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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 OSTI2024

Hydrokinetic tidal energy resource assessment following international electrotechnical commission guidelines

Marine renewable energy can be used as a viable energy source to alleviate the impact of the climate crisis and have a carbon-free electricity sector in the future. Especially the energetic tidal streams are an attractive source of clean energy due to the periodic occurrence of high tidal flows daily. However, before any deployment of tidal turbine farms, it is essential to perform a resource assessment depending on the scope and scale of the project. Here, the International Electrotechnical Commission has developed a technical standard for assessing the tidal stream resource "IEC 62600-201 TS" to aid in this effort: determine a particular site's feasibility and perform the project layout design. In this study, we implemented and validated a high-resolution three-dimensional numerical model and provided results following the IEC TS for a project layout design in a highly energetic tidal channel, Tacoma Narrows of Puget Sound, in the State of Washington, USA. Implementation of the guidelines has helped adequately identify the undisturbed theoretical and technical resources with less bias, where the latter included energy extraction from the flow field arranging a hypothetical tidal energy converter (TEC) array. Also, following the standard, we carefully assessed the changes to channel flow properties from TECs, such as the kinetic energy flux and annual energy production (AEP), to provide the detailed information required for a larger project layout design. Ultimately, this work has shown the important role of IEC TS in tidal stream resource assessment, which can simultaneously act as a benchmark for other studies worldwide.

13 HYDRO ENERGY↗
DOE OSTI2023

Identifying human failure events (HFEs) for external hazard probabilistic risk assessment

In recent years, several advancements in nuclear power plant (NPP) probabilistic risk assessment (PRA) have been driven by increased understanding of external hazards, plant response, and uncertainties. However, major sources of uncertainty associated with external hazard PRA remain. One important source is how risk-significant human actions that are carried out to enable plant response and recovery from natural hazards cause the close coupling of physical impacts on plants and overall plant risk during these hazard events. This makes human reliability and human-plant interactions important elements to consider in resolving PRA gaps in external hazards. One of the challenges in considering human response in external hazard probabilistic risk assessment (XHPRA) is that most existing human reliability analysis (HRA) models were not developed for assessing actions outside the control room (termed ex-control room actions) and hazard response. To support this new scope, HRA models will need to be developed or modified to support identification of human activities, causal factors, and uncertainties inherent in external hazard response, thereby providing insights regarding event timing and physical event conditions as they relate to human performance. In this study, there are two main objectives: (1) evaluate the applicability of an existing cognitive-based HRA method, Phoenix, to ex-control room actions, and (2) identify sources of uncertainty to be characterized or reduced in order to make this method suitable for XHPRA. The first step of such work is performed by assessing the suitability of existing HRA methods to support identifying human failure events (HFEs) for human response to flooding hazards. These HFEs are human actions or inactions that are involved in human responses to flooding hazards and could contribute to the loss of a critical function for the plant in the scenario being examined. Here, in this work, decomposition analyses using the cognitive-based Phoenix HRA model are used to identify HFEs. The Phoenix method was found to be suitable for analyzing ex-control room actions as well as identifying specific HFEs and underlying crew failure modes (CFMs). However, the method's suitability for use in ex-control room actions would benefit from expanding the available CFMs to accommodate a larger variety of physical and communication tasks.

42 ENGINEERING↗
DOE OSTI2022

Thermodynamic assessment of nonstoichiometric oxides for solar thermochemical fuel production

