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At least 127 records · Page 7

Assessment of Low-Altitude Atmospheric Turbulence Models for Aircraft Aeroelasticity

We investigate the dynamic aeroelastic response of large but slow aircraft in low-altitude atmospheric turbulence. To this end, three turbulence models of increasing fidelity, namely, the one-dimensional von Kármán model, the two-dimensional Kaimal model and full three-dimensional wind fields extracted from large-eddy simulations (LES) are used to simulate ambient turbulence near the ground. Load calculations and flight trajectory predictions are conducted for a representative high-aspect-ratio wing aircraft, using a fully coupled nonlinear flight dynamics/aeroelastic model, when it operates in background atmospheric turbulence generated by the aforementioned models. Comparison of load envelopes and spectral content, on vehicles of varying flexibility, shows strong dependency between the selected turbulence model and aircraft aeroelastic response (e.g. 58% difference in the predicted magnitude of the wing root bending moment between LES and von Kármán models). This is mainly due to the presence of large flow structures at low altitudes that have comparable dimensions to the vehicle, and which despite the relatively small wind speeds within the Earth boundary layer, result in overall high load events for slow-moving vehicles. Results show that one-dimensional models that do not capture those effects provide fairly non-conservative load estimates and are unsuitable for very flexible airframe design.

atmospheric turbulence↗

Uranium carbide properties for advanced fuel modeling – A review

Uranium carbides are receiving renewed interest as a preferred nuclear fuel composition for advanced reactors due to their numerous favorable properties. Like many other refractory and transition metal carbides these compounds exist in both hypo- and hyper-stoichiometric compositions which results in significant variations in physical, thermal, and mechanical properties. This manuscript surveys both historic and recent literature to compile important properties data mainly as a function of temperature and carbon content to support fuel performance modeling. Expressions and fits for such properties are also suggested when allowed by complete data sets. Finally, the manuscript also attempts to highlight gaps and discrepancies in the reported data to assist the nuclear fuels community identify key areas that may require further attention in terms of future research and development.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Baryogenesis in a parity solution to the strong CP problem

Abstract Space-time parity can solve the strong CP problem and introduces a spontaneously broken SU(2) R gauge symmetry. We investigate the possibility of baryogenesis from a first-order SU(2) R phase transition similar to electroweak baryogenesis. We consider a model with the minimal Higgs content, for which the strong CP problem is indeed solved without introducing extra symmetry beyond parity. Although the parity symmetry seems to forbid the SU(2) R anomaly of theB−Lsymmetry, the structure of the fermion masses can allow for the SU(2) R sphaleron process to produce non-zeroB−Lasymmetry of Standard Model particles so that the wash out by the SU(2) L sphaleron process is avoided. The setup predicts a new hyper-charged fermion whose mass is correlated with the SU(2) R symmetry breaking scale and hence with the SU(2) R gauge boson mass, and depending on the origin of CP violation, with an electron electric dipole moment. In a setup where CP violation and the first-order phase transition are assisted by a singlet scalar field, the singlet can be searched for at future colliders.

Physics↗

WETO Stack [SWR-24-81]

The WETO Stack software is a collection of data, data analysis scripts, and website content produced through the Holistic Modeling Project’s Portfolio Coordination task. The purpose of the software is to characterize the collection of wind energy software projects supported by the U.S. Department of Energy’s Wind Energy Technologies Office. The included data contains characteristics of the actively funded software projects, and the data analysis scripts provide insights into the breadth, depth, and maturity of the collection of software projects. The website content presents the results of the analyses as well as reports from workshops and other events. It can be viewed at https://nrel.github.io/WETOStack/index.html.

Mudafort, Rafael↗

Data-driven electrolyte design for lithium metal anodes

Improving Coulombic efficiency (CE) is key to the adoption of high energy density lithium metal batteries. Liquid electrolyte engineering has emerged as a promising strategy for improving the CE of lithium metal batteries, but its complexity renders the performance prediction and design of electrolytes challenging. Here, we develop machine learning (ML) models that assist and accelerate the design of high-performance electrolytes. Using the elemental composition of electrolytes as the features of our models, we apply linear regression, random forest, and bagging models to identify the critical features for predicting CE. Our models reveal that a reduction in the solvent oxygen content is critical for superior CE. We use the ML models to design electrolyte formulations with fluorine-free solvents that achieve a high CE of 99.70%. This work highlights the promise of data-driven approaches that can accelerate the design of high-performance electrolytes for lithium metal batteries.

