The exploration of the complex composition space for high entropy alloys (HEAs) is extremely challenging and resource intensive using traditional materials discovery approaches. Here, we apply Bayesian optimization in the form of active learning with a neural network model to efficiently explore the vast composition space of HEAs with a focus on predicting their stable phases. For example, by focusing data acquisition on the uncertain regions, we achieved a testing accuracy of 95% with 27% of an experimental HEA dataset, comparable to the accuracy (94.6%) of a random forest model trained with 80% of the full dataset (2198 quinary HEAs). Similarly, with just similar to 2% of a CALPHAD dataset we achieved a testing accuracy for phase predictions above 96%, which is comparable to the accuracy (above 97%) achieved when an XGboost model is trained with nearly the full dataset (664,650 quinary HEAs). Thus, our approach greatly facilitates both computational and experimental exploration of HEA design spaces.

As new alloys are being developed for additive manufacturing (AM) applications, questions related to the temperature-dependent structural and compositional stability of these alloys remain. In this work, the benefits and limitations of a unique method for testing this stability are presented. This system employs the use of polychromatic synchrotron light to perform energy-dispersive x-ray diffraction (ED-XRD) on an electrostatically levitated sample at high temperatures. In comparison with a traditional angular-dispersive setup, the container-less electrostatic levitation method has unique advantages, including quicker acquisition times, simultaneous compositional information through fluorescence emissions, a reduction in background noise, and, importantly, concurrent/subsequent measurement of thermophysical properties. This combined method is ideal for phase transition studies by holding the levitated sample at a stable position and temperature through controlled heating and temperature management. To illustrate these capabilities, we show ED-XRD data of the well-known martensitic phase transition (hcp to bcc) in Ti-6Al-4V. In addition, results from the novel alloy Ni51Cu44Cr5 are presented. This alloy is shown to maintain an fcc structure upon heating. However, the concentration of Cu is reduced at high temperatures, resulting in a decrease in the lattice constant. As concurrent thermophysical properties are probed, these preliminary structure and composition experiments demonstrate the capabilities of this technique to determine the composition-processing-structure-properties of metal alloys for AM.

With countless global industries pledging and pursuing decarbonization targets set for the 2030 – 2050 timeframe, the aerospace industry faces many key challenges including reduction of greenhouse gas emissions, contrail abatement, and development/adoption of technologies with higher Fuel-to-Electricity (FTE) conversion efficiencies. One such technology identified as a potential fit for commercial aircraft is the solid oxide fuel cell and gas turbine (SOFC-GT) hybrid power system. Progress in system-level SOFC-GT modeling is critical to produce higher fidelity feasibility studies used to influence SOFC design and performance targets of the future. In this study, the first ProMax 5.0-based SOFC-GT model was developed, validated, and optimized. The impact of process configuration, balance-of-plant, and operating conditions were investigated. An optimal process design comprising 8 SOFC stacks and 7 Energy Storage and Power Generation (ESPG) modules with a total power output of > 7.0-MW and FTE conversion efficiencies of 73 – 76% is reported. Additionally, preliminary airplane architecture with the 7 onboard ESPG modules is presented to show the feasibility of future, hybrid electric airplane design.

