Results for “relevancy ranking” — Page 3

DOE OSTI2023

Examining the potential for detecting simultaneous noble gas and aerosol samples in the international monitoring system radionuclide network

The purpose of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) is to establish a legally binding ban on nuclear weapon test explosions or any other nuclear explosions. The Preparatory Commission for the CTBT Organization (CTBTO PrepCom) is developing the International Monitoring System (IMS) that includes a global network of 80 stations to monitor for airborne radionuclides upon entry into force of the CTBT. All 80 radionuclide stations will monitor for particulate radionuclides and at least half of the stations will monitor for radioxenon. The airborne radionuclide monitoring is an important verification technology both for the detection of a radionuclide release and in the determination of whether the release event originates from a nuclear explosion as opposed to an industrial use of nuclear materials. Nuclear power plants and many medical isotope production facilities release radioxenon into the atmosphere. Low levels of a few particulate isotopes, such as iodine, may also be released. Detections of multiple isotopes are useful for screening the radionuclide samples for relevance to the Treaty. This paper examines the anticipated joint detections in the IMS of noble gas and particulate isotopes from underground nuclear explosions where breaches in the underground containment vents from low levels to up to 1% of the radionuclide inventory of the resulting fission products to the atmosphere. Detection probabilities are based on 844 simulated release events spaced out at 17 release locations and one year in time. Six different release (venting) scenarios, including two fractionated scenarios, were analyzed. When ranked by detection probability, 11 particulate isotopes and one noble gas isotope ( 133 Xe) appear in the top 20 isotopes for all six release scenarios. Using the 11 particulate isotopes and the one noble gas isotope, the IMS has nearly the same detection probability as when 45 particulate and 4 noble gas isotopes are used. Thus, a limited list of relevant radionuclides may be sufficient for treaty verification purposes. The probability that at least one particulate and at least one radioxenon isotope would be detected in the IMS from the release events ranged from 0.15 to 0.86 depending on the release scenario.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2021

Learning Associations between Features and Clusters: An Interpretable Deep Clustering Method

Explore the source record for details and available documents.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Theory of overparametrization in quantum neural networks

The prospect of achieving quantum advantage with quantum neural networks (QNNs) is exciting. Understanding how QNN properties (for example, the number of parameters $M$) affect the loss landscape is crucial to designing scalable QNN architectures. Here we rigorously analyze the overparametrization phenomenon in QNNs, defining overparametrization as the regime where the QNN has more than a critical number of parameters $M_c$ allowing it to explore all relevant directions in state space. In this study, our main results show that the dimension of the Lie algebra obtained from the generators of the QNN is an upper bound for $M_c$, and for the maximal rank that the quantum Fisher information and Hessian matrices can reach. Underparametrized QNNs have spurious local minima in the loss landscape that start disappearing when $M$ ≥ $M_c$. Thus, the overparametrization onset corresponds to a computational phase transition where the QNN trainability is greatly improved. We then connect the notion of overparametrization to the QNN capacity, so that when a QNN is overparametrized, its capacity achieves its maximum possible value.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Updates to Relevance Vector Machine: Multiclass Classification, Variable Selection, and Proof-of-Concept Application to Safeguards Fresh Fuel Verification using List-Mode Neutron Collar Data

