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At least 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Eliminating Yield Anisotropy and Enhancing Ductility in Mg Alloys by Shear Assisted Processing and Extrusion

Solid phase processing techniques such as friction stir welding, Shear assisted processing and extrusion (ShAPE)/ friction extrusion and cold spray have been successfully demonstrated as promising thermomechanical methods to produce metallic materials with enhanced performance. In this study, AZ series with and without silicon, ZK60 Mg alloys in as-received forms (as-cast or as-extruded) were processed using Shear Assisted Processing and Extrusion (ShAPE). Microstructural characterization was performed using EBSD and TEM and revealed that as compared to the feedstock materials/ billets, friction extruded Mg alloys had more uniform microstructure, equiaxed grains, finer and homogeneously distributed precipitates and chemical homogeneity. It was also observed that basal planes were not oriented parallel to extrusion axis. As a result, rod products exhibited significantly reduced (in some cases eliminated) yield asymmetry and achieved enhanced ductility, which were uncommon or difficult to attain using conventional processing techniques. In addition, modified texture likely suppressed deformation twinning under compressive deformation.

Shear Assisted Processing and Extrusion, SHAPE, ma↗
DOE OSTI2022

Techno-Economic Analysis for Co-Processing Fast Pyrolysis Liquid in Fossil Refineries

Recent work at the National Renewable Energy Laboratory (NREL) and throughout the bioenergy community has highlighted incentives associated with co-processing bio-intermediates in existing refineries to reduce capital costs associated with renewable fuels and chemicals production and reduce overall risk for emerging biomass conversion technologies. This presentation summarizes the techno-economic analysis results from the NREL-Petrobras collaboration that focused on refinery integration of fast pyrolysis oil through co-processing in the fluid catalytic cracking (FCC) process. The NREL-Petrobras work highlights the economic opportunity for refiners to engage in co-processing for low-carbon products and introduces the risks for refiners based on variability in crude and fossil-product markets. The NREL-Petrobras results also serve as a basis to inform policy design that reduces economic risk for refinery co-processing and repurposing opportunities. The final topics in the presentation highlight experimental capabilities and emerging analysis approaches at NREL and partner laboratories that support the development and commercial deployment of refinery utilization strategies.

bio-fuels↗
DOE OSTI2020

Thermal Process Technology for Nuclear Applications - 20379

ANSTO's Synroc technology has been developed to provide a safe, secure matrix for the immobilization and final disposal of radioactive waste. Synroc technology will be used to manage radioactive wastes from the production of the radioisotope Molybdenum-99 (Mo-99). This paper shall outline various stages of the process development with specific reference to the thermal treatment technology of calcination. Calcination is a key step in the Synroc process [1-2].The rotary thermal processing system includes: an advanced heating element design for increased robustness and ease of remote operation and maintenance, an enhanced modular design of components for ease of remote maintenance in a hot cell and in compliance with hot cell radioactive environment requirements for safety, reliability and maintainability. In addition to thermal treatment of waste from nuclear medicine production, this technology provides solutions for a variety of nuclear materials processing applications including sintering UO{sub 2} pellets for reactor fuel rods, oxidation of UO{sub 2} pellets, swarf, and powder to U{sub 3}O{sub 8}, de-nitration of Uranyl nitrate and hydrofluorination of UO{sub 2} pellets. The paper will also discuss thermal processing solutions for a range of nuclear applications. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Overview of Upcoming Process Improvement Efforts at the Saltstone Facilities at the Savannah River Site - 20474

The Saltstone Facilities at the Savannah River Site (SRS) process and dispose of low activity salt solution waste generated by other liquid waste facilities. Today in the Liquid Waste System (LWS), approximately 125 million liters of salt waste remain to be processed. The Saltstone Production Facility (SPF) receives the decontaminated salt waste, which is mixed with dry feeds consisting of cement, fly ash and slag to produce the saltstone. The mixed slurry is pumped to the Saltstone Disposal Units (SDUs) for safe disposal in the Saltstone Disposal Facility (SDF). To support continuous Salt Waste Processing Facility (SWPF) operations at annual processing volumes many times higher than present, significant modifications are required to ensure that the SPF has the capacity to support the throughput of salt waste. These changes include several infrastructure upgrades that are being worked through the Enhanced Low Activity Waste Disposal (ELAWD) project. In addition to infrastructure upgrades, Savannah River Remediation (SRR), the Savannah River Site's Liquid Waste Contractor for the U.S. Department of Energy, has identified a flowsheet improvement opportunity of implementing a cement-free saltstone formulation to eliminate cement from the current three component formulation. This two-component formulation would simplify the procurement, transport, off-loading, and storage of the premix materials, and increase the storage capacity for the individual components. This flowsheet, when implemented, will reduce operational risk and improve throughput necessary to achieve disposal rates necessary for SWPF operations. Research has been completed to confirm the feasibility of this formulation, with the new cement-free flowsheet expected to be implemented in the next few years. Improvements have also been identified downstream of the SPF to increase SDU utilization. Specifically, a concentrated effort has taken place to raise the fill height in SDU 6 to the full disposal height, 13 meters, to maximize the usage of each SDU in support of the liquid waste disposal mission. This improvement has been made through additional thermal modeling and improved process understanding to create a SDU flammability model and control strategy more representative of facility operations. This work will allow for the completion of construction and operational readiness for SDU 7 while filling SDU 6 to ensure there is no lapse in available space once SWPF starts up. A summary of these improvements as they relate to increased throughput will be provided along with associated status. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

A New Understanding of Decarbonizing Industrial Process Heat

Analysis conducted over the last few years has improved our understanding of how industrial process heat is used in the United States. These improvements are important for characterizing the possibilities for industrial decarbonization. However, this analysis has largely been conducted from technical perspective and has remained disconnected from the social processes that underlie how industrial firms may adopt and implement technologies to decarbonize their process heating operations. This presentation introduces the concept of generic and configurational technology systems, and outlines the how the incorporation of user requirements and local contexts are essential for successful implementation of configurational systems. Insights drawn from semi-structured interviews with representatives of industrial firms are used to support the hypothesis that industrial process heat technologies are configurational. The potential implications for strategies to decarbonize process heat are then discussed.

adoption↗
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)↗