Two Decades of Aerospace Vehicle Analysis with HyperSizer and HyperX
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Structural Weight Estimation↗
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Integration of Structural Analysis and Manufacturing Process Planning for Global Optimization with Automated Fiber Placement
Design of mass-efficient composite structures intended for Automated Fiber Placement (AFP) requires close interaction between structural analysis and manufacturing process planning. Tools exist for each of these disciplines, but software interplay has been insufficient for rapid and efficient design iteration. Within the NASA Advanced Composites Consortium (ACC), the Design for Manufacturing (DFM) task has made significant progress towards linking these disciplines and respective software – HyperX (design), CAPP (process planning), and VCP (tool path generation). The initial focus in previous work was on data exchange between disciplines. The ability to both export and consume composite design and manufacturing data to and from each tool. This paper focuses on the effort to automate and streamline the connection between the tools listed above, with the goal of being able to automatically generate a composite AFP design that is mass-efficient and manufacturable. The optimization method being pursued is a bi-level approach, where each tool performs optimization within its discipline. The optimization in HyperX is focused on mass and laminate strength, while CAPP is focused on maximizing manufacturability. VCP is used to generate fiber paths for each design iteration. These sub-processes are wrapped with a global level optimization, driven by HyperX, used to converge the design. This paper describes the current state of this effort, which is a completed HyperX-VCP iteration loop and initial work on the HyperX-CAPP iteration loop. Additionally, example results are shown for a wind blade structure with double curvature.
Automated Fiber Placement↗
Design for Manufacturing of Structures with Automated Fiber Placement via Integration of Analysis and Process Planning
Under the Design for Manufacturing (DFM) task in the NASA HiCAM program, significant process has been made towards establishing a fully automated optimization process that spans the structural analysis, design, and manufacturing process planning for Automated Fiber Placement (AFP) structures. Previous efforts in this area established the data formats and mapping processes needed to exchange data between disciplines. The software tools used in the framework are HyperX (structural optimization), CAPP (process planning), and VCP (AFP path generation). The work has culminated with automation of data exchanges and an optimization process that drives the three software toward convergence. Within this framework, HyperX is used to generate mass-optimum composite designs which are iterated with VCP and CAPP to improve manufacturability of the designs. As the ply manufacturing process is adjusted by CAPP and VCP, HyperX continually re-assesses the structural integrity of the part and makes adjustments to the laminate as needed. For example, the position of fiber steering and tow overlaps/gaps can necessitate changes to the laminate design. Once the design converges, the end result is a stack of plies that meets both structural and manufacturing requirements. This paper presents the details of the framework and demonstrations the automated process on several parts with significant double-curvature.
HiCAM↗
Thermoplastic Matrix Composite Design for Cryotanks Using Multiscale Modeling and Bayesian Optimization
Designing lightweight, robust cryogenic storage tanks is critical for future launch vehicles, in-space propellant storage, and hydrogen powered aircraft. This work presents a multiscale modeling and Bayesian optimization framework for the design of thermoplastic matrix composite cryotanks. Molecular dynamics simulations are first used to determine temperature-dependent constituent properties for candidate thermoplastic matrices, which are homogenized to the lamina scale using NASA’s Multiscale Analysis Tool (NASMAT). These lamina properties, in combination with laminate family generation rules, are evaluated in HyperX structural optimization software to identify stacking sequences that meet all cryogenic load requirements. A Bayesian optimization framework is applied, with HyperX in the loop (via the HyperX API) to efficiently search across material and laminate design variables, yielding an optimized cryotank configuration with significant reductions in design cycle time compared to exhaustive search approaches.
thermoplastics↗
Effects of Defects Analysis and Sizing Framework for Efficient Design of Composite Structures
Design of large composite structures requires striking a balance between permitted flaw size,strength margins, weight, and production rate. Stringent requirements manufacturing flaws can result in a lightweight structure because the strength properties are assumed to be closer to pristine. However, these stringent requirements can lead to production delays due to increased inspection and rework needed during the layup and rejection of parts after cure. Conversely, permitting larger flaws can reduce production delays, but will likely result in a heavier structure due to increased conservatism needed to maintain acceptable structural margins. The tradeoff between these criteria can vary between different structures and material systems, so the balance between manufacturing and design requirements is always a moving target. Assessment of this tradeoff requires having the ability to quickly evaluate the impact of flaw size on strength margin across an entire structure for a large number of load cases. The approach taken in this work is to implement an effects of defects analysis and sizing framework within HyperX. HyperX performs optimization of composite structures; this capability has been enhanced to include structural flaw data in the margin of safety calculations performed during optimization. Both the flaw import process and analysis of flaws have been generalized such that any flaw type from any source can be considered. The resulting tool enables rapid assessment of the impact of defects both at a vehicle and part level.
