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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Role of climate goals and clean-air policies on reducing future air pollution deaths in China: a modelling study

Over 3 million people still die every year from diseases caused by exposure to outdoor PM 2.5 air pollution, and more than a quarter of these premature deaths occur in China. In addition to clean air policies that target pollution emissions, climate policies aimed at reducing fossil-fuel CO 2 emissions (e.g., to avoid 1.5°C of warming) may also dramatically improve air quality and public health. Yet there has been no comprehensive accounting of public health outcomes under different energy pathways and local clean air management decisions in China. In particular, further research is needed to understand the relationships among climate and clean air polices and future health burdens in China, where an aging population will further exacerbate the impacts of air pollution. Using a China-focused integrated assessment model (GCAM-China) and a dynamic emission projection model (DPEC), we project future Chinese air quality in scenarios spanning a range of global climate targets (i.e. 1.5°0C, 2°C, NDC, unambitious, baseline, and 4.5°C) as well as national clean air actions (i.e. 2015-pollution, current-pollution, and ambitious-pollution). We then evaluate the health impacts of PM2·5 air pollution of scenario matrix using the chemical transport model WRF-CMAQ and the latest epidemiological concentration–response (C-R) functions (i.e. GBD2019). We find that, without ambitious climate mitigation (e.g., under current NDC pledges), Chinese deaths related the PM2.5 air pollution do not substantially decrease—and often grow—by mid-century, regardless of clean air policies and air quality improvements. For example, in scenarios that track China’s current NDC pledge and deploy best-available pollution control technologies, PM 2.5 -related deaths in China decrease slightly by 2030 (to 1.2 million per year) but no further by mid-century (Ambitious-pollution-NDC-goals; 1.2 million deaths in 2050) despite substantial and continuous improvements in population-weighted air quality (27.2 to 16.0 µg/m 3 from 2030 to 2050). The contrary trends of improving air quality and increasing PM 2·5 -related deaths in many of our scenarios reveals the extent to which extra efforts are needed to compensate for the established fact of increasing age of China’s population in future. Substantial decreases in China’s PM 2.5 -related deaths and age-standardized death rates (e.g., decreasing by 0.3–0.5 million deaths and 10.2–14.2 per 100,000 population age-standardized death rates per year) thus require the sort of large-scale transition in energy sources entailed by scenarios that meet international climate goals to avoid 1.5°C and 2°C of warming (Ambitious-pollution-2°C- and 1.5°C-goals).

58 GEOSCIENCES↗
DOE OSTI2021

Calibration-Free Quantitative Analysis of Lithium-Ion Battery (LiB) Electrode Materials Using Laser-Induced Breakdown Spectroscopy (LIBS)

Recent years have seen a surge in the demand for high-performance battery electrode materials for automotive and various electronic device applications. Improving battery performance requires precise knowledge of the structure–composition properties of active electrode materials. To this effect, quantitative and precise estimation of the composition of advanced electrode materials, containing trace amounts of dopants, provide immense value toward developing next-generation high-capacity battery materials. Herein, we demonstrate the application of calibration-free laser-induced breakdown spectroscopy (LIBS) as a powerful analytical tool for rapid and reliable quantitative spectrochemical characterizations of layered Li metal oxide cathodes containing Mo and Cr dopants (<5 atom %). Specifically, we employ the LIBS using an internal calibration methodology to establish the quantitative elemental ratios of major (Ni, Mn, Co) and trace dopant (Cr, Mo) transition metals to bulk Li contents in diverse cathode material samples such as LiNi 0.5 Mn 0.5 O 2 (NM-50/50), LiNi 0.33 Mn 0.33 Co 0.33 O 2 (NMC), LiNi 0.317 Mn 0.317 Co 0.317 Cr 0.05 O 2 (Cr-doped NMC), and LiNi 0.5– x /2 Mn 0.5– x /2 Mo x O 2 ( x = 0.03, 0.04, 0.05) (Mo-doped NM-50/50) that were synthesized via sol–gel routes. The LIBS-estimated elemental compositions are in good agreement with the nominal stoichiometric values. Furthermore, ex situ LIBS characterizations presented here pave the path for future high-efficacy application of calibration-free quantitative LIBS for rapid in situ analyses of elemental composition changes in battery electrode materials under operation that need not resort to off-site analytical techniques requiring cumbersome sample preparations and/or external standards.

