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At least 829 records · Page 46

A Design Methodology for Optimizing and Integrating Composite Materials in Gear Structures

The application of composite materials to gear structures is complex because of the gear shape, the need for precise dimensional tolerances, and the complex dynamic load condition. Methods are presented in this work to design and optimize an integrated composite hub-web structure that can be used as part of a hybrid composite-steel gear. The composite hub-web structure is a planar structure with a large decrease in thickness from the hub to the rim. Methods for design and optimization of this variable-thickness structure are presented along with a method for forming braided prepreg material to conform to the shape of this structure. A layered approach is presented that integrates cut plies or filler materials for thickness buildup with continuous-fiber layers for the primary load path. An additional gear design concept is presented that has an axially extended continuous-fiber composite structure that can be combined with the planar structure. A proposed optimization methodology is introduced where an optimized design is output for each type of optimization simulation. Through this process, composite knowledge can be incorporated in the optimization, and more control is given over the design during the process. The methods in this study provide a tool for designing and optimizing composite structures for gears and other high-power-density applications.

optimization↗

Investigating Additively Manufactured 17-4 PH for Structural Applications

17-4 is used regularly to manufacture force transducers particularly for wind tunnel testing. Such applications place demanding structural requirements on the transducers with static safety factors of 1.5 common and the potential for additional dynamic loads. Additive manufacturing (AM) of transducers is very appealing because of significant potential cost and time savings as well as increased design flexibility. This study looks at the processing of 17-4 powder using selective laser melting by two different facilities using their own best practices. Hot isostatic pressing (HIP) is used by both facilities as part of the thermomechanical processing following printing to explore whether it can improve the consistency of mechanical properties. Results revealed that HIP reduced average porosity of 17-4 parts and that the yield strength of parts following solutionization and aging met wrought material property targets. Strain to failure of one of the facilities parts was less than 5% compared to greater than 9% for the other facility. Inspection of failure surfaces revealed this discrepancy could be attributed to pores (2-4% area fraction) on the failure surface of the low ductility parts. Phase content varied between the facilities with one facility producing fully martensitic parts and the other containing some retained austenite. The phase content of the starting powder and a slower than air cooling rate following the final heat treatment above the austenite eutectoid temperature are likely sources of the retained austenite. Taken together these results suggest that the current state of the art in AM 17-4 processing is sufficient for many NASA force measurement applications, but that attention is required at each stage of processing to assure desired mechanical properties.

Burns, Devin E.↗

Quasi-Static and Dynamic Analysis of Composite Panels: Characterization and Validation

The predictive capability of a progressive damage model to simulate the quasi-static and dynamic crushing of composite specimens is evaluated in this article. The material model is commercially available within the ABAQUS finite element software package, i.e., “Damage for Fiber reinforced Composites”, and is often utilized to simulate damage progression and failure in static and dynamic failure scenarios such as crushing of a composite plate. The composite specimens used in this study consist of quasi-isotropic C-shaped and corrugated composite panels comprised of carbon fiber/epoxy braided fabric. The C-shaped panel specimen is used to calibrate the model and optimize material/model properties through comparison with experimental results. Then, using the same model parameters, the quasi-static crush response of the corrugated panel is predicted. The predictive capability of the model is further demonstrated by simulating the dynamic crushing response of both C-shaped and corrugated panels using the same material properties as in the quasi-static crush case with only minor adjustments for the dynamic elastic properties (i.e., rate dependent modulus). Results show that the in-built material model available in ABAQUS can successfully reproduce experimental results for both panels (C-shaped and corrugated) subjected to both quasi-static and dynamic loading scenarios. A small-scale parametric study on physical (experimentally measurable) and nonphysical (purely mathematical) model parameters was also conducted. It can be concluded that, achieving successful simulation results requires a more in-depth understanding of the influence of model parameter variation on the mechanical response of the composite together with the strategies and challenges of the utilized modeling methodology (e.g., FEA mesh density, etc.).

