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At least 829 records · Page 46

Multicriterion benefit evaluation methodology for safety enhancements in nuclear power plants and application for FLEX strategies

Here we propose a multicriterion benefit evaluation (MCBE) methodology for evaluating costs and benefits of implementing safety enhancements in nuclear power plants. The MCBE methodology establishes a comprehensive evaluation scope using multiple evaluation criteria (including public risk, occupational risk, plant revenue, and plant cost) and multiple contexts (including plant normal operations, incidents, and accidents). The MCBE methodology formulates a benefit or cost element as the product of a monetary consequence and its occurrence-likelihood change. The MCBE methodology also incorporates a decision maker’ preferences toward occurrence likelihood and monetary consequence into cost and benefit estimations through a modified usage of cumulative prospect theory. This paper applies the MCBE methodology to the implementation of diverse and flexible coping strategy (FLEX) in a generic nuclear power plant as an illustrative example. The FLEX benefits are evaluated through three types of influence paths: plant safety enhancement, risk-informed activities, and potential additional credit of FLEX in supporting plant operation and maintenance-efficiency improvement. The benefit-to-cost ratio (BCR) of FLEX implementation is calculated. Sensitivity analyses are conducted to examine the impacts of modeling assumptions and input parameter values on the BCR.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Green’s function methods for excited states and x-ray spectra of functional materials

Many interesting properties of functional materials, such as dynamic response and thermodynamic behavior, depend on their excited state properties. These functional properties are often related to excitations in the system, such as phonons and plasmons, which lead to inelastic losses, lifetime, and other dynamic effects. The excitations are pure many-body correlation effects that are missing from independent particle theories. They are revealed in x-ray spectra such as photoemission and absorption, where they show up as satellites beyond the quasi-particle approximation. Our main focus in this work is the use of Green's function methods to describe these effects. In particular, we discuss how the cumulant Green's function provides a unified treatment of such dynamic correlation effects in many contexts. Besides a robust theoretical framework, these methods also yield widely applicable tools for practical calculations of many functional properties of materials. Furthermore, this methodology is illustrated with a number of applications ranging from optical and x-ray spectra to thermodynamic properties, and dynamic response. Some recent extensions for more correlated systems are also briefly discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Minimization of Measurement Uncertainty in Optical Frequency Domain Reflectometry

Optical frequency domain reflectometry (OFDR) is a technique for interrogating optical fiber sensors to generate relative, quasi-distributed measurements. Although Optical frequency domain reflectometry (OFDR) is increasingly being adopted for aerospace, energy production, and structural monitoring applications, the quantification of uncertainty for OFDR measurements has not been developed beyond sparse empirical relationships. To address this knowledge gap, an uncertainty metric for OFDR measurements was developed. This uncertainty metric was applied to weight the edges between OFDR measurements on directed correlation graphs and analyzed to minimize the cumulative uncertainty. In conclusion, this work is the first to propose an uncertainty metric for OFDR and provides a generalized mathematical framework for optimizing OFDR hardware selection, optical fiber sensor selection, and postprocessing strategy.

42 ENGINEERING↗

Model-Based Detection Scheme for Spoofed Sensor Data in Grid-Connected Inverters

In this article, a novel method to detect spoofed sensor data (SSD) for grid-connected inverters is proposed. First, a Kalman filter is used to estimate the inverter status in the proposed method. Then, the impact of SSD on the residual between estimation and control reference is analyzed. By leveraging the standard error of residual, an adaptive cumulative sum (CUSUM) chart is developed to achieve fast SSD detection and improve robustness. In addition, the proposed SSD detection method is verified by the hardware experiment. A comparative experiment with a conventional method also demonstrates the rapidity and robustness of the proposed method. Lastly, the performance of the proposed method under different noise covariance matrices is analyzed. Comprehensive analysis shows that the proposed method meets the detection requirement in IEEE 1547 Standard.

