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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Virtual Engineering (VE) (vebio)

The Virtual Engineering (VE, vebio) project provides a set of Python modules to enable users to connect mathematical models of unit operations to predict outcomes for an entire chemical process. This VE approach is currently being developed to support the beginning-to-end simulation of the low-temperature conversion of lignocellulosic biomass to a fuel precursor, but the underlying communication functions can be readily extended to connect models from other domains. The models and features currently included in the VE library include a models/simulations for pretreatment, enzymatic hydrolysis, and aerobic bioreaction.

Young, Ethan↗
DOE OSTI2024

A three-dimensional model of terrain-induced updrafts for movement ecology studies

Abstract Background Spatially explicit simulation models of animal movements through the atmosphere necessarily require a representation of the spatial and temporal variation of atmospheric conditions. In particular, for movements of soaring birds that rely extensively on vertical updrafts to avoid flapping flight, accurate and reliable estimation of the vertical component of wind is critical. The interaction between wind and complex terrain shapes both the horizontal and vertical wind fields, highlighting the need to model the coupling between local terrain features and atmospheric conditions at scales relevant to animal movement. Methods In this work, we propose a new empirical model for estimating the orographic updraft field. The model is developed using computational fluid dynamics simulations of canonical atmospheric conditions over moderately complex terrain. To isolate buoyancy and thermal effects, and focus on terrain-induced effects, we use only simulations of a neutrally stratified atmosphere to develop the model. The model, which we name Engineering Vertical Velocity Estimator (EVVE), is simple to implement and is a function of the underlying terrain elevation map, the desired height above ground level (AGL), and wind conditions at a reference height (80 m). We validate the model with data from the Alaiz mountain (Spain) field campaign. Results Compared to observations, the proposed improved model estimates the updrafts at 120 m AGL with a mean error of 0.11 m/s ( $$\sigma =0.28$$ σ = 0.28 m/s), compared to 0.85 m/s ( $$\sigma =0.58$$ σ = 0.58 m/s) for its baseline. For typical land-based wind turbine hub heights of 80 m AGL, the proposed model has a mean error of 0.04 m/s ( $$\sigma =0.25$$ σ = 0.25 m/s), compared to baseline 0.54 m/s ( $$\sigma =0.45$$ σ = 0.45 m/s) estimations. We illustrate an application of the model in movement ecology by comparing simulated tracks and presence maps of golden eagles ( Aquila chrysaetos ) moving across two distinct landscapes. The tracks and presence maps are obtained using a simple heuristic-based movement model, with the updraft field given by the proposed model and a wind vector-based estimation approach that is currently in wide use in movement ecology studies of raptors and other soaring birds. Conclusions We highlight that movement model results can be sensitive to the underlying orographic updraft model, especially in studies of fine-scale movements in regions of complex topography. We suggest adopting the proposed model rather than the wind vector estimation method for studies of soaring bird movements.

17 WIND ENERGY↗
DOE OSTI2023

Image Classification Using Convolutional Neural Networks to Automate Visual Inspection of CCO Containers (Rev. 1)

The Savannah River Site is automating the receipt and inspection of Criticality Control Overpack drums to aid in nuclear waste disposal. The Advanced Engineering group is automating this receipt and inspection process to assist the site’s goals. Part of this process includes visually inspecting CCO drums to ensure that no defects or security risks are present. This research focuses on developing a machine learning model to automatically classify drums as passing or failing inspection. The machine learning model was implemented using the open-source Tensorflow library and uses a Convolutional Neural Network architecture to extract features and differentiate between images. The model was able to achieve an average of 85% accuracy on a dataset of 288 drums. This project’s goal was to prove the validity of computer vision in an automation process and provide a starting place for continued research.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Evaluation of a Reduced-Order Model for IBR Fault Response Representation via OEM Blackbox Models

This paper presents a fully implemented inverter reduced-order-model (ROM) in an EMT simulation (PSCAD) library component for direct user utilization in protection studies. The developed inverter ROM has the following features: Equivalent to a full inverter-based resource (IBR) inverter model with positive- and negative-sequence current formulation and representation. A Python script is developed to fully automate this process, including training data generation, ROM parameter training, updating parameters, and model verification and validation. The ROM is validated using both IEEE 2800-compliant and non-compliant OEM modes in a real-world system, building confidence of its usability by protection engineers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

