Symbolic reliability analysis and optimization of ECU networks

An efficient Boolean algebraic algorithm for the symbolic reliability and sensitivity analysis of coherent two-terminal networks with s independent components is described. The algorithm is also applicable to a fault tree model without NOT gates. The algorithm uses the concept originally proposed by A. Grnarov, L. Kleinrock, and M. Gerla (1979). After the algorithm is presented, the errors in the original technique are illustrated by two examples. The algorithm is extended t compute the reliability importance of a given component (sensitivity of system reliability to a given component's reliability). A computer program implementing the modified algorithm is used to solve and obtain measured time complexities for a large set of network and fault tree models.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

The authors describe an efficient Boolean algebraic algorithm to compute the probability of a union of nondisjoint sets as applied to symbolic reliability analysis. Coherent networks and fault-trees with statistically-independent components characterized by their minimal pathsets or cutsets are used as examples for generating the nondisjoint sets. The algorithm uses the concept of multiple variable inversion originally proposed by A. Grnarov et al. (1979). The authors illustrate improvements in the use of the multiple variable inversion technique for this problem using two examples. The algorithm is extended to compute the reliability importance of a given component (sensitivity of system reliability to the component reliability). A computer program implementing the modified algorithm is used to solve and obtain measured time complexities for a large set of network and fault tree models. >

Typical, numerical structural optimization is well established in improving structural design in its final design phase. The overall product topology is then already defined and structural optimization is “only” used to improve shape and size parameters, which have no influence on the global mechanical topology. Significant decisions have been made already in earlier development stages. However, it is desirable to expand this optimization capabilities to CAE based support for the definition and preliminary design of the general layout, geometrical and structural architecture, equipment configuration and functional requirements. For satellites such a support can be defined as follows: Finding the conceptual geometrical architecture of a satellite satisfying the basic geometrical, mechanical and thermal requirements within an automated optimization process. This includes mainly the (a) topology and geometry of the basic structural components, (b) placements of basic components and equipment and (c) preliminary concept evaluation (e.g. FEM, etc.) Intentionally, the satellite design engineering team should be supplied with a set of feasible or nearly feasible satellite configurations (satisfying the main geometric, mechanical and thermal requirements) serving as a good starting basis for satellite configuration development in early design phases. The design engineers investigate these preliminary conceptual satellite designs for the remaining, typically more specific and more locally acting requirements (e.g. fastening, piping, etc...). In this way the main basic effects guiding satellite design can be taken into account at the very early development stages and, moreover, can be compared with alternative designs to find the best tradeoff. This is a great advantage and progress compared to the traditional design process. Optimization now starts to enter the early and important design phases, the real significant design decisions can now be made by support of optimization techniques. It should be further noted, that our system is not proposed to substitute the design engineers, but to supplement and to enlarge the potentials of the design branch to reach a better design in a shorter time conforming to concurrent engineering issues. In this paper our approach for an automated satellite conceptual design method will be presented, and emphasis is put on demonstration and verification by the satellite GammaBus 1 (the carrier of the Galileo system) as well as other real space applications. Further some main aspects regarding discrete-continuous optimization for structural configuration tasks from an algorithmic point of view are discussed to round out this paper

This study proposes an algorithm-aided design (AAD) framework for using daylight in the early phases of architectural design. Within the scope of the proposed AAD, a performance-based design approach has been adopted that can suggest design solutions by optimising with the Genetic Algorithm (GA) that evaluates the results obtained from daylight calculation. The AAD framework was developed using the visual programming application (Dynamo), which interoperates with BIM Software Autodesk Revit. A case study is simulated to show how the algorithm is used to generate, evaluate and evolve a massing study, demonstrating the potential use and implementation of the framework. The investigations focus on the development of the use of daylight in architecture using the advantages of computational design tools.