25 ENERGY STORAGE↗

The direct and indirect drivers shaping RNA viral communities in grassland soils

ABSTRACT Recent studies have revealed diverse RNA viral communities in soils. Yet, how environmental factors influence soil RNA viruses remains largely unknown. Here, we recovered RNA viral communities from bulk metatranscriptomes sequenced from grassland soils managed for 5 years under multiple environmental conditions including water content, plant presence, cultivar type, and soil depth. More than half of the unique RNA viral contigs (64.6%) were assigned with putative hosts. About 74.7% of these classified RNA viral contigs are known as eukaryotic RNA viruses suggesting eukaryotic RNA viruses may outnumber prokaryotic RNA viruses by nearly three times in this grassland. Of the identified eukaryotic RNA viruses and the associated eukaryotic species, the most dominant taxa were Mitoviridae with an average relative abundance of 72.4%, and their natural hosts, Fungi with an average relative abundance of 56.6%. Network analysis and structural equation modeling support that soil water content, plant presence, and type of cultivar individually demonstrate a significant positive impact on eukaryotic RNA viral richness directly as well as indirectly on eukaryotic RNA viral abundance via influencing the co-existing eukaryotic members. A significant negative influence of soil depth on soil eukaryotic richness and abundance indirectly impacts soil eukaryotic RNA viral communities. These results provide new insights into the collective influence of multiple environmental and community factors that shape soil RNA viral communities and offer a structured perspective of how RNA virus diversity and ecology respond to environmental changes. IMPORTANCE Climate change has been reshaping the soil environment as well as the residing microbiome. This study provides field-relevant information on how environmental and community factors collectively shape soil RNA communities and contribute to ecological understanding of RNA viral survival under various environmental conditions and virus-host interactions in soil. This knowledge is critical for predicting the viral responses to climate change and the potential emergence of biothreats.

59 BASIC BIOLOGICAL SCIENCES↗

Validation of energetic particle transport models for time-dependent integrated simulations of burning plasmas (Final ST Report)

The major goal of this project is to deliver a suite of validated energetic particle (EP) modeling tools for time-dependent integrated tokamak simulations (with the code TRANSP) that can be used for modeling plasma discharges featuring a substantial EP content, such as burning plasmas. During FY20, issues were resolved with an energetic particle transport model called TGLF-EP, with improvements made to the TGLF-EP workflow, generation of input files, and interpretation of runs on the NERSC supercomputing cluster. The recipient also gave input on simulations with the code TRANSP to reproduce the reference JET discharge, and assessed the accuracy and uncertainties of the simulated B field, current evolution, thermal plasma profiles, stored energy, etc. Input was also given on interpretation of fast-ion instability calculations and recommendations for modifications to JET afterglow discharge for the upcoming DT campaign.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Strain Gauge Diagnostic Development for use in Vessel Health Monitoring for Hydro-shots

Six-foot vessels are a crucial component to protecting high fidelity equipment at DARHT. Analysis shows these vessels have a limited life span (~10 shots) due to fatigue, ratcheting, and damage accumulation. Vessel health monitoring and diagnostics can help inform decision on a vessel’s fitness for service. Strain gauges are an easy and effective sensor for use in vessel health monitoring. In early March, J-2 executed a qualification shot, uniform blast loading with minimal fragments, with bi-axial strain gauges fielded at four locations around vessel. Several damage features were extracted from the data, and frequency content helps to validate computer modelling of the vessel response. Permanent plastic strain at each location was significant with location one having the most strain at the end state, with 230 micro-strain. However, residual pressure in the vessel could be a major factor in this strain. PEEQ is a measure of total plastic equivalent strain accumulation. The equivalent strain at location one exceeded the plastic strain limit four times and accumulated the most PEEQ with 2036 micro-strain. As expected, this qualification shot did contribute to damage in the vessel, and should be considered in its fitness for service, but not critical enough to pull it from service. Frequency content also gave valuable information on the modal response of the vessel and contributes to the understanding of how the vessel responds to the initial blast load with an expected lower frequency membrane/breathing mode and transitioning to higher frequency bending modes in the vessel wall.

