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At least 91 records · Page 5

Aspects of scaling and scalability for flow-based sampling of lattice QCD

Recent applications of machine-learned normalizing flows to sampling in lattice field theory suggest that such methods may be able to mitigate critical slowing down and topological freezing. However, these demonstrations have been at the scale of toy models, and it remains to be determined whether they can be applied to state-of-the-art lattice quantum chromodynamics calculations. Assessing the viability of sampling algorithms for lattice field theory at scale has traditionally been accomplished using simple cost scaling laws, but as we discuss in this work, their utility is limited for flow-based approaches. We conclude that flow-based approaches to sampling are better thought of as a broad family of algorithms with different scaling properties, and that scalability must be assessed experimentally.

Abbott, Ryan↗

An integrated computational materials engineering framework to analyze the failure behaviors of carbon fiber reinforced polymer composites for lightweight vehicle applications

A bottom-up multi-scale modeling approach is used to develop an Integrated Computational Materials Engineering (ICME) framework for carbon fiber reinforced polymer (CFRP) composites, which has the potential to reduce development to deployment lead time for structural applications in lightweight vehicles. In this work, we develop and integrate computational models comprising of four size scales to fully describe and characterize three types of CFRP composites. In detail, the properties of the interphase region are determined by an analytical gradient model and molecular dynamics analysis at the nano-scale, which is then incorporated into micro-scale unidirectional (UD) representative volume element (RVE) models to characterize the failure strengths and envelopes of UD CFRP composites. Then, the results are leveraged to propose an elasto-plastic-damage constitutive law for UD composites to study the fiber tows of woven composites as well as the chips of sheet molding compound (SMC) composites. Subsequently, the failure mechanisms and failure strengths of woven and SMC composites are predicted by the meso-scale RVE models. Finally, building upon the models and results from lower scales, we show that a homogenized macro-scale model can capture the mechanical performance of a hat-section-shaped part under four-point bending. Along with the model integration, we will also demonstrate that the computational results are in good agreement with experiments conducted at different scales. The present work illustrates the potential and significance of integrated multi-scale computational modeling tools that can virtually evaluate the performance of CFRP composites and provide design guidance for CFRP composites used in structural applications.

36 MATERIALS SCIENCE↗

Experimental Tests of Lateral Bedload Transport Induced by a Yawed Submerged Vane Array in Open-Channel Flows

This work proposes the use of an array of yawed porous vanes to control the lateral bedload transport by locally steering bedform migration and maximize the amount of sediments redirected toward a potential sediment extraction system or bypass channel. A laboratory experiment was conducted in a quasifield-scale channel with an array of permeable vanes installed on one side, in live-bed conditions under bedload dominant regime, i.e., negligible suspended load. A baseline experiment without vanes was also performed for comparison. The evolution of migrating bedforms of different scales was tracked in space and time using a high-resolution, state-of-the-art laser scanning device. The bedload transport rate in the streamwise direction was first calculated using bedforms’ geometry and migration velocity, and then spatially distributed over the entire monitored area using a new Eulerian-averaged grid-mapping method. This allowed us to introduce a new methodology to estimate the lateral bedload transport using control volume theory and applying mass conservation. Quantitative assessments of lateral bedload transport along the channel yield consistent results, suggesting that the vanes effectively move sediments laterally as intended. Under the investigated setup, the maximum lateral sediment transport rate ranges from 9% to 18% of the whole domain-averaged streamwise transport rate. The developed methodology also allowed to identify the location where sediment capture could be maximized for the given vane spatial distribution.

