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DOE OSTI2024

Electron cyclotron emission detection of neoclassical tearing modes for control for ITER

Successful operation of ITER requires control of magnetic instabilities including neoclassical tearing modes (NTMs) that can degrade confinement and lead to disruption. Low latency detection by electron cyclotron emission (ECE) diagnostics has been demonstrated in a few current experiments. Using a synthetic diagnostic, we demonstrate low latency NTM detection for ITER with plasmas described by ITER IMAS database scenarios and with realistic limitations imposed on the instrumentation by these high temperature scenarios. 2/1 NTMs are detected 430 ms after magnetic island seeding and before island locking. The radiometer configuration was optimized using simulation, and the smallest detectable island size was explored. Island sizes of ∼3 cm are detectable at the 2/1 surface. The simulated signals incorporate recent physics models for island growth and rotation, which show early locking and continued island growth after locking and before disruption. This work determines limits for ITER ECE spatial resolution imposed by relativistic broadening of channels, which informs hardware design. Real-time detection is demonstrated in hardware that is required by ITER, including on an NI PXI-7853R FPGA system. Development of a synthetic diagnostic and details of the hardware will be discussed.

Cyclotron radiation↗

DOE OSTI2017

Molecular weight and uniformity define the mechanical performance of lignin-based carbon fiber

Lignin-based carbon fiber represents a renewable and low-cost alternative to petroleum-based carbon fiber. However, the poor mechanical performance of current lignin carbon fiber hinders its application. We hypothesized that the lower optimal mechanical performance is caused by the inherent heterogeneity of lignin. It is still unknown how the molecular weights (MWs) and lignin uniformity will impact the performance of lignin carbon fiber. We thereby addressed this hypothesis by fractionating lignin into fractions with different MWs and polydispersity indices (PDIs). An enzyme–mediator-based method and a dialysis method were developed to derive lignin fractions with increased MW and decreased PDI. Lignin fractions were electro-spun into fibers after blending with polyacrylonitrile (PAN) at 1 : 1 (w/w) ratio. The fractionation in general improved the spinnability of lignin to allow us to obtain finer lignin-based carbon fibers. The elastic modulus of lignin carbon fibers, as measured by nanoindentation, was increased as the lignin MW increased and as PDI decreased. The scatter plot and linear regression revealed very good correlation between the elastic modulus and PDI, as well as certain correlation between the elastic modulus and MW. XRD and Raman spectroscopy revealed that the crystallite size and the content of the pre-graphitic turbostratic carbon increased with higher lignin MW and lower PDI, revealing the mechanism of the improvement in carbon fiber mechanical performance. Finally, this study elucidated the impacts of lignin MW and uniformity on the mechanical properties of carbon fiber, and could thus guide the development of lignin processing technologies for quality lignin-based carbon fiber.

09 BIOMASS FUELS↗

DOE OSTI2019

Transfer of autocollimator calibration for use with scanning gantry profilometers for accurate determination of surface slope and curvature of state-of-the-art x-ray mirrors

X-ray optics, desired for beamlines at free-electron-laser and diffraction-limited-storage-ring x-ray light sources, must have almost perfect surfaces, capable of delivering light to experiments without significant degradation of brightness and coherence. To accurately characterize such optics at an optical metrology lab, two basic types of surface slope profilometers are used: The long trace profilers (LTPs) and nanometer optical measuring (NOM) like angular deflectometers, based on electronic autocollimator (AC) ELCOMAT-3000. The inherent systematic errors of the instrument's optical sensors set the principle limit to their measuring performance. Where autocollimator of a NOM-like profiler may be calibrated at a unique dedicated facility, this is for a particular configuration of distance, aperture size, and angular range that does not always match the exact use in a scanning measurement with the profiler. Here we discuss the developed methodology, experimental set-up, and numerical methods of transferring the calibration of one reference AC to the scanning AC of the Optical Surface Measuring System (OSMS), recently brought to operation at the ALS Xray Optics Laboratory. We show that precision calibration of the OSMS performed in three steps, allows us to provide high confidence and accuracy low-spatial-frequency metrology and not â€print into' measurements the inherent systematic error of tool in use. Here, with the examples of the OSMS measurements with a state-of-The-Art x-ray aspherical mirror, available from one of the most advanced vendors of X-ray optics, we demonstrate the high efficacy of the developed calibration procedure. The results of our work are important for obtaining high reliability data, needed for sophisticated numerical simulations of beamline performance and optimization of beamline usage of the optics. This work was supported by the U. S. Department of Energy under contract number DE-AC02-05CH11231.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

