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At least 1,549 records · Page 86
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Co-Processing Fast Pyrolysis Bio-Oils and Hydrothermal Liquefaction Biocrudes in Fluid Catalytic Cracking and Hydroprocessing in Refineries

Co-processing of biogenic feedstocks within the existing petroleum infrastructure represents an opportunity to incorporate large volumes of bio-carbon into transportation fuels. However, upgrading intermediate liquids from biomass and waste to final products efficiently and economically, while minimizing impacts to existing refinery infrastructure, remains a notable barrier to commercialization. The co-processing project, Bio-oil Co-processing with Refinery Streams, aimed to generate foundational knowledge for processing renewable intermediates in petroleum refineries and offer co-processing strategies, as well as develop new methods for biogenic carbon tracking and measurement.

bio-oil↗
DOE OSTI2024

Development of Leaching Processes for the Recovery of Rare Earth Elements from Acid Mine Drainage Precipitates

Acid mine drainage (AMD) has been a challenge for mine operators to address and has had significant environmental impacts when there is a failure to address it. Fortunately, there is a regulation in the US that requires the treatment of AMD before water can be discharged into the environment. AMD is generated when sulfide minerals are exposed to water and air from mining. The acidic water then leaches metals from the surrounding rock, creating the potential for environmental contamination of this acidic water containing dissolved metals. AMD can contain high concentrations of metals like iron, aluminum, and manganese and also have been shown to contain trace concentrations of critical minerals, including rare earth elements (REEs). This environmental waste stream is now being researched as a potential source for REEs. There is a patented process for processing and extracting REEs from AMD which produces rare earth oxide preconcentrate (REOP) from AMD treatment precipitates and a final stage mixed rare earth oxide (MREO) product. This body of research examines a selective leaching process for each of these products and determines the activation energy associated with the leaching processes. Acid leaching with HCl was examined to selectively leach REEs from REOP while contaminant metals remained in the solid residue. The maximum leaching recovery of the REEs from the REOP was approximately 90% and an activation energy of 6.4 kJ/mol at pH 3.0. Ammonium chloride leaching was examined to selectively remove contaminant metals from a MREO product. The ammonium chloride process successfully leached major contaminant metals in excess of 85% recovery and had a maximum activation energy of 40.0 kJ/mol.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Benefits and challenges of vibroacoustic process monitoring to support operators in nuclear research facilities

According to the International Atomic Energy Agency in 2024, global nuclear energy capacity is projected to increase by 2.5 times by 2050 in their high-case scenario. Research on the laboratory scale of innovative processes within nuclear facilities is ongoing to improve nuclear fuel cycle capabilities. Vibroacoustic process monitoring of these techniques has potential to inform operators regarding process specific metrics, predictive maintenance, and anomalous event detection. Additionally, this type of monitoring has the potential to aid in nuclear safeguards. Challenges regarding vibroacoustic monitoring in these environments include high temperature, high radiation, limited access, and shielded equipment limiting sensor type and placement. Microphones, accelerometers, and temperature sensors were deployed both inside and near these environments during operation to determine environment driven limitations, sound attenuation of containment enclosures, process specific metrics, and future potential of vibroacoustic monitoring in these environments. Overall, this work highlights the benefits and limitations of vibroacoustic process monitoring in nuclear research facilities.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Optimal Methanol Production via Sorption-Enhanced Reaction Process

