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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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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Multi-Physics Based Thermo-Well Fatigue Design Tool

In this study, mathematical-based models for fatigue life were developed for Resistance Temperature Detectors (RTDs)/thermo-wells in high-pressure, cryogenic flow environments. A literature review that identified bench-scale stainless steel fatigue data at cryogenic temperatures that can be used to validate fatigue life mathematical models was pursued. Developing the ability to predict the fatigue life of RTDs/thermo-wells in high-pressure, cryogenic flow environments, especially liquid oxygen (LOX), will lead to a lower incidence of RTD damage and failure during propulsion test activities. During this performance period, the project was transitioned to a computational RTD/thermos-well fatigue modeling effort rather than the previously proposed experimental fatigue testing in FY19 since the computational modeling approach will provide a better fundamental understanding of fatigue behavior at cryogenic temperatures prior to pursuing potentially costly experimental tests. Due to COVID-19 issues impairing access to some needed university partnerships, tools and lab facilities, FY20efforts are continuing into FY21 and will be reported upon in greater detail in the FY21 report

Harry Ryan↗
DOE OSTI2022

Recent Developments in the WEC-Sim Open-Source Design Tool: Preprint

WEC-Sim (Wave Energy Converter SIMulator) is an open-source code for simulating wave energy converters, which has been actively developed and applied to simulate a wide variety of device archetypes and has become a popular tool since its initial release in 2014. WEC-Sim is developed jointly by the National Renewable Energy Laboratory (NREL) and Sandia National Laboratories (SNL) within the MATLAB/SIMULINK environment. Figure 1 illustrates a general wave-to-wire model which begins with a deployment site resource characterization, which is used to complete the hydrodynamic simulation of a single WEC (or array), with the power generation profile imported to a grid simulator to understand the influence on the local electrical network. While modelling the entire wave-to-wire is difficult and encompass multiple time scales and physics, WEC-Sim is focused on the hydrodynamics simulation to predict, analyze and optimize WEC dynamics and power performance. WEC-Sim simulations are performed in the time domain based on the radiation and diffraction method using hydrodynamics coefficients derived from boundary element method (BEM) based-frequency-domain potential flow solvers (e.g., WAMIT, NEMOH, Capytaine, or ANSYS-AQWA). Within this level of modeling fidelity, WEC-Sim can handle floating body hydrodynamics, mechanical and electrical power generation methods, advanced control implementation, mooring systems, and other unique applications such as desalination. Table 1 lists additional WEC-Sim functionalities, which are created using prebuilt Simulink blocks and MATLAB scripts that can simulate a wide range of floating systems and the corresponding auxiliary subsystems.

hydrodynamics modeling↗
DOE OSTI2024

Advanced Features and Recent Developments in the WEC-Sim Open-Source Design Tool: Preprint

WEC-Sim is an open-source tool developed in Matlab/Simulink to simulate wave energy converters. WEC-Sim has been developed jointly by the National Renewable Energy Laboratory (NREL) and Sandia National Laboratories (SNL) since its initial release in 2014. WEC-Sim simulations are performed in the time domain based on the radiation and diffraction method using hydrodynamics coefficients derived from boundary element method (BEM)-based frequency-domain potential flow solvers (e.g., WAMIT, NEMOH, Capytaine, or ANSYS-AQWA). Within this level of modeling fidelity, WEC-Sim can handle floating body hydrodynamics, mechanical and electrical power generation methods, advanced control implementation, mooring systems, and other unique applications such as desalination. WEC-Sim functionalities are developed using Simulink blocks and Matlab functions. WEC-Sim is capabilities include simulation of different wave conditions, constraints and PTOs, body dynamics, mooring systems, among other advanced features such as nonlinear hydrodynamics, nonlinear PTOs, body-to-body interactions, etc.

