Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “site detection”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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

At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Extended Application of State LiDAR Datasets in Locating Orphaned Wells in Appalachian Region

Location inaccuracies in historical and state oil and gas well databases present a major challenge in locating these orphaned wells. To address this, modern scientific methods such as Light Detection and Ranging (LiDAR), aerial magnetic remote sensing, and digital GIS products have been employed. LiDAR technology uses light to detect surface area changes, providing detailed surface views. This is a workflow to process LiDAR data for use in locating orphaned wells.

Gorantla, Vijaya [NETL Site Support Contractor, Na↗
DOE OSTI2020

Sensor Recommendations for Long Term Monitoring of the F-Area Seepage Basins

In mid-2018, a new paradigm for long-term monitoring was developed after of decade of applied research projects funded by the Department of Energy’s office of Environmental Management Technology Development program. The program at SRNL was focused on transitioning complex environmental waste sites from active to passive remediations strategies. A key result of these studies was that the use of enhanced attenuation approaches at radiologically contaminated sites will result in the creation of secondary source areas in the subsurface that will require monitoring for decades. Alternative monitoring approaches are being developed and tested at the Savannah River Site’s F-Area Hazardous Waste Management Facility, the new paradigm provides innovative solutions that will significantly lower costs of monitoring through the coupling of data collection, machine learning and deterministic groundwater modeling. The foundation of this approach is a well-optimized network of sensors for measuring hydrogeochemical master variables that control, and therefore act as indicators of groundwater contaminant transport. By monitoring changes in the controlling master variables over time arising from geological and environmental shifts, predictive modelling can assist with identifying new strategies for ensuring regulatory requirements are met if trends toward conditions for potential remobilization of attenuated contaminants are detected. In this report, we evaluated commercially available single parameter sensor platforms (e.g., temperature/depth) and configurable multi-parameter sensor platforms (e.g., pH, oxidation-reduction potential, temperature, depth, dissolved oxygen, and conductivity). Each was scored using an optimization function based on how well the system supports the proposed long-term monitoring paradigm, in general, and the site-specific conditions at F-Area, in particular. Several viable sensor systems were identified. Of these, a combined platform including the In-Situ Aqua TROLL 500 multi-parameter sensor platform and the In-Situ temperature/depth sensor had the highest rating and was identified as the most suitable candidate for installation and monitoring of the master variables and potentiometric surface that control groundwater contaminant plumes emanating from the F-Area Seepage Basins. The discussion of recommended potential deployment locations builds upon recommendations made by Denham et al (2019).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Protecting Websites from Cross-Site Scripting (XSS) Attacks: A Novel Configuration using Pulse Secure © Pulse Connect Secure © and Virtual Web Application Firewall (vWAF)

Cross-site scripting (XSS), one of the most prevalent forms of client-side attacks, is when bad actors attempt to access sensitive information from the backend web server and other systems on the backend network. Some XSS attacks attempt to access client-side sensitive information, such as cookies. Web application firewalls (WAFs) are a first line of defense where common Uniform Resource Locator (URL) patterns are analyzed to detect and block known attacks. This paper describes a novel configuration using the Pulse Secure © Pulse Connect Secure © (PCS © ) Secure Socket Layer Virtual Private Network software and Virtual Web Application Firewall (vWAF) that protects a website from XSS attacks. This paper also presents novel aspects of the configuration that control the redirection of traffic through the vWAF and provide fine-grained behavioral control at the application level while decoupling the PCS and vWAF configurations. The intended audience for this paper comprises system and site administrators who are familiar with standard web server environments. These configuration details might prove useful during the design of a more secure infrastructure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Long-range transported continental aerosol in the eastern North Atlantic: three multiday event regimes influence cloud condensation nuclei

