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Results for “emergent pattern”

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 OSTI2016

Cost-Effectiveness Analysis of Intensity Modulated Radiation Therapy Versus 3-Dimensional Conformal Radiation Therapy for Preoperative Treatment of Extremity Soft Tissue Sarcomas

Purpose: Create a cost-effectiveness model comparing preoperative intensity modulated radiation therapy (IMRT) versus 3-dimensional conformal radiation therapy (3DCRT) for extremity soft tissue sarcomas. Methods and Materials: Input parameters included 5-year local recurrence rates, rates of acute wound adverse events, and chronic toxicities (edema, fracture, joint stiffness, and fibrosis). Health-state utilities were used to calculate quality-adjusted life years (QALYs). Overall treatment costs per QALY or incremental cost-effectiveness ratio (ICER) were calculated. Roll-back analysis was performed using average costs and utilities to determine the baseline preferred radiation technique. One-way, 2-way, and probabilistic sensitivity analyses (PSA) were performed for input parameters with the largest impact on the ICER. Results: Overall treatment costs were $17,515.58 for 3DCRT compared with $22,920.51 for IMRT. The effectiveness was higher for IMRT (3.68 QALYs) than for 3DCRT (3.35 QALYs). The baseline ICER for IMRT was $16,842.75/QALY, making it the preferable treatment. The ICER was most sensitive to the probability of local recurrence, upfront radiation costs, local recurrence costs, certain utilities (no toxicity/no recurrence, grade 1 toxicity/no local recurrence, grade 4 toxicity/no local recurrence), and life expectancy. Dominance patterns emerged when the cost of 3DCRT exceeded $15,532.05 (IMRT dominates) or the life expectancy was under 1.68 years (3DCRT dominates). Furthermore, preference patterns changed based on the rate of local recurrence (threshold: 13%). The PSA results demonstrated that IMRT was the preferred cost-effective technique for 64% of trials compared with 36% for 3DCRT. Conclusions: Based on our model, IMRT is the preferred technique by lowering rates of local recurrence, severe toxicities, and improving QALYs. From a third-party payer perspective, IMRT should be a supported approach for extremity soft tissue sarcomas.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

A MATHEMATICAL MODEL FOR AN HOURGLASS MAGNETIC FIELD

Starting with a mathematical boundary value problem for the magnetic vector potential in an axisymmetric cylindrical coordinate system, we derive a general solution for any arbitrary current distribution using the method of Green's functions. We use this to derive an analytic form for an hourglass magnetic field pattern created by electrical currents that are concentrated near (but not confined within) the equatorial plane of a cylindrical coordinate system. Our solution is not characterized by a cusp at the equatorial plane, as in previous solutions based on a current sheet. The pattern we derive provides a very good fit to hourglass magnetic field patterns emerging from three-dimensional numerical simulations of core formation, and can in principle be used for source-fitting of observed magnetic hourglass patterns.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

A historical and comparative review of 50 years of root data collection in Puerto Rico

Fine roots play an important role in plant nutrition, as well as in carbon, water, and nutrient cycling. Fine roots account for a third of terrestrial net primary production (NPP), and inclusion of their structure and function in global carbon models should improve predictions of ecosystem responses to climate change. However, studies focusing on underground plant components are much less frequent than those on aboveground structure. This is more marked in the tropics, where one-third of the planet's terrestrial NPP is produced. Some tropical forests have been more represented in the literature than others, as demonstrated in the collective studies in Puerto Rico. This Caribbean island's biodiversity, frequency of natural disturbances, ease of access to forests, and long-term plots have created an ideal place for the study of tropical ecological processes. This review of the literature emphasizes 50 years of root research and patterns revealed around Puerto Rico. The data in this review were compiled from scientific publications, conference reports, symposiums, and raw data shared by some researches. Emergent patterns include the shallow distribution of fine roots, the great variation in root biomass among different forest types, little variation in root phosphorus concentrations, the slow recovery of root biomass after Hurricane Hugo, and the fact that most data on roots come from the wet tropical Luquillo Experimental Forest, causing other habitat types to be underrepresented. This review also shows the gaps in knowledge about fine roots in the island's ecosystems, which should be used to promote and guide future studies. Abstract in Spanish is available with online material.

