Modeling of Sagging for 3D printed Layers During the Curing Process
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The capability of producing complex, high performance metal parts on demand has established laser powder bed fusion (LPBF) as a promising additive manufacturing technology, yet deeper understanding of the laser-material interaction is crucial to exploit the potential of the process. By simultaneous in-situ synchrotron x-ray and schlieren imaging, we probe directly the interconnected fluid dynamics of the vapour jet formed by the laser and the depression it produces in the melt pool. The combined imaging shows the formation of a stable plume over stable surface depressions, which becomes chaotic following transition to a full keyhole. We quantify process instability across several parameter sets by analysing keyhole and plume morphologies, and identify a previously unreported threshold of the energy input required for stable line scans. The effect of the powder layer and its impact on process stability is explored. These high-speed visualisations of the fluid mechanics governing LPBF enable us to identify unfavourable process dynamics associated with unwanted porosity, aiding the design of process windows at higher power and speed, and providing the potential for in-process monitoring of process stability.
As the current global pandemic makes abundantly clear, we need a better understanding of infectious disease to safeguard human health, the economy and global security. Modern omics techniques hold the promise of providing a comprehensive understanding of the molecular mechanisms of life, including causes of pathogenesis from infectious disease at the molecular level, but we there is a serious gap in annotation of gene function. For as much as half of the genes and gene products encoded in genomes the molecular and/or cellular function is unknown or only partially understood. Recent innovations in fluorescence microscopy for live cell imaging and genetic engineering make it possible to determine the temporal correlation between molecular events, such as a gene being expressed due to host-pathogen interaction, and cellular events, such as bacterial invasion of immune cells. This is turn allows us to gain new insight as to the molecular and cellular role of individual genes and will enable the discovery and validation of new molecular mechanisms essential for infectious disease. Knowing the molecular mechanisms of disease processes will provide new therapeutic targets or novel countermeasure strategies. We aimed to develop a lattice light sheet fluorescence microscope as a unique resource at LLNL for long time course live cell imaging experiments; to develop the reagents and cell lines needed to monitor molecular events during the course pathogenic bacteria infecting mammalian immune cells; and to demonstrate that we could capture molecular events during an infection. We fully commissioned the LLNL lattice light sheet microscope and conducted initial proof of principle imaging experiments on mammalian immune cells and pathogenic bacteria. It is clear from the experience gained that long time course live cell imaging has tremendous potential to help elucidate molecular mechanisms of host-pathogen interactions and to help annotate gene function, which would establish a basis for new countermeasures. It is also clear that if live cell imaging is to realize its full potential new data processing and analysis tools will need to be developed to facilitate analysis of molecular events within cells; new sample chambers and stages could facilitate studies with a wider range of cell and tissue types; and alternative molecular tagging methods need to be explored to enable more facile engineering of cells labeled with molecular specificity.
Over recent years, ceramic matrix materials such as SiC–SiC and C–C have been gaining interest for use in fusion reactors, light water reactors (LWRs), and high-temperature reactors (HTRs). These materials are good candidates to operate in very high temperature and moderate to high radiation environments. The evaluation of composite materials, in general, is challenging because of variations in precursor materials, variations in the fabrication process across fabricators, and the wide range of potential fiber architectures, to name a few. However, the need to evaluate neutron-irradiated properties adds another layer of complexity, which includes cost, timeline, and specimen size limitations (often associated with irradiation testing). A qualification methodology for the use of ceramic composites is provided in the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code Section III-5-HHB. The methodology is supported by ASTM International (ASTM) guides, which provide a pathway to accomplish this effort. Part of the qualification strategy is for the designer to collect material property data on environmental conditions representative of its design envelope. These data include irradiation effects. This report presents an experimental study and test campaign developed to partially address this gap by providing initial mechanical and physical property data required for design. A variety of different materials using different manufacturing techniques are considered as part of this campaign. The test plan suggests performing a screening or partial irradiation study to assist the designer during the material selection process. The designer can then perform a more comprehensive qualification study if the material performance is promising. This work focuses on the status of the specimen preparations (machining of samples), the current test methods and failure analysis as well as the preparation of irradiation vehicles for the irradiation campaign. The irradiation will be performed at Oak Ridge National Laboratory (ORNL) in the High Flux Isotope Reactor (HFIR) and at Idaho National Laboratory (INL) in the Advanced Test Reactor (ATR).
