Strategies for initial sizing and operating point analysis of analog circuits

This study estimated availability of an air compression system and a nitrogen generation system in liquefied natural gas—floating production storage and offloading unit (LNG-FPSO) with different design stages to investigate the gap between the availability at the early design stage and that at the late design stage. Although availability estimation in the early design stage is more important than the late design stage, it is difficult to estimate the availability accurately in the early design stage. The design stage was divided into three depending on the design progress. Monte Carlo simulation technique was employed for the availability estimation. The results of the availability estimation showed that there was 0.434% difference between the early and late design stages. This meant that the availability in the early design stage was underestimated due to limited information. A sensitivity analysis was performed to investigate critical factors affecting the results. The investigated factors were failure rate, repair time, redundant equipment, and modified preventive maintenance schedule. The most critical factor was redundant equipment. It increased 0.486% availability.

The solution of a system of nonlinear algebraic or transcendental equations is probably one of the most difficult problems in numerical analysis. In general, it is almost impossible to find the solution, unless an approximate value is already known. Linear equations occur more frequently in numerical calculations, simply because it is difficult and sometimes impossible to solve the corresponding nonlinear problem. Most of the equations governing the physical world are nonlinear, but very often for simplicity and tractability linear models are considered. Solution of boundary value problems for differential equations also lead to a nonlinear equation or a system of nonlinear equations. Solution of a system of nonlinear equations also arises in numerical analysis, while deriving certain formulae. As we have seen in Chapter 6, the Gaussian quadrature formulae can be obtained by solving a system of nonlinear equations.

Abstract: In this paper, we apply the Homotopy Perturbation Transform Method (HPTM) to obtain the solution of Non-Linear RLC Circuit Equation. This method is a combination of the Laplace transform method with the homotopy perturbation method. The HPTM can provide analytical solutions to nonlinear equations just by employing the initial conditions and the nonlinear term decomposed by using the He’s polynomials. Keywords: Homotopy perturbation, Laplace transform, He’s polynomials, Non-linear RLC circuit equation.

Effective design collaboration during the early design stages in architecture is a condition for effective overall design and construction. This can be facilitated, supported and promoted through visual technological means. Collaborative design protocols implemented within the engineering fields (electrical and mechanical) can be adapted to the built environment design with emerging augmented reality technologies being the enablers for that shift. Architectural design requires a strongly visual approach to communication and means through which multiple disciples can collaborate effectively. Therefore, the aim of the research is to investigate principles and protocols to assist early design stage collaborative design among multidisciplinary teams, through visual and tactile user interfaces. This paper explores the current paradigm in AEC (architecture, engineering and construction), design collaboration and multidisciplinary group dynamics during the early design and conceptual stages in architecture. Afterwards, a design protocol is suggested, literature review regarding collaborative design and design protocols is summarized and further research is proposed on optimization and standardization of early design collaborative design in AEC.

Supplier involvement in automotive component design: are there really large US Japan differences?

Design for energy efficiency in early stages: A top-down method for new product development

Life Cycle Assessment (LCA) is used and accepted as a method to assess environmental impacts and resource use of buildings. In practice, LCA is typically used in stages where the design of the building is already finalized. However, LCA-calculations from early design stages can be used actively in design and optimization of the building. One of the obstacles to early stage LCA is that extensive data input on precise material types and amounts is needed, which is limited in early design stages. The simplifications needed for a designer in an early design LCA is addressed in a research project, where an extensive library of predefined building components and installations were developed and integrated into the existing Danish LCAbyg tool. The library assists the user in establishing a full building inventory by simple inputs of geometry of the building and a selection from the library of building element layers. However, the simplified approach to LCA of a building at early design stages inevitably affects results compared with results of a calculation made at later design stages where more, specific data is available. This paper presents an evaluation of building cases, modelled with the same background database and life cycle stages, using the simplified early design LCA approach and a detailed LCA approach. The evaluation includes testing of how well the predefined components in the early design approach fit with the case buildings and comparisons of the total material input and precision of the final LCA results.

Differential — algebraic equations (DAE) differ from other problems with solutions given by smooth and continuous parametric sets. They combine specifics of the nonlinear algebraic or transcendental equations with those of ODE. Correct formulation of the Cauchy problem for such equations requires solution of a system of nonlinear equations. In this chapter we will describe and investigate the algorithm of numerical continuation of Cauchy problem solution for different forms of DAE.

A hybrid metamodel-based method for quick energy prediction in the early design stage

A novel harmonic balance surrogate-based technique to create fast and accurate behavioral models predicting, in the early design stage, the performance of nonlinear analog devices during immunity tests is presented. The obtained immunity model hides the real netlist, reduces the simulation time, and avoids expensive and time-consuming measurements after tape-out, while still providing high accuracy. The model can easily be integrated into a circuit simulator together with additional subcircuits, e.g., board and package models, as such allowing to efficiently reproduce complete immunity test setups during the early design stage and without disclosing any intellectual property. The novel method is validated by means of application to an industrial case study, being an automotive voltage regulator, clearly showing the technique's capabilities and practical advantages.