To expand the capabilities of safeguards authorities to verify the integrity of fresh fuel assemblies, Oak Ridge National Laboratory has retrofit the existing electronics of the JCC-71 uranium neutron coincidence collar, which contains 18 3 He neutron detectors and an external 241 AmLi(α, n) neutron interrogation source arranged to surround a fresh nuclear fuel assembly. The new electronics system allows analysts to record list-mode neutron multiplicity data in addition to the singles and doubles rates that are currently measured. Based on previous proof-of-concept research, analysis of these new data will identify off-normal fuel configurations in an assembly and characterize or localize the specific partial fuel defects. The purpose of this report it to document the analysis algorithm development and then to demonstrate its capability for the safeguards verification of fresh fuel assemblies using list mode neutron collar data. To analyze the complex list-mode data collected with the upgraded uranium neutron collar, multivariate classification algorithms are being developed using a novel classification method, the relevance vector machine. This approach may be applied to multiclass problems to estimate the probability that test data belongs to one of many possible classes of data. In addition, our method identifies the most useful variables/channels for making predictions, which illuminates the basis for the model’s predictions, and this interpretability is largely unique among data analytics methods. Variable selection occurs during model training and parameter tuning and does not need any external hyperparameter tuning routines. Finally, we apply the modified relevance vector machine to a simulated dataset of list-mode neutron collar data generated with the radiation transport code MCNP. The method can correctly identify off-normal fuel configurations, categorize the data according to four fuel defect scenarios, and rank the channels in the data according to prediction utility. For nuclear safeguards applications, it is concluded that this method has the potential to increase the sensitivity and reliability to detect missing fuel rods from a standard 17 x 17 Pressurized Water Reactor (PWR) fresh fuel assembly. Within this analysis, “off-normal” (i.e., missing fuel rods) were correctly classified in 17 simulated test scenarios with one quarter (25%) of the fresh fuel rods missing using a training data set of 58 simulated measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Constitutive Model Development for Aging Polymer Encapsulants (ASC P&EM FY2021 L2 Milestone 7836)

This SAND report fulfills the completion requirements for the ASC Physics and Engineering Modeling Level 2 Milestone 7836 during Fiscal Year 2021. The Sandia Simplified potential energy clock (SPEC) non-linear viscoelastic constitutive model was developed to predict a whole host of polymer glass physical behaviors in order to provide a tool to assess the effects of stress on these materials over their lifecycle. Polymer glasses are used extensively in applications such as electronics packaging, where encapsulants and adhesives can be critical to device performance. In this work, the focus is on assessing the performance of the model in predicting material evolution associated with long-term physical aging, an area that the model has not been fully vetted in. These predictions are key to utilizing models to help demonstrate electronics packaging component reliability over decades long service lives, a task that is very costly and time consuming to execute experimentally. The initiating hypothesis for the work was that a model calibration process can be defined that enables confidence in physical aging predictions under ND relevant environments and timescales without sacrificing other predictive capabilities. To test the hypothesis, an extensive suite of calibration and aging data was assembled from a combination of prior work and collaborating projects (Aging and Lifetimes as well as the DoD Joint Munitions Program) for two mission relevant epoxy encapsulants, 828DGEBA/DEA and 828DGEBA/T403. Multiple model calibration processes were developed and evaluated against the entire set of data for each material. A qualitative assessment of each calibration's ability to predict the wide range of aging responses was key to ranking the calibrations against each other. During this evaluation, predictions that were identified as non-physical, i.e., demonstrated something that was qualitatively different than known material behavior, were heavily weighted against the calibration performance. Thus, unphysical predictions for one aspect of aging response could generate a lower overall rating for a calibration process even if that process generated better quantitative predictions for another aspect of aging response. This insurance that all predictions are qualitatively correct is important to the overall aim of utilizing the model to predict residual stress evolution, which will depend on the interplay amongst the different material aging responses. The DSC-focused calibration procedure generated the best all-around aging predictions for both materials, demonstrating material models that can qualitatively predict the whole host of different physical aging responses that have been measured. This step forward in predictive capability comes from an unanticipated source, utilization of calorimetry measurements to specify model parameters. The DSC-focused calibration technique performed better than compression-focused techniques that more heavily weigh measurements more closely related to the structural responses to be predicted. Indeed, the DSC-focused calibration procedure was only possible due to recent incorporation of the enthalpy and heat capacity features into SPEC that was newly verified during this L2 milestone. Fundamentally similar aspects of the two material model calibrations as well as parametric studies to assess sensitives of the aging predictions are discussed within the report. A perspective on the next steps to the overall goal of residual stress evolution predictions under stockpile conditions closes the report.