Naghipour Ghezeljeh, Paria↗

Probability Bounds Analysis Applied to Multi-Purpose Crew Vehicle Nonlinearity

The Multi-Purpose Crew Vehicle (MPCV) Program Orion vehicle finite element model (FEM) was updated based on a modal test performed by Lockheed Martin. Due to nonlinearity observed in the test results, linear low force level (LL) and high force level (HL) FEMs were developed for use during various Space Launch System (SLS) flight regimes depending on expected forcing levels. Uncertainty models were derived for the combined MPCV and MPCV Stage Adaptor LL and HL Hurty/Craig-Bampton (HCB) components based on the MPCV structural test article Configuration 4 modal test-analysis correlation results. Subsequently, system-level uncertainty quantification analyses were performed using both models for various SLS flight configurations to determine the impact of the nonlinearity on important system metrics. The system metrics included both transfer functions associated with attitude control and dynamic loads associated with aerodynamic buffeting during ascent. In each case, an independent Monte Carlo (MC) analysis was performed, and no attempt was made to combine the results. The Hybrid Parametric Variation (HPV) method was used to develop the LL and HL MPCV HCB uncertainty models. The HPV method provides both parametric and non-parametric components of uncertainty. The non-parametric uncertainty accounts for the difference in model-form between the linearized analytical model and the corresponding linearized component test results in the form of mode shapes and frequencies at that force level. This linear model-form uncertainty is implemented in the HPV method using random matrix theory. However, the HPV uncertainty models developed for the linear LL and HL MPCV components do not account for the nonlinearity in the MPCV. With respect to the linearized models, this nonlinearity is also an uncertainty in model form, but in this case, it must be treated independently as an epistemic uncertainty. It represents a lack of knowledge, in contrast to an aleatory uncertainty due to the randomness of a variable. In the case of an epistemic variable, the true value is unknown, only the interval within which it lies is known. Epistemic uncertainty can be reduced with increased knowledge, while in general, aleatory uncertainty cannot. This work combines the epistemic uncertainty due to the MPCV nonlinearity with the parametric and non-parametric uncertainty within the HPV method using a second order propagation approach. The LL and HL test data is augmented with surrogate test data derived from a nonlinear MPCV representation. The impact of the MPCV nonlinearity on system response statistics is determined using a series of cumulative distribution functions in the form of a horsetail plot, or p-box. This results in an interval of probabilities for a specific response value, or an interval of response values at a specific probability.

Daniel C Kammer↗

Human System Risk Changes in 2021

The Human System Risk Board (HSRB) has the overall responsibility for tracking the evolution of the top ~30 human system risks that it has identified to be associated with human spaceflight. As part of this process, the Board is charged with maintaining a consistent, integrated process to mitigate those risks, and developing evidence-based risk posture recommendations. Risks are re-evaluated in a Continuous Risk Management (CRM) process. This session will summarize the risk posture changes that have occurred in the last year and what high level research, performance, and epidemiologic data have informed those changes. Human System Risks updated in 2021 include: Dynamic Loads, Sensorimotor, EVA, Crew Egress, Behavioral Medicine, Electrical Shock, Human System Integration Architecture (HSIA), Toxic Exposure, Bone Fracture, Cardiovascular, Medical Conditions, Renal Stone, CO2 Exposure, and Pharmacology.

Mary Van Baalen↗

Lessons Learned and Best Practices for Utilizing a Generalized Composite Impact Model

A material model which incorporates several key capabilities which have been identified as lacking in currently available composite impact models has been developed. The material model utilizes experimentally based tabulated input to define the evolution of plasticity and damage as opposed to specifying discrete input parameters (such as modulus and strength). It has been implemented into the commercially available transient dynamic finite element code LS-DYNA® as MAT_213. The model can simulate the nonlinear deformation, damage and failure that take place in a composite under dynamic loading conditions. As MAT_213 is now being used by a general user community that did not participate in the model development process, a number of issues have been identified that caused uncertainty in assembling a MAT_213 input deck and conducting a MAT_213 analysis. The overall goal of this effort is to develop a quantified set of lessons learned and best practices which will permit a new user to conduct useful MAT_213 simulations without needing to have detailed expert knowledge of the material model and its theoretical underpinnings.

