Process-specific design strategy enables exceptional as-deposited strength-ductility synergy in novel Al–Ce alloys via additive friction stir deposition (AFSD)
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Soni, Vishal (ORCID:0000000193561023)↗
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Results for “process design”
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.
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On the process of designing material qualification type specimens manufactured using laser powder bed fusion
Not Available
Tekerek, Emine (ORCID:0000000273201319)↗
Accelerating the design of lattice structures using machine learning
Lattices remain an attractive class of structures due to their design versatility; however, rapidly designing lattice structures with tailored or optimal mechanical properties remains a significant challenge. With each added design variable, the design space quickly becomes intractable. To address this challenge, research efforts have sought to combine computational approaches with machine learning (ML)-based approaches to reduce the computational cost of the design process and accelerate mechanical design. While these efforts have made substantial progress, significant challenges remain in (1) building and interpreting the ML-based surrogate models and (2) iteratively and efficiently curating training datasets for optimization tasks. Here, we address the first challenge by combining ML-based surrogate modeling and Shapley additive explanation (SHAP) analysis to interpret the impact of each design variable. We find that our ML-based surrogate models achieve excellent prediction capabilities (R 2 > 0.95) and SHAP values aid in uncovering design variables influencing performance. We address the second challenge by utilizing active learning-based methods, such as Bayesian optimization, to explore the design space and report a 5 × reduction in simulations relative to grid-based search. Collectively, these results underscore the value of building intelligent design systems that leverage ML-based methods for uncovering key design variables and accelerating design.
36 MATERIALS SCIENCE↗
A Redox-Electrodialysis Model with Zero Fitting Parameters: Insights into Process Limitations, Design, and Material Interventions
Redox-Electrodialysis (r-ED) is an electrochemical desalination cell architecture that has recently received considerable interest, due to its low energy demand relative to electrochemical desalination technologies that rely on electrode-based ion removal. To further improve the energy efficiency of r-ED, we developed a lumped mathematical model with no adjustable parameters to investigate the various sources of overpotential within the cell. Existing models of electrodialysis and r-ED cells either do not accurately incorporate all phenomena contributing to the overpotential or utilize empirical fitting parameters. The model developed here indicates that ohmic overpotentials, especially in the diluate chamber, are the most significant contributors to energy losses. Based on this insight, we hypothesized that adding an ion exchange resin wafer in the diluate compartment would increase the ionic conductivity and decrease the energy demand. Experimental results showed an 18% reduction in specific energy use while achieving the same degree of salt removal (20 mM to 12 mM). Furthermore, the resin wafer enabled complete desalination to potable drinking levels at a current density previously unachievable within practical operating voltage limits (4.93 mA cm -2 ). We also expanded the model to explore differences in r-ED energy use between configurations using multiple cells and a single cell with increased area.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DIVA/DeviceEditor (DIVA) v5.1
The DIVA software interfaces a process in which researchers design their DNA with a web-based graphical user interface (DeviceEditor), submit their designs to a central queue, and a few weeks later receive their sequence-verified clonal constructs. Each researcher independently designs the DNA to be constructed with a web-based BioCAD tool, and presses a button to submit their designs to a central queue. Researchers have web-based access to their DNA design queues, and can track the progress of their submitted designs as they progress from "evaluation", to "waiting for reagents", to "in progress", to "complete". Researchers access their completed constructs through the central DNA repository. Along the way, all DNA construction success/failure rates are captured in a central database. his success/failure rate data can be leveraged to refine the DNA assembly design process.
Lane, Stephen↗
Ion-Conducting Polymer Design and Process for Incorporation into Copper Nanoparticles: Phase 1 (CRADA Final Report)
We will explore the improvement of the electrocatalytic efficiency of CO 2 conversion to ethylene by coating part of the surface of Cu nanoparticle electrodes with ion-conductng polymers. These polymers will be produced by depositing monomers onto the electrodes and polymerizing them via an external stimulus.
09 BIOMASS FUELS↗
Design and Analysis of a 25 MWe Supercritical CO2 Turbo Machine
This paper presents the design and analysis of a turbo machine operating with supercritical carbon dioxide (sCO2) in a 25 MWe Recompression Brayton Cycle (RCBC). The work was performed under US Department of Energy (DoE) program DE-EE-0010318. The design process involves the aerodynamic design of the compressor and turbine, including the initial layout of flowpaths and stage configurations to achieve high efficiency and performance. Additionally, a comprehensive rotodynamic analysis is performed to ensure the stability and reliability of the system. Conceptual designs for a high-speed motor and synchronous generator that match turbomachinery requirements are also developed from first principles.
