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At least 271 records · Page 15

A review of criticality dosimetry at the Y-12 National Security Complex and practical importance of dose accuracy in emergency response

A nuclear criticality results in the emission of both neutron and gamma radiation and can produce doses to personnel near the event that exceed 0.1 Gy (10 rad). The primary purpose of nuclear accident dosimetry is to rapidly identify affected personnel in need of prompt medical treatment and to reassure personnel who have been only minimally exposed. While accurate dosimetry is desired, it must be recognized that dose determinations made from whole-body dosimeters or simple triage methods are very rough estimates and contain significant uncertainties. Even when accounting for factors like varying neutron energy spectra, mean photon energies, body orientation within the radiation field, and transient effects on dosimeter response, etc., the end value is a dosimetric quantity defined for very specific radiological conditions and determined within a simple phantom usually at a single depth. Of more importance is the biological response to the radiation, which will vary by person and can be affected by the individual’s radiation sensitivity, age, gender, mass, and underlying health conditions. The overall biological, person-specific response to a given dose cannot be precisely determined except by patient symptom observation and individual biological dosimetry (e.g. chromosome analysis, lymphocyte ratios, etc.). This work describes and discusses the criticality accident dosimetry program at the Y-12 National Security Complex, a United States Department of Energy National Nuclear Security Administration facility. In conclusion, the primary goals of the Y-12 accident dosimetry program are, among others, the rapid identification of significantly exposed persons, prompt routing of exposed workers for medical evaluation and treatment, and the ultimate processing of dosimeters to assign doses to personnel.

61 RADIATION PROTECTION AND DOSIMETRY↗

The relation between quasars’ optical spectra and variability

Abstract Brightness variation is an essential feature of quasars, but its mechanism and relationship to other physical quantities are not understood well. We aimed to find the relationship between the optical variability and spectral features to reveal the regularity behind the random variation. It is known that a quasar’s Fe ii/Hβ flux ratio and equivalent width of [O iii]5007 are negatively correlated; this is called Eigenvector 1. In this work, we visualized the relationship between the position on this Eigenvector 1 (EV1) plane and how the brightness of the quasars had changed after ∼10 yr. We conducted three analyses, using a different quasar sample in each. The first analysis showed the relation between the quasars’ distributions on the EV1 plane and how much they had changed brightness, using 13438 Sloan Digital Sky Survey quasars. This result shows how brightness changes later are clearly related to the position on the EV1 plane. In the second analysis, we plotted the sources reported as “changing-look quasars” (or “changing-state quasars”) on the EV1 plane. This result shows that the position on the EV1 plane corresponds to the activity level of each source, and the bright or dim states of them are distributed on the opposite sides divided by the typical quasar distribution. In the third analysis, we examined the transition vectors on the EV1 plane using sources with multiple-epoch spectra. This result shows that the brightening and dimming sources move on a similar path and they reach a position corresponding to the opposite activity level. We also found this trend is opposite to the empirical rule that $R_{\rm {Fe\, \small {II}}}$ positively correlated with the Eddington ratio, which has been proposed based on the trends of a large number of quasars. From all these analyses, it is indicated that quasars tend to oscillate between both sides of the distribution ridge on the EV1 plane; each of them corresponds to a dim state and a bright state. This trend in optical variation suggests that significant brightness changes, such as changing-look quasars, are expected to repeat.

Astronomy & Astrophysics↗

Personalized and uncertainty-aware coronary hemodynamics simulations: From Bayesian estimation to improved multi-fidelity uncertainty quantification

