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At least 1,081 records · Page 60

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Quaternary Semiconductor Cd1−xZnxTe1−ySey for High-Resolution, Room-Temperature Gamma-Ray Detection

The application of Cd0.9Zn0.1Te (CZT) single crystals, the primary choice for high-resolution, room-temperature compact gamma-ray detectors in the field of medical imaging and homeland security for the past three decades, is limited by the high cost of production and maintenance due to low detector grade crystal growth yield. The recent advent of its quaternary successor, Cd0.9Zn0.1Te1−ySey (CZTS), has exhibited remarkable crystal growth yield above 90% compared to that of ~33% for CZT. The inclusion of Se in appropriate stoichiometry in the CZT matrix is responsible for reducing the concentration of sub-grain boundary (SGB) networks which greatly enhances the compositional homogeneity and growth yield. SGB networks also host defect centers responsible for charge trapping, hence their reduced concentration ensures minimized charge trapping. Indeed, CZTS single crystals have shown remarkable improvement in electron charge transport properties and energy resolution over CZT detectors. However, our studies have found that the overall charge transport in CZTS is still limited by the hole trapping. In this article, we systematically review the advances in the CZTS growth techniques, its performance as room-temperature radiation detector, and the role of defects and their passivation studies needed to improve the performance of CZTS detectors further.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Performance Study of Virtual Frisch Grid CdZnTeSe Detectors

Nuclear detectors for x-ray and gamma-ray spectroscopy and imaging are a vital tool in many homeland security, medical imaging, astrophysics and other applications. Most of these applications require room-temperature operation due to the operational constraints imposed by a cryogenic cooling system. CdZnTe (CZT) has been the main material with the desired detection properties, and CZT crystals have been used commercially for three decades. However, CdZnTe still suffers from long-standing issues of high densities of performance-limiting intrinsic defects such as Te inclusions and networks of dislocation walls (sub-grain boundaries). A recently invented new quaternary material CdZnTeSe showed excellent material properties for radiation detection. The material was found to be free from dislocation networks, possess reduced Te inclusions, and have better compositional homogeneity. Virtual Frisch grid detectors were fabricated from crystals taken from a CdZnTeSe ingot that was grown by the traveling heater method. The detectors were fabricated from an as-grown ingot, bypassing the post-growth annealing process commonly practiced for industrial-grade CZT. The performances of the detectors were studied with different Frisch grid lengths using an amplifier shaping time ranging from 1–6 µs. The detectors showed high-quality spectroscopic performance with an as-measured energy resolution of ~1.1% at 662 keV for an optimum Frisch grid length of 3 mm. The charge collection was observed to enhance for longer Frisch grids.

47 OTHER INSTRUMENTATION↗

NASA NTRS2007

Electromechanical acoustic liner

A multi-resonator-based system responsive to acoustic waves includes at least two resonators, each including a bottom plate, side walls secured to the bottom plate, and a top plate disposed on top of the side walls. The top plate includes an orifice so that a portion of an incident acoustical wave compresses gas in the resonators. The bottom plate or the side walls include at least one compliant portion. A reciprocal electromechanical transducer coupled to the compliant portion of each of the resonators forms a first and second transducer/compliant composite. An electrical network is disposed between the reciprocal electromechanical transducer of the first and second resonator.

Sheplak, Mark↗

DOE OSTI2021

Icypaw

The Intermode Communication Protocol Wrapper, or Icypaw, structures and facilitates communication between endpoints in a network. It is used to connect various independent software and hardware components into one loosely organized system controllable from one or more locations. The code uses the MQTT protocol to communicate and enhances it with a useful framework. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-8293 O

Van Der Wall, JayW.↗

DOE OSTI2021

Short Term Plasticity for Artificial Neural Networks

Achieving efficient learning for AI systems was identified as a major challenge in the DOE's recently released, AI for Science , report. The human brain is capable of efficient and low-powered learning. It is likely that implementing brain-like principles will lead to more efficient AI systems. In this LDRD, I aim to contribute to this goal by creating a foundation for implementing and studying a brain phenomenon termed short term plasticity (STP) in spiking artificial neural networks within Sandia. First, data collected by the Allen Institute for Brain Science (AIBS) was analyzed to see if STP could be classified into types using the data collected. Although the data was inadequate at the time, AIBS has updated their database and created models that could be utilized in the future. Second, I began creating a software package to assess the ability of a Boltzmann machine utilizing STP to sample from national security data.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Advanced Tri-lab Software Environment (ATSE)

