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This fastener used in induction heating is a wire screen basically of an eddy current carrying material such as carbon steel. Selected wires in the screen are copper, sheathed in an insulating material. The screen is placed between two sheets of thermoplastics. When inductively heated, the composite softens and flows around the apertures of the screen. After this heating and joining, the copper wires may be used to conduct electricity.
Most of the spectral characteristics of ordinary chondrites and S-asteroids in the visible and infrared can be reduced to three numerical values. These values represent the depth of the absorption band resulting from octahedrally coordinated Fe(sup 2+), the reflectance at 0.56 microns and the slope of the continuum (as measured according to convention). By plotting these three characteristics, it is possible to immediately compare the spectral characteristics of large numbers of ordinary chondrites and S-asteroids. Commonality of spectral characteristics between these populations can thus be evaluated on the basis of overlap in position on three two-coordinate systems: albedo vs. band depth, band depth vs. slope, and slope vs. albedo. In order to establish identity, members of the two populations must overlap on all three of these independent parameter spaces. In this coordinate system, spectra of 23 ordinary chondrites (representing all metamorphic grades), and 39 S-asteroids were compared. It was found that there was no overlap between the two populations in terms of the slope vs. band depth parameters, nor were most chondrites identical to the S-asteroids with respect to the other criteria. However, the controversial question remains: Where are the parent bodies of the chondrites? Perhaps an even more critical question is: Where are our samples of the S-asteroids? Considering the geography of the asteroid belt and the theory that early solar-system electromagnetic induction heating differentiated protoasteroids in the inner portion of the main belt, it was suggested that although S-asteroids and ordinary chondrites have very similar mineralogy, the S-asteroids are mixtures of metallic nickel iron and silicates which resulted from magmatism induced by electromagnetic heating whereas chondrites were only slightly metamorphosed nebular condensates. In this scenario chondrites would have been derived from a population of bodies with thermal lag times so short that they were not subjected to melting during the phase of the electromagnetic induction heating event but only to various degrees of pervasive metamorphism. Furthermore, these objects would then have been too small to be observed and systematically included in the library of asteroidal spectra. It was also suggested that the parametric distribution of S-asteroid spectra could be reproduced by mixing various proportions of NiFe meteorite and achondritic materials. This has also been demonstrated in the laboratory.
To support the eventual development of a nuclear thermal rocket engine, a state-of-the-art experimental test setup has been constructed to evaluate the performance characteristics of candidate fuel element materials and geometries in representative environments. The test device simulates the environmental conditions (minus the radiation) to which nuclear rocket fuel components will be subjected during reactor operation. Test articles mounted in the simulator are inductively heated in such a manner as to accurately reproduce the temperatures and heat fluxes normally expected to occur as a result of nuclear fission while at the same time being exposed to flowing hydrogen. This project is referred to as the Nuclear Thermal Rocket Element Environment Simulator or NTREES. The NTREES device is located at the Marshall Space flight Center in a laboratory which has been modified to accommodate the high powers required to heat the test articles to the required temperatures and to handle the gaseous hydrogen flow required for the tests. Other modifications to the laboratory include the installation of a nitrogen gas supply system and a cooling water supply system. During the design and construction of the facility, every effort was made to comply with all pertinent regulations to provide assurance that the facility could be operated in a safe and efficient manner. The NTREES system can currently supply up to 50 kW of inductive heating to the fuel test articles, although the facility has been sized to eventually allow test article heating levels of up to several megawatts.
Mixing and temperature measurements on argon plasma operating as heater for surrounding sheath of air or hydrogen
The Toroid Bonding Gun is and induction heating device. It is a self contained, portable, low powered induction welding system developed for bonding or joining plastic, ceramic, or metallic parts. Structures can be bonded in a factory or in a the field. This type of equipment allows for applying heat directly to the bond lines and/or to the adhesives without heating the entire structure, supports, and fixtures of a bonding assembly. The induction heating gun originally developed for use in the fabrication of space Gangs of bonders are now used to rapidly join composite sheet and structural components. Other NASA-developed applications of this bonding technique include the joining of thermoplastic composites, thermosetting composites, metals, and combinations of these materials.
The NorthStar pressed and sintered 29 mm diameter, 0.5 mm thick Mo-100 disks will be subjected to large temperature gradients when in beam during production. The beam preferentially heats the disk center, while the aggressive cooling by the helium keeps areas outside the beam spot relatively cool. The result is a temperature gradient of up to 900°C over the radial distance of 14.5 mm. To test the disk integrity with this high temperature gradient, a special holder for a single disk was made such that proper cooling can be applied as in the design target and the disk heating can be replicated with induction heating. NorthStar press and sintered disks were used for these tests.
