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At least 379 records · Page 21

Advancements Toward ASME Nuclear Code Case for Compact Heat Exchangers

Our research team proposes to advance the state of the ASME section III code (nuclear service) for Compact Heat Exchangers (CHX). This work will improve the technical state of CHXs and lay the foundation necessary for these heat exchangers to be certified for use in nuclear service. During the course of this work, we will advance the understanding of the performance, integrity, and lifetime of the CHXs for use in any industrial application, making their use more attractive and accessible to the industry. We will do this by developing qualification and inspection procedures that utilize Non-destructive evaluation (NDE) and advanced in-service inspection techniques, with insight from the industrial utility leader EPRI. We have enlisted colleagues at MPR Associates (MPR), an elite nuclear code consulting firm, who are experts on the ASME section III code and who, with input from members of the ASME section III committee, will direct the testing and help develop a series of documents that define the rules and regulations for use of the CHX. Colleagues at North Carolina State University (NCSU) and Oregon State University (OSU) will conduct extensive tensile, creep, and fatigue experiments on diffusion bonded samples (manufactured by US-based Vacuum Process engineering) along with modeling using the elastic perfectly plastic assumptions and comprehensive full inelastic finite element analysis (FEA). This work will allow analysis by design and confidence in the strength of different internal structures. To ensure industry acceptance and long term confidence, team members at the University of Wisconsin–Madison (UW), University of Michigan (UM), Georgia Tech (GT), and the University of Idaho (UI) will extensively test prototypic heat exchangers manufactured by US-based manufactures CompRex and Vacuum Process Engineering (VPE), a leader in the development of advanced CHX. This testing will include the use of various working fluids (salt, sodium, helium, and sCO2) to evaluate operational issues as well as structural integrity under the most severe conditions. Post-test analysis of the tested CHXs coupled with pre/in-service/post NDE (ultrasonic and radiography) led by the Electric Power Research Institute (EPRI) will be incorporated into the development of the rules and regulations for their use in nuclear service.

42 ENGINEERING↗

Data-driven prediction of geometry- and toolpath sequence-dependent intra-layer process conditions variations in laser powder bed fusion

Geometrical features and toolpath sequence are two important factors that cause process condition variations, such as variations in the meltpool temperature or meltpool size, that might lead to undesired material properties in the laser powder bed fusion (LPBF) process. Due to the high dynamics and complex physics of the LPBF process, it is difficult to predict variations in process conditions with simulations alone. Advances in measurement technology and computational technologies open up new possibilities for smart manufacturing. In this paper, a data-driven method to predict intra-layer variations in the processing conditions that source from the toolpath sequence and part geometry is presented. The approach is demonstrated using two-color on-axis pyrometer measurements. Three demonstration cases are presented in which it is demonstrated (1) how the trained predictive model can be used as a filter to ease the interpretation of process variations and discover patterns related to toolpath and part geometry, and (2) how to generate predictions that can be used for feedforward control, i.e., for adjusting laser power or scanning speed along the toolpath using a meltpool temperature prediction model generated based on on-axis measurements. Results show that the developed prediction model is able to meaningfully predict process variations resulted from toolpath sequence and geometry. Predictions are aligned with the results from the related work of others and for the case of 180° laser path turnarounds in our high-speed X-ray imaging experiments. In conclusion, the potential issues related to the current maturity status of the process and measuring equipment that could in practice affect the performance of the proposed solutions are also discussed.

42 ENGINEERING↗

Enhanced Catalyst Durability for the Oxidative Production of Biobased Chemicals (Cooperative Research and Development Final Report)

This CRADA will facilitate technology maturation for NREL-developed atomic layer deposition (ALD) coated catalyst materials that are tailored for durability during the oxidative production of biobased chemicals. This project will address optimizing process parameters for scaling aluminum oxide (Al 2 O 3 ) ALD coated catalysts, demonstrating ALD coated catalyst performance for biomass oxidation, and validating economic models that project significant cost benefits for ALD-enhanced catalytic processes. This work will strengthen private-public partnerships in the area of advanced catalyst manufacturing for energy-related technology. Critical information will be collected to elevate the Technology Readiness Level and increase our competitiveness for cooperative R&D agreements and licensing. Success of this work will be crosscutting as it can facilitate advanced catalyst development for both renewable and conventional processes.