Abstract. The eastern North Atlantic (ENA) is a region dominated by pristine marine environment and subtropical marine boundary layer clouds. Under unperturbed atmospheric conditions, the regional aerosol regime in the ENA varies seasonally due to different seasonal surface-ocean biogenic emissions, removal processes, and meteorological regimes. However, during periods when the marine boundary layer aerosol in the ENA is impacted by particles transported from continental sources, aerosol properties within the marine boundary layer change significantly, affecting the concentration of cloud condensation nuclei (CCN). Here, we investigate the impact of long-range transported continental aerosol on the regional aerosol regime in the ENA using data collected at the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) user facility on Graciosa Island in 2017 during the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) campaign. We develop an algorithm that integrates number concentrations of particles with optical particle dry diameter (Dp) between 100 and 1000 nm, single scattering albedo, and black carbon concentration to identify multiday events (with duration >24 consecutive hours) of long-range continental aerosol transport in the ENA. In 2017, we detected nine multiday events of long-range transported particles that correspond to ∼ 7.5 % of the year. For each event, we perform HYSPLIT 10 d backward trajectories analysis, and we evaluate CALIPSO aerosol products to assess, respectively, the origins and compositions of aerosol particles arriving at the ENA site. Subsequently, we group the events into three categories, (1) mixture of dust and marine aerosols, (2) mixture of marine and polluted continental aerosols from industrialized areas, and (3) biomass burning aerosol from North America and Canada, and we evaluate their influence on aerosol population and cloud condensation nuclei in terms of potential activation fraction and concentrations at supersaturation of 0.1 % and 0.2 %. The arrival of plumes dominated by the mixture of dust and marine aerosol in the ENA in the winter caused significant increases in baseline Ntot. Simultaneously, the baseline particle size modes and CCN potential activation fraction remained almost unvaried, while cloud condensation nuclei concentrations increased proportionally to Ntot. Events dominated by a mixture of marine and polluted continental aerosols in spring, fall, and winter led to a statistically significant increase in baseline Ntot, a shift towards larger particular sizes, a higher CCN potential activation fractions, and cloud condensation nuclei concentrations of >170 % and up to 240 % higher than during baseline regime. Finally, the transported aerosol plumes characterized by elevated concentration of biomass burning aerosol from continental wildfires detected in the summertime did not statistically contribute to increase baseline aerosol particle concentrations in the ENA. However, particle diameters were larger than under baseline conditions, and CCN potential activation fractions were >75 % higher. Consequentially, cloud concentration nuclei concentrations increased by ∼ 115 % during the period affected by the biomass burning events. Our results suggest that, through the year, multiday events of long-range continental aerosol transport periodically affect the ENA and represent a significant source of CCN in the marine boundary layer. Based on our analysis, in 2017, the multiday aerosol plume transport dominated by a mixture of dust and marine aerosol, a mixture of marine and polluted continental aerosols, and biomass burning aerosols caused increases in the NCCN baseline regime of, respectively, 6.6 %, 8 %, and 7.4 % at SS 0.1 % (and, respectively, 6.5 %, 8.2 %, and 7.3 % at SS 0.2 %) in the ENA.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Oxide-Free Three-Dimensional Germanium/Silicon Core–Shell Metalattice Made by High-Pressure Confined Chemical Vapor Deposition

