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DOE OSTI2015

SU-E-J-253: The Radiomics Toolbox in the Computational Environment for Radiological Research (CERR)

Purpose: To present an open source and free platform to facilitate radiomics research — The “Radiomics toolbox” in CERR. Method: There is scarcity of open source tools that support end-to-end modeling of image features to predict patient outcomes. The “Radiomics toolbox” strives to fill the need for such a software platform. The platform supports (1) import of various kinds of image modalities like CT, PET, MR, SPECT, US. (2) Contouring tools to delineate structures of interest. (3) Extraction and storage of image based features like 1st order statistics, gray-scale co-occurrence and zonesize matrix based texture features and shape features and (4) Statistical Analysis. Statistical analysis of the extracted features is supported with basic functionality that includes univariate correlations, Kaplan-Meir curves and advanced functionality that includes feature reduction and multivariate modeling. The graphical user interface and the data management are performed with Matlab for the ease of development and readability of code and features for wide audience. Open-source software developed with other programming languages is integrated to enhance various components of this toolbox. For example: Java-based DCM4CHE for import of DICOM, R for statistical analysis. Results: The Radiomics toolbox will be distributed as an open source, GNU copyrighted software. The toolbox was prototyped for modeling Oropharyngeal PET dataset at MSKCC. The analysis will be presented in a separate paper. Conclusion: The Radiomics Toolbox provides an extensible platform for extracting and modeling image features. To emphasize new uses of CERR for radiomics and image-based research, we have changed the name from the “Computational Environment for Radiotherapy Research” to the “Computational Environment for Radiological Research”.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

A Common Tracking Software Project

Abstract The reconstruction of the trajectories of charged particles, or track reconstruction, is a key computational challenge for particle and nuclear physics experiments. While the tuning of track reconstruction algorithms can depend strongly on details of the detector geometry, the algorithms currently in use by experiments share many common features. At the same time, the intense environment of the High-Luminosity LHC accelerator and other future experiments is expected to put even greater computational stress on track reconstruction software, motivating the development of more performant algorithms. We present here A Common Tracking Software (ACTS) toolkit, which draws on the experience with track reconstruction algorithms in the ATLAS experiment and presents them in an experiment-independent and framework-independent toolkit. It provides a set of high-level track reconstruction tools which are agnostic to the details of the detection technologies and magnetic field configuration and tested for strict thread-safety to support multi-threaded event processing. We discuss the conceptual design and technical implementation of ACTS, selected applications and performance of ACTS, and the lessons learned.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

PyDynamicWindow v1

This software is developed for researchers to evaluate the energy performance of of dynamic windows in the world-wide climate, and this first version focuses on thermochromic windows. We bring new indicators (necessity level and recommendation index) to the evaluation system for thermochromic windows. We estimate the majority users of this software tool will be non-commercial academic researchers. But commercial companies can also use it to optimize their products and estimate where their product has the most promising market.

Gao, Yuan↗

DOE OSTI2025

RxnRover/CyRxnOpt

CyRxnOpt aims to provide a single software interface to various optimization algorithms, mainly designed for chemical process optimization applications. CyRxnOpt generalizes the optimization process into four high-level “phases”: Installation, Configuration, Training, and Prediction. This allows developers to program to a general interface for each phase of the optimization, simplifying the development of user-friendly tools to lower the barrier of entry into chemical process optimization, especially for automated laboratory workflows which can greatly benefit from access to various optimization techniques. It is also designed so researchers can easily add new or existing algorithms into existing workflows in a user-friendly manner.