09 BIOMASS FUELS↗

In-Situ Process Monitoring Evaluation and Demonstration using Advanced Characterization with Laser Powder Bed Systems

Oak Ridge National Laboratory’s (ORNL) Manufacturing Demonstration Facility (MDF) worked with EOS Group to evaluate the current in-situ sensor capabilities of an EOS M290 Laser Powder Bed Fusion machine. The M290 was fitted with a 1 Mega-Pixel (MP) grayscale visible-light camera and a 5 MP temporally integrated (TI) near-infrared (NIR) camera. One print from stainless steel (SS) 316 and two from Inconel 625 (IN625) were performed where data including in-situ imaging and a machine log file were captured. These data were subsequently analyzed using a Dynamic Multi-Scale Segmentation Convolutional Neural Network (DMSCNN) trained on user defined classes and correlated to as-printed flaws, in the form of porosity, discovered in X-Ray Computed Tomography (XCT). In Phase I, two indications were detected in-situ and spatially correlated to stochastic lack-of-fusion flaws discovered using XCT. In Phase II, using these links from in-situ signatures to XCT flaw populations, a second neural network (NN) was trained to create a Voxelized Property Prediction Model (VPPM) to predict porosity percentages within the part using only features garnered from the in-situ data from two IN625 complex geometries. The VPPM was able to accurately predict porosity values for IN625 parts with an R 2 value of 0.764.

36 MATERIALS SCIENCE↗

In-Situ Process Monitoring Evaluation and Demonstration using Advanced Characterization with Laser Powder Bed Systems

Oak Ridge National Laboratory’s (ORNL) Manufacturing Demonstration Facility (MDF) worked with EOS Group to evaluate the current in-situ sensor capabilities of an EOS M290 Laser Powder Bed Fusion machine. The M290 was fitted with a 1 Mega-Pixel (MP) grayscale visible-light camera and a 5 MP temporally integrated (TI) near-infrared (NIR) camera. One print from stainless steel (SS) 316 and two from Inconel 625 (IN625) were performed where data including in-situ imaging and a machine log file were captured. These data were subsequently analyzed using a Dynamic Multi-Scale Segmentation Convolutional Neural Network (DMSCNN) trained on user defined classes and correlated to as-printed flaws, in the form of porosity, discovered in X-Ray Computed Tomography (XCT). In Phase I, two indications were detected in-situ and spatially correlated to stochastic lack-of-fusion flaws discovered using XCT. In Phase II, using these links from in-situ signatures to XCT flaw populations, a second neural network (NN) was trained to create a Voxelized Property Prediction Model (VPPM) to predict porosity percentages within the part using only features garnered from the in-situ data from two IN625 complex geometries. The VPPM was able to accurately predict porosity values for IN625 parts with an R 2 value of 0.764.

36 MATERIALS SCIENCE↗

Cost‐Responsive Optimization of Nickel Nanoparticle Synthesis

Abstract Early‐stage cost evaluation during catalyst development holds the potential to accelerate the commercialization and deployment of advanced catalytic materials for sustainable chemical processes. The modeling and assessment of manufacturing costs as early as the laboratory synthesis scale, for example, focusing on materials costs and synthesis performance metrics, can support the development of an experimental–economic feedback loop that enables rapid insight into cost drivers associated with catalyst synthesis and highlights areas that require focused research and development effort. Ultimately, this feedback loop supports the realization of an economic understanding of the overall synthetic process and highlights opportunities to reduce costs, serving as the foundation for the scale‐up of catalyst manufacturing. Herein, a case study is presented utilizing CatCost, a free and publicly available estimation tool for the evaluation of catalyst manufacturing costs, to perform a cost‐responsive optimization of the synthesis of nickel nanoparticles (Ni NPs). It is demonstrated that reagent substitutions with more cost‐effective analogs, coupled with stoichiometric optimization, afford a 58% reduction in raw materials cost without changing the product yield or properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A data-driven framework for predicting machining stability: employing simulated data, operational modal analysis, and enhanced transfer learning