The Advanced Tri-lab Software Environment (ATSE) is an effort to build an open, modular, extensible, community-engaged, and vendor-adaptable software ecosystem that enables the prototyping of new technologies for improving the ASC computing environment. The initial target for ATSE is to accelerate the maturity of the Arm ecosystem for supporting ASC computing and the high-performance computing community more broadly. ATSE provides an integrated and optimized software stack that includes: 1) Application development environment and libraries including compilers, math libraries, tools, MPI, and OpenMP, 2) Low-level system software including optimized Linux, network stack, file systems, containers, and virtual machines, 3) Job scheduling and management including workload manager, application launcher, and user tools, and 4) System administration and management tools supporting booting, monitoring, and operating system image management. SAND2020-12377 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Younge, Andrew J.↗

NASA NTRS1991

Evolution of the large Deep Space Network antennas

The evolution of the largest antenna of the US NASA Deep Space Network (DSN) is described. The design, performance analysis, and measurement techniques, beginning with its initial 64-m operation at S-band (2295 MHz) in 1966 and continuing through the present ka-band (32-GHz) operation at 70 m, is described. Although their diameters and mountings differ, these parabolic antennas all employ a Cassegrainian feed system, and each antenna dish surface is constructed of precision-shaped perforated-aluminum panels that are secured to an open steel framework

Imbriale, William A.↗

DOE OSTI2024

Security Constrained Distributed Transaction Model for Multiple Prosumers

Massive access of renewable energy has prompted demand-side distributed resources to participate in regulation and improve flexibility of power systems. With large-scale access of massive, decentralized, and diverse distributed resources, demand-side market members have transformed from traditional “consumers” to “prosumers”. To explore the distributed transaction model of prosumers, in this paper, a multi-prosumer distributed transaction model is proposed, and the Conditional Value-at-Risk (CVaR) theory is applied to quantify potential risks caused by the stochastic characteristics inherited from renewable energy. First, a prosumer model under constraints of the distribution network including photovoltaic units, fuel cells, energy storage system, central air conditioning and flexible loads is established, and a multi-prosumer distributed transaction strategy is proposed to achieve power sharing among multiple prosumers. Second, a prosumer transaction model based on CVaR is constructed to measure risks inherited from the uncertainty of PV output within the prosumer and ensure safety of system operation in extreme PV output scenarios. Then, the alternating direction multiplier method (ADMM) is utilized to solve the constructed model efficiently. Finally, distributed transaction costs of prosumers are distributed fairly based on the generalized Nash equilibrium to maximize social benefits. Simulation results show the multi-prosumer distributed transaction mechanism established under the proposed generalized Nash equilibrium method can encourage power sharing among prosumers, increasing their own income and social benefits. Also, the CVaR can assist decision making of prosumers in weighting the risks and benefits, improving system resilience through energy management of prosumers.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

End-to-end Analytics for Grid Arch Design & All-hazard Assessment

Resiliency, reliability, and security of the next-generation smart grid depend upon leveraging advanced communication and computing technologies, integrating them with physical power systems, and developing real-time, fast, data-based applications to help in wide-area monitoring and control of the grid. Using a high sampling data rate from phasor measurement units (PMUs) to develop applications has opened the door to achieving the next-generation grid requirements. The North American Synchrophasor Initiative Network (NASPlnet) was developed in 2007-09 to create a standard and guide for PMU data exchanges. With the advancement in both networking and grid requirements, it is necessary to evaluate the performance of different NASPInet versions and their impact on applications. Therefore, we need a cyber-power cosimulation framework that supports very large-scale co-simulation capable of running in parallel, high-performance computing platforms and capturing real-life network behavior. This work presents a cyber-physical co-simulation testbed using NS3 to model the communication network, GridPACK to model the power grid, and HELICS as a co-simulation engine. Comparative analysis of latency in synchrophasor networks and a performance evaluation of a power system stabilizer application based on PMU data in an Institute of Electrical and Electronics Engineers 39-bus test system is presented using this co-simulation testbed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

A data-driven operational model for traffic at the Dallas Fort Worth International Airport

