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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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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Application of advanced reliability methods to local strain fatigue analysis

When design factors are considered as random variables and the failure condition cannot be expressed by a closed form algebraic inequality, computations of risk (or probability of failure) might become extremely difficult or very inefficient. This study suggests using a simple, and easily constructed, second degree polynomial to approximate the complicated limit state in the neighborhood of the design point; a computer analysis relates the design variables at selected points. Then a fast probability integration technique (i.e., the Rackwitz-Fiessler algorithm) can be used to estimate risk. The capability of the proposed method is demonstrated in an example of a low cycle fatigue problem for which a computer analysis is required to perform local strain analysis to relate the design variables. A comparison of the performance of this method is made with a far more costly Monte Carlo solution. Agreement of the proposed method with Monte Carlo is considered to be good.

Wu, T. T.↗
NASA NTRS1984

Advanced reliability method for fatigue analysis

When design factors are considered as random variables and the failure condition cannot be expressed by a closed form algebraic inequality, computations of risk (or probability of failure) may become extremely difficult or very inefficient. This study suggests using a simple and easily constructed second degree polynomial to approximate the complicated limit state in the neighborhood of the design point; a computer analysis relates the design variables at selected points. Then a fast probability integration technique (i.e., the Rackwitz-Fiessler algorithm) can be used to estimate risk. The capability of the proposed method is demonstrated in an example of a low cycle fatigue problem for which a computer analysis is required to perform local strain analysis to relate the design variables. A comparison of the performance of this method is made with a far more costly Monte Carlo solution. Agreement of the proposed method with Monte Carlo is considered to be good.

Wu, Y.-T.↗
NASA NTRS2019

Modeling Meteoroid Densities for Spacecraft Risk Assessment

This report describes the methodologies and algorithms that NASA’s Meteoroid Environment Office (MEO) currently utilizes to measure meteoroid densities. We discuss the needs for an accurate model for the meteoroid density distribution in its Meteoroid Engineering Model (MEM), and its potential implications for spacecraft design. The recently developed process is heavily derived from that of previous work, although subtle differences exist. A thorough comparison of the best-fit densities derived for sixty meteoroids in and with the process described here shows that discrepancies in final densities larger than a factor of two are measured for ∼ 20% of our test events. Such a level of discrepancy suggests that any density calculated using similar methods cannot be assumed to represent a unique fit to the data. Additional observational data for meteoroids beyond those utilized in this work will be essential for producing more reliable and repeatable density measurements.

Ehlert, Steven↗
NASA NTRS2019

Assessing GEO and LEO Repeating Conjunctions Using High Fidelity Brute Force Monte Carlo Simulations

Probability of collision (P(sub c)) estimates for Earth-orbiting satellites typically assume a temporally-isolated conjunction event. However, under certain conditions two objects may experience multiple high-risk close approach events over the course of hours or days. In these repeating conjunction cases, the P(sub c) accumulates as each successive encounter occurs. The NASA Conjunction Assessment Risk Analysis team has updated its “brute force Monte Carlo” (BFMC) software to estimate such accumulating P(sub c) values for repeating conjunctions. This study describes the updated BFMC algorithm and discusses the implications for conjunction risk assessment.

Baars, Luis↗
NASA NTRS2019

Assessing Geo and Leo Repeating Conjunctions Using High Fidelity Brute Force Monte Carlo Simulations

Probability of collision (P(sub c)) estimates for Earth-orbiting satellites typically assume a temporally-isolated conjunction event. However, under certain conditions two objects may experience multiple high-risk close approach events over the course of hours or days. In these repeating conjunction cases, the P(sub c) accumulates as each successive encounter occurs. The NASA Conjunction Assessment Risk Analysis team has updated its “brute force Monte Carlo” (BFMC) software to estimate such accumulating P(sub c) values for repeating conjunctions. This study describes the updated BFMC algorithm and discusses the implications for conjunction risk assessment.

