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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Using Neural Networks to Identify Mixture Components in Hyperspectral Reflectance Data

Neural networks have been employed to identify materials of interest from hyperspectral data (generally imagery) based on their unique spectral signatures. This approach assumes that there is a single material that is standing out from the rest of the spectrum to be identified. However, pixels often contain more than one material, or a material of interest may itself be a mixture of multiple materials. Neural networks are only as good as the data used to train them, and it takes a great deal of work in the laboratory to identify, make, and measure all potential mixtures of interest. Thus, researchers often calculate synthetic spectra using algorithms with varying degrees of fidelity to the physics that govern the interactions between light and multiple materials. In this work, we have (1) adapted a neural network designed to identify mixture components from Raman spectroscopy to work with visible to near‐infrared reflectance data and (2) tested three common mixture algorithms to determine the most accurate and least computationally expensive method to build synthetic training datasets. With our initial test dataset, we have achieved accuracies of > 90% and found that the synthetic training dataset produced using the Hapke mixture model provides the best results.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Characterization of Fuel Cladding Chemical Interaction on a High Burnup U-10Zr Metallic Fuel via Electron Energy Loss Spectroscopy Enhanced by Machine Learning

Fuel cladding chemical interaction (FCCI) is one of the main performance limiting factors for metallic nuclear fuels. The interaction destabilizes the martensitic microstructure and deteriorates mechanical properties of HT-9 cladding. The detection of low atomic number elements (Z<10) and overlapping of elemental peaks can be problematic in interpreting energy dispersive X-ray spectroscopy (EDS) data. Electron energy loss spectroscopy (EELS) provides precise elemental edge energy values and can detect elements with a low atomic number. This work utilizes EELS to study the distribution of lanthanides and light elements at the interaction region. The sample was prepared from the FCCI region of a U-10Zr (wt.%) solid fuel with HT-9 cladding, irradiated to a burnup of 13.2 at.%. Processing the EELS data included three major steps: 1) enhance the signal to noise ratio by denoising the spectrum with principal component analysis (PCA) method, removing background and performing deconvolution; 2) identify chemical elements with core energy loss edges; 3) confirm different phases using a popular machine learning method, K-means. This work presents qualitative assessment of lanthanides and light elements like carbon (C) and oxygen (O) enhanced by the application of machine learning algorithms. By comparing with EDS elemental maps, EELS provides higher resolution chemical maps, reveals the distribution of carbon at the interaction region supporting the formation of zirconium carbide, a rind-like microstructure feature that was proposed to mitigate the chemical interaction. Furthermore, the plasmon peak map was also found to indicate an energy shift associated with the formation of phases/compounds. K-means clustering method was used on the processed electron energy loss (EEL) spectrum to automatically reveal different phases. The resulting clustered maps from K-means clustering align well with elemental maps confirming certain phases, especially Fe-Ce and Zr-C, in the FCCI region.

EELS↗
DOE OSTI2024

Evolution of the two-neutron configuration from 11 Li to 13 Li

In this work we investigate the two-neutron decay of 13 Li and of the excited states of 11 Li populated via one-proton removal from 14 Be and 12 Be, respectively. A phenomenological model is used to describe the decay of 11 Li and 13 Li. While the first one displays important sequential components, the second one appears dominated by the direct two-neutron decay. A microscopic three-body model is used to extract information on the spatial configuration of the emitted neutrons before the decay and shows that the average distance between the neutrons increases going from 11 Li to 13 Li.

Dineutron decay↗
DOE OSTI2024

Gamma, electron beam and X-ray irradiation effects on polymers in an advanced bone cement mixer device