42 ENGINEERING↗

COOL-LAMPS. I. An Extraordinarily Bright Lensed Galaxy at Redshift 5.04

In this paper, we report the discovery of COOL J1241+2219, a strongly lensed galaxy at redshift z = 5.043 ± 0.002 with observed magnitude z AB = 20.47, lensed by a moderate-mass galaxy cluster at z = 1.001 ± 0.001. COOL J1241+2219 is the brightest lensed galaxy currently known at optical and near-infrared wavelengths at z $\gtrsim$ 5; it is ~5 times brighter than the prior record-holder lensed galaxy, and several magnitudes brighter than the brightest unlensed galaxies known at these redshifts. It was discovered as part of COOL-LAMPS, a collaboration initiated to find strongly lensed systems in recent public optical imaging data. We characterize the lensed galaxy, as well as the central galaxy of the lensing cluster using ground-based grizJH imaging and optical spectroscopy. We report model-based magnitudes, and derive stellar masses, dust content, metallicity, and star-formation rates via stellar-population synthesis modeling. Our lens mass modeling, based on ground-based imaging, implies a median source magnification of ~30, which puts the stellar mass and star-formation rate (in the youngest age bin, closest to the epoch of observation) at logM* = ${10.11}_{-0.26}^{+0.21}$ and SFR = ${27}_{-9}^{+13} M_⊙$ yr –1 , respectively. We constrain a star-formation history for COOL J1241+2219 consistent with constant star formation across ~1 Gyr of cosmic time, and that places this galaxy on the high-mass end of the star-forming main sequence. COOL J1241+2219 is two to four times more luminous than a galaxy with the characteristic UV luminosity at these redshifts. The UV continuum slope β = –2.2 ± 0.2 places this galaxy on the blue side of the observed distribution of galaxies at z = 5, although the lack of Lyα emission indicates dust sufficient to suppress this emission.

79 ASTRONOMY AND ASTROPHYSICS↗

Neutronic Consideration of TREAT Facility Fuel SiC Recladding

The Transient Reactor Test (TREAT) Facility is an air-cooled reactor composed of graphite-urania fuel encapsulated in zirconium alloy canisters and surrounded by ~2 ft (~61 cm) of nuclear grade graphite. The primary role of TREAT is to provide in-pile nuclear-heated safety research via transient testing [1]. Benchmark efforts have demonstrated sensitivity of TREAT neutronics models to graphite cross section data and key neutron poisons found in the fuel assemblies [2]. During fabrication of TREAT fuel assemblies, a small concentration of boron was inadvertently introduced with variable concentration into the aggregate of fuel blocks prepared for TREAT use. The concentration of boron, and its respective uncertainty, represent the most sensitive component in a neutronics study; unfortunately, nothing can be done to reduce or otherwise mitigate its impact. Hydrogen in the fuel blocks reduces the mean free path of the core and its true quantity and uncertainty is approximated. The hydrogen remains from pitch binder used in the fuel fabrication process and was not completely released due to incomplete fuel graphitization. Destructive fuel testing is necessary to quantify the actual hydrogen content and to improve benchmark model quality. A third neutron poison of some significance is the hafnium impurity in the Zircaloy-3 (Zry-3) assembly cladding. The quantity of hafnium is expected to be within nominal manufacturing limits for nuclear grade zircaloy. Recladding the fuel assemblies with material that is less neutron absorbing is expected to benefit reactor neutron economy. Moreover, TREAT’s total transient energy is restricted based on the rate of Zry-3 oxidation in TREAT’s air coolant environment. Hence, cladding with more benign air reaction kinetics could dramatically uprate the facility’s experimental capability. Silicon carbide (SiC) has been proposed as a candidate material for recladding TREAT assemblies, as SiC/SiC demonstrate favorable properties within nuclear environments [3]. The current operational limits of TREAT are restricted by the oxidation of Zry-3. Change of the cladding to SiC could feasibly double the current temperature limitation. Recladding opportunities allow for previously damaged fuel assemblies to be returned to service, as Zry-3 is not commercially available. The initial effort required to consider proceeding with any recladding effort is to neutronically characterize key reactor parameters while replacing Zry-3 with SiC. A characterization summary, with respective results, is provided herein.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Drop Analysis of the Advanced Test Reactor Fresh Fuel Shipping Container with Heavier Low-Enriched Uranium Fuel Contents

