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DOE OSTI2024

Acoustic Measurements of Solvent Extraction Processes in Support of Safeguards

The proposed poster focuses on using acoustic monitoring to advance detection techniques for reprocessing equipment in support of nuclear safeguards. The usage of free air acoustic monitoring has been previously demonstrated at Idaho National Laboratory (INL) at facilities such as the Advanced Test Reactor and the National Security Test Range. However, this work focuses on a deployment environment dedicated to monitoring separation processes, using solvent extraction equipment such as centrifugal contactors. This environment offers an opportunity for signal discovery and in characterizing acoustic signatures of the equipment in operation. This data can support the development of safeguards by design and security by design measures for aqueous reprocessing facilities. Furthermore, this type of monitoring can aid in early detection and identification of removed materials indicating diversion, which is essential for initiating material recovery and actor identification. The results of this work include data from nine low-frequency acoustic sensors used to investigate potential acoustic characteristics of centrifugal contactors used in multi-stage processes. The results also discuss the correlation between the signatures and the operation of the contactor banks.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗

DOE OSTI2025

A Novel Manufacturing Process of Lightweight Automotive Seats: Integration of Additive Manufacturing and Reinforced Polymer Composite

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

A Novel Manufacturing Process of Lightweight Automotive Seats (Integration of Additive Manufacturing and Reinforced Polymer Composite)

Lightweight automotive seats offer multiple benefits to original equipment manufacturers in terms of cost savings from various aspects, including less material usage, more integrated processes, and compliance with Corporate Average Fuel Economy Standards. Original equipment manufacturers have been focusing on innovative ways to produce light weight automotive seats. The commercially available automotive seats are currently made of multiple metal components combined through welding and fasteners. The use of additive manufacturing and composite structures is particularly useful for light weighting the automotive components. Additive manufacturing (AM) offers multiple advantages over traditional manufacturing processes such as freedom of design thereby enabling complex structural geometries, mass customization and waste minimization, and control over the fiber alignment through deposition in a predetermined pattern. Combining metal inserts with polymer composites through a novel manufacturing process allows design of lightweight and high-performance materials for automotive components. However, fabricating these metal polymer composite structures through traditional manufacturing processes limits their mechanical properties due to limited design freedom, lack of control over fiber orientation in composite parts, and poor interfacial bonding between the constituent materials. It is essential to develop a novel manufacturing process to enable high throughput production of lightweight automotive seats using metal and polymer composites. As such it is important to design the automotive seat suitable for manufacturing via this process and perform mechanical characterization on various subcomponents of the seat to ensure that the design and performance requirements provided by the auto manufacturer are met. The aim of this project is to develop a novel manufacturing technique to produce lightweight automotive seat by combining AM with conventional manufacturing processes. The car seat back panel will be designed via topology optimization and numerical simulations to minimize the overall weight while ensuring it meets all the performance requirements. The optimization of the seat back structure will be based on computational stress analysis to maximize the stiffness and minimize the weight. Materials currently used by Ford Motor Company will be adopted for a few subcomponents while the in-house composite materials will be used for the rest of the seat back. The composite and metallic materials will be tested to determine their mechanical properties as these are necessary for simulations. A novel manufacturing process will be developed to integrate AM metal inserts with discontinuous reinforced composite through large scale additive manufacturing and compression overmolding processes. The developed manufacturing technique will be used to fabricated various subcomponents suitable for the seat back design and mechanically tested to determine their properties. The manufacturing of the lightweight seat back design through this process involves integrated AM metal inserts with the composite structure for recliner connection. The manufacturing of the entire seat back which is lightweight through the novel manufacturing process will be discussed. The performance of the designed seat back will be investigated through numerical simulations and shown to meet all the requirements provided by the auto manufacturer. The final goal of developing a novel manufacturing process for lightweight automotive seats is met through design optimization of seat back, manufacturing of subcomponents, mechanical characterization, and validation through numerical simulations. The routes to achieve the final goal of the project and the depth in which they were investigated changed throughout the project due to personnel changes and the COVID-19 pandemic. The project resulted in the development of a novel manufacturing process to integrate metal inserts with tailored polymer composite preforms through overmolding. Leveraging this proven manufacturing process, a lightweight seat back was designed through topology optimization and numerical simulations. The designed seat back uses AM metal inserts and compression overmolding of tailored polymer composite preforms obtained via large scale additive manufacturing. The metal polymer composite structures fabricated through this process exhibited enhancement in stiffness and improved ductility upon testing. Overall, the project provided an alternative design and manufacturing technique for automotive seat back that enables weight saving while meeting the safety and performance requirements.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Bench-scale Development of a Transformational Graphene Oxide-based Membrane Process for Post-combustion CO 2 Capture

