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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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12 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Pressure-tuned quantum criticality in the large-D antiferromagnet DTN

Strongly correlated spin systems can be driven to quantum critical points via various routes. In particular, gapped quantum antiferromagnets can undergo phase transitions into a magnetically ordered state with applied pressure or magnetic field, acting as tuning parameters. These transitions are characterized by z = 1 or z = 2 dynamical critical exponents, determined by the linear and quadratic low-energy dispersion of spin excitations, respectively. Employing high-frequency susceptibility and ultrasound techniques, we demonstrate that the tetragonal easy-plane quantum antiferromagnet NiCl 2 · 4SC(NH 2 ) 2 (aka DTN) undergoes a spin-gap closure transition at about 4.2 kbar, resulting in a pressure-induced magnetic ordering. The studies are complemented by high-pressure-electron spin-resonance measurements confirming the proposed scenario. Powder neutron diffraction measurements revealed that no lattice distortion occurs at this pressure and the high spin symmetry is preserved, establishing DTN as a perfect platform to investigate z = 1 quantum critical phenomena. The experimental observations are supported by DMRG calculations, allowing us to quantitatively describe the pressure-driven evolution of critical fields and spin-Hamiltonian parameters in DTN.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Digital Twin Network (DTN): Concepts, Architecture, and Key Technologies

With the commercial deployment of 5G and the migration of internet from IPv4 to IPv6, the new development of the network technology has highly attracted the attention of the industry. The intelligentization of network is believed as the trend of the new generation of network development. The network provides the foundation for the information transmission in the digital society, and the digitalization of the network itself is the prerequisite for the intelligent development. Facing the goal of the new generation of digital and intelligent network, this paper introduces the new concept of "digital twin network (DTN)", designs the system architecture, and analyzes the key technologies of DTN. By investigating the challenges of DTN, this paper points out the future development direction of digital twin network.

digital twin network↗
DOE OSTI2021

Magnetic ground state of the one-dimensional ferromagnetic chain compounds M (NCS) 2 (thiourea) 2 (M=Ni,Co)

The magnetic properties of the two isostructural molecule-based magnets— Ni ( NCS ) 2 ( thiourea ) 2 , S = 1 [ thiourea = SC ( NH 2 ) 2 ] and Co ( NCS ) 2 ( thiourea ) 2 , S = 3 / 2 —are characterized using several techniques in order to rationalize their relationship with structural parameters and to ascertain magnetic changes caused by substitution of the spin. Zero-field heat capacity and muon-spin relaxation measurements reveal low-temperature long-range ordering in both compounds, in addition to Ising-like ( D < 0 ) single-ion anisotropy ( D Co ~ - 100 K, D Ni ~ - 10 K). Crystal and electronic structure, combined with dc-field magnetometry, affirm highly quasi-one-dimensional behavior, with ferromagnetic intrachain exchange interactions J Co ≈ + 4 K and J Ni ~ + 100 K and weak antiferromagnetic interchain exchange, on the order of J ' ~ - 0.1 K. Furthermore, electron charge- and spin-density mapping reveals through-space exchange as a mechanism to explain the large discrepancy in J -values despite, from a structural perspective, the highly similar exchange pathways in both materials. Both species can be compared to the similar compounds M Cl 2 ( thiourea ) 4 , M = Ni(II) (DTN) and Co(II) (DTC), where DTN is known to harbor two magnetic-field-induced quantum critical points. Direct comparison of DTN and DTC with the compounds studied here shows that substituting the halide Cl - ion for the NCS - ion results in a dramatic change in both the structural and magnetic properties.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The phase-2 particle x-ray temporal diagnostic for simultaneous measurement of multiple x-ray and nuclear emission histories from OMEGA implosions (invited)

Electron-temperature (T e ) measurements in implosions provide valuable diagnostic information, as T e is negligibly affected by residual flows and other non-thermal effects unlike ion-temperature inferred from a fusion product spectrum. In OMEGA cryogenic implosions, measurement of T e (t) can be used to investigate effects related to time-resolved hot-spot energy balance. The newly implemented phase-2 Particle X-ray Temporal Diagnostic (PXTD) utilizes four fast-rise (~15 ps) scintillator-channels with distinct x-ray filtering. Titanium and stepped aluminum filtering were chosen to maximize detector sensitivity in the 10–20 keV range, as it has been shown that these x rays have similar density and temperature weighting to the emitted deuterium–tritium fusion neutrons (DTn) from OMEGA Cryo-DT implosions. High quality data have been collected from warm implosions at OMEGA. These data have been used to infer spatially integrated T e (t) with <10% uncertainty at peak emission. Nuclear and x-ray emission histories are measured with 10 ps relative timing uncertainty for x rays and DTn and 12 ps for x rays and deuterium- 3 He protons (D 3 Hep). A future upgrade to the system will enable spatially integrated T e (t) with 40 ps time-resolution from cryogenic DT implosions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

