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3,361 records · Page 65

Draft ASME Code Case to qualify L-PBF 316H material for Section III, Division 5 applications

This report documents the AMMT program’s development and submission of a draft ASME Code Case to qualify Laser Powder Bed Fusion (L PBF) Type 316H stainless steel for Section III, Divi-sion 5 Class A and SM high temperature nuclear applications. It summarizes the technical basis, the comprehensive high temperature mechanical test database assembled between 2023–2026, and the proposed code language and qualification framework submitted to ASME. The work was co-ordinated across multiple national laboratories and leverages prior ASME efforts to integrate additive manufacturing into the Boiler & Pressure Vessel Code. The body of the report describes the experimental database and analysis supporting the Code Case: tensile, creep, fatigue, creep fatigue, and thermal aging tests collected from multiple additive manufacturing sites, machine types, and powder lots, with material processed by a solution anneal heat treatment. The dataset — including both full size and subsized specimens and tests oriented parallel and perpendicular to build direction — shows limited tensile anisotropy, tensile properties comparable to wrought 316H, creep strength within the scatter of wrought material, but markedly reduced creep ductility above about 650 °C associated with rapid σ phase formation in L PBF microstructures. The draft Code Case itself prescribes a staged qualification model (manufacturing process qualification, component qualification, and per build witness testing), treats L PBF components as equivalent to Type 316 weld metal for design and inspection, and requires mechanical, chemical, and metallographic controls tied to ASTM/ISO 52946. Key acceptance criteria include tensile tests within a 90% prediction interval of the AMMT dataset, a creep fatigue screening test adapted from ASME Section III, Division 5, Subsection HB, HBB 2800 but with the cycle acceptance reduced to 100 for L PBF material, and double volumetric inspection of production components. The report concludes that the present data support treating L PBF 316H as analogous to conventional fusion weld metal for Division 5 design and inspection, while highlighting important caveats: the σ phase driven loss of creep ductility above ~650 °C, preliminary indications of enhanced creep fatigue sensitivity in some lots, and remaining gaps in long term aging and additional cyclic testing. Recommended next actions include completing outstanding cyclic and long duration creep/aging tests on the solution annealed condition, supporting inclusion of the 316H chemistry and heat treatment in ASTM/ISO 52946, and continuing engagement with ASME and NRC during balloting and review to enable industry adoption.

Messner, Mark C. (ORCID:0000000200404385)

Integrated Process-Structure-Property Simulations for Additive Manufacturing Using the Open-Source Materialite Package

The microstructure and properties of additively manufactured (AM) metals are strongly dependent on process conditions. Therefore, process-structure-property (PSP) simulations are a useful tool for exploring process parameter space, studying process variations, and quantifying uncertainty in material properties. However, integrating process-structure and structure-property simulations often involves connecting multiple software packages. Each package may use unique data structures and require substantial domain knowledge. This presentation demonstrates PSP simulation capabilities of Materialite, an open-source package developed at NASA Langley Research Center. Materialite simplifies model linkages by using a common data structure and model interface, enabling straightforward simulation across a PSP model chain. Physics-based models, including kinetic Monte Carlo and crystal plasticity, are implemented within the package. The model interface is also intended to simplify implementation of new models and enable integration with external simulation tools. Example use cases include uncertainty quantification with PSP models and GPU-accelerated powder bed fusion AM process models.

additive manufacturing

Optimizing Renewable Ammonia Production for a Sustainable Fertilizer Supply Chain Transition

