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At least 541 records · Page 30

Braneworld cosmological effect on freeze-in dark matter density and lifetime frontier

In the 5-dimensional braneworld cosmology, the Friedmann equation of our 4-dimensional universe on a brane is modified at high temperatures while the standard Big Bang cosmology is reproduced at low temperatures. Based on two well-known scenarios, the Randall–Sundrum and Gauss–Bonnet braneworld cosmologies, we investigate the braneworld cosmological effect on the relic density of a non-thermal dark matter particle whose interactions with the Standard Model particles are so weak that its relic density is determined by the freeze-in mechanism. For dark matter production processes in the early universe, we assume a simple scenario with a light vector-boson mediator for the dark matter particle to communicate with the Standard Model particles. We find that the braneworld cosmological effect can dramatically alters the resultant dark matter relic density from the one in the standard Big Bang cosmology. As an application, we consider a right-handed neutrino dark matter in the minimal B – L extended Standard Model with a light B – L gauge boson (Z') as a mediator. We find an impact of the braneworld cosmological effect on the search for the long-lived Z' boson at the planned/proposed Lifetime Frontier experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A light scalar explanation of (g - 2) μ and the KOTO anomaly

The KOTO experiment has recently performed a search for neutral Kaons decaying into neutral pions and a pair of neutrinos. Three events were observed in the KOTO signal region, with an expected background of about 0.05. Since no clear signal of systematic errors have been found, the excess of events in the decay K-L → π 0 v$\overline{v}$ is quite intriguing. One possibility to explain this anomaly would be the presence of a scalar $\phi$ with mass of the order of the pion mass and inducing decays K-L → π 0 $\phi$ which mimic the observed signal. A scalar with mass of the order of the pion mass and a coupling to muons of the order of the Standard Model Higgs coupling could also explain the muon anomalous magnetic moment anomaly (g - 2) μ . We built on these facts to show that a light singlet scalar with couplings to the leptons and quarks as the ones induced by mixing with Higgs states in two Higgs doublet models may lead to an explanation of both anomalies. More specifically, we show that this is the case in the so-called type-X models in which leptons and quarks couple to two different Higgs doublets, and for scalar masses that are in the range between 40 and 70 MeV. Due to the relatively large coupling to leptons required to fit (g - 2) μ , the scalar lifetime accidentally falls into the sub-nanosecond range which is essential to evade the severe proton beam dump experiments and astrophysical constraints, though it becomes sensitive to constraints from electron beam dump experiments. The additional phenomenological properties of this model are discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Flavor-changing light bosons with accidental longevity

We consider a model with a complex scalar field that couples to (e, μ) or (μ, τ) within the “longevity” window: [|m l 1 – m l 2 |, m l 1 + m l 2 ] in which l 1 and l 2 are the two different charged leptons. Within such a mass window, even a relatively large coupling (e.g. of the size commensurate with the current accuracy/discrepancy in the muon g – 2 experiment) leads to long lifetimes and macroscopic propagation distance between production and decay points. We propose to exploit several existing neutrino experiments and one future experiment to probe the parameter space of this model. For the μ – e sector, we exploit the muonium decay branching ratio and the production and decay sequence at the LSND experiment, excluding the parametric region suggested by g μ – 2 anomaly. For the τ – μ sector, we analyze three main production mechanisms of scalars at beam dump experiments: the Drell-Yan process, the heavy meson decay, and the muon scattering. We explore the constraints from the past CHARM and NuTeV experiments, and evaluate sensitivity for the proposed beam dump experiment, SHiP. The latter can thoroughly probe the parameter space relevant for the g μ – 2 anomaly.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A theory of dark pions

We present a complete model of a dark QCD sector with light dark pions, broadly motivated by hidden naturalness arguments. The dark quarks couple to the Standard Model via irrelevant Z- and Higgs-portal operators, which encode the low-energy effects of TeV-scale fermions interacting through Yukawa couplings with the Higgs field. The dark pions, depending on their CP properties, behave as either composite axion-like particles (ALPs) mixing with the Z or scalars mixing with the Higgs. The dark pion lifetimes fall naturally in the most interesting region for present and proposed searches for long-lived particles, at the LHC and beyond. This is demonstrated by studying in detail three benchmark scenarios for the symmetries and structure of the theory. Within a coherent framework, we analyze and compare the GeV-scale signatures of flavor-changing meson decays to dark pions, the weak-scale decays of Z and Higgs bosons to hidden hadrons, and the TeV-scale signals of the ultraviolet theory. New constraints are derived from B decays at CMS and from Z-initiated dark showers at LHCb, focusing on the displaced dimuon signature. We also emphasize the strong potential sensitivity of ATLAS and CMS to dark shower signals with large multiplicities and long lifetimes of the dark pions. As a key part of our phenomenological study, we perform a new data-driven calculation of the decays of a light ALP to exclusive hadronic Standard Model final states. The results are provided in a general form, applicable to any model with arbitrary flavor-diagonal couplings of the ALP to fermions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Data-Agnostic, Continuous Machine Learning Framework for Application in High Energy Physics and Beyond: Phase 1 Final Scientific/Technical Report

