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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

MORPHOLOGICAL AND RADIATION DAMAGE INFORMED THERMAL PROPERTY PREDICTION IN SCALED GEOMETRIC DOMAINS

This proposed work has the potential to rewrite the way the nuclear industry investigates new fuel and nuclear material designs. The current rubric of nuclear material design has myriad steps in the process, and while certain physics are modeled accurately, each step must be connected in order to obtain an entire description of the process. At present, neutronic, thermal, microstructural, fission product chemistry and migration, and radiation defect analysis (hereafter referred to together as “combined analysis”) are performed, albeit separately. There is no existing method which combines these physics in an attempt to understand the natural interactions between these phenomena. Consequently, the timeline for design, fabrication, experiment, validation, and licensing can take years. A disruptive approach is required to accelerate the development of new technology. This proposed undertaking creates a validated computational framework, generating a new microscopic-to-macroscopic methodology yielding thermal property predictions for nuclear fuels and materials at an engineering spatial scale.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Multipoint Observations of Energetic Particle Injections and Substorm Activity During a Conjunction Between Magnetospheric Multiscale (MMS) and Van Allen Probes

Here, this study examines multipoint observations during a conjunction between Magnetospheric Multiscale (MMS) and Van Allen Probes on 7 April 2016 in which a series of energetic particle injections occurred. With complementary data from Time History of Events and Macroscale Interactions during Substorms, Geotail, and Los Alamos National Laboratory spacecraft in geosynchronous orbit (16 spacecraft in total), we develop new insights on the nature of energetic particle injections associated with substorm activity. Despite this case involving only weak substorm activity (maximum AE <300 nT) during quiet geomagnetic conditions in steady, below-average solar wind, a complex series of at least six different electron injections was observed throughout the system. Intriguingly, only one corresponding ion injection was clearly observed. All ion and electron injections were observed at <600 keV only. MMS reveals detailed substructure within the largest electron injection. A relationship between injected electrons with energy <60 keV and enhanced whistler mode chorus wave activity is also established from Van Allen Probes and MMS. Drift mapping using a simplified magnetic field model provides estimates of the dispersionless injection boundary locations as a function of universal time, magnetic local time, and L shell. The analysis reveals that at least five electron injections, which were localized in magnetic local time, preceded a larger injection of both electrons and ions across nearly the entire nightside of the magnetosphere near geosynchronous orbit. The larger ion and electron injection did not penetrate to L < 6.6, but several of the smaller electron injections penetrated to L < 6.6. Due to the discrepancy between the number, penetration depth, and complexity of electron versus ion injections, this event presents challenges to the current conceptual models of energetic particle injections.

58 GEOSCIENCES↗
DOE OSTI2018

Senescence chips for ultrahigh-throughput isolation and removal of senescent cells

Cellular senescence plays an important role in organismal aging and age-related diseases. However, it is challenging to isolate low numbers of senescent cells from small volumes of biofluids for downstream analysis. Furthermore, there is no technology that could selectively remove senescent cells in a high-throughput manner. In this work, we developed a novel microfluidic chip platform, termed senescence chip, for ultrahigh-throughput isolation and removal of senescent cells. The core component of our senescence chip is a slanted and tunable 3D micropillar array with a variety of shutters in the vertical direction for rapid cell sieving, taking advantage of the characteristic cell size increase during cellular senescence. The 3D configuration achieves high throughput, high recovery rate, and device robustness with minimum clogging. We demonstrated proof-of-principle applications in isolation and enumeration of senescent mesenchymal stem cells (MSCs) from undiluted human whole blood, and senescent cells from mouse bone marrow after total body irradiation, with the single cell resolution. After scale-up to a multilayer and multichannel structure, our senescence chip achieved ultrahigh-throughput removal of senescent cells from human whole blood with an efficiency of over 70% at a flow rate of 300 ml/hr. Sensitivity and specificity of our senescence chips could be augmented with implementation of multiscale size separation, and identification of background white blood cells using their cell surface markers such as CD45. With the advantages of high throughput, robustness, and simplicity, our senescence chips may find wide applications and contribute to diagnosis and therapeutic targeting of cellular senescence.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Modeling dust mineralogical composition: sensitivity to soil mineralogy atlases and their expected climate impacts