Micromechanics↗

Validation of the Corcos Model for the Space Launch System using Unsteady Pressure Sensitive Paint

During atmospheric ascent launch vehicles (LVs) experience large dynamic loads at transonic conditions where aerodynamic buffet is most critical. To estimate buffet loads, coupled loads analyses typically utilize suitable forcing functions, called buffet forcing functions (BFFs). One of the key buffet environment contributors is the turbulent boundary layer (TBL) on the LV outer skin. The TBL-induced fluctuating pressures can be estimated using the widely-accepted Corcos model. In the context of transonic buffet, the performance of this model is not well established, partly because of lack of data. To fill this gap, NASA recently acquired extremely high-spatial-density data for the Space Launch System (SLS) vehicle, using the unsteady pressure sensitive paint (uPSP) optical measurement technique. A methodology is developed for validation of the Corcos model using these unique data, with a focus on the LV-design application. The model hypotheses are verified and the model parameters are empirically tuned. For selected panels on the vehicle, BFF coherence factors are derived based on the Corcos model and the associated panel BFFs are compared to uPSP data. It is shown that the modeled BFFs are in agreement with direct integration of uPSP data, except for regions where pressure fluctuations are spatially nonuniform. In those regions, the Corcos-based BFFs exhibit inherent limitations of BFF estimation methods that rely on discrete pressure measurements.

buffet↗

Validation of the Corcos Model for the Space Launch System using Unsteady Pressure Sensitive Paint

During atmospheric ascent launch vehicles (LVs) experience large dynamic loads at transonic conditions where aerodynamic buffet is most critical. To estimate buffet loads, coupled loads analyses typically utilize suitable forcing functions, called buffet forcing functions (BFFs). One of the key buffet environment contributors is the turbulent boundary layer (TBL) on the LV outer skin. The TBL-induced fluctuating pressures can be estimated using the widely-accepted Corcos model. In the context of transonic buffet, the performance of this model is not well established, partly because of lack of data. To fill this gap, NASA recently acquired extremely high-spatial-density data for the Space Launch System (SLS) vehicle, using the unsteady pressure sensitive paint (uPSP) optical measurement technique. A methodology is developed for validation of the Corcos model using these unique data, with a focus on the LV-design application. The model hypotheses are verified and the model parameters are empirically tuned. For selected panels on the vehicle, BFF coherence factors are derived based on the Corcos model and the associated panel BFFs are compared to uPSP data. It is shown that the modeled BFFs are in agreement with direct integration of uPSP data, except for regions where pressure fluctuations are spatially nonuniform. In those regions, the Corcos-based BFFs exhibit inherent limitations of BFF estimation methods that rely on discrete pressure measurements.

buffet↗

Current Capabilities of AFRL’s Spacecraft Simulation Tool

Assessment of spacecraft integration issues is typically accomplished with a combination of numerical tools developed to simulate different regions with different key physics. For instance, a detailed study of spacecraft with an electric propulsion device requires a device model, a plume model, and a spacecraft charging model. AFRL’s in-house spacecraft simulation tool, TURF, is now capable of performing all of these calculations in one simulation. In addition, the plume simulation capability has been expanded significantly to improve speed and accuracy. Other upgrades in TURF include adaptive mesh refinement (AMR) and dynamic load balancing. All of these upgrades are covered in this paper by providing detailed descriptions or pointing to relevant references. This paper also presents three example simulations demonstrating its multi-physics multi-scale capability.

spacecraft simulation↗

A Partitioned - Task Parallel Implementation of the NASA Multiscale Analysis Tool for High Performance Computing

The NASA Multiscale Analysis Tool (NASMAT) is a platform for multiscale modeling of composites which can perform analysis of materials with any arbitrary number of length scales. The platform supports modularity, scalability, and interoperability using recursive procedures and data structures. A Macro solver driven parallelization scheme often limits the capability of NASMAT to scale as it has access to limited memory and number of cores (often one core/thread) and often forces to implement macro solver specific changes to the platform. In this work, a partitioned task-parallel approach is adopted, where the parallelization strategy adopted for NASMAT is independent of the macro solver and the computational resources are managed independently. The programming architecture takes into account the hierarchy of multiple scales (task-dependence) and the heterogeneous nature (dynamic load balancing) of computation through implementation of a hierarchy-informed task parallel model. The partitioned nature of the framework further extends the “plug and play” capability of NASMAT. preCICE, an open-source library for coupling multiphysics solver in a partitioned manner, is adopted to integrate NASMAT with an external macro solver by implementing a NASMAT adapter for preCICE. Speedup and scalability of the framework is studied for micromechanical models of varying size.

task-parallel↗

Human Thermal Assessment of Traverse and Geology Task Iterations During Simulated Lunar Extravehicular Activity

