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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 217 records · Page 12

A note on thermal history kernel for unsteady heat transfer of a spherical particle

When a particle is subjected to an unsteady ambient flow, in terms of either time-dependent relative velocity or time-dependent temperature difference, the net heat transfer from the particle cannot be calculated based on the quasi-steady heat transfer correlation alone. Due to unsteady evolution of the thermal boundary layer, there is also a history contribution to heat transfer. The history contribution to heat transfer is expressed as a convolution integral of past evolution of temperature difference between the particle and the surrounding. While Basset history force and its finite Reynolds number extension have been well studied, similar understanding of unsteady heat transfer and thermal history kernel is lacking. Here, we use existing particle-resolved simulation results to develop a finite Peclet number thermal history kernel, which when used with the convolution integral is demonstrated to accurately predict unsteady heat transfer over a range of Peclet numbers and particle-to-fluid heat capacity ratio.

42 ENGINEERING↗

Imaginary admittance and charge transfer resistance correlate to the physiological status of Shewanella oneidensis cultures in real time

Monitoring microbial activity is essential for industrial and environmental applications to proceed efficiently. To minimize time and labor-intensive monitoring, a new paradigm is required for in-situ, real time analysis. Since bioconversion of organics is accomplished by microorganisms through the oxidation of feedstocks linked to the reduction of electron acceptors, microorganisms can be viewed as electrochemical catalysts. In this respect, cell membranes have an electrical potential, which is analogous to a conventional capacitor and linked dynamically to cellular activity. Here, in this study, we demonstrate the use of electrochemical impedance spectrometry (EIS) and cyclic voltammetry (CV) for monitoring microbial metabolic activity in real time, in-situ. The effect of organic electron donors as a function of concentration to the physiological status of strains of Shewanella oneidensis was determined. In this study, the pyomelanin overproducer (S. oneidensis ΔhmgA) and the pyomelanin deficient mutant (S. oneidensis ΔmelA) were chosen due to different surface electrochemical characteristics along with differences in oxygen utilization efficiency. CV, relative admittance, phase shift and permittivity changed with growth status and correlated with electron flow from organic carbon sources and terminal electron acceptor availability. This work offers a novel and inexpensive approach to real time monitoring with the advantage of abundant data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Axial vs equatorial: Capturing the intramolecular charge transfer state geometry in conformational polymorphic crystals of a donor–bridge–acceptor dyad in nanosecond-time-scale

Two conformational polymorphs of a donor–bridge–acceptor (D-B-A) dyad, p-(CH 3 ) 2 N-C 6 H 4 -(CH 2 ) 2 -(1-pyrenyl)/PyCHDMA, were studied, where the electron donor (D) moiety p-(CH 3 ) 2 N-C 6 H 4 /DMA is connected through a bridging group (B), –CH 2 –CH 2 –, to the electron acceptor (A) moiety pyrene. Though molecular dyads like PyCHDMA have the potential to change solar energy into electrical current through the process of photoinduced intramolecular charge transfer (ICT), the major challenge is the real-time investigation of the photoinduced ICT process in crystals, necessary to design solid-state optoelectronic materials. The time-correlated single photon counting (TCSPC) measurements with the single crystals showed that the ICT state lifetime of the thermodynamic form, PyCHDMA1 (pyrene and DMA: axial), is ~3 ns, whereas, for the kinetic form, PyCHDMA20 (pyrene and DMA: equatorial), it is ~7 ns, while photoexcited with 375 nm radiation. The polymorphic crystals were photo-excited and subsequently probed with a pink Laue x-ray beam in time-resolved x-ray diffraction (TRXRD) measurements. The TRXRD results suggest that in the ICT state, due to electron transfer from the tertiary N-atom in DMA moiety to the bridging group and pyrene moiety, a decreased repulsion between the lone-pair and the bond-pair at N-atom induces planarity in the C–N–(CH 3 ) 2 moiety, in both polymorphs. The Natural Bond Orbital calculations and partial atomic charge analysis by Hirshfeld partitioning also corroborated the same. Although the interfragment charge transfer (IFCT) analysis using the TDDFT results showed that for the charge transfer excitation in both conformers, the electrons were transferred from the DMA moiety to mostly the pyrene moiety, the bridging group has little role to play in that.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Burn parameters affect PAH emissions at conditions relevant for prescribed fires

