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At least 433 records · Page 24

Acoustic‐Modulated, Selective Particle Deposition for Muti‐Material Additive Manufacturing

Powder‐based additive manufacturing (AM) is an important technology in fabricating complex 3D products. In powder‐based AM, a powder deposition system plays a key role in determining the resolution, density, and properties of printed parts. An acoustic‐actuated particle deposition approach, which utilizes acoustic waves to actuate a glass nozzle, enables the deposition of particles in a cost‐effective way. However, the capability to programmably deposit different particles using acoustic waves has yet to be fully demonstrated. Herein, a selective particle deposition approach via acoustic modulation for muti‐material AM is demonstrated. Sequential and parallel depositions of two types of particles by modulating the signal inputs and resonant frequencies of piezo transducers are demonstrated. An AM process is demonstrated by integrating this acoustic‐actuated particle deposition approach with a heat‐curing mechanism. Several products from this system are produced as well. It is expected that this particle deposition approach can be used in a wide spectrum of applications, such as direct manufacturing of multi‐functional materials/devices.

36 MATERIALS SCIENCE↗

A state of the art Lambertson septum magnet of the RHIC beam injection system

The beam injection system of the Relativistic Heavy Ion Collider (RHIC) is the last section of the beam transfer line which transports the beam from the Alternating Gradient Synchrotron (AGS) to RHIC and comes under the acronym AtR (AGS to RHIC). The Lambertson septum magnet is one of the magnetic elements of the RHIC injection system. This paper presents results from the 2D and 3D electromagnetic design of the RHIC Lambertson septum magnet which has unique design features to minimize the magnetic field at the circulated beam region including the fringe field regions at the entrance and exit of the magnet.

43 PARTICLE ACCELERATORS↗

Magnetism in curved geometries

Curvature impacts physical properties across multiple length scales, ranging from the macroscopic scale, where the shape and size vary drastically with the curvature, to the nanoscale at interfaces and inhomogeneities in materials with structural, chemical, electronic, and magnetic short-range order. In quantum materials, where correlations, entanglement, and topology dominate, the curvature opens the path to novel characteristics and phenomena that have recently emerged and could have a dramatic impact on future fundamental and applied studies of materials. Particularly, magnetic systems hosting non-collinear and topological states and 3D magnetic nanostructures strongly benefit from treating curvature as a new design parameter to explore prospective applications in the magnetic field and stress sensing, microrobotics, and information processing and storage. This Perspective gives an overview of recent progress in synthesis, theory, and characterization studies and discusses future directions, challenges, and application potential of the harnessing curvature for 3D nanomagnetism.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Enhancements in Laser-Direct-Drive Nuclear Performance with Target Radius

Inertial confinement fusion is likely to require significant improvements in technology and design for large targets to implode at high driver energies. Here, to assess the potential for benefits, we report on nuclear performance as a function of target radius 𝑅 t in direct-drive cryogenic implosions as performed on the OMEGA laser. The neutron yield and areal density are found to increase as 𝑅 5.0±0.2 t and 𝑅 1.8±0.2 t , respectively, and exhibit a much stronger dependence on target radius than previous studies have assumed. As this paper demonstrates, these types of sensitivities should be expected when implosions are unstable, and have been degraded by a range of multidimensional effects in 3D. If the imperfections in a target and laser system are fixed in magnitude, it follows that larger implosions have higher relative quality, and approach criteria to ignite much more quickly than commonly appreciated.

inertial confinement fusion↗

Performance Evaluation of Heterogeneous GPU Programming Frameworks for Hemodynamic Simulations

Preparing for the deployment of large scientific and engineering codes on upcoming exascale systems with GPU-dense nodes is made challenging by the unprecedented diversity of device architectures and heterogeneous programming models. In this work, we evaluate the process of porting a massively parallel, fluid dynamics code written in CUDA to SYCL, HIP, and Kokkos with a range of backends, using a combination of automated tools and manual tuning. We use a proxy application along with a custom performance model to inform the results and identify additional optimization strategies. At scale performance of the programming model implementations are evaluated on pre-production GPU node architectures for Frontier and Aurora, as well as on current NVIDIA device-based systems Summit and Polaris. Real-world workloads representing 3D blood flow calculations in complex vasculature are assessed. Our analysis highlights critical trade-offs between code performance, portability, and development time.

