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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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At least 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

A graph-based computational framework for simulation and optimisation of coupled infrastructure networks

Here, we present a computational framework that facilitates the construction, instantiation, and analysis of large-scale optimization and simulation applications of coupled energy networks. The framework integrates the optimization modeling package PLASMO and the simulation package DMNetwork (built around PETSc). These tools use a common graphbased abstraction that enables us to achieve compatibility between data structures and to build applications that use network models of different physical fidelity. We also describe how to embed these tools within complex computational workflows using SWIFT, which is a tool that facilitates parallel execution of multiple simulation runs and management of input and output data. We discuss how to use these capabilities to target coupled natural gas and electricity systems.

42 ENGINEERING↗
DOE OSTI2024

Repurposing of the Run 2 CMS High Level Trigger Infrastructure as a Cloud Resource for Offline Computing

The former CMS Run 2 High Level Trigger (HLT) farm is one of the largest contributors to CMS compute resources, providing about 25k job slots for offline computing. This CPU farm was initially employed as an opportunistic resource, exploited during inter-fill periods, in the LHC Run 2. Since then, it has become a nearly transparent extension of the CMS capacity at CERN, being located on-site at the LHC interaction point 5 (P5), where the CMS detector is installed. This resource has been configured to support the execution of critical CMS tasks, such as prompt detector data reconstruction. It can therefore be used in combination with the dedicated Tier 0 capacity at CERN, in order to process and absorb peaks in the stream of data coming from the CMS detector. The initial configuration for this resource, based on statically configured VMs, provided the required level of functionality. However, regular operations of this cluster revealed certain limitations compared to the resource provisioning and use model employed in the case of WLCG sites. A new configuration, based on a vacuum-like model, has been implemented for this resource in order to solve the detected shortcomings. This paper reports about this redeployment work on the permanent cloud for an enhanced support to CMS offline computing, comparing the former and new models’ respective functionalities, along with the commissioning effort for the new setup.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Towards an Introspective Dynamic Model of Globally Distributed Computing Infrastructures

Large-scale scientific collaborations like ATLAS, Belle II, CMS, DUNE, and others involve hundreds of research institutes and thousands of researchers spread across the globe. These experiments generate petabytes of data, with volumes soon expected to reach exabytes. Consequently, there is a growing need for computation, including structured data processing from raw data to consumer-ready derived data, extensive Monte Carlo simulation campaigns, and a wide range of end-user analysis. To manage these computational and storage demands, centralized workflow and data management systems are implemented. However, decisions regarding data placement and payload allocation are often made disjointly and via heuristic means. A significant obstacle in adopting more effective heuristic or AI-driven solutions is the absence of a quick and reliable introspective dynamic model to evaluate and refine alternative approaches. In this study, we aim to develop such an interactive system using real-world data. By examining job execution records from the PanDA workflow management system, we have pinpointed key performance indicators such as queuing time, error rate, and the extent of remote data access. The dataset includes five months of activity. Additionally, we are creating a generative AI model to simulate time series of payloads, which incorporate visible features like category, event count, and submitting group, as well as hidden features like the total computational load—derived from existing PanDA records and computing site capabilities. These hidden features, which are not visible to job allocators, whether heuristic or AI-driven, influence factors such as queuing times and data movement.

kilic, Ozgur Ozan [Brookhaven National Laboratory ↗
DOE OSTI2024

Status of Mercury and Imp: Two Monte Carlo Transport Codes Developed Using Shared Infrastructure at Lawrence Livermore National Laboratory

The Monte Carlo Transport Project at Lawrence Livermore National Laboratory develops two Monte Carlo transport codes used in production by a sizable internal user community. Mercury is a Monte Carlo particle transport code used to model the interaction of neutrons, gammas, and light ions with a material. Imp is an implicit Monte Carlo thermal x-ray photon transport code used to model the interaction of x-ray photons with a material. This paper describes the two codes and highlights recent developments.

