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DOE OSTI2023

In situ embedment of type K sheathed thermocouples with directed energy deposition

Advanced nuclear reactor systems require new technologies for heat transfer and system monitoring. Additive manufacturing (AM) offers the design flexibility to allow in-situ sensor embedment through smart manufacturing for real-time monitoring, and performance of these systems. Here, this study focuses on experiments investigating the feasibility of in-situ sensor embedment using directed energy deposition (DED). Type K thermocouples are embedded into 316L stainless steel (SS) samples using two different configurations (e.g., exposed and embedded tips) and two designs (e.g., flush to substrate) within an AM base. Embedded sensor samples are analyzed via in-situ measurements and high-temperature performance validation tests at 350ºC and 900ºC. Temperature performance results at both temperature tests show good agreement with manufacturer specifications proving that these sensors could still capture accurate temperature readings after in-situ embedment during DED processing. An additional optimization experiment was conducted on the exposed tip configuration using a surrogate thermocouple to improve tolerances and the embedment process. Results improved tolerances, lower porosity, smaller gaps between the sensor and base, and better junction contact for the sensor. Although further optimization of this embedment strategy is necessary to improve the structural stability and tolerances within the component, this research strategy provides a proof-of-feasibility for DED embedment with commercial sheathed thermocouples. This research provides early impact on embedment of sensor for multiple materials and complex geometric components..

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Optimization of the Observing Cadence for the Rubin Observatory Legacy Survey of Space and Time: A Pioneering Process of Community-focused Experimental Design

Vera C. Rubin Observatory is a ground-based astronomical facility under construction, a joint project of the National Science Foundation and the U.S. Department of Energy, designed to conduct a multipurpose 10 yr optical survey of the Southern Hemisphere sky: the Legacy Survey of Space and Time. Significant flexibility in survey strategy remains within the constraints imposed by the core science goals of probing dark energy and dark matter, cataloging the solar system, exploring the transient optical sky, and mapping the Milky Way. The survey’s massive data throughput will be transformational for many other astrophysics domains and Rubin’s data access policy sets the stage for a huge community of potential users. To ensure that the survey science potential is maximized while serving as broad a community as possible, Rubin Observatory has involved the scientific community at large in the process of setting and refining the details of the observing strategy. The motivation, history, and decision-making process of this strategy optimization are detailed in this paper, giving context to the science-driven proposals and recommendations for the survey strategy included in this Focus Issue.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRSDate not supplied

Selection of Alternator Voltage for Dynamic Radioisotope Power Systems

In this paper, we present a study to select an appropriate alternator voltage of the free-piston Stirling convertors (FPSC) for efficient and light Dynamic Radioisotope Power Systems (DRPS). With a system thermal-to-electrical efficiency 3-4 times greater than radioisotope thermoelectric generator (RTG) systems and a higher power density than Brayton systems in the power range of interest for radioisotope-powered systems, Stirling-based DRPS is uniquely suited to benefit upcoming NASA missions. Much effort has been invested in the design and optimization of the thermal, mechanical, and materials aspects of FPSCs, but the electrical aspect has been more nebulous. Therefore, in this paper, a preliminary study will be presented to select the appropriate Stirling alternator voltage to develop a light and efficient system using available flight components. Power conversion systems face a trade between efficiency and system volume/mass with the optimal trade being determined by the application. Neglecting non-idealities related to insulation thickness and winding packing factor and assuming a constant winding area, alternator efficiency is independent of alternator voltage. Because wire size and alternator current can be traded against turn count and alternator voltage without impacting efficiency, the guidance on the optimal design comes from analysis of the controller power electronics and the remainder of the system. Properties of available flight-qualified electrical components, such as rated voltage/current and on-resistance, typically come in discrete values instead of a continuous range of values. With multiple components being required to form the power conversion stage of the controller, each limited to incremental values, a continuous optimization is of little benefit. Instead of a continuous optimization, a random process using properties of the available components can be used to develop a Pareto design front indicating the optimized trade space. The most advantageous trade between system efficiency and mass for the system at hand can then be selected from the range of feasible designs. In the final paper, the design process, assumptions, and preliminary results will be presented.

