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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Security of additive manufacturing: Attack taxonomy and survey

Additive manufacturing (AM) is a rapidly growing, multibillion dollar industry. AM is increasingly being used to manufacture functional parts, including components of safety critical systems in aerospace, automotive, and other industries. This makes AM an attractive attack target. AM Security is a fairly new field of research that addresses this novel threat. Here, this paper serves dual purposes: For researchers just entering AM security, we provide an in-depth introduction to this highly multi-disciplinary research field. And, for active researchers in the field, this paper provides a comprehensive, structured survey of the state of the art as well as our proposal for attack taxonomies.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Organismic materials for beyond von Neumann machines

The elementary basis of intelligence in organisms with a central nervous system includes neurons and synapses and their complex interconnections forming neural circuits. In non-neural organisms such as slime mold with gel-like media, viscosity modulation enables adaptation to changing environments. At a larger scale, collective intelligence emerges via social interactions and feedback in animal colonies. Learning and memory are therefore multi-scale features that evolve as a result of constant interactions with the environment. There is growing interest in emulating such features of intelligence in computing machines and autonomous systems. Materials that can respond to their environment in a manner similar to organisms (referred to as "organismic materials") therefore may be of interest as hardware components in artificial intelligence machines. In this brief review, we present a class of semiconductors called correlated oxides as candidates for learning machines. The term "correlated" refers to the fact that electrons in such lattices strongly interact and the ground state is not what is predicted by classical band theory. Such materials can undergo insulator-metal transitions at near ambient conditions under external stimuli such as thermal or electrical fields, strain, and chemical doping. Depending on the mechanism driving the transition, intermediate states can be metastable with different volatilities, and the time scales of phase change can be controlled over many orders of magnitude. The change in electronic properties can be sharp or gradual, leading to digital or analog behavior. These properties enable the realization of artificial neurons and synapses and emulate the associative and non-associative learning characteristics found in various organisms. We examine microscopic properties concerning electronic and structural transitions leading to collective behavior and theoretical treatments of the ground state and dynamical response, showcasing VO 2 as a model system. Next, we briefly review algorithms designed from the plasticity demonstrated by phase changing systems. Finally, we conclude the brief review with suggestions for future research toward realizing non-von Neumann machines.

42 ENGINEERING↗
DOE OSTI2020

Overview of lithium injection and flowing liquid lithium results from the US–China collaboration on EAST

A multi-institutional team consisting of national labs and universities has been conducting research to understand and control the plasma-material interface (PMI) to improve long pulse discharge control and performance in the EAST device in Hefei, China. One particular focus of the group has been to evaluate the performance of different plasma-facing component (PFC) technologies and materials, particularly lithium. Flowing liquid lithium PFC technologies are currently into their third generation of development and deployment in EAST, demonstrating recycling control and mitigation of edge-localized modes (ELMs). A lithium powder dropper has also been used to control ELMs while a lithium granule injector has demonstrated ELM triggering and pacing. To support this work, the facilities at the Center for Plasma Material Interactions such as HIDRA are being commissioned and utilized to develop/test the technologies before deployment on EAST. This paper will present a summary of the collaborative lithium PMI program on EAST.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Control And Optimization Modular Modeling Application For Nuclear Deployment

The purpose of the COMMAND code is to provide a flexible, scalable tool for use in developing, integrating, and testing the technologies necessary for achieving autonomous operations of advanced nuclear reactors. The code enables users to efficiently implement custom simulations and experiments by combining key methods from different software modules. These modules are focused on: modeling and simulation tools, such as nuclear simulation tools used for high-fidelity modeling (e.g., Reactor Excursion and Leak Analysis Program [RELAP5-3D] and Monte Carlo N-Particle [MCNP]); machine learning and optimization tools (e.g., anomaly detection and data-driven modeling techniques); advanced control in its digital, high-performance, and supervisory control forms (e.g., proportional integral derivative (PID) control and model predictive control (MPC); and integration with hardware through industrial communication protocols. To ensure flexibility and scalability, COMMAND was designed to be both modular—the software “pieces” all inherit from generic building blocks and can be combined and connected to create complicated simulations—and high performing—designed for parallel processing, enabling simulations and experiments to take advantage of multi-core computers, servers, and nodes. The code is written in the Python programming language due to the language's popularity, active community, and open-source and cross-platform nature. Maintaining consistency with other simulation tools used within the nuclear energy community, users implement simulations and experiments through text input files, which define components, parameters, connections, etc., through lines of text. Given that COMMAND is written in Python, these input files are native Python scripts, and so use the standard Python structure and formatting. This also enables users to take advantage of Python's extensive package library to develop custom capabilities for their specific use cases.

