Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Batch processing”

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 649 records · Page 36

Plant-Scale Concentration Column Designs for SHINE Target Solution Utilizing AG 1 Anion Exchange Resin

Argonne is assisting SHINE Medical Technologies (SHINE) in their efforts to develop SHINE, an accelerator-driven process that will utilize a uranyl-sulfate solution for the production of fission product Mo-99. An integral part of the process is the development of a column for the separation and recovery of Mo-99, followed by a concentration column to reduce the product volume from 15-25 L to <1 L. Argonne has collected data from batch studies and breakthrough column experiments to utilize the VERSE (Versatile Reaction Separation) simulation program (Purdue University) to design plant-scale product recovery and concentration processes.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Optimization of a Lithium Ion Battery Bioleaching Process Utilizing Organic Acids Produced by Gluconobacter oxydans

Growing our global economic and environmental focus relies, in part, on our development of a sustainable system to recycle valuable metals. This endeavor to recycle these elements falls within the scope of Idaho National Laboratories (INL) mission to pursue new sustainable energy systems that are competitive. To succeed in this endeavor in not only a low-cost but environmentally safe practice, Gluconobacter oxydans was utilized for its ability to produce a bio-lixiviant known for its critical material leaching abilities. G. oxydans is a rod-shaped, gram negative, acidophilic, and obligately aerobic organism. Unlike many other aerobic organisms, it does not completely oxidize its carbon sources to water and carbon dioxide. Instead it incompletely oxidizes its substrates to aldehydes, ketones and organic acids. Because of this metabolic pathway, it was utilized in a batch reactor setting to produce sufficient amounts of a low-pH bio-lixiviant so that leaching processes could be performed on lithium ion battery cathode powders. Some of these processes included adding different molar ratios of a redox agent to the produced bio-lixiviant, alternating concentrations of lithium ion battery cathode powders, varying leaching time, and changing the temperature each leach was performed at. From this, a biohydrometallurgy process was successfully created for the leaching of cobalt from lithium ion cathode powders This project provided a multitude of laboratory and research experiences that resulted in ample opportunity for professional and personal growth. In addition to this, the INL experience fostered the development of many personal skills and business skills to assist in future career opportunities.

25 ENERGY STORAGE↗

Evolution of AISI 304L stainless steel part properties due to powder recycling in laser powder-bed fusion

Selective laser melting (SLM) is a powder-bed fusion process in Additive Manufacturing (AM) that uses a laser beam to selectively fuse layers of powder into near net-shape components with little porosity. However, inconsistencies in the part properties due to the presence of defects in as-built components has hindered the widespread adoption of SLM for industrial applications forcing researchers to study the sources of variation for quality control purposes. A critical area suspected of creating variation in the part properties is the feedstock, where batch-to-batch differences as well as changes in the powder properties with reuse have the potential to affect performance. During processing, laser spatter and condensate eject from the melt pool and deposit into the powder-bed surrounding the parts. These particulates, more commonly known as ejecta, differ morphologically and chemically from the virgin powder compromising its reusability. In this study, 304L stainless steel powder was recycled for a total of 5 times through a systematic approach aimed at accelerating powder degradation to reveal the influence on both the tensile and impact toughness properties. Through analysis of variance (ANOVA), it was found that tensile properties did not change with reuse, while the impact toughness showed a steady decline illustrating the differences in static and dynamic part properties due to powder recycling.