Free-Piston Stirling Convertor Controller, Dynamic↗

DOE OSTI2022

Predictive Tools for Customizing Heat Treatment of Additively Manufactured Aerospace Components

Laser-bed powder fusion (LBPF) additive manufacturing is increasingly being used to produce components of complex geometries using the Ni-base superalloy Inconel 718. The composition and the microstructure of the alloy are currently well optimized for wrought components made using conventional manufacturing processes such as rolling, forging, extrusion, etc. The attractive mechanical properties of the alloy result from the underlying austenitic matrix with fine equiaxed grains, and a high density and uniform distribution of the precipitation hardening phase, γ". Heat treatment steps such as homogenization, solutioning and aging are well documented for the wrought alloy. However, when the same wrought alloy compositions are used for the additive manufacturing (AM) processes, the asprocessed microstructure is significantly different, because of the different thermal history associated with LBPF, including rapid solidification and multiple temperature excursions that lead to multiple re-melting and reheating in the solid state. Rapid solidification introduces potential non-equilibrium effects at the moving solid-liquid interfaces that impact the extent of solute segregation, as well as the morphology of the dendritic grains that form. In order to recover the target mechanical properties, AM components have to undergo post-process heat treatments. However, such heat treatments have to be custom designed for the AM process and the component geometry because of the expected vast differences in the microstructure at various locations of a component with complex geometry. The homogenization and precipitation steps should be optimized for the component so that target mechanical properties can be obtained throughout the part. The objective of this research is to utilize High Performance Computing in phase field simulations of microstructure evolution during post-processing of AM components. The physics-based modeling will be beneficial in reducing the experimental effort required for heat treatment process selection, optimization, and certification, thus leading to a significant reduction in energy consumption for AM and post-processing heat treatment. The optimization study will help identify heat treatments steps that are critical for development of a final desired microstructure with the minimum energy input. This combined with shortening of the production cycle (time-to-market) by reducing the number of failed parts (property targets), and reduction in the number of iterations for process optimization, will enable 30-40% savings in the energy costs. Phase field simulations of the degree of homogenization and the effect of local matrix composition on the nucleation and growth of competing precipitating phases were performed using the Microstructure Evolution Using Massively Parallel Phase Field Simulations code developed in-house at the Oak Ridge National Laboratory. The simulations were able to successfully capture the kinetics of nucleation and growth, and morphologies of various precipitating phases as a function of local matrix compositions and composition gradients characteristic of local microstructures arising from location-dependent variations in the thermal conditions. Future work will involve extending the simulations to a length scale consisting of multiple dendrites, so that the effect of homogenization on the coarsening of the dendrites can be simulated and used as an additional input to the optimization of the heat treatment process.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Modeling powder spreadability in powder-based processes using the discrete element method

Powder-bed fusion (PBF) processes refer to a subset of Additive Manufacturing (AM) techniques where powder is spread on the build-plate before melting (by a laser or electron beam). While PBF processes are attractive due to their ability for realizing complex structures that are either difficult or impossible to create through conventional means, the parts fabricated with these techniques can exhibit defects such as pores, inclusions, and excessive surface roughness. To minimize these defects, much research has been dedicated towards process maturation by optimizing laser or electron beam parameters. However, these developmental efforts typically do not address the recoating process where achieving dense and uniform layers of powder is a necessity for ensuring process repeatability and part quality. While the recoating process can be studied through experimentation, the dynamics of particle movement are difficult to analyze experimentally. Therefore, here, in this study, powder spreading in PBF was simulated through the Discrete Element Method (DEM) to elucidate the mechanisms that control powder-bed quality. Utilizing the Buckingham Pi theorem, a dimensionless metric referred to as the spreading index is developed that combines powder-bed density, roughness, and particle size to assess the quality of powder layers. The formulated spreading index is then related to several dimensionless quantities that provide insight into the mechanisms dominating powder spreading in PBF. The DEM simulations conducted in this work focused on the scenario where powder is spread onto an existing powder bed and revealed that a reduction in the recoating velocity causes an increase in the spreading index while little to no impact on the spreading index was observed when varying layer thickness from 30 μm to 75 μm.Particle size effects on the powder-bed quality were also investigated.