Two-step solar thermochemical cycling (STC) based on nonstoichiometric oxides is an ideal means of solar fuel (e.g., H 2 , CO) production. Screening of nonstoichiometric oxides with excellent thermodynamic performance is key to achieving high solar-to-fuel efficiency. However, application-driven materials assessment intended for reactor-level solar fuel production performance requires mimicking realistic operating conditions of on-sun tests in a laboratory setting, which makes oxides assessment and screening an onerous task to accomplish experimentally. In this work, a rapid assessment and screening model of nonstoichiometric oxides for two-step solar thermochemical cycling assuming fixed-bed flow pattern and quasi-equilibration of the solid with the flowing gas phase is developed, with solar-to-fuel efficiency being the target function of optimization. The model accounts for the thermodynamic parameters of oxide materials and typical operating conditions of experimental thermochemical cycling. This study employed the model to explore and compare two groups of typical nonstoichiometric oxides (CeO 2 - and (LaSr)MnO 3 -based) for their maximum efficiency under their uniquely optimized cycling conditions. The results show that CeO 2 can reach a maximum efficiency of 12.9% at reduction temperature of 1500 °C, which is superior to other candidate materials, including 20 mol% Zr-doped CeO 2 (10.1%), La 0.6 Sr 0.4 MnO 3 (2.5%) and La 0.8 Sr 0.2 MnO 3 (3.3%). Even when the reduction temperature is lowered to 1350 °C, ceria yields the highest efficiency amongst the candidate STC materials considered. The optimal cycling strategy depends on the inherent thermodynamic properties of the oxides. This approach serves as a framework for assessing the maximum efficiency and optimal conditions of candidate thermochemical materials within a range of constraints rather than comparing materials under arbitrary cycling conditions, which may inherently favor one material over another. For oxidation temperatures below 800–1000 °C, the model could be further improved by considering reaction kinetics.

14 SOLAR ENERGY↗
DOE OSTI2022

Techno-economic and life cycle assessment of aluminum electrorefining from mixed scraps using ionic liquid

Aluminum production from bauxite ore uses significantly high amount of energy and capital expenditure. Recycle and reuse of aluminum can be economical and minimize the environmental impacts. Smelter based recycle and reuse of aluminum is used in recent days, however, it also uses high amount of energy with high cost of production and yields high life cycle impacts. The University of Alabama has developed aluminum electrorefining technology from mixed scraps using ionic liquids as an alternative to traditional smelter based recycle and reuse. This study has explored the techno-economical, and life cycle viability of that technology. An excel-based techno-economic and life cycle assessment model was developed at Idaho National Laboratory for techno-economic and life cycle assessment. SimaPro was used to get the necessary database for the life cycle assessment. This study determined that a 20,000 kg/day ionic liquid-based electrorefining system can be profitable with a net yearly profit of $2.00 million. Further, in terms of net global warming potential, it emits 0.92 kg CO 2 equivalent per kg of aluminum recycled, whereas the traditional smelter-based recycle technology emits 1.57 kg CO 2 equivalent per kg of aluminum recycled, and the aluminum production from bauxite ore emits 17.8 kg CO 2 equivalent per kg of aluminum produced. In other life cycle assessment categories, electrorefining of aluminum emits >88 % less than aluminum production from bauxite ore and it is also better than traditional aluminum recycling in six out of ten categories studied. This makes ionic liquid-based electrorefining technology a very promising technology in terms of process economics and environmental sustainability.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The Climatic Impact‐Driver Framework for Assessment of Risk‐Relevant Climate Information

Abstract The climate science and applications communities need a broad and demand‐driven concept to assess physical climate conditions that are relevant for impacts on human and natural systems. Here, we augment the description of the “climatic impact‐driver” (CID) approach adopted in the Working Group I (WGI) contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report. CIDs are broadly defined as “physical climate system conditions (e.g., means, events, and extremes) that affect an element of society or ecosystems. Depending on system tolerance, CIDs and their changes can be detrimental, beneficial, neutral, or a mixture of each across interacting system elements and regions.” We give background information on the IPCC Report process that led to the development of the 7 CID types (heat and cold, wet and dry, wind, snow and ice, coastal, open ocean, and other) and 33 distinct CID categories, each of which may be evaluated using a variety of CID indices. This inventory of CIDs was co‐developed with WGII to provide a useful collaboration point between physical climate scientists and impacts/risk experts to assess the specific climatic phenomena driving sectoral responses and identify relevant CID indices within each sector. The CID Framework ensures that a comprehensive set of climatic conditions informs adaptation planning and risk management and may also help prioritize improvements in modeling sectoral dynamics that depend on climatic conditions. CIDs contribute to climate services by increasing coherence and neutrality when identifying and communicating relevant findings from physical climate research to risk assessment and planning activities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Critical adjustment of land mitigation pathways for assessing countries' climate progress

