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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Effect of process route on powder three-dimensional-printing of metal powders

The purpose of this study is to investigate the effect of two unique processing routes (solvent jetting (SJ) and binder jetting (BJ)), on the green density of printed stainless steel 316L (SS316L) and Nickel (Ni) powders. In the SJ processing route, a solvent is jetted unto the powder/binder mixture to selectively activate the binder, layer by layer. In the BJ processing route, a solution of the binder mixture is jetted onto the powder bed to selectively bind powder particles. The effects of printing parameters such as layer height, roller speed, shaker speed and nozzle temperature on the green density of printed components are investigated and compared for both processing routes. Results show that layer height and nozzle temperature affect the relative density of the printed compact for both processing routes. Slightly higher relative densities were achieved via the SJ route, with the overall highest relative density being 42.7% at 100 µ m layer height and 70% nozzle temperature for the SS316L components and 43.7% at 150 µ m layer height and 90% nozzle temperature for the Ni components, respectively. Results also show an increase in the final sintered relative density with an increase in green (printed) relative density of the solvent jetted SS316L components, with the highest relative density being 87.2%. The paper studies the influence of printing parameters on the green density of printed SS316L and Ni samples in an unprecedented effort to provide a comparative understanding of the process-property relationships in BJ and SJ of SS316L and Ni components to the additive manufacturing research community.

Engineering↗
DOE OSTI2023

Process-dependent anisotropic thermal conductivity of laser powder bed fusion AlSi10Mg: impact of microstructure and aluminum-silicon interfaces

Purpose AlSi10Mg alloy is commonly used in laser powder bed fusion due to its printability, relatively high thermal conductivity, low density and good mechanical properties. However, the thermal conductivity of as-built materials as a function of processing (energy density, laser power, laser scanning speed, support structure) and build orientation, are not well explored in the literature. This study aims to elucidate the relationship between processing, microstructure, and thermal conductivity. Design/methodology/approach The thermal conductivity of laser powder bed fusion (L-PBF) AlSi10Mg samples are investigated by the flash diffusivity and frequency domain thermoreflectance (FDTR) techniques. Thermal conductivities are linked to the microstructure of L-PBF AlSi10Mg, which changes with processing conditions. The through-plane exceeded the in-plane thermal conductivity for all energy densities. A co-located thermal conductivity map by frequency domain thermoreflectance (FDTR) and crystallographic grain orientation map by electron backscattered diffraction (EBSD) was used to investigate the effect of microstructure on thermal conductivity. Findings The highest through-plane thermal conductivity (136 ± 2 W/m-K) was achieved at 59 J/mm 3 and exceeded the values reported previously. The in-plane thermal conductivity peaked at 117 ± 2 W/m-K at 50 J/mm 3 . The trend of thermal conductivity reducing with energy density at similar porosity was primarily due to the reduced grain size producing more Al-Si interfaces that pose thermal resistance. At these interfaces, thermal energy must convert from electrons in the aluminum to phonons in the silicon. The co-located thermal conductivity and crystallographic grain orientation maps confirmed that larger colonies of columnar grains have higher thermal conductivity compared to smaller columnar grains. Practical implications The thermal properties of AlSi10Mg are crucial to heat transfer applications including additively manufactured heatsinks, cold plates, vapor chambers, heat pipes, enclosures and heat exchangers. Additionally, thermal-based nondestructive testing methods require these properties for applications such as defect detection and simulation of L-PBF processes. Industrial standards for L-PBF processes and components can use the data for thermal applications. Originality/value To the best of the authors’ knowledge, this paper is the first to make coupled thermal conductivity maps that were matched to microstructure for L-PBF AlSi10Mg aluminum alloy. This was achieved by a unique in-house thermal conductivity mapping setup and relating the data to local SEM EBSD maps. This provides the first conclusive proof that larger grain sizes can achieve higher thermal conductivity for this processing method and material system. This study also shows that control of the solidification can result in higher thermal conductivity. It was also the first to find that the build substrate (with or without support) has a large effect on thermal conductivity.

