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DOE OSTI2022

Comparing Calibration Algorithms for the Rapid Characterization of Pretreated Corn Stover Using Near-Infrared Spectroscopy

Rapid characterization of biomass composition is a key enabling technology for biorefineries—the ability to measure the chemical composition of biomass materials entering the biorefinery as well as the composition of key process intermediate streams would allow real-time process control and the development of robust models to predict process performance. The utility of near-infrared (NIR) spectroscopy for rapid characterization requires multivariate algorithms for building calibration models. The most prevalent algorithm used for building calibration models using NIR spectra is the linear modeling algorithm Partial Least Squares Regression (PLS). Nonlinear regression algorithms (which are typically more computationally intensive than linear modeling approaches) have gained popularity in recent years due to their ability to solve a wide variety of classification and regression problems and the dramatic increase in available computational resources. In this work, we demonstrate that a calibration model can predict the composition of corn stover process intermediate samples pretreated with three different treatments—hot water (HW), dilute acid (DA), and deacetylation followed by dilute acid (DDA). We quantitatively compare three different algorithms for building prediction models based on near-infrared spectroscopy—partial least squares (PLS), support vector machines (SVM), and random forests (RF). We demonstrate the utility of improving model performance by accounting for instrument performance variability using repeated measurements of standard materials (e.g., the “repeatability file” strategy) and investigate its performance with nonlinear regression techniques, and we discuss methods for quantifying the uncertainties of specific predictions among the three methods.

09 BIOMASS FUELS↗

DOE OSTI2017

Convergence and Commercial Momentum - Industrial Internet of Things Evolution

Industrial instrumentation and sensors are purpose-built for applications. Rugged and proven for field applications in harsh environments, such as on an oil platform or in a copper mine 5,000-feet below ground, these instruments require reliability and performance. Before the turn of the millennium, industrial technology-and information technology (IT) in particular-drove these systems, and they often exceeded the abilities of consumer products. However, as we stand today, commercial Internet of Things (IoT) technology has advanced rapidly, with industrial control systems lagging in intelligence and features. Experienced owner-operators of industrial facilities recognize the buzz surrounding the Industrial Internet of Things (IIoT) but often shun the notion of consumer-grade devices being installed and integrated into an operational control system. During the International Society of Automation (ISA) Process Control and Safety Forum (PCS) in Houston, Texas, in November 2016, ISA’s Communication Division convened a panel to focus on IIoT. Experienced industrial and control engineers on the panel expressed concerns and reservations with IIoT. Whereas some acknowledged an interest in the topic, others did not recognize it as an inevitable part of the industrial controls landscape. Granted, IIoT is still mostly a vision in the instrumentation and automation landscape; however, its place on stage is coming into view. During the opening session of PCS 2016, ISA President Jim Keaveney rhetorically asked the audience if IoT had peaked and also wondered if “cyber” would be the next area for innovation. This paper will explore the nexus of “domestic” IoT and how product evolution will drive its development toward that of IIoT.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Build plate conduction cooling for thermal management of wire arc additive manufactured components

Wire arc additive manufacturing (WAAM) allows for quick, large component manufacturing with fast deposition rates while leveraging readily available wire feedstock that is significantly cheaper than metal powder. However, the increased deposition rate of this process requires enhanced thermal management as failures can occur due to overheating. A common strategy to mitigate overheating is to dwell, or pause, between individual layers; however, this can significantly increase build times and eliminate the advantage of additive manufacturing being able to manufacture components quickly. To help mitigate this issue, this study explores the use of active cooling to maintain process control and to decrease overall build time. In this work, conductive cooling applied to either the bottom or side of the print substrate was explored. Results from this study showed that bottom build plate active cooling can be used to decrease dwell times by up to 50% and decrease cool-down to room temperature after the building process by up to 75%. Results from this study demonstrate that the use of active cooling strategies for WAAM can be used for better thermal control over the process and should be further investigated.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Evaluation of Material Balance Approaches for Hanford Direct-Feed Low Activity Waste Processing - 20022

