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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRSDate not supplied

Gateway Program Safety and Mission Assurance Integration - the Future of Safe Deep Space Human Exploration

As a foundational element of the National Aeronautics and Space Administration (NASA) Artemis Campaign, the Gateway is an incrementally built cislunar spacecraft that will serve as a platform for deep space human exploration, science, and technology demonstration. The Gateway will be a unifying catalyst for international partners around the world to establish sustained deep space scientific investigations, lunar surface access, and missions to Mars. As human exploration moves farther away from Earth, spacecraft designs must prioritize and optimize mass and volume allocations, while minimizing human and spacecraft risk. To accomplish this objective, the Gateway Program Safety and Mission Assurance functions develop, implement, and ensure compliance with requirements, in concert with the accurate characterization and transparent communication of residual hazard risks, for integrated safety, reliability and maintainability and quality assurance. Safety and Mission Assurance was a key contributor during Gateway program pre-formulation and formulation activities where safety and reliability analysis was embedded in the Gateway Systems Engineering and Integration team. During these early program stages, a preliminary Gateway Integrated Hazard Analysis and Preliminary Gateway Probabilistic Risk Assessment assisted in Gateway architectural and operational definition as part of a risk-informed design process. As the deep space architecture has matured, the integrated Safety and Mission Assurance analyses have matured, new safety review processes have been developed, and requirements have been refined to ensure compliance with integrated safety and mission assurance objectives. The Gateway Program is currently concluding the preliminary design review informed milestone, where the primary objectives included: - Ensured completeness and consistency of the preliminary design, including the meeting of all requirements within appropriate margins and acceptable risk posture. - Identification of any major issues moving forward to the Critical Design phase. At this milestone, Safety and Mission Assurance provided numerous products, including Gateway Top Risks and Risk Mitigation Plans, updated integrated hazard analyses, updated probabilistic risk assessment, Crew Survival Analysis Report, and updated Safety and Mission Assurance Requirements and Plans. These products provide a many-faceted perspective on the inherent risk and available mitigations involved in flying the current proposed vehicle design and anticipated stack configurations. In addition, Safety and Mission Assurance identified top technical, process and workforce concerns to be addressed as the program progresses toward the critical design phase. This paper will detail the evolution of the Gateway Program Safety and Mission Assurance integration functions, provide its current status and lessons learned for future human spaceflight programs. Throughout this paper the key tenets of the Gateway Program Safety and Mission Assurance will be discussed: - Application of a risk-informed approach to identify and mitigate areas of highest risk. - Leverage of valuable processes and lessons learned from earlier spaceflight programs. - Development of Safety and Mission Assurance products to inform design risk trades. - Utilization of common Safety and Mission Assurance practices to identify safety risks for multiple perspectives: top-down, bottom-up, and across lines of integration. - Approval of safety hazards at the appropriate level of authority, keeping most deliberation closest to design expertise and elevating risks of greatest concern for program-level consideration. - Championing of Safety and Mission Assurance processes and forums to foster a pervasive safety culture that is transparent, inclusive, and collaborative between all partners. These tenets have allowed the Gateway Safety and Mission Assurance function to play a key role in optimized vehicle design evolution, and early identification and mitigation of Gateway program and Artemis mission risk.

Helen Vaccaro↗
NASA NTRSDate not supplied

Intent Modeling and Intent Conflict Probability Calculation for Operations in Upper Class E Airspace

This work presents probabilistic intent models for two typical vehicles in ETM operational environment. Several methods, including analytical methods for approximated solutions and a numerical method for exact solution, are presented and applied to compute the intent conflict probability for ETM operations. A comparison of these methods will be conducted in the final paper. Furthermore, simulations will be performed to verify the probabilistic intent model and verify the results of intent conflict probability from different methods.