Chatter, a self-excited vibration phenomenon, presents a significant challenge in machining operations, particularly in high-speed milling, where it can degrade tool life, reduce material removal efficiency, and compromise workpiece quality. Addressing this challenge requires a reliable predictive model that can accommodate the complex dynamics of various machining scenarios. This study introduces a novel, data-driven approach to predicting machining stability, leveraging over 140,000 simulated datasets and employing advanced techniques such as operational modal analysis (OMA), enhanced transfer learning (TL), and receptance coupling substructure analysis (RCSA). By integrating these methodologies, the framework effectively classifies and predicts chatter across diverse operational modes, achieving robust and accurate outcomes. Our model utilizes a Random Forest (RF) classifier trained with the comprehensive dataset, which demonstrates substantial improvements in both predictive accuracy and robustness. Specifically, the RF model achieved an accuracy rate of 85%, an area under the curve (AUC) of 0.90, and an F1 score of 0.88, underscoring its capability to adapt to varying machining configurations. These results highlight the framework’s potential to enhance operational efficiency and machining quality by providing reliable chatter predictions across a broad range of machining parameters. In conclusion, this research thus offers a significant advancement in predictive maintenance for machining processes, enabling more stable and efficient manufacturing operations.

42 ENGINEERING↗

High Precision, High Frequency Printed Antennas

An emerging trend in advanced manufacturing is printed electronics and sensors. The ability to print customized electronics and sensors integrated into functional packages is a growing need within a variety of growing markets such as smart manufacturing, internet of things (IoT), and the small satellite industry. Both Oak Ridge National Laboratory (ORNL) and the MITRE Corporation have seedling research efforts evaluating the potential for future printed electronic systems. High frequency, wide-bandwidth phased array antennas (i.e. >45 GHz) open the door to new applications. However, such sensors require currently prohibitively small feature sizes for commercial 3D printing technologies along with increasing challenges with connecting the driving electronics to such features. An additional finding with related advanced manufacturing challenges is the rapid production of 3D additive connectors for integration with commercial printed circuit boards (PCBs), primarily for advanced in-circuit inspection techniques. This work is developing additive manufacturing processes for producing connected and conductive fine scale 3D features. The primary focus was on aerosol-jet printing (AJP), which has a small minimum resolution (<50 µm) but is traditionally printed flat with small height/width aspect ratios <<1, and developing controls to enable fully 3D, high aspect ratio, and unsupported features. In Phase 1 of this effort, baselines of process performance were characterized, and test coupons produced for both ultra-high frequency antennas and microstructures to support reverse engineering of PCBs. In Phase 2, these efforts will be extended for system demonstration of ultra-high frequency antenna arrays, as well as reverse engineering circuitry for dense PCBs.

42 ENGINEERING↗

Solid Free-Form Fabrication of Continuous Fiber Reinforced Composites for Propulsion Application