Martin, Aristotle↗

Numerical Modeling & Optimization of the iProTech Pitching Inertial Pump (PIP) Wave Energy Converter (WEC) (CRADA Final Report)

This project represents a continuation of the collaboration between iProTech and NLR to simulate, optimize and design the iProTech Pitching Inertial Pump (PIP) device. The objectives of this TEAMER project are twofold: 1. Refining the physical characteristics of the existing iProTech PIP WEC-Sim model to enhance the model’s fidelity and include controllable components. Key model enhancements target the inclusion of Coulomb friction, the introduction of a controllable bypass valve, and the replacement of traditional check valves with advanced motorized ones. 2. Exploring traditional and advanced control algorithms. From traditional methods like latching control to cutting-edge reinforcement learning (RL) algorithms, the goal is to ensure the PIP device's adaptability and optimal performance across a range of ocean conditions. NLR is tasked with augmenting the WEC-Sim model and implementing the control algorithms, culminating in performance comparison analyses. iProTech will update their existing 3D models, advise on model improvements, and determine crucial system metrics. WEC-Sim, developed in MATLAB/SIMULINK with Simscape Multibody, is the main piece of software that will be used in this project. Coupled with the MATLAB RL Toolbox, it offers a robust platform for in-depth simulation and optimization of the iProTech PIP device. Building on previous work to explore the PIP design space and optimize its geometry, mass distribution, center of gravity and other key parameters, this project aims to refine iProTech’s existing numerical models and develop effective control algorithms that can seamlessly integrate into their future hardware testing campaigns.

16 TIDAL AND WAVE POWER↗

De-Risking Exploration for Geothermal Plays in Magmatic Environments Through Open-Source Tools: An Open-Source Python Framework for 2D and 3D Play Fairway Analysis

The De-Risking Exploration for Geothermal Plays in Magmatic Environments (DEEPEN) project seeks to accelerate superhot geothermal development by reducing exploration risk through advanced open-source modeling tools. This work presents a novel Python-based framework, geoPFA, for conducting 2D and 3D play fairway analysis (PFA) tailored to superhot geothermal systems. Building on previous methodologies, the framework integrates thermo-hydro-mechanical-chemical simulation outputs from TReactMech, resulting in improved representation of subsurface properties that are critical to superhot resource producibility. The workflow has been applied to the Nesjavellir field in Iceland, a candidate site for the third Iceland Deep Drilling Project's superhot production scenarios. This application demonstrates the value of modular, transparent, and extensible workflows for integrating geological, geophysical, and simulation-derived datasets in high-enthalpy environments. Preliminary results indicate favorable zones consistent with known hydrothermal activity and suggest possible upflow from the Hengill volcanic system. The geoPFA library is publicly available, offering a scalable and reproducible approach to geothermal exploration across varied geological contexts.

15 GEOTHERMAL ENERGY↗

Scalable GPS Data Logging To Support Advanced Fleet Analysis

This highlight details the key takeaways from a project that utilized NLR's Fleet Research, Energy Data, and Insights (FleetREDI) data analysis pipeline. National Laboratory of the Rockies researchers developed and demonstrated low-cost, open-source Arduino data loggers with 3D-printed cases that are compatible with global navigational systems and built with components available ubiquitously worldwide, enabling cost-effective collection and analysis of fleet operational data. Validated on an overseas transit bus fleet, NLR analysis showed that, with sufficient charging opportunities, 90% of observed duty cycles could be accomplished by electric buses with no modifications to operations.

33 ADVANCED PROPULSION SYSTEMS↗

Development of a Miniaturized Mobile Mapping System for In-Row, Under-Canopy Phenotyping

This paper focuses on the development of a miniaturized mobile mapping platform with advantages over current agricultural phenotyping systems in terms of acquiring data that facilitate under-canopy plant trait extraction. The system is based on an unmanned ground vehicle (UGV) for in-row, under-canopy data acquisition to deliver accurately georeferenced 2D and 3D products. The paper addresses three main aspects pertaining to the UGV development: (a) architecture of the UGV mobile mapping system (MMS), (b) quality assessment of acquired data in terms of georeferencing information as well as derived 3D point cloud, and (c) ability to derive phenotypic plant traits using data acquired by the UGV MMS. The experimental results from this study demonstrate the ability of the UGV MMS to acquire dense and accurate data over agricultural fields that would facilitate highly accurate plant phenotyping (better than above-canopy platforms such as unmanned aerial systems and high-clearance tractors). Plant centers and plant count with an accuracy in the 90% range have been achieved.