Collective progress towards the Paris Agreement’s temperature targets will be assessed by the Agreement’s Global Stocktake process. Global emission pathways by Integrated Assessment Models (IAMs) are a likely benchmark against which aggregated countries’ greenhouse gas mitigation pledges will be assessed. However, this approach requires comparability, which is currently hampered by a 5 GtCO2yr-1 mismatch between the estimated global land anthropogenic flux of IAMs and countries’ GHG inventories (GHGIs) for 2005-2015. We show that this gap is mostly the result of differences in how the anthropogenic forest sink is defined. Countries define managed forest more broadly than IAMs, and on this larger area typically consider anthropogenic also fluxes due to human-induced environmental change, which IAMs do not include their pathways. Using five IAMs and a dynamic global vegetation model (DGVM), we present and apply a novel method that adjusts IAM results to the countries’ definition, closing the gap with GHGIs at global and regional scale. When expressed in a way compatible with GHGIs, adjusted 1.5°C and well-below 2°C pathways have a cumulative CO2 balance until carbon neutrality that is 110–176 GtCO2 lower than the original IAMs pathways. The use of these country-compatible emission pathways under the Global Stocktake would therefore be essential for an accurate assessment of the collective progress towards the Paris Agreement’s climate goals.

Grassi, Giacomo↗
DOE OSTI2024

FEW questions, many answers: using machine learning to assess how students connect food–energy–water (FEW) concepts

There is growing support and interest in postsecondary interdisciplinary environmental education which integrate concepts and disciplines in addition to providing varied perspectives. There is a need to assess student learning in these programs as well as rigorous evaluation of educational practices, especially of complex synthesis concepts. This work tests a text classification machine learning model as a tool to assess student systems thinking capabilities using two questions anchored by the Food-Energy-Water (FEW) Nexus phenomena by answering two questions (1) Can machine learning models be used to identify instructor-determined important concepts in student responses? (2) What do college students know about the interconnections between food, energy and water, and how have students assimilated systems thinking into their constructed responses about FEW? Reported here are a broad range of model performances across 26 text classification models associated with two different assessment items, with model accuracy ranging from 0.755 to 0.992. Expert-like responses were infrequent in our dataset compared to responses providing simpler, incomplete explanations of the systems presented in the question. For those students moving from describing individual effects to multiple effects, their reasoning about the mechanism behind the system indicates advanced systems thinking ability. Specifically, students exhibit higher expertise for explaining changing water usage than discussing tradeoffs for such changing usage. This research represents one of the first attempts to assess the links between foundational, discipline-specific concepts and systems thinking ability. These text classification approaches to scoring student FEW Nexus Constructed Responses (CR) indicate how these approaches can be used, in addition to several future research priorities for interdisciplinary, practice-based education research. Development of further complex question items using machine learning would allow evaluation of the relationship between foundational concept understanding and integration of those concepts as well as more nuanced understanding of student comprehension of complex interdisciplinary concepts.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

Advancing a toolkit of diverse futures approaches for global environmental assessments

Global Environmental Assessments (GEAs) support national and international policy making for sustainable development. They rely on quantitative scenarios produced by Integrated Assessment Models (IAMs) to assess alternative futures. IAM-based scenarios can provide a coherent assessment framework that integrates different subsystems and their interactions. However, these top-down approaches have limited ability to represent key local dynamics, unexpected events, or the role of diverse actors. Other methods, including participatory scenarios, can help co-create narratives that emphasize diverse contents with clear links to existing decision-making. However, these bottom-up approaches provide only limited insight into global processes and are not constrained by measurable parameters. In our review, we identify four key challenges for current GEA scenarios: surprise, scale, diversity and imagination. We illustrate how these challenges can be overcome by combining top-down and bottom-up scenario approaches and conclude with a call to action for future research to take on this trans-disciplinary challenge.

Pereira, Laura M.↗
DOE OSTI2024

Plan evaluation for heat resilience: complementary methods to comprehensively assess heat planning in Tempe and Tucson, Arizona