36 MATERIALS SCIENCE↗

Advancing continuous enzymatic hydrolysis for improved biomass saccharification

Background: A deployable, continuous enzymatic hydrolysis (CEH) process can address cost and commercialization risks associated with second-generation (Gen2) biorefinery sugar/lignin/ethanol production while contributing to energy supply and security. Developments in commercial enzymatic hydrolysis formulations targeting Gen2 pretreated biomass such as deacetylated mechanically refined (DMR) biomass necessitate a reassessment of the existing hybrid simultaneous saccharification and fermentation (SSF) approach. Notably, the practice of "finishing hydrolysis" in SSF has become problematic with the introduction of oxidative enzymes, such as lytic polysaccharide monooxygenases (LPMOs), into commercial cellulase formulations as these require specific redox conditions and cofactor. Moreover, continuous SSF has not been demonstrated at commercial scale, limiting deployment and the associated economic benefits to farmers, producers, and support industries. Results: Continuous enzymatic hydrolysis (CEH) was demonstrated at bench scale to enable optimal saccharification performance of deacetylated mechanically refined (DMR) pretreated biomass. Diafiltration was demonstrated to retain pretreated biomass solids and enzymes for continuous reaction while removing solubilized product sugars in situ. A significant breakthrough afforded by the CEH process is its ability to achieve equivalent endpoint conversions with approximately 50% lower enzyme loading. Yields of glucose and xylose were increased ~ 15% and ~ 4%, respectively, over batch hydrolysis. Unlike SSF using yeast or Zymomonas, CEH allows precise optimization of pH, temperature, oxygen tension, LPMO mediator concentration, and removal of end-product inhibitors. Conclusions: Advanced CEH holds promise as a transformational, process-intensified, and cost-effective method for producing soluble clarified biomass sugars and insoluble lignin-rich streams. Enhancing saccharification performance, optimizing operating parameters, and employing membrane filtration will help overcome existing challenges and enable the efficient production of valuable biomaterials from lignocellulosic biomass.

09 BIOMASS FUELS↗

Process Development for Hydrothermal Liquefaction of Algae Feedstocks in a Continuous-Flow Reactor

Wet algae slurries can be converted into an upgradeable biocrude by hydrothermal liquefaction (HTL). High levels of carbon conversion to gravity-separable biocrude product were accomplished at relatively low temperature (350 °C) in a continuous-flow, pressurized (sub-critical liquid water) environment (20 MPa). As opposed to earlier work in batch reactors reported by others, direct oil recovery was achieved without the use of a solvent and biomass trace components were removed by processing steps so that they did not cause process difficulties. High conversions were obtained even with high slurry concentrations of up to 35 wt% of dry solids. Catalytic hydrotreating was effectively applied for hydrodeoxygenation, hydrodenitrogenation, and hydrodesulfurization of the biocrude to form liquid hydrocarbon fuel. Catalytic hydrothermal gasification was effectively applied for HTL byproduct water cleanup and fuel gas production from water soluble organics, allowing the water to be considered for recycle of nutrients to the algae growth ponds. As a result, high conversion of algae to liquid hydrocarbon and gas products was found with low levels of organic contamination in the byproduct water. All three process steps were accomplished in bench-scale, continuous-flow reactor systems such that design data for process scale-up was generated.

algae↗

A dimensionless number for high-throughput design of multi-principal element alloys in directed energy deposition

The present study demonstrates the development of a dimensionless number to predict the build height in the additive manufacturing technique of directed energy deposition (DED). The build height can also be used to estimate the dendrite arm spacing and, thus, the cooling rate in the fabrication of samples. A baseline sample, 316L stainless steel, was used to fit the build height to the dimensionless number. A range of process parameters, including laser power, laser feed rate, powder flow rate, layer thickness, and hatch spacing, were varied. Based upon dendrite arm spacing, the estimated cooling rate varied between 102 and 104 K/s. Using the fitted relationship for the stainless steel, high-throughput (HT) processing of multi-principal element alloys (MPEAs) was performed. For this study, HT is the ability to fabricate a batch of 25 bulk samples (∼1 cm3) with different compositions within a 5-h period with ±10 at. % accuracy. A range of compositions using in situ alloying of elemental powders in the Fe–Ni–Cr–Mo system were made. The MPEAs' build height followed the same relationship to the dimensionless number as the 316L alloy. The dimensionless number predicts both macro and meso-scale features in HT processing, thus offering a design tool for choosing process parameters in DED additive manufacturing. Also, the ability to control or increase cooling rates can enhance the ability to promote metastability as well as control meso-scale chemical distributions of alloy samples.

