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At least 397 records · Page 22

Disentangling Sources of Gene Tree Discordance in Phylogenomic Data Sets: Testing Ancient Hybridizations in Amaranthaceae s.l

Gene tree discordance in large genomic data sets can be caused by evolutionary processes such as incomplete lineage sorting and hybridization, as well as model violation, and errors in data processing, orthology inference, and gene tree estimation. Species tree methods that identify and accommodate all sources of conflict are not available, but a combination of multiple approaches can help tease apart alternative sources of conflict. Here, using a phylotranscriptomic analysis in combination with reference genomes, we test a hypothesis of ancient hybridization events within the plant family Amaranthaceae s.l. that was previously supported by morphological, ecological, and Sanger-based molecular data. The data set included seven genomes and 88 transcriptomes, 17 generated for this study. We examined gene-tree discordance using coalescent-based species trees and network inference, gene tree discordance analyses, site pattern tests of introgression, topology tests, synteny analyses, and simulations. We found that a combination of processes might have generated the high levels of gene tree discordance in the backbone of Amaranthaceae s.l. Furthermore, we found evidence that three consecutive short internal branches produce anomalous trees contributing to the discordance. Overall, our results suggest that Amaranthaceae s.l. might be a product of an ancient and rapid lineage diversification, and remains, and probably will remain, unresolved. This work highlights the potential problems of identifiability associated with the sources of gene tree discordance including, in particular, phylogenetic network methods. Our results also demonstrate the importance of thoroughly testing for multiple sources of conflict in phylogenomic analyses, especially in the context of ancient, rapid radiations. We provide several recommendations for exploring conflicting signals in such situations.

59 BASIC BIOLOGICAL SCIENCES↗

Thermally Mobile Trace Elements in Carbonaceous Chondrites from Cold and Hot Deserts

Some decades ago, Anders and co-workers used RNAA to classify a number of trace elements as being volatile during nebular condensation and accretion into primitive objects based upon their strong depletion in (equilibrated) ordinary chondrites relative to C1 chondrites. Such elements, e.g. Ag, Bi, Cd, Cs, In, Se, Te, Tl, Zn and others, exhibit nearly constant, C1-normalized atomic abundances in C2 (CM2) and in C3 chondrites. They interpreted the near-constancy of these abundances according to a 2-component model in which volatiles were introduced into carbonaceous (and other) chondrites as Cl material which was diluted with differing proportions of high-temperature (i.e. volatile-free) components. In this view, mean volatile element abundances of 0.48 in C2 and 0.24-0.29 x C1 in C3 chondrites indicated that C2 and C3 chondrites are, respectively, about 1:1 and 1:2-3 mixtures of Cl-like and high temperature materials. More recently, C1 normalized abundances of such volatile elements are nearly constant in most C2-6 chondrites (i.e. 25 non-Antarctic meteorites, nearly all falls, and 36 Antarctic finds) consistent with a 2- component mixing model. However, rather than being quantized, mean volatile element contents in each chondrite define a continuum from 0.92-0.14 x Cl for these 61 chondrites. A few carbonaceous chondrites - the first having been the NIPR consortium samples B-7904, Y-82162 and Y-86720 - show an altered pattern: many of the volatile elements in each exhibit the usual constancy of C1-normalized atomic abundances, but modified by further depletion of Cd and other elements like Tl and Bi. These are the most mobile trace elements, i.e. those most readily vaporized and lost from primitive meteorites during week-long heating at greater than or equal to 400 C under low ambient pressures (initially 10 (exp -5) atm H2), simulating metamorphic conditions in a primitive parent body. Similarities between mobile element data for B-7904, Y-82162 and Y-86720 with those for Murchison heated at 500-700 C suggest that these Antarctic C1 and C2-like chondrites were metamorphosed at temperatures like these in the interiors of their parent bodies. Metamorphic temperatures inferred from RNAA data and textural/mineralogic alterations are internally consistent, agreeing with those evident in heated Murchison samples. These 3 chondrites were also heated late in their histories since all have lost cosmogenic 3-He, presumably during close solar approach, and B-7904 and Y-86720 seem also to have lost substantial proportions of radiogenic He-4 and Ar-40, cf. data. Similarities in spectral reflectance data for C-, G-, B- and F- asteroids, for these meteorites and for heated Murchison samples suggest that thermally metamorphosed interior materials in these asteroids were excavated by impacts and re-deposited on them, forming their present surfaces. Establishment of the thermal metamorphic histories of carbonaceouis chondrites, then, is essential to establishing the evolution and present-day nature of C-type and related asteroids.

