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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

How Snow Aggregate Ellipsoid Shape and Orientation Variability Affects Fall Speed and Self-Aggregation Rates

Snow aggregate shapes and orientations have long been known to exhibit substantial variability. Despite this observed variability, most weather and climate prediction models use fixed power-law functions that deterministically map particle size to mass and fall speed. As such, integrated quantities like precipitation and self-aggregation rates currently ignore nonlinear effects resulting from variation in shape and orientation for aggregates of the same size. This study therefore develops an analytic framework that couples an empirically based bivariate distribution of ellipsoid shapes to classical hydrodynamic theory so as to capture an appropriate dispersion of masses, projected areas, and fall speeds for an assumed size distribution. For a fixed aggregate size, shape variations produce approximately ±0.13 m s -1 standard deviation of fall speed which increases the mass flux fall speed dispersion by more than 100% over traditional microphysics models. This increased fall speed dispersion results predominantly from shape-induced mass dispersion whereas orientation and drag dispersion play a lesser role. Shape variations can increase mass- and reflectivity-weighted fall speeds by up to 60% of traditional models whereas self-aggregation rates can increase by a factor of 100 for very small slope parameters. This implies that aggregate shape variations effectively forestall the theorized onset of fall speed distribution narrowing and subsequent quenching of the aggregation process. As a result, it is likely that secondary ice formation is necessary to prevent an ever decreasing slope parameter. The mathematical theory presented in this study is used to develop simple correction factors for snow forecast and climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The Ice Particle and Aggregate Simulator (IPAS). Part III: Verification and Analysis of Ice–Aggregate and Aggregate–Aggregate Collection for Microphysical Parameterization

Abstract The Ice Particle and Aggregate Simulator (IPAS) is used to theoretically represent the aggregation process of ice crystals. Aggregates have a variety of formations based on initial ice particle size, shape, and falling orientation, all of which influence water phase partitioning. Aggregate dimensional properties and density changes are calculated for monomer–monomer (MON–MON), monomer–aggregate (MON–AGG), and aggregate–aggregate (AGG–AGG) collection to be used by ice-microphysical models for improvement in aggregation parameterizations. Aggregates are chosen from a database of 9 744 000 preformed combinations to be further collected (see Part II). AGG–AGG collection results in more extreme and a smaller range of aggregate aspect ratios than MON–AGG collection. A majority of aggregates are closer to prolate than oblate spheroids, regardless of collection type, except for quasi-horizontally oriented particles that have extreme aspect ratios to begin with. MON–AGG collection frequently results in an increase in density upon collection, whereas MON–MON and AGG–AGG collection almost always result in particle density decreases, with extreme reductions near 99% for MON–MON collection. MON–MON collection results in the greatest decreases in density but then quickly becomes unaffected by the addition of more monomers due to inherent size differences between monomers and aggregates. Finally, a holistic analysis to in situ observations of cloud particle images is presented. IPAS 2D aspect ratios surround a median value of 0.6 and closely follow that of previous studies while varying by no more than ≈12% on average from observed aggregates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Not All Aggregates Are Made the Same: Distinct Structures of Solution Aggregates Drastically Modulate Assembly Pathways, Morphology, and Electronic Properties of Conjugated Polymers

Abstract Tuning structures of solution‐state aggregation and aggregation‐mediated assembly pathways of conjugated polymers is crucial for optimizing their solid‐state morphology and charge‐transport property. However, it remains challenging to unravel and control the exact structures of solution aggregates, let alone to modulate assembly pathways in a controlled fashion. Herein, aggregate structures of an isoindigo–bithiophene‐based polymer (PII‐2T) are modulated by tuning selectivity of the solvent toward the side chain versus the backbone, which leads to three distinct assembly pathways: direct crystallization from side‐chain‐associated amorphous aggregates, chiral liquid crystal (LC)‐mediated assembly from semicrystalline aggregates with side‐chain and backbone stacking, and random agglomeration from backbone‐stacked semicrystalline aggregates. Importantly, it is demonstrated that the amorphous solution aggregates, compared with semicrystalline ones, lead to significantly improved alignment and reduced paracrystalline disorder in the solid state due to direct crystallization during the meniscus‐guided coating process. Alignment quantified by the dichroic ratio is enhanced by up to 14‐fold, and the charge‐carrier mobility increases by a maximum of 20‐fold in films printed from amorphous aggregates compared to those from semicrystalline aggregates. This work shows that by tuning the precise structure of solution aggregates, the assembly pathways and the resulting thin‐film morphology and device properties can be drastically tuned.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The Ice Particle and Aggregate Simulator (IPAS). Part II: Analysis of a Database of Theoretical Aggregates for Microphysical Parameterization

