Exploration of automatic optimisation for CUDA programming

KAUST Repository

Al-Mouhamed, Mayez; Khan, Ayaz ul Hassan

2014-01-01

© 2014 Taylor & Francis. Writing optimised compute unified device architecture (CUDA) program for graphic processing units (GPUs) is complex even for experts. We present a design methodology for a restructuring tool that converts C-loops into optimised CUDA kernels based on a three-step algorithm which are loop tiling, coalesced memory access and resource optimisation. A method for finding possible loop tiling solutions with coalesced memory access is developed and a simplified algorithm for restructuring C-loops into an efficient CUDA kernel is presented. In the evaluation, we implement matrix multiply (MM), matrix transpose (M-transpose), matrix scaling (M-scaling) and matrix vector multiply (MV) using the proposed algorithm. We present the analysis of the execution time and GPU throughput for the above applications, which favourably compare to other proposals. Evaluation is carried out while scaling the problem size and running under a variety of kernel configurations. The obtained speedup is about 28-35% for M-transpose compared to NVIDIA Software Development Kit, 33% speedup for MV compared to general purpose computation on graphics processing unit compiler, and more than 80% speedup for MM and M-scaling compared to CUDA-lite.

Exploration of automatic optimisation for CUDA programming

KAUST Repository

Al-Mouhamed, Mayez

2014-09-16

© 2014 Taylor & Francis. Writing optimised compute unified device architecture (CUDA) program for graphic processing units (GPUs) is complex even for experts. We present a design methodology for a restructuring tool that converts C-loops into optimised CUDA kernels based on a three-step algorithm which are loop tiling, coalesced memory access and resource optimisation. A method for finding possible loop tiling solutions with coalesced memory access is developed and a simplified algorithm for restructuring C-loops into an efficient CUDA kernel is presented. In the evaluation, we implement matrix multiply (MM), matrix transpose (M-transpose), matrix scaling (M-scaling) and matrix vector multiply (MV) using the proposed algorithm. We present the analysis of the execution time and GPU throughput for the above applications, which favourably compare to other proposals. Evaluation is carried out while scaling the problem size and running under a variety of kernel configurations. The obtained speedup is about 28-35% for M-transpose compared to NVIDIA Software Development Kit, 33% speedup for MV compared to general purpose computation on graphics processing unit compiler, and more than 80% speedup for MM and M-scaling compared to CUDA-lite.

Shape optimisation and performance analysis of flapping wings

KAUST Repository

Ghommem, Mehdi

2012-09-04

In this paper, shape optimisation of flapping wings in forward flight is considered. This analysis is performed by combining a local gradient-based optimizer with the unsteady vortex lattice method (UVLM). Although the UVLM applies only to incompressible, inviscid flows where the separation lines are known a priori, Persson et al. [1] showed through a detailed comparison between UVLM and higher-fidelity computational fluid dynamics methods for flapping flight that the UVLM schemes produce accurate results for attached flow cases and even remain trend-relevant in the presence of flow separation. As such, they recommended the use of an aerodynamic model based on UVLM to perform preliminary design studies of flapping wing vehicles Unlike standard computational fluid dynamics schemes, this method requires meshing of the wing surface only and not of the whole flow domain [2]. From the design or optimisation perspective taken in our work, it is fairly common (and sometimes entirely necessary, as a result of the excessive computational cost of the highest fidelity tools such as Navier-Stokes solvers) to rely upon such a moderate level of modelling fidelity to traverse the design space in an economical manner. The objective of the work, described in this paper, is to identify a set of optimised shapes that maximise the propulsive efficiency, defined as the ratio of the propulsive power over the aerodynamic power, under lift, thrust, and area constraints. The shape of the wings is modelled using B-splines, a technology used in the computer-aided design (CAD) field for decades. This basis can be used to smoothly discretize wing shapes with few degrees of freedom, referred to as control points. The locations of the control points constitute the design variables. The results suggest that changing the shape yields significant improvement in the performance of the flapping wings. The optimisation pushes the design to "bird-like" shapes with substantial increase in the time

Probabilistic sensitivity analysis of optimised preventive maintenance strategies for deteriorating infrastructure assets

International Nuclear Information System (INIS)

Daneshkhah, A.; Stocks, N.G.; Jeffrey, P.

2017-01-01

Efficient life-cycle management of civil infrastructure systems under continuous deterioration can be improved by studying the sensitivity of optimised preventive maintenance decisions with respect to changes in model parameters. Sensitivity analysis in maintenance optimisation problems is important because if the calculation of the cost of preventive maintenance strategies is not sufficiently robust, the use of the maintenance model can generate optimised maintenances strategies that are not cost-effective. Probabilistic sensitivity analysis methods (particularly variance based ones), only partially respond to this issue and their use is limited to evaluating the extent to which uncertainty in each input contributes to the overall output's variance. These methods do not take account of the decision-making problem in a straightforward manner. To address this issue, we use the concept of the Expected Value of Perfect Information (EVPI) to perform decision-informed sensitivity analysis: to identify the key parameters of the problem and quantify the value of learning about certain aspects of the life-cycle management of civil infrastructure system. This approach allows us to quantify the benefits of the maintenance strategies in terms of expected costs and in the light of accumulated information about the model parameters and aspects of the system, such as the ageing process. We use a Gamma process model to represent the uncertainty associated with asset deterioration, illustrating the use of EVPI to perform sensitivity analysis on the optimisation problem for age-based and condition-based preventive maintenance strategies. The evaluation of EVPI indices is computationally demanding and Markov Chain Monte Carlo techniques would not be helpful. To overcome this computational difficulty, we approximate the EVPI indices using Gaussian process emulators. The implications of the worked numerical examples discussed in the context of analytical efficiency and organisational

Computational intelligence-based polymerase chain reaction primer selection based on a novel teaching-learning-based optimisation.

Science.gov (United States)

Cheng, Yu-Huei

2014-12-01

Specific primers play an important role in polymerase chain reaction (PCR) experiments, and therefore it is essential to find specific primers of outstanding quality. Unfortunately, many PCR constraints must be simultaneously inspected which makes specific primer selection difficult and time-consuming. This paper introduces a novel computational intelligence-based method, Teaching-Learning-Based Optimisation, to select the specific and feasible primers. The specified PCR product lengths of 150-300 bp and 500-800 bp with three melting temperature formulae of Wallace's formula, Bolton and McCarthy's formula and SantaLucia's formula were performed. The authors calculate optimal frequency to estimate the quality of primer selection based on a total of 500 runs for 50 random nucleotide sequences of 'Homo species' retrieved from the National Center for Biotechnology Information. The method was then fairly compared with the genetic algorithm (GA) and memetic algorithm (MA) for primer selection in the literature. The results show that the method easily found suitable primers corresponding with the setting primer constraints and had preferable performance than the GA and the MA. Furthermore, the method was also compared with the common method Primer3 according to their method type, primers presentation, parameters setting, speed and memory usage. In conclusion, it is an interesting primer selection method and a valuable tool for automatic high-throughput analysis. In the future, the usage of the primers in the wet lab needs to be validated carefully to increase the reliability of the method.

Power law-based local search in spider monkey optimisation for lower order system modelling

Science.gov (United States)

Sharma, Ajay; Sharma, Harish; Bhargava, Annapurna; Sharma, Nirmala

2017-01-01

The nature-inspired algorithms (NIAs) have shown efficiency to solve many complex real-world optimisation problems. The efficiency of NIAs is measured by their ability to find adequate results within a reasonable amount of time, rather than an ability to guarantee the optimal solution. This paper presents a solution for lower order system modelling using spider monkey optimisation (SMO) algorithm to obtain a better approximation for lower order systems and reflects almost original higher order system's characteristics. Further, a local search strategy, namely, power law-based local search is incorporated with SMO. The proposed strategy is named as power law-based local search in SMO (PLSMO). The efficiency, accuracy and reliability of the proposed algorithm is tested over 20 well-known benchmark functions. Then, the PLSMO algorithm is applied to solve the lower order system modelling problem.

Comparison of the genetic algorithm and incremental optimisation routines for a Bayesian inverse modelling based network design

Science.gov (United States)

Nickless, A.; Rayner, P. J.; Erni, B.; Scholes, R. J.

2018-05-01

The design of an optimal network of atmospheric monitoring stations for the observation of carbon dioxide (CO2) concentrations can be obtained by applying an optimisation algorithm to a cost function based on minimising posterior uncertainty in the CO2 fluxes obtained from a Bayesian inverse modelling solution. Two candidate optimisation methods assessed were the evolutionary algorithm: the genetic algorithm (GA), and the deterministic algorithm: the incremental optimisation (IO) routine. This paper assessed the ability of the IO routine in comparison to the more computationally demanding GA routine to optimise the placement of a five-member network of CO2 monitoring sites located in South Africa. The comparison considered the reduction in uncertainty of the overall flux estimate, the spatial similarity of solutions, and computational requirements. Although the IO routine failed to find the solution with the global maximum uncertainty reduction, the resulting solution had only fractionally lower uncertainty reduction compared with the GA, and at only a quarter of the computational resources used by the lowest specified GA algorithm. The GA solution set showed more inconsistency if the number of iterations or population size was small, and more so for a complex prior flux covariance matrix. If the GA completed with a sub-optimal solution, these solutions were similar in fitness to the best available solution. Two additional scenarios were considered, with the objective of creating circumstances where the GA may outperform the IO. The first scenario considered an established network, where the optimisation was required to add an additional five stations to an existing five-member network. In the second scenario the optimisation was based only on the uncertainty reduction within a subregion of the domain. The GA was able to find a better solution than the IO under both scenarios, but with only a marginal improvement in the uncertainty reduction. These results suggest

Robustness analysis of bogie suspension components Pareto optimised values

Science.gov (United States)

Mousavi Bideleh, Seyed Milad

2017-08-01

Bogie suspension system of high speed trains can significantly affect vehicle performance. Multiobjective optimisation problems are often formulated and solved to find the Pareto optimised values of the suspension components and improve cost efficiency in railway operations from different perspectives. Uncertainties in the design parameters of suspension system can negatively influence the dynamics behaviour of railway vehicles. In this regard, robustness analysis of a bogie dynamics response with respect to uncertainties in the suspension design parameters is considered. A one-car railway vehicle model with 50 degrees of freedom and wear/comfort Pareto optimised values of bogie suspension components is chosen for the analysis. Longitudinal and lateral primary stiffnesses, longitudinal and vertical secondary stiffnesses, as well as yaw damping are considered as five design parameters. The effects of parameter uncertainties on wear, ride comfort, track shift force, stability, and risk of derailment are studied by varying the design parameters around their respective Pareto optimised values according to a lognormal distribution with different coefficient of variations (COVs). The robustness analysis is carried out based on the maximum entropy concept. The multiplicative dimensional reduction method is utilised to simplify the calculation of fractional moments and improve the computational efficiency. The results showed that the dynamics response of the vehicle with wear/comfort Pareto optimised values of bogie suspension is robust against uncertainties in the design parameters and the probability of failure is small for parameter uncertainties with COV up to 0.1.

Group search optimiser-based optimal bidding strategies with no Karush-Kuhn-Tucker optimality conditions

Science.gov (United States)

Yadav, Naresh Kumar; Kumar, Mukesh; Gupta, S. K.

2017-03-01

General strategic bidding procedure has been formulated in the literature as a bi-level searching problem, in which the offer curve tends to minimise the market clearing function and to maximise the profit. Computationally, this is complex and hence, the researchers have adopted Karush-Kuhn-Tucker (KKT) optimality conditions to transform the model into a single-level maximisation problem. However, the profit maximisation problem with KKT optimality conditions poses great challenge to the classical optimisation algorithms. The problem has become more complex after the inclusion of transmission constraints. This paper simplifies the profit maximisation problem as a minimisation function, in which the transmission constraints, the operating limits and the ISO market clearing functions are considered with no KKT optimality conditions. The derived function is solved using group search optimiser (GSO), a robust population-based optimisation algorithm. Experimental investigation is carried out on IEEE 14 as well as IEEE 30 bus systems and the performance is compared against differential evolution-based strategic bidding, genetic algorithm-based strategic bidding and particle swarm optimisation-based strategic bidding methods. The simulation results demonstrate that the obtained profit maximisation through GSO-based bidding strategies is higher than the other three methods.

A comparison of an energy/economic-based against an exergoeconomic-based multi-objective optimisation for low carbon building energy design

International Nuclear Information System (INIS)

García Kerdan, Iván; Raslan, Rokia; Ruyssevelt, Paul; Morillón Gálvez, David

2017-01-01

This study presents a comparison of the optimisation of building energy retrofit strategies from two different perspectives: an energy/economic-based analysis and an exergy/exergoeconomic-based analysis. A recently retrofitted community centre is used as a case study. ExRET-Opt, a novel building energy/exergy simulation tool with multi-objective optimisation capabilities based on NSGA-II is used to run both analysis. The first analysis, based on the 1st Law only, simultaneously optimises building energy use and design's Net Present Value (NPV). The second analysis, based on the 1st and the 2nd Laws, simultaneously optimises exergy destructions and the exergoeconomic cost-benefit index. Occupant thermal comfort is considered as a common objective function for both approaches. The aim is to assess the difference between the methods and calculate the performance among main indicators, considering the same decision variables and constraints. Outputs show that the inclusion of exergy/exergoeconomics as objective functions into the optimisation procedure has resulted in similar 1st Law and thermal comfort outputs, while providing solutions with less environmental impact under similar capital investments. This outputs demonstrate how the 1st Law is only a necessary calculation while the utilisation of the 1st and 2nd Laws becomes a sufficient condition for the analysis and design of low carbon buildings. - Highlights: • The study compares an energy-based and an exergy-based building design optimisation. • Occupant thermal comfort is considered as a common objective function. • A comparison of thermodynamic outputs is made against the actual retrofit design. • Under similar constraints, second law optimisation presents better overall results. • Exergoeconomic optimisation solutions improves building exergy efficiency to double.

Biomass supply chain optimisation for Organosolv-based biorefineries.

Science.gov (United States)

Giarola, Sara; Patel, Mayank; Shah, Nilay

2014-05-01

This work aims at providing a Mixed Integer Linear Programming modelling framework to help define planning strategies for the development of sustainable biorefineries. The up-scaling of an Organosolv biorefinery was addressed via optimisation of the whole system economics. Three real world case studies were addressed to show the high-level flexibility and wide applicability of the tool to model different biomass typologies (i.e. forest fellings, cereal residues and energy crops) and supply strategies. Model outcomes have revealed how supply chain optimisation techniques could help shed light on the development of sustainable biorefineries. Feedstock quality, quantity, temporal and geographical availability are crucial to determine biorefinery location and the cost-efficient way to supply the feedstock to the plant. Storage costs are relevant for biorefineries based on cereal stubble, while wood supply chains present dominant pretreatment operations costs. Copyright © 2014 Elsevier Ltd. All rights reserved.

Optimisation of gas-cooled reactors with the aid of mathematical computers

Energy Technology Data Exchange (ETDEWEB)

Margen, P H

1959-04-15

Reactor optimisation is the task of finding the combination of values of the independent variables in a reactor design producing the lowest cost of electricity. In a gas-cooled reactor the number of independent variables is particularly large and the optimisation process is, therefore, laborious. The present note describes a procedure for performing the entire optimisation procedure with the aid of a mathematical computer in a single operation, thus saving time for the design staff. Detailed equations and numerical constants are proposed for the thermal and cost relations involved. The reactor physics equations, on the other hand are merely stated as general functions of the relevant variables. The task of expressing these functions as detailed equations will be covered by separate documents prepared by the reactor physics department.

Optimisation of gas-cooled reactors with the aid of mathematical computers

International Nuclear Information System (INIS)

Margen, P.H.

1959-04-01

Reactor optimisation is the task of finding the combination of values of the independent variables in a reactor design producing the lowest cost of electricity. In a gas-cooled reactor the number of independent variables is particularly large and the optimisation process is, therefore, laborious. The present note describes a procedure for performing the entire optimisation procedure with the aid of a mathematical computer in a single operation, thus saving time for the design staff. Detailed equations and numerical constants are proposed for the thermal and cost relations involved. The reactor physics equations, on the other hand are merely stated as general functions of the relevant variables. The task of expressing these functions as detailed equations will be covered by separate documents prepared by the reactor physics department

Study on the evolutionary optimisation of the topology of network control systems

Science.gov (United States)

Zhou, Zude; Chen, Benyuan; Wang, Hong; Fan, Zhun

2010-08-01

Computer networks have been very popular in enterprise applications. However, optimisation of network designs that allows networks to be used more efficiently in industrial environment and enterprise applications remains an interesting research topic. This article mainly discusses the topology optimisation theory and methods of the network control system based on switched Ethernet in an industrial context. Factors that affect the real-time performance of the industrial control network are presented in detail, and optimisation criteria with their internal relations are analysed. After the definition of performance parameters, the normalised indices for the evaluation of the topology optimisation are proposed. The topology optimisation problem is formulated as a multi-objective optimisation problem and the evolutionary algorithm is applied to solve it. Special communication characteristics of the industrial control network are considered in the optimisation process. In respect to the evolutionary algorithm design, an improved arena algorithm is proposed for the construction of the non-dominated set of the population. In addition, for the evaluation of individuals, the integrated use of the dominative relation method and the objective function combination method, for reducing the computational cost of the algorithm, are given. Simulation tests show that the performance of the proposed algorithm is preferable and superior compared to other algorithms. The final solution greatly improves the following indices: traffic localisation, traffic balance and utilisation rate balance of switches. In addition, a new performance index with its estimation process is proposed.

Agent-Based Decision Control—How to Appreciate Multivariate Optimisation in Architecture

DEFF Research Database (Denmark)

Negendahl, Kristoffer; Perkov, Thomas Holmer; Kolarik, Jakub

2015-01-01

, the method is applied to a multivariate optimisation problem. The aim is specifically to demonstrate optimisation for entire building energy consumption, daylight distribution and capital cost. Based on the demonstrations Moth’s ability to find local minima is discussed. It is concluded that agent-based...... in the early design stage. The main focus is to demonstrate the optimisation method, which is done in two ways. Firstly, the newly developed agent-based optimisation algorithm named Moth is tested on three different single objective search spaces. Here Moth is compared to two evolutionary algorithms. Secondly...... optimisation algorithms like Moth open up for new uses of optimisation in the early design stage. With Moth the final outcome is less dependent on pre- and post-processing, and Moth allows user intervention during optimisation. Therefore, agent-based models for optimisation such as Moth can be a powerful...

Crystal structure optimisation using an auxiliary equation of state

Science.gov (United States)

Jackson, Adam J.; Skelton, Jonathan M.; Hendon, Christopher H.; Butler, Keith T.; Walsh, Aron

2015-11-01

Standard procedures for local crystal-structure optimisation involve numerous energy and force calculations. It is common to calculate an energy-volume curve, fitting an equation of state around the equilibrium cell volume. This is a computationally intensive process, in particular, for low-symmetry crystal structures where each isochoric optimisation involves energy minimisation over many degrees of freedom. Such procedures can be prohibitive for non-local exchange-correlation functionals or other "beyond" density functional theory electronic structure techniques, particularly where analytical gradients are not available. We present a simple approach for efficient optimisation of crystal structures based on a known equation of state. The equilibrium volume can be predicted from one single-point calculation and refined with successive calculations if required. The approach is validated for PbS, PbTe, ZnS, and ZnTe using nine density functionals and applied to the quaternary semiconductor Cu2ZnSnS4 and the magnetic metal-organic framework HKUST-1.

Crystal structure optimisation using an auxiliary equation of state

International Nuclear Information System (INIS)

Jackson, Adam J.; Skelton, Jonathan M.; Hendon, Christopher H.; Butler, Keith T.; 3 Institute and Department of Materials Science and Engineering, Yonsei University, Seoul 120-749 (Korea, Republic of))" data-affiliation=" (Centre for Sustainable Chemical Technologies and Department of Chemistry, University of Bath, Claverton Down, Bath BA2 7AY (United Kingdom); Global E3 Institute and Department of Materials Science and Engineering, Yonsei University, Seoul 120-749 (Korea, Republic of))" >Walsh, Aron

2015-01-01

Standard procedures for local crystal-structure optimisation involve numerous energy and force calculations. It is common to calculate an energy–volume curve, fitting an equation of state around the equilibrium cell volume. This is a computationally intensive process, in particular, for low-symmetry crystal structures where each isochoric optimisation involves energy minimisation over many degrees of freedom. Such procedures can be prohibitive for non-local exchange-correlation functionals or other “beyond” density functional theory electronic structure techniques, particularly where analytical gradients are not available. We present a simple approach for efficient optimisation of crystal structures based on a known equation of state. The equilibrium volume can be predicted from one single-point calculation and refined with successive calculations if required. The approach is validated for PbS, PbTe, ZnS, and ZnTe using nine density functionals and applied to the quaternary semiconductor Cu 2 ZnSnS 4 and the magnetic metal-organic framework HKUST-1

Crystal structure optimisation using an auxiliary equation of state

Energy Technology Data Exchange (ETDEWEB)

Jackson, Adam J.; Skelton, Jonathan M.; Hendon, Christopher H.; Butler, Keith T. [Centre for Sustainable Chemical Technologies and Department of Chemistry, University of Bath, Claverton Down, Bath BA2 7AY (United Kingdom); Walsh, Aron, E-mail: a.walsh@bath.ac.uk [Centre for Sustainable Chemical Technologies and Department of Chemistry, University of Bath, Claverton Down, Bath BA2 7AY (United Kingdom); Global E" 3 Institute and Department of Materials Science and Engineering, Yonsei University, Seoul 120-749 (Korea, Republic of)

2015-11-14

Standard procedures for local crystal-structure optimisation involve numerous energy and force calculations. It is common to calculate an energy–volume curve, fitting an equation of state around the equilibrium cell volume. This is a computationally intensive process, in particular, for low-symmetry crystal structures where each isochoric optimisation involves energy minimisation over many degrees of freedom. Such procedures can be prohibitive for non-local exchange-correlation functionals or other “beyond” density functional theory electronic structure techniques, particularly where analytical gradients are not available. We present a simple approach for efficient optimisation of crystal structures based on a known equation of state. The equilibrium volume can be predicted from one single-point calculation and refined with successive calculations if required. The approach is validated for PbS, PbTe, ZnS, and ZnTe using nine density functionals and applied to the quaternary semiconductor Cu{sub 2}ZnSnS{sub 4} and the magnetic metal-organic framework HKUST-1.

Optimising Reactive Control in non-ideal Efficiency Wave Energy Converters

DEFF Research Database (Denmark)

Strager, Thomas; Lopez, Pablo Fernandez; Giorgio, Giuseppe

2014-01-01

When analytically optimising the control strategy in wave energy converters which use a point absorber, the efficiency aspect is generally neglected. The results presented in this paper provide an analytical expression for the mean harvested electrical power in non-ideal efficiency situations....... These have been derived under the assumptions of monochromatic incoming waves and linear system behaviour. This allows to establish the power factor of a system with non-ideal efficiency. The locus of the optimal reactive control parameters is then studied and an alternative method of representation...... is developed to model the optimal control parameters. Ultimately we present a simple method of choosing optimal control parameters for any combination of efficiency and wave frequency....

Comprehensive optimisation of China’s energy prices, taxes and subsidy policies based on the dynamic computable general equilibrium model

International Nuclear Information System (INIS)

He, Y.X.; Liu, Y.Y.; Du, M.; Zhang, J.X.; Pang, Y.X.

2015-01-01

Highlights: • Energy policy is defined as a complication of energy price, tax and subsidy policies. • The maximisation of total social benefit is the optimised objective. • A more rational carbon tax ranges from 10 to 20 Yuan/ton under the current situation. • The optimal coefficient pricing is more conducive to maximise total social benefit. - Abstract: Under the condition of increasingly serious environmental pollution, rational energy policy plays an important role in the practical significance of energy conservation and emission reduction. This paper defines energy policies as the compilation of energy prices, taxes and subsidy policies. Moreover, it establishes the optimisation model of China’s energy policy based on the dynamic computable general equilibrium model, which maximises the total social benefit, in order to explore the comprehensive influences of a carbon tax, the sales pricing mechanism and the renewable energy fund policy. The results show that when the change rates of gross domestic product and consumer price index are ±2%, ±5% and the renewable energy supply structure ratio is 7%, the more reasonable carbon tax ranges from 10 to 20 Yuan/ton, and the optimal coefficient pricing mechanism is more conducive to the objective of maximising the total social benefit. From the perspective of optimising the overall energy policies, if the upper limit of change rate in consumer price index is 2.2%, the existing renewable energy fund should be improved

Beam position optimisation for IMRT

International Nuclear Information System (INIS)

Holloway, L.; Hoban, P.

2001-01-01

Full text: The introduction of IMRT has not generally resulted in the use of optimised beam positions because to find the global solution of the problem a time consuming stochastic optimisation method must be used. Although a deterministic method may not achieve the global minimum it should achieve a superior dose distribution compared to no optimisation. This study aimed to develop and test such a method. The beam optimisation method developed relies on an iterative process to achieve the desired number of beams from a large initial number of beams. The number of beams is reduced in a 'weeding-out' process based on the total fluence which each beam delivers. The process is gradual, with only three beams removed each time (following a small number of iterations), ensuring that the reduction in beams does not dramatically affect the fluence maps of those remaining. A comparison was made between the dose distributions achieved when the beams positions were optimised in this fashion and when the beams positions were evenly distributed. The method has been shown to work quite effectively and efficiently. The Figure shows a comparison in dose distribution with optimised and non optimised beam positions for 5 beams. It can be clearly seen that there is an improvement in the dose distribution delivered to the tumour and a reduction in the dose to the critical structure with beam position optimisation. A method for beam position optimisation for use in IMRT optimisations has been developed. This method although not necessarily achieving the global minimum in beam position still achieves quite a dramatic improvement compared with no beam position optimisation and is very efficiently achieved. Copyright (2001) Australasian College of Physical Scientists and Engineers in Medicine

Medium-term generation programming in competitive environments: a new optimisation approach for market equilibrium computing

International Nuclear Information System (INIS)

Barquin, J.; Centeno, E.; Reneses, J.

2004-01-01

The paper proposes a model to represent medium-term hydro-thermal operation of electrical power systems in deregulated frameworks. The model objective is to compute the oligopolistic market equilibrium point in which each utility maximises its profit, based on other firms' behaviour. This problem is not an optimisation one. The main contribution of the paper is to demonstrate that, nevertheless, under some reasonable assumptions, it can be formulated as an equivalent minimisation problem. A computer program has been coded by using the proposed approach. It is used to compute the market equilibrium of a real-size system. (author)

Zipf's Law of Abbreviation and the Principle of Least Effort: Language users optimise a miniature lexicon for efficient communication.

Science.gov (United States)

Kanwal, Jasmeen; Smith, Kenny; Culbertson, Jennifer; Kirby, Simon

2017-08-01

The linguist George Kingsley Zipf made a now classic observation about the relationship between a word's length and its frequency; the more frequent a word is, the shorter it tends to be. He claimed that this "Law of Abbreviation" is a universal structural property of language. The Law of Abbreviation has since been documented in a wide range of human languages, and extended to animal communication systems and even computer programming languages. Zipf hypothesised that this universal design feature arises as a result of individuals optimising form-meaning mappings under competing pressures to communicate accurately but also efficiently-his famous Principle of Least Effort. In this study, we use a miniature artificial language learning paradigm to provide direct experimental evidence for this explanatory hypothesis. We show that language users optimise form-meaning mappings only when pressures for accuracy and efficiency both operate during a communicative task, supporting Zipf's conjecture that the Principle of Least Effort can explain this universal feature of word length distributions. Copyright © 2017 Elsevier B.V. All rights reserved.

Multi-Optimisation Consensus Clustering

Science.gov (United States)

Li, Jian; Swift, Stephen; Liu, Xiaohui

Ensemble Clustering has been developed to provide an alternative way of obtaining more stable and accurate clustering results. It aims to avoid the biases of individual clustering algorithms. However, it is still a challenge to develop an efficient and robust method for Ensemble Clustering. Based on an existing ensemble clustering method, Consensus Clustering (CC), this paper introduces an advanced Consensus Clustering algorithm called Multi-Optimisation Consensus Clustering (MOCC), which utilises an optimised Agreement Separation criterion and a Multi-Optimisation framework to improve the performance of CC. Fifteen different data sets are used for evaluating the performance of MOCC. The results reveal that MOCC can generate more accurate clustering results than the original CC algorithm.

Ant colony optimisation for economic dispatch problem with non-smooth cost functions

Energy Technology Data Exchange (ETDEWEB)

Pothiya, Saravuth; Kongprawechnon, Waree [School of Communication, Instrumentation and Control, Sirindhorn International Institute of Technology, Thammasat University, P.O. Box 22, Pathumthani (Thailand); Ngamroo, Issarachai [Center of Excellence for Innovative Energy Systems, Faculty of Engineering, King Mongkut' s Institute of Technology Ladkrabang, Bangkok 10520 (Thailand)

2010-06-15

This paper presents a novel and efficient optimisation approach based on the ant colony optimisation (ACO) for solving the economic dispatch (ED) problem with non-smooth cost functions. In order to improve the performance of ACO algorithm, three additional techniques, i.e. priority list, variable reduction, and zoom feature are presented. To show its efficiency and effectiveness, the proposed ACO is applied to two types of ED problems with non-smooth cost functions. Firstly, the ED problem with valve-point loading effects consists of 13 and 40 generating units. Secondly, the ED problem considering the multiple fuels consists of 10 units. Additionally, the results of the proposed ACO are compared with those of the conventional heuristic approaches. The experimental results show that the proposed ACO approach is comparatively capable of obtaining higher quality solution and faster computational time. (author)

Mutual information-based LPI optimisation for radar network

Science.gov (United States)

Shi, Chenguang; Zhou, Jianjiang; Wang, Fei; Chen, Jun

2015-07-01

Radar network can offer significant performance improvement for target detection and information extraction employing spatial diversity. For a fixed number of radars, the achievable mutual information (MI) for estimating the target parameters may extend beyond a predefined threshold with full power transmission. In this paper, an effective low probability of intercept (LPI) optimisation algorithm is presented to improve LPI performance for radar network. Based on radar network system model, we first provide Schleher intercept factor for radar network as an optimisation metric for LPI performance. Then, a novel LPI optimisation algorithm is presented, where for a predefined MI threshold, Schleher intercept factor for radar network is minimised by optimising the transmission power allocation among radars in the network such that the enhanced LPI performance for radar network can be achieved. The genetic algorithm based on nonlinear programming (GA-NP) is employed to solve the resulting nonconvex and nonlinear optimisation problem. Some simulations demonstrate that the proposed algorithm is valuable and effective to improve the LPI performance for radar network.

Dose optimisation in computed radiography

International Nuclear Information System (INIS)

Schreiner-Karoussou, A.

2005-01-01

After the installation of computed radiography (CR) systems in three hospitals in Luxembourg a patient dose survey was carried out for three radiographic examinations, thorax, pelvis and lumbar spine. It was found that the patient doses had changed in comparison with the patient doses measured for conventional radiography in the same three hospitals. A close collaboration between the manufacturers of the X-ray installations, the CR imaging systems and the medical physicists led to the discovery that the speed class with which each radiographic examination was to be performed, had been ignored, during installation of the digital imaging systems. A number of procedures were carried out in order to calibrate and program the X-ray installations in conjunction with the CR systems. Following this optimisation procedure, a new patient dose survey was carried out for the three radiographic examinations. It was found that patient doses for the three hospitals were reduced. (authors)

Computed tomography dose optimisation in cystic fibrosis: A review.

LENUS (Irish Health Repository)

Ferris, Helena

2016-04-28

Cystic fibrosis (CF) is the most common autosomal recessive disease of the Caucasian population worldwide, with respiratory disease remaining the most relevant source of morbidity and mortality. Computed tomography (CT) is frequently used for monitoring disease complications and progression. Over the last fifteen years there has been a six-fold increase in the use of CT, which has lead to a growing concern in relation to cumulative radiation exposure. The challenge to the medical profession is to identify dose reduction strategies that meet acceptable image quality, but fulfil the requirements of a diagnostic quality CT. Dose-optimisation, particularly in CT, is essential as it reduces the chances of patients receiving cumulative radiation doses in excess of 100 mSv, a dose deemed significant by the United Nations Scientific Committee on the Effects of Atomic Radiation. This review article explores the current trends in imaging in CF with particular emphasis on new developments in dose optimisation.

Simulation-Based Planning of Optimal Conditions for Industrial Computed Tomography

DEFF Research Database (Denmark)

Reisinger, S.; Kasperl, S.; Franz, M.

2011-01-01

We present a method to optimise conditions for industrial computed tomography (CT). This optimisation is based on a deterministic simulation. Our algorithm finds task-specific CT equipment settings to achieve optimal exposure parameters by means of an STL-model of the specimen and a raytracing...

A framework for the computer-aided planning and optimisation of manufacturing processes for components with functional graded properties

Science.gov (United States)

Biermann, D.; Gausemeier, J.; Heim, H.-P.; Hess, S.; Petersen, M.; Ries, A.; Wagner, T.

2014-05-01

In this contribution a framework for the computer-aided planning and optimisation of functional graded components is presented. The framework is divided into three modules - the "Component Description", the "Expert System" for the synthetisation of several process chains and the "Modelling and Process Chain Optimisation". The Component Description module enhances a standard computer-aided design (CAD) model by a voxel-based representation of the graded properties. The Expert System synthesises process steps stored in the knowledge base to generate several alternative process chains. Each process chain is capable of producing components according to the enhanced CAD model and usually consists of a sequence of heating-, cooling-, and forming processes. The dependencies between the component and the applied manufacturing processes as well as between the processes themselves need to be considered. The Expert System utilises an ontology for that purpose. The ontology represents all dependencies in a structured way and connects the information of the knowledge base via relations. The third module performs the evaluation of the generated process chains. To accomplish this, the parameters of each process are optimised with respect to the component specification, whereby the result of the best parameterisation is used as representative value. Finally, the process chain which is capable of manufacturing a functionally graded component in an optimal way regarding to the property distributions of the component description is presented by means of a dedicated specification technique.

Exploiting Genomic Knowledge in Optimising Molecular Breeding Programmes: Algorithms from Evolutionary Computing

Science.gov (United States)

O'Hagan, Steve; Knowles, Joshua; Kell, Douglas B.

2012-01-01

Comparatively few studies have addressed directly the question of quantifying the benefits to be had from using molecular genetic markers in experimental breeding programmes (e.g. for improved crops and livestock), nor the question of which organisms should be mated with each other to best effect. We argue that this requires in silico modelling, an approach for which there is a large literature in the field of evolutionary computation (EC), but which has not really been applied in this way to experimental breeding programmes. EC seeks to optimise measurable outcomes (phenotypic fitnesses) by optimising in silico the mutation, recombination and selection regimes that are used. We review some of the approaches from EC, and compare experimentally, using a biologically relevant in silico landscape, some algorithms that have knowledge of where they are in the (genotypic) search space (G-algorithms) with some (albeit well-tuned ones) that do not (F-algorithms). For the present kinds of landscapes, F- and G-algorithms were broadly comparable in quality and effectiveness, although we recognise that the G-algorithms were not equipped with any ‘prior knowledge’ of epistatic pathway interactions. This use of algorithms based on machine learning has important implications for the optimisation of experimental breeding programmes in the post-genomic era when we shall potentially have access to the full genome sequence of every organism in a breeding population. The non-proprietary code that we have used is made freely available (via Supplementary information). PMID:23185279

Coil optimisation for transcranial magnetic stimulation in realistic head geometry.

Science.gov (United States)

Koponen, Lari M; Nieminen, Jaakko O; Mutanen, Tuomas P; Stenroos, Matti; Ilmoniemi, Risto J

Transcranial magnetic stimulation (TMS) allows focal, non-invasive stimulation of the cortex. A TMS pulse is inherently weakly coupled to the cortex; thus, magnetic stimulation requires both high current and high voltage to reach sufficient intensity. These requirements limit, for example, the maximum repetition rate and the maximum number of consecutive pulses with the same coil due to the rise of its temperature. To develop methods to optimise, design, and manufacture energy-efficient TMS coils in realistic head geometry with an arbitrary overall coil shape. We derive a semi-analytical integration scheme for computing the magnetic field energy of an arbitrary surface current distribution, compute the electric field induced by this distribution with a boundary element method, and optimise a TMS coil for focal stimulation. Additionally, we introduce a method for manufacturing such a coil by using Litz wire and a coil former machined from polyvinyl chloride. We designed, manufactured, and validated an optimised TMS coil and applied it to brain stimulation. Our simulations indicate that this coil requires less than half the power of a commercial figure-of-eight coil, with a 41% reduction due to the optimised winding geometry and a partial contribution due to our thinner coil former and reduced conductor height. With the optimised coil, the resting motor threshold of abductor pollicis brevis was reached with the capacitor voltage below 600 V and peak current below 3000 A. The described method allows designing practical TMS coils that have considerably higher efficiency than conventional figure-of-eight coils. Copyright © 2017 Elsevier Inc. All rights reserved.

Risk based test interval and maintenance optimisation - Application and uses

International Nuclear Information System (INIS)

Sparre, E.

1999-10-01

The project is part of an IAEA co-ordinated Research Project (CRP) on 'Development of Methodologies for Optimisation of Surveillance Testing and Maintenance of Safety Related Equipment at NPPs'. The purpose of the project is to investigate the sensitivity of the results obtained when performing risk based optimisation of the technical specifications. Previous projects have shown that complete LPSA models can be created and that these models allow optimisation of technical specifications. However, these optimisations did not include any in depth check of the result sensitivity with regards to methods, model completeness etc. Four different test intervals have been investigated in this study. Aside from an original, nominal, optimisation a set of sensitivity analyses has been performed and the results from these analyses have been compared to the original optimisation. The analyses indicate that the result of an optimisation is rather stable. However, it is not possible to draw any certain conclusions without performing a number of sensitivity analyses. Significant differences in the optimisation result were discovered when analysing an alternative configuration. Also deterministic uncertainties seem to affect the result of an optimisation largely. The sensitivity of failure data uncertainties is important to investigate in detail since the methodology is based on the assumption that the unavailability of a component is dependent on the length of the test interval

Structure and weights optimisation of a modified Elman network emotion classifier using hybrid computational intelligence algorithms: a comparative study

Science.gov (United States)

Sheikhan, Mansour; Abbasnezhad Arabi, Mahdi; Gharavian, Davood

2015-10-01

Artificial neural networks are efficient models in pattern recognition applications, but their performance is dependent on employing suitable structure and connection weights. This study used a hybrid method for obtaining the optimal weight set and architecture of a recurrent neural emotion classifier based on gravitational search algorithm (GSA) and its binary version (BGSA), respectively. By considering the features of speech signal that were related to prosody, voice quality, and spectrum, a rich feature set was constructed. To select more efficient features, a fast feature selection method was employed. The performance of the proposed hybrid GSA-BGSA method was compared with similar hybrid methods based on particle swarm optimisation (PSO) algorithm and its binary version, PSO and discrete firefly algorithm, and hybrid of error back-propagation and genetic algorithm that were used for optimisation. Experimental tests on Berlin emotional database demonstrated the superior performance of the proposed method using a lighter network structure.

Efficient GPU-based skyline computation

DEFF Research Database (Denmark)

Bøgh, Kenneth Sejdenfaden; Assent, Ira; Magnani, Matteo

2013-01-01

The skyline operator for multi-criteria search returns the most interesting points of a data set with respect to any monotone preference function. Existing work has almost exclusively focused on efficiently computing skylines on one or more CPUs, ignoring the high parallelism possible in GPUs. In...

Modern multicore and manycore architectures: Modelling, optimisation and benchmarking a multiblock CFD code

Science.gov (United States)

Hadade, Ioan; di Mare, Luca

2016-08-01

Modern multicore and manycore processors exhibit multiple levels of parallelism through a wide range of architectural features such as SIMD for data parallel execution or threads for core parallelism. The exploitation of multi-level parallelism is therefore crucial for achieving superior performance on current and future processors. This paper presents the performance tuning of a multiblock CFD solver on Intel SandyBridge and Haswell multicore CPUs and the Intel Xeon Phi Knights Corner coprocessor. Code optimisations have been applied on two computational kernels exhibiting different computational patterns: the update of flow variables and the evaluation of the Roe numerical fluxes. We discuss at great length the code transformations required for achieving efficient SIMD computations for both kernels across the selected devices including SIMD shuffles and transpositions for flux stencil computations and global memory transformations. Core parallelism is expressed through threading based on a number of domain decomposition techniques together with optimisations pertaining to alleviating NUMA effects found in multi-socket compute nodes. Results are correlated with the Roofline performance model in order to assert their efficiency for each distinct architecture. We report significant speedups for single thread execution across both kernels: 2-5X on the multicore CPUs and 14-23X on the Xeon Phi coprocessor. Computations at full node and chip concurrency deliver a factor of three speedup on the multicore processors and up to 24X on the Xeon Phi manycore coprocessor.

Module detection in complex networks using integer optimisation

Directory of Open Access Journals (Sweden)

Tsoka Sophia

2010-11-01

Full Text Available Abstract Background The detection of modules or community structure is widely used to reveal the underlying properties of complex networks in biology, as well as physical and social sciences. Since the adoption of modularity as a measure of network topological properties, several methodologies for the discovery of community structure based on modularity maximisation have been developed. However, satisfactory partitions of large graphs with modest computational resources are particularly challenging due to the NP-hard nature of the related optimisation problem. Furthermore, it has been suggested that optimising the modularity metric can reach a resolution limit whereby the algorithm fails to detect smaller communities than a specific size in large networks. Results We present a novel solution approach to identify community structure in large complex networks and address resolution limitations in module detection. The proposed algorithm employs modularity to express network community structure and it is based on mixed integer optimisation models. The solution procedure is extended through an iterative procedure to diminish effects that tend to agglomerate smaller modules (resolution limitations. Conclusions A comprehensive comparative analysis of methodologies for module detection based on modularity maximisation shows that our approach outperforms previously reported methods. Furthermore, in contrast to previous reports, we propose a strategy to handle resolution limitations in modularity maximisation. Overall, we illustrate ways to improve existing methodologies for community structure identification so as to increase its efficiency and applicability.

Energy thermal management in commercial bread-baking using a multi-objective optimisation framework

International Nuclear Information System (INIS)

Khatir, Zinedine; Taherkhani, A.R.; Paton, Joe; Thompson, Harvey; Kapur, Nik; Toropov, Vassili

2015-01-01

In response to increasing energy costs and legislative requirements energy efficient high-speed air impingement jet baking systems are now being developed. In this paper, a multi-objective optimisation framework for oven designs is presented which uses experimentally verified heat transfer correlations and high fidelity Computational Fluid Dynamics (CFD) analyses to identify optimal combinations of design features which maximise desirable characteristics such as temperature uniformity in the oven and overall energy efficiency of baking. A surrogate-assisted multi-objective optimisation framework is proposed and used to explore a range of practical oven designs, providing information on overall temperature uniformity within the oven together with ensuing energy usage and potential savings. - Highlights: • A multi-objective optimisation framework to design commercial ovens is presented. • High fidelity CFD embeds experimentally calibrated heat transfer inputs. • The optimum oven design minimises specific energy and bake time. • The Pareto front outlining the surrogate-assisted optimisation framework is built. • Optimisation of industrial bread-baking ovens reveals an energy saving of 637.6 GWh

Self-optimisation and model-based design of experiments for developing a C–H activation flow process

Directory of Open Access Journals (Sweden)

Alexander Echtermeyer

2017-01-01

Full Text Available A recently described C(sp3–H activation reaction to synthesise aziridines was used as a model reaction to demonstrate the methodology of developing a process model using model-based design of experiments (MBDoE and self-optimisation approaches in flow. The two approaches are compared in terms of experimental efficiency. The self-optimisation approach required the least number of experiments to reach the specified objectives of cost and product yield, whereas the MBDoE approach enabled a rapid generation of a process model.

Combining simulation and multi-objective optimisation for equipment quantity optimisation in container terminals

OpenAIRE

Lin, Zhougeng

2013-01-01

This thesis proposes a combination framework to integrate simulation and multi-objective optimisation (MOO) for container terminal equipment optimisation. It addresses how the strengths of simulation and multi-objective optimisation can be integrated to find high quality solutions for multiple objectives with low computational cost. Three structures for the combination framework are proposed respectively: pre-MOO structure, integrated MOO structure and post-MOO structure. The applications of ...

Advanced optimisation - coal fired power plant operations

Energy Technology Data Exchange (ETDEWEB)

Turney, D.M.; Mayes, I. [E.ON UK, Nottingham (United Kingdom)

2005-03-01

The purpose of this unit optimization project is to develop an integrated approach to unit optimisation and develop an overall optimiser that is able to resolve any conflicts between the individual optimisers. The individual optimisers have been considered during this project are: on-line thermal efficiency package, GNOCIS boiler optimiser, GNOCIS steam side optimiser, ESP optimisation, and intelligent sootblowing system. 6 refs., 7 figs., 3 tabs.

Smart meter deployment optimisation and its analysis for appliance load monitoring

Directory of Open Access Journals (Sweden)

Ahmed Shaharyar Khwaja

2015-04-01

Full Text Available In this study, the authors study the problem of smart meter deployment optimisation for appliance load monitoring, that is, to monitor a number of devices without any ambiguity using the minimum number of low-cost smart meters. The importance of this problem is due to the fact that the number of meters should be reduced to decrease the deployment cost, improve reliability and decrease congestion. In this way, in future, smart meters can provide additional information about the type and number of distinct devices connected, besides their normal functionalities concerned with providing overall energy measurements and their communication. The authors present two exact smart meter deployment optimisation algorithms, one based on exhaustive search and the other based on efficient implementation of the exhaustive search. They formulate the problem mathematically and present computational complexity analysis of their algorithms. Simulation scenarios show that for a typical number of home appliances, the efficient search method is significantly faster compared to the exhaustive search and can provide the same optimal solution. The authors also show the dependency of their method on the distribution of the load pattern that can potentially be in a typical household.

Wireless-Uplinks-Based Energy-Efficient Scheduling in Mobile Cloud Computing

Directory of Open Access Journals (Sweden)

Xing Liu

2015-01-01

Full Text Available Mobile cloud computing (MCC combines cloud computing and mobile internet to improve the computational capabilities of resource-constrained mobile devices (MDs. In MCC, mobile users could not only improve the computational capability of MDs but also save operation consumption by offloading the mobile applications to the cloud. However, MCC faces the problem of energy efficiency because of time-varying channels when the offloading is being executed. In this paper, we address the issue of energy-efficient scheduling for wireless uplink in MCC. By introducing Lyapunov optimization, we first propose a scheduling algorithm that can dynamically choose channel to transmit data based on queue backlog and channel statistics. Then, we show that the proposed scheduling algorithm can make a tradeoff between queue backlog and energy consumption in a channel-aware MCC system. Simulation results show that the proposed scheduling algorithm can reduce the time average energy consumption for offloading compared to the existing algorithm.

Integration of Monte-Carlo ray tracing with a stochastic optimisation method: application to the design of solar receiver geometry.

Science.gov (United States)

Asselineau, Charles-Alexis; Zapata, Jose; Pye, John

2015-06-01

A stochastic optimisation method adapted to illumination and radiative heat transfer problems involving Monte-Carlo ray-tracing is presented. A solar receiver shape optimisation case study illustrates the advantages of the method and its potential: efficient receivers are identified using a moderate computational cost.

Optimisation of BPMN Business Models via Model Checking

DEFF Research Database (Denmark)

Herbert, Luke Thomas; Sharp, Robin

2013-01-01

We present a framework for the optimisation of business processes modelled in the business process modelling language BPMN, which builds upon earlier work, where we developed a model checking based method for the analysis of BPMN models. We define a structure for expressing optimisation goals...... for synthesized BPMN components, based on probabilistic computation tree logic and real-valued reward structures of the BPMN model, allowing for the specification of complex quantitative goals. We here present a simple algorithm, inspired by concepts from evolutionary algorithms, which iteratively generates...

Cultural-based particle swarm for dynamic optimisation problems

Science.gov (United States)

Daneshyari, Moayed; Yen, Gary G.

2012-07-01

Many practical optimisation problems are with the existence of uncertainties, among which a significant number belong to the dynamic optimisation problem (DOP) category in which the fitness function changes through time. In this study, we propose the cultural-based particle swarm optimisation (PSO) to solve DOP problems. A cultural framework is adopted incorporating the required information from the PSO into five sections of the belief space, namely situational, temporal, domain, normative and spatial knowledge. The stored information will be adopted to detect the changes in the environment and assists response to the change through a diversity-based repulsion among particles and migration among swarms in the population space, and also helps in selecting the leading particles in three different levels, personal, swarm and global levels. Comparison of the proposed heuristics over several difficult dynamic benchmark problems demonstrates the better or equal performance with respect to most of other selected state-of-the-art dynamic PSO heuristics.

Multicriteria Optimisation in Logistics Forwarder Activities

Directory of Open Access Journals (Sweden)

Tanja Poletan Jugović

2007-05-01

Full Text Available Logistics forwarder, as organizer and planner of coordinationand integration of all the transport and logistics chains elements,uses adequate ways and methods in the process of planningand decision-making. One of these methods, analysed inthis paper, which could be used in optimisation of transportand logistics processes and activities of logistics forwarder, isthe multicriteria optimisation method. Using that method, inthis paper is suggested model of multicriteria optimisation of logisticsforwarder activities. The suggested model of optimisationis justified in keeping with method principles of multicriteriaoptimization, which is included in operation researchmethods and it represents the process of multicriteria optimizationof variants. Among many different processes of multicriteriaoptimization, PROMETHEE (Preference Ranking OrganizationMethod for Enrichment Evaluations and Promcalc& Gaia V. 3.2., computer program of multicriteria programming,which is based on the mentioned process, were used.

A computationally efficient approach for template matching-based ...

Indian Academy of Sciences (India)

In this paper, a new computationally efficient image registration method is ...... the proposed method requires less computational time as compared to traditional methods. ... Zitová B and Flusser J 2003 Image registration methods: A survey.

Efficient Backprojection-Based Synthetic Aperture Radar Computation with Many-Core Processors

Directory of Open Access Journals (Sweden)

Jongsoo Park

2013-01-01

Full Text Available Tackling computationally challenging problems with high efficiency often requires the combination of algorithmic innovation, advanced architecture, and thorough exploitation of parallelism. We demonstrate this synergy through synthetic aperture radar (SAR via backprojection, an image reconstruction method that can require hundreds of TFLOPS. Computation cost is significantly reduced by our new algorithm of approximate strength reduction; data movement cost is economized by software locality optimizations facilitated by advanced architecture support; parallelism is fully harnessed in various patterns and granularities. We deliver over 35 billion backprojections per second throughput per compute node on an Intel® Xeon® processor E5-2670-based cluster, equipped with Intel® Xeon Phi™ coprocessors. This corresponds to processing a 3K×3K image within a second using a single node. Our study can be extended to other settings: backprojection is applicable elsewhere including medical imaging, approximate strength reduction is a general code transformation technique, and many-core processors are emerging as a solution to energy-efficient computing.

Efficient computation of hashes

International Nuclear Information System (INIS)

Lopes, Raul H C; Franqueira, Virginia N L; Hobson, Peter R

2014-01-01

The sequential computation of hashes at the core of many distributed storage systems and found, for example, in grid services can hinder efficiency in service quality and even pose security challenges that can only be addressed by the use of parallel hash tree modes. The main contributions of this paper are, first, the identification of several efficiency and security challenges posed by the use of sequential hash computation based on the Merkle-Damgard engine. In addition, alternatives for the parallel computation of hash trees are discussed, and a prototype for a new parallel implementation of the Keccak function, the SHA-3 winner, is introduced.

Modulation aware cluster size optimisation in wireless sensor networks

Science.gov (United States)

Sriram Naik, M.; Kumar, Vinay

2017-07-01

Wireless sensor networks (WSNs) play a great role because of their numerous advantages to the mankind. The main challenge with WSNs is the energy efficiency. In this paper, we have focused on the energy minimisation with the help of cluster size optimisation along with consideration of modulation effect when the nodes are not able to communicate using baseband communication technique. Cluster size optimisations is important technique to improve the performance of WSNs. It provides improvement in energy efficiency, network scalability, network lifetime and latency. We have proposed analytical expression for cluster size optimisation using traditional sensing model of nodes for square sensing field with consideration of modulation effects. Energy minimisation can be achieved by changing the modulation schemes such as BPSK, 16-QAM, QPSK, 64-QAM, etc., so we are considering the effect of different modulation techniques in the cluster formation. The nodes in the sensing fields are random and uniformly deployed. It is also observed that placement of base station at centre of scenario enables very less number of modulation schemes to work in energy efficient manner but when base station placed at the corner of the sensing field, it enable large number of modulation schemes to work in energy efficient manner.

