Stochastic Bifurcation of the North Atlantic Circulation under a Midrange Future Climate Scenario with the NASA-GISS ModelE
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Anastasia Romanou↗
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Symmetric Mass Generation
In recent years tantalizing signs for a novel phase have been reported that is chirally symmetric but nevertheless exhibits massive bound states. The necessary condition for such a phase, referred to as Symmetric Mass Generation (SMG), is the cancellation of all (continuous and discrete) 't~Hooft anomalies. In 3+1 dimensions this occurs in systems containing a multiple of 16 massless Weyl fermions. SMG was originally discovered in lower dimensional condensed matter systems. We present results investigating four dimensional field theories with gauge group SU(3). Our findings suggest that SU(3) with $N_f=8$ fundamental fermions exhibits an SMG phase not only on the lattice but also in the infinite cutoff continuum limit. If confirmed, SMG could provide a new UV completion of the standard model and give rise to new scenarios for beyond standard model physics.
Hasenfratz, Anna [U. Colorado, Boulder] (ORCID:000↗
Using Qualitative Hazard Analysis to Guide Quantitative Safety Analysis
Quantitative methods can be beneficial in many types of safety investigations. However, there are many difficulties in using quantitative m ethods. Far example, there may be little relevant data available. This paper proposes a framework for using quantitative hazard analysis to prioritize hazard scenarios most suitable for quantitative mziysis. The framework first categorizes hazard scenarios by severity and likelihood. We then propose another metric "modeling difficulty" that desc ribes the complexity in modeling a given hazard scenario quantitatively. The combined metrics of severity, likelihood, and modeling difficu lty help to prioritize hazard scenarios for which quantitative analys is should be applied. We have applied this methodology to proposed concepts of operations for reduced wake separation for airplane operatio ns at closely spaced parallel runways.
Shortle, J. F.↗
North American natural gas market and infrastructure developments under different mechanisms of renewable policy coordination
Not Available
Avraam, Charalampos↗
Accounting for nonuniformity of bulk‐solvent: A mosaic model
Abstract A flat mask‐based model is almost universally used in macromolecular crystallography to account for disordered (bulk) solvent. This model assumes any voxel of the crystal unit cell that is not occupied by the atomic model is occupied by the solvent. The properties of this solvent are assumed to be exactly the same across the whole volume of the unit cell. While this is a reasonable approximation in practice, there are a number of scenarios where this model becomes suboptimal. In this work, we enumerate several of these scenarios and describe a new generalized approach to modeling the bulk‐solvent which we refer to as mosaic bulk‐solvent model. The mosaic bulk‐solvent model allows nonuniform features of the solvent in the crystal to be accounted for in a computationally efficient way. It is implemented in the computational crystallography toolbox and the Phenix software.
Afonine, Pavel V.↗
Using long‐term data from a whole ecosystem warming experiment to identify best spring and autumn phenology models
Abstract Predicting vegetation phenology in response to changing environmental factors is key in understanding feedbacks between the biosphere and the climate system. Experimental approaches extending the temperature range beyond historic climate variability provide a unique opportunity to identify model structures that are best suited to predicting phenological changes under future climate scenarios. Here, we model spring and autumn phenological transition dates obtained from digital repeat photography in a boreal Picea ‐ Sphagnum bog in response to a gradient of whole ecosystem warming manipulations of up to +9°C, using five years of observational data. In spring, seven equally best‐performing models for Larix utilized the accumulation of growing degree days as a common driver for temperature forcing. For Picea , the best two models were sequential models requiring winter chilling before spring forcing temperature is accumulated. In shrub, parallel models with chilling and forcing requirements occurring simultaneously were identified as the best models. Autumn models were substantially improved when a CO 2 parameter was included. Overall, the combination of experimental manipulations and multiple years of observations combined with variation in weather provided the framework to rule out a large number of candidate models and to identify best spring and autumn models for each plant functional type.