36 MATERIALS SCIENCE↗

DOE OSTI2021

High-salinity brine desalination with amine-based temperature swing solvent extraction: A molecular dynamics study

Solvent extraction desalination (SED) is a promising technique for efficiently treating high salinity brines. However, only a few studies in the literature have investigated the influence of the molecular characteristics of the organic solvents on the emergent performance of the separation process. Thus, in this work we investigate the influence of the molecular structure of four different secondary amines on the desalination process of a concentrated aqueous solution of NaCl. Molecular dynamics simulations and free energy calculations are used to obtain the thermodynamic and structural properties of the pure solvent bulk phase, as well as a homogeneous solvent-water bulk mixture. Furthermore, solvent-water and solvent-brine interfacial systems are used to explicitly analyze the water partitioning behavior in the relevant temperature range for SED. The water solubilization in these secondary amines is found to be an exothermic process. Additionally, although the hydrogen-bonding interaction between the water and solvent molecules are beneficial, this interaction is not necessarily the dominant factor for ranking the water solubility performance of the different solvents. Finally, the excess volume of mixing of the bulk solvent-water mixture, as well as the electrostatic surface features of the solvents are also found to provide important clues for screening solvent behavior.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Towards a classification of rank r $\mathscr{N}$ = 2 SCFTs. Part II. Special Kahler stratification of the Coulomb branch

We study the stratification of the singular locus of four dimensional $\mathscr{N}$ = 2 Coulomb branches. We present a set of self-consistency conditions on this stratification which can be used to extend the classification of scale-invariant rank 1 Coulomb branch geometries to two complex dimensions, and beyond. The calculational simplicity of the arguments presented here stems from the fact that the main ingredients needed - the rank 1 deformation patterns and the pattern of inclusions of rank 2 strata - are discrete topological data which satisfy strong self-consistency conditions through their relationship to the central charges of the SCFT. This relationship of the stratification data to the central charges is used here, but is derived and explained in a companion paper by one of the authors. We illustrate the use of these conditions by re-analyzing many previously-known examples of rank 2 SCFTs, and also by finding examples of new theories. The power of these conditions stems from the fact that for Coulomb branch stratifications a conjecturally complete list of physically allowed “elementary slices” is known. By contrast, constraining the possible elementary slices of symplectic singularities relevant for Higgs branch stratifications remains an open problem.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Empirical Dynamic Modeling Reveals Complexity of Methane Fluxes in a Temperate Salt Marsh

Abstract Methane dynamics within salt marshes are complex because vegetation types, temperature, oscillating water levels, and changes in salinity and redox conditions influence CH 4 production, consumption, oxidation, and emissions. These non‐linear and complex interactions among variables affect the traditionally expected functional relationships and present challenges for interpreting and developing process‐based models. We employed empirical dynamic modeling (EDM) and convergent cross mapping (CCM) as a novel approach for characterizing seasonal/multiday and diurnal CH 4 dynamics by inferring causal variables, lags, and interconnections among multiple biophysical variables within a temperate salt marsh using 5 years of eddy covariance data. EDM/CCM is a nonparametric approach capable of quantifying the coupling between variables while determining time scales where variable interactions are the most relevant. We found that gross primary productivity, tidal creek dissolved oxygen, and temperature were important for seasonal/multiday dynamics (rho = 0.73–0.80), while water level was most important for diurnal dynamics during both the growing and dormancy phenoperiods (rho = 0.72 and 0.56, respectively). Lags for the top‐ranked variables (i.e., gross primary productivity, dissolved oxygen, temperature, water level) occurred between 1 and 5 weeks at the seasonal scale and 1–24 hr at the diurnal scale. The EDM had high prediction capabilities for intra‐/inter‐seasonal patterns and annual CH 4 sums but had limitations in representing large, infrequent fluxes. Results highlight the importance of non‐linearity, drivers, lag times, and interconnections among multiple biophysical variables that regulate CH 4 fluxes in tidal wetlands. This research introduces a novel approach to examining CH 4 fluxes, which will aid in evaluating current paradigms in wetlands and other ecosystems.