Optimisation on processing parameters for minimising warpage on side arm using response surface methodology (RSM) and particle swarm optimisation (PSO)

Science.gov (United States)

Rayhana, N.; Fathullah, M.; Shayfull, Z.; Nasir, S. M.; Hazwan, M. H. M.; Sazli, M.; Yahya, Z. R.

2017-09-01

This study presents the application of optimisation method to reduce the warpage of side arm part. Autodesk Moldflow Insight software was integrated into this study to analyse the warpage. The design of Experiment (DOE) for Response Surface Methodology (RSM) was constructed and by using the equation from RSM, Particle Swarm Optimisation (PSO) was applied. The optimisation method will result in optimised processing parameters with minimum warpage. Mould temperature, melt temperature, packing pressure, packing time and cooling time was selected as the variable parameters. Parameters selection was based on most significant factor affecting warpage stated by previous researchers. The results show that warpage was improved by 28.16% for RSM and 28.17% for PSO. The warpage improvement in PSO from RSM is only by 0.01 %. Thus, the optimisation using RSM is already efficient to give the best combination parameters and optimum warpage value for side arm part. The most significant parameters affecting warpage are packing pressure.

A computationally efficient OMP-based compressed sensing reconstruction for dynamic MRI

International Nuclear Information System (INIS)

Usman, M; Prieto, C; Schaeffter, T; Batchelor, P G; Odille, F; Atkinson, D

2011-01-01

Compressed sensing (CS) methods in MRI are computationally intensive. Thus, designing novel CS algorithms that can perform faster reconstructions is crucial for everyday applications. We propose a computationally efficient orthogonal matching pursuit (OMP)-based reconstruction, specifically suited to cardiac MR data. According to the energy distribution of a y-f space obtained from a sliding window reconstruction, we label the y-f space as static or dynamic. For static y-f space images, a computationally efficient masked OMP reconstruction is performed, whereas for dynamic y-f space images, standard OMP reconstruction is used. The proposed method was tested on a dynamic numerical phantom and two cardiac MR datasets. Depending on the field of view composition of the imaging data, compared to the standard OMP method, reconstruction speedup factors ranging from 1.5 to 2.5 are achieved. (note)

A fuzzy-based particle swarm optimisation approach for task assignment in home healthcare

Directory of Open Access Journals (Sweden)

Mutingi, Michael

2014-11-01

Full Text Available Home healthcare (HHC organisations provide coordinated healthcare services to patients at their homes. Motivated by the ever-increasing need for home-based care, the assignment of tasks to available healthcare staff is a common and complex problem in homecare organisations. Designing high quality task schedules is critical for improving worker morale, job satisfaction, service efficiency, service quality, and competitiveness over the long term. The desire is to provide high quality task assignment schedules that satisfy the patient, the care worker, and the management. This translates to maximising schedule fairness in terms of workload assignments, avoiding task time window violation, and meeting management goals as much as possible. However, in practice, these desires are often subjective as they involve imprecise human perceptions. This paper develops a fuzzy multi-criteria particle swarm optimisation (FPSO approach for task assignment in a home healthcare setting in a fuzzy environment. The proposed approach uses a fuzzy evaluation method from a multi-criteria point of view. Results from illustrative computational experiments show that the approach is promising.

The multiple roles of computational chemistry in fragment-based drug design

Science.gov (United States)

Law, Richard; Barker, Oliver; Barker, John J.; Hesterkamp, Thomas; Godemann, Robert; Andersen, Ole; Fryatt, Tara; Courtney, Steve; Hallett, Dave; Whittaker, Mark

2009-08-01

Fragment-based drug discovery (FBDD) represents a change in strategy from the screening of molecules with higher molecular weights and physical properties more akin to fully drug-like compounds, to the screening of smaller, less complex molecules. This is because it has been recognised that fragment hit molecules can be efficiently grown and optimised into leads, particularly after the binding mode to the target protein has been first determined by 3D structural elucidation, e.g. by NMR or X-ray crystallography. Several studies have shown that medicinal chemistry optimisation of an already drug-like hit or lead compound can result in a final compound with too high molecular weight and lipophilicity. The evolution of a lower molecular weight fragment hit therefore represents an attractive alternative approach to optimisation as it allows better control of compound properties. Computational chemistry can play an important role both prior to a fragment screen, in producing a target focussed fragment library, and post-screening in the evolution of a drug-like molecule from a fragment hit, both with and without the available fragment-target co-complex structure. We will review many of the current developments in the area and illustrate with some recent examples from successful FBDD discovery projects that we have conducted.

Solving difficult problems creatively: A role for energy optimised deterministic/stochastic hybrid computing

Directory of Open Access Journals (Sweden)

Tim ePalmer

2015-10-01

Full Text Available How is the brain configured for creativity? What is the computational substrate for ‘eureka’ moments of insight? Here we argue that creative thinking arises ultimately from a synergy between low-energy stochastic and energy-intensive deterministic processing, and is a by-product of a nervous system whose signal-processing capability per unit of available energy has become highly energy optimised. We suggest that the stochastic component has its origin in thermal noise affecting the activity of neurons. Without this component, deterministic computational models of the brain are incomplete.

Solving difficult problems creatively: a role for energy optimised deterministic/stochastic hybrid computing.

Science.gov (United States)

Palmer, Tim N; O'Shea, Michael

2015-01-01

How is the brain configured for creativity? What is the computational substrate for 'eureka' moments of insight? Here we argue that creative thinking arises ultimately from a synergy between low-energy stochastic and energy-intensive deterministic processing, and is a by-product of a nervous system whose signal-processing capability per unit of available energy has become highly energy optimised. We suggest that the stochastic component has its origin in thermal (ultimately quantum decoherent) noise affecting the activity of neurons. Without this component, deterministic computational models of the brain are incomplete.

Optimisation of phase ratio in the triple jump using computer simulation.

Science.gov (United States)

Allen, Sam J; King, Mark A; Yeadon, M R Fred

2016-04-01

The triple jump is an athletic event comprising three phases in which the optimal proportion of each phase to the total distance jumped, termed the phase ratio, is unknown. This study used a whole-body torque-driven computer simulation model of all three phases of the triple jump to investigate optimal technique. The technique of the simulation model was optimised by varying torque generator activation parameters using a Genetic Algorithm in order to maximise total jump distance, resulting in a hop-dominated technique (35.7%:30.8%:33.6%) and a distance of 14.05m. Optimisations were then run with penalties forcing the model to adopt hop and jump phases of 33%, 34%, 35%, 36%, and 37% of the optimised distance, resulting in total distances of: 13.79m, 13.87m, 13.95m, 14.05m, and 14.02m; and 14.01m, 14.02m, 13.97m, 13.84m, and 13.67m respectively. These results indicate that in this subject-specific case there is a plateau in optimum technique encompassing balanced and hop-dominated techniques, but that a jump-dominated technique is associated with a decrease in performance. Hop-dominated techniques are associated with higher forces than jump-dominated techniques; therefore optimal phase ratio may be related to a combination of strength and approach velocity. Copyright © 2016 Elsevier B.V. All rights reserved.

Improving Computational Efficiency of Prediction in Model-Based Prognostics Using the Unscented Transform

Science.gov (United States)

Daigle, Matthew John; Goebel, Kai Frank

2010-01-01

Model-based prognostics captures system knowledge in the form of physics-based models of components, and how they fail, in order to obtain accurate predictions of end of life (EOL). EOL is predicted based on the estimated current state distribution of a component and expected profiles of future usage. In general, this requires simulations of the component using the underlying models. In this paper, we develop a simulation-based prediction methodology that achieves computational efficiency by performing only the minimal number of simulations needed in order to accurately approximate the mean and variance of the complete EOL distribution. This is performed through the use of the unscented transform, which predicts the means and covariances of a distribution passed through a nonlinear transformation. In this case, the EOL simulation acts as that nonlinear transformation. In this paper, we review the unscented transform, and describe how this concept is applied to efficient EOL prediction. As a case study, we develop a physics-based model of a solenoid valve, and perform simulation experiments to demonstrate improved computational efficiency without sacrificing prediction accuracy.

Power-efficient computer architectures recent advances

CERN Document Server

Själander, Magnus; Kaxiras, Stefanos

2014-01-01

As Moore's Law and Dennard scaling trends have slowed, the challenges of building high-performance computer architectures while maintaining acceptable power efficiency levels have heightened. Over the past ten years, architecture techniques for power efficiency have shifted from primarily focusing on module-level efficiencies, toward more holistic design styles based on parallelism and heterogeneity. This work highlights and synthesizes recent techniques and trends in power-efficient computer architecture.Table of Contents: Introduction / Voltage and Frequency Management / Heterogeneity and Sp

ATLAS software configuration and build tool optimisation

Science.gov (United States)

Rybkin, Grigory; Atlas Collaboration

2014-06-01

ATLAS software code base is over 6 million lines organised in about 2000 packages. It makes use of some 100 external software packages, is developed by more than 400 developers and used by more than 2500 physicists from over 200 universities and laboratories in 6 continents. To meet the challenge of configuration and building of this software, the Configuration Management Tool (CMT) is used. CMT expects each package to describe its build targets, build and environment setup parameters, dependencies on other packages in a text file called requirements, and each project (group of packages) to describe its policies and dependencies on other projects in a text project file. Based on the effective set of configuration parameters read from the requirements files of dependent packages and project files, CMT commands build the packages, generate the environment for their use, or query the packages. The main focus was on build time performance that was optimised within several approaches: reduction of the number of reads of requirements files that are now read once per package by a CMT build command that generates cached requirements files for subsequent CMT build commands; introduction of more fine-grained build parallelism at package task level, i.e., dependent applications and libraries are compiled in parallel; code optimisation of CMT commands used for build; introduction of package level build parallelism, i. e., parallelise the build of independent packages. By default, CMT launches NUMBER-OF-PROCESSORS build commands in parallel. The other focus was on CMT commands optimisation in general that made them approximately 2 times faster. CMT can generate a cached requirements file for the environment setup command, which is especially useful for deployment on distributed file systems like AFS or CERN VMFS. The use of parallelism, caching and code optimisation significantly-by several times-reduced software build time, environment setup time, increased the efficiency of

Real-time optimisation of the Hoa Binh reservoir, Vietnam

DEFF Research Database (Denmark)

Richaud, Bertrand; Madsen, Henrik; Rosbjerg, Dan

2011-01-01

-time optimisation. First, the simulation-optimisation framework is applied for optimising reservoir operating rules. Secondly, real-time and forecast information is used for on-line optimisation that focuses on short-term goals, such as flood control or hydropower generation, without compromising the deviation...... in the downstream part of the Red River, and at the same time to increase hydropower generation and to save water for the dry season. The real-time optimisation procedure further improves the efficiency of the reservoir operation and enhances the flexibility for the decision-making. Finally, the quality......Multi-purpose reservoirs often have to be managed according to conflicting objectives, which requires efficient tools for trading-off the objectives. This paper proposes a multi-objective simulation-optimisation approach that couples off-line rule curve optimisation with on-line real...

Use of artificial intelligence techniques for optimisation of co-combustion of coal with biomass

Energy Technology Data Exchange (ETDEWEB)

Tan, C.K.; Wilcox, S.J.; Ward, J. [University of Glamorgan, Pontypridd (United Kingdom). Division of Mechanical Engineering

2006-03-15

The optimisation of burner operation in conventional pulverised-coal-fired boilers for co-combustion applications represents a significant challenge This paper describes a strategic framework in which Artificial Intelligence (AI) techniques can be applied to solve such an optimisation problem. The effectiveness of the proposed system is demonstrated by a case study that simulates the co-combustion of coal with sewage sludge in a 500-kW pilot-scale combustion rig equipped with a swirl stabilised low-NOx burner. A series of Computational Fluid Dynamics (CFD) simulations were performed to generate data for different operating conditions, which were then used to train several Artificial Neural Networks (ANNs) to predict the co-combustion performance. Once trained, the ANNs were able to make estimations of unseen situations in a fraction of the time taken by the CFD simulation. Consequently, the networks were capable of representing the underlying physics of the CFD models and could be executed efficiently for a large number of iterations as required by optimisation techniques based on Evolutionary Algorithms (EAs). Four operating parameters of the burner, namely the swirl angles and flow rates of the secondary and tertiary combustion air were optimised with the objective of minimising the NOx and CO emissions as well as the unburned carbon at the furnace exit. The results suggest that ANNs combined with EAs provide a useful tool for optimising co-combustion processes.

Optimisation in radiotherapy II: Programmed and inversion optimisation algorithms

International Nuclear Information System (INIS)

Ebert, M.

1997-01-01

This is the second article in a three part examination of optimisation in radiotherapy. The previous article established the bases of optimisation in radiotherapy, and the formulation of the optimisation problem. This paper outlines several algorithms that have been used in radiotherapy, for searching for the best irradiation strategy within the full set of possible strategies. Two principle classes of algorithm are considered - those associated with mathematical programming which employ specific search techniques, linear programming type searches or artificial intelligence - and those which seek to perform a numerical inversion of the optimisation problem, finishing with deterministic iterative inversion. (author)

An efficient optimisation method in groundwater resource ...

African Journals Online (AJOL)

DRINIE

2003-10-04

Oct 4, 2003 ... theories developed in the field of stochastic subsurface hydrology. In reality, many ... Recently, some researchers have applied the multi-stage ... Then a robust solution of the optimisation problem given by Eqs. (1) to (3) is as ...

Techno-economic optimisation of energy systems; Contribution a l'optimisation technico-economique de systemes energetiques

Energy Technology Data Exchange (ETDEWEB)

Mansilla Pellen, Ch

2006-07-15

The traditional approach currently used to assess the economic interest of energy systems is based on a defined flow-sheet. Some studies have shown that the flow-sheets corresponding to the best thermodynamic efficiencies do not necessarily lead to the best production costs. A method called techno-economic optimisation was proposed. This method aims at minimising the production cost of a given energy system, including both investment and operating costs. It was implemented using genetic algorithms. This approach was compared to the heat integration method on two different examples, thus validating its interest. Techno-economic optimisation was then applied to different energy systems dealing with hydrogen as well as electricity production. (author)

Simulation optimisation

International Nuclear Information System (INIS)

Anon

2010-01-01

Over the past decade there has been a significant advance in flotation circuit optimisation through performance benchmarking using metallurgical modelling and steady-state computer simulation. This benchmarking includes traditional measures, such as grade and recovery, as well as new flotation measures, such as ore floatability, bubble surface area flux and froth recovery. To further this optimisation, Outotec has released its HSC Chemistry software with simulation modules. The flotation model developed by the AMIRA P9 Project, of which Outotec is a sponsor, is regarded by industry as the most suitable flotation model to use for circuit optimisation. This model incorporates ore floatability with flotation cell pulp and froth parameters, residence time, entrainment and water recovery. Outotec's HSC Sim enables you to simulate mineral processes in different levels, from comminution circuits with sizes and no composition, through to flotation processes with minerals by size by floatability components, to full processes with true particles with MLA data.

Numerical Analysis and Geometry Optimisation of Vertical Vane of Room Air-conditioner

Directory of Open Access Journals (Sweden)

Al-Obaidi Abdulkareem Sh. Mahdi

2018-01-01

Full Text Available Vertical vanes of room air-conditioners are used to control and direct cold air. This paper aims to study vertical vane as one of the parameters that affect the efficiency of dissipating cold air to a given space. The vertical vane geometry is analysed and optimised for lower production cost using CFD. The optimised geometry of the vertical vane should have the same or increased efficiency of dissipating cold air and have lesser mass compared to the existing original design. The existing original design of vertical vane is simplified and analysed by using ANSYS Fluent. Efficiency of wind direction is define as how accurate the direction of airflow coming out from vertical vane. In order to calculate the efficiency of wind direction, 15° and 30° rotation of vertical vane inside room air-conditioner are simulated. The efficiency of wind direction for 15° rotation of vertical vane is 57.81% while efficiency of wind direction for 30° rotation of vertical vane is 47.54%. The results of the efficiency of wind direction are used as base reference for parametric study. The parameters investigated for optimisation of vertical vane are focused at length of long span, tip chord and short span. The design of 15% decreased in vane surface area at tip chord is the best optimised design of vertical vane because the efficiency of wind direction is the highest as 60.32%.

Improving computational efficiency of Monte Carlo simulations with variance reduction

International Nuclear Information System (INIS)

Turner, A.; Davis, A.

2013-01-01

CCFE perform Monte-Carlo transport simulations on large and complex tokamak models such as ITER. Such simulations are challenging since streaming and deep penetration effects are equally important. In order to make such simulations tractable, both variance reduction (VR) techniques and parallel computing are used. It has been found that the application of VR techniques in such models significantly reduces the efficiency of parallel computation due to 'long histories'. VR in MCNP can be accomplished using energy-dependent weight windows. The weight window represents an 'average behaviour' of particles, and large deviations in the arriving weight of a particle give rise to extreme amounts of splitting being performed and a long history. When running on parallel clusters, a long history can have a detrimental effect on the parallel efficiency - if one process is computing the long history, the other CPUs complete their batch of histories and wait idle. Furthermore some long histories have been found to be effectively intractable. To combat this effect, CCFE has developed an adaptation of MCNP which dynamically adjusts the WW where a large weight deviation is encountered. The method effectively 'de-optimises' the WW, reducing the VR performance but this is offset by a significant increase in parallel efficiency. Testing with a simple geometry has shown the method does not bias the result. This 'long history method' has enabled CCFE to significantly improve the performance of MCNP calculations for ITER on parallel clusters, and will be beneficial for any geometry combining streaming and deep penetration effects. (authors)

Techno-economic optimisation of energy systems

International Nuclear Information System (INIS)

Mansilla Pellen, Ch.

2006-07-01

The traditional approach currently used to assess the economic interest of energy systems is based on a defined flow-sheet. Some studies have shown that the flow-sheets corresponding to the best thermodynamic efficiencies do not necessarily lead to the best production costs. A method called techno-economic optimisation was proposed. This method aims at minimising the production cost of a given energy system, including both investment and operating costs. It was implemented using genetic algorithms. This approach was compared to the heat integration method on two different examples, thus validating its interest. Techno-economic optimisation was then applied to different energy systems dealing with hydrogen as well as electricity production. (author)

Optimizing the gear efficiency under consideration of thermal optimisation strategies and customer-specific load conditions; Optimierung des Getriebewirkungsgrads unter Beruecksichtigung thermischer Optimierungsstrategien und kundenspezifischer Lastkollektive

Energy Technology Data Exchange (ETDEWEB)

Inderwisch, Kathrien; Kuecuekay, Ferit [Technische Univ. Braunschweig (Germany). Inst. fuer Fahrzeugtechnik

2012-11-01

Nowadays, the automotive industry have been received more attention to improve the transmission efficiency. Most of the researches have been concentrated on development and optimisation on transmission actuators, shifting elements, bearings, lubricants or lightweight constructions. Due to the low load requirements and associated low efficiencies for transmissions in driving cycles the transmissions cause energy losses which cannot be neglected. Two main stategies can be followed up for the optimisation of transmission efficiency. At first the efficiency benefit of transmissions through optimisation of hardware components will be presented. The second possibility is the representation of an optimal thermal management especially at low temperatures. Warming-up the transmission oil or transmission components can increase the efficiency of transmissions significantly. Techniques like this become more important in the course of electrification of drive trains and therefore decreased availability of heat. A simulation tool for calculation and minimisation of power loss for manual and dual-clutch transmissions was developed at the Institute of Automotive Engineering and verified by measurements. The simulation tool calculates the total transmission efficiency as well as the losses of individual transmission components depending on various environmental conditions. In this paper, the results in terms of increasing the efficiency of transmissions by optimisation of hardware components will be presented. Furthermore, the effects of temperature distribution in the transmission as well as the potential of minimising loss at low temperatures through thermal management will be illustrated. (orig.)

Optimised Renormalisation Group Flows

CERN Document Server

Litim, Daniel F

2001-01-01

Exact renormalisation group (ERG) flows interpolate between a microscopic or classical theory and the corresponding macroscopic or quantum effective theory. For most problems of physical interest, the efficiency of the ERG is constrained due to unavoidable approximations. Approximate solutions of ERG flows depend spuriously on the regularisation scheme which is determined by a regulator function. This is similar to the spurious dependence on the ultraviolet regularisation known from perturbative QCD. Providing a good control over approximated ERG flows is at the root for reliable physical predictions. We explain why the convergence of approximate solutions towards the physical theory is optimised by appropriate choices of the regulator. We study specific optimised regulators for bosonic and fermionic fields and compare the optimised ERG flows with generic ones. This is done up to second order in the derivative expansion at both vanishing and non-vanishing temperature. An optimised flow for a ``proper-time ren...

Parametric studies and optimisation of pumped thermal electricity storage

International Nuclear Information System (INIS)

McTigue, Joshua D.; White, Alexander J.; Markides, Christos N.

2015-01-01

Highlights: • PTES is modelled by cycle analysis and a Schumann-style model of the thermal stores. • Optimised trade-off surfaces show a flat efficiency vs. energy density profile. • Overall roundtrip efficiencies of around 70% are not inconceivable. - Abstract: Several of the emerging technologies for electricity storage are based on some form of thermal energy storage (TES). Examples include liquid air energy storage, pumped heat energy storage and, at least in part, advanced adiabatic compressed air energy storage. Compared to other large-scale storage methods, TES benefits from relatively high energy densities, which should translate into a low cost per MW h of storage capacity and a small installation footprint. TES is also free from the geographic constraints that apply to hydro storage schemes. TES concepts for electricity storage rely on either a heat pump or refrigeration cycle during the charging phase to create a hot or a cold storage space (the thermal stores), or in some cases both. During discharge, the thermal stores are depleted by reversing the cycle such that it acts as a heat engine. The present paper is concerned with a form of TES that has both hot and cold packed-bed thermal stores, and for which the heat pump and heat engine are based on a reciprocating Joule cycle, with argon as the working fluid. A thermodynamic analysis is presented based on traditional cycle calculations coupled with a Schumann-style model of the packed beds. Particular attention is paid to the various loss-generating mechanisms and their effect on roundtrip efficiency and storage density. A parametric study is first presented that examines the sensitivity of results to assumed values of the various loss factors and demonstrates the rather complex influence of the numerous design variables. Results of an optimisation study are then given in the form of trade-off surfaces for roundtrip efficiency, energy density and power density. The optimised designs show a

A constriction factor based particle swarm optimisation algorithm to solve the economic dispatch problem including losses

Energy Technology Data Exchange (ETDEWEB)

Young, Steven; Montakhab, Mohammad; Nouri, Hassan

2011-07-15

Economic dispatch (ED) is one of the most important problems to be solved in power generation as fractional percentage fuel reductions represent significant cost savings. ED wishes to optimise the power generated by each generating unit in a system in order to find the minimum operating cost at a required load demand, whilst ensuring both equality and inequality constraints are met. For the process of optimisation, a model must be created for each generating unit. The particle swarm optimisation technique is an evolutionary computation technique with one of the most powerful methods for solving global optimisation problems. The aim of this paper is to add in a constriction factor to the particle swarm optimisation algorithm (CFBPSO). Results show that the algorithm is very good at solving the ED problem and that CFBPSO must be able to work in a practical environment and so a valve point effect with transmission losses should be included in future work.

Optimising the operation of hybrid coolers by means of efficient control equipment; Optimierung der Betriebsweise von Hybridkuehlern durch effiziente Steuerungstechnik

Energy Technology Data Exchange (ETDEWEB)

Odrich, T.; Koenig, H. [Jaeggi/Guentner (Schweiz) AG, Trimbach (Switzerland)

2007-07-01

Due to its functional principle and design, the hybrid dry cooler holds a high potential for saving water and energy. Purely convective heat discharge during dry operation in the case of a high annual rate of utilisation, evaporative cooling during the wetting cycle at peak load times or high ambient temperatures and infinitely adjustable fan speed in both operating modes permit a very substantial recooling performance at low operating costs and with little space requirement. However, the efficiency of hybrid dry coolers depends to a large degree on how intelligently the cooling functions are controlled and on the control strategy. The present article demonstrates that the control strategy contributes decisively to minimising water and energy consumption and costs. Besides describing the actual functions of a hybrid cooler control system it presents a control strategy for automatic lowering of the setpoint and hence optimisation of the refrigeration process. It discusses the option of operating multiple hybrid coolers by means of a hydraulic network and presents an optimised control concept for this purpose which is based on a master control unit. In conclusion the study shows that hybrid coolers need their own optimised control unit if maximum savings in energy and water are to be achieved.

Flow optimisation of a biomass mixer; Stroemungstechnische Optimierung eines Biomasse-Ruehrwerks

Energy Technology Data Exchange (ETDEWEB)

Casartelli, E.; Waser, R. [Hochschule fuer Technik und Architektur Luzern (HTA), Horw (Switzerland); Fankhauser, H. [Fankhauser Maschinenfabrik, Malters (Switzerland)

2007-03-15

This illustrated final report for the Swiss Federal Office of Energy (SFOE) reports on the optimisation of a mixing system used in biomass reactors. Aim of this work was to improve the fluid dynamic qualities of the mixer in order to increase its efficiency while, at the same time, maintaining robustness and low price. Investigative work performed with CFD (Computational Fluid Dynamics) is reported on. CFD is quoted by the authors as being very effective in solving such optimisation problems as it is suited to flows that are not easily accessible for analysis. Experiments were performed on a fermenter / mixer model in order to confirm the computational findings. The results obtained with two and three-dimensional simulations are presented and discussed, as are those resulting from the tests with the 1:10 scale model of a digester. Initial tests with the newly developed mixer-propellers in a real-life biogas installation are reported on and further tests to be made are listed.

SLA-based optimisation of virtualised resource for multi-tier web applications in cloud data centres

Science.gov (United States)

Bi, Jing; Yuan, Haitao; Tie, Ming; Tan, Wei

2015-10-01

Dynamic virtualised resource allocation is the key to quality of service assurance for multi-tier web application services in cloud data centre. In this paper, we develop a self-management architecture of cloud data centres with virtualisation mechanism for multi-tier web application services. Based on this architecture, we establish a flexible hybrid queueing model to determine the amount of virtual machines for each tier of virtualised application service environments. Besides, we propose a non-linear constrained optimisation problem with restrictions defined in service level agreement. Furthermore, we develop a heuristic mixed optimisation algorithm to maximise the profit of cloud infrastructure providers, and to meet performance requirements from different clients as well. Finally, we compare the effectiveness of our dynamic allocation strategy with two other allocation strategies. The simulation results show that the proposed resource allocation method is efficient in improving the overall performance and reducing the resource energy cost.

Sequential projection pursuit for optimised vibration-based damage detection in an experimental wind turbine blade

Science.gov (United States)

Hoell, Simon; Omenzetter, Piotr

2018-02-01

To advance the concept of smart structures in large systems, such as wind turbines (WTs), it is desirable to be able to detect structural damage early while using minimal instrumentation. Data-driven vibration-based damage detection methods can be competitive in that respect because global vibrational responses encompass the entire structure. Multivariate damage sensitive features (DSFs) extracted from acceleration responses enable to detect changes in a structure via statistical methods. However, even though such DSFs contain information about the structural state, they may not be optimised for the damage detection task. This paper addresses the shortcoming by exploring a DSF projection technique specialised for statistical structural damage detection. High dimensional initial DSFs are projected onto a low-dimensional space for improved damage detection performance and simultaneous computational burden reduction. The technique is based on sequential projection pursuit where the projection vectors are optimised one by one using an advanced evolutionary strategy. The approach is applied to laboratory experiments with a small-scale WT blade under wind-like excitations. Autocorrelation function coefficients calculated from acceleration signals are employed as DSFs. The optimal numbers of projection vectors are identified with the help of a fast forward selection procedure. To benchmark the proposed method, selections of original DSFs as well as principal component analysis scores from these features are additionally investigated. The optimised DSFs are tested for damage detection on previously unseen data from the healthy state and a wide range of damage scenarios. It is demonstrated that using selected subsets of the initial and transformed DSFs improves damage detectability compared to the full set of features. Furthermore, superior results can be achieved by projecting autocorrelation coefficients onto just a single optimised projection vector.

Mechatronic System Design Based On An Optimisation Approach

DEFF Research Database (Denmark)

Andersen, Torben Ole; Pedersen, Henrik Clemmensen; Hansen, Michael Rygaard

The envisaged objective of this paper project is to extend the current state of the art regarding the design of complex mechatronic systems utilizing an optimisation approach. We propose to investigate a novel framework for mechatronic system design. The novelty and originality being the use...... of optimisation techniques. The methods used to optimise/design within the classical disciplines will be identified and extended to mechatronic system design....

Energy balance of the optimised CVT-hybrid-driveline

Energy Technology Data Exchange (ETDEWEB)

Hoehn, Bernd-Robert; Pflaum, Hermann; Lechner, Claus [Forschungsstelle fuer Zahnraeder und Getriebebau, Technische Univ. Muenchen, Garching (Germany)

2009-07-01

Funded by the DFG (German Research Foundation) and some industry partners like GM Powertrain Europe, ZF, EPCOS the Optimised CVT-Hybrid was developed at Technische Universitaet Muenchen in close collaboration with the industry and is currently under scientific investigation. Designed as a parallel hybrid vehicle the Optimised CVT-Hybrid combines a series-production diesel engine with a small electric motor. The core element of the driveline is a two range continuously variable transmission (i{radical}i-transmission), which is based on a chain variator. By a special shifting process without interruption of traction force the ratio range of the chain variator is used twice; thereby a wide transmission-ratio spread is achieved by low complexity. Thus the transmission provides a large pull-away ratio for the small electric motor and a fuel-efficient overdrive ratio for the ic-engine. Instead of heavy and space-consuming accumulators a small efficient package of double layer capacitors (UltraCaps) is used for electric energy and power storage. The driveline management is done by an optimised vehicle controller. Within the scope of the research project two prototype drivelines were manufactured. One driveline is integrated into an Opel Vectra Caravan and is available for investigations at the roller dynamometer and in the actual road traffic. The second hybrid driveline is assembled at the powertrain test rig of the FZG for detailed analysis of system behaviour and fuel consumption. Based on measurements of standardised driving cycles system behaviour, fuel consumption and a detailed energy balance of the Optimised CVT-Hybrid are presented. In comparison to the series-production vehicle the fuel savings are shown. (orig.)

Multi-terminal pipe routing by Steiner minimal tree and particle swarm optimisation

Science.gov (United States)

Liu, Qiang; Wang, Chengen

2012-08-01

Computer-aided design of pipe routing is of fundamental importance for complex equipments' developments. In this article, non-rectilinear branch pipe routing with multiple terminals that can be formulated as a Euclidean Steiner Minimal Tree with Obstacles (ESMTO) problem is studied in the context of an aeroengine-integrated design engineering. Unlike the traditional methods that connect pipe terminals sequentially, this article presents a new branch pipe routing algorithm based on the Steiner tree theory. The article begins with a new algorithm for solving the ESMTO problem by using particle swarm optimisation (PSO), and then extends the method to the surface cases by using geodesics to meet the requirements of routing non-rectilinear pipes on the surfaces of aeroengines. Subsequently, the adaptive region strategy and the basic visibility graph method are adopted to increase the computation efficiency. Numeral computations show that the proposed routing algorithm can find satisfactory routing layouts while running in polynomial time.

Optimisation of synergistic biomass-degrading enzyme systems for efficient rice straw hydrolysis using an experimental mixture design.

Science.gov (United States)

Suwannarangsee, Surisa; Bunterngsook, Benjarat; Arnthong, Jantima; Paemanee, Atchara; Thamchaipenet, Arinthip; Eurwilaichitr, Lily; Laosiripojana, Navadol; Champreda, Verawat

2012-09-01

Synergistic enzyme system for the hydrolysis of alkali-pretreated rice straw was optimised based on the synergy of crude fungal enzyme extracts with a commercial cellulase (Celluclast™). Among 13 enzyme extracts, the enzyme preparation from Aspergillus aculeatus BCC 199 exhibited the highest level of synergy with Celluclast™. This synergy was based on the complementary cellulolytic and hemicellulolytic activities of the BCC 199 enzyme extract. A mixture design was used to optimise the ternary enzyme complex based on the synergistic enzyme mixture with Bacillus subtilis expansin. Using the full cubic model, the optimal formulation of the enzyme mixture was predicted to the percentage of Celluclast™: BCC 199: expansin=41.4:37.0:21.6, which produced 769 mg reducing sugar/g biomass using 2.82 FPU/g enzymes. This work demonstrated the use of a systematic approach for the design and optimisation of a synergistic enzyme mixture of fungal enzymes and expansin for lignocellulosic degradation. Copyright © 2012 Elsevier Ltd. All rights reserved.

Wireless-Uplinks-Based Energy-Efficient Scheduling in Mobile Cloud Computing

OpenAIRE

Xing Liu; Chaowei Yuan; Zhen Yang; Enda Peng

2015-01-01

Mobile cloud computing (MCC) combines cloud computing and mobile internet to improve the computational capabilities of resource-constrained mobile devices (MDs). In MCC, mobile users could not only improve the computational capability of MDs but also save operation consumption by offloading the mobile applications to the cloud. However, MCC faces the problem of energy efficiency because of time-varying channels when the offloading is being executed. In this paper, we address the issue of ener...

Optimisation of decision making under uncertainty throughout field lifetime: A fractured reservoir example

Science.gov (United States)

Arnold, Dan; Demyanov, Vasily; Christie, Mike; Bakay, Alexander; Gopa, Konstantin

2016-10-01

Assessing the change in uncertainty in reservoir production forecasts over field lifetime is rarely undertaken because of the complexity of joining together the individual workflows. This becomes particularly important in complex fields such as naturally fractured reservoirs. The impact of this problem has been identified in previous and many solutions have been proposed but never implemented on complex reservoir problems due to the computational cost of quantifying uncertainty and optimising the reservoir development, specifically knowing how many and what kind of simulations to run. This paper demonstrates a workflow that propagates uncertainty throughout field lifetime, and into the decision making process by a combination of a metric-based approach, multi-objective optimisation and Bayesian estimation of uncertainty. The workflow propagates uncertainty estimates from appraisal into initial development optimisation, then updates uncertainty through history matching and finally propagates it into late-life optimisation. The combination of techniques applied, namely the metric approach and multi-objective optimisation, help evaluate development options under uncertainty. This was achieved with a significantly reduced number of flow simulations, such that the combined workflow is computationally feasible to run for a real-field problem. This workflow is applied to two synthetic naturally fractured reservoir (NFR) case studies in appraisal, field development, history matching and mid-life EOR stages. The first is a simple sector model, while the second is a more complex full field example based on a real life analogue. This study infers geological uncertainty from an ensemble of models that are based on the carbonate Brazilian outcrop which are propagated through the field lifetime, before and after the start of production, with the inclusion of production data significantly collapsing the spread of P10-P90 in reservoir forecasts. The workflow links uncertainty

Optimisation of LHCb Applications for Multi- and Manycore Job Submission

CERN Document Server

Rauschmayr, Nathalie; Graciani Diaz, Ricardo; Charpentier, Philippe

The Worldwide LHC Computing Grid (WLCG) is the largest Computing Grid and is used by all Large Hadron Collider experiments in order to process their recorded data. It provides approximately 400k cores and storages. Nowadays, most of the resources consist of multi- and manycore processors. Conditions at the Large Hadron Collider experiments will change and much larger workloads and jobs consuming more memory are expected in future. This has lead to a shift of paradigm which focuses on executing jobs as multiprocessor tasks in order to use multi- and manycore processors more efficiently. All experiments at CERN are currently investigating how such computing resources can be used more efficiently in terms of memory requirements and handling of concurrency. Until now, there are still many unsolved issues regarding software, scheduling, CPU accounting, task queues, which need to be solved by grid sites and experiments. This thesis develops a systematic approach to optimise the software of the LHCb experiment fo...

For Time-Continuous Optimisation

DEFF Research Database (Denmark)

Heinrich, Mary Katherine; Ayres, Phil

2016-01-01

Strategies for optimisation in design normatively assume an artefact end-point, disallowing continuous architecture that engages living systems, dynamic behaviour, and complex systems. In our Flora Robotica investigations of symbiotic plant-robot bio-hybrids, we re- quire computational tools...

Efficient quantum computing with weak measurements

International Nuclear Information System (INIS)

Lund, A P

2011-01-01

Projective measurements with high quantum efficiency are often assumed to be required for efficient circuit-based quantum computing. We argue that this is not the case and show that the fact that they are not required was actually known previously but was not deeply explored. We examine this issue by giving an example of how to perform the quantum-ordering-finding algorithm efficiently using non-local weak measurements considering that the measurements used are of bounded weakness and some fixed but arbitrary probability of success less than unity is required. We also show that it is possible to perform the same computation with only local weak measurements, but this must necessarily introduce an exponential overhead.

Validation of a large-scale audit technique for CT dose optimisation

International Nuclear Information System (INIS)

Wood, T. J.; Davis, A. W.; Moore, C. S.; Beavis, A. W.; Saunderson, J. R.

2008-01-01

The expansion and increasing availability of computed tomography (CT) imaging means that there is a greater need for the development of efficient optimisation strategies that are able to inform clinical practice, without placing a significant burden on limited departmental resources. One of the most fundamental aspects to any optimisation programme is the collection of patient dose information, which can be compared with appropriate diagnostic reference levels. This study has investigated the implementation of a large-scale audit technique, which utilises data that already exist in the radiology information system, to determine typical doses for a range of examinations on four CT scanners. This method has been validated against what is considered the 'gold standard' technique for patient dose audits, and it has been demonstrated that results equivalent to the 'standard-sized patient' can be inferred from this much larger data set. This is particularly valuable where CT optimisation is concerned as it is considered a 'high dose' technique, and hence close monitoring of patient dose is particularly important. (authors)

Research article – Optimisation of paediatrics computed radiographyfor full spine curvature measurements using a phantom: a pilot study

NARCIS (Netherlands)

de Haan, Seraphine; Reis, Cláudia; Ndlovu, Junior; Serrenho, Catarina; Akhtar, Ifrah; Garcia, José Antonio; Linde, Daniël; Thorskog, Martine; Franco, Loris; Hogg, Peter

2015-01-01

Aim: Optimise a set of exposure factors, with the lowest effective dose, to delineate spinal curvature with the modified Cobb method in a full spine using computed radiography (CR) for a 5-year-old paediatric anthropomorphic phantom. Methods: Images were acquired by varying a set of parameters:

High-efficiency photorealistic computer-generated holograms based on the backward ray-tracing technique

Science.gov (United States)

Wang, Yuan; Chen, Zhidong; Sang, Xinzhu; Li, Hui; Zhao, Linmin

2018-03-01

Holographic displays can provide the complete optical wave field of a three-dimensional (3D) scene, including the depth perception. However, it often takes a long computation time to produce traditional computer-generated holograms (CGHs) without more complex and photorealistic rendering. The backward ray-tracing technique is able to render photorealistic high-quality images, which noticeably reduce the computation time achieved from the high-degree parallelism. Here, a high-efficiency photorealistic computer-generated hologram method is presented based on the ray-tracing technique. Rays are parallelly launched and traced under different illuminations and circumstances. Experimental results demonstrate the effectiveness of the proposed method. Compared with the traditional point cloud CGH, the computation time is decreased to 24 s to reconstruct a 3D object of 100 ×100 rays with continuous depth change.

An Efficient UD-Based Algorithm for the Computation of Maximum Likelihood Sensitivity of Continuous-Discrete Systems

DEFF Research Database (Denmark)

Boiroux, Dimitri; Juhl, Rune; Madsen, Henrik

2016-01-01

This paper addresses maximum likelihood parameter estimation of continuous-time nonlinear systems with discrete-time measurements. We derive an efficient algorithm for the computation of the log-likelihood function and its gradient, which can be used in gradient-based optimization algorithms....... This algorithm uses UD decomposition of symmetric matrices and the array algorithm for covariance update and gradient computation. We test our algorithm on the Lotka-Volterra equations. Compared to the maximum likelihood estimation based on finite difference gradient computation, we get a significant speedup...

Process and Economic Optimisation of a Milk Processing Plant with Solar Thermal Energy

DEFF Research Database (Denmark)

Bühler, Fabian; Nguyen, Tuong-Van; Elmegaard, Brian

2016-01-01

. Based on the case study of a dairy factory, where first a heat integration is performed to optimise the system, a model for solar thermal process integration is developed. The detailed model is based on annual hourly global direct and diffuse solar radiation, from which the radiation on a defined......This work investigates the integration of solar thermal systems for process energy use. A shift from fossil fuels to renewable energy could be beneficial both from environmental and economic perspectives, after the process itself has been optimised and efficiency measures have been implemented...... surface is calculated. Based on hourly process stream data from the dairy factory, the optimal streams for solar thermal process integration are found, with an optimal thermal storagetank volume. The last step consists of an economic optimisation of the problem to determine the optimal size...

Finite Element Optimised Back Analysis of In Situ Stress Field and Stability Analysis of Shaft Wall in the Underground Gas Storage

Directory of Open Access Journals (Sweden)

Yifei Yan

2016-01-01

Full Text Available A novel optimised back analysis method is proposed in this paper. The in situ stress field of an underground gas storage (UGS reservoir in a Turkey salt cavern is analysed by the basic theory of elastic mechanics. A finite element method is implemented to optimise and approximate the objective function by systematically adjusting boundary loads. Optimising calculation is performed based on a novel method to reduce the error between measurement and calculation as much as possible. Compared with common back analysis methods such as regression method, the method proposed can further improve the calculation precision. By constructing a large circular geometric model, the effect of stress concentration is eliminated and a minimum difference between computed and measured stress can be guaranteed in the rectangular objective region. The efficiency of the proposed method is investigated and confirmed by its capability on restoring in situ stress field, which agrees well with experimental results. The characteristics of stress distribution of chosen UGS wells are obtained based on the back analysis results and by applying the corresponding fracture criterion, the shaft walls are proven safe.

Computationally efficient real-time interpolation algorithm for non-uniform sampled biosignals.

Science.gov (United States)

Guven, Onur; Eftekhar, Amir; Kindt, Wilko; Constandinou, Timothy G

2016-06-01

This Letter presents a novel, computationally efficient interpolation method that has been optimised for use in electrocardiogram baseline drift removal. In the authors' previous Letter three isoelectric baseline points per heartbeat are detected, and here utilised as interpolation points. As an extension from linear interpolation, their algorithm segments the interpolation interval and utilises different piecewise linear equations. Thus, the algorithm produces a linear curvature that is computationally efficient while interpolating non-uniform samples. The proposed algorithm is tested using sinusoids with different fundamental frequencies from 0.05 to 0.7 Hz and also validated with real baseline wander data acquired from the Massachusetts Institute of Technology University and Boston's Beth Israel Hospital (MIT-BIH) Noise Stress Database. The synthetic data results show an root mean square (RMS) error of 0.9 μV (mean), 0.63 μV (median) and 0.6 μV (standard deviation) per heartbeat on a 1 mVp-p 0.1 Hz sinusoid. On real data, they obtain an RMS error of 10.9 μV (mean), 8.5 μV (median) and 9.0 μV (standard deviation) per heartbeat. Cubic spline interpolation and linear interpolation on the other hand shows 10.7 μV, 11.6 μV (mean), 7.8 μV, 8.9 μV (median) and 9.8 μV, 9.3 μV (standard deviation) per heartbeat.

Integrated energy efficient data centre management for green cloud computing : the FP7 GENiC project experience

NARCIS (Netherlands)

Torrens, J.I.; Mehta, D.; Zavrel, V.; Grimes, D.; Scherer, Th.; Birke, R.; Chen, L.; Rea, S.; Lopez, L.; Pages, E.; Pesch, D.

2016-01-01

Energy consumed by computation and cooling represents the greatest percentage of the average energy consumed in a data centre. As these two aspects are not always coordinated, energy consumption is not optimised. Data centres lack an integrated system that jointly optimises and controls all the

MRI to X-ray mammography intensity-based registration with simultaneous optimisation of pose and biomechanical transformation parameters.

Science.gov (United States)

Mertzanidou, Thomy; Hipwell, John; Johnsen, Stian; Han, Lianghao; Eiben, Bjoern; Taylor, Zeike; Ourselin, Sebastien; Huisman, Henkjan; Mann, Ritse; Bick, Ulrich; Karssemeijer, Nico; Hawkes, David

2014-05-01

Determining corresponding regions between an MRI and an X-ray mammogram is a clinically useful task that is challenging for radiologists due to the large deformation that the breast undergoes between the two image acquisitions. In this work we propose an intensity-based image registration framework, where the biomechanical transformation model parameters and the rigid-body transformation parameters are optimised simultaneously. Patient-specific biomechanical modelling of the breast derived from diagnostic, prone MRI has been previously used for this task. However, the high computational time associated with breast compression simulation using commercial packages, did not allow the optimisation of both pose and FEM parameters in the same framework. We use a fast explicit Finite Element (FE) solver that runs on a graphics card, enabling the FEM-based transformation model to be fully integrated into the optimisation scheme. The transformation model has seven degrees of freedom, which include parameters for both the initial rigid-body pose of the breast prior to mammographic compression, and those of the biomechanical model. The framework was tested on ten clinical cases and the results were compared against an affine transformation model, previously proposed for the same task. The mean registration error was 11.6±3.8mm for the CC and 11±5.4mm for the MLO view registrations, indicating that this could be a useful clinical tool. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Optimising the neutron environment of Radiation Portal Monitors: A computational study

Energy Technology Data Exchange (ETDEWEB)

Gilbert, Mark R., E-mail: mark.gilbert@ccfe.ac.uk [United Kingdom Atomic Energy Authority, Culham Science Centre, Abingdon OX14 3DB (United Kingdom); Ghani, Zamir [United Kingdom Atomic Energy Authority, Culham Science Centre, Abingdon OX14 3DB (United Kingdom); McMillan, John E. [Department of Physics and Astronomy, University of Sheffield, Hicks building, Hounsfield Road, Sheffield S3 7RH (United Kingdom); Packer, Lee W. [United Kingdom Atomic Energy Authority, Culham Science Centre, Abingdon OX14 3DB (United Kingdom)

2015-09-21

Efficient and reliable detection of radiological or nuclear threats is a crucial part of national and international efforts to prevent terrorist activities. Radiation Portal Monitors (RPMs), which are deployed worldwide, are intended to interdict smuggled fissile material by detecting emissions of neutrons and gamma rays. However, considering the range and variety of threat sources, vehicular and shielding scenarios, and that only a small signature is present, it is important that the design of the RPMs allows these signatures to be accurately differentiated from the environmental background. Using Monte-Carlo neutron-transport simulations of a model {sup 3}He detector system we have conducted a parameter study to identify the optimum combination of detector shielding, moderation, and collimation that maximises the sensitivity of neutron-sensitive RPMs. These structures, which could be simply and cost-effectively added to existing RPMs, can improve the detector response by more than a factor of two relative to an unmodified, bare design. Furthermore, optimisation of the air gap surrounding the helium tubes also improves detector efficiency.

User-friendly Tool for Power Flow Analysis and Distributed Generation Optimisation in Radial Distribution Networks

Directory of Open Access Journals (Sweden)

M. F. Akorede

2017-06-01

Full Text Available The intent of power distribution companies (DISCOs is to deliver electric power to their customers in an efficient and reliable manner – with minimal energy loss cost. One major way to minimise power loss on a given power system is to install distributed generation (DG units on the distribution networks. However, to maximise benefits, it is highly crucial for a DISCO to ensure that these DG units are of optimal size and sited in the best locations on the network. This paper gives an overview of a software package developed in this study, called Power System Analysis and DG Optimisation Tool (PFADOT. The main purpose of the graphical user interface-based package is to guide a DISCO in finding the optimal size and location for DG placement in radial distribution networks. The package, which is also suitable for load flow analysis, employs the GUI feature of MATLAB. Three objective functions are formulated into a single optimisation problem and solved with fuzzy genetic algorithm to simultaneously obtain DG optimal size and location. The accuracy and reliability of the developed tool was validated using several radial test systems, and the results obtained are evaluated against the existing similar package cited in the literature, which are impressive and computationally efficient.

Efficient Secure Multiparty Subset Computation

Directory of Open Access Journals (Sweden)

Sufang Zhou

2017-01-01

Full Text Available Secure subset problem is important in secure multiparty computation, which is a vital field in cryptography. Most of the existing protocols for this problem can only keep the elements of one set private, while leaking the elements of the other set. In other words, they cannot solve the secure subset problem perfectly. While a few studies have addressed actual secure subsets, these protocols were mainly based on the oblivious polynomial evaluations with inefficient computation. In this study, we first design an efficient secure subset protocol for sets whose elements are drawn from a known set based on a new encoding method and homomorphic encryption scheme. If the elements of the sets are taken from a large domain, the existing protocol is inefficient. Using the Bloom filter and homomorphic encryption scheme, we further present an efficient protocol with linear computational complexity in the cardinality of the large set, and this is considered to be practical for inputs consisting of a large number of data. However, the second protocol that we design may yield a false positive. This probability can be rapidly decreased by reexecuting the protocol with different hash functions. Furthermore, we present the experimental performance analyses of these protocols.

Optimal design of CHP-based microgrids: Multiobjective optimisation and life cycle assessment

International Nuclear Information System (INIS)

Zhang, Di; Evangelisti, Sara; Lettieri, Paola; Papageorgiou, Lazaros G.

2015-01-01

As an alternative to current centralised energy generation systems, microgrids are adopted to provide local energy with lower energy expenses and gas emissions by utilising distributed energy resources (DER). Several micro combined heat and power technologies have been developed recently for applications at domestic scale. The optimal design of DERs within CHP-based microgrids plays an important role in promoting the penetration of microgrid systems. In this work, the optimal design of microgrids with CHP units is addressed by coupling environmental and economic sustainability in a multi-objective optimisation model which integrates the results of a life cycle assessment of the microgrids investigated. The results show that the installation of multiple CHP technologies has a lower cost with higher environmental saving compared with the case when only a single technology is installed in each site, meaning that the microgrid works in a more efficient way when multiple technologies are selected. In general, proton exchange membrane (PEM) fuel cells are chosen as the basic CHP technology for most solutions, which offers lower environmental impacts at low cost. However, internal combustions engines (ICE) and Stirling engines (SE) are preferred if the heat demand is high. - Highlights: • Optimal design of microgrids is addressed by coupling environmental and economic aspects. • An MILP model is formulated based on the ε-constraint method. • The model selects a combination of CHP technologies with different technical characteristics for optimum scenarios. • The global warming potential (GWP) and the acidification potential (AP) are determined. • The output of LCA is used as an input for the optimisation model

Optimisation of a parallel ocean general circulation model

Science.gov (United States)

Beare, M. I.; Stevens, D. P.

1997-10-01

This paper presents the development of a general-purpose parallel ocean circulation model, for use on a wide range of computer platforms, from traditional scalar machines to workstation clusters and massively parallel processors. Parallelism is provided, as a modular option, via high-level message-passing routines, thus hiding the technical intricacies from the user. An initial implementation highlights that the parallel efficiency of the model is adversely affected by a number of factors, for which optimisations are discussed and implemented. The resulting ocean code is portable and, in particular, allows science to be achieved on local workstations that could otherwise only be undertaken on state-of-the-art supercomputers.

Results of the 2010 IGSC Topical Session on Optimisation

International Nuclear Information System (INIS)

Bailey, Lucy

2014-01-01

topical session reflected the diversity of optimisation goals that may be pursued in the framework of a geological disposal programme. While optimisation of protection, as defined by ICRP, is regarded as a process to keep the magnitude of individual doses, the number of people exposed, and the likelihood of potential exposure as low as reasonably achievable with economic and social factors being taken into account, optimisation can also be seen as a way of increasing the technical quality and robustness of the whole waste management process. An optimal solution means addressing safety requirements whilst balancing other factors such as the need to use resources efficiently, political and acceptance issues and any other boundary conditions imposed by society. It was noted that optimisation variables are not well defined and could be quite programme-specific. However, the discussion showed a lot of agreement and consensus of views. In particular, the summary noted general agreement on the following points: - Optimisation is a process that can be checked and reviewed and needs to be transparent. Optimisation is therefore a learning process, and as such can contribute to building confidence in the safety case by the demonstration of ongoing learning across the organisation. - Optimisation occurs at each stage of the disposal facility development programme, and is therefore forward looking rather than focussed on re-examining past decisions. Optimisation should be about the right way forward at each stage, making the best decisions to move forward from the present situation based on current knowledge and understanding. - Regulators need to be clear about their requirements and these requirements become constraints on the optimisation process, together with any societal constraints that may be applied in certain programmes. Optimisation therefore requires a permanent dialogue between regulator and implementer. - Once the safety objectives (dose/risk targets and other

A hybrid credibility-based fuzzy multiple objective optimisation to differential pricing and inventory policies with arbitrage consideration

Science.gov (United States)

Ghasemy Yaghin, R.; Fatemi Ghomi, S. M. T.; Torabi, S. A.

