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

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17 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Evaluation of Portable Programming Models to Accelerate LArTPC Detector Simulations

The Liquid Argon Time Projection Chamber (LArTPC) technology is widely used in high energy physics experiments, including the upcoming Deep Underground Neutrino Experiment (DUNE). Accurately simulating LArTPC detector responses is essential for analysis algorithm development and physics model interpretations. Accurate LArTPC detector response simulations are computationally demanding, and can become a bottleneck in the analysis workflow. Compute devices such as General-Purpose Graphics Processing Units (GPGPUs) have the potential to substantially accelerate simulations compared to traditional CPU-only processing. The software development that requires often carries the cost of specialized code refactorization and porting to match the target hardware architecture. With the rapid evolution and increased diversity of the computer architecture landscape, it is highly desirable to have a portable solution that also maintains reasonable performance. We report our ongoing effort in evaluating Kokkos as a basis for this portable programming model using LArTPC simulations in the context of the Wire-Cell Toolkit, a C++ library for LArTPC simulations, data analysis, reconstruction and visualization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Evaluation of Portable Programming Models to Accelerate LArTPC Detector Simulations

The Liquid Argon Time Projection Chamber (LArTPC) technology is widely used in high energy physics experiments, including the upcoming Deep Underground Neutrino Experiment (DUNE). Accurately simulating LArTPC detector responses is essential for analysis algorithm development and physics model interpretations. Accurate LArTPC detector response simulations are computationally demanding, and can become a bottleneck in the analysis workflow. Compute devices such as General-Purpose Graphics Processing Units (GPGPUs) have the potential to substantially accelerate simulations compared to traditional CPU-only processing. The software development for these compute accelerators often carries the cost of specialized code refactorization and porting to match the target hardware architecture. With the rapid evolution and increased diversity of the computer architecture landscape, it is highly desirable to have a portable solution that also maintains reasonable performance. We report our ongoing effort in evaluating Kokkos as a basis for this portable programming model using LArTPC simulations in the context of the Wire-Cell Toolkit, a C++ library for LArTPC simulations, data analysis, reconstruction and visualization.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

The upgrade and re-validation of the Compact Muon Solenoid Electromagnetic Calorimeter Control and Safety Systems during the Second Long Shutdown of the Large Hadron Collider at CERN

The Electromagnetic Calorimeter (ECAL) is one of the subdetectors of the Compact Muon Solenoid (CMS), a general-purpose particle detector at the CERN Large Hadron Collider (LHC). The CMS ECAL Detector Control System (DCS) and the CMS ECAL Safety System (ESS) have supported the detector operations and ensured the detector’s integrity since the CMS commissioning phase, more than 10 years ago. Over this long period, several changes to both systems were necessary to correct issues, extend functionality and keep them in-line with current hardware technologies and the evolution of software platforms. Due to the constraints imposed on significant changes to a running system, major hardware and software upgrades were therefore deferred to the second LHC Long Shutdown (LS2). This paper presents the architectures of the CMS ECAL control and safety systems, discusses the ongoing and planned upgrades, details implementation processes and validation methods and highlights the expectations for the post-LS2 systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Modeling the Nonlinear Rheology of Polymer Additive Manufacturing

This report summarizes molecular and continuum simulation studies focused on developing physics - based predictive models for the evolution of polymer molecular order during the nonlinear processing flows of additive manufacturing. Our molecular simulations of polymer elongation flows identified novel mechanisms of fluid dissipation for various polymer architectures that might be harnessed to enhance material processability. In order to predict the complex thermal and flow history of polymer realistic additive manufacturing processes, we have developed and deployed a high - performance mesh - free hydrodynamics module in Sandia's LAMMPS software. This module called RHEO – short for Reproducing Hydrodynamics and Elastic Objects – hybridizes an updated - Lagrange reproducing - kernel method for complex fluids with a bonded particle method (BPM) to capture solidification and solid objects in multiphase flows. In combination, our two methods allow rapid, multiscale characterization of the hydrodynamics and molecular evolution of polymers in realistic processing geometries.