Engineering↗
DOE OSTI2021

Effects of Wire Diameter and Filament Size on the Processing Window of Bi-2212 Round Wire

High engineering critical current density (J E of 1300 A/mm 2 at 4.2 K and 15 T) in Bi-2212 round wire has been achieved through a partial melt, overpressure heat treatment process. J E varies strongly with processing conditions, particularly the maximum heat treatment temperature (T max ). Increasing T max results in longer time in the melt (defined as the time between when Bi-2212 melts on heating and when Bi-2212 begins to form on cooling), more bridging between the filaments, lower J E , and higher ac losses. A wide processing window with a large range of T max that has a nearly constant J E is desired for processing large coils with large thermal mass and significant thermal time constants that may make precise control over the desired temperature – time profiles uncertain. Accordingly, we wanted to explore broadening the T max window by controlling the Bi-2212 powder melting or wire architecture design. In this work, we report on studies of the performance variation with T max for two production wires with a filling factor of about 20% and 85 × 18 filaments where filament size was varied by changing the wire diameter, a process which also shortens the distance between filaments. We found that wires with smaller filament diameter (9 to 11 μm) showed a peak J E at the low end of T max and also a J E that was more sensitive to T max . A J E – T max plot showed a plateau J E (4.2 K, 5 T) of ~1100 A/mm 2 between T max of 886 and 894 °C for 1.0 and 1.2 mm wires, where J E is less sensitive to the wire diameter and T max . This J E plateau range is a preferred processing window for achieving high J E in coils.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Extracting Resilience Metrics From Distribution Utility Data Using Outage and Restore Process Statistics

Resilience curves track the accumulation and restoration of outages during an event on an electric distribution grid. We show that a resilience curve generated from utility data can always be decomposed into an outage process and a restore process and that these processes generally overlap in time. We use many events in real utility data to characterize the statistics of these processes, and derive formulas based on these statistics for resilience metrics such as restore duration, customer hours not served, and outage and restore rates. The formulas express the mean value of these metrics as a function of the number of outages in the event. We also give a formula for the variability of restore duration, which allows us to predict a maximum restore duration with 95% confidence. Overall, we give a simple and general way to decompose resilience curves into outage and restore processes and then show how to use these processes to extract resilience metrics from standard distribution system data.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Analytical Study and Experimental Verification of Shear-Thinning Ink Flow in Direct Ink Writing Process

Abstract Direct ink writing (DIW) process is a facile additive manufacturing technology to fabricate three-dimensional (3D) objects with various materials. Its versatility has attracted considerable interest in academia and industry in recent years. As such, upsurging endeavors are invested in advancing the ink flow behaviors in order to optimize the process resolution and the printing quality. However, so far, the physical phenomena during the DIW process are not revealed in detail, leaving a research gap between the physical experiments and its underlying theories. Here, we present a comprehensive analytical study of non-Newtonian ink flow behavior during the DIW process. Different syringe-nozzle geometries are modeled for the comparative case studies. By using the computational fluid dynamics (CFD) simulation method, we reveal the shear-thinning property during the ink extrusion process. Besides, we study the viscosity, shear stress, and velocity fields, and analyze the advantages and drawbacks of each syringe-nozzle model. On the basis of these investigations and analyses, we propose an improved syringe-nozzle geometry for stable extrusion and high printing quality. A set of DIW printing experiments and rheological characterizations are carried out to verify the simulation studies. The results developed in this work offer an in-depth understanding of the ink flow behavior in the DIW process, providing valuable guidelines for optimizing the physical DIW configuration toward high-resolution printing and, consequently, improving the performance of DIW-printed objects.

Engineering↗
DOE OSTI2026

Identifying Bounds of Inorganic Content in Solventless Processing of Hybrid Solid Electrolytes