The medical device industry has been investigating ways to increase the use of alternatives to cobalt-60 gamma radiation and ethylene-oxide gas sterilization, such as electron beam (E-beam) and X-ray radiation, due to regulatory and market pressures. One impediment to switching to E-beam or X-ray technology for sterilization is the lack of data on the effects of these radiation sources on medical device polymers. To provide such data this work considers irradiation and testing of a common single-use medical bone cement mixing system, the Stryker Advanced Cement Mixer (ACM®), that is composed of seven polymer materials. The ACM® devices considered here were processed to sterilization-relevant doses (15, 25, 50, and 70 kGy) using three radiation technologies: gamma, E-beam, and X-ray. The system and its polymer components were tested for product functionality, as well as mechanical and visual properties to determine how exposure effects may be influenced by radiation technology and dose level. We found that although there were instances of statistically significant differences in effects between the gamma-irradiated products and those irradiated with E-beam and X-ray, those effects were negligible in terms of retained functionality of the product and retained mechanical properties of the polymer components. Overall, results of this study demonstrate that, for of the effects studied, E-beam and X-ray are viable alternatives to cobalt-60 gamma radiation for sterilization of the polymer-based device investigated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Pore-Scale Microenvironments Control Anthropogenic Carbon Mineralization Outcomes in Basalt

Thin sections and hand samples from 50 sidewall cores from the Wallula Basalt Pilot Demonstration, a basaltic carbon sequestration demonstration, provided the opportunity for the in-depth analysis of carbon mineralization induced by the injection of supercritical CO 2 . In this study, we used optical petrography and scanning electron microscopy to characterize the physical and chemical characteristics of the basalt components influenced by carbon mineralization reactions from all available hand samples and thin sections within the three CO 2 injection zones and caprock flow interiors. We found extensive carbonate mineralization, mostly in the form of nodules that were shown to be chemically zoned: Ca-dominant in the core regions and Ca-bearing Fe-dominant in the outer regions. Carbonate mineralization also took the form of fracture-filling carbonate cement, and acicular aragonite was also observed. Overall, we clarified the structural and paragenetic relationships between newly formed minerals, identifying a new fibro-palagonite-like, poorly crystalline silicate phase that grew on the carbonate nodules and pore-lining zeolites. Here we observed Fe-dominant carbonate precipitates surrounding acicular aragonite and rhombohedral Ca-carbonate cores, whereas previous studies of these zoned nodules did not observe these structures. A comprehensive accounting of the carbon mineralization products is vital to understand and predict the behavior of supercritical CO 2 in the subsurface given both the diversity of the host rock between and within injection zones, especially considering that the morphology and chemistry of the diverse precipitates are influenced by the pore-scale microenvironments of the basalt.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Decontamination of SARS-CoV-2 and Other RNA Viruses from N95 Level Meltblown Polypropylene Fabric Using Heat under Different Humidities

In March of 2020, the World Health Organization declared a pandemic of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The pandemic led to a shortage of N95-grade filtering facepiece respirators (FFRs), especially surgical-grade N95 FFRs for protection of healthcare professionals against airborne transmission of SARS-CoV-2. We and others have previously reported promising decontamination methods that may be applied to the recycling and reuse of FFRs. In this study we tested disinfection of three viruses, including SARS-CoV-2, dried on a piece of meltblown fabric, the principal component responsible for filtering of fine particles in N95-level FFRs, under a range of temperatures (60–95 °C) at ambient or 100% relative humidity (RH) in conjunction with filtration efficiency testing. We found that heat treatments of 75 °C for 30 min or 85 °C for 20 min at 100% RH resulted in efficient decontamination from the fabric of SARS-CoV-2, human coronavirus NL63 (HCoV-NL63), and another enveloped RNA virus, chikungunya virus vaccine strain 181/25 (CHIKV-181/25), without lowering the meltblown fabric’s filtration efficiency.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Analysis of Narrow Bipolar Events Using Mode Decomposition Methods

Multi-resolution analysis methods can reveal the underlying physical dynamics of nonstationary signals, such as those from lightning. In this paper we demonstrate the application of two multi-resolution analysis methods: Ensemble Empirical Mode Decomposition (EEMD) and Variational Mode Decomposition (VMD) in a comparative way in the analysis of electric field change waveforms from lightning. EEMD and VMD decompose signals into a set of Intrinsic Mode Functions (IMFs). The IMFs can be combined using distance and divergence metrics to obtain noise reduction or to obtain new waveforms that isolate the physical processes of interest while removing irrelevant components of the original signal. We apply the EEMD and VMD methods to the observations of three close Narrow Bipolar Events (NBEs) that were reported by Rison et al. The ΔE observations reveal the occurrence of complex oscillatory processes after the main NBE sferic. We show that both EEMD and VMD are able to isolate the oscillations from the main NBE, with VMD being more effective of the two methods since it requires the least user supervision. The oscillations are found to begin at the end of the NBEs' downward fast positive breakdown and appear to be produced by a half-wavelength standing wave within a weakly-conducting resonant ionization cavity left behind in the wake of the streamer-based NBE event. In conclusion, additional analysis shows that one of the NBEs was likely initiated by an energetic cosmic ray shower, and also corrects a misinterpretation in the literature that fast breakdown is an artifact of NBE-like events in interferometer observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Substructure in the stellar halo near the Sun: I. Data-driven clustering in integrals-of-motion space

