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DOE OSTI2019

Spatially tracking carbon through the root-rhizosphere-soil system using laser ablation-IRMS

The intimate relationships between plant roots, rhizosphere, and soil are fostered by the release of organic compounds from the plant into soil through various forms of rhizodeposition and the simultaneous harvestingof inorganic nutrients from the soil to the plant. Here we present a method to spatially track and map the migration of plant-derived carbon (C) through roots into the rhizosphere and surrounding soil using laser ablation-isotope ratio mass spectrometry (LA-IRMS). Weused switchgrass microcosms containing soil from field plots at the Kellogg Biological Station (Hickory Corners, Michigan, USA), which have been cropped with switchgrass since 2008. We used a 13 CO 2 tracerto isotopically label switchgrass plants for two diel cycles and tracked subsequent movement of labeled C using the spatially specific (<100 µm resolution) δ 13 C analysis enabled by LA-IRMS.This approach permitted assessment of variable C flow through different roots and enabled mapping of spatial variability of C allocation to the rhizosphere. Highly 13 C-enriched C (consistent with production during the 13 CO 2 application period) extended ~0.5 – 1 mm from the root into the soil, suggesting that the majority of recent plant-derived C was within this distance of the root after 48 hours. Tracking the physical extent of root exudation into the rhizosphere can help evaluate the localization of plant-microbe interactions in highly variable subsurface environments,and the use of the isotopic label can differentiate freshly fixed C (presumably from root exudates) from other types of subsurface C (e.g., plant necromass and microbial turnover). The LA-IRMS technique mayalso serve as a valuable screening technique to identify areas of high activity for additional microbial or geochemicalassays.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Investigating the dependence of SCM simulated precipitation and clouds on the spatial scale of large-scale forcing at SGP [Investigating the scale dependence of SCM simulated precipitation and cloud by using gridded forcing data at SGP]

Large-scale forcing data, such as vertical velocity and advective tendencies, are required to drive single-column models (SCMs), cloud-resolving models, and large-eddy simulations. Previous studies suggest that some errors of these model simulations could be attributed to the lack of spatial variability in the specified domain-mean large-scale forcing. This study investigates the spatial variability of the forcing and explores its impact on SCM simulated precipitation and clouds. A gridded large-scale forcing data during the March 2000 Cloud Intensive Operational Period at the Atmospheric Radiation Measurement program's Southern Great Plains site is used for analysis and to drive the single-column version of the Community Atmospheric Model Version 5 (SCAM5). When the gridded forcing data show large spatial variability, such as during a frontal passage, SCAM5 with the domain-mean forcing is not able to capture the convective systems that are partly located in the domain or that only occupy part of the domain. This problem has been largely reduced by using the gridded forcing data, which allows running SCAM5 in each subcolumn and then averaging the results within the domain. This is because the subcolumns have a better chance to capture the timing of the frontal propagation and the small-scale systems. As a result, other potential uses of the gridded forcing data, such as understanding and testing scale-aware parameterizations, are also discussed.

58 GEOSCIENCES↗

DOE OSTI2018

Regional surname affinity: A spatial network approach

Abstract Objective We investigate surname affinities among areas of modern‐day China, by constructing a spatial network, and making community detection. It reports a geographical genealogy of the Chinese population that is result of population origins, historical migrations, and societal evolutions. Materials and methods We acquire data from the census records supplied by China's National Citizen Identity Information System, including the surname and regional information of 1.28 billion registered Chinese citizens. We propose a multilayer minimum spanning tree (MMST) to construct a spatial network based on the matrix of isonymic distances, which is often used to characterize the dissimilarity of surname structure among areas. We use the fast unfolding algorithm to detect network communities. Results We obtain a 10‐layer MMST network of 362 prefecture nodes and 3,610 edges derived from the matrix of the Euclidean distances among these areas. These prefectures are divided into eight groups in the spatial network via community detection. We measure the partition by comparing the inter‐distances and intra‐distances of the communities and obtain meaningful regional ethnicity classification. Discussion The visualization of the resulting communities on the map indicates that the prefectures in the same community are usually geographically adjacent. The formation of this partition is influenced by geographical factors, historic migrations, trade and economic factors, as well as isolation of culture and language. The MMST algorithm proves to be effective in geo‐genealogy and ethnicity classification for it retains essential information about surname affinity and highlights the geographical consanguinity of the population.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Preserved and variable spatial‐chemical changes of lipids across tomato leaves in response to central vein wounding reveals potential origin of linolenic acid in signal transduction cascade

