Having scaled the highest peaks of mountains and explored the depths of oceans of the Earth, humans always had an intense curiosity to explore the outer space while gazing through ever powerful telescopes from Galileo's time onwards trying to learn more about the heavenly bodies and their movements. The development of several new technologies finally culminated with the launch of Sputnik 1 by the Soviet Union on October 4, 1957. This was the world's first artificial satellite weighing 83.6 kgs, orbiting the Earth in 98.1 minutes. The launch of Sputnik 1 ushered a new era of political, scientific and technological achievements that became to be known as the Space Age, which led to rapid advances in material science, rocketry, computers and many other areas largely produced by a race between U.S.A and Soviet Union, who tried to smart over each other's achievements. One of the glorious moments of 20th Century and of the space age was the landing of a man on the Moon on Apollo-11 mission, which was watched by nearly 500 million people.

Actually, the origin of space race can be traced to Germany, who beginning in the 1930s and continuing during World War II researched and built operational ballistic missiles. In fact, the Germans were able to experiment with liquid-fuelled rockets capable of reaching high altitudes and long distances. It is generally believed that developments in the USA and USSR can be attributed to this capability developed by Germany during WWII. In 1955, both the United States and the Soviet Union were building ballistic missiles that could be utilized to launch objects into space. Indeed, on 12 April 1961, the USSR launched Yuri Gagarin into orbit around the Earth on Vostok 1. Subsequently, 3 weeks later, on 5 May 1961, Alan Shepard became the first American in space, launched on a suborbital mission Mercury-Redstone 3. The space race including the Moon-race between the USA and USSR continued

Ultimately, the collapse of the USSR and the Challenger disaster in 1986 led to a slowdown of the space race resulting in a drastic cut of funds for the space program during the 1990s. When the Information Age began in the 1990s, space exploration and related technologies significantly increased. Today, several countries have space programs ranging from technological ventures to full-fledged space programs with launch facilities. Japan, India and China are the major players in this race from the Asian region and have plans to send humans into space. There are many scientific and commercial satellites in use today, with a total of thousands of satellites in orbit. Several countries like Israel, South Korea, Brazil, European Consortium, Indonesia, Malaysia, Thailand, Philippines, Iran, Bangladesh, Pakistan, and North Korea have space organizations and intend to launch their own satellites or conduct research

A spacecraft system comprises various subsystems that are determined by a mission profile. The spacecraft subsystems may include attitude determination and control (ADAC), guidance, navigation and control (GN&C), communications (Comms), command and data handling (C&DH), power (EPS), thermal control (TCS), propulsion, and structures. Typically payloads are also included.

A launch vehicle is used to transport and place a spacecraft or satellites into space. The launch vehicle propels the spacecraft from the Earth's surface, through the atmosphere, and into an orbit, the exact orbit being dependent upon the mission configuration. The launch vehicle may be expendable or reusable.

The spacecraft needs an electrical power generation and distribution subsystem for powering the various subsystems. For a mission near the Sun, solar panels are often used to generate electrical power. For spacecraft designed to operate in more distant locations, a Radioisotope Thermoelectric Generator (RTG) may be used to generate electrical power.

The spacecraft is designed to withstand launch loads imparted by the launch vehicle, and must have interfaces for all the subsystems. Depending upon the mission profile, the structural subsystems may need to withstand large loads imparted by entry into the atmosphere of another planetary body, and from landing on the surface of the planetary body.

The spacecraft is designed to withstand transit through the Earth's atmosphere and the space environment. It must, therefore, be able to operate in a vacuum with temperatures potentially below zero and ranging across hundreds of degrees Celsius as well as (if subject to re-entry) withstand the presence of plasmas. Material requirements therefore may include the use of high melting temperature, low density materials such as beryllium and reinforced carbon-carbon or (possibly due to the lower thickness requirements despite its high density) tungsten or ablative carbon/carbon composites. Depending on the mission profile, the spacecraft may also need to operate on the surface of another planetary body. The thermal control subsystem may be passive, dependent on the selection of materials with specific radiative properties. Active thermal control makes use of electrical heaters and certain actuators such as louvers to control temperature to lie within the specific ranges.