Environmental Sciences & Ecology↗

DOE OSTI2022

A QUBO formulation for top-τ eigencentrality nodes

The efficient calculation of the centrality or “hierarchy” of nodes in a network has gained great relevance in recent years due to the generation of large amounts of data. The eigenvector centrality (aka eigencentrality) is quickly becoming a good metric for centrality due to both its simplicity and fidelity. In this work we lay the foundations for solving the eigencentrality problem of ranking the importance of the nodes of a network with scores from the eigenvector of the network, using quantum computational paradigms such as quantum annealing and gate-based quantum computing. The problem is reformulated as a quadratic unconstrained binary optimization (QUBO) that can be solved on both quantum architectures. The results focus on correctly identifying a given number of the most important nodes in numerous networks given by the sparse vector solution of our QUBO formulation of the problem of identifying the top- τ highest eigencentrality nodes in a network on both the D-Wave and IBM quantum computers.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Capturing many-body correlation effects with quantum and classical computing

Theoretical descriptions of excited states of molecular systems in high-energy regimes are crucial for supporting and driving many experimental efforts at light source facilities. However, capturing their complicated correlation effects requires formalisms that provide a hierarchical infrastructure of approximations. These approximations lead to an increased overhead in classical computing methods and, therefore, decisions regarding the ranking of approximations and the quality of results must be made on purely numerical grounds. The emergence of quantum computing methods has the potential to change this situation. Here, in this study, we demonstrate the efficiency of the quantum phase estimator (QPE) in identifying core-level states relevant to x-ray photoelectron spectroscopy. We compare and validate the QPE predictions with exact diagonalization and real-time equation-of-motion coupled-cluster formulations, which are some of the most accurate methods for states dominated by collective correlation effects.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2022

Performance Testing of a Moving Bed Gasifier Using Coal, Biomass, and Waste Plastic Blends to Generate White Hydrogen

The objective of this DOE-funded project by the Electric Power Research Institute, Inc. (EPRI), Hamilton Maurer International (HMI) and Sotacarbo S.p.A. (Sotacarbo), is to qualify coal, biomass, and plastic waste blends based on performance testing of selected pellet recipes in a pilot-scale updraft moving-bed gasifier. The testing provides relevant data to advance the commercial-scale design of the moving-bed gasifier to be able to successfully use these feedstocks to produce hydrogen. In particular, the effects of the waste plastics on feedstock development (i.e., blending and pelletizing) and the resulting products (i.e., syngas compositions, organic condensate production, and ash characteristics) are a focus. The gasifier is Hamilton Mauer International, Inc. (HMI)’s moving-bed gasifier, which has been proven capable of gasifying nearly all coal ranks. It has also shown the ability in prior testing work to gasify wood chips. However, mixtures of these fuels with plastic wastes had not yet been prepared and gasified together. The feedstocks were prepared by California Pellet Mill (CPM) under contract to HMI. The technical tasks for this research project included: • Feed Procurement and Preparation: Nine different feedstocks were prepared from varying compositions of PRB coal, corn stover biomass, and car fluff waste plastics. Fuel pellets were produced by California Pellet Mill (CPM) and shipped to Sotacarbo’s test facility in Italy. • Test Plan Development: A test plan was created to define the test runs to be performed. The test plan detailed the different tests that were run, instrumentation used, extractive samples taken, and relevant figures of merit. • Gasifier Testing: Tests were performed in the pilot-scale gasifier at Sotacarbo using nine different fuel feedstocks generated from varying mixtures of coal, biomass, and plastic wastes. The testing provides information on gasification reaction efficiency/performance, yielding relevant data for models used to scale up the gasifier design. This task will also included work to reassemble the gasifier at Sotacarbo and perform a baseline 100% coal run. • Data Analysis and Reporting: Review of the data, determination of figures of merit, and interpretation of the results was reported. The results can be used to specify the range of feedstock blends that can be successfully gasified as well as quantify gasifier outputs based on specific blends. The tri-fuel pelletizing conducted at CPM and gasification testing results from Sotacarbo’s 30mm up draft moving bed gasifier are significant. Providing data for an established gasifier to help accelerate its updated design to be able to accommodate feedstocks composed of coal, biomass, and plastic waste. This should ultimately lead to development and commercialization of a lower cost, white hydrogen generation system.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2023

Performance Testing of a Moving-Bed Gasifier Using Coal, Biomass, and Waste Plastic Blends to Generate White Hydrogen