Wildfire smoke is a health hazard as it contains carcinogenic volatile compounds and fine particulate matter. In particular, exposure to polycyclic aromatic hydrocarbons (PAHs) is a major concern, since these compounds have been recognized as important contributors to the overall carcinogenic risk. In this work, gas and particle-phase PAH emissions from combustion of Eastern White Pine (Pinus strobus) were quantified using time-of-flight mass spectrometry over a range of burn conditions representative of wildfires and prescribed fires, including fuel moisture, heat flux, and oxygen concentration. We found that changing the burn environment lead to a variability of up to 77% in phenanthrene/anthracene emissions. This could explain a large part of the variability in PAH emission factors from biomass combustion reported in the literature. Here, we found that optimal conditions for fuel moisture content of 20–30%, sample heat load of 60 - 70 kW m -2 , and oxygen concentrations of 5–15% can significantly reduce the emissions of heavy molar weight PAHs. Our analysis showed that the relative carcinogenic risk from PAH exposure can be reduced by more than 50% under optimal conditions. In light of the increasing use of prescribed fire for forest management, the relationship between emissions and burn conditions that we have established provides a guidance for assessing the expected health impact from prescription burns, and can inform strategies to reduce PAH emissions from prescribed fire activities.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Extinction Monitoring of Pulsed Proton Beams Using FPGA-Based Peak Detection

The Mu2e experiment at Fermilab imposes stringent requirements on the elimination of out-of-time beam in its pulsed proton beam - a requirement known as "extinction". We present a method to measure the out-of-time particle rates to calculate the level of extinction in the inter-pulse gaps. The proposed method utilizes an array of quartz Cherenkov radiators and photomultiplier tubes to detect particles scattered from a vacuum chamber in the M4 transfer beamline at Fermilab.The measurement will employ a new μTCA-based FPGA system for data acquisition and signal processing, utilizing real-time peak detection algorithms to count scattered beam particles. By integrating data over many transfers, the time profile of the out-of-time beam will be resolved to fractional levels relative to that of the in-time beam. These results are compared with G4beamline simulations to validate models of beam transport, dynamics, and extinction, providing critical input for optimizing beam delivery to Mu2e.

Hensley, Ryan [UC, Davis]↗

Advancing spatiotemporal forecasts of CO 2 plume migration using deep learning networks with transfer learning and interpretation analysis

Accurate and timely forecasts of CO 2 plume distribution throughout the injection and post-injection phases are crucial for detecting plume migration, assessing leakage risks, and supporting operational decisions in geologic carbon storage (GCS). Current convolutional neural network-based approaches primarily focus on spatial information and overlook temporal dependencies in plume distributions, thus limiting their ability to capture dynamic movement effects and provide accurate predictions of plume migration. In this work, we propose two deep learning models, Auto-Encoder (AE)-LSTM and Encoder-Decoder (ED)-ConvLSTM, each uniquely designed to capture both spatial and temporal features. We apply the proposed methods to forecast the dynamic distribution of CO 2 plumes based on 108 reservoir simulations over a 30-year injection and a 30-year post-injection period. The results indicate that the ED-ConvLSTM model outperforms the AE-LSTM model in accurately predicting the spatiotemporal dynamics of CO 2 plume migration, achieving R 2 values above 0.99. To provide a deeper understanding of these model predictions, we employ a gradient-based explanation method on the trained models. This approach provides insights into the influence of input variables on plume migration forecasts and uncovers the underlying prediction mechanisms of the proposed models. Furthermore, we introduce a transfer learning technique, enabling fast and accurate plume migration forecasting in the post-injection phase by leveraging the trained model during the injection phase. This reduces the necessity for extensive data collection or re-training. In conclusion, the methods proposed in our work enhances the performance and interpretability of CO 2 plume migration forecasts, thereby facilitating informed decision-making throughout the entire lifecycle of GCS applications.

