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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Negative extreme events in gross primary productivity and their drivers in China during the past three decades

Climate extremes have remarkable impacts on ecosystems and are expected to increase with future global warming. However, only few studies have focused on the ecological extreme events and their drivers in China. In this study, we carried out an analysis of negative extreme events in gross primary productivity (GPP) in China and the sub-regions during 1982–2015, using monthly GPP simulated by 12 process-based models (TRENDYv6) and an observation-based model (Yao-GPP). Extremes were defined as the negative 5th percentile of GPP anomalies, which were further merged into individual extreme events using a three-dimensional contiguous algorithm. Spatio-temporal patterns of negative GPP anomalies were analyzed by taking the 1000 largest extreme events into consideration. Results showed that the effects of extreme events decreased annual GPP by 2.8% (i.e. 208 TgC year –1 ) in TRENDY models and 2.3% (i.e. 151 TgC year –1 ) in Yao-GPP. Hotspots of extreme GPP deficits were mainly observed in North China (–53 gC m –2 year –1 ) in TRENDY models and Northeast China (–42 gC m –2 year –1 ) in Yao-GPP. For China as a whole, attribution analyses suggested that extreme low precipitation was associated with 40%–50% of extreme negative GPP events. Most events in northern and western China could be explained by meteorological droughts (i.e. low precipitation) while GPP extreme events in southern China were more associated with temperature extremes, in particular with cold spells. GPP was revealed to be much more sensitive to heat/drought than to cold/wet extreme events. Here, combined with projected changes in climate extremes in China, GPP negative anomalies caused by drought events in northern China and by temperature extremes in southern China might be more prominent in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A tale of two towers: comparing NEON and AmeriFlux data streams at Bartlett Experimental Forest

Long-term ecological data are essential for detecting impacts of climate change and other global change factors, and for making informed predictions about future change. However, long-term measurements are rarely replicated at the site level, which raises questions about their representativeness. We used a multiscale approach to evaluate the agreement of parallel observations from AmeriFlux and NEON (National Ecological Observatory Network) towers at Bartlett Experimental Forest, New Hampshire, USA. The two towers are separated by a horizontal distance of 93 m. Here, we focused our analysis on standard meteorological variables; fluxes of CO 2 , sensible heat, and latent heat measured by eddy covariance; and phenology derived from PhenoCam imagery. Results suggest excellent agreement between AmeriFlux and NEON in meteorology and phenology, and good agreement in fluxes at the half-hourly scale. However, large disagreements in CO 2 and latent heat fluxes occurred at the annual scale, with implications especially for the forest carbon balance. The AmeriFlux tower measurements indicate a site that is close to carbon-neutral (-8 ± 65 g C m -2 y -1 , mean ± 1 SD), whereas the NEON tower measurements indicate a forest that is a carbon sink (-137 ± 10 g C m -2 y -1 ). Causes of this disagreement may include measurement height (26 m vs. 35 m), which resulted in different flux footprints being measured by the two towers, and differences in the flux measurement systems. Our results suggest the need for caution when attempting to merge long-term flux data from two different measurement platforms, and when using measurements from any one measurement platform to inform decision-making on issues related to carbon accounting or natural climate solutions.

Carbon cycle↗
DOE OSTI2026

Ensemble Kalman filter for data assimilation coupled with low-resolution computations techniques applied in fluid dynamics