36 MATERIALS SCIENCE↗
DOE OSTI2024

An integrated modeling framework with open architecture for phase field simulation of multi-component alloys

An integrated modeling framework (PanPhaseField) has been developed, which enables a direct and fast coupling between CALPHAD calculations and large-scale phase field simulations for multi-component alloys. Further, it adopts an open architecture allowing for integration of user-defined phase field models in a plug-and-play manner by taking full advantage of the user-friendly graphical interface of Pandat software. The developed modeling platform becomes an enabling tool that can be used to simulate the evolution of spatially varying microstructures of industrial complex alloys for various engineering applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

C2QA - Bosonic Qiskit

The practical benefits of hybrid quantum information processing hardware that contains continuous-variable objects (bosonic modes such as mechanical or electromagnetic oscillators) in addition to traditional (discrete-variable) qubits have recently been demonstrated by experiments with bosonic codes that reach the break-even point for quantum error correction [1]–[5] and by efficient Gaussian boson sampling simulation of the Franck-Condon spectra of triatomic molecules [6] that is well beyond the capabilities of current qubit-only hardware. The goal of this Co-design Center for Quantum Advantage (C2QA) project is to develop an instruction set architecture (ISA) for hybrid qubit/bosonic mode systems that contains an inventory of the fundamental operations and measurements that are possible in such hardware. The corresponding abstract machine model (AMM) would also contain a description of the appropriate error models associated with the gates, measurements and time evolution of the hardware. This information has been implemented as an extension of IBM Qiskit. IBM Qiskit is an open-source software development toolkit (SDK) for simulating the quantum state of a quantum circuit and for running the same circuits on prototype hardware within the IBM Quantum Experience. We introduce the Bosonic Qiskit software to enable the simulation of hybrid qubit/bosonic systems using the existing Qiskit software development kit [7]. This implementation can be used for simulating new hybrid systems, verifying proposed physical systems, and modeling systems larger than can currently be constructed. We also cover tutorials and example use cases included within the software to study JaynesCummings models, bosonic Hubbard models, plotting Wigner functions and animations, and calculating maximum likelihood estimations using Wigner functions.

quantum, boson, Qiskit↗
DOE OSTI2022

Evolution of HEP Processing Frameworks

HEP data-processing software must support the disparate physics needs of many experiments. For both collider and neutrino environments, HEP experiments typically use data-processing frameworks to manage the computational complexities of their large-scale data processing needs. Data-processing frameworks are being faced with new challenges this decade. The computing landscape has changed from the past three decades of homogeneous single-core x86 batch jobs running on grid sites. Frameworks must now work on a heterogeneous mixture of different platforms: multi-core machines, different CPU architectures, and computational accelerators; and different computing sites: grid, cloud, and high-performance computing. We describe these challenges in more detail and how frameworks may confront them. Given their historic success, frameworks will continue to be critical software systems that enable HEP experiments to meet their computing needs. Frameworks have weathered computing revolutions in the past; they will do so again with support from the HEP community

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Resilient Entanglement Distribution in a Multihop Quantum Network

The evolution of quantum networking requires architectures capable of dynamically reconfigurable entanglement distribution to meet diverse user needs and ensure tolerance against transmission disruptions. We introduce multihop quantum networks to improve network reach and resilience by enabling quantum communications across intermediate nodes, thus broadening network connectivity and increasing scalability. We present multihop two-qubit polarization-entanglement distribution within a quantum network at the Oak Ridge National Laboratory campus. Our system uses wavelength-selective switches for adaptive bandwidth management on a software-defined quantum network that integrates a quantum data plane with classical data and control planes, creating a flexible, reconfigurable mesh. Our network distributes entanglement across six nodes within three subnetworks, each located in a separate building, optimizing quantum state fidelity and transmission rate through adaptive resource management. Additionally, we demonstrate the network's resilience by implementing a link recovery approach that monitors and reroutes quantum resources to maintain service continuity despite link failures—paving the way for scalable and reliable quantum networking infrastructures.

