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At least 163 records · Page 9

DeCOIL: Optimization of Degenerate Codon Libraries for Machine Learning-Assisted Protein Engineering

With advances in machine learning (ML)-assisted protein engineering, models based on data, biophysics, and natural evolution are being used to propose informed libraries of protein variants to explore. Synthesizing these libraries for experimental screens is a major bottleneck, as the cost of obtaining large numbers of exact gene sequences is often prohibitive. Degenerate codon (DC) libraries are a cost-effective alternative for generating combinatorial mutagenesis libraries where mutations are targeted to a handful of amino acid sites. However, existing computational methods to optimize DC libraries to include desired protein variants are not well suited to design libraries for ML-assisted protein engineering. To address these drawbacks, we present DEgenerate Codon Optimization for Informed Libraries (DeCOIL), a generalized method which directly optimizes DC libraries to be useful for protein engineering: to sample protein variants that are likely to have both high fitness and high diversity in the sequence search space. Using computational simulations and wet-lab experiments, we demonstrate that DeCOIL is effective across two specific case studies, with potential to be applied to many other use cases. DeCOIL offers several advantages over existing methods, as it is direct, easy-to-use, generalizable, and scalable. With accompanying software, DeCOIL can be readily implemented to generate desired informed libraries.

59 BASIC BIOLOGICAL SCIENCES↗

User Role Identification in Software Vulnerability Discussions over Social Networks

Understanding and early awareness of software vulnerabilities is vital for preventing and mitigating potential impacts from cybersecurity events. One step toward early characterization of software vulnerabilities may involve analyzing discussion and spread of information in online social networks. Prior work has used information from such discussions over multiple online forums to develop dynamic networks among users followed by analysis of structure, spread, and information evolution. In this work, we advance the state-of-the-art by focusing on data-driven learning of types, roles, and transition of roles exhibited by users over time. In social networks, users take on particular roles based on their actions and structure of the network. Identifying “meaningful” roles can help separate potential users of interest from the larger community, and identify patterns in a network. We will identify and compare roles found in online forums (e.g., Twitter) using techniques such as feature-based Non-negative Matrix Factorization coupled with topological and influence-based measures of centrality. Since users’ activities change over time, we also analyze role evolution in dynamic networks.

Jones, Rebecca D.↗

Astrometric Calibration and Performance of the Dark Energy Spectroscopic Instrument Focal Plane

Abstract The Dark Energy Spectroscopic Instrument, consisting of 5020 robotic fiber positioners and associated systems on the Mayall telescope at Kitt Peak, Arizona, is carrying out a survey to measure the spectra of 40 million galaxies and quasars and produce the largest 3D map of the universe to date. The primary science goal is to use baryon acoustic oscillations to measure the expansion history of the universe and the time evolution of dark energy. A key function of the online control system is to position each fiber on a particular target in the focal plane with an accuracy of 11 μ m rms 2D. This paper describes the set of software programs used to perform this function along with the methods used to validate their performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Development of an Efficient Approach to Perform Neutronics Simulations for Plutonium-238 Production

Conversion of 238Pu decay heat into usable electricity is imperative to power National Aeronautics and Space Administration (NASA) deep space exploration missions; however, the current stockpile of 238Pu is diminishing and the quality is less than ideal. In response, the US Department of Energy and NASA have undertaken a program to reestablish a domestic 238Pu production program and a technology demonstration sub-project has been initiated. Neutronics simulations for 238Pu production play a vital role in this project because the results guide reactor safety-basis, target design and optimization, and post-irradiation examination activities. A new, efficient neutronics simulation tool written in Python was developed to evaluate, with the highest fidelity possible with approved tools, the time-dependent nuclide evolution and heat deposition rates in 238Pu production targets irradiated in the High Flux Isotope Reactor (HFIR). The Python Activation and Heat Deposition Script (PAHDS) was developed specifically for experiment analysis in HFIR and couples the MCNP5 and SCALE 6.1.3 software quality assured tools to take advantage of an existing high-fidelity MCNP HFIR model, the most up-to-date ORIGEN code, and the most up-to-date nuclear data. Three cycle simulations were performed with PAHDS implementing ENDF/B-VII.0, ENDF/B-VII.1, and the Hybrid Library GPD-Rev0 cross-section libraries. The 238Pu production results were benchmarked against VESTA-obtained results and the impact of various cross-section libraries on the calculated metrics were assessed.

depletion↗

Radio Frequency Sensor: Very High Frequency Radio Frequency Lightning Detection in Geostationary Orbit

