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At least 811 records · Page 45

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 operation). 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 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 geographical 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 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 Agency.

Monell, Donald W.↗

A Robust Design Methodology for Optimal Microscale Secondary Flow Control in Compact Inlet Diffusers

It is the purpose of this study to develop an economical Robust design methodology for microscale secondary flow control in compact inlet diffusers. To illustrate the potential of economical Robust Design methodology, two different mission strategies were considered for the subject inlet, namely Maximum Performance and Maximum HCF Life Expectancy. The Maximum Performance mission maximized total pressure recovery while the Maximum HCF Life Expectancy mission minimized the mean of the first five Fourier harmonic amplitudes, i.e., 'collectively' reduced all the harmonic 1/2 amplitudes of engine face distortion. Each of the mission strategies was subject to a low engine face distortion constraint, i.e., DC60<0.10, which is a level acceptable for commercial engines. For each of these missions strategies, an 'Optimal Robust' (open loop control) and an 'Optimal Adaptive' (closed loop control) installation was designed over a twenty degree angle-of-incidence range. The Optimal Robust installation used economical Robust Design methodology to arrive at a single design which operated over the entire angle-of-incident range (open loop control). The Optimal Adaptive installation optimized all the design parameters at each angle-of-incidence. Thus, the Optimal Adaptive installation would require a closed loop control system to sense a proper signal for each effector and modify that effector device, whether mechanical or fluidic, for optimal inlet performance. In general, the performance differences between the Optimal Adaptive and Optimal Robust installation designs were found to be marginal. This suggests, however, that Optimal Robust open loop installation designs can be very competitive with Optimal Adaptive close loop designs. Secondary flow control in inlets is inherently robust, provided it is optimally designed. Therefore, the new methodology presented in this paper, combined array 'Lower Order' approach to Robust DOE, offers the aerodynamicist a very viable and economical way of exploring the concept of Robust inlet design, where the mission variables are brought directly into the inlet design process and insensitivity or robustness to the mission variables becomes a design objective.

Anderson, Bernhard H.↗

Generative Representations for Computer-Automated Design Systems

With the increasing computational power of Computers, software design systems are progressing from being tools for architects and designers to express their ideas to tools capable of creating designs under human guidance. One of the main limitations for these computer-automated design programs is the representation with which they encode designs. If the representation cannot encode a certain design, then the design program cannot produce it. Similarly, a poor representation makes some types of designs extremely unlikely to be created. Here we define generative representations as those representations which can create and reuse organizational units within a design and argue that reuse is necessary for design systems to scale to more complex and interesting designs. To support our argument we describe GENRE, an evolutionary design program that uses both a generative and a non-generative representation, and compare the results of evolving designs with both types of representations.

Hornby, Gregory S.↗

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.↗

Design for Reliability and Safety Approach for the NASA New Launch Vehicle

The United States National Aeronautics and Space Administration (NASA) is in the midst of a space exploration program intended for sending crew and cargo to the international Space Station (ISS), to the moon, and beyond. This program is called Constellation. As part of the Constellation program, NASA is developing new launch vehicles aimed at significantly increase safety and reliability, reduce the cost of accessing space, and provide a growth path for manned space exploration. Achieving these goals requires a rigorous process that addresses reliability, safety, and cost upfront and throughout all the phases of the life cycle of the program. This paper discusses the "Design for Reliability and Safety" approach for the NASA new crew launch vehicle called ARES I. The ARES I is being developed by NASA Marshall Space Flight Center (MSFC) in support of the Constellation program. The ARES I consists of three major Elements: A solid First Stage (FS), an Upper Stage (US), and liquid Upper Stage Engine (USE). Stacked on top of the ARES I is the Crew exploration vehicle (CEV). The CEV consists of a Launch Abort System (LAS), Crew Module (CM), Service Module (SM), and a Spacecraft Adapter (SA). The CEV development is being led by NASA Johnson Space Center (JSC). Designing for high reliability and safety require a good integrated working environment and a sound technical design approach. The "Design for Reliability and Safety" approach addressed in this paper discusses both the environment and the technical process put in place to support the ARES I design. To address the integrated working environment, the ARES I project office has established a risk based design group called "Operability Design and Analysis" (OD&A) group. This group is an integrated group intended to bring together the engineering, design, and safety organizations together to optimize the system design for safety, reliability, and cost. On the technical side, the ARES I project has, through the OD&A environment, implemented a probabilistic approach to analyze and evaluate design uncertainties and understand their impact on safety, reliability, and cost. This paper focuses on the use of the various probabilistic approaches that have been pursued by the ARES I project. Specifically, the paper discusses an integrated functional probabilistic analysis approach that addresses upffont some key areas to support the ARES I Design Analysis Cycle (DAC) pre Preliminary Design (PD) Phase. This functional approach is a probabilistic physics based approach that combines failure probabilities with system dynamics and engineering failure impact models to identify key system risk drivers and potential system design requirements. The paper also discusses other probabilistic risk assessment approaches planned by the ARES I project to support the PD phase and beyond.