This paper presents an innovative Reduced-order model (ROM) for merging experimental and simulation data using data assimilation (DA) to estimate the "True" state of a fluid dynamics system, leading to more accurate predictions. Our methodology introduces a novel approach by implementing the ensemble Kalman filter (EnKF) within a reduced-dimensional framework, grounded in a robust theoretical foundation and applied to fluid dynamics. To address the substantial computational demands of DA, the proposed ROM employs low-resolution (LR) techniques to drastically reduce computational costs. This innovative approach involves downsampling datasets for DA computations, followed by an advanced reconstruction technique based on low-cost singular value decomposition (lcSVD). The lcSVD method, a key innovation in this paper, has never been applied to DA before and offers a highly efficient way to enhance resolution with minimal computational resources. Our results demonstrate significant reductions in both computation time and RAM usage through these LR techniques without compromising the accuracy of the estimations. For instance, in a turbulent test case, for a data compression rate of 15.9, the LR approach can achieve a speed-up of 13.7 and a RAM compression of 90.9% while maintaining a low relative root mean square error (RRMSE) of 2.6%, compared to 0.8% in the high-resolution (HR) reference. Furthermore, we highlight the effectiveness of the EnKF in estimating and predicting the state of fluid flow systems based on limited observations and given low-fidelity numerical data. This paper highlights the potential of the proposed DA method in fluid dynamics applications, particularly for improving computational efficiency in CFD and related fields. Its ability to balance accuracy with low computational and memory costs makes it especially suitable for large-scale and real-time applications, such as environmental monitoring or engineering design. This method will be incorporated into ModelFLOWs-app.

Data Assimilation↗
DOE OSTI2019

Modeling Concept and Numerical Simulation of Ultrasonic Wave Propagation in a Moving Fluid-Structure Domain based on a Monolithic Approach

Here in the present study, we propose a novel multiphysics model that merges two time-dependent problems – the Fluid-Structure Interaction (FSI) and the ultrasonic wave propagation in a fluid-structure domain with a one directional coupling from the FSI problem to the ultrasonic wave propagation problem. This model is referred to as the “eXtended fluid-structure interaction (eXFSI)” problem. This model comprises isothermal, incompressible Navier-Stokes equations with nonlinear elastodynamics using the Saint-Venant Kirchhoff solid model. The ultrasonic wave propagation problem comprises monolithically coupled acoustic and elastic wave equations. To ensure that the fluid and structure domains are conforming, we use the ALE technique. The solution principle for the coupled problem is to first solve the FSI problem and then to solve the wave propagation problem. Accordingly, the boundary conditions for the wave propagation problem are automatically adopted from the FSI problem at each time step. The overall problem is highly nonlinear, which is tackled via a Newton-like method. The model is verified using several alternative domain configurations. To ensure the credibility of the modeling approach, the numerical solution is contrasted against experimental data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Coupled modeling of a directly heated tubular solar receiver for supercritical carbon dioxide Brayton cycle: Optical and thermal-fluid evaluation

In single phase performance and appealing thermo-physical properties supercritical carbon dioxide (s-CO 2 ) make a good heat transfer fluid candidate for concentrating solar power (CSP) technologies. The development of a solar receiver capable of delivering s-CO 2 at outlet temperatures ~973 K is required in order to merge CSP and s-CO 2 Brayton cycle technologies. A coupled optical and thermal-fluid modeling effort for a tubular receiver is undertaken to evaluate the direct tubular s-CO 2 receiver’s thermal performance when exposed to a concentrated solar power input of ~0.3–0.5 MW. Ray tracing, using SolTrace, is performed to determine the heat flux profiles on the receiver and computational fluid dynamics (CFD) determines the thermal performance of the receiver under the specified heating conditions. Moreover, an in-house MATLAB code is developed to couple SolTrace and ANSYS Fluent. CFD modeling is performed using ANSYS Fluent to predict the thermal performance of the receiver by evaluating radiation and convection heat loss mechanisms. Understanding the effects of variation in heliostat aiming strategy and flow configurations on the thermal performance of the receiver was achieved through parametric analyses. Finally, a receiver thermal efficiency ~85% was predicted and the surface temperatures were observed to be within the allowable limit for the materials under consideration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Green fluorescence protein-based content-mixing assay of SNARE-driven membrane fusion

Soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) proteins mediate intracellular membrane fusion by forming a ternary SNARE complex. A minimalist approach utilizing proteoliposomes with reconstituted SNARE proteins yielded a wealth of information pinpointing the molecular mechanism of SNARE-mediated fusion and its regulation by accessory proteins. Two important attributes of a membrane fusion are lipid-mixing and the formation of an aqueous passage between apposing membranes. These two attributes are typically observed by using various fluorescent dyes. Currently available in vitro assay systems for observing fusion pore opening have several weaknesses such as cargo-bleeding, incomplete removal of unencapsulated dyes, and inadequate information regarding the size of the fusion pore, limiting measurements of the final stage of membrane fusion. In the present study, we used a biotinylated green fluorescence protein and streptavidin conjugated with Dylight 594 (DyStrp) as a Föster resonance energy transfer (FRET) donor and acceptor, respectively. This FRET pair encapsulated in each v-vesicle containing synaptobrevin and t-vesicle containing a binary acceptor complex of syntaxin 1a and synaptosomal-associated protein 25 revealed the opening of a large fusion pore of more than 5 nm, without the unwanted signals from unencapsulated dyes or leakage. This system enabled determination of the stoichiometry of the merging vesicles because the FRET efficiency of the FRET pair depended on the molar ratio between dyes. Here, we report a robust and informative assay for SNARE-mediated fusion pore opening. - Highlights: • SNARE proteins drive membrane fusion and open a pore for cargo release. • Biotinylated GFP and DyStrp was used as the reporter pair of fusion pore opening. • Procedure for efficient SNARE reconstitution and reporter encapsulation was established. • The FRET pair reported opening of a large fusion pore bigger than 5 nm. • The assay was robust and provided information of stoichiometry of vesicle fusion.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Investigation on temperature-induce conformational change of immobilized β 2 adrenergic receptor

Highlights: • Temperature could regulate protein conformational. • The receptor chromatography can simulate the pathological conditions of human fever. The β{sub 2} adrenergic receptor (β{sub 2}-AR) is a prototypical family A G protein-coupled receptor (GPCR) and an excellent model system for studying the mechanism of GPCR activation. Purified β{sub 2}-AR was immobilized on macroporous silica gel to obtain liquid chromatographic stationary phase. The resulting phase was packed into a stainless steel column (4.6 × 50 mm, 7 μm) and used for on-line chromatographic system. When column oven temperature increased from 20.0 °C to 40.0 °C, uncomplete separate chromatographic peaks of ephedrine and pseudoephedrine as receptor conformational probe were gradually merged into one peak, meanwhile retention time and resolution of the probes were reduced correspondingly, which suggested that temperature could regulate protein conformation. Temperature-induced conformational change of immobilized β{sub 2}-AR, especially changes at higher temperatures, indicated that constructed receptor chromatography could simulate fever disease state of human body and clarify receptor conformation change at pathological condition. At the same time this study could also provide new ideas for screening active components in pathological conditions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Progression of vasogenic edema induced by activated microglia under permanent middle cerebral artery occlusion

Highlights: • Vasogenic edema was visualized by superimposing TTC staining on T2WI. • Vasogenic edema moved from the ischemic core to the peripheral region. • Microglial activation was spread from the ischemic core to the peripheral region. • Microglial inhibition suppressed the progression of vasogenic edema. • Microglia are involved in vasogenic edema progression in ischemic stroke. Brain edema is a severe complication that accompanies ischemic stroke. Increasing evidence shows that inflammatory cytokines impair tight junctions of the blood-brain barrier, suggesting the involvement of microglia in brain edema. In this study, we examined the role of microglia in the progression of ischemic brain edema using mice with permanent middle cerebral artery occlusion. The intensity of T2-weighted imaging (T2WI) in the cerebral cortex and the striatum was elevated 3 h after occlusion and spread to peripheral regions of the ischemic hemisphere. Merged images of 2,3,5-triphenyl tetrazolium chloride staining and T2WI revealed the exact vasogenic edema region, which spread from the ischemic core to outside the ischemic region. Microglia were strongly activated in the ischemic region 3 h after occlusion and, notably, activated microglia were observed in the non-ischemic region 24 h after occlusion. Pretreatment with minocycline, an inhibitor of microglial activation clearly suppressed not only vasogenic edema but also infarct formation. We demonstrated in this study that vasogenic edema spreads from the ischemic core to the peripheral region, which can be elicited, at least in part, by microglial activation induced by ischemia.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Integrating biocatalysis with chemocatalysis for selective transformations