Baars, Luis↗
NASA NTRS1995

Next generation fire suppressants

Spectrex, Inc., located in Cedar Grove, NJ is a manufacturer of fire detection and suppression equipment. Spectrex is one of the original pioneers in high speed fire detection and suppression systems for combat vehicles. Spectrex has installed fire suppressions systems in thousands of combat vehicles and ships throughout the world. Additionally, they manufacture flame explosion detectors, ship damage control systems, and optical gas and vapor detectors. The culmination of several years of research and development has recently produced an innovative electro-optical continuous monitoring systems called SharpEye 20/20I IR(sup 3) and SAFEYE that provide fast and reliable gas, vapor, aerosol, flame, and explosion detection. SharpEye 20/20I IR(sup 3) is a self-contained triple spectrum flame detector which scans for oscillating IR radiation (1 to 10 Hz) in the spectral bands ranging from 4.0 to 5.0 microns and uses programmed algorithms to check the ratio and correlation of data received by the three sensors to make the system highly immune to false alarms. It is extremely sensitive as it can detect a 1 x 1 square foot gasoline pan fire at 200 feet in less than 3 seconds. The sensitivity is user programmable, offering 4 ranges of detection. SAFEYE is comprised of a selected number of multispectral ban microprocessors controlled detectors which are in communication with one or more radiation sources that is projected along a 600 feet optical path. The signals from the selected narrow bands are processed and analyzed by highly sophisticated algorithms. It is ideal for high risk, remote, large areas such as petroleum and chemical manufacturing sites, waste dumps, aircraft cargo bays, and ship compartments. The SAFEYE will perform direct readings of the presence or rate of rise of concentrations of gases, vapors, or aerosols at the range of parts per million and provide alarms at various set points at different levels of concentrations.

Brown, Jerry A.↗
NASA NTRS2004

Case Study of Risk Mitigation Based on Hardware/Software Integration (HSI) Testing for the International Space Station (ISS) Node 2 Module

Within the pressurized elements of the International Space Station (ISS), requirements exist to ensure a safe, habitable environment for the crew. In order to provide this environment, thermal control components work in conjunction with software controls to provide heat rejection for subsystem avionics equipment, for the environmental control system and for experiment payloads. It is essential to ISS operations, mission success and crew safety that necessary testing incorporates the extreme conditions to ensure proper performance. This paper provides a general description and methodology applied to thermal related Hardware/Software Integration (HSI) tests for the ISS Node 2 module. A detailed test plan was developed and implemented with two objectives: the first was for risk mitigation of the thermal control algorithms and software qualification, and the second was for data collection which will substantiate thermalhydraulic models of the Internal Active Thermal Control System (IATCS). Analytical models are utilized to determine on-orbit performance for conditions and scenarios where the simulation of actual on-orbit system performance is limited by test configuration constraints. Node 2 IATCS HSI activities were performed at the Alenia Spazio facility in Torino, Italy with participation from the National Aeronautics and Space Administration (NASA), Alenia Spazio, Jacobs Engineering Sverdrup (JE Sverdrup) and Boeing.

Holt, James Mike↗
NASA NTRS2008

Suborbital Science Program: Dryden Flight Research Center

This viewgraph presentation reviews the suborbital science program at NASA Dryden Flight Research Center. The Program Objectives are given in various areas: (1) Satellite Calibration and Validation (Cal/val)--Provide methods to perform the cal/val requirements for Earth Observing System satellites; (2) New Sensor Development -- Provide methods to reduce risk for new sensor concepts and algorithm development prior to committing sensors to operations; (3) Process Studies -- Facilitate the acquisition of high spatial/temporal resolution focused measurements that are required to understand small atmospheric and surface structures which generate powerful Earth system effects; and (4) Airborne Networking -- Develop disruption-tolerant networking to enable integrated multiple scale measurements of critical environmental features. Dryden supports the NASA Airborne Science Program and the nation in several elements: ER-2, G-3, DC-8, Ikhana (Predator B) & Global Hawk and Reveal. These are reviewed in detail in the presentation.

