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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17

High accuracy barrier heights, enthalpies, and rate coefficients for chemical reactions

Abstract Quantitative chemical reaction data, including activation energies and reaction rates, are crucial for developing detailed kinetic mechanisms and accurately predicting reaction outcomes. However, such data are often difficult to find, and high-quality datasets are especially rare. Here, we use CCSD(T)-F12a/cc-pVDZ-F12// ω B97X-D3/def2-TZVP to obtain high-quality single point calculations for nearly 22,000 unique stable species and transition states. We report the results from these quantum chemistry calculations and extract the barrier heights and reaction enthalpies to create a kinetics dataset of nearly 12,000 gas-phase reactions. These reactions involve H, C, N, and O, contain up to seven heavy atoms, and have cleaned atom-mapped SMILES. Our higher-accuracy coupled-cluster barrier heights differ significantly (RMSE of ∼5 kcal mol −1 ) relative to those calculated at ω B97X-D3/def2-TZVP. We also report accurate transition state theory rate coefficients $${k}_{\infty }(T)$$ k ∞ ( T ) between 300 K and 2000 K and the corresponding Arrhenius parameters for a subset of rigid reactions. We believe this data will accelerate development of automated and reliable methods for quantitative reaction prediction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Department of Energy – Office of Science: Pacific Northwest Site Office Environmental Monitoring Plan for the DOE-SC PNNL Site

The Pacific Northwest Site Office (PNSO) manages the contract for operations at the U.S. Department of Energy Office of Science (DOE-SC) Pacific Northwest National Laboratory (PNNL) Site in Richland, Washington. Radiological operations at the DOE-SC PNNL Site expanded in 2010 with the completion of facilities at the Physical Sciences Facility. As a result of the expanded radiological work at the site, the Washington State Department of Health (WDOH) has required that offsite environmental surveillance be conducted as part of the PNNL Site Radioactive Air Emissions License. The environmental monitoring and surveillance requirements of various orders, regulations, and guidance documents consider emission levels and subsequent risk of negative human and environmental impacts. This Environmental Monitoring Plan (EMP) describes air surveillance activities at the DOE-SC PNNL Site. The determination of offsite environmental surveillance needs evolved out of a Data Quality Objectives process (Barnett et al. 2010) and Implementation Plan (Snyder et al. 2010). The entire EMP is a compilation of several documents, which include: - the Main Document, this text, (PNNL-20919), - Attachment 1, Sampling and Analysis Plan (SAP) (PNNL-20919-1), - Attachment 2, Data Management Plan (DMP) (PNNL-20919-2), and - Attachment 3, Dose Assessment Guidance (DAG) (PNNL-20919-3). Although the EMP is considered the compilation of these documents, each covers topics that can be updated independently. As a result, each may have different publication dates. Current version dates can be verified with Effluent Management staff. The procedures, forms, and data management activities described herein may change with radiological research projects at the DOE-SC PNNL Site. The scope of this EMP will evolve as needed, during routine reviews or in response to changes in facility operations. This document provides the SAP, DMP, and DAG effective at the time of publication. Updates to this document will be published at the discretion of the Effluent Management group of PNNL.

54 ENVIRONMENTAL SCIENCES↗

ESGF project plan for ramping down development activities and transition the project and data to a new team

This document summarizes the current software development activities carried by the ESGF team with planned delivery dates before the transition of the project to a new team. The work we started on the publishing, search and retrieval, and the backend for indexing and data management that can be deployed using Kubernetes are planned to be delivered within the next three months; however, this assumes that the current team members will continue to work on the project. The activities are listed in Table 1 by priority and in case we lose team members, development of lower priority tasks can be paused and passed to the new team with its current status. Team members can be re-assigned based on their availability and transition work needed. Table 2 below describe activities necessary to help project transition to the new team. Deadlines for these activities are before October 1 st of 2022 or the completion of a successful transition. Support during the transition period assumes that we will have 3 key ESGF members and the ESGF PI supported at the 50% level or less for the duration of the transition. The level of support is an estimate, and it depends on several factors that cannot be decided at this time. The total cost of the proposed work and support activities for fiscal year 2021 is $1,270K with $230K carry over to fiscal year 2022. The cost for the support work listed in Table 2 is the sum of the two rows “HW support” and “project support, maintenance, and transition efforts”, colored blue, in Table1 which adds up to $720K. This cost is included in the $1,270K cost in table 1.