Kulathunga, Dulitha Prasanna [Iowa State Universit↗

DOE OSTI2015

Building a Cyberinfrastructure for Environmental System Science: Modeling Frameworks, Data Management, and Scientific Workflows, Workshop Report, Potomac, Maryland, April 30-May 1, 2015

The Environmental System Science (ESS) activity within the Department of Energy’s (DOE) Office of Biological and Environmental Research (BER) seeks to advance a robust, predictive understanding of terrestrial environments, extending from bedrock to the top of the vegetative canopy and from molecular to global scales, through an iterative cycle of model-driven experimentation and observation dubbed MODEX. Considerable progress has been made toward achieving this overarching goal, but widely recognized is the fragmentation across projects and disciplines of the relevant modeling and simulation capabilities, observational and experimental data, analysis algorithms, and workflow tools. This fragmentation creates significant challenges for studying impacts and feedbacks in these complex multiscale systems. These challenges are further exacerbated by ongoing disruptive changes in high-performance computational architectures and the exponential growth in the types and volume of data that render obsolete the conventional approaches to software development and data management. Overcoming these challenges will require the development of a BER Climate and Environmental Sciences Division (CESD)–wide enabling cyberinfrastructure to support data management, cross-domain modeling, data analysis, and collaborative research. To explore the potential for working groups to initiate and guide a more integrated and community-based cyberinfrastructure, BER held the ESS Workshop on Model-Data Integration: Modeling Frameworks, Data Management, and Scientific Workflows on April 30-May 1, 2015, following the ESS Principal Investigator Meeting in Potomac, Maryland. Participants included model developers, software engineers, and data management specialists from eight national laboratories, which represented a wide range of projects and programs from CESD as well as cross-cutting projects from DOE’s Office of Advanced Scientific Computing Research (ASCR; both BER and ASCR are operated from within DOE’s Office of Science). A series of plenary talks provided background information and clarified the workshop’s three objectives: (1) develop requirements for this community-based cyberinfrastructure to ensure enhanced scientific productivity of the community as a whole; (2) identify challenges associated with developing this new cyberinfrastructure using a phased approach guided by project-driven use cases; and, given these requirements and challenges, (3) chart a path forward for ESS working groups to lead the phased development of the new cyberinfrastructure.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

7th Annual Earth System Grid Federation Face-to-Face Conference Report

The Seventh Annual Earth System Grid Federation (ESGF) Face-to-Face (F2F) Conference held December 4–8, 2017, in San Francisco, California, USA, assembled together a collection of independently funded national and international projects comprised of government agencies, institutions, and companies dedicated to the creation, management, analysis, and distribution of extreme-scale scientific data. The purpose of the conference was to discuss sustaining and enhancing the resilient ESGF data infrastructure with friendlier tools for the expanding global scientific community—this year’s emphasis was placed on the preparedness of the Coupled Model Intercomparison Project, phase 6 (CMIP6). It also focused on new tools that fulfill important and strategic capability gaps in scientific data archiving, access, analysis, and knowledge discovery. As the Executive Committee Chair of ESGF, I would like to personally thank each of conference attendees and those who could not attend but contributed to and/or supported the development of the ESGF software stack. It is an exciting time for the ESGF consortium as we continue to grow and adjust, remaining always adaptable, motivated, and responsive to our growing base of community projects. As we move forward, our ESGF organization is confronting and addressing many changes during a time of larger national and international commitment with fewer community resources. That said, our commitment to our sponsors and the community remains strong as we continue to meet the challenges before us and bring inspired developers and the scientific community together through forums like this conference, ensuring our ESGF organization remains robust and at the cutting edge of technology.

58 GEOSCIENCES↗

DOE OSTI2015

Integrated IO Services for Trilinos Data Structures

The Trilinos Project is an effort to develop algorithms and enabling technologies within an object- oriented software framework for the solution of large-scale, complex multi-physics engineering and scientific problems. A unique design feature of Trilinos is its focus on packages. While the abstractions make it easy to incorporate advanced processing and data manipulation tools, it is not always obvious how to take advantage of these features. The trios package incorporated two years ago offers general data management services, but has yet to offer integrated support for core Trilinos data structures, such as those offered in the Tpetra package. An initial attempt to incorporate native Trilinos data structure support into trios services revealed the complexity, from a non-mathematician's perspective, of using Trilinos. This project sought to understand the complexities and potential barriers not just for non-mathematicians that want to contribute to or use Trilinos, but potentially for new mathematically-inclined users as well that may want to offer services to support users. This report documents the challenges for trios to offer some simple data manipulation required as a precursor to any direct data services integration and makes recommendations for clarifying the performance implications and general approach to use.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

