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NASA NTRS1999

Aerospace Systems Design in NASA's Collaborative Engineering Environment

Past designs of complex aerospace systems involved an environment consisting of collocated design teams with project managers, technical discipline experts, and other experts (e.g. manufacturing and systems operations). These experts were generally qualified only on the basis of past design experience and typically had access to a limited set of integrated analysis tools. These environments provided less than desirable design fidelity, often lead to the inability of assessing critical programmatic and technical issues (e.g., cost risk, technical impacts), and generally derived a design that was not necessarily optimized across the entire system. The continually changing, modern aerospace industry demands systems design processes that involve the best talent available (no matter where it resides) and access to the best design and analysis tools. A solution to these demands involves a design environment referred to as collaborative engineering. The collaborative engineering environment evolving within the National Aeronautics and Space Administration (NASA) is a capability that enables the Agency's engineering infrastructure to interact and use the best state-of-the-art tools and data across organizational boundaries. Using collaborative engineering, the collocated team is replaced with an interactive team structure where the team members are geographically distributed and the best engineering talent can be applied to the design effort regardless of physical location. In addition, a more efficient, higher quality design product is delivered by bringing together the best engineering talent with more up-to-date design and analysis tools. These tools are focused on interactive, multidisciplinary design and analysis with emphasis on the complete life cycle of the system, and they include nontraditional, integrated tools for life cycle cost estimation and risk assessment. NASA has made substantial progress during the last two years in developing a collaborative engineering environment. NASA is planning to use this collaborative engineering infrastructure to provide better aerospace systems life cycle design and analysis, which includes analytical assessment of the technical and programmatic aspects of a system from "cradle to grave." This paper describes the recent NASA developments in the area of collaborative engineering, the benefits (realized and anticipated) of using the developed capability, and the long-term plans for implementing this capability across the Agency.

Monell, Donald W.↗

NASA NTRS2005

Tow-Steered Panels With Holes Subjected to Compression or Shear Loads

Tailoring composite laminates to vary the fiber orientations within a fiber layer of a laminate to address non-uniform stress states and provide structural advantages such as the alteration of principal load paths has potential application to future low-cost, light-weight structures for commercial transport aircraft. Evaluation of this approach requires the determination of the effectiveness of stiffness tailoring through the use of curvilinear fiber paths in flat panels including the reduction of stress concentrations around the holes and the increase in load carrying capability. Panels were designed through the use of an optimization code using a genetic algorithm and fabricated using a tow-steering approach. Manufacturing limitations, such as the radius of curvature of tows the machine could support, avoidance of wrinkling of fibers and minimization of gaps between fibers were considered in the design process. Variable stiffness tow-steered panels constructed with curvilinear fiber paths were fabricated so that the design methodology could be verified through experimentation. Finite element analysis where each element s stacking sequence was accurately defined is used to verify the behavior predicted based on the design code. Experiments on variable stiffness flat panels with central circular holes were conducted with the panels loaded in axial compression or shear. Tape and tow-steered panels are used to demonstrate the buckling, post-buckling and failure behavior of elastically tailored panels. The experimental results presented establish the buckling performance improvements attainable by elastic tailoring of composite laminates.

Jegley, Dawn C.↗

NASA NTRS2008

Evolution of Safety Analysis to Support New Exploration Missions

NASA is currently developing the Ares I launch vehicle as a key component of the Constellation program which will provide safe and reliable transportation to the International Space Station, back to the moon, and later to Mars. The risks and costs of the Ares I must be significantly lowered, as compared to other manned launch vehicles, to enable the continuation of space exploration. It is essential that safety be significantly improved, and cost-effectively incorporated into the design process. This paper justifies early and effective safety analysis of complex space systems. Interactions and dependences between design, logistics, modeling, reliability, and safety engineers will be discussed to illustrate methods to lower cost, reduce design cycles and lessen the likelihood of catastrophic events.

