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At least 1,009 records · Page 56

Boiling on Microconfigured Composite Surfaces Enhanced

Boiling heat transfer is one of the key technologies for the two-phase active thermal-control system used on space platforms, as well as for the dynamic power systems aboard the International Space Station. Because it is an effective heat transfer mode, boiling is integral to many space applications, such as heat exchangers and other cooling devices. Nucleate boiling near the critical heat flux (CHF) can transport very large thermal loads with a much smaller device and much lower pumping power than for single-phase heat exchangers. However, boiling performance sharply deteriorates in a reduced-gravity environment, and operation in the CHF regime is somewhat perilous because of the risk of burnout to the device surface. New materials called microconfigured metal-graphite composites can enhance boiling. The photomicrograph shows the microconfiguration (x3000) of the copper-graphite (Cu-Gr) surface as viewed by scanning electronic microscope. The graphite fiber tips appear as plateaus with rugged surfaces embedded in the copper matrix. It has been experimentally demonstrated that this type of material manifests excellent boiling heat transfer performance characteristics and an increased CHF. Nonisothermal surfaces were less sensitive to variations of wall superheat in the CHF regime. Because of the great difference in conductivity between the copper base and the graphite fiber, the composite surfaces have a nonisothermal surface characteristic and, therefore, will have a much larger "safe" operating region in the CHF regime. In addition, the thermocapillary forces induced by the temperature differences between the fiber tips and the metal matrix play an important role in bubble detachment, and may not be adversely affected in a reduced-gravity environment. All these factors indicate that microconfigured composites may improve the reliability and economy (dominant factors in all space applications) of various thermal components found on spacecraft during future missions.

Chao, David F.↗

Real time evolution for ultracompact Hamiltonian eigenstates on quantum hardware

In this work we present a detailed analysis of variational quantum phase estimation (VQPE), a method based on real-time evolution for ground and excited state estimation on near-term hardware. We derive the theoretical ground on which the approach stands, and demonstrate that it provides one of the most compact variational expansions to date for solving strongly correlated Hamiltonians. At the center of VQPE lies a set of equations, with a simple geometrical interpretation, which provides conditions for the time evolution grid in order to decouple eigenstates out of the set of time evolved expansion states, and connects the method to the classical filter diagonalization algorithm. Further, we introduce what we call the unitary formulation of VQPE, in which the number of matrix elements that need to be measured scales linearly with the number of expansion states, and we provide an analysis of the effects of noise which substantially improves previous considerations. The unitary formulation allows for a direct comparison to iterative phase estimation. Our results mark VQPE as both a natural and highly efficient quantum algorithm for ground and excited state calculations of general many-body systems. We demonstrate a hardware implementation of VQPE for the transverse field Ising model. Further, we illustrate its power on a paradigmatic example of strong correlation (Cr2 in the SVP basis set), and show that it is possible to reach chemical accuracy with as few as ~50 timesteps.

Klymko, Katherine↗

Post-Deployment Characterization of Glass Fiber-Reinforced Thermoset and Thermoplastic Composite Tidal Turbine Blades

In 2021, the National Renewable Energy Laboratory (NREL) supported Verdant Power with the most successful tidal energy deployment in U.S. history. Three of their Gen5d 5 m turbines were deployed as part of the Roosevelt Island Tidal Energy project. Initially, the three rotors initially deployed were manufactured from glass fiber-reinforced epoxy composites. Midway through the deployment, one rotor was replaced with one manufactured at NREL. The new rotor utilized a novel infusible thermoplastic resin system. Since the deployment, one epoxy rotor and one thermoplastic rotor were returned to NREL for continued materials and manufacturing research. The two rotors underwent full-scale structural testing before being sectioned and cut into specimens for a variety of manufacturing quality tests, thermomechanical characterization, and evaluation of material performance in marine environments to understand the key differences between the fiberglass-reinforced epoxy and Elium composites used for the respective rotors. Matrix burn-off tests showed that the Elium blades had a considerably higher fiber volume fraction compared to the epoxy blades (61% vs. 49%). Environmental aging of the specimens showed that the epoxy laminates absorbed more water over the conditioning period; however, it was determined that the Elium laminates had higher diffusion coefficients, so they initially absorbed water faster. Finally, one full epoxy blade and one full Elium blade were conditioned at ambient temperatures for up to 11 months, while periodic mass measurements were taken. The datasets were extrapolated to assume a full 20-year operational life span, and it was determined that the blades would not reach full saturation during that time span.