Lipschutz, M. E.↗

Thermally Mobile Trace Elements in Carbonaceous Chondrites From Cold and Hot Deserts

Some decades ago, Anders and co-workers used RNAA to classify a number of trace elements as being volatile during nebular condensation and accretion into primitive objects based upon their strong depletion in (equilibrated) ordinary chondrites relative to C1 chondrites. Such elements, e.g. Ag, Bi, Cd, Cs, In, Se, Te, Tl, Zn and others, exhibit nearly constant, C1-normalized atomic abundances in C2 (CM2) and in C3 chondrites. They interpreted the near-constancy of these abundances according to a 2-component model in which volatiles were introduced into carbonaceous (and other) chondrites as C1 material which was diluted with differing proportions of high-temperature (i.e. volatile-free) components. In this view, mean volatile element abundances of 0.48 in C2 and 0.24-0.29 x C1 in C3 chondrites indicated that C2 and C3 chondrites are, respectively, about 1:1 and 1:2-3 mixtures of C1-like and high temperature materials. More recently, Xiao and Lipschutz found that C-normalized abundances of such volatile elements are nearly constant in most C2-6 chondrites (i.e. 25 non-Antarctic meteorites, nearly all falls, and 36 Antarctic finds) consistent with a 2-component mixing model. However, rather than being quantized, mean volatile element contents in each chondrite define a continuum from 0.92-0.14 x C1 for these 61 chondrites. A few carbonaceous chondrites, the first having been the NIPR consortium samples B-7904, Y-82162 and Y-86720, show an altered pattern: many of the volatile elements in each exhibit the usual constancy of C1-normalized atomic abundances, but modified by further depletion of Cd and other elements like Tl and Bi. These are the most mobile trace elements, i.e. those most readily vaporized and lost from primitive meteorites during week-long heating at greater than or equal to 400 C under low ambient pressures (initially 10(exp -5) atm H2), simulating metamorphic conditions in a primitive parent body. Similarities between mobile element data for B-7904, Y-82162 and Y-86720 with those for Murchison heated at 500-700 C, suggest that these Antarctic C1 - and C2-like chondrites were metamorphosed at temperatures like these in the interiors of their parent bodies. Metamorphic temperatures inferred from RNAA data and textural/mineralogic alterations are internally consistent, agreeing., with those evident in heated Murchison samples. These 3 chondrites were also heated late in their histories since all have lost cosmogenic He-3, presumably during close solar approach, and B-7904 and Y-86720 seem also to have lost substantial proportions of radiogenic He-4 and Ar-40 cf. data in. Similarities in spectral reflectance data for C-, G-, B- and F- asteroids, for these meteorites and for heated Murchison samples suggest that thermally metamorphosed interior materials in these asteroids were excavated by impacts and re-deposited on them, forming their present surfaces. Establishment of the thermal metamorphic histories of carbonaceous chondrites, then, is essential to establishing the evolution and present-day nature of C-type and related asteroids.

Lipschutz, M. E.↗

Hydra: computer vision for data quality monitoring

Hydra, initially developed for Hall-D in 2019, is a system that utilizes computer vision to perform near real time data quality monitoring. Since then, it has been deployed across all experimental halls at Jefferson Lab, with the CLAS12 collaboration in Hall-B being the first outside of GlueX to fully utilize Hydra. The system comprises back end processes that manage the models, their inferences, and the data flow. Finally, the front-end components, accessible via web pages, allow detector experts and shift crews to view and interact with the system.