Pozulp, Michael↗
DOE OSTI2015

Positron production at extreme light infrastructure – nuclear physics (ELI-NP)

Applied and material physics studies with positron beams of Fermi–surfaces, defects, interfaces etc. offer excellent diagnostics tools. At ELI-NP, an intense γ beam of about 10{sup 11} photons/s with energies up to 3.5 MeV will be used to generate a positron beam via pair production in a tungsten converter target. To obtain a high intensity beam of moderated positrons the design of the positron source is of high importance. The design of a dedicated positron source at ELI–NP is being investigated based on extensive GEANT4 simulations. The goal of the simulations is to optimize the geometry of the target and the gamma beam collimation. We present here the characteristics of the positron beam obtained for different geometries of the converter target.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

SparseMaps—A systematic infrastructure for reduced-scaling electronic structure methods. III. Linear-scaling multireference domain-based pair natural orbital N-electron valence perturbation theory

Multi-reference (MR) electronic structure methods, such as MR configuration interaction or MR perturbation theory, can provide reliable energies and properties for many molecular phenomena like bond breaking, excited states, transition states or magnetic properties of transition metal complexes and clusters. However, owing to their inherent complexity, most MR methods are still too computationally expensive for large systems. Therefore the development of more computationally attractive MR approaches is necessary to enable routine application for large-scale chemical systems. Among the state-of-the-art MR methods, second-order N-electron valence state perturbation theory (NEVPT2) is an efficient, size-consistent, and intruder-state-free method. However, there are still two important bottlenecks in practical applications of NEVPT2 to large systems: (a) the high computational cost of NEVPT2 for large molecules, even with moderate active spaces and (b) the prohibitive cost for treating large active spaces. In this work, we address problem (a) by developing a linear scaling “partially contracted” NEVPT2 method. This development uses the idea of domain-based local pair natural orbitals (DLPNOs) to form a highly efficient algorithm. As shown previously in the framework of single-reference methods, the DLPNO concept leads to an enormous reduction in computational effort while at the same time providing high accuracy (approaching 99.9% of the correlation energy), robustness, and black-box character. In the DLPNO approach, the virtual space is spanned by pair natural orbitals that are expanded in terms of projected atomic orbitals in large orbital domains, while the inactive space is spanned by localized orbitals. The active orbitals are left untouched. Our implementation features a highly efficient “electron pair prescreening” that skips the negligible inactive pairs. The surviving pairs are treated using the partially contracted NEVPT2 formalism. A detailed comparison between the partial and strong contraction schemes is made, with conclusions that discourage the strong contraction scheme as a basis for local correlation methods due to its non-invariance with respect to rotations in the inactive and external subspaces. A minimal set of conservatively chosen truncation thresholds controls the accuracy of the method. With the default thresholds, about 99.9% of the canonical partially contracted NEVPT2 correlation energy is recovered while the crossover of the computational cost with the already very efficient canonical method occurs reasonably early; in linear chain type compounds at a chain length of around 80 atoms. Calculations are reported for systems with more than 300 atoms and 5400 basis functions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Engaging local industry in the development of basic research infrastructure and instrumentation – The case of HIE-ISOLDE and ESS Scandinavia

Two world-class research facilities, the European Spallation Source, ESS, and the light-source facility MAX-IV, are being built in southern Sweden. They will primarily, when completed, be used for research in the fields of material sciences, life sciences, medicine and pharmacology. Their construction and the operation and maintenance of them for many years will create new business opportunities for companies in Europe in general and in Sweden, Denmark and Norway in particular in many different sectors. A project, CATE, Cluster for Accelerator Technology, was set up with the aim to strengthen the skills of companies in the Öresund-Kattegat-Skagerrak region in Scandinavia in the field of accelerator technology such that they will become competitive and be able to take advantage of the potential of these two research facilities. CATE was strategically important and has helped to create partnerships between companies and new business opportunities in the region.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Driving the grid forward: How electric vehicle adoption shapes power system infrastructure and emissions

