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At least 1,189 records · Page 66

Hierarchical Bayesian method for mapping biogeochemical hot spots using induced polarization imaging

In floodplain environments, a naturally reduced zone (NRZ) is considered to be a common biogeochemical hot spot, having distinct microbial and geochemical characteristics. Although important for understanding their role in mediating floodplain biogeochemical processes, mapping the subsurface distribution of NRZs over the dimensions of a floodplain is challenging, as conventional wellbore data are typically spatially limited and the distribution of NRZs is heterogeneous. In this work, we present an innovative methodology for the probabilistic mapping of NRZs within a three-dimensional (3-D) subsurface domain using induced polarization imaging, which is a noninvasive geophysical technique. Measurements consist of surface geophysical surveys and drilling-recovered sediments at the U.S. Department of Energy field site near Rifle, CO (USA). Inversion of surface time domain-induced polarization (TDIP) data yielded 3-D images of the complex electrical resistivity, in terms of magnitude and phase, which are associated with mineral precipitation and other lithological properties. By extracting the TDIP data values colocated with wellbore lithological logs, we found that the NRZs have a different distribution of resistivity and polarization from the other aquifer sediments. To estimate the spatial distribution of NRZs, we developed a Bayesian hierarchical model to integrate the geophysical and wellbore data. In addition, the resistivity images were used to estimate hydrostratigraphic interfaces under the floodplain. Validation results showed that the integration of electrical imaging and wellbore data using a Bayesian hierarchical model was capable of mapping spatially heterogeneous interfaces and NRZ distributions thereby providing a minimally invasive means to parameterize a hydrobiogeochemical model of the floodplain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multi‐Material Gradient Printing Using Meniscus‐enabled Projection Stereolithography (MAPS)

Light‐based additive manufacturing methods are widely used to print high‐resolution 3D structures for applications in tissue engineering, soft robotics, photonics, and microfluidics, among others. Despite this progress, multi‐material printing with these methods remains challenging due to constraints associated with hardware modifications, control systems, cross‐contamination, waste, and resin properties. Here, a new printing platform coined Meniscus‐enabled Projection Stereolithography (MAPS) is reported, a vat‐free method that relies on generating and maintaining a resin meniscus between a crosslinked structure and bottom window to print lateral, vertical, discrete, or gradient multi‐material 3D structures with no waste and user‐defined mixing between layers. MAPS is compatible with a wide range of resins shown and can print complex multi‐material 3D structures without requiring specialized hardware, software, or complex washing protocols. MAPS's ability to print structures with microscale variations in mechanical stiffness, opacity, surface energy, cell densities, and magnetic properties provides a generic method to make advanced materials for a broad range of applications.

bioprinting↗

Visual Systems Mapping to Define and Compare Woody Biomass LCAs for Sustainable Systems

The challenge addressed in this research centres on the need to choose between several biomass sources and energy production processes, while supporting rural economies and resilience of forest systems. A key barrier to effective decision-making for strategies using biomass is the lack of standardized and transparent life cycle assessment (LCA) baselines. These baselines are critical for assessing the impacts of biomass strategies but often vary due to regional factors and chosen simplifying assumptions of the LCAs. However, omitting key variables can mean the LCA omits key feedback and balancing loops relevant to fully assessing impacts of the change or test scenario. To address these complexities, this project employs a systems engineering approach: visual systems mapping. This technique is used to define the boundaries and dynamic behaviours of LCA baselines, enhancing transparency. By examining five literature sources and their documented baseline scenarios, the systems mapping case-studies demonstrates an approach to documenting and archiving these baselines. Recommendations are that visual systems mapping should be used to document key assumptions, such as baselines, of LCAs. Further, where possible open data repositories should hold key information about LCA baselines and reproducible workflows (e.g., using open-source tools) should be used to improve transparency and comparability in LCAs. Given the consensus within the broader scientific community on the importance of replicable data practices, this research reinforces the need for standardized frameworks and systems engineering tools in LCAs. This research demonstrates a pathway to more transparent, standardized, and comparable LCAs, that may bolster decisions for biomass systems.

