ESGF-Assistant: A Domain-Specific Large Language Model for Navigating Earth System Data
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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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High-frequency (HF) transformers are an essential part of many power electronic devices. The performance and behavior of HF transformers can greatly affect the efficiency and performance of all systems, particularly, from a parasitic parameter point of view. In this article, HF transformers' parasitic parameters, such as leakage inductances and parasitic capacitances, are analyzed using a novel analytical method, finite element method (FEM), and experimental measurements of different structures and winding arrangements. Also, the magnetic field, electric field, electric displacement field, and electric potential distribution within the transformers are simulated and analyzed. Four different HF transformers with E and U cores with different windings are designed and analyzed. Investigation outcomes help to classify structures according to the trade-off between leakage inductances and series parasitic capacitances. This information can later be used for the optimal selection and design of transformers as a function of their operating frequency for any power rating and voltage level. Moreover, 3-D FEM and experimental results validate the proposed methodology to be used for designing HF transformers in high-voltage/power applications.
This article presents the results of a research that is part of a larger collaborative effort between the Lawrence Berkeley National Laboratory and the Pacific Earthquake Engineering Research Center, funded by the US Department of Energy Office of Cybersecurity, Energy Security and Emergency Response. The main objective of this study is to assess a suite of near and far-field simulated ground motions obtained from 20 realizations of an M7 Hayward Fault earthquake in the San Francisco Bay Area, California USA, and inform the selection of rupture simulation parameters leading to strong motions. To this aim, comparisons are conducted with NGA-W2 and directivity ground-motion models and a selected population of records. An archetypal steel moment-resisting frame is utilized to assess infrastructure response distributions. The analyses carried out for each simulated event and subdomain with consistent properties in terms of shallow shear-wave velocity proved to be instrumental for better interpreting the differences between simulated motions and empirical models. The main reasons identified for variances between simulations and empirical relationships included (1) directivity effects fully captured by the simulations across the full breadth of rupture models; (2) site vicinity to ruptures that incorporate large-slip patches, particularly if these are in the forward-directivity direction; and (3) presence of geologic structures that can “trap” seismic waves and produce ground motions with large amplitude and long signal duration. The analyses carried out in this work provide a path for interpreting ground-motion site and event specificity obtained from a suite of physics-based simulations, differing only in the rupture model characterization, to inform the selection of simulation scenarios for site-specific engineering analyses under strong excitations. Evidence from this work points to the possibility that current hazard models may underestimate ground-motion intensities in areas where the combined effect of directivity and site conditions results in large ground-motion amplitudes.
One of the health risks posed to astronauts during deep space flights is exposure to high charge, high-energy (HZE) ions (Z > 13), which can lead to the induction of hepatocellular carcinoma (HCC). However, little is known on the molecular mechanisms of HZE irradiation-induced HCC. We performed comparative RNA-Seq transcriptomic analyses to assess the carcinogenic effects of 600 MeV/n 56 Fe (0.2 Gy), 1 GeV/n 16 O (0.2 Gy), and 350 MeV/n 28 Si (0.2 Gy) ions in a mouse model for irradiation-induced HCC. C3H/HeNCrl mice were subjected to total body irradiation to simulate space environment HZE-irradiation, and liver tissues were extracted at five different time points post-irradiation to investigate the time-dependent carcinogenic response at the transcriptomic level. Our data demonstrated a clear difference in the biological effects of these HZE ions, particularly immunological, such as Acute Phase Response Signaling, B Cell Receptor Signaling, IL-8 Signaling, and ROS Production in Macrophages. Also seen in this study were novel unannotated transcripts that were significantly affected by HZE. To investigate the biological functions of these novel transcripts, we used a machine learning technique known as self-organizing maps (SOMs) to characterize the transcriptome expression profiles of 60 samples (45 HZE-irradiated, 15 non-irradiated control) from liver tissues. A handful of localized modules in the maps emerged as groups of co-regulated and co-expressed transcripts. The functional context of these modules was discovered using overrepresentation analysis. We found that these spots typically contained enriched populations of transcripts related to specific immunological molecular processes (e.g., Acute Phase Response Signaling, B Cell Receptor Signaling, IL-3 Signaling), and RNA Transcription/Expression. A large number of transcripts were found differentially expressed post-HZE irradiation. These results provide valuable information for uncovering the differences in molecular mechanisms underlying HZE specific induced HCC carcinogenesis. Additionally, a handful of novel differentially expressed unannotated transcripts were discovered for each HZE ion. Taken together, these findings may provide a better understanding of biological mechanisms underlying risks for HCC after HZE irradiation and may also have important implications for the discovery of potential countermeasures against and identification of biomarkers for HZE-induced HCC.