DelFrate, John↗
NASA NTRS2010

Suborbital Science Program

Program Objectives: 1) Satellite Calibration and Validation: Provide methods to perform the cal/val requirements for Earth Observing System satellites. 2) New Sensor Development: Provide methods to reduce risk for new sensor concepts and algorithm development prior to committing sensors to operations. 3) Process Studies: Facilitate the acquisition of high spatial/temporal resolution focused measurements that are required to understand small atmospheric and surface structures which generate powerful Earth system effects. 4) Airborne Networking: Develop disruption-tolerant networking to enable integrated multiple scale measurements of critical environmental features. Dryden Capabilities include: a) Aeronautics history of aircraft developments and milestones. b) Extensive history and experience in instrument integration. c) Extensive history and experience in aircraft modifications. d) Strong background in international deployments. e) Long history of reliable and dependable execution of projects. f) Varied aircraft types providing different capabilities, performance and duration.

Vachon, Jacques↗
NASA NTRS1994

Interactive visualization of Earth and Space Science computations

Computers have become essential tools for scientists simulating and observing nature. Simulations are formulated as mathematical models but are implemented as computer algorithms to simulate complex events. Observations are also analyzed and understood in terms of mathematical models, but the number of these observations usually dictates that we automate analyses with computer algorithms. In spite of their essential role, computers are also barriers to scientific understanding. Unlike hand calculations, automated computations are invisible and, because of the enormous numbers of individual operations in automated computations, the relation between an algorithm's input and output is often not intuitive. This problem is illustrated by the behavior of meteorologists responsible for forecasting weather. Even in this age of computers, many meteorologists manually plot weather observations on maps, then draw isolines of temperature, pressure, and other fields by hand (special pads of maps are printed for just this purpose). Similarly, radiologists use computers to collect medical data but are notoriously reluctant to apply image-processing algorithms to that data. To these scientists with life-and-death responsibilities, computer algorithms are black boxes that increase rather than reduce risk. The barrier between scientists and their computations can be bridged by techniques that make the internal workings of algorithms visible and that allow scientists to experiment with their computations. Here we describe two interactive systems developed at the University of Wisconsin-Madison Space Science and Engineering Center (SSEC) that provide these capabilities to Earth and space scientists.

Hibbard, William L.↗
NASA NTRS1992

An expert system for diagnosing environmentally induced spacecraft anomalies

A new rule-based, machine independent analytical tool was designed for diagnosing spacecraft anomalies using an expert system. Expert systems provide an effective method for saving knowledge, allow computers to sift through large amounts of data pinpointing significant parts, and most importantly, use heuristics in addition to algorithms, which allow approximate reasoning and inference and the ability to attack problems not rigidly defined. The knowledge base consists of over two-hundred (200) rules and provides links to historical and environmental databases. The environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose. The system's driver translates forward chaining rules into a backward chaining sequence, prompting the user for information pertinent to the causes considered. The use of heuristics frees the user from searching through large amounts of irrelevant information and allows the user to input partial information (varying degrees of confidence in an answer) or 'unknown' to any question. The modularity of the expert system allows for easy updates and modifications. It not only provides scientists with needed risk analysis and confidence not found in algorithmic programs, but is also an effective learning tool, and the window implementation makes it very easy to use. The system currently runs on a Micro VAX II at Goddard Space Flight Center (GSFC). The inference engine used is NASA's C Language Integrated Production System (CLIPS).