With the growth of 3D printing in the production space, it is inevitable that quality assurance will be needed to keep final products within the constraints of requirements. Also, the variety of materials that can be used with 3D printing has increased over the years. Testing also must consider the process of manufacturing. This paper focuses its efforts on the finished product and not the process of manufacturing. Ultrasonic testing is a type of nondestructive testing. The experiments performed in this study aim to explore the usefulness of ultrasonic testing in materials that are 3D printed. The two materials used in this study are steel alloy metals and aluminum blocks of the same dimensions—120 mm × 40 mm × 15 mm. These materials represent common choices in additive manufacturing processes. The chosen alloys, such as Aluminum (6063T6) and grade-304 stainless steel, possess distinct properties crucial for validating the proposed testing method. Metal 3D-printed materials play a pivotal role in diverse industries, since ensuring their structural integrity is imperative for reliability and safety. Testing is crucial to identify and mitigate defects that could compromise the functionality and longevity of the final products, especially in applications with demanding performance requirements. An ultrasonic transducer is used to scan for subsurface defects within the samples and an oscilloscope is used to analyze the signals. Furthermore, several Machine Learning (ML) techniques are used to estimate the severity of the defects. The application of Machine Learning methods in the manufacturing industry has proven advantageous in terms of detecting defects due to its practicality and wide application. Due to their distinct benefits in processing image information, convolutional neural networks (CNNs) are the preferred method when working with picture data. In order to perform binary and multi-class classification, support vector machines that employ the alternative kernel function are a viable option for processing sensor signals and picture data. The study reveals that ultrasonic tests are viable for metallic materials. The primary objective of this work is to evaluate and validate the application of ultrasonic testing for the inspection of 3D-printed steel alloy metals and aluminum blocks. The novelty lies in the integration of Machine Learning techniques to estimate defect severity, offering a comprehensive and non-invasive approach to quality assessment in 3D-printed materials. The proposed method can successfully detect the presence of internal defects in objects, as well as estimate the location and severity of the defects.

In this paper, small blocks of 17-4 PH stainless steel were manufactured via extrusion-based bound powder extrusion (BPE)/atomic diffusion additive manufacturing (ADAM) technology in two different orientations. Ultrasonic bending-fatigue and uniaxial tensile tests were carried out on the test specimens prepared from the AM blocks. Specifically, a recently-introduced small-size specimen design is employed to carry out time-efficient fatigue tests. Based on the results of the testing, the stress–life (S-N) curves were created in the very high-cycle fatigue (VHCF) regime. The effects of the printing orientation on the fatigue life and tensile strength were discussed, supported by fractography taken from the specimens’ fracture surfaces. The findings of the tensile test and the fatigue test revealed that vertically-oriented test specimens had lower ductility and a shorter fatigue life than their horizontally-oriented counterparts. The resulting S-N curves were also compared against existing data in the open literature. It is concluded that the large-sized pores (which originated from the extrusion process) along the track boundaries strongly affect the fatigue life and elongation of the AM parts.

The integrity of the final printed components is mostly dictated by the adhesion between the particles and phases that form upon solidification, which is a major problem in printing metallic parts using available In-Space Manufacturing (ISM) technologies based on the Fused Deposition Modeling (FDM) methodology. Understanding the melting/solidification process helps increase particle adherence and allows to produce components with greater mechanical integrity. We developed a phase-field model of solidification for binary alloys. The phase-field approach is unique in capturing the microstructure with computationally tractable costs. The developed phase-field model of solidification of binary alloys satisfies the stability conditions at all temperatures. The suggested model is tuned for Ni-Cu alloy feedstocks. We derived the Ginzburg-Landau equations governing the phase transformation kinetics and solved them analytically for the dilute solution. We calculated the concentration profile as a function of interface velocity for a one-dimensional steady-state diffuse interface neglecting elasticity and obtained the partition coefficient, k, as a function of interface velocity. Numerical simulations for the diluted solution are used to study the interface velocity as a function of undercooling for the classic sharp interface model, partitionless solidification, and thin interface.

In this paper, the phase structure, composition distribution, grain morphology, and hardness of Al6061 alloy samples made with additive friction stir deposition (AFS-D) were examined. A nearly symmetrical layer-by-layer structure was observed in the cross section (vertical with respect to the fabrication-tool traversing direction) of the as-deposited Al6061 alloy samples made with a back-and-forth AFS-D strategy. Equiaxed grains were observed in the region underneath the fabrication tool, while elongated grains were seen in the "flash region" along the mass flow direction. No clear grain size variance was discovered along the AFS-D build direction except for the last deposited layer. Grains were significantly refined from the feedstock (~163.5 µm) to as-deposited Al6061 alloy parts (~8.5 µm). The hardness of the as-fabricated Al6061 alloy was lower than those of the feedstock and their heat-treated counterparts, which was ascribed to the decreased precipitate content and enlarged precipitate size.