composite manufacturing↗

The importance of maldistribution matching for thermal performance of compact heat exchangers

Compact heat exchangers have gained increased attention in recent years, particularly in demanding applications where high temperatures, high pressures, and/or high power densities are required. For decades, the heat exchanger (HX) community believes that flow maldistribution is a key factor for HX effectiveness, that is, reducing the degree of flow maldistribution (MALD) can help increase the HX effectiveness. Therefore, significant efforts have been devoted in the past to optimizing the header geometry to minimize flow maldistribution. This work was initially motivated by this, and the original goal was to figure out a HX header design with the lowest maldistribution. However, by systematically constructing a comprehensive maldistribution matrix, the analysis revealed that the HX effectiveness is not actually determined by the MALD, but instead dominated by the degree of maldistribution mismatch (MISM). This conclusion was also theoretically generalized, which indicated that matching of the local heat capacity rate is key for achieving maximum performance. The MISM provides a local means of tracking this information, while the MALD only provides a global approximation of the maldistribution itself. With this new perspective, flow maldistribution needs not necessarily be avoided, but instead matched between two fluid streams, to improve the HX performance. We demonstrated that by carefully designing the header geometry to match the velocity profiles of the two fluids in a 2 MW PCHE with molten salt and supercritical carbon dioxide (sCO2) as the heat transfer fluids, the HX could achieve a higher effectiveness even when the maldistribution increased. Finally, a technoeconomic study using a CSP system as an example revealed that the use of this new HX design paradigm could result in CSP capital cost savings as large as 16.6%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Investigation of ion irradiation effects on mineral analogues of concrete aggregates

Irradiation can cause prominent damage to reactor concrete aggregates leading to amorphization, strength and modulus decrease, radiation induced volume expansion (RIVE) and micro-cracking, which limits their long-term performance. Here, to develop an improved understanding of irradiation effects in concrete, three mineral analogues of concrete aggregates (limestone, marble and quartzite) were irradiated by 5.5 MeV He ions and 13 MeV Ni ions to surface doses of 0.011 displacements per atom (dpa) and 0.23 dpa, respectively, at room temperature. The two different ion species allow irradiation spectrum effects (ionizing and displacive) to be examined. Irradiation induced cracks were observed in He irradiated limestone and marble, and Ni irradiated quartzite. Full amorphization was observed in Ni irradiated quartzite with 14.3 % RIVE, and ∼25 % hardness and modulus decrease, while almost no change was observed in He irradiated quartzite except 4.35 % RIVE, revealing a possible ionization enhanced diffusion effect for high energy light ions. Furthermore, partial amorphization was observed in Ni irradiated marble and limestone matrix with a 12 % hardness decrease in marble while no amorphization was observed for He irradiation with a 20 % hardness increase in limestone matrix. The role of knock-on damage and irradiation spectrum on amorphization, volumetric expansion and mechanical property changes are discussed. Moreover, the onset and critical doses for amorphization and RIVE in quartz are obtained for ion irradiations at room temperature. The dose dependence of RIVE exhibits a delay compared to the amorphization behavior. The superior irradiation resistance of calcite phase compared to quartz phase implies there could be advantages to using calcareous aggregates and lowering the usage of siliceous aggregates for concrete in nuclear power plants for extended operation beyond 60 years. However, other effects such as corrosion, aging and reactions during severe accidents should also be considered, and further investigations are needed.

Amorphous↗

Structural response reconstruction using a system-equivalent singular vector basis

Here, this paper develops a novel method for reconstructing the full-field response of structural dynamic systems using sparse measurements. The singular value decomposition is applied to a frequency response matrix relating the structural response to physical loads, base motion, or modal loads. The left singular vectors form a non-physical reduced basis that can be used for response reconstruction with far fewer sensors than existing methods. The contributions of the singular vectors to measured response are termed singular-vector loads (SVLs) and are used in a regularized Bayesian framework to generate full-field response estimates and confidence intervals. The reconstruction framework is applicable to the estimation of single data records and power spectral densities from multiple records. Reconstruction is successfully performed in configurations where the number of SVLs to identify is less than, equal to, and greater than the number of sensors used for reconstruction. In a simulation featuring a seismically excited shear structure, SVL reconstruction significantly outperforms modal FRF-based reconstruction and successfully estimates full-field responses with as few as two uniaxial accelerometers. SVL reconstruction is further verified in a simulation featuring an acoustically excited cylinder. Finally, response reconstruction and uncertainty quantification are performed on an experimental structure with three shaker inputs and 27 triaxial accelerometer outputs.

