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At least 217 records · Page 12

Evaluation and Demonstration of Blockchain Applicability Framework

Blockchain technology has been gaining great interest from a variety of industry sectors, including financial, food processing, and power and energy markets. Realizing the strength of blockchain technology beyond the successful application in the cryptocurrency arena, researchers have been evaluating and using blockchain for applications such as supply chain management, transactive industry (both financial and energy), system integrity, device cybersecurity, identity management, and much more. One of the unique elements of the blockchain technology that made it such a captivating technology to researchers is its plethora of features. Some of the features include smart contracts, cryptocurrency and tokenizing, immutable distributed ledger, cryptographic hashing, and digital signature. In addition, there are multiple types of blockchains, such as permissioned/private and permissionless/public, and various consensus models, such as proof-of-work, proof-of-authority, proof-of-burn, and proof-of-stake. Therefore, it is often non-trivial to determine if an application requires a blockchain. If so, what kind of blockchain and consensus is most appropriate? This paper discusses the blockchain applicability framework (BAF), which was specifically designed with the purpose to answer those questions. BAF is divided into five domains, 18 subdomains, and about 100 controls. It is designed to ingest detailed user requirements to perform a weighted evaluation that is built on mathematical constructs to determine the ideal combination of blockchain that is appropriate for an application. Along with the core logical formulation of BAF, this paper depicts the efficacy of BAF through two use cases

Gourisetti, Sri Nikhil G.↗

Identifying Entangled Physics Relationships Through Sparse Matrix Decomposition to Inform Plasma Fusion Design

We report a sustainable burn platform through inertial confinement fusion (ICF) has been an ongoing challenge for over 50 years. Mitigating engineering limitations and improving the current design involves an understanding of the complex coupling of physical processes. While sophisticated simulation codes are used to model ICF implosions, these tools contain necessary numerical approximation but miss physical processes that limit predictive capability. Identification of relationships between controllable design inputs to ICF experiments and measurable outcomes (e.g., neutron yield, neutron velocity, areal density) from performed experiments can help guide the future design of experiments and development of simulation codes, to potentially improve the accuracy of the computational models used to simulate ICF experiments. We use sparse matrix decomposition methods to identify clusters of a few related design variables. Sparse principal component analysis (SPCA) identifies groupings that are related to the physical origin of the variables (laser, hohlraum, and capsule). A variable importance analysis finds that in addition to variables highly correlated with neutron yield, such as picket power and laser energy, variables that represent a dramatic change of the ICF design, such as number of pulse steps, are also very important. The obtained sparse components are then used to train a random forest (RF) regression surrogate for predicting total yield. The RF performance on the training and testing data compares with the performance of the RF trained using all the design variables considered. This work is intended to inform design changes in future ICF experiments by augmenting the expert intuition and simulation results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Spatiotemporal Controls on the Delivery of Dissolved Organic Matter to Streams Following a Wildfire

Warmer and drier climate has contributed to increased occurrence of large, high severity wildfires in the Pacific Northwest, drawing concerns for water quality and ecosystem recovery. While nutrient fluxes generally increase post-fire, the composition of organic matter (OM) transported to streams immediately following a fire is poorly constrained, yet can play an integral role in downstream water quality and biogeochemistry. Here, we quantified the spatiotemporal patterns of dissolved OM (DOM) chemistry for five streams burned by wildfires in Oregon, USA in 2020. We sampled over a 24-hour storm event one month after the fire, revealing variable temporal behavior in DOM dynamics. DOM chemistry was directly related with burn severity spatially. Specifically, nitrogen and aromatic character of DOM increased in streams burned at greater severity. Our results suggest a spatial overprinting of DOM dynamics immediately following fire activity and highlight a key gap in our knowledge of post-fire DOM transport to streams.