An automated and portable method for selecting an optimal GPU frequency

Power consumption poses a significant challenge in current and emerging graphics processing unit (GPU) enabled high-performance computing systems. In modern GPUs, dynamic voltage frequency scaling (DVFS) appears to be a reliable control to regulate power consumption and performance. However, the DVFS design space is large - hence, brute-force approaches are infeasible to select the optimal frequency. Furthermore, no single frequency can be universally optimal for applications with varying computational intensities. Thus, the application's complexity and the availability of a wide range of frequency settings are a challenge in selecting the optimal frequency configuration for a given GPU workload. To that end, this paper proposes a systematic approach that consists of three steps. The feature characterization study identifies the fine-grain GPU utilization metrics that influence the power consumption and execution time of a given workload. To understand the performance, power, and energy consumption behaviors of a workload across GPU's DVFS design space, we derived analytical power and performance models using the identified fine-grain features. Here, it is shown that the same set of GPU utilization metrics can estimate both the power consumption and execution time while being agnostic of changes to frequency and input sizes. Applying a power control with the single objective of reducing power may cause performance degradation, leading to more energy consumption. A multi-objective approach is proposed to select the optimal GPU DVFS configuration for a workload that reduces power consumption with negligible degradation in performance. The evaluation was conducted using SPEC ACCEL benchmarks and three real applications - NAMD LAMMPS, and LSTM on NVIDIA GV100, GA100, and AMD MI210 GPUs. On average, real applications showed 29.6% energy savings with a performance loss of 5.2% on GA100 and 22.6% energy savings with a performance loss of 4.7% on GV100. Moreover, the proposed models are portable to real applications, GPU architectures, and vendors, and require metric collection at only the default frequency rather than all supported DVFS configurations. Additionally, we conducted a comparison between our models and the GPU assembly instructions (PTX)-based static models. The results revealed a significant reduction in the average error rates, with a decrease from 19.7% to 3.1% for power models and from 29.4% to 5.2% for performance models.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Inverse methods for design of soft materials

Functional soft materials, comprising colloidal and molecular building blocks that self-organize into complex structures as a result of their tunable interactions, enable a wide array of technological applications. Inverse methods provide a systematic means for navigating their inherently high-dimensional design spaces to create materials with targeted properties. Furthermore, while multiple physically motivated inverse strategies have been successfully implemented in silico, their translation to guiding experimental materials discovery has thus far been limited to a handful of proof-of-concept studies. In this perspective, we discuss recent advances in inverse methods for design of soft materials that address two challenges: (1) methodological limitations that prevent such approaches from satisfying design constraints and (2) computational challenges that limit the size and complexity of systems that can be addressed. Strategies that leverage machine learning have proven particularly effective, including methods to discover order parameters that characterize complex structural motifs and schemes to efficiently compute macroscopic properties from the underlying structure. We also highlight promising opportunities to improve the experimental realizability of materials designed computationally, including discovery of materials with functionality at multiple thermodynamic states, design of externally directed assembly protocols that are simple to implement in experiments, and strategies to improve the accuracy and computational efficiency of experimentally relevant models.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Enhanced and stabilized hydrogen production from methanol by ultrasmall Ni nanoclusters immobilized on defect-rich h-BN nanosheets

Employing liquid organic hydrogen carriers (LOHCs) to transport hydrogen to where it can be utilized relies on methods of efficient chemical dehydrogenation to access this fuel. Therefore, developing effective strategies to optimize the catalytic performance of cheap transition metal-based catalysts in terms of activity and stability for dehydrogenation of LOHCs is a critical challenge. Here, we report the design and synthesis of ultrasmall nickel nanoclusters (∼1.5 nm) deposited on defect-rich boron nitride (BN) nanosheet (Ni/BN) catalysts with higher methanol dehydrogenation activity and selectivity, and greater stability than that of some other transition-metal based catalysts. The interface of the two-dimensional (2D) BN with the metal nanoparticles plays a strong role both in guiding the nucleation and growth of the catalytically active ultrasmall Ni nanoclusters, and further in stabilizing these nanoscale Ni catalysts against poisoning by interactions with the BN substrate. We provide detailed spectroscopy characterizations and density functional theory (DFT) calculations to reveal the origin of the high productivity, high selectivity, and high durability exhibited with the Ni/BN nanocatalyst and elucidate its correlation with nanocluster size and support–nanocluster interactions. This study provides insight into the role that the support material can have both regarding the size control of nanoclusters through immobilization during the nanocluster formation and also during the active catalytic process; this twofold set of insights is significant in advancing the understanding the bottom-up design of high-performance, durable catalytic systems for various catalysis needs.