47 OTHER INSTRUMENTATION↗

Laser-Plasma Spectroscopy of Hydroxyl with Applications

This article discusses laser-induced laboratory-air plasma measurements and analysis of hydroxyl (OH) ultraviolet spectra. The computations of the OH spectra utilize line strength data that were developed previously and that are now communicated for the first time. The line strengths have been utilized extensively in interpretation of recorded molecular emission spectra and have been well-tested in laser-induced fluorescence applications for the purpose of temperature inferences from recorded data. Moreover, new experiments with Q-switched laser pulses illustrate occurrence of molecular recombination spectra for time delays of the order of several dozen of microseconds after plasma initiation. The OH signals occur due to the natural humidity in laboratory air. Centrifugal stretching of the Franck-Condon factors and r-centroids are included in the process of determining the line strengths that are communicated as a Supplementary File. Laser spectroscopy applications of detailed OH computations include laser-induced plasma and combustion analyses, to name but two applications. This work also includes literature references that address various diagnosis applications.

47 OTHER INSTRUMENTATION↗

A non-PRE double-peaked burst with oscillations: burning front propagation and stalling

Non-photospheric-radius-expansion (non-PRE) double-peaked bursts may be explained in terms of spreading (and temporary stalling) of thermonuclear flames from a rotational pole on the neutron star surface, as we argued in a previous study. Here we analyze Rossi X-ray Timing Explorer (RXTE) Proportional Counter Array (PCA) data of such a burst from the low mass X-ray binary (LMXB) system 4U 1636-536, and show that our model (with ignition at high latitudes) can qualitatively explain the observed burst profile, and spectral evolution. Moreover, the evolution of the source radius inferred from the data shows a strong signature of temporary stalling of the burning front, which is an essential ingredient of our model. This implies that an understanding of thermonuclear flame spreading on neutron stars can be achieved by a simultaneous study of the evolution of intensity and spectrum of these bursts. We also report the discovery of millisecond period brightness oscillations from this burst, which is the first such observation from a non-PRE double-peaked burst. Our model can explain the corresponding oscillation amplitude during the first (weaker) peak, and the absence of oscillations during the second peak. We discuss how observations of oscillations during non-PRE double-peaked bursts provide an additional t 001 for understanding thermonuclear flame spreading successfully.

Bhattacharyya, Sudip↗

The natural thermoluminescence of meteorites. IV - Ordinary chondrites at the Lewis Cliff ice field

Results of natural thermoluminescence (TL) measurements of 302 meteorites from the vicinity of the Lewis Cliff in the Beardmore region of Antarctica are presented in order to identify fragments of a single fall and to elucidate ice sheet movements and the mechanisms by which meteorite concentration occurs at this site. From the distribution of meteorites on the ice, the shape of the fields of 'paired' meteorites, and trends in the natural TL data, it is inferred that there is a western component to the movement of the ice at this location, as well as the previously supposed movement to the north. The western vector explains the concentration of meteorites along the western edge of the ice tongue. These new natural TL data identify several recent falls and several meteorites which probably had unusually small perihelia immediately prior to capture by the earth.

Benoit, Paul H.↗

A Representation Fusion Framework for Decoupling Diagnostic Information in Multimodal Learning

Modern medicine increasingly relies on multimodal data, ranging from clinical notes to imaging and genomics, to guide diagnosis and treatment. However, integrating these heterogeneous data sources in a principled and interpretable manner remains a major challenge. We present MODES (Multi-mOdal Disentangled Embedding Space), a representation fusion framework that explicitly separates shared and modality-specific factors of variation, offering a structured latent space for multimodal information that improves both prediction and interpretability. By leveraging pre-trained unimodal foundation models, MODES mitigates the dependency on extensive paired datasets, crucial in data-scarce clinical settings. We introduce a masking strategy that optimizes representation dimensionality by eliminating low-information dimensions, to achieve compact, information-rich representations. Our framework demonstrates superior performance in predicting diagnoses and phenotypes compared to unimodal and conventional fusion models. MODES also enables robust diagnostic inference in missing data scenarios, offering an opportunity toward interpretable and efficient multimodal diagnostics in personalized healthcare.