2015-10-01

In most markets, price differentiation mechanisms enable manufacturers to offer different prices for their products or services in different customer segments; however, the perfect price discrimination is usually impossible for manufacturers. The importance of accounting for uncertainty in such environments spurs an interest to develop appropriate decision-making tools to deal with uncertain and ill-defined parameters in joint pricing and lot-sizing problems. This paper proposes a hybrid bi-objective credibility-based fuzzy optimisation model including both quantitative and qualitative objectives to cope with these issues. Taking marketing and lot-sizing decisions into account simultaneously, the model aims to maximise the total profit of manufacturer and to improve service aspects of retailing simultaneously to set different prices with arbitrage consideration. After applying appropriate strategies to defuzzify the original model, the resulting non-linear multi-objective crisp model is then solved by a fuzzy goal programming method. An efficient stochastic search procedure using particle swarm optimisation is also proposed to solve the non-linear crisp model.

Analysis and optimisation of heterogeneous real-time embedded systems

DEFF Research Database (Denmark)

Pop, Paul; Eles, Petru; Peng, Zebo

2005-01-01

. The success of such new design methods depends on the availability of analysis and optimisation techniques. Analysis and optimisation techniques for heterogeneous real-time embedded systems are presented in the paper. The authors address in more detail a particular class of such systems called multi...... of application messages to frames. Optimisation heuristics for frame packing aimed at producing a schedulable system are presented. Extensive experiments and a real-life example show the efficiency of the frame-packing approach....

Analysis and optimisation of heterogeneous real-time embedded systems

DEFF Research Database (Denmark)

Pop, Paul; Eles, Petru; Peng, Zebo

2006-01-01

. The success of such new design methods depends on the availability of analysis and optimisation techniques. Analysis and optimisation techniques for heterogeneous real-time embedded systems are presented in the paper. The authors address in more detail a particular class of such systems called multi...... of application messages to frames. Optimisation heuristics for frame packing aimed at producing a schedulable system are presented. Extensive experiments and a real-life example show the efficiency of the frame-packing approach....

Dendritic nonlinearities are tuned for efficient spike-based computations in cortical circuits.

Science.gov (United States)

Ujfalussy, Balázs B; Makara, Judit K; Branco, Tiago; Lengyel, Máté

2015-12-24

Cortical neurons integrate thousands of synaptic inputs in their dendrites in highly nonlinear ways. It is unknown how these dendritic nonlinearities in individual cells contribute to computations at the level of neural circuits. Here, we show that dendritic nonlinearities are critical for the efficient integration of synaptic inputs in circuits performing analog computations with spiking neurons. We developed a theory that formalizes how a neuron's dendritic nonlinearity that is optimal for integrating synaptic inputs depends on the statistics of its presynaptic activity patterns. Based on their in vivo preynaptic population statistics (firing rates, membrane potential fluctuations, and correlations due to ensemble dynamics), our theory accurately predicted the responses of two different types of cortical pyramidal cells to patterned stimulation by two-photon glutamate uncaging. These results reveal a new computational principle underlying dendritic integration in cortical neurons by suggesting a functional link between cellular and systems--level properties of cortical circuits.

Computer-based teaching module design: principles derived from learning theories.

Science.gov (United States)

Lau, K H Vincent

2014-03-01

The computer-based teaching module (CBTM), which has recently gained prominence in medical education, is a teaching format in which a multimedia program serves as a single source for knowledge acquisition rather than playing an adjunctive role as it does in computer-assisted learning (CAL). Despite empirical validation in the past decade, there is limited research into the optimisation of CBTM design. This review aims to summarise research in classic and modern multimedia-specific learning theories applied to computer learning, and to collapse the findings into a set of design principles to guide the development of CBTMs. Scopus was searched for: (i) studies of classic cognitivism, constructivism and behaviourism theories (search terms: 'cognitive theory' OR 'constructivism theory' OR 'behaviourism theory' AND 'e-learning' OR 'web-based learning') and their sub-theories applied to computer learning, and (ii) recent studies of modern learning theories applied to computer learning (search terms: 'learning theory' AND 'e-learning' OR 'web-based learning') for articles published between 1990 and 2012. The first search identified 29 studies, dominated in topic by the cognitive load, elaboration and scaffolding theories. The second search identified 139 studies, with diverse topics in connectivism, discovery and technical scaffolding. Based on their relative representation in the literature, the applications of these theories were collapsed into a list of CBTM design principles. Ten principles were identified and categorised into three levels of design: the global level (managing objectives, framing, minimising technical load); the rhetoric level (optimising modality, making modality explicit, scaffolding, elaboration, spaced repeating), and the detail level (managing text, managing devices). This review examined the literature in the application of learning theories to CAL to develop a set of principles that guide CBTM design. Further research will enable educators to

Evolutionary programming for neutron instrument optimisation

Energy Technology Data Exchange (ETDEWEB)

Bentley, Phillip M. [Hahn-Meitner Institut, Glienicker Strasse 100, D-14109 Berlin (Germany)]. E-mail: phillip.bentley@hmi.de; Pappas, Catherine [Hahn-Meitner Institut, Glienicker Strasse 100, D-14109 Berlin (Germany); Habicht, Klaus [Hahn-Meitner Institut, Glienicker Strasse 100, D-14109 Berlin (Germany); Lelievre-Berna, Eddy [Institut Laue-Langevin, 6 rue Jules Horowitz, BP 156, 38042 Grenoble Cedex 9 (France)

2006-11-15

Virtual instruments based on Monte-Carlo techniques are now integral part of novel instrumentation development and the existing codes (McSTAS and Vitess) are extensively used to define and optimise novel instrumental concepts. Neutron spectrometers, however, involve a large number of parameters and their optimisation is often a complex and tedious procedure. Artificial intelligence algorithms are proving increasingly useful in such situations. Here, we present an automatic, reliable and scalable numerical optimisation concept based on the canonical genetic algorithm (GA). The algorithm was used to optimise the 3D magnetic field profile of the NSE spectrometer SPAN, at the HMI. We discuss the potential of the GA which combined with the existing Monte-Carlo codes (Vitess, McSTAS, etc.) leads to a very powerful tool for automated global optimisation of a general neutron scattering instrument, avoiding local optimum configurations.

Evolutionary programming for neutron instrument optimisation

International Nuclear Information System (INIS)

Bentley, Phillip M.; Pappas, Catherine; Habicht, Klaus; Lelievre-Berna, Eddy

2006-01-01

Virtual instruments based on Monte-Carlo techniques are now integral part of novel instrumentation development and the existing codes (McSTAS and Vitess) are extensively used to define and optimise novel instrumental concepts. Neutron spectrometers, however, involve a large number of parameters and their optimisation is often a complex and tedious procedure. Artificial intelligence algorithms are proving increasingly useful in such situations. Here, we present an automatic, reliable and scalable numerical optimisation concept based on the canonical genetic algorithm (GA). The algorithm was used to optimise the 3D magnetic field profile of the NSE spectrometer SPAN, at the HMI. We discuss the potential of the GA which combined with the existing Monte-Carlo codes (Vitess, McSTAS, etc.) leads to a very powerful tool for automated global optimisation of a general neutron scattering instrument, avoiding local optimum configurations

Time varying acceleration coefficients particle swarm optimisation (TVACPSO): A new optimisation algorithm for estimating parameters of PV cells and modules

International Nuclear Information System (INIS)

Jordehi, Ahmad Rezaee

2016-01-01

Highlights: • A modified PSO has been proposed for parameter estimation of PV cells and modules. • In the proposed modified PSO, acceleration coefficients are changed during run. • The proposed modified PSO mitigates premature convergence problem. • Parameter estimation problem has been solved for both PV cells and PV modules. • The results show that proposed PSO outperforms other state of the art algorithms. - Abstract: Estimating circuit model parameters of PV cells/modules represents a challenging problem. PV cell/module parameter estimation problem is typically translated into an optimisation problem and is solved by metaheuristic optimisation problems. Particle swarm optimisation (PSO) is considered as a popular and well-established optimisation algorithm. Despite all its advantages, PSO suffers from premature convergence problem meaning that it may get trapped in local optima. Personal and social acceleration coefficients are two control parameters that, due to their effect on explorative and exploitative capabilities, play important roles in computational behavior of PSO. In this paper, in an attempt toward premature convergence mitigation in PSO, its personal acceleration coefficient is decreased during the course of run, while its social acceleration coefficient is increased. In this way, an appropriate tradeoff between explorative and exploitative capabilities of PSO is established during the course of run and premature convergence problem is significantly mitigated. The results vividly show that in parameter estimation of PV cells and modules, the proposed time varying acceleration coefficients PSO (TVACPSO) offers more accurate parameters than conventional PSO, teaching learning-based optimisation (TLBO) algorithm, imperialistic competitive algorithm (ICA), grey wolf optimisation (GWO), water cycle algorithm (WCA), pattern search (PS) and Newton algorithm. For validation of the proposed methodology, parameter estimation has been done both for

Efficiency using computer simulation of Reverse Threshold Model Theory on assessing a “One Laptop Per Child” computer versus desktop computer

Directory of Open Access Journals (Sweden)

Supat Faarungsang

2017-04-01

Full Text Available The Reverse Threshold Model Theory (RTMT model was introduced based on limiting factor concepts, but its efficiency compared to the Conventional Model (CM has not been published. This investigation assessed the efficiency of RTMT compared to CM using computer simulation on the “One Laptop Per Child” computer and a desktop computer. Based on probability values, it was found that RTMT was more efficient than CM among eight treatment combinations and an earlier study verified that RTMT gives complete elimination of random error. Furthermore, RTMT has several advantages over CM and is therefore proposed to be applied to most research data.

An exergy-based multi-objective optimisation model for energy retrofit strategies in non-domestic buildings

International Nuclear Information System (INIS)

García Kerdan, Iván; Raslan, Rokia; Ruyssevelt, Paul

2016-01-01

While the building sector has a significant thermodynamic improvement potential, exergy analysis has been shown to provide new insight for the optimisation of building energy systems. This paper presents an exergy-based multi-objective optimisation tool that aims to assess the impact of a diverse range of retrofit measures with a focus on non-domestic buildings. EnergyPlus was used as a dynamic calculation engine for first law analysis, while a Python add-on was developed to link dynamic exergy analysis and a Genetic Algorithm optimisation process with the aforementioned software. Two UK archetype case studies (an office and a primary school) were used to test the feasibility of the proposed framework. Different measures combinations based on retrofitting the envelope insulation levels and the application of different HVAC configurations were assessed. The objective functions in this study are annual energy use, occupants' thermal comfort, and total building exergy destructions. A large range of optimal solutions was achieved highlighting the framework capabilities. The model achieved improvements of 53% in annual energy use, 51% of exergy destructions and 66% of thermal comfort for the school building, and 50%, 33%, and 80% for the office building. This approach can be extended by using exergoeconomic optimisation. - Highlights: • Integration of dynamic exergy analysis into a retrofit-oriented simulation tool. • Two UK non-domestic building archetypes are used as case studies. • The model delivers non-dominated solutions based on energy, exergy and comfort. • Exergy destructions of ERMs are optimised using GA algorithms. • Strengths and limitations of the proposed exergy-based framework are discussed.

Electricity storages - optimised operation based on spot market prices; Stromspeicher. Optimierte Fahrweise auf Basis der Spotmarktpreise

Energy Technology Data Exchange (ETDEWEB)

Bernhard, Dominik; Roon, Serafin von [FfE Forschungsstelle fuer Energiewirtschaft e.V., Muenchen (Germany)

2010-06-15

With its integrated energy and climate package the last federal government set itself ambitious goals for the improvement of energy efficiency and growth of renewable energy production. These goals were confirmed by the new government in its coalition agreement. However, they can only be realised if the supply of electricity from fluctuating renewable sources can be made to coincide with electricity demand. Electricity storages are therefore an indispensable component of the future energy supply system. This article studies the optimised operation of an electricity storage based on spot market prices and the influence of wind power production up to the year 2020.

Applying a Global Sensitivity Analysis Workflow to Improve the Computational Efficiencies in Physiologically-Based Pharmacokinetic Modeling

Directory of Open Access Journals (Sweden)

Nan-Hung Hsieh

2018-06-01

Full Text Available Traditionally, the solution to reduce parameter dimensionality in a physiologically-based pharmacokinetic (PBPK model is through expert judgment. However, this approach may lead to bias in parameter estimates and model predictions if important parameters are fixed at uncertain or inappropriate values. The purpose of this study was to explore the application of global sensitivity analysis (GSA to ascertain which parameters in the PBPK model are non-influential, and therefore can be assigned fixed values in Bayesian parameter estimation with minimal bias. We compared the elementary effect-based Morris method and three variance-based Sobol indices in their ability to distinguish “influential” parameters to be estimated and “non-influential” parameters to be fixed. We illustrated this approach using a published human PBPK model for acetaminophen (APAP and its two primary metabolites APAP-glucuronide and APAP-sulfate. We first applied GSA to the original published model, comparing Bayesian model calibration results using all the 21 originally calibrated model parameters (OMP, determined by “expert judgment”-based approach vs. the subset of original influential parameters (OIP, determined by GSA from the OMP. We then applied GSA to all the PBPK parameters, including those fixed in the published model, comparing the model calibration results using this full set of 58 model parameters (FMP vs. the full set influential parameters (FIP, determined by GSA from FMP. We also examined the impact of different cut-off points to distinguish the influential and non-influential parameters. We found that Sobol indices calculated by eFAST provided the best combination of reliability (consistency with other variance-based methods and efficiency (lowest computational cost to achieve convergence in identifying influential parameters. We identified several originally calibrated parameters that were not influential, and could be fixed to improve computational

Optimisation in X-ray and Molecular Imaging 2015

International Nuclear Information System (INIS)

Baath, Magnus; Hoeschen, Christoph; Mattsson, Soeren; Mansson, Lars Gunnar

2016-01-01

This issue of Radiation Protection Dosimetry is based on contributions to Optimisation in X-ray and Molecular Imaging 2015 - the 4. Malmoe Conference on Medical Imaging (OXMI 2015). The conference was jointly organised by members of former and current research projects supported by the European Commission EURATOM Radiation Protection Research Programme, in cooperation with the Swedish Society for Radiation Physics. The conference brought together over 150 researchers and other professionals from hospitals, universities and industries with interests in different aspects of the optimisation of medical imaging. More than 100 presentations were given at this international gathering of medical physicists, radiologists, engineers, technicians, nurses and educational researchers. Additionally, invited talks were offered by world-renowned experts on radiation protection, spectral imaging and medical image perception, thus covering several important aspects of the generation and interpretation of medical images. The conference consisted of 13 oral sessions and a poster session, as reflected by the conference title connected by their focus on the optimisation of the use ionising radiation in medical imaging. The conference included technology-specific topics such as computed tomography and tomosynthesis, but also generic issues of interest for the optimisation of all medical imaging, such as image perception and quality assurance. Radiation protection was covered by e.g. sessions on patient dose benchmarking and occupational exposure. Technically-advanced topics such as modelling, Monte Carlo simulation, reconstruction, classification, and segmentation were seen taking advantage of recent developments of hardware and software, showing that the optimisation community is at the forefront of technology and adapts well to new requirements. These peer-reviewed proceedings, representing a continuation of a series of selected reports from meetings in the field of medical imaging

Modelling study, efficiency analysis and optimisation of large-scale Adiabatic Compressed Air Energy Storage systems with low-temperature thermal storage

International Nuclear Information System (INIS)

Luo, Xing; Wang, Jihong; Krupke, Christopher; Wang, Yue; Sheng, Yong; Li, Jian; Xu, Yujie; Wang, Dan; Miao, Shihong; Chen, Haisheng

2016-01-01

Highlights: • The paper presents an A-CAES system thermodynamic model with low temperature thermal energy storage integration. • The initial parameter value ranges for A-CAES system simulation are identified from the study of a CAES plant in operation. • The strategies of system efficiency improvement are investigated via a parametric study with a sensitivity analysis. • Various system configurations are discussed for analysing the efficiency improvement potentials. - Abstract: The key feature of Adiabatic Compressed Air Energy Storage (A-CAES) is the reuse of the heat generated from the air compression process at the stage of air expansion. This increases the complexity of the whole system since the heat exchange and thermal storage units must have the capacities and performance to match the air compression/expansion units. Thus it raises a strong demand in the whole system modelling and simulation tool for A-CAES system optimisation. The paper presents a new whole system mathematical model for A-CAES with simulation implementation and the model is developed with consideration of lowing capital cost of the system. The paper then focuses on the study of system efficiency improvement strategies via parametric analysis and system structure optimisation. The paper investigates how the system efficiency is affected by the system component performance and parameters. From the study, the key parameters are identified, which give dominant influences in improving the system efficiency. The study is extended onto optimal system configuration and the recommendations are made for achieving higher efficiency, which provides a useful guidance for A-CAES system design.

Topology optimisation of natural convection problems

DEFF Research Database (Denmark)

Alexandersen, Joe; Aage, Niels; Andreasen, Casper Schousboe

2014-01-01

This paper demonstrates the application of the density-based topology optimisation approach for the design of heat sinks and micropumps based on natural convection effects. The problems are modelled under the assumptions of steady-state laminar flow using the incompressible Navier-Stokes equations...... coupled to the convection-diffusion equation through the Boussinesq approximation. In order to facilitate topology optimisation, the Brinkman approach is taken to penalise velocities inside the solid domain and the effective thermal conductivity is interpolated in order to accommodate differences...... in thermal conductivity of the solid and fluid phases. The governing equations are discretised using stabilised finite elements and topology optimisation is performed for two different problems using discrete adjoint sensitivity analysis. The study shows that topology optimisation is a viable approach...

ICT for whole life optimisation of residential buildings

Energy Technology Data Exchange (ETDEWEB)

Haekkinen, T.; Vares, S.; Huovila, P.; Vesikari, E.; Porkka, J. (VTT Technical Research Centre of Finland, Espoo (FI)); Nilsson, L.-O.; Togeroe, AA. (Lund University (SE)); Jonsson, C.; Suber, K. (Skanska Sverige AB (SE)); Andersson, R.; Larsson, R. (Cementa, Malmoe (SE)); Nuorkivi, I. (Skanska Oyj, Helsinki (FI))

2007-08-15

The research project 'ICT for whole life optimisation of residential buildings' (ICTWLORB) developed and tested the whole life design and optimisation methods for residential buildings. The objective of the ICTWLORB project was to develop and implement an ICT based tool box for integrated life cycle design of residential building. ICTWLORB was performed in cooperation with Swedish and Finnish partners. The ICTWLORB project defined as a premise that an industrialised building process is characterised by two main elements: a building concept based approach and efficient information management. Building concept based approach enables (1) the product development of the end product, (2) repetition of the basic elements of the building from one project to others and (3) customisation of the end-product considering the specific needs of the case and the client. Information management enables (1) the consideration of wide spectrum of aspects including building performance, environmental aspects, life cycle costs and service life, and (2) rapid adapting of the design to the specific requirements of the case. (orig.)

Methodological principles for optimising functional MRI experiments

International Nuclear Information System (INIS)

Wuestenberg, T.; Giesel, F.L.; Strasburger, H.

2005-01-01

Functional magnetic resonance imaging (fMRI) is one of the most common methods for localising neuronal activity in the brain. Even though the sensitivity of fMRI is comparatively low, the optimisation of certain experimental parameters allows obtaining reliable results. In this article, approaches for optimising the experimental design, imaging parameters and analytic strategies will be discussed. Clinical neuroscientists and interested physicians will receive practical rules of thumb for improving the efficiency of brain imaging experiments. (orig.) [de

Optimisation of a parallel ocean general circulation model

Directory of Open Access Journals (Sweden)

M. I. Beare

1997-10-01

Full Text Available This paper presents the development of a general-purpose parallel ocean circulation model, for use on a wide range of computer platforms, from traditional scalar machines to workstation clusters and massively parallel processors. Parallelism is provided, as a modular option, via high-level message-passing routines, thus hiding the technical intricacies from the user. An initial implementation highlights that the parallel efficiency of the model is adversely affected by a number of factors, for which optimisations are discussed and implemented. The resulting ocean code is portable and, in particular, allows science to be achieved on local workstations that could otherwise only be undertaken on state-of-the-art supercomputers.

Optimisation of a parallel ocean general circulation model

Directory of Open Access Journals (Sweden)

M. I. Beare

Full Text Available This paper presents the development of a general-purpose parallel ocean circulation model, for use on a wide range of computer platforms, from traditional scalar machines to workstation clusters and massively parallel processors. Parallelism is provided, as a modular option, via high-level message-passing routines, thus hiding the technical intricacies from the user. An initial implementation highlights that the parallel efficiency of the model is adversely affected by a number of factors, for which optimisations are discussed and implemented. The resulting ocean code is portable and, in particular, allows science to be achieved on local workstations that could otherwise only be undertaken on state-of-the-art supercomputers.

Dimensional ranges and rolling efficiency in a tandem cold rolling mill

Energy Technology Data Exchange (ETDEWEB)

Larkiola, J.

1997-12-31

In this work, physical models and a neural network theory have been combined in order to predict the properties of a steel strip and to optimise the process parameters in cold rolling. The prediction of the deformation resistance of the material and the friction parameter is based on the physical model presented by Bland, Ford and Ellis and artificial neural network computing (ANN). The accuracy of these models has been tested and proved by using a large amount of the measured data. With the aid of these models it has been shown that (a) the small change to the relative reduction distribution can have a clear effect upon the rolling efficiency, (b) the dimensional ranges of the tandem cold roll mill can be determined and optimised and (c) the possibility to cold roll a new product of new width, strength or thickness can be determined and the parameters of the tandem cold rolling process can be optimised. (orig.) 43 refs.

Optimisation of groundwater level monitoring networks using geostatistical modelling based on the Spartan family variogram and a genetic algorithm method

Science.gov (United States)

Parasyris, Antonios E.; Spanoudaki, Katerina; Kampanis, Nikolaos A.

2016-04-01

Groundwater level monitoring networks provide essential information for water resources management, especially in areas with significant groundwater exploitation for agricultural and domestic use. Given the high maintenance costs of these networks, development of tools, which can be used by regulators for efficient network design is essential. In this work, a monitoring network optimisation tool is presented. The network optimisation tool couples geostatistical modelling based on the Spartan family variogram with a genetic algorithm method and is applied to Mires basin in Crete, Greece, an area of high socioeconomic and agricultural interest, which suffers from groundwater overexploitation leading to a dramatic decrease of groundwater levels. The purpose of the optimisation tool is to determine which wells to exclude from the monitoring network because they add little or no beneficial information to groundwater level mapping of the area. Unlike previous relevant investigations, the network optimisation tool presented here uses Ordinary Kriging with the recently-established non-differentiable Spartan variogram for groundwater level mapping, which, based on a previous geostatistical study in the area leads to optimal groundwater level mapping. Seventy boreholes operate in the area for groundwater abstraction and water level monitoring. The Spartan variogram gives overall the most accurate groundwater level estimates followed closely by the power-law model. The geostatistical model is coupled to an integer genetic algorithm method programmed in MATLAB 2015a. The algorithm is used to find the set of wells whose removal leads to the minimum error between the original water level mapping using all the available wells in the network and the groundwater level mapping using the reduced well network (error is defined as the 2-norm of the difference between the original mapping matrix with 70 wells and the mapping matrix of the reduced well network). The solution to the

Optimised Design and Analysis of All-Optical Networks

DEFF Research Database (Denmark)

Glenstrup, Arne John

2002-01-01

through various experiments and is shown to produce good results and to be able to scale up to networks of realistic sizes. A novel method, subpath wavelength grouping, for routing connections in a multigranular all-optical network where several wavelengths can be grouped and switched at band and fibre......This PhD thesis presents a suite of methods for optimising design and for analysing blocking probabilities of all-optical networks. It thus contributes methodical knowledge to the field of computer assisted planning of optical networks. A two-stage greenfield optical network design optimiser...... is developed, based on shortest-path algorithms and a comparatively new metaheuristic called simulated allocation. It is able to handle design of all-optical mesh networks with optical cross-connects, considers duct as well as fibre and node costs, and can also design protected networks. The method is assessed...

Optimising Shovel-Truck Fuel Consumption using Stochastic ...

African Journals Online (AJOL)

Optimising the fuel consumption and truck waiting time can result in significant fuel savings. The paper demonstrates that stochastic simulation is an effective tool for optimising the utilisation of fossil-based fuels in mining and related industries. Keywords: Stochastic, Simulation Modelling, Mining, Optimisation, Shovel-Truck ...

Reference voltage calculation method based on zero-sequence component optimisation for a regional compensation DVR

Science.gov (United States)

Jian, Le; Cao, Wang; Jintao, Yang; Yinge, Wang

2018-04-01

This paper describes the design of a dynamic voltage restorer (DVR) that can simultaneously protect several sensitive loads from voltage sags in a region of an MV distribution network. A novel reference voltage calculation method based on zero-sequence voltage optimisation is proposed for this DVR to optimise cost-effectiveness in compensation of voltage sags with different characteristics in an ungrounded neutral system. Based on a detailed analysis of the characteristics of voltage sags caused by different types of faults and the effect of the wiring mode of the transformer on these characteristics, the optimisation target of the reference voltage calculation is presented with several constraints. The reference voltages under all types of voltage sags are calculated by optimising the zero-sequence component, which can reduce the degree of swell in the phase-to-ground voltage after compensation to the maximum extent and can improve the symmetry degree of the output voltages of the DVR, thereby effectively increasing the compensation ability. The validity and effectiveness of the proposed method are verified by simulation and experimental results.

Multidisciplinary Design Optimisation (MDO) Methods: Their Synergy with Computer Technology in the Design Process

Science.gov (United States)

Sobieszczanski-Sobieski, Jaroslaw

1999-01-01

The paper identifies speed, agility, human interface, generation of sensitivity information, task decomposition, and data transmission (including storage) as important attributes for a computer environment to have in order to support engineering design effectively. It is argued that when examined in terms of these attributes the presently available environment can be shown to be inadequate. A radical improvement is needed, and it may be achieved by combining new methods that have recently emerged from multidisciplinary design optimisation (MDO) with massively parallel processing computer technology. The caveat is that, for successful use of that technology in engineering computing, new paradigms for computing will have to be developed - specifically, innovative algorithms that are intrinsically parallel so that their performance scales up linearly with the number of processors. It may be speculated that the idea of simulating a complex behaviour by interaction of a large number of very simple models may be an inspiration for the above algorithms; the cellular automata are an example. Because of the long lead time needed to develop and mature new paradigms, development should begin now, even though the widespread availability of massively parallel processing is still a few years away.

A Distributed Snapshot Protocol for Efficient Artificial Intelligence Computation in Cloud Computing Environments

Directory of Open Access Journals (Sweden)

JongBeom Lim

2018-01-01

Full Text Available Many artificial intelligence applications often require a huge amount of computing resources. As a result, cloud computing adoption rates are increasing in the artificial intelligence field. To support the demand for artificial intelligence applications and guarantee the service level agreement, cloud computing should provide not only computing resources but also fundamental mechanisms for efficient computing. In this regard, a snapshot protocol has been used to create a consistent snapshot of the global state in cloud computing environments. However, the existing snapshot protocols are not optimized in the context of artificial intelligence applications, where large-scale iterative computation is the norm. In this paper, we present a distributed snapshot protocol for efficient artificial intelligence computation in cloud computing environments. The proposed snapshot protocol is based on a distributed algorithm to run interconnected multiple nodes in a scalable fashion. Our snapshot protocol is able to deal with artificial intelligence applications, in which a large number of computing nodes are running. We reveal that our distributed snapshot protocol guarantees the correctness, safety, and liveness conditions.

Optimising resource management in neurorehabilitation.

Science.gov (United States)

Wood, Richard M; Griffiths, Jeff D; Williams, Janet E; Brouwers, Jakko

2014-01-01

To date, little research has been published regarding the effective and efficient management of resources (beds and staff) in neurorehabilitation, despite being an expensive service in limited supply. To demonstrate how mathematical modelling can be used to optimise service delivery, by way of a case study at a major 21 bed neurorehabilitation unit in the UK. An automated computer program for assigning weekly treatment sessions is developed. Queue modelling is used to construct a mathematical model of the hospital in terms of referral submissions to a waiting list, admission and treatment, and ultimately discharge. This is used to analyse the impact of hypothetical strategic decisions on a variety of performance measures and costs. The project culminates in a hybridised model of these two approaches, since a relationship is found between the number of therapy hours received each week (scheduling output) and length of stay (queuing model input). The introduction of the treatment scheduling program has substantially improved timetable quality (meaning a better and fairer service to patients) and has reduced employee time expended in its creation by approximately six hours each week (freeing up time for clinical work). The queuing model has been used to assess the effect of potential strategies, such as increasing the number of beds or employing more therapists. The use of mathematical modelling has not only optimised resources in the short term, but has allowed the optimality of longer term strategic decisions to be assessed.

Geometrical exploration of a flux-optimised sodium receiver through multi-objective optimisation

Science.gov (United States)

Asselineau, Charles-Alexis; Corsi, Clothilde; Coventry, Joe; Pye, John

2017-06-01

A stochastic multi-objective optimisation method is used to determine receiver geometries with maximum second law efficiency, minimal average temperature and minimal surface area. The method is able to identify a set of Pareto optimal candidates that show advantageous geometrical features, mainly in being able to maximise the intercepted flux within the geometrical boundaries set. Receivers with first law thermal efficiencies ranging from 87% to 91% are also evaluated using the second law of thermodynamics and found to have similar efficiencies of over 60%, highlighting the influence that the geometry can play in the maximisation of the work output of receivers by influencing the distribution of the flux from the concentrator.

Intelligent Internet-based information system optimises diabetes mellitus management in communities.

Science.gov (United States)

Wei, Xuejuan; Wu, Hao; Cui, Shuqi; Ge, Caiying; Wang, Li; Jia, Hongyan; Liang, Wannian

2018-05-01

To evaluate the effect of an intelligent Internet-based information system upon optimising the management of patients diagnosed with type 2 diabetes mellitus (T2DM). In 2015, a T2DM information system was introduced to optimise the management of T2DM patients for 1 year in Fangzhuang community of Beijing, China. A total of 602 T2DM patients who were registered in the health service centre of Fangzhuang community were enrolled based on an isometric sampling technique. The data from 587 patients were used in the final analysis. The intervention effect was subsequently assessed by statistically comparing multiple parameters, such as the prevalence of glycaemic control, standard health management and annual outpatient consultation visits per person, before and after the implementation of the T2DM information system. In 2015, a total of 1668 T2DM patients were newly registered in Fangzhuang community. The glycaemic control rate was calculated as 37.65% in 2014 and significantly elevated up to 62.35% in 2015 ( p information system, the rate of standard health management was increased from 48.04% to 85.01% ( p information system optimised the management of T2DM patients in Fangzhuang community and decreased the outpatient numbers in both community and general hospitals, which played a positive role in assisting T2DM patients and their healthcare providers to better manage this chronic illness.

Power-Efficient Computing: Experiences from the COSA Project

Directory of Open Access Journals (Sweden)

Daniele Cesini

2017-01-01

Full Text Available Energy consumption is today one of the most relevant issues in operating HPC systems for scientific applications. The use of unconventional computing systems is therefore of great interest for several scientific communities looking for a better tradeoff between time-to-solution and energy-to-solution. In this context, the performance assessment of processors with a high ratio of performance per watt is necessary to understand how to realize energy-efficient computing systems for scientific applications, using this class of processors. Computing On SOC Architecture (COSA is a three-year project (2015–2017 funded by the Scientific Commission V of the Italian Institute for Nuclear Physics (INFN, which aims to investigate the performance and the total cost of ownership offered by computing systems based on commodity low-power Systems on Chip (SoCs and high energy-efficient systems based on GP-GPUs. In this work, we present the results of the project analyzing the performance of several scientific applications on several GPU- and SoC-based systems. We also describe the methodology we have used to measure energy performance and the tools we have implemented to monitor the power drained by applications while running.

Optimisation of a Swedish district heating system with reduced heat demand due to energy efficiency measures in residential buildings

International Nuclear Information System (INIS)

Åberg, M.; Henning, D.

2011-01-01

The development towards more energy efficient buildings, as well as the expansion of district heating (DH) networks, is generally considered to reduce environmental impact. But the combined effect of these two progressions is more controversial. A reduced heat demand (HD) due to higher energy efficiency in buildings might hamper co-production of electricity and DH. In Sweden, co-produced electricity is normally considered to displace electricity from less efficient European condensing power plants. In this study, a potential HD reduction due to energy efficiency measures in the existing building stock in the Swedish city Linköping is calculated. The impact of HD reduction on heat and electricity production in the Linköping DH system is investigated by using the energy system optimisation model MODEST. Energy efficiency measures in buildings reduce seasonal HD variations. Model results show that HD reductions primarily decrease heat-only production. The electricity-to-heat output ratio for the system is increased for HD reductions up to 30%. Local and global CO 2 emissions are reduced. If co-produced electricity replaces electricity from coal-fired condensing power plants, a 20% HD reduction is optimal for decreasing global CO 2 emissions in the analysed DH system. - Highlights: ► A MODEST optimisation model of the Linköping district heating system is used. ► The impact of heat demand reduction on heat and electricity production is examined. ► Model results show that heat demand reductions decrease heat-only production. ► Local and global CO 2 emissions are reduced. ► The system electricity-to-heat output increases for reduced heat demand up to 30%.

A covert attention P300-based brain-computer interface: Geospell.

Science.gov (United States)

Aloise, Fabio; Aricò, Pietro; Schettini, Francesca; Riccio, Angela; Salinari, Serenella; Mattia, Donatella; Babiloni, Fabio; Cincotti, Febo

2012-01-01

The Farwell and Donchin P300 speller interface is one of the most widely used brain-computer interface (BCI) paradigms for writing text. Recent studies have shown that the recognition accuracy of the P300 speller decreases significantly when eye movement is impaired. This report introduces the GeoSpell interface (Geometric Speller), which implements a stimulation framework for a P300-based BCI that has been optimised for operation in covert visual attention. We compared the Geospell with the P300 speller interface under overt attention conditions with regard to effectiveness, efficiency and user satisfaction. Ten healthy subjects participated in the study. The performance of the GeoSpell interface in covert attention was comparable with that of the P300 speller in overt attention. As expected, the effectiveness of the spelling decreased with the new interface in covert attention. The NASA task load index (TLX) for workload assessment did not differ significantly between the two modalities. This study introduces and evaluates a gaze-independent, P300-based brain-computer interface, the efficacy and user satisfaction of which were comparable with those off the classical P300 speller. Despite a decrease in effectiveness due to the use of covert attention, the performance of the GeoSpell far exceeded the threshold of accuracy with regard to effective spelling.

Efficient computation of argumentation semantics

CERN Document Server

Liao, Beishui

2013-01-01

Efficient Computation of Argumentation Semantics addresses argumentation semantics and systems, introducing readers to cutting-edge decomposition methods that drive increasingly efficient logic computation in AI and intelligent systems. Such complex and distributed systems are increasingly used in the automation and transportation systems field, and particularly autonomous systems, as well as more generic intelligent computation research. The Series in Intelligent Systems publishes titles that cover state-of-the-art knowledge and the latest advances in research and development in intelligen

Computationally Efficient Power Allocation Algorithm in Multicarrier-Based Cognitive Radio Networks: OFDM and FBMC Systems

Directory of Open Access Journals (Sweden)

Shaat Musbah

2010-01-01

Full Text Available Cognitive Radio (CR systems have been proposed to increase the spectrum utilization by opportunistically access the unused spectrum. Multicarrier communication systems are promising candidates for CR systems. Due to its high spectral efficiency, filter bank multicarrier (FBMC can be considered as an alternative to conventional orthogonal frequency division multiplexing (OFDM for transmission over the CR networks. This paper addresses the problem of resource allocation in multicarrier-based CR networks. The objective is to maximize the downlink capacity of the network under both total power and interference introduced to the primary users (PUs constraints. The optimal solution has high computational complexity which makes it unsuitable for practical applications and hence a low complexity suboptimal solution is proposed. The proposed algorithm utilizes the spectrum holes in PUs bands as well as active PU bands. The performance of the proposed algorithm is investigated for OFDM and FBMC based CR systems. Simulation results illustrate that the proposed resource allocation algorithm with low computational complexity achieves near optimal performance and proves the efficiency of using FBMC in CR context.

Share-of-Surplus Product Line Optimisation with Price Levels

Directory of Open Access Journals (Sweden)

X. G. Luo

2014-01-01

Full Text Available Kraus and Yano (2003 established the share-of-surplus product line optimisation model and developed a heuristic procedure for this nonlinear mixed-integer optimisation model. In their model, price of a product is defined as a continuous decision variable. However, because product line optimisation is a planning process in the early stage of product development, pricing decisions usually are not very precise. In this research, a nonlinear integer programming share-of-surplus product line optimization model that allows the selection of candidate price levels for products is established. The model is further transformed into an equivalent linear mixed-integer optimisation model by applying linearisation techniques. Experimental results in different market scenarios show that the computation time of the transformed model is much less than that of the original model.

Performance Measurements in a High Throughput Computing Environment

CERN Document Server

AUTHOR|(CDS)2145966; Gribaudo, Marco

The IT infrastructures of companies and research centres are implementing new technologies to satisfy the increasing need of computing resources for big data analysis. In this context, resource profiling plays a crucial role in identifying areas where the improvement of the utilisation efficiency is needed. In order to deal with the profiling and optimisation of computing resources, two complementary approaches can be adopted: the measurement-based approach and the model-based approach. The measurement-based approach gathers and analyses performance metrics executing benchmark applications on computing resources. Instead, the model-based approach implies the design and implementation of a model as an abstraction of the real system, selecting only those aspects relevant to the study. This Thesis originates from a project carried out by the author within the CERN IT department. CERN is an international scientific laboratory that conducts fundamental researches in the domain of elementary particle physics. The p...

Spin-neurons: A possible path to energy-efficient neuromorphic computers

Energy Technology Data Exchange (ETDEWEB)

Sharad, Mrigank; Fan, Deliang; Roy, Kaushik [School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana 47907 (United States)

2013-12-21

Recent years have witnessed growing interest in the field of brain-inspired computing based on neural-network architectures. In order to translate the related algorithmic models into powerful, yet energy-efficient cognitive-computing hardware, computing-devices beyond CMOS may need to be explored. The suitability of such devices to this field of computing would strongly depend upon how closely their physical characteristics match with the essential computing primitives employed in such models. In this work, we discuss the rationale of applying emerging spin-torque devices for bio-inspired computing. Recent spin-torque experiments have shown the path to low-current, low-voltage, and high-speed magnetization switching in nano-scale magnetic devices. Such magneto-metallic, current-mode spin-torque switches can mimic the analog summing and “thresholding” operation of an artificial neuron with high energy-efficiency. Comparison with CMOS-based analog circuit-model of a neuron shows that “spin-neurons” (spin based circuit model of neurons) can achieve more than two orders of magnitude lower energy and beyond three orders of magnitude reduction in energy-delay product. The application of spin-neurons can therefore be an attractive option for neuromorphic computers of future.

Design of optimised backstepping controller for the synchronisation ...

Indian Academy of Sciences (India)

Ehsan Fouladi

2017-12-18

Dec 18, 2017 ... for the proposed optimised method compared to PSO optimised controller or any non-optimised backstepping controller. Keywords. Colpitts oscillator; backstepping controller; chaos synchronisation; shark smell algorithm; particle .... The velocity model is based on the gradient of the objective function, tilting ...

Convolutional networks for fast, energy-efficient neuromorphic computing.

Science.gov (United States)

Esser, Steven K; Merolla, Paul A; Arthur, John V; Cassidy, Andrew S; Appuswamy, Rathinakumar; Andreopoulos, Alexander; Berg, David J; McKinstry, Jeffrey L; Melano, Timothy; Barch, Davis R; di Nolfo, Carmelo; Datta, Pallab; Amir, Arnon; Taba, Brian; Flickner, Myron D; Modha, Dharmendra S

2016-10-11

Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state-of-the-art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware's underlying energy-efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively >6,000 frames/s per Watt), and (iii) can be specified and trained using backpropagation with the same ease-of-use as contemporary deep learning. This approach allows the algorithmic power of deep learning to be merged with the efficiency of neuromorphic processors, bringing the promise of embedded, intelligent, brain-inspired computing one step closer.

Friction stir welding: multi-response optimisation using Taguchi-based GRA

Directory of Open Access Journals (Sweden)

Jitender Kundu

2016-01-01

Full Text Available In present experimental work, friction stir welding of aluminium alloy 5083- H321 is performed for optimisation of process parameters for maximum tensile strength. Taguchi’s L9 orthogonal array has been used for three parameters – tool rotational speed (TRS, traverse speed (TS, and tool tilt angle (TTA with three levels. Multi-response optimisation has been carried out through Taguchi-based grey relational analysis. The grey relational grade has been calculated for all three responses – ultimate tensile strength, percentage elongation, and micro-hardness. Analysis of variance is the tool used for obtaining grey relational grade to find out the significant process parameters. TRS and TS are the two most significant parameters which influence most of the quality characteristics of friction stir welded joint. Validation of predicted values done through confirmation experiments at optimum setting shows a good agreement with experimental values.

The Goal Specificity Effect on Strategy Use and Instructional Efficiency during Computer-Based Scientific Discovery Learning

Science.gov (United States)

Kunsting, Josef; Wirth, Joachim; Paas, Fred

2011-01-01

Using a computer-based scientific discovery learning environment on buoyancy in fluids we investigated the "effects of goal specificity" (nonspecific goals vs. specific goals) for two goal types (problem solving goals vs. learning goals) on "strategy use" and "instructional efficiency". Our empirical findings close an important research gap,…

Simultaneous Topology, Shape, and Sizing Optimisation of Plane Trusses with Adaptive Ground Finite Elements Using MOEAs

Directory of Open Access Journals (Sweden)

Norapat Noilublao

2013-01-01

Full Text Available This paper proposes a novel integrated design strategy to accomplish simultaneous topology shape and sizing optimisation of a two-dimensional (2D truss. An optimisation problem is posed to find a structural topology, shape, and element sizes of the truss such that two objective functions, mass and compliance, are minimised. Design constraints include stress, buckling, and compliance. The procedure for an adaptive ground elements approach is proposed and its encoding/decoding process is detailed. Two sets of design variables defining truss layout, shape, and element sizes at the same time are applied. A number of multiobjective evolutionary algorithms (MOEAs are implemented to solve the design problem. Comparative performance based on a hypervolume indicator shows that multiobjective population-based incremental learning (PBIL is the best performer. Optimising three design variable types simultaneously is more efficient and effective.

Optimising parallel R correlation matrix calculations on gene expression data using MapReduce.

Science.gov (United States)

Wang, Shicai; Pandis, Ioannis; Johnson, David; Emam, Ibrahim; Guitton, Florian; Oehmichen, Axel; Guo, Yike

2014-11-05

High-throughput molecular profiling data has been used to improve clinical decision making by stratifying subjects based on their molecular profiles. Unsupervised clustering algorithms can be used for stratification purposes. However, the current speed of the clustering algorithms cannot meet the requirement of large-scale molecular data due to poor performance of the correlation matrix calculation. With high-throughput sequencing technologies promising to produce even larger datasets per subject, we expect the performance of the state-of-the-art statistical algorithms to be further impacted unless efforts towards optimisation are carried out. MapReduce is a widely used high performance parallel framework that can solve the problem. In this paper, we evaluate the current parallel modes for correlation calculation methods and introduce an efficient data distribution and parallel calculation algorithm based on MapReduce to optimise the correlation calculation. We studied the performance of our algorithm using two gene expression benchmarks. In the micro-benchmark, our implementation using MapReduce, based on the R package RHIPE, demonstrates a 3.26-5.83 fold increase compared to the default Snowfall and 1.56-1.64 fold increase compared to the basic RHIPE in the Euclidean, Pearson and Spearman correlations. Though vanilla R and the optimised Snowfall outperforms our optimised RHIPE in the micro-benchmark, they do not scale well with the macro-benchmark. In the macro-benchmark the optimised RHIPE performs 2.03-16.56 times faster than vanilla R. Benefiting from the 3.30-5.13 times faster data preparation, the optimised RHIPE performs 1.22-1.71 times faster than the optimised Snowfall. Both the optimised RHIPE and the optimised Snowfall successfully performs the Kendall correlation with TCGA dataset within 7 hours. Both of them conduct more than 30 times faster than the estimated vanilla R. The performance evaluation found that the new MapReduce algorithm and its

A methodological approach to the design of optimising control strategies for sewer systems

DEFF Research Database (Denmark)

Mollerup, Ane Loft; Mikkelsen, Peter Steen; Sin, Gürkan

2016-01-01

This study focuses on designing an optimisation based control for sewer system in a methodological way and linking itto a regulatory control. Optimisation based design is found to depend on proper choice of a model, formulation of objective function and tuning of optimisation parameters. Accordin......This study focuses on designing an optimisation based control for sewer system in a methodological way and linking itto a regulatory control. Optimisation based design is found to depend on proper choice of a model, formulation of objective function and tuning of optimisation parameters....... Accordingly, two novel optimisation configurations are developed, where the optimisation either acts on the actuators or acts on the regulatory control layer. These two optimisation designs are evaluated on a sub-catchment of the sewer system in Copenhagen, and found to perform better than the existing...

Topology optimisation of passive coolers for light-emitting diode lamps

DEFF Research Database (Denmark)

Alexandersen, Joe

2015-01-01

This work applies topology optimisation to the design of passive coolers for light-emitting diode (LED) lamps. The heat sinks are cooled by the natural convection currents arising from the temperature difference between the LED lamp and the surrounding air. A large scale parallel computational....... The optimisation results show interesting features that are currently being incorporated into industrial designs for enhanced passive cooling abilities....

The Energy-Efficient Quarry: Towards improved understanding and optimisation of energy use and minimisation of CO2 generation in the aggregates industry.

Science.gov (United States)

Hill, Ian; White, Toby; Owen, Sarah

2014-05-01

industry on a web-based platform. This tool guides quarry managers and operators through the complex, multi-layered, iterative, process of assessing the energy efficiency of their own quarry operation. They are able to evaluate the optimisation of the energy-efficiency of the overall quarry through examining both the individual stages of processing, and the interactions between them. The project is also developing on-line distance learning modules designed for Continuous Professional Development (CPD) activities for staff across the quarrying industry in the EU and beyond. The presentation will describe development of the model, and the format and scope of the resulting software tool and its user-support available to the quarrying industry.

A knowledge representation model for the optimisation of electricity generation mixes

International Nuclear Information System (INIS)

Chee Tahir, Aidid; Bañares-Alcántara, René

2012-01-01

Highlights: ► Prototype energy model which uses semantic representation (ontologies). ► Model accepts both quantitative and qualitative based energy policy goals. ► Uses logic inference to formulate equations for linear optimisation. ► Proposes electricity generation mix based on energy policy goals. -- Abstract: Energy models such as MARKAL, MESSAGE and DNE-21 are optimisation tools which aid in the formulation of energy policies. The strength of these models lie in their solid theoretical foundations built on rigorous mathematical equations designed to process numerical (quantitative) data related to economics and the environment. Nevertheless, a complete consideration of energy policy issues also requires the consideration of the political and social aspects of energy. These political and social issues are often associated with non-numerical (qualitative) information. To enable the evaluation of these aspects in a computer model, we hypothesise that a different approach to energy model optimisation design is required. A prototype energy model that is based on a semantic representation using ontologies and is integrated to engineering models implemented in Java has been developed. The model provides both quantitative and qualitative evaluation capabilities through the use of logical inference. The semantic representation of energy policy goals is used (i) to translate a set of energy policy goals into a set of logic queries which is then used to determine the preferred electricity generation mix and (ii) to assist in the formulation of a set of equations which is then solved in order to obtain a proposed electricity generation mix. Scenario case studies have been developed and tested on the prototype energy model to determine its capabilities. Knowledge queries were made on the semantic representation to determine an electricity generation mix which fulfilled a set of energy policy goals (e.g. CO 2 emissions reduction, water conservation, energy supply

Shape optimisation and performance analysis of flapping wings

KAUST Repository

Ghommem, Mehdi; Collier, Nathan; Niemi, Antti; Calo, Victor M.

2012-01-01

optimised shapes produce efficient flapping flights, the wake pattern and its vorticity strength are examined. This work described in this paper should facilitate better guidance for shape design of engineered flying systems.

A primer on the energy efficiency of computing

Energy Technology Data Exchange (ETDEWEB)

Koomey, Jonathan G. [Research Fellow, Steyer-Taylor Center for Energy Policy and Finance, Stanford University (United States)

2015-03-30

The efficiency of computing at peak output has increased rapidly since the dawn of the computer age. This paper summarizes some of the key factors affecting the efficiency of computing in all usage modes. While there is still great potential for improving the efficiency of computing devices, we will need to alter how we do computing in the next few decades because we are finally approaching the limits of current technologies.

Optimal design and operation of a photovoltaic-electrolyser system using particle swarm optimisation

Science.gov (United States)

Sayedin, Farid; Maroufmashat, Azadeh; Roshandel, Ramin; Khavas, Sourena Sattari

2016-07-01

In this study, hydrogen generation is maximised by optimising the size and the operating conditions of an electrolyser (EL) directly connected to a photovoltaic (PV) module at different irradiance. Due to the variations of maximum power points of the PV module during a year and the complexity of the system, a nonlinear approach is considered. A mathematical model has been developed to determine the performance of the PV/EL system. The optimisation methodology presented here is based on the particle swarm optimisation algorithm. By this method, for the given number of PV modules, the optimal sizeand operating condition of a PV/EL system areachieved. The approach can be applied for different sizes of PV systems, various ambient temperatures and different locations with various climaticconditions. The results show that for the given location and the PV system, the energy transfer efficiency of PV/EL system can reach up to 97.83%.

Convolutional networks for fast, energy-efficient neuromorphic computing

Science.gov (United States)

Esser, Steven K.; Merolla, Paul A.; Arthur, John V.; Cassidy, Andrew S.; Appuswamy, Rathinakumar; Andreopoulos, Alexander; Berg, David J.; McKinstry, Jeffrey L.; Melano, Timothy; Barch, Davis R.; di Nolfo, Carmelo; Datta, Pallab; Amir, Arnon; Taba, Brian; Flickner, Myron D.; Modha, Dharmendra S.

2016-01-01

Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state-of-the-art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware’s underlying energy-efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively >6,000 frames/s per Watt), and (iii) can be specified and trained using backpropagation with the same ease-of-use as contemporary deep learning. This approach allows the algorithmic power of deep learning to be merged with the efficiency of neuromorphic processors, bringing the promise of embedded, intelligent, brain-inspired computing one step closer. PMID:27651489

Multi-binding site model-based curve-fitting program for the computation of RIA data

International Nuclear Information System (INIS)

Malan, P.G.; Ekins, R.P.; Cox, M.G.; Long, E.M.R.

1977-01-01

In this paper, a comparison will be made of model-based and empirical curve-fitting procedures. The implementation of a multiple binding-site curve-fitting model which will successfully fit a wide range of assay data, and which can be run on a mini-computer is described. The latter sophisticated model also provides estimates of binding site concentrations and the values of the respective equilibrium constants present: the latter have been used for refining assay conditions using computer optimisation techniques. (orig./AJ) [de

Optimisation of monochrome images

International Nuclear Information System (INIS)

Potter, R.

1983-01-01

Gamma cameras with modern imaging systems usually digitize the signals to allow storage and processing of the image in a computer. Although such computer systems are widely used for the extraction of quantitative uptake estimates and the analysis of time variant data, the vast majority of nuclear medicine images is still interpreted on the basis of an observer's visual assessment of a photographic hardcopy image. The optimisation of hardcopy devices is therefore vital and factors such as resolution, uniformity, noise grey scales and display matrices are discussed. Once optimum display parameters have been determined, routine procedures for quality control need to be established; suitable procedures are discussed. (U.K.)

GATE: Improving the computational efficiency

International Nuclear Information System (INIS)

Staelens, S.; De Beenhouwer, J.; Kruecker, D.; Maigne, L.; Rannou, F.; Ferrer, L.; D'Asseler, Y.; Buvat, I.; Lemahieu, I.