42 ENGINEERING↗

Quantum-Based Molecular Dynamics Simulations Using Tensor Cores

Tensor cores, along with tensor processing units, represent a new form of hardware acceleration specifically designed for deep neural network calculations in artificial intelligence applications. Tensor cores provide extraordinary computational speed and energy efficiency but with the caveat that they were designed for tensor contractions (matrix–matrix multiplications) using only low-precision floating-point operations. Despite this perceived limitation, we demonstrate how tensor cores can be applied with high efficiency to the challenging and numerically sensitive problem of quantum-based Born–Oppenheimer molecular dynamics, which requires highly accurate electronic structure optimizations and conservative force evaluations. The interatomic forces are calculated on-the-fly from an electronic structure that is obtained from a generalized deep neural network, where the computational structure naturally takes advantage of the exceptional processing power of the tensor cores and allows for high performance in excess of 100 Tflops on a single Nvidia A100 GPU. Stable molecular dynamics trajectories are generated using the framework of extended Lagrangian Born–Oppenheimer molecular dynamics, which combines computational efficiency with long-term stability, even when using approximate charge relaxations and force evaluations that are limited in accuracy by the numerically noisy conditions caused by the low-precision tensor core floating-point operations. A canonical ensemble simulation scheme is also presented, where the additional numerical noise in the calculated forces is absorbed into a Langevin-like dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A reliable algorithm for optimal control synthesis

In recent years, powerful design tools for linear time-invariant multivariable control systems have been developed based on direct parameter optimization. In this report, an algorithm for reliable optimal control synthesis using parameter optimization is presented. Specifically, a robust numerical algorithm is developed for the evaluation of the H(sup 2)-like cost functional and its gradients with respect to the controller design parameters. The method is specifically designed to handle defective degenerate systems and is based on the well-known Pade series approximation of the matrix exponential. Numerical test problems in control synthesis for simple mechanical systems and for a flexible structure with densely packed modes illustrate positively the reliability of this method when compared to a method based on diagonalization. Several types of cost functions have been considered: a cost function for robust control consisting of a linear combination of quadratic objectives for deterministic and random disturbances, and one representing an upper bound on the quadratic objective for worst case initial conditions. Finally, a framework for multivariable control synthesis has been developed combining the concept of closed-loop transfer recovery with numerical parameter optimization. The procedure enables designers to synthesize not only observer-based controllers but also controllers of arbitrary order and structure. Numerical design solutions rely heavily on the robust algorithm due to the high order of the synthesis model and the presence of near-overlapping modes. The design approach is successfully applied to the design of a high-bandwidth control system for a rotorcraft.

Vansteenwyk, Brett↗

High density associative memory

A multi-layered, thin-film, digital memory having associative recall. There is a first memory matrix and a second memory matrix. Each memory matrix comprises, a first layer comprising a plurality of electrically separated row conductors; a second layer comprising a plurality of electrically separated column conductors intersecting but electrically separated from the row conductors; and, a plurality of resistance elements electrically connected between the row condutors and the column conductors at respective intersections of the row conductors and the column conductors, each resistance element comprising, in series, a first resistor of sufficiently high ohmage to conduct a sensible element current therethrough with virtually no heat-generating power consumption when a low voltage as employed in thin-film applications is applied thereacross and a second resistor of sufficiently high ohmage to conduct no sensible current therethrough when a low voltage as employed in thin-film applications is applied thereacross, the second resistor having the quality of breaking down to create a short therethrough upon the application of a breakdown level voltage across the first and second resistors.

Moopenn, Alexander W.↗

Engaging the Regulatory Community to Aid Environmental Consenting/Permitting Processes for Marine Renewable Energy

Regulators involved in consenting/permitting marine renewable energy (MRE) have faced multiple challenges due to relatively new, unfamiliar technologies and uncertainty surrounding potential environmental impacts. This has resulted in slow progress for the MRE industry, including long consenting timeframes and extensive and expensive monitoring requirements, which increase financial risk for investors. OES-Environmental has surveyed regulators internationally to understand their key knowledge gaps and perspectives to support the development of the MRE industry. From the results of these surveys a data transferability process and a risk retirement pathway have been developed to assess consenting and monitoring requirements in proportion to risk. A tool for discovering existing data sets by using an online matrix has been developed, along with training materials, regulatory guidance documents, and a strategic outreach plan to engage regulators and advisers. his engagement and the application of these products should lead to a better understanding of the environmental effects of marine energy, and more efficient consenting processes.