The objective of this DOE-funded project by the Electric Power Research Institute, Inc. (EPRI), Hamilton Maurer International (HMI) and Sotacarbo S.p.A. (Sotacarbo), is to qualify coal, biomass, and plastic waste blends based on performance testing of selected pellet recipes in a pilot-scale updraft moving-bed gasifier. The testing provides relevant data to advance the commercial-scale design of the moving-bed gasifier to be able to successfully use these feedstocks to produce hydrogen. In particular, the effects of the waste plastics on feedstock development (i.e., blending and pelletizing) and the resulting products (i.e., syngas compositions, organic condensate production, and ash characteristics) are a focus. The gasifier is Hamilton Mauer International, Inc. (HMI)’s moving-bed gasifier, which has been proven capable of gasifying nearly all coal ranks. It has also shown the ability in prior testing work to gasify wood chips. However, mixtures of these fuels with plastic wastes had not yet been prepared and gasified together. The feedstocks were prepared by California Pellet Mill (CPM) under contract to HMI. The technical tasks for this research project included: • Feed Procurement and Preparation: Nine different feedstocks were prepared from varying compositions of PRB coal, corn stover biomass, and car fluff waste plastics. Fuel pellets were produced by California Pellet Mill (CPM) and shipped to Sotacarbo’s test facility in Italy. • Test Plan Development: A test plan was created to define the test runs to be performed. The test plan detailed the different tests that were run, instrumentation used, extractive samples taken, and relevant figures of merit. • Gasifier Testing: Tests were performed in the pilot-scale gasifier at Sotacarbo using nine different fuel feedstocks generated from varying mixtures of coal, biomass, and plastic wastes. The testing provides information on gasification reaction efficiency/performance, yielding relevant data for models used to scale up the gasifier design. This task will also included work to reassemble the gasifier at Sotacarbo and perform a baseline 100% coal run. • Data Analysis and Reporting: Review of the data, determination of figures of merit, and interpretation of the results was reported. The results can be used to specify the range of feedstock blends that can be successfully gasified as well as quantify gasifier outputs based on specific blends. The tri-fuel pelletizing conducted at CPM and gasification testing results from Sotacarbo’s 30mm up draft moving bed gasifier are significant. Providing data for an established gasifier to help accelerate its updated design to be able to accommodate feedstocks composed of coal, biomass, and plastic waste. This should ultimately lead to development and commercialization of a lower cost, white hydrogen generation system.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2021

Gasification of Mixed Blends of Coal, Biomass, and Plastic Waste

The objective of this DOE-funded project by the Electric Power Research Institute, Inc. (EPRI), Hamilton Maurer International (HMI) and Sotacarbo S.p.A. (Sotacarbo), is to qualify coal, biomass, and plastic waste blends based on performance testing of selected pellet recipes in a pilot-scale updraft moving-bed gasifier. The testing provides relevant data to advance the commercial-scale design of the moving-bed gasifier to be able to successfully use these feedstocks to produce hydrogen. In particular, the effects of the waste plastics on feedstock development (i.e., blending and pelletizing) and the resulting products (i.e., syngas compositions, organic condensate production, and ash characteristics) are a focus. The gasifier is Hamilton Mauer International, Inc. (HMI)’s moving-bed gasifier, which has been proven capable of gasifying nearly all coal ranks. It has also shown the ability in prior testing work to gasify wood chips. However, mixtures of these fuels with plastic wastes had not yet been prepared and gasified together. The feedstocks were prepared by California Pellet Mill (CPM) under contract to HMI. The technical tasks for this research project included: • Feed Procurement and Preparation: Nine different feedstocks were prepared from varying compositions of PRB coal, corn stover biomass, and car fluff waste plastics. Fuel pellets were produced by California Pellet Mill (CPM) and shipped to Sotacarbo’s test facility in Italy. • Test Plan Development: A test plan was created to define the test runs to be performed. The test plan detailed the different tests that were run, instrumentation used, extractive samples taken, and relevant figures of merit. • Gasifier Testing: Tests were performed in the pilot-scale gasifier at Sotacarbo using nine different fuel feedstocks generated from varying mixtures of coal, biomass, and plastic wastes. The testing provides information on gasification reaction efficiency/performance, yielding relevant data for models used to scale up the gasifier design. This task will also included work to reassemble the gasifier at Sotacarbo and perform a baseline 100% coal run. • Data Analysis and Reporting: Review of the data, determination of figures of merit, and interpretation of the results was reported. The results can be used to specify the range of feedstock blends that can be successfully gasified as well as quantify gasifier outputs based on specific blends. The tri-fuel pelletizing conducted at CPM and gasification testing results from Sotacarbo’s 30mm up draft moving bed gasifier are significant. Providing data for an established gasifier to help accelerate its updated design to be able to accommodate feedstocks composed of coal, biomass, and plastic waste. This should ultimately lead to development and commercialization of a lower cost, white hydrogen generation system.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2023