Non-invasive simulations of coronary hemodynamics have improved clinical risk stratification and treatment outcomes for coronary artery disease, compared to relying on anatomical imaging alone. However, simulations typically use empirical approaches to distribute total coronary flow amongst the arteries in the coronary tree, which ignores patient variability, the presence of disease, and other clinical factors. Further, uncertainty in the clinical data often remains unaccounted for in the modeling pipeline. We present an end-to-end uncertainty-aware pipeline to (1) personalize coronary flow simulations by incorporating vessel-specific coronary flows as well as cardiac function; and (2) predict clinical and biomechanical quantities of interest with improved precision, while accounting for uncertainty in the clinical data. We assimilate patient-specific measurements of myocardial blood flow from clinical CT myocardial perfusion imaging to estimate branch-specific coronary artery flows. Simulated noise in the clinical data is used to estimate the joint posterior distributions of the model parameters using adaptive Markov Chain Monte Carlo sampling. Additionally, the posterior predictive distribution for the relevant quantities of interest is determined using a new approach combining multi-fidelity Monte Carlo estimation with non-linear, data-driven dimensionality reduction. This leads to improved correlations between high- and low-fidelity model outputs. Our framework accurately recapitulates clinically measured cardiac function as well as branch-specific coronary flows under measurement noise uncertainty. We observe substantial reductions in confidence intervals for estimated quantities of interest compared to single-fidelity Monte Carlo estimation and state-of-the-art multi-fidelity Monte Carlo methods. This holds especially true for quantities of interest that showed limited correlation between the low- and high-fidelity model predictions. In addition, the proposed multi-fidelity Monte Carlo estimators are significantly cheaper to compute than traditional estimators, under a specified confidence level or variance. The proposed pipeline for personalized and uncertainty-aware predictions of coronary hemodynamics is based on routine clinical measurements and recently developed techniques for CT myocardial perfusion imaging. The proposed pipeline offers significant improvements in precision and reduction in computational cost.

Bayesian parameter estimation↗

Measurement and analysis of clothes dryer air leakage

Each year clothes dryer appliances are sold globally in the tens of millions. Both vented and ventless types are common and are heated by combustion, electric resistance, or electric heat pumps. In the dyer air path, segments can be defined between components such as the drum, blower, filter, screens or grills, and heat exchangers (where applicable). In this work, a technique was developed to experimentally measure air leakage into and from the segments of a clothes dryer. Detailed leakage measurements were taken on two vented and one ventless residential clothes dryer. The measurements were quantified as a leakage flow coefficient for each segment. For two dryers (one vented and one ventless), these flow coefficients were combined with in situ operating pressure measurements to determine leakage flow rates for each segment. For these two units under normal operation with air pressures within 0.5 kPa (50 mm water column) of ambient pressure, volumetric system air leakage was found to be about 20–60% of the blower airflow. Furthermore, a quasi–steady state psychrometric analysis was conducted on vented dryers with negatively pressurized drums. The analysis revealed that leakage quantity, location, and direction are essential to achieving an acceptable energy balance and accurate modeling results for a vented heat pump clothes dryer but are of limited significance for vented electric resistance clothes dryers.

42 ENGINEERING↗

IER-519 CED-2: Final Design for Thermal/Epithermal eXperiments (TEX) with Absorbers to Provide Validation Benchmarks for Hanford Tank Farms

The Hanford tank farms contain 56 million gallons of waste across 177 tanks. The primary criticality safety concern for the waste is the plutonium inventory in waste solids – approximately 670 kg in total. Criticality safety analysis credits the absorption and dilution properties of the large quantities of other elements (aluminum, chromium, iron, manganese, nickel, silicon, sodium, and zirconium) present in the waste. Of these, iron and manganese are by far the most significant neutron absorbers, particularly for the waste compositions of highest criticality safety concern. The criticality safety analyses at the Hanford Waste Treatment and Vitrification Plant (WTP) and the Savannah River tank farms also credit iron and manganese as the primary neutron absorbers to demonstrate subcriticality.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Land use-land cover gradient demonstrates the importance of perennial grasslands with intact soils for building soil carbon in the fertile Mollisols of the North Central US

The impact of land use change and agricultural management on the cycling of soil organic carbon (SOC) is not well understood, limiting our ability to manage for, and accurately model, soil carbon changes at both local and regional scales. To address this issue, here we combined long-term soil incubations with acid-hydrolysis and dry combustion to parse total SOC (C t ) into three operationally defined SOC pools (active, slow, and recalcitrant) from 9 long-term sites with varying land uses on current and former tallgrass prairie soil. Land uses represented a gradient of soil disturbance histories including remnant prairie, restored prairie, grazed pasture, annual crop rotations, and continuous maize. Dry combustion was used to estimate total carbon (C t , physical), while acid hydrolysis of both the active (C a ) and slow (C s ) pools was used to estimate a recalcitrant carbon pool (C r , chemical). Non-linear modeling of CO 2 efflux data from the long-term incubations was then used to estimate C a , and the decomposition rates of both C a and C s (k a and k r , biological). The size of the slow pools C s was then defined mathematically as C t- (C a + C r ). Remnant prairie had the highest C t , while cool-season pasture and a 35-y-old restored prairie had higher C t than the other agricultural systems. All agricultural systems, including pasture, had the highest fraction of C t as C r (~50%), whose mean residence time (MRT) in these soils is ≥500 years (Paul et al., 2001a) demonstrating that this fraction persists, while the more labile fractions were lost over the course of a few months (C a ) to a few decades (C s ) as a result of tillage-intensive agriculture. The two- to four-decade MRT time of C s indicated a pool likely to be more responsive to the 20 to 40 years of land-use practices used at some of the sites. The C s pool was largest in the remnant- and 35-y-old prairies indicating significant C accrual and stabilization compared to the agricultural ecosystems. Interestingly, the remnant prairie maintained the highest C a pool as well, demonstrating the strong connection between the quantity of fresh C inputs and the potential for long-term C stabilization and accrual. The accumulation of C in active (≈labile) pools as a first step toward long-term stabilization highlights the tenuous nature of early carbon gains, which can be quickly lost in response to climate change or poor management.

