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At least 613 records · Page 34

DIGITAL APPLICATIONS USING REAL-TIME VEHICLE EXHAUST INFORMATION

Vehicle emission is a major source of air pollution that causes a significant number of deaths globally. It has a profound impact on energy and the environment as well. The existing vehicle emission monitoring system is unable to help mitigating the pollution properly and therefore, requires precise real-time pollution measurement. The purpose of this paper is to discuss novel applications using the real-time measurement of pollutants from a vehicle tailpipe where exhaust gases enter the environment. Today, it is possible to measure such emission due to the emergence of affordable digital technologies such as the Internet of Things (IoT), wireless connectivity, cloud platform, and artificial intelligence. This paper discusses how digital technologies can be used for real-time monitoring of NOx gas as a measure of vehicle emission and predictive analytics applications. A description of data collection and pre-processing methodologies, actual collected data, and an approach to identify patterns between inputs such as vehicle speed and altitude and output such as NOx emission are included. Applying a simple neural network has produced promising results and is a first step towards developing predictive applications.

Digital, Vehicle Exhaust, IoT, AI, 1.4.2, Predicti↗

Digital risk analysis in nuclear engineering projects: Designing for safety, performance, reliability, and security

Cyber-informed engineering and security-by-design frameworks are important in promoting the need to identify cybersecurity concerns early in the systems engineering lifecycle so risks from adversarial cyber-attacks can be eliminated or reduced through engineering design practices. In addition to adversarial risk, risk in operational technology systems also includes non-adversarial and unintentional risk from other factors such as human performance errors, environmental conditions, design flaws, and device degradation or failure. This paper introduces a new concept for characterizing digital risk, both adversarial and non-adversarial, and provides the basis for initial research into a novel digital risk analysis approach focused on incorporating attack difficulty into a multi-attribute analysis technique using robust decision-making. This digital risk characterization is also used to frame a discussion on the challenges of competing objectives and competing stakeholder requirements in an integrated energy system project that incorporates a small modular reactor and industrial facility.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

FAIR AI models in high energy physics

Abstract The findable, accessible, interoperable, and reusable (FAIR) data principles provide a framework for examining, evaluating, and improving how data is shared to facilitate scientific discovery. Generalizing these principles to research software and other digital products is an active area of research. Machine learning models—algorithms that have been trained on data without being explicitly programmed—and more generally, artificial intelligence (AI) models, are an important target for this because of the ever-increasing pace with which AI is transforming scientific domains, such as experimental high energy physics (HEP). In this paper, we propose a practical definition of FAIR principles for AI models in HEP and describe a template for the application of these principles. We demonstrate the template’s use with an example AI model applied to HEP, in which a graph neural network is used to identify Higgs bosons decaying to two bottom quarks. We report on the robustness of this FAIR AI model, its portability across hardware architectures and software frameworks, and its interpretability.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Geoscience Laser Altimeter System: Characteristics and Performance of the Altimeter Receiver

The Geoscience Laser Altimeter System (GLAS) on board ICESat spacecraft measures the surface height (altimetry) via the time of flight of its 1064 nm laser pulse. The GLAS laser transmitter produces 6 ns wide pulses with 70 mJ energy at 1064 nm at a 40 Hz rate. The altimeter receiver consists of a telescope, aft optics, a silicon avalanche photodiode, and electronic amplifiers. The transmitted and echo pulse waveforms are digitized at 1 GHz rate. The laser pulse time of flight is determined on the ground from the two digitized pulse waveforms and their positions in the full waveform record (about 5.4 ms ong) by computing the pulse centroids or by curve fitting. The GLAS receiver algorithms in on board software selects the two waveform segments containing the transmitted and the echo pulses and sends them to ground. The probability of echo pulse detection and the accuracy of time of flight measurement depend on the received signal level, the background light within the receiver field of view, the inherent detector and amplifier noise, the quantization of the digitizer, and some times by cloud obscurations. A receiver model has been developed to calculate the probability of detection and accuracy of the altimeter measurements with these noise sources. From prelaunch testing, the minimum detectable echo pulse energy for 90% detection probability was about 0.1 fj/pulse onto the detector. Such a receiver sensitivity allows GLAS to measure the surface height through clouds with optical density less than 2. The echo pulse energy required to achieve 10 cm ranging accuracy was found to be about 3 times higher than the minimum detectable signal level. The smallest single shot range measurement error, which was determined by ranging to a fixed target with strong echo pulses and no background light, was 2 to 3cm. The maximum linear response echo pulse energy was 10 fJ/pulse for the strongest echo signals, assuming a Lambertian scattering snow surface, clear sky atmosphere transmission, and no pulse width spreading due to surface slopes. Results from the initial 38 days of GLAS operation on-orbit with Laser 1, showed the echo pulse energies varied, as expected, over a wide dynamic range due to the variability of atmosphere transmission and Earth surface characteristics. The receiver was able to reliably detect the ground surface echoes and measure time of flight under such dynamic conditions, except when there were dense clouds. When over Antarctica, the echo pulse energies were several times stronger than predicted. This suggests that the 1064 nm backscattering from the snow pack and ice-sheet &ce are not completely Lambertian but is somewhat peaked at opposit.ion. With Laser 1, the peak amplitude of the echo pulses from flat ice sheets under clear sky conditions exceeded the linear response range of the receiver, causing some pulse waveform distortion due to saturation. We have characterized the effects of receiver saturation on the time of flight, pulse width, and pulse energy measurements for flat surface by testing a night spare detector in the lab with simulated echo pulses. A data processing algorithm that minimizes the errors due to saturation for these measurements are described.