Graphene-based materials, such as graphene and graphene oxide (GO), have been considered as next-generation membrane materials. GTI Energy and The State University of New York at Buffalo (UB) have been developing a transformational GO-based membrane process (designated as GO2) that integrates a high CO 2 /N 2 selectivity membrane (GO-1) and a high CO 2 flux membrane (GO-2) for post-combustion CO 2 capture. An innovative membrane structure, consisting of GO nanochannels intercalated by single-walled carbon nanotube (SWCNT), was developed. The membrane prepared on hollow fiber substrate showed CO 2 permeance as high as 1,300 GPU with CO 2 /N 2 selectivity >200. The membranes were successfully scaled up to effective area of 50-100 cm 2 . The 50-100 cm 2 membranes showed CO 2 /N 2 selectivity ≥200 and CO 2 permeance ≥1,000 GPU for the GO-1 type, and CO 2 /N 2 selectivity ≥20 and CO 2 permeance ≥2,500 GPU for the GO-2 type. The CO 2 capture performance of the GO-based membranes was tested using a simulated flue gas. The testing results indicate that the GO-based membranes are stable in the presence of flue gas contaminants. The GO-based membranes were then further scaled up to a surface area of 1,000 cm 2 . Good stability was achieved during an integrated testing with GO-1 and GO-2 membranes using simulated flue gas. A bench-scale system was designed, constructed, and tested at the National Carbon Capture Center (NCCC). Good stability was achieved during testing of a single-stage process with >10 shutdowns/startups at NCCC. During the integrated testing, the membranes showed good stability at 50°C and 57°C. 70-90% CO 2 removal efficiencies and ≥95% CO 2 purity were validated during the steady state operation at NCCC. Techno-economic analysis indicates the GO2 membrane-based process technology provides a reduction in both the levelized cost of electricity (LCOE) and cost of capture when compared to the reference B12B case presented in the Cost and Performance Baseline for Fossil Energy Plants Volume 1: Bituminous Coal and Natural Gas to Electricity study prepared by the National Energy Technology Laboratory (NETL), before considering any system optimization or improvement opportunities. The benefits are primarily driven by a reduction in the equipment costs of the CO 2 capture process vs. the solvent-based reference process in NETL Case B12B as well as a decrease in the base plant size.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2024

Interparticle Characterization of Mechanical Biomass Particle-Particle and Particle-Wall Interactions

