SEARCH · Engineering Papers

Results for “Production Processes”

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.

SourceResearch connectionFrom yearThrough year

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

At least 145 records · Page 8

All sources NASA NTRS DOE OSTI

DOE OSTI2024

A Review on Solid State Batteries: Life Cycle Perspectives

This report briefly reviews the characteristics of solid-state batteries (SSBs) and the life-cycle analysis (LCA) studies that have been completed for SSBs. Compared with conventional lithium-ion batteries (LIBs), SSBs offer improved safety and potentially higher energy density — both enabled by replacing liquid electrolytes with solid electrolytes and using lithium metal anodes. Several challenges impede the commercialization of SSBs, primarily related to the stability of the interface between the solid electrolyte and the electrodes. Several options are under consideration for SSB electrolyte and cathode chemistries. As a result, the production processes for these components and the corresponding battery packs are still under development and can differ significantly from those used for conventional LIB pack production. A robust comparison of SSBs with LIBs through LCA is important to analyze the environmental benefits and challenges associated with this alternative battery system. While the literature provides only a few LCA studies focused on SSBs, with significant uncertainty in their life-cycle inventories (LCIs), those studies collectively suggest that solid electrolyte manufacturing is the major environmental hotspot, followed by cathode and anode production.

25 ENERGY STORAGE↗

DOE OSTI2020

Analyzing Next-Generation Supply Chains Using the Materials Flows through Industry Tool

The Materials Flows through Industry (MFI) tool is a supply chain modeling tool developed at the National Renewable Energy Laboratory (NREL) with funding from the Department of Energy's Advanced Manufacturing Office. MFI was created to identify and analyze opportunities to reduce the energy and carbon intensities of the U.S. industrial sector (Hanes and Carpenter 2017). In this work, we present an overview of the MFI tool's structure and capabilities, as well as the results of using MFI to analyze a novel NREL-developed process to 'upcycle' PET plastic into higher-value composite materials (Rorrer et al. 2019). This process combines recycled PET (rPET) plastic with inputs that can be derived from biomass, including muconic acid, acrylic acid, and ethylene glycol, to chemically break down the plastic back to its monomers in a process called glycolization. Then, repolymerization and the application of fiberglass yields the valuable glass fiber reinforced plastic (GFRP) composite, a performance material used in the manufacture of wind turbine blades, boat hulls, and other applications. This rPET-derived GFRP was found to have superior strength and fiberglass adhesion compared to conventional GFRP formulations. Our findings indicate that this GFRP production process, were it to be widely commercialized beyond its current lab-scale, could potentially reduce the fossil energy intensity of the GFRP supply chain by between 37% and 58% compared to the conventional method of GFRP manufacture from fossil-derived inputs. We also estimate potential supply chain greenhouse gas (GHG) emissions reductions between 30% and 40% from this process. Scaling these GHG offset estimates up to annual GFRP production in the U.S. would be roughly equivalent to removing between 150,000 and 200,000 vehicles from U.S. roads. These ranges of impact estimates represent the range of differences associated with the various economic allocation methods we have assumed for the intensity contributions from the first life of the PET plastic. Following Shen et al. (2010), we derive economic allocation factors from the current price ratios of clear- and green-colored recycled PET plastic to virgin PET resin ('waste-valuation' approach) or assume them to be zero in a more simplistic allocation ('cutoff' approach). Future work involving the MFI modeling tool will also be discussed, including preliminary results comparing the energy intensity of conventional and bio-based nylons manufacturing. Attendees will also be encouraged to conduct MFI supply chain modeling of their own by requesting a user account on the MFI web application, which is freely available to the public at the following address: https://mfitool.nrel.gov.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Comparison of Commercial, State-of-the-Art, Fossil-Based Ammonia Production