Sun, Xiao-Li↗

Santa Barbara Desalination Digital Twin Technical Report

A digital twin is a computer model that has sufficient breadth and fidelity to enable diagnostic and predictive analyses for outputs of interest. We have constructed a digital twin of the SB desal plant using the ProteusLib software developed for NAWI under task 4.2.2, and specifically the ProteusLib models of pumps, filters, mixers, splitters, and reverse osmosis units and a seawater property model. The steps needed to configure this digital twin with the real conditions of the SB desal plant are: (1) Data reconciliation, which is gathering the data and plant connectivity and ensure that all relevant values are present and in the correct units and validating the data using material and energy balances, and correct for errors, gaps, or deviations; (2) Parameter estimation, which is matching model parameters with data from previous step, filling missing parameters with initial estimates, then iteratively refining estimated values. Once we completed the digital twin, we used the optimization capabilities of ProteusLib to compute outputs of interest over a chosen range of inputs. The primary output of interest to the owners of the plant is its specific energy consumption (kWh/acre-foot). The remainder of this report will provide more detail on the data reconciliation, parameter estimation, and analyses we performed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Wind turbine drivetrains: state-of-the-art technologies and future development trends

Abstract. This paper presents the state-of-the-art technologies and development trends of wind turbine drivetrains – the system that converts kinetic energy of the wind to electrical energy – in different stages of their life cycle: design, manufacturing, installation, operation, lifetime extension, decommissioning and recycling. Offshore development and digitalization are also a focal point in this study. Drivetrain in this context includes the whole power conversion system: main bearing, shafts, gearbox, generator and power converter. The main aim of this article is to review the drivetrain technology development as well as to identify future challenges and research gaps. The main challenges in drivetrain research identified in this paper include drivetrain dynamic responses in large or floating turbines, aerodynamic and farm control effects, use of rare-earth material in generators, improving reliability through prognostics, and use of advances in digitalization. These challenges illustrate the multidisciplinary aspect of wind turbine drivetrains, which emphasizes the need for more interdisciplinary research and collaboration.

17 WIND ENERGY↗

Synchrotron light source X-ray detection with Low-Gain Avalanche Diodes

Abstract Low Gain Avalanche Diodes (LGADs) represent the state-of-the-art in timing measurements and will instrument the future Timing Detectors of ATLAS and CMS for the High-Luminosity LHC. While initially conceived as a sensor for charged particles, the intrinsic gain of LGADs makes it possible to detect low-energy X-rays with good energy resolution and excellent time resolution (tens of picoseconds). Using the Stanford Synchrotron Radiation Lightsource (SSRL) at SLAC, several LGADs designs were characterized with energies from 5 to 70 keV. The SSRL provides 10 ps pulsed X-ray bunches separated by 2 ns intervals with an energy dispersion (ΔE/E) of 10 -4 . LGADs from Hamamatsu Photonics (HPK) and Brookhaven National Laboratory (BNL) with different thicknesses ranging from 20 μm to 50 μm and different gain layer designs were read out using fast amplification boards and digitized with a high bandwidth and high sampling rate oscilloscope. PIN devices from HPK and AC-LGADs from BNL were characterized as well. A systematic and detailed characterization of the devices' energy linearity, resolution, and time resolution as a function of X-ray energy was performed for different biasing voltages at room temperature and are reported in this work. The charge collection and multiplication mechanism were simulated using Geant4 and TCAD Sentaurus, providing an important handle for interpreting the data.