25 ENERGY STORAGE↗
DOE OSTI2024

Elucidating the Gas-Phase Behavior of Nitazene Analog Protomers Using Structures for Lossless Ion Manipulations Ion Mobility-Orbitrap Mass Spectrometry

2-benzylbenzimidazoles, or “nitazenes”, are a class of novel synthetic opioids (NSOs) that are increasingly being detected alongside fentanyl analogs and other opioids in drug overdose cases. Nitazenes can be 20x more potent than fentanyl but are not routinely tested for during postmortem or clinical toxicology drug screens; thus, their prevalence in drug overdose cases may be under-reported. Traditional analytical workflows utilizing liquid chromatography-tandem mass spectrometry (LC-MS/MS) often require additional confirmation with authentic reference standards to identify a novel nitazene. However, additional analytical measurements with ion mobility spectrometry (IMS) may provide a path towards reference-free identification, which would greatly accelerate NSO identification rates in toxicology labs. Presented here are the first IMS and collision cross section (CCS) measurements on a set of fourteen nitazene analogs using a Structures for Lossless Ion Manipulations (SLIM)-Orbitrap MS. All nitazenes exhibited two high intensity baseline-separated IMS distributions, which fentanyls and other drug and drug-like compounds also exhibit. Incorporating water into the electrospray ionization (ESI) solution caused the intensities of the higher mobility IMS distributions to increase the intensities of the lower mobility IMS distributions to decrease. Nitazenes lacking a nitro group at the R1 position exhibited the greatest shifts in signal intensities due to water. Furthermore, IMS-MS/MS experiments showed that the higher mobility IMS distributions of all nitazenes produced fragment ions with m/z 72, 100, and other low intensity fragments while the lower mobility IMS distributions only produced fragment ions with m/z 72 and 100. The IMS, solvent, and fragmentation studies provide experimental evidence that nitazenes potentially exhibit three gas-phase protomers. In conclusion, the cyclic IMS capability of SLIM was also employed to partially resolve four sets of structurally similar nitazene isomers (e.g., protonitazene/isotonitazene, butonitazene/isobutonitazene/secbutonitazene), showcasing the potential of using high-resolution IMS separations in MS-based workflows for reference-free identification of emerging nitazenes and other NSOs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Machine-learning accelerated geometry optimization in molecular simulation

Geometry optimization is an important part of both computational materials and surface science because it is the path to finding ground state atomic structures and reaction pathways. These properties are used in the estimation of thermodynamic and kinetic properties of molecular and crystal structures. This process is slow at the quantum level of theory because it involves an iterative calculation of forces using quantum chemical codes such as density functional theory (DFT), which are computationally expensive and which limit the speed of the optimization algorithms. It would be highly advantageous to accelerate this process because then one could do either the same amount of work in less time or more work in the same time. Here, we provide a neural network (NN) ensemble based active learning method to accelerate the local geometry optimization for multiple configurations simultaneously. We illustrate the acceleration on several case studies including bare metal surfaces, surfaces with adsorbates, and nudged elastic band for two reactions. In all cases, the accelerated method requires fewer DFT calculations than the standard method. In addition, we provide an Atomic Simulation Environment (ASE)-optimizer Python package to make the usage of the NN ensemble active learning for geometry optimization easier.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Role of the junction voltage on the overflow current in light-emitting diodes

