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At least 1,513 records · Page 84

Landscape Environmental Assessment Framework

LEAF Version 2.0 is a framework comprising of three models RUSLE2, WEPS, and AGNPS. The framework can predict row crop, crop residue, and energy crop yields at a sub-field resolutions for various combinations of soil, climate and crop management and residue harvesting practices. It estimates the loss of soil, carbon, and nutrients to the atmosphere, to the groundwater, and to runoff. It also models the overland flow of water and washed-off sediments, nutrients and other chemicals to provide estimates of sediment, nutrient, and chemical loadings to water bodies within a watershed. AGNPS model and wash-off calculations are the new additions to this version of LEAF. Development of LEAF software is supported by DOE's BETO program.

Nair, Shyam↗

Parallel-In-Time For Moving Meshes

With steadily growing computational resources available, scientists must develop e ective ways to utilize the increased resources. High performance, highly parallel software has be- come a standard. However until recent years parallelism has focused primarily on the spatial domain. When solving a space-time partial di erential equation (PDE), this leads to a sequential bottleneck in the temporal dimension, particularly when taking a large number of time steps. The XBraid parallel-in-time library was developed as a practical way to add temporal parallelism to existing se- quential codes with only minor modi cations. In this work, a rezoning-type moving mesh is applied to a di usion problem and formulated in a parallel-in-time framework. Tests and scaling studies are run using XBraid and demonstrate excellent results for the simple model problem considered herein.

97 MATHEMATICS AND COMPUTING↗

Probabilistic Error Bounds for Low-Rank Tensor Decompositions Used in Large-Scale Data Analysis Applications (LDRD Final Report)

This report documents a research project on analyzing low-rank tensor models for data analysis that took place at Sandia National Laboratories from October 2023–September 2025. The focus of this work was to extend theoretical frameworks from statistics and probability theory for use with models for scalar, vector, and matrix data to models with tensor, or general multi-dimensional array, data. Through this work, we have provided a new set of tools for bounding errors on low-rank tensor models of both complete and sampled data. The remainder of this report is organized as follows. In Section 1, we describe the proposed work at the start of the project. Section 2 describes the research advances made as part of the project. Other research contributions in the form of conference presentations and software development is provided in Section 3. Workforce development at Sandia and Florida Atlantic University (via a subcontract on this project) is provided in Section 4.

97 MATHEMATICS AND COMPUTING↗

Agile Acceleration of LLVM Flang Support for Fortran 2018 Parallel Programming

The LLVM Flang compiler ("Flang") is currently Fortran 95 compliant, and the frontend can parse Fortran 2018. However, Flang does not have a comprehensive 2018 test suite and does not fully implement the static semantics of the 2018 standard. We are investigating whether agile software development techniques, such as pair programming and test-driven development (TDD), can help Flang to rapidly progress to Fortran 2018 compliance. Because of the paramount importance of parallelism in high-performance computing, we are focusing on Fortran’s parallel features, commonly denoted “Coarray Fortran.” We are developing what we believe are the first exhaustive, open-source tests for the static semantics of Fortran 2018 parallel features, and contributing them to the LLVM project. A related effort involves writing runtime tests for parallel 2018 features and supporting those tests by developing a new parallel runtime library: the CoArray Fortran Framework of Efficient Interfaces to Network Environments (Caffeine).

Rasmussen, Katherine↗

Landscape Environmental Assessment Framework

LEAF Version 2.0 is a framework comprising of three models RUSLE2, WEPS, and AGNPS. The framework can predict row crop, crop residue, and energy crop yields at a sub-field resolutions for various combinations of soil, climate and crop management and residue harvesting practices. It estimates the loss of soil, carbon, and nutrients to the atmosphere, to the groundwater, and to runoff. It also models the overland flow of water and washed-off sediments, nutrients and other chemicals to provide estimates of sediment, nutrient, and chemical loadings to water bodies within a watershed. AGNPS model and wash-off calculations are the new additions to this version of LEAF. Development of LEAF software is supported by DOE's BETO program.