Safie, Fayssal, M.↗

Risk Evaluation in the Pre-Phase A Conceptual Design of Spacecraft

Typically, the most important decisions in the design of a spacecraft are made in the earliest stages of its conceptual design the Pre-Phase A stages. It is in these stages that the greatest number of design alternatives is considered, and the greatest number of alternatives is rejected. The focus of Pre-Phase A conceptual development is on the evaluation and comparison of whole concepts and the larger-scale systems comprising those concepts. This comparison typically uses general Figures of Merit (FOMs) to quantify the comparative benefits of designs and alternative design features. Along with mass, performance, and cost, risk should be one of the major FOMs in evaluating design decisions during the conceptual design phases. However, risk is often given inadequate consideration in conceptual design practice. The reasons frequently given for this lack of attention to risk include: inadequate mission definition, lack of rigorous design requirements in early concept phases, lack of fidelity in risk assessment methods, and under-evaluation of risk as a viable FOM for design evaluation. In this paper, the role of risk evaluation in early conceptual design is discussed. The various requirements of a viable risk evaluation tool at the Pre-Phase A level are considered in light of the needs of a typical spacecraft design study. A technique for risk identification and evaluation is presented. The application of the risk identification and evaluation approach to the conceptual design process is discussed. Finally, a computational tool for risk profiling is presented and applied to assess the risk for an existing Pre-Phase A proposal. The resulting profile is compared to the risks identified for the proposal by other means.

Fabisinski, Leo L., III↗

Lunar Wormbot: Design and Development of a Ground Base Robotic Tunneling Worm for Operation in Harsh Environments

From 1969 to 1972, the National Aeronautics and Space Administration (NASA) sent Apollo missions to the moon to conduct various exploration experiment. A few of the missions were directed to the study and sampling of moon soil, otherwise known as lunar regolith. The extent of the sample acquisition was limited due to the astronauts' limited ability to penetrate the moon's surface to a depth greater than three meters. However. the samples obtained were sufficient enough to provide key information pertaining to lunar regolith material properties that would further assist in future exploration endeavors. Analysis of the collected samples showed that the properties of lunar regolith may lead to knowledge of processed materials that will be beneficial for future human exploration or colonization. However, almost 40 years after the last Apollo mission, limited infonnation is known about regions underneath the moon's surface. Future lunar missions will require hardware that possesses the ability to burrow to greater depths in order to collect samples for subsequent analysis. During the summer of 2010, a team (Dr. Jessica Gaskin, Michael Kuhlman. Blaze Sanders, and Lafe Zabowski) from the NASA Robotics Academy at Marshall Space Flight Center (MSFC) was given the task of designing a robot to function as a soil collection and analysis device. Working with the National Space Science and Technology Center (NSSTC), the team was able to propose an initial design, build a prototype, and test the various subsystems of the prototype to be known as the "Lunar Wormbot" (LW). The NASA/NSSTC team then transferred the project to a University of Alabama in Huntsville (UAH) Mechanical and Aerospace Engineering (MAE) senior design class for further development. The UAH team was to utilize the NASA Systems Engineering Engine Design Process in the continuance of the Lunar Wormbot project. This process was implemented in order to coordinate the efforts of the team and guide the design of the project to ensure a high quality product that met requirements within the academic year timeframe. When the transition from the NASA NSSTC team to the UAH team occurred in August 2010, the scope and requirements were provided to the UAH team. The main objective for the UAH team was to design and fabricate a robotic burrowing prototype using peristaltic or earthworm-like motion with the purpose of collecting soil samples. The team was tasked with the design of a sub-system of the LW called the locomotive, or active, segment. Through the design process, the team extensively reviewed the requirements and functions to be performed of the LW, which led to the proposal of a final design. The present paper provides the details of the development of the design up to and including the Critical Design Review (CDR) of the Lunar Wormbot. This document briefly describes thc overall system and its function but primarily focuses on the design and implementation of the locomotive segment. Content presented includes: general design and system functionality, technical drawings, system analysis, manufacturing methods, and general project costs.