Soil dust aerosols are a key component of the climate system, as they interact with short- and long-wave radiation, alter cloud formation processes, affect atmospheric chemistry and play a role in biogeochemical cycles by providing nutrient inputs such as iron and phosphorus. The influence of dust on these processes depends on its physicochemical properties, which, far from being homogeneous, are shaped by its regionally varying mineral composition. The relative amount of minerals in dust depends on the source region and shows a large geographical variability. However, many state-of-the-art Earth system models (ESMs), upon which climate analyses and projections rely, still consider dust mineralogy to be invariant. The explicit representation of minerals in ESMs is more hindered by our limited knowledge of the global soil composition along with the resulting size-resolved airborne mineralogy than by computational constraints. In this work we introduce an explicit mineralogy representation within the state-of-the-art Multiscale Online Nonhydrostatic AtmospheRe CHemistry (MONARCH) model. We review and compare two existing soil mineralogy datasets, which remain a source of uncertainty for dust mineralogy modeling and provide an evaluation of multiannual simulations against available mineralogy observations. Soil mineralogy datasets are based on measurements performed after wet sieving, which breaks the aggregates found in the parent soil. Our model predicts the emitted particle size distribution (PSD) in terms of its constituent minerals based on brittle fragmentation theory (BFT), which reconstructs the emitted mineral aggregates destroyed by wet sieving. Our simulations broadly reproduce the most abundant mineral fractions independently of the soil composition data used. Feldspars and calcite are highly sensitive to the soil mineralogy map, mainly due to the different assumptions made in each soil dataset to extrapolate a handful of soil measurements to arid and semi-arid regions worldwide. For the least abundant or more difficult-to-determine minerals, such as iron oxides, uncertainties in soil mineralogy yield differences in annual mean aerosol mass fractions of up to ~ 100 %. Although BFT restores coarse aggregates including phyllosilicates that usually break during soil analysis, we still identify an overestimation of coarse quartz mass fractions (above 2 µm in diameter). In a dedicated experiment, we estimate the fraction of dust with undetermined composition as given by a soil map, which makes up ~ 10 % of the emitted dust mass at the global scale and can be regionally larger. Changes in the underlying soil mineralogy impact our estimates of climate-relevant variables, particularly affecting the regional variability of the single-scattering albedo at solar wavelengths or the total iron deposited over oceans. All in all, this assessment represents a baseline for future model experiments including new mineralogical maps constrained by high-quality spaceborne hyperspectral measurements, such as those arising from the NASA Earth Surface Mineral Dust Source Investigation (EMIT) mission.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Adaptive two-regime method: Application to front propagation

The Adaptive Two-Regime Method (ATRM) is developed for hybrid (multiscale) stochastic simulation of reaction-diffusion problems. It efficiently couples detailed Brownian dynamics simulations with coarser lattice-based models. The ATRM is a generalization of the previously developed Two-Regime Method [Flegg et al., J. R. Soc., Interface 9, 859 (2012)] to multiscale problems which require a dynamic selection of regions where detailed Brownian dynamics simulation is used. Typical applications include a front propagation or spatio-temporal oscillations. In this paper, the ATRM is used for an in-depth study of front propagation in a stochastic reaction-diffusion system which has its mean-field model given in terms of the Fisher equation [R. Fisher, Ann. Eugen. 7, 355 (1937)]. It exhibits a travelling reaction front which is sensitive to stochastic fluctuations at the leading edge of the wavefront. Previous studies into stochastic effects on the Fisher wave propagation speed have focused on lattice-based models, but there has been limited progress using off-lattice (Brownian dynamics) models, which suffer due to their high computational cost, particularly at the high molecular numbers that are necessary to approach the Fisher mean-field model. By modelling only the wavefront itself with the off-lattice model, it is shown that the ATRM leads to the same Fisher wave results as purely off-lattice models, but at a fraction of the computational cost. The error analysis of the ATRM is also presented for a morphogen gradient model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

