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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A phenology- and trend-based approach for accurate mapping of sea-level driven coastal forest retreat

The rapid replacement of upland forest by encroaching marshland is a striking manifestation of global sea-level rise (SLR). Timely and high-resolution information on the location and extent of transition forest (the ecotone between upland forest and marsh where tree mortality due to seawater intrusion begins) is fundamental to understanding the processes and patterns of SLR-driven landscape reorganization. Despite its significance, accurate characterization of salt-impacted transition forest remains challenging due to the complexity of coastal environments, scarcity of ground-truth data, and the lack of effective mapping algorithms. Here we use the full archive of Landsat images between 1984 and 2021 to investigate the spectral, temporal, and phenological characteristics of transition forest, and develop a robust framework for monitoring coastal vegetation shifts in the mid-Atlantic U.S., a global SLR hotspot. Here, we found that transition forest exhibits strong negative NDVI trends and a deviation of land surface phenology from marsh and upland forest that distinguishes itself from surrounding vegetation. By integrating temporal trends and land surface phenology, our results demonstrate superior discrimination between marsh and coastal forests to existing map products (e.g. NOAA Coastal Change Analysis Program, National Land Cover Database) that allows a reliable identification of the coastal treeline. We applied the approach to map regional land cover in 1985, 2000 and 2020 (overall classification accuracy >92%) and found that the area of coastal forest decreased by 22.0% from 1985 to 2020, the majority of which transitioned to marshland (92.3%, 5.3 × 10 3 ha). Based upon fine-scale patterns of coastal transgression, we created a practical workflow for spatially explicit quantification of forest retreat rates. Concurrent with rising sea level, coastal forests migrated upslope from 0.63 (± 0.27) m above sea level in 1985 to 0.78 (± 0.32) m above sea level in 2020, and horizontal forest retreat rates accelerated from 3.1 (range of 0–36) m yr -1 during 1985–2000 to 4.7 (0–55) m yr -1 during 2001–2020. As SLR continues to accelerate, our study may serve as a scalable solution for consistent tracking of coastal landscape evolution that is urgently needed for sustainable forest and wetland management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Resolve the Clear-Sky Continuous Diurnal Cycle of High-Resolution ECOSTRESS Evapotranspiration and Land Surface Temperature

Although numerous evapotranspiration (ET) estimates have been developed from remote sensing measurements, a diurnally resolved product with high spatial resolution (<100 m) is still lacking, which is critically needed for agricultural and ecological monitoring. The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) provides, for the first time, ET at 70 m resolution with diurnal samplings, enabling a step toward filling this data gap. This study developed the first framework to resolve the full diurnal cycle of ET and Land Surface Temperature (LST) from sporadic ECOSTRESS measurements. We first constructed 70 m diurnal LST utilizing a diurnal temperature cycle (DTC) model that fused ECOSTRESS and Geostationary Operational Environmental Satellite (GOES) LST. Next, we derived 70 m diurnal ET from the diurnally resolved LST, along with ancillary meteorological and reflectance data sets, using the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) algorithm. This framework was tested in two regions: A relatively homogeneous semiarid grassland landscape (centered at the US-Seg Ameriflux site) and a heterogeneous humid cropland landscape (centered at US-ARM). Our diurnally resolved LST and ET successfully reproduced the spatial patterns in the native ECOSTRESS measurements during overpasses for both landscapes (LST: r > 0.97, RMSE ~2°C; ET: r > 0.99, and RMSE = 1–7 W m -2 ). The constructed time series also well captured the temporal variability of the in situ measurements (especially under clear-sky conditions) at both US-Seg and US-ARM, albeit performance varying with availability and quality of ECOSTRESS samples. This study sets the stage for testing and applying our framework to broader climates, biomes, and landscapes toward eventually generating diurnally resolved 70 m global operational LST/ET products to enhance ecological/agricultural applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Remote sensing from unoccupied aerial systems: Opportunities to enhance Arctic plant ecology in a changing climate