Faber, Jacob [Idaho National Laboratory (INL), Ida↗
DOE OSTI2017

Final Report: Utilizing Alternative Fuel Ignition Properties to Improve SI and CI Engine Efficiency

Experimental and modeling studies were completed to explore leveraging physical and chemical fuel properties for improved thermal efficiency of internal combustion engines. Fundamental studies of the ignition chemistry of ethanol and iso-octane blends and constant volume spray chamber studies of gasoline and diesel sprays supported the core research effort which used several reciprocating engine platforms. Single cylinder spark ignition (SI) engine studies were carried out to characterize the impact of ethanol/gasoline, syngas (H 2 and CO)/gasoline and other oxygenate/gasoline blends on engine performance. The results of the single-cylinder engine experiments and other data from the literature were used to train a GT Power model and to develop a knock criteria based on reaction chemistry. The models were used to interpret the experimental results and project future performance. Studies were also carried out using a state of the art, direct injection (DI) turbocharged multi- cylinder engine with piezo-actuated fuel injectors to demonstrate the promising spray and spark timing strategies from single-cylinder engine studies on the multi-cylinder engine. Key outcomes and conclusions of the studies were: 1. Efficiency benefits of ethanol and gasoline fuel blends were consistent and substantial (e.g. 5-8% absolute improvement in gross indicated thermal efficiency (GITE)). 2. The best ethanol/gasoline blend (based on maximum thermal efficiency) was determined by the engine hardware and limits based on component protection (e.g. peak in-cylinder pressure or maximum turbocharger inlet temperature) – and not by knock limits. Blends with <50% ethanol delivered significant thermal efficiency gains with conventional SI hardware while maintain good safety integrity to the engine hardware. 3. Other compositions of fuel blends including syngas (H 2 and CO) and other dilution strategies provided significant efficiency gains as well (e.g. 5% absolute improvement in ITE). 4. When the combination of engine and fuel system is not knock limited, multiple fuel injection events maintain thermal efficiency while improving engine-out emissions (e.g. CO, UHC, and particulate number).

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Distance and Properties of NGC 4993 as the Host Galaxy of the Gravitational-wave Source GW170817

Recently, the optical counterpart of the gravitational-wave source GW170817 has been identified in the NGC 4993 galaxy. Together with evidence from observations in electromagnetic waves, the event has been suggested as a result of a merger of two neutron stars (NSs). We analyze the multi-wavelength data to characterize the host galaxy property and its distance to examine if the properties of NGC 4993 are consistent with this picture. Our analysis shows that NGC 4993 is a bulge-dominated galaxy with r{sub eff}∼2--3 kpc and a Sérsic index of n=3--4 for the bulge component. The spectral energy distribution from 0.15 to 24 μm indicates that this galaxy has no significant ongoing star formation, a mean stellar mass of (0.3--1.2)×10{sup 11} M{sub ⊙}, a mean stellar age greater than ∼3 Gyr, and a metallicity of about 20%–100% of solar abundance. Optical images reveal dust lanes and extended features that suggest a past merging activity. Overall, NGC 4993 has characteristics of normal, but slightly disturbed elliptical galaxies. Furthermore, we derive the distance to NGC 4993 with the fundamental plane relation using 17 parameter sets of 7 different filters and the central stellar velocity dispersion from the literature, finding an angular diameter distance of 37.7 ± 8.7 Mpc. NGC 4993 is similar to some host galaxies of short gamma-ray bursts (GRBs) but much different from those of long GRBs, supporting the picture of GW170817 as a result of the merger of two NSs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Productive Programming of Distributed Systems with the SHAD C++ Library

