Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “additives”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Additive and Subtractive Manufacturing Augmented Reality Interface (ASMARI)

Industry 4.0 represents the next evolution of industrial technology. Some of the key characteristics of Industry 4.0 include augmented reality and additive manufacturing. In support of this evolution, researchers at Oak Ridge National Lab created a prototype augmented reality (AR) interface, ASMARI. This prototype acts as a common interface for both industrial additive and subtractive machines. Additionally, in the changing industrial workspace of Industry 4.0, the role of humans will also change. This interface focuses on increasing productivity and situational awareness, while providing new interaction modalities for interacting with hardware. The prototype was also evaluated by multiple users who provided positive feedback on the system. Ultimately, the prototype represents a first step towards significant integration between augmented reality and additive manufacturing.

Borish, Michael↗
DOE OSTI2022

Impacts of the Additive Manufacturing Process on the Roughness of Engine Scale Vanes and Cooling Channels

Abstract By leveraging the additive manufacturing (AM) platform, development time and costs for turbine component testing can be reduced relative to traditional investment casting. Surface roughness is a key characteristic of the additive manufacturing process that can impact flow, heat transfer, and mechanical integrity of printed components. There are multiple design and build considerations that result in variability in surface roughness, especially when additively fabricating complicated three-dimensional vanes and internal cooling passages. This study characterizes the surface roughness of internal cooling passages, vanes, and flat external surface samples made using additive manufacturing, specifically the direct metal laser sintering process. The samples were manufactured with various wall thicknesses, layer thicknesses, build locations, build directions, and on different AM machines. A combination of computed tomography scanning and optical profilometry was used to evaluate surface roughness levels. The data indicate that the dominant factors in roughness for a given layer thickness are a function of wall thickness, build location, and build direction.

Engineering↗
DOE OSTI2023

Printability and Overall Cooling Performance of Additively Manufactured Holes With Inlet and Exit Rounding

Abstract To improve cooling effectiveness of gas turbine hardware, various film cooling hole shapes have previously been researched. Unique design modifications have recently been made possible through the design freedom allotted by additive manufacturing (AM). As one example, creating a rounded inlet for a film-cooling hole can mitigate separation at the inlet. This study explores various geometric features by exploiting the uses of additive manufacturing for shaped film cooling holes at engine scale. Both printability and cooling performance were evaluated. Resulting from this study, additively manufactured holes with hole inlet and exit rounding were printed with some variations from the design intent (DI). The largest deviations from the design intent occurred from dross roughness features located on the leeward side of the hole inlet. The measured overall effectiveness indicated that an as-built inlet fillet decreased in-hole convection as well as decreased jet mixing compared to the as-built sharp inlet. Including an exit fillet, which prevented an overbuilt diffuser exit, was also found to decrease jet mixing. A particular insight gained from this study is the importance of the convective cooling within the hole to the overall cooling performance. In-hole roughness, which is a result of additive manufacturing, increased convective cooling within the holes but also increased jet mixing as the coolant exited the hole. The increased jet mixing caused low overall effectiveness downstream of injection.

Engineering↗
DOE OSTI2023

Experimental and Numerical Investigation of Flow Boiling in Additive Manufactured Foam Structures With Vapor Pathways

Abstract The unique properties of metal foams make them potential candidates for a range of applications, including microsystem thermal management. Using additive manufacturing to create foam-type structures can improve upon prior thermal solutions by eliminating thermal interface materials and allowing for customization/local control of parameters. In the present investigation, flow boiling in additive-manufactured metal foams is investigated both experimentally and numerically. Two test samples, one with uniform structure and the other with pathways for vapor removal, are compared both experimentally and numerically. A conjugate computational fluid dynamics and heat transfer (CFD-HT) model utilizing a three-dimensional volume of fluid (VOF) model with accompanying evaporation/condensation model provided in-depth visualization of the boiling flow phenomena. The experiments generated the thermohydraulic performance over a range of heat fluxes, demonstrating that the sample incorporating dedicated vapor pathways performed better in both pressure and heat transfer performance metrics compared to the uniform foam. Additionally, negative system-level effects (i.e., hydraulic oscillations) were shown to be abated using the vapor removal structures. The numerical model yielded further insight into the factors contributing to the improved performance. Results indicated the pathways functioned as vapor removal channels, allowing the generated vapor to vent from the foam structure into the lanes. Further computational investigations demonstrated changes in flow regimes, where the addition of vapor channels caused the flow to change from churn to annular. Bubble behavior unique to the vapor pathway structure was studied, showing stagnant regions that eject vapor into the channel.