Local renewable ammonia production using electrolytic hydrogen is an emerging approach to alleviate emissions attributed to synthetic nitrogen fertilizer production while also insulating against fluctuations in fertilizer prices and mitigating transportation costs and emissions. However, replacing ammonia currently produced using fossil fuels will not be immediate. To this end, we develop a supply chain transition model, which first optimizes the design and hourly operation of new renewable ammonia facilities to minimize production costs and then optimizes the annual installation timing, production scale, and location of these new renewable facilities along with ammonia transportation to meet county resolution demands. The objective is to augment and eventually replace conventional ammonia market imports in an economically competitive manner. We performed a case study for Minnesota's ammonia supply chain and found that a full transition to in-state renewable production by 2032 is optimal. This is incentivized by the U.S. federal government's clean hydrogen production credits. This transition results in 99 % reduction in carbon intensity along with stable supply costs below $475 per metric tonne. New renewable production facilities are an order of magnitude smaller than existing conventional plants. They use both wind and solar resources and operate dynamically to minimize expensive battery and hydrogen storage capacities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Deep Learning and Photogrammetric Reconstruction for Automated Crack Detection and Dimensional Measurement in Mining Operations

Surface crack detection and dimensional measurement at active mining sites present significant safety and operational challenges. Manual inspection methods are labor-intensive, spatially incomplete, and expose personnel to hazardous environments, while existing automated approaches have been developed primarily for concrete civil infrastructure and have not been validated on the complex, variable surfaces characteristic of mining environments. This dissertation presents an automated pipeline that integrates deep learning semantic segmentation with Structure-from-Motion photogrammetry to detect surface cracks and measure their aperture, length, and vertical displacement from standard RGB imagery acquired during routine Uncrewed Aerial Vehicle (UAV) survey operations, without requiring additional sensor hardware or manual measurement. The pipeline combines a U-Net architecture with an EfficientNet-B0 encoder, pretrained on the SDNET2018 concrete crack dataset and fine-tuned on a mining-specific dataset spanning laboratory concrete specimens, coal refuse impoundment embankments, and post-blast limestone quarry benches. Photogrammetric reconstruction is performed using COLMAP Structure-from-Motion and Multi-View Stereo, with crack segmentation masks projected into the reconstructed point cloud to enable three-dimensional vertical displacement measurement through local plane fitting and bimodal surface detection. The pipeline was validated across 36 controlled laboratory specimens at three imaging distances and four vertical displacement levels, achieving aperture measurement RMSE of 0.047 cm and R² of 0.954, and vertical displacement RMSE of 0.140 cm and R² of 0.966, against independent caliper measurements. Field application at a coal refuse impoundment in southwestern Pennsylvania detected 71 crack components across the embankment crest, with a dominant longitudinal crack exhibiting aperture values reaching 28 cm and a 95th percentile vertical displacement of 35.53 cm, consistent in magnitude and spatial distribution with simultaneously acquired LiDAR-derived estimates. Application across four post-blast limestone quarry bench datasets in California successfully characterized blast-induced fracture networks at ground sampling distances ranging from 0.59 to 1.23 cm/pixel, with detected crack geometries physically consistent with observable surface conditions at each site. The results demonstrate that deep learning-based crack detection and photogrammetric measurement can be integrated into routine UAV inspection workflows at mining sites, providing repeatable, scalable, and quantitative crack characterization across surface types, crack scales, and displacement magnitudes not previously addressed in the literature. The pipeline requires no dedicated surveying equipment beyond the UAV platforms already deployed at mine sites for survey and monitoring purposes, supporting practical adoption within existing operational workflows.

