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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Developing Ultra Reliable Life Support for the Moon and Mars

Recycling life support systems can achieve ultra reliability by using spares to replace failed components. The added mass for spares is approximately equal to the original system mass, provided the original system reliability is not very low. Acceptable reliability can be achieved for the space shuttle and space station by preventive maintenance and by replacing failed units, However, this maintenance and repair depends on a logistics supply chain that provides the needed spares. The Mars mission must take all the needed spares at launch. The Mars mission also must achieve ultra reliability, a very low failure rate per hour, since it requires years rather than weeks and cannot be cut short if a failure occurs. Also, the Mars mission has a much higher mass launch cost per kilogram than shuttle or station. Achieving ultra reliable space life support with acceptable mass will require a well-planned and extensive development effort. Analysis must define the reliability requirement and allocate it to subsystems and components. Technologies, components, and materials must be designed and selected for high reliability. Extensive testing is needed to ascertain very low failure rates. Systems design should segregate the failure causes in the smallest, most easily replaceable parts. The systems must be designed, produced, integrated, and tested without impairing system reliability. Maintenance and failed unit replacement should not introduce any additional probability of failure. The overall system must be tested sufficiently to identify any design errors. A program to develop ultra reliable space life support systems with acceptable mass must start soon if it is to produce timely results for the moon and Mars.

Jones, Harry W.↗
DOE OSTI2022

Test Results for Checking Reliability of Selected ENDF/B-VIII.0 Evaluated Uncertainties

This report summarizes error messages obtained from counter-checking whether 1 H, 9 Be, 12 C, 27 Al, 235,238 U and 238–242 Pu relative uncertainties of ENDF/B-VIII.0 are realistic. Large parts of this report were generated automatically by the code CovVal. This code allows to test the reliability of relative uncertainties of any isotope. It gives generic error and warning messages if evaluated relative uncertainties of a particular reaction are likely under- or over-estimated. In addition to these error and warning messages, I added comments whether the flagged uncertainties are truly under- or overestimated. I call out these uncertainties that should be further investigated and corrected by an evaluator for an upcoming release of ENDF/B-VIII.1.

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS1976

Reliability analysis of structures under periodic proof tests in service

A reliability analysis of structures subjected to random service loads and periodic proof tests treats gust loads and maneuver loads as random processes. Crack initiation, crack propagation, and strength degradation are treated as the fatigue process. The time to fatigue crack initiation and ultimate strength are random variables. Residual strength decreases during crack propagation, so that failure rate increases with time. When a structure fails under periodic proof testing, a new structure is built and proof-tested. The probability of structural failure in service is derived from treatment of all the random variables, strength degradations, service loads, proof tests, and the renewal of failed structures. Some numerical examples are worked out.

Yang, J.-N.↗
NASA NTRS1975

Assessment of NDE reliability data

Twenty sets of relevant nondestructive test (NDT) reliability data were identified, collected, compiled, and categorized. A criterion for the selection of data for statistical analysis considerations was formulated, and a model to grade the quality and validity of the data sets was developed. Data input formats, which record the pertinent parameters of the defect/specimen and inspection procedures, were formulated for each NDE method. A comprehensive computer program was written and debugged to calculate the probability of flaw detection at several confidence limits by the binomial distribution. This program also selects the desired data sets for pooling and tests the statistical pooling criteria before calculating the composite detection reliability. An example of the calculated reliability of crack detection in bolt holes by an automatic eddy current method is presented.

Yee, B. G. W.↗
NASA NTRS1991

Reliability growth models for NASA applications

The objective of any reliability growth study is prediction of reliability at some future instant. Another objective is statistical inference, estimation of reliability for reliability demonstration. A cause of concern for the development engineer and management is that reliability demands an excessive number of tests for reliability demonstration. For example, the Space Transportation Main Engine (STME) program requirements call for .99 reliability at 90 pct. confidence for demonstration. This requires running 230 tests with zero failure if a classical binomial model is used. It is therefore also an objective to explore the reliability growth models for reliability demonstration and tracking and their applicability to NASA programs. A reliability growth model is an analytical tool used to monitor the reliability progress during the development program and to establish a test plan to demonstrate an acceptable system reliability.

