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At least 433 records · Page 24

All sources NASA NTRS DOE OSTI

NASA NTRS2015

Optimization of a Wcl6 CVD System to Coat UO2 Powder with Tungsten

In order to achieve deep space exploration via Nuclear Thermal Propulsion (NTP), Marshall Space Flight Center (MSFC) is developing W-UO2 CERMET fuel elements, with focus on fabrication, testing, and process optimization. A risk of fuel loss is present due to the CTE mismatch between tungsten and UO2 in the W-60vol%UO2 fuel element, leading to high thermal stresses. This fuel loss can be reduced by coating the spherical UO2 particles with tungsten via H2/WCl6 reduction in a fluidized bed CVD system. Since the latest incarnation of the inverted reactor was completed, various minor modifications to the system design were completed, including an inverted frit sublimer. In order to optimize the parameters to achieve the desired tungsten coating thickness, a number of trials using surrogate HfO2 powder were performed. The furnace temperature was varied between 930 C and 1000degC, and the sublimer temperature was varied between 140 C and 200 C. Each trial lasted 73-82 minutes, with one lasting 205 minutes. A total of 13 trials were performed over the course of three months, two of which were re-coatings of previous trials. The powder samples were weighed before and after coating to roughly determine mass gain, and Scanning Electron Microscope (SEM) data was also obtained. Initial mass results indicated that the rate of layer deposition was lower than desired in all of the trials. SEM confirmed that while a uniform coating was obtained, the average coating thickness was 9.1% of the goal. The two re-coating trials did increase the thickness of the tungsten layer, but only to an average 14.3% of the goal. Therefore, the number of CVD runs required to fully coat one batch of material with the current configuration is not feasible for high production rates. Therefore, the system will be modified to operate with a negative pressure environment. This will allow for better gas mixing and more efficient heating of the substrate material, yielding greater tungsten coating per trial.

Belancik, Grace A.↗

NASA NTRSDate not supplied

Structural Sizing of a Transonic Truss-Braced Wing

Accurate finite element modeling (FEM) is a vital part of the modern aircraft design process. As aircraft become increasingly complex, the time-consuming nature of detailed FEM approaches comes at a significant cost to program timeline and budget. In an effort produce modeling efforts that are sufficiently accurate and minimally costly, a proposed FEM approach and optimization scheme for a composite aircraft is explored, including a discussion of the manufacturing constraints of a highly tailored composite panel design. A high-fidelity structural model of a transonic truss-braced wing (TTBW) is generated, and the components are sized by structural optimization to satisfy buckling and strength constraints while subjected to critical maneuver loads. The structural modeling approaches and sizing of a TTBW are discussed, including details for FEM approaches, verification of an approximated FEM approach, a sizing optimization using the optimization software LS-OPT, and a manufacturing trial of integrally stiffened composite panels conducted to explore the validity of highly tailored composites as a design consideration. The results of study discussed herein indicate that the proposed FEM approach is suitable for modeling composite-construction aircraft and for use in sizing optimization. Further efforts regarding integrally stiffened composite panels will indicate the suitability of this method for the integration of highly tailored composite panels into the design and optimization process, given the manufacturability of such panels as shown here.

Finite Element↗

DOE OSTI2025

Artificial intelligence driven laser parameter search: Inverse design of photonic surfaces using greedy surrogate-based optimization