tropics↗
NASA NTRS1975

The structure and evolution of coronal holes

Soft X-ray observations of coronal holes are analyzed to determine the structure, temporal evolution, and rotational properties of those features as well as possible mechanisms which may account for their almost rigid rotational characteristics. It is shown that coronal holes are open features with a divergent magnetic-field configuration resulting from a particular large-scale magnetic-field topology. They are apparently formed when the successive emergence and dispersion of active-region fields produce a swath of unipolar field founded by fields of opposite polarity, and they die when large-scale field patterns emerge which significantly distort the original field configuration. Two types of holes are described (compact and elongated), and three possible rotation mechanisms are considered: a rigidly rotating subphotospheric phenomenon, a linking of high and low latitudes by closed field lines, and an interaction between moving coronal material and open field lines.

Timothy, A. F.↗
DOE OSTI2025

3D pattern formation of a protein–membrane suspension

Many essential cellular processes, including cell division and the establishment of cell polarity during embryogenesis, are regulated by pattern-forming proteins. These proteins often need to bind to a substrate, such as the cell membrane, onto which they interact and form two-dimensional (2D) patterns. It is unclear how the membrane’s continuity and dimensionality impact pattern formation. Here, we address this gap using the MinDE system, a prototypical example of pattern-forming membrane proteins. We show that when the lipid substrate is fragmented into submicrometer-sized diffusive liposomes, adenosine triphosphate-driven protein–protein interactions generate three-dimensional (3D) spatially extended patterns, despite the complete loss of membrane continuity. Remarkably, these 3D patterns emerge at scales four orders of magnitude larger than the individual liposomes. By systematically varying protein concentration, liposome size, and density, we observed and characterized a variety of 3D dynamical patterns not seen on continuous 2D membranes, including traveling waves, dynamical spirals, and a coexistence phase. Simulations and linear stability analysis of a coarse-grained model revealed that the physical properties of the dispersed membrane effectively rescale both the protein–membrane binding rates and diffusion, two key parameters governing pattern formation and wavelength selection. These findings highlight the robustness of Min’s pattern-forming ability, suggesting that protein–membrane suspensions could serve as an adaptable template for studying out-of-equilibrium self-organization in 3D, beyond in vivo contexts.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Parametric study of flow patterns behind the standing accretion shock wave for core-collapse supernovae

In this study, we conduct three-dimensional hydrodynamic simulations systematically to investigate the flow patterns behind the accretion shock waves that are commonly formed in the post-bounce phase of core-collapse supernovae. Adding small perturbations to spherically symmetric, steady, shocked accretion flows, we compute the subsequent evolutions to find what flow pattern emerges as a consequence of hydrodynamical instabilities such as convection and standing accretion shock instability for different neutrino luminosities and mass accretion rates. Depending on these two controlling parameters, various flow patterns are indeed realized. We classify them into three basic patterns and two intermediate ones; the former includes sloshing motion (SL), spiral motion (SP), and multiple buoyant bubble formation (BB); the latter consists of spiral motion with buoyant-bubble formation (SPB) and spiral motion with pulsationally changing rotational velocities (SPP). Although the post-shock flow is highly chaotic, there is a clear trend in the pattern realization. The sloshing and spiral motions tend to be dominant for high accretion rates and low neutrino luminosities, and multiple buoyant bubbles prevail for low accretion rates and high neutrino luminosities. It is interesting that the dominant pattern is not always identical between the semi-nonlinear and nonlinear phases near the critical luminosity; the intermediate cases are realized in the latter case. Running several simulations with different random perturbations, we confirm that the realization of flow pattern is robust in most cases.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Divergent trait controls on soluble sugars and starch underlie global strategies of tree carbohydrate storage