Davis, Maggie [ORNL] (ORCID:0000000181319328)↗

On observers in holographic maps

A straightforward gravitational path integral calculation implies that closed universes are trivial, described by a one dimensional Hilbert space. Two recent papers by Harlow-Usatyuk-Zhao and Abdalla-Antonini-Iliesiu-Levine have sought to ameliorate this issue by defining special rules to incorporate observers into the path integral. However, the proposed rules are different, leading to differing results for the Hilbert space dimension. Moreover, the former work offers a holographic map realized using a non-isometric code construction to complement their path integral result and clarify its physics. In this work, we propose a non-isometric code that implements the second construction, allowing thorough comparison. Our prescription may be thought of as simply removing the portion of the map that acts on the observer, while preserving the rest, creating an effective holographic boundary at the observer-environment interface. This proposal can be directly applied to general holographic maps for both open and closed universes of any dimension.

AdS-CFT correspondence↗

The quantum $\mathrm{UV}$-$\mathrm{IR}$ map for line defects in $$ \mathfrak{gl} $$(3)-type class $\mathcal{S}$ theories

We consider the quantum UV-IR map for line defects in class S theories of $\mathfrak{gl}$(3)-type. This map computes the protected spin character which counts framed BPS states with spin for the bulk-defect system. We give a geometric method of computing this map motivated by the physics of five-dimensional $\mathcal{N}$ = 2 supersymmetric Yang-Mills theory, and compute it explicitly in various examples. As a spin-off we propose a new way of computing a certain specialization of the HOMFLY polynomial for links in $\mathbb{R}^3$, as a sum over BPS webs attached to the link.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Double Kerr-Schild spacetimes and the Newman-Penrose map

The Newman-Penrose map, which is closely related to the classical double copy, associates certain exact solutions of Einstein’s equations with self-dual solutions of the vacuum Maxwell equations. Here we initiate an extension of the Newman-Penrose map to a broader class of spacetimes. As an example, we apply principles from the Newman-Penrose map to associate a self-dual gauge field to the Kerr-Taub-NUT-(A)dS spacetime and we show that the result agrees with previously studied examples of classical double copies. The corresponding field strength exhibits a discrete electric-magnetic duality that is distinct from its (Hodge star) self-dual property.

scattering amplitudes↗

On the completeness of contraction map proof method for holographic entropy inequalities

The contraction map proof method is the commonly used method to prove holographic entropy inequalities. Existence of a contraction map corresponding to a holographic entropy inequality is a sufficient condition for its validity. But is it also necessary? In this note, we answer that question in affirmative for all linear holographic entropy inequalities with rational coefficients. We show that the pre-image of a non-contraction map is not a hypercube, but a proper cubical subgraph, and show that this manifests as alterations to the geodesic structure in the bulk, which leads to the violation of inequalities by holographic geometries obeying the RT formula.

97 MATHEMATICS AND COMPUTING↗

Optimizing Travel Time to Outpatient Interventional Radiology Procedures in a Multi-Site Hospital System Using a Google Maps Application

The purpose of this study is to determine whether a custom Google Maps application can optimize site selection when scheduling outpatient interventional radiology (IR) procedures within a multi-site hospital system. The Google Maps for Business Application Programming Interface (API) was used to develop an internal web application that uses real-time traffic data to determine estimated travel time (ETT; minutes) and estimated travel distance (ETD; miles) from a patient’s home to each a nearby IR facility in our hospital system. Hypothetical patient home addresses based on the 33 cities comprising our institution’s catchment area were used to determine the optimal IR site for hypothetical patients traveling from each city based on real-time traffic conditions. For 10/33 (30%) cities, there was discordance between the optimal IR site based on ETT and the optimal IR site based on ETD at non-rush hour time or rush hour time. By choosing to travel to an IR site based on ETT rather than ETD, patients from discordant cities were predicted to save an average of 7.29 min during non-rush hour (p = 0.03), and 28.80 min during rush hour (p < 0.001). Using a custom Google Maps application to schedule outpatients for IR procedures can effectively reduce patient travel time when more than one location providing IR procedures is available within the same hospital system.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Optimization of Hot Deformation Parameters and Constitutive Analysis for As-Cast Mg-5Li-3Zn-0.3Y Alloy Using Processing Maps