To counter the equilibrium limitations in traditional methanol production from synthesis gas, a periodic and sorption-enhanced methanol synthesis process (SE-MeOH) with in situ removal of water byproduct is designed and optimized. A generalized reaction–adsorption modeling and simulation framework is coupled with a simulation-based constrained gray-box optimizer to obtain the optimal cycle configuration, design parameters, process specifications, and operating conditions. The best-case results indicate that SE-MeOH processes can break the barrier of the current limit of industrial methanol yield and improve it by 55–87% with a slight compromise (9–46%) on CH 3 OH production capacity. This trade-off is a result of periodic operation which is required for sorption enhancement. The techno-economic optimization of a base industrial reactor also leads to more than 7% improvement in methanol yield with only 2% decrease in production capacity while keeping the cost of syngas-to-methanol production competitive. The SE-MeOH system is further optimized through varying the feed specifications and number of reactor tubes. Furthermore, the results suggest that the synthesis gas composition, flow rate, and number of tubes are the major factors in determining methanol process performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Simultaneous Process and Heat Exchanger Network Synthesis Using a Discrete Temperature Grid

We present mixed-integer linear programming models for utility targeting and heat exchanger network synthesis that account for variable stream temperatures and flow rates as well as unclassified streams and thus can be combined with process synthesis optimization models. By projecting temperature information onto a fixed discrete temperature grid, the model remains linear even under variable temperatures and flow rates, leading to a more tractable optimization model. The proposed model is well suited to address problems in the area of process intensification where the close interaction between different phenomena naturally leads to process synthesis problems with unclassified process streams. Several extensions are presented, including nonisothermal mixing as well as phase changes. Moreover, we show how a nonuniform grid can be adopted to reduce the complexity of the model for medium and large-size problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Versatile Sequential Casting Processing for Highly Efficient and Stable Binary Organic Photovoltaics

Forming an ideal bulk heterojunction (BHJ) morphology is a critical issue governing the photon to electron process in organic solar cells (OSCs). Complementary to the widely-used blend casting (BC) method for BHJ construction, sequential casting (SC) can also enable similar or even better morphology and device performance for OSCs. Here, BC and SC methods on three representative donor:acceptor (D:A) blends are utilized, that is, PM6:PC 71 BM, PM6:IT-4F and PM6:L8-BO. Higher power conversion efficiencies (PCEs) in all cases by taking advantage of beneficial morphology from SC processing are achieved, and a champion PCE of 18.86% (certified as 18.44%) based on the PM6:L8-BO blend is reached, representing the record value among binary OSCs. The observations on phase separation and vertical distribution inspire the proposal of the swelling–intercalation phase-separation model to interpret the morphology evolution during SC processing. Further, the vertical phase segregation is found to deliver an improvement of device performance via affecting the charge transport and collection processes, as evidenced by the D:A-ratio-dependent photovoltaic properties. Besides, OSCs based on SC processing show advantages on device photostability and upscale fabrication. Finally, this work demonstrates the versatility and efficacy of the SC method for BHJ-based OSCs.

14 SOLAR ENERGY↗
DOE OSTI2022

Observational process data analytics using causal inference

Voluminous process data are available with the paradigm shift toward smart manufacturing. However, most historical data are observational, containing noncausal correlations due to confounders and mediators. Estimating causal effects from observational data remains a bottleneck in leveraging them for active applications such as optimization and control. Further, this work aims to introduce a causal modeling framework for analyzing observational process data and extracting quantitative causal information. We demonstrate a real-world application in steel manufacturing where causal inference is used to analyze observational production data and improve the steelmaking process. Additionally, we propose a novel formulation for identifying critical process parameters from observational data, where causal inference is combined with variance-based methods to estimate corresponding risks of interventions to the manufacturing system. The proposed methods are compared with statistical ones to illustrate that causally interpreting statistical correlation leads to problematic results, while the provided workflow generates satisfactory strategies for process improvement.

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

Effect of melting processes on the structure and precipitation of a heavy rainstorm in Beijing

Abstract Beijing and its surrounding areas experienced a torrential rainstorm from July 21 to 22, 2012. Previous studies have shown that melting was the main rainwater source in this process. In this paper, melting conversion processes were set to zero (NPMLT test) to analyze the effect of microphysical processes on the structure and precipitation of the convective system. The results showed that without the melting processes, the wind shear at the 700 hPa level decreased, and the wind field in Beijing and its surrounding areas changed. The cold front system moved faster, and the rainfall amount only reached the low rain level, much lower than that during the actual rainstorm. The hydrometeors sources had apparently changed. Though the latent heat release was large and little latent heat absorption occurred in the NPMLT test, the net latent heat did not affect the development of the convective system, and the precipitation was low. Therefore, microphysical processes greatly influence precipitation and convective system.