Quantum-well (QW)-based light emitters, such as light-emitting diodes (LEDs) and lasers, of various semiconductor materials experience a reduction in their efficiency when operating at higher temperatures, a phenomenon referred to as “thermal droop.” Among the various claims on the origins of thermal droop, an increased overflow current with increasing temperatures is a common contender. Since overflow of carriers can only occur when the junction voltage 𝑉 Junction approaches the built-in voltage 𝑉 BI of any diodes, we develop a simple method relating the difference between 𝑉 Junction and 𝑉 BI to approximate the upper limit of overflow occurring in QW-based light-emitting diodes. The measured difference between 𝑉 Junction and 𝑉 BI of state-of-the-art commercial blue and green In⁢Ga⁢N-based LEDs at temperatures up to ∼450 K suggests negligible overflow. To further experimentally verify the absence of overflow, we perform temperature-dependent electron emission spectroscopy on the same commercial blue and green LEDs and find no evidence of thermally enhanced overflow carriers up to ∼450 K. In agreement with our claims that 𝑉 Junction must approach 𝑉 BI for overflow to occur, two-dimensional temperature-dependent electrical simulations of violet, blue, and green LEDs including alloy disorder and V-defects demonstrate that overflow can be significant in violet LEDs, where the small band offset between the In⁢Ga⁢N QW and Ga⁢N cladding layers due to the larger QW bandgap requires larger 𝑉 Junction to reach standard operating current densities, thereby approaching 𝑉 BI . By contrast, simulations indicate that overflow is negligible in blue and green LEDs, whose smaller QW bandgaps result in smaller quasi-Fermi levels difference to reach significant carrier injection, resulting in a 𝑉 Junction much smaller than 𝑉 BI up to large operating current densities. Considering that overflow is negligible in blue and longer-wavelength LEDs, and our observations of the large thermal droop occurring at low current densities, where Shockley-Read-Hall (SRH) recombination dominates, we conclude that thermally enhanced SRH processes are the most significant contributor to thermal droop. Finally, we also simulate the carrier densities in the different QWs of a multiple-QW LED and observe a reduction in the total carrier density at a given operating current density, which results in a decrease in the total Auger-Meitner current of the LED from just the thermally enhanced carrier redistribution among QWs without taking any possible additional temperature dependence of their recombination coefficients. Taking all this into account, minimizing thermal droop effects in LEDs can be achieved by a reduction in defect density, using wider band gap p-n junction-defining cladding layers, and operating at higher currents.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Utilizing machine learning to improve the precision of fluorescence imaging of cavity-generated spin squeezed states

We present a supervised learning model to calibrate the photon collection rate during the fluorescence imaging of cold atoms. The linear regression model finds the collection rate at each location on the sensor such that the atomic population difference equals that of a highly precise optical cavity measurement. This 192 variable regression results in a measurement variance 27% smaller than our previous single variable regression calibration. The measurement variance is now in agreement with the theoretical limit due to other known noise sources. This model efficiently trains in less than a minute on a standard personal computer's CPU and requires less than 10 min of data collection. Furthermore, the model is applicable across a large change in population difference and across data collected on different days.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Observation of W W γ Production and Search for H γ Production in Proton-Proton Collisions at s = 13 TeV

The observation of W W γ production in proton-proton collisions at a center-of-mass energy of 13 TeV with an integrated luminosity of 138 fb − 1 is presented. The observed (expected) significance is 5.6 (5.1) standard deviations. Events are selected by requiring exactly two leptons (one electron and one muon) of opposite charge, moderate missing transverse momentum, and a photon. The measured fiducial cross section for W W γ is 5.9 ± 0.8 ( stat ) ± 0.8 ( syst ) ± 0.7 ( modeling ) fb , in agreement with the next-to-leading order quantum chromodynamics prediction. The analysis is extended with a search for the associated production of the Higgs boson and a photon, which is generated by a coupling of the Higgs boson to light quarks. The result is used to constrain the Higgs boson couplings to light quarks. © 2024 CERN, for the CMS Collaboration 2024 CERN

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Grid-Forming and Grid-Following Inverter Comparison of Droop Response

With the increase in penetration of inverter-based resources (IBRs) in the electrical power system, the ability of these devices to provide grid support to the system has become a necessity. With standards previously developed for the interconnection requirements of grid-following inverters (GFLI) (most commonly photovoltaic inverters), it has been well documented how these inverters “should” respond to changes in voltage and frequency. However, with other IBRs such as grid-forming inverters (GFMIs) (used for energy storage systems, standalone systems, and as uninterruptable power supplies) these requirements are either: not yet documented, or require a more in deep analysis. With the increased interest in microgrids, GFMIs that can be paralleled onto a distribution system have become desired. With the proper control schemes, a GFMI can help maintain grid stability through fast response compared to rotating machines. This paper will present an experimental comparison of commercially available GFMI and GFLI ' responses to voltage and frequency deviation, as well as the GFMI operating as a standalone system and subjected to various changes in loads.

