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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 901 records · Page 50

Modeling 233 Pa Generation in Thorium-fueled Reactors for Safeguards

Thorium has been considered as a possible alternative to uranium for nuclear fuel for many decades. It is three to four times more abundant in the earth than uranium and produces significantly less long-lived transuranic nuclear waste. Some claim thorium poses fewer proliferation concerns than other fuel types largely due to 232 U buildup (and associated high energy gamma-emitting decay products) in the irradiated thorium fuel. However, to fully explore potential proliferation concerns, generation and subsequent decay of 233 Pa produced in the reactor core still must be studied. With its half-life of 27 days, 233 Pa decays to 233 U, which is an International Atomic Energy Agency (IAEA) defined special fissionable material that can be used for nuclear weapons production. With more research being dedicated to thorium-fueled reactors, and several of these reactor designs possessing online fuel processing (allowing for on-site protactinium separation), it is important to understand this potential proliferation pathway. In particular, it is theoretically possible to extract protactinium from the irradiated fuel salt before it decays into 233 U. This hypothetical potential diversion can become an even greater proliferation concern if the extracted protactinium is purified through a second separation of protactinium approximately ten days later to remove the short half-life decay products of 232 Pa and 234 Pa, thus resulting in a higher concentration of the 233 Pa isotope, which decays into weapons usable 233 U with hardly any 232 U or 234 U in it. To estimate the concern of this potential proliferation challenge of thorium, different nuclear material accountancy techniques were reviewed for their viability to quantify 233 Pa if extracted from used thorium fuel. Characteristics of interest included technology maturity, cost, precision, and time taken to acquire results. Some technologies, like hybrid K-edge densitometry and passive gamma spectroscopy, appear to be viable techniques based on current literature. Due to the limited scope of this project, only passive gamma spectroscopy was further investigated. Three different reactor types (PWR, CANDU, MSR) were modeled with mixed thorium-uranium oxide fuels that were burned until the fuel was spent. The protactinium in the used fuel was extracted at the time of shutdown and the change in isotopic content of the protactinium quantified. Gamma spectroscopy simulations were performed for the protactinium isotopes and their decay products at various decay times. Given the simplicity of the models and large assumptions made (e.g. no background, no shielding, no self-attenuation), the initial results indicate that though 233 Pa is detectible for all the reactor types modeled at all decay times (0 to 300 days), more work should be done with higher fidelity models.

07 ISOTOPE AND RADIATION SOURCES↗

Extreme waves in present and future climates using physics-based synthetic tropical cyclones in the Gulf of Mexico.

Historically, extreme waves have been the most destructive force in the Gulf of Mexico, destroying and damaging thousands of offshore structures. The American Petroleum Institute has revised its design criteria for offshore platforms several times over the decades, as new data continues to become available, showing that data for our present climate is insufficient. This problem is exacerbated in a changing climate. By using synthetic physics-based tropical cyclones to force a third-generation wave model, we can generate adequate statistics for present and future climates. These simulations have been completed using Joule Supercomputer.

Climate Change↗

Digital polycrystalline microstructure generation using diffusion probabilistic models

Accurate micromechanical simulation of polycrystalline materials requires a realistic digital representation of the grain scale microstructure. Here, this work demonstrates the use of a generative diffusion probabilistic model for synthesizing single phase polycrystalline realizations. The model performs well and is capable of producing realistic microstructures consisting of not just simple equiaxed structures but also structures exhibiting more complex spatial arrangements. Masked microstructure generation reveals that the model is context aware of morphological descriptors which may be encoded in the latent space. Training on more diverse data sets, with scaled up architectures, may enable development of future models capable of synthesizing even more complex microstructural features.