High-performance computing (HPC) is often perceived as a matter of making large-scale systems (e.g., clusters) run as fast as possible, regardless the required programming effort. However, the idea of "bringing HPC to the masses" has recently emerged. Inspired by this vision, we have designed SHAD, the Scalable High-performance Algorithms and Data-structures library. SHAD is open source software, written in C++, for C++ developers. Unlike other HPC libraries for distributed systems, which rely on SPMD models, SHAD adopts a shared-memory programming abstraction, to make C++ programmers feel at home. Underneath, SHAD manages tasking and data-movements, moving the computation where data resides and taking advantage of asynchrony to tolerate network latency. At the bottom of his stack, SHAD can interface with multiple runtime systems: this not only improves developer’s productivity, by hiding the complexity of such software and of the underlying hardware, but also greatly enhance code portability. Thanks to its abstraction layers, SHAD can indeed target different systems, ranging from laptops to HPC clusters, without any need for modifying the user-level code. We have prototyped and open-sourced the implementation of (a subset of) the C++ standard library (STL) targeting multi-node HPC clusters. Our work allows plain STL-based C++ code to scale on HPC systems, with no need for rewriting the code to exploit the complex hardware. SHAD is available under Apache v2 License at https://github.com/pnnl/SHAD. In this paper we overview the design of the SHAD library, depicting its main components: runtime systems abstractions for tasking; parallel and distributed data-structures; STL-compliant interfaces and algorithms.

Castellana, Vito G.↗
DOE OSTI2021

Assessing the life-cycle environmental impacts of the wood pallet sector in the United States

Wood pallets play a critical role in the movement and storage of goods worldwide. They are an important component in the complex global supply chain and used by almost every industry. It is therefore important to assess the environmental implications of the wood pallet supply chain and identify optimization strategies that can be implemented. In this paper, primary 2018 annual production data collected from U.S. pallet manufacturers were used to develop the first industry-average life-cycle inventory (LCI). A new functional unit was proposed to perform a more refined and accurate environmental life-cycle assessment of the wood pallet supply chain. Using the LCI data developed, a cradle-to-grave industry-average life-cycle impact assessment was performed. This novel approach quantifies environmental impacts of a generic multi-use pallet, including repair and remanufacturing. The total global warming impact was 10.4 kg CO 2 e per 45.4 t of pallet loads of product delivered using wood pallets. The manufacturing stage contributed the most, about 35%, followed by the raw material supply stage. About 41% of total primary energy consumption was from renewable sources, with most sourced from biomass. Fossil fuels comprised about 52% of the total (225 MJ per functional unit) primary energy consumption. Total environmental impact was significantly affected by two main parameters: reference service life and load-bearing capacity. Pallet repair was also found to be an important component of the wood pallet supply chain, which has a low environmental footprint compared with the overall impact of a pallet and enables mitigation of overall impact by extending the reference service life. Finally, at end-of-life, common industry practices demonstrated substantial potential environmental benefits that can minimize overall environmental impact.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Atacama Large Aperture Submillimeter Telescope (AtLAST) science: Resolving the hot and ionized Universe through the Sunyaev-Zeldovich effect