Solid-state lithium batteries require safe, robust electrolytes to enable higher energy densities and improved safety over conventional cells. Hybrid polymer–ceramic electrolytes are a promising solution, combining the processability of polymers with the high ionic conductivity and mechanical strength of inorganic fillers. In this work, we demonstrate a solventless, UV-curing method to produce hybrid solid electrolytes using a poly(ethylene glycol) dimethyl ether (PEGDME)-based photocurable matrix incorporating Li 1.5 Al 0.5 Ge 1.5 (PO 4 ) 3 (LAGP) or Li 7 La 3 Zr 2 O 12 (LLZO) ceramic electrolyte. Inorganic filler loadings up to ∼55 wt.% could be successfully incorporated via this process which was the highest inorganic content at which the slurry remains processable and cured into a uniform film. The resulting UV-cured composite electrolytes remain flexible and exhibit room-temperature ionic conductivities on the order of 10 −4 S·cm −1 , along with notably improved lithium-ion transference numbers compared to conventional polymer electrolytes. Similar performance and processing limits were observed for both LAGP and LLZO, indicating that ceramic filler chemistry does not significantly affect the UV-curing process or the electrolyte's ion transport properties in this regime. Eliminating solvents from fabrication not only simplifies processing and mitigates environmental concerns but also enables higher solid contents that enhance mechanical strength and help suppress lithium dendrite formation. In conclusion, this scalable approach thus paves the way for manufacturing robust composite solid electrolytes for next-generation solid-state batteries (SSBs).

Batteries↗
DOE OSTI2018

Effect of Barothermal Processing on the Solid-State Formation of the Structure and Properties of 16 at % Si–Al Hypereutectic Alloy

We describe barothermal processing (hot isostatic pressing) of a 16 at % Si–Al binary alloy for 3 h at a temperature of 560°C and pressure of 100 MPa for 3 h, in combination with measurements of heat effects during cooling. The results demonstrate that this processing leads to the fragmentation of the silicon structural constituent and ensures a high degree of homogenization of the as-prepared alloy. Heat treatment of the 16 at % Si–Al alloy at 560°C and a pressure of 100 MPa leads to a thermodynamically driven enhanced silicon dissolution, up to ~10 at %, in the aluminum matrix, resulting in the formation of a supersaturated solid solution, which subsequently decomposes during cooling. We analyze the complete porosity elimination process, which makes it possible to obtain a material with 100% relative density. According to differential barothermal analysis, microstructural analysis, and scanning and transmission electron microscopy data, barothermal processing of the 16 at % Si–Al alloy produces a bimodal size distribution of the silicon phase constituent: microparticles 3.6 μm in average size and nanoparticles down to ~1 nm in diameter. The Al matrix has been shown to contain a high density of edge dislocations. Barothermal processing reduces the thermal expansion coefficient and microhardness of the hypereutectic alloy. We conclude that solid-state barothermal processing is an effective tool for completely eliminating microporosity from the 16 at % Si–Al alloy, reaching a high degree of homogenization, and controlling the microstructure of the alloy, in particular by producing high dislocation density in the aluminum matrix.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Stochastic representation and conditioning of process-based geological model by deep generative and recognition networks

Accurate and realistic geological modeling is the core of oil and gas development and production. In recent years, process-based methods are developed to produce highly realistic geological models by simulating the physical processes that reproduce the sedimentary events and develop the geometry. However, the complex dynamic processes are extremely expensive to simulate, making process-based models difficult to be conditioned to field data. In this work, we propose a comprehensive generative adversarial network framework as a machine-learning-assisted approach for mimicking the outputs of process-based geological models with fast generation. The main objective of our work is to obtain a continuous parametrization of the highly realistic process-based geological models which enables us to calibrate the models and condition the models to data. Numerical results are presented to illustrate the capability of our proposed methodology.

58 GEOSCIENCES↗
DOE OSTI2024

High-Throughput Computing: Case Study of Medical Image Processing Applications

HPC is designed for large-scale simulations using monolithic codes of tightly coupled processes highly optimized to deliver decreased time to solution. Medical image processing is not a traditional field of HPC. Similar to AI applications, medical image processing parses large datasets, typically multiple times, to support a variety of studies for classification, diagnosis or monitoring purposes. The convergence of AI, HPC and Big Data encouraged more fields using image processing to transition to HPC. However, not all applications benefit from the same optimizations. In this paper we focus on high throughput medical image processing applications that analyze a huge dataset of small MRI images and that require HPC systems to decrease the time of parsing the entire dataset and not individual MRIs. We show in this research the performance of running SLANT, an image processing application for a whole brain segmentation, on large-scale systems and highlight performance limitations. We present optimizations prioritizing throughput that exhibit a 3.5x speed-up on the Summit Supercomputer that can be used as a baseline for building a high-throughput execution framework for other HPC systems.