The Arctic is warming at a faster rate than any other biome on Earth, resulting in widespread changes in vegetation composition, structure, and function that have important feedbacks to the global climate system. The heterogeneous nature of arctic landscapes creates challenges for monitoring and improving understanding of these ecosystems, as current efforts typically rely on ground, airborne, or satellite-based observations that are limited in space, time, or pixel resolution. The use of remote sensing instruments on small Unoccupied Aerial Systems (UASs) has emerged as an important tool to bridge the gap between detailed, but spatially limited ground-level measurements, and lower resolution, but spatially extensive high-altitude airborne and satellite observations. UASs allow researchers to view, describe and quantify vegetation dynamics at fine spatial scales (1-10 cm) over areas much larger than typical field plots. UASs can be deployed with a high degree of temporal flexibility, enabling observation across diurnal, seasonal, and annual timescales. In this work, we review how established and emerging UAS remote sensing technologies can enhance arctic plant ecological research by quantifying fine-scale vegetation patterns and processes, and by enhancing the ability to link ground-based measurements with broader-scale information obtained from airborne and satellite platforms. Synthesis: Improved ecological understanding and model representation of arctic vegetation is needed to forecast the fate of the Arctic in a rapidly changing climate. Observations from UASs provide an approach to address this need, however, the use of this technology in the Arctic currently remains limited. Here we share recommendations to better enable and encourage the use of UASs to improve the description, scaling, and model representation of arctic vegetation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Bacterial response to the 2021 Orange County, California, oil spill was episodic but subtle relative to natural fluctuations

ABSTRACT An oil spill began in October 2021 off the coast of Orange County, California, releasing 24,696 gallons of crude oil into coastal environments. Although oil spills, such as this one, are recurrent accidents along the California coast, no prior studies have been performed to examine the severity of the local bacterial response. A coastal 10-year time series of short-read metagenomes located within the impacted area allowed us to quantify the magnitude and duration of the disturbance relative to natural fluctuations. We found that the largest change in bacterial beta-diversity occurred at the end of October. The change in taxonomic beta-diversity corresponded with an increase in the sulfur-oxidizing clade Candidatus Thioglobus, an increase in the total relative abundance of potential hydrocarbon-degrading bacteria, and an anomalous decline in the picocyanobacteria Synechococcus . Similarly, changes in function were related to anomalous declines in photosynthetic pathways and anomalous increases in sulfur metabolism pathways as well as aromatic degradation pathways. There was a lagged response in taxonomy and function to peaks in total PAHs. One week after peaks in total PAH concentrations, the largest shifts in taxonomy were observed, and 1 week after the taxonomy shifts were observed, unique functional changes were seen. This response pattern was observed twice during our sampling period, corresponding with the combined effect of resuspended PAHs and increased nutrient concentrations due to physical transport events. Thus, the impact of the spill on bacterial communities was temporally extended and demonstrates the need for continued monitoring for longer than 3 months after initial oil exposure. IMPORTANCE Oil spills are common occurrences in waterways, releasing contaminants into the aquatic environment that persist for long periods of time. Bacterial communities are rapid responders to environmental disturbances, such as oil spills. Within bacterial communities, some members will be susceptible to the disturbance caused by crude oil components and will decline in abundance, whereas others will be opportunistic and will be able to use crude oil components for their metabolism. In many cases, when an oil spill occurs, it is difficult to assess the oil spill’s impact because no samples were collected prior to the accident. Here, we examined the bacterial response to the 2021 Orange County oil spill using a 10-year time series that lies within the impacted area. The results presented here are significant because (i) susceptible and opportunistic taxa to oil spills within the coastal California environment are identified and (ii) the magnitude and duration of the in situ bacterial response is quantified for the first time.

Brock, Melissa L. (ORCID:0000000340329241)↗
DOE OSTI2024

Associations between regional blood-brain barrier permeability, aging, and Alzheimer’s disease biomarkers in cognitively normal older adults

