CREEPY: Computationally-Redundant, Energy-Efficient Processing for Y'all.
Abstract not provided.
Deng, Bobin↗
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Results for “Process Efficiency”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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AI-Enabled Discovery and Physics-Based Optimization of Energy Efficient Processing Strategies for Advanced Turbine Alloys (Final Technical Report)
In this project, the multi-organizational team of academic and industrial researchers from the University of Kentucky an aerospace and energy generation OEM partner has leveraged novel Digital Process Twin (DPT) models of process/structure interactions (i.e., process-induced surface integrity) to advance a paradigm of fully integrated computational materials engineering (ICME). Using efficient process models as the core of a digital process simulator for a reinforcement learning algorithm, the team has integrated industrial data and metrics of structure/performance/energy relationships and manufacturing-related energy metrics to optimize dynamic processing parameters for significantly improved life-cycle energy efficiency of advanced γ-TiAl low-pressure turbine (LPT) alloys, as indicated by a set of design relevant parameters (e.g., residual stresses and scrap rate). The key objective and anticipated outcome of the project was at least a 10% reduction in life-cycle embodied energy for a recently developed, γ-TiAl low-pressure turbine (LPT) alloy and nickel-based superalloy Inconel 718, through the adoption of the proposed AI-enabled process optimization approach. The final project outcomes significantly exceeded this original target, realizing manufacturing-related energy efficiency improvements of more than 130% for TiAl and up to 80% for Inconel 718. Rather than following the prevailing and highly inefficient empirical paradigm, the proposed study demonstrated the feasibility of adopting a digital, physics-based process design and optimization paradigm. The recurring need for manual intervention, rework, reinspection causes significant production bottlenecks and unnecessary expense associated with delivering the requisite component quality. The OEM partner, and turbine industry in general, expect to reap significant cost and resource savings if an AI-optimized set of parameters can be applied to specific machining operations. The technical scope of the proposed project involved the paving of a realistic path towards model-based and AI-enabled Integrated Computational Materials Engineering (ICME), and away from inefficient empirical process optimization and legacy manufacturing practices, which are no longer able to efficiently process novel high-performance turbine alloy materials. The project team will address the fundamental knowledge gap that currently exists within the ICME paradigm with respect to the process/structure/performance/energy impacts of finishing processes. While significant resources have been devoted to the ‘early stages’ of manufacturing, such as alloy design, primary and secondary processing, finishing processes have not been adequately integrated within ICME. To provide an actionable path towards model-based finishing process design (e.g., machining, burnishing, grinding, polishing), we will employ a novel AI-enabled process optimization paradigm, based on a computationally efficient, physics-based process simulator. Through limited experimental work to calibrate and validate our process simulator model via an advanced in-situ characterization technique and process optimization via reinforcement learning, the project will seek to demonstrate a viable alternative to the inefficient ‘legacy’ processing strategies, empirical testing and broad scope machining learning approaches, all of which fail to adequately consider complex process physics. The project team has identified an intermetallic γ-TiAl LPT alloy, which is currently being used as part of the OEM partner’s advanced gas turbine designs. This particular alloy poses significant manufacturing challenges during finishing operations, which limit the degree to which the current turbine design can be manufactured in an energy- and cost-efficient manner. Empirical testing and numerical modeling efforts to optimize processing parameters for γ-TiAl have not been able to resolve these manufacturing challenges, so the proposed physics-based AI-enabled optimization technology would offer a truly novel and transformative capability. The multi-organizational team of academic and industry experts from the UKY and the OEM partner will work together closely to demonstrate the analytical and experimental critical function and characteristic proof of concept of this novel approach.