This Phase 1 effort has focused on the development of continual learning frameworks for use in machine learning, specifically in the applied context of High Energy Physics (HEP). Machine learning (ML) is a transformative technology by which computers, typically through the use of neural networks, are able to perform tasks with proficiency that rivals or surpasses that of human users. Model Degradation & Catastrophic Forgetting are two undesired phenomena which can occur in ML where the performance of a model degrades when either deployed on novel data streams, or trained on novel data which are sufficiently different than the data the models were initially trained on. A natural example where these sorts of effects can be observed is in the performance of detectors in harsh environments, where the detector signature may change over the lifetime of the detector as it ages and deteriorates — precisely what occurs in the experiments conducted in HEP. Real world HEP data is therefore an excellent test-ground and use-case for Continual Learning paradigms, which are techniques used in ML to counteract these problems. Ensemble learning is one such technique, where multiple smaller models are trained on subsets of the overall data and are ensembled together during inference. The intuition behind this technique is that, although there are shifts in the distributions which govern the incoming data streams, these shifts are not expected to be homogeneous or global. If a sufficient diversity in solutions within the various sub-models has been achieved, then at least one sub-model is expected to retain its performance within the overall ensemble. One further strength of this approach is that the architectures of the various models do not need to be identical, and in fact even different modalities of data can naturally be combined in this way. This work focused on applying ensemble learning techniques to derive results using two main datasets, anomaly detection in HEP data & time-series forecasting in semiconductor manufacturing data. Semiconductor manufacturing involves data with surprising similarity to that of HEP (e.g. wafer maps look very similar to digi-occupancy maps) and Cerium Lab’s prominence within the semiconductor industry makes semiconductor manufacturing a natural opportunity for commercialization of this work. Our efforts have led to two strong results. The first is that we evaluated the proposed ensembling techniques using previously proposed machine learning architectures for use in anomaly detection, namely AutoEncoder based models and their derivatives. We also developed new architectures which have not been evaluated in this context before. In fact, this work marks the first use of Vision Transformers for anomaly detection in HEP. Second, we demonstrated that ensemble learning significantly improves model performance in scenarios prone to degradation, validating its effectiveness across both HEP and semiconductor datasets. These results further support ensemble learning as a powerful strategy for mitigating catastrophic forgetting and maintaining robust performance in evolving data environments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

wtDigiTwin (Wind Turbine Digital Twin) [SWR-21-15]

This wind turbine digital twin software (wtDigiTwin) provides a digital twin solution for wind turbine applications. The focus of wtDigiTwin is to estimate loads, motions and environmental conditions for an operating wind turbine. The program uses supervisory control and data acquisition (SCADA) measurements as inputs, together with a wind turbine model. The wind industry is currently challenged by the high cost of operation and maintenance. These costs could be mitigated if component failures are predicted, but such predictions are difficult unless the turbines are equipped with expensive measuring devices. The alternative is to use a digital twin such as wtDigiTwin to estimate the necessary signals. wtDigiTwin can perform online prediction of signals that are otherwise not measured, using a limited set of reliable measurements and a physics-based model. The predicted signals can be used in applications that have direct cost benefits: 1) real-time estimation of the fatigue consumption of key components of the wind turbine; 2) root cause analyses and failure detections ; 3) lifetime reassessments ; 4) improvements to follow-on designs. The current version provides examples to estimate wind speed, thrust, torque, tower-top position, and tower loads on an onshore wind turbine using the following measurements tower top acceleration, generator torque, pitch, and rotational speed. The model combines a linear state-space model, a wind speed estimator, and a Kalman filter algorithm that integrates measurements with the state model to perform state estimations. The state space model is obtained either using OpenFAST linearizations, or using the yams package provided with the software.

