18,642 research outputs found
Predictive maintenance for the heated hold-up tank
We present a numerical method to compute an optimal maintenance date for the
test case of the heated hold-up tank. The system consists of a tank containing
a fluid whose level is controlled by three components: two inlet pumps and one
outlet valve. A thermal power source heats up the fluid. The failure rates of
the components depends on the temperature, the position of the three components
monitors the liquid level in the tank and the liquid level determines the
temperature. Therefore, this system can be modeled by a hybrid process where
the discrete (components) and continuous (level, temperature) parts interact in
a closed loop. We model the system by a piecewise deterministic Markov process,
propose and implement a numerical method to compute the optimal maintenance
date to repair the components before the total failure of the system.Comment: arXiv admin note: text overlap with arXiv:1101.174
The instanton method and its numerical implementation in fluid mechanics
A precise characterization of structures occurring in turbulent fluid flows
at high Reynolds numbers is one of the last open problems of classical physics.
In this review we discuss recent developments related to the application of
instanton methods to turbulence. Instantons are saddle point configurations of
the underlying path integrals. They are equivalent to minimizers of the related
Freidlin-Wentzell action and known to be able to characterize rare events in
such systems. While there is an impressive body of work concerning their
analytical description, this review focuses on the question on how to compute
these minimizers numerically. In a short introduction we present the relevant
mathematical and physical background before we discuss the stochastic Burgers
equation in detail. We present algorithms to compute instantons numerically by
an efficient solution of the corresponding Euler-Lagrange equations. A second
focus is the discussion of a recently developed numerical filtering technique
that allows to extract instantons from direct numerical simulations. In the
following we present modifications of the algorithms to make them efficient
when applied to two- or three-dimensional fluid dynamical problems. We
illustrate these ideas using the two-dimensional Burgers equation and the
three-dimensional Navier-Stokes equations
Key Challenges and Opportunities in Hull Form Design Optimisation for Marine and Offshore Applications
New environmental regulations and volatile fuel
prices have resulted in an ever-increasing need for reduction
in carbon emission and fuel consumption. Designs of marine
and offshore vessels are more demanding with complex
operating requirements and oil and gas exploration
venturing into deeper waters and hasher environments.
Combinations of these factors have led to the need to
optimise the design of the hull for the marine and offshore
industry. The contribution of this paper is threefold. Firstly,
the paper provides a comprehensive review of the state-ofthe-
art techniques in hull form design. Specifically, it
analyses geometry modelling, shape transformation,
optimisation and performance evaluation. Strengths and
weaknesses of existing solutions are also discussed.
Secondly, key challenges of hull form optimisation specific
to the design of marine and offshore vessels are identified
and analysed. Thirdly, future trends in performing hull
form design optimisation are investigated and possible
solutions proposed. A case study on the design optimisation
of bulbous bow for passenger ferry vessel to reduce wavemaking
resistance is presented using NAPA software.
Lastly, main issues and challenges are discussed to stimulate
further ideas on future developments in this area, including
the use of parallel computing and machine intelligence
Hybridization of multi-objective deterministic particle swarm with derivative-free local searches
The paper presents a multi-objective derivative-free and deterministic global/local hybrid algorithm for the efficient and effective solution of simulation-based design optimization (SBDO) problems. The objective is to show how the hybridization of two multi-objective derivative-free global and local algorithms achieves better performance than the separate use of the two algorithms in solving specific SBDO problems for hull-form design. The proposed method belongs to the class of memetic algorithms, where the global exploration capability of multi-objective deterministic particle swarm optimization is enriched by exploiting the local search accuracy of a derivative-free multi-objective line-search method. To the authors best knowledge, studies are still limited on memetic, multi-objective, deterministic, derivative-free, and evolutionary algorithms for an effective and efficient solution of SBDO for hull-form design. The proposed formulation manages global and local searches based on the hypervolume metric. The hybridization scheme uses two parameters to control the local search activation and the number of function calls used by the local algorithm. The most promising values of these parameters were identified using forty analytical tests representative of the SBDO problem of interest. The resulting hybrid algorithm was finally applied to two SBDO problems for hull-form design. For both analytical tests and SBDO problems, the hybrid method achieves better performance than its global and local counterparts
State of the Art in the Optimisation of Wind Turbine Performance Using CFD
Wind energy has received increasing attention in recent years due to its sustainability and geographically wide availability. The efficiency of wind energy utilisation highly depends on the performance of wind turbines, which convert the kinetic energy in wind into electrical energy. In order to optimise wind turbine performance and reduce the cost of next-generation wind turbines, it is crucial to have a view of the state of the art in the key aspects on the performance optimisation of wind turbines using Computational Fluid Dynamics (CFD), which has attracted enormous interest in the development of next-generation wind turbines in recent years. This paper presents a comprehensive review of the state-of-the-art progress on optimisation of wind turbine performance using CFD, reviewing the objective functions to judge the performance of wind turbine, CFD approaches applied in the simulation of wind turbines and optimisation algorithms for wind turbine performance. This paper has been written for both researchers new to this research area by summarising underlying theory whilst presenting a comprehensive review on the up-to-date studies, and experts in the field of study by collecting a comprehensive list of related references where the details of computational methods that have been employed lately can be obtained
Hypervolume-based Multi-objective Bayesian Optimization with Student-t Processes
Student- processes have recently been proposed as an appealing alternative
non-parameteric function prior. They feature enhanced flexibility and
predictive variance. In this work the use of Student- processes are explored
for multi-objective Bayesian optimization. In particular, an analytical
expression for the hypervolume-based probability of improvement is developed
for independent Student- process priors of the objectives. Its effectiveness
is shown on a multi-objective optimization problem which is known to be
difficult with traditional Gaussian processes.Comment: 5 pages, 3 figure
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