Photonic surfaces designed with specific optical characteristics are becoming increasingly crucial for novel energy harvesting and storage systems. The design of these surfaces can be achieved by texturing materials using lasers. The optimal adjustment of laser fabrication parameters to achieve target surface optical properties is an open challenge. Thus, we develop a surrogate-based optimization approach. Our framework employs the Random Forest algorithm to model the forward relationship between the laser fabrication parameters and the resulting optical characteristics. During the optimization process, we use a greedy, prediction-based exploration strategy that iteratively selects batches of laser parameters to be used in experimentation by minimizing the predicted discrepancy between the surrogate model’s outputs and the user-defined target optical characteristics. This strategy allows for efficient identification of optimal fabrication parameters without the need to model the error landscape directly. We demonstrate the efficiency and effectiveness of our approach on two synthetic benchmarks and two specific experimental applications of photonic surface inverse design targets. By calculating the average performance of our algorithm compared to other state of the art optimization methods, we show that our algorithm performs, on average, twice as well across all benchmarks. Additionally, a warm starting inverse design technique for changed target optical characteristics enhances the performance of the introduced approach.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1994

Aerodynamic shape optimization of a HSCT type configuration with improved surface definition

Two distinct parametrization procedures of generating free-form surfaces to represent aerospace vehicles are presented. The first procedure is the representation using spline functions such as nonuniform rational b-splines (NURBS) and the second is a novel (geometrical) parametrization using solutions to a suitably chosen partial differential equation. The main idea is to develop a surface which is more versatile and can be used in an optimization process. Unstructured volume grid is generated by an advancing front algorithm and solutions obtained using an Euler solver. Grid sensitivity with respect to surface design parameters and aerodynamic sensitivity coefficients based on potential flow is obtained using an automatic differentiator precompiler software tool. Aerodynamic shape optimization of a complete aircraft with twenty four design variables is performed. High speed civil transport aircraft (HSCT) configurations are targeted to demonstrate the process.

Thomas, Almuttil M.↗

DOE OSTI2024

Image-Based Fracture Surface Defect Characterization Methods for Additively Manufactured Ti-6Al-4V Tested in Fatigue

Abstract Fatigue initiation in additively manufactured samples/parts often occurs at processed-induced defects such as lack-of-fusion (LoF), keyhole, or other morphological/microstructural defects that have unique characteristics and measurable qualities. Attempts at identifying and minimizing such defects have utilized optimized processing conditions along with in situ and ex situ characterization that includes metallography and/or X-ray computed tomography (XCT). This paper highlights the benefits of using fracture surface analyses to detect and quantify defects that may not be detected by metallography/XCT due to sectioning and resolution limits. In addition to using manual quantification of fatigue initiating LoF and keyhole defects on fracture surfaces, image-based machine learning using convolutional neural networks such as U-Net were also used to automate the process. Statistical analyses were used to identify the extreme cases of defects that initiated and accelerated fatigue and to model the distribution of defect size and shape characteristics to distinguish the type of defect. Initial results show agreement between trained machine learning models and ground truth data in defect segmentation, and the distributions of defect characteristics are distinguishable to particular process-induced defect types.

Materials Science↗

DOE OSTI2022

Predictive process mapping for laser powder bed fusion: A review of existing analytical solutions

One of the main challenges in the laser powder bed fusion (LPBF) process is making dense and defect-free components. These porosity defects are dependent upon the melt pool geometry and the processing conditions. Power-velocity (PV) processing maps can aid in visualizing the effects of LPBF processing variables and mapping different defect regimes such as lack-of-fusion, under-melting, balling, and keyholing. This work presents an assessment of existing analytical equations and models that provide an estimate of the melt pool geometry as a function of material properties. The melt pool equations are then combined with defect criteria to provide a quick approximation of the PV processing maps for a variety of materials. Finally, the predictions of these processing maps are compared with experimental data from the literature. Here, the predictive processing maps can be computed quickly and can be coupled with dimensionless numbers and high-throughput (HT) experiments for validation. The present work provides a boundary framework for designing the optimal processing parameters for new metals and alloys based on existing analytical solutions.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Embedding thermocouples in SS316 with laser powder bed fusion