Guo, Chunwei↗
DOE OSTI2018

Understanding coastal wetland hydrology with a new regional‐scale, process‐based hydrological model

Abstract Coastal wetlands represent an ecotone between ocean and terrestrial ecosystems, providing important services, including flood mitigation, fresh water supply, erosion control, carbon sequestration, and wildlife habitat. The environmental setting of a wetland and the hydrological connectivity between a wetland and adjacent terrestrial and aquatic systems together determine wetland hydrology. Yet little is known about regional‐scale hydrological interactions among uplands, coastal wetlands, and coastal processes, such as tides, sea level rise, and saltwater intrusion, which together control the dynamics of wetland hydrology. This study presents a new regional‐scale, physically based, distributed wetland hydrological model, PIHM‐Wetland, which integrates the surface and subsurface hydrology with coastal processes and accounts for the influence of wetland inundation on energy budgets and evapotranspiration (ET). The model was validated using in situ hydro‐meteorological measurements and Moderate Resolution Imaging Spectroradiometer (MODIS) ET data for a forested and herbaceous wetland in North Carolina, USA, which confirmed that the model accurately represents the major wetland hydrological behaviours. Modelling results indicate that topographic gradient is a primary control of groundwater flow direction in adjacent uplands. However, seasonal climate patterns become the dominant control of groundwater flow at lower coastal plain and land–ocean interface. We found that coastal processes largely influence groundwater table (GWT) dynamics in the coastal zone, 300 to 800 m from the coastline in our study area. Among all the coastal processes, tides are the dominant control on GWT variation. Because of inundation, forested and herbaceous wetlands absorb an additional 6% and 10%, respectively, of shortwave radiation annually, resulting in a significant increase in ET. Inundation alters ET partitioning through canopy evaporation, transpiration, and soil evaporation, the effect of which is stronger in cool seasons than in warm seasons. The PIHM‐Wetland model provides a new tool that improves the understanding of wetland hydrological processes on a regional scale. Insights from this modelling study provide benchmarks for future research on the effects of sea level rise and climate change on coastal wetland functions and services.

Zhang, Yu↗
DOE OSTI2024

A novel digital lifecycle for Material‐Process‐Microstructure‐Performance relationships of thermoplastic olefins foams manufactured via supercritical fluid assisted foam injection molding

Abstract This research significantly enhances the applicability of thermoplastic olefins (TPOs) in the automotive industry using supercritical N 2 as a physical foaming agent, effectively addressing the limitations of traditional chemical agents. It merges experimental results with simulations to establish detailed material‐process‐microstructure‐performance (MP2) relationships, targeting 5–20% weight reductions. This innovative approach labeled digital lifecycle (DLC) helps accurately predict tensile, flexural, and impact properties based on the foam microstructure, along with experimentally demonstrating improved paintability. The study combines process simulations with finite element models to develop a comprehensive digital model for accurately predicting mechanical properties. Our findings demonstrate a strong correlation between simulated and experimental data, with about a 5% error across various weight reduction targets, marking significant improvements over existing analytical models. This research highlights the efficacy of physical foaming agents in TPO enhancement and emphasizes the importance of integrating experimental and simulation methods to capture the underlying foaming mechanism to establish material‐process‐microstructure‐performance (MP2) relationships. Highlights Establishes a material‐process‐microstructure‐performance (MP2) for TPO foams Sustainably produces TPO foams using supercritical (ScF) N 2 with 20% lightweighting Shows enhanced paintability for TPO foam improved surface aesthetics Digital lifecycle (DLC) that predicts both foam microstructure and properties DLC maps process effects & microstructure onto FEA mesh for precise prediction

