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At least 1,675 records · Page 93

Rate-Based Absorption Modeling for Postcombustion CO 2 Capture with Additively Manufactured Structured Packing

Carbon capture using amine-based solvents in an absorption process is a leading candidate for reducing greenhouse gas emissions in industrial flue gas streams. To reduce operating costs and associated parasitic energy of these processes, process intensification utilizing additively manufactured structured packing has emerged as a new technology to manage exothermic reactions during absorption while improving CO 2 capture. A rate-based model framework has been developed for these novel packings that incorporates the mass and heat transfer phenomena for amine-based absorption of CO 2 . The rate-based model framework is first benchmarked using available solubility data and pilot plant data for aqueous monoethanolamine. The model validation shows accurate prediction of both CO 2 equilibrium partial pressures and ion speciation for solubility data as well as CO 2 capture, temperature profile, and solvent composition for pilot plant data in the absorption column. The model framework is then applied toward predicting the CO 2 capture performance of additively manufactured structured packing. Simulations agree with experimental data in predicting the CO 2 capture and the capture performance increase due to cooling within the structured packing device. Finally, advantages of this rate-based model framework are the utilization of correlations that may predict mass transfer and heat transfer coefficients of the packing based on the geometric properties of the device and the implementation of the model framework in open-source programming.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Continuous Polymer Synthesis and Manufacturing of Polyurethane Elastomers Enabled by Automation

Connecting polymer synthesis and processing is an important challenge for streamlining the manufacturing of polymeric materials. In this work, the automated synthesis of acrylate-capped polyurethane oligomers is integrated with vat photopolymerization 3D printing. This strategy enabled the rapid manufacturing of a library of polyurethane-based elastomeric materials with differentiated thermal and mechanical properties. The automated semi-continuous batch synthesis approach proved enabling for resins with otherwise short shelf lives because the intimate connection between synthesis, formulation, and processing. Structure-property studies demonstrated the ability to tune properties through systematic alteration of crosslink density and chemical composition.

36 MATERIALS SCIENCE↗

Are There Opportunities To Re-Think How We Manufacture Synthetic Graphite?

This manuscript contributes a Viewpoint article to ACS Sustainable Resource Management and discusses the graphite supply chain, growing mismatch between graphite demand and global manufacturing capacity, current graphite manufacturing technologies, and different feedstocks.

alternative carbon feedstocks↗

Electrostatic sensors for SPIDER experiment: Design, manufacture of prototypes, and first tests

A system of electrostatic sensors has been designed for the SPIDER (Source for the production of Ions of Deuterium Extracted from RF plasma) experiment, prototype RF source of the ITER NBI (neutral beam injection). A prototype of the sensor system was manufactured and tested at the BATMAN (BAvarian Test MAchine for Negative ions) facility, where the plasma environment is similar to that of SPIDER. Different aspects concerning the mechanical manufacturing and the signal conditioning are presented, among them the RF compensation adopted to reduce the RF effects which could lead to overestimated values of the electron temperature. The first commissioning tests provided ion saturation current values in the range assumed for the design, so the deduced plasma density estimate is consistent with the expected values.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Infrared thermography for laser-based powder bed fusion additive manufacturing processes

Additive manufacturing (AM) has the potential to revolutionize discrete part manufacturing, but improvements in processing of metallic materials are necessary before AM will see widespread adoption. A better understanding of AM processes, resulting from physics-based modeling as well as direct process metrology, will form the basis for these improvements. Infrared (IR) thermography of AM processes can provide direct process metrology, as well as data necessary for the verification of physics-based models. We review selected works examining how IR thermography was implemented and used in various powder-bed AM processes. This previous work, as well as significant experience at the National Institute of Standards and Technology in temperature measurement and IR thermography for machining processes, shapes our own research in AM process metrology with IR thermography. We discuss our experimental design, as well as plans for future IR measurements of a laser-based powder bed fusion AM process.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Porosity of additive manufacturing parts for process monitoring