Background Increased blood-brain barrier permeability (BBBp) has been hypothesized as a feature of aging that may lead to the development of Alzheimer’s disease (AD). We sought to identify the brain regions most vulnerable to greater BBBp during aging and examine their regional relationship with neuroimaging biomarkers of AD. Methods We studied 31 cognitively normal older adults (OA) and 10 young adults (YA) from the Berkeley Aging Cohort Study (BACS). Both OA and YA received dynamic contrast-enhanced MRI (DCE-MRI) to quantify K trans values, as a measure of BBBp, in 37 brain regions across the cortex. The OA also received Pittsburgh compound B (PiB)-PET to create distribution volume ratios (DVR) images and flortaucipir (FTP)- PET to create partial volume corrected standardized uptake volume ratios (SUVR) images. Repeated measures ANOVA assessed the brain regions where OA showed greater BBBp than YA. In OA, K trans values were compared based on sex, Aβ positivity status, and APOE4carrier status within a composite region across the areas susceptible to aging. We used linear models and sparse canonical correlation analysis (SCCA) to examine the relationship between K trans and AD biomarkers. Results OA showed greater BBBp than YA predominately in the temporal lobe, with some involvement of parietal, occipital and frontal lobes. Within an averaged ROI of affected regions, there was no difference in K trans values based on sex or Aβ positivity, but OA who were APOE4carriers had significantly higher K trans values. There was no direct relationship between averaged K trans and global Aβ pathology, but there was a trend for an Ab status by tau interaction on K trans in this region. SCCA showed increased K trans was associated with increased PiB DVR, mainly in temporal and parietal brain regions. There was not a significant relationship between K trans and FTP SUVR. Discussion Our findings indicate that the BBB shows regional vulnerability during normal aging that overlaps considerably with the pattern of AD pathology. Greater BBBp in brain regions affected in aging is related to APOE genotype and may also be related to the pathological accumulation of Aβ.

Science & Technology - Other Topics↗
DOE OSTI2024

Rupture Jumping and Seismic Complexity in Models of Earthquake Cycles for Fault Stepovers with Off-Fault Plasticity

ABSTRACT Fault stepovers are prime examples of geometric complexity in natural fault zones that may affect seismic hazard by determining whether an earthquake rupture continues propagating or abruptly stops. However, the long-term pattern of seismicity near-fault stepovers and underlying mechanisms of rupture jumping in the context of earthquake cycles are rarely studied. Leveraging a hybrid numerical scheme combining the finite element and the spectral boundary integral methods, FEBE, we carry out fully dynamic simulations of sequences of earthquakes and aseismic slip for both compressive and tensile stepovers with off-fault plasticity. We consider a rate-and-state friction law for the fault friction and pressure-sensitive Drucker–Prager plasticity for the off-fault bulk response. We observe that the accumulation of plastic deformation, an indication of off-fault damage, is significantly different in the two cases, with more plastic deformation projected in the overlapping region for the tensile stepover. The seismic pattern for a tensile stepover is more complex than for a compressive stepover, and incorporating plasticity also increases complexity, relative to the elastic case. A tensile stepover with off-fault plasticity shows rupture segmentation, temporal clustering, and frequent rupture jumping from one fault to another. These results shed light on possible mechanisms of rupture jumping in fault stepovers as well as the long-term evolution of the fault zone.

Geochemistry & Geophysics↗
DOE OSTI2022

Climate Leads to Reversed Latitudinal Changes in Chinese Flood Peak Timing

Changes in river floods under a changing climate are of worldwide concerns, but relevant knowledge is limited especially over the East Asia monsoon region. Here we examine changes in flood peak timing based on the most comprehensive flood dataset to date across China during 1961-2017. The temporal shifts of Chinese flood peak timing range from -19.0 days earlier to +14.0 days later per decade. Earlier flood occurrences are mainly observed in northern China, with delayed flood occurrences in the south. The spatial pattern of reversed latitudinal changes in flood timing leads to growing spatial extents of concurrent river floods over China. Soil moisture plays an important role in modulating such changes, despite precipitation determines the climatological mean dates of flood occurrences. Our results highlight a strong climate signal on the changes in flood timing over China, and call for coordinated efforts in alleviating expanding flood hazards related to the changes in flood timing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Reduced ecosystem resilience quantifies fine-scale heterogeneity in tropical forest mortality responses to drought

Sensitivity of forest mortality to drought in carbon-dense tropical forests remains fraught with uncertainty, while extreme droughts are predicted to be more frequent and intense. Here, in this study, the potential of temporal autocorrelation of high-frequency variability in Landsat Enhanced Vegetation Index (EVI), an indicator of ecosystem resilience, to predict spatial and temporal variations of forest biomass mortality is evaluated against in situ census observations for 64 site-year combinations in Costa Rican tropical dry forests during the 2015 ENSO drought. Temporal autocorrelation, within the optimal moving window of 24 months, demonstrated robust predictive power for in situ mortality (leave-one- out cross-validation R 2 = 0.54), which allows for estimates of annual biomass mortality patterns at 30 m resolution. Subsequent spatial analysis showed substantial fine-scale heterogeneity of forest mortality patterns, largely driven by drought intensity and ecosystem properties related to plant water use such as forest deciduousness and topography. Highly deciduous forest patches demonstrated much lower mortality sensitivity to drought stress than less deciduous forest patches after elevation was controlled. Our results highlight the potential of high-resolution remote sensing to “fingerprint” forest mortality and the significant role of ecosystem heterogeneity in forest biomass resistance to drought.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Integrated Biophysical Modeling and Image Analysis: Application to Neuro-Oncology