The present study has the objective to show that a Fourier Transform IR (FTIR) spectrometer in a single-beam reflection mode can be used for direct comparison of fractured vs nonfractured Si3N4 surfaces. This can be done because the FTIR method permits a digital summation of nearly 1000 scans of the fracture surface. Commercial-grade Si3N4, Y2O3, and Al2O3 were used in the study. The samples were heat treated in a vacuum induction heating furnace at either 1000 C for 10 h or 1200 C for 10 h each. Use of Fourier transform IR reflection spectroscopic analysis and X-ray diffraction shows that 10 h at 1200 C is sufficient to devitrify the amorphous grain boundary phase of Si3N4 containing 15 percent Y2O3 + 2 percent Al2O3 densification aids.
A thin (.005) flexible ceramic susceptor (carbon) was discovered. It was developed to join ceramics, plastics, metals, and combinations of these materials using a unique induction heating process. Bonding times for laboratory specimens comparing state of the art technology to induction bonding were cut by a factor of 10 to 100 times. This novel type of carbon susceptor allows for applying heat directly and only to the bondline without heating the entire structure, supports, and fixtures of a bonding assembly. The ceramic (carbon film) susceptor produces molten adhesive or matrix material at the bond interface. This molten material flows through the perforated susceptor producing a fusion between the two parts to be joined, which in many instances has proven to be stronger than the parent material. Bonding can be accomplished in 2 minutes on areas submitted to the inductive heating. Because a carbon susceptor is used in bonding carbon fiber reinforced plastics and ceramics, there is no radar signature or return making it an ideal process for joining advanced aerospace composite structures.
RTX Technology Research Center (RTRC), together with Collins Aerospace (Collins) and Oak Ridge National Laboratory (ORNL) has developed an Artificial Intelligence (AI) / Machine Learning (ML) guided solution to advance the manufacturing and assembly of high performance and lightweight thermoplastic composite (TPC) aerospace products. The solution aims to lower risk, cost and lead time for induction heating based welding and consolidation processes for TPC structure. The cost and lead time of part and material specific process development for induction welding (IW) and induction consolidation will be reduced by replacing traditional empirical methods with optimization methods that merge AI/ML and physics-based process simulations and process experiments with sensing and controls. TPC-IW process development is empirical in nature, and uncertainties in material & process behavior exist near & far from the induction coil. Physics-based simulations can be leveraged directly for process optimization but can be too computationally expensive to run in high fidelity and real time to do robust process optimization. The key impact of successful TPC induction consolidation and welding is cost & lead time reduction for part & material specific consolidation and welding recipes. This is an enabler for more rapid deployment of TPC structures via joining assembly, which can reduce energy & cost intensive usage of autoclaves & ovens. The solution aimed to advance the U.S. Department of Energy’s interests in using thermoplastics and automation in composite manufacturing for improvement of products for existing markets via increased production speeds, reduced costs, and lowered use of energy. Welded TPC structures can offer significant weight & energy savings for high-value commercial aerospace & industrial applications compared to metal & thermoset composite structures assembled by mechanical fastening and/or adhesive bonding. The project was organized into two Budget Periods. Budget Period 1 (BP1) was 15 months and its goal was to perform ML process optimization framework development & deployment on lab-coupon aerostructure components. A Go/No-Go Review was performed at the end of BP1 to verify fulfilment of key tasks & milestones to justify a Go Decision to move into the next Budget Period. Budget Period 2 (BP2) was 12 months and its goal was the deployment of the ML framework for ML process optimization of pilot industrial scale aerostructure components. The overall project aim was to develop & demonstrate ML-enhanced modeling framework that learns process-property mapping from multiple data sources at different fidelities. During BP1, the team accomplished key tasks & milestones to demonstrate the concept of multi-source ML for TPC aerostructure consolidation and assembly. First, the team completed documentation of induction based TPC heating requirements including baseline metrics to compare measured results against. Next the team completed demonstration of data generation from physics-based simulations for ML surrogate model generation and demonstrated the integration of physics-based simulation data into multi-source AI/ML algorithms. In parallel, the team established the lab-coupon scale induction welding system and completed a process to label and reduce generated data from physics-based simulation and experiments for ML surrogate models to enable multi-source ML model training & testing. To complete BP1, the team integrated physics-based simulation data and experimental data into multi-source ML algorithms. This was based on the team completing ML deployment of the induction welding on a lab system at RTRC and AI/ML deployment on existing induction welding line at Collins. ORNL visited both Collins and RTRC sites to witness the TPC induction welding process. Then, ORNL designed and constructed a new version of their vision-based sensing system better adapted to acquire process signals of the TPC induction welding process for process anomaly and defect detection. In BP2, the team accomplished key tasks & milestones to scale up multi-source ML for TPC aerostructure consolidation and assembly from the lab-coupon scale to the pilot-industrial scale. In BP2, the team demonstrated real time anomaly & defect detection via experiments performed by ORNL & RTRC. The team completed ML-optimization heating trials for TPC induction consolidation at Collins, and the team confirmed pilot industrial scale experimental data from Collins was compatible with the developed ML pipeline from RTRC. The team completed sub-element scale ML process optimization demonstration at RTRC, where the team leveraged RTRC’s robotic TPC welding setup to de-risk the ML process optimization by performing ML analysis of recorded temperatures to account for complex part features. Then, the team applied its ML-derived control strategies and ML process optimization framework at Collins to the pilot-industrial scale on a demo skin-stiffener part representative of a nacelle aerostructure fan cowl section. The key innovation is the AI/ML framework enabling effective process development of high performance, lightweight, energy efficient TPCs for composite aircraft structures.