54 ENVIRONMENTAL SCIENCES↗

Additive manufacturing of multiscale NiFeMn multi-principal element alloys with tailored composition

Nanostructured multi-principal element alloys (MPEAs) have been explored as next-generation engineering materials due to unique mechanical and functional properties which have significant advantages over traditional dilute alloys. However, the practical applications of nanostructured MPEAs are still limited due to the lack of scalable processing approaches to prepare a large quantity of nanostructured MPEAs, as well as lack of an efficient pathway for high-throughput discovery of better functional nanostructured MPEAs within their vast compositional space. Here we tackle these challenges by presenting an integrated approach by combining direct-ink-writing-based additive manufacturing, solid-state sintering, and chemical dealloying to manufacture hierarchically porous MPEAs. The hierarchical structure is comprised of macro- and micro-scale pores introduced via extrusion printing and polymer decomposition during sintering, as well as nanoscale pores formed via chemical dealloying. The macro- and micro-scale pores allow efficient dealloying of a large mass of material as the diffusion length that the corroding medium must penetrate remains at the scale of the ligaments formed after sintering (∼10 μm), despite the large volume of the 3D-printed samples. In addition, this integrated approach enables versatile control of the alloy composition via precisely tuning the ratio of elemental powders in the starting ink, thus offering a pathway for high-throughput discovery of novel functional MPEAs. As a case study, multiscale macro/micro/nanoporous NiFeMn MPEAs with three different compositions were investigated as catalysts to reduce the overpotential of oxygen evolution reaction (OER), where NiFeMn-based electrocatalysts display composition-dependent performance such that the overpotential measured at a current of 0.5 A g −1 for OER increases in the order of Ni 58 Fe 29 Mn 13 ⩽ Ni 64 Fe 26 Mn 10 < Ni 76 Fe 18 Mn 6 . This introduced manufacturing process offers new opportunities for scalable fabrication and rapid screening of nanostructured multi-component complex alloys.

36 MATERIALS SCIENCE↗

SDSS-IV MaNGA: The incidence of major mergers in type I and II AGN host galaxies in the DR15 sample

We present a study on the incidence of major mergers and their impact on the triggering of nuclear activity in 47 type I and 236 type II optically selected AGN from the MaNGA DR15 sample. From an estimate of non-parametric image predictors (Gini, M_20, concentration (C), asymmetry (A), clumpiness (S), Sérsic index (n), and shape asymmetry ()) using the SDSS images, in combination with a Linear Discriminant Analysis Method, we identified major mergers and merger stages. We reinforced our results by looking for bright tidal features in our post-processed SDSS and DESI legacy images. We find a statistically significant higher incidence of major mergers of 29 per cent ± 3 per cent in our type I+II AGN sample compared to 22 per cent ± 0.8 per cent for a non-AGN sample matched in redshift, stellar mass, colour, and morphological type, finding also a prevalence of post-coalescence (51 per cent ± 5 per cent) over pre-coalescence (23 per cent ± 6 per cent) merger stages. The levels of AGN activity among our massive major mergers are similar to those reported in other works using [O iii] tracers. However, similar levels are produced by our AGN-galaxies hosting stellar bars, suggesting that major mergers are important promoters of nuclear activity but are not the main nor the only mechanism behind the AGN triggering. The tidal strength parameter Q was considered at various scales looking for environmental differences that could affect our results on the merger incidence, finding non-significant differences. Finally, the H-H β diagram could be used as an empirical predictor for the flux coming from an AGN source, useful to correct photometric quantities in large AGN samples emerging from surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

Comparing matching prescriptions between pre-equilibrium and hydrodynamic models in high-energy nuclear collisions