MASSIVE HYBRID PARALLELISM FOR FULLY IMPLICIT MULTIPHYSICS

As hardware advances continue to modify the supercomputing landscape, traditional scientific software development practices will become more outdated, ineffective, and inefficient. The process of rewriting/retooling existing software for new architectures is a Sisyphean task, and results in substantial hours of development time, effort, and money. Software libraries which provide an abstraction of the resources provided by such architectures are therefore essential if the computational engineering and science communities are to continue to flourish in this modern computing environment. The Multiphysics Object Oriented Simulation Environment (MOOSE) framework enables complex multiphysics analysis tools to be built rapidly by scientists, engineers, and domain specialists, while also allowing them to both take advantage of current HPC architectures, and efficiently prepare for future supercomputer designs. MOOSE employs a hybrid shared-memory and distributed-memory parallel model and provides a complete and consistent interface for creating multiphysics analysis tools. In this paper, a brief discussion of the mathematical algorithms underlying the framework and the internal object-oriented hybrid parallel design are given. Representative massively parallel results from several applications areas are presented, and a brief discussion of future areas of research for the framework are provided.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

Massive hybrid parallelism for fully implicit multiphysics

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

FENIX: Towards a Fully Integrated Multiphysics Framework for Plasma Facing Component Modeling

Computational tools have a crucial role to play in accelerating the deployment of fusion as a clean, reliable, abundant, and sustainable energy source. Multiphysics, high-fidelity simulation capabilities can help model, study, and predict intricate interactions between materials performance, plasma exposure, neutron irradiation, and engineering processes. As such, they can assist in the resolution of scientific and engineering challenges underpinning design, construction, and commission of fusion power plants. To address these needs, ongoing efforts are leveraging the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework and delivering new computational tools for the fusion community. These tools inherit crucial attributes from MOOSE. They are open-source, modular, integrated with nuclear industry-standard software quality assurance processes, and enable multiphysics, multi-fidelity, fully integrated, zero- to three-dimensional, and massively parallel simulations. After a short overview of these capabilities, we will present the development of Fusion ENergy Integrated multiphys-X (FENIX), a MOOSE-based application designed to enable plasma facing component design and performance evaluation. Throughout their lifetime, plasma facing components are exposed to extreme thermal loads, repeated thermal shocks, and irradiation by plasma ions, neutral particles, and high-energy neutrons. Consequently, designing a plasma facing component with acceptable lifetime degradation is extremely challenging. FENIX aims to model the multiphysics environment in which plasma facing components evolve to accelerate their design studies. To that end, FENIX couples existing MOOSE capabilities such as heat transfer, thermomechanics, and thermal hydraulics, with tritium transport via the MOOSE-based Tritium Migration Analysis Program, Version 8 (TMAP8), with neutronics via the MOOSE-based high-fidelity neutron-photon transport and fluid dynamics code Cardinal, and finally with Particle-in-Cell plasma simulation capabilities being developed in this project. In this study, we present the current FENIX capabilities and preliminary results of its application to model the Tritium Plasma Experiment set up at Idaho National Laboratory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

AMReX: a framework for block-structured adaptive mesh refinement

AMReX is a C++ software framework that supports the development of block-structured adaptive mesh refinement (AMR) algorithms for solving systems of partial differential equations (PDEs) with complex boundary conditions on current and emerging architectures. AMR reduces the computational cost and memory footprint compared to a uniform mesh while preserving the local descriptions of different physical processes in complex multiphysics algorithms. Current AMReX-based application codes span a number of areas, including atmospheric modeling, astrophysics, combustion, cosmology, fluctuating hydrodynamics, multiphase flows, and particle accelerators. In particular, the AMReX-Astro GitHub repository holds a number of astrophysical modeling tools based on AMReX. The origins of AMReX trace back to the BoxLib software framework. AMReX supports a number of different time-stepping strategies and spatial discretizations. Solution strategies supported by AMReX range from level-by-level approaches (with or without subcycling in time) with multilevel synchronization to full-hierarchy approaches, and any combination thereof. User-defined kernels that operate on patches of data can be written in C++ or Fortran; there is also a Fortran-interface functionality which wraps the core C++ data structures and operations in Fortran wrappers so that an application code based on AMReX can be written entirely in Fortran.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