Instruments & Instrumentation↗

Georectified polygon database of ground-mounted large-scale solar photovoltaic sites in the United States.

Over 4,400 large-scale solar photovoltaic (LSPV) facilities operate in the United States as of December 2021, representing more than 60 gigawatts of electric energy capacity. Of these, over 3,900 are ground-mounted LSPV facilities with capacities of 1 megawatt direct current (MW dc ) or more. Ground-mounted LSPV installations continue increasing, with more than 400 projects appearing online in 2021 alone; however, a comprehensive, publicly available georectified dataset including spatial footprints of these facilities is lacking. The United States Large-Scale Solar Photovoltaic Database (USPVDB) was developed to fill this gap. Using US Energy Information Administration (EIA) data, locations of 3,699 LSPV facilities were verified using high-resolution aerial imagery, polygons were digitized around panel arrays, and attributes were appended. Quality assurance and control were achieved via team peer review and comparison to other US PV datasets. Data are publicly available via an interactive web application and multiple downloadable formats, including: comma-separated value (CSV), application programming interface (API), and GIS shapefile and GeoJSON.

14 SOLAR ENERGY↗

Organo–organic and organo–mineral interfaces in soil at the nanometer scale

The capacity of soil as a carbon (C) sink is mediated by interactions between organic matter and mineral phases. However, previously proposed layered accumulation of organic matter within aggregate organo–mineral microstructures has not yet been confirmed by direct visualization at the necessary nanometer-scale spatial resolution. Here, we identify disordered micrometer-size organic phases rather than previously reported ordered gradients in C functional groups. Using cryo-electron microscopy with electron energy loss spectroscopy (EELS), we show organo–organic interfaces in contrast to exclusively organo–mineral interfaces. Single-digit nanometer-size layers of C forms were detected at the organo–organic interface, showing alkyl C and nitrogen (N) enrichment (by 4 and 7%, respectively). At the organo–mineral interface, 88% (72–92%) and 33% (16–53%) enrichment of N and oxidized C, respectively, indicate different stabilization processes than at organo–organic interfaces. However, N enrichment at both interface types points towards the importance of N-rich residues for greater C sequestration.

58 GEOSCIENCES↗

ASCR@40: Highlights and Impacts of ASCR’s Programs

A report compiled by the ASCAC Subcommittee on the 40-year history of ASCR for the U.S. Department of Energy’s Office of Advanced Scientific Computing Research. The Office of Advanced Scientific Computing Research (ASCR) sits within the Office of Science in the Department of Energy (DOE). Per their web pages, “the mission of the ASCR program is to discover, develop, and deploy computational and networking capabilities to analyze, model, simulate, and predict complex phenomena important to the DOE.” This succinct statement encompasses a wide range of responsibilities for computing and networking facilities; for procuring, deploying, and operating high performance computing, networking, and storage resources; for basic research in mathematics and computer science; for developing and sustaining a large body of software; and for partnering with organizations across the Office of Science and beyond. While its mission statement may seem very contemporary, the roots of ASCR are quite deep—long predating the creation of DOE. Applied mathematics and advanced computing were both elements of the Theoretical Division of the Manhattan Project. In the early 1950s, the Manhattan Project scientist and mathematician John von Neumann, then a commissioner for the AEC (Atomic Energy Commission), advocated for the creation of a Mathematics program to support the continued development and applications of digital computing. Los Alamos National Laboratory (LANL) scientist John Pasta created such a program to fund researchers at universities and AEC laboratories. Under several organizational name changes, this program has persisted ever since, and would eventually grow to become ASCR.