Photothermal CO 2 hydrogenation is a promising route to produce methanol as a sustainable liquid solar fuel. However, most existing catalysts require a combination of solar irradiation and additional heat input to achieve a satisfactory reaction rate. For the few that can be driven solely by light, their reaction rates are one order of magnitude lower. We develop a photothermal catalyst with multilevel interfaces that achieves improved methanol production from photothermal CO 2 hydrogenation without external heat. The catalyst features a layered structure comprising Cu/ZnO/Al 2 O 3 (CZA) covered by oxidized carbon black (oCB), where the oCB/CZA interface promotes efficient heat generation and transfer, and the Cu/oxide interface contributes to high catalytic activity. Under a mild pressure of 8 bar, our oCB/CZA catalyst shows a methanol selectivity of 64.7% with a superior production rate of 4.91 mmol·g cza −1 ·h −1 , at least one order of magnitude higher than other photothermal catalysts solely driven by light. This work demonstrates a photothermal catalyst design strategy for liquid solar fuel production.
Projection of the contribution of ice sheets to sea level change as part of the Coupled Model Intercomparison Project Phase 6 (CMIP6) takes the form of simulations from coupled ice sheet–climate models and stand-alone ice sheet models, overseen by the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6). This paper describes the experimental setup for process-based sea level change projections to be performed with stand-alone Greenland and Antarctic ice sheet models in the context of ISMIP6. The ISMIP6 protocol relies on a suite of polar atmospheric and oceanic CMIP-based forcing for ice sheet models, in order to explore the uncertainty in projected sea level change due to future emissions scenarios, CMIP models, ice sheet models, and parameterizations for ice–ocean interactions. We describe here the approach taken for defining the suite of ISMIP6 stand-alone ice sheet simulations, document the experimental framework and implementation, and present an overview of the ISMIP6 forcing to be used by participating ice sheet modeling groups.
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During space travel approximately 50 of the crew experience symptoms of motion sickness that can range from mild forms of nausea or dizziness to severe malaise and vomiting1. Developing an effective treatment for these symptoms has become a priority of the National Aeronautics and Space Administration (NASA). Autogenic-Feedback Training Exercise (AFTE) is a nonpharmacological countermeasure for mitigating motion sickness. It involves training subjects to control physiological responses in high stress environments2. The primary goal of this experiment is to evaluate the effectiveness of AFTE for increasing tolerance to motion sickness in high stress environments.
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The land ice contribution to global mean sea level rise has not yet been predicted1 using ice sheet and glacier models for the latest set of socio-economic scenarios, nor using coordinated exploration of uncertainties arising from the various computer models involved. Two recent international projects generated a large suite of projections using multiple models2,3,4,5,6,7,8, but primarily used previous-generation scenarios9 and climate models10, and could not fully explore known uncertainties. Here we estimate probability distributions for these projections under the new scenarios11,12 using statistical emulation of the ice sheet and glacier models. We find that limiting global warming to 1.5 degrees Celsius would halve the land ice contribution to twenty-first-century sea level rise, relative to current emissions pledges. The median decreases from 25 to 13 centimetres sea level equivalent (SLE) by 2100, with glaciers responsible for half the sea level contribution. The projected Antarctic contribution does not show a clear response to the emissions scenario, owing to uncertainties in the competing processes of increasing ice loss and snowfall accumulation in a warming climate. However, under risk-averse (pessimistic) assumptions, Antarctic ice loss could be five times higher, increasing the median land ice contribution to 42 centimetres SLE under current policies and pledges, with the 95th percentile projection exceeding half a metre even under 1.5 degrees Celsius warming. This would severely limit the possibility of mitigating future coastal flooding. Given this large range (between 13 centimetres SLE using the main projections under 1.5 degrees Celsius warming and 42 centimetres SLE using risk-averse projections under current pledges), adaptation planning for twenty-first-century sea level rise must account for a factor-of-three uncertainty in the land ice contribution until climate policies and the Antarctic response are further constrained.
