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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Bacterial fitness for plant colonization is influenced by plant growth substrate

Despite advances in our understanding of bacterial plant colonization, the extent to which growth substrate influences the molecular mechanisms enabling bacteria to efficiently colonize plants remains poorly understood. To address this, we used randomly barcoded transposon mutagenesis sequencing (RB-TnSeq) in Paraburkholderia graminis OAS925, an efficient rhizosphere colonizer, and Brachypodium distachyon grown in six different substrates. Of the 382 rhizosphere colonization genes that we identified in OAS925, 348 genes (91.1%) are dependent on the growth substrate evaluated, and 34 genes (8.9%) are shared across all the substrates. Both the core and substrate-dependent colonization genes are from multiple functional categories, demonstrating the multifaceted and major impact that plant growth substrate has on bacterial colonization. The identified colonization genes and their varied importance across plant growth substrates could not be readily explained by differences in root exudate profiles, suggesting that the substrate environment itself plays an outsized role in the ability of a bacterium to colonize the rhizosphere. Our data confirm that bacterial fitness for plant colonization is strongly influenced by plant growth substrate type and highlights the importance of taking this parameter into consideration when engineering bacterial strains for improved host colonization.

Paraburkholderia↗
DOE OSTI2020

A systems genetics approach to deciphering the effect of dosage variation on leaf morphology in Populus

Abstract Gene copy number variation is frequent in plant genomes of various species, but the impact of such gene dosage variation on morphological traits is poorly understood. We used a large population of Populus carrying genomically characterized insertions and deletions across the genome to systematically assay the effect of gene dosage variation on a suite of leaf morphology traits. A systems genetics approach was used to integrate insertion and deletion locations, leaf morphology phenotypes, gene expression, and transcriptional network data, to provide an overview of how gene dosage influences morphology. Dosage-sensitive genomic regions were identified that influenced individual or pleiotropic morphological traits. We also identified cis-expression quantitative trait loci (QTL) within these dosage QTL regions, a subset of which modulated trans-expression QTL as well. Integration of data types within a gene co-expression framework identified co-expressed gene modules that are dosage sensitive, enriched for dosage expression QTL, and associated with morphological traits. Functional description of these modules linked dosage-sensitive morphological variation to specific cellular processes, as well as candidate regulatory genes. Together, these results show that gene dosage variation can influence morphological variation through complex changes in gene expression, and suggest that frequently occurring gene dosage variation has the potential to likewise influence quantitative traits in nature.

Biochemistry & Molecular Biology↗
DOE OSTI2024

The Exometabolome of Xylella fastidiosa in Contact with Paraburkholderia phytofirmans Supernatant Reveals Changes in Nicotinamide, Amino Acids, Biotin, and Plant Hormones

Microbial competition within plant tissues affects invading pathogens’ fitness. Metabolomics is a great tool for studying their biochemical interactions by identifying accumulated metabolites. Xylella fastidiosa, a Gram-negative bacterium causing Pierce’s disease (PD) in grapevines, secretes various virulence factors including cell wall-degrading enzymes, adhesion proteins, and quorum-sensing molecules. These factors, along with outer membrane vesicles, contribute to its pathogenicity. Previous studies demonstrated that co-inoculating X. fastidiosa with the Paraburkholderia phytofirmans strain PsJN suppressed PD symptoms. Here, we further investigated the interaction between the phytopathogen and the endophyte by analyzing the exometabolome of wild-type X. fastidiosa and a diffusible signaling factor (DSF) mutant lacking quorum sensing, cultivated with 20% P. phytofirmans spent media. Liquid chromatography–mass spectrometry (LC-MS) and the Method for Metabolite Annotation and Gene Integration (MAGI) were used to detect and map metabolites to genomes, revealing a total of 121 metabolites, of which 25 were further investigated. These metabolites potentially relate to host adaptation, virulence, and pathogenicity. Notably, this study presents the first comprehensive profile of X. fastidiosa in the presence of a P. phytofirmans spent media. The results highlight that P. phytofirmans and the absence of functional quorum sensing affect the ratios of glutamine to glutamate (Gln:Glu) in X. fastidiosa. Additionally, two compounds with plant metabolism and growth properties, 2-aminoisobutyric acid and gibberellic acid, were downregulated when X. fastidiosa interacted with P. phytofirmans. These findings suggest that P. phytofirmans-mediated disease suppression involves modulation of the exometabolome of X. fastidiosa, impacting plant immunity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Ecological and genomic variation in ectomycorrhizal fungal exploration types

