Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Process optimization”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Comprehensive 3D Multiphysics Model on Electrochemical Recovery of O 2 from Metabolic CO 2 at the International Space Station (ISS)

The International Space Station (ISS) is presently equipped with an elaborate, heavy, and high-power consuming system that recovers approximately 50% of O 2 from metabolic CO 2 as part of the atmospheric revitalization (AR) at the ISS habitat. Future long-duration missions will require a sustainable and efficient system capable of yielding a minimum of 75% O 2 recovery to reach the self-sufficiency required for long space missions beyond earth’s low orbit. A Macrofluidic Electrochemical Reactor (MFECR) technology development effort is currently underway at NASA Marshall Space Flight Center (MSFC) to not only increase significantly current O 2 recovery efficiency, improving self-sufficiency on AR at the ISS habitat and future long missions, but also reduce the complexity of the system. The authors have developed and deployed a comprehensive 3D multiphysics model that thoroughly replicates the actual configuration and fluid/material domains of the MFECR. The coupled physics in this multiphysics model include multicomponent-multiphase electrochemical-driven reactions, non-ideal mass transport mechanism, free and porous flow, heat transfer, CO 2 solubility on alkaline electrolyte, water condensation on porous medium, and DC electrical current generation along with Joule heating effect. This model is aimed to conduct quantitive benchmark on three different MFECR’s layouts, one without serpentine paths (plain) and two with serpentines leading to four and twelve paths respectively. Once experimental data is generated via a test matrix of 200 tests, the model will be validated to conduct MFECR’s process optimization and revalidate the quantitive benchmark on three different MFECR’s layouts.

Jesus A. Dominguez↗
NASA NTRS2023

Additive Manufacturing of Oxide Dispersion Strengthened Multi Principle Element Alloys for Future Aerospace Applications

Oxide Dispersion Strengthened (ODS) materials have long been of interest for their high temperature applications, and additive manufacturing enables their manufacturing viability. The ODS multi-principle element alloy NiCoCr was prepared using powder metallurgy techniques, additively manufactured, and evaluated for its processingmicrostructure-property relationships. The high temperature foundations of nickel-base superalloys and ODS materials were combined with the manufacturing advantages of 3D printing and the chemical simplicity of NiCoCr to inspire this work, which was divided into powder and printed material assessments. The project was achieved through multiple iterative project loops to assess the processing parameters’ impact on the microstructure and mechanical properties of the feedstock powder and printed material. The powder investigations (Chapter 3) focused on understanding the oxide coating that formed on the metal powder following acoustic mixing. Time of Flight Secondary Ion Mass Spectrometry was used to semi-quantitatively assess the amount of yttrium on the surface of the mixed powders, and indicated that a combination of higher mixing condition energy and moderate mixing time resulted in the most oxide coating on the NiCoCr powder. The results were supported by a qualitative assessment of scanning electron images of coated powder particles. Following mixing, the ODS NiCoCr was consolidated by Laser Powder Bed Fusion. The evaluations of the printed material (Chapter 4) frst considered screening experiments including Archimedes’ density, porosity, and grain size and number metrics from electron backscatter diffraction data. After the ideal additive manufacturing parameters were identifed, both the oxide homogeneity and yield strength were discussed for the idealized printed material. Overall, the project suggests that the combined use of qualitative or semi-quantitative powder surface analysis with Archimedes’ density analyses can be a valid high-throughput technique which can lead to process optimization of Laser Powder Bed Fusion additively manufactured ODS material.

Laura G Wilson↗
NASA NTRSDate not supplied

Influence of Feed Rate on Microstructure and Hardness of Conventionally Spun-formed Al 6061-O Plate

The effect of feed rate on the hardness and microstructure of a 7.35-mm-thick section from a spin-formed Al 6061 cylinder is investigated via microhardness mapping and electron backscatter diffraction (EBSD) analysis. The through-thickness hardness and microtexture profiles, corresponding to a true thickness strain of ≈ 0.3, are utilized to evaluate microstructural variations that could influence mechanical anisotropy and spin formability. The microhardness data reveal distinct gradients from the outer to the inner mold line that vary with feed rate and may be a function of the level of forming strain in the material. The microtextural mapping data expose a minor influence from feed rate, but contain trends through the material cross-section that suggest variations in the location-dependent stress states. The results demonstrate for the first time that the relationship between spin forming deformation and hardness or texture variations can be exploited to optimize processing parameters and mechanical response.

