Surrogate modeling of RF circuit blocks

Surrogate models are a cost-effective replacement for expensive computer simulations in design space exploration. Literature has already demonstrated the feasibility of accurate surrogate models for single radio frequency (RF) and microwave devices. Within the European Marie Curie project O-MOORE-NICE! (Operational Model Order Reduction for Nanoscale IC Electronics) we aim to investigate the feasibility of the surrogate modeling approach for entire RF circuit blocks. This paper presents an overview about the surrogate model type selection problem for low noise amplifier modeling

Numerical Simulation and Customized DACM Based Design Optimization

PhD thesis in Offshore technologyThe diverse numerical modelling, analysis and simulation tools that have been developed and introduced to markets are intended to perform the virtual design and testing of products and systems without the construction of physical prototypes. Digital prototyping in the form of computer modelling and simulation are important means of numerical model predictions, i.e. design validation and verification. However, as the tools advance to more precise and diverse applications, the operation eventually becomes more complex, computationally expensive and error prone; this is particularly true for complex multi-disciplinary and multidimensional problems; for instance, in multi-body dynamics, Fluid-Structure Interaction (FSI) and high-dimensional numerical simulation problems. On the other hand, integrating design optimization operations into the product and system development processes, through the computer based applications, makes the process even more complex and highly expensive. This thesis analyses and discusses causes of complexity in numerical modelling, simulation and optimization operations and proposes new approaches/frameworks that would help significantly reduce the complexity and the associated computational costs. Proposed approaches mainly integrate, simplify and decompose or approximate complex numerical simulation based optimization problems into simpler, and to metamodel-based optimization problems. Despite advancing computational technologies in continuum mechanics, the design and analysis tools have developed in separate directions with regard to ‘basis functions’ of the technologies until recent developments. Basis functions are the building blocks of every continuous function. Continuous functions in every computational tool are linear combinations of specific basis functions in the function space. Since first introduced, basis functions in the design and modelling tools have developed so rapidly that various complex physical problems can today be designed and modelled to the highest precision. On the other hand, most analysis tools still utilize approximate models of the problems from the latter tools, particularly if the problem involves complex smooth geometric designs. The existing gap between the basis functions of the tools and the increasing precision of models for analysis introduce tremendous computational costs. Moreover, to transfer models from one form of basis function to another, additonal effort is required. The variation of the basis functions also demands extra effort in numerical simulation based optimization processes. This thesis discusses the recently developed integrated modelling and analysis approach that utilizes the state-of-the-art basis function (NURBS function) for both design and analysis. A numerical simulation based shape optimization framework that utilizes the state-of-the-art basis function is also presented in a study in the thesis. One of the common multidisciplinary problem that involves multiple models of domains in a single problem, fluid-structure interaction (FSI) problem, is studied in the thesis. As the name implies, the two models of domains involved in any FSI problems are fluid and structure domain models. In order to solve the FSI problems, usually three mathematical components are needed: namely, i) fluid dynamics model, ii) structural mechanics model and, iii) the FSI model. This thesis presents the challenges in FSI problems and discusses different FSI approaches in numerical analysis. A comparative analysis of computational methods, based on the coupling and temporal discretization schemes, is discussed using a benchmark problem, to give a better understanding of what a multidisciplinary problem is and the challenge for design optimizations that involve such problems. [...

A METAMODELLING IMPLEMENTATION OF A TWO-WAY COUPLED MESOSCALE-MICROSCALE FLOW MODEL FOR URBAN AREA SIMULATIONS

Systems of coupled prognostic mesoscale and microscale models have been used as a tool to accurately simulate flows around artificial structures and over densely-built urban areas. Typical implementations of such systems are based on a one-way coupling scheme, where the mesoscale model provides initial and boundary conditions for each off-line application of the microscale model. While very successful in predicting steady-state flows within specific local-scale areas, such schemes fail to account for feedbacks on the mesoscale flow induced by the presence of structures in smaller scales. Unfortunately, the large gap of spatial and temporal scales practically prohibits parallel on-line execution of the mesoscale and microscale models for any significant time interval. It is therefore necessary that a simplifying approach is adopted, where the microscale feedback is spatially and temporally upscaled to interact with parts of the mesoscale domain covering the urban area. In the present work a two-way coupled model system is developed, consisting of the prognostic mesoscale model MEMO and the microscale model MIMO. The microscale feedback on the mesoscale domain is simulated using a metamodelling approach, where the effect of local flows on the vertical profiles is estimated for representative urban areas of sizes up to a few hundred meters and used as calibration input for a set of interpolating metamodels. The feedback from the microscale metamodels is then introduced back in the mesoscale grid by means of Newtonian relaxation. As an illustrative application, simulations for the city of Athens, Greece during a multi-day period are presented. Effects of the microscale feedback on the mesoscale flow become evident both as a reduction of lower-level wind speeds in urban cells as well as an overall increase in turbulent kinetic energy production over densely-built areas

NOSTROMO - D5.2 - ATM Performance Metamodels - Final Release

This deliverable presents the third iteration of the development of the two micromodels Flitan and Mercury and the results obtained with them with the active learning process, as described in the deliverables D3.X. In this iteration, Flitan implemented concepts from PJ08.01 and PJ02.08, and Mercury implemented a module related to PJ07.02. Mercury also developed an additional module related to PJ01.01, which description is presented in Annex only, since no results could be produced in time with it for this deliverable. The development is presented in two different chapters for each simulator, with general descriptions referred to from D5.1. The modules related to each SESAR solution are described separately. The latest version of the meta-modelling process is described briefly, followed by the results obtained with the two simulators, in distinct sections. This chapter shows the performance of the meta-model with respect to approximating micro simulators

Surrogate Modelling with Sequential Design for Expensive Simulation Applications

The computational demands of virtual experiments for modern product development processes can get out of control due to fine resolution and detail incorporation in simulation packages. These demands for appropriate approximation strategies and reliable selection of evaluations to keep the amount of required evaluations were limited, without compromising on quality and requirements specified upfront. Surrogate models provide an appealing data‐driven strategy to accomplish these goals for applications including design space exploration, optimization, visualization or sensitivity analysis. Extended with sequential design, satisfactory solutions can be identified quickly, greatly motivating the adoption of this technology into the design process