Some metal additive manufacturing processes can produce parts with internal porosity, either intentionally (with careful selection of the process parameters) or unintentionally (if the process is not well-controlled.) Material porosity is undesirable for aerospace parts - since porosity could lead to premature failure - and desirable for some biomedical implants, since surface-breaking pores allow for better integration with biological tissue. Changes in a part's porosity during an additive manufacturing build may also be an indication of an undesired change in the process. We are developing an ultrasonic sensor for detecting changes in porosity in metal parts during fabrication on a metal powder bed fusion system, for use as a process monitor. This paper will describe our work to develop an ultrasonic-based sensor for monitoring part porosity during an additive build, including background theory, the development and detailed characterization of reference additive porosity samples, and a potential design for in-situ implementation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Characterizing performances of solder paste printing process at flexible manufacturing lines

Solder paste printing (SPP) has been a challenge on printed circuit board (PCB) manufacturing, evident by the proliferation of solder paste inspection equipment, or substituted by rigorous non-value added activity of manual inspections. The objective of this study is to characterize the SPP performance of various products manufactured in flexible production lines with different equipment configurations, and determine areas for process improvement. The study began by collecting information on SPP performance relative to component placement (CP) process, and to the proportion of mixed products. Using a clustering algorithm to group similar elements together, SPP performance across all product-production line pairs are statistically modeled to discover the trend and the influential factors. The main findings are: (a) Ratio of overall dpku for CP and SPP processes are 2:1; (b) logistic regression models of SPP performance indicated that only effects of product-production line and solder paste printer configuration are significant; (c) PCB circuitry design with BGA components and single solder paste printer line configurations generated the highest monthly defects, with the highest variation in the latter.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Compliance and control characteristics of an additive manufactured-flexure stage

This paper presents a compliance and positioning control characteristics of additive manufactured-nanopositioning system consisted of the flexure mechanism and voice coil motor (VCM). The double compound notch type flexure stage was designed to utilize the elastic deformation of two symmetrical four-bar mechanisms to provide a millimeter-level working range. Additive manufacturing (AM) process, stereolithography, was used to fabricate the flexure stage. The AM stage was inspected by using 3D X-ray computerized tomography scanner: air-voids and shape irregularity. The compliance, open-loop resonance peak, and damping ratio of the AM stage were measured 0.317 mm/N, 80 Hz, and 0.19, respectively. The AM stage was proportional-integral-derivative positioning feedback-controlled and the capacitive type sensor was used to measure the displacement. As a result, the AM flexure mechanism was successfully 25 nm positioning controlled within 500 μm range. The resonance peak was found approximately at 280 Hz in closed-loop. This research showed that the AM flexure mechanism and the VCM can provide millimeter range with high precision and can be a good alternative to an expensive metal-based flexure mechanism and piezoelectric transducer.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Influence of emitter ring manufacturing tolerances on electron beam quality of high power gyrotrons

A sensitivity analysis of manufacturing imperfections and possible misalignments of the emitter ring in the gyrotron cathode structure on the electron beam quality has been performed. It has been shown that a possible radial displacement of the emitter ring of the order of few tens of microns can cause dramatic effects on the beam quality and therefore the gyrotron operation. Two different design approaches are proposed in order to achieve an electron beam which is less sensitive to manufacturing imperfections.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multiscale fatigue crack initiation in hierarchical additively manufactured alloys

Bioinspired hierarchical microstructures offer a route toward engineered fatigue resistance in additively manufactured alloys. However, it remains unclear how discrete structural constituents independently govern damage accumulation, particularly during the critical fatigue initiation regime where short cracks strongly interact with local microstructure. Here, we investigate multiscale fatigue initiation in a dual-phase, nanolamellar AlCoCrFeNi 2.1 high-entropy alloy. By comparing microscale specimens that isolate the nanolamellar structure against macroscale specimens containing the full melt-pool architecture, we identify size-dependent fatigue initiation mechanisms. We find that failure is dictated by nanolamellar interfaces at the microscale, whereas mesoscale melt pool boundaries serve to initiate fatigue at the macroscale. This mechanistic shift is accompanied by a transition from macroscale quasi-brittle failure to microscale plasticity-driven crack extension. Our results provide a physical framework for understanding how structural hierarchy governs the transition from discrete microstructural deformation to continuum fatigue fracture behavior, informing the design of damage-tolerant, additively manufactured alloys.