The Hanford Site has accumulated millions of gallons of tank waste from reprocessing spent fuel to recover plutonium, uranium, cesium, and strontium. The supernatant from the accumulated tank waste will be treated using a Direct Feed Low-Activity Waste approach. The supernatant will be treated to remove solids and cesium in the Tank-Side Cesium Removal process in the Hanford tank farm, then vitrified in a semi-batch process in the Hanford Waste Treatment and Immobilization Plant (WTP). Currently, each batch of feed is sampled at three locations prior to being fed to the melter: the feed qualification tank in the Hanford tank farm as well as the concentrate receipt vessel (CRV) and melter feed preparation vessel (MFPV) in the WTP. The feed qualification sample is taken from a large batch of accumulated feed, only two to three samples are expected each year. Approximately 275 samples from the CRVs and 1100 samples from the MFPV are expected each year. An evaluation was performed to determine if a material balance based on the feed qualification sample could replace most of the sampling in the CRVs and MFPVs. The evaluation consisted of three elements: (1) determination of the practicality of using a material balance to estimate the stream composition of the CRV and MFPV contents, (2) evaluation of whether the material balance could be automated using the existing process control system, and (3) determination of the uncertainty in glass composition using the material balance approach. It is assumed that periodic sampling at the CRV and MFPV would be performed periodically to re-baseline the material balance, evaluations are in progress to determine the frequency of this periodic sampling. Process sample locations downstream of the melter were reviewed as well, but the partitioning of semi-volatile species in the melter was determined to preclude extending the material balance approach past the melter. It was determined that replacement of the CRV sample location was feasible and did not increase process uncertainty or significantly impact waste loading. Replacement of the MFPV sample was also determined to be feasible, but that measurement of the glass former chemical addition may be needed prior to addition of these chemicals to the MFPV. This measurement could be performed by an in situ laser-induced breakdown spectroscopy (LIBS) system. Limited tests were performed to evaluate LIBS for direct measurements of the low-activity waste melter feed. The use of a material balance would eliminate over 1200 samples each year if only 10% of the CRV and MFPV batches are sampled and could likely allow the WTP laboratory to operate on days only versus 24/7 operation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Fermilab's Horizontal Test Stand Upgrade Overview and Commissioning

Cryo-assemblies with the Nb 3 Sn MQXFA low-beta quadrupoles for the High Luminosity LHC (HL-LHC) upgrade will be tested at Fermilab's magnet test facility. A total of 10 cryo-assemblies will be delivered to CERN within the US HL-LHC Accelerator Upgrade Project (AUP). The horizontal test stand at Fermilab already has been used for testing the existing LHC inner-triplet quadrupoles, but the stand and corresponding electrical and cryogenic sub-systems were not operational for more than a decade. In order to restore the test stand functions and meet the design and test requirements for the HL-LHC magnets, the existing horizontal test facility at Fermilab underwent a significant refurbishment of the cryogenic and mechanical components. Most of the upgrades were completed and verified during so called zero-magnet test by late 2020, and then final commissioning of the upgraded horizontal test stand was completed during the first cryo-assembly test in 2023. These tests verified the major cryo-mechanical installations, as well as the basic test stand operations, including controlled cooldown and operation at 1.9 K, magnet protection and process controls. Here, in this paper, overview of the Fermilab's horizontal test facility upgrade and commissioning of these upgrades are presented.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Atmosphere Effects in Laser Powder Bed Fusion: A Review

The use of components fabricated by laser powder bed fusion (LPBF) requires the development of processing parameters that can produce high-quality material. Manipulating the most commonly identified critical build parameters (e.g., laser power, laser scan speed, and layer thickness) on LPBF equipment can generate acceptable parts for established materials and moderately intricate part geometries. The need to fabricate increasingly complex parts from unique materials drives the limited research into LPBF process control using underutilized parameters, such as atmosphere composition and pressure. As presented in this review, manipulating atmosphere composition and pressure in laser beam welding has been shown to expand processing windows and produce higher-quality welds. The similarities between laser beam welding and laser-based AM processes suggest that this atmosphere control research could be effectively adapted for LPBF, an area that has not been widely explored. Tailoring this research for LPBF has significant potential to reveal novel processing regimes. This review presents the current state of the art in atmosphere research for laser beam welding and LPBF, with a focus on studies exploring cover gas composition and pressure, and concludes with an outlook on future LPBF atmosphere control systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

In-Situ Synchrotron X-ray Computed Microtomography and Diffraction Investigation of Deformation and Fracture Behavior in a Laser Powder Bed Fusion Processed 316L Stainless Steel

Introduce defects into laser powder bed fusion stainless steel samples by controlling processing parameters. Perform in-situ x-ray microtomography on L-PBF stainless steel samples during plastic deformation. Relate defect characteristics and evolution to tensile behavior. Understand how processing conditions translate to initial defect characteristics. Track and evaluate defect evolution as a function of plastic deformation. Determine how deformation and fracture mechanics change as a result of AM defects.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Robust multivariable predictive control for laser-aided powder deposition processes