36 MATERIALS SCIENCE↗

Data-Driven Selection of Tessellation Models Describing Polycrystalline Microstructures

Tessellation models have proven to be useful for the geometric description of grain microstructures in polycrystalline materials. With the use of a suitable tessellation model, the complex morphology of grains can be represented by a small number of parameters assigned to each grain, which not only entails a significant reduction in complexity, but also facilitates the investigation of certain geometric features of the microstructure. However, for a given set of microstructural data, the choice of a particular geometric model is traditionally based on researcher intuition. The model should provide a sufficiently good approximation to the data, while keeping the number of parameters small. In this paper, we discuss general aspects of the process of model selection and suggest several criteria for selecting an appropriate candidate from a certain set of tessellation models. The choice of candidate represents a trade-off between accuracy and complexity of the model. Here, the selected model is used solely to approximate given data samples, but it also provides guidance for developing stochastic tessellation models and generating virtual microstructures. Model fitting is carried out by simulated annealing, applied in a consistent manner to twelve different tessellation models.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Application and evaluation of a pattern-based building energy model calibration method using public building datasets

Building performance simulation has been adopted to support decision making in the building life cycle. An essential issue is to ensure a building energy simulation model can capture the reality and complexity of buildings and their systems in both the static characteristics and dynamic operations. Building energy model calibration is a technique that takes various types of measured performance data (e.g., energy use) and tunes key model parameters to match the simulated results with the actual measurements. This study performed an application and evaluation of an automated pattern-based calibration method on commercial building models that were generated based on characteristics of real buildings. A public building dataset that includes high-level building attributes (e.g., building type, vintage, total floor area, number of stories, zip code) of 111 buildings in San Francisco, California, USA, was used to generate building models in EnergyPlus. Monthly level energy use calibrations were then conducted by comparing building model results against the actual buildings' monthly electricity and natural gas consumption. The results showed 57 out of 111 buildings were successfully calibrated against actual buildings, while the remaining buildings showed opportunities for future calibration improvements. Enhancements to the pattern-based model calibration method are identified to expand its use for: (1) central heating, ventilation and air conditioning (HVAC) systems with chillers, (2) space heating and hot water heating with electricity sources, (3) mixed-use building types, and (4) partially occupied buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Pentamidine blocks the interaction between mutant S100A5 and RAGE V domain and inhibits the RAGE signaling pathway

The human S100 protein family contains small, dimeric and acidic proteins that contain two EF-hand motifs and bind calcium. When S100A5 binds calcium, its conformation changes and promotes interaction with the target protein. The extracellular domain of RAGE (Receptor of Advanced Glycation End products) contain three domains: C1, C2 and V. The RAGE V domain is the target protein of S100A5 that promotes cell survival, growth and differentiation by activating several signaling pathways. Pentamidine is an apoptotic and antiparasitic drug that is used to treat or prevent pneumonia. Here, we found that pentamidine interacts with S100A5 using HSQC titration. We elucidated the interactions of S100A5 with RAGE V domain and pentamidine using fluorescence and NMR spectroscopy. We generated two binary models—the S100A5-RAGE V domain and S100A5-Pentamidine complex—and then observed that the pentamidine and RAGE V domain share a similar binding region in mS100A5. We also used the WST-1 assay to investigate the bioactivity of S100A5, RAGE V domain and pentamidine. These results indicated that pentamidine blocks the binding between S100A5 and RAGE V domain. This finding is useful for the development of new anti-proliferation drugs. - Highlights: • The interaction between mS100A5–RAGE V was investigated by fluorescence spectroscopy. • The interfacial residues on mS100A5–RAGE V and mS100A5–pentamidine contact surface were mapped by {sup 1}H-{sup 15}N HSQC experiments. • mS100A5–RAGE V and mS100A5–pentamidine complex models were generated from NMR restraints using HADDOCK program. • The bioactivity of the mS100A5–RAGE V and mS100A5–pentamidine complex was studied using WST-1 assay.

60 APPLIED LIFE SCIENCES↗

Formation of environmentally persistent free radicals (EPFRs) on ZnO at room temperature: Implications for the fundamental model of EPFR generation

Environmentally persistent free radicals (EPFRs) have significant environmental and public health impacts. Here, we demonstrate that EPFRs formed on ZnO nanoparticles provide two significant surprises. First, EPR spectroscopy shows that phenoxy radicals form readily on ZnO nanoparticles at room temperature, yielding EPR signals similar to those previously measured after 250°C exposures. Vibrational spectroscopy supports the conclusion that phenoxy-derived species chemisorb to ZnO nanoparticles under both exposure temperatures. Second, DFT calculations indicate that electrons are transferred from ZnO to the adsorbed organic (oxidizing the Zn), the opposite direction proposed by previous descriptions of EPFR formation on metal oxides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