Boyles, Charles↗

Integrated Design Results for the MSR SRC Mars Ascent Vehicle

The primary mission of the NASA Mars Sample Return (MSR) Campaign is to return samples of the Martian surface to Earth for scientific study. As part of this campaign, NASA is developing a Mars Ascent Vehicle (MAV). This vehicle must survive an approximate two year journey to the Martian surface as a payload aboard a separate lander spacecraft. After residing on the surface for another year, the MAV will carry a payload of samples into orbit. From there, following ejection from the MAV, the samples will rendezvous with an Earth return spacecraft for capture, and ultimately, return to Earth.The design of the MAV represents a number of unique challenges, as no launch vehicle has ever left the surface of a planet other than Earth. Although conceptual designs for a MAV have been in various levels of development since the 1970s, none have achieved the level of fidelity and support that exists in the current MSR-MAV design. Early MSR-MAV concept studies examined multiple methods of propulsion, ultimately deciding that a Two Stage to Orbit (TSTO) solid propulsion vehicle would provide the most capable performance in a Martian environment. Following this key architecture decision, the vehicle design was further matured to a Solid-Solid Guided-Guided (SSGG) architecture for NASA Key Decision Point A (KDP-A). Although the SSGG design was able to meet all mission constraints, concerns were raised regarding limited mass margin on other elements of the MSR campaign at such an early phase. A design challenge was issued to reduce MAV total mass by as much as possible. It was ultimately determined that by moving a number of components of the vehicle second stage to the first stage, the overall vehicle mass could be reduced significantly. The new design featured a much smaller and completely unguided second stage. This paper describes the resultant Solid-Solid Guided-Unguided (SSGU) MAV design concept developed as part of the Systems Requirement Cycle (SRC). This design was developed primarily by NASA Marshall Space Flight Center (MSFC), in association with NASA Jet Propulsion Laboratory (JPL) and NASA Langley Research Center (LaRC). The TSTO vehicle includes one solid rocket motor per stage. As the vehicle second stage is unguided, it features spin-stabilization to maintain vehicle stability during flight. An electromechanically actuated Thrust Vector Control (TVC) and a monopropellant Reaction Control System (RCS) is employed for active guidance on the first stage. The vehicle is designed to deliver up to 0.47kg of Martian samples to a Mars circular orbit of 380km at 27° inclination. Due to the extremely unique design constraints of this mission, and a recent transition to a Risk Class A posture, the MAV team was compelled to devise unconventional solutions to the vehicle design. The detailed design and analysis of these subsystems and the vehicle as a whole are discussed in this paper relative to all of the engineering disciplines involved.

MSR↗

Coupled Aeropropulsive Design Optimization of a Podded Electric Propulsor

New aircraft concepts are increasingly relying on non-traditional propulsion systems to achieve lower energy consumption. These non-traditional technologies, such as boundary layer ingestion or distributed electric propulsion, require a tight integration of the propulsion sys- tem to the airframe, and therefore, a traditional design approach where the aerodynamics and propulsion disciplines are considered separately is likely to result in sub-optimal designs. As a result, we have to rely on coupled aeropropulsive design optimization, in which fully coupled aeropropulsive models are optimized to maximize the advantages of these tightly integrated propulsion systems. Despite its advantages, aeropropulsive design optimization is a relatively new field, and significant advancements are required for wide adoption of this approach, especially in the context of robustness. In this work, we introduce two fully coupled aeropropulsive design optimization approaches that are compatible with CFD models with body-force terms and boundary conditions to model the effects of the propulsion system in the flow field. To test these new approaches, we developed a podded electric fan model based on the aft-propulsor of NASA’s STARC-ABL concept. This simple design problem enables us to rapidly develop and test different aeropropulsive coupling approaches, while including the challenging physical interactions that arise from coupling CFD and propulsion models. The coupled aeropropulsive model is implemented using the MPhys library, which is built with NASA’s OpenMDAO frame- work. Using this benchmark design problem, we demonstrate the robustness of the approaches and our aeropropulsive design optimization framework by performing a sweep of optimizations for a total of 50 CFD-based aeropropulsive design optimizations. Furthermore, the new aero- propulsive coupling approaches enable multi-point design optimizations. We demonstrate this capability in a multi-point design optimization problem where we optimize cruise performance subject to a fan-face distortion constraint at rolling take-off conditions. The aeropropulsive modeling approaches we present in this work represent a significant milestone in the field of aeropropulsive design optimization. The framework we developed is extremely robust and flexible, and these developments will be crucial for future aeropropulsive design optimizations of complete turbofan engines.