The Advanced Test Reactor Fresh Fuel Shipping Container (ATR FFSC) is a rectangular stainless steel container used for shipping radioactive material. The container is described in the ATR FFSC Safety Analysis Report (SAR). Per the ATR FFSC SAR, the ATR FFSC is designated a Type AF-96 packaging per the definition of 10 CFR §71.4, and was originally designed to transport high enriched uranium (HEU) reactor fuel elements for the Advanced Test Reactor (ATR), the Advanced Test Reactor Critical (ATRC) facility, the Massachusetts Institute of Technology Reactor (MITR), and the University of Missouri Research Reactor (MURR). The Department of Energy, National Nuclear Security Administration’s (NNSA), Office of Material Management and Minimization (M3) is working with the Idaho National Laboratory (INL) to develop and qualify new low enriched uranium (LEU) fuels and technologies for use in the ATR, ATRC, MITR, and MURR reactors. The LEU fuel elements will weigh significantly more than the current HEU designs and, combined with their associated Fuel Handling Enclosures for packaging, some configurations will exceed the 50 lbf used in the ATR FFSC qualifying drop tests. There are LEU versions of MITR, MURR, and ATR fuel elements. However, for this evaluation, drop analysis of the ATR FFSC with only the heavier ATR Low Enrichment (LOWE) fuel element is considered in this evaluation because the LOWE fuel element is the heaviest of the considered LEU fuel elements. The ATR HEU fuel element and the ATR LOWE fuel element are identical in every design aspect except for the fuel meat inside the 19 fuel plates. The LEU fuel meats are made using a U-10Mo high-density foil rather than uranium dispersed in aluminum in the HEU fuel elements. The high density of the uranium in the LEU fuel meat increases the LOWE fuel element weight to just under 44 lbf (versus the 22.1 lbf weight of the tested ATR HEU fuel element). ATR fuel elements are placed in a thin-gauge aluminum weldment called a "Fuel Handling Enclosure" during packaging. The Fuel Handling Enclosure is used to cover and protect the element during loading and unloading operations. The ATR Fuel Handling Enclosure weighs about 15 lbf per the drawings in the ATR FFSC SAR and the weight is accounted for in this evaluation. Transporting the heavier LEU fuel elements require evaluation of two issues. The first is the effect of the increased mass of the LEU fuel elements on the survivability of the ATR FFSC package following the requisite drop qualifications. The second is the effect of the increased mass of the fuel plates on the fuel element during the same drops. The ATR FFSC containing an ATR HEU fuel element in an ATR Fuel Handling Enclosure was physically dropped multiple times to qualify the container as a Type AF-96 package. The ATR FFSC SAR describes the drop tests performed with an actual ATR HEU fuel element weighing 22.1 lbf contained in a 14.3 lbf Fuel Handling Enclosure for a total payload of 36.4 lbf. Those drop tests showed that the ATR FFSC maintained containment of the ATR HEU fuel element and the fuel element was not significantly damaged. (Containment herein is not defined as a leak tight but is retention of the radioactive contents.) The purpose of the evaluation is to analytically show that, for a similar set of tests, the ATR FFSC maintains containment of the heavier ATR LOWE fuel element and to assess the damage to the fuel element during the drops. The approach was to create finite element analysis (FEA) models that produce the same results as the physical drops. Those models were then used as the benchmarks for the follow-on analyses using the heavier contents. FEA models of the drops of ATR FFSC using up to a 115 lbf fuel element were run and evaluated. Likewise, drops of a LOWE fuel element weighing 44 lbf in the ATR FFSC were run and evaluated. It is important to note that this report was done at the quality level necessary to be included in a nuclear facility safety basis. However, it is not the intent of this report to conclude the suitability of the ATR FFSC for transporting the heavier payloads. This report only describes the results of the FEA as related to the required drop scenarios. Incorporation of the FEA into the safety basis will be evaluated by the ATR FFSC design authority. The physical drop tests of the HEU fuel element and FEA drop analysis for the LOWE fuel element showed noteworthy damage to the fuel plates. An aluminum protective block was conceived to mitigate the damage. The concept requires the blocks to be placed in the fuel element between the end boxes and fuel plates. Additional FEA drop analyses were performed using the protective block. The addition of the blocks is primarily intended to mitigate the damage to the LOWE fuel element fuel plates. However, FEA drop analyses of the ATR HEU fuel element with the blocks were also performed and included for information.

