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At least 919 records · Page 51

Limits on the Abundance and Burial Depth of Lunar Polar Ice

The Diviner imaging radiometer experiment aboard the Lunar Reconnaissance Orbiter has revealed that surface temperatures in parts of the lunar polar regions are among the lowest in the solar system. Moreover, modeling of these Diviner data using realistic thermal conductivity profiles for lunar regolith and topography-based illumination has been done, with surprising results. Large expanses of circum-polar terrain appear to have near-subsurface temperatures well below 110K, despite receiving episodic low-angle solar illumination [Paige et al., 2010]. These subsurface cold traps could provide areally extensive reservoirs of volatiles. Here we examine the limits to abundance and burial depth of putative volatiles, based on the signature they would create for orbital thermal and epithermal neutrons. Epithermals alone are not sufficient to break the abundance-depth ambiguity, while thermal neutrons provide an independent constraint on the problem. The subsurface cold traps are so large that even modest abundances, well below that inferred from LCROSS observations, would produce readily detectable signatures in the Lunar Prospector neutron spectrometer data [Colaprete et al., 2010]. Specifically, we forward-model the thermal and epithermal neutron leakage flux that would be observed for various ice concentrations, given the depth at which ice stability begins. The LCROSS results point to a water-equivalent hydrogen abundance (WEH) in excess of 10 wt%, when all hydrogenous species are added together (except for H2, detected by LAMP on LRO [Gladstone et al., 2010]). When such an ice abundance is placed in a layer below the stability depth of Paige et al., the epithermal and thermal neutron leakage fluxes are vastly reduced and very much at odds with orbital observations. So clearly an environment that is conducive to cold trapping is necessary but not sufficient for the presence of volatiles such as water. We present the limits on the abundances that are indeed consistent with orbital data. At the LCROSS impact site itself, the data are consistent with very high ice abundances at 50-100 cm depth. However, radar results rule out these high abundances.

Elphic, Richard C.↗

Understanding Olivine and Pyroxene in Chondritic IDPs

There is a widespread depletion of Cr from the FeO-rich olivine in Wild-2, relative to type IIA chondrules(Frank et al., 2014)-the degree of this depletion is akin to that in unequilibrated chondrites such as Krymka (LL3.2) or Rainbow (CO3.2).Since Cr is highly mobile under even mild thermal metamorphism(as low as 200ºC), it is a sensitive indicator of such an event, showing greater depletion in smaller grains (i.e., matrix vs. chondrules) (Grossman and Brearley, 2005). Grossman and Brearley (2005) found that the distribution of Cr in FeO-rich olivine systematically changes as metamorphism increases between type 3.0 and type 3.2. Thus, Wild-2 olivine appears to carry evidence of mild thermal metamorphism. It is critical to determine whether there is any evidence for this from samples of other comets. For this we can examine an hydrous chondritic IDPs. Unfortunately, the data for olivine and pyroxene in IDPs is sparse, mainly decades old and lacks useful information on minor elements. We have begun to collect new compositional data for olivine and pyroxene in chondritic interplanetary dust particles (filling a major gap in our knowledge, as approximately half of these grains derive from comets), to determine whether the results obtained for Wild-2 are typical for comets in general, or whether Wild-2 (or its accretion components) has experienced an atypical geological history. A determination that a comet, or its accretion components, had experienced significant thermal metamorphism would greatly alter models of early solar system history.

Michael Zolensky↗

Valuing the Future Electric Grid: A Bid-Based Approach

Energy storage resources (ESRs) and other zero marginal cost (ZMC) resources have unique characteristics that are not fully captured in today’s electricity planning and operations modeling tools. Because the modeling assumptions used in these tools are simplified approximations of how operations and investment decisions occur in the real-world, accurately representing cost and operational characteristics are key for determining how these resources impact price formation. Questions such as—Where should we build new transmission? Will a small modular reactor earn enough revenue to participate in the future electric grid? Is retrofitting a coal plant with carbon capture technology economically feasible?—all require accurate electricity prices, which aren’t available from today’s electricity planning and operations modeling tools. As an example, production cost models (PCMs) are heavily utilized tools that determine the cost and reliability of the electric system. However, as PCMs were developed to help thermal generators manage their fuel inventories, production cost modeling is largely based on fuel prices. Because ESRs do not incur fuel costs, they are often modeled as ZMC resources. In reality, ESRs incur opportunity costs as well as technology-specific (degradation) costs that are non-trivial to calculate but are important for price formation. In this research, we identify options to incorporate more realistic opportunity and degradation costs in ESR bidding algorithms. Expanding available bidding assumptions allows energy system modelers to develop more accurate economic valuations for ESRs, leading to more accurate price formation from leading energy system modeling tools.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Environmentally Assisted Fatigue in Light Water Reactor Environment