Nonstructural carbohydrate (NSC) stores buffer tree metabolism, osmotic regulation, and defense, thereby mediating tolerance and survival under climate extremes. Yet, the functional and evolutionary determinants of interspecific variation in NSC remain elusive, limiting understanding and prediction of forest carbon allocation and mortality under global change. Here, we present a cross-species synthesis of NSC concentrations across multiple organs for 281 woody species from 102 mixed forest communities worldwide, where we quantified species-specific deviations from community means to disentangle intrinsic trait effects from environmental and methodological variation. We found phylogenetic signals in NSC deviations, with coniferous gymnosperms and evergreen species consistently maintaining lower stem soluble sugars and starch concentrations than co-occurring angiosperms and deciduous species, respectively. A global pattern emerged where greater stomatal sensitivity to leaf water potential was associated with declines in the relative concentrations of both sugars and starch. In contrast, xylem hydraulic safety traits showed weak and organ-dependent relationships with NSC concentrations. Sugars increased with photosynthetic capacity and declined with wood density, whereas starch showed the reverse pattern, which aligned with the distinct functional-metabolic roles of sugars and starch. By integrating trait-based ecology with a community-centered framework, our study provides global evidence that stomatal regulation, photosynthetic capacity, specific leaf area, and wood density jointly govern interspecific NSC variation, through contrasting effects on sugars and starch. These are among the most broadly measured traits globally, thus the emergent carbohydrate–trait relationships can have broad applications toward understanding and predicting forest growth and survival under climate change.

tropic system↗
NASA NTRS1998

Radiative Ignition and Transition to Spread Investigation (RITSI)

A total of 25 experiments was conducted in the Glovebox Facility on the Third United States Microgravity payload (USMP3) mission to study the behavior of both flaming and smoldering ignition events, the transition from ignition to the flame/smoldering spread, and the flame/smoldering growth pattern in air. Twenty one of the 25 experiments were flaming experiments and the remainder were smoldering experiments. Ignition was initiated by a heated wire across a thermally thin filter paper in the middle of the sample for the two-dimensional configuration and by a focused beam from a halogen/tungsten lamp at the center of the sample for the three-dimensional configuration. The external air flow velocity was varied from 0 cm/s to 6.5 cm/s. The ignition and subsequent flame spread events were recorded by a video camera, a 35 mm camera, and 6 thermocouples (2 in the gas phase and 4 in the sample). The results indicate that non-piloted radiative ignition of the paper by external thermal radiation tends to occur more easily than in normal gravity. In the two-dimensional configuration, the transition from ignition to downstream flame spread never occurred; only the transition to upstream spread took place. In the three-dimensional configuration, a char growth pattern emerged in the shape of a fan, with the ignited area as the center of the fan and the fan spreading in the upstream direction. The internal angle of the fan increased with an increase in external flow velocity (higher flow velocity gave a more opened fan pattern). At an external flow velocity of 5 cm/s, the flame was horseshoe-shaped and the char pattern became an elongated semicircle toward upstream. It appears that the peak upstream flame spread rate was reached at a higher external velocity than for the two-dimensional flame front. Flame spread much faster along open edges of the sample paper than along the sample face, presumably due to there being larger supply of oxygen and energy feedback at the open edges than at the surface. These results indicate the possible importance of the effect of the flame front shape such as the curvature of the flame front on spread rate and flame strength. A complex, unexpected finger-shaped char growth pattern was observed during the smoldering experiment. Higher external flow velocity increased the number of localized smoldering fronts, of the char fingers they left behind, and frequency of bifurcations from the fingers. At present, it is not clear what caused such a complex char growth pattern.

Kashiwagi, Takashi↗
DOE OSTI2023

Combining Agent Based Modeling and System Dynamics to Investigate the Circularity of Plastics

The United States currently produces about 1 million metric ton of ocean plastic pollution annually. One proposed solution to combat plastic waste is a circular economy (CE), which aims to transition from today's take-make-waste linear pattern of production and consumption to a system where the value of resources is maximized over time. Two key methods in industrial ecology are useful in assessing the viability of CE: (1) System Dynamics (SD) and (2) Agent Based Modeling (ABM). In prior work, the plastic life cycle was modeled with SD and ABM. The two models calculate recycling rates and costs in different ways, making it difficult to pinpoint necessary next steps. We integrate the ABM and SD models - linking the emergent patterns from micro-level human decisions to system level processes - which allows a more comprehensive understanding of feedbacks, costs, and environmental impacts. The integrated model is more accurate, and can be used to visualize recycling rates and human health and environmental impacts over time. The difference between the integrated and original SD model prompts a Sobol sensitivity analysis, which is used to understand which behavioral factors most affect plastic recycling patterns. We find that the habitual component is typically the most influential in promoting positive recycling behavior. Additionally, we utilize the combined model to understand and visualize how various behavioral intervention scenarios, like improved access to recycling programs and cart tagging, influence recycling patterns; these results can guide future policy-making.