High-entropy alloys (HEAs) with concentrated solid solutions are conceived to possess a rugged atomic and energy landscape in which dislocation motion necessarily proceeds to accommodate mechanical deformation. Fundamental questions remain as to how rough the energy landscape is and to what extent it can be influenced by the local ordering of their constituent elements. Here, we construct and report the potential energy landscape (PEL) governing screw dislocation motion in refractory HEAs that reveals a hierarchical and multilevel structure with a collection of small basins nested in large metabasin. This striking feature pertaining to HEAs exerts a trapping force and back stress on saddle point activations, retarding dislocation movement. Further, by introducing chemical short-range order, the energy landscape is smoothed but skewed to different degrees that shifts the rate-liming process from kink-glide to kink-pair nucleation. The chemical disorder-roughened PEL in HEAs, analogous to structural disorder induced in metallic glasses, signifies the role of various barrier-hopping processes underlying the extraordinary mechanical behaviors of the two distinct groups of materials.
Using density functional theory combined with the Boltzmann transport equation, we uncover a new class of high-performance thermoelectric materials, i.e., supertetrahedral Ga 4 C-family materials characterized by an ultrahigh thermoelectric figure of merit (ZT), which is produced both by a large power factor and ultralow lattice thermal conductivity. The former is contributed by multiple electronic band degeneracies, flat bands and valley anisotropy, while the latter is contributed both by strong phonon scattering and low phonon group velocity. Furthermore, we find that tensile strain engineering may further suppress lattice thermal conductivity, while well retaining the multi-band degeneracies, valley anisotropy and flat bands. In addition to the band degeneracy, the scattering mechanism of the system can also dominate the power factor in the process of strain implementation. Consequently, a novel thermoelectric phenomenon, i.e., a high thermoelectric figure of merit, is observed in Ca 4 C with a ZT value larger than 4.4 under a small strain ratio (0.75%). In conclusion, our theoretical studies not only uncover a new class of high-performance thermoelectric materials integrating multiple effective mechanisms, but also establish a realistic material plateau to investigate the competitive effect of multiple factors on enhancing the thermoelectric figure of merit.
Abstract Turbine blades generally present surface roughness introduced in the manufacturing process or caused by in-service degradation, which can have a significant impact on aero-thermal performance. A better understanding of the fundamental physical mechanisms arising from the interaction between the roughness and the turbine flow at engine-relevant conditions can provide insights for the design of blades with improved efficiency and longer operational life. To this end, a high-fidelity numerical framework combining a well-validated solver for direct numerical simulation and a second-order accurate immersed boundary method is employed to predict roughness-induced aero-thermal effects on an LS89 high-pressure turbine (HPT) blade at engine-relevant conditions. Different amplitudes and distributions of surface roughness are investigated and a reference smooth-blade simulation under the same flow conditions is conducted for comparison. Roughness of increasing amplitude progressively shifts the blade suction side boundary layer transition upstream, producing larger values of the turbulent kinetic energy and higher total wake losses. The on-surface data-capturing capabilities of the numerical framework provide direct measurements of the heat flux and the skin friction coefficient, hence offering quantitative information between the surface topology and engineering-relevant performance parameters. This work may provide a benchmark for future numerical studies of turbomachinery flows with roughness.
