Search NASA⌕ Search

SEARCH · Search NASA

Results for “Redundancy”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Fault tolerant kinematic control of hyper-redundant manipulators

Hyper-redundant spatial manipulators possess fault-tolerant features because of their redundant structure. The kinematic control of these manipulators is investigated with special emphasis on fault-tolerant control. The manipulator tasks are viewed in the end-effector space while actuator commands are in joint-space, requiring an inverse kinematic algorithm to generate joint-angle commands from the end-effector ones. The rate-inverse kinematic control algorithm presented in this paper utilizes the pseudoinverse to accommodate for joint motor failures. An optimal scale factor for the robust inverse is derived.

Bedrossian, Nazareth S.↗
NASA NTRS1994

Failure tolerant operation of kinematically redundant manipulators

Redundant manipulators may compensate for failed joints with their additional degrees of freedom. In this paper such a manipulator is considered fault tolerant if it can guarantee completion of a task after any one of its joints has failed. This fault tolerance of kinematically redundant manipulators is insured here. Methods to analyze the manipulator's work space find regions inherently suitable for critical tasks because of their high level of failure tolerance. Constraints are then placed on the manipulator's range of motion to guarantee completion of a task.

Lewis, Christopher L.↗
NASA NTRS1995

Direct Adaptive Impedance Control Of Redundant Manipulators

Method of controlling mechanical impedance of end effector of robotic manipulator related to method described in "Adaptive Impedance Control of Redundant Manipulators" (NPO-18606). Present method does not require detailed knowledge and computation of dynamics and inverse kinematic transformation of manipulator. Provides for control globally stable in presence of bounded disturbances. Applicable to both nonredundant and redundant manipulators performing tasks involving impacts between manipulator and objects in its environment, and controlled contact between end effector and object, such as deburring.

Seraji, Homayoun↗
NASA NTRS1995

Software For Analysis Of Reliability, Redundancy, And Cost

CARRAC is software tool for combined analysis of reliability, redundancy, and cost of alternative choices of subsystem that is part of larger system. Uses various parameters entered from computer keyboard to determine subsystem and redundancy method (if any) that minimizes cost. Also, calculation selected from five different mathematical models that enable application of CARRAC to wide variety of cases. Uses parameters to calculate and compare total expected cost for alternatives of a chosen subsystem. Written in Microsoft Quick-Basic v4.5.

Patterson, R. L.↗
NASA NTRS1996

Site Partitioning for Redundant Arrays of Distributed Disks

Redundant arrays of distributed disks (RADD) can be used in a distributed computing system or database system to provide recovery in the presence of disk crashes and temporary and permanent failures of single sites. In this paper, we look at the problem of partitioning the sites of a distributed storage system into redundant arrays in such a way that the communication costs for maintaining the parity information are minimized. We show that the partitioning problem is NP-hard. We then propose and evaluate several heuristic algorithms for finding approximate solutions. Simulation results show that significant reduction in remote parity update costs can be achieved by optimizing the site partitioning scheme.

Mourad, Antoine N.↗
NASA NTRS1997

A Comprehensive Reliability Methodology for Assessing Risk of Reusing Failed Hardware Without Corrective Actions with and Without Redundancy

This paper deals with the development of a reliability methodology to assess the consequences of using hardware, without failure analysis or corrective action, that has previously demonstrated that it did not perform per specification. The subject of this paper arose from the need to provide a detailed probabilistic analysis to calculate the change in probability of failures with respect to the base or non-failed hardware. The methodology used for the analysis is primarily based on principles of Monte Carlo simulation. The random variables in the analysis are: Maximum Time of Operation (MTO) and operation Time of each Unit (OTU) The failure of a unit is considered to happen if (OTU) is less than MTO for the Normal Operational Period (NOP) in which this unit is used. NOP as a whole uses a total of 4 units. Two cases are considered. in the first specialized scenario, the failure of any operation or system failure is considered to happen if any of the units used during the NOP fail. in the second specialized scenario, the failure of any operation or system failure is considered to happen only if any two of the units used during the MOP fail together. The probability of failure of the units and the system as a whole is determined for 3 kinds of systems - Perfect System, Imperfect System 1 and Imperfect System 2. in a Perfect System, the operation time of the failed unit is the same as that of the MTO. In an Imperfect System 1, the operation time of the failed unit is assumed as 1 percent of the MTO. In an Imperfect System 2, the operation time of the failed unit is assumed as zero. in addition, simulated operation time of failed units is assumed as 10 percent of the corresponding units before zero value. Monte Carlo simulation analysis is used for this study. Necessary software has been developed as part of this study to perform the reliability calculations. The results of the analysis showed that the predicted change in failure probability (P(sub F)) for the previously failed units is as high as 49 percent above the baseline (perfect system) for the worst case. The predicted change in system P(sub F) for the previously failed units is as high as 36% for single unit failure without any redundancy. For redundant systems, with dual unit failure, the predicted change in P(sub F) for the previously failed units is as high as 16%. These results will help management to make decisions regarding the consequences of using previously failed units without adequate failure analysis or corrective action.