Spin forming↗
NASA NTRSDate not supplied

High-Throughput Strategies that Encompass Experiments and Machine Learning to Predict the Mechanical Properties of Additive Manufactured Aerospace Alloys

Small Punch Test (SPT) uses a thin disk of material to predict mechanical properties. While SPT has existed for decades, it has been used largely as a qualitative evaluator of mechanical properties. Recent advances in computational modeling have enabled the extraction of uniaxial stress-strain response from the measured SPT load-displacement data. Due to small sample volumes and unidirectional testing, SPT is conducive to high-throughput automation and ideally suited to extract properties from high-cost materials. Aerospace alloys have been of recent interest to the Additive Manufacturing (AM) community due to AM’s unique ability to fabricate complex designs not possible, or extremely arduous, with conventional manufacturing. In this research, SPT, coupled with Materials Informatics and computational modeling, is used to develop relevant Process-Structure-Property relationships to decrease the cost and time of process optimization for AM aerospace alloys, namely Inconel 718, Inconel 625, and Niobium C103.

High-throughput Testing↗
NASA NTRSDate not supplied

Influence of Feed Rate on Microstructure and Hardness of Conventionally Spun-formed Al 6061-O Plate

The effect of feed rate on the mechanical properties and microstructure of a 7.35-mm-thick section from a spin-formed Al 6061 cylinder is investigated via microhardness mapping and electron backscatter diffraction (EBSD) analysis. The through-thickness hardness and microtexture profiles, corresponding to a true thickness strain of ≈ 0.3, are utilized to evaluate microstructural variations that could influence mechanical anisotropy and spin formability. The microhardness data reveal distinct gradients from the outer to the inner mold line that vary with feed rate and may be a function of the level of forming strain in the material. The microtextural mapping data expose a minor influence from feed rate, but contain trends through the material cross-section that suggest variations in the location-dependent stress states. The results demonstrate for the first time that the relationship between spin forming deformation and hardness or texture variations can be exploited to optimize processing parameters and mechanical response.

Spin forming↗
NASA NTRS2026

Manufacturing and Scale-Up of Natural Fiber Composite eVTOL Propeller Skin and C-Channel

This report presents the manufacturing and scale-up of natural fiber composites for aerospace applications, conducted within NASA’s Convergent Aeronautics Solutions portfolio to advance aircraft capabilities and efficiency. The effort focused on the development and demonstration of two proof-of-concept articles, an Electric Vertical Take-off and Landing (eVTOL) propeller skin and a C-channel, produced through an iterative design and process optimization approach. Best practices and guidance on addressing key challenges with bio-based composite materials and manufacturing is provided. Ideally suited for non-load-bearing structural components, these emerging materials offer potential for weight reduction, vibration damping, noise mitigation, interference-free communication, and cost savings, without compromising the performance of safety-critical primary structures.

Natural fibers↗
DOE OSTI2020

Corrosion Behavior of Developmental Iron Phosphate Waste Forms: FY20 Status Report

Corrosion tests were performed to assess the dissolution behaviors of developmental iron phosphate materials that are being evaluated as an alternative to the glass-bonded sodalite ceramic waste form to immobilize salt wastes from electrochemical separation operations. Production of the iron phosphate waste form results in dehalogenation of the waste salt that increases potential waste loading. Ferric oxide is added to the waste form to increase the chemical durability. Tests conducted to optimize the amount of ferric oxide used to make the waste form are summarized in this report. Specimens prepared from materials made with between 17 and 34 mole % ferric oxide were subjected to two test methods to assess the effects of the iron content on the relative durability and retention of immobilized salt cations including cesium, strontium, and neodymium. Modified ASTM C1308 test results show the intrinsic durability was significantly higher for materials made with 27 mol % ferric oxide. Further additions generated iron-rich inclusion phases and did not improve durability. Modified ASTM C1285 test results show that solution feedback attenuates the dissolution rate similar to what is observed for borosilicate glasses within seven days. Analyses of test specimens after 42 days show no evidence that surface layers formed. Combined with previous studies addressing the salt loading, a composition region of the ammonium (di)hydrogen phosphate-waste salt-ferric oxide ternary has been defined for durable waste form compositions. Materials with that composition can be used to determine optimal processing conditions, assess long-term performance, and parameterize a degradation model.