Alshowkan, Muneer [Oak Ridge National Laboratory (↗
DOE OSTI2021

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↗
DOE OSTI2025

Improving the Capabilities and Computational Efficiency of the RTE+RRTMGP Radiation Code (Final Report)

This report details progress on the RTE+RRTMGP radiation codes made during the period of performance. RTE+RRTMGP is a set of codes for computing radiative fluxes in planetary atmospheres. RRTMGP uses a k-distribution to provide an optical description (absorption and possibly Rayleigh optical depth) of the gaseous atmosphere, along with the relevant source functions, on a pre-determined spectral grid given temperatures, pressures, and gas concentration. RTE computes fluxes given spectrally-resolved optical descriptions and source functions. Spectrally-resolved fluxes are summarized (“reduced”) via a user extensible class. The initial release of the code and the design choices are described in Pincus et al. 2019; the codes are available on Github. Although RRTMGP was based on current (at the time) empirical spectroscopic data, RTE and RRTMGP were developed in large part to modernize software practices. The design focused on flexibility broadly interpreted: by separating code from data and allowing data to drive computation; in coupling to the host model (e.g. the coupling of clouds to radiative fluxes is user-controlled); with respect to programming languages (computational tasks are accessed via widely-compatible C interfaces); and with respect to hardware (the codes run on a range of CPU and GPU architectures). The code also puts an emphasis on modularity and clarity. RTE+RRTMGP v1.0 was released in September 20219. This award supported the evolution of the RTE+RRTMGP code base to support greater flexibility, accuracy, and efficiency.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Leveraging the Run 3 experience for the evolution of the ATLAS software-based readout towards HL-LHC

The High-Luminosity Large Hadron Collider (HL-LHC), scheduled to start operating in 2030, aims to increase the instantaneous luminosity by a factor of 10 compared to the LHC. To match this increase, the ATLAS experiment has been implementing a major upgrade program divided into two phases. The first phase (Phase-I), completed in 2022, introduced new trigger and detector systems that have been used during the Run 3 data taking period which began in July 2022. These systems have been used in conjunction with the new Data Acquisition (DAQ) Readout system, based on a software application called Software Readout Driver (SW ROD). SW ROD receives and aggregates data from the front-end electronics via the Front-End Link eXchange (FELIX) system and passes aggregated data fragments to the High-Level Trigger (HLT) system. During Run 3, SW ROD operates in parallel with the legacy Readout System (ROS) at an input rate of 100 kHz. For the Phase-II, the legacy ROS will be completely replaced with a new system based on the next generation of FELIX and an evolution of the SW ROD application called Data Handler. Data Handler has the same functional requirements as SW ROD but must be able to operate at an input rate of 1 MHz. To facilitate this evolution the SW ROD has been implemented using plugin architecture. This contribution presents the design and implementation of the SW ROD application for Run 3, along with the strategy for its evolution to the Phase-II Readout system. It discusses the lessons learned during Run 3 and describes the challenges that have been addressed to accomplish the demanding performance requirements of HL-LHC.

Kolos, Serguei [Univ. of California, Irvine, CA (U↗
DOE OSTI2022

Enabling New Flexibility in the SUNDIALS Suite of Nonlinear and Differential/Algebraic Equation Solvers

In recent years, the SUite of Nonlinear and DIfferential/ALgebraic equation Solvers (SUNDIALS) has been redesigned to better enable the use of application-specific and third-party algebraic solvers and data structures. Throughout this work, we have adhered to specific guiding principles that minimized the impact to current users while providing maximum flexibility for later evolution of solvers and data structures. The redesign was done through the addition of new linear and nonlinear solvers classes, enhancements to the vector class, and the creation of modern Fortran interfaces. The vast majority of this work has been performed “behind-the-scenes,” with minimal changes to the user interface and no reduction in solver capabilities or performance. These changes allow SUNDIALS users to more easily utilize external solver libraries and create highly customized solvers, enabling greater flexibility on extreme-scale, heterogeneous computational architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Matilda v1.0: An R package for probabilistic climate projections using a reduced complexity climate model