42 ENGINEERING↗

Ecological stoichiometry as a foundation for omics-enabled biogeochemical models of soil organic matter decomposition

Coupled biogeochemical cycles drive ecosystem ecology by influencing individual-to-community scale behaviors; yet the development of process-based models that accurately capture these dynamics remains elusive. Soil organic matter (SOM) decomposition in particular is influenced by resource stoichiometry that dictates microbial nutrient acquisition (‘ecological stoichiometry’). Despite its basis in biogeochemical modeling, ecological stoichiometry is only implicitly considered in high-resolution microbial investigations and the metabolic models they inform. State-of-science SOM decomposition models in both fields have advanced largely separately, but they agree on a need to move beyond seminal pool-based models. This presents an opportunity and a challenge to maximize the strengths of various models across different scales and environmental contexts. To address this challenge, we contend that ecological stoichiometry provides a framework for merging biogeochemical and microbiological models, as both explicitly consider substrate chemistries that are the basis of ecological stoichiometry as applied to SOM decomposition. We highlight two gaps that limit our understanding of SOM decomposition: (1) understanding how individual microorganisms alter metabolic strategies in response to substrate stoichiometry and (2) translating this knowledge to the scale of biogeochemical models. We suggest iterative information exchange to refine the objectives of high-resolution investigations and to specify limited dynamics for representation in large-scale models, resulting in a new class of omics-enabled biogeochemical models. Assimilating theoretical and modelling frameworks from different scientific domains is the next frontier in SOM decomposition modelling; advancing technologies in the context of stoichiometric theory provides a consistent framework for interpreting molecular data, and further distilling this information into tractable SOM decomposition models.

Carbon cycling↗

Reuniting philosophy and science to advance cancer research

Cancers rely on multiple, heterogeneous processes at different scales, pertaining to many biomedical fields. Therefore, understanding cancer is necessarily an interdisciplinary task that requires placing specialised experimental and clinical research into a broader conceptual, theoretical, and methodological framework. Without such a framework, oncology will collect piecemeal results, with scant dialogue between the different scientific communities studying cancer. We argue that one important way forward in service of a more successful dialogue is through greater integration of applied sciences (experimental and clinical) with conceptual and theoretical approaches, informed by philosophical methods. By way of illustration, we explore six central themes: (i) the role of mutations in cancer; (ii) the clonal evolution of cancer cells; (iii) the relationship between cancer and multicellularity; (iv) the tumour microenvironment; (v) the immune system; and (vi) stem cells. In each case, we examine open questions in the scientific literature through a philosophical methodology and show the benefit of such a synergy for the scientific and medical understanding of cancer.

59 BASIC BIOLOGICAL SCIENCES↗

Turbulence regimes in the nocturnal roughness sublayer: Interaction with deep convection and tree mortality in the Amazon

We investigated the influence of seasonality and proximity to the forest canopy on nocturnal turbulence regimes in the roughness sublayer of a Central Amazon forest. Since convective systems of different scales are common in this region, we also analyzed the effect of extreme wind gusts (propagated from convective downdrafts) on the organization of the turbulence regimes, and their potential to cause the mortality of canopy trees. Our data include high-frequency winds, temperature and ozone concentration at different heights during the dry and wet seasons of 2014. In addition, we used critical wind-speed data derived from a tree-winching experiment and a modeling study conducted in the same study site. Two different turbulence regimes were identified at three heights above the canopy: a weakly stable (WS) and a very stable regime (VS). The threshold wind speeds that mark the transition between turbulence regimes were larger during the dry season and increased as a function of the height above the canopy. The turbulent fluxes of sensible heat and momentum during the WS accounted for 88% of the entire nighttime flux. Downdrafts occurred only in the WS and favored a fully coupled state of wind flow along the canopy profile. The destructive potential of winds was four times higher than on nights without downdrafts.

