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Enhanced HLW glass property-composition models - phase 3

During the present phase (Phase 3) of work to enhance and expand the HLW glass property-composition models, test data for 137 glasses were collected and incorporated into the combined WTP/ORP database. The new data include those collected on glasses from two statistically designed matrices to augment the moderate alumina region (the HLW16-MA matrix covering the region of 9 wt% < Al2O3 < 12 wt% with 16 glasses) and the ultra-high alumina region (the HLW16-UHA matrix covering the region of 26 wt% < Al2O3 < 29 wt% with 29 glasses). The addition of ORP glasses over the different phases of testing has significantly expanded the combined WTP/ORP database. The compiled data include glass compositions, PCT (B, Li and Na) releases, spinel T1%, electrical conductivity, viscosity, TCLP-Cd releases, and nepheline formation upon CCC. With the exception of the CCC spinel formation data – the CCC data will be used to support the further development of nepheline models for Hanford HLW glasses.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Enhanced HLW Glass Property-Composition Models – Phase 2

As a continuation of the Phase 1 HLW model development work as part of a phased approach to enhance and expand HLW glass property-composition models, additional data were collected for the HLW glass dataset and used to revise the models developed during Phase 1. These data are for glasses that are collectively referred to as ORP-2014 glasses. The sources of additional data for the Phase 2 work included: (i) actively designed glasses formulated to support various glass studies at VSL since the completion of Phase 1; and (ii) glasses from two statistically designed matrices to supplement the existing HLW compositional space. The Phase 2 matrix design was intended to augment and improve the coverage in the high aluminum region.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Glass Property-Composition Models Update for use in Direct Feed High-Level Waste Flowsheet Development: EWG3.0

A set of preliminary glass property models and constraints were developed and augmented by models from literature for use in design of Direct Feed High-Level Waste glasses for flowsheet evaluation, testing, and design of the High-Level Waste Facility at the Hanford Waste Treatment and Immobilization Plant. These models and constraints are meant to be used as a placeholder while glass property-composition data gaps are filled and final plant operating models are developed. This report describes the motivation and intended use of the models, the compilation of data, model fitting and selection, and methods to apply the models and constraints in glass design, and offers example calculations demonstrating their intended use.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Glass Property-Composition Models Update for use in Direct Feed High-Level Waste Flowsheet Development

A set of preliminary glass property models and constraints were developed and augmented by models from literature for use in design of direct-feed high-level waste (DFHLW) glasses for flowsheet evaluation, testing, and design of the Tank Waste Treatment and Immobilization Plant (WTP) high-level waste (HLW) Facility. These models and constraints are meant to be used as a place-holder while glass property-composition data gaps are filled and final plant operating models are developed. This report describes the motivation and intended use of the models, the compilation of data, model fitting and selection, methods to apply the models and constraints in glass design and offers example calculations demonstrating their intended use.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Glass Property-Composition Models Update for use in Direct Feed High-Level Waste Flowsheet Development: EWG2.6

A set of preliminary glass property models and constraints were developed and augmented by models from literature for use in design of direct-feed high-level waste (DFHLW) glasses for flowsheet evaluation, testing, and design of the Waste Treatment and Immobilization Plant (WTP) high-level waste (HLW) Facility. These models and constraints are meant to be used as a place-holder while glass property-composition data gaps are filled and final plant operating models are developed. This report describes the motivation and intended use of the models, the compilation of data, model fitting and selection, methods to apply the models and constraints in glass design and offers example calculations demonstrating their intended use.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Non-growing Season Plant Nutrient Uptake Controls Arctic Tundra Vegetation Composition: Modeling Archive

This Modeling Archive is in support of a NGEE-Arctic publication: Riley et al. (2021) “Non-growing season plant nutrient uptake controls Arctic tundra vegetation composition under future climate” (Riley et al., 2021). The dataset contains “ecosys” model outputs reported in Riley et al. (2021) that examines the role of non-growing season (NGS) nutrient dynamics on 21st century vegetation composition. The study highlighted the importance of these nutrient dynamics on the emergent plant functional type distributions, focusing on their role in shrub expansion. The study showed that ignoring NGS nutrient dynamics led to a dramatic under-prediction of shrub expansion by year 2100, motivating the need to include these processes in Earth System Models. Included are modeled net primary production (NPP) and nitrogen (N) uptake for two scenarios: (1) baseline and (2) no NGS N uptake. The output is provided (1) at 25 km resolution across the North American tundra; (2) for years 2012 through 2100; and (3) PFT-specific. Dataset contains 20 NetCDF files in a zip file and one pdf.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Validating methods for modeling composition gradients in planar shock experiments

An interface is Rayleigh–Taylor (RT) unstable when acceleration pushes a less dense material into a more dense one, and the growth of the instability is governed partly by the Atwood number gradient. Double-shell inertial confinement fusion capsules have a foam spacer layer pushing on an inner capsule composed of a beryllium tamper and high-Z inner shell, and so have RT unstable interfaces that require benchmarking. To this end, the results of a planar shock experiment with beryllium/tungsten targets are presented. One target had the normal bilayer construction of beryllium and tungsten in two distinct layers; the second target had the beryllium grading into tungsten with a quasi-exponential profile, motivated by the potential for reduced RT growth with the gradient profile. Simulations mimic the shock profiles for both targets and match the shock velocity to within 5%. These results validate the ability of our simulations to model double-shell capsules with bilayer or graded layer Be/W inner shells, which are needed to design future experiments at the National Ignition Facility.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

MetaText: Compositional Generalization in Deep Language Models

Compositional generalization, the ability to infer and reason using novel combinations of previously encountered entities and structures, is a trait of great utility across a variety of deep learning tasks; it implies a certain ability to reason using consistent and therefore interpretable rules, to understand the constituent parts of its input at multiple levels of granularity, to be robust to spurious differences between semantically equivalent inputs, and more. We seek to understand the degree to which existing natural language models achieve or fall short of compositional generalization across a variety of tasks, whether there are distinct types of compositional generalization in practice, and to identify avenues of intervention through which we can improve models’ compositional generalization ability. After exploring these questions using an array of models, tasks, and potential interventions we see that large, pretrained language models have encountered sufficient training data to account for a variety of fine-grained compositional behavior but still struggle to reason at the level of phrases or larger language structures. Non-intrusive, data-based interventions in the form of augmenting individual sequences with compressed versions of themselves or deriving new examples from induced grammars prove insufficient to encourage greater levels of compositional reasoning, indicating that future work might benefit most from focusing on changes to a model’s inductive bias at the architectural or loss level, or by integrating compositionality-boosting data interventions into the large-scale pretraining process itself.

97 MATHEMATICS AND COMPUTING↗