CO 2 plume evolution in a depleted natural gas reservoir: Modeling of conformance uncertainty reduction over time

Uncertainty in the long-term fate of CO 2 injected for geologic carbon sequestration (GCS) is a significant barrier to the adoption of GCS as a greenhouse-gas emission-mitigation for industry and regulatory agencies alike. Here, we present a modeling study that demonstrates that the uncertainty in forecasts of GCS site performance decreases over time as monitoring data are used to update operational models. We consider a case study of GCS in a depleted natural gas reservoir, with CO 2 injection occurring over 20 years, with a 50-year post-injection site care period. We constructed a detailed model to generate the actual model output, which is considered synthetic observation data. A series of simpler operational models based on limited data and assumptions about how an operator would model such a site are then run and compared against actual model output at specific monitoring points after one year, two years, etc. The operational model is updated and improved using the synthetic observation data from the actual model at the same time intervals. Model parameter values and model features needed to be updated over time to improve matches to the actual model. These kinds of model adjustments would be a normal part of reservoir engineering and site management at GCS sites. Uncertainty in two key measures related to site performance decreases with time: extent of the CO 2 plume up-dip migration, and radial extent of the pressure pulse. This conclusion should help allay the concerns of industry and regulators about uncertainty in long-term fate of CO 2 at GCS sites.

54 ENVIRONMENTAL SCIENCES↗

Conditional guided generative diffusion for particle accelerator beam diagnostics

Abstract Advanced accelerator-based light sources such as free electron lasers (FEL) accelerate highly relativistic electron beams to generate incredibly short (10s of femtoseconds) coherent flashes of light for dynamic imaging, whose brightness exceeds that of traditional synchrotron-based light sources by orders of magnitude. FEL operation requires precise control of the shape and energy of the extremely short electron bunches whose characteristics directly translate into the properties of the produced light. Control of short intense beams is difficult due to beam characteristics drifting with time and complex collective effects such as space charge and coherent synchrotron radiation. Detailed diagnostics of beam properties are therefore essential for precise beam control. Such measurements typically rely on a destructive approach based on a combination of a transverse deflecting resonant cavity followed by a dipole magnet in order to measure a beam’s 2D time vs energy longitudinal phase-space distribution. In this paper, we develop a non-invasive virtual diagnostic of an electron beam’s longitudinal phase space at megapixel resolution (1024 × 1024) based on a generative conditional diffusion model. We demonstrate the model’s generative ability on experimental data from the European X-ray FEL.

43 PARTICLE ACCELERATORS↗

Vortex and gap generation in gauge models of graphene

Effective quantum field theoretical continuum models for graphene are investigated. The models include a complex scalar field and a vector gauge field. Different gauge theories are considered and their gap patterns for the scalar, vector, and fermion excitations are investigated. Different gauge groups lead to different relations between the gaps, which can be used to experimentally distinguish the gauge theories. In this class of models the fermionic gap is a dynamic quantity. The finite-energy vortex solutions of the gauge models have the flux of the ''magnetic field'' quantized, making the Bohm-Aharonov effect active even when external electromagnetic fields are absent. The flux comes proportional to the scalar field angular momentum quantum number. The zero modes of the Dirac equation show that the gauge models considered here are compatible with fractionalization.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Applications of flow models to the generation of correlated lattice QCD ensembles

Machine-learned normalizing flows can be used in the context of lattice quantum field theory to generate statistically correlated ensembles of lattice gauge fields at different action parameters. This work demonstrates how these correlations can be exploited for variance reduction in the computation of observables. Three different proof-of-concept applications are demonstrated using a novel residual flow architecture: continuum limits of gauge theories, the mass dependence of QCD observables, and hadronic matrix elements based on the Feynman–Hellmann approach. In all three cases, it is shown that statistical uncertainties are significantly reduced when machine-learned flows are incorporated as compared with the same calculations performed with uncorrelated ensembles or direct reweighting. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