Predescu, Maria↗
DOE OSTI2025

Modeling a High-Temperature Electrochemically Driven Water-Gas-Shift Process Using a Mixed-Conducting Membrane without External Electrical Power

This paper develops a model to predict and interpret the performance of an elevated-temperature, electrochemical, membrane-assisted, water-gas-shift process. The process uses separated feed streams of H 2 O and CO to produce separated streams of H 2 and CO 2 , without an external electrical power source. The dense ceramic membrane is mixed ionic-electronic-conducting (MIEC) gadolinium-doped ceria (GDC) and the porous composite electrodes are Ni-YSZ. At elevated temperature, GDC conducts both oxygen ions and small polarons. The present process uses chemical potential to drive the process. Electrochemical oxidation of CO proceeds within the composite anode and H 2 O reduction proceeds within the composite cathode. At high temperature (e.g., T > 700 °C), GDC has significant electronic leakage in the form of a reduced-cerium small polaron, which supports the charge-transfer reactions. In a typical electrolyzer or fuel cell, this leakage is significantly problematic. However, the present process depends on the leakage current to complete the electrochemical circuit. Model development and validation is based on measured material properties and reactor performance. Potential applications include using CO-rich blast-furnace off gases in steel processing, producing separated streams of H 2 and CO 2 .

Zhu, Huayang↗
DOE OSTI2022

Idaho National Laboratory Data Acquisition And Processing System

The INLDAS data acquisition and processing system is designed to develop prototype measurements and real-time processing techniques. The INLDAS hardware and firmware currently consists of National Instruments • NI-DAQmx 14.1 • cDAQ-9184 • 9205 • 9211 INLDAS can perform of standard data acquisition functions as well as novel functions and real-time processing algorithms. There are 3 acquisition modes to choose from: • Continuous mode runs when the user hits start, processing data and logging it to file • SWTrigger mode waits for one or more predefined triggers before acquiring data. It will buffer data as well, so it can record data that happened shortly before the trigger • Wakeup mode waits on predefined timers. When a time goes off, it acquires a preset amount of data There are also 3 Data Processing Modes • Normal mode does no processing besides the rolling average • FFT Mode Performs an FFT on incoming data every time the time window has elapsed • STFFT mode

Smith, JamesA↗
DOE OSTI2023

Processing Temperature Effect on Failure Behavior of Unidirectional Thermoplastic Polymer-fiber-reinforced Polymers (PFRPs)

This study aimed to examine the influence of processing temperature on the mechanical and morphological characteristics of unidirectional (UD) thermoplastic polymer-fiber-reinforced polymers (PFRPs), utilizing UHMWPE-polymer-fiber-reinforced HDPE composites as an example. To achieve this objective, UD thermoplastic PFRPs were produced through filament winding and hot pressing techniques, employing five distinct processing temperatures within the range spanning from the melting onset temperature of the polymer matrix to the melting peak temperature of the reinforcing polymer fiber. By conducting the uni-axial tensile tests on the UD UHMWPE-polymer-fiber-reinforced HDPE composites fabricated at different processing temperatures, it was shown that the optimal longitudinal tensile properties of the composites, comparable with glass-fiber-reinforced thermoset or thermoplastic polymers (GFRPs or GFRTPs) can be achieved when the processing temperature does not significantly exceeds the melting onset temperature of the reinforcing polymer fiber. However, when the processing temperature exceeds this threshold, the mechanical properties of the composites are significantly reduced, as evidenced by the transition in the failure morphology from the presence of significant splitting cracks to the occurrence of plastic necking due to the complete melting of the reinforcing polymer fibers in a composite. Particularly, the ductile behavior of the optimal thermoplastic PFRPs investigated in this study is superior than that of carbon-fiber-reinforced thermoset or thermoplastic polymers (CFRPs or CFRTPs) and even GFRPs and GFRTPs. This study not only provides valuable insights into the proper fabrication of high-performance thermoplastic PFRPs but also offers useful experimental data that can aid in the validation and development of computational models, particularly those related to processing modeling.