Abstract State-of-the-art simulations of high-energy nuclear collisions rely on hybrid setups, involving in particular a pre-equilibrium stage to let the system evolve from a far-from-equilibrium initial condition towards a near-equilibrated state after which fluid dynamics can be applied meaningfully. A known issue is the mismatch between the equation of state in the fluid-dynamical evolution and the effective one in the previous stage, which leads to discontinuities at the interface between the two models. Here we introduce a new matching prescription at this interface, based on the entropy, and we compare it with the standard one relying on local energy conservation. We study the behavior of various quantities at the switching time between the models and investigate a number of final-state hadronic observables. For the latter, we show that they are not modified significantly by the choice of matching prescription, provided an appropriate normalization is chosen for the initial state. In turn, our approach reduces sizeably the ratio of bulk over thermodynamic pressure at the beginning of the fluid-dynamical stage.

Borghini, Nicolas (ORCID:0000000239063258)↗

Resolving Conflicting Physical and Biochemical Feedbacks to Climate in Response to Long-Term Warming

The goal of the research was to increase our understanding of the microbial mechanisms that control soil organic matter decay in the context of a changing climate. We hypothesized that a major source of carbon respired after long-term soil warming is recalcitrant soil C mineralized by microbes. We found that long-term warming was associated with decreased fungal communities but not bacterial communities, with bacterial communities in organic horizon soils significantly affected by warming. Molecular analysis indicated that this community shift was towards a more oligotrophic community, consistent with previously observed decreased in soil organic matter quality and quantity. We further hypothesized that low labile C resulting from long-term warming has selected for a microbial community that is better able to mineralize recalcitrant C. Analysis of soil communities and individual isolates physiology showed that long-term warming caused bacteria to have increased potential lignolytic activitiy as well as increased carbohydrate degradation potential. This increased ability to degrade recalcitrant soil organic matter is suggested as a mechanism for accelerated soil carbon loss with long-term warming. Soil warming was shown to have little change in transcriptional activity or proteins levels of the enzymes related to recalcitrant C, and little change in the temperature sensitivity of enzyme activity.

54 ENVIRONMENTAL SCIENCES↗

The impact of baryonic potentials on the gravothermal evolution of self-interacting dark matter haloes

The presence of a central baryonic potential can have a significant impact on the gravothermal evolution of self-interacting dark matter (SIDM) haloes. We extend a semi-analytical fluid model to incorporate the influence of a static baryonic potential and calibrate it using controlled N-body simulations. We construct benchmark scenarios with varying baryon concentrations and different SIDM models, including constant and velocity-dependent self-interacting cross-sections. The presence of the baryonic potential induces changes in SIDM halo properties, including central density, core size, and velocity dispersion, and it accelerates the halo’s evolution in both expansion and collapse phases. Furthermore, we observe a quasi-universality in the gravothermal evolution of SIDM haloes with the baryonic potential, resembling a previously known feature in the absence of the baryons. By appropriately rescaling the physical quantities that characterize the SIDM haloes, the evolution of all our benchmark cases exhibits remarkable similarity. In conclusion, our findings offer a framework for testing SIDM predictions using observations of galactic systems where baryons play a significant dynamical role.

79 ASTRONOMY AND ASTROPHYSICS↗

Preparation and Characterization of Various Kraft Lignins and Impact on Their Pyrolysis Behaviors

Lignin-derived chemicals and fuel products have received much attention in the context of bio-refinery. In this study we prepared and characterized various lignin samples from black liquor (BL), a major byproduct from the pulp and paper manufacturing processes, and studied the pyrolysis behaviors of these isolated lignin samples at 600 °C under a N2 atmosphere. Three lignin samples were isolated from the Kraft pulping BL of Loblolly pine linerboard grade process (KL, obtained by direct evaporation; L10, obtained by precipitation at pH 10; L3, obtained by precipitation at pH 3), while another three were from the Kraft pulping BL of Loblolly pine bleach grade process (KB, B10, B3). The inorganic elements present in lignin samples were analyzed using an inductively coupled plasma (ICP) analyzer. The KL and KB samples contained a larger amount of inorganic elements, especially Na and S, than did the other lignin samples. Owing to large quantities of inorganic elements, the ash contents in KL and KB were higher than in the precipitated lignin samples (L10, B10, L3, and B3). These inorganic elements have a significant effect on the subsequent pyrolysis process, as a result, more extensive depolymerization of lignin occurred in KL and KB samples, leading to the formation of fewer pyrolysis oils, with lower molecular weights. NMR analyses of pyrolysis oils show that more methoxyl groups and ether bonds were cleaved, resulting in fewer methoxyl groups and aromatic C–O bonds for the KL and KB heavy oil than for the precipitated lignin heavy oil.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Investigating the effects of precise mass measurements of Ru and Pd isotopes on machine learning mass modeling