Metalattices are crystalline arrays of uniform particles in which the period of the crystal is close to some characteristic physical length scale of the material. In this work, we explore the synthesis and properties of a germanium metalattice in which the similar to 70 nm periodicity of a silica colloidal crystal template is close to the similar to 24 nm Bohr exciton radius of the nanocrystalline Ge replica. The problem of Ge surface oxidation can be significant when exploring quantum confinement effects or designing electronically coupled nanostructures because of the high surface area to volume ratio at the nanoscale. To eliminate surface oxidation, we developed a coreshell synthesis in which the Ge metalattice is protected by an oxide-free Si interfacial layer, and we explore its properties by transmission electron microscopy (TEM), Raman spectroscopy, and electron energy loss spectroscopy (EELS). The interstices of a colloidal crystal film grown from 69 nm diameter spherical silica particles were filled with polycrystalline Ge by high-pressure confined chemical vapor deposition (HPcCVD) from GeH4. After the SiO2 template was etched away with aqueous HF, the Ge replica was uniformly coated with an amorphous Si shell by HPcCVD as confirmed by TEM-EDS (energy-dispersive X-ray spectroscopy) and Raman spectroscopy. Formation of the shell prevents oxidation of the Ge core within the detection limit of XPS. The electronic properties of the core-shell structure were studied by accessing the Ge 3d edge onset using STEM-EELS. A blue shift in the edge onset with decreasing size of Ge sites in the metalattices suggests quantum confinement of the Ge core. The degree of quantum confinement of the Ge core depends on the void sizes in the template, which is tunable by using silica particles of varying size. The edge onset also shows a shift to higher energy near the shell in comparison with the Ge core. This shift along with the observation of Ge-Si vibrational modes in the Raman spectrum indicate interdiffusion of Ge and Si. Both the size of the voids in the template and core-shell interdiffusion of Si and Ge can in principle be tuned to modify the electronic properties of the Ge metalattice.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Autonomous scanning probe microscopy investigations over WS2 and Au{111}

Abstract Individual atomic defects in 2D materials impact their macroscopic functionality. Correlating the interplay is challenging, however, intelligent hyperspectral scanning tunneling spectroscopy (STS) mapping provides a feasible solution to this technically difficult and time consuming problem. Here, dense spectroscopic volume is collected autonomously via Gaussian process regression, where convolutional neural networks are used in tandem for spectral identification. Acquired data enable defect segmentation, and a workflow is provided for machine-driven decision making during experimentation with capability for user customization. We provide a means towards autonomous experimentation for the benefit of both enhanced reproducibility and user-accessibility. Hyperspectral investigations on WS 2 sulfur vacancy sites are explored, which is combined with local density of states confirmation on the Au{111} herringbone reconstruction. Chalcogen vacancies, pristine WS 2 , Au face-centered cubic, and Au hexagonal close-packed regions are examined and detected by machine learning methods to demonstrate the potential of artificial intelligence for hyperspectral STS mapping.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Field Insights: Strengthening Digital Assurance Through On-Site Network Monitoring

The accelerating deployment of digital energy infrastructure, ranging from inverter-based resources (IBRs), battery energy storage systems (BESS), to advanced grid control platforms, has brought unprecedented visibility, flexibility, and efficiency to the electric grid. However, this digital transformation also introduces new cybersecurity challenges, particularly in the form of supply chain risks and operational blind spots at the grid edge. Over the past year, the Department of Energy’s Office of Cybersecurity, Energy Security, and Emergency Response (CESER), through its Rapid Risk Assessment initiative, along with the Grid Deployment Office (GDO), through its Technical Assistance for Digital Assurance (TADA) initiative, have supported a series of on-site network engagements led by Idaho National Laboratory (INL). These engagements, conducted in partnership with asset owners across the country, have focused on identifying real-world vulnerabilities and misconfigurations in operational environments, many of which are not detectable through remote assessments or traditional compliance audits. The goal of this report is to distill key findings and lessons learned during network hunt engagements from INL’s fiscal year (FY) 2024 - 2025. It is intended to help asset owners—regardless of their participation in the program—better understand the evolving threat landscape and adopt practical measures to secure their digital energy infrastructure.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Active Neutron Interrogation as a Method for Verification of the Absence of Special Nuclear Material in Arms Control Dismantlement