Ectomycorrhizal fungi (EMF) produce mycelia with variable extension and complexity, which can be classified according to soil ‘exploration types’ (ETs). ETs have received attention as one of the few mycorrhizal trait frameworks, but without an empirical classification of ET functional diversity and environmental preferences, understanding and interpreting EMF biogeographic patterns has been difficult. We conducted a synthesis combining: comparative EMF genomics to describe functional divergence in decomposition and nutrient cycling genes across ETs; and EMF trait distribution modeling across continental Europe, pairing soil and root EMF surveys to establish biogeographic ET niche profiles. We demonstrate a signature of ETs encoded in EMF genomes, which is independent from phylogeny and linked to biomass production strategies. EMF ET relative abundances were separated by soil, root, and dominant tree leaf type habitats and exhibited unique correlations with forest biotic (e.g. plant productivity and plant pathogen densities) and abiotic (e.g. nitrogen deposition and soil pH) conditions. These findings support a theory that EMF niche partitioning can be partially explained by extraradical mycelial traits, with underlying variation in ET biogeography likely arising from distinct decomposition and nutrient cycling potentials. We also identify important limitations to this trait framework and provide a guided outlook for future research.

biogeography↗
DOE OSTI2020

Validation of ORIGEN for VVER-440 Spent Fuel with Application to Fork Detector Safeguards Measurements

The US Department of Energy National Nuclear Security Administration and the European Atomic Energy Community (Euratom) are collaborating with the Radiation and Nuclear Safety Authority in Finland to assess spent fuel verification methods for potential application to measurements at the planned spent fuel encapsulation plant and geological repository prior to final disposal in Finland. The fork detector (FDET) used to measure the neutron and gamma radiation from a given spent fuel assembly is an existing technology widely used by the International Atomic Energy Agency (IAEA) and Euratom for the safeguards verification of spent fuel operator declaration. Recently, an FDET data analysis software, referred to as the ORIGEN module, was developed and incorporated into the IAEA/Euratom Integrated Review and Analysis Program. This module uses the ORIGEN burnup code to calculate the nuclide concentrations and the neutron and gamma source terms in the spent fuel based on operator declarations. Then, to predict the expected FDET signals for a given fuel assembly, the module combines the source terms calculated by ORIGEN with FDET response functions that were pre-generated using MCNP models. The inspector can compare the calculated signals to the measured values in real time to identify possible anomalies in fuel assembly’s operator declaration, integrity, or measurement. In this work, the capability of the ORIGEN module was extended from application to typical light water reactor fuels to use for VVER-440 assembly types. The accuracy of ORIGEN for this type of fuel assembly calculations was assessed by comparing calculated nuclide concentrations against destructive assay measurements for VVER-440 spent fuel. The performance of the ORIGEN module for FDET safeguards verification in routine inspections was assessed using FDET measurement data for 13 spent VVER-440 assemblies that were measured at the Loviisa Nuclear Power Plant in Finland, by comparing the calculated signals to the measured quantities. The results show that the calculated FDET neutron and gamma detector signals are generally within 12% of the measurements except for one assembly. Thus, these results are applicable to future safeguards verification in the planned Finland encapsulation plant, such as for passive neutron albedo reactivity safeguards measurements.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

PWR loading pattern optimization with reinforcement learning

The core loading pattern optimization problem belongs to the class of combinatorial optimization problem and has been studied since the dawn of commercial nuclear energy industry. It is characterized by multiple objectives and constraints, with a very high number of candidate patterns, which makes it impossible to solve explicitly. Stochastic optimization methodologies including Genetic Algorithms and Simulated Annealing are used by different nuclear utilities and vendors to perform fuel cycle reload design. Nevertheless, hand-designed solutions continue to be the prevalent method in the industry. To improve the state-of-the-art core reload patterns, we aim to create a method as scalable as possible, that agrees with the designer's goal of performance and safety. To help in this task Deep Reinforcement Learning (DRL), in particular Proximal Policy Optimization is leveraged. DRL has recently experienced a strong impetus from its successes applied to games, sometimes even reaching 'super-human' performances. This paper lays out the foundation of this method and proposes to study the behavior of several hyper-parameters that influence the DRL algorithm. The algorithm is highly dependent on multiple factors such as an exploration/exploitation trade-off that manifests through different parameters such as the number of loading patterns seen and the number of samples collected before a policy update, but also the shape of the objective function derived for the core design. Experimental results also demonstrate the effectiveness of the method in finding high-quality solutions from scratch within a reasonable amount of time. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Bacterial effectors mimicking ubiquitin-proteasome pathway tweak plant immunity