Grid Support, Inverter, Droop Control, Volt-VAR, F↗
DOE OSTI2022

Application-Driven Creation of Building Metadata Models with Semantic Sufficiency

Semantic metadata models such as Brick, RealEstateCore, Project Haystack, and BOT promise to simplify and lower the cost of developing software for smart buildings, enabling the widespread deployment of energy efficiency applications. However, creating these models remains a challenge. Despite recent advances in creating models from existing digital representations like point labels and architectural models, there is still no feedback mechanism to ensure that the human input to these methods results in a model that can actually support the desired software. In this paper, we introduce the notion of semantic sufficiency, a practical principle for semantic metadata model creation that asserts that a model is "finished" when it contains the metadata necessary to support a given set of applications. To support semantic sufficiency, we design a standard representation for capturing application metadata requirements and a templating system for generating common metadata model components with limited user input. We then construct an iterative model creation workflow that integrates metadata requirements to direct the model creation effort, and present several novel optimizations that increase the model utility while minimizing the effort by a human operator. These new abstractions for model creation and validation lower model development costs and ensure the utility of the resulting model, thus facilitating the adoption of intelligent building applications.

applications↗
DOE OSTI2024

Hydroxide Exchange Membrane Carbon Capture (HEMCC) Using Nickel Hydroxide Batteries and Flow-through Membranes

Proposed is an electrochemical nickel hydroxide based hydroxide exchange membrane carbon capture (HEMCC) device for Direct Air Capture (DAC) of CO2. DAC has been identified as one of the key net negative carbon technologies to achieve net zero carbon emissions. Net negative carbon technologies are required to offset continued emissions from dilute CO2 sources such as agriculture and construction. The majority of current DAC technologies at scale (>1 KT∙yr-1) are adsorbent based technologies with significant energy cost. The traditional DAC energy cost is primarily driven by the temperature swing required to regenerate the sorbent and has been shown to be 1.8 MWh·ton-1 at the system level. Electrochemical pH swing devices are a growing research area for carbon capture devices with the goal of lowering the energy cost required for DAC. A pH gradient is built by generating OH- at the cathode and consuming OH- at the anode. An acid-base equilibrium with CO2 allows for the capture of CO2 at the cathode and release at the anode. This extends from other electrochemical CO2 capture devices based on pKa shifts of an electrochemically active organic species allowing for the capture and release of CO2. Electrochemical CO2 capture is considered promising based on potentially low energy costs to capture CO2 in comparison with current temperature swing adsorption technologies. This work explores Ni(OH)2 electrodes to produce the pH gradient for CO2 capture and release. At the cathode NiOOH is reduced to Ni(OH)2 while at the anode Ni(OH)2 is oxidized to NiOOH. The symmetrical electrodes allow for a low voltage requirement; the thermodynamic potential difference of standard electrochemical reactions is zero. Most of the voltage observed is to produce the pH gradient with the remainder driving the polarization of the electrodes. There is a resistance component as well, but this is small in comparison due to the low current densities used in the device, nominally 2 mA·cm-1. Two similar devices are presented, a traditional MEA (membrane electrode assembly) and a flow-through MEA. The traditional MEA separates the two Ni(OH)2 electrodes with an 80μm Piperion® membrane. While the flow-through membrane separates the electrodes with a three piece membrane consisting of two 80μm Piperion® membranes with a porous membrane between them. In the traditional MEA system air is passed over the cathode for capture, while the flow-through MEA the air is passed through the porous membrane isolated from the electrodes. The traditional MEA has been used to establish a baseline performance of the device and has been shown to capture CO2 at an energy cost of 1 MWh·ton-1 at the device level. An understanding has been built around the components of that energy cost including the relationship of flux to current density, effect of a regeneration process, transient battery behavior, and gas losses coinciding with changing the polarization of the batteries. The flow-through MEA looks to address of transient battery behavior and gas losses. It allows for denser, higher capacity electrodes, which can lean on traditional Ni-MH battery technology used in alkaline batteries used today. The higher capacities, limit the transient battery effect on flux in the device. Gas losses are addressed by having a continuous inlet air stream to the device and continuous outlet product.

