One of the early motivations of space science was the opportunity for astronomy to use hitherto inaccessible wavelengths, from gamma–and X–rays to infrared, and visible–light astronomy, from orbiting telescopes, was allowed better seeing, free of atmospheric contamination. Meteorological observations and earth remote sensing required orbiting cameras and infrared radiometers. All needed applications of optics.

It will be clear from foregoing chapters that, for space instrumentation, optics should (i) have qualities of rugged mechanical design, (ii) be built of lightweight non–contaminating materials, and (iii) survive years of unattended use in orbit. This chapter offers an introductory account of materials and opto–mechanical design techniques which have been serving these ends. Optical design as such, and physics of sensors, are beyond our scope. The steady improvement of sensor and detector systems, often of great sensitivity, has fostered parallel development of computation and suppression of stray light. As in all space endeavours, pre–launch qualification testing should be carefully and thoroughly conducted. Operation and adjustment in space requires mechanisms whose life may be limited, but in-orbit repair or replacement is either impossible or very costly; hence trade–off decisions may be difficult to make.

Materials for optics

As remarked in paragraph 2.7.12, the concern with glasses and ceramics is their brittleness while exposed to the launch environment. The chart (Fig. 2.31) of fracture toughness versus strength for the diversity of materials shows optical glasses, as a class, to have high strength but low toughness.

General background

Preamble

The temperature of laboratories in which space experiments are assembled, calibrated and tested is nominally 20°C (293 K) and it is thus not surprising that in general this is a most desirable operating temperature for that same equipment in space. There is nothing unique about this temperature. It is, within a relatively small band, a typical temperature that is experienced anywhere on the Earth's surface and, as fossil records show, has remained remarkably stable over billions of years.

Interestingly an Earth satellite is in a similar thermal environment, modified of course by the presence of the Earth. It is instructive therefore to consider what each of these thermal environments are and in what subtle ways they differ.

The temperature of the Earth

Essentially the Earth's surface temperature of about 290K results from the fact that the Earth orbits the Sun, which has a luminosity of 3.9 × 1026 W, and is at a mean distance of 1 Astronomical Unit (AU) from it, that is 1.5 × 1011 m. The emitted solar power crosses the surfaces of a succession of concentric, imaginary spheres centered on the Sun. The sphere which intercepts the Earth has a radius equal to the Astronomical Unit, so it is a simple calculation to show that the energy flux density at the distance of the Earth is 1.37 kWm−2. Thus the power equivalent to a one bar electric fire is received across every square metre of the Earth's projected area.

Preamble

The selection and operation of an appropriate and efficient project management scheme is as necessary to the success of a space project as the selection of the correct electronic components or the execution of a competent thermal design. Unlike pure engineering tasks, project management concerns the engineering of complex systems, the components of which are individual human beings. These sometimes exceed their specifications and sometimes fail to meet them, but they are always different. The presentation here of a structured approach to the creation of a project management scheme does not imply that one structure will suit all projects or all individuals. Considerable effort and care is needed to ensure that the management plan is efficient, appropriate and agreeable to all parties. The task of designing a project management plan can be seen as a method of ensuring that the project meets its time and cost budgets, in the same way as the electronic and mechanical engineering described previously in the book seek to meet power and mass budgets.

Introduction

Management is a very common word in everyday life but an accurate definition of it is difficult to get agreement on amongst practitioners. One definition that can be considered is:

Although there are some unfortunate overtones in the last part of the definition, this description is a good one for endeavors like space projects which require a team of people with a mix of skills.

Scientific observations from space require instruments which can operate in the orbital environment. The skills needed to design such special instruments span many disciplines. This book aims to bring together the elements of the design process. It is, first, a manual for the newly graduated engineer or physicist involved with the design of instruments for a space project. Secondly the book is a text to support the increasing number of undergraduate and MSc courses which offer, as part of a degree in space science and technology, lecture courses in space engineering and management. To these ends, the book demands no more than the usual educational background required for such students.

Following their diverse experience, the authors outline a wide range of topics from space environment physics and system design, to mechanisms, some space optics, project management and finally small science spacecraft. Problems frequently met in design and verification are addressed. The treatment of electronics and mechanical design is based on taught courses wide enough for students with a minimum background in these subjects, but in a book of this length and cost, we have been unable to cover all aspects of spacecraft design. Hence topics such as the study of attitude control and spacecraft propulsion for inflight manœuvres, with which most instrument designers would not be directly involved, must be found elsewhere.

The authors are all associated with University groups having a long tradition of space hardware construction, and between them, they possess over a century of personal experience in this relatively young discipline.

Initial design

In the beginning

Designing electronic subsystems for space vehicles can be considered in two overlapping phases. The circuitry has to carry out the required signal processing functions but also has to be capable of overcoming the particular problems associated with the subsystem existing and operating in the environment associated with the spacecraft.

In the early stages of a design, estimates have to be made of mass, volume and power consumption to determine what is feasible, within the constraints imposed by the spacecraft. Estimates are also required for cost, time and manpower to ensure that the flight hardware can be realistically produced by the required delivery date. Thus it is important to consider as soon as possible what problems associated with the space environment are seriously going to effect these estimates compared to a ground – based design.

A long life mission will have a significant impact on costs due to the requirement for increased reliability of components and manufacturing techniques, and for the introduction of component or system redundancy.

Apart from the requirements of telemetry transmitter power and type of antenna, the orbit can have a very significant effect on cost if it is associated with a high radiation environment. This may require the use of highly specialized, radiation tolerant components which may be difficult to procure. A high radiation environment can also have a major impact on mass where the wall thickness of the structure is no longer defined by structural and electrostatic screening requirements but by its ability to absorb radiation.