97 MATHEMATICS AND COMPUTING↗

A substrate-induced gating mechanism is conserved among Gram-positive IgA1 metalloproteases

The mucosal adaptive immune response is dependent on the production of IgA antibodies and particularly IgA1, yet opportunistic bacteria have evolved mechanisms to specifically block this response by producing IgA1 proteases (IgA1Ps). Our lab was the first to describe the structures of a metal-dependent IgA1P (metallo-IgA1P) produced from Gram-positive Streptococcus pneumoniae both in the absence and presence of its IgA1 substrate through cryo-EM single particle reconstructions. This prior study revealed an active-site gating mechanism reliant on substrate-induced conformational changes to the enzyme that begged the question of whether such a mechanism is conserved among the wider Gram-positive metallo-IgA1P subfamily of virulence factors. Here, we used cryo-EM to characterize the metallo-IgA1P of a more distantly related family member from Gemella haemolysans, an emerging opportunistic pathogen implicated in meningitis, endocarditis, and more recently bacteremia in the elderly. While the substrate-free structures of these two metallo-IgA1Ps exhibit differences in the relative starting positions of the domain responsible for gating substrate, the enzymes have similar domain orientations when bound to IgA1. Together with biochemical studies that indicate these metallo-IgA1Ps have similar binding affinities and activities, these data indicate that metallo-IgA1P binding requires the specific IgA1 substrate to open the enzymes for access to their active site and thus, largely conform to an “induced fit” model.

59 BASIC BIOLOGICAL SCIENCES↗

Perspectives of active Si photonics devices for data communication and optical sensing

Si photonics has made rapid progress in research and commercialization in the past two decades. While it started with electronic–photonic integration on Si to overcome the interconnect bottleneck in data communications, Si photonics has now greatly expanded into optical sensing, light detection and ranging (LiDAR), optical computing, and microwave/RF photonics applications. From an applied physics point of view, this perspective discusses novel materials and integration schemes of active Si photonics devices for a broad range of applications in data communications, spectrally extended complementary metal–oxide–semiconductor (CMOS) image sensing, as well as 3D imaging for LiDAR systems. We also present a brief outlook of future synergy between Si photonic integrated circuits and Si CMOS image sensors toward ultrahigh capacity optical I/O, ultrafast imaging systems, and ultrahigh sensitivity lab-on-chip molecular biosensing.

electronic band structure↗

Active Flash: Out-of-core Data Analytics on Flash Storage

Next generation science will increasingly come to rely on the ability to perform efficient, on-the-fly analytics of data generated by high-performance computing (HPC) simulations, modeling complex physical phenomena. Scientific computing workflows are stymied by the traditional chaining of simulation and data analysis, creating multiple rounds of redundant reads and writes to the storage system, which grows in cost with the ever-increasing gap between compute and storage speeds in HPC clusters. Recent HPC acquisitions have introduced compute node-local flash storage as a means to alleviate this I/O bottleneck. We propose a novel approach, Active Flash, to expedite data analysis pipelines by migrating to the location of the data, the flash device itself. We argue that Active Flash has the potential to enable true out-of-core data analytics by freeing up both the compute core and the associated main memory. By performing analysis locally, dependence on limited bandwidth to a central storage system is reduced, while allowing this analysis to proceed in parallel with the main application. In addition, offloading work from the host to the more power-efficient controller reduces peak system power usage, which is already in the megawatt range and poses a major barrier to HPC system scalability. We propose an architecture for Active Flash, explore energy and performance trade-offs in moving computation from host to storage, demonstrate the ability of appropriate embedded controllers to perform data analysis and reduction tasks at speeds sufficient for this application, and present a simulation study of Active Flash scheduling policies. These results show the viability of the Active Flash model, and its capability to potentially have a transformative impact on scientific data analysis.

99 GENERAL AND MISCELLANEOUS↗

A COUPLED 2 × 2D BABCOCK–LEIGHTON SOLAR DYNAMO MODEL. I. SURFACE MAGNETIC FLUX EVOLUTION

The need for reliable predictions of the solar activity cycle motivates the development of dynamo models incorporating a representation of surface processes sufficiently detailed to allow assimilation of magnetographic data. In this series of papers we present one such dynamo model, and document its behavior and properties. This first paper focuses on one of the model’s key components, namely surface magnetic flux evolution. Using a genetic algorithm, we obtain best-fit parameters of the transport model by least-squares minimization of the differences between the associated synthetic synoptic magnetogram and real magnetographic data for activity cycle 21. Our fitting procedure also returns Monte Carlo-like error estimates. We show that the range of acceptable surface meridional flow profiles is in good agreement with Doppler measurements, even though the latter are not used in the fitting process. Using a synthetic database of bipolar magnetic region (BMR) emergences reproducing the statistical properties of observed emergences, we also ascertain the sensitivity of global cycle properties, such as the strength of the dipole moment and timing of polarity reversal, to distinct realizations of BMR emergence, and on this basis argue that this stochasticity represents a primary source of uncertainty for predicting solar cycle characteristics.