The integration of biocatalysis with chemocatalysis combines the excellent selectivity of the former with the robust reactivity of the latter and offers many advantages, such as lower cost, higher yield, enhanced selectivity, as well as less waste generation. Despite the challenge of incompatibilities between different classes of catalysts, recent advances in synthetic chemistry and biology provide ample opportunities for multistep cascade transformations that combine biocatalysis and chemocatalysis. In this research, we review recent progress in merging biocatalysis with chemocatalysis, highlighting selected examples of photo-/electricity-driven biotransformations and recently developed strategies for addressing the catalyst incompatibility issue.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Tailoring Microbial Fitness Through Computational Steering and CRISPRi-Driven Robustness Regulation

The widespread application of genetically modified microorganisms (GMMs) across diverse sectors underscores the pressing need for robust strategies to mitigate the risks associated with their potential uncontrolled escape. This study merges computational modeling with CRISPR interference (CRISPRi) to refine GMM metabolic robustness. Utilizing ensemble modeling, we achieved high-throughput in silico screening for enzymatic targets susceptible to expression alterations. Translating these insights, we developed functional CRISPRi, boosting fitness control via multiplexed gene knockdown. Our method, enhanced by an insulator-improved gRNA structure and an off-switch circuit controlling a compact Cas12m, resulted in rationally engineered strains with escape frequencies below National Institutes of Health standards. The effectiveness of this approach was confirmed under various conditions, showcasing its ability for secure GMM management. This research underscores the resilience of microbial metabolism, strategically modifying key nodes to halt growth without provoking significant resistance, thereby enabling more reliable and precise GMM control. A record of this paper's transparent peer review process is included in the supplemental information.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Reconstruction of concrete microstructure using complementarity of X-ray and neutron tomography

The concrete microstructure was successfully reconstructed using the complementarity of X-ray and neutron computed tomography (CT). Neither tomogram alone was found to be suitable to properly describe the microstructure of concrete under this study. However, by merging the information revealed by the two modalities, and using image segmentation, noise reduction, and image registration techniques we reconstruct the concrete microstructure. Void, aggregate, and cement paste phases are successfully captured down to the images' spatial resolution, even though the aggregate consists of multiple minerals. The coarse-aggregate volume fraction of the reconstructed microstructure was similar to that of the mixing proportions. Furthermore, image-based finite element analysis is performed to demonstrate the effects of microstructure on stress concentration and strain localization.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Numerical simulation of phase transition problems with explicit interface tracking

Phase change is ubiquitous in nature and industrial processes. Started from the Stefan problem, it is a topic with a long history in applied mathematics and sciences and continues to generate outstanding mathematical problems. For instance, the explicit tracking of the Gibbs dividing surface between phases is still a grand challenge. Our work has been motivated by such challenge and here we report on progress made in solving the governing equations of continuum transport in the presence of a moving interface by the front tracking method. The most pressing issue is the accounting of topological changes suffered by the interface between phases wherein break up and/or merge takes place. The underlying physics of topological changes require the incorporation of space-time subscales not at reach at the moment. Therefore we use heuristic geometrical arguments to reconnect phases in space. This heuristic approach provides new insight in various applications and it is extensible to include subscale physics and chemistry in the future. We demonstrate the method on applications such as simulating freezing, melting, dissolution, and precipitation. The later examples also include the coupling of the phase transition solution with the Navier-Stokes equations for the effect of flow convection.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Modeling wave propagation in elastic solids via high-order accurate implicit-mesh discontinuous Galerkin methods