36 MATERIALS SCIENCE↗

A critical review on additive manufacturing of refractory alloys from a data analytics perspective- beyond nickel-based superalloys

Refractory alloys (RAs) are promising materials due to their exceptional physicochemical properties, but most research remains at the laboratory scale. For broader adoption, advancements in manufacturing are essential. Because their high stability makes conventional methods like machining and casting difficult, additive manufacturing (AM) is emerging as an effective approach for fabricating refractory alloy components. However, AM's repeated non-equilibrium thermal cycles introduce undesired features (e.g. defects, anisotropic microstructures, and residual stresses), which are magnified due to RAs’ unique properties. This paper comprehensively reviews the state-of-the-art methods of AM for refractory alloys. It explores data analytics techniques to establish design rules based on multi-fidelity experimental and computational methods. Furthermore, it investigates integrated, collaborative efforts to harmonise standalone databases, information, knowledge, and predictive models at multi-physics, multi-stage, and multi-scale. Unlike the existing literature that focuses primarily on material systems or process fundamentals, this work provides an integrated perspective on AM of refractory alloys from a data analytics standpoint, highlighting the roles of integrated computational materials engineering (ICME), verification, validation, and uncertainty quantification (VV&UQ), and digital twin-driven qualification in overcoming data scarcity and accelerating rapid qualification.

Additive manufacturing↗

Elastocaloric cooling of additive manufactured shape memory alloys with large latent heat

The stress-induced martensitic phase transformation of shape memory alloys (SMAs) is the basis for elastocaloric cooling. In this paper, we employ additive manufacturing to fabricate TiNi SMAs, and demonstrate compressive elastocaloric cooling in the TiNi rods with transformation latent heat as large as 20 J g -1 . Adiabatic compression on as-fabricated TiNi displays cooling ΔT as high as -7.5 °C with recoverable superelastic strain up to 5%. Unlike conventional SMAs, additive manufactured TiNi SMAs exhibit linear superelasticity with narrow hysteresis in stress–strain curves under both adiabatic and isothermal conditions. Microstructurally, we find that there are Ti 2 Ni precipitates typically one micron in size with a large aspect ratio enclosing the TiNi matrix. Finally, a stress transfer mechanism between reversible phase transformation in the TiNi matrix and mechanical deformation in Ti 2 Ni precipitates is believed to be the origin of the unique superelasticity behavior.

36 MATERIALS SCIENCE↗

Multi-physics modeling of grain growth during solidification in electron beam additive manufacturing of Inconel 718

While experimental work has shown promising results regarding control of additive manufacturing metal grain structure, the effects of processing parameters on the grain structure is difficult to understand and predict from experiment alone. To this end, a modeling framework is developed which sequentially couples a macro-scale, semi-analytic thermal model, and a meso-scale, cellular automata-based microstructure model. This framework is applied to electron beam additive manufacturing of Inconel 718 using a complex spot scan pattern. The model shows that, with the same scan pattern, variations in the spot time and electron-beam current produce thermal histories with significant spatial and temporal differences, which then produce complex solidification conditions from the interplay between molten pools in the same layer and subsequent layers, resulting in vastly different grain structures. Additionally, it is noted that the framework can significantly reduce the computational expenses for coupled thermal-metallurgical problems, and has the potential to be used for component level problems.