The next step in arms control reductions will deal with both strategic and non-strategic weapons, presenting new and hard challenges for verification. One verification approach that might be used in support of these reductions is the concept of deferred verification, which forgoes inspections at sensitive nuclear sites and relies on an inspection regime having access to the open segment of a State's nuclear sector, in "monitored transfer zones." A component of this approach is the anticipated need for an instrument suite capable of detecting well-shielded highly-enriched uranium or plutonium where it isn't supposed to be. This specific need was recently identified by the United Nations Institute for Disarmament Research in an enabling operating concept they call "contain and dispose." At the foundation of this approach is the idea that items declared as "not nuclear" are, by definition, not treaty limited and are thus "fair-game" for inspection and questioning. Active Neutron Interrogation (ANI), using beta-delayed neutron emissions as the signature for special nuclear material (SNM) detection, is a promising method to address this challenge. The method is quick, has high sensitivity and high specificity for detecting shielded SNM, is robust against changing background radiation environments, is robust against the presence of unknown shielding, and avoids the use of gamma-ray spectrometry which may introduce complications due to the potential release of sensitive information. This paper will present recent research activities exploring technical aspects of using ANI as a FAIRGAME verification method and discuss future prospects and research needs

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2020

Mars Extant Life: What's Next? Conference Report

On November 5–8, 2019, the ‘‘Mars Extant Life: What’s Next?’’ conference was convened in Carlsbad, New Mexico. The conference gathered a community of actively publishing experts in disciplines related to habitability and astrobiology. Primary conclusions are as follows: A significant subset of conference attendees concluded that there is a realistic possibility that Mars hosts indigenous microbial life. A powerful theme that permeated the conference is that the key to the search for martian extant life lies in identifying and exploring refugia (‘‘oases’’), where conditions are either permanently or episodically significantly more hospitable than average. Based on our existing knowledge of Mars, conference participants highlighted four potential martian refugium (not listed in priority order): Caves, Deep Subsurface, Ices, and Salts. The conference group did not attempt to reach a consensus prioritization of these candidate environments, but instead felt that a defensible prioritization would require a future competitive process. Within the context of these candidate environments, we identified a variety of geological search strategies that could narrow the search space. Additionally, we summarized a number of measurement techniques that could be used to detect evidence of extant life (if present). Again, it was not within the scope of the conference to prioritize these measurement techniques—that is best left for the competitive process. We specifically note that the number and sensitivity of detection methods that could be implemented if samples were returned to Earth greatly exceed the methodologies that could be used at Mars. Finally, important lessons to guide extant life search processes can be derived both from experiments carried out in terrestrial laboratories and analog field sites and from theoretical modeling.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Lessons Learned from Hanford's Purex Tunnel 2 Structural Stabilization Project - 20509

In 2019, U.S. Department of Energy (DOE) contractor CH2M Hill Plateau Remediation Company (CHPRC) completed structurally stabilizing the Plutonium Uranium Extraction Plant (Purex) waste storage Tunnel 2 with engineered grout. This action significantly reduced risk to Hanford workers, the surrounding community and environment by preventing future collapse of the tunnel and possible release of radioactive materials. Decades of plutonium production at the Purex facility required construction of two large underground tunnels for storage of highly contaminated plutonium processing equipment that had failed during the operation of Purex and other facilities across the Hanford Site. Following the partial collapse of Purex Tunnel 1 on May 9, 2017, DOE and CHPRC took immediate action to safely stabilize the collapsed section of the tunnel. The hole in the tunnel was filled the next day as a temporary stabilization measure, and no contamination was detected as a result of the partial collapse of the tunnel. Workers then stabilized Tunnel 1 in its entirety by filling with engineered grout, which also encapsulated the radioactive equipment and railcars within the tunnel. Grouting eliminated the risk of further collapse and stabilized the tunnel contents, all while not precluding future remedial actions or final closure decisions. While conducting an integrity analysis of Tunnel 1 by using construction drawings, photos and other historical documents, project teams also analyzed the much larger Purex Tunnel 2. The analysis found Tunnel 2 did not meet current codes for structural integrity, and it may not be able to bear the weight of the soil above the tunnel. Therefore, it was determined that Tunnel 2 was also at risk of collapse. DoE's independent panel of experts determined grouting to be the best choice for stabilizing Tunnel 2 because it provides the highest level of stability and protection, and does not preclude future remedial actions. DOE authorized CHPRC to commence work and the Purex Tunnel 2 Structural Stabilization Project was launched in December of 2017. The paper will discuss the process of recognizing the following critical aspects and risks associated with stabilizing Tunnel 2, and the actions taken by the project team to mitigate these risks, including: - Tunnel investigation and data collection to assist with future remediation; - On-site batching and mock-ups to provide the large quantity of grout required for stabilizing the tunnel; - Workforce involvement and innovative actions that mitigated the project's most significant potential hazards, including traffic control; - Project team high level of execution translated into successful project execution. Sharing lessons learned from this critical risk-reduction effort can enhance the safety and efficiency of other complex and hazardous projects across the DOE complex. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Machine Learning Modeling Pipeline for Extracting Nuclear Proliferation Events of Interest from Open Data Sources (U)