Crack detection, Dimensional Measurement

WINDSAT Free Flyer Using the Advanced TIROS-N Satellite

The results of this study show the feasibility of carrying a wind measuring lidar on an ATN-derivative free flying spacecraft. The overall configuration fits within the Shuttle bay and uses the same techniques for STS Launch as the proposed SAATN spacecraft. The lidar can be made light enough that the total weight of the satellite is well within the capability of the onboard propulsion system for transfers to a Sun synchronous orbit at 833 km attitude. The principal techniques for weight minimization are the use of the Perkin Elmer proprietary HIP process for the telescope, new packaging concepts for the laser and for the optics-laser interface, and the application of current technology to the signal processing hardware. Power minimization is achieved for the lidar primarily by use of a low pulse repetition frequency, i.e., 2pps, and again by the use of current processor technology. The power capability of the spacecraft is enhanced by increasing the ATN array size 25 percent, through the addition of two more solar array panels of the present size, and by limiting the range of Sun angles over which the spacecraft is operated. The same basic concept for the lidar as proposed in the Shuttle Windsat study is recommended here, but there are some changes in details to improve weight and power. No major technology break-throughs are required for the lidar, but some technology experiments are recommended for the laser subsystem to verify isotopic gas lifetime and performance, modulator life and weight, and for space qualification. Spacecraft changes are all natural modifications or growth to accommodate the payload. Overall, the proposed system provides substantial margin for the uncertainties for the future and for potential payload change, and also demonstrates the reasonableness of the Windsat Free Flyer concept.

Herbert M Gurk

Technology Readiness Assessment for Stirling Power Convertor

Stirling-based power conversion system could represent a critical enabling technology for future NASA missions, offering significantly enhanced power efficiency over traditional thermoelectric systems. To ensure the successful infusion of this technology into deep space and planetary surface missions, a rigorous evaluation of its maturity and associated risks is essential. The objective of this Technology Readiness Assessment (TRA) is to determine the current technology readiness level (TRL) of the Stirling power convertor and identify key technical risks and challenges associated with its maturation and potential infusion into a targeted flight system. The evaluation process will rigorously follow the NASA TRA procedure: (1) determining the requirements that underpin the design, function, and performance; (2) finding and listing all new technology elements (NTEs) and critical technology elements (CTEs); (3) identifying the level of integration assumed for the assessment; and (4) assessing the TRL for each NTE and CTE. The overall subassembly TRL will then be determined via a roll-up using the “weakest link” criterion, culminating in a final (5) assessment of risks to further progression of maturity. This paper will present the results of a comprehensive technology readiness assessment (TRA) conducted on the Stirling-based dynamic power conversion subassembly, excluding the radioisotope heat source. The paper will also describe a detailed breakdown of the TRL roll-up and a matrix of identified risks and recommended mitigation paths, along with identified key technical risks and challenges to achieve the required long-duration performance. Key Words: Radioisotope Power Conversion, Technology Readiness Assessment

Radioisotope Power Conversion

Data Analysis for GOPEX Image Frames

This article describes the data analysis based on the image frames received at the Solid State Imaging (SSI) camera of the Galileo Optical Experiment (GOPEX) demonstration conducted between December 9 and 16, 1992. Laser uplink was successfully established between the ground and the Galileo spacecraft during its second Earth-gravity-assist phase in December 1992. SSI camera frames were acquired which contained images of detected laser pulses transmitted from the Table Mountain Facility (TMF), Wrightwood, California, and the Starfire Optical Range (SOR), Albuquerque, New Mex/co. Laser pulse data were processed using standard image-processing techniques at the Multimission Image Processing Laboratory (MIPL) for preliminary pulse identification and to produce public re/ease images. Subsequent image analysis corrected for background noise to measure received pulse intensities. Data were plotted to obtain histograms on a dmly basis and were then compared with theoretical results derived from applicable weak-turbulence and strong-turbulence considerations. This article describes processing steps and compares the theories with the experimented results. Quantitative agreement was found in both turbulence regimes, and better agreement would have been found, given more received laser pulses. Future experiments should consider methods to reliably measure low-intensity pulses, and through experimented planning to geometrically locate pulse positions with greater certainty.