Context. Merger debris is expected to populate the stellar haloes of galaxies. In the case of the Milky Way, this debris should be apparent as clumps in a space defined by the orbital integrals of motion of the stars. Aims. Our aim is to develop a data-driven and statistics-based method for finding these clumps in integrals-of-motion space for nearby halo stars and to evaluate their significance robustly. Methods. We used data from Gaia EDR3, extended with radial velocities from ground-based spectroscopic surveys, to construct a sample of halo stars within 2.5 kpc from the Sun. We applied a hierarchical clustering method that makes exhaustive use of the single linkage algorithm in three-dimensional space defined by the commonly used integrals of motion energy E, together with two components of the angular momentum, L z and L ⊥ . To evaluate the statistical significance of the clusters, we compared the density within an ellipsoidal region centred on the cluster to that of random sets with similar global dynamical properties. By selecting the signal at the location of their maximum statistical significance in the hierarchical tree, we extracted a set of significant unique clusters. By describing these clusters with ellipsoids, we estimated the proximity of a star to the cluster centre using the Mahalanobis distance. Additionally, we applied the HDBSCAN clustering algorithm in velocity space to each cluster to extract subgroups representing debris with different orbital phases. Results. Our procedure identifies 67 highly significant clusters (> 3σ), containing 12% of the sources in our halo set, and 232 subgroups or individual streams in velocity space. In total, 13.8% of the stars in our data set can be confidently associated with a significant cluster based on their Mahalanobis distance. Inspection of the hierarchical tree describing our data set reveals a complex web of relations between the significant clusters, suggesting that they can be tentatively grouped into at least six main large structures, many of which can be associated with previously identified halo substructures, and a number of independent substructures. This preliminary conclusion is further explored in a companion paper, in which we also characterise the substructures in terms of their stellar populations. Conclusions. Our method allows us to systematically detect kinematic substructures in the Galactic stellar halo with a data-driven and interpretable algorithm. The list of the clusters and the associated star catalogue are provided in two tables available at the CDS.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

The Large Hadron–Electron Collider at the HL-LHC

The Large Hadron–Electron Collider (LHeC) is designed to move the field of deep inelastic scattering (DIS) to the energy and intensity frontier of particle physics. Exploiting energy-recovery technology, it collides a novel, intense electron beam with a proton or ion beam from the High-Luminosity Large Hadron Collider (HL-LHC). The accelerator and interaction region are designed for concurrent electron–proton and proton–proton operations. This report represents an update to the LHeC’s conceptual design report (CDR), published in 2012. It comprises new results on the parton structure of the proton and heavier nuclei, QCD dynamics, and electroweak and top-quark physics. It is shown how the LHeC will open a new chapter of nuclear particle physics by extending the accessible kinematic range of lepton–nucleus scattering by several orders of magnitude. Due to its enhanced luminosity and large energy and the cleanliness of the final hadronic states, the LHeC has a strong Higgs physics programme and its own discovery potential for new physics. Building on the 2012 CDR, this report contains a detailed updated design for the energy-recovery electron linac (ERL), including a new lattice, magnet and superconducting radio-frequency technology, and further components. Challenges of energy recovery are described, and the lower-energy, high-current, three-turn ERL facility, PERLE at Orsay, is presented, which uses the LHeC characteristics serving as a development facility for the design and operation of the LHeC. An updated detector design is presented corresponding to the acceptance, resolution, and calibration goals that arise from the Higgs and parton-density-function physics programmes. This paper also presents novel results for the Future Circular Collider in electron–hadron (FCC-eh) mode, which utilises the same ERL technology to further extend the reach of DIS to even higher centre-of-mass energies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