In FY2020, the Savannah River National Laboratory (SRNL) and the Sanghani Center for Artificial Intelligence and Data Analytics at Virginia Polytechnic Institute and State University entered a collaboration funded by Department of Energy’s (DOE) Office of Defense Nuclear Nonproliferation Research and Development. The project’s mission was to take the first steps toward developing a demonstration prototype system that uses multiple machine learning and data analytics methods on largescale open data sources to identify new, developing, and/or undeclared nuclear programs. Given the SRNL team’s on-site perspective of events culminating in the DOE’s decision to pursue the Savannah River Plutonium Processing Facility (SRPPF), the team targeted the identification of events and indicators in retrospective datasets that pointed to the activity of “fissile core fabrication at the Savannah River Site” prior to the official announcement in May of 2018. A preliminary modeling pipeline was developed in FY20 that showed the datasets contained adequate signal for continuation of efforts. In FY21, a modular demonstration prototype modeling pipeline has continued in development for two text-based data sources: a broad internet archive (Webhose Ltd.) and a decahose Twitter database (i.e., a global sampling of one in every ten Tweets). The techniques that have been developed rely on graph theory and anomaly detection to identify contextual shifts in key words and phrases at various points in time such that indicators of events of interest could be identified and subsequently, events could be extracted from the corpuses. The foundational concept behind the approaches is that contextual shifts in key words and phrases can act as indicators of events of interest. Both datasets have proven successful in extracting events of interest related to pit production at the Savannah River Site prior to the official announcement. In addition, the pipelines have generated a wide range of events broadly summarized as: the awarding of DOE contracts at major sites, DOE investments in various programs, accidents at DOE national laboratories, speculations about the fate of pit production in the DOE complex, domestic and international shipments and receipts of nuclear materials at DOE sites, termination of non-proliferation agreements with Russia, termination of MOX, new weapons development approvals/testing, nuclear posture reviews, major DOE cleanup/production milestones, political opinions, and nuclear watch groups’ opinions, among many others.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Formation of the oxyl’s potential energy surface by the spectral kinetics of a vibrational mode

One of the most reactive intermediates for oxidative reactions is the oxyl radical, an electron-deficient oxygen atom. The discovery of a new vibration upon photoexcitation of the oxygen evolution catalysis detected the oxyl radical at the SrTiO3 surface. The vibration was assigned to a motion of the sub-surface oxygen underneath the titanium oxyl (Ti–O●−) created upon hole transfer to (or electron extraction from) a hydroxylated surface site. Evidence for such an interfacial mode is derived from its spectral shape, which exhibited a Fano resonance—a coupling of a sharp normal mode to continuum excitations. Here, this Fano resonance is utilized to derive precise formation kinetics of the oxyl radical and its associated potential energy surface (PES). From the Fano lineshape, the formation kinetics are obtained from the anti-resonance (the kinetics of the coupling factor), the resonance (the kinetics of the coupled continuum excitations), and the frequency integrated spectrum (the kinetics of the normal mode’s cross-section). All three perspectives yield logistic function growth with a half-rise of 2.3 ± 0.3 ps and a time constant of 0.48 ± 0.09 ps. A non-equilibrium transient associated with photoexcitation is separated from the rise of the equilibrated PES. The logistic function characterizes the oxyl coverage at the very initial stages (t ∼ 0) to have an exponential growth rate that quickly decreases toward zero as a limiting coverage is reached. Such time-dependent reaction kinetics identify a dynamic activation barrier associated with the formation of a PES and quantify it for oxyl radical coverage.