Schädel, Christina↗
Synchronous Machine Governor Upgrade
Conventional generation sources play a critical role in the stability and reliability of the electrical grid, particularly as we transition towards more renewable energy sources. To understand and accurately emulate their behavior for optimizing grid operations and ensuring seamless integration with renewable technologies, it is essential to better emulate the grid- and plant-level impacts of conventional generation sources, such as natural gas (NG) driven heat recovery steam generators (HRSGs) and combustion turbines (CTs). Therefore, a governor model is developed in a programmable logic controller (PLC) to investigate the performance of the conventional generator under various dynamic operating conditions and to identify the impact on grid stability in a controlled environment. The governor model aims to enable the hardware-in-the-loop (HIL) based emulation of these conventional generation sources using the existing 2 MVA synchronous machine/generator that is driven by a flexible 2.5 MW variable speed drive. This setup will allow us to replicate the dynamic characteristics and response behaviors of NG-driven HRSGs and CTs. The controls for the emulated conventional plants follow the industry standard and are adjustable, ensuring they accurately reflect the operational capabilities and limitations of real-world systems. These controls include load-following capabilities, ramp rates, startup and shutdown sequences, and emissions characteristics. By incorporating these adjustable controls, we aim to capture the nuanced impacts of conventional generation, such as their ability to provide ancillary services like frequency regulation, voltage support, and spinning reserve. In this report, we simulate two types of dynamic operations: grid-connected and islanding. For each dynamic operation, representative starting sequences are tested, including turbine purge, ignition, speed ramping up, generator excitation and synchronizing, and breaker close. The HIL based tests provides insights for field deployment, specifically the high-fidelity governor model provides results to predict the potential stability and reliability risk and suggest possible integration measures (e.g., generation and load balancing, tuning of governor control parameters). Ultimately, this enhanced emulation capability will be integrated into our Advanced Research on Integrated Energy Systems (ARIES), enabling us to conduct comprehensive studies on the interactions between conventional and renewable energy sources. By better understanding these interactions, we can develop strategies to optimize the overall performance and reliability of the grid. This will support the deployment of advanced grid management techniques, such as demand response, grid-forming inverters, and energy storage systems. The main contributions are summarized as follows: (1) This report introduces a PLC-based governor model for gas turbines. This model accurately simulates the dynamic behavior of conventional generation sources under various operational scenarios; (2) The model is integrated with an HIL testbed that includes a 2.5 MW variable speed drive and a 2 MVA synchronous machine. This setup enables realistic, real-time emulation of conventional power plants, particularly NG driven HRSGs and CTs; (3) The developed model is adaptable to various gas turbine configurations and allows for precise control over parameters such as MW ramp rates. This flexibility makes it a valuable tool for future research and industry collaboration; and (4) By incorporating the model into the National Renewable Energy Laboratory's Advanced Research on Integrated Energy Systems, the report lays the groundwork for future studies on interactions between conventional and renewable energy sources, enhancing the ability to develop advanced grid management strategies.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Fractionation of nitrogen isotopic on Mars: The role of the regolith as a buffer
We have measured the adsorption of molecular nitrogen (N2) on palagonite, and modeled the adsorbed nitrogen inventory on the martian regolith. We were motivated by the fact that models of isotopic evolution predict stronger N2 fractionation than reported by Viking. Possible scenarios for reconciling models with the observation include a heavy CO2 atmosphere early in the planet's history, continued outgassing of N2 throughout the history of Mars, or a substantial adsorbed inventory. In this paper we investigate the plausibility of the last explanation. We find that the regolith reservoir of adsorbed N2 is inadequate by itself to buffer the atmospheric isotopic composition, but may play a role depending on the total regolith surface area available.
Zent, A. P.↗
Core-edge integrated predictive studies of ST40 and NSTX plasmas with the scrape-off layer box model