Abstract Membrane lipids serve as substrates for the generation of numerous signaling lipids when plants are exposed to environmental stresses, and jasmonic acid, an oxidized product of 18‐carbon unsaturated fatty acids (e.g., linolenic acid), has been recognized as the essential signal in wound‐induced gene expression. Yet, the contribution of individual membrane lipids in linolenic acid generation is ill‐defined. In this work, we performed spatial lipidomic experiments to track lipid changes that occur locally at the sight of leaf injury to better understand the potential origin of linolenic and linoleic acids from individual membrane lipids. The central veins of tomato leaflets were crushed using surgical forceps, leaves were cryosectioned and analyzed by two orthogonal matrix‐assisted laser desorption/ionization mass spectrometry imaging platforms for insight into lipid spatial distribution. Significant changes in lipid composition are only observed 30 min after wounding, while after 60 min lipidome homeostasis has been re‐established. Phosphatidylcholines exhibit a variable pattern of spatial behavior in individual plants. Among lysolipids, lysophosphatidylcholines strongly co‐localize with the injured zone of wounded leaflets, while, for example, lysophosphatidylglycerol (LPG) (16:1) accumulated preferentially toward the apex in the injured zone of wounded leaflets. In contrast, two other LPGs (LPG [18:3] and LPG [18:2]) are depleted in the injured zone. Our high‐resolution co‐localization imaging analyses suggest that linolenic acids are predominantly released from PCs with 16_18 fatty acid composition along the entire leaf, while it seems that in the apex zone PG (16:1_18:3) significantly contributes to the linolenic acid pool. These results also indicate distinct localization and/or substrate preferences of phospholipase isoforms in leaf tissue.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

An approach to characterizing spatial aspects of image system blur

Quantitative X-ray radiographic imaging systems that utilize a charged couple device (CCD) camera connected to a thick, monolithic scintillator can exhibit blur that varies spatially across the field of view, especially for thick scintillators used in pulse-power radiography of dynamically compressed objects. Here, a three-point approach to estimating and accounting for this effect is demonstrated by (a) using a local estimation technique to measure the effect of blurring a calibration object at key locations across the field of view, (b) combining each of the local estimates into a spatially varying blurring function via partitions of unity interpolation, and (c) resolving the effects of that blur on the image by solving an ill-posed inverse problem using a spatially varying regularization term. The technique is demonstrated on synthetic examples and actual radiographs collected at the Naval Research Laboratory’s (NRL)Mercury pulsed power facility.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

An enhanced droplet-based liquid microjunction surface sampling system coupled with HPLC-ESI-MS/MS for spatially resolved analysis

Droplet-based liquid microjunction surface sampling coupled with high-performance liquid chromatography (HPLC)-electrospray ionization (ESI)-tandem mass spectrometry (MS/MS) for spatially resolved analysis provides the possibility of effective analysis of complex matrix samples and can provide a greater degree of chemical information from a single spot sample than is typically possible with a direct analysis of an extract. Described here is the setup and enhanced capabilities of a discrete droplet liquid microjunction surface sampling system employing a commercially available CTC PAL autosampler. The system enhancements include incorporation of a laser distance sensor enabling unattended analysis of samples and sample locations of dramatically disparate height as well as reliably dispensing just 0.5 μL of extraction solvent to make the liquid junction to the surface, wherein the extraction spot size was confined to an area about 0.7 mm in diameter; software modifications improving the spatial resolution of sampling spot selection from 1.0 to 0.1 mm; use of an open bed tray system to accommodate samples as large as whole-body rat thin tissue sections; and custom sample/solvent holders that shorten sampling time to approximately 1 min per sample. Lastly, the merit of these new features was demonstrated by spatially resolved sampling, HPLC separation, and mass spectral detection of pharmaceuticals and metabolites from whole-body rat thin tissue sections and razor blade (“crude”) cut mouse tissue.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Multi-approach assessment of the spatial distribution of the specific yield: application to the Crau plain aquifer, France