Stariha, S. A.↗
DOE OSTI2021

Integration of CO2 Electrolysis with Microbial Syngas Upgrading to Rewire the Carbon Economy

This project has worked towards demonstrating and understanding the conversion of waste CO2 into value added fuels and chemicals. If successful, our proposed technology will incentivize CO2 capture and can add carbon efficiency to biorefineries. We have integrated two conversion technologies to demonstrate a novel approach of combining electrolytic CO2 reduction with biocatalytic CO upgrading. Industrial partners 3M and Dioxide Materials have recently demonstrated electrolytic conversion of CO2 and water to syngas using inexpensive renewable energy. Concurrently, supporting partner Lanzatech has demonstrated industrial scale CO fermentation using steel mill waste CO as a substrate. This presentation will highlight the investment BETO has made to establish a CO2 electrolysis test station and CO fermentation at NREL. We will also discuss the process of increasing the size of the electrolyzers to meet fermentation needs, along with the investigation into the affect CO2 concentration and contaminates have on electrolyzer efficiency, lifetime, and specificity. Additionally, we have begun to examine the downstream impact of electrolyzer off-gas CO:H2 ratios have on the metabolism of C. autoethanologen. Experimental results along input from our industrial partners have led to a baseline techno-economic and life cycle analyses. These results enabled the identification of key cost drivers and carbon intensity of the process. We have used these metrics to identify technology gaps to iteratively inform the process optimization and potential deployment siting to achieve economically viable, sustainable conversion of biopower-derived flue gases to fuels and chemical intermediates.

bioenergy↗
DOE OSTI2022

Component-wise reduced-order model design optimization such as for lattice design optimization

Systems and methods for optimizing a lattice structure design are disclosed herein. In some embodiments, a method for optimizing a lattice structure design can include (i) modeling the lattice structure with a component-wise reduced-order model (CWROM) and (ii) optimizing the CWROM based on a selected criterion using a topology optimization algorithm for lattice design. The selected criterion can include a boundary condition and a load applied to the lattice structure. By modeling the lattice structure as a CWROM, the optimization process can be very fast while still permitting the accurate computation of physical quantities of the lattice structure.

Choi, Youngsoo↗
DOE OSTI2025

Validation Testing for Molten Chloride Reactor Experiment Equipment Removal and Disposal Techniques

The Molten Chloride Reactor Experiment (MCRE) will be the first reactor featuring a fast-spectrum molten chloride circulating nuclear fuel system in the world. Planning for equipment removal and disposal (ERD) of MCRE has identified several technology gaps due to the unique environment of this nuclear experiment. Some of the gaps arise from the application of existing disassembly and/or sizing methods to novel material forms or in novel configurations. Others arise from unknown material behavior. This paper summarizes proposed test plans for ERD validation experiments to address these complicated or unknown equipment removal procedures. At the Waste Management Symposia in 2024, the Idaho National Laboratory (INL) MCRE ERD team presented the challenges associated with hosting multiple nuclear experiments in series with only brief transition periods between systems. Such difficulties include higher dose rates, the presence of radioisotopes infrequently encountered in reactor decommissioning and radioactive waste management, lack of intrinsic remote-operations infrastructure in the test bed, space constraints in the test bed, and contamination minimization requirements. To address these challenges, remote or semi-remote technologies are planned to be implemented in a non-hot cell environment with limited space availability. The team also discussed how a systems engineering approach is being used for conceptual development and design of equipment removal systems to address these challenges. For example, to reduce constraints for the removal of more difficult components, non-activated, noncontaminated elements are planned to be taken out first where possible. Still, there are complexities associated with the remaining components. In this work, the operational framework for MCRE ERD was reviewed for technical gaps and open questions, and test plans were drafted to address these areas. The tests plans were written for the following categories: vision systems, pipe cutting, drill/grout/filler, flush salt, and miscellaneous, with the miscellaneous group consisting of tests like techniques for removing bearings and reflector bricks. The test plans explore material, infrastructure, and staffing requirements needed for test execution. The test plans additionally focus on the evaluation of success. Determining the outcome of a test is imperative - as these explorative actions have the potential to rearrange or re-scope planned ERD activities. Success criteria identified thus far include required tool output, required area(s), debris production and mitigation, and repeatability. Test plans are an essential aspect of the systems engineering approach to MCRE ERD. They are used as the beginning steps in defining use cases for the ERD system. Performance of the validation tests is expected to begin in the summer of 2025 and will take approximately 9 to 12 months to complete. Execution of these plans will be expedited by specifying test needs ahead of time, facilitating efficient interactions with any subcontractors tasked with running the requested tests. Evaluating the outcomes of these tests will inform MCRE ERD procedures and timing and will also identify additional technical constraints for the MCRE ERD System. This upfront process optimization effort will help the project save time and resources at the end of the experiment.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2023

Towards Efficient Alternating Current Optimal Power Flow Analysis on Graphical Processing Units

We present a solution of sparse ACOPF analysis on GPU. In particular, we discuss the performance bottlenecks and detail our efforts to accelerate the linear solver, a core component of ACOPF that dominates the computational time. ACOPF solutions of two large-scale systems, synthetic Northeast (25,000 buses) and Eastern (70,000 buses) \cite{birchfield2017tamu-cases} on GPU show promising speed-up compared to CPU based solution using a state-of-the-art solver. To our knowledge, this is the first result demonstrating acceleration of sparse ACOPF on GPUs.