54 ENVIRONMENTAL SCIENCES↗

Compact automated apparatus for rapid astatine recovery from nitric acid media: Design, application, and impurity characterization

We report automation of irradiated bismuth target dissolution and astatine recovery from nitric acid media has been achieved at Texas A&M University. This process can be controlled remotely; it does not require any chemical treatment or evaporation of dissolution solution prior to the separation of above-mentioned elements on an extraction chromatography column, making the final product ready within 20 min. The accompanying radio-impurities have been identified and successfully separated from astatine, leading to greater than 99% radiopurity of the desired fractions. The system consists of only one pump and a set of LabVIEW controlled valves, and allows the connection of up to 10 different columns, providing the opportunity to prepare a variety of air dry columns, which can be different column geometries, containing astatine ready for further chemistry or shipment to desired facilities.

42 ENGINEERING↗

Combined Experimental/Numerical Study of the Soot Formation Process in a Gasoline Direct-Injection Spray in the Presence of Laser-Induced Plasma Ignition

Here, combustion issued from an eight-hole, direct-injection spray was experimentally studied in a constant-volume pre-burn combustion vessel using simultaneous high-speed diffused back-illumination extinction imaging (DBIEI) and OH* chemiluminescence. DBIEI has been employed to observe the liquid-phase of the spray and to quantitatively investigate the soot formation and oxidation taking place during combustion. The fuel-air mixture was ignited with a plasma induced by a single-shot Nd:YAG laser, permitting precise control of the ignition location in space and time. OH* chemiluminescence was used to track the high-temperature ignition and flame. The study showed that increasing the delay between the end of injection and ignition drastically reduces soot formation without necessarily compromising combustion efficiency. For long delays between the end of injection and ignition (1.9 ms) soot formation was eliminated in the main downstream charge of the fuel spray. However, poorly atomized and large droplets formed at the end of injection (dribble) eventually do form soot near the injector even when none is formed in the main charge. The quantitative soot measurements for these spray and ignition scenarios, resolved in time and space, represents a significant new achievement. Reynolds-averaged Navier-Stokes (RANS) simulations were performed to assess spray mixing and combustion. An analysis of the predicted fuel-air mixture in key regions, defined based upon experimental observations, was used to explain different flame propagation speeds and soot production tendencies when varying ignition timing. The mixture analysis indicates that soot production can be avoided if the flame propagates into regions where the equivalence ratio (Φ) is already below 2. Reactive RANS simulations have also been performed, but with a poor match against the experiment, as the flame speed and heat-release rate are largely over estimated. This modeling weakness appears related to a very high level of turbulent viscosity predicted for the high-momentum spray in the RANS simulations, which is an important consideration for modeling ignition and flame propagation in mixtures immediately created by the spray.

42 ENGINEERING↗

Advances in prediction of tokamak experiments with theory-based models

The successful validation of theory-based models of transport, MHD stability, heating and current drive, with tokamak measurements over the last 20 years, has laid the foundation for a new era where these models can be routinely used in a "predict first" approach to design and predict the outcomes of experiments on tokamaks today. The capability to predict the plasma confinement and core profiles with a quantified uncertainty, based on a multi-machine, international, database of experience, will provide confidence that a proposed discharge will remain within the operational limits of the tokamak. Developing this predictive capability for the first generation of burning plasma devices, beginning with ITER, and progressing to tokamak demonstration reactors, is a critical mission of fusion energy research. Major advances have been made implementing this predict first methodology on today's tokamaks. In this work, an overview of several of these recent advances will be presented, providing the integrated modeling foundations of the experimental successes. The first steps to include boundary plasmas, and tokamak control systems, have been made. A commitment to predicting experiments as part of the planning process is needed in order to collect predictive accuracy data and evolve the models and software into a robust whole discharge pulse design simulator.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Plasma-Assisted Pre-Chamber Ignition System for Highly Dilute Stoichiometric Heavy-Duty Natural Gas Engines (Final Technical Report)