Here, a high-order accurate implicit-mesh discontinuous Galerkin framework for wave propagation in single-phase and bi-phase solids is presented. The framework belongs to the embedded-boundary techniques and its novelty regards the spatial discretization, which enables boundary and interface conditions to be enforced with high-order accuracy on curved embedded geometries. High-order accuracy is achieved via high-order quadrature rules for implicitly-defined domains and boundaries, whilst a cell-merging strategy addresses the presence of small cut cells. The framework is used to discretize the governing equations of elastodynamics, written using a first-order hyperbolic momentum-strain formulation, and an exact Riemann solver is employed to compute the numerical flux at the interface between dissimilar materials with general anisotropic properties. The space-discretized equations are then advanced in time using explicit high-order Runge–Kutta algorithms. Several two- and three-dimensional numerical tests including dynamic adaptive mesh refinement are presented to demonstrate the high-order accuracy and the capability of the method in the elastodynamic analysis of single- and bi-phases solids containing complex geometries.

42 ENGINEERING↗
DOE OSTI2023

A multifidelity deep operator network approach to closure for multiscale systems

Projection-based reduced order models (PROMs) have shown promise in representing the behavior of multiscale systems using a small set of generalized (or latent) variables. Despite their success, PROMs can be susceptible to inaccuracies, even instabilities, due to the improper accounting of the interaction between the resolved and unresolved scales of the multiscale system (known as the closure problem). In the current work, we interpret closure as a multifidelity problem and use a multifidelity deep operator network (DeepONet) framework to address it. In addition, to enhance the stability and/or accuracy of the multifidelity-based closure, we employ the recently developed ``in-the-loop" training approach from the literature on coupling physics and machine learning models. The resulting approach is tested on shock advection for the one-dimensional viscous Burgers equation and vortex merging for the two-dimensional Navier-Stokes equations. Furthermore, the numerical experiments show significant improvement of the predictive ability of the closure-corrected PROM over the un-corrected one both in the interpolative and the extrapolative regimes.

42 ENGINEERING↗
DOE OSTI2015

Autoignition response of n -butanol and its blend with primary reference fuel constituents of gasoline.

We study the influence of blending n-butanol on the ignition delay times of n -heptane and iso-octane, the primary reference fuels for gasoline. The ignition delay times are measured using a rapid compression machine, with an emphasis on the low-to-intermediate temperature conditions. The experiments are conducted at equivalence ratios of 0.4 and 1.0, for a compressed pressure of 20 bar, with the temperatures at the end of compression ranging from 613 K to 979 K. The effect of n -butanol addition on the development of the two-stage ignition characteristics for the two primary reference fuels is also examined. The experimental results are compared to predictions obtained using a detailed chemical kinetic mechanism, which has been obtained by a systematic merger of previously reported base models for the combustion of the individual fuel constituents. In conclusion, a sensitivity analysis on the base, and the merged models, is also performed to understand the dependence of autoignition delay times on the model parameters.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2015

A numerical study of the diffusive-thermal instability of opposed nonpremixed tubular flames