60 APPLIED LIFE SCIENCES↗

Ensemble variational Fokker-Planck methods for data assimilation

Particle flow filters solve Bayesian inference problems by smoothly transforming a set of particles into samples from the posterior distribution. Particles move in state space under the flow of an McKean-Vlasov-Itˆo process. This work introduces the Variational Fokker-Planck (VFP) framework for data assimilation, a general approach that includes previously known particle flow filters as special cases. The McKean-Vlasov-Itˆo process that transforms particles is defined via an optimal drift that depends on the selected diffusion term. It is established that the underlying probability density - sampled by the ensemble of particles - converges to the Bayesian posterior probability density. For a finite number of particles the optimal drift contains a regularization term that nudges particles toward becoming independent random variables. Based on this analysis, we derive computationally-feasible approximate regularization approaches that penalize the mutual information between pairs of particles, and avoid particle collapse. Moreover, the diffusion plays a role akin to a particle rejuvenation approach that aims to alleviate particle collapse. The VFP framework is very flexible. Different assumptions on prior and intermediate probability distributions can be used to implement the optimal drift, and localization and covariance shrinkage can be applied to alleviate the curse of dimensionality. A robust implicit-explicit method is discussed for the efficient integration of stiff McKean- Vlasov-Itˆo processes. Here, the effectiveness of the VFP framework is demonstrated on three progressively more challenging test problems, namely the Lorenz ’63, Lorenz ’96 and the quasi-geostrophic equations.

97 MATHEMATICS AND COMPUTING↗

TMI Rain Rate Estimation Over Land and Ocean Utilizing Convective and Stratiform Discrimination

Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) radiometer brightness temperature data in the 85 GHz channel (T85) reveal distinct local minima in a regional map containing a Mesoscale Convective System (MCS). This is because of relatively small footprint size (approximately 5.5 km) and strong extinction properties in this channel of the TMI. A map of rain rate for that region, deduced from simultaneous measurements made by the Precipitation Radar (PR) on board the TRMM satellite, reveals that these T85 minima, produced by scattering, correspond to local PR rain maxima. Utilizing the PR rain rate map as a guide, we infer from TMI data the presence of three different kinds of thunderstorms or Cbs. They are young, mature, and decaying Cbs that have a scale of about 20 km on the average. Two parameters enable us to infer these three kinds of Cbs objectively: a) the magnitude of scattering depression deduced from local T85 minima and b) the mean horizontal gradient of T85 around such minima. Knowing the category of a given Cb, we can estimate the rain rate associated with it. Such estimation is done with the help of relationships linking T85 minimum to rain rate in each Cb type. Similarly, a weak background rain rate in all the areas where T85 is less than 260 K is deduced with another relationship linking T85 to rain rate. In our rain retrieval model, this background rain constitutes the stratiform rain where the Cbs are absent. Initially, these relationships are optimized or tuned utilizing the PR and TMI data of a few MCS events. After such tuning, the model is applied to independent MCS cases. The areal distribution of light (1-10 mm/hr), moderate (10-20 mm/hr), and intense (> 20 mm/hr) rain rates are retrieved satisfactorally. Accuracy in the estimates of the light, moderate and intense rain areas and the mean rain rates associated with such areas in these independent MCS cases is on the average about 15%. Taking advantage of this ability of our retrieval method, one could derive the latent heat input into the atmosphere over the 760 km wide swath of the TMI radiometer in the tropics.

