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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

AmeriFlux FLUXNET-1F US-ARb ARM Southern Great Plains burn site- Lamont

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-ARb ARM Southern Great Plains burn site- Lamont. This is the FLUXNET version of the carbon flux data for the site US-ARb ARM Southern Great Plains burn site- Lamont produced by applying the standard ONEFlux (1F) software. Site Description - The ARM SGP Burn site is located in the native tallgrass prairies of the USDA Grazinglands Research Laboratory near El Reno, OK. One of two adjacent 35 ha plots, the US-ARb plot was burned on 2005/03/08. The second plot, US-ARc, was left unburned as the control for experimental purposes. Aside from 2005, the region evaded burning activities for at least 15 years. Current disturbances consist of only light grazing activities.

Torn, Margaret↗
DOE OSTI2024

Validation of prediction capability of operating space for plasma initiation in MAST-U

DYON is a plasma initiation modelling code that solves the differential equation system of the full circuit equations (plasma current, active coil currents and eddy currents in full passive structures) and 0D global energy and particle balance equations (Kim 2022 Nucl. Fusion 62 126012). In order to test the capability of the full electromagnetic plasma initiation model to predict individual discharges in experiments and thus the operating space in the device, a dedicated experimental database was built in MAST-U by scanning the prefilled gas pressure p 0 and the induced loop voltage V loop . In the experimental operating space of p 0 and V loop the lower and the upper limits of p 0 are determined by the plasma breakdown failure and the plasma burn-through failure, respectively. The lower limit of V loop is determined by the plasma burn-through failure. By directly reading the control room data used in each discharge (i.e. currents in the solenoid, poloidal field coils, and toroidal field coils, p 0 , and gas puffing rate), the full electromagnetic DYON consistently predicted the failed breakdown, failed burn-through, and successful plasma initiation discharges in the experimental database, demonstrating its capability to predict the operating space for inductive plasma initiation. The Paschen curve calculated with the effective connection length in MAST-U indicates a much higher p 0 required for plasma breakdown than the experimental data, indicating that individual field line evaluation is necessary to calculate the quantitative requirements for Townsend breakdown. The demonstration in this paper shows that the full electromagnetic DYON could be a useful simulation tool to assess the feasibility of inductive plasma initiation and to optimise operating scenarios in future devices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Iraq/Afghanistan war lung injury reflects burn pits exposure