97 MATHEMATICS AND COMPUTING↗

ATHENA: Analytical Tool for Heterogeneous Neuromorphic Architectures

The ASC program seeks to use machine learning to improve efficiencies in its stockpile stewardship mission. Moreover, there is a growing market for technologies dedicated to accelerating AI workloads. Many of these emerging architectures promise to provide savings in energy efficiency, area, and latency when compared to traditional CPUs for these types of applications — neuromorphic analog and digital technologies provide both low-power and configurable acceleration of challenging artificial intelligence (AI) algorithms. If designed into a heterogeneous system with other accelerators and conventional compute nodes, these technologies have the potential to augment the capabilities of traditional High Performance Computing (HPC) platforms [5]. This expanded computation space requires not only a new approach to physics simulation, but the ability to evaluate and analyze next-generation architectures specialized for AI/ML workloads in both traditional HPC and embedded ND applications. Developing this capability will enable ASC to understand how this hardware performs in both HPC and ND environments, improve our ability to port our applications, guide the development of computing hardware, and inform vendor interactions, leading them toward solutions that address ASC’s unique requirements.

97 MATHEMATICS AND COMPUTING↗

Multilevel Cybersecurity for Photovoltaic Systems

The motivation behind this project is to protect critical infrastructure in electric power generation pertaining to solar photovoltaic (PV) systems. This growing renewable energy resource is becoming a more vital part of the nation’s energy portfolio, particularly since it has achieved grid-parity to existing generation methods in terms of cost. It is thus vital that steps be taken to ensure the cybersecurity of these assets. The project goal was to devise a multilevel cybersecurity solution to address PV security gaps at the inverter and system levels, and field test the solution under the supervision and review of a US-based solar inverter manufacturer and PV installer/operator. A two-level cyberattack defense approach was formulated whereby the first level, the solar inverter level, hardens individual devices and achieves a deeply cyber-secure inverter. The inverter level security involves a multi-layer defense-in-depth approach for securing the inverter while also providing data for the system level algorithms. The second level, the system level, addresses intrusion detection and restoration involving an ensemble of inverters and relevant systems.

14 SOLAR ENERGY↗

Development of LANDSAT Derived Forest Cover Information for Integration into Adirondack Park GIS

Based upon observed changes in timber harvest practices partially attributable to forest biomass removable for energy supply purposes, the Adirondack Park Agency began in 1979 a multi-year project to implement a digital geographic information system (GIS). An initial developmental task was an inventory of forest cover information and analysis of forest resource change and availability. While developing the GIS, a pilot project was undertaken to evaluate the usefulness of LANDSAT derived land cover information for this purpose, and to explore the integration of LANDSAT data into the GIS. The prototype LANDSAT analysis project involved: (1) the use of both recent and historic data to derive land cover information for two dates; and (2) comparison of land cover over time to determine quantitative and geographic changes. The "recent data," 1978 full foliage data over portions of four LANDSAT scenes, was classified, using ground truth derived training samples in various forested and non-forested categories. Forested categories include the following: northern hardwoods, pine, spruce-fir, and pine plantation, while nonforested categories include wet-conifer, pasture, grassland, urban, exposed soil, agriculture, and water.

Curran, R. P.↗

Constitutive Modeling of the Facesheet to Core Interface in Honeycomb Sandwich Panels Subject to Mode I Delamination

A new cohesive zone traction-separation law, which includes the effects of fiber bridging, has been developed, implemented with a finite element (FE) model, and applied to simulate the delamination between the facesheet and core of a composite honeycomb sandwich panel. The proposed traction-separation law includes a standard initial cohesive component, which accounts for the initial interfacial stiffness and energy release rate, along with a new component to account for the fiber bridging contribution to the delamination process. Single cantilever beam tests on aluminum honeycomb sandwich panels with carbon fiber reinforced polymer facesheets were used to characterize and evaluate the new formulation and its finite element implementation. These tests, designed to evaluate the mode I toughness of the facesheet to core interface, exhibited significant fiber bridging and large crack process zones, giving rise to a concave downward concave upward pre-peak shape in the load-displacement curve. Unlike standard cohesive formulations, the proposed formulation captures this observed shape, and its results have been shown to be in excellent quantitative agreement with experimental load-displacement and apparent critical energy release rate results, representative of a payload fairing structure, as well as local strain fields measured with digital image correlation.

composites↗

De-Risking Field Deployment of Power System Innovations Using Hardware-in-the-Loop Experiments