The ability to model the interplay between the core and edge of tokamak plasmas is crucial to designing both the plasma operating scenario of a fusion pilot plant and the design of the tokamak itself. Scrape-off-layer (SOL) models that are tailored to integrated scenario modeling need to have fast turn-around time and minimal computational burden to enable wide parameter-space coverage for design scoping. The SOL 0-D Box model is a reduced SOL model based on global power and particle balance that captures the essential physics of SOL transport with little computational cost. The usage of the 0-D Box model in core-edge coupled simulations has been demonstrated in both interpretive and predictive modes on a variety of devices. This paper presents a sensitivity study of the 0-D Box model to the input SOL heat-flux width for an ST40 plasma. This study demonstrates that accurate prediction of this width is crucial to predicting global performance parameters of a plasma scenario, such as energy confinement time and flux consumption. We also present an extension of the Box model to 1-D to allow for parallel variation of plasma parameters along the magnetic field lines. The 1-D Box model is then compared with SOLPS-ITER simulations of an NSTX plasma. Advantages and limitations of the Box model are discussed, and future directions are outlined.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Modeling Summary of ASNF in DOE Sealed Standard Canisters
A pathway for road-ready and final disposition packaging configurations for the aluminum-clad spent nuclear fuel (ANSF) fuel dictates storage within helium backfilled sealed DOE standard canisters. The typical packaging configuration for the 15-foot DOE canisters places 10 advance test reactor (ATR) elements within a Type 1a basket, and three baskets are loaded within each DOE canister. During in-reactor operations and cooling pond storage conditions, oxyhydroxide layers form on the surface of the aluminum clad fuel. These layers produce hydrogen gas over time due to the fuel’s radiation field. As part of the packing procedure, the ATR fuel should be dried to remove any residual physio-/chemi- sorbed water bound to the surface. The results of this modeling will include results at fully saturated and fully dried conditions. In addition, fuels that are currently stored at the Savannah River Site were also studied for their potential for hydrogen and pressure build up. These two additional fuels modeled were the Missouri University Research Reactor (MURR) fuel, which is packaged in the same configuration as the ATR, but with a 10-foot-tall DOE standard canister. This was selected due to its relatively high decay heat compared to other DOE-managed ASNF. The second additional fuel studied with the modeling effort was the High Flux Isotope Reactor (HFIR) fuel. This fuel is modeled as two separate DOE canisters with the inner and outer annulus split for storage. The HFIR was selected for study due to its high aluminum cladding surface area. In the associated experimental work, Task 2 - Oxyhydroxide Layer Radiolytic Gas Generation Resolution, additional tests were completed in a helium environment, and updated G-values for the radiolytic production of hydrogen from the oxyhydroxide layers were provided. These values were 2.92 ×10 -4 µmol/J at 50% relative humidity and 4.12 ×10 -4 µmol/J at 100% relative humidity. These values are lower than the value for Argon that was used in prior modeling results. In addition, prior modeling results have been completed with the G-value applied to just the mass of the corrosion layer, and this has been updated to apply the G-value for hydrogen generation to the full mass of the fuel. These two effects combine to show much smaller pressure and hydrogen build up for the sealed canister model. For a nominal scenario of stored ATR fuel, after 50 years the model results give a 1.36 atm total pressure, 7% mole percent hydrogen, for the upper decay heat, 1.51 atm total pressure, 16% mole percent hydrogen, and for upper decay heat with undried fuel 2.6 atm total pressure, 15% mole percent hydrogen. For the MURR nominal case, the model results give 1.34 atm and 6% hydrogen, for upper decay heat this gives 1.41 atm total pressure with 10.8 % hydrogen, and for upper decay heat with undried fuel, this gives 2.38 atm total pressure with 9.9% hydrogen. The nominal scenario for HFIR fuel gives 1.39 atm total pressure with 9.9% hydrogen, the upper decay heat case gives 1.43 atm with 12.1% hydrogen, and the upper decay heat with undried fuel gives 2.17 atm total pressure with 11.9% hydrogen. These results confirm the ATR scenario bounds the other intact ASNF modeled here. No case modeled yields significant oxygen, and the lower decay heat cases for all fuels modeled have hydrogen concentrations that are under the 4% flammability limit after 50 years of storage. In addition, the modeled pressures for all cases are all significantly below the 500-psi limit for the DOE standard sealed canister.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Reservoir Thermal Energy Storage Benchmarking (Rev. 3)