Plant pathogenic Gram-negative bacteria evade the host plant immune system by secreting Type III (T3E) and Type IV effector (T4E) proteins into the plant cytoplasm. Mostly T3Es are secreted into the plant cells to establish pathogenicity by affecting the vital plant process viz. metabolic pathways, signal transduction and hormonal regulation. Ubiquitin-26S proteasome system (UPS) exists as one of the important pathways in plants to control plant immunity and various cellular processes by employing several enzymes and enzyme components. Pathogenic and non-pathogenic bacteria are found to secrete effectors into plants with structural and/or functional similarity to UPS pathway components like ubiquitin E3 ligases, F-box domains, cysteine proteases, inhibitor of host UPS or its components, etc. The bacterial effectors mimic UPS components and target plant resistance proteins for degradation by proteasomes, thereby taking control over the host cellular activities as a strategy to exert virulence. Thus, the bacterial effectors circumvent plant cellular pathways leading to infection and disease development. Finally, this review highlights known bacterial T3E and T4E proteins that function and interfere with the ubiquitination pathway to regulate the immune system of plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Plant Cell Identity in the Era of Single-Cell Transcriptomics

High-throughput single-cell transcriptomic approaches have revolutionized our view of gene expression at the level of individual cells, providing new insights into their heterogeneity, identities, and functions. Recently, technical challenges to the application of single-cell transcriptomics to plants have been overcome, and many plant organs and tissues have now been subjected to analyses at single-cell resolution. In this review, we describe these studies and their impact on our understanding of the diversity, differentiation, and activities of plant cells. We particularly highlight their impact on plant cell identity, including unprecedented views of cell transitions and definitions of rare and novel cell types. Lastly, we also point out current challenges and future opportunities for the application and analyses of single-cell transcriptomics in plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A gene-editing/complementation strategy for tissue-specific lignin reduction while preserving biomass yield

Lignification of secondary cell walls is a major factor conferring recalcitrance of lignocellulosic biomass to deconstruction for fuels and chemicals. Genetic modification can reduce lignin content and enhance saccharification efficiency, but usually at the cost of moderate-to-severe growth penalties. We have developed a method, using a single DNA construct that uses CRISPR–Cas9 gene editing to knock-out expression of an endogenous gene of lignin monomer biosynthesis while at the same time expressing a modified version of the gene’s open reading frame that escapes cutting by the Cas9 system and complements the introduced mutation in a tissue-specific manner. Expressing the complementing open reading frame in vessels allows for the regeneration of Arabidopsis plants with reduced lignin, wild-type biomass yield, and up to fourfold enhancement of cell wall sugar yield per plant. The above phenotypes are seen in both homozygous and bi-allelic heterozygous T1 lines, and are stable over at least four generations. The method provides a rapid approach for generating reduced lignin trees or crops with one single transformation event, and, paired with a range of tissue-specific promoters, provides a general strategy for optimizing loss-of-function traits that are associated with growth penalties. This method should be applicable to any plant species in which transformation and gene editing are feasible and validated vessel-specific promoters are available.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Transcript and metabolite network perturbations in lignin biosynthetic mutants of Arabidopsis

Abstract Lignin, one of the most abundant polymers in plants, is derived from the phenylpropanoid pathway, which also gives rise to an array of metabolites that are essential for plant fitness. Genetic engineering of lignification can cause drastic changes in transcription and metabolite accumulation with or without an accompanying development phenotype. To understand the impact of lignin perturbation, we analyzed transcriptome and metabolite data from the rapidly lignifying stem tissue in 13 selected phenylpropanoid mutants and wild-type Arabidopsis (Arabidopsis thaliana). Our dataset contains 20,974 expressed genes, of which over 26% had altered transcript levels in at least one mutant, and 18 targeted metabolites, all of which displayed altered accumulation in at least one mutant. We found that lignin biosynthesis and phenylalanine supply via the shikimate pathway are tightly co-regulated at the transcriptional level. The hierarchical clustering analysis of differentially expressed genes (DEGs) grouped the 13 mutants into 5 subgroups with similar profiles of mis-regulated genes. Functional analysis of the DEGs in these mutants and correlation between gene expression and metabolite accumulation revealed system-wide effects on transcripts involved in multiple biological processes.