Thrasher, Chard W.↗

NASA NTRS2014

NASA's Space Launch System: A Cornerstone Capability for Exploration

Under construction today, the National Aeronautics and Space Administration's (NASA) Space Launch System (SLS), managed at the Marshall Space Flight Center, will provide a robust new capability for human and robotic exploration beyond Earth orbit. The vehicle's initial configuration, scheduled for first launch in 2017, will enable human missions into lunar space and beyond, as well as provide game-changing benefits for space science missions, including offering substantially reduced transit times for conventionally designed spacecraft. From there, the vehicle will undergo a series of block upgrades via an evolutionary development process designed to expedite mission capture as capability increases. The Space Launch System offers multiple benefits for a variety of utilization areas. From a mass-lift perspective, the initial configuration of the vehicle, capable of delivering 70 metric tons (t) to low Earth orbit (LEO), will be the world's most powerful launch vehicle. Optimized for missions beyond Earth orbit, it will also be the world's only exploration-class launch vehicle capable of delivering 25 t to lunar orbit. The evolved configuration, with a capability of 130 t to LEO, will be the most powerful launch vehicle ever flown. From a volume perspective, SLS will be compatible with the payload envelopes of contemporary launch vehicles, but will also offer options for larger fairings with unprecedented volume-lift capability. The vehicle's mass-lift capability also means that it offers extremely high characteristic energy for missions into deep space. This paper will discuss the impacts that these factors - mass-lift, volume, and characteristic energy - have on a variety of mission classes, particularly human exploration and space science. It will address the vehicle's capability to enable existing architectures for deep-space exploration, such as those documented in the Global Exploration Roadmap, a capabilities-driven outline for future deep-space voyages created by the International Space Exploration Coordination Group, which represents 12 of the world's space agencies. In addition, this paper will detail this new rocket's capability to support missions beyond the human exploration roadmap, including robotic precursor missions to other worlds or uniquely high-mass space operation facilities in Earth orbit. As this paper will explain, the SLS Program is currently building a global infrastructure asset that will provide robust space launch capability to deliver sustainable solutions for exploration.

Creech, Stephen D.↗

NASA NTRS2014

NASA Space Launch System: A Cornerstone Capability for Exploration

Under construction today, the National Aeronautics and Space Administration's (NASA) Space Launch System (SLS), managed at the Marshall Space Flight Center, will provide a robust new capability for human and robotic exploration beyond Earth orbit. The vehicle's initial configuration, sched will enable human missions into lunar space and beyond, as well as provide game-changing benefits for space science missions, including offering substantially reduced transit times for conventionally designed spacecraft. From there, the vehicle will undergo a series of block upgrades via an evolutionary development process designed to expedite mission capture as capability increases. The Space Launch System offers multiple benefits for a variety of utilization areas. From a mass-lift perspective, the initial configuration of the vehicle, capable of delivering 70 metric tons (t) to low Earth orbit (LEO), will be the world's most powerful launch vehicle. Optimized for missions beyond Earth orbit, it will also be the world's only exploration-class launch vehicle capable of delivering 25 t to lunar orbit. The evolved configuration, with a capability of 130 t to LEO, will be the most powerful launch vehicle ever flown. From a volume perspective, SLS will be compatible with the payload envelopes of contemporary launch vehicles, but will also offer options for larger fairings with unprecedented volume-lift capability. The vehicle's mass-lift capability also means that it offers extremely high characteristic energy for missions into deep space. This paper will discuss the impacts that these factors - mass-lift, volume, and characteristic energy - have on a variety of mission classes, particularly human exploration and space science. It will address the vehicle's capability to enable existing architectures for deep-space exploration, such as those documented in the Global Exploration Roadmap, a capabilities-driven outline for future deep-space voyages created by the International Space Exploration Coordination Group, which represents 14 of the world's space agencies. In addition, this paper will detail this new rocket's capability to support missions beyond the human exploration roadmap, including robotic precursor missions to other worlds or uniquely high-mass space operation facilities in Earth orbit. As this paper will explain, the SLS Program is currently building a global infrastructure asset that will provide robust space launch capability to deliver sustainable solutions for exploration.

