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This report documents the digitization of figures from LA-10860-MS in order to import the data into the CritView software application. The original figures were created by Los Alamos National Laboratory and the latest revision was released in 1986. All figures were digitized using Engauge Digitizer (ver. 12.1) .
SkyPy is an open-source Python package for simulating the astrophysical sky. It comprises a library of physical and empirical models across a range of observables and a command-line script to run end-to-end simulations. The library provides functions that sample realisations of sources and their associated properties from probability distributions. Simulation pipelines are constructed from these models using a YAML-based configuration syntax, while task scheduling and data dependencies are handled internally and the modular design allows users to interface with external software. SkyPy is developed and maintained by a diverse community of domain experts with a focus on software sustainability and interoperability. By fostering development, it provides a framework for correlated simulations of a range of cosmological probes including galaxy populations, large scale structure, the cosmic microwave background, supernovae and gravitational waves. Version 0.4 implements functions that model various properties of galaxies including luminosity functions, redshift distributions and optical photometry from spectral energy distribution templates. Future releases will provide additional modules, for example, to simulate populations of dark matter halos and model the galaxy-halo connection, making use of existing software packages from the astrophysics community where appropriate.
Many organizations are tasked with the collection and processing of large quantities of data from various measurement devices. Data reported from these sources are often not interoperable with datasets and software used by analysts and other organizations in the same field, introducing barriers for collaboration on large-scale projects. This poses a particular problem for cross-device comparisons and machine learning applications. To address these challenges, the open source Time-Series Data Pipelines (Tsdat) software was developed by a joint collaboration between Pacific Northwest National Laboratory, the National Renewable Energy Laboratory, and Sandia National Laboratories to facilitate collaboration and accelerate advancements in the Marine Energy domain through the development of an open-source ecosystem of tools. This paper will describe the Tsdat software and the data standards within which the framework operates. A beta version of the framework has been released and is currently being used by several projects in marine energy, wind energy, and building energy systems.
High-throughput PCR screening is vital in synthetic biology and metabolic engineering as it allows researchers to rapidly analyze and detect numerous targeted genetic mutation in the genome. Current challenges for high-throughput PCR screening in synthetic biology include efficiently preparing genomic DNA, optimizing protocols for diverse sample types, managing contamination risks, and effectively analyzing the large volumes of data generated while ensuring consistent and accurate results. In this study, we present the development of a High Throughput Genome Releaser (HTGR), an innovative device addressing common challenges in screening PCR. This genome DNA releaser is designed based on a squash method for rapid, cost-effective, and efficient DNA release, optimized for subsequent PCR reactions. After experimenting with various synthetic materials, we selected a plastic that closely replicates the smooth surface and compression properties of microscope slides, ensuring reliable performance. We engineered a device featuring a 96-Well Plate and a shear applicator, operable both manually and automatically, and compatible with standard liquid-handling robot platform. This compatibility enhances ease of use in high-throughput PCR workflows. Additionally, we developed software to support its automatic functions. Our results demonstrated that the specially engineered 96-Well Plate and HTGR can effectively squash fungal spores , which release enough genome DNA for PCR screening. The genome releaser facilitates the preparation of PCR-amplifiable genomic DNA substrate from 96 samples within minutes, eliminates the need for extraction buffers, and is adaptable to a wide range of microorganisms and cells, which could significantly advance biomanufacturing processes.
During the summer and fall of 2021, several functional area drills were held that focused on exercising Consequence Management’s (CM) ability to extract and use data from RadResponder for the purpose of answering intermediate-phase questions presented as technical inject requests for information (RFI) in Sandia National Laboratories (SNL) Consequence Management Operational System (COSMOS) software. The scenario chosen was that of Northern Lights 2016 (NL16) which was a large-scale nuclear power plant (NPP) release exercise in the state of Minnesota. The NL16 data was extracted from the Radiological Assessment and Monitoring System (RAMS) event where it was created and was reformatted for implanting to a new RadResponder event. Next, the beta-version of a laboratory sample data simulator was used to generate more sample data that was injected to the event. Five “mini-drills” were devised with each prompt defined by a data-based need. For each drill, a team of assessment and NARAC scientists worked the problem using the drill prompt and the available data in RadResponder. The teams held a kickoff meeting, had several days to work the problem, and then reported their results as well as observations in a hotwash. Several areas for improvement in both the software and process were identified during the course of these drills. This report will document the process of addressing each RFI and the discovered gaps in both software capability and methodology so that they can be considered for future development and investment by the CM and NIRT programs.