Abstract Escalating impacts from climate change and urban heat are increasing the urgency for communities to equitably plan for heat resilience. Cities in the desert Southwest are among the hottest and fastest warming in the U.S., placing them on the front lines of heat planning. Urban heat resilience requires an integrated planning approach that coordinates strategies across the network of plans that shape the built environment and risk patterns. To date, few studies have assessed cities’ progress on heat planning. This research is the first to combine two emerging plan evaluation approaches to examine how networks of plans shape urban heat resilience through case studies of Tempe and Tucson, Arizona. The first methodology, Plan Quality Evaluation for Heat Resilience, adapts existing plan quality assessment approaches to heat. We assess whether plans meet 56 criteria across seven principles of high-quality planning and the types of heat strategies included in the plans. The second methodology, the Plan Integration for Resilience Scorecard™ (PIRS™) for Heat, focuses on plan policies that could influence urban heat hazards. We categorize policies by policy tool and heat mitigation strategy and score them based on their heat impact. Scored policies are then mapped to evaluate their spatial distribution and the net effect of the plan network. The resulting PIRS™ for Heat scorecard is compared with heat vulnerability indicators to assess policy alignment with risks. We find that both cities are proactively planning for heat resilience using similar plan and strategy types, however, there are clear and consistent opportunities for improvement. Combining these complementary plan evaluation methods provides a more comprehensive understanding of how plans address heat and a generalizable approach that communities everywhere could use to identify opportunities for improved heat resilience planning.

Environmental Sciences & Ecology↗
DOE OSTI2022

Island of misfit tortoises: waif gopher tortoise health assessment following translocation

Translocation, the intentional movement of animals from one location to another, is a common management practice for the gopher tortoise (Gopherus polyphemus). Although the inadvertent spread of pathogens is a concern with any translocation effort, waif tortoises—individuals that have been collected illegally, injured and rehabilitated or have unknown origins—are generally excluded from translocation efforts due to heightened concerns of introducing pathogens and subsequent disease to naïve populations. However, repurposing these long-lived animals for species recovery is desirable when feasible, and introducing waif tortoises may bolster small populations facing extirpation. The objective of this study was to assess the health of waif tortoises experimentally released at an isolated preserve in Aiken County, SC, USA. Our assessments included visual examination, screening for 14 pathogens using conventional or quantitative polymerase chain reaction (qPCR) and haematological evaluation. Of the 143 individuals assessed in 2017 and 2018, most individuals (76%; n = 109 of 143) had no overt clinical evidence of disease and, when observed, clinical findings were mild. In both years, we detected two known tortoise pathogens, Mycoplasma agassizii and Mycoplasma testudineum, at a prevalence of 10.2–13.9% and 0.0–0.8%, respectively. Additionally, we found emydid Mycoplasma, a bacterium commonly found in box turtles (Terrapene spp.), in a single tortoise that showed no clinical evidence of infection. The presence of nasal discharge was an important, but imperfect, predictor of Mycoplasma spp. infection in translocated tortoises. Hemogram data were comparable with wild populations. Our study is the first comprehensive effort to assess pathogen prevalence and hemogram data of waif gopher tortoises following translocation. Although caution is warranted and pathogen screening necessary, waif tortoises may be an important resource for establishing or augmenting isolated populations when potential health risks can be managed.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

On alert for Ebola: public health risk assessment of travellers from Uganda to the USA during the 2022 outbreak

Abstract Background On 20 September 2022, the Ugandan Ministry of Health declared an outbreak of Ebola disease caused by Sudan ebolavirus. Methods From 6 October 2022 to 10 January 2023, Centers for Disease Control and Prevention (CDC) staff conducted public health assessments at five US ports of entry for travellers identified as having been in Uganda in the past 21 days. CDC also recommended that state, local and territorial health departments (‘health departments’) conduct post-arrival monitoring of these travellers. CDC provided traveller contact information, daily to 58 health departments, and collected health department data regarding monitoring outcomes. Results Among 11 583 travellers screened, 132 (1%) required additional assessment due to potential exposures or symptoms of concern. Fifty-three (91%) health departments reported receiving traveller data from CDC for 10 114 (87%) travellers, of whom 8499 (84%) were contacted for monitoring, 1547 (15%) could not be contacted and 68 (1%) had no reported outcomes. No travellers with high-risk exposures or Ebola disease were identified. Conclusion Entry risk assessment and post-arrival monitoring of travellers are resource-intensive activities that had low demonstrated yield during this and previous outbreaks. The efficiency of future responses could be improved by incorporating an assessment of risk of importation of disease, accounting for individual travellers’ potential for exposure, and expanded use of methods that reduce burden to federal agencies, health departments, and travellers.