Effects of defects↗
Integration of Design Data Into Automated Fiber Placement Process Planning Metrics
With the ever-expanding aviation industry, a need is arising for more rapid production of composite aircraft to meet increasing demand. State-of-the-art aircraft such as the Boeing 787showcase 50% composite material usage by weight, highlighting this emerging industry-wide adoption of the material system. Currently, many of the large structures associated with these aircraft are manufactured additively via Automated Fiber Placement (AFP). The AFP process shows great potential for efficient manufacturing, however unavoidable defects still occur because of tool surface geometry, placement errors, or poor process planning, resulting in decreased quality and throughput. Due to such effects, it is critical to incorporate design for manufacturing (DFM) principles to achieve the optimal manufacturing plan and resulting structure. This work will develop a methodology for incorporating design information into process planning metrics in an automated fashion to achieve an optimal set of process inputs.The analysis incorporates HyperX, Computer Aided Process Planning (CAPP) and Vericut Composite Programming (VCP). Safety margins from HyperX are imported into CAPP where AFP defects are mapped to the values. The resulting margins are then incorporated into the CAPP manufacturability algorithms, creating a design informed process planning analysis
Automated Fiber Placement↗
Effects of Defects Analysis and Sizing Framework for Efficient Design of Composite Structures
Design of large composite structures requires striking a balance between permitted flaw size,strength margins, weight, and production rate. Stringent requirements manufacturing flaws can result in a lightweight structure because the strength properties are assumed to be closer to pristine. However, these stringent requirements can lead to production delays due to increased inspection and rework needed during the layup and rejection of parts after cure. Conversely, permitting larger flaws can reduce production delays, but will likely result in a heavier structure due to increased conservatism needed to maintain acceptable structural margins. The tradeoff between these criteria can vary between different structures and material systems, so the balance between manufacturing and design requirements is always a moving target. Assessment of this tradeoff requires having the ability to quickly evaluate the impact of flaw size on strength margin across an entire structure for a large number of load cases. The approach taken in this work is to implement an effects of defects analysis and sizing framework within HyperX. HyperX performs optimization of composite structures; this capability has been enhanced to include structural flaw data in the margin of safety calculations performed during optimization. Both the flaw import process and analysis of flaws have been generalized such that any flaw type from any source can be considered. The resulting tool enables rapid assessment of the impact of defects both at a vehicle and part level.
Effects of defects↗
Enabling Future Robotic Missions with Multicore Processors
Recent commercial developments in multicore processors (e.g. Tilera, Clearspeed, HyperX) have provided an option for high performance embedded computing that rivals the performance attainable with FPGA-based reconfigurable computing architectures. Furthermore, these processors offer more straightforward and streamlined application development by allowing the use of conventional programming languages and software tools in lieu of hardware design languages such as VHDL and Verilog. With these advantages, multicore processors can significantly enhance the capabilities of future robotic space missions. This paper will discuss these benefits, along with onboard processing applications where multicore processing can offer advantages over existing or competing approaches. This paper will also discuss the key artchitecural features of current commercial multicore processors. In comparison to the current art, the features and advancements necessary for spaceflight multicore processors will be identified. These include power reduction, radiation hardening, inherent fault tolerance, and support for common spacecraft bus interfaces. Lastly, this paper will explore how multicore processors might evolve with advances in electronics technology and how avionics architectures might evolve once multicore processors are inserted into NASA robotic spacecraft.
multi-core processor↗
Application of a Rapid Design Tool to a 3D Woven Structural Joint
The optimization of composite structural joints is an iterative process and a multiscale problem. High fidelity finite element modeling of joints with 3D woven and laminated materials can become computationally expensive. The aim of this paper is to establish a reliable analysis process for the optimization of a composite Y-joint (curved Pi-joint), to be used in an aircraft fuselage, using commercial rapid joint design, analysis, and optimization software. The rapid joint design tool was investigated as a substitute and/or complement to a finite element analysis software. A composite Pi-joint and a composite Y-joint were evaluated using the rapid joint design tool to determine the applicability and limits of the software. Furthermore, three main preliminary parametric studies were performed to better understand the capability of the tool in predicting the stress distributions and trends in the Y-joint. The parameters investigated were the joint curvature, the laminated skin thickness, the adhesive systems, and the ply composition. Lastly, trends in predicted failure load were produced as a function of skin thickness (16ply, 24ply and 32ply). Failure loads were found with varying joint curvature and skin thickness using stress-based adherend failure criterion. The rapid joint design tool was also validated against existing experimental results.
Bonded Joints↗