58 GEOSCIENCES↗

SR19007 - Future TCAP Implementation Issues

This project demonstrates the success of the PDRD program in bringing a concept from the R&D phase to direct plant funding. Although Mini-TCAP technology is overall at a TRL of ~6.5, the specific questions addressed in this project were brought from a low (2-3 TRL) to a TRL 5 over the course of the project. This project successfully completed all initial goals ahead of schedule (inventory control, guard bed, ammonia impact, and cycle time) and furthermore addressed additional scope (continued TCAP evaluation, ion chamber) in FY20. First, this project resolved minor inventory control issues by introducing a new parameter tracking and correcting for inventory changes over multiple cycles. This project also involved modification of the previously constructed plant-configured Mini-TCAP in order to allow ammonia impurity studies. TCAP was tested with ammonia in the feed stream both with and without a guard bed present to determine guard bed efficacy and the effect of ammonia if it enters TCAP. The TCAP columns were then replaced with brazed columns, where the LN2 cooling coil is brazed to the column and the column is self-brazed along the coils. This drastically improved heat transfer and consequently reduced cycle time compared to the previous columns, in which the coils were mechanically held in place. Finally, additional scopes were taken on in FY20, including evaluation of TCAP with faster cycle time and procurement of ion chambers for future TCAP integration.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Resilient Control of Networked Microgrids Using Vertical Federated Reinforcement Learning: Designs and Real-Time Test-Bed Validations

Improving system-level resiliency of networked microgrids against adversarial cyber-attacks is an important aspect in the current regime of increased inverter-based resources (IBRs). To achieve that, this paper contributes in designing a hierarchical control layer, in conjunction with the existing control layers, resilient to adversarial attack signals. Considering model complexities, unknown dynamical behaviors of IBRs, and privacy issues regarding data sharing in multi-party-owned microgrids, designing such a control layer is non-trivial. Here, to tackle these issues, a novel federated reinforcement learning (Fed-RL) method is proposed. To grasp the interconnected dynamics of networked microgrids, the paper develops Federated Soft Actor-Critic (FedSAC) algorithm following the vertical structure of implementing Fed-RL. Next, utilizing the OpenAI Gym interface, we built a custom set-up in GridLAB-D/HELICS co-simulation platform, named Resilient RL Co-simulation (ResRLCoSIM), to train the RL agents with IEEE 123-bus benchmark comprising 3 interconnected microgrids. Finally, the learned policies in the simulation are transferred to the real-time hardware-in-the-loop (HIL) test-bed developed using the high-fidelity Hypersim platform. Finally, experiments show that the simulator-trained RL controllers achieve desirable performance with the test-bed platform, validating the minimization of the sim-to-real gap.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Frequency-Domain Spectroscopic Study of the Photosystem I Supercomplexes, Isolated IsiA Monomers, and the Intact IsiA Ring

The PSI 3 -IsiA 18 supercomplex is one of the largest and most complicated assemblies in photosynthesis. The IsiA ring, composed of 18 IsiA monomers (IsiA 18 ) surrounding the PSI trimer (PSI 3 ), forms under iron-deficient condition in cyanobacteria and acts as a peripheral antenna. Based on the supercomplex structure recently determined via cryo-EM imaging, we model various optical spectra of the IsiA monomers and IsiA 18 ring. Comparison of the absorption and emission spectra of the isolated IsiA monomers and the full ring reveals that about 2.7 chlorophylls (Chls) are lost in the isolated IsiA monomers. The best fits for isolated monomers spectra are obtained assuming the absence of Chl 508, Chl 517 and 70% loss of Chl 511. The best model describing all three hexamers and the entire ring suggests that the lowest energy pigments are Chls 511, 514 and 517. Based on the modeling results presented in this work we conclude that there are most likely three entry points for EET from the IsiA6 hexamer to the PSI core monomer, with two of these entry points likely being located next to each other (i.e. nine entry points from IsiA 18 to the PSI 3 trimer). Lastly, we show that excitation energy transfer inside individual monomers is fast (< 2 ps at T = 5 K) and at least 20 times faster than inter-monomer energy transfer.