08 HYDROGEN↗

NASA NTRS1978

Theory and applications for optimization of every part of a photovoltaic system

A general method is presented for quantitatively optimizing the design of every part and fabrication step of an entire photovoltaic system, based on the criterion of minimum cost/Watt for the system output power. It is shown that no element or process step can be optimized properly by considering only its own cost and performance. Moreover, a fractional performance loss at any fabrication step within the cell or array produces the same fractional increase in the cost/Watt of the entire array, but not of the full system. One general equation is found to be capable of optimizing all parts of a system, although the cell and array steps are basically different from the power-handling elements. Applications of this analysis are given to show (1) when Si wafers should be cut to increase their packing fraction; and (2) what the optimum dimensions for solar cell metallizations are. The optimum shadow fraction of the fine grid is shown to be independent of metal cost and resistivity as well as cell size. The optimum thicknesses of both the fine grid and the bus bar are substantially greater than the values in general use, and the total array cost has a major effect on these values. By analogy, this analysis is adaptable to other solar energy systems.

Redfield, D.↗

DOE OSTI2023

Gold Nanoparticles AuNP Decorated on Fused Graphene-like Materials for Application in a Hydrogen Generation

The search for a sustainable, alternative fuel source to replace fossil fuels has led to an increased interest in hydrogen fuel. This combustible gas is not only clean-burning but can readily be produced via the hydrolysis of sodium borohydride. The main drawback of this reaction is that the reaction occurs relatively slowly and requires a catalyst to improve efficiency. This study explored a novel composite material made by combining gold nanoparticles and fused graphene-like materials (AuFGLM) as a catalyst for generating hydrogen via sodium borohydride. The novel fused graphene-like material (FGLM) was made with a sustainable dextrose solution and by using a pressure-processing method. Imaging techniques showed that FGLM appears to be an effective support template for nanoparticles. Transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) and Raman spectroscopy were used to characterize and determine the size, shape, and structure of nanoparticles and composites. The TEM study characterized the fused carbon backbone as it began to take on a rounder shape. The TEM images also revealed that the average diameter of the gold nanoparticle was roughly 23 nm. The FTIR study confirmed O-H, C-C, and C=O as functional groups in the materials. The EDS analysis showed that the composite contained approximately 6.3% gold by weight. The crystal structures of FGLM and AuFGLM were identified via P-XRD analysis. Various reaction conditions were used to test the catalytic ability of AuFGLM, including various solution pHs, temperatures, and doses of NaBH 4 . It was observed that optimal reaction conditions included high temperature, an acidic solution pH, and a higher dose of NaBH 4 . The activation energy of the reaction was determined to be 45.5 kJ mol -1 , and it was found that the catalyst could be used multiple times in a row with an increased volume of hydrogen produced in ensuing trials. The activation energy of this novel catalyst is competitive compared to similar catalysts and its ability to produce hydrogen over multiple uses makes the material an exciting choice for catalyzing the hydrolysis of NaBH 4 for use as a hydrogen fuel source.

08 HYDROGEN↗

DOE OSTI2024

Deriving cloud droplet number concentration from surface-based remote sensors with an emphasis on lidar measurements