B M Levine

Battery/Ultracapacitor Evaluation for X-38 Crew Return Vehicle (CRV)

This presentation reported on the evaluation of the battery/ultracapacitor for the crew return vehicle (CRV). The CRV, as part of the international space station (ISS) planning, will be available to return to earth an ill or injured crew person, or if the ISS becomes unsafe, and the shuttle is not available. The requirements of the X-38 CRV are reviewed, and in light of the power requirements, the battery's required performance is reviewed. The ultracapacitor bank, and its test method is described. The test results are reviewed. A picture of the test set up is displayed showing the ultracapacitor bank and the NiMH battery. The presentation continues by reviewing tests of 5 available trade high power cell designs: (1) Hawker lead acid, (2) Bolder lead acid, (3) Energizer NiMH, (4) Sanyo NiCd, and (5) Energizer NiCd. The test methods and results are reviewed. There is also a review of the issues concerning lead acid batteries and conclusions.

Darcy, Eric

NASA Aerospace Flight Battery Systems Program Update

The objectives of NASA's Aerospace Flight Battery Systems Program is to: develop, maintain and provide tools for the validation and assessment of aerospace battery technologies; accelerate the readiness of technology advances and provide infusion paths for emerging technologies; provide NASA projects with the required database and validation guidelines for technology selection of hardware and processes relating to aerospace batteries; disseminate validation and assessment tools, quality assurance, reliability, and availability information to the NASA and aerospace battery communities; and ensure that safe, reliable batteries are available for NASA's future missions.

Manzo, Michelle

What to Do Until the Money Runs Out: A Refinement Framework for Cognitive Engineering in the Real World

A case study is presented to illustrate some of the problems of applying cognitive science to complex human-machine systems. Disregard for facts about human cognition often undermines the safety, reliability, and cost-effectiveness of complex systems. Yet single-point methods (for example, better user-interface design), whether rooted in computer science or in experimental psychology, fall far short of addressing systems-level problems in a timely way using realistic resources. A model-based methodology is proposed for organizing and prioritizing the cognitive engineering effort, focusing appropriate expertise on major problems first, then moving to more sophisticated refinements if time and resources permit. This case study is based on a collaborative effort between the Human Factors Division at NASA-Ames and the Spaceborne Imaging Radar SIR-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) Project at the Jet Propulsion Laboratory (JPL), California institute of Technology. The first SIR-C/X-SAR Shuttle mission flew successfully in April, 1994. A series of such missions is planned to provide radar data to study Earth's ecosystems, climatic and geological processes, hydrologic cycle, and ocean circulation. In addition to JPL and NASA personnel, the SIR-C/X-SAR operations team included Scientists and engineers from the German and Italian space agencies.

Shafto, Michael G.

Vidyut3d: A Gpu Accelerated Fluid Solver for Non-Equilibrium Plasmas on Adaptive Grids

We present the numerical methods, programming methodology, verification, and performance assessment of a non-equilibrium plasma fluid solver that can effectively utilize current and upcoming central processing and graphics processing unit (CPU+GPU) architectures, in this work. Our plasma fluid model solves the coupled conservation equations for species transport, electrostatic Poisson and electron temperature on adaptive Cartesian grids. Our solver is written using performance portable adaptive-grid/particle management library, AMReX, and is portable over widely available vendor specific GPU architectures. We present verification of our solver using method of manufactured solutions that indicate formal second order accuracy with central diffusion and fifth-order weighted-essentially-non-oscillatory (WENO) advection scheme. We also verify our solver with published literature on capacitive discharges and atmospheric pressure streamer propagation. We demonstrate the use of our solver on two 3D simulation cases: an atmospheric streamer propagation in Ar-H2 mixtures and a low pressure twin electrode radio frequency reactor. Our performance studies on three different CPU+GPU architectures indicate approximately 150-400X speed-up using AMD and NVIDIA GPUs per time step compared to a single CPU core for a 4 million cell simulation with 15 species.

Sitaraman, Hariswaran

Design aspects in small aircraft gas turbine fuel injectors

The causes of fuel injector spray deterioration and the effects of this deterioration on engine durability and performance are discussed. Small aircraft gas turbine fuel injectors present special design challenges due to low fuel flow rates involved and the physical size limitations. The principal fuel injector performance requirements are discussed in relation to their effect on the hydraulic, aerodynamic, and thermal design of aerating fuel injectors.