This project explored advanced ignition technologies to significantly enhance efficiency and reduce operating costs for heavy-duty natural gas engines operating at stoichiometric conditions, while meeting ultra-low NOx emission standards. The main goal was to develop and validate a plasma-assisted pre-chamber ignition system that could deliver at least a 2% increase in brake thermal efficiency (BTE) and a 4% decrease in total cost of ownership (TCO) compared to a typical multi-cylinder engine with three-way catalyst aftertreatment, ensuring compatibility with the expected 2027 EPA/CARB regulations. In the first half of the project, the research team concentrated on developing and testing plasma-assisted pre-chamber ignition using nanosecond pulsed discharges. Extensive experiments were conducted in an optically accessible rapid-compression and expansion machine, a constant-volume chamber, and an optical single-cylinder engine. Experiments were coupled with CFD simulations. The work produced unique insights into pre-chamber flame formation, jet ignition, dilution effects, and flame quenching at pressures, temperatures, and dilution levels relevant to engines. Although plasma-assisted ignition showed promise in controlled lab settings, the research also identified fundamental and practical challenges when applying this technology to real engine conditions. Midway through the project, a crucial pivot was made, guided by three key findings. First, the power electronics required for nanosecond plasma discharges were found to be too costly for commercial use, undermining the project’s cost-of-ownership goals. Second, nanosecond plasma ignition was highly sensitive to turbulent flow in the pre-chamber, resulting in lower ignition reliability than traditional spark under engine-like conditions. Third, achieving a truly diffuse low-temperature plasma at high pressures near top dead center was not possible, reducing the anticipated chemical enhancement benefits. These results collectively suggested that continuing with plasma-assisted ignition was unlikely to meet both efficiency and cost objectives. In response, the project shifted focus to a more realistic approach: enhancing traditional spark-based pre-chamber ignition with significantly less spark energy. Using insights gained earlier in the project, the team redesigned the pre-chamber to maintain high dilution tolerance and quick combustion, even with lower ignition energy. Testing confirmed that with optimized pre-chamber design and combustion timing, a lower-energy spark could reliably ignite highly diluted stoichiometric mixtures, reduce burn time, and boost thermal efficiency. Final engine testing and techno-economic analysis verified that this revised approach successfully achieved the project goals. The optimized pre-chamber ignition system provided over a 2% increase in calculated brake thermal efficiency compared to the baseline engine. Notably, the lower ignition energy and simplified hardware reduced component stress, extended maintenance intervals, and lowered the total cost of ownership. When used with stoichiometric operation and traditional three-way aftertreatment, the system remained compatible with near-zero NOx emissions targets without increasing cost or complexity in the emissions control system. In summary, although the project deviated from its initial plasma-assisted ignition idea, the work produced a more practical and commercially viable solution. The results show that precisely optimized, low-energy pre-chamber spark ignition can significantly improve efficiency and reduce overall ownership costs for heavy-duty natural gas engines. This directly aligns with DOE goals for cleaner, more efficient, and cost-effective transportation technologies.

03 NATURAL GAS↗

How do soil microbes shape ecosystem biogeochemistry in the context of global change?

Earth system models disagree on the future of global soil carbon C, with projections ranging from losses of 70 Pg to gains of 250 Pg by the year 2100 (Todd-Brown et al., 2014). This disagreement is due, in part, to the high degree of uncertainty in the mechanisms that control soil C, the largest dynamic pool of organic C on Earth. It remains unclear how climate change, rising atmospheric CO2 levels, and other environmental changes will combine to affect global soil C. As key engineers of biogeochemical cycling, microbes play a crucial role in soil C responses to these environmental changes. Yet, the path toward representing microbes in soil models remains uncertain. Furthermore, we address four burning questions relevant for modelling microbial ecological, evolutionary, and biogeochemical processes in soils: (1) What is the role of soil microbes in biogeochemical cycling? (2) Does microbial community composition matter for soil carbon cycling? (3) Which ecological and evolutionary processes contribute to functional changes? (4) How should we model microbial eco-evolutionary mechanisms in soil C models?