This descriptive case series retrospectively reviewed medical records from thirty-one previously healthy, war-fighting veterans who self-reported exposure to airborne hazards while serving in Iraq and Afghanistan between 2003 and the present. They all noted new-onset dyspnea, which began during deployment or as a military contractor. Twenty-one subjects underwent non-invasive pulmonary diagnostic testing, including maximum expiratory pressure (MEP) and impulse oscillometry (IOS). In addition, five soldiers received a lung biopsy; tissue results were compared to a previously published sample from a soldier in our Iraq Afghanistan War Lung Injury database and others in our database with similar exposures, including burn pits. We also reviewed civilian control samples (5) from the Stony Brook University database. Military personnel were referred to our International Center of Excellence in Deployment Health and Medical Geosciences, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell under the auspices of Northwell IRB: 17-0140-FIMR Feinstein Institution for Medical Research “Clinicopathologic characteristics of Iraq Afghanistan War Lung Injury.” We retrospectively examined medical records, including exposure data, radiologic imaging, and non-invasive pulmonary function testing (MGC Diagnostic Platinum Elite Plethysmograph) using the American Thoracic Society (ATS) standard interpretation based on Morgan et al., and for a limited cohort, biopsy data. Lung tissue, when available, was examined for carbonaceous particles, polycyclic aromatic hydrocarbons (Raman spectroscopy), metals, titanium connected to iron (Brookhaven National Laboratory, National Synchrotron Light Source II, Beamline 5-ID), oxidized metals, combustion temperature, inflammatory cell accumulation and fibrosis, neutrophil extracellular traps, Sirius red, Prussian Blue, as well as polarizable crystals/particulate matter/dust. Among twenty-one previously healthy, deployable soldiers with non-invasive pulmonary diagnostic tests, post-deployment, all had severely decreased MEP values, averaging 42% predicted. These same patients concurrently demonstrated abnormal airways reactance (X5Hz) and peripheral/distal airways resistance (D5–D20%) via IOS, averaging – 1369% and 23% predicted, respectively. These tests support the concept of airways hyperresponsiveness and distal airways narrowing, respectively. Among the five soldiers biopsied, all had constrictive bronchiolitis. We detected the presence of polycyclic aromatic hydrocarbons (PAH)—which are products of incomplete combustion—in the lung tissue of all five warfighters. All also had detectable titanium and iron in the lungs. Metals were all oxidized, supporting the concept of inhaling burned metals. Combustion temperature was consistent with that of burned petrol rather than higher temperatures noted with cigarettes. All were nonsmokers. Neutrophil extracellular traps were reported in two biopsies. Compared to our prior biopsies in our Middle East deployment database, these histopathologic results are similar, since all database biopsies have constrictive bronchiolitis, one has lung fibrosis with titanium bound to iron in fixed mathematical ratios of 1:7 and demonstrated polarizable crystals. These results, particularly constrictive bronchiolitis and polarizable crystals, support the prior data of King et al. (N. Engl. J. Med. 365:222–230, 2011) Soldiers in this cohort deployed to Iraq and Afghanistan since 2003, with exposure to airborne hazards, including sandstorms, burn pits, and improvised explosive devices, are at high risk for developing chronic clinical respiratory problems, including: (1) reduction in respiratory muscle strength; (2) airways hyperresponsiveness; and (3) distal airway narrowing, which may be associated with histopathologic evidence of lung damage, reflecting inhalation of burned particles from burn pits along with particulate matter/dust. Non-invasive pulmonary diagnostic tests are a predictor of burn pit-induced lung injury

36 MATERIALS SCIENCE↗
DOE OSTI2026

Real-time avoidance of the L-mode and H-mode density limit via machine-learned stability metrics

Reliable operation of burning plasma tokamaks will require robust control strategies to avoid macroscopic instability limits such as the L-mode and H-mode density limits (LDL, HDL). In this work, we explore closed-loop avoidance of these phenomena at DIII-D using machine-learned risk metrics. Feedback control is implemented via the ‘DL Supervisor’ scheme, which regulates the chosen risk metric by reducing the density target or increasing NBI heating in real-time. Using the LDL 25 risk metric, the LDL is reproducibly suppressed. We also introduce an HDL risk metric in this study, HDL 25 , which reduces the False Positive Rate by 2x compared to the Greenwald fraction. Applying this scaling to a plasma current ramp-down, we successfully avoid an HDL-driven H/L back-transition. These experiments constitute the first demonstration of real-time DL avoidance using machine-learned risk metrics. These instability metrics outline a path to safer high-density operation, more reliable ramp-down scenarios, and improved off-normal control for next-step devices such as ITER and SPARC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