Prabhakara, C.↗

The occultation of 28 Sgr by Titan

We present a comprehensive analysis of data obtained during the 1989 July 3 occultation of 28 Sgr by Titan. The data set includes 23 lightcurves from 15 separate stations, spanning wavelengths from 0.36 to 0.89 micron. A detailed model of the structure of Titan's atmosphere in the altitude range 250 to 450 km is developed, giving the distribution of temperature, pressure, haze optical depth, and zonal wind velocity as a function of altitude and latitude. Haze layers detected in Titan's stratosphere are about one scale height higher than inferred from Voyager data, and show a wavelength dependence indicative of particle sizes on the order of 0.1 micron. A marked north-south dichotomy in haze density is observed with a transition to lower density south of about -20 deg latitude. Zonal wind speeds are inferred from global distortions from spherical symmetry and are of the order of 100 m/s with significant increase toward higher latitudes. Titan's high atmosphere shows substantial axial symmetry; the position angle of the symmetry axis is equal to the position angle of Saturn's spin axis to within about 1 deg.

Hubbard, W. B.↗

Dynamics of the 4-day wave in the Southern Hemisphere polar stratosphere

Horizontal wind and temperature data are employed to investigate the dynamics of the 4-day wave in the Southern Hemisphere polar stratosphere. They were derived from synoptic maps of satellite-measured brightness temperatures, which were generated using the fast Fourier synoptic mapping technique of Salby (1982). Circulation statistics from these data are compared to those from the NMC operational stratospheric analyses, demonstrating improvements afforded by detailed treatment of asynoptic sampling effects. The 40-day wave is isolated using temporally filtered data. Several events of wave growth and decay are observed in the upper stratosphere during August 1980. Derived zonal-mean and eddy statistics suggest that the 4-day wave results from an instability of the zonal-mean flow near 55-60S, at and above 1 mb. It is inferred from climatological data that the source of the instability is the 'double-jet' structure in the upper stratosphere and mesosphere.

Randel, William J.↗

Further adoption of conservation tillage can increase maize yields in the western US Corn Belt

Conservation tillage can reduce soil erosion, increase soil health, and decrease labor and fuel input costs. Despite these benefits, potential yield impacts remain an important concern for farmers considering adoption. Previous research suggests that conservation tillage is likely to have the largest yield benefits in more arid conditions, but a lack of field-level analyses across climatic, management and soil conditions limits confidence in such predictions. Satellite imagery provides the opportunity to monitor agricultural lands at sub-field resolution across large spatial scales and wide environmental gradients. Here we investigate the maize yield impacts of conservation tillage in the semi-arid western US Corn Belt, using sub-field resolution datasets on tillage practices and crop yields derived from satellite data spanning four states (Nebraska, Kansas, South Dakota, and North Dakota) between 2008 and 2020. On these datasets, we estimate heterogenous yield outcomes for several thousand maize fields across gradients in climate, soil quality and irrigation status by using a causal forests analysis, an adaptation of the random forests machine-learning algorithm for causal inference on observational data. We find that long-term adoption of conservation tillage increased rainfed maize yields by an average of 9.9% in the region. Impacts on irrigated yields were small and not statistically significant. These results, along with an analysis of variables related to greater than average yield benefits, indicate that improved water infiltration and retention are the primary reasons for conservation tillage benefits. Despite yield benefits, many fields estimated to see increased yields under long term low till have not adopted the practice. Therefore, we identify specific counties likely to benefit most from increased levels of adoption. Our results strengthen the understanding of the impacts of conservation agriculture on crop yields and help define environments and counties most likely to benefit from conservation tillage.

54 ENVIRONMENTAL SCIENCES↗

KG-Hub—building and exchanging biological knowledge graphs

Knowledge graphs (KGs) are a powerful approach for integrating heterogeneous data and making inferences in biology and many other domains, but a coherent solution for constructing, exchanging, and facilitating the downstream use of KGs is lacking. Here we present KG-Hub, a platform that enables standardized construction, exchange, and reuse of KGs. Features include a simple, modular extract–transform–load pattern for producing graphs compliant with Biolink Model (a high-level data model for standardizing biological data), easy integration of any OBO (Open Biological and Biomedical Ontologies) ontology, cached downloads of upstream data sources, versioned and automatically updated builds with stable URLs, web-browsable storage of KG artifacts on cloud infrastructure, and easy reuse of transformed subgraphs across projects. Current KG-Hub projects span use cases including COVID-19 research, drug repurposing, microbial–environmental interactions, and rare disease research. KG-Hub is equipped with tooling to easily analyze and manipulate KGs. KG-Hub is also tightly integrated with graph machine learning (ML) tools which allow automated graph ML, including node embeddings and training of models for link prediction and node classification.