Operational intent↗
NASA NTRS1988

NESSUS (Numerical Evaluation of Stochastic Structures Under Stress)/EXPERT: Bridging the gap between artificial intelligence and FORTRAN

The development of a probabilistic structural analysis methodology (PSAM) is described. In the near-term, the methodology will be applied to designing critical components of the next generation space shuttle main engine. In the long-term, PSAM will be applied very broadly, providing designers with a new technology for more effective design of structures whose character and performance are significantly affected by random variables. The software under development to implement the ideas developed in PSAM resembles, in many ways, conventional deterministic structural analysis code. However, several additional capabilities regarding the probabilistic analysis makes the input data requirements and the resulting output even more complex. As a result, an intelligent front- and back-end to the code is being developed to assist the design engineer in providing the input data in a correct and appropriate manner. The type of knowledge that this entails is, in general, heuristically-based, allowing the fairly well-understood technology of production rules to apply with little difficulty. However, the PSAM code, called NESSUS, is written in FORTRAN-77 and runs on a DEC VAX. Thus, the associated expert system, called NESSUS/EXPERT, must run on a DEC VAX as well, and integrate effectively and efficiently with the existing FORTRAN code. This paper discusses the process undergone to select a suitable tool, identify an appropriate division between the functions that should be performed in FORTRAN and those that should be performed by production rules, and how integration of the conventional and AI technologies was achieved.

Fink, Pamela K.↗
NASA NTRS2005

Robust Control Design for Systems With Probabilistic Uncertainty

This paper presents a reliability- and robustness-based formulation for robust control synthesis for systems with probabilistic uncertainty. In a reliability-based formulation, the probability of violating design requirements prescribed by inequality constraints is minimized. In a robustness-based formulation, a metric which measures the tendency of a random variable/process to cluster close to a target scalar/function is minimized. A multi-objective optimization procedure, which combines stability and performance requirements in time and frequency domains, is used to search for robustly optimal compensators. Some of the fundamental differences between the proposed strategy and conventional robust control methods are: (i) unnecessary conservatism is eliminated since there is not need for convex supports, (ii) the most likely plants are favored during synthesis allowing for probabilistic robust optimality, (iii) the tradeoff between robust stability and robust performance can be explored numerically, (iv) the uncertainty set is closely related to parameters with clear physical meaning, and (v) compensators with improved robust characteristics for a given control structure can be synthesized.

Crespo, Luis G.↗
NASA NTRS2014

International Space Station End-of-Life Probabilistic Risk Assessment

The International Space Station (ISS) end‐of‐life (EOL) cycle is currently scheduled for 2020, although there are ongoing efforts to extend ISS life cycle through 2028. The EOL for the ISS will require deorbiting the ISS. This will be the largest manmade object ever to be de‐orbited therefore safely deorbiting the station will be a very complex problem. This process is being planned by NASA and its international partners. Numerous factors will need to be considered to accomplish this such as target corridors, orbits, altitude, drag, maneuvering capabilities etc. The ISS EOL Probabilistic Risk Assessment (PRA) will play a part in this process by estimating the reliability of the hardware supplying the maneuvering capabilities. The PRA will model the probability of failure of the systems supplying and controlling the thrust needed to aid in the de‐orbit maneuvering.

Duncan, Gary W.↗
NASA NTRS1989

Probabilistic structural analysis methods of hot engine structures

Development of probabilistic structural analysis methods for hot engine structures is a major activity at Lewis Research Center. Recent activities have focused on extending the methods to include the combined uncertainties in several factors on structural response. This paper briefly describes recent progress on composite load spectra models, probabilistic finite element structural analysis, and probabilistic strength degradation modeling. Progress is described in terms of fundamental concepts, computer code development, and representative numerical results.

Chamis, C. C.↗
NASA NTRS2001

Free Vibration of Uncertain Unsymmetrically Laminated Beams

Monte Carlo Simulation and Stochastic FEA are used to predict randomness in the free vibration response of thin unsymmetrically laminated beams. For the present study, it is assumed that randomness in the response is only caused by uncertainties in the ply orientations. The ply orientations may become random or uncertain during the manufacturing process. A new 16-dof beam element, based on the first-order shear deformation beam theory, is used to study the stochastic nature of the natural frequencies. Using variational principles, the element stiffness matrix and mass matrix are obtained through analytical integration. Using a random sequence a large data set is generated, containing possible random ply-orientations. This data is assumed to be symmetric. The stochastic-based finite element model for free vibrations predicts the relation between the randomness in fundamental natural frequencies and the randomness in ply-orientation. The sensitivity derivatives are calculated numerically through an exact formulation. The squared fundamental natural frequencies are expressed in terms of deterministic and probabilistic quantities, allowing to determine how sensitive they are to variations in ply angles. The predicted mean-valued fundamental natural frequency squared and the variance of the present model are in good agreement with Monte Carlo Simulation. Results, also, show that variations between plus or minus 5 degrees in ply-angles can affect free vibration response of unsymmetrically and symmetrically laminated beams.