59 BASIC BIOLOGICAL SCIENCES↗

NRC Multiphysics Analysis Capability Deployment (FY2020--Part 3)

This report details progress and activities of Idaho National Laboratory (INL) on the NRC project ”Development and Modeling Support for Advanced Non-Light Water Reactors.” The tasks completed for this report are as follows: First, Task 2c: Explicit modeling of pebble transient temperature response. In this simulation, the PBMR-400 reactor experiences a 20 second power ramp from 100% to 150% power. This is followed by a similar reduction in the power back to 100%. Several multiscale pebble coupling approaches are tested with one pebble per mesh element in the active core region. The results show good conservation behavior and the stability of the coupling. Next, Extended scope part 1: An assessment of the computational efficiency of the DFEM heat transfer solver shows good scalability. The DFEM solver is a factor of 4 more expensive in solution time than the FEM solver for heat transfer problems due to the increased number of degrees of freedom. Nonetheless, the DFEM approach provides the user with the flexibility to model gap heat transfer problems. Then Extended scope part 2: the GapHeatTransferInterfaceMaterial was improved to give the user increased flexibility with the modeling of heat transfer through gaps with the DFEM solver. A number of gap parameters can now be coupled both through functions and variables. Finally, Extended scope part 3: demonstration of how the gap width between hexagonal fuel cells can be calculated during a heat up transient and used in the GapHeat- TransferInterface model. A full domain DFEM model with gap expansion is coupled to a SubApp that models the thermal expansion of the base plate. The results show the expected physical behavior, although have not been fully bench- marked at this point in time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Time-dependent saturation and physics-based nonlinear model of cross-beam energy transfer

The nonlinear physics of cross-beam energy transfer (CBET) for multi-speckled laser beams is examined using large-scale particle-in-cell simulations for a range of laser and plasma conditions relevant to indirect-drive inertial confinement fusion (ICF) experiments. The time-dependent growth and saturation of CBET involve complex, nonlinear ion and electron dynamics, including ion trapping-induced enhancement and detuning, ion acoustic wave (IAW) nonlinearity, oblique forward stimulated Raman scattering (FSRS), and backward stimulated Brillouin scattering (BSBS) in a CBET-amplified seed beam. Ion-trapping-induced detuning of CBET is captured in the kinetic linear response by a new δf-Gaussian-mixture algorithm, enabling an accurate characterization of trapping-induced non-Maxwellian distributions. Ion trapping induces nonlinear processes, such as changes to the IAW dispersion and nonlinearities (e.g., bowing and self-focusing), which, together with pump depletion, FSRS, and BSBS, determine the time-dependent nature and level of CBET gain as the system approaches a steady state. Using VPIC simulations at intensities at and above the onset threshold for ion trapping and the insight from the time-dependent saturation analyses, we construct a nonlinear CBET model from local laser and plasma conditions that predicts the CBET gain and the energy deposition into the plasma. This model is intended to provide a more accurate, physics-based description of CBET saturation over a wide range of conditions encountered in ICF hohlraums compared with linear CBET gain models with ad hoc saturation clamps often used in laser ray-based methods in multi-physics codes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Information transfer with a gravitating bath