AmeriFlux FLUXNET-1F US-KS1 Kennedy Space Center (slash pine)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-KS1 Kennedy Space Center (slash pine). This is the FLUXNET version of the carbon flux data for the site US-KS1 Kennedy Space Center (slash pine) produced by applying the standard ONEFlux (1F) software. Site Description - The Kennedy Space Center Slash Pine Flatwoods site is located in the Merritt Island National Wildlife Refuge at the Kennedy Space Center (KSC) on the east coast of central Florida. Occupying 310 ha of local forest, the slash pine flatwoods ecosystem is managed as an uneven-aged stand with a sparsely populated overstory and a dense oak-dominated understory. Disturbances tend to occur on a 7 to 10 year cycle, mostly related to fire or hurricane activity. Prescribed fires have been conducted since 1969 to control understory fuel. The most recent burn was conducted in February of 1995. Following the burn, the stand was allowed to naturally regenerate into a open canopy of slash pines, less than 15% of canopy coverage ( on the order of 15-30 trees per ha), with a understory mostly composed of saw palmetto and scrub oak. There was a seasonally wet swale to the southeast that was on the margin of the flux tower footprint. A severe drought gripped most of Florida beginning in 1998 until the later half of 2001 resulting in four years of relatively low annual precipitation totals. Exceptionally high annual rainfall amounts in 2004 were the result of a pair of hurricanes that hit the area in August and September of 2004. Wind directions for the site are as follows: W and NW in the winter, afternoon E sea breeze in the summer.

Drake, Bert↗
DOE OSTI2024

A Physical Metric for Inertial Confinement Fusion Capsules

The performance of fusion capsules on the National Ignition Facility (NIF) is strongly affected by the physical properties of the hot deuterium–tritium (DT) fuel, such as the mass, areal density, and pressure of the hot spot at the stagnation time. All of these critical quantities depend on one measured quantity, which is the ratio of the specific peak implosion energy to the specific internal energy of the hot spot. This unique physical quantity not only can measure the incremental progress of the inertial confinement fusion capsules towards ignition but also measures the conversion of the peak implosion kinetic energy of the pusher shell into the internal energy of the hot fuel in a capsule. Analysis of existing NIF shots to date are performed. The ratio metric is compared quantitatively with the ignition criterion. Results provide new perspectives on the NIF experiments by which the performance of the burning plasma can be determined and controlled through the fine tune of the implosion parameters, which improves future designs and predictions of the ignition capsules.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Smokeless Chimney using Smoke Opacity as a Combustion Control Parameter (CRADA Final Report)

If operated poorly, wood burning heaters can produce large amounts of particulate matter (PM). Although several instruments are available to monitor PM, most require dilution air and are unable to sample directly from a flue due to the high PM concentrations and temperatures. Opacity sensors can measure color, opacity and smoke density from wood heater stacks. They operate by transmitting a light beam through the emission source and measuring the amount of light intensity lost (opacity) and light not reflected (color). Although opacity sensors are used in several areas, none have been thoroughly evaluated or optimized for measuring smoke from wood heaters.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Assessment of a reconfiguration of the InterSpread Plus US national FMD model as a potential tool to analyze a foot-and-mouth disease outbreak on a single large cattle feedlot in the United States

An incursion of foot-and-mouth disease (FMD) into the United States remains a concern of high importance and would have devastating socioeconomic impacts to the livestock and associated industries. This highly transmissible and infectious disease poses continual risk for introduction into the United States (US), due to the legal and illegal global movement of people, animals, and animal products. While stamping out has been shown to effectively control FMD, depopulation of large cattle feedlots (>50,000 head) presents a number of challenges for responders due to the resources required to depopulate and dispose of large numbers of animals in a timely and effective manner. However, evaluating alternative strategies for FMD control on large feedlots requires a detailed within-farm modeling approach, which can account for the unique structure of these operations. To address this, we developed a single feedlot, within-farm spread model using a novel configuration within the InterSpread Plus (ISP) framework. As proof of concept we designed six scenarios: (i) depopulation - the complete depopulation of the feedlot, (ii) burn-through – a managed “burn-through” where the virus is allowed to spread through the feedlot and only movement restriction and biosecurity are implemented, (iii) firebreak-NV – targeted depopulation of infected pens and adjacent pens without vaccination; (iv) firebreak - targeted depopulation of infected pens and adjacent pens with vaccination of remaining pens; (v) harvest-NV - selective harvest of pens where a 100% movement restriction is applied for 28-30 days, then pens are set for selection to be sent to slaughter, while allowing a controlled “burn-through” without vaccination; and (vi) harvest - selective harvest of pens with vaccination. Overall, the burn-through scenario (ii) had the shortest epidemic duration (31d (30, 33)) median (25th, 75th percentiles), while the firebreak scenario (iv) had the longest (47d (38,55)). Additionally, we found that scenarios implementing depopulation delayed the peak day of infection and reduced the total number of pens infected compared to non-depopulation scenarios.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Numerical Treatment of Shock-induced Nuclear Burning in Double Detonation Type Ia Supernovae