A thermodynamic model was developed and validated to analyze a high-performance solid oxide fuel cell and gas turbine (SOFC-GT) hybrid power system for electric aviation. This study used a process simulation software package (ProMax) to study the role of SOFC design and operation on the feasibility and performance of the hybrid system. Standard modules, including compressor, turbine, heat exchanger, reforming reactor, and combustor were used from the ProMax tool suite while a custom module was created to simulate the SOFC stack. The model used an SOFC test data set as an input. Additional SOFC stack performance effects, such as pressure, temperature, and utilization of air and fuel, were added from open source data. System performance predictors were SOFC specific power, fuel-to-electricity conversion efficiency, and hybrid system efficiency. Using these input data and predictors, a static thermodynamic performance model was created that can be modified for different system configurations and operating conditions. Prior to creating the final aircraft performance model, initial demonstration models were developed to validate output results. We used the NASA SOFC model as a benchmark, which was created with their Numerical Propulsion System Simulator (NPSS) software framework. Our output results matched within 1% of both the NASA model and open source SOFC performance data. With confidence gained in the accuracy of this model, a 1-MW SOFC-GT hybrid power system was constructed for an aircraft propulsion concept. Overall hybrid system efficiencies of > 75% FTE were observed during standard 36,000 feet cruise flight conditions.

Aluminum alloys are among the top candidate materials for in-space manufacturing (ISM) due to their lightweight and relatively low melting temperature. A fundamental problem in printing metallic parts using available ISM methods, based on the fused deposition modeling (FDM) technique, is that the integrity of the final printed components is determined mainly by the adhesion between the initial particles. Engineering the surface melt can pave the way to improve the adhesion between the particles and manufacture components with higher mechanical integrity. Here, we developed a phase-field model of surface melting, where the surface energy can directly be implemented from the experimental measurements. The proposed model is adjusted to Al 7075-T6 alloy feedstocks, where the surface energy of these alloys is measured using the sessile drop method. Effect of mechanics has been included using transformation and thermal strains. The effect of elastic energy is compared here with the corresponding cases without mechanics. Two different geometric samples (cylindrical and spherical) are studied, and it is found that cylindrical particles form a more disordered structure upon size reduction compared to the spherical samples.

Currently, no commercial aluminum 7000 series filaments are available for making aluminum parts using fused deposition modeling (FDM)-based additive manufacturing (AM). The key technical challenge associated with the FDM of aluminum alloy parts is consolidating the loosely packed alloy powders in the brown-body, separated by thin layers of surface oxides and polymer binders, into a dense structure. Classical pressing and sintering-based powder metallurgy (P/M) technologies are employed in this study to assist the development of FDM processing strategies for making strong Al7075 AM parts. Relevant FDM processing strategies, including green-body/brown-body formation and the sintering processes, are examined. The microstructures of the P/M-prepared, FDM-like Al7075 specimens are analyzed and compared with commercially available FDM 17-4 steel specimens. We explored the polymer removal and sintering strategies to minimize the pores of FDM-Al7075-sintered parts. Furthermore, the mechanisms that govern the sintering process are discussed.