42 ENGINEERING↗
Inverse Aerodynamic Design of Gas Turbine Blades using Probabilistic Machine Learning
Abstract One of the critical components in Industrial Gas Turbines (IGT) is the turbine blade. Design of turbine blades needs to consider multiple aspects like aerodynamic efficiency, durability, safety and manufacturing, which make the design process sequential and iterative. The sequential nature of these iterations forces a long design cycle time, ranging from several months to years. Due to the reactionary nature of these iterations, little effort has been made to accumulate data in a manner that allows for deep exploration and understanding of the total design space. This is exemplified in the process of designing the individual components of the IGT resulting in a potential unrealized efficiency. To overcome the aforementioned challenges, we demonstrate a probabilistic inverse design machine learning framework, namely PMI (PMI), to carry out an explicit inverse design. PMI calculates the design explicitly without costly iteration and overcomes the challenges associated with ill-posed inverse problems. In this work the framework will be demonstrated on inverse aerodynamic design of three-dimensional turbine blades.
Engineering↗
An Economics-by-Design Approach Applied to a Heat Pipe Microreactor Concept
Microreactors present a potential paradigm shift in the nuclear industry. Emphasis thus far has been on large-scale multi-billion-dollar projects that cater solely to grid electricity market. These projects can be challenging to finance and execute. On the other hand, microreactors are intended to target a wide variety of smaller niche markets and are expected to be factory-fabricated and more readily deployable. While diseconomies of scale for microreactors may tend to raise their costs per energy output (MWh) relative to large nuclear plants, offsetting gains can be expected from standardization, simplification, passive safety, lower radionuclide inventories, factory fabrication, fast installation, and low financing costs. To adequately assess these contributions, designers should have a different perspective on cost drivers than for large nuclear plants and can utilize novel approaches for systematic cost reduction. To account for these important aspects of microreactors, this report proposes an economics-by-design approach that places economic considerations at the center of the design process. The methodology builds on existing frameworks such as design-to-cost and value engineering, expanding them to new markets (beyond the grid), new attributes (beyond costs alone), and introducing the approach at earlier points in the design cycle. Design parameters and technical specifications are systematically evaluated until costs meet market entry points, while also providing the high-priority performance attributes of the particular use case. Determining first-order estimates for different components early in the process enables designers to focus R&D efforts on the biggest overall cost contributors and components with the most cost uncertainty. The analysis is always guided by market needs and threshold prices. In addition to microreactors, the approach is expected to be useful for other classes of nuclear reactors as well. The analysis was applied to a concept found in the open literature (the Design A heat-pipe reactor). A comprehensive bottom-up estimate was generated by leveraging a new microreactor-specific code of accounts and a range of cost equations. The initial estimate for levelized cost of electricity (LCOE) unsurprisingly exceeded market ranges since the use case had prioritized technological readiness over economic considerations in design choices. An alternate concept was then proposed, with various assumptions/targets made to reduce the largest cost contributors. Changes in the neutron spectrum, the power output, and building structures were found to make even the first-of-a-kind of this modified concept competitive with diesel generation in some remote communities. Learning rate (LR) assumptions indicated cost reductions achieved from sequential unit deployments could expand the range of competitiveness to include additional markets as deployments proceed.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
A spatial superstructure approach to the optimal design of modular processes and supply chains
Modularity is a design principle that aims to provide flexibility for spatio-temporal assembly/disassembly and reconfiguration of systems. This design principle can be applied to multiscale (hierarchical) manufacturing systems that connect units, processes, facilities, and entire supply chains. Designing modular systems is challenging because of the need to capture spatial interdependencies that arise between system components due to product exchange/transport between components and due to product transformation in such components. In this work, we propose an optimization framework to facilitate the design of modular manufacturing systems. Central to our approach is the concept of a spatial superstructure, which is a graph that captures all possible system configurations and interdependencies between components. The spatial superstructure is a generalization of the notion of a superstructure and of a p-graph used in process design, in that it encodes spatial (geographical) context of the system components. Here, we show that this generalization facilitates the simultaneous design and analysis of processes, facilities, and of supply chains. Our framework aims to select the system topology from the spatial superstructure that minimizes design cost and that maximizes design modularity. We show that this design problem can be cast as a mixed-integer, multi-objective optimization formulation. We demonstrate these capabilities using a case study arising in the design of a plastic waste upcycling supply chain.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Toward an Envelope of Design Solutions for Combined/Intensified Reaction/Separation Systems
In this work, we develop an envelope of design solutions for combined intensified reaction/separation systems. The attainable region-based continuous flow stirred tank reactor equivalence principle is applied to characterize design boundaries for a given chemistry independent of process design. The thermodynamic-based Generalized Modular Representation Framework is then employed to generate candidate process alternatives along the design boundaries. The proposed approach is showcased via a case study on olefin metathesis. As a result, we also highlight the need to incorporate the attainable region-based constraints into synthesis strategies to assist effective bounding of design/intensification space.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Pareto Optimization of Analog Circuits Using Reinforcement Learning
Analog circuit optimization and design presents a unique set of challenges in the IC design process. Many applications require the designer to optimize for multiple competing objectives, which poses a crucial challenge. Motivated by these practical aspects, we propose a novel method to tackle multi-objective optimization for analog circuit design in continuous action spaces. In particular, we propose to (i) extrapolate current techniques in Multi-Objective Reinforcement Learning to continuous state and action spaces and (ii) provide for a dynamically tunable trained model to query user defined preferences in multi-objective optimization in the analog circuit design context.