Islam, Zahabul (ORCID:0000000169613209)↗

SU-E-T-531: Performance Evaluation of Multithreaded Geant4 for Proton Therapy Dose Calculations in a High Performance Computing Facility

Purpose: To evaluate the efficiency of multithreaded Geant4 (Geant4-MT, version 10.0) for proton Monte Carlo dose calculations using a high performance computing facility. Methods: Geant4-MT was used to calculate 3D dose distributions in 1×1×1 mm3 voxels in a water phantom and patient's head with a 150 MeV proton beam covering approximately 5×5 cm2 in the water phantom. Three timestamps were measured on the fly to separately analyze the required time for initialization (which cannot be parallelized), processing time of individual threads, and completion time. Scalability of averaged processing time per thread was calculated as a function of thread number (1, 100, 150, and 200) for both 1M and 50 M histories. The total memory usage was recorded. Results: Simulations with 50 M histories were fastest with 100 threads, taking approximately 1.3 hours and 6 hours for the water phantom and the CT data, respectively with better than 1.0 % statistical uncertainty. The calculations show 1/N scalability in the event loops for both cases. The gains from parallel calculations started to decrease with 150 threads. The memory usage increases linearly with number of threads. No critical failures were observed during the simulations. Conclusion: Multithreading in Geant4-MT decreased simulation time in proton dose distribution calculations by a factor of 64 and 54 at a near optimal 100 threads for water phantom and patient's data respectively. Further simulations will be done to determine the efficiency at the optimal thread number. Considering the trend of computer architecture development, utilizing Geant4-MT for radiotherapy simulations is an excellent cost-effective alternative for a distributed batch queuing system. However, because the scalability depends highly on simulation details, i.e., the ratio of the processing time of one event versus waiting time to access for the shared event queue, a performance evaluation as described is recommended.

60 APPLIED LIFE SCIENCES↗

Scalable deep text comprehension for Cancer surveillance on high-performance computing

Background: Deep Learning (DL) has advanced the state-of-the-art capabilities in bioinformatics applications which has resulted in trends of increasingly sophisticated and computationally demanding models trained by larger and larger data sets. This vastly increased computational demand challenges the feasibility of conducting cutting-edge research. One solution is to distribute the vast computational workload across multiple computing cluster nodes with data parallelism algorithms. In this study, we used a High-Performance Computing environment and implemented the Downpour Stochastic Gradient Descent algorithm for data parallelism to train a Convolutional Neural Network (CNN) for the natural language processing task of information extraction from a massive dataset of cancer pathology reports. We evaluated the scalability improvements using data parallelism training and the Titan supercomputer at Oak Ridge Leadership Computing Facility. To evaluate scalability, we used different numbers of worker nodes and performed a set of experiments comparing the effects of different training batch sizes and optimizer functions.Results: We found that Adadelta would consistently converge at a lower validation loss, though requiring over twice as many training epochs as the fastest converging optimizer, RMSProp. The Adam optimizer consistently achieved a close 2nd place minimum validation loss significantly faster; using a batch size of 16 and 32 allowed the network to converge in only 4.5 training epochs.Conclusions: We demonstrated that the networked training process is scalable across multiple compute nodes communicating with message passing interface while achieving higher classification accuracy compared to a traditional machine learning algorithm.

Qiu, John X.↗

Process optimization of caustic scrubber and iodine-129 immobilization in sodalite-based waste forms

Caustic scrubbers are proposed to remove vaporized iodine from nuclear fuel reprocessing plants. Resulting caustic slurries of radioactive iodine ( 129 I) and other anions can be captured and immobilized into the cage structures of sodalite-type minerals. Here, mixed anion sodalites were hydrothermally synthesized from a simulated caustic scrubber solution containing hydroxide/water, carbonate, chlorine, bromine, iodine, nitrate, and nitrite ions with added kaolinite. Experiments were conducted with twenty-five different sets of process conditions. Resulting powders were characterized by quantitative X-ray diffraction (XRD) and multi-functional thermal analysis, including gravimetry, calorimetry, and mass spectrometry. Using statistical analysis, process variables were tailored to maximize conversion of kaolinite into cage silicates, immobilize caustic scrubber anions, and minimize amorphous content. Further, chemical analysis showed the incorporation of all the targeted ions into the solids. Detailed investigation of a batch characterized after washing (creating secondary waste) and one without washing but subsequent calcination is given. This work contributes to defining the constraints required for subsequent consolidation process steps of the waste form to avoid volatilization.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Preshaping clear glass at low temperatures