Hot deformation behavior of as-cast Mg-5Li-3Zn-0.3Y (wt.%) alloy has been studied by establishing processing maps covering the range of 200-450 °C in temperature and 0.001-10 s{sup −1} in strain rate. The map corresponding to the strain of 0.7 reveals that a domain of dynamic recrystallization occurred at 340-400 °C/0.01-0.158 s{sup −1} with its peak efficiency of approximately 31%. Analysis of the flow behaviors and microstructural observations indicated that dynamic recrystallization occurred in the domain, in which fine microstructure can be achieved. The above conditions represent the optimum processing parameters, and the flow instability regimes are also recognized from the maps. The average deformation in the deformed range was 136.414 kJ/mol which is close to that for lattice self-diffusion in magnesium and far smaller than that for as-cast Mg-5.75Zn-0.73Y-0.36Zr (wt.%) alloy. It is believed that a lower activation energy for Mg-5Li-3Zn-0.3Y alloy can partly result from both the weak particle pinning effects and adding Li into the Mg-Zn-Y-Zr alloy. Results of extrusion experiments conducted at 350 °C show that the alloy can be easily extruded with good mechanical properties of the yield strength of 132 MPa, the fracture strength of 215 MPa and the elongation of 20.9%, and the grains can be well refined.

36 MATERIALS SCIENCE↗

High-Throughput Nanoindentation Mapping of Additively Manufactured T91 Steel

Here, this work aims to adapt nanoindentation mapping combined with a k-means algorithm as a high-throughput technique to study the nano-scale spatial changes in mechanical properties for a heterogeneous material. This technique can also classify the individual data points based on their properties. Hundreds to thousands of indents were performed on additively manufactured T91 at room temperature, 300°C, 400°C, and 500°C across a square area with a side length of 120 μm to 400 μm. From this data, the hardness and reduced modulus at each point could be calculated and mapped. Using k-means clustering, we were able to arrange the data into three or four clusters corresponding roughly to the ferritic and martensitic phases as well as one or two intermediate clusters sampling both the phases. The hardness of these two phases appears to be quite stable as a function of temperature. Nanoindentation mapping and the k-means algorithm can therefore be used to rapidly assess the feasibility of heterogeneous materials under extreme conditions, such as nuclear reactor steels.

36 MATERIALS SCIENCE↗

A Conterminous USA-Scale Map of Relative Tidal Marsh Elevation

Abstract Tidal wetlands provide myriad ecosystem services across local to global scales. With their uncertain vulnerability or resilience to rising sea levels, there is a need for mapping flooding drivers and vulnerability proxies for these ecosystems at a national scale. However, tidal wetlands in the conterminous USA are diverse with differing elevation gradients, and tidal amplitudes, making broad geographic comparisons difficult. To address this, a national-scale map of relative tidal elevation ( Z * MHW ), a physical metric that normalizes elevation to tidal amplitude at mean high water (MHW), was constructed for the first time at 30 × 30-m resolution spanning the conterminous USA. Contrary to two study hypotheses, watershed-level median Z * MHW and its variability generally increased from north to south as a function of tidal amplitude and relative sea-level rise. These trends were also observed in a reanalysis of ground elevation data from the Pacific Coast by Janousek et al. (Estuaries and Coasts 42 (1): 85–98, 2019). Supporting a third hypothesis, propagated uncertainty in Z * MHW increased from north to south as light detection and ranging (LiDAR) errors had an outsized effect under narrowing tidal amplitudes. The drivers of Z * MHW and its variability are difficult to determine because several potential causal variables are correlated with latitude, but future studies could investigate highest astronomical tide and diurnal high tide inequality as drivers of median Z * MHW and Z * MHW variability, respectively. Watersheds of the Gulf Coast often had propagated Z * MHW uncertainty greater than the tidal amplitude itself emphasizing the diminished practicality of applying Z * MHW as a flooding proxy to microtidal wetlands. Future studies could focus on validating and improving these physical map products and using them for synoptic modeling of tidal wetland carbon dynamics and sea-level rise vulnerability analyses.

Holmquist, James R. (ORCID:0000000325466766)↗

Biparametric investigation of the general standard map: multistability and global bifurcations

We investigate multistability and global bifurcations in the general standard map, a biparametric two-dimensional map. Departing from the conservative case of the map, we describe the evolution of periodic solutions and their basins of attraction as dissipation builds up, paying special attention on how the biparametric variation affects multistability. We examine general and specific phenomena and behavior for three distinct dynamical regimes, namely small, moderate, and large damping and different forcing amplitudes. Also, we report numerically the mechanism of global bifurcations associated to small chaotic attractors in the multistable system. Several global bifurcations are investigated as dissipation increases. Specifically, through the characterization of an interior, a merging and a boundary crisis, we study the crucial role played by fundamental hyperbolic invariant structures, such as unstable periodic orbits and their stable and unstable invariant manifolds, in the mechanisms by which the phase space is globally transformed.