The biomass materials industry faces significant challenges in managing material variability and its impact on storage and handling systems. Physical properties such as moisture content, particle size, and density fluctuate considerably, leading to operational issues like bridging and ratholing that disrupt material flow. These variations create a complex cascade effect throughout the process chain, affecting transportation, storage, and conversion processes. The economic consequences of this variability manifest in increased operational costs, maintenance requirements, and system downtime. Environmental factors further complicate the situation, as weather conditions and seasonal availability influence material properties and system performance. Engineers employ specialized equipment design, material characterization protocols, and pre-processing steps like size reduction and homogenization to address these challenges. A critical knowledge gap exists between continuous-level constitutive models and particle-scale behavior. This project developed a novel device to quantify interparticle mechanics between biomass particles, measuring friction and adhesion forces between particles and wall materials. The research focused on corn stover and southern pine forest residue, creating a comprehensive database of particle interactions. This breakthrough enables direct application in particle-based computational modeling, advancing the field's understanding of biomass handling characteristics and supporting the development of more reliable and efficient storage and handling systems. The project's outcomes contribute significantly to understanding biomass's mechanical and flow characteristics, particularly how variability at the particle level affects larger-scale handling operations. This knowledge is crucial for engineering feedstock supply systems that consistently meet quality and cost specifications for various conversion processes. The innovative experimental setup developed through this research represents a significant advancement in biomass characterization methodology. Providing precise measurements of particle-level interactions establishes a foundation for more accurate predictive modeling of bulk material behavior. This enhanced understanding of fundamental particle mechanics enables engineers to anticipate better and address handling challenges before they manifest in full-scale operations. This research opens new avenues for optimizing biomass handling systems through data-driven design approaches. The comprehensive database of particle interactions serves as a valuable resource for future research and development efforts, potentially leading to more efficient and cost-effective biomass processing solutions. This advancement in particle-level mechanics could revolutionize how biomass handling systems are designed and operated, contributing to more sustainable and reliable renewable energy production.

09 BIOMASS FUELS↗

DOE OSTI2025

Seismoacoustic Monitoring of Pyroprocessing Equipment

With the projected increase in world nuclear capacity comes the hurdle of spent nuclear fuel. Pyroprocessing is one method to process irradiated fuel by using high temperatures and electrochemical steps to separate radioactive components. High temperatures, high radiation levels, and equipment confined to a heavily shielded hot cell are a few of the challenges introduced regarding safeguards for pyroprocessing. The first stage of the process utilizes an element chopper to cut irradiated fuel into smaller pieces, offering the potential to identify equipment operation through seismoacoustic monitoring. Eleven seismic and infrasound sensors were deployed at various locations and distances near a pyroprocessing hot cell to evaluate signals emitted from the chopper. Signals were processed using short-time Fourier transforms and manually scanned to locate chopping events. Operator logs were then collected for a ground truth comparison. Results indicate that both infrasound and seismic signals offer the ability to accurately measure this stage of pyroprocessing, though seismic signals are more prominent. Sensor locations are also evaluated to determine where the signal is detectable. This type of monitoring offers a method to aid in safeguards and proliferation detection by validating a pyroprocessing facility’s schedule and identifying activity that does not align with records.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Informing Plant Asset Reliability and Availability Through AI-Driven Analysis of Operator Logs

The availability and reliability of nuclear power plant (NPP) structures, systems, and components (SSCs) are critical parameters for NPP safety. Tracking these parameters is necessary but costly and labor-intensive, requiring the collection and evaluation of SSC event data such as shutdowns, startups, and failures. To show how these events are needed for the parameters an example is given: one measure of reliability is based on the number of equipment failure events and the number of run hours (i.e., the time from a startup event to a shutdown event). Here, this work investigates using artificial intelligence (AI) to mine NPP operator log entry texts for SSC event data. Four AI approaches were explored for identifying these events, including natural language processing (NLP) methods, generative AI, generative AI combined with NLP, and topic modeling. A key challenge addressed with all four approaches is the brevity of operator log entries. Among these four a neural network–based NLP method was shown to be the most promising for this application, achieving F1 scores of 86.0% for shutdowns, 92.2% for startups, and 80.4% for failures on a subject-matter-expert-curated dataset from NPP operator logs, compared to a baseline of 66.6% for a random classifier. This shows that NLP methods can perform better than generative AI. Additionally, the NLP methods combined with generative AI were shown to perform better than generative AI alone. Generative AI was most successful at providing the background information for the NLP methods to use. This work demonstrates the potential to use AI to automate parameter collection from NPP operator log entries and other records.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Moving from Information Assurance to Functional Assurance with Engineered Controls