Engineering↗
DOE OSTI2020

Construction-Scale Concrete Additive Manufacturing and its Application in Infrastructure Energy Storage

Construction is filled with labor intensive, hazardous, and often wasteful processes. It is also an enormous industry, so improvements in efficiency could have a tremendous economic impact. Construction-scale additive manufacturing is one path toward achieving those improvements. In this paper, a construction-scale additive manufacturing system, called Sky-BAAM, is presented. In addition to possibly leading to more energy-efficient construction practices, leveraging additive manufacturing in construction opens the solution space to more energy efficient building design. One such design, the EMPOWER wall, is also presented in this paper. The exterior of the wall is shaped to maximize heat transfer, while acting as form work for an internal energy-storage system. This allows energy to be stored in the wall during off-peak times and retrieved during peak periods.

Atkins, Celeste↗
DOE OSTI2020

Effects of O 2 addition on in-plasma photo-assisted etching of Si with chlorine

Addition of oxygen was used to control the in-plasma photo-assisted etching (PAE) of p-type Si(100) and poly-Si in a high density, inductively coupled, Faraday-shielded, Ar/Cl 2 (225/25 SCCM), 60 mTorr plasma. After etching, samples were transferred under vacuum to an UHV x-ray photoelectron spectroscopy chamber for surface analysis. Samples etched under PAE conditions (ion energies below the ionassisted etching, IAE, threshold) had a thicker surface oxide and lower [Cl] surface concentration, when compared to samples etched under IAE conditions (ion energies above the IAE threshold). PAE was found not to be affected by 0.1 or 0.25 SCCM O 2 addition, while etching stopped with more than 0.5 SCCM O 2 addition. IAE with RF power on the sample stage, resulting in -65 V self-bias, was not affected by up to 2 SCCM of oxygen addition but decreased rapidly when more than 5 SCCM O 2 was added to the plasma. These results imply that PAE may be completely suppressed, while IAE occurs unobstructed. The implications of these findings are discussed in view of applications involving continuous wave and pulsed-plasma processes.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Performance Improvement of Lithium Metal Batteries Enabled By LiBF 3 CN as a New Electrolyte Additive

A newly synthesized electrolyte additive, lithium trifluoro(cyano) borate (LiBF 3 CN), has been investigated for electrochemical performance improvement of lithium metal batteries. The LiBF 3 CN has a structure where one fluorine atom of BF 4 – is substituted with a cyano group (–CN) prepared by the reaction of boron trifluoride etherate with lithium cyanide. The electrochemical performance in symmetric Li/Li cells and NCM523/Li cells is significantly improved upon the incorporation of LiBF 3 CN as an electrolyte additive into a carbonate-based electrolyte. Extensive characterization of the deposited lithium metal reveals that a thin (≈20 nm) and robust SEI composed of LiN x O y , Li 3 N and Li 2 O is formed by the reductive decomposition of the LiBF 3 CN additive, which plays an important role in decreasing the resistance and stabilizing lithium deposition/stripping. The insight into the substitution effect of a functional group obtained from this work provides guidance for the design of new electrolyte additives.

25 ENERGY STORAGE↗
DOE OSTI2024

Impact of Electrolyte Additives on the Lifetime of High Voltage NMC Lithium-Ion Pouch Cells

This work involves improving the lifetime of lithium-ion cells during high voltage cycling using electrolyte additives. Three generations of electrolyte additives were investigated and screened in NMC442/graphite pouch cells using a 24 h voltage-hold protocol at 40 degrees C to accelerate oxidative reactions occurring at 4.4 V. Once promising additives and combinations were identified, they were then tested in cobalt-free NMC640/graphite cells for long-term cycling to upper cutoff voltages of 4.3, 4.4, and 4.5 V at temperatures of 20, 40, and 55 degrees C. Degradation mechanisms were probed using dV/dQ analysis, micro-X-ray fluorescence spectroscopy, and electrochemical impedance spectroscopy. The primary failure mode of cells held at high voltages is due to increase in cell impedance, which is correlated to the dissolution of transition metals, specifically manganese, originating from the positive electrode. We believe this dissolution is presumably due to the formation of a high impedance rock salt surface layer on the NMC positive electrode particles. Such deleterious outcomes can be limited by selecting an appropriate electrolyte additive package. It is hoped that this paper can provide a starting point for developing NMC Li-ion cells that can operate to voltages as high as 4.4 V and still display long lifetimes.