Ducted fuel injection (DFI) is a proposed fuel injection concept for achieving substantial reductions in emissions. In this concept, the fuel is injected through a coannular duct, resulting in increased fuel-air mixing and minimized formation of soot and other unwanted combustion products. Apart from comprehensive experimental investigations on DFI, so far computational studies have been limited to single-point Reynolds-averaged Navier Stokes simulations. Therefore, the objective of this work is to complement these studies by performing large-eddy simulations using a diffuse-interface method to examine the physical mechanisms and combustion processes of DFI, specifically focusing on the mixing process and the effect of fuel-ducting on combustion and pollutant emissions. To this end, finite-rate chemistry simulations are performed of the DFI configuration corresponding to the Engine Combustion Network Spray A injector at transcritical conditions (n-dodecane fuel, 60 bar pressure and 1000 K temperature chamber conditions). A two-equation soot model is employed for the qualitative analysis of soot emissions. Direct comparisons of averaged and instantaneous flow field results with the Spray A configuration are performed to assess the effect of DFI on the first- and second-stage ignition and soot formation. Compared to the free-spray condition, the results show that the DFI case exhibits a combination of (i) increased mass flow rate and entrained air, (ii) larger pressure drop magnitude and flow velocity, and (iii) a closer-to-stoichiometric mixture composition (both globally and locally), each of which is conjectured to contribute toward reduced soot production.
Here, we describe a data-driven, multiscale technique to model reactive wetting of a silver–aluminum alloy on a Kovar™ (Fe-Ni-Co alloy) surface. We employ molecular dynamics simulations to elucidate the dependence of surface tension and wetting angle on the drop’s composition and temperature. A design of computational experiments is used to efficiently generate training data of surface tension and wetting angle from a limited number of molecular dynamics simulations. The simulation results are used to parameterize models of the material’s wetting properties and compute the uncertainty in the models due to limited data. The data-driven models are incorporated into an engineering-scale (continuum) model of a silver–aluminum sessile drop on a Kovar™ substrate. Model predictions of the wetting angle are compared with experiments of pure silver spreading on Kovar™ to quantify the model-form errors introduced by the limited training data versus the simplifications inherent in the molecular dynamics simulations. The paper presents innovations in the determination of “convergence” of noisy MD simulations before they are used to extract the wetting angle and surface tension, and the construction of their models which approximate physio-chemical processes that are left unresolved by the engineering-scale model. Together, these constitute a multiscale approach that integrates molecular-scale information into continuum scale models.
Abstract This research paper focuses on the thermo-hydro-mechanical (THM) modeling of brine migration in a heated borehole test conducted as part of the ongoing Brine Availability Test in Salt (BATS) at the Waste Isolation Pilot Plant (WIPP) in New Mexico. It is a component of the international collaboration project DECOVALEX-2023 (DEvelopment of COupled models and their VALidation against EXperiments), which aims to understand the THM processes governing brine flow in heated rock salt repositories through collaborative analysis by multiple research teams. Using the TOUGH–FLAC simulator, THM simulations were performed and compared with data from the BATS phase 1a. This experiment involved two identical horizontal-borehole arrays, one heated and one serving as a control, both equipped with sensor arrays. Analysis of measurements revealed water flow rate surges during heater power transitions, with the highest jump observed during cooling. Acoustic emission activity exhibited distinct patterns in response to heater power changes, suggesting that damage to rock salt is particularly pronounced during the cooling phase. The THM simulations successfully captured these phenomena, highlighting the significance of thermal effects, brine migration, and mechanical behavior in predicting brine availability in heated and damaged rock salt. Our modeling also revealed the critical interplay between heating and cooling-induced damage and its influence on flow properties, particularly affecting brine inflow estimation. Notably, we found that cooling-induced brine inflow spikes result from increased permeability due to tensile dilatancy. These findings have important implications for the development of robust containment strategies and enhance our understanding of the complex processes involved in repository performance.
Low-temperature plasma catalysis holds promise for electrification of energy-intensive chemical processes such as methane reforming and ammonia synthesis.