Spatially distributed values of the specific yield, a fundamental parameter for transient groundwater mass balance calculations, were obtained by means of three independent methods for the Crau plain, France. In contrast to its traditional use to assess recharge based on a given specific yield, the water-table fluctuation (WTF) method, applied using major recharging events, gave a first set of reference values. Then, large infiltration processes recorded by monitored boreholes and caused by major precipitation events were interpreted in terms of specific yield by means of a one-dimensional vertical numerical model solving Richards’ equations within the unsaturated zone. Finally, two gravity field campaigns, at low and high piezometric levels, were carried out to assess the groundwater mass variation and thus alternative specific yield values. The range obtained by the WTF method for this aquifer made of alluvial detrital material was 2.9– 26%, in line with the scarce data available so far. The average spatial value of specific yield by the WTF method (9.1%) is consistent with the aquifer scale value from the hydro-gravimetric approach. In this investigation, an estimate of the hitherto unknown spatial distribution of the specific yield over the Crau plain was obtained using the most reliable method (the WTF method). A groundwater mass balance calculation over the domain using this distribution yielded similar results to an independent quantification based on a stable isotope-mixing model. This agreement reinforces the relevance of such estimates, which can be used to build a more accurate transient hydrogeological model.

58 GEOSCIENCES↗

DOE OSTI2023

A general spatial-temporal framework for short-term building temperature forecasting at arbitrary locations with crowdsourcing weather data

Weather forecasting has been a critical component to predict and control building energy consumption for better building energy management. Without accessibility to other data sources, the onsite observed temperatures or the airport temperatures are used in forecast models. In this paper, we present a novel approach by utilizing the crowdsourcing weather data from neighboring personal weather stations (PWS) to improve the weather forecast accuracy around buildings using a general spatial-temporal modeling framework. The final forecast is based on the ensemble of local forecasts for the target location using neighboring PWSs. Our approach is distinguished from existing literature in various aspects. First, we leverage the crowdsourcing weather data from PWS in addition to public data sources. In this way, the data is at much finer time resolution (e.g., at 5-minute frequency) and spatial resolution (e.g., arbitrary location vs grid). Second, our proposed model incorporates spatial-temporal correlation information of weather variables between the target building and a set of neighboring PWSs so that underlying correlations can be effectively captured to improve forecasting performance. Here, we demonstrate the performance of the proposed framework by comparing to the benchmark models on temperature forecasting for a building located at an arbitrary location at San Antonio, Texas, USA. In general, the proposed model framework equipped with machine learning technique such as Random Forest can improve forecasting by 50% compares with persistent model and has 90% chance to outperform airport forecast in short-term forecasting. In a real-time setting, the proposed model framework can provide more accurate temperature forecasting results compared with using airport temperature forecast for most forecast horizon. Moreover, we analyze the sensitivity of model parameters to gain insights on how crowdsourcing data from the neighboring personal weather stations impacts forecasting performance. Finally, we implement our model in other cities such as Syracuse and Chicago to test the model's performance in different landforms and climate types.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

A Simple Method for Improving the Spatial Resolution in Infrared Laser Ablation Mass Spectrometry Imaging