This NETL report provides a comprehensive techno-economic analysis of current, state-of-the-art, fossil-based ammonia production processes, explicitly utilizing natural gas as the feedstock. The study thoroughly investigates three distinct configurations: conventional Steam Methane Reforming (SMR) without carbon capture, SMR integrated with carbon capture and storage (CCS), and Autothermal Reforming (ATR) also with CCS. The analysis incorporates detailed equipment cost accounting as part of its methodology. The primary objective is to meticulously evaluate the cost and performance of these established and emerging technological pathways, considering factors such as capital expenditures, operational costs, and energy consumption. While the report acknowledges and quantifies environmental impacts, its central focus remains on the economic and technical feasibility of each process design employing these current technologies. The analysis provides a direct comparison of the Levelized Cost of Ammonia (LCOA) for each pathway, revealing how the integration of CCS within these state-of-the-art systems impacts the overall production cost. The ATR+CCS configuration, representing an advanced approach, emerged with a slightly more favorable LCOA compared to SMR+CCS. This benefit was attributed to its inherent process efficiencies, high carbon capture rates, and economy of scale advantages. The report details the energy consumption profiles for each case, including metrics like net energy consumption and thermal efficiency, which are critical for assessing the performance of these contemporary industrial processes. Sensitivity analyses further explore how variables such as natural gas price, capital costs, and capacity factors influence the LCOA across all scenarios, offering critical insights into the economic robustness and scalability of these current ammonia production technologies.

03 NATURAL GAS↗

DOE OSTI2022

Radiation Shielding Analysis of Niowave’s Uranium Target Assembly 2 (UTA-2) Facility for Molybdenum-99 Production

Niowave is seeking to develop a commercial medical isotope production process using a low-enriched uranium accelerator-driven subcritical reactor (ADSR) system to produce molybdenum-99. As part of the US Department of Energy national laboratory support to develop low enriched uranium molybdenum-99 production technologies, Oak Ridge National Laboratory is providing research and development resources to assist Niowave in the design and licensing process of its technology. The goals of this work under the radiation shielding task are to assist Niowave in developing a methodology and framework for efficient radiation shielding simulations of their Uranium Target Assembly 2 facility and to provide preliminary radiation shielding calculations and design recommendations for the facility.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2025

Lightweight Metal Stamping Optimization Enabled by Artificial Intelligence

Successfully manufacturing an automotive body structure made via the sheet metal stamping process depends upon simultaneous consideration of component design, tooling design, stamping process control, and material properties. In many cases, introducing lightweight sheet materials (e.g., aluminum alloys, magnesium alloys, advanced high strength steels) holds the potential to significantly reduce vehicle weight, but challenges the stamping process by introducing materials with inherently less ductility. Successful and repeatable applications require co-developing the stamping process controls with the varying material properties, including formability. During the stamping process, as soon as the forming limit of the sheet is exceeded, the material shows localized necking which quickly leads to splits. Controlling process variability to avoid these material splits will enable deployment of less formable, lighter, and stronger materials for stamped automotive components. A typical optimization procedure for manufacturing requires an iterative process involving parameter setting, execution of computational simulations, and modifying the parameters. The entire process demands substantial computational time, making it impractical for real-time feedback towards rapid corrective actions required for in-line control for running production processes. To overcome this challenge, artificial intelligence (AI) can be leveraged to determine optimal manufacturing parameters within a single manufacturing cycle time. This research proposes an in-line optimization framework incorporating a trained AI model to predict kidney-shaped die forming. Preliminary results indicate that the AI framework can accurately predict draw-in values based on a given parameter set, a process referred to as forward prediction. Furthermore, the AI framework can also predict the optimal parameter set that leads to the desired draw-in values, referred to as inverse optimization (or backward prediction). This research has been performed in collaborations with USCAR (US Council for Automotive Research) and AutoForm. The members of USCAR are Ford, GM, and Stellantis.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Techno-economic and Life Cycle Analysis of MixAlco® Processes for Mixed Alcohol Production from Brown Algae