The diffusive-thermal (D-T) instability of opposed nonpremixed tubular flames near extinction is investigated here using two-dimensional (2-D) direct numerical simulations together with the linear stability analysis. Two different initial conditions (IC), i.e. the perturbed IC and the C-shaped IC are adopted to elucidate the effects of small and large amplitude disturbances on the formation of flame cells, similar to conditions found in linear stability analysis and experiments, respectively. The characteristics of the D-T instability of tubular flames are identified by a critical Damköhler number, Da C , at which the D-T instability first occurs and the corresponding number of flame cells for three different tubular flames with different flame radii. It is found that Da C predicted through linear stability analysis shows good agreement with that obtained from the 2-D simulations performed with two different ICs. The flame cell number, N cell , from the 2-D simulations with the perturbed IC is also found to be equal to an integer close to the maximum wavenumber, k max , obtained from the linear stability analysis. However, N cell from the 2-D simulations with the C-shaped IC is smaller than k max and N cell found from the simulations with the perturbed IC. This is primarily because the strong reaction at the edges of the horseshoe-shaped cellular flame developed from the C-shaped IC is more likely to produce larger flame cells and reduce N cell . It is also found that for cases with the C-shaped IC, once the cellular instability occurs, the number of flame cells remains constant until global extinction occurs by incomplete reaction manifested by small Da. It is also verified through the displacement speed, S d , analysis that the two edges of the horseshoe-shaped cellular flame are stationary and therefore do not merge due to the diffusion–reaction balance at the edges. Moreover, large negative S d is observed at the local extinction points while small positive or negative S d features in the movement of flame cells as they adjust their location and size towards steady state.

42 ENGINEERING↗
DOE OSTI2022

A parallel discrete dislocation dynamics/kinetic Monte Carlo method to study non-conservative plastic processes

Non-conservative processes play a fundamental role in plasticity and are behind important macroscopic phenomena such as creep, dynamic strain aging, loop raft formation, etc. In the most general case, vacancy-induced dislocation climb is the operating unit mechanism. While dislocation/vacancy interactions have been modeled in the literature using a variety of methods, the approaches developed rely on continuum descriptions of both the vacancy population and its fluxes. However, there are numerous situations in physics where point defect populations display heterogeneous concentrations and/or non-smooth kinetics. Here, a kinetic Monte Carlo (kMC) approach for modeling vacancy transport in response to arbitrary stress fields is used. Vacancies are treated as point particles and are coupled to the dislocation substructure representing a deformed material via an advection term defined by the local stress gradients. The stress fields and the dislocation substructure are evolved using a discrete dislocation dynamics (DDD) module. To extend the coupled model to the treatment of large systems, we have implemented it in the massively-parallel DDD code ParaDiS. To avoid numerical incompatibilities associated with merging deterministic (DDD) and stochastic (kMC) integration algorithms, we cast the entire elasto-plastic-diffusive problem within a single stochastic framework, taking advantage of a parallel kMC algorithm to evolve the system as a single event-driven process. The large-scale implementation enables the study of the evolution of a variety of dislocation-defect scenarios governed by non-conservative transport kinetics. After carrying out an exhaustive numerical and computational analysis of our parallel algorithm, we show results that emphasize situations where inhomogeneous vacancy dynamics are of relevance, and compare discrete kinetics to continuum solutions for several cases.

36 MATERIALS SCIENCE↗
DOE OSTI2024

SAM-I-Am: Semantic boosting for zero-shot atomic-scale electron micrograph segmentation

Image segmentation is a critical enabler for tasks ranging from medical diagnostics to autonomous driving. However, the correct segmentation semantics — where are boundaries located? what segments are logically similar? — change depending on the domain, such that state-of-the-art foundation models can generate meaningless and incorrect results. Moreover, in certain domains, fine-tuning and retraining techniques are infeasible: obtaining labels is costly and time-consuming; domain images (micrographs) can be exponentially diverse; and data sharing (for third-party retraining) is restricted. To enable rapid adaptation of the best segmentation technology, we propose the concept of semantic boosting: given a zero-shot foundation model, guide its segmentation and adjust results to match domain expectations. Here, we apply semantic boosting to the Segment Anything Model (SAM) to obtain microstructure segmentation for transmission electron microscopy. Our booster, SAM-I-Am, serves as a post-processing engine that extracts geometric and textural features of various intermediate masks to perform mask removal and mask merging operations. We demonstrate a zero-shot performance increase of (absolute) +21.35%, +12.6%, +5.27% in mean IoU, and a -9.91%, -18.42%, -4.06% drop in mean false positive masks across images of three difficulty classes over vanilla SAM (ViT-L).

36 MATERIALS SCIENCE↗