agent-based modeling↗
DOE OSTI2022

Emerging signals of declining forest resilience under climate change

Forest ecosystems depend on their capacity to withstand and recover from natural and anthropogenic perturbations (that is, their resilience). Experimental evidence of sudden increases in tree mortality is raising concerns about variation in forest resilience, yet little is known about how it is evolving in response to climate change. Here we integrate satellite-based vegetation indices with machine learning to show how forest resilience, quantified in terms of critical slowing down indicators, has changed during the period 2000–2020. We show that tropical, arid and temperate forests are experiencing a significant decline in resilience, probably related to increased water limitations and climate variability. By contrast, boreal forests show divergent local patterns with an average increasing trend in resilience, probably benefiting from warming and CO 2 fertilization, which may outweigh the adverse effects of climate change. These patterns emerge consistently in both managed and intact forests, corroborating the existence of common large-scale climate drivers. Reductions in resilience are statistically linked to abrupt declines in forest primary productivity, occurring in response to slow drifting towards a critical resilience threshold. Approximately 23% of intact undisturbed forests, corresponding to 3.32 Pg C of gross primary productivity, have already reached a critical threshold and are experiencing a further degradation in resilience. Together, these signals reveal a widespread decline in the capacity of forests to withstand perturbation that should be accounted for in the design of land-based mitigation and adaptation plans

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

PROTEUS: Machine Learning Driven Resilience for Extreme-scale Systems

The objective of this project is to design, develop, and evaluate scalable software to enhance resilience, data checkpointing, program restart, and analysis. The proposed tasks are to 1) develop scalable machine learning techniques to learn temporal change patterns in a scalable and in-situ manner, and to minimize data movement and maximize learning locally closest to data; 2) design a concise data representation and indexing mechanism to capture the distribution of changes in data that can guarantee point-wise user-defined tolerable errors while reducing the data storage requirements by an order of magnitude or more; 3) develop data reduction techniques as library modules; 4) exploit local SSD for minimizing data movement in storage hierarchy; 5) develop anomaly detection algorithms that can predict corruptions based on learning of emerging patterns; 6) develop software libraries to be incorporated within widely used data formats and APIs; and 7) evaluate the proposed software using DOE scientific applications. The outcomes of the proposed work are to satisfy many synergistic data reduction and resilience requirements for large-scale data intensive applications executed on extreme-scale computing systems. The developed mechanism for error-bound data approximation is directly applicable to existing scientific applications. Through machine learning from historical events and change distribution, this work will enable anomaly detection for DOE computer facility.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A network approach for multiscale catchment classification using traits

Abstract. The classification of river catchments into groups with similar biophysical characteristics is useful to understand and predict their hydrological behavior. The increasing availability of remote sensing and other large-scale geospatial datasets has enabled the use of advanced data-driven approaches to classify catchments using traits such as topography, geology, climate, land cover, land use, and human influence. Unsupervised clustering algorithms based on the Euclidean distance are commonly used for trait-based classification but are not suitable for highly dimensional data. In this study we present a new network-based method for multi-scale catchment classification, which can be applied to large datasets and used to determine the traits associated with different catchment groups. In this framework, two networks are analyzed in parallel: the first being where the nodes are traits and the second being where the nodes are catchments. In both cases, edges represent pairwise similarity, and a network cluster detection algorithm is used for the classification. The trait network is used to investigate redundancy in the trait data and to condense this information into a small number of interpretable categories. The catchments network is used to classify the catchments into clusters and to identify representative catchments for the different groups using the degree centrality metric. We apply this method to classify 9067 river catchments across the contiguous United States at both regional and continental scales using 274 non-categorical traits. At the continental scale, we identify 25 interpretable trait categories and 34 catchment clusters of sizes greater than 50. We find that catchments with similar trait categories are typically located in the same region, with different spatial patterns emerging among clusters dominated by natural and anthropogenic traits. We also find that the catchment clusters exhibit distinct hydrological behavior based on an analysis of streamflow indices. This network approach provides several advantages over traditional means of classification, including better separation of clusters, the use of alternate similarity metrics that are more suitable for highly dimensional data, and reducing redundancy in the trait information. The paired catchment–trait networks enable analysis of hydrological behavior using the dominant trait categories for each catchment cluster. The approach can be used at multiple spatial scales since the network topologies adjust automatically to reflect the trait patterns at the scale of investigation. Finally, the representative catchments identified as hub nodes in the network can be used to guide transferable observational and modeling strategies. The method is broadly applicable beyond hydrology for classification of other complex systems that utilize different types of trait datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Emergent Subpopulation Behavior Uncovered with a Community Dynamic Metabolic Model of Escherichia coli Diauxic Growth