42 ENGINEERING↗

Identifying management opportunities to combat climate, land, and marine threats across less climate exposed coral reefs

Conserving coral reefs is critical for maintaining marine biodiversity, protecting coastlines, and supporting livelihoods in many coastal communities. Climate change threatens coral reefs globally, but researchers have identified a portfolio of coral reefs (bioclimatic units [BCUs]) that are relatively less exposed to climate impacts and strongly connected to other coral reef systems. These reefs provide a proactive opportunity to secure a long-term future for coral reefs under climate change. To help guide local management efforts, we quantified marine cumulative human impact (CHI) from climate, marine, and land pressures (2013 and from 2008 to 2013) in BCUs and across countries tasked with BCU management. Additionally, we created a management index based on common management measures and policies for each pressure source (climate, marine, and land) to identify a country's intent and commitment to effectively manage these pressures. Twenty-two countries (79%) had increases in CHI from 2008 to 2013. Climate change pressures had the highest proportional contribution to CHI across all reefs and in all but one country (Singapore), but 18 BCUs (35%) and nine countries containing BCUs (32%) had relatively high land and marine impacts. There was a significant positive relationship between climate impact and the climate management index across countries (R 2 = 0.43, p = 0.02), potentially signifying that countries with greater climate impacts are more committed to managing them. However, this trend was driven by climate management intent in Fiji and Bangladesh. Our results can be used to guide future fine-scale analyses, national policies, and local management decisions, and our management indices reveal areas where management components can be improved. Cost-effectively managing local pressures (e.g., fishing and nutrients) in BCUs is essential for building a climate-ready future that benefits coral reefs and people.

59 BASIC BIOLOGICAL SCIENCES↗

Hybrid AI-ML and FE-based Digital Twin Predictive Modeling Framework for a PWR Coolant System Components: Updates on Multi-Time-Series-3D-Location Dependent Usages Factor Prediction

The long-term operation (LTO) of nuclear power plants (NPP) beyond their original design life of 40 years can lead to more material damage associated with cyclic fatigue under thermal-mechanical loading cycles and associated long-term exposure of reactor material to the deleterious reactor-coolant environments. However, under this LTO condition, the reactor components can still safely operate but may require more frequent Nondestructive Evaluation (NDE) of reactor components. Requiring frequent NDE inspections may lead to frequent NPP shutdowns which can lead to power outages and additional NDE inspection cost-related economic loss. The economic loss can be minimized by reducing uncertainty in life estimation of safety-critical pressure boundary components and by implementing a more digital approach such as using upcoming digital-twin (DT) technology for predicting the structural states (e.g., time and location dependent inside/outside thickness temperature, stress, strain, plastic deformation, etc.) and associated fatigue life of a component in real time. The DT framework is based on limited experimental data, Artificial-intelligence (AI)-Machine-Learning (ML) and multiphysics-computationalmechanics such as finite element- (FE) based models. Given the real-time thermal-hydraulic process measurements from several existing plant sensors, the overall goal of the DT framework is to predict the cumulative usages factors or equivalent fatigue lives in real time and at any random 3D location of the components. This includes inaccessible locations such as inside the thickness or location of a component. This prediction can be at thousands to millions of 3D point clouds or locations like conventional FE-based models, but without running an FE model in real time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

An Updated Life Cycle Assessment of Utility-Scale Solar Photovoltaic Systems Installed in the United States