79 ASTRONOMY AND ASTROPHYSICS↗

Efficient data acquisition and training of collisional-radiative model artificial neural network surrogates through adaptive parameter space sampling

Abstract Effective plasma transport modeling of magnetically confined fusion devices relies on having an accurate understanding of the ion composition and radiative power losses of the plasma. Generally, these quantities can be obtained from solutions of a collisional-radiative (CR) model at each time step within a plasma transport simulation. However, even compact, approximate CR models can be computationally onerous to evaluate, and in-situ evaluation of these models within a larger plasma transport code can lead to a rigid bottleneck. As a way to bypass this bottleneck, we propose deploying artificial neural network (ANN) surrogates to allow rapid evaluation of the necessary plasma quantities. However, one issue with training an accurate ANN surrogate is the reliance on a sufficiently large and representative training and validation data set, which can be time-consuming to generate. In this work we explore a data-driven active learning and training routine to allow autonomous adaptive sampling of the problem parameter space to ensure a sufficiently large and meaningful set of training data is assembled for the network training. As a result, we can demonstrate approximately order-of-magnitude savings in required training data samples to produce an accurate surrogate.

97 MATHEMATICS AND COMPUTING↗

KSR1 is a functional protein kinase capable of serine autophosphorylation and direct phosphorylation of MEK1

The extracellular signal-regulated kinase/mitogen-activated protein kinase (ERK/MAPK) pathway is a highly conserved signaling pathway that regulates diverse cellular processes including differentiation, proliferation, and survival. Kinase suppressor of Ras-1 (KSR1) binds each of the three ERK cascade components to facilitate pathway activation. Even though KSR1 contains a C-terminal kinase domain, evidence supporting the catalytic function of KSR1 remains controversial. In this study, we produced recombinant wild-type or kinase-inactive (D683A/D700A) KSR1 proteins in Escherichia coli to test the hypothesis that KSR1 is a functional protein kinase. Recombinant wild-type KSR1, but not recombinant kinase-inactive KSR1, underwent autophosphorylation on serine residue(s), phosphorylated myelin basic protein (MBP) as a generic substrate, and phosphorylated recombinant kinase-inactive MAPK/ERK kinase-1 (MEK1). Furthermore, FLAG immunoprecipitates from KSR1{sup -/-} colon epithelial cells stably expressing FLAG-tagged wild-type KSR1 (+KSR1), but not vector (+vector) or FLAG-tagged kinase-inactive KSR1 (+D683A/D700A), were able to phosphorylate kinase-inactive MEK1. Since TNF activates the ERK pathway in colon epithelial cells, we tested the biological effects of KSR1 in the survival response downstream of TNF. We found that +vector and +D683A/D700A cells underwent apoptosis when treated with TNF, whereas +KSR1 cells were resistant. However, +KSR1 cells were sensitized to TNF-induced cell loss in the absence of MEK kinase activity. These data provide clear evidence that KSR1 is a functional protein kinase, MEK1 is an in vitro substrate of KSR1, and the catalytic activities of both proteins are required for eliciting cell survival responses downstream of TNF.

60 APPLIED LIFE SCIENCES↗

Discovery and Preclinical Characterization of 6-Chloro-5-[4-(1-hydroxycyclobutyl)phenyl]-1 H -indole-3-carboxylic Acid (PF-06409577), a Direct Activator of Adenosine Monophosphate-activated Protein Kinase (AMPK), for the Potential Treatment of Diabetic Nephropathy

Adenosine monophosphate-activated protein kinase (AMPK) is a protein kinase involved in maintaining energy homeostasis within cells. On the basis of human genetic association data, AMPK activators were pursued for the treatment of diabetic nephropathy. Identification of an indazole amide high throughput screening (HTS) hit followed by truncation to its minimal pharmacophore provided an indazole acid lead compound. Optimization of the core and aryl appendage improved oral absorption and culminated in the identification of indole acid, PF-06409577 (7). Compound 7 was advanced to first-in-human trials for the treatment of diabetic nephropathy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Aggregate data‐driven dynamic modeling of active distribution networks with DERs for voltage stability studies

