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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

An Overview of the Space Environments and Spacecraft Effects Organization Concept

The National Aeronautics and Space Administration (NASA) is embarking on a course to expand human presence beyond Low Earth Orbit (LEO) while also expanding its mission to explore our Earth, and the solar system. Destinations such as Near Earth Asteroids (NEA), Mars and its moons, and the outer planets are but a few of the mission targets. Each new destination presents an opportunity to increase our knowledge on the solar system and the unique environments for each mission target. NASA has multiple technical and science discipline areas specializing in specific space environments fields that will serve to enable these missions. To complement these existing discipline areas, a concept is presented focusing on the development of a space environment and spacecraft effects (SESE) organization. This SESE organization includes disciplines such as space climate, space weather, natural and induced space environments, effects on spacecraft materials and systems, and the transition of research information into application. This space environment and spacecraft effects organization will be composed of Technical Working Groups (TWG). These technical working groups will survey customers and users, generate products, and provide knowledge supporting four functional areas: design environments, engineering effects, operational support, and programmatic support. The four functional areas align with phases in the program mission lifecycle and are briefly described below. Design environments are used primarily in the mission concept and design phases of a program. Environment effects focuses on the material, component, sub-system, and system-level response to the space environment and include the selection and testing to verify design and operational performance. Operational support provides products based on real time or near real time space weather to mission operators to aid in real time and near-term decision-making. The programmatic support function maintains an interface with the numerous programs within NASA, other federal government agencies, and the commercial sector to ensure that communications are well established and the needs of the programs are being met. The programmatic support function also includes working in coordination with the program in anomaly resolution and generation of lessons learned documentation. The goal of this space environment and spacecraft effects organization is to develop decision-making tools and engineering products to support all mission phases from mission concept through operations by focusing on transitioning research to application. Products generated by this space environments and effects application are suitable for use in anomaly investigations. This paper will describe the scope and purpose of the space environments and spacecraft effects organization and describe the TWG's and their relationship to the functional areas.

Edwards, David L.↗
NASA NTRS2014

Air Traffic Management Technology Demonstration 1 (ATD-1) Tech Transfer Document Summary: Version 3.0

This document summarizes transfer of NASA's terminal sequencing and spacing (TSS) and interval management (IM) technologies to the FAA (Federal Aviation Administration), as part of its Air Traffic Management Technology (ATM) Demonstration 1 activity. This activity, referred to as ATD-1, is part of NASA's Airspace Systems Program (ASP) specifically, its System Analysis, Integration, and Evaluation (SAIE) Project. ATD-1 is a multi-year research and development effort aimed at accelerating implementation and deployment of NASA-developed ATM technologies by the FAA. These technologies are designed to improve the utilization of Performance-Based Navigation (PBN) procedures inside congested terminal airspace. In terms of NASA's Technology Readiness Levels (TRLs), ATD-1 is focused on maturing its associated technologies from the Technology Development stage (TRL 4) to the Technology Demonstration stage (TRL 6). In order to ensure that the products of this tech-transfer are relevant and useful, NASA has created strong partnerships with the FAA and key industry stakeholders.

Technology transfer↗
NASA NTRS2019

Moon Base Life Support Design Depends on Launch Cost, Crew Size, and Mission Duration

Brief human space missions such as Apollo and the Space Shuttle used material storage for life support but a long mission such as a space station uses a recycling life support system. The upcoming Moon visits will probably be brief with few crew at first but in the future there may be a long-term or even permanent Moon base with a large crew. The initial life support system will probably use storage and resupply of materials from Earth, but it could be replaced later by recycling, especially if launch cost per kilogram is high. Moon base life support design is investigated considering requirements, performance, reliability, cost, and risk. The launch cost, crew size, and mission duration are variable parameters that affect the life support design choice. Greater launch cost, crew size, or mission duration all tend to make recycling more cost-effective than resupply.

Jones, Harry W.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-27111-DND

Rigid aeroshell systems are rapidly approaching the payload limit that current technology can deliver while fitting within the payload envelope of existing launch vehicles. The need for higher entry mass, landing elevation, and more controllability has pushed NASA to improve existing atmospheric entry technologies to further its scientific and exploration capabilities. Hypersonic Inflatable Aerodynamic Decelerators (HIADs) are an emerging technology that allows entry vehicles to deliver larger payloads to higher landing elevations by providing a larger aeroshell diameter than rigid aeroshells. HIADs offer new methods of entry vehicle trajectory control through shape morphing of the inflatable aeroshell. This dissertation explores different concepts of morphing a HIAD by assessing its structural integrity, aerodynamic performance, and systems integration. Analytical models are developed to predict the amount of force required to achieve a desired morphed shape, an actuator and sensor are selected based on performance requirements, and a controller is designed to morph the HIAD through Lift-to-Drag modulation. The actuator and sensor system and controller are then integrated into a small-scale development unit of a HIAD and experimental results are compared to numerical simulations. Conclusions and contributions of this research are presented along with a discussion on further research opportunities of Morphing HIADs.