20 FOSSIL-FUELED POWER PLANTS↗
Melter Downtime Impacts on DFLAW Glass Production and Process Efficiency - 17117
The Hanford Tank Waste Treatment and Immobilization Plant (WTP) pilot studies found that semi-volatile elements started to leave the molten glass pool and enter the offgas stream when the melter became idle. The rate at which the semi-volatile elements leave the molten glass pool follows a typical half-life decay curve. The WTP Direct Feed Low-Activity Waste (DFLAW) program is using existing LAW offgas treatment systems to capture semi-volatile elements leaving the melters. A new building, Effluent Management Facility (EMF), will be built to process effluents generated by the offgas treatment equipment. The effluents are concentrated by evaporation and are recycled to the melter feed streams. Computer modeling studies show that increased amounts of semi-volatile elements in the recycles due to melter downtime adversely impact the DFLAW operations. The extent to which glass productions and process efficiencies are hampered depends upon the frequency, duration, and pattern of the downtime events. Various scenarios were investigated using randomly generated and operator-anticipated downtime schedules. This paper discusses 1) derivation of the volatility half-life curves, 2) downtime schedules, 3) increased amount of semi-volatile elements in recycled material as a result of melter shut down, 4) impacts to glass production and process efficiency, and 5) comparison of scenario results. This study concludes that plant operators can mitigate much of the negative effects of semi-volatile element recycles by managing melter downtime and idle time when possible. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DU Processing Efficiency and Reclamation: Plasma Arc Melting
The work described here corresponds to one piece of a larger effort to increase material usage efficiency during DU processing operations. In order to achieve this goal, multiple technologies and approaches are being tested. These technologies occupy a spectrum of technology readiness levels (TRLs). Plasma arc melting (PAM) is one of the technologies being investigated. PAM utilizes a high temperature plasma to melt materials. Depending on process conditions, there are potential opportunities for recycling and material reclamation. When last routinely operational, the LANL research PAM showed extremely promising results for recycling and reclamation of DU and DU alloys. The current TRL is lower due to machine idleness for nearly two decades, which has proved difficult to restart. This report describes the existing results, promising techniques, and the process of bringing this technology back to readiness at LANL.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Processing Strategies for an Organic Photovoltaic Module with over 10% Efficiency
Abstract not provided
Liao, Chuang-Yi↗
SU-E-P-27: Efficient Process for AccuBoost Planning and Treatment Delivery to Minimize Patient Compression Time
Purpose: To implement an efficient and robust process for AccuBoost planning and treatment delivery that can be safely performed by a single Physicist while minimizing patient’s total session time. Methods: Following a thorough commissioning and validation process, templates were created in the brachytherapy planning system for each AccuBoost applicator. Tables of individual and total nominal dwell times for each applicator as a function of separation were generated to streamline planning while an Excel-based nomogram provided by the vendor functions as a secondary verification of the treatment parameters. Tables of surface dose as a function of separation and applicator, along with concise guidance documents for applicator selection, are readily available during the planning process. The entire process is described in a set of detailed Standard Operating Procedures which, in addition to the items described above, include a verbal time-out between the primary planner and the individual performing the secondary verification as well as direct visual confirmation of applicator placement using an articulated mirror. Prior to treatment initiation, a final time-out is conducted with the Radiation Oncologist. Chart documentation is finalized after the patient is released from compression following completion of the treatment. Results: With the aforementioned procedures, it has been possible to consistently limit the time required to prepare each treatment such that the patient is typically under compression for less than 10 minutes per orientation prior to the initiation of the treatment, which is particularly important for APBI cases. This process can be overseen by a single physicist assisted by a dosimetrist and has been optimized during the past 16 months, with 180 treatment sessions safely completed to date. Conclusion: This work demonstrates the implementation of an efficient and robust process for real-time-planned AccuBoost treatments that effectively minimizes the time that the patient is under compression.
60 APPLIED LIFE SCIENCES↗
New Materials and an Efficient Processing Approach for Materials for Harsh Environments – Continuous Electric Field Assisted Sintering
Electric-field assisted sintering (EFAS) is an advanced manufacturing method for the consolidation and processing of ceramic and metal materials. It is a particularly excellent candidate for efficient materials processing as it has greater than 90% energy cost savings and improved CO2 emissions compared to traditional sintering in a furnace. This is due to direct rapid heating of the materials and molds leveraging an electrification phenomenon called Joule heating where electrical current is passed through the sample/mold assemblies causing direct heating. The technique does have limitations though as it is traditionally a batch-process and suffers from scale up difficulties. To overcome this, researchers at Idaho National Laboratory changed the form factor of traditional EFAS instruments to develop and construct a continuous rolling electric-field assisted sintering (CEFAS) device. Its unique design creates highly localized electrical, thermal, and mechanical process parameters for continuous samples of limitless length. Advanced core shell powder materials were also created using fluidized powder bed atomic layer deposition of core/shell solid oxide electrochemical electrode/electrolyte BaCe0.7Zr0.1Y0.1Yb0.1O3 (BCZYYb) and yttrium doped BaZrO3 (BZY) to be a feedstock for the new CEFAS instrument. The innovative core/shell powder is hypothesized to have high protonic conductivity with enhanced environmental resistance. The completed project covers innovations in process control and design enabled by control theory, finite element modeling and mechanical design, three dimensionally printed carbon-carbon composite manufacturing and utilization, and green materials processing techniques.