Central nervous system (CNS) tumors come with vastly heterogeneous histologic, molecular, and radiographic landscapes, rendering their precise characterization challenging. The rapidly growing fields of biophysical modeling and radiomics have shown promise in better characterizing the molecular, spatial, and temporal heterogeneity of tumors. Integrative analysis of CNS tumors, including clinically acquired multi-parametric magnetic resonance imaging (mpMRI) and the inverse problem of calibrating biophysical models to mpMRI data, assists in identifying macroscopic quantifiable tumor patterns of invasion and proliferation, potentially leading to improved (a) detection/segmentation of tumor subregions and (b) computer-aided diagnostic/prognostic/predictive modeling. This article presents a summary of (a) biophysical growth modeling and simulation,(b) inverse problems for model calibration, (c) these models' integration with imaging workflows, and (d) their application to clinically relevant studies. We anticipate that such quantitative integrative analysis may even be beneficial in a future revision of the World Health Organization (WHO) classification for CNS tumors, ultimately improving patient survival prospects.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Gene content evolution in the arthropods

Background: Arthropods comprise the largest and most diverse phylum on Earth and play vital roles in nearly every ecosystem. Their diversity stems in part from variations on a conserved body plan, resulting from and recorded in adaptive changes in the genome. Dissection of the genomic record of sequence change enables broad questions regarding genome evolution to be addressed, even across hyper-diverse taxa within arthropods. Results: Using 76 whole genome sequences representing 21 orders spanning more than 500 million years of arthropod evolution, we document changes in gene and protein domain content and provide temporal and phylogenetic context for interpreting these innovations. We identify many novel gene families that arose early in the evolution of arthropods and during the diversification of insects into modern orders. We reveal unexpected variation in patterns of DNA methylation across arthropods and examples of gene family and protein domain evolution coincident with the appearance of notable phenotypic and physiological adaptations such as flight, metamorphosis, sociality, and chemoperception. Conclusions: These analyses demonstrate how large-scale comparative genomics can provide broad new insights into the genotype to phenotype map and generate testable hypotheses about the evolution of animal diversity.

Arthropods↗
DOE OSTI2022

Panoramic Mapping of Phonon Transport from Ultrafast Electron Diffraction and Scientific Machine Learning

Abstract One central challenge in understanding phonon thermal transport is a lack of experimental tools to investigate frequency‐resolved phonon transport. Although recent advances in computation lead to frequency‐resolved information, it is hindered by unknown defects in bulk regions and at interfaces. Here, a framework that can uncover microscopic phonon transport information in heterostructures is presented, integrating state‐of‐the‐art ultrafast electron diffraction (UED) with advanced scientific machine learning (SciML). Taking advantage of the dual temporal and reciprocal‐space resolution in UED, and the ability of SciML to solve inverse problems involving coupled Boltzmann transport equations, the frequency‐dependent interfacial transmittance and frequency‐dependent relaxation times of the heterostructure from the diffraction patterns are reliably recovered. The framework is applied to experimental Au/Si UED data, and a transport pattern beyond the diffuse mismatch model is revealed, which further enables a direct reconstruction of real‐space, real‐time, frequency‐resolved phonon dynamics across the interface. The work provides a new pathway to probe interfacial phonon transport mechanisms with unprecedented details.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Microwave Heating-Induced Temperature Gradients in Liquid–Liquid Biphasic Systems

Microwaves (MWs) can enable the electrification and intensification of chemical manufacturing. They have been applied to various unit separations, such as drying, distillation, and extraction, entailing gas–liquid and solid–liquid systems. However, a limited quantitative understanding of MW-heated liquid–liquid biphasic systems related to extraction exists. This work measures the temporal and spatial temperature difference between an aqueous and an organic phase in batch and continuous microfluidic modes. We demonstrate permanent temperature differences between phases over 35 °C and spatiotemporal periodic and quasiperiodic oscillations modulated by the flow patterns. The temperature differences are primarily driven by the faster absorption rate of MW irradiation by the aqueous phase versus the slower heat transfer from the aqueous phase to the organic phase. These are amplified by low specific interfacial area and modifications of the electromagnetic field. We employ a multiphysics model to predict the temperature difference in a batch system. The model is in good agreement with the experiments. We demonstrate a strong effect of input power, dielectric properties of organic solvents, the volume of solvents, and the volume ratio between phases on the temperature difference. A simple analytical model describes the temperature difference and provides design principles. Furthermore, the combined approach offers new insights into the design and optimization of the MW-heated biphasic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Neutral Mode Dominates the Forced Global and Regional Surface Temperature Response in the Past and Future