Putcha, Chandra S.↗
NASA NTRS2002

Restoring Redundancy to the MAP Propulsion System

The Microwave Anisotropy Probe (MAP) is a follow-on to the Differential Microwave Radiometer (DMR) instrument on the Cosmic Background Explorer (COBE). Due to the MAP project's limited mass, power, and financial resources, a traditional reliability concept including fully redundant components was not feasible. The MAP design employs selective hardware redundancy, along with backup software modes and algorithms, to improve the odds of mission success. In particular, MAP's propulsion system, which is used for orbit maneuvers and momentum management, uses eight thrusters positioned and oriented in such a way that its thruster-based attitude control modes can maintain three-axis attitude control in the event of the failure of any one thruster.

O'Donnell, James R., Jr.↗
NASA NTRS1988

Equalization in redundant channels

A miscomparison between a channel's configuration data base and a voted system configuration data base in a redundant channel system having identically operating, frame synchronous channels triggers autoequalization of the channel's historical signal data bases in a hierarchical, chronological manner with that of a correctly operating channel. After equalization, symmetrization of the channel's configuration data base with that of the system permits upgrading of the previously degraded channel to full redundancy. An externally provided equalization command, e.g., manually actuated, can also trigger equalization.

Tulpule, Bhalchandra R.↗
NASA NTRS2008

Factors which Limit the Value of Additional Redundancy in Human Rated Launch Vehicle Systems

The National Aeronautics and Space Administration (NASA) has embarked on an ambitious program to return humans to the moon and beyond. As NASA moves forward in the development and design of new launch vehicles for future space exploration, it must fully consider the implications that rule-based requirements of redundancy or fault tolerance have on system reliability/risk. These considerations include common cause failure, increased system complexity, combined serial and parallel configurations, and the impact of design features implemented to control premature activation. These factors and others must be considered in trade studies to support design decisions that balance safety, reliability, performance and system complexity to achieve a relatively simple, operable system that provides the safest and most reliable system within the specified performance requirements. This paper describes conditions under which additional functional redundancy can impede improved system reliability. Examples from current NASA programs including the Ares I Upper Stage will be shown.

Anderson, Joel M.↗
NASA NTRS2004

Using Redundancy To Reduce Errors in Magnetometer Readings

A method of reducing errors in noisy magnetic-field measurements involves exploitation of redundancy in the readings of multiple magnetometers in a cluster. By "redundancy"is meant that the readings are not entirely independent of each other because the relationships among the magnetic-field components that one seeks to measure are governed by the fundamental laws of electromagnetism as expressed by Maxwell's equations. Assuming that the magnetometers are located outside a magnetic material, that the magnetic field is steady or quasi-steady, and that there are no electric currents flowing in or near the magnetometers, the applicable Maxwell 's equations are delta x B = 0 and delta(raised dot) B = 0, where B is the magnetic-flux-density vector. By suitable algebraic manipulation, these equations can be shown to impose three independent constraints on the values of the components of B at the various magnetometer positions. In general, the problem of reducing the errors in noisy measurements is one of finding a set of corrected values that minimize an error function. In the present method, the error function is formulated as (1) the sum of squares of the differences between the corrected and noisy measurement values plus (2) a sum of three terms, each comprising the product of a Lagrange multiplier and one of the three constraints. The partial derivatives of the error function with respect to the corrected magnetic-field component values and the Lagrange multipliers are set equal to zero, leading to a set of equations that can be put into matrix.vector form. The matrix can be inverted to solve for a vector that comprises the corrected magnetic-field component values and the Lagrange multipliers.