36 MATERIALS SCIENCE↗

NASA NTRS1993

Development of methodologies for the estimation of thermal properties associated with aerospace vehicles

Thermal stress analyses are an important aspect in the development of aerospace vehicles such as the National Aero-Space Plane (NASP) and the High-Speed Civil Transport (HSCT) at NASA-LaRC. These analyses require knowledge of the temperature within the structures which consequently necessitates the need for thermal property data. The initial goal of this research effort was to develop a methodology for the estimation of thermal properties of aerospace structural materials at room temperature and to develop a procedure to optimize the estimation process. The estimation procedure was implemented utilizing a general purpose finite element code. In addition, an optimization procedure was developed and implemented to determine critical experimental parameters to optimize the estimation procedure. Finally, preliminary experiments were conducted at the Aircraft Structures Branch (ASB) laboratory.

Scott, Elaine P.↗

NASA NTRS2009

NASA Tech Briefs, March 2009

Topics covered include: Improved Instrument for Detecting Water and Ice in Soil; Real-Time Detection of Dust Devils from Pressure Readings; Determining Surface Roughness in Urban Areas Using Lidar Data; DSN Data Visualization Suite; Hamming and Accumulator Codes Concatenated with MPSK or QAM; Wide-Angle-Scanning Reflectarray Antennas Actuated by MEMS; Biasable Subharmonic Membrane Mixer for 520 to 600 GHz; Hardware Implementation of Serially Concatenated PPM Decoder; Symbolic Processing Combined with Model-Based Reasoning; Presentation Extensions of the SOAP; Spreadsheets for Analyzing and Optimizing Space Missions; Processing Ocean Images to Detect Large Drift Nets; Alternative Packaging for Back-Illuminated Imagers; Diamond Machining of an Off-Axis Biconic Aspherical Mirror; Laser Ablation Increases PEM/Catalyst Interfacial Area; Damage Detection and Self-Repair in Inflatable/Deployable Structures; Polyimide/Glass Composite High-Temperature Insulation; Nanocomposite Strain Gauges Having Small TCRs; Quick-Connect Windowed Non-Stick Penetrator Tips for Rapid Sampling; Modeling Unsteady Cavitation and Dynamic Loads in Turbopumps; Continuous-Flow System Produces Medical-Grade Water; Discrimination of Spore-Forming Bacilli Using spoIVA; nBn Infrared Detector Containing Graded Absorption Layer; Atomic References for Measuring Small Accelerations; Ultra-Broad-Band Optical Parametric Amplifier or Oscillator; Particle-Image Velocimeter Having Large Depth of Field; Enhancing SERS by Means of Supramolecular Charge Transfer; Improving 3D Wavelet-Based Compression of Hyperspectral Images; Improved Signal Chains for Readout of CMOS Imagers; SOI CMOS Imager with Suppression of Cross-Talk; Error-Rate Bounds for Coded PPM on a Poisson Channel; Biomorphic Multi-Agent Architecture for Persistent Computing; and Using Covariance Analysis to Assess Pointing Performance.

Source record↗

DOE OSTI2025

Active oversight and quality control in standard Bayesian optimization for autonomous experiments

The fusion of experimental automation and machine learning has catalyzed a new era in materials research, prominently featuring Gaussian Process (GP) Bayesian Optimization (BO) driven autonomous experiments. Here we introduce a Dual-GP approach that enhances traditional GPBO by adding a secondary surrogate model to dynamically constrain the experimental space based on real-time assessments of the raw experimental data. This Dual-GP approach enhances the optimization efficiency of traditional GPBO by isolating more promising space for BO sampling and more valuable experimental data for primary GP training. We also incorporate a flexible, human-in-the-loop intervention method in the Dual-GP workflow to adjust for unanticipated results. We demonstrate the effectiveness of the Dual-GP model with synthetic model data and implement this approach in autonomous pulsed laser deposition experimental data. This Dual-GP approach has broad applicability in diverse GPBO-driven experimental settings, providing a more adaptable and precise framework for refining autonomous experimentation for more efficient optimization.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Engine Combustion System Optimization Using Computational Fluid Dynamics and Machine Learning: A Methodological Approach