We present a benchmark problem to assess the treatment of shock-induced nuclear burning in the context of double detonation Type Ia supernovae. In a stratified white dwarf model, we implement a shock-detection criterion that suppresses burning in zones characterized by compression and significant pressure gradients, controlled by a tunable parameter, f shock . One-dimensional simulations, using the open-source Castro suite, were conducted across three treatments—burning fully enabled, and burning suppressed with f shock = 2/3 and f shock = 1—across three spatial resolutions (5.0, 2.5, and 0.3125 km). At the finest resolution, the burning-enabled and f shock = 1 models converge, while the f shock = 2/3 front continues to show slight offset behavior. Since most simulations are carried out at much lower resolutions, our tests support the idea that burning in shocks should always be disabled in practice. We also observe that the behavior of lower-resolution simulations remains extremely sensitive to the choice of f shock .

GPU computing↗
DOE OSTI2022

Burnable absorbers in nuclear reactors – A review

Burnable absorbers can benefit nuclear reactors of virtually any design by providing reactivity control for extended fuel cycles, tritium production, burning of long-lived radionuclides, and reactor safety. When selecting the ideal burnable absorber type and its design, one must consider the resulting impact on the reactor’s fuel cycle design and cost, reactivity, thermal hydraulics, manufacturing, and radiation response. These selection criteria, as well as neutronic and thermophysical material property requirements, may be vastly different depending on whether the burnable absorber is intended for use in a commercial water-cooled reactor, a research reactor, or a next-generation advanced reactor system. A recent integration, synthesis, description of past and present technologies, and identification of existing gaps and areas of future research is lacking on these important topics. Here, this paper includes a fundamental description of the use of burnable absorbers and their impacts on reactivity, absorber depletion, self-shielding, basic thermophysical properties, and the use of burnable absorbers in next-generation nuclear applications..

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

3D radiated power analysis of JET SPI discharges using the Emis3D forward modeling tool

Abstract Precise values for radiated energy in tokamak disruption experiments are needed to validate disruption mitigation techniques for burning plasma tokamaks like ITER and SPARC. Control room analysis of radiated power ( P rad ) on JET assumes axisymmetry, since fitting 3D radiation structures with limited bolometry coverage is an under-determined problem. In mitigated disruptions, radiation is toroidally asymmetric and 3D, due to fast-growing 3D MHD modes and localized impurity sources. To address this problem, Emis3D adopts a physics motivated forward modeling (‘guess and check’) approach, comparing experimental bolometry data to synthetic data from user-defined radiation structures. Synthetic structures are observed with the Cherab modeling framework and a best fit chosen using a reduced χ 2 statistic. 2D tomographic inversion models are tested, as well as helical flux tubes and 3D MHD simulated structures from JOREK. Two nominally identical pure neon shattered pellet injection (SPI) mitigated discharges in JET are analyzed. 2D tomographic inversions with added toroidal freedom are the best fits in the thermal quench (TQ) and current quench (CQ). In the pre-TQ, 2D reconstructions are statistically the best fits, but are likely over-optimized and do not capture the 3D radiation structure seen in fast camera images. The next-best pre-TQ fits are helical structures that extend towards the high-field side, consistent with an impurity flow under the magnetic nozzle effect also observed in JOREK simulations. Whole-disruption radiated fractions of 0.98 + 0.03 / − 0.29 and 1.01 + 0.02 / − 0.17 are found, suggesting that the stored energy may have been fully mitigated by each SPI, although mitigation efficiencies well below ITER and SPARC requirements for high energy pulses are still within the large uncertainties. Emis3D is also used to validate JOREK SPI simulations, and confirms improvements in matching experiment from changes to impurity modeling. Time-dependent toroidal peaking factors are calculated and discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Soil Carbon and Nitrogen Elemental Analysis and Middle Infrared Spectroscopy from the Kougarok Fire Complex, Seward Peninsula, Alaska, 2022