Chemistry↗
DOE OSTI2024

TRACER Perspectives on Gulf-Breeze and Bay-Breeze Circulations and Coastal Convection

Abstract This study explores gulf-breeze circulations (GBCs) and bay-breeze circulations (BBCs) in Houston–Galveston, investigating their characteristics, large-scale weather influences, and impacts on surface properties, boundary layer updrafts, and convective clouds. The results are derived from a combination of datasets, including satellite observations, ground-based measurements, and reanalysis datasets, using machine learning, changepoint detection method, and Lagrangian cell tracking. We find that anticyclonic synoptic patterns during the summer months (June–September) favor GBC/BBC formation and the associated convective cloud development, representing 74% of cases. The main Tracking Aerosol Convection Interactions Experiment (TRACER) site located close to the Galveston Bay is influenced by both GBC and BBC, with nearly half of the cases showing evident BBC features. The site experiences early frontal passages ranging from 1040 to 1630 local time (LT), with 1300 LT being the most frequent. These fronts are stronger than those observed at the ancillary site which is located further inland from the Galveston Bay, including larger changes in surface temperature, moisture, and wind speed. Furthermore, these fronts trigger boundary layer updrafts, likely promoting isolated convective precipitating cores that are short lived (average convective lifetime of 63 min) and slow moving (average propagation speed of 5 m s −1 ), primarily within 20–40 km from the coast.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Assessment of Borehole Gravity (Density) Monitoring for CO 2 Injection into the Dover 33 Reef

The Midwest Regional Carbon Sequestration Partnership (MRCSP) was founded in 2003 as part of the U.S. Department of Energy’s (DOE’s) Regional Carbon Sequestration Partnership initiative. Since its founding, MRCSP has made significant strides toward making CCUS a viable option for states in the region. The public/private consortium, funded through the DOE Regional Carbon Sequestration Initiative, brings together nearly 40 industry partners and 10 states. Battelle, as the project lead, oversees research, development and operations and coordinates activities among the partners. The incremental, phased approach has built a valuable knowledge base for the industry and paved the way for commercial-scale adoption of CCUS technologies. From 2008 to 2020, MRCSP Phase III focused on the development of large-scale injection projects. This report is part of a series of reports prepared under the Midwestern Regional Carbon Sequestration Partnership (MRCSP) Phase III (Development Phase). These reports summarize and detail the findings of the work conducted under the Phase III project. This report presents the results of BHG surveys conducted in the Lawnichak-Myskier 1-33 well in the Dover 33 reef by Tellus Gravity and Micro-g LaCoste in 2013, 2016, and 2018. A comparison of the data from the three surveys was performed to determine the feasibility of BHG to detect and monitor the location of the injected CO 2 in the reef over time. In addition, modeling was performed to compare the field data with the modeled data. Applying time-lapse BHG monitoring to a carbon sequestration site consists of determining temporal gravity anomalies related to the injection of CO 2 , and exclusively associated to the redistribution of the fluids in the pore space.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

The major trimeric antenna complexes serve as a site for qH-energy dissipation in plants