Advances in available glass chemistries and glass processing methods have accompanied and enabled some of the biggest technology revolutions, from the development and mass production of light bulbs to low-loss fiber optics and durable smartphone touchscreens. An emerging generation of low-temperature processing technologies aims to continue this important trend and make a broader array of glass components mass producible. In the issue, Mader et al. (1) describe one such innovation in glass processing—the use of low-temperature injection molding to preshape silica particle–filled composites that can later be transformed into transparent fused silica glass objects. Traditionally, transparent glass objects are manufactured in high volume from molten or softened glass, which is floated, drawn, blown, cast, or blow-molded to a desired shape (see the figure, top). The glass composition and processing technique dictate the working temperature, which is usually quite high (near 1000°C) and often restricts the choice of compatible equipment or limits the choice of glass composition. Because geometry-specific capital investment is required for production, drastic or frequent component design changes or small batches may be cost prohibitive. Alternatively, transparent glass components can also be shaped at ambient temperature from solid glass by a series of subtractive processes, including cutting or multiple stages of grinding, followed by slower processing steps, such as polishing or etching. This approach is somewhat less amenable to mass production, and certain geometries containing tool-inaccessible regions cannot be fabricated in this way. Several emerging glass-shaping technologies aim to reduce the required manufacturing temperatures and still provide access to a broader range of glass compositions and component geometries (see the figure). These approaches use a three-step process. First, a desired shape is preformed at low temperature from a glass-forming, organic-inorganic composite. Next, the preform is dried, and organic materials used to bind particles are removed. Finally, the preform is heated (sintered) well below the glass-melting temperature to densify to transparent glass. Although the second and third steps do occur at increased temperatures, only standard, geometry-agnostic driers and furnaces are required. This strategy builds on the well-studied sol-gel approach to forming monolithic glass, where silica network–forming chemical solutions are poured into molds, slowly dried, and condensed into dense glass without melting (2). In a departure from the sol-gel process, these new technologies use solvents, cross-linkers, and polymers to formulate organic-inorganic composites tuned for compatibility with a particular shaping process, with formats ranging from photocurable liquids to shear-thickening pastes to solids. The composite inorganic loadings are also typically higher than those in the pure sol-gel approach, which drastically reduces shrinkage in comparison.

36 MATERIALS SCIENCE↗

In‐situ Analysis of Paste Properties in Resonant Acoustic Mixers for Quality Monitoring

Formulation control is key to achieving consistent target properties of energetic materials, as feedstock variations and slight deviations in the ratios of different ingredients can have major effects on final product properties, particularly in dense pastes with high particle loading >65 vol.%. In large‐scale operations, it is imperative to either correct or remove batches of material that perform outside baseline property specifications as early as possible to avoid unnecessary processing of suboptimal material. Quality monitoring is the practice of measuring material properties during processing using process analytical technologies as opposed to only testing the properties of the final product; it is a key principle in the quality‐by‐design frameworks used for designing formulations and manufacturing processes. Herein, a process analytical technology method for correlating material properties of dense pastes directly after mixing in a Resonant Acoustic Mixer to motor data is developed and used to detect differences in the particle content of dense paste formulations. This method was also capable of detecting variations in powder feedstock properties, such as particle packing efficiency, and is sensitive enough to detect changes of 2 wt.% in the total solids content of the formulation. The techniques presented herein show excellent promise for use as a process analytical technology capable of quantifying formulation effects on material movement modes during resonant acoustic mixing.

Materials science↗

Effect of water vapor and thermal history on nuclear waste feed conversion to glass

Water affects the glass melting process by interacting with the foam layer at the glass melt surface and by influencing the batch conversion reactions. Water vapor from the nuclear waste slurry feed maintains a high water vapor pressure in the melter atmosphere. To investigate to what extent water vapor affects the vitrification of nuclear waste in joule-heated, cold-top melters, a series of feed expansion experiments were performed under humid and dry atmospheres using samples of low-activity waste (LAW) melter feed simulants. Melting of feed pellets in the presence of water vapor slightly decreased the temperature of primary foam onset, but did not significantly affect the feed volume expansion by foaming or the foam-collapse temperature. Sets of feed expansion experiments and evolved gas analyses were also performed to check the effect of thermal history on LAW feed samples tested as direct slurry, loose powder, and slow- and fast-dried pellets.

