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At least 109 records · Page 6

Transport Analysis & Optimization in a MW-Scale CO2 Electrolyzer (Final Report)

As Twelve continues to scale up their CO2 electrolyzers, both in the size of a single cell and in the number of cells used in a stack, thermal management becomes a growing concern, since excess heat can affect reaction yield and accelerate degradation. In this project, we aim to computationally explore how the anode flow fields used in Twelve’s CO2 electrolyzers function as heat exchangers. In particular, using a homogenized model of a CO2 electrolyzer, we first estimate the amount of heat generated in a cell. Then, we develop a computational fluid dynamics (CFD) model of the so-called “flow field”, i.e. a flow manifold, based on Twelve’s CAD drawings, to evaluate how these flow fields perform as a heat exchanger for the generated heat. We explore both a single cell and a 3-cell stack operating in parallel, where heat generated in one cell can now be transferred to another cell. We evaluate how performance is affected when environmental heat losses are taken into account. Finally, we leverage topology optimization to explore the types of design features a computational optimization algorithm would suggest to supplement our intuition. Overall, our work aims to provide design recommendations for CO2 electrolyzer flow fields and provides a foundation for future studies of flow field optimization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

A deep learning and finite element approach for exploration of inverse structure–property designs of lightweight hybrid composites

Hybrid composites have important applications, such as high-performance and lightweight materials in aerospace and automotive industries. Hybrid composites utilize the synergy of diverse fillers to achieve desired material properties, but usually have more complicated microstructures. While topology optimization can optimize a particular property, designing hybrid composites for customized mechanical performances, e.g. full-range stress–strain curve, remains challenging. Here, a computational framework that integrated finite element analysis (FEA) and artificial intelligence (AI) methods of Conditional Generative Adversarial Networks (cGAN) deep learning and transfer learning was developed to establish inverse structure–property relationships and design tailor-made hybrid composites. Based on FEA-generated datasets of hybrid fiber-particle–matrix microstructures and their corresponding full-range stress–strain curves, a cGAN architecture was trained to generate tailored microstructures and establish structure–property relationships. Similarity in microstructural features and well-matched stress–strain curves based on the AI-generated composites were achieved. In conclusion, transfer learning was used to expand the pre-trained model for designing different materials systems.

Hybrid composites

Operational resilience of additively manufactured parts to stealthy cyberphysical attacks using geometric and process digital twins

Cyberphysical attacks on the digital backbone of Additive Manufacturing (AM) can compromise the printed part’s functionality. They can alter features in the digital geometry to introduce geometric defects (e.g., missing fillets) or alter process parameters to create local defects (e.g., voids). Addressing the downtime, waste, and quality deterioration associated with existing solutions requires operational resilience, i.e., rapid elimination or disruption of defect formation (to retain part function) without production stoppage or part disposal (to retain yield). This need is unmet due to the inherently unpredictable nature of attack-induced alterations, lack of access to the original geometric model for identification of altered geometric features, and in-process imposition of unknown process dynamics via attack-driven alteration of real-time-uncontrolled (or exogenous) parameters. This work establishes the above-mentioned operational resilience for the first time by creating two Digital Twins (DT). The Geometric DT (Geo-DT) is based on a unique physical-field-driven soft sensor and topology optimization method. The Process Digital Twin (Pro-DT) combines local defect quantification with a novel Reinforcement Learning formulation and training method. The importance of these methodological advances and the scalability of our approach are examined on a real AM testbed. It is shown that Geo-DT can correct geometric defects without access to the original digital geometry or explicit knowledge of attack-altered geometric features. Further, Pro-DT can accelerate real-time disruption of local defects despite attack-driven imposition of unknown process dynamics. We discuss how our framework goes beyond the contemporary focus on pre-attack security and in-attack detection towards resilience for AM and beyond.

Additive Manufacturing

Designing Cellular Metal Structures for Thermal Insulation

This project focused on developing topology optimization software to design advanced metal thermal insulators. Initially, solid designs were created that matched the thermal performance of current baseline designs but were significantly heavier. To address this, cellular materials were incorporated, specifically the octet structure which is known for its high strength-to-weight ratio and thermal properties. By leveraging these cellular designs at various densities, superior thermal and mechanical performance was achieved without added weight. This novel approach enhances thermal management and structural integrity under extreme conditions, offering promising advancements for thermal protection systems.