The need for producing renewable fuels from biomass has increased due to depleting fossil resources and environmental concerns. However, the low fraction of biomass carbon converted to product is an undeniable drawback for most current biofuel productions from fermentation due to undecomposed lignin in biomass composition and carbon loss as CO 2 . In this work, two main production routes of the MixAlco® process, the ketonization route (KR) and esterification route (ER) are evaluated for the mixed alcohol production by brown algae, a third-generation biomass without lignin. A novel fermentation process using syntrophic bacteria consortia (SBC) is developed to produce acetic acid from waste gas produced by KR and ER process. The paper investigates the integrated flowsheet for these alternative routes, using techno-economic and life cycle analysis to compare the minimum selling price and environmental impacts. From TEA, we find that the overall costs for KR and ER are lower than the SBC processes. The cost of ketonization routes is lower than esterification routes. The capital cost and operating cost for the ER+SBC process are the highest. Raw materials and utilities are the two major costs for all the processing routes examined. Here, the MSP for the ER+SBC process is the lowest out of all four routes. ER process performs the best in terms of environmental impacts except in water depletion compared with other processes, while the KR process performs the worst regarding the environmental metrics.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Building a Prospective LCA Framework to Analyze Emerging Technologies in a Dynamic System Context

NREL's Lifecycle Analysis Integration into Opensource Numerical models (LiAISON) framework computes temporally explicit life cycle impacts and resource uses for specific technologies (foreground) in a dynamic system context (background). LiAISON computes results for a series of environmental mid-points enabling an analysis of prospective tradeoffs of emerging technologies toward 2100. This prospective feature is of critical importance when analyzing present-day emerging technologies whose large-scale impacts during deployment phases will occur in different, future system contexts. LiAISON systematically accounts for dynamic system changes by applying an integrated background of the future energy-economy-land-climate system, generated by exogenous integrated assessment models (IAMs). Using IAM scenarios, LiAISON generates a time-series of life cycle inventory (LCI) databases, which are then used to calculate the impacts per functional unit per time step. This expands current practice of using static, future system assumptions, e.g., a specific grid-mix each year. Further, IAM scenarios are provided in a standardized format of shared-socioeconomic pathways (SSP) and representative concentration pathways (RCP) combinations. These are coherent, regularly, published, and peer-reviewed scenario combinations that establish a reproducible and standardized societal and climate mitigation futures context. They are comparable across IAMs and expand the system boundary of the traditional LCA by including dimensions such as societal and behavioral changes. We apply the framework to assess two emerging Power-to-Hydrogen processes, high temperature electrolysis using solid oxide fuel cell (HT-SOE) and polymer electrolyte membrane electrolysis (PEME). We compare the technologies to a baseline Hydrogen production process via steam methane reforming. Despite the decarbonized electricity systems' beneficial effects on the PtH2 processes' carbon intensities, we find environmental tradeoffs, which require technology improvements via learning-by-doing to be alleviated. Future work via ongoing collaborations will focus on linking the framework to other energy-economy-land-climate models and open-source life cycle inventory databases.

ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Internal defect detection and characterization of samarium-cobalt sintered magnets by ultrasonic testing technique

Excessive quantities of samarium-cobalt (Sm-Co) magnet material are being scrapped needlessly due to a lack of understanding of inhomogeneity distribution and unacceptable internal defects. If there is a way to identify, locate, characterize and when needed separate the defective portions of magnet material, utilization can be increased and product quality improved. Further, the magnets’ magnetic and mechanical performance can be improved by reducing the occurrence of internal defects. This paper reports on a cost-effective and efficient nondestructive evaluation method based on an ultrasonic testing (UT) technique applied for detecting and characterizing internal defects in Sm-Co sintered magnets. Applying the UT technique will allow users to comprehensively analyze internal defects, such as inclusions, porosity, microcracks, and other structural irregularities, check for homogeneity and anomalous regions and give the locations of these internal anomalies and defects within the Sm-Co sintered magnets. The UT technique can also be applied to other rare-earth permanent magnets, such as sintered or die-upset neodymium-iron-boron (Nd-Fe-B) magnets. The UT technique can effectively guide quality control and acceptable product selection, in addition to optimizing the magnet alloy design and production processes. Therefore, it can facilitate the improvement of magnet manufacturing efficiency and machinability, reduce scrap, prolong service life, increase the use of what would be post-production waste, and enhance product reuse and recycling at end-of-life disposition.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Multi-Analytical Investigation of Arsenical Transfer and Remediation on Nineteenth-Century Green Books