16 TIDAL AND WAVE POWER↗

Random projection using random quantum circuits

The random sampling task performed by Google's Sycamore processor gave us a glimpse of the “quantum supremacy era.” This has definitely shed some light on the power of random quantum circuits in this abstract task of sampling outputs from the (pseudo)random circuits. In this paper, we explore a practical near-term use of local random quantum circuits in dimensional reduction of large low-rank data sets. We make use of the well-studied dimensionality reduction technique called the random projection method. This method has been extensively used in various applications such as image processing, logistic regression, entropy computation of low-rank matrices, etc. We prove that the matrix representations of local random quantum circuits with sufficiently shorter depths [ ∼ O ( n ) ] serve as good candidates for random projection. We demonstrate numerically that their projection abilities are not far off from the computationally expensive classical principal components analysis on MNIST and CIFAR-100 image datasets. We also benchmark the performance of quantum random projection against the commonly used classical random projection in the tasks of dimensionality reduction of image data sets and computing von Neumann entropies of large low-rank density matrices. And finally, using variational quantum singular value decomposition, we demonstrate a near-term implementation of extracting the singular vectors with dominant singular values after quantum random projecting a large low-rank matrix to lower dimensions. All such numerical experiments unequivocally demonstrate the ability of local random circuits to randomize a large Hilbert space at sufficiently shorter depths with robust retention of properties of large data sets in reduced dimensions. Published by the American Physical Society 2024

Kumaran, Keerthi (ORCID:0009000949125721)↗

Electric-field control of spin dynamics during magnetic phase transitions

Controlling magnetization dynamics is imperative for developing ultrafast spintronics and tunable microwave devices. However, the previous research has demonstrated limited electric-field modulation of the effective magnetic damping, a parameter that governs the magnetization dynamics. Here, we propose an approach to manipulate the damping by using the large damping enhancement induced by the two-magnon scattering and a nonlocal spin relaxation process in which spin currents are resonantly transported from antiferromagnetic domains to ferromagnetic matrix in a mixed-phased metallic alloy FeRh. This damping enhancement in FeRh is sensitive to its fraction of antiferromagnetic and ferromagnetic phases, which can be dynamically tuned by electric fields through a strain-mediated magnetoelectric coupling. In a heterostructure of FeRh and piezoelectric PMN-PT, we demonstrated a more than 120% modulation of the effective damping by electric fields during the antiferromagnetic-to-ferromagnetic phase transition. Our results demonstrate an efficient approach to controlling the magnetization dynamics, thus enabling low-power tunable electronics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Validation of Robustness in TCR Design Strategies

Advanced Manufacturing (AM) has been identified as one of key pathways in accelerating deployment of next generation of nuclear power plants. The nuclear industry continues to predominately rely on fabrication techniques and materials that their codes and standards were approved decades ago. This legacy approach in the highly regulated nuclear sector has brought uncertainty to commercial viability of nuclear energy in the U.S. The Transformational Challenge Reactor (TCR), sought to utilize AM methods for fabrication of a High Temperature Gas Reactor (HTGR). The program sought to leverage AM to construct a non-conventional geometry made up of TRISO fuel and hydride moderator in SiC matrix. This project objective was to provide independent analysis of the core configuration with separate set of tools and approaches than utilized by the TCR team in a 2-year time frame. This NEUP project also tackled a question: Can AM be a cost-effective tool in changing the commercial paradigm of nuclear. We investigated this question in-context of a micro HTGR. While respecting the inherit uncertainty in our input parameters, overall we saw that AM has potential in improving economic competitiveness of nuclear energy when employed on multiple fronts (i.e. few percentage cost improvement per component). Given realizing AM requires mass orders and large R&D investment for commercial utilization, Department of Energy should focus its support on few key enabling technologies and support their codes and standards development and qualification cost (including irradiation as applicable) rather than taking a diluted approach.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Predicting viscoelastic response and delayed failures in general laminated composites

Although graphite fibers behave in an essentially elastic manner, the polymeric matrix of graphite/epoxy composites is a viscoelastic material which exhibits creep and delayed failures. The creep process is quite slow at room temperature, but may be accelerated by higher temperatures, moisture absorption, and other factors. Techniques are being studied to predict long-term behavior of general laminates based on short-term observations of the unidirectional material at elevated temperatures. A preliminary numerical procedure based on lamination theory is developed for predicting creep and delayed failures in laminated composites. A modification of the Findley nonlinear power law is used to model the constitutive behavior of a lamina. An adaptation of the Tsai-Hill failure criterion is used to predict the time-dependent strength of a lamina. Predicted creep and delayed failure results are compared with typical experimental data.