An omnipresent feature of the multi-phase “cosmic web” — the large-scale filamentary backbone of the Universe — is that warm/hot (≳ 10 5 K) ionized gas pervades it. This gas constitutes a relevant contribution to the overall universal matter budget across multiple scales, from the several tens of Mpc-scale intergalactic filaments, to the Mpc intracluster medium (ICM), all the way down to the circumgalactic medium (CGM) surrounding individual galaxies, on scales from ~ 1 kpc up to their respective virial radii (~ 100 kpc). The study of the hot baryonic component of cosmic matter density represents a powerful means for constraining the intertwined evolution of galactic populations and large-scale cosmological structures, for tracing the matter assembly in the Universe and its thermal history. To this end, the Sunyaev-Zeldovich (SZ) effect provides the ideal observational tool for measurements out to the beginnings of structure formation. The SZ effect is caused by the scattering of the photons from the cosmic microwave background off the hot electrons embedded within cosmic structures, and provides a redshift-independent perspective on the thermal and kinematic properties of the warm/hot gas. Still, current and next-generation (sub)millimeter facilities have been providing only a partial view of the SZ Universe due to any combination of: limited angular resolution, spectral coverage, field of view, spatial dynamic range, sensitivity, or all of the above. In this paper, we motivate the development of a wide-field, broad-band, multi-chroic continuum instrument for the Atacama Large Aperture Submillimeter Telescope (AtLAST) by identifying the scientific drivers that will deepen our understanding of the complex thermal evolution of cosmic structures. On a technical side, this will necessarily require efficient multi-wavelength mapping of the SZ signal with an unprecedented spatial dynamic range (from arcsecond to degree scales) and we employ detailed theoretical forecasts to determine the key instrumental constraints for achieving our goals.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

FORCE Update 2024

The Framework for Optimization of Resources and Economics (FORCE) tool suite is the U.S. Department of Energy’s Nuclear Integrated Energy Systems (IES) Program flagship tool suite for technoeconomic IES analysis of IES. This tool suite is useful for analysis designed to evaluate and improve the technoeconomics of energy production systems, particularly for systems including nuclear technology. In this report, we document the development activity for the FORCE tool suite to extend its capabilities as performed during fiscal year 2024. In addition to reliability and accessibility, capability is one of the three standards guiding the development of the FORCE tool suite and the software codes that are its constituent parts. Extending the capabilities of the FORCE tool suite allows analysis both within the IES program as well as industry, university, and laboratory partners to perform analysis with more accuracy, insight, and impactful narrative. Four areas of capability development were the focus of activity this year: economic parameter uncertainty quantification, multiresolution analysis, components-to-optimization workflow automation, and statespace construction workflows for real-time optimal control. In economic parameter uncertainty quantification, the ability of HERON to capture risk due to scenarios (weather and energy demand uncertainty) was expanded to also include uncertainties in financial parameters such as capital cost or operation and maintenance costs. By including these sources of uncertainty, which are sometimes very large compared with scenario uncertainty, HERON is better able to capture the risk posed by investment in various IES technology. Because of this, analysts can also consider the reduction in risks that can be realized by choice of some technologies. In multiresolution analysis, development activity extended on work completed previously. In fiscal year 2023, methods for decomposing time series signals, such as demand, solar and wind availability, and price profiles, were analyzed and down-selected to those most effective at splitting signals into different resolutions. These resolutions allow considering the influence of different energy demand and supply behaviors across different time scales. For example, energy demand might be divided into seasonal, weekly, and hourly profiles. In fiscal year 2024, this preliminary work was extended and implemented within the Risk Analysis Virtual Environment (RAVEN) risk and uncertainty analysis platform, which is used throughout the FORCE framework. This development of the “multi-resolution time series analysis” (MR-TSA) module in RAVEN allows training synthetic history generators on complex time series. These synthetic history generators can then be used in HERON for generating scenarios that represent possible market and weather scenarios that can be analyzed on different time scales. We envision completing this work in the future, implementing multiresolution dispatch optimization strategies that can make the most beneficial use of these stratified time histories. In components-to-optimization workflow development, workflows for translating user inputs of components into algorithms for algebraic optimization were selected and implemented. Similar algorithms within the Holistic Energy Resource Optimization Network (HERON) were separated from the main code base of HERON and gathered with the components-to-optimization workflows in the new Dispatch Optimization Variable Engine (DOVE) software library. This modularization allows FORCE users to analyze dispatch optimization and energy system duty cycles independently of HERON, which previously was a burdensome task. Additionally, these dispatch optimization algorithms, set up in an independent library, can now be used across all software applications within FORCE, especially including the real-time optimal control software Optimization of Real-time Capacity Allocation (ORCA). Allowing FORCE software to share dispatch optimization algorithms within a single library allows for improved software maintenance and reliability. In statespace characterization workflow development, alternative workflows for optimizing dispatch with additional technical accuracy was the focus, particularly to improve the real-time optimization decision making in ORCA. Using algorithms and workflows initially developed for the Feasible Actuator Range Modifier (FARM), workflows for determining the statespace representation of IES were identified and demonstrated. The resulting dispatch optimization required a more robust optimization algorithm than that originally used in HERON (and moved to DOVE), which required adding an alternate workflow to DOVE that can more accurately match the behavior of physical systems using a partial differential equation representation. In conclusion, capability developments in the FORCE tool suite in fiscal year 2024 have improved the ability of the FORCE tool suite to perform