Engineering↗
DOE OSTI2024

In‐mold rheology and automated process control for injection molding of recycled polypropylene

Abstract Manufacturing plastic parts with secondary feedstocks has risen to the forefront of importance in recent years. However, the variation in molecular weight and rheology of secondary feedstock can lead to inconsistent part quality. This work evaluates the effectiveness of a novel closed‐loop adaptive process control system that adjusts nozzle pressure in response to in‐mold pressure data. Five different recycled polypropylene blends, with a broad distribution of flow properties, were evaluated to determine the effectiveness of the control system at reducing processing variation. The experimental results show that the process control strategy reduced the variation within the mold, as seen by in‐mold pressure curves and calculated in‐mold viscosity values. Additionally, the parameters that control the automated process adjustments were investigated, showing the importance of optimization. The analysis of the correlation between in‐mold rheology and mechanical properties showed a slight variation in the mechanical properties and parts weight with a coefficient of variation of under 5%. Overall, the results demonstrate the ability of pressure‐controlled molding and automated viscosity adjustment to reduce the variability when molding a secondary feedstock. Highlights Pressure‐controlled injection molding of recycled polypropylene. Automated closed‐loop adaptive process control methodology. Methodology resulted in a reduction in pressure variation during molding. Changes in mechanical properties and in‐mold viscosity were investigated. Results show the potential of pressure‐controlled molding at reducing variation.

Krantz, Joshua↗
DOE OSTI2025

Correlating processing variables to material properties in recycled polypropylene: A data‐driven approach

Abstract Polypropylene (PP) is one of the most widely used plastics, yet its recycling remains limited, with less than 1% of solid waste PP being reprocessed. Mechanical recycling through extrusion is the most practical method, but inconsistent reprocessing conditions introduce variability in material properties. While temperature, screw speed, and residence time influence the thermomechanical stress applied during reprocessing, there are no standardized guidelines for optimizing these parameters. This study examines how these factors shape the properties of recycled PP, using conditions designed to mimic post‐industrial recycled (PIR) scrap. Residence time was measured using colorimetric tracking and correlated with molecular weight, viscosity, and mechanical properties over multiple extrusion cycles. Data‐driven modeling, including response surface methodology, support vector machines, and artificial neural networks, identified processing temperature as the dominant factor in material degradation, followed by residence time. Mechanical properties remained stable, while viscosity decreased predictably with increasing residence time. By linking reprocessing conditions to property evolution, this study provides a method to optimize processing parameters and reduce variability in recycled PP. These findings help manufacturers improve process control, making recycled PP more predictable for reuse in manufacturing. Highlights Study of PIR‐quality PP without additives or compatibilizers. Residence time analysis shows processing temperature drives PP property changes. Mark‐Houwink enables quick molecular weight checks for quality control. Models predict mechanical and rheological shifts in reprocessing. Optimized processing parameters minimize property degradation in recycling.

Estela‐García, John E. [Polymer Engineering Center↗
DOE OSTI2022

In-process monitoring and prediction of droplet quality in droplet-on-demand liquid metal jetting additive manufacturing using machine learning