With the ever-increasing demand for sustainable energy, alcohol fuels have garnered interest for use in heavy duty engines. The significant infrastructure for ethanol production and blending of ethanol with gasoline make these fuels/fuel blends desirable candidates. However, development of heavy duty engine technology that is capable of burning alcohol fuels while retaining the advantages of traditional diesel combustion requires an improved understanding of the soot formation for these fuels under conditions relevant to mixing-controlled combustion. This work uses an extinction diagnostic to study the sooting tendency of ethanol and gasoline/ethanol blends ranging from E10 to E98 during ignition in a homogeneous environment. Experiments were conducted in a rapid compression machine (RCM) for compressed conditions of 20 ± 1 bar and an approximately constant temperature (± 10K) which was unique for each fuel. For a given soot volume fraction, a linear relationship was observed between ethanol content and the equivalence ratio in which that soot volume fraction was formed. Accounting for the oxygenated nature of ethanol, E85 and E98 fuels produced similar amounts of soot at a given Φ ox, , suggesting other factors outside of fuel oxygen content, such as fuel morphology, impact soot formation. Ignition delay data is reported for compressed pressures of 20 ± 1 bar and compressed temperatures ranging from 633 – 670 K for E10 and 771 – 789 K for E98. Varying pressures for E10 and E98 at conditions producing similar soot volume fractions demonstrated a linear dependence of soot formation on pressure, regardless of if the pressure considered was at top dead center or peak combustion pressure. Furthermore, the data gleaned from this work will be used to select soot models and chemical kinetic mechanisms for RCM simulations to ultimately model heavy duty engine technology with the studied fuels.
An internally-cooled diaphragm for an internally-cooled compressor is provided. The internally-cooled diaphragm may include an annular body configured to cool a process fluid flowing through a fluid pathway of the internally-cooled compressor. The annular body may define a return channel of the fluid pathway, and a cooling pathway in thermal communication with the fluid pathway. The return channel may be configured to at least partially diffuse and de-swirl the process fluid flowing therethrough, and the cooling pathway may be configured to receive a coolant to absorb heat from the process fluid flowing through the return channel.
Earth system models disagree on the future of global soil carbon C, with projections ranging from losses of 70 Pg to gains of 250 Pg by the year 2100 (Todd-Brown et al., 2014). This disagreement is due, in part, to the high degree of uncertainty in the mechanisms that control soil C, the largest dynamic pool of organic C on Earth. It remains unclear how climate change, rising atmospheric CO2 levels, and other environmental changes will combine to affect global soil C. As key engineers of biogeochemical cycling, microbes play a crucial role in soil C responses to these environmental changes. Yet, the path toward representing microbes in soil models remains uncertain. Furthermore, we address four burning questions relevant for modelling microbial ecological, evolutionary, and biogeochemical processes in soils: (1) What is the role of soil microbes in biogeochemical cycling? (2) Does microbial community composition matter for soil carbon cycling? (3) Which ecological and evolutionary processes contribute to functional changes? (4) How should we model microbial eco-evolutionary mechanisms in soil C models?
Process variability during the manufacture of gas turbine engine hot section components can significantly affect the material’s resulting microstructure. In casting, for instance, geometric variation within a component (thin sections versus thick sections, radial location) influences cooling rates and the resulting grain size. The high temperature creep response is known to be sensitive to grain size owing to a diffusional creep mechanism which occurs more readily along grain boundaries. Microstructural variation correspondingly drives mechanical behavior which propagates into component scale performance uncertainty. These factors are essential when planning inspection, maintenance, and repair strategies within a reliability framework. These benefits provide opportunities to increase overall energy efficiency through refined margins. Critically, there is an opportunity to bolster existing data-driven reliability models using physics-driven process-structure-property relations. Here we present recent work establishing a framework for evaluating the probabilistic creep performance of high-temperature materials. A novel microstructure-sensitive crystal plasticity finite element model is established that captures both grain boundary and crystallographic deformation effects. The computationally expensive physics model is calibrated using a statistical approach and this high-fidelity model is subsequently used to train a computationally efficient machine learning surrogate model. The surrogate model is essential for sampling a large ensemble of simulated structure-property pair results. The ensemble data are then mined to extract salient trends to be incorporated into a microstructure-sensitive reliability model. The proposed approach represents a novel way to capture microstructure-sensitive trends from physics-based models within a modern reliability framework.