2006-01-01

GATE is a software dedicated to Monte Carlo simulations in Single Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET). An important disadvantage of those simulations is the fundamental burden of computation time. This manuscript describes three different techniques in order to improve the efficiency of those simulations. Firstly, the implementation of variance reduction techniques (VRTs), more specifically the incorporation of geometrical importance sampling, is discussed. After this, the newly designed cluster version of the GATE software is described. The experiments have shown that GATE simulations scale very well on a cluster of homogeneous computers. Finally, an elaboration on the deployment of GATE on the Enabling Grids for E-Science in Europe (EGEE) grid will conclude the description of efficiency enhancement efforts. The three aforementioned methods improve the efficiency of GATE to a large extent and make realistic patient-specific overnight Monte Carlo simulations achievable

How to apply the Score-Function method to standard discrete event simulation tools in order to optimise a set of system parameters simultaneously: A Job-Shop example will be discussed

DEFF Research Database (Denmark)

Nielsen, Erland Hejn

2000-01-01

During the last 1-2 decades, simulation optimisation of discrete event dynamic systems (DEDS) has made considerable theoretical progress with respect to computational efficiency. The score-function (SF) method and the infinitesimal perturbation analysis (IPA) are two candidates belonging to this ...

The optimisation of wedge filters in radiotherapy of the prostate

International Nuclear Information System (INIS)

Oldham, Mark; Neal, Anthony J.; Webb, Steve

1995-01-01

A treatment plan optimisation algorithm has been applied to 12 patients with early prostate cancer in order to determine the optimum beam-weights and wedge angles for a standard conformal three-field treatment technique. The optimisation algorithm was based on fast-simulated-annealing using a cost function designed to achieve a uniform dose in the planning-target-volume (PTV) and to minimise the integral doses to the organs-at-risk. The algorithm has been applied to standard conformal three-field plans created by an experienced human planner, and run in three PLAN MODES: (1) where the wedge angles were fixed by the human planner and only the beam-weights were optimised; (2) where both the wedge angles and beam-weights were optimised; and (3) where both the wedge angles and beam-weights were optimised and a non-uniform dose was prescribed to the PTV. In the latter PLAN MODE, a uniform 100% dose was prescribed to all of the PTV except for that region that overlaps with the rectum where a lower (e.g., 90%) dose was prescribed. The resulting optimised plans have been compared with those of the human planner who found beam-weights by conventional forward planning techniques. Plans were compared on the basis of dose statistics, normal-tissue-complication-probability (NTCP) and tumour-control-probability (TCP). The results of the comparison showed that all three PLAN MODES produced plans with slightly higher TCP for the same rectal NTCP, than the human planner. The best results were observed for PLAN MODE 3, where an average increase in TCP of 0.73% (± 0.20, 95% confidence interval) was predicted by the biological models. This increase arises from a beneficial dose gradient which is produced across the tumour. Although the TCP gain is small it comes with no increase in treatment complexity, and could translate into increased cures given the large numbers of patients being referred. A study of the beam-weights and wedge angles chosen by the optimisation algorithm revealed

Image quality and dose management in digital radiography: A new paradigm for optimisation

International Nuclear Information System (INIS)

Busch, H. P.; Faulkner, K.

2005-01-01

The advent of digital imaging in radiology, combined with the explosive growth of technology, has dramatically improved imaging techniques. This has led to the expansion of diagnostic capabilities, both in terms of the number of procedures and their scope. Throughout the world, film/ screen radiography systems are being rapidly replaced with digital systems. Many progressive medical institutions have acquired, or are considering the purchase of computed radiography systems with storage phosphor plates or direct digital radiography systems with flat panel detectors. However, unknown to some users, these devices offer a new paradigm of opportunity and challenges. Images can be obtained at a lower dose owing to the higher detective quantum efficiency (DQE). These fundamental differences in comparison to conventional film/screens necessitate the development of new strategies for dose and quality optimisations. A set of referral criteria based upon three dose levels is proposed. (authors)

Sizing Combined Heat and Power Units and Domestic Building Energy Cost Optimisation

Directory of Open Access Journals (Sweden)

Dongmin Yu

2017-06-01

Full Text Available Many combined heat and power (CHP units have been installed in domestic buildings to increase energy efficiency and reduce energy costs. However, inappropriate sizing of a CHP may actually increase energy costs and reduce energy efficiency. Moreover, the high manufacturing cost of batteries makes batteries less affordable. Therefore, this paper will attempt to size the capacity of CHP and optimise daily energy costs for a domestic building with only CHP installed. In this paper, electricity and heat loads are firstly used as sizing criteria in finding the best capacities of different types of CHP with the help of the maximum rectangle (MR method. Subsequently, the genetic algorithm (GA will be used to optimise the daily energy costs of the different cases. Then, heat and electricity loads are jointly considered for sizing different types of CHP and for optimising the daily energy costs through the GA method. The optimisation results show that the GA sizing method gives a higher average daily energy cost saving, which is 13% reduction compared to a building without installing CHP. However, to achieve this, there will be about 3% energy efficiency reduction and 7% input power to rated power ratio reduction compared to using the MR method and heat demand in sizing CHP.

Optimisation of window settings for traditional and noise-optimised virtual monoenergetic imaging in dual-energy computed tomography pulmonary angiography

International Nuclear Information System (INIS)

D'Angelo, Tommaso; ''G. Martino'' University Hospital, Messina; Bucher, Andreas M.; Lenga, Lukas; Arendt, Christophe T.; Peterke, Julia L.; Martin, Simon S.; Leithner, Doris; Vogl, Thomas J.; Wichmann, Julian L.; Caruso, Damiano; University Hospital, Latina; Mazziotti, Silvio; Blandino, Alfredo; Ascenti, Giorgio; University Hospital, Messina; Othman, Ahmed E.

2018-01-01

To define optimal window settings for displaying virtual monoenergetic images (VMI) of dual-energy CT pulmonary angiography (DE-CTPA). Forty-five patients who underwent clinically-indicated third-generation dual-source DE-CTPA were retrospectively evaluated. Standard linearly-blended (M 0 .6), 70-keV traditional VMI (M70), and 40-keV noise-optimised VMI (M40+) reconstructions were analysed. For M70 and M40+ datasets, the subjectively best window setting (width and level, B-W/L) was independently determined by two observers and subsequently related with pulmonary artery attenuation to calculate separate optimised values (O-W/L) using linear regression. Subjective evaluation of image quality (IQ) between W/L settings were assessed by two additional readers. Repeated measures of variance were performed to compare W/L settings and IQ indices between M 0 .6, M70, and M40+. B-W/L and O-W/L for M70 were 460/140 and 450/140, and were 1100/380 and 1070/380 for M40+, respectively, differing from standard DE-CTPA W/L settings (450/100). Highest subjective scores were observed for M40+ regarding vascular contrast, embolism demarcation, and overall IQ (all p<0.001). Application of O-W/L settings is beneficial to optimise subjective IQ of VMI reconstructions of DE-CTPA. A width slightly less than two times the pulmonary trunk attenuation and a level approximately of overall pulmonary vessel attenuation are recommended. (orig.)

A future for computational fluid dynamics at CERN

CERN Document Server

Battistin, M

2005-01-01

Computational Fluid Dynamics (CFD) is an analysis of fluid flow, heat transfer and associated phenomena in physical systems using computers. CFD has been used at CERN since 1993 by the TS-CV group, to solve thermo-fluid related problems, particularly during the development, design and construction phases of the LHC experiments. Computer models based on CFD techniques can be employed to reduce the effort required for prototype testing, saving not only time and money but offering possibilities of additional investigations and design optimisation. The development of a more efficient support team at CERN depends on to two important factors: available computing power and experienced engineers. Available computer power IS the limiting resource of CFD. Only the recent increase of computer power had allowed important high tech and industrial applications. Computer Grid is already now (OpenLab at CERN) and will be more so in the future natural environment for CFD science. At CERN, CFD activities have been developed by...

Computer Architecture for Energy Efficient SFQ

Science.gov (United States)

2014-08-27

IBM Corporation (T.J. Watson Research Laboratory) 1101 Kitchawan Road Yorktown Heights, NY 10598 -0000 2 ABSTRACT Number of Papers published in peer...accomplished during this ARO-sponsored project at IBM Research to identify and model an energy efficient SFQ-based computer architecture. The... IBM Windsor Blue (WB), illustrated schematically in Figure 2. The basic building block of WB is a "tile" comprised of a 64-bit arithmetic logic unit

CFD optimisation of a stadium roof geometry: a qualitative study to improve the wind microenvironment

Directory of Open Access Journals (Sweden)

Sofotasiou Polytimi

2017-01-01

Full Text Available The complexity of the built environment requires the adoption of coupled techniques to predict the flow phenomena and provide optimum design solutions. In this study, coupled computational fluid dynamics (CFD and response surface methodology (RSM optimisation tools are employed to investigate the parameters that determine the wind comfort in a two-dimensional stadium model, by optimising the roof geometry. The roof height, width and length are evaluated against the flow homogeneity at the spectator terraces and the playing field area, the roof flow rate and the average interior pressure. Based on non-parametric regression analysis, both symmetric and asymmetric configurations are considered for optimisation. The optimum design solutions revealed that it is achievable to provide an improved wind environment in both playing field area and spectator terraces, giving a further insight on the interrelations of the parameters involved. Considering the limitations of conducting a two-dimensional study, the obtained results may beneficially be used as a basis for the optimisation of a complex three-dimensional stadium structure and thus become an important design guide for stadium structures.

Exergy analysis and optimisation of a marine molten carbonate fuel cell system in simple and combined cycle configuration

International Nuclear Information System (INIS)

Dimopoulos, George G.; Stefanatos, Iason C.; Kakalis, Nikolaos M.P.

2016-01-01

Highlights: • Process modelling and optimisation of an integrated marine MCFC system. • Component-level and spatially distributed exergy analysis and balances. • Optimal simple cycle MCFC system with 45.5% overall exergy efficiency. • Optimal combined cycle MCFC system with 60% overall exergy efficiency. • Combined cycle MCFC system yields 30% CO_2 relative emissions reduction. - Abstract: In this paper we present the exergy analysis and design optimisation of an integrated molten carbonate fuel cell (MCFC) system for marine applications, considering waste heat recovery options for additional power production. High temperature fuel cells are attractive solutions for marine energy systems, as they can significantly reduce gaseous emissions, increase efficiency and facilitate the introduction of more environmentally-friendly fuels, like LNG and biofuels. We consider an already installed MCFC system onboard a sea-going vessel, which has many tightly integrated sub-systems and components: fuel delivery and pre-reforming, internal reforming sections, electrochemical conversion, catalytic burner, air supply and high temperature exhaust gas. The high temperature exhaust gasses offer significant potential for heat recovery that can be directed into both covering the system’s auxiliary heat requirements and power production. Therefore, an integrated systems approach is employed to accurately identify the true sources of losses in the various components and to optimise the overall system with respect to its energy efficiency, taking into account the various trade-offs and subject to several constraints. Here, we present a four-step approach: a. dynamic process models development of simple and combined-cycle MCFC system; b. MCFC components and system models calibration via onboard MCFC measurements; c. exergy analysis, and d. optimisation of the simple and combined-cycle systems with respect to their exergetic performance. Our methodology is based on the

Statistical meandering wake model and its application to yaw-angle optimisation of wind farms

DEFF Research Database (Denmark)

Thøgersen, Emil; Tranberg, Bo; Herp, Jürgen

2017-01-01

deterministic models to a statistical meandering wake model (SMWM), where a random directional deflection is assigned to a narrow wake in such a way that on average it resembles a broad Jensen wake. In a second step, the model is further generalised to wind-farm level, where the deflections of the multiple...... wakes are treated as independently and identically distributed random variables. When carefully calibrated to the Nysted wind farm, the ensemble average of the statistical model produces the same wind-direction dependence of the power efficiency as obtained from the standard Jensen model. Upon using...... the JWM to perform a yaw-angle optimisation of wind-farm power output, we find an optimisation gain of 6.7% for the Nysted wind farm when compared to zero yaw angles and averaged over all wind directions. When applying the obtained JWM-based optimised yaw angles to the SMWM, the ensemble-averaged gain...

Dose optimisation in single plane interstitial brachytherapy

DEFF Research Database (Denmark)

Tanderup, Kari; Hellebust, Taran Paulsen; Honoré, Henriette Benedicte

2006-01-01

patients,       treated for recurrent rectal and cervical cancer, flexible catheters were       sutured intra-operatively to the tumour bed in areas with compromised       surgical margin. Both non-optimised, geometrically and graphically       optimised CT -based dose plans were made. The overdose index...... on the       regularity of the implant, such that the benefit of optimisation was       larger for irregular implants. OI and HI correlated strongly with target       volume limiting the usability of these parameters for comparison of dose       plans between patients. CONCLUSIONS: Dwell time optimisation significantly......BACKGROUND AND PURPOSE: Brachytherapy dose distributions can be optimised       by modulation of source dwell times. In this study dose optimisation in       single planar interstitial implants was evaluated in order to quantify the       potential benefit in patients. MATERIAL AND METHODS: In 14...

Power supply of Eurotunnel. Optimisation based on traffic and simulation studies

Energy Technology Data Exchange (ETDEWEB)

Marie, Stephane [SNCF, Direction de l' Ingenierie, Saint-Denis (France). Dept. des Installations Fixes de Traction Electrique; Dupont, Jean-Pierre; Findinier, Bertrand; Maquaire, Christian [Eurotunnel, Coquelles (France)

2010-12-15

In order to reduce electrical power costs and also to cope with the significant traffic increase, a new study was carried on feeding the tunnel section from the French power station, thus improving and reinforcing the existing network. Based on a design study established by SNCF engineering department, EUROTUNNEL chose a new electrical scheme to cope with the traffic increase and optimise investments. (orig.)

Optimisation of preparation conditions and properties of phytosterol liposome-encapsulating nattokinase.

Science.gov (United States)

Dong, Xu-Yan; Kong, Fan-Pi; Yuan, Gang-You; Wei, Fang; Jiang, Mu-Lan; Li, Guang-Ming; Wang, Zhan; Zhao, Yuan-Di; Chen, Hong

2012-01-01

Phytosterol liposomes were prepared using the thin film method and used to encapsulate nattokinase (NK). In order to obtain a high encapsulation efficiency within the liposome, an orthogonal experiment (L9 (3)(4)) was applied to optimise the preparation conditions. The molar ratio of lecithin to phytosterols, NK activity and mass ratio of mannite to lecithin were the main factors that influenced the encapsulation efficiency of the liposomes. Based on the results of a single-factor test, these three factors were chosen for this study. We determined the optimum extraction conditions to be as follows: a molar ratio of lecithin to phytosterol of 2 : 1, NK activity of 2500 U mL⁻¹ and a mass ratio of mannite to lecithin of 3 : 1. Under these optimised conditions, an encapsulation efficiency of 65.25% was achieved, which agreed closely with the predicted result. Moreover, the zeta potential, size distribution and microstructure of the liposomes prepared were measured, and we found that the zeta potential was -51 ± 3 mV and the mean diameter was 194.1 nm. From the results of the scanning electron microscopy, we observed that the phytosterol liposomes were round and regular in shape and showed no aggregation.

Computationally efficient dynamic modeling of robot manipulators with multiple flexible-links using acceleration-based discrete time transfer matrix method

DEFF Research Database (Denmark)

Zhang, Xuping; Sørensen, Rasmus; RahbekIversen, Mathias

2018-01-01

This paper presents a novel and computationally efficient modeling method for the dynamics of flexible-link robot manipulators. In this method, a robot manipulator is decomposed into components/elements. The component/element dynamics is established using Newton–Euler equations, and then is linea......This paper presents a novel and computationally efficient modeling method for the dynamics of flexible-link robot manipulators. In this method, a robot manipulator is decomposed into components/elements. The component/element dynamics is established using Newton–Euler equations......, and then is linearized based on the acceleration-based state vector. The transfer matrices for each type of components/elements are developed, and used to establish the system equations of a flexible robot manipulator by concatenating the state vector from the base to the end-effector. With this strategy, the size...... manipulators, and only involves calculating and transferring component/element dynamic equations that have small size. The numerical simulations and experimental testing of flexible-link manipulators are conducted to validate the proposed methodologies....

Alternatives for optimisation of rumen fermentation in ruminants

Directory of Open Access Journals (Sweden)

T. Slavov

2017-06-01

Full Text Available Abstract. The proper knowledge on the variety of events occurring in the rumen makes possible their optimisation with respect to the complete feed conversion and increasing the productive performance of ruminants. The inclusion of various dietary additives (supplements, biologically active substances, nutritional antibiotics, probiotics, enzymatic preparations, plant extracts etc. has an effect on the intensity and specific pathway of fermentation, and thus, on the general digestion and systemic metabolism. The optimisation of rumen digestion is a method with substantial potential for improving the efficiency of ruminant husbandry, increasing of quality of their produce and health maintenance.

Structured Parallel Programming Patterns for Efficient Computation

CERN Document Server

McCool, Michael; Robison, Arch

2012-01-01

Programming is now parallel programming. Much as structured programming revolutionized traditional serial programming decades ago, a new kind of structured programming, based on patterns, is relevant to parallel programming today. Parallel computing experts and industry insiders Michael McCool, Arch Robison, and James Reinders describe how to design and implement maintainable and efficient parallel algorithms using a pattern-based approach. They present both theory and practice, and give detailed concrete examples using multiple programming models. Examples are primarily given using two of th

Energy-Efficient FPGA-Based Parallel Quasi-Stochastic Computing

Directory of Open Access Journals (Sweden)

Ramu Seva

2017-11-01

Full Text Available The high performance of FPGA (Field Programmable Gate Array in image processing applications is justified by its flexible reconfigurability, its inherent parallel nature and the availability of a large amount of internal memories. Lately, the Stochastic Computing (SC paradigm has been found to be significantly advantageous in certain application domains including image processing because of its lower hardware complexity and power consumption. However, its viability is deemed to be limited due to its serial bitstream processing and excessive run-time requirement for convergence. To address these issues, a novel approach is proposed in this work where an energy-efficient implementation of SC is accomplished by introducing fast-converging Quasi-Stochastic Number Generators (QSNGs and parallel stochastic bitstream processing, which are well suited to leverage FPGA’s reconfigurability and abundant internal memory resources. The proposed approach has been tested on the Virtex-4 FPGA, and results have been compared with the serial and parallel implementations of conventional stochastic computation using the well-known SC edge detection and multiplication circuits. Results prove that by using this approach, execution time, as well as the power consumption are decreased by a factor of 3.5 and 4.5 for the edge detection circuit and multiplication circuit, respectively.

The Inertia Weight Updating Strategies in Particle Swarm Optimisation Based on the Beta Distribution

Directory of Open Access Journals (Sweden)

Petr Maca

2015-01-01

Full Text Available The presented paper deals with the comparison of selected random updating strategies of inertia weight in particle swarm optimisation. Six versions of particle swarm optimization were analysed on 28 benchmark functions, prepared for the Special Session on Real-Parameter Single Objective Optimisation at CEC2013. The random components of tested inertia weight were generated from Beta distribution with different values of shape parameters. The best analysed PSO version is the multiswarm PSO, which combines two strategies of updating the inertia weight. The first is driven by the temporally varying shape parameters, while the second is based on random control of shape parameters of Beta distribution.

Efficient O(N) recursive computation of the operational space inertial matrix

International Nuclear Information System (INIS)

Lilly, K.W.; Orin, D.E.

1993-01-01

The operational space inertia matrix Λ reflects the dynamic properties of a robot manipulator to its tip. In the control domain, it may be used to decouple force and/or motion control about the manipulator workspace axes. The matrix Λ also plays an important role in the development of efficient algorithms for the dynamic simulation of closed-chain robotic mechanisms, including simple closed-chain mechanisms such as multiple manipulator systems and walking machines. The traditional approach used to compute Λ has a computational complexity of O(N 3 ) for an N degree-of-freedom manipulator. This paper presents the development of a recursive algorithm for computing the operational space inertia matrix (OSIM) that reduces the computational complexity to O(N). This algorithm, the inertia propagation method, is based on a single recursion that begins at the base of the manipulator and progresses out to the last link. Also applicable to redundant systems and mechanisms with multiple-degree-of-freedom joints, the inertia propagation method is the most efficient method known for computing Λ for N ≥ 6. The numerical accuracy of the algorithm is discussed for a PUMA 560 robot with a fixed base

ExRET-Opt: An automated exergy/exergoeconomic simulation framework for building energy retrofit analysis and design optimisation

International Nuclear Information System (INIS)

García Kerdan, Iván; Raslan, Rokia; Ruyssevelt, Paul; Morillón Gálvez, David

2017-01-01

Highlights: • Development of a building retrofit-oriented exergoeconomic-based optimisation tool. • A new exergoeconomic cost-benefit indicator is developed for design comparison. • Thermodynamic and thermal comfort variables used as constraints and/or objectives. • Irreversibilities and exergetic cost for end-use processes are substantially reduced. • Robust methodology that should be pursued in everyday building retrofit practice. - Abstract: Energy simulation tools have a major role in the assessment of building energy retrofit (BER) measures. Exergoeconomic analysis and optimisation is a common practice in sectors such as the power generation and chemical processes, aiding engineers to obtain more energy-efficient and cost-effective energy systems designs. ExRET-Opt, a retrofit-oriented modular-based dynamic simulation framework has been developed by embedding a comprehensive exergy/exergoeconomic calculation method into a typical open-source building energy simulation tool (EnergyPlus). The aim of this paper is to show the decomposition of ExRET-Opt by presenting modules, submodules and subroutines used for the framework’s development as well as verify the outputs with existing research data. In addition, the possibility to perform multi-objective optimisation analysis based on genetic-algorithms combined with multi-criteria decision making methods was included within the simulation framework. This addition could potentiate BER design teams to perform quick exergy/exergoeconomic optimisation, in order to find opportunities for thermodynamic improvements along the building’s active and passive energy systems. The enhanced simulation framework is tested using a primary school building as a case study. Results demonstrate that the proposed simulation framework provide users with thermodynamic efficient and cost-effective designs, even under tight thermodynamic and economic constraints, suggesting its use in everyday BER practice.

Optimising for sun and light - the environmental performance of bio-climatic high-rise offices by Malaysian architect Kenneth Yeang

Energy Technology Data Exchange (ETDEWEB)

Ip, K.; Puteri Shireen Jahnkassim [University of Brighton (United Kingdom). School of the Environment

2000-07-01

Bioclimatic highrises represent an architectural response to the problem of regionalism in highrises and are based mainly on climate as a form determinant. They integrate sky courts, the use of vertical landscaping and vegetation, sun shading and use of natural ventilation in transitional areas such as the lift and ground floor lobbies. Sensitivity studies on bioclimatic highrises in tropical climate have shown that the use of daylight to save electric light and the optimum design of the building envelope can achieve significant energy savings by maintaining the balance between thermal and lighting requirements. In this study the overall envelope of two of Ken Yeang's highrise design, Menara Mesiniaga and Menara UMNO, are optimised with regards to the balance between the opposing impacts - daylight and solar gain. Apart from the external design features, the applications of photovoltaic systems to enhance the energy efficiency of these buildings are also investigated. The optimisation is carried out through the use of the FACET computer program that incorporates the use of dynamic thermal simulation program APACHE and lighting simulation RADIANCE. The paper concludes with the energy saving potential of bioclimatic design and limitations of the current study. (author)

Expect systems and optimisation in process control

Energy Technology Data Exchange (ETDEWEB)

Mamdani, A.; Efstathiou, J. (eds.)

1986-01-01

This report brings together recent developments both in expert systems and in optimisation, and deals with current applications in industry. Part One is concerned with Artificial Intellegence in planning and scheduling and with rule-based control implementation. The tasks of control maintenance, rescheduling and planning are each discussed in relation to new theoretical developments, techniques available, and sample applications. Part Two covers model based control techniques in which the control decisions are used in a computer model of the process. Fault diagnosis, maintenance and trouble-shooting are just some of the activities covered. Part Three contains case studies of projects currently in progress, giving details of the software available and the likely future trends. One of these, on qualitative plant modelling as a basis for knowledge-based operator aids in nuclear power stations is indexed separately.

Expert systems and optimisation in process control

International Nuclear Information System (INIS)

Mamdani, A.; Efstathiou, J.

1986-01-01

This report brings together recent developments both in expert systems and in optimisation, and deals with current applications in industry. Part One is concerned with Artificial Intellegence in planning and scheduling and with rule-based control implementation. The tasks of control maintenance, rescheduling and planning are each discussed in relation to new theoretical developments, techniques available, and sample applications. Part Two covers model based control techniques in which the control decisions are used in a computer model of the process. Fault diagnosis, maintenance and trouble-shooting are just some of the activities covered. Part Three contains case studies of projects currently in progress, giving details of the software available and the likely future trends. One of these, on qualitative plant modelling as a basis for knowledge-based operator aids in nuclear power stations is indexed separately. (author)

Automation of route identification and optimisation based on data-mining and chemical intuition.

Science.gov (United States)

Lapkin, A A; Heer, P K; Jacob, P-M; Hutchby, M; Cunningham, W; Bull, S D; Davidson, M G

2017-09-21

Data-mining of Reaxys and network analysis of the combined literature and in-house reactions set were used to generate multiple possible reaction routes to convert a bio-waste feedstock, limonene, into a pharmaceutical API, paracetamol. The network analysis of data provides a rich knowledge-base for generation of the initial reaction screening and development programme. Based on the literature and the in-house data, an overall flowsheet for the conversion of limonene to paracetamol was proposed. Each individual reaction-separation step in the sequence was simulated as a combination of the continuous flow and batch steps. The linear model generation methodology allowed us to identify the reaction steps requiring further chemical optimisation. The generated model can be used for global optimisation and generation of environmental and other performance indicators, such as cost indicators. However, the identified further challenge is to automate model generation to evolve optimal multi-step chemical routes and optimal process configurations.

A Computationally Efficient Method for Polyphonic Pitch Estimation

Directory of Open Access Journals (Sweden)

Ruohua Zhou

2009-01-01

Full Text Available This paper presents a computationally efficient method for polyphonic pitch estimation. The method employs the Fast Resonator Time-Frequency Image (RTFI as the basic time-frequency analysis tool. The approach is composed of two main stages. First, a preliminary pitch estimation is obtained by means of a simple peak-picking procedure in the pitch energy spectrum. Such spectrum is calculated from the original RTFI energy spectrum according to harmonic grouping principles. Then the incorrect estimations are removed according to spectral irregularity and knowledge of the harmonic structures of the music notes played on commonly used music instruments. The new approach is compared with a variety of other frame-based polyphonic pitch estimation methods, and results demonstrate the high performance and computational efficiency of the approach.

On efficiently computing multigroup multi-layer neutron reflection and transmission conditions

International Nuclear Information System (INIS)

Abreu, Marcos P. de

2007-01-01

In this article, we present an algorithm for efficient computation of multigroup discrete ordinates neutron reflection and transmission conditions, which replace a multi-layered boundary region in neutron multiplication eigenvalue computations with no spatial truncation error. In contrast to the independent layer-by-layer algorithm considered thus far in our computations, the algorithm here is based on an inductive approach developed by the present author for deriving neutron reflection and transmission conditions for a nonactive boundary region with an arbitrary number of arbitrarily thick layers. With this new algorithm, we were able to increase significantly the computational efficiency of our spectral diamond-spectral Green's function method for solving multigroup neutron multiplication eigenvalue problems with multi-layered boundary regions. We provide comparative results for a two-group reactor core model to illustrate the increased efficiency of our spectral method, and we conclude this article with a number of general remarks. (author)

A computationally efficient fuzzy control s

Directory of Open Access Journals (Sweden)

Abdel Badie Sharkawy

2013-12-01

Full Text Available This paper develops a decentralized fuzzy control scheme for MIMO nonlinear second order systems with application to robot manipulators via a combination of genetic algorithms (GAs and fuzzy systems. The controller for each degree of freedom (DOF consists of a feedforward fuzzy torque computing system and a feedback fuzzy PD system. The feedforward fuzzy system is trained and optimized off-line using GAs, whereas not only the parameters but also the structure of the fuzzy system is optimized. The feedback fuzzy PD system, on the other hand, is used to keep the closed-loop stable. The rule base consists of only four rules per each DOF. Furthermore, the fuzzy feedback system is decentralized and simplified leading to a computationally efficient control scheme. The proposed control scheme has the following advantages: (1 it needs no exact dynamics of the system and the computation is time-saving because of the simple structure of the fuzzy systems and (2 the controller is robust against various parameters and payload uncertainties. The computational complexity of the proposed control scheme has been analyzed and compared with previous works. Computer simulations show that this controller is effective in achieving the control goals.

Classification of osteoporosis by artificial neural network based on monarch butterfly optimisation algorithm.

Science.gov (United States)

Devikanniga, D; Joshua Samuel Raj, R

2018-04-01

Osteoporosis is a life threatening disease which commonly affects women mostly after their menopause. It primarily causes mild bone fractures, which on advanced stage leads to the death of an individual. The diagnosis of osteoporosis is done based on bone mineral density (BMD) values obtained through various clinical methods experimented from various skeletal regions. The main objective of the authors' work is to develop a hybrid classifier model that discriminates the osteoporotic patient from healthy person, based on BMD values. In this Letter, the authors propose the monarch butterfly optimisation-based artificial neural network classifier which helps in earlier diagnosis and prevention of osteoporosis. The experiments were conducted using 10-fold cross-validation method for two datasets lumbar spine and femoral neck. The results were compared with other similar hybrid approaches. The proposed method resulted with the accuracy, specificity and sensitivity of 97.9% ± 0.14, 98.33% ± 0.03 and 95.24% ± 0.08, respectively, for lumbar spine dataset and 99.3% ± 0.16%, 99.2% ± 0.13 and 100, respectively, for femoral neck dataset. Further, its performance is compared using receiver operating characteristics analysis and Wilcoxon signed-rank test. The results proved that the proposed classifier is efficient and it outperformed the other approaches in all the cases.

Issues with performance measures for dynamic multi-objective optimisation

CSIR Research Space (South Africa)

Helbig, M

2013-06-01

Full Text Available Symposium on Computational Intelligence in Dynamic and Uncertain Environments (CIDUE), Mexico, 20-23 June 2013 Issues with Performance Measures for Dynamic Multi-objective Optimisation Mard´e Helbig CSIR: Meraka Institute Brummeria, South Africa...

The optimisation of the laser-induced forward transfer process for fabrication of polyfluorene-based organic light-emitting diode pixels

Science.gov (United States)

Shaw-Stewart, James; Mattle, Thomas; Lippert, Thomas; Nagel, Matthias; Nüesch, Frank; Wokaun, Alexander

2013-08-01

Laser-induced forward transfer (LIFT) has already been used to fabricate various types of organic light-emitting diodes (OLEDs), and the process itself has been optimised and refined considerably since OLED pixels were first demonstrated. In particular, a dynamic release layer (DRL) of triazene polymer has been used, the environmental pressure has been reduced down to a medium vacuum, and the donor receiver gap has been controlled with the use of spacers. Insight into the LIFT process's effect upon OLED pixel performance is presented here, obtained through optimisation of three-colour polyfluorene-based OLEDs. A marked dependence of the pixel morphology quality on the cathode metal is observed, and the laser transfer fluence dependence is also analysed. The pixel device performances are compared to conventionally fabricated devices, and cathode effects have been looked at in detail. The silver cathode pixels show more heterogeneous pixel morphologies, and a correspondingly poorer efficiency characteristics. The aluminium cathode pixels have greater green electroluminescent emission than both the silver cathode pixels and the conventionally fabricated aluminium devices, and the green emission has a fluence dependence for silver cathode pixels.

The optimisation of the laser-induced forward transfer process for fabrication of polyfluorene-based organic light-emitting diode pixels

Energy Technology Data Exchange (ETDEWEB)

Shaw-Stewart, James, E-mail: james.shaw-stewart@ed.ac.uk [Materials Group, General Energies Department, Paul Scherrer Institut, CH-5232 Villigen-PSI (Switzerland); Laboratory for Functional Polymers, Empa Swiss Federal Laboratories for Materials Science and Technology, Überlandstrasse 129, CH-8600 Dübendorf (Switzerland); Mattle, Thomas [Materials Group, General Energies Department, Paul Scherrer Institut, CH-5232 Villigen-PSI (Switzerland); Lippert, Thomas, E-mail: thomas.lippert@psi.ch [Materials Group, General Energies Department, Paul Scherrer Institut, CH-5232 Villigen-PSI (Switzerland); Nagel, Matthias [Laboratory for Functional Polymers, Empa Swiss Federal Laboratories for Materials Science and Technology, Überlandstrasse 129, CH-8600 Dübendorf (Switzerland); Nüesch, Frank, E-mail: frank.nueesch@empa.ch [Laboratory for Functional Polymers, Empa Swiss Federal Laboratories for Materials Science and Technology, Überlandstrasse 129, CH-8600 Dübendorf (Switzerland); Section de science et génie des matériaux, EPFL, CH-1015 Lausanne (Switzerland); Wokaun, Alexander [Materials Group, General Energies Department, Paul Scherrer Institut, CH-5232 Villigen-PSI (Switzerland)

2013-08-01

Laser-induced forward transfer (LIFT) has already been used to fabricate various types of organic light-emitting diodes (OLEDs), and the process itself has been optimised and refined considerably since OLED pixels were first demonstrated. In particular, a dynamic release layer (DRL) of triazene polymer has been used, the environmental pressure has been reduced down to a medium vacuum, and the donor receiver gap has been controlled with the use of spacers. Insight into the LIFT process's effect upon OLED pixel performance is presented here, obtained through optimisation of three-colour polyfluorene-based OLEDs. A marked dependence of the pixel morphology quality on the cathode metal is observed, and the laser transfer fluence dependence is also analysed. The pixel device performances are compared to conventionally fabricated devices, and cathode effects have been looked at in detail. The silver cathode pixels show more heterogeneous pixel morphologies, and a correspondingly poorer efficiency characteristics. The aluminium cathode pixels have greater green electroluminescent emission than both the silver cathode pixels and the conventionally fabricated aluminium devices, and the green emission has a fluence dependence for silver cathode pixels.

Efficient Resource Management in Cloud Computing

OpenAIRE

Rushikesh Shingade; Amit Patil; Shivam Suryawanshi; M. Venkatesan

2015-01-01

Cloud computing, one of the widely used technology to provide cloud services for users who are charged for receiving services. In the aspect of a maximum number of resources, evaluating the performance of Cloud resource management policies are difficult to optimize efficiently. There are different simulation toolkits available for simulation and modelling the Cloud computing environment like GridSim CloudAnalyst, CloudSim, GreenCloud, CloudAuction etc. In proposed Efficient Resource Manage...

Parallel unstructured mesh optimisation for 3D radiation transport and fluids modelling

International Nuclear Information System (INIS)

Gorman, G.J.; Pain, Ch. C.; Oliveira, C.R.E. de; Umpleby, A.P.; Goddard, A.J.H.

2003-01-01

In this paper we describe the theory and application of a parallel mesh optimisation procedure to obtain self-adapting finite element solutions on unstructured tetrahedral grids. The optimisation procedure adapts the tetrahedral mesh to the solution of a radiation transport or fluid flow problem without sacrificing the integrity of the boundary (geometry), or internal boundaries (regions) of the domain. The objective is to obtain a mesh which has both a uniform interpolation error in any direction and the element shapes are of good quality. This is accomplished with use of a non-Euclidean (anisotropic) metric which is related to the Hessian of the solution field. Appropriate scaling of the metric enables the resolution of multi-scale phenomena as encountered in transient incompressible fluids and multigroup transport calculations. The resulting metric is used to calculate element size and shape quality. The mesh optimisation method is based on a series of mesh connectivity and node position searches of the landscape defining mesh quality which is gauged by a functional. The mesh modification thus fits the solution field(s) in an optimal manner. The parallel mesh optimisation/adaptivity procedure presented in this paper is of general applicability. We illustrate this by applying it to a transient CFD (computational fluid dynamics) problem. Incompressible flow past a cylinder at moderate Reynolds numbers is modelled to demonstrate that the mesh can follow transient flow features. (authors)

Research on Duct Flow Field Optimisation of a Robot Vacuum Cleaner

Directory of Open Access Journals (Sweden)

Xiao-bo Lai

2011-11-01

Full Text Available The duct of a robot vacuum cleaner is the length of the flow channel between the inlet of the rolling brush blower and the outlet of the vacuum blower. To cope with the pressure drop problem of the duct flow field in a robot vacuum cleaner, a method based on Pressure Implicit with Splitting of Operators (PRISO algorithm is introduced and the optimisation design of the duct flow field is implemented. Firstly, the duct structure in a robot vacuum cleaner is taken as a research object, with the computational fluid dynamics (CFD theories adopted; a three-dimensional fluid model of the duct is established by means of the FLUENT solver of the CFD software. Secondly, with the k-∊ turbulence model of three-dimensional incompressible fluid considered and the PRISO pressure modification algorithm employed, the flow field numerical simulations inside the duct of the robot vacuum cleaner are carried out. Then, the velocity vector plots on the arbitrary plane of the duct flow field are obtained. Finally, an investigation of the dynamic characteristics of the duct flow field is done and defects of the original duct flow field are analysed, the optimisation of the original flow field has then been conducted. Experimental results show that the duct flow field after optimisation can effectively reduce pressure drop, the feasibility as well as the correctness of the theoretical modelling and optimisation approaches are validated.

Research on Duct Flow Field Optimisation of a Robot Vacuum Cleaner

Directory of Open Access Journals (Sweden)

Xiao-bo Lai

2011-11-01

Full Text Available The duct of a robot vacuum cleaner is the length of the flow channel between the inlet of the rolling brush blower and the outlet of the vacuum blower. To cope with the pressure drop problem of the duct flow field in a robot vacuum cleaner, a method based on Pressure Implicit with Splitting of Operators (PRISO algorithm is introduced and the optimisation design of the duct flow field is implemented. Firstly, the duct structure in a robot vacuum cleaner is taken as a research object, with the computational fluid dynamics (CFD theories adopted; a three‐dimensional fluid model of the duct is established by means of the FLUENT solver of the CFD software. Secondly, with the k‐ε turbulence model of three‐ dimensional incompressible fluid considered and the PRISO pressure modification algorithm employed, the flow field numerical simulations inside the duct of the robot vacuum cleaner are carried out. Then, the velocity vector plots on the arbitrary plane of the duct flow field are obtained. Finally, an investigation of the dynamic characteristics of the duct flow field is done and defects of the original duct flow field are analysed, the optimisation of the original flow field has then been conducted. Experimental results show that the duct flow field after optimisation can effectively reduce pressure drop, the feasibility as well as the correctness of the theoretical modelling and optimisation approaches are validated.

Optimised heat recovery steam generators for integrated solar combined cycle plants

Science.gov (United States)

Peterseim, Jürgen H.; Huschka, Karsten

2017-06-01

The cost of concentrating solar power (CSP) plants is decreasing but, due to the cost differences and the currently limited value of energy storage, implementation of new facilities is still slow compared to photovoltaic systems. One recognized option to lower cost instantly is the hybridization of CSP with other energy sources, such as natural gas or biomass. Various references exist for the combination of CSP with natural gas in combined cycle plants, also known as Integrated Solar Combined Cycle (ISCC) plants. One problem with current ISCC concepts is the so called ISCC crisis, which occurs when CSP is not contributing and cycle efficiency falls below efficiency levels of solely natural gas only fired combined cycle plants. This paper analyses current ISCC concepts and compares them with two optimised designs. The comparison is based on a Kuraymat type ISCC plant and shows that cycle optimization enables a net capacity increase of 1.4% and additional daily generation of up to 7.9%. The specific investment of the optimised Integrated Solar Combined Cycle plant results in a 0.4% cost increase, which is below the additional net capacity and daily generation increase.

Utility systems operation: Optimisation-based decision making

International Nuclear Information System (INIS)

Velasco-Garcia, Patricia; Varbanov, Petar Sabev; Arellano-Garcia, Harvey; Wozny, Guenter

2011-01-01

Utility systems provide heat and power to industrial sites. The importance of operating these systems in an optimal way has increased significantly due to the unstable and in the long term rising prices of fossil fuels as well as the need for reducing the greenhouse gas emissions. This paper presents an analysis of the problem for supporting operator decision making under conditions of variable steam demands from the production processes on an industrial site. An optimisation model has been developed, where besides for running the utility system, also the costs associated with starting-up the operating units have been modelled. The illustrative case study shows that accounting for the shut-downs and start-ups of utility operating units can bring significant cost savings. - Highlights: → Optimisation methodology for decision making on running utility systems. → Accounting for varying steam demands. → Optimal operating specifications when a demand change occurs. → Operating costs include start-up costs of boilers and other units. → Validated on a real-life case study. Up to 20% cost savings are possible.

Improving linear transport infrastructure efficiency by automated learning and optimised predictive maintenance techniques (INFRALERT)

Science.gov (United States)

Jiménez-Redondo, Noemi; Calle-Cordón, Alvaro; Kandler, Ute; Simroth, Axel; Morales, Francisco J.; Reyes, Antonio; Odelius, Johan; Thaduri, Aditya; Morgado, Joao; Duarte, Emmanuele

2017-09-01

The on-going H2020 project INFRALERT aims to increase rail and road infrastructure capacity in the current framework of increased transportation demand by developing and deploying solutions to optimise maintenance interventions planning. It includes two real pilots for road and railways infrastructure. INFRALERT develops an ICT platform (the expert-based Infrastructure Management System, eIMS) which follows a modular approach including several expert-based toolkits. This paper presents the methodologies and preliminary results of the toolkits for i) nowcasting and forecasting of asset condition, ii) alert generation, iii) RAMS & LCC analysis and iv) decision support. The results of these toolkits in a meshed road network in Portugal under the jurisdiction of Infraestruturas de Portugal (IP) are presented showing the capabilities of the approaches.

Genetic algorithms and artificial neural networks for loading pattern optimisation of advanced gas-cooled reactors

Energy Technology Data Exchange (ETDEWEB)

Ziver, A.K. E-mail: a.k.ziver@imperial.ac.uk; Pain, C.C; Carter, J.N.; Oliveira, C.R.E. de; Goddard, A.J.H.; Overton, R.S

2004-03-01

A non-generational genetic algorithm (GA) has been developed for fuel management optimisation of Advanced Gas-Cooled Reactors, which are operated by British Energy and produce around 20% of the UK's electricity requirements. An evolutionary search is coded using the genetic operators; namely selection by tournament, two-point crossover, mutation and random assessment of population for multi-cycle loading pattern (LP) optimisation. A detailed description of the chromosomes in the genetic algorithm coded is presented. Artificial Neural Networks (ANNs) have been constructed and trained to accelerate the GA-based search during the optimisation process. The whole package, called GAOPT, is linked to the reactor analysis code PANTHER, which performs fresh fuel loading, burn-up and power shaping calculations for each reactor cycle by imposing station-specific safety and operational constraints. GAOPT has been verified by performing a number of tests, which are applied to the Hinkley Point B and Hartlepool reactors. The test results giving loading pattern (LP) scenarios obtained from single and multi-cycle optimisation calculations applied to realistic reactor states of the Hartlepool and Hinkley Point B reactors are discussed. The results have shown that the GA/ANN algorithms developed can help the fuel engineer to optimise loading patterns in an efficient and more profitable way than currently available for multi-cycle refuelling of AGRs. Research leading to parallel GAs applied to LP optimisation are outlined, which can be adapted to present day LWR fuel management problems.

A COMPARATIVE STUDY ON MULTI-SWARM OPTIMISATION AND BAT ALGORITHM FOR UNCONSTRAINED NON LINEAR OPTIMISATION PROBLEMS

Directory of Open Access Journals (Sweden)

Evans BAIDOO

2016-12-01

Full Text Available A study branch that mocks-up a population of network of swarms or agents with the ability to self-organise is Swarm intelligence. In spite of the huge amount of work that has been done in this area in both theoretically and empirically and the greater success that has been attained in several aspects, it is still ongoing and at its infant stage. An immune system, a cloud of bats, or a flock of birds are distinctive examples of a swarm system. . In this study, two types of meta-heuristics algorithms based on population and swarm intelligence - Multi Swarm Optimization (MSO and Bat algorithms (BA - are set up to find optimal solutions of continuous non-linear optimisation models. In order to analyze and compare perfect solutions at the expense of performance of both algorithms, a chain of computational experiments on six generally used test functions for assessing the accuracy and the performance of algorithms, in swarm intelligence fields are used. Computational experiments show that MSO algorithm seems much superior to BA.

Linear-scaling time-dependent density-functional theory beyond the Tamm-Dancoff approximation: Obtaining efficiency and accuracy with in situ optimised local orbitals

Energy Technology Data Exchange (ETDEWEB)

Zuehlsdorff, T. J., E-mail: tjz21@cam.ac.uk; Payne, M. C. [Cavendish Laboratory, J. J. Thomson Avenue, Cambridge CB3 0HE (United Kingdom); Hine, N. D. M. [Department of Physics, University of Warwick, Coventry CV4 7AL (United Kingdom); Haynes, P. D. [Department of Materials, Imperial College London, Exhibition Road, London SW7 2AZ (United Kingdom); Department of Physics, Imperial College London, Exhibition Road, London SW7 2AZ (United Kingdom); Thomas Young Centre for Theory and Simulation of Materials, Imperial College London, Exhibition Road, London SW7 2AZ (United Kingdom)

2015-11-28

We present a solution of the full time-dependent density-functional theory (TDDFT) eigenvalue equation in the linear response formalism exhibiting a linear-scaling computational complexity with system size, without relying on the simplifying Tamm-Dancoff approximation (TDA). The implementation relies on representing the occupied and unoccupied subspaces with two different sets of in situ optimised localised functions, yielding a very compact and efficient representation of the transition density matrix of the excitation with the accuracy associated with a systematic basis set. The TDDFT eigenvalue equation is solved using a preconditioned conjugate gradient algorithm that is very memory-efficient. The algorithm is validated on a small test molecule and a good agreement with results obtained from standard quantum chemistry packages is found, with the preconditioner yielding a significant improvement in convergence rates. The method developed in this work is then used to reproduce experimental results of the absorption spectrum of bacteriochlorophyll in an organic solvent, where it is demonstrated that the TDA fails to reproduce the main features of the low energy spectrum, while the full TDDFT equation yields results in good qualitative agreement with experimental data. Furthermore, the need for explicitly including parts of the solvent into the TDDFT calculations is highlighted, making the treatment of large system sizes necessary that are well within reach of the capabilities of the algorithm introduced here. Finally, the linear-scaling properties of the algorithm are demonstrated by computing the lowest excitation energy of bacteriochlorophyll in solution. The largest systems considered in this work are of the same order of magnitude as a variety of widely studied pigment-protein complexes, opening up the possibility of studying their properties without having to resort to any semiclassical approximations to parts of the protein environment.

Greater power and computational efficiency for kernel-based association testing of sets of genetic variants.

Science.gov (United States)

Lippert, Christoph; Xiang, Jing; Horta, Danilo; Widmer, Christian; Kadie, Carl; Heckerman, David; Listgarten, Jennifer

2014-11-15

Set-based variance component tests have been identified as a way to increase power in association studies by aggregating weak individual effects. However, the choice of test statistic has been largely ignored even though it may play an important role in obtaining optimal power. We compared a standard statistical test-a score test-with a recently developed likelihood ratio (LR) test. Further, when correction for hidden structure is needed, or gene-gene interactions are sought, state-of-the art algorithms for both the score and LR tests can be computationally impractical. Thus we develop new computationally efficient methods. After reviewing theoretical differences in performance between the score and LR tests, we find empirically on real data that the LR test generally has more power. In particular, on 15 of 17 real datasets, the LR test yielded at least as many associations as the score test-up to 23 more associations-whereas the score test yielded at most one more association than the LR test in the two remaining datasets. On synthetic data, we find that the LR test yielded up to 12% more associations, consistent with our results on real data, but also observe a regime of extremely small signal where the score test yielded up to 25% more associations than the LR test, consistent with theory. Finally, our computational speedups now enable (i) efficient LR testing when the background kernel is full rank, and (ii) efficient score testing when the background kernel changes with each test, as for gene-gene interaction tests. The latter yielded a factor of 2000 speedup on a cohort of size 13 500. Software available at http://research.microsoft.com/en-us/um/redmond/projects/MSCompBio/Fastlmm/. heckerma@microsoft.com Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

Energy efficient hybrid computing systems using spin devices

Science.gov (United States)

Sharad, Mrigank

Emerging spin-devices like magnetic tunnel junctions (MTJ's), spin-valves and domain wall magnets (DWM) have opened new avenues for spin-based logic design. This work explored potential computing applications which can exploit such devices for higher energy-efficiency and performance. The proposed applications involve hybrid design schemes, where charge-based devices supplement the spin-devices, to gain large benefits at the system level. As an example, lateral spin valves (LSV) involve switching of nanomagnets using spin-polarized current injection through a metallic channel such as Cu. Such spin-torque based devices possess several interesting properties that can be exploited for ultra-low power computation. Analog characteristic of spin current facilitate non-Boolean computation like majority evaluation that can be used to model a neuron. The magneto-metallic neurons can operate at ultra-low terminal voltage of ˜20mV, thereby resulting in small computation power. Moreover, since nano-magnets inherently act as memory elements, these devices can facilitate integration of logic and memory in interesting ways. The spin based neurons can be integrated with CMOS and other emerging devices leading to different classes of neuromorphic/non-Von-Neumann architectures. The spin-based designs involve `mixed-mode' processing and hence can provide very compact and ultra-low energy solutions for complex computation blocks, both digital as well as analog. Such low-power, hybrid designs can be suitable for various data processing applications like cognitive computing, associative memory, and currentmode on-chip global interconnects. Simulation results for these applications based on device-circuit co-simulation framework predict more than ˜100x improvement in computation energy as compared to state of the art CMOS design, for optimal spin-device parameters.

Computation of the efficiency distribution of a multichannel focusing collimator

International Nuclear Information System (INIS)

Balasubramanian, A.; Venkateswaran, T.V.

1977-01-01

This article describes two computer methods of calculating the point source efficiency distribution functions of a focusing collimator with round tapered holes. The first method which computes only the geometric efficiency distribution is adequate for low energy collimators while the second method which computes both geometric and penetration efficiencies can be made use of for medium and high energy collimators. The scatter contribution to the efficiency is not taken into account. In the first method the efficiency distribution of a single cone of the collimator is obtained and the data are used for computing the distribution of the whole collimator. For high energy collimator the entire detector region is imagined to be divided into elemental areas. Efficiency of the elemental area is computed after suitably weighting for the penetration within the collimator septa, which is determined by three dimensional geometric techniques. The method of computing the line source efficiency distribution from point source distribution is also explained. The formulations have been tested by computing the efficiency distribution of several commercial collimators and collimators fabricated by us. (Auth.)

Efficient Multi-Party Computation over Rings

DEFF Research Database (Denmark)

Cramer, Ronald; Fehr, Serge; Ishai, Yuval

2003-01-01

Secure multi-party computation (MPC) is an active research area, and a wide range of literature can be found nowadays suggesting improvements and generalizations of existing protocols in various directions. However, all current techniques for secure MPC apply to functions that are represented by ...... the usefulness of the above results by presenting a novel application of MPC over (non-field) rings to the round-efficient secure computation of the maximum function. Basic Research in Computer Science (www.brics.dk), funded by the Danish National Research Foundation.......Secure multi-party computation (MPC) is an active research area, and a wide range of literature can be found nowadays suggesting improvements and generalizations of existing protocols in various directions. However, all current techniques for secure MPC apply to functions that are represented...... by (boolean or arithmetic) circuits over finite fields. We are motivated by two limitations of these techniques: – Generality. Existing protocols do not apply to computation over more general algebraic structures (except via a brute-force simulation of computation in these structures). – Efficiency. The best...

Numerical optimisation of friction stir welding: review of future challenges

DEFF Research Database (Denmark)

Tutum, Cem Celal; Hattel, Jesper Henri

2011-01-01

During the last decade, the combination of increasingly more advanced numerical simulation software with high computational power has resulted in models for friction stir welding (FSW), which have improved the understanding of the determining physical phenomena behind the process substantially....... This has made optimisation of certain process parameters possible and has in turn led to better performing friction stir welded products, thus contributing to a general increase in the popularity of the process and its applications. However, most of these optimisation studies do not go well beyond manual...

Optimisation of X-ray examinations: General principles and an Irish perspective

International Nuclear Information System (INIS)

Matthews, Kate; Brennan, Patrick C.

2009-01-01

In Ireland, the European Medical Exposures Directive [Council Directive 97/43] was enacted into national law in Statutory Instrument 478 of 2002. This series of three review articles discusses the status of justification and optimisation of X-ray examinations nationally, and progress with the establishment of Irish diagnostic reference levels. In this second article, literature relating to optimisation issues arising in SI 478 of 2002 is reviewed. Optimisation associated with X-ray equipment and optimisation during day-to-day practice are considered. Optimisation proposals found in published research are summarised, and indicate the complex nature of optimisation. A paucity of current, research-based guidance documentation is identified. This is needed in order to support a range of professional staff in their practical implementation of optimisation.

Optimisation of test and maintenance based on probabilistic methods

International Nuclear Information System (INIS)

Cepin, M.