Optimization propulsion aerodynamics↗

Integrated Design Results for the MSR SRC Mars Ascent Vehicle

The primary mission of the NASA Mars Sample Return (MSR) Campaign is to return samples of the Martian surface to Earth for scientific study. As part of this campaign, NASA is developing a Mars Ascent Vehicle (MAV). This vehicle must survive an approximate two-year journey to the Martian surface as a payload aboard a separate lander spacecraft. After residing on the surface for another year, the MAV will carry a payload of samples into orbit. From there, following ejection from the MAV, the samples will rendezvous with an Earth return spacecraft for capture, and ultimately, return to Earth. The design of the MAV represents a number of unique challenges, as no launch vehicle has ever left the surface of a planet other than Earth. Although conceptual designs for a MAV have been in various levels of development since the 1970s, none have achieved the level of fidelity and support that exists in the current MSR-MAV design. Early MSR-MAV concept studies examined multiple methods of propulsion, ultimately deciding that a Two-Stage-to-Orbit (TSTO) solid propulsion vehicle would provide the most capable performance in a Martian environment. Following this key architecture decision, the vehicle design was further matured to a Solid-Solid Guided-Guided (SSGG) architecture for NASA Key Decision Point A (KDP-A). Although the SSGG design was able to meet all mission constraints, concerns were raised regarding limited mass margin on other elements of the MSR campaign at such an early phase. A design challenge was issued to reduce MAV total mass by as much as possible. It was ultimately determined that by moving a number of components of the vehicle second stage to the first stage, the overall vehicle mass could be reduced significantly. The new design features a much smaller and completely unguided second stage. This paper describes the resultant Solid-Solid Guided-Unguided (SSGU) MAV design concept developed as part of the Systems Requirement Cycle (SRC). This design was developed primarily by NASA Marshall Space Flight Center (MSFC), in association with NASA Jet Propulsion Laboratory (JPL) and NASA Langley Research Center (LaRC). The TSTO vehicle includes one solid rocket motor per stage. As the vehicle second stage is unguided, it features spin-stabilization to maintain vehicle stability during flight. An electromechanically actuated Thrust Vector Control (TVC) system and a monopropellant Reaction Control System (RCS) are employed for active guidance on the first stage. The vehicle is designed to deliver up to 0.47kg of Martian samples to a Mars circular orbit of 380km at 27° inclination. Due to the extremely unique design constraints of this mission, and a recent transition to a Risk Class A posture, the MAV team was compelled to devise unconventional solutions to the vehicle design. The detailed design and analysis of these subsystems and the vehicle as a whole are discussed in this paper relative to all of the engineering disciplines involved.

MAV↗

Broadening JPL’s Mission Formulation Paradigm with Human Centered Design

Within NASA’s highly competitive environment for funding, Human Centered Design (HCD) and cybernetics could provide advantages to proposers during the mission formulation phase. Opportunities are limited when it comes to funding new science missions. Proposers are challenged to make a compelling case about the scientific desirability, technical feasibility, and resource viability of their concepts. Organizations follow established processes for proposal development using teams that typically include scientists, engineers, and managers. These team members are highly experienced subject matter experts (SME) in their own disciplines, and can respond to requirements from the solicitation. However, they are typically not trained as designers and communicators. Their approach is rooted within NASA’s science and technology paradigm. How can we improve the proposal development process, refine workflow between team members, and deliver clear and appealing offerings to the stakeholders and evaluators? These questions have been addressed by today’s most innovative companies (e.g., Apple, Google, 3M, Dyson), where the design process is not limited simply to engineering and management, but involves an all-encompassing approach drawing from fields such as social sciences, design, and the arts. Like these commercial enterprises, NASA currently employs systems thinking and integrated design, but can benefit further by moving beyond its current practices, which are mostly driven by rigid engineering, technology, science, and project management considerations. At JPL’s Innovation Foundry and through the Solar System Mission Formulation Office, we broadened this paradigm by including HCD in the mission formulation workflow. Our goal was to create a proposal with improved clarity and appeal, thus helping our team to communicate its message and aid evaluators with their work. In this paper we provide examples and lessons learned from our recent proposal development effort using HCD. We discuss touch points where we infused non-linear designerly approaches and cybernetic circularity into the workflow. Implemented design topics include operational design for team building; process design throughout distinct phases of the proposal development and writing process; communication design for streamlined exchange of information within the team and to stakeholders; interaction design; graphic design; and creating boundary objects. While these approaches may feel new or foreign to SMEs and managers in the aerospace community, they produced significant benefits in this mission formulation effort. We will describe how such approaches can be used to broaden NASA’s technology-driven paradigm through design, thus creating an environment which fosters innovation, improved communication, and strategic advantage for proposers and their organizations.