The application of additively manufactured (AM) stainless steel (SS) parts is rapidly emerging in a broad spectrum of industries. Laser powder bed fusion (LPBF) and direct laser deposition (DLD) are the main AM methods to fabricate a vast range of SSs like 316 L, AISI 420, 17-4 PH, 304 L, and AISI 4135. This article focuses on the corrosion performance of additively manufactured stainless steel parts made by LPBF and DLD. The passive film formation mechanisms and the corrosion performance of LPBF/DLD AM SS parts are discussed in comparison to their conventionally made counterparts. Microstructural features like porosity, inclusions, residual stress, surface roughness, elemental segregation, phases, and grain size distribution are elaborated thoroughly from the corrosion point of view, closely linked with the AM processing parameters. Generally, process parameters play an important role in the corrosion properties of AM parts by impacting the microstructural features. Assuming a proper set of parameters for the printing process, the overall corrosion performance of AM SS is better than its conventional counterparts. However, there are still controversies around some important aspects such as passive film structure, the nature of residual stress, post heat treatment processes, and grain size distribution and their impact on corrosion performance, which emphasizes the need for future studies in this area.

The effect of aging processes on the tensile properties of C-18150 copper alloy samples, made by laser powder-bed-fusion additive manufacturing (AM) process with three different fabrication orientations (horizontal, angled, and vertical to the build direction), are investigated. For the as-fabricated C-18150 AM parts, horizontal and angled fabrication directions result in marginally better tensile strengths and much improved strain-to-failure values than those of vertically built AM parts. After the aging treatment, tensile strength can be significantly enhanced with a sacrifice of the strain-to-failure value. Moreover, the highest tensile strength is achieved by treating the as-fabricated samples at an aging temperature of 500 °C for 2 h. At 800 °F (427 °C), both tensile strength and ductility are smaller than low temperature values (room temperature and 400 °F/ 204 °C). Phase constituents, microstructure, and composition distribution of the AM parts are characterized to gain insight into the measured tensile properties.

With the steep growth of metal Additive Manufacturing (or 3D printing), evaluating and fine-tuning its fabrication process has become a crucial part of its development. Mapping of elastic properties of additively manufactured samples was successfully performed with the highly adaptable Resonant Ultrasound Spectroscopy technique. The general method used so far for elastic moduli measurements of additively manufactured alloys (stress-strain tensile testing) only allows the finding of the Young's modulus, and that, with moderate accuracy. Here, we report on elastic constants of additively manufactured Ti64 and CL 80CU alloys measured with resonant ultrasound. The moduli found are generally slightly lower than those for their wrought version. As expected, the elastic properties are more or less uniform within a given volume, depending on the fabrication parameters or location with respect of the build direction. The behavior of the alloys with heat treatment and proton irradiation was also tested and will be reported elsewhere.

The effects of thermal history on the thermal properties of C-18150 (Cu-1.5Cr-0.5Zr, wt%) parts made by the laser powder-bed-fusion (L-PBF) additive manufacturing (AM) process with three different fabrication orientations (horizontal, angled, and vertical to the build direction) were investigated. A significant difference in thermal properties between as-fabricated and fully heat-treated L-PBF C-18150 samples was observed, and the mechanisms of such behaviors are discussed. (C) 2021 Society of Manufacturing Engineers (SME). Published by Elsevier Ltd. All rights reserved.

In this paper, titanium nitrides were produced on commercially pure titanium samples by laser nitriding processes, with the goal of improving bio-compatibility and corrosion resistance. To identify the critical set of laser nitriding processing parameters (a combination of both laser scanning parameters and the N2 content processing gas), mouse MLO-Y4 cells were utilized for bio-compatibility evaluation, and simulated body fluid was used for electrochemical behavior examination to characterize corrosion performance. The modified surfaces were also characterized with scanning electron microscope, X-ray diffraction, and nano-indentation techniques to reveal the connections between the bio-compatibility/corrosion resistance performance and the nitrided layer composition, thickness, and surface roughness. For improved bio-compatibility and corrosion resistance performance, a dense and thick titanium-nitride dendritic layer is desirable, which can be formed in a pure N2 environment, together with a high laser energy density.