Abstract The Radio Frequency Sensor (RFS), a new radio frequency lightning detector, was launched into geosynchronous orbit in December 2021, and first collected data in January 2022. RFS is a specialized software‐defined radio receiver that detects, records, and reports impulsive broadband radio‐frequency (RF) signatures from lightning in the very high frequency (VHF; 30–300 MHz) range. Its vantage point from a Western hemisphere geosynchronous orbit provides unique opportunities to study evolution of RF lightning signatures over the durations of thunderstorms over the Americas and Pacific Ocean. Its overlapping view with the Geostationary Lightning Mappers (GOES‐16 & 17) enables additional comparisons between the sources of optical emissions and associated VHF emissions that were not possible with previous sensors. We find that RFS preferentially detects bright VHF signals called transionospheric pulse pairs (trans‐ionospheric pulse pairs (TIPPs)). It is estimated that more than 85% of the RFS‐detected lightning events are TIPPs. This paper presents initial results from the first year and a half of on‐orbit operation.

54 ENVIRONMENTAL SCIENCES↗

A software package for plasma facing component analysis and design: the Heat flux Engineering Analysis Toolkit (HEAT)

The engineering limits of plasma facing components (PFCs) constrain the allowable operational space of tokamaks. Poorly managed heat fluxes that push the PFCs beyond their limits not only degrade core plasma performance via elevated impurities, but can also result in PFC failure due to thermal stresses or melting. Simple axisymmetric assumptions fail to capture the complex interaction between 3D PFC geometry and 2D or 3D plasmas. This results in fusion systems that must either operate with increased risk or reduce PFC loads, potentially through lower core plasma performance, to maintain a nominal safety factor. High precision 3D heat flux predictions are necessary to accurately ascertain the state of a PFC given the evolution of the magnetic equilibrium. A new code, the Heat flux Engineering Analysis Toolkit (HEAT), has been developed to provide high precision 3D predictions and analysis for PFCs. HEAT couples many otherwise disparate computational tools together into a single open source python package. Magnetic equilibrium, engineering CAD, finite volume solvers, scrape off layer plasma physics, visualization, high performace computing, and more, are connected in a single web-based user interface. Linux users may use HEAT without any software prerequisites via an appImage. This manuscript introduces HEAT, discusses the software architecture, presents first HEAT results, and outlines physics modules in development.

divertor physics↗

Capability in Theory, Modeling, and Validation for a Range of Innovative Fusion Concepts using High-Fidelity Moment-Kinetic Models

A computational modeling capability is created and available to the fusion community to understand and design lower-cost and innovative fusion concepts. The approach uses high- fidelity kinetic, moment-kinetic, and moment models and includes sophisticated plasma- boundary interactions. A majority of fusion-relevant simulations are performed with magnetohydrodynamic models and hybrid particle-in-cell codes, with limited-fidelity electron and kinetic physics. However, in fusion configurations like Z-pinches, field-reversed- configurations, plasma jet magneto-inertial fusion, spinning mirrors, and others, kinetic effects (both electron and ions) are critical to understand the physics and design scaling into the highly kinetic regime of a burning fusion plasma. Furthermore, as present fusion machines move towards a burning plasma regime, liquid-metal blankets are needed to handle first-wall heat- flux, reduce erosion, and eventually for energy conversion and fuel breeding. The work performed under this ARPA-E BETHE Capability Team advances the state-of-the-art in modeling and understanding plasma dynamics in fusion devices and its coupling with liquid-metal dynamics. These are critical areas of research for fusion energy to become realizable. To address these complex problems, we have leveraged and extended computational capabilities through the code, Gkeyll (developed jointly with Princeton Plasma Physics Laboratory and academic partners), for kinetic and moment modeling of fusion plasmas. The Concept Teams supported by this Capability Team include the Wisconsin High-field Axisymmetric Mirror (WHAM), Centrifugal Mirror Experiment (CFME), Plasma-Jet Magneto- Inertial Fusion (PJMIF), and solid and liquid wall plasma-material interaction studies relevant to a number of fusion concepts including Zap Energy’s Z-pinch. This software is open-source and available to the fusion community as a high-fidelity tool for the design of lower-cost fusion experiments. 3D gyrokinetic simulations of WHAM are now possible for long enough time scales to understand the evolution of interchange instabilities. 3D multi-fluid simulations of CMFE at higher Mach numbers are now possible for detailed design iterations with the goal of stability. The state-of-the-art in understanding shock formation and shock mitigation regimes in merging liners for PJMIF have been furthered by our kinetic simulations. Our novel models and frameworks studying plasma-material interaction by incorporating wall emission for various solid wall materials of relevance to pulsed and steady fusion concepts have advanced the state-of-the-art in our understanding of particle fluxes, heat fluxes, and other quantities at cathodes and anodes. The results from this work may explain discrepancies between experimental and theoretical predictions of achieved current densities in pulsed concepts such as Z-pinches. Another significant contribution of this Capability Team is the development and deployment of a novel experimental platform, LEX (Liquid Electrode eXperiment), at Virginia Tech to understand liquid metal free-surface response to electromagnetic pulses. The novel experiments along with model validation quantified the effect of different materials and sizes of liquid metal droplets on the radiative power balance of fusion plasmas for pulsed concepts. Furthermore, these experiments provided mitigation strategies for violent liquid metal response for high current pulses as would be expected in fusion regimes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