54 ENVIRONMENTAL SCIENCES↗

Dynamics of a single polyampholyte chain

Polymers that feature both positive and negative charges along chains, known as polyampholytes, represent a class of materials that hold promise for a new generation of energy storage devices, the design of which will require knowledge of the underlying structure and dynamics. Here, we develop a theory based on the Rouse model for the dynamic structure factor of a single polyampholyte chain in the weak coupling regime (negligible intramolecular electrostatics) or subjected to weak external electric fields (governed by linear response). Neglecting effects of small ions, we find deviations in scaling from the classic Rouse theory and make predictions for scattering experiments performed on polyampholytes. We find that, under weak coupling with arbitrarily strong fields, the dynamics are highly dependent on the charge distribution and consequently look at two representative examples—random charge densities and periodic charge densities—with different scaling properties. Additionally, under weak fields, the dynamics are largely independent of charge distribution. Finally, we investigate the influence of hydrodynamic effects and the implications of including inertial effects in the model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bioenergy for climate change mitigation: Scale and sustainability

Many global climate change mitigation pathways presented in IPCC assessment reports rely heavily on the deployment of biomass for bioenergy, often used in conjunction with carbon capture and storage (BECCS). We review the literature on bioenergy, including the modelling of bioenergy in integrated assessment models (IAMs) and bottom-up modelling and non-modelling studies on the implications of bioenergy use. We summarise the limitations of existing modelling studies and what is known about the potential co-benefits and adverse side-effects of bioenergy systems. We find that the implications of bioenergy supply on mitigation and other sustainability criteria are context dependent and influenced by feedstock, management regime, climatic region, scale of deployment and the counterfactual land use and energy system. However, due to limitations of the existing models, and uncertainty over the future context with respect to the many variables that influence availability of biomass and land resources, it is not possible to precisely quantify the sustainability implications for different scales of bioenergy implementation. Given these uncertainties, the dependence on large-scale deployment of bioenergy in mitigation scenarios carries risks. The deployment of bioenergy technologies and the evolution of biomass supply chains at a scale that achieves significant mitigation and carbon sequestration requires integrative policies, coordinated institutions and improved governance mechanisms. As a result, bioenergy, and the use of land to produce biomass, is an essential part of many climate mitigation strategies but there are limits to its use due to trade-offs with sustainability.

09 BIOMASS FUELS↗

Multiscale Normalizing Flows for Gauge Theories

Scale separation is an important physical principle that has previously enabled algorithmic advances such as multigrid solvers. Previous work on normalizing flows has been able to utilize scale separation in the context of scalar field theories, but the principle has been largely unexploited in the context of gauge theories. This work gives an overview of a new method for generating gauge fields using hierarchical normalizing flow models. This method builds gauge fields from the outside in, allowing different parts of the model to focus on different scales of the problem. Numerical results are presented for $U(1)$ and $SU(3)$ gauge theories in 2, 3, and 4 spacetime dimensions.

Abbott, Ryan↗

Dynamic coevolution of baseflow and multiscale groundwater flow system during prolonged droughts

Field and numerical studies suggest that baseflow is composed of waters from a spectrum of groundwater flow paths termed the Groundwater Flow System (GWFS) – from shallow hillslope contributions to watershed-scale deep circulation originating in headwaters and discharging into lowland rivers. Here, we explore the evolution of the GWFS under prolonged droughts to understand its dynamics and multiscale nature, and to elucidate its role in baseflow generation and recession at the watershed scale. In this work, we consider three drought scenarios of varying severity and simulate groundwater flow in a 2-D cross-section of an idealized watershed with deep permeable bedrock, tracking the evolution of flow paths, baseflow, and residence times during the recession process. We find that baseflow generation at different drainage stages, and within different subwatersheds, is influenced distinctly by flow paths of different scales, depending on the relative strength of the flow paths and the position of the subwatersheds relative to the recharge/discharge zones of the deeper watershed-scale groundwater circulation. Despite having the same local relief, geology, and climate, baseflow from each subwatershed has a distinct recession behavior and time-dependent residence time distribution. Also, the hydraulic and transport characteristics of baseflow generation co-evolve and are strongly affected by the connection state of the water table to subwatersheds. These findings suggest that asynchrony and dissimilarity of baseflow generation from hillslopes under the impact of the watershed-scale groundwater flow, and interactions with local-scale and intermediate-scale groundwater flow, must be taken into account when interpreting baseflow recession data and building conceptual baseflow models at the watershed scale.