Gasoline compression ignition (GCI) engines are considered an attractive alternative to traditional spark-ignition and diesel engines. Here, a Machine Learning-Grid Gradient Ascent (ML-GGA) approach was developed to optimize the performance of internal combustion engines. ML offers a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. The developed ML-GGA model was compared with a recently developed Machine Learning-Genetic Algorithm (ML-GA). Detailed investigations of optimization solver parameters and variable limit extension were performed in the present ML-GGA model to improve the accuracy and robustness of the optimization process. Detailed descriptions of the different procedures, optimization tools, and criteria that must be followed for a successful output are provided here. The developed ML-GGA approach was used to optimize the operating conditions (case 1) and the piston bowl design (case 2) of a heavy-duty diesel engine running on a gasoline fuel with a research octane number (RON) of 80. The ML-GGA approach yielded >2% improvements in the merit function, compared with the optimum obtained from a thorough computational fluid dynamics (CFD) guided system optimization. The predictions from the ML-GGA approach were validated with engine CFD simulations. This study demonstrates the potential of ML-GGA to significantly reduce the time needed for optimization problems, without loss in accuracy compared with traditional approaches.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRSDate not supplied

Small Particle Glovebox Experiments - Preliminary Results

A substantial portion of the asteroid samples returned by the HAYABUSA2 and OSIRIS-REx missions will consist of small (submm) components (due to the collection of those particles on the asteroid surface and due to the fragmenting of larger, friable material post-collection). In order to minimize the alteration/oxidation of asteroid regolith, the bulk collections will be stored and curated in nitrogen purged gloveboxes. The processing of small particles in an N2 glovebox will present challenges that are different from those experienced during lunar and meteorite sample processing. Particles in this size range are susceptible to unpredictable electrostatic charging that can result in sample loss during processing operations. Methods for the handling of sub-mm particles have been well developed for environments with ambient atmospheric conditions and relative humidity (RH) ranges between 40-70%. In such conditions, a number of factors can be successfully employed to minimize the effects of triboelectric charging, including the use of Po-210 sources that neutralize excess charge and the utilization of conductive manipulation tools and sample substrates. However, relative humidity levels above 40% also contribute significantly to dissipation of triboelectric effects. We had not previously investigated our charge mitigation methods in a completely dry, nitrogen-purged environment, or whether they would be sufficient in enabling the successful processing of sub-mm samples. Current glovebox configurations in use in our lunar and meteorite curation laboratories are optimized for the processing of macroscopic samples and tools; these glovebox designs are likely unsuitable for the processing of collections for which the bulk collection is comprised of sub-mm components. Small particle sample preparation requires the use of an optical magnification instrument – typically a stereo binocular microscope with at least 20x magnification. Current glovebox designs are not optimized for the utilization or integration of stereo microscopes; while many current cabinets include microscope viewports that enable the use of small, externally mounted stereo microscopes, the focusing methods (usually involving the use of a lab jack) lack the fidelity and precision required for small particle manipulation and imaging. Working distances of higher (>50x magnification) objective lenses may preclude the external use of a stereo microscope through a viewport; in order to successfully manipulate and image very small (< 20m) particles, stereo and digital microscope systems that are integrated within the glovebox should be investigated. Finally, ergonomic considerations for small particle work within a glovebox must be considered to minimize risk of injury to sample processors. In order to investigate some of the unknown parameters relating to small particle processing within an N2 glovebox, we conducted preliminary, qualitative experiments utilizing a small lunar cabinet that was originally used for film development.