Turner, Neal↗

Influence of the air-cooled supercritical carbon dioxide recompression cycle design-point on molten salt power tower techno-economic performance

Here, this paper investigates the techno-economic performance of a molten salt power tower integrated with an air-cooled supercritical carbon dioxide recompression cycle. Prior research into the cycle design point showed trade-offs between efficiency, cost, and temperature difference across the heat input, resulting in trade-offs between the design-point generation of the molten salt power tower system and the cost of sensible-heat thermal energy storage. Prior research into cycle off-design showed that colder ambient temperature designs have higher efficiencies on cold days but lower efficiency and capacity degradation on hot days. We present a framework to evaluate how cycle design, cost, and corresponding off-design performance affect the techno-economic performance of the molten salt power tower system. We use a steady-state off-design cycle model assuming fixed shaft speeds, inventory control, and air-cooler fan power control and integrate the cycle model with the molten salt power tower model from the National Renewable Energy Laboratory's System Advisor Model. First, we present a surrogate model that uses a heuristic approach to correct the interpolation when the cycle reaches capacity limitations at ambient temperatures hotter than design. Next, we evaluate how the recompression cycle design-point ambient temperature, air-cooler approach temperature, air-cooler fan power, and recuperator conductance influence cycle and system design metrics. Finally, we complete annual simulations using an hourly "duck curve" pricing schedule and present annual performance metrics to evaluate the cumulative effects of the cycle design parameters and corresponding off-design performance on molten salt power tower techno-economics.

14 SOLAR ENERGY↗

Design Basis Document / Owner’s Technical Specification for Nitrate Salt Systems in CSP Projects (Final Technical Report)

The number of commercial coal, gas, and nuclear projects built over the past 100 years number in the thousands. As such, there is a large database, available to a wide range of commercial engineering contractors, on proven designs. In essence, unsuccessful designs have, through generations of iterations, been identified and then deleted from further consideration. In contrast, the number of commercial parabolic trough projects using nitrate salt for the thermal storage media is perhaps 60. Further, the number of commercial central receiver projects using nitrate salt as the working fluid is on the order of 20, including estimates for China. Given the relative immaturity of salt technology, and commercial pressures to successfully bid new solar projects into a mature electricity market, solar projects often promise more than has been delivered. The Design Basis Document / Owner’s Technical Specification is a first step in the iteration process. The report describes the successful features of commercial projects, outlines a range equipment and system failures in projects that didn’t operate as intended, and provides a draft set of design changes intended to correct the known problems. The product of the study is 3 volumes of technical material; one volume is on parabolic trough technologies; a second is on central receiver technologies, and the third is on potential design changes to parabolic trough and central receiver projects. The 3 volumes, which total some 590 pages, can be found at https://www.solardynllc.com/csp-plant-technologies. One of the principal topics in the report is the use of functional or prescriptive specifications. Functional specifications describe what the equipment needs to do, consistent with the minimum legal requirements of the local jurisdictions. The details of how this is to be accomplished is developed by the engineering contractor. Prescriptive specifications, which are developed by the Owner, prescribe to the engineering contractor how the functional requirements are to be met. This arrangement ensures that the favorable experience from a previous project is repeated. One example is the design code for the hot salt tank in central receiver projects. The closest design basis is API Standard 650 Welded Steel Tanks for Oil Storage. However, the maximum design temperature in API 650 is 260 °C. As such, solar projects have typically adopted a hybrid Code approach, in which allowable material stresses are taken from ASME Section II Materials. Further, since the tanks experience daily changes in temperature and in (static) pressure, and since portions of the tank can operate at stresses beyond the elastic range, the low cycle fatigue life of the tank is conducted using the rules of Section VIII Division 2. However, in a recent study by NREL, the principal damage mechanism was identified as creep rather than fatigue. Further, design stresses permitted under Section VIII Division 2, corresponding to a fatigue life of 30 years, result in projected creep lifetimes of only 2 to 5 years. An alternate design approach, prescribed by the Owner, would be based on Code sections intended for high temperature service in the creep regime. A candidate is Section III Division 5. Granted, this is a nuclear code section, and it’s use would not likely be mandated by local jurisdictions. However, the effects of creep have been deemed to be of sufficient importance that one nuclear project developer, and one central receiver project developer, have stipulated in the tank design specification that the equipment be designed to the requirements of Section III Division 5.