Selecting composite materials considering cost and environmental impact in the early phases of aircraft structure design

The early phase of design contains multiple sources of unexpected circumstances which include the change or addition of performance requirements or design conditions with the process of the design phases. Therefore, designers are required to design considering those unexpected circumstances in the after phases. Previously, we proposed a preference set-based design (PSD) method, which obtains a unique design solution set from a point of view of design preference and robustness under various sources of uncertainties while incorporating the designer's preference in the early phase of design. PSD method represents the uncertain design information as the interval set. This paper proposes a new design method based on PSD method which can obtain diverse possible design solution sets for unexpected circumstances by deriving the multiple feasible design domains which satisfy the required performances. Obtaining diverse possible design solution sets could deal with the unexpected circumstances by selecting the optimal design solution from obtained diverse possible design solution sets in the early phase. In this paper, the proposed design method is applied to the design problem of an active isolation system of 4-story building to correspond to the additional unexpected earthquake ground motion which the designer cannot consider at the early phase of design.

Our goal is to provide a Multi-Perspective viewpoint interactive interface media of sketch-based for rapid get spatial layout in Show-Window. In traditional way, designer is used to describe concept in early phases of design by Single-Perspective viewpoint via sketch in Show-Window design environment. It usually makes blind spot of spatial vision in early phases of design because it can't break the Single-Perspective viewpoint. Therefore we present an interactive media of sketch-based that can get Multi-Perspective viewpoint in early phases of design to support designer. Show-Window designer not only can have synchronic interaction with object of the design environment, and have more design thinking and variability of spatial layout but also can immediate edit, revise the vision and generate an optimum spatial layout again, and reduce time cost of later phases of design by design sketch after via the interactive media.

More and more embedded systems provide a multitude of services, implemented by a large number of networked hardware components. In early design phases, dimensioning such complex systems in terms of monetary costs, power consumption, reliability etc. demands for new analysis approaches at the electronic system level. In this paper, two symbolic system level reliability analysis approaches are introduced. First, a formal approach based on Binary Decision Diagrams is presented that allows to calculate exact reliability measures for small to moderate-sized systems. Second, a simulative approach is presented that hybridizes a Monte Carlo simulation with a SAT solver and delivers adequate approximations of the reliability measures for large and complex systems.

Graph-based symbolic technique is a viable tool for calculating the behavior or the characterization of an analog circuit. Traditional symbolic analysis tools typically are used to calculate the behavior or the characteristic of a circuit in terms of symbolic parameters (Gielen et al., 1994). The introduction of determinant decision diagrams based symbolic analysis technique allows exact symbolic analysis of much larger analog circuits than any other existing approaches (Shi & Tan, 2000; 2001). Furthermore, with hierarchical symbolic representations (Tan et al., 2005; Tan & Shi, 2000), exact symbolic analysis via DDD graphs essentially allows the analysis of arbitrarily large analog circuits. Some recent advancement in DDD ordering technique and variants of DDD allow even larger analog circuits to be analyzed (Shi, 2010a;b). Once the circuit’s small-signal characteristics are presented by DDDs, the evaluation of DDDs, whose CPU time is proportional to the sizes of DDDs, will give exact numerical values. However, with large networks, the DDD size can be huge and the resulting evaluation can be very time consuming.

This paper presents a design and simulation environment to support the validation of design concepts for embedded systems during early design phases. The tool is built around a methodology based on rapid prototyping. The MCEMS Toolbox supports the designer during the architectural, detailed design and implementation phase with a set of models, software and hardware for system description, prototype synthesis and execution under real-time conditions. Thus, specifications can be validated during early design phases which shortens the overall development time. >

Traditional multiphase flow simulations often include less rigorous boundary condition assumptions, because flowline models are commonly isolated from both upstream well inflow and downstream processing facilities. Such an approach can be even more unrealistic if the flowline model network is complicated for example, where connected with subsea processing equipment. Within this kind of system, changes in fluid behavior are even more sensitive to overall operability. A full field integrated simulation, which includes well inflow, subsea equipment (XTs and manifolds), subsea processing, flowlines, and/or arriving facilities, offers a more realistic solution. This paper describes the application and value of performing full field integrated simulations throughout the life-cycle phases of field development. The solver used for the simulation provides a powerful tool to screen design alternatives to identify the optimal field solution in a cost efficient way at an early design phase. In the detailed design phase the dynamic simulations using the same full field model can be performed to ensure system operability. Similarly, in the life-of-field operation phase, the same full field model can be used to perform real time metering and monitoring as well as "look-ahead" forecasting as part of an advisory system. This is usually instrumental for a challenging field production. As the simulation model evolves since early design phase until the life-of-field operation, it promotes a comprehensive continuity. "One model one solution" provides an effective design and operation tool. Such a tool is able to provide a wide range of information that is relevant across multidisciplinary teams.