Airports are on the front line of significant innovations, allowing the movement of more people and goods faster, cheaper, and with greater convenience. As air travel continues to grow, airports will face challenges in responding to increasing passenger vehicle traffic, which leads to lower operational efficiency, poor air quality, and security concerns. This paper evaluates methods for traffic demand forecasting combined with traffic microsimulation, which will allow airport operations staff to accurately predict traffic and congestion. Using two years of detailed data describing individual vehicle arrivals and departures, aircraft movements, and weather at Dallas-Fort Worth (DFW) International Airport, we evaluate multiple prediction methods including the Auto Regressive Integrated Moving Average (ARIMA) family of models, traditional machine learning models, and DeepAR, a modern recurrent neural network (RNN). We find that these algorithms are able to capture the diurnal trends in the surface traffic, and all do very well when predicting the next 30 minutes of demand. Longer forecast horizons are moderately effective, demonstrating the challenge of this problem and highlighting promising techniques as well as potential areas for improvement. Traffic demand is not the only factor that contributes to terminal congestion, because temporary changes to the road network, such as a lane closure, can make benign traffic demand highly congested. Combining a demand forecast with a traffic microsimulation framework provides a complete picture of traffic and its consequences. The result is an operational intelligence platform for exploring policy changes, as well as infrastructure expansion and disruption scenarios. To demonstrate the value of this approach, we present results from a case study at DFW Airport assessing the impact of a policy change for vehicle routing in high demand scenarios. This framework can assist airports like DFW as they tackle daily operational challenges, as well as explore the integration of emerging technology and expansion of their services into long term plans.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Energy Storage Sizing, Placement and Valuation for Distribution Networks

SAND2023-05682O The Energy Storage Sizing, Placement, and Valuation for Distribution software allows a user to simulate sizing, placement, and operation of one or more storage assets on a distribution grid. Among its features are measuring differences to determine the best combinations, and options for configuring and comparing results. This new simulation capability leverages the Open Distribution System Simulator and the Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS). Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Tamrakar, Ujjwol↗

DOE OSTI2023

A 5G Enabled Adaptive Computing Workflow for Greener Power Grid

5G wireless technology can deliver higher data speeds, ultra low latency, more reliability, massive network capacity, increased availability, and a more uniform user experience to users. It brings additional power to help address the challenges brought by renewable integration and decarbonization. In this paper, a 5G enabled adaptive computing workflow tool has been presented that consists of various computing resources, such as 5G equipment, edge computing, cluster, Graphics processing unit (GPU) and cloud computing, with two examples showing technical feasibility for edge-grid-cloud interaction for real-time monitoring, security assessment, and forecasting. Benefiting from the high data transmission speed and massive connection capability of 5G, the workflow shows its potential to seamlessly integrate various applications at distributed and/or centralized locations to build more complex and powerful functions, with better flexibility.

5G technology, computational workflow, edge comput↗

DOE OSTI2026

Resilience Measurement Framework For Post-deployment Artificial Intelligence (ai) Integrated Systems

Resilience is largely defined as the ability to adapt or recover from adverse conditions, stresses, attacks, or compromises on systems that use or are enabled by digital resources. In Artificial Intelligence Management and Research for Advanced Networked Testbed Hub (AMARANTH), resilience is measured in the amount of time it took from the beginning of a testing period for the model to reach predictions outside of the original 95% confidence interval or using the Kullback-Leibler (KL) divergence theorem, the Population Stability Index (PSI), and traditional methods such as root mean squared error (RMSE) threshold. Artificial Intelligence (AI) model drift is of significant concern when deploying AI-integrated systems into critical and/or secure environments. Drift can impact resilience of the AI-integrated system post-deployment and requires consistent maintenance and upkeep to ensure the model is accurate and precise. To quantify model drift and predict the point when a model's drift becomes unacceptable, we describe using Kullback-Leibler (KL) divergence, Population Stability Index (PSI) and/or confidence interval width estimations to determine the point of failure and time to failure of a model post-deployment. Through simple code functions, the KL-divergence, PSI, confidence interval, and root mean squared (RMSE) point of failures can be used to derive when a model needs to be maintained as well as the impact of adversarial action through statistical means.

Yockey, Patience [Idaho National Laboratory (INL),↗

DOE OSTI2024

The Lithuania 100% Renewable Energy Study - Interim Results: Electricity System Scenarios for 2030 [Slides]

Lithuania's Energy Vision aims to achieve self-sufficiency in electricity generation by 2035 and transition to 100% renewable energy as soon as possible while maintaining affordability, reliability, and energy security. The Lithuania Energy Agency (LEA) is partnering with the National Renewable Energy Laboratory (NREL) to conduct the Lithuania 100% Renewable Energy Study (Lithuania 100) to provide evidence-based analysis for development of Lithuania's National Energy Independence Strategy. The Lithuania 100 Study leverages unique tools and capabilities of NREL to provide rigorous technical analysis of clean energy policies to achieve 100% renewable energy, and assess impacts on electricity grid operations, hydrogen system development, electricity distribution networks, air quality, and human health outcomes. The study is supported by a stakeholder committee chaired by the Ministry of Energy of Lithuania and implemented by four technical working groups. This report provides highlights of key interim results from modeling of Lithuania's near-term electricity grid through the year 2030. Results show that Lithuania has sufficient renewable energy potential, flexible generation capacity, and interconnection with neighboring European Union countries to reliably meet projected 2030 electricity demand with 100% renewable energy. A range of scenarios were modeled, each of which achieves at least 100% renewable energy in electricity, on average over the year, by 2030. Potential demands for hydrogen across industrial and transportation sectors were also evaluated, as well as the cost of hydrogen produced in Lithuania by 2030.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2005