Abstract. Given the importance of constraining cloud droplet number concentrations (Nd) in low-level clouds, we explore two methods for retrieving Nd from surface-based remote sensing that emphasize the information content in lidar measurements. Because Nd is the zeroth moment of the droplet size distribution (DSD), and all remote sensing approaches respond to DSD moments that are at least 2 orders of magnitude greater than the zeroth moment, deriving Nd from remote sensing measurements has significant uncertainty. At minimum, such algorithms require the extrapolation of information from two other measurements that respond to different moments of the DSD. Lidar, for instance, is sensitive to the second moment (cross-sectional area) of the DSD, while other measures from microwave sensors respond to higher-order moments. We develop methods using a simple lidar forward model that demonstrates that the depth to the maximum in lidar-attenuated backscatter (Rmax⁡) is strongly sensitive to Nd when some measure of the liquid water content vertical profile is given or assumed. Knowledge of Rmax⁡ to within 5 m can constrain Nd to within several tens of percent. However, operational lidar networks provide vertical resolutions of > 15 m, making a direct calculation of Nd from Rmax⁡ very uncertain. Therefore, we develop a Bayesian optimal estimation algorithm that brings additional information to the inversion such as lidar-derived extinction and radar reflectivity near the cloud top. This statistical approach provides reasonable characterizations of Nd and effective radius (re) to within approximately a factor of 2 and 30 %, respectively. By comparing surface-derived cloud properties with MODIS satellite and aircraft data collected during the MARCUS and CAPRICORN II campaigns, we demonstrate the utility of the methodology.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Hanford Direct Feed Low Activity Waste Program Throughput Optimization Through Modeling - 18587

The Direct Feed Low Activity Waste (DFLAW) program at Hanford allows for the early treatment of tank wastes years earlier than previously planned. Operational Research (OR) modeling is being used to provide invaluable insight into how complex and integrated processes will operate. The DFLAW OR models are used to help optimize the design and operation of the integrated system. The DFLAW OR models include the processes and real-life complexities involved in the day-to-day operation of the systems and equipment, and can predict key performance characteristics including throughput, mission timescale, equipment and labor utilization, lag storage and capacity requirements. The DFLAW OR models also have the in-built capability to simulate random events such as equipment failures. Adding random variability to models introduces a real-life element to model results. For example, OR modeling breakdown analysis of equipment failure and restoration times may inform specific improvements to a design and plant operation, including areas where the provision of spare (duty/standby) equipment would prove beneficial; the optimum number and capacity of lag storage tanks (for waste intermediate storage, reagents, etc.); operational issues, including scheduling constraints, labor resource constraints, effect of shift schedules (e.g. days only, extended shifts, 24/7),, maintenance strategies, including planned maintenance, equipment upgrades, on-hand spare part stockholding, etc. At Hanford, standalone OR models to date, have been used to help identify key operational issues and improve the design and operation of individual systems within the Tank Farms, Low Activity Waste Pretreatment System (LAWPS), Low Activity Waste (LAW) Vitrification and Effluent Management Facility (EMF) and Integrated Disposal Facility (IDF), logistics and infrastructure, 222-S laboratory [References 1 and 2] including: - Identification of critical spares including transfer pumps; - Underpin size and number of lag storage tanks to maintain continuous LAW feed to the LAW melters; - Underpin sample turnaround times at the 222-S Laboratory (e.g. feed prequalification and evaporator campaign samples) and determine how targets can be achieved without impacting waste feed delivery to LAWPS and the LAW Vitrification Facility; - Determine operational strategy required at IDF including shift schedules and sizes and the number of ILAW transporters that can support DFLAW throughput; - Identification of lag storage management strategies for glass formers, reagents, other consumables due to delivery distance and delays due to bad weather; and - Truck delivery badging needs to support 24/7 operation and management of shift in/out times required to reduce congestion. An Integrated DFLAW OR model has been developed and combines the standalone OR models such that integrated throughput and availability can be assessed from a program perspective. The Integrated OR model will provide a more detailed understanding of the interactions between Tank Farms, LAWPS, LAW VIT and IDF such that key bottleneck areas can be identified and ensure improvements are focused. Examples of future improvements that may be considered include identification of critical spare parts, required on-site maintenance capabilities, shift scheduling, and craft and labor availability. The methods, results and insights derived by DFLAW OR modeling efforts are expected to provide useful applications to other projects that involve combinations of mechanical handling, chemical processing, waste treatment/packaging or environmental remediation operations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2009

