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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 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Development of high-availability ATCA/PCIe data acquisition instrumentation

Latest Fusion energy experiments envision a quasi-continuous operation regime. In consequence, the largest experimental devices, currently in development, specify high-availability (HA) requirements for the whole plant infrastructure. HA features enable the whole facility to perform seamlessly in the case of failure of any of its components, coping with the increasing duration of plasma discharges (steady-state) and assuring safety of equipment, people, environment and investment. IPFN developed a control and data acquisition system, aiming for fast control of advanced Fusion devices, which is thus required to provide such HA features. The system is based on in-house developed Advanced Telecommunication Computing Architecture (ATCA) instrumentation modules - IO blades and data switch blades, establishing a PCIe network on the ATCA shelf's back-plane. The data switch communicates to an external host computer through a PCIe data network. At the hardware management level, the system architecture takes advantage of ATCA native redundancy and hot swap specifications to implement fail-over substitution of IO or data switch blades. A redundant host scheme is also supported by the ATCA/PCIe platform. At the software level, PCIe provides implementation of hot plug services, which translate the hardware changes to the corresponding software/operating system devices. The paper presents how the ATCA and PCIe based system can be setup to perform with the desired degree of HA, thus being suitable for advanced Fusion control and data acquisition systems. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Mu2e - Research & Development

Current efforts are being conducted at Fermi National Laboratory to study potential violations in accepted theory that would otherwise suggest a restructuring of our fundamental understanding of the universe. Mu2e is one of these frontier projects that studies Charged Lepton Flavor Violation (CLFV) which if observed, would suggest physics beyond the Standard Model. Therefore, this note encompasses several projects that contribute to the fruition of Mu2e investigations. Due to the broad range of disciplinary inconsistencies that each project requires, all the work is being presented as a means of justifying contribution to Mu2e. The projects are comprised of a simulation exploring the extinction level of proton pulses after Recycler ring re-bunching by using G4beamline to simulate an 8GeV proton beam interaction with a titanium target, three Cherenkov radiation-based detectors and 2/3-fold and 3/3-fold coincidence rate analysis. Additionally, supplemental work for the implementation of a Micro Telecommunications Computing Architecture (TCA) crate to establish a peak finding algorithm to ensure that the out-of-time beam is less than 10$^{−10}$ fractional level along with single-layer inefficiency analysis on scintillation counters for the Cosmic-Ray Veto (CRV) analysis to ensure the overall inefficiency is 10$^{−4}$. Preliminary results have been achieved for the G4beamline simulation 2/3-fold and 3/3-fold coincidences which are in the order of 10$^{−9}$ and 10$^{−10}$, respectively. Only preliminary results of a triangular counter and four rectangular di-counters for the CRV have been realized. The microTCA crate development is still ongoing.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Characterization of Intrinsic Fiber Optic Temperature Sensors by In-core and Furnace Testing

Increased research and development in nuclear technology has raised the demand for novel sensors and instrumentation to meet data objectives, and survive in different conditions and environments, beyond conventional light water reactor (LWR) environments. Expediting the deployment of advanced nuclear technologies by developing, demonstrating, and qualifying advanced reactor fuel forms necessitates a deeper understanding of how irradiation affects fuels and materials' performance. To achieve a more comprehensive understanding of fuels and materials performance, researchers require more specialized experiments and measurements. The demand for innovative sensors to support nuclear fuel development arises from the complexity of materials' behavior under irradiation and the challenges of deploying instrumentation in Material Test Reactors (MTRs) for irradiation tests. Additionally, measurements of material properties require integrated measurement systems to characterize thermal properties, mechanical properties, chemistry, and microstructure [1]. Among the potential measurement techniques, optical fiber-based sensors have been identified as potential sensors to measure different physical phenomena such as temperature, strain, pressure, and fluid level. Optical fiber sensors have the capability to provide multi-sensing and multiplexing instrumentation, allowing the measurement of different physical parameters within a single sensor configuration, and transmitting data collected at multiple locations through a single fiber. They offer immunity to electromagnetic interference, electrical passivity, compatibility with various sensing methodologies, and cost-effectiveness. Beyond their widespread use in telecommunications, silica fiber-based instruments are utilized in industrial applications, even at temperatures reaching 300?400°C, such as distributed temperature sensing in oil and gas recovery. The Department of Energy (DOE) is interested in using fiber optics to support fuel cycle development [2]. Fiber optics are an excellent candidate for harsh environment sensing, including sensing at very high temperatures (1900oC for sapphire optical fibers). Distributed fiber optic sensing has been deployed in other harsh environments like coal gasification plants [3]. Distributed strain sensing, which operates similarly to distributed temperature sensing, has been deployed to monitor underground mines and fibers have been imbedded in soil to monitor sink-hole development [4][5]. The application of fiber optic sensors to advanced reactor development is a promising area of research.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