This report summarizes the Environmentally Assisted Fatigue (EAF) research conducted at ANL under the US DOE Light Water Reactor Sustainability (LWRS) program. Starting from a rich background in theoretical and experimental EAF, ANL previously developed an approach to evaluate fatigue performance of reactor materials in light water reactor environments with the correction factor F en . The approach was based on a large body of experimental work performed at ANL and elsewhere, and was consistent with American Society of Mechanical Engineers (ASME)’s methodology governing the design and construction of reactor components. In recent years, the program was focused on component fatigue prediction and made several major and fundamental contributions in this area. These accomplishments help meet the needs identified by the industry concerning component level fatigue predictions in complex, transient conditions. The main contribution of the ANL program involved the development of a system-level model for estimating residual strain and life of nuclear reactor coolant system components under connected-system-thermal-mechanical boundary conditions. The goal was to predict the stress hotspots, strain residuals, strain amplitudes and the resulting fatigue lives. Thermal-mechanical stress analysis was performed considering thermal stratification and a design-basis reactor loading cycle. Based on the finite element (FE) model results, the strain residuals, strain amplitudes and resulting fatigue lives of reactor coolant system (RCS) components were predicted. The results show that some of the RCS components can have significantly different strain amplitudes, residual strain, and fatigue lives, despite having similar geometry and material. In addition, the simulated component-level strain profile can guide the selection of appropriate test inputs for conducting laboratory-scale EAF tests. Building upon the system-level model, ANL developed a digital twin (DT) framework to predict the structural states and associated fatigue life of components in real-time. This framework is a comprehensive system designed to predict the structural states and fatigue lives of reactor components. It includes multiple models and integrates artificial intelligence (AI), machine learning (ML), and FE based modeling tools to evaluate the structural states and fatigue lives.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Phase Change Processes for Thermal Management Systems and Science Investigations

This white paper focuses on the scientific rationale and motivation for deploying phase change processes-based spacecraft thermal management systems for space missions [1,2]. Phase change processes need to be implemented in the design of various life support systems, sub-critical cryogenic and thermal control systems, taking advantage of the latent heat of phase change so as to significantly increase the heat transfer rate per unit fluid mass. Experimental data are critical to understanding gravitational effects on complex phase change processes using novel materials and working fluids. Experimental data can be acquired by either designing new testing platforms or performing experiments with simulant fluids on existing microgravity platforms. With the acquired data, theoretical flow physics models and numerical simulations can then be validated for use under long-duration microgravity conditions. The acquired data and validated models will enable the deployment of game-changing thermal management systems with remarkably improved efficiency and stability in heat acquisition, transport, and rejection for long-duration space missions.

Fluid mechanics↗

Development of an emulation-simulation thermal control model for space station application

Many features were added to the Thermal Control System (TCS) program to increase its user-friendliness. Several apparent inconsistencies were identified. In some instances, these have led to modifications to the source programs. With the summary line-sizing information, the user can more readily compare the TCS program results with other available data. Two mathematical models were completed: one deals with sizing and analysis of bus heat exchangers and the other provides a means of analyzing a variety of heat pipe radiator designs. A generic heat pipe model was added to the TCS Analysis Program.