General & Internal Medicine↗
DOE OSTI2024

Scenario development for safety assessment in deep geologic disposal of high-level radioactive waste and spent nuclear fuel: A review

Radiation and radioactive substances result in the production of radioactive wastes which require safe management and disposal to avoid risks to human health and the environment. To ensure permanent safe disposal, the performance of a deep geological repository for radioactive waste is assessed against internationally agreed risk-based standards. Assessing postclosure safety of the future system's evolution includes screening of features, events, and processes (FEPs) relevant to the situation, their subsequent development into scenarios, and finally the development and execution of safety assessment (SA) models. Global FEP catalogs describe important natural and man-made repository system features and identify events and processes that may affect these features into the future. By combining FEPs, many of which are uncertain, different possible future system evolution scenarios are derived. Repository licensing should consider both the reference or “base” evolution as well as alternative futures that may lead to radiation release, pollution, or exposures. Scenarios are used to derive and consider both base and alternative evolutions, often through production of scenario-specific SA models and the recombination of their results into an assessment of the risk of harm. Furthermore, while the FEP-based scenario development process outlined here has evolved somewhat since its development in the 1980s, the fundamental ideas remain unchanged. A spectrum of common approaches is given here (e.g., bottom–up vs. top–down scenario development, probabilistic vs. bounding handling of uncertainty), related to how individual numerical models for possible futures are converted into a determination as to whether the system is safe (i.e., how aleatoric uncertainty and scenarios are integrated through bounding or Monte Carlo approaches).

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

Few-shot Learning for Post-disaster Structure Damage Assessment

Automating post-disaster damage assessment with remote sensing data is critical for faster surveys of structures impacted by natural disasters. One significant obstacle to training state-of-the-art deep neural networks to support this automation is that large quantities of labelled data are often required. However, obtaining those labels is particularly unrealistic to support post-disaster damage assessment in a timely manner. Few-shot learning methods could help to mitigate this by reducing the amount of labelled data required to successfully train a model while achieving satisfactory results. To this end, we explore a feature reweighting method to the YOLOv3 object detection architecture to achieve few-shot learning of damage assessment models on the xBD dataset. Our results show that the feature reweighting approach yield improved mAP over the baseline with significantly fewer labelled samples. In addition, we use t-SNE to analyze the class-specific reweighting vectors generated by the reweighting module in order to evaluate their inter-class and intra-class similarity. We find that the vectors form clusters based on class, and that these clusters overlap with visually similar classes. Those results show the potential to employ this few-shot learning strategy for rapid damage assessment with post-event remote sensing images.

Bowman, Jordan↗
DOE OSTI2023

Visualization Quality Assessment

Understanding how inaccuracies in visualizations affect users’ perception and understanding of scientific data is hard. Inaccuracies in visualizations are quite common and could arise from a range of sources such as errors in the original dataset arising from compression artifacts, errors in the capturing device, noise during transmission of the data, effects due to the algorithm being used to convert data to visualization images, images generated from neural networks, and sources we have yet to discover. Many image quality assessment metrics have been developed to quantify image errors. However, these are usually focused on “natural images” rather than visualizations of scientific data. Common image quality assessment metrics (IQAs) include MSE, PSNR, perceptual metrics such SSIM, FSIM as well as perceptual metrics using deep learning approaches. However, a critical part of understanding how errors are perceived by humans, and subsequently developing more accurate quality assessment metrics, is through user evaluation studies. The goal of this software is to develop a visualization quality assessment (VQA) process that will enable the generation of VQAs that can be used to quantify errors in scientific data visualizations. The VQA development process will include software to support user evaluation experimental design, analysis of visualization differences against standard quality metrics, and the ability to develop additional VQA metrics specific to scientific visualization images.

Grosset, Andre↗
DOE OSTI2024

LiAISON (Life-cycle Assessment Integration into Scalable Open-source Numerical models) [SWR-24-01]

We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE)7. We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming. Scientific publication available here: https://pubs.acs.org/doi/full/10.1021/acs.est.2c04246

Ghosh, Tapajyoti↗
DOE OSTI2022

The Worldwide C3S CORDEX Grand Ensemble: A Major Contribution to Assess Regional Climate Change in the IPCC AR6 Atlas