Recent advances in manufacturing technologies have enabled the fabrication of complex geometries for a wide range of applications, including the energy, aerospace, and civil sectors. The ability to integrate sensors at critical locations within these complex components during the manufacturing process could benefit process monitoring and control by reducing reliance on models to relate surface measurements to internal phenomena. This study investigated embedding thermocouples in a SS316 matrix using laser powder bed fusion. Under optimal processing conditions, embedded thermocouples were characterized post-building, finding good bonding to the matrix with no melt pool penetration to the sensing elements. Futher, the embedded thermocouple performed similarly to an identical non-embedded thermocouple during thermal testing to 500 °C with only a slight difference in response time, which was attributed to the differences in mass and the associated thermal time constants.

image analysis↗

DOE OSTI2025

Assessment of Benefits of Solid-State Advanced Manufacturing Processes for Nuclear Energy Products

The Advanced Materials and Manufacturing Technology (AMMT) program develops cross cutting technologies in support of a broad range of nuclear reactor technologies and maintains U.S. leadership in materials and manufacturing technologies for nuclear energy applications. This overall project provides the U.S. Department of Energy a critical feasibility study comparison of three solid-state processes to other AM processes, thereby providing the feasibility of the solid-state processes examined to manufacture 316H SS and ODS steel components: • Fused-filament fabrication (FFF): This work provides an initial evaluation of the impact of powder morphology and sizes on the FFF process, and the feasibility and adaptability for different material systems, to use FFF for ODS steels and 316 SS. • Shear-assisted processing and extrusion (ShAPE): Specifically for this portion of the project on ShAPE tube forming, the objectives will be to determine the feasibility to direct tube forming of high tensile strength steel tubing, specifically for ODS steel to determine the effect of the patented extrusion process on the dispersoids of the ODS material. Additionally, as often ODS powders are mechanically alloyed and therefore more platelike or angular, this feasibility was to explore the impact on the optimization process and initial feasibility of direct tube forming. • Cold spray and friction stir additive manufacturing as a stretch goal: Bulk and near net shape manufacturing processes for high-temperature, high-strength alloys are needed. Additionally, cold spray techniques can be applied in-situ at the operational level for repair and can provide multiple benefits to the nuclear industry. These tasks aim to provide information to show benefits of cold spray during the full life cycle, namely research and development, product manufacturing, and repair to mention a few key points.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRSDate not supplied

Structural Sizing of a Composite Transonic Truss-Braced Wing

Finite Element↗

NASA NTRS1976

Space stable thermal control coatings

The MOX method, i.e., the use of zinc and titanium oxalate precursors, has the distinct advantages of simple and rapid processing, and of controlled pigment particle size. The chemical identify of TiOX was determined. The Zn/Ti ratio effect on the reflectance spectra and ultraviolet irradiation stability in vacuum for Zn2TiO4 was examined. Optimized processing parameters are considered for reproducibly obtaining a pigment of the most desirable optical properties and behavior.

Harada, Y.↗

NASA NTRS1981

Defect design of insulation systems for photovoltaic modules

A defect-design approach to sizing electrical insulation systems for terrestrial photovoltaic modules is presented. It consists of gathering voltage-breakdown statistics on various thicknesses of candidate insulation films where, for a designated voltage, module failure probabilities for enumerated thickness and number-of-layer film combinations are calculated. Cost analysis then selects the most economical insulation system. A manufacturing yield problem is solved to exemplify the technique. Results for unaged Mylar suggest using fewer layers of thicker films. Defect design incorporates effects of flaws in optimal insulation system selection, and obviates choosing a tolerable failure rate, since the optimization process accomplishes that. Exposure to weathering and voltage stress reduces the voltage-withstanding capability of module insulation films. Defect design, applied to aged polyester films, promises to yield reliable, cost-optimal insulation systems.