42 ENGINEERING↗

Verification of Special Nuclear Material (SNM) using Active Well Coincidence Counter (AWCC) and a High Purity Germanium (HPGe) Detector

SNM verification can be accomplished via two methods i.e. destructive analysis (DA) or nondestructive analysis (NDA). The DA modes are much more accurate compared to NDA modes; nevertheless, the sample's physical integrity is destroyed in the process. Techniques such as ICP-MS, ID-ICP-MS, TI-MS are few examples of DA, where a bulk material is ground and mixed with a solution (some form of acid) to acquire a homogenous sample. In contrast, NDA modes utilize signals emitted by the sample such as gamma, neutrons, light, or heat to analyze samples under investigation. HPGe detectors are some of the most frequently used gamma detectors to assay SNM. However, in a high activity scenario it provides a large uncertainty and sometimes becomes unfeasible to measure low energy gamma rays. Meanwhile, neutron detectors are not affected by the gamma background, therefore they can be used in addition to the gamma detectors to verify total fissile mass ({sup 235}U + {sup 239}Pu) of SNM. The AWCC is one of the thermal neutron NDA systems developed at the Los Alamos National Laboratory (LANL). It consists of 42 {sup 3}He detectors to measure gross neutrons (singles), coincidence neutrons (doubles), higher order multiplicity counting (triples, quadruples, etc.). It can effectively operate in both active and passive neutron interrogation modes. It can utilize AmLi, AmBe, or {sup 252}Cf active interrogation neutron sources. It is used to verify declared fissile mass ({sup 235}U or {sup 239}Pu) present in SNM. Objectives: Calibrate HPGe and AWCC for lightly irradiated (with enough {sup 137}Cs gamma background) ∼93% enriched HEU fuels; Verify fissile mass ({sup 235}U +{sup 239}Pu) content using AWCC and HPGe; Model and benchmark AWCC in MCNP6. Neutron coincidence and multiplicity counting: Two or more neutrons are coincident if they are detected by the system within the specified gate window; In AWCC: Gate window is 128 μsec; Induced fission in fissile material such as {sup 235}U and {sup 239}Pu - emission of time correlated neutrons - Singles, Doubles, Triples, or Quadruples; No induced fission in non-fissile materials- no correlated neutrons - only singles. SNM can be verified with high accuracy and precision using gamma and neutron NDA instruments such as HPGe and AWCC. Interaction with thermal neutrons. Non-fissile atoms - do not emit correlated neutrons. Fissile atoms - emit correlated neutrons during induced fission events. The time correlated neutrons can be detected by using coincidence or multiplicity counters such as AWCC. Likewise, {sup 235}U produces 186 keV gamma peak that can be measured by a HPGe gamma detector. Counts under 186 keV gamma peak provide information about {sup 235}U content. Combining AWCC and HPGe results can provide better understanding of special nuclear material under investigation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Particle Track Classification Using Quantum Associative Memory (Final Technical Report)

This project explored the use of quantum-assisted algorithms for pattern matching in sub-atomic physics experiments. Pattern matching algorithms are commonly employed to prune data of random noise and to help discriminate between signals generated by particle tracks of interest and signals generated by background events. The quantum-assisted algorithms explored in this project were based on an Ising formulation of quantum associative model (QAMM) recall and quantum content-addressable memory (QCAM) recall. The recall is performed by comparing a probe pattern with those stored in a library of patterns encoded in the QAMM/QCAM model. The classification accuracy of QAMM and QCAM recall was determined as a function of detector resolution, noise, and efficiency and pattern density, where pattern density is defined as the ratio of the number of reference signal patterns encoded in the library to each pattern’s length. We found that QAMM achieved high classification accuracy when applied to datasets with low pattern density. QCAM achieved high classification accuracy for datasets with high pattern density and was found to be more robust to detector noise. The project methodology and results are described in detail in our arXiv preprint (arXiv:2011.11848) . This project was conducted by scientists at the Johns Hopkins University Applied Physics Laboratory and Oak Ridge National Laboratory from August 2018 to August 2020 and was supported by DOE grant DE-SC0019497.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