54 ENVIRONMENTAL SCIENCES↗

Using Multiscale Ethane/Methane Observations to Attribute Coal Mine Vent Emissions in the San Juan Basin From 2013 to 2021

Abstract Source attribution of natural gas emissions from fossil fuels in New Mexico's San Juan Basin (SJB) is challenging due to source heterogeneity and emissions transience. We demonstrate that ethane (C 2 H 6 ) to methane (CH 4 ) mixing ratios can identify and separate sources over different scales using various measurement techniques. We report simultaneous CH 4 and C 2 H 6 observations near a coal mine vent and oil and gas (O&G) emission sources using ground‐based in situ measurements in 2020/2021. During these campaigns, we observed a stable coal vent C 2 H 6 :CH 4 ratio of 1.28% ± 0.11%, discernibly different than nearby O&G source ratios ranging from 0.9% to 16.8%. We analyze airborne observations of the SJB taken in 2014/2015 that exhibit similar coal vent ratios and further show the region's heterogeneity. We identify episodic O&G sources, including a gas plant source detected in 2014/2015 that is absent in our 2020/2021 data. We examine total column observations of C 2 H 6 and CH 4 made in 2013 with a solar spectrometer and find a C 2 H 6 :CH 4 ratio of 1.3% ± 0.4% for the coal vent. The stable and unique coal vent ratio relative to other O&G sources in the region is used to demonstrate that consistent attribution is possible using various measurement methods at multiple scales across many years. Finally, we demonstrate that using C 2 H 6 as a proxy for fossil CH 4 inversions can inform detailed basin‐scale inversions, provided we understand source specific changes in the C 2 H 6 :CH 4 ratio like we report in the SJB.

54 ENVIRONMENTAL SCIENCES↗

Combined visualisation of cavitation and vortical structures in a real-size optical diesel injector

A high-speed flow visualisation set-up comprising of combined diffuse backlight illumination (DBI) and schlieren imaging has been developed to illustrate the highly transient, two-phase flow arising in a real-size optical fuel injector. The different illumination nature of the two techniques, diffuse and parallel light respectively, allows for the capturing of refractive-index gradients due to the presence of both interfaces and density gradients within the orifice. Hence, the onset of cavitation and secondary-flow motion within the sac and injector hole can be concurrently visualised. Experiments were conducted utilising a diesel injector fitted with a single-hole transparent tip (ECN spray D) at injection pressures of 700–900 bar and ambient pressures in the range of 1–20 bar. High-speed DBI images obtained at 100,000 fps revealed that the orifice, due to its tapered layout, is mildly cavitating with relatively constant cavity sheets arising mainly in regions of manufacturing imperfections. Nevertheless, schlieren images obtained at the same frame rate demonstrated that a multitude of vortices with short lifetimes arise at different scales in the sac and nozzle regions during the entire duration of the injection cycle but the vortices do not necessarily result in phase change. The magnitude and exact location of coherent vortical structures have a measurable influence on the dynamics of the spray emerging downstream the injector outlet, leading to distinct differences in the variation of its cone angle depending on the injection and ambient pressures examined.

42 ENGINEERING↗

DECOVALEX-2019 (Task E Final Report)