Given the high deployment targets for solar photovoltaics (PV) needed to meet U.S. decarbonization goals, and the limited carbon budget remaining to limit global temperature rise, accurate accounting of the energy-use and greenhouse-gas emissions over the life-cycle of PV systems is needed. In the United States, most PV systems are large utility-scale systems which use single-axis trackers and central inverters, which are not commonly examined in existing life-cycle assessment (LCA) literature. In this study, we present a cradle-to-grave LCA of a typical silicon U.S. utility PV (UPV) installation which is consistent with the utility system features documented in the annual NREL PV system cost benchmark reports. We analyze and present results for four main metrics: cumulative energy demand (CED), greenhouse gas (GHG) emissions, energy payback time (EPBT), and carbon payback time (CPBT). We consider six primary manufacturing options: three based on an imported PV module supply chain (comparing low-carbon imports, high-carbon imports, and average imports), and three based on a potential domestic PV module supply chain (comparing low-carbon U.S. regions, high-carbon U.S. regions, and average U.S. regions). These manufacturing options were then paired with installation locations to create six main cases: low-carbon options were installed in Phoenix (Arizona), high-carbon options were installed in Seattle (Washington), and average options were installed in Fredonia (Kansas). These locations were selected to represent a range of irradiance and grid mixes in the United States, in order to illustrate the likely range of EPBTs and CPBTs possible across the United States. For all six cases, a sensitivity analysis for end-of-life (EOL) handling was explored to capture current and future management options: landfilling, partial recycling, and high-quality recycling. For the purposes of this report, the benchmark system was defined to use an average imported supply chain with partial recycling, installed in Fredonia (Kansas). CED results show ratios at or below 0.1 MJ oil-eq /MJgenerated which demonstrates efficient use of primary energy resources (below a 1:1 ratio), and represents a slight improvement over previous results in literature. GHG emissions per kWh range from 10-36 g CO 2 e, which are consistent with or lower than previous results published by NREL and IEA-PVPS. We use a graphical approach for calculating EPBT and CPBT in this report, which improves upon methods typically used in literature by accounting for non-linearity and avoiding data quality issues associated with long-term projections. EPBT was determined to vary from 0.5 to 1.2 years, with a benchmark EPBT of 0.6 years; CPBT was shown to vary from 0.8 to 20 years, with benchmark CPBT of 2.1 years, which is lower than other estimates from recent literature (typically >2 years).

14 SOLAR ENERGY↗

Simple gain probability functions for large reflector antennas of JPL/NASA

Simple models for the patterns as well as their cumulative gain probability and probability density functions of the Deep Space Network antennas are developed. These are needed for the study and evaluation of interference from unwanted sources such as the emerging terrestrial system, High Density Fixed Service, with the Ka-band receiving antenna systems in Goldstone Station of the Deep Space Network.

large reflector antenna probability density functi↗

Hybrid data-driven and model-informed online tool wear detection in milling machines

Precision machining tool wear is responsible for low product throughput and quality. Monitoring the tool wear online is vital to prevent degradation in machining quality. However, direct real-time tool wear measurement is not practical. This paper presents residual-based anomaly detection models, combining a hybrid model comprised of a physics-based model and a data-driven model (a decision tree or a neural network) to predict signals of interest (e.g., power or forces) under nominal conditions, followed by Page’s cumulative sum test for detecting tool wear on-line using the computer numerical control machine measurements. The most informative features are ranked using dynamic programming and its approximation variants from real-time measurements and machine settings, such as the width of cut, depth of cut, feed rate and spindle speed, that serve as inputs to the predictive models. The baseline nominal model is incrementally updated with experimental data via a gradient boosted adaptation model to generate the residuals that account for discrepancies between the actual machine data under normal conditions and the baseline nominal model predictions. The hybrid model is validated against 20 Mazak milling machine experimental tests and one Haas run-to-failure experiment. The proposed anomaly detector is applied to synthetic data from simulations of the physics-based model at different operating conditions, measurement noise levels, and tool wear levels, and the methods were able to achieve an overall 92% accuracy in data with 1% noise. The anomaly detection methods based on hybrid model reduced the false alarms of either the data-driven or physical-based models alone, and are found to be capable of good online detection of tool wear.

Online anomaly detection↗

Basin-Wide Approaches to Hydropower Licensing

This presentation summarizes findings from a 2020 NREL technical report including the FERC relicensing process for non-federal hydropower projects, analyzes FERC-licensed projects with license expiration dates from 2018-2037, discusses FERC's authority to coordinate license terms of hydropower projects within a shared river basin and provides basin-wide case studies and considerations to hydropower relicensing. In the United States there are 1,043 active FERC-licensed hydroelectric projects with a total capacity of 56,097 MW. Of those, 647 with a total capacity of 21,870 MW have license expiration dates from 2018-2037. The expected workload in conjunction with the time, cost, and complexity associated with issuing a single new license has led to initiatives that aim to increase the efficiency of the relicensing process. Federal and state regulators and licensees in California, Maine, New York, and Wisconsin have begun to develop approaches to look at hydropower relicensing as part of a larger system - a river basin. These basin-wide approaches seek to coordinate different stages of the relicensing process for multiple projects at the same time. The goal of these basin-wide approaches is to increase the efficiency of the relicensing process and allow for a more comprehensive analysis of the cumulative impacts of the projects within the basin. These innovative approaches to relicensing could also reduce the workload for regulators and costs associated with relicensing. This presentation discusses some of the findings from the Basin-wide Approaches to Hydropower Relicensing: Case Studies and Considerations including a summary of the key considerations for the FERC relicensing process for non-federal hydropower projects, key findings from the analysis of FERC-licensed projects with license expiration dates from 2018-2037, discusses FERC's authority to coordinate license terms of hydropower projects within a shared river basin and provides basin-wide case studies and considerations to hydropower relicensing.