Ongoing design activities at Argonne National Laboratory are requiring a thorough verification of the Argonne Reactor Computation codes be performed. DIF3D is central to this system. The driver for this effort requires the 3D Cartesian, triangular-Z, and hexagonal-Z core geometry options of DIF3D be verified. Previous work identified the DIF3D features required to be verified to support current design activities, features of which are generally applicable to hexagonal-Z fast reactor designs. The scope of this verification effort includes verifying DIF3D’s ability to correctly translate the user’s model in to DIF3D’s preferred format, verifying that options planned for use have the desired effect, and verifying the correctness of the eigenvalue, fixed-source, forward, and adjoint solvers in DIF3D-FD and DIF3D-VARIANT. This manuscript provides the verification tasks and their results with respect to the features needed for current design activities. Since analytic solutions of the neutron diffusion and transport equations are either limited in scope or not possible, multiple tiers of problems unique to each solver and geometry type were implemented. Each of these tiers tests features independent and complementary arguments for why the separate testing of functionalities is acceptable. Finally, this separate testing was also supplemented with a high-level integral check of each the diffusion and transport capabilities and applicable geometries. To accommodate cases which an analytic solution is not feasible, MCNP6.2 was relied upon to provide a higher-order reference solution. This therefore required that the capabilities within MCNP6.2 which were relied upon for this work are also verified in this work. No MCNP discrepancies were noted in this effort. Note that the MCNP6.2 verification included in this work does not stand as a full verification of MCNP6.2, but merely verifies the features used in verifying DIF3D. The verification effort identified no issues that are debilitating or otherwise impactful to design usage of DIF3D, and thus DIF3D version 11.0, release 3012 is considered verified. The types of issues that were identified were predominantly in the areas of: unclear documentation, software bugs which were inconsequential to final results, editing options which were ignored in favor of printing more information than requested, bugs in the outputs of intermediate results, or secondary output binary file information which was not present. While not a bug, this verification report also identified that the algorithm used to evaluate the peak fast flux in a nodal transport solution can be quite unreliable due to the polynomial order used and the location of the peak within the mesh. The authors of the report therefore recommend the usage of the EvaluateFlux software (distributed with ARC) as a more robust alternative.
The goal of this milestone was to help CEED-enabled ECP applications (particularly ExaSMR, MARBL, ExaAM, ExaWind and E3SM) in their preparations for the Aurora and Frontier architectures. This work included collaboration with ECP vendors and porting and optimization of CEED’s benchmarks and miniapps to early access hardware. As part of this milestone, we also made the best bake-off problems and bake-off kernel implementation from Nek, MFEM, libParanumal and the external community available in the latest libCEED release, libCEED-0.7. During the milestone period we also organized, in virtual form, the fourth CEED Annual meeting (CEED4AM) which included representatives from ECP applications, vendors and software technology projects. The specific tasks addressed in this milestone were to: (1) Work with vendors to port and run CEED benchmarks on early access systems for Aurora and Frontier; (2) Make the best BP/BK implementations from Nek, MFEM, libParanumal and external community available in libCEED; (3) Organize the next CEED Annual meeting (CEED4AM); and (4) Optimize CEED applications and miniapps for Aurora and Frontier architectures. The artifacts delivered include the next libCEED release, libCEED-0.7, and a number of developments integrated within applications to improve their GPU performance and capabilities. See the CEED website, http://ceed.exascaleproject.org and the CEED GitHub organization, http://github.com/ceed for more details.
DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features, such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, DP-range correction, DP long range, graphics processing unit support for customized operators, model compression, non-von Neumann molecular dynamics, and improved usability, including documentation, compiled binary packages, graphical user interfaces, and application programming interfaces. This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, this article presents a comprehensive procedure for conducting molecular dynamics as a representative application, benchmarks the accuracy and efficiency of different models, and discusses ongoing developments.
This is Volume 1 of a two-volume document that collects the verification and validation (V&V) works done for the PLTEMP/ANL code during the years of its development and improvement. Volume 1 describes the V&V of sixteen capabilities of the PLTEMP/ANL code that were identified by research reactor analysts as frequently used in their thermal-hydraulic analysis. Volume 2 describes the V&V of developments and improvements since the release of PLTEMP/ANL Version 4.3. Each chapter of the document focuses on verifying or validating a specific part of the software that calculates a specific phenomenon, e.g., channel flow calculation, coolant property calculation, heat transfer calculation, and flow instability calculation. Software verification is performed by comparing the code with hand calculation, Microsoft spreadsheet calculation, Mathematica calculation, or MATLAB calculation. The software validation is done by comparing the code with experimental data or a widely tested code like the RELAP5 code. In addition, some PLTEMP/ANL V&V works that are available in the open literature are simply cited in Volume 1 of the document. PLTEMP/ANL has been used in the safety analysis reports of several US and foreign research reactors licensed and converted from highly enriched uranium fuel to low-enriched uranium fuel. A list of such reactors is given in Volume 1 of the document.