Taneja, Vidya S.↗
NASA NTRSDate not supplied

Design for Reliability (DfR) in Space Life Support

The engineering process of Design for Reliability (DfR) is well established in the automotive and aerospace industries. DfR should be useful in the future development of space life support systems. DfR is a sequence of tasks that develop system requirements and plan reliability analysis and testing. First and fundamentally, the reliability requirement is defined. Next the system reliability model is developed, often using a reliability block diagram. The overall system reliability requirement is allocated to the subsystems and an estimate of the attainable reliability is made. This expected reliability can be improved by simplifying the design by removing components or by replacing less reliable components. Improving reliability can require difficult compromises, such as reducing performance requirements, increasing budget, or extending testing. The actual system reliability can be determined only by testing, which should continue long enough to provide the required confidence in the measured value. New systems often have unexpected design errors that cause failures in early testing. The usual reliability improvement process of testing, finding the failure modes, and redesigning to remove them reduces the failure rate and is referred to as “reliability growth.” After redesign has been completed, the system should be further tested to determine the actual achieved reliability more accurately. If the final system failure rate is too high, redundant systems can be used to improve overall operational reliability. Adding redundancy simply to increase the one- or two-fault tolerance metric may sometimes reduce reliability. Reliability can be improved in three ways: redesigning the system to include more reliable subsystems and components, reliability growth testing and failure mode removal, and by using parallel redundant systems. DfR should combine these approaches to achieve the required reliability while managing performance, cost, and schedule.

Reliability↗
NASA NTRSDate not supplied

Design for Reliability (DfR) in Space Life Support

The engineering process of Design for Reliability (DfR) is well established in the automotive and aerospace industries. DfR should be useful in the future development of space life support systems. DfR is a sequence of tasks that develop system requirements and plan reliability analysis and testing. First and fundamentally, the reliability requirement is defined. Next the system reliability model is developed, often using a reliability block diagram. The overall system reliability requirement is allocated to the subsystems and an estimate of the attainable reliability is made. This expected reliability can be improved by simplifying the design by removing components or by replacing less reliable components. Improving reliability can require difficult compromises, such as reducing performance requirements, increasing budget, or extending testing. The actual system reliability can be determined only by testing, which should continue long enough to provide the required confidence in the measured value. New systems often have unexpected design errors that cause failures in early testing. The usual reliability improvement process of testing, finding the failure modes, and redesigning to remove them reduces the failure rate and is referred to as “reliability growth.” After redesign has been completed, the system should be further tested to determine the actual achieved reliability more accurately. If the final system failure rate is too high, redundant systems can be used to improve overall operational reliability. Adding redundancy simply to increase the one- or two-fault tolerance metric may sometimes reduce reliability. Reliability can be improved in three ways: redesigning the system to include more reliable subsystems and components, reliability growth testing and failure mode removal, and by using parallel redundant systems. DfR should combine these approaches to achieve the required reliability while managing performance, cost, and schedule.

Reliability↗
NASA NTRS2014

Validity and Reliability of Dynamic Visual Acuity (DVA) Measurement During Walking