Rolincik, Mark↗
NASA NTRSDate not supplied

OASSIS: Onboard Adaptive Safe-site Identification System Y3

The OASSIS Year 3 project continues to innovate with three goals: 1) transition to a generic configuration compatible with GNC flight software, 2) implement a new, computationally-efficient TRN algorithm for lunar landing, and 3) integrate with the a HWIL testbed to validate lunar landing GNC systems. This project enables lunar lander GNC flight software to be tested dynamically without the need of a costly flight campaign and without the risk of catastrophic hardware loss. Additionally, the TRN algorithm development and testing enhances the state-of-the-art in pinpoint landing navigation, ultimately improving the overall landing accuracy, safety, and reliability of a crewed lunar landing mission.

James S Mccabe↗
NASA NTRS2023

IMPACTing Medical System Design with a Risk Analysis Tool [“IMPACT” sur la Conception du Système Médical avec un Outil d'Analyse des Risques]

Background: Following the success of Artemis I, NASA is preparing for human extended duration missions. Ongoing efforts are focused on mitigating mission-related risks, including those affecting crew health and performance. Communication latency, logistics of resupply and time frame of medical evacuation are barriers to provision of healthcare for these missions, especially with respect to constraints in mass, volume, and crew training. An in-depth assessment of medical risks, capabilities and resources for a specific mission design is necessary to determine an optimal balance that maximizes likelihood of mission success. Overview: IMPACT (Informed Mission Planning via Analysis of Complex Tradespaces) is a dynamic tool designed to estimate medical risk and outcomes for a specific mission design. In its current iteration, a list of medical conditions selected based on likelihood of occurrence and/or consequence was linked to a set of clinical capabilities and resources necessary for diagnosis and management. A probabilistic risk analysis tool was then used to identify and estimate the likelihood and consequence of risks through the following outcome metrics: loss of crew life (inflight mortality due to medical conditions), need for medical evacuation (return to definitive care), and crew disability (task time affected based on how medical conditions influence the ability to perform specific exploration mission crew tasks). Finally, the model’s optimization algorithm provides recommendations for medical capabilities that maximize risk mitigation relative to mass and volume constraints. In the Spring of 2023, IMPACT was utilized to estimate outcome metrics for a design reference mission that would be representative of an extended duration Artemis mission. Notional data generated were then used to determine a recommended set of medical capabilities and resources relative to user-defined mass and volume constraints. A multidisciplinary team has also been updating IMPACT to strengthen the model’s fidelity. Figure 1 shows how updates to outcome metric inputs for the conditions resulted in different capability and resource allocation recommendations. Discussion: This presentation will discuss the IMPACT tool and share the latest data generated for a representative extended duration Artemis mission. Efforts to improve the fidelity of data generated by the model’s algorithm will also be discussed.

K A Shair↗
NASA NTRSDate not supplied

IMPACTing Medical System Design with a Risk Analysis Tool

Background: Following the success of Artemis I, NASA is preparing for human extended duration missions. Ongoing efforts are focused on mitigating mission-related risks, including those affecting crew health and performance. Communication latency, logistics of resupply and time frame of medical evacuation are barriers to provision of healthcare for these missions, especially with respect to constraints in mass, volume, and crew training. An in-depth assessment of medical risks, capabilities and resources for a specific mission design is necessary to determine an optimal balance that maximizes likelihood of mission success. Overview: IMPACT (Informed Mission Planning via Analysis of Complex Tradespaces) is a dynamic tool designed to estimate medical risk and outcomes for a specific mission design. In its current iteration, a list of medical conditions selected based on likelihood of occurrence and/or consequence was linked to a set of clinical capabilities and resources necessary for diagnosis and management. A probabilistic risk analysis tool was then used to identify and estimate the likelihood and consequence of risks through the following outcome metrics: loss of crew life (inflight mortality due to medical conditions), need for medical evacuation (return to definitive care), and crew disability (task time affected based on how medical conditions influence the ability to perform specific exploration mission crew tasks). Finally, the model’s optimization algorithm provides recommendations for medical capabilities that maximize risk mitigation relative to mass and volume constraints. In the Spring of 2023, IMPACT was utilized to estimate outcome metrics for a design reference mission that would be representative of an extended duration Artemis mission. Notional data generated were then used to determine a recommended set of medical capabilities and resources relative to user-defined mass and volume constraints. A multidisciplinary team has also been updating IMPACT to strengthen the model’s fidelity. Figure 1 shows how updates to outcome metric inputs for the conditions resulted in different capability and resource allocation recommendations. Discussion: This presentation will discuss the IMPACT tool and share the latest data generated for a representative extended duration Artemis mission. Efforts to improve the fidelity of data generated by the model’s algorithm will also be discussed.