First-principles study of an S = 1 quasi one-dimensional quantum molecular magnetic material

We use density functional theory to study the structural, magnetic, and electronic structures of the organometallic quantum magnet NiCl 2-4 SC (NH 2 ) 2 (DTN). Recent work has demonstrated the quasi one-dimensional nature of the molecular crystal and studied its quantum phase transitions at low temperatures. The system includes a magnetoelectric (ME) coupling and, when doped with Br, the presence of an exotic Bose-glass state. Using the generalized gradient approximation with inclusion of a van der Waals term to account for weak intermolecular forces and by introducing a Hubbard U term to the total energy, we systematically show that our calculations reproduce the magnetic anisotropy, the intermolecular exchange coupling strength, and the magnetoelectric effect in DTN, which have been observed in previous experiments. Further analysis of the electronic structure gives insight into the underlying magnetic interactions, including what mechanisms may be causing the ME effect. Using this computationally efficient model, we predict what effect applying an electric field might have on the magnetic properties of this quantum magnet.

1-dimensional spin chains↗
DOE OSTI2019

Unified Geometric Multigrid Algorithm for Hybridized High-Order Finite Element Methods

In this paper, we consider a standard elliptic partial differential equation and propose a geometric multigrid algorithm based on Dirichlet-to-Neumann (DtN) maps for hybridized high-order finite element methods. The proposed unified approach is applicable to any locally conservative hybridized finite element method including multinumerics with different hybridized methods in different parts of the domain. For these methods, the linear system involves only the unknowns residing on the mesh skeleton, and constructing intergrid transfer operators is therefore not trivial. The key to our geometric multigrid algorithm is the physics-based energy-preserving intergrid transfer operators which depend only on the fine scale DtN maps. Thanks to these operators, we completely avoid upscaling of parameters and no information regarding subgrid physics is explicitly required on coarse meshes. Moreover, our algorithm is agglomeration-based and can straightforwardly handle unstructured meshes. We perform extensive numerical studies with hybridized mixed methods, hybridized discontinuous Galerkin methods, weak Galerkin methods, and hybridized versions of interior penalty discontinuous Galerkin methods on a range of elliptic problems including subsurface flow through highly heterogeneous porous media. We compare the performance of different smoothers and analyze the effect of stabilization parameters on the scalability of the multigrid algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Thermal decoupling of deuterium and tritium during the ICF shock-convergence phase

We report that a series of thin glass-shell shock-driven DT gas-filled capsule implosions was conducted at the OMEGA laser facility. These experiments generate conditions relevant to the central plasma during the shock-convergence phase of ablatively driven inertial confinement fusion (ICF) implosions. The spectral temperatures inferred from the DTn and DDn spectra are most consistent with a two-ion-temperature plasma, where the initial apparent temperature ratio, $\frac{T_T}{T_P}$, is 1.5. This is an experimental confirmation of the long-standing conjecture that plasma shocks couple energy directly proportional to the species mass in multi-ion plasmas. The apparent temperature ratio trend with equilibration time matches expected thermal equilibration described by hydrodynamic theory. This indicates that deuterium and tritium ions have different energy distributions for the time period surrounding shock convergence in ignition-relevant ICF implosions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Enabling Low-Overhead HT-HPC Workflows at Extreme Scale using GNU Parallel

GNU Parallel is a versatile and powerful tool for process parallelization widely used in scientific computing. This paper demonstrates its effective application in high-performance computing (HPC) environments, particularly focusing on its scalability and efficiency in executing large-scale high-throughput high-performance computing (HT-HPC) workflows. Through real-world examples, we highlight GNU Parallel’s performance across various HPC workloads, including GPU computing, container-based workloads, and node-local NVMe storage. Our results on two leading supercomputers, OLCF’s Frontier and NERSC’s Perlmutter, showcase GNU Parallel’s rapid process dispatching ability and its capacity to maintain low overhead even at extreme scales. We explore GNU Parallel’s application in massive parallel file transfers using a scheduled Data Transfer Node (DTN) cluster, emphasizing its broad utility in diverse scientific workflows. Beyond its direct application as a viable workflow manager, GNU Parallel can be employed in conjunction with other workflow systems as a "last-mile" parallelizing driver and as a quick prototyping tool to design and extract parallel profiles from application executions. We then argue that the potential for GNU Parallel to transform workflow management at extreme scales is substantial, paving the way for more efficient and effective scientific discoveries.