Books containing heavy metals, specifically nineteenth-century green arsenical books, have been identified at Northwestern University Libraries, raising health and safety concerns related to handling. Copper acetoarsenite pigments, such as emerald green, were detected on book covers, decorative page edges, labels, and other components using noninvasive analytical techniques including X-ray fluorescence (XRF), Raman spectroscopy, and Fourier-transform infrared (FTIR) spectroscopy. Further examination of selected volumes using synchrotron radiation (SR) techniques revealed pigment migration, degradation, and arsenic transfer to adjacent books. This paper expands on initial findings through two related experiments. The first explored the transfer of arsenic using mechanical friction; Staedtler Mars® white vinyl erasers rubbed on arsenical books generated crumbs which were analyzed via scanning electron microscopy–energy-dispersive X-ray spectroscopy (SEM-EDX). Results confirmed the transfer of arsenic, copper, and lead, with decorative page edges being particularly prone to shedding arsenic onto other materials. The second experiment tested remediation methods on a book contaminated by prolonged exposure to an arsenical neighbor. Surface cleaning using erasers and a vacuum removed flecks of pigment but did not eliminate non-chromophoric arsenic as confirmed by SR analyses, which highlights its presence either as a degradation product embedded within the paper or present in the paper as part of its production process. Findings demonstrate the acute toxicity risk posed by arsenical books and support the need for safe handling protocols. However, materials with only trace levels of arsenic embedded during production may pose a lower risk of transfer. Cross contamination beyond prolonged direct contact appears limited. These results highlight critical considerations for library preservation practices and future research on arsenic in historical materials.

arsenic↗

DOE OSTI2022

Case studies of robots and automation as health/safety interventions in small manufacturing enterprises

This article reviews the experiences of 63 case studies of small businesses (<250 employees) with manufacturing automation equipment acquired through a health/safety intervention grant program. The review scope included equipment technologies classified as industrial robots (n = 17), computer numerical control (CNC) machining (n = 29), or other programmable automation systems (n = 17). Descriptions of workers' compensation (WC) claim injuries and identified risk factors that motivated the acquisition of the equipment were extracted from grant applications. Other aspects of the employer experiences, including qualitative and quantitative assessment of effects on risk factors for musculoskeletal disorders (MSD), effects on productivity, and employee acceptance of the intervention were summarized from the case study reports. Case studies associated with a combination of large reduction in risk factors, lower cost per affected employee, and reported increases in productivity were CNC stone cutting system, CNC/vertical machining system, automated system for bottling, CNC/routing system for plastics products manufacturing, and a CNC/Cutting system for vinyl/carpet. Six case studies of industrial robots reported quantitative reductions in MSD risk factors in these diverse manufacturing industries: snack foods; photographic film, paper, plate, and chemical; machine shops; leather goods and allied products; plastic products; and iron and steel forging. Furthermore, this review of health/safety intervention case studies indicates that advanced (programmable) manufacturing automation, including industrial robots, reduced workplace musculoskeletal risk factors, and improved process productivity in most cases.

42 ENGINEERING↗

DOE OSTI2024

Integrated Process for Direct Air Capture of CO 2 and Electrochemical Conversion to Ethanol

This Cooperative Research and Development Agreement (CRADA) between UT-Battelle, LLC and Reactwell, L.L.C. aimed to facilitate the development of an energy-efficient and cost-effective technology that captures carbon dioxide (CO 2 ) from ambient air and converts it electrochemically to ethanol. Direct air capture (DAC) of CO 2 offers the prospect of permanently lowering the atmospheric CO 2 concentration, providing economic and energy-efficient technologies can be developed and deployed at a large scale. DAC has the potential for high-capacity atmospheric CO 2 capture, the flexibility of placement anywhere on earth, and the generation of high-purity CO 2 streams. The most significant technical challenge with DAC is the very low atmospheric concentration of CO 2 , thereby requiring sorbents that bind CO 2 quickly, strongly, and selectively against other components in the air. Integrating DAC with CO 2 conversion into useful chemicals, fuels, or materials can provide an economically feasible solution for mitigating climate change. As long as the carbon contained in these products is taken from the atmosphere and no additional carbon emissions result from their production, processing, and transportation, they can be considered carbon-neutral products. This CRADA facilitated the development of a new net-zero emission technology that closes the carbon cycle by combining DAC with the catalytic electrochemical conversion of CO 2 into ethanol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Thermobifida fusca Cel6B moves bidirectionally while processively degrading cellulose