PSI/J: A Portable Interface for Submitting, Monitoring, and Managing Jobs

It is generally desirable for high-performance computing (HPC) applications to be portable between HPC systems, for example to make use of more performant hardware, make effective use of allocations, and to co-locate compute jobs with large datasets. Unfortunately, moving scientific applications between HPC systems is challenging for various reasons, most notably that HPC systems have different HPC schedulers. We introduce PSI/J, a job management abstraction API intended to simplify the construction of software components and applications that are portable over various HPC scheduler implementations. We argue that such a system is both necessary and that no viable alternative currently exists. We analyze similar notable APIs and attempt to determine the factors that influenced their evolution and adoption by the HPC community. We base the design of PSI/J on that analysis. We describe how PSI/J has been integrated in three workflow systems and one application, and also show via experiments that PSI/J imposes minimal overhead.

Hategan, Mihael↗

Π4U: A high performance computing framework for Bayesian uncertainty quantification of complex models

We present Π4U,{sup 1} an extensible framework, for non-intrusive Bayesian Uncertainty Quantification and Propagation (UQ+P) of complex and computationally demanding physical models, that can exploit massively parallel computer architectures. The framework incorporates Laplace asymptotic approximations as well as stochastic algorithms, along with distributed numerical differentiation and task-based parallelism for heterogeneous clusters. Sampling is based on the Transitional Markov Chain Monte Carlo (TMCMC) algorithm and its variants. The optimization tasks associated with the asymptotic approximations are treated via the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). A modified subset simulation method is used for posterior reliability measurements of rare events. The framework accommodates scheduling of multiple physical model evaluations based on an adaptive load balancing library and shows excellent scalability. In addition to the software framework, we also provide guidelines as to the applicability and efficiency of Bayesian tools when applied to computationally demanding physical models. Theoretical and computational developments are demonstrated with applications drawn from molecular dynamics, structural dynamics and granular flow.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Computer Programs For Analysis Of Thermally Reactive Tracer Tests In Geothermal Reservoirs

The Tracer Analysis Toolbox (TAT) is a stand-alone executable software package that focuses on reservoir monitoring, using changes in concentration of thermally degrading tracers between and injection well and a production well to reflect the temperature-time histories along flow paths through the reservoir. By conducting such tests periodically, the thermal evolution of the flow paths connecting injection wells to production wells can be monitored. Because this approach is sensitive to temperature along the whole path, it can detect changes well before they occur at the distal end of the path (i.e., the production well). Thus, the thermally degrading tracer method provides early detection of thermal decline before it impacts that well. The goal of TAT is to simplify planning of a reactive tracer monitoring campaign and interpretation of results by providing: (1) tracer test planning and analysis tools to define the necessary kinetic parameters, injection concentrations, and other tracer parameters that are suitable for the expected reservoir residence time and temperature, (2) identification of tracers with suitable characteristics (defined by (1)) and (3) a suite of analysis programs to analyze tracer test results.

Plummer, MitchellAaron [Idaho National Laboratory ↗

Real-Time Automated Pathogen Identification by Enhanced Ribotyping (RAPIER) LDRD Final Report

Funded through the IHNS/E&HS investment area for FY16-18, the RAPIER LDRD sought to evaluate the potential benefits and applicability of the new Oxford MinION nanopore sequencer to pathogen diagnostic applications in biodefense, biosurveillance, and global/public health. The project had four primary objectives: 1) to investigate the performance of the MinION sequencer while building facility with its operation, 2) to develop microfluidic library prep automation facilitating the use of the MinION in field-forward or point-of-care applications, 3) to leverage CRISPR/Cas9 technology to enable targeted identification of bacterial pathogens, and 4) to capitalize on the real- time data output capabilities of the MinION to enable rapid sequence-based diagnostics. While the rapid evolution of the MinION sequencing technology during the course of the project posed a number of challenges and required a reassessment of initial project priorities, it also provided unique opportunities, notably culminating in our development of the RUBRIC real-time selective sequencing software.