K A Shair↗
NASA NTRS2013

Risk-Constrained Dynamic Programming for Optimal Mars Entry, Descent, and Landing

A chance-constrained dynamic programming algorithm was developed that is capable of making optimal sequential decisions within a user-specified risk bound. This work handles stochastic uncertainties over multiple stages in the CEMAT (Combined EDL-Mobility Analyses Tool) framework. It was demonstrated by a simulation of Mars entry, descent, and landing (EDL) using real landscape data obtained from the Mars Reconnaissance Orbiter. Although standard dynamic programming (DP) provides a general framework for optimal sequential decisionmaking under uncertainty, it typically achieves risk aversion by imposing an arbitrary penalty on failure states. Such a penalty-based approach cannot explicitly bound the probability of mission failure. A key idea behind the new approach is called risk allocation, which decomposes a joint chance constraint into a set of individual chance constraints and distributes risk over them. The joint chance constraint was reformulated into a constraint on an expectation over a sum of an indicator function, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the chance-constraint optimization problem can be turned into an unconstrained optimization over a Lagrangian, which can be solved efficiently using a standard DP approach.

Ono, Masahiro↗
NASA NTRS2013

Analytical Algorithms to Quantify the Uncertainty in Remaining Useful Life Prediction

This paper investigates the use of analytical algorithms to quantify the uncertainty in the remaining useful life (RUL) estimate of components used in aerospace applications. The prediction of RUL is affected by several sources of uncertainty and it is important to systematically quantify their combined effect by computing the uncertainty in the RUL prediction in order to aid risk assessment, risk mitigation, and decisionmaking. While sampling-based algorithms have been conventionally used for quantifying the uncertainty in RUL, analytical algorithms are computationally cheaper and sometimes, are better suited for online decision-making. While exact analytical algorithms are available only for certain special cases (for e.g., linear models with Gaussian variables), effective approximations can be made using the the first-order second moment method (FOSM), the first-order reliability method (FORM), and the inverse first-order reliability method (Inverse FORM). These methods can be used not only to calculate the entire probability distribution of RUL but also to obtain probability bounds on RUL. This paper explains these three methods in detail and illustrates them using the state-space model of a lithium-ion battery.

Sankararaman, Shankar↗
NASA NTRS2003

Software for Simulating a Complex Robot

RoboSim (Robot Simulation) is a computer program that simulates the poses and motions of the Robonaut a developmental anthropomorphic robot that has a complex system of joints with 43 degrees of freedom and multiple modes of operation and control. RoboSim performs a full kinematic simulation of all degrees of freedom. It also includes interface components that duplicate the functionality of the real Robonaut interface with control software and human operators. Basically, users see no difference between the real Robonaut and the simulation. Consequently, new control algorithms can be tested by computational simulation, without risk to the Robonaut hardware, and without using excessive Robonaut-hardware experimental time, which is always at a premium. Previously developed software incorporated into RoboSim includes Enigma (for graphical displays), OSCAR (for kinematical computations), and NDDS (for communication between the Robonaut and external software). In addition, RoboSim incorporates unique inverse-kinematical algorithms for chains of joints that have fewer than six degrees of freedom (e.g., finger joints). In comparison with the algorithms of OSCAR, these algorithms are more readily adaptable and provide better results when using equivalent sets of data.

Goza, S. Michael↗