Abstract Electric distribution networks increasingly host distributed energy resources based on power electronic converter (PEC) toward active distribution networks (ADN). Despite advances in computational capabilities, electromagnetic transient models are limited in scalability because of their reliance on exact data about the distribution system and each of its components. Similarly, the use of the DER_A model, which is intended to examine the combined dynamic behavior of many DERs, is limited by the difficulty in parameterization. There is a need for improved dynamic models of DERs for use in large power system simulations for stability analysis. This paper proposes an aggregate model‐free, data‐driven approach for deriving a dynamic partitioned model (DPM) of ADNs. Detailed residential distribution feeders were first developed, including PEC‐based DERs and composite load models (CMLDs), from which the aggregated DPM was derived. The performance was evaluated through various case studies and validated against the detailed ADN model and state‐of‐the‐art DER_A model with CMLD. The data‐driven DPM achieved a of over 90%, accurately representing the aggregated dynamic behavior of ADNs. Furthermore, the DPM significantly accelerated the simulation process with a computational speedup of 68 times compared to the detailed ADN and a 3.5 times speedup compared to the DER_A CMLD model.

42 ENGINEERING↗

UPR/Mayaguez High Energy Physics

This year the University of Puerto Rico at Mayaguez (UPRM) High Energy Physics (HEP) group continued with the ongoing research program outlined in the grant proposal. The program is centered on the Compact Muon Solenoid (CMS) experiment at the proton-proton (pp) collisions at the Large Hadron Collider (LHC) at CERN in Geneva, Switzerland. The main research focus is on data analysis and on the preparation for the High Luminosity (HL) LHC or experiment detector upgrade. The physics data analysis included Higgs Doublet Search and measurement of the (1) Λ 0 b branching fraction, (2) B meson mass, and (3) hyperon θ - b lifetime. The detector upgrade included work on the preparations for the Forward Pixel (FPIX) detector Silicon Sensor Testing in a production run at Fermilab. In addition, the group has taken responsibilities on the Software Release through our former research associate Dr. Eric Brownson who acted until last December as a Level Two Offline Manager for the CMS Upgrade. In support of the CMS data analysis activities carried out locally, the UPRM group has built and maintains an excellent Tier3 analysis center in Mayaguez. This allowed us to analyze large data samples and to continue the development of algorithms for the upgrade tracking robustness we started several years ago, and we plan to resume in the near future. This project involves computer simulation of the radiation damage to be suffered at the higher luminosities of the upgraded LHC. This year we continued to serve as a source of outstanding students for the field of high energy physics. Three of our graduate students finished their MS work in May, 2014, Their theses research were on data analysis of heavy quark b-physics. All of them are currently enrolled at Ph.D. physics program across the nation. One of them (Hector Moreno) at New Mexico University (Hector Moreno), one at University of New Hampshire (Sandra Santiesteban) and one at University of Puerto Rico-Rio Piedras (Carlos Malca). The students H. Moreno and C. Malca has been directly supervised by Dr. Mendez and S. Santiesteban supervised by Dr. Ramirez. During the last 13 years, our group have graduated 23 MS students on experimental High Energy Physics data analysis and applied hardware techniques. Most of the students have been supported by DOE grants, included this grant. Since 2001, Dr. Mendez have directly supervised eleven students, Dr. Ramirez three students and the former PI (Dr. Lopez) nine students. These theses work are fully documented in the group web page (http://charma.uprm.edu). The High Energy Physics group at Mayaguez is small and presently consists of three Physics faculty members, the Senior Investigators Dr. Hector Mendez (Professor) and Dr. Juan Eduardo Ramirez (Professor), and Dr. Sudhir Malik who was just hired in July 2014. Dr. Ramirez is in charge of the UPRM Tier-3 computing and will be building the network bandwidth infrastructure for the campus, while Dr. Mendez will continues his effort in finishing the heavy quark physics data analysis and moving to work on SUSY analysis for the 2015 data. Our last grant application in 2012 was awarded only for 2013-2014. As a result our postdoc position was lost last month of March. Since then, we have hired Dr. Malik as a new faculty in order to reinforce the group and to continue our efforts with the CMS experiment. Our plan is to hire another junior faculty in the next two years to strengthen the HEP group even further. Dr. Mendez continues with QuarkNet activities involving an ever larger group of high school physics teachers from all around Puerto Rico.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Processing data communications events by awakening threads in parallel active messaging interface of a parallel computer

Processing data communications events in a parallel active messaging interface (`PAMI`) of a parallel computer that includes compute nodes that execute a parallel application, with the PAMI including data communications endpoints, and the endpoints are coupled for data communications through the PAMI and through other data communications resources, including determining by an advance function that there are no actionable data communications events pending for its context, placing by the advance function its thread of execution into a wait state, waiting for a subsequent data communications event for the context; responsive to occurrence of a subsequent data communications event for the context, awakening by the thread from the wait state; and processing by the advance function the subsequent data communications event now pending for the context.