Kapania, Rakesh K.↗
NASA NTRS2014

International Space Station End-of-Life Probabilistic Risk Assessment

Although there are ongoing efforts to extend the ISS life cycle through 2028, the International Space Station (ISS) end-of-life (EOL) cycle is currently scheduled for 2020. The EOL for the ISS will require de-orbiting the ISS. This will be the largest manmade object ever to be de-orbited, therefore safely de-orbiting the station will be a very complex problem. This process is being planned by NASA and its international partners. Numerous factors will need to be considered to accomplish this such as target corridors, orbits, altitude, drag, maneuvering capabilities, debris mapping etc. The ISS EOL Probabilistic Risk Assessment (PRA) will play a part in this process by estimating the reliability of the hardware supplying the maneuvering capabilities. The PRA will model the probability of failure of the systems supplying and controlling the thrust needed to aid in the de-orbit maneuvering.

Duncan, Gary↗
NASA NTRS2011

Application of Probabilistic Methods to Assess Risk Due to Resonance in the Design of J-2X Rocket Engine Turbine Blades

The LOX-Hydrogen J-2X Rocket Engine, which is proposed for use as an upper-stage engine for numerous earth-to-orbit and heavy lift launch vehicle architectures, is presently in the design phase and will move shortly to the initial development test phase. Analysis of the design has revealed numerous potential resonance issues with hardware in the turbomachinery turbine-side flow-path. The analysis of the fuel pump turbine blades requires particular care because resonant failure of the blades, which are rotating in excess of 30,000 revolutions/minutes (RPM), could be catastrophic for the engine and the entire launch vehicle. This paper describes a series of probabilistic analyses performed to assess the risk of failure of the turbine blades due to resonant vibration during past and present test series. Some significant results are that the probability of failure during a single complete engine hot-fire test is low (~1%) because of the small likelihood of resonance, but that the probability increases to around 30% for a more focused turbomachinery-only test because all speeds will be ramped through and there is a greater likelihood of dwelling at more speeds. These risk calculations have been invaluable for use by program management in deciding if risk-reduction methods such as dampers are necessary immediately or if the test can be performed before the risk-reduction hardware is ready.

Brown, Andrew M.↗
NASA NTRS1977

Limitations to growth of microorganisms on Uranus, Neptune, and Titan

Reappraisal of the probabilistic policy toward planetary contamination by terrestrial microorganisms carried aboard space probes is suggested on the grounds that assignment of numerical probabilities to qualitatively unknown phenomena, as expressed in Phillips's (1974) formulation of the probability of contamination, is inappropriate. As an alternative, it is proposed that fundamental knowledge of the interacting nature of life on earth, interrelations between terrestrial organisms, and continuing effects of these organisms on earth's atmosphere and surface should guide the formulation of a sounder scientific quarantine policy. Simple conservative atmospheric models most favorable for life on Uranus and Neptune are examined. It is concluded that terrestrial microorganisms will not grow on either planet due to limitations of liquid water, atmospheric convection to lethal depths, the absence of energy sources and nutrients, the presence of ammonia and hydrogen, insufficient concentrations of biologically necessary ions, and the lack of a surface. The likelihood of terrestrial microorganism growth on Titan is found to be vanishingly small.

Margulis, L.↗
NASA NTRS1993

Reliability based structural optimization - A simplified safety index approach

A probabilistic optimal design methodology for complex structures modelled with finite element methods is presented. The main emphasis is on developing probabilistic analysis tools suitable for optimization. An advanced second-moment method is employed to evaluate the failure probability of the performance function. The safety indices are interpolated using the information at mean and most probable failure point. The minimum weight design with an improved safety index limit is achieved by using the extended interior penalty method of optimization. Numerical examples covering beam and plate structures are presented to illustrate the design approach. The results obtained by using the proposed approach are compared with those obtained by using the existing probabilistic optimization techniques.