For propulsion related applications, materials must be able to demonstrate excellent ablation and oxidation resistance at temperature approaching 3500 C, adequate load bearing capabilities, non-catastrophic failure modes, and ability to withstand transient thermal shock. A potential list of propulsion-material property requirements includes, low density, high elastic modulus, low thermal-expansion coefficient, high thermal conductivity, excellent erosion and oxidation/corrosion resistance, and flaw-insensitivity. In many cases, they will also need to be able to be joined, survive thermal cycling and multi-axial stress states, and for reusable applications, the materials must maintain the above attributes after prolonged exposure to extremely harsh chemical environments. The final and possibly most important attribute for these materials are the need to be lower cost and readily available in large quantities. Recently, Advanced Ceramics Research, Inc. (ACR) has developed low cost, flexible-manufacturing processes for Zr & Hf-based carbon fiber reinforced composites, materials with good oxidation and ablation resistance up to 3500 C. This process, called Continuous Composite Co-extrusion (C(sup 3)), incorporates carbon fibers to fabricate 'in-situ' carbide and boride-matrix/carbon fiber composites. M is a variation of ACR's manufacturing process for low-cost structural ceramic materials called Fibrous Monoliths with carbon fiber reinforcements. Fibrous Monolithic materials have a distinct fibrous texture, consist of intertwined cells of a primary phase, separated by cell boundaries of a tailored secondary phase and show very high fracture energies, damage tolerance, and graceful failure. Since they are monolithic powder based composites; they can be manufactured by conventional powder processing techniques using inexpensive raw materials. This combination of high performance and low cost is a breakthrough that could enable wider application of ceramics in high temperature applications. Typical volume fractions of the two phases are 80 to 95% for the cell phase and 5 to 20% for the interpenetrating cell boundary phase. ACR is currently developing an innovative solid freeform form fabrication (SFF) approach to produce Hf and Zr based ceramic composite components reinforced with continuous carbon fiber tows for critical structural components such as tubes and blisks. The process is simple, robust and will be widely applicable to a number of material systems. This technique was originally developed at the University of Delaware Center for Composite Materials (UD-CCM) for rapid fabrication of polymer matrix composites by a technique called automated tow placement or ATP. The current process is being developed in collaboration with UD-CCM. The paper will detail the freeform fabrication process to create low-cost ceramic fiber reinforced composites for high-temperature applications. The results of mechanical properties and microstructural characterization will be presented, together with examples of complex shapes and parts. It is believed that the process will be able to create complex shaped parts for propulsion applications at an order of magnitude lower cost than current CVI and PIP processes.

Vaidyanathan, R.↗

Space Technology Mission Directorate: Game Changing Development

NASA and the aerospace community have deep roots in manufacturing technology and innovation. Through it's Game Changing Development Program and the Advanced Manufacturing Technology Project NASA develops and matures innovative, low-cost manufacturing processes and products. Launch vehicle propulsion systems are a particular area of interest since they typically comprise a large percentage of the total vehicle cost and development schedule. NASA is currently working to develop and utilize emerging technologies such as additive manufacturing (i.e. 3D printing) and computational materials and processing tools that could dramatically improve affordability, capability, and reduce schedule for rocket propulsion hardware.

Gaddis, Stephen W.↗

Design Process of a Pressure Transducer Vibration Fixture

This paper details the iterative design cycle of a fixture used to mount two types of pressure transducers for vibration testing which allows for functional testing without the removal of the transducers. The objective of the fixture is to prove that the pressure transducers can survive vibrations induced during launch. This would increase the Technology Readiness Level of the pressure transducers which is a requirement for the Lunar Advanced Volatile Analysis subsystem preliminary design review. During the design process, additive manufacturing is considered as a manufacturing method of the fixture as a way to investigate the use of additive manufacturing for the final flight version of the Fluid Sub System manifold. It is ultimately shown that the added ability to perform functional testing and optimization for additive manufacturing made the fixture less than ideal for vibration testing. It is determined that the best option is to design and manufacture a traditional vibration fixture without the ability to perform functional testing of components while attached and a separate part to investigate the application of additive manufacturing to the Fluid Subsystem manifold.