54 ENVIRONMENTAL SCIENCES↗

Machine learning to identify geologic factors associated with production in geothermal fields: A casestudy using 3D geologic data, Brady geothermal field, Nevada

In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in the Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity production and direct use of hydrothermal fluids. Transmissive fluid flow pathways are relatively rare in the subsurface but are critical components of hydrothermal systems like Brady and many other types of fluid flow systems in fractured rock. The ML method, non-negative matrix factorization with k-means clustering (NMFk), is applied to a library of fourteen 3D geologic characteristics hypothesized to control hydrothermal circulation in the Brady geothermal field. Our results indicate the macro-scale faults and a local step-over in the fault system preferentially occur along with production wells when compared to injection wells and non-productive wells. We infer that these are the key geologic characteristics that control the through-going hydrothermal transmission pathways at Brady. Our results demonstrate 1) the specific geologic controls on the Brady hydrothermal system and 2) the efficacy of pairing ML techniques with 3D geologic characterization to enhance the understanding of subsurface processes.

15 GEOTHERMAL ENERGY↗

Fully Automated Profile-based Calibration Strategy for Airborne and Terrestrial Mobile LiDAR Systems with Spinning Multi-beam Laser Units

LiDAR-based mobile mapping systems (MMS) are rapidly gaining popularity for a multitude of applications due to their ability to provide complete and accurate 3D point clouds for any and every scene of interest. However, an accurate calibration technique for such systems is needed in order to unleash their full potential. In this paper, we propose a fully automated profile-based strategy for the calibration of LiDAR-based MMS. The proposed technique is validated by comparing its accuracy against the expected point positioning accuracy for the point cloud based on the used sensors’ specifications. The proposed strategy was seen to reduce the misalignment between different tracks from approximately 2 to 3 m before calibration down to less than 2 cm after calibration for airborne as well as terrestrial mobile LiDAR mapping systems. In other words, the proposed calibration strategy can converge to correct estimates of mounting parameters, even in cases where the initial estimates are significantly different from the true values. Furthermore, the results from the proposed strategy are also verified by comparing them to those from an existing manually-assisted feature-based calibration strategy. The major contribution of the proposed strategy is its ability to conduct the calibration of airborne and wheel-based mobile systems without any requirement for specially designed targets or features in the surrounding environment. The above claims are validated using experimental results conducted for three different MMS – two airborne and one terrestrial – with one or more LiDAR unit.

47 OTHER INSTRUMENTATION↗

System and method for large-area pulsed laser melting of metallic powder in a laser powder bed fusion application

The present disclosure relates to systems and methods for performing large area laser powder bed fusion (LBPF) to form a plurality of layers of a 3D part in a layer-by-layer fashion using meltable powder particles. In one implementation the system makes use of a first light source, which may be a diode laser subsystem, for generating a first light pulse of a first duration. The first light is used to preheat a substrate underneath a new layer of powder particles, wherein the substrate is formed from a previously fused quantity of the powder particles. A second light source, which may be a pulse laser, generates a second light pulse subsequent to the first light pulse. The second light pulse has a second duration shorter than the first duration by a factor of at least about 10, and fully melts the new layer of powder particles in addition to the substrate, to achieve a smooth printed layer. The wavelength of the first light pulse also differs from a wavelength of the second light pulse.

Khairallah, Saad A.↗

Long Reach Robotic Arm

The Accelerator Division at Fermilab began a robotics program, known as the AD Robotics Initiative. A multi-axis robotic arm was proposed to be included in the program. This summer internship, our team began the planning and design for this project, called the Long Reach Robotic Arm. The problem is that critical systems around the magnets require analysis when water leaks cause them to fail. However, the tightly compacted parts and the quadrupole magnet, weighing approximately 1,000 pounds, cause access viewing problems. The process of having to dismantle and remove the magnet is time-consuming; it is not an efficient solution. The goal for the Long Reach Robotic Arm was to extend and reach behind the component of the Main Injector while "snaking" around and avoiding obstructions. At the start of the project, my teammate, Amanda Hoeksema, and I coded a program in the C language that will determine the number of links and their respective lengths for the robot arm. After, we began the 3D CAD model of the robot arm, base, and counterweight system. The design of the Long Reach Robotic Arm provided a learning experience in learning how to code in the C programming language, using SDL libraries and understanding mechanical engineering.