Abstract Bulk ice-microphysical models parameterize the dynamic evolution of ice particles from advection, collection, and sedimentation through a cloud layer to the surface. Frozen hydrometeors can grow to acquire a multitude of shapes and sizes, which influence the distribution of mass within cloud systems. Aggregates, defined herein as the collection of ice particles, have a variety of formations based on initial ice particle size, shape, falling orientation, and the number of particles that collect. This work focuses on using the Ice Particle and Aggregate Simulator (IPAS) as a statistical tool to repetitively collect ice crystals of identical properties to derive bulk aggregate characteristics. A database of 9 744 000 aggregates is generated with resulting properties analyzed. After 150 single ice crystals (monomers) collect, the most extreme aggregate aspect ratio calculations asymptote toward and ϕ ca ≈ 0.50 for aggregates composed of quasi-horizontally oriented and randomly oriented monomers, respectively. The results presented are largely consistent with both a previous theoretical study and estimates derived from ground-based observations from two different geographic locations. Particle falling orientation highly influences newly formed aggregate aspect ratios from the collection of particles with extreme aspect ratios; quasi-horizontally oriented particles can produce aggregate aspect ratios an order of magnitude more extreme than randomly oriented particles but can also produce near-spherical aggregates as the number of monomers comprising the aggregate reach approximately 100. Finally, a majority of collections result in aggregates that are closer to prolate than oblate spheroids.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Thermodynamic Properties of Aggregate Coated by Different Types of Waste Plastic: Adhesion and Moisture Resistance of Asphalt-Aggregate Systems

The utilization of acidic aggregates in hot-mix asphalt (HMA) is often inevitable due to the limited supply of locally available aggregates, posing a potential threat of moisture damage to asphalt pavements. In this regard, the use of urban waste plastic to coat the low-quality aggregates is a promising way to improve the moisture resistance. This study fundamentally evaluated the compatibility between asphalt and plastic-coated aggregate by measuring surface energy, and for the first time compared the effects of different types of waste plastic including high-density polyethylene (HDPE), low-density polyethylene (LDPE), polyethylene terephthalate (PET), polyvinyl chloride (PVC), and polypropylene (PP). The plastic-coating significantly altered the chemistry of aggregate surface by increasing the nonpolar components and reducing the polar components. Such changes remarkably increased the dry adhesion energy between asphalt and aggregate and enhanced the wettability of aggregate. For the acidic aggregates, the polymeric treatment could decrease the value of wet adhesive, which indicated the debonding tendency in the presence of water was reduced. Finally, the energy ratios of the asphalt-aggregate combinations significantly increased by the surface pretreatment, which proved the effect of waste plastic coating on improving the moisture damage resistance of asphalt mixtures. By comparison, the HDPE coating was the most effective way to enhance the compatibility with asphalt, followed by PP and LDPE coatings. The PVC and PET coatings were investigated as the least effective way. In conclusion, this study cannot only contribute to the potential large-scale utilization of waste plastic but also remove the obstacles of using large quantities of acidic natural aggregate in asphalt pavements.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A Comparison of Classical and Aggregation-Based Algebraic Multigrid Preconditioners for High-Fidelity Simulation of Wind Turbine Incompressible Flows

This paper presents a comparison of parallel strong scaling performance of classical and aggregation algebraic multigrid (AMG) preconditioners in the context of wind turbine simulations. Fluid motion is governed by the incompressible Navier--Stokes equations, discretized in space with control-volume finite elements and in time with an inexact projection scheme using an implicit integrator. A discontinuous-Galerkin sliding-mesh algorithm captures rotor motion. The momentum equations are solved with iterative Krylov methods, preconditioned by symmetric Gauss--Seidel (SGS) in Trilinos and $\ell_1$ SGS in hypre. The mass-continuity equation is solved with GMRES preconditioned by AMG and can account for the majority of simulation time. Reducing this continuity solve time is crucial. Wind turbine simulations present two unique challenges for AMG preconditioned solvers: the computational meshes include strongly anisotropic elements, and mesh motion requires matrix reinitialization and computation of preconditioners at each time step. Detailed timing profiles are presented and analyzed, and best practices are discussed for both classical and aggregation-based AMG. Results are presented for simulations of two different wind turbines with up to 6 billion grid points on two different computer architectures. For moving mesh problems that require linear-system reinitialization, the well-established strategy of amortizing preconditioner setup costs over a large number of time steps to reduce the solve time is no longer valid. Instead, results show that faster time to solution is achieved by reducing preconditioner setup costs at the expense of linear-system solve costs. Standard smoothed aggregation with Chebyshev relaxation was found to perform poorly when compared with classical AMG in terms of solve time and robustness. However, plain aggregation was comparable to classical AMG.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Simultaneous Insight into Dissolution and Aggregation of Metal Sulfide Nanoparticles through Single-Particle Inductively Coupled Plasma Mass Spectrometry