Inductively heated graphite furnace, having a source of blackbody radiation, for calibration of pyrometers up to 3,000 degrees k
Induction-heating evaporation method for making platinum films with optimum reflectance and optical constants for the vacuum ultraviolet
Abstract Development of high‐performance electrocatalysts for water splitting is crucial for a sustainable hydrogen economy. In this study, rapid heating of ruthenium(III) acetylacetonate by magnetic induction heating (MIH) leads to the one‐step production of Ru‐RuO₂/C nanocomposites composed of closely integrated Ru and RuO₂ nanoparticles. The formation of Mott‐Schottky heterojunctions significantly enhances charge transfer across the Ru‐RuO 2 interface leading to remarkable electrocatalytic activities toward both hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) in 1 m KOH. Among the series, the sample prepares at 300 A for 10 s exhibits the best performance, with an overpotential of only −31 mV for HER and +240 mV for OER to reach the current density of 10 mA cm⁻ 2 . Additionally, the catalyst demonstrates excellent durability, with minimal impacts of electrolyte salinity. With the sample as the bifunctional catalysts for overall water splitting, an ultralow cell voltage of 1.43 V is needed to reach 10 mA cm⁻ 2 , 160 mV lower than that with a commercial 20% Pt/C and RuO₂/C mixture. These results highlight the significant potential of MIH in the ultrafast synthesis of high‐performance catalysts for electrochemical water splitting and sustainable hydrogen production from seawater.
Modular chemical process intensification (MCPI) is an emerging field where chemical processing is performed using small-scale modular equipment instead of conventional large centralized chemical plants. Conventional chemical plants benefit from economies of scale that encourage scale-up to ever larger plants. A goal of MCPI is to develop technology that intensifies processing so that equipment can be dramatically smaller and integrated into modular systems. Scale-up occurs by adding more modules in parallel rather than making the equipment larger. A key concept is that equipment and modules can ultimately be cheaper by leveraging economies of mass production, analogous to the automotive industry, in manufacturing the equipment. This project made significant progress toward this outcome by meeting the RAPID institute metric to reduce equipment cost by 20% for each doubling in manufacturing volume. The MCPI application was thermochemical technology that is being commercialized by STARS Technology Corporation, one of the CRADA partners. The technology converts solar and renewable power to chemical energy to produce renewable hydrogen, fuels, and chemicals. The benefit to the public is reduction in greenhouse gases that are contributing to climate change. The project transitioned the steam methane reforming (SMR) reactor from conventional fabrication methods to additive manufacturing (AM) direct metal laser sintering (DMLS) process. This is projected to reduce the cost of making a reactor by 58% when producing 100 reactors per year. Innovations in the DMLS process produced a patented design that reduces reactor weight by 60%. Reductions in material costs and processing time extend the DMLS advantage to higher production volumes. The new design promises to be 38% cheaper than the conventional processes at 1000 units per year. The resulting 87% reduction in the steam methane reforming (SMR) module cost in scaling from current costs meets the RAPID metric. The project was successful in producing and testing the first ever additively manufactured SMR reactors. A reactor achieved over 82% efficiency in converting electric power to chemical energy, which is a world record for an inductively heated SMR. The project has contributed to the design and assembly of a first demonstration plant that is headed to a hydrogen bus filling station in Thousand Palms, CA.