MO-G-BRF-07: Anomalously Fast Diffusion of Carbon Nanotubes Carriers in 3D Tissue Model

Purpose: We aim to investigate and understand diffusion process of carbon nanotubes (CNTs) and other nanoscale particles in tissue and organs. Methods: In this research, we utilized a 3D model tissue of hepatocellular carcinoma (HCC)cultured in inverted colloidal crystal (ICC) scaffolds to compare the diffusivity of CNTs with small molecules such as Rhodamine and FITC in vitro, and further investigated the transportation of CNTs with and without targeting ligand, TGFβ1. The real-time permeation profiles of CNTs in HCC tissue model with high temporal and spatial resolution was demonstrated by using standard confocal microscopy. Quantitative analysis of the diffusion process in 3D was carried out using luminescence intensity in a series of Z-stack images obtained for different time points of the diffusion process after initial addition of CNTs or small molecules to the cell culture and the image data was analyzed by software ImageJ and Mathematica. Results: CNTs display diffusion rate in model tissues substantially faster than small molecules of the similar charge such as FITC, and the diffusion rate of CNTs are significantly enhanced with targeting ligand, TGFβ1. Conclusion: In terms of the advantages of in-vitro model, we were able to have access to measuring the rate of CNT penetration at designed conditions with variable parameters. And the findings by using this model, changed our understanding about advantages of CNTs as nanoscale drug carriers and provides design principles for making new drug carriers for both treatment and diagnostics. Additionally the fast diffusion opens the discussion of the best possible drug carriers to reach deep parts of cancerous tissues, which is often a prerequisite for successful cancer treatment. This work was supported by the Center for Photonic and Multiscale Nanomaterials funded by National Science Foundation Materials Research Science and Engineering Center program DMR 1120923. The work was also partially supported by NSF grant ECS-0601345; EFRI-BSBA 0938019; CBET 0933384; CBET 0932823; CBET 1036672, AFOSR MURI 444286-P061716 and NIH 1R21CA121841-01A2.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Origin of the injection-dependent emission blueshift and linewidth broadening of III-nitride light-emitting diodes

III-nitride light-emitting diodes (LEDs) exhibit an injection-dependent emission blueshift and linewidth broadening that is severely detrimental to their color purity. By using first-principles multi-scale modeling that accurately captures the competition between polarization-charge screening, phase-space filling, and many-body plasma renormalization, we explain the current-dependent spectral characteristics of polar III-nitride LEDs fabricated with state-of-the-art quantum wells. Our analysis uncovers a fundamental connection between carrier dynamics and the injection-dependent spectral characteristics of light-emitting materials. For example, polar III-nitride LEDs offer poor control over their injection-dependent color purity due to their poor hole transport and slow carrier-recombination dynamics, which forces them to operate at or near degenerate carrier densities. Designs that accelerate carrier recombination and transport and reduce the carrier density required to operate LEDs at a given current density lessen their injection-dependent wavelength shift and linewidth broadening.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Multiscale dynamics of reactive fronts in the subsurface