Nair, Shyam↗

Standardizng Data

To enable the rational design of nanomaterials for improved efficacy and safety, it is critical to understand and exploit the physicochemical properties that drive biological behavior (Morris, 2010). Data mining and computer simulation are essential for deriving information about nanomaterial behavior; however, the datasets needed to support such studies are sparse and stored across a variety of repositories and resources. Schrurs and Lison (2012) have expressed the need for more coherence and structure in the conduct of nanotechnology research. Additionally, the lack of common reporting standards and non-uniformity of information reported have proven to be significant barriers to such data sharing and re-use. The Nanotechnology Working Group (Nano WG), of the US National Institutes of Health National Cancer Informatics Program, has been focused on addressing these barriers. The Nano WG - which includes representatives from over 20 organizations including government agencies, academia, industry, standards organizations, and alliances -has developed ISA-TAB-Nano (Thomas et al, 2013), a general framework for representing and integrating diverse types of data related to the description and characterization of nanomaterials. Recognizing that nanoparticle characterization studies have many of the same challenges as ‘omics-based assays, the Nano WG joined the ISA Commons (Sansone et al., 2012) to leverage lessons learned in ‘omics data sharing. The ISA Commons community brings together 50 collaborators at over 30 scientific organizations around the globe, including regulatory and industrial participants in an increasingly diverse set of life science domains. At the core of the ISA Commons is the ISA metadata tracking framework which forms the basis for the ISA-TAB-Nano extension. The extension of the ISA framework to nanotechnology domain illustrates the power of a synergistic approach that seeks the interoperability of data across multiple research disciplines. To increase adoption, especially in the commercial arena from vendors and manufactures, the ISA-Tab-Nano data-sharing specification has also been submitted for consideration as a standard to the American Society for Testing and Materials (ASTM). Delivering a community-driven specification is only the first phase of the process. To be useful and used, ISA-TAB-Nano must be implemented by tools and databases to assist researchers in reporting their data accordingly, shielding them from unnecessary complexity. Our next step is to extend the open source ISA Software Suite to provide user-oriented tools for the collection, curation, and storage of data compliant with the ISA-TAB-Nano specification. Future work will also focus on the application of the ISA-TAB-Nano format to support emerging standards on minimal information about nanomaterials in biological research (Ostraat et al, 2012; MinChar). ISA-TAB-Nano development is a community-driven effort and we welcome new contributions, collaborations and domain expertise. We invite researchers, software developers, vendors, and other stakeholders to work with us to implement the ISA-Tab-Nano format in their existing systems and research. Likewise, we welcome engagement of regulators, funding agencies, editors, and other policy makers to discuss how this standard can be used to facilitate the sharing and reuse of nanotechnology data across a wide range of disciplines. More information about the ISA-TAB-Nano project can be found online at https://wiki.nci.nih.gov/display/ICR/ISA-TAB-Nano.

informatics↗

Distributed Resources for the Earth System Grid Advanced Management (DREAM)

The DREAM project was funded more than 3 years ago to design and implement a next-generation ESGF (Earth System Grid Federation) architecture which would be suitable for managing and accessing data and services resources on a distributed and scalable environment. In particular, the project intended to focus on the computing and visualization capabilities of the stack, which at the time were rather primitive. At the beginning, the team had the general notion that a better ESGF architecture could be built by modularizing each component, and redefining its interaction with other components by defining and exposing a well defined API. Although this was still the high level principle that guided the work, the DREAM project was able to accomplish its goals by leveraging new practices in IT that started just about 3 or 4 years ago: the advent of containerization technologies (specifically, Docker), the development of frameworks to manage containers at scale (Docker Swarm and Kubernetes), and their application to the commercial Cloud. Thanks to these new technologies, DREAM was able to improve the ESGF architecture (including its computing and visualization services) to a level of deployability and scalability beyond the original expectations. Overall, during its three-year lifespan, DREAM has undertaken innovative research work and prototyping: many of its solutions (the new containerized architecture, the Visus visualization engine, the Solr Cloud based search service) were handed over to the ESGF collaboration, which will make them operational and use them as their future software basis.