Mon, G. R.↗

DOE OSTI2023

Exploration of superconducting multi-mode cavity architectures for quantum computing

Superconducting radio-frequency (SRF) cavities coupled to transmon circuits have proven to be a promising platform for building high-coherence quantum information processors. An essential aspect of this realization involves designing high quality factor three-dimensional superconducting cavities to extend the lifetime of quantum systems. To increase the computational capability of this architecture, we are exploring a multimode approach. This paper presents the design optimization process of a multi-cell SRF cavity to perform quantum computation based on an existing design developed in the scope of particle accelerator technology. We perform parametric electromagnetic simulations to evaluate and optimize the design. In particular, we focus on the analysis of the interaction between a nonlinear superconducting circuit known as the transmon and the cavity. This parametric design optimization is structured to serve as a blueprint for future studies on similar systems.

Reineri, Alessandro↗

DOE OSTI2023

Advanced Tritium Process Analytics and Optimization via a Digital Twin, SRNL-TR-2023-00550

Improving the process knowledge and understanding of TCAP can be achieved by incorporating advanced tools. This project addresses “Advanced analytics for modeling, forecasting, & optimization of the tritium refinement process” and is being applied to the TCAP process. The value of digitization and advanced analytics for TCAP data are tracking of gas mixtures & inventories is presently a manual effort that is rather cumbersome. Incorporating some automation into the data capture will reduce errors and storing data in an accessible database that can be used for tracking as well as process improvements. In addition, the database approach will enable longer term history to be maintained rather than the current practice of deleting data after six months. The digitized and automated data will allow for models to be developed for the process and will enable the forecasting and optimization.

Korinko, Paul S.↗

DOE OSTI2024

Part-scale microstructure prediction for laser powder bed fusion Ti-6Al-4V using a hybrid mechanistic and machine learning model

Laser powder bed fusion (LPBF) Ti-6Al-4V is widely studied for use in structural applications in aerospace and medical industries, but mechanical anisotropy and microstructural inhomogeneity prohibits its wider adoption. Although successful microstructure prediction models have been developed, a remaining challenge is their limited integration across length/time scales and validation by experimental studies. Here, this work proposes a physics-augmented machine learning surrogate model to unite predictions of LPBF temperature, β phase morphology and texture, and α/α’ formation into a single framework that is calibrated and validated with experiments. First, a phase field (PF) model of the martensitic β→α’ transformation is developed and calibrated using data from in-situ synchrotron cyclic heating/cooling studies quantifying the variation of α phase fraction with time. In parallel, an established finite difference-Monte Carlo (FDMC) model predicts the part-scale temperature profile and β grain formation during solidification. A dataset is developed using LPBF cyclic temperature descriptors from the FDMC model as inputs and corresponding α/α’ phase fraction and width from the PF model as outputs. Five machine learning (ML) regression models are tested and optimized, having mean absolute error in testing ≤ 4 %, and the k-nearest neighbors (KNN) model is selected as the best performing. The KNN model is called at the nodal level during post-processing of the FDMC model to replace and downscale the response of the PF model. The combined agility and accuracy of the hybrid FDMC-ML model enables part-scale microstructure predictions that can be further used for property predictions to accelerate AM process optimization.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Manufacturability-based optical design optimization for advanced Kirkpatrick–Baez X-ray focusing mirrors

The advanced Kirkpatrick–Baez (AKB) mirror setup is an effective and compelling solution to provide stable X-ray nano-focusing for synchrotron radiation or free-electron laser beamlines. We propose an AKB mirror design optimization approach to mitigate the difficulties associated with mirror fabrication by minimizing the total slope ranges of the four curved mirrors while achieving the expected focusing performance. In the optimization, we have considered geometry constraints to ensure the beam acceptance with the required clear aperture, the diffraction-limited focal size with the adequate numerical aperture, and the desired mirror gaps for adjustment and the necessary working distance for the sample stage. Additionally, practical constraints linked to mirror metrology and fabrication, such as mirror length limits and curvature uncertainty in measurement, are taken into account. Furthermore, progressive objective optimization eliminates the need for any initial guess, fully automating the AKB optimization process. This approach facilitates the development of an elegant Wolter-I or Wolter-III type AKB design solution that satisfies these multiple constraints. In cases where constraints cannot be simultaneously satisfied, the optimization results provide valuable insights into areas where trade-offs need to be considered. Simulations with ray tracing and wavefront propagation validate the optimized AKB design showing high tolerance to the beam incident angle.