basin-wide↗

Using Life Cycle Assessment to Inform CBI Research Priorities

Life cycle assessment (LCA) is used within the Center for Bioenergy Innovation (CBI) to provide information about how feedstock agricultural practices, supply chain logistics, biorefinery operating parameters, and the slate of biofuels and products contribute to environmental impacts, and how CBI's research priorities can result in less impactful biofuel supply chains. This poster provides an overview of the LCA methodology used within CBI and focuses on data needs in general and from other CBI teams. Assumptions and simplifications within biofuel LCA studies are reviewed, including options for modeling multi-functional processes. Calculation details for life cycle environmental impacts used within CBI - global warming potential, cumulative energy demand, and the Available Water Remaining indicator - are presented, along with a discussion of carbon intensity as an alternative metric for evaluating sustainable aviation fuel and other biofuels. The process of interpreting impact results to guide research priorities is discussed, with examples drawn from CBI's upcoming manuscript on switchgrass yield and cell wall composition.

bioenergy↗

Relating Measured Component Damage to Assessed Component Reliability in Reliability Integrity Management (RIM)

There is currently no widely agreed detailed general method for licensing a novel plant incorporating novel materials (or materials being deployed in novel environments); in many such situations, there are no directly applicable engineering code cases for decision-makers (including regulators) to rely on. It may be possible to develop an approach to licensing such a plant that is based on the Reliability and Integrity Management (RIM) approach delineated in ASME BPVC Section XI Division 2. NRC Regulatory Guide 1.246, Rev.0, endorses, with conditions, the subject portion of the ASME Code. But that portion of the ASME code is written at a very high level, and there are fundamental technical challenges associated with applying it literally to licensing a real plant. In the RIM approach, applicants need to do the following (among other things): • Allocate target reliabilities to structures, systems, and components (SSCs) that collectively support the top-level plant safety and availability objectives; • Understand failure modes of those SSCs, and the degradation mechanisms that could lead to those failure modes; • Develop and propose a program of surveillances that will identify degradation prior to failure of SSCs; • Provide a means of reporting results, taking actions for anomalous or undesirable conditions, and give the regulator assurance of continued safe operations. Applying RIM in a specific case will call for advances in the state of practice of relating physical observables to functional reliability of certain component types. Except where a given level of damage corresponds to a failed (or nearly failed) state, it is not practical to establish a precise quantitative relationship between physical observables and reliability. This paper focuses on managing risk of passive component failures based on observable damage parameters. A simple approach to cumulative damage modeling will be illustrated with a view to possible use in RIM applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Environmental and economic analyses of chemical recycling via dissolution of waste polyethylene terephthalate

Globally, more than 1000 organizations and 175 nations are facing the plastic waste problem and have realized the need to transition from “linear-to-circular” economy of plastics. While the current mechanical recycling technologies for plastics are struggling to increase the U.S. plastic recycling rates beyond 9%, chemical recycling technologies become important complementary technologies to the predominant mechanical recycling that are needed to realize the circular economy in plastics supply chains. Dissolution is one such chemical recycling technology that can recycle waste plastic back into high-quality virgin grade plastic. However, the environmental and economic impacts of chemical recycling of waste polyethylene terephthalate (PET) via dissolution technology using a green solvent are unknown. Our study evaluated environmental metrics such as greenhouse gas (GHG) emissions and cumulative energy demand, and economic metrics such as net present value (NPV), minimum selling price, payback period, return on investment, and discounted internal rate of return for three dissolution processes with polymer recovery via anti-solvent, evaporation, and cooling precipitation techniques. The dissolution process with evaporation technique was the most economically favorable, whereas that with cooling technique was the most environmentally favorable. The anti-solvent approach had low economic performance and the highest environmental impacts. The NPV for all of these technologies ranged from $2.67 MM to $10.93 MM for a capacity of 8,400 MT/year and was found to be the highest for dissolution with evaporation approach and the least for anti-solvent approach. The cradle-to-gate GHG emissions and energy demand for PET dissolution processes ranged from 1.33-3.77 kg CO2-eq/kg of chemically recycled (CR) PET and18.9-56.1 MJ/kg of CR-PET, respectively. These economic and environmental metrics will be helpful in evaluating the sustainability of circular PET supply chains in the U.S.