C. J. Snead↗

DOE OSTI2024

The Critical Influence of Spin–Dry Technique on the Surface Passivation Quality of Crystalline Silicon Solar Cell Structures

This study examines the effects of spin-dry (SD) and N 2 blow-dry (ND) techniques on the quality and surface passivation performance of silicon oxide grown in ozone-dissolved deionized water. The SD method achieves greater oxide thickness uniformity, averaging 1.39 nm ± 4.17% across 49 points, compared to 1.68 nm ± 21.67% for the ND wafers. However, persistently poor passivation of ozonated oxide-grown wafers following the SD process is exhibited, with carrier lifetime, τ eff < 0.3 ms and saturation current density, J 0 (per side) ranging from 26 to 45 fA cm 2 . These findings are analyzed in the context of the fundamental phenomena involved in the drying processes of both techniques. Following this, an optimized spin-drying process is developed, resulting in improved τ eff and J 0 values of 1.4 ms and 5.6 fA cm –2 , respectively. Scanning electron microscopy further confirms that the oxide films dried with the enhanced SD technique are free of pinholes.

14 SOLAR ENERGY↗

NASA NTRS1992

Infrared readout electronics; Proceedings of the Meeting, Orlando, FL, Apr. 21, 22, 1992

The present volume on IR readout electronics discusses cryogenic readout using silicon devices, cryogenic readout using III-V and LTS devices, multiplexers for higher temperatures, and focal-plane signal processing electronics. Attention is given to the optimization of cryogenic CMOS processes for sub-10-K applications, cryogenic measurements of aerojet GaAs n-JFETs, inP-based heterostructure device technology for ultracold readout applications, and a three-terminal semiconductor-superconductor transimpedance amplifier. Topics addressed include unfulfilled needs in IR astronomy focal-plane readout electronics, IR readout integrated circuit technology for tactical missile systems, and radiation-hardened 10-bit A/D for FPA signal processing. Also discussed are the implementation of a noise reduction circuit for spaceflight IR spectrometers, a real-time processor for staring receivers, and a fiber-optic link design for INMOS transputers.

Fossum, Eric R.↗

NASA NTRS2002

Use of High Fidelity Methods in Multidisciplinary Optimization-A Preliminary Survey

Multidisciplinary optimization is a key element of design process. To date multidiscipline optimization methods that use low fidelity methods are well advanced. Optimization methods based on simple linear aerodynamic equations and plate structural equations have been applied to complex aerospace configurations. However, use of high fidelity methods such as the Euler/ Navier-Stokes for fluids and 3-D (three dimensional) finite elements for structures has begun recently. As an activity of Multidiscipline Design Optimization Technical Committee (MDO TC) of AIAA (American Institute of Aeronautics and Astronautics), an effort was initiated to assess the status of the use of high fidelity methods in multidisciplinary optimization. Contributions were solicited through the members MDO TC committee. This paper provides a summary of that survey.

Guruswamy, Guru P.↗

NASA NTRS2003

Search-based optimization

The problem of determining the minimum cost hypothetical ancestral sequences for a given cladogram is known to be NP-complete (Wang and Jiang, 1994). Traditionally, point estimations of hypothetical ancestral sequences have been used to gain heuristic, upper bounds on cladogram cost. These include procedures with such diverse approaches as non-additive optimization of multiple sequence alignment, direct optimization (Wheeler, 1996), and fixed-state character optimization (Wheeler, 1999). A method is proposed here which, by extending fixed-state character optimization, replaces the estimation process with a search. This form of optimization examines a diversity of potential state solutions for cost-efficient hypothetical ancestral sequences and can result in greatly more parsimonious cladograms. Additionally, such an approach can be applied to other NP-complete phylogenetic optimization problems such as genomic break-point analysis. c2003 The Willi Hennig Society. Published by Elsevier Science (USA). All rights reserved.