2001-01-01

This paper presents a method, which based on models and results of probabilistic safety assessment, minimises the nuclear power plant risk by optimisation of arrangement of safety equipment outages. The test and maintenance activities of the safety equipment are timely arranged, so the classical static fault tree models are extended with the time requirements to be capable to model real plant states. A house event matrix is used, which enables modelling of the equipment arrangements through the discrete points of time. The result of the method is determination of such configuration of equipment outages, which result in the minimal risk. Minimal risk is represented by system unavailability. (authors)

PHYSICAL-MATEMATICALSCIENCE MECHANICS SIMULATION CHALLENGES IN OPTIMISING THEORETICAL METAL CUTTING TASKS

Directory of Open Access Journals (Sweden)

Rasul V. Guseynov

2017-01-01

Full Text Available Abstract. Objectives In the article, problems in the optimising of machining operations, which provide end-unit production of the required quality with a minimum processing cost, are addressed. Methods Increasing the effectiveness of experimental research was achieved through the use of mathematical methods for planning experiments for optimising metal cutting tasks. The minimal processing cost model, in which the objective function is polynomial, is adopted as a criterion for the selection of optimal parameters. Results Polynomial models of the influence of angles φ, α, γ on the torque applied when cutting threads in various steels are constructed. Optimum values of the geometrical tool parameters were obtained using the criterion of minimum cutting forces during processing. The high stability of tools having optimal geometric parameters is determined. It is shown that the use of experimental planning methods allows the optimisation of cutting parameters. In optimising solutions to metal cutting problems, it is found to be expedient to use multifactor experimental planning methods and to select the cutting force as the optimisation parameter when determining tool geometry. Conclusion The joint use of geometric programming and experiment planning methods in order to optimise the parameters of cutting significantly increases the efficiency of technological metal processing approaches. 

Fast multi-core based multimodal registration of 2D cross-sections and 3D datasets.

Science.gov (United States)

Scharfe, Michael; Pielot, Rainer; Schreiber, Falk

2010-01-11

Solving bioinformatics tasks often requires extensive computational power. Recent trends in processor architecture combine multiple cores into a single chip to improve overall performance. The Cell Broadband Engine (CBE), a heterogeneous multi-core processor, provides power-efficient and cost-effective high-performance computing. One application area is image analysis and visualisation, in particular registration of 2D cross-sections into 3D image datasets. Such techniques can be used to put different image modalities into spatial correspondence, for example, 2D images of histological cuts into morphological 3D frameworks. We evaluate the CBE-driven PlayStation 3 as a high performance, cost-effective computing platform by adapting a multimodal alignment procedure to several characteristic hardware properties. The optimisations are based on partitioning, vectorisation, branch reducing and loop unrolling techniques with special attention to 32-bit multiplies and limited local storage on the computing units. We show how a typical image analysis and visualisation problem, the multimodal registration of 2D cross-sections and 3D datasets, benefits from the multi-core based implementation of the alignment algorithm. We discuss several CBE-based optimisation methods and compare our results to standard solutions. More information and the source code are available from http://cbe.ipk-gatersleben.de. The results demonstrate that the CBE processor in a PlayStation 3 accelerates computational intensive multimodal registration, which is of great importance in biological/medical image processing. The PlayStation 3 as a low cost CBE-based platform offers an efficient option to conventional hardware to solve computational problems in image processing and bioinformatics.

Efficient and Flexible Climate Analysis with Python in a Cloud-Based Distributed Computing Framework

Science.gov (United States)

Gannon, C.

2017-12-01

As climate models become progressively more advanced, and spatial resolution further improved through various downscaling projects, climate projections at a local level are increasingly insightful and valuable. However, the raw size of climate datasets presents numerous hurdles for analysts wishing to develop customized climate risk metrics or perform site-specific statistical analysis. Four Twenty Seven, a climate risk consultancy, has implemented a Python-based distributed framework to analyze large climate datasets in the cloud. With the freedom afforded by efficiently processing these datasets, we are able to customize and continually develop new climate risk metrics using the most up-to-date data. Here we outline our process for using Python packages such as XArray and Dask to evaluate netCDF files in a distributed framework, StarCluster to operate in a cluster-computing environment, cloud computing services to access publicly hosted datasets, and how this setup is particularly valuable for generating climate change indicators and performing localized statistical analysis.

Computational efficiency for the surface renewal method

Science.gov (United States)

Kelley, Jason; Higgins, Chad

2018-04-01

Measuring surface fluxes using the surface renewal (SR) method requires programmatic algorithms for tabulation, algebraic calculation, and data quality control. A number of different methods have been published describing automated calibration of SR parameters. Because the SR method utilizes high-frequency (10 Hz+) measurements, some steps in the flux calculation are computationally expensive, especially when automating SR to perform many iterations of these calculations. Several new algorithms were written that perform the required calculations more efficiently and rapidly, and that tested for sensitivity to length of flux averaging period, ability to measure over a large range of lag timescales, and overall computational efficiency. These algorithms utilize signal processing techniques and algebraic simplifications that demonstrate simple modifications that dramatically improve computational efficiency. The results here complement efforts by other authors to standardize a robust and accurate computational SR method. Increased speed of computation time grants flexibility to implementing the SR method, opening new avenues for SR to be used in research, for applied monitoring, and in novel field deployments.

Optimising ICT effectiveness in instruction and learning: Multilevel transformation theory and a pilot project in secondary education

NARCIS (Netherlands)

Mooij, Ton

2016-01-01

Specific combinations of educational and ICT conditions including computer use may optimise learning processes, particularly for learners at risk. This position paper asks which curricular, instructional, and ICT characteristics can be expected to optimise learning processes and outcomes,and how to

Statistically and Computationally Efficient Estimating Equations for Large Spatial Datasets

KAUST Repository

Sun, Ying; Stein, Michael L.

2014-01-01

For Gaussian process models, likelihood based methods are often difficult to use with large irregularly spaced spatial datasets, because exact calculations of the likelihood for n observations require O(n3) operations and O(n2) memory. Various approximation methods have been developed to address the computational difficulties. In this paper, we propose new unbiased estimating equations based on score equation approximations that are both computationally and statistically efficient. We replace the inverse covariance matrix that appears in the score equations by a sparse matrix to approximate the quadratic forms, then set the resulting quadratic forms equal to their expected values to obtain unbiased estimating equations. The sparse matrix is constructed by a sparse inverse Cholesky approach to approximate the inverse covariance matrix. The statistical efficiency of the resulting unbiased estimating equations are evaluated both in theory and by numerical studies. Our methods are applied to nearly 90,000 satellite-based measurements of water vapor levels over a region in the Southeast Pacific Ocean.

Statistically and Computationally Efficient Estimating Equations for Large Spatial Datasets

KAUST Repository

Sun, Ying

2014-11-07

For Gaussian process models, likelihood based methods are often difficult to use with large irregularly spaced spatial datasets, because exact calculations of the likelihood for n observations require O(n3) operations and O(n2) memory. Various approximation methods have been developed to address the computational difficulties. In this paper, we propose new unbiased estimating equations based on score equation approximations that are both computationally and statistically efficient. We replace the inverse covariance matrix that appears in the score equations by a sparse matrix to approximate the quadratic forms, then set the resulting quadratic forms equal to their expected values to obtain unbiased estimating equations. The sparse matrix is constructed by a sparse inverse Cholesky approach to approximate the inverse covariance matrix. The statistical efficiency of the resulting unbiased estimating equations are evaluated both in theory and by numerical studies. Our methods are applied to nearly 90,000 satellite-based measurements of water vapor levels over a region in the Southeast Pacific Ocean.

Optimisation of logistics processes of energy grass collection

Science.gov (United States)

Bányai, Tamás.

2010-05-01

objective function of the optimisation is the maximisation of the profit which means the maximization of the difference between revenue and cost. The objective function trades off the income of the assigned transportation demands against the logistic costs. The constraints are the followings: (1) the free capacity of the assigned transportation resource is more than the re-quested capacity of the transportation demand; the calculated arrival time of the transportation resource to the harvesting place is not later than the requested arrival time of them; (3) the calculated arrival time of the transportation demand to the processing and production facility is not later than the requested arrival time; (4) one transportation demand is assigned to one transportation resource and one resource is assigned to one transportation resource. The decision variable of the optimisation problem is the set of scheduling variables and the assignment of resources to transportation demands. The evaluation parameters of the optimised system are the followings: total costs of the collection process; utilisation of transportation resources and warehouses; efficiency of production and/or processing facilities. However the multidimensional heuristic optimisation method is based on genetic algorithm, but the routing sequence of the optimisation works on the base of an ant colony algorithm. The optimal routes are calculated by the aid of the ant colony algorithm as a subroutine of the global optimisation method and the optimal assignment is given by the genetic algorithm. One important part of the mathematical method is the sensibility analysis of the objective function, which shows the influence rate of the different input parameters. Acknowledgements This research was implemented within the frame of the project entitled "Development and operation of the Technology and Knowledge Transfer Centre of the University of Miskolc". with support by the European Union and co-funding of the European Social

An efficient approach for improving virtual machine placement in cloud computing environment

Science.gov (United States)

Ghobaei-Arani, Mostafa; Shamsi, Mahboubeh; Rahmanian, Ali A.

2017-11-01

The ever increasing demand for the cloud services requires more data centres. The power consumption in the data centres is a challenging problem for cloud computing, which has not been considered properly by the data centre developer companies. Especially, large data centres struggle with the power cost and the Greenhouse gases production. Hence, employing the power efficient mechanisms are necessary to optimise the mentioned effects. Moreover, virtual machine (VM) placement can be used as an effective method to reduce the power consumption in data centres. In this paper by grouping both virtual and physical machines, and taking into account the maximum absolute deviation during the VM placement, the power consumption as well as the service level agreement (SLA) deviation in data centres are reduced. To this end, the best-fit decreasing algorithm is utilised in the simulation to reduce the power consumption by about 5% compared to the modified best-fit decreasing algorithm, and at the same time, the SLA violation is improved by 6%. Finally, the learning automata are used to a trade-off between power consumption reduction from one side, and SLA violation percentage from the other side.

SEDRX: A computer program for the simulation Si(Li) and Ge(Hp) x-ray detectors efficiency

International Nuclear Information System (INIS)

Benamar, M.A.; Benouali, A.; Tchantchane, A.; Azbouche, A.; Tobbeche, S. Centre de Developpement des Techniques Nucleaires, Algiers; Labo. des Techniques Nucleaires)

1992-12-01

The difficulties encountered in measuring the x-ray detectors efficiency has motivated to develop a computer program to simulate this parameter. this program computes the efficiency of detectors as a function of energy. the computation of this parameter is based on the fitting coefficients of absorption in the case of photoelectric, coherent and incoherent factors. These coefficients are given by Mc Master library or may be determined by the interpolation based on cubic splines

Ontology-based coupled optimisation design method using state-space analysis for the spindle box system of large ultra-precision optical grinding machine

Science.gov (United States)

Wang, Qianren; Chen, Xing; Yin, Yuehong; Lu, Jian

2017-08-01

With the increasing complexity of mechatronic products, traditional empirical or step-by-step design methods are facing great challenges with various factors and different stages having become inevitably coupled during the design process. Management of massive information or big data, as well as the efficient operation of information flow, is deeply involved in the process of coupled design. Designers have to address increased sophisticated situations when coupled optimisation is also engaged. Aiming at overcoming these difficulties involved in conducting the design of the spindle box system of ultra-precision optical grinding machine, this paper proposed a coupled optimisation design method based on state-space analysis, with the design knowledge represented by ontologies and their semantic networks. An electromechanical coupled model integrating mechanical structure, control system and driving system of the motor is established, mainly concerning the stiffness matrix of hydrostatic bearings, ball screw nut and rolling guide sliders. The effectiveness and precision of the method are validated by the simulation results of the natural frequency and deformation of the spindle box when applying an impact force to the grinding wheel.

A method for the calculation of collision strengths for complex atomic structures based on Slater parameter optimisation

International Nuclear Information System (INIS)

Fawcett, B.C.; Mason, H.E.

1989-02-01

This report presents details of a new method to enable the computation of collision strengths for complex ions which is adapted from long established optimisation techniques previously applied to the calculation of atomic structures and oscillator strengths. The procedure involves the adjustment of Slater parameters so that they determine improved energy levels and eigenvectors. They provide a basis for collision strength calculations in ions where ab initio computations break down or result in reducible errors. This application is demonstrated through modifications of the DISTORTED WAVE collision code and SUPERSTRUCTURE atomic-structure code which interface via a transformation code JAJOM which processes their output. (author)

An efficient and rigorous thermodynamic library and optimal-control of a cryogenic air separation unit

DEFF Research Database (Denmark)

Gaspar, Jozsef; Ritschel, Tobias Kasper Skovborg; Jørgensen, John Bagterp

2017-01-01

-linear model based control to achieve optimal techno-economic performance. Accordingly, this work presents a computationally efficient and novel approach for solving a tray-by-tray equilibrium model and its implementation for open-loop optimal-control of a cryogenic distillation column. Here, the optimisation...... objective is to reduce the cost of compression in a volatile electricity market while meeting the production requirements, i.e. product flow rate and purity. This model is implemented in Matlab and uses the ThermoLib rigorous thermodynamic library. The present work represents a first step towards plant...

Evaluation of the efficiency of computer-aided spectra search systems based on information theory

International Nuclear Information System (INIS)

Schaarschmidt, K.

1979-01-01

Application of information theory allows objective evaluation of the efficiency of computer-aided spectra search systems. For this purpose, a significant number of search processes must be analyzed. The amount of information gained by computer application is considered as the difference between the entropy of the data bank and a conditional entropy depending on the proportion of unsuccessful search processes and ballast. The influence of the following factors can be estimated: volume, structure, and quality of the spectra collection stored, efficiency of the encoding instruction and the comparing algorithm, and subjective errors involved in the encoding of spectra. The relations derived are applied to two published storage and retrieval systems for infared spectra. (Auth.)

Synthesis of A Sustainable Sago-Based Value Chain via Fuzzy Optimisation Approach

Directory of Open Access Journals (Sweden)

Chong Jeffrey Hong Seng

2018-01-01

Full Text Available Sago starch is one of the staple foods for human, especially in Asia’s Region. It can be produced via sago starch extraction process (SSEP. During the SSEP, several types of sago wastes are generated such as sago fiber (SF, sago bark (SB and sago wastewater (SW. With the increase in production of existing factories and sago mills, the sago industrial practice in waste disposal management is gaining more attention, thus implementation of effective waste management is vital. One of the promising ways to have effective waste management is to create value out of the sago wastes. In a recent study, sago-based refinery, which is a facility to convert sago wastes into value-added products (e.g., bio-ethanol and energy was found feasible. However, the conversion of other value added products from sago wastes while considering the environmental impact has not been considered in sago value chain. Therefore, an optimum sago value chain, which involved conversion activities of sago wastes into value-added products, is aimed to be synthesised in this work. The optimum sago value chain will be evaluated based on profit and carbon emissions using fuzzy-based optimisation approach via a commercial optimisation software, Lingo 16.0. To illustrate the the developed approach, an industrial case study has been solved in this work.

Optimising costs in WLCG operations

CERN Document Server

Pradillo, Mar; Flix, Josep; Forti, Alessandra; Sciabà, Andrea

2015-01-01

The Worldwide LHC Computing Grid project (WLCG) provides the computing and storage resources required by the LHC collaborations to store, process and analyse the 50 Petabytes of data annually generated by the LHC. The WLCG operations are coordinated by a distributed team of managers and experts and performed by people at all participating sites and from all the experiments. Several improvements in the WLCG infrastructure have been implemented during the first long LHC shutdown to prepare for the increasing needs of the experiments during Run2 and beyond. However, constraints in funding will affect not only the computing resources but also the available effort for operations. This paper presents the results of a detailed investigation on the allocation of the effort in the different areas of WLCG operations, identifies the most important sources of inefficiency and proposes viable strategies for optimising the operational cost, taking into account the current trends in the evolution of the computing infrastruc...

Efficient Sustainable Operation Mechanism of Distributed Desktop Integration Storage Based on Virtualization with Ubiquitous Computing

Directory of Open Access Journals (Sweden)

Hyun-Woo Kim

2015-06-01

Full Text Available Following the rapid growth of ubiquitous computing, many jobs that were previously manual have now been automated. This automation has increased the amount of time available for leisure; diverse services are now being developed for this leisure time. In addition, the development of small and portable devices like smartphones, diverse Internet services can be used regardless of time and place. Studies regarding diverse virtualization are currently in progress. These studies aim to determine ways to efficiently store and process the big data generated by the multitude of devices and services in use. One topic of such studies is desktop storage virtualization, which integrates distributed desktop resources and provides these resources to users to integrate into distributed legacy desktops via virtualization. In the case of desktop storage virtualization, high availability of virtualization is necessary and important for providing reliability to users. Studies regarding hierarchical structures and resource integration are currently in progress. These studies aim to create efficient data distribution and storage for distributed desktops based on resource integration environments. However, studies regarding efficient responses to server faults occurring in desktop-based resource integration environments have been insufficient. This paper proposes a mechanism for the sustainable operation of desktop storage (SODS for high operational availability. It allows for the easy addition and removal of desktops in desktop-based integration environments. It also activates alternative servers when a fault occurs within a system.

Optimisation of timetable-based, stochastic transit assignment models based on MSA

DEFF Research Database (Denmark)

Nielsen, Otto Anker; Frederiksen, Rasmus Dyhr

2006-01-01

(CRM), such a large-scale transit assignment model was developed and estimated. The Stochastic User Equilibrium problem was solved by the Method of Successive Averages (MSA). However, the model suffered from very large calculation times. The paper focuses on how to optimise transit assignment models...

Pareto Efficient Solutions of Attack-Defence Trees

DEFF Research Database (Denmark)

Aslanyan, Zaruhi; Nielson, Flemming

2015-01-01

Attack-defence trees are a promising approach for representing threat scenarios and possible countermeasures in a concise and intuitive manner. An attack-defence tree describes the interaction between an attacker and a defender, and is evaluated by assigning parameters to the nodes, such as proba......Attack-defence trees are a promising approach for representing threat scenarios and possible countermeasures in a concise and intuitive manner. An attack-defence tree describes the interaction between an attacker and a defender, and is evaluated by assigning parameters to the nodes......, such as probability or cost of attacks and defences. In case of multiple parameters most analytical methods optimise one parameter at a time, e.g., minimise cost or maximise probability of an attack. Such methods may lead to sub-optimal solutions when optimising conflicting parameters, e.g., minimising cost while...... maximising probability. In order to tackle this challenge, we devise automated techniques that optimise all parameters at once. Moreover, in the case of conflicting parameters our techniques compute the set of all optimal solutions, defined in terms of Pareto efficiency. The developments are carried out...

A comparison of forward planning and optimised inverse planning

International Nuclear Information System (INIS)

Oldham, Mark; Neal, Anthony; Webb, Steve

1995-01-01

A radiotherapy treatment plan optimisation algorithm has been applied to 48 prostate plans and the results compared with those of an experienced human planner. Twelve patients were used in the study, and a 3, 4, 6 and 8 field plan (with standard coplanar beam angles for each plan type) were optimised by both the human planner and the optimisation algorithm. The human planner 'optimised' the plan by conventional forward planning techniques. The optimisation algorithm was based on fast-simulated-annealing. 'Importance factors' assigned to different regions of the patient provide a method for controlling the algorithm, and it was found that the same values gave good results for almost all plans. The plans were compared on the basis of dose statistics and normal-tissue-complication-probability (NTCP) and tumour-control-probability (TCP). The results show that the optimisation algorithm yielded results that were at least as good as the human planner for all plan types, and on the whole slightly better. A study of the beam-weights chosen by the optimisation algorithm and the planner will be presented. The optimisation algorithm showed greater variation, in response to individual patient geometry. For simple (e.g. 3 field) plans it was found to consistently achieve slightly higher TCP and lower NTCP values. For more complicated (e.g. 8 fields) plans the optimisation also achieved slightly better results with generally less numbers of beams. The optimisation time was always ≤5 minutes; a factor of up to 20 times faster than the human planner

Cost evaluation to optimise radiation therapy implementation in different income settings: A time-driven activity-based analysis.

Science.gov (United States)

Van Dyk, Jacob; Zubizarreta, Eduardo; Lievens, Yolande

2017-11-01

With increasing recognition of growing cancer incidence globally, efficient means of expanding radiotherapy capacity is imperative, and understanding the factors impacting human and financial needs is valuable. A time-driven activity-based costing analysis was performed, using a base case of 2-machine departments, with defined cost inputs and operating parameters. Four income groups were analysed, ranging from low to high income. Scenario analyses included department size, operating hours, fractionation, treatment complexity, efficiency, and centralised versus decentralised care. The base case cost/course is US$5,368 in HICs, US$2,028 in LICs; the annual operating cost is US$4,595,000 and US$1,736,000, respectively. Economies of scale show cost/course decreasing with increasing department size, mainly related to the equipment cost and most prominent up to 3 linacs. The cost in HICs is two or three times as high as in U-MICs or LICs, respectively. Decreasing operating hours below 8h/day has a dramatic impact on the cost/course. IMRT increases the cost/course by 22%. Centralising preparatory activities has a moderate impact on the costs. The results indicate trends that are useful for optimising local and regional circumstances. This methodology can provide input into a uniform and accepted approach to evaluating the cost of radiotherapy. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Identity-Based Authentication for Cloud Computing

Science.gov (United States)

Li, Hongwei; Dai, Yuanshun; Tian, Ling; Yang, Haomiao

Cloud computing is a recently developed new technology for complex systems with massive-scale services sharing among numerous users. Therefore, authentication of both users and services is a significant issue for the trust and security of the cloud computing. SSL Authentication Protocol (SAP), once applied in cloud computing, will become so complicated that users will undergo a heavily loaded point both in computation and communication. This paper, based on the identity-based hierarchical model for cloud computing (IBHMCC) and its corresponding encryption and signature schemes, presented a new identity-based authentication protocol for cloud computing and services. Through simulation testing, it is shown that the authentication protocol is more lightweight and efficient than SAP, specially the more lightweight user side. Such merit of our model with great scalability is very suited to the massive-scale cloud.

Optimisation of a novel trailing edge concept for a high lift device

CSIR Research Space (South Africa)

Botha, JDM

2014-09-01

Full Text Available A novel concept (referred to as the flap extension) is implemented on the leading edge of the flap of a three element high lift device. The concept is optimised using two optimisation approaches based on Genetic Algorithm optimisations. A zero order...

Energy-optimised mini-refrigerators; Energieoptimierter Minikuehlschrank. Massnahmen zur Optimierung der Energieeffizienz von Minikuehlschraenken

Energy Technology Data Exchange (ETDEWEB)

Burri, A.

2007-10-15

This illustrated final report for the Swiss Federal Office of Energy (SFOE) takes a look at measures to be taken to optimise the energy-efficiency of small refrigerators. Such devices are typically to be found in hotel rooms and on boats as well as in caravans and motor homes. The majority of these mini-refrigerators use the absorption principle for cooling. Although less efficient than their compressor-driven counterparts, absorption refrigerators satisfy market requirements and customer wishes with regard to noiseless and maintenance-free operation. The report discusses how optimisation of the absorption principle could lead to energy savings in the long term. The operating principles and energy balances of such refrigerators are discussed and a market overview is presented. Energy consumption of the refrigerators, possible savings and energy costs are discussed. The advantages and disadvantages of various cooling systems are examined as are further possibilities for making savings such as the optimisation of sizing, installation methods, airflow factors and operating temperatures.

Efficient Parallel Kernel Solvers for Computational Fluid Dynamics Applications

Science.gov (United States)

Sun, Xian-He

1997-01-01

Distributed-memory parallel computers dominate today's parallel computing arena. These machines, such as Intel Paragon, IBM SP2, and Cray Origin2OO, have successfully delivered high performance computing power for solving some of the so-called "grand-challenge" problems. Despite initial success, parallel machines have not been widely accepted in production engineering environments due to the complexity of parallel programming. On a parallel computing system, a task has to be partitioned and distributed appropriately among processors to reduce communication cost and to attain load balance. More importantly, even with careful partitioning and mapping, the performance of an algorithm may still be unsatisfactory, since conventional sequential algorithms may be serial in nature and may not be implemented efficiently on parallel machines. In many cases, new algorithms have to be introduced to increase parallel performance. In order to achieve optimal performance, in addition to partitioning and mapping, a careful performance study should be conducted for a given application to find a good algorithm-machine combination. This process, however, is usually painful and elusive. The goal of this project is to design and develop efficient parallel algorithms for highly accurate Computational Fluid Dynamics (CFD) simulations and other engineering applications. The work plan is 1) developing highly accurate parallel numerical algorithms, 2) conduct preliminary testing to verify the effectiveness and potential of these algorithms, 3) incorporate newly developed algorithms into actual simulation packages. The work plan has well achieved. Two highly accurate, efficient Poisson solvers have been developed and tested based on two different approaches: (1) Adopting a mathematical geometry which has a better capacity to describe the fluid, (2) Using compact scheme to gain high order accuracy in numerical discretization. The previously developed Parallel Diagonal Dominant (PDD) algorithm

Distributed optimisation problem with communication delay and external disturbance

Science.gov (United States)

Tran, Ngoc-Tu; Xiao, Jiang-Wen; Wang, Yan-Wu; Yang, Wu

2017-12-01

This paper investigates the distributed optimisation problem for the multi-agent systems (MASs) with the simultaneous presence of external disturbance and the communication delay. To solve this problem, a two-step design scheme is introduced. In the first step, based on the internal model principle, the internal model term is constructed to compensate the disturbance asymptotically. In the second step, a distributed optimisation algorithm is designed to solve the distributed optimisation problem based on the MASs with the simultaneous presence of disturbance and communication delay. Moreover, in the proposed algorithm, each agent interacts with its neighbours through the connected topology and the delay occurs during the information exchange. By utilising Lyapunov-Krasovskii functional, the delay-dependent conditions are derived for both slowly and fast time-varying delay, respectively, to ensure the convergence of the algorithm to the optimal solution of the optimisation problem. Several numerical simulation examples are provided to illustrate the effectiveness of the theoretical results.

A Bayesian Approach for Sensor Optimisation in Impact Identification

Directory of Open Access Journals (Sweden)

Vincenzo Mallardo

2016-11-01

Full Text Available This paper presents a Bayesian approach for optimizing the position of sensors aimed at impact identification in composite structures under operational conditions. The uncertainty in the sensor data has been represented by statistical distributions of the recorded signals. An optimisation strategy based on the genetic algorithm is proposed to find the best sensor combination aimed at locating impacts on composite structures. A Bayesian-based objective function is adopted in the optimisation procedure as an indicator of the performance of meta-models developed for different sensor combinations to locate various impact events. To represent a real structure under operational load and to increase the reliability of the Structural Health Monitoring (SHM system, the probability of malfunctioning sensors is included in the optimisation. The reliability and the robustness of the procedure is tested with experimental and numerical examples. Finally, the proposed optimisation algorithm is applied to a composite stiffened panel for both the uniform and non-uniform probability of impact occurrence.

Credit price optimisation within retail banking

African Journals Online (AJOL)

2014-02-14

Feb 14, 2014 ... cost based pricing, where the price of a product or service is based on the .... function obtained from fitting a logistic regression model .... Note that the proposed optimisation approach below will allow us to also incorporate.

Design optimisation of powers-of-two FIR filter using self-organising random immigrants GA

Science.gov (United States)

Chandra, Abhijit; Chattopadhyay, Sudipta

2015-01-01

In this communication, we propose a novel design strategy of multiplier-less low-pass finite impulse response (FIR) filter with the aid of a recent evolutionary optimisation technique, known as the self-organising random immigrants genetic algorithm. Individual impulse response coefficients of the proposed filter have been encoded as sum of signed powers-of-two. During the formulation of the cost function for the optimisation algorithm, both the frequency response characteristic and the hardware cost of the discrete coefficient FIR filter have been considered. The role of crossover probability of the optimisation technique has been evaluated on the overall performance of the proposed strategy. For this purpose, the convergence characteristic of the optimisation technique has been included in the simulation results. In our analysis, two design examples of different specifications have been taken into account. In order to substantiate the efficiency of our proposed structure, a number of state-of-the-art design strategies of multiplier-less FIR filter have also been included in this article for the purpose of comparison. Critical analysis of the result unambiguously establishes the usefulness of our proposed approach for the hardware efficient design of digital filter.

An operations research and simulation based study on improving the efficiency of a slurry drying tower

Directory of Open Access Journals (Sweden)

De Jongh, E.

2013-08-01

Full Text Available This paper relates to a company that produces washing powders. The focus is on improving the efficiency of gas usage (per unit of powder produced in the furnace that produces hot air. This hot air is an integral part of washing powder production: it dries the viscous slurry and transforms it into the base powder used in all washing powders. The cost of gas is the factorys largest expense. This paper attempts to increase the productivity and profitability of the operations by applying operations research using MATLAB and the non-linear optimiser called SNOPT (sparse non-linear optimiser. Using these techniques, a proposed solution that aims to balance the amount of open space between spraying slurry, as well as the overlap of spraying slurry within the furnace, is obtained. This is achieved by optimising the positioning of the top layer of 24 lances. The placement of the bottom layer of lances is done by positioning them in the areas of biggest overlap. These improvements result in a positive impact on the amount of gas burnt within the furnace to dry slurry to powder.

[Efficiency of computer-based documentation in long-term care--preliminary project].

Science.gov (United States)

Lüngen, Markus; Gerber, Andreas; Rupprecht, Christoph; Lauterbach, Karl W

2008-06-01

In Germany the documentation of processes in long-term care is mainly paper-based. Planning, realization and evaluation are not supported in an optimal way. In a preliminary study we evaluated the consequences of the introduction of a computer-based documentation system using handheld devices. We interviewed 16 persons before and after introducing the computer-based documentation and assessed costs for the documentation process and administration. The results show that reducing costs is likely. The job satisfaction of the personnel increased, more time could be spent for caring for the residents. We suggest further research to reach conclusive results.

Optimisation of laser welding parameters for welding of P92 material using Taguchi based grey relational analysis

Directory of Open Access Journals (Sweden)

Shanmugarajan B.

2016-08-01

Full Text Available Creep strength enhanced ferritic (CSEF steels are used in advanced power plant systems for high temperature applications. P92 (Cr–W–Mo–V steel, classified under CSEF steels, is a candidate material for piping, tubing, etc., in ultra-super critical and advanced ultra-super critical boiler applications. In the present work, laser welding process has been optimised for P92 material by using Taguchi based grey relational analysis (GRA. Bead on plate (BOP trials were carried out using a 3.5 kW diffusion cooled slab CO2 laser by varying laser power, welding speed and focal position. The optimum parameters have been derived by considering the responses such as depth of penetration, weld width and heat affected zone (HAZ width. Analysis of variance (ANOVA has been used to analyse the effect of different parameters on the responses. Based on ANOVA, laser power of 3 kW, welding speed of 1 m/min and focal plane at −4 mm have evolved as optimised set of parameters. The responses of the optimised parameters obtained using the GRA have been verified experimentally and found to closely correlate with the predicted value.

Efficient p-value evaluation for resampling-based tests

KAUST Repository

Yu, K.

2011-01-05

The resampling-based test, which often relies on permutation or bootstrap procedures, has been widely used for statistical hypothesis testing when the asymptotic distribution of the test statistic is unavailable or unreliable. It requires repeated calculations of the test statistic on a large number of simulated data sets for its significance level assessment, and thus it could become very computationally intensive. Here, we propose an efficient p-value evaluation procedure by adapting the stochastic approximation Markov chain Monte Carlo algorithm. The new procedure can be used easily for estimating the p-value for any resampling-based test. We show through numeric simulations that the proposed procedure can be 100-500 000 times as efficient (in term of computing time) as the standard resampling-based procedure when evaluating a test statistic with a small p-value (e.g. less than 10( - 6)). With its computational burden reduced by this proposed procedure, the versatile resampling-based test would become computationally feasible for a much wider range of applications. We demonstrate the application of the new method by applying it to a large-scale genetic association study of prostate cancer.

An Emotional Agent Model Based on Granular Computing

Directory of Open Access Journals (Sweden)

Jun Hu

2012-01-01

Full Text Available Affective computing has a very important significance for fulfilling intelligent information processing and harmonious communication between human being and computers. A new model for emotional agent is proposed in this paper to make agent have the ability of handling emotions, based on the granular computing theory and the traditional BDI agent model. Firstly, a new emotion knowledge base based on granular computing for emotion expression is presented in the model. Secondly, a new emotional reasoning algorithm based on granular computing is proposed. Thirdly, a new emotional agent model based on granular computing is presented. Finally, based on the model, an emotional agent for patient assistant in hospital is realized, experiment results show that it is efficient to handle simple emotions.

Computationally efficient optimisation algorithms for WECs arrays

DEFF Research Database (Denmark)

Ferri, Francesco

2017-01-01

In this paper two derivative-free global optimization algorithms are applied for the maximisation of the energy absorbed by wave energy converter (WEC) arrays. Wave energy is a large and mostly untapped source of energy that could have a key role in the future energy mix. The collection of this r...

Optimisation of the Laser Cutting Process

DEFF Research Database (Denmark)

Dragsted, Birgitte; Olsen, Flemmming Ove

1996-01-01

The problem in optimising the laser cutting process is outlined. Basic optimisation criteria and principles for adapting an optimisation method, the simplex method, are presented. The results of implementing a response function in the optimisation are discussed with respect to the quality as well...

Fast multi-core based multimodal registration of 2D cross-sections and 3D datasets

Directory of Open Access Journals (Sweden)

Pielot Rainer

2010-01-01

Full Text Available Abstract Background Solving bioinformatics tasks often requires extensive computational power. Recent trends in processor architecture combine multiple cores into a single chip to improve overall performance. The Cell Broadband Engine (CBE, a heterogeneous multi-core processor, provides power-efficient and cost-effective high-performance computing. One application area is image analysis and visualisation, in particular registration of 2D cross-sections into 3D image datasets. Such techniques can be used to put different image modalities into spatial correspondence, for example, 2D images of histological cuts into morphological 3D frameworks. Results We evaluate the CBE-driven PlayStation 3 as a high performance, cost-effective computing platform by adapting a multimodal alignment procedure to several characteristic hardware properties. The optimisations are based on partitioning, vectorisation, branch reducing and loop unrolling techniques with special attention to 32-bit multiplies and limited local storage on the computing units. We show how a typical image analysis and visualisation problem, the multimodal registration of 2D cross-sections and 3D datasets, benefits from the multi-core based implementation of the alignment algorithm. We discuss several CBE-based optimisation methods and compare our results to standard solutions. More information and the source code are available from http://cbe.ipk-gatersleben.de. Conclusions The results demonstrate that the CBE processor in a PlayStation 3 accelerates computational intensive multimodal registration, which is of great importance in biological/medical image processing. The PlayStation 3 as a low cost CBE-based platform offers an efficient option to conventional hardware to solve computational problems in image processing and bioinformatics.

Statistical meandering wake model and its application to yaw-angle optimisation of wind farms

International Nuclear Information System (INIS)

Thøgersen, E; Tranberg, B; Greiner, M; Herp, J

2017-01-01

The wake produced by a wind turbine is dynamically meandering and of rather narrow nature. Only when looking at large time averages, the wake appears to be static and rather broad, and is then well described by simple engineering models like the Jensen wake model (JWM). We generalise the latter deterministic models to a statistical meandering wake model (SMWM), where a random directional deflection is assigned to a narrow wake in such a way that on average it resembles a broad Jensen wake. In a second step, the model is further generalised to wind-farm level, where the deflections of the multiple wakes are treated as independently and identically distributed random variables. When carefully calibrated to the Nysted wind farm, the ensemble average of the statistical model produces the same wind-direction dependence of the power efficiency as obtained from the standard Jensen model. Upon using the JWM to perform a yaw-angle optimisation of wind-farm power output, we find an optimisation gain of 6.7% for the Nysted wind farm when compared to zero yaw angles and averaged over all wind directions. When applying the obtained JWM-based optimised yaw angles to the SMWM, the ensemble-averaged gain is calculated to be 7.5%. This outcome indicates the possible operational robustness of an optimised yaw control for real-life wind farms. (paper)

Statistical meandering wake model and its application to yaw-angle optimisation of wind farms

Science.gov (United States)

Thøgersen, E.; Tranberg, B.; Herp, J.; Greiner, M.

2017-05-01

The wake produced by a wind turbine is dynamically meandering and of rather narrow nature. Only when looking at large time averages, the wake appears to be static and rather broad, and is then well described by simple engineering models like the Jensen wake model (JWM). We generalise the latter deterministic models to a statistical meandering wake model (SMWM), where a random directional deflection is assigned to a narrow wake in such a way that on average it resembles a broad Jensen wake. In a second step, the model is further generalised to wind-farm level, where the deflections of the multiple wakes are treated as independently and identically distributed random variables. When carefully calibrated to the Nysted wind farm, the ensemble average of the statistical model produces the same wind-direction dependence of the power efficiency as obtained from the standard Jensen model. Upon using the JWM to perform a yaw-angle optimisation of wind-farm power output, we find an optimisation gain of 6.7% for the Nysted wind farm when compared to zero yaw angles and averaged over all wind directions. When applying the obtained JWM-based optimised yaw angles to the SMWM, the ensemble-averaged gain is calculated to be 7.5%. This outcome indicates the possible operational robustness of an optimised yaw control for real-life wind farms.

Site-specific optimisation of the countermeasure structure on rehabilitation of radioactive contaminated territories

Energy Technology Data Exchange (ETDEWEB)

Yatsalo, B.I.; Okhrimenko, D.V.; Lisyanski, B.G.; Okhrimenko, I.V.; Mirzeabassov, O.A. [Obninsk Institute of Nuclear Power Engineering, Obninsk, Kaluga (Russian Federation)

2000-05-01

The use of 'soft' countermeasures (CMs) (agricultural CMs, some administrative ones, except for relocation/resettlement and some 'strong' measures on restriction of living conditions) allows considering the radiological and economic parameters for assessing their effectiveness. In this case cost-benefit analysis (CBA) or some its modification are used. However, the determination of various radiological and economic parameters (and their combination) is not enough for making final decisions on countermeasure implementation. All radiological, ecological and economic characteristics and other expert knowledge, corresponding standards and regulations should be taken into account, and many of them may not be used very often in analytical methods directly. The approaches to evaluating strong' CMs are based, as a rule, on expert judgements (MAUA, M-Crit). However, in practice they can lead to any result given in advance or to a choice of an weighted solution which does not comply with opinions by most experts due to considerable range of expert opinions and subjective weights for chosen attributes/criteria. Implementation of CMs on rehabilitation of contaminated territories should be based on the radiation protection principles. However, these principles are declared only when realising CMs on rehabilitation of contaminated territories after the Chernobyl accident. In practice some national or departmental standards are used and principles of justification'/'optimisation' are not examined. Taking into consideration a complex character of tasks on CM analysis and comparison of various alternatives it is quite necessary to use up-to-date computer decision support systems (DSSs). One of the systems which is directly intended for site-specific rehabilitation of territories subjected to radioactive contamination after the Chernobyl accident is the PRANA DSS. A key block of PRANA is 'analysis and optimisation of CMs structure

Site-specific optimisation of the countermeasure structure on rehabilitation of radioactive contaminated territories

International Nuclear Information System (INIS)

Yatsalo, B.I.; Okhrimenko, D.V.; Lisyanski, B.G.; Okhrimenko, I.V.; Mirzeabassov, O.A.

2000-01-01

The use of 'soft' countermeasures (CMs) (agricultural CMs, some administrative ones, except for relocation/resettlement and some 'strong' measures on restriction of living conditions) allows considering the radiological and economic parameters for assessing their effectiveness. In this case cost-benefit analysis (CBA) or some its modification are used. However, the determination of various radiological and economic parameters (and their combination) is not enough for making final decisions on countermeasure implementation. All radiological, ecological and economic characteristics and other expert knowledge, corresponding standards and regulations should be taken into account, and many of them may not be used very often in analytical methods directly. The approaches to evaluating strong' CMs are based, as a rule, on expert judgements (MAUA, M-Crit). However, in practice they can lead to any result given in advance or to a choice of an weighted solution which does not comply with opinions by most experts due to considerable range of expert opinions and subjective weights for chosen attributes/criteria. Implementation of CMs on rehabilitation of contaminated territories should be based on the radiation protection principles. However, these principles are declared only when realising CMs on rehabilitation of contaminated territories after the Chernobyl accident. In practice some national or departmental standards are used and principles of justification'/'optimisation' are not examined. Taking into consideration a complex character of tasks on CM analysis and comparison of various alternatives it is quite necessary to use up-to-date computer decision support systems (DSSs). One of the systems which is directly intended for site-specific rehabilitation of territories subjected to radioactive contamination after the Chernobyl accident is the PRANA DSS. A key block of PRANA is 'analysis and optimisation of CMs structure'. It is intended for : -determination of territories

3D based integrated support concept for improving safety and cost-efficiency of nuclear decommissioning projects

International Nuclear Information System (INIS)

Szoeke, Istvan

2016-01-01

extensive rework during the decommissioning phase. 3D technologies have the potential for minimising knowledge loss during the transition to decommissioning, and support efficient reconstruction of design and other knowledge supporting more optimised decommissioning strategies. Application of advanced 3D visualisation technologies are applied for planning the manipulation of heavy large components in decommissioning projects. With the decreasing time and cost investment required for application of 3D simulation and AR technology, an increasing number of experts are exploring the possibilities in using such methods for supporting on-site logistics (categorisation, transportation, and temporary storage) of contaminated and activated components during decommissioning. 3D radiological simulation and visualisation technology provides a new more efficient way for explaining complex radiological conditions, work plans, and compliance with regulatory requirements. Advanced support systems based on 3D technologies have successfully been applied in the decommissioning of a number of nuclear installations (e.g. Fugen NPP, Chernobyl NPP, Leningrad NPP, Andreeva Bay branch of Northwest Center for Radioactive Waste Management in NW Russia) for increasing safety and optimising costs. For further details the reader is referred to the literature

GAOS: Spatial optimisation of crop and nature within agricultural fields

NARCIS (Netherlands)

Bruin, de S.; Janssen, H.; Klompe, A.; Lerink, P.; Vanmeulebrouk, B.

2010-01-01

This paper proposes and demonstrates a spatial optimiser that allocates areas of inefficient machine manoeuvring to field margins thus improving the use of available space and supporting map-based Controlled Traffic Farming. A prototype web service (GAOS) allows farmers to optimise tracks within

Lap time simulation and design optimisation of a brushed DC electric motorcycle for the Isle of Man TT Zero Challenge

Science.gov (United States)

Dal Bianco, N.; Lot, R.; Matthys, K.

2018-01-01

This works regards the design of an electric motorcycle for the annual Isle of Man TT Zero Challenge. Optimal control theory was used to perform lap time simulation and design optimisation. A bespoked model was developed, featuring 3D road topology, vehicle dynamics and electric power train, composed of a lithium battery pack, brushed DC motors and motor controller. The model runs simulations over the entire ? or ? of the Snaefell Mountain Course. The work is validated using experimental data from the BX chassis of the Brunel Racing team, which ran during the 2009 to 2015 TT Zero races. Optimal control is used to improve drive train and power train configurations. Findings demonstrate computational efficiency, good lap time prediction and design optimisation potential, achieving a 2 minutes reduction of the reference lap time through changes in final drive gear ratio, battery pack size and motor configuration.

Reduction environmental effects of civil aircraft through multi-objective flight plan optimisation

International Nuclear Information System (INIS)

Lee, D S; Gonzalez, L F; Walker, R; Periaux, J; Onate, E

2010-01-01

With rising environmental alarm, the reduction of critical aircraft emissions including carbon dioxides (CO 2 ) and nitrogen oxides (NO x ) is one of most important aeronautical problems. There can be many possible attempts to solve such problem by designing new wing/aircraft shape, new efficient engine, etc. The paper rather provides a set of acceptable flight plans as a first step besides replacing current aircrafts. The paper investigates a green aircraft design optimisation in terms of aircraft range, mission fuel weight (CO 2 ) and NO x using advanced Evolutionary Algorithms coupled to flight optimisation system software. Two multi-objective design optimisations are conducted to find the best set of flight plans for current aircrafts considering discretised altitude and Mach numbers without designing aircraft shape and engine types. The objectives of first optimisation are to maximise range of aircraft while minimising NO x with constant mission fuel weight. The second optimisation considers minimisation of mission fuel weight and NO x with fixed aircraft range. Numerical results show that the method is able to capture a set of useful trade-offs that reduce NO x and CO 2 (minimum mission fuel weight).

An energy efficient and high speed architecture for convolution computing based on binary resistive random access memory

Science.gov (United States)

Liu, Chen; Han, Runze; Zhou, Zheng; Huang, Peng; Liu, Lifeng; Liu, Xiaoyan; Kang, Jinfeng

2018-04-01

In this work we present a novel convolution computing architecture based on metal oxide resistive random access memory (RRAM) to process the image data stored in the RRAM arrays. The proposed image storage architecture shows performances of better speed-device consumption efficiency compared with the previous kernel storage architecture. Further we improve the architecture for a high accuracy and low power computing by utilizing the binary storage and the series resistor. For a 28 × 28 image and 10 kernels with a size of 3 × 3, compared with the previous kernel storage approach, the newly proposed architecture shows excellent performances including: 1) almost 100% accuracy within 20% LRS variation and 90% HRS variation; 2) more than 67 times speed boost; 3) 71.4% energy saving.

Optimisation: how to develop stake holder involvement

International Nuclear Information System (INIS)

Weiss, W.

2003-01-01

The Precautionary Principle is an internationally recognised approach for dealing with risk situations characterised by uncertainties and potential irreversible damages. Since the late fifties, ICRP has adopted this prudent attitude because of the lack of scientific evidence concerning the existence of a threshold at low doses for stochastic effects. The 'linear, no-threshold' model and the 'optimisation of protection' principle have been developed as a pragmatic response for the management of the risk. The progress in epidemiology and radiobiology over the last decades have affirmed the initial assumption and the optimisation remains the appropriate response for the application of the precautionary principle in the context of radiological protection. The basic objective of optimisation is, for any source within the system of radiological protection, to maintain the level of exposure as low as reasonably achievable, taking into account social and economical factors. Methods tools and procedures have been developed over the last two decades to put into practice the optimisation principle with a central role given to the cost-benefit analysis as a means to determine the optimised level of protection. However, with the advancement in the implementation of the principle more emphasis was progressively given to good practice, as well as on the importance of controlling individual levels of exposure through the optimisation process. In the context of the revision of its present recommendations, the Commission is reenforcing the emphasis on protection of the individual with the adoption of an equity-based system that recognizes individual rights and a basic level of health protection. Another advancement is the role that is now recognised to 'stakeholders involvement' in the optimisation process as a mean to improve the quality of the decision aiding process for identifying and selecting protection actions considered as being accepted by all those involved. The paper

Optimisation of Storage for Concentrated Solar Power Plants

Directory of Open Access Journals (Sweden)

Luigi Cirocco

2014-12-01

Full Text Available The proliferation of non-scheduled generation from renewable electrical energy sources such concentrated solar power (CSP presents a need for enabling scheduled generation by incorporating energy storage; either via directly coupled Thermal Energy Storage (TES or Electrical Storage Systems (ESS distributed within the electrical network or grid. The challenges for 100% renewable energy generation are: to minimise capitalisation cost and to maximise energy dispatch capacity. The aims of this review article are twofold: to review storage technologies and to survey the most appropriate optimisation techniques to determine optimal operation and size of storage of a system to operate in the Australian National Energy Market (NEM. Storage technologies are reviewed to establish indicative characterisations of energy density, conversion efficiency, charge/discharge rates and costings. A partitioning of optimisation techniques based on methods most appropriate for various time scales is performed: from “whole of year”, seasonal, monthly, weekly and daily averaging to those best suited matching the NEM bid timing of five minute dispatch bidding, averaged on the half hour as the trading settlement spot price. Finally, a selection of the most promising research directions and methods to determine the optimal operation and sizing of storage for renewables in the grid is presented.

Warpage optimisation on the moulded part with straight-drilled and conformal cooling channels using response surface methodology (RSM) and glowworm swarm optimisation (GSO)

Science.gov (United States)

Hazwan, M. H. M.; Shayfull, Z.; Sharif, S.; Nasir, S. M.; Zainal, N.

2017-09-01

In injection moulding process, quality and productivity are notably important and must be controlled for each product type produced. Quality is measured as the extent of warpage of moulded parts while productivity is measured as a duration of moulding cycle time. To control the quality, many researchers have introduced various of optimisation approaches which have been proven enhanced the quality of the moulded part produced. In order to improve the productivity of injection moulding process, some of researches have proposed the application of conformal cooling channels which have been proven reduced the duration of moulding cycle time. Therefore, this paper presents an application of alternative optimisation approach which is Response Surface Methodology (RSM) with Glowworm Swarm Optimisation (GSO) on the moulded part with straight-drilled and conformal cooling channels mould. This study examined the warpage condition of the moulded parts before and after optimisation work applied for both cooling channels. A front panel housing have been selected as a specimen and the performance of proposed optimisation approach have been analysed on the conventional straight-drilled cooling channels compared to the Milled Groove Square Shape (MGSS) conformal cooling channels by simulation analysis using Autodesk Moldflow Insight (AMI) 2013. Based on the results, melt temperature is the most significant factor contribute to the warpage condition and warpage have optimised by 39.1% after optimisation for straight-drilled cooling channels and cooling time is the most significant factor contribute to the warpage condition and warpage have optimised by 38.7% after optimisation for MGSS conformal cooling channels. In addition, the finding shows that the application of optimisation work on the conformal cooling channels offers the better quality and productivity of the moulded part produced.

Optimisation and symmetry in experimental radiation physics

International Nuclear Information System (INIS)

Ghose, A.

1988-01-01

The present monograph is concerned with the optimisation of geometric factors in radiation physics experiments. The discussions are essentially confined to those systems in which optimisation is equivalent to symmetrical configurations of the measurement systems. They include, measurements of interaction cross section of diverse types, determination of polarisations, development of detectors with almost ideal characteristics, production of radiations with continuously variable energies and development of high efficiency spectrometers etc. The monograph is intended for use by experimental physicists investigating primary interactions of radiations with matter and associated technologies. We have illustrated the various optimisation procedures by considering the cases of the so-called ''14 MeV'' on d-t neutrons and gamma rays with energies less than 3 MeV. Developments in fusion technology are critically dependent on the availability accurate cross sections of nuclei for fast neutrons of energies at least as high as d-t neutrons. In this monograph we have discussed various techniques which can be used to improve the accuracy of such measurements and have also presented a method for generating almost monoenergetic neutrons in the 8 MeV to 13 MeV energy range which can be used to measure cross sections in this sparingly investigated region

Analysis and optimisation of a mixed fluid cascade (MFC) process

Science.gov (United States)

Ding, He; Sun, Heng; Sun, Shoujun; Chen, Cheng

2017-04-01

A mixed fluid cascade (MFC) process that comprises three refrigeration cycles has great capacity for large-scale LNG production, which consumes a great amount of energy. Therefore, any performance enhancement of the liquefaction process will significantly reduce the energy consumption. The MFC process is simulated and analysed by use of proprietary software, Aspen HYSYS. The effect of feed gas pressure, LNG storage pressure, water-cooler outlet temperature, different pre-cooling regimes, liquefaction, and sub-cooling refrigerant composition on MFC performance are investigated and presented. The characteristics of its excellent numerical calculation ability and the user-friendly interface of MATLAB™ and powerful thermo-physical property package of Aspen HYSYS are combined. A genetic algorithm is then invoked to optimise the MFC process globally. After optimisation, the unit power consumption can be reduced to 4.655 kW h/kmol, or 4.366 kW h/kmol on condition that the compressor adiabatic efficiency is 80%, or 85%, respectively. Additionally, to improve the process further, with regards its thermodynamic efficiency, configuration optimisation is conducted for the MFC process and several configurations are established. By analysing heat transfer and thermodynamic performances, the configuration entailing a pre-cooling cycle with three pressure levels, liquefaction, and a sub-cooling cycle with one pressure level is identified as the most efficient and thus optimal: its unit power consumption is 4.205 kW h/kmol. Additionally, the mechanism responsible for the weak performance of the suggested liquefaction cycle configuration lies in the unbalanced distribution of cold energy in the liquefaction temperature range.

Optimisation of wire-cut EDM process parameter by Grey-based response surface methodology

Science.gov (United States)

Kumar, Amit; Soota, Tarun; Kumar, Jitendra

2018-03-01

Wire electric discharge machining (WEDM) is one of the advanced machining processes. Response surface methodology coupled with Grey relation analysis method has been proposed and used to optimise the machining parameters of WEDM. A face centred cubic design is used for conducting experiments on high speed steel (HSS) M2 grade workpiece material. The regression model of significant factors such as pulse-on time, pulse-off time, peak current, and wire feed is considered for optimising the responses variables material removal rate (MRR), surface roughness and Kerf width. The optimal condition of the machining parameter was obtained using the Grey relation grade. ANOVA is applied to determine significance of the input parameters for optimising the Grey relation grade.