High-resolution simulations of a turbulent boundary layer impacting two obstacles in tandem

High-fidelity large-eddy simulations of the flow around two rectangular obstacles are carried out at a Reynolds number of 10 000 based on the freestream velocity and the obstacle height. The incoming flow is a developed turbulent boundary layer. Mean-velocity components, turbulence fluctuations, and the terms of the turbulent-kinetic-energy budget are analyzed for three flow regimes: skimming flow, wake interference, and isolated roughness. Three regions are identified where the flow undergoes the most significant changes: the first obstacle’s wake, the region in front of the second obstacle, and the region around the second obstacle. In the skimming-flow case, turbulence activity in the cavity between the obstacles is limited and mainly occurs in a small region in front of the second obstacle. In the wake-interference case, there is a strong interaction between the freestream flow that penetrates the cavity and the wake of the first obstacle. Furthermore, this interaction results in more intense turbulent fluctuations between the obstacles. In the isolated-roughness case, the wake of the first obstacle is in good agreement with that of an isolated obstacle. Separation bubbles with strong turbulent fluctuations appear around the second obstacle.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Cooperative Charge Ordering Signature of Trimer Molecules in Infinite-Layer CaCoO 2

The infinite-layer compound CaCoO 2 provides a compelling platform to explore how local orbital distortions evolve into collective electronic order. Using resonant soft x-ray scattering (RSXS) and its time-resolved counterpart (tr-RSXS), we reveal a cooperative coupling between two intertwined orders at the same in-plane wave vector, 𝑞 ≈ (1/4, 1/4, 0), comprising a quasi-two-dimensional orbital order associated with the distorted Co (1) sites and a quasi-three-dimensional trimerlike charge order stabilized through Co-O-Ca hybridization. The charge-sensitive component exhibits a uniform relaxation time of ∼400 fs (391 ± 5 fs) across multiple Co resonances, evidencing a collective charge response. A comparable timescale observed in the orbital order associated with the highly distorted Co (1) sites indicates that this collective behavior naturally originates from the same orbital framework that mediates both charge and orbital degrees of freedom. Together, these findings establish CaCoO 2 as a model system in which Jahn-Teller distortions, orbital hybridization, and geometric frustration cooperate to form molecular trimer units that dictate the macroscopic electronic behavior.

Lee, J.-S. [SLAC National Accelerator Laboratory (↗
DOE OSTI2022

Improved Control Strategy of Grid-Forming Inverters for Fault Ride-Through in a Microgrid System

This paper develops an improved control strategy of grid-forming (GFM) inverters with fault ride-through capabilities to guarantee the stable operation of microgrids under fault conditions, especially islanded microgrids and asymmetrical faults. The proposed control strategy includes the dual control of positive-sequence and negative-sequence control as well as the adaptive virtual impedance (VI) control. Unlike existing works, the proposed strategy applies the VI control for only the d component of the positive-sequence control and leaves the q component of the positive-sequence control and the dq component of the negative-sequence control as zero, thus achieving improved stability and balanced three-phase voltages under asymmetrical faults. The adaptive feature of the VI control guarantees the stability of the GFM inverter under severe faults, which could cause the saturation of the inner current loop and instability if the VI is not adaptive. Simulation results of various unbalanced faults with high- and low-fault impedances show that the proposed control strategy improves the stability of the GFM inverter and achieves stable and balanced output voltages in islanded microgrids. And the algorithm also improves the stability of GFM inverters under balanced faults with high- and low-fault impedances.

adaptive virtual impedance control↗
DOE OSTI2022

Volumetric additive manufacturing of silica glass with microscale computed axial lithography

Glass is increasingly desired as a material for manufacturing complex microscopic geometries, from the micro-optics in compact consumer products to microfluidic systems for chemical synthesis and biological analyses. As the size, geometric, surface roughness, and mechanical strength requirements of glass evolve, conventional processing methods are challenged. We introduce microscale computed axial lithography (micro-CAL) of fused silica components, by tomographically illuminating a photopolymer-silica nanocomposite that is then sintered. We fabricated three-dimensional microfluidics with internal diameters of 150 micrometers, free-form micro-optical elements with a surface roughness of 6 nanometers, and complex high-strength trusses and lattice structures with minimum feature sizes of 50 micrometers. As a high-speed, layer-free digital light manufacturing process, micro-CAL can process nanocomposites with high solids content and high geometric freedom, enabling new device structures and applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Multiscale Machine-Learned Modeling Infrastructure RAS