Recent progress on understanding the temperature-dependent irradiation resistance ranking among NiFe, NiCoCr, and NiCoFeCr alloys: A review

Systematic temperature-effects investigations on damage evolution in ion-irradiated Ni-based concentrated solid-solution alloys (CSAs) are pivotal to provide reliance on their use in nuclear applications. Here, in search of the origin behind the temperature-dependent irradiation resistance ranking among equiatomic NiFe, NiCoCr and NiCoFeCr alloys, we have compared, previously experimental and theoretical published data involving ion irradiation experiments performed on these alloys with new ion channeling results from ion-irradiated NiCoFeCr at 500 K. Moreover, the current results are compared with independent theoretical calculations and relevant TEM results from literature, which allow us to suggest that the lower migration energy of vacancies in NiCoCr, as compared with those in NiFe and NiCoFeCr, is the reason behind why NiCoCr is no longer outperforming NiFe under ion irradiation above 300 K.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2022

Performance Testing of a Moving-Bed Gasifier Using Coal, Biomass, and Waste Plastic Blends to Generate White Hydrogen

The objective of this DOE-funded project by the Electric Power Research Institute, Inc. (EPRI), Hamilton Maurer International (HMI) and Sotacarbo S.p.A. (Sotacarbo), is to qualify coal, biomass, and plastic waste blends based on performance testing of selected pellet recipes in a pilot-scale updraft moving-bed gasifier. The testing will provide relevant data to advance the commercial-scale design of the moving-bed gasifier to be able to successfully use these feedstocks to produce hydrogen. In particular, the effects of the waste plastics on feedstock development (i.e., blending and pelletizing) and the resulting products (i.e., syngas compositions, organic condensate production, and ash characteristics) are a focus. The gasifier is Hamilton Mauer International, Inc. (HMI)’s moving-bed gasifier, which has been proven capable of gasifying nearly all coal ranks. It has also shown the ability in prior testing work to gasify wood chips. However, mixtures of these fuels with plastic wastes have not been prepared and gasified together. The feedstocks will be prepared by California Pellet Mill (CPM) under contract to HMI. The technical tasks and current status for this two-year research project are: Feed Procurement and Preparation: Nine different feedstocks were prepared from varying compositions of PRB coal, corn stover biomass, and car fluff waste plastics. Fuel pellets were produced by California Pellet Mill and shipped to Sotacarbo’s test facility in Italy. Test Plan Development: A test plan was created to define the test runs to be performed. The test plan detailed the different tests that were run, instrumentation used, extractive samples taken, and relevant figures of merit. Gasifier Testing: Tests are currently being performed in the pilot-scale gasifier at Sotacarbo using nine different fuel feedstocks generated from varying mixtures of coal, biomass, and plastic wastes. The testing will provide information on gasification reaction efficiency/performance, yielding relevant data for models used to scale up the gasifier design. This task will also include work to reassemble the gasifier at Sotacarbo and perform a baseline 100% coal run. Data Analysis and Reporting: Review of the data, determination of figures of merit, and interpretation of the results to be reported. The results will be used to specify the range of feedstock blends that can be successfully gasified as well as quantify gasifier outputs based on specific blends. This paper will be summarize the pelletizing procedure that insures the viability of the tri-fuel pellets for the gasification runs that are being performed at Sotacarbo’s 30mm up draft moving bed gasifier. Initial gasification tests have been conducted, and all the lab scale tri-fuel pellet gasification runs will be completed by the fall of 2022. Performance data will enable modeling of a full-scale HMI industrial scale gasifier supporting both CHP and Hydrogen production.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2021