In mass spectrometry imaging of tissues, the size of structures that can be distinguished is determined by the spatial resolution of the imaging technique. Here, the spatial resolution of IR laser ablation is markedly improved by increasing the distance between the laser and the focusing lens. As the distance between the laser and the lens is increased from 1 to 18 m, the ablation spot size decreases from 440 to 44 μm. This way, only the collimated center of the divergent laser beam is directed on the focusing lens, which results in better focusing of the beam. Part of the laser energy is lost at longer distance, but this is compensated by focusing of the radiation to a smaller area on the sample surface. The long distance can also be achieved by a set of mirrors, between which the radiation travels before it is directed to the focusing lens and the sample. This method for improving the spatial resolution can be utilized in mass spectrometry imaging of tissues by techniques that utilize IR laser ablation, such as laser ablation electrospray ionization, laser ablation atmospheric pressure photoionization, and matrix-assisted laser desorption electrospray ionization. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Statistical Estimation of Strain Using Spatial Correlation Functions

Ex-situ estimation of strains from deformed micrographs is not possible as there are no persistent features which can be tracked. Two point spatial statistics enable the rigorous quantification of spatial patterns in heterogeneous media. In this paper, we propose a novel method for estimating strains directly from dissimilar micrographs using a continuum mechanics approach. Rather than operating directly on images from sequential frames, as is done in digital image correlation, we operate on different microstructure realizations. This is made possible by comparing the spatial autocorrelation maps of deformed and undeformed micrographs rather than direct comparison of images. Additionally, a Bayesian framework is proposed for quantifying uncertainty. We first illustrate the efficacy of this method on speckle pattern images from digital image correlation experiments. Then, we demonstrate that the method is capable of operating on dissimilar micrographs using deformed synthetic binary microstructures. Finally, we present a case study on polycrystalline additively manufactured 316L deformed via tension. The proposed method works well and we discuss implications and limitations of the presented work.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Anomalous transport in disordered fracture networks: Spatial Markov model for dispersion with variable injection modes

Here we investigate tracer transport on random discrete fracture networks that are characterized by the statistics of the fracture geometry and hydraulic conductivity. While it is well known that tracer transport through fractured media can be anomalous and particle injection modes can have major impact on dispersion, the incorporation of injection modes into effective transport modeling has remained an open issue. The fundamental reason behind this challenge is that—even if the Eulerian fluid velocity is steady—the Lagrangian velocity distribution experienced by tracer particles evolves with time from its initial distribution, which is dictated by the injection mode, to a stationary velocity distribution. We quantify this evolution by a Markov model for particle velocities that are equidistantly sampled along trajectories. This stochastic approach allows for the systematic incorporation of the initial velocity distribution and quantifies the interplay between velocity distribution and spatial and temporal correlation. The proposed spatial Markov model is characterized by the initial velocity distribution, which is determined by the particle injection mode, the stationary Lagrangian velocity distribution, which is derived from the Eulerian velocity distribution, and the spatial velocity correlation length, which is related to the characteristic fracture length. This effective model leads to a time-domain random walk for the evolution of particle positions and velocities, whose joint distribution follows a Boltzmann equation. Finally, we demonstrate that the proposed model can successfully predict anomalous transport through discrete fracture networks with different levels of heterogeneity and arbitrary tracer injection modes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Spatially dependent embedded self-shielding method for nonuniform temperature distribution

The embedded self-shielding method (ESSM) is simple and robust, and applicable to any geometrical configuration to account for resonance self-shielding by performing fixed source transport calculations. ESSM is very similar to the subgroup method, which has been successful in the MPACT neutronics code developed by CASL. The subgroup method introduces errors in a least-squares fitting process that is used to generate subgroup quadrature sets and cannot be applied to thermal energy groups, as ESSM introduces error for spatially dependent self-shielded cross sections inside the fuel. This study focused on integrating the conventional ESSM with an improved Stoker-Weiss method to obtain spatially dependent resonance self-shielded cross sections for a nonuniform fuel temperature distribution. Here, the proposed method would serve as a substitute for the subgroup method in high fidelity simulations using CASL’s VERA. Benchmark results show that this new, spatially dependent ESSM (SDESSM) is an appropriate candidate to replace the subgroup method.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Particulate Fuel Modeling of MC 2 -3 using Iterative Local Spatial Self-shielding Method