97 MATHEMATICS AND COMPUTING↗

Spatial Access Priority Mapping (SAPM) with Fishers: A Quantitative GIS Method for Participatory Planning

Spatial management tools, such as marine spatial planning and marine protected areas, are playing an increasingly important role in attempts to improve marine management and accommodate conflicting needs. Robust data are needed to inform decisions among different planning options, and early inclusion of stakeholder involvement is widely regarded as vital for success. One of the biggest stakeholder groups, and the most likely to be adversely impacted by spatial restrictions is the fishing community. In order to take their priorities into account, planners need to understand spatial variation in their perceived value of the sea. Here, a readily accessible, novel method for quantitatively mapping fishers’ spatial access priorities is presented. Spatial access priority mapping, or SAPM, uses only basic functions of standard spreadsheet and GIS software. Unlike the use of remote-sensing data, SAPM actively engages fishers in participatory mapping, documenting rather than inferring their priorities. By so doing, SAPM also facilitates the gathering of other useful data, such as local ecological knowledge. The method was tested and validated in Northern Ireland, where over 100 fishers participated in a semi-structured questionnaire and mapping exercise. The response rate was excellent, 97%, demonstrating fishers’ willingness to be involved. The resultant maps are easily accessible and instantly informative, providing a very clear visual indication of which areas are most important for the fishers. The maps also provide quantitative data, which can be used to analyse the relative impact of different management options on the fishing industry and can be incorporated into planning software, such as MARXAN, to ensure that conservation goals can be met at minimum negative impact to the industry. This research shows how spatial access priority mapping can facilitate the early engagement of fishers and the ready incorporation of their priorities into the decision-making process in a transparent, quantitative way.

54 ENVIRONMENTAL SCIENCES↗

FY25 Report on Water NSTF Testing: Parametric and Accident Testing with Lower Tank Inlet

The Natural Convection Shutdown Heat Removal Test Facility (NSTF) at Argonne National Laboratory has continued to generate empirical validation data on the performance of water-based reactor cavity cooling system (RCCS) for seven years. This data is actively being used to support the development of passive decay heat removal systems for advanced reactors. Distinguishing this facility are 1) the large, ½ scale of the facility and 2) its governance under an NQA-1 qualified program for producing data of the highest pedigree for advanced reactor designers and regulators. In addition to the experimental activities discussed in this report, a computational modeling program continues to support the experimental program and further accuracy and understanding of the computational models. Together, the experimental and computational work create a mutually beneficial relationship integral to the overall program objective of advancing the understanding of the RCCS technology.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Delegated Regressor, A Robust Approach for Automated Anomaly Detection in the Soil Radon Time Series Data

We propose a new method based on the idea of delegating regressors for predicting the soil radon gas concentration (SRGC) and anomalies in radon or any other time series data. The proposed method is compared to different traditional boosting e.g., Extreme Gradient Boosting (EGB) and simple regression methods e.g., support vector regressors with linear kernel and radial kernel in terms of accurate predictions. R language has been used for the statistical analysis of radon time series (RTS) data. The results obtained show that the proposed methodology predicts SRGC more accurately when compared to different traditional boosting and regression methods. The best correlation is found between the actual and predicted radon concentration for window size of 2 i.e., two days before and after the start of seismic activities. RTS data was collected from 05 February 2017 to 16 February 2018, including 7 seismic events recorded during the study period. Findings of study show that the proposed methodology predicts the SRGC with more precision, for all the window sizes, by overlapping predicted with the actual radon time series concentrations.

54 ENVIRONMENTAL SCIENCES↗

Developing a New Model to Estimate the Costs to Decommission DOE's Active Facilities - 16368

The Active Facilities Data Collection System (AFDCS) is a major means the U.S. Department of Energy (DOE or Department) uses to estimate its out-year environmental liability for the active and surplus facilities across the Department. The previous AFDCS cost model was based on cost assumptions that date back to the mid-1990s. The model is being replaced with a model that reflects more recent facility disposition experience and costs. DOE's Office of Environmental Management's (DOE-EM) historical cost collection database provides the basis for the new AFDCS cost model. This paper describes the process that was used to update the AFDCS facility data inputs, analyze this data, and formulate historical costs and parameters. This process created a robust and reliable cost model that will provide DOE with a valid estimate of the facilities' disposition costs. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