K Mccaldon

Solvent-Mediated Control of Nanocellulose Dispersion: An Integrated Computational and Experimental Investigation

Fibrillated cellulose derived from forestry feedstocks represents a renewable and high-strength materials platform for circular bioeconomies. However, its practical implementation is hindered by the irreversible aggregation of nanocellulose architectures, including cellulose nanofibers (CNFs). Solvent-based dispersion offers a simple and practical route to prevent CNF aggregation. Here, in this work, we integrate classical and enhanced sampling molecular dynamics (MD) simulations with experimental suspension rheology and atomic force microscopy (AFM) to elucidate how solvent environments tune CNF–CNF interactions and dispersion stability. CNF–CNF contact free energies computed from MD simulations reveal reduced aggregation in acetone/water, γ-valerolactone (GVL)/water, and tetrahydrofuran (THF)/water and pure acetone compared with pure water, reflecting stronger CNF-solvent relative to inter-CNF interactions. Correspondingly, CNF-solvent suspensions in these solvent systems exhibit stronger inter-fibril network structures and enhanced recovery compared to water, indicating improved CNF-solvent affinity. Liquid cell AFM imaging in acetone–water mixtures and in pure acetone further confirm the presence of well-dispersed CNFs. By combining multiscale computation with targeted experiments, this study establishes a rational framework for solvent design to achieve stable nanocellulose dispersions for high-strength biobased materials and efficient bioenergy conversion.

cellulose

Revolutionizing thermal Management in Next-Generation AI data centers: Challenges and breakthrough innovations

Data centers (DCs) serve as critical infrastructure for powering the growth and evolution of AI. Next-generation AI DCs present unique challenges in thermal management driven by unprecedented computational demands. This paper provides a comprehensive summary of key stakeholder perspectives on technology gaps, infrastructure requirements, test bed needs, emerging opportunities, and preliminary solutions related to thermal management for AI DCs. It establishes six strategic pillars of thermal management for next generation AI DC: reliability, deployability, efficiency, resilience, measurability, and valorization. The discussion spans a range of critical topics, including advanced cooling technologies, thermal strategies for emerging modular and edge DCs, system-level optimization and control frameworks, infrastructure planning and grid integration designs, benchmarking approaches, and pathways for waste heat recovery and reuse. The proposed research, development, and demonstration efforts are aimed at accelerating the deployment of AI DCs while ensuring energy efficiency, reliability, safety, and regulatory compliance.

Wang, Pengtao [ORNL] (ORCID:0000000214713429)

Quantum Circuits for the Preparation of Spin Eigenfunctions on Quantum Computers

The application of quantum algorithms to the study of many-particle quantum systems requires the ability to prepare wave functions that are relevant in the behavior of the system under study. Hamiltonian symmetries are important instruments used to classify relevant many-particle wave functions and to improve the efficiency of numerical simulations. In this work, quantum circuits for the exact and approximate preparation of total spin eigenfunctions on quantum computers are presented. Two different strategies are discussed and compared: exact recursive construction of total spin eigenfunctions based on the addition theorem of angular momentum, and heuristic approximation of total spin eigenfunctions based on the variational optimization of a suitable cost function. The construction of these quantum circuits is illustrated in detail, and the preparation of total spin eigenfunctions is demonstrated on IBM quantum devices, focusing on three- and five-spin systems on graphs with triangle connectivity.