There is a pressing global need to increase the use of renewable energy sources and limit greenhouse gas emissions. Towards this goal, highly efficient and molecularly selective chemical processes that operate under mild conditions are critical. Plasmonic photocatalysis uses optically resonant metallic nanoparticles and their resulting plasmonic, electronic, and phononic light-matter interactions to drive chemical reactions. The promise of simultaneous high-efficiency and product-selective reactions with plasmon photocatalysis provides a compelling opportunity to rethink how chemistry is achieved. Plasmonic nanoparticles serve as nanoscale ‘antennas’ that enable strong light–matter interactions, surpassing the light-harvesting capabilities one would expect purely from their size. Complex composite structures, combining engineered light harvesters with more chemically active components, are a focal point of current research endeavors. In this review, we provide an overview of recent advances in plasmonic catalysis. We start with a discussion of the relevant mechanisms in photochemical transformations and explain hot-carrier generation and distributions from several ubiquitous plasmonic antennae. Then we highlight three important types of catalytic processes for sustainable chemistry: ammonia synthesis, hydrogen production and CO 2 reduction. To help elucidate the reaction mechanism, both state-of-art electromagnetic calculations and quantum mechanistic calculations are discussed. This review provides insights to better understand the mechanism of plasmonic photocatalysis with a variety of metallic and composite nanostructures toward designing and controlling improved platforms for green chemistry in the future.
Flaring associated natural gas is commonly employed in the oil and gas industry to reduce methane (CH 4 ) emissions but generates carbon dioxide (CO 2 ) and harmful pollutants, significantly contributing to air pollution and posing risks to public health. To mitigate this impact, M2X Energy Inc. has developed a small-scale, modular gas-to-methanol system. This system features an engine reformer that performs fuel-rich partial oxidation of wellhead gas to produce syngas—a mixture of carbon monoxide (CO) and hydrogen (H 2 )—followed by a downstream reactor for methanol synthesis. This study focused on computational fluid dynamics (CFD) modeling of the engine reformer to simulate partial oxidation chemistry, predict the rich-burn operating limit, and assess syngas quality, ultimately aiding in design and operational optimization. The CFD model, developed within a Reynolds-Averaged Navier-Stokes (RANS) turbulence framework, incorporated sub-models for turbulent combustion, a chemical mechanism with polycyclic aromatic hydrocarbon (PAH) pathways, and soot emissions to accurately capture the fuel-rich, turbulent jet ignition and combustion processes. Model validation against experimental data showed good agreement across pre- and main-chamber pressures, apparent heat release rates, and exhaust gas concentrations of key species (H 2 , CO, CO 2 , CH 4 ) for varying intake equivalence ratios. Here, the model identified a rich-burn operating limit near a fuel-air equivalence ratio of 2.35, consistent with experimental observations. Furthermore, syngas quality analysis revealed that extending the rich-burn limit through engine reformer optimization could enhance syngas production, contributing to higher methanol synthesis efficiency.
The fine geometric and topological control afforded by additive manufacturing technologies has enabled the manufacture of architected materials across length scales, and enabling tunable mechanical performance as a function of local and global design. Progress has been made to tune the mechanical response of architected materials through geometry, but understanding how the geometry and processing conditions will inform the microstructure remains a challenge due to the rapid solidification in laser powder bed fusion. This study uses in situ X-ray imaging and electron backscatter diffraction microscopy to demonstrate that the melt pool size, microstructure morphology, and elastic strain distribution is influenced by a combination of lattice geometry and laser processing conditions. These results indicate that within larger melt pools the local thermal gradients are sufficient to enable a columnar-to-equiaxed transition across the melt pool. Furthermore, the solidification mechanisms producing these microstructures are examined across the first 5 ms of melting and solidification, described via in situ high-speed X-ray imaging and mirrored via multiphysics simulation.