Exoplanet Community Report on Direct Infrared Imaging of Exoplanets

Direct infrared imaging and spectroscopy of exoplanets will allow for detailed characterization of the atmospheric constituents of more than 200 nearby Earth-like planets, more than is possible with any other method under consideration. A flagship mission based on larger passively cooled infrared telescopes and formation flying technologies would have the highest angular resolution of any concept under consideration. The 2008 Exoplanet Forum committee on Direct Infrared Imaging of Exoplanets recommends: (1) a vigorous technology program including component development, integrated testbeds, and end-to-end modeling in the areas of formation flying and mid-infrared nulling; (2) a probe-scale mission based on a passively cooled structurally connected interferometer to be started within the next two to five years, for exoplanetary system characterization that is not accessible from the ground, and which would provide transformative science and lay the engineering groundwork for the flagship mission with formation flying elements. Such a mission would enable a complete exozodiacal dust survey (<1 solar system zodi) in the habitable zone of all nearby stars. This information will allow for a more efficient strategy of spectral characterization of Earth-sized planets for the flagship missions, and also will allow for optimization of the search strategy of an astrometric mission if such a mission were delayed due to cost or technology reasons. (3) Both the flagship and probe missions should be pursued with international partners if possible. Fruitful collaboration with international partners on mission concepts and relevant technology should be continued. (4) Research and Analysis (R&A) should be supported for the development of preliminary science and mission designs. Ongoing efforts to characterize the the typical level of exozodiacal light around Sun-like stars with ground-based nulling technology should be continued.

Danchi, William C.↗

DOE OSTI2024

Precise relative magnitude measurement improves fracture characterization during hydraulic fracturing

SUMMARY Microseismic monitoring is an important technique to obtain detailed knowledge of in-situ fracture size and orientation during stimulation to maximize fluid flow throughout the rock volume and optimize production. Furthermore, considering that the frequency of earthquake magnitudes empirically follows a power law (i.e. Gutenberg–Richter), the accuracy of microseismic event magnitude distributions is potentially crucial for seismic risk management. In this study, we analyse microseismicity observed during four hydraulic fracture treatments of the legacy Cotton Valley experiment in 1997 at the Carthage gas field of East Texas, where fractures were activated at the base of the sand-shale Upper Cotton Valley formation. We perform waveform cross-correlation to detect similar event clusters, measure relative amplitude from aligned waveform pairs with a principal component analysis, then measure precise relative magnitudes. The new magnitudes significantly reduce the deviations between magnitude differences and relative amplitudes of event pairs. This subsequently reduces the magnitude differences between clusters located at different depths. Reduction in magnitude differences between clusters suggests that some attenuation-related biases could be effectively mitigated with relative magnitude measurements. The maximum likelihood method is applied to understand the magnitude frequency distributions and quantify the seismogenic index of the clusters. Statistical analyses with new magnitudes suggest that fractures that are more favourably oriented for shear failure have lower b-value and higher seismogenic index, suggesting higher potential for relatively larger earthquakes, rather than fractures subparallel to maximum horizontal principal stress orientation.

58 GEOSCIENCES↗

DOE OSTI2025

BAGELS for simultaneous polarization, orbit, and optics control in electron storage rings

We present a new method for minimizing the effects of radiative depolarization in electron storage rings by use of a minimal number of special vertical orbit bumps. The bumps can be used to minimize the effects of radiative depolarization while simultaneously maintaining other common benefits of vertical orbits, e.g., transverse coupling and vertical dispersion control. Because simultaneously optimizing the large number of vertical correctors in a ring is operationally infeasible, we use dimensionality reduction to define a minimal number of the most effective groups of vertical correctors that can be optimized during operation, motivating the name “Best Adjustment Groups for ELectron Spin” (BAGELS). The method is streamlined by using suitable “basis bumps” instead of all individual vertical correctors. We define three types of basis bumps for different purposes: (i) generates no delocalized transverse coupling nor delocalized vertical dispersion, (ii) generates no delocalized vertical dispersion, and (iii) generates no delocalized transverse coupling. BAGELS has been essential in the design of the Electron Storage Ring (ESR) of the Electron-Ion Collider (EIC) and will be beneficial for any polarized electron ring, including FCC-ee. HERA and LEP would have likely benefitted as well. We use BAGELS to significantly increase polarization in the 18 GeV EIC-ESR, beyond what is achievable with conventional methods; in the 1-IP lattice, we nearly double the asymptotic polarization, and in the 2-IP lattice, we more than triple the asymptotic polarization. We also use BAGELS to construct knobs that can be used for global coupling correction, and knobs that generate vertical emittance for beam size matching, all while having minimal impacts on the polarization and orbit/optics. Published by the American Physical Society 2025

43 PARTICLE ACCELERATORS↗

DOE OSTI2017

Pathways to Mesoporous Resin/Carbon Thin Films with Alternating Gyroid Morphology