We model the effect of plug-in electric vehicle (EV) adoption on U.S. power system generator capacity investment, operations, and emissions through 2050 by estimating power systems outcomes under a range of EV adoption trajectory scenarios. Our EV adoption scenarios are informed by 1) an Energy Information Administration scenario with no policy intervention, 2) EV growth expected under the Inflation Reduction Act (IRA), 3) a Biden Administration 50% EV sales target by 2030, 4) the Environmental Protection Agency’s projections under vehicle emissions standards, and 5) the International Energy Agency’s roadmap to Net Zero by 2050. We find across these scenarios that increasing EV adoption induces investment in new wind, solar, storage, and natural gas capacity, affecting power generation mix and emissions. The net effect of increasing EV adoption beyond our IRA base case is to increase power sector emissions by about 5 mtCO 2 eq per EV-year in 2026 (comparable to displaced gasoline vehicle combustion emissions), but this effect rapidly drops to annual levels below 1 mtCO 2 eq per EV-year by 2032 and continues below this level through 2050. Consequential effects of EV adoption vary regionally, with most regions primarily increasing wind or solar capacity and some regions primarily increasing natural gas capacity, even in 2050. Our national emissions estimates per EV-year are relatively robust to the level of EV adoption beyond our baseline and to variation in assumptions about power systems, EV behavior, and policy.

Science & Technology - Other Topics↗
DOE OSTI2023

Extending the distributed computing infrastructure of the CMS experiment with HPC resources

Particle accelerators are an important tool to study the fundamental properties of elementary particles. Currently the highest energy accelerator is the LHC at CERN, in Geneva, Switzerland. Each of its four major detectors, such as the CMS detector, produces dozens of Petabytes of data per year to be analyzed by a large international collaboration. The processing is carried out on the Worldwide LHC Computing Grid, that spans over more than 170 compute centers around the world and is used by a number of particle physics experiments. Recently the LHC experiments were encouraged to make increasing use of HPC resources. While Grid resources are homogeneous with respect to the used Grid middleware, HPC installations can be very different in their setup. In order to integrate HPC resources into the highly automatized processing setups of the CMS experiment a number of challenges need to be addressed. For processing, access to primary data and metadata as well as access to the software is required. At Grid sites all this is achieved via a number of services that are provided by each center. However at HPC sites many of these capabilities cannot be easily provided and have to be enabled in the user space or enabled by other means. At HPC centers there are often restrictions regarding network access to remote services, which is again a severe limitation. The paper discusses a number of solutions and recent experiences by the CMS experiment to include HPC resources in processing campaigns.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Optimizing CMS build infrastructure via Apache Mesos

The Offline Software of the CMS Experiment at the Large Hadron Collider (LHC) at CERN consists of 6M lines of in-house code, developed over a decade by nearly 1000 physicists, as well as a comparable amount of general use open-source code. A critical ingredient to the success of the construction and early operation of the WLCG was the convergence, around the year 2000, on the use of a homogeneous environment of commodity x86-64 processors and Linux.Apache Mesos is a cluster manager that provides efficient resource isolation and sharing across distributed applications, or frameworks. It can run Hadoop, Jenkins, Spark, Aurora, and other applications on a dynamically shared pool of nodes. Lastly, we present how we migrated our continuous integration system to schedule jobs on a relatively small Apache Mesos enabled cluster and how this resulted in better resource usage, higher peak performance and lower latency thanks to the dynamic scheduling capabilities of Mesos.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Design of the protoDUNE raw data management infrastructure

The Deep Underground Neutrino Experiment (DUNE) will employ a set of Liquid Argon Time Projection Chambers (LArTPC) with a total mass of 40 kt as the main components of its Far Detector. In order to validate this technology and characterize the detector performance at full scale, an ambitious experimental program (called “protoDUNE”) has been initiated which includes a test of the large-scale prototypes for the single-phase and dual-phase LArTPC technologies, which will run in a beam at CERN. The total raw data volume that is slated to be collected during the scheduled 3-month beam run is estimated to be in excess of 2.5 PB for each detector. This data volume will require that the protoDUNE experiment carefully design the DAQ, data handling and data quality monitoring systems to be capable of dealing with challenges inherent with peta-scale data management while simultaneously fulfilling the requirements of disseminating the data to a worldwide collaboration and DUNE associated computing sites. Here in this paper, we present our approach to solving these problems by leveraging the design, expertise and components created for the LHC and Intensity Frontier experiments into a unified architecture that is capable of meeting the needs of protoDUNE.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