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

A spatial superstructure approach to the optimal design of modular processes and supply chains

Modularity is a design principle that aims to provide flexibility for spatio-temporal assembly/disassembly and reconfiguration of systems. This design principle can be applied to multiscale (hierarchical) manufacturing systems that connect units, processes, facilities, and entire supply chains. Designing modular systems is challenging because of the need to capture spatial interdependencies that arise between system components due to product exchange/transport between components and due to product transformation in such components. In this work, we propose an optimization framework to facilitate the design of modular manufacturing systems. Central to our approach is the concept of a spatial superstructure, which is a graph that captures all possible system configurations and interdependencies between components. The spatial superstructure is a generalization of the notion of a superstructure and of a p-graph used in process design, in that it encodes spatial (geographical) context of the system components. Here, we show that this generalization facilitates the simultaneous design and analysis of processes, facilities, and of supply chains. Our framework aims to select the system topology from the spatial superstructure that minimizes design cost and that maximizes design modularity. We show that this design problem can be cast as a mixed-integer, multi-objective optimization formulation. We demonstrate these capabilities using a case study arising in the design of a plastic waste upcycling supply chain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Boron capture stabilizing the diffusion barriers in a two-step Mo-Si-B coated refractory multi-principal element alloy

A Mo-Si-B based coating has been applied on a refractory multi-principal element alloy (RMPEA) using a two-step coating strategy and has endured more than 750 hours of thermal cycling oxidation exposure between room temperature to 1300°C with a minimal weight change. Here, the formation of the Mo 5 SiB 2 diffusion barrier in the coating prevents the inward diffusion of the coating components. Then, boron is captured by the RMPEA, resulting in the formation of a solid solution X 5 SiB 2 (X= W, Mo, Ta, Nb, V) layer and an RMPEA-B boride layer underneath it that acts as the second diffusion barrier.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Link between light-triggered Mg-banding and chamber formation in the planktic foraminifera Neogloboquadrina dutertrei

Mg/Ca ratios of planktic foraminifera are commonly used to reconstruct past ocean temperatures. However, intrashell Mg/Ca ratios exhibit a pattern of alternating high and low Mg-bands in many species. Whereas mechanisms controlling Mg variability are poorly constrained, recent experiments demonstrate that it is paced by the diurnal light/dark cycle in Orbulina universa , which forms a terminal shell of simple spherical geometry. It is unknown whether Mg-heterogeneity is diurnally paced in species with complex shell morphologies, or is the result of growth processes. Here, we show that high Mg/Ca-calcite also forms at night in cultured specimens of the multi-chambered planktic foraminifera Neogloboquadrina dutertrei . Our results demonstrate that N. dutertrei adds a significant amount of calcite, and nearly all Mg-bands, after the final chamber forms. Furthermore, these results have implications for interpreting patterns of calcification in N. dutertrei, and possibly other foraminifera species, and suggests diurnal Mg-banding is an intrinsic component of biomineralization in planktic foraminifera.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

A critical review on additive manufacturing of refractory alloys from a data analytics perspective- beyond nickel-based superalloys