14 SOLAR ENERGY↗

NDARC NASA Design and Analysis of Rotorcraft - Input, Appendix 4

The NDARC code performs design and analysis tasks. The design task involves sizing the rotorcraft to satisfy specified design conditions and missions. The analysis tasks can include off-design mission performance analysis, flight performance calculation for point operating conditions, and generation of subsystem or component performance maps. The principal tasks (sizing, mission analysis, flight performance analysis) are shown in the figure as boxes with heavy borders. Heavy arrows show control of subordinate tasks. The aircraft description consists of all the information, input and derived, that denes the aircraft. The aircraft consists of a set of components, including fuselage, rotors, wings, tails, and propulsion. This information can be the result of the sizing task; can come entirely from input, for a fixed model; or can come from the sizing task in a previous case or previous job. The aircraft description information is available to all tasks and all solutions. The sizing task determines the dimensions, power, and weight of a rotorcraft that can perform a specified set of design conditions and missions. The aircraft size is characterized by parameters such as design gross weight, weight empty, rotor radius, and engine power available. The relations between dimensions, power, and weight generally require an iterative solution. From the design flight conditions and missions, the task can determine the total engine power or the rotor radius (or both power and radius can be fixed), as well as the design gross weight, maximum takeoff weight, drive system torque limit, and fuel tank capacity. For each propulsion group, the engine power or the rotor radius can be sized. Missions are defined for the sizing task, and for the mission performance analysis. A mission consists of a number of mission segments, for which time, distance, and fuel burn are evaluated. For the sizing task, certain missions are designated to be used for design gross weight calculations; for transmission sizing; and for fuel tank sizing. The mission parameters include mission takeoff gross weight and useful load. For specified takeoff fuel weight with adjustable segments, the mission time or distance is adjusted so the fuel required for the mission equals the takeoff fuel weight. The mission iteration is on fuel weight or energy. Flight conditions are specified for the sizing task, and for the flight performance analysis. For the sizing task, certain flight conditions are designated to be used for design gross weight calculations; for transmission sizing; for maximum takeoff weight calculations; and for anti-torque or auxiliary thrust rotor sizing. The flight condition parameters include gross weight and useful load. For flight conditions and mission takeoff, the gross weight can be maximized, such that the power required equals the power available. A flight state is defined for each mission segment and each flight condition. The aircraft performance can be analyzed for the specified state, or a maximum effort performance can be identified. The maximum effort is specified in terms of a quantity such as best endurance or best range, and a variable such as speed, rate of climb, or altitude.

Rotorcraft Input↗

Engineering Design Tools for Shape Memory Alloy Actuators: CASMART Collaborative Best Practices and Case Studies

The primary goal of the Consortium for the Advancement of Shape Memory Alloy Research and Technology (CASMART) is to enable the design of revolutionary applications based on shape memory alloy (SMA) technology. In order to help realize this goal and reduce the development time and required experience for the fabrication of SMA actuation systems, several modeling tools have been developed for common actuator types and are discussed herein along with case studies, which highlight the capabilities and limitations of these tools. Due to their ability to sustain high stresses and recover large deformations, SMAs have many potential applications as reliable, lightweight, solid-state actuators. Their advantage over classical actuators can also be further improved when the actuator geometry is modified to fit the specific application. In this paper, three common actuator designs are studied: wires, which are lightweight, low-profile, and easily implemented; springs, which offer actuation strokes upwards of 200 at reduced mechanical loads; and torque tubes, which can provide large actuation forces in small volumes and develop a repeatable zero-load actuation response (known as the two-way shape memory effect). The modeling frameworks, which have been implemented in the design tools, are developed for each of these frequently used SMA actuator types. In order to demonstrate the versatility and flexibility of the presented design tools, as well as validate their modeling framework, several design challenges were completed. These case studies include the design and development of an active hinge for the deployment of a solar array or foldable space structure, an adaptive solar array deployment and positioning system, a passive air temperature controller for regulation flow temperatures inside of a jet engine, and a redesign of the Corvette active hatch, which allows for pressure equalization of the car interior. For each of the presented case studies, a prototype or proof-of-concept was fabricated and the experimental results and lessons learned are discussed. This analysis presents a collection of CASMART collaborative best practices in order to allow readers to utilize the available design tools and understand their modeling principles. These design tools, which are based on engineering models, can provide first-order optimal designs and are a basic and efficient method for either demonstrating design feasibility or refining design parameters. Although the design and integration of an SMA-based actuation system always requires application- and environment-specific engineering considerations, common modeling tools can significantly reduce the investment required for actuation system development and provide valuable engineering insight.