Maheshwari, Ketan↗
DOE OSTI2018

Resource Aware Intelligent Network Services (RAINS) Final Technical Report

The Resource Aware Intelligent Network Services (RAINS) project conducted research and developed technologies in the area of cyber infrastructure resource modeling and computation. The goal of this work was to provide a foundation to enable intelligent, software defined services which spanned the network AND the resources which connect to the network. A Multi-Resource Service Plane (MRSP) was defined, which allows resource owners/managers to locate and place themselves from a topology and service availability perspective within the dynamic networked cyberinfrastructure ecosystem. The MRSP enables the presentation of integrated topology views and computation results which can include resources across the spectrum of compute, storage, and networks. The RAINS project developed MSRP includes the following key components: i) Multi-Resource Service (MRS) Ontology/Multi-Resource Markup Language (MRML), ii) Resource Computation Engine (RCE), iii) Modular Driver Framework (to allow integration of a variety of external resources). The MRS/MRML is a general and extensible modeling framework that allows for resource owners to model, or describe, a wide variety of resource types. All resources are described using three categories of elements: Resources, Services, and Relationships between the elements. This modeling framework defines a common method for the transformation of cyber infrastructure resources into data in the form of MRML models. In order to realize this infrastructure datification, the RAINS project developed a model based computation system, i.e. “RAINS Computation Engine (RCE)”. The RCE has the ability to ingest, process, integrate, and compute based on automatically generated MRML models. The RCE interacts with the resources thru system drivers which are specific to the type of external network or resource controller. The RAINS project developed a modular and pluggable driver system which facilities a variety of resource controllers to automatically generate, maintain, and distribute MRML based resource descriptions. Once all of the resource topologies are absorbed by the RCE, a connected graph of the full distributed system topology is constructed, which forms the basis for computation and workflow processing. The RCE includes a Modular Computation Element (MCE) framework which allows for tailoring of the computation process to the specific set of resources under control, and the services desired. The input and output of an MCE are both model data based on MRS/MRML ontology and schema. Some of the RAINS project accomplishments include: Development of general and extensible multi-resource modeling framework; Design of a Resource Computation Engine (RCE) system which includes the following key capabilities; Absorb a variety of multi-resource model types and build integrated models; Novel architecture which uses model based communications across the full stack for all Flexible provision of abstract or intent based user facing interfaces; Workflow processing based on model descriptions; Release of the RCE as an open source software; Deployment of RCE in the University of Maryland/Mid-Atlantic Crossroad ScienceDMZ in prototype mode with a plan under way to transition to production; Deployment at the Argonne National Laboratory DTN Facility in prototype mode; Selection of RCE by the DOE SENSE (SDN for End-to-end Networked Science at the Exascale) project as the basis for their orchestration service.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

SDN-NGenIA, a Software Defined Next Generation Integrated Architecture for HEP and Data Intensive Science

This project aims to enable the LHC and other leading programs in high energy physics and other global science domains funded by the DOE to operate with a new level of efficiency and control, through the development of a Next Generation Integrated Architecture (NGenIA) based on intelligent software defined network (SDN)-driven network systems coupled to high throughput applications. While the initial focus is on the challenging LHC use case, the systems and products being developed are general, and apply to many fields of data intensive science ranging from astrophysical sky surveys to bioinformatics and earth observation, as well as other organizations facing the challenges of extracting knowledge from distributed multi-petabyte data stores. A central concept in this development program is a new paradigm ‘consistent network operations’ among widely distributed computing and storage facilities, where stable high throughput flows, at set rates, cross load-balanced network paths, up to flexible high water marks that are adjusted in real time to accommodate other network traffic. The large smooth flows are launched and managed by SDN services that act in concert with the experiments’ site-resident data distribution and management systems, to meet the expanding needs of the science programs. The technical goals include the construction of autonomous, intelligent site-resident services that interact dynamically with network-resident services, and with the science programs’ principal data distribution and management tools, to request or command network resources in support of high throughput petascale to exascale workflow Specific work items include: 1. Developing compact Data Transfer Nodes (DTNs) with auto-tuning functions that support data transfer rates in the 100 Gbps to the 1 Tbps range when used with high throughput data transfer applications 2. Deep site orchestration among virtualized clusters, storage subsystems and subnets to successfully coschedule CPU, storage and network resources 3. Science-program designed site architectures, operational modes, and policy and resource usage priorities, adjudicated across multiple network domains and virtual organizations, using the orchestration functions and methods 4. Seamlessly extending end-to-end operation across both extra-site and intra-site boundaries through the use of Open vSwitch (OVS), FireQoS + next generation Science DMZs 5. Novel methods of system integration that enable granular control of extreme scale long distance transfers through flow matching of scattered source-destination address pairs to multi-domain dynamic circuits 6. Funneling massive sets of streams to DTNs at the site edge hosting petascale buffer pools configured for flows of 100 Gbps and up, exploiting state of the art data transfers 7. Adaptive scheduling based on pervasive end-to-end monitoring, including DTN or compute-node resident agents providing comprehensive end-system profiling 8. Developing unsupervised and supervised machine learning and modeling methods to optimize the workflow involving terabyte to multi-petabyte datasets.

47 OTHER INSTRUMENTATION↗