The last decade has seen needs for integrating new technologies in power system. Unlike other industries, field mis-operation of novel technologies in power system can create heavy economic losses. Thus, de-risking field deployment is critical. This webinar will provide background on technology readiness level introduced by the space industry and the use of these readiness levels in power industry to assess the maturity level of power system technologies. This webinar will discuss the different approaches used to de-risk field deployment of controller technologies and power hardware technologies. This webinar will also discuss the challenges and limitations of these de-risking approaches. Finally, the webinar will provide results from hardware-in-the-loop experiments performed at National Renewable Energy Laboratory.

controller hardware-in-the-loop↗

Mechanical properties and strain localization of WA-DED printed P91 steel

This paper discusses a P91 steel block that was additively manufactured by wire arc direct energy deposition (WA-DED) followed by two types of post-process heat treatment (PPHT). Vickers microhardness and digital image correlation tensile tests were performed along the building direction. The global mechanical properties (i.e., microhardness and tensile properties) and the local mechanical responses (i.e., hardness fluctuation and strain localization) were systematically investigated. Results showed that (1) all P91 specimens showed higher strengths than American Society of Mechanical Engineers standard requirements for wrought P91 steel, (2) the as-printed P91 exhibited much higher average hardness and fluctuations than that after PPHT, (3) PPHT reduced P91 strengths but improved the ductility significantly, and (4) strain localization presented in the as-printed specimen during uniform deformation in tensile tests. The hardness fluctuation and strain localization along the building direction of the AP P91 were caused by different thermal histories received during WA-DED. The study indicated that PPHT, ideally tempering-only heat treatment, is necessary for the WA-DED printed P91 steel.

Mechanical properties↗

Smart Manufacturing Pathways for Industrial Decarbonization and Thermal Process Intensification

Rapid decarbonization is fast becoming the primary environmental and sustainability initiative for many economic sectors. Industry consumes more than 30 % of all primary energy in the United States and accounts for nearly 25 % of all greenhouse gas (GHG) emissions. More than 70 % of energy consumed by the industrial sector is related to thermal processes, which are also the largest contributors of carbon emissions, overwhelmingly due to the combustion of fossil fuels. Thermal process intensification (TPI) seeks to dramatically improve the energy performance of thermal systems through technology pillars focusing on alternative energy sources and processes, supplemental technologies, and waste heat management. The impacts of TPI have significant overlap with the goals of industrial decarbonization (ID) that seeks to phase out all GHG emissions from industrial activities. Emerging supplemental technologies such as smart manufacturing (SM) and the industrial internet of things (IoT) enable significant opportunities for the optimization of manufacturing processes. Combining strategies for TPI and ID with SM and IoT can open and enhance existing opportunities for saving time and energy via approaches such as tighter control of temperature zones, better adjustment of thermal systems for variations in production levels and feedstock properties, and increased process throughput. Data collected by smart processes will also enable new advanced solutions such as digital twins and machine learning algorithms to further improve thermal system savings. Herein, this paper examines the individual pathways of TPI, ID, and SM and how the combination of all three can accelerate energy and GHG reductions.

42 ENGINEERING↗

Messaging for Impact: Behavioral Science-Based Communication Strategies to Advance Energy Efficiency

Currently, five legal authorities require U.S. federal agencies to purchase energy-efficient products. However, compliance with these requirements has consistently been low (~55%). Recent surveys indicate that energy efficiency requirements are not communicated properly within federal agencies and energy-efficiency is not a top priority. In the constantly evolving energy industry, with many solutions for a clean energy future, effective communication methods are vital for widespread adoption of energy efficiency. We have been conducting experiments within the U.S. federal sector that test the effectiveness of messaging strategies developed by using behavioral science principles like loss aversion, framing, and herd behavior. This will identify effective communications methods that encourage energy efficiency adoption. In this study, we measure the effectiveness of different communication strategies by monitoring the web traffic of hyperlinks placed within our digital communications and outreach materials. To determine effective strategies that influence federal buyer behavior, the web traffic from subjects that received the behavioral science-based messaging (treatment group) is compared to that from subjects that received regular messaging (control group) for each of the strategies. This paper provides an overview of the behavioral science principles that we applied, data collection methods, and results of our analysis. Since the lack of effective communication of energy-efficiency policies is also a common problem in the private sector, the messaging strategies developed in this study can be applicable to other large private sector institutions

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