36 MATERIALS SCIENCE↗
SU-C-304-02: Robust and Efficient Process for Acceptance Testing of Varian TrueBeam Linacs Using An Electronic Portal Imaging Device (EPID)
Purpose: The purpose of this project was to develop a process that utilizes the onboard kV and MV electronic portal imaging devices (EPIDs) to perform rapid acceptance testing (AT) of linacs in order to improve efficiency and standardize AT equipment and processes. Methods: In this study a Varian TrueBeam linac equipped with an amorphous silicon based EPID (aSi1000) was used. The conventional set of AT tests and tolerances was used as a baseline guide, and a novel methodology was developed to perform as many tests as possible using EPID exclusively. The developer mode on Varian TrueBeam linac was used to automate the process. In the current AT process there are about 45 tests that call for customer demos. Many of the geometric tests such as jaw alignment and MLC positioning are performed with highly manual methods, such as using graph paper. The goal of the new methodology was to achieve quantitative testing while reducing variability in data acquisition, analysis and interpretation of the results. The developed process was validated on two machines at two different institutions. Results: At least 25 of the 45 (56%) tests which required customer demo can be streamlined and performed using EPIDs. More than half of the AT tests can be fully automated using the developer mode, while others still require some user interaction. Overall, the preliminary data shows that EPID-based linac AT can be performed in less than a day, compared to 2–3 days using conventional methods. Conclusions: Our preliminary results show that performance of onboard imagers is quite suitable for both geometric and dosimetric testing of TrueBeam systems. A standardized AT process can tremendously improve efficiency, and minimize the variability related to third party quality assurance (QA) equipment and the available onsite expertise. Research funding provided by Varian Medical Systems. Dr. Sasa Mutic receives compensation for providing patient safety training services from Varian Medical Systems, the sponsor of this study.
07 ISOTOPE AND RADIATION SOURCES↗
Simultaneously Improving Process Efficiency and Mechanical Properties in Aluminum Alloys with Applied Magnetic Fields
In the aluminum heat treatment sector, large resistive batch furnaces are used for many heat treatment processes and are generally always running, operating at approximately 20–30% efficiency. The primary avenue for energy savings lies in shortening heat treatment times, which can be 24+ hours for solutionizing (450–625 °C) and aging treatments (150–250 ℃), depending on the alloy and specification requirements. The application of high magnetic fields (<9 T) has shown to significantly reduce aluminum alloy heat treatment times, while achieving enhanced mechanical properties. Here, we explore the effects of thermomagnetic processing on the heat treatment response of a commercial aluminum alloy A390.1. Heat treatment times were reduced by >80%, while achieving ~10% improvement in microhardness, and these improvements persisted after longer thermal exposures simulating use. The microstructural evolution and resulting properties will be discussed.
Kesler, Michael [ORNL] (ORCID:0000000161423128)↗
Development of Efficient Process for Manufacturing of Thermoplastic Composites with Tailored Properties (CRADA 511)
This is a collaborative effort between Battelle Memorial Institute as manager and operator of Pacific Northwest National Laboratory (PNNL) and ESI North America Inc. (“ESI” or “Participant”) to apply computation and data analytics to the challenge of light weighting with a focus on the battery enclosures of electric vehicles (EVs). EVs use heavy batteries to increase range and power. A complex-shaped battery enclosure is required to meet a host of challenging performance requirements. The ability to virtually develop composite parts such as battery enclosure with tailored properties to meet required performance will be highly valuable to the automotive industry. However, efficient simulation of composite-manufacturing processes remains a challenging issue since simulation involves multiscale models in space and time, highly non-linear and anisotropic behavior, strongly coupled multi-physics, and complex geometries. This work will advance the state of the art by reducing the computational burden of composite optimization by using simulation data from a limited number of configurations off-line and then developing a reduced order model (ROM) using data analytics and machine learning (ML). Develop a data driven approach to link features of the material and manufacturing processes to the mechanical properties of thermoplastic composite parts.
42 ENGINEERING↗
Efficient process for producing saccharides and ethanol from a biomass feedstock
Described herein is a process for producing saccharides and ethanol from biomass feedstock that includes (a) producing an enzyme composition by culturing a fungal strain(s) in the presence of a lignocellulosic medium, (b) using the enzyme composition to saccharify the biomass feedstock, and (c) fermenting the saccharified biomass feedstock to produce ethanol. The process is scalable and, in certain aspects, is capable of being deployed on farms, thereby allowing local production of saccharides and ethanol and resulting in a reduction of energy and other costs for farm operators. Optional steps to improve the biomass-to-fuel conversion efficiency are also contemplated, as are uses for byproducts of the process described herein.
09 BIOMASS FUELS↗
Efficient process for producing saccharides and ethanol from a biomass feedstock
Described herein is a process for producing saccharides and ethanol from biomass feedstock that includes (a) producing an enzyme composition by culturing a fungal strain(s) in the presence of a lignocellulosic medium, (b) using the enzyme composition to saccharify the biomass feedstock, and (c) fermenting the saccharified biomass feedstock to produce ethanol. The process is scalable and, in certain aspects, is capable of being deployed on farms, thereby allowing local production of saccharides and ethanol and resulting in a reduction of energy and other costs for farm operators. Optional steps to improve the biomass-to-fuel conversion efficiency are also contemplated, as are uses for byproducts of the process described herein.