36 MATERIALS SCIENCE

The Development of Design Tools for Fault Tolerant Quantum Dot Cellular Automata Based Logic

We are developing software to explore the fault tolerance of quantum dot cellular automata gate architectures in the presence of manufacturing variations and device defects. The Topology Optimization Methodology using Applied Statistics (TOMAS) framework extends the capabilities of the A Quantum Interconnected Network Array Simulator (AQUINAS) by adding front-end and back-end software and creating an environment that integrates all of these components. The front-end tools establish all simulation parameters, configure the simulation system, automate the Monte Carlo generation of simulation files, and execute the simulation of these files. The back-end tools perform automated data parsing, statistical analysis and report generation.

Armstrong, Curtis D.

NASA Additive Manufacturing Initiatives for Deep Space Human Exploration

Additive Manufacturing (AM) is being infused into aerospace industries at an accelerated pace. Reasons for this rapid adoption include: (1) Innovation Capability e.g. design features such as topology optimization, integrated fluid passages, and mesh structures; (2) Rapid Development and Optimization - ability to quickly iterate the design, development, and test cycle; (3) Affordability - reductions in part counts, cost, and schedule. NASA's Marshall Space Flight Center (MSFC) has taken a leadership role in application of AM technologies for deep space human exploration, leading the Agency's In Space Manufacturing (ISM) initiative and the application of AM for a broad variety of space propulsion systems. MSFC has championed the development of ISM capabilities since our first reduced-gravity aircraft experiment flew in 1999. Partnering with Made In Space, MSFC placed the first 3D Printer on ISS in 2014 and the second generation printer, the Additive Manufacturing Facility, in 2016. The next ISS technology demonstration will be the Refabricator, a recycler/basic printer scheduled to launch in late Fall 2018. Ground-based development is progressing in common use materials, metals 3D printing, printed electronics, and the new cornerstone of ISM, the FabLab. The latest developments in each area will be described. An overview of NASA's In Space Robotic Manufacturing and Assembly (IRMA) ground-based risk reduction projects will also be presented. MSFC has aggressively incorporated AM capabilities for design and development of space propulsion components. The capabilities have been rapidly matured and extensively exercised to produce and hot-fire test the Additive Manufacturing Demonstrator Engine, an in-space class prototype engine. This experience base has been extended to support Aerojet Rocketdyne in the application of AM to the RS-25, the Space Launch System Core Stage engine, and to small propulsion systems and thrusters for small satellites and cubesats. The latest developments will be described. In responding to a request from NASA's Commercial Crew Program for a consistent methodology for evaluation of AM processes and parts, MSFC began development of a draft standard for AM space flight hardware in late 2014. The draft was broadly disseminated for comments in mid-2015, and subsequently revised into two documents, a standard and a specification for AM space flight hardware, which were formally released by MSFC in October 2017. An overview of the key elements of these documents will be presented.

Clinton, Raymond

Passive Aeroelastic Tailoring

The Passive Aeroelastic Tailoring (PAT) project was tasked with investigating novel methods to achieve passive aeroelastic tailoring on high aspect ratio wings. The goal of the project was to identify structural designs or topologies that can improve performance and/or reduce structural weight for high-aspect ratio wings. This project considered two unique approaches, which were pursued in parallel: through-thickness topology optimization and composite tow-steering.

Smith, Benjamin

Robotics System Process and Concept for On-orbit Assembly for Potential Mars Sample Return

Proposed Mars Sample Return (MSR) missions would require on-orbit assembly of containment vessels to meet backward Planetary Protection requirements and transfer of the sample container through various stations and positions. Some operations would have to be performed autonomously, and others would require ground-in-loop decision-making stages and verification processes. One concept design for an Earth Return Orbiter (ERO) Capture, Contain, and Return System (CCRS) Transfer Mechanism (TM) is a multi-Degree of Freedom (DOF) manipulator that utilizes a passive End Effector (EE) to assist in containment vessel assembly. To converge on a feasible design, a robotic system process has been instantiated. This process is composed of three main phases: robotic problem definition (operating environment, operations/functions, system goals), robotic solution selection (trade studies on the number of degrees of freedom, number of mechanisms, types of mechanisms), robotic solution design, implementation, and verification and validation (kinematic configuration, robotic and kinematic analysis and topology optimization of components). As a final product of this process, a half-scale functional prototype of the TM was developed to demonstrate the end-to-end operation capability.