54 ENVIRONMENTAL SCIENCES↗

Technology Enablers for Advanced Gasoline Compression Ignition Engines

To meet current emission regulations and increasingly demanding global fleet CO2 standards on fuel economy and future trends towards life cycle GHG emissions, advanced combustion engines remain significant in the passenger vehicle sector to achieve high efficiency and low emissions over the full operating range. Lean burn gasoline compression ignition (GCI) technology has shown to have the most potential in reaching these goals, although it faces challenges in the operating range. In this study, an advanced GCI engine is considered with the capability to operate under two combustion modes, namely low temperature combustion (LTC) and GCI. They are enabled with the use of two Hyundai in-house developed technologies; an advanced valve control mechanism known as continuously variable valve duration (CVVD) and a high-pressure gasoline injection system. At low load, the engine utilizes dual CVVD and dual CVVT (continuously variable valve timing) mechanisms for both intake and exhaust valvetrains to enable NVO (negative valve overlap) to trap hot residuals. The hot residuals enable low load auto-ignition, and the phasing control of that auto-ignition is achieved by varying the degrees of NVO, and in turn, the amount of hot residuals. This is done in real time with respect to the changes in engine loads or operating conditions, significantly improving cylinder-phasing control in LTC mode, and subsequently is able to realize a fuel economy gain and reduced emission benefits. Early direct injection during NVO or intake stroke is used to form homogenous or quasi-homogenous air-fuel mixture for LTC. At mid to high loads, late direct injection of gasoline or GCI mode is employed to take advantage of the high volatility and high resistance to auto-ignition of gasoline fuel, so that diesel-engine like high combustion efficiency can be achieved with lower soot emissions for the same NOx level as diesel combustion. In this paper, the key control and fueling technologies that enable this multiple mode combustion are introduced, and the resultant analysis on engine test and CFD simulation at LTC and GCI operating conditions are presented in detail.

Gasoline compression ignition, low temperature com↗

Best Practices for Measuring the Modulation Transfer Function of Video Endoscopes

Endoscopes are crucial for assisting in surgery and disease diagnosis, including the early detection of cancer. The effective use of endoscopes relies on their optical performance, which can be characterized with a series of metrics such as resolution, vital for revealing anatomical details. The modulation transfer function (MTF) is a key metric for evaluating endoscope resolution. However, the 2020 version of the ISO 8600-5 standard, while introducing an endoscope MTF measurement method, lacks empirical validation and excludes opto-electronic video endoscopes, the largest family of endoscopes. Measuring the MTF of video endoscopes requires tailored standards that address their unique characteristics. This paper aims to expand the scope of ISO 8600-5:2020 to include video endoscopes, by optimizing the MTF test method and addressing parameters affecting measurement accuracy. We studied the effects of intensity and uniformity of image luminance, chart modulation compensation, linearity of image digital values, auto gain control, image enhancement, image compression and the region of interest dimensions on images of slanted-edge test charts, and thus the MTF based on these images. By analyzing these effects, we provided recommendations for setting and controlling these factors to obtain accurate MTF curves. Our goal is to enhance the standard’s relevance and effectiveness for measuring the MTF of a broader range of endoscopic devices, with potential applications in the MTF measurement of other digital imaging devices.

47 OTHER INSTRUMENTATION↗

Reducing NOx Emissions in Ammonia Combustors

Ammonia continues to attract growing interest as a carbonneutral replacement fuel, motivating numerous research efforts toward understanding fundamental ammonia combustion characteristics. A major challenge for the use of ammonia is the development of combustor technologies for mitigating potentially high NOx emissions from the fuel-bound nitrogen chemical pathways to acceptable levels. Our work focuses on a staged RQL combustor architecture for minimizing the NOx emission levels through burning fuel-rich in the primary stage to formcombustion products containing significant levels of hydrogen in addition to nitrogen and water with minimal NOx formation. The subsequent quench and burnout stages of the combustor must then quickly burn residual hydrogen with flame-temperatures moderated by nitrogen and water forming in the first stage. Chemical Reactor Network modeling was used to understand and identify optimal stoichiometry and residence times in each stage for minimizing NOx emissions and to quantify pressure and temperature effects. Reducing the overall NOx emissions requires relatively long residence times in the primary stage to achieve near equilibrium NO levels due to kinetically controlling processes. For conditions relevant to gas turbines (e.g., 30 atm), our work indicates that NOx emissions below 20 ppm are theoretically achievable in a staged RQL combustor architecture. However, these emission predictions significantly depend on the accuracies of currently available chemical kinetic mechanisms which have not been extensively validated under elevated pressure and temperature conditions relevant to gas turbines.