This is Volume 2 of a two-volume document that collects the verification and validation (V&V) works done for the PLTEMP/ANL code during the years of its development and improvement. Volume 1 describes the V&V of sixteen capabilities of the PLTEMP/ANL code that were identified by research reactor analysts as frequently used in their thermal-hydraulic analysis. Volume 2 describes the V&V of developments and improvements since the release of PLTEMP/ANL Version 4.3. Each chapter of the document focuses on verifying or validating a specific part of the software that calculates a particular phenomenon, e.g., channel flow calculation, coolant property calculation, heat transfer calculation, and flow instability calculation. Software verification is performed by comparing the code with a hand calculation, Microsoft spreadsheet calculation, Mathematica calculation, or MATLAB calculation. The software validation is achieved by comparing the code with experimental data or a widely tested code like the RELAP5 code. In addition, some PLTEMP/ANL V&V works that are available in the open literature are simply referenced in Volume 1 of the document. PLTEMP/ANL has been used in safety analysis reports of several US and foreign research reactors licensed and converted from highly enriched uranium fuel to low-enriched uranium fuel. A list of such reactors is given in Volume 1 of the document.
V ORO ++ is a software library written in C++ for computing the Voronoi tessellation, a technique in computational geometry that is widely used for analyzing systems of particles. V ORO ++ was released in 2009 and is based on computing the Voronoi cell for each particle individually. Here, we take advantage of modern computer hardware, and extend the original serial version to allow for multithreaded computation of Voronoi cells via the OpenMP application programming interface. We test the performance of the code, and demonstrate that it can achieve parallel efficiencies greater than 95% in many cases. Further, the multithreaded extension follows standard OpenMP programming paradigms, allowing it to be incorporated into other programs. We provide an example of this using the VoroTop software library, performing a multithreaded Voronoi cell topology analysis of up to 102.4 million particles.
pvlib python is a community-developed, open-source software toolbox for simulating the performance of solar photovoltaic (PV) energy components and systems. It provides reference implementations of over 100 empirical and physics-based models from the peer-reviewed scientific literature, including solar position algorithms, irradiance models, thermal models, and PV electrical models. In addition to individual low-level model implementations, pvlib python provides high-level workflows that chain these models together like building blocks to form complete “weather-to-power” photovoltaic system models. It also provides functions to fetch and import a wide variety of weather datasets useful for PV modeling. pvlib python has been developed since 2013 and follows modern best practices for open-source python software, with comprehensive automated testing, standards-based packaging, and semantic versioning. Its source code is developed openly on GitHub and releases are distributed via the Python Package Index (PyPI) and the conda-forge repository. pvlib python’s source code is made freely available under the permissive BSD-3 license. Here we (the project’s core developers) present an update on pvlib python, describing capability and community development since our 2018 publication (Holmgren, Hansen, & Mikofski, 2018).
Here, we present MESA-Web,a cloud resource with an online interface to the Modules for Experiments in Stellar Astrophysics (MESA) software instrument. MESA-Web allows learners to evolve stellar models without the need to download and install MESA. Since being released in 2015, MESA-Web has delivered over 17,000 calculations to over 2,200 unique learners and currently performs about 11 jobs per day. MESA-Web can be used as an educational tool for stars in the classroom or for scientific investigations. We report on new capabilities of MESA-Web introduced since its 2015 release including learner-supplied nuclear reaction rates, custom stopping conditions, and an expanded selection of input parameters. To foster collaboration we have created a Zenodo MESA-Web community hub, where instructors can openly share examples of using MESA-Web in the classroom. We discuss two examples in the current community hub. The first example is a lesson module on Red Giant Branch stars that includes a suite of exercises designed to fit a range of learners and a Jupyter workbook for additional analysis. The second example is lesson materials for an upper-level Astronomy majors course in Stars and Radiation that includes an assignment verifying some of the expected trends that are presented in a popular stellar physics textbook.
Rule-based modeling is an approach that permits constructing reaction networks based on the specification of rules for molecular interactions and transformations. These rules can encompass details such as the interacting sub-molecular domains and the states and binding status of the involved components. Conceptually, fine-grained spatial information such as locations can also be provided. Through “wildcards” representing component states, entire families of molecule complexes sharing certain properties can be specified as patterns. This can significantly simplify the definition of models involving species with multiple components, multiple states, and multiple compartments. The systems biology markup language (SBML) Level 3 Multi Package Version 1 extends the SBML Level 3 Version 1 core with the “type” concept in the Species and Compartment classes. Therefore, reaction rules may contain species that can be patterns and exist in multiple locations. Multiple software tools such as Simmune and BioNetGen support this standard that thus also becomes a medium for exchanging rule-based models. This document provides the specification for Release 2 of Version 1 of the SBML Level 3 Multi package. No design changes have been made to the description of models between Release 1 and Release 2; changes are restricted to the correction of errata and the addition of clarifications.