Gilstrap, Andrew↗

A laser ultrasonics-based approach for rapid screening of high entropy alloys

This project demonstrates a laser ultrasonics-based characterization methodology for rapid metallic materials design and discovery via in situ determination of phases, microstructures and elastic properties with respect to temperature. Ultrasonic waves are strongly affected by material microstructure, and therefore serve as a facile means to probe elastic properties, phase content and their size distributions and volume fractions. In this study, a laser ultrasonic technique is used to systematically study the evolution of properties in a set of interrelated simple binary alloys and high entropy alloys (HEA). Phase transformations and microstructural changes inferred from the ultrasonic signals will be correlated with electron microscopy data and predictions using calculations of phase diagrams (CALPHAD). The non-contact and non-destructive ultrasonic testing approach developed in this study could overcome several limitations associated with current material characterization methods for materials discovery. It is expected that laser ultrasonics-based methodology developed in this work will be utilized to evaluate novel graded composition HEAs currently being developed at the Idaho National Laboratory (INL) using advanced manufacturing methods based on direct energy deposition and spark plasma sintering processes, and contribute to accelerate the discovery of HEAs.

36 MATERIALS SCIENCE↗

A laser ultrasonics-based approach for rapid screening of high entropy alloys

The primary objective of this seed project is to develop a laser ultrasonics-based characterization methodology for rapid metallic materials design and discovery via in situ determination of phases, microstructures and elastic properties with respect to temperature. Ultrasonic waves are strongly affected by material microstructure, and therefore, serve as a facile means to probe elastic properties, phase content and their size distributions and volume fractions. In this study, a laser ultrasonic technique will be used to systematically study the evolution of properties in a set of interrelated simple binary alloys and high entropy alloys (HEA). Phase transformations and microstructural changes inferred from the ultrasonic signals will be correlated with electron microscopy data and predictions using calculations of phase diagrams (CALPHAD). The non-contact and non-destructive ultrasonic testing approach developed in this study could overcome several limitations associated with current material characterization methods for materials discovery. It is expected that the products of the proposed work will be utilized to evaluate novel graded composition HEAs currently being developed at the Idaho National Laboratory (INL) using advanced manufacturing methods based on direct energy deposition and spark plasma sintering processes, and contribute to accelerate the discovery of HEAs.

36 MATERIALS SCIENCE↗

Lifetime Energy Savings Via Advanced Manufacturing of Low Density Steels for Transportation Applications

The purpose of this “Low Density Steels for Transportation Applications” project was to develop an alloy composition and processing parameters that would result in a material suitable for use in automotive structural components at a reduced density over the current advanced high strength steel (AHSS) materials used. The project work successfully developed a robust alloy capable of exceeding project mechanical property targets at each stage of development, with an 8% density reduction over benchmark AHSS materials (7.8 g/cm3). The developed alloy has the potential to offer significant vehicle lightweighting and improved fuel economy, without sacrificing the increased passenger safety of more traditional AHSS. Through the three tasks of the project, (1) Alloy design and small-scale laboratory evaluation, (2) Laboratory development of hot rolled material and (3) Laboratory development of a cold rolled material, the laboratory work utilized advanced characterization and analytical methods on novel alloy compositions subjected to both conventional and non-conventional processing operations.

36 MATERIALS SCIENCE↗

Editorial: Multi-Omics Technologies for Optimizing Synthetic Biomanufacturing

Industrial manufacturing endures as an essential human activity yielding a variety of useful products; it plays a significant role in the global economy with huge impacts in everyday life. However, the manufacturing process requires consumption of various raw materials (especially petroleum derivatives), generates a variety of harmful waste products, causes pollution, and is energetically inefficient. Biological manufacturing from sustainable, affordable, and scalable feedstocks potentially enables the displacement of the entire portfolio of currently available products produced by industrial processes, enabling the manufacturing of renewable and eco-friendly products (Clomburg et al., 2017). Thus, successful development of a robust biomanufacturing strategy and technology platform, based on the latest advances in synthetic biology and chemical catalysis, will decrease both the cost and production time compared with previous manufacturing processes. Development of biomanufacturing processes using a synthetic biology platform requires the multidisciplinary efforts of science and engineering fields including molecular biology, microbiology, genetic engineering, informatics, metabolic modeling and chemical or process engineering (El Karoui et al., 2019).