Transformational Spaceport and Range Concept of Operations: A Vision to Transform Ground and Launch Operations

The Transformational Concept of Operations (CONOPS) provides a long-term, sustainable vision for future U.S. space transportation infrastructure and operations. This vision presents an interagency concept, developed cooperatively by the Department of Defense (DoD), the Federal Aviation Administration (FAA), and the National Aeronautics and Space Administration (NASA) for the upgrade, integration, and improved operation of major infrastructure elements of the nation s space access systems. The interagency vision described in the Transformational CONOPS would transform today s space launch infrastructure into a shared system that supports worldwide operations for a variety of users. The system concept is sufficiently flexible and adaptable to support new types of missions for exploration, commercial enterprise, and national security, as well as to endure further into the future when space transportation technology may be sufficiently advanced to enable routine public space travel as part of the global transportation system. The vision for future space transportation operations is based on a system-of-systems architecture that integrates the major elements of the future space transportation system - transportation nodes (spaceports), flight vehicles and payloads, tracking and communications assets, and flight traffic coordination centers - into a transportation network that concurrently accommodates multiple types of mission operators, payloads, and vehicle fleets. This system concept also establishes a common framework for defining a detailed CONOPS for the major elements of the future space transportation system. The resulting set of four CONOPS (see Figure 1 below) describes the common vision for a shared future space transportation system (FSTS) infrastructure from a variety of perspectives.

Source record↗

DOE OSTI2025

Sparse-Data Deep Learning Strategies for Radiographic Non-Destructive Testing

Radiography is an imaging technique used in a variety of applications, such as medical diagnosis, airport security, and nondestructive testing. We present a deep learning system for extracting information from radiographic images. We perform various prediction tasks using our system, including material classification and regression on the dimensions of a given object that is being radiographed. Our system is designed to address the sparse-data issue for radiographic nondestructive testing applications. It uses a radiographic simulation tool for synthetic data augmentation, and it uses transfer learning with a pre-trained convolutional neural network model. Using this system, our preliminary results indicate that the object geometry regression task saw an improvement of 70% in the R-squared value when using a multi-regime model. In addition, we increase the performance of the object material classification tasks by utilizing data from different imaging systems. In particular, using neutron imaging improved the material classification accuracy by 20% when compared to x-ray imaging.

convolutional neural networks↗

DOE OSTI2024

WEC as a multiport

SAND2025-00555O WEC as a multiport is a software tool that simplifies the modeling and design of ocean wave energy converters (WECs) using a multi-port network framework in the frequency domain. Users can simulate the dynamic interactions between WECs and ocean waves, optimizing energy extraction and system performance. This tool supports the analysis of complex wave energy systems, aiding in the development of efficient and effective WEC designs. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Coe, Ryan↗

DOE OSTI2021

Annual Stormwater Report for the Y-12 National Security Complex Oak Ridge, Tennessee

This is the eighth annual stormwater report prepared in accordance with the modified National Pollutant Discharge Elimination System permit issued to the Y-12 National Security Complex (Y-12) on April 1, 2014. This modified permit removed the authorization to augment flow in East Fork Poplar Creek (EFPC) and thus removed the requirement to sample this effluent in conjunction with other major outfalls on EFPC. The general condition of the site continues to improve. The repair of Outfall 014 is complete and sampling was performed in 2020 from the new Outfall 014 structure. This repair marks a significant improvement in the storm drain network infrastructure. There are several construction and demolition activities currently in progress at Y-12. These include the construction of the Uranium Processing Facility, the Mercury Treatment Facility on EFPC, the site-wide power grid upgrade, and the demolition of the Biology Complex. Current stormwater protections have proven effective in 2020; however, moving forward, these projects will present challenges for the protection of stormwater. Therefore, oversight of these activities, and all other construction and demolition projects, will continue to be a priority in 2021. Y-12 will continue to implement appropriate best management practices and reduce outside material storage areas where possible.

54 ENVIRONMENTAL SCIENCES↗