Strahle, Jackson W

Making & Breaking the Rules for DED Design

Design for Additive Manufacturing (DfAM) is widely used to describe design activities and guidelines employed in the creation of Additively Manufactured (AM) parts. Basic design rules for widely adopted processes like Powder Bed Fusion (PBF) are relatively understood including material performance, part size constraints, self-supporting angles, overhangs, wall thicknesses, and feature resolution. Complexity is often inherent with PBF using organically inspired solutions through generative design and topology optimization software to create designs that often cannot be realized via traditional manufacturing processes. The design rules for Directed Energy Deposition (DED) are less well known, and, in some cases, the lack of understanding is likely inhibiting broader application of the various DED processes. This presentation covers key design rules for DED fusion processes and elucidates opportunities like multi-material deposition and build approaches ranging from basic features to complex large-scale parts. Complementary to the opportunistic characteristics of DfAM for DED, Manufacture for AM (MfAM) encompasses the restrictive aspects of the manufacturing lifecycle with limitations due to bead width and wall thickness, self-supporting angles, surface texture, microstructural evolution, and residual stresses. AM enabled part design must always consider the entire value chain starting with incoming feedstock (e.g. plate, wire, or powder) and progressing through the printing process, post-processing (e.g. machining, inspection), and final system assembly. Key considerations, like the tradeoffs between feature resolution and build rate, for process and part selection and economic assessments will be discussed as DED is often traded against other AM processes. After highlighting typical DED design rules, we will also show how some of those rules can be broken via use cases and part designs that span the full spectrum of DED processes with examples of various DED part designs.

Additive Manufacturing

Force Measurement for Wind Tunnel Facilities - Current Practices and Research Investments

This presentation will provide an introduction to strain gage balances (force transducers) used in NASA’s wind tunnel facilities. It will cover the breadth of wind tunnel applications using balances ranging from cryogenic facilities to facilities with aero heating affects. Specific areas of expertise including six-component balance design and calibration will also be discussed. Moreover, research areas including additive manufacturing of wind tunnel balances, the development of topology optimization tools to produce novel force transducer geometries, and dynamic force measurement will also be highlighted.

Wind tunnel balance

Advanced Flexible Transformers

Advanced grid solutions are comprised of advanced transmission technologies and grid enhancing technologies. In this webinar, experts will provide participants with insights into eight advanced grid solutions. The advanced transmission technologies that will be discussed include point-to-point high voltage direct current and advanced conductoring and the grid enhancing technologies that experts will explore include topology optimization, advanced power flow control, dynamic line rating, energy storage, virtual power plants, and advanced flexible transformers

flexible power transformer, power flow controller,

Architectural scaling tradeoffs in modular 3D bosonic quantum processors

We propose a modular three-dimensional bosonic quantum processor built from repeatable coupled-cavity modules linked by configurable interconnect networks. Using hardware-motivated graph-theoretic measures, we compare nearest-neighbor, hub-based, and hybrid architectures in terms of interconnect count, communication distance, resource concentration, and implementation complexity. Rather than identifying a universally optimal topology, our analysis shows how these architectures redistribute the costs of scaling, including wiring and port requirements, nonlocal communication distance, exposure to shared resources, routing bottlenecks, and scheduling overhead. Case studies of a \(3\times3\) processor and a larger hierarchical architecture further distinguish finite-size performance from asymptotic scaling. The resulting framework provides a systematic basis for evaluating modular three-dimensional bosonic processors and for identifying the device-level parameters required for quantitative hardware design.