A Mechatronic Solution for Efficiency Optimisation

DEFF Research Database (Denmark)

Conrad, Finn; Hansen, M.R.; Andersen, T.O.

2004-01-01

This paper presents and discusses concepts concerning regeneration of potential energy in hydraulic forklift trucks. A conventional forklift system has been investigated for energy efficiency and compared to an investigated for energy efficiency and compared to an investigated for energy efficien...

Hybrid coolers under part-load conditions - Optimisation of operating costs and energy consumption; Simulation und Berechnung von hybriden Trockenkuehlern imTeillastbereich - Optimierung von Betriebskosten und Energieverbrauch

Energy Technology Data Exchange (ETDEWEB)

Koenig, H.

2007-07-01

This comprehensive article takes a look at new European guidelines on the energy performance of buildings in which the total efficiency of the buildings or heat-transportation systems under partial loading is considered. On the basis of a real-life example, the author examines the influence of various components such as compressors, pumps and ventilators on energy consumption. Hybrid coolers are looked at and the characteristics of refrigeration machines with respect to varying outside temperature are discussed. Combined cooling for computer centres is examined and switchable, redundant combined systems are looked at. Optimisation of cooling systems for falling outside temperatures and the operation of cold-water systems are looked at. Simulation topics are discussed and optimisation with respect to costs and energy consumption are examined.

A Computational Framework for Efficient Low Temperature Plasma Simulations

Science.gov (United States)

Verma, Abhishek Kumar; Venkattraman, Ayyaswamy

2016-10-01

Over the past years, scientific computing has emerged as an essential tool for the investigation and prediction of low temperature plasmas (LTP) applications which includes electronics, nanomaterial synthesis, metamaterials etc. To further explore the LTP behavior with greater fidelity, we present a computational toolbox developed to perform LTP simulations. This framework will allow us to enhance our understanding of multiscale plasma phenomenon using high performance computing tools mainly based on OpenFOAM FVM distribution. Although aimed at microplasma simulations, the modular framework is able to perform multiscale, multiphysics simulations of physical systems comprises of LTP. Some salient introductory features are capability to perform parallel, 3D simulations of LTP applications on unstructured meshes. Performance of the solver is tested based on numerical results assessing accuracy and efficiency of benchmarks for problems in microdischarge devices. Numerical simulation of microplasma reactor at atmospheric pressure with hemispherical dielectric coated electrodes will be discussed and hence, provide an overview of applicability and future scope of this framework.

Optimised operation of an off-grid hybrid wind-diesel-battery system using genetic algorithm

International Nuclear Information System (INIS)

Gan, Leong Kit; Shek, Jonathan K.H.; Mueller, Markus A.

2016-01-01

Highlights: • Diesel generator’s operation is optimised in a hybrid wind-diesel-battery system. • Optimisation is performed using wind speed and load demand forecasts. • The objective is to maximise wind energy utilisation with limited battery storage. • Physical modelling approach (Simscape) is used to verify mathematical model. • Sensitivity analyses are performed with synthesised wind and load forecast errors. - Abstract: In an off-grid hybrid wind-diesel-battery system, the diesel generator is often not utilised efficiently, therefore compromising its lifetime. In particular, the general rule of thumb of running the diesel generator at more than 40% of its rated capacity is often unmet. This is due to the variation in power demand and wind speed which needs to be supplied by the diesel generator. In addition, the frequent start-stop of the diesel generator leads to additional mechanical wear and fuel wastage. This research paper proposes a novel control algorithm which optimises the operation of a diesel generator, using genetic algorithm. With a given day-ahead forecast of local renewable energy resource and load demand, it is possible to optimise the operation of a diesel generator, subjected to other pre-defined constraints. Thus, the utilisation of the renewable energy sources to supply electricity can be maximised. Usually, the optimisation studies of a hybrid system are being conducted through simple analytical modelling, coupled with a selected optimisation algorithm to seek the optimised solution. The obtained solution is not verified using a more realistic system model, for instance the physical modelling approach. This often led to the question of the applicability of such optimised operation being used in reality. In order to take a step further, model-based design using Simulink is employed in this research to perform a comparison through a physical modelling approach. The Simulink model has the capability to incorporate the electrical

Efficient computation of Laguerre polynomials

NARCIS (Netherlands)

A. Gil (Amparo); J. Segura (Javier); N.M. Temme (Nico)

2017-01-01

textabstractAn efficient algorithm and a Fortran 90 module (LaguerrePol) for computing Laguerre polynomials . Ln(α)(z) are presented. The standard three-term recurrence relation satisfied by the polynomials and different types of asymptotic expansions valid for . n large and . α small, are used

An optimised portfolio management model, incorporating best practices

OpenAIRE

2015-01-01

M.Ing. (Engineering Management) Driving sustainability, optimising return on investments and cultivating a competitive market advantage, are imperative for organisational success and growth. In order to achieve the business objectives and value proposition, effective management strategies must be efficiently implemented, monitored and controlled. Failure to do so ultimately result in; financial loss due to increased capital and operational expenditure, schedule slippages, substandard deliv...

Optimisation and assessment of three modern touch screen tablet computers for clinical vision testing.

Directory of Open Access Journals (Sweden)

Humza J Tahir

Full Text Available Technological advances have led to the development of powerful yet portable tablet computers whose touch-screen resolutions now permit the presentation of targets small enough to test the limits of normal visual acuity. Such devices have become ubiquitous in daily life and are moving into the clinical space. However, in order to produce clinically valid tests, it is important to identify the limits imposed by the screen characteristics, such as resolution, brightness uniformity, contrast linearity and the effect of viewing angle. Previously we have conducted such tests on the iPad 3. Here we extend our investigations to 2 other devices and outline a protocol for calibrating such screens, using standardised methods to measure the gamma function, warm up time, screen uniformity and the effects of viewing angle and screen reflections. We demonstrate that all three devices manifest typical gamma functions for voltage and luminance with warm up times of approximately 15 minutes. However, there were differences in homogeneity and reflectance among the displays. We suggest practical means to optimise quality of display for vision testing including screen calibration.

Optimisation and assessment of three modern touch screen tablet computers for clinical vision testing.

Science.gov (United States)

Tahir, Humza J; Murray, Ian J; Parry, Neil R A; Aslam, Tariq M

2014-01-01

Technological advances have led to the development of powerful yet portable tablet computers whose touch-screen resolutions now permit the presentation of targets small enough to test the limits of normal visual acuity. Such devices have become ubiquitous in daily life and are moving into the clinical space. However, in order to produce clinically valid tests, it is important to identify the limits imposed by the screen characteristics, such as resolution, brightness uniformity, contrast linearity and the effect of viewing angle. Previously we have conducted such tests on the iPad 3. Here we extend our investigations to 2 other devices and outline a protocol for calibrating such screens, using standardised methods to measure the gamma function, warm up time, screen uniformity and the effects of viewing angle and screen reflections. We demonstrate that all three devices manifest typical gamma functions for voltage and luminance with warm up times of approximately 15 minutes. However, there were differences in homogeneity and reflectance among the displays. We suggest practical means to optimise quality of display for vision testing including screen calibration.

CREATIV: Research-based innovation for industry energy efficiency

International Nuclear Information System (INIS)

Tangen, Grethe; Hemmingsen, Anne Karin T.; Neksa, Petter

2011-01-01

Improved energy efficiency is imperative to minimise the greenhouse gas emissions and to ensure future energy security. It is also a key to continued profitability in energy consuming industry. The project CREATIV is a research initiative for industry energy efficiency focusing on utilisation of surplus heat and efficient heating and cooling. In CREATIV, international research groups work together with key vendors of energy efficiency equipment and an industry consortium including the areas metallurgy, pulp and paper, food and fishery, and commercial refrigeration supermarkets. The ambition of CREATIV is to bring forward technology and solutions enabling Norway to reduce both energy consumption and greenhouse gas emissions by 25% within 2020. The main research topics are electricity production from low temperature heat sources in supercritical CO 2 cycles, energy efficient end-user technology for heating and cooling based on natural working fluids and system optimisation, and efficient utilisation of low temperature heat by developing new sorption systems and compact compressor-expander units. A defined innovation strategy in the project will ensure exploitation of research results and promote implementation in industry processes. CREATIV will contribute to the recruitment of competent personnel to industry and academia by educating PhD and post doc candidates and several MSc students. The paper presents the CREATIV project, discusses its scientific achievements so far, and outlines how the project results can contribute to reducing industry energy consumption. - Highlights: → New technology for improved energy efficiency relevant across several industries. → Surplus heat exploitation and efficient heating and cooling are important means. → Focus on power production from low temperature heat and heat pumping technologies. → Education and competence building are given priority. → The project consortium includes 20 international industry companies and

Energy Savings from Optimised In-Field Route Planning for Agricultural Machinery

Directory of Open Access Journals (Sweden)

Efthymios Rodias

2017-10-01

Full Text Available Various types of sensors technologies, such as machine vision and global positioning system (GPS have been implemented in navigation of agricultural vehicles. Automated navigation systems have proved the potential for the execution of optimised route plans for field area coverage. This paper presents an assessment of the reduction of the energy requirements derived from the implementation of optimised field area coverage planning. The assessment regards the analysis of the energy requirements and the comparison between the non-optimised and optimised plans for field area coverage in the whole sequence of operations required in two different cropping systems: Miscanthus and Switchgrass production. An algorithmic approach for the simulation of the executed field operations by following both non-optimised and optimised field-work patterns was developed. As a result, the corresponding time requirements were estimated as the basis of the subsequent energy cost analysis. Based on the results, the optimised routes reduce the fuel energy consumption up to 8%, the embodied energy consumption up to 7%, and the total energy consumption from 3% up to 8%.

Plant-wide dynamic and static optimisation of supermarket refrigeration systems

DEFF Research Database (Denmark)

Green, Torben; Izadi-Zamanabadi, Roozbeh; Razavi-Far, Roozbeh

2013-01-01

Optimising the operation of a supermarket refrigeration system under dynamic as well as steadystate conditions is addressedin thispaper. For thispurpose anappropriateperformance function that encompasses food quality, system efficiency, and also component reliability is established. The choice...... in the system. Simulation results is used to substantiate the suggestedmethodology....

Optimised low-dose multidetector CT protocol for children with cranial deformity

Energy Technology Data Exchange (ETDEWEB)

Vazquez, Jose Luis [Complejo Hospitalario Universitario de Vigo, Department of Radiology, Vigo, Pontevedra (Spain); Pombar, Miguel Angel [Complejo Hospitalario Universitario de Santiago, Department of Radiophysics, Santiago de Compostela, La Coruna (Spain); Pumar, Jose Manuel [Complejo Hospitalario Universitario de Santiago, Department of Radiology, Santiago de Compostela, La Coruna (Spain); Campo, Victor Miguel del [Complejo Hospitalario Universitario de Vigo, Department of Public Health, Vigo, Pontevedra (Spain)

2013-08-15

To present an optimised low-dose multidetector computed tomography (MDCT) protocol for the study of children with cranial deformity. Ninety-one consecutive MDCT studies were performed in 80 children. Studies were performed with either our standard head CT protocol (group 1, n = 20) or a low-dose cranial deformity protocol (groups 2 and 3). Group 2 (n = 38), initial, and group 3 (n = 33), final and more optimised. All studies were performed in the same 64-MDCT equipment. Cranial deformity protocol was gradationally optimised decreasing kVp, limiting mA range, using automatic exposure control (AEC) and increasing the noise index (NI). Image quality was assessed. Dose indicators such us CT dose index volume (CTDIvol), dose-length product (DLP) and effective dose (E) were used. The optimised low-dose protocol reached the following values: 80 kVp, mA range: 50-150 and NI = 23. We achieved a maximum dose reduction of 10-22 times in the 1- to 12-month-old cranium in regard to the 2004 European guidelines for MDCT. A low-dose MDCT protocol that may be used as the first diagnostic imaging option in clinically selected patients with skull abnormalities. (orig.)

When weather forecasts control the heating. Operational optimisation of administrative buildings with weather forecast control; Wenn Wetterprognosen die Heizung steuern. Betriebsoptimierung von Verwaltungsgebaeuden mit Wettervorhersage-Steuerung

Energy Technology Data Exchange (ETDEWEB)

Friedrich, Uwe

2011-07-01

With the aim of achieving an optimum indoor environment and lowering operating costs in the long term, the performance of a so-called ''operational optimisation with weather forecast control'' system has been tested in three administrative buildings in the German state of North Rhine-Westphalia since 2007. The operation of the heating systems is optimised based on a thermodynamic computer model and local weather forecast data. The result: A tangible increase in comfort with simultaneous heat energy savings. (orig.)

Computational Intelligence and Wavelet Transform Based Metamodel for Efficient Generation of Not-Yet Simulated Waveforms

Science.gov (United States)

Oltean, Gabriel; Ivanciu, Laura-Nicoleta

2016-01-01

The design and verification of complex electronic systems, especially the analog and mixed-signal ones, prove to be extremely time consuming tasks, if only circuit-level simulations are involved. A significant amount of time can be saved if a cost effective solution is used for the extensive analysis of the system, under all conceivable conditions. This paper proposes a data-driven method to build fast to evaluate, but also accurate metamodels capable of generating not-yet simulated waveforms as a function of different combinations of the parameters of the system. The necessary data are obtained by early-stage simulation of an electronic control system from the automotive industry. The metamodel development is based on three key elements: a wavelet transform for waveform characterization, a genetic algorithm optimization to detect the optimal wavelet transform and to identify the most relevant decomposition coefficients, and an artificial neuronal network to derive the relevant coefficients of the wavelet transform for any new parameters combination. The resulted metamodels for three different waveform families are fully reliable. They satisfy the required key points: high accuracy (a maximum mean squared error of 7.1x10-5 for the unity-based normalized waveforms), efficiency (fully affordable computational effort for metamodel build-up: maximum 18 minutes on a general purpose computer), and simplicity (less than 1 second for running the metamodel, the user only provides the parameters combination). The metamodels can be used for very efficient generation of new waveforms, for any possible combination of dependent parameters, offering the possibility to explore the entire design space. A wide range of possibilities becomes achievable for the user, such as: all design corners can be analyzed, possible worst-case situations can be investigated, extreme values of waveforms can be discovered, sensitivity analyses can be performed (the influence of each parameter on the

Computational Intelligence and Wavelet Transform Based Metamodel for Efficient Generation of Not-Yet Simulated Waveforms.

Directory of Open Access Journals (Sweden)

Gabriel Oltean

Full Text Available The design and verification of complex electronic systems, especially the analog and mixed-signal ones, prove to be extremely time consuming tasks, if only circuit-level simulations are involved. A significant amount of time can be saved if a cost effective solution is used for the extensive analysis of the system, under all conceivable conditions. This paper proposes a data-driven method to build fast to evaluate, but also accurate metamodels capable of generating not-yet simulated waveforms as a function of different combinations of the parameters of the system. The necessary data are obtained by early-stage simulation of an electronic control system from the automotive industry. The metamodel development is based on three key elements: a wavelet transform for waveform characterization, a genetic algorithm optimization to detect the optimal wavelet transform and to identify the most relevant decomposition coefficients, and an artificial neuronal network to derive the relevant coefficients of the wavelet transform for any new parameters combination. The resulted metamodels for three different waveform families are fully reliable. They satisfy the required key points: high accuracy (a maximum mean squared error of 7.1x10-5 for the unity-based normalized waveforms, efficiency (fully affordable computational effort for metamodel build-up: maximum 18 minutes on a general purpose computer, and simplicity (less than 1 second for running the metamodel, the user only provides the parameters combination. The metamodels can be used for very efficient generation of new waveforms, for any possible combination of dependent parameters, offering the possibility to explore the entire design space. A wide range of possibilities becomes achievable for the user, such as: all design corners can be analyzed, possible worst-case situations can be investigated, extreme values of waveforms can be discovered, sensitivity analyses can be performed (the influence of each

Computational Intelligence and Wavelet Transform Based Metamodel for Efficient Generation of Not-Yet Simulated Waveforms.

Science.gov (United States)

Oltean, Gabriel; Ivanciu, Laura-Nicoleta

2016-01-01

The design and verification of complex electronic systems, especially the analog and mixed-signal ones, prove to be extremely time consuming tasks, if only circuit-level simulations are involved. A significant amount of time can be saved if a cost effective solution is used for the extensive analysis of the system, under all conceivable conditions. This paper proposes a data-driven method to build fast to evaluate, but also accurate metamodels capable of generating not-yet simulated waveforms as a function of different combinations of the parameters of the system. The necessary data are obtained by early-stage simulation of an electronic control system from the automotive industry. The metamodel development is based on three key elements: a wavelet transform for waveform characterization, a genetic algorithm optimization to detect the optimal wavelet transform and to identify the most relevant decomposition coefficients, and an artificial neuronal network to derive the relevant coefficients of the wavelet transform for any new parameters combination. The resulted metamodels for three different waveform families are fully reliable. They satisfy the required key points: high accuracy (a maximum mean squared error of 7.1x10-5 for the unity-based normalized waveforms), efficiency (fully affordable computational effort for metamodel build-up: maximum 18 minutes on a general purpose computer), and simplicity (less than 1 second for running the metamodel, the user only provides the parameters combination). The metamodels can be used for very efficient generation of new waveforms, for any possible combination of dependent parameters, offering the possibility to explore the entire design space. A wide range of possibilities becomes achievable for the user, such as: all design corners can be analyzed, possible worst-case situations can be investigated, extreme values of waveforms can be discovered, sensitivity analyses can be performed (the influence of each parameter on the

Design optimisation of a flywheel hybrid vehicle

Energy Technology Data Exchange (ETDEWEB)

Kok, D.B.

1999-11-04

during the engine start-up and shutdown periods. Correct throttle valve control ensures that hydrocarbon emissions are not critical for legislative emission limits, but the engine's standard lambda control cannot prevent an increase of nitric oxides. In order to improve tailpipe emissions, the thermo-chemical behaviour of the catalytic converter is investigated and adapted for hybrid vehicle application. In cold-start situations, the fuel consumption and exhaust gas emissions of a mechanical driveline with internal combustion engine increase. A detailed numerical investigation of the thermal behaviour of the hybrid driveline showed that the energy-efficient operation of the engine decreases thermal waste energy that is available to warm up driveline components. Therefore, a redesign of the cooling circuitry and thermal management of the driveline was required to improve system warm-up. A computer model has been developed that combines the functional description of the flywheel hybrid vehicle with the calculation of energy losses. Apart from standardised European drive cycles, velocity profiles that represent more realistic vehicle utilisation are used to assess and optimise the hybrid vehicle's fuel economy, exhaust gas emission and acceleration performance. Subdivision of energy consumption enabled the classification of those systems and components that have a major effect on fuel consumption. Of these, the optimised flywheel system, the hydraulic system, and the transmission consume energy of comparable magnitude in city driving. It is shown that the system's fuel economy is mainly a result of the improved engine operation. Regenerative braking has only limited effect on vehicle fuel consumption. Experiments with an early prototype of the hybrid driveline yielded no gains in fuel consumption when compared to a conventional CVT reference vehicle due to high storage losses in the flywheel system. However, the improved prototype of the flywheel hybrid

Perspective: Memcomputing: Leveraging memory and physics to compute efficiently

Science.gov (United States)

Di Ventra, Massimiliano; Traversa, Fabio L.

2018-05-01

It is well known that physical phenomena may be of great help in computing some difficult problems efficiently. A typical example is prime factorization that may be solved in polynomial time by exploiting quantum entanglement on a quantum computer. There are, however, other types of (non-quantum) physical properties that one may leverage to compute efficiently a wide range of hard problems. In this perspective, we discuss how to employ one such property, memory (time non-locality), in a novel physics-based approach to computation: Memcomputing. In particular, we focus on digital memcomputing machines (DMMs) that are scalable. DMMs can be realized with non-linear dynamical systems with memory. The latter property allows the realization of a new type of Boolean logic, one that is self-organizing. Self-organizing logic gates are "terminal-agnostic," namely, they do not distinguish between the input and output terminals. When appropriately assembled to represent a given combinatorial/optimization problem, the corresponding self-organizing circuit converges to the equilibrium points that express the solutions of the problem at hand. In doing so, DMMs take advantage of the long-range order that develops during the transient dynamics. This collective dynamical behavior, reminiscent of a phase transition, or even the "edge of chaos," is mediated by families of classical trajectories (instantons) that connect critical points of increasing stability in the system's phase space. The topological character of the solution search renders DMMs robust against noise and structural disorder. Since DMMs are non-quantum systems described by ordinary differential equations, not only can they be built in hardware with the available technology, they can also be simulated efficiently on modern classical computers. As an example, we will show the polynomial-time solution of the subset-sum problem for the worst cases, and point to other types of hard problems where simulations of DMMs

A new computationally-efficient two-dimensional model for boron implantation into single-crystal silicon

International Nuclear Information System (INIS)

Klein, K.M.; Park, C.; Yang, S.; Morris, S.; Do, V.; Tasch, F.

1992-01-01

We have developed a new computationally-efficient two-dimensional model for boron implantation into single-crystal silicon. This paper reports that this new model is based on the dual Pearson semi-empirical implant depth profile model and the UT-MARLOWE Monte Carlo boron ion implantation model. This new model can predict with very high computational efficiency two-dimensional as-implanted boron profiles as a function of energy, dose, tilt angle, rotation angle, masking edge orientation, and masking edge thickness

Efficient computation of clipped Voronoi diagram for mesh generation

KAUST Repository

Yan, Dongming

2013-04-01

The Voronoi diagram is a fundamental geometric structure widely used in various fields, especially in computer graphics and geometry computing. For a set of points in a compact domain (i.e. a bounded and closed 2D region or a 3D volume), some Voronoi cells of their Voronoi diagram are infinite or partially outside of the domain, but in practice only the parts of the cells inside the domain are needed, as when computing the centroidal Voronoi tessellation. Such a Voronoi diagram confined to a compact domain is called a clipped Voronoi diagram. We present an efficient algorithm to compute the clipped Voronoi diagram for a set of sites with respect to a compact 2D region or a 3D volume. We also apply the proposed method to optimal mesh generation based on the centroidal Voronoi tessellation. Crown Copyright © 2011 Published by Elsevier Ltd. All rights reserved.

Efficient computation of clipped Voronoi diagram for mesh generation

KAUST Repository

Yan, Dongming; Wang, Wen Ping; Lé vy, Bruno L.; Liu, Yang

2013-01-01

The Voronoi diagram is a fundamental geometric structure widely used in various fields, especially in computer graphics and geometry computing. For a set of points in a compact domain (i.e. a bounded and closed 2D region or a 3D volume), some Voronoi cells of their Voronoi diagram are infinite or partially outside of the domain, but in practice only the parts of the cells inside the domain are needed, as when computing the centroidal Voronoi tessellation. Such a Voronoi diagram confined to a compact domain is called a clipped Voronoi diagram. We present an efficient algorithm to compute the clipped Voronoi diagram for a set of sites with respect to a compact 2D region or a 3D volume. We also apply the proposed method to optimal mesh generation based on the centroidal Voronoi tessellation. Crown Copyright © 2011 Published by Elsevier Ltd. All rights reserved.

A reliability-based maintenance technicians' workloads optimisation model with stochastic consideration

Science.gov (United States)

Ighravwe, D. E.; Oke, S. A.; Adebiyi, K. A.

2016-06-01

The growing interest in technicians' workloads research is probably associated with the recent surge in competition. This was prompted by unprecedented technological development that triggers changes in customer tastes and preferences for industrial goods. In a quest for business improvement, this worldwide intense competition in industries has stimulated theories and practical frameworks that seek to optimise performance in workplaces. In line with this drive, the present paper proposes an optimisation model which considers technicians' reliability that complements factory information obtained. The information used emerged from technicians' productivity and earned-values using the concept of multi-objective modelling approach. Since technicians are expected to carry out routine and stochastic maintenance work, we consider these workloads as constraints. The influence of training, fatigue and experiential knowledge of technicians on workload management was considered. These workloads were combined with maintenance policy in optimising reliability, productivity and earned-values using the goal programming approach. Practical datasets were utilised in studying the applicability of the proposed model in practice. It was observed that our model was able to generate information that practicing maintenance engineers can apply in making more informed decisions on technicians' management.

Thermal performance monitoring and optimisation

International Nuclear Information System (INIS)

Sunde, Svein; Berg; Oeyvind

1998-01-01

Monitoring of the thermal efficiency of nuclear power plants is expected to become increasingly important as energy-market liberalisation exposes plants to increasing availability requirements and fiercer competition. The general goal in thermal performance monitoring is straightforward: to maximise the ratio of profit to cost under the constraints of safe operation. One may perceive this goal to be pursued in two ways, one oriented towards fault detection and cost-optimal predictive maintenance, and another determined at optimising target values of parameters in response to any component degradation detected, changes in ambient conditions, or the like. Annual savings associated with effective thermal-performance monitoring are expected to be in the order of $ 100 000 for power plants of representative size. A literature review shows that a number of computer systems for thermal-performance monitoring exists, either as prototypes or commercially available. The characteristics and needs of power plants may vary widely, however, and decisions concerning the exact scope, content and configuration of a thermal-performance monitor may well follow a heuristic approach. Furthermore, re-use of existing software modules may be desirable. Therefore, we suggest here the design of a flexible workbench for easy assembly of an experimental thermal-performance monitor at the Halden Project. The suggested design draws heavily on our extended experience in implementing control-room systems featured by assets like high levels of customisation, flexibility in configuration and modularity in structure, and on a number of relevant adjoining activities. The design includes a multi-computer communication system and a graphical user's interface, and aims at a system adaptable to any combination of in-house or end user's modules, as well as commercially available software. (author)

Development of the hard and soft constraints based optimisation model for unit sizing of the hybrid renewable energy system designed for microgrid applications

Science.gov (United States)

Sundaramoorthy, Kumaravel

2017-02-01

The hybrid energy systems (HESs) based electricity generation system has become a more attractive solution for rural electrification nowadays. Economically feasible and technically reliable HESs are solidly based on an optimisation stage. This article discusses about the optimal unit sizing model with the objective function to minimise the total cost of the HES. Three typical rural sites from southern part of India have been selected for the application of the developed optimisation methodology. Feasibility studies and sensitivity analysis on the optimal HES are discussed elaborately in this article. A comparison has been carried out with the Hybrid Optimization Model for Electric Renewable optimisation model for three sites. The optimal HES is found with less total net present rate and rate of energy compared with the existing method

An approach to the efficient assessment of safety and usability of computer based control systems, VeNuS 2. Global final report

International Nuclear Information System (INIS)

Nelke, T.; Dlugosch, C.; Olaverri Monreal, C.; Sachse, K.; Thuering, M.

2015-01-01

Prior to the use of computer-based instrumentation and control the evidence of sufficient safety, development methods and the suitability of man-machine interface must be provided. For this purpose, validation methods must be available, if possible supported by appropriate tools. Based on the multitude of the data which has to be taken into account it is important to generate technical documentation, to realize efficient operation and to prevent human based errors. An approach for computer based generation of user manuals for the operation of technical systems was developed in the VeNuS 2 project. A second goal was to develop an approach to evaluate the usability of safety relevant digital human-machine-interfaces (e.g. for nuclear industries). Therefore a software tool has been developed to assess aspects of usability of user interfaces by considering safety-related priorities. Additionally new or well known methods for provision of evidence of sufficient safety and usability for computer based systems shall be developed in a prototyped way.

Formulation and optimisation of raft-forming chewable tablets containing H2 antagonist.

Science.gov (United States)

Prajapati, Shailesh T; Mehta, Anant P; Modhia, Ishan P; Patel, Chhagan N

2012-10-01

The purpose of this research work was to formulate raft-forming chewable tablets of H2 antagonist (Famotidine) using a raft-forming agent along with an antacid- and gas-generating agent. Tablets were prepared by wet granulation and evaluated for raft strength, acid neutralisation capacity, weight variation, % drug content, thickness, hardness, friability and in vitro drug release. Various raft-forming agents were used in preliminary screening. A 2(3) full-factorial design was used in the present study for optimisation. The amount of sodium alginate, amount of calcium carbonate and amount sodium bicarbonate were selected as independent variables. Raft strength, acid neutralisation capacity and drug release at 30 min were selected as responses. Tablets containing sodium alginate were having maximum raft strength as compared with other raft-forming agents. Acid neutralisation capacity and in vitro drug release of all factorial batches were found to be satisfactory. The F5 batch was optimised based on maximum raft strength and good acid neutralisation capacity. Drug-excipient compatibility study showed no interaction between the drug and excipients. Stability study of the optimised formulation showed that the tablets were stable at accelerated environmental conditions. It was concluded that raft-forming chewable tablets prepared using an optimum amount of sodium alginate, calcium carbonate and sodium bicarbonate could be an efficient dosage form in the treatment of gastro oesophageal reflux disease.

Transitions in the computational power of thermal states for measurement-based quantum computation

International Nuclear Information System (INIS)

Barrett, Sean D.; Bartlett, Stephen D.; Jennings, David; Doherty, Andrew C.; Rudolph, Terry

2009-01-01

We show that the usefulness of the thermal state of a specific spin-lattice model for measurement-based quantum computing exhibits a transition between two distinct 'phases' - one in which every state is a universal resource for quantum computation, and another in which any local measurement sequence can be simulated efficiently on a classical computer. Remarkably, this transition in computational power does not coincide with any phase transition, classical, or quantum in the underlying spin-lattice model.

Energy efficient maintenance. Project report; Energioptimerende vedligehold. Projektrapport

Energy Technology Data Exchange (ETDEWEB)

Bjerg, J. (Center for Drift og Vedligehold, Frederici (Denmark)); Dam Wied, M.; Skjershede Nielsen, P.; Holt, J. (NRGi Raadgivning A/S, Aarhus (Denmark)); Dam, M. (Energi Horsens, Horsens (Denmark)); Holk Lauridsen, V. (Teknologisk Institut, Energieffektivisering og Ventilation, Taastrup (Denmark))

2010-03-15

Together with four case companies, the project developed and tested a model for energy-efficient maintenance. In each of the companies, the model was adjusted through a cooperation process aiming at combining energy optimisation and maintenance as part of specific production optimisation. When correctly planned, energy-efficient maintenance is interesting for all companies. An overall solution was made, which can facilitate major energy savings and production efficiency improvement. (LN)

Efficient scatter model for simulation of ultrasound images from computed tomography data

Science.gov (United States)

D'Amato, J. P.; Lo Vercio, L.; Rubi, P.; Fernandez Vera, E.; Barbuzza, R.; Del Fresno, M.; Larrabide, I.

2015-12-01

Background and motivation: Real-time ultrasound simulation refers to the process of computationally creating fully synthetic ultrasound images instantly. Due to the high value of specialized low cost training for healthcare professionals, there is a growing interest in the use of this technology and the development of high fidelity systems that simulate the acquisitions of echographic images. The objective is to create an efficient and reproducible simulator that can run either on notebooks or desktops using low cost devices. Materials and methods: We present an interactive ultrasound simulator based on CT data. This simulator is based on ray-casting and provides real-time interaction capabilities. The simulation of scattering that is coherent with the transducer position in real time is also introduced. Such noise is produced using a simplified model of multiplicative noise and convolution with point spread functions (PSF) tailored for this purpose. Results: The computational efficiency of scattering maps generation was revised with an improved performance. This allowed a more efficient simulation of coherent scattering in the synthetic echographic images while providing highly realistic result. We describe some quality and performance metrics to validate these results, where a performance of up to 55fps was achieved. Conclusion: The proposed technique for real-time scattering modeling provides realistic yet computationally efficient scatter distributions. The error between the original image and the simulated scattering image was compared for the proposed method and the state-of-the-art, showing negligible differences in its distribution.

Topology Optimisation of Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Thike Aye Min

2016-01-01

Full Text Available Wireless sensor networks are widely used in a variety of fields including industrial environments. In case of a clustered network the location of cluster head affects the reliability of the network operation. Finding of the optimum location of the cluster head, therefore, is critical for the design of a network. This paper discusses the optimisation approach, based on the brute force algorithm, in the context of topology optimisation of a cluster structure centralised wireless sensor network. Two examples are given to verify the approach that demonstrate the implementation of the brute force algorithm to find an optimum location of the cluster head.

Optimal Optimisation in Chemometrics

NARCIS (Netherlands)

Hageman, J.A.

2004-01-01

The use of global optimisation methods is not straightforward, especially for the more difficult optimisation problems. Solutions have to be found for items such as the evaluation function, representation, step function and meta-parameters, before any useful results can be obtained. This thesis aims

Study on Parallel Processing for Efficient Flexible Multibody Analysis based on Subsystem Synthesis Method

Energy Technology Data Exchange (ETDEWEB)

Han, Jong-Boo; Song, Hajun; Kim, Sung-Soo [Chungnam Nat’l Univ., Daejeon (Korea, Republic of)

2017-06-15

Flexible multibody simulations are widely used in the industry to design mechanical systems. In flexible multibody dynamics, deformation coordinates are described either relatively in the body reference frame that is floating in the space or in the inertial reference frame. Moreover, these deformation coordinates are generated based on the discretization of the body according to the finite element approach. Therefore, the formulation of the flexible multibody system always deals with a huge number of degrees of freedom and the numerical solution methods require a substantial amount of computational time. Parallel computational methods are a solution for efficient computation. However, most of the parallel computational methods are focused on the efficient solution of large-sized linear equations. For multibody analysis, we need to develop an efficient formulation that could be suitable for parallel computation. In this paper, we developed a subsystem synthesis method for a flexible multibody system and proposed efficient parallel computational schemes based on the OpenMP API in order to achieve efficient computation. Simulations of a rotating blade system, which consists of three identical blades, were carried out with two different parallel computational schemes. Actual CPU times were measured to investigate the efficiency of the proposed parallel schemes.

A flexible, extendable, modular and computationally efficient approach to scattering-integral-based seismic full waveform inversion

Science.gov (United States)

Schumacher, F.; Friederich, W.; Lamara, S.

2016-02-01

We present a new conceptual approach to scattering-integral-based seismic full waveform inversion (FWI) that allows a flexible, extendable, modular and both computationally and storage-efficient numerical implementation. To achieve maximum modularity and extendability, interactions between the three fundamental steps carried out sequentially in each iteration of the inversion procedure, namely, solving the forward problem, computing waveform sensitivity kernels and deriving a model update, are kept at an absolute minimum and are implemented by dedicated interfaces. To realize storage efficiency and maximum flexibility, the spatial discretization of the inverted earth model is allowed to be completely independent of the spatial discretization employed by the forward solver. For computational efficiency reasons, the inversion is done in the frequency domain. The benefits of our approach are as follows: (1) Each of the three stages of an iteration is realized by a stand-alone software program. In this way, we avoid the monolithic, unflexible and hard-to-modify codes that have often been written for solving inverse problems. (2) The solution of the forward problem, required for kernel computation, can be obtained by any wave propagation modelling code giving users maximum flexibility in choosing the forward modelling method. Both time-domain and frequency-domain approaches can be used. (3) Forward solvers typically demand spatial discretizations that are significantly denser than actually desired for the inverted model. Exploiting this fact by pre-integrating the kernels allows a dramatic reduction of disk space and makes kernel storage feasible. No assumptions are made on the spatial discretization scheme employed by the forward solver. (4) In addition, working in the frequency domain effectively reduces the amount of data, the number of kernels to be computed and the number of equations to be solved. (5) Updating the model by solving a large equation system can be

Property-Based Anonymous Attestation in Trusted Cloud Computing

Directory of Open Access Journals (Sweden)

Zhen-Hu Ning

2014-01-01

Full Text Available In the remote attestation on Trusted Computer (TC computing mode TCCP, the trusted computer TC has an excessive burden, and anonymity and platform configuration information security of computing nodes cannot be guaranteed. To overcome these defects, based on the research on and analysis of current schemes, we propose an anonymous proof protocol based on property certificate. The platform configuration information is converted by the matrix algorithm into the property certificate, and the remote attestation is implemented by trusted ring signature scheme based on Strong RSA Assumption. By the trusted ring signature scheme based on property certificate, we achieve the anonymity of computing nodes and prevent the leakage of platform configuration information. By simulation, we obtain the computational efficiency of the scheme. We also expand the protocol and obtain the anonymous attestation based on ECC. By scenario comparison, we obtain the trusted ring signature scheme based on RSA, which has advantages with the growth of the ring numbers.

Using Field Data for Energy Efficiency Based on Maintenance and Operational Optimisation. A Step towards PHM in Process Plants

Directory of Open Access Journals (Sweden)

Micaela Demichela

2018-03-01

Full Text Available Energy saving is an important issue for any industrial sector; in particular, for the process industry, it can help to minimize both energy costs and environmental impact. Maintenance optimization and operational procedures can offer margins to increase energy efficiency in process plants, even if they are seldom explicitly taken into account in the predictive models guiding the energy saving policies. To ensure that the plant achieves the desired performance, maintenance operations and maintenance results should be monitored, and the connection between the inputs and the outcomes of the maintenance process, in terms of total contribution to manufacturing performance, should be explicit. In this study, a model for the energy efficiency analysis was developed, based on cost and benefits balance. It is aimed at supporting the decision making in terms of technical and operational solutions for energy efficiency, through the optimization of maintenance interventions and operational procedures. A case study is here described: the effects on energy efficiency of technical and operational optimization measures for bituminous materials production process equipment. The idea of the Conservation Supply Curve (CSC was used to capture both the cost effectiveness of the measures and the energy efficiency effectiveness. The optimization was thus based on the energy consumption data registered on-site: data collection and modelling of the relevant data were used as a base to implement a prognostic and health management (PHM policy in the company. Based on the results from the analysis, efficiency measures for the industrial case study were proposed, also in relation to maintenance optimization and operating procedures. In the end, the impacts of the implementation of energy saving measures on the performance of the system, in terms of technical and economic feasibility, were demonstrated. The results showed that maintenance optimization could help in reaching

Work management to optimise occupational radiological protection

International Nuclear Information System (INIS)

Ahier, B.

2009-01-01

Although work management is no longer a new concept, continued efforts are still needed to ensure that good performance, outcomes and trends are maintained in the face of current and future challenges. The ISOE programme thus created an Expert Group on Work Management in 2007 to develop an updated report reflecting the current state of knowledge, technology and experience in the occupational radiological protection of workers at nuclear power plants. Published in 2009, the new ISOE report on Work Management to Optimise Occupational Radiological Protection in the Nuclear Power Industry provides up-to-date practical guidance on the application of work management principles. Work management measures aim at optimising occupational radiological protection in the context of the economic viability of the installation. Important factors in this respect are measures and techniques influencing i) dose and dose rate, including source- term reduction; ii) exposure, including amount of time spent in controlled areas for operations; and iii) efficiency in short- and long-term planning, worker involvement, coordination and training. Equally important due to their broad, cross-cutting nature are the motivational and organisational arrangements adopted. The responsibility for these aspects may reside in various parts of an installation's organisational structure, and thus, a multi-disciplinary approach must be recognised, accounted for and well-integrated in any work. Based on the operational experience within the ISOE programme, the following key areas of work management have been identified: - regulatory aspects; - ALARA management policy; - worker involvement and performance; - work planning and scheduling; - work preparation; - work implementation; - work assessment and feedback; - ensuring continuous improvement. The details of each of these areas are elaborated and illustrated in the report through examples and case studies arising from ISOE experience. They are intended to

Efficient characterisation of large deviations using population dynamics

Science.gov (United States)

Brewer, Tobias; Clark, Stephen R.; Bradford, Russell; Jack, Robert L.

2018-05-01

We consider population dynamics as implemented by the cloning algorithm for analysis of large deviations of time-averaged quantities. We use the simple symmetric exclusion process with periodic boundary conditions as a prototypical example and investigate the convergence of the results with respect to the algorithmic parameters, focussing on the dynamical phase transition between homogeneous and inhomogeneous states, where convergence is relatively difficult to achieve. We discuss how the performance of the algorithm can be optimised, and how it can be efficiently exploited on parallel computing platforms.

A robust algorithm for optimisation and customisation of fractal dimensions of time series modified by nonlinearly scaling their time derivatives: mathematical theory and practical applications.

Science.gov (United States)

Fuss, Franz Konstantin

2013-01-01

Standard methods for computing the fractal dimensions of time series are usually tested with continuous nowhere differentiable functions, but not benchmarked with actual signals. Therefore they can produce opposite results in extreme signals. These methods also use different scaling methods, that is, different amplitude multipliers, which makes it difficult to compare fractal dimensions obtained from different methods. The purpose of this research was to develop an optimisation method that computes the fractal dimension of a normalised (dimensionless) and modified time series signal with a robust algorithm and a running average method, and that maximises the difference between two fractal dimensions, for example, a minimum and a maximum one. The signal is modified by transforming its amplitude by a multiplier, which has a non-linear effect on the signal's time derivative. The optimisation method identifies the optimal multiplier of the normalised amplitude for targeted decision making based on fractal dimensions. The optimisation method provides an additional filter effect and makes the fractal dimensions less noisy. The method is exemplified by, and explained with, different signals, such as human movement, EEG, and acoustic signals.

Secure Data Access Control for Fog Computing Based on Multi-Authority Attribute-Based Signcryption with Computation Outsourcing and Attribute Revocation.

Science.gov (United States)

Xu, Qian; Tan, Chengxiang; Fan, Zhijie; Zhu, Wenye; Xiao, Ya; Cheng, Fujia

2018-05-17

Nowadays, fog computing provides computation, storage, and application services to end users in the Internet of Things. One of the major concerns in fog computing systems is how fine-grained access control can be imposed. As a logical combination of attribute-based encryption and attribute-based signature, Attribute-based Signcryption (ABSC) can provide confidentiality and anonymous authentication for sensitive data and is more efficient than traditional "encrypt-then-sign" or "sign-then-encrypt" strategy. Thus, ABSC is suitable for fine-grained access control in a semi-trusted cloud environment and is gaining more and more attention recently. However, in many existing ABSC systems, the computation cost required for the end users in signcryption and designcryption is linear with the complexity of signing and encryption access policy. Moreover, only a single authority that is responsible for attribute management and key generation exists in the previous proposed ABSC schemes, whereas in reality, mostly, different authorities monitor different attributes of the user. In this paper, we propose OMDAC-ABSC, a novel data access control scheme based on Ciphertext-Policy ABSC, to provide data confidentiality, fine-grained control, and anonymous authentication in a multi-authority fog computing system. The signcryption and designcryption overhead for the user is significantly reduced by outsourcing the undesirable computation operations to fog nodes. The proposed scheme is proven to be secure in the standard model and can provide attribute revocation and public verifiability. The security analysis, asymptotic complexity comparison, and implementation results indicate that our construction can balance the security goals with practical efficiency in computation.

Water quality modelling and optimisation of wastewater treatment network using mixed integer programming

CSIR Research Space (South Africa)

Mahlathi, Christopher

2016-10-01

Full Text Available Instream water quality management encompasses field monitoring and utilisation of mathematical models. These models can be coupled with optimisation techniques to determine more efficient water quality management alternatives. Among these activities...

HAlign-II: efficient ultra-large multiple sequence alignment and phylogenetic tree reconstruction with distributed and parallel computing.

Science.gov (United States)

Wan, Shixiang; Zou, Quan

2017-01-01

Multiple sequence alignment (MSA) plays a key role in biological sequence analyses, especially in phylogenetic tree construction. Extreme increase in next-generation sequencing results in shortage of efficient ultra-large biological sequence alignment approaches for coping with different sequence types. Distributed and parallel computing represents a crucial technique for accelerating ultra-large (e.g. files more than 1 GB) sequence analyses. Based on HAlign and Spark distributed computing system, we implement a highly cost-efficient and time-efficient HAlign-II tool to address ultra-large multiple biological sequence alignment and phylogenetic tree construction. The experiments in the DNA and protein large scale data sets, which are more than 1GB files, showed that HAlign II could save time and space. It outperformed the current software tools. HAlign-II can efficiently carry out MSA and construct phylogenetic trees with ultra-large numbers of biological sequences. HAlign-II shows extremely high memory efficiency and scales well with increases in computing resource. THAlign-II provides a user-friendly web server based on our distributed computing infrastructure. HAlign-II with open-source codes and datasets was established at http://lab.malab.cn/soft/halign.

Optimisation of a propagation-based x-ray phase-contrast micro-CT system

Science.gov (United States)

Nesterets, Yakov I.; Gureyev, Timur E.; Dimmock, Matthew R.

2018-03-01

Micro-CT scanners find applications in many areas ranging from biomedical research to material sciences. In order to provide spatial resolution on a micron scale, these scanners are usually equipped with micro-focus, low-power x-ray sources and hence require long scanning times to produce high resolution 3D images of the object with acceptable contrast-to-noise. Propagation-based phase-contrast tomography (PB-PCT) has the potential to significantly improve the contrast-to-noise ratio (CNR) or, alternatively, reduce the image acquisition time while preserving the CNR and the spatial resolution. We propose a general approach for the optimisation of the PB-PCT imaging system. When applied to an imaging system with fixed parameters of the source and detector this approach requires optimisation of only two independent geometrical parameters of the imaging system, i.e. the source-to-object distance R 1 and geometrical magnification M, in order to produce the best spatial resolution and CNR. If, in addition to R 1 and M, the system parameter space also includes the source size and the anode potential this approach allows one to find a unique configuration of the imaging system that produces the required spatial resolution and the best CNR.

Optimisation Platform for copper ore processing at the Division of Concentrator of KGHM Polska Miedz S.A.

Directory of Open Access Journals (Sweden)

Kuzba Bogdan

2016-01-01

Full Text Available The idea of Optimisation Platform is to create an innovative system. It is dedicated to technology and cost efficiency improvement of process realized at the Division of Concentrators of KGHM Polska Miedz SA. This highly sophisticated tool is based on visual, acoustic and vibrating detection systems. The range of its functionality was described in this work. Three main utility modules were described: froth flotation image processing (FloVis, grinding and classification monitoring (MillVis and belt conveyors control unit (ConVis. The effects of implementation of the system under KGHM conditions were described. It is concluded that the Optimisation Platform is one of the most promising solution for improvement of technology and economy performance at the Division of Concentrators of KGHM Polska Miedz S.A.

Efficient frequent pattern mining algorithm based on node sets in cloud computing environment

Science.gov (United States)

Billa, V. N. Vinay Kumar; Lakshmanna, K.; Rajesh, K.; Reddy, M. Praveen Kumar; Nagaraja, G.; Sudheer, K.

2017-11-01

The ultimate goal of Data Mining is to determine the hidden information which is useful in making decisions using the large databases collected by an organization. This Data Mining involves many tasks that are to be performed during the process. Mining frequent itemsets is the one of the most important tasks in case of transactional databases. These transactional databases contain the data in very large scale where the mining of these databases involves the consumption of physical memory and time in proportion to the size of the database. A frequent pattern mining algorithm is said to be efficient only if it consumes less memory and time to mine the frequent itemsets from the given large database. Having these points in mind in this thesis we proposed a system which mines frequent itemsets in an optimized way in terms of memory and time by using cloud computing as an important factor to make the process parallel and the application is provided as a service. A complete framework which uses a proven efficient algorithm called FIN algorithm. FIN algorithm works on Nodesets and POC (pre-order coding) tree. In order to evaluate the performance of the system we conduct the experiments to compare the efficiency of the same algorithm applied in a standalone manner and in cloud computing environment on a real time data set which is traffic accidents data set. The results show that the memory consumption and execution time taken for the process in the proposed system is much lesser than those of standalone system.

Advantages of Task-Specific Multi-Objective Optimisation in Evolutionary Robotics.

Science.gov (United States)

Trianni, Vito; López-Ibáñez, Manuel

2015-01-01

The application of multi-objective optimisation to evolutionary robotics is receiving increasing attention. A survey of the literature reveals the different possibilities it offers to improve the automatic design of efficient and adaptive robotic systems, and points to the successful demonstrations available for both task-specific and task-agnostic approaches (i.e., with or without reference to the specific design problem to be tackled). However, the advantages of multi-objective approaches over single-objective ones have not been clearly spelled out and experimentally demonstrated. This paper fills this gap for task-specific approaches: starting from well-known results in multi-objective optimisation, we discuss how to tackle commonly recognised problems in evolutionary robotics. In particular, we show that multi-objective optimisation (i) allows evolving a more varied set of behaviours by exploring multiple trade-offs of the objectives to optimise, (ii) supports the evolution of the desired behaviour through the introduction of objectives as proxies, (iii) avoids the premature convergence to local optima possibly introduced by multi-component fitness functions, and (iv) solves the bootstrap problem exploiting ancillary objectives to guide evolution in the early phases. We present an experimental demonstration of these benefits in three different case studies: maze navigation in a single robot domain, flocking in a swarm robotics context, and a strictly collaborative task in collective robotics.

Advantages of Task-Specific Multi-Objective Optimisation in Evolutionary Robotics.

Directory of Open Access Journals (Sweden)

Vito Trianni

Full Text Available The application of multi-objective optimisation to evolutionary robotics is receiving increasing attention. A survey of the literature reveals the different possibilities it offers to improve the automatic design of efficient and adaptive robotic systems, and points to the successful demonstrations available for both task-specific and task-agnostic approaches (i.e., with or without reference to the specific design problem to be tackled. However, the advantages of multi-objective approaches over single-objective ones have not been clearly spelled out and experimentally demonstrated. This paper fills this gap for task-specific approaches: starting from well-known results in multi-objective optimisation, we discuss how to tackle commonly recognised problems in evolutionary robotics. In particular, we show that multi-objective optimisation (i allows evolving a more varied set of behaviours by exploring multiple trade-offs of the objectives to optimise, (ii supports the evolution of the desired behaviour through the introduction of objectives as proxies, (iii avoids the premature convergence to local optima possibly introduced by multi-component fitness functions, and (iv solves the bootstrap problem exploiting ancillary objectives to guide evolution in the early phases. We present an experimental demonstration of these benefits in three different case studies: maze navigation in a single robot domain, flocking in a swarm robotics context, and a strictly collaborative task in collective robotics.

Digital radiography: are the manufacturers' settings too high? Optimisation of the Kodak digital radiography system with aid of the computed radiography dose index

International Nuclear Information System (INIS)

Peters, Sinead E.; Brennan, Patrick C.

2002-01-01

Manufacturers offer exposure indices as a safeguard against overexposure in computed radiography, but the basis for recommended values is unclear. This study establishes an optimum exposure index to be used as a guideline for a specific CR system to minimise radiation exposures for computed mobile chest radiography, and compares this with manufacturer guidelines and current practice. An anthropomorphic phantom was employed to establish the minimum milliamperes consistent with acceptable image quality for mobile chest radiography images. This was found to be 2 mAs. Consecutively, 10 patients were exposed with this optimised milliampere value and 10 patients were exposed with the 3.2 mAs routinely used in the department of the study. Image quality was objectively assessed using anatomical criteria. Retrospective analyses of 717 exposure indices recorded over 2 months from mobile chest examinations were performed. The optimised milliampere value provided a significant reduction of the average exposure index from 1840 to 1570 (p<0.0001). This new ''optimum'' exposure index is substantially lower than manufacturer guidelines of 2000 and significantly lower than exposure indices from the retrospective study (1890). Retrospective data showed a significant increase in exposure indices if the examination was performed out of hours. The data provided by this study emphasise the need for clinicians and personnel to consider establishing their own optimum exposure indices for digital investigations rather than simply accepting manufacturers' guidelines. Such an approach, along with regular monitoring of indices, may result in a substantial reduction in patient exposure. (orig.)

Energy and wear optimisation of train longitudinal dynamics and of traction and braking systems

Science.gov (United States)

Conti, R.; Galardi, E.; Meli, E.; Nocciolini, D.; Pugi, L.; Rindi, A.

2015-05-01

Traction and braking systems deeply affect longitudinal train dynamics, especially when an extensive blending phase among different pneumatic, electric and magnetic devices is required. The energy and wear optimisation of longitudinal vehicle dynamics has a crucial economic impact and involves several engineering problems such as wear of braking friction components, energy efficiency, thermal load on components, level of safety under degraded or adhesion conditions (often constrained by the current regulation in force on signalling or other safety-related subsystem). In fact, the application of energy storage systems can lead to an efficiency improvement of at least 10% while, as regards the wear reduction, the improvement due to distributed traction systems and to optimised traction devices can be quantified in about 50%. In this work, an innovative integrated procedure is proposed by the authors to optimise longitudinal train dynamics and traction and braking manoeuvres in terms of both energy and wear. The new approach has been applied to existing test cases and validated with experimental data provided by Breda and, for some components and their homologation process, the results of experimental activities derive from cooperation performed with relevant industrial partners such as Trenitalia and Italcertifer. In particular, simulation results are referred to the simulation tests performed on a high-speed train (Ansaldo Breda Emu V250) and on a tram (Ansaldo Breda Sirio Tram). The proposed approach is based on a modular simulation platform in which the sub-models corresponding to different subsystems can be easily customised, depending on the considered application, on the availability of technical data and on the homologation process of different components.