Cyber threats to operational technology demand more than traditional IT defenses—they require full-spectrum mission assurance. Cyber-Informed Engineering (CIE) is an approach that embeds engineered controls into system design to ensure critical functions remain safe and reliable, even under attack. Unlike conventional cybersecurity tools, engineered controls act directly on physical processes to prevent unacceptable outcomes such as equipment damage or mission failure. This session will outline the CIE framework and share examples of consequence-based design that deliver true resilience, not just fail-safe behaviors. Attendees will learn how to integrate these principles into the engineering lifecycle to support resilient-by-design architectures and inform emerging standards. This talk sets the stage for the panel discussion on advancing CIE across sectors as digital and physical systems converge.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Hydrogen from Carbonaceous Waste Material - Hydrogen Fuel Cells Prize Phase 2 Voucher: Cooperative Research and Development (Final Report)

NLR conducted a conceptual design study for scaling up biomass conversion technology from Green Fortress Engineering (GFE). GFE has proprietary technology where cellulosic biomass is thermally converted to a tar-free syngas. A ceramic membrane separation unit (MSU) previously developed with NLR can extract high-purity hydrogen from the syngas. The energy content of the retentate stream is sufficient to power the process with a gas-powered genset. Design details including mass and energy balances, process and instrumentation diagrams (P&ID), and major equipment schedules were delivered.

08 HYDROGEN↗

DOE OSTI2024

FARM supervisory capabilities for thermal energy storage

The FARM (Feasible Actuator Range Modifier) module is a component of the RAVEN-based FORCE framework for the analysis of Integrated Energy Systems (IES). FARM aids HERON in the solution of the power dispatch problem by evaluating feasible set-point signals to be issued to the control systems of the different IES unit components. Set-points need to satisfy limits on both production variables (i.e., the variables to be optimized such as the electrical power, etc.) and process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.). To enforce all these limits, a two-stage approach is adopted. First, the power dispatcher algorithm in HERON module estimates set-points that meet the constraints on the production variables, e.g., power levels and power ramp rate limits. These constraints are called explicit constraints. Then, if necessary, FARM adjusts these set-points to ensure the respect of the limits on the process variables of interest, given the knowledge of the system dynamics acquired through machine learning algorithms. These constraints are called implicit constraints. From this standpoint, FARM constitutes a bridge between the HERON power dispatcher that adopts a simplified description of the IES unit (low-resolution physics) and the HYBRID high-fidelity models (high-resolution physics). In this report, an overview of the major capabilities of the latest release of FARM is provided, along with a summary of the tool demonstration campaign conducted at the Dynamic Energy Technology and Integration Laboratory (DETAIL) facility. These results assess the performance of the control system architecture embedding FARM both as a Validator of the HERON power dispatcher and as a real time Supervisory control scheme. Additionally, the report outlines the areas that FARM might benefit from, along with proposed solutions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

Development of algorithms for augmenting and replacing conventional process control using reinforcement learning

Here, this work seeks to allow for the online operation and training of model-free reinforcement learning (RL) agents but limit the risk to system equipment and personnel. The parallel implementation of RL alongside more conventional process control (CPC) allows for the RL algorithm to learn from CPC. The past performance of both methods are assessed on a continuous basis allowing for a transition from CPC to RL and, if needed, transitioning back to CPC from RL. This allows for the RL algorithm to slowly and safely assume control of the process without significant degradation in control performance. It is shown that the RL can derive a near optimal policy even when coupled with a suboptimal CPC. It is also demonstrated that the coupled RL-CPC algorithm learns at a faster rate than traditional RL methods of exploration while the algorithm’s performance does not deteriorate below CPC, even when exposed to an unknown operating condition.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2026