A primary advantage to using reduced complexity climate models (RCMs) has been their ability to quickly conduct probabilistic climate projections, a key component of uncertainty quantification in many impact studies and multisector systems. Providing frameworks for such analyses has been a target of several RCMs used in studies of the future co-evolution of the human and Earth systems. In this paper, we present Matilda, an open-science R software package that facilitates probabilistic climate projection analysis, implemented here using the Hector simple climate model in a seamless and easily applied framework. The primary goal of Matilda is to provide the user with a turn-key method to build parameter sets from literature-based prior distributions, run Hector iteratively to produce perturbed parameter ensembles (PPEs), weight ensembles for realism against observed historical climate data, and compute probabilistic projections for different climate variables. This workflow gives the user the ability to explore viable parameter space and propagate uncertainty to model ensembles with just a few lines of code. The package provides significant freedom to select different scoring criteria and algorithms to weight ensemble members, as well as the flexibility to implement custom criteria. Additionally, the architecture of the package simplifies the process of building and analyzing PPEs without requiring significant programming expertise, to accommodate diverse use cases. We present a case study that provides illustrative results of a probabilistic analysis of mean global surface temperature as an example of the software application.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Evolution of the ATLAS TDAQ online software framework towards Phase-II upgrade: Use of Kubernetes as an orchestrator of the ATLAS Event Filter computing farm

The ATLAS experiment at the LHC at CERN continuously evolves its TDAQ system to meet the challenges of new physics goals and technological advancements. As ATLAS prepares for the Phase-II Run 4 of the LHC, significant enhancements in the TDAQ Controls and Configuration (TDAQ-CC) tools have been designed to ensure efficient data collection, processing, and management. This abstract presents the evolution of ATLAS TDAQ-CC system leading up to Phase-II Run 4. As part of the evolution towards Phase-II, Kubernetes has been chosen to orchestrate the Event Filter (EF) farm. By leveraging Kubernetes, ATLAS can dynamically allocate computing resources, scale processing capacity in response to changing data taking conditions and ensure high availability of data processing services. The integration of the Kubernetes with the TDAQ Run Control framework enables perfect synchronisation between the experiment’s data acquisition components and the computing infrastructure. We will discuss the architectural considerations and implementation challenges involved in Kubernetes integration with the ATLAS TDAQ-CC system. We will highlight the benefits of using Kubernetes as an EF farm orchestrator, including improved resource utilization, enhanced fault tolerance, and simplified deployment and management of data processing workflows. In addition, we will report on the extensive testing of Kubernetes that was conducted using a farm of 2500 servers within the experiment data taking environment, demonstrating its scalability and robustness in handling the demands of the ATLAS TDAQ system for Phase-II. The adoption of Kubernetes represents a significant step forward in the evolution of ATLAS TDAQ-CC system, aligning with industry best practices in container orchestration.

Corso Radu, Alina [Univ. of California, Irvine, CA↗
DOE OSTI2024

Evolution of the SLATE linear algebra library

SLATE (Software for Linear Algebra Targeting Exascale) is a distributed, dense linear algebra library targeting both CPU-only and GPU-accelerated systems, developed over the course of the Exascale Computing Project (ECP). While it began with several documents setting out its initial design, significant design changes occurred throughout its development. In some cases, these were anticipated: an early version used a simple consistency flag that was later replaced with a full-featured consistency protocol. In other cases, performance limitations and software and hardware changes prompted a redesign. Sequential communication tasks were parallelized; host-to-host MPI calls were replaced with GPU device-to-device MPI calls; more advanced algorithms such as Communication Avoiding LU and the Random Butterfly Transform (RBT) were introduced. Early choices that turned out to be cumbersome, error prone, or inflexible have been replaced with simpler, more intuitive, or more flexible designs. Applications have been a driving force, prompting a lighter weight queue class, nonuniform tile sizes, and more flexible MPI process grids. Of paramount importance has been building a portable library that works across several different GPU architectures – AMD, Intel, and NVIDIA – while keeping a clean and maintainable codebase. Here we explore the evolving design choices and their effects, both in terms of performance and software sustainability.