Adam Milne Slagle↗
NASA NTRSDate not supplied

The Porous Microstructure Analysis (PuMA) software

The open-source Porous Microstructure Analysis (PuMA) software was implemented to offer an efficient framework for determining material characteristics from 3D microstructures. Its development was inspired by progress in X-ray microtomography, an imaging technology that captures the internal structure of materials in 3D, and even in a 4D temporal context. Over recent years, this method has transformed the domain of materials science due to its capability to non-destructively examine material microstructures while presenting digital data about their geometrical details. It has provided insights into materials relevant to several NASA missions, including heatshields, parachute fabrics, meteorites, and other advanced composites. PuMA, in its current version 3, delivers an array of features, spanning from basic geometric insights of a microstructure to intricate anisotropic thermo-elastic and chemical behavior. Specifically, the software evaluates morphological attributes (specific surface area, volume fractions, mean intercept lengths, orientation) and physical characteristics (conductivity, elasticity, permeability, and tortuosity). Additionally, it can model material degradation processes, such as oxidation and surface chemistry interactions. The software can generate synthetic microstructures, from straightforward geometrical designs to intricate woven and non-woven geometries. Coupling material generation and characterization enable parametric studies and sensitivity analysis to optimize the microstructural performance and inform design decisions and reliability assessment based on uncertainty quantification. A recent addition to PuMA includes the TomoSAM plugin, devised to incorporate the cutting-edge Segment Anything Model (SAM). SAM is a promptable deep learning model that can identify objects and create image masks in a zero-shot manner, based only on a few user clicks. The synergy between these tools aids in the segmentation of complex 3D datasets from tomography or other imaging techniques, which would otherwise require a laborious manual segmentation process.

Tomography↗
NASA NTRSDate not supplied

The Porous Microstructure Analysis (PuMA) software

The open-source Porous Microstructure Analysis (PuMA) software was created to offer an efficient framework for determining material properties from 3D microstructures. Its development was inspired by progress in X-ray microtomography, an imaging technology that captures the internal structure of materials in 3D, and even in a 4D temporal context. Over recent years, this method has transformed the domain of materials science due to its capability to non-destructively examine material microstructures while presenting digital data about their geometrical details. It has provided insights into materials relevant to several NASA missions, including heatshields, parachute fabrics, meteorites, and other advanced composites. PuMA, in its current version 3, delivers an array of features, spanning from basic geometric insights of a microstructure to intricate anisotropic thermo-elastic and chemical behavior. Specifically, the software evaluates morphological attributes (specific surface area, volume fractions, mean intercept lengths, orientation) and physical characteristics (conductivity, elasticity, permeability, and tortuosity). Additionally, it can model material degradation processes, such as oxidation and surface chemistry interactions. The software can generate synthetic microstructures, from straightforward geometrical designs to intricate woven and non-woven geometries. Coupling material generation and characterization enables parametric studies and sensitivity analysis to optimize the microstructural performance and inform design decisions and reliability assessment based on uncertainty quantification. A recent addition to PuMA includes the TomoSAM plugin, devised to incorporate the cutting-edge Segment Anything Model (SAM) into our image segmentation workflow. SAM is a promptable deep learning model that can identify objects and create image masks in a zero-shot manner, based only on a few user clicks. The synergy between these tools aids in the segmentation of complex 3D datasets from tomography and other imaging techniques, which would otherwise require a laborious manual segmentation process.

Tomography↗
NASA NTRS2010

Constellation Ground Systems Launch Availability Analysis: Enhancing Highly Reliable Launch Systems Design

Success of the Constellation Program's lunar architecture requires successfully launching two vehicles, Ares I/Orion and Ares V/Altair, within a very limited time period. The reliability and maintainability of flight vehicles and ground systems must deliver a high probability of successfully launching the second vehicle in order to avoid wasting the on-orbit asset launched by the first vehicle. The Ground Operations Project determined which ground subsystems had the potential to affect the probability of the second launch and allocated quantitative availability requirements to these subsystems. The Ground Operations Project also developed a methodology to estimate subsystem reliability, availability, and maintainability to ensure that ground subsystems complied with allocated launch availability and maintainability requirements. The verification analysis developed quantitative estimates of subsystem availability based on design documentation, testing results, and other information. Where appropriate, actual performance history was used to calculate failure rates for legacy subsystems or comparative components that will support Constellation. The results of the verification analysis will be used to assess compliance with requirements and to highlight design or performance shortcomings for further decision making. This case study will discuss the subsystem requirements allocation process, describe the ground systems methodology for completing quantitative reliability, availability, and maintainability analysis, and present findings and observation based on analysis leading to the Ground Operations Project Preliminary Design Review milestone.