MuMMI RAS is the application component of the Multiscale Machine-Learned Modeling Infrastructure (MuMMI). It simulates RAS protein interactions at three scales of resolution coupled with ML-based selection and in-situ feedback. MuMMI RAS is particularly configured for massive scale, running thousands of simultaneous jobs with several terabytes of data on Lassen and Summit.

Moon, JosephY.↗
DOE OSTI2021

A Heterogeneous System for Eagle Detection, Deterrent, and Wildlife Collision Detection for Wind Turbines (Final Technical Report)

This report summarizes the design, implementation, and test of an integrated system for automated detection and deterrence of eagles, with included wind turbine blade strike detection and imaging functionality. A machine learning approach was used in conjunction with a 360° camera system for automated detection and classification of golden eagles. This was developed using footage obtained from trained golden eagles and other raptors, in collaboration with wildlife biologists and professional bird handlers. Oregon State University developed a visual deterrent system, which uses inflatable anthropomorphic sculptures with random, kinetic motion to deter eagles, and conducted limited field testing on live eagles; the deterrent can be triggered by the visual detection of eagles using the vision system. Finally, a multi-sensor module was developed that is mounted at the turbine blade root. This module measures vibration and other motions to detect blade strikes, and an integrated on-blade camera captures an image of any impacting objects. Long-term, this blade strike detection system is intended to support an automatic monitoring and certification system for the eagle detection and deterent system. Independent field testing of each system component is described. Testing of the integrated system on an operational wind turbine was conducted across three separate field tests. This includes multi-day fields tests on a General Electric 1.5MW wind turbine at the National Renewable Energy Laboratory (NREL) National Wind Technology Center (NWTC) in Boulder, CO in October 2018 and July 2019; installation procedures, test procedures, and a summary of collected data are presented. A third multi-day on-turbine field test is also presented, which was performed using a General Electric 1.5MW wind turbine at the North American Wind Research and Training Center (NAWRTC) at Mesalands Community College, Tucumcari, NM in April 2019. Across these field tests, the vision system was demonstrated using unmanned aerial vehicles (UAV), and the eagle classification algorithm was not tested; the visual deterrent system was demonstrated, including automatic, remote deployment following surrogate visual detections; and, multi-sensor on-blade data was recorded across multiple wind turbine operational conditions and through more than 100 surrogate blade strikes using soft projectiles, including the successful demonstration of automatic image capture of striking objects. This data set was also used for offline development and validation of enhanced collision detection algorithms. As summarized in this report, the development and field validation of an integrated detection, deterrent, and blade collision detection system represents a critical proof of concept for future technology development of related detection and deterrent technologies, where both deterrent as well as collision detection recording devices are needed for future siting, monitoring, and operation of wind turbine installations, both onshore and offshore.

17 WIND ENERGY↗
DOE OSTI2025

LAMP Project Facility and Space Requirements

The project will require significant space over the lifetime of the project to successfully execute design, technology maturation, component testing and verification, and final removal and installation. The types of space required falls into three general categories: office, storage, and laboratory. Figure 1 below summarizes the project space requirements by project lifecycle. The specific color coding indicates the availability (and potential risk to the project) of the particular type of space: green indicates space that is already allocated and in use by the LAMP project; yellow indicates space that is expected to be easily transitioned from its current use to the project; red indicates a space that is use by multiple users or other projects, and will most likely require high-level negotiations and planning to become available to the project. Figure 2 summarizes the LAMP Space Requirements by calendar year and type throughout the duration of the project. As can be seen in Fig. 2, the maximum space needed by the project exceeds 40,000 square feet, with an average space requirement over the lifetime of the project equal to approximately 25,000 square feet.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Using Separation-Enhanced Isotope Ratio Mass Spectrometry to Enable Increased Renewable Carbon Content in Transportation Fuels (CRADA 525)