Gates, Mark↗
DOE OSTI2021

GR-Athena++: Puncture Evolutions on Vertex-centered Oct-tree Adaptive Mesh Refinement

Numerical relativity is central to the investigation of astrophysical sources in the dynamical and strong-field gravity regime, such as binary black hole and neutron star coalescences. Current challenges set by gravitational-wave and multimessenger astronomy call for highly performant and scalable codes on modern massively parallel architectures. We present GR-Athena++, a general-relativistic, high-order, vertex-centered solver that extends the oct-tree, adaptive mesh refinement capabilities of the astrophysical (radiation) magnetohydrodynamics code Athena++. To simulate dynamical spacetimes, GR-Athena++ uses the Z4c evolution scheme of numerical relativity coupled to the moving puncture gauge. We demonstrate stable and accurate binary black hole merger evolutions via extensive convergence testing, cross-code validation, and verification against state-of-the-art effective-one-body waveforms. GR-Athena++ leverages the task-based parallelism paradigm of Athena++ to achieve excellent scalability. We measure strong-scaling efficiencies above 95% for up to ~1.2 × 10 4 CPUs and excellent weak scaling is shown up to ~10 5 CPUs in a production binary black hole setup with adaptive mesh refinement. GR-Athena++ thus allows for the robust simulation of compact binary coalescences and offers a viable path toward numerical relativity at exascale.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Strengthening the Security of Operational Technology: Understanding Contemporary Bill of Materials

The evolution of cyber-physical infrastructure has made its security more challenging. The last few years have witnessed a convergence of hardware and software segments in various domains, including operational technology (OT) which is responsible for carrying out critical tasks such as monitoring and controlling power grids, nuclear plants, transportation, and emergency services. Both hardware and software encapsulate numerous open source and proprietary subcomponents, making it crucial for end-users to understand the composition of the products they are using. For example, wind turbines incorporate thousands of lines of code (software) used for the turbine's design, planning, operation, and analytics in addition to the numerous hardware subcomponents that construct it. Due to the highly complex nature of software and hardware, knowledge of the components and subcomponents is required to mitigate cyber vulnerabilities and defend against cyberattacks. There has also been a transformation from a traditional linear supply chain into a global, dynamic, diverse, and interconnected system. The digitization of the supply chain makes it easier to find and exploit vulnerabilities. Critical infrastructures (e.g., power grids, oil, natural gas, water, and wastewater) rely on OT to function, and if the OT is compromised, equipment damage and potential interruption of services could result. A significant security measure to protect OT systems from disruption is to develop a supply chain bill of materials (BoM) corresponding to the software and hardware used in OT, along with attestations amongst vendors and asset owners. A supply chain BoM is a proactive way to understand the inherent vulnerabilities in the system and mitigate them in advance of being exploited. BoMs bolster the trust placed in the digital infrastructure and enhance software supply chain security by sustaining the management of component obsolescence and compliance, along with the seclusion of unsafe segments of a specific product. Adopting BoM tools is becoming increasingly important across various government sectors, as evidenced by the recent U.S. executive order on cybersecurity (NIST 2021). This paper aims to classify BoMs based on structure, functionality, component type, and architecture. The work also discusses case studies to further highlight the benefits of BoMs. In addition, it identifies missing pieces in existing BoM implementations so that future research may identify bounds on where it could expect to make improvements and directly enable researchers to identify promising areas for exploration. Further, the authors provide valuable recommendations to tool developers, researchers, and standardizing organizations (policymakers), additionally benefitting critical infrastructure owners and government executives. This aids in paving a path for future work, thereby, providing suggestions to determine a tool for consumers that best suit their needs.

97 MATHEMATICS AND COMPUTING↗