Most of the simple methods described in Part III have almost no potential for practical applications, due mainly to stability problems. This fourth part of the book concerns methods at the next higher level of sophistication, here referred to as the first generation of numerical methods for computational gasdynamics. However sophisticated they may be in other ways, by definition, first-generation methods do not use flux averaging, slope averaging, or other forms of solution sensitivity, except possibly upwinding. As a result, first-generation methods experience a sharp trade-off between accuracy and stability: They can model shocks well but then experience low accuracy in smooth regions; or they can model smooth regions well but then experience poor stability near shocks in the form of spurious oscillations and overshoots. The next part of the book, Part V, describes solution-sensitive second- and third-generation numerical methods, which reduce this trade-off by doing one thing in smooth regions and another at shocks. First-generation methods prove useful in undemanding applications and, more importantly, are the basic building blocks of second- and third-generation methods.

Chapter 17 describes numerical methods for scalar conservation laws. Chapter 18 extends those methods to the Euler equations using flux vector splitting and Riemann solvers. Chapter 19 concerns solid and far-field boundary treatments, a crucial topic avoided until now by using periodic boundaries as in Chapter 15 or infinite boundaries as in Chapter 16.

Fluid dynamics concerns fluid motions. No single book, or even shelf of books, could hope to describe the full range of known fluid dynamics. By tradition, introductory books mainly concern three simplified categories of flow:

1. Gasdynamics – compressible frictionless flows.

2. Viscous flows, boundary layers, and turbulence – incompressible frictional flows.

3. Potential flows – irrotational frictionless flows.

Books with generic titles like fluid dynamics, fluid mechanics, or aerodynamics generally survey all three basic categories of flow. Other books concern just gasdynamics or just viscous flows. These books sacrifice breadth for depth. Given the huge differences between compressible inviscid flows and viscous incompressible flows, single-topic treatments make sense for many readers, who need to know only one or the other.

Computational fluids dynamics (CFD) concerns computer simulations of fluid flows. Each type of fluid flow listed above has inspired a myriad of competing numerical methods, each with its own pros and cons, each demanding a good understanding of both traditional fluid dynamics and numerical analysis. As a result, the size of computational fluid dynamics far exceeds that of traditional fluid dynamics. At the present time, most CFD books survey numerical methods for all three of the basic flow categories. While such surveys work well for traditional fluid dynamics, the larger size of CFD requires more compromises and trade-offs. With so much to cover, even a two-volume survey can only describe the basic principles and techniques common to all three categories of flows, plus a limited and sometimes arbitrary sampling of the principles and techniques specific to each category of flow.

Introduction

This chapter concerns boundary treatments. Before now, the book has avoided boundary treatments by using either infinite boundaries or periodic boundaries, but one cannot remain innocent forever. Boundary conditions and governing equations have equal importance, despite the fact that most sources, including this one, spend most of their time focused on the governing equations. For the same governing equations, boundary conditions distinguish flow over a plane from flow over a train from flow over a space shuttle from any other sort of flow. In practice, numerical boundary treatments often consume a large percentage of computational gasdynamics codes, both in terms of the number of lines of code and in terms of the development effort.

This chapter concerns two types of boundaries – solid and far-field boundaries. Solid boundaries are also known as surface, wall, rigid, or impermeable boundaries; naturally enough, solid boundaries occur at the surfaces of solid objects. This chapter considers only stationary solid boundaries. Far-field boundaries are also known as open, artificial, permeable, or remote boundaries. Far-field boundaries limit the computational domain to a reasonable finite size; the true boundaries may be extremely far away, or even infinitely far away, at least conceptually. In general, when the physical domain is very large or infinite, then the farther away the numerical far-field boundary is, the more accurate but also the more costly the numerical approximation will be. Far-field boundaries are divided into inflow boundaries, where fluid enters the computational domain, and outflow boundaries, where fluid exits the computational domain. In multidimensions, far-field boundaries may also be streamlines, across which fluid neither exits nor enters.

Introduction

The last two chapters dramatically demonstrate the folly in attempting to represent a discontinuous function by a single polynomial. In the best case, with the entire true function available, the single polynomial representation will suffer from narrow width but large-amplitude Gibbs oscillations near the jump discontinuities, at least when minimizing the error in ordinary norms, as seen in Chapter 7. In more typical cases, with only limited information about the true function available or, more specifically, with only samples of the function available, the single polynomial will suffer from the Runge phenomenon, a relatively severe form of spurious oscillation that can increase rapidly as the number of samples increases, as seen in Chapter 8.

To overcome the problems associated with single-polynomial reconstructions, this chapter will consider piecewise-polynomial reconstructions, which were introduced earlier in Section 6.3, especially in Example 6.8. In piecewise-polynomial reconstructions, instead of representing the entire function by a single polynomial, we represent different local regions or cells by different polynomials. Figure 9.1 illustrates a typical piecewise-polynomial representation. By using separate and independent polynomials for each cell, only the cells containing jump discontinuities need suffer from large spurious oscillations, rather than the entire representation. Furthermore, piecewise-polynomial representations naturally allow jump discontinuities: the simplest reconstructions allow jump discontinuities only at cell edges, whereas the subcell resolution techniques discussed in Section 9.4 allow jump discontinuities to occur anywhere, including the insides of cells. Of course, piecewise-polynomial reconstructions cost more to build and evaluate and require more storage space than a single polynomial reconstruction; however, for discontinuous functions, the accuracy improvements easily justify the additional costs.