The Early Design Reliability Prediction Method

2012 ◽  
Author(s):  
Bryan M. O’Halloran ◽  
Chris Hoyle ◽  
Robert B. Stone ◽  
Irem Y. Tumer
Keyword(s):  
Failure Rate ◽  
Electrical Power ◽  
Prediction Method ◽  
Reliability Prediction ◽  
Electrical Power System ◽  
Early Design ◽  
Design Reliability ◽  
Design Alternative ◽  
Final Design

The purpose of this paper is to formalize the Early Design Reliability Prediction Method (EDRPM) into a comprehensive framework, then to provide a case study using an Electrical Power System (EPS) which shows the usefulness of the methods. EDRPM has been developed to facilitate decision making in early design using quantitative reliability results [1]. Candidate components and design alternative are eliminated using justification provided by EDRPM. The output of this method is a set of design alternative that have a reliability values at or greater than a preset reliability goal. At the completion of applying EDRPM, additional metrics can be used to determine a final design. This research addresses the need for reliability methods to be moved earlier in the design process. Current methods are applicable after components have been selected. EDRPM is used during functional design, and when concepts are generated. This method also calculates functional failure rates which are applied to generate the function and component distributions. The results of the case study shows that several candidate components and design alternatives can be eliminated using EDRPM. It is demonstrated that only a subset of designs that meet the failure rate piece of the reliability goal should not be eliminated. The reliability goal is the combination of two parts; the failure rate and the probability of not exceeding the failure rate. Several of these design still have a probability of exceeding the second piece of the reliability goal given that they meet the first.

The early design reliability prediction method

2019 ◽  
Vol 30 (4) ◽  
pp. 489-508
Author(s):  
Bryan M. O’Halloran ◽  
Christopher Hoyle ◽  
Irem Y. Tumer ◽  
Robert B. Stone
Keyword(s):  
Prediction Method ◽  
Reliability Prediction ◽  
Early Design ◽  
Design Reliability

scholarly journals Solar Module Integrated Converters as Power Generator in Small Spacecrafts: Design and Verification Approach

Aerospace ◽  
2019 ◽  
Vol 6 (5) ◽  
pp. 61 ◽  
Author(s):  
Jesus Gonzalez-Llorente ◽  
Aleksander A. Lidtke ◽  
Ken Hatanaka ◽  
Ryo Kawauchi ◽  
Kei-Ichi Okuyama
Keyword(s):  
Failure Rate ◽  
Rapid Development ◽  
Electrical Power ◽  
Solar Array ◽  
Electrical Power System ◽  
Solar Module ◽  
Small Satellites ◽  
Frequent Failure ◽  
Verification Process ◽  
The Cost

As small satellites are becoming more widespread for new businesses and applications, the development time, failure rate and cost of the spacecraft must be reduced. One of the systems with the highest cost and the most frequent failure in the satellite is the Electrical Power System (EPS). One approach to achieve rapid development times while reducing the cost and failure rate is using scalable modules. We propose a solar module integrated converter (SMIC) and its verification process as a key component for power generation in EPS. SMIC integrates the solar array, its regulators and the telemetry acquisition unit. This paper details the design and verification process of the SMIC and presents the in-orbit results of 12 SMICs used in Ten-Koh satellite, which was developed in less than 1.5 years. The in-orbit data received since the launch reveal that solar module withstands not only the launching environment of H-IIA rocket but also more than 1500 orbits in LEO. The modular approach allowed the design, implementation and qualification of only one module, followed by manufacturing and integration of 12 subsequent flight units. The approach with the solar module can be followed in other components of the EPS such as battery and power regulators.