Non-NASA Center↗

NASA NTRS2013

Reliability of CCGA 1152 and CCGA 1272 Interconnect Packages for Extreme Thermal Environments

Ceramic column grid array (CCGA) packages have been increasing in use based on their advantages of high interconnect density, very good thermal and electrical performance, and compatibility with standard surface-mount packaging assembly processes. CCGA packages are used in space applications such as in logics and microprocessor functions, telecommunications, flight avionics, and payload electronics. As these packages tend to have less solder joint strain relief than leaded packages, the reliability of CCGA packages is very important for short- and long-term space missions. Certain planetary satellites require operations of thermally uncontrolled hardware under extremely cold and hot temperatures with large diurnal temperature change from day to night. The planetary protection requires the hardware to be baked at +125 C for 72 hours to kill microbugs to avoid any biological contamination, especially for sample return missions. Therefore, the present CCGA package reliability research study has encompassed the temperature range of 185 to +125 C to cover various NASA deep space missions. Advanced 1152 and 1272 CCGA packaging interconnects technology test hardware objects have been subjected to ex treme temperature thermal cycles from 185 to +125 C. X-ray inspections of CCGA packages have been made before thermal cycling. No anomalous behavior and process problems were observed in the x-ray images. The change in resistance of the daisy-chained CCGA interconnects was measured as a function of increasing number of thermal cycles. Electrical continuity measurements of daisy chains have shown no anomalies, even until 596 thermal cycles. Optical inspections of hardware have shown a significant fatigue for CCGA 1152 packages over CCGA 1272 packages. No catastrophic failures have been observed yet in the results. Process qualification and assembly are required to optimize the CCGA assembly processes. Optical inspections of CCGA boards have been made after 258 and 596 thermal cycles. Corner columns have started showing significant fatigue per optical inspection results.

Ramesham, Rajeshuni↗

NASA NTRS2001

Optimization of Training Sets for Neural-Net Processing of Characteristic Patterns from Vibrating Solids

Artificial neural networks have been used for a number of years to process holography-generated characteristic patterns of vibrating structures. This technology depends critically on the selection and the conditioning of the training sets. A scaling operation called folding is discussed for conditioning training sets optimally for training feed-forward neural networks to process characteristic fringe patterns. Folding allows feed-forward nets to be trained easily to detect damage-induced vibration-displacement-distribution changes as small as 10 nm. A specific application to aerospace of neural-net processing of characteristic patterns is presented to motivate the conditioning and optimization effort.

Decker, Arthur J.↗

DOE OSTI2024

Integrated Technology for Cost-Effective CO2 Capture and Formic Acid Production: Modeling, Optimization, and Economic Analysis

A novel reactive technology is being investigated that electrochemically converts CO2 into valuable chemicals, particularly formic acid. This work focuses on identifying the optimal design and operation of an integrated membrane-based CO2 capture unit with the electrochemical conversion process. In this setup, the CO2 in the flue gas permeates through a CO2-selective membrane and enters an electrolyzer to produce formic acid, creating an integrated reaction module. To refine the chemical product, gas products from the electrolyzer are directed to a pressure swing adsorption unit, while the liquid product undergoes refinement to achieve commercial-grade formic acid using reactive distillation. A membrane CO2 capture model and an electrochemical conversion model have been developed using the IDAES Integrated Platform (Institute for the Design of Advanced Energy System), facilitating rigorous flowsheet modeling and process design and optimization.

Wang, Maojian↗

DOE OSTI2024

Department of Energy/IDEA: More best-practices research

This article continues the overview of the U.S. Department of Energy and IDEA collaboration by highlighting additional case studies that demonstrate innovative engineering approaches in district energy systems. It focuses on how campuses are improving efficiency, integrating advanced technologies, and reducing energy use and emissions through data-driven strategies. The University of Cincinnati is featured for its highly efficient chilled water system, using advanced algorithms and upgraded “smart chillers” to optimize performance, reduce energy consumption, and lower costs. Wake Forest University emphasizes a data-informed modernization process, using system optimization and targeted building improvements to significantly boost efficiency and reduce overall energy use. Arizona Western College showcases creative solutions to extreme cooling demands, including system redesign, smart controls, and thermal storage to improve reliability and cut peak energy costs. Overall, the article demonstrates that combining innovative engineering, real-time data analysis, and system optimization can significantly enhance performance, reduce emissions, and deliver cost savings in district energy systems.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