97 MATHEMATICS AND COMPUTING↗

Evolution of standardization and dissemination of cryo-EM structures and data jointly by the community, PDB, and EMDB

Cryogenic electron microscopy (cryo-EM) methods began to be used in the mid-1970s to study thin and periodic arrays of proteins. Following a half-century of development in cryo-specimen preparation, instrumentation, data collection, data processing and modeling software, cryo-EM has become a routine method for solving structures from large biological assemblies to small biomolecules at near to true atomic resolution. This review explores the critical roles played by the Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB) in partnership with the community to develop the necessary infrastructure to archive cryo-EM maps and associated models. Public access to cryo-EM structure data has in turn facilitated better understanding of structure-function relationships and advancement of image processing and modeling tool development. The partnership between the global cryo-EM community and PDB and EMDB leadership has synergistically shaped the standards for metadata, one-stop deposition of maps and models, and validation metrics to assess the quality of cryo-EM structures. The advent of cryo-electron tomography (cryo-ET) for in situ molecular cell structures at a broad resolution range and their correlations with other imaging data introduces new data archival challenges in terms of data size and complexity in the years to come.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

CRADA FINAL REPORT FOR CRADA NO. CR-08-001 CEMENTITIOUS BARRIERS PARTNERSHIPS

The Cementitious Barriers Partnership (CBP), led by the Savannah River National Laboratory, has achieved its ultimate purpose to support progress in final treatment and disposal of legacy waste and closure of High-Level Waste (HLW) tanks in the DOE complex. The CBP achieved its goal by developing experimental programs with results that supported the development of a reasonable and credible set of software tools to improve understanding and prediction of the structural, hydraulic and chemical performance of cementitious barriers and waste forms used in nuclear applications. These experimental data and software tools are and will continue to reduce the uncertainties in the current methodologies for assessing cementitious barrier performance and increase the consistency and transparency of the assessment process. The CBP has made a significant impact in reducing risk and uncertainties in the performance assessments that directly impact U.S. Department of Energy (DOE) environmental cleanup and closure programs. The CBP has developed an experimentally-based, integrated modeling tool that serves as a screening tool known as the CBP Software Toolbox, Version 3.0. The CBP products reduce the uncertainties of current methodologies for assessing cementitious barrier performance and increasing the consistency and transparency of the DOE assessment process. This CBP Software Toolbox predicts the hydraulic properties and chemical stability of cement matrix phases and release fluxes of constituents, in response to variable boundary conditions. Therefore, the CBP tools are reducing the uncertainty by coupling multiscale and multi-physics processes, including physical-chemical evolution and transport phenomena applied to heterogeneous materials with changing boundary conditions. In addition, the CBP Experimental and Characterization Program has provided test data to support chemical and physical degradation mechanisms for cementitious barriers. These tools have application to low activity waste forms, high level waste tank closure, D&D and entombment of major nuclear facilities, landfill waste acceptance criteria, and in-situ grouting and immobilization of vadose zone contamination. The CBP also provided: 1) a forum for DOE-NRC technical exchange, 2) material characterization to support performance assessment (PA) predictions, 3) uncertainty reduction in PA predictions, 4) base case performance to improve PA predictions, and 5) improvement in understanding and quantification of moisture and contaminant transport used in PAs. Additional CBP accomplishments include: sponsorship of a national test bed workshop to obtain collaboration in establishing the path forward to obtain actual data supporting future predictions of cementitious barrier performance, and participation in an International Atomic Energy Agency (IAEA) Cooperative Research Project on the use of cementitious barriers for low-level radioactive waste treatment and disposal.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Abstract for CRADA between National Energy Technology Laboratory and Shell International Exploration & Production, Inc