A deep learning upscaling framework: Reactive transport and mineral precipitation in fracture-matrix systems

Pore-scale modeling has limited applicability at large scales due to its high computational cost. One common approach to upscale pore-scale models is the use of effective medium theories, which homogenize small-scale features in a porous structure and characterize the medium by macroscale properties (e.g., permeability) and equations (e.g., Darcy’s law). However, there are classes of physical processes for which effective medium approximations may become inaccurate, e.g., mineral precipitation and clogging during reactive transport. We have developed a deep learning upscaling framework, in which pore-scale modeling is directly employed in macroscale systems, without relying on effective medium approximations. The upscaling framework is first developed for general multiscale systems and then applied to modeling reactive transport with mineral precipitation in the altered layer in fracture-matrix structures. Solute transport from the fractures to the matrix is modeled as a wall boundary condition for the fractures, which, in turn, is predicted by recurrent neural networks using the concentration histories at the fracture-matrix boundary. Specifically, we consider a meter-scale fracture network embedded in sandstones, where the smallest feature is at the micron scale. Here the proposed framework allows us to span five orders of magnitude in length scales by capturing mineral precipitation in the altered layer of the rock matrix at the pore scale across the entire meter-scale fracture network.

42 ENGINEERING↗
DOE OSTI2025

Tutorial: Machine-Learning-Based CREASE-2D Analysis of 2D SAXS Profiles to Characterize Anisotropic Nanostructures in Soft Materials

We present a tutorial to guide users on how to extend the Computational Reverse Engineering Analysis of Scattering Experiments-2D (CREASE-2D) framework to interpret their experimental two-dimensional small-angle scattering (SAS) data from soft materials (e.g., polymers, peptide amphiphiles, biomolecular fibrils). Unlike most traditional SAS analysis approaches, which typically rely on azimuthally averaged onedimensional (1D) profiles, CREASE-2D utilizes the complete 2D scattering profile to reveal information about anisotropy in the structure. In past applications, CREASE has provided insights into complex structural features, including the cross-sectional shapes of assembled nanostructures and dispersity in these features, which are difficult to discern with existing analytical models. While (1D- ) CREASE has been applied to SANS and SAXS data, this tutorial shares the steps for implementing CREASE-2D using an example of a dipeptide solution system, for which we have SAXS data. We present details for these steps involved in using CREASE-2D to interpret SAXS profiles: how to preprocess SAXS data, define relevant structural features, generate three-dimensional real-space structures for specific values of these features, train a machine learning (ML) surrogate model to predict scattering profiles for given structural features, and optimize these features using genetic algorithms (GA). Then, we use these steps to interpret complex 2DSAXS data collected from dipeptide solutions that, in microscopy images, exhibit nanoscale structures that could be elliptical tubes/ flat tapes/cylinders or a combination of these cross sections. Open-source codes, computational hardware, and software requirements, as well as the strengths and limitations of this protocol, are also presented. We expect researchers working with (soft) biomaterials, peptide amphiphiles, amphiphilic polymer solutions, polymer nanocomposites, and blends of particles/polymers will find this CREASE-2D method and this tutorial of use.

CREASE↗
DOE OSTI2023

Emergence of high piezoelectricity from competing local polar order-disorder in relaxor ferroelectrics

Relaxor ferroelectrics are known for outstanding piezoelectric properties, finding a broad range of applications in advanced electromechanical devices. Decoding the origins of the enhanced properties, however, have long been complicated by the heterogeneous local structures. Here, we employ the advanced big-box refinement method by fitting neutron-, X-ray-based total scattering, and X-ray absorption spectrum simultaneously, to extract local atomic polar displacements and construct 3D polar configurations in the classical relaxor ferroelectric Pb(Mg 1/3 Nb 2/3 )O 3 –PbTiO 3 . Our results demonstrate that prevailing order-disorder character accompanied by the continuous rotation of local polar displacements commands the composition-driven global structure evolution. The omnidirectional local polar disordering appears as an indication of macroscopic relaxor characteristics. Combined with phase-field simulations, it demonstrates that the competing local polar order-disorder between different states with balanced local polar length and direction randomness leads to a flattening free-energy profile over a wide polar length, thus giving rise to high piezoelectricity. Our work clarifies that the critical structural feature required for high piezoelectricity is the competition states of local polar rather than relaxor.