Plant Sciences↗
DOE OSTI2022

Proteome-scale Deployment of Protein Structure Prediction Workflows on the Summit Supercomputer

Deep learning has contributed to major advances in the prediction of protein structure from sequence, a fundamental problem in structural bioinformatics. With predictions now approaching the accuracy of crystallographic experiments, and with accelerators like GPUs and TPUs making inference using large models rapid, genome-level structure prediction becomes an obvious aim. Leadership-class computing resources can be used to perform genome-scale protein structure prediction using state-of-the-art deep learning models, providing a wealth of new data for systems biology applications. Here we describe our efforts to efficiently deploy the AlphaFold v.2 program, for full-proteome structure prediction, at scale on the Oak Ridge Leadership Computing Facility's resources, including the Summit supercomputer. We performed inference to produce the predicted structures for 40,526 protein sequences, corresponding to four prokaryotic proteomes and one plant proteome, using under 4,400 total Summit node hours, equivalent to using the majority of the supercomputer for a little over one hour. We also designed an optimized structure refinement that reduced the time for the relaxation stage of the AlphaFold pipeline by over 10X for longer sequences. We demonstrate the types of analyses that can be performed on proteome-scale collections of sequences, including a search for novel quaternary structures and implications for functional annotation.

Gao, Mu↗
DOE OSTI2024

Dinickel enzyme evolved to metabolize the pharmaceutical metformin and its implications for wastewater and human microbiomes

Metformin is the first-line treatment for type II diabetes patients and a pervasive pollutant with more than 180 million kg ingested globally and entering wastewater. The drug’s direct mode of action is currently unknown but is linked to effects on gut microbiomes and may involve specific gut microbial reactions to the drug. In wastewater treatment plants, metformin is known to be transformed by microbes to guanylurea, although genes encoding this metabolism had not been elucidated. In the present study, we revealed the function of two genes responsible for metformin decomposition (mfmA and mfmB) found in isolated bacteria from activated sludge. MfmA and MfmB form an active heterocomplex (MfmAB) and are members of the ureohydrolase protein superfamily with binuclear metal-dependent activity. MfmAB is nickel-dependent and catalyzes the hydrolysis of metformin to dimethylamine and guanylurea with a catalytic efficiency (k cat /K M ) of 9.6 × 10 3 M -1 s -1 and KM for metformin of 0.82 mM. MfmAB shows preferential activity for metformin, being able to discriminate other close substrates by several orders of magnitude. Crystal structures of MfmAB show coordination of binuclear nickel bound in the active site of the MfmA subunit but not MfmB subunits, indicating that MfmA is the active site for the MfmAB complex. Mutagenesis of residues conserved in the MfmA active site revealed those critical to metformin hydrolase activity and its small substrate binding pocket allowed for modeling of bound metformin. In conclusion, this study characterizes the products of the mfmAB genes identified in wastewater treatment plants on three continents, suggesting that metformin hydrolase is widespread globally in wastewater.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Process optimization of caustic scrubber and iodine-129 immobilization in sodalite-based waste forms

Caustic scrubbers are proposed to remove vaporized iodine from nuclear fuel reprocessing plants. Resulting caustic slurries of radioactive iodine ( 129 I) and other anions can be captured and immobilized into the cage structures of sodalite-type minerals. Here, mixed anion sodalites were hydrothermally synthesized from a simulated caustic scrubber solution containing hydroxide/water, carbonate, chlorine, bromine, iodine, nitrate, and nitrite ions with added kaolinite. Experiments were conducted with twenty-five different sets of process conditions. Resulting powders were characterized by quantitative X-ray diffraction (XRD) and multi-functional thermal analysis, including gravimetry, calorimetry, and mass spectrometry. Using statistical analysis, process variables were tailored to maximize conversion of kaolinite into cage silicates, immobilize caustic scrubber anions, and minimize amorphous content. Further, chemical analysis showed the incorporation of all the targeted ions into the solids. Detailed investigation of a batch characterized after washing (creating secondary waste) and one without washing but subsequent calcination is given. This work contributes to defining the constraints required for subsequent consolidation process steps of the waste form to avoid volatilization.