Abstract In droplet-on-demand liquid metal jetting (DoD-LMJ) additive manufacturing, complex physical interactions govern the droplet characteristics, such as size, velocity, and shape. These droplet characteristics, in turn, determine the functional quality of the printed parts. Hence, to ensure repeatable and reliable part quality it is necessary to monitor and control the droplet characteristics. Existing approaches for in-situ monitoring of droplet behavior in DoD-LMJ rely on high-speed imaging sensors. The resulting high volume of droplet images acquired is computationally demanding to analyze and hinders real-time control of the process. To overcome this challenge, the objective of this work is to use time series data acquired from an in-process millimeter-wave sensor for predicting the size, velocity, and shape characteristics of droplets in DoD-LMJ process. As opposed to high-speed imaging, this sensor produces data-efficient time series signatures that allows rapid, real-time process monitoring. We devise machine learning models that use the millimeter-wave sensor data to predict the droplet characteristics. Specifically, we developed multilayer perceptron-based non-linear autoregressive models to predict the size and velocity of droplets. Likewise, a supervised machine learning model was trained to classify the droplet shape using the frequency spectrum information contained in the millimeter-wave sensor signatures. High-speed imaging data served as ground truth for model training and validation. These models captured the droplet characteristics with a statistical fidelity exceeding 90%, and vastly outperformed conventional statistical modeling approaches. Thus, this work achieves a practically viable sensing approach for real-time quality monitoring of the DoD-LMJ process, in lieu of the existing data-intensive image-based techniques.

Gaikwad, Aniruddha (ORCID:0000000285642621)↗
DOE OSTI2024

A Gaussian process autoregressive model capturing microstructure evolution paths in a Ni–Mo–Nb alloy

Additive manufacturing is increasingly being employed to produce components of complex geometries in structural alloys because of the expected energy savings associated with the near-net-shape capability and the ability to build in novel internal features that are not possible with many conventional manufacturing approaches. However, because of the extreme thermal conditions encountered, the non-equilibrium microstructures produced during powder bed-based additive manufacturing processes must be subjected to custom post-heat treatment processes to recover the target mechanical properties. Phase-field models and simulation techniques have matured to a state where the microstructure evolution paths, and the morphologies of the resulting precipitate phases can be predicted reasonably accurately, considering alloy-specific thermodynamic and kinetic aspects of the nucleation and growth processes. However, phase-field simulations are computationally intensive, which precludes the ability to apply the simulations directly to the length scale of the entire component. Therefore, it is highly desirable to develop low-computational-cost surrogate models that effectively capture the physics at the microstructural length scale, while facilitating the design of optimized processing conditions resulting in location-specific targeted microstructures at the component scale. The work presented here demonstrates the application of the materials knowledge system framework to develop a surrogate model that effectively captures the microstructural path during annealing of a Ni–Mo–Nb alloy containing different Mo and Nb compositions known to segregate during solidification under additive manufacturing conditions. Specifically, the surrogate model built in this work is based on a Gaussian process autoregressive model informed by statistical representation of simulated microstructures using two-point correlations and dimensionality reduction through principal component analysis. In conclusion, this surrogate model is shown to capture the bifurcation of the microstructural path during precipitation, which yields a microstructure dominated by the $\gamma^{\prime\prime}$ phase at high Nb concentrations and the $\delta$ phase at low Nb concentrations.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Improvement of the Processes of Liquid-Phase Epitaxial Growth of Nanoheteroepitaxial Structures

We have revealed the shortcomings of equipment and technological approaches in growing nanoheteroepitaxial structures with quantum dots by liquid-phase epitaxy. We have developed and fabricated a new vertical barreltype cassette for growing quantum dots and epitaxial layers of various thicknesses in one technological process. A physico-mathematical simulation has been carried out of the processes of liquid-phase epitaxial growth of quantumdimensional structures with the use of the program product SolidWorks (FlowSimulation program). Analysis has revealed the presence of negative factors influencing the growth process of the above structures. The mathematical model has been optimized, and the equipment has been modernized without additional experiments and measurements. The flow dynamics of the process gas in the reactor at various flow rates has been investigated. A method for tuning the thermal equipment has been developed. The calculated and experimental temperature distributions in the process of growing structures with high reproducibility are in good agreement, which confirms the validity of the modernization made.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

Process-Defect-Structure-Property Correlations During Laser Powder Bed Fusion of Alloy 718: Role of In Situ and Ex Situ Characterizations