Creech, Stephen D.↗

NASA NTRS2017

High-Fidelity Multidisciplinary Design Optimization of Aircraft Configurations

To evaluate new airframe technologies we need design tools based on high-fidelity models that consider multidisciplinary interactions early in the design process. The overarching goal of this NRA is to develop tools that enable high-fidelity multidisciplinary design optimization of aircraft configurations, and to apply these tools to the design of high aspect ratio flexible wings. We develop a geometry engine that is capable of quickly generating conventional and unconventional aircraft configurations including the internal structure. This geometry engine features adjoint derivative computation for efficient gradient-based optimization. We also added overset capability to a computational fluid dynamics solver, complete with an adjoint implementation and semiautomatic mesh generation. We also developed an approach to constraining buffet and started the development of an approach for constraining utter. On the applications side, we developed a new common high-fidelity model for aeroelastic studies of high aspect ratio wings. We performed optimal design trade-o s between fuel burn and aircraft weight for metal, conventional composite, and carbon nanotube composite wings. We also assessed a continuous morphing trailing edge technology applied to high aspect ratio wings. This research resulted in the publication of 26 manuscripts so far, and the developed methodologies were used in two other NRAs. 1

Martins, Joaquim R. R. A.↗

NASA NTRS2021

Design of a Tiltwing Concept Vehicle for Urban Air Mobility

NASA is establishing a fleet of conceptual air vehicle designs to support research and development for Urban Air Mobility (UAM). This fleet of vehicles will enable examination of the sensitivity of UAM vehicle designs to technology assumptions, identify key research and development needs for UAM aircraft, and provide the UAM community with reference vehicles that are publicly available and based upon known assumptions. To date, four six-passenger reference vehicles have been established: a quadrotor, a side-by-side, a lift-plus-cruise, and a quiet single main rotor helicopter; this paper adds a tiltwing vehicle to the fleet. This paper details the design process that was followed in order to establish the tiltwing vehicle in the fleet, including early conceptual design decisions, sizing and configuration trades, structural analyses, proprotor design and aeroacoustic predictions, and aerodynamic analyses. The resulting tiltwing vehicle uses a turboelectric propulsion system to power six proprotors positioned on a tilting main wing and two tilting proprotors positioned on the horizontal tail. This paper also compares the resulting tiltwing vehicle with the other six-passenger reference vehicles, including an updated lift-plus-cruise vehicle, and then proposes future studies. The fleet of UAM reference vehicles will continue to evolve; subsequent versions of the reference vehicles will be based upon the results of future trade studies and technology developments.

Urban Air Mobility↗

NASA NTRS2022

Design of Rigid-Flex PCB Robotics Leveraging Validated Finite Element Simulations

The use of rigid-flex printed circuit board (PCB) as primary structure has the potential to reduce the weight and volume of robotic systems. In the case of robotics for interplanetary exploration, these systems can leverage origami-inspired folding for increased mobility options and reduced storage volume. Folding rigid-flex PCB robotics can be constructed with rigid PCB connected by short Nomex fabric hinges coupled with flex PCB ribbon cables that permits enhanced system flexibility and energy dissipation to promote impact survivability. This paper presents a design methodology of rigid-flex PCB systems with an emphasis on impact resistance. The design process considers solder joint adequacy, panel bending, and fracture using a finite element (FE) model. The proposed design methodology is developed using a case study with NASA JPL's Pop-Up Folding Flat Explorer Robot (PUFFER). First, the finite-element (FE) modeling methodology is presented with consideration to both frequency and time-domain modeling applications, which include operational self-contact analysis and high impact scenarios. The time-domain impact modeling methodology utilizes hyperelastic material properties for the Nomex hinges. This modeling method is validated using image correlation of PUFFER drop tests. A flowchart is presented to guide users through a validated Abaqus modeling procedure for highly flexible rigid-flex systems. Next, a case study is presented in which PUFFER is subject to drop heights representative of falls into Lunar pits and then the design is refined for a more optimum impact performance. Finally, the results of the case study are used to inform a generalized design methodology for rigid-flex PCB robotics subject to high-impact loads with the considerations presented.