1. Brief summary of progress to date. Major Goals of the Project. Overreaching goals of the proposed activity are to develop an or- ganizing framework to describe nonlinear reactive transport in geologic systems over many length and time scales, and corresponding physics-based adaptive multi-scale hybrid models. We will also provide computational tools for robust uncertainty quantification in hybrid simulations. Major Activities of the Project. The major activities in this reporting period have focused on developing a time-averaging framework for ADR transport (Task 1) and global diagnosis criteria for spatio-temporal algorithm refinement (Task 2), as well as numerical validation and verification of the analytical approaches developed. The main activities are as follows: (a) We use homogenization theory to perform a spatio-temporal upscaling of pore-scale advection- diffusion equation in a periodic porous medium in the presence of fluctuating boundary conditions on some parts of the boundary and nonlinear chemical reaction on the solid-liquid interface and we investigate the constraints under which the macroscopic equation gives an accurate explanation of the underlying physics at the pore scale. We demonstrate that the dynamics at the continuum scale is strongly influenced by the interplay between signal frequency at the boundary and transport processes at the pore level. Furthermore, we show that by choosing appropriate scaling factors, a homogenized equation along with expressions for the effective coefficients reliably describe the concentration of solute at the length and time scales vastly different from physically robust micro-scale provided that some specific scale separation constraints are met. Our analysis proves that if the reaction rate or advection at the micro-scale are large, the effectiveness of the homogenized model is impeded. (b) We test numerically the conditions derived theoretically for advective-diffusive and reactive trans- port in a fracture with planar walls subject to temporally oscillating Dirichlet boundary conditions. The numerical analysis confirms the theoretical predictions. Significant Results. Two paper are in preparation. 2. Description of work yet to be accomplished The Tasks yet to be accomplished are listed below: (a) Quantify the impact of uncertainty in wall geometry of planar fractures on predictions hybrids of ARD transport (b) Develop coupling conditions for time hybridzation (c) Quantify the impact of uncertainty in pore geometry on predictions of hybrids of ARD transport in porous media, i.e. develop stochastic hybrid models (d) Use the hybrids combined with X-Ray tomographic images of pore scale structure (from Dr. Gouze, see letter of collaboration) to model dynamic changes in porosity/permeability

42 ENGINEERING↗
DOE OSTI2024

Conservation of model degraded pine wood with selected organosilicons studied by XFM and nanoindentation

Previous research found that some organosilicon treatments proved effective in stabilizing waterlogged wood dimensions during drying. The present research aimed to determine the mechanism of wood stabilization by these chemicals to understand their mode of action. Here, the study used chemically (ChP) and biologically degraded (BP) model Scots pine wood treated with Methyltrimethoxysilane (MTMS), (3-Mercaptopropyl) trimethoxysilane (MPTMS), or 1,3-Bis(diethylamino)-3-propoxypropanol)-1,1,3,3-tetramethyldisiloxane (DEAPTMDS). Synchrotron-based X-ray fluorescence microscopy (XFM) was used to investigate the penetration of organosilicons into the wood cellular structure and cell walls, and nanoindentation was used to study the mechanical properties of the treated wood cell walls. All treatments resulted in high volumetric anti-shrink efficiency (ASE V ) values of 74-82%, except for MTMS-treated ChP with an ASE V of 52%. The multiscale XFM results revealed that all applied organosilicons penetrated throughout the whole wooden blocks and deposited in both cell lumina and cell walls. The retention of all applied organosilicons was highest in BP wood, and so was the dimensional stabilization effect. MTMS-treated ChP had the lowest measured cell wall infiltration, which likely contributed to its lower ASE v . DEAPTMDS treatments plasticized the cell walls and resulted in lowered nanoindentation elastic modulus (E s NI ) and hardness (H) for all types of wood. MTMS and MPTMS had modest effects on cell wall mechanical properties, and the effect depended on the type of wood. The final effect of organosilicon treatment on the dimensional wood stabilization and mechanical properties of wood cell walls depended not only on the type of the applied organosilicon but also the type of wood degradation. This means that the treatment cannot be considered universal, and specific approaches are needed for the conservation of individual wooden objects. Although some mechanisms are now better understood, such as the need for organosilicons to infiltrate the cell walls and the plasticizing effect of DEAPTMDS, other aspects will benefit from a more detailed analysis of the molecular interactions between organosilicons and wood polymers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Multiscale simulation of the ground and photo-induced charge-separated states of a molecular triad in polar organic solvent: Exploring the conformations, fluctuations, and free energy landscapes