Refractory alloys (RAs) are promising materials due to their exceptional physicochemical properties, but most research remains at the laboratory scale. For broader adoption, advancements in manufacturing are essential. Because their high stability makes conventional methods like machining and casting difficult, additive manufacturing (AM) is emerging as an effective approach for fabricating refractory alloy components. However, AM's repeated non-equilibrium thermal cycles introduce undesired features (e.g. defects, anisotropic microstructures, and residual stresses), which are magnified due to RAs’ unique properties. This paper comprehensively reviews the state-of-the-art methods of AM for refractory alloys. It explores data analytics techniques to establish design rules based on multi-fidelity experimental and computational methods. Furthermore, it investigates integrated, collaborative efforts to harmonise standalone databases, information, knowledge, and predictive models at multi-physics, multi-stage, and multi-scale. Unlike the existing literature that focuses primarily on material systems or process fundamentals, this work provides an integrated perspective on AM of refractory alloys from a data analytics standpoint, highlighting the roles of integrated computational materials engineering (ICME), verification, validation, and uncertainty quantification (VV&UQ), and digital twin-driven qualification in overcoming data scarcity and accelerating rapid qualification.

Additive manufacturing↗
DOE OSTI2025

Neutrino interaction vertex reconstruction in DUNE with Pandora deep learning

The Pandora Software Development Kit and algorithm libraries perform reconstruction of neutrino interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at the Deep Underground Neutrino Experiment, which will operate four large-scale liquid argon time projection chambers at the far detector site in South Dakota, producing high-resolution images of charged particles emerging from neutrino interactions. While these high-resolution images provide excellent opportunities for physics, the complex topologies require sophisticated pattern recognition capabilities to interpret signals from the detectors as physically meaningful objects that form the inputs to physics analyses. A critical component is the identification of the neutrino interaction vertex. Subsequent reconstruction algorithms use this location to identify the individual primary particles and ensure they each result in a separate reconstructed particle. A new vertex-finding procedure described in this article integrates a U-ResNet neural network performing hit-level classification into the multi-algorithm approach used by Pandora to identify the neutrino interaction vertex. The machine learning solution is seamlessly integrated into a chain of pattern-recognition algorithms. The technique substantially outperforms the previous BDT-based solution, with a more than 20% increase in the efficiency of sub-1 cm vertex reconstruction across all neutrino flavours.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Metal 3D Printing of Low-NOX Fuel Injectors with Integrated Temperature Sensors (Final Technical Report)

This technical report presents the exploration of design and prototyping of an Oxy-fuel injector with integrated temperature sensing capabilities using Additive Manufacturing (AM) technology. The AM process has proven itself as a viable method to fabricate complex shapes for custom-designed metallic components rapidly. The lack of assembly requirements and the virtually unlimited geometrical complexity renders the AM process particularly attractive for fabricating complex energy system components. The unique layer-by-layer fabrication technique allows the embedding of sensors within complex components early in the design process. Sensors can be embedded (without post-production component modifications) in AM-fabricated components through two distinct processes: Stop and Go or Post-Integration. The Stop and Go fabrication process allows sensor placement within a cavity during fabrication; where the process is allowed to continue upon sensor placement. Post-integration process supports selective build of customized compartments for sensors within the part. The Stop and Go process requires an extremely accurate re-alignment of the powder-bed during the restart process. Additionally, metallization and shorting of sensors due to a considerably high temperature of the AM process creates significant fabrication challenges and limit the types of sensors that can be embedded. The Post-Integration of sensors is a practical alternative for components that can be effectively designed and fabricated with pre-built complex sensor compartments without the need for post-production component modifications. The proposed effort aimed at exploring the fabrication of an oxy-fuel injector designed for high-pressure Oxy-Combustion applications (Combustor for Directly Heated Supercritical Power Cycle) with integrated temperature measurement capabilities using the AM technique. Since the current design methodology of injectors is based on conventional fabrication techniques (e.g., multi-step machining and welding processes), a new paradigm of design methodology needs to be developed for their adaptation in the AM fabrication process. One of the most challenging issues addressed in powder bed fusion is the removal of powder from internal channels/cavities as the powder to be removed has been lightly sintered during the fabrication process. In this research, a major task has been assigned to developing and evaluating powder removal techniques that will ultimately be used when removing sintered powder from cavities/channels used for sensor placement. Achieving thorough powder removal will permit the incorporation of intricate cavities, integrated fasteners, or other novel features to incorporate sensors into parts directly post-fabrication – allowing for the novel, AM-based design practices to be developed and employ for sensor integration. The designed injector was initially tested at atmospheric conditions to review its successful operation. The tests were carried out for different firing inputs; with a minimum of 55 kW and a maximum of 275 kW. Later tests were carried out for pressurized conditions between 82 kW to 275 kW firing input. A pressure of 16.35bar was observed in the combustion chamber pressure during the pressurized test of 275 kW firing input; test duration was 15 seconds. Integrated thermocouples within the injector provided temperature data for test operations. The data revealed during the atmospheric condition the injector temperature is almost unaffected by the combustion. However, during the pressurized condition, the injector temperature rapidly up to 205°C within 15 seconds; at a 275 kW firing input.