Colwell, Gene T.↗

Validation of Universal Cryogenic Flow Boiling Correlations in Thermal Desktop for Liquid Hydrogen

Developing accurate models of two-phase cryogenic flow will reduce risk and reduce margins for future NASA vehicles such as the Nuclear Thermal Propulsion (NTP) system. Currently there is a need for more accurate, direct cryogenic data-anchored models for various boiling and two-phase phenomena. The focus of the current work is on modeling steady state cryogenic flow boiling in the transfer line that connects a propellant storage tank to an engine or customer receiver tank. This paper presents Thermal Desktop model validation results against several historical liquid hydrogen (LH2) heated tube experiments that cover a wide range of inlet conditions, mass flux, and heat flux. New universal cryogenic flow boiling correlations were recently developed and anchored to the largest cryogenic flow boiling database assembled in the world to-date. The new universal correlations are patched together and implemented into Thermal Desktop to compare model performance against the built-in flow boiling correlations. Axial wall temperature predictions as a function of preponderant parameters like heat flux, mass flux, inlet pressure, inlet quality, tube diameter, etc. using the two sets of flow boiling correlations are compared against the experimental data. Overall, the Thermal Desktop model with the new universal cryogenic flow boiling correlations demonstrates an improvement in predictive performance over the Thermal Desktop model using built-in correlations for both wall temperature and location of critical heat flux compared to the data for LH2 flow boiling in heated tubes.

Cryogenic Propellant Transfer↗

Validation of Universal Cryogenic Flow Boiling Correlations in Thermal Desktop for Liquid Hydrogen

Developing accurate models of two-phase cryogenic flow will reduce risk and reduce margins for future NASA vehicles such as the Nuclear Thermal Propulsion (NTP) system. Currently there is a need for more accurate, direct cryogenic data-anchored models for various boiling and two-phase phenomena. The focus of the current work is on modeling steady state cryogenic flow boiling in the transfer line that connects a propellant storage tank to an engine or customer receiver tank. This paper presents Thermal Desktop model validation results against several historical liquid hydrogen (LH2) heated tube experiments that cover a wide range of inlet conditions, mass flux, and heat flux. New universal cryogenic flow boiling correlations were recently developed and anchored to the largest cryogenic flow boiling database assembled in the world to-date. The new universal correlations are patched together and implemented into Thermal Desktop to compare model performance against the built-in flow boiling correlations. Axial wall temperature predictions as a function of preponderant parameters like heat flux, mass flux, inlet pressure, inlet quality, tube diameter, etc. using the two sets of flow boiling correlations are compared against the experimental data. Overall, the Thermal Desktop model with the new universal cryogenic flow boiling correlations demonstrates an improvement in predictive performance over the Thermal Desktop model using built-in correlations for both wall temperature and location of critical heat flux compared to the data for LH2 flow boiling in heated tubes.

cryogenic propellant transfer↗

Robust finite-temperature many-body scarring on a quantum computer

Mechanisms for suppressing thermalization in disorder-free many-body systems, such as Hilbert space fragmentation and quantum many-body scars, have recently attracted much interest in foundations of quantum statistical physics and potential quantum information processing applications. However, their sensitivity to realistic effects such as finite temperature remains largely unexplored. Here, we have utilized IBM's Kolkata quantum processor to demonstrate an unexpected robustness of quantum many-body scars at finite temperatures when the system is prepared in a thermal Gibbs ensemble. We identify such robustness in the PXP model, which describes quantum many-body scars in experimental systems of Rydberg atom arrays and ultracold atoms in tilted Bose-Hubbard optical lattices. By contrast, other theoretical models which host exact quantum many-body scars are found to lack such robustness and their scarring properties quickly decay with temperature. Our study sheds light on the important differences between scarred models in terms of their algebraic structures, which impacts their resilience to finite temperature. Published by the American Physical Society 2024

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Disorder to Order in Interface Patterns: Thermal Noise to Limit Cycle Transition in Dendrite Sidebranch Formation