Spacewalks or extravehicular activities (EVA) in microgravity are mentally and physically demanding. Current microgravity EVAs are predominantly focused on upper body tasks on engineered surfaces; however, the introduction of gravity means that crew members during future lunar EVAs will be required to perform tasks that generate full body workloads such as navigating natural lunar terrain while conducting geological sampling. To date, only 12 people have walked on the surface of the Moon resulting in limited knowledge of suited thermal regulation under lunar-relevant physical workloads. To address this gap, a study is underway to focus on spacesuit operations with simulated lunar EVA workloads. This study presents methodology for collecting standard thermal measures during suit testing. In this pilot study, two suited subjects underwent simulated lunar EVAs using the NASA Active Response Gravity Offload System (ARGOS) to simulate the effects of partial gravity. Each lunar EVA, lasting three to five hours, included various metabolically demanding EVA tasks. Subjects donned the NASA Mark III (MK III) space suit and were offloaded to 1/6th G (lunar gravity). A subset task circuit from one of these simulations replicated an EVA traverse to a lunar crater, taking a geological sample, and returning to base. The suited subject walked one 1500 m (0% grade) and three 500 m traverses at three different grades (10, 20, 30%). Between each traverse, subjects performed geology sampling tasks (0 and 10% grade). Thermal measurements included core and skin temperature, liquid cooling garment (LCG) inlet and outlet temperature, and spacesuit gas inlet and outlet temperature and humidity. Compared to baseline core temperature (S1 = 37.07±0.32 °C, S2 = 37.27±0.01 °C) and mean skin temperature (S1 = 32.38±0.34 °C, S2 = 33.62±0.03 °C), after a 1500 m traverse, each suited subject showed an increased core temperature (S1 = 37.23±0.12 °C, S2 = 37.41±0.11°C) and decreased mean skin temperature (S1 = 32.16±0.17 °C, S2 = 31.53±1.15 °C) at a delta LCG temperature (S1 = 1.86±0.24 °C, S2 = 2.20±0.76 °C) and delta suit humidity (S1 = 9.66±1.49 %, S2 = 11.50±1.58 %). Core temperature continued to increase from compounding traverse and geology tasks (S1 = 38.04±0.03 °C, S2 = 38.1±0.02 °C) accompanied by an increase in delta LCG temperature (S1 = 2.24±0.13 °C, S2 = 2.67±0.12 °C) and delta suit humidity (S1 = 28±2.42 %, S2 = 31±2.13 %). Conversely, as the circuit progressed, mean skin temperature continued to decrease due to sustained LCG heat rejection (S1 = 30.08±0.15 °C, S2 = 30.28±0.07 °C). During the simulated EVA circuit core temperature increased to elevated values and remained elevated as heat was retained while mean skin temperature decreased due to peripheral heat offloaded to the LCG. The thermal measures collected during this study provided critical heat loading dynamics during lunar EVA tasks. Including core and skin temperatures along with suited thermal measures provides a standard data collection scheme for human thermal metrics during EVA task management. Data collected in this configuration can be used to build future lunar EVA task circuits and human thermal predictions.

Bradley Hoffmann↗

A Partitioned -Task Parallel Implementation of the NASA Multiscale Analysis Tool for High Performance Computing

The NASA Multiscale Analysis Tool (NASMAT) is a “plug and play” software package that allows users to conduct massively multiscale modeling of hierarchical and nonlinear materials. This work extends the scalability and improves the High Performance Computing friendliness of NASMAT by adopting a Partitioned Task-Parallel approach. Interoperability of NASMAT with external software is enhanced through preCICE, a open source library for multiphysics coupling in a partitioned manner. Enhancement through preCICE allows for easy integration of NASMAT to other macro solvers and dissociates the parallelization strategy adopted within NASMAT from the macro solver. The task-parallel framework based on Master-Worker approach is implemented as the parallelization scheme. The scheme accounts for hierarchy of multiple scales (task-dependence) and heterogeneous nature (dynamic load balancing) of computations. The applicability and scalability of the framework will be evaluated by analyzing large scale engineering problems through massively multiscale methods.