Abstract Background Cellulose, an abundant biopolymer, has great potential to be utilized as a renewable fuel feedstock through its enzymatic degradation into soluble sugars followed by sugar fermentation into liquid biofuels. However, crystalline cellulose is highly resistant to hydrolysis, thus industrial-scale production of cellulosic biofuels has been cost-prohibitive to date. Mechanistic studies of enzymes that break down cellulose, called cellulases, are necessary to improve and adapt such biocatalysts for implementation in biofuel production processes. Thermobifida fusca Cel6B ( Tf Cel6B) is a promising candidate for industrial use due to its thermostability and insensitivity to pH changes. However, mechanistic studies probing Tf Cel6B hydrolytic activity have been limited to ensemble-scale measurements. Results We utilized optical tweezers to perform single-molecule, nanometer-scale measurements of enzyme displacement during cellulose hydrolysis by Tf Cel6B. Records featured forward motility on the order of 0.17 nm s −1 interrupted by backward motions and long pauses. Processive run lengths were on the order of 5 nm in both forward and backward directions. Motility records also showed rapid bidirectional displacements greater than 5 nm. Single-enzyme velocity and bulk ensemble activity were assayed on multiple crystalline cellulose allomorphs revealing that the degree of crystallinity and hydrogen bonding have disparate effects on the single-molecule level compared to the bulk scale. Additionally, we isolated and monitored the catalytic domain of Tf Cel6B and observed a reduction in velocity compared to the full-length enzyme that includes the carbohydrate-binding module. Applied force has little impact on enzyme velocity yet it readily facilitates dissociation from cellulose. Preliminary measurements at elevated temperatures indicated enzyme velocity strongly increases with temperature. Conclusions The unexpected motility patterns of Tf Cel6B are likely due to previously unknown mechanisms of processive cellulase motility implicating irregularities in cellulose substrate ultrastructure. While Tf Cel6B is processive, it has low motility at room temperature. Factors that most dramatically impact enzyme velocity are temperature and the presence of its native carbohydrate-binding module and linker. In contrast, substrate ultrastructure and applied force did not greatly impact velocity. These findings motivate further study of Tf Cel6B for its engineering and potential implementation in industrial processes.

Johnson, Madeline M. (ORCID:000000029518293X)↗

DOE OSTI2023

Surface Roughness Effects from Additive Manufacturing in High Efficiency Gas Turbine Combustion Systems

In the past, clean combustion systems were characterized by high system development costs due to growing complexity and escalating manufacturing costs from conventional manufacturing processes. As a result, high efficiency concepts are difficult to design and more difficult to be cost-effectively manufactured. In recent years, with the introduction of additive manufacturing (AM) technologies, the rapid prototyping and mass production processes of clean combustion systems are promising to be significantly simplified with significant reduction in terms of engine manufacturing cost and engine energy cost. Compared with conventional manufacturing built parts, the AM process enabled a simpler design to be adopted for the nozzle, reducing the number of required braze and weld joints from twenty-five to just five. The resulting nozzle was 25% lighter and five times more durable and contributed to a 15% reduction in fuel burn in comparison with the previous model produced. Applying these improvements to a fleet of 5,000 turbofan engines at 150 kN thrust would result in fuel cost savings of $ \$ $6B annually (at $ \$ $5/gallon Jet-A fuel price, 700 gallon/hour fuel consumption rate, and 2,300 operational hours per year), and reduce CO2 emissions by more than 25 million tons per year. These advances support core Department of Energy (DOE) missions in energy efficiency, improving productivity, and environmental sustainability. Maximizing the benefit of these new capabilities will require high prediction capability of high speed turbulent flow with wall modeled Large Eddy Simulation (LES). GE Aviation maintains that advanced simulation technology and supercomputing is required in order to provide the appropriate boundary conditions to realize the maximum potential of AM and Ceramic Matrix Composite to reduce cooling flow, a first order penalty on the Brayton cycle. The algorithm developed using the ANSYS/Fluent software would provide the foundation for entirely new avenues of research and development with potential multi-billion dollar impact to the US economy, and significant reduction in carbon based emissions across the aerospace and power generation industries. The formulation of this iWLES (integral wall model for LES) is generic and allows to capture the changes in flow dynamics that have a significant impact on the wall bounded flow characteristics, such as swirler effective area, bulk swirl number, local pressure distribution, exit velocity profile, and turbulence kinetic energy profile. A periodic channel flow with rough flat plate is simulated using LES (Wall-Adapting Local Eddy-viscosity) model to verify the implementation of iWLES in the Fluent User Defined Function (UDF). As the flow fields are highly sensitive due to surface roughness of the wall bounded flows in the combustion systems, there is significant potential to conduct further LES studies focusing on the turbulence boundary layer interaction. Accurately capturing near wall physics will elucidate the impact of rough surfaces on combustor flow and aero-thermal interactions.