John Bell↗

NASA NTRS2022

Design of Rigid-Flex PCB Robotics Leveraging Validated Finite Element Simulations

The use of rigid-flex printed circuit board (PCB) as primary structure has the potential to reduce the weight and volume of robotic systems. In the case of robotics for interplanetary exploration, these systems can leverage origamiinspired folding for increased mobility options and reduced storage volume. Folding rigid-flex PCB robotics can be constructed with rigid PCB connected by short Nomex fabric hinges coupled with flex PCB ribbon cables that permits enhanced system flexibility and energy dissipation to promote impact survivability. This paper presents a design methodology of rigidflex PCB systems with an emphasis on impact resistance. The design process considers solder joint adequacy, panel bending, and fracture using a finite element (FE) model. The proposed design methodology is developed using a case study with NASA JPL’s Pop-Up Folding Flat Explorer Robot (PUFFER). First, the finite-element (FE) modeling methodology is presented with consideration to both frequency and time-domain modeling applications, which include operational self-contact analysis and high impact scenarios. The time-domain impact modeling methodology utilizes hyperelastic material properties for the Nomex hinges. This modeling method is validated using image correlation of PUFFER drop tests. A flowchart is presented to guide users through a validated Abaqus modeling procedure for highly flexible rigid-flex systems. Next, a case study is presented in which PUFFER is subject to drop heights representative of falls into Lunar pits and then the design is refined for a more optimum impact performance. Finally, the results of the case study are used to inform a generalized design methodology for rigid-flex PCB robotics subject to high-impact loads with the considerations presented.

de la Croix, Jean-Pierre↗

DOE OSTI2021

Machine Learning Tools Set for Natural Gas Fuel Cell System Design

This study is focusing on leveraging the system design tools set for the next-generation solid oxide fuel cell (SOFC) based natural gas fuel cell (NGFC) system. Conventionally, system design and optimization of NGFC systems rely heavily on traditional reduced order model (ROM) techniques and designers’ experience level. For overcoming the technical barriers of system design, multiple multi-physics models and machine learning (ML) tools have been utilized to automate the conceptual design process and enhance the reliability of solutions for the NGFC system. The proposed tools set includes a physics-informed ML tool for automated ROM construction that leverages advances in deep neural networks to significantly reduce ROM prediction error for the NGFC power island compared to traditional approaches. The constructed physics-informed ML ROM can be used in system design, and optimization tools set Institute for the Design of Advanced Energy Systems (IDAES) Process Systems Engineering (PSE) framework. The tools set also provides a user-friendly graphic user interface built within Jupyter Notebooks, and the complete tools set is open-source public available.

Wang, Dewei↗

NASA NTRSDate not supplied

Knowledge Discovery for Early Failure Assessment of Complex Engineered Systems Using Natural Language Processing

Emerging complex engineered systems may have unexpected safety issues due to novel operational environments, increasing autonomy, human-machine interaction, and other factors. To prevent failures in operation or testing that necessitate costly redesign, it is desirable to predict likely failure modes early in the design process. Text-based information about past engineering failures presents one possible solution by facilitating the retrieval of information that can inform new designs. However, identifying documents containing relevant information and extracting required information can be prohibitively time-consuming when implemented at scale. In this research, an automated natural language processing-based framework is proposed to discover relevant knowledge from documents containing failure-related design information. Documents containing usable information are filtered using sentiment analysis based on a custom lexicon specialized for engineering design and by filtering out documents containing only irrelevant topics. Next, from the identified usable documents, information relating to engineering failures, contributing factors that can be controlled at design time (“risk factors”), and recommended preventative actions are extracted. Semantic similarity is then used to group similar pieces of extracted information for improved generalizability. The proposed framework is applied to NASA’s Lessons Learned Information System (LLIS). The framework can be used to identify documents containing usable failure-related design information from other databases, extract relevant information from these documents, and generalize the acquired knowledge such that it can be applied to novel systems.

Sequoia R. Andrade↗

NASA NTRS1993

Functional categories for future flight deck designs

With the addition of each new system on the flight deck, the danger of increasing overall operator workload while reducing crew understanding of critical mission information exists. The introduction of more powerful onboard computers, larger databases, and the increased use of electronic display media may lead to a situation of flight deck 'sophistication' at the expense of losses in flight crew capabilities and situational awareness. To counter this potentially negative impact of new technology, research activities are underway to reassess the flight deck design process. The fundamental premise of these activities is that a human-centered, systems-oriented approach to the development of advanced civil aircraft flight decks will be required for future designs to remain ergonomically sound and economically competitive. One of the initial steps in an integrated flight deck process is to define the primary flight deck functions needed to support the mission goals of the vehicle. This would allow the design team to evaluate candidate concepts in relation to their effectiveness in meeting the functional requirements. In addition, this would provide a framework to aid in categorizing and bookkeeping all of the activities that are required to be performed on the flight deck, not just activities of the crew or of a specific system. This could then allow for a better understanding and allocation of activities in the design, an understanding of the impact of a specific system on overall system performance, and an awareness of the total crew performance requirements for the design. One candidate set of functional categories that could be used to guide an advanced flight deck design are described.