Stable isotope ratio measurements of carbon atoms using isotope ratio mass spectrometry (IRMS) can be an effective tool for quantifying biogenic carbon in co-processed fuels, with results approaching the precision and accuracy of accelerator mass spectrometry (AMS). The lower cost of an IRMS may enable deployment to refineries, improving access and analysis turnaround times (≤2 hours), and, by extension, provide data that can allow process optimization to maximize renewable carbon in desired refinery products. This project explored the integration of chemical separation with IRMS analyses to enable highly detailed tracking of biogenic carbon into fuel product streams separated by boiling point range, chemical class, or specific compound. Forty-nine fuels and fuel components of fossil and biogenic origin, spanning gasoline and diesel boiling point ranges, were received from three refiners and were analyzed for their δ 13 C values via IRMS. Results spanned a 13 C range from ca. 10‰ to 44‰ and reflect materials derived from sustainable sources (e.g., C4 or C3 plants, animal-based pathways, syngas) or from fossil-derived fuels. Common ranges are approximately 18‰ to 9‰ and approximately 30‰ to 20‰ for C4 and C3 plants, respectively, and approximately 34‰ to 24‰ and approximately 70‰ to 33‰ for petroleum-derived fuels and methane, respectively. Fuel-like standards were developed and tested using direct-injection elemental analyzer (EA) IRMS for liquid fuels. This method was compared with the published methods, yielding statistically similar results. Four blend curve sets were produced ranging from 0% to 100% of a fuel containing biogenic carbon, focusing on 0% to 10% biogenic carbon. Linear fits were the most applicable for two of the four blend curve sets; however, two sets were found to exhibit slightly quadratic behavior, which was more pronounced in low biogenic blend samples, necessitating second-order fits. The origin of the slight quadratic behavior remains unclear; however, the discussion points to possible interpretations. CanmetENERGY thoroughly characterized a majority of the samples using one- and two-dimensional gas chromatography (GC and GC×GC, respectively) and other analyses. Selected samples were subjected to solid phase extraction (SPE) for saturate, olefin, aromatic, and polar (SOAP) analysis, and the resulting solvent-diluted fractions containing saturates and aromatics were returned to Pacific Northwest National Laboratory (PNNL), where the solvent was removed via evaporation or physical separation using GC techniques. Characterization and separations provided an understanding of saturate and aromatic content, as well as boiling point ranges for each sample and sample fraction. Samples resulting from SPE were examined using EA-IRMS and gas chromatography combustion IRMS (GC-C-IRMS) analyses. Both approaches suggest that the range in values between end-members can be increased by selecting the paraffinic or aromatic fraction of the end-member or by selecting among individual compounds resulting from GC separation of the paraffinic fractions. Considerable work remains to put these approaches into practice and statistically validate the benefit for using a fraction or individual compound over bulk analysis of a sample. However, initial results suggest that separations provide advantages for samples having blend ratios of less than 10% biogenic blendstocks. 13 C results showed statistically similar biofuel blend results to those obtained at PNNL, although additional work is needed to obtain better reproducibility. Select samples were sent to Los Alamos National Laboratory (LANL) for IRMS measurements and Beta Analytics for AMS measurements. This work suggests that IRMS and AMS yield closely comparable results and in some circumstances, IRMS could serve as a surrogate for AMS. While additional work is needed to better resolve statistical advantages for separations and better show the comparable nature of IRMS and AMS in both the biogenic carbon analysis of bulk chemical classes, initial results from this study suggest that these should be pursued in order to proliferate this approach for quantifying biogenic carbon in transportation fuels to the refinery level, thereby potentially enabling process optimization in co-processing scenarios.

09 BIOMASS FUELS↗
DOE OSTI2026

PIP-II LB650 Cryomodule Mockup

Fermilab’s PIP-II project requires accurate cable routing in the LB650 cryomodule, a confined and difficult-to-access system. We designed a full-scale mockup using a 15-ft, 7-ft 8020 frame and twenty-three PLA interfaces. CAD modeling and lifting analysis has been verified for safe assembly With all components ordered, the mockup will allow technicians to rehearse routing and identify issues before working on the real cryomodule.

Oribello, Francis [Northern Illinois U.]↗