Dillard, D. A.↗

Solar generation and storage of O2 (a 1 delta g)

An investigation was performed of the technical steps required to design a solar powered oxygen-iodine laser. Singlet delta oxygen is formed upon transfer of energy from selected photoexcited dye molecules to ground state molecular oxygen and then is concentrated and stored as an endoperoxide by reaction with an aromatic hydrocarbon. The endoperoxide, when heated, releases singlet oxygen in high yield thus providing a regenerable source of laser fuel. Energy transfer from dye molecules to molecular oxygen was investigated. When dye molecules were adsorbed to polymer substrates it was observed that the dye became embedded in the polymer matrix. Porphin dyes were incorporated into films of 1,4-dimethyl-2-poly(vinylnaphthalene), 2PVN. An endoperoxide was formed when porphin-doped 2PVN was exposed to visible radiation. This demonstrates the possibility of generating singlet oxygen using solar energy and concentrating and storing it in one simple step. Transport of energy by exciton migration in polycrystalline dye films was also investigated.

Twarowski, Allen J.↗

Progress of Ongoing NASA Lithium-Ion Cell Verification Testing for Aerospace Applications

A Lithium-ion Verification and Validation Program with the purpose to assess the capabilities of current aerospace lithium-ion (Li-ion) battery cells to perform in a low-earth-orbit (LEO) regime was initiated in 2002. This program involves extensive characterization and LEO life testing at ten different combinations of depth-of-discharge, temperature, and end-of-charge voltage. The test conditions selected for the life tests are defined as part of a statistically designed test matrix developed to determine the effects of operating conditions on performance and life of Li-ion cells. Results will be used to model and predict cell performance and degradation as a function of test operating conditions. Testing is being performed at the Naval Surface Warfare Center/Crane Division in Crane, Indiana. Testing was initiated in September 2004 with 40 Ah cells from Saft and 30 Ah cells from Lithion. The test program has been expanded with the addition of modules composed of 18650 cells from ABSL Power Solutions in April 2006 and the addition of 50 Ah cells from Mine Safety Appliances Co. (MSA) in June 2006. Preliminary results showing the average voltage and average available discharge capacity for the Saft and Lithion packs at the test conditions versus cycles are presented.

McKissock, Barbara I.↗

Algorithm for Wavefront Sensing Using an Extended Scene

A recently conceived algorithm for processing image data acquired by a Shack-Hartmann (SH) wavefront sensor is not subject to the restriction, previously applicable in SH wavefront sensing, that the image be formed from a distant star or other equivalent of a point light source. That is to say, the image could be of an extended scene. (One still has the option of using a point source.) The algorithm can be implemented in commercially available software on ordinary computers. The steps of the algorithm are the following: 1. Suppose that the image comprises M sub-images. Determine the x,y Cartesian coordinates of the centers of these sub-images and store them in a 2xM matrix. 2. Within each sub-image, choose an NxN-pixel cell centered at the coordinates determined in step 1. For the ith sub-image, let this cell be denoted as si(x,y). Let the cell of another subimage (preferably near the center of the whole extended-scene image) be designated a reference cell, denoted r(x,y). 3. Calculate the fast Fourier transforms of the sub-sub-images in the central NxN portions (where N < N and both are preferably powers of 2) of r(x,y) and si(x,y). 4. Multiply the two transforms to obtain a cross-correlation function Ci(u,v), in the Fourier domain. Then let the phase of Ci(u, v) constitute a phase function, phi(u,v). 5. Fit u and v slopes to phi (u,v) over a small u,v subdomain. 6. Compute the fast Fourier transform, Si(u,v) of the full NxN cell si(x,y). Multiply this transform by the u and phase slopes obtained in step 4. Then compute the inverse fast Fourier transform of the product. 7. Repeat steps 4 through 6 in an iteration loop, cumulating the u and slopes, until a maximum iteration number is reached or the change in image shift becomes smaller than a predetermined tolerance. 8. Repeat steps 4 through 7 for the cells of all other sub-images.