Qiao, Yao↗
DOE OSTI2018

Data from Increasing Ethanol Yield through Fiber Conversion in Corn Dry Grind Process

Conversion of corn fiber to ethanol in the dry grind process could increase ethanol yields, reduce downstream processing costs and improve overall process profitability. This work investigates the in-situ conversion of corn fiber into ethanol (cellulase addition during simultaneous saccharification and fermentation) during dry grind process. Addition of 30 FPU/g fiber cellulase resulted in 4.6% increase in ethanol yield compared to the conventional process. Use of excess cellulase (120 FPU/g fiber) resulted in incomplete fermentation and lower ethanol yield compared to the conventional process. Multiple factors including high concentrations of ethanol and phenolic compounds were responsible for yeast stress and incomplete fermentation in excess cellulase experiments.

Conversion↗
DOE OSTI2024

A Co-Registered In-Situ and Ex-Situ Dataset of Electrical, Acoustic, and CT Characteristics from Wire Arc Additive Manufacturing Process

Recent progress in sensing techniques and data analytics tools have significantly accelerated the development of Wire Arc Additive Manufacturing (WAAM) systems. This data centric approach emphasizes leveraging available data throughout the production process to optimize performance. Integration of extensive data analysis provides the opportunity to improve precision, reduce waste, and enhance the quality of produced parts. This method relies on AI/ML models and optimization techniques, which are developed using the data collected from various sources, including in-situ sensors, ex-situ imaging, and manufacturing process parameters. The quality and diversity of this data, along with the alignment between different data streams (achieved through spatiotemporal registration) are critical for the successful development of AI/ML and optimization models. In this work, we present a spatiotemporally registered dataset generated during the WAAM process of deposition of a rectangular block. The dataset includes the comprehensive description of deposition process, process parameters, in-situ collected welding characteristics, acoustic data, and X-Ray Computed Tomography analysis data for the build. Dataset A Co-Registered In-Situ and Ex-Situ Dataset of Electrical, Acoustic, and CT Characteristics from Wire Arc Additive Manufacturing Process has arisen under UT-Battelle, LLC’s Prime Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy (DOE) to manage and operate the Oak Ridge National Laboratory. UT-Battelle, LLC will not assert any rights under United States law or under the Prime Contract it has in the dataset against any user of the dataset, including any copyrights or patent rights. UT-Battelle, LLC requests that attribution to the dataset is provided as academically appropriate.

42 ENGINEERING↗
DOE OSTI2024

In Situ Plasma processing of SRF cuperconducting cavities at JLAB, 2024 Update

Jefferson Lab has an ongoing R&D program in plasma processing. The experimental program investi-gated processing using argon/oxygen and heli-um/oxygen gas mixtures. Plasma processing is a com-mon technique where the free oxygen produced by the plasma breaks down and removes hydrocarbons from surfaces. This increases the work function and reduces the secondary emission coefficient. The initial focus of the effort was processing C100 cavities by injecting RF power into the high order mode (HOM) coupler ports. We also developed the methods for establishing a plasma in C75 cryomodules where the RF power is injected via the fundamental power-coupler. Four C100 cryomodules were in situ processed in the CE-BAF accelerator in May 2023 with the cryomodules returning to an operational status in Sept. 2023. The overall operational energy gain for the four cryomod-ules was 49 MeV. Methods, systems and results from processing cryomodules in the CEBAF accelerator and vertical test results are presented. Current status and future plans are discussed.