Abbott, Terence S.↗

NASA NTRSDate not supplied

Knowledge Discovery for Early Failure Assessment of Complex Engineered Systems Using Natural Language Processing

Emerging complex engineered systems may have unexpected safety issues due to novel operational environments, increasing autonomy, human-machine interaction, and other factors. To prevent failures in operation or testing that necessitate costly redesign, it is desirable to predict likely failure modes early in the design process. Information about past engineering failures in natural language format presents one possible solution by enabling the retrieval of information that can inform new designs. However, identifying documents containing usable information and extracting the required information can be prohibitively time-consuming when implemented at scale. In this research, an automated natural language processing (NLP) framework is proposed to discover relevant knowledge from documents containing failure-related design information. The framework is applied to NASA’s Lessons Learned Information System (LLIS),which is publicly available. Documents containing usable information are filtered using two different NLP-based models. Next, from the identified usable documents, a failure taxonomy is extracted using a partitioned hierarchical topic modeling approach. Partitions of the document describe different sections of the failure taxonomy – i.e., failure, cause of failure, and recommendations – as indicated by the structure of the original document. The extracted failure taxonomy can be leveraged in early design failure assessment methods. Moreover, the framework can be used to identify documents containing usable failure-related design information from other databases and extract relevant information from these documents.

Documentation and Information Science↗

NASA NTRSDate not supplied

Knowledge Discovery for Early Failure Assessment of Complex Engineered Systems Using Natural Language Processing

Emerging complex engineered systems may have unexpected safety issues due to novel operational environments, increasing autonomy, human-machine interaction, and other factors. To prevent failures in operation or testing that necessitate costly redesign, it is desirable to predict likely failure modes early in the design process. Information about past engineering failures in natural language format presents one possible solution by enabling the retrieval of information that can inform new designs. However, identifying documents containing usable information and extracting the required information can be prohibitively time-consuming when implemented at scale. In this research, an automated natural language processing (NLP) framework is proposed to discover relevant knowledge from documents containing failure-related design information. The framework is applied to NASA’s Lessons Learned Information System (LLIS),which is publicly available. Documents containing usable information are filtered using two different NLP-based models. Next, from the identified usable documents, a failure taxonomy is extracted using a partitioned hierarchical topic modeling approach. Partitions of the document describe different sections of the failure taxonomy – i.e., failure, cause of failure, and recommendations – as indicated by the structure of the original document. The extracted failure taxonomy can be leveraged in early design failure assessment methods. Moreover, the framework can be used to identify documents containing usable failure-related design information from other databases and extract relevant information from these documents.

Documentation and Information Science↗

NASA NTRS1998

Aircraft Structural Mass Property Prediction Using Conceptual-Level Structural Analysis

This paper describes a methodology that extends the use of the Equivalent LAminated Plate Solution (ELAPS) structural analysis code from conceptual-level aircraft structural analysis to conceptual-level aircraft mass property analysis. Mass property analysis in aircraft structures has historically depended upon parametric weight equations at the conceptual design level and Finite Element Analysis (FEA) at the detailed design level ELAPS allows for the modeling of detailed geometry, metallic and composite materials, and non-structural mass coupled with analytical structural sizing to produce high-fidelity mass property analyses representing fully configured vehicles early in the design process. This capability is especially valuable for unusual configuration and advanced concept development where existing parametric weight equations are inapplicable and FEA is too time consuming for conceptual design. This paper contrasts the use of ELAPS relative to empirical weight equations and FEA. ELAPS modeling techniques are described and the ELAPS-based mass property analysis process is detailed Examples of mass property stochastic calculations produced during a recent systems study are provided This study involved the analysis of three remotely piloted aircraft required to carry scientific payloads to very high altitudes at subsonic speeds. Due to the extreme nature of this high-altitude flight regime,few existing vehicle designs are available for use in performance and weight prediction. ELAPS was employed within a concurrent engineering analysis process that simultaneously produces aerodynamic, structural, and static aeroelastic results for input to aircraft performance analyses. The ELAPS models produced for each concept were also used to provide stochastic analyses of wing structural mass properties. The results of this effort indicate that ELAPS is an efficient means to conduct multidisciplinary trade studies at the conceptual design level.