High concentrations of ice: Investigations using polarimetric radar observations combined with in situ measurements and cloud modeling (Final Report)

This DOE-funded joint project had the over-arching goal of understanding the reasons for observed size distributions of ice particles in cold clouds. Its approach involves the use of cloud models and field observations by radar and aircraft of real storms. The project addresses three major research objectives: (1) Utilize a novel polarimetric radar technique to retrieve size distributions and amounts of ice from radar data collected during the previous DOE ARM field campaigns; (2) Evaluate the results of ice microphysical retrievals using available in situ aircraft measurements and other remote sensors (e.g., vertically pointing cloud radars and wind profilers); (3) Improve the treatment of microphysical processes leading to cloud glaciation and ice multiplication in numerical cloud models. The study was performed by three research organizations: University of Oklahoma, The Hebrew University of Jerusalem, Israel, and Lund University, Sweden. The Israel and Swedish partners were funded by the sub-awards from the University of Oklahoma. Cloud modeling studies have been performed by the research teams at The Hebrew University of Jerusalem (HUJ) and Lund University to identify the origins of high concentrations of cloud ice in areas of high ice water content (HIWC). The Hebrew University Cloud Model (HUCM) with full spectral bin microphysics and the Lund University aerosol-cloud (AC) model with a hybrid bin / bulk microphysics scheme complementing HUCM were utilized for simulations. Both research teams had particular focus on secondary ice production (SIP) as one of the possible sources of enhanced ice concentration. The HUJ group suggested a novel concept of ice multiplication during droplet freezing. It is assumed that splintering and droplet fragmentation during droplet freezing takes place because of dendritic growth within a supercooled drop. The resulting simulations of SIP generated small ice in concentrations exceeding hundreds per liter similar to what was observed in the HIWC regions of the tropical storms. The Lund team explored the SIP mechanisms such as breakup of ice particles due to ice-ice collisions and ice sublimation that are expected to dominate the continental storms. They also quantified the impact of homogeneous nucleation of cloud droplets on the total number concentration of ice at very low temperatures near the tops of the clouds. Additionally, the Lund AC model is able to simulate the effect of aerosols of various types (including biological) on the cloud life cycle and the corresponding ice production. The HUCM / AC model was used to simulate one of the “golden” cases of the DOE MC3E campaign on 20 May 2011. The model output was converted into the fields of polarimetric radar variables using the polarimetric radar forward operator developed at the University of Oklahoma and compared with radar observations and in situ microphysical measurements onboard research aircraft. It was demonstrated that specific differential phase KDP is the best radar parameter to identify the HIWC areas and quantify the corresponding ice parameters. For the first time, the shape of the vertical profile of KDP was realistically reproduced by the cloud model with the KDP maximum in the dendritic growth layer (DGL) centered at the -15°C isotherm. The University of Oklahoma team has developed a methodology for polarimetric radar retrievals of such microphysical parameters of ice as ice water content (IWC), mean volume diameter (Dm), and total number concentration (Nt) of ice particles. These retrievals have been validated using in situ aircraft measurements during 6 field campaigns and proved to be quite robust and reliable. This allowed to build the first climatology of the vertical profiles of polarimetric radar variables and retrieved microphysical parameters for the three types of weather systems: continental MCSs, maritime MCSs, and tropical cyclones / hurricanes (Hu and Ryzhkov 2022). The data were collected by a multitude of the WSR-88D radars in 13 continental and 10 maritime MCSs and 11 landfalling hurricanes. The HIWC areas were identified within the examined storms and the corresponding “HIWC statistics” was compared with the “background” one without HIWC. An overarching conclusion of the study is that maritime tropical storms (MCSs and hurricanes) are characterized by smaller size ice in higher concentration compared to the continental MCSs. High ice water content in the HIWC areas is primarily caused by a strong jump in a number concentration of ice particles rather than the increase of their size compared to the “background” environment. This may point to the homogeneous nucleation of excessive amounts of supercooled droplets and / or secondary ice production as the possible origins of HIWC. Such a climatology provides a good observational reference for the modelers to evaluate the performance of their models. As an example, the in-depth analysis of the 20 May 2011 MC3E case shows that the advanced cloud models developed in the course of this study still tend to underestimate the number concentration of ice in the HIWC areas although they succeed in reproducing realistically looking vertical profiles of IWC and Nt. The results of the project research are summarized in 13 journal papers.