With the advent of metal Additive Manufacturing (AM), or 3D printing, the focus on evaluating and fine-tuning the fabrication process has become crucial. High-resolution volumetric mapping of elastic properties throughout an AM built sample can be done, “biopsy” style, with the highly adaptable Resonant Ultrasound Spectroscopy (RUS) technique. We report results of elastic constants measurements on AM-fabricated Ti64 and CL 80CU bronze (i.e., Cu0.9Sn0.1) alloy with RUS. Despite an easily observable pore distribution, surprisingly sharp spectra and good RUS fits were obtained for both. The average E and G moduli obtained for AM Ti64 at room temperature are ≈104 and ≈39.4 GPa, respectively. The values are only a few percent lower than those of the traditionally manufactured alloy. Moreover, stress-strain measurements on dog-bone samples of Ti64 from the sample batch lead to a value of 101 GPa for E. Heat-treatment of as-manufactured Ti64 samples lead to a slight increase in both moduli. For the investigated bronze, an ≈10% variation of elastic properties within a cross section of a printed sample was observed. The average E and G moduli obtained for AMCL 80CU bronze at room temperature are ≈111 and ≈40.9 GPa, respectively.

Alloy parts fabricated by the selected laser melting (SLM) additive manufacturing process generally contain many defects. Non-destructive Positron Annihilation Lifetime Spectroscopy (PALS) measurements were applied to evaluate these defects. The two -component positron lifetime method was used to analyze the evolution of two types of defects, mono -vacancy and vacancy cluster. Stainless steel 316 SLM samples were prepared using two sets of SLM processing parameters. For SLM samples, the temperature effect of heat treatment was examined by PALS. The effect of plastic deformation is also examined using PALS.

Current parabolic trough receiver tubes are evacuated and operate at temperatures below 400°C. Manufacturing and maintaining evacuated tube receivers over an expected 30-year lifetime is costly, and complex. In addition, their temperature limitations affect plant cycle efficiency. In this project a novel low cost non-evacuated and thermally insulated receiver tube is field tested for thermal capacitance and optical efficiency. Three measurements of temperature were takine for the thermal capacitance test resulting in a heat loss of 0.6kW at 10oC and 1.2kW at 20°C. Ten optical efficiency tests were performed, and the mean was found to be 78.3% with a standard deviation of 1.37%.

•As-fabricated AM Ti samples have deteriorated corrosion behavior.•Post heat treatment improves the corrosion behavior of AM Ti alloy parts.•Post heat treatment results in stress relief of Ti AM parts and formation of a BCC phase.•AM coupled with post heat treatment produces Ti AM parts with acceptable corrosion behavior.

An accurate estimate of fixed operating costs is essential to determine the financial viability of any proposed project. Although other researchers have reported maintenance costs for large-scale concentrating solar power (CSP) plants in the United States [1 - 2], there is currently little information available specifically for small-scale CSP or solar Industrial Process Heat (IPH) plants. This paper discusses the maintenance of an operating small-scale CSP plant in Louisiana over a four year period. The results are also applicable to a small-scale IPH plant. Maintenance activities and costs are discussed for the collector field, the power block, and the cooling tower. For the collector field, a study of the degradation of mirror reflectance between washings was performed for three different types of reflective polymer thin films (3M 1100, 3M 2020, and Konica Minolta). Overall, the 3M 2020 film provided better reflectivity between washings than the other films. An optimized mirror washing schedule was determined. Optimal mirror washing schedules are very site-dependent, but for this humid subtropical location, the most economical washing schedule was found to be every 114 days, or approximately three times per year. A recommended maintenance plan for small-scale CSP and IPH plants is presented and actual maintenance costs over a four year period are provided. It was found that maintenance costs for small-scale plants are substantially larger than for large-scale plants, and that maintenance costs for small-scale IPH plants are much lower than for small-scale CSP plants, making IPH applications significantly more attractive. The average annual maintenance cost for a small-scale CSP plant was found to be approximately $457/kWe, or $0.27/kWhe. For a small-scale IPH plant the costs were $3.72/m2, $7.81/kWt, and $0.005/kWht.