Hydrogen applications in airport operations: a review using the Port Authority of New York and New Jersey as an illustrative airport system

Airports combine aircraft propulsion, ground operations, stationary power systems, and fuel logistics in ways that make emissions reduction technically and operationally complex. Existing studies often assess hydrogen applications in these areas separately, limiting understanding of the shared infrastructure, safety, and operational constraints that shape airport deployment. This review evaluates hydrogen across three airport-relevant operational domains: aviation propulsion, ground support equipment and vehicles, and stationary power systems. Within aviation propulsion, the review examines sustainable aviation fuel production and hydrogen-powered aircraft as two distinct hydrogen-relevant pathways. The Port Authority of New York and New Jersey is used as an illustrative airport system to relate the literature to a real operating context. Drawing on peer-reviewed studies, technical reports, demonstration projects, and public operational information, the review also includes screening-level calculations of hydrogen demand and potential CO 2 e reductions for selected applications. The findings show that hydrogen's role is highly application-specific. Near-term opportunities are strongest where hydrogen serves as a low-carbon process input, supports selected high-utilization ground equipment, or contributes to resilient stationary power-system configurations. Hydrogen-powered aircraft remain a longer-term option because storage, fueling infrastructure, certification, cost, and NO x management continue to constrain deployment. Across all domains, infrastructure readiness, fuel logistics, safety requirements, and leakage management emerge as recurring determinants of viability. Future research should focus on cross-domain infrastructure planning, comparative assessment of hydrogen against alternative pathways, improved treatment of leakage and non-CO 2 effects, and clearer safety and regulatory frameworks for airport deployment.

08 HYDROGEN↗

DOE OSTI2024

Special Nuclear Material Hold-up Measurement

Facilities that process special nuclear material (SNM) generally have a variety of equipment, shielding, and nearby radiation sources, which can pose challenges when performing nondestructive analysis (NDA) within the facility, as shown in Figure 1. In this figure, the left image features two individuals performing a holdup measurement of a large duct at a posting, utilizing a detector probe attached to a yardstick to reduce some aspect of the measurement uncertainty. Note that the distance to the holdup within the pipe from the posting cannot be accounted for. The right image similarly features several individuals guiding a holdup measurement of a ducting pipe several meters overhead, by attaching a detector probe to a long handle and lining that up with a posting on the outside of the pipe. SNM processing begets SNM holdup, and this difficulty with accurate NDA can result in unaccounted accumulation of SNM holdup within a process or area. Normal SNM processing operations can accumulate holdup within filters, pumps, pipes, ducts, other equipment, and facility support systems, as demonstrated by Figure 2. It is important for deactivation and decommissioning (D&D) gloveboxes and their ancillary equipment, material accountability, criticality safety, facility operations, waste management, radiation safety, and security to accurately characterize the location, composition, and quantity of this holdup to minimize these associated risks and potential diversion pathways. Current NDA techniques for assay of holdup are expensive, time consuming, and have high uncertainty.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Experimental Investigation of Plasma Processing for PIP-II SSR2 Cavities

Field emission and multipacting are critical factors that limit the achievable operational gradient of superconducting radio frequency (SRF) cavities. Plasma processing (PP) has been demonstrated as an effective in-situ technique for mitigating hydrocarbon-induced field emission and multipacting across a range of cavity geometries. In this work, we present the initial development and subsequent application of plasma processing for PIP-II type II spoke resonators (SSR2). The process was carried out at room temperature on an SSR2 cavity equipped with the CM-style high-power coupler and installed in the cryostat. Cavity performance was evaluated through comparative cold tests conducted before and after plasma processing.