ABSTRACT Microbes have adapted to greatly variable environments in order to survive both short-term perturbations and permanent changes. A classical and yet still actively studied example of adaptation to dynamic environments is the diauxic shift of Escherichia coli , in which cells grow on glucose until its exhaustion and then transition to using previously secreted acetate. Here we tested different hypotheses concerning the nature of this transition by using dynamic metabolic modeling. To reach this goal, we developed an open source modeling framework integrating dynamic models (ordinary differential equation systems) with structural models (metabolic networks) which can take into account the behavior of multiple subpopulations and smooth flux transitions between time points. We used this framework to model the diauxic shift, first with a single E. coli model whose metabolic state represents the overall population average and then with a community of two subpopulations, each growing exclusively on one carbon source (glucose or acetate). After introduction of an environment-dependent transition function that determined the balance between subpopulations, our model generated predictions that are in strong agreement with published data. Our results thus support recent experimental evidence that diauxie, rather than a coordinated metabolic shift, would be the emergent pattern of individual cells differentiating for optimal growth on different substrates. This work offers a new perspective on the use of dynamic metabolic modeling to investigate population heterogeneity dynamics. The proposed approach can easily be applied to other biological systems composed of metabolically distinct, interconverting subpopulations and could be extended to include single-cell-level stochasticity. IMPORTANCE Escherichia coli diauxie is a fundamental example of metabolic adaptation, a phenomenon that is not yet completely understood. Further insight into this process can be achieved by integrating experimental and computational modeling methods. We present a dynamic metabolic modeling approach that captures diauxie as an emergent property of subpopulation dynamics in E. coli monocultures. Without fine-tuning the parameters of the E. coli core metabolic model, we achieved good agreement with published data. Our results suggest that single-organism metabolic models can only approximate the average metabolic state of a population, therefore offering a new perspective on the use of such modeling approaches. The open source modeling framework that we provide can be applied to model general subpopulation systems in more-complex environments and can be extended to include single-cell-level stochasticity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Stripe and bubble ratchets on asymmetric substrates

We show that various nonmonotonic ratchet effects can arise when mesophase pattern-forming systems, which exhibit anisotropic crystal, stripe, and bubble regimes, are coupled to one-dimensional asymmetric substrates under ac driving. The patterns emerge in the absence of a substrate when the ratio of attraction to repulsion is varied for particles with competing short-range attraction and long-range repulsion potentials. In the presence of the substrate, we find that the ratchet efficiency varies nonmonotonically with increasing attraction, depending upon how well the mesophase morphology matches the substrate spacing and periodicity. For strong repulsion, there is a weak but finite ratchet effect, while at intermediate attraction, there is a robust ratchet effect in which the system forms stripes aligned with the substrate symmetry direction. For strong attraction, large bubbles appear that have weak or no ratchet effects when the bubble width exceeds the substrate lattice spacing, causing the bubble to be only weakly coupled to the substrate. For very strong attraction, small bubbles form and undergo a strong ratchet effect with an efficiency that oscillates as a function of ac drive amplitude. Although the small bubble regime is a strongly correlated regime in which each bubble contains many particles, the system behaves as if it is in a single-particle regime since the bubble width is much smaller than the substrate lattice spacing. We map out the different rectification phases as a function of the pattern morphology, substrate strength, and ac drive amplitude. The pronounced ratchet effects that we observe in some regimes can be exploited for pattern sorting in hard and soft matter systems. Published by the American Physical Society 2024

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

The Safe Urban Harvests Study: A Community-Driven Cross-Sectional Assessment of Metals in Soil, Irrigation Water, and Produce from Urban Farms and Gardens in Baltimore, Maryland