Not Available

Cao, Xiaoqing↗

DOE OSTI2017

Additive Manufacturing of Fuel Injectors

Additive manufacturing (AM), also known as 3D-printing, has been shifting from a novelty prototyping paradigm to a legitimate manufacturing tool capable of creating components for highly complex engineered products. An emerging AM technology for producing metal parts is the laser powder bed fusion (L-PBF) process; however, industry manufacturing specifications and component design practices for L-PBF have not yet been established. Solar Turbines Incorporated (Solar), an industrial gas turbine manufacturer, has been evaluating AM technology for development and production applications with the desire to enable accelerated product development cycle times, overall turbine efficiency improvements, and supply chain flexibility relative to conventional manufacturing processes (casting, brazing, welding). Accordingly, Solar teamed with EWI on a joint two-and-a-half-year project with the goal of developing a production L-PBF AM process capable of consistently producing high-nickel alloy material suitable for high temperature gas turbine engine fuel injector components. The project plan tasks were designed to understand the interaction of the process variables and their combined impact on the resultant AM material quality. The composition of the high-nickel alloy powders selected for this program met the conventional cast Hastelloy X compositional limits and were commercially available in different particle size distributions (PSD) from two suppliers. Solar produced all the test articles and both EWI and Solar shared responsibility for analyzing them. The effects of powder metal input stock, laser parameters, heat treatments, and post-finishing methods were evaluated. This process knowledge was then used to generate tensile, fatigue, and creep material properties data curves suitable for component design activities. The key process controls for ensuring consistent material properties were documented in AM powder and process specifications. The basic components of the project were: • Powder metal input stock: Powder characterization, dimensional accuracy, metallurgical characterization, and mechanical properties evaluation. • Process parameters: Laser parameter effects, post-printing heat-treatment development, mechanical properties evaluation, and post-finishing technique. • Material design curves: Room and elevated temperature tensiles, low cycle fatigue, and creep rupture properties curves generated. • AM specifications: Key metal powder characteristics, laser parameters, and heat-treatment controls identified.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Correlation Between Structure and Properties of Low-Carbon Cu-Ni-Mo-Ti-Nb Ultrahigh-Strength Steel

Low-carbon Cu-Ni-Mo-Ti-Nb steel having more than 1700 MPa tensile strength and good low-temperature impact toughness was successfully designed and processed for automobile, defence and structural applications. The steel was thermomechanical controlled processed at a different finish rolling temperatures (750-850 °C) and cooled at two different conditions: air cooling and water quenching. Evolutions of microstructure and precipitates were thoroughly characterised to understand the effect of different factors, such as steel composition, finish rolling temperature and cooling rate on the mechanical properties. The results indicate that the steel processed at 750 °C finish rolling temperature (FRT) followed by water quenching has exhibited superior tensile properties with a yield strength of 1034-1449 MPa, the tensile strength of 1598-1726 MPa and total elongation of 10-13%. Such an ultrahigh-strength level is primarily attributed to the combined effect of lower bainite dominated microstructure along with precipitation hardening. The satisfactory low-temperature toughness is promoted by low finish rolling temperature and higher amount of misorientation offered by the boundaries within the lower bainite.

36 MATERIALS SCIENCE↗

DOE OSTI2013

A Cryogenic Test Stand for Large Superconducting Solenoid Magnets

A new test stand for testing large superconducting solenoid magnets at the Fermilab Central Helium Liquifier (CHL) has been designed, and operated. This test stand has been used to test a coupling coil for the Muon Ionization Cooling Experiment (MICE), and future uses include solenoids for the Fermilab mu2e experiment. This paper describes the test stand design and operation including controlled cool-down and warm-up. Overviews of the process controls system and the quench management system are also included.