36 MATERIALS SCIENCE↗

The case for digital twins in metal additive manufacturing

The digital twin (DT) is a relatively new concept that is finding increased acceptance in industry. A DT is generally considered as comprising a physical entity, its virtual replica, and two-way digital data communications in-between. Its primary purpose is to leverage the process intelligence captured within digital models—or usually their faster-solving surrogates—towards generating increased value from the physical entities. The surrogate models are created using machine learning based on data obtained from the field, experiments and digital models, which may be physics-based or statistics-based. Anomaly detection and correction, and diagnostic closed-loop process control are examples of how a process DT can be deployed. In the manufacturing industry, its use can achieve improvements in product quality and process productivity. Metal additive manufacturing (AM) stands to gain tremendously from the use of DTs. This is because the AM process is inherently chaotic, resulting in poor repeatability. However, a DT acting in a supervisory role can inject certainty into the process by actively keeping it within bounds through real-time control commands. Closed-loop feedforward control is achieved by observing the process through sensors that monitor critical parameters and, if there are any deviations from their respective optimal ranges, suitable corrective actions are triggered. The type of corrective action (e.g. a change in laser power or a modification to the scanning speed) and its magnitude are determined by interrogating the surrogate models. Because of their artificial intelligence (AI)-endowed predictive capabilities, which allow them to foresee a future state of the physical twin (e.g. the AM process), DTs proactively take context-sensitive preventative steps, whereas traditional closed-loop feedback control is usually reactive. Apart from assisting a build process in real-time, a DT can help with planning the build of a part by pinpointing the optimum processing window relevant to the desired outcome. Again, the surrogate models are consulted to obtain the required information. In this article, we explain how the application of DTs to the metal AM process can significantly widen its application space by making the process more repeatable (through quality assurance) and cheaper (by getting builds right the first time).

36 MATERIALS SCIENCE↗

Improved Productivity with Multilaser Rotary Powder Bed Fusion Additive Manufacturing

Laser powder bed fusion (LPBF) enables the fabrication of intricate, geometrically complex structures with a sufficiently fine surface finish for many engineering applications with a diversity of available feedstock metals. However, the production rate of LPBF systems is not well suited for mass production in comparison to traditional manufacturing methods. LPBF systems measure their deposition rates in 100's of grams per hour, while other processes measure in kilograms per hour or even in the case of processes such as forming, stamping, and casting, 100's of kilograms per hour. To be widely adopted in industry for mass production, LPBF requires a new scalable architecture that enables many orders of magnitude improvement in deposition rate, while maintaining the geometry freedom of additive manufacturing. This article explores concepts that could achieve as much as four orders of magnitude increase in the production rate through the application of (1) rotary table kinematic arrangements; (2) a dramatic number of simultaneously operating lasers; (3) reductions of laser optic size; (4) improved scanning techniques; and (5) an optimization of toroidal build plate size. To theoretically demonstrate the possibilities of production improvements, a productivity analysis is proposed for synchronous reluctance motors with relevance to the electric vehicle industry, given the recent increase in the diversity of printable soft magnetic alloys. The analysis provides insights into the impact of the architecture and process parameters necessary to optimize rotary powder bed fusion for mass production.