42 ENGINEERING↗

Space Propulsion Design and Analysis

This software provides an improved methodology for predicting launcher base pressure and heat loads for RSRM (Reusable Solid Rocket Motor) launchers by accounting for complex anisotropic stress/strains and variable turbulent Prandtl and Schmidt numbers. A "building block" approach to turbulence model development, and validation has been applied for improved missile/launcher base region analysis. Modifications to existing kappa - epsilon turbulence models and application of scalar variance models are incorporated into a RANS-based method for aeropropulsive flow modeling, directly related to base flow methodology. (RANS stands for Reynolds-averaged Navier-Stokes.) The models are applied in a RANS solver framework and can improve analysis of other complex flow fields. The enhanced models provide a more accurate predictive capability for improving the design and analysis of RSRM launcher configuration. The kappa - epsilon model enhancements have been shown to improve the capability for predicting turbulence effects in base blow environments. The scalar variance models have been assessed over a wide range of flow configurations to improve prediction of turbulent scalar mixing.

Sinha, Neeraj↗

Integration of Multifidelity Multidisciplinary Computer Codes for Design and Analysis of Supersonic Aircraft

This paper documents the development of a conceptual level integrated process for design and analysis of efficient and environmentally acceptable supersonic aircraft. To overcome the technical challenges to achieve this goal, a conceptual design capability which provides users with the ability to examine the integrated solution between all disciplines and facilitates the application of multidiscipline design, analysis, and optimization on a scale greater than previously achieved, is needed. The described capability is both an interactive design environment as well as a high powered optimization system with a unique blend of low, mixed and high-fidelity engineering tools combined together in the software integration framework, ModelCenter. The various modules are described and capabilities of the system are demonstrated. The current limitations and proposed future enhancements are also discussed.

Geiselhart, Karl A.↗

Advanced Information Systems Technology (AIST) Overview & Current and Recent Projects

"NASA's Advanced Information Systems Technology (AIST) Program identifies, develops, and supports adoption of software and information systems, as well as novel computer science technologies expected to be needed by the Earth Science Division in the 5-10-year timeframe. Overall, the AIST Program is focusing on advanced technologies and innovative concepts with three main objectives: O1. Enable new observation measurements and new observing systems design and operations through intelligent, timely, dynamic, and coordinated distributed sensing; O2. Enable agile science analyses that fully utilize the large amount of diverse observations using advanced analytic tools, visualizations, and computing environments, and that interact seamlessly with relevant observing systems; O3. Enable the development of integrated Earth Science frameworks that mirror the Earth with state-of-the-art models (Earth system models and others), timely and relevant observations, and analytic tools. This thrust will provide technology for enabling near- and long-term science and policy decisions (""""science decisions"""" including planning for the acquisition of new measurements; the development of new models or science analysis; the integration of Earth observations in novel ways; applications to inform choices, support decisions, and guide actions for societal benefit; etc.). AIST objectives aim at optimizing Earth Science mission return – NOS from an observation point of view and ACF/ESDT from an information analysis and utilization point of view. The assets and data accessed and utilized in these systems may come from NASA and non-NASA sources. "

Earth Science Remote Sensing; Information Systems↗

SimELIT: A Novel GUI-Based Comprehensive Ion Trajectory Simulation Software for Mass Spectrometry

Ion trajectory simulation in mass spectrometry systems from injection to detection is technically challenging but very important for better understanding the ion dynamics in instrument development. Here, in this work, we present SimELIT (Simulator of Eulerian and Lagrangian Ion Trajectories), a novel ion trajectory simulation platform. SimELIT is built upon a suite of multiphysics solvers compiled into OpenFOAM (an open-source numerical solver library particularly used for computational mechanics), with a simple web-based graphical user interface (GUI) allowing users to define the details of OpenFOAM cases and run simulations. SimELIT is a modular program and can provide extensions of physics (e.g., gas flows, electrodynamic fields) and thus enable ion trajectory simulations from the ion source to detector. The current version (SimELIT) provides two numerical solvers for ion trajectory simulations–(1) a Lagrangian particle tracker in vacuum and (2) a Eulerian ion density solver in background gas in the presence of electric fields. Here, we describe the architecture of SimELIT, including its use of Docker and the React Framework, and demonstrate the computation of ion trajectories of multiple m/z values in a static/linear voltage drop in vacuum (across a 1 m long flight tube). Further, the drift motion of ions under 1 Torr pressure conditions in a static background (N 2 ) gas through a 20 V/cm static electric field is shown. The results produced from SimELIT were compared with SIMION and theoretical estimates. In addition, we report the computation of ion trajectories in electrodynamic fields within a planar FAIMS device operating at atmospheric pressure.