While magnetic field-assisted processing shows promise in improving alloys’ mechanical properties, insufficient descriptions of heating methods hinder development of tailored processing pathways. This study investigates how induction and conventional heating affect microstructures of near-eutectoid Fe–C steel with and without 9 T magnetic field. Conventionally heated samples in field showed more austenite grain growth compared to inductively heated counterparts. Annealing twin frequency increased under field, with twin density increases not fully explained by larger grain sizes.
Considering the phase diagrams of metallic spent fuel constituents, the melting and solidifying of spent metallic fuel causes three immiscible layers (actinide-rich, lanthanide-rich, and Group II-rich) and the condensate phase (Group I) to form. We believe this anticipated immiscibility offers an untapped opportunity for innovative fuel cycle solutions. Through the proposed project, we anticipate confirming the expected phase behavior and develop a thermal treatment process to rapidly extract actinides from spent metallic fuels. The prime apparatus for both purposes is a traveling molten zone system with induction heating. We envision that one rapid pass of the molten zone from the bottom to the top of the metallic rod incorporating species of spent metallic fuels should produce the expected immiscible layer formation and provide species partitioning data effectively and cleanly. It will also demonstrate an actinide extraction process by concentrating the impurities at the top segment of the rod and leaving the actinide species behind as the bulk rod. The successful execution of the project will demonstrate proof of concept for a transformative process path for used metal fuels in terms of economics and safeguards.
This article introduces the Future Foundries platform developed at Oak Ridge National Laboratory, a first-generation research system designed to demonstrate convergent manufacturing. Convergent manufacturing brings together additive, subtractive, and transformative processes in a digitally interconnected environment to enable end-to-end production workflows. By linking traditionally discrete steps, convergent platforms accelerate production, improve repeatability, and support high-mix, low-volume manufacturing. The Future Foundries platform exemplifies this vision in practice by combining four modular, vendor-agnostic process cells that include robotic WAAM, induction heating, optical metrology, and machining, coordinated through an automated pallet handler and a ROS 2-based digital thread. This architecture provides the flexibility and scalability needed for agile production in small and medium-sized manufacturing enterprises and for field deployable manufacturing. Two case studies illustrate the platform’s capabilities. The first presents an integrated workflow for fabricating, transforming, and repairing critical replacement components, showing how consolidated thermal, additive, inspection, and machining operations reduce manual part handling and streamline process flow. The second case study highlights coordinated multi-part production enabled by automated pallet logistics and multi-cell scheduling. Together, these examples showcase convergent manufacturing as a practical and scalable strategy for strengthening domestic casting and forging capacity, improving supply-chain resilience, and enabling rapid, adaptable production of mission-critical components.
An analysis is presented that establishes how correction-free radiance measurements or pyrometry can be performed on targets in furnaces where there may be significant additional radiance from heated furnace walls or from reflecting surfaces close to the target. These configurations are common in microgravity and containerless processing applications where a specular target is radiantly heated in a hot-wall furnace, or inductively heated from the fields arising from nearby closely spaced electromagnetic coils. Proper design requires that the pyrometer does not view any images of the background features in the specular target so that stray radiation will not be reflected into the viewing optics of the pyrometer. To analyze the problem, conventional paraxial optics analysis is shown to be significantly in error. Instead a method of nonparaxial ray tracing, based on the derivatives of the ray paths, shows how the images must be located. This leads to analytical results that can be used to design such systems. The findings are applied to the furnace geometries that are presently being considered for flight in LEO.
A detailed analysis of the accuracy of several techniques recently developed for integrating stiff ordinary differential equations is presented. The techniques include two general-purpose codes EPISODE and LSODE developed for an arbitrary system of ordinary differential equations, and three specialized codes CHEMEQ, CREK1D, and GCKP4 developed specifically to solve chemical kinetic rate equations. The accuracy study is made by application of these codes to two practical combustion kinetics problems. Both problems describe adiabatic, homogeneous, gas-phase chemical reactions at constant pressure, and include all three combustion regimes: induction, heat release, and equilibration. To illustrate the error variation in the different combustion regimes the species are divided into three types (reactants, intermediates, and products), and error versus time plots are presented for each species type and the temperature. These plots show that CHEMEQ is the most accurate code during induction and early heat release. During late heat release and equilibration, however, the other codes are more accurate. A single global quantity, a mean integrated root-mean-square error, that measures the average error incurred in solving the complete problem is used to compare the accuracy of the codes. Among the codes examined, LSODE is the most accurate for solving chemical kinetics problems. It is also the most efficient code, in the sense that it requires the least computational work to attain a specified accuracy level. An important finding is that use of the algebraic enthalpy conservation equation to compute the temperature can be more accurate and efficient than integrating the temperature differential equation.