36 MATERIALS SCIENCE↗

Smart manufacturing maturity models and their applicability: a review

The purpose of this paper is to review existing smart manufacturing (SM) maturity models' dimensions and maturity levels to assess their applicability and drawbacks. There are many maturity models available but many of them have not been validated or do not provide a useful guide or tool for applications. This gap creates the need for a review of the existing maturity model's applicability. Nineteen peer-reviewed maturity models related to “Digital Transformation,” “Industry 4.0” or “Smart Manufacturing” were selected based on a systematic literature review and five consulting firm models were selected based on the author's industry knowledge. The chosen models were analyzed to determine 10 categories of dimensions. Then they are assessed on a 1–5 scale for how applicable they are in the 10 categories of dimensions. The five “consulting firm” models have a first-mover advantage, are more widely used in industry and are more applicable, but some require payment, and they lack published details and validation. The 19 “peer reviewed” models are not as widely used, lack awareness in the industry and are not as easy to apply because of no web tool for self-assessment, but they are improving. The categories defined to characterize the models and facilitate comparisons for users include “Information Technology (IT) and Cyber-Physical System (CPS) and Data,” “Strategy and Organization,” “Supply Chain and Logistics,” “Products and Services,” “Culture and Employees,” “Technology and Capabilities,” “Customer and Market,” “Cybersecurity and Risk,” “Leadership and Management” and “Governance and Compliance.” The analyzed maturity models were particularly weak in the areas of cybersecurity, leadership and governance. Researchers and practitioners can use this review with consideration of their specific needs to determine if a maturity model is applicable or if a new model needs to be developed. The review can also aid in the development of maturity models through the discussion of each of the dimension categories. Finally, compared to existing reviews of SM maturity models, this research determines comprehensive dimension categories and focuses on applicability and drawbacks.

42 ENGINEERING↗

Effect of sintering temperature on feature resolution and flexural strength of ceramics fabricated through vat photopolymerization additive manufacturing

Although ceramic additive manufacturing (AM) could be used to fabricate complex, high-resolution parts for diverse, functional applications, one ongoing challenge is optimizing the post-process, particularly sintering, conditions to consistently produce geometrically accurate and mechanically robust parts. This study aims to investigate how sintering temperature affects feature resolution and flexural properties of silica-based parts formed by vat photopolymerization (VPP) AM. Test artifacts were designed to evaluate features of different sizes, shapes and orientations, and three-point bend specimens printed in multiple orientations were used to evaluate mechanical properties. Sintering temperatures were varied between 1000°C and 1300°C. Deviations from designed dimensions often increased with higher sintering temperatures and/or larger features. Higher sintering temperatures yielded parts with higher strength and lower strain at break. Many features exhibited defects, often dependent on geometry and sintering temperature, highlighting the need for further analysis of debinding and sintering parameters. To the best of the authors’ knowledge, this is the first time test artifacts have been designed for ceramic VPP. This work also offers insights into the effect of sintering temperature and print orientation on flexural properties. These results provide design guidelines for a particular material, while the methodology outlined for assessing feature resolution and flexural strength is broadly applicable to other ceramics, enabling more predictable part performance when considering the future design and manufacture of complex ceramic parts.

36 MATERIALS SCIENCE↗

Glass Additive and Subtractive Manufacturing of a Fiber Optic Rotary Encoder for Downhole Pressure Sensing

This article presents a fiber optic rotary encoder-based pressure sensor for downhole applications. The rotary encoder, which is composed of an encoding pad and an all-glass optical fiber sensing head, converts the rotation angles of a pressure transducer to digital codes. The optical fiber only serves as the telemetry channel to directly transmit the data in digital format such that the environmental temperature influence and the long-time drift are minimized. The glass additive and subtractive manufacturing (ASM) techniques are used to embed the multichannel optical fibers into a bulk-fused silica glass substrate. Because the fused silica glass shares a similar material property to the optical fiber (e.g., thermal expansion coefficient), the optical fiber sensing head is well sealed and fixed even at an elevated temperature. The picosecond laser blackening technique is used to fabricate the high reflectivity contrast encoding pad with high accuracy. Here, the proposed pressure sensor was manufactured and experimentally verified to have a signal-to-noise ratio (SNR) of 23 dB and a linear pressure response with a root-mean-square error (RMSE) of 0.37. During the 400-h 250 °C long-term stability test, there was no digital code variation. In addition, a mathematical model to study the relationships between the sensor’s performances and design parameters was established. According to the model, a 12-bit encoder (0.02% pressure sensitivity) can be achieved with a radius of 20 mm.

02 PETROLEUM↗