A spacecraft needs a propulsion system to perform momentum management manoeuvers. A conventional propulsion subsystem may include fuel, tankage, valves, pipes, and thrusters. The thermal control system interfaces with the propulsion subsystem by monitoring the temperature of relevant components, and by preheating tanks and thrusters in preparation for a spacecraft manoeuvre.

The payload depends upon the mission of the spacecraft. Typical payloads may include scientific instruments such as cameras, telescopes, or particle detectors, cargo, or may include a human crew.

The spacecraft may also have a module, which is basically a detachable compartment of the spacecraft. For example, a lunar excursion module (LEM) or simply a lunar module is a smaller spacecraft that carries astronauts from the command module to the surface of the Moon and back. Likewise, a space capsule is a smaller spacecraft designed to transport people and support human life in outer space. The Space Shuttle was a reusable spacecraft with wings for a controlled descent through the Earth's atmosphere.

In summary, the spacecraft and its systems must operate with very high reliability under the most unforgiving extreme conditions, from the stress and intense heat of launch and re-entry, to the near absolute zero temperature and vacuum of space including exposure to a variety of radiations and possible collision with space orbiting bodies. The spacecraft requires equipment and systems that can function in either atmospheric or non-atmospheric conditions. And importantly, the cost of a failure is always at stake in any kind of space launch. A small launch vehicle, such as the U.S. Pegasus, costs approximately $15 million, but a versatile, reusable launch vehicle, such as the U.S. Space Shuttle, costs over $1 billion. A small experimental satellite can cost a few million dollars, but an advanced spy satellite or scientific satellite may cost more than $1 billion.

The International Space Station (ISS) is a habitable artificial satellite in low Earth orbit (LEO). It is the ninth space station following its predecessors like the Salyut, Almaz, Skylab and Mir stations The ISS has a modular structure and its first component was launched in 1998. Now it is the largest artificial station in orbit and is visible to the naked eye from the Earth. Its various components have been launched by the American Space Shuttle as well as by Russian Proton and Soyuz rockets. The ISS serves as a microgravity research laboratory with a space environment, in which crew members conduct experiments in astronomy, biology, environment, meteorology, physics, and many other areas. The ISS also serves as an international laboratory for the testing of spacecraft systems and equipment required for other missions such as to the Moon and Mars.

The greatest advantage of pursuing the rather expensive space programs has had its effect in the development of numerous spin-off technologies in many other areas, which in the long run results in significant payoffs.

The idea of space tourism is also becoming more popular in spite of the high cost. This is not without technical problems. Launch to an Earth-orbit requires accelerating to Mach 26 or a speed of about 8 kms/second, and to achieve this, a significant amount of propellant is required - about 10 tons per passenger. Rocket engines use liquid propellant and oxidizer since there is no air in space. Typically, a long-distance airliner has about half its mass as the fuel. But to get to orbit a rocket needs to be about 90% propellant. So the rest of the rocket and passengers are allocated only 10%. Such a rocket needs to have a very light structure, which should be also very strong so that it can survive the acceleration, vibration and aerodynamic stresses. In due course, reusable launch vehicles may come to be operated routinely, just like aircrafts. At present, the space programs are usually carried out by Government agencies and organizations. With private agencies coming into play, space tourism may become realizable.

The present issue of International Journal of Performability Engineering (IJPE) concerns performance related issues and case studies, as these are of importance to the readers of IJPE. Therefore it was considered appropriate to choose the theme of performance analysis of space vehicles for the special issue. Space vehicles may include satellites, unmanned space vehicles, manned space vehicles, as well as the International Space Station (ISS). Performance analyses include all types of analyses pertinent to the performance of a space vehicle. The special issue is intended to cover methods and assessments.

When I first put the idea of bringing out a special issue of this kind to Dr. William Vesely of NASA Headquarters, he agreed to work towards this possibility. And he sought some time to respond to my request, presumably for sounding his colleagues who are working on various aspects of the theme. I am delighted to see a very good response to the call for possible contributions to this issue. The result is that finally Dr. Vesely selected a set of 12 papers for this issue which I may add is also the maximum number of papers contained in any special issues brought out by the IJPE.

I owe gratefulness to Dr. Vesely for his editing and to the authors who have contributed their valuable papers to this special issue. I believe that this is a first of its kind effort that has been made by any journal. The organizations, industries, researchers and academia world over will find the information contained in this issue of interest for their work. The readers of IJPE will also find the issue of great interest.