hydrodynamics modeling↗
NASA NTRS2012

A Design Rationale Capture Tool to Support Design Verification and Re-use

A design rationale tool (DR tool) was developed to capture design knowledge to support design verification and design knowledge re-use. The design rationale tool captures design drivers and requirements, and documents the design solution including: intent (why it is included in the overall design); features (why it is designed the way it is); information about how the design components support design drivers and requirements; and, design alternatives considered but rejected. For design verification purposes, the tool identifies how specific design requirements were met and instantiated within the final design, and which requirements have not been met. To support design re-use, the tool identifies which design decisions are affected when design drivers and requirements are modified. To validate the design tool, the design knowledge from the Taxiway Navigation and Situation Awareness (T-NASA; Foyle et al., 1996) system was captured and the DR tool was exercised to demonstrate its utility for validation and re-use.

design verification↗
DOE OSTI2025

Lightweight Metal Stamping Optimization Enabled by Artificial Intelligence

Successfully manufacturing an automotive body structure made via the sheet metal stamping process depends upon simultaneous consideration of component design, tooling design, stamping process control, and material properties. In many cases, introducing lightweight sheet materials (e.g., aluminum alloys, magnesium alloys, advanced high strength steels) holds the potential to significantly reduce vehicle weight, but challenges the stamping process by introducing materials with inherently less ductility. Successful and repeatable applications require co-developing the stamping process controls with the varying material properties, including formability. During the stamping process, as soon as the forming limit of the sheet is exceeded, the material shows localized necking which quickly leads to splits. Controlling process variability to avoid these material splits will enable deployment of less formable, lighter, and stronger materials for stamped automotive components. A typical optimization procedure for manufacturing requires an iterative process involving parameter setting, execution of computational simulations, and modifying the parameters. The entire process demands substantial computational time, making it impractical for real-time feedback towards rapid corrective actions required for in-line control for running production processes. To overcome this challenge, artificial intelligence (AI) can be leveraged to determine optimal manufacturing parameters within a single manufacturing cycle time. This research proposes an in-line optimization framework incorporating a trained AI model to predict kidney-shaped die forming. Preliminary results indicate that the AI framework can accurately predict draw-in values based on a given parameter set, a process referred to as forward prediction. Furthermore, the AI framework can also predict the optimal parameter set that leads to the desired draw-in values, referred to as inverse optimization (or backward prediction). This research has been performed in collaborations with USCAR (US Council for Automotive Research) and AutoForm. The members of USCAR are Ford, GM, and Stellantis.

36 MATERIALS SCIENCE↗
NASA NTRS1942

Design of Tools for Press-countersinking or Dimpling 0.040-inch-thick-24S-T Sheet

A set of dimpling tools was designed for 0.040-inch 24S-T sheet and flush-type rivets 1/8 inch in diameter with 100 degree countersunk heads. The dimples produced under different conditions of pressure, sheet thickness, and drill diameter are presented as cross-sectional photographs magnified 20 times. The most satisfactory values for the dimpling tools were found to be: maximum punch diameter, 0.231 inch; maximum die diameter, 0.223 inch; maximum mandrel diameter, 0.128 inch; dimple angle, 100 degree; punch springback angle, 1 1/2 degree; and die springback angle, 2 degree.

Templin, R L↗
NASA NTRS1984

Design enhancement tools in MSC/NASTRAN

Design sensitivity is the calculation of derivatives of constraint functions with respect to design variables. While a knowledge of these derivatives is useful in its own right, the derivatives are required in many efficient optimization methods. Constraint derivatives are also required in some reanalysis methods. It is shown where the sensitivity coefficients fit into the scheme of a basic organization of an optimization procedure. The analyzer is to be taken as MSC/NASTRAN. The terminator program monitors the termination criteria and ends the optimization procedure when the criteria are satisfied. This program can reside in several plances: in the optimizer itself, in a user written code, or as part of the MSC/EOS (Engineering Operating System) MSC/EOS currently under development. Since several excellent optimization codes exist and since they require such very specialized technical knowledge, the optimizer under the new MSC/EOS is considered to be selected and supplied by the user to meet his specific needs and preferences. The one exception to this is a fully stressed design (FSD) based on simple scaling. The gradients are currently supplied by various design sensitivity options now existing in MSC/NASTRAN's design sensitivity analysis (DSA).

Wallerstein, D. V.↗