Branlard, Emmanuel↗

Development of Graphite Thermal and Mechanical Modeling Capabilities in Grizzly

Nuclear-grade graphites are used extensively in the core designs of multiple types of advanced nuclear reactors. In the reactor environment, graphite is exposed over long durations to extreme conditions, including high temperatures, radiation and potentially molten salt and oxygen. Exposure to these conditions can cause several degradation mechanisms in graphite, including nonuniform volumetric strains induced by irradiation and thermal expansion, which lead to stresses that can compromise the performance of graphite components. Evaluating component integrity, predicting component performance over the reactor lifetime, and developing design standards all require robust tools for predicting fracture initiation and propagation in graphite structural components in nuclear reactors. This report documents progress in an ongoing effort to develop modeling and simulation tools in the Grizzly code for predicting the performance of graphite exposed to reactor conditions. Recent developments include a set of thermal and mechanical models that now include the IG-110, NBG-18, and H-451 graphite grades. Improvements have also been made to a nonlinear damaged plasticity model applicable to predicting damage under tension and compression to quasibrittle materials, including graphite. In addition, enhancements have been made to the extended finite element method implementation targeted at simulating graphite fracture. These include new capabilities for crack nucleation in the interior of a solid body, improved treatment of crack nucleation on free surfaces, and more robust modeling approaches for crack growth approaching free surfaces or other cracks.

36 MATERIALS SCIENCE↗

Significant life extension of lithium-ion batteries using compact metallic lithium reservoir with passive control

Both traditional graphite-based lithium-ion batteries and next generation silicon-based chemistries suffer significant capacity fade from loss of cyclable lithium due to continued solid-electrolyte interphase growth. A possible engineering solution to maintaining the capacity of cells is incorporating a metallic lithium reservoir and discharging the reservoir into a working electrode to make up for lost cyclable lithium. Here, metallic lithium reservoirs are inserted into both pouch- and cylindrical-format cells. Significant capacity recovery and lifetime extension are demonstrated for traditional graphite and Si/graphite-based cells. In this work, a combination of post-mortem characterization and modeling provide insight into how the lithium distribution as a function of position from reservoir vary with recovery rate. The potential of using passive control to potentially eliminate the need for extra wiring for the third electrode is explored using a simple resistor.

25 ENERGY STORAGE↗

Photoinitiated Reactions of Molecules and Radicals in Molecular Beams

The UV photochemistry of organic molecules is a fundamental process that governs reactions in the atmosphere, synthetic chemistry, processing of organic aerosols, and biological damage in living tissues. In many organic molecules, the ensuing evolution involves pathways that are in competition, giving rise to different products, isomerization, coupling to other electronic states, and secondary reactive collisions. Because photodissociation is usually fast (picoseconds to microseconds), these processes are far from equilibrium and are controlled by kinetic competition and dynamical forces. The work accomplished was focused primarily on the photochemistry of alpha-keto carboxylic acids, a group of acids produced from natural sources, which are implicated in aerosol formation and biological processes. In the atmosphere, they are destroyed mainly by solar radiation. Studying their photochemistry has been surprisingly difficult because of the complexity of their excited electronic states, and the effect of collisions and secondary reactions. The second project investigated the lifetime of excited electronic states of pyrazine and picoline and had both experimental and theoretical aspects. The work focused on a model molecule, pyruvic acid (PA), because it was hypothesized that it should be a good source of the unstable carbene, methylhydroxycarbene (MHC). PA has an internal hydrogen bond that controls the evolution of its decomposition. The decomposition was studied following excitation to two of its lowest excited states reached by laser irradiation at 351 and 193 nm. The photodissociation dynamics in the absence and presence of collisions was monitored and compared. Understanding the UV photochemistry requires the use of complementary experimental approaches. Two methods were enlisted, which together generated a comprehensive and detailed set of results: (i) The time-sliced velocity map imaging (SVMI) instrument at USC was exploited to determine kinetic energy release of fragments, fast dissociation timescales, and internal state distributions of fragments for which Resonance Enhanced Multiphoton Ionization (REMPI) schemes exist; and (ii) The multiplexed photoionization mass spectrometer (MPIMS) setup developed at the Sandia Combustion Research Facility was used for product discovery, achieved by exploiting tunable narrowband VUV radiation at the Advanced Light Source (ALS), and to follow in real time their subsequent unimolecular and bimolecular reactions. The experimental conditions ranged from collisionless molecular beams to study nascent products to flow reactors of variable pressures to study subsequent bimolecular reactions of the products. The goals stated above were successfully accomplished. By exciting PA to its lowest excited state, MHC was identified as the only primary product and its isomerization to vinylalcohol and acetaldehyde was directly observed in real time. Moreover, we reported the first bimolecular reaction of MHC, which was with acetaldehyde, and identified its reaction product. This paves the way for the study of other reactions of this important carbene intermediate. When excitation was carried out at 193 nm, which imparted much higher energy to PA, many more products were directly observed in real time, some deriving from three-body dissociation. Quantitative branching ratios and secondary reactions of radical products were also determined and analyzed. The studies of pyrazine and picoline focused on the second excited state of these molecules and showed (via ionization studies) that their excited states were very short lived (<100 fs) because of efficient couplings to lower electronic states via vibronic coupling. Theoretical work on modeling the absorption spectrum and decay mechanisms of the excited states are in progress in collaboration with theoreticians.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bimetallic Coinage Metal Complexes of Tetradentate ortho Ter arylene Ligands