This is a special issue focusing on performance analysis of space vehicles. Methodologies, techniques, decision approaches, applications, and viewpoints are presented. The papers cover a diverse assortment of topics. Even though many are focused on performance assessments of space vehicles, the subjects covered are relevant to the field of performability engineering in general. I trust the readers will find the papers interesting and informative. A synopsis of each paper covering its unique and important contribution is outlined as follows:

Two Case Studies Illustrating the Management of Risks for the International Space Station

By: K. Carter-Journet, J. Calhoun, M. Raftery, and M. Lutomski, U.S.A.

Two case studies are described that illustrate how Probabilistic Risk Assessment (PRA) is practically used in risk-informed decision making for the International Space Station (ISS). The first case describes how risks from the impacts from micrometeoroid and orbital debris (MMOD) are controlled. The second study describes assessments of potentially increasing risks from commercial vehicles that will visit the ISS. These studies are some of the best examples of the actual implementation of risk-informed decision making.

Estimating the Risk of a New Launch Vehicle Using Historical Design Element Data

By: R. Cross, U.S.A.,

This paper describes an approach that has been developed by a working group consisting of NASA, the Federal Aviation Administration (FAA), and the Air Force. Historical data of new launch vehicles are analyzed to estimate the failure probabilities for given types of systems and functions that can then be appropriately synthesized to estimate the failure probability of a new launch vehicle. This approach offers an important alternative to traditional component-based models that generally underestimate the failure probability of a new launch vehicle.

Orbital Warehouse Design for an Extra-terrestrial Supply-Chain Distribution Model

By: N. Chari, U. Venkatadri, and C. Diallo, Canada

This is an interesting paper in the methodology used and the results that are obtained. A supply network is defined that involves the terrestrial launch facility, the ISS, a group of hotels, a warehouse, and a lunar base. Assuming given altitudes for the ISS and lunar base, optimal altitudes for the hotels and warehouse are determined by minimizing an expression for the total energy required in orbital transfers. Using these given altitudes, fuel and supply requirements are then determined. This approach has the potential for greater extensions and applications.

On the Estimation of Space Launch Vehicle Reliability

By: S. Guarro, U.S.A.

This paper reviews approaches used to estimate the reliability of a new space launch vehicle. These approaches are classified as two types-direct estimation approaches using past history and indirect bottom-up approaches using component level models and data. The features of the different approaches are then described along with the contributions they include as well as exclude. The significant value of the paper is the practical insights and conclusions that are derived based on past experience and past space launch vehicle history.

Shuttle Risk Progression-Focus on Historical Risk Increases

By: T. Hamlin, U.S.A.

The Space Shuttle PRA has been extensively used and updated to follow the upgrades made to the Space Shuttle. This paper retraces the evolution of the estimated Probability for the Loss of Crew and Vehicle (PLOCV). The focus is on the increased estimates of PLOCV that are obtained by backward retracing of the upgrades that were made up through the first flight. The risk progression evolution that is thereby obtained is a stepwise progression. The risk progression evolution can serve as a useful reference in estimating the risk evolution of a new launch vehicle.

Fiber Breakage Model for COPV Reliability Estimation

By: R. P. Heydorn and P. L. N. Murthy, U.S.A.

Because of their strength and light weight, composite overwrapped pressure vessels (COPVs) are employed in new systems including a number that are used on the ISS. An issue with COPVs is the potential occurrence of catastrophic stress rupture. This paper develops a formula for the reliability of a COPV that models the basic mechanistic process involved in the failure occurrence. Comparisons are made with the purely empirical Weibull model that is often used. The work provides a potential, significant improvement in COPV reliability estimation.

Use of a PRA in Supporting the Design of a GOES Weather Satellite and Ground System

By: P. Kalia, R. Pair, J. Uhlenbrock, V. Quaney, and Y. Shi, U.S.A.

This paper describes the employment of a PRA throughout development of design of the Geostationary Operational Environmental Satellite (GOES). The paper is interesting in describing the interactions between the PRA analysts and the designers and how specific PRA results were used to improve the design. The paper also describes the different considerations involved in modeling the ground support system for the satellite. The paper is a documented case of how a PRA provides cost-effective benefits in terms of the improvement of reliability during the design.