Atomic masses are a foundational quantity in our understanding of nuclear structure, astrophysics, and fundamental symmetries. The longstanding goal of creating a predictive global model for the binding energy of a nucleus remains a significant challenge, however, and prompts the need for precise measurements of atomic masses to serve as anchor points for model developments. We present precise mass measurements of neutron-rich Ru and Pd isotopes performed at the Californium Rare Isotope Breeder Upgrade facility at Argonne National Laboratory using the Canadian Penning Trap mass spectrometer. The masses of 108 Ru, 110 Ru, and 116 Pd were measured to a relative mass precision $\delta$⁢$m/m$ ≈ 10 -8 via the phase-imaging ion-cyclotron-resonance technique, and represent an improvement of approximately an order of magnitude over previous measurements. Further, these mass data were used in conjunction with the physically interpretable machine learning (PIML) model, which uses a mixture density neural network to model mass excesses via a mixture of Gaussian distributions. The effects of our new mass data on a Bayesian-updating of a PIML model are presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Flow Induced Vibration Studies in Pressurized Helium Gas Cooling Channels

Production of metastable Technetium-99 (Tc-99m), a radioactive tracer that emits gamma rays, is vital to the medical imaging community. Tc-99m is extracted from the decay of Molybdenum-99 (Mo-99) which has a half-life of about 2-3 days. The work presented in this report is part of the NNSA’s mission to produce Mo-99 commercially, within the US, without the use of highly enriched uranium (HEU) in support of nonproliferation and global security. Los Alamos National Laboratory (LANL) is working with NorthStar Medical Radioisotopes (NMR) on their efforts to produce Mo-99 through the irradiation of Mo-100 targets using an electron beam. The NMR target comprises a stack of approximately 60-70 Mo-100 disks with diameter 24 mm and thickness 0.74 mm held in stainless steel laminations, each separated using 0.25 mm thick stainless steel spacers. The symmetric target stack is housed in an Inconel vessel with two Inconel windows on either side. Two electron accelerators are used to produce 40 MeV, 3.16 µA electron beams each that penetrate the Inconel windows and irradiate the Mo-100 disks. Approximately 90% of the total 250 kW beam power is deposited in the NMR target during the irradiation process. During irradiation, pressurized helium gas flows through 0.25 mm thin gaps between the disks cooling the beam window, target disks, disk laminations and spacers. Both NMR and LANL have found during cold testing of the target system (no heat deposition) that the Mo-100 disks undergo significant mass loss and disk breakage due to vibrations induced by the flowing helium gas. The mass loss is not only undesirable due to monetary loss from reduced final quantities of Mo-99, but also due to the hazards associated with radioactive material trapped in the cooling lines and particle filters. The effect of flow rate and target geometry on the flow induced vibrations need to be quantified, and recommendations provided to minimize this mass loss. This work describes LANL’s experimental characterization of the flow induced vibrations and disk mass loss in a reduced scale set-up containing 10 Mo-100 disks. We use high speed imaging, displacement measurements and microphone measurements combined with signal processing to estimate the vibration frequency of each disk. The effect of disk thickness, target fit and duration of testing on the mass loss is described. We find that in the current configuration of NMR targets, the vibrations and mass loss on the first disk are minimized, while those in the adjacent disks are highest. The microphone and high-speed image data show that increased flow rates and increased duration of testing increases vibration frequency and mass loss. The mass loss is due to both disk rotation and back and forth motion. There are visible wear marks on the disks with the highest mass loss. We also note that the current NMR window gap reduces flow induced vibrations compared to the previous smaller gaps. Longer duration testing will provide more data and verification for the findings presented in this report. The work will be continued in FY 24.