Building energy models are largely comparative in nature, from early design phase to final energy code compliance models. While there is merit in a comparative framework, with the advent of empirical compliance targets, improving the efficacy of building energy models is imperative to better align model results with future building energy consumption. To refine this alignment, even early design phase energy models should undergo proper quality checking to improve the reliability of comparative studies and yield design strategy results that will hold true in later design phases and in future building energy consumption. Subject to time or user expertise, many early design phase energy models forgo proper quality checking, which can lead to misaligned expectations when the intent for a building owner is to ultimately meet empirical compliance targets. This paper outlines an automated approach to help energy modelers efficiently quality check early design phase energy models and minimize discrepancies between comparative modeling and empirically based performance targets. The test cases presented in this paper demonstrate how quality checking improves the reliability of early comparative studies.

In a time when major technological advancements are happening at incredible rates and where demands for next-generation systems are constantly growing, advancements in failure analysis methods must constantly be developed, as well. Performance and safety are always top concerns for high-risk complex systems, and therefore, it is important for new failure analysis methods to be explored in order to obtain more useful and comprehensive failure information as early as possible, particularly during early design phases when detailed models might not yet exist. Therefore, this paper proposes a qualitative, function-based failure analysis method for early design phases that is capable of not only analyzing potential failure modes for physical components, but also for any manufacturing processes that might cause failures, as well. In this paper, the proposed method is first described in general and then applied in a case study of a proposed design for a nanochannel DNA sequencing device. Lastly, this paper discusses how more advanced and detailed analyses can be incorporated into this approach during later design phases, when more failure information becomes available.

Building energy models are largely comparative in nature, from early design phase to final energy code compliance models. While there is merit in a comparative framework, with the advent of empirical compliance targets, improving the efficacy of building energy models is imperative to better align model results with future building energy consumption. To refine this alignment, even early design phase energy models should undergo proper quality checking to improve the reliability of comparative studies and yield design strategy results that will hold true in later design phases and in future building energy consumption. Subject to time or user expertise, many early design phase energy models forgo proper quality checking, which can lead to misaligned expectations when the intent for a building owner is to ultimately meet empirical compliance targets. This paper outlines an automated approach to help energy modelers efficiently quality check early design phase energy models and minimize discrepancies between comparative modeling and empirically based performance targets. The test cases presented in this paper demonstrate how quality checking improves the reliability of early comparative studies.

Energy consumption during the use phase often contributes significantly to the overall energy demand and to the environmental impacts of an elect(on)ic product’s lifecycle. Therefore, regulations, standards, and customers tend to demand that the electronic industry supplies products with lesser consumption. However, manufacturers lack of systematic methods and tools to integrate energy consumption into their design projects from the early design phases. This paper presents the Synergico method which is meant to be incorporated in the current design practices of manufacturing companies, therefore helping design more energetically efficient electr(on)ic products without compromising the other design criteria (ergonomics, performances, usage value, quality, cost, delay, etc.). This method is based on three tools to use from the earliest design phases. Firstly, an In-Use Energy consumption indicator providing an assessment of the energy consumption during the use phase during each design phase. Thanks to the consideration of several use scenarios, it calculates values of the product’s energy consumption for each product sub-assembly, and each operating mode, thus monitoring the consumption and compliance of a product with design objectives. Secondly, a Guideline-based tool adapted to electronic products. These guidelines can easily be filtered to consider only the most relevant ones according to the context (design phase, expert concerned, scope of the guideline, etc.). Thirdly, a Lifecycle Check tool to verify that no pollution trade-offs, between life cycle phases, would hinder the design of an energy efficient product with good overall environmental performances. A case study illustrates the use and integration of the Synergico method and the way it coordinates the tools.