Here, three-dimensional (3D) mesoporous thin films with sub-100 nm periodic lattices are of increasing interest as templates for a number of nanotechnology applications, yet are hard to achieve with conventional top-down fabrication methods. Block copolymer self-assembly derived mesoscale structures provide a toolbox for such 3D template formation. In this work, single (alternating) gyroidal and double gyroidal mesoporous thin-film structures are achieved via solvent vapor annealing assisted co-assembly of poly(isoprene- block -styrene- block -ethylene oxide) (PI- b -PS- b -PEO, ISO) and resorcinol/phenol formaldehyde resols. In particular, the alternating gyroid thin-film morphology is highly desirable for potential template backfilling processes as a result of the large pore volume fraction. In situ grazing-incidence small-angle X-ray scattering during solvent annealing is employed as a tool to elucidate and navigate the pathway complexity of the structure formation processes. The resulting network structures are resistant to high temperatures provided an inert atmosphere. The thin films have tunable hydrophilicity from pyrolysis at different temperatures, while pore sizes can be tailored by varying ISO molar mass. A transfer technique between substrates is demonstrated for alternating gyroidal mesoporous thin films, circumventing the need to re-optimize film formation protocols for different substrates. Increased conductivity after pyrolysis at high temperatures demonstrates that these gyroidal mesoporous resin/carbon thin films have potential as functional 3D templates for a number of nanomaterials applications.

3D templates↗

DOE OSTI2023

High-harmonic generation from artificially stacked 2D crystals

Here, we report a coherent layer-by-layer build-up of high-order harmonic generation (HHG) in artificially stacked transition metal dichalcogenides (TMDC) crystals in their various stacking configurations. In the experiments, millimeter-sized single crystalline monolayers are synthesized using the gold foil-exfoliation method, followed by artificially stacking on a transparent substrate. High-order harmonics up to the 19th order are generated by the interaction with a mid-infrared (MIR) driving laser. We find that the generation is sensitive to both the number of layers and their relative orientation. For AAAA stacking configuration, both odd- and even-orders exhibit a quadratic increase in intensity as a function of the number of layers, which is a signature of constructive interference of high-harmonic emission from successive layers. Particularly, we observe some deviations from this scaling at photon energies above the bandgap, which is explained by self-absorption effects. For AB and ABAB stacking, even-order harmonics remain below the detection level, consistent with the presence of inversion symmetry. Our study confirms our capability of producing nonperturbative high-order harmonics from stacked layered materials subjected to intense MIR fields without damaging samples. Our results have implications for optimizing solid-state HHG sources at the nanoscale and developing high-harmonics as an ultrafast probe of artificially stacked layered materials. Because the HHG process is a strong-field driven process, it has the potential to probe high-momentum and energy states in the bandstructure combined with atomic-scale sensitivity in real space, making it an attractive probe of novel material structures such as the Moiré pattern.

2D materials↗

DOE OSTI2025

Performance Evaluation of LPBF Manufactured 316H Components

This work represents the continuation of a benchmark study that includes modeling, fabrication and characterization as demonstration to support industry’s adoption of advanced manufacturing processes in a variety of structures. This comprehensive study investigated the feasibility of using additive manufacturing (AM) technologies, specifically Laser Powder Direct Energy Deposition (LP-DED) and Laser Powder Bed Fusion (LPBF), to produce complex nuclear microreactor components using 316H stainless steel. The research focused on manufacturing an expanded elbow pipe component with transitioning sections, which are traditionally difficult and costly to produce through conventional manufacturing methods. The overall study’s primary objectives are therefore demonstrating AM viability for nuclear applications, optimizing process parameters, developing comprehensive material characterization protocols, validating computational modeling approaches, and establishing manufacturing guidelines for complex geometries. Although the initial work included the phased approach of cubical, upscaled cylindrical components, it is to enable to obtain more knowledge for the printing of the expanded elbow structure. The project achieved significant progress in process development by successfully optimizing LP-DED parameters to achieve 99.16-99.97% relative density in 316H stainless steel components. Through systematic evaluation of sixteen cube samples with varied laser powers (400-700W) and scan speeds (600-900 mm/min), optimal processing windows were identified at 500-550W with 600-700 mm/min or 650-700W with 650-900 mm/min scan speeds. The DED manufactured 316H demonstrated mechanical properties comparable or superior to wrought materials, with Young's modulus ranging from 153-208 GPa and controlled microstructural characteristics including greater than 95% face-centered cubic (FCC) phases and engineered cellular structures with sizes between 3.23-6.17 µm.