We report a new spatial self-shielding method for particulate fuels has been developed based on disadvantage factors and implemented in the MC 2 -3 code. This method named the iterative local spatial self-shielding (ILSS) method considers the shadowing effect of randomly distributed particles on spatial self-shielding in particles through a homogenized composition region added outside the particle of interest at the center. The self-shielded cross sections of the central particle are determined iteratively since they are used in determining the cross sections of the homogenized composition region. The ILSS method was verified for infinite stochastic medium problems of single and multiple types of particles, VHTR unit cell problems, and HTTR assembly problems. The verification test results show that the ILSS method accurately predicts the stochastic particle shadowing effect and reaction rates in particles, whereas the regular array model and the stochastic collision probability method underpredict the particle shadowing effect and overestimate reaction rates in particles.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Scale-dependent spatial variabilities of hydrological exchange flows and transit time in a large regulated river

Hydrological exchange flows (HEF) across the river-aquifer interface and the associated residence time of river water in the aquifer have important implications for contaminant plume migration and biogeochemical processes in the river corridor. HEFs and residence time are influenced by both subsurface physical features and hydrologic forcing related to the transport process, which can exhibit complex spatial and temporal variations. In this study, we used a massively parallel subsurface flow model and a particle-tracking model to study the influences of different control factors on spatial variability of HEFs and residence time distributions (RTD) in the Hanford Reach of the Columbia River in Washington State. A total number of 100M particles were randomly injected in time and space and then tracked in a model domain that covers a 51-km 2 area (15.1M model cells). We used hourly river stages and groundwater levels to drive the model to provide dynamic velocity fields for the particle tracking in the simulation period that was longer than 2 years. The groundwater flow simulation and particle-tracking results provide the first comprehensive assessment of the spatial distribution of HEFs and residence time in large complex river corridors. Overall, our results show that the aquifer hydrogeological structure has the strongest correlation with the extent and magnitude of exchange flux. The residence time exhibits complex patterns that are impacted by all the river geomorphologic, hydrodynamic, and hydrogeologic factors and are strongly correlated with the downwelling ratio of exchange flux. The new insights gained through this study can be used to support the development of reduced-order models of HEFs and RTDs for large complex river systems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

The effect of spatial micro-CT image resolution and surface complexity on the morphological 3D analysis of open porous structures

In material science microfocus X-ray computed tomography (micro-CT) is one of the most popular non-destructive techniques to visualise and quantify the internal structure of materials in 3D. Despite constant system improvements, state-of-the-art micro-CT images can still hold several artefacts typical for X-ray CT imaging that hinder further image-based processing, structural and quantitative analysis. For example spatial resolution is crucial for an appropriate characterisation as the voxel size essentially influences the partial volume effect. However, defining the adequate image resolution is not a trivial aspect and understanding the correlation between scan parameters like voxel size and the structural properties is crucial for comprehensive material characterisation using micro-CT. Therefore, the objective of this study was to evaluate the influence of the spatial image resolution on the micro-CT based morphological analysis of three-dimensional (3D) open porous structures with a high surface complexity. In particular the correlation between the local surface properties and the accuracy of the micro-CT-based macro-morphology of 3D open porous Ti6Al4V structures produced by selective laser melting (SLM) was targeted and revealed for rough surfaces a strong dependence of the resulting structure characteristics on the scan resolution. Reducing the surface complexity by chemical etching decreased the sensitivity of the overall morphological analysis to the spatial image resolution and increased the detection limit. This study showed that scan settings and image processing parameters need to be customized to the material properties, morphological parameters under investigation and the desired final characteristics (in relation to the intended functional use). Customization of the scan resolution can increase the reliability of the micro-CT based analysis and at the same time reduce its operating costs. - Highlights: • We examine influence of the image resolution on μCT-based morphological analysis. • Surface properties influence accuracy of μCT-based morphology of porous structures. • Total porosity was the least sensitive to surface complexity and scan voxel size. • The beam thickness analysis was overestimated by the surface roughness. • Voxel size customization can significantly reduce a cost of the μCT-based analysis.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Spatial design principles for sustainable hydropower development in river basins