97 MATHEMATICS AND COMPUTING↗

SU-G-JeP1-13: Innovative Tracking Detector for Dose Monitoring in Hadron Therapy: Realization and Monte Carlo Simulations

Purpose: Development of strategies to monitor range uncertainties is necessary to improve treatment planning in Charged Particle Therapy (CPT) and fully exploit the advantages of ion beams. Our group developed (within the framework of the INSIDE project funded by the Italian research ministry) and is currently building a compact detector Dose Profiler (DP) able to backtrack charged secondary particles produced in the patient during the irradiation. Furthermore we are studying monitoring strategy exploiting charged secondary emission profiles to control the range of the ion beam. Methods: This contribution reports on the DP detector design and construction status. The detector consists of a charged secondary tracker composed of scintillating fiber layers and a LYSO calorimeter for particles energy measurement.The detector layout has been optimized using the FLUKA Monte Carlo (MC) simulation software. The simulation of a 220 MeV Carbon beam impinging on a PMMA target has been performed to study the detector response, exploiting previous secondary radiation measurements performed by our group. The emission profile of charged secondary particles was reconstructed backtracking the particles to their generation point to benchmark the DP performances. Results: The DP construction status, including the technological details will be presented. The feasibility of range monitoring with DP will be demonstrated by means of MC studies. The correlation of the charged secondary particles emission shape with the position of the Bragg peak (BP) will be shown, as well as the spatial resolution achievable on the BP position estimation (less than 3 mm) in the clinical like conditions. Conclusion: The simulation studies supported the feasibility of an accurate range monitoring technique exploiting the use of charged secondary fragments emitted during the particle therapy treatment. The DP experimental tests are foreseen in 2016, at CNAO particle therapy center in Pavia.

60 APPLIED LIFE SCIENCES↗

A pervasive parallel framework for visualization: final report for FWP 10-014707

We are on the threshold of a transformative change in the basic architecture of highperformance computing. The use of accelerator processors, characterized by large core counts, shared but asymmetrical memory, and heavy thread loading, is quickly becoming the norm in high performance computing. These accelerators represent significant challenges in updating our existing base of software. An intrinsic problem with this transition is a fundamental programming shift from message passing processes to much more fine thread scheduling with memory sharing. Another problem is the lack of stability in accelerator implementation; processor and compiler technology is currently changing rapidly. This report documents the results of our three-year ASCR project to address these challenges. Our project includes the development of the Dax toolkit, which contains the beginnings of new algorithms for a new generation of computers and the underlying infrastructure to rapidly prototype and build further algorithms as necessary.

97 MATHEMATICS AND COMPUTING↗

Constructing a working taxonomy of functional Ada software components for real-time embedded system applications

A major impediment to a systematic attack on Ada software reusability is the lack of an effective taxonomy for software component functions. The scope of all possible applications of Ada software is considered too great to allow the practical development of a working taxonomy. Instead, for the purposes herein, the scope of Ada software application is limited to device and subsystem control in real-time embedded systems. A functional approach is taken in constructing the taxonomy tree for identified Ada domain. The use of modular software functions as a starting point fits well with the object oriented programming philosophy of Ada. Examples of the types of functions represented within the working taxonomy are real time kernels, interrupt service routines, synchronization and message passing, data conversion, digital filtering and signal conditioning, and device control. The constructed taxonomy is proposed as a framework from which a need analysis can be performed to reveal voids in current Ada real-time embedded programming efforts for Space Station.