Prioritizing Countries by Concern Regarding Access to Weapons of Mass Destruction Materials

This article presents a global prioritization methodology that evaluates the relative risks of non-state actor acquisition of materials that could be used in chemical, biological, radiological, nuclear and high explosive Weapons of Mass Destruction (WMD) from the country’s relevant infrastructure. Prioritization is based on three domains: 1. Assessing relative scale of materials in each country, 2. The country’s corresponding security posture, and 3. The presence of threat actors. The output is a list of countries prioritized from greatest risk to least. Rather than providing an overall 1 to N ranking, however, the results are placed into tiers based upon their natural groupings within the three domains. The countries in the highest tiers are flagged as potential US national security concern; those scoring in the middle and at the bottom are flagged as posing lower US national security concern. A systematic approach assesses each country by leveraging many disciplines, such as risk and decision analysis, as well as expert judgement. A quantitative value model based on Multi-Attribute Value Theory (MAVT) organizes the objectives scoring criteria into a value tree using lessons learned from previous studies, published literature, and expert judgement. The article presents the prioritization categories and corresponding value model scoring criteria to include measurement type, weight, range, and value preference. Country names and data are notional in order to share the details on the underlying methodology and model without identification of actual security risks. A deliberative process addresses factors external to the model and scrutinizes inputs, methodology, model, and results.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2020

The effect of school intervention programs on the body mass index of adolescents: a systematic review with meta-analysis

Abstract Effective obesity interventions in adolescent populations have been identified as an immediate priority action to stem the increasing prevalence of adult obesity. The purpose of this meta-analysis was to make a quantitative analysis of the impact of school-based interventions on body mass index during adolescence. Studies were retrieved from PubMed, Scopus, Science Direct and Web of Science databases. Results were pooled using a random-effects model with 95% confidence interval considered statistically significant. Of the 18 798 possible relevant articles identified, 12 articles were included in this meta-analysis. The global result showed a low magnitude effect, though it was statistically significant (N = 14 428), global e.s. = −0.055, P = 0.004 (95% CI = −0.092, −0.017). Heterogeneity was low among the studies (I2 = 9.017%). The funnel plot showed no evidence of publication bias. The rank-correlation test of Begg (P = 0.45641) and Egger’s regression (P = 0.19459) confirmed the absence of bias. This meta-analysis reported a significant effect favoring the interventions; however, future research are needed since the reported the evidence was of low magnitude, with the studies following a substantial range of approaches and mostly had a modest methodological quality.

Saavedra Dias, R.↗

DOE OSTI2024

Experimental Considerations for Estimating Degradation in PV Modules

Carefully controlled laboratory experiments and measurements can enable the determination of acceleration factors suitable for extrapolation to durability and performance of a fielded PV module. Ideally, a single mechanism can be identified with appropriate acceleration factors for extrapolation to the field. However, even with a single mechanism, the inherent uncertainty in these factors leads to uncertainty in the extrapolation which is greater the higher the acceleration factor. This course will explain how because of the wide range of acceleration factors for a given degradation mode, utilizing acceleration factors greater than about 10x will typically lead to unacceptable uncertainty in the results. Therefore, if even just a rank ordering of materials is desired, acceleration factors must be minimized which requires a good general understanding of the scale of the different acceleration factors for the degradation mode of interest. In this tutorial we will discuss what the different purposes are for many of the accelerated stress tests used today. E.g., what is a qualification test, a highly accelerated stress test, a rank ordering test, or a service life prediction test. We will discuss how one can understand the relationship between test results and expected field performance. A single accelerated stress test condition cannot duplicate outdoor exposure for all possible degradation pathways; therefore, one must use targeted evaluation of material properties at different stress levels to determine the relevant acceleration factors and fit it to a model. We will also discuss how to interpret the results of experiments understanding what is relevant/not relevant, or not e valuated in a test. There are many common error people make in their test interpretations because they push the stress levels to be too harsh. This creates biases and can mask the relevant failure modes and mechanisms or will erroneously lead one to over design materials against things that aren't relevant. Several case studies will be presented to illustrate appropriate interpretation of accelerated stress testing results.

degradation↗