42 ENGINEERING↗
DOE OSTI2020

Synergistic and Antagonistic Effects of Aromatics on the Agglomeration of Gas Hydrates

Abstract Surfactants are often used to stabilize aqueous dispersions. For example, surfactants can be used to prevent hydrate particles from forming large plugs that can clog, and sometimes rupture pipelines. Changes in oil composition, however dramatically affect the performance of said surfactants. In this work we demonstrate that aromatic compounds, dissolved in the hydrocarbon phase, can have both synergistic and antagonistic effects, depending on their molecular structure, with respect to surfactants developed to prevent hydrate agglomerations. While monocyclic aromatics such as benzene were found to disrupt the structure of surfactant films at low surfactant density, they are expelled from the interfacial film at high surfactant density. On the other hand, polycyclic aromatics, in particular pyrene, are found to induce order and stabilize the surfactant films both at low and high surfactant density. Based on our simulation results, polycyclic aromatics could behave as natural anti-agglomerants and enhance the performance of the specific surfactants considered here, while monocyclic aromatics could, in some cases, negatively affect performance. Although limited to the conditions chosen for the present simulations, the results, explained in terms of molecular features, could be valuable for better understanding synergistic and antagonistic effects relevant for stabilizing aqueous dispersions used in diverse applications, ranging from foodstuff to processing of nanomaterials and advanced manufacturing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Freezing water at constant volume and under confinement

Water expands upon freezing. What happens when water is cooled below 0 °C in an undeformable, constant-volume container? This is a fundamental question in materials thermodynamics, and is also relevant in biological, geological, and technological applications in which ice forms under nano-, meso-, or macroscale confinement. Here, we analyze the phase-equilibria and kinetic behaviors of water and ice-1h in an isochoric (constant-volume) system. By making use of the Helmholtz potential F (temperature, volume), in contrast to the Gibbs potential G (temperature, pressure), we demonstrate significant changes in phase behavior when the specific volume of the container is constrained below that of ice-1h. We construct a T–V (temperature–volume) phase diagram for water and ice that features a broad two-phase equilibrium region, and we further derive an isochoric nucleation theory that reveals the existence of a critical confinement volume, on the order of microns, below which ice-1h is kinetically prohibited from forming.

42 ENGINEERING↗
DOE OSTI2025

How Interface Evolution at the Nanoscale Dictates Protonic Ceramic Cell Behavior

Understanding the effects of heterointerfaces in nanodevices remains a challenge in interface engineering for systems applied in solid oxide fuel cells, catalysis, sensors, and memristors [1]. Previous studies have shown that the presence of interfaces in ceramic oxide nanodevices affects their impedance properties compared to bulk systems [2]. In this work, we analyze a thin-film model system designed to study the interfaces between representative electrode and electrolyte materials employed in protonic ceramic electrochemical cells for the reversible conversion of hydrogen o electricity. The investigated device features a 21-layer architecture that alternates between an electrode material PBSCF (PrBa 0.5 Sr 0.5 Co 1.5 Fe 0.5 O 5+ϵ ) and a proton-conducting electrolyte BZY (BaZr 0.8 Y 0.2 O 3-δ ), with uniform 20 nm thickness for each layer. Here, the device was fabricated using Pulsed Laser Deposition (PLD) and supported on a conductive Nb-doped STO (Nb-SrTiO 3 ) substrate.