Buchen, James↗
DOE OSTI2024

Dialogue Between Lighting and HVAC Systems: Improving building system integration

Lighting systems have long been capable of sensing when someone enters or exits a room and using that knowledge to turn lights on or off. More recently, connected lighting systems with sensors integrated into every luminaire have become broadly available, facilitating highly granular occupancy detection. Similarly, HVAC systems have long been able to use an understanding of building occupancy to adjust temperature setpoints and reduce energy use without significant impacts to occupant comfort. Energy codes (e.g., ASHRAE/IES Standard 90.1, IECC, Title 24) now require “occupied standby HVAC control,” whereby systems adjust both temperature and ventilation setpoints in zones that are determined to be unoccupied during normal occupancy hours. Here, this article discusses current issues that stymie the integration of Lighting and HVAC systems, and DOE activities focused on addressing them.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Cooperative Research and Development Agreement between National Energy Technology Laboratory and Pyrochem Catalyst Company [Abstract]

A catalytic converter is a key enabling technology for more advanced engine technologies to meet the more stringent fuel economy and emission standards of the future, particularly the requirement to treat emissions formed during a cold start (which account for between 60-80% of total emissions). As internal combustion engine technology is expected to remain a dominant force in the market, new and innovative catalyst technologies are needed with low temperature activity to reduce exhaust pollutants by 90% at temperatures as low as 150°C, with a performance lifetime that exceeds 150,000 miles of driving. Considering current catalyst technology only starts to convert pollutants at 200°C, the challenge is significant. Pyrochem Catalyst Company (PCC) has developed a promising PyroCatTM pyrochlore catalyst technology (that incorporates an NETL technology licensed by PCC), which has shown activity better than current state of the art and approaching the 150°C target. NETL and PCC will collaborate to transition PyroCatTM from lab-scale testing to commercialization through the generation of a commercially representative monolith catalyst that can be sent to automotive companies and catalyst manufacturers to validate in their reactor systems.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Update of Erosion Conditions and Assessment of Mitigation Options for the L-Bar Site

The L-Bar former uranium milling site was remediated and closed per regulations and is now under the long-term stewardship of the U.S. Department of Energy, Office of Legacy Management (DOE/LM). Since assuming stewardship in 2004, DOE/LM has observed erosion and sedimentation processes at the L-Bar Site that will challenge meeting the design closure criteria in the long term, and therefore erosion control structures were installed in several areas. Portions of these structures were subsequently damaged by summer convective storm events and they are being redesigned. At the request of DOE/LM, Desert Research Institute (DRI) reviewed the proposed redesign plans of the erosion control structures. The purpose of this review is to support DOE/LM decisions regarding mitigation of ongoing erosion processes, including assessing possible repair of the existing erosion control structures, as well as plan for effective long-term site management. This design review is performed in reference to the Uranium Mill Tailings Radiation Control Act (UMTRCA) standards contained in 40 CFR 192.02 that require containment of residual radioactive material be effective for up to 1,000 years (if achievable, but certainly for 200 years), limit radon release, protect groundwater, and minimize future maintenance. The erosion control structures under review are not subject to the UMTRCA standard directly, but they contribute to the performance of the overall containment system by virtue of their relationship with the large diversion channels bounding the disposal cell. The 11 design drawings included in “Erosion Control Alternatives Analysis, L-Bar, New Mexico, Disposal Site, LTS-111-0043-08-002,” dated January 11, 2019, and listed in Appendix A, and supporting calculations in Weston (2019) are the focus of the review. Additionally, DOE/LM provided supporting data such as a 2018 photogrammetry-based digital elevation model of the site, precipitation records collected from an on-site weather station, and sedimentation records collected at an on-site basin. This assessment includes review of the proposed design to mitigate current site conditions but also addresses site changes between the initial erosion assessment report (Miller et al., 2012) and current conditions. The analysis is at a predesign engineering level and does not include development of hydraulic or sediment transport models. Site precipitation data are included in Miller et al. (2012). The natural conditions of the site, the design of site diversion systems, observed erosion at the site, and predesign engineering analysis are used to develop a holistic view of the challenges to L-Bar Site stability and possible responsive actions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Technical analysis of filter testing at the U.S. Department of Energy Filter Test Facility