Sexstone, Matthew G.↗

NASA NTRS1998

Aircraft Structural Mass Property Prediction Using Conceptual-Level Structural Analysis

This paper describes a methodology that extends the use of the Equivalent LAminated Plate Solution (ELAPS) structural analysis code from conceptual-level aircraft structural analysis to conceptual-level aircraft mass property analysis. Mass property analysis in aircraft structures has historically depended upon parametric weight equations at the conceptual design level and Finite Element Analysis (FEA) at the detailed design level. ELAPS allows for the modeling of detailed geometry, metallic and composite materials, and non-structural mass coupled with analytical structural sizing to produce high-fidelity mass property analyses representing fully configured vehicles early in the design process. This capability is especially valuable for unusual configuration and advanced concept development where existing parametric weight equations are inapplicable and FEA is too time consuming for conceptual design. This paper contrasts the use of ELAPS relative to empirical weight equations and FEA. ELAPS modeling techniques are described and the ELAPS-based mass property analysis process is detailed. Examples of mass property stochastic calculations produced during a recent systems study are provided. This study involved the analysis of three remotely piloted aircraft required to carry scientific payloads to very high altitudes at subsonic speeds. Due to the extreme nature of this high-altitude flight regime, few existing vehicle designs are available for use in performance and weight prediction. ELAPS was employed within a concurrent engineering analysis process that simultaneously produces aerodynamic, structural, and static aeroelastic results for input to aircraft performance analyses. The ELAPS models produced for each concept were also used to provide stochastic analyses of wing structural mass properties. The results of this effort indicate that ELAPS is an efficient means to conduct multidisciplinary trade studies at the conceptual design level.

Sexstone, Matthew G.↗

NASA NTRS2016

Evaluation of Novel Liner Concepts for Fan and Airframe Noise Reduction

This paper presents a review of four novel liner concepts: soft vanes, over-the-rotor liners, external liners, and flap side-edge liners. A number of similarities in the design and evaluation of these concepts emerged during these investigations. Since these were the first attempts to study these particular liner concepts, there was limited information to guide the design process. In all cases, the target frequencies (or frequency range) were known, but the optimum acoustic impedance and optimum liner placement were typically not known. For these cases, the maximum available surface was used and a c-impedance was targeted based on the assumption the sound field impinges on the surface at normal incidence. This choice proved fruitful for every application. An impedance prediction model was used to design variable-depth liner configurations, and a graphical design code (ILIAD) was developed to aid in this process. The ability to build increasingly complex liner configurations via additive manufacturing was key, such that multiple designs could quickly be tested in a normal incidence impedance tube. The Two-Thickness Method was used to evaluate available bulk materials, such that bulk liners could also be considered for each application. These novel liner concepts provide sufficient noise reduction to warrant further investigations.

Jones, M. G.↗

NASA NTRS1990

Integrated topology and shape optimization in structural design

Structural optimization procedures usually start from a given design topology and vary its proportions or boundary shapes to achieve optimality under various constraints. Two different categories of structural optimization are distinguished in the literature, namely sizing and shape optimization. A major restriction in both cases is that the design topology is considered fixed and given. Questions concerning the general layout of a design (such as whether a truss or a solid structure should be used) as well as more detailed topology features (e.g., the number and connectivities of bars in a truss or the number of holes in a solid) have to be resolved by design experience before formulating the structural optimization model. Design quality of an optimized structure still depends strongly on engineering intuition. This article presents a novel approach for initiating formal structural optimization at an earlier stage, where the design topology is rigorously generated in addition to selecting shape and size dimensions. A three-phase design process is discussed: an optimal initial topology is created by a homogenization method as a gray level image, which is then transformed to a realizable design using computer vision techniques; this design is then parameterized and treated in detail by sizing and shape optimization. A fully automated process is described for trusses. Optimization of two dimensional solid structures is also discussed. Several application-oriented examples illustrate the usefulness of the proposed methodology.

Bremicker, M.↗