DVA is primarily subserved by the vestibulo‐ocular reflex mechanism. Individuals with vestibular hypofunction commonly experience highly debilitating illusory movement or blurring of visual images during daily activities possibly, due to impaired DVA. Even without pathologies, gradual age‐related morphological deterioration is evident in all components of the vestibular system. We examined the construct validity to detect age‐related differences and test‐retest reliability of DVA measurements performed during walking. METHODS: Healthy adults were recruited into 3 groups: 1. young (20‐39years, n=18), 2. middle‐aged (40‐59years, n=14), and 3. older adults (60‐80years, n=15). Randomly selected seven participants from each group (n=21) participated in retesting. Participants were excluded if they had a history of vestibular or neuromuscular pathologies, dizziness/vertigo or >1 falls in the past year. Older persons with MMSE scores <29/30 were excluded to minimize cognitive errors. Participants' age, height, weight and normal walking speed were recorded. The binocular DVA was measured while walking on a treadmill at 0.8 m/s, 1.0 m/s and 1.2 m/s speeds. The walking speeds chosen represent a range of slow to moderate walking speeds for adult life span in participants who have no current mobility problems. The monitor that displayed Landolt 'C' optotypes was placed at 50 cm from the eyes for nearDVA (primary compensation by otolith organs) and at 3.0 m for farDVA (primary compensation by semicircular canals). A mixed factor ANOVA (age group x speed) was performed separately for the Near and FarDVA for detecting group differences. Intraclass correlation coefficients (ICCs) were calculated for each condition to determine test‐retest reliability. RESULTS: The three age groups were not different in their height, weight and normal walking speed (p>0.05). The post hoc analyses for DVA measurements demonstrated that each group was significantly different from the other two groups for Near as well as FarDVA (p<0.001‐p=0.031). The effect of speed was significant for both NearDVA (p=0.012) and FarDVA (p=0.014), however, there was no age group x speed interaction (FarDVA p=0.607, NearDVA p=0.343). The ICCs for Near and FarDVA ranged between 0.85‐ 0.88 and 0.71‐0.87, respectively. CONCLUSIONS: Differences in DVA between the three age groups were detected by using both Near and FarDVA protocols irrespective of the walking speed. Therefore, age group‐specific reference values should be used for detecting malfunction. Further, consistency in walking speed is critical for comparing between studies. NearDVA at all walking speeds and FarDVA at the speed of 1.2 m/s demonstrated excellent testretest reliability. FarDVA at 0.8 m/s and 1.0 m/s demonstrated good test‐retest reliability (ICCs 0.71 and 0.77, respectively).

Deshpande, Nandini↗
NASA NTRS1982

Photovoltaic module reliability improvement through application testing and failure analysis

During the first four years of the U.S. Department of Energy (DOE) National Photovoltatic Program, the Jet Propulsion Laboratory Low-Cost Solar Array (LSA) Project purchased about 400 kW of photovoltaic modules for test and experiments. In order to identify, report, and analyze test and operational problems with the Block Procurement modules, a problem/failure reporting and analysis system was implemented by the LSA Project with the main purpose of providing manufacturers with feedback from test and field experience needed for the improvement of product performance and reliability. A description of the more significant types of failures is presented, taking into account interconnects, cracked cells, dielectric breakdown, delamination, and corrosion. Current design practices and reliability evaluations are also discussed. The conducted evaluation indicates that current module designs incorporate damage-resistant and fault-tolerant features which address field failure mechanisms observed to date.

Dumas, L. N.↗
NASA NTRS1971

Table for estimating parameters of Weibull distribution

Table yields best linear invariant /BLI/ estimates for log of reliable life under censored life tests, permitting reliability estimations in failure analysis of items with multiple flaws. These BLI estimates have uniformly smaller expected loss than Gauss-Markov best linear unbiased estimates.

Mann, N. R.↗
NASA NTRS2010

Ultra Reliable Closed Loop Life Support for Long Space Missions

Spacecraft human life support systems can achieve ultra reliability by providing sufficient spares to replace all failed components. The additional mass of spares for ultra reliability is approximately equal to the original system mass, provided that the original system reliability is not too low. Acceptable reliability can be achieved for the Space Shuttle and Space Station by preventive maintenance and by replacing failed units. However, on-demand maintenance and repair requires a logistics supply chain in place to provide the needed spares. In contrast, a Mars or other long space mission must take along all the needed spares, since resupply is not possible. Long missions must achieve ultra reliability, a very low failure rate per hour, since they will take years rather than weeks and cannot be cut short if a failure occurs. Also, distant missions have a much higher mass launch cost per kilogram than near-Earth missions. Achieving ultra reliable spacecraft life support systems with acceptable mass will require a well-planned and extensive development effort. Analysis must determine the reliability requirement and allocate it to subsystems and components. Ultra reliability requires reducing the intrinsic failure causes, providing spares to replace failed components and having "graceful" failure modes. Technologies, components, and materials must be selected and designed for high reliability. Long duration testing is needed to confirm very low failure rates. Systems design should segregate the failure causes in the smallest, most easily replaceable parts. The system must be designed, developed, integrated, and tested with system reliability in mind. Maintenance and reparability of failed units must not add to the probability of failure. The overall system must be tested sufficiently to identify any design errors. A program to develop ultra reliable space life support systems with acceptable mass should start soon since it must be a long term effort.

Jones, Harry W.↗