Zhu, Shaojiang [Fermilab] (ORCID:0000000293180092)

Rapid Assessment of Aircraft Structural Topologies for Multidisciplinary Optimization and Weight Estimation

Algorithms for rapid generation of moderate-fidelity structural finite element models of air vehicle structures to allow more accurate weight estimation earlier in the vehicle design process have been developed. Application of these algorithms should help to rapidly assess many structural layouts before the start of the preliminary design phase and eliminate weight penalties imposed when actual structure weights exceed those estimated during conceptual design. By defining the structural topology in a fully parametric manner, the structure can be mapped to arbitrary vehicle configurations being considered during conceptual design optimization. Recent enhancements to this approach include the porting of the algorithms to a platform-independent software language Python, and modifications to specifically consider morphing aircraft-type configurations. Two sample cases which illustrate these recent developments are presented.

Samareh, Jamshid A.

Optimization of the Magnetic Field Topology in the Hall Effect Rocket with Magnetic Shielding

NASA's Hall Effect Rocket with Magnetic Shielding (HERMeS) 12.5 kilowatt Technology Demonstration Unit-1 (TDU-1) has been the subject of extensive technology maturation in preparation for flight system development. The TDU-1 thruster implements a magnetically shielded field topology and has demonstrated the elimination of the discharge channel erosion. Extensive wear testing of the TDU Hall thrusters has identified the thruster front pole covers as the next life limiting component. This effort aims to explore and investigate alternate magnetic field topologies to assess whether reductions in the front pole cover erosion can be attained while still maintaining very low erosion rates on the discharge channel walls. NASA GRC (Glenn Research Center) and JPL (Jet Propulsion Laboratory) have begun a magnetic field topology characterization and optimization study by designing four candidate magnetic field topologies that reduce the effectiveness of the shielding along the discharge channel walls with the intent to also reduce the erosion rates along the pole covers. Three of the four candidate magnetic field topologies have been manufactured subjected to an extensive test campaign that includes performance, plume, and stability characterization. In the Phase I test segment, the thruster's oscillation magnitude and laser-induced fluorescence (LIF) measurements of the plasma plume were performed for the three candidate topologies. In Phase I, the thruster's oscillation magnitude and LIF measurements were performed for the three candidate topologies. Phase I test results found that the B1 configuration attained lower oscillation levels than the baseline topology (B0). Additionally, laser induced fluorescence measurements along the discharge chamber centerline found that upstream retraction of the thruster’s peak magnetic field does result in an upstream shift of the acceleration zone but the magnitude of the shift does not correspond one-to-one to the shift in the location of the peak radial magnetic field magnitude. Phase II test segment will include performing performance, stability, plume, and erosion measurements for the various candidate magnetic field topologies..

Kamhawi, Hani

Optimization of the Magnetic Field Topology in the Hall Effect Rocket with Magnetic Shielding

NASA's Hall Effect Rocket with Magnetic Shielding (HERMeS) 12.5kW Technology Demonstration Unit-1 (TDU-1) has been the subject of extensive technology maturation in preparation for flight system development. The TDU-1 thruster implements a magnetically shielded field topology and has demonstrated the elimination of the discharge channel erosion. Extensive wear testing the TDU Hall thrusters has identified the thruster front pole covers as the next life limiting component. This effort aims to explore and investigate alternate magnetic field topologies to assess whether reductions in the front pole cover erosion can be attained while still maintaining very low erosion rates on the discharge channel walls. NASA GRC and JPL have begun a magnetic field topology characterization and optimization study by designing four candidate magnetic field topologies that reduce the effectiveness of the shielding along the discharge channel walls with the intent to also reduce the erosion rates along the pole covers. Three of the four candidate magnetic field topologies have been manufactured subjected to an extensive test campaign that includes performance, plume, and stability characterization. In Phase I of the testing campaign, the thruster's oscillation magnitude and Laser Induced fluorescence (LIF) measurements of the plasma plume were performed for the three candidate topologies. In Phase I, the thruster's oscillation magnitude and LIF measurements were performed for the three candidate topologies. Phase I test results found that the B1 configuration attained lower oscillation levels than B0. Additionally, LIF measurements along the discharge chamber centerline found that upstream retraction of the thruster's peak magnetic field does result in an upstream shift of the acceleration zone but the magnitude of the shift does not correspond one-to-one to the shift in the location of the peak radial magnetic field magnitude. Phase II test segment will include performing performance, stability, plume, and erosion measurements for the various candidate magnetic field topologies.