dos Santos, Gabriel T. [Northwestern University, E↗
DOE OSTI2022

Science Applications of Phased Array Radars

Phased array radars (PARs) are a promising observing technology, at the cusp of being available to the broader meteorological community. PARs offer near instantaneous sampling of the atmosphere with flexible beam forming, multi-functionality, low operational and maintenance costs, and without mechanical inertia limitations. These PAR features are transformative compared to those offered by our current reflector-based meteorological radars. The integration of PARs into meteorological research has the potential to revolutionize the way we observe the atmosphere. The rate of adoption of PARs in research will depend on many factors including i) the need to continue educating the scientific community on the full technical capabilities and trade-offs of PARs through an engaging dialogue with the science and engineering communities and ii) the need to communicate the breadth of scientific bottlenecks that PARs can overcome in atmospheric measurements and the new research avenues that are now possible using PARs in concert with other measurement systems. The former is the subject of a companion article that focuses on PAR technology while the latter is the objective here.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Imaging APO-BMI with Micro X-ray Computed Tomography (CT)

APO-BMI is a high-strength, high-temperature, and low-density foam comprised of 1,2-bis(2-aminophenylthio) ethane (APO-Link, formerly Apocure-601) and 4,4’-bismaleimidodiphenylmethane (BMI) that is used structural applications within the aerospace and weapons manufacturing sectors. APO-link is the diamine reagent used to synthesize BMI, a thermosetting resin. This resin can remain in a molten, flowing state for an extended period of time before crosslinking, allowing addition of glass or carbon microballoons to form its final structure. A portion of the current project was to observe the thermal effects on the structural integrity of the foam associated with exposure to an ion beam. Features within the foam were imaged using micro X-ray computed tomography (CT). The resulting imaging provided evidence that microballoon structure remained mostly intact at the points of failure, indicating that the failure of the material was occurring in the binder material.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Ultra-High Temperature Thermal Barrier Coating Development and Validation

The most effective method to improve industrial gas turbine power is to increase firing temperature. To maintain component durability at these higher temperatures, thermal barrier coatings (TBC’s) are playing an increasing role in protecting turbine hardware. TBC’s have been successfully used on Solar Turbines’ combustor liners and turbine airfoils, but there is a need for TBC’s that can operate at higher temperatures. Based on recent, favorable rig testing experience, Solar recognized that yttrium aluminum garnet (YAG) TBC’s made by the Solution Precursor Plasma Spray Process (SPPS) has great potential for higher turbine temperatures. This testing verified the thermal cycle durability of the SPPS YAG TBC’s, as well as demonstrated that the temperature drop through the SPPS YAG TBC was twice that measured across a companion APS YSZ TBC. The SPPS YAG TBC with the potential for a 200°C improvement in temperature capability represents a materials breakthrough. The SPPS process also produces a number of unique microstructural features that confer superior properties. SPPC TBC’s have ultra-fine splats that increase toughness and erosion resistance, and the process can be tailored to produce through-thickness cracks for strain-tolerance and control porosity for lower thermal conductivity and increase coating abradability. This proposal would include further development of SPPS YAG density-graded coatings, optimization of the application process, and validation of higher temperature capability and durability through rig and engine testing of coated combustion liners and turbine outer air seals. The technology would be advanced from a TRL 3 to a proposed TRL 6 by overcoming processing concerns on efficiency, application distance and optimization of a graded coating without impacting coating durability by demonstrating the coating performance on components in rig and development gas turbine engine testing.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Sustainable production of plastic degrading enzymes

The 21st century faces the challenge of transitioning to a climate-neutral economy. This hurdle will need to be addressed in a myriad of approaches, including all societal spheres, as highlighted in several UN and EU reports, including new and accessed technologies. Among them, biotechnology can play a core role by exploiting its environmental benefits (e.g., substituting fossil-based products and expected greenhouse emission reductions). In some cases, biotech can even outperform fossil counterparts' features (e.g., the biodegradability of some bioplastics). Microalga is an attractive bioplastic feedstock in this scenario since it directly substitutes petroleum and captures CO2. However, albeit its environmental benefits, the microalgal process still needs to be tipped economically and the net-positive ecological impact improved to drive adoption. To that end, we envisioned the use of a green alga as a source of bioplastic feedstock and industrial enzymes, combining natural traits of microalgae with engineered properties in a resourceful process to petroleum-based products replacement. As proof of concept, we demonstrated that we could use C. reinhardtii, a green algae, to produce plastic-degrading enzymes. We assemble a vector to secrete PHL7, a recently described PETase, capable of degrading post-consumer PET plastic. We successfully engineered the cell line to secrete the plastic-degrading enzyme. We confirmed the secretion of the enzyme by observing halos in agar plates supplemented with plastic dispersions, enzymatic assays, zymograms, and protein sequencing of supernatant samples. This approach allows using green algae to replace petrochemical-derived plastic while producing the tool necessary to recycle existing plastics sustainably.