Plants and algae are faced with a conundrum: harvesting sufficient light to drive their metabolic needs while dissipating light in excess to prevent photodamage, a process known as nonphotochemical quenching. A slowly relaxing form of energy dissipation, termed qH, is critical for plants’ survival under abiotic stress; however, qH location in the photosynthetic membrane is unresolved. Here, we tested whether we could isolate subcomplexes from plants in which qH was induced that would remain in an energy-dissipative state. Interestingly, we found that chlorophyll (Chl) fluorescence lifetimes were decreased by qH in isolated major trimeric antenna complexes, indicating that they serve as a site for qH-energy dissipation and providing a natively quenched complex with physiological relevance to natural conditions. Next, we monitored the changes in thylakoid pigment, protein, and lipid contents of antenna with active or inactive qH but did not detect any evident differences. Finally, we investigated whether specific subunits of the major antenna complexes were required for qH but found that qH was insensitive to trimer composition. Because we previously observed that qH can occur in the absence of specific xanthophylls, and no evident changes in pigments, proteins, or lipids were detected, we tentatively propose that the energy-dissipative state reported here may stem from Chl–Chl excitonic interaction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Understanding the morphology and chemical activity of model ZrO x /Au (111) catalysts for CO 2 hydrogenation

In this study, the growth of ZrO x on Au (111) was investigated using scanning tunneling microscopy (STM) and synchrotron-based ambient pressure X-ray photoelectron spectroscopy (AP-XPS). Nanostructures of ZrO x (x= 1,2) at the sub-monolayer (≤ 0.3 ML) level were prepared by vapor depositing Zr metal onto Au (111) followed by oxidation with O 2 or CO 2 . At low coverages of the admetal (< 0.05 ML), the formed ZrO x nanostructures were dispersed randomly on the terraces and steps of the Au(111) substrate. Strong oxide-metal interactions prevented the formation of islands of zirconia. The ZrO x nanostructures displayed a reactivity towards CO 2 and H 2 not seen for bulk zirconia. C 1 s AP-XPS results indicated that CO 2 molecules adsorbed on Zr/ZrO x /Au(111) surfaces could undergo partial decomposition on Zr (CO 2 , gas → CO gas + O ads ), or react with oxygen sites from ZrO x to yield carbonates (Zr-CO 3, ads ). Further, after exposing ZrO 2 /Au (111) surfaces to 1:3 mixtures of CO 2 :H 2 , the formation of HCOO, CO 3 , and CH 3 O was detected in AP-XP spectra. These chemical species decomposed at temperatures in the range of 400-600 K, making them possible reaction intermediates for methanol synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Machine Learning‐Assisted Microearthquake Location Workflow for Monitoring the Newberry Enhanced Geothermal System

Abstract Enhanced geothermal systems (EGS) offer a sustainable energy source but face challenges in accurately locating microearthquakes induced during reservoir stimulation. Locating these microearthquakes provides reliable feedback on the stimulation progress. Current deep learning methods for locating earthquakes require extensive data sets for training, which is problematic as detected microearthquakes are often limited. To address the scarcity of training data, we propose a practical workflow using probabilistic multilayer perceptron (PMLP) which predicts microearthquake locations from cross‐correlation time lags in waveforms. Utilizing a 3D velocity model of Newberry site derived from ambient noise interferometry, we generate numerous synthetic microearthquakes and 3D acoustic waveforms for PMLP training. Accurate synthetic tests prompt us to apply the trained network to the 2012 and 2014 stimulation field waveforms. To enhance the accuracy of source localization, we carefully handpick the P‐arrival times. Predictions on the 2012 stimulation data set show major microseismic activity at depths of 0.5–1.2 km, correlating with a known casing leakage scenario. In the 2014 data set, the majority of predictions concentrate at 2.0–2.9 km depths, consistent with results obtained from conventional physics‐based inversion, and align with the presence of natural fractures from 2.0 to 2.7 km. We validate our findings by comparing the synthetic and field picks, demonstrating a satisfactory match for the first arrivals. By combining the benefits of quick inference speeds and accurate location predictions, we demonstrate the feasibility of using realistic synthetic data set to locate microseismicity for EGS monitoring.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Multi-Source Machine Learning and Thermoplastics Enhanced Aerostructure Manufacturing (mTEAM)