43 PARTICLE ACCELERATORS↗

Seismicity and Stress Associated With a Fluid-Driven Fracture: Estimating the Evolving Geometry

A coupled approach, combining the theory of rate- and state-dependent friction and methods from poroelasticity, forms the basis for a quantitative relationship between displacements and fluid leak-off from a growing fracture and changes in the rate of seismic events in the region surrounding the fracture. Poroelastic Green's functions link fracture aperture changes and fluid flow from the fracture to changes in the stress field and pore pressure in the adjacent formation. The theory of rate- and state-dependent friction provides a connection between Coulomb stress changes and variations in the rate of seismic events. Numerical modeling indicates that the Coulomb stress changes can vary significantly between formations with differing properties. The relationship between the seismicity rate changes and the changes in the formation stresses and fluid pressure is nonlinear, but a transformation produces a quantity that is linearly related to the aperture changes and fluid leak-off from the fracture. The methodology provides a means for mapping changes in seismicity into fracture aperture changes and to image an evolving fracture. An application to observed microseismicity associated with a hydrofracture reveals asymmetric fracture propagation within two main zones, with extended propagation in the upper zone. Furthermore, the time-varying volume of the fracture agrees with the injected volume, given by the integration of rate changes at the injection well, providing validation of the estimated aperture changes.

58 GEOSCIENCES↗

Neural network ensembles and uncertainty estimation for predictions of inelastic mechanical deformation using a finite element method-neural network approach

The finite element method (FEM) is widely used to simulate a variety of physics phenomena. Approaches that integrate FEM with neural networks (NNs) are typically leveraged as an alternative to conducting expensive FEM simulations in order to reduce the computational cost without significantly sacrificing accuracy. However, these methods can produce biased predictions that deviate from those obtained with FEM, since these hybrid FEM-NN approaches rely on approximations trained using physically relevant quantities. In this work, an uncertainty estimation framework is introduced that leverages ensembles of Bayesian neural networks to produce diverse sets of predictions using a hybrid FEM-NN approach that approximates internal forces on a deforming solid body. The uncertainty estimator developed herein reliably infers upper bounds of bias/variance in the predictions for a wide range of interpolation and extrapolation cases using a three-element FEM-NN model of a bar undergoing plastic deformation. This proposed framework offers a powerful tool for assessing the reliability of physics-based surrogate models by establishing uncertainty estimates for predictions spanning a wide range of possible load cases.

42 ENGINEERING↗

Molecular axis distribution moments in ultrafast transient absorption spectroscopy: A path toward ultrafast quantum state tomography

In ultrafast time-resolved experiments with gas phase molecules, the alignment of the molecular axis relative to the polarization of the interacting laser pulses plays a crucial role in determining the dynamics following this light–matter interaction. The molecular axis distribution is influenced by the interacting pulses and is intrinsically linked to the electronic coherences of the excited molecules. However, in typical theoretical calculations of such interactions, the signal is either calculated for a single molecule in the molecular frame or averaged over all possible molecular orientations to compare with the experiment. Such averaging removes information about anisotropy in the molecular-axis distribution, even though anisotropic contributions can play a significant role in the measured experimental signal. Here, we calculate the laboratory frame transient electronic first-order polarization [P (1) ] spectra in terms of separated molecular frame and laboratory frame quantities. The laboratory frame polarizations are compared with orientation-averaged quantum master equation calculations, demonstrating that orientation-averaging captures only the isotropic contributions. We show that our formalism also allows us to evaluate the anisotropic contributions to the spectrum. Lastly, we discuss the application of this approach to achieve ultrafast quantum state tomography using transient absorption spectroscopy and field observables in nonlinear spectroscopy.

74 ATOMIC AND MOLECULAR PHYSICS↗

Energetic particle optimization of quasi-axisymmetric stellarator equilibria

Abstract An important goal of stellarator optimization is to achieve good confinement of energetic particles such as, in the case of a reactor, alphas created by deuterium–tritium fusion. In this work, a fixed-boundary stellarator equilibrium was re-optimized for energetic particle confinement via a two-step process: first, by minimizing deviations from quasi-axisymmetry (QA) on a single flux surface near the mid-radius, and secondly by maintaining this improved QA while minimizing the analytical quantity Γ C , which represents the angle between magnetic flux surfaces and contours of J | | , the second adiabatic invariant. This was performed multiple times, resulting in a group of equilibria with significantly reduced energetic particle losses, as evaluated by Monte Carlo simulations of alpha particles in scaled-up versions of the equilibria. This is the first time that energetic particle losses in a QA stellarator have successfully been reduced by optimizing Γ C . The relationship between energetic particle losses and metrics such as QA error ( E q a ) and Γ C in this set of equilibria were examined via statistical methods and a nearly linear relationship between volume-averaged Γ C and prompt particle losses was found.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