43 PARTICLE ACCELERATORS↗

Immortal rays: Rethinking random ray neutron transport on GPU architectures

The Random Ray Method (TRRM) is a recently developed adaptation of the Method of Characteristics for neutral particle transport simulations. TRRM has demonstrated excellent performance on 3D nuclear reactor benchmark problems using CPU-based compute systems. When porting to GPU-based systems, however, new performance challenges arise that are unique to processors targeting massive fine-grained parallelism. For smaller problems, or for large problems that are domain decomposed across many computational nodes, the problem size per node has insufficient parallelism to saturate GPU node resources, thus greatly limiting speedup. In this study, we report on a newly developed “immortal ray” variant of TRRM. Here, the immortal ray technique exposes significantly more fine-grained parallelism by fundamentally reformulating the numerical details of ray discretization, resulting in performance tradeoffs with significant overall benefit on GPUs. For very small 2D simulation problems we found the new immortal ray variant allowed for up to a 4.4x speedup when run on a single GPU. For larger 3D simulation problems we found the new variant improved strong scaling by 3x when run on the Summit supercomputer.

97 MATHEMATICS AND COMPUTING↗

Integrated Traction Drive Thermal Management: Keystone Project 3

The presentation represents a report of accomplishments during FY 2024 and is prepared for 2024 DOE VTO Annual Merit Review. The project goal is identifying pathways enabling high-performance, compact, and reliable integrated electric drives and facilitation of achieving DOE 2025 target of 33 kW/L system power density for an electric traction drive through support of other EDT consortium members in design and development of thermal management systems for their respective integrated drive concepts. Specific objectives are: 1) research and evaluation of motor-integrated power electronics packaging technologies and thermal management approaches; 2) explore novel materials and manufacturing options (3D printing with thermally enhanced polymers or ceramic materials) for key thermal management system components; 3) develop thermal management system and its sub-components to enable integrated electric drive DOE power density targets in collaboration with project partners; 4) support activities of DOE's Electric Drive Technologies (EDT) consortium members, Oak Ridge National Laboratory (ORNL), University of Wisconsin and Georgia Tech research teams in thermal management component design and thermal modeling of their integrated traction drives.

ADVANCED PROPULSION SYSTEMS↗

Mu2e Production Target Thermal Test Project

The Mu2e experiment requires a production target that is capable of operating under extreme thermal conditions caused by an 8 GeV proton beam. This project’s objective supports the development of the Mu2e Pro- duction Target by testing the Stickman model’s thermal behavior. Angel Flores Luviano has assisted Jonathan Williams in progressing this project by contributing to the development of a Radiative Cooling Test Fixture (RCTF) that will be used to evaluate the thermal behavior of the new production target model. Engineering calculations were performed to an- alyze thermal performance and pressure drop within the cold well and wa- ter cooling circuit. These calculations also determined the optimal sizing for key components of the water system. An engineering note was made to document these calculations. CAD models of the water circuit piping, thermocouple mounting bars, and radiator chimney were developed, and prototype test rig components were fabricated using 3D printing. Future work will focus on continued RCTF development which includes control system integration, heater hardware design, and interfaces that can be scaled up to increase thermal capacity.