42 ENGINEERING↗

DOE OSTI2023

Surface Roughness Effects from Additive Manufacturing in High Efficiency Gas Turbine Combustion Systems

In the past, clean combustion systems were characterized by high system development costs due to growing complexity and escalating manufacturing costs from conventional manufacturing processes. As a result, high efficiency concepts are difficult to design and more difficult to be cost-effectively manufactured. In recent years, with the introduction of additive manufacturing (AM) technologies, the rapid prototyping and mass production processes of clean combustion systems are promising to be significantly simplified with significant reduction in terms of engine manufacturing cost and engine energy cost. Compared with conventional manufacturing built parts, the AM process enabled a simpler design to be adopted for the nozzle, reducing the number of required braze and weld joints from twenty-five to just five. The resulting nozzle was 25% lighter and five times more durable and contributed to a 15% reduction in fuel burn in comparison with the previous model produced. Applying these improvements to a fleet of 5,000 turbofan engines at 150 kN thrust would result in fuel cost savings of $6B annually (at $5/gallon Jet-A fuel price, 700 gallon/hour fuel consumption rate, and 2,300 operational hours per year),and reduce CO2 emissions by more than 25 million tons per year. These advances support core Department of Energy (DOE)missions in energy efficiency, improving productivity, and environmental sustainability. Maximizing the benefit of these new capabilities will require high prediction capability of high speed turbulent flow with wall modeled Large Eddy Simulation (LES). GE Aviation maintains that advanced simulation technology and supercomputing is required in order to provide the appropriate boundary conditions to realize the maximum potential of AM and Ceramic Matrix Composite to reduce cooling flow, a first order penalty on the Brayton cycle. The algorithm developed using the ANSYS/Fluent software would provide the foundation for entirely new avenues of research and development with potential multi-billion dollar impact to the US economy, and significant reduction in carbon based emissions across the aerospace and power generation industries. The formulation of this iWLES (integral wall model for LES) is generic and allows to capture the changes in flow dynamics that have a significant impact on the wall bounded flow characteristics, such as swirler effective area, bulk swirl number, local pressure distribution, exit velocity profile, and turbulence kinetic energy profile. A periodic channel flow with rough flat plate is simulated using LES (Wall-Adapting Local Eddy-viscosity) model to verify the implementation of iWLES in the Fluent User Defined Function (UDF). As the flow fields are highly sensitive due to surface roughness of the wall bounded flows in the combustion systems, there is significant potential to conduct further LES studies focusing on the turbulence boundary layer interaction. Accurately capturing near wall physics will elucidate the impact of rough surfaces on combustor flow and aero-thermal interactions.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2022

Testing of the Defense Waste Processing Facility Cold Chemical Dissolution Method in Sludge Batch 10 Qualification

For each sludge batch that is processed in the Defense Waste Processing Facility (DWPF), the Savannah River National Laboratory (SRNL) tests the applicability of the digestion methods used by the DWPF Laboratory for elemental analysis of Sludge Receipt and Adjustment Tank (SRAT) Receipt samples and SRAT Product process control samples. DWPF SRAT samples are typically dissolved using a method referred to as the DWPF Cold Chemical or Cold Chem Method (CC), (see DWPF Procedure SW4-15.201- 2.1).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Smart Preprocessing & Robust Integration Emulator