A benchmarking analysis of RTES research funded by GTO through the Beyond Batteries projects was conducted against the ESGC to see where they fit within the identified ESGC Use Cases. The projects were found to advance knowledge in multiple ESGC use cases, either directly or in some cases, indirectly as enabling technologies. This analysis is helpful to understand where RTES and associated research fits into the larger discussion around energy storage technologies. Also, a retrospective analysis of the Beyond Batteries projects was conducted to evaluate what the projects learned and how the results can be applied to advance the value of RTES. Major results of each of the studies are summarized in Table 2. Additionally, a comparative metrics analysis for RTES was completed to understand where RTES lies within the energy storage industry. Metrics for evaluation of RTES and its comparison to other storage technologies were selected and ranges of their values compiled. The selected metrics – LCOE (levelized cost of energy), capital costs, roundtrip efficiency, energy storage capacity, and storage time – were chosen based on data availability and have a particularly strong influence on the potential deployment of a storage technology. Charts which compare the metrics are presented in section 4.3 and show ranges for each of the 10 selected technologies. However, due to a lack of domestic operational facilities, values for RTES and for portions of the remaining technologies are based on theoretical modeling and studies of best-case scenarios. LCOE estimates for RTES fall within the lower reaches of Figure 15, but nevertheless amount to 2 – 5 times the ESGC Roadmap goal for LCOE, for example in the Facilitating and Evolving Grid Use Case. Capital costs for RTES sit on the higher end (Figure 16) but are expected to decrease as new projects are developed and the technology is refined. The theoretical roundtrip efficiency reported for RTES varies from mid to high percentages (Figure 17) with efficiencies upwards of 93% in modeled scenarios in the Portland Basin (Bershaw et al.,2020). RTES is also expected to have the largest energy storage capacities and longest storage times, likely matched only by lower efficiency hydrogen storage. To better assess the role that RTES could play in energy storage we examined it’s potential in the U.S. The potential depends on many factors. Recently, many researchers have started looking at deep sedimentary basins, depleted oil and gas fields, and basalt formations as potential targets for RTES development. The United States Geological Survey (USGS) has analyzed various cities and shown substantial RTES potential in the cooling sector (Pepin et al., 2021). By modeling RTES in low-quality groundwater (e.g., brackish), it is shown to be favorable across the U.S. with particular suitability in the Illinois Basin, Coastal Plains, and Basin and Range regions. Seasonal RTES operations have also been modeled in the Portland Basin by those at the USGS and Portland State University to simulate an RTES system supplying heating loads needed for the Oregon Health and Science University. Simulations suggest that high conductive heat loss in the initial years exists but tends to decrease with increasing time and development of the resource due to self-insulating nature of the basalts (Burns et al., 2020). Other national laboratory efforts are taking a close look at many of the technical issues involved with RTES (McLing et al., 2019, McLing et al., 2022). These include difficulties in understanding geochemical, hydrogeological, mechanical, and microbiological changes at such elevated temperatures and operational scenarios. Major gaps in research are identified and suggested for future work. With this increased focus to understand how to make RTES successful in the U.S., this technology could be a potential solution to many of the nation’s energy storage problems. For the energy independence of this country, the DOE should prioritize de-risking this technology by making future investments in pilot-scale demonstrations to attract potential investors.
15 GEOTHERMAL ENERGY↗
Full Order/Reduced Order Modeling Thermal Analysis Comparison of Crash-Burn Scenario using Aria and Pressio_Aria
This work summarizes the findings of a reduced order model (ROM) study performed using Sierra ROM module Pressio_Aria on Sandia National Laboratories' (SNL) Crash-Burn L2 milestone thermal model with pristine geometry. Comparisons are made to full order model (FOM) results for this same Crash-Burn model using Sierra multiphysics module Aria.
97 MATHEMATICS AND COMPUTING↗
SCALE Analyses of Scenarios in the High-Temperature Gas-Cooled Reactor Fuel Cycle
This report demonstrates the SCALE code system’s capabilities in modeling and simulating scenarios in the High-Temperature Gas-cooled Reactor (HTGR) nuclear fuel cycle as part of a United States Nuclear Regulatory Commission (NRC) project that aims to demonstrate the capabilities of the SCALE and MELCOR codes for non-light water reactor (non-LWR) modeling and simulation.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Baryon isocurvature scenario in inflationary cosmology - A particle physics model and its astrophysical implications
A phenomenological model to produce isocurvature baryon-number fluctuations is proposed in the framework of inflationary cosmology. The resulting spectrum of density fluctuation is very different from the conventional Harrison-Zel'dovich shape. The model, with the parameters satisfying several requirements from particle physics and cosmology, provides an appropriate initial condition for the minimal baryon isocurvature scenario of galaxy formation discussed by Peebles.