Quantum Genetic Algorithms for Computer Scientists

OpenAIRE

Lahoz Beltrá, Rafael

2016-01-01

Genetic algorithms (GAs) are a class of evolutionary algorithms inspired by Darwinian natural selection. They are popular heuristic optimisation methods based on simulated genetic mechanisms, i.e., mutation, crossover, etc. and population dynamical processes such as reproduction, selection, etc. Over the last decade, the possibility to emulate a quantum computer (a computer using quantum-mechanical phenomena to perform operations on data) has led to a new class of GAs known as “Quantum Geneti...

Optimisation of electrical system for offshore wind farms via genetic algorithm

DEFF Research Database (Denmark)

Chen, Zhe; Zhao, Menghua; Blaabjerg, Frede

2009-01-01

An optimisation platform based on genetic algorithm (GA) is presented, where the main components of a wind farm and key technical specifications are used as input parameters and the electrical system design of the wind farm is optimised in terms of both production cost and system reliability....... The power losses, wind power production, initial investment and maintenance costs are considered in the production cost. The availability of components and network redundancy are included in the reliability evaluation. The method of coding an electrical system to a binary string, which is processed by GA......, is developed. Different GA techniques are investigated based on a real example offshore wind farm. This optimisation platform has been demonstrated as a powerful tool for offshore wind farm design and evaluation....

A computationally efficient 3D finite-volume scheme for violent liquid–gas sloshing

CSIR Research Space (South Africa)

Oxtoby, Oliver F

2015-10-01

Full Text Available We describe a semi-implicit volume-of-fluid free-surface-modelling methodology for flow problems involving violent free-surface motion. For efficient computation, a hybrid-unstructured edge-based vertex-centred finite volume discretisation...

Particle swarm optimisation classical and quantum perspectives

CERN Document Server

Sun, Jun; Wu, Xiao-Jun

2016-01-01

IntroductionOptimisation Problems and Optimisation MethodsRandom Search TechniquesMetaheuristic MethodsSwarm IntelligenceParticle Swarm OptimisationOverviewMotivationsPSO Algorithm: Basic Concepts and the ProcedureParadigm: How to Use PSO to Solve Optimisation ProblemsSome Harder Examples Some Variants of Particle Swarm Optimisation Why Does the PSO Algorithm Need to Be Improved? Inertia and Constriction-Acceleration Techniques for PSOLocal Best ModelProbabilistic AlgorithmsOther Variants of PSO Quantum-Behaved Particle Swarm Optimisation OverviewMotivation: From Classical Dynamics to Quantum MechanicsQuantum Model: Fundamentals of QPSOQPSO AlgorithmSome Essential ApplicationsSome Variants of QPSOSummary Advanced Topics Behaviour Analysis of Individual ParticlesConvergence Analysis of the AlgorithmTime Complexity and Rate of ConvergenceParameter Selection and PerformanceSummaryIndustrial Applications Inverse Problems for Partial Differential EquationsInverse Problems for Non-Linear Dynamical SystemsOptimal De...

An Efficient Neural-Network-Based Microseismic Monitoring Platform for Hydraulic Fracture on an Edge Computing Architecture

Directory of Open Access Journals (Sweden)

Xiaopu Zhang

2018-06-01

Full Text Available Microseismic monitoring is one of the most critical technologies for hydraulic fracturing in oil and gas production. To detect events in an accurate and efficient way, there are two major challenges. One challenge is how to achieve high accuracy due to a poor signal-to-noise ratio (SNR. The other one is concerned with real-time data transmission. Taking these challenges into consideration, an edge-computing-based platform, namely Edge-to-Center LearnReduce, is presented in this work. The platform consists of a data center with many edge components. At the data center, a neural network model combined with convolutional neural network (CNN and long short-term memory (LSTM is designed and this model is trained by using previously obtained data. Once the model is fully trained, it is sent to edge components for events detection and data reduction. At each edge component, a probabilistic inference is added to the neural network model to improve its accuracy. Finally, the reduced data is delivered to the data center. Based on experiment results, a high detection accuracy (over 96% with less transmitted data (about 90% was achieved by using the proposed approach on a microseismic monitoring system. These results show that the platform can simultaneously improve the accuracy and efficiency of microseismic monitoring.

An Efficient Neural-Network-Based Microseismic Monitoring Platform for Hydraulic Fracture on an Edge Computing Architecture.

Science.gov (United States)

Zhang, Xiaopu; Lin, Jun; Chen, Zubin; Sun, Feng; Zhu, Xi; Fang, Gengfa

2018-06-05

Microseismic monitoring is one of the most critical technologies for hydraulic fracturing in oil and gas production. To detect events in an accurate and efficient way, there are two major challenges. One challenge is how to achieve high accuracy due to a poor signal-to-noise ratio (SNR). The other one is concerned with real-time data transmission. Taking these challenges into consideration, an edge-computing-based platform, namely Edge-to-Center LearnReduce, is presented in this work. The platform consists of a data center with many edge components. At the data center, a neural network model combined with convolutional neural network (CNN) and long short-term memory (LSTM) is designed and this model is trained by using previously obtained data. Once the model is fully trained, it is sent to edge components for events detection and data reduction. At each edge component, a probabilistic inference is added to the neural network model to improve its accuracy. Finally, the reduced data is delivered to the data center. Based on experiment results, a high detection accuracy (over 96%) with less transmitted data (about 90%) was achieved by using the proposed approach on a microseismic monitoring system. These results show that the platform can simultaneously improve the accuracy and efficiency of microseismic monitoring.

Some computational challenges of developing efficient parallel algorithms for data-dependent computations in thermal-hydraulics supercomputer applications

International Nuclear Information System (INIS)

Woodruff, S.B.

1994-01-01

The Transient Reactor Analysis Code (TRAC), which features a two-fluid treatment of thermal-hydraulics, is designed to model transients in water reactors and related facilities. One of the major computational costs associated with TRAC and similar codes is calculating constitutive coefficients. Although the formulations for these coefficients are local, the costs are flow-regime- or data-dependent; i.e., the computations needed for a given spatial node often vary widely as a function of time. Consequently, a fixed, uniform assignment of nodes to prallel processors will result in degraded computational efficiency due to the poor load balancing. A standard method for treating data-dependent models on vector architectures has been to use gather operations (or indirect adressing) to sort the nodes into subsets that (temporarily) share a common computational model. However, this method is not effective on distributed memory data parallel architectures, where indirect adressing involves expensive communication overhead. Another serious problem with this method involves software engineering challenges in the areas of maintainability and extensibility. For example, an implementation that was hand-tuned to achieve good computational efficiency would have to be rewritten whenever the decision tree governing the sorting was modified. Using an example based on the calculation of the wall-to-liquid and wall-to-vapor heat-transfer coefficients for three nonboiling flow regimes, we describe how the use of the Fortran 90 WHERE construct and automatic inlining of functions can be used to ameliorate this problem while improving both efficiency and software engineering. Unfortunately, a general automatic solution to the load-balancing problem associated with data-dependent computations is not yet available for massively parallel architectures. We discuss why developers should either wait for such solutions or consider alternative numerical algorithms, such as a neural network

Topology optimised wavelength dependent splitters

DEFF Research Database (Denmark)

Hede, K. K.; Burgos Leon, J.; Frandsen, Lars Hagedorn

A photonic crystal wavelength dependent splitter has been constructed by utilising topology optimisation1. The splitter has been fabricated in a silicon-on-insulator material (Fig. 1). The topology optimised wavelength dependent splitter demonstrates promising 3D FDTD simulation results....... This complex photonic crystal structure is very sensitive against small fabrication variations from the expected topology optimised design. A wavelength dependent splitter is an important basic building block for high-performance nanophotonic circuits. 1J. S. Jensen and O. Sigmund, App. Phys. Lett. 84, 2022...

Unified commutation-pruning technique for efficient computation of composite DFTs

Science.gov (United States)

Castro-Palazuelos, David E.; Medina-Melendrez, Modesto Gpe.; Torres-Roman, Deni L.; Shkvarko, Yuriy V.

2015-12-01

An efficient computation of a composite length discrete Fourier transform (DFT), as well as a fast Fourier transform (FFT) of both time and space data sequences in uncertain (non-sparse or sparse) computational scenarios, requires specific processing algorithms. Traditional algorithms typically employ some pruning methods without any commutations, which prevents them from attaining the potential computational efficiency. In this paper, we propose an alternative unified approach with automatic commutations between three computational modalities aimed at efficient computations of the pruned DFTs adapted for variable composite lengths of the non-sparse input-output data. The first modality is an implementation of the direct computation of a composite length DFT, the second one employs the second-order recursive filtering method, and the third one performs the new pruned decomposed transform. The pruned decomposed transform algorithm performs the decimation in time or space (DIT) data acquisition domain and, then, decimation in frequency (DIF). The unified combination of these three algorithms is addressed as the DFTCOMM technique. Based on the treatment of the combinational-type hypotheses testing optimization problem of preferable allocations between all feasible commuting-pruning modalities, we have found the global optimal solution to the pruning problem that always requires a fewer or, at most, the same number of arithmetic operations than other feasible modalities. The DFTCOMM method outperforms the existing competing pruning techniques in the sense of attainable savings in the number of required arithmetic operations. It requires fewer or at most the same number of arithmetic operations for its execution than any other of the competing pruning methods reported in the literature. Finally, we provide the comparison of the DFTCOMM with the recently developed sparse fast Fourier transform (SFFT) algorithmic family. We feature that, in the sensing scenarios with

Optimisation of milling parameters using neural network

Directory of Open Access Journals (Sweden)

Lipski Jerzy

2017-01-01

Full Text Available The purpose of this study was to design and test an intelligent computer software developed with the purpose of increasing average productivity of milling not compromising the design features of the final product. The developed system generates optimal milling parameters based on the extent of tool wear. The introduced optimisation algorithm employs a multilayer model of a milling process developed in the artificial neural network. The input parameters for model training are the following: cutting speed vc, feed per tooth fz and the degree of tool wear measured by means of localised flank wear (VB3. The output parameter is the surface roughness of a machined surface Ra. Since the model in the neural network exhibits good approximation of functional relationships, it was applied to determine optimal milling parameters in changeable tool wear conditions (VB3 and stabilisation of surface roughness parameter Ra. Our solution enables constant control over surface roughness parameters and productivity of milling process after each assessment of tool condition. The recommended parameters, i.e. those which applied in milling ensure desired surface roughness and maximal productivity, are selected from all the parameters generated by the model. The developed software may constitute an expert system supporting a milling machine operator. In addition, the application may be installed on a mobile device (smartphone, connected to a tool wear diagnostics instrument and the machine tool controller in order to supply updated optimal parameters of milling. The presented solution facilitates tool life optimisation and decreasing tool change costs, particularly during prolonged operation.

DIMOND II: Measures for optimising radiological information content and dose in digital imaging

International Nuclear Information System (INIS)

Dowling, A.; Malone, J.; Marsh, D.

2001-01-01

The European Commission concerted action on 'Digital Imaging: Measures for Optimising Radiological Information Content and Dose', DIMOND II, was conducted by 12 European partners over the period January 1997 to June 1999. The objective of the concerted action was to initiate a project in the area of digital medical imaging where practice was evolving without structured research in radiation protection, optimisation or justification. The main issues addressed were patient and staff dosimetry, image quality, quality criteria and technical issues. The scope included computed radiography (CR), image intensifier radiography and fluoroscopy, cardiology and interventional procedures. The concerted action was based on the consolidation of work conducted in the partner's institutions together with elective new work. Protocols and approaches to dosimetry, radiological information content/image quality measurement and quality criteria were established and presented at an international workshop held in Dublin in June 1999. Details of the work conducted during the DIMOND II concerted action and a summary of the main findings and conclusions are presented in this contribution. (author)

Energy efficiency of computer power supply units - Final report

Energy Technology Data Exchange (ETDEWEB)

Aebischer, B. [cepe - Centre for Energy Policy and Economics, Swiss Federal Institute of Technology Zuerich, Zuerich (Switzerland); Huser, H. [Encontrol GmbH, Niederrohrdorf (Switzerland)

2002-11-15

This final report for the Swiss Federal Office of Energy (SFOE) takes a look at the efficiency of computer power supply units, which decreases rapidly during average computer use. The background and the purpose of the project are examined. The power supplies for personal computers are discussed and the testing arrangement used is described. Efficiency, power-factor and operating points of the units are examined. Potentials for improvement and measures to be taken are discussed. Also, action to be taken by those involved in the design and operation of such power units is proposed. Finally, recommendations for further work are made.

A-VCI: A flexible method to efficiently compute vibrational spectra

Science.gov (United States)

Odunlami, Marc; Le Bris, Vincent; Bégué, Didier; Baraille, Isabelle; Coulaud, Olivier

2017-06-01

The adaptive vibrational configuration interaction algorithm has been introduced as a new method to efficiently reduce the dimension of the set of basis functions used in a vibrational configuration interaction process. It is based on the construction of nested bases for the discretization of the Hamiltonian operator according to a theoretical criterion that ensures the convergence of the method. In the present work, the Hamiltonian is written as a sum of products of operators. The purpose of this paper is to study the properties and outline the performance details of the main steps of the algorithm. New parameters have been incorporated to increase flexibility, and their influence has been thoroughly investigated. The robustness and reliability of the method are demonstrated for the computation of the vibrational spectrum up to 3000 cm-1 of a widely studied 6-atom molecule (acetonitrile). Our results are compared to the most accurate up to date computation; we also give a new reference calculation for future work on this system. The algorithm has also been applied to a more challenging 7-atom molecule (ethylene oxide). The computed spectrum up to 3200 cm-1 is the most accurate computation that exists today on such systems.

Navigating catastrophes: Local but not global optimisation allows for macro-economic navigation of crises

Science.gov (United States)

Harré, Michael S.

2013-02-01

Two aspects of modern economic theory have dominated the recent discussion on the state of the global economy: Crashes in financial markets and whether or not traditional notions of economic equilibrium have any validity. We have all seen the consequences of market crashes: plummeting share prices, businesses collapsing and considerable uncertainty throughout the global economy. This seems contrary to what might be expected of a system in equilibrium where growth dominates the relatively minor fluctuations in prices. Recent work from within economics as well as by physicists, psychologists and computational scientists has significantly improved our understanding of the more complex aspects of these systems. With this interdisciplinary approach in mind, a behavioural economics model of local optimisation is introduced and three general properties are proven. The first is that under very specific conditions local optimisation leads to a conventional macro-economic notion of a global equilibrium. The second is that if both global optimisation and economic growth are required then under very mild assumptions market catastrophes are an unavoidable consequence. Third, if only local optimisation and economic growth are required then there is sufficient parametric freedom for macro-economic policy makers to steer an economy around catastrophes without overtly disrupting local optimisation.

Ants Colony Optimisation of a Measuring Path of Prismatic Parts on a CMM

Directory of Open Access Journals (Sweden)

Stojadinovic Slavenko M.

2016-03-01

Full Text Available This paper presents optimisation of a measuring probe path in inspecting the prismatic parts on a CMM. The optimisation model is based on: (i the mathematical model that establishes an initial collision-free path presented by a set of points, and (ii the solution of Travelling Salesman Problem (TSP obtained with Ant Colony Optimisation (ACO. In order to solve TSP, an ACO algorithm that aims to find the shortest path of ant colony movement (i.e. the optimised path is applied. Then, the optimised path is compared with the measuring path obtained with online programming on CMM ZEISS UMM500 and with the measuring path obtained in the CMM inspection module of Pro/ENGINEER® software. The results of comparing the optimised path with the other two generated paths show that the optimised path is at least 20% shorter than the path obtained by on-line programming on CMM ZEISS UMM500, and at least 10% shorter than the path obtained by using the CMM module in Pro/ENGINEER®.

Optimising Magnetostatic Assemblies

DEFF Research Database (Denmark)

Insinga, Andrea Roberto; Smith, Anders

theorem. This theorem formulates an energy equivalence principle with several implications concerning the optimisation of objective functionals that are linear with respect to the magnetic field. Linear functionals represent different optimisation goals, e.g. maximising a certain component of the field...... approached employing a heuristic algorithm, which led to new design concepts. Some of the procedures developed for linear objective functionals have been extended to non-linear objectives, by employing iterative techniques. Even though most the optimality results discussed in this work have been derived...

ECOS: a configurable, multi-terabyte database supporting engineering and technical computing at Sizewell B

International Nuclear Information System (INIS)

Binns, F.; Fish, A.

1992-01-01

One of the three main classes of computing support systems is concerned with the technical and engineering aspects of Sizewell-B power station. These aspects are primarily concerned with engineering means to optimise plant use to maximise power output by increasing availability and efficiency. At Sizewell-B the Engineering Computer system (ECOS) will provide the necessary support facilities, and is described. ECOS is being used by the station commissioning team and for monitoring the state of some plant already in service. (Author)

Computer-aided modeling framework for efficient model development, analysis and identification

DEFF Research Database (Denmark)

Heitzig, Martina; Sin, Gürkan; Sales Cruz, Mauricio

2011-01-01

Model-based computer aided product-process engineering has attained increased importance in a number of industries, including pharmaceuticals, petrochemicals, fine chemicals, polymers, biotechnology, food, energy, and water. This trend is set to continue due to the substantial benefits computer-aided...... methods introduce. The key prerequisite of computer-aided product-process engineering is however the availability of models of different types, forms, and application modes. The development of the models required for the systems under investigation tends to be a challenging and time-consuming task....... The methodology has been implemented into a computer-aided modeling framework, which combines expert skills, tools, and database connections that are required for the different steps of the model development work-flow with the goal to increase the efficiency of the modeling process. The framework has two main...

Optimisation of expansion liquefaction processes using mixed refrigerant N_2–CH_4

International Nuclear Information System (INIS)

Ding, He; Sun, Heng; He, Ming

2016-01-01

Highlights: • A refrigerant composition matching method for N_2–CH_4 expansion processes. • Efficiency improvements for propane pre-cooled N_2–CH_4 expansion processes. • The process shows good adaptability to varying natural gas compositions. - Abstract: An expansion process with a pre-cooling system is simulated and optimised by Aspen HYSYS and MATLAB"™. Taking advantage of higher specific refrigeration effect of methane and easily reduced refrigeration temperature of nitrogen, the designed process adopts N_2–CH_4 as a mixed refrigerant. Based on the different thermodynamic properties and sensitivity difference of N_2 and CH_4 over the same heat transfer temperature range, this work proposes a novel method of matching refrigerant composition which aims at single-stage or multi-stage series expansion liquefaction processes with pre-cooling systems. This novel method is applied successfully in propane pre-cooled N_2–CH_4 expansion process, and the unit power consumption is reduced to 7.09 kWh/kmol, which is only 5.35% higher than the global optimised solutions obtained by genetic algorithm. This novel method can fulfil the accomplishments of low energy consumption and high liquefaction rate, and thus decreases the gap between the mixed refrigerant and expansion processes in energy consumption. Furthermore, the high exergy efficiency of the process indicates good adaptability to varying natural gas compositions.

Computer Architecture Techniques for Power-Efficiency

CERN Document Server

Kaxiras, Stefanos

2008-01-01

In the last few years, power dissipation has become an important design constraint, on par with performance, in the design of new computer systems. Whereas in the past, the primary job of the computer architect was to translate improvements in operating frequency and transistor count into performance, now power efficiency must be taken into account at every step of the design process. While for some time, architects have been successful in delivering 40% to 50% annual improvement in processor performance, costs that were previously brushed aside eventually caught up. The most critical of these

Optimisation of searches for Supersymmetry with the ATLAS detector

Energy Technology Data Exchange (ETDEWEB)

Zvolsky, Milan

2012-01-15

The ATLAS experiment is one of the four large experiments at the Large Hadron Collider which is specifically designed to search for the Higgs boson and physics beyond the Standard Model. The aim of this thesis is the optimisation of searches for Supersymmetry in decays with two leptons and missing transverse energy in the final state. Two different optimisation studies have been performed for two important analysis aspects: The final signal region selection and the choice of the trigger selection. In the first part of the analysis, a cut-based optimisation of signal regions is performed, maximising the signal for a minimal background contamination. By this, the signal yield can in parts be more than doubled. The second approach is to introduce di-lepton triggers which allow to lower the lepton transverse momentum threshold, thus enhancing the number of selected signal events significantly. The signal region optimisation was considered for the choice of the final event selection in the ATLAS di-lepton analyses. The trigger study contributed to the incorporation of di-lepton triggers to the ATLAS trigger menu. (orig.)

Dispersion-Flattened Composite Highly Nonlinear Fibre Optimised for Broadband Pulsed Four-Wave Mixing

DEFF Research Database (Denmark)

Lillieholm, Mads; Galili, Michael; Oxenløwe, Leif Katsuo

2016-01-01

We present a segmented composite HNLF optimised for mitigation of dispersion-fluctuation impairments for broadband pulsed four-wave mixing. The HNLF-segmentation allows for pulsed FWMprocessing of a 13-nm wide input WDM-signal with -4.6-dB conversion efficiency...

Approaches and challenges to optimising primary care teams’ electronic health record usage

Directory of Open Access Journals (Sweden)

Nancy Pandhi

2014-07-01

Full Text Available Background Although the presence of an electronic health record (EHR alone does not ensure high quality, efficient care, few studies have focused on the work of those charged with optimising use of existing EHR functionality.Objective To examine the approaches used and challenges perceived by analysts supporting the optimisation of primary care teams’ EHR use at a large U.S. academic health care system.Methods A qualitative study was conducted. Optimisation analysts and their supervisor were interviewed and data were analysed for themes.Results Analysts needed to reconcile the tension created by organisational mandates focused on the standardisation of EHR processes with the primary care teams’ demand for EHR customisation. They gained an understanding of health information technology (HIT leadership’s and primary care team’s goals through attending meetings, reading meeting minutes and visiting with clinical teams. Within what was organisationally possible, EHR education could then be tailored to fit team needs. Major challenges were related to organisational attempts to standardise EHR use despite varied clinic contexts, personnel readiness and technical issues with the EHR platform. Forcing standardisation upon clinical needs that current EHR functionality could not satisfy was difficult.Conclusions Dedicated optimisation analysts can add value to health systems through playing a mediating role between HIT leadership and care teams. Our findings imply that EHR optimisation should be performed with an in-depth understanding of the workflow, cognitive and interactional activities in primary care.

Optimisation of liquid scintillation counting conditions to determine low activity levels of tritium and radiostrontium in aqueous solution

Energy Technology Data Exchange (ETDEWEB)

Rauret, Gemma; Mestres, J.S.; Ribera, Merce; Rajadel, Pilar (Barcelona Univ. (Spain). Dept. de Quimica Analitica)

1990-08-01

An optimisation of the counting conditions for the measurement of aqueous solutions of tritium or radiostrontium using Insta-Gel II as scintillator is presented. The variables optimised were the window, the ratio of mass of sample to mass of scintillator and the total volume of the counting mixture. An optimisation function which takes into account each of these variables, the background and also the efficiency is proposed. The conditions established allow the lowest possible detection limit to be reached. For tritium, this value was compared with that obtained when the standard method for water analysis was applied. (author).

Efficient approach for reliability-based optimization based on weighted importance sampling approach

International Nuclear Information System (INIS)

Yuan, Xiukai; Lu, Zhenzhou

2014-01-01

An efficient methodology is presented to perform the reliability-based optimization (RBO). It is based on an efficient weighted approach for constructing an approximation of the failure probability as an explicit function of the design variables which is referred to as the ‘failure probability function (FPF)’. It expresses the FPF as a weighted sum of sample values obtained in the simulation-based reliability analysis. The required computational effort for decoupling in each iteration is just single reliability analysis. After the approximation of the FPF is established, the target RBO problem can be decoupled into a deterministic one. Meanwhile, the proposed weighted approach is combined with a decoupling approach and a sequential approximate optimization framework. Engineering examples are given to demonstrate the efficiency and accuracy of the presented methodology

A novel sleep optimisation programme to improve athletes' well-being and performance.

Science.gov (United States)

Van Ryswyk, Emer; Weeks, Richard; Bandick, Laura; O'Keefe, Michaela; Vakulin, Andrew; Catcheside, Peter; Barger, Laura; Potter, Andrew; Poulos, Nick; Wallace, Jarryd; Antic, Nick A

2017-03-01

To improve well-being and performance indicators in a group of Australian Football League (AFL) players via a six-week sleep optimisation programme. Prospective intervention study following observations suggestive of reduced sleep and excessive daytime sleepiness in an AFL group. Athletes from the Adelaide Football Club were invited to participate if they had played AFL senior-level football for 1-5 years, or if they had excessive daytime sleepiness (Epworth Sleepiness Scale [ESS] >10), measured via ESS. An initial education session explained normal sleep needs, and how to achieve increased sleep duration and quality. Participants (n = 25) received ongoing feedback on their sleep, and a mid-programme education and feedback session. Sleep duration, quality and related outcomes were measured during week one and at the conclusion of the six-week intervention period using sleep diaries, actigraphy, ESS, Pittsburgh Sleep Quality Index, Profile of Mood States, Training Distress Scale, Perceived Stress Scale and the Psychomotor Vigilance Task. Sleep diaries demonstrated an increase in total sleep time of approximately 20 min (498.8 ± 53.8 to 518.7 ± 34.3; p sleep efficiency (p sleep efficiency, fatigue and vigour indicate that a sleep optimisation programme may improve athletes' well-being. More research is required into the effects of sleep optimisation on athletic performance.

Bus Access Optimisation for FlexRay-based Distributed Embedded Systems

DEFF Research Database (Denmark)

Pop, Traian; Pop, Paul; Eles, Petru

2007-01-01

-real time communication in a deterministic manner. In this paper, we propose techniques for optimising the FlexRay bus access mechanism of a distributed system, so that the hard real-time deadlines are met for all the tasks and messages in the system. We have evaluated the proposed techniques using...

Efficiency improvement of technological preparation of power equipment manufacturing

Science.gov (United States)

Milukov, I. A.; Rogalev, A. N.; Sokolov, V. P.; Shevchenko, I. V.

2017-11-01

Competitiveness of power equipment primarily depends on speeding-up the development and mastering of new equipment samples and technologies, enhancement of organisation and management of design, manufacturing and operation. Actual political, technological and economic conditions cause the acute need in changing the strategy and tactics of process planning. At that the issues of maintenance of equipment with simultaneous improvement of its efficiency and compatibility to domestically produced components are considering. In order to solve these problems, using the systems of computer-aided process planning for process design at all stages of power equipment life cycle is economically viable. Computer-aided process planning is developed for the purpose of improvement of process planning by using mathematical methods and optimisation of design and management processes on the basis of CALS technologies, which allows for simultaneous process design, process planning organisation and management based on mathematical and physical modelling of interrelated design objects and production system. An integration of computer-aided systems providing the interaction of informative and material processes at all stages of product life cycle is proposed as effective solution to the challenges in new equipment design and process planning.

Computing with memory for energy-efficient robust systems

CERN Document Server

Paul, Somnath

2013-01-01

This book analyzes energy and reliability as major challenges faced by designers of computing frameworks in the nanometer technology regime.  The authors describe the existing solutions to address these challenges and then reveal a new reconfigurable computing platform, which leverages high-density nanoscale memory for both data storage and computation to maximize the energy-efficiency and reliability. The energy and reliability benefits of this new paradigm are illustrated and the design challenges are discussed. Various hardware and software aspects of this exciting computing paradigm are de

Efficient computation of the joint sample frequency spectra for multiple populations.

Science.gov (United States)

Kamm, John A; Terhorst, Jonathan; Song, Yun S

2017-01-01

A wide range of studies in population genetics have employed the sample frequency spectrum (SFS), a summary statistic which describes the distribution of mutant alleles at a polymorphic site in a sample of DNA sequences and provides a highly efficient dimensional reduction of large-scale population genomic variation data. Recently, there has been much interest in analyzing the joint SFS data from multiple populations to infer parameters of complex demographic histories, including variable population sizes, population split times, migration rates, admixture proportions, and so on. SFS-based inference methods require accurate computation of the expected SFS under a given demographic model. Although much methodological progress has been made, existing methods suffer from numerical instability and high computational complexity when multiple populations are involved and the sample size is large. In this paper, we present new analytic formulas and algorithms that enable accurate, efficient computation of the expected joint SFS for thousands of individuals sampled from hundreds of populations related by a complex demographic model with arbitrary population size histories (including piecewise-exponential growth). Our results are implemented in a new software package called momi (MOran Models for Inference). Through an empirical study we demonstrate our improvements to numerical stability and computational complexity.

Multiobjective optimisation of energy systems and building envelope retrofit in a residential community

International Nuclear Information System (INIS)

Wu, Raphael; Mavromatidis, Georgios; Orehounig, Kristina; Carmeliet, Jan

2017-01-01

Highlights: • Simultaneous optimisation of building envelope retrofit and energy systems. • Retrofit and energy systems change interact and should be considered simultaneously. • Case study quantifies cost-GHG emission tradeoffs for different retrofit options. - Abstract: In this paper, a method for a multi-objective and simultaneous optimisation of building energy systems and retrofit is presented. Tailored to be suitable for the diverse range of existing buildings in terms of age, size, and use, it combines dynamic energy demand simulation to explore individual retrofit scenarios with an energy hub optimisation. Implemented as an epsilon-constrained mixed integer linear program (MILP), the optimisation matches envelope retrofit with renewable and high efficiency energy supply technologies such as biomass boilers, heat pumps, photovoltaic and solar thermal panels to minimise life cycle cost and greenhouse gas (GHG) emissions. Due to its multi-objective, integrated assessment of building transformation options and its ability to capture both individual building characteristics and trends within a neighbourhood, this method is aimed to provide developers, neighbourhood and town policy makers with the necessary information to make adequate decisions. Our method is deployed in a case study of typical residential buildings in the Swiss village of Zernez, simulating energy demands in EnergyPlus and solving the optimisation problem with CPLEX. Although common trade-offs in energy system and retrofit choice can be observed, optimisation results suggest that the diversity in building age and size leads to optimal strategies for retrofitting and building system solutions, which are specific to different categories. With this method, GHG emissions of the entire community can be reduced by up to 76% at a cost increase of 3% compared to the current emission levels, if an optimised solution is selected for each building category.

A Robust Algorithm for Optimisation and Customisation of Fractal Dimensions of Time Series Modified by Nonlinearly Scaling Their Time Derivatives: Mathematical Theory and Practical Applications

Directory of Open Access Journals (Sweden)

Franz Konstantin Fuss

2013-01-01

Full Text Available Standard methods for computing the fractal dimensions of time series are usually tested with continuous nowhere differentiable functions, but not benchmarked with actual signals. Therefore they can produce opposite results in extreme signals. These methods also use different scaling methods, that is, different amplitude multipliers, which makes it difficult to compare fractal dimensions obtained from different methods. The purpose of this research was to develop an optimisation method that computes the fractal dimension of a normalised (dimensionless and modified time series signal with a robust algorithm and a running average method, and that maximises the difference between two fractal dimensions, for example, a minimum and a maximum one. The signal is modified by transforming its amplitude by a multiplier, which has a non-linear effect on the signal’s time derivative. The optimisation method identifies the optimal multiplier of the normalised amplitude for targeted decision making based on fractal dimensions. The optimisation method provides an additional filter effect and makes the fractal dimensions less noisy. The method is exemplified by, and explained with, different signals, such as human movement, EEG, and acoustic signals.

Computer vision based room interior design

Science.gov (United States)

Ahmad, Nasir; Hussain, Saddam; Ahmad, Kashif; Conci, Nicola

2015-12-01

This paper introduces a new application of computer vision. To the best of the author's knowledge, it is the first attempt to incorporate computer vision techniques into room interior designing. The computer vision based interior designing is achieved in two steps: object identification and color assignment. The image segmentation approach is used for the identification of the objects in the room and different color schemes are used for color assignment to these objects. The proposed approach is applied to simple as well as complex images from online sources. The proposed approach not only accelerated the process of interior designing but also made it very efficient by giving multiple alternatives.

Optimisation models for decision support in the development of biomass-based industrial district-heating networks in Italy

International Nuclear Information System (INIS)

Chinese, Damiana; Meneghetti, Antonella

2005-01-01

A system optimisation approach is proposed to design biomass-based district-heating networks in the context of industrial districts, which are one of the main successful productive aspects of Italian industry. Two different perspectives are taken into account, that of utilities and of policy makers, leading to two optimisation models to be further integrated. A mixed integer linear-programming model is developed for a utility company's profit maximisation, while a linear-programming model aims at minimising the balance of greenhouse-gas emissions related to the proposed energy system and the avoided emissions due to the substitution of current fossil-fuel boilers with district-heating connections. To systematically compare their results, a sensitivity analysis is performed with respect to network size in order to identify how the optimal system configuration, in terms of selected boilers to be connected to a multiple energy-source network, may vary in the two cases and to detect possible optimal sizes. Then a factorial analysis is adopted to rank desirable client types under the two perspectives and identify proper marketing strategies. The proposed optimisation approach was applied to the design of a new district-heating network in the chair-manufacturing district of North-Eastern Italy. (Author)

Optimisation of the PCR-invA primers for the detection of Salmonella ...

African Journals Online (AJOL)

A polymerase chain reaction (PCR)-based method for the detection of Salmonella species in water samples was optimised and evaluated for speed, specificity and sensitivity. Optimisation of Mg2+ and primer concentrations and cycling parameters increased the sensitivity and limit of detection of PCR to 2.6 x 104 cfu/m.

Sizing Combined Heat and Power Units and Domestic Building Energy Cost Optimisation

OpenAIRE

Dongmin Yu; Yuanzhu Meng; Gangui Yan; Gang Mu; Dezhi Li; Simon Le Blond

2017-01-01

Many combined heat and power (CHP) units have been installed in domestic buildings to increase energy efficiency and reduce energy costs. However, inappropriate sizing of a CHP may actually increase energy costs and reduce energy efficiency. Moreover, the high manufacturing cost of batteries makes batteries less affordable. Therefore, this paper will attempt to size the capacity of CHP and optimise daily energy costs for a domestic building with only CHP installed. In this paper, electricity ...

Graphics processor efficiency for realization of rapid tabular computations

International Nuclear Information System (INIS)

Dudnik, V.A.; Kudryavtsev, V.I.; Us, S.A.; Shestakov, M.V.

2016-01-01

Capabilities of graphics processing units (GPU) and central processing units (CPU) have been investigated for realization of fast-calculation algorithms with the use of tabulated functions. The realization of tabulated functions is exemplified by the GPU/CPU architecture-based processors. Comparison is made between the operating efficiencies of GPU and CPU, employed for tabular calculations at different conditions of use. Recommendations are formulated for the use of graphical and central processors to speed up scientific and engineering computations through the use of tabulated functions

Computer-Based Learning: Interleaving Whole and Sectional Representation of Neuroanatomy

Science.gov (United States)

Pani, John R.; Chariker, Julia H.; Naaz, Farah

2013-01-01

The large volume of material to be learned in biomedical disciplines requires optimizing the efficiency of instruction. In prior work with computer-based instruction of neuroanatomy, it was relatively efficient for learners to master whole anatomy and then transfer to learning sectional anatomy. It may, however, be more efficient to continuously…

Optimisation of technical specifications using probabilistic methods

International Nuclear Information System (INIS)

Ericsson, G.; Knochenhauer, M.; Hultqvist, G.

1986-01-01

During the last few years the development of methods for modifying and optimising nuclear power plant Technical Specifications (TS) for plant operations has received increased attention. Probalistic methods in general, and the plant and system models of probabilistic safety assessment (PSA) in particular, seem to provide the most forceful tools for optimisation. This paper first gives some general comments on optimisation, identifying important parameters and then gives a description of recent Swedish experiences from the use of nuclear power plant PSA models and results for TS optimisation

Turbulence optimisation in stellarator experiments

Energy Technology Data Exchange (ETDEWEB)

Proll, Josefine H.E. [Max-Planck/Princeton Center for Plasma Physics (Germany); Max-Planck-Institut fuer Plasmaphysik, Wendelsteinstr. 1, 17491 Greifswald (Germany); Faber, Benjamin J. [HSX Plasma Laboratory, University of Wisconsin-Madison, Madison, WI 53706 (United States); Helander, Per; Xanthopoulos, Pavlos [Max-Planck/Princeton Center for Plasma Physics (Germany); Lazerson, Samuel A.; Mynick, Harry E. [Plasma Physics Laboratory, Princeton University, P.O. Box 451 Princeton, New Jersey 08543-0451 (United States)

2015-05-01

Stellarators, the twisted siblings of the axisymmetric fusion experiments called tokamaks, have historically suffered from confining the heat of the plasma insufficiently compared with tokamaks and were therefore considered to be less promising candidates for a fusion reactor. This has changed, however, with the advent of stellarators in which the laminar transport is reduced to levels below that of tokamaks by shaping the magnetic field accordingly. As in tokamaks, the turbulent transport remains as the now dominant transport channel. Recent analytical theory suggests that the large configuration space of stellarators allows for an additional optimisation of the magnetic field to also reduce the turbulent transport. In this talk, the idea behind the turbulence optimisation is explained. We also present how an optimised equilibrium is obtained and how it might differ from the equilibrium field of an already existing device, and we compare experimental turbulence measurements in different configurations of the HSX stellarator in order to test the optimisation procedure.

On some limitations of reaction-diffusion chemical computers in relation to Voronoi diagram and its inversion

International Nuclear Information System (INIS)

Adamatzky, Andrew; Lacy Costello, Benjamin de

2003-01-01

A reaction-diffusion chemical computer in this context is a planar uniform chemical reactor, where data and results of a computation are represented by concentration profiles of reactants and the computation itself is implemented via the spreading and interaction of diffusive and phase waves. This class of chemical computers are efficient at solving problems with a 'natural' parallelism where data sets are decomposable onto a large number of geographically neighboring domains which are then processed in parallel. Typical problems of this type include image processing, geometrical transformations and optimisation. When chemical based devices are used to solve such problems questions regarding their reproducible, efficiency and the accuracy of their computations arise. In addition to these questions what are the limitations of reaction-diffusion chemical processors--what type of problems cannot currently and are unlikely ever to be solved? To answer the questions we study how a Voronoi diagram is constructed and how it is inverted in a planar chemical processor. We demonstrate that a Voronoi diagram is computed only partially in the chemical processor. We also prove that given a specific Voronoi diagram it is impossible to reconstruct the planar set (from which diagram was computed) in the reaction-diffusion chemical processor. In the Letter we open the first ever line of enquiry into the computational inability of reaction-diffusion chemical computers

An efficient algorithm for computing fixed length attractors based on bounded model checking in synchronous Boolean networks with biochemical applications.

Science.gov (United States)

Li, X Y; Yang, G W; Zheng, D S; Guo, W S; Hung, W N N

2015-04-28

Genetic regulatory networks are the key to understanding biochemical systems. One condition of the genetic regulatory network under different living environments can be modeled as a synchronous Boolean network. The attractors of these Boolean networks will help biologists to identify determinant and stable factors. Existing methods identify attractors based on a random initial state or the entire state simultaneously. They cannot identify the fixed length attractors directly. The complexity of including time increases exponentially with respect to the attractor number and length of attractors. This study used the bounded model checking to quickly locate fixed length attractors. Based on the SAT solver, we propose a new algorithm for efficiently computing the fixed length attractors, which is more suitable for large Boolean networks and numerous attractors' networks. After comparison using the tool BooleNet, empirical experiments involving biochemical systems demonstrated the feasibility and efficiency of our approach.

Green computing: power optimisation of vfi-based real-time multiprocessor dataflow applications

NARCIS (Netherlands)

Ahmad, W.; Holzenspies, P.K.F.; Stoelinga, Mariëlle Ida Antoinette; van de Pol, Jan Cornelis

2015-01-01

Execution time is no longer the only performance metric for computer systems. In fact, a trend is emerging to trade raw performance for energy savings. Techniques like Dynamic Power Management (DPM, switching to low power state) and Dynamic Voltage and Frequency Scaling (DVFS, throttling processor

Efficient MATLAB computations with sparse and factored tensors.

Energy Technology Data Exchange (ETDEWEB)

Bader, Brett William; Kolda, Tamara Gibson (Sandia National Lab, Livermore, CA)

2006-12-01

In this paper, the term tensor refers simply to a multidimensional or N-way array, and we consider how specially structured tensors allow for efficient storage and computation. First, we study sparse tensors, which have the property that the vast majority of the elements are zero. We propose storing sparse tensors using coordinate format and describe the computational efficiency of this scheme for various mathematical operations, including those typical to tensor decomposition algorithms. Second, we study factored tensors, which have the property that they can be assembled from more basic components. We consider two specific types: a Tucker tensor can be expressed as the product of a core tensor (which itself may be dense, sparse, or factored) and a matrix along each mode, and a Kruskal tensor can be expressed as the sum of rank-1 tensors. We are interested in the case where the storage of the components is less than the storage of the full tensor, and we demonstrate that many elementary operations can be computed using only the components. All of the efficiencies described in this paper are implemented in the Tensor Toolbox for MATLAB.

Computationally efficient implementation of combustion chemistry in parallel PDF calculations

International Nuclear Information System (INIS)

Lu Liuyan; Lantz, Steven R.; Ren Zhuyin; Pope, Stephen B.

2009-01-01

In parallel calculations of combustion processes with realistic chemistry, the serial in situ adaptive tabulation (ISAT) algorithm [S.B. Pope, Computationally efficient implementation of combustion chemistry using in situ adaptive tabulation, Combustion Theory and Modelling, 1 (1997) 41-63; L. Lu, S.B. Pope, An improved algorithm for in situ adaptive tabulation, Journal of Computational Physics 228 (2009) 361-386] substantially speeds up the chemistry calculations on each processor. To improve the parallel efficiency of large ensembles of such calculations in parallel computations, in this work, the ISAT algorithm is extended to the multi-processor environment, with the aim of minimizing the wall clock time required for the whole ensemble. Parallel ISAT strategies are developed by combining the existing serial ISAT algorithm with different distribution strategies, namely purely local processing (PLP), uniformly random distribution (URAN), and preferential distribution (PREF). The distribution strategies enable the queued load redistribution of chemistry calculations among processors using message passing. They are implemented in the software x2f m pi, which is a Fortran 95 library for facilitating many parallel evaluations of a general vector function. The relative performance of the parallel ISAT strategies is investigated in different computational regimes via the PDF calculations of multiple partially stirred reactors burning methane/air mixtures. The results show that the performance of ISAT with a fixed distribution strategy strongly depends on certain computational regimes, based on how much memory is available and how much overlap exists between tabulated information on different processors. No one fixed strategy consistently achieves good performance in all the regimes. Therefore, an adaptive distribution strategy, which blends PLP, URAN and PREF, is devised and implemented. It yields consistently good performance in all regimes. In the adaptive parallel

The Effect of Computer Automation on Institutional Review Board (IRB) Office Efficiency

Science.gov (United States)

Oder, Karl; Pittman, Stephanie

2015-01-01

Companies purchase computer systems to make their processes more efficient through automation. Some academic medical centers (AMC) have purchased computer systems for their institutional review boards (IRB) to increase efficiency and compliance with regulations. IRB computer systems are expensive to purchase, deploy, and maintain. An AMC should…

An investigation into the application of modern heuristic optimisation techniques to problems in power and processing utilities

International Nuclear Information System (INIS)

Dahal, Keshav Prasad

2000-01-01

The work contained in this thesis demonstrates that there is a significant requirement for the development and application of new optimisation techniques for solving industrial scheduling problems, in order to achieve a better schedule with significant economic and operational impact. An investigation of how modern heuristic approaches, such as genetic algorithm (GA), simulated annealing (SA), fuzzy logic and hybrids of these techniques, may be developed, designed and implemented appropriately for solving short term and long term NP-hard scheduling problems that exist in electric power utilities and process facilities. GA and SA based methods are developed for generator maintenance scheduling using a novel integer encoding and appropriate GA and SA operators. Three hybrid approaches (an inoculated GA, a GA/SA and a GA with fuzzy logic) are proposed in order to improve the solution performance, and to take advantage of any flexibilities inherent in the problem. Five different GA-based approaches are investigated for solving the generation scheduling problem. Of those, a knowledge-based hybrid GA approach achieves better solutions in a shorter computational time. This approach integrates problem specific knowledge, heuristic dispatch calculation and linear programming within the GA-framework. The application of a GA-based methodology is proposed for the scheduling of storage tanks of a water treatment facility. The proposed approach is an integration of a GA and a heuristic rule-base. The GA string considers the tank allocation problem, and the heuristic approach solves the rate determination problems within the framework of the GA. For optimising the schedule of operations of a bulk handling port facility, a generic modelling tool is developed characterising the operational and maintenance activities of the facility. A GA-based approach is integrated with the simulation software for optimising the scheduling of operations of the facility. Each of these approaches is

Developing a computationally efficient dynamic multilevel hybrid optimization scheme using multifidelity model interactions.

Energy Technology Data Exchange (ETDEWEB)

Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Gray, Genetha Anne (Sandia National Laboratories, Livermore, CA); Castro, Joseph Pete Jr. (; .); Giunta, Anthony Andrew

2006-01-01

Many engineering application problems use optimization algorithms in conjunction with numerical simulators to search for solutions. The formulation of relevant objective functions and constraints dictate possible optimization algorithms. Often, a gradient based approach is not possible since objective functions and constraints can be nonlinear, nonconvex, non-differentiable, or even discontinuous and the simulations involved can be computationally expensive. Moreover, computational efficiency and accuracy are desirable and also influence the choice of solution method. With the advent and increasing availability of massively parallel computers, computational speed has increased tremendously. Unfortunately, the numerical and model complexities of many problems still demand significant computational resources. Moreover, in optimization, these expenses can be a limiting factor since obtaining solutions often requires the completion of numerous computationally intensive simulations. Therefore, we propose a multifidelity optimization algorithm (MFO) designed to improve the computational efficiency of an optimization method for a wide range of applications. In developing the MFO algorithm, we take advantage of the interactions between multi fidelity models to develop a dynamic and computational time saving optimization algorithm. First, a direct search method is applied to the high fidelity model over a reduced design space. In conjunction with this search, a specialized oracle is employed to map the design space of this high fidelity model to that of a computationally cheaper low fidelity model using space mapping techniques. Then, in the low fidelity space, an optimum is obtained using gradient or non-gradient based optimization, and it is mapped back to the high fidelity space. In this paper, we describe the theory and implementation details of our MFO algorithm. We also demonstrate our MFO method on some example problems and on two applications: earth penetrators and

"Transit data"-based MST computation

Directory of Open Access Journals (Sweden)

Thodoris Karatasos

2017-10-01

Full Text Available In this work, we present an innovative image recognition technique which is based on the exploitation of transit-data in images or simple photographs of sites of interest. Our objective is to automatically transform real-world images to graphs and, then, compute Minimum Spanning Trees (MST in them.We apply this framework and present an application which automatically computes efficient construction plans (for escalator or low-emission hot spots for connecting all points of interest in cultural sites, i.e., archaeological sites, museums, galleries, etc, aiming to to facilitate global physical access to cultural heritage and artistic work and make it accessible to all groups of population.

Defect correction and multigrid for an efficient and accurate computation of airfoil flows

NARCIS (Netherlands)

Koren, B.

1988-01-01

Results are presented for an efficient solution method for second-order accurate discretizations of the 2D steady Euler equations. The solution method is based on iterative defect correction. Several schemes are considered for the computation of the second-order defect. In each defect correction

Model-based online optimisation. Pt. 1: active learning; Modellbasierte Online-Optimierung moderner Verbrennungsmotoren. T. 1: Aktives Lernen

Energy Technology Data Exchange (ETDEWEB)

Poland, J.; Knoedler, K.; Zell, A. [Tuebingen Univ. (Germany). Lehrstuhl fuer Rechnerarchitektur; Fleischhauer, T.; Mitterer, A.; Ullmann, S. [BMW Group (Germany)

2003-05-01

This two-part article presents the model-based optimisation algorithm ''mbminimize''. It was developed in a corporate project of the University Tuebingen and the BMW Group for the purpose of optimising internal combustion engines online on the engine test bed. The first part concentrates on the basic algorithmic design, as well as on modelling, experimental design and active learning. The second part will discuss strategies for dealing with limits such as knocking. (orig.) [German] Dieser zweiteilige Beitrag stellt den modellbasierten Optimierungsalgorithmus ''mbminimize'' vor, der in Kooperation von der Universitaet Tuebingen und der BMW Group fuer die Online-Optimierung von Verbrennungsmotoren entwickelt wurde. Der vorliegende erste Teil konzentriert sich auf das grundlegende algorithmische Design, auf Modellierung, Versuchsplanung und aktives Lernen. Der zweite Teil diskutiert Strategien zur Behandlung von Limits wie Motorklopfen.

Preconditioned stochastic gradient descent optimisation for monomodal image registration

NARCIS (Netherlands)

Klein, S.; Staring, M.; Andersson, J.P.; Pluim, J.P.W.; Fichtinger, G.; Martel, A.; Peters, T.

2011-01-01

We present a stochastic optimisation method for intensity-based monomodal image registration. The method is based on a Robbins-Monro stochastic gradient descent method with adaptive step size estimation, and adds a preconditioning matrix. The derivation of the pre-conditioner is based on the

In-cylinder diesel spray combustion simulations using parallel computation: A performance benchmarking study

International Nuclear Information System (INIS)

Pang, Kar Mun; Ng, Hoon Kiat; Gan, Suyin

2012-01-01

Highlights: ► A performance benchmarking exercise is conducted for diesel combustion simulations. ► The reduced chemical mechanism shows its advantages over base and skeletal models. ► High efficiency and great reduction of CPU runtime are achieved through 4-node solver. ► Increasing ISAT memory from 0.1 to 2 GB reduces the CPU runtime by almost 35%. ► Combustion and soot processes are predicted well with minimal computational cost. - Abstract: In the present study, in-cylinder diesel combustion simulation was performed with parallel processing on an Intel Xeon Quad-Core platform to allow both fluid dynamics and chemical kinetics of the surrogate diesel fuel model to be solved simultaneously on multiple processors. Here, Cartesian Z-Coordinate was selected as the most appropriate partitioning algorithm since it computationally bisects the domain such that the dynamic load associated with fuel particle tracking was evenly distributed during parallel computations. Other variables examined included number of compute nodes, chemistry sizes and in situ adaptive tabulation (ISAT) parameters. Based on the performance benchmarking test conducted, parallel configuration of 4-compute node was found to reduce the computational runtime most efficiently whereby a parallel efficiency of up to 75.4% was achieved. The simulation results also indicated that accuracy level was insensitive to the number of partitions or the partitioning algorithms. The effect of reducing the number of species on computational runtime was observed to be more significant than reducing the number of reactions. Besides, the study showed that an increase in the ISAT maximum storage of up to 2 GB reduced the computational runtime by 50%. Also, the ISAT error tolerance of 10 −3 was chosen to strike a balance between results accuracy and computational runtime. The optimised parameters in parallel processing and ISAT, as well as the use of the in-house reduced chemistry model allowed accurate

Computationally Efficient Clustering of Audio-Visual Meeting Data

Science.gov (United States)

Hung, Hayley; Friedland, Gerald; Yeo, Chuohao

This chapter presents novel computationally efficient algorithms to extract semantically meaningful acoustic and visual events related to each of the participants in a group discussion using the example of business meeting recordings. The recording setup involves relatively few audio-visual sensors, comprising a limited number of cameras and microphones. We first demonstrate computationally efficient algorithms that can identify who spoke and when, a problem in speech processing known as speaker diarization. We also extract visual activity features efficiently from MPEG4 video by taking advantage of the processing that was already done for video compression. Then, we present a method of associating the audio-visual data together so that the content of each participant can be managed individually. The methods presented in this article can be used as a principal component that enables many higher-level semantic analysis tasks needed in search, retrieval, and navigation.