09 BIOMASS FUELS↗

Stable High‐Conductivity Ethylenedioxythiophene Polymers via Borane‐Adduct Doping

Efficient doping of polymer semiconductors is required for high conductivity and efficient thermoelectric performance. Lewis acids, e.g., B(C 6 F 5 ) 3 , have been widely employed as dopants, but the mechanism is not fully understood. 1:1 “Wheland type” or zwitterionic complexes of B(C 6 F 5 ) 3 are created with small conjugated molecules 3,6-bis(5-(7-(5-methylthiophen-2-yl)-2,3-dihydrothieno[3,4-b][1,4]dioxin-5-yl)thiophen-2-yl)-2,5-dioctyl-2,5-dihydropyrrolo[3,4-c]pyrrole-1,4-dione [oligo_DPP(EDOT) 2 ] and 3,6-bis(5''-methyl-[2,2':5',2''-terthiophen]-5-yl)-2,5-dioctyl-2,5-dihydropyrrolo[3,4-c]pyrrole-1,4-dione [oligo_DPP(Th) 2 ]. Using a wide variety of experimental and computational approaches, the doping ability of these Wheland Complexes with B(C 6 F 5 ) 3 are characterized for five novel diketopyrrolopyrrole-ethylenedioxythiophene (DPP-EDOT)-based conjugated polymers. The electrical properties are a strong function of the specific conjugated molecule constituting the adduct, rather than acidic protons generated via hydrolysis of B(C 6 F 5 ) 3 , serving as the oxidant. It is highly probable that certain repeat units/segments form adduct structures in p -type conjugated polymers which act as intermediates for conjugated polymer doping. Electronic and optical properties are consistent with the increase in hole-donating ability of polymers with their cumulative donor strengths. The doped film of polymer (DPP(EDOT) 2 -(EDOT) 2 ) exhibits exceptionally good thermal and air-storage stability. The highest conductivities, ≈300 and ≈200 S cm -1 , are achieved for DPP(EDOT) 2 -(EDOT) 2 doped with B(C 6 F 5 ) 3 and its Wheland complexes.

36 MATERIALS SCIENCE↗

Nanocellulose‐Carboxymethylcellulose Electrolyte for Stable, High‐Rate Zinc‐Ion Batteries

Abstract Aqueous Zn ion batteries (ZIBs) are one of the most promising battery chemistries for grid‐scale renewable energy storage. However, their application is limited by issues such as Zn dendrite formation and undesirable side reactions that can occur in the presence of excess free water molecules and ions. In this study, a nanocellulose‐carboxymethylcellulose (CMC) hydrogel electrolyte is demonstrated that features stable cycling performance and high Zn 2+ conductivity (26 mS cm −1 ), which is attributed to the material's strong mechanical strength (≈70 MPa) and water‐bonding ability. With this electrolyte, the Zn‐metal anode shows exceptional cycling stability at an ultra‐high rate, with the ability to sustain a current density as high as 80 mA cm −2 for more than 3500 cycles and a cumulative capacity of 17.6 Ah cm −2 (40 mA cm −2 ). Additionally, side reactions, such as hydrogen evolution and surface passivation, are substantially reduced due to the strong water‐bonding capacity of the CMC. Full Zn||MnO 2 batteries fabricated with this electrolyte demonstrate excellent high‐rate performance and long‐term cycling stability (>500 cycles at 8C). These results suggest the cellulose‐CMC electrolyte as a promising low‐cost, easy‐to‐fabricate, and sustainable aqueous‐based electrolyte for ZIBs with excellent electrochemical performance that can help pave the way toward grid‐scale energy storage for renewable energy sources.