36 MATERIALS SCIENCE↗

NASA NTRS2016

Average Cross-Sectional Area of DebriSat Fragments Using Volumetrically Constructed 3D Representations

Debris fragments from the hypervelocity impact testing of DebriSat are being collected and characterized for use in updating existing satellite breakup models. One of the key parameters utilized in these models is the ballistic coefficient of the fragment which is directly related to its area‐to‐mass ratio. However, since the attitude of fragments varies during their orbital lifetime, it is customary to use the average cross‐sectional area in the calculation of the area‐to‐mass ratio. The average cross‐sectional area is defined as the average of the projected surface areas perpendicular to the direction of motion and has been shown to be equal to one‐fourth of the total surface area of a convex object. Unfortunately, numerous fragments obtained from the DebriSat experiment show significant concavity (i.e., shadowing) and thus we have explored alternate methods for computing the average cross‐sectional area of the fragments. An imaging system based on the volumetric reconstruction of a 3D object from multiple 2D photographs of the object was developed for use in determining the size characteristic (i.e., characteristics length) of the DebriSat fragments. For each fragment, the imaging system generates N number of images from varied azimuth and elevation angles and processes them using a space‐carving algorithm to construct a 3D point cloud of the fragment. This paper describes two approaches for calculating the average cross‐sectional area of debris fragments based on the 3D imager. Approach A utilizes the constructed 3D object to generate equally distributed cross‐sectional area projections and then averages them to determine the average cross‐sectional area. Approach B utilizes a weighted average of the area of the 2D photographs to directly compute the average cross‐sectional area. A comparison of the accuracy and computational needs of each approach is described as well as preliminary results of an analysis to determine the "optimal" number of images needed for the 3D imager to accurately measure the average cross sectional area of objects with known dimensions.

Scruggs, T.↗

DOE OSTI2025

Investigating the relationship between simulation parameters and flow variables in simulating atmospheric gravity waves for wind energy applications

Wind farms, particularly offshore clusters, are becoming larger than ever before. Besides influencing the surface wind flow and the inflow for downstream wind farms, large wind farms can trigger atmospheric gravity waves in the inversion layer and the free atmosphere aloft. Wind-farm-induced gravity waves can cause adverse pressure gradients upstream of the wind farm, which contribute to the global blockage effect, and can induce favorable pressure gradients above and downstream of the wind farm that enhance wake recovery. Numerical modeling is a powerful means of studying these wind-farm-induced atmospheric gravity waves, but it comes with the challenge of handling spurious reflections of these waves from domain boundaries. Typically, approaches which employ radiation boundary conditions and forcing zones are used to avoid these reflections. However, the simulation setup of these approaches relies heavily on ad hoc processes. For instance, the widely used Rayleigh damping method requires ad hoc tuning to produce a setup that may only produce satisfactory results for a particular case. To provide more systematic guidance on setting up realistic simulations of atmospheric gravity waves, we conduct a large-eddy simulation (LES) study of flow over a 2D hill and through a wind farm canopy that explores the optimum domain size and damping layer setup depending on the fundamental parameters which determine the flow characteristics. In this work, we only consider linearly stratified conditions (i.e., no inversion layer), thereby focusing on internal gravity waves in the free atmosphere and their reflections from the domain boundaries. This type of flow is governed by a single Froude number, which dictates most of the internal wave properties, such as wavelength, amplitude, and direction. This, in turn, will dictate the optimum domain size and Rayleigh damping layer setup. We find the effective horizontal and vertical wavelengths (the representative wavelengths of the entire wave spectrum) to be the appropriate length scales to size the domain and damping layer thickness, and the optimal Rayleigh damping coefficient scales with the Brunt–Väisälä frequency. Considering Froude numbers seen in wind farm applications, we propose recommendations to limit the reflections to less than 10 % of the total upward-propagating wave energy. Typically, damping is done at the top boundary, but given the non-periodic lateral boundary conditions of practical wind farm simulation domains, we find that damping the inflow–outflow boundaries is of equal importance to damping the top boundary. The Brunt–Väisälä frequency-normalized damping coefficient should be between 1 and 10. The damping layer thickness should be at least one effective vertical wavelength; damping layers exceeding 1.5 times the vertical wavelength are found to be unnecessary. The domain length and height should accommodate at least one effective horizontal and vertical wavelength, respectively. Moreover, Rayleigh damping does not damp the waves completely, and the non-damped energy might accumulate over the simulation time.

17 WIND ENERGY↗