Azam, Saad↗
DOE OSTI2022

Application of Linear Additive Conditions for Near-Infrared Diffuse Reflectance Absorption Spectroscopy

Determining the homogeneity of material mixing in real time during product processing is critical for quality control. According to the Kubelka–Munk (K-M) function of diffuse reflectance absorption spectrum, absorbance (A) is approximately linear with the content of the components when the sample scattering coefficient (S) is in a certain range. The S is determined by the particle size of powder samples. Therefore, this study determined particle size ranges that satisfy linear additivity in near-infrared diffuse reflectance spectroscopy (NIRDRS). Thus, the proposed NIRDRS analysis technique can be used to determine the homogeneity of material mixes or analyze the percentages of the components in the mixture. In this study, vitamin B3 and vitamin C were used for preparing mixed samples with varying percentages. The experimental results revealed that linear additivity is satisfied when the powder particle size is in the range of less than 280, 280–450, and 450–900 μm. When the confidence level is 0.01, the actual mixed spectra are not significantly different from the “simulated mixed spectra” constructed by linear addition, with their relative deviations less than 1.08%. The absolute errors of the actual and analytic percentages were within 2.98% for each component in the mixtures. The above conclusions also hold for sorghum, which has a complex material composition. Statistical models cannot analyze the percentages of components in the mixture. In contrast, linear addition and direct calibration approach avoids the use of a large number of samples for statistical modeling and analyze the percentages of mixed samples. Meanwhile, it can be used to discriminate and analyze the material mixing uniformity by building a mechanistic model.

Feng, Zhiyue↗
DOE OSTI2022

ODI notebook additive_manufacturing_video_2022

Additive Manufacturing, video dataset Two-photon lithography (TPL) is a widely used 3D nanoprinting technique that uses laser light to create objects. Challenges to large-scale adoption of this additive manufacturing method include identifying light dosage parameters and monitoring during fabrication. A research team from LLNL, Iowa State University, and Georgia Tech is applying machine learning models to tackle these challenges-i.e., accelerate the process of identifying optimal light dosage parameters and automate the detection of part quality. Funded by LLNL's Laboratory Directed Research and Development Program, the project team has curated a video dataset of TPL processes for parameters such as light dosages, photo-curable resins, and structures. Both raw and labeled versions of the datasets are available on the links in the Open Data Initiative page. The code uses the labeled dataset. Notebook compiled by Nisha Mulakken (mulakken1@llnl.gov) for LLNL Open Data Initiative, Summer 2022. Original code provided by research team. Publications: X.Y. Lee, S.K. Saha, S. Sarkar, B. Giera. "Automated detection of part quality during two-photon lithography via deep learning." Additive Manufacturing 36, December 2020: doi.org/10.1016/j.addma.2020.101444 X.Y. Lee, S.K. Saha, S. Sarkar, B. Giera. "wo Photon lithography additive manufacturing: Video dataset of parameter sweep of light dosages, photo-curable resins, and structures." Data in Brief 32, October 2020. doi.org/10.1016/j.dib.2020.106119.

Mulakken, NishaJ↗
DOE OSTI2024

PyTorch Implementation of Log-Additive Convolutional Neural Networks

This code is a collection of python code that defines, trains, and tests Log-Additive Convolutional Neural Networks. The model components and training routine are based on the PyTorch python library. The code implements the Log-Additive Convolutional Neural Networks as described in Pagendam et al. 2023. In addition to the Log-Additive Convolutional Neural Networks, this library also defines the Log-Normal Density loss function as described in Pagendam et al. 2023. Code from this paper is not publicly available, so the Pytorch implementation of this type of model is unique to this library.

Callis, Skylar↗
DOE OSTI2023

Development and evaluation of a skeletal mechanism for EHN additized gasoline mixtures in large Eddy simulations of HCCI combustion