Late-time dominance of entanglement islands plays a critical role in addressing the information paradox for black holes in AdS coupled to an asymptotic non-gravitational bath. A natural question is how this observation can be extended to gravitational systems. To gain insight into this question, we explore how this story is modified within the context of Karch-Randall braneworlds when we allow the asymptotic bath to couple to dynamical gravity. We find that because of the inability to separate degrees of freedom by spatial location when defining the radiation region, the entanglement entropy of radiation emitted into the bath is a time-independent constant, consistent with recent work on black hole information in asymptotically flat space. If we instead consider an entanglement entropy between two sectors of a specific division of the Hilbert space, we then find non-trivial time-dependence, with the Page time a monotonically decreasing function of the brane angle---provided both branes are below a particular angle. However, the properties of the entropy depend discontinuously on this angle, which is the first example of such discontinuous behavior for an AdS brane in AdS space.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Tracking C–H activation with orbital resolution

Transition metal reactivity toward carbon–hydrogen (C–H) bonds hinges on the interplay of electron donation and withdrawal at the metal center. Manipulating this reactivity in a controlled way is difficult because the hypothesized metal-alkane charge-transfer interactions are challenging to access experimentally. Using time-resolved x-ray spectroscopy, we track the charge-transfer interactions during C–H activation of octane by a cyclopentadienyl rhodium carbonyl complex. Changes in oxidation state as well as valence-orbital energies and character emerge in the data on a femtosecond to nanosecond timescale. The x-ray spectroscopic signatures reflect how alkane-to-metal donation determines metal-alkane complex stability and how metal-to-alkane back-donation facilitates C–H bond cleavage by oxidative addition. Furthermore, the ability to dissect charge-transfer interactions on an orbital level provides opportunities for manipulating C–H reactivity at transition metals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Systems and methods for determining ground water-surface water interactions

Systems for determining GW/SW interaction are provided. The systems can include: a sensing assembly comprising sensors for pressure, fluid conductivity, temperature, and transfer resistance; processing circuitry operatively coupled to the sensing assembly and configured to receive data from the sensing assembly and process the data to provide a GW/SW interaction, wherein the data includes pressure, fluid conductivity, temperature, transfer resistance data. Methods for determining GW/SW interaction are provided. The methods can include: receiving real time data including pressure, fluid conductivity, temperature, and transfer resistance; from at least some of the data received simulating the SW/GW interaction; and fitting the real time data with the simulated data to provide actual SW/GW interaction.

Johnson, Timothy C.↗

Systems and methods for determining ground water-surface water interactions

Systems for determining GW/SW interaction are provided. The systems can include: a sensing assembly comprising sensors for pressure, fluid conductivity, temperature, and transfer resistance; processing circuitry operatively coupled to the sensing assembly and configured to receive data from the sensing assembly and process the data to provide a GW/SW interaction, wherein the data includes pressure, fluid conductivity, temperature, transfer resistance data. Methods for determining GW/SW interaction are provided. The methods can include: receiving real time data including pressure, fluid conductivity, temperature, and transfer resistance; from at least some of the data received simulating the SW/GW interaction; and fitting the real time data with the simulated data to provide actual SW/GW interaction.

Johnson, Timothy C.↗

FAIRification, Quality Assessment, and Missingness Pattern Discovery for Spatiotemporal Photovoltaic Data

The ongoing growth of the photovoltaic market has pushed the demand for power forecasting and performance evaluation for a huge population of PV power plants. Through access to a large number of time series data sets from different power plants, we have found common issues that impede the modeling process. Namely, the time series data are hard to transfer between groups due to differences in variable nomenclature, and the quality of the data sets can vary. We address the issue of variable nomenclature by FAIRifying spatiotemporal PV time series data. Through the creation of a solar power plant ontology, we propose standards for the naming and structure of metadata used to describe the data from these power plants. Using the structure from this ontology, we have developed both R and Python packages for the automation of the FAIRification process. We have also developed an R package that automates the analysis of the quality of a data set through the designation of letter grades. With access to large time series data sets across many power plants, we can utilize spatiotemporal coherence between the sites in order to improve the quality of our data. To solve the issue of data missingness, we propose the use of Spatiotemporal-GNN autoencoders to detect and impute missing values from a data set by utilizing data from power plants nearby.

14 SOLAR ENERGY↗