97 MATHEMATICS AND COMPUTING

Process-level cost analysis of hybrid manufacturing pathways for aerospace structural components

Hybrid manufacturing is a promising route for producing complex aerospace components, yet systematic cost benchmarking across multiple additive-subtractive pathways remains limited. This study presents a comprehensive process-based cost analysis of seven hybrid manufacturing routes, including laser powder bed fusion (L-PBF), powder- and wire-directed energy deposition (DED), wire arc additive manufacturing (WAAM), additive friction stir deposition (AFSD), metal binder jetting (MBJ), and agility forging, followed by scanning and finish machining. Parametric cost models incorporating direct material, labor, and energy costs were developed. L-PBF results are discussed in detail for a pickle fork component and directly compared with commercial pricing. Across all hybrid routes, labor emerged as the dominant cost driver, contributing more than 70% of total manufacturing cost in some cases. AFSD exhibited the lowest cost for aluminum components, with MBJ being its 316 L stainless steel counterpart, after accounting for geometric scaling. Benchmarking against industrial quotes suggests that hybrid manufacturing can achieve cost levels comparable to those of commercial services, although labor-intensive processes exhibit greater deviation. The analysis highlights automation of material handling, setup, and supervision as key opportunities for improving economic competitiveness. Overall, the proposed framework provides a quantitative basis for evaluating and optimizing hybrid manufacturing pathways for aerospace applications.

Baruah, Sweta [ORNL] (ORCID:0009000174256207)

Air-Broadened Line Shapes in the 2n3 R Branch of 12ch4 Between 6014 and 6100 cm-1

Complete and accurate information on line shape parameters of 2?3 methane transitions for air broadening as a function of temperature is critical not only for the correct interpretation of the observed atmospheric spectra but also for the development of a reliable theoretical model. For this reason, we obtained a series of high-resolution, high S/N spectra of high-purity 12CH4 and 12CH4 broadened with dry air at temperatures in the 130 to 295 K range using the Bruker IFS 125HR Fourier transform spectrometer at JPL. Two absorption cells were used in the experiment, a White cell with path length of 13 m for room temperature spectra and a 21 m Herriott cella for cold sample spectra. The 15 spectra used in the analysis consisted of 3 low pressure (0.26 to 2.57 Torr) spectra with pure 12CH4 and 12 air-broadened spectra with total sample pressures of 79-805 Torr and volume mixing ratios of methane between 0.23 and 1%. A multispectrum least-squares fitting techniqueb was employed to fit all 15 spectra simultaneously. Preliminary results for select R(J) manifolds will be presented.

V Malathy Devi

Thermochemically-Closed Sonic-Flow Inversion for Enthalpy and Temperature in Multispecies Arc-Jet Flows

A thermochemically-closed sonic-flow inversion framework (TSIF) is developed to infer bulk enthalpy and total temperature upstream of a choked nozzle in arc-jet flows. The formulation recasts a pressure-rise total enthalpy quantification technique as an inverse problem in characteristic-velocity c * space using measured mass flow rate, upstream total pressure, gas composition, and nozzle throat geometry as inputs. Unlike calorimetric energy-balance approaches or optical diagnostics, the method relies primarily on routinely measured facility quantities combined with explicit thermochemical closure. Thermochemical states are obtained using NASA’s open-source Chemical Equilibrium with Applications (CEA) code, enabling construction of a chemistry-consistent relation between characteristic velocity, total enthalpy, and total temperature under equilibrium or frozen assumptions. A discharge coefficient is self-calibrated using cold-flow (arc-off) operation data and applied to hot-flow (arc-on) measurements, enabling upstream losses to be accounted for without empirical correlations. The framework is applied to air, N 2 , and CO 2 –N 2 arc-jet flows and demonstrates expected trends for the inferred thermochemical states as function of arc power, specific energy input, mass-flow, heater configuration, and test gas. In the air limit, under equilibrium assumptions, the method recovers the classical high-enthalpy asymptotic correlation of Winovich with a mean residual of 4.4%, demonstrating compatibility with established sonic-flow scaling, while extending applicability to arbitrary multi-species mixtures and non-equilibrium chemistry. The framework provides a mixture-flexible methodology for determining bulk thermochemical states in modern arc-jet environments using routine facility pressure, mass-flow, gas-composition, and nozzle-geometry information together with a cold-flow calibration.

stagnation heat flux