Nanoparticles (NPs) and their colloidal aggregates are ubiquitous and play important roles in the transport and release of metals. Knowledge of their dissolution rates and aggregation behavior in solution are crucial for better prediction of their fate in biogeochemical cycling, ecotoxicity, and environmental remediation. There are however significant technical challenges to accurately obtain such information as a result of the heterogeneity and highly dynamic transformation exhibited by NPs, particularly at relatively low particle concentrations in aqueous systems. Here, we quantitatively examine the simultaneous dissolution and aggregation behavior of metal sulfide NPs using single-particle inductively coupled plasma mass spectrometry (spICP–MS). We focus on nickel sulfide (NiS), with additional data presented for copper sulfide (CuS) and cobalt sulfide (CoS). The kinetics of metal release (dissolution and disaggregation) of NiS was fastest under strongly oxidizing conditions (from 0.04 to >3 min –1 with H 2 O 2 ) and were slower under near-neutral (HEPES buffer/H 2 O) and acidic (1 mM HNO 3 ) conditions (≤0.006 min –1 ). Metal release kinetics in HNO 3 was not faster than in H 2 O or HEPES, suggesting that the solution pH has an influence over both the dissolution kinetics of individual particles and the NP aggregation states, which in combination affect metal release rates over time. Between different metal sulfides, the measured metal release rates were largely consistent with predictions based on the crystallinity, solubility products, and specific surface areas of the NPs, following an order of CoS > NiS > CuS. Here, the spICP–MS approach described here can be easily applied to the characterization of metal release and aggregation of other NPs at low concentrations (~10 5 particles/mL) typically found in natural environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Validation on Aggregate Flexibility from Residential Air Conditioning Systems for Building-to-Grid Integration

To facilitate the integration of buildings to the power grid, battery-equivalent models have been proposed to characterize and quantify aggregate flexibility from building loads. An analytical method has been proposed to construct such a flexibility model for thermostatically controlled loads. Since this analytical method is derived from a simplified representation of building thermal dynamics, it is necessary to evaluate the resulting flexibility model in a more realistic context. This paper focuses on the validation of this analytical method for estimating aggregate flexibility from residential air conditioning (ACs) systems. A high-fidelity model is first developed to mimic thermal behaviors of a residential AC system through a co-simulation between Modelica and EnergyPlus. A population of virtual residential AC systems is then generated by randomizing parameters of the high-fidelity model. Finally, an aggregate flexibility model is constructed for the residential AC population using the analytical method and validated using results from simulation of the high-fidelity model. It is found that the flexibility estimated using the analytical method is with reasonable accuracy, but can be improved by explicitly incorporating heat gains into the method.

Huang, Sen↗
DOE OSTI2021

Effects of Cement Changes and Aggregate System on Mechanical Properties of Concrete

In this paper, mechanical properties of concrete mixtures containing different cementitious combinations and two aggregate systems were investigated under plastic and drying conditions. Emphasis was laid on durability and shrinkage of concrete. Life Cycle Analysis was also conducted by using Green Concrete LCA Webtool. Results indicated that the presence of larger aggregate sizes tend to enhance durability of concrete. The presence of nanosilica also imparted superior mechanical properties to concrete. A cementitious combination containing Portland Limestone Cement and fly ash with larger aggregate sizes emerged as a better performing mixture in terms of mechanical properties and with minimum environmental impact.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Texture Development and Stress–Strain Partitioning in Periclase + Halite Aggregates

Multiphase materials are widely applied in engineering due to desirable mechanical properties and are of interest to geoscience as rocks are multiphase. High-pressure mechanical behavior is important for understanding the deep Earth where rocks deform at extreme pressure and temperature. In order to systematically study the underlying physics of multiphase deformation at high pressure, we perform diamond anvil cell deformation experiments on MgO + NaCl aggregates with varying phase proportions. Lattice strain and texture evolution are recorded using in-situ synchrotron x-ray diffraction and are modeled using two-phase elasto-viscoplastic self-consistent (EVPSC) simulations to deduce stress, strain, and deformation mechanisms in individual phases and the aggregate. Texture development of MgO and NaCl are affected by phase proportions. In NaCl, a (100) compression texture is observed when small amounts of MgO are present. In contrast, when deformed as a single phase or when large amounts of MgO are present, NaCl develops a (110) texture. Stress and strain evolution in MgO and NaCl also show different trends with varying phase proportions. Based on the results from this study, we construct a general scheme of stress evolution as a function of phase proportion for individual phases and the aggregate.

Lin, Feng↗
DOE OSTI2021

Virtual Battery Aggregator (Virtual Battery Aggregator for Distributed Energy Resource Management Systems)

Distributed energy resource management systems (DERMS) are being deployed in feeders with high distributed energy resource (DER) penetration to provide visibility of DERs and enable DER control strategies for grid operators. DERMS can support centralized grid controls by aggregating individual DER information into a single virtual DER model. This codebase creates algorithms for a DERMS platform that are able to aggregate a set of DERs that can be modeled as batteries, create a virtual battery model for centralized grid controls, and dispatch power setpoints to the individual DERs based on a desired virtual power setpoint received from the centralized grid control. It integrates with existing co-simulation frameworks and models for buildings, DERs, and distribution systems. While the DERMS is designed to work with batteries, it can be used with any DER that can be defined by a generalized battery model.

Blonsky, Michael↗