Reliability Characteristics of a Satellite Communication System Including Earth Station and Terrestrial System

By: K. Nagiya and M. Ram, India

This is an interesting paper in that it shows how basic Markov models can be applied to a satellite system and associated support systems to determine expressions for the associated reliability, availability, mean time to failure, and expected profit. Even though the models are basic, what is useful is the set of insights gained and general behaviors obtained by varying the different parameters over the range of values of interest. Sensitivity measures are also defined which give the rate of change. The models also serve as a basis for extensions to more complex models.

Informative Bayesian Quantification of Design Reliability Based on Test Characteristics and Test Results

By: W. E. Vesely, U.S.A.,

Often the design reliability of a new system is statistically estimated using only the successes and failures observed in given tests. This paper shows how design reliability estimates can be significantly improved by incorporating the basic characteristics of the tests conducted, the faults detected, and the corrections made. The number of tests needed to achieve a given reliability criterion can thereby be significantly reduced. Reliability growth can also be more effectively monitored. The approach can have significant impacts as shown by the variety of applications.

Systematic Quantification of the Prior Risk Assurance of a New System Using Bayesian Evidence Analysis

By: W. E. Vesely, U.S.A.,

The total risk assurance of a new system is obtained from initial assessments plus additional tests conducted. The initial assessments provide the prior risk assurance which can be expressed as the confidence in an acceptable risk. This paper uses evidence analysis principles to systematically combine the diverse qualitative and quantitative results obtained from the initial assessments to obtain the measure of the overall risk assurance. Even though used in many other fields, the approach is generally not used for risk assurance. The benefits can be significant.

Modeling Rate of Occurrence of Failures with Log-Gaussian Process Models-A Case Study for Prognosis and Health Management of a Fleet of Vehicles

By: M. Wayne and M. Modarres, U.S.A.

Log-Gaussian Process Regression (GPR) handles general non-linear relationships by specifying a general form for the kernel function which defines the covariances of the dependent variables. The kernel function contains different possible behaviors with associated weights (hyperparameters) which are estimated from data. As the paper shows, GPR is a powerful technique for monitoring general trends in failure occurrences. It also has the important potential for monitoring fault occurrences as well as failure occurrences in reliability growth applications.

Bayes Linear Bayes Graphical Models in the Design of Optimal Test Strategies

By: K. J. Wilson., J. Quigley, T. Bedford, and L. Walls, U.K.

Bayesian networks (BN) are used in a wide variety of applications. The problem in many practical applications is the explosion of states and variables that result and that must be input. This paper presents an important linear Bayes approach for addressing this problem which uses optimal linear relationships among the states and variables. Conjugate distributions are also used for discrete state probabilities allowing efficient updating. The applications described for optimizing test strategies show the power of the approach in modeling multiple decision alternatives.

Finally, I wish to thank all the contributors for their papers. I was truly gratified by their excellent papers and timely responses.

William E. Vesely received his B.S. in Physics in 1964 from Case Institute of Technology and his M.S. and Ph.D. in Nuclear Engineering in 1966 and 1968, respectively, from the University of Illinois. Dr. Vesely has been in the risk assessment field for over 40 years. He was a principal author of the first major Probabilistic Risk Assessment (PRA) performed on nuclear plants, WASH-1400. He worked at the Nuclear Regulatory Commission as a risk specialist, and has been a PRA consultant for the Department of Defense, Department of Energy, various National Laboratories and various companies. Dr. Vesely has developed numerous approaches for risk and reliability evaluations, including techniques for data mining, pattern recognition, and risk trending.

Dr. Vesely has published over 100 papers and reports on PRA, statistical analysis, data analysis, and expert systems. He has been an adjunct professor for several universities.

Dr. Vesely has assurance responsibilities for risk assessments carried out by NASA. He also has responsibility for methods and tool developments for risk assessments and reliability assessments. He lectures at NASA's Probabilistic Risk Assessment (PRA) Courses and teaches NASA Fault Tree Courses.

He is the principal author of the Fault Tree Handbook with Aerospace Applications published by NASA. He served as a technical coordinator for Space Shuttle PRA.