Design tools↗

NDARC - NASA Design and Analysis of Rotorcraft: Input and Data Structures - Vol 2

The NDARC code performs design and analysis tasks. The design task involves sizing the rotorcraft to satisfy specified design conditions and missions. The analysis tasks can include off-design mission performance analysis, flight performance calculation for point operating conditions, and generation of subsystem or component performance maps. Figure 1-1 illustrates the tasks. The principal tasks (sizing, mission analysis, flight performance analysis) are shown in the figure as boxes with heavy borders. Heavy arrows show control of subordinate tasks. The aircraft description (figure 1-1) consists of all the information, input and derived, that defines the aircraft. The aircraft consists of a set of components, including fuselage, rotors, wings, tails, and propulsion. This information can be the result of the sizing task; can come entirely from input, for a fixed model; or can come from the sizing task in a previous case or previous job. The aircraft description information is available to all tasks and all solutions (indicated by light arrows). The sizing task determines the dimensions, power, and weight of a rotorcraft that can perform a specified set of design conditions and missions. The aircraft size is characterized by parameters such as design gross weight, weight empty, rotor radius, and engine power available. The relations between dimensions, power, and weight generally require an iterative solution. From the design flight conditions and missions, the task can determine the total engine power or the rotor radius (or both power and radius can be fixed), as well as the design gross weight, maximum takeoff weight, drive system torque limit, and fuel tank capacity. For each propulsion group, the engine power or the rotor radius can be sized. Missions are defined for the sizing task, and for the mission performance analysis. A mission consists of a number of mission segments, for which time, distance, and fuel burn are evaluated. For the sizing task, certain missions are designated to be used for design gross weight calculations; for transmission sizing; and for fuel tank sizing. The mission parameters include mission takeoff gross weight and useful load. For specified takeoff fuel weight with adjustable segments, the mission time or distance is adjusted so the fuel required for the mission (burned plus reserve) equals the takeoff fuel weight. The mission iteration is on fuel weight or energy. Flight conditions are specified for the sizing task, and for the flight performance analysis. For the sizing task, certain flight conditions are designated to be used for design gross weight calculations; for transmission sizing; for maximum takeoff weight calculations; and for antitorque or auxiliary thrust rotor sizing. The flight condition parameters include gross weight and useful load. For flight conditions and mission takeoff, the gross weight can be maximized, such that the power required equals the power available. A flight state is defined for each mission segment and each flight condition. The aircraft performance can be analyzed for the specified state, or a maximum effort performance can be identified. The maximum effort is specified in terms of a quantity such as best endurance or best range, and a variable such as speed, rate of climb, or altitude. The aircraft must be trimmed, by solving for the controls and motion that produce equilibrium in the specified flight state. Different trim solution definitions are required for various flight states. Evaluating the rotor hub forces may require solution of the blade flap equations of motion.

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NDARC - NASA Design and Analysis of Rotorcraft: Input - Vol 3