We present the NPIPE processing pipeline, which produces calibrated frequency maps in temperature and polarization from data from the Planck Low Frequency Instrument (LFI) and High Frequency Instrument (HFI) using high-performance computers. NPIPE represents a natural evolution of previous Planck analysis efforts, and combines some of the most powerful features of the separate LFI and HFI analysis pipelines. For example, following the LFI 2018 processing procedure, NPIPE uses foreground polarization priors during the calibration stage in order to break scanning-induced degeneracies. Similarly, NPIPE employs the HFI 2018 time-domain processing methodology to correct for bandpass mismatch at all frequencies. In addition, NPIPE introduces several improvements, including, but not limited to: inclusion of the 8% of data collected during repointing manoeuvres; smoothing of the LFI reference load data streams; in-flight estimation of detector polarization parameters; and construction of maximally independent detector-set split maps. For component-separation purposes, important improvements include: maps that retain the CMB Solar dipole, allowing for high-precision relative calibration in higher-level analyses; well-defined single-detector maps, allowing for robust CO extraction; and HFI temperature maps between 217 and 857 GHz that are binned into 0'.9 pixels (Nside = 4096), ensuring that the full angular information in the data is represented in the maps even at the highest Planck resolutions. The net effect of these improvements is lower levels of noise and systematics in both frequency and component maps at essentially all angular scales, as well as notably improved internal consistency between the various frequency channels. Based on the NPIPE maps, we present the first estimate of the Solar dipole determined through component separation across all nine Planck frequencies. The amplitude is (3366.6 ± 2.7) μK, consistent with, albeit slightly higher than, earlier estimates. From the large-scale polarization data, we derive an updated estimate of the optical depth of reionization of τ = 0.051 ± 0.006, which appears robust with respect to data and sky cuts. There are 600 complete signal, noise and systematics simulations of the full-frequency and detector-set maps. As a Planck first, these simulations include full time-domain processing of the beam-convolved CMB anisotropies. The release of NPIPE maps and simulations is accompanied with a complete suite of raw and processed time-ordered data and the software, scripts, auxiliary data, and parameter files needed to improve further on the analysis and to run matching simulations.
We completed all the Milestones and disseminated results at the 2021 Computational Approaches for Cancer Workshop (CAFCW21) at the SuperComputing21 conference. As part of Milestone 1, we developed and implemented a prototype digital twin of metastatic melanoma patients, performed quality checks on the code and released it as open source. The work has directly driven major grant proposals by the team on computational digital twins and supporting software infrastructure, including a successful fellowship application by the PI. Work was lead by Paul Macklin (Contact PI, Indiana University), in collaboration with Ilya Shmulevich (PI, Institute for Systems Biology), Tina Hernandez-Boussard (PI, Stanford Univ.), Jeffrey Bryan (Co-I, University of Missouri), Snigdhansu Chatterjee (Co-I, University of Minnesota), and Mohammad Fallahi-Sichani (Co-I, U. of Virginia). Postdoctoral student Heber L. Rocha (Macklin lab, IU) performed intensive computational work, in collaboration with Senior Research Scientist Boris Aguilar (Shmulevich lab, ISB).
Background Papers on COVID-19 are being published at a high rate and concern many different topics. Innovative tools are needed to aid researchers to find patterns in this vast amount of literature to identify subsets of interest in an automated fashion. Objective We present a new online software resource with a friendly user interface that allows users to query and interact with visual representations of relationships between publications. Methods We publicly released an application called PLATIPUS (Publication Literature Analysis and Text Interaction Platform for User Studies) that allows researchers to interact with literature supplied by COVIDScholar via a visual analytics platform. This tool contains standard filtering capabilities based on authors, journals, high-level categories, and various research-specific details via natural language processing and dozens of customizable visualizations that dynamically update from a researcher’s query. Results PLATIPUS is available online and currently links to over 100,000 publications and is still growing. This application has the potential to transform how COVID-19 researchers use public literature to enable their research. Conclusions The PLATIPUS application provides the end user with a variety of ways to search, filter, and visualize over 100,00 COVID-19 publications.</:p>
Flash-X is a highly composable multiphysics software system that can be used to simulate physical phenomena in several scientific domains. It derives some of its solvers from FLASH, which was first released in 2000. Flash-X has a new framework that relies on abstractions and asynchronous communications for performance portability across a range of increasingly heterogeneous hardware platforms. Flash-X is meant primarily for solving Eulerian formulations of applications with compressible and/or incompressible reactive flows. It also has a built-in, versatile Lagrangian framework that can be used in many different ways, including implementing tracers, particle-in-cell simulations, and immersed boundary methods.