YOU-ONLY-LOOK-ONCE (YOLO) FOR RADIO FREQUENCY SIGNAL CLASSIFICATION

We propose a method that uses deep learning (DL) to identify and frame various signals that are present in an environment. This DL framework is based on the You Only Look Once (YOLO) object detection pipeline Our work demonstrates a specific application of high performance computing and computer vision to the field of telecommunications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

An Erlang-Based Front End Framework for Accelerator Controls

We have developed a new front-end framework for the ACNET control system in Erlang. Erlang is a functional programming language developed for real-time telecommunications applications. The primary task of the front-end software is to connect the control system with drivers collecting data from individual field bus devices. Erlang's concurrency and message passing support have proven well-suited for managing large numbers of independent ACNET client requests for front-end data. Other Erlang features which make it particularly well-suited for a front-end framework include fault-tolerance with process monitoring and restarting, real-time response,and the ability to change code in running systems. Erlang's interactive shell and dynamic typing make writing and running unit tests an easy part of the development process. Erlang includes mechanisms for distributing applications which we will use for deploying our framework to multiple front-ends, along with a configured s et of device drivers. We've developed Erlang code to use Fermilab's TCLK event distribution clock and Erlang's interface to C/C++ allows hardware-specific driver access.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Distributed and Secure Spectrum Sharing for 5G and 6G Networks

Secure spectrum sharing or spectrum co-existence of multiple 5G networks and future 6G networks is a powerful enabler technology. The National Spectrum Strategy (NSS) published by the White House in November, 2023, and the subsequent NSS implementation plan led by the National Telecommunication and Information Administration (NTIA) is the driver of a national effort to enable co-existence of government incumbents and commercial networks in selected spectrum bands. Cellular networks such as 5G & 6G and non-cellular Wi-Fi 6E & 7 are the prominent wireless technologies considered for co-existence with incumbent wireless links. Security of the spectrum sharing solutions is a must to make this transformation of spectrum use possible, specially for mission critical communications. However, current spectrum sharing solutions rely on centralized data bases with inherent vulnerabilities. This paper focuses on secure spectrum sharing among multiple 5G networks using unlicensed and shared frequency bands. It presents an innovative AI/ML based distributed spectrum sharing approach that can be autonomously used by multiple networks. Each sharing network uses its own observation of the Radio Frequency (RF) environment, which consists of RF measurements reported from the 5G User Equipment (UE), to adjust the transmission power levels for secure co-existence. Data is presented to illustrate the superior performance of this solution compared to other spectrum sharing solutions where each network can utilize usage data of the other networks. Finally it discusses how this efficient spectrum sharing solution can evolve in the future for the 6G networks.

5G↗
DOE OSTI2026

Entropy-defect synergy for dual luminescence mechanism in spinel: Time-resolved anti-counterfeiting and fingerprint visualization