Kulikov, Igor↗
NASA NTRS2013

Investigating Actuation Force Fight with Asynchronous and Synchronous Redundancy Management Techniques

Within distributed fault-tolerant systems the term force-fight is colloquially used to describe the level of command disagreement present at redundant actuation interfaces. This report details an investigation of force-fight using three distributed system case-study architectures. Each case study architecture is abstracted and formally modeled using the Symbolic Analysis Laboratory (SAL) tool chain from the Stanford Research Institute (SRI). We use the formal SAL models to produce k-induction based proofs of a bounded actuation agreement property. We also present a mathematically derived bound of redundant actuation agreement for sine-wave stimulus. The report documents our experiences and lessons learned developing the formal models and the associated proofs.

Hall, Brendan↗
NASA NTRSDate not supplied

SysML Success Tree for DAVINCI In-Situ Campaign Requirements Validation and Redundancy Assessment

The DAVINCI mission will scientifically study the Venusian atmosphere to better understand the current state of the planet and its evolutionary history. This will be accomplished by deploying a descent probe to collect in-situ atmospheric dynamic and spectroscopic measurements, characterize ambient temperatures and pressures during descent, and surface imaging below the cloud layer. To better characterize the DAVINCI In-Situ Campaign, a success tree, developed in the SysML tool, MagicDraw, was created to define the events necessary to have a successful in-situ campaign, for each phase of the campaign. This success tree was also used to validate DAVINCI Program, Mission, and Element level requirements. In addition, because DAVINCI is a single-string mission, the success tree was also used to identify areas of redundancy and resiliency throughout the campaign. The initial redundancy assessment recommended further on-orbit evaluation of the probe’s communication system, as well as further evaluation of the ability of the mass spectrometer turbo-molecular pump to handle the expected decent environment. During the integration and test phase of the overall mission, the success tree will be used to guide the mission validation process, helping to ensure that the in-situ mission elements can perform in accordance with the DAVINCI In-Situ Concept of Operations document.

model-based↗
NASA NTRSDate not supplied

SysML Success Tree for DAVINCI In-Situ Campaign Requirements Validation and Redundancy Assessment

The DAVINCI mission will scientifically study the Venusian atmosphere to better understand the current state of the planet and its evolutionary history. This will be accomplished by deploying a descent probe to collect in-situ atmospheric dynamic and spectroscopic measurements, characterize ambient temperatures and pressures during descent, and surface imaging below the cloud layer. To better characterize the DAVINCI In-Situ Campaign, a success tree, developed in the SysML tool, MagicDraw, was created to define the events necessary to have a successful in-situ campaign, for each phase of the campaign. This success tree was also used to validate DAVINCI Program, Mission, and Element level requirements. In addition, because DAVINCI is a single-string mission, the success tree was also used to identify areas of redundancy and resiliency throughout the campaign. The initial redundancy assessment recommended further on-orbit evaluation of the probe’s communication system, as well as further evaluation of the ability of the mass spectrometer turbo-molecular pump to handle the expected decent environment. During the integration and test phase of the overall mission, the success tree will be used to guide the mission validation process, helping to ensure that the in-situ mission elements can perform in accordance with the DAVINCI In-Situ Concept of Operations document.

ConOps↗
NASA NTRSDate not supplied

SysML Success Tree for DAVINCI In-Situ Campaign Requirements Validation and Redundancy Assessment

The DAVINCI mission will scientifically study the Venusian atmosphere to better understand the current state of the planet and its evolutionary history. This will be accomplished by deploying a descent probe to collect in-situ atmospheric dynamic and spectroscopic measurements, characterize ambient temperatures and pressures during descent, and surface imaging below the cloud layer. To better characterize the DAVINCI In-Situ Campaign, a success tree, developed in the SysML tool, MagicDraw, was created to define the events necessary to have a successful in-situ campaign, for each phase of the campaign. This success tree was also used to validate DAVINCI Program, Mission, and Element level requirements. In addition, because DAVINCI is a single-string mission, the success tree was also used to identify areas of redundancy and resiliency throughout the campaign. The initial redundancy assessment recommended further on-orbit evaluation of the probe’s communication system, as well as further evaluation of the ability of the mass spectrometer turbo-molecular pump to handle the expected decent environment. During the integration and test phase of the overall mission, the success tree will be used to guide the mission validation process, helping to ensure that the in-situ mission elements can perform in accordance with the DAVINCI In-Situ Concept of Operations document.

model-based↗