In September and October of 2022, soil samples were collected at the Kougarok Fire Complex near mile marker 86 of the Nome-Taylor Highway on the Seward Peninsula of Alaska. This study site was chosen due to its unique fire history, as the Kougarok Fire Complex has experienced multiple wildfires since 1971. As the Arctic warms, the risk of Arctic tundra fires continues to increase due to warmer summer temperatures and higher frequency of lightning. Burned soil carbon or pyrogenic carbon (PyC) is an important component of C cycling after wildfire, and one that is often overlooked in tundra systems where wildfires are historically rare. To better understand PyC signatures and quantify PyC presence in post-regeneration permafrost regions, soils were sampled from soil pits within the 1971, 2002, and 2019 burn sites, as well as two unburned control sites. At each site, three soil pits were dug to the permafrost table. Soil samples were collected with a trowel from the face of each pit at 10 cm increments down to the permafrost table. Thaw depth, maximum vegetation height, vegetation species composition, and O horizon depth were also collected at each soil pit. An HS2 Hydrosense II Handheld Soil Moisture Sensor was used to collect volumetric soil moisture content at each 10 cm sampling increment. This dataset includes one *.csv of middle infrared spectroscopy measurements of soil samples, one *.csv of field observations, one *.csv of carbon and nitrogen analysis of soil samples, and one *.kml of sampling locations.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Building a machine learning surrogate model for wildfire activities within a global Earth system model

Abstract. Wildfire is an important ecosystem process, influencing land biogeophysical and biogeochemical dynamics and atmospheric composition. Fire-driven loss of vegetation cover, for example, directly modifies the surface energy budget as a consequence of changing albedo, surface roughness, and partitioning of sensible and latent heat fluxes. Carbon dioxide and methane emitted by fires contribute to a positive atmospheric forcing, whereas emissions of carbonaceous aerosols may contribute to surface cooling. Process-based modeling of wildfires in Earth system land models is challenging due to limited understanding of human, climate, and ecosystem controls on fire counts, fire size, and burned area. Integration of mechanistic wildfire models within Earth system models requires careful parameter calibration, which is computationally expensive and subject to equifinality. To explore alternative approaches, we present a deep neural network (DNN) scheme that surrogates the process-based wildfire model with the Energy Exascale Earth System Model (E3SM) interface. The DNN wildfire model accurately simulates observed burned area with over 90 % higher accuracy with a large reduction in parameterization time compared with the current process-based wildfire model. The surrogate wildfire model successfully captured the observed monthly regional burned area during validation period 2011 to 2015 (coefficient of determination, R2=0.93). Since the DNN wildfire model has the same input and output requirements as the E3SM process-based wildfire model, our results demonstrate the applicability of machine learning for high accuracy and efficient large-scale land model development and predictions.