Here, the approach of a multiscale simulation that combines quantum chemical calculations, classical molecular dynamics simulations, and statistical physics to integrate the information of the electronic states of a conformationally complex molecule into its structural distribution over an ensemble was performed to understand the influence of a polar organic solvent on the structural stability of carotene-porphyrin-fullerene molecular triad in both the ground and the photoinduced charge-separated excited states. The excited states of the triad were computed with the ab initio quantum chemical calculations using the algebraic diagrammatic construction through the second order correction (ADC(2)) method and the time-dependent density functional theory (TDDFT). The replica exchange molecular dynamics was used for the enhanced sampling of the ensemble in order to explore the phase space of the ground state and the photoinduced charge-separated excited state of triad in explicit tetrahydrofuran (THF) solvent. An importance sampling was strategically employed to bridge the gap between the two computational methods that aim to explore distinct realms of dynamics. We analyzed the free energy landscape, the structural fluctuations, the solvent arrangements, the static dielectric constant, and the interactions between the triad and the solvent molecules. The analysis of the free energy landscape of the triad indicates that the charge-separated excited state of the triad is thermodynamically stable in a linearly extended geometry, while the ground-state triad explores several extended and bent conformations that are populated in the local free energy minima separated by low free energy barriers at an order of thermal fluctuation (kBT). The stabilization of a linearly extended structure of the charge-separated excited state triad is predominantly due to the solvation interactions (van der Waals and electrostatic interactions) between the triad and the THF molecules as well as the interactions within the THF molecules. Differences in the charge distribution on a molecular triad induce slight changes in the dielectric property of THF near the triad. Our study suggests that by measuring the differences in a dielectric response of solvent near the triad, it is possible to provide insight into the population of the charge-separated electronic state of the triad relative to that of the ground state.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Bayesian and variational Bayesian approaches for flows in heterogeneous random media

In this paper, we study porous media flows in heterogeneous stochastic media. We propose an efficient forward simulation technique that is tailored for variational Bayesian inversion. As a starting point, the proposed forward simulation technique decomposes the solution into the sum of separable functions (with respect to randomness and the space), where each term is calculated based on a variational approach. This is similar to Proper Generalized Decomposition (PGD). Next, we apply a multiscale technique to solve for each term (as in ) and, further, decompose the random function into 1D fields. As a result, our proposed method provides an approximation hierarchy for the solution as we increase the number of terms in the expansion and, also, increase the spatial resolution of each term. We use the hierarchical solution distributions in a variational Bayesian approximation to perform uncertainty quantification in the inverse problem. We conduct a detailed numerical study to explore the performance of the proposed uncertainty quantification technique and show the theoretical posterior concentration.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Concrete in engineered barriers for radioactive waste disposal facilities - phenomenological study and assessment of long term performance

The paper aims to highlight recent developments at the Belgian Nuclear Research Centre SCK-CEN in experimental and numerical study of the coupled physical-chemical behaviour of concrete subject to chemical degradation. The discussion mainly focusses on three inter-linked research projects covering novel experimental methods to study the alteration of hydraulic and transport properties during carbonation and calcium leaching, a pore scale numerical model to capture microstructural changes due to the above degradation processes and a generic multiscale model aimed at determining evolution of the properties of a macrostructure over the long term. The paper also describes supplementary continuum scale numerical studies concerning concrete-clay interactions and geochemical impact on the physical structure of concrete. Preliminary findings from these studies show encouraging results such as the development of novel leaching, water permeability and diffusion apparatus, a robust pore scale model based on Lattice-Boltzmann method and a mesoscale study focused on the importance of interfacial transition zones on the effective diffusivity for linear and nonlinear diffusion problems. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

Estimating nonrigid motion from inconsistent intensity with robust shape features