Yokoyama, Jun'ichi↗
The development and use of decision support framework for informing selection of select agent toxins with modelling studies to inform permissible toxin amounts
Many countries have worked diligently to establish and implement policies and processes to regulate high consequence pathogens and toxins that could have a significant public health impact if misused. In the United States, the Antiterrorism and Effective Death Penalty Act of 1996 (Public Law 104-132, 1996), as amended by the Bioterrorism Preparedness and Response Act of 2002 (Public Law 107-188, 2002) requires that the Department of Health and Human Services (HHS) [through the Centers for Disease Control and Prevention (CDC)] establish a list of bacteria, viruses, and toxins that have the potential to pose a severe threat to public health and safety. Currently, this list is reviewed and updated on a biennial basis using input from subject matter experts (SMEs). We have developed decision support framework (DSF) approaches to facilitate selection of select toxins and, where toxicity data are known, conducted modelling studies to inform selection of toxin amounts that should be excluded from select agent regulations. Exclusion limits allow laboratories to possess toxins under an established limit to support their research or teaching activities without the requirement to register with the Federal Select Agent Program. Fact sheets capturing data from a previously vetted SME workshop convened by CDC, literature review and SME input were developed to assist in evaluating toxins using the DSF approach. The output of the DSF analysis agrees with the current select toxin designations, and no other toxins evaluated in this study were recommended for inclusion on the select agent and toxin list. To inform the selection of exclusion limits, attack scenarios were developed to estimate the amount of toxin needed to impact public health. Scenarios consisted of simulated aerosol releases of a toxin in high-population-density public facilities and the introduction of a toxin into a daily consumable product supply chain. Using published inhalation and ingestion median toxic dose (TD 50 ) and median lethal dose (LD 50 ) values, where available, a range of toxin amounts was examined to estimate the number of people exposed to these amounts in these scenarios. Based on data generated by these models, we proposed toxin exclusion values corresponding to levels below those that would trigger a significant public health response (i.e., amounts estimated to expose up to ten people by inhalation or one hundred people by ingestion to LD 50 or TD 50 levels of toxin in the modeled scenarios).
60 APPLIED LIFE SCIENCES↗
Twin sterile neutrino dark matter
We propose that the dark matter of our Universe could be sterile neutrinos which reside within the twin sector of a mirror twin Higgs model. In our scenario, these particles are produced through a version of the Dodelson-Widrow mechanism that takes place entirely within the twin sector, yielding a dark matter candidate that is consistent with x-ray and gamma-ray line constraints. Furthermore, this scenario can naturally avoid the cosmological problems that are typically encountered in mirror twin Higgs models. In particular, if the sterile neutrinos in the Standard Model sector decay out of equilibrium, they can heat the Standard Model bath and reduce the contributions of the twin particles to N eff . Such decays also reduce the effective temperature of the dark matter, thereby relaxing constraints from large-scale structure. The sterile neutrinos included in this model are compatible with the seesaw mechanism for generating Standard Model neutrino masses. Published by the American Physical Society 2024
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Fusing time-varying mosquito data and continuous mosquito population dynamics models
Climate change is arguably one of the most pressing issues affecting the world today and requires the fusion of disparate data streams to accurately model its impacts. Mosquito populations respond to temperature and precipitation in a nonlinear way, making predicting climate impacts on mosquito-borne diseases an ongoing challenge. Data-driven approaches for accurately modeling mosquito populations are needed for predicting mosquito-borne disease risk under climate change scenarios. Many current models for disease transmission are continuous and autonomous, while mosquito data is discrete and varies both within and between seasons. This study uses an optimization framework to fit a non-autonomous logistic model with periodic net growth rate and carrying capacity parameters for 15 years of daily mosquito time-series data from the Greater Toronto Area of Canada. The resulting parameters accurately capture the inter-annual and intra-seasonal variability of mosquito populations within a single geographic region, and a variance-based sensitivity analysis highlights the influence each parameter has on the peak magnitude and timing of the mosquito season. This method can easily extend to other geographic regions and be integrated into a larger disease transmission model. This method addresses the ongoing challenges of data and model fusion by serving as a link between discrete time-series data and continuous differential equations for mosquito-borne epidemiology models.
97 MATHEMATICS AND COMPUTING↗
Use of Machine Learning Techniques for Iidentification of Robust Teleconnections to East African Rainfall Variability in Observations and Models
Providing advance warning of East African rainfall variations is a particular focus of several groups including those participating in the Famine Early Warming Systems Network. Both seasonal and long-term model projections of climate variability are being used to examine the societal impacts of hydrometeorological variability on seasonal to interannual and longer time scales. The NASA / USAID SERVIR project, which leverages satellite and modeling-based resources for environmental decision making in developing nations, is focusing on the evaluation of both seasonal and climate model projections to develop downscaled scenarios for using in impact modeling. The utility of these projections is reliant on the ability of current models to capture the embedded relationships between East African rainfall and evolving forcing within the coupled ocean-atmosphere-land climate system. Previous studies have posited relationships between variations in El Niño, the Walker circulation, Pacific decadal variability (PDV), and anthropogenic forcing. This study applies machine learning methods (e.g. clustering, probabilistic graphical model, nonlinear PCA) to observational datasets in an attempt to expose the importance of local and remote forcing mechanisms of East African rainfall variability. The ability of the NASA Goddard Earth Observing System (GEOS5) coupled model to capture the associated relationships will be evaluated using Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations.
Roberts, J. Brent↗