The DECOVALEX Project is an on-going international research collaboration, established in 1992, to advance the understanding and modeling of coupled Thermal (T), Hydrological (H), Mechanical (M) and Chemical (C) processes in geological in geological systems. DECOVALEX was initially motivated by the recognition that prediction of these coupled effects is an essential part of the performance and safety assessment of geologic disposal systems for radioactive waste and spent nuclear fuel. Later it was realized that these processes also play a critical role in other subsurface engineering activities, such as subsurface CO 2 storage, enhanced geothermal systems, and unconventional oil and gas production through hydraulic fracturing. Research teams from many countries (e.g., Canada, China, Czech Republic, Finland, France, Germany, Japan, Republic of Korea, Spain, Sweden, Switzerland, Taiwan, United Kingdom, and the United States) various institutions have participated in the DECOVALEX Project over the years, providing a wide range of perspectives and solutions to these complex problems. These institutions represent radioactive waste management organizations, national research institutes, regulatory agencies, universities, as well as industry and consulting groups. This document is the final report of Task E which was proposed and coordinated by Andra, the National Radioactive Waste Management Agency in France, presenting the technical definitions of the problems studied, approaches applied, achievements made and outstanding issues for future research. The purpose of Task E of the DECOVALEX-2019 project is to investigate upscaling THM modelling from small-scale experiments (some cubic meters) to full-scale experiments (some ten cubic meters) and finally to the scale of the waste repository (cubic kilometers). To achieve this aim, the data of two in-situ heating experiments performed by Andra (the French National Radioactive Waste Management Agency) in the Meuse/Haute-Marne Underground Research Laboratory (MHM URL) have formed the basis for the understanding of the THM behavior of the COx at different scales. The first experiment provided the reference values of the THM parameters by means of a calibration exercise and they were used for a blind prediction and an interpretative analysis of the second one.

58 GEOSCIENCES↗

A deep learning model for automatic analysis of cavities in irradiated materials

Transmission electron microscopy (TEM) is a commonly used technique in materials science for defect investigation. Quantitative analysis of defects is important for understanding the properties of a material, but manual analysis of TEM micrographs can be time-consuming and prone to error, especially when the defects have irregular shapes rather than spherical shapes. Many existing methods or deep learning models do not handle a wide range of sizes for the same object type within a single image. In this work, we present a framework that enables users to train an instance segmentation model called Mask R- CNN on any microstructure dataset, perform multi-detection on the same image at different scales, and obtain properties (e.g., size, area) of the objects based on the desired shape (e.g., circle, ellipse, rectangle). Additionally, we have developed a parallel detection module that uses multiple GPUs to increase the efficiency of the object detection process. We demonstrate the capabilities of our framework using a set of TEM images of cavities with different shapes, size distributions, and background contrasts. Finally, we show that the performance of our model in terms of density, size, and swelling of the cavities is comparable to the human average and that our model achieves the highest recall value compared to existing methods due to the use of image multi-rescaling.

36 MATERIALS SCIENCE↗

Multiscale and Multivariate Transportation System Visualization for Shopping District Traffic and Regional Traffic

In this paper, we present a suite of visualization techniques for sensor-based transportation system data at different scales to facilitate the exploration of interconnected traffic dynamics at intersections and highways. Additionally, these techniques are designed for analyzing multivariate traffic data from radar-based highway sensors and camera-based intersection sensors recording turn movements and vehicle speed, in the Chattanooga Metropolitan Area, with the capability of (a) revealing multiscale mobility patterns using different levels of data aggregation (e.g., individual sensor for microscale, multiple sensors along a corridor for mesoscale, and a larger number of sensors across the region for macroscale visualization) at different intervals (e.g., 5-min intervals, time of day, full day, and day-of-the-week), and (b) exploring the spatial variation of multiple traffic-related variables (e.g., volumes, speeds, turn movements, and traffic light colors) provided by the sensors. We close with a case study to demonstrate the effectiveness of our multiscale and multivariate visualization techniques. At microscale, we focused on intersection data from a shopping district around Shallowford Road in East Chattanooga. For mesoscale visualization, we studied the Shallowford Road corridor and an adjacent stretch of I-75. At macroscale, we included highway data from the Chattanooga Metropolitan Area. All visualizations were integrated into a web-based situational awareness tool to promote user access and interaction. At a minimum, each visualization provides the option for selecting dates for real-time (depending on sensor availability) and historical data, and additional information on hovering, though most provide more detailed information, including different views of the selected data, or interactive highlights.