58 GEOSCIENCES↗
DOE OSTI2025

THE DESIGN OF RADIAL HONEYCOMB LATTICES FOR IMPACT ENERGY ABSORPTION IN RADIOACTIVE MATERIALS PACKAGES

In this research we present a variation on the corrugation technique of honeycomb lattices, for cylindrical honeycombs, making them much easier to design for impact energy absorption in radioactive materials packages. This variation, termed radial honeycomb lattices, eliminates the residual strain and saddle effect. The use of honeycomb lattices provides advantages over the typically used foams. While foams are effective at absorbing impact energy, they can burn, their material properties are difficult to control, they can degrade over time, and procurement of raw materials can be dependent on timing of manufacturer batch runs. While the weaknesses of foam are strengths for honeycomb lattices, lattices have a different set of problems. Typically, when cylindrical honeycomb lattices are manufactured, they are manufactured flat, wrapped around a mandrel of the desired radius, and then brazed. This approach introduces residual strains, resulting in the saddle effect, which limits both the radial thickness and cylinder length. The radial honeycomb lattice approach presented here makes the design of thicker and longer cylinder honeycombs possible. To address these issues, we propose a honeycomb lattice which changes in cross-section from the inner to the outer radius of the cylinder. This causes the lattice to automatically wrap into a cylinder as it exits the corrugating gears. The theoretically bounding case, of a square cross-section at the inner radius, transitioning through a hexagon, to a diamond cross-section at the outer radius, results in a maximum thickness of approximately 41% of the inner radius. Full mathematical derivations, implemented in computer code, allow for the design of an entire radial honeycomb lattice, including the corrugating gears. To accomplish this only the radial thickness, inner cross-section shape, cell size, and nominal gear radius need to be specified, making the design of these lattices very efficient. Radial honeycomb lattice prototypes have demonstrated that the honeycomb does indeed wrap into a cylinder as intended, without the saddle effect, and can therefore be used to create thick-walled cylinders of any length. These design improvements make cylindrical honeycomb lattices much more accessible as a design element for radioactive materials packages

Johnson, William R. [Savannah River National Labor↗
DOE OSTI2023

Comparison of machine learning systems trained to detect Alfvén eigenmodes using the CO 2 interferometer on DIII-D

Abstract A Machine-Learning (ML) based detection scheme that automatically detects Alfvén Eigenmodes (AE) in a labelled DIII-D database is presented here. Controlling AEs is important for the success of planned burning plasma devices such as ITER, since resonant fast ions can drive AEs unstable and degrade the performance of the plasma or damage the first walls of the machine vessel. Artificial Intelligence could be useful for real-time detection and control of AEs in steady-state plasma scenarios by implementing ML-based models into control algorithms that drive actuators for mitigation of AE impacts. Thus, the objective is to compare differences in performance between using two different recurrent neural network systems (Reservoir Computing Network and Long Short Term Memory Network) and two different representations of the C O 2 phase data (simple and crosspower spectrograms). All C O 2 interferometer chords are used to train both models, but only one is processed during each training step. The results from the model and data comparison show higher performance for the RCN model (True Positive Rate = 90% and False Positive Rate = 14%), and that using simple magnitude spectrograms is sufficient to detect AEs. Also, the vertical C O 2 interferometer chord passing near the center is better for ML-based detection of AEs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Physics and technology considerations for the deuterium–tritium fuel cycle and conditions for tritium fuel self sufficiency