Gernand, Jeffrey L.↗
NASA NTRS1986

Manned Mars mission environmental control and life support subsystem

A specific design is not presented, but the general philosophy regarding potential Environmental Control/Life Support System (ECLSS) requirements, concepts, issues, and technology needs are discussed. The focus is on a manned Mars mission occurring in the late 1990's. Discussions on the Trans-Mars Vehicle, the Mars Excursion Module (MEM), and a Martian base facility are covered. The functions, performance requirements, and design loads of a typical ECLSS are listed, and the issues and technology briefly discussed. Several ECLSS concepts and options are identified, and comparative weights and volumes are provided for these. Several aspects of the space station ECLSS are contrasted with the Mars element ECLSS.

Hueter, Uwe↗
NASA NTRS1991

Systematic methods for knowledge acquisition and expert system development

Nine cooperating rule-based systems, collectively called AUTOCREW which were designed to automate functions and decisions associated with a combat aircraft's subsystems, are discussed. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base and to assess the cooperation between the rule bases. Simulation and comparative workload results for two mission scenarios are given. The scenarios are inbound surface-to-air-missile attack on the aircraft and pilot incapacitation. The methodology used to develop the AUTOCREW knowledge bases is summarized. Issues involved in designing the navigation sensor selection expert in AUTOCREW's NAVIGATOR knowledge base are discussed in detail. The performance of seven navigation systems aiding a medium-accuracy INS was investigated using Kalman filter covariance analyses. A navigation sensor management (NSM) expert system was formulated from covariance simulation data using the analysis of variance (ANOVA) method and the ID3 algorithm. ANOVA results show that statistically different position accuracies are obtained when different navaids are used, the number of navaids aiding the INS is varied, the aircraft's trajectory is varied, and the performance history is varied. The ID3 algorithm determines the NSM expert's classification rules in the form of decision trees. The performance of these decision trees was assessed on two arbitrary trajectories, and the results demonstrate that the NSM expert adapts to new situations and provides reasonable estimates of the expected hybrid performance.

Belkin, Brenda L.↗
NASA NTRS2010

Constellation Ground Systems Launch Availability Analysis: Enhancing Highly Reliable Launch Systems Design

Success of the Constellation Program's lunar architecture requires successfully launching two vehicles, Ares I/Orion and Ares V/Altair, in a very limited time period. The reliability and maintainability of flight vehicles and ground systems must deliver a high probability of successfully launching the second vehicle in order to avoid wasting the on-orbit asset launched by the first vehicle. The Ground Operations Project determined which ground subsystems had the potential to affect the probability of the second launch and allocated quantitative availability requirements to these subsystems. The Ground Operations Project also developed a methodology to estimate subsystem reliability, availability and maintainability to ensure that ground subsystems complied with allocated launch availability and maintainability requirements. The verification analysis developed quantitative estimates of subsystem availability based on design documentation; testing results, and other information. Where appropriate, actual performance history was used for legacy subsystems or comparative components that will support Constellation. The results of the verification analysis will be used to verify compliance with requirements and to highlight design or performance shortcomings for further decision-making. This case study will discuss the subsystem requirements allocation process, describe the ground systems methodology for completing quantitative reliability, availability and maintainability analysis, and present findings and observation based on analysis leading to the Ground Systems Preliminary Design Review milestone.

Gernand, Jeffrey L.↗
NASA NTRS2000

Performance Monitoring of Distributed Data Processing Systems

Test and checkout systems are essential components in ensuring safety and reliability of aircraft and related systems for space missions. A variety of systems, developed over several years, are in use at the NASA/KSC. Many of these systems are configured as distributed data processing systems with the functionality spread over several multiprocessor nodes interconnected through networks. To be cost-effective, a system should take the least amount of resource and perform a given testing task in the least amount of time. There are two aspects of performance evaluation: monitoring and benchmarking. While monitoring is valuable to system administrators in operating and maintaining, benchmarking is important in designing and upgrading computer-based systems. These two aspects of performance evaluation are the foci of this project. This paper first discusses various issues related to software, hardware, and hybrid performance monitoring as applicable to distributed systems, and specifically to the TCMS (Test Control and Monitoring System). Next, a comparison of several probing instructions are made to show that the hybrid monitoring technique developed by the NIST (National Institutes for Standards and Technology) is the least intrusive and takes only one-fourth of the time taken by software monitoring probes. In the rest of the paper, issues related to benchmarking a distributed system have been discussed and finally a prescription for developing a micro-benchmark for the TCMS has been provided.