RTX Technology Research Center (RTRC), together with Collins Aerospace (Collins) and Oak Ridge National Laboratory (ORNL) has developed an Artificial Intelligence (AI) / Machine Learning (ML) guided solution to advance the manufacturing and assembly of high performance and lightweight thermoplastic composite (TPC) aerospace products. The solution aims to lower risk, cost and lead time for induction heating based welding and consolidation processes for TPC structure. The cost and lead time of part and material specific process development for induction welding (IW) and induction consolidation will be reduced by replacing traditional empirical methods with optimization methods that merge AI/ML and physics-based process simulations and process experiments with sensing and controls. TPC-IW process development is empirical in nature, and uncertainties in material & process behavior exist near & far from the induction coil. Physics-based simulations can be leveraged directly for process optimization but can be too computationally expensive to run in high fidelity and real time to do robust process optimization. The key impact of successful TPC induction consolidation and welding is cost & lead time reduction for part & material specific consolidation and welding recipes. This is an enabler for more rapid deployment of TPC structures via joining assembly, which can reduce energy & cost intensive usage of autoclaves & ovens. The solution aimed to advance the U.S. Department of Energy’s interests in using thermoplastics and automation in composite manufacturing for improvement of products for existing markets via increased production speeds, reduced costs, and lowered use of energy. Welded TPC structures can offer significant weight & energy savings for high-value commercial aerospace & industrial applications compared to metal & thermoset composite structures assembled by mechanical fastening and/or adhesive bonding. The project was organized into two Budget Periods. Budget Period 1 (BP1) was 15 months and its goal was to perform ML process optimization framework development & deployment on lab-coupon aerostructure components. A Go/No-Go Review was performed at the end of BP1 to verify fulfilment of key tasks & milestones to justify a Go Decision to move into the next Budget Period. Budget Period 2 (BP2) was 12 months and its goal was the deployment of the ML framework for ML process optimization of pilot industrial scale aerostructure components. The overall project aim was to develop & demonstrate ML-enhanced modeling framework that learns process-property mapping from multiple data sources at different fidelities. During BP1, the team accomplished key tasks & milestones to demonstrate the concept of multi-source ML for TPC aerostructure consolidation and assembly. First, the team completed documentation of induction based TPC heating requirements including baseline metrics to compare measured results against. Next the team completed demonstration of data generation from physics-based simulations for ML surrogate model generation and demonstrated the integration of physics-based simulation data into multi-source AI/ML algorithms. In parallel, the team established the lab-coupon scale induction welding system and completed a process to label and reduce generated data from physics-based simulation and experiments for ML surrogate models to enable multi-source ML model training & testing. To complete BP1, the team integrated physics-based simulation data and experimental data into multi-source ML algorithms. This was based on the team completing ML deployment of the induction welding on a lab system at RTRC and AI/ML deployment on existing induction welding line at Collins. ORNL visited both Collins and RTRC sites to witness the TPC induction welding process. Then, ORNL designed and constructed a new version of their vision-based sensing system better adapted to acquire process signals of the TPC induction welding process for process anomaly and defect detection. In BP2, the team accomplished key tasks & milestones to scale up multi-source ML for TPC aerostructure consolidation and assembly from the lab-coupon scale to the pilot-industrial scale. In BP2, the team demonstrated real time anomaly & defect detection via experiments performed by ORNL & RTRC. The team completed ML-optimization heating trials for TPC induction consolidation at Collins, and the team confirmed pilot industrial scale experimental data from Collins was compatible with the developed ML pipeline from RTRC. The team completed sub-element scale ML process optimization demonstration at RTRC, where the team leveraged RTRC’s robotic TPC welding setup to de-risk the ML process optimization by performing ML analysis of recorded temperatures to account for complex part features. Then, the team applied its ML-derived control strategies and ML process optimization framework at Collins to the pilot-industrial scale on a demo skin-stiffener part representative of a nacelle aerostructure fan cowl section. The key innovation is the AI/ML framework enabling effective process development of high performance, lightweight, energy efficient TPCs for composite aircraft structures.

36 MATERIALS SCIENCE↗