NASMAT↗

Space Launch System Unsteady Forces Developed from Unsteady-Pressure-Sensitive-Paint–Based Corcos Model Parameters

During atmospheric ascent, launch vehicles (LVs) experience large dynamic loads at transonic conditions where aerodynamic buffet is most critical. To estimate buffet loads, coupled loads analyses typically utilize suitable forcing functions, called buffet forcing functions (BFFs). One of the key buffet environment contributors is the turbulent boundary layer (TBL) on the LV outer skin. The TBL-induced fluctuating pressures can be estimated using the widely-accepted Corcos model. In the context of transonic buffet, the performance of this model is not well established, partly because of lack of data. To fill this gap, NASA recently acquired extremely high-spatial-density data for the Space Launch System (SLS) vehicle, using the unsteady pressure sensitive paint (uPSP) optical measurement technique. A methodology is developed for validation of the Corcos model using these unique data, with a focus on the LV-design application. The model hypotheses are verified and the model parameters are empirically tuned. For selected panels on the vehicle, BFF coherence factors are derived based on the Corcos model and the associated panel BFFs are compared to uPSP data. It is shown that the modeled BFFs are in agreement with direct integration of uPSP data, except for regions where pressure fluctuations are spatially nonuniform. In those regions, the Corcos-based BFFs exhibit inherent limitations of BFF estimation methods that rely on discrete pressure measurements.

buffet↗

A Hybrid Transfer Function Procedure for Broadband Auralization Within Small Flight Vehicle Interiors

Auralization of the sound fields within flight vehicle interiors is of interest to aircraft designers considering crew and passenger ride quality. Computer models can be used to predict the filtering effects that the fuselage structure and interior volume have on the exterior sound field in order to simulate the resulting cabin interior noise. However, this can become expensive when a wide frequency range of analysis suitable for passenger auralization is desired. This is particularly the case when using deterministic modeling methods such as finite element analysis (FEA) wherein prohibitively high levels of detail and finite element discretizations are required to resolve the wavelengths at high frequencies. On the contrary, Statistical Energy Analysis (SEA), while not capturing important modal behaviors at low frequencies, is better suited for higher frequency analyses where structural and interior dynamics exhibit high modal overlap and spatially averaged physical quantities suffice. For this reason, a hybrid procedure is considered here that utilizes FE modal solutions at lower frequencies and SEA results at higher frequencies. A transfer function dataset containing the exterior to interior vibroacoustic filtering effect is calculated accordingly and subsequently stored to be used for a variety of exterior dynamic load cases. At low frequencies, the transfer function dataset detail is related to the level of FE model refinement whereas at high frequencies it functions as an equalizer array with a level of detail corresponding to the SEA subsystem partitioning scheme. The above procedure is described herein and demonstrated on a six passenger flight vehicle with eight propulsors in a hover flight condition.

auralization↗

A Hybrid Transfer Function Procedure for Broadband Auralization Within Small Flight Vehicle Interiors

Auralization of the sound fields within flight vehicle interiors is of interest to aircraft designers considering crew and passenger ride quality. Computer models can be used to predict the filtering effects that the fuselage structure and interior volume have on the exterior sound field in order to simulate the resulting cabin interior noise. However, this can become expensive when a wide frequency range of analysis suitable for passenger auralization is desired. This is particularly the case when using deterministic modeling methods such as finite element analysis (FEA) wherein prohibitively high levels of detail and finite element discretizations are required to resolve the wavelengths at high frequencies. On the contrary, Statistical Energy Analysis (SEA), while not capturing important modal behaviors at low frequencies, is better suited for higher frequency analyses where structural and interior dynamics exhibit high modal overlap and spatially averaged physical quantities suffice. For this reason, a hybrid procedure is considered here that utilizes FE modal solutions at lower frequencies and SEA results at higher frequencies. A transfer function dataset containing the exterior to interior vibroacoustic filtering effect is calculated accordingly and subsequently stored to be used for a variety of exterior dynamic load cases. At low frequencies, the transfer function dataset detail is related to the level of FE model refinement whereas at high frequencies it functions as an equalizer array with a level of detail corresponding to the SEA subsystem partitioning scheme. The above procedure is described herein and demonstrated on a six passenger flight vehicle with eight propulsors in a hover flight condition.

auralization↗

Additive Manufacturing at NASA

Additive Manufacturing (AM) is certainly changing the space industry and providing new opportunities to travel to low earth orbit and explore our universe. New design opportunities –not previously possible –for new high performance metal alloys, light-weighting, managing thermal, structural, and dynamic loads are being enabled by AM. This presentation will showcase the vast portfolio of NASA’s AM activities in the last 12 years; transportation from Earth to Destination, Habitat at Destination, Lander from Station to Surface, and Science mission spacecrafts. NASA’s technical excellence is being leveraged heavily in the AM community thru collaborative projects, partnership agreements, tech transfer program. Challenges as well as opportunities will be discussed.