To achieve the desired particle size of biomass feedstocks during preprocessing for trouble-free handling and conversion to produce biofuels and bioproducts, the raw materials must undergo a crucial milling process. The particle size of biomass plays a critical role in subsequent biofuel manufacturing, where a larger area-to-volume ratio facilitates efficient synthesis while balancing the impact of moisture on biomass storage. To optimize biofuel production efficiency and overcome these challenges, it is imperative to accurately predict the particle size distribution (PSD) of the biomass in the design of efficient preprocessing systems. The population balance model (PBM), upon empirical calibration and validation, can provide rapid prediction of post-milling PSD of granular biomass. However, PSD has limitations related to mass conservation and the absence of moisture considerations. To overcome these drawbacks, a deep learning model called the enhanced deep neural operator (DNO+) is implemented in the code. This model not only retains the capabilities of the PBM in handling complex mapping functions but also incorporates additional factors influencing the system. By considering various experimental conditions such as sieve size and moisture content, the trained DNO+ model can effectively predict the PSD after milling for any given feed PSD. To further reduce the reliance on experimental data, the PBM is integrated into the DNO+ model, resulting in a physics-informed DNO+ (PIDNO+). The PIDNO+ model addresses the non-conservation of quality exhibited by the PBM while inheriting the advantages of the DNO+ model in considering multiple influencing factors. Moreover, the PIDNO+ model significantly reduces the amount of data required for model training. Both deep learning models, i.e., DNO+ and PIDNO+, are excellent in predictive performance, offering swift and accurate machine learning-based predictions. The use of this code that contains these models will assist in guiding the proper milling equipment selection and operational conditions to achieve the desired biomass particle sizes, ensuring the efficiency of subsequent biofuel and bioproduct production processes.

Xia, Yidong [Idaho National Laboratory (INL), Idah↗

DOE OSTI2020

Deep Exclusive p 0 Electroproduction Measured in Hall A at Jefferson Lab with the Upgraded CEBAF

Our understanding of the proton's structure in terms of its fundamental degrees of freedom, quarks and gluons, is incomplete. Generalized Parton Distributions (GPDs) can enhance our understanding of the partonic structure of the proton as it includes the correlation between the momentum and transverse position of partons. Exclusive electroproduction of the pion (ep→e'p'π 0 ) is one of the potential channels to access the GPDs. GPDs are defined at the Bjorken limit where the total amplitude can be factorized in a hard scattering of the photon off the quark and a soft part described by the GPDs. At sufficiently high Q 2 , a factorization scheme for exclusive meson production processes exists but only for longitudinally polarized virtual photons. As long as the longitudinally polarized virtual photons dominate the cross-section, we can have factorization and extract the GPDs. But the existing data for π 0 production at low Q 2 and low x B show the dominance of transverse part of the cross-section over the longitudinal one. Some transversity GPD models have found that an effective way to factorize the contribution from transversely polarized virtual photons to explain the dominance of σ T over σ L , shown by existing data. The experiment E12-06-114 ran in experimental Hall A during 2014-2016. The primary goal of this experiment was to measure the DVCS cross-section but the experimental configuration also allows the measurement of deep exclusive π 0 production. Taking advantage of the upgraded CEBAF at Jefferson Lab, we explored the high Bjorken-x (0.60) and high Q 2 regime for the first time. The extracted cross-section terms for π 0 production helps us to test the validity of QCD factorization in our kinematic regime. Our π 0 production results can be used to test and improve the existing models of proton structure. Cross-section results will be presented at two different Q 2 values for fixed x B of 0.60.

Karki, Bishnu↗

DOE OSTI2025

Testing the lepton content of the proton at HERA and EIC

Although protons are baryons with an overall vanishing lepton number, they possess a non-trivial leptonic content arising from quantum fluctuations which can be described by lepton parton distribution functions (PDFs) of the proton. These PDFs have been recently computed and can be used to define lepton-induced processes at high-energy colliders. In this article, we propose a novel way to test the computation of lepton PDFs of the proton by analyzing both non-resonant di-lepton and resonant Z gauge boson production processes induced by leptons within the proton at proton-electron colliders like HERA and EIC. Despite the fact that lepton PDFs of the proton are known to be small, this work demonstrates that both processes imply a measurable yield of events at HERA and EIC, which could be used to test these PDFs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