Purpose: To develop a nonrigid motion estimation method that is robust to heterogeneous intensity inconsistencies amongst the image pairs or image sequence. Methods: Intensity and contrast variations, as in dynamic contrast enhanced magnetic resonance imaging, present a considerable challenge to registration methods based on general discrepancy metrics. In this study, the authors propose and validate a novel method that is robust to such variations by utilizing shape features. The geometry of interest (GOI) is represented with a flexible zero level set, segmented via well-behaved regularized optimization. The optimization energy drives the zero level set to high image gradient regions, and regularizes it with area and curvature priors. The resulting shape exhibits high consistency even in the presence of intensity or contrast variations. Subsequently, a multiscale nonrigid registration is performed to seek a regular deformation field that minimizes shape discrepancy in the vicinity of GOIs. Results: To establish the working principle, realistic 2D and 3D images were subject to simulated nonrigid motion and synthetic intensity variations, so as to enable quantitative evaluation of registration performance. The proposed method was benchmarked against three alternative registration approaches, specifically, optical flow, B-spline based mutual information, and multimodality demons. When intensity consistency was satisfied, all methods had comparable registration accuracy for the GOIs. When intensities among registration pairs were inconsistent, however, the proposed method yielded pronounced improvement in registration accuracy, with an approximate fivefold reduction in mean absolute error (MAE = 2.25 mm, SD = 0.98 mm), compared to optical flow (MAE = 9.23 mm, SD = 5.36 mm), B-spline based mutual information (MAE = 9.57 mm, SD = 8.74 mm) and mutimodality demons (MAE = 10.07 mm, SD = 4.03 mm). Applying the proposed method on a real MR image sequence also provided qualitatively appealing results, demonstrating good feasibility and applicability of the proposed method. Conclusions: The authors have developed a novel method to estimate the nonrigid motion of GOIs in the presence of spatial intensity and contrast variations, taking advantage of robust shape features. Quantitative analysis and qualitative evaluation demonstrated good promise of the proposed method. Further clinical assessment and validation is being performed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Multiphase Model of Semisolid Slurry Generation and Isothermal Holding During Cooling Slope Rheoprocessing of A356 Al Alloy

In the present paper, we present an experimentally validated 3D multiphase and multiscale solidification model to understand the transport processes involved during slurry generation with a cooling slope. In this process, superheated liquid alloy is poured at the top of the cooling slope and allowed to flow along the slope under the influence of gravity. As the melt flows down the slope, it progressively loses its superheat, starts solidifying at the melt/slope interface with formation of solid crystals, and eventually exits the slope as semisolid slurry. In the present simulation, the three phases considered are the parent melt as the primary phase, and the solid grains and air as secondary phases. The air phase forms a definable air/liquid melt interface as the free surface. After exiting the slope, the slurry fills an isothermal holding bath maintained at the slope exit temperature, which promotes further globularization of microstructure. The outcomes of the present model include prediction of volume fractions of the three different phases considered, grain evolution, grain growth, size, sphericity and distribution of solid grains, temperature field, velocity field, macrosegregation and microsegregation. In addition, the model is found to be capable of making predictions of morphological evolution of primary grains at the onset of isothermal coarsening. The results obtained from the present simulations are validated by performing quantitative image analysis of micrographs of the rapidly oil-quenched semisolid slurry samples, collected from strategic locations along the slope and from the isothermal slurry holding bath.

36 MATERIALS SCIENCE↗
DOE OSTI2017

A Hybrid Multi-Scale Model of Crystal Plasticity for Handling Stress Concentrations

Microstructural effects become important at regions of stress concentrators such as notches, cracks and contact surfaces. A multiscale model is presented that efficiently captures microstructural details at such critical regions. The approach is based on a multiresolution mesh that includes an explicit microstructure representation at critical regions where stresses are localized. At regions farther away from the stress concentration, a reduced order model that statistically captures the effect of the microstructure is employed. The statistical model is based on a finite element representation of the orientation distribution function (ODF). As an illustrative example, we have applied the multiscaling method to compute the stress intensity factor K I around the crack tip in a wedge-opening load specimen. The approach is verified with an analytical solution within linear elasticity approximation and is then extended to allow modeling of microstructural effects on crack tip plasticity.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Multiscale modeling of spring phenology across Deciduous Forests in the Eastern United States