The International Space Station (ISS) has been operating in space for over 14 years and permanently crewed for over 12 years. Throughout this time, the ISS Program has implemented and continually improved its risk management process. This ISS risk management process identifies risks that may exist and alternatives for mitigation if the risks are significant. Risk management has provided input that has been essential to the program management decision making process. Risks can be reduced, mitigated or accepted and are prioritized to ensure program resources are used as efficiently as possible. The ISS risk management process has increased the probability of success of the ISS mission objectives and overall crew safety.
This paper presents two case studies on how the ISS risk management process has been used to address specific areas of risk. The first case describes how the ISS Program has analyzed and mitigated the risk of Micrometeoroid Orbital Debris (MMOD) strikes to pressurized modules. MMOD has been a major safety concern since the beginning of the program. The second case study describes the risk assessment of Visiting Vehicle (VV) collisions. There has been a significant increase in the number of visiting vehicle flights to the ISS since the retirement of the Space Shuttle Program. This has caused an elevated cumulative risk of collision when considering the frequency of vehicle traffic to the ISS.

As part of the National Aeronautics and Space Administration’s (NASA) Constellation (Cx) Program, a data-based approach was developed to estimate the probability of a loss of vehicle for the Ares I-X flight. This approach, called the Complexity Risk Assessment Method (CRAM), utilizes historical data to estimate the failure probability of elements of given designs. Particular elements are then combined to obtain a generic vehicle design with an associated generic failure probability. The generic failure probability is then further modified to account for features of a new launch vehicle. CRAM is used only for ascent until the vehicle is in a proper and stable orbit. This paper provides a discussion of CRAM as well as an example as applied to the Antares launch vehicle. CRAM is still being refined as part of ongoing methods development with the Common Standards Working Group (CSWG) consisting of NASA, the Federal Aviation Administration (FAA), and the Air Force.

This study presents the design of a warehouse facility in geocentric orbit, to efficiently transfer goods from a terrestrial launch site to multiple destinations such as the International Space Station, prospective hotels, and a lunar base. The proposed distribution model will find the optimum mass flow from the warehouse by jointly determining the optimal altitudes of the hotels and warehouse. A numerical analysis is carried out to minimize the energy required to satisfy this network. The altitudes are heavily dependent on the mass allocated to each destination at launch. Based on requirements for oxygen, water, food, fuel, and waste; the placement of the warehouse and hotels have been established. Sensitivity analyses of different supply frequencies have also been examined.

The paper reviews the common definitions of reliability that are relevant to launch vehicles (LVs) and discusses their theoretical and practical interpretations. The paper then proceeds to a discussion of the data and methods available for reliability estimation at various LV system maturity stages, presenting examples of results and estimations obtained by past and recent studies. This leads to practical considerations concerning the meaning of typical reliability estimations that are generated in common space industry practice, and their degree of correspondence and consistency with the theoretical definitions of the parameters they seek to quantify. Final observations and comments are drawn from these considerations.

This paper is the product of the author’s personal experience and interest in the topic of launch vehicle reliability. Neither the paper as a whole or any of its specific contents represents an official position of The Aerospace Corporation

It is important to future human spaceflight programs, to understand the early mission risk and the impact of design, process, and operational changes on risk. The Shuttle risk progression assessment used the knowledge gained from 30 years of operational flights and the Shuttle Probabilistic Risk Assessment (PRA) to calculate the risk of Shuttle Loss of Crew at significant milestones beginning with the first flight. The results indicated that the Shuttle risk tends to follow a step function as opposed to following a traditional reliability growth pattern. In addition, the results showed that risk can increase due to trading safety margin for increased performance, due to external events or due to intended (disabling ejection seats) or unintended (Space Shuttle Main Engine Block II upgrade) consequences of design changes. This paper will focus on examining those cases where risk increased and explore the lessons that can be learned by new programs.

The most commonly used reliability model to predict the probability of a COPV rupture is based on the Weibull distribution. In this paper we propose an alternative reliability model based on the idea that the stress rupture process is preceded by the formation and evolution of fiber breakage clusters. The fiber breaks in this process are described by a Bose-Einstein distribution which leads to a Polya urn model that describes the progression of the number of fiber breaks. This urn model shows that two distinct paths for the formation of breakage clusters are possible. In the first one a few breakage clusters are shown to have a dominant number of breaks. In the second one, the breakage clusters are shown to have the number of breaks evenly distributed across clusters. Simulations suggest that the dominant case leads to a high variance across the total number of breaks, whereas the evenly distributed case leads to a smaller variance. A small number of clusters will lead to fiber breakage reliability models that estimate a higher reliability than does the Weibull.