The collaboration between the Coordinated Regional Climate Downscaling Experiment (CORDEX) and the Earth System Grid Federation (ESGF) provides open access to an unprecedented ensemble of regional climate model (RCM) simulations, across the 14 CORDEX continental-scale domains, with global coverage. These simulations have been used as a new line of evidence to assess regional climate projections in the latest contribution of the Working Group I (WGI) to the IPCC Sixth Assessment Report (AR6), particularly in the regional chapters and the Atlas. Here, we present the work done in the framework of the Copernicus Climate Change Service (C3S) to assemble a consistent worldwide CORDEX grand ensemble, aligned with the deadlines and activities of IPCC AR6. This work addressed the uneven and heterogeneous availability of CORDEX ESGF data by supporting publication in CORDEX domains with few archived simulations and performing quality control. It also addressed the lack of comprehensive documentation by compiling information from all contributing regional models, allowing for an informed use of data. In addition to presenting the worldwide CORDEX dataset, we assess here its consistency for precipitation and temperature by comparing climate change signals in regions with overlapping CORDEX domains, obtaining overall coincident regional climate change signals. The C3S CORDEX dataset has been used for the assessment of regional climate change in the IPCC AR6 (and for the interactive Atlas) and is available through the Copernicus Climate Data Store (CDS).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Quantitative Performance Assessment of Proxy Apps and Parents (ECP Proxy App Project Milestone ADCD-504-9)

This report presents highlights of these efforts. Section 2 describes work that has been done to compare the performance of proxy applications on AMD MI60 vs. Nvidia V100 GPUs. So far only a small set of ECP proxies are running on AMD GPUs, but we will continue to expand this analysis as additional proxies become available. We find that although the MI60 and V100 have nearly the same measured memory bandwidth, memory bound proxy app kernels perform 20-30% worse on the MI60. Further work is needed to refine these comparisons to determine whether the root cause is due to differences in the hardware, software stack, platform specific optimization, or some combination of the three. Section 3 describes our continuing effort to find methods to accurately assess the similarity of proxies and parents. We have recently seen very encouraging results using a cosine similarity metric. This technique uses the angle between two vectors of hardware performance counters to characterize the similarity (or difference) between two applications or proxies. We show not only that several widely used proxies are highly similar to their parents, but also that they differ from non-related codes. We also show that cosine similarity can be used to identify gaps and redundancies in suites and even to gain insight into the effects of architectural differences between platforms. Our work on assessing the Exascale toolchain is ongoing. Our successes with performance measurement tools are evident from the data provided in this report. However, our assessments across the broader tool chain are still too incomplete to provide a meaningful report at this time. We will continue to assess tools and work with vendors and third party developers as issues are identified.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Assessment of Methane Generation from the Thermolysis of Organics in Caustic Waste

Methane generation has been detected during thermolytic Hydrogen Generation Rate (HGR) testing of SRS tank waste and in simulant samples. Simulant testing has shown methane generation in the presence of trimethylsilanol (TMS) and radioactive sample testing has shown methane generation in presence of methylmercury, both of which are found within SRS waste tanks. The 2019 report Evaluation of the Current State of Knowledge for Thermolysis of Organics within SRS Waste Forming Volatile Organic Compounds (VOCs) reviewed historical data and assessed literature pertaining to thermolytic methane generation. That review recommended undertaking thermolysis studies on simulated waste to detect and quantify VOCs. The purpose of this assessment is to review chemistry and current knowledge of organics in SRS waste to recommend which organics in SRS waste tanks, if any, should be tested for thermolytic methane generation. An evaluation of observed methane generation rates has been performed to assess the implication for current CSTF controls. Based on the inputs used in this report, it was concluded that no methane generation data observed to date has challenged the existing 5% organic contribution to the Composite Lower Flammability Limit (CLFL) assumption in the CSTF tank farm at temperatures below 100 °C. Evidence shows that thermolytic pathways to methane generation become significant at temperatures >100 °C in caustic waste. Currently, the influences of thermolytic methane production on the flammability of vessels at >100 °C (e.g., evaporators) is unclear. It is recommended that testing should be undertaken using the HGR experimental approach for methane generation. The initial simulant testing should obtain quantitative methane generation rates at elevated temperatures for methylated siloxanes/silanes and methylmercury with the goal of determining the current mechanism for thermolytic methane generation seen in SRS tank waste. The results of this testing should then be compiled and analyzed to ascertain the risk of challenging the current projected organic contribution of 5% to the CLFL at elevated temperatures. Following this testing, an evaluation of possible flammable gas generation in the 2H and 3H Evaporators should be performed to assess the risk of methane generation at the high temperatures employed by the evaporators.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