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

Long-term warming in a Mediterranean-type grassland affects soil bacterial functional potential but not bacterial taxonomic composition

Abstract Climate warming is known to impact ecosystem composition and functioning. However, it remains largely unclear how soil microbial communities respond to long-term, moderate warming. In this study, we used Illumina sequencing and microarrays (GeoChip 5.0) to analyze taxonomic and functional gene compositions of the soil microbial community after 14 years of warming (at 0.8–1.0 °C for 10 years and then 1.5–2.0 °C for 4 years) in a Californian grassland. Long-term warming had no detectable effect on the taxonomic composition of soil bacterial community, nor on any plant or abiotic soil variables. In contrast, functional gene compositions differed between warming and control for bacterial, archaeal, and fungal communities. Functional genes associated with labile carbon (C) degradation increased in relative abundance in the warming treatment, whereas those associated with recalcitrant C degradation decreased. A number of functional genes associated with nitrogen (N) cycling (e.g., denitrifying genes encoding nitrate-, nitrite-, and nitrous oxidereductases) decreased, whereas nifH gene encoding nitrogenase increased in the warming treatment. These results suggest that microbial functional potentials are more sensitive to long-term moderate warming than the taxonomic composition of microbial community.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Community‐Level Metabolic Shifts Following Land Use Change in the Amazon Rainforest Identified by a Supervised Machine Leaning Approach

ABSTRACT The Amazon rainforest has been subjected to high rates of deforestation, mostly for pasturelands, over the last few decades. This change in plant cover is known to alter the soil microbiome and the functions it mediates, but the genomic changes underlying this response are still unresolved. In this study, we used a combination of deep shotgun metagenomics complemented by a supervised machine learning approach to compare the metabolic strategies of tropical soil microbial communities in pristine forests and long‐term established pastures in the Amazon. Machine learning‐derived metagenome analysis indicated that microbial community structures (bacteria, archaea and viruses) and the composition of protein‐coding genes were distinct in each plant cover type environment. Forest and pasture soils had different genomic diversities for the above three taxonomic groups, characterised by their protein‐coding genes. These differences in metagenome profiles in soils under forests and pastures suggest that metabolic strategies related to carbohydrate and energy metabolisms were altered at community level. Changes were also consistent with known modifications to the C and N cycles caused by long‐term shifts in aboveground vegetation and were also associated with several soil physicochemical properties known to change with land use, such as the C/N ratio, soil temperature and exchangeable acidity. In addition, our analysis reveals that these alterations in land use can also result in changes to the composition and diversity of the soil DNA virome. Collectively, our study indicates that soil microbial communities shift their overall metabolic strategies, driven by genomic alterations observed in pristine forests and long‐term established pastures with implications for the C and N cycles.

carbon and nitrogen cycles↗
DOE OSTI2022

Cognitive Aging as a Human Factor: Effects of Age on Human Performance

Nuclear power plant (NPP) control room operators must make ongoing computations and decisions that maximize production and ensure safety, which places a high cognitive burden on the operators. How cognitions such as attention, visuospatial ability, and working memory interact with socio-technical systems to achieve optimal operations is well studied. However, there is an absence of research that examines how cognitive functioning within the NPP control room environment is moderated by developmental aging processes. This is of critical importance because different types of cognitive actions are known to develop and peak at different times across the adult life span, and it is becoming increasingly clear that there is no age at which all cognitive faculties operate at maximum capacity. Thus, given that NPPs are experiencing an aging workforce, it is vital to identify how mission critical cognitions change with age. This paper reviews implications of aging on reactor operators in the current and new fleet. We highlight lessons that can be learned from state-of-the-art human factors research that considers aging, lessons from the large cognitive aging literature, and lessons from aging workers in other industries that use sophisticated socio-technical systems, such as aviation. We also consider the important subject of aging effects versus expertise and present preliminary data that support the premise that age of operator is linked to effective and efficient operations but that this relationship may be moderated by level of operations expertise. In conclusion, we apply these lessons to future considerations for aging research in current nuclear operations and with the advent of advanced modernized control rooms.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

SAS4A/SASSYS-1 Commercial Grade Dedication Example Report for a Generic Sodium Pool-Type Fast Reactor Application