Advanced Low Temperature Combustion modes, such as the Sandia proposed Additive-Mixing Fuel Injection (AMFI), can unlock significant potential to boost fuel conversion efficiency and ultimately improve the energy conversion of internal combustion engines. This is a novel improved combustion process that is enabled by supplying small (<5%) variable amounts of autoignition improver to the fuel to enhance the engine operation and control. Common, diesel-fuel ignition-quality enhancing additive, 2-ethylexyl nitrate (EHN), is doped into gasoline to enable Sandia LTGC + AMFI combustion. This manuscript focuses on the development of a reduced sub-mechanism for EHN chemical kinetics at engine relevant conditions that is implemented into a skeletal mechanism for chemical kinetic studies of gasoline surrogate fuels. The mechanism validation utilized zero-dimensional numerical simulations and comparison to shock tube ignition-delay data of pure and EHN-doped n-heptane. Additional validation is presented with Homogeneous Charge Compression-Ignition (HCCI) engine data of pure and EHN-doped research-grade E10 gasoline. Then, the mechanism was deployed in a 3-D computational fluid dynamics (CFD) using Large Eddy Simulations (LES) to model the HCCI engine experiments of 0.4% vol EHN additized E10 gasoline at several equivalence ratios. Simulations showed a very good performance of the mechanism, and the model accurately reproduced (a) the ignition point, (b) combustion phasing, (c) combustion duration, and (d) the peak of the heat release rates of the engine experiments. The results show that EHN promotes Low-Temperature Heat Release, ultimately driving the gasoline to autoignite at thermodynamic conditions where the fuel would not otherwise ignite. Overall, this work demonstrates a viable reduced chemical-kinetic mechanism for EHN and shows that it can be combined with a skeletal gasoline mechanism for CFD-LES analysis of well-mixed LTGC that matches well with experimental results. The CFD-LES analysis also shows the spatial distribution of EHN-fuel interactions that control the autoignition throughout the combustion chamber.

Guleria, Gaurav↗
DOE OSTI2025

In situ Visible Light and Thermal Imaging Data from a Laser Powder Bed Fusion Additive Manufacturing Process Co-Registered to X-ray Computed Tomography and Fatigue Data

This dataset is comprised of in situ sensing data collected during a laser-based powder bed fusion additive manufacturing process, as well as rasterized scan path information, post-build X-ray computed tomography (XCT), and fatigue test results. A total of 64 cylinders, approximately 15 mm in diameter and 102 mm tall, were printed out of stainless steel 316H on a Colibrium Additive Concept Laser M2 Series 5 machine. Parameters known to produce dense material were used to construct 56 of these cylinders, while the remaining 8 cylinders were printed with relatively high energy density parameters prone to producing keyhole pores. In addition, two spatter generation blocks were constructed upstream of the 64 cylinders such that ejecta produced during the melting of the spatter generators were stochastically seeded onto the 64 cylinders. Based on previous experiments, these spatter particles were theorized to produce stochastic lack-of-fusion pores. During the construction of the build, high-resolution images of reflected light in the visible spectrum were captured both before and after recoating for each print layer. Additionally, temporally integrated thermal imaging in the near infrared spectrum produced integrated sum and max images on a layerwise basis. The multimodal in situ data has been co-registered to the build plate coordinate system, allowing for identification of process anomalies (e.g., spatter particles) apparent in the two sensors. Following construction of the build, the cylinders were subjected to XCT to identify internal flaws, and the resulting data have also been registered to the build plate coordinate system. Finally, 60 of the 64 cylinders were machined into fatigue coupons conforming to ASTM E466 and subsequently subjected to either high- or -low-cycle fatigue testing. The results of the fatigue tests have also been included in the dataset, and the XCT data corresponded to the approximate location of the gauge sections of the machine fatigue specimen geometry.

42 ENGINEERING↗
DOE OSTI2021

Effect of additives on carbon dioxide uptake and compressive strength of dry-cast concrete

The main thrust of the work reported herein is to study the effect of chemical additives to make beneficial use of carbon dioxide in enhancing the compressive strength of dry-cast concrete. The additives used in this investigation were calcium and magnesium oxides and silicates, nickel oxide, sodium hydroxide, sodium bicarbonate and strontium chloride. The experimental results showed that both the carbonation reactions and the compressive strength of dry-cast concrete mixtures were improved when using chemical additives. Experimental investigations for optimisation were also undertaken with selected additives to further increase the carbon dioxide uptake and improve the compressive strength. The best results were obtained when using calcium silicate in combination with calcium oxide. The early-age compressive strength of specimens made from the optimised mixture increased from 9·82 MPa to 13·32 MPa, and the specimens’ carbon dioxide uptake increased from 8·76% to 10·62% of cement weight.

Construction & Building Technology↗
DOE OSTI2020

Utility of Big Area Additive Manufacturing for Part Production for Low-Head Hydropower (CRADA NFE-18-07280 Final Report)

ORNL worked with Cadens, LLC, to explore the use of additive manufacturing (AM) to produce low-cost parts for low-head hydropower systems. Cadens develops design optimization software that leverages the flexible, low-cost, high-strength benefits of AM and composite materials. Cadens also operates a micro-hydro lab to test AM components in controlled environments. Until now, Cadens’ tests have been limited to components of a size that they can cost-effectively manufacture using local commercial systems. This project provided an opportunity for Cadens to scale up their modular AM hydropower parts using the capabilities of Big Area Additive Manufacturing (BAAM). This project was a success and resulted in the design and fabrication of several end-use parts of a hydropower system, using a Big Area Additive Manufacturing (BAAM) system. The fabricated parts include a draft tube, thimble, runner housing mold, PVC end fitting and two PVC pipe supports. In addition, a runner system was fabricated using fused deposition modeling on a 3D Platform Workbench 400 Series System.