Introducing CO₂ into geothermal systems as a working fluid in reservoirs can enhance geothermal conductivity, production, and pressure maintenance. A cross-disciplinary interaction of geothermal reservoir stimulation and CO₂ utilization satisfies renewable energy demands and operations that support sustainable energy infrastructure. Challenges to implementing CO₂-stimulated geothermal enhancement (CS-GE) include (1) accurately characterizing and imaging CO₂-stimulated geothermal reservoirs; (2) quantitatively inferring CS-GE evolution under current and future engineered conditions for cost effective operations; and (3) monitoring resources by improving observational methods to advance the understanding of complex geothermal systems for sweep efficiency and, ultimately, cost effectiveness. NETL and Shell will collaborate under this CRADA to develop software to image key features, including CO₂-stimulated fracture imaging, CO₂ fluid sweep imaging and heat transfer and exchange imaging by leveraging available datasets and applying advanced Artificial Intelligence/Machine Learning (AI/ML), multi-level data analytics and data/information fusion to better understand the comprehensive mechanisms of CO₂-stimulated geothermal systems.

15 GEOTHERMAL ENERGY↗

Recent evolution of risk analyses in atomic bomb survivor studies: new methods and applications

Abstract Several decades ago a dramatic leap forward occurred in the development and application of statistical methods for modeling radiation risk at the Radiation Effects Research Foundation (RERF). Poisson regression analysis for grouped person-year cohort data and the linear excess relative risk model were introduced, and subsequently a devoted software system, Epicure® (https://www.hirosoft.com), was developed by researchers at RERF and at the U.S. National Cancer Institute. Numerous advancements in understanding radiation effects on humans were made possible with these methods, which are still the state-of-the-art for risk assessment at RERF and have remained part of the standard toolbox for radiation—and other environmental—epidemiological studies worldwide. Nevertheless, as our understanding of radiation risk has increased, so have the breadth and depth of questions that require answers based on emerging data that are not amenable to these conventional methods. This overview briefly recounts the conventional methods and then describes our recent diversification into the use or development of new statistical approaches to meet the challenges of burgeoning biological data and emerging mechanistic information. We briefly discuss the development and application of new methods, current and planned, that are part of the RERF Statistics Department’s role in supporting institution-wide research, especially in our collaborations involving the Life Span Study, Adult Health Study, and First-generation Offspring Clinical Study. Some approaches to modeling and assessing radiation risk with newer methods mentioned herein have already been published, while some are still in development or are only beginning at the proposal stage.

Oncology↗

Massively parallel phase-field simulations targeting exascale

The interface thickness in the phase-field (PF) method limits its simulation scales. Consequently, large-scale PF simulations become prohibitively expensive for resolving the extremely fine microstructures that typically form during rapid solidification processing. This challenge is significant in predicting microstructure evolution in metal additive manufacturing and has been identified by the United States Department of Energy’s Exascale Computing Project. Here, to address this, we develop a multi-GPU and MPI-based massively parallel simulation code, utilizing state-of-the-art algorithms, software, and libraries, for large-scale three-dimensional (3D) PF simulations. We report the first GPU-parallel PF simulations on Frontier (currently the second TOP500 exascale cluster) and Summit machines, taking dendritic growth as an example problem. We evaluate the parallel performance of our implementation using scaling studies with more than 24 000 GPUs (among the largest known computations to date) and the acceleration performance using large-scale simulations of dendritic growth in 3D. Finally, massively parallel GPUs in these supercomputers enabled the first coupled multiscale simulations of laser melting and subsequent dendritic solidification on the scale of a full melt-pool, demonstrating the feasibility of performing PF simulations with a point total over 2 billion grid points within an acceptable time.

Exascale↗

HEP Software Foundation Community White Paper Working Group – Visualization

In modern High Energy Physics (HEP) experiments visualization of experimental data has a key role in many activities and tasks across the whole data chain: from detector development to monitoring, from event generation to reconstruction of physics objects, from detector simulation to data analysis, and all the way to outreach and education. In this paper, the definition, status, and evolution of data visualization for HEP experiments will be presented. Suggestions for the upgrade of data visualization tools and techniques in current experiments will be outlined, along with guidelines for future experiments. This paper expands on the summary content published in the HSF \emph{Roadmap} Community White Paper~\cite{HSF-CWP-2017-01}

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

HEP Software Foundation Community White Paper Working Group – Conditions Data

To produce the best physics results, high energy physics experiments require access to calibration and other non-event data during event data processing. These conditions data are typically stored in databases that provide versioning functionality, allowing physicists to make improvements while simultaneously guaranteeing the reproducibility of their results. With the increased complexity of modern experiments, and the evolution of computing models that demand large scale access to conditions data, the solutions for managing this access have evolved over time. In this white paper we give an overview of the conditions data access problem, present convergence on a common solution and present some considerations for the future.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