On the memory attribution problem: A solution and case study using MPI

As parallel applications running on large–scale computing systems become increasingly memory constrained, the ability to attribute memory usage to the various components of the application is becoming increasingly important. We present the design and implementation of memnesia, a novel memory usage profiler for parallel and distributed message–passing applications. Our approach captures both application– and message–passing library–specific memory usage statistics from unmodified binaries dynamically linked to a message–passing communication library. Using microbenchmarks and proxy applications, we evaluated our profiler across three Message Passing Interface (MPI) implementations and two hardware platforms. Furthermore, the results show that our approach and the corresponding implementation can accurately quantify memory resource usage as a function of time, scale, communication workload, and software or hardware system architecture, clearly distinguishing between application and MPI library memory usage at a per–process level. With this new capability, we show that job size, communication workload, and hardware/software architecture influence peak runtime memory usage. In practice, this tool provides a potentially valuable source of information for application developers seeking to measure and optimize memory usage.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Computing Bottleneck Structures at Scale for High-Precision Network Performance Analysis

The Theory of Bottleneck Structures is a recently-developed framework for studying the performance of data networks. It describes how local perturbations in one part of the network propagate and interact with others. This framework is a powerful analytical tool that allows network operators to make accurate predictions about network behavior and thereby optimize performance. Previous work implemented a software package for bottleneck structure analysis, but applied it only to toy examples. In this work, we introduce the first software package capable of scaling bottleneck structure analysis to production-size networks. Here, we benchmark our system using logs from ESnet, the Department of Energy's high-performance data network that connects research institutions in the U.S. Using the previously published tool as a baseline, we demonstrate that our system achieves vastly improved performance, constructing the bottleneck structure graphs in 0.21 s and calculating link derivatives in 0.09 s on average. We also study the asymptotic complexity of our core algorithms, demonstrating good scaling properties and strong agreement with theoretical bounds. These results indicate that our new software package can maintain its fast performance when applied to even larger networks. They also show that our software is efficient enough to analyze rapidly changing networks in real time. Overall, we demonstrate the feasibility of applying bottleneck structure analysis to solve practical problems in large, real-world data networks.

benchmark↗

DOE OSTI2020

Performance simulation of the soft gamma-ray concentrator

The soft gamma-ray concentrator is a telescope mission concept utilizing a suitable arrangement of bent multilayer structures of alternating low- and high-density materials. This lens is able to channel gamma-ray photons via total external reflection and concentrate the incident radiation to a point. The channeling technique offers the potential for concentrating gamma rays with focal lengths <10 m and energies >100 keV, beyond the reach of current grazing-incidence hard x-ray mirrors. For the performance estimation of such an instrument, we have developed a flexible set of computer modeling tools to compute the optical properties of multilayer structures, predict the channeling efficiency for a given multilayer configuration, and aid in the optimization of potential gamma-ray concentrator-based telescope designs. This modeling includes the multilayer optical properties calculated by the IMD software, the ray tracing using an IDL code, and the focal plane detector simulation by MEGAlib. We illustrate the potential of this approach by presenting simulated astronomical observations from a balloon-borne platform. The final result, including simulated effective area, instrument sensitivity, and polarization performance, shows that the gamma-ray concentrator will provide greatly increased sensitivity for next-generation soft gamma-ray missions with modest cost and complexity.