10 SYNTHETIC FUELS↗

Upgrade of the Materials Analysis Particle Probe (MAPP-U) to decipher the impact of lithium-based surfaces on NSTX-U plasma behavior

Understanding the plasma wall interaction (PWI) remains a critical issue for the feasibility of thermonuclear magnetic fusion energy solutions. Key issues with PWI mechanisms in fusion tokamak reactors include: evolution of surface chemistry and its role on hydrogen retention. In particular how low-Z coatings such as lithium can impact the behavior of plasma at the edge and in the core. PMI (plasma-material interactions) are particularly important for strategies that involve low-recycling regimes and the use of lithium PFS (plasma-facing surfaces) to attain them, as in the case of NSTX-U. Recent reports have indicated the importance of access to the evolving plasma-facing surface during and in-between plasma discharges. Changes in surface chemistry and morphology due to ion bombardment and the difficulty of diagnosing plasma-facing surfaces, especially reactive surfaces, complicate the development of a predictive understanding of the wall and its interaction with the plasma. Consequently, this impairs the ability to design advanced PFC materials for future plasma-burning fusion reactors and appropriate PMI code validation. The Materials Analysis Particle Probe (MAPP) is an established and on-going PMI probe diagnostic system compatible with the highly chemically reactive system of lithium and boron coatings adopted by the NSTX-U research program. MAPP is the first PMI diagnostic to capture the surface physics and chemistry in-vacuo in a fusion tokamak system and correlate this data to controlled plasma shots. Currently MAPP captures this information at a fixed radial location at the NSTX-U outboard divertor region. The MAPP diagnostic has enabled understanding of the near-surface and surface chemistry of complex evolving lithiated and borated carbon-based PFC surfaces retention and transport of hydrogen. Coupled to atomistic simulations in collaboration with P. Krstic of Stony Brook U. MAPP has been very successful in achieving high-impact scientific research in its current grant period evidenced by two invited review articles and over 20 peer-reviewed manuscripts and over 40 contributed and invited presentations at both national and international conferences.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Energetic particle physics: Chapter 7 of the special issue: on the path to tokamak burning plasma operation

We review the physics of energetic particles (EPs) in magnetically confined burning fusion plasmas with focus on advances since the last update of the ITER Physics Basis (Fasoli et al 2007 Nucl. Fusion 47 S264). Topics include basic EP physics, EP generation, diagnostics of EPs and instabilities, the interaction of EPs and thermal plasma instabilities, EP-driven instabilities, energetic particle modes (EPMs), and turbulence, linear and nonlinear stability and simulation of EP-driven instabilities and EPMs, 3D effects, scenario optimization strategies based on EP phase-space control, EPs in reduced field scenarios in ITER before DT, and the physics of runaway electrons. We describe the simulation and modeling of EPs in fusion plasmas, including instability drive and damping as well as EP transport, with a range of approaches from first-principles to reduced models, including gyrokinetic simulations, kinetic-MHD models, gyrofluid models, reduced models, and semi-analytical approaches.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Molecular-scale mechanisms of CO 2 mineralization in nanoscale interfacial water films