Flores Luviano, Angel Augusto [Unlisted, US]↗

Root genetics in the field to understand drought adaptation and carbon sequestration (Final Scientific/Technical Report)

For all crop plants, roots play a critical role in growth. Roots anchor the plants, and are the primary site of nutrient and water uptake. Roots are also the main source of C to soil in the form of root tissues and exudates, and thus greatly influence SOM stocks. To perform these functions, primary roots extend into soil, producing a network of branching roots of characteristic form, known as its root system architecture (RSA). RSA varies among species, and among varieties within a species that are adapted to different environments. Root traits are major targets for the second green revolution because of their potential to improve crop productivity, increase drought tolerance and nutrient acquisition, and increase C capture of soil. Improving the quality of roots in maize will be particularly valuable, since this crop is planted on over 92 million acres annually in the US. The future sustainability of agricultural systems relies on their ability to enhance soil organic matter (SOM) storage and reduce GHG emissions, while maintaining or enhancing productivity. This program had two components, Sensors and Models. For the first component, we designed and built a high-throughput phenotyping platform for root pulling of maize plants. This eliminated the physical labor of manually pulling up plants and reduced the number of personnel required down to one. The standardized pulling mechanism allowed recording force curves during the pulling process, providing additional information. We validated that the maximum force for pulling the root system was well-correlated with the root system mass and provided root crowns for further RSA analysis. These root crowns identified significant correlations with 2D root area and root depth, along with 3D root volume, total root length and number of root tips. We then used this system for field-based studies in maize on the genetics of root system architecture and its relation to nitrogen-use efficiency (NUE), including using lines relevant to the Corteva breeding program. Varieties were also evaluated at Corteva sites in the cornbelt and Danforth farm in Missouri, to establish responses across sites. From these studies we have identified genetic loci associated with root traits and created mutant lines for these loci and correlations of root traits with NUE. For the Models component, we worked to incorporate root and soil characteristics into the MEMS 2.0 soil and ecosystem biogeochemical model. Existing soil C models, such as Century, are unable to represent specific root trait interactions with the soil environment and therefore to accurately forecast the potential C sequestration benefits of root breeding under different climatic and soil type conditions. We have developed the MEMS 2.0 ecosystem biogeochemical model to improve quantification of farm-scale soil carbon and greenhouse gas emissions. The new knowledge and large datasets produced by this project will be used to develop and drive an innovative model capable of forecasting the impacts on soil C stocks and nutrient dynamics. An innovation was to use the empirical data from the field studies (in 1, above) to model genetic variation in nitrogen use efficiencies and soil C input. Our work demonstrated that maize root-derived C rapidly replaces existing soil C and after 3 years of continuous maize, up to 20% of soil organic C in the topsoil (0-15cm) and 3% in the subsoil (15-30cm) was contributed by maize. However, this contribution did not entirely represent a net increase. Root C contribution to soil was affected by maize genetics. We have analyzed soils derived from the CSU field trials for C and N stocks, in the different soil physical fractions represented by the MEMS model, using both physical fractionation with elemental analyses, and Fourier transformed infrared spectroscopy. Data will be used to link crop nitrogen use efficiencies with soil C sequestration and provide data to bridge the field trials with the model development, for verification of model predictions. The project had a number of successful outcomes: we have used the new phenotyping platform to identify new genetic loci that can enhance root phenotypes; we have partnered with multiple maize seed companies phenotype varieties in their breeding programs; we have developed the MEMS model that can help inform industry on the potential for carbon sequestration in the agricultural sector, and which is now available at the CSU Soil Carbon Solutions Center for use.

59 BASIC BIOLOGICAL SCIENCES↗

Investigation of chemical stabilities and contact angle of 3D printed polymers with CO 2 capture solvents to enhance absorber performance

Increasing absorption rate in aqueous amine CCS systems is one avenue to decrease capital cost by reducing the overall size of the absorber column. One potential route is by replacing conventional steel packing with custom designed packing made from 3D printed polymers. 3D printing offers endless flexibility in packing designs to better enhance liquid/gas contact, increase CO 2 mass transfer and create compact absorber columns. Additionally, before exploring novel packing designs, it is necessary to identify polymer materials that can be 3D printed while also showing long-term physical and surface property stability upon exposure to corrosive amine solutions. Four polymers that are commonly used for 3D printing were evaluated using CO 2 -loaded amine solution at temperatures typically observed in the absorber column. Three polymers, high-density polystyrene (HDPS), acrylonitrile butadiene styrene (ABS) and nylon were found to be physically stable after 5000 hr of amine exposure at temperatures up to 60 °C. The contact angle (wetting) of water and CO 2 -loaded aqueous amine solution on the polymer surfaces were also stable after exposure to the CO2-loaded amine solution.

36 MATERIALS SCIENCE↗