Engineering topics
Rhodes, Russel
Publications and source records attributed to Rhodes, Russel.
A Methodology for Quantifying Certain Design Requirements During the Design Phase
A methodology for developing and balancing quantitative design requirements for safety, reliability, and maintainability has been proposed. Conceived as the basis of a more rational approach to the design of spacecraft, the methodology would also be applicable to the design of automobiles, washing machines, television receivers, or almost any other commercial product. Heretofore, it has been common practice to start by determining the requirements for reliability of elements of a spacecraft or other system to ensure a given design life for the system. Next, safety requirements are determined by assessing the total reliability of the system and adding redundant components and subsystems necessary to attain safety goals. As thus described, common practice leaves the maintainability burden to fall to chance; therefore, there is no control of recurring costs or of the responsiveness of the system. The means that have been used in assessing maintainability have been oriented toward determining the logistical sparing of components so that the components are available when needed. The process established for developing and balancing quantitative requirements for safety (S), reliability (R), and maintainability (M) derives and integrates NASA s top-level safety requirements and the controls needed to obtain program key objectives for safety and recurring cost (see figure). Being quantitative, the process conveniently uses common mathematical models. Even though the process is shown as being worked from the top down, it can also be worked from the bottom up. This process uses three math models: (1) the binomial distribution (greaterthan- or-equal-to case), (2) reliability for a series system, and (3) the Poisson distribution (less-than-or-equal-to case). The zero-fail case for the binomial distribution approximates the commonly known exponential distribution or "constant failure rate" distribution. Either model can be used. The binomial distribution was selected for modeling flexibility because it conveniently addresses both the zero-fail and failure cases. The failure case is typically used for unmanned spacecraft as with missiles.
In-Space Propulsion Assessment Processes and Criteria for Affordable Systems
In a world of high launch costs to Low Earth Orbit (LEO), and of costs nearly twice as high to Geosynchronous Earth Orbit (GEO), it is clear that processes and criteria are required which will surface the path to greater affordability. Further, with propulsion systems making up a major part of the systems placed into multiple orbits, or beyond, it is clear that addressing propulsion systems for in-space propulsion (ISP) is a key part to breaking the barriers to affordable systems. While multitudes of Earth to Orbit transportation system efforts focus on reduced costs, the often neglected costs and related interactions of the in-space system equally require improvements that will enable broad end-to end customer affordability.
A white paper: Operational efficiency. New approaches to future propulsion systems
Advanced launch systems for the next generation of space transportation systems (1995 to 2010) must deliver large payloads (125,000 to 500,000 lbs) to low earth orbit (LEO) at one tenth of today's cost, or 300 to 400 $/lb of payload. This cost represents an order of magnitude reduction from the Titan unmanned vehicle cost of delivering payload to orbit. To achieve this sizable reduction, the operations cost as well as the engine cost must both be lower than current engine system. The Advanced Launch System (ALS) is studying advanced engine designs, such as the Space Transportation Main Engine (STME), which has achieved notable reduction in cost. The results are presented of a current study wherein another level of cost reduction can be achieved by designing the propulsion module utilizing these advanced engines for enhanced operations efficiency and reduced operations cost.