13 HYDRO ENERGY↗
DOE OSTI2020

Feedstock Modification for Enhanced Additive Alloys

This project investigated the use of Y 2 O 3 nanoparticles to enhance IN625 feedstock for metal additive manufacturing. The oxide nanoparticles are adhered to the outer surface of the pre-alloyed IN625 powder feedstock, and serve to form an oxide dispersion strengthened (ODS) material in situ during processing. The conventional and enhanced feedstocks were processed using a laser powder bed fusion additive manufacturing (AM) system. The properties of the AM materials were characterized at elevated temperatures and compared to conventional wrought material. The addition of the Y 2 O 3 nanoparticles improved the yield strength, stress rupture, and corrosion properties of the AM material, and compared more favorably with conventional wrought IN625. This research will enable future adoption of additively manufactured ODS-IN625 components with superior properties to current printed IN625 material.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Development of a Multi-physics Model to Optimize Continuous Liquid Interface Production (CLIP) for Additive Manufacturing (Carbon3D HPC4Mfg Final Report)

Continuous Liquid Interface Production (CLIP) is poised to bring additive manufacturing to multiple American manufacturing sectors owing to its unique combination of rapid print speeds and material options that resemble injection molding thermoplastics. In spite of these benefits, CLIP is still a maturing process. To improve our understanding and control of the process, this project developed a multi-physics computational model that encompasses the coupled chemical-physical processes of photopolymerization and fluid flow to predict part outcomes. A physically predictive model can enable rapid optimization of CLIP and reduce the current cycle time and waste associated with optimization by four-fold. Ultimately, this effort will help open the U.S. $400B plastic manufacturing industry to the key benefits of additive manufacturing, namely mass customization, unlimited design space, and a cost- and energy-effective path to mainstream manufacturing. In the course of the project we produced a model which coupled fluid-flow, species transport, and photochemistry to model the Carbon CLIP process. As the development proceeded, we validated the code against theory and experiments. The resulting code was transferred to Carbon, and we expect it to be a useful part of their modeling capability. Future work includes improvements to the fluid solver’s robustness and performance, along with the addition of additional physics models.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Layer Time Control for Large Scale Additive Manufacturing Using High Performance Computing

This work proposes to optimize an additive manufacturing AM process to reduce energy and printing cost. The polymer AM process is inherently dependent on the time-temperature history of each layer to maintain geometric tolerances and mechanical integrity. Our preliminary study shows that regression-based layer time control model using thermal images could result in up to 30% build time reduction for simple geometries. This proposed work would use high-performance computing (HPC) to couple the data-driven model with thermal simulation for better predicting layer temperature profiles, improving throughput of large-scale additive manufacturing, and reducing its energy cost. We have developed a method to optimize a layer deposition time (a.k.a. layer time) for large-scale AM via physics-based simulations. A long layer time leads to an over-cooled surface on which a new layer is deposited, and therefore, it may result in a weak bonding or debonding between layers, cracking, or warping. A short layer time leads to a high temperature of the structure due to insufficient cooling, and therefore, the structure may not be stiff enough and may collapse during manufacturing. Therefore, it is important to estimate the optimal layer time in additive manufacturing for a high-quality product. The temperature of a top layer right before deposition is recommended to be slightly higher than the glass temperature of the material. A temperature cooling was approximated to an exponential function of time, and the optimized layer time was obtained based on a target temperature while maintaining a minimal printing time. The material used is carbon fiber-reinforced polycarbonate (CF/PC), and the large-scale deposition system used is LSAM TM from Thermwood Corporation. Three different layer time cases were used for experiments, and a series of thermal images were obtained via an infra-red (IR) camera during the entire AM processes. AM process simulations were performed using a finite element method and the temperature profiles from the simulation were in good agreements with those from experiments. The layer time optimization was performed based on the temperature profiles from the simulations. A layer temperature with the optimal layer time was confirmed as the target temperature through simulation. In addition to the development of a layer time optimization method, we have developed a numerical framework for AM simulation with element activations in sync with toolpath, based on an open source finite element framework, DEAL.II. A major portion of this work was presented at SAMPE 2022 Conference and Exhibition on May 2022, and published in Proceedings of SAMPE 2022.

42 ENGINEERING↗