Okeke, Benedict C.↗
High-Efficiency Process for CO 2 Conversion to Hydrocarbon Fuels
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10 SYNTHETIC FUELS↗
Unsupervised Segmentation and Clustering Workflow for Efficient Processing of 4D-STEM and 5D-STEM Data
Four-dimensional scanning transmission electron microscopy (4D-STEM) enables mapping of diffraction information with nanometer-scale spatial resolution, offering detailed insight into local structure, orientation, and strain. However, as data dimensionality and sampling density increase, particularly for in situ scanning diffraction experiments (5D-STEM), robust segmentation of structurally consistent behavior across sequential measurements becomes essential for efficient and physically meaningful analysis. Here, we introduce a clustering framework that identifies crystallographically distinct domains from 4D-STEM datasets. By using local diffraction-pattern similarity as a metric, the method extracts closed contours delineating spatially contiguous regions. This approach produces cluster-averaged diffraction patterns that improve signal quality while reducing data volume by orders of magnitude, enabling rapid and accurate orientation, phase, and strain mapping. We demonstrate the applicability of this approach to in situ liquid-cell 4D-STEM data of gold nanoparticle growth. Our method provides a scalable and generalizable route for spatially coherent segmentation, data compression, and quantitative structure–strain mapping across diverse 4D-STEM modalities. The full analysis code and example workflows are publicly available to support reproducibility and reuse.
4D-STEM↗
Chloride Molten Salt Electrolysis Enables Integrated and Energy-Efficient Process for NdFeB Magnet Fabrication
Rare-earth elements (REEs) have been identified by NATO, the USDOE, and USGS as critical materials, i.e., materials which have significant demand yet pose supply-chain risks. Many of the existing processes for separations, metallization, and final parts production used across the REE supply chain involve energy intensive steps. For example, neodymium (Nd or NdPr) is produced using oxyfluoride electrolysis of Nd 2 O 3 , which requires hydrofluoric acid to produce a key electrolyte component (NdF 3 ) and generates undesired perfluorocarbon (PFC) gases. Such challenges make securing a resilient supply chain for NdFeB permanent magnets in countries like the United States prohibitively difficult. Here, we propose a chloride-based MSE process that circumvents these challenges, delivering high-purity NdPr from a (NdPr)Cl 3 feed from upstream REE separations. This eliminates environmentally-damaging steps of oxalate or carbonate precipitation and calcination, and enables superior production rates due to greater solubility of (NdPr)Cl 3 in chloride melts compared to Nd 2 O 3 . We show that CMSE generates high-purity NdPr (99.4 wt.%) while being energy-efficient (~ 6 kWh/kg-Nd). NdPr from CMSE was used to fabricate a NdFeB magnet with an excellent maximum energy product (> 40 MGOe), comparable to commercially available NdFeB magnets. This establishes CMSE as a leading approach for integrated, energy-efficient NdFeB magnet production.
Materials science↗
Sensor network design for maximizing process efficiency: An algorithm and its application
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acid gas removal unit↗
Catalytic hydroprocessing of fast pyrolysis oils: Impact of biomass feedstock on process efficiency
Here, we report here on an experimental study to produce refinery-ready fuel blendstocks via catalytic hydrodeoxygenation (upgrading) of pyrolysis oil using several biomass feedstocks and various blends. Blends were tested along with the pure materials to determine the effect of blending on product yields and qualities. Within experimental error, oil yields from fast pyrolysis and upgrading are shown to be linear functions of the blend components. Switchgrass exhibited lower fast pyrolysis and upgrading yields than the woody samples, which included clean pine, oriented strand board (OSB), and a mix of pinon and juniper (PJ). The notable exception was PJ, for which the poor upgrading yield of 18% was likely associated with the very high viscosity of the PJ fast pyrolysis oil (947 cp). The highest fast pyrolysis yield (54% dry basis) was obtained from clean pine, while the highest upgrading yield (50%) was obtained from a blend of 80% clean pine and 20% OSB (CP 8 OSB 2 ). For switchgrass, reducing the fast pyrolysis temperature to 450 degrees C resulted in a significant increase to the pyrolysis oil yield and reduced hydrogen consumption during hydrotreating, but did not directly affect the hydrotreating oil yield. The water content of fast pyrolysis oils was also observed to increase linearly with the summed content of potassium and sodium, ranging from 21% for clean pine to 37% for switchgrass. Multiple linear regression models demonstrate that fast pyrolysis is strongly dependent upon the contents lignin and volatile matter as well as the sum of potassium and sodium.
09 BIOMASS FUELS↗
Removal of Enzymatic and Fermentation Inhibitory Compounds from Biomass Slurries for Enhanced Biorefinery Process Efficiencies
Abstract not provided
Gurram, R. N.↗