Ojha, Anand K.↗
NASA NTRSDate not supplied

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben D Phillips↗
NASA NTRSDate not supplied

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben Phillips↗
NASA NTRS1984

STS II - Beyond Shuttle

Advanced launch vehicle systems, which could replace the Space Shuttle to meet the expanded space transportation demands of commercial, governmental, and military space users in the post 2000 time frame, are examined. Vehicle scenarios, mission requirements, vehicle concepts, economics, and technology requirements are assessed. Vehicle requirements are to achieve significant reductions in operations and life-cycle costs while increasing the overall launch capacity. Vehicle designs emphasize conventional rocket-powered configurations derived from Space Shuttle concepts and based on evolutionary technologies. Technologies focus on high performance, cost-effective design and manufacturing and on high operational productivity.

Eldred, C. H.↗
NASA NTRS1998

High Performance, Robust Control of Flexible Space Structures: MSFC Center Director's Discretionary Fund

Many spacecraft systems have ambitious objectives that place stringent requirements on control systems. Achievable performance is often limited because of difficulty of obtaining accurate models for flexible space structures. To achieve sufficiently high performance to accomplish mission objectives may require the ability to refine the control design model based on closed-loop test data and tune the controller based on the refined model. A control system design procedure is developed based on mixed H2/H(infinity) optimization to synthesize a set of controllers explicitly trading between nominal performance and robust stability. A homotopy algorithm is presented which generates a trajectory of gains that may be implemented to determine maximum achievable performance for a given model error bound. Examples show that a better balance between robustness and performance is obtained using the mixed H2/H(infinity) design method than either H2 or mu-synthesis control design. A second contribution is a new procedure for closed-loop system identification which refines parameters of a control design model in a canonical realization. Examples demonstrate convergence of the parameter estimation and improved performance realized by using the refined model for controller redesign. These developments result in an effective mechanism for achieving high-performance control of flexible space structures.

Whorton, M. S.↗
NASA NTRS1976

A model-based analysis of a display for helicopter landing approach

A control theoretic model of the human pilot was used to analyze a baseline electronic cockpit display in a helicopter landing approach task and to generate display quickening laws designed to improve pilot-vehicle performance. A simple fixed base simulation provided comparative tracking data which allowed refinement of the pilot model.

Hess, R. A.↗
NASA NTRS1998

Euler Calculations at Off-Design Conditions for an Inlet of Inward Turning RBCC-SSTO Vehicle

The inviscid performance of an inward turning inlet design is calculated computationally for the first time. Hypersonic vehicle designs based on the inward turning inlets have been shown analytically to have increased effective specific impulse and lower heat load than comparably designed vehicles with two-dimensional inlets. The inward turning inlets are designed inversely from inviscid stream surfaces of known flow fields. The computational study is performed on a Mach 12 inlet design to validate the performance predicted by the design code (HAVDAC) and calculate its off-design Mach number performance. The three-dimensional Euler equations are solved for Mach 4, 8, and 12 using a software package called SAM, which consists of an unstructured mesh generator (SAMmesh), a three-dimensional unstructured mesh flow solver (SAMcfd), and a CAD-based software (SAMcad). The computed momentum averaged inlet throat pressure is within 6% of the design inlet throat pressure. The mass-flux at the inlet throat is also within 7 % of the value predicted by the design code thereby validating the accuracy of the design code. The off-design Mach number results show that flow spillage is minimal, and the variation in the mass capture ratio with Mach number is comparable to an ideal 2-D inlet. The results from the inviscid flow calculations of a Mach 12 inward turning inlet indicate that the inlet design has very good on and off-design performance which makes it a promising design candidate for future air-breathing hypersonic vehicles.

Takashima, N.↗
NASA NTRS1991

The effect of on/off indicator design on state confusion, preference, and response time performance, executive summary

Investigated are five designs of software-based ON/OFF indicators in a hypothetical Space Station Power System monitoring task. The hardware equivalent of the indicators used in the present study is the traditional indicator light that illuminates an ON label or an OFF label. Coding methods used to represent the active state were reverse video, color, frame, check, or reverse video with check. Display background color was also varied. Subjects made judgments concerning the state of indicators that resulted in very low error rates and high percentages of agreement across indicator designs. Response time measures for each of the five indicator designs did not differ significantly, although subjects reported that color was the best communicator. The impact of these results on indicator design is discussed.

Donner, Kimberly A.↗