Reddy, Mahidhar V.↗
NASA NTRS2009

Johnson Space Center's Risk and Reliability Analysis Group 2008 Annual Report

The Johnson Space Center (JSC) Safety & Mission Assurance (S&MA) Directorate s Risk and Reliability Analysis Group provides both mathematical and engineering analysis expertise in the areas of Probabilistic Risk Assessment (PRA), Reliability and Maintainability (R&M) analysis, and data collection and analysis. The fundamental goal of this group is to provide National Aeronautics and Space Administration (NASA) decisionmakers with the necessary information to make informed decisions when evaluating personnel, flight hardware, and public safety concerns associated with current operating systems as well as with any future systems. The Analysis Group includes a staff of statistical and reliability experts with valuable backgrounds in the statistical, reliability, and engineering fields. This group includes JSC S&MA Analysis Branch personnel as well as S&MA support services contractors, such as Science Applications International Corporation (SAIC) and SoHaR. The Analysis Group s experience base includes nuclear power (both commercial and navy), manufacturing, Department of Defense, chemical, and shipping industries, as well as significant aerospace experience specifically in the Shuttle, International Space Station (ISS), and Constellation Programs. The Analysis Group partners with project and program offices, other NASA centers, NASA contractors, and universities to provide additional resources or information to the group when performing various analysis tasks. The JSC S&MA Analysis Group is recognized as a leader in risk and reliability analysis within the NASA community. Therefore, the Analysis Group is in high demand to help the Space Shuttle Program (SSP) continue to fly safely, assist in designing the next generation spacecraft for the Constellation Program (CxP), and promote advanced analytical techniques. The Analysis Section s tasks include teaching classes and instituting personnel qualification processes to enhance the professional abilities of our analysts as well as performing major probabilistic assessments used to support flight rationale and help establish program requirements. During 2008, the Analysis Group performed more than 70 assessments. Although all these assessments were important, some were instrumental in the decisionmaking processes for the Shuttle and Constellation Programs. Two of the more significant tasks were the Space Transportation System (STS)-122 Low Level Cutoff PRA for the SSP and the Orion Pad Abort One (PA-1) PRA for the CxP. These two activities, along with the numerous other tasks the Analysis Group performed in 2008, are summarized in this report. This report also highlights several ongoing and upcoming efforts to provide crucial statistical and probabilistic assessments, such as the Extravehicular Activity (EVA) PRA for the Hubble Space Telescope service mission and the first fully integrated PRAs for the CxP's Lunar Sortie and ISS missions.

Valentine, Mark↗
NASA NTRS1991

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system components, part 2

The technical effort and computer code enhancements performed during the sixth year of the Probabilistic Structural Analysis Methods program are summarized. Various capabilities are described to probabilistically combine structural response and structural resistance to compute component reliability. A library of structural resistance models is implemented in the Numerical Evaluations of Stochastic Structures Under Stress (NESSUS) code that included fatigue, fracture, creep, multi-factor interaction, and other important effects. In addition, a user interface was developed for user-defined resistance models. An accurate and efficient reliability method was developed and was successfully implemented in the NESSUS code to compute component reliability based on user-selected response and resistance models. A risk module was developed to compute component risk with respect to cost, performance, or user-defined criteria. The new component risk assessment capabilities were validated and demonstrated using several examples. Various supporting methodologies were also developed in support of component risk assessment.

Source record↗
NASA NTRS2005

Diagnosing Hybrid Systems: a Bayesian Model Selection Approach

In this paper we examine the problem of monitoring and diagnosing noisy complex dynamical systems that are modeled as hybrid systems-models of continuous behavior, interleaved by discrete transitions. In particular, we examine continuous systems with embedded supervisory controllers that experience abrupt, partial or full failure of component devices. Building on our previous work in this area (MBCG99;MBCG00), our specific focus in this paper ins on the mathematical formulation of the hybrid monitoring and diagnosis task as a Bayesian model tracking algorithm. The nonlinear dynamics of many hybrid systems present challenges to probabilistic tracking. Further, probabilistic tracking of a system for the purposes of diagnosis is problematic because the models of the system corresponding to failure modes are numerous and generally very unlikely. To focus tracking on these unlikely models and to reduce the number of potential models under consideration, we exploit logic-based techniques for qualitative model-based diagnosis to conjecture a limited initial set of consistent candidate models. In this paper we discuss alternative tracking techniques that are relevant to different classes of hybrid systems, focusing specifically on a method for tracking multiple models of nonlinear behavior simultaneously using factored sampling and conditional density propagation. To illustrate and motivate the approach described in this paper we examine the problem of monitoring and diganosing NASA's Sprint AERCam, a small spherical robotic camera unit with 12 thrusters that enable both linear and rotational motion.