Thin sample directional solidification experiments have been carried out in the model succinonitrile-camphor system to examine the origin of secondary branches in dendrite morphologies. Thermal noise at the dendrite tip creates interface instabilities which amplify to form sidebranches. This is accepted as the primary mode of sidebranching in dendritic growth from an undercooled melt and occurs in directional solidification of dendrites. The proposed limit cycle couples the growth of the tip with the initiation of the sidebranch. Directional solidification of curved interfaces is a driven dissipative system with the potential to form a limit cycle. Two sets of experiments were performed, the first holding velocity constant and evolving the gradient and the second imposing oscillating velocities around the natural period of sidebranching. Both experimental methods were found to characterize a transition from disordered sidebranching induced by thermal noise to ordered sidebranching produced by the limit cycle mechanisms. This is the first quantitative measurement of previously hypothesized limit cycle growth. These experiment sets have been quantitatively analyzed for dynamic behavior seen in limit cycles. High-quality data sets of the tip and instability enable the measurement of the FFT and analysis through a power spectrum. At low gradients, the sidebranches are found to be excited by thermal noise far away from the tip. As the gradient increases and velocity is held constant, the distance between the instability and tip decreases until limit cycle growth is found between the tip of the primary dendrite and the first forming sidebranch. An alternative to the deterministic limit cycles seen in experiments of gradient evolution is a limit cycle actively driven through the square wave oscillation of velocity. Crucial observations of the solidified microstructure conclude that this produced periodic interconnected bridges between the primary dendrites. This is a finding with potentially significant implications for commercial applications.

Trevor Lyons↗

On the relationship between tectonic plates and thermal mantle plume morphology

Models incorporating plate-like behavior, i.e., near uniform surface velocity and deformation concentrated at plate boundaries, into a convective system, heated by a mix of internal and basal heating and allowing for temperature dependent viscosity, were constructed and compared to similar models not possessing plate-like behavior. The simplified numerical models are used to explore how plate-like behavior in a convective system can effect the lower boundary layer from which thermal plumes form. A principal conclusion is that plate-like behavior can significantly increase the temperature drop across the lower thermal boundary layer. This temperature drop affects the morphology of plumes by determining the viscosity drop across the boundary layer. Model results suggest that plumes on planets possessing plate-like behavior, e.g., the Earth, may differ in morphologic type from plumes on planets not possessing plate-like behavior, e.g., Venus and Mars.

Lenardic, A.↗

Modeling and Automation Framework for High IBR Integration in Large-Scale Power Systems

The increasing prevalence of power electronics- interfaced renewable generation sources is leading to a gradual replacement of traditional thermal generation-based synchronous machines. In this context, the modeling of a large-scale power grid that incorporates a significant number of inverter-based resources is crucial for understanding the dynamics and effects of these resources on the power system. This study investigates the positive sequence model of grid-following and grid-forming inverters. Additionally, this work explores the integration of distributed energy resources using population as an indicator of their relative geographic locations. To address challenge to integrate these inverter based resources into a realistic grid of the US Western interconnection, automation scripts are developed to streamline the process of replacing conventional generators with grid-following and grid-forming inverters, as well as allocating distributed energy resources. Different penetration levels of these inverters are considered, and their frequency regulation support following a disturbance is compared through dynamic simulations.

Lyu, Xue↗

Thermal and Deposition Modeling of the Canister Deposition Field Demonstration

This report provides initial thermal and deposition modeling results of the spent nuclear fuel (SNF) storage system planned for use in the Canister Deposition Field Demonstration (CDFD). The goal of the CDFD testing is to collect deposition measurements on the surface of the dry shielded canister (DSC) to aid in chloride-induced stress corrosion crack (CISCC) research. Ideally this testing will occur in a marine coastal environment but at the time of this report no official site has been selected. The CDFD will use the NUHOMS ® Advanced Horizontal Storage Module – High Seismic (AHSM-HS) with a 32PTH2 canister. The SNF assemblies will be replaced with electrical heaters. Canisters are currently being outfitted with these heaters and tested at Sandia National Laboratory (SNL). Thermal modeling was conducted to ensure the electrical heaters were representative of the temperature distribution found within a storage system with SNF. Deposition models were built to evaluate contaminant deposition on SNF canisters. The CDFD testing will help to validate these models, which will then be used to plan and inform on-site test programs and predictive models for the timing and occurrence of canister CISCC.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Modeling of Thermal Decomposition of TATB-Based Explosive for Safety Analysis

We investigate and model the cook-off behavior of LX-17 to understand the response of explosive systems in abnormal thermal environments. Decomposition has been explored via conventional ODTX (One-Dimensional Time-to-eXplosion), PODTX (ODTX with pressure-measurement), TGA (Thermo-Gravimetric Analysis), and DSC (Differential Scanning Calorimetry) experiments under isothermal and ramped temperature profiles. The data were used to fit reaction rate parameters for proposed schemes in an ALE3D computational model. This model includes chemical reactions, thermo- and hydro-dynamics, and material properties, including thermal expansion, compressibility, and strength. These parameterizations were carried out utilizing a Python evolutionary optimization method on LLNL’s high-performance computing clusters. Additional experiments are being developed to further characterize and monitor decomposition intermediates to improve the model. Once experimentally validated, this model will be scalable to several applications involving LX-17. Furthermore, the optimization methodology developed herein should be applicable to other high explosive materials.