97 MATHEMATICS AND COMPUTING↗

Subgrain geometrically necessary dislocation density mapping in spalled Ta in three dimensions

Here, in this work, the intragranular distributions of the densities of geometrically necessary dislocations (GNDs) generated in a polycrystalline tantalum (Ta) sample loaded in shock compression to spall are investigated. The sample studied is a highly resolved three-dimensional (3D) map of the orientations, grain boundary morphology, and voids across a 0.276mm 3 (with sample dimensions of 688.5µm x 669µm x 600µm) region of the microstructure about the spall plane obtained by TriBeam tomography. We present a formulation for calculating the crystallographic screw and edge character GND densities at a material point within body centered cubic (BCC) crystals when provided any number of potential slip systems or modes. Combining the 3D characterization, GND formulation, and a sample containing ≈ 6000 grains, we sought statistically relevant correlations between GND density per grain with grain size, grain orientation, void formation, and proximity from the spall plane. We show that GND density per grain increases with decreasing distance from the spall plane. Most grains had heterogeneously distributed GND densities but were free of any detectable voids, at least within the ≈ 1.5µm resolution of the characterization technique. It is found that the GND density for most grains is insensitive to grain size and grain orientation. Only the fraction of grains with the highest GND densities tended to have a [001] parallel to shock-direction orientation. Intragranular 3D maps of GNDs reveals that grains that contain voids have high GND density concentrations in the intragranular region immediately surrounding the void. The local intragranular GND mapping also showed voids that are connected to grain boundaries preferred to grow into the grain with the larger size, regardless of orientation.

36 MATERIALS SCIENCE↗

Mapping structural heterogeneity at the nanoscale with scanning nano-structure electron microscopy (SNEM)

Here, in this work, we explore the use of scanning electron diffraction (also known as 4D-STEM) coupled with electron atomic pair distribution function analysis (ePDF) to understand the local order (structure and chemistry) as a function of position in a complex multicomponent system, a hot rolled, Ni-encapsulated, Zr 65 Cu 17.5 Ni 10 Al 7.5 bulk metallic glass (BMG), with a spatial resolution of 3 nm. We show that it is possible to gain insight into the chemistry and chemical clustering/ordering tendency in different regions of the sample, including in the vicinity of nano-scale crystallites that are identified from virtual dark field images and in heavily deformed regions at the edge of the BMG. In addition to simpler analysis, unsupervised machine learning was used to extract partial PDFs from the material, modeled as a quasi-binary alloy, and map them in space. These maps allowed key insights not only into the local average composition, as validated by EELS, but also a unique insight into chemical short-range ordering tendencies in different regions of the sample during formation. The experiments are straightforward and rapid and, unlike spectroscopic measurements, don’t require energy filters on the instrument. We spatially map different quantities of interest (QoI’s), defined as scalars that can be computed directly from positions and widths of ePDF peaks or parameters refined from fits to the patterns. We developed a flexible and rapid data reduction and analysis software framework that allows experimenters to rapidly explore images of the sample on the basis of different QoI’s. The power and flexibility of this approach are explored and described in detail. Because of the fact that we are getting spatially resolved images of the nanoscale structure obtained from ePDFs we call this approach scanning nano-structure electron microscopy (SNEM), and we believe that it will be powerful and useful extension of current 4D-STEM methods.

36 MATERIALS SCIENCE↗

Nanoscale mapping of point defect concentrations with $\mathrm{4D-STEM}$

Vacancies are missing atoms in a crystalline material, and occur both at equilibrium (varying with temperature) and out of equilibrium such as when crystalline materials are damaged with radiation or corrosion. While we know of their importance, particularly regarding diffusive mechanisms, it is not straightforward to experimentally measure their concentration or to visualize them directly. Traditionally, measurements such as positron annihilation spectroscopy and to some degree X-ray diffraction can measure average concentrations, but generally lack the ability to visualize or quantify a heterogenous concentration of vacancies that can occur at the level of individual defects and microstructural features. Here, we present a method to map vacancy concentrations and their distribution using local lattice parameter measurements with a high-resolution electron microscope. Our method utilizes a Au thin film as a model to demonstrate the method via four-dimensional scanning transmission electron microscopy (4D-STEM) by correlating the differences between changes in lattice parameter and the volumetric thermal expansion during in situ heating experiments. The vacancy mapping methodology is also applied to non-equilibrium defects accumulated in pure Al via knock-on electron beam irradiation. Our method demonstrates the ability to map point defect concentrations in heterogeneous systems in situ with nanometer spatial resolution. The result is a technique that can provide direct measurements of vacancy concentrations at the level of individual defects in studies of materials in and out of equilibrium.