Abstract Using a large suite of Green's function perturbation experiments, we construct the emergent dynamical operator for surface temperature and extract the most excitable mode. The leading mode turns out to be the most dominant mode excited by the climate forcing of doubling CO 2 , alone capturing 56% of the total spatial variances of the surface temperature response. The pattern of the leading mode is partly organized by the atmospheric annular modes in both hemispheres, and further modulated by the feedbacks from ocean circulations. Though derived from a single model, the leading mode can capture the spatio‐temporal variabilities of the global mean surface temperature over the past century in both the CMIP6 model simulations and observations. Moreover, the leading mode is most efficiently excited by radiative forcings from the midlatitude bands centered around 45°N and 25°S, where most human activities take place, suggesting the potency of human influence on the climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Impact of gas background on XFEL single-particle imaging

Abstract Single-particle imaging (SPI) using X-ray free-electron Lasers (XFELs) offers the potential to determine protein structures at high spatial and temporal resolutions without the need for crystallization or vitrification. However, the technique faces challenges due to weak diffraction signals from single proteins and significant background scattering from gases used for sample delivery. A recent observation of a diffraction pattern from an isolated GroEL protein complex Ekeberg T et al. (Light Sci Appl 13:15, 2024.https://doi.org/10.1038/274s41377-023-01352-7) had similar numbers of signal and background photons. Ongoing efforts aim to reduce the background created by sample delivery, with one approach replacing most of the used gas with helium Yenupuri T et al. (Sci Rep 14:4401, 2024.https://doi.org/10.1038/s41598-024-54605-9). In this study, we investigate the effects of a reduced background on the resolution limits for SPI of isolated proteins under different experiment conditions. As a test case, we used GroEL, and we used experimentally derived parameters for our simulations. We observe that background significantly impacts the achievable resolution, particularly when the signal strength is comparable to the background. This is best exemplified at 6.0 keV, where a background reduction by a factor of 10 leads to a resolution improvement from 1.9 to 1.2 nm, for a dataset of$$10^4$$patterns.

Science & Technology - Other Topics↗
DOE OSTI2022

Evaluating seasonal and regional distribution of snowfall in regional climate model simulations in the Arctic

In this study, we investigate how the regional climate model HIRHAM5 reproduces the spatial and temporal distribution of Arctic snowfall when compared to CloudSat satellite observations during the examined period of 2007–2010. For this purpose, both approaches, i.e., the assessments of the surface snowfall rate (observation-to-model) and the radar reflectivity factor profiles (model-to-observation), are carried out considering spatial and temporal sampling differences. The HIRHAM5 model, which is constrained in its synoptic representation by nudging to ERA-Interim, represents the snowfall in the Arctic region well in comparison to CloudSat products. The spatial distribution of the snowfall patterns is similar in both identifying the southeastern coast of Greenland and the North Atlantic corridor as regions gaining more than twice as much snowfall as the Arctic average, defined here for latitudes between 66 and 81°N. Excellent agreement (difference less than 1%) in the Arctic-averaged annual snowfall rate between HIRHAM5 and CloudSat is found, whereas ERA-Interim reanalysis shows an underestimation of 45% and significant deficits in the representation of the snowfall rate distribution. From the spatial analysis, it can be seen that the largest differences in the mean annual snowfall rates are an overestimation near the coastlines of Greenland and other regions with large orographic variations as well as an underestimation in the northern North Atlantic Ocean. To a large extent, the differences can be explained by clutter contamination, blind zone or higher resolution of CloudSat measurements, but clearly HIRHAM5 overestimates the orographic-driven precipitation. The underestimation of HIRHAM5 within the North Atlantic corridor south of Svalbard is likely connected to a poor description of the marine cold air outbreaks which could be identified by separating snowfall into different circulation weather type regimes. By simulating the radar reflectivity factor profiles from HIRHAM5 utilizing the Passive and Active Microwave TRAnsfer (PAMTRA) forward-modeling operator, the contribution of individual hydrometeor types can be assessed. Looking at a latitude band at 72–73°N, snow can be identified as the hydrometeor type dominating radar reflectivity factor values across all seasons. The largest differences between the observed and simulated reflectivity factor values are related to the contribution of cloud ice particles, which is underestimated in the model, most likely due to the small sizes of the particles. The model-to-observation approach offers a promising diagnostic when improving cloud schemes, as illustrated by comparison of different schemes available for HIRHAM5.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Online randomized interpolative decomposition with a posteriori error estimator for temporal PDE data reduction