The synthesis, structural and photophysical properties of five bimetallic coinage metal complexes of three tetradentate charge-transfer (CT) ligands are presented. The ligand structures incorporate donor/acceptor moieties electronically decoupled by ortho connection to a bridging biphenylene group. The M M distances observed in the crystal structures of the bimetallic complexes are shorter than the sum of the Van der Waals radii of the metal ions, suggesting stabilizing interactions between the d10 metal centers. Additionally, short distances between the bridging biphenylene and metal atoms suggest arylene metal interactions. Bimetallic Cu, Ag, and Au complexes of the ligand incorporating a carbazole donor and pyridyl acceptor (N2R22-) show absorption and emission energies that trend with the ionization potential of each metal, indicating metal character in the excited state. These properties contrast with our previously reported mononuclear Zn complex of N2R22-The structural and photophysical properties of five bimetallic d10 coinage metal complexes were presented. The M M distances observed in the crystal structures of the bimetallic complexes are shorter than the sum of the metals’ Van der Waals radii, suggesting attractive interactions between the d10 metal centers. Additionally, short distances between the bridging biphenylene and metal atoms suggest arylene metal interactions. The absorption and emission spectra of the bimetallic complexes redshift based on the oxidation potential of the metal ion. This suggests involvement of metal based orbitals in the excited state transitions of the bimetallic complexes, which was corroborated by molecular modeling. High photoluminescent quantum yields were observed in solution and in rigid media (up to PL = 0.75), and the excited state lifetimes in solution were found to exceed several microseconds.

Shariaty, Darius Allen [University of Southern Cal↗

Modeling of Marginal Cost for PV Inverter Ancillary Services Considering Inverter Aging under Transactive Energy Framework

PV inverters can provide ancillary services while providing active power. Transactive energy system (TES) incentivizes PV inverter to provide ancillary services and compensates for the cost of additional power losses due to additional reactive power production. However, providing ancillary services can shorten the lifetime of the PV inverter since additional reactive power increases the thermal stress of the PV inverter. This paper theoretically derives the lifetime shortening effect of a PV inverter when providing ancillary services. Based on the lifetime estimation, an improved marginal cost curve for the PV inverter ancillary services is derived. The improved marginal cost quantitively describe the willingness of the PV inverter to provide ancillary services by the given active power production and the ambient temperature. The proposed model is validated by a simulation case study.

Liu, Yunting↗

A Hybrid Physics-Based, Data-Driven Approach to Model Damage Accumulation in Corrosion of Polymeric Adhesives

The degradation of polymeric adhesives in dissimilar joints is a menace to electric and structural components of the automotive industry. In polymeric adhesives, failure often occurs due to damage accumulated from discrete environmental sources—thermal degradation, oxidation, hydrolysis, radiation, and moisture—that are combined with progressive damage mechanisms, such as aging and fatigue. Because most damage mechanisms that lead to degradation act in parallel, the estimation of the lifetime of a polymeric material becomes a significant reliability issue, no study currently exists that can simultaneously consider even two of these phenomena. Most current efforts are directed toward a single-phenomenon, single-model approach in which a model is developed to cover one specific damage mechanism. While this approach is advantageous in exploring single mechanisms, it is strongly inconclusive for degradation that occurs by multiple damage mechanisms. Our team plans to take a fresh perspective by designing a hybrid constitutive/data-driven approach that allows models of different damage mechanisms to be integrated into one model and then used to explore the degradation-induced failure of polymeric adhesives. The theoretical-computational part of this work is divided into four research components as described in the Approach section below.