Wallace, Robert↗

Success Path Method: Introduction to the Success Path Method Software Tool©

As part of its commitment to advancing safety and reliability assessment methodologies, Argonne National Laboratory pioneered the use of an evaluation method called the Success Path Method (SPM) to improve risk management for offshore oil and gas operations. The development of the SPM at Argonne has been driven by the need to improve existing risk assessment methodologies by focusing on the steps necessary for success rather than failure modes alone. This is particularly important for industrial environments like offshore facilities that perform multiple functions under a continuously evolving set of operational conditions – such as water depth and temperature, currents, and weather conditions. In these dynamic environments, the traditional Probabilistic Risk Assessment (PRA) approach is far too complex as it focuses on what can go wrong – which comprises an infinite failure space that must be fully explored and understood. By shifting the focus to a finite space of success paths, the SPM enables operators and decision makers to prioritize a manageable number of steps that must go right to ensure success. Building on its five decades of experience in safety assessments for the nuclear industry, Argonne made major adaptations to existing risk assessment methods utilizing features similar to fault trees that are traditionally used in PRA to map all pathways in which the system can malfunction. In contrast, SPM identifies the components and processes that must function correctly to achieve specific outcomes – such as preventing the uncontrolled release of hydrocarbons during drilling operations. The SPM framework integrates equipment, procedures, software, processes, and human actions to ensure that physical barriers meet critical safety functions in dynamic operational conditions. This approach helps identify failure modes and improve operational risk management by narrowing the focus to key success elements, which in turn reduces uncertainty and helps users understand, manage, and respond to failures.

97 MATHEMATICS AND COMPUTING↗

ExaTN

A challenging scientific problem that will benefit from exascale computing is predictive simulation of two- and three-dimensional quantum many-body Hamiltonians in condensed matter physics, together with the related strong entanglement problems in quantum chemistry and quantum computing. Efficient numerical simulations will require new insights into wavefunction compression algorithms that scale on extremely heterogeneous HPC architectures. To address this need, we propose to develop a scalable math library of parallel multi-linear algebraic numerical primitives for hierarchical tensor compression. Our library will subsequently be used for building an efficient, performance-portable HPC framework for simulating strongly correlated quantum systems. In particular, our will will be the first to deliver a massively parallel implementation of the multiscale entanglement renormalization ansatz (MERA), a hierarchical tensor decomposition quantum scheme capable of expressing local expectation values of strongly entangled higher-dimensional quantum systems efficiently. To address the extreme complexity and high computational cost of such schemes, we will automate their parallel implementation by delivering an integrated software framework, ExaTN (Exascale Tensor Networks), that will process hierarchical tensor representations on exascale HPC systems via an asymchronous task-based programming model. As a specific application, our framework will provide scientists with a capability of simulating strongly entangled quantum systems, thus positioning ORNL as a strategic leader in modeling of strongly correlated materials.

McCaskey, AlexanderJ↗

Physics demonstration and verification of MOOSE framework reactor module meshing capabilities

The recently developed Reactor module in the open-source MOOSE framework includes finite element meshing capabilities for analysis of common reactor geometries. Capabilities in the Reactor module have been employed to generate meshes for physics applications including a sodium-cooled fast reactor core analysis using Griffin, a fast reactor assembly thermal deformation analysis using MOOSE Tensor Mechanics, and a heat-pipe cooled microreactor coupled analysis using Griffin, Bison, and Sockeye. The process to build these meshes using MOOSE's meshing capabilities is described. Physics simulation results using MOOSE-based meshes have been verified to match results which leverage external meshing software such as Cubit or Argonne's Mesh Tools. MOOSE's Reactor module provides significant advantages compared to the use of external meshing tools when analyzing Cartesian and hexagonal reactor lattices using MOOSE-based applications: accessibility to the end user, low barrier to entry for new users, speed of mesh generation, volume preservation of meshed fuel pins, and simplification of analysis workflow when using MOOSE applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

New Developments and Verification of the Fusion Blanket Simulation Capabilities in the MOOSE Framework

This poster contains new developments and updates in the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework related to fusion modeling and simulation, and forms the basis for an on-going effort in modeling whole fusion devices at Idaho National Laboratory using MOOSE. In this work, a slice of the midplane of a proposed ceramic breeder blanket design for the Fusion Nuclear Science Facility is simulated using a combination of neutronics, 1D system level thermal hydraulics for helium, 3D heat conduction, and tritium transport. Previous work focused on the engineering scale full assembly of a blanket sector, but the simulations here form the basis for software quality and verification efforts to increase confidence as the large scale simulations continue. This poster was presented at the Idaho National Laboratory Intern Poster Session 2023.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