BACKGROUND: Emerging evidence suggests social, health, environmental, and economic benefits of urban agriculture (UA). However, limited work has characterized the risks from metal contaminant exposures faced by urban growers and consumers of urban-grown produce. OBJECTIVES: We aimed to answer community-driven questions about the safety of UA and the consumption of urban-grown produce by measuring concentrations of nine metals in the soil, irrigation water, and urban-grown produce across urban farms and gardens in Baltimore, Maryland. METHODS: We measured concentrations of 6 nonessential [arsenic (As), barium (Ba), cadmium (Cd), chromium (Cr), lead (Pb), nickel (Ni)] and three essential [copper (Cu), manganese (Mn), zinc (Zn)] metals in soil, irrigation water, and 13 types of urban-grown produce collected from 104 UA sites. We compared measured concentrations to existing public health guidelines and analyzed relationships between urban soil and produce concentrations. In the absence of guidelines for metals in produce, we compared metals concentrations in urban-grown produce with those in produce purchased from farmers markets and grocery stores (both conventionally grown and U.S. Department of Agriculture–certified organic). RESULTS: Mean concentrations of all measured metals in irrigation water were below public health guidelines. Mean concentrations of nonessential metals in growing area soils were below public health guidelines for Ba, Cd, Pb, and Ni and at or below background for As and Cr. Though we observed a few statistically significant differences in concentrations between urban and nonurban produce items for some combinations, no consistent or discernable patterns emerged. DISCUSSION: Screening soils for heavy metals is a critical best practice for urban growers. Given limitations in existing public health guidelines for metals in soil, irrigation water, and produce, additional exposure assessment is necessary to quantify potential human health risks associated with exposure to nonessential metals when engaging in UA and consuming urban-grown produce. Conversely, the potential health benefits of consuming essential metals in urban-grown produce also merit further research. https://doi.org/10.1289/EHP9431

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Variations in northeast Asian summer precipitation driven by the Atlantic multidecadal oscillation

By analysing a 113–year (1900–2012) observational dataset, it is shown in this work that the interdecadal fluctuation of the summer precipitation over Northeast Asia differs from that in central East Asia during the 20th century, and has experienced three interdecadal shifts in the 1920s, mid-1960s and late 1990s. That fluctuation coincides well with the multidecadal fluctuation of the sea surface temperature in the North Atlantic, known as the Atlantic Multidecadal Oscillation (AMO). The AMO affects Northeast Asia via a circumglobal teleconnection pattern extending from the North Atlantic to North America. Corresponding with the positive phase of this teleconnection pattern, a tripolar pattern emerges in the Asian–North Pacific sector, with anomalous low pressure over Northeast Asia and high pressure over Lake Baikal and the mid-latitude western North Pacific. These results suggest that the positive phase of the AMO favours the occurrence of cold vortex over Northeast Asia and anomalous highs over Lake Baikal and the mid-latitude western North Pacific in summer, which enhances the East Asian summer monsoon and southward intrusion of high-latitude cold air, and eventually increases the summer precipitation in Northeast Asia. Furthermore, initialized decadal prediction simulations using the CCSM4 model reproduce well the observed variations of the AMO and its associated atmospheric teleconnection but with slightly shifted geographic locations. The simulated anomalous Northeast Asia cold vortex and strong East Asian summer monsoon, lead to above-normal summer precipitation over Northeast Asia. The modelling results confirm that the multidecadal variability in the North Atlantic can cause the observed interdecadal variations of Northeast Asia summer precipitation. Our results suggest that to understand and predict interdecadal climate change over Northeast Asia, it is important to consider the key role of the AMO.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Instabilities and finger formation in replacement fronts driven by an oversaturated solution: FINGER FORMATION IN MINERAL REPLACEMENT

We consider a simple model of infiltration-driven mineral replacement, in which the chemical coupling between precipitation and dissolution leads to the appearance of a reaction front advancing into the system. Such fronts are usually accompanied by a local increase of porosity. We analyze the linear stability of the replacement front to establish whether such a localized porosity increase can lead to global instability and pattern formation in these systems. We find that for a wide range of control parameters such fronts are unstable. However, both short- and long-wavelength perturbations are stabilized, whereas in a purely dissolutional instability only short wavelengths are stable. We analyze the morphologies of the dissolution patterns emerging in the later stages of the evolution of the system, when the dynamics are beyond the linear regime. Implications of these results for the natural systems are discussed, particularly in the context of karst formation in terra rossa-covered carbonate bedrock.

58 GEOSCIENCES↗