Probabilistic Risk Assessment (PRA) was initially adopted and implemented by NASA in the operational phase of human space flight programs and more recently for the next generation human and robotic space explorations as well as the key operational space missions. Since its first use at NASA, PRA has become recognized throughout the agency as a method of assessing complex mission risks as part of an overall approach to assuring safety and mission success. PRA is now included as a requirement during the design phase of both NASA next generation human space systems as well as high priority robotic/operational missions. This paper presents the application of the first comprehensive PRA during the design phase of the Geostationary Operational Environmental Satellite R-Series (GOES-R). This PRA is also unique in that it includes the first quantitative ground system analysis conducted at NASA. The design and operational changes resulting from the GOES-R PRA are discussed in detail in this paper.

This paper investigates the various reliability characteristics of a satellite communication system. The complete satellite system consists of the satellite, earth station, and terrestrial system. Partial and complete failure states of the system are evaluated. The system has partially failed due to failure of the transmitter or receiver and is completely failed due to failure of the satellite or failure of terrestrial systems. All failure rates are assumed to be constant and a constant repair rate is assumed for all failures. Using Laplace transformations and Markov process theory, the transition state probabilities, availability, reliability, MTTF, cost effectiveness and sensitivity analysis of the system are determined. Particular cases and graphical illustrations are also presented.

A common practice is to use random sampling statistics to estimate the demonstrated reliability of a new system from the number of successes and failures. This can grossly overestimate or underestimate the true reliability because of the na?ve assumptions involved. A more detailed approach is presented which accounts for the characteristics of the test, the faults identified and the corrections made. The Bayesian framework accommodates a prior reliability estimate and comprehensively handles uncertainties. The examples show the wide areas of application from determining test strategies to tracking reliability growth. The applications described are believed to be new. The approach needs to be more widely implemented because of its features.

The total risk assurance of a new system such as a spacecraft is based on initial reviews, testing, and operational experience. The initial reviews include inspections, audits, and qualitative and quantitative analyses. The risk assurance provided by the initial reviews can be termed the prior risk assurance. The information provided by the initial reviews can be qualitative or quantitative. Bayesian evidence analysis is shown to be capable of systematically translating the diverse information to a common scale to systematically quantify the prior risk assurance provided. Evidence analysis principles and probability rules are used in this translation. The quantified prior risk assurance that is obtained can be compared to numerical criteria and can then be updated with testing and operational data to obtain the updated system reliability estimate. Bayesian evidence analysis has a strong background and provides a unique capability of quantifying individual sources of risk assurance and the total risk assurance provided. The particular methodology presented here is believed to be new.

Gaussian Process Regression (GPR) is a flexible non-parametric regression technique that provides an alternative solution to the model selection problem commonly seen in parametric models. GPR models are able to easily model complex non-linear relationships that are often present in rate of occurrence of failure data. The predictive distributions that result from the regression models are then used to provide valuable insights into the behavior of the data. An example of the application of this approach has been demonstrated for modeling the rate of occurrence of failure of a fleet of vehicles on a monthly basis. The Log-GPR model applied in this context is useful for detecting significant reliability problems that may occur over time. In order to assess the generalization capability of the model to accurately represent a test data set, a goodness of fit test is also presented.

Test and analysis plays a vital role in reducing uncertainty about the true performance of an engineering system. However tests can be expensive and designing an optimal test strategy can be challenging. We propose a Bayesian modelling process, which takes the form of a Bayesian Network, to determine anticipated test efficacy. Such a model supports engineering managers in assessing trade-offs between test resources and uncertainty reduction. Inference based on a full Bayesian model can be computationally demanding to the extent that it can limit practical application. To overcome this constraint, we develop a Bayes linear approximation for inference. This approach is known as a Bayes linear Bayes graphical model. After explaining the key principles of the method, we provide an application to a real industrial test to establish the condition of an ageing engineering system.