25 ENERGY STORAGE↗

Thermal Management by Engineering the Alignment of Nanocellulose

One of the grand current research challenges is to improve the energy efficiency of residential and commercial buildings, which cumulatively consume more than 40% of the energy generated globally. In addition to improving the comfort of the inhabitants and mitigating the growing energy consumption problem, new building materials and technologies could provide a safe strategy for geoengineering to mitigate global climate change. Herein, recent progress in developing such advanced materials from nanocellulose, which is often derived from wood or even dirty feedstocks like waste, is reviewed. By using chemical and bacteria-enabled processing, nanocellulose can be used to fabricate broadband photonic reflectors, thermally super-insulating aerogels, solar gain regulators, and low-emissivity coatings, with potential applications in windows, roofs, walls, and other components of buildings envelopes. These material developments draw inspiration from advanced energy management found in nature, such as the nanoporous photonic structures that evolved in cuticles of beetles. Fabrication of such materials takes advantage of mesoscale liquid crystalline self-assembly, which allows for pre-designed control of cellulose nanoparticle orientations at the mesoscale. Finally, with the potential fully realized, such materials could one day transform the current energy-lossy buildings into energy plants on Earth and possibly even enable extraterrestrial habitats.

36 MATERIALS SCIENCE↗

Sequential Dual Alignments Introduce Synergistic Effect on Hexagonal Boron Nitride Platelets for Superior Thermal Performance

Planarly aligning 2D platelets is challenging due to their additional orientational freedom compared to 1D materials. Here, this study reports a sequential dual-alignment approach, employing an extrusion-printing-induced shear force and rotating-magnetic-field-induced force couple for platelet planarly alignment in a yield-stress support bath. It is hypothesized that the partial alignment induced by a directional shear force facilitates subsequent axial rotation of the platelets for planar alignment under an external force couple, resulting in a synergistic alignment effect. This sequential dual-alignment approach achieves better planar alignment of 2D modified hexagonal boron nitride (mhBN). Specifically, the thermal conductivity of the 40 wt% mhBN/epoxy composite is significantly higher (692%) than that of unaligned composites, surpassing the cumulative effect of individual methods (only 133%) with a 5 times more synergistic effect. For 30, 40, and 50 wt% mhBN composites, the thermal conductivity values (5.9, 9.5, and 13.8 W m –1 K –1 ) show considerable improvement compared to the previously reported highest values (5.3, 6.6, and 8.6 W m –1 K –1 ). Additionally, a 3D mhBN/epoxy heat sink is printed and evaluated to demonstrate the feasibility of device fabrication. The approach enables the planar alignment of electrically or thermally conducting 2D fillers during 3D fabrication.

36 MATERIALS SCIENCE↗

Engineering Electrical Transport by Implantation‐Induced Defects in CrN Films Without Affecting Thermal Conductivity

The transport properties of CrN thin films deposited on sapphire have been tailored through structural modifications induced by cumulative argon implantation. As-grown samples experience the typical structural transition in CrN films from orthorhombic at low temperature to cubic above the Néel temperature (≈280 K) and exhibit a metallic-like conduction in both phases. With increasing implantation dose, the conduction mode shifts to a semiconductor-like behavior in both phases, albeit at different damage levels. Analysis of the results suggests that hopping conduction becomes dominant beyond a given damage threshold. The results highlight a promising correlation between defect engineering and conduction mechanisms, offering valuable insights into the versatile electrical properties of CrN films. These implantation-induced defects scatter carriers, leading to a decrease in their mobility. As the implantation dose increases, the defect landscape evolves, modifying the density of states. However, up to a dose of 0.050 dpa, no significant influence on phonon scattering is observed. This approach demonstrates that ion implantation enables precise tuning of CrN's electrical properties without affecting thermal conductivity, offering valuable insights into defect engineering in transition metal nitrides and underscoring its potential for transport properties decorrelation.

defects↗