The U.S. Department of Energy (DOE) technical standard DOE-STD-3020-2015 requires verification testing at the Filter Test Facility (FTF) of high-efficiency particulate air (HEPA) filters to be installed in nuclear facility (Hazard Category 1, 2, 3, and radiological facilities) confinement ventilation systems, or to be installed in habitability systems (e.g., filters for protection of workers required to act for the control and mitigation of emergency situations). Filters in these applications perform a safety function in accident situations, are designated as important to safety, or are necessary for habitability systems. Different FTFs have operated for decades, and results of tests are available to examine the need for and benefits of continued execution of 100 percent QA verification testing. The objective of this study and resulting report was to assess the need for 100 percent QA testing at the current FTF in Maryland, based on an examination of a database of test results from 2013 to August 2020. Filters that require independent testing per DOE-STD-3020-2015 to be installed in nuclear facilities are sent to the FTF before being shipped to the facilities. The FTF examines the documentation (e.g., certificates of compliance, results of particle penetration and airflow resistance testing by the manufacturers, labels affixed to filters and packages, and other requirements specified in purchase orders by the nuclear facility operators), implements visual inspections of the physical state of the filters, and checks the dimensions of frames. Filters that meet the documentation and visual inspection requirements are subjected to particle penetration and airflow resistance testing. In case of rejections, the filters are shipped back to the manufacturers, at the cost of the manufacturers, for replacement. Filters that pass all tests are shipped to the nuclear facilities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Systems Packages for Washington State Building Performance Standard Incentive Program: Phase 1 Analysis

Starting in 2026 Washington State building performance standards will come into effect that require commercial buildings larger than 50,000 sf to meet site energy use intensity targets. To support a state incentive program designed to encourage building owners to start complying early, we characterized the building stock energy use of 11 building types, analyzed 43 energy upgrade measures, and developed seven packages of energy upgrade measures using the ComStock energy analysis tool. Each energy upgrade package included from 4 to 17 energy measures consisting of lighting, HVAC, and envelope upgrades. Package savings were calculated for four priority building types using a sample of 35,000 buildings characterized by four building area bins, three climate zones, and two county types (urban and rural). Of the 28 package and building type combinations analyzed, 17 (61%) met or exceeded program energy savings targets and two packages met targets for all four building types.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Fort Erie On-Demand Transit Case Study

Rural and smaller-sized communities in North America face unique mobility challenges due to their low population density, lower public transit spending per capita compared to major cities, and a high reliance on private vehicles. In recent years, communities such as Fort Erie, Ontario have restructured or advanced their public transit systems using on-demand services. Fort Erie is a relatively sparsely populated region of 32,901 residents, spread across a land area of 166 square kilometers (64 square miles), for an average population density of 193 residents per square kilometer (500 per square mile). In October 2021, the town implemented a mobility-on-demand system integrated with smartphone software to replace its fixed-route community bus system, which consisted of four buses with three routes, each with a roughly one-hour, one way loop. The new service utilizes a fleet of six minivans, two of which are retrofitted with wheelchair-accessible ramps. The system may require that a passenger requesting a standard van walk up to 400 meters (a quarter mile) to their pickup location to optimize vehicle routing while providing origin-to-destination service. The on-demand system proved effective in providing service, eclipsing pre-pandemic ridership by 40%, decreasing greenhouse gas emissions per ride by 63%, and decreasing the cost per ride to the town by 29%. This report documents both the previous system and the new system in terms of routes, ridership, costs, fuel, and other notable system parameters. This work is part of an ongoing series of case studies on providing small communities with on-demand, right-sized vehicle service coupled with a smartphone application.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Laboratory Instrument Software Controlled Spread Spectrum Time Domain Reflectometry for Electrical Cable Testing