Giaccone, Bianca [Fermilab] (ORCID:000000027275846↗

DOE OSTI2025

Part distortion monitoring in additive manufacturing using machining

In additive manufacturing, accumulation of residual stresses can result in severe part distortion from the desired preform shape. Current methods for in-situ part distortion monitoring in additive manufacturing typically require expensive sensors, or capital equipment, and require time-consuming post-processing to understand the shape deviation. This paper presents an in-situ method, in the context of hybrid manufacturing, for part distortion detection using machining of additively manufactured parts. As a surrogate, three test artifacts were used to represent different distorted geometries. The tool axis positions from the machine tool controller and the cutting power were monitored during a facing operation. Cutting power data was used to detect the tool entry and exit in the workpiece using a novel approach with power standard deviation metric. The workpiece geometry and distorted configuration was subsequently predicted for positional and rotational deviations to within 2 mm accuracy using synchronized tool position data with cutting power. The proposed method can be used in a hybrid (additive and subtractive) machine tool to periodically check part distortion in the additive build. The method is applicable for any additive process and is low-cost and computationally inexpensive.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Cytrics Repository Of Analysis Tools And Engineering Resources

Cybersecurity Testing for Resilient Industrial Control Systems (CyTRICS) is a DOE-funded project that works with vendors to evaluate the cybersecurity of equipment used in US critical infrastructure. In the process of testing systems, CyTRICS researchers often develop custom tools. The tools in this repository were developed during multiple CyTRICS tests to assist with the testing process. They help solve problems encountered by CyTRICS researchers and address uncommon testing subjects for which limited tooling is available. They are useful to other researchers working on similar systems and architectures.

Laird, SutterE↗

DOE OSTI2025

Enabling Industrial Re-Use of Large-Format Additive Manufacturing Molding and Tooling

Large-format additive manufacturing (LFAM) is an enabling manufacturing technology capable of producing large parts with highly complex geometries for a wide variety of applications, including automotive, infrastructure/construction, and aerospace mold and tooling. In the past decade, the LFAM industry has seen widespread use of bio-based, glass, and/or carbon fiber reinforced thermoplastic composites which, when printed, serve as a lower-cost alternative to metallic parts. One of the highest-volume materials utilized by the industry is carbon fiber (CF)-filled polycarbonate (PC), which in out-of-autoclave applications can achieve comparable mechanical performance to metal at a significantly lower cost. Previous work has shown that if this material is recovered at various points throughout the manufacturing process for both the lab and pilot scale, it can be mechanically recycled with minimal impacts on the functional performance and printability of the material while significantly reducing the feedstock costs. End-of-life (EOL) CF-PC components were processed through industrial shredding, melt compounding, and LFAM equipment, followed by evaluation of the second-life material properties. Experimental assessments included quantitative analysis of fiber length attrition, polymer molecular weight degradation using gel permeation chromatography (GPC), density changes via pycnometry, thermal performance using dynamic mechanical analysis (DMA), and mechanical performance (tensile properties) in both the X- and Z-directions. Results demonstrated a 24.6% reduction in average fiber length compared to virgin prints, accompanied by a 21% decrease in X-direction tensile strength and a 39% reduction in tensile modulus. Despite these reductions, Z-direction tensile modulus improved by 4%, density increased by 6.8%, and heat deflection temperature (HDT) under high stress retained over 97% of its original value. These findings underscore the potential for integrating mechanically recycled CF-PC into industrial LFAM applications while highlighting the need for technological innovations to mitigate fiber degradation and enhance material performance for broader adoption. This critical step toward circular material practices in LFAM offers a pathway to reducing feedstock costs and environmental impact while maintaining functional performance in industrial applications.

additive manufacturing↗

DOE OSTI2025

Package Testing Program Process for Validation and Verification of Software

The purpose of this document is to define the process for validation and verification (V&V) of software used to test the thermal data acquisition equipment in the Oak Ridge National Laboratory (ORNL) Package Testing Program (PTP) as part of the testing configuration(s). This process adheres to all applicable ORNL Standards Based Management System requirements and correlates with the PTP Quality Management System and the Software Quality Assurance Plan.

97 MATHEMATICS AND COMPUTING↗