36 MATERIALS SCIENCE↗

SMITHERS: An object-oriented modular mapping methodology for MCNP-based neutronic–thermal hydraulic multiphysics

A novel object-oriented modular mapping methodology for externally coupled neutronics–thermal hydraulics multiphysics simulations was developed. The Simulator using MCNP with Integrated Thermal-Hydraulics for Exploratory Reactor Studies (SMITHERS) code performs on-the-fly mapping of material-wise power distribution tallies implemented by MCNP-based neutron transport/depletion solvers for use in estimating coolant temperature and density distributions with a separate thermal-hydraulic solver. The key development of SMITHERS is that it reconstructs the hierarchical geometry structure of the material-wise power generation tallies from the depletion solver automatically, with only a modicum of additional information required from the user. In addition, it performs the basis mapping from the combinatorial geometry of the depletion solver to the required geometry of the thermal-hydraulic solver in a generalizable manner, such that it can transparently accommodate varying levels of thermal-hydraulic solver geometric fidelity, from the nodal geometry of multi-channel analysis solvers to the pin-cell level of discretization for sub-channel analysis solvers.

42 ENGINEERING↗

Situational awareness-enhancing community-level load mapping with opportunistic machine learning

Motivated by present and forthcoming challenges in the adoption and integration of distributed renewable energy, we develop a machine learning (ML) approach that builds short-fuse mappings connecting the occasionally-unobservable true load in one target community with information-rich signals collected from relatively more instrumented reference communities. Our setting is inspired by and tailored to target communities with significant unobservable behind-the-meter solar generation, where true load (a relatively well-behaved quantity of interest to grid operators) is hard to discern during daytime due to insufficient instrumentation and/or privacy reasons, but that can be related to reference communities with low unobservable distributed variable generation or with sufficient instrumentation. The developed mapping, herein realized with Support Vector Machine regression, is built using nighttime data from all communities, when their distributed generation is low or zero. Our ML algorithm opportunistically learns to correlate signals of interest and then is operationally used the next day to shed light into target community load evolution. The mapping is subsequently rebuilt, rolling its short-fuse scope perpetually forward in time. Here, we demonstrate the efficacy of our approach on nine synthetically generated topologies and associated timeseries stemming from real-world data, on which we observe cumulative error performance that yields lower than 10% and 15% daily-averaged mean absolute percentage errors in target community load estimation on more than about 75% and 90% of days, respectively, in multiple yearly evaluations that shed light on long-term performance also under seasonal and one-off effects. The proposed ML-powered methodology can offer grid operators much-improved visibility into a previously obscure space and can also serve as an additional source of information in broader, multi-modal solar disaggregation solutions.

14 SOLAR ENERGY↗

Molecular Transducers of Physical Activity Consortium (MoTrPAC): Mapping the Dynamic Responses to Exercise

Exercise provides a robust physiological stimulus that evokes cross-talk between a wide range of tissues via hormonal, cellular and molecular signals that when repeated regularly over time (i.e., training) improves physiological capacity, benefits numerous organ systems and decreases the risk for premature mortality. In spite of its fundamental importance, a gap remains in identifying the detailed molecular signals and responses to exercise and its benefits for health and disease prevention. To further knowledge in this emerging area, the Molecular Transducers of Physical Activity Consortium (MoTrPAC) was established to generate a molecular map of the effects of acute and chronic exercise. MoTrPAC investigators are conducting preclinical and clinical studies to better understand the systemic effects of exercise across multiple tissues. The preclinical studies were performed on more than 700 rats with the analysis of twenty or more organs per rat. The clinical study involves a large cohort of ~2600 individuals with a range of ages and fitness levels (untrained, trained, highly trained) who will be evaluated physiologically and by molecular probing of blood, muscle and adipose tissues before and after acute and chronic endurance or resistance exercise. Multi-omic analyses (genomics, epigenomics, transcriptomics, proteomics and metabolomics/lipidomics) will be performed followed by state-of-the-art bioinformatics to create a molecular map of exercise. This mapping project will provide a public database that is expected to enhance our understanding of the health benefits of physical activity in many organ systems and potentially provide insight into mitigating diseases through activity.

Sanford, James A.↗