The calamitous impacts of untethered carbon emission from fossil-fuel-burning energy infrastructure calls for accelerated development of large-scale CO 2 capture, utilization, and storage technologies that are underpinned by fundamental understanding of molecular-level chemical processes. In the subsurface, rocks rich in divalent metals can react with CO 2 , permanently sequestering it in the form of stable metal carbonate minerals, with the CO 2 -H 2 O composition of the post-injection pore fluid acting as a primary control variable. Herein, we compare mechanistic reaction pathways for aqueous-mediated carbonation with carbon mineralization occurring in nanoscale adsorbed water films. In the extreme of pores filled with a CO 2 -dominant fluid, carbonation reactions are confined to nanometer-thick water films coating mineral surfaces, which enable metal cation release, transport, nucleation, and crystallization of metal carbonate minerals. Though seemingly counterintuitive, laboratory studies have demonstrated facile carbonation rates in these low water environments, which in recent years has begun to be better understood in mechanistic detail. The overarching objective of this review is to delineate the unique underlying molecular-scale reaction mechanisms that govern CO 2 mineralization in these reactive and dynamic quasi-2D interfaces. Here. we highlight the importance of understanding unique properties in thin water films, such as how water dielectric properties, and consequently ion solvation/hydration behavior, can change under nanoconfinement. We conclude by identifying important frontiers for future work and opportunities to exploit these fundamental chemical insights for decarbonization technologies in the 21st century.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

On The Deflagration to Detonation Transition in 1.65 g cm -3 Pentaerythritol Tetranitrate

The LANL Weapons Response Group is charged with making determinations for a wide range of scenarios regarding the probability that inadvertent ignition of the high explosive (HE) components might cause nuclear yield, or dispersal of special nuclear material, during assembly/disassembly operations at the Pantex Plant. These scenarios are categorized based on the nature of the ignition causing stimulus, i.e. impact, electrostatic discharge, pressure-shear, etc. However, for all of these scenarios, regardless of how ignition is achieved, there must also be a credible path for the burning HE to transition to detonation for yield or dispersal to occur. If it can be determined that there is no feasible path for deflagration-to-detonation transition (DDT), the scenario space that requires mitigative action is greatly reduced. The strategy to support Weapons Response determinations is to use experimentation and observation to evaluate HE response in severe “overtest” configurations. To increase with confidence in the margins of HE response, these overtests are designed, by controlling parameters known to enhance HE response violence, to be more severe than what is ever encountered in the actual operations environment at the Plant. This study is focused on DDT in pentaerythritol tetranitrate (PETN), a high explosive that is used in LANL’s detonators. PETN is known to be able to DDT at certain densities, and this represents a safety concern. The PETN in LANL’s detonators is commonly a density of 1.65 g cm -3 . However, DDT has never been observed at this density in PETN. In this work, we studied the DDT reaction in 1.65 g cm -3 PETN to determine whether DDT is possible at this density, and if so, what length of PETN is required for the transition to occur. In any of the tests conducted, we did not observe DDT in 1.65 g cm -3 PETN. It is possible that the DDT length for 1.65 g cm -3 PETN is greater than 6” (the available run length in the experiments), but this length is simply not available in a detonator, and is therefore not a concern.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Interpreting machine learning prediction of fire emissions and comparison with FireMIP process-based models

Annual burned areas in the United States have increased 2-fold during the past decades. With more large fires resulting in more emissions of fine particulate matter, an accurate prediction of fire emissions is critical for quantifying the impacts of fires on air quality, human health, and climate. This study aims to construct a machine learning (ML) model with game-theory interpretation to predict monthly fire emissions over the contiguous US (CONUS) and to understand the controlling factors of fire emissions. The optimized ML model is used to diagnose the process-based models in the Fire Modeling Intercomparison Project (FireMIP) to inform future development. Results show promising performance for the ML model, Community Land Model (CLM), and Joint UK Land Environment Simulator-Interactive Fire And Emission Algorithm For Natural Environments (JULES-INFERNO) in reproducing the spatial distributions, seasonality, and interannual variability of fire emissions over the CONUS. Regional analysis shows that only the ML model and CLM simulate the realistic interannual variability of fire emissions for most of the subregions (r >0.95 for ML and r =0.14~0.70 for CLM), except for Mediterranean California, where all the models perform poorly (r =0.74 for ML and r <0.30 for the FireMIP models). Regarding seasonality, most models capture the peak emission in July over the western US. However, all models except for the ML model fail to reproduce the bimodal peaks in July and October over Mediterranean California, which may be explained by the smaller wind speeds of the atmospheric forcing data during Santa Ana wind events and limitations in model parameterizations for capturing the effects of Santa Ana winds on fire activity. Furthermore, most models struggle to capture the spring peak in emissions in the southeastern US, probably due to underrepresentation of human effects and the influences of winter dryness on fires in the models. As for extreme events, both the ML model and CLM successfully reproduce the frequency map of extreme emission occurrence but overestimate the number of months with extremely large fire emissions. Comparing the fire PM 2.5 emissions from the ML model with process-based fire models highlights their strengths and uncertainties for regional analysis and prediction and provides useful insights into future directions for model improvements.