Components made by laser powder bed fusion (L-PBF) additive processes require extensive trial and error optimization to minimize defects and arrive at targeted microstructure and properties. In this paper, in situ infrared thermography and ex situ surface roughness measurements were explored as methodologies to ensure Inconel ® 718-part quality. For a given laser energy of 200 Watts, prismatic samples were produced with different exposure times (80 to 110 µs) and point spacings (80 to 110 µm). The infrared intensities from laser–material interaction zones were measured spatially and temporally. The conditions leading to higher IR intensity and lowest surface roughness values correlated well with less porosity and coarse solidification grain structure. The transition from highly columnar to misoriented growth is attributed to changes in thermal gradients and liquid–solid interface velocities. Hardness measurements and electron microscopy of the as-processed and post-processed heat-treated samples show complex transitions in microstructural states including the heavily dislocated FCC matrix, reduction of dislocation density, and copious precipitation, respectively. These results show that the geometry-process-structure-property correlations are dynamic, and they cascade depending on the transitions of phase states from powder to liquid to solid, as well as phase decompositions and deformations within the solid FCC phase. Finally, validity of using analytical weld process models to describe the above phenomena is also highlighted.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Kinetic Study on Alloying Element Transfer During an Electroslag Remelting Process

Experimental and theoretical studies have been carried out to investigate the effects of slag on the alloying elements in ingots during the electroslag remelting (ESR) process with a focus on developing a mass-transfer model to understand the mechanism of slag-metal reaction. Stainless steel 1Cr21Ni5Ti was used as the electrode and remelted with two different kinds of slags using a 50-kg ESR furnace. The contents of sulfur, aluminum, titanium and silicon along the axial direction of the produced ingots were analyzed. On the basis of the penetration and film theories, the theoretical model developed in this work elucidates the kinetics of the slag-metal reaction revealing the mechanism of alloying element transfer during the ESR process. The calculation results obtained from the model agree well with the experimental results. The model indicates that the resultant [O] coming from the desulfurization reaction of (O{sup 2−}) + [S] = (S{sup 2−}) + [O] causes the oxidation of alloying elements in steel by [M] + [O] = (MO). The distribution ratio of sulfur L{sub S} decreases with the increase of slag temperature in the first slag-temperature-rising period, and the concentration of sulfur in the ingot at the beginning of the ESR process is lower than in the rest of the process because of the combination of the large distribution ratio of sulfur L{sub S} and excellent kinetic conditions. The concentration of aluminum along the height of the ingot has an increasing trend in the first slag-temperature-rising period, while it has a decreasing trend in the rest of the process. Two methods can solve this problem: one is starting up the ESR furnace by high temperature molten slag technology and the other is continually adding extra titania into the molten slag in the first slag-temperature-rising period.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Process Evaluation of AISI 4340 Steel Manufactured by Laser Powder Bed Fusion

Laser powder bed fusion (L-PBF) involves the consolidation of metal powder, layer by layer, through laser melting and solidification. In this study, process parameters are optimized for AISI 4340 steel to produce dense and homogeneous structures. The optimized process parameters produce mechanical properties at the center of the build plate that are comparable to wrought in the vertical and horizontal orientations after heat treatment and machining. Four subsequent builds are filled with specimens to evaluate the mechanical behavior as a function of location and orientation. Variations in the mechanical properties are likely due to recoater blade interactions with the powder and uneven gas flow. The results obtained in this study are analyzed to assess the reliability and reproducibility of the process. A different build evaluates the performance of near-net-shaped tensile specimens angled 35°-90° from the build plate surface (horizontal). Ductility measurements and surface roughness vary significantly as a function of the build angle. In the stress-relieved and as-built conditions, the mechanical behavior of vertically oriented specimens exhibits somewhat lower and more variable ductility than horizontally oriented specimens. Therefore, several process variables affect the mechanical properties of parts produced by the L-PBF process.

36 MATERIALS SCIENCE↗