This research discusses development of a software-controlled laboratory instrument based spread spectrum time domain reflectometry system (SSTDR). This constitutes one task within PNNL’s Light Water Sustainability Program (LWRS) whose mission includes advancing nondestructive examination (NDE) techniques for off-line and on-line in-situ cable condition monitoring. In 2022, PNNL evaluated SSTDR for detection and characterization of a number of cable anomalies (Glass et al. 2022). The review included comparison of SSTDR to Frequency Domain Reflectometry (FDR) techniques which have enjoyed encouraging feedback and are starting to be used in nuclear power plants for periodic cable condition monitoring of cable systems as part of the plant’s overall cable aging management program. The FDR test introduces a broad-band chirp onto the cable at the cable end then listens for any reflection from a change of impedance along the cable caused by a damaged conductor or insulation, splices, contact with moisture, or other cable anomalies. The signal is captured in the frequency domain then transformed back to the time domain using an inverse Fourier transform (IFT). Based on the velocity of propagation, the impedance response signal is plotted against distance along the cable. Peak locations along the X-axis indicate the distance along the cable where a portion of the signal has been reflected back to the instrument as a result of a cable anomaly. The FDR test is considered the gold standard of reflectometry however it does require the cable to be de-energized to perform the test. The LIVEWIRE commercial SSTDR produces a similar plot to the FDR however all processing is in the time domain. A pseudo-random noise code (PN code) is input onto the cable conductor and the instrument listens for any reflected response from cable anomalies. The SSTDR processes the signal as an autocorrelation comparing the input PN code to any reflected signal detected. The autocorrelation analysis for thermal aging, water and water ingress detection, ground fault and phase-to-phase fault detection at various locations along the cable and with the cable attached and detached from a motor load, and on both energized and un-energized conditions were performed. These results were contrasted to Frequency Domain Reflectometry (FDR) measurements of the un-energized cable. Results were encouraging but indicated more work was warranted – particularly with the SSTDR, it seemed that the insulation damage would likely be better evaluated with multiple bandwidth cable tests particularly including larger bandwidths than were possible with the current commercial instrument. The commercial instrument’s bandwidth was set at 6, 12, 24, and 48MHz but note that SSTDR and FDR definitions of bandwidth trend similarly but are not the same. The FDR response could be more broadly adjusted, and the bandwidth of 100 to 500 MHz produced the best responses. FDR responses to anomalies were clearer than SSTDR responses and indications were that a broader bandwidth SSTDR may lead to improved SSTDR detection capability. This project used a laboratory instrument based SSTDR (primarily using an Arbitrary Waveform Generator (AWG) and a digital oscilloscope plus Python in-house software) that allowed software adjustment of the SSTDR bandwidth, window functions applied to the exciting Pseudo-random Noise (PN) code plus and other aspects of the SSTDR signal processing. Hereafter, this will be referred to as the PNNL SSTDR. Evaluating specific performance of the PNNL SSTDR is left to a separate report. This report documents hardware and software development to produce the SSTDR cable test system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

An Applied Strategy for Using Empirical and Hybrid Models in Online Monitoring

The monitoring of plant equipment for failure prediction is one of the key contributors to operation and maintenance (O&M) costs for a nuclear power plant (NPP) because O&M monitoring depends on labor-intensive activities that are required to meet high equipment reliability standards. These activities rely primarily on humans for information gathering, condition diagnosis, and predictive analysis. Online monitoring aims to automate these activities by relying on sensors to replace human information gathering and machine learning to replace human analysis and decision making. To facilitate automated monitoring, a systematic strategy for anomaly detection is needed to optimally use the available sensor data, empirical models, and physics-supported models. This strategy is essential to provide credible reasoning on why and when an empirical (i.e., purely data-driven) versus hybrid (i.e., physics-supported) approach should be used and to determine the ideal mix of these two approaches for a defined anomaly detection scope. The extant methods usually adopt an ad hoc trial-and-error approach that, in addition to being time-consuming and costly, is also highly subjective; it is impacted by the background and the skill set of the personnel making the decisions. Thus, such an approach cannot guarantee an optimum outcome. This represents the motivation of the current research effort, which is focused on devising a scientifically supported strategy for the optimum selection of anomaly detection methods. This report presents a detailed assessment of the main anomaly detection techniques within the empirical or hybrid method streams. Empirical methods include pattern, statistical, and causal inference. Hybrid methods include the use of physics models to train and test data methods, reduce data dimensionality, reduce data-model complexity, augment data, and reduce empirical uncertainty; hybrid methods also include the use of data to tune physics models. The listed techniques within these two streams represent the vast majority of techniques performed for anomaly detection. Using the techniques as outcomes, a strategy was developed to enable a systematic decision-making process to lead to one of these techniques. The strategy is driven by key decision points related to data relevance, simple modeling feasibility, data inference, physics-modeling value, data dimensionality, physics knowledge, method of validation, performance, data availability and suitability for training and testing, cause-effect, entropy inference, and model fitting. Each of these decision points in the strategy is explained in detail in this report with examples, along with the scientific basis behind the decisions and outcomes in common and simplified terminology. The strategy is developed for use by any NPP staff with basic engineering or science knowledge. A user-friendly graphical state flow diagram was also developed as a visual presentation of the strategy. The strategy was tested and demonstrated through two pilot projects for the application of anomaly detection at an NPP. Each pilot had two use cases: an initial case in which certain decisions were made that resulted in one or more empirical techniques and a revised use case where one or more key decisions were modified resulting in using a set of hybrid methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