36 MATERIALS SCIENCE↗

Review—“Knees” in Lithium-Ion Battery Aging Trajectories

Lithium-ion batteries can last many years but sometimes exhibit rapid, nonlinear degradation that severely limits battery lifetime. In this work, we review prior work on “knees” in lithium-ion battery aging trajectories. We first review definitions for knees and three classes of “internal state trajectories” (termed snowball, hidden, and threshold trajectories) that can cause a knee. We then discuss six knee “pathways”, including lithium plating, electrode saturation, resistance growth, electrolyte and additive depletion, percolation-limited connectivity, and mechanical deformation—some of which have internal state trajectories with signals that are electrochemically undetectable. Additionally, we also identify key design and usage sensitivities for knees. Finally, we discuss challenges and opportunities for knee modeling and prediction. Our findings illustrate the complexity and subtlety of lithium-ion battery degradation and can aid both academic and industrial efforts to improve battery lifetime.

25 ENERGY STORAGE↗

Dry Deposition of Atmospheric Aerosols: Approaches, Observations, and Mechanisms

Aerosols are liquid or solid particles suspended in the atmosphere, typically with diameters on the order of nanometers to microns. These particles impact air quality and the radiative balance of the planet. Dry deposition is a key process for the removal of aerosols from the atmosphere and plays an important role in controlling the lifetime of atmospheric aerosols. Dry deposition is driven by turbulence and shows a strong dependence on particle size. This review summarizes the mechanisms behind aerosol dry deposition, including measurement approaches, field observations, and modeling studies. We identify several gaps in the literature, including deposition over the cryosphere (i.e., snow and ice surfaces) and the ocean; in addition, we highlight new techniques to measure black carbon fluxes. While recent advances in aerosol instrumentation have enhanced our understanding of aerosol sources and chemistry, dry deposition and other loss processes remain poorly investigated.

Chemistry↗

Description of FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment

The urgency to deliver fusion power is growing now more than ever, with increasing pressure for both public programs and private companies to meet milestones timelines and overcome significant remaining technical challenges to ensure growth of a nascent fusion industry in time to meet rapidly growing clean energy demands. With incredible advancements in computation and years of investment in fusion model development and validation, integrated modeling is poised to fill a key role in accelerating the timeline to a fusion pilot plant (FPP). Future fusion pilot plants will operate in regimes far beyond current experience, and device design will rely on physics-based prediction and extrapolation. Many concepts will also rely on simulation to assess safety (shielding, tritium management, materials activation and lifetimes), economics and scalability before the decision to build. Importantly, integrated simulation can be used to reveal and solve the complexities of system integration that may otherwise not be apparent in physical components or models developed in isolation. New experimental test facilities that produce relevant conditions to validate and resolve key technical challenges for various subsystems (materials, blankets, fuel cycle, etc.) have been repeatedly called for by the fusion community but are not yet realized. Integrated modeling has an important role in identifying realistic load conditions (thermal, electromagnetic, plasma, neutron and photon loads, etc.) and defining the components and experiments for these test facilities in order to ensure meaningful validation that sufficiently reduces modeling uncertainties and technical risk for the full integrated reactor. The Fusion REactor Design and Assessment (FREDA) SciDAC project is building a component-based integrated modeling framework & data structure to enable self-consistent, multi-fidelity, iterative optimization workflows for the fusion reactor design process. FREDA aims to shorten the time to viable designs by providing a set of flexible workflows to support the various stages of the design process using an integrated model hierarchy, ranging from the simple analytic descriptions to the highest fidelity, theory-based plasma and engineering modeling developed by the fusion and fission communities. These tools are expected to be needed for timely support of FPP design in the milestone program and in the FIRE collaboratives. The plasma simulation backbone of FREDA is IPS-FASTRAN with newly developed coupled Core-Edge Pedestal-SOL (CESOL) workflows, which is being extended to the far-SOL region up to the plasma facing components. FREDA incorporates the FERMI engineering modeling suite and will enable self-consistent evaluation of the thermal shields, limiters, blanket, magnets, and other surrounding structures with predictions of temperatures, erosion, dpa, activation, tritium generation and transport, creep, corrosion, material degradation, etc. Parametric generation of 3D CAD enables rapid iteration of component geometry in response to plasma and loading specifications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Dependence of Deep Convective Cell Properties on Meteorological and Aerosol Conditions during TRACER