McIlraith, Sheila A.↗
NASA NTRS2000

Demonstration of the Application of Composite Load Spectra (CLS) and Probabilistic Structural Analysis (PSAM) Codes to SSME Heat Exchanger Turnaround Vane

This report describes a probabilistic structural analysis performed to determine the probabilistic structural response under fluctuating random pressure loads for the Space Shuttle Main Engine (SSME) turnaround vane. It uses a newly developed frequency and distance dependent correlation model that has features to model the decay phenomena along the flow and across the flow with the capability to introduce a phase delay. The analytical results are compared using two computer codes SAFER (Spectral Analysis of Finite Element Responses) and NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) and with experimentally observed strain gage data. The computer code NESSUS with an interface to a sub set of Composite Load Spectra (CLS) code is used for the probabilistic analysis. A Fatigue code was used to calculate fatigue damage due to the random pressure excitation. The random variables modeled include engine system primitive variables that influence the operating conditions, convection velocity coefficient, stress concentration factor, structural damping, and thickness of the inner and outer vanes. The need for an appropriate correlation model in addition to magnitude of the PSD is emphasized. The study demonstrates that correlation characteristics even under random pressure loads are capable of causing resonance like effects for some modes. The study identifies the important variables that contribute to structural alternate stress response and drive the fatigue damage for the new design. Since the alternate stress for the new redesign is less than the endurance limit for the material, the damage due high cycle fatigue is negligible.

Rajagopal, Kadambi R.↗
NASA NTRS1991

Simulation of probabilistic wind loads and building analysis

Probabilistic wind loads likely to occur on a structure during its design life are predicted. Described here is a suitable multifactor interactive equation (MFIE) model and its use in the Composite Load Spectra (CLS) computer program to simulate the wind pressure cumulative distribution functions on four sides of a building. The simulated probabilistic wind pressure load was applied to a building frame, and cumulative distribution functions of sway displacements and reliability against overturning were obtained using NESSUS (Numerical Evaluation of Stochastic Structure Under Stress), a stochastic finite element computer code. The geometry of the building and the properties of building members were also considered as random in the NESSUS analysis. The uncertainties of wind pressure, building geometry, and member section property were qualified in terms of their respective sensitivities on the structural response.

Shah, Ashwin R.↗
NASA NTRS2017

Methods for Probabilistic Uncertainty Analysis and Bayesian Analysis with Examples of Statistically Analyzing Data to Revise MMOD Risk Estimates and Compare Models

Probabilistic methods are presented for characterizing and quantifying uncertainties in models and model predictions. Techniques are given for constructing specific uncertainty distributions based on available information. Alternative techniques are given for propagating uncertainties in model inputs to obtain the uncertainty in the model result or prediction. Bayesian techniques are also described for utilizing data and information to update and revise model results and predictions. The focus is on applications with numerous specific examples given. The use of data to revise Micrometeoroid and Orbital Debris (MMOD) risk prediction models are among the examples given.

Risk↗
NASA NTRS2019

TURBOMAT: A Probabilistic Turbomachinery Aeroelastic Analysis Tool

An integration of aeroelastic analysis procedures with probabilistic analysis methods enables us to design safe reliable engines with quantified reliability. Towards this goal, a graphical user interface (GUI) based tool that integrates the codes Aeroelastic analysis of propfans (ASTROP2) and Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) is developed. The tool entitled TURBOMachinery Aeroelastic Analysis Tool (TURBOMAT), is developed utilizing the MATrix Laboratory (Matlab) Guide (Graphical User Interface Development) tool box. TURBOMAT provides a user friendly computational environment for rapid assessment of Turbomachinery blades flutter characteristics, subjected to uncertain loading conditions with variability in material and aerodynamic properties. The tool is seen as an education tool for new students and young engineers starting their careers in structural Aeroelasticity who want to learn and understand aeroelastic aspects of turbomachinery components, fans, compressors and turbines, including uncertainties in loading and material properties.A typical fan blade configuration geometry was chosen to demonstrate the tool. The results are presented in the form of probabilistic density function (PDF), the cumulative distribution function (CDF) and sensitivity factors. Both first order fast probability integration (FPI) and the Monto Carlo (MC) techniques are used in the analysis and compared. The tool enabled us to quantify blade flutter reliability as well as the ranking of uncertain variables and their importance to blade flutter response.

Aeroelastic Analysis↗