Projections of the sea level contribution from the Greenland and Antarctic ice sheets (GrIS and AIS) rely on atmospheric and oceanic drivers obtained from climate models. The Earth System Models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6) generally project greater future warming compared with the previous Coupled Model Intercomparison Project phase 5 (CMIP5) effort. Here we use four CMIP6 models and a selection of CMIP5 models to force multiple ice sheet models as part of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6). We find that the projected sea level contribution at 2100 from the ice sheet model ensemble under the CMIP6 scenarios falls within the CMIP5 range for the Antarctic ice sheet but is significantly increased for Greenland. Warmer atmosphere in CMIP6 models results in higher Greenland mass loss due to surface melt. For Antarctica, CMIP6 forcing is similar to CMIP5 and mass gain from increased snowfall counteracts increased loss due to ocean warming.
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Numerical, process-based simulations of tidewater glacier evolution are necessary to project future sea-level change under various climate scenarios. Previous work has shown that nonlinearities in tidewater glacier and ice stream dynamics can lead to biases in simulated ice mass change in the presence of noisy forcings. Ice sheet modeling projections that are used in the IPCC Assessment Report 6 (AR6) utilize atmospheric and oceanic forcings at annual temporal resolution, omitting any higher frequency forcings. Here, we quantify the effect of seasonal (<1 year) tidewater glacier terminus oscillations on decadal-scale (30 years) mass change. We use an idealized geometry to mimic realistic tidewater glacier geometries and investigate the impact of the magnitude of seasonal oscillations, bed slope at the glacier terminus, and basal friction law. We find that omitting seasonal terminus motion results in biased mass change projections, with up to an 39% underestimate or 25% overestimate of mass loss when seasonality is neglected, depending on bed slope and magnitude of oscillations. The bias is most sensitive to the magnitude of the seasonal terminus oscillations and exhibits very little sensitivity to choice of friction law. Although omitting seasonal terminus motion may bias mass change projections of individual glaciers, further work is needed to investigate the impact on ice sheet mass change projections. In order to achieve this, seasonality in atmospheric and oceanic forcings must be adequately represented and observations of seasonal terminus positions and tidewater glacier thickness changes must be acquired to evaluate numerical models. Note: Zip folder contains all videos listed in the supplemental document and can be downloaded for viewing.
Mass loss from the Greenland Ice Sheet can be partitioned between surface mass balance and discharge due to ice dynamics through its marine-terminating outlet glaciers. A perturbation to a glacier terminus (e.g., a calving event) results in both an instantaneous response in velocity and mass loss and a diffusive response due to the evolution of ice thickness over time. This diffusive response means the total impact of a retreat event can take decades to be fully realized. Here we model the committed response of the Greenland Ice Sheet by applying perturbations to the marine-terminating glacier termini that represent recent observed changes, and simulating the response over the 21st century, while holding the climate forcing constant. The sensitivity of the ice sheet response to model parameter uncertainty is explored within an ensemble framework, and Gravity Recovery and Climate Experiment data is used to constrain the results using a Bayesian calibration approach. We find that the Greenland Ice Sheet's committed contribution to 21st century sea level rise is at least 33.5 [17.5 52.4] mm (25th and 75th percentiles in brackets), with at least 6 mm being attributable directly to terminus retreat that occurred between 2007 and 2015. The spread in our projections is driven by uncertainty in the basal friction coefficient. Our results complement the ISMIP6 Greenland projections, which report the ice sheet response to future forcing, excluding the background response. In this way, we can obtain estimates of Greenland's total contribution to sea level rise in 2100.
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This research focuses on electromagnetic interference (EMI) / electromagnetic compatibility (EMC) design and analysis in power electronics systems. To limit the EMI under the standards, different methods and strategies are investigated. Parasitic parameters of high frequency (HF) transformer are analyzed using a novel analytical method, finite element method (FEM), and experimental measurements for different structures and windings arrangements. Also, the magnetic field, electric field, electric displacement, and electric potential distribution are simulated and analyzed. Moreover, a high voltage system is considered and analyzed to improve the EMC. The EMI propagation paths are analyzed. The EMI noise level of the system is obtained and compared to the IEC61800-3 standard. To improve the EMC, the parasitic parameters of the transformer, as the main path of EMI circulation, are analyzed and optimized to block the propagation. Furthermore, the geometry structure of the HF transformer is optimized to lower the parasitics in the system. Three pareto-optimal techniques are investigated for the optimization. The models and results are verified by 3D-FEM and experimental results for several given scenarios. Furthermore, the EMC modeling and conducted EMI analysis are developed for a system including an AC-DC-DC power supply (rectifier and dual active bridge (DAB) converter). Moreover, the common mode (CM) EMI noise propagation through the system is discussed and the noise sources and effect of components on the noise are analyzed. Additionally, the CM impedance of different parts of the system and the noise levels are discussed. Finally, EMI attenuation techniques were applied to the system.