In the U.S., a key component of the commercialization of advanced reactors is completion of a license application, which must ultimately be approved by the Nuclear Regulatory Commission (NRC). The approval of the license application by the NRC is contingent on satisfactory demonstration of the design basis and the response of the advanced reactor design to transient and accident scenarios using accepted codes and methods. This report describes the qualification and dedication requirements that the advanced reactor safety analysis system software SAS4A/SASSYS-1 are expected to need to fulfill to be used for sodium-cooled pool-type fast reactor licensing. The qualification and dedication requirements are identified through performance critical characteristics and evaluation model acceptance criteria representative of the advanced reactor design considered for licensing. This document captures, additionally, the verification process developed to demonstrate that the software fulfills the qualification and dedication requirements for a generic sodium-cooled pool-type fast reactor as part of the commercial grade dedication process. Like most software that has primarily existed in the research and development space, the most significant challenge facing SAS4A/SASSYS-1 for use in a licensing framework is the availability of a documentation basis describing the code pedigree. SAS4A/SASSYS-1 has been used for licensing of the fast flux test facility (FFTF) and the JOYO sodium-cooled fast reactor in Japan, as well as the design of the CRBR Plant. However, the historical verification and validation (V&V) activities supporting SAS4A/SASSYS-1 development do not align with modern software quality assurance (SQA) and V&V requirements. Two approaches to use of SAS4A/SASSYS-1 in a commercial licensing framework have been identified: commercial-grade dedication (CGD) and software qualification. The methods and requirements prescribed in the ASME NQA-1-2008/2009 Standard and Regulatory Guide 1.203 on the evaluation model development and assessment process (EMDAP) have been used as guidance to define the CGD and qualification processes, respectively. A qualification and dedication requirements matrix has been developed which utilizes fundamental software verification. In this process, software verification is defined as a software quality process aimed at defining software requirement specifications, developing software design documentation, and performing and documenting acceptance testing of the code against requirements. A key element of software qualification and dedication includes determination of software acceptance with respect to critical characteristics relevant to the functional requirements of the software. To assist with identification of cross-cutting transient phenomena and functional requirements, domestic SFR vendor designs have been reviewed to identify a reference SFR design. For this report, the reference design is defined as a pool-type reactor with metal alloy fuel, a liquid-metal intermediate heat transport system, and passive decay heat rejection systems. Given this reference, a series of high-level cross-cutting phenomena was identified for a general class of single-fault undercooling or reactivity insertion transients that scopes the design basis space, with the goal of assisting with prioritization of documentation development efforts for key transient models in SAS: 1) Reactivity feedback response prior to scram; 2) System-wide thermal inertia; 3) Transition in natural circulation flow regime in heat removal systems; 4) Decay heat generation; 5) Steady-state fuel characterization; 5) Clad/fuel behavior at elevated temperatures; 6) Point kinetics and decay heat; 7) Pump coastdown behavior; 8) Core flow redistribution in loss of forced convection; 9) Pool stratification. As a demonstration of CGD of SAS4A/SASSYS-1 for a sodium pool reactor, a software qualification and dedication gap analysis as it relates to code documentation has been performed. This effort leverages the framework established as part of the SAS4A/SASSYS-1 SQA Program. This CGD demonstration provides a framework that vendors can build upon to demonstrate the applicability of the SAS4A/SASSYS-1 software for licensing a sodium-cooled pool-type fast reactor.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Method to Investigate Cognitive Aging Effects in Nuclear Operations Using the Rancor Microworld Simulator

Many nuclear power plant (NPP) operators are close to, or at retirement age. Since NPP operators are responsible for tasks that engage different and complex cognitive abilities, human factors researchers recently called for the need to examine cognitive aging effects and potential interactions with modernized control rooms. One way control rooms are being modernized is by replacing paper-based procedures with computer-based procedures (CBPs). This paper outlines a method for testing preference and usability of three types of CBPs as a function of age, in simulated NPP operations. The Rancor Microworld Simulator will be used, which mimics an NPP control room, allowing novices to learn to perform operator tasks quickly. The experiment will have two independent variables: age (young and old) and CBP-type (Type 1, Type 2, and Type 3). The three types of CBPs vary in levels of embedded instrumentation and controls. Adults aged 18–25 years (young group) and =60 years (older group) will be recruited from the general population. The dependent variables will be preference and usability metrics via survey and simulator logs. All participants will perform two scenario types (startup and loss of feedwater operations) and will be randomly assigned to one type of CBP to guide them through the scenario. Analyses of variance (ANOVAs) will be used to determine whether there is a main effect of age and any age x CBP-type interactions on the preference and usability dependent variables.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