Multimodal luminescent materials, while promising for anti-counterfeiting, often lack dynamic time-dependent responses and controllable spatial distribution, limiting their encryption capabilities in the spatiotemporal dimension. Here, this work presents a coordinated control strategy based on entropy and defect engineering, and uses a backpropagation (BP) neural network for material screening to successfully prepare spinel Mg 0.8 (Fe 0.04 Co 0.04 Ni 0.04 Cu 0.04 Zn 0.04 )Cr 2 O 4 (MgA 5 CO) phosphors with time-dependent dynamic luminescence behavior. This phosphor simultaneously activated the d-d transition luminescence (∼618 nm) derived from Co 2+ /Cr 3+ and the defect luminescence (∼398 nm) related to zinc vacancies (V Zn ) in a single-phase solid solution. The phosphor exhibits a time-dependent color evolution from pink to purple under fixed-wavelength excitation, due to the different excited-state dynamics and decay lifetimes associated with the d-d transition and defect luminescence. Structural characterization and spectral analysis confirmed the existence of V Zn and its significant role in defect luminescence process. The fluorescent and dynamic luminescent properties of entropy-based spinel oxide enable its use in advanced anti-counterfeiting applications like fingerprint recognition and color-changing dedicated anti-counterfeiting mark, showing promise in high-end and time-dynamic anti-counterfeiting fields. This research not only developed a new type of fluorescent dynamic anti-counterfeiting material, but also provided a new idea for constructing advanced optical functional materials with multiple luminescence mechanisms.

Defect project↗
DOE OSTI2025

Topochemical Synthesis and Electronic Structure of High-Crystallinity Infinite-Layer Nickelates on an Orthorhombic Substrate

Superconductivity in infinite-layer nickelates has stirred much research interest, to which questions regarding the nature of superconductivity remain elusive. A critical leap forward to address these intricate questions is through the growth of high-crystallinity infinite-layer nickelates, including the “parent” phase. Here, we report the synthesis of a high-quality thin-film nickelate, NdNiO 2 . This is achieved through the growth of a perovskite precursor phase (NdNiO 3 ) of superior crystallinity on the NdGaO 3 substrate by off-axis RF magnetron sputtering and a low-temperature topochemical reduction using NaH. We observe a nonlinear Hall effect at low temperatures in this “non-doped” phase. We further study the electronic properties using advanced X-ray scattering and first-principles calculations. We observe spectroscopic indications of the enhanced two-dimensionality and a reduced hybridization of Nd 5d and Ni 3d orbitals. These findings unlock new pathways for preparing high-quality infinite-layer nickelates and provide new insights into the intrinsic features of these compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Network traffic control for multi-homed end-hosts via SDN

Software-defined networking (SDN) is an emerging technology of efficiently controlling and managing computer networks, such as in data centres, wide-area networks, as well as in ubiquitous communication. In this study, the authors explore the idea of embedding the SDN components, represented by SDN controller and virtual switch, in end-hosts to improve network performance. In particular, the authors consider load balancing across multiple network interfaces on end-hosts with different link capacity scenarios. The authors have explored and implemented different SDN-based load-balancing approaches based on OpenFlow software switches, and have demonstrated the feasibility and the potential of this approach. The proposed system has been evaluated with MultiPath transmission control protocol (MPTCP). Furthermore, the proposed results demonstrated the potential of applying the SDN concepts on multi-homed devices resulting in an increase in achieved throughput of 55% compared to the legacy single network approach and 10% compared to the MPTCP.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Chiral Kirigami for Bend‐Tolerant Reconfigurable Hologram with Continuously Variable Chirality Measures

Abstract Despite the commonality of static holograms, the holography with multiple information layers and reconfigurable grey‐scale images at communication frequencies remain a confluence of scientific challenges. One well‐known difficulty is the simultaneous modulation of phase and amplitude of electromagnetic wavefronts with a high modulation depth. A less appreciated challenge is scrambling of the information and images with hologram bending. Here, this work shows that chirality‐guided pixelation of plasmonic kirigami sheets enables tunable multiplexed holography at terahertz (THz) frequencies. The convex and concave structures with slanted Au strips exhibit gradual variations in geometries facilitating modulation of light ellipticity reaching 40 deg. Real‐time switching of 3D images of the letter “ M ” and the Mona Lisa demonstrates the possibility of complex grey‐scale information content and importance of continuously variable mirror asymmetry. Microscale chirality measures of each pixel experiences little change with bending while retaining controllable reconfigurability upon stretching, which translates to remarkable resilience of chiral holograms to bending. Simplicity of their design with local chirality measures opens the door to information technologies with fault‐tolerant THz encryption, wearable holographic devices, and new communication technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Botnet behaviour analysis: How would a data analytics-based system with minimum a priori information perform?