Constructability is a concept with relative and not absolute value to increase optimization capacity of resources such as workforce, time, cost, quality, and working environment conditions. Given the growing complexity of projects and the increased number of failed and abandoned projects, the necessity to implement constructability in projects has become more tangible. Although the effects of lack of quantitative definition of constructability role in the traditional construction approaches are evident and have led to lack of coordination in performance of construction projects, so far no comprehensive quantitative approach has been considered to analyze the obstacles to constructability implementation. This study aims to identify and categorize the obstacles to facilitating the presence of contractors in the early stages of planning and design to implement constructability. In this study a comprehensive list of obstacles to constructability implementation is developed as a questionnaire. This questionnaire was presented to the experts, active in the field of construction. Finally, its results were analyzed using exploratory factor analysis method. Totally, 63 obstacles were questioned, then they were categorized by some of the experts of this industry into five categories of macro factors, including contractual, environmental, managerial, technical, and organizational. The significance of this study is due to this fact that identifying and categorizing the key obstacles to constructability implementation provides a useful reference for managers and owners of the construction industry to identify and develop solutions to resolve them. Identifying the obstacles to the presence of contractors in the planning and design stage and having a quantitative view toward this issue affects project implementability. In this regard, one can present more effective solutions to facilitate the presence of contractors in the early stages of design and also improves the effectiveness of constructability.

Introduction (problem statement and relevance). The need to increase the operating speeds and input torque of automobile transmissions because of their vibration is becoming a more and more urgent problem.The purpose of the study was to substantiate the applicability of harmonic analysis, which makes it possible to determine the actual values of vibration values during a steady oscillatory process, for the initial assessment of the gearbox vibration activity.Methodology and research methods. The calculation of the gearbox vibration activity was carried out by modal and harmonic analyses, implemented by the finite element method, and followed by the experimental study of gearbox vibration on a test bench.Scientific novelty and results. The presented experimental and calculated results of the research show that the difference between the experimental and calculated values is no more than 4.2%. This proves the possibility of applying modal and harmonic analysis to predict the gearbox vibration state at an early stage of product design at the stand.Practical significance. The given calculation algorithm makes it possible to predict, with a sufficient degree of accuracy, the vibration of the gearbox before the manufacture of a prototype in experimental production.

Some important parameters of the machine tool layout have to be selected in the early stages of design when a shortage of information makes application of the finite element method impractical. As a computer-aided tool in these stages, the form-shaping function (FSF)-based approach can be used. It allows evaluation of the kinematic and geometric errors and compliance issue static deformations, which contribute significantly to the total machining error as applied to precision machine tools. The FSF-based methodology gives important information allowing layouts’ comparison and structure optimization under uncertainty in requirements and limitations relating to the designed machine under strong time constraints. Six different layouts of a turning center are investigated to compare the effect of geometrical errors and compliance of machine structure on part accuracy in the range of less than five microns. Motion errors of machine tool components were measured by laser equipment during machine tool assembly and inspection. Compliance-induced errors are included in the evaluation to take into consideration cutting forces. Obtained data were used as the input for simulation of machining a sample workpiece—a sphere whose size, position, and form errors are used as criteria for layout comparison. Since the FSF-based results correlate well with the experimental data, the developed approach can be considered as an effective tool for application in the early stages of machine design.

Life cycle assessment (LCA) is generally considered as a suitable methodology for the evaluation of environmental impacts of processes. However, it requires large amount and often inaccessible process data at early design stages. The present study provides an approach to streamline LCA for a broad set of biomass process chains. The proposed method breaks away from conventional LCA work in that the purpose is to support decision at early stages assuming minimal use of data available and points to most dominant LCA impacts, providing useful feedback to process design. The prediction mechanism employs decision trees, which form “if-then rules” using a set of critical parameters of the process chain with respect to various environmental impacts. The models classify products into three classes, namely having low, medium, and high environmental impact. Data for model development were obtained from early design stages and include descriptors of the molecular structure of the product and process chain-related variables corresponding to chemistry, complexity, and generic process conditions. Twenty-three LCA metrics were selected as target attributes, according to the ReCiPe and the cumulative energy demand (CED) methods. A broad set of process chains is derived from the work of Karka et al. (Int J Life Cycle Assess 22(9):1418–1440, 2017). Results demonstrate that the average classification error for the decision trees ranges between 13.4 and 43.8% for the various LCA metrics and multifunctionality approaches. Allocation approaches present a better classification performance (up to 25% error) compared with the substitution approach for LCA metrics, such as climate change, CED, and human health. For the majority of models, low- and high-output classes are characterized by better predictive performance compared with the medium class. The interpretability of selected decision trees is analyzed in terms of pruning levels and “irrational” branches. The results of the application of the decision tress for recently published case studies show for instance that 8 out of 13 cases were correctly classified for CED. The proposed approach provides a first generation of models in the form of computationally inexpensive and easily interpretable decision trees that can be used as pre-screening tools for the environmental assessment of bio-based production ahead of detailed design and conventional LCA approaches. The transparent structure of the decision trees facilitates the identification of critical decision variables providing insights for improvement in terms of process parameters, biomass feedstock, or even targeted product.

Visualized strategy for predicting buildings energy consumption during early design stage using parametric analysis