43 PARTICLE ACCELERATORS↗

DOE OSTI2018

Abstract for CRADA between Solar Turbines Incorporated and NETL

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Final Report – Cooperative Research and Development Agreement between National Energy Technology Laboratory and Solar Turbines Incorporated

The National Energy Technology Laboratory is developing the Raman Gas Analyzer (RGA) to be a fast, non-destructive instrument for on-line measurement of gas composition. The RGA prototype has been demonstrated to have an extremely fast response (<1 second) multi-gas analysis capability. All but the noble gases are Raman active, but Raman interaction is weak with gas phase substances. The RGA uses a reflectively lined capillary as the optical cell in a patented configuration, providing both a small sample volume for fast gas exchange, and a much greater Raman signal collection than traditional instrument configurations. This allows very fast measurement of fuel gases (hydrogen, methane, ethane, propane) as well as other common industrial gases (including CO, CO2, N2, O2, H2O). The RGA provides a new enabling technology for faster, smarter process control based on the chemical composition of the gases in the process, such as improving fuel flexibility and efficiency for power generation systems. NETL has constructed a field prototype of the RGA to test the instrument performance in various applications in fossil energy. Through this CRADA, the RGA prototype operation was tested using hydrocarbon mixtures and hydrogen on a combustor test rig for potential use in gas turbine engine testing. The testing was performed at the Solar Turbines Incorporated Harbor Drive facility in downtown San Diego, CA on December 3-7, 2018. The RGA was installed outside a combustor test bay, with a ¼" sample line connected from a point shortly upstream of the test combustor. The combustion test building online gas chromatograph reported analysis of a sample every 6 minutes. During testing, seven test conditions of pure gas or gas mixtures were supplied to a pressurized combustion test rig. A sample of the fuel gas was continuously analyzed using the RGA with a 1 second measurement and reporting time. For each test condition, once the steady condition was reached, the composition of the gas from the RGA measurements is reported, along with the expected composition from the flow meters, and the composition reported by the online gas chromatograph (GC). During this testing, the real-time measurement capability of the RGA was readily apparent. The composition changes occurring in real-time could be followed and observed to correspond to combustion behavior changes on the video monitor at the operator station. The largest concentration species were tracked well through the tests; however, from comparison of the RGA one-second data with the GC steady-state points, it appears the RGA had some difficulty with quantifying hydrocarbon mixtures, especially when some of the hydrocarbons were at low concentration. The difficulty was particularly noted for ethane and butane in these tests. The NETL team intends to address this in 2019. Moderate concentrations of nitrogen, carbon dioxide, and hydrogen (>10%) were readily observed in the spectral data and quantified closely to the GC measurements. While calibration data for propylene was collected in preparation for this testing, it was not observed during the testing, even when the test conditions had high concentrations of propane.

Source record↗

DOE OSTI2019

Final Report – Cooperative Research and Development Agreement between National Energy Technology Laboratory and Oxergy, Inc.

The NETL Raman Gas Analyzer (RGA) has been demonstrated to have an extremely fast response (<1 second) multi-gas analysis capability. All but the noble gases are Raman active, although the Raman interaction is weak. The RGA uses a reflectively lined capillary as the optical cell, providing both a small sample volume for fast gas exchange, and a much greater Raman signal collection than traditional instrument configurations. This allows very fast measurement of fuel gases (hydrogen, methane, ethane, propane) as well as other common industrial gases (carbon monoxide, carbon dioxide, nitrogen, oxygen, and water). This provides a new enabling technology for faster, smarter process control based on the chemical composition of the gases in the process – including improved fuel flexibility and efficiency for power generation systems. Research and development up to 2016 resulted in the construction of two field prototypes of the NETL RGA, which has been in applied to various laboratory applications for testing. The results of the testing have been used to improve the RGA design, with the intent to support technology transfer. The quality of the optical capillary used in the RGA is critical to its performance, and prior work at NETL produced a few optical capillaries superior to those commercially available. The production of high optical quality capillaries, however, was inconsistent in its results. With the support of the DOE Office of Technology Transitions, through the Technology Commercialization Fund program, this project was undertaken to address this commercialization barrier and to also evaluate the possible application of Raman gas analysis to a supercritical water gasification process being developed by Oxergy Inc. Oxergy, a small business located in Fairbanks, Alaska, is developing ultra-compact thermochemical reaction devices built with advanced manufacturing processes. Chief Technology Officer Jonathan Kamler holds the (pending) patent to Oxergy’s core reactor technology. Oxergy maintains wet-lab and combustion-lab space at the University of Alaska Fairbanks Center for Sustainable Living in Palmer, Alaska, where Mr. Kamler operates a pilot-scale, supercritical water gasification system designed and built by Oxergy. Mr. Kamler also operates an All Powers Labs Power Pallet gasifier coupled to a 10KW electrical generator as a dry biomass test platform at the Palmer facility. Both systems are suitable for real-world, collaborative testing of Raman gas analysis applications. The objectives of the CRADA include making the production of high-quality optical capillaries consistent and high yield, investigating other options for optical waveguides, and testing the capillaries for measurements in supercritical water gasification. Success on these objectives will support commercialization of both the RGA and supercritical water gasification technologies. Through the work performed on this project, a new apparatus was constructed and optimized to provide consistent production of high-quality optical capillaries. Several thick-walled capillaries were coated using this apparatus and shipped to Oxergy in September 2018 for testing in both dry gasification and supercritical water gasification process monitoring applications at University of Alaska Fairbanks facilities in Palmer. The strong earthquake near Anchorage and Palmer in November 2018 caused extensive damage and closure of the facilities used by Oxergy, preventing Oxergy from proceeding with experimental testing before the end of the project; the facility has been closed indefinitely. Earthquake damage prohibited the completion of all the project objectives prior to the end of the project. However, significant progress was made toward addressing a core technology commercialization barrier. The largest and most mature potential market for Raman gas analysis is its use in analytical instruments, which require sensitivity and low detection limits, and Oxergy’s market research found that market inertia is a barrier to commercial success in this market. Although NETL’s innovations in capillary coating have substantially improved Raman gas analysis capability, the likely market is expected to be niche applications that value the fast detection of real-time changes in gas composition.