Alison Park↗

Technology Drives Exploration: How NASA Is Embracing Additive Manufacturing

NASA has over 60 years of technology development that enabled human space and space science exploration “for the benefit of all humankind”. This presentation will start with the overview of NASA’s organization structure; the roles NASA’s leadership plays as well as 10 regional centers’ focused areas and capabilities. It will also highlight NASA’s Mission Directorates –Science, Human, Aeronautics, and Technology. With the onset of the newer and still evolving procurement business model (NASA being a buyer, instead of maker), a question remains: which is the right framework under which NASA can best integrate the capabilities of commercial, international, and other US government entities into a coherent exploration strategy? Another critical consideration is identifying which critical technologies to invest in NASA and which capabilities are better suited for commercialization as NASA as a buyer. Additive Manufacturing (AM) is certainly changing the space industry and providing new opportunities to travel to low earth orbit and explore our universe. New design opportunities –not previously possible –for new high performance metal alloys, light-weighting, managing thermal, structural, and dynamic loads are being enabled by AM. This presentation will showcase the vast portfolio of NASA’s AM activities in the last 13 years; transportation from Earth to Destination, Habitat at Destination, Lander from Station to Surface, and Science mission spacecrafts. NASA’s technical excellence is being leveraged heavily in the AM and Commercial Space community through collaborative projects, partnership agreements, tech transfer program. Examples of challenges of AM implementation as well as opportunities will be discussed.

Alison Park↗

Extending ISS Life Beyond 2030

The United States On-orbit Segment (USOS) of the International Space Station (ISS) was designed to meet a 15-year on-orbit life. Since the first hardware was launched in late 1998, the ISS would have reached its end of life in 2013. With the realization that the ISS would be needed well into the next decade, and beyond, a multi-disciplinary effort was undertaken to extend the ISS’ life through 2028 and to show that further extension to 2040 and beyond is not only feasible but achievable. Currently, NASA and the ISS international partners have agreed to extend its operations through 2030. This collaborative effort ensures that the ISS will continue to serve as a hub for scientific research, international cooperation, and educational endeavors for the next decade. Maintaining a continuous human presence in Low Earth Orbit (LEO) is desirable for testing new LEO, lunar, and deep-space technologies; conducting scientific research in micro-gravity for the benefit of life on Earth; and enabling a seamless transition of capabilities to one or more commercially owned and operated destinations. This paper provides an overview of the ISS life extension project with a particular focus on the analytical approach used to assess the primary structure. This analytical approach includes future operations planning, critical location screening, on-orbit dynamic load simulation, on-orbit optical property degradation studies, on-orbit thermal analyses, spectra generation, crack model idealization, fracture analyses, and post processing. Structural life results and identification of the most critical on-orbit events are presented. Also addressed are life extension approaches for other affected sub-systems, including: 1. Secondary Structure. 2. Materials. Evaluations consider environmental exposure to atomic oxygen, ionizing and gamma radiation, fluids, etc. Life limited materials, wear, and usage effects are also considered. 3. Environmental Control and Life Support Systems, including oxygen supply and generation, water recovery and management, and regenerative hardware. Evaluations are performed to determine which hardware can be run to failure and which are assessed for life extension. 4. Electrical power system. ISS is powered by eight channels of solar arrays and an electrical energy storage system providing 357 kWh power. Power generation and balance analyses are performed considering hardware degradation and increasing power demand. 5. Logistics and maintenance. Analyses are performed to determine critical spares required to maintain functionality. Consideration is given to supply chain health, obsolescence issues, onboard stowage availability, and up-mass capability. The successful life extension results have built confidence to safely operate, maintain and enhance the ISS well beyond the current decade. Extending the operational life of the ISS maintains an international presence in LEO and serves to avoid a gap in capability necessary to fulfill the exploration and research needs of NASA, international partners, and industry without interruption until a commercial space station is operational.

design life↗