42 ENGINEERING↗
DOE OSTI2024

Advances in Electrospun Poly(ε-caprolactone)-Based Nanofibrous Scaffolds for Tissue Engineering

Tissue engineering has great potential for the restoration of damaged tissue due to injury or disease. During tissue development, scaffolds provide structural support for cell growth. To grow healthy tissue, the principal components of such scaffolds must be biocompatible and nontoxic. Poly(ε-caprolactone) (PCL) is a biopolymer that has been used as a key component of composite scaffolds for tissue engineering applications due to its mechanical strength and biodegradability. However, PCL alone can have low cell adherence and wettability. Blends of biomaterials can be incorporated to achieve synergistic scaffold properties for tissue engineering. Electrospun PCL-based scaffolds consist of single or blended-composition nanofibers and nanofibers with multi-layered internal architectures (i.e., core-shell nanofibers or multi-layered nanofibers). Nanofiber diameter, composition, and mechanical properties, biocompatibility, and drug-loading capacity are among the tunable properties of electrospun PCL-based scaffolds. Scaffold properties including wettability, mechanical strength, and biocompatibility have been further enhanced with scaffold layering, surface modification, and coating techniques. In this article, we review nanofibrous electrospun PCL-based scaffold fabrication and the applications of PCL-based scaffolds in tissue engineering as reported in the recent literature.

Polymer Science↗
DOE OSTI2020

Time-variable Radio Recombination Line Emission in W49A

We present new Jansky Very Large Array (VLA) images of the central region of the W49A star-forming region at 3.6 cm and at 7 mm at resolutions of 0.″15 (1650 au) and 0.″04 (440 au), respectively. The 3.6 cm data reveal new morphological detail in the ultracompact H ii region population, as well as several previously unknown and unresolved sources. In particular, source A shows elongated, edge-brightened bipolar lobes, indicative of a collimated outflow, and source E is resolved into three spherical components. We also present VLA observations of radio recombination lines at 3.6 cm and 7 mm, and IRAM Northern Extended Millimeter Array (NOEMA) observations at 1.2 mm. Three of the smallest ultracompact H ii regions (sources A, B2, and G2) all show broad kinematic linewidths, with ΔV {sub FWHM} ≳ 40 km s{sup −1}. A multi-line analysis indicates that broad linewidths remain after correcting for pressure broadening effects, suggesting the presence of supersonic flows. Substantial changes in linewidth over the 21 yr time baseline at both 3.6 cm and 7 mm are found for source G2. At 3.6 cm, the linewidth of G2 changed from 31.7 ± 1.8 km s{sup −1} to 55.6 ± 2.7 km s{sup −1}, an increase of +23.9 ± 3.4 km s{sup −1}. The G2 source was previously reported to have shown a 3.6 cm continuum flux density decrease of 40% between 1994 and 2015. This source sits near the center of a very young bipolar outflow whose variability may have produced these changes.

79 ASTRONOMY AND ASTROPHYSICS↗