How can dams be arranged within a river basin such that they benefit society? Recent interest in this question has grown in response to the worldwide trend toward developing hydropower as a source of renewable energy in Asia and South America, and the movement toward removing unnecessary dams in the US. Environmental and energy sustainability are important practical concerns, and yet river development has rarely been planned with the goal of providing society with a portfolio of ecosystem services into the future. We organized a review and synthesis of the growing research in sustainable river basin design around four spatial decisions: Is it better to build fewer mainstem dams or more tributary dams? Should dams be clustered or distributed among distant subbasins? Where should dams be placed along a river? At what spatial scale should decisions be made? We came up with the following design principles for increasing ecological sustainability: (i) concentrate dams within a subset of tributary watersheds and avoid downstream mainstems of rivers, (ii) disperse freshwater reserves among the remaining tributary catchments, (iii) ensure that habitat provided between dams will support reproduction and retain offspring, and (iv) formulate spatial decision problems at the scale of large river basins. Based on our review, we discuss trade-offs between hydropower and ecological objectives when planning river basin development. We hope that future testing and refinement of principles extracted from our review will define a path toward sustainable river basin design.

13 HYDRO ENERGY↗

DOE OSTI2019

Spatial patterns of extracellular enzymes: Combining X-ray computed micro-tomography and 2D zymography

We report that linking the distribution of enzyme activity to the size and properties of soil pores is a necessary prerequisite for mechanistic understanding of soil biochemical processes. In this study we used soil 2D zymography and X-ray computed tomography (μCT) to assess the relationship between enzymes and pores. The objectives of the study were (i) to assess spatial distribution patterns in the activity of six enzymes contributing to C, N and P cycles, namely, cellobiohydrolase, β-glucosidase, xylanase acid phosphatase, leucine aminopeptidase, and N-acetylglucosaminidase, in soils from five long-term land use and management practices, (ii) to study the correlation between enzyme activities and μCT information, i.e., pore characteristics and image grayscale values, and (iii) to explore the potential use of soil 2D zymography in predicting enzyme activities within 3D soil cores. 3D pore-size distributions were obtained from μCT images of 13 intact soil cores and then 8–15 2D zymography maps were taken from each core. Spatial distributions in the activities of all studied enzymes were auto-correlated; the spatial correlation ranges were equal to ~7–8 mm. The relative activity of all enzymes was positively associated within 60–180 μm Ø pores. Combining 3D μCT information with 2D zymography maps visualized the overall patterns of enzyme activity distributions with respect to soil pores and particulate organic matter locations. Based on the findings we propose a conceptual scheme relating localization of microorganisms, enzymes and substrates to pores of different size ranges. Specifically, we suggest that pores in the tens of microns size range represent optimal microbial habitats, and as such are associated with greater microbial abundance, leading to high enzyme production and activity.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Ambient Single-Cell Analysis and Native Tissue Imaging Using Laser-Ablation Electrospray Ionization Mass Spectrometry with Increased Spatial Resolution

Laser ablation electrospray ionization mass spectrometry (LAESI-MS) is an emerging method that has the potential to transform the field of metabolomics. This is in part due to LAESI-MS being an ambient ionization method that requires minimal sample preparation and uses (endogenous) water for in situ analysis. This application note details the employment of the ‘LAESI microscope’ source to perform spatially resolved MS analysis of cells and MS imaging (MSI) of tissues at high spatial resolution. This source configuration utilizes a long-working distance reflective objective that permits both visualization of the sample and a smaller LAESI laser beam profile than conventional LAESI setups. In this work, we analyzed 200 single cells of Allium cepa (red onion) and imaged Fittonia argyroneura (nerve plant) in high spatial resolution using this source coupled to a Fourier transform mass spectrometer for high mass resolution and high mass accuracy metabolomics.

59 BASIC BIOLOGICAL SCIENCES↗