Botnets, as one of the most aggressive threats, has used different techniques, topologies, and communication protocols in different stages of their lifecycle since 2003. Hence, identifying botnets has become very challenging specifically given that they can upgrade their methodology at any time. Various detection approaches have been proposed by the cyber-security researchers, focusing on different aspects of these threats. In this work, 5 different botnet detection approaches are investigated. These systems are selected based on the technique used and type of data used where 2 are public rule–based systems (BotHunter and Snort) and the other 3 use machine learning algorithm with different feature extraction methods (packet payload based and traffic flow based). On the other hand, 4 of these systems are based on a priori knowledge while one is using minimum a priori information. The objective here is to evaluate the effectiveness of these approaches under different scenarios (eg, multi-botnet and single-botnet classifications) as well as exploring how a system with minimum a priori information would perform. The goal is to investigate if a system with minimum a priori information could result in a competitive performance compared to systems using a priori knowledge. The evaluation is shown on 24 publicly available botnet data sets. Results indicate that a machine learning–based system with minimum a priori information not only achieves a very high performance but also generalizes much better than the other systems evaluated on a wide range of botnet structures (from centralized to decentralized botnets).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Search for a charged Higgs boson in pp collisions at √s = 8 TeV

Our search for a charged Higgs boson is performed with a data sample corresponding to an integrated luminosity of 19.7 ± 0.5 fb -1 collected with the CMS detector in proton-proton collisions at √s=8,TeV. The charged Higgs boson is searched for in top quark decays for m H± < m t - m b, and in the direct production pp → t(b)H ± for m H± > m t - m b. The H ± → τ ± ν τ and H ± → tb decay modes in the final states τ h +jets, μτ h , ℓ+jets, and ℓℓ’ (ℓ =e, μ) are considered in the search. No signal is observed and 95% confidence level upper limits are set on the charged Higgs boson production. Furthermore, a model-independent upper limit on the product branching fraction B(t→H±b)B(H±→τ±ντ)=1.2-0.15% is obtained in the mass range m H± = 80–160 GeV, while the upper limit on the cross section times branching fraction σ(pp→t(b)H±)B(H ± → τ ± ν τ )=0.38-0.025 pb is set in the mass range m H+ = 180–600 GeV. Here, σ(pp → t(b)H±) stands for the cross section sum σ(pp→t¯(b)H+)+σ(pp→t(b¯)H-). Assuming B(H ± →tb)=1, an upper limit on σ(pp → t(b)H±) of 2.0–0.13 pb is set for m H± = 180–600 GeV. The combination of all considered decay modes and final states is used to set exclusion limits in the m H ± -tan β parameter space in different MSSM benchmark scenarios.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Indian summer monsoon variability forecasts in the North American multimodel ensemble

The representation of the seasonal mean and interannual variability of the Indian summer monsoon rainfall (ISMR) in nine global ocean-atmosphere coupled models that participated in the North American Multimodal Ensemble (NMME) phase 1 (NMME:1), and in nine global ocean-atmosphere coupled models participating in the NMME phase 2 (NMME:2) from 1982–2009, is evaluated over the Indo-Pacific domain with May initial conditions. The multi-model ensemble (MME) represents the Indian monsoon rainfall with modest skill and systematic biases. There is no significant improvement in the seasonal forecast skill or interannual variability of ISMR in NMME:2 as compared to NMME:1. The NMME skillfully predicts seasonal mean sea surface temperature (SST) and some of the teleconnections with seasonal mean rainfall. However, the SST-rainfall teleconnections are stronger in the NMME than observed. The NMME is not able to capture the extremes of seasonal mean rainfall and the simulated Indian Ocean-monsoon teleconnections are opposite to what are observed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Experimenting in the cloud: The digital divide's impact on innovation

This paper builds on a recent National Science Foundation working paper that identified a strong association between cloud use and various types of innovation but did not consider whether 1) cloud adoption is a reliable indicator of the innovation orientation of a firm, or 2) cloud adoption enables various types of innovation. We estimate propensity score matching and endogenous treatment effect models to control for innovation orientation, producing evidence to test the second explanation. Here, findings support an enabling effect of the cloud on innovation providing concrete evidence of the adverse impact of the digital divide.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