99 GENERAL AND MISCELLANEOUS↗
IER 537: CERBERUS – Copper Critical Experiment Design [Slides]
This document details the CERBERUS copper critical experiment design process, including information on preliminary design criteria, case analysis, and experiment designs. Future work is anticipated and includes the creation of a more detailed model, additional investigation regarding varying interstitial material thickness and varying Cu reflector thickness, cost analysis, and down select to final set of configurations.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Opportunities for Process Intensification with Membranes to Promote Circular Economy Development for Critical Minerals
This poster for Foundations of Computer Aided Process Design (FOCAPD 2024) outlines how process systems engineering (PSE) ideas can be applied to critical mineral processing. Specifically, the poster focuses on how PSE can enhance process intensification with membranes to accelerate the development of a circular economy for critical minerals.
Dougher, Molly↗
Preliminary System Interface Failure Mode Analysis for Two Advanced Reactors
This study explores two distinct Balance of Plant (BOP) configurations: the Rankine cycle for a sodium-cooled fast reactor (SFR) and the Brayton cycle for a gas-cooled reactor (GCR). As representative designs, the Power Reactor Innovative Small Module (PRISM) by GE Hitachi Nuclear Energy was selected for the SFR, while the Gas Turbine Modular Helium Reactor (GT MHR) by General Atomics was chosen for the gas-cooled reactor. Both configurations were adapted to deliver high-quality heat for industrial applications. A Failure Modes and Effects Analysis (FMEA) was conducted for each system to identify critical failure modes affecting key components. This study marks the first phase of a two-step design optimization approach, integrating FMEA into the design process. Based on the analysis, design modifications and mitigation strategies were proposed to enhance system resilience. The second phase, to be detailed in a subsequent report, will focus on the role of the control system in mitigating these failures. The FMEA serves as a foundation for defining the control topology, ensuring system resilience against component failures that could compromise essential functions, such as electricity and heat production.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Membranes in Solar-Driven Evaporation: Design Principles and Applications
In this study, solar-driven evaporation process brings exciting opportunities to recover clean water and resources in a sustainable way from diverse sources like seawater and wastewater. Separation membranes, as a vital material in many environmental and energy applications, can contribute significantly to this process owing to their structural features. However, the unique roles of membranes in solar evaporator construction and process design are seldom recognized and not summarized yet from scientific principles and application demands, which forms the motivation of this review. Herein, the roles of membranes in different processes based on solar-driven evaporation are focused and the design principles of membrane materials and devices to meet the requirements of these applications are discussed. Fabrication strategies for photothermal membranes are introduced primarily, followed by a discussion on how to design membrane materials, devices, and processes to pursue optimal performance and realize advanced functions accompanied by evaporation. Furthermore, the future of this field is forecast with both challenges and opportunities.
14 SOLAR ENERGY↗
Initial development and verification of a primary load design method based on elastic-perfectly plastic analysis
This report describes a new primary load design method to supplement the current design-by-elastic-analysis rules in Section III, Division 5, Subsection HB, Subpart B of the ASME Boiler and Pressure Vessel Code, covering the design and construction of Class A high temperature nuclear structural components. The main objectives for the new design method are to provide a procedure that can be applied to components with complicated geometries and to simplify the primary load design process by providing rules more compatible with modern finite element analysis. The report includes a complete set of design rules, presented as a draft ASME Code Case, as well as a commentary on the rules and a set of verification problems. The verification design problems demonstrate the new primary load design rules produce safe, efficient components when compared to the current Division 5 approach, while greatly simplifying the design analysis process.
42 ENGINEERING↗