54 ENVIRONMENTAL SCIENCES↗

Elliptic flow coalescence to identify the $f_0$(980) content

Here we use a simple coalescence model to generate $f_0$(980) particles for three configurations: a $s\bar{s}$ meson, a $u\bar{u}s\bar{s}$ tetraquark, and a $K^+K^–$ molecule. The phase-space information of the coalescing constituents is taken from a multiphase transport (AMPT) simulation of heavy-ion collisions. It is shown that the number of constituent quarks scaling of the elliptic flow anisotropy can be used to discern $s\bar{s}$ from $u\bar{u}s\bar{s}$ and $K^+K^–$ configurations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Microbial seasonality promotes soil respiratory carbon emission in natural ecosystems: A modeling study

Seasonality is a key feature of the biosphere and the seasonal dynamics of soil carbon (C) emissions represent a fundamental mechanism regulating the terrestrial–climate interaction. We applied a microbial explicit model—CLM-Microbe—to evaluate the impacts of microbial seasonality on soil C cycling in terrestrial ecosystems. Additionally, the CLM-Microbe model was validated in simulating belowground respiratory fluxes, that is, microbial respiration, root respiration, and soil respiration at the site level. On average, the CLM-Microbe model explained 72% (n = 19, p < 0.0001), 65% (n = 19, p < 0.0001), and 71% (n = 18, p < 0.0001) of the variation in microbial respiration, root respiration, and soil respiration, respectively. We then compared the model simulations of soil respiratory fluxes and soil organic C content in top 1 m between the CLM-Microbe model with (CLM-Microbe) and without (CLM-Microbe_wos) seasonal dynamics of soil microbial biomass in natural biomes. Removing soil microbial seasonality reduced model performance in simulating microbial respiration and soil respiration, but led to slight differences in simulating root respiration. Compared with the CLM-Microbe, the CLM-Microbe_wos underestimated the annual flux of microbial respiration by 0.6%–32% and annual flux of soil respiration by 0.4%–29% in natural biomes. Correspondingly, the CLM-Microbe_wos estimated higher soil organic C content in top 1 m (0.2%–7%) except for the sites in Arctic and boreal regions. Our findings suggest that soil microbial seasonality enhances soil respiratory C emissions, leading to a decline in SOC storage. An explicit representation of soil microbial seasonality represents a critical improvement for projecting soil C decomposition and reducing the uncertainties in global C cycle projection under the changing climate.

59 BASIC BIOLOGICAL SCIENCES↗

Axion domain walls, small instantons, and non-invertible symmetry breaking

Non-invertible global symmetry often predicts degeneracy in axion potentials and carries important information about the global form of the gauge group. When these symmetries are spontaneously broken they can lead to the formation of stable axion domain wall networks which support topological degrees of freedom on their worldvolume. Such non-invertible symmetries can be broken by embedding into appropriate larger UV gauge groups where small instanton contributions lift the vacuum degeneracy, and provide a possible solution to the domain wall problem. We explain these ideas in simple illustrative examples and then apply them to the Standard Model, whose gauge algebra and matter content are consistent with several possible global structures. Each possible global structure leads to different selection rules on the axion couplings, and various UV completions of the Standard Model lead to more specific relations. As a proof of principle, we also present an example of a UV embedding of the Standard Model which can solve the axion domain wall problem. The formation and annihilation of the long-lived axion domain walls can lead to observables, such as gravitational wave signals. Observing such signals, in combination with the axion coupling measurements, can provide valuable insight into the global structure of the Standard Model, as well as its UV completion.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