Power grid analysis, GPU↗
DOE OSTI2024

A Framework for the Optimization of Water Treatment Processes Under Uncertainty Assessed through Process Operability

Conference presentation conveying work conducted on developing a framework for the optimization of water treatment processes after applying robust optimization and process operability tools. The objective of this framework is to optimize treatment processes under the uncertainty of source water conditions. This work contributes to robust optimization and process operability methodologies, allowing for the extension of probability from statistical models to operability calculations.

Barber, Hunter↗
DOE OSTI2026

Multi-Fidelity Bayesian Optimization with Gaussian Processes for Double Shell Inertial Confinement Fusion Target Design

Reliable, secure access to energy is a major focus for national security efforts. One potential route to such energy is through fusion reactions in inertial confinement fusion (ICF) experiments. Such experiments are carried out at facilities such as the National Ignition Facility (NIF) in Livermore, California, where high powered lasers are used to compress a DT fuel-containing target to the necessary high temperature, high pressure conditions. These experiments are limited in number, which creates a heavy dependence on high fidelity predictive physics simulations and analysis performed “pre shot,” or before the experiment occurs. Many of these simulations in higher dimensions (2D and 3D) are computationally expensive, so finding optimal simulation-based designs presents its own challenges. In this work, we present our multi-fidelity Bayesian optimization with Gaussian processes (GPs) for ICF double shell targets, where a 1D surrogate model is used to help find a 2D surrogate model, enabling us to find optimal targets in the higher fidelity (2D), while saving computational cost.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1971

An optimal system design process for a Mars roving vehicle

The problem of determining the optimal design for a Mars roving vehicle is considered. A system model is generated by consideration of the physical constraints on the design parameters and the requirement that the system be deliverable to the Mars surface. An expression which evaluates system performance relative to mission goals as a function of the design parameters only is developed. The use of nonlinear programming techniques to optimize the design is proposed and an example considering only two of the vehicle subsystems is formulated and solved.

Pavarini, C.↗
DOE OSTI2025

Enhancing Gaussian Process Surrogates for Optimization and Posterior Approximation via Random Exploration

This paper proposes novel noise-free Bayesian optimization strategies that rely on a random exploration step to enhance the accuracy of Gaussian process surrogate models. The new algorithms retain the ease of implementation of the classical GP-UCB algorithm, but the additional random exploration step accelerates their convergence, nearly achieving the optimal convergence rate. Furthermore, to facilitate Bayesian inference with intractable likelihoods, we propose to utilize optimization iterates for maximum a posteriori estimation to build a Gaussian process surrogate model for the unnormalized log-posterior density. We provide bounds for the Hellinger distance between the true and the approximate posterior distributions in terms of the number of design points. We demonstrate the effectiveness of our Bayesian optimization algorithms in nonconvex benchmark objective functions, in a machine learning hyperparameter tuning problem, and in a black-box engineering design problem. The effectiveness of our posterior approximation approach is demonstrated in two Bayesian inference problems for parameters of dynamical systems.

Bayesian inference↗
DOE OSTI2020

Laser Powder Bed Fusion Additive Manufacturing In-Process Monitoring and Optimization Using Thermionic Emission Detection

In this project, the emission of electrons during laser powder bed fusion additive manufacturing was identified and investigated to resolve the underlying dynamics driven by laser-material interactions. Laser powder bed fusion involves the selective laser melting of metal powder particles layer by layer which fuse together forming a larger 3D structure. Laser-based additive manufacturing approaches such as laser powder bed fusion hold the potential to revolutionize manufacturing of complex metal components in the aerospace, medical, and automotive industries. However, the difficulty in producing defect-free components by metal 3D printing is a major hurdle for widespread commercial adoption. This project resolved important dynamics in laser powder bed fusion including the identification of plasma formation mechanisms, transitions between laser-induced melting modes and stochastic precursors to defect formation. These findings were realized through implementation of electronic sensing diagnostics into an existing testbed system and harnessing capabilities developed for the time dependent analysis of laser powder bed fusion datasets. Importantly, the results advance our understanding of laser-material interactions and reveal that detection of thermionic emission can also resolve information critical to optimization of the laser powder bed fusion fabrication process. The findings are critical for advancing our fundamental understanding of the laser powder bed fusion process and can help assure the requisite fidelity of fabricated components.

36 MATERIALS SCIENCE↗