59 BASIC BIOLOGICAL SCIENCES↗

Ultrafast radiographic imaging and tracking: An overview of instruments, methods, data, and applications

Ultrafast radiographic imaging and tracking (U-RadIT) use state-of-the-art ionizing particle and light sources to experimentally study sub-nanosecond transients or dynamic processes in physics, chemistry, biology, geology, materials science and other fields. These processes are fundamental to modern technologies and applications, such as nuclear fusion energy, advanced manufacturing, communication, and green transportation, which often involve one mole or more atoms and elementary particles, and thus are challenging to compute by using the first principles of quantum physics or other forward models. One of the central problems in U-RadIT is to optimize information yield through, e.g. high-luminosity X-ray and particle sources, efficient imaging and tracking detectors, novel methods to collect data, and large-bandwidth online and offline data processing, regulated by the underlying physics, statistics, and computing power. We review and highlight recent progress in: (a.) Detectors such as high-speed complementary metal-oxide semiconductor (CMOS) cameras, hybrid pixelated array detectors integrated with Timepix4 and other application-specific integrated circuits (ASICs), and digital photon detectors; (b.) U-RadIT modalities such as dynamic phase contrast imaging, dynamic diffractive imaging, and four-dimensional (4D) particle tracking; (c.) U-RadIT data and algorithms such as neural networks and machine learning, and (d.) Applications in ultrafast dynamic material science using XFELs, synchrotrons and laser-driven sources. Hardware-centric approaches to U-RadIT optimization are constrained by detector material properties, low signal-to-noise ratio, high cost and long development cycles of critical hardware components such as ASICs. Interpretation of experimental data, including comparisons with forward models, is frequently hindered by sparse measurements, model and measurement uncertainties, and noise. Alternatively, U-RadIT make increasing use of data science and machine learning algorithms, including experimental implementations of compressed sensing. Machine learning and artificial intelligence approaches, refined by physics and materials information, may also contribute significantly to data interpretation, uncertainty quantification and U-RadIT optimization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Near net shape processing: A necessity for advanced materials applications

High quality discrete parts are the backbones for successful operation of equipment used in transportation, communication, construction, manufacturing, and appliances. Traditional shapemaking for discrete parts is carried out predominantly by machining, or removing unwanted material to produce the desired shape. As the cost and complexity of modern materials escalates, coupled with the expense and environmental hazards associated with handling of scrap, it is increasingly important to develop near net shape processes for these materials. Such processes involve casting of liquid materials, consolidation of powder materials, or deformation processing of simple solid shapes into the desired shape. Frequently, several of these operations may be used in sequence to produce a finished part. The processes for near net shape forming may be applied to any type of material, including metals, polymers, ceramics, and their composites. The ability to produce shapes is the key to implementation of laboratory developments in materials science into real world applications. This seminar presents an overview of near net shapemaking processes, some application examples, current developments, and future research opportunities.

Kuhn, Howard A.↗

IPAD: A unique approach to government/industry cooperation for technology development and transfer

A key element to improved industry productivity is effective management of Computer Aided Design / Computer Aided Manufacturing (CAD/CAM) information. To stimulate advancement, a unique joint government/industry project designated Integrated Programs for Aerospace-Vehicle Design (IPAD) was carried out from 1971 to 1984. The goal was to raise aerospace industry productivity through advancement of computer based technology to integrate and manage information involved in the design and manufacturing process. IPAD research was guided by an Industry Technical Advisory Board (ITAB) composed of over 100 representatives from aerospace and computer companies. The project complemented traditional NASA/DOD research to develop aerospace design technology and the Air Force's Integrated Computer Aided Manufacturing (ICAM) program to advance CAM technology. IPAD had unprecedented industry support and involvement and served as a unique approach to government industry cooperation in the development and transfer of advanced technology. The IPAD project background, approach, accomplishments, industry involvement, technology transfer mechanisms and lessons learned are summarized.

Fulton, Robert E.↗