33 ADVANCED PROPULSION SYSTEMS↗

Entanglement transitions from restricted Boltzmann machines

The search for novel entangled phases of matter has lead to the recent discovery of a new class of “en- tanglement transitions,” exemplified by random tensor networks and monitored quantum circuits. Most known examples can be understood as some classical ordering transitions in an underlying statistical mechanics model, where entanglement maps onto the free-energy cost of inserting a domain wall. In this paper we study the possibility of entanglement transitions driven by physics beyond such statistical mechanics mappings. Motivated by recent applications of neural-network-inspired variational Ansätze, we investigate under what conditions on the variational parameters these Ansätze can capture an entanglement transition. We study the entanglement scaling of short-range restricted Boltzmann machine (RBM) quantum states with random phases. For uncorrelated random phases, we analytically demonstrate the absence of an entanglement transition and reveal subtle finite-size effects in finite-size numerical simulations. Introducing phases with correlations decaying as 1/r α in real space, we observe three regions with a different scaling of entanglement entropy depending on the exponent α. We study the nature of the transition between these regions, finding numerical evidence for critical behavior. Furthermore, our work establishes the presence of long-range correlated phases in RBM-based wave functions as a required ingredient for entanglement transitions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Fungal drops: a novel approach for macro- and microscopic analyses of fungal mycelial growth

Abstract This study presents an inexpensive approach for the macro- and microscopic observation of fungal mycelial growth. The ‘fungal drops’ method allows to investigate the development of a mycelial network in filamentous microorganisms at the colony and hyphal scales. A heterogeneous environment is created by depositing 15–20 µl drops on a hydrophobic surface at a fixed distance. This system is akin to a two-dimensional (2D) soil-like structure in which aqueous-pockets are intermixed with air-filled pores. The fungus (spores or mycelia) is inoculated into one of the drops, from which hyphal growth and exploration take place. Hyphal structures are assessed at different scales using stereoscopic and microscopic imaging. The former allows to evaluate the local response of regions within the colony (modular behaviour), while the latter can be used for fractal dimension analyses to describe the hyphal network architecture. The method was tested with several species to underpin the transferability to multiple species. In addition, two sets of experiments were carried out to demonstrate its use in fungal biology. First, mycelial reorganization of Fusarium oxysporum was assessed as a response to patches containing different nutrient concentrations. Second, the effect of interactions with the soil bacterium Pseudomonas putida on habitat colonization by the same fungus was assessed. This method appeared as fast and accessible, allowed for a high level of replication, and complements more complex experimental platforms. Coupled with image analysis, the fungal drops method provides new insights into the study of fungal modularity both macroscopically and at a single-hypha level.

Buffi, Matteo↗

A Dynamic Pore Network Model for Imbibition Simulation Considering Corner Film Flow

Wetting films can develop in the corners of angular pores under strong wetting conditions. Modeling the dynamics of corner film remains elusive using direct numerical simulations because of the significant scale difference between main meniscus and corner film flow. In this paper, the modified interacting capillary bundle model (ICB), developed in our previous work to describe accurately corner film dynamics in a single square tube, is incorporated into a single-pressure dynamic pore network model (DPNM) to simulate imbibition in strongly wetting porous media with corner film flow. The traditional pore network is decomposed into several layers of interacting subpore networks where the 0th layer of subpore network simulates the main meniscus flow and higher layers the corner film flow. The fluid flow between different layers is captured by interlayer throats. In addition, the snap-off mechanism caused by the thickening of wetting corner film is considered. The accuracy of the developed model is validated for four cases: spontaneous imbibition in a single square tube, wetting fluid redistribution through corner films under a capillary pressure difference, snap off in a narrow throat connecting two large pores, and imbibition dynamics in a real microfluidic porous geometry. The validated model is then used to simulate both spontaneous and controlled imbibition in a pore network with random pore size distribution. Finally, the interaction between corner film and main meniscus flow in porous media is analyzed from a pore-scale perspective.

58 GEOSCIENCES↗