The NDARC code performs design and analysis tasks. The design task involves sizing the rotorcraft to satisfy specified design conditions and missions. The analysis tasks can include off-design mission performance analysis, flight performance calculation for point operating conditions, and generation of subsystem or component performance maps. Figure 1-1 illustrates the tasks. The principal tasks (sizing, mission analysis, flight performance analysis) are shown in the figure as boxes with heavy borders. Heavy arrows show control of subordinate tasks. The aircraft description (figure 1-1) consists of all the information, input and derived, that defines the aircraft. The aircraft consists of a set of components, including fuselage, rotors, wings, tails, and propulsion. This information can be the result of the sizing task; can come entirely from input, for a fixed model; or can come from the sizing task in a previous case or previous job. The aircraft description information is available to all tasks and all solutions (indicated by light arrows). The sizing task determines the dimensions, power, and weight of a rotorcraft that can perform a specified set of design conditions and missions. The aircraft size is characterized by parameters such as design gross weight, weight empty, rotor radius, and engine power available. The relations between dimensions, power, and weight generally require an iterative solution. From the design flight conditions and missions, the task can determine the total engine power or the rotor radius (or both power and radius can be fixed), as well as the design gross weight, maximum takeoff weight, drive system torque limit, and fuel tank capacity. For each propulsion group, the engine power or the rotor radius can be sized. Missions are defined for the sizing task, and for the mission performance analysis. A mission consists of a number of mission segments, for which time, distance, and fuel burn are evaluated. For the sizing task, certain missions are designated to be used for design gross weight calculations; for transmission sizing; and for fuel tank sizing. The mission parameters include mission takeoff gross weight and useful load. For specified takeoff fuel weight with adjustable segments, the mission time or distance is adjusted so the fuel required for the mission (burned plus reserve) equals the takeoff fuel weight. The mission iteration is on fuel weight or energy. Flight conditions are specified for the sizing task, and for the flight performance analysis. For the sizing task, certain flight conditions are designated to be used for design gross weight calculations; for transmission sizing; for maximum takeoff weight calculations; and for antitorque or auxiliary thrust rotor sizing. The flight condition parameters include gross weight and useful load. For flight conditions and mission takeoff, the gross weight can be maximized, such that the power required equals the power available. A flight state is defined for each mission segment and each flight condition. The aircraft performance can be analyzed for the specified state, or a maximum effort performance can be identified. The maximum effort is specified in terms of a quantity such as best endurance or best range, and a variable such as speed, rate of climb, or altitude. The aircraft must be trimmed, by solving for the controls and motion that produce equilibrium in the specified flight state. Different trim solution definitions are required for various flight states. Evaluating the rotor hub forces may require solution of the blade flap equations of motion.

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NDARC - NASA Design and Analysis of Rotorcraft: Input - Appendix 3

The NDARC code performs design and analysis tasks. The design task involves sizing the rotorcraft to satisfy specified design conditions and missions. The analysis tasks can include off-design mission performance analysis, flight performance calculation for point operating conditions, and generation of subsystem or component performance maps. Figure 1-1 illustrates the tasks. The principal tasks (sizing, mission analysis, flight performance analysis) are shown in the figure as boxes with heavy borders. Heavy arrows show control of subordinate tasks. The aircraft description (figure 1-1) consists of all the information, input and derived, that defines the aircraft. The aircraft consists of a set of components, including fuselage, rotors, wings, tails, and propulsion. This information can be the result of the sizing task; can come entirely from input, for a fixed model; or can come from the sizing task in a previous case or previous job. The aircraft description information is available to all tasks and all solutions (indicated by light arrows). The sizing task determines the dimensions, power, and weight of a rotorcraft that can perform a specified set of design conditions and missions. The aircraft size is characterized by parameters such as design gross weight, weight empty, rotor radius, and engine power available. The relations between dimensions, power, and weight generally require an iterative solution. From the design flight conditions and missions, the task can determine the total engine power or the rotor radius (or both power and radius can be fixed), as well as the design gross weight, maximum takeoff weight, drive system torque limit, and fuel tank capacity. For each propulsion group, the engine power or the rotor radius can be sized. Missions are defined for the sizing task, and for the mission performance analysis. A mission consists of a number of mission segments, for which time, distance, and fuel burn are evaluated. For the sizing task, certain missions are designated to be used for design gross weight calculations; for transmission sizing; and for fuel tank sizing. The mission parameters include mission takeoff gross weight and useful load. For specified takeoff fuel weight with adjustable segments, the mission time or distance is adjusted so the fuel required for the mission (burned plus reserve) equals the takeoff fuel weight. The mission iteration is on fuel weight or energy. Flight conditions are specified for the sizing task, and for the flight performance analysis. For the sizing task, certain flight conditions are designated to be used for design gross weight calculations; for transmission sizing; for maximum takeoff weight calculations; and for antitorque or auxiliary thrust rotor sizing. The flight condition parameters include gross weight and useful load. For flight conditions and mission takeoff, the gross weight can be maximized, such that the power required equals the power available. A flight state is defined for each mission segment and each flight condition. The aircraft performance can be analyzed for the specified state, or a maximum effort performance can be identified. The maximum effort is specified in terms of a quantity such as best endurance or best range, and a variable such as speed, rate of climb, or altitude. The aircraft must be trimmed, by solving for the controls and motion that produce equilibrium in the specified flight state. Different trim solution definitions are required for various flight states. Evaluating the rotor hub forces may require solution of the blade flap equations of motion.

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