Traditional low-rank approximation is a powerful tool for compressing large data matrices that arise in simulations of partial differential equations (PDEs), but suffers from high computational cost and requires several passes over the PDE data. The compressed data may also lack interpretability thus making it difficult to identify feature patterns from the original data. Here, to address these issues, we present an online randomized algorithm to compute the interpolative decomposition (ID) of large-scale data matrices in situ. Compared to previous randomized IDs that used the QR decomposition to determine the column basis, we adopt a streaming ridge leverage score-based column subset selection algorithm that dynamically selects proper basis columns from the data and thus avoids an extra pass over the data to compute the coefficient matrix of the ID. In particular, we adopt a single-pass error estimator based on the non-adaptive Hutch++ algorithm to provide real-time error approximation for determining the best coefficients. As a result, our approach only needs a single pass over the original data and thus is suitable for large and high-dimensional matrices stored outside of core memory or generated in PDE simulations. A strategy to improve the accuracy of the reconstructed data gradient, when desired, within the ID framework is also presented. We provide numerical experiments on turbulent channel flow and ignition simulations, and on the NSTX Gas Puff Image dataset, comparing our algorithm with the offline ID algorithm to demonstrate its utility in real-world applications.

Column subset selection↗
DOE OSTI2022

Atmospheric teleconnection associated with the Atlantic multidecadal variability in summer: assessment of the CESM1 model

Observational analysis shows that the Atlantic multidecadal variability (AMV) is associated with climate variability in the Northern Hemisphere through a zonal atmospheric teleconnection extending from the North Atlantic Ocean and propagating eastward around the Northern Hemisphere. Here, we studied the fidelity of model simulations in reproducing the observed summer AMV and the associated impacts on the mid-latitude climate by analysing simulations using the National Centre for Atmospheric Research Community Earth System Model Version 1 (CESM1), including CESM1 North Atlantic idealized and pacemaker simulations, CESM1 large ensemble twentieth century uninitialized simulations and large ensemble initialized CESM1 decadal predictions. To further compare the fidelity of CESM1, we also analysed large ensemble simulations from three other models. Our results suggest that the uninitialized large ensemble simulations from all models can produce an AMV time evolution and its regional climate impacts similar to the observations to certain degree. By initializing the observed oceanic condition in decadal prediction simulations, the simulated AMV and its regional impacts are closer to the observed ones than those in uninitialized ensemble simulations. In addition, the pacemaker simulations that nudged the time-evolving observed North Atlantic sea surface temperature anomalies produce spatiotemporal characteristics of the AMV and AMV climate impacts closer to the observed ones than the uninitialized simulations. We conclude that although coupled models can produce AMV and its regional impacts similar to observed, proper initialization and bias correction of the sea surface temperature spatial and temporal structure can improve this capability.

Initialization↗
DOE OSTI2021

In-situ digital image correlation and thermal monitoring in directed energy deposition additive manufacturing

As in welding, directed energy deposition (DED) additive manufacturing (AM) generates complex residual stresses and distortions commensurate with the complexity of the scan pattern used for deposition. To date, measuring DED distortions on complex geometries has only been achieved post process, discarding the complex thermomechanical history that leads to that final material state. In this work, surround stereo digital image correlation (DIC) is used to 3D map surfaces and strain tensors in-situ in a powder-blown laser DED system. Infrared thermography is then projected onto these surfaces to record the full thermomechanical history of printed parts. DIC presents a unique challenge to DED AM, as no part exists at the beginning of deposition, which (a) prevents application of an appropriate speckle pattern and (b) denies the user a zero strain reference frame. Solutions to these problems are proposed and their limitations explored herein. In sum, this work presents a relatively low-cost solution to monitoring and optimizing the unique temporal artifacts induced by complex scan strategies that was previously unobtainable.

42 ENGINEERING↗