Kamhawi, Hani

Multiphysics Design Optimization and Additive Manufacturing of Nuclear Components (Final CRADA Report - Executive Summary)

Westinghouse Electric Company (WEC) actively participated in the advancement of the nuclear fuel and reactor design space and requested the help of Oak Ridge National Laboratory (ORNL) in the creation of a new design tool set. This report details the creation of a collection of software tool sets that are linked together to collectively assist WEC design engineers in developing novel ideas outside the normal scope of traditional nuclear fuel and reactor design formulas. Specifically, Siemens HEEDS, a design space exploration and parametric optimization software, monitored and changed parameters in a collection of softwares to meet the team’s objective. The HEEDS parametric optimization method, SHERPA, was developed to control the Siemens NX CAD platform to adjust the native CAD of a hexahedral spacer grid. This new geometry can be used to execute a topological design optimization by the NX Topology software add-in. The resulting geometry is additively manufacturable. This topological optimization occurred twice—once on the spacer grid’s spring, and once on the dimple geometry. These new geometries were imported by Siemens’ STAR-CCM+, a multiphysics structural and fluid dynamic computational solver in which the spring geometry is deflected to match the rod insertion configuration. Along with the dimple geometry, this new deflected spring was used to complete a hydraulic assessment of a single-unit cell comprising one rod, one spring, and two dimples. The HEEDS SHERPA algorithm ranks the design based on the final mass of the unit cell and the hydraulic pressure drop performance. The ORNL team demonstrated the ability to use this software and provided engineering judgement to apply modern aerospace aerodynamic design. The effort has been focused on thinking outside the conventional design space and redesigning a spacer grid to perform beyond the WEC set objectives. Furthermore, the ORNL team also demonstrated that the HEEDS optimization routine can independently develop a design that meets the WEC design goals. Although these designs were at a low technology readiness level, their demonstration confirmed the team’s capability to create novel advanced nuclear concepts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS

Finite elements for Matérn-type random fields: Uncertainty in computational mechanics and design optimization

This work highlights an approach for incorporating realistic uncertainties into scientific computing workflows based on finite elements, focusing on prevalent applications in computational mechanics and design optimization. We leverage Matérn-type Gaussian random fields (GRFs) generated using the SPDE method to model aleatoric uncertainties, including environmental influences, variating material properties, and geometric ambiguities. Our focus lies on delivering practical GRF realizations that accurately capture imperfections and variations and understanding how they impact the predictions of computational models as well as the shape and topology of optimized designs. Here we describe a numerical algorithm based on solving a generalized SPDE to sample GRFs on arbitrary meshed domains. The algorithm leverages established techniques and integrates seamlessly with the open-source finite element library MFEM and associated scientific computing workflows, like those found in industrial and national laboratory settings. Our solver scales efficiently for large-scale problems and supports various domain types, including surfaces and embedded manifolds. We showcase its versatility through biomechanics and topology optimization applications, emphasizing the potential to influence these domains. The flexibility and efficiency of SPDE-based GRF generation empowers us to run large-scale optimization problems on 2D and 3D domains, including finding optimized designs on embedded surfaces, and to generate design features and topologies beyond the reach of conventional techniques. Moreover, these capabilities allow us to model and quantify geometric uncertainties on reconstructed submanifolds, such as the interpolated surfaces of cerebral aneurysms provided by postprocessing CT scans. In addition to offering benefits in these specific domains, the proposed techniques transcend specific applications and generalize to arbitrary forward and backward problems in uncertainty quantification involving finite elements.

97 MATHEMATICS AND COMPUTING

Topology and layout optimization of discrete and continuum structures

The basic features of the ground structure method for truss structure an continuum problems are described. Problems with a large number of potential structural elements are considered using the compliance of the structure as the objective function. The design problem is the minimization of compliance for a given structural weight, and the design variables for truss problems are the cross-sectional areas of the individual truss members, while for continuum problems they are the variable densities of material in each of the elements of the FEM discretization. It is shown how homogenization theory can be applied to provide a relation between material density and the effective material properties of a periodic medium with a known microstructure of material and voids.

Bendsoe, Martin P.