54 ENVIRONMENTAL SCIENCES↗

Multi-machine validation of plasma initiation modelling and prospects for future devices: Predicting plasma initiation using only hardware design and control room input data

This paper reports on the generic prediction capability of full electromagnetic plasma initiation modelling with DYON, which was carried out for the first time in fusion research by the joint modelling of the International Tokamak Physics Activity—Integrating Operation Scenario group. The following devices were included in the experiment database: VEST (spherical torus, copper coils, Stainless steel wall, R/a = 0.3 m/0.2 m, V v = 3.7 m 3 ), MAST-U (spherical torus, copper coils, C wall, R/a = 0.7 m/0.5 m, V v = 55 m 3 ), EAST (conventional tokamak, superconducting coils, metallic wall, R/a = 1.85 m/0.5 m, V v = 38 m 3 ), DIII-D (conventional tokamak, copper coils, C wall, R/a = 1.67 m/0.65 m, V v = 35 m 3 ), and KSTAR (conventional tokamak, superconducting coils, C wall, R/a = 1.8 m/0.5 m, V v = 55 m 3 ). Despite the different hardware features of the devices, the required operating spaces of the loop voltage induction and prefill gas pressure for inductive plasma initiation in each device were successfully reproduced by the predictive simulations with DYON using only the individual hardware design and the control room input data for each discharge. This successful validation across multiple machines demonstrates that the full electromagnetic DYON modelling can capture the essential physics of inductive plasma initiation. The simulation settings commonly employed for all modelling and the modifications necessary to account for the discrepancies between individual devices are reported. Predictions for ITER based on the multi-machine validation indicate that a wide range of prefill gas pressures exists for the Townsend breakdown and the plasma burn-through (0.01–1.5 mPa).

DYON↗

Wildfire smoke impacts lake ecosystems

Abstract Wildfire activity is increasing globally. The resulting smoke plumes can travel hundreds to thousands of kilometers, reflecting or scattering sunlight and depositing particles within ecosystems. Several key physical, chemical, and biological processes in lakes are controlled by factors affected by smoke. The spatial and temporal scales of lake exposure to smoke are extensive and under‐recognized. We introduce the concept of the lake smoke‐day, or the number of days any given lake is exposed to smoke in any given fire season, and quantify the total lake smoke‐day exposure in North America from 2019 to 2021. Because smoke can be transported at continental to intercontinental scales, even regions that may not typically experience direct burning of landscapes by wildfire are at risk of smoke exposure. We found that 99.3% of North America was covered by smoke, affecting a total of 1,333,687 lakes ≥10 ha. An incredible 98.9% of lakes experienced at least 10 smoke‐days a year, with 89.6% of lakes receiving over 30 lake smoke‐days, and lakes in some regions experiencing up to 4 months of cumulative smoke‐days. Herein we review the mechanisms through which smoke and ash can affect lakes by altering the amount and spectral composition of incoming solar radiation and depositing carbon, nutrients, or toxic compounds that could alter chemical conditions and impact biota. We develop a conceptual framework that synthesizes known and theoretical impacts of smoke on lakes to guide future research. Finally, we identify emerging research priorities that can help us better understand how lakes will be affected by smoke as wildfire activity increases due to climate change and other anthropogenic activities.

54 ENVIRONMENTAL SCIENCES↗