59 BASIC BIOLOGICAL SCIENCES↗

Transport processes in the middle atmosphere: Reflections after MAP

The Middle Atmosphere Program (MAP) has provided a focus for considerable research on atmospherical radiative, chemical, and dynamical processes and the mutual coupling among these processes. In particular, major advances have occurred in the understanding of constituent transport as a result of near-global measurements obtained during MAP from several satellite based instruments (e.g., LIMS, SAMS, SAGE, and SSU among others). Using selected portions of these data, the development is reviewed of progress in understanding transport processes with special emphasis on dynamically active periods. Examples are presented which demonstrate coupling between chemistry and dynamics. In addition to the constituent data, the use is reviewed of Ertel's potential vorticity, inferred from satellite temperature data, as a diagnostic for interpreting transport phenomena. Finally, the use is briefly illustrated of 3-D model simulations, in conjunction with the satellite data, for providing additional insight into fundamental transport mechanisms.

Grose, W. L.↗

Digital Lunar Exploration Sites (DLES) Terrain Crafting

Humans will soon be returning to the surface of the Moon with NASA’s Artemis program. The Artemis program is an international collaboration that will consist of a complex series of space systems and missions to explore the lunar surface and pave the way for the future exploration of Mars. NASA and its partners rely heavily on simulation for lighting and navigation studies as well as training astronauts, flight controllers, and mission support staff. The NASA Exploration Systems Simulations (NExSyS) team in the Simulation and Graphics Branch (ER7) in the Engineering Directorate at NASA’s Johnson Space Center has built up many simulation products to support this effort, one of which is the Digital Lunar Exploration Sites (DLES). DLES is a collection of products used to simulate and render the lunar surface in a digital environment. We discussed and presented an overview of the DLES products at the 2022 IEEE Aerospace Conference in Big Sky, MT with a paper titled "Digital Lunar Exploration Sites". This “DLES Terrain Crafting” paper will expand on the information previously provided in “DLES” paper and dive deeper into the details of the terrain crafting process and the toolsets used to support this task. The best digital data currently available of the lunar surface is provided by the Lunar Reconnaissance Orbiter (LRO). Its Lunar Orbiter Laser Altimeter (LOLA) achieves an impressive resolution of 5m per pixel at the Lunar South Pole (LSP) and can generate datasets covering a large continuous region near the LSP. There are a few additional methods, such as Shape from Shading which can infer higher resolution data (up to 1m per pixel) from the LRO Narrow Angle Camera (NAC) images. However, surface-based simulations require higher-resolution data, and this paper will discuss the process of enhancing the terrain to meet that need. The process begins with capturing statistical data of craters in the regions of interest using images provided by the LRO NAC. This data is then used to scatter artificial features which are not captured in the truth data, resulting in an enhanced DEM with a much higher resolution of 20cm per pixel. Many tools were built up to assist in the creation of these artificial Digital Elevation Models (DEM), which this paper will discuss in detail. DEMs themselves are a very powerful representation of a planetary surface, and many operations and tools can utilize the data they contain. This paper includes a description of the rendering of the lunar surface in a graphics engine, generation of contact patches to simulate tire to ground interaction, and ray tracing utilities to model Line of Sight (LOS) interactions with the terrain. This paper will also explore some new tool sets currently under development which aim to utilize Machine Learning (ML) to assist in the identification of craters from LRO NAC imagery. While this is not a novel idea, the NExSyS team is developing a unique approach which may result in more robust identification of crater characteristics.

Artemis↗

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.

99 - GENERAL AND MISCELLANEOUS↗

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.

99 - GENERAL AND MISCELLANEOUS↗