The tritium aspects of the DT fuel cycle embody some of the most challenging feasibility and attractiveness issues in the development of fusion systems. The review and analyses in this paper provide important information to understand and quantify these challenges and to define the phase space of plasma physics and fusion technology parameters and features that must guide a serious R&D in the world fusion program. We focus in particular on components, issues and R&D necessary to satisfy three 'principal requirements': (1) achieving tritium self-sufficiency within the fusion system, (2) providing a tritium inventory for the initial start-up of a fusion facility, and (3) managing the safety and biological hazards of tritium. A primary conclusion is that the physics and technology state-of-the-art will not enable DEMO and future power plants to satisfy these principal requirements. We quantify goals and define specific areas and ideas for physics and technology R&D to meet these requirements. A powerful fuel cycle dynamics model was developed to calculate time-dependent tritium inventories and flow rates in all parts and components of the fuel cycle for different ranges of parameters and physics and technology conditions. Dynamics modeling analyses show that the key parameters affecting tritium inventories, tritium start-up inventory, and tritium self-sufficiency are the tritium burn fraction in the plasma (f b ), fueling efficiency (η f ), processing time of plasma exhaust in the inner fuel cycle (t p ), reactor availability factor (AF), reserve time (tr) which determines the reserve tritium inventory needed in the storage system in order to keep the plant operational for time t r in case of any malfunction of any part of the tritium processing system, and the doubling time (t d ). Results show that η f f b > 2% and processing time of 1–4 h are required to achieve tritium self-sufficiency with reasonable confidence. For η f f b = 2% and processing time of 4 h, the tritium start-up inventory required for a 3 GW fusion reactor is ~11 kg, while it is <5 kg if η f f b = 5% and the processing time is 1 h. To achieve these stringent requirements, a serious R&D program in physics and technology is necessary. The EU-DEMO direct internal recycling concept that carries fuel directly from the plasma exhaust gas to the fueling systems without going through the isotope separation system reduces the overall processing time and tritium inventories and has positive effects on the required tritium breeding ratio (TBR R ). A significant finding is the strong dependence of tritium self-sufficiency on the reactor availability factor. Simulations show that tritium self-sufficiency is: impossible if AF < 10% for any η f f b , possible if AF > 30% and 1% ≤ η f f b ≤ 2%, and achievable with reasonable confidence if AF > 50% and η f f b > 2%. These results are of particular concern in light of the low availability factor predicted for the near-term plasma-based experimental facilities (e.g. FNSF, VNS, CTF), and can have repercussions on tritium economy in DEMO reactors as well, unless significant advancements in RAMI are made. There is a linear dependency between the tritium start-up inventory and the fusion power. The required tritium start-up inventory for a fusion facility of 100 MW fusion power is as small as 1 kg. Since fusion power plants will have large powers for better economics, it is important to maintain a 'reserve' tritium inventory in the tritium storage system to continue to fuel the plasma and avoid plant shutdown in case of malfunctions of some parts of the tritium processing lines. But our results show that a reserve time as short as 24 h leads to unacceptable reserve and start-up inventory requirements. Therefore, high reliability and fast maintainability of all components in the fuel cycle are necessary in order to avoid the need for storing reserve tritium inventory sufficient for continued fusion facility operation for more than a few hours. The physics aspects of plasma fueling, tritium burn fraction, and particle and power exhaust are highly interrelated and complex, and predictions for DEMO and power reactors are highly uncertain because of lack of experiments with burning plasma. Fueling by pellet injection on the high field side of tokamak has evolved to be the preferred method to fuel a burning plasma. Extrapolation from the DIII-D penetration scaling shows fueling efficiency expected in DEMO to be <25%, but such extrapolations are highly uncertain. The fueling efficiency of gas in a reactor relevant regime is expected to be extremely poor and not very useful for getting tritium into the core plasma efficiently. Gas fueling will nonetheless be useful for feedback control of the divertor operating parameters. Extensive modeling has been carried out to predict burn fraction, fueling requirements, and fueling efficiency for ITER, DEMO, and beyond. The fueling rate required to operate Q = 10 ITER plasmas in order to provide the required core fueling, helium exhaust and radiative divertor plasma conditions for acceptable divertor power loads was calculated. If this fueling is performed with a 50–50 DT mix, the tritium burn fraction in ITER would be ~0.36%, which is too low to satisfy the self-sufficiency conditions derived from the dynamics modeling for fusion reactors. Extrapolation to DEMO using this approach would also yield similarly low burn fraction. Extensive analysis presented shows that specific features of edge neutral dynamics in ITER and fusion reactors, which are different from present experiments, open possibilities for optimization of tritium fueling and thus to improve the burn fraction. Using only tritium in pellet fueling of the plasma core, and only deuterium for edge density, divertor power load and ELM control results in significant increase of the burn fraction to 1.8–3.6%. These estimates are performed with physics models whose results cannot be fully validated for ITER and DEMO plasma conditions since these cannot be achieved in present tokamak experiments. Thus, several uncertainties remain regarding particle transport and scenario requirements in ITER and DEMO. The safety standard requirements for protection of the public and release guidelines for tritium have been reviewed. General safety approaches including minimizing tritium inventories, reducing tritium permeation through materials, and decontaminating material for waste disposal have been suggested.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Huslia Tribal Council Biomass Project: A Project to Increase Sustainability and Reduce Energy Costs in Huslia, AK