An Intelligent Hybrid Model for Bus Load Forecasting in Electrical Short-Term Operation Tasks

2012 ◽  
pp. 540-562
Author(s):  
Ricardo Menezes Salgado ◽  
Takaaki Ohishi ◽  
Rosangela Ballini
Keyword(s):  
Power System ◽  
Hybrid Model ◽  
Electrical Power ◽  
Load Forecasting ◽  
Electrical Power System ◽  
Term Operation ◽  
Operating Load ◽  
Conventional Models ◽  
Safe Operating

The main objective of this chapter is to present a hybrid model for bus load forecasting. This approach represents an essential tool for the operation of the electrical power system and the hybrid model combines a bus clustering process and a load forecasting model. As a case study, the model was applied to the real Brazilian electrical system, and the results revealed a performance similar to that of conventional models for bus load forecasting, but about 14 times faster. The results are compatible with the safe operating load levels for the Brazilian electrical power system and have proved to be adequate for use in real operation tasks.

scholarly journals Comparasion of Different Configuration of Hybrid Electrical Power System – A Case Study of a Site in Peshawar

2020 ◽  
Vol 7 (08) ◽  
pp. 268-273
Author(s):  
Raheemullah Khan ◽  
◽  
Jehan Parvez ◽  
Abdur Rehman ◽  
Muhammad Ibrahim ◽  
...  
Keyword(s):  
Power System ◽  
Electrical Power ◽  
Electrical Power System ◽  
System A ◽  
A Site

scholarly journals Probabilistic Model-Based Diagnosis: An Electrical Power System Case Study

2010 ◽  
Vol 40 (5) ◽  
pp. 874-885 ◽  
Author(s):  
Ole J. Mengshoel ◽  
Mark Chavira ◽  
Keith Cascio ◽  
Scott Poll ◽  
Adnan Darwiche ◽  
...  
Keyword(s):  
Power System ◽  
Probabilistic Model ◽  
Electrical Power ◽  
Electrical Power System ◽  
Model Based

scholarly journals Resiliency analysis for complex engineered system design

2015 ◽  
Vol 29 (1) ◽  
pp. 93-108 ◽  
Author(s):  
Hoda Mehrpouyan ◽  
Brandon Haley ◽  
Andy Dong ◽  
Irem Y. Tumer ◽  
Christopher Hoyle
Keyword(s):  
Electrical Power ◽  
Nonlinear Dynamical System ◽  
Operating Environment ◽  
Electrical Power System ◽  
Nonlinear Dynamical ◽  
Complex Engineered Systems ◽  
Failure Propagation ◽  
Engineered Systems ◽  
Mean Time

AbstractResilience is a key driver in the design of systems that must operate in an uncertain operating environment, and it is a key metric to assess the capacity for systems to perform within the specified performance envelop despite disturbances to their operating environment. This paper describes a graph spectral approach to calculate the resilience of complex engineered systems. The resilience of the design architecture of complex engineered systems is deduced from graph spectra. This is calculated from adjacency matrix representations of the physical connections between components in complex engineered systems. Furthermore, we propose a new method to identify the most vulnerable components in the design and design architectures that are robust to transmission of failures. Nonlinear dynamical system and epidemic spreading models are used to compare the failure propagation mean time transformation. Using these metrics, we present a case study based on the Advanced Diagnostics and Prognostics Testbed, which is an electrical power system developed at NASA Ames as a subsystem for the ramp system of an infantry fighting vehicle.

Research on Reliability of Equipments Based on Interval Prediction Method

2013 ◽  
Vol 330 ◽  
pp. 279-281
Author(s):  
Jian Fang Liu ◽  
Jian Hua Yang
Keyword(s):  
System Theory ◽  
Prediction Method ◽  
Grey System Theory ◽  
Reliability Prediction ◽  
Grey System ◽  
Design Decisions ◽  
Remarkable Effect ◽  
Interval Prediction ◽  
Design Reliability ◽  
Method Of Design

While reliability is an important aspect of equipment quality, it has a remarkable effect on the usability of equipments. Reliability can reflect equipments' ability of keeping performance. As a method of design, reliability prediction is the fundamental of design decisions. In this paper, the grey system theory is used to deal with the data of reliability, and the method of interval prediction to predicate the reliability of equipments and analyze how to improve its reliability.

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