Dutra Molino, Joao Vitor↗
DOE OSTI2026

Towards libraries of different ultrasmall amorphous silica cage topologies

Cage topology controlled at the nanometer length scale is expected to enable original functionalities, e.g., in catalysis and therapeutics. Cages are fundamental structural motifs of clathrates and their topological duals, Frank-Kasper phases, and are constituents of mesoporous silica frameworks. However, with one exception, they have not been synthesized as discrete particles. By varying reactant ratios of surfactant, oil, and silane, we report the discovery of 5(12)6(2) and 5(12)6(8) amorphous silica polyhedra, each coexisting with the previously identified 5(12) cage, using combined cryo-transmission electron microscopy (cryo-TEM) and single-particle reconstruction (SPR). Notably, the 5(12)6(8) polyhedron represents a topology not previously observed in mesoporous silica frameworks. Control over structural features is demonstrated, and insights into cage formation mechanisms are provided. Structural outcomes are summarized in a ternary morphology diagram alongside prior results, bridging serendipitous discovery and intentional design of silica cages displaying a level of control over silica polymerization rivaling nature.

Jang, Dong June [Department of Materials Science a↗
DOE OSTI2023

Lessons Learned From Ventilation and Glovebox Flooding Via Overfilling of the Wet Vacuum System in a Plutonium Facility

In the summer of 2021, operations personnel requested maintenance personnel to fill a wet vacuum (Wetvac) seal water tank in a plutonium facility at Los Alamos National Laboratory (LANL). After the filling was finished, the fill valve of the Wetvac seal water tank was left open and a ‘dead-man’ valve on an isolation line failed to close properly. After a series of other failures, the water exited the glovebox and contaminated three rooms of the first floor of the facility and an underlying area in the basement. A retrospective analysis of this event determined that there was no risk of a criticality due to the inherent design features of the ventilation system. This paper will explain the driving factors behind how this event was able to happen, as well as some of the major lessons learned that can be universally applied to other nuclear facilities. One of the main causes of the event was the delegation of work to maintenance personnel that were not qualified for the work being asked of them. Additionally, there was a lack of coordination between criticality safety engineers and facility operations equipment owners regarding equipment and connections present on the seal water tanks for the Wetvac, specifically the presence of overflow drain lines. The respective criticality safety evaluation credited an overflow drain line being present on the seal water tanks that was later found to have not been present. Lastly, there are lessons to be learned regarding equipment configuration and designing systems with safety in mind.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Approaches for the Simulation of Coupled Processes in Evolving Fractured Porous Media Enabled by Exascale Computing

Models have historically represented fractured porous media with continuum descriptions that characterize the media using bulk parameters. The impact of small-scale features is not captured in these models, although they may be controlling the performance of subsurface applications. Pore-scale models can simulate processes in small-scale features by representing the pore space geometry explicitly but are computationally expensive for large domains. The alternative multiscale approach entails the combination of pore-scale and continuum-scale descriptions in a single framework. We use Chombo-Crunch, a computational capability that discretizes complex geometries with an adaptive, embedded boundary method to contrast these two approaches. Chombo-Crunch takes advantage of recent computational performance and memory bandwidth improvements resulting from the emergence of exascale computing resources. These combined improvements enable the efficient simulation of reactive transport in fractured media with a high degree of fidelity and the ability to capture the control small-scale processes exert on the overall medium evolution.

42 ENGINEERING↗