Powers, T.↗
DOE OSTI2022

Electrochemical CO2 conversion to formic acid through the Andora Process

Electrochemical utilization or conversion of CO2 can be used to convert waste CO2 into targeted high-value and cost-effective commercial products. Conventional processes for CO2 conversion to fuel sources are challenging and expensive due to their requirement for high temperatures and pressures. Electrochemically, a catalyst can be used at a fixed applied potential to reduce CO2 to form a desired product with less competition at modest operating conditions. Formic acid (FA) has recently become a product of interest for CO2 conversion due to its potential for hydrogen storage and fuel cell applications. Electrochemically, FA is produced through a direct two-electron transfer process involving CO2 with a proton source, requiring less energy input and fewer reaction steps than traditional processes. However, there remain significant obstacles for the broader-scale implementation of CO2 on the market, including competition with unwanted CO and H, the presence of molecular oxygen, and stability of the electrocatalyst. In order to overcome some of these challenges, a new continuous flow Andora Process was developed consisting of two separate cells to decouple electrochemical reduction of the charge carrier with the FA production via an engineered catalyst. Recent experimental results show that with appropriate design changes and operating conditions to the flow system, FA production above 500 mM can be achieved along with efficiencies above 80%. TEA and LCA assessments of the Andora Process show a potential for the reduction in the GWP potential and cost saving compared to the current comparative formic acid production process.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Bench Scale Process for Low Cost CO 2 Capture Using a Phase-Changing Absorbent: Final Scientific/Technical Report

The objective of this project is to design and build a bench-scale process for a novel phase-changing aminosilicone-based CO 2 -capture solvent. The project will establish scalability and technical and economic feasibility of using a phase-changing CO 2 -capture absorbent for post-combustion capture of CO 2 from coal-fired power plants. The U.S. Department of Energy’s goal for Transformational Carbon Capture Technologies is the development of technologies available for demonstration by 2025 that can capture 90% of emitted CO 2 with at least 95% CO 2 purity for less than $40/tonne of CO 2 captured. In the first budget period of the project, the bench-scale phase-changing CO2 capture process was designed using data and operating experience generated under a previous project (ARPA-e project DE-AR0000084). Sizing and specification of all major unit operations was completed, including detailed process and instrumentation diagrams. The system was designed to operate over a wide range of operating conditions to allow for exploration of the effect of process variables on CO 2 capture performance. In the second budget period of the project, individual bench-scale unit operations were tested to determine the performance of each of each unit. Solids production was demonstrated in dry simulated flue gas across a wide range of absorber operating conditions, with single stage CO 2 conversion rates up to 75mol%. Desorber operation was demonstrated in batch mode, resulting in desorption performance consistent with the equilibrium isotherms for GAP-0/CO 2 reaction. Important risks associated with gas humidity impact on solids consistency and desorber temperature impact on thermal degradation were explored, and adjustments to the bench-scale process were made to address those effects. Corrosion experiments were conducted to support selection of suitable materials of construction for the major unit operations in the process. The bench scale unit operations were assembled into a continuous system to support steady state system testing. In the third budget period of the project, continuous system testing was conducted, including closed-loop operation of the absorber and desober systems. Slurries of GAP-0/GAP-0 carbamate/water mixtures produced in the absorber were pumped successfully to the desorber unit, and regenerated solvent was returned to the absorber. A techno-economic analysis, EH&S risk assessment, and solvent manufacturability study were completed.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2017

SME Acceptability Determination For DWPF Process Control (U)

The statistical system described in this document is called the Product Composition Control System (PCCS). K. G. Brown and R. L. Postles were the originators and developers of this system as well as the authors of the first three versions of this technical basis document for PCCS. PCCS has guided acceptability decisions for the processing at the Defense Waste Processing Facility (DWPF) at the Savannah River Site (SRS) since the start of radioactive operations in 1996. The author of this revision to the document gratefully acknowledges the firm technical foundation that Brown and Postles established to support the ongoing successful operation at the DWPF. Their integration of the glass propertycomposition models, developed under the direction of C. M. Jantzen, into a coherent and robust control system, has served the DWPF well over the last 20+ years, even as new challenges, such as the introduction into the DWPF flowsheet of auxiliary streams from the Actinide Removal Process (ARP) and other processes, were met. The purpose of this revision is to provide a technical basis for modifications to PCCS required to support the introduction of waste streams from the Salt Waste Processing Facility (SWPF) into the DWPF flowsheet. An expanded glass composition region is anticipated by the introduction of waste streams from SWPF, and property-composition studies of that glass region have been conducted. Jantzen, once again, directed the development of glass property-composition models applicable for this expanded composition region. The author gratefully acknowledges the technical contributions of C.M. Jantzen leading to the development of these glass property-composition models. The integration of these models into the PCCS constraints necessary to administer future acceptability decisions for the processing at DWPF is provided by this sixth revision of this document.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