Deep convective cells significantly influence Earth’s energy balance and water cycle. However, their accurate representation in numerical models remains challenging due to their small spatiotemporal scales and limited observational constraints. This study examines over ∼400 deep convective cells near Houston, observed by a dual-polarization C-band radar during the Tracking Aerosol Convection Interactions Experiment (TRACER) intensive observation period (June–September 2022). Cells are categorized by lifetime into short-lived (<40 min), intermediate-lived (40–80 min), and long-lived (80+ min) groups. Long-lived cells were broader (∼13.2 km at 2–4-km height) and deeper (∼11.4 km) than short-lived cells (∼6.4-km width, ∼7.31-km height). Using random forest (RF) modeling and correlation analyses, precipitable water vapor (PWV), 2–6-km lapse rate, 0–8-km bulk shear, and fine aerosol mass concentration (Mass_f) are identified as key predictors of cell lifetime. Higher PWV is associated with significantly longer convective cell lifetimes compared to the low-PWV group, particularly within low 2–6-km temperature lapse rate (LR_26km), moderate-to-higher 0–8-km bulk shear (BS_08km), and low-to-moderate Mass_f environments. RF analysis also identifies low-level (0–2 km) equivalent potential temperature, PWV, Mass_f, and surface latent heat flux as key predictors for cell width and height. Short-lived cells have higher aerosol number concentrations (500–1000-nm size range), linked to onshore wind conditions and marine aerosols; however, their low concentration suggests the sensitivity may reflect associated meteorological regimes rather than a direct aerosol effect. Long-lived cells have higher concentrations of organic and sulfate aerosols, while short-lived cells exhibit higher black carbon concentrations. These results highlight the intricate dependence of convective cell lifetimes and structure on environmental moisture, thermodynamics, wind shear, and aerosol characteristics.

54 ENVIRONMENTAL SCIENCES↗

Quantifying the reduction in cavitation-induced erosion damage in the Spallation Neutron Source mercury target by means of small-bubble gas injection

Here, a model developed to represent the progress of erosion damage in liquid-metal spallation target vessels was modified to incorporate the effect of gas injection on the erosion rate. The liquid mercury target system for the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory now operates with helium gas injection to reduce target vessel fatigue stress and cavitation-induced erosion damage. Erosion damage is a primary degradation phenomenon affecting the service life of SNS target vessels, and cavitation mitigation techniques, such as small-bubble gas injection, have been implemented to reduce damage and extend target lifetimes. Erosion depths in samples removed from SNS targets after operation were measured using laser line scanning. These measurements confirmed that gas injection reduced erosion damage. However, quantifying the damage reduction due to gas injection was complicated by variations in lifetime, power, and gas injection rates between different targets. In this study, the operating power and gas injection rate of targets were incorporated into an erosion damage prediction model to quantify their effects on erosion damage reduction. Values of a power scaling factor, β, were calculated by comparing modeled with measured erosion damage. These values indicate that the use of gas injection at the SNS reduced damage to a level equivalent to operating targets without gas injection at 35–47% of the actual beam power. To account for the gas injection effect on the cavitation damage, a simple exponential form based on analysis of the scaling factor β was developed to incorporate the gas rate history with a scaling factor γ in the erosion damage modeling.

47 OTHER INSTRUMENTATION↗

A plant-by-plant strategy for high-ambition coal power phaseout in China

More than half of current coal power capacity is in China. A key strategy for meeting China’s 2060 carbon neutrality goal and the global 1.5 °C climate goal is to rapidly shift away from unabated coal use. Here we detail how to structure a high-ambition coal phaseout in China while balancing multiple national needs. We evaluate the 1037 currently operating coal plants based on comprehensive technical, economic and environmental criteria and develop a metric for prioritizing plants for early retirement. We find that 18% of plants consistently score poorly across all three criteria and are thus low-hanging fruits for rapid retirement. We develop plant-by-plant phaseout strategies for each province by combining our retirement algorithm with an integrated assessment model. With rapid retirement of the low-hanging fruits, other existing plants can operate with a 20- or 30-year minimum lifetime and gradually reduced utilization to achieve the 1.5 °C or well-below 2 °C climate goals, respectively, with complete phaseout by 2045 and 2055.

20 FOSSIL-FUELED POWER PLANTS↗