Sidick, Erkin↗

Digital Twin Model for Advanced Manufacture of a Rotating Detonation Engine Injector

A digital twin material model (DTMM) of an additive manufacturing (AM) process was created to advance the state of the art in rotating detonation engine (RDE) injector design. Current RDE injectors are designed with large pressure drops, enabling a stable and repeatable combustion process. However, this comes at the cost of system efficiency. For the technology to transition to commercial fossil-based power generation, it is important to develop injectors with reduced flow losses. Low-loss injectors are difficult to design and manufacture with conventional manufacturing techniques. AM enables new design options, but the AM manufacturing process must be thoroughly understood to result in a robust design. A DTMM provides the necessary insight by defining the cause-effect relationships between process parameters, microstructure features, and properties. Therefore, a DTMM to support the design and manufacturing process was developed and applied to the design of a new additively manufactured low-loss injector. The injector combustion behavior was characterized through hot-fire tests, and mechanical performance was compared to the DTMM predictions. The two project goals were the successful development of the DTMM and the demonstration of an improved RDE injector design. The RDE injector design and DTMM developments occurred on parallel but dependent paths. The injector was designed to reduce pressure drop by increasing the cross-sectional flow area ratio between the injector air passages and the combustor annulus. This resulted in less structural material, raising the concern that thin members would be susceptible to high-cycle fatigue (HCF) under the periodic loading inherent to an RDE. It was most important for the DTMM to predict behavior in these features; therefore, the injector design concept guided the material thicknesses used in fatigue tests. The DTMM development started by manufacturing a series of coupons over the range of possible AM process variations. A design-of-experiment approach was used to select which process variable combinations gave the most efficient coverage relevant to the injector design space. The microstructure in each of these coupons was characterized, and then computational methods were used to create a numerical model of the correlation between process variables and microstructure. Next, a set of HCF samples were tested to calibrate existing models that map microstructure to HCF performance. Together, these two links formed the DTMM that calculates HCF behavior from AM process variables. Two injector prototypes were additively manufactured. The first injector design strategy aggressively pursued low-loss performance by substantially increasing the oxidizer flow area. The combination of manufacturing lead times and the fatigue testing schedule meant that the DTMM was not available when building this first prototype. Therefore, its process parameters were chosen based on a manual review of the available coupon data. This prototype was built successfully and evaluated in 58 combustion tests. Sustained detonation was achieved with remarkably reduced pressure loss, and some tests even displayed pressure loss characteristics similar to conventional gas turbine combustors. This achieved the project goal of improving RDE injector design. The second injector was manufactured according to the optimized parameters predicted by the DTMM. The flow area modifications of this injector were less aggressive than the first injector since demonstrating low pressure loss was not an objective of the second hot-fire test series. Rather, the test objective was to cause high cycle fatigue failure in the part due to periodic loading from the rotating detonation wave. The observed number of cycles to failure was to be compared to the number predicted by the DTMM and thereby assess the utility of the DTMM in component design. However, the required level of vibration was not obtained during combustion. Therefore, high cycle fatigue was not experienced in the hot-fire tests of the second injector. Fatigue data was obtained by further testing the second injector in a conventional HCF test apparatus. The injector demonstrated HCF strength above the DTMM prediction. In fact, it did not fail and testing was only discontinued due to reaching the end of the period of performance. This points to some success in the project’s primary goal of successfully developing and applying the DTMM to a component design. Implementing the DTMM recommendations for optimal processing parameters led to a part with acceptable properties. The DTMM was also shown to be an efficient correlator of data and to provide insight into the relationship between process settings, microstructure, and property performance. However, the failure of the DTMM prediction to match the experimental result of the injector fatigue test also points to the need to include significantly more data in the model development. In this project, coupons made with identical processing parameters exhibited drastically different properties from each other and from the injector part, which clearly influences the accuracy of a model that predicts performance based on parameters. Uncertainties in the build process must be quantified to develop more robust models. A denser and broader matrix of coupon process and geometry variations, several repeated builds of every point, more in-situ build process measurements, and direct observation of tensile and HCF sample microstructure (as opposed to separate microstructure specimens) are recommendations to improve future AM modeling efforts.

20 FOSSIL-FUELED POWER PLANTS↗