The Huslia Tribal Council (HTC) and the Tanana Chiefs Conference (TCC), partnering with the City of Huslia, the Yukon-Koyukuk School District, and Alaska Native Tribal Health Consortium, applied to the U.S. Department of Energy Office of Indian Energy for funding of a community biomass boiler system. The biomass system contributes to heating three community buildings in Huslia, Alaska with locally harvested fuels: the clinic, the water treatment plant/washeteria, and the school. The remaining heating needs are supported by in-building oil-fired boilers, burning imported heating fuel. Some issues, such as control set points on the oil boilers, need to be resolved before the biomass heating system is used at full capacity. The project objectives of the community biomass boiler system were cost reduction, carbon reduction, community resilience, and economic development. Once fully operational, the cost reduction from decreased fuel oil usage due to support from the biomass boiler system is expected to more than offset the cost of purchasing locally harvested biofuel, resulting in overall savings to the community. Locally sourced wood is considered carbon-neutral, so the biomass boiler system decreases the carbon footprint of heating the community buildings. The project increases resilience by decreasing dependence on heating oil brought in from elsewhere. Lastly, it produces economic development by employing locals to gather the wood burned in the biomass boiler. This project satisfies all of the objectives that HTC set out to achieve.

09 BIOMASS FUELS↗
DOE OSTI2021

The response of the Amazon ecosystem to the photosynthetically active radiation fields: integrating impacts of biomass burning aerosol and clouds in the NASA GEOS Earth system model

The Amazon experiences fires every year, and the resulting biomass burning aerosols, together with cloud particles, influence the penetration of sunlight through the atmosphere, increasing the ratio of diffuse to direct photosynthetically active radiation (PAR) reaching the vegetation canopy and thereby potentially increasing ecosystem productivity. In this study, we use the NASA Goddard Earth Observing System (GEOS) model with coupled aerosol, cloud, radiation, and ecosystem modules to investigate the impact of Amazon biomass burning aerosols on ecosystem productivity, as well as the role of the Amazon's clouds in tempering this impact. The study focuses on a 7-year period (2010–2016) during which the Amazon experienced a variety of dynamic environments (e.g., La Niña, normal years, and El Niño). The direct radiative impact of biomass burning aerosols on ecosystem productivity – called here the aerosol diffuse radiation fertilization effect – is found to increase Amazonian gross primary production (GPP) by 2.6 % via a 3.8 % increase in diffuse PAR (DFPAR) despite a 5.4 % decrease in direct PAR (DRPAR) on multiyear average during burning seasons. On a monthly basis, this increase in GPP can be as large as 9.9 % (occurring in August 2010). Consequently, the net primary production (NPP) in the Amazon is increased by 1.5 %, or ~92 Tg C yr -1 – equivalent to ~37 % of the average carbon lost due to Amazon fires over the 7 years considered. Clouds, however, strongly regulate the effectiveness of the aerosol diffuse radiation fertilization effect. The efficiency of this fertilization effect is the highest in cloud-free conditions and linearly decreases with increasing cloud amount until the cloud fraction reaches ~0.8, at which point the aerosol-influenced light changes from being a stimulator to an inhibitor of plant growth. Nevertheless, interannual changes in the overall strength of the aerosol diffuse radiation fertilization effect are primarily controlled by the large interannual changes in biomass burning aerosols rather than by changes in cloudiness during the studied period.

54 ENVIRONMENTAL SCIENCES↗