36 MATERIALS SCIENCE↗

NASA NTRS1988

Integrated nonlinear structural analysis and design

An integrated approach to the design optimization of structures which require nonlinear analysis is proposed. The optimization process begins with a linearized structural response and the amount of nonlinearity is increased as the optimum design becomes closer. The proposed approach has the potential of reducing substantially the computational cost of the optimization. Two truss examples are used for demonstration.

Haftka, Raphael T.↗

DOE OSTI2023

Optics Studies for Multipass Energy Recovery at CEBAF: ER@CEBAF

Energy recovery linacs (ERLs), focus on recycling the kinetic energy of electron beam for the purpose of accelerating a newly injected beam within the same accelerating structure. The rising developments in the super conducting radio frequency technology, ERL technology has achieved several noteworthy milestones over the past few decades. In year 2003, Jefferson Lab has successfully demonstrated a single pass energy recovery at the CEBAF accelerator. Furthermore, they conducted successful experiments with IR-FEL demo and upgrades, as well as the UV FEL driver. This multi-pass, multi-GeV range energy recovery demonstration proposed to be carried out at CEBAF accelerator at Jefferson Lab focuses on demonstrating highest energy recovery in super conducting linac in the low-current range. Continuous electron beam accelerate up to 7.5 GeV within 5-passes and decelerate in the next 5-passes recovering RF energy and dumps at a low energy dump. The beamline optics design for recirculating linacs require special attention to avoid beam instabilities due to RF wakefields. Usually, multi-pass linac beam lines require stronger focusing at lower energies as that is necessary to avoid beam breakup (BBU) instabilities, even with this small beam current. The CEBAF linac optics optimization is focused on balancing over-focusing at higher energies and beta excursions at lower energies. The race-track-shaped geometry of CEBAF accelerator allows its linacs to accommodate multiple energy beams simultaneously, while individual recirculating arcs transporting one beam energy, are shared between accelerating/decelerating beams. For the linac optics optimization process, an extended strategy is used that is originally used in 6-pass Recirculating Linac design of the LHeC, to represent the ten passes through a single linac. Using proper mathematical expressions, linac optics optimization can be achieved with evolutionary genetic algorithms, with Multi-Objective optimization. This thesis introduces a CEBAF optics redesign tailored to accommodates the ER@CEBAF multi-pass ER scheme. The isochronous arcs were retuned to match into optics solutions for optimized 10-pass linacs. Within this work, a single bunch particle tracking analysis presented here focuses on the further improvements of the beamline and beam transportation.

Neththikumara, Isurumali↗

NASA NTRS2014

Cure Cycle Design Methodology for Fabricating Reactive Resin Matrix Fiber Reinforced Composites: A Protocol for Producing Void-free Quality Laminates

For the fabrication of resin matrix fiber reinforced composite laminates, a workable cure cycle (i.e., temperature and pressure profiles as a function of processing time) is needed and is critical for achieving void-free laminate consolidation. Design of such a cure cycle is not trivial, especially when dealing with reactive matrix resins. An empirical "trial and error" approach has been used as common practice in the composite industry. Such an approach is not only costly, but also ineffective at establishing the optimal processing conditions for a specific resin/fiber composite system. In this report, a rational "processing science" based approach is established, and a universal cure cycle design protocol is proposed. Following this protocol, a workable and optimal cure cycle can be readily and rationally designed for most reactive resin systems in a cost effective way. This design protocol has been validated through experimental studies of several reactive polyimide composites for a wide spectrum of usage that has been documented in the previous publications.

Hou, Tan-Hung↗