Computational Properties of the Hippocampus Increase the Efficiency of Goal-Directed Foraging through Hierarchical Reinforcement Learning

Directory of Open Access Journals (Sweden)

Eric Chalmers

2016-12-01

Full Text Available The mammalian brain is thought to use a version of Model-based Reinforcement Learning (MBRL to guide goal-directed behavior, wherein animals consider goals and make plans to acquire desired outcomes. However, conventional MBRL algorithms do not fully explain animals’ ability to rapidly adapt to environmental changes, or learn multiple complex tasks. They also require extensive computation, suggesting that goal-directed behavior is cognitively expensive. We propose here that key features of processing in the hippocampus support a flexible MBRL mechanism for spatial navigation that is computationally efficient and can adapt quickly to change. We investigate this idea by implementing a computational MBRL framework that incorporates features inspired by computational properties of the hippocampus: a hierarchical representation of space, forward sweeps through future spatial trajectories, and context-driven remapping of place cells. We find that a hierarchical abstraction of space greatly reduces the computational load (mental effort required for adaptation to changing environmental conditions, and allows efficient scaling to large problems. It also allows abstract knowledge gained at high levels to guide adaptation to new obstacles. Moreover, a context-driven remapping mechanism allows learning and memory of multiple tasks. Simulating dorsal or ventral hippocampal lesions in our computational framework qualitatively reproduces behavioral deficits observed in rodents with analogous lesions. The framework may thus embody key features of how the brain organizes model-based RL to efficiently solve navigation and other difficult tasks.

Topology Optimisation for Coupled Convection Problems

DEFF Research Database (Denmark)

Alexandersen, Joe

This thesis deals with topology optimisation for coupled convection problems. The aim is to extend and apply topology optimisation to steady-state conjugate heat transfer problems, where the heat conduction equation governs the heat transfer in a solid and is coupled to thermal transport...... in a surrounding uid, governed by a convection-diffusion equation, where the convective velocity field is found from solving the isothermal incompressible steady-state Navier-Stokes equations. Topology optimisation is also applied to steady-state natural convection problems. The modelling is done using stabilised...... finite elements, the formulation and implementation of which was done partly during a special course as prepatory work for this thesis. The formulation is extended with a Brinkman friction term in order to facilitate the topology optimisation of fluid flow and convective cooling problems. The derived...

On efficiency of fire simulation realization: parallelization with greater number of computational meshes

Science.gov (United States)

Valasek, Lukas; Glasa, Jan

2017-12-01

Current fire simulation systems are capable to utilize advantages of high-performance computer (HPC) platforms available and to model fires efficiently in parallel. In this paper, efficiency of a corridor fire simulation on a HPC computer cluster is discussed. The parallel MPI version of Fire Dynamics Simulator is used for testing efficiency of selected strategies of allocation of computational resources of the cluster using a greater number of computational cores. Simulation results indicate that if the number of cores used is not equal to a multiple of the total number of cluster node cores there are allocation strategies which provide more efficient calculations.

Algorithme intelligent d'optimisation d'un design structurel de grande envergure

Science.gov (United States)

Dominique, Stephane

The implementation of an automated decision support system in the field of design and structural optimisation can give a significant advantage to any industry working on mechanical designs. Indeed, by providing solution ideas to a designer or by upgrading existing design solutions while the designer is not at work, the system may reduce the project cycle time, or allow more time to produce a better design. This thesis presents a new approach to automate a design process based on Case-Based Reasoning (CBR), in combination with a new genetic algorithm named Genetic Algorithm with Territorial core Evolution (GATE). This approach was developed in order to reduce the operating cost of the process. However, as the system implementation cost is quite expensive, the approach is better suited for large scale design problem, and particularly for design problems that the designer plans to solve for many different specification sets. First, the CBR process uses a databank filled with every known solution to similar design problems. Then, the closest solutions to the current problem in term of specifications are selected. After this, during the adaptation phase, an artificial neural network (ANN) interpolates amongst known solutions to produce an additional solution to the current problem using the current specifications as inputs. Each solution produced and selected by the CBR is then used to initialize the population of an island of the genetic algorithm. The algorithm will optimise the solution further during the refinement phase. Using progressive refinement, the algorithm starts using only the most important variables for the problem. Then, as the optimisation progress, the remaining variables are gradually introduced, layer by layer. The genetic algorithm that is used is a new algorithm specifically created during this thesis to solve optimisation problems from the field of mechanical device structural design. The algorithm is named GATE, and is essentially a real number

Thermodynamic optimisation and analysis of four Kalina cycle layouts for high temperature applications

DEFF Research Database (Denmark)

Modi, Anish; Haglind, Fredrik

2015-01-01

The Kalina cycle has seen increased interest in the last few years as an efficient alternative to the conventional steam Rankine cycle. However, the available literature gives little information on the algorithms to solve or optimise this inherently complex cycle. This paper presents a detailed a...

Dose to population as a metric in the design of optimised exposure control in digital mammography

International Nuclear Information System (INIS)

Klausz, R.; Shramchenko, N.

2005-01-01

This paper describes a methods for automatic optimisation of parameter (AOP) in digital mammography systems. Using a model of the image chain, contrast to noise ratio (CNR) and average glandular dose (AGD) are computed for possible X-ray parameters and breast types. The optimisation process consists of the determination of the operating points providing the lowest possible AGD for each CNR level and breast type. The proposed metric for the dose used in the design of an AOP mode is the resulting dose to the population, computed by averaging the AGD values over the distribution of breast types in the population. This method has been applied to the automatic exposure control of new digital mammography equipment. Breast thickness and composition are estimated from a low dose pre-exposure and used to index tables containing sets of optimised operating points. The resulting average dose to the population ranges from a level comparable to state-of-the-art screen/film mammography to a reduction by a factor of two. Using this method, both CNR and dose are kept under control for all breast types, taking into consideration both individual and collective risk. (authors)

Risk-informed optimisation of railway tracks inspection and maintenance procedures

International Nuclear Information System (INIS)

Podofillini, Luca; Zio, Enrico; Vatn, Jorn

2006-01-01

Nowadays, efforts are being made by the railway industry for the application of reliability-based and risk-informed approaches to maintenance optimisation of railway infrastructures, with the aim of reducing the operation and maintenance expenditures while still assuring high safety standards. In particular, in this paper, we address the use of ultrasonic inspection cars and develop a methodology for the determination of an optimal strategy for their use. A model is developed to calculate the risks and costs associated with an inspection strategy, giving credit to the realistic issues of the rail failure process and including the actual inspection and maintenance procedures followed by the railway company. A multi-objective optimisation viewpoint is adopted in an effort to optimise inspection and maintenance procedures with respect to both economical and safety-related aspects. More precisely, the objective functions here considered are such to drive the search towards solutions characterized by low expenditures and low derailment probability. The optimisation is performed by means of a genetic algorithm. The work has been carried out within a study of the Norwegian National Rail Administration (Jernbaneverket)

Computer-Aided Test Flow in Core-Based Design

NARCIS (Netherlands)

Zivkovic, V.; Tangelder, R.J.W.T.; Kerkhoff, Hans G.

2000-01-01

This paper copes with the efficient test-pattern generation in a core-based design. A consistent Computer-Aided Test (CAT) flow is proposed based on the required core-test strategy. It generates a test-pattern set for the embedded cores with high fault coverage and low DfT area overhead. The CAT

Optimised cantilever biosensor with piezoresistive read-out

DEFF Research Database (Denmark)

Rasmussen, Peter; Thaysen, J.; Hansen, Ole

2003-01-01

We present a cantilever-based biochemical sensor with piezoresistive read-out which has been optimised for measuring surface stress. The resistors and the electrical wiring on the chip are encapsulated in low-pressure chemical vapor deposition (LPCVD) silicon nitride, so that the chip is well sui...

An Efficient Sleepy Algorithm for Particle-Based Fluids

Directory of Open Access Journals (Sweden)

Xiao Nie

2014-01-01

Full Text Available We present a novel Smoothed Particle Hydrodynamics (SPH based algorithm for efficiently simulating compressible and weakly compressible particle fluids. Prior particle-based methods simulate all fluid particles; however, in many cases some particles appearing to be at rest can be safely ignored without notably affecting the fluid flow behavior. To identify these particles, a novel sleepy strategy is introduced. By utilizing this strategy, only a portion of the fluid particles requires computational resources; thus an obvious performance gain can be achieved. In addition, in order to resolve unphysical clumping issue due to tensile instability in SPH based methods, a new artificial repulsive force is provided. We demonstrate that our approach can be easily integrated with existing SPH based methods to improve the efficiency without sacrificing visual quality.

The optimisation study of tbp synthesis process by phosphoric acid

International Nuclear Information System (INIS)

Amedjkouh, A.; Attou, M.; Azzouz, A.; Zaoui, B.

1995-07-01

The present work deals with the optimisation study of TBP synthesis process by phosphoric acid. This way of synthesis is more advantageous than POCL3 or P2O5 as phosphatant agents. these latters are toxic and dangerous for the environnement. The optimisation study is based on a series of 16 experiences taking into account the range of variation of the following parameters : temperature, pressure, reagents mole ratio, promoter content. the yield calculation is based on the randomisation of an equation including all parameters. the resolution of this equation gave a 30% TBP molar ratio. this value is in agreement with that of experimental data

Assessment of grid optimisation measures for the German transmission grid using open source grid data

Science.gov (United States)

Böing, F.; Murmann, A.; Pellinger, C.; Bruckmeier, A.; Kern, T.; Mongin, T.

2018-02-01

The expansion of capacities in the German transmission grid is a necessity for further integration of renewable energy sources into the electricity sector. In this paper, the grid optimisation measures ‘Overhead Line Monitoring’, ‘Power-to-Heat’ and ‘Demand Response in the Industry’ are evaluated and compared against conventional grid expansion for the year 2030. Initially, the methodical approach of the simulation model is presented and detailed descriptions of the grid model and the used grid data, which partly originates from open-source platforms, are provided. Further, this paper explains how ‘Curtailment’ and ‘Redispatch’ can be reduced by implementing grid optimisation measures and how the depreciation of economic costs can be determined considering construction costs. The developed simulations show that the conventional grid expansion is more efficient and implies more grid relieving effects than the evaluated grid optimisation measures.

Effectiveness of an implementation optimisation intervention aimed at increasing parent engagement in HENRY, a childhood obesity prevention programme - the Optimising Family Engagement in HENRY (OFTEN) trial: study protocol for a randomised controlled trial.

Science.gov (United States)

Bryant, Maria; Burton, Wendy; Cundill, Bonnie; Farrin, Amanda J; Nixon, Jane; Stevens, June; Roberts, Kim; Foy, Robbie; Rutter, Harry; Hartley, Suzanne; Tubeuf, Sandy; Collinson, Michelle; Brown, Julia

2017-01-24

Family-based interventions to prevent childhood obesity depend upon parents' taking action to improve diet and other lifestyle behaviours in their families. Programmes that attract and retain high numbers of parents provide an enhanced opportunity to improve public health and are also likely to be more cost-effective than those that do not. We have developed a theory-informed optimisation intervention to promote parent engagement within an existing childhood obesity prevention group programme, HENRY (Health Exercise Nutrition for the Really Young). Here, we describe a proposal to evaluate the effectiveness of this optimisation intervention in regard to the engagement of parents and cost-effectiveness. The Optimising Family Engagement in HENRY (OFTEN) trial is a cluster randomised controlled trial being conducted across 24 local authorities (approximately 144 children's centres) which currently deliver HENRY programmes. The primary outcome will be parental enrolment and attendance at the HENRY programme, assessed using routinely collected process data. Cost-effectiveness will be presented in terms of primary outcomes using acceptability curves and through eliciting the willingness to pay for the optimisation from HENRY commissioners. Secondary outcomes include the longitudinal impact of the optimisation, parent-reported infant intake of fruits and vegetables (as a proxy to compliance) and other parent-reported family habits and lifestyle. This innovative trial will provide evidence on the implementation of a theory-informed optimisation intervention to promote parent engagement in HENRY, a community-based childhood obesity prevention programme. The findings will be generalisable to other interventions delivered to parents in other community-based environments. This research meets the expressed needs of commissioners, children's centres and parents to optimise the potential impact that HENRY has on obesity prevention. A subsequent cluster randomised controlled pilot

Optimisation of Protection as applicable to geological disposal: the ICRP view

International Nuclear Information System (INIS)

Weiss, W.

2010-01-01

Wolfgang Weiss (BfS), vice-chair of ICRP Committee 4, recalled that the role of optimisation is to select the best protection options under the prevailing circumstances based on scientific considerations, societal concerns and ethical aspects as well as considerations of transparency. An important role of the concept of optimisation of protection is to foster a 'safety culture' and thereby to engender a state of thinking in everyone responsible for control of radiation exposures, such that they are continuously asking themselves the question, 'Have I done all that I reasonably can to avoid or reduce these doses?' Clearly, the answer to this question is a matter of judgement and necessitates co-operation between all parties involved and, as a minimum, the operating management and the regulatory agencies, but the dialogue would be more complete if other stakeholders were also involved. What kinds of checks and balances or factors would be needed to be considered for an 'optimal' system? Can indicators be identified? Quantitative methods may provide input to this dialogue but they should never be the sole input. The ICRP considers that the parameters to take into account include also social considerations and values, environmental considerations, as well as technical and economic considerations. Wolfgang Weiss approached the question of the distinction to be made between system optimisation (in the sense of taking account of social and economic as well as of all types of hazards) and optimisation of radiological protection. The position of the ICRP is that the system of protection that it proposes is based on both science (quantification of the health risk) and value judgement (what is an acceptable risk?) and optimisation is the recommended process to integrate both aspects. Indeed, there has been evolution since the old system of intervention levels to the new system, whereby, even if the level of the dose or risk (which is called constraint in ICRP-81 ) is met

Methods for Optimisation of the Laser Cutting Process

DEFF Research Database (Denmark)

Dragsted, Birgitte

This thesis deals with the adaptation and implementation of various optimisation methods, in the field of experimental design, for the laser cutting process. The problem in optimising the laser cutting process has been defined and a structure for at Decision Support System (DSS......) for the optimisation of the laser cutting process has been suggested. The DSS consists of a database with the currently used and old parameter settings. Also one of the optimisation methods has been implemented in the DSS in order to facilitate the optimisation procedure for the laser operator. The Simplex Method has...... been adapted in two versions. A qualitative one, that by comparing the laser cut items optimise the process and a quantitative one that uses a weighted quality response in order to achieve a satisfactory quality and after that maximises the cutting speed thus increasing the productivity of the process...

High efficiency USC power plant - present status and future potential

Energy Technology Data Exchange (ETDEWEB)

Blum, R [Faelleskemikerne I/S Fynsvaerket (Denmark); Hald, J [Elsam/Elkraft/TU Denmark (Denmark)

1999-12-31

Increasing demand for energy production with low impact on the environment and minimised fuel consumption can be met with high efficient coal fired power plants with advanced steam parameters. An important key to this improvement is the development of high temperature materials with optimised mechanical strength. Based on the results of more than ten years of development a coal fired power plant with an efficiency above 50 % can now be realised. Future developments focus on materials which enable an efficiency of 52-55 %. (orig.) 25 refs.

High efficiency USC power plant - present status and future potential

Energy Technology Data Exchange (ETDEWEB)

Blum, R. [Faelleskemikerne I/S Fynsvaerket (Denmark); Hald, J. [Elsam/Elkraft/TU Denmark (Denmark)

1998-12-31

Increasing demand for energy production with low impact on the environment and minimised fuel consumption can be met with high efficient coal fired power plants with advanced steam parameters. An important key to this improvement is the development of high temperature materials with optimised mechanical strength. Based on the results of more than ten years of development a coal fired power plant with an efficiency above 50 % can now be realised. Future developments focus on materials which enable an efficiency of 52-55 %. (orig.) 25 refs.

Optimisation of multiplet identifier processing on a PLAYSTATION® 3

Science.gov (United States)

Hattori, Masami; Mizuno, Takashi

2010-02-01

To enable high-performance computing (HPC) for applications with large datasets using a Sony® PLAYSTATION® 3 (PS3™) video game console, we configured a hybrid system consisting of a Windows® PC and a PS3™. To validate this system, we implemented the real-time multiplet identifier (RTMI) application, which identifies multiplets of microearthquakes in terms of the similarity of their waveforms. The cross-correlation computation, which is a core algorithm of the RTMI application, was optimised for the PS3™ platform, while the rest of the computation, including data input and output remained on the PC. With this configuration, the core part of the algorithm ran 69 times faster than the original program, accelerating total computation speed more than five times. As a result, the system processed up to 2100 total microseismic events, whereas the original implementation had a limit of 400 events. These results indicate that this system enables high-performance computing for large datasets using the PS3™, as long as data transfer time is negligible compared with computation time.

Operational Radiological Protection and Aspects of Optimisation

International Nuclear Information System (INIS)

Lazo, E.; Lindvall, C.G.

2005-01-01

Since 1992, the Nuclear Energy Agency (NEA), along with the International Atomic Energy Agency (IAEA), has sponsored the Information System on Occupational Exposure (ISOE). ISOE collects and analyses occupational exposure data and experience from over 400 nuclear power plants around the world and is a forum for radiological protection experts from both nuclear power plants and regulatory authorities to share lessons learned and best practices in the management of worker radiation exposures. In connection to the ongoing work of the International Commission on Radiological Protection (ICRP) to develop new recommendations, the ISOE programme has been interested in how the new recommendations would affect operational radiological protection application at nuclear power plants. Bearing in mind that the ICRP is developing, in addition to new general recommendations, a new recommendation specifically on optimisation, the ISOE programme created a working group to study the operational aspects of optimisation, and to identify the key factors in optimisation that could usefully be reflected in ICRP recommendations. In addition, the Group identified areas where further ICRP clarification and guidance would be of assistance to practitioners, both at the plant and the regulatory authority. The specific objective of this ISOE work was to provide operational radiological protection input, based on practical experience, to the development of new ICRP recommendations, particularly in the area of optimisation. This will help assure that new recommendations will best serve the needs of those implementing radiation protection standards, for the public and for workers, at both national and international levels. (author)

A framework for inverse planning of beam-on times for 3D small animal radiotherapy using interactive multi-objective optimisation

International Nuclear Information System (INIS)

Balvert, Marleen; Den Hertog, Dick; Van Hoof, Stefan J; Granton, Patrick V; Trani, Daniela; Hoffmann, Aswin L; Verhaegen, Frank

2015-01-01

Advances in precision small animal radiotherapy hardware enable the delivery of increasingly complicated dose distributions on the millimeter scale. Manual creation and evaluation of treatment plans becomes difficult or even infeasible with an increasing number of degrees of freedom for dose delivery and available image data. The goal of this work is to develop an optimisation model that determines beam-on times for a given beam configuration, and to assess the feasibility and benefits of an automated treatment planning system for small animal radiotherapy.The developed model determines a Pareto optimal solution using operator-defined weights for a multiple-objective treatment planning problem. An interactive approach allows the planner to navigate towards, and to select the Pareto optimal treatment plan that yields the most preferred trade-off of the conflicting objectives. This model was evaluated using four small animal cases based on cone-beam computed tomography images. Resulting treatment plan quality was compared to the quality of manually optimised treatment plans using dose-volume histograms and metrics.Results show that the developed framework is well capable of optimising beam-on times for 3D dose distributions and offers several advantages over manual treatment plan optimisation. For all cases but the simple flank tumour case, a similar amount of time was needed for manual and automated beam-on time optimisation. In this time frame, manual optimisation generates a single treatment plan, while the inverse planning system yields a set of Pareto optimal solutions which provides quantitative insight on the sensitivity of conflicting objectives. Treatment planning automation decreases the dependence on operator experience and allows for the use of class solutions for similar treatment scenarios. This can shorten the time required for treatment planning and therefore increase animal throughput. In addition, this can improve treatment standardisation and

IMPROVING TACONITE PROCESSING PLANT EFFICIENCY BY COMPUTER SIMULATION, Final Report

Energy Technology Data Exchange (ETDEWEB)

William M. Bond; Salih Ersayin

2007-03-30

This project involved industrial scale testing of a mineral processing simulator to improve the efficiency of a taconite processing plant, namely the Minorca mine. The Concentrator Modeling Center at the Coleraine Minerals Research Laboratory, University of Minnesota Duluth, enhanced the capabilities of available software, Usim Pac, by developing mathematical models needed for accurate simulation of taconite plants. This project provided funding for this technology to prove itself in the industrial environment. As the first step, data representing existing plant conditions were collected by sampling and sample analysis. Data were then balanced and provided a basis for assessing the efficiency of individual devices and the plant, and also for performing simulations aimed at improving plant efficiency. Performance evaluation served as a guide in developing alternative process strategies for more efficient production. A large number of computer simulations were then performed to quantify the benefits and effects of implementing these alternative schemes. Modification of makeup ball size was selected as the most feasible option for the target performance improvement. This was combined with replacement of existing hydrocyclones with more efficient ones. After plant implementation of these modifications, plant sampling surveys were carried out to validate findings of the simulation-based study. Plant data showed very good agreement with the simulated data, confirming results of simulation. After the implementation of modifications in the plant, several upstream bottlenecks became visible. Despite these bottlenecks limiting full capacity, concentrator energy improvement of 7% was obtained. Further improvements in energy efficiency are expected in the near future. The success of this project demonstrated the feasibility of a simulation-based approach. Currently, the Center provides simulation-based service to all the iron ore mining companies operating in northern

Optimised resource construction for verifiable quantum computation

International Nuclear Information System (INIS)

Kashefi, Elham; Wallden, Petros

2017-01-01

Recent developments have brought the possibility of achieving scalable quantum networks and quantum devices closer. From the computational point of view these emerging technologies become relevant when they are no longer classically simulatable. Hence a pressing challenge is the construction of practical methods to verify the correctness of the outcome produced by universal or non-universal quantum devices. A promising approach that has been extensively explored is the scheme of verification via encryption through blind quantum computation. We present here a new construction that simplifies the required resources for any such verifiable protocol. We obtain an overhead that is linear in the size of the input (computation), while the security parameter remains independent of the size of the computation and can be made exponentially small (with a small extra cost). Furthermore our construction is generic and could be applied to any universal or non-universal scheme with a given underlying graph. (paper)

Extending Particle Swarm Optimisers with Self-Organized Criticality

DEFF Research Database (Denmark)

Løvbjerg, Morten; Krink, Thiemo

2002-01-01

Particle swarm optimisers (PSOs) show potential in function optimisation, but still have room for improvement. Self-organized criticality (SOC) can help control the PSO and add diversity. Extending the PSO with SOC seems promising reaching faster convergence and better solutions.......Particle swarm optimisers (PSOs) show potential in function optimisation, but still have room for improvement. Self-organized criticality (SOC) can help control the PSO and add diversity. Extending the PSO with SOC seems promising reaching faster convergence and better solutions....

Regulation of Voltage and Frequency in Solid Oxide Fuel Cell-Based Autonomous Microgrids Using the Whales Optimisation Algorithm

Directory of Open Access Journals (Sweden)

Sajid Hussain Qazi

2018-05-01

Full Text Available This study explores the Whales Optimization Algorithm (WOA-based PI controller for regulating the voltage and frequency of an inverter-based autonomous microgrid (MG. The MG comprises two 50 kW DGs (solid oxide fuel cells, SOFCs interfaced using a power electronics-based voltage source inverter (VSI with a 120-kV conventional grid. Four PI controller schemes for the MG are implemented: (i stationary PI controller with fixed gain values (Kp and Ki, (ii PSO tuned PI controller, (iii GWO tuned PI controller, and (iv WOA tuned PI controller. The performance of these controllers is evaluated by monitoring the system voltage and frequency during the transition of MG operation mode and changes in the load. The MATLAB/SIMULINK tool is utilised to design the proposed model of grid-tied MG alongside the MATLAB m-file to apply an optimisation technique. The simulation results show that the WOA-based PI controller which optimises the control parameters, achieve 62.7% and 59% better results for voltage and frequency regulation, respectively. The eigenvalue analysis is also provided to check the stability of the proposed controller. Furthermore, the proposed system also satisfies the limits specified in IEEE-1547-2003 for voltage and frequency.

Economic optimisation of a wind power plant for isolated locations

International Nuclear Information System (INIS)

Fortunato, B.; Mummolo, G.; Cavallera, G.

1997-01-01

This paper presents a model of a wind power plant for isolated locations composed of a vertical axis wind turbine connected to a self-excited induction generator operating at constant voltage and frequency; a back-up diesel generator and a battery system are moreover included in the system. Constant voltage and frequency are obtained only by controlling the generator appropriately. The control system is supposed to be optimised so that the system operates at the highest efficiency. In order to improve the total efficiency even further, a gear-box to vary the gear transmission ratio between the turbine and the generator has been considered. A ''Monte Carlo'' type simulation has been used to analyse the operation of that system over a one year period. The model is based on a probability density function of the wind speed derived by statistical data concerning a given location and on the probabilistic curve of the load required by an isolated location. The cost per kW h for different dimensions of the main components has been evaluated and the optimum configuration has been identified. (author)

Projection computation based on pixel in simultaneous algebraic reconstruction technique

International Nuclear Information System (INIS)

Wang Xu; Chen Zhiqiang; Xiong Hua; Zhang Li

2005-01-01

SART is an important arithmetic of image reconstruction, in which the projection computation takes over half of the reconstruction time. An efficient way to compute projection coefficient matrix together with memory optimization is presented in this paper. Different from normal method, projection lines are located based on every pixel, and the following projection coefficient computation can make use of the results. Correlation of projection lines and pixels can be used to optimize the computation. (authors)

Improving Vector Evaluated Particle Swarm Optimisation by incorporating nondominated solutions.

Science.gov (United States)

Lim, Kian Sheng; Ibrahim, Zuwairie; Buyamin, Salinda; Ahmad, Anita; Naim, Faradila; Ghazali, Kamarul Hawari; Mokhtar, Norrima

2013-01-01

The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. This algorithm optimises one objective using a swarm of particles where their movements are guided by the best solution found by another swarm. However, the best solution of a swarm is only updated when a newly generated solution has better fitness than the best solution at the objective function optimised by that swarm, yielding poor solutions for the multiobjective optimisation problems. Thus, an improved Vector Evaluated Particle Swarm Optimisation algorithm is introduced by incorporating the nondominated solutions as the guidance for a swarm rather than using the best solution from another swarm. In this paper, the performance of improved Vector Evaluated Particle Swarm Optimisation algorithm is investigated using performance measures such as the number of nondominated solutions found, the generational distance, the spread, and the hypervolume. The results suggest that the improved Vector Evaluated Particle Swarm Optimisation algorithm has impressive performance compared with the conventional Vector Evaluated Particle Swarm Optimisation algorithm.

Occupancy-based illumination control of LED lighting systems

NARCIS (Netherlands)

Caicedo Fernandez, D.R.; Pandharipande, A.; Leus, G.

2011-01-01

Light emitting diode (LED)-based systems are considered to be the future of lighting. We consider the problem of energy-efficient illumination control of such systems. Energy-efficient system design is based on two aspects: localised information on occupancy and optimisation of dimming levels of the

Design of Circularly-Polarised, Crossed Drooping Dipole, Phased Array Antenna Using Genetic Algorithm Optimisation

DEFF Research Database (Denmark)

Larsen, Niels Vesterdal

2007-01-01

A printed drooping dipole array is designed and constructed. The design is based on a genetic algorithm optimisation procedure used in conjunction with the software programme AWAS. By optimising the array G/T for specific combinations of scan angles and frequencies an optimum design is obtained...

Robust fault detection of linear systems using a computationally efficient set-membership method

DEFF Research Database (Denmark)

Tabatabaeipour, Mojtaba; Bak, Thomas

2014-01-01

In this paper, a computationally efficient set-membership method for robust fault detection of linear systems is proposed. The method computes an interval outer-approximation of the output of the system that is consistent with the model, the bounds on noise and disturbance, and the past measureme...... is trivially parallelizable. The method is demonstrated for fault detection of a hydraulic pitch actuator of a wind turbine. We show the effectiveness of the proposed method by comparing our results with two zonotope-based set-membership methods....

Optimising mobile phase composition, its flow-rate and column temperature in HPLC using taboo search.

Science.gov (United States)

Guillaume, Y C; Peyrin, E

2000-03-06

A chemometric methodology is proposed to study the separation of seven p-hydroxybenzoic esters in reversed phase liquid chromatography (RPLC). Fifteen experiments were found to be necessary to find a mathematical model which linked a novel chromatographic response function (CRF) with the column temperature, the water fraction in the mobile phase and its flow rate. The CRF optimum was determined using a new algorithm based on Glover's taboo search (TS). A flow-rate of 0.9 ml min(-1) with a water fraction of 0.64 in the ACN-water mixture and a column temperature of 10 degrees C gave the most efficient separation conditions. The usefulness of TS was compared with the pure random search (PRS) and simplex search (SS). As demonstrated by calculations, the algorithm avoids entrapment in local minima and continues the search to give a near-optimal final solution. Unlike other methods of global optimisation, this procedure is generally applicable, easy to implement, derivative free, conceptually simple and could be used in the future for much more complex optimisation problems.

A biophysical approach to the optimisation of dendritic-tumour cell electrofusion

International Nuclear Information System (INIS)

Sukhorukov, Vladimir L.; Reuss, Randolph; Endter, Joerg M.; Fehrmann, Steffen; Katsen-Globa, Alisa; Gessner, Petra; Steinbach, Andrea; Mueller, Kilian J.; Karpas, Abraham; Zimmermann, Ulrich; Zimmermann, Heiko

2006-01-01

Electrofusion of tumour and dendritic cells (DCs) is a promising approach for production of DC-based anti-tumour vaccines. Although human DCs are well characterised immunologically, little is known about their biophysical properties, including dielectric and osmotic parameters, both of which are essential for the development of efficient electrofusion protocols. In the present study, human DCs from the peripheral blood along with a tumour cell line used as a model fusion partner were examined by means of time-resolved cell volumetry and electrorotation. Based on the biophysical cell data, the electrofusion protocol could be rapidly optimised with respect to the sugar composition of the fusion medium, duration of hypotonic treatment, frequency range for stable cell alignment, and field strengths of breakdown pulses triggering membrane fusion. The hypotonic electrofusion consistently gave a tumour-DC hybrid rate of up to 19%, as determined by counting dually labelled fluorescent hybrids in a microscope. This fusion rate is nearly twice as high as that usually reported in the literature for isotonic media. The experimental findings and biophysical approach presented here are generally useful for the development of efficient electrofusion protocols, especially for rare and valuable human cells

Optimisation based design of a district energy system for an eco-town in the United Kingdom

International Nuclear Information System (INIS)

Weber, C.; Shah, N.

2011-01-01

The reduction of CO 2 emissions linked with human activities (mainly energy services and transport), together with the increased use of renewable energies, remain high priorities on various political agendas. However, considering the increased consumption of energy services (especially electricity), and the stochastic nature of some of the most promising renewable energies (wind for instance), the challenge is to find the optimal mix of technologies that will provide the energy services, without increasing the CO 2 emissions, but nonetheless ensuring reliability of supply. The focus of this paper is to present the DESDOP tool, based on mixed integer linear optimisation technics, that helps giving insight in the optimal mix of technologies that will simultaneously help decrease the emissions while at the same time guarantee resilience of supply. The results show that while it is not yet possible to avoid electricity from the grid completely (hence nuclear or fossil fuel), CO 2 reductions up to 20%, at no extra costs compared to the business-as-usual case, are easily achievable. -- Research highlights: → Mixed integer linear optimisation techniques are a powerful tool to design and optimise district energy systems. → Integrated energy conversion systems (especially combination of CHPs and heat-pumps) allow CO2 reductions for energy services of at least 20% at no extra-costs compared to business-as-usual (grid and boiler). → While the grid (hence nuclear and/or fossil fuels) cannot be avoided as long as electricity storage doesn't come of age, the criticism of anti-wind lobbyists regarding the ineffectiveness of wind power could not be verified.

Multi-Dimensional Bitmap Indices for Optimising Data Access within Object Oriented Databases at CERN

CERN Document Server

Stockinger, K

2001-01-01

Efficient query processing in high-dimensional search spaces is an important requirement for many analysis tools. In the literature on index data structures one can find a wide range of methods for optimising database access. In particular, bitmap indices have recently gained substantial popularity in data warehouse applications with large amounts of read mostly data. Bitmap indices are implemented in various commercial database products and are used for querying typical business applications. However, scientific data that is mostly characterised by non-discrete attribute values cannot be queried efficiently by the techniques currently supported. In this thesis we propose a novel access method based on bitmap indices that efficiently handles multi-dimensional queries against typical scientific data. The algorithm is called GenericRangeEval and is an extension of a bitmap index for discrete attribute values. By means of a cost model we study the performance of queries with various selectivities against uniform...

Efficient and Flexible Computation of Many-Electron Wave Function Overlaps.

Science.gov (United States)

Plasser, Felix; Ruckenbauer, Matthias; Mai, Sebastian; Oppel, Markus; Marquetand, Philipp; González, Leticia

2016-03-08

A new algorithm for the computation of the overlap between many-electron wave functions is described. This algorithm allows for the extensive use of recurring intermediates and thus provides high computational efficiency. Because of the general formalism employed, overlaps can be computed for varying wave function types, molecular orbitals, basis sets, and molecular geometries. This paves the way for efficiently computing nonadiabatic interaction terms for dynamics simulations. In addition, other application areas can be envisaged, such as the comparison of wave functions constructed at different levels of theory. Aside from explaining the algorithm and evaluating the performance, a detailed analysis of the numerical stability of wave function overlaps is carried out, and strategies for overcoming potential severe pitfalls due to displaced atoms and truncated wave functions are presented.

Efficient Minimum-Phase Prefilter Computation Using Fast QL-Factorization

DEFF Research Database (Denmark)

Hansen, Morten; Christensen, Lars P.B.

2009-01-01

This paper presents a novel approach for computing both the minimum-phase filter and the associated all-pass filter in a computationally efficient way using the fast QL-factorization. A desirable property of this approach is that the complexity is independent on the size of the matrix which is QL...

Paper-Based and Computer-Based Concept Mappings: The Effects on Computer Achievement, Computer Anxiety and Computer Attitude

Science.gov (United States)

Erdogan, Yavuz

2009-01-01

The purpose of this paper is to compare the effects of paper-based and computer-based concept mappings on computer hardware achievement, computer anxiety and computer attitude of the eight grade secondary school students. The students were randomly allocated to three groups and were given instruction on computer hardware. The teaching methods used…

On the Design of Energy-Efficient Location Tracking Mechanism in Location-Aware Computing

Directory of Open Access Journals (Sweden)

MoonBae Song

2005-01-01

Full Text Available The battery, in contrast to other hardware, is not governed by Moore's Law. In location-aware computing, power is a very limited resource. As a consequence, recently, a number of promising techniques in various layers have been proposed to reduce the energy consumption. The paper considers the problem of minimizing the energy used to track the location of mobile user over a wireless link in mobile computing. Energy-efficient location update protocol can be done by reducing the number of location update messages as possible and switching off as long as possible. This can be achieved by the concept of mobility-awareness we propose. For this purpose, this paper proposes a novel mobility model, called state-based mobility model (SMM to provide more generalized framework for both describing the mobility and updating location information of complexly moving objects. We also introduce the state-based location update protocol (SLUP based on this mobility model. An extensive experiment on various synthetic datasets shows that the proposed method improves the energy efficiency by 2 ∼ 3 times with the additional 10% of imprecision cost.

Multi-objective optimisation of aircraft flight trajectories in the ATM and avionics context

Science.gov (United States)

Gardi, Alessandro; Sabatini, Roberto; Ramasamy, Subramanian

2016-05-01

The continuous increase of air transport demand worldwide and the push for a more economically viable and environmentally sustainable aviation are driving significant evolutions of aircraft, airspace and airport systems design and operations. Although extensive research has been performed on the optimisation of aircraft trajectories and very efficient algorithms were widely adopted for the optimisation of vertical flight profiles, it is only in the last few years that higher levels of automation were proposed for integrated flight planning and re-routing functionalities of innovative Communication Navigation and Surveillance/Air Traffic Management (CNS/ATM) and Avionics (CNS+A) systems. In this context, the implementation of additional environmental targets and of multiple operational constraints introduces the need to efficiently deal with multiple objectives as part of the trajectory optimisation algorithm. This article provides a comprehensive review of Multi-Objective Trajectory Optimisation (MOTO) techniques for transport aircraft flight operations, with a special focus on the recent advances introduced in the CNS+A research context. In the first section, a brief introduction is given, together with an overview of the main international research initiatives where this topic has been studied, and the problem statement is provided. The second section introduces the mathematical formulation and the third section reviews the numerical solution techniques, including discretisation and optimisation methods for the specific problem formulated. The fourth section summarises the strategies to articulate the preferences and to select optimal trajectories when multiple conflicting objectives are introduced. The fifth section introduces a number of models defining the optimality criteria and constraints typically adopted in MOTO studies, including fuel consumption, air pollutant and noise emissions, operational costs, condensation trails, airspace and airport operations

SmartVeh: Secure and Efficient Message Access Control and Authentication for Vehicular Cloud Computing.

Science.gov (United States)

Huang, Qinlong; Yang, Yixian; Shi, Yuxiang

2018-02-24

With the growing number of vehicles and popularity of various services in vehicular cloud computing (VCC), message exchanging among vehicles under traffic conditions and in emergency situations is one of the most pressing demands, and has attracted significant attention. However, it is an important challenge to authenticate the legitimate sources of broadcast messages and achieve fine-grained message access control. In this work, we propose SmartVeh, a secure and efficient message access control and authentication scheme in VCC. A hierarchical, attribute-based encryption technique is utilized to achieve fine-grained and flexible message sharing, which ensures that vehicles whose persistent or dynamic attributes satisfy the access policies can access the broadcast message with equipped on-board units (OBUs). Message authentication is enforced by integrating an attribute-based signature, which achieves message authentication and maintains the anonymity of the vehicles. In order to reduce the computations of the OBUs in the vehicles, we outsource the heavy computations of encryption, decryption and signing to a cloud server and road-side units. The theoretical analysis and simulation results reveal that our secure and efficient scheme is suitable for VCC.

An improved Lobatto discrete variable representation by a phase optimisation and variable mapping method

International Nuclear Information System (INIS)

Yu, Dequan; Cong, Shu-Lin; Sun, Zhigang

2015-01-01

Highlights: • An optimised finite element discrete variable representation method is proposed. • The method is tested by solving one and two dimensional Schrödinger equations. • The method is quite efficient in solving the molecular Schrödinger equation. • It is very easy to generalise the method to multidimensional problems. - Abstract: The Lobatto discrete variable representation (LDVR) proposed by Manoloupolos and Wyatt (1988) has unique features but has not been generally applied in the field of chemical dynamics. Instead, it has popular application in solving atomic physics problems, in combining with the finite element method (FE-DVR), due to its inherent abilities for treating the Coulomb singularity in spherical coordinates. In this work, an efficient phase optimisation and variable mapping procedure is proposed to improve the grid efficiency of the LDVR/FE-DVR method, which makes it not only be competing with the popular DVR methods, such as the Sinc-DVR, but also keep its advantages for treating with the Coulomb singularity. The method is illustrated by calculations for one-dimensional Coulomb potential, and the vibrational states of one-dimensional Morse potential, two-dimensional Morse potential and two-dimensional Henon–Heiles potential, which prove the efficiency of the proposed scheme and promise more general applications of the LDVR/FE-DVR method

An improved Lobatto discrete variable representation by a phase optimisation and variable mapping method

Energy Technology Data Exchange (ETDEWEB)

Yu, Dequan [School of Physics and Optoelectronic Technology, Dalian University of Technology, Dalian 116024 (China); State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical and Computational Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023 (China); Cong, Shu-Lin, E-mail: shlcong@dlut.edu.cn [School of Physics and Optoelectronic Technology, Dalian University of Technology, Dalian 116024 (China); Sun, Zhigang, E-mail: zsun@dicp.ac.cn [State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical and Computational Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023 (China); Center for Advanced Chemical Physics and 2011 Frontier Center for Quantum Science and Technology, University of Science and Technology of China, 96 Jinzhai Road, Hefei 230026 (China)

2015-09-08

Highlights: • An optimised finite element discrete variable representation method is proposed. • The method is tested by solving one and two dimensional Schrödinger equations. • The method is quite efficient in solving the molecular Schrödinger equation. • It is very easy to generalise the method to multidimensional problems. - Abstract: The Lobatto discrete variable representation (LDVR) proposed by Manoloupolos and Wyatt (1988) has unique features but has not been generally applied in the field of chemical dynamics. Instead, it has popular application in solving atomic physics problems, in combining with the finite element method (FE-DVR), due to its inherent abilities for treating the Coulomb singularity in spherical coordinates. In this work, an efficient phase optimisation and variable mapping procedure is proposed to improve the grid efficiency of the LDVR/FE-DVR method, which makes it not only be competing with the popular DVR methods, such as the Sinc-DVR, but also keep its advantages for treating with the Coulomb singularity. The method is illustrated by calculations for one-dimensional Coulomb potential, and the vibrational states of one-dimensional Morse potential, two-dimensional Morse potential and two-dimensional Henon–Heiles potential, which prove the efficiency of the proposed scheme and promise more general applications of the LDVR/FE-DVR method.

Energy Efficiency in Computing (1/2)

CERN Multimedia

CERN. Geneva

2016-01-01

As manufacturers improve the silicon process, truly low energy computing is becoming a reality - both in servers and in the consumer space. This series of lectures covers a broad spectrum of aspects related to energy efficient computing - from circuits to datacentres. We will discuss common trade-offs and basic components, such as processors, memory and accelerators. We will also touch on the fundamentals of modern datacenter design and operation. Lecturer's short bio: Andrzej Nowak has 10 years of experience in computing technologies, primarily from CERN openlab and Intel. At CERN, he managed a research lab collaborating with Intel and was part of the openlab Chief Technology Office. Andrzej also worked closely and initiated projects with the private sector (e.g. HP and Google), as well as international research institutes, such as EPFL. Currently, Andrzej acts as a consultant on technology and innovation with TIK Services (http://tik.services), and runs a peer-to-peer lending start-up. NB! All Academic L...

An efficient hysteresis modeling methodology and its implementation in field computation applications

Energy Technology Data Exchange (ETDEWEB)

Adly, A.A., E-mail: adlyamr@gmail.com [Electrical Power and Machines Dept., Faculty of Engineering, Cairo University, Giza 12613 (Egypt); Abd-El-Hafiz, S.K. [Engineering Mathematics Department, Faculty of Engineering, Cairo University, Giza 12613 (Egypt)

2017-07-15

Highlights: • An approach to simulate hysteresis while taking shape anisotropy into consideration. • Utilizing the ensemble of triangular sub-regions hysteresis models in field computation. • A novel tool capable of carrying out field computation while keeping track of hysteresis losses. • The approach may be extended for 3D tetra-hedra sub-volumes. - Abstract: Field computation in media exhibiting hysteresis is crucial to a variety of applications such as magnetic recording processes and accurate determination of core losses in power devices. Recently, Hopfield neural networks (HNN) have been successfully configured to construct scalar and vector hysteresis models. This paper presents an efficient hysteresis modeling methodology and its implementation in field computation applications. The methodology is based on the application of the integral equation approach on discretized triangular magnetic sub-regions. Within every triangular sub-region, hysteresis properties are realized using a 3-node HNN. Details of the approach and sample computation results are given in the paper.

Improving Vector Evaluated Particle Swarm Optimisation by Incorporating Nondominated Solutions

Directory of Open Access Journals (Sweden)

Kian Sheng Lim

2013-01-01

Full Text Available The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. This algorithm optimises one objective using a swarm of particles where their movements are guided by the best solution found by another swarm. However, the best solution of a swarm is only updated when a newly generated solution has better fitness than the best solution at the objective function optimised by that swarm, yielding poor solutions for the multiobjective optimisation problems. Thus, an improved Vector Evaluated Particle Swarm Optimisation algorithm is introduced by incorporating the nondominated solutions as the guidance for a swarm rather than using the best solution from another swarm. In this paper, the performance of improved Vector Evaluated Particle Swarm Optimisation algorithm is investigated using performance measures such as the number of nondominated solutions found, the generational distance, the spread, and the hypervolume. The results suggest that the improved Vector Evaluated Particle Swarm Optimisation algorithm has impressive performance compared with the conventional Vector Evaluated Particle Swarm Optimisation algorithm.

Sensitivity Filters In Topology Optimisation As A Solution To Helmholtz Type Differential Equation

DEFF Research Database (Denmark)

Lazarov, Boyan Stefanov; Sigmund, Ole

2009-01-01

The focus of the study in this article is on the use of a Helmholtz type differential equation as a filter for topology optimisation problems. Until now various filtering schemes have been utilised in order to impose mesh independence in this type of problems. The usual techniques require topology...... information about the neighbour sub-domains is an expensive operation. The proposed filtering technique requires only mesh information necessary for the finite element discretisation of the problem. The main idea is to define the filtered variable implicitly as a solution of a Helmholtz type differential...... equation with homogeneous Neumann boundary conditions. The properties of the filter are demonstrated for various 2D and 3D topology optimisation problems in linear elasticity, solved on sequential and parallel computers....

Positive Wigner functions render classical simulation of quantum computation efficient.

Science.gov (United States)

Mari, A; Eisert, J

2012-12-07

We show that quantum circuits where the initial state and all the following quantum operations can be represented by positive Wigner functions can be classically efficiently simulated. This is true both for continuous-variable as well as discrete variable systems in odd prime dimensions, two cases which will be treated on entirely the same footing. Noting the fact that Clifford and Gaussian operations preserve the positivity of the Wigner function, our result generalizes the Gottesman-Knill theorem. Our algorithm provides a way of sampling from the output distribution of a computation or a simulation, including the efficient sampling from an approximate output distribution in the case of sampling imperfections for initial states, gates, or measurements. In this sense, this work highlights the role of the positive Wigner function as separating classically efficiently simulable systems from those that are potentially universal for quantum computing and simulation, and it emphasizes the role of negativity of the Wigner function as a computational resource.

MeshTree: A Delay optimised Overlay Multicast Tree Building Protocol

OpenAIRE

Tan, Su-Wei; Waters, A. Gill; Crawford, John

2005-01-01

We study decentralised low delay degree-constrained overlay multicast tree construction for single source real-time applications. This optimisation problem is NP-hard even if computed centrally. We identify two problems in traditional distributed solutions, namely the greedy problem and delay-cost trade-off. By offering solutions to these problems, we propose a new self-organising distributed tree building protocol called MeshTree. The main idea is to embed the delivery tree in a degree-bound...

A knowledge-based control system for air-scour optimisation in membrane bioreactors.

Science.gov (United States)

Ferrero, G; Monclús, H; Sancho, L; Garrido, J M; Comas, J; Rodríguez-Roda, I

2011-01-01

Although membrane bioreactors (MBRs) technology is still a growing sector, its progressive implementation all over the world, together with great technical achievements, has allowed it to reach a mature degree, just comparable to other more conventional wastewater treatment technologies. With current energy requirements around 0.6-1.1 kWh/m3 of treated wastewater and investment costs similar to conventional treatment plants, main market niche for MBRs can be areas with very high restrictive discharge limits, where treatment plants have to be compact or where water reuse is necessary. Operational costs are higher than for conventional treatments; consequently there is still a need and possibilities for energy saving and optimisation. This paper presents the development of a knowledge-based decision support system (DSS) for the integrated operation and remote control of the biological and physical (filtration and backwashing or relaxation) processes in MBRs. The core of the DSS is a knowledge-based control module for air-scour consumption automation and energy consumption minimisation.

Inversion based on computational simulations

International Nuclear Information System (INIS)

Hanson, K.M.; Cunningham, G.S.; Saquib, S.S.

1998-01-01

A standard approach to solving inversion problems that involve many parameters uses gradient-based optimization to find the parameters that best match the data. The authors discuss enabling techniques that facilitate application of this approach to large-scale computational simulations, which are the only way to investigate many complex physical phenomena. Such simulations may not seem to lend themselves to calculation of the gradient with respect to numerous parameters. However, adjoint differentiation allows one to efficiently compute the gradient of an objective function with respect to all the variables of a simulation. When combined with advanced gradient-based optimization algorithms, adjoint differentiation permits one to solve very large problems of optimization or parameter estimation. These techniques will be illustrated through the simulation of the time-dependent diffusion of infrared light through tissue, which has been used to perform optical tomography. The techniques discussed have a wide range of applicability to modeling including the optimization of models to achieve a desired design goal

Analyzing parameters optimisation in minimising warpage on side arm using response surface methodology (RSM)

Science.gov (United States)

Rayhana, N.; Fathullah, M.; Shayfull, Z.; Nasir, S. M.; Hazwan, M. H. M.

2017-09-01

This paper presents a systematic methodology to analyse the warpage of the side arm part using Autodesk Moldflow Insight software. Response Surface Methodology (RSM) was proposed to optimise the processing parameters that will result in optimal solutions by efficiently minimising the warpage of the side arm part. The variable parameters considered in this study was based on most significant parameters affecting warpage stated by previous researchers, that is melt temperature, mould temperature and packing pressure while adding packing time and cooling time as these is the commonly used parameters by researchers. The results show that warpage was improved by 10.15% and the most significant parameters affecting warpage are packing pressure.

HVAC system optimisation-in-building section

Energy Technology Data Exchange (ETDEWEB)

Lu, L.; Cai, W.; Xie, L.; Li, S.; Soh, Y.C. [School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore (Singapore)

2004-07-01

This paper presents a practical method to optimise in-building section of centralised Heating, Ventilation and Air-Conditioning (HVAC) systems which consist of indoor air loops and chilled water loops. First, through component characteristic analysis, mathematical models associated with cooling loads and energy consumption for heat exchangers and energy consuming devices are established. By considering variation of cooling load of each end user, adaptive neuro-fuzzy inference system (ANFIS) is employed to model duct and pipe networks and obtain optimal differential pressure (DP) set points based on limited sensor information. A mix-integer nonlinear constraint optimization of system energy is formulated and solved by a modified genetic algorithm. The main feature of our paper is a systematic approach in optimizing the overall system energy consumption rather than that of individual component. A simulation study for a typical centralized HVAC system is provided to compare the proposed optimisation method with traditional ones. The results show that the proposed method indeed improves the system performance significantly. (author)

Pre-operative optimisation of lung function

Directory of Open Access Journals (Sweden)

Naheed Azhar

2015-01-01

Full Text Available The anaesthetic management of patients with pre-existing pulmonary disease is a challenging task. It is associated with increased morbidity in the form of post-operative pulmonary complications. Pre-operative optimisation of lung function helps in reducing these complications. Patients are advised to stop smoking for a period of 4–6 weeks. This reduces airway reactivity, improves mucociliary function and decreases carboxy-haemoglobin. The widely used incentive spirometry may be useful only when combined with other respiratory muscle exercises. Volume-based inspiratory devices have the best results. Pharmacotherapy of asthma and chronic obstructive pulmonary disease must be optimised before considering the patient for elective surgery. Beta 2 agonists, inhaled corticosteroids and systemic corticosteroids, are the main drugs used for this and several drugs play an adjunctive role in medical therapy. A graded approach has been suggested to manage these patients for elective surgery with an aim to achieve optimal pulmonary function.

An Optimisation Approach for Room Acoustics Design

DEFF Research Database (Denmark)

Holm-Jørgensen, Kristian; Kirkegaard, Poul Henning; Andersen, Lars

2005-01-01

This paper discuss on a conceptual level the value of optimisation techniques in architectural acoustics room design from a practical point of view. It is chosen to optimise one objective room acoustics design criterium estimated from the sound field inside the room. The sound field is modeled...... using the boundary element method where absorption is incorporated. An example is given where the geometry of a room is defined by four design modes. The room geometry is optimised to get a uniform sound pressure....

The thermodynamic efficiency of computations made in cells across the range of life

Science.gov (United States)

Kempes, Christopher P.; Wolpert, David; Cohen, Zachary; Pérez-Mercader, Juan

2017-11-01

Biological organisms must perform computation as they grow, reproduce and evolve. Moreover, ever since Landauer's bound was proposed, it has been known that all computation has some thermodynamic cost-and that the same computation can be achieved with greater or smaller thermodynamic cost depending on how it is implemented. Accordingly an important issue concerning the evolution of life is assessing the thermodynamic efficiency of the computations performed by organisms. This issue is interesting both from the perspective of how close life has come to maximally efficient computation (presumably under the pressure of natural selection), and from the practical perspective of what efficiencies we might hope that engineered biological computers might achieve, especially in comparison with current computational systems. Here we show that the computational efficiency of translation, defined as free energy expended per amino acid operation, outperforms the best supercomputers by several orders of magnitude, and is only about an order of magnitude worse than the Landauer bound. However, this efficiency depends strongly on the size and architecture of the cell in question. In particular, we show that the useful efficiency of an amino acid operation, defined as the bulk energy per amino acid polymerization, decreases for increasing bacterial size and converges to the polymerization cost of the ribosome. This cost of the largest bacteria does not change in cells as we progress through the major evolutionary shifts to both single- and multicellular eukaryotes. However, the rates of total computation per unit mass are non-monotonic in bacteria with increasing cell size, and also change across different biological architectures, including the shift from unicellular to multicellular eukaryotes. This article is part of the themed issue 'Reconceptualizing the origins of life'.