Marcial, Jose↗

Software For Automated Leak Detection Using Infrared Camera

This code can read in videos or images in either a batch or real-time format. Videos are broken up into frames, and the frames are processed using an optical flow algorithm to decipher movement between adjacent frames. This adherent movement is ran through a convolutional neural network that automatically classifies the contents of the video. Additional content inside the code aids with noisy images and removal of nuisance movement.

Walker, CodyM. [Idaho National Laboratory (INL), I↗

Big PanDa Workflow Management on Titan for High Energy and Nuclear Physics and for Future Extreme Scale Scientific Application

Over a three year period, from 2016-2019, this project demonstrated the scientific benefits of integrating the Titan supercomputer at Oak Ridge Leadership Computing Facility into traditional high throughput grid based distributed computing systems managed by PanDA, the workflow management system used for the execution of all distributed computing applications by the ATLAS experiment at the Large Hadron Collider. PanDA manages millions of batch jobs daily at hundreds of clusters worldwide on request by thousands of physicist users, and processes more than an exabyte of data annually using grid middleware. High levels of operational use of Titan was sustained by PanDA in order to meet the physics goals of ATLAS. The success of this project led to the use of other supercomputers worldwide by ATLAS, and to the adoption of PanDA by other experiments and other scientists. Multiple innovative operational and computer science research goals were achieved supporting the use of supercomputers for scientific domains with large scale distributed data and distributed processing needs.

97 MATHEMATICS AND COMPUTING↗

Uranium Solubility and Supernate Enrichment Testing for Accelerated Basin De-Inventory Discards to Concentration, Storage, and Transfer Facilities

After future Accelerated Basin De-inventory (ABD) enriched uranium discards into sludge batches (SB), portions of supernate decants during SB preparation will be blended into salt batches (StB) and the resulting feeds must meet the nuclear safety requirements for the Salt Waste Processing Facility (SWPF). During previous SB10 sampling and testing, which involved H-Canyon material containing enriched uranium being mixed with Tank 51 sludge shortly after the H-Canyon stream was neutralized, it was identified that the uranium isotopic enrichment in the supernate deviated from the uranium isotopic enrichment in the slurry. The higher uranium isotopic enrichment in the supernate introduced the risk of challenging the feed requirements of SWPF. The ABD material added to SB11 was isotopically diluted with depleted uranium, mitigating any downstream impacts. However, H-Canyon desires to eliminate or minimize future depleted uranium additions in order to meet the mission schedule.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

2.2.3.106 - Lignin-First Biorefinery Development

The Lignin-First Biorefinery Development (LigFirst) project aims to develop a cost-effective, and scalable biomass fractionation strategy based on reductive catalytic fractionation (RCF). The RCF process uses a protic solvent, hydrogen gas or a hydrogen donor, and a metal catalyst in the presence of intact biomass to produce a stable, depolymerized lignin oil and a polysaccharide pulp, which can both be converted to value-added products in parallel processes. RCF is a promising strategy to enable the use of woody feedstocks in biochemical conversion processes and is also promising as a means to valorize lignin with equal emphasis to biomass carbohydrates. Guided by techno-economic analysis and life cycle assessment and in collaboration with industry partners, we are actively developing RCF methods to 1) avoid the need for exogenous hydrogen gas, 2) substantially reduce reactor pressure via use of low vapor pressure solvents, 3) separate the lignin solvolysis and catalytic processes through reaction engineering solutions, 4) reduce solvent loading below what can be achieved in typical batch reactors, and 5) avoid or minimize the use of organic solvents. The LigFirst project also collaborates closely with the Lignin Utilization and Lignin Conversion-to-SAF projects for critical substrate handoffs and analytics. Overall, the LigFirst project is enabling new approaches that ultimately can enable RCF to be a feedstock-agnostic method to valorize both polysaccharides and lignin.

BIOMASS FUELS↗