Chemistry - Chemical explosives↗

Roadmap for thermal property measurements of Molten Salt Reactor systems

Thermal properties of molten salts, both with and without fissile and fertile material, are fundamental to modeling and simulation that supports design, construction, operation, and accident progression evaluation of molten salt reactors. This roadmap provides guidance to the research community on the types and amounts of required data for base, or carrier, salt systems, recommends simulated burnup fuel salt compositions to evaluate, and provides a technical foundation for a focused salt property evaluation matrix. The property values generated from both computation and experimental methods are used to develop models that constitute the Molten Salt Thermal Properties Database (MSTDB). While the building blocks of MSTDB are fundamental in nature, its data facilitates constructing engineering models that allow stakeholders to investigate the behavior of specific compositions of interest and supports broader modeling and simulation of MSRs through coupling to multi-physics, multi-scale mass accountancy tools.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Parallelized Carbon Oxidation and Surface Recession Model in Direct-Simulation Monte Carlo Code, SPARTA

Ablative thermal protection system (TPS) materials for spacecraft are composites that often consist of a carbon-based reinforcement and a polymeric matrix. During Earth re-entry, they endure high-temperature oxidation and surface recession. Oxidation is an important mechanism for ablation, sometimes leading to the weakening, spallation, or failure of the oxidized fibers at the surface and in the char layer. However, more details are required including accurate material properties of the fiber microstructure, whether the fibers recede homogenously or localized at pits, and the role of pyrolysis outgassing in order to evaluate the role oxidation plays in the degradation and failure mechanisms of these materials. In this work, we demonstrate a parallelizable oxidation-driven ablation model developed for detailed, large-scale simulations in the DSMC code SPARTA. We also develop robust algorithms which handle the conservation of the surface state after an ablation step. Finally, we verify our model for both simple and more complex chemistry as well as microstructures with reaction statistics, oxidation depth calculations, and detailed visualization of oxidation-induced material recession at the microscale.

V Arias↗

Capsule network-based semantic segmentation model for thermal anomaly identification on building envelopes

Thermography technology is widely used to inspect thermal anomalies in building façade systems. Computer vision-based techniques provide opportunities to autonomously detect such heat anomalies to significantly improve the efficiency of decision-making for building envelope retrofitting and maintenance. Here, in this work, we propose a novel Capsule Network-based deep learning model – CapsLab – that detects and identifies thermal anomalies by semantic segmentation. CapsLab is built based on our proposed prediction-tuning capsule (PT-Capsule) layer. Different from a traditional capsule layer, which consists of part-whole transformation and capsule-routing process, the proposed layer is composed of a prediction and tuning process, which helps decreasing the number of model parameters significantly. While the applicability of traditional Capsule Networks (CapsNets) has been limited to simpler tasks and smaller datasets due to their scalability issue, we can leverage the lightweight of the proposed PT-Capsule layer, and apply it to the semantic segmentation task. In this work, we also employ our previously presented performance metric, referred to as the Anomaly Identification Metric (AIM) (Kakillioglua et al. 2021), to evaluate the segmentation outputs. Traditional performance metrics do not accurately reflect the true performance of the segmentation models in thermal anomaly identification due to the high subjectivity in the annotation process and higher overlap ratio sensitivity of the standard metrics. AIM, on the other hand, is robust to these drawbacks. Experimental results show, both qualitatively and quantitatively, that our proposed segmentation method can effectively segment the thermal anomalies. Specifically, our model provides 9.38% and 13.53% improvements over the baseline model – DeepLabV3+ – based on traditional mIoU score and the AIM score, respectively, while requiring less model parameters and less computation at the same time. In addition, the scores that the AIM metric generates better align with the scores provided by building performance experts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