47 OTHER INSTRUMENTATION↗

DOE OSTI2013

Strategy for Multi-Scale Single-Phase Flow Coupling

For practical nuclear engineering applications, multi-scale analysis by adopting the combined use of different scale computational tools, such as system thermal-hydraulics and CFD codes is vital when three-dimensional effects play an important role in the evolution of a given transient or accident scenario. The feasibility of coupling low-fidelity systems codes with higher fidelity CFD tools was demonstrated previously under NEAMS by coupling SAS4A/SASSYS-1 with the commercial CFD code STAR-CD and STAR-CCM+. An “adhoc” coupling strategy was implemented. With the advances in numerical techniques and software engineering, such as the availability of PETSc and MOOSE, modernization of existing systems codes or the development of new system code becomes more compelling. MOOSE (Multi-physics Object Oriented Simulation Environment) is a parallel computational framework developed at INL for enabling the solution of complex, fully-implicit multiphysics systems. It has been utilized in many nuclear applications including the system analysis codes RELAP-7 and the SFR module under current NEAMS Reactor Product Line (RPL). This motivates the development of a coupled scheme for MOOSE-based system analysis code and the commercial CFD code STAR-CCM+. STAR-CCM+ is a generalpurpose commercial CFD code using finite volume formulation for the analysis of compressible and incompressible flows and heat transfer, and it is being included in the toolkit of the NEAMS RPL. This investigation is important for the integration between the MOOSE-based system codes and the high-fidelity advanced simulation capabilities developed under the NEAMS RPL.

Hu, R.↗

DOE OSTI2014

Lifetime Energy and Environmental Impacts of Insulation Materials in Commercial Building Applications – Assessment Methodology and Sample Calculations

Application of insulation materials to building envelopes is a relatively easy and effective way of reducing energy consumption for space conditioning and, consequently, limiting the negative environmental impacts from the buildings sector. While insulation materials have a positive impact on the environment by reducing energy consumption in buildings, they also have some negative environmental impacts associated with their ‘embodied energy’. The total lifetime environmental impacts of insulation materials are a summation of: (1) direct impacts due to their embodied energy, and (2) indirect or environmental impacts avoided due to the reduced building energy consumption. It is important to identify insulation materials for buildings that will result in minimum negative environmental impacts. The objective of this project was to perform an assessment of the lifetime energy and environmental impacts of building insulation materials based on a previously developed protocol. The developed protocol was used for calculating the lifetime environmental impacts of selected insulation materials. Two Excel-based tools were developed: 1) to calculate embodied energy and GWP (equivalent CO 2 emissions) of insulation materials, and 2) to estimate energy savings and avoided environmental impacts due to the use of insulation materials in buildings. The direct environmental impacts were estimated using data from existing literature and life cycle analysis software; the indirect impacts were based on simulations of prototype whole-building models. This report summarizes the simulation study based on the recommendations of a previously developed protocol (A protocol for lifetime energy and environmental impact assessment of building insulation materials) by Shrestha et al., 2014. It also discusses a simplified algorithm based technique developed to quantify energy savings potential without requiring whole-building energy simulations. The report describes a proposed protocol that is intended to provide a comprehensive list of factors to be considered in evaluating the direct and indirect environmental impacts of building insulation materials, as well as detailed descriptions of standardized calculation methodologies to determine those impacts. Estimating the energy savings impact of insulation materials for the buildings in United States was an important aspect of this recommendation and comparative analyses of selected insulation materials were performed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2013

SAS4A/SASSYS-1 Modernization

SAS4A/SASSYS-1 is a software simulation tool used to perform deterministic analysis of anticipated events as well as design basis and beyond design basis accidents for advanced nuclear reactors. This report summarizes recent tasks to modernize the SAS4A/SASSYS-1 code system to improve internal data management and to update the code documentation to reflect recent code developments. The motivation for performing these updates stems from the relevance of SAS4A/SASSYS-1 to a number of U.S. Department of Energy programs as well as domestic and international collaborations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2017

Maestro Workflow Conductor

MaestroWF is a Python tool and software package for loading YAML study specifications that represents a simulation campaign. The package is capable of parameterizing a study, pulling dependencies automatically, formatting output directories, and managing the flow and execution of the campaign. MaestroWF also provides a set of abstracted objects that can also be used to develop user specific scripts for launching simulation campaigns.

Di Natale, Francesco↗