Chorpening, Benjamin↗

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 OSTI2024

Effects of input gradient regularization on neural networks time-series forecasting of thermal power systems

This study proposes using neural networks, specifically gated recurrent unit (GRU), long-short-term memory (LSTM), and transformer networks, to improve control strategies in a 450 MW coal-fired power plant. However, neural networks face issues of becoming overly dependent on just a few variables to make predictions, which negatively impacts control decisions that rely on the model to determine the value of all manipulated variables. The paper introduces regularization techniques, including noise injection and input gradient regularization, during the training phase. Here, the work presents novel contributions in adapting neural networks to control industrial systems and applying regularization techniques from computer vision to industrial process control. Results demonstrate the effectiveness of input gradient regularization in reducing model dependence on subsets of variables, emphasizing the balance between fidelity and controllability. Further exploration is recommended, including the development of recurrent transformers, closed-loop control testing, and a sensitivity analysis on computer models to provide further insight.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2022

Leveraging Multiple Raman Excitation Wavelength Systems for Process Monitoring of Nuclear Waste Streams

Processing nuclear waste from sites such as Hanford is a significant environmental cleanup need while being a significant logistical challenge. Integration of process monitoring tools, that can provide in situ and real-time feedback about the process, can significantly alleviate needs to collect grab samples for process control and product characterization. Raman spectroscopy paired with chemometric analysis is one process monitoring tool that can provide chemical composition information on a large number of chemical targets in nuclear waste streams. However, methods to improve limits of detection as well as drop uncertainty in quantification are needed. Optimizing instrument specifications can achieve this, here this is demonstrated by comparing limits of detection for key analytes when using Raman systems with 671 nm, 532 nm, and 405 nm excitation wavelengths. Generally, limits of detection decease (allowing the measurement of lower salt concentrations) with decreasing wavelength. Similarly, data collection times and averaging were optimized. Finally, multiple chemometric modeling approaches were leveraged, including multiblock methods that combined data from all three Raman systems to simultaneously quantify targets with improved sensitivity.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

Marine ARM GPCI Investigation of Clouds Infrared Sea Surface Temperature Autonomous Radiometer (ISAR) Field Campaign Report

Sea surface temperature (SST) is one of the most appropriate and important climate parameters: a widespread increase is an indicator of global warming and modifications of the geographical distribution of SST are an extremely sensitive indicator of climate change. There is high demand for accurate, reliable, high-spatial-and-temporal-resolution SST measurements for the parameterization of ocean-atmosphere heat, momentum, and gas (SST is therefore critical to understanding the processes controlling the global carbon dioxide budget) fluxes, for detailed diagnostic and process-orientated studies to better understand the behavior of the climate system, as model boundary conditions, for assimilation into climate models, and for the rigorous validation of climate model output. In order to achieve an overall net flux uncertainty < 10 W/m 2 (Bradley and Fairall, 2006), the sea surface (skin) temperature (SSST) must be measured to an error < 0.1 C and a precision of 0.05 C. Anyone experienced in shipboard meteorological measurements will recognize this is a tough specification. These demands require complete confidence in the content, interpretation, accuracy, reliability, and continuity of observational SST data—criteria that can only be fulfilled by the successful implementation of an ongoing data product validation strategy.

54 ENVIRONMENTAL SCIENCES↗