Abstract Phenological events, such as bud burst, are strongly linked to ecosystem processes in temperate deciduous forests. However, the exact nature and magnitude of how seasonal and interannual variation in air temperatures influence phenology is poorly understood, and model‐based phenology representations fail to capture local‐ to regional‐scale variability arising from differences in species composition. In this paper, we use a combination of surface meteorological data, species composition maps, remote sensing, and ground‐based observations to estimate models that better represent how community‐level species composition affects the phenological response of deciduous broadleaf forests to climate forcing at spatial scales that are typically used in ecosystem models. Using time series of canopy greenness from repeat digital photography, citizen science data from the USA National Phenology Network, and satellite remote sensing‐based observations of phenology, we estimated and tested models that predict the timing of spring leaf emergence across five different deciduous broadleaf forest types in the eastern United States. Specifically, we evaluated two different approaches: (i) using species‐specific models in combination with species composition information to ‘upscale’ model predictions and (ii) using repeat digital photography of forest canopies that observe and integrate the phenological behavior of multiple representative species at each camera site to calibrate a single model for all deciduous broadleaf forests. Our results demonstrate variability in cumulative forcing requirements and photoperiod cues across species and forest types, and show how community composition influences phenological dynamics over large areas. At the same time, the response of different species to spatial and interannual variation in weather is, under the current climate regime, sufficiently similar that the generic deciduous forest model based on repeat digital photography performed comparably to the upscaled species‐specific models. More generally, results from this analysis demonstrate how in situ observation networks and remote sensing data can be used to synergistically calibrate and assess regional parameterizations of phenology in models.

Melaas, Eli K.↗
DOE OSTI2017

Miniaturized Air-to-Refrigerant Heat Exchangers

Air-to-refrigerant Heat eXchangers (HX) are an essential component of Heating, Ventilation, Air-Conditioning, and Refrigeration (HVAC&R) systems, serving as the main heat transfer component. The major limiting factor to HX performance is the large airside thermal resistance. Recent literature aims at improving heat transfer performance by utilizing enhancement methods such as fins and small tube diameters; this has lead to almost exhaustive research on the microchannel HX (MCHX). The objective of this project is to develop a miniaturized air-to-refrigerant HX with at least 20% reduction in volume, material volume, and approach temperature compared to current state-of-the-art multiport flat tube designs and also be capable of production within five years. Moreover, the proposed HX’s are expected to have good water drainage and should succeed in both evaporator and condenser applications. The project leveraged Parallel-Parametrized Computational Fluid Dynamics (PPCFD) and Approximation-Assisted Optimization (AAO) techniques to perform multi-scale analysis and shape optimization with the intent of developing novel HX designs whose thermal-hydraulic performance exceeds that of state-of-the-art MCHX. Nine heat exchanger geometries were initially chosen for detailed analysis, selected from 35+ geometries which were identified in previous work at the University of Maryland, College Park. The newly developed optimization framework was exercised for three design optimization problems: (DP I) 1.0kW radiator, (DP II) 10kW radiator and (DP III) 10kW two-phase HX. DP I consisted of the design and optimization of 1.0kW air-to-water HX’s which exceeded the project requirements of 20% volume/material reduction and 20% better performance. Two prototypes for the 1.0kW HX were prototyped, tested and validated using newly-designed airside and refrigerant side test facilities. DP II, a scaled version DP I for 10kW air-to-water HX applications, also yielded optimized HX designs which met project requirements. Attempts to prototype a 10kW have presented unique manufacturing challenges, especially regarding tube blockages and structural stability. DP III comprised optimizing two-phase HX’s for a 3.0Ton capacity in a heat pump / air-conditioning unit for cooling mode application using R410A as the working fluid. The HX’s theoretically address the project requirements. System-level analysis showed the HX’s achieved up to 15% improvement in COP while also reducing overall unit charge by 30-40%. The project methodology was capable of developing HX’s which can outperform current state-of-the-art MCHX by at least 20% reduction in volume, material volume, and approach temperature. Additionally, the capability for optimization using refrigerant charge as an objective function was developed. The five-year manufacturing feasibility of the